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Because of the ongoing expansion of urban areas, transportation systems are being increasingly moved beneath the ground into tunnels. However, the construction of tunnels is very challenging regarding unexpected geological conditions, the protection of existing buildings from damage, and the control of financial and safety risks. During the tunnel construction process, different simulations are performed to predict, for example, settlements, soil excavation, or grouting behavior. Although these simulations should strongly interact, they often use independent heterogeneous geological data models and resources, thus resulting in unreliable predictions. This paper presents a hybrid ground data model along with necessary access concepts to support the automated management and exchange of continuously updated geological information among interacting simulations. The ground data model uses a boundary and a decomposition representation of the ground geometry with material information attached to each representation. These representations are converted to one another on demand to make up-to-date ground information available for participating tunneling simulations. To validate the proposed model and concepts, a case study is presented in which two typical simulations are coupled using the prototypically implemented hybrid ground data model. [ABSTRACT FROM AUTHOR]

Current processes for design and detailing in structural engineering are often broken up into a sequence of partial processes because of the complexity of the problem. But sequential additions of separate solutions rarely lead to an optimal design. For example, the basic structural system is often developed with its geometry and topology but without consideration of important aspects of structural performance, like robustness, redundancy, ductility. Decisions on performance are left for later design stages, when it is still possible to change details but too late to improve the structural system. A design that takes into account multiple objectives, such as safety, functionality, and aesthetics, requires a complete reconsideration of the authors' conventional sequential structural design process. Most engineering tools were developed many years ago as technology was much more limited, resulting in separate tools for separate objectives to be used in succession. In this paper, a new approach is presented as integrative structural design (ISD), where separate state-of-the-art solutions are synchronized in such a way that designers are not confined to predetermined solution paths but rather are enabled to consider different objectives concurrently including interactions between objectives. The resulting design tool for the conceptual, interactive modeling, simulation, and visualization of structural design or integrative design is presented under the term integrative structural design system (ISDS). [ABSTRACT FROM AUTHOR]

In Part I of this two-part study, a theory is provided for the extension of the lattice discrete particle model (LDPM) to include fiber reinforcing capability. The resulting model, LDPM-F, is calibrated and validated in the present paper by comparing numerical simulations with experimental data gathered from the literature. The analyzed experiments include direct tension, confined and unconfined compression, and notched three-point bending tests. [ABSTRACT FROM AUTHOR]

The research into modeling walking-induced dynamic loading and its effects on footbridge structures and people using them has been intensified in the past decade after some high profile vibration serviceability failures. In particular, the crowd induced loading, characterized by spatially restricted movement of pedestrians, has kept attracting attention of researchers. However, it is the normal spatially unrestricted pedestrian traffic, and its vertical dynamic loading component, that is the most relevant for vibration serviceability checks for most footbridges. Despite the existence of numerous design procedures concerned with this loading, the current confidence in its modeling is low due to lack of verification of the models on as-built structures. This is the motivation behind reviewing the existing design procedures for modeling normal pedestrian traffic in this paper and evaluating their performance against the experimental data acquired on two as-built footbridges. Additionally, the use of Monte Carlo simulations is also investigated. Possible factors that cause discrepancies between measured and calculated vibration responses, including possibility of existence of pedestrian-structure dynamic interaction, are discussed. [ABSTRACT FROM AUTHOR]

This research proposes a hybrid simulation approach based upon the principles of system dynamics (SD) and discrete event simulation (DES), which facilitates a better understanding of complex interactions among various processes in large-scale construction. The significance of the construction context that interacts with construction operations is highlighted, and a hybrid SD-DES approach is proposed as a means to capture the feedback between the two. In particular, this paper focuses on how to seamlessly integrate SD and DES within the framework of a modeling perspective. For the purpose of substantiating the discussion, a pipeline installation process is modeled using the proposed hybrid approach, with specific consideration given to how the approach can serve to address complex interactions between operation and context. [ABSTRACT FROM AUTHOR]

The importance of integrating construction knowledge into the design process has long been recognized by the construction industry. This paper studies early contractor involvement in design and its impact on construction schedule performance through a combined empirical case study and theoretical simulation analysis. Pipe and steel fabricators’ inputs at different design stages of industrial construction projects are identified. The case study shows that these inputs lead to improved drawing quality, material supply, information flow, and consequently improved construction schedule performance. This impact on construction schedule is illustrated using actual project data and simulation techniques. Simulation models were developed to demonstrate intuitively the impact at the construction operation level and they allow people to gain management insights through simulation experiments. Better understanding of the early contractor involvement process and its benefit can improve buy-in and help industry practitioners to reach the full potential of this concept. [ABSTRACT FROM AUTHOR]

The integration of modeling and simulation tools with robust and efficient methods of optimal design offers a rational approach to explore new concepts and designs. However, a widespread adaptation of these tools in the industry design environment will require that they incorporate a systematic analysis of uncertainty in all aspects of the design process. A lack of confidence in designs generated in a simulation-based approach is the result of uncertainties in the predictive capabilities of physics-based models used in the simulations, and poor representation of uncertainties and their propagation in a coupled systems engineering design problem. A data- and knowledge-lean environment, typical of a design process involving novel concepts, further exacerbates the situation; design engineers often make gross assumptions about distributional information of random variables and parameters, thereby adding to the uncertainty associated with the design results. The paper focuses on numerical and analytical tools by which to model uncertainty and risk in a simulation-based design environment, including cases where the uncertainty does not conform to standard probabilistic distributions. A specific focus of the modeling effort is an approach to establish confidence intervals for response predictions available from analytical and numerical models, as well as surrogate approximations used in the design process. Innovative adaptations of formal optimization methods in a nondeterministic design setting are discussed, including design problem formulations that examine the nondeterministic design problem in a multicriteria optimization framework. Simple design problems are used to illustrate the concepts and to underscore the deficiencies in a purely deterministic approach to the design problem. [ABSTRACT FROM AUTHOR]

The focus of this paper is to demonstrate the application of a recently developed Bayesian state estimation method to the recorded seismic response of a building and to discuss the issue of model selection. The method, known as the particle filter, is based on stochastic simulation. Unlike the well-known extended Kalman filter, it is applicable to highly nonlinear systems with non-Gaussian uncertainties. The particle filter is applied to strong motion data recorded in the 1994 Northridge earthquake in a seven-story hotel whose structural system consists of nonductile reinforced-concrete moment frames, two of which were severely damaged during the earthquake. We address the issue of model selection. Two identification models are proposed: a time-varying linear model and a simplified time-varying nonlinear degradation model. The latter is derived from a nonlinear finite-element model of the building previously developed at Caltech. For the former model, the resulting performance is poor since the parameters need to vary significantly with time in order to capture the structural degradation of the building during the earthquake. The latter model performs better because it is able to characterize this degradation to a certain extent even with its parameters fixed. For this case study, the particle filter provides consistent state and parameter estimates, in contrast to the extended Kalman filter, which provides inconsistent estimates. It is concluded that for a state estimation procedure to be successful, at least two factors are essential: an appropriate estimation algorithm and a suitable identification model. [ABSTRACT FROM AUTHOR]

Permeability is an important property that influences the performance of hot-mix asphalt (HMA). It is a function of compaction effort, and several properties of HMA such as asphalt content, and the shape and size distribution of aggregates. Due to the different laboratory and field methods for measuring permeability, and the interaction among the factors that influence its value, it would be difficult to develop an analytical equation that accurately relates permeability to all factors contributing to HMA permeability. This paper presents a simple equation for approximating the permeability of asphalt mixes. It utilizes the percent air voids and surface area of aggregates. The equation is empirical but it is derived based on the well-known Kozeny–Carman equation for calculating the permeability of granular materials. The developed equation was used successfully to fit permeability data collected from several studies that carried field and laboratory measurements of HMA permeability. A finite element model was developed to investigate the influence of the gradient of percent air voids in HMA on water flow patterns. The x-ray computed tomography was used to measure the percent air void gradients among sublayers of the asphalt mix. The permeability of these sublayers was calculated using the developed equation, and used as an input to the finite element model. The simulation results show that air void gradients in HMA encourage lateral flow in the horizontal direction and reduce the flow in the vertical direction. [ABSTRACT FROM AUTHOR]

Operational performance in residential construction production systems is assessed based on measures such as average house-completion time, number of houses under construction, lead time, and customer service. These systems, however, are prone to nonuniformity and interruptions caused by a wide range of variables such as inclement weather conditions, accidents at worksites, fluctuations in demand for houses, and rework. The availability and capacity of resources therefore are not the sole measures for evaluating construction production systems capacity, especially when rework is involved. The writers' aim is to investigate the effects of rework timeframe and frequency/length on tangible performance measures. Different call-back timeframes for rework and their impact on house-completion times are modeled and analyzed. Volume home-building was chosen as the industry sector studied in the research reported in this paper because it is a data-rich environment. The writers designed several experiments to model on time, late, and early call-back timeframes in the presence of rework with different length and frequency. Both mathematical modeling and discrete-event simulation were then used to compare and contrast outputs. The measurements showed that the average completion time is shorter in systems interrupted by frequent but short rework. In other words, a smaller downstream buffer between processes is required to avoid work starvation than those systems affected by infrequent but long interruptions. Early call-backs for rework can significantly increase the number of house completions over the long run. This indicates that there is an opportunity for the mass house-building sector to improve work practice and project delivery by effectively managing rework and its related variables. The research reported in this paper builds on the current body-of-knowledge by applying even-flow production theory to the analysis of rework in the residential construction sector, with the intention of ensuring minimal disruption to construction production process and improving productivity. [ABSTRACT FROM AUTHOR]