Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Noah”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Methodology for physics-informed generation of synthetic neutron time-of-flight measurement data

Accurate neutron cross section data are a vital input to the simulation of nuclear systems for a wide range of applications from energy production to national security. The evaluation of experimental data is a key step in producing accurate cross sections. There is a widely recognized lack of reproducibility in the evaluation process due to its artisanal nature and therefore there is a call for improvement within the nuclear data community. This can be realized by automating/standardizing viable parts of the process, namely, parameter estimation by fitting theoretical models to experimental data. This automation effort could greatly benefit from a synthetic data resource. This work leverages problem-specific physics, Monte Carlo sampling, and a general methodology for data synthesis to generate unlimited, labelled experimental cross-section data that is statistically indistinguishable to the observed data. Heuristic and, where applicable, rigorous statistical comparisons to observed data support this claim. The demonstration is based on/limited to transmission measurements at Rensselaer Polytechnic Institute (RPI) and energy-differential cross sections in the resolved resonance region (RRR). An open-source software is published alongside this article that executes the complete methodology to produce high-utility synthetic datasets. The goal of this work is to provide an approach and corresponding tool that will allow the evaluation community to begin exploring more data-driven, ML-based solutions to long-standing challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Conservative discontinuous Galerkin interpolation: Sheared boundary conditions

Local studies of accretion disks and laboratory magnetized plasmas employ analytical coordinate mappings that introduce sheared boundary conditions (BCs). Here, we present a discontinuous Galerkin (DG) algorithm to apply such BCs based on projections and quadrature-free integration. The procedure is high-order accurate, preserves moments exactly and works in multiple dimensions. Tests of increasing complexity are provided, beginning with translations of one and two dimensional fields, followed by 3D and 5D simulations with sheared (twist-shift) BCs. Results show that the algorithm is (p + 1)-order accurate in the DG representation and (p + 2) -order accurate in the cell averages, with p being the order of the polynomial basis. Quantification of the algorithm's hyperdiffusion and discussion of aliasing errors are given. This technique enables conservative local simulations of plasma turbulence with DG, not possible until now.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A universal implementation of radiative effects in neutrino event generators

Due to the similarities between electron-nucleus (eA) and neutrino-nucleus scattering (νA), eA data can contribute key information to improve cross-section modeling in eA and hence in νA event generators. However, to compare data and generated events, either the data must be radiatively corrected or radiative effects need to be included in the event generators. We implemented a universal radiative corrections program that can be used with all reaction mechanisms and any eA event generator. Our program includes real photon radiation by the incident and scattered electrons, and virtual photon exchange and photon vacuum polarization diagrams. It uses the “extended peaking” approximation for electron radiation and neglects charged hadron radiation. This method, validated with GENIE, can also be extended to simulate νA radiative effects. This work facilitates data-event-generator comparisons used to improve νA event generators for the next-generation of neutrino experiments. Program Title: emMCRadCorr CPC Library link to program files:https://doi.org/10.17632/hmsxg82vnf.1 Developer's repository link:https://github.com/e4nu/emMCRadCorr Licensing provisions: AGPLv3 Programming language:C++ Nature of problem: Radiative effects can significantly modify the event kinematics and the resulting cross-sections. Such effects must be accounted for when comparing event generators to eA data. Existing radiative correction codes are tailored to specific processes and topologies, and are limited to a restricted phase space defined by the spectrometer acceptance. Therefore, a more general approach is required to apply radiative corrections to semi-inclusive and exclusive eA measurements. Solution method: Our program incorporates real photon radiation from both the incident and scattered electrons, as well as virtual photon exchange and photon vacuum polarization effects. It employs the “extended peaking” approximation for electron radiation while neglecting contributions from charged hadron radiation. The code is fully decoupled from event generator codes and can be used for all event generators in the market.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Machine learning-assisted identification of potential sources of bias in measurements of prompt-fission neutron spectra

Unrecognized sources of uncertainty (USU) can bias the reported mean and/or covariance of experimental nuclear data. These biases, in turn, can propagate through evaluated nuclear data to application simulations or may poorly inform nuclear theory that is fitted to the experimental data. Such unknown sources of bias must be tied to the inherent physical constituents of the measurements such as the characteristics of a detector response or a background reduction technique. Here, in this article, a sparse Bayesian learning model is used to support experts in their efforts to identify and characterize USU in experimental prompt fission neutron spectra (PFNS) for spontaneous fissioning of 252 Cf by linking observed biases to features of the measurement system. Three different bias components were found. The first acts as a verification case for the algorithm as it identifies a bias coming from a well-known source related to the use of 6 Li in the neutron detection system. The second two cases demonstrate how this method can benefit the evaluation of experimental nuclear data by identifying, quantifying, and relating unknown biases to potential causes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Mineral detection of neutrinos and dark matter. A whitepaper

Minerals are solid state nuclear track detectors — nuclear recoils in a mineral leave latent damage to the crystal structure. Depending on the mineral and its temperature, the damage features are retained in the material from minutes (in low-melting point materials such as salts at a few hundred °C) to timescales much larger than the 4.5 Gyr-age of the Solar System (in refractory materials at room temperature). The damage features from the O (50) MeV fission fragments left by spontaneous fission of 238U and other heavy unstable isotopes have long been used for fission track dating of geological samples. Laboratory studies have demonstrated the readout of defects caused by nuclear recoils with energies as small as O (1) keV. This whitepaper discusses a wide range of possible applications of minerals as detectors for E R ≳ O (1) keV nuclear recoils: Using natural minerals, one could use the damage features accumulated over O (10) Myr–O (1) Gyr to measure astrophysical neutrino fluxes (from the Sun, supernovae, or cosmic rays interacting with the atmosphere) as well as search for Dark Matter. Using signals accumulated over months to few-years timescales in laboratory-manufactured minerals, one could measure reactor neutrinos or use them as Dark Matter detectors, potentially with directional sensitivity. Research groups in Europe, Asia, and America have started developing microscopy techniques to read out the O (1)–O (100) damage features in crystals left by O (0.1)–O (100) keV nuclear recoils. We report on the status and plans of these programs. Furthermore, the research program towards the realization of such detectors is highly interdisciplinary, combining geoscience, material science, applied and fundamental physics with techniques from quantum information and Artificial Intelligence.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Nonvolatile electrochemical memory at 600°C enabled by composition phase separation

Silicon-based microelectronics are limited to ~150°C and therefore not suitable for the extremely high temperatures in aerospace, energy, and space applications. While wide-band-gap semiconductors can provide high-temperature logic, nonvolatile memory devices at high temperatures have been challenging. In this work, we develop a nonvolatile electrochemical memory cell that stores and retains analog and digital information at temperatures as high as 600°C. Through correlative scanning transmission electron microscopy, we show that this high-temperature information retention is a result of composition phase separation between the oxidized and reduced forms of amorphous tantalum oxide. This result demonstrates a memory concept that is resilient at extreme temperatures and reveals phase separation as the principal mechanism that enables nonvolatile information storage in these electrochemical memory cells.

42 ENGINEERING↗
DOE OSTI2023

Equity implications of net-zero emissions: A multi-model analysis of energy expenditures across income classes under economy-wide deep decarbonization policies

With companies, states, and countries targeting net-zero emissions around midcentury, there are questions about how these targets alter household welfare and finances, including distributional effects across income groups. This paper examines the distributional dimensions of technology transitions and net-zero policies with a focus on welfare impacts across household incomes. The analysis uses a model intercomparison with a range of energy-economy models using harmonized policy scenarios reaching economy-wide, net-zero CO 2 emissions across the United States in 2050. Here we employ a novel linking approach that connects output from detailed energy system models with survey microdata on energy expenditures across income classes to provide distributional analysis of net-zero policies. Although there are differences in model structure and input assumptions, we find broad agreement in qualitative trends in policy incidence and energy burdens across income groups. Models generally agree that direct energy expenditures for many households will likely decline over time with reference and net-zero policies. However, there is variation in the extent of changes relative to current levels, energy burdens relative to reference levels, and electricity expenditures. Policy design, primarily how climate policy revenues are used, has first-order impacts on distributional outcomes. Net-zero policy costs, in both absolute and relative terms, are unevenly distributed across households, and relative increases in energy expenditures are higher for lowest-income households. However, we also find that recycled revenues from climate policies have countervailing effects when rebated on a per-capita basis, offsetting higher energy burdens and potentially even leading to net progressive outcomes. Model results also show carbon Laffer curves, where revenues from net-zero policies increase but then decline with higher stringencies, which can diminish the progressive effects of climate policies. We also illustrate how using annual income deciles for distributional analysis instead of expenditure deciles can overstate the progressivity of emissions policies by overweighting revenue impacts on the lowest-income deciles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

The short-term comprehensive impact of the phase-out of global coal combustion on air pollution and climate change

With the continuous intensification of global warming, the reduction and ultimate phase-out of coal combustion is an inevitable trend in the future global energy transformation. This study comprehensively analyzed the impact of phasing out coal combustion on global emissions and concentrations of air pollutants, radiative fluxes, meteorology and climate using Community Earth System Model 2 (CESM2). The results indicate that after the global phase-out of coal combustion, there is a marked decrease in the concentrations of sulfur dioxide (SO 2 ), nitrogen oxides (NO x ) and fine particulate matter (PM 2.5 ), with some regions experiencing a reduction of exceeding 50%. There is no significant change in global ozone (O 3 ) concentration. There are decreasing AOD and positive radiative fluxes globally in the short term, though the cloud contributes minor negative radiative fluxes. The global air temperature may increase by approximately (0.02 ± 0.15) °C on average with regional and seasonal variations, and the precipitation may potentially increase by approximately (2.7 ± 40.6) mm yr −1 globally and over 20% in equatorial regions in the short term. But combined with the decreasing trend of cloud water content in the Northern Hemisphere, it indicates a potential increase in the extremity of precipitation events. In conclusion, this study provides references for global control of air pollution, mitigation strategies of climate change, and transformation of energy structures under the objective of “carbon neutrality”, such as focusing on the negative climate impacts of exacerbating regional warming and increasing extreme precipitation resulting from the rapid reduction of aerosols in the short term.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Economic feasibility of in-motion wireless power transfer in a high-density traffic corridor

Electricity is expected to become a dominant power source in the transportation sector, but under a stationary recharging model, electric powered vehicles still suffer some disadvantages relative to conventional vehicles. Recent developments in wireless power transfer (WPT) technology can enable an alternative vehicle recharging model wherein power is supplied to vehicles while they are moving, mitigating the need for charging stops and high-capacity on-board energy storage. One of the greatest concerns associated with dynamic WPT is that the required infrastructure costs would be prohibitively high; however, the life-cycle costs and benefits of such a system have been under-researched. Here in this work, we apply a systems-level assessment to a case study of a WPT charging system located on the densely trafficked I-710 corridor in Los Angeles, California. Detailed cost estimates for electronics and implementation, high-fidelity energy consumption modeling, and survey-derived adoption projections are applied to evaluate scenarios of economic feasibility and environmental impact. Results show that a “1st-of-a-kind” system can achieve a payback in 20 years while maintaining operating cost advantages relative to petroleum fueling. System economics are shown to improve substantially with “nth-of-a-kind” capital costs. Discussion focuses on the effect of uptake trajectory on economic viability and detailed economics outcomes for light duty and heavy duty vehicles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Dicarboxylic acid emissions from a GDI engine equipped with a catalytic gasoline particulate filter

Dicarboxylic acids play an important role in atmospheric chemistry, yet their emissions from primary sources, such as internal combustion engines, has not been extensively studied. In this paper, KOH impregnated quartz filters were loaded with exhaust gases from a gasoline direct injection (GDI) engine equipped with a catalytic gasoline particulate filter (GPF). All filters were analyzed for carboxylic and dicarboxylic acids using a derivatized gas chromatography-mass spectroscopy method. Exhaust gas was sampled from pre-GPF and post-GPF locations to determine the performance of the GPF regarding acid conversion. Lean and stoichiometric engine modes were considered with non-oxygenated gasoline and 10% splash blended ethanol in gasoline (E10) to examine the impact of stoichiometry and fuel type. Acid emissions represented as much as 0.51% of total unburned hydrocarbon emissions for total monocarboxylic acids and as much as 0.40% for total dicarboxylic acids. Individual acid concentrations were as high as 38 mg/kg-fuel for monocarboxylic acids and as high as 29 mg/kg-fuel for dicarboxylic acids. Overall, the study found that fuel oxygenates had mixed impact on the acid emissions. Engine-out monocarboxylic acids were reduced when using the E10 fuel by approximately 30–45% for the stoichiometric condition and increased marginally for the lean condition. Dicarboxylic acid emissions were generally insensitive to ethanol content. However, the engine condition significantly affected the acid emissions. Lean operation produced a factor of two to an order of magnitude higher emissions rates of both monocarboxylic and dicarboxylic acids than the stoichiometric condition. The catalytic GPF eliminated between 80 and 92% of the acids emitted from the engine, allowing some acids to be emitted into the environment.

42 ENGINEERING↗
DOE OSTI2020

Influence of physical and chemical hydrology on bioremediation of a U-contaminated aquifer informed by reactive transport modeling incorporating 238 U/ 235 U ratios

Microbially-catalyzed reductive immobilization of aqueous uranium (U) as a solid phase has been proposed as a U remediation technique. Both laboratory and field experiments have demonstrated that this reduction reaction alters the 238 U/ 235 U ratio, producing a 238 U-enriched U(IV) solid. In contrast, other major U reactive transport processes fractionate these isotopes much less. This suggests the potential to quantify the extent of bioreduction occurring in groundwater containing U using the 238 U/ 235 U ratio, which would substantially improve upon current practices largely relying on U concentration measurements alone. Current reactive transport models for uranium dynamics include only concentration measurements, which are strongly influenced by highly coupled reactive transformation and aqueous transport processes. The complex physical and chemical behavior of U potentially compromises such quantitative analysis of U storage and release. Here we report the first numerical reactive transport model which explicitly incorporates variations in the 238 U/ 235 U ratio of U and demonstrates improved interpretation of the principal chemical reactions and groundwater transport processes affecting the subsurface mobility and distribution of this widespread contaminant. Recent U bioreduction studies performed in a contaminated aquifer in Rifle, Colorado, USA applied Rayleigh distillation models to interpret U stable isotope fractionation observed as a result of acetate amendment. These simplified models were unable to resolve the spatiotemporal pattern of U isotope fractionation recorded in the aqueous solutes. Here, we employ the multi-component, isotope-enabled CrunchTope reactive transport software to interpret these measured U isotope ratios, and demonstrate accurate reproduction of observed trends in both geochemistry and 238 U/ 235 U ratios for two consecutive years of field experiments. Overall, our results indicate that accurately modeling both the U concentration and isotope ratio distributions greatly constrains the parameter space of the model. We find that the transport properties of U in the Rifle aquifer are governed by the presence of low-permeability regions, which the isotopes are uniquely sensitive to. When U reduction is spatially constrained by these low-permeability regions, the shift in the 238 U/ 235 U ratio becomes more muted. Accurate modeling of observed U isotope ratios thus provides a powerful means to better understand bioremediation, and the current study serves to advance the application of this novel method.

238U/235U↗
DOE OSTI2025

Temperature dependence of uranium and thorium partitioning in igneous zircons

Zircon is a key mineral in geochronology because of its chemical and physical durability and tendency to incorporate radioactive trace elements such as U and Th. Quantifying the partitioning of the actinide elements is critical to constrain initial non-secular equilibrium amounts of 230 Th in zircon. An excess or deficit of 206 Pb will be produced from such an initial excess/deficit of 230 Th from the secular equilibrium condition, which influences the calculated 206 Pb/ 238 U age (Schärer, 1984, Mattinson, 1973). However, there is no standard way to calculate Th/U partitioning ratios when applying age corrections to young igneous zircon, making uncertainties hard to estimate. To better understand U and Th partitioning of zircon/melt that is the cornerstone of the secular disequilibrium correction, zircon was synthesized in one-atmosphere experiments using basaltic andesite, andesite, and rhyolite starting materials, doped with Zr, U, and Th. Different experimental temperatures and oxygen fugacity conditions (ΔQFM−4 to ΔQFM+4) were explored to examine their effects on U and Th partitioning. In addition, we specifically quantify the effects of sector zoning, fractional crystallization, and melt composition on U and Th partitioning. By combining experimental and natural zircon data, we find that temperature has the primary control on the partitioning of U and Th in the zircon and calibrate an inverse relationship between these partition coefficients and crystallization temperatures. The calibrated equation can be applied to the 230 Th correction for an improvement in the accuracy of Th-corrected 206 Pb/ 238 U dates when the zircon crystallization temperature is known.

206Pb/238U dating↗
DOE OSTI2026

How deep is your soil? Quantifying and spatially analyzing understudied deep soil in the United States

Deep soil is largely understudied and important in understanding biogeochemical processes in soil. Here, understudied soil is defined as the difference between soil studied to a known depth and the estimated bedrock depth. To understand more about deep soil, the understudied soil in the US was quantified and spatially analyzed using soil survey data and model estimates of bedrock depth. An equation was derived to find understudied soil using the dataset parameters “max lower depth studied”, “depth to bedrock”, and “likelihood of bedrock in the top 200 cm”. The survey data and bedrock model revealed that soil has been studied to an average depth of 1-2 meters, and the average depth to bedrock is 20 meters. Soil data density in the soil surveys was greatest in the West Coast, Midwest, and areas historically managed for agricultural, while the non-contiguous US and interior West were underrepresented. The soil had been studied deeper than the estimated soil depth in 455 out of 56,889 observation points concentrated in Alaska, California, Texas, Florida, Puerto Rico, and the US Virgin Islands. To understand the diversity and any taxonomic bias of the global soil data available, soil order was compared to US-based National Resource Conservation Service percentages and it was found that Oxisols, Alfisols, Ultisols, Andisols, and Histosols were overrepresented while Gelisols, Aridisols, Vertisols, Entisols, and Spodosols are underrepresented. Soil depth is important in exploring the complexity of biogeochemical processes that take place in soil.

Bedrock↗
DOE OSTI2025

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗