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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Shift Happens: Building Robust AI Models with Domain Adaptation

Artificial Intelligence (AI) is revolutionizing physics research—from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data—exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This summer school session will introduce students to common challenges in applying AI across domains and present solutions based on domain adaptation—a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery. The concepts discussed are broadly applicable across physics and other scientific disciplines, making this a valuable topic for anyone interested in building robust, transferable AI models for science.

Ciprijanovic, A. [Fermilab] (ORCID:000000031281719↗
DOE OSTI2025

AI in Astrophysics: Tackling Domain Shift, Model Robustness and Uncertainty

Artificial Intelligence (AI) is revolutionizing physics research from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This talk will introduce common challenges in applying AI across domains and present solutions based on domain adaptation a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery.

Ciprijanvoic, Aleksandra [Fermilab] (ORCID:0000000↗
DOE OSTI2020

Final Technical Report for project entitled Highly Active, Durable, and Ultra-Low PGM NSTF Thin Film ORR Catalysts and Support

In this project, the objective was to develop new oxygen reduction reaction (ORR) electrocatalysts for proton exchange membrane fuel cells (PEMFCs) which could exceed all of the Department of Energy (DOE) 2020 targets listed in DE-FOA-0001224, Subtopic 1b, Table I. The expected outcome was development of one or more electrocatalysts which are substantially improved over the current state-of-the-art in terms of overall activity, durability, and cost, and are suitable for automotive traction and stationary fuel cell applications. This report summarizes this project’s progress towards meeting the stated objectives and includes a summary of key findings and conclusions. The development activities towards new highly active and durable thin film electrocatalysts has led to the discovery of several electrocatalysts which approached or exceeded several DOE 2020 targets for activity, durability, and performance in proton exchange membrane fuel cell (membrane electrode assemblies (MEAs). In this project, electrocatalyst development focused on systematic physical and electrochemical characterization of electrocatalyst activity, durability, and performance in MEAs as a function of electrocatalyst fabrication, compositional and structural variables. The project approach was to develop relationships between the catalyst functional responses (activity, durability and performance) with catalyst physical properties and catalyst fabrication methods. Additionally, the thin film catalysts were integrated onto the unique and durable 3M Nanostructured Thin Film (NSTF) support, consisting of arrays of self-assembled organic crystalline whiskers. The catalysts were evaluated against the project targets via extensive electrochemical characterization in MEA format at 3M, advanced structural and compositional microscopy at Oak Ridge National Laboratory (ORNL), and atomic structure analysis via XAFS at Argonne National Laboratory (ANL). The extensive electrochemical and physical characterization resulted in development of several trends which correlate the catalysts’ electrochemical properties to their physical properties, including composition, structure, and method of fabrication. The development was guided by density functional theory (DFT) modeling at Purdue University and kinetic Monte Carlo (kMC) modeling at Johns Hopkins University. The catalyst simulations provided key insights into the observed experimental activity and durability trends, and additionally were utilized to assess new electrocatalyst concepts prior to or coincident with physical catalyst development. This development has led to several electrocatalyst candidates with activity and durability which approach or exceed DOE targets. One class of catalysts, based on nm-scale thin layers of Pt on Ir, met or exceeded 6 of the 6 DOE targets the project addressed.

08 HYDROGEN↗
DOE OSTI2022

Universality of a truncated sigma-model

Bosonic quantum field theories, even when regularized using a finite lattice, possess an infinite dimensional Hilbert space and, therefore, cannot be simulated in quantum computers with a finite number of qubits. A truncation of the Hilbert space is then needed and the physical results are obtained after a double limit: one to remove the truncation and another to remove the regulator (the continuum limit). A simpler alternative is to find a model with a finite dimensional Hilbert space belonging to the same universality class as the continuum model (a “qubitization”), so only the space continuum limit is required. A qubitization of the 1 + 1 dimensional asymptotically free O(3) nonlinear σ-model based on ideas of non-commutative geometry was previously proposed [1] and, in this paper, we provide evidence that it reproduces the physics of the σ-model both in the infrared and the ultraviolet regimes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A Novel Approach to Modeling Biomass Pyrolysis in a Fluidized Bed Reactor

A novel approach to simulating biomass pyrolysis in a fluidized bed of mostly inert material is presented. The bed is assumed to be externally heated, although simulation of autothermal operation with partial oxidation of the products is a future objective. Combining pyrolysis reaction kinetics developed by the CRECK Modeling Group and a previously published component properties model, material and energy balances are closed by tracking the residence time of biomass particles without regard for their exact spatial distribution. The model is used to simulate a pilot-scale fluidized bed pyrolysis process being developed at Iowa State University, and model predictions are compared with experimental results for red oak and corn stover feedstocks. The results are in general agreement, with the model typically predicting more noncondensable gas and less low-boiling liquid products. The differences are ascribed to the limitations of the kinetics model. This model provides a rigorous energy balance for fluidized bed pyrolysis processes that can be incorporated into commercial flowsheet models with the capacity for future addition of partial oxidation reactions and implementation of improved kinetics models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Parametric matrix models

We present a general class of machine learning algorithms called parametric matrix models. In contrast with most existing machine learning models that imitate the biology of neurons, parametric matrix models use matrix equations that emulate physical systems. Similar to how physics problems are usually solved, parametric matrix models learn the governing equations that lead to the desired outputs. Parametric matrix models can be efficiently trained from empirical data, and the equations may use algebraic, differential, or integral relations. While originally designed for scientific computing, we prove that parametric matrix models are universal function approximators that can be applied to general machine learning problems. After introducing the underlying theory, we apply parametric matrix models to a series of different challenges that show their performance for a wide range of problems. For all the challenges tested here, parametric matrix models produce accurate results within an efficient and interpretable computational framework that allows for input feature extrapolation.

Computational science↗
NASA NTRS2002

A Deterministic Interfacial Cyclic Oxidation Spalling Model: Algebraic Approximation, Descriptive Parameters, and Normalized Universal Curve - Part 2

A cyclic oxidation interfacial spalling model has been developed in Part 1. The governing equations have been simplified here by substituting a new algebraic expression for the series (Good-Smialek approximation). This produced a direct relationship between cyclic oxidation weight change and model input parameters. It also allowed for the mathematical derivation of various descriptive parameters as a function of the inputs. It is shown that the maximum in weight change varies directly with the parabolic rate constant and cycle duration and inversely with the spall fraction, all to the 1/2 power. The number of cycles to reach maximum and zero weight change vary inversely with the spall fraction, and the ratio of these cycles is exactly 1:3 for most oxides. By suitably normalizing the weight change and cycle number, it is shown that all cyclic oxidation weight change model curves can be represented by one universal expression for a given oxide scale.

Smialek, James L.↗
DOE OSTI2023

Creation of Multiple Effect Evaporator and Combined Cycle Modelica Modules, and Optimization of Potable Water Generation from Saltwater Sources (Final Technical Report)

Modelica models for a Heat Recovery Steam Generator (HRSG) and Multiple Effect Evaporator have been developed. These models have been validated against results from literature and from an actual cogeneration system on the campus of NC State University. The models are capable of connecting to other components to create multi-input, multi-output energy systems with storage, also known as integrated energy systems. An existing 35 MW gas turbine model is connected to the HRSG model created for this project to produce 9 bar steam. The high pressure steam feeds a backpressure steam turbine from the library to generate additional electric power. 2 bar steam leaves the turbine to supply an 8 effect MEE to generate water for a community. As part of the effort, three research papers were submitted (two published in ANS Proceedings and one submitted to Applied Energy).

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

High concentrations of ice: Investigations using polarimetric radar observations combined with in situ measurements and cloud modeling (Final Report)

This DOE-funded joint project had the over-arching goal of understanding the reasons for observed size distributions of ice particles in cold clouds. Its approach involves the use of cloud models and field observations by radar and aircraft of real storms. The project addresses three major research objectives: (1) Utilize a novel polarimetric radar technique to retrieve size distributions and amounts of ice from radar data collected during the previous DOE ARM field campaigns; (2) Evaluate the results of ice microphysical retrievals using available in situ aircraft measurements and other remote sensors (e.g., vertically pointing cloud radars and wind profilers); (3) Improve the treatment of microphysical processes leading to cloud glaciation and ice multiplication in numerical cloud models. The study was performed by three research organizations: University of Oklahoma, The Hebrew University of Jerusalem, Israel, and Lund University, Sweden. The Israel and Swedish partners were funded by the sub-awards from the University of Oklahoma. Cloud modeling studies have been performed by the research teams at The Hebrew University of Jerusalem (HUJ) and Lund University to identify the origins of high concentrations of cloud ice in areas of high ice water content (HIWC). The Hebrew University Cloud Model (HUCM) with full spectral bin microphysics and the Lund University aerosol-cloud (AC) model with a hybrid bin / bulk microphysics scheme complementing HUCM were utilized for simulations. Both research teams had particular focus on secondary ice production (SIP) as one of the possible sources of enhanced ice concentration. The HUJ group suggested a novel concept of ice multiplication during droplet freezing. It is assumed that splintering and droplet fragmentation during droplet freezing takes place because of dendritic growth within a supercooled drop. The resulting simulations of SIP generated small ice in concentrations exceeding hundreds per liter similar to what was observed in the HIWC regions of the tropical storms. The Lund team explored the SIP mechanisms such as breakup of ice particles due to ice-ice collisions and ice sublimation that are expected to dominate the continental storms. They also quantified the impact of homogeneous nucleation of cloud droplets on the total number concentration of ice at very low temperatures near the tops of the clouds. Additionally, the Lund AC model is able to simulate the effect of aerosols of various types (including biological) on the cloud life cycle and the corresponding ice production. The HUCM / AC model was used to simulate one of the “golden” cases of the DOE MC3E campaign on 20 May 2011. The model output was converted into the fields of polarimetric radar variables using the polarimetric radar forward operator developed at the University of Oklahoma and compared with radar observations and in situ microphysical measurements onboard research aircraft. It was demonstrated that specific differential phase KDP is the best radar parameter to identify the HIWC areas and quantify the corresponding ice parameters. For the first time, the shape of the vertical profile of KDP was realistically reproduced by the cloud model with the KDP maximum in the dendritic growth layer (DGL) centered at the -15°C isotherm. The University of Oklahoma team has developed a methodology for polarimetric radar retrievals of such microphysical parameters of ice as ice water content (IWC), mean volume diameter (Dm), and total number concentration (Nt) of ice particles. These retrievals have been validated using in situ aircraft measurements during 6 field campaigns and proved to be quite robust and reliable. This allowed to build the first climatology of the vertical profiles of polarimetric radar variables and retrieved microphysical parameters for the three types of weather systems: continental MCSs, maritime MCSs, and tropical cyclones / hurricanes (Hu and Ryzhkov 2022). The data were collected by a multitude of the WSR-88D radars in 13 continental and 10 maritime MCSs and 11 landfalling hurricanes. The HIWC areas were identified within the examined storms and the corresponding “HIWC statistics” was compared with the “background” one without HIWC. An overarching conclusion of the study is that maritime tropical storms (MCSs and hurricanes) are characterized by smaller size ice in higher concentration compared to the continental MCSs. High ice water content in the HIWC areas is primarily caused by a strong jump in a number concentration of ice particles rather than the increase of their size compared to the “background” environment. This may point to the homogeneous nucleation of excessive amounts of supercooled droplets and / or secondary ice production as the possible origins of HIWC. Such a climatology provides a good observational reference for the modelers to evaluate the performance of their models. As an example, the in-depth analysis of the 20 May 2011 MC3E case shows that the advanced cloud models developed in the course of this study still tend to underestimate the number concentration of ice in the HIWC areas although they succeed in reproducing realistically looking vertical profiles of IWC and Nt. The results of the project research are summarized in 13 journal papers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling of the High Temperature Test Facility PG-26 Transient Using RELAP-7

The High Temperature Test Facility (HTTF) is an electrically heated, helium cooled, experimental facility located at Oregon State University (OSU). Modeling of the HTTF PG-26 transient using a multi-app approach utilizing MOOSE and RELAP-7 was conducted. A 3-D model of the HTTF core, reflector, core barrel, and RPV was generated, and 3-D heat conduction throughout the structure was coupled to 1-D fluid flow results from RELAP-7. The model was able to accurately predict peak ceramic core temperatures experienced during the transient which helps validate the capability of RELAP-7 to model advanced gas-cooled nuclear reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

BuildingsBench: A Benchmark for Universal Building Load Forecasting [SWR-23-51]

The residential and commercial building stock in the United States is responsible for a significant percentage of energy consumption and greenhouse gas emissions. Electrification of end-uses, as well as decarbonizing the electrical grid through renewable energy sources such as solar and wind, constitutes the pathway to zero-emission buildings. Forecasting day-ahead building energy consumption is an integral part of this solution. Currently, specialized forecasting models are hand-made for each individual building, which is time-consuming, expensive, and leads to duplicated efforts. BuildingsBench is a Python software framework for training and comparing generalized machine learning models for universal building load forecasting. This challenge tasks a single foundational model to generalize its forecasts for a wide variety of buildings, across geographic regions, building types, weather patterns, and more. This software provide code for pre-training such models and subsequently evaluating their performance on a suite of hundreds of diverse real and synthetic buildings. BuildingsBench is a platform for: - Large-scale pretraining with the synthetic Buildings-900K dataset for short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock and is extracted from the NREL End-Use Load Profiles database. - Benchmarking on two tasks evaluating generalization: zero-shot STLF and transfer learning for STLF. We provide an index-based PyTorch Dataset for large-scale pretraining, easy data loading for multiple real building energy consumption datasets as PyTorch Tensors or Pandas DataFrames, simple (persistence) to advanced (transformer) baselines, metrics management, and more.

Emami, Patrick↗
NASA NTRS1994

Development and initial test of the University of Wisconsin global isentropic-sigma model

The description of a global version of the University of Wisconsin (UW) hybrid isentropic-sigma (theta-sigma) model and the results from an initial numerical weather prediction experiment are presented in this paper. The main objectives of this initial test are to (1) discuss theta-sigma model development and computer requirements, (2) demonstrate the ability of the UW theta-sigma model for global numerical weather prediction using realistic orography and parameterized physical processes, and (3) compare the transport of an inert trace constituent against a nominally 'identical' sigma coordinate model. Initial and verifying data for the 5-day simulations presented in this work were supplied by the Goddard Earth Observing System (GEOS-1) data assimilation system. The time period studied is 1-6 February 1985. This validation experiment demonstrates that the global UW theta-sigma model produces a realistic 5-day simulation of the mass and momentum distributions when compared to both the identical sigma model and GEOS-1 verification. Root-mean-square errors demonstrate that the theta-sigma model is slightly more accurate than the nominally identical sigma model with respect to standard synoptic variables. Of particular importance, the UW theta-sigma model displays a distinct advantage over the conventional sigma model with respect to the prognostic simulation of inert trace constituent transport in amplifying baroclinic waves of the extratropics. This is especially true in the upper troposphere and stratosphere where the spatial integrity and conservation of an inert trace constituent is severely compromised in the sigma model compared to the theta-sigma model.

Zapotocny, Tom H.↗
NASA NTRS1972

Universal instability associated with the plasmapause and its role in geomagnetic micropulsations.

The observed close correlation between the plasmapause and micropulsations is explained on the basis of a universal instability model. Both theoretical and experimental studies of a nonhomogeneous magnetoplasma indicate that a steep plasma density gradient at the plasmapause is likely the origin of the universal instability in the magnetosphere. Drift waves excited at the plasmapause may be unstable in the direction of the electron drift and propagate eastward nearly perpendicularly to the magnetic field. The drift waves, however, tend to convert very quickly to ion sound or Alfven waves with a much larger phase velocity parallel to the magnetic field. This may be a possible source mechanism for rather regular geomagnetic micropulsations, and specific mechanisms are identified for the long- and short-period cases.

Kikuchi, H.↗
NASA NTRS1979

Spatial quantification of maps or images - Cell size or pixel size implications

The paper discusses spatial quantification of maps or images. Spatial accuracies evaluated by mapping and inventory measures were observed with a range of cell sizes for a 10.36 sq km soil survey segment. The distribution of interboundary distances in a map was evaluated as unique, characterizing information; experimentally observed relationships between accuracy and cell size and interboundary distance distribution parameters and cell size led to a model of the process of spatial quantization. Grid positioning effects were evaluated and were significant only at the level of individual mapping units; two generations of 'universal' process models were derived, implemented, and evaluated.

Wehde, M. E.↗
NASA NTRS1994

A standard satellite control reference model

This paper describes a Satellite Control Reference Model that provides the basis for an approach to identify where standards would be beneficial in supporting space operations functions. The background and context for the development of the model and the approach are described. A process for using this reference model to trace top level interoperability directives to specific sets of engineering interface standards that must be implemented to meet these directives is discussed. Issues in developing a 'universal' reference model are also identified.

Golden, Constance↗
NASA NTRS1991

Modes of interconnected lattice trusses using continuum models, part 1

This represents a continuing systematic attempt to explore the use of continuum models--in contrast to the Finite Element Models currently universally in use--to develop feedback control laws for stability enhancement of structures, particularly large structures, for deployment in space. We shall show that for the control objective, continuum models do offer unique advantages. It must be admitted of course that developing continuum models for arbitrary structures is no easy task. In this paper we take advantage of the special nature of current Large Space Structures--typified by the NASA-LaRC Evolutionary Model which will be our main concern--which consists of interconnected orthogonal lattice trusses each with identical bays. Using an equivalent one-dimensional Timoshenko beam model, we develop an almost complete continuum model for the evolutionary structure. We do this in stages, beginning only with the main bus as flexible and then going on to make all the appendages also flexible-except for the antenna structure. Based on these models we proceed to develop formulas for mode frequencies and shapes. These are shown to be the roots of the determinant of a matrix of small dimension compared with mode calculations using Finite Element Models, even though the matrix involves transcendental functions. The formulas allow us to study asymptotic properties of the modes and how they evolve as we increase the number of bodies which are treated as flexible. The asymptotics, in fact, become simpler.

Balakrishnan, A. V.↗
NASA NTRS1994

A new method for determining the Hubble constant from sub-TeV gamma-ray observations

The present uncertainty in the Hubble constant leaves unresolved questions regarding the age of the universe and related matters involving the amount and nature of the dark matter in the universe, consistency with the inflationary model of the universe, and the need for a cosmological constant. It is clear that a significantly precise determination of the Hubble constant by as many different methods as possible is crucial to our knowledge and understanding of the character of the universe. We propose here an entirely new method for determining the Hubble constant, based on measuring the extinction of high-energy gamma-rays emitted by detectable gamma-ray emitting blazars at various redshifts.

Salamon, M. H.↗
DOE OSTI2022

Control rod modeling in liquid metal-cooled fast reactors

Control rod modeling in Liquid Metal-cooled Fast Reactors (LMFRs) is important for an accurate simulation, especially in depletion calculations. Recently, control rod search and cusping models have been added to the LUPINE multiphysics fast reactor simulator. LUPINE stands for the 'LMFR Utility for Physics Informed Nuclear Engineering' and is currently being developed at North Carolina State University. LUPINE models the coupled multiphysics effects in LMFRs, including neutronics, thermal hydraulics, thermal expansion, and depletion. The control rod search has been implemented using a Newton-secant search in an inexact-Newton iteration and the cusping model uses a polynomial technique to correct for control rod cusping. The control rod cusping and search models were demonstrated by modeling the Advanced Burner Reactor (ABR) MET-1000 Sodium-cooled Fast Reactor (SFR) and a long-life Lead-cooled Fast Reactor (LFR) based on a Westinghouse Electric Company, LLC (WEC) design. A differential control rod worth curve was calculated for both reactor models to demonstrate the control rod cusping model. The SFR and LFR models were used to demonstrate the importance of modeling control rod movement during depletion calculations and the adverse effect of control rods on cycle length is demonstrated. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗