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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

COVID-19 pandemic ramifications on residential Smart homes energy use load profiles

The COVID-19 pandemic has significantly affected people’s behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre– and post–COVID-19 pandemic times. The weekend usage patterns look similar pre– and post–COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗
DOE OSTI2023

Intensive and extensive margins of the peak load: Measuring adaptation with mixed frequency panel data

In this work we investigate the response of daily electricity peak load to daily maximum temperatures across states in Europe and India. We propose a method that decomposes short- from medium/long-run effects, retains the high frequency nature of the load-weather covariation and treats economic growth as a modulating factor. By simultaneously exploiting variation in unexpected daily weather anomalies and decade-long climatic changes in each location we decompose transitory - intensive margin - adjustments from permanent - extensive margin - adjustments. We find that the shocks over the long-run differ substantially from the short-run dynamics. Furthermore, we find evidence that per capita income modulates the adjustments over the short- and long-run. We project that in response to climate change around 2050 the peak load may increase by up to 20%-30% in Southern Europe and in several states in India, depending on the degree of warming and the evolution of socio-economic conditions. Even with a limited scope to two world regions, we identify that the structure of the economy and differences in future income growth matter in shaping the adaptation to climate change. Our decomposition allows to identify how future weather anomalies can further amplify the relative increase associated to the shift in the climate norm. Assuming that the interannual variability of maximum temperatures follows the distribution observed in the past, we find a doubling of the impacts of climate change during the summer in Europe. Uncertainty around the distribution of future weather anomalies may lead to further unexpected peak load amplifications. Our results have important policy implications for power systems’ generation capacity, transmission and storage, as we show that the challenges to accommodate the peak load in days with extreme temperatures may substantially increase already around mid-century.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Mechanical response of lithium fluoride under off-principal dynamic shock-ramp loading

Single crystal lithium fluoride (LiF), oriented [100], was shock loaded and subsequently shocklessly compressed in two experiments at the Z Machine. We employed velocimetry measurements in order to obtain an impactor velocity, shock transit times, and in-situ particle velocities for LiF samples up to ~1.8 mm thick. We also performed a dual thickness Lagrangian analysis on the in-situ velocimetry data to obtain the mechanical response along the loading path of these experiments. Finally, we observed an elastic response on one experiment during initial shockless compression from 100 GPa before yielding. The relatively large thickness differences utilized for the dual sample analyses (up to ~1.8 mm) combined with a relative timing accuracy of ~0.2 ns resulted in an uncertainty of less than 1% on density and stress at ~200 GPa peak loading on one experiment and <4% on peak loading at ~330 GPa for another. The stress-density analyses from these experiments compare favorably with recent equation of state models for LiF.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Aggregate modeling of fast-acting demand response and control under real-time pricing

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop a more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.

Aggregate Modeling↗
DOE OSTI2018

Aggregate Load Controllers and Associated Methods

Aggregate load controllers and associated methods are described. According to one aspect, a method of operating an aggregate load controller includes using an aggregate load controller having an initial state, applying a stimulus to a plurality of thermostatic controllers which are configured to control a plurality of respective thermostatic loads which receive electrical energy from an electrical utility to operate in a plurality of different operational modes, accessing data regarding a response of the thermostatic loads as a result of the applied stimulus, using the data regarding the response, determining a value of at least one design parameter of the aggregate load controller, and using the determined value of the at least one design parameter, configuring the aggregate load controller to control amounts of the electrical energy which are utilized by the thermostatic loads.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

U-net architected deep material network training with microstructure local field information

The Deep Material Network (DMN) has recently emerged as a powerful reduced-order modeling framework for simulating the mechanical response of heterogeneous materials such as composites. Unlike most data-driven approaches that directly learn a material’s response under prescribed loading, the DMN acts as a homogenization operator, learning the kinematic constraints and mechanical interactions of the underlying microstructure. However, traditional DMN training relies exclusively on homogenized effective properties derived from Direct Numerical Simulations (DNS), discarding the rich local field data that govern microstructural interactions. In this work, we extend the DMN framework to incorporate such local field information into the offline training process. Utilizing a U-Net architecture, we augment the DMN training objective to include the first and second statistical moments of the local stress fields obtained from linear DNS. This ensures that the learned network topology not only fits the effective stiffness but also accurately reflects the internal local stress and strain partitioning of the microstructure. The results confirm that supervising the localization process during training yields a superior surrogate model, reducing local prediction errors by an order of magnitude and significantly improving generalization to unseen nonlinear constitutive behaviors compared to traditional DMNs.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Small Fatigue Crack Growth Mechanisms and Interfacial Stability in Cold-Spray 6061 Aluminum Alloys and Coatings

Cold-spray-processed aluminum alloys have static mechanical properties superior to those of aerospace cast alloys, and similar to those of their wrought counterparts, making them good candidates for structural applications. However, their broad and confident use relies upon systematic fatigue crack growth studies to investigate and demonstrate the materials' performance in critical high-integrity components. In this work, the fatigue crack growth behavior in early stages (small crack growth regime) was investigated for cold-spray processed 6061 aluminum alloys and coatings, at stress ratio R = 0.1, in room temperature laboratory air. The effects of the characteristic microstructure and initial flaw size on the fatigue crack growth response were systematically examined, and the crack growth mechanisms at the microstructural scale were established and compared to those of long cracks. The mechanical interfacial stability of coatings was examined in cold-spray 6061-rolled 6061-T6 couples. An original method of quantifying the deposition-substrate interfacial strength, and correlating it to the response under cyclic loading via crack-interface stability maps, was developed. The proposed methodology is based on combined scratch testing and fracture mechanics formulations, and failure at the coating-substrate interface can be predicted for any crack growth scenario under cyclic loading. The method can be broadly used for the design and optimization of cold-spray and other coatings, as well as in structural repair.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of Boron Addition on Creep Strain during Impression Creep of P91 Steel

In an attempt to understand the effect of boron addition on creep deformation behavior under high stress and high temperature in martensitic P91 steel, impression creep tests were carried out on boron-free P91 (P91) and boron-added P91 (P91B) steels. The experimental program consisted of three steps, i.e., characterization of as-received steels by microhardness, optical microscopy (OM), transmission electron microscopy (TEM), electron backscattered diffraction (EBSD) and wavelength-dispersive spectroscopy (WDS); impression creep tests at 445 MPa and 625 °C on as-received steels; characterization at deformed plastic zones of impression-crept specimens by microhardness, OM, EBSD, TEM and WDS. Impression creep tests were run till a depth of penetration of 1.8 mm was achieved for both cases which ensured a sufficient plastic zone underneath indenter for subsequent microstructural investigations. Coarsening of M{sub 23}C{sub 6} carbides was observed in P91 steel during high-temperature creep loading, which leads to extensive strain hardening in deformed plastic region, resulting in impaired creep performance. On the contrary, dynamic recrystallization in P91B steel results in formation of small strain-free grains during creep loading which are responsible for increased resistance of the material to shear stresses during an impression creep test.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Direct shear strength of rebar-coupler anchor systems for steel-plate composite (SC) walls

This work focuses on the direct shear behavior of rebar-coupler anchor systems, and their use for anchorage of steel-plate composite (SC) walls to the concrete basemat of safety-related nuclear facilities. Large-scale rebar-coupler anchor specimens were tested under direct shear loading until failure. The results included the applied load-slip displacement responses of the specimens, the direct shear strength, and the observed failure mode. The American Concrete Institute (ACI) 349 code equation for calculating the direct shear strength of embedded anchors was compared with the direct shear strengths from the tests. The code equation underestimated the direct shear strength of the anchor system, because it was based on the assumption that shear failure occurs in the rebars, whereas experimental observations indicated that shear fracture failure occurred in the coupler rather than the rebars. The design equation was updated to utilize the net shear area of the coupler instead of the rebars, after which the direct shear strengths from the tests could be calculated with reasonable accuracy. The experimental results were also used to propose an empirical model for the shear force-slip displacement response of rebar-coupler anchor systems.

42 ENGINEERING↗
DOE OSTI2019

A Hierarchical Charging Control of Plug-in Electric Vehicles with Simple Flexibility Model

The demand for plug-in electric vehicles (PEVs) is increasing exponentially, which could have significant effects on the power grid, because charging one PEV is nearly equivalent to adding three houses to the power system. Even though PEVs increase demand on the electric grid, their capability to actively interact with the grid presents excellent opportunities for load management, demand response, and various other grid services. This paper proposes an innovative scheduling and control framework to enable smart PEV charging for grid services while meeting PEV owners’ travel needs. In the proposed framework, each set of electric vehicle supply equipment (EVSE) is equipped with a controller that estimates charging power and energy flexibility based on vehicle characteristics, EVSE power rating, battery energy state, and upcoming trip information. With the charging flexibility model received from each EVSE controller, the central coordinator determines the optimal power allocation for a look-ahead time window for the given grid services. The proposed charging coordination strategy can help reduce the computational complexity and communication requirement compared with existing methods. It is also scalable to the expanding PEV fleet and robust to uncertainties in upcoming vehicle trips and future system condition. The proposed method is studied using a prototypical feeder developed at Pacific Northwest National Laboratory and detailed trip information extracted from the National Household Travel Survey.

Wu, Di↗
DOE OSTI2020

A novel shallow bore ground heat exchanger for ground source heat pump applications—Model development and validation

A novel ground heat exchanger design, the Underground Thermal Battery (UTB), was proposed as a low-cost alternative to the conventional vertical bore ground heat exchanger (VBGHE) for the application of ground source heat pumps (GSHPs). The UTB is designed to be installed in a shallow borehole (less than 6 m deep) and thus could cost much less than the conventional VBGHE, which usually is installed in vertical bores 60 m deep. By utilizing natural convection of water and phase change materials, the UTB tempers its temperature change in response to thermal loads, which helps improve the efficiency of GSHPs. A one-dimensional (1D) model of the UTB has been developed and validated with the measured performance data of a small-scale UTB, as well as the simulation results of a more detailed three dimensional (3D) numerical model, which accounts for both heat transfer and fluid dynamics in the UTB. Further, this 1D model is computationally much more efficient than the 3D model and thus can simulate the annual performance of the UTB with acceptable computation time. The 1D model has been used to evaluate the performance of the UTB so that it can be compared with the conventional VBGHE.

42 ENGINEERING↗
DOE OSTI2015

Effect of proteoglycans at interfaces as related to location, architecture, and mechanical cues

Covalently bound functional GAGs orchestrate tissue mechanics through time-dependent characteristics. The role of specific glycosaminoglycans (GAGs) at the ligament-cementum and cementum-dentin interfaces within a human periodontal complex were examined. Matrix swelling and resistance to compression under health and modeled diseased states was investigated. The presence of keratin sulfate (KS) and chondroitin sulfate (CS) GAGs at the ligament-cementum and cementum-dentin interfaces in human molars (N = 5) was illustrated by using enzymes, atomic force microscopy (AFM), and AFM-based nanoindentation. Furthermore, the change in physical characteristics of modeled diseased states through sequential digestion of keratin sulfate (KS) and chondroitin sulfate (CS) GAGs was investigated. One-way ANOVA tests with P < 0.05 were performed to determine significant differences between groups. Additionally, the presence of mineral within the seemingly hygroscopic interfaces was investigated using transmission electron microscopy. Immunohistochemistry (N = 3) indicated presence of biglycan and fibromodulin small leucine rich proteoglycans at the interfaces. Digestion of matrices with enzymes confirmed the presence of KS and CS GAGs at the interfaces by illustrating a change in ti ssue architecture and mechanics. A significant increase in height (nm), decrease in elastic modulus (GPa), and tissue deformation rate (nm/s) of the PDL-C attachment site (215 ± 63-424 ± 94 nm; 1.5 ± 0.7-0.4 ± 0.2 GPa; 21 ± 7-48 ± 22 nm/s), and cementum-dentin interface (122 ± 69-360 ± 159 nm; 2.9 ± 1.3-0.7 ± 0.3 GPa; 18 ± 4-30 ± 6 nm/s) was observed. The sequential removal of GAGs indicated loss in intricate structural hierarchy of hygroscopic interfaces. From a mechanics perspective, GAGs provide tissue recovery/resilience. Our results provide insights into the role of GAGs toward conserved tooth movement in the socket in response to mechanical loads, and modulation of potentially deleterious strain at tissue interfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Solution structure analysis of the periplasmic region of bacterial flagellar motor stators by small angle X-ray scattering

Highlights: • Solution shape of peptidoglycan binding domains from the flagellar motor determined. • Previously unobserved conformational states are revealed. • Suggests a potential structural rearrangement associated with stator activation. • Provides mechanistic insight into how flagellar motor stators are activated. The bacterial flagellar motor drives the rotation of helical flagellar filaments to propel bacteria through viscous media. It consists of a dynamic population of mechanosensitive stators that are embedded in the inner membrane and activate in response to external load. This entails assembly around the rotor, anchoring to the peptidoglycan layer to counteract torque from the rotor and opening of a cation channel to facilitate an influx of cations, which is converted into mechanical rotation. Stator complexes are comprised of four copies of an integral membrane A subunit and two copies of a B subunit. Each B subunit includes a C-terminal OmpA-like peptidoglycan-binding (PGB) domain. This is thought to be linked to a single N-terminal transmembrane helix by a long unstructured peptide, which allows the PGB domain to bind to the peptidoglycan layer during stator anchoring. The high-resolution crystal structures of flagellar motor PGB domains from Salmonella enterica (MotB{sub C2}) and Vibrio alginolyticus (PomB{sub C5}) have previously been elucidated. Here, we use small-angle X-ray scattering (SAXS). We show that unlike MotB{sub C2}, the dimeric conformation of the PomB{sub C5} in solution differs to its crystal structure, and explore the functional relevance by characterising gain-of-function mutants as well as wild-type constructs of various lengths. These provide new insight into the conformational diversity of flagellar motor PGB domains and experimental verification of their overall topology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Influence of the micro- and nanoscale local mechanical properties of the interfacial transition zone on impact behavior of concrete made with different aggregates

The influence of the microscale local mechanical properties of the interfacial transition zone (ITZ) on macro-level mechanical response and impact behavior is studied for concretes made with copper slag and gravel aggregates. 3D nanotech vertical scanning interferometry, scanning electron microscopy coupled with energy dispersive X-ray micro-analysis, digital image analysis, and 3D X-ray computed tomography were used to characterize the microstructures and the ITZs. It was deduced that a stronger and denser ITZ in the copper slag specimen would reduce its vulnerability to stiffness loss and contribute to its elastic and more ductile response under impact loading. The analysis also indicated that a significant degeneration in the pore structure of the gravel specimen associated with a relatively weaker and non-homogeneous ITZ occurred under impact. Finally, it was also concluded that increased roughness of ITZ may contribute to the load-carrying capacity of concrete under impact by improving contact point interactions and energy dissipation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recurrent neural network-based multiaxial plasticity model with regularization for physics-informed constraints

We report a recurrent neural network (RNN) based model is developed as a surrogate to predict nonlinear plastic response under multiaxial loading. The RNN-based model is trained and tested on stress versus strain curves generated using a numerical solution based on the classical radial return method. Besides simply learning the basic constitutive relationship, a novel approach is taken to enforce certain physical conditions. Specifically, regularization is employed to maintain non-negative plastic power density throughout the loading history thereby ensuring monotonically increasing plastic work and thermodynamic consistency. Enforcing physics in this manner permits coupling of the data-driven RNN approach with physics-based knowledge and laws. This has the effect of reducing the necessary amount of data and ensuring known physical laws are not violated. Since, once trained, the model need not perform the expensive task of solving nonlinear equations, its efficiency is orders of magnitude greater than its numerical counterpart. The RNN-based model has been trained on varied sets of data and the accuracy on test datasets validated. The developed model is general and robust and has widespread application such as in the simulation of metal forming, large scale plasticity, and part life prediction.

42 ENGINEERING↗
DOE OSTI2017

Mechanical properties of water desalination and wastewater treatment membranes

Applications of membrane technology in water desalination and wastewater treatment have increased significantly in the past fewdecades due to itsmany advantages over otherwater treatment technologies.Water treatment membranes provide high flux and contaminant rejection ability and require good mechanical strength and durability. Thus, assessing the mechanical properties of water treatment membranes is critical not only to their design, but also for studying their failure mechanisms, including the surface damage, mechanical and chemical ageing, delamination and loss of dimensional stability of the membranes. The various experimental techniques to assess themechanical properties ofwastewater treatment and desalinationmembranes are reviewed. Uniaxial tensile test, bending test, dynamic mechanical analysis, nanoindentation and bursting tests are the most widely used mechanical characterization methods for water treatment membranes. Mechanical degradations induced by fouling, chemical cleaning as well as membrane delamination are then discussed. Moreover, in order to study the membranesmechanical responses under similar loading conditions, the stress-state of the membranes are analyzed and advanced mechanical testing approaches are proposed. Lastly, some perspectives are highlighted to study the structure-properties relationship for wastewater treatment and water desalination membranes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

A real-time multiphysics model of a pressurized solid oxide electrolysis cell (SOEC) for cyber-physical simulation

Solid oxide electrolysis cells (SOEC) can play important roles in integrated energy systems (IES) as the hydrogen production hub and the resilience energy hub. When tied to a microgrid with high renewable penetration, the SOEC is subjected to rapid load transitions in response to the intermittent renewable generations that occur not only in diurnal cycles but also in short timeframes (e.g., sub-minute). The cyber-physical simulation approach can derisk operability research but requires a real-time dynamic SOEC model. In the present work, a real-time multiphysics model for pressurized SOEC is developed and validated in the pressure range from 1.4 to 8bar. Further, the accuracy of the single repeating unit (SRU) assumption in SOEC stack simulation is quantified. A guidance of more than 45 cells in one SOEC stack is recommended to safely apply the SRU assumption. Modeling results suggest that at a given current density, more power is consumed by SOEC at elevated operating pressures. The anode air and cathode stream have major impacts on thermal management, highlighting the potential benefit of integrating SOEC with other thermal processes in IES. To achieve high hydrogen production efficiency, the SOEC could operate at the maximum endothermic point to maximize the use of thermal energy. The real-time execution of the developed SOEC model is also demonstrated, which only takes 0.1% of the fixed time step of 5ms. The developed model establishes the basis for cyber-physical simulation of SOEC hybrid systems.

25 ENERGY STORAGE↗