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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Vertically Resolved Retrievals of Aerosol Concentrations and Effective Radii from the DOE Combined HSRL and Raman lidar Measurement Study (CHARMS) Merged High-Spectral-Resolution Lidar-Raman Lidar Data Set

The Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility is a key component of DOE’s research strategy to address global climate change. The objective of the ARM Facility is to provide an experimental testbed for studying important atmospheric effects, particularly cloud and aerosol processes, and testing parameterizations of these processes for use in climate change models. ARM observational sites include a broad array of instruments to characterize cloud and aerosol properties, atmospheric state variables, and incoming and outgoing radiation. Advanced lidar systems provide valuable and unique information about the atmospheric column. We examine the potential for providing vertically resolved information about aerosol size and concentration with a combination of two such lidar systems, the Raman lidar and the High-Spectral-Resolution Lidar (HSRL). Currently ARM has a limited ability to remotely measure profiles of aerosol optical and microphysical properties on an operational basis. Although the Southern Great Plains (SGP), Eastern North Atlantic (ENA), and North Slope of Alaska (NSA, Oliktok Point location only) Raman lidars provide profiles of aerosol backscatter and extinction at 355 nm, additional information is required to better characterize the impacts of aerosols on radiation and clouds. Recent advances in lidar retrieval theory and algorithm development (Müller et al. 1999, 2014; Chemyakin et al. 2014) demonstrate that multi-wavelength lidar retrieval algorithms that use measurements of aerosol extinction at both 355 and 532 nm and backscatter at 355, 532, and 1064 nm have the potential to constrain both the aerosol optical (e.g., complex index of refraction, scattering, etc.) and microphysical properties (e.g., effective radius, concentration). This advancement greatly increases the utility of the remote-sensed aerosol observations. Based on this work, the HSRL group at the National Aeronautics and Space Administration (NASA)’s Langley Research Center (LaRC) developed automated algorithms for retrieving aerosol optical and microphysical properties, demonstrated these retrievals using data from the unique NASA/LaRC airborne multi-wavelength HSRL-2 system, and validated these retrievals using coincident airborne in situ data (Müller et al. 2014; Sawamura et al. 2017). We report here on the use of ARM instrumentation to gather a multi-wavelength ground-based lidar data set to test such retrievals. Continuous (24/7) operation of the co-located SGP Raman lidar and University of Wisconsin (UW) HSRL during the 10-week Combined HSRL and Raman lidar Measurement Study (CHARMS) (mid-July through September 2015) allowed the acquisition of a unique, multi-wavelength ground-based lidar data set. The ARM SGP Raman lidar (RLID) measured profiles of aerosol backscatter, extinction, and depolarization at 355 nm and profiles of water vapor mixing ratio and temperature. The UW HSRL simultaneously measured profiles of aerosol backscatter, extinction and depolarization at 532 nm and aerosol backscatter at 1064 nm. This RLID+HSRL combination provided a test data set to investigate these more advanced aerosol retrieval techniques with the potential to greatly improve aerosol characterization in the lower atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

FY2017 Updates to the SAS4A/SASSYS-1 Safety Analysis Code

The SAS4A/SASSYS-1 safety analysis software is used to perform deterministic analysis of anticipated events as well as design-basis and beyond-design-basis accidents for advanced fast reactors. It plays a central role in the analysis of U.S. DOE conceptual designs, proposed test and demonstration reactors, and in domestic and international collaborations. This report summarizes the code development activities that have taken place during FY2017. Extensions to the void and cladding reactivity feedback models have been implemented, and Control System capabilities have been improved through a new virtual data acquisition system for plant state variables and an additional Block Signal for a variable lag compensator to represent reactivity feedback for novel shutdown devices. Current code development and maintenance needs are also summarized in three key areas: software quality assurance, modeling improvements, and maintenance of related tools. With ongoing support, SAS4A/SASSYS-1 can continue to fulfill its growing role in fast reactor safety analysis and help solidify DOE’s leadership role in fast reactor safety both domestically and in international collaborations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A time-parallel method for the solution of PDE-constrained optimization problems

We study a time-parallel approach to solving quadratic optimization problems with linear time-dependent partial differential equation (PDE) constraints. These problems arise in formulations of optimal control, optimal design and inverse problems that are governed by parabolic PDE models. They may also arise as subproblems in algorithms for the solution of optimization problems with nonlinear time-dependent PDE constraints, e.g., in sequential quadratic programming methods. We apply a piecewise linear finite element discretization in space to the PDE constraint, followed by the Crank-Nicolson discretization in time. The objective function is discretized using finite elements in space and the trapezoidal rule in time. At this point in the discretization, auxiliary state variables are introduced at each discrete time interval, with the goal to enable: (i) a decoupling in time; and (ii) a fixed-point iteration to recover the solution of the discrete optimality system. The fixed-point iterative schemes can be used either as preconditioners for Krylov subspace methods or as smoothers for multigrid (in time) schemes. We present promising numerical results for both use cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Numerical Integration of Viscoelastic Models

Accurate modeling of viscoelasticity remains an important consideration for a variety of materials (e.g. polymers and inorganic glasses). As such, over the previous decades a substantial body of work has been dedicated to developing appropriate constitutive models for viscoelasticity ranging from initial considerations of linear thermoviscoelasticity to more complex non-linear formulations incorporating fictive temperatures or potential energy clocks including the use of both internal state variable(ISV) and hereditary integral representations. Nonetheless, relatively limited (in comparison to plasticity) attention has been paid to the numerical integration of such schemes. In terms of integral based formulations, Taylor et al. first considered the problem of the integration of a linear viscoelasticity model. That work focused on the integration of the hereditary integrals and demonstrated improved performance of the new scheme with a custom finite element code over an existing finite difference reference. Chambers and Becker, using a free volume based shift factor, also considered the integration of the hereditary integrals and the impact on the problem of a pressurized thick-walled cylinder and developed an adaptive scheme to bound the error. Chambers later developed three-point Gauss and composite integration schemes for the hereditary integrals and noted improved accuracy. With respect to ISV-based schemes, formulations for the non-linear Schapery model have been proposed. However, in those efforts greater attention was paid to convergence of the non-linear solution scheme than impact of numerical integration. Various authors (e.g. Holzapfel and Simo and Hughes) have also studied the use of convolution integrals with differential forms of ISVs for temperature-independent formulations. Regardless, while the "potential energy clock" (PEC) and "simplified potential energy clock"(SPEC) models have been used to study a variety of non-linear responses (e.g.), limited attention has been paid to the numerical performance. As will be discussed later, the "clock" at the center of the formulations includes temperature and complex history dependence making the numerical integration of such a model even more challenging. Thus, in the current work an initial effort towards characterizing the numerical integration of the constitutive model through simplified problems is performed. To that end, in Section 2 the theory of the model is briefly presented while the numerical integration is discussed in Section 3. Results of various studies characterizing the numerical behavior and performance are then given in Section 4. Finally, some concluding remarks and thoughts for follow on works are provided in Section 5.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Eulerian Applications Project - xRage: High Explosives Package [Slides]

At the most elementary level, the high explosive model in xRage (or many other hydro codes) computes the amount of material that changes from a high explosive reactant to a high explosive product during a time step and accounts for the energy added to the flow by this reaction. The actual chemical reactions that occur during this conversion are not modeled. These processes are very complicated and involve levels of spatial and temporal resolution that are generally not practical for an application code. They would also require a state variable representation that includes all of the chemical species that are produced by the reaction and account for multiple stage chemical reactions. Instead the explosive models we generally use are phenomenological and try to represent the most important physics that drive the explosive wave in a very simplified way. These models generally have a number of tunable parameters that must be calibrated to experiment.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

Development of a Multi-physics Capability for Predicting Residual Stress in a GTS Reservoir.

This report documents completion of a Level 2 Milestone on the development of a multi-physics capability to predict the evolving material state through the manufacturing process of a Gas Transfer Systems (GTS) reservoir. We present details on new developments and capability improvements that address the following completion criteria: (i) validation of a microstructure evolution model, including recrystallization and strain aging, (ii) demonstration of the capability to remesh, map and transfer material state (internal state variables) and residual stress from forging to machining to welding processes, and (iii) formal V&V characterization and quantification of uncertainties of material parameters and manufacturing process parameters on residual stress.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modular Linear Thermoviscoelastic Model

Time-dependent, viscoelastic responses of materials like polymers and glasses have long been studied. As such, a variety of models have been put forth to describe the behavior including simple rheological models (e.g. Maxwell, Kelvin), linear "fading memory" theories, and hereditary integral based linear thermal viscoelastic approaches as well as more recent nonlinear theories that are either integral, fictive temperature, or differential internal state variable based. The current work details a new LINEAR_THERMOVISCOELASTIC model that has been added to LAME. This formulation represents a viscoelastic theory that neglects some of the phenomenological details of the PEC/SPEC models in favor of efficiency and simplicity. Furthermore, this new model is a first step towards developing "modular" viscoelastic capabilities akin to those available with hardening descriptions for plasticity models in LAME. Specifically, multiple different (including user-defined) shift-factor forms are implemented with each being easily selected via parameter specification rather than requiring distinct material models.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simple Algorithms for a Physics Code Base

Project 1: Developing a container for state variables in a physics code. Project 2: Setting up near-continuous performance and usage metrics monitoring of a physics code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Navigation and Meteorological Data from Multiple Sensors on Airborne Platform (NAVMET-AIR) Value-Added Product Report

The Navigation and Meteorological Data from Multiple Sensors on Airborne Platform (NAVMET-AIR) value-added product encompasses the aafnaviwg data set in the ARM Data Center (ADC), known as the IWG file, named for the Inter-Agency Working Group for Airborne Data and Telemetry Systems (IWGADTS). Its purpose is to produce a suite of tools to promote standardization of instrument interface, data format, and data processing. This data set’s contents are navigational and meteorological state variables at 1 Hz. It also contains higher-order data flags created by ARM Aerial Facility (AAF) scientists to aid analysis such as periods when the aircraft is flying level, operating in maneuvers, or flying through cloud. Due to the nature of research flights, the payload of the aircraft consists of many duplicate and overlapping instruments to ensure, in case of instrument failure, there is a backup to record the data. Measurements from multiple instruments are consolidated into a single file. Each variable of this data set is carefully chosen from the onboard instrumentation and quality checked by AAF scientists to create this wholistic and most accurate data set for airborne research. This document is intended to be a hub towards the individual “read me” files produced for each campaign. For reference about what instrument was used for calculations on specific days, the read me files are located in the ARM IOP archive at the addresses listed, or access the IOP (intensive operational period) database at https://www.archive.arm.gov/.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Facilitating better and faster simulations of aerosol-cloud interactions in Earth system models

Focal Area(s): 1. Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising a hierarchy of models. 2. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: One major challenge that Earth system models (ESMs) face in providing credible prediction of the Earth system and its water cycle characteristics (e.g., mean state, variability, and extreme events) is to accurately simulate aerosol-cloud interactions (ACI). The physical, chemical, and dynamical processes affecting ACI are extremely complex and they range from nanoscale to planetary scale. In each model development cycle, scientists spend significant efforts investigating model deficiencies and uncertainties associated with aerosols (e.g., emissions, chemical processes, aerosol microphysics, and transport) and clouds (e.g., macrophysics, microphysics, turbulence, and large-scale circulation) in order to develop improved treatments. However, despite decades of active research, ACI is still a major source of uncertainty in climate projections, even though great progress has been made. Specific scientific challenges include: (i) Parameterizations are developed based on limited data; (ii) The complexity of a parameterization required for accurate predictions is not understood; (iii) Incomplete and unknown physics leads to errors in the fully coupled Earth system; and (iv) Complex physics is computationally too expensive to employ in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Thermomechanical Modeling of Copper

The plastic deformation of metals is a dissipative process. Some fraction of the plastic work is converted to heat which, given the temperature dependent response of metals, produces a thermal-mechanical coupling. In various cases, for instance when the loading is dynamic, this interaction can impact the resulting response of a material and/or system. Thus, appropriately capturing the heat generation from plastic work is necessary for various solid mechanics analysis. Determination of the fraction of work converted to heat has been long studied. Recent developments have demonstrated that the fraction is not constant but depends on various state variables. Resolving these features requires combined modeling and experimental studies. To this end, 304L stainless steel – a poor thermal conductor – was recently subjected to such an investigation. Advanced modeling capabilities were deployed to assess novel thermomechanically coupled experiments. As a complement to that study, in the current work a similar investigation is performed on copper – a good thermal conductor – to assess performance on the opposite end of the spectrum. The current document discusses these modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Modeling Oxygen Partial Pressure in Solid Oxide Electrolysis Cells: The Microstructure Effect

Oxygen partial pressure is an important thermodynamic state variable that affects both the performance and degradation of solid oxide electrolysis cells. In this work, a 3D model developed from Virkar’s 1D model has been applied to reconstructed and synthetic microstructures of Ni-YSZ-GDC-LSCF cell. The effect of the microstructures, including the thickness of the YSZ and GDC layer, and the compositions of the hydrogen and oxygen electrode, on the distribution of oxygen partial pressure has been investigated. The results show that the maximum oxygen partial pressure may occur on the interface between oxygen electrode and GDC layer or between GDC layer and YSZ layer depending on the rate of oxygen ion exchange between GDC and YSZ. A thicker GDC layer lowers the maximum oxygen partial pressure in the cell, while a thicker YSZ layer lowers the maximum oxygen partial pressure in the hydrogen electrode. In addition, the Ni:YSZ ratio and porosity also affects the maximum partial pressure. These findings provide insights on mitigating degradation in solid oxide electrolysis cell by tuning the microstructures.

Lei, Yinkai↗
DOE OSTI2025

Deep Learning-based Surrogate Model for Efficient Reservoir Simulation in Large-scale Geological Carbon Storage: Application in IBDP Dataset

This project introduces an advanced deep learning (DL)-based surrogate modeling approach to enhance the efficiency and accuracy of large-scale geological carbon storage (GCS) simulations. Using the Illinois Basin Decatur Project (IBDP) dataset as training data, the study employs a residual U-Net architecture to predict critical state variables such as pressure and CO₂ saturation, as well as CO₂ plume migration. By incorporating key geological parameters (e.g., porosity, permeability, and rock facies) and physics-informed inputs like the diffusive time of flight and time step, the DL model effectively reduces computational complexity while maintaining robust physical constraints. Compared to traditional simulators like Eclipse, the DL model achieves remarkable accuracy, with a root mean square error (RMSE) of 1.57 psi for pressure and 0.007 for saturation, and dramatically reduces computational time from hours to just 69.9 seconds for 50-step simulations. These results demonstrate the potential of innovative DL methodologies to improve the predictivity and operational efficiency of GCS simulations, providing a reliable foundation for decision-making in CCS operations. Supported by the SMART initiative, this project underscores the success of leveraging computational innovations to advance CCS technologies.

advanced deep learning↗
DOE OSTI2017

Restart File Improvements for MPACT

This report documents the work performed to address several defects and features request related to the restart capability in MPACT. The following defects were fixed as a part of this milestone: • #3616 (Defect) Error in MPACT Restart Files with BPRs, • #3637 (Defect) Restart with Semi-PC Yields Inconsistent Results, • #3652 (Defect) Fix Incorrect Exposure Value on HDF File After Restart, • #3777 (Defect) Fix State Point Number when Using Restart File, • #3986 (Defect) Pin Exposures are Incorrect, • #4106 (Defect) Pin Exposures Equal to Zero After Restart, and • #4288 (Defect) Core Average Exposure Wrong when Reading Restart Files. The new features that were added are: • Axial Re-meshing capability, • Incorporation of MAMBA-1D data necessary to restart coupled MPACT/CTF/MAMBA calculations, and • Addition of state variables to the restart file. Numerous tests were also implemented to verify and protect these features and this report was prepared to document the work performed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Surface Meteorological Station - Astoria, OR (AST) - Raw Data

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

17 WIND ENERGY↗
DOE OSTI2021

Surface Meteorological Station - Forks, WA (FKS) - Raw Data

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

17 WIND ENERGY↗
DOE OSTI2021

Surface Meteorological Station - North Bend, OR (OTH) - Raw Data

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

17 WIND ENERGY↗