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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Refined interpretation of electron temperature response to neutral beam injection at DIII-D

Accurate particle and power deposition profiles of neutral beam injection (NBI) are essential to transport studies, and that information is usually acquired through Monte Carlo simulations with a given collisional model. The deposition process of the energetic beam particles leads to the informative electron temperature (T e ) evolution trajectory, which can be captured by electron cyclotron emission (ECE) system due to its good spatial and temporal resolution. Previously, some work has been done to interpret the T e responses to the pulsed NBI as a linear heating source with Fourier-based techniques, although that approach fell short when the fast ion slowing-down time becomes significant (~100 ms). It has been observed in DIII-D that the modulated NBI pulses (10–50 Hz) reduce local core T e values ~0.1 keV through cold electron dilution in high-T e (>2 keV) plasmas alongside accumulative heating. Here, a novel approach to interpret the T e response to NBI was developed by linearizing and modeling the detailed T e evolution trajectory using coherently averaged ECE data based on the different time scales of the terms in the local power and particle balance equations. The technique does not require absolute calibrations of ECE and is independent of collisional models. The resulting beam deposition profiles show good consistency and reasonable agreement with Monte Carlo calculations based on the atomic data from the Atomic Data and Analysis Structure (ADAS). Local electron density response measured by Thomson scattering (TS) also suggests the same features when the beam pulse is large enough for that diagnostic to resolve. The remaining discrepancies are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Curvature of the spectral energy distributions of blazars

In this paper, spectral energy distributions (SED) of both synchrotron and inverse Compton (IC) components of a sample of Fermi bright blazars are fitted by a log-parabolic law. The second-degree term of the log parabola measures the curvature of an SED. We find a statistically significant correlation between the synchrotron peak frequency and its curvature. This result is in agreement with the theoretical prediction and confirms previous studies that dealt with a single source with observations at various epochs or a small sample. If a broken power law is employed to fit the SED, the difference between the two spectral indices (i.e., |α{sub 2} – α{sub 1}|) can be considered a 'surrogate' of the SED curvature. We collect data from the literature and find a correlation between the synchrotron peak frequency and the spectral difference. We do not find a significant correlation between the IC peak frequency and its curvature, which may be caused by a complicated seed photon field. It is also found that the synchrotron curvatures are on average larger than those of IC curvatures, and there is no correlation between these two parameters. As suggested by previous works, both the log-parabolic law of the SED and the above correlation can be explained by statistical and/or stochastic particle accelerations. Based on a comparison of the slops of the correlation, our result seems to favor stochastic acceleration mechanisms and emission processes. Additional evidence, including SED modeling, particle acceleration simulation, and comparisons between some predictions and empirical relations/correlations, also seems to support the idea that the electron energy distribution (and/or synchrotron SED) may be log-parabolic.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

CHOLLA: A NEW MASSIVELY PARALLEL HYDRODYNAMICS CODE FOR ASTROPHYSICAL SIMULATION

We present Computational Hydrodynamics On ParaLLel Architectures (Cholla ), a new three-dimensional hydrodynamics code that harnesses the power of graphics processing units (GPUs) to accelerate astrophysical simulations. Cholla models the Euler equations on a static mesh using state-of-the-art techniques, including the unsplit Corner Transport Upwind algorithm, a variety of exact and approximate Riemann solvers, and multiple spatial reconstruction techniques including the piecewise parabolic method (PPM). Using GPUs, Cholla evolves the fluid properties of thousands of cells simultaneously and can update over 10 million cells per GPU-second while using an exact Riemann solver and PPM reconstruction. Owing to the massively parallel architecture of GPUs and the design of the Cholla code, astrophysical simulations with physically interesting grid resolutions (≳256{sup 3}) can easily be computed on a single device. We use the Message Passing Interface library to extend calculations onto multiple devices and demonstrate nearly ideal scaling beyond 64 GPUs. A suite of test problems highlights the physical accuracy of our modeling and provides a useful comparison to other codes. We then use Cholla to simulate the interaction of a shock wave with a gas cloud in the interstellar medium, showing that the evolution of the cloud is highly dependent on its density structure. We reconcile the computed mixing time of a turbulent cloud with a realistic density distribution destroyed by a strong shock with the existing analytic theory for spherical cloud destruction by describing the system in terms of its median gas density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package

The Geant4 simulation toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models rely on measured cross-sections and phenomenological models with the physically motivated parameters that are tuned to cover many application domains. To study what uncertainties are associated with the Geant4 physics models we have designed and implemented a comprehensive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies. It also enables analysis of multiple variants of the resulting physics observables of interest in order to estimate the uncertainties associated with the simulation model choices. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. exible run-time con gurable work ow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented in this paper and illustrated with selected results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Constraining Neutron Capture Cross Sections for Unstable Nuclei with Surrogate Reaction Data and Theory

Obtaining reliable data for nuclear reactions on unstable isotopes remains an extremely important task and a formidable challenge. Neutron capture cross sections—crucial ingredients for models of astrophysical processes, national security applications, and simulations of nuclear energy generation—are particularly elusive, as both projectile and target in the reaction are unstable. We demonstrate a new method for determining cross sections for neutron capture on unstable isotopes, using 87 Y (n , γ) as a prototype. To validate the method, a benchmark experiment is carried out to obtain the known 90 Zr (n , γ) cross section analogously. Our approach, which employs an indirect (“surrogate”) measurement combined with theory, can be generalized to a larger class of nuclear reactions. It can be used both with traditional stable-beam experiments and in inverse kinematics at rare-isotope facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Light emission from silicon nanocrystals

The main experimental results of studies of the photoluminescence of silicon nanocrystals and theoretical methods developed for the description of optical processes occurring in them are reviewed. Special attention is focused on silicon nanocrystals in the SiO{sub 2} matrix that were the object of most of the studies. Two fundamental theoretical methods described in detail are the multiband effective-mass method and the tight-binding method which have found wide application in simulating various processes occurring in nanostructures. A phenomenological model for excitons self-trapped on the surface of oxidized silicon nanocrystals, which has been recently developed on the basis of experimental results obtained by femtosecond spectroscopy, is reported.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Guideline 36 Savings Calculator v0.1

This software package contains a simple calculator that can be used to estimate savings from implementing a retrofit of HVAC controls to ASHRAE Guideline 36 in a multi-zone office building. Implemented in Excel, the calculator has a user-interface front-end to configure parameters of the case study, such as location, building size, and existing control strategies, and a back-end containing results from a large number of pre-run annual energy simulations. The software package also contains the simulation models and associated pre- and post-processing scripts to generate these results.

Blum, David↗
DOE OSTI2022

What is the Right Size for a Residential Building Parcel Locker?

Common-carrier parcel lockers present a solution for decreasing delivery times, traffic congestion, and emissions in dense urban areas through consolidation of deliveries. Multi-story residential buildings with large number of residents, and thus a high volume of online package orders, are one of the best venues for installing parcel lockers. But what is the right size for a residential building locker that would suit the residents’ and building managers’ needs? Because of the novelty of parcel lockers, there is no clear guideline for determining the right locker size and configuration for a residential building given the resident population. A small locker would result in packages exceeding capacity and being left in the lobby, increasing the building manager’s workload and confusing and inconveniencing users. On the other hand, a large locker is more expensive, more difficult to install, and unappealing to residents. To answer this question, we installed a common-carrier parcel locker in a residential building in downtown Seattle, WA, U.S.A. Through collecting detailed data on locker usage from the locker provider company, we studied and quantified carriers’ delivery patterns and residents’ online shopping and package pickup behaviors. We then used this information to model the locker delivery and pickup process, and simulated several locker configurations to find the one that best suits the delivery needs of the building. These findings could aid urban planners and building managers in choosing the right size for residential building lockers that meet delivery demand while minimizing costs and contributing to environmental benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Zeolite membrane cascade for tritium extraction and recovery systems

Membrane separation by zeolite membranes has been proposed as a pre-concentration stage for the tritium extraction from the purge helium of the breeding blanket combined with a final recovery by the catalytic membrane reactor PERMCAT. This fully continuous operation improves the tritium management in fusion machines, minimizing the tritium inventory. For the first time, the permeation measurements for H{sub 2} - He mixtures through a MFI-alumina hollow fibre membrane has been measured for different compositions (0.1 - 20% H{sub 2}) and temperatures. Such a highly permeable membrane, although it shows a limited selectivity, appears attractive for tritium recovery in the blanket. This will imply its operation in a membrane cascade, for which simulation work is ongoing. Mathematically the process is modeled using mass balance equations that can be transformed into the matrix form and solved iteratively assuming a permeate concentration on the first step of iteration, until the separation requirements are fulfilled.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Modeling energy balance while correcting for measurement error via free knot splines

Measurements of energy balance components (energy intake, energy expenditure, changes in energy stores) are often plagued with measurement error. Doubly-labeled water can measure energy intake (EI) with negligible error, but is expensive and cumbersome. An alternative approach that is gaining popularity is to use the energy balance principle, by measuring energy expenditure (EE) and change in energy stores (ES) and then back-calculate EI. Gold standard methods for EE and ES exist and are known to give accurate measurements, albeit at a high cost. We propose a joint statistical model to assess the measurement error in cheaper, non-intrusive measures of EE and ES. We let the unknown true EE and ES for individuals be latent variables, and model them using a bivariate distribution. We try both a bivariate Normal as well as a Dirichlet Process Mixture Model, and compare the results via simulation. Our approach, is the first to account for the dependencies that exist in individuals’ daily EE and ES. We employ semiparametric regression with free knot splines for measurements with error, and linear components for error free covariates. We adopt a Bayesian approach to estimation and inference and use Reversible Jump Markov Chain Monte Carlo to generate draws from the posterior distribution. Based on the semiparameteric regression, we develop a calibration equation that adjusts a cheaper, less reliable estimate, closer to the true value. Along with this calibrated value, our method also gives credible intervals to assess uncertainty. A simulation study shows our calibration helps produce a more accurate estimate. Furthermore, our approach compares favorably in terms of prediction to other commonly used models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Phosphorus sorption and its environmental predictors across pantropical forest soils sampled over the past decade

Tropical forest productivity is frequently constrained by soil phosphorus (P) availability, yet global Land Surface Model (LSM), which are used to simulate ecosystem processes, still represent P cycling in tropical regions only in a limited way, largely because of scarce observational data. Phosphorus adsorption and desorption of dissolved inorganic P to and from soil minerals (hereafter termed sorption), is an important process for predicting how much P is available to plants. This dataset was created to improve predictions of soil P sorption in tropical soils by identifying the isotherm equation that best describes pantropical soils. It includes raw measurements of environmental variables, such as soil properties and climate, together with P sorption data collected from 40 forest soil pits from 9 Forest Global Earth Observatory (ForestGEO) sites across 7 tropical countries during 2018-2022. The data are organized by site, country, and continent. Each site may include several soil pits. For each pit, P sorption was measured across a range of soil P concentrations to build sorption isotherm curves, typically with about 6 to 8 measurements per curve. While sorbed P varies across these concentration levels, the other environmental variables remain constant at the plot level.

Aluminum oxide↗
DOE OSTI2021

Sierra/SolidMechanics for Target Pulse Analysis

Sierra is a Multiphysics engineering simulation software suite developed and maintained by Sandia National Laboratories. Created for nuclear weapon needs, it is available to national laboratories with a foreign national restriction. The STS Target Systems analysis team is interested in using Sierra to perform explicit dynamics simulations of the tantalum clad tungsten target blocks as a response to sudden temperature changes induced by proton beam pulses. The capability already exists with Abaqus|Explicit, however, there are time and cost limitations due to licensing. The following document serves as a “quick-start” guide to the successful setup, simulation, and post-processing of a target model in Sierra on the OZ3 computing cluster at the Spallation Neutron Source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Complementary Subsurface Characterization Methods to Develop a Geologic Model for the EGS Collab Experiment, Sanford Underground Research Facility

The EGS (Enhanced Geothermal Systems) Collab project was performed within the Sanford Underground Research Facility (SURF) with a goal of understanding processes and evaluation of models related to hydraulic simulation of rock at depth. The present work deals with the development of Testbed 2 where experiments were conducted at a depth of 1.25 km and were located within a well-characterized testbed in a metamorphic, amphibolite host rock. A total of eleven boreholes varying in length between 10.6 m and 81.2 m were continuously cored to develop the testbed. In addition to the continuous coring of the amphibolite host rock, geophysical instrumentation supporing electrical resisivity tomography (ERT), microearthquake (MEQ) detection, and optical fiber providing distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) were installed in the monitoring boreholes, all of which produced a comprehensive complementary suite of characterization and monitoring technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Mapping Quasar Light Echoes in 3D with Ly α Forest Tomography

The intense radiation emitted by luminous quasars dramatically alters the ionization state of their surrounding IGM. This so-called proximity effect extends out to tens of Mpc, and manifests as large coherent regions of enhanced Ly (Ly) forest transmission in absorption spectra of background sightlines. In this work, we present a novel method based on Ly forest tomography, which is capable of mapping these quasar "light echoes" in three dimensions. Using a dense grid (10-100) of faint (m r ≈ 24.7 mag) background galaxies as absorption probes, one can measure the ionization state of the IGM in the vicinity of a foreground quasar, yielding detailed information about the quasar's radiative history and emission geometry. An end-to-end analysis-combining cosmological hydrodynamical simulations post-processed with a quasar emission model, realistic estimates of galaxy number densities, and instrument + telescope throughput-is conducted to explore the feasibility of detecting quasar light echoes. We present a new, fully Bayesian statistical method that allows one to reconstruct quasar light echoes from thousands of individual low-S/N transmission measurements. Armed with this tool, we undertake an exhaustive parameter study and show that light echoes can be convincingly detected for luminous (M 1450 <-27.5 mag, corresponding to m 1450 < 18.4 mag at z≃3.6) quasars at redshifts 3 < z QSO < 5, and that a relative precision better than 20% on the quasar age can be achieved for individual objects in the expected range of ages between 1 and 100 Myr. The observational requirements are relatively modest: Moderate-resolution (R ≳ 750), multiobject spectroscopy at a low signal-to-noise ratio (S/N > 5) is sufficient, requiring three-hour integrations using existing instruments on 8 m class telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The E3SM Diagnostics Package (E3SM Diags v2.7): a Python-based diagnostics package for Earth system model evaluation

Abstract. The E3SM Diagnostics Package (E3SM Diags) is a modern, Python-based Earth system model (ESM) evaluation tool (with Python module name e3sm_diags), developed to support the Department of Energy (DOE) Energy Exascale Earth System Model (E3SM). E3SM Diags provides a wide suite of tools for evaluating native E3SM output, as well as ESM data on regular latitude–longitude grids, including output from Coupled Model Intercomparison Project (CMIP) class models. E3SM Diags is modeled after the National Center for Atmospheric Research (NCAR) Atmosphere Model Working Group (AMWG, 2022) diagnostics package. In its version 1 release, E3SM Diags included a set of core essential diagnostics to evaluate the mean physical climate from model simulations. As of version 2.7, more process-oriented and phenomenon-based evaluation diagnostics have been implemented, such as analysis of the quasi-biennial oscillation (QBO), the El Niño–Southern Oscillation (ENSO), streamflow, the diurnal cycle of precipitation, tropical cyclones, ozone and aerosol properties. An in situ dataset from DOE's Atmospheric Radiation Measurement (ARM) program has been integrated into the package for evaluating the representation of simulated cloud and precipitation processes. This tool is designed with enough flexibility to allow for the addition of new observational datasets and new diagnostic algorithms. Additional features include customizable figures; streamlined installation, configuration and execution; and multiprocessing for fast computation. The package uses an up-to-date observational data repository maintained by its developers, where recent datasets are added to the repository as they become available. Finally, several applications for the E3SM Diags module were introduced to fit a diverse set of use cases from the scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado

Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modeling and Simulation of Advanced Manufacturing Techniques using MOOSE and MALAMUTE

Advanced manufacturing techniques offer increased geometry complexity, energy and material usage efficiency improvements, and an expanded palette of materials as compared to conventional manufacturing approaches. Advanced-manufacturing-produced parts can experience wide variations in the final microstructure, and these microstructure variations significantly impact the parts’ performance. In this chapter, we present recent code developments within Multiphysics Object-Oriented Simulation Environment (MOOSE) and in the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE). Here we demonstrate applying these modeling and simulation codes to two advanced manufacturing process types: advanced sintering techniques and laser-based additive manufacturing techniques. The multiphysics and multiscale capabilities of these codes enable prediction of the microstructure evolution resulting from variations in the Advanced manufacturing process parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2011

New Developments in MadGraph/MadEvent

We here present some recent developments of MadGraph/MadEvent since the latest published version, 4.0. These developments include: Jet matching with Pythia parton showers for both Standard Model and Beyond the Standard Model processes, decay chain functionality, decay width calculation and decay simulation, process generation for the Grid, a package for calculation of quarkonium amplitudes, calculation of Matrix Element weights for experimental events, automatic dipole subtraction for next-to-leading order calculations, and an interface to FeynRules, a package for automatic calculation of Feynman rules and model files from the Lagrangian of any New Physics model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗