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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Enabling Advanced Snow Physics within Land Surface Models Through an Interoperable Model-Physics Coupling Framework

Accurate estimation of snow accumulation and melt is a critical part of decision-making in snow-dominated watersheds. In this study, we demonstrate a flexible methodology to couple a detailed snow model, Crocus, separately to two different land surface models (LSMs), Noah-MP and Noah. The original LSMs and the coupled models (Noah-MP-Crocus and Noah-Crocus) are used to simulate snow depth, snow water equivalent, and other water and energy states and fluxes. The results of simulations are compared against a wide range of independent gridded and point scale reference datasets. Our results show that coupling the detailed snow model, Crocus, with the LSMs improves the snow depth and snow water equivalent relative to independent observations. Overall, larger improvements are obtained with coupling Crocus to the Noah LSM, with the coupled Noah-Crocus configuration reducing the RMSE and bias of snow depth from 2-12% and 57-75%, respectively, relative to Snow Data Assimilation System (SNODAS) and snow product from the University of Arizona. On the other hand, smaller improvements are obtained by coupling Crocus with Noah-MP. The Coupled Noah-MP-Crocus reduces the snow depth bias but slightly degrades the RMSE of snow depth and snow water equivalent. The corresponding impacts in other water budget terms such as evapotranspiration, soil moisture, and streamflow, however, are mixed, pointing to the significant need to improve the coupling assumptions of these processes within land models. Overall, the interoperable coupling framework demonstrated here offers the opportunity to include more detailed snow physics and processes, and to advance data assimilation systems through improved exploitation of information from snow remote sensing instruments.

Snow model↗
DOE OSTI2012

HANFORD RIVER PROTECTION PROJECT ENHANCED MISSION PLANNING THROUGH INNOVATIVE TOOLS LIFECYCLE COST MODELING AND AQUEOUS THERMODYNAMIC MODELING - 12134

Two notable modeling efforts within the Hanford Tank Waste Operations Simulator (HTWOS) are currently underway to (1) increase the robustness of the underlying chemistry approximations through the development and implementation of an aqueous thermodynamic model, and (2) add enhanced planning capabilities to the HTWOS model through development and incorporation of the lifecycle cost model (LCM). Since even seemingly small changes in apparent waste composition or treatment parameters can result in large changes in quantities of high-level waste (HLW) and low-activity waste (LAW) glass, mission duration or lifecycle cost, a solubility model that more accurately depicts the phases and concentrations of constituents in tank waste is required. The LCM enables evaluation of the interactions of proposed changes on lifecycle mission costs, which is critical for decision makers.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

CSP-Plant Modeling Guidelines and Compliance of the System Advisor Model (SAM): Preprint

Accurately modeling risks, costs, and electricity output is essential to the financing and advancement of concentrating solar power projects. To address this need, a group of CSP experts created a guideline document, titled SolarPACES Guideline for Bankable STE Yield Assessment (1). To make this information more accessible and allow stakeholders to test specific models against the recommendations, the guidelines have been condensed into a spreadsheet-based checklist. The checklist was applied to NREL's System Advisory Model (SAM) CSP modeling software, providing useful feedback to both the checklist group and the SAM development team. This study showed a strong agreement between SAM and the guidelines, demonstrated the use of the guidelines in model validation, and resulted in several recommended improvements to SAM.

14 SOLAR ENERGY↗
DOE OSTI2024

Fuel Performance Modeling Status Update and Potential Model Improvements

Fuel performance modeling status update and potential model improvements overview of TRISO fuel performance modeling codes PARFUME/BISON, AGR experiment support, potential modeling improvements, BISON smeared cracking model, BISON fission product source term, and AGR-3/4 reirradiation heating test.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Modeling atmospheric data and identifying dynamics Temporal data-driven modeling of air pollutants

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. Furthermore, with the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our model using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The electroweak phase transition in the Inert Doublet Model

We study the strength of a first-order electroweak phase transition in the Inert Doublet Model (IDM), where particle dark matter (DM) is comprised of the lightest neutral inert Higgs boson. We improve over previous studies in the description and treatment of the finite-temperature effective potential and of the electroweak phase transition. We focus on a set of benchmark models inspired by the key mechanisms in the IDM leading to a viable dark matter particle candidate, and illustrate how to enhance the strength of the electroweak phase transition by adjusting the masses of the yet undiscovered IDM Higgs states. We argue that across a variety of DM masses, obtaining a strong enough first-order phase transition is a generic possibility in the IDM. We find that due to direct dark matter searches and collider constraints, a sufficiently strong transition and a thermal relic density matching the universal DM abundance is possible only in the Higgs funnel regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Use of a Reduced Order Model (ROM) to Simulate SOFC Performance in System Models

Numerical models for design and optimization of fuel cell-based power generation systems require an accurate representation of the SOFC stack performance over a wide range of operating conditions. Response surface techniques were used with detailed SOFC stack model results to create a computationally efficient reduced order model (ROM) of the stack that retains desirable information about its internal state, which can be important in system optimization studies to preclude operation under off-design conditions that can adversely impact overall reliability. A tool was developed to randomly sample selected input parameters, obtain stack solutions for these sampled cases, perform regression to obtain response surfaces for stack performance and other metrics of interest, and export the response surfaces as a ROM. The ROM was then successfully implemented in an Aspen Plus® system model for a natural gas fuel cell (NGFC) power system. Additional work to characterize the ROM’s approximation error is ongoing.

Modeling & Simulation↗
DOE OSTI2026

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗
DOE OSTI2013

System Advisor Model: Flat Plate Photovoltaic Performance Modeling Validation Report

The System Advisor Model (SAM) is a free software tool that performs detailed analysis of both system performance and system financing for a variety of renewable energy technologies. This report provides detailed validation of the SAM flat plate photovoltaic performance model by comparing SAM-modeled PV system generation data to actual measured production data for nine PV systems ranging from 75 kW to greater than 25 MW in size. The results show strong agreement between SAM predictions and field data, with annualized prediction error below 3% for all fixed tilt cases and below 8% for all one axis tracked cases. The analysis concludes that snow cover and system outages are the primary sources of disagreement, and other deviations resulting from seasonal biases in the irradiation models and one axis tracking issues are discussed in detail.

14 SOLAR ENERGY↗
DOE OSTI2017

Predicting the severity of spurious “double ITCZ” problem in CMIP5 coupled models from AMIP simulations [Tropical versus extratropical origins of the spurious 'double ITCZ' in coupled climate models]

The severity of the double Intertropical Convergence Zone (DI) problem in climate models can be measured by a tropical precipitation asymmetry index (PAI), indicating whether tropical precipitation favors the Northern Hemisphere or the Southern Hemisphere. Examination of 19 Coupled Model Intercomparison Project phase 5 models reveals that the PAI is tightly linked to the tropical sea surface temperature (SST) bias. As one of the factors determining the SST bias, the asymmetry of tropical net surface heat flux in Atmospheric Model Intercomparison Project (AMIP) simulations is identified as a skillful predictor of the PAI change from an AMIP to a coupled simulation, with an intermodel correlation of 0.90. Using tropical top-of-atmosphere (TOA) fluxes, the correlations are lower but still strong. However, the extratropical asymmetries of surface and TOA fluxes in AMIP simulations cannot serve as useful predictors of the PAI change. Furthermore, this study suggests that the largest source of the DI bias is from the tropics and from atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Interface and embedded joint methods for modeling dynamic fracture opening by explosive products [Two methods for modeling dynamic fracture opening by explosive products]

Two computational approaches are proposed in the paper to model dynamic fracture opening by explosive products. The first method assumes that the fractures may be modeled using flow elements embedded along the mesh lines. This method models crack opening in a straightforward way by splitting the nodes of the computational grid. It can account for crack branching; however, the crack directions are constrained by existing mesh faces, which may lead to mesh dependence. Also, the stress in flow elements is calculated explicitly separate from the surrounding solid elements that can impose additional limits on the time step stability condition for explicit integration. The second approach uses embedded flow elements to model the cracks. Typical thickness of the cracks is much smaller than the element size. Therefore, gas pressure in the cracks is assumed to be in stress equilibrium with the element stress. To achieve this, the crack thickness and the state of the gas is updated simultaneously with the state of the solid element which contains the crack. Therefore, the time step is controlled by the explicit solver applied for the solid and does not depend on the thickness of the crack. In conclusion, the main disadvantage of the second approach is due to the complexity of modeling multiple intersecting cracks, which go through the same element. We discuss the areas of possible applications of these 2 methods and the ways to improve and enhance them for future practical applications.

58 GEOSCIENCES↗
DOE OSTI2020

Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition

Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.

Hanson, Joshua↗
DOE OSTI2019

Constraints on mediator-based dark matter and scalar dark energy models using $\sqrt{s}$ = 13 TeV pp collision data collected by the ATLAS detector

Constraints on selected mediator-based dark matter models and a scalar dark energy model using up to 37 fb ₋1 $\sqrt{s}$ = 13 TeV pp collision data collected by the ATLAS detector at the LHC during 2015-2016 are summarised in this paper. The conclusions of experimental searches in a variety of final states are interpreted in terms of a set of spin-1 and spin-0 single-mediator dark matter simplified models and a second set of models involving an extended Higgs sector plus an additional vector or pseudo-scalar mediator. The searches considered in this paper constrain spin-1 leptophobic and leptophilic mediators, spin-0 colour-neutral and colour-charged mediators and vector or pseudo-scalar mediators embedded in extended Higgs sector models. In this case, also $\sqrt{s}$ = 8 TeV pp collision data are used for the interpretation of the results. The results are also interpreted for the first time in terms of light scalar particles that could contribute to the accelerating expansion of the universe (dark energy).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Experimental determination of lead carbonate solubility at high ionic strengths: A Pitzer model description

In this article, solubility measurements of lead carbonate, PbCO 3 (cr), cerussite, as a function of total ionic strengths are conducted in the mixtures of NaCl and NaHCO 3 up to I = 1.2 mol•kg –1 and in the mixtures of NaHCO 3 and Na 2 CO 3 up to I = 5.2 mol•kg –1 , at room temperature (22.5 ± 0.5 °C). The solubility constant (log K sp ) for cerussite, PbCO 3 (cr) = Pb 2+ + CO 3 2- was determined as –13.76 ± 0.15 (2σ) with a set of Pitzer parameters describing the specific interactions of PbCO 3 (aq), Pb(CO 3 ) 2 2- , and Pb(CO 3 )Cl – with the bulk-supporting electrolytes, based on the Pitzer model. The model developed in this work can reproduce the experimental results including model-independent solubility values from the literature over a wide range of ionic strengths with satisfactory accuracy. The model is expected to find applications in numerous fields, including the accurate description of chemical behavior of lead in geological repositories, the modeling of formation of oxidized Pb–Zn ore deposits, and the environmental remediation of lead contamination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗