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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Home energy management under realistic and uncertain conditions: A comparison of heuristic, deterministic, and stochastic control methods

We report home energy management systems (HEMS) have been shown to reduce energy bills and to provide grid services including peak demand reduction and demand flexibility. However, uncertainty in residential energy systems is a significant issue and can reduce the benefits of a HEMS to the homeowner or grid operator. Sources of uncertainty include weather forecasts, predictions of energy-related occupant activities (e.g., hot water draws), and parameter estimation for the building envelope and energy-consuming equipment. This paper tackles the problem of uncertainty by developing a framework that simulates HEMS in uncertain conditions and evaluates the performance of multiple control strategies. A linear, reduced-order residential building model for model predictive control applications is derived and compared to a full-order model. Stochastic model predictive control is shown to perform better than deterministic and heuristic methods when considering realistic forecasts with uncertainty. The framework can evaluate the performance of HEMS in real-world applications, which can help de-risk HEMS deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Microgrid Frequency Stability: A Proactive Scheme Based on Dynamic Predictions

The dynamic nature of microgrids introduces challenges in the context of frequency stability. This work presents a framework where the future state of microgrid frequency is predicted and corrective actions are optimized. Predictions are generated through Bayesian filters leveraging synchronized data acquired via PMUs. Taking a proactive approach makes it possible to optimize corrective actions considering dynamic system conditions. Testing is conducted via Matlab simulations. The performance of the solution presented in this work is compared to traditional load-shedding schemes and to predictive solutions found in literature. The results indicate that the proposed framework outperforms both. Some of the advantages of this framework include a reduction in amount of load dropped during compensation, the use of adaptive parameters which eliminates the need to simulate contingency conditions, and dynamic uncertainty quantification provided the particle filter.

Paramo, Gian↗
DOE OSTI2025

Multi-faceted framework for extrapolating early age flexural strength to facilitate rapid lifting/handling of high-volume fly ash precast members

Maintaining adequate early-age structural performance for precast concrete components has grown in importance as more sustainable mix designs become more widespread. Achieving high-early flexural strength is particularly crucial to facilitate rapid removal of hardened concrete components from formwork, often within 24 h after fresh concrete placement. Limited research has assessed the effectiveness of traditional design methods in correlating flexural strength with compressive strength for next-generation mix designs, or demonstrated extrapolation of such material performance to larger-scale structural tests. This paper presents a multi-faceted framework to reassess early-age flexural strength for concretes made with relatively high proportions of fly ash from both fresh and harvested sources. Here, the framework provides several pathways, from which the user can select based upon available resources and the specific application, to improve accuracy of early-age cracking moment calculations. Furthermore, the scope includes evaluation of strength performance under curing conditions emulative of those in a precast facility, recommending modulus of rupture equations which are more performance-driven than current design provisions, and experimental tests on prefabricated concrete beams to validate the proposed methodologies. Correlations of early-age strength with both concrete age and maturity measurements compare the effectiveness of utilizing in-situ data to further enhance the prediction methods. Ultimately, the proposed framework helped reduce errors when calculating cracking moment capacity at early ages by tailoring calculations to reflect mix-dependent behavior. Furthermore, most estimates of cracking moment were within 25 % of their corresponding experimental test results, thus promoting confidence for using these strategies with high-volume fly ash precast structures.

42 ENGINEERING↗
DOE OSTI2022

System benefits of industrial battery storage: A comparison of grid and facility control and dispatch

Customer-owned, distributed battery installations are being incentivized by utilities to increase installed battery capacity. In many of these incentive agreements, the battery owner relinquishes battery control to the utility in exchange for incentive money. The industrial sector has lagged in storage installation when compared to the residential and commercial sectors. This study compares the economic advantages to utilities and industrial facilities in different dispatch control situations. The study presents a novel framework for the optimization of multiple systems using load profiles from the industrial, residential, and commercial sectors. Case studies are presented to illustrate different dispatch scenarios. Further, the simulations showed more fiscal benefit for the industrial facilities to dispatch the battery for electrical demand reduction than utility dispatch. In the case studies, facility dispatch control resulted in an increase of facility savings by a factor of about 8.7 when compared to utility dispatch. Battery size plays a significant factor on the impact of the grid’s generating costs, showing that larger batteries can provide significant benefit even if dispatched by the facility. Future policies concerning industrial battery installations should consider overall economic benefits to utility and facility in the form of rate structures and incentive participation based on battery size.

25 ENERGY STORAGE↗
DOE OSTI2023

Robust Vector BOTDA Signal Processing with Probabilistic Machine Learning

This paper presents a novel probabilistic machine learning (PML) framework to estimate the Brillouin frequency shift (BFS) from both Brillouin gain and phase spectra of a vector Brillouin optical time-domain analysis (VBOTDA). The PML framework is used to predict the Brillouin frequency shift (BFS) along the fiber and to assess its predictive uncertainty. We compare the predictions obtained from the proposed PML model with a conventional curve fitting method and evaluate the BFS uncertainty and data processing time for both methods. The proposed method is demonstrated using two BOTDA systems: (i) a BOTDA system with a 10 km sensing fiber and (ii) a vector BOTDA with a 25 km sensing fiber. The PML framework provides a pathway to enhance the VBOTDA system performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Advances in benchmarking and round robin testing for PEM water electrolysis: Reference protocol and hardware

While the number of publications in the PEM water electrolysis community increases each year, no common ground concerning reference hardware (test cells and test bench) and testing protocols has been yet established. This would, however, be necessary for the comparability of experimental results. First attempts for such reference hardware and procedures have been made in the framework of the Task 30 Electrolysis within the Technology Collaboration Programme on Advanced Fuel Cells (AFC TCP) of the International Energy Agency (IEA). Since then, improvements of both the test hardware (test cell and components) as well as the measurement protocol were identified, and a revised methodology and key results based on a comprehensive measurement series have been obtained. A detailed protocol for testing commercial reference components with a reference laboratory test cell developed in-house by Fraunhofer ISE is presented. For evaluation of the protocol and the hardware, it was tested at three different institutions at the same time. Impedance spectroscopic and polarization data was acquired and analyzed. The obtained differences in performance were calculated to give the community an expectation window to compare own data to. Finally, the importance of a thorough temperature control and the conditioning phase are demonstrated.

08 HYDROGEN↗
DOE OSTI2026

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗
DOE OSTI2025

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom

Energy-efficient ventilation control plays an important role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate representations of indoor airflow, their high computational cost limits their use in real-time building control. In this work, we present a neural operator learning framework that combines the physical accuracy of CFD with the computational efficiency of machine learning to enable building ventilation control with the high-fidelity fluid dynamics models. Our method jointly optimizes the airflow supply rates and vent angles to reduce energy use and adhere to air quality constraints. We train an ensemble of neural operator transformer models to learn the mapping from building control actions to airflow fields using high-resolution CFD data. This learned neural operator is then embedded in an optimization-based control framework for building ventilation control. Experimental results show that our approach achieves significant energy savings compared to maximum airflow rate control, rule-based control, as well as data-driven control methods using spatially averaged CO 2 prediction and deep learning–based reduced-order models, while consistently maintaining safe indoor air quality. These results highlight the practicality and scalability of our method in maintaining energy efficiency and indoor air quality in real-world buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

ReaxFF-based molecular dynamics study of bio-derived polycyclic alkanes as potential alternative jet fuels

This work investigates the initial stages of the pyrolysis of HtH-1 (C 18 H 32 ; 2,2,7,7,8a,8b-hexamethyl-dodecahydrobiphenylene) and HtH-2 (C 18 H 34 ; 1,1',3,3,3',3'-hexamethyl-1,1'-bi(cyclohexane)), which are bio-derived polycyclic alkanes and potential jet fuels, using ReaxFF force field based molecular dynamics (MD) simulations. Global Arrhenius parameters, such as activation energies and pre-exponential factors, are calculated and used to analyze the overall decomposition kinetics of the fuels. HtH-1 decomposes faster than HtH-2 at the same temperature and density conditions, and they have a faster decomposition rate compared to some existing jet-fuels, such as JP-10. A systematic reaction analysis framework developed in this work is applied to determine a temperature-dependent decomposition mechanism. At lower temperature, the central C-C bond connecting the two cyclohexane rings is dominantly broken in both HtH-1 and HtH-2. However, C-CH 3 bond breaking becomes dominant with increasing temperature due to the large increase in entropy during this reaction. Major products from HtH-1 are C 5 H 8 and C 4 H 8 , and those from HtH-2 are C 4 H 8 and C 2 H 4 . The major products predict that HtH-1 has a higher sooting tendency than HtH-2, which is consistent with measurements. The impact of HtH-2 on the pyrolysis of HtH-1 is also investigated in their binary mixtures. HtH-1 and HtH-2 decompose by unimolecular reactions, and they rarely interact with each other during the pyrolysis of the mixtures. Furthermore, this work demonstrates that ReaxFF can be used to investigate pyrolysis and combustion chemistry of existing or future fuels and to contribute to the development of their chemical kinetic models without any a priori input and chemical intuition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

X-ray absorption spectroscopy of trivalent Eu, Gd, Tb, and Dy chlorides and oxychlorides

Growing interest in next generation molten salt nuclear reactors necessitates a fundamental understanding of the chemical and physico-chemical properties of fission products, including elements of the lanthanide series. In this study, we probed coordination environment of Eu, Gd, Tb, and Dy in their chloride salts with both laboratory and synchrotron scale X-ray absorption spectroscopy (XAS). Here the aerobic melting was carried out with LnCl 3 ·nH 2 O, where Ln is Eu, Gd, Tb, and Dy, and yielded predominant formation of oxychlorides (LnOCl), that was confirmed by extended X-ray absorption fine structure (EXAFS) analysis and X-ray diffraction (XRD). Density functional theory (DFT) and time-dependent density functional theory (TDDFT) computations were performed to obtain ground state structures, lattice parameters, and to simulate L 3 -edge XANES (X-ray absorption near edge structure) spectra of the LnCl 3 ·nH 2 O and LnOCl. A blue shift, initially predicted by our calculations, was also observed for the experimental Ln L 3 -edge XANES spectra of the hydrated trichlorides vs oxychlorides, highlighting the power of combining the predictive ability of theory with experiment to elucidate the properties of the compounds of interest. The blue shift is indicative of structural stabilization of LnCl 3 ·nH 2 O due to higher symmetry compared with LnOCl. To the best of knowledge, this is a first study providing the framework for fundamental insights into the structure of Ln trichlorides and oxychlorides in support of future characterization of lanthanides in the molten salt environment.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ammonia Synthesis by a Supported Iron-Lithium Hydride Precatalyst: Silicon Nitride Support Enabled Synthesis and Nitrogen Reservoir Dynamics

Amorphous silicon nitride (Si 3 N 4 ) is an unconventional support for the chemisorption of organometallic complexes and offers potential improvements in active site stability and reactivity through enhanced metal-nitrogen covalency and orbital overlap in bonding interactions with the nitride framework. Here, we show that silicon nitride-supported iron mesityl complexes display divergent reactivity compared to their silica-supported homologues, resisting metallic particle formation under reducing pretreatment conditions (exposure to excess organolithium reagents) and maintaining active iron/lithium speciation under ammonia synthesis conditions that is absent on the oxide support. When the organometallic iron complex on silicon nitride is exposed to excess n-butyllithium, iron remains isolated, catalyzing the conversion of butyllithium to lithium hydride, resulting in a divalent iron site in a polyhydride environment. In contrast, the silica-supported complex is converted to reduced iron clusters without forming persistent isolated hydrides. These structural differences lead to markedly different catalytic behaviors under ammonia synthesis conditions. The Li/Fe/Si 3 N 4 catalyst is highly active (7.5 mol NH 3 /mol Fe/h at 300 °C, 10 bar, or 46 mol NH 3 /mol Fe/h at 400 °C, 10 bar), while both the silica-supported analog and the nonlithiated Si 3 N 4 -supported species are inactive. Notably, this activity is enhanced relative to previously reported iron-lithium hydride composite catalysts (0.43–4.1 mol NH 3 /mol Fe/h at 300 °C, 10 bar) and relative to the industrial benchmark promoted iron catalyst KM1 (3.0 mol NH 3 /mol Fe/h at 400 °C, 10 bar). The catalyst activation and LiH/LiNH x nitrogen reservoir dynamics for Li/Fe/Si 3 N 4 are studied by X-ray Absorption, Mössbauer, and in situ DRIFT spectroscopies and isotopic exchange kinetics.

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

Photocatalytic Ammonia Synthesis using Fe-Based MOFs: The Role of Ligand Functionalization

Photocatalytic ammonia (NH 3 ) synthesis offers a carbon-neutral alternative to the Haber−Bosch process, which generates 42 million metric tons of CO 2 equivalent emissions annually. However, solar-to-ammonia conversion with contemporary photocatalysts remains far from practical requirements, and understanding the limiting factors in systems with well-defined active sites is crucial. Here, we show how the μ 3 -oxo-centered trinuclear Fe cluster in MIL-101(Fe) functions as the catalytic motif for N 2 -to-NH 3 conversion through combined experimental and computational investigations. Comparative studies with a molecular analogue demonstrate that the cluster is stabilized within the MOF framework, sustaining redox cycling and maintaining high catalytic activity. We systematically functionalized the dicarboxylate ligands of MIL-101(Fe) with −NH 2 , −Br, −NO 2 , −F, and −CF 3 to probe how ligand chemistry modulates Fe electron density, N 2 adsorption capacity, and proton availability, correlating these properties with catalytic performance using spectroscopic and surface characterization techniques alongside timeresolved infrared to assess excited-state lifetimes. F-functionalization optimally balances N 2 activation, proton availability at Fe active sites, and excited-state lifetimes, boosting NH 3 production by ∼ 60% relative to unmodified MIL-101(Fe). This study of ligandfunctionalized MIL-101(Fe) MOFs uncovers the underlying structure-activity relationships and advances design principles for solardriven NH 3 synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Proof-of-concept of a reinforcement learning framework for wind farm energy capture maximization in time-varying wind

Here, we present a proof-of-concept distributed reinforcement learning framework for wind farm energy capture maximization. The algorithm we propose uses Q-Learning in a wake-delayed wind farm environment and considers time-varying, though not yet fully turbulent, wind inflow conditions. These algorithm modifications are used to create the Gradient Approximation with Reinforcement Learning and Incremental Comparison (GARLIC) framework for optimizing wind farm energy capture in time-varying conditions, which is then compared to the FLOw Redirection and Induction in Steady State (FLORIS) static lookup table wind farm controller baseline.

17 WIND ENERGY↗
DOE OSTI2025

A semi-analytic estimate for the effective sound speed counterterm in the EFTofLSS

The Effective Field Theory of Large Scale Structure (EFTofLSS) has found tremendous success as a perturbative framework for the evolution of large scale structure, and it is now routinely used to compare theoretical predictions against cosmological observations. The model for the total matter field includes one nuisance parameter at 1-loop order, the effective sound speed, which can be extracted by matching the EFT to full N-body simulations. In this work we first leverage the Layzer-Irvine cosmic energy equation to show that the equation of state can be exactly computed with knowledge of the fully nonlinear power spectrum. When augmented with separate universe methods, we show one can estimate the effective sound speed. This estimate is in good agreement with simulation results, with errors at the few tens of percent level. Here, we apply our method to investigate the cosmology dependence of the effective sound speed and to shed light on what cosmic structures shape its value.

Cosmological perturbation theory in GR and beyond↗
DOE OSTI2021

The Dark Energy Survey supernova programme: modelling selection efficiency and observed core-collapse supernova contamination

ABSTRACT The analysis of current and future cosmological surveys of Type Ia supernovae (SNe Ia) at high redshift depends on the accurate photometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes an essential step for training and testing photometric classification algorithms, and for correcting biases introduced by selection effects and contamination arising from core-collapse SNe in the photometric SN Ia samples. We use published SN time-series spectrophotometric templates, rates, luminosity functions, and empirical relationships between SNe and their host galaxies to construct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark Energy Survey (DES) 5-yr photometric SN sample, comparing our simulations of DES with the observed DES transient populations. We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data. We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and before photometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation, we find that the predicted contamination varies from 7.2 to 11.7 per cent, with an average of 8.8 per cent and an r.m.s. of 1.1 per cent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveys without fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmology analysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associated systematic uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Meta-virus resource (MetaVR): expanding the frontiers of viral diversity with 24 million uncultivated virus genomes

Viruses are ubiquitous in all environments and impact host metabolism, evolution, and ecology, although our knowledge of their biodiversity is still extremely limited. Viral diversity from genomic and metagenomic datasets has led to an explosion of uncultivated virus genomes (UViGs) and the development of specialized databases to catalog this viral diversity, though many lack comprehensive integration. Here, we introduce meta-virus resource (MetaVR), the successor of the IMG/VR database, designed to overcome previous limitations such as large-scale querying and programmatic access. Drawing on the increase of publicly available genomes and metagenomes, MetaVR significantly expands viral diversity, now comprising 24,435,662 UViGs, a 57.6% increase from its predecessor, organized into over 12 million viral operational taxonomic units. Key enhancements include the integration of curated eukaryotic host information, the integration of protein clusters and predicted structures for comparative studies, and an API for programmatic data access. Furthermore, MetaVR features an updated taxonomic framework based on ICTV release 39, assignment to Baltimore classes, and enhanced host assignment through novel computational tools like iPHoP. These advancements position MetaVR as a unique resource for exploring viral diversity, evolution, and host interactions across diverse environments. MetaVR can be freely accessed at https://www.meta-virome.org/.

Fiamenghi, Mateus B↗
DOE OSTI2024

Performance analysis of superconductor-constriction-superconductor transmon qubits

Here, this work presents a computational analysis of a superconducting transmon qubit design, in which the superconductor-insulator-superconductor (SIS) Josephson junction is replaced by a coplanar, superconductor-constriction-superconductor (ScS) nanobridge junction. Within the scope of Ginzburg-Landau theory, we find that the nanobridge ScS transmon has an improved charge dispersion compared to the SIS transmon, with a tradeoff of smaller anharmonicity. These calculations provide a framework for estimating the superconductor material properties and junction dimensions compatible with gigahertz frequency ScS transmon operation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimal Economic Dispatch and Load-Following Strategies for Nuclear Integrated Energy Systems

The need for distributed and adaptable energy resources that can handle the growing unpredictability in both supply and demand is rising as the power system continues to modernize. In order to satisfy those needs and maintain grid resilience, nuclear power plants can dynamically control their output, despite typically being used as baseload generators. By incorporating energy storage and renewable energy sources, nuclear integrated energy systems are designed to satisfy the electrical and thermal demands of different end-user applications while ensuring flexible power operation. These systems generate revenue by participating in both wholesale and ancillary services electricity markets, as well as commodity markets for various byproducts generated from coupled industrial processes. This study addresses the economic dispatch efficiency of a tightly coupled nuclear integrated energy system comprising a gigawatt-scale light water reactor, commercialized in the U.S., a high-temperature steam electrolysis unit, a district heating network, and specified electrical loads. To demonstrate the nuclear power plant’s flexibility within the day-ahead unit commitment and economic dispatch framework, while maintaining equilibrium even during periods of refueling outages, this paper develops a mixed-integer linear programming framework that models the subsystems and components of its nuclear steam supply system. A systematic comparative analysis of flexible versus baseload nuclear power plant operation under varying levels of renewable energy integration indicates that flexible operation enhances system profitability by more than 18% while also increasing energy storage utilization, improving reactor responsiveness to load fluctuations, and allowing for greater participation across numerous electricity markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗