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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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NASA NTRS2018

The Ability of NASA's Meteoroid Engineering Model to Replicate in Situ Impact Data

Meteoroid environment models must describe the mass, directionality, velocity, and density distributions of meteoroids in order to correctly predict the rate at which meteoroids impact spacecraft. We present an updated version of NASA's Meteoroid Engineering Model (MEM) that better captures the correlation between directionality and velocity and incorporates a bulk density distribution. We compare the resulting model with the rate of large particle impacts seen on the Long Duration Exposure Facility (LDEF) and the Pegasus I and II satellites. The updated model shows closer agreement with these in situ data than previous versions of MEM.

Moorhead, Althea V.↗
NASA NTRS1990

Data compression applied to HHVT

A task order was written by the High Resolution, High Frame Rate Video Technology (HHVT) project engineers to study data compression techniques that could be applied to the HHVT system. Specifically, the goals of the HHVT data compression study are to accomplish the following: (1) Determine the downlink capabilities of the Space Shuttle and Space Station Freedom to support HHVT data (i.e., determine the maximum data rates and link availability); (2) Determine current and projected capabilities of high speed storage media to support HHVT data by determining their maximum data acquisition/transmission rates and volumes; (3) Identify which experiment in the HHVT Users' Requirement data base need data compression, based on the experiments' imaging requirements; (4) Select the best data compression technique for each of these users by identifying a technique that provides compression but minimizes distortion; and (5) Investigate state-of-the-art technologies for possible implementation of selected data compression techniques. Data compression will be needed because of the high data rates and larger volumes of data that will result from the use of digitized video onboard the Space Shuttle and Space Station Freedom.

Thompson, William K.↗
NASA NTRS2004

Turbomachine Sealing and Secondary Flows - Part 3: Review of Power-Stream Support, Unsteady Flow Systems, Seal and Disk Cavity Flows, Engine Externals, and Life and Reliability Issues - Part 3

The issues and components supporting the engine power stream are reviewed. It is essential that companies pay close attention to engine sealing issues, particularly on the high-pressure spool or high-pressure pumps. Small changes in these systems are reflected throughout the entire engine. Although cavity, platform, and tip sealing are complex and have a significant effect on component and engine performance, computational tools (e.g., NASA-developed INDSEAL, SCISEAL, and ADPAC) are available to help guide the designer and the experimenter. Gas turbine engine and rocket engine externals must all function efficiently with a high degree of reliability in order for the engine to run but often receive little attention until they malfunction. Within the open literature statistically significant data for critical engine components are virtually nonexistent; the classic approach is deterministic. Studies show that variations with loading can have a significant effect on component performance and life. Without validation data they are just studies. These variations and deficits in statistical databases require immediate attention.

Hendricks, R. C.↗
NASA NTRS2014

Spinoff 2013

Topics covered include: Innovative Software Tools Measure Behavioral Alertness; Miniaturized, Portable Sensors Monitor Metabolic Health; Patient Simulators Train Emergency Caregivers; Solar Refrigerators Store Life-Saving Vaccines; Monitors Enable Medication Management in Patients' Homes; Handheld Diagnostic Device Delivers Quick Medical Readings; Experiments Result in Safer, Spin-Resistant Aircraft; Interfaces Visualize Data for Airline Safety, Efficiency; Data Mining Tools Make Flights Safer, More Efficient; NASA Standards Inform Comfortable Car Seats; Heat Shield Paves the Way for Commercial Space; Air Systems Provide Life Support to Miners; Coatings Preserve Metal, Stone, Tile, and Concrete; Robots Spur Software That Lends a Hand; Cloud-Based Data Sharing Connects Emergency Managers; Catalytic Converters Maintain Air Quality in Mines; NASA-Enhanced Water Bottles Filter Water on the Go; Brainwave Monitoring Software Improves Distracted Minds; Thermal Materials Protect Priceless, Personal Keepsakes; Home Air Purifiers Eradicate Harmful Pathogens; Thermal Materials Drive Professional Apparel Line; Radiant Barriers Save Energy in Buildings; Open Source Initiative Powers Real-Time Data Streams; Shuttle Engine Designs Revolutionize Solar Power; Procedure-Authoring Tool Improves Safety on Oil Rigs; Satellite Data Aid Monitoring of Nation's Forests; Mars Technologies Spawn Durable Wind Turbines; Programs Visualize Earth and Space for Interactive Education; Processor Units Reduce Satellite Construction Costs; Software Accelerates Computing Time for Complex Math; Simulation Tools Prevent Signal Interference on Spacecraft; Software Simplifies the Sharing of Numerical Models; Virtual Machine Language Controls Remote Devices; Micro-Accelerometers Monitor Equipment Health; Reactors Save Energy, Costs for Hydrogen Production; Cameras Monitor Spacecraft Integrity to Prevent Failures; Testing Devices Garner Data on Insulation Performance; Smart Sensors Gather Information for Machine Diagnostics; Oxygen Sensors Monitor Bioreactors and Ensure Health and Safety; Vision Algorithms Catch Defects in Screen Displays; and Deformable Mirrors Capture Exoplanet Data, Reflect Lasers.

Source record↗
NASA NTRS2018

Integrated Data Visualization for Human Missions

Interplanetary missions produce exceptionally large and complex volumes of data that can be extremely difficult to navigate. This is especially true for human missions. This project seeks to develop an integrated data visualization environment that builds on the success of Apollo17.org allowing for integration of operational, engineering and scientific data while also preserving the context under which it was collected during the mission. We will build a product that integrates existing data from the Neutral Buoyancy Lab (NBL) to improve data visualization for extra vehicular activity and interplanetary missions.

Regberg, Aaron B.↗
DOE OSTI2017

An assessment of CFD-based wall heat transfer models in piston engines

The lack of accurate submodels for in-cylinder heat transfer has been identified as a key shortcoming in developing truly predictive, physics-based computational fluid dynamics (CFD) models that can be used to develop combustion systems for advanced high-efficiency, low-emissions engines. Only recently have experimental methods become available that enable accurate near-wall measurements to enhance simulation capability via advancing models. Initial results show crank-angle dependent discrepancies with respect to previously used boundary-layer models of up to 100%. However, available experimental data is quite sparse (only few data points on engine walls) and limited (available measurements are those of heat flux only). Predictive submodels are needed for medium-resolution ("engineering") LES and for unsteady Reynolds-averaged simulations (URANS). Recently, some research groups have performed DNS studies on engine-relevant conditions using simple geometries. These provide very useful data for benchmarking wall heat transfer models under such conditions. Further, a number of new and more sophisticated models have also become available in the literature which account for these engine-like conditions. Some of these have been incorporated while others of a more complex nature, which include solving additional partial differential equations (PDEs) within the thin boundary layer near the wall, are underway. These models will then be tested against the available DNS/experimental data in both SI (spark-ignition) and CI (compression-ignition) engines.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Methods and systems for evaluating data transportability in distribution grids

This document describes systems and techniques for evaluating and improving distribution-grid data transportability. These systems and techniques allow engineers to quantify the data transportability of a communication system within or connected to a distribution grid, which represents an ability to transport in real-time telemetry from source locations (e.g., sensors in the distribution grid) to control mechanisms. Distribution engineers can use the sensor readings to perform grid analytics, control operating parameters, and operate protection systems. Distribution engineers can also use the transportability of the communication system to evaluate the observability of the distribution grid, which represents an ability to combine actual measurements and various types of computations (e.g., analytics, estimators, forecasters) from a system model. Distribution engineers can then generate a sensor allocation plan that indicates the number and location of sensors to maximize observability for a fixed sensor cost and/or minimize sensor cost for predetermined observability.

Taft, Jeffrey D.↗
NASA NTRS1990

High speed turboprop aeroacoustic study (counterrotation). Volume 2: Computer programs

The isolated counterrotating high speed turboprop noise prediction program developed and funded by GE Aircraft Engines was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in the NASA-Lewis 8 x 6 and 9 x 15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counter rotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attack was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combined into a single prediction program. The results were compared with data taken during the flight test of the B727/UDF (trademark) engine demonstrator aircraft.

Whitfield, C. E.↗
NASA NTRS2011

Designing a Distributed Space Systems Simulation in Accordance with the Simulation Interoperability Standards Organization (SISO)

Simulations are essential for engineering design. These virtual realities provide characteristic data to scientists and engineers in order to understand the details and complications of the desired mission. A standard development simulation package known as Trick is used in developing a source code to model a component (federate in HLA terms). The runtime executive is integrated into an HLA based distributed simulation. TrickHLA is used to extend a Trick simulation for a federation execution, develop a source code for communication between federates, as well as foster data input and output. The project incorporates international cooperation along with team collaboration. Interactions among federates occur throughout the simulation, thereby relying on simulation interoperability. Communication through the semester went on between participants to figure out how to create this data exchange. The NASA intern team is designing a Lunar Rover federate and a Lunar Shuttle federate. The Lunar Rover federate supports transportation across the lunar surface and is essential for fostering interactions with other federates on the lunar surface (Lunar Shuttle, Lunar Base Supply Depot and Mobile ISRU Plant) as well as transporting materials to the desired locations. The Lunar Shuttle federate transports materials to and from lunar orbit. Materials that it takes to the supply depot include fuel and cargo necessary to continue moon-base operations. This project analyzes modeling and simulation technologies as well as simulation interoperability. Each team from participating universities will work on and engineer their own federate(s) to participate in the SISO Spring 2011 Workshop SIW Smackdown in Boston, Massachusetts. This paper will focus on the Lunar Rover federate.

Cowen, Benjamin↗
NASA NTRS2014

Spring 2014 Internship Diffuser Data Analysis

J-2X engine testing on the A-2 test stand at the NASA John C. Stennis Space Center (SSC) has recently concluded. As part of that test campaign, the engine was operated at lower power levels in support of expanding the use of J-2X to other missions. However, the A-2 diffuser was not designed for engine testing at the proposed low power levels. To evaluate the risk of damage to the diffuser, computer simulations were created of the rocket engine exhaust plume inside the 50ft long, water-cooled, altitude-simulating diffuser. The simulations predicted that low power level testing would cause the plume to oscillate in the lower sections of the diffuser. This can possibly cause excessive vibrations, stress, and heat transfer from the plume to the diffuser walls. To understand and assess the performance of the diffuser during low power level engine testing, nine accelerometers and four strain gages were installed around the outer surface of the diffuser. The added instrumentation also allowed for the verification of the rocket exhaust plume computational model. Prior to engine hot-fire testing, a diffuser water-flow test was conducted to verify the proper operation of the newly installed instrumentation. Subsequently, two J-2X engine hot-fire tests were completed. Hot-Fire Test 1 was 11.5 seconds in duration, and accelerometer and strain data verified that the rocket engine plume oscillated in the lower sections of the diffuser. The accelerometers showed very different results dependent upon location. The diffuser consists of four sections, with Section 1 being closest to the engine nozzle and Section 4 being farthest from the engine nozzle. Section 1 accelerometers showed increased amplitudes at startup and shutdown, but low amplitudes while the diffuser was started. Section 3 accelerometers showed the opposite results with near zero G amplitudes prior to and after diffuser start and peak amplitudes to +/- 100G while the diffuser was started. Hot-Fire Test 1 strain gages showed different data dependent on section. Section 1 strains were small, and were in the range of 50 to 150 microstrain, which would result in stresses from 1.45 to 4.35 ksi. The yield stress of the material, A-285 Grade C Steel, is 29.7 ksi. Section 4 strain gages showed much higher values with strains peaking at 1600 microstrain. This strain corresponds to a stress of 46.41 ksi, which is in excess of the yield stress, but below the ultimate stress of 55 to 75 ksi. The decreased accelerations and strain in Section 1, and the increased accelerations and strain in Sections 3 and 4 verified the computer simulation prediction of increased plume oscillations in the lower sections of the diffuser. Hot-Fire Test 2 ran for a duration of 125 seconds. The engine operated at a slightly higher power level than Hot-Fire Test 1 for the initial 35 seconds of the test. After 35 seconds the power level was lowered to Hot-Fire Test 1 levels. The acceleration and strain data for Hot-Fire Test 2 was similar during the initial part of the test. However, just prior to the engine being lowered to the Hot-Fire Test 1 power level, the strain gage data in Section 4 showed a large decrease to strains near zero microstrain from their peak at 1500 microstrain. Future work includes further strain and acceleration data analysis and evaluation.

Laigaie, Robert T.↗
NASA NTRS1991

Mars Observer as a precursor to intensive exploration of Mars

The Mars Observer Mission, to be launched by the United States in September 1992, is designed to perform an extended orbital study of the Martian surface, atmosphere, climate, and gravitational and magnetic fields using a spacecraft in Mars orbit for one Martian year. This information will add to the global data base that is necessary for increasing scientific understanding of Mars, as well as for planning the next stages of intensive exploration of the planet. Future missions will progress from more specific robotic exploration to eventual human exploration, and will require progressively more detailed engineering information. Mars Observer will provide key basic data including planet shape, gravity field, geodetic framework, topography, characteristics of the surface, atmospheric profiles, dust content of the atmosphere, and wind field. Special data products for engineering purposes could be obtained from the currently planned data return, and additional engineering data could be returned by augmentation to the basic Mars Observer's operation.

Cunningham, Glenn E.↗
DOE OSTI2025

Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?

Machine learning (ML) has been leveraged to tackle a diverse range of tasks in almost all branches of nuclear engineering. Many of the successes in ML applications can be attributed to the recent performance breakthroughs in deep learning, the growing availability of computational power, data, and easy-to-use ML libraries. However, these empirical successes have often outpaced our formal understanding of the ML algorithms. An important but under-rated area is uncertainty quantification (UQ) of ML. ML-based models are subject to approximation uncertainty when they are used to make predictions, due to sources including but not limited to, data noise, data coverage, extrapolation, imperfect model architecture and the stochastic training process. The goal of this paper is to clearly explain and illustrate the importance of UQ of ML. We will elucidate the differences in the basic concepts of UQ of physics-based models and data-driven ML models. Various sources of uncertainties in physical modeling and data-driven modeling will be discussed, demonstrated, and compared. We will also present and demonstrate a few techniques to quantify the ML prediction uncertainties, including Monte Carlo dropout, deep ensemble, Bayesian neural networks, Gaussian Processes and conformal prediction. Lastly, we will discuss the need for building a verification, validation and UQ framework to establish ML credibility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1974

Space shuttle maneuvering engine reusable thrust chamber program. Task 11: Stability analyses and acoustic model testing data dump

The combustion stability characteristics of engines applicable to the Space Shuttle Orbit Maneuvering System and the adequacy of acoustic cavities as a means of assuring stability in these engines were investigated. The study comprised full-scale stability rating tests, bench-scale acoustic model tests and analysis. Two series of stability rating tests were made. Acoustic model tests were made to determine the resonance characteristics and effects of acoustic cavities. Analytical studies were done to aid design of the cavity configurations to be tested and, also, to aid evaluation of the effectiveness of acoustic cavities from available test results.

Oberg, C. L.↗
NASA NTRS1974

Low-cycle fatigue analysis of a cooled copper combustion chamber

A three-dimensional finite element elastoplastic strain analysis was performed for the throat section of regeneratively cooled rocket engine combustion chamber. The analysis included thermal and pressure loads, and the effects of temperature dependent material properties, to determine the strain range corresponding to the engine operating cycle. The strain range was used in conjunction with OFHC copper isothermal fatigue test data to predict engine low-cycle fatigue life. The analysis was performed for chamber configuration and operating conditions corresponding to a hydrogen-oxygen chamber which was fatigue tested to failure at the NASA Lewis Research Center.

Miller, R. W.↗
NASA NTRS2001

Use of Soft Computing Technologies for a Qualitative and Reliable Engine Control System for Propulsion Systems

The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to improve overall vehicle system safety, reliability, and rocket engine performance by development of a qualitative and reliable engine control system (QRECS). Specifically, this will be addressed by enhancing rocket engine control using SCT, innovative data mining tools, and sound software engineering practices used in Marshall's Flight Software Group (FSG). The principle goals for addressing the issue of quality are to improve software management, software development time, software maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control methodologies, but to provide alternative design choices for control, implementation, performance, and sustaining engineering, all relative to addressing the issue of reliability. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion (system level), software engineering for embedded flight software systems, and soft computing technologies (i.e., neural networks, fuzzy logic, data mining, and Bayesian belief networks); some of which are briefed in this paper. For this effort, the targeted demonstration rocket engine testbed is the MC-1 engine (formerly FASTRAC) which is simulated with hardware and software in the Marshall Avionics & Software Testbed (MAST) laboratory that currently resides at NASA's Marshall Space Flight Center, building 4476, and is managed by the Avionics Department. A brief plan of action for design, development, implementation, and testing a Phase One effort for QRECS is given, along with expected results. Phase One will focus on development of a Smart Start Engine Module and a Mainstage Engine Module for proper engine start and mainstage engine operations. The overall intent is to demonstrate that by employing soft computing technologies, the quality and reliability of the overall scheme to engine controller development is further improved and vehicle safety is further insured. The final product that this paper proposes is an approach to development of an alternative low cost engine controller that would be capable of performing in unique vision spacecraft vehicles requiring low cost advanced avionics architectures for autonomous operations from engine pre-start to engine shutdown.

Trevino, Luis↗
NASA NTRS1977

Identification of Spey engine dynamics in the augmentor wing jet STOL research aircraft from flight data

The development and validation of a spey engine model is described. An analysis of the dynamical interactions involved in the propulsion unit is presented. The model was reduced to contain only significant effects, and was used, in conjunction with flight data obtained from an augmentor wing jet STOL research aircraft, to develop initial estimates of parameters in the system. The theoretical background employed in estimating the parameters is outlined. The software package developed for processing the flight data is described. Results are summarized.

Dehoff, R. L.↗
NASA NTRS1981

Optimization of thrust algorithm calibration for Computing System (TCS) for Thrust the NASA Highly Maneuverable Aircraft Technology (HiMAT) vehicle's propulsion system

A simplified gross thrust computing technique for the HiMAT J85-GE-21 engine using altitude facility data was evaluated. The results over the full engine envelope for both the standard engine mode and the open nozzle engine mode are presented. Results using afterburner casing static pressure taps are compared to those using liner static pressure taps. It is found that the technique is very accurate for both the standard and open nozzle engine modes. The difference in the algorithm accuracy for a calibration based on data from one test condition was small compared to a calibration based on data from all of the test conditions.

Hamer, M. J.↗