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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 271 records · Page 15

Design and Testing of CPAS Main Deployment Bag Energy Modulator

During the developmental testing program for CPAS (Capsule Parachute Assembly System), the parachute system for the NASA Orion Crew Module, simulation revealed that high loads may be experienced by the pilot risers during the most devere deployment conditions. As the role of the pilot parachutes is to deploy the main parachutes, these high loads introduced the possibility of main deployment failure. In order to mitigate these high loads, a set of energy modulators was incorporated between the pilot riser and the main deployment bag. An extensive developmental program was implemented to ensure the adequacy of these energy modulators. After initial design comparisons, the energy modulator design was validated through slow-speed joint tests as well as through high-speed bungee tests. This paper documents the design, development, and results of multiple tests completed on the final design.

Mollmann, Catherine↗

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

47 OTHER INSTRUMENTATION↗

Learning-Based Building Flexibility Estimation and Control to Improve Microgrid Economics and Resilience: Preprint

This paper proposes a learning-based building flexibility estimation and control framework to improve system economics and resilience. A data-driven building load flexibility model consisting of weather forecasting and estimating load consumption is proposed to quantify building heating, ventilation, and air conditioning (HVAC) load flexibility. A reinforcement learning-based microgrid controller is proposed to dispatch distributed generators, distributed energy resources, and build HVAC loads while taking flexibility information as one of the inputs. Simulation analysis is conducted on the model of a real microgrid in California. The effectiveness of the proposed learning-based building flexibility estimation and control in reducing microgrid energy costs and improving the sustainability of critical loads is demonstrated.

building load flexibility↗

Atomic Energy Accuracy of Neural Network Potentials: Harnessing Pretraining and Transfer Learning

Machine learning-based interatomic potentials (MLIPs) have transformed the prediction of potential energy surfaces (PESs), achieving accuracy comparable to ab initio calculations. However, atomic energy predictions, often assumed to lack physical meaning, remain underexplored. In this study, we demonstrate that inaccuracies in atomic energy predictions reduce the robustness and transferability of Neural Network Potentials (NNPs) and atomic energy error can be masked in total energy predictions due to error cancellation. Here, we validate this finding using challenging configurations involving deformation and failure under tensile loading. By pretraining atomic energy predictions using empirical potentials and applying transfer learning with density functional theory (DFT) data, we achieve notable improvements in the accuracy of total energy, forces, and stress predictions. Furthermore, this approach enhances the robustness and transferability of NNPs, emphasizing the importance of atomic energy predictions in developing high-quality and reliable MLIPs.

Active Learning↗

Met-Ocean Characterization for the Atlantic Marine Energy Center’s (AMEC’s) Gulf of Maine Wave Test Sites

Comprehensive and consistent analysis, characterization, and classification of the wave climate at open-ocean wave energy converter (WEC) test sites guided by international standards enables commensurable evaluation and comparison of met-ocean characteristics, including wave energy resources and wave load conditions. Herein, we present results from a comprehensive feasibility-level met-ocean characterization for two Atlantic Marine Energy Center (AMEC) WEC test sites in the Gulf of Maine.

16 TIDAL AND WAVE POWER↗

Bridging the Gap for Powering Data Centers

The rapid expansion of data centers, primarily driven by artificial intelligence, is outpacing the adaptability of the U.S. electric grid. This report, developed by Idaho National Laboratory (INL) , presents a gap analysis of some of the infrastructure challenges associated with large-scale data center deployment. Drawing from a national workshop hosted by INL in October of 2025, the report synthesizes stakeholder insights, survey data, and technical discussions to identify critical barriers and research needs. Key findings highlight the growing preference for behind-the-meter generation, the perceived inadequacy of legacy interconnection processes, and the urgent need for improved coordination between utilities, regulators, and data center developers. Environmental concerns such as water use and noise pollution, as well as economic constraints like equipment lead times and cost allocation, are also explored. The report outlines national lab capabilities in modeling, simulation, and technical assistance, and proposes targeted R&D priorities to support resilient, scalable, and efficient integration of data centers into the grid.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Performance characteristics of a diesel engine using low- and medium-energy gases as a fuel supplement (fumigation)

The use of low- and medium-energy gases derived from solid waste is investigated. Gases that simulate those gases that could be derived from refuse were injected into the air inlet of a 298-kilowatt (400 horsepower) diesel engine as a fuel supplement. This process is called fumigation. Three different gases with thermal-energy contents of 6.11 MJ/cu m (164 Btu/cu ft), 18.1 MJ/cu m (485 Btu/cu ft), and 18.8 MJ/cu m (505 Btu/cu ft, respectively, were used at rates ranging as high as 20 percent of the normal fuel oil energy at four different engine load points. The test results indicated approximately 100 percent gas energy utilization with no observable deleterious effect on the engine.

Monford, L. G.↗

Wind Loading on CSP Collectors

The project significantly enhanced the community's understanding of the fundamental physics drivers underlying the wind-loading experienced by concentrating solar power (CSP) collector structures (i.e., parabolic troughs and heliostats) as well as their support structures. This project had two overarching objectives: (1) detailed measurements to characterize the prevailing wind conditions and resulting operational loads on collector structures, and (2) development and validation of a computationally efficient, high-fidelity modeling tool capable of predicting wind-loading in deep-array installations. Over three years, we conducted comprehensive at-scale field measurements of the atmospheric turbulent wind conditions, and the resulting wind loads on parabolic troughs and heliostats. Two at-scale measurement campaigns yielded first-of-its-kind, high-resolution, long-term datasets that are used to characterize the complex flow field and wind loading on parabolic-troughs and heliostats in operational power plants. The high-resolution measurements collected during these campaigns were used to validate the high-fidelity computational models developed at NREL. These open-source computationally efficient models were shown to be accurate in predicting wind-driven loads on collectors without the need for a large supercomputer.

14 SOLAR ENERGY↗

Techno-Economic Assessment of Data Center Load Demand Powered by Small Modular Reactors and Distributed Energy Resources

The rapid increase in data center energy demand, driven by AI and large-scale data processing, poses significant challenges to global energy infrastructure. Data centers require substantial and reliable energy for continuous operations and high-performance computing. Current electrical grids face issues such as transmission bottlenecks and aging infrastructure, making it difficult to meet these demands. Integrating inverter-based-resources (IBRs) like solar and wind presents both opportunities and challenges due to their intermittent nature. Small Modular Reactors (SMRs) offer a promising solution with their enhanced safety, modularity, reliability, and scalability, providing consistent base load power ideal for data center operations. This study presents a comprehensive techno-economic assessment of powering data center load demand using a combination of SMRs and IBRs with grid-connected and islanded mode. This study utilized Idaho National Laboratory’s (INL) HPC data center hourly load profiles and Xendee microgrid optimization platform to conduct the analysis. In this configuration, SMRs serves as the primary base load power source, consistently providing a steady supply of electricity necessary to meet the minimum load demand of the data center with support from the IBRs. Key performance indicators such as Levelized Cost of Electricity (LCOE), Net Present Value (NPV) has been calculated to assess the economic feasibility. The findings from this research will underscore the strategic benefits of integrating SMR plant with DERs – particularly for critical infrastructure load such as data centers.

14 - SOLAR ENERGY↗

The strength of laminated composite materials under repeated impact loading

When low velocity and energy impact is exerted on a laminated composite material, in a perpendicular direction to the plane of the laminate, invisible damage may develop. It is shown analytically and experimentally that the invisible damage occurs during the first stage of contact between the impactor and the laminate and is a result of the contact stresses. However, the residual flexural strength changes only slightly, because it depends mainly on the outer layers, and these remain undamaged. Repeated impact intensifies the damage inside the laminate and causes larger bending under equivalent impact load. Finally, when the damage is most severe, even though it is still invisible, the laminate fails because of bending on the tension side. If the repeated impact is halted before final fracture occurs the residual strength and modulus would decrease by a certain amount.

Rotem, Assa↗

Flight Arrival Data for Each Airport

This dataset contains flight arrival data for each airport, which serves as the input for generating load profiles and estimating energy needs and fleet and charger requirements. ![image](distribution-flight-arrivals.png) Distribution of annual flight arrivals across different airport categories.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fixture For Compression-After-Impact Tests Of Thin Specimens

Special fixture holds specimen of laminated composite material in 20-klb (89-kN) or larger load frame for compression-after-impact test. In preparation for test, specimen damaged by dropping weight on it at known kinetic energy. During test, specimen loaded in compression, and load measured, until specimen fails. Measurement data used to characterize compressive strength of specimen after impact important indicator of ability of structural components made of composite material to tolerate damage. Tests give more-realistic measures of tolerance to damage.

Nettles, Alan T.↗

Architecture for Web-Based Visualization of Large-Scale Energy Domains: Preprint

With the growing penetration of inverter-based distributed energy resources and increased loads through electrification, power systems analyses are becoming more important and more complex. Moreover, these analyses increasingly involve the combination of interconnected energy domains with data that are spatially and temporally increasing in scale by orders of magnitude, surpassing the capabilities of many existing analysis and decision-support systems. We present the architectural design, development, and application of a high-resolution web-based visualization environment capable of cross-domain analysis of tens of millions of energy assets, focusing on scalability and performance. Our system supports the exploration, navigation, and analysis of large data from diverse domains such as electrical transmission and distribution systems, mobility and electric vehicle charging networks, communications networks, cyber assets, and other supporting infrastructure. We evaluate this system across multiple use cases, describing the capabilities and limitations of a web-based approach for high-resolution energy system visualizations.

grid modernization↗

An Improved Plastically Dilatant Unified Viscoplastic Constitutive Formulation for Multiscale Analysis of Polymer Matrix Composites Under High Strain Rate Loading

Polymer matrix composites are commonly used to fabricate energy-absorbing structures expected to experience impact loading. As such, a detailed understanding of the dynamic response of the constituent materials is necessary. Since the rate, temperature, and pressure dependence of carbon fiber reinforced polymer matrix composites are primarily manifestations of the rate, temperature, and pressure dependence of the polymer matrix, it is crucial that the constitutive behavior of the matrix be accurately characterized. In this work, an existing unified viscoplastic constitutive formulation is extended to ensure thermodynamic consistency and to more accurately account for the tension-compression asymmetry observed in the response of polymeric materials. A new plastic potential function is proposed, and elementary loading conditions are utilized to determine relations between model constants to ensure nonnegative plastic dissipation, a necessary thermodynamic requirement. Expressions for plastic Poisson’s ratios are derived and are bounded by enforcing nonnegative plastic dissipation. The model is calibrated against available experimental data from tests conducted over a range of strain rates, temperatures, and loading cases on a representative thermoset epoxy; good correlation between simulations and experimental data is obtained. Temperature rises due to the conversion of plastic work to heat are computed via the adiabatic heat energy equation. The viscoplastic polymer model is then used as a constitutive model in the generalized method of cells micromechanics theory to investigate the effects of matrix adiabatic heating on the high strain rate response of a unidirectional composite. The thermodynamic consistency of the model ensures plastic dissipation can only cause an increase in temperature. Simulation results indicate that significant thermal softening due to the conversion of plastic work to heat is observed in the composite for matrix dominated deformation modes.

Impact loading↗

EVI-EnSitePy (Electric Vehicle Infrastructure – Energy Estimation and Site Optimization Tool in Python) [EVI-X Modeling Suite] [SWR-25-07]

EVI-EnSitePy is a comprehensive agent-based tool designed for the analysis and design of high-power charging sites, encompassing a wide array of site agents including Electric Vehicles (EVs), chargers, energy storage units (ESS), renewable energy resources (DER), and loads. This versatile tool offers diverse functionalities and a modular modeling approach, allowing detailed configuration of agents based on power ratings, port numbers, energy capacities, demand requirements, charger interfaces, and flexibility to customize the tool for project specific goals. By simulating agent interactions and employing various metrics, EVI-EnSitePy enables the assessment of site performance, exploration of energy management systems (EMS), and implementation of innovative EV charging policies. Utilizing EV charge schedules and arrival states, the tool performs thorough charging site simulations, with outputs consisting of agent and site-level power profiles and statistical metrics. Employing a tree graph structure, EVI-EnSitePy supports nested site structures and power distribution modeling. The tool's ability to generate charging schedules deterministically or via stochastic analysis further enhances its versatility. Through its features and capabilities, EVI-EnSitePy offers a powerful platform for informed decision-making in the realm of high-power charging site design and operation.

Jackson, Derek [National Renewable Energy Laborato↗

Satellite Power Systems (SPS) concept definition study, exhibit C. Volume 1: Executive summary

The Department of Energy (DOE) is currently conducting an evaluation of approaches to provide energy to meet demands in the post-2000 time period. The Satellite Power System (SPS) is a candidate for producing significant quantities of base-load power using solar energy as the source. The SPS concept is illustrated for a solar photovoltaic concept. A satellite, located at geosynchronous orbit, converts solar energy to dc electrical energy using large solar arrays. This study is a continuing effort to provide system definition data to aid in the evaluation of the SPS concept.

Hanley, G. M.↗

Deformation and damage of composite plates under impact loading

Transient deformation and damage were studied in impacted graphite/epoxy plates. The plates were 8-ply and 16-ply quasi-isotropic laminates clamped around a 12.7 cm diameter circumference. They were instrumented with surface and embedded strain gages and loaded by a 202 gr mass dropped from a height of 1.8 m. The load history and imparted energy were obtained by means of an accelerometer attached to the impactor. Transient strains at various locations through the thickness and at various distances from the loading point were obtained. The characteristic features of the strain records are associated with specific failure modes in the laminate. The deformation history was also correlated with the induced damage as detected by X-radiography and ultrasonics. Impact damage is more extensive in the thicker laminate. Damage takes the form of delaminated strips parallel to the fiber direction in each ply and increasing in length from top to bottom.

Daniel, I. M.↗

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to subhourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

accuracy↗