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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Thermal Modeling of an Advanced Geared Turbofan for Distributed Engine Control Application

Reliability and life-expectancy of gas turbine engine components is very much correlated to the temperature environment in which they operate. This is no different for control system components, especially those with electronic parts. In recent years, the concept of Distributed Engine Control (DEC) has emerged to address the limitations of the current centralized control implementation. This new approach involves relocating control system components from a relatively benign environment to the harsher thermal environment of the engine casing and its surrounding structures and cavities. In this paper, an approach to modeling the gas turbine thermal environment is described. The modeling approach is applied to a 3rd generation geared turbofan design with a focus on the engine locations where control instrumentation and actuation could be installed. The analysis was conducted with an eye toward component reliability and service life as it relates to the thermal environment. The results were found to be reasonable. Furthermore, the model is shown to execute in real-time within a multi-model simulation environment that demonstrates the capability to interact with hardware to drive test equipment.

Kratz, Jonathan↗
DOE OSTI2018

FY2017 Analysis Annual Progress Report

During fiscal year 2017, the U.S. Department of Energy Vehicle Technologies Office (VTO) funded analysis projects supportive of VTO’s goals to pursue early stage research in vehicle and mobility system technologies to reduce petroleum dependence, increase energy reliability and security, improve transportation affordability, and promote economic growth. VTO analysis projects result in a foundation of data, analytical models, and applied analyses that provide insights into critical transportation energy problems and assist in research investment prioritization and portfolio planning.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

FY2018 Analysis Annual Progress Report

During fiscal year 2018 (FY 2018), the U.S. Department of Energy Vehicle Technologies Office (VTO) funded analysis projects supportive of VTO’s goals to pursue early stage research in vehicle and mobility system technologies to improve energy efficiency, increase energy reliability and security, improve transportation affordability, and promote economic growth. VTO analysis projects result in a foundation of data, analytical models, and applied analyses that provide insights into critical transportation energy problems and assist in research investment prioritization and portfolio planning.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Analysis Program Annual Progress Report (FY2020)

During fiscal year 2020 (FY 2020), the U.S. Department of Energy Vehicle Technologies Office (VTO) funded analysis projects supportive of VTO’s goals to pursue early stage research in vehicle and mobility system technologies to reduce petroleum dependence, increase energy reliability and security, improve transportation affordability, and promote economic growth. VTO analysis projects result in a foundation of data, analytical models, and applied analyses that provide insights into critical transportation energy problems and assist in research investment prioritization and portfolio planning. This document presents a brief overview of VTO analysis efforts and progress for projects funded in FY 2020. Each of the progress reports includes project objectives, approach, and highlights of the technical results that were accomplished during the fiscal year.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1992

Quantifying parameters for Bayesian prior assumptions when estimating the probability of failure of software

Software reliability has become increasingly important, especially in life-critical situations. The ability to measure the results of testing and to quantify software reliability is needed. If this is accomplished, a certain minimum amount of reliability for a piece of software can be specified, and testing and/or other analysis may be done until that minimum number has been attained. There are many models for estimating software reliability. The accuracy of these models has been challenged and many revisions for the models and recalibration techniques have been devised. Of particular interest is the method of estimating the probability of failure of software when no failures have yet occurred in its current version as described by Miller. This model uses black box testing with formulae based on Bayesian estimation. The focus is on three interrelated issues: estimating the probability of failure when testing has revealed no errors; modifying this estimation when the input use distribution does not match the test distribution; and combining the results from random testing with other relevant information to obtain a possibly more accurate estimate of the probability of failure. Obtaining relevant information about the software and combining the results for a better estimate for the Miller model are discussed.

Long, Jacquelyn E.↗
NASA NTRS2006

Closed-Loop Evaluation of an Integrated Failure Identification and Fault Tolerant Control System for a Transport Aircraft

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems developed for failure detection, identification, and reconfiguration, as well as upset recovery, need to be evaluated over broad regions of the flight envelope or under extreme flight conditions, and should include various sources of uncertainty. To apply formal robustness analysis, formulation of linear fractional transformation (LFT) models of complex parameter-dependent systems is required, which represent system uncertainty due to parameter uncertainty and actuator faults. This paper describes a detailed LFT model formulation procedure from the nonlinear model of a transport aircraft by using a preliminary LFT modeling software tool developed at the NASA Langley Research Center, which utilizes a matrix-based computational approach. The closed-loop system is evaluated over the entire flight envelope based on the generated LFT model which can cover nonlinear dynamics. The robustness analysis results of the closed-loop fault tolerant control system of a transport aircraft are presented. A reliable flight envelope (safe flight regime) is also calculated from the robust performance analysis results, over which the closed-loop system can achieve the desired performance of command tracking and failure detection.

Shin, Jong-Yeob↗
DOE OSTI2022

High-throughput platform for yeast morphological profiling predicts the targets of bioactive compounds

Abstract Morphological profiling is an omics-based approach for predicting intracellular targets of chemical compounds in which the dose-dependent morphological changes induced by the compound are systematically compared to the morphological changes in gene-deleted cells. In this study, we developed a reliable high-throughput (HT) platform for yeast morphological profiling using drug-hypersensitive strains to minimize compound use, HT microscopy to speed up data generation and analysis, and a generalized linear model to predict targets with high reliability. We first conducted a proof-of-concept study using six compounds with known targets: bortezomib, hydroxyurea, methyl methanesulfonate, benomyl, tunicamycin, and echinocandin B. Then we applied our platform to predict the mechanism of action of a novel diferulate-derived compound, poacidiene. Morphological profiling of poacidiene implied that it affects the DNA damage response, which genetic analysis confirmed. Furthermore, we found that poacidiene inhibits the growth of phytopathogenic fungi, implying applications as an effective antifungal agent. Thus, our platform is a new whole-cell target prediction tool for drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

OC6 Phase IV: Validation of CFD Models for Stiesdal TetraSpar Floating Offshore Wind Platform

ABSTRACT With only a few floating offshore wind turbine (FOWT) farms deployed anywhere in the world, FOWT technology is still in its infancy, building on a modicum of real‐world experience to advance the nascent industry. To support further development, engineers rely heavily on modeling tools to accurately portray the behavior of these complex systems under realistic environmental conditions. This reliance creates a need for verification and validation of such tools to improve reliability of load and dynamic response prediction and analysis capabilities of FOWT systems. The Offshore Code Comparison Collaboration, Continued with Correlation and unCertainty (OC6) project was created under the framework of the International Energy Agency to address this need and considers a three‐sided verification and validation between engineering level models, computational fluid dynamics (CFD), and experimental results. In this paper, a novel floating offshore wind platform, the Stiesdal TetraSpar, is simulated using CFD under the load conditions defined by Phase IV of the OC6 project. The comparison of these CFD results against the experimental results demonstrated the ability to predict the platform response to waves when imposing the measured wave signals as input. Although validation versus experiment was largely successful, the damping behavior was impacted by uncertainties likely originating from the mooring system and sensor umbilical cable. This extensive comparison effort with multiple CFD practitioners offers insight into best practices to achieve reliable results.

17 WIND ENERGY↗
NASA NTRS1982

Kerr Reservoir LANDSAT experiment analysis for November 1980

An experiment was conducted on the waters of Kerr Reservoir to determine if reliable algorithms could be developed that relate water quality parameters to remotely sensed data. LANDSAT radiance data was used in the analysis since it is readily available and covers the area of interest on a regular basis. By properly designing the experiment, many of the unwanted variations due to atmosphere, solar, and hydraulic changes were minimized. The algorithms developed were constrained to satisfy rigorous statistical criteria before they could be considered dependable in predicting water quality parameters. A complete mix of different types of algorithms using the LANDSAT bands was generated to provide a thorough understanding of the relationships among the data involved. The study demonstrated that for the ranges measured, the algorithms that satisfactorily represented the data are mostly linear and only require a maximum of one or two LANDSAT bands. Rationing techniques did not improve the results since the initial design of the experiment minimized the errors that this procedure is effective against. Good correlations were established for inorganic suspended solids, iron, turbidity, and secchi depth.

Lecroy, S. R.↗
DOE OSTI2019

Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation

Verification and validation (V&V) of computer codes and models used in simulations are two aspects of the scientific practice of high importance that recently have been discussed widely by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to the model’s relation to the real world and its intended use. Because complex simulations are generally opaque to a practitioner, the Duhem problem can arise with verification and validation due to their entanglement; such an entanglement makes it impossible to distinguish whether a coding error or the model’s general inadequacy to its target should be blamed in the case of a failure. I argue that a clear distinction between computer modeling and simulation has to be made to disentangle verification and validation. Drawing on that distinction, I suggest to associate modeling with verification and simulation, which shares common epistemic strategies with experimentation, with validation. To explain the reasons for their entanglement in practice, I propose a Weberian ideal–typical model of modeling and simulation as roles in practice. I examine an approach to mitigate the Duhem problem for verification and validation that is generally applicable in practice and is based on differences in epistemic strategies and scopes. Based on this analysis, I suggest two strategies to increase the reliability of simulation results, namely, avoiding alterations of verified models at the validation stage as well as performing simulations of the same target system using two or more different models. In response to Winsberg’s claim that verification and validation are entangled I argue that deploying the methodology proposed in this work it is possible to mitigate inseparability of V&V in many if not all domains where modeling and simulation are used.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

Data Assessment↗
NASA NTRSDate not supplied

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

Data Assessment↗
DOE OSTI2023

Thermodynamic parametric analysis of refueling heavy-duty hydrogen fuel-cell electric vehicles

Reliable design and safe operation of heavy-duty hydrogen refueling stations are essential for the successful deployment of heavy-duty fuel cell electric vehicles (FCEVs). Fueling heavy-duty FCEVs is different from light-duty vehicles in terms of the dispensed hydrogen quantities and fueling rates, requiring tailored fueling station design for each vehicle class. In particular, the selection and design of the onboard hydrogen storage tank system and the fueling performance requirements influence the safe design of hydrogen fueling stations. A thermodynamic modeling and analysis are performed to evaluate the impact of various fueling parameters and boundary conditions on the fueling performance of heavy-duty FCEVs. Here, we studied the effect of dispenser pressure ramp rate and precooling temperature, initial tank temperature and pressure, ambient temperature, and onboard storage design parameters, such as onboard storage pipe diameter and length, on the fueling rate and final vehicle state-of-charge, while observing prescribed tank pressure and temperature safety limits. An important finding was the sensitivity of the temporal fueling rate profile and the final tank state of charge to the design factors impacting pressure drop between the dispenser and vehicle tank, including onboard storage pipe diameter selection, and flow coefficients of nozzle, valves, and fittings. The fueling rate profile impacts the design and cost of the hydrogen precooling unit upstream of the dispenser.

08 HYDROGEN↗
NASA NTRS1975

Experience gained from computer processing of physical experimental data during the restoration of measured values

The processing stage in which the restored values of the physical parameters are received is described. The following main steps are discussed: estimation of the state of the telemetry data, processing of the calibration data, and determination of the errors in the data; data decommutation and analysis of the structure of measurement cycles for each instrument; decoding, estimates of the reliability of the restored data, and their agreement with the models adopted for the measurement process; and analysis of errors due to deterministic and random factors. A block diagram of the method is presented.

Mamotko, Z. N.↗
DOE OSTI2026

Sedimentation and Nonlinear Trapping in Texas Reservoirs Identified Using Remote Sensing and Bathymetric Survey Records

Decreasing reservoir storage capacity due to sedimentation poses great challenges to aging U.S. reservoirs, as it reduces the efficacy and reliability of their socio‐economic services. However, systematic assessments of reservoir sedimentation rates and associated issues remain limited because of sparse and infrequent bathymetry survey data. In this study, we use remote sensing‐driven estimates of sediment concentrations to identify regions experiencing rapid reservoir capacity loss, as observed in repeated bathymetry surveys. Our analysis focuses on Texas, where one of the most reliable state‐level reservoir capacity loss data sets is available through a unique long‐term monitoring program by the Texas Water Development Board. We find that reservoirs with large storage capacities and high sedimentation rate are concentrated in Northeast Texas. We also show that reduced forest, increased barren land, and erosive soil properties are co‐varying with high reservoir sedimentation rates. Temporal changes in the longitudinal gradient of the remotely sensed sediment flux highlight the nonlinear nature of sediment trapping processes, and can be used to estimate the reservoir storage capacity loss over time. In combination with standard bathymetry surveys, our approach shows potential for more cost‐effective and frequent assessment of reservoir storage loss.

Lee, Jiyong [ORNL] (ORCID:0000000198957406)↗
DOE OSTI2019

Used Fuel Storage Monitoring Using Helium-4 Scintillation Fast Neutron Detectors and Neutron Spectral Analysis

This project aimed to address the technology gap in the reliable methods to verify contents of sealed dry storage casks for spent nuclear fuel. Helium-4 gas scintillation neutron detectors was proposed to be developed into a neutron spectroscopy and imaging system for nuclear security and safeguards applications. 4 He gas is significantly more available than 3 He gas and it has unique advantages such as low gamma interaction probability and direct detection of fast neutrons. Due to the sheer amount of fissile materials in a single dry cask, there is a significant neutron fluence emitted whose energies range from thermal to uncollided high-energy neutrons suitable for the detection capability of the 4 He detectors. Our project demonstrated the first ever neutron spectroscopic capabilities using 4 He detectors, explored novel detector design and performed detector characterization. It further qualified the detectors for use in various applications including high-flux environments with significant gamma-fluence. Computer simulations were used to test various large cask measurement system designs and tests, beyond the compact prototype system and laboratory measurements exploring the feasibility of the neutron spectroscopic approach. Although some cask-characterization methods proved unfeasible, alternative characterization methods using the He-4 detectors were explored and generated promising results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1983

Analysis of the impact of error detection on computer performance

Conventionally, reliability analyses either assume that a fault/error is detected immediately following its occurrence, or neglect damages caused by latent errors. Though unrealistic, this assumption was imposed in order to avoid the difficulty of determining the respective probabilities that a fault induces an error and the error is then detected in a random amount of time after its occurrence. As a remedy for this problem a model is proposed to analyze the impact of error detection on computer performance under moderate assumptions. Error latency, the time interval between occurrence and the moment of detection, is used to measure the effectiveness of a detection mechanism. This model is used to: (1) predict the probability of producing an unreliable result, and (2) estimate the loss of computation due to fault and/or error.

Shin, K. C.↗