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Results for “simulation evaluation”

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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of subsurface transport processes of delayed gas signatures applicable to underground nuclear explosions

Radioactive gas signatures from underground nuclear explosions (UNEs) result from gas-migration processes occurring in the subsurface. The processes considered in this study either drive or retard upward migration of gases from the detonation cavity. The relative importance of these processes is evaluated by simulating subsurface transport in a dual-permeability medium for the multi-tracer Noble Gas Migration Experiment (NGME) originally intended to study some aspects of transport from a UNE. For this experiment, relevant driving processes include weak two-phase convection driven by the geothermal gradient, over pressuring of the detonation cavity, and barometric pumping while gas sorption, dissolution, radioactive decay, and usually diffusion represent retarding processes. From deterministic simulations we found that over-pressuring of the post-detonation chimney coupled with barometric pumping produced a synergistic effect amplifying the tracer-gas reaching the surface. Bounding simulations indicated that the sorption and dissolution of gases, tending to retard transport, were much smaller than anticipated by earlier laboratory studies. The NGME observations themselves show that differences in gas diffusivity have a larger effect on influencing upward transport than do the combined effects of tracer-gas sorption and dissolution, which is consistent with a Sobol’ sensitivity analysis. Both deterministic simulations and those considering parametric uncertainties of transport-related properties predict that the excess in concentration of SF 6 compared to 127 Xe as might be captured in small volumetric samples should be much smaller than the order-of-magnitude contrast found in the large-volume gas samples taken at the site. While extraction of large-volume subsurface gas samples is shown to be capable of distorting in situ gas compositions, the highly variable injection rate of SF 6 into the detonation cavity relative to that of 127 Xe at the start of the field experiment is the most likely explanation for the large difference in observed concentrations.

58 GEOSCIENCES↗
DOE OSTI2025

First-principles elucidation of defect-mediated Li transport in hexagonal boron nitride

Hexagonal boron nitride (hBN) is a promising candidate as a protective membrane or separator in Li-ion and Li–S batteries, given its excellent chemical stability, mechanical robustness, and high thermal conductivity. In addition, hBN can be functionalized by introducing defects and dopants, or be directly integrated into other active components of batteries, which further augments its appeal to the field. Here, we use first-principles simulations to evaluate the role of atomic defects in hBN in regulating the Li-ion diffusion mechanism and associated kinetics. Specifically, the following four distinct types of vacancy defects are considered: isolated single B and N vacancies, a B–N vacancy pair, and a B 3 N vacancy cluster. It is found that these defect sites generally favor Li intercalation and out-of-plane diffusion but slow down in-plane Li-ion diffusion due to a strong Li trapping effect at the defect sites. Such a trapping effect is, however, highly local such that it does not necessarily affect the overall Li-ion conductivity in defected hBN layers. The present systematic evaluation of the impact of atomic defects on Li ion migration and accompanied charge analysis of hBN lattice in response to Li-ion diffusion provide a mechanistic understanding of Li-ion transport behavior in defected hBN and highlight the potential of defect engineering to achieve optimal material performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Improving DFIG performance under fault scenarios through evolutionary reinforcement learning based control

The double-fed induction generator (DFIG) usually experiences high rotor current and DC capacitor link voltage during system fault events. In this paper, a novel data-driven approach is proposed to enhance the DFIG performance under fault scenarios. An advanced reinforcement learning (RL) algorithm called guided surrogate-gradient-based evolution strategy (GSES) is used to control the DFIG power and capacitor DClink voltage by adjusting the optional reference signals. This controller is able to prevent the rotor of DFIG from overcurrent risk and maintain the grid-connected operation. The proposed GSES-based control algorithm was evaluated through simulations on a 3.6-MW DFIG in PSCAD/EMTDC software. Results have validated the effectiveness of the proposed GSESbased control algorithm in improving the DFIG performance under fault scenarios.

42 ENGINEERING↗
DOE OSTI2018

Determination and Assessment of Optimum Internal Thermal Insulation for Masonry Walls in Historic Multifamily Buildings

A large portion of existing building stock is comprised of load-bearing masonry buildings, particularly in the Midwest and on the East Coast, though such buildings are distributed across the US. Most of them have uninsulated walls or suffer from insufficient thermal insulation materials. These buildings are inseparable parts of the cultural, social, and economic characteristics of their cities. Due to heritage and preservation concerns, zoning, and space restrictions, they cannot be retrofitted with exterior insulation. Interior insulation must therefore be considered as an alternative. Lack of insulation directly results in energy waste as well as heat loss and gain. Furthermore, it adversely affects heating, ventilation, and air conditioning (HVAC) loads, equipment sizing, indoor air quality, and thermal comfort for residents. The objective of this study is to simulate and evaluate the effects of various internal thermal insulation materials and strategies on mass masonry load-bearing walls in multifamily buildings with attention to various variables and parameters. It not only addresses the energy performance and cost savings associated with an interior insulation retrofit, but also outlines other variables and parameters that are factors in the selection of optimum insulation material, including installations costs, payback periods, useful internal space loss, and options for the depth of the interior insulation retrofit. In conclusion, the audience for this paper is diverse: homeowners, contractors and remodelers, architects and designers, engineers, housing and preservation authorities, and more can benefit from understanding the results outlined in this study.

42 ENGINEERING↗
DOE OSTI2015

Vanadium oxide (VO) based low cost counter electrode in dye sensitized solar cell (DSSC) applications

Vanadium oxide nanostars were synthesized by chemical method. The prepared Vanadium oxide nanostars are introduced into dye sensitized solar cell (DSSC) as counter electrode (CE) catalyst to replace the expensive platinum (Pt). The products were characterized by X-ray diffractometry (XRD), scanning electron microscopy (SEM), and Brunauer–Emmett–Teller (BET) method. The photovoltaic performance of the VO as counter electrode based DSSC was evaluated under simulated standard global AM 1.5G sunlight (100 mW/cm{sup 2}). The solar to electrical energy conversion efficiency (η) of the DSSC was found to be 0.38%.This work expands the Counter electrode catalyst, which can help to reduce the cost of DSSC and thereby encourage their fundamental research and commercial application.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

On the isotropic Raman spectrum of Ar{sub 2} and how to benchmark ab initio calculations of small atomic clusters: Paradox lost

This is the long-overdue answer to the discrepancies observed between theory and experiment in Ar{sub 2} regarding both the isotropic Raman spectrum and the second refractivity virial coefficient, B{sub R} [Gaye et al., Phys. Rev. A 55, 3484 (1997)]. At the origin of this progress is the advent (posterior to 1997) of advanced computational methods for weakly interconnected neutral species at close separations. Here, we report agreement between the previously taken Raman measurements and quantum lineshapes now computed with the employ of large-scale CCSD or smartly constructed MP2 induced-polarizability data. By using these measurements as a benchmark tool, we assess the degree of performance of various other ab initio computed data for the mean polarizability α, and we show that an excellent agreement with the most recently measured value of B{sub R} is reached. We propose an even more refined model for α, which is solution of the inverse-scattering problem and whose lineshape matches exactly the measured spectrum over the entire frequency-shift range probed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Selective-area growth of GaN nanowires on SiO{sub 2}-masked Si (111) substrates by molecular beam epitaxy

We analyze a method to selectively grow straight, vertical gallium nitride nanowires by plasma-assisted molecular beam epitaxy (MBE) at sites specified by a silicon oxide mask, which is thermally grown on silicon (111) substrates and patterned by electron-beam lithography and reactive-ion etching. The investigated method requires only one single molecular beam epitaxy MBE growth process, i.e., the SiO{sub 2} mask is formed on silicon instead of on a previously grown GaN or AlN buffer layer. We present a systematic and analytical study involving various mask patterns, characterization by scanning electron microscopy, transmission electron microscopy, and photoluminescence spectroscopy, as well as numerical simulations, to evaluate how the dimensions (window diameter and spacing) of the mask affect the distribution of the nanowires, their morphology, and alignment, as well as their photonic properties. Capabilities and limitations for this method of selective-area growth of nanowires have been identified. A window diameter less than 50 nm and a window spacing larger than 500 nm can provide single nanowire nucleation in nearly all mask windows. The results are consistent with a Ga diffusion length on the silicon dioxide surface in the order of approximately 1 μm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

On analysis and stochastic modeling of the particle kinetic energy equation in particle-laden isotropic turbulent flows

In this study, we analyze three-dimensional particle-laden, isotropic turbulence to develop an understanding of inertial particle dynamics from a kinetic energy perspective. Data trends implying inhomogeneous sampling of the flow by particles are identified and used to support a proposed particle behavior: particles appear to accumulate in regions of low flow kinetic energy over time because they lose kinetic energy and slow down in such regions, ultimately causing them to spend more time there. To elucidate this behavior, we derive a particle kinetic energy equation from the particle momentum equation, which incorporates inertial effects through the Schiller–Naumann drag correlation. Upon extracting fundamental physics from this equation, hypotheses regarding the role of the Stokes number in the temporal change of particle kinetic energy and the previously proposed particle behavior are evaluated using simulation data considering three Stokes numbers. Finally, a Fokker–Planck equation is used to derive the steady-state probability density function of the particle kinetic energy. The model fits the simulation data well and provides a tool for further investigation into understanding preferential concentration, as well as a reduced order model for predicting particle kinetic energy in turbulent flows.

42 ENGINEERING↗
DOE OSTI2024

XFEL SASE pulses can enhance time-dependent observables

Abstract X-ray free electron lasers (XFELs) have emerged as powerful sources of short and intense x-ray pulses. We propose a simple and robust procedure which takes advantage of the inherent stochasticity of self-amplified stimulated emission (SASE) pulses to enhance the time-resolution and signal strength of the recorded data. Notably, the proposed method is able to enhance the average signal without knowledge of the signal strength of individual shots. Simple metrics for the probe pulses are introduced, such as an effective pulse duration applicable to SASE pulses characterised in the time domain using e.g. an X-band transverse cavity. The approach is evaluated using simulated and real pulse data in the context of ultrafast electron dynamics in a molecule. Utilising H 2 as a model system, we demonstrate the efficacy of the method theoretically, successfully enhancing the predicted nonresonant ultrafast x-ray scattering signal associated with electron dynamics. The method presented is broadly applicable and offers a general strategy for enhancing time-dependent observables at XFELs.

data analysis↗
DOE OSTI2025

Algorithmic Advancements for High-Order Self-Gravitating Hydrodynamics

Self-gravity plays a key role in the formation and evolution of many astronomical objects. Though gravity is often dominant at large scales, other forces (e.g., gas pressure gradients, radiation, and/or magnetic fields) often compete. It is therefore essential for numerical simulations to evaluate their interplay accurately and robustly. Hanawa & Mullen derived a 4th-order accurate finite volume scheme to solve the equations of self-gravitating hydrodynamics on a uniform Cartesian grid. In this work, we supply improvements to the algorithm that (1) mitigate spurious gravitational circulation and (2) greatly simplify the evaluation of the high order corrections. The proposed algorithm provides the gravitational acceleration (ρg) and the gravitational energy release (ρv · g) as source terms for the hydrodynamic equations, all while preserving conservation of linear momentum. Spurious heating and/or cooling associated with truncation error in the numerical evaluation of the gravitational energy release decreases in proportion to the fourth power of the cell width. We demonstrate fourth order convergence on smooth problems (e.g., 3D inclined sound wave propagation and 3D equilibria). An application test tracks the spherical collapse of a polytrope by an imposed, sudden decrease of the central gas pressure; a bounce and second collapse (associated with a spherical accretion shock) are robustly captured by the high order algorithm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A lightweight, user-configurable detector ASIC digital architecture with on-chip data compression for MHz X-ray coherent diffraction imaging

Today, most X-ray pixel detectors used at light sources transmit raw pixel data off the detector ASIC. With the availability of more advanced ASIC technology nodes for scientific application, more digital functionalities from the computing domains (e.g., compression) can be integrated directly into a detector ASIC to increase data velocity. In this paper, we describe a lightweight, user-configurable detector ASIC digital architecture with on-chip compression which can be implemented in 130 nm technologies in a reasonable area on the ASIC periphery. In addition, we present a design to efficiently handle the variable data from the stream of parallel compressors. The architecture includes user-selectable lossy and lossless compression blocks. The impact of lossy compression algorithms is evaluated on simulated and experimental X-ray ptychography datasets. This architecture is a practical approach to increase pixel detector frame rates towards the continuous 1 MHz regime for not only coherent imaging techniques such as ptychography, but also for other diffraction techniques at X-ray light sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Trabecula: A Random Generator of Computational Phantoms for Bone Marrow Dosimetry

This study was motivated by the efforts on evaluation of radiation risk for leukemia incidence in the Techa River Cohort, where the main bone marrow dose contributors were 89,90Sr (bone-seeking beta emitters). Energy deposition in bone marrow targets was evaluated by simulating radiation particle transport using computational phantoms. The present paper describes the computer program “Trabecula” implementing an algorithm for parametric generation of computational phantoms, which serve as the basis for calculating bone marrow doses. “Trabecula” is a user-friendly tool that automatically converts analytical models into voxelized representations that are directly compatible as input to MCNP.

Shishkina, Elena A.↗
DOE OSTI2025

Construction of the damped Ly⁢𝛼 absorber catalog for DESI DR2 Ly⁢𝛼 BAO

We present the Damped Ly⁢𝛼 Toolkit for automated detection and characterization of damped Ly⁢𝛼 absorbers (DLAs) in quasar spectra. Our method uses quasar spectral templates with and without absorption from intervening DLAs to reconstruct observed quasar forest regions. The best-fitting model determines whether a DLA is present while estimating the redshift and HI column density. With an optimized quality cut on detection significance (Δ⁢𝜒$^{2}_{𝑟}$ >0.03), the technique achieves an estimated 80% purity and 79% completeness when evaluated on simulated spectra with S/N>2 that are free of broad absorption lines (BALs). We provide a catalog containing candidate DLAs from the DLA Toolkit detected in DESI DR1 quasar spectra, of which 21 719 were found in S/N>2 spectra with predicted log 10 ⁡(𝑁 𝙷𝙸 )>20.3 and detection significance Δ⁢𝜒$^{2}_{𝑟}$ >0.03. We compare the Damped Ly⁢𝛼 Toolkit to two alternative DLA finders based on a convolutional neural network and Gaussian process models. We present a strategy for combining these three techniques to produce a high-fidelity DLA catalog from DESI DR2 for the Ly⁢𝛼 forest baryon acoustic oscillation measurement. The combined catalog contains 41 152 candidate DLAs with log 10 ⁡(𝑁 𝙷𝙸 )>20.3 from quasar spectra with S/N>2. We estimate this sample to be approximately 85% pure and 79% complete when BAL quasars are excluded.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

CMOS-Based Single-Cycle in-Memory XOR/XNOR

Big data applications are on the rise, and so is the number of data centers. The ever-increasing massive data pool needs to be periodically backed up in a secure environment. Moreover, a massive amount of securely backed-up data is required for training binary convolutional neural networks for image classification. XOR and XNOR operations are essential for large-scale data copy verification, encryption, and classification algorithms. The disproportionate speed of existing compute and memory units makes the von Neumann architecture inefficient to perform these Boolean operations. Compute-in-memory (CiM) has proved to be an optimum approach for such bulk computations. The existing CiM-based XOR/XNOR techniques either require multiple cycles for computing or add to the complexity of the fabrication process. Here, we propose a CMOS-based hardware topology for single-cycle in-memory XOR/XNOR operations. Our design provides at least 2× improvement in the latency compared with other existing CMOS-compatible solutions. We verify the proposed system through circuit/system-level simulations and evaluate its robustness using a 5000-point Monte Carlo variation analysis. This all-CMOS design paves the way for practical implementation of CiM XOR/XNOR at scaled technology nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Game Theoretic Orchestration for Cooperation among Power Distribution System Applications

The evolving transformation with the proliferation of distributed energy resources and advanced metering, necessitates advanced distribution systems to integrate and orchestrate a large number of grid-edge devices while also serving multiple system-level objectives such as resilience, decarbonization, equity and other system mandates. The parallel deployment and control of resources towards achieving diverse objectives may lead to conflicts between applications that want to control overlapping sets of device setpoints, potentially leading to oscillatory behavior and suboptimal performance. This work aims at leveraging game theoretic framework to drive cooperative behavior among competitive applications. The work proposes a weighted-consensus based game design to facilitate conflict resolution through consensus-building iterations for modular platform. Simulation-based evaluation on a sample test system demonstrates the performance the proposed deconfliction strategy in resolving operational conflicts and achieving close-to-optimal trade off among the applications. Results also compare the proposed strategy with a distribution optimization approach and illustrate it effectiveness in diverse apps regardless of their design while also incentivizing apps with flexible design.

Advanced distribution operations, cooperation, app↗
DOE OSTI2026

Regularizing INR with Diffusion Prior for Self-Supervised 3D Reconstruction OF Neutron Computed Tomography Data

Recently, generative diffusion priors have made huge strides as inverse problem solvers, including the ability to be adapted for inference on out-of-distribution data. Concurrently, implicit neural representations (INRs) have emerged as fast and lightweight inverse imaging solvers that are amenable to hybrid approaches that combine learned priors with traditional inverse problem formulations. In this paper, we present a diffusive computed tomography (CT) inversion framework for regularizing INRs called Diffusive INR (DINR), designed to enable high-quality reconstruction from sparse-view neutron CT. Pretrained purely on synthetic data, DINR is evaluated on simulated and experimentally obtained observations of concrete microstructures, where traditional reconstruction methods suffer substantial degradation when the number of views is reduced. Our approach delivers superior performance, reduces reconstruction artifacts, and achieves gains in PSNR and SSIM, enabling accurate micro-structural characterization even under extreme data limitations compared to state-of-the-art sparse-view reconstruction techniques.

Hossain, Maliha [ORNL]↗