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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Improving Dark Energy Constraints Using Low-Redshift Large-Scale Structures

The primary goal of this project was to improve constraints on dark energy measurements by improving our ability to extract cosmological information from low redshift large-scale structures. PI Clowe's project's primary aim was to reduce the bias in measurements of the masses of clusters of galaxies to a level where the evolution of the cluster mass function can be used in the Vera Rubin Observatory's Legacy Survey of Space and Time Dark Energy Science Collaboration survey to improve the accuracy of the measurement of dark energy and other cosmological parameters. Co-PI Seo's project studied observational systematics affecting large-scale clustering of galaxies, which will be used to improve dark energy constraints from the Dark Energy Spectroscopic Instrument (DESI). The cluster lensing project employed a series of simulations and observations of clusters of galaxies to test numerous potential systematic errors in cluster mass measurements using weak gravitational lensing as the accuracy of current weak lensing measurements are more than order of magnitude worse than what is required to use clusters of galaxies for accurate determination of dark energy parameters. PI Clowe and group developed and analyzed simulations to test for, and correct biases introduced in, the weak lensing measurement process. Finally, PI Clowe and group developed a method of detecting clusters using galaxy overdensities and applied the method to the BLISS and DES surveys. The success of spectroscopic dark energy mission such as the extended Baryon Oscillation Spectroscopic Survey (eBOSS) and the Dark Energy Spectroscopic Instrument (DESI) will depend on a thorough understanding of various observational systematics in the target density fluctuations that would give rise to spurious, non-cosmological signals. PI Seo and group developed a deep learning, artificial neural network (ANN) technique that modeled and mitigated such effects, aimed at deriving more robust galaxy clustering signals not only for the baryon acoustic oscillation feature and redshift-space distortions but also for primordial non-Gaussianity constraint.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Ground-state properties of light 4 n self-conjugate nuclei in ab initio no-core Monte Carlo shell model calculations with nonlocal N N interactions

We report J π = 0 + ground-state energies and point-proton radii of 4 He, 8 Be, 12 C, 16 O, and 20 Ne nuclei calculated by the ab initio no-core Monte Carlo shell model with the JISP16 and Daejeon16 nonlocal NN interactions. Ground-state energies are obtained in the basis spaces up to seven oscillator shells (N shell =7) with several oscillator energies (ℏω) around the optimal oscillator energy for the convergence of ground-state energies. These energy eigenvalues are extrapolated to obtain estimates of converged ground-state energies in each basis space using energy variances of computed energy eigenvalues. We further extrapolate these energy-variance-extrapolated energies obtained in the finite basis spaces to infinite basis-space results with an empirical exponential form. This form features a dependence on the basis-space size but is independent of the value of ℏω used for the harmonic-oscillator basis functions. Point-proton radii for these states of atomic nuclei are also calculated following techniques employed for the energies. From these results, it is found that the Daejeon16 NN interaction provides good agreement with experimental data up to approximately 16 O, while the JISP16 NN interaction provides good agreement with experimental data up to approximately 12 C. Beyond these nuclei, the interactions produce overbinding accompanied by radii that are too small. These findings suggest and encourage further revisions of nonlocal NN interactions towards the investigation of nuclear structure in heavier-mass regions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Synthesizing realistic sand assemblies with denoising diffusion in latent space

Abstract The shapes and morphological features of grains in sand assemblies have far‐reaching implications in many engineering applications, such as geotechnical engineering, computer animations, petroleum engineering, and concentrated solar power. Yet, our understanding of the influence of grain geometries on macroscopic response is often only qualitative, due to the limited availability of high‐quality 3D grain geometry data. In this paper, we introduce a denoising diffusion algorithm that uses a set of point clouds collected from the surface of individual sand grains to generate grains in the latent space. By employing a point cloud autoencoder, the three‐dimensional point cloud structures of sand grains are first encoded into a lower‐dimensional latent space. A generative denoising diffusion probabilistic model is trained to produce synthetic sand that maximizes the log‐likelihood of the generated samples belonging to the original data distribution measured by a Kullback‐Leibler divergence. Numerical experiments suggest that the proposed method is capable of generating realistic grains with morphology, shapes and sizes consistent with the training data inferred from an F50 sand database. We then use a rigid contact dynamic simulator to pour the synthetic sand in a confined volume to form granular assemblies in a static equilibrium state with targeted distribution properties. To ensure third‐party validation, 50,000 synthetic sand grains and the 1542 real synchrotron microcomputed tomography (SMT) scans of the F50 sand, as well as the granular assemblies composed of synthetic sand grains are made available in an open‐source repository.

Vlassis, Nikolaos N.↗
DOE OSTI2020

Toward controlled functional sequencing and hierarchical structuring in imidazolium ionenes

This focused mini-review highlights recent advances related to the design and applications of imidazolium ionenes and forward-looking perspectives. Creative strategies which employ established synthetic approaches and utilize the modularity of the imidazole moiety unlock great potential for tailoring both functional and structural features arising from precise spacing of ionic groups within the polymer backbone. Here, as imidazolium ionenes draw more interest, increased sophistication of chemical modifications and material processing is occurring, with a corresponding shift toward more demanding applications. Synthetic routes for placement and sequencing of ionic content are discussed, in addition to recent approaches to control structure and self-assembly or tune behaviors of imidazolium ionenes and composites.

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

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part I: Model Formulation

Here, this paper formulates a new particle-in-cell method for the Vlasov–Maxwell system. Under the Lorenz gauge condition, Maxwell’s equations for the electromagnetic fields can be written as a collection of scalar and vector wave equations. The use of potentials for the fields motivates the adoption of a Hamiltonian formulation for particles that employs the generalized (conjugate) momentum. A notable advantage offered by the Hamiltonian formulation is the elimination of time derivatives in the Lorenz gauge formulation that are required by the standard Newton–Lorentz treatment of the particles. This allows the fields to retain the full time-accuracy guaranteed by the field solver. The resulting updates for particles require only knowledge of the fields and their spatial derivatives. An analytical method for constructing these spatial derivatives is presented that exploits the underlying integral solution used in the field solver for the wave equations. Moreover, these derivatives are demonstrated to converge at the same rate as the fields in both time and space. The Method of Lines Transpose field solver we consider in this work is globally first-order accurate in time and high-order accurate in space (e.g., fourth- and fifth-order) and belongs to a larger class of methods which are unconditionally stable, can address geometry, and leverage $\mathcal {O}(N)$ fast summation methods for efficiency. We demonstrate the method on several well-established benchmark problems on bounded domains, including a plasma sheath as well as a relativistic particle beam. The efficacy of the proposed formulation is established by comparing with a second-order accurate finite-difference time-domain method that employs a leapfrog time advance for particles and a charge conserving map suitable for bounded domains. The new method shows mesh-independent numerical heating properties even in cases where the plasma Debye length is smaller than the grid spacing. This is an important feature of the new method for problems defined on bounded domains, because it permits the use of coarser grids in space in the representation of the fields. Such a capability has significant implications for the simulation of plasmas in bounded domains with complex geometry, where the ratio between the largest and smallest cells can vary significantly. The use of high-order spatial approximations in the new method also means that fewer grid points are required in order to achieve a fixed accuracy. Our results also suggest that the new method can be used with fewer simulation particles per cell compared to the benchmark explicit method, which permits further computational savings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Optimal CO 2 storage management considering safety constraints in multi-stakeholder multi-site GCS projects: A Markov game perspective

Geological carbon storage (GCS) projects could involve a diverse array of stakeholders or players from public, private, and regulatory sectors, each with different objectives and responsibilities. Given the complexity, scale, and long-term nature of GCS operations, determining whether individual stakeholders can independently optimize their interests — or whether collaborative coalition agreements are needed — remains a central question for effective GCS project planning and management. To access large, high-quality storage resources, future GCS deployment may increasingly occur in geologically connected sites, where shared geological features such as pressure space and reservoir pore capacity can lead to competitive behavior among stakeholders. In this work, we propose a paradigm based on Markov games to quantitatively investigate how different coalition structures affect the goals of stakeholders. We frame this multi-stakeholder multi-site problem as a multi-agent reinforcement learning problem with safety constraints. Our approach enables agents to learn optimal strategies while complying with safety regulations. We present an example where multiple operators are injecting CO 2 into their respective project areas in a geologically connected basin. To address the high computational cost of repeated simulations of high fidelity models, a previously developed surrogate model based on the Embed-to-Control (E2C) framework is employed. Our results demonstrate the effectiveness of the proposed framework in addressing optimal management of CO 2 storage when multiple stakeholders with different objectives and goals are involved.

58 GEOSCIENCES↗
DOE OSTI2023

Automated phase segmentation and quantification of high-resolution TEM image for alloy design

In the alloy design and development process, a wealth of atomically resolved structural high-resolution transmission electron microscopy (HRTEM) images are produced. Identifying the different nano-precipitate phases and tracking their evolution under various compositions and during manufacturing or post-processing requires hundreds of HRTEM images and thousands of precipitates. The nanoscopic phase information labeling and analysis purely relies on humans are prohibitively costly and time-consuming, sometimes not reliable because of the lack of authoritative knowledge. Here, in this work, we develop a novel unsupervised machine learning approach coupled with adaptive computer vision techniques with features in the Fourier space to automatically determine the number of phases and segment/quantify the phases with nanoscale resolution, allowing for quantitative correlation between nanostructure formation, processing and functional properties. To automate the phase extraction/quantification and ascertain its applicability, we have applied the developed framework to the HRTEM images from several alloy systems, processing conditions, image magnifications, and phase types and morphologies (precipitates, nano-twins, stacking faults, crystalline matrix, and amorphous structures) for verification. This study paves the road for compression, visualization, and translation of raw image structural data into physically relevant information in real-time with minimal human supervision. It shows the promise of enabling high-throughput materials characterization for the acceleration of alloy manufacturing and design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Initial calculations for source term of Molten Salt Reactors

This paper provides an overview of the current MSR design space and lists unique features of the various designs under consideration. Some general considerations for source terms calculation for Molten Salt Reactors (MSRs) are explained. Applicability and limitations of terminology currently defined for legacy light water reactor (LWR) systems are discussed in the view of MSRs and the need for updated terminology is discussed. Calculations carried out for the Molten Salt Reactor Experiment (MSRE) are discussed with a qualitative comparison to the designs presented. The nature of the fission products (FPs) and actinides for Low enriched uranium, thorium and fast U/Pu fuel cycles employed in representative molten salt reactor systems are discussed. Computational results are obtained from a code (Serpent 2) with online reprocessing. Divergence in source terms when fission product bubbling is demonstrated. The source release for each molten salt reactor during postulated accidents is also presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Interface Nucleus Templating of Modular Intermetallic Morphologies: Chemical Pressure Complementarity, Columnar Domains, and Complex Disorder in Y 13 Ag 42.7 Zn 29.7

One element of the diversity of intermetallic phases is the formation of complex structures from the assembly of fragments of simpler structures. Recently, we devised the Interface Nuclear Approach as a model for understanding such modular arrangements, in which the intergrowth of different structures is driven by chemical pressure (CP) relief at shared motifs at the domain interfaces, referred to as interface nuclei. In this Article, we present the synthesis, crystal structure, and CP analysis of a new compound that expands on this theme, Y 13 Ag 42.7 Zn 29.7 . Its hexagonal structure contains interpenetrating domains based on the CaPd 5+x and EuMg 5 types. The CaPd 5+x -based regions are reminiscent of the lamellar intergrowth structures previously observed in the Y−Ag−Zn system. In Y 13 Ag 42.7 Zn 29.7 , however, the domains have a different morphology, forming columns that adopt a hexagonal rod-packing. The geometrical features of the remaining spaces are assigned, using the program GrowDomain, to the cores of trigonal units of the EuMg 5 type, while layers of disordered atoms occur at heights along z where the parent structures are mismatched. At the CaPd 5+x -type/EuMg 5 -type interfaces, simple interface nucleus motifs with strong CP-complementarity can be identified, while their distribution within the parent structures supports the notion of templated architectures in modular intermetallics.

Chemical structure↗
DOE OSTI2025

Continuous Evolution of Eu 2+ /Eu 3+ Mixed Valency Driven by Pressure and Temperature

Continuous mixed valency involving Eu 2+ and Eu 3+ in Eu 4 Bi 6 Se 13 can be induced under applied pressure or at reduced temperatures. The monoclinic structure of Eu 4 Bi 6 Se 13 , crystallizing in the P2 1 /m space group (No. 11), features linear chains of Eu atoms aligned along the b-axis. Magnetic susceptibility measurements, conducted both parallel and perpendicular to the b-axis and analyzed using Curie–Weiss theory, alongside high-pressure partial fluorescence yield (PFY) data from X-ray absorption spectroscopy (XAS), indicate the material’s propensity to adopt a mixed-valent state. Within this state, the trivalent Eu 3+ configuration becomes increasingly favored as the pressure rises or the temperature decreases.

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

End-to-End Automated Segmentation Framework for Four-Dimensional Scanning Transmission Electron Microscopy Data

Four-dimensional scanning transmission electron microscopy (4D-STEM) is powerful for rapidly characterizing arrays of nanoparticles produced via high-throughput synthesis. However, such 4D-STEM datasets typically contain thousands of nanoparticles, each characterized by thousands of diffraction patterns spatially distributed across the nanoparticle, necessitating efficient and comprehensive analysis. We propose an end-to-end segmentation framework to automatically segment each nanoparticle into regions with distinct composition/orientation of crystal grains, using only the 4D-STEM data. Bragg disk information is extracted in a physics-informed manner from the diffraction patterns at each spatial location and combined with the real space coordinates to form feature vectors. These feature vectors are then used as inputs to a Gaussian mixture model (GMM) to segment the nanoparticle into distinct regions. We also develop two visualization tools based on the GMM outputs to infer the interface transition and the degree of superposition. Our framework comprehensively integrates machine learning tools and physics knowledge, and provides a basis for substantially compressing enormous 4D-STEM datasets, e.g., by replacing the full 4D-STEM dataset for each nanoparticle with only a single set of Bragg disk features for each distinct crystal grain identified in the nanoparticle. In this article, we demonstrate the power of our framework by presenting results for real, complex datasets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Eligibility Assessment of Items in the TA-60 Rack Assembly and Alignment Complex Legacy Storage Yard

The U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office (NA-LA), documented and evaluated seven structures in the Technical Area 60 (TA-60) Rack Assembly and Alignment Complex (RAAC) legacy storage yard at Los Alamos National Laboratory (LANL or Laboratory) for listing in the National Register of Historic Places (National Register). This documentation and evaluation was conducted in compliance with Section 106 of the National Historic Preservation Act of 1966, as amended; the Code of Federal Regulations (36 CFR 800); the Programmatic Agreement among the U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office, the New Mexico State Historic Preservation Office and the Advisory Council on Historic Preservation Concerning Management of the Historic Properties at Los Alamos National Laboratory, Los Alamos New Mexico (PA)1; and A Plan for the Management of the Cultural Heritage at Los Alamos National Laboratory, New Mexico (LANL’s Cultural Resources Management Plan (2017). NA-LA makes the following National Register eligibility determinations: la cuna; the rack transporter (jeep, rack trailer, and steering dolly); the Mexia diagnostic rack; the Mexia device canister; the Mexia device mounting stand; and the Mexia target stand are eligible for listing in the National Register, and the second steering dolly is not eligible for listing in the National Register. This National Register evaluation was completed because LANL proposes to develop a consolidated waste facility in TA-60 next to the former RAAC. Across 3.56 acres, LANL proposes to construct an 8,000-square-foot, pre-engineered waste storage building; a 1,500-square-foot office/warehouse building; and 28,500 square feet of covered storage. The development will also include access control features and fencing, parking spaces, and utilities. Additionally, the Laboratory will continue to use the southern part of TA-60-0017 and reuse TA-60-0086 and TA-60-0324 in the development. The consolidated waste facility will operate as a central accumulation area—storing universal waste, mixed low-level (radioactive) waste, hazardous chemicals, and New Mexico special waste—until the waste can be shipped off site.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Time-dependent orbital-free density functional theory: Background and Pauli kernel approximations

Time-dependent orbital-free density functional theory (DFT) is an efficient method for calculating the dynamic properties of large-scale quantum systems due to the low computational cost compared to standard time-dependent DFT. In this work, we formalize this method by mapping the real system of interacting fermions onto a fictitious system of noninteracting bosons. The dynamic Pauli potential and associated kernel emerge as key ingredients of time-dependent orbital-free DFT. Using the uniform electron gas as a model system, we derive an approximate frequency-dependent Pauli kernel. Pilot calculations suggest that space nonlocality is a key feature for this kernel. Nonlocal terms arise already in the second-order expansion with respect to unitless frequency and reciprocal space variable ($\frac{ω}{qk_F}$ and $\frac{q}{2k_F}$, respectively). Given the encouraging performance of the proposed kernel, we expect it will lead to more accurate orbital-free DFT simulations of nanoscale systems out of equilibrium. Additionally, the proposed path to formulate nonadiabatic Pauli kernels presents several avenues for further improvements which can be exploited in future work to improve the results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Situation awareness and dynamic ensemble forecasting of abnormal behavior in cyber-physical system

A plurality of monitoring nodes may each generate a time-series of current monitoring node values representing current operation of a cyber-physical system. A feature-based forecasting framework may receive the time-series of and generate a set of current feature vectors using feature discovery techniques. The feature behavior for each monitoring node may be characterized in the form of decision boundaries that separate normal and abnormal space based on operating data of the system. A set of ensemble state-space models may be constructed to represent feature evolution in the time-domain, wherein the forecasted outputs from the set of ensemble state-space models comprise anticipated time evolution of features. The framework may then obtain an overall features forecast through dynamic ensemble averaging and compare the overall features forecast to a threshold to generate an estimate associated with at least one feature vector crossing an associated decision boundary.

Abbaszadeh, Masoud↗
DOE OSTI2022

Multiomic atlas with functional stratification and developmental dynamics of zebrafish cis -regulatory elements

Zebrafish, a popular organism for studying embryonic development and for modeling human diseases, has so far lacked a systematic functional annotation program akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created a central repository to store and process zebrafish developmental functional genomic data. Our data coordination center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and re-analyzed published genomic data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements throughout development, including classes with distinct features dependent on their activity in time and space. We delineated the distinct distance topology and chromatin features between regulatory elements active during zygotic genome activation and those active during organogenesis. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predicted functional relationships between them beyond sequence similarity, thus extending the utility of zebrafish developmental genomics to mammals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Low Space Harmonic Content Windings (LSHWs) Applied to Improve the Pareto Front in Design Optimization of Electric Machines

In design optimization of high performance electric machines where the power density is increasingly a key metric, it is often desirable to maximize the average torque output within a given volume. However, if a smooth output is also required, the torque ripple may become a hurdle as it tends to increase with the average torque for conventional windings. A direct benefit of low space harmonic content windings (LSHWs), featuring the suppression or elimination of targeted non-working orders in the winding magnetomotive force (MMF), is the torque ripple reduction. This paper provides a detailed analysis of torque ripple pairs and the space-time harmonic order mapping, with concise results that applies to both distributed windings and fractionalslot concentrated windings (FSCWs) of any slot/pole combination. Metamodel-based optimizations are performed to compare two LSHWs with a conventional winding. Improved Pareto fronts are validated, which confirms higher torque producing capabilities at various torque ripple thresholds for LSHWs.

33 ADVANCED PROPULSION SYSTEMS↗