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3D printing of concrete (3DPC) has been demonstrated to be a potential and viable solution for different infrastructure applications considering its multiple benefits and the continuous advances in achieving an advanced manufacturing process, using innovative materials, and using unique approaches to demonstrate high-performance characteristics. Still, some challenges remain to be addressed as this technology advances through the stages of prototyping, validation, and testing; looking to establish itself as an alternative to cast concrete for the mass production of civil infrastructure. The research presented in this dissertation is focused on the influence of the fabrication process of 3D-printed concrete on three relevant aspects for its deployment in large-scale scenarios. These aspects include the scalability of mixture development for different printing systems, the mechanical performance of reinforced 3D-printed elements, and the initial evaluation of durability properties. This research aims to contribute to the development of strategies to understand the effects of the mixture composition and the use of supplementary cementitious materials (SCMs) in the process of mixture development to enhance the printability characteristics, fresh state properties, and durability properties of these materials. Furthermore, the incorporation of novel reinforcement alternatives and controlled architectures, in addition to the study of the transport properties of 3D-printed elements can lead to advances in the use of 3D-printed concrete in structural applications.

Concrete-filled steel tubular (CFST) columns have been widely recognised in construction due to their high load-bearing capacity and aesthetical appeal. However, the existing CFST connections such as welded connections are complicated and the one-sided bolts in the literature are either difficult to install or fabricate. This thesis focused on the CFST moment connection with proposed innovative one-sided bolt that is fast to install and easy to fabricate. It could achieve full tensile capacity of bolts and classified as moment-resisting connection. This allows faster construction time and simpler fabrication, which could be a potential alternative to existing CFST moment connections.

This thesis provides a novel route to advance the polymer-cement composite's performance via Graphene-engineered modification. The discovered antifoaming mechanism of Graphene oxide controls the air-entraining phenomenon of redispersible polymer and significantly enhances the performance of nano-engineered polymer cement composites. This research disclosed that unveiled antifoaming effect of the graphene oxide nanosheets introduces a new mechanism and provides a breakthrough for the efficient fabrication of advanced smart hybrid cementitious materials.

The applications of hollow sections members have gained broad recognition in civil construction considering both their functional advantages and architectural features. However, the use of such members presents challenges in connections to other structural members. In comparison to welded connections, bolted connections are regarded as an alternative with ease of installation and maintenance. This PhD study aims to develop a one-sided bolt configuration (i.e. the elliptical one-sided bolt) for structural assembly with practical and convenient installation sequence, as well as to evaluate and understand the mechanical performance of such elliptical one-sided joints in shear and tension as two fundamental loading scenarios in practices.

Geomaterials (e.g. cement, concrete and rock) are easily damaged and collapsed in underground infrastructures and during earth resource extraction where extreme loading conditions (like earthquakes, rockbursts, and explosion) and complicated stress states are frequently encountered. A comprehensive investigation of dynamic behaviours (including mechanical, fracturing and deformation properties) of geomaterials can help understand their failure mechanisms and predict the failure process in such scenarios. The obtained knowledge can be further used for warning and protection in advance during mining and infrastructure constructions.

Leaf Area Index (LAI) is commonly defined as the total area of a leaf per unit area of the ground. LAI is an important variable for characterizing plant canopy related to the interception of solar radiation. Direct measurement of LAI by destructive sampling is tedious, time-consuming, and labor-intensive. With the advance of remote sensing, studies have explored multispectral and hyperspectral remote sensing image data and LiDAR point clouds as individual sources to estimate LAI indirectly. This study investigates the estimation of LAI for maize row crops over the growing season based on features derived from high resolution LiDAR and hyperspectral data acquired simultaneously from a UAV platform. Support Vector Regression (SVR) models are developed using cross validation and evaluated relative to the contribution of the multi-modality remote sensing data. The study is based on data acquired for experiments in plant breeding and evaluation of nitrogen management practice trials conducted at the Agronomy Center for Research and Education (ACRE) in 2021 and 2022, respectively. Reference data for the models were collected using a LI-COR® LAI-2200-C Plant Canopy Analyzer. Including both LiDAR and hyperspectral data sources in the SVR model improved the 𝑅_ref^2 (relative to 1:1 comparison line), RMSE and Relative RMSE (rRMSE) values for both the plant breeding and nitrogen management practice experiments, although incremental gains were small overall. More importantly, it was observed that the contributions of the LiDAR vs hyperspectral inputs to the models also varied throughout the growing season.

Efficient and safe operations are critical to civil infrastructure systems (CIS) such as airports. Currently, the operation performance is highly dependent on experienced human operators. For example, the expertise of air traffic controllers in runway assignments greatly impacts on the safety and efficiency of airport operations, as it impacts the overall traffic flow on the surface of airports. The large amount of operation data generated by the recent monitoring technology provides the potential to use historical data to guide less-experienced human operators in achieving high performance. However, current research falls short in adequately accounting for the uncertainties in operations and automatically utilizing historical data to optimize operations for safety and efficiency. For example, in metropolitan airports, the efficiency and safety of ground traffic depend on the experiences of air traffic controllers (ATC). Improper handling of traffic flows could increase collision risks and flight delays, progressively impacting air traffic networks. ATC must be skillful in assigning a runway for each aircraft while observing the historical and real-time air traffic data (e.g., Airport Surface Detection Equipment, Model X (ASDE-X)). However, due to the uncertainty and contextual changes in operations, the lack of guidelines for adjusting runway assignments in different scenarios makes it hard for less experienced ATCs to make effective adjustments. Automatically planning and designing safe and efficient runway assignments with uncertain and changing traffic is a practical challenge. This research aims to establish a framework for automatically interpreting the historical recorded operational data into optimal control strategies, focusing on the critical runway assignment strategies for assisting human operators (i.e., ATC) with air traffic monitoring data. Especially this research conducted a data-driven simulation augmented by multi-objective runway assignment algorithms in airports that can proactively guide proper uses and real-time improvements of runway assignments in various traffic scenarios for multi-objective air traffic management. Two specific objectives include: 1) establishing a data-driven method that uses historical data (e.g., ASDE-X) for constructing operation simulations (e.g., airport traffic simulations); 2) exploring the strategies for multi-objective runway assignment under changing and uncertain traffic scenarios. The proposed research consists of three steps, as shown in the following: 1) transfer the large-scale and noisy historical data into a meaningful operation process model with traffic parameters and events derived from the data. This transformation would help to build the foundation of the simulation models of aircraft ground traffic operation; 2) build and validate the data-driven trajectory-based simulation model for airport tower operations with the historical data from the ASDE-X data. The comparison between the aircraft taxiing performance predicted by the simulation and real-world records will help to identify the validity of the data-driven airport tower operation simulations; 3) examine a multi-objective optimization algorithm that explores runway assignments under changing traffic scenarios. An optimal runway assignment should achieve multi-objective airport operation (e.g., maximum throughput, minimum fuel consumption) while minimizing the operational risks (e.g., conflicts in taxiing) under uncertainties. The developed trajectory mapping approach can consistently achieve above 95% matching accuracy for moving aircraft on the ground. The average required computational time for each aircraft’s trajectory is less than 2.8 seconds. The developed simulation model can effectively simulate the traffic on the ground at airports. The correlation coefficient value between the simulated taxiing time of aircraft and real-world records is 0.90, and the average difference between the average simulated taxiing time of aircraft and real-world records is around 79 seconds. The developed multi-objective optimizations for runway assignments can efficiently reduce the number of conflicting taxiing operations and the total fuel consumption and increase the hourly airport throughput by 71%, 38%, and 44%, respectively, under the changing traffic settings with speed and schedule variations. This research is expected to contribute to the progress of technologies for automated civil infrastructure operations, particularly in airports. The data-driven simulations and optimization approach developed in this study can be readily customized to suit different airports.

Commercial timber plantations are extensively found in Australia and around the world. However, high-resolution observations of tree water use and carbon assimilation, especially in young plantations, are still rare. Therefore, this thesis quantifies, using both experimental data and modelling applications, the water and carbon fluxes in a young Eucalyptus globulus plantation in Australia. Results from this thesis emphasize the highly dynamic water use and carbon uptake by young and recently established trees. Considering that management practices are usually solely based on mature trees, this thesis produces useful findings for more robust policies and licensing procedures that acknowledge the entire plantation management cycle.

Due to the difficulty in physically observing the phenomena inside the actual ladle furnace in the industry, to ascertain optimized methodology for high-grade steel production, an investigation was carried out using numerical modeling to simulate the behavior of alloying elements within the liquid steel bulk using ANSYS Fluent 2020 R1 (ANSYS Inc., Pittsburgh, PA, USA). The model solves the governing equations utilized in computing the trajectories of each particle in the discrete phase. Furthermore, a user defined (UDF) code maps the mass of each parcel based on the total amount of alloy injected. The code also defines the total time it takes for the shell formed around the added materials to melt or dissolve. The study consists of a two-step procedure: ladle stirring by argon inert gas injection and mixing study by injecting micro-alloying elements to capture the flow field, turbulence, and species transport occurring during the refining process. A generic dual plug ladle metallurgy furnace, dimensions, and data obtained from Nucor Steel is used to validate the CFD simulation results. Concise parametric studies consist of ladle geometry design adjustments, variations of argon gas flow rates, and different alloying elements. Though the efficiency of the LMF process is quantified using the mixing time, which decreases as initial gas flow rates increase, results from this study show that extremely high charging of ladles is optional in obtaining shorter mixing. Also, particles behave substantially differently when their densities are below or above that of steel, and their melting points and specific heat capacities influence the time it takes for them to melt or dissolve. The overall potential outcome for this study is to improve the mixing practices due to different optimal procedures required by some materials than others.

The dynamic work environments in construction and civil infrastructure sectors remain susceptible to safety risks. These sectors are among the most hazardous industries with high rates of worksite accidents. Worksite accidents in the construction and infrastructure industries result in adverse cost, schedule, and quality deviations from project plans. Despite recent advancements in the theory and practice of construction and infrastructure worksite safety, there is currently a gap in quantitatively measuring the impacts of worksite accidents. This thesis aims to quantify the impacts of worksite accidents on cost, schedule, and quality of work, and support effective decision-making. Moreover, it explores features that determine the injury type at the individual level of analysis.

Glass-Reinforced Polymer (GRP) bolts are increasingly used in Australian coal mines as a means of rib support in heading development and for coal-face equipment recovery. Unlike metallic rock bolts, GRP bolts are made through pultrusion resulting in anchor bolts with differing performance characteristics to that of steel. Therefore, previous studies of steel rock bolts could not be utilised to describe the load transfer characteristics of their fibreglass counterparts. This thesis expanded on the shear load transfer mechanisms of fully grouted fibreglass rock bolts utilising a double shear system. Analytical and numerical models were also developed to simulate the shear performance of the fibreglass rock bolts. Two experimental test schemes were carried out. The first with clean shear interfaces and the second with infilled shear interfaces comprised of sandy clay, applied to a thickness of 5mm. Two types of fully grouted rock bolts; 20-tonne and 30-tonne were tested with pretension loads of 0kN, 10kN, 15kN and 20kN. It was found that increasing the pretension also increased the confining pressures at the shear interfaces for both clean and infilled joints. This in turn reduced the damage propagating from the bolt at the shear interface as well as reducing the hinge point bending. Infilled shear interface samples experienced a decrease in the failure displacement while also resulting in an increase to the peak shear force. The analytical model was developed utilising the Fourier transform, energy balance theory and linear elastic theory. The result was an empirical relationship that could determine the double shear performance of fibreglass rock bolts with close agreement to the experimental data. Coefficients were incorporated to facilitate model calibration and tuning. Finally, three-dimensional (3D) modelling was utilised to conduct numerical simulations of fibreglass rock bolts subjected to single shear and double shear scenarios. The numerical model was calibrated against experimental data and then extended to conduct a sensitivity analysis on fibreglass rock bolts subjected to variations of the double shear test parameters. Scenarios included rock bolt installation angles, shearing rates and various host rock strengths. The combined experimental, analytical and numerical studies provide a comprehensive understanding of the shear behaviour of fibreglass rock bolts. By studying the impact of pretension and shear interfaces, this research has successfully modelled the shear failure mechanisms of 20-tonne and 30-tonne fibreglass rock bolts.

This focus of this thesis is the application of text detection, which is a field within computer vision, in structural drawings. To understand a structural system and conduct a rapid assessment of an existing structure would benefit from the ability to read the information contained within the drawing or related engineering documents. Extracting engineering data manually from the structural drawings is incredibly time-consuming and expensive. In addition, the variation in human engineers’ experience makes the output prone to errors and false evaluations. In this study, the latest development in computer vision, especially for text detection, using large volumes of words in some structural drawings, is explored and evaluated. The goal is to read text in structural drawings, which usually has some feature noises due to the high complexity of the structural annotations and lines. The dataset consists of computer-generated structural drawings which have different word shapes and types of fonts with various text orientations. The utilized structural drawings are floor plans, and thus contain structural details which are filled with various structural element labels and dimensions. Fine tuning of the pre-trained model yieldssignificant performance in unstructured text detection, especially in the model’s recall. The results demonstrate that the developed predictive modeling workflow and its computational requirements are sufficient for the unstructured text detection in structural drawings

Multifunctional additive manufacturing has the immense potential of addressing present needs within structural health monitoring by enabling a new additive manufacturing paradigm that redefines what a sensor is, or what sensors should resemble. To achieve this, the properties of printed components must be precisely tailored to meet structure specific and application specific requirements. However due to the limited number of commercially available multifunctional filaments, this research investigates the in-house creation of adaptable piezoresistive multifunctional filaments and their potential within structural health monitoring applications based upon their characterized piezoresistive responses. To do so, a rigid polylactic acid based-filament and a flexible thermoplastic polyurethane based-filament were modified to impart piezoresistive properties using carbon nanofibers. The filaments were produced using different mixing techniques, nanoparticle concentrations, and optimally selected manufacturing parameters from a design of experiments approach. The resulting filaments exhibited consistent resistivity values which were found to be less variable under specific mixing techniques than commercially available multifunctional filaments. This improved consistency was found to be a key factor which held back currently available piezoresistive filaments from fulfilling needs within structural health monitoring. To demonstrate the ability to meet these needs, the piezoresistive responses of three dog-bone shaped sensor sizes were measured under monotonic and cyclic loading conditions for the optimally manufactured filaments. The characterized piezoresistive responses demonstrated high strain sensitivities under both tensile and compressive loads. These piezoresistive sensors demonstrated the greatest sensitivity in tension, where all three sensor sizes exhibited gauge factors over 30. Cyclic loading supported these results and further demonstrated the accuracy and reliability of the printed sensors within SHM applications.

This dissertation focused on cured-in-place-pipe (CIPP) technology, which is being used to repair sewer pipes across the globe. The CIPP process involves the manufacture of a new fiber-reinforced composite plastic pipe inside an existing damaged pipe. By 2022, the global CIPP market will exceed $2.5 billion and constitute 40% of the U.S. pipe rehabilitation market. In recent years, concerns about the type, magnitude, and toxicity of chemical air emissions associated with CIPP installations have markedly increased. CIPP installations in Asia, Europe, Oceania, and North America have been associated with indoor and ambient air contamination incidents, afflicted schools, daycare centers, homes, and offices and prompted building evacuations. This research program was designed to better understand chemical release into the air during CIPP composite manufacture and the human health risks. Principles and techniques from the environmental engineering, air quality, material science, and risk analysis were applied. This dissertation contains three chapters and each chapter is a stand-alone manuscript, with the first chapter already having been published.Chapter 1 involved the characterization of chemical emissions for steam-cured CIPP installations in Indiana (IN, sanitary sewer) and California (CA, storm sewer). It was discovered that a complex multiphase mixture of organic vapor, water vapor, and particulate (condensable vapor and partially cured resin) was emitted. Chemicals captured included a variety of hazardous air pollutants, carcinogens, endocrine disrupting compounds, and other chemicals with little toxicity data. The materials captured in California during 4 CIPP installations, when normalized against styrene concentration, exhibited different toxicity towards mouse cells. This toxicity indicated that non-styrene compounds were probably responsible for toxicity. Testing revealed significant and previously unreported worker and public safety chemical risks existed with CIPP installations.Chapter 2 describes experiments conducted to determine which CIPP manufacturing conditions (i.e. curing pressure, temperature, time and ventilation) influenced chemical air emissions during and after composite manufacture. During thermal manufacture, approximately 8.87 wt% volatile organic compounds (VOC) was released into the air at standard pressure. For the CIPP styrene-based resin examined, chemical volatilization during manufacture was influenced by pressure, but temperature and heating time did not influence the composition of chemical residual inside the new composite. All cured composites, regardless of temperature or heating time, contained approximately 3 wt% VOC. No statistical difference was found for either: (1) VOC loading across cured composites or (2) styrene emission into the air across cured composites despite different curing temperature and heating times. Styrene was the most abundant compound detected in the composite and in air. High styrene air concentration signals inhibited the author’s ability to determine if other non-styrene compounds were emitted into the air. Short-term ventilation (2 hr) of the new composite reduced styrene air concentration to near zero in 10 min, but styrene levels rebounded when ventilation was halted. Due to the high styrene loading in the cured composite, it is expected that ventilation will only temporarily reduce VOC air levels in pipes, manholes, and other affected spaces.Chapter 3 includes inhalation health risk assessment due to chemical emission from CIPPs during manufacture and use. Publicly available worksite data for ultraviolet (UV)-light and steam-CIPP installations were utilized and Monte Carlo simulation was applied. Data-gaps were also identified. Health risks associated with newly manufactured (post-cured) chemical emission from lab scale CIPPs were also evaluated. For CIPP resins and post-cured CIPPs 31 chemicals have been quantified among which many are unique volatile organic chemicals VOCs, but only 8 air testing studies were found. At a steam-CIPP worksite, VOCs were found in a condensed multiphase mixture discharged into air, 4 VOCs were detected in the vapor phase, while only styrene vapor phase results could be used for risk assessment. Worksite styrene levels (1,825 ppmv, 1,070 ppmv, 220-270 ppmv, 140 ppmv) have been reported indicating a health risk can exist. Monte Carlo simulation using literature data revealed that for the single UV-CIPP and single steam-CIPP study negligible styrene HQs were found, while unacceptable styrene LECRs% > 10−4 (i.e. 37-38%) were obtained. Monte Carlo simulation on laboratory data showed that post-cured emissions from the composite cured longer increased the unacceptable styrene LECR (from 17.86% to 21.12%) and HQ (0.95% to 8.04%). Whereas curing the composite at greater temperature reduced the styrene LECR and HQ to 0.89%. and 0, respectively. Ventilation also diminished the acceptable LECR% in all composites but did not reduce the carcinogenic health risk to an acceptable level. Health risk can exist as evidenced by limited air testing data. More studies are needed to examine inhalation health risks associated with the CIPP manufacturing process and newly manufactured plastics.

Most new vehicles manufactured in the last two years are connected vehicles (CV) that transmit back to the original equipment manufacturer at near real-time fidelity. These CVs generate billions of data points on an hourly basis, which can provide valuable data to agencies to improve the overall mobility experience for users. However, with this growing scale of CV big data, stakeholders need efficient and scalable methodologies that allow agencies to draw actionable insights from this large-scale data for daily operational use. This dissertation presents a suite of applications, illustrated through case studies, that use CV data for assessing and managing mobility and safety on surface transportation systems. A systematic review of construction zone CV data and crashes on Indiana’s interstates for the calendar year 2019, found a strong correlation between crashes and hard-braking event data reported by CVs. Trajectory-level CV data analyzed for a construction zone on interstate 70 provided valuable insights into travel time and traffic signal performance impacts on the surrounding road network. An 11-state analysis of electric and hybrid vehicle usage in proximity to public charging stations highlighted regions under and overserved by charging infrastructure, providing quantitative support for infrastructure investment allocations informed by real-world usage trends. CV data were further leveraged to document route choice behavior during active freeway incidents providing stakeholders with a historical record of observed routing patterns to inform future alternate route planning strategies. CV trajectory data analysis facilitated the identification of trip chaining activities resulting in improved outlier curation and realistic estimation of travel time metrics. The overall contribution of this thesis is developing analytical big data procedures to process billions of CV data records to inform engineering and public policy investments in infrastructure capacity, highway safety improvements, and new EV infrastructure. These scalable and efficient analysis techniques proposed in this dissertation will help agencies at the federal, state and local levels in addition to private sector stakeholders in assessing transportation system performance at-scale and enable informed data-driven decision making.

Understanding how different vegetation covers may impact water resources is crucial for rural productivity, especially where water is limited. This thesis examined the water balance in two different catchments, one dominated by a pasture and the other mostly covered by a blue gum plantation. It was found that the water lost by the pasture via evapotranspiration was lower than in the plantation, and during hot and dry periods, including heat waves, tree transpiration is largely reduced. The findings will support future studies addressing challenges of a changing climate in relation to water resources and rural productivity.

Concrete is the second most consumed material in the world after water and is an essential element of constructed infrastructure. Over 14 billion m3 of concrete are being produced annually, resulting in a serious impact on the environment. The production of cement, which is the main component of concrete, is responsible for 5 – 8 % of global CO2 emissions. As a result, several global initiatives have been undertaken to achieve carbon neutrality by 2050. This carbon neutrality target coincides with the Paris Agreement's goal to limit global warming to 1.5 °C. A well-known, and successful strategy to reduce CO2 emissions in the concrete industry is to use supplementary cementitious materials (SCMs) as a partial replacement for cement. However, it is projected that in 2030 the demand for two of the most commonly used SCMs, fly ash and slag cement, will exceed their supply. Using nontraditional and natural pozzolans (NNPs) can help to close this supply gap, but there is a lack of knowledge regarding the reactivity and long-term performance of these materials. The purpose of this research was to perform experiments on several NNPs, some of which can be supplied in commercially viable quantities with the objective of evaluating their performance in cementitious systems (mortars and concretes) with the goal of accurately assessing their potential for use as alternative SCMs. The mortar study was performed using a total of 11 different NNPs, belonging to 4 distinctive groups and distributed as follows: 3 from the group of calcined clays (CCs) - CC1, CC2, and CC3, 3 from the group of natural pozzolans (NPs) - NP1, NP2 and NP3, 2 from the group of fluidized bed combustion (FBCs) ashes - FBC1 and FBC2, and 3 from the group of bottom ashes (GBAs) - GBA1, GBA2, and GBA3. The concrete study was performed on 4 different materials, one from each of the previously mentioned groups. The materials selected for concrete study were the worst-performing members of each group, as determined by the analysis of the test results obtained from mortars. These included CC2, NP3, FBC1, and GBA3 materials. This approach was adopted under the assumption that achieving adequate concrete characteristics with lowest-quality materials will all but assure satisfactory performance of concretes with higher-quality materials. The findings generated from this research indicate that several of the NNPs used in this study present a viable alternative to traditional SCMs. As an example, out of the 11 NNPS, 9 were found to conform to the requirements of the ASTM C618-19, the standard specification currently used to assess the suitability of coal fly ash and raw or calcined natural pozzolans for use in concrete. Results obtained from tests performed on mortars demonstrated that, when used at the replacement level of 25%, all 11 NNPs produced mixtures with characteristics similar to those obtained from the plain cement (OPC) mortar. For that reason, this level of replacement was selected to prepare concrete specimens. The results collected from concrete specimens showed that, when compared to plain concrete, mixtures with all 4 NNPs attained comparable (or improved) mechanical (compressive and flexural strength), durability (freeze-thaw resistance), and transport (formation factor and rate of water absorption) properties. As in the case of traditional SCMs, the mixtures with NNPs were found to require extended curing times to fully realize their property-enhancing potential associated with pozzolanic reactions. Overall, the best performing materials were those from the CCs group, followed by those belonging to, respectively, NPs, GBAs, and FBCs groups.

Cement composite is one of the most widely used construction materials but is a big contributor to global carbon emissions. Therefore, there is a strong global demand for reducing the use and emission from cement. This thesis introduces an approach to enhancing cement composites by nanoengineering interfaces and potentially reducing cement usage. Findings from this research pave the way for large-scale development of carbon-neutral cement composites.

The smashing mantis shrimp is a crustacean that uses its dactyl club to defend itself or prey on other animals. This dactyl club is so strong that it can reach accelerations as high as a bullet of a caliber 0.22 gun and impact without breaking. We seek to understand the secrets behind the staggering properties of this club that withstand several high-damage impacts without breaking catastrophically. The dactyl club comprises three parts: the impact region, the periodic region, and the striated region. The first region of interest is the periodic region. This region is made of a helicoidal arrangement of fibers called Bouligand architecture, and in this architecture, cracks only form in the matrix between fibers. The first research project approximates the Bouligand composite with a single helicoidal crack embedded in an isotropic material. The test consists of a disk with a notch under quasistatic biaxial boundary conditions. We found an enhancement of mechanical properties when we increase the pitch angle. In the following section, a coarse-grained model is developed. This model allows multiple crack formation. This approximation tells us that as the initial crack grows, the driving force of crack propagation, the energy release rate, diminishes. The crack stops growing, confining itself, and allowing multiple crack nucleation and delocalization. At the same time, this dissipates more energy as more cracked surfaces appear. Hashin damage model with a cohesive zone model are used under different boundary conditions, geometries, and material properties, to model Bouligand composites. The helicoidal composites outperform the reference ones in peak load and absorbed energy. The next part of this thesis investigates the bicontinuous particles present in the impact surface of the dactyl club. These bicontinuous particles consist of a soft phase (organic) and a hard phase (hydroxyapatite) that can withstand high strain rates. Their stiffness and strength increase with strain rate. On the other hand, preliminary studies suggest that they perform well in cyclic loading. Finally, we proceed to use the helicoidal composites to design structural parts. We introduce a model for simulating the fiber-reinforced composites called LARC05. We verify, validate, and then use models for fiber-reinforced composites.

The research described in this dissertation began in response to frequent questions from users of several crosswalks near a university campus. At each crosswalk was a sign indicating that motorists should yield to pedestrians in the crosswalk. That this message was not being interpreted uniformly was a concern at locations where heterogeneous road users (pedestrians, cyclists, and motorists) were interacting. Instead of trying to impose a single interpretation on users of each crosswalk, it was decided to observe and analyze interactions between users of the crosswalk. Several hours of video were recorded of pedestrians and motorists “negotiating” the right of way at the crosswalk. Because these crossing locations were marked but not signalized, they were called “semi-controlled crosswalks”. The negotiations took place during what were called pedestrian-motorist interactions (PMIs). The PMIs observed on video can be characterized as a “zebra-crossing” game, as described in Chapter 4 of this dissertation. Recently, computer vision (CV) algorithms have been extensively used in road users’ detection and tracking at an unparalleled spatial-temporal scale. In this study, CV algorithms have been applied to convert the video recordings into a large-scale spatial-temporal trajectory dataset including 800 pedestrians and cyclists interacting with more than 500 vehicles. Utilizing the trajectory dataset, a spatial-temporal graph convolutional network-based sequence to sequence (ST-GCN-Seq2Seq) algorithm has been developed to reasonably forecast heterogeneous road users’ trajectories and behavior in real time. Combining CV and ST-GCN-Seq2Seq algorithms can help both design an intelligent tracking system and achieve a form of “smart” interaction at semi-controlled crosswalks for heterogeneous road users. Based on road users’ arrival patterns detected from CV algorithms, it is likely that a "smart" control strategy can minimize the delay of pedestrians and motorists at crosswalks. Therefore, another branch of this study is to investigate the “smart” control strategies at crosswalks using traffic signal controllers. A reinforcement learning framework was proposed as the “smart” control strategy, and several experiments were conducted using microsimulation. The proposed reinforcement learning framework is able to reduce traffic delay (efficiency), considering real-time pedestrian flow rates and vehicle flow rates with appropriate sensors.

Acoustic rainfall sensing in mapping spatial-temporal variation of rainfall events in urban areas.

The development of the thin and flexible prefabricated glass fibre reinforced polymer (GFRP) composites has been recognised as an innovative wrapping material that requires the inclusion of infills to complete its retrofitting system. However, the actual performance of this system still needs to be explored, and its structural contribution to axial and flexural behaviour of columns is yet to be determined. This study focused on the impact of the GFRP wrapping system on the axial and flexural behaviour of reinforced concrete (RC) and timber columns. The study included development of three-dimensional (3D) finite element (FE) and theoretical models to obtain an improved understanding about the performance of the investigated columns. Firstly, the effectiveness of the thin GFRP wrapping and its contribution to the axial compressive behaviour of concrete, grout, and epoxy infill materials was explored, and the compressive behaviour of GFRP-wrapped infill materials was numerically elaborated using FE modelling. The experimental results showed that the properties of the infill material have a significant impact on the confinement effect of the wrapping system. The FE investigations that considered concrete damaged plasticity model for simulating the behaviour of materials, had an excellent agreement with the experimental results in predicting the overall compressive behaviour of the various infill materials. Secondly, the flexural behaviour of circular RC columns strengthened by a GFRP wrapping system was explored experimentally, numerically and theoretically. The adopted system was found to improve the flexural capacity of columns by up to 250%. The assumption of a non-perfect bond between constituent materials in modelling the wrapped column infilled with grout, was shown to better correlate with their corresponding results, indicating inadequate bond performance. Thirdly, the effect of rehabilitation with the thin GFRP composites was examined on the axial performance of short timber columns. Experimental work was conducted on undamaged and damaged short timber columns with three levels of splitting. Numerical and analytical investigations were established to evaluate the performance of the studied samples. The experimental results showed that the GFRP wrapping system had a significant impact on the axial performance of columns, with samples had epoxy infill contributing the most to the yield and peak strengthening ratios by 238% and 214%, respectively. The results of the numerical and analytical investigations were in good agreement with the experimental results. Furthermore, the contribution of the GFRP wrapping system to the flexural capacity of circular timber columns was evaluated. The use of carbon fibre reinforced polymer (CFRP) straps within the epoxy infill was examined. Finite element modelling (FEM) and theoretical analyses were performed, and the results were compared with experimental results. The outcome of study demonstrated that the use of GFRP wrapping system with epoxy infill and bonded CFRP straps outperformed the investigated columns in terms of flexural strength and energy absorption due to the high elastic modulus and tensile strength of CFRP straps in contrast with other constituent materials. The theoretical study revealed that the estimation of tension failure in timber yielded results that corresponded more closely to experimental and FEM results. Finally, FE study was performed using ABAQUS software package to provide a better understanding of the influence of various design parameters on the axial and flexural behaviour of GFRP-wrapped RC columns. The results of the FE investigations showed that including epoxy infill within the GFRP wrapping system improves the axial and flexural load capacities and failure modes of the columns more significantly when compared to grout infill. For columns under compression, the smaller the column size, the higher the impact of GFRP confinement on axial capacity and stiffness. For columns under flexure, the GFRP circumferential repair with an epoxy infill was more effective than grout infills in improving the flexural capacity of RC columns. This study provided a thorough assessment of the performance of GFRP wrapping system and its influence on the axial and flexural behaviour of RC and timber columns. In addition, a deep understanding of the impact of various design parameters on the axial and flexural behaviour of RC columns was presented. Overall, the investigated GFRP wrapping system was found to be a suitable strengthening approach for circular structural columns that can enhance their performance.

Cement stabilization is used to improve weak soils that support civil infrastructures. The mechanical behaviour of improved soils has been extensively investigated in the laboratory using conventional equipment. However, our knowledge of micro-mechanical behaviour of cemented sands are limited. This project investigated the mechanical behaviour cemented sand using in-situ X-Ray computed tomography. Small-scale experiments on cement bonds and cemented sand under pure shear, tension, compression and triaxial loading were conducted. Finally, a new cohesive-frictional constitutive model for cemented sand was developed based on experimental results and validated for triaxial loading conditions with improved predictions of mechanical behaviour and failure mechanisms.

Research Questions for Engineering Resilience in Healthcare. Delivered on 17 March 2022 to FIReS Network Webinar 2.

In the United States, buildings are responsible for almost 40% of the country’s total energy consumption and 38% of the total greenhouse gas emissions. Researchers are constantly seeking sustainable and efficient energy generation solutions for buildings as society continues to cope with the intensifying energy crisis and environmental deterioration. Thermoelectric technology is one such solution that potentially can lead to significant energy recovery and conversion between waste or excess thermal energy and electrical energy. One promising application is integrating thermoelectric materials into the building envelope (TBE) for power generation and building heating and cooling without transporting energy among subsystems and refrigerant use. TBE can combine structural support and thermal storage with power generation and thermal-activated cooling and heating, thereby contributing to sustainable living and energy. TBE technology is still in its early development stages. This dissertation aimed to develop a fundamental understanding of the characteristics, behaviors, operation, and control of TBE systems as energy-efficient measures for thermal energy harvesting and thermal comfort regulation and to address the significant research gaps concerning high-conversion efficiency materials and optimal module configuration as well as system deployment related to real-world applications. Accordingly, this dissertation focused on the following three key objectives: (1) development and characterization of new thermoelectric composite materials; (2) identification of optimal designs and controls of TBE and established mathematical models for performance simulation; and (3) quantification of the energy-saving benefits of TBE. The following five aspects specifically were investigated: (1) Material development and characterization. New thermoelectric cement composites were developed with cement and various additives, material concentrations, and fabrication methods in the laboratory. Their thermoelectric properties (e.g., Seebeck coefficient, thermal conductivity, electrical conductivity, power factor, and the figure of merit) were measured simultaneously and characterized at 300–350 K. (2) Module evaluation. Commercially available thermoelectric modules (TEMs) were assessed using well-designed test apparatus in both the heat pumping and power generation modes. The test results validated the numerical model, which assisted with performance comparison and material selection between cement-based and commercial TEMs for the TBE prototype. (3) Prototype assessment. A convective TBE prototype and a radiant TBE prototype were designed, assembled, and evaluated in a pair of controlled testing chambers. The TBE’s surface temperature, thermal capacity, and COP were assessed under summer and winter conditions. (4) Prototype modeling. The first-principle-based numerical models of both the convective and radiant TBE prototypes were developed in Modelica. The modeling results indicated good agreement with the experimental data. The verified models were used to study the impacts of the design parameters and operating conditions on the heat pumping performance of TBE. (5) System simulation. A TBE building system model was established by integrating the TBE prototype model within a building’s heat balance model, considering the building construction, climate condition, power control, etc. Its seasonal performance under various climate conditions was studied to identify the potential optimal operation and energy savings. This dissertation confirmed several key findings in the areas of material development, system design and operation, and energy savings. The TBE achieved higher efficiency with a heat pump for heating than for cooling generally. The TBE heating system performed better than a conventional electric heater (efficiency assumed at 0.9). The measures that improved TBE heating efficiency were enhancing the material’s thermoelectric properties, optimizing the geometry and number of TEMs, and improving the boundary heat transfer of TEMs. This dissertation concluded that the TBE system is a promising alternative to conventional heating systems in buildings. Furthermore, the knowledge gained will strengthen the understanding of thermoelectrics in the building domain and guide further development in TBE, as well as facilitate the operation of net-zero energy and carbon-neutral buildings.

Human and animal faeces can contaminate natural waters that are used for recreation. This can result in disease and significant risk to public health. This thesis developed a framework to improve existing assessment methods for sources of faecal pollution in waterways, associated risks, and health and economic impacts to the community by using novel genetic approaches. This framework was applied to the Yarra River as a case study. It was found that the river had low levels of mainly animal faecal pollution, but was safe to swim.

The trucking industry seems to be resistant to electrification, even though truck electrification can lead to large societal as well as user benefits. This dissertation develops a framework to inform policy making and enhance electric vehicle (EV) preparedness in the trucking industry through the study of two interrelated elements: (a) the adoption of electric trucks and (b) the appropriate implementation of electric truck technology. These two elements cover the user perspective, which is not adequately studied, and the agency perspective, which is pivotal in the decision-making process. Specifically, this study addressed the following research questions: (i) which factors affect the purchase decisions of truck fleet managers or owners for electric trucks? (ii) what is the ranking of and interrelationships between the barriers to the adoption of electric trucks? (iii) which location criteria should be considered for the strategic implementation of dynamic wireless charging (DWC) in a freight transportation network and where should this technology be located based on these criteria, and (iv) what is the impact of electric truck adoption on highway revenue and potential of alternative funding mechanisms to recover the revenue loss? For the adoption of electric trucks, a stated preference survey was designed and distributed online to truck fleet managers/owners in the U.S., gathering 200 completed responses. Statistical and multi-criteria decision-making approaches were employed to identify the factors that affect the purchase intentions of truck fleet managers and explore the barriers to electric truck adoption. The results showed that the purchase intentions of truck fleet managers are affected by trucking firm and truck fleet characteristics, behavioral factors/opinions regarding electric trucks, and awareness of innovative charging technologies. Furthermore, electric truck adoption would be accelerated if stakeholders focused on the barriers related to the business model, product availability, and charging time. Additionally, electric truck adopters and non-adopters may not be viewed as one homogenous group, since differences were found in the ranking and interrelationships of barriers to electric truck adoption between these two groups. The implementation of electric truck technology was examined based on the truck fleet managers’ survey, secondary data sources and the case of Indiana, U.S. A multi-criteria decision-making spatial approach was proposed to identify the candidate locations for the deployment of DWC. It was concluded that the most suitable locations for DWC lanes were on interstates, near airports and ports and away from EV charging stations. A data-driven framework was also developed to quantify the impact of electric truck adoption and estimate the optimal fee for each truck to recover the revenue loss. Using the market penetration levels estimated based on the survey data collected, the average annual fuel tax revenue loss for Indiana was approximately $349M. To maintain the same tax revenue per vehicle, annual fees ranging from $969 (in 2021) to $1,243 (in 2035) for single-unit trucks and $6,192 to $7,321 for combination trucks would be needed. To address public relations problems of EV fee implementation, this study also discussed alternative mitigation measures: a vehicle-miles-traveled fee and a pay-as-you-charge fee. In summary, this dissertation contributes to the body of literature by providing significant insights regarding the perspectives of truck fleet managers for electric trucks as well as a comprehensive list of all the location criteria for DWC. The proposed frameworks and study findings can be used by policymakers and other major stakeholders of the EV ecosystem to frame certain strategies to accelerate electric truck adoption, identify the most suitable locations for charging infrastructure, better understand the impact of electric trucks on the highway revenue, and provide the groundwork for developing EV roadmaps.

In this dissertation, we focus on developing activity-based frameworks to model future mobilities (e.g., car-sharing) to study their characteristics and evaluate their impacts on travellers' behaviors using the activity-based modelling (ABM) approach. Besides, we also leverage the ABM approach to further apply it to the non-transport domain to examine the impact of transport-related policies on Coronavirus 2019 (COVID-19) pandemic modelling.

Significant seasonal changes in chemical and microbiological water quality can occur in buildings at different fixture locations due to temperature and time dependent reaction rates. Here, a series of calibrated plumbing hydraulic-water quality models were developed for the extensively monitored Retrofitted Net-zero Energy, Water & Waste (ReNEWW) house in West Lafayette, Indiana USA. Knowledge gaps that inhibited higher resolution water quality modeling were also identified. The eight new models predict the absolute level of free chlorine, total trihalomethanes (TTHM), Cu (Copper), Fe (Iron), Pb (lead), NO3 – (nitrate-nitrogen), heterotrophic plate count (HPC), and Legionella spp. concentration at each fixture for plumbing use, operational characteristics, and design layouts of the plumbing system. Model development revealed that the carrying capacity to describe Legionella spp. growth (and other organisms) under water usage and plumbing design conditions is lacking in the literature. This information needed for higher resolution modeling. Reducing building water use by 25% prompted increased absolute concentrations of HPC and Legionella, each increasing by a factor of about 105. When the service line length was increased, Legionella spp. concentrations increased by up to 106 gene copies /L in the Summer season. The proposed modeling framework can be used to support better planning, design, analysis, and operational decision-making.

Highway workers are required to work close to moving traffic during road construction and maintenance activities, which exposes them to the risk of being struck by a distracted driver or intruding vehicle. In addition, work zones disturb the usual traffic flow and patterns due to changes in the existing geometric layout of a roadway, and this is also problematic for the drivers as they must navigate a layout of signs, barrels, and lane changes while keeping the vehicle in control. Moreover, late-night tasks, reckless driving, inconsistent work zones, drunk driving, and increased vehicle miles traveled are some of the additional causes of work zone incidents in the United States. Nationwide, around 40,000 accidents occur each year in highway work zones due to vehicle intrusion into the work zone and have steadily increased during the past ten years. Most often, the driver and passenger of the vehicle are the victims of such accidents. The resulting fatalities, injuries, and property damage due to such incidents lead to significant expenses, prolonged travel delays, and potential damage to expensive products in transit. While traditional safety precautions (e.g., truck-mounted attenuators, rumble strips, speed monitoring displays) can help enhance work zone safety, the number of work zone intrusions calls for designing and implementing emerging intrusion alert technologies to warn drivers and workers when errant vehicles intrude into the work zone. Several state Departments of Transportation (DOTs) have begun examining the use of intrusion alert technologies to mitigate work zone intrusions. While previous studies examined the general effectiveness (e.g., sound levels, work zone coverage, deployment characteristics, etc.) of these technologies in both controlled and active construction and maintenance work zones, there are still significant research gaps in investigating how well these intrusion technologies alert the driver and workers, and no documented best practices are available for transportation agencies and DOTs interested in implementing them. In addition, these technologies have been through many improvements and modifications, and further research is imperative to ascertain their chances of acceptance by workers and contractors. To address these gaps, this thesis focuses on (a) empirically examining the effectiveness, implications, and practices of four commercially available intrusion technologies in enhancing work zone safety through various field tests and surveys, and (b) empirically investigating the effectiveness of these technologies considering drivers’ cognitive processing (perception -reaction time) and responses in case of work zone intrusion. The findings of this research study provide detailed information on the identification and testing procedures of technologies and offer guidelines and recommendations for adopting these technologies for practitioners and professionals in the highway construction sector. The proposed decision-making matrix and multi-criteria decision-making framework are based on the empirical data obtained from the various field experiments, literature review, and evaluation survey. This study also provides valuable insights into the overall effectiveness (i.e., by considering functional characteristics, associated drivers’ responses and reactions, and current implementation) of commercially available intrusion technologies to incorporate required modifications in designing and implementing these technologies to enhance work zone safety. The long-term outcome of this study is to significantly reduce the injuries and fatalities in highway maintenance work zones in Indiana and across the country.

Safety monitoring of the ageing train structures has always been a major challenge to the rail industry. This thesis develops a damage detection system based on nonlinear ultrasonic wave to identify fatigue crack at early stage on bogie frame to avoid catastrophic failure.

Graphene oxide nanosheets have demonstrated strong potential for reinforcing cement composites, but their poor dispersion in the cement matrix and difficulty of identification from microstructure remained to be solved. This thesis overcomes the dispersion issue and proposes effective approaches to image-based microstructure characterisation of graphene oxide-reinforced cement composites.

The use of glass fibre reinforced polymer (GFRP) has been increasing due to its considerable advantages such as high strength-to-weight ratio, resistance to corrosion, ease of installation and the relatively low cost. In comparison, wood is vulnerable to biological deterioration and harsh environmental conditions over time. It appears that a proper combination of GFRP and timber may take advantage of their individual merits and provide satisfactory mechanical performance and durability for the resulting FRP/timber composite structure. This PhD research studies the performances of GFRP timber composite structures including GFRP-confined timber structure and GFRP timber sandwich structure.

Over the past few decades, alkali-activated materials (AAMs) have shown the potential as alternative construction materials because of their high mechanical performance, low CO2 emissions, and the utilisation of industrial wastes as raw material such as fly ashn(FA). However, the curing conditions, reaction mechanisms, and durability or long-term performance of AAMs over ordinary Portland cement materials (OPC) are still under exploration. In addition, AAMs are required to exhibit adequate/superior durability to match OPCs. A wide range of precursor materials, different chemical compositions, lack of standard code of practices, complex reaction mechanisms, and variable experimental methodologies in the AAM field, have led to complexities in engineering and application and assessing durability. This body of work aims at understanding efflorescence, leaching properties and the mechanical properties of low, intermediate, and high-calcium-based AAMs. AAMs with different calcium contents in the FA precursor, with sodium silicate, sodium hydroxide, and sodium carbonate were used as activators. Representative molecular models of geopolymer were developed and molecular dynamics (MD) simulations were performed on AAMs with alkaline solvents, aimed to understand the underlying atomistic interactions. The primary objective was to understand the FA-slag based AAMs phases deterioration under efflorescence and leaching exposure, with a detailed physical and chemical analysis of the process. The research conducted was multidisciplinary and broadly classified into three parts. The first part of the work was to understand the effect of mixed activators on phase deterioration of AAMs. The second part of the work was to understand the effect of FA-slag ratio and Na2O content on reaction products. Specifically focused to understand the changes in 27Al and 23Na environment before and after efflorescence exposure. The third part of the research work discusses the effect of FA-slag ratio and Na2O content on the reaction products under leaching exposure. The outcomes of this research have contributed to the knowledge of efflorescence and leaching behaviour of alkali-activated materials. The parametric formulations of precursors and activators discussed in this work can be optimised to develop stable AAMs under various conditions.

Hydraulic fracturing is typically adopted to enhance permeability by creating a large contact area between the fluids and the hot rock. Thermal cracking will occur due to cold fluid injection near the wellbore and along the primary hydraulic fracture surface. However, the associated micro-crack initiation and propagation mechanisms in heterogeneous crystalline rocks are still unclear. This study addresses the micro-crack initiation and propagation of poly-crystalline granite. The mechanical properties of granite are estimated using homogenization methods based upon the micro-scale mechanical properties and thermal expansion coefficients of major rock-forming minerals as well as its micro-structural information.

The quality, safety, and environment Standards, each respectively referred to as ISO 9001:2015, ISO 45001:2018 and ISO 14001:2015, have been released and for the first time in the world as a united, integrated management system (IMS) that can be applied to organisations. This IMS is the combination of the said ISO Standards for quality, safety, and environment. Organisation’s may address one, two or all three of these Standards. This thesis explores how professional development (PD) in construction workplaces supports workers to have the knowledge, awareness, and competency to deliver IMS. PD is the mechanism used by workplaces to address and prevent issues such as the loss of work because of poor productivity, loss of life, and the lack of preventing pollution. There is a very clear opportunity as this is the ‘first time ever’ in the world that quality, safety, and environment can present a unified delivery for IMS because of the recognition that these three areas are inter-related as an IMS rather than isolated entities. Consequently, PD now must be delivered as a IMS reflecting this IMS model. Workplace learning is essential in understanding the context and the problem in identifying and reducing the gap in aligning PD to IMS. It is within this thesis this gap and need is explored. An IMS ensures that, by delivering on quality, safety and environment, an organisation operates and functions well, ultimately making a profit. An organisation must not only make a profit through providing quality product and services, it will survive only if it also delivers on the social contract to provide for the safety of interested parties both internally and externally. Furthermore, the product and service should be delivered to minimise environmental impact. To meet these IMS Standards, the PD of people in workplaces should be addressed in an integrated and effective way in alignment with the IMS. My motivation in undertaking this research stems from problems I experienced, and what I have seen others experienced, resulting from what I assume is poor alignment between PD and IMS. This problem relates to the phenomenon of learning in the workplace. This research focuses upon the question, “How does professional development in the construction workplace align with integrated management systems?” The research was not a test of a theory and hypotheses of why there is the misalignment of PD with the lack of IMS in the workplace. Instead, the research developed conceptual themes to explain the experiences of workers who participated. The participant cross-section consisted of construction and engineering workers and owners in business, that operate an IMS from 15 construction workplaces in Australia that operated locally, regionally, and nationally. These targeted participants were male and female workers that ranged from their 20’s to 60’s in age that directly have the responsibility of managing the IMS. The data collected came from semi formal interviews (resulting in transcripts of the interview) and reviewed secondary data such as documented information and photos. I then used a qualitative methodology with the tool of thematic analysis. The themes developed can contribute to knowledge about PD, workplace learning, and IMS, and better prepare owners and management with the utilisation of IMS to guide PD that delivers quality, safety, and environmental controls within their workplace.

This thesis discusses the application of deep neural network in TBM parameters prediction and tunnel inspection. Three different of neural network models with different structures are established and optimized according to different application scenarios. The test results show that these models are feasible.

This thesis introduces a new numerical tool combining the advantages of discrete and continuum modelling approaches to provide quantitative descriptions on the interaction of different phases in silty sands (i.e. water, fines and coarse phases). With this new approach, both fluid and fines particles are treated as continuous phases, while coarse sand particles are still treated as a discontinuous phase to maintain the discrete feature of geomaterials. The main outcomes of this study include i) the comprehensive DEM study on the effect of fines on the behaviour of silty sands, ii) the development of a new continuum approach with a two-phase Eulerian-Eulerian CFD model to upscale fine granular material from discrete to continuum phase, and iii) the development of a three-phase CFD-DEM coupling framework for detail descriptions silty sands at a satisfactory level.

This thesis examines the thermal and economic performance of closely spaced energy piles. It identifies that intermittent operation of the ground source heat pump improves the geothermal energy utilisation and reduces the thermal interaction between the piles due to lower thermal impacts in the ground, compared to continuous operation of the ground source heat pump. Also, the economic and environmental benefits of energy piles are significant for buildings with yearly heating and cooling demand and are higher for energy pile systems with greater pile spacing, longer pile lengths and larger number of piles operating as energy piles.

This dissertation focuses on developing a series of mathematical models to understand the role of urban transportation system, urban mobility and information dissemination in the spreading process of infectious diseases within metropolitan areas. Urban transportation system serves as the catalyst of disease contagion since it provides the mobility for bringing people to participate in intensive urban activities and has high passenger volume and long commuting time which facilitates the spread of contagious diseases. In light of significant needs in understanding the connection between disease contagion and the urban transportation systems, both macroscopic and microscopic models are developed and the dissertation consists of three main parts. The first part of the dissertation aims to model the macroscopic level of disease spreading within urban transportation system based on compartment models. Nonlinear dynamic systems are developed to model the spread of infectious disease with various travel modes, compare models with and without contagion during travel, understand how urban transportation system may facilitate or impede epidemics, and devise control strategies for mitigating epidemics at the network level. The hybrid automata is also introduced to account for systems with different levels of control and with uncertain initial epidemic size, and reachability analysis is used to over-approximate the disease trajectories of the nonlinear systems. The 2003 Beijing SARS data are used to validate the effectiveness of the model. In addition, comprehensive numerical experiments are conducted to understand the importance of modeling travel contagion during urban disease outbreaks and develop control strategies for regulating the entry of urban transportation system to reduce the epidemic size. The second part of the dissertation develops a data-driven framework to investigate the disease spreading dynamics at individual level. In particular, the contact network generation algorithm is developed to reproduce individuals' contact pattern based on smart card transaction data of metro systems from three major cities in China. Disease dynamics are connected with contact network structures based on individual based mean field and origin-destination pair based mean field approaches. The results suggest that the vulnerability of contact networks solely depends on the risk exposure of the most dangerous individual, however, the overall degree distribution of the contact network determines the difficulties in controlling the disease from spreading. Moreover, the generation model is proposed to depict how individuals get into contact and their contact duration, based on their travel characteristics. The metro data are used to validate the correctness of the generation model, provide insights on monitoring the risk level of transportation systems, and evaluate possible control strategies to mitigate the impacts due to infectious diseases. Finally, the third part of the dissertation focuses on the role played by information in urban travel, and develops a multiplex network model to investigate the co-evolution of disease dynamics and information dissemination. The model considers that individuals may obtain information on the state of diseases by observing the disease symptoms from the people they met during travel and from centralized information sources such as news agencies and social medias. As a consequence, the multiplex networks model is developed with one layer capturing information percolation and the other layer modeling the disease dynamics, and the dynamics on one layer depends on the dynamics of the other layer. The multiplex network model is found to have three stable states and their corresponding threshold values are analytically derived. In the end, numerical experiments are conducted to investigate the effectiveness of local and global information in reducing the size of disease outbreaks and the synchronization between disease and information dynamics is discussed.

Recent research developments have indicated that asphalt mixture durability and pavement life can be increased by modifying the Superpave asphalt mixture design method to achieve an in-place density of 95%, 2% higher than the conventional density requirements of approximately 93% (7% air voids content). Doing so requires increasing the design air voids content to 5% from the conventional requirement of 4 percent. After successful laboratory testing of this modified mixture design method, known as Superpave 5, two controlled field trials and one full scale demonstration project, the Indiana Department of Transportation (INDOT) let 12 trial projects across the six INDOT districts based on the design method. The Purdue University research team was tasked with observing the implementation of the Superpave 5 mixture design method, documenting the construction and completing an in-depth analysis of the quality control and quality assurance (QC/QA) data obtained from the projects. QC/QA data for each construction project were examined using various statistical metrics to determine construction performance with respect to INDOT Superpave 5 specifications. The data indicate that, on average, the contractors achieved 5% laboratory air voids, which coincides with the Superpave 5 recommendation of 5% laboratory air voids. However, on average, the as-constructed in-place density of 93.8% is roughly 1% less than the INDOT Superpave 5 specification. The findings of this study will benefit the future implementation of this modified mixture design method.

Traffic is inevitably a major source of air pollution, particularly in urban areas. Efforts are made towards reducing emissions by improving vehicle and fuel technology and promoting alternative, sustainable modes of transportation. Although the emergence of EVs has shown capabilities of decreasing energy use and emissions levels, the EV market is developing slowly mainly due to drivers’ range anxiety and charging time. Electric roadways (ERs) have been proposed as a solution to overcome the concerns related to EVs by converting road segments into powered lanes where vehicles can be charged as they move along the roadway. This technology has the potential to increase driving range, decrease battery size and thus, lower the weight and the cost of EVs. In this context, exploring the challenging concept of ERs comes natural. Since data on the market acceptance and the environmental implications on this technology are limited to non-existent, this thesis has the following objectives: 1) identify the factors that affect the short- and long-term intention to use ERs, 2) estimate the level of adoption of the ER technology and identify characteristics of the market segments and 3) assess the impact of ERs on criteria pollutants and greenhouse gas emissions based on the market adoption results. To achieve these objectives, a survey of the general population in Los Angeles, California was conducted, gathering 600 responses representative of gender and age in the area. Los Angeles is considered a leader in electro-mobility and thus, a natural choice for the implementation of ERs. The short-or long-term intentions to drive on ERs and purchase an EV knowing about the availability of ERs were found to be correlated and thus, were modeled simultaneously using a bivariate ordered probit model. The compatibility of the ER technology with respondents’ lifestyle and needs, respondents’ tendency towards using sustainable forms of transportation, respondents’ innovativeness and perceived environmental benefits were among the most significant variables found to affect the short-term and long-term intention to use ERs. The level of adoption of the ER technology and corresponding market segments were identified using a combination of Principal Component Analysis (PCA) and Cluster Analysis. Three clusters emerged from the analysis: early adopters (48.5%), mid-adopters (27.67%) and late adopters (23.83%) that differed in terms of demographics and socioeconomic characteristics, travel and EV charging characteristics and level of awareness. The adoption levels found were then used to estimate the emissions change due to the implementation of the ERs by 2050. Using the California Air Resources Board’s (CARB) 2017 EMissions FACtor model (EMFAC). Two scenarios were examined considering light-duty vehicles (LDVs) in a specific corridor: “with” and “without electrification” scenarios. The results suggested that the ER technology for light-duty vehicles has the potential to provide emission reductions of 4 to 24%. A sensitivity analysis was also conducted to examine the effect of speed on the results. Turning to the practical implications, this thesis can provide a foundational framework for the evaluation of the ER technology in terms of environmental and economic viability and set the groundwork for future research. Ultimately, the short-term and long-term intention analysis can be used as a draft guide by state and local agencies and inform their strategic short- or long- range plans for mobility. By segmenting potential users, policy makers and transport operators can be informed about the main challenges regarding the promotion of the ER technology to distinct market segments and devise ways to accelerate its adoption. The findings from the impact analysis of ERs on criteria pollutants and greenhouse gases can also inform long-range transportation plans and existing regulations and policies in California and beyond.

LiDAR units onboard airborne and terrestrial platforms have been established as a proven technology for the acquisition of dense point clouds for a wide range of applications, such as digital building model generation, transportation corridor monitoring, precision agriculture, and infrastructure monitoring. Furthermore, integrating such systems with one or more cameras would allow forward and backward projection between imagery and LiDAR data, thus facilitating several high-level data processing activities such as reliable feature extraction and colorization of point clouds. However, the attainment of the full 3D point positioning potential of such systems is contingent on an accurate calibration of the mobile mapping unit as a whole. This research aims at proposing a calibration procedure for terrestrial multi-unit LiDAR systems to directly estimate the mounting parameters relating several spinning multi-beam laser scanners to the onboard GNSS/INS unit in order to derive point clouds with high positional accuracy. To ensure the accuracy of the estimated mounting parameters, an optimal configuration of target primitives and drive-runs is determined by analyzing the potential impact of bias in mounting parameters of a LiDAR unit on the resultant point cloud for different orientations of target primitives and different drive-run scenarios. This impact is also verified experimentally by simulating a bias in each mounting parameter separately. Next, the optimal configuration is used within an experimental setup to evaluate the performance of the proposed calibration procedure. Then, this proposed multi-unit LiDAR system calibration strategy is extended for multi-LiDAR multi-camera systems in order to allow a simultaneous estimation of the mounting parameters relating the different laser scanners as well as cameras to the onboard GNSS/INS unit. Such a calibration improves the registration accuracy of point clouds derived from LiDAR data and imagery, along with their accuracy with respect to the ground truth. Finally, in order to qualitatively evaluate the calibration results for a generic mobile mapping system and allow the visualization of point clouds, imagery data, and their registration quality, an interface denoted as Image-LiDAR Interactive Visualization Environment (I-LIVE) is developed. Apart from its visualization functions (such as 3D point cloud manipulation and image display/navigation), I-LIVE mainly serves as a tool for the quality control of GNSS/INS-derived trajectory and LiDAR-camera system calibration. The proposed multi-sensor system calibration procedures are experimentally evaluated by calibrating several mobile mapping platforms with varying number of LiDAR units and cameras. For all cases, the system calibration is seen to attain accuracies better than the ones expected based on the specifications of the involved hardware components, i.e., the LiDAR units, cameras, and GNSS/INS units.

The rise of technologies and the Internet have provided opportunities to connect logistics demand and supply using the crowd. In this system, named crowd-shipping (CS), a requester doing the shipping selects a courier via a platform. In reality, the idea of CS has been explored by many firms over the last several years. However, there is a lack of fundamental understanding of the issues related to: (1) the markets that are likely to be influenced by CS; (2) the considerations that govern the success of this system; and the (3) the impacts of CS and its design. To address these issues, there is a need of understanding CS system's stakeholders, such as requesters' (i.e. senders') and potential couriers' (i.e. driver-partners') behaviors as well as operations and management of CS firms. This research will address these gaps by conducting a survey to understand driver-partners' behaviors and requesters' behaviors given the CS services availability in the logistics market. Then, pricing and compensation strategies are designed and modeled based on behavior rules of supply and demand generations as well as various CS market penetrations. As such, this research addresses the CS industry in a triad of supply, demand, and operations and management. This research uses advanced econometrics, statistics analysis, mixed integer optimization, and data science techniques to analyze data and generate insights. The contributions of this research are to identify the contributing factors that impact the emerging logistics service. This research also reveals factors that influence the current and future shipping behaviors of requesters, as well as influencing factors of the individuals' willingness to work as driver-partners. The integrated matching and routing models have been developed to examine different pricing and compensation strategies under several market penetration scenarios. `Individual' price and compensation have found to provide the highest profit for CS platform providers. This research provides meaningful knowledge for stakeholders, especially for the CS firms to develop business strategies. Several remarkable benefits that CS firms can obtain include: focusing on some specific population groups to recruit driver-partners (e.g. people with children, middle-aged people having lower incomes, or no car ownership); addressing certain market segments to promote CS services (e.g. tight-window delivery packages, peripheral products, or personal health and medicine items); implementing `individual' or `flatted' pricing and compensation strategies depending on the time of the day, the day of the week, or the market penetration; and improving platform features to incorporate requesters' and driver-partners' expectations.

Due to the slender geometries of aboveground storage tanks, maintaining the stability under wind gusts of these tanks has always been a challenge. Therefore, this thesis aims to provide a through insight on the behavior of tanks under wind gusts using finite element analysis and computational fluid dynamic (CFD) analysis. The present thesis is composed of three independent studies, and different types of analysis were conducted. In Chapter 2, the main purpose is to model the wind loading dynamically and to investigate whether a resonance can be triggered. Research on tanks subjected to static wind load have thrived for decades, while only few studies consider the wind loading dynamically. Five tanks with different height (H) to diameter (D) ratios, ranging from 0.2 to 4, were investigated in this chapter. To ensure the quality of the obtained solution, a study on the time step increment of an explicit dynamic analysis, and a on the mesh convergence were conducted before the analyses were performed. The natural vibration frequencies and the effective masses of the selected tanks were first solved. Then, the tanks were loaded with wind gusts with the magnitude of the pressure fluctuating at the frequency associating with the most effective mass and other frequencies. Moreover, tanks with eigen-affine imperfections were also considered. It was concluded that resonance was not observed in any of these analyses. However, since the static buckling capacity and the dynamic buckling capacity has a relatively large difference for tall tanks (H/D ≥ 2.0), a proper safety factor shall be included during the design if a static analysis is adopted. Chapter 3 focus on the effect of an internal pressure generated by wind gusts on open-top tanks. Based on boundary layer wind tunnel tests (BLWT), a significant pressure would be generated on the internal side of the tank shell when a gust of wind blow through an open-top tank. This factor so far has not been sufficiently accounted for by either ASCE-7 or API 650, despite the fact that this internal pressure may almost double the design pressure. Therefore, to investigate the effect of the wind profile along with the internal pressure, multiple wind profiles specified in different design documents were considered. The buckling capacities of six tanks with aspect ratios (H/D) ranging from 0.1 to 4 were analyzed adopting geometrically nonlinear analysis with imperfection using an arc-length algorithm (Riks analysis). Material nonlinearity was also included in some analyses. It was observed that the buckling capacity of a tank obtained using ASCE-7/API 650 wind profile is higher than buckling capacities obtained through any other profiles. It was then concluded that the wind profile dictated by the current North American design documents may not be conservative enough and may need a revision. Chapter 4 investigates how CFD can be applied to obtain the wind pressure distribution on tanks. Though CFD has been widely employed in different research areas, to the author’s best knowledge, only one research has been dedicated to investigate the interaction between wind gusts and tanks using CFD. Thus, a literature review on the guideline of selecting input parameter for CFD and a parametric study as how to choose proper input parameters was presented in Chapter 4. A tank with an aspect ratio of 0.5 and a flat roof was employed for the parametric study. To ensure the validity of the input parameters, the obtained results were compared with published BLWT results. After confirming that the selected input parameters produces acceptable results, tanks with aspect ratio ranging from 0.4 to 2 were adopted and wind pressure distribution on such tanks were reported. It was concluded that the established criteria for deciding the input parameters were able to guarantee converged results, and the obtained pressure coefficients agree well with the BLWT results available in the literature.

In 2011, the Deep River Portage-Burns Waterway Watershed was identified as a priority in the Northwest Indiana watershed management framework by the Northwester Indiana Regional Planning Committee. 319 grant cost-share programs were initiated in effort of maintaining and restoring the health of Deep River Portage-Burns Waterway Watershed. A watershed management plans have been developed for this watershed which proposed the implementation of vegetated filter strips (VFS) as an option. In this thesis work, the effectiveness of VFS as a best management practice (BMP) for the Deep River system was evaluated using a hydrological model scheme. In this research, a Nonpoint Source Pollution and Erosion Comparison Tool (NSPECT) model and a Soil Water Assessment Tool (SWAT) model were constructed with required watershed characteristic data and climate data. The initial hydrologic and nutrient parameters of the SWAT model were further calibrated using SWAT Calibration and Uncertainty Programs (SWAT_CUP) with historical flow and nutrient data in a two-stage calibration process. The calibrated parameters were validated to accurately simulate the field condition and preserved in SWAT model for effectiveness analysis of BMP implementations. To evaluate the effectiveness of VFS as a BMP, four different scenarios of VFS implementations along the Turkey Creek was simulated with the calibrated SWAT model. With the implementation of VFS in the tributary subbasin of Turkey Creek, the annual total phosphorus (TP) of the VFS implemented subbasin was reduced by 1.60% to 78.95% and the annual TP of downstream subbasins were reduced by 0.09% to 55.42%. Daily percentage of TP reductions ranged from 0% to 90.3% on the VFS implemented subbasin. Annual TP reductions of the four scenarios ranged from 28.11 kg to 465.01 kg.

Wetlands are dispersed fractal aquatic habitats that play a key role in watershed eco-hydrology. Wetlands provide critical habitats for specialized fauna and flora, process nutrients, and store water. Wetlands are found in a wide range of landscapes and climates, including humid/tropical regions where surface water is abundant, and in semiarid/arid regions with surface-water deficits. Wetland morphology and hydrology are governed by geomorphology and climate. Wetlands are dynamic; they change in space and time in response to unsteady external conditions, and over longer term to internal process feedbacks. Together, wetlands form a mosaic of heterogeneous, dynamic, aquatic habitats in varying spatial organizations, networked by hydrological and ecological connections. The overarching goal of the proposed research is to provide a robust theoretical framework to model the dynamics of multiple wetlands spread across watersheds (wetlandscape). In particular, the three main lens I used for identifying the spatiotemporal variability in wetlandscapes were: hydrology, morphology and ecology. Indeed, the hydrological modeling of wetlands is of key importance to determine which habitats are potentially able to host aquatic and semiaquatic species, as well as function as retention basin for storing considerable amount of water or for processing nutrients. Wetlands interaction with the landscape topography is essential to characterize the morphological attributes of these waterbodies. Different generating mechanisms have produced differences in wetland shapes and extent. However, even if wetlands are different among regions, and also within the same landscape, the set of function that they can support is similar. In the present research, I have also proposed that because water accumulates at low elevations, topography-based models helpful for the identification of wetlands in landscapes. These types of models are useful especially in those cases were wetlands data are sparse or not available. The proposed approaches could reproduce the abundance and distribution of active wetlands found in the NWI database, despite the differences in identification methods. In particular, I found that wetland size distributions in all the conterminous United States share the same Pareto pdf. Furthermore, the wetland shape is constrained into a narrow range of 2D fractal dimension (1.33;1.5). Since this method can be carried out with only a DEM as input, the proposed framework can be applied to any DEM to extract the location and the extent of depressional wetlands.Wetlands are among the most biologically diverse ecosystems, serving as habitats to a wide range of unique plants and animal life. In fact, wetlands and their surrounding terrestrial habitats are critical for the conservation and management of aquatic and semi-aquatic species. Understating the degree and dynamics of connectedness among individual wetlands is a challenge that unites the fields of ecology and hydrology. Connectivity among spatially distributed mosaic of wetlands, embedded in uplands, is critical for aquatic habitat integrity and to maintain metapopulation biodiversity. Land-use and climate change, among other factors, contribute to wetland habitat loss and fragmentation of dispersal networks. Here, I present an approach for modeling dynamic spatiotemporal changes, driven by stochastic hydroclimatic forcing, in topology of dispersal networks formed by connecting habitat zones within wetlands. I examined changes in topology of dispersal networks resulting from temporal fluctuations in hydroclimatic forcing, finding that optimal dispersal network are available only for limited time period, thus species need to constantly adapt to cope with adverse conditions. Loss of wetlands leads to habitat fragmentation and decrease in landscape connectivity, which in turn hampers the dispersal and survival of wetland-dependent species. Ecosystem functions arise from interdependent processes and feedbacks operating concurrently at multiple scales. In this thesis, I integrated stochastic models for landscape hydrology to study the temporal variability in wetlands attributes (e.g., stage, surface area and storage volume, carrying capacity) with ecological network theory allows for characterization of the spatiotemporal dynamics of habitat distribution and connectivity that is essential to meta-communities. The proposed framework can be applied in diverse landscapes and hydro-climates, and could thus be used at larger scales. The proposed approach could also inform conservation and restoration efforts that target landscape functions linked to transport in wet ecological corridors. The interdisciplinarity that characterizes this work allows for a wide spectrum of potential applications. Despite the ultimate goal of the thesis consists in the eco-hydrologic modeling of wetlandscapes, the backbone of the proposed models could be extended to any kind of patchily habitat driven by stochastic forcing.

In the past decade, high-strength reinforcement (fy > 60 ksi) has become more prevalent and more widely accepted. Building codes such as ACI 318-14 do not address the use of highstrength reinforcement for proper development and splicing of reinforcement. Furthermore, research on development of high-strength reinforcement is limited. The objective of the study is to develop a suitable expression for the development and splicing of high-strength reinforcement.Of particular interest is evaluating the influence of splice length and confinement on bond strength as well as evaluating the effectiveness of high-strength transverse reinforcement on bond strength. The study tested 22 large-scale concrete beams reinforced with ASTM A615Grade 100 deformed steel bars: 11 specimens without transverse reinforcement within the splice region (unconfined) and 11 specimens with transverse reinforcement within the splice region (confined). Splice lengths varied from 40 bar diameters to 120 bar diameters, which are some of the largest ever tested. The effect of the test variables which were systematically studied, foundthat splice strength is nonlinearly related with splice length and can be represented by a power equation. Furthermore, it was found that high-strength transverse reinforcement does not improve bond strength compared with the use of Grade 60 transverse reinforcement. Considering the test results and review of historical test results, an analytical investigation was conducted which developed a simple expression for estimating the capacity of both unconfinedand confined beams. The results are compared with the current building code design expressions as well as other proposed bond strength equations. The research conducted here provides the basis for development of a design expression that will allow for the incorporation of highstrength reinforcement in future building codes.

The use of digital three-dimensional (3D) data has increased over the last two decades as private and public firms have begun to realize its utility. Mobile Terrestrial Laser Scanning (MTLS) or Mobile Mapping Systems (MMS), which utilizes LiDAR (Light Detection and Ranging) data collection from a moving platform along with advances in positioning systems—e.g., Global Navigation Satellite Systems (GNSS), Inertial Navigation Systems (INS), and Distance Measurement Instruments (DMIs)—have paved the way for efficient, abundant, and accurate 3D data collection. Validation and control targets are vital to ensure relative and/or absolute accuracy for MTLS projects. The focus of this dissertation is to evaluate several types of targets and the positional spacing of said targets for MTLS.A mostly planar two-dimensional (2D) targeting system (painted target on ground) is commonly used to constrain, register, and validate the 3D point clouds from MTLS. In this dissertation, 3D objects—a sphere and a cube—were evaluated with varied angles of incidence and point densities as more appropriate alternatives to constrain and validate the 3D MTLS point clouds. Next, a planar circular 2D target—with the use of the raw intensity of the LiDAR pulse as another measured dimension—was evaluated as a proof of concept to also constrain and validate 3D LiDAR data. A third and final component of this dissertation explored analyses of INS data to determine the positional spacing of control and validation targets in MTLS projects to provide maximum accuracy for all data points.