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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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135 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Performance assessment of PHITS simulations for the inverse-kinematic p( 7 Li,n) 7 Be reaction based on fast-neutron measurements with a diamond detector

The inverse-kinematics p( 7 Li,n) 7 Be reaction produces forward-focused neutron emission, offering enhanced usable flux and reduced shielding requirements. Reliable simulation of such neutron fields is essential for the development of compact accelerator-based neutron sources. In this study, a PHITS-based simulation framework for the reaction was experimentally assessed using fast-neutron measurements. Forward-directed neutrons were measured with a diamond neutron detector and quantitatively compared with simulations with newly prepared IK-Frag cross-section file based on the proton-induced reaction data in ENDF/B-VIII.1, TENDL-2023, and JENDL-4.0/HE. Measurements and simulations were performed for incident 7 Li 3+ energies ranging from 15.0 to 25.0 MeV using a 50 μm-thick polypropylene target. For all conditions, the PHITS-based simulation framework reproduced the deposited energy spectra at the correct order of magnitude. The comparison of deposited energy spectra in the diamond detector showed high correlation coefficients across all investigated energies, indicating reasonable agreement in spectral shape between simulations and measurements. This work represents an initial step toward establishing a benchmark for PHITS simulations of the inverse kinematic reaction between an incident lithium-ion and a proton target.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Synergistic learning with multi-task DeepONet for efficient PDE problem solving

Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine learning to address issues such as data sparsity and overfitting in neural networks. In this work, we apply MTL to problems in science and engineering governed by partial differential equations (PDEs). However, implementing MTL in this context is complex, as it requires task-specific modifications to accommodate various scenarios representing different physical processes. To this end, we present a multi-task deep operator network (MT-DeepONet) to learn solutions across various functional forms of source terms in a PDE and multiple geometries in a single concurrent training session. We introduce modifications in the branch network of the vanilla DeepONet to account for various functional forms of a parameterized coefficient in a PDE. Additionally, we handle parameterized geometries by introducing a binary mask in the branch network and incorporating it into the loss term to improve convergence and generalization to new geometry tasks. Our approach is demonstrated on three benchmark problems: (1) learning different functional forms of the source term in the Fisher equation; (2) learning multiple geometries in a 2D Darcy Flow problem and showcasing better transfer learning capabilities to new geometries; and (3) learning 3D parameterized geometries for a heat transfer problem and demonstrate the ability to predict on new but similar geometries. Finally, our MT-DeepONet framework offers a novel approach to solving PDE problems in engineering and science under a unified umbrella based on synergistic learning that reduces the overall training cost for neural operators.

42 ENGINEERING↗
DOE OSTI2024

An overview of the E3SM version 2 large ensemble and comparison to other E3SM and CESM large ensembles

Abstract. This work assesses a recently produced 21-member climate model large ensemble (LE) based on the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 2 (E3SM2). The ensemble spans the historical era (1850 to 2014) and 21st century (2015 to 2100), using the SSP370 pathway, allowing for an evaluation of the model's forced response. A companion 500-year preindustrial control simulation is used to initialize the ensemble and estimate drift. Characteristics of the LE are documented and compared against other recently produced ensembles using the E3SM version 1 (E3SM1) and Community Earth System Model (CESM) versions 1 and 2. Simulation drift is found to be smaller, and model agreement with observations is higher in versions 2 of E3SM and CESM versus their version 1 counterparts. Shortcomings in E3SM2 include a lack of warming from the mid to late 20th century, likely due to excessive cooling influence of anthropogenic sulfate aerosols, an issue also evident in E3SM1. Associated impacts on the water cycle and energy budgets are also identified. Considerable model dependence in the response to both aerosols and greenhouse gases is documented and E3SM2's sensitivity to variable prescribed biomass burning emissions is demonstrated. Various E3SM2 and CESM2 model benchmarks are found to be on par with the highest-performing recent generation of climate models, establishing the E3SM2 LE as an important resource for estimating climate variability and responses, though with various caveats as discussed herein. As an illustration of the usefulness of LEs in estimating the potential influence of internal variability, the observed CERES-era trend in net top-of-atmosphere flux is compared to simulated trends and found to be much larger than the forced response in all LEs, with only a few members exhibiting trends as large as observed, thus motivating further study.

58 GEOSCIENCES↗
DOE OSTI2023

DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding

Abstract Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million technical drawings with 132,890 object names and 22,394 viewpoints extracted from 14 years of US design patent documents. We demonstrate the usefulness of DeepPatent2 with conceptual captioning. We further provide the potential usefulness of our dataset to facilitate other research areas such as 3D image reconstruction and image retrieval.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Overview of the Dragonfly Entry Aerosciences Measurements (DrEAM) Suite

NASA Ames and Langley arepartnering with DLR to propose acomprehensive instrumentation suite known as the Dragonfly Entry Aerosciences Meas-urements (DrEAM). DrEAM being the first competed mission to fly EDL instrumentation as part of NASA’s Engineering Science Investigation (ESI).DrEAM will provide key aerothermodynamicdata and performance analysisfor Dragonfly’s forebody and backshell therma lprotection system (TPS),and also includes a DLR-provided Data Acquisition System(DAS).Titan’s atmosphere predominantly consists of nitro-gen (~98% by mole) with small amounts of methane(~2% by mole)and other trace gases. CN is a strong ra-diator and is found in nonequilibriumconcentrationsfor Titan entry. The accurate modeling of nonequilibrium CN radiation has proven to be a difficult task. Prompted by the Huygensmission, many experimental campaigns and analyses were performed to better understand the aerothermal environments experience by the probe dur-ing Titan entry[1].However, the Huygens probe carried no heatshieldinstrumentation. Therefore,the DrEAM instrumentation suite will significantly advance the state-of-the-art not only by documenting theenviron-ment and performance of Dragonfly’sentry system but also by making keymeasurements in Titan’s atmos-phere for thefirst time, thus providing new benchmark dataapplicable to entry science more generally. Current Measurement Goals: Aerothermal envi-ronments and TPS responsewill be measured using sen-sors similarto the Mars Entry, Descent, and Landing In-strumentation2 (MEDLI2) Integrated Sensor Plug(MISP) and the COMbined Aerothermaland Radiome-ter Sensor (COMARS)suite[2], with the latter supplied by DLR.For MEDLI2, MISP usedembedded thermo-couples (TCs) todirectly measure in-depth temperature of theTPS at several locations,which can also be used to infer surface environmentsvia inverse analysis. For DrEAM, the MISPstyle plugswill be known as Drag-onfly Sensors for Aero-Thermal Reconstruction (Drag-STR)plugs. On Schiaparelli, the COMARSsuite in-cludedthree total surface-mounted heatflux sensors, three pressure sensors, and one radiometer. For DrEAM, the COMARS package will be known as COmbined Sensor System for Titan Atmosphere (COSSTA). Atmospheric density measurements and capsuleaerodynamic data will be obtained throughthe onboard Inertial Measurement Unit (IMU),supple-mented by pressure transducers similar tothose used by the MEDLI Mars Entry AtmosphericData System (MEADS).The DrEAM pressure sensors will be known as Dragonfly Atmospheric Flight Transducers(DrAFT) Both DragSTR and DrAFThave flight heritagefrom MISP and MEADS on the MSLand Mars 2020mis-sions, and the COMARS suite successfullyflew on the ESA Schiaparelli EDMlander. A preliminary layout of the sensors is shown in Fig. 1. Because Dragonflyuses the same aeroshell provider (i.e., LockheedMartin) and materials for the TPS,with what are expected to be sim-ilar thicknesses as MSL and Mars 2020on both the heat shield and backshell, theDrEAMinstrumentation will look to utilize the same techniques and processes as de-veloped byMEDLI and MEDLI2for vehicle integra-tion. This commonality alsoenables DrEAMto lever-age the extensiveground test qualifications performed forMEDLI and MEDLI2 and claim substantial heritagefor this system.

A Brandis↗
DOE OSTI2023

Thermal Scattering Law Data Development for Paraffin Wax

Paraffin wax is often used as a nuclear moderator to slow down the fast neutrons in experimental critical assemblies [1]. It is a colorless and soft solid material that consists primarily of straight-chain alkanes (n-alkanes), which are hydrocarbons with the general formula CnH2n+2 [2-3]. The length of the hydrocarbon chain ranges from C20 to C30 and higher [2]. It is distinguished by its solid state at room temperature and begins to melt above approximately 310 K [4]. Paraffin wax is a commonly employed substance in the manufacture of shielding. One of its noteworthy characteristics is its ability to effectively absorb the neutrons. Also, it possesses a high macroscopic cross section, which enables it to efficiently moderate neutrons. As a result, paraffin wax is extensively utilized in various applications where moderation and shielding of neutrons are needed. For simulations, it is necessary to evaluate its thermal scattering law (TSL) and cross sections. Computationally, classical molecular dynamics (CMD) simulations provide the capability of simulating atomic details. For example, several unary, binary, and few multi component mixtures have been investigated of the paraffin model by using molecular dynamics simulations [5-12]. An assessment of thermal neutron scattering in a heavy paraffinic oil treated both as a solid and a viscous fluid containing 25% linear branched paraffin (C30H62), 35% one ring cycloalkane (C30H60), 15% two rings cycloalkane (C30H58), and 25% aromatic (C30H60) chains has been studied using CMD simulations for producing TSL data [13]. Nevertheless, there is lack of TSL and cross section data for paraffin wax as most of the reported analyses focus on the unary and binary mixture of n-alkanes, which is not consistent with actual paraffin wax [2]. In this work, we applied the equilibrium CMD simulations technique to explore the structure and dynamical properties of wax, which are fundamental input to calculate the TSL. A paraffin wax system was modeled using the CMD code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) [14-15] with the semi-empirical COMPASS [16] force field. The density of state (DOS) was calculated from the normalized velocity autocorrelation function (VACF), which is the Fourier transform of the normalized VACF. The DOS was used for the calculation of the TSL and thermal scattering cross sections. The paraffin wax atomic system was constructed by using the MedeA material design platform [17], and was benchmarked using available properties (i.e., density, bond lengths, angles, diffusivity, and viscosity).

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2024

DAISY Benchmark Performance Data

This repository contains the underlying data from benchmark experiments for Drifting Acoustic Instrumentation SYstems (DAISYs) in waves and currents described in "Performance of a Drifting Acoustic Instrumentation SYstem (DAISY) for Characterizing Radiated Noise from Marine Energy Converters" (https://link.springer.com/article/10.1007/s40722-024-00358-6). DAISYs consist of a surface expression connected to a hydrophone recording package by a tether. Both elements are instrumented to provide metadata (e.g., position, orientation, and depth). Information about how to build DAISYs is available at https://www.pmec.us/research-projects/daisy. The repository's primary content is three compressed archives (.zip format), each containing multiple MATLAB binary data files (.mat format). A table relating individual data files to figures in the paper, as well as the structure of each file, is included in the repository as a Word document (Data Description MHK-DR.docx). Most of the files contain time series information for a single DAISY deployment (file naming convention: [site]_DAISY_[Drift #].mat) consisting of processed hydrophone data and associated metadata. For a limited number of DAISY deployments, the hydrophone package was replaced with an acoustic Doppler velocimeter (file naming convention: [site]_DAISY_[Drift #]_ADV.mat). Data were collected over several years at three locations: (1) Sequim Bay at Pacific Northwest National Laboratory's Marine & Coastal Research Laboratory (MCRL) in Sequim, WA, the energetic tidal channel in Admiralty Inlet, WA (Admiralty Inlet), and the U.S. Navy's Wave Energy Test Site (WETS) in Kaneohe, HI. Brief descriptions of data files at each location follow. - MCRL - (1) Drift #4 and #16 contrast the performance of a DAISY and a reference hydrophone (icListen HF Reson), respectively, in the quiescent interior of Sequim Bay (September 2020). (2) Drift #152 and #153 are velocity measurements for a drifting acoustic Doppler velocimeter in in the tidally-energetic entrance channel inside a flow shield and exposed to the flow, respectively (January 2018). (3) Two non-standard files are also included: DAISY_data.mat corresponds to a subset of a DAISY drift over an Adaptable Monitoring Package (AMP) and AMP_data.mat corresponds to approximately co-temporal data for a stationary hydrophone on the AMP (February 2019). - Admiralty Inlet - (1) Drift #1-12 correspond to tests with flow shielded DAISYs, unshielded DAISYs, a reference hydrophone, and drifting acoustic Doppler velocimeter with 5, 10, and 15 m tether lengths between surface expression and hydrophone recording package (July 2022). (2) Drift #13-20 correspond to tests of flow shielded DAISYs with three different tether materials (rubber cord, nylon line, and faired nylon line) in lengths of 5, 10, and 15 m (July 2022). - WETS - (1) Drift #30-32 correspond to tests with a heave plate incorporated into the tether (standard configuration for wave sites), rubber cord only, and rubber cord, but with a flow shielded hydrophone (November 2022). (2) Drift #49-58 and Drift #65-68 correspond to measurements around mooring infrastructure at the 60 m berth where time-delay-of-arrival localization was demonstrated for different DAISY arrangements and hydrophone depths (November 2022).

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Preliminary Design of a New Pulsed-Neutron Die--Away Experiments with Absorbers (IER-552 CED-1)

This report presents the preliminary design (CED-1) of IER-552, pulsed-neutron die-away (PNDA) experiments with absorbers, to be conducted by Lawrence Livermore National Laboratory (LLNL). The goal of the PNDA experiments with absorbing materials is to produce high-quality, low-cost integral benchmarks that can be used to validate cross sections that are high priority nuclear data for the Department of Energy’s Nuclear Criticality Safety Program (NCSP). PNDA experiments can be used to generate nuclear data validation benchmarks quickly and cheaply, as they do not require fissile material or a nuclear facility to conduct them. The original PNDA experiments were set up at LLNL under IER-501. Extending the PNDA experiments to include absorbing materials leverages existing facilities and resources at LLNL to validate cross sections, with a basic experiment design that uses a neutron generator to impinge a short, mono-energetic neutron pulse on a poisoned, moderating target sample. The neutron pulse lasts 100 µs, after which the neutron population in the sample reaches thermal equilibrium and later spatial equilibrium. In this fully equilibrized state, the neutron population has a characteristic decay-time eigenvalue. The eigenvalue can be used as an integral parameter to validate nuclear data involved with neutron scattering and absorption. Two observables can be measured: the neutron population and the population of secondary γ-rays produced by inelastic and capture reactions. This report explores the feasibility of both approaches. For γ-ray measurements, this allows for direct measurement of reactions of interest for validation. During the neutron burst time, inelastic (prompt) γ-rays dominate, and these data can be isolated for validation of neutron inelastic scattering data. After the pulse ends, neutron capture (delayed) γ-rays dominate and are produced by many reaction channels as neutrons slow down to thermal energies. Two sets of γ-ray spectra (inelastic, capture) can be produced for validation. Additionally, the time-dependent decay of the capture γ-ray population when the neutron population is thermalized and in its fundamental mode can be used for validation. Two experiments can be imagined where pulsed neutrons are used to validate the nuclear data of absorbing materials. The first integrates well into the existing PNDA testbed at LLNL. The absorber material would be introduced into a moderating target and the same neutron generator, neutron detectors, electronics, and shielding box used for IER-501 would be employed. From the same experimental setup, many absorbing materials can be validated by simply changing the neutron poison in the moderator. The only significant modification would be the introduction of a γ-ray detector. Such an experiment would primarily serve to validate nuclear data in the thermal energy range. The second kind of experiment would validate the fast and epithermal energy range. It would involve pulsing neutron into a bare assembly of the absorber material and measuring the die-away of neutrons. The fast leakage of such an assembly requires nanosecond neutron-generator pulse widths and fast detectors/electronics that could measure ~200 ns die-away curves. This kind of experiment would ideally be performed at a cyclotron, like that available at Lawrence Berkeley National Laboratory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

ANALYSIS OF THE MSL/MEDLI ENTRY DATA WITH COUPLED CFD AND MATERIAL RESPONSE.

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heat-shield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material. PICA is a lightweight carbon fiber/polymeric resin material that offers out-standing performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on Open-FOAM (PATO) using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA, is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Mars Science Laboratory↗