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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

End-Use Savings Shapes Measure Documentation: Console Water-to-Air Geothermal Heat Pump

Executive Summary Building on the successfully completed effort to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models over the past several years, the objective of this work is to produce national datasets that empower analysts working for federal, state, utility, city, and manufacturer stakeholders to answer a broad range of analysis questions. The goal of this work is to develop energy efficiency, electrification, and demand flexibility end-use load shapes (electricity, gas, propane, or fuel oil) that cover most of the high-impact, market-ready (or nearly market-ready) measures. An end-use savings shape is the difference in energy consumption between a baseline building and a building with an energy efficiency, electrification, or demand flexibility measure applied. It results in a time series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ComStock is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The baseline model intends to represent the U.S. commercial building stock as it existed in 2018. This measure models the conversion of an existing heating, ventilating, and air-conditioning (HVAC) system to a series of “console” water-to-air heat pumps served by a ground heat exchanger. Console water-to-air geothermal heat pumps (GHP) are all-in-one packages that have no or minimal ductwork and serve individual spaces. Properly designed ground heat exchanger-coupled systems can offer benefits in energy efficiency relative to “conventional” HVAC systems, as well as facilitating beneficial electrification. Console GHPs can be coupled to a ground loop on the source side and can directly replace electric baseboard heaters or air-source packaged terminal heat pumps. Console GHPs can also bring in outdoor air for ventilation. This measure will be referred to throughout the document as the “Console GHP” upgrade.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Verification and Validation of a Modified Numerical Algorithm for Simulation of Transient Unconfined Groundwater Flow

This report extends verification and validation testing of the NUFT package of codes (Nitao 2000a,b) to the US1P module of code designed for simulation of single-phase mixed or “coupled” saturated and unsaturated (or “variably saturated”) groundwater flow. Importantly, the verification and validation testing of US1P in this report includes performance evaluation of a modified numerical algorithm that was not included in prior quality assurance (QA) of the NUFT package by Carle et al. (2014) for Underground Test Area (UGTA) project activities, which are directed at assessment of radionuclide contamination in groundwater sourced from underground nuclear test locations at the Nevada National Security Site (NNSS). An immediate purpose of this report is to provide QA for ongoing large-scale, three-dimensional (3-D) groundwater flow modeling of transient water levels associated with longterm water supply pumping and underground nuclear testing at the NNSS (Jackson and Fenelon, 2018; Jackson et al., 2021). For UGTA activities, the QA refers to the standards of ASTM (1996) for verification and validation testing of groundwater modeling codes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

GNET2: an R package for constructing gene regulatory networks from transcriptomic data

Abstract Motivation The Gene Network Estimation Tool (GNET) is designed to build gene regulatory networks (GRNs) from transcriptomic gene expression data with a probabilistic graphical model. The data preprocessing, model construction and visualization modules of the original GNET software were developed on different programming platforms, which were inconvenient for users to deploy and use. Results Here, we present GNET2, an improved implementation of GNET as an integrated R package. GNET2 provides more flexibility for parameter initialization and regulatory module construction based on the core iterative modeling process of the original algorithm. The data exchange interface of GNET2 is handled within an R session automatically. Given the growing demand for regulatory network reconstruction from transcriptomic data, GNET2 offers a convenient option for GRN inference on large datasets. Availability and implementation The source code of GNET2 is available at https://github.com/jianlin-cheng/GNET2. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

solposx: A Python package for determining solar position and atmospheric refraction

solposx is a Python package of reference algorithms for calculating the sun’s position and atmospheric refraction. The package includes 11 solar position algorithms and 6 refraction models from the past 50 years. All functions follow a standardized design pattern, making it easy to compare different algorithms. The provided algorithm implementations have been thoroughly vetted, making the package a valuable research tool and a reliable reference for implementing solar position algorithms in other programming languages or applications.

Jensen, Adam R. [Technical University of Denmark, ↗
DOE OSTI2026

Statistical generic design of glass and optimization: Selective review on oxide glasses

Designing a single glass composition for a multidimensional property space is challenging, and the difficulty increases with the number of design criteria. Traditionally, the task is accomplished using multiple statistical models that describe the relationships between composition (C) and property (P) values, i.e., C-P models. Recently, the structure (S)-property (P) statistical modeling has emerged as a complementary approach. The S-P modeling approach has also been shown to be a preferred method for modeling glass properties, particularly when a small data set is available, such as in single-component studies, or when strong nonlinearities exist between composition and properties. The combined model package, C-S-P, implements the concept of generic glass design, i.e., designing glass for performance by first selecting a specific or optimized set of glass network structural groups using S-P models and then transferring the designed structures (genes) to a particular composition using C-S models. This article reviews a set of supporting cases from the previous C-S-P modeling studies of phosphate, silicate, and borosilicate glasses, which are relevant for many critical commercial applications. The methodology for developing the statistical C-S-P database is presented, enabling the application of P?S?C to achieve a generic glass design and optimization, targeting multiple design criteria for both performance and processing properties simultaneously.

Network structure↗
DOE OSTI2023

Numerical Optimization of Spray-Guided Spark Assistance for Cold Idle Operation in a Heavy-Duty Gasoline Compression Ignition Engine

This article describes the results of a response surface model (RSM)-based numerical optimization campaign for spray-guided spark assistance at cold operations in a heavy-duty gasoline compression ignition (GCI) engine. On the basis of an earlier work on spark-assisted GCI cold combustion, a space-filling design of experiments (DoE) method was first undertaken to investigate a multitude of hardware design variables and engine operating parameters. The main design variables included the number of injector nozzles, fuel split quantities and injection timings, and spark timing. The objective variables were engine combustion efficiency (ŋ c ), maximum pressure rise rate (MPRR), and engine-out nitrogen oxide (NO x ) emissions. A total of 150 design candidates were automatically generated using the Sobol sequence method provided by the commercial software package, CAESES. Then, closed-cycle computational fluid dynamic (CFD) spark-assisted GCI simulations under cold idling operations were performed. The outcomes from the CFD-DoE design campaign were utilized to construct high-fidelity RSMs that allowed for further design optimization of the spark plug- and fuel injector-related design variables, along with fuel injection strategy parameters. A merit function with respect to objective variables was formulated with an appropriate weight assignment on each objective variable. Finally, the best design candidate was identified from the RSM-based optimization process and further validated in the CFD analysis. The best design candidate showed the potential to significantly improve combustion efficiency (ŋ c > 90%) over the baseline at cold idle while satisfying MPRR and NOx emissions constraints (MPRR < 5 bar/CAD and NO x < 4.5 g/kWh).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

DESIGN AND TESTING OF A 275 BAR 700 DEGREE CELSIUS EXPANDER FOR AN INTEGRALLY GEARED SUPERCRITICAL CO2 COMPANDER

An integrally-geared (IG) compressor-expander (compander) for use in a nominal 10 MW-scale concentrated solar power (CSP) supercritical carbon dioxide (sCO2) plant application was designed, manufactured, and tested. The integrally-geared compander (IGC) developed for this application comprises multiple pinion shafts interacting through a single bull gear to create a compact package and utilize a lowcost, low-speed driver. The present work will detail the design of the high-pressure high-temperature expander casing on an integrally geared frame, and illustrate how the project successfully mitigated the risk of fatigue and creep while allowing for rapid thermal transients in the design. Furthermore, test data from the test campaign will be presented supporting the analysis. Test results also show temperature profiles during operation exceeding 720° Celsius.

wilkes, jason↗
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 OSTI2026

Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)↗
DOE OSTI2023

Operando Temperature Measurements of Photovoltaic Laser Power Converter Devices Under Continuous High-Intensity Illumination

Photovoltaic devices that operate under extremely high irradiances, such as laser power converters (LPCs), may also operate at elevated temperatures, even under active cooling, as the result of large temperature gradients. We demonstrate the operation of GaAs LPC devices under orders of magnitude of irradiances up to 150 W/cm 2 in a monochromatic laser simulator with an active cooling stage. The steady-state open-circuit voltage (V OC ) as a function of irradiance is known to droop at high irradiance as the result of junction heating, but the junction temperature can be difficult to measure by conventional methods. Fast, transient V OC measurements under these extreme operating conditions are used here to determine the junction temperature. Empirical V OC temperature coefficients of the devices at each irradiance of interest are determined and used as an integral part of this technique. We show that the thermal design of different LPC devices strongly affects the operating temperature of the junctions. Knowledge of the operating temperature can be a strong tool for understanding the nature of loss mechanisms and improving the design for the operation of photovoltaic LPCs at high irradiances. Furthermore, this technique can be used for laboratory devices during initial design as well as to characterize mass-produced and packaged devices for quality control.

14 SOLAR ENERGY↗
DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗
DOE OSTI2023

Space Situational Awareness for Python

SSAPy is a python package allowing for fast and precise orbital modeling. SSAPy is designed with speed and accuracy in mind and offers the following capabilities: - A variety of integrators, including Runge-Kutta, SciPy, SGP4, etc. - Customizable force propagation models, including a variety of Earth gravity models, lunar gravity, radiation pressure, etc. - Multiple-hypothesis tracking (MHT) UCT linker - Vectorized computations - Short arc probabilistic orbit determination - Conjunction probability estimation - Uncertainty quantification - Monte Carlo data fusion - Support for multiple coordinate frames (with coordinate frame conversions)

Schlafly, Edward↗
DOE OSTI2025

OpenFerro v0.1.0

OpenFerro is a Python package for on-lattice atomistic dynamics simulation of ferroic materials. OpenFerro is based on JAX, a high-performance linear algebra package supporting auto-differentiation and GPU acceleration. OpenFerro is designed to minimize the effort required to build on-lattice Hamiltonian models, and to perform molecular dynamics (MD) and Landau-Lifshitz-Gilbert simulations. Unlike existing codes, OpenFerro provides a unified interface to model different types of local order parameters.

Xie, Pinchen [Lawrence Berkeley National Laborator↗
DOE OSTI2020

Permanent Criticality Termination Processes in Disposed DPCs

This report aims at answering what, how, and when spent nuclear fuel (SNF) or dual-purpose canister (DPC) characteristics could be impacted by disposal events and processes, including decay, corrosion, dissolution, and criticality, such that the potential for criticality initiation or continuation in disposed DPCs becomes permanently significantly diminished. This report uses the term "permanent termination of criticality to denote the significant diminishment of criticality potential, not absolute prevention. The occurrence of disposal processes and events is a direct function of disposal time. For fundamental processes (e.g., decay), time is absolute; however, for other processes (e.g., corrosion), time is relative because it is driven by a combination of DPC characteristics (e.g., fuel conditions, basket composition), geologic parameters (e.g., infiltration rate), engineered barrier design, and other processes and events that impact in-package chemistry.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Machine Learning Enabled Sensor Fusion for In-Situ Defect Detection in Laser Powder Bed Fusion

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. The current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques such as X-Ray Computed Tomography (XCT), which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. RTX Technologies Research Center (RTRC) has licensed ORNL’s Peregrine software package – a printer- and camera-agnostic data analytics tool designed specifically for detecting process anomalies using in situ data collected during powder bed printing. The goal of this project was to feed temporally rich, multi-modal sensor data, including visible light, integrated near infrared (NIR), and spatially mapped co-axial melt pool thermal emission data into Peregrine to enable detection of subsurface flaws. XCT data was used as ground truth training data to allow Peregrine’s deep learning algorithms to recognize anomalies in these complex data streams in both test artifacts and industrially relevant geometries. Completion of this program has seen the successful implementation of multi-modal, multi-layer sensor data footprints for training of machine learning models in Peregrine. Flaws detected in XCT data have been successfully detected directly from this in situ data footprint, and initial analyses of the in situ probability-of-detection has been conducted, showing performance levels commensurate with traditional non-destructive evaluation (NDE) methods. The in situ monitoring methodology was then applied to an industrially relevant component that was using post-build NDE, highlighting the utility of the proposed method for hard-to-inspect AM components. As a direct result of this program, two journal manuscripts [1], [2] have been published in Additive Manufacturing, with additional manuscripts planned following program completion.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimizing Batch Crystallization with Model-based Design of Experiments

Poster for Foundations of Computer Aided Process Design (FOCAPD) 2024 describing the formality of model-based design of experiments for batch crystallization. This paper focuses on the implementation of model-based design of experiments for parameter precision, enabled by Pyomo.DoE, a package in Python. Specifically, this work outlines an identifiability analysis for the estimability of the model parameters in a batch crystallization system.

Lynch, Hailey↗
DOE OSTI2025

Custom Equipment Development for Processing of Surplus Plutonium

Facilities and Material • Location: Savannah River Site K-Area, South Carolina • Plutonium designated as surplus is blended with adulterant material, re-packaged and shipped to WIPP in New Mexico • Currently one operational glovebox for downblending, facility modifications and construction of three additional glovebox lines in progress • Current operations are highly manual requiring full PPE and reader/worker steps

Krementz, Daniel [Savannah River National Laborato↗
DOE OSTI2020

Improving Heat Conduction of Insulated Metal Substrate with Thermal Pyrolytic Graphite Core for SiC Power Module Packaging

TPG-core IMS concept was jointly explored in this study. Integrating high thermally conductive TPG graphite core into IMS is expected to simultaneously achieve high thermal conductivity from TPG and electrical functionalities from IMS. Nearly 2x thermal conductivity and 30% weight saving was demonstrated on TPG-core IMS compared to conventional Cu-core IMS. Significant junction temperature reduction (11°C) in steady state and power cycling was revealed by the thermal analysis as the result of improved thermal spreading in plane and through the thickness. The study also proved the manufacturability and compatibility of this TPG-core IMS structure to the existing IMS production and power module assembling. Finally, the integration of TPG and IMS paves a new packaging route to increase heat load, improve reliability, simplify module design and reduce assembling cost and number of steps.

36 MATERIALS SCIENCE↗