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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 1,369 records · Page 76

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DOE OSTI2023

High Speed Data Acquisition for Real Time Feedback in a Light Duty Engine Combustion-Mode Switching Application

The paper describes the integration of a high-speed data acquisition and diagnostics controller used in an advanced engine platform. The controller enables ultra-low emissions and new benchmarks of engine efficiency while running a Gasoline Compression Ignition (GCI) cycle on a 2.2L, 4-cylinder engine. The system enables real-time combustion feedback and vibration analysis in engines. The paper focuses on: (1) the development of an interpolative sampling algorithm for transposition of time acquired data to the crank angle domain using a production crank sensor (60-2 tooth wheel); (2) the control unit, high-speed data acquisition, communication rates between the dedicated data acquisition and base controller to ensure cycle-to-cycle feedback; and, (3) validation exercises using cylinder pressure measurements. Here, the study shows how the algorithm resolves cylinder pressure information over an engine cycle, validating its robustness across acquisition rates of 50 and 200 kHz, with crank angle resolutions of 0.5° and 0.1°. Results show that the 50 kHz, 0.5° hardware yield combustion phasing and torque estimates within 0.1° and 1% torque of those attained with the 200 kHz, 0.1° hardware. Finally, study shows the dedicated controller and communication speeds allow for next-cycle fuel injection correction for speeds above 5000 rpm.

42 ENGINEERING↗

NASA NTRS2001

PAGEMS

Glenn Research Center has extensive instrumentation developed for measuring particulate and gaseous emissions. The Particulate and Gaseous Emissions Measurement System (PAGEMS) is a mobile facility housing advanced instrumentation used for measuring combustion particulates and gaseous species. Particulates sizes ranging from 10 nm to 10 mm can be measured along with SO2, NO, NO2, CO, CO2, THC and O2 . Measurements can be made from subatmospheric up to 60 atm. Representative data from two engine tests will be discussed. In one test, the fuel sulfur content was changed, while the other test (T-63 engine) used various fuel additives. Probe design is essential to acquiring accurate particulate data. I will discuss the AEDC designed particulate probe, and the results of a University of Minnesota calibration study using the probe. Another suite of instrumentation, a tunable diode laser (TDL), enables in-situ real time gaseous species measurements. Representative TDL data from a T-38 aircraft will be presented. In conclusion, near term measurement opportunities will be discussed.

Bulzan, Dan↗

DOE OSTI2023

Systems, devices, and methods for performing augmented reality responsive to monitoring user behavior

Systems, devices, and methods are described for performing augmented reality (AR) to assist user performing a task in an environment. An AR device may be configured to capture real-time data. An AR engine may be configured to monitor user behavior from the real-time data responsive to feature extraction from the real-time data, compare the user behavior to pre-defined work procedures, and generate augmented reality objects to be output by the AR device.

Yoon, SuJong↗

NASA NTRS1978

Comparison of calculated and altitude-facility-measured thrust and airflow of two prototype F100 turbofan engines

A comparison is made of the facility performance data for the two engines with an engine performance model, and it provides corrections that can be applied to the model so that it represents the test engines accurately over the flight envelope. Test conditions ranged from Mach numbers of 0.80 to 2.00 and altitudes from 4020 meters to 15,240 meters. Two distortion screens were used to determine the effect of distortion on airflow. Reynolds number effects were also determined. Engine hysteresis is documented, as is an attempt to determine engine degradation. The calibrated engine model had a twice standard deviation accuracy of approximately 1.24 percent for corrected airflow and 2.38 percent for gross thrust.

Kurtenbach, F. J.↗

NASA NTRS2001

Development of a Gas-Fed Pulse Detonation Research Engine

In response to the growing need for empirical data on pulse detonation engine performance and operation, NASA Marshall Space Flight Center has developed and placed into operation a low-cost gas-fed pulse detonation research engine. The guiding design strategy was to achieve a simple and flexible research apparatus, which was inexpensive to build and operate. As such, the engine was designed to operate as a heat sink device, and testing was limited to burst-mode operation with run durations of a few seconds. Wherever possible, maximum use was made of standard off-the-shelf industrial or automotive components. The 5-cm diameter primary tube is about 90-cm long and has been outfitted with a multitude of sensor and optical ports. The primary tube is fed by a coaxial injector through an initiator tube, which is inserted directly into the injector head face. Four auxiliary coaxial injectors are also integrated into the injector head assembly. All propellant flow is controlled with industrial solenoid valves. An automotive electronic ignition system was adapted for use, and spark plugs are mounted in both tubes so that a variety of ignition schemes can be examined. A microprocessor-based fiber-optic engine control system was developed to provide precise control over valve and ignition timing. Initial shakedown testing with hydrogen/oxygen mixtures verified the need for Schelkin spirals in both the initiator and primary tubes to ensure rapid development of the detonation wave. Measured pressure wave time-of-flight indicated detonation velocities of 2.4 km/sec and 2.2 km/sec in the initiator and primary tubes, respectively. These values implied a fuel-lean mixture corresponding to an H2 volume fraction near 0.5. The axial distribution for the detonation velocity was found to be essentially constant along the primary tube. Time-resolved thrust profiles were also acquired for both underfilled and overfilled tube conditions. These profiles are consistent with previous time-resolved measurements on single-cycle tubes where the thrust is found to peak as the detonation wave exits the tube, and decay as the tube blows down.

Litchford, Ron J.↗

NASA NTRS1990

Data transmission networks

A task order was written by the High Resolution, High Frame Rate Video Technology (HHVT) project engineers to investigate data compression techniques that could be applied to the HHVT system, and both existing and planned downlink/uplink capabilities of the Space Shuttle and Space Station Freedom. The following tasks were included: (1) Investigate signal channel availability and determine both the maximum possible data rate and the average data rate; (2) Identify time blocks for HHVT video transmission assuming time sharing and interruptions in the communication links; (3) Determine the bit error rates to be expected; and (4) Define the transmit and receive interfaces. A summary chart of the data transmission capabilities for Tracking and Data Relay Satellite System (TDRSS), the Space Shuttle, Space Station Freedom, Spacelab, and USLab are also presented.

Alexovich, Robert↗

NASA NTRS2012

The Algorithm Theoretical Basis Document for Level 1A Processing

The first process of the Geoscience Laser Altimeter System (GLAS) Science Algorithm Software converts the Level 0 data into the Level 1A Data Products. The Level 1A Data Products are the time ordered instrument data converted from counts to engineering units. This document defines the equations that convert the raw instrument data into engineering units. Required scale factors, bias values, and coefficients are defined in this document. Additionally, required quality assurance and browse products are defined in this document.

Jester, Peggy L.↗

NASA NTRS1957

Altitude-Wind-Tunnel Investigation of the 19B-2, 19B-8, and 19XB-1 Jet Propulsion Engines: Performance and Windmilling Drag Characteristics - 3

The performance characteristics of the 19B-8 and 19XB-1 turbojet engines and the windmilling-drag characteristics of the 19B-6 engine were determined in the Cleveland altitude wind tunnel. The investigations were conducted on the 19B-8 engine at simulated altitudes from 5000 to 25,000 feet with various free-stream ram-pressure ratios and on the 19XB--1 engine at simulated altitudes from 5000 to 30,000 feet with approximately static free-stream conditions. Data for these two engines are presented to show the effect of altitude, free-stream ram-pressure ratio, and tail-pipe-nozzle area on engine performance. A 21-percent reduction in tail-pipe-nozzle area of the 19B-8 engine increased the let thrust 43 percent the net thrust 72 percent, and the fuel consumption 64 percent. An increase in free-stream ram-pressure ratio raised the jet thrust and the air flow and lowered the net thrust throughout the entire range of engine speeds for the 19B-8 engine. At similar operating conditions, the corrected jet thrust and corrected air flow were approximately the same for both engines, and the corrected specific fuel consumption based on jet thrust was lower for the 19XB-1 engine than for the 19B-8 engine. The thrust and air-flow data obtained with both engines at various altitudes for a given free-stream rampressure ratio were generalized to standard sea-level atmospheric conditions. The performance parameters involving fuel consumption generalized only at high engine speeds at simulated altitudes as high as 15,000 feet. The windmilling drag of the 19B-8 engine increased rapidly as the airspeed was increased.

Fleming, WIlliam A.↗

NASA NTRS1993

PATSTAGS: PATRAN-To-STAGSC-1 Translator

PATSTAGS computer program translates data from PATRAN finite-element mathematical model into STAGS input records used for engineering analysis. Reads data from PATRAN neutral file and writes STAGS input records into STAGS input file and UPRESS data file. Supports translations of nodal constraints, and of nodal, element, force, and pressure data. Written in FORTRAN 77.

Otte, Neil↗

NASA NTRSDate not supplied

TPSAS-NF1676L-33992-DND

The CERES Science Team integrates and fuses observations from 6 CERES instruments aboard the Terra, Aqua, S-NPP, and NOAA-20 missions with data from more than 20 other unique data sources. Following the November 2017 launch of CERES Flight Model 6 (FM6) onboard NOAA20, CERES has now amassed over 80 instrument-years of valuable Earth radiation budget data. The rapidly growing volume of CERES data coupled with the introduction of new data products alongside improvements to existing science algorithms fosters the requirement for faster, more flexible, and scalable data production and orchestration. New virtualized, cloud-centric compute hardware hosted by the NASA Langley Research Center’s (LaRC) Atmospheric Sciences Data Center (ASDC) provides an ideal environment for these ever-increasing data production demands for CERES. This poster discusses updates to the implementation of the CERES Data Management Team’s (DMT) CERES AuTomAted job Loading sYSTem (CATALYST), a custom data processing workflow engine for CERES, to use on-demand computing resources to perform automated CERES data production processing in a Linux-based container environment. Linux containers provide CERES the flexibility to build multiple production environments in containers tailored for specific workloads and allow effortless provisioning of resources based on the CERES Science Team’s data production requirements.

Thomas N. Hillyer↗

NASA NTRS2010

GLobal Integrated Design Environment (GLIDE): A Concurrent Engineering Application

The GLobal Integrated Design Environment (GLIDE) is a client-server software application purpose-built to mitigate issues associated with real time data sharing in concurrent engineering environments and to facilitate discipline-to-discipline interaction between multiple engineers and researchers. GLIDE is implemented in multiple programming languages utilizing standardized web protocols to enable secure parameter data sharing between engineers and researchers across the Internet in closed and/or widely distributed working environments. A well defined, HyperText Transfer Protocol (HTTP) based Application Programming Interface (API) to the GLIDE client/server environment enables users to interact with GLIDE, and each other, within common and familiar tools. One such common tool, Microsoft Excel (Microsoft Corporation), paired with its add-in API for GLIDE, is discussed in this paper. The top-level examples given demonstrate how this interface improves the efficiency of the design process of a concurrent engineering study while reducing potential errors associated with manually sharing information between study participants.

McGuire, Melissa L.↗

NASA NTRSDate not supplied

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗

NASA NTRSDate not supplied

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

Carl Malings↗

NASA NTRS1989

Large liquid rocket engine transient performance simulation system

Phase 1 of the Rocket Engine Transient Simulation (ROCETS) program consists of seven technical tasks: architecture; system requirements; component and submodel requirements; submodel implementation; component implementation; submodel testing and verification; and subsystem testing and verification. These tasks were completed. Phase 2 of ROCETS consists of two technical tasks: Technology Test Bed Engine (TTBE) model data generation; and system testing verification. During this period specific coding of the system processors was begun and the engineering representations of Phase 1 were expanded to produce a simple model of the TTBE. As the code was completed, some minor modifications to the system architecture centering on the global variable common, GLOBVAR, were necessary to increase processor efficiency. The engineering modules completed during Phase 2 are listed: INJTOO - main injector; MCHBOO - main chamber; NOZLOO - nozzle thrust calculations; PBRNOO - preburner; PIPE02 - compressible flow without inertia; PUMPOO - polytropic pump; ROTROO - rotor torque balance/speed derivative; and TURBOO - turbine. Detailed documentation of these modules is in the Appendix. In addition to the engineering modules, several submodules were also completed. These submodules include combustion properties, component performance characteristics (maps), and specific utilities. Specific coding was begun on the system configuration processor. All functions necessary for multiple module operation were completed but the SOLVER implementation is still under development. This system, the Verification Checkout Facility (VCF) allows interactive comparison of module results to store data as well as provides an intermediate checkout of the processor code. After validation using the VCF, the engineering modules and submodules were used to build a simple TTBE.

Mason, J. R.↗

NASA NTRS1993

Specialized data analysis for the Space Shuttle Main Engine and diagnostic evaluation of advanced propulsion system components

The Marshall Space Flight Center is responsible for the development and management of advanced launch vehicle propulsion systems, including the Space Shuttle Main Engine (SSME), which is presently operational, and the Space Transportation Main Engine (STME) under development. The SSME's provide high performance within stringent constraints on size, weight, and reliability. Based on operational experience, continuous design improvement is in progress to enhance system durability and reliability. Specialized data analysis and interpretation is required in support of SSME and advanced propulsion system diagnostic evaluations. Comprehensive evaluation of the dynamic measurements obtained from test and flight operations is necessary to provide timely assessment of the vibrational characteristics indicating the operational status of turbomachinery and other critical engine components. Efficient performance of this effort is critical due to the significant impact of dynamic evaluation results on ground test and launch schedules, and requires direct familiarity with SSME and derivative systems, test data acquisition, and diagnostic software. Detailed analysis and evaluation of dynamic measurements obtained during SSME and advanced system ground test and flight operations was performed including analytical/statistical assessment of component dynamic behavior, and the development and implementation of analytical/statistical models to efficiently define nominal component dynamic characteristics, detect anomalous behavior, and assess machinery operational condition. In addition, the SSME and J-2 data will be applied to develop vibroacoustic environments for advanced propulsion system components, as required. This study will provide timely assessment of engine component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. This contract will be performed through accomplishment of negotiated task orders.

Source record↗

NASA NTRS2001

Robust Strategy for Rocket Engine Health Monitoring

Monitoring the health of rocket engine systems is essentially a two-phase process. The acquisition phase involves sensing physical conditions at selected locations, converting physical inputs to electrical signals, conditioning the signals as appropriate to establish scale or filter interference, and recording results in a form that is easy to interpret. The inference phase involves analysis of results from the acquisition phase, comparison of analysis results to established health measures, and assessment of health indications. A variety of analytical tools may be employed in the inference phase of health monitoring. These tools can be separated into three broad categories: statistical, rule based, and model based. Statistical methods can provide excellent comparative measures of engine operating health. They require well-characterized data from an ensemble of "typical" engines, or "golden" data from a specific test assumed to define the operating norm in order to establish reliable comparative measures. Statistical methods are generally suitable for real-time health monitoring because they do not deal with the physical complexities of engine operation. The utility of statistical methods in rocket engine health monitoring is hindered by practical limits on the quantity and quality of available data. This is due to the difficulty and high cost of data acquisition, the limited number of available test engines, and the problem of simulating flight conditions in ground test facilities. In addition, statistical methods incur a penalty for disregarding flow complexity and are therefore limited in their ability to define performance shift causality. Rule based methods infer the health state of the engine system based on comparison of individual measurements or combinations of measurements with defined health norms or rules. This does not mean that rule based methods are necessarily simple. Although binary yes-no health assessment can sometimes be established by relatively simple rules, the causality assignment needed for refined health monitoring often requires an exceptionally complex rule base involving complicated logical maps. Structuring the rule system to be clear and unambiguous can be difficult, and the expert input required to maintain a large logic network and associated rule base can be prohibitive.

Santi, L. Michael↗

NASA NTRS2006

System Would Detect Foreign-Object Damage in Turbofan Engine

A proposed data-fusion system, to be implemented mostly in software, would further process the digitized and preprocessed outputs of sensors in a turbofan engine to detect foreign-object damage (FOD) [more precisely, damage caused by impingement of such foreign objects as birds, pieces of ice, and runway debris]. The proposed system could help a flight crew to decide what, if any, response is necessary to complete a flight safely, and could aid mechanics in deciding what post-flight maintenance action might be needed. The sensory information to be utilized by the proposed system would consist of (1) the output of an accelerometer in an engine-vibration-monitoring subsystem and (2) features extracted from a gas path analysis. ["Gas path analysis" (GPA) is a term of art that denotes comprehensive analysis of engine performance derived from readings of fuel-flow meters, shaft-speed sensors, temperature sensors, and the like.] The acceleration signal would first be processed by a wavelet-transform-based algorithm, using a wavelet created for the specific purpose of finding abrupt FOD-induced changes in noisy accelerometer signals. Two additional features extracted would be the amplitude of vibration (determined via a single- frequency Fourier transform calculated at the rotational speed of the engine), and the rate of change in amplitude due to an FOD-induced rotor imbalance. This system would utilize two GPA features: the fan efficiency and the rate of change of fan efficiency with time. The selected GPA and vibrational features would be assessed by two fuzzy-logic inference engines, denoted the "Gas Path Expert" and the "Vibration Expert," respectively (see Figure 1). Each of these inference engines would generate a "possibility" distribution for occurrence of an FOD event: Each inference engine would assign, to its input information, degrees of membership, which would subsequently be transformed into basic probability assignments for the gas path and vibration components. The outputs of the inference engines would be fused by use of Dempster s combination algorithm (more precisely, an algorithm, based on the Dempster-Shafer-Yager theory of evidence, for fusing uncertain or imprecise information) to provide a reduced body of information to a human or computer decision maker. Figure 2 depicts some outputs generated in response to simulated accelerometer and GPA signals

Torso, James A.↗

NASA NTRS2004

Harnessing Systems Engineering Methodology in Using Earth Science Research Data for Real Applications

For the last three decades, Earth science remote sensing technologies have been providing an enormous amount of useful data and information serving to broaden our understanding of the home planet as a system. NASA's Earth science program has deployed about 18 complex satellites and is in the process of defining and launching multiple observing systems in this decade. At the same time, the European Community and many other countries such as Russia, France, India, Japan, and China have also significantly contributed to Earth science research. To date, the majority of such efforts have concentrated on expanding our scientific understanding of the multiple nonlinear and chaotic processes of Earth's behavior. In recent years, legislators and stakeholders have put serious pressure on the science community to devote more attention to making use of scientific results for societal benefit. For instance, there are a number of areas such as energy forecasting, aviation safety, agricultural efficiency, disaster management, air quality and public health that can directly take advantage of Earth science results to analyze and predict large scale problems and conditions. This is becoming even more important now that we live in a global economy interconnected via the internet and transportation systems; regional environmental conditions can have far reaching impact across continental boundaries. These factors dictate requirements for global data that can help us assess and control the devastating problems of famine, water resources, wildfires, human health and more. To do this requires a serious, organized, and systematic approach that transfers fundamental research products to the applied sciences domain. This paper presents a systems engineering and management process that can effectively make such transfer of data to the user community. Examples are presented on how the above decision making framework can help in solving critical problems such as the spread of vector borne diseases, forecasts of harmful algal blooms as well as forest fires and wildfires, and the intercontinental transport of dust storms and pollution.

Habib, Shahid↗