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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

ZND Verification Tests for Reactive Burn Models in FLAG

The ZND theory, named after Zeldovich, von Neumann, and Doering, provides a simple model for one-dimensional ideal steady-state detonation. It assumes that the detonation wave front starts with a shock that is a discontinuous jump and is followed by a finite-length reaction zone. Reactive burn (also called reactive flow) models are based on ZND theory, as they model the shock initiation and detonation process with a finite reaction rate. The ZND wave propagation test is essentially the only available test case where an analytic solution exists for verification of reactive burn models in numerical codes. However, there are extensions and variants of the ZND test that have been devised for verification of multidimensional flows. The objective of this work is to provide verification of the reactive burn models currently implemented in the Lagrangian hydrocode FLAG and investigate the influence of mesh resolution, artificial viscosity models, and the Arbitrary Lagrangian-Eulerian (ALE) Euler relaxer on the simulation results. The burn models of interest are the Wescott-Stewart-Davis (WSD) model, the Scaled Uniform Reactive Flow (SURF) model (specifically with the SURFplus model extension), and the Arrhenius shock temperature state dependent WSD (AWSD) model. Previously, Ralph Menikoff has used ZND tests for verification of the SURF and SURFplus models in the Eulerian hydrocode xRAGE. The ZND tests here are somewhat different than the approach by Menikoff. In particular, we use a piston-driven ZND detonation wave (via a prescribed constant velocity boundary condition) in a Lagrangian framework whereas Menikoff had a ZND wave followed by a invariant rarefaction wave. The xRAGE simulations were carried out on uniform grids and adaptive mesh refinement (AMR) grids. Although AMR was recently implemented in FLAG and now fully functional for 2D simulations, it will not be evaluated with ZND tests at this time. Some work has been done previously for validating the reactive burn models in FLAG. For example, the validation studies of SURF with shock-to-detonation (SDT) tests, cylinder tests, and gap-stick tests. Further validation of the AWSD, WSD, and SURF models is described in for SDT, multi-shock, cylinder, and corner-turning tests. Recently, a large parameter study with approximately twenty SDT tests was performed to validate the AWSD, WSD, SURF, and SURFplus models while also investigating mesh resolution and artificial viscosity settings. To the best of our knowledge, the current work represents the first documented verification of these burn models in FLAG. The reader should note that many of the tables and figures in this report use units of cm/g/µs, which are the default units for FLAG. However, some lengths and velocities are expressed in µm and mm/µs, respectively, which are typical units for detonation analyses.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Design and Initial Verification Testing of an In Situ Load Retention Aging Fixture

Load retention is a key metric used to evaluate long-term mechanical functionality of polymeric materials. Its measurement currently requires periodically removing the aging fixtures from the ovens, removing the specimens from the fixtures, and performing load testing on the specimens. The ability to perform load measurement in situ (i.e., without having to remove the specimens from the fixtures, and possibly even the ovens) would facilitate data acquisition/analysis, improve data quality, and enable uninterrupted compression of specimens which is more representative of the actual application.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Research to Develop Flood Barrier Testing Strategies for Nuclear Power Plants

The U.S. Nuclear Regulatory Commission has developed regulations regarding the siting and design of nuclear power plants (NPPs) that are aimed at addressing various natural hazards, including flooding. Flood barriers are designed to prevent water from entering NPP areas containing structures, systems, and components (SSCs) important to safety. The barriers are used at NPPs along with drains, sumps, pumps, valves, plugs, and site grading as part of the plant flood protection features that protect SSCs from experiencing external or internal flooding and mitigate the effects of flooding on NPP operations. The performance of flood protection features, including flood barriers at NPPs, has been an ongoing concern. Domestic and international operational experience provides clear indications that flood barrier performance has significant safety implications, especially for aging NPPs. The observed deficiencies show that flood barriers should be designed and installed properly, then adequately tested, inspected, and maintained in order to ensure that they perform their intended functions during flooding events. Here, this paper reviews available information related to flood barriers employed at U.S. NPPs and provides an overview and categorization of NPP flood barriers. It identifies potential domestic and international flood barrier testing facilities, including operating and decommissioned U.S. NPPs. Finally, this paper presents the technical and logistical considerations that should be made when developing specific testing strategies and protocols for flood barriers, such as the selection of flood barriers, test locations, testing approach, performance criteria, and testing parameters.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Engineered ACE2-Fc counters murine lethal SARS-CoV-2 infection through direct neutralization and Fc-effector activities

Soluble angiotensin-converting enzyme 2 (ACE2) constitutes an attractive antiviral capable of targeting a wide range of coronaviruses using ACE2 as their receptor. Using structure-guided approaches, we developed a series of bivalent ACE2-Fcs harboring functionally and structurally validated mutations that enhance severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor binding domain recognition by up to ~12-fold and remove angiotensin enzymatic activity. The lead variant M81 potently cross-neutralized SARS-CoV-2 variants of concern (VOCs), including Omicron, at subnanomolar half-maximal inhibitory concentration and was capable of robust Fc-effector functions, including antibody-dependent cellular cytotoxicity, phagocytosis, and complement deposition. When tested in a stringent K18-hACE2 mouse model, Fc-enhanced ACE2-Fc delayed death by 3 to 5 days or effectively resolved lethal SARS-CoV-2 infection in both prophylactic and therapeutic settings via the combined effects of neutralization and Fc-effector functions. These data add to the demonstrated utility of soluble ACE2 as a valuable SARS-CoV-2 antiviral and indicate that Fc-effector functions may constitute an important component of ACE2-Fc therapeutic activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Production and tests of the ADDC for the Micromegas detector of the ATLAS New Small Wheel

The Large Hadron Collider (LHC) at CERN will perform a series of upgrades to allow luminosity increases during the next physics runs expected from 2022 on. These will also significantly increase the trigger rates of all the detectors. As part of the ATLAS Phase-I upgrade, the current Small Wheel muon detectors will be replaced with state-of-the-art New Small Wheel (NSW) detectors to cope with the increased luminosity of the LHC. The Address in Real Time Data Driver Card (ADDC) is designed to transmit the trigger data from the resistive Micro-Mesh Gaseous Structure (Micromegas) detectors of the NSW. The ART ASIC on the ADDC is a customdesigned chip to receive theAddress in Real Time (ART) signals from theVMMfront-end ASIC and perform hit-selection processing. The processed trigger data is then sent to the Trigger Processor (TP) through optical links. A total of 512 ADDCs will be installed on the detector close to the front-end boards. Therefore, those cards must be able to work properly in a high radiation and magnetic field environment. Furthermore, after four rounds of prototyping, the ADDC production was launched in January of 2019. 600 ADDC boards have been produced and tested with an automated test stand. This test setup can simulate the front-end signals and provide "Level-1 Data Driver Card" (L1DDC) functions as well as part of the TP functions. Thus, the ADDC functionality and stability can be verified without the remaining NSW electronics. This paper describes the ADDC hardware prototype development, radiation and integration testing, and the ADDC automated production test procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Deep level defects and cation sublattice disorder in ZnGeN 2

The III-nitrides have revolutionized lighting technology and power electronics. Expanding the nitride semiconductor family to include the heterovalent ternary nitrides opens up new and exciting opportunities for device design that may help overcome some of the limitations of the binary nitrides as well as new applications. However, the more complex cation sublattice also gives rise to new complexities with both native and extrinsic defects, such as disorder on the cation sublattice. Here, depth-resolved cathodoluminescence spectroscopy and surface photovoltage spectroscopy measurements of defect energy levels in ZnGeN 2 combined with transmission microscopy and crystal lattice diffraction reveal optical signatures of mid-gap states that can be associated with cation sublattice disorder. The energies of these characteristic optical signatures in ZnGeN 2 thin films grown by metal-organic chemical vapor deposition are in good agreement with energy levels predicted by density functional theory for specific thermodynamically stable native point defects. To test the dependence of these defect signatures on crystal atomic composition, we correlated spatially-resolved optical and atomic composition measurements using spatially resolved x-ray photoelectron spectroscopy with systematically varied growth conditions on the same ZnGeN 2 films. The resultant elemental maps versus defect spectral energies and intensities suggest that cation antisite complexes (Zn Ge -Ge Zn ) versus isolated native point defects form preferentially and introduce mid-gap states that dominate electron-hole pair recombination. Complexing of Zn Ge and Ge Zn antisites manifests as disorder in the cation sub-lattice and leads to the formation of wurtzitic ZnGeN 2 as indicated by transmission electron microscopy diffraction patterns and x-ray diffraction (XRD) reciprocal space maps. Furthermore, these findings emphasize the importance of growth conditions to control cation place exchange.

42 ENGINEERING↗
DOE OSTI2024

At-power subcritical multiplication in the Advanced Test Reactor during nuclear requalification testing

Power division information during nuclear requalification of the Advanced Test Reactor (ATR) is of considerable interest as an importance function for observed changes to core reactivity. The degree to which a given physical subdivision of a critical reactor acts as a neutron source for other lobes is not analytically characterized for general application. When ATR operates at power, individual power-producing lobes rely on each other as neutron sources in order to maintain constant power, which in general requires either exactly critical multiplication within a reactor or an external neutron source. Here, this work shows that fuel element and lobe powers in ATR can be related with subcritical multiplication theory. Subcritical multiplication factors are computed with a physically validated analytical method based on actual at-power operation, quantifying for each lobe its dependence on other lobes as an external neutron source. This explanation is significant for ATR due to the desire to irradiate a large variety of experiments simultaneously, each having its impact on the core neutron population. For any physical subdivision of any other critical reactor, it is likewise true that the subdivision undergoes only subcritical multiplication.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Deciphering the small-angle scattering of polydisperse hard spheres using deep learning

We introduce a deep learning approach for analyzing the scattering function of the polydisperse hard sphere system. We use a variational autoencoder-based neural network to learn the bidirectional mapping between the scattering function and the system parameters, including the volume fraction and polydispersity. Such that the trained model serves both as a generator that produces a scattering function from the system parameters and an inferrer that extracts system parameters from the scattering function. We first generate a scattering dataset by carrying out molecular dynamics simulations of the polydisperse hard spheres modeled by the truncated-shifted Lennard-Jones model, then analyze the scattering function dataset using singular value decomposition to confirm the feasibility of dimensional compression. Then, we split the dataset into training and testing sets and train our neural network on the training set only. Our generator model produces a scattering function with significantly higher accuracy compared to the traditional Percus–Yevick approximation and β correction, and the inferrer model can extract the volume fraction and polydispersity with much higher accuracy than traditional model functions.

Ding, Lijie [ORNL] (ORCID:0000000227454606)↗
DOE OSTI2024

teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

GradDFT. A software library for machine learning enhanced density functional theory

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange–correlation energy functionals. GradDFT employs a pioneering parametrization of exchange–correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.

Chemistry↗
DOE OSTI2020

Proposal for testing the electric Aharonov-Bohm effect with superconductors

The phase of the wave function of charged matter is sensitive to the value of the electric potential, even when the matter never enters any region with nonvanishing electromagnetic fields. Despite its fundamental character, this archetypal electric Aharonov-Bohm effect has evidently never been observed. Here, we propose an experiment to detect the electric potential through its coupling to the superconducting order parameter. A potential difference between two superconductors will induce a relative phase shift that is observable via the DC Josephson effect even when no electromagnetic fields ever act on the superconductors, and even if the potential difference is later reduced to zero. This is a type of electromagnetic memory effect, and would directly demonstrate the physical significance of the electric potential.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Image Distinguishability Analysis Testing Through Principal Components and Its Application to Hot Spot Scale Invariance

Hot spots are spatial regions of intense energy localization that govern initiation of secondary high explosives. Studies that characterize or compare simulated hot spots are frequently either qualitatively descriptive or resort to quantitative distribution functions that neglect stochastic variations and spatial correlations—effects that are also neglected in common comparison tests like the Kolmogorov–Smirnov test. To this end, we develop an image distinguishability analysis (IDA) test based on principal component (PC) analysis that makes pixel-by-pixel comparisons between small, for example, O(<10), image data sets. The IDA test makes comparisons through a generalized distance metric in the PC space and a test statistic that is derived to calculate mathematical equation-values. Here, we derive a statistical distribution and criticality criterion to determine whether images are distinguishable from established baselines. We apply the IDA test on images generated from molecular dynamics simulations of hot spots from pore collapse in TATB to assess scale invariance in the complex patterns of hot spots that form in a representative high explosive crystal. The IDA test shows that TATB hot spot spatial temperature fields and their derived temperature histograms exhibit scale-invariant features over specific intervals of shock orientation, strength, and initial pore diameter. However, the IDA test also shows that qualitatively different conclusions regarding invariance can be reached depending on whether the hot spot is treated as a spatially correlated field as opposed to a distribution function that lacks spatial information.

organic↗
DOE OSTI2024

Structural and functional characterization of IgG- and non-IgG-based T-cell-engaging bispecific antibodies

Bispecific T-cell-engaging antibodies are a growing class of therapeutics with numerous molecules being tested in clinical trials and, currently, seven of them have received market approval. They are structurally complex and function as adaptors to redirect the cytotoxicity of T cells to kill tumor cells. T-cell-engaging bispecific antibodies can be generally divided into two categories: IgG/IgG-like and non-IgG-like formats. Different formats may have different intrinsic potencies and physiochemical properties, and comprehensive studies are needed to gain a better understanding of how the differences in formats impact on structural and functional characteristics. In this study, we designed and generated bispecific T-cell-engaging antibodies with IgG-like (DVD-Ig) and non-IgG (BiTE) formats. Both target the same pair of antigens (EGFR and CD3) to minimize the possible influence of targets on functional characterization. We performed a side-by-side comparison to assess differences in the physiochemical and biological properties of these two bispecific T-cell-engaging antibodies using a variety of breast and ovarian cancer cell-based functional assays to delineate the structural–functional relationships and anti-tumor activities/potency. We found that the Fc portion of T-cell-engaging bispecific antibodies can significantly impact antigen binding activity, potency, and stability in addition to eliciting different mechanisms of action that contribute the killing of cancer cells.

cluster of differentiation 3 (CD3)↗
DOE OSTI2021

Deriving Transmissibility Functions from Finite Elements for Specifications

This work explores deriving transmissibility functions for a missile from a measured location at the base of the fairing to a desired location within the payload. A pressure on the outside of the fairing and the rocket motor’s excitation creates an acceleration at a measured location and a desired location. Typically, the desired location is not measured. In fact, it is typical that the payload may change, but measured acceleration at the base of the fairing is generally similar to previous test flights. Given this knowledge, it is desired to use a finite-element model to create a transmissibility function which relates acceleration from the previous test flight’s measured location at the base of the fairing to acceleration at a location in the new payload. Four methods are explored for deriving this transmissibility, with the goal of finding an appropriate transmissibility when both the pressure and rocket motor excitation are equally present. In conclusion, these methods are assessed using transient results from a simple example problem, and it is found that one of the methods gives good agreement with the transient results for the full range of loads considered.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Soil enzymes as indicators of soil function: A step toward greater realism in microbial ecological modeling

Soil carbon (C) and nitrogen (N) cycles and their complex responses to environmental changes have received increasing attention. However, large uncertainties in model predictions remain, partially due to the lack of explicit representation and parameterization of microbial processes. One great challenge is to effectively integrate rich microbial functional traits into ecosystem modeling for better predictions. Here, using soil enzymes as indicators of soil function, we developed a competitive dynamic enzyme allocation scheme and detailed enzyme-mediated soil inorganic N processes in the Microbial-ENzyme Decomposition (MEND) model. We conducted a rigorous calibration and validation of MEND with diverse soil C-N fluxes, microbial C:N ratios, and functional gene abundances from a 12-year CO 2 × N grassland experiment (BioCON) in Minnesota, USA. In addition to accurately simulating soil CO 2 fluxes and multiple N variables, the model correctly predicted microbial C:N ratios and their negative response to enriched N supply. Model validation further showed that, compared to the changes in simulated enzyme concentrations and decomposition rates, the changes in simulated activities of eight C-N-associated enzymes were better explained by the measured gene abundances in responses to elevated atmospheric CO 2 concentration. In conclusion, our results demonstrated that using enzymes as indicators of soil function and validating model predictions with functional gene abundances in ecosystem modeling can provide a basis for testing hypotheses about microbially mediated biogeochemical processes in response to environmental changes. Further development and applications of the modeling framework presented here will enable microbial ecologists to address ecosystem-level questions beyond empirical observations, toward more predictive understanding, an ultimate goal of microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Geospatial Information, Metadata, and Maps for Global River Corridor Science Focus Area Sites (v5)

This dataset provides geospatial information, metadata, and maps for the Pacific Northwest National Laboratory (PNNL) River Corridor Science Focus Area (RC-SFA; https://www.pnnl.gov/projects/river-corridor) sites. The RC-SFA works to transform understanding of spatial and temporal dynamics in river corridor hydrobiogeochemical functions from molecular reaction to watershed and basin scales. The knowledge we gain is used to formulate and test hypotheses and to improve mechanistic representation of river corridor processes and their response to disturbances in multiscale models of integrated hydrobiogeochemical function. The data provided includes Site ID, latitude, longitude, stream name, and common ID (COMID) for sites used across the RC-SFA. The COMID can be used to find and download data from NHDPlus (https://www.epa.gov/waterdata/nhdplus-national-hydrography-dataset-plus) and other platforms. The sites included are non-exhaustive. Sites (including past sites) will be added to this data package in the future. Data generated from the RC SFA can be accessed at https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA. This data package was originally published in April 2023. It was updated in June 2023 (v2; modified files), December 2023 (v3; modified files), January 2025 (v4; modified files), and December 2025 (v5; modified files). See the change history section in the readme for more details. This dataset is comprised of one main data folder. The data folder consists of (1) file-level metadata; (2) data dictionary; (3) readme; (4) methods codes; (5) geospatial information for all RC SFA sites including International Generic Sample Number (IGSN); (6) maps of all sites and sites in Washington State, USA; and (7) a subfolder with the shapefile of all sites. All files are .csv, .pdf, .shp, .cpg, .dbf, .prj, .qmd, or .shx. We thank the Confederated Tribes and Bands of the Yakama Nation for access to field locations where some data were collected in Washington state. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Characterizing photovoltaic backsheet adhesion degradation using the wedge and single cantilever beam tests, Part II: Accelerated tests

Photovoltaic (PV) backsheets provide critical moisture, mechanical, and electrical insulation to the backside of PV modules, but their continued functionality depends upon their ability to remain well adhered over years of harsh environmental exposure. A study of adhesive strength was conducted on several PV backsheet types exposed to indoor accelerated weathering. Two adhesion tests – the wedge test and single cantilever beam test – were used to measure adhesion energy in four backsheets: two with fluoropolymer-based outer (airside) layers – polyvinyl fluoride (PVF), polyvinylidene fluoride (PVDF) – and two with non-fluoropolymer-based outer layers–polyamide (PA) and polyethylene terephthalate (PET). The effects of changes in temperature, ultraviolet (UV) irradiance, relative humidity, and a periodic water spray were studied. The PET-, PVF- and PVDF-based backsheets all showed instances of debonding in an adhesive layer, which is commonly reported. Furthermore, for the PA-, PET-, and PVDF-based backsheets, adhesion energy dropped fairly rapidly with exposure, reaching very low levels by 4000 h. The PVF-based backsheet was relatively robust to weathering. Pull-off of an outer chalking layer in the PA- and PET-based backsheets suggested a sensitivity to UV. Adhesion in these two backsheets was also highly sensitive to changes in moisture level. Changes in UV irradiance and temperature did not show a statistically significant effect on adhesion loss for the exposure levels used. The present work is part of a two-part adhesion study on both field-weathered and indoor-exposed backsheets, and forms a basis for understanding adhesion degradation across a variety of backsheet types and degradation factors.

14 SOLAR ENERGY↗
DOE OSTI2026

Empirical investigation of nuclear correlation function distributions in lattice QCD

Two-point correlation functions of systems with baryon number 𝐵 ∈ {1,2,3,4} are investigated using lattice quantum chromodynamics (QCD). In particular, the empirical distributions of importance-sampling Monte-Carlo samples of these correlation functions are examined as a function of the spacetime separation between the two points and the baryon number. While the exact forms of these distributions are not known for QCD, recent work has determined asymptotic expressions for analogous correlation function distributions in simpler theories such as scalar field theory and the disordered phase of the 𝑂⁡(𝑁) model. The theoretical 𝑂⁡(𝑁) model distributions are found to provide an accurate description of the empirical QCD distributions at zero momentum over a wide range of temporal separations for each baryon number when assessed with a range of different statistical tests. In particular, the behavior of the baryon number 𝐵 QCD correlation function at large temporal separation is well reproduced by the 𝑂⁡(𝑁 ∼ 2/𝐵) model distribution.

Lattice field theory↗