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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Synthetic data generation for machine learning model training for energy theft scenarios using cosimulation

Abstract Technical and non‐technical losses in distribution circuits result in significant economic costs to power utilities. One type of non‐technical loss is energy theft by various means including illegal tapping of feeders, bypassing the meter, and billing fraud. These losses are usually hard to detect, and can remain undetected for long periods of time. Machine learning models have been proven effective in detecting these conditions, but rely on the availability of large, good‐quality training data sets. The problem is exacerbated by the imbalanced nature of data related to these conditions—energy theft, though costly, is very rare. The available data sets generally have very few samples of theft with most of the data pertaining to normal operation. Such data sets are generally not suitable to train machine learning models. In this paper, an overview of energy theft detection techniques, the challenges with their data needs, and the limitations of current techniques to bridge such data limitations is presented. A co‐simulation framework is proposed to generate reliable training data for machine learning algorithms for theft detection. An example scenario is presented and a machine learning model is built to detect certain kinds of energy theft.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Evaluating the stability and activity of dilute Cu-based alloys for electrochemical CO 2 reduction

Cu-based catalysts currently offer the most promising route to actively and selectively produce value-added chemicals via electrochemical reduction of CO 2 (eCO 2 R); yet further improvements are required for their wide-scale deployment in carbon mitigation efforts. Here, we systematically investigate a family of dilute Cu-based alloys to explore their viability as active and selective catalysts for eCO 2 R through a combined theoretical–experimental approach. Using a quantum–classical modeling approach that accounts for dynamic solvation effects, we assess the stability and activity of model single-atom catalysts under eCO 2 R conditions. Our calculations identify that the presence of eCO2R intermediates, such as CO*, H*, and OH*, may dynamically influence the local catalyst surface composition. Additionally, we identify through binding energy descriptors of the CO*, CHO*, and OCCO* dimer intermediates that certain elements, such as group 13 elements (B, Al, and Ga), enhance the selectivity of C 2+ species relative to pure Cu by facilitating CO dimerization. The theoretical work is corroborated by preliminary testing of eCO 2 R activity and selectivity of candidate dilute Cu-based alloy catalyst films prepared by electron beam evaporation in a zero-gap gas diffusion electrode-based reactor. Of all studied alloys, dilute CuAl was found to be the most active and selective toward C 2+ products like ethylene, consistent with the theoretical predictions. Finally, we attribute the improved performance of dilute CuAl alloys to more favorable dimerization reaction energetics of bound CO species relative to that on pure Cu. In a broader context, the results presented here demonstrate the power of our simulation framework in terms of rational catalyst design.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

The ScIDEP muon radiography project at the Egyptian Pyramid of Khafre

The ScIDEP Collaboration is constructing muon telescopes based on scintillator technology to investigate the internal structure of the Egyptian Pyramid of Khafre at Giza near Cairo using cosmic-ray muons. The collaboration aims to scan the pyramid from multiple viewpoints, both inside the king’s burial chamber that is located centrally at the base of the pyramid, and outside of the pyramid, to potentially identify any new internal structures. An overview of the project is presented, including the development of the data-acquisition system, the simulation framework, and very first detector studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Demonstration of the Advanced Dynamic System Modeling Tool TRANSFORM in a Molten Salt Reactor Application via a Model of the Molten Salt Demonstration Reactor

Liquid-fueled nuclear reactors, particularly molten salt reactors (MSRs), have recently gained significant interest in the advanced reactor community. As with all reactors, modeling and simulation are critical to advanced reactor design and licensing and will be required for MSR deployment. However, there are significant gaps in existing simulation capabilities for MSRs, particularly with the unique challenges of liquid-fueled systems (e.g., fission product transport). Furthermore, advanced reactor designers require near-term tools that are readily modifiable to perform design and analysis, including the ability to extend their analysis beyond the primary system to auxiliary systems. Transient Simulation Framework of Reconfigurable Models (TRANSFORM), a Modelica-based, system modeling library developed at Oak Ridge National Laboratory, is an advanced tool that can help meet some of the near-term needs of the advanced reactor community. Here, this paper describes advanced system modeling criteria and presents TRANSFORM to the advanced reactor community by demonstration of system modeling capabilities and support of advanced analysis workflows, i.e., the Risk Analysis Virtual Environment (RAVEN) framework from Idaho National Laboratory, using the liquid-fueled Molten Salt Demonstration Reactor (MSDR) as a reference design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Advanced Multiphysics Code Coupling for Cladding Surface Thermocouples During Two-Phase Heat Transfer from Nuclear Fuel

Transient testing of nuclear fuel involves the evaluation of fuel performance under off-normal and accident conditions and is essential for proving design performance. Instrumentation included in such experiments commonly includes thermocouples attached to the outer surface of the cladding to provide temperature measurements throughout the transient. However, the presence of thermocouples on the cladding surface can alter the local heat transfer characteristics with the surrounding coolant. These localized effects can influence the temperature of the nearby cladding surface and introduce uncertainties in interpreting the thermocouple data. Understanding the impact of thermocouples attached to the outer surface of the cladding is crucial for accurate data interpretation as well as its effect on the thermomechanical behavior of the cladding. This paper presents a novel methodology for simulating the impact of outer cladding thermocouples during transient testing of nuclear fuels. The simulation framework leverages the thermal-hydraulic capabilities of RELAP5-3D coupled to the BISON fuel performance code through the RELAPCouplingApp interface. The methodology is compared against Accident Tolerant Fuel Reactivity Initiated Accident-1-E experiment performed at Idaho National Laboratory. The results reveal approximately 100°C difference between thermocouple-altered temperature and virgin cladding surface. The model overpredicts surface rewet time due to conservative correlations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Study of the muon component in the core-corona model using CONEX 3D

The discrepancy between models and data regarding the muon content in air showers generated by ultra-high energy cosmic rays still needs to be solved. The CONEX simulation framework provides a flexible tool to assess the impact of different interaction properties and thus address the muon puzzle. In this work, we present the multidimensional extension of CONEX and show its performance compared to CORSIKA by discussing muon-related air-shower features for three experiments: KASCADE, IceTop, and the Pierre Auger Observatory. We also implement an effective version of the core-corona model to demonstrate the impact of the core effect, as observed at the LHC, on the muon content in air showers produced by ultra-high energy cosmic rays. At a primary energy of E$_{0}$ = 10$^{19}$ eV, we obtain an increase of 15% to 20% in the muon content.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Design of the American Wake Experiment (AWAKEN) field campaign

The American WAKE experimeNt (AWAKEN) is a multi-institutional collaborative field campaign, starting in March 2022, that will gather an unprecedented data set including both atmospheric observations and wind plant operational data. This comprehensive data set will be used to characterize the wind plant performance and turbine loading in different operational and atmospheric conditions and validate the use of different wind plant control strategies and simulation frameworks. An extensive field campaign like AWAKEN requires proper coordination and long-term planning to be successful. In this paper, we review the major activities planned during AWAKEN to provide information for current and future project partners. Specifically, we provide information about the project sites, their planned instruments, and how these will relate to the scientific objectives of the overall AWAKEN project.

17 WIND ENERGY↗
DOE OSTI2026

Long-term socioeconomic trends and climate variability as drivers of virtual water scarcity in China

Water scarcity can have far-reaching sectoral impacts beyond its physical location through the propagation of virtual water flows. Socioeconomic and hydroclimatic changes affect local and virtual water scarcity by altering availability and demand. Yet most studies of this phenomenon focus on volumetric footprints, and the few on water scarcity risk have not examined hydroclimatic variability beyond long-term trends. In this study, we ask how gross domestic product (GDP) and population changes, long-term meteorological trends, sea surface temperature (SST) patterns, and interannual meteorological variability affect water scarcity in China, both locally (through the local water scarcity risk index, LWSR) and remotely (through the virtual water scarcity risk index, VWSR). Counterfactual scenarios were compared in a regression-and-simulation framework, with the socioeconomic and meteorological drivers varying over 1923–2019 and the multi-regional input–output structure staying fixed at 2017. Relative to a 5 year baseline centered on 2017, GDP and population changes have induced a cumulative 17%–50% increase in LWSR and 13%–21% increase in VWSR, outweighing the effect of long-term meteorological trends. phase change in one of two examined SST patterns induce 4%–13% differences in LWSR and 1%–4% differences in VWSR. Interannual meteorological variability induces 10%–20% standard deviations in LWSR and 3%–7% in VWSR. The findings highlight the importance of using longer time series to accurately assess local and virtual water scarcity situations. Water scarcity management should prioritize socioeconomic factors when planning at century-long timescales and prioritize hydroclimatic factors at multidecadal or shorter timescales. water managers should consider interannual variabilities in LWSR and VWSR and plan for potential occurrences of extreme conditions.

climate variability↗
DOE OSTI2025

Estimating the energy threshold of phonon-mediated superconducting qubit detectors operated in an energy-relaxation sensing scheme

In recent years, the lack of a conclusive detection of weakly interacting massive particle dark matter at the 10 GeV/c 2 mass scale and above has encouraged development of low-threshold detector technology aimed at probing lighter dark matter candidates. Detectors based on Cooper-pair-breaking sensors have emerged as a promising avenue for this detection due to the low (meV-scale) energy required for breaking a Cooper pair in most superconductors. Among them, devices based on superconducting qubits are interesting candidates for sensing due to their observed sensitivity to broken Cooper pairs. Here, we have developed an end-to-end G 4 CMP -based simulation framework and have used it to evaluate performance metrics of qubit-based devices operating in a gate-based “energy relaxation” readout scheme, akin to those used in recent studies of qubit sensitivity to ionizing radiation. We find that for this readout scheme, the qubit acts as a phonon sensor with an energy threshold ranging down to ≃ 0.4 eV for near-term performance parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Coordinate transformation methodology for simulating quasistatic elastoplastic solids

Molecular dynamics simulations frequently employ periodic boundary conditions where the positions of the periodic images are manipulated in order to apply deformation to the material sample. For example, Lees-Edwards conditions use moving periodic images to apply simple shear. Here, we examine the problem of precisely comparing this type of simulation to continuum solid mechanics. We employ a hypo-elastoplastic mechanical model, and develop a projection method to enforce quasi-static equilibrium. We introduce a simulation framework that uses a fixed Cartesian computational grid on a reference domain, and imposes deformation via a time-dependent coordinate transformation to the physical domain. As a test case for our method, we consider the evolution of shear bands in a bulk metallic glass using the shear transformation zone theory of amorphous plasticity. We examine the growth of shear bands in simple shear and pure shear conditions as a function of the initial preparation of the bulk metallic glass.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Biomimetic, Soft-Material Synapse for Neuromorphic Computing: from Device to Network

Neuromorphic computing refers to a variety of brain-inspired computers, devices, and models inspired by the interconnectivity, performance, and energy efficiency of the human brain. Unlike the ubiquitous von Neumann computer architectures with complex processor cores and sequential computation, biological neurons and synapses operate by storing and processing information simultaneously with the capacity of flexible adaptation resulting in massive computational capability with much less power consumption. The search for a synaptic material which can closely imitate bio-synapse has led to an alamethicin-doped, synthetic biomembrane which can emulate key synaptic functions due to generic memristive property enabling learning and computation. This two-terminal, biomolecular memristor, in contrast to its solid-state counterparts, features similar structure, switching mechanism, and ionic transport modality as biological synapses while consuming considerably lower power. In this paper, we outline a methodology for using this biomolecular synapse to build neural networks capable of solving real-world problems. The physical mechanism underlying its volatile memristance is explored followed by the development of a model of this device for circuit simulation. We outline a circuit design technique to integrate this synapse with solid-state neuron circuit for hardware implementation. Based on these results, we develop a high level simulation framework and use a training scheme called Evolutionary Optimization for Neuromorphic System (EONS) to generate networks for solving two problems, namely iris dataset classification and EEG classification task. The small network size and comparable to state-of-the-art accuracy of these preliminary networks show its potential to enhance synaptic functionality in next generation neuromorphic hardware.

Sakib hasan, Md↗
DOE OSTI2019

Capacity Valuation of Demand Response in the Presence of Variable Generation through Monte Carlo Analysis

While smart demand-side management technologies have significant potential to support the integration of variable renewable generation sources in the electricity system, rigorously quantifying the contribution of demand response to meeting peak demand remains a challenge due to the nontrivial intertemporal considerations involved in demand response operations. This paper contributes to the field of capacity value by studying the effect of customer participation in DR programs, investigating the contribution that shiftable loads can provide for capacity value in a smart, standalone system. This paper uses a Monte Carlo simulation to investigate the effect of DR on the loss of load probability in a sequential simulation framework. Also presented here is a load-shifting model for customer loads where time of use is based on need, priority, and the availability of generation. Results of this work present a quantitative value for the equivalent firm capacity of demand response programs for a specific test case that depends on the participation rate among consumers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Leveraging Multiple Connected Traffic Light Signals in an Energy-Efficient Speed Planner

Connecting automated vehicles to traffic lights can lead to significant energy savings by enabling them to pass through intersections in an energy-efficient way without unnecessary stops. A cellular-based communication system connecting multiple traffic lights can help realize the full potential of energy-efficient driving at intersections. Thus, we propose a hierarchical speed planner that can leverage information from multiple connected traffic lights. The proposed speed planner consists of two modules: a green window selector and a reference trajectory generator. The green window selector, based on Dijkstra’s algorithm, finds a series of "green windows" for connected traffic lights that builds an energy-optimal path for vehicles to follow. The reference trajectory generator finds optimal entering times, based on the selected green window at each intersection, and then computes reference trajectories. Deriving and using analytical optimal entering speeds as a function of entering times allows us to guarantee the computational simplicity suitable for real-time implementation. We also demonstrate how to balance energy and traffic flow perspectives in the reference trajectory generator. Lastly, a high-fidelity simulation framework is used to evaluate the proposed speed planner and quantify the extent to which it can save energy in various real-world urban route scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Design, Preparation, and Execution of the 100-AV Field Test for the CIRCLES Consortium: Methodology and Implementation of the Largest Mobile Traffic Control Experiment to Date

This article presents the comprehensive design, setup, execution, and evaluation of the MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via CAV-in-the-Loop Lagrangian Energy Smoothing (CIRCLES) Consortium, which aimed to mitigate traffic congestion using partially autonomous vehicles (AVs) (see “Summary”). The experiment involved 100 vehicles on Nashville’s Interstate 24 (I-24) highway, utilizing various control algorithms to smooth stop-and-go traffic waves. The execution of the MVT experiment required a coordinated effort from multiple teams. This article details the meticulous planning process, the coordinated efforts of multiple teams, and the innovative use of a dynamic agent-based simulation framework for traffic evaluation. Here, the contributions of this work include demonstrating and providing a detailed roadmap for large-scale live traffic experiments, illustrating the lessons learned from the MVT experiment, and introducing the other articles in this issue and their complementary relationship in the MVT experiment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Transactive Implementation of Decentralized Electricity Market for Grid-Edge Systems

The electricity landscape is evolving towards more decentralized approaches due to the proliferation of distributed energy resources and the participation of increasingly smart consumers and producers (prosumers). Recent advances in information and communication technologies and smart metering, provides strategic opportunities for “prosumers” to reform their conventional energy practices towards more consumer-centric economies. From an operational perspective, managing power distribution networks is becoming more difficult with such active grid-edge systems providing limited to no visibility or control. Transactive Energy (TE) has been emerging as a key enabler towards effectively and efficiently integrating prosumers into competitive electricity markets. This work presents a transactive implementation of community-centric markets. A co-simulation framework is developed for evaluating the proposed market structure with high-fidelity models. Case studies on the IEEE-123 node test system demonstrate that community-centric transactive markets can enable communities of prosumers to operate collaboratively as grid-edge systems. The potential benefits of implementing community-centric TE systems are also illustrated.

transactive, microgrids, centralized market operat↗
DOE OSTI2022

Efficient Topology Assessment for Integrated Transmission and Distribution Network with 10,000+ Inverter-based Resources

The renewable energy proliferation calls upon the grid operators and planners to systematically evaluate the potential impacts of distributed energy resources (DERs). Considering the significant differences between various inverter-based resources (IBRs), especially the different capabilities between grid-forming inverters and grid-following inverters, it is crucial to develop an efficient and effective assessment procedure besides available co-simulation framework with high computation burdens. This paper presents a streamlined graph-based topology assessment for the integrated power system transmission and distribution networks. Graph analyses were performed based on the integrated graph of modified miniWECC grid model and IEEE 8500-node test feeder model, high performance computing platform with 40 nodes and total 2400 CPUs has been utilized to process this integrated graph, which has 100,000+ nodes and 10,000+ IBRs. The node ranking results not only verified the applicability of the proposed method, but also revealed the potential of distributed grid forming (GFM) and grid following (GFL) inverters interacting with the centralized power plants.

Graph Analysis, Topology evaluation, Infrastructur↗
DOE OSTI2022

Novel Real- Time EMT- TS Modeling Architecture for Feeder Blackstart Simulations

This paper presents the development and benchmarking of a novel real-time electromagnetic-transient and transient-stability (EMT-TS) modeling architecture for distribution feeder restoration studies. The work presents for the first time in the literature a real-time EMT-TS testbed in which the grid-forming unit is simulated in EMT domain, operating as the slack bus of the phasor domain while including unbalanced voltage conditions. To evaluate the performance and limitations of the proposed model, an equivalent EMT testbed is developed to serve as a benchmark. First, the co-simulation framework and the domain coupling methodology are introduced. Next, the steady state operation of the EMT-TS and EMT models are matched. Then, tests are conducted to analyze the transient performance of the proposed EMT-TS model when compared to its EMT benchmark. Results reveal that when utilizing a battery energy storage system (BESS) as the grid-forming unit, the EMT-TS testbed can maintain high accuracy for typical load steps.

Paduani, Victor↗