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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Post-test Inspection of NASA’s Evolutionary Xenon Thruster Long-Duration Test Hardware: Discharge Chamber

The NEXT Long-Duration Test is part of a comprehensive thruster service life assessment intended to demonstrate overall throughput capability, validate service life models, quantify wear rates as a function of time and operating condition, and identify any unknown life-limiting mechanisms. The test was voluntarily terminated in February 2014after demonstrating 51,184 hours of high-voltage operation, 918 kg of propellant throughput, and 35.5 MN-s of total impulse. The post-test inspection of the thruster hardware began shortly afterwards with a combination of non-destructive and destructive analysis techniques, and is presently nearing completion. This paper presents relevant results of the post-test inspection for the discharge chamber as well as other miscellaneous components such as the high-voltage propellant isolators and electrical cabling. Comparison of magnetic field measurements taken during pretest and post-test inspections indicate that the field strength did not degrade, consistent with performance data obtained during the test. Inspection of discharge chamber mesh samples show a deposition coating primarily composed of grid material that is approximately 15 μm in thickness. This thickness is well within the retention capability of the mesh and is therefore not expected to present any issues. Approximately 3.1 grams of deposition flakes were found at the bottom of the discharge chamber, composed primarily of grid material and carbon. Calculated size histograms of these flakes indicate that 99% have a maximum dimension of 200 μm or smaller, which is significantly less than the ion optics grid gap. Larger flakes that are capable of causing a grid-to-grid short will be analyzed to determine if their formation will occur in flight or is a facility effect. The high-voltage propellant isolators as well as numerous other electrical insulators were inspected and no evidence of arcing or any other issues were found.

Rohit Shastry↗
NASA NTRSDate not supplied

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗
NASA NTRSDate not supplied

Hybrid Approaches to Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Systems Health Management↗
NASA NTRSDate not supplied

Physics Informed Neural Nets for Systems Health Management

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Development in data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. The research work presents application of physics-informed neural nets application to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage.

Physics Informed↗
DOE OSTI2020

Residential Battery Modeling for Control-Oriented Techno-Economic Studies: Preprint

Electrochemical batteries, which serve as electric energy storage devices, are becoming increasingly popular among residential buildings that incorporate solar photovoltaic (PV) systems to help meet their energy needs. Battery economics are affected by performance degradation over time, and managing this degradation can help extend the battery's lifespan. The tradeoff between operational costs/benefits and managing battery degradation is of significant research interest. One of the key factors for assessing battery degradation is the dispatch strategy used to control the charging and discharging of the battery. Conventional dispatch strategies typically use simple rule-based methods, and these overly aggressive charging/discharging cycles can significantly reduce a battery’s life span. Our research seeks to develop optimized dispatch strategies for grid-connected PV homes with a goal of extending battery life while simultaneously taking into consideration utility costs and occupant comfort. To achieve this goal, we adapted lithium-ion battery life- and cyclic-degradation models for use in high-fidelity building simulations, so whole-building and grid-interactive controllers can dispatch the batteries along with other flexible loads. With the help of a co-simulation platform, we performed a simulation study to compute the optimized dispatch strategies for relevant operating conditions brought about by changing geographical locations, weather conditions, and utility pricing. Comparing the optimized strategies with the conventional strategies resulted in a >50% decrease in capacity degradation and >10% average reduction in operational costs during the months of January and July in Fort Collins, Colorado; Phoenix, Arizona; and Portland, Oregon.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Measuring Critical Fuel Properties for Simulations to Accelerate Fuel Qualification

NREL's sustainable aviation fuel (SAF) research in the area of fuel properties and end use is focused on accelerating SAF development and deployment. This will be achieved by close collaboration with BETO program researchers on fuel property measurement and development of structure-property relationships. Additionally, fuel properties measured at often extreme engine operating conditions will be measured, and will be used as inputs to exascale ready simulations of aviation combustion turbines to reveal impacts of properties on turbine operation. This research will potentially lead to a widening of the allowable fuel property range for SAF, expanding SAF production process options and production volumes.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1997

Comparison Tools for Assessing the Microgravity Environment of Missions, Carriers and Conditions

The Principal Component Spectral Analysis and the Quasi-steady Three-dimensional Histogram techniques provide the means to describe the microgravity acceleration environment of an entire mission on a single plot. This allows a straight forward comparison of the microgravity environment between missions, carriers, and conditions. As shown in this report, the PCSA and QTH techniques bring both the range and median of the microgravity environment onto a single page for an entire mission or another time period or condition of interest. These single pages may then be used to compare similar analyses of other missions, time periods or conditions. The PCSA plot is based on the frequency distribution of the vibrational energy and is normally used for an acceleration data set containing frequencies above the lowest natural frequencies of the vehicle. The QTH plot is based on the direction and magnitude of the acceleration and is normally used for acceleration data sets with frequency content less than 0.1 Hz. Various operating conditions are made evident by using PCSA and QTH plots. Equipment operating either full or part time with sufficient magnitude to be considered a disturbance is very evident as well as equipment contributing to the background acceleration environment. A source's magnitude and/or frequency variability is also evident by the source's appearance on a PCSA plot. The PCSA and QTH techniques are valuable tools for extracting useful information from acceleration data taken over large spans of time. This report shows that these techniques provide a tool for comparison between different sets of microgravity acceleration data, for example different missions, different activities within a mission, and/or different attitudes within a mission. These techniques, as well as others, may be employed in order to derive useful information from acceleration data.

DeLombard, Richard↗
DOE OSTI2023

Evaluation of supply air temperature control performance with different control strategies at air handling units

Due to its nonlinear feature, supply air temperature control systems at air handling units using single-loop fixed gain control frequently suffer unstable response under dynamic conditions. This paper is aimed at identifying a more effective control strategy to stabilize the valve control and achieve desirable supply air temperature response under various operation conditions by evaluating three control strategies, cascade, gain scheduling and cascade plus gain scheduling controls. Firstly, a control-oriented model is developed and calibrated through open-loop tests. Then, the control issues with single-loop fixed gain control are evaluated through simulations and field tests, which indicates that the system has more aggressive response or becomes unstable under lower load conditions when the chilled-water flow rate is less than 0.1 L/s. Finally, three control strategies are proposed and evaluated. Further, the results reveal that all three proposed controls can achieve better robustness with the integral square error of supply air temperature decreased to 16%, 47% and 5%, respectively, under lower load condition. However, since high-frequency oscillation of the control valve occurs with cascade and cascade plus gain scheduling control, the gain scheduling control is recommended considering a trade-off among the supply air temperature response, valve lifetime and implementation complexity.

42 ENGINEERING↗
NASA NTRS1982

A detailed treatment of two-dimensional, starved lubrication in the vicinity of two counter-rotating cylinders

The problem of starved lubrication in the inlet region for the case of line contact between two nondeforming, equal radii cylinders rotating in opposite directions with equal surface speeds is considered. The lubricant is assumed to be a constant density, isoviscous, Newtonian fluid. The usual approach, which involves the use of Reynolds equation everywhere, is not followed. Instead, the situation is restricted to one in which the lubricant enters the contact region in thin films which adhere to the cylinders. Using Reynolds equation only at the line of centers and a suitable thin film approximation far from that point, the intervening region is treated as a general creeping flow region. Solutions, incorporating complete free surface boundary conditions, are obtained numerically. The hitherto unobtained results due to this approach include the existence of a unique free surface location for a fixed set of operating conditions.

Medrow, R. A.↗
NASA NTRS1987

Short efficient ejector systems

A research program was conducted to improve the performance of low pressure ratio ejector systems. The results show that short, efficient ejectors operating at nearly ideal performance are possible through the use of forced mixer lobes. Forced mixer lobes generate large scale axial vorticity which results in rapid mixing and improved diffuser performance. Ejector testing was conducted using both an ejector wind tunnel. Numerous mixer lobe variations were tested to develop lobe design guidelines. The improved performance of mixer-ejectors is presented over a range of operating conditions. Results of mixer lobe angle, penetration, and alignment are presented. Lobe angles of up to 25 deg, coupled with diffuser wall angles over 20 deg, operate without separation, allowing efficient, short ejector systems. Both warm and cold flow test results are presented. Temperature similarity expressions previously developed are further formulated and verified.

Presz, Walter M., Jr.↗
NASA NTRS1989

Modeling of transient heat pipe operation

Mathematical models and an associated computer program for heat pipe startup from the frozen state have been developed. Finite element formulations of the governing equations are written for each heat pipe region for each operating condition during startup from the frozen state. The various models were checked against analytical and experimental data available in the literature for three specific types of operation. Computations using the methods developed were made for a space shuttle reentry mission where a heat pipe cooled leading edge was used on the wing.

Colwell, Gene T.↗
NASA NTRS1991

Mechanical behavior of a continuous fiber reinforced aluminum matrix composite subjected to transverse and thermal loading

The transverse properties of an aluminum alloy metal matrix composite reinforced by continuous alumina fibers were investigated. The composite is subjected to both mechanical and cyclic thermal loading. The results of an experimental program indicate that the shakedown concept of structural mechanics provides a means of describing the material behavior. When the loading conditions are within the shakedown region, the material finally responds in an elastic manner after initial plastic response, and for loading conditions outside the shakedown region, the material exhibits a rapid incremental plastic strain accumulation. The failure strain varies by an order of magnitude according to the operating conditions. Hence, for high mechanical and low thermal loading, the failure strains is small; for low mechanical and high thermal loading, the failure strain is large.

Jansson, S.↗
NASA NTRS2010

Heat Flux and Wall Temperature Estimates for the NASA Langley HIFiRE Direct Connect Rig

An objective of the Hypersonic International Flight Research Experimentation (HIFiRE) Program Flight 2 is to provide validation data for high enthalpy scramjet prediction tools through a single flight test and accompanying ground tests of the HIFiRE Direct Connect Rig (HDCR) tested in the NASA LaRC Arc Heated Scramjet Test Facility (AHSTF). The HDCR is a full-scale, copper heat sink structure designed to simulate the isolator entrance conditions and isolator, pilot, and combustor section of the HIFiRE flight test experiment flowpath and is fully instrumented to assess combustion performance over a range of operating conditions simulating flight from Mach 5.5 to 8.5 and for various fueling schemes. As part of the instrumentation package, temperature and heat flux sensors were provided along the flowpath surface and also imbedded in the structure. The purpose of this paper is to demonstrate that the surface heat flux and wall temperature of the Zirconia coated copper wall can be obtained with a water-cooled heat flux gage and a sub-surface temperature measurement. An algorithm was developed which used these two measurements to reconstruct the surface conditions along the flowpath. Determinations of the surface conditions of the Zirconia coating were conducted for a variety of conditions.

Cuda, Vincent, Jr.↗
NASA NTRS2009

MODIS On-Board Blackbody Function and Performance

Two MODIS instruments are currently in orbit, making continuous global observations in visible to long-wave infrared wavelengths. Compared to heritage sensors, MODIS was built with an advanced set of on-board calibrators, providing sensor radiometric, spectral, and spatial calibration and characterization during on-orbit operation. For the thermal emissive bands (TEB) with wavelengths from 3.7 m to 14.4 m, a v-grooved blackbody (BB) is used as the primary calibration source. The BB temperature is accurately measured each scan (1.47s) using a set of 12 temperature sensors traceable to NIST temperature standards. The onboard BB is nominally operated at a fixed temperature, 290K for Terra MODIS and 285K for Aqua MODIS, to compute the TEB linear calibration coefficients. Periodically, its temperature is varied from 270K (instrument ambient) to 315K in order to evaluate and update the nonlinear calibration coefficients. This paper describes MODIS on-board BB functions with emphasis on on-orbit operation and performance. It examines the BB temperature uncertainties under different operational conditions and their impact on TEB calibration and data product quality. The temperature uniformity of the BB is also evaluated using TEB detector responses at different operating temperatures. On-orbit results demonstrate excellent short-term and long-term stability for both the Terra and Aqua MODIS on-board BB. The on-orbit BB temperature uncertainty is estimated to be 10mK for Terra MODIS at 290K and 5mK for Aqua MODIS at 285K, thus meeting the TEB design specifications. In addition, there has been no measurable BB temperature drift over the entire mission of both Terra and Aqua MODIS.

Xiaoxiong, Xiong↗
NASA NTRS2011

Modeling Weather Impact on Ground Delay Programs

Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.

Wang, Yao↗
NASA NTRS2015

A Maneuvering Flight Noise Model for Helicopter Mission Planning

A new model for estimating the noise radiation during maneuvering flight is developed in this paper. The model applies the Quasi-Static Acoustic Mapping (Q-SAM) method to a database of acoustic spheres generated using the Fundamental Rotorcraft Acoustics Modeling from Experiments (FRAME) technique. A method is developed to generate a realistic flight trajectory from a limited set of waypoints and is used to calculate the quasi-static operating condition and corresponding acoustic sphere for the vehicle throughout the maneuver. By using a previously computed database of acoustic spheres, the acoustic impact of proposed helicopter operations can be rapidly predicted for use in mission-planning. The resulting FRAME-QS model is applied to near-horizon noise measurements collected for the Bell 430 helicopter undergoing transient pitch up and roll maneuvers, with good agreement between the measured data and the FRAME-QS model.

Greenwood, Eric↗
NASA NTRS2016

Post-Test Inspection of NASA's Evolutionary Xenon Thruster Long-Duration Test Hardware: Discharge and Neutralizer Cathodes

The NEXT Long-Duration Test is part of a comprehensive thruster service life assessment intended to demonstrate overall throughput capability, validate service life models, quantify wear rates as a function of time and operating condition, and identify any unknown life-limiting mechanisms. The test was voluntarily terminated in February 2014 after demonstrating 51,184 hours of high-voltage operation, 918 kg of propellant throughput, and 35.5 MN-s of total impulse. The post-test inspection of the thruster hardware began shortly afterwards with a combination of non-destructive and destructive analysis techniques, and is presently nearing completion. This paper presents relevant results of the post-test inspection for both discharge and neutralizer cathodes. Discharge keeper erosion was found to be significantly reduced from what was observed in the NEXT 2 kh wear test and NSTAR Extended Life Test, providing adequate protection of vital cathode components throughout the test with ample lifetime remaining. The area of the discharge cathode orifice plate that was exposed by the keeper orifice exhibited net erosion, leading to cathode plate material building up in the cathode-keeper gap and causing a thermally-induced electrical short observed during the test. Significant erosion of the neutralizer cathode orifice was also found and is believed to be the root cause of an observed loss in flow margin. Deposition within the neutralizer keeper orifice as well as on the downstream surface was thicker than expected, potentially resulting in a facility-induced impact on the measured flow margin from plume mode. Neutralizer keeper wall erosion on the beam side was found to be significantly lower compared to the NEXT 2 kh wear test, likely due to the reduction in beam extraction diameter of the ion optics that resulted in decreased ion impingement. Results from the post-test inspection have led to some minor thruster design improvements.

Electric Propulsion↗
NASA NTRS2016

Post-Test Inspection of NASA's Evolutionary Xenon Thruster Long-Duration Test Hardware: Discharge Chamber

The NEXT Long-Duration Test is part of a comprehensive thruster service life assessment intended to demonstrate overall throughput capability, validate service life models, quantify wear rates as a function of time and operating condition, and identify any unknown life-limiting mechanisms. The test was voluntarily terminated in February 2014 after demonstrating 51,184 hours of high-voltage operation, 918 kg of propellant throughput, and 35.5 MN-s of total impulse. The post-test inspection of the thruster hardware began shortly afterwards with a combination of non-destructive and destructive analysis techniques, and is presently nearing completion. This paper presents relevant results of the post-test inspection for the discharge chamber as well as other miscellaneous components such as the high-voltage propellant isolators and electrical cabling. Comparison of magnetic field measurements taken during pretest and post-test inspections indicate that the field strength did not degrade, consistent with performance data obtained during the test. Inspection of discharge chamber mesh samples show a deposition coating primarily composed of grid material that is approximately 15 micrometers in thickness. This thickness is well within the retention capability of the mesh and is therefore not expected to present any issues. Approximately 3.1 grams of deposition flakes were found at the bottom of the discharge chamber, composed primarily of grid material and carbon. Calculated size histograms of these flakes indicate that 99% have a maximum dimension of 200 micrometers or smaller, which is significantly less than the ion optics grid gap. Larger flakes that are capable of causing a grid-to-grid short will be analyzed to determine if their formation will occur in flight or is a facility effect. The high-voltage propellant isolators as well as numerous other electrical insulators were inspected and no evidence of arcing or any other issues were found.

Electric Propulsion↗