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

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Understanding and promoting the reaction kinetics of photothermally driven Diels–Alder reaction with minimized side reactions

The thermoreversible Diels–Alder (DA) reaction involving furan and maleimide precursors has been extensively exploited to develop reversible thermosets for circular economy and additive manufacturing. Recently, applications of photothermal nanoparticles, which can absorb light and generate nanoscale heat, have gained significant attention in driving the Diels–Alder (DA) reaction more efficiently. This approach can be utilized by various applications, for example, solar light-enhanced recycling, self-healing at targeted area, and photothermal 3-D printing. Here, in this work, we address an important fundamental question on the photothermal approach: how does the reaction kinetics of the photothermally driven DA reaction compared to that of the conventional heat driven one? We found that the forward DA reaction kinetics varies dramatically depending on a type of heat sources, i.e., light-induced photothermal heat or conventional heat, despite of a similar bulk temperature. We observed that the light-induced photothermal heat significantly enhances the DA reaction rate in comparison to the bulk heating in an inert environment. On the contrary, the photothermally driven forward DA reaction is significantly slower than that of the heat driven reaction in the presence of oxygen. This is attributed to the photoexcited electrons in photothermal nanoparticles that can generate singlet oxygen ( 1 O 2 ) in the presence of visible light. This singlet oxygen may facilitate an endoperoxide side reaction on the furan group, ultimately, retard the DA reaction from the furan group. These results reveal the effectiveness of photothermal nanoparticles in accelerating DA reaction while underscoring the need to minimize oxygen exposure to prevent unfavorable side reactions.

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

Powers of magnetic graph matrix: Fourier spectrum, walk compression, and applications

Magnetic graphs, originally developed to model quantum systems under magnetic fields, have recently emerged as a powerful framework for analyzing complex directed networks. Existing research has primarily used the spectral properties of the magnetic graph matrix to study global and stationary network features. However, their capacity to model local, nonequilibrium behaviors, often described by matrix powers, remains largely unexplored. We present a combinatorial interpretation of the magnetic graph matrix powers through directed walk profiles—counts of graph walks indexed by the number of edge reversals. Crucially, we establish that walk profiles correspond to a Fourier transform of magnetic matrix powers. The connection allows exact reconstruction of walk profiles from magnetic matrix powers at multiple discrete potentials, and more importantly, an even smaller number of potentials often suffices for accurate approximate reconstruction in real networks. This shows the empirical compressibility of the information captured by the magnetic matrix. This fresh perspective suggests further applications; for example, we illustrate how powers of the magnetic matrix can identify frustrated directed cycles (e.g., feedforward loops) and can be effectively employed for link prediction by encoding local structural details in directed graphs.

complex networks↗
DOE OSTI2026

Data-driven Mori–Zwanzig modeling of Lagrangian particle dynamics in turbulent flows

The dynamics of Lagrangian particles in turbulence play a crucial role in mixing, transport, and dispersion in complex flows. Their trajectories exhibit highly nontrivial statistical behavior, motivating the development of surrogate models that can reproduce these trajectories without incurring the high computational cost of direct numerical simulations of the full Eulerian field. This task is particularly challenging because reduced-order models typically lack access to the full set of interactions with the underlying turbulent field. Novel data-driven machine learning techniques can be powerful in capturing and reproducing complex statistics of the reduced-order/surrogate dynamics. In this work, we show how one can learn a surrogate dynamical system that is able to evolve a turbulent Lagrangian trajectory in a way that is point-wise accurate for short-time predictions (with respect to Kolmogorov time) and stable and statistically accurate at long times. This approach is based on the Mori–Zwanzig formalism, which prescribes a mathematical decomposition of the full dynamical system into resolved dynamics that depend on the current state and the past history of a reduced set of observables, and the unresolved orthogonal dynamics due to unresolved degrees of freedom of the initial state. We show how by training this reduced order model on a point-wise error metric on short time-prediction, we are able to correctly learn the dynamics of Lagrangian turbulence, such that also the long-time statistical behavior is stably recovered at test time. This opens up a range of applications, for example, for the control of active Lagrangian agents in turbulence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Cone beam neutron interferometry: From modeling to applications

Phase-grating moiré interferometers (PGMIs) have emerged as promising candidates for the next generation of neutron interferometry, enabling the use of a polychromatic beam and manifesting interference patterns that can be directly imaged by existing neutron cameras. However, the modeling of the various PGMI configurations is limited to cumbersome numerical calculations and backward propagation models which often do not enable one to explore the setup parameters. Here we generalize the Fresnel scaling theorem to introduce a k -space model for PGMI setups illuminated by a cone beam, thus enabling an intuitive forward propagation model for a wide range of parameters and experimental setups. The interference manifested by a PGMI is shown to be a special case of the Talbot effect, and the optimal fringe visibility is shown to occur at the moiré location of the Talbot distances. We derive analytical expressions for the contrast and the propagating intensity profiles in various conditions and provide the first analysis of the PGMI dark-field imaging signal when considering sample characterization. The model's predictions are compared to experimental measurements and good agreement is found between them. Last, we propose and experimentally verify a method to recover contrast at typically inaccessible PGMI autocorrelation lengths. The presented work provides a toolbox for analyzing and understanding existing PGMI setups and their future applications, for example extensions to two-dimensional PGMIs and characterization of samples with nontrivial structures. Published by the American Physical Society 2024

Sarenac, D. (ORCID:0000000185753367)↗
DOE OSTI2024

Fusion Neutron Generator

The proposed code, named FROG (Fusion neutron Generator) is built upon the open-source particle transport Monte Carlo toolkit Geant4. Geant4 provides C++ classes that can be leveraged to build application-specific codes dealing with the transport of particles through matter. Geant4-based codes are applied in high-energy particle physics experiments, medical applications, shielding, and space applications for example. The FROG code allows the user to define the geometry of a neutron converter device shaped as a hollow cylinder, where a neutron breeding material such as lithium deuteride (LiD) is cladded by two concentric cylinders. Such neutron converter is then placed inside a regular nuclear fission reactor, where thermal neutrons will react with the neutron breeder material (typically, Lithium 6), and through a series of reactions, will generate high-energy neutrons – neutrons whose kinetic energy are around 14 MeV. The hollowed central portion can hold a specimen that will be bombarded by high-energy neutrons created inside the neutron breeding material. Figuratively speaking, this type of device transforms neutrons from thermal (~0.625 eV) to fusion (~14 MeV) energies and is sometimes termed “fusion-to-thermal neutron converters” in the literature. The code consists of C++ source file compiled and linked to generate an executable. The user can select the dimensions of the converter (radius, length, and thickness of the breeder material), the breeder material type, the cladding material, and the specimen material that will be activated or irradiated. As input, the neutron flux for a specific location inside a reactor, for instance, positions in ATR, is required. As output, the code predicts the number of high-energy neutrons produced, the total neutron flux and fluence as well as its detailed spectrum. The physics involved in such device is very complex, as it requires modeling neutron transport, light-ion (tritons) transport, as well as fusion reactions. The Geant4 toolkit provides the required physical models.

Martin, NicholasP. [Idaho National Laboratory (INL↗
DOE OSTI2024

Particle accelerator spin-transparent storage rings for beyond state-of-the-art science

We describe spin-transparent storage rings that exhibit coherence times of many hours and store a large number of particles and their use in novel applications. For example, these rings can be used to directly measure the electric dipole moment of the electron, relevant to CP violation and matter-antimatter asymmetry in the universe, and to search for axion-mediated forces. These rings can also serve as a compelling platform for quantum computing. In particular, we will describe how spin-transparent rings can be used in conjunction with ion traps to enhance scalability and increase quantum-coherence times of ion quantum computing.

Suleiman, R.↗
DOE OSTI2024

Particle Accelerator Spin-Transparent Storage Rings for Beyond State-of-the-Art Science

We will describe spin-transparent storage rings that exhibit spin-coherence times of several hours and store a large number of particles and their use in novel applications. For example, these rings can be used to directly measure the electric dipole moment of the electron, relevant to CP violation and matter-antimatter asymmetry in the universe, and to search for dark energy and ultra-light dark matter*. These rings can also serve as a compelling platform for quantum computing. In this presentation, we will describe how spin-transparent rings can be used in conjunction with ion traps to enhance scalability and increase quantum coherence times of ion quantum computing.

Suleiman, R.↗
DOE OSTI2025

DOE FAIR Surrogate Benchmarks Supporting AI and Simulation Research (SBI Surrogate Benchmark Initiative) (Final Report)

Computational Science is being revolutionized by integrating AI and simulation and, in particular, by deep learning surrogate models that can replace all or part of traditional large‐scale HPC computations. Such surrogates can achieve remarkable performance improvements, as much as several orders of magnitude, and save both compute time and energy. The Surrogate Benchmark Initiative (SBI) project creates a community repository and FAIR (Findable, Accessible, Interoperable, and Reusable) data ecosystem for HPC application surrogate benchmarks. The SBI team comes from Argonne National Laboratory (ANL), Indiana University (IU), Rutgers University, the University of Tennessee, Knoxville (UTK), and the University of Virginia(UVA). SBI repositories include data, code, and all relevant collateral artifacts, that the science and engineering community needs to use and reuse these data sets and surrogates. SBI repositories generate active research from both participants in SBI and the broader AI and domain science communities. This project develops surrogates that use several different neural nets to learn and quickly infer the results of simulations and data systems and capture them as surrogate benchmarks with a rich set of metadata, covering. Data; Model; Metrics specification; Machine specification; Science, Speed, Power Results, We research FAIR metadata for these benchmarks. We develop application surrogate examples as benchmarks across many fields (ANL, UTK, IU, UVA). We also study non Surrogate benchmarks that have many common features and similar issues regarding FAIRness. We work with MLCommons (UVA, UTK), which is a major machine learning benchmarking activity where we get metadata ontologies, software, and benchmarks, benchmarks have datasets, models, and metadata, and they need a technical framework developed by UTK and Rutgers and deployed by UVA. We study features of Surrogates, including performance, training set size, and uncertainty quantification (Rutgers, UVA and IU).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

FAIR Surrogate Benchmarks Supporting AI and Simulation Research (Final Report)

Computational Science is being revolutionized by integrating AI and simulation and, in particular, by deep learning surrogate models that can replace all or part of traditional large‐scale HPC computations. Such surrogates can achieve remarkable performance improvements, as much as several orders of magnitude, and save both compute time and energy. The Surrogate Benchmark Initiative (SBI) project creates a community repository and FAIR (Findable, Accessible, Interoperable, and Reusable) data ecosystem for HPC application surrogate benchmarks. The SBI team comes from Argonne National Laboratory (ANL), Indiana University (IU), Rutgers University, the University of Tennessee, Knoxville (UTK), and the University of Virginia (UVA). SBI repositories include data, code, and all relevant collateral artifacts that the science and engineering community need to use and reuse these data sets and surrogates. SBI repositories generate active research from both the participants in SBI and the broad community of AI and domain scientists. This project develops surrogates that use several different neural nets to learn and quickly infer the results of simulations and data systems and captures them as surrogate benchmarks with a rich set of metadata covering: Data; Model; Metrics specification; Machine specification; and Science, Speed, and Power Results. We research FAIR metadata for these benchmarks. We develop application surrogate examples as benchmarks across many fields (ANL, UTK, IU, UVA). We also study non-Surrogate benchmarks that have many common features and similar issues as regards FAIRness. We work with MLCommons (UVA, UTK), which is a major machine learning benchmarking activity where we get metadata ontologies, software, and benchmarks, Benchmarks have datasets, models, and metadata and they need a technical framework developed by UTK and Rutgers and deployed by UVA. We study features of Surrogates including performance, training set size, and uncertainty quantification (Rutgers, UVA and IU).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Review of recent WEC-Sim (v6.1) advanced features

WEC-Sim (Wave Energy Converter SIMulator) is an opensource software for modeling the motions, loads and power generation of wave energy converters. WEC-Sim performs simulations in the time domain using hydrodynamic coefficients calculated by boundary element method (BEM) frequency-domain potential flow solvers such as WAMIT, NEMOH, Capytaine, or Ansys AQWA. WEC-Sim development is ongoing, including various features, applications, and example cases used to demonstrate potential use-cases to meet the needs of the growing marine energy industry. Through input from a broad user base and an extensive team of developers and collaborators, new features of WEC-Sim are developed to expand the software’s use cases and improve overall functionality. Three new WEC-Sim features highlighted in this paper include updating WEC-Sim to be compatible with MoorDyn Version 2, incorporation of second order excitation loads (quadratic transfer functions) and allowing for dynamically changing hydrodynamics.

13 HYDRO ENERGY↗
NASA NTRS1972

Constant tension device for gravity simulation

Mechanical device for simulating lunar gravitation is described. Details of construction are illustrated and example of application is provided. Device works opposite to effects of earth gravity and produces effects similar to lunar conditions by providing mechanical lifting forces.

Orlowski, W. F.↗
NASA NTRS1972

Two-dimensional area scanning with image dissectors.

An image dissector system for direct two-dimensional area scanning has been fabricated and is briefly described. Examples of application to direct scanning and digitization of photographic images are given.

Tifft, W. G.↗
NASA NTRS1972

Some remarks on elastic crack-tip stress fields.

It is shown that if the displacement field and stress intensity factor are known as functions of crack length for any symmetrical load system acting on a linear elastic body in plane strain, then the stress intensity factor for any other symmetrical load system whatsoever on the same body may be directly determined. The result is closely related to Bueckner's (1970) weight function, through which the stress intensity factor is expressed as a sum of work-like products between applied forces and values of the weight function at their points of application. An example of the method is given wherein the solution for a crack in a remotely uniform stress field is used to generate the expression for the stress intensity factor due to an arbitrary traction distribution on the faces of a crack. A corresponding theory is developed in an appendix for three-dimensional crack problems, although this appears to be directly useful chiefly for problems in which there is axial symmetry.

Rice, J. R.↗
NASA NTRS1973

Minimal hardware, binary sequence pseudonoise generator and detector

General purpose sequence generator which includes 35-stage field shift register determines mathematical properties of polynomials such as divisibility, period, order of roots, and other parameters that effect desirability of various sequences for specific applications; for example, irreducible polynomials which characterize sequences with randomness properties.

Perlman, M.↗
NASA NTRS1972

Methodology for the systems engineering process. Volume 3: Operational availability

A detailed description and explanation of the operational availability parameter is presented. The fundamental mathematical basis for operational availability is developed, and its relationship to a system's overall performance effectiveness is illustrated within the context of identifying specific availability requirements. Thus, in attempting to provide a general methodology for treating both hypothetical and existing availability requirements, the concept of an availability state, in conjunction with the more conventional probability-time capability, is investigated. In this respect, emphasis is focused upon a balanced analytical and pragmatic treatment of operational availability within the system design process. For example, several applications of operational availability to typical aerospace systems are presented, encompassing the techniques of Monte Carlo simulation, system performance availability trade-off studies, analytical modeling of specific scenarios, as well as the determination of launch-on-time probabilities. Finally, an extensive bibliography is provided to indicate further levels of depth and detail of the operational availability parameter.

Nelson, J. H.↗
NASA NTRS1973

Radiation measurements from polar and geosynchronous satellites

During the 1960's, radiation budget measurements from satellites have allowed quantitative study of the global energetics of our atmosphere-ocean system. A continuing program is planned, including independent measurement of the solar constant. Thus far, the measurements returned from two basically different types of satellite experiments are in agreement on the long term global scales where they are most comparable. This fact, together with independent estimates of the accuracy of measurement from each system, shows that the energy exchange between earth and space is now measured better than it can be calculated. Examples of application of the radiation budget data were shown. They can be related to the age-old problem of climate change, to the basic question of the thermal forcing of our circulation systems, and to the contemporary problems of local area energetics and computer modeling of the atmosphere.

Vonderhaar, T. H.↗
NASA NTRS1972

Stability analysis of Riccati covariance equations of Kalman filter.

The present paper takes the basic mathematical approach to analyze the stability of Riccati equations. First, a simple stability criterion like that of the linear constant coefficient system is sought for the nonlinear constant Riccati Equation. Then, a complete analysis on the limiting covariance P follows. The analysis is focussed on the main theorem. Finally, the computational aspects of the Riccati equations are analyzed with examples. The application of this analysis is to provide a simple stability criterion for the Kalman filter computation to test and predict filter convergence and thus modify filter parameters accordingly.

Teng, L.↗