Search

In this paper, a state-space method for double-beam systems with variable cross sections is developed, making it possible to calculate the transverse vibration of the double-beams accurately and effectively. Due to the variability in the double-beam cross sections with the viscoelastic interlayer in between, the governing equations of vibration for the systems become highly coupled partial differential equations, making the problem difficult to solve. A basic double-beam system is introduced to modify the original governing equations to two inhomogeneous differential equations. Given the separation of variables, several mode-shape coefficients and a state variable are defined to construct the state-space equations. The coupling terms and variables are transferred into the constant coefficient matrix of the state-space equations, decoupling them. Numerical procedures are presented to solve the state-space equations to obtain homogenous and inhomogeneous solutions, including the natural frequencies and mode shapes in free vibration and the dynamic responses in forced vibration, respectively. The method has substantial advantages in decoupling high-order partial differential equations and can be further extended to solve complex structural systems. Numerical results also demonstrate that the method is accurate and efficient. Finally, an engineering application with a rail-bridge with a floating slab track is discussed in detail with the method.

The use of biochar as a concrete constituent has been proposed to reduce the massive carbon footprint of concrete. Due to the low density and complex porosity of biochar, microstructural analysis of Portland cement-biochar composites is challenging. This causes challenges to the improvement of the micro-scale understanding of biochar composite behavior. This work advances the microstructural understanding of Portland cement composites with 0, 5, and 25 volume percent (vol%) of cement replaced with wood biochar by applying common characterization techniques of mercury intrusion porosimetry (MIP), gas sorption, scanning electron microscopy, and isothermal heat flow calorimetry (HFC) in conjunction with 1H nuclear magnetic resonance (NMR) and micro-X-ray computed tomography (XCT) analysis techniques. The combination of these techniques allows a multi-scale investigation of the effect of biochar on the microstructure of cement paste. NMR and XCT techniques allow the observation and quantification of the pore space. HFC and MIP confirmed that biochar absorbs moisture and reduces the effective water-cement ratio. Gas sorption, MIP, and NMR shows that 5 vol% replacement does not significantly affect the gel and capillary pore structures. Results from XCT (supported by MIP and NMR) show that biochar can reduce the formation of larger pores. Importantly, XCT results suggest that biochar can act as a flaw in the microstructure which could explain reductions in the mechanical properties. Overall, the mechanical properties already analyzed in the literature are consistent with the microstructural changes observed, and these results highlight the need to carefully tailor the volume fraction of biochar to control its effect on the paste microstructure.

Abstract: Terrestrial evapotranspiration is the second‐largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross‐disciplinary group of ET scientists to overcome the challenges identified in this paper and ultimately advance our integrated understanding of ET.

Nurseries and greenhouses face challenges of limited water supply and increased demand for irrigation efficiency to minimize runoff and mitigate water loss to the environment. Overhead irrigation systems are among the most widely used methods for container plants, particularly in small container sizes. However, there is a lack of research examining the distribution uniformity (DU) of the most used sprinklers in nursery settings. Our study investigated the DU of different overhead sprinkler types and models commonly used in outdoor nurseries in the United States to guide greater adoption of higher irrigation efficiency technology. Catch-can experiments compared ten different sprinkler models in small (4.6 m × 4.6 m) and large (9.1 m × 9.1 m) square experimental plots in Irvine, California. We measured water volume, wind speed, and operating pressure, and calculated the application rate for 189 test runs conducted between Mar 2020 and May 2023. Our results show that of the models tested, the greatest DU was achieved by the Hunter MP2000 at 276 kPa (DU = 0.78 ± 0.05) in the small spacing, and the Senninger Xcel Wobbler with a 3.97 mm nozzle at 172 kPa (DU = 0.76 ± 0.06) in the large spacing. Wind speed and operating conditions affected the DU and spatial uniformity of irrigation among the ten models, highlighting the importance of maintaining operating pressures at the manufacturer's recommendations to ensure optimal application rates and DU. Together these results offer a quantitative comparison of sprinkler performance at different operating pressure and in a wide range of wind speeds, allowing users to select sprinkler models that best fit their operation and maximize water conservation.

We conduct coupled thermo-hydro-mechanical modeling of a KBS-3V repository design in crystalline rocks, using data and conditions from the Forsmark in Olkiluoto repository sites in Sweden and Finland. The study focuses on repository performance related to the impact of thermal and hydraulic evolution on the potential for thermal–mechanical damage to underground repository excavations. For the designs and conditions considered at the Forsmark and Olkiluoto repository sites, the simulations show a peak temperature well under the adopted performance target of a 100°C maximum temperature, whereas there is still a high potential for thermal–mechanical damage to the KBS-3V waste deposition holes. The thermal–mechanical damage is much more likely if rock permeability is so low that it delays saturation and swelling of bentonite-clay-based backfill beyond the time for the thermal–mechanical peak, which occurs 50 to 100 years after nuclear waste deposition. We also found that sidewalls of the KBS-3V emplacement tunnels are vulnerable to tensile fracturing due to the combined effect of thermal stressing and backfill swelling. The study highlights a strong interaction between bentonite-based backfill and host rock through capillary suction along with induced rock desaturation. A careful design and selection of the bentonite-clay-based backfill materials for KBS-3V tunnels and deposition holes can facilitate a timely saturation and backfill swelling that in turn can minimize thermal–mechanical damage.

In the 2023 phase of the international collaborative DECOVALEX modeling project, Task E focused on understanding thermal, hydrological, and mechanical (THM) processes related to predicting brine migration in the excavation damaged zone around a heated excavation in salt. Salt is attractive as a disposal medium for radioactive waste because it is self-healing and is essentially impermeable and non-porous in the far field. Investigation of the short-term, near-field behavior is important for radioactive waste disposal because this early period strongly controls the amount of inflowing brine. Brine leads to corrosion of waste forms and waste packages, and possible dissolution of radionuclides with brine transport being a potential transport vector to the accessible environment.The Task was divided into steps. Step 0 included matching unheated brine inflow data from boreholes at the Waste Isolation Pilot Plant (WIPP) and matching temperature observations during a Brine Availability Test in Salt (BATS) heater test. Step 1 included validation of models against a thermo-poroelastic analytical solution, and two-phase flow around an excavation. Finally, Step 2 required all the individual components covered in steps 0 and 1 to come together to match observed brine inflow behavior during the same BATS heater test.There were a range of approaches from the teams, from mechanistic to prescriptive. Given the uncertainties in the problem, some teams used one- or two-dimensional models of the processes, while other teams included more geometrical complexity in three-dimensional models. Task E was a learning experience for the teams involved, and feedback from the modeling teams has led to changes in follow-on BATS experiments at WIPP. The primary Task E lessons learned were the impact of hydrologic initialization methods (wetting up vs. drying down), the difference between confined and unconfined thermal expansion, and the large changes in permeability associated with heating and cooling.

Axially loaded piles in liquefiable soils can undergo severe settlement due to an earthquake event. During shaking, the settlement is caused by the decreased shaft and tip capacity from excess pore pressures (ue) generated around the pile. Post shaking, soil settlement from the reconsolidation of liquefied soil surrounding the pile results in the development of additional load (known as drag load), causing downdrag settlement of the pile. Estimating the axial load distribution and pile settlement is essential for designing and evaluating the performance of axially loaded piles in liquefiable soils. In practice, a simplified neutral plane solution method is used, where the liquefied soils are modeled as a consolidating layer without considering the effect of ue generation/dissipation. A TzQzLiq analysis models the load and settlement response of axially loaded piles in liquefiable soils by accounting for the effect of excess pore pressure (ue) generation/dissipation on the shaft and tip capacity. This paper presents the deficiencies of the simplified neutral plane method in predicting the drag load as well as the downdrag settlement by comparing it with the TzQzLiq analysis validated with hypergravity model tests. The results show that the drag load and the downdrag settlement predicted by the neutral plane method might be over- or under-estimated depending on the pile load, the rate of ue dissipation, and the soil settlement. For the cases studied, it was found that most of the pile settlement occurs during shaking due to the decrease in the pile's tip resistance from the development of ue in the soil surrounding it. While large drag loads develop during reconsolidation, the resulting downdrag settlement is small. While the neutral plane method generally predicted a downdrag settlement comparable to that of the TzQzLiq analysis, it overpredicted drag load and could not predict co-seismic settlement. Finally, the study advocates for the development and use of a displacement-based procedure (accounting for all the mechanisms occurring during and after an earthquake event) such as based on TzQzLiq analysis in accurately evaluating the performance of the pile (i.e., the pile settlement and the maximum load), thus providing an overall safe, efficient, and optimized design.

As buried water reservoirs are increasingly being utilized to store and deliver water, they are now regarded as critical infrastructures that must continue to operate in the event of an earthquake. This paper presents the results of a large-scale numerical parametric study that was carried out to advance our understanding of the seismic fluid-structure-soil interaction (FSSI) response of buried water reservoirs. Advanced nonlinear three-dimensional (3D) FSSI numerical models of reservoirs were employed while considering reservoir size, embedment depth, soil profile, and ground motion variability. The study showed that, unlike other conventional underground structures, the peak ground acceleration (PGA) has the strongest correlation to the reservoir seismic response. Increasing the embedment depth or reservoir size was found to generally increase the demands on the structural elements while reducing the base and backfill slippage. Softer sites were found to cause an increase in the roof racking and including the vertical component of the motion increased the water dynamic pressures. Among the columns, the ones closest to the center were found to experience the highest demands and the ones at the corner the lowest. In fact, in some extreme cases, a total collapse of the reservoir was initiated by column failure due to the lack of structural redundancy. The roof in-plane shear stresses were observed to accumulate near the walls, indicating a diaphragm behavior. The reservoir's unique seismic response compared to other underground structures makes generalizing the commonly used simplified design procedures inapplicable. Instead, 3D FSSI numerical models were demonstrated to be a reliable tool for the seismic design of buried reservoirs.

This study proposes an approach of leveraging information gathered from multiple traffic data sources at different resolutions to obtain approximate inference on the traffic distribution of Chicago's O'Hare Airport area. Specifically, it proposes the ingestion of traffic datasets at different resolutions to build spatiotemporal models for predicting the distribution of traffic volume on the road network. Due to its good adaptability and flexibility for spatiotemporal data, the Gaussian process (GP) regression was employed to provide short-term forecasts using data collected by loop detectors (sensors) and supplemented by telematics data. The GP regression is used to make predictions of the distribution of the proportion of sensor data traffic volume represented by the telematics data for each location of the sensors. Consequently, the fitted GP model can be used to determine the approximate traffic distribution for a testing location outside of the training points. Policymakers in the transportation sector can find the results of this work helpful for making informed decisions relating to current and future transportation conditions in the area.

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

It was last estimated in 2016 that data centers (DCs) comprise approximately 2% of total US electricity consumption. However, this estimate is currently being updated to account for the massive increase in computing needs due to streaming, cryptocurrency, and artificial intelligence (AI). To prevent energy consumption that tracks with increasing computing needs, it is imperative we identify energy efficiency strategies and investments beyond the low-hanging fruit solutions. In a two-phased research approach, we ask: What non-technical barriers still impede energy efficiency (EE) practices and investments in the data center sector, and what can be done to overcome these barriers? In particular, we are focused on social and organizational barriers to EE. In Phase I, we performed a literature review and found that technical solutions are abundant in the literature, but fail to address the top-down cultural shifts that need to take place in order to adapt new energy efficiency strategies. In Phase II, reported here, we interviewed 16 data center operators/experts to ground-truth our literature findings. Our interview protocols focus on three aspects of DC decision-making: procurement practices, metrics and monitoring, and perceived barriers to energy efficiency. We find that vendors are the key drivers of procurement decisions, advanced efficiency metrics are facility-specific, and there is convergence in the design of advanced facilities due to the heat density of parallelized infrastructure. Our ultimate goals for our research are to design DC decarbonization policies that target organizational structure, empower individual staff, and foster a supportive external market.

Shearing of fractures and faults is important because it can result in permeability change or even induce seismicity—both are keys for efficient and safe energy recovery and storage in Earth systems. Quantitative analysis of shearing of intersecting fractures and faults is challenging because it can involve dynamic frictional contacts that are complicated by deformation of the rock matrix. To predict the shearing of intersecting fractures/faults, we attempt to answer the question of how intersections impact the shearing of a fracture network and whether we can simplify the description as compared to classical discrete fracture network (DFN) models. To answer these questions, we conducted a series of numerical simulations on scenarios for variable numbers of intersecting fractures. All these examples yield consistent results: the results of using DFNs are consistent with those of using hypothetical major paths. This leads to a new model, which we name simplified discrete fracture network model, to analyze shearing of intersecting fractures/faults using major path(s). We found that the intersections of fractures do not fundamentally change the shearing of two intersecting fractures if the intersecting angles are small. Furthermore, increasing the number of fractures/faults may relax the stress as more fractures/faults become available for shearing and distributing the stress. The simplified DFN model, which can capture efficiently the shearing behavior of each major paths from a large number of intersecting fractures/faults, will be a promising conceptual model that is complementary to existing equivalent continuum and discrete fracture models to analyze shearing of intersecting fractures/faults.

This research paper focuses on the thermo-hydro-mechanical (THM) modeling of brine migration in a heated borehole test conducted as part of the ongoing Brine Availability Test in Salt (BATS) at the Waste Isolation Pilot Plant (WIPP) in New Mexico. It is a component of the international collaboration project DECOVALEX-2023 (DEvelopment of COupled models and their VALidation against EXperiments), which aims to understand the THM processes governing brine flow in heated rock salt repositories through collaborative analysis by multiple research teams. Using the TOUGH–FLAC simulator, THM simulations were performed and compared with data from the BATS phase 1a. This experiment involved two identical horizontal-borehole arrays, one heated and one serving as a control, both equipped with sensor arrays. Analysis of measurements revealed water flow rate surges during heater power transitions, with the highest jump observed during cooling. Acoustic emission activity exhibited distinct patterns in response to heater power changes, suggesting that damage to rock salt is particularly pronounced during the cooling phase. The THM simulations successfully captured these phenomena, highlighting the significance of thermal effects, brine migration, and mechanical behavior in predicting brine availability in heated and damaged rock salt. Our modeling also revealed the critical interplay between heating and cooling-induced damage and its influence on flow properties, particularly affecting brine inflow estimation. Notably, we found that cooling-induced brine inflow spikes result from increased permeability due to tensile dilatancy. These findings have important implications for the development of robust containment strategies and enhance our understanding of the complex processes involved in repository performance.

Abstract: Coupled thermo-hydro-mechanical (THM) processes in fractured rocks have been a topic of intense scientific research for more than 30 years. The present paper takes a look into the past and highlights some scientific advances which are of an unusual “out-of-the-box” nature, and then looks forward and discusses possible directions of future research in this interesting field of study. Concerning future research directions, we see a trend from a focus on coupled THM processes in single fractures or a few interacting fractures, to the study of coupled THM behavior in complex fracture network systems where the fractures act collectively giving rise to local stress concentration points and points of large pressure gradients. Three examples of future research directions are presented. First is an effort towards identifying characterizing parameters of a fracture network that play a direct controlling role in major coupled THM phenomena (such as induced seismicity and flow channeling), rather than parameters of stochastic distributions of fractures in the network. The second example of research direction is accounting for the heterogeneity and hierarchy of fractures in a fault or fracture zone which has been associated with major THM events in a number of geo-energy projects. The third example is at the opposite end of the first; here it is recognized that in some cases, the coupled THM processes in fractured rocks may be controlled dominantly by only a few key bridges. Identification, characterization, and evaluation of these key bridges should be one of the important research directions in the coming days.

Complete representation of rainfall–runoff responses in complex, large watersheds using a single-objective parameterization approach in watershed models is often unachievable. In this study we present a calibration approach for the SWAT+ model that independently fits model parameters for different flow segments of the hydrograph. The approach is demonstrated for the Feather River, California, USA, using daily streamflow from the Lake Oroville Reservoir outlet gage. Results show that when model parameters were independently fitted for different flow segments the KGE, NSE, PBIAS, and RSR values improved to 0.96, 0.99, −3.3, and 0.10, respectively, compared to 0.72, 0.66, −9.30, and 0.53, respectively, achieved under a multiobjective and full hydrograph (average hydrograph) calibration. The results highlight that when considering the average hydrograph and flow duration curves, a more balanced representation of both poorly and well-performing segments is achieved, emphasizing the importance of segment-specific parameterization and multi-objective evaluation for accurately representing different flow conditions.

One-dimensional site response analysis (1D SRA) remains the standard practice in considering the effect of local soil deposits and predicting site-specific ground motions, although its range of applicability to realistic seismic wavefields is still in question. In this 1D approach, horizontal and vertical ground shaking are assumed to be induced by vertically propagating shear and compressional waves, respectively. A recent study based on analytical two-dimensional (2D) plane waves and simple point source earthquake simulations has shown two mechanistic limitations in this 1D modelling technique for general inclined seismic waves, that is, systematic over-prediction of the vertical motion and wave trapping in the 1D soil column. In this article, we evaluate in detail the applicability of this 1D modelling approach to realistic three-dimensional (3D) simulated seismic wavefields in shallow sedimentary basins. Linear-viscoelastic 1D SRA predictions using two types of input motions that are commonly used in practice—rock outcrop and in-column motions, are compared with the reference true site response results from 3D earthquake simulations in terms of various measures in the frequency and time domain. It is shown that the horizontal motion in the 3D seismic wavefield exhibits dominant shear wave propagation phenomenon, while the vertical motion is a combined effect of compressional and shear waves and can be over-predicted by the 1D approach when the incident seismic waves are inclined. Direct evidence of the wave refraction process that leads to the vertical motion over-prediction is provided. 1D SRA with in-column inputs can yield motions that have significantly longer duration compared to the true 3D site response solution due to trapped waves, casting in doubt the frequent need for increased soil damping in existing site studies to compensate for wave attenuation due to scattering alone. Sensitivity investigation on the increase of soil profile damping by a multiplier Dmul shows Dmul values compatible with those found in the literature for both horizontal and vertical motions. It is shown that the level of Dmul optimized for a best match of the spectral acceleration is dependent on the characteristic of the input motion and a larger Dmul is typically required for the vertical component. In contrast, 1D SRA with outcrop motions predicts motions with shorter significant duration due to its inability to capture the basin-edge generated surface waves. A suite of ground motion simulations was performed to assess the sensitivity of the observations to the basin geologic structure including the velocity gradient, rock-basin impedance contrast and basin depth. The analysis results show that the accuracy of the simplified 1D procedure is dependent on the wavefield composition of both the input motions and the true 3D site response solution. While the horizontal motions in shallow sedimentary basins can, to the first order, be reasonably captured by the simplified 1D approach, 1D SRA for the vertical component is in general not reliable and contributions from inclined shear waves should be accounted for in site-specific evaluation of the vertical design ground motion.

Terrestrial production and export of dissolved organic and inorganic carbon (DOC and DIC) to streams depends on water flow and biogeochemical processes in and beneath soils. Yet, understanding of these processes in a rapidly changing climate is limited. Using the watershed-scale reactive-transport model BioRT-HBV and stream data from a snow-dominated catchment in the Rockies, we show deeper groundwater flow averaged about 20% of annual discharge, rising to ∼35% in drier years. DOC and DIC production and export peaked during snowmelt and wet years, driven more by hydrology than temperature. DOC was primarily produced in shallow soils (1.94 ± 1.45 gC/m2/year), stored via sorption, and flushed out during snowmelt. Some DOC was recharged to and further consumed in the deeper subsurface via respiration (−0.27 ± 0.02 gC/m2/year), therefore reducing concentrations in deeper groundwater and stream DOC concentrations at low discharge. Consequently, DOC was primarily exported from the shallow zone (1.62 ± 0.96 gC/m2/year, compared to 0.12 ± 0.02 gC/m2/year from the deeper zone). DIC was produced in both zones but at higher rates in shallow soils (1.34 ± 1.00 gC/m2/year) than in the deep subsurface (0.36 ± 0.02 gC/m2/year). Deep respiration elevated DIC concentrations in the deep zone and stream DIC concentrations at low discharge. In other words, deep respiration is responsible for the commonly-observed increasing DOC concentrations (flushing) and decreasing DIC concentrations (dilution) with increasing discharge. DIC export from the shallow zone was ~66% of annual export but can drop to ∼53% in drier years. Numerical experiments suggest lower carbon production and export in a warmer, drier future, and a higher proportion from deeper flow and respiration processes. These results underscore the often-overlooked but growing importance of deeper processes in a warming climate.

In this study, laboratory loose mix oven aging was compared to field aging to begin calibration for a medium-term oven aging (MTOA) protocol. Five different oven aging temperatures were implemented at different durations to evaluate the change in chemical and rheological aging parameters for four plant-produced asphalt concrete (AC) mixes. The sulfoxide (SUL) index failed to show a consistent trend with aging for extracted binders obtained from both loose mixes and field slabs. The carbonyl area (CA) index was found to show a linear trend with the binders’ rheological parameters. The results of the field calibration indicate that loose mix oven aging of 20 h at 100 °C can simulate field aging at 0.5–0.6 in. (12 mm to 15 mm) depth after six years of pavement life in the climate region and for the material tested. Based on these results for a hot climate, loose mix aging of 20 h at 100 °C was proposed as the MTOA protocol for AC mixes for future studies.

Geochemically driven alterations of fractures in multi-mineral media can create altered layers (ALs) at the fracture-matrix interface. Spatial variations in the AL significantly influence mass transfer across the interface, and the hydraulic and mechanical properties of the fractured medium. A real-rock based microfluidic experiment reported spatial variations in AL thickness despite the initially smooth fracture surface, suggesting potential effects of matrix heterogeneity on AL development. However, the respective contribution of structural and mineralogical characteristics is still poorly understood. Using the microfluidic experimental data and a micro-continuum reactive transport model, we systematically evaluated how micro-porosity and initial mineral texture impact AL development and thus the overall reactive transport behaviors. Our simulation results confirmed that the extent of AL spatial variations, mainly controlled by mineralogical texture, influences the evolution of reaction and permeability in different ways. Accounting for spatial heterogeneity in mineral distribution produces “channeling” structures in ALs and lower overall reaction (by up to 35.6%), but larger permeability increase (by up to 9.8%). The characteristic length of the reactive mineral cluster was observed to dominate the internal texture of ALs. Whereas the presence of micro-porosity can enhance mineral accessibility via improving connectivity for flow and transport, and lead to both higher bulk reaction, that is, thicker ALs, and permeability enhancement. Considerations of surface roughness with characteristic length on the same order of magnitude as mineral texture did not change the overall development of AL, which further highlights the importance of accounting for rock matrix properties in predicting long-term evolution of fractured media. The resulting spatial variations of ALs and their impacts on bulk properties, however, are expected to be further complicated by the coupling of chemical and mechanical processes, and may trigger matrix disaggregation, erosion and other mechanisms of fractured media alteration.

We present a new pore-scale model for multicomponent advective-diffusive transport with coupled mineral dissolution and precipitation. Both dissolution and precipitation are captured simultaneously by introducing a phase transformation vector field representing the direction and magnitude of the overall phase change. An effective viscosity model is adopted in simulating fluid flow during mineral dissolution-precipitation that can accurately capture the velocity field without introducing any empirical parameters. The proposed approach is validated against analytical solutions and interface tracking simulations in simplified structures. After validation, the proposed approach is employed in modeling realistic rocks where mineral dissolution and precipitation are dominant at different locations. We have identified three regimes for mineral dissolution-precipitation coupling: (a) compact dissolution-precipitation where dissolution is dominant near the inlet and precipitation is dominant near the outlet, (b) wormhole dissolution with clustered precipitation where dissolution generates wormholes in the main flow paths and precipitation clogs the secondary flow paths, and (c) dissolution dominant where all solid grains are gradually dissolved. In the three regimes, the proposed approach provides reliable porosity-permeability relationships that cannot be described well by traditional macroscale models. We find that the permeability can increase while the overall porosity decreases when the main flow paths are expanded by dissolution and adjacent pore spaces are clogged by precipitation.

To ensure the safety of geological disposal of high-level radioactive waste, in-situ experiments have been carried out to examine the behavior of rocks in underground research laboratories (URLs). At the Meuse/Haute-Marne URL in France, the French National Radioactive Waste Management Agency (Andra) has been assessing the Callovo-Oxfordian claystone (COx) as potential host rock of geological disposal by subjecting the COx to in-situ heating mimicking exothermic radioactive waste. Results of the in-situ experiments are used to validate and bolster the numerical simulators for predicting the thermo-hydromechanically (THM) coupled behavior of the COx. The numerical simulators are, however, yet to be tested for predicting the failure and fracture development of the COx during heating, which is of paramount importance to the safety of the geological disposal. In this research, we modelled a recently carried out in-situ experiment at the Meuse/Haute-Marne URL using the TOUGH-FLAC simulator to predict the failure and fracture development of the COx during heating. The objectives are to examine the effects of (i) the weak bedding planes, (ii) the softening rate of matrix/weak plane strengths, and (iii) the stiffness anisotropy of the COx on the development of shear and tensile fractures during heating. Results show that considering failure along the weak planes enabled accurate predictions of fracture development. Also, fracture development intensified at a softening rate beyond a threshold level and the geometry of fractures was significantly affected by the stiffness anisotropy. These results will help boost the reliability of the safety and performance assessment of geological disposal in claystone.

Control applications that facilitate Demand Flexibility (DF) are difficult to deploy at scale in existing buildings. The heterogeneity of systems and non-standard naming conventions for metadata describing data points in building automation systems often lead to ad-hoc and building-specific applications. In recent years, several researchers investigated semantic models to describe the meaning of building data. They suggest that these models can enhance the deployment of building applications, enabling data exchanges among heterogeneous sources and their portability across different buildings. However, the studies in question fail to explore these capabilities in the context of controls. This paper proposes a novel semantics-driven framework for developing and deploying portable DF control applications. The design of the framework leverages an iterative design science research methodology, evolving from evidence gathered through simulation and field demonstrations. The framework aims to decouple control applications from specific buildings and control platforms, enabling these control applications to be configured semi-automatically. This allows application developers and researchers to streamline the onboarding of new applications that could otherwise be time-consuming and resource-intensive. The framework has been validated for its capability to facilitate the deployment of control applications sharing the same codebase across diverse virtual and real buildings. The demonstration successfully tested two controls for load shifting and shedding in four virtual buildings using the Building Optimization Testing Framework (BOPTEST) and in one real building using the control platform VOLTTRON. Insights into the current limitations, benefits, and challenges of generalizable controls and semantic models are derived from the deployment efforts and outcomes to guide future research in this field.

When renewing building facades in most Chinese cities, covers are often designed and installed to conceal the outdoor units of residential split air conditioners for congruousness of building facades. However, how those covers impact airflow and energy efficiency should be thoroughly examined. This study investigates two popular designs of cover (louver and circular-hole) and selects Nanjing, renowned for its hot summers, as the case city. This study employs Computational Fluid Dynamics models to simulate airflow obstruction caused by the covers surrounding the outdoor units. Grey Model, trained from the CFD results, quantifies interactions between design of cover and inlet air temperature. Additionally, a thermodynamic model assesses the covers' impact on the coefficient of performance of air conditioners. The findings reveal that the primary cause of outdoor unit overheating is warm air backflow from the outlet to the inlet. A mere 1 °C increase in inlet air temperature can reduce COP by 4.1%–8.7%. The maximum temperature differences caused by different designs of cover are 4.5 °C for the louver type and 4.4 °C for the circular-hole type. To mitigate these negative impacts, optimal design recommendations are provided: a minimum distance between the cover and outdoor unit of 0.29 m for louver type and 0.1 m for circular-hole type, both feasible in most installations. These findings can help designers, manufacturers, installers and policymakers, to facilitate the design and installation of optimal covers for outdoor air-conditioning units, thus minimizing energy efficiency losses.

Abstract: This paper focuses on the impact of elevated temperatures on the adsorptive and capillarity water retention mechanisms of unsaturated soils under constrained (constant volume) conditions. This topic is critical for simulating the thermo-hydraulic behavior of soils in hydrogeological or geotechnical applications, including climate change effects on near surface soils, energy piles or soil borehole thermal energy storage systems in unsaturated soil layers, and buffers for geological nuclear waste repositories. A nonisothermal soil water retention curve (SWRC) that separately considers the temperature-dependency of the key parameters governing adsorptive and capillarity water retention mechanisms and soil physical parameters (e.g., surface tension, contact angle, adsorption capacity, cation exchange capacity, mean cavitation suction, air entry value and equilibrium film thickness) was developed to provide insights into the impact of temperature on water retention over the full suction range. The nonisothermal SWRC was validated using experimental data on high plasticity clays, with a good prediction of temperature effects on adsorption and capillarity water retention mechanisms in constrained unsaturated soils.

With the growth of attention to equity in transportation, there is a need to understand differing definitions of transportation equity and what constitutes impactful equity work. This report examines definitions and assesses equity work within transportation in California. We do this by analyzing the expert perspectives of 28 transportation professionals who also identify as Black or people of color. Interviews were transcribed and coded for major themes. Results indicated that there is tension around what constitutes meaningful transportation equity work. Key findings centered around a distinction between “performative” equity work and “authentic” equity work. Performative equity work privileges the comfort and perspective of dominant groups, reinforces the status quo, stays in the realm of the rhetoric, and often results in superficial changes only. Authentic equity work centers the experience of Black people and people of color, embraces discomfort, transforms dominant culture, and results in measurable changes to the lives of those historically oppressed. Key recommendations include supporting action-oriented equity work, especially around resource allocation and redistribution of decision-making power to communities. The paper includes visions for more equitable transportation futures.

Deep Reinforcement Learning (DRL)-based control shows enhanced performance in the management of integrated energy systems when compared with Rule-Based Controllers (RBCs), but it still lacks scalability and generalisation due to the necessity of using tailored models for the training process. Transfer Learning (TL) is a potential solution to address this limitation. However, existing TL applications in building control have been mostly tested among buildings with similar features, not addressing the need to scale up advanced control in real-world scenarios with diverse energy systems. This paper assesses the performance of an online heterogeneous TL strategy, comparing it with RBC and offline and online DRL controllers in a simulation setup using EnergyPlus and Python. The study tests the transfer in both transductive and inductive settings of a DRL policy designed to manage a chiller coupled with a Thermal Energy Storage (TES). The control policy is pre-trained on a source building and transferred to various target buildings characterised by an integrated energy system including photovoltaic and battery energy storage systems, different building envelope features, occupancy schedule and boundary conditions (e.g., weather and price signal). The TL approach incorporates model slicing, imitation learning and fine-tuning to handle diverse state spaces and reward functions between source and target buildings. Results show that the proposed methodology leads to a reduction of 10% in electricity cost and between 10% and 40% in the mean value of the daily average temperature violation rate compared to RBC and online DRL controllers. Moreover, online TL maximises self-sufficiency and self-consumption by 9% and 11% with respect to RBC. Conversely, online TL achieves worse performance compared to offline DRL in either transductive or inductive settings. However, offline Deep Reinforcement Learning (DRL) agents should be trained at least for 15 episodes to reach the same level of performance as the online TL. Therefore, the proposed online TL methodology is effective, completely model-free and it can be directly implemented in real buildings with satisfying performance.

Heat waves are increasing in severity, duration, and frequency. The Multi-Scenario Extreme Weather Simulator (MEWS) models this using historical data, climate model outputs, and heat wave multipliers. In this study, MEWS is applied for planning of a community resilience hub in Hau’ula, Hawaii. The hub will have normal operations and resilience operations modes. Both these modes were modeled using EnergyPlus. The resilience operations mode includes cutting off air conditioning for many spaces to decrease power requirements during emergencies. Results were simulated for 300 future weather files generated by MEWS for 2020, 2040, 2060, and 2080. Shared socioeconomic pathways 2–4.5, 3–7.0 and 5–8.5 were used. The resilience operations mode results show two to six times increase of hours of exceedance beyond 32.2 °C from present conditions, depending on climate scenario and future year. The resulting decrease in thermal resilience enables an average decrease of energy use intensity of 26% with little sensitivity to climate change. The decreased thermal resilience predicted in the future is undesirable, but was not severe enough to require a more energy-intensive resilience mode. Instead, planning is needed to assure vulnerable individuals are given prioritized access to air-conditioned parts of the hub if worst-case heat waves occur.

This article presents a comparative simulation-based control logic design process. It uses the Control Description Language (CDL) and the ASHRAE Guideline 36 high-performing building control sequences with the Modelica Buildings Library (MBL) to demonstrate a comparative analysis of two control designs for a data center chilled water plant. Details include a description of the closed-loop plant and control design methodology, including sizing and parameterization, base and alternative (Guideline 36) control logic with software implementation structure, and outline of the simulation experimentation process. The selected control designs are paired with comparable chilled water plant configurations. The models include a chiller, a water-side economizer, and an evaporative cooling tower. The plant provides cooling at 27ºC zone supply air temperature to a data center in Sacramento, CA. The comparative simulation results examined the impacts of a selected control logic detail, and present an example model-based design application. Overall, the simulation results showed a 25% annual and a 18% summer energy use reduction for alternative controls. This shows that simulation-based control logic design performance evaluation can improve energy efficiency and resilience aspects of system controls at large.

Earthquakes present worldwide risk to economic and human safety. The 2023 earthquakes in Turkiye provided a reminder of the potential for catastrophic consequences with 50,700 deaths and 15.7 million people affected. The ability to predict ground motions and infrastructure damage for earthquakes continues to be a challenging problem for scientists and engineers. Until now, estimates of ground motions have been performed empirically by looking at sparse data from past earthquakes. This approach can provide statistical information on intensity amplitudes but cannot inform site-specific ground motions essential to developing the most effective resilience. Interest has grown in large-scale computational models to simulate earthquakes at regional scale. The U.S. Department of Energy EarthQuake SIMulation (EQSIM) framework was developed for regional-scale earthquake simulations at unprecedented fidelity, taking advantage of emerging GPU-accelerated systems. This article describes the EQSIM workflow and demonstrates regional-scale simulations with the new computational capability available to scientists in their quest to mitigate future disasters.

In this study we construct and compare three different deep learning (DL) models for estimating daily snow water equivalent (SWE) from high-resolution gridded meteorological fields over the Rocky Mountain region. To train the DL models, Snow Telemetry (SNOTEL) station-based SWE observations are used as the prediction target. All DL models produce higher median Nash-Sutcliffe Efficiency (NSE) values than a conceptual SWE model and interpolated gridded data sets, although mean squared errors also tend to be higher. Sensitivity of the SWE prediction to the model's input variables is analyzed using an explainable artificial intelligence (XAI) method, yielding insight into the physical relationships learned by the models. This method reveals the dominant role precipitation and temperature play in snowpack dynamics. In applying our models to estimate SWE throughout the Rocky Mountains, an extrapolation problem arises since the statistical properties of SWE (e.g., annual maximum) and geographical properties of individual grid points (e.g., elevation) differ from the training data. This problem is solved by normalizing the SWE with its historical maximum value to alleviate extrapolation for all tested DL models. Our work shows that the DL models are promising tools for estimating SWE, and sufficiently capture relevant physical relationships to make them useful for spatial and temporal extrapolation of SWE values.

We combine X-ray-specific tracer particles, a photon counting detector, and a liquid metal jet anode X-ray source to achieve O(1 kHz) X-ray imaging speeds in the laboratory, 15× faster than previous comparable studies with O(50 μm) tracers. To examine the limits of this measurement technique we conduct three experiments: 2D and 3D X-ray particle velocimetry (XPV) of Poiseuille pipe flow, 3D XPV of flow around a Taylor bubble, and 3D scalar mixing with a laminar jet. These experiments demonstrate the performance improvement achievable by combining the aforementioned elements, the applicability to multiphase flows and deforming systems, and the potential to capture scalar and vector quantities simultaneously. Most importantly, these experiments are conducted with a laboratory-scale system, showing that in-lab X-ray particle velocimetry techniques are now becoming usable for a wider range of flows of interest. Furthermore, the design of XPV experiments is discussed to clarify the trade offs between achievable imaging speed, domain size and spatiotemporal resolution.

Building energy simulations often rely on abstract assumptions when it comes to natural ventilation, such as ‘windows always open [or closed]’ or ‘windows open when outdoor temperature is below a certain threshold.’ However, simulations based on these assumptions fail to fully exploit the cooling potential of natural ventilation, as its effectiveness can be enhanced or diminished by various factors, including the presence of thermal mass. This issue also extends to smart home controls, where determining the window schedule becomes challenging without information about the building's response to outdoor conditions. To address these issues, this study has developed an analytical model for window operation schedules that leverages the passive cooling from natural ventilation. The analytical model was validated against a Modelica simulation. A case study utilizing the BESTEST model of ANSI/ASHRAE Standard 140 underwent validation with EnergyPlus simulations, showing strong concordance. The algorithm provides window schedule recommendations adapted to various airflow rates, thermal masses, and climate variations. The case study demonstrated that proper window scheduling could reduce indoor temperature by up to 8 °C under the given simulation settings, thereby improving resilience and indicating potential energy savings. Furthermore, the paper explores the potential opportunities and challenges this approach presents, especially for building simulation and smart home applications.

Irrigation is the most significant consumer of freshwater worldwide. Deciding on the right amount of irrigation is crucial for sustainable water management and food production. The Penman-Monteith (P-M) reference crop evapotranspiration (ETO) is the gold standard in irrigation management and scheduling; however, its calculation requires measurements from multiple sensors over an extended reference grass surface. The cost of land, sensors, maintenance, and water to keep the grass surface green impedes having a dense network of ETO stations. To solve this challenge, this research aims to develop an input-limited ETO estimation approach based on historical weather data and machine learning (ML) algorithms to relax the need for a reference grass surface. This approach, called “SolarET,” takes solar radiation (RS) data as its sole input. RS is the only meteorological driving factor of ETO that does not rely on the measuring surface. To test the generalizability of SolarET, we test its performance over unseen arbitrary locations across California. California is chosen as the case study since it is one of the world's most hydrologically altered and agriculturally productive regions. In total, 19,088,736 hourly data samples from 131 automated weather stations have been used in this study. The ML models have been trained over 114 stations and tested over 17 unseen stations, each representing a California climatic zone. Our findings point to the superiority of decision tree-based algorithms versus neural networks. SolarET works best in irrigation-oriented regions of California (e.g., Central Valley) and is less accurate in coastal and desert zones. Our results demonstrate the higher accuracy of SolarET using hourly (RMSE = 0.93 mm/day) and daily (RMSE = 0.97 mm/day) RS data in comparison to well-known empirical alternatives like Priestley-Taylor (PT) (RMSE = 1.35 mm/day) and Hargreaves-Samani (HS) (RMSE = 2.69 mm/day).

Solifluction processes in the Arctic are highly complex, introducing uncertainties in estimating current and future soil carbon storage and fluxes, and assessment of hillslope and infrastructure stability. This study aims to enhance our understanding of triggers and drivers of soil movement of permafrost-affected hillslopes in the Arctic. To achieve this, we established an extensive soil deformation and temperature sensor network, covering 48 locations across multiple hillslopes within a 1 km2 watershed on the Seward Peninsula, AK. We report depth-resolved measurements down to 1.8 m depth for May to September 2022, a period conducive to soil movement due to deepening thaw layers and frequent rain events. Over this period, surface movements of up to 334 mm were recorded. In general, these movements occur close to the thawing front, and are initiated as thawing reaches depths of 0.4-0.75 m. The largest movements were observed at the top of the south-east facing slope, where soil temperatures are cold (mean annual soil temperatures averaging −1.13 °C) and slopes are steeper than 15°. Our analysis highlights three primary factors influencing movements: slope angle, soil thermal conditions, and thaw depth. The latter two significantly impact the generation of pore water pressures at the thaw-freeze interface. Specifically, soil thermal conditions govern the liquid water content, while thaw depth influences both the height of the water column and, consequently, the pressure at the thawing front. These factors affect soil properties, such as cohesion and internal friction angle, which are crucial determinants of slope stability. This underscores the significance of a precise understanding of subsurface thermal conditions, including spatial and temporal variability in soil temperature and thaw depth, when assessing and predicting slope instabilities. Based on our observations, we developed a factor of safety proxy that consistently falls below the triggering threshold for all probes exhibiting displacements exceeding 50 mm. This study offers novel insights into patterns and triggers of hillslope movements in the Arctic and provides a venue to evaluate their impact on soil redistribution.

We present a study directly measuring the electron‐beam‐induced plasticity of amorphous Al2O3 coatings. Core–shell nanostructures are employed as small‐scale model systems for two‐dimensional coatings made by atomic layer deposition (ALD). Copper nanowires (NWs) are used as substrates for ALD deposition, representing a model system for interconnects commonly found in integrated circuits. Experiments are performed in situ in a transmission electron microscope (TEM) and further analyzed with electron energy loss spectroscopy (EELS). Our in situ TEM tensile experiments reveal the highly plastic behavior of the ALD shell, which withstands a maximum strain of 188%. Comparable samples under beam‐off conditions show a brittle fracture, which underlines the effect of electron irradiation. The electron‐beam‐activated bond switching within the amorphous network enables compensation of the applied tensile strain, leading to viscous flow. By incorporating an intermediate nanocrystalline layer within the Al2O3 shell, the plasticity is suppressed and brittle fracture occurs. This work directly demonstrates the tuning of mechanical properties in amorphous ALD structures through electron irradiation.

Existing simplified procedures for evaluating soil liquefaction potential or for estimating excess pore pressures during earthquakes are typically based on undrained cyclic tests performed on saturated soil samples under controlled loading and boundary conditions. Under such conditions, the effect of excess pore pressure (ue) dissipation and redistribution to neighboring soil layers cannot be accounted for. Existing simplified procedures treat liquefiable layers as isolated soil layers without any boundary conditions even if dense and loose layers are very thin, permeable, and adjacent to each other. However, redistribution is likely to increase and decrease ue in the neighboring dense and loose layers respectively. Until now, no procedure short of fully coupled numerical analysis is available to estimate the importance of redistribution. This paper presents an approximate analytical procedure for assessing the effects of ue redistribution in (1) soil layers that would have liquefied if they were undrained, and (2) soil layers that would have not liquefied even if undrained. It is found that a layer that is initially assumed liquefied under undrained conditions might not even liquefy accounting for the ue redistribution to neighboring layers. On the other hand, a layer initially assumed to not liquefy can develop significant ue and can even liquefy due to pore pressure migration from the neighboring layers. Thus, accounting for redistributed ue is important for liquefaction consequence assessment quantification, particularly in systems that span the depth of these effects like deep foundations. Migration of u toward the tip of a pile can reduce its capacity, even if the tip is embedded in a dense sand layer. On the other hand, if redistribution can result in the reduction of ue in initially assumed liquefied layers, risks associated with liquefaction might be avoided. A criterion is also developed to evaluate the thicknesses of a layer below which redistribution could prevent liquefaction even if the layer is deemed liquefied according to the existing liquefaction-triggering procedures. Finally, the proposed procedure is illustrated by application to selected shaking events of centrifuge tests involving liquefaction of layered soil profiles. The predictions from the procedure matched the centrifuge test results reasonably.

Abstract: Climate change and the increase of population pose challenges to ensuring suitable water supply in water-scarce regions. This work presents a comparative analysis of the water-supply approaches adopted in Los Angeles, Southeastern Spain, and Sydney. Results show a decrease in per-capita water use in the period 2000–2020, which reflects an improvement in water conservation. Social factors in the domain of hydropolitics and economic efficiency explain the divergence of water policies adopted. The adaptation to water scarcity and growing population in three regions of developed countries located in different continents sheds light on challenges facing the achievement of water security worldwide.