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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High fidelity multiphysics tightly coupled model for a lead cooled fast reactor concept and application to statistical calculation of hot channel factors

A tightly coupled multiphysics code system is established using the MOOSE framework for hot channel factor (HCF) evaluation on a Lead Fast Reactor (LFR) concept. The coupled system is driven by the Griffin multiphysics coupling capability under which the MOOSE Heat Transfer module and NekRS computational fluid dynamics solver are coupled for conjugate heat transfer using the Cardinal application. The coupled capability is demonstrated on an LFR assembly model based on materials and geometry of a prototypical lead-cooled fast reactor design by Westinghouse Electric Company, LLC. Moreover, the work integrates the Multiphysics Object Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM) to perform calculations for statistical analysis of HCF. Furthermore, the coupling strategy and workflow demonstrated in this paper is not only useful for predicting accurate hot channel factors for different kinds of advanced reactors but also for other engineering applications such as control rod worth assessment, generation of high-fidelity database for Artificial intelligence (AI)/machine learning (ML) training, design optimization and multi-resolution modeling.

Cardinal↗
DOE OSTI2020

Probing the Local Site Disorder and Distortion in Pyrochlore High-Entropy Oxides

High-entropy oxides (HEOs) have attracted great interest in diverse fields because of their inherent opportunities to tailor and combine materials functionalities. The control of local order/disorder in the class is by extension a grand challenge toward realizing their vast potential. In this paper, we report the first examples of pyrochlore HEOs with five M-site cations, for Nd 2 M 2 O 7 , in which the local structure has been investigated by neutron diffraction and pair distribution function (PDF) analysis. The average structure of the pyrochlores is found to be orthorhombic Imma, in agreement with radius-ratio rules governing the structural archetype. The computed PDFs from density functional theory relaxed special quasirandom structure models are compared with real space PDFs in this work to evaluate M-site order/disorder. Reverse Monte Carlo combined with ab initio molecular dynamics and Metropolis Monte Carlo simulations demonstrates that Nd 2 (Ta 0.2 Sc 0.2 Sn 0.2 Hf 0.2 Zr 0.2 ) 2 O 7 is synthesized with its M-site local to nanoscale order highly randomized/disordered, while Nd 2 (Ti 0.2 Nb 0.2 Sn 0.2 Hf 0.2 Zr 0.2 ) 2 O 7+x exhibits a strong distortion of the TiO 6 octahedron and small degree of Ti chemical short-range order (SRO) on the subnanometer scale. Calculations suggest that this may be intrinsic, energetically favored SRO rather than due to sample processing. These results offer an important demonstration that the engineered variation of participating ions in HEOs, even among those with very similar radii, provides richly diverse opportunities to control local order/disorder motifs—and therefore materials properties for future designs. This work also hints at the exquisite level of detail that may be needed in computational and experimental data analysis to guide structure–property tuning in the emerging HEO materials class.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Exploring Building Retrofit Strategies Using AutoBEM Under Future Weather Scenarios

This study evaluates the long-term effectiveness of energy conservation measures (ECMs) on building energy consumption using AutoBEM, a scalable modeling framework driven by the high-resolution Model America dataset. We simulated 18,951 buildings in Flagstaff, Arizona under four climate scenarios using Future Typical Meteorological Year (fTMY) weather files for six time periods spanning from 1980 to 2099. Six ECMs were analyzed across electricity and gas usage, including HVAC fuel-switching, insulation upgrades, and infiltration control. While some measures, such as reducing space infiltration by percentage, showed minimal or even negative impact on total energy savings at the aggregate level, they proved highly effective for specific building types. Conversely, HVAC electrification offers high gas reduction but shifts demand to electricity, highlighting critical trade-offs under different climate trajectories. Building-type-specific analysis under SSP5-RCP8.5 (2080–2099) revealed significant variation in ECM performance, underscoring the need for targeted retrofit strategies. This study demonstrates the power of combining fTMY projections with large-scale simulations to inform data-driven retrofit planning.

Chowdhury, Shovan [ORNL]↗
DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Rational Enzyme Design for Controlled Functionalization of Acetylated Xylan for Cell-Free Polymer Biosynthesis

Xylan O-acetyltransferase 1 (XOAT1) is involved in O-acetylating the backbone of hemicellulose xylan. Recent structural analysis of XOAT1 showed two unequal lobes forming a cleft that is predicted to accommodate and position xylan acceptors into proximity with the catalytic triad. Here, we used docking and molecular dynamics simulations to investigate the optimal orientation of xylan in the binding cleft of XOAT1 and identify putative key residues (Gln445 and Arg444 on Minor lobe & Asn312, Met311 and Asp403 on Major lobe) involved in substrate interactions. Site-directed mutagenesis coupled with biochemical analyses revealed the major lobe of XOAT1 is important for xylan binding. Mutation of single key residues yielded XOAT1 variants with various enzymatic efficiencies that are applicable to one-pot synthesis of xylan polymers with different degrees of O-acetylation. Taken together, our results demonstrate the effectiveness of computational modeling in guiding enzyme engineering aimed at modulating xylan and redesigning plant cell walls.

93 SC - Biological and Environmental Research (BER↗
DOE OSTI2025

Validation and moisture content sensitivity analysis of cross-laminated timber wall assemblies in EnergyPlus

Cross-laminated timber buildings are becoming more common in North America, with many numerical studies showing potential energy savings. However, no studies have validated any EnergyPlus heat transfer algorithms or quantified their accuracy in simulating CLT in building envelopes. This study empirically validates the heat flux predictions for each of EnergyPlus's heat transfer algorithms (Conduction Transfer Functions (CTF), Effective Moisture Penetration Depth (EMPD), Conduction Finite Difference (CondFD), and Heat and Moisture Transfer (HAMT)) for two different CLT ply thicknesses with both summer and winter boundary conditions measured in controlled lab experiments. It also evaluates the model sensitivity of heat flux and heating and cooling loads to moisture content. The 1D validation shows that the HAMT model is the most accurate among all algorithms. All EnergyPlus's heat flux predictions are accurate independent of CLT plate thickness for summer conditions. However, the three constant property algorithms (CTF, EMPD, and CondFD) underpredict heat flux throughout the whole day during winter conditions. The 1D sensitivity analysis indicates that elevated moisture content can increase peak heat fluxes through the material by up to 20 %. Finally, the whole building model sensitivity analysis shows increased heating load and slight cooling load variation due to increased moisture content when using constant property models. The analysis shows significantly lower peak thermal demand (7 % lower heating and 6 % lower cooling) and monthly thermal load (8 % less cooling and 6 % less heating) predictions when using HAMT vs a constant property model.

42 ENGINEERING↗
DOE OSTI2024

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization. The pipeline facilitates data-driven protein engineering by consolidating sequence-function data to inform directed evolution and provide the requisite data for machine learning-guided protein engineering (MLPE). LevSeq enables quality control of mutagenesis libraries prior to screening, which reduces time and resource costs. Simulation studies demonstrate LevSeq’s ability to accurately detect variants under various experimental conditions. Lastly, we show LevSeq’s utility in engineering protoglobins for new-to-nature chemistry. Widespread adoption of LevSeq and sharing of the data will enhance our understanding of protein sequence-function landscapes and empower data-driven directed evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Liquid and Glass Phases of an Alkylguanidinium Sulfonate Hydrogen-Bonded Organic Framework

Glassy phases of framework materials feature unique and tunable properties that are advantageous for gas separation membranes, solid electrolytes, and phase-change memory applications. However, the structural and chemical diversity of porous frameworks that can be liquified and quenched into a glass has been limited by thermal decomposition at-or below-the high temperatures required to induce a melting transition. Utilizing a desymmetrization strategy, in this work we report a new guanidinium organosulfonate hydrogen-bonded organic framework (HOF) that melts and vitrifies below 100 °C. In this low-temperature regime, non-covalent interactions between guest molecules and the porous framework become a dominant contributor to the overall stability of the structure, resulting in unusual phase behavior such as guest dependent melting, glass, and recrystallization transitions. Through molecular dynamics simulations and pair distribution function analysis, we show that the local structure of the amorphous liquid and glass phase resembles that of the parent crystalline framework. Access to molten phases of framework materials at moderate temperatures should permit the use of more thermally sensitive functional groups and enhance the structural control and tunability that can be realized in network-forming glasses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Hidden vibronic and excitonic structure and vibronic coherence transfer in the bacterial reaction center

We report two-dimensional electronic spectroscopy (2DES) experiments on the bacterial reaction center (BRC) from purple bacteria, revealing hidden vibronic and excitonic structure. Through analysis of the coherent dynamics of the BRC, we identify multiple quasi-resonances between pigment vibrations and excitonic energy gaps, and vibronic coherence transfer processes that are typically neglected in standard models of photosynthetic energy transfer and charge separation. We support our assignment with control experiments on bacteriochlorophyll and simulations of the coherent dynamics using a reduced excitonic model of the BRC. We find that specific vibronic coherence processes can readily reveal weak exciton transitions. While the functional relevance of such processes is unclear, they provide a spectroscopic tool that uses vibrations as a window for observing excited state structure and dynamics elsewhere in the BRC via vibronic coupling. Vibronic coherence transfer reveals the upper exciton of the “special pair” that was weakly visible in previous 2DES experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Sensitivity analysis of small modular reactor mPower with ATHLET

Small modular reactor (SMR) possesses the characteristics of less radioactive source term, simpler structure, modular design and features like passive safety as well as low risk of proliferation. Developed and designed by Babcock and Wilcox, the mPower reactor is one of pronouncing small modular reactors that adopts the integrated design of the pressurized water reactor, steam generator and a built-in internal control rod drive mechanism. In this paper, the code ATHLET (Analysis of fossil-hydraulics of Leaks and Transients) is used to model the mPower reactor. At the same time, the sensitivity analysis of the core structure and geometric parameters of the pipeline loop, as well as the steady-state simulation and post-exothermic simulation are carried out depending on the given scenarios. In addition, the sensitivity analysis of pressure, temperature and mass flow in the secondary loop is performed. The results of this study will mitigate some of the frequent misunderstanding in the field and will help to better understand the design of SMR and provide basic research data for further research. However, there are limitations in the current research. Considering that the mPower is still in the conceptual design, the established model is only based on the limited public data while detailed parameters are still in myth, which leads to certain level of uncertainties in the calculation. Besides, the research is mainly on the influence of sensitivity analysis under steady state conditions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

A State-Space Model for Stability Boundary Analysis of Grid-Following Voltage Source Converters Considering Grid Conditions

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification.

grid-connected inverters↗
DOE OSTI2024

A Novel Two Stage Collimation Unit for Fermilab Booster

A new two-stage collimation unit (2SC) for Fermilab Booster will be installed during 2024 summer shutdown. It is a supplementary collimator for existing single stage Booster collimators. Design details of this 2SC adapted to Booster conditions are described. Results of beam dynamics simulations on collimation efficiency and evaluation of collimator shielding with MARS code on this new system are presented. The analysis on beam dynamics shows that the system will help to collimate up to about 1% of the beam in a confined way and, prompt and residual activation meet Fermilab Radiological Control limits in current as well as during PIP-II era high intensity operation of the Booster.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Depletion Analysis of a Generic Fast Spectrum Molten Salt Reactor Supporting Material Control and Accounting (Rev.1)

Advanced reactors are of interest for a variety of use scenarios, and there are numerous advanced reactor designs being considered, which includes molten salt reactors (MSRs). Depending on the design, advanced reactors may have more extensive material control and accounting (MC&A) processes than current Light Water Reactor (LWR) designs. This project evaluated the use of Monte Carlo simulations for generating information that could guide the development of MC&A approaches for MSRs. In particular, the current capabilities of MCNP version 6.3 internally coupled with CINDER’90 were assessed for a fast spectrum liquid fueled MSR with online fission product removal and refueling. The fission product removal and refueling was performed in batches, and a Python wrapper was developed to control the simulations and update the fuel composition.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Optimal Energy Scheduling and Sensitivity Analysis for Integrated Power-Water-Heat Systems

The conventionally independent power, water, and heating networks are becoming more tightly connected, which motivates their joint optimal energy scheduling to improve the overall efficiency of an integrated energy system. However, such a joint optimization is known as a challenging problem with complex network constraints and couplings of electric, hydraulic, and thermal models that are nonlinear and nonconvex. We formulate an optimal power-water-heat flow (OPWHF) problem and develop a computationally efficient heuristic to solve it. The proposed heuristic decomposes OPWHF into subproblems, which are iteratively solved via convex relaxation and convex-concave procedure. Simulation results validate that the proposed framework can improve operational flexibility and social welfare of the integrated system, wherein the water and heating networks respond as virtual energy storage to time-varying energy prices and solar photovoltaic generation. Moreover, we perform sensitivity analysis to compare two modes of heating network control: by flow rate and by temperature. Our results reveal that the latter is more effective for heating networks with a wider space of pipeline parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Large-signal Stability Analysis of Grid-forming Inverters with Equivalent-circuit Models

Here, this paper proposes an energy function-based direct method for large-signal stability assessment of grid-forming (GFM) inverters leveraging an equivalent-circuit representation of all involved control- and physical-layer dynamics. Three different primary controls, a standard inner-current outer-voltage cascaded-control architecture, output LCL filter, and reference-current saturation limiting are featured in the modeling and analysis framework. A composite energy function for the GFM inverter is obtained by summing up individual energy contributions gleaned from the circuit representation. The approach can readily be generalized to different primary controls, output-filter arrangements, and current limiters since it is based on a circuit-theoretic foundation. Numerical simulations validate the efficacy of the approach in estimating the critical clearing time following a large-signal disturbance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2020

Constructing a Testing Application for GWMS

Many of Fermilab’s High Energy Physics experiments require High Throughput Computing to carry out simulations, data reconstruction, and data analysis. Glidein Workflow Management System (GWMS) is a tool that distributes High Throughput Computing. The purpose of GWMS is to provide convenient access to Grid resources and sites. GWMS is coupled to HTCondor. HTCondor is the workload management system that is used for scheduling and job control. Users submit jobs to a local HTCondor queue and GWMS will make sure the job will run on one of the many remote resources.

Neely-Brown, LeRayah↗
DOE OSTI2021

A Modeling Tool to Analyze the Performance of Industrial Cooling Towers

Energy efficiency and energy savings have become an important factor as industries look for ways to save energy and minimize their energy consumption while reducing their carbon footprint. Cooling towers are utilized significantly in industries for either serving chillers or process cooling. Depending on the size of the cooling tower, it can use a surprising amount of energy and water, which is why it is crucial to make sure that the facility has optimized their cooling tower.A modeling tool has been developed to perform a thorough analysis of a cooling tower and its various operations to ensure that the facility has optimized its cooling tower. This model analyzes an annual base case in comparison with the revised case of a cooling tower operation. This modeling tool simulates 8,760 hourly calculations for fan power for various fan controls, water consumption, and pumping energy consumption and demand based on the user’s location and its corresponding Typical Meteorological Year 3 (TMY3) weather data. This model is capable to simulate up to five cooling tower cells as one large tower utilizing one pump or parallel pumping. The successful validated cooling tower model should assist industry to save energy at their facility through their cooling tower, whether they use it for process cooling or heating, ventilation and air conditioning (HVAC) applications. The entering/leaving water temperatures based on a monthly operating schedule or a wet-bulb temperature schedule will be used as inputs, and the model can calculate savings in energy for various conditions including variable-frequency drive (VFD) on the fan/pump, drift eliminators, number of cycles of concentration, reduced water flow rate, etc.

Hooper, Josh↗