Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Performance Modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Improved Mars Helicopter Aerodynamic Rotor Model for Comprehensive Analyses

The Mars Helicopter is part of the NASA Mars 2020 rover mission scheduled to launch in July of 2020. Its goal is to demonstrate the viability and potential of heavier-than-air vehicles in the Martian atmosphere. Ultimately, it aims to bridge the resolution gap between orbiters and the rover as well as allow access to otherwise inaccessible regions. The low density of the Martian atmosphere and the relatively small-scale rotor result in very low Reynolds number flows. The low density and low Reynolds numbers reduce the lifting force and lifting efficiency, respectively. This paper describes the generation of the improved Mars Helicopter aerodynamic rotor model. The goal is to generate a performance model for the Mars Helicopter rotor using a free wake analysis, since this has a low computational cost for design. The improvements in the analysis are two-fold and are expanded on from two prior publications. First, the fidelity of the simulations is increased by performing higher-order two-dimensional time-accurate OVERFLOW simulations allowing for higher accuracy aerodynamic coefficients and a better understanding of the boundary layer behavior as well as its transient features. Second, a version of the model is generated to duplicate the exact testing conditions in the 25-ft. diameter Space Simulator at the Jet Propulsion Laboratory, which allows for better correlation of rotor performance figures. Previous work correlated performance with that test, but did not consider the higher temperatures in the experiment compared to those of the Martian atmosphere. The higher temperatures in the experiment are expected to give conservative performance estimates, as they give rise to an increase in speed of sound and decrease in observed Reynolds numbers.

Analyses↗
NASA NTRS2013

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-Level Winds for Space Launch

On the day of launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds for their launch customers. During launch operations, the payload/launch team sometimes asks the LWOs if they expect the upper-level winds to change during the countdown. The LWOs used numerical weather prediction model point forecasts to provide the information, but did not have the capability to quickly retrieve or adequately display the upper-level observations and compare them directly in the same display to the model point forecasts to help them determine which model performed the best. The LWOs requested the Applied Meteorology Unit (AMU) develop a graphical user interface (GUI) that will plot upper-level wind speed and direction observations from the Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Profiling System (AMPS) rawinsondes with point forecast wind profiles from the National Centers for Environmental Prediction (NCEP) North American Mesoscale (NAM), Rapid Refresh (RAP) and Global Forecast System (GFS) models to assess the performance of these models. The AMU suggested adding observations from the NASA 50 MHz wind profiler and one of the US Air Force 915 MHz wind profilers, both located near the Kennedy Space Center (KSC) Shuttle Landing Facility, to supplement the AMPS observations with more frequent upper-level profiles. Figure 1 shows a map of KSC/CCAFS with the locations of the observation sites and the model point forecasts.

Bauman, William H., III↗
NASA NTRS2011

Model Adaptation for Prognostics in a Particle Filtering Framework

One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

Saha, Bhaskar↗
DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to subhourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

accuracy↗
NASA NTRS2018

Improved Mars Helicopter Aerodynamic Rotor Model for Comprehensive Analyses

The Mars Helicopter is part of the NASA Mars 2020 rover mission scheduled to launch in July of 2020. Its goal is to demonstrate the viability and potential of heavier-than-air vehicles in the Martian atmosphere. Ultimately, it aims to bridge the resolution gap between orbiters and the rover as well as allow access to otherwise inaccessible regions. The low density of the Martian atmosphere and the relatively small-scale rotor result in very low Reynolds number flows. The low density and low Reynolds numbers reduce the lifting force and lifting efficiency, respectively. This paper describes the generation of the improved Mars Helicopter aerodynamic rotor model. The goal is to generate a performance model for the Mars Helicopter rotor using a free wake analysis, since this has a low computational cost for design. The improvements in the analysis are two-fold and are expanded on from two prior publications. First, the fidelity of the simulations is increased by performing higher-order two-dimensional time-accurate OVERFLOW simulations allowing for higher accuracy aerodynamic coefficients and a better understanding of the boundary layer behavior as well as its transient features. Second, a version of the model is generated to duplicate the exact testing conditions in the 25–ft. diameter Space Simulator at the Jet Propulsion Laboratory, which allows for better correlation of rotor performance figures. Previous work correlated performance with that test, but did not consider the higher temperatures in the experiment compared to those of the Martian atmosphere. The higher temperatures in the experiment are expected to give conservative performance estimates, as they give rise to an increase in speed of sound and decrease in observed Reynolds numbers.

Grip, Håvard F.↗
NASA NTRS1991

The joint US/UK 1990 epoch world magnetic model

A detailed summary of the data used, analyses performed, modeling techniques employed, and results obtained in the course of the 1990 Epoch World Magnetic Modeling effort are given. Also, use and limitations of the GEOMAG algorithm are presented. Charts and tables related to the 1990 World Magnetic Model (WMM-90) for the Earth's main field and secular variation in Mercator and polar stereographic projections are presented along with useful tables of several magnetic field components and their secular variation on a 5-degree worldwide grid.

Quinn, John M.↗
DOE OSTI2020

Summary of Analytical Results from Samples Supporting Tank Closure Cesium Removal (TCCR) Batch 3 and Modeling Results for Cs Loading on CST

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal (TCCR) process to remove 137 Cs from tank waste supernate using an ion exchange process. As part of that process, Savannah River National Laboratory (SRNL) receives and analyzes samples in support of the qualification of each batch to be processed. SRNL recently received supernate samples retrieved from Tank 10H as well as in-tank batch contact samples for characterization in support of qualifying Batch 3 for processing through the TCCR unit. Some results from analysis of those samples have been previously reported. This report documents the remaining analyses of the in-tank batch contact samples as well as the results of ZAM (Zheng, Anthony, Miller) isotherm modeling performed for comparison to the measured results. Results of the additional analyses include analysis of the loading of other radionuclides besides 137 Cs on the crystalline silicotitanate (CST) contained within the in-tank batch contact test samples. Results from those analyses revealed the next highest contributor to the activity on the CST was 90 Sr with an average loading of 2.76E+08 dpm/g CST compared to 3.56E+10 dpm/g CST for the 137Cs. Isotopes of plutonium were also detected on the samples. ZAM modeling was performed using the measured composition of the Tank 10H Batch 3 qualification samples. The modeling predicted a maximum Cs loading approximately 2.2x higher than the measured result. This is a slightly lower ratio (expected/measured) compared to what was observed for the prior TCCR in-tank batch contact testing performed for Batches 1A and 2 where the ZAM results were 2.7-2.8x higher than the measured values.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Heliostat sizing methodology for concentrating solar thermal industrial process heat projects

This study presents a method to obtain a heliostat size that minimizes the levelized cost of heat (LCOH) of a heliostat-based concentrating solar thermal system for applications of solar heating for industrial processes at operating temperatures from 565 to 1550°C. The method extends prior work by embedding a routine for system design that obtains near-optimal subsystem sizes, increasing the fidelity of drive cost functions, and adding an optical performance model to supplement the previously developed cost models, which we update to reflect current pricing trends. An illustrative business case is developed for Daggett, California, targeting specified annual thermal energy outputs of 50 to 400 GWh th . Optical performance is modeled using verified estimates from the literature. A surrogate heliostat cost model, derived from commercial heliostat designs and scaled for production volume, installation, and operations and maintenance costs, is used to develop cost functions. Results show that heliostat size strongly affects the LCOH, producing a characteristic U-shaped trend with a robust near-optimal window of 7-20 m 2 ; the heliostat size producing the lowest project cost in our study grows slightly as the project size increases, and is reduced as the operating temperature increases. The findings in this study are consistent with the general trend of smaller heliostats being deployed at existing projects for high-temperature industrial process heat and reflect the significant reduction in power electronics and other per-heliostat costs. The methodology we propose is general and can be tailored to revised cost curves as the technology continues to evolve.

14 SOLAR ENERGY↗
DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Data, scripts, and figures associated with a manuscript studying impact of climate and topography on post-fire vegetation recovery.

This data package is associated with the publication “Impact of Topography and Climate on Post-fire Vegetation Recovery Across Different Burn Severity and Land Cover Types through Machine Learning” submitted to Remote Sensing of Environment (Zahura et al. 2023). In this research, a machine learning algorithm, random forest (RF), was utilized to examine the impact of climate and topography on post-fire vegetation recovery. We used enhanced vegetation index (EVI) to examine varying burn severity and land cover types. The data package includes the input files for RF model training, outputs from model predictions and analysis, and python scripts to run the model, analyze the results to understand model performance and interpretability, and plot manuscript figures. This data package contains three folders (Data, Scripts, and Figures), a file-level metadata (FLMD) csv, and a data dictionary (dd) csv. Please see Postfire_recovery_flmd.csv for a list of all files contained in this data package and descriptions for each. The data dictionary (Postfire_recovery_dd.csv) describes the csv column headers. The “Data” folder provides all the inputs and outputs to train the RF model, evaluate performance, and interpret predictions. The “Scripts” folder contains python scripts and jupyter notebooks for model training and result analysis. The “Figures” folder includes the figures used in the manuscript in “.png” and “.jpg” format.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Earth observing system instrument pointing control modeling for polar orbiting platforms

An approach to instrument pointing control performance assessment for large multi-instrument platforms is described. First, instrument pointing requirements and reference platform control systems for the Eos Polar Platforms are reviewed. Performance modeling tools including NASTRAN models of two large platforms, a modal selection procedure utilizing a balanced realization method, and reduced order platform models with core and instrument pointing control loops added are then described. Time history simulations of instrument pointing and stability performance in response to commanded slewing of adjacent instruments demonstrates the limits of tolerable slew activity. Simplified models of rigid body responses are also developed for comparison. Instrument pointing control methods required in addition to the core platform control system to meet instrument pointing requirements are considered.

Briggs, H. C.↗
NASA NTRS1986

Queueing Network Models for Parallel Processing of Task Systems: an Operational Approach

Computer performance modeling of possibly complex computations running on highly concurrent systems is considered. Earlier works in this area either dealt with a very simple program structure or resulted in methods with exponential complexity. An efficient procedure is developed to compute the performance measures for series-parallel-reducible task systems using queueing network models. The procedure is based on the concept of hierarchical decomposition and a new operational approach. Numerical results for three test cases are presented and compared to those of simulations.

Mak, Victor W. K.↗
DOE OSTI2024

SPIDARman: System-Level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors

In nuclear power plants (NPPs), anomalies arising from sensors or human errors (HEs) can undermine the performance and reliability of plant operations. Anomaly detection models can be employed to detect sensor errors and HEs. Additionally, physics-informed machine learning models can utilize the known physics of the system, as described by mathematical equations, to ensure that sensor values are consistent with physical laws. Hence, we propose SPIDARman: System-level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors, a holistic physics-informed anomaly detection approach based on generative adversarial networks (GANs) to detect anomalies in both automatically collected sensor data and manually collected surveillance data. Here we test our approach on data collected from a flow loop testbed, showcasing its potential to detect anomalies. Results demonstrate that the proposed model performs better than the baseline GAN-based models in detecting sensor and surveillance anomalies, suggesting the potential of physics-informed anomaly detection GAN models in NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1994

Turbulence compressibility corrections

The basic objective of this research was to identify, develop and recommend turbulence models which could be incorporated into CFD codes used in the design of the National AeroSpace Plane vehicles. To accomplish this goal, a combined effort consisting of experimental and theoretical phases was undertaken. The experimental phase consisted of a literature survey to collect and assess a database of well documented experimental flows, with emphasis on high speed or hypersonic flows, which could be used to validate turbulence models. Since it was anticipated that this database would be incomplete and would need supplementing, additional experiments in the NASA Ames 3.5-Foot Hypersonic Wind Tunnel (HWT) were also undertaken. The theoretical phase consisted of identifying promising turbulence models through applications to simple flows, and then investigating more promising models in applications to complex flows. The complex flows were selected from the database developed in the first phase of the study. For these flows it was anticipated that model performance would not be entirely satisfactory, so that model improvements or corrections would be required. The primary goals of the investigation were essentially achieved. A large database of flows was collected and assessed, a number of additional hypersonic experiments were conducted in the Ames HWT, and two turbulence models (kappa-epsilon and kappa-omega models with corrections) were determined which gave superior performance for most of the flows studied and are now recommended for NASP applications.

Coakley, T. J.↗
NASA NTRS2021

Predicting near-saturated hydraulic conductivity in urban soils

Pedotransfer functions (PTFs) provide point predictions of soil hydraulic properties from more readily measured soil characteristics, yet uncertainties and biases in measurement methods, sampling distributions, and boundary conditions can limit accuracy when estimating near-saturated hydraulic conductivity (K(n)). These limitations may be particularly problematic in understudied urban landscapes that often contain altered hydraulic properties. To better treat deficiencies in PTF performance, we addressed three objectives, which were to: 1) develop PTFs to predict urban K(n), 2) assess bulk density and coarse fragments as explanatory variables; and 3) evaluate the predictive capability of these PTFs by comparing their output to measured hydraulic conductivity values from three other studies of urban soil hydraulics. We used artificial neural networks (ANN) and random forest (RF) approaches to predict urban K(n), with the training dataset including 307 tension infiltrometer tests and other measurements drawn from urban soil assessments in 11 U.S. cities. The PTFs utilized a hierarchy of inputs, starting with percentage sand, silt, clay, and then adding percentage coarse fragments and bulk density. The ANN models performed similar to the RF models, and all models exhibited similar or better predictive performance as models results collected from published articles. The inclusion of bulk density or coarse fragments did not improve accuracy over soil texture alone. Possible reasons for this result include low correlation between K(n) and bulk density and the exclusion of large voids during flow measurements with tension infiltrometers. The models have been made available as an open-source software package to encourage adoption by users working in urban systems.

Jinshi Jian↗
DOE OSTI2024

Status Report on Fast Flux Test Facility Mechanistic Fuel Failure Experiment Analysis with BISON for Post Irradiation Examination Support

The renewed interest in metallic U-Zr nuclear fuel alloy has led to a drive for deeper understanding of the mechanisms driving the phenomena observed under irradiation conditions. The Department of Energy Advanced Fuel Campaign has developed infrastructure to support metallic fuel development, including Post Irradiation Examination (PIE) of legacy Fast Flux Test Facility (FFTF) Mechanistic Fuel Failure (MFF) experiments. The PIE performed on legacy FFTF MFF experiments gives insight on metallic fuel performance and can address the lack of knowledge and scarcity of reliable data identified in several studies over recent years. Unfortunately, PIE efforts can cost significant time and resources which can impede the progress of metallic U-Zr fuel development. Metallic U-Zr fuel performance modeling can be used to inform PIE efforts on regions of interest for relevant investigations and can help understand phenomena observed in PIE. This report demonstrates the current progress of FFTF MFF fuel performance simulations using the BISON fuel performance code and discusses the support provided by simulation to PIE efforts. Progress in temperature, profilometry, fission gas release, plenum pressure, and zirconium redistribution simulation results have been demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models: Preprint

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to inter-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of said approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating two different clipping correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons will be performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The models can improve accuracy up to 3% in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

clipping↗
DOE OSTI2022

HERA M&S Exercise Problem Description Report

The Nuclear Energy Agency (NEA) Framework for Irradiation Experiments (FIDES) program includes the High burnup Experiments for Reactivity initiated Accident (HERA) Joint Experimental Program (JEEP). The HERA project is focused on studying Light Water Reactor (LWR) fuel behavior during Reactivity Initiated Accident (RIA) conditions. The HERA experiment plan includes analytical integral experiments using test specimens tailored to investigate specific conditions of relevance as well as prototypic integral experiments focused on irradiated fuel from prototypic origin. Modeling & simulation (M&S) is a key component of any experiment program, and the HERA JEEP is coordinating a M&S exercise. The purpose of this document is to provide problem descriptions to support the HERA M&S exercise based on fuel performance modeling. The HERA M&S exercise is expected to evolve into multiple efforts in outyears. This document may be revised and expanded to incorporate those evolutions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗