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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

AGR-2 Compact 6-4-1 Post-Irradiation Examination Results

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program was established to perform research and development on tristructural isotropic (TRISO)-coated particle fuel to support deployment of a high-temperature gas-cooled reactor (HTGR). The work continues as part of the Advanced Reactor Technologies (ART) TRISO Fuel Program. The overarching goal of the program is to provide a baseline fuel qualification data set to support licensing and operation of an HTGR. To achieve these goals, the program includes the elements of fuel fabrication, irradiation, post-irradiation examination (PIE) and safety/heating testing, fuel performance modeling, and fission product transport (INL 2017). Several fuel irradiation experiments have been performed at the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL), and additional irradiations are planned. These experiments are intended to provide data on fuel performance under irradiation, support fuel fabrication process development, qualify fuel for operating and accident conditions, provide irradiated fuel for accident testing, and support development of fuel performance and fission product transport models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Characterizing the performance of node-aware strategies for irregular point-to-point communication on heterogeneous architectures

Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computational efficiency, while also increasing the amount of data to be communicated and the number of potential data flow paths. In this work, we characterize the performance of irregular point-to-point communication with MPI on heterogeneous compute environments through performance modeling, demonstrating the limitations of standard communication strategies for both device-aware and staging-through-host communication techniques. Presented models suggest staging communicated data through host processes then using node-aware communication strategies for high inter-node message counts. Notably, the models also predict that node-aware communication utilizing all available CPU cores to communicate inter-node data leads to the most performant strategy when communicating with a high number of nodes. Furthermore, model validation is provided via a case study of irregular point-to-point communication patterns in distributed sparse matrix–vector products. Importantly, we include a discussion on the implications model predictions have on communication strategy design for emerging supercomputer architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Development and testing of coarse-grained models for ultrasonic simulations of cast austenitic stainless steel

Ultrasonic inspection of cast austenitic stainless steel (CASS) in the nuclear industry is particularly challenging because of sound field scatter and attenuation caused by the coarse-grained microstructure. Modeling and simulation are important tools in ultrasonic testing, as they can be used to help address key aspects of inspections, such as developing new probe designs, predicting inspection reliability, and testing phased-array focal laws. However, developing a useful and reliable CASS model is challenging due to the many grain interfaces and crystalline orientations that must be captured. We demonstrate a method of creating a realistic CASS model that is usable in CIVA, a commercially available modeling and simulation software platform. Using polished and chemically etched sections, we generate models of a coarse-grained equiaxed specimen and a columnar specimen. We also test an alternative method of generating a coarse-grained model using Voronoi regions. We qualitatively compare sound field scatter and quantitatively compare sound field attenuation and beam partitioning in simulated sound fields to those of laboratory-measured sound fields. Results show that the Voronoi models perform as well as or better than the models based on actual grain morphology. Here we also show that model-to-model randomness in Voronoi grain structure can impact the magnitude of a simulated echo response by a factor of two or more. Although CASS models are potentially a good depiction of reality for a given scenario, they should not be considered representative since CASS morphology can change significantly from specimen to specimen or within the same specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Learning Estimation of Daily Ground–Level NO 2 Concentrations from Remote Sensing Data

The limited number of nitrogen dioxide (NO 2 ) surface measurements calls for the development of highly accurate approaches to estimating surface NO 2 concentrations. In this study, we leverage a new satellite instrument, the TROPOspheric Monitoring Instrument (TROPOMI), along with other predictor variables, to estimate daily surface NO 2 concentrations over Texas in 2019. We use the deep convolutional neural network (Deep-CNN), an advanced deep learning algorithm, to obtain estimates and achieve a correlation coefficient (R) of 0.91, an index of agreement (IOA) of 0.95, and a mean absolute bias (MAB) of 1.75 ppb in surface NO 2 estimation. Additionally, we leverage a novel approach, SHapley Additive exPlanations (SHAP), to describe how Deep-CNN understands each predictor variable. The SHAP results show that the Deep-CNN model has an advanced understanding of the dataset, revealing that TROPOMI closely captures levels of NO 2 . In addition, we show the superiority of our Deep-CNN model at estimating surface NO 2 over other well-known machine learning and regression models in the field, including the support vector machines (SVM), random forest (RF), and multiple linear regression (MLR). Although SVM and RF show strong capabilities at estimating surface NO 2 concentrations, their accuracy is inferior to that of the Deep-CNN model, ranking second and third in model accuracy in this study. The MLR, however, shows a poor ability at NO 2 estimation and ranks last among all models. Furthermore, testing the impact of sample size on model performance, we also show that, compared to other models, Deep-CNN needs more samples to trigger its strength at surface NO 2 estimation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Use of Event-Time Embeddings via RNN to Discern Novel Event Sequences in EHRs

In highly configurable health information technology (HIT) systems, such as VistA of the Veterans Health Administration, the variations in how the system is used among different healthcare facilities and how the data are recorded can be significant. Despite the successful standardization of care efforts, some of these variations can be indicative of HIT hazards and demand further investigation. In this work, we implemented a recurrent neural network (RNN) architecture to learn clinical provider order sequences and their temporal dynamics while predicting the orders' terminal state. We demonstrate model performance and provide a use case for the model discerning novel event sequences. This model is proposed to find novel event sequences in an operational environment.

Ozmen, Ozgur↗
NASA NTRS1973

Monopropellant hydrazine resistojet: Data correlation

The design, development, and testing of an engineering model nominal 20-millipound thrust monopropellant hydrazine resistojet program is divided into six basic tasks. Included in these tasks are analyses, design, test, and data correlation of the electrothermal hydrazine thruster (EHT). A brief summary is provided of the analyses conducted for the EHT and the design of the engineering model thruster. Some of the results of the engineering model tests are then compared with the analytical performance models generated early in the program.

Murch, C. K.↗
NASA NTRS1979

Low cost point focus solar concentrator, phase 1

Design concepts and plans for mass-production facilities and equipment, field installation, and maintenance were developed and used for cost analysis of a pneumatically stabilized plastic film point focus solar concentrator which has potential application in conjunction with Brayton cycle engines or supply of thermal energy. A sub-scale reflector was fabricated and optically tested by laser ray tracing to determine focal deviations of the surface slope and best focal plane. These test data were then used for comparisons with theoretical concentrator performance modeling and predictions of full-scale design performance. Results of the economic study indicate the concentrator design will have low cost when mass-produced and has cost/performance parameters that fall within current Jet Propulsion Laboratory goals.

Source record↗
NASA NTRS1993

A numerical study of confined turbulent jets

A numerical investigation is reported of turbulent incompressible jets confined in two ducts, one cylindrical and the other conical with a 5 degree divergence. In each case, three Craya-Curtet numbers are considered which correspond, respectively, to flow situations with no moderate and strong recirculation. Turbulence closure is achieved by using the k-epsilon model and a recently proposed realizable Reynolds stress algebraic equation model that relates the Reynolds stresses explicitly to the quadratic terms of the mean velocity gradients and ensures the positiveness of each component of the turbulent kinetic energy. Calculations are carried out with a finite-volume procedure using boundary-fitted curvilinear coordinates. A second-order accurate, bounded convection scheme and sufficiently fine grids are used to prevent the solutions from being contaminated by numerical diffusion. The calculated results are compared extensively with the available experimental data. It is shown that the numerical methods presented are capable of capturing the essential flow features observed in the experiments and that the realizable Reynolds stress algebraic equation model performs much better than the k-epsilon model for this class of flows of great practical importance.

Zhu, J.↗
NASA NTRS1993

Evaluation of Baldwin-Barth turbulence model with thin-layer Navier-Stokes computation of an axisymmetric afterbody-exhaust jet flowfield

Axisymmetric steady flowfield over a steep circular arc afterbody with a choked exhaust jet in a subsonic freestream is numerically investigated using overflow code, developed by NASA Ames. The accuracy of Baldwin-Barth one-equation turbulence model for the computation of separated flow and plume shear layers is assessed by a comparison of predictions with available measurements from NASA Langley. The results show that the Baldwin-Barth turbulence model performs better than the Baldwin-Lomax algebraic model in predicting the surface pressure distribution in the separated flow region of the afterbody. In the jet mixing layer, the Baldwin-Barth model considerably unpredicts the growth of the shear layer, as does the Baldwin-Lomax model. It is shown that the one-equation turbulence model needs improvement for the prediction of separated flow due to smooth adverse pressure gradient, and mixing layer growth.

Kandula, M.↗
NASA NTRS1993

Foil bearing research at Penn State

Foil journal bearings consist of a compliant metal shell or foil which supports a rigid journal by means of a fluid film. Foil bearings are considered to be a potential alternative to rolling element or traditional rigid surface bearings in cryogenic turbomachinery applications. The prediction of foil bearing performance requires the coupled solution of the foil deflection and the fluid flow in the bearing clearance between the rotor and the foil. The investigations being conducted in the Department of Mechanical Engineering at Penn State are focused in three areas: theoretical prediction of steady state bearing performance, modeling of the dynamic bearing characteristics to determine performance in rotor systems, and experimental verification of analysis codes. The current status and results from these efforts will be discussed.

Carpino, Marc↗
NASA NTRS2000

Geopotential Model Improvement Using POCM_4B Dynamic Ocean Topography Information: PGM2000A

The two-year mean (1993-1994) Dynamic Ocean Topography (DOT) field implied by the POCM_4B circulation model was used to develop normal equations for DOT, in a surface spherical harmonic representation. These normal equations were combined with normal equations from satellite tracking data, surface gravity data, and altimeter data from TOPEX/Poseidon and ERS-1. Several least-squares combination solutions were developed in this fashion, by varying parameters such as the maximum degree of the estimated DOT and the relative weights of the different data. The solutions were evaluated in terms of orbit fit residuals, GPS/Leveling-derived undulations, and independent DOT information from in situ WOCE hydrographic data. An optimal solution was developed in this fashion which was originally presented at the 1998 EGS meeting in Nice, France. This model, designated here PGM2000A, maintains the orbit and land geoid modeling performance of EGM96, while improving its marine geoid modeling capability. In addition, PGM2000A's error spectrum is considerably more realistic than those of other contemporary gravitational models and agrees well with the error spectrum of EGM96. We will present the development and evaluation of PGM2000A, with particular emphasis on the weighting of the DOT information implied by POCM_4B. We will also present an inter-comparison of PGM2000A with the GRIM5-C1 and TEG-4 models. Directions for future work and problematic areas will be identified.

Pavlis, N. K.↗
NASA NTRS2013

GPS Estimates of Integrated Precipitable Water Aid Weather Forecasters

Global Positioning System (GPS) meteorology provides enhanced density, low-latency (30-min resolution), integrated precipitable water (IPW) estimates to NOAA NWS (National Oceanic and Atmospheric Adminis tration Nat ional Weather Service) Weather Forecast Offices (WFOs) to provide improved model and satellite data verification capability and more accurate forecasts of extreme weather such as flooding. An early activity of this project was to increase the number of stations contributing to the NOAA Earth System Research Laboratory (ESRL) GPS meteorology observing network in Southern California by about 27 stations. Following this, the Los Angeles/Oxnard and San Diego WFOs began using the enhanced GPS-based IPW measurements provided by ESRL in the 2012 and 2013 monsoon seasons. Forecasters found GPS IPW to be an effective tool in evaluating model performance, and in monitoring monsoon development between weather model runs for improved flood forecasting. GPS stations are multi-purpose, and routine processing for position solutions also yields estimates of tropospheric zenith delays, which can be converted into mm-accuracy PWV (precipitable water vapor) using in situ pressure and temperature measurements, the basis for GPS meteorology. NOAA ESRL has implemented this concept with a nationwide distribution of more than 300 "GPSMet" stations providing IPW estimates at sub-hourly resolution currently used in operational weather models in the U.S.

Moore, Angelyn W.↗
NASA NTRS2019

Using Machine Learning to Develop a Predictive Model for Future Fire Seasons

The deep learning model shows promise for predicting areas of high wildfire potential. Full evaluation of the model performance is ongoing. Currently, the developed deep learning model is better overall at predicting the number of fires over the acres burned. Acres burned is dependent on location, suppression plan, and current conditions. Antecedent conditions are only one piece of the equation. In-season changes are not accounted for. An ignition source is required, which further complicates the model training and prediction.

White, Andrew T.↗
NASA NTRS2023

Front Range Wildland Fires: Evaluating the Efficacy of Remote Sensing Imagery in Monitoring Forest Fuels Treatment Methods

Over the last several decades, wildfire frequency and severity in forested areas along Colorado’s Front Range have increased due to a buildup of fuels. This has led to an increase in forest treatments, as well as an increased need to evaluate the success of these treatments. Remote sensing products offer an efficient and cost-effective way to monitor forest treatments; however, not all remote sensing products and analysis techniques have been explored by Coloradan land managers. Specifically, project partners at the Colorado State Forest Service (CSFS) and the Colorado Forest Restoration Institute (CFRI) were interested in using an effective and streamlined method of mapping canopy cover to better monitor forest treatment success. To support their needs, the NASA DEVELOP Front Range Wildland Fires team explored National Agricultural Imagery Program (NAIP) imagery at different spatial resolutions and numbers of training points with NASA’s Shuttle Radar Topography Mission (SRTM) Data Elevation Model (DEM) as a predictor in addition to NAIP imagery spectral predictors. From this analysis, we created classified canopy cover rasters, and compared accuracy metrics across model iterations. We also determined that the best performing model, with an overall accuracy of 0.900 uses 2021 NAIP imagery at 2-meter resolution, 800 training points, 200 testing points, does not use topographic predictors, and reclassifies shadow pixels via a pre-selected NDVI threshold.

Remote Sensing↗
NASA NTRS2005

New Integrated Modeling Capabilities: MIDAS' Recent Behavioral Enhancements

The Man-machine Integration Design and Analysis System (MIDAS) is an integrated human performance modeling software tool that is based on mechanisms that underlie and cause human behavior. A PC-Windows version of MIDAS has been created that integrates the anthropometric character "Jack (TM)" with MIDAS' validated perceptual and attention mechanisms. MIDAS now models multiple simulated humans engaging in goal-related behaviors. New capabilities include the ability to predict situations in which errors and/or performance decrements are likely due to a variety of factors including concurrent workload and performance influencing factors (PIFs). This paper describes a new model that predicts the effects of microgravity on a mission specialist's performance, and its first application to simulating the task of conducting a Life Sciences experiment in space according to a sequential or parallel schedule of performance.

Gore, Brian F.↗
NASA NTRS1991

A distributed fault-detection and diagnosis system using on-line parameter estimation

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

Guo, T.-H.↗
NASA NTRSDate not supplied

Parametric Modeling and Mission Performance Analysis of a True Parallel Hybrid Turboprop Aircraft for Freighter Operations

Hybrid-electric propulsion systems for short-haul, cargo carrying aircraft have emerged as promising solutions for an environmentally sustainable future for commercial aviation. The novel propulsion architecture presents significant complexity and requires the development of new methodologies to account for the unique coupling and integration between critical design variables. This paper presents a comprehensive study on the modeling, performance assessment, and design space exploration of a C-130H freighter aircraft retrofitted with a parallel hybrid electric powertrain. Details on the development of parametric models for both the baseline and true parallel hybrid (TPH) aircraft and the integrated electrified aircraft propulsion (EAP) system sizing approach are presented along with detailed performance analyses of payload/range capabilities for short-haul cargo missions. For 2030, 2040, and 2050 EAP technology levels, the TPH C-130H configuration with a ~2.12 MW class EAP system has a range capability of 485-1,028 nautical miles and block fuel savings of 27-44%.

efficiency↗
NASA NTRSDate not supplied

AIRNOISEUAM: An Urban Air Mobility Noise-Exposure Prediction Tool

A new software tool called AIRNOISEUAM is introduced that models the noise exposure of Urban Air Mobility (UAM) operations. Given relevant UAM aircraft performance models, mission profiles, and Noise-Power-Distance data, AIRNOISEUAM predicts the noise exposure footprint for receptors on the ground. The performance of AIRNOISEUAM using a Robinson R66 helicopter model and a six-passenger quadrotor model, and a diverse set of scenarios from NASA’s UAM human-in-the-loop simulations is compared to that of the industry-standard tool with the same inputs. The predicted noise exposure results from both tools are found to be nearly identical. AIRNOISEUAM offers a fast-time, flexible interface and modular design to facilitate the dynamic requirements of the aviation research community.

Urban air mobility↗