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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Thermomechanical analysis and modeling of involute-shaped fuel plates using the Cheverton–Kelley experiments for the High Flux Isotope Reactor

Three research reactors with involute-shaped fuel plates are pursuing conversion from highly enriched uranium to low-enriched uranium fuel. Various core design and safety evaluation studies are essential to assess the feasibility of the conversion. The use of 3D computational multiphysics codes is being explored in these analyses and therefore they must undergo a thorough evaluation and quality assurance process due to their potential impact on nuclear safety. Here, the Cheverton and Kelley physical tests performed in the late 1960s to investigate the deflections of HFIR’s outer plate under uniform pressure and temperature fields are simulated by employing commercially available computational codes, with the goals to (1) verify and validate the models and numerical solvers implemented in the codes for thermomechanical analysis of involute reactor plates and (2) to develop a benchmark computational test to evaluate future versions of existing software or newly developed computational codes. The results of the simulations showed good agreement with each other as well as against the Cheverton–Kelley experimental data. Some minor deviations were observed for a few multiphysics cases and their potential origins and impact on the analysis results is investigated in the paper. The validated models increase the confidence in using multiphysics codes to evaluate existing or new LEU designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Material Assessment for ITER's Collective Thomson Scattering first mirror

The International Thermonuclear Energy Reactor (ITER) Collective Thomson Scattering (CTS) system is a diagnostic instrument that measures plasma density and velocity through Thomson scattering of microwave radiation. Some of the key components of the CTS are quasi-optical mirrors that are used to produce astigmatic beam patterns, which have impact on the strength and spatial resolution of the diagnostic signal. The mirrors are exposed to neutron radiation, which may alter the quality of the signal received. In this work, three different materials (molybdenum (Mo), stainless steel 316 (SS-316) and tungsten (W)) are considered for the first mirror of the CTS. The objective is to access which of the material studied are best suited for this mirror, considering different neutron radiation loads simulated scenarios defined by ITER, based on the resultant stresses and temperature distributions. For it, the neutron irradiation, and subsequent heat-load on the mirrors are simulated using the Monte Carlo N-Particle (MCNP) code. Based on the MCNP heat-load results, transient thermal-structural Finite Element Analysis (FEA) of the mirror over a 400 s discharge, with and without cooling on the rear side, are conducted using in commercial FEA software ANSYS. Results show that of the tested materials Mo and W are the most suitable material for this application. Even though, this study does not yet consider the variation of the material properties with temperature, it presents a quick initial satisfactory assessment that may be considered in subsequent and more complex analysis. (authors)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Evaluation of Multiple Inverter Volt-VAR Control Interactions with Realistic Grid Impedances

Integration of large numbers of distributed photovoltaic (PV) systems in electric distribution circuits often requires advanced functions (e.g. volt-VAR, frequency-Watt etc.). However, significant concerns have been raised about potential for PV inverters with such controls to interact with one another in a way that could cause grid instability. The lack of standardized inverter models makes it hard to simulate such transient interactions in software. Similarly it is very hard to test these dynamic inverter interactions in the laboratory. In this paper, unique Power Hardware-in-the-Loop (PHIL) techniques are presented to experimentally test for interactions of multiple PV inverters connected to multiple points-of-common-coupling (PCCs) with grid impedances between them. Sample test results are provided from simulation-only scenarios and PHIL testing. Though simulation results indicated possible harmful interactions between inverters' volt-VAR controllers; no such interactions were found in the limited hardware testing.

14 SOLAR ENERGY↗
DOE OSTI2016

Three-dimensional quadratic modeling and quantitative evaluation of the diaphragm on a volumetric CT scan in patients with chronic obstructive pulmonary disease

Purpose: In patients with chronic obstructive pulmonary disease (COPD), diaphragm function may deteriorate due to reduced muscle fiber length. Quantitative analysis of the morphology of the diaphragm is therefore important. In the authors current study, they propose a diaphragm segmentation method for COPD patients that uses volumetric chest computed tomography (CT) data, and they provide a quantitative analysis of the diaphragmatic dimensions. Methods: Volumetric CT data were obtained from 30 COPD patients and 10 normal control patients using a 16-row multidetector CT scanner (Siemens Sensation 16) with 0.75-mm collimation. Diaphragm segmentation using 3D ray projections on the lower surface of the lungs was performed to identify the draft diaphragmatic lung surface, which was modeled using quadratic 3D surface fitting and robust regression in order to minimize the effects of segmentation error and parameterize diaphragm morphology. This result was visually evaluated by an expert thoracic radiologist. To take into consideration the shape features of the diaphragm, several quantification parameters—including the shape index on the apex (SIA) (which was computed using gradient set to 0), principal curvatures on the apex on the fitted diaphragm surface (CA), the height between the apex and the base plane (H), the diaphragm lengths along the x-, y-, and z-axes (XL, YL, ZL), quadratic-fitted diaphragm lengths on the z-axis (FZL), average curvature (C), and surface area (SA)—were measured using in-house software and compared with the pulmonary function test (PFT) results. Results: The overall accuracy of the combined segmentation method was 97.22% ± 4.44% while the visual accuracy of the models for the segmented diaphragms was 95.28% ± 2.52% (mean ± SD). The quantitative parameters, including SIA, CA, H, XL, YL, ZL, FZL, C, and SA were 0.85 ± 0.05 (mm{sup −1}), 0.01 ± 0.00 (mm{sup −1}), 17.93 ± 10.78 (mm), 129.80 ± 11.66 (mm), 163.19 ± 13.45 (mm), 71.27 ± 17.52 (mm), 61.59 ± 16.98 (mm), 0.01 ± 0.00 (mm{sup −1}), and 34 380.75 ± 6680.06 (mm{sup 2}), respectively. Several parameters were correlated with the PFT parameters. Conclusions: The authors propose an automatic method for quantitatively evaluating the morphological parameters of the diaphragm on volumetric chest CT in COPD patients. By measuring not only the conventional length and surface area but also the shape features of the diaphragm using quadratic 3D surface modeling, the proposed method is especially useful for quantifying diaphragm characteristics. Their method may be useful for assessing morphological diaphragmatic changes in COPD patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-C-207B-05: Tissue Segmentation of Computed Tomography Images Using a Random Forest Algorithm: A Feasibility Study

Purpose: Develop an automated Random Forest algorithm for tissue segmentation of CT examinations. Methods: Seven materials were classified for segmentation: background, lung/internal gas, fat, muscle, solid organ parenchyma, blood/contrast, and bone using Matlab and the Trainable Weka Segmentation (TWS) plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance each evaluated over a pixel radius of 2n, (n = 0–4). Also noise reduction and edge preserving filters, Gaussian, bilateral, Kuwahara, and anisotropic diffusion, were evaluated. The algorithm used 200 trees with 2 features per node. A training data set was established using an anonymized patient’s (male, 20 yr, 72 kg) chest-abdomen-pelvis CT examination. To establish segmentation ground truth, the training data were manually segmented using Eclipse planning software, and an intra-observer reproducibility test was conducted. Six additional patient data sets were segmented based on classifier data generated from the training data. Accuracy of segmentation was determined by calculating the Dice similarity coefficient (DSC) between manual and auto segmented images. Results: The optimized autosegmentation algorithm resulted in 16 features calculated using maximum, mean, variance, and Gaussian blur filters with kernel radii of 1, 2, and 4 pixels, in addition to the original CT number, and Kuwahara filter (linear kernel of 19 pixels). Ground truth had a DSC of 0.94 (range: 0.90–0.99) for adult and 0.92 (range: 0.85–0.99) for pediatric data sets across all seven segmentation classes. The automated algorithm produced segmentation with an average DSC of 0.85 ± 0.04 (range: 0.81–1.00) for the adult patients, and 0.86 ± 0.03 (range: 0.80–0.99) for the pediatric patients. Conclusion: The TWS Random Forest auto-segmentation algorithm was optimized for CT environment, and able to segment seven material classes over a range of body habitus and CT protocol parameters with an average DSC of 0.86 ± 0.04 (range: 0.80–0.99).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

MPCpy v0.1

This software can be used to develop and test Model Predictive Control (MPC) algorithms with simulated buildings or deploy MPC in real buildings. This includes the gathering of exogenous data, training of simplified models, and control optimization.

Blum, David↗
DOE OSTI2021

Skywalker v.2

SAND2022-2193 O Skywalker is a software library that facilitates the creation of test drivers for atmospheric parameterizations used in climate models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Overfelt, James↗
DOE OSTI2024

pnnl-predictive-phenomics/csc052-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Bacillus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

Torres, Victor E.↗
DOE OSTI2024

pnnl-predictive-phenomics/csc031-gem

Genome-Scale Metabolic Model of CarbStor Community member Microbacterium (csc031) Continuous Validation with Memote These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity

McNaughton, Andrew [@PNNL]↗
DOE OSTI2024

pnnl-predictive-phenomics/csc009-gem

Genome-Scale Metabolic Model of CarbStore Community member Curtobacterium (csc009) Continuous Validation with Memote These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity

Lin, Tesia↗
DOE OSTI2024

pnnl-predictive-phenomics/csc040-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Rhodococcus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

McNaughton, Andrew [@PNNL]↗
DOE OSTI2024

pnnl-predictive-phenomics/csc043-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Paenibacillus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

Zucker, Jeremy [Pacific Northwest National Laborat↗
DOE OSTI2020

Framework For Spatial Agricultural Crop Yield Prediction Model Development

This framework was developed to provide data preprocessing for spatiotemporal agricultural yield data and remote sensing data for modelling using artificial neural networks (ANNs) to predict subfield crop yield estimates. The software includes methods to train, validate, and test ANN models. It also include methods to infer on new remote sensing data.

Griffel, LloydM.↗
DOE OSTI2013

AGR-2 Data Qualification Report for ATR Cycles 151B-2, 152A, 152B, 153A, 153B and 154A

This report documents the data qualification status of AGR-2 fuel irradiation experimental data from Advanced Test Reactor (ATR) Cycles 152A, 152B, 153A, 153B, and 154A, as recorded in the Nuclear Data Management and Analysis System (NDMAS). The AGR-2 data streams addressed include thermocouple (TC) temperatures, sweep gas data (flow rate, pressure, and moisture content), and fission product monitoring system (FPMS) data for each of the six capsules in the experiment. A total of 13,400,520 every minute instantaneous TC and sweep gas data records were received and processed by NDMAS for this period. Of these data, 8,911,791 records (66.5% of the total) were determined to be Qualified based on NDMAS accuracy testing and data validity assessment. For temperature, there were 4,266,081 records (74% of the total TC data) that were Failed due to TC instrument failures. For sweep gas flows, there were 222,648 gas flow records (2.91% of the flow data) that were Failed. The inlet gas flow failures due to gas flow cross-talk and leakage problems that occurred after Cycle 150A were corrected by using the same gas mixture in all six capsules and the Leadout. For FPMS data, NDMAS received and processed preliminary release rate and release-to-birth rate ratio (R/B) data for three reactor cycles (Cycles 149B, 150B, and 151A) . This data consists of 45,983 release rate records and 45,235 R/B records for the 12 radionuclides reported. The qualification status of these FPMS data has been set to In Process until receipt of Quality Assurance-approved data generator reports. All of the above data have been processed and tested using a SAS®-based enterprise application software system, stored in a secure Structured Query Language database, made available on the NDMAS Web portal (http://ndmas.inl.gov), and approved by the INL STIM for release to both internal and appropriate external Very High Temperature Reactor Program participants.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Pilot Readiness Development Program for Autonomous Pathogen Detection System (APDS) (Final Report)

The purpose of this CRADA was to develop, integrate, and test design changes to LLNL’s field prototype autonomous pathogen detection system (APDS). The desired result of this project was an improved design of the APDS, along with test data characterizing performance of the new hardware, software, and processes. This improved design was to be closer to the final production design for operation. The third amendment to the Statement of Work (SOW) significantly redefined the scope of the work from general improvements to creating a NGSS built system that included the improvements from before and prepared the system for head to head testing for the BioWatch Gen-3 program. All deliverables were met on time and on budget.

Henderer, Bruce D.↗
DOE OSTI2017

Release Notes for Whisper-1.1

Whisper is a statistical analysis package developed in 2014 to support nuclear criticality safety (NCS) validation [1-3]. It uses the sensitivity profile data for an application as computed by MCNP6 [4-6] along with covariance files [7,8] for the nuclear data to determine a baseline upper-subcritical-limit (USL) for the application. Whisper version 1.0 was first developed and used at LANL in 2014 [3]. During 2015-2016, Whisper was updated to version 1.1 [9] and is to be included with the upcoming release of MCNP6.2. This document describes the Whisper-1.1 package that will be included with the MCNP6.2 release during 2017. Specific details are provided on the computer systems supported, the software quality assurance (SQA) procedures, installation, and testing. This document does not address other important topics, such as the importance of sensitivity-uncertainty (SU) methods to NCS validation, the theory underlying SU methodology, tutorials on the usage of MCNP-Whisper, practical approaches to using SU methodology to support and extend traditional validation, etc. There are over 50 documents included with Whisper-1.1 and available in the MCNP Reference Collection on the MCNP website (mcnp.lanl.gov) that address all of those topics and more. In this document, however, a complete bibliography of relevant MCNP-Whisper references is provided.

97 MATHEMATICS AND COMPUTING↗