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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

An Assessment of CFD Effectiveness for Vortex Flow Simulation to Meet Preliminary Design Needs

The low-speed flight and transonic maneuvering characteristics of combat air vehicles designed for efficient supersonic flight are significantly affected by the presence of free vortices. At moderate-to-high angles of attack, the flow invariably separates from the leading edges of the swept slender wings, as well as from the forebodies of the air vehicles, and rolls up to form free vortices. The design of military vehicles is heavily driven by the need to simultaneously improve performance and affordability.1 In order to meet this need, increasing emphasis is being placed on using Modeling & Simulation environments employing the Integrated Product & Process Development (IPPD) concept. The primary focus is on expeditiously providing design teams with high-fidelity data needed to make more informed decisions in the preliminary design stage. Extensive aerodynamic data are needed to support combat air vehicle design. Force and moment data are used to evaluate performance and handling qualities; surface pressures provide inputs for structural design; and flow-field data facilitate system integration. Continuing advances in computational fluid dynamics (CFD) provide an attractive means of generating the desired data in a manner that is responsive to the needs of the preliminary design efforts. The responsiveness is readily characterized as timely delivery of quality data at low cost.

Raj, P.↗
NASA NTRS2019

WWAO-WSWC Workshop Report 2019 Final

EXECUTIVE SUMMARY The Western States Water Council (WSWC) and the NASA Western Water Applications Office (WWAO) hosted a joint workshop on technology transfer for water management in the Western U.S. The goals of the workshop were to understand how different agencies approach the technology transfer and research to operations (R2O) process, identify best practices, and discuss existing barriers to successful technology infusion into operational water resource management systems at the state and federal level. The workshop took place August 7-9, 2019 in Irvine, CA. Key outcomes of the meeting include the following:• U.S. Rep. Grace Napolitano provided opening remarks for the workshop, where she highlighted the critical value of water data and the importance of collaboration between state and federal agencies in working to advance the use of water data in water management, planning and policy. • A total of 33 participants (including remote participants) were part of the workshop. They included principal investigators and project teams supported by NASA (Cyanobacteria Assessment Network, Evapotranspiration for Western States, Evaporative Stress Index, the Airborne Snow Observatory, Satellite-based Snow Water Equivalent in the Sierra Nevadas, and Fallowed Area Mapping) as well as representatives from federal (USGS, NOAA, USBR, EPA) and state (CA, WY, OR, NE) agency partners. • One main outcome of the meeting was the consensus that successful transitions of new applications and new technologies into operations require careful planning, effective communication within and across institutions, resources and considerable time investments. In addition, there was broad agreement that significant lead time is often required to allow for identification of financial and technical resources to sustain operational use of new data, information and tools.• The meeting included remarks from U.S. Rep. Napolitano and discussions during presentations and breakout groups about key opportunities to develop best practices and streamline the technology transfer process. • For example, one key set of best practices that emerged revolved around the the importance of building trust and establishing clear lines of communication between the research and operational institutions. The conversations led to defining two key components of trust-building. The first aspect is purely technical. It requires effectively demonstrating that the proposed application meets the end user’s needs in terms of accuracy, format, resolution, latency, metadata and documentation. The second aspect of building trust involves developing sustained, productive and mutually-beneficial relationships with the partner operational agency. The best practices presented here span both the technical as well as the relational aspects of cultivating trust. • This workshop served as a first step in developing a broader community discussion around R2O in western water management. Many of the best practices and lessons learned described in this report represent starting places for action within the WWAO, WSWC and our colleagues’ institutions. • Effective implementation of the best practices that emerged from this workshop will require sustained investments of time, resources and transition planning. In recognition of this, the WSWC and the WWAO proposed continuation of discussions begun at the workshop through a series of semi-annual or annual workshops.

Wilardson, Tony↗
DOE OSTI2020

Machine Learning for Automated Extraction of Building Geometry

As data science comes to buildings, the promise of using machine learning and novel sources of data has received much attention. Advances in machine learning and computer vision algorithms, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics – cost-effectively, and at scale. Acquisition of features such as footprint are time consuming and costly to acquire with today’s manual methods, but can be streamlined through intelligent software-based solutions applied to satellite images. When combined with aerial RGB and thermal images, full 3D geometries and thermal maps can be constructed to determine additional characteristics such as window to wall ratio, height, number of stories and envelope thermal characteristics. In this paper we present three contributions to accelerate these high potential opportunities: (1) a methodical analysis of how these features can be integrated into today’s simulation and data driven software tools to enhance efficiency measure identification and owner/operator decision making; (2) development and accuracy testing of open source deep neural network methods to extract building footprints from satellite imagery, including the curation and application of openly available GIS datasets for training and continued development by others; and (3) an open framework for drone-based image capture and creation of 3D building geometries. This work represents an important bridge between high-level studies that span diverse application areas and those that detail point solutions yet cannot be easily replicated or extended.

Touzani, Samir↗
NASA NTRS2006

Embedded Sensors for Measuring Surface Regression

The development and evaluation of new hybrid and solid rocket motors requires accurate characterization of the propellant surface regression as a function of key operational parameters. These characteristics establish the propellant flow rate and are prime design drivers affecting the propulsion system geometry, size, and overall performance. There is a similar need for the development of advanced ablative materials, and the use of conventional ablatives exposed to new operational environments. The Miniature Surface Regression Sensor (MSRS) was developed to serve these applications. It is designed to be cast or embedded in the material of interest and regresses along with it. During this process, the resistance of the sensor is related to its instantaneous length, allowing the real-time thickness of the host material to be established. The time derivative of this data reveals the instantaneous surface regression rate. The MSRS could also be adapted to perform similar measurements for a variety of other host materials when it is desired to monitor thicknesses and/or regression rate for purposes of safety, operational control, or research. For example, the sensor could be used to monitor the thicknesses of brake linings or racecar tires and indicate when they need to be replaced. At the time of this reporting, over 200 of these sensors have been installed into a variety of host materials. An MSRS can be made in either of two configurations, denoted ladder and continuous (see Figure 1). A ladder MSRS includes two highly electrically conductive legs, across which narrow strips of electrically resistive material are placed at small increments of length. These strips resemble the rungs of a ladder and are electrically equivalent to many tiny resistors connected in parallel. A substrate material provides structural support for the legs and rungs. The instantaneous sensor resistance is read by an external signal conditioner via wires attached to the conductive legs on the non-eroding end of the sensor. The sensor signal can be transmitted from inside a high-pressure chamber to the ambient environment, using commercially available feedthrough connectors. Miniaturized internal recorders or wireless data transmission could also potentially be employed to eliminate the need for producing penetrations in the chamber case. The rungs are designed so that as each successive rung is eroded away, the resistance changes by an amount that yields a readily measurable signal larger than the background noise. (In addition, signal-conditioning techniques are used in processing the resistance readings to mitigate the effect of noise.) Hence, each discrete change of resistance serves to indicate the arrival of the regressing host material front at the known depth of the affected resistor rung. The average rate of regression between two adjacent resistors can be calculated simply as the distance between the resistors divided by the time interval between their resistance jumps. Advanced data reduction techniques have also been developed to establish the instantaneous surface position and regression rate when the regressing front is between rungs.

Gramer, Daniel J.↗
DOE OSTI2021

OpenET: Filling a Critical Data Gap in Water Management for the Western United States

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

In Situ Inference for Earth System Predictability

Focal Area: Focal Area 3: Insight gleaned from complex simulated data using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: An understanding of future evolution in precipitation extremes is critical to numerous DOE mission questions. Extreme events are by nature short time-scale events that are difficult to diagnose in available model data. Accurate modeling of extreme events necessarily requires high spatial resolution at the storm scale locally. However, the environment in which storms grow is dependent on global, remote, processes. These complex spatiotemporal relationships are impossible to diagnose at resolutions required to accurately model storms responsible for extreme precipitation. At exascale, climate simulations will produce results at fine enough resolution to investigate these relationships. However, the resulting data from these simulations will be far too large to save for post-simulation analysis. We advocate for fitting statistical models inside the simulations as they run, a context known as in situ, which will facilitate scientific investigations using the full fine-scale data stream. Figure 1 shows an example of the type of model we could consider, a Bayesian hierarchical spatial regression model. Precipitation extremes at each grid cell are modeled using extreme value distributions. Since extremes are rare, fitting models to individual grid cells can result in high variance and poor estimates. Instead, the model can be made more robust by smoothing the parameters of the extreme value model across space. Additionally, the parameters themselves can be functionally linked to other variables elsewhere in the simulation. Thus, we can use the fine-scale data to build more robust models for extremes that link extreme behavior to other climate patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Thermodynamics of Crystallization and Phase-Separation in Melt-Derived Nuclear Waste Forms

This project aimed to gain detailed and fundamental understanding of the stability of glass waste forms to be used for safe and reliable encapsulation of nuclear waste. The focus was to understand thermodynamic and structural properties involved in crystallization and phase separation in melt-derived waste form glasses and glass-ceramics by studying a baseline glass composition with varying additives. This was achieved by combining neutron total scattering, advanced calorimetric measurements, and extensive modeling study. This project harnessed diverse and complementary approaches and expertise from four collaborating interdisciplinary institutions (two universities, one national laboratory, and one UK university partner). Samples were prepared at the national laboratory and exchanged with the two university institutions. The thermodynamic data obtained by various advanced calorimetry techniques were linked to the underlying short-range structure of waste forms measured by state-of-the-art neutron total scattering experiments. An important element of this project was extensive modeling to interpret and fundamentally understand the experimental results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Development of a Consistent GEOsat Cloud Property Dataset for the CERES Climate Data Record

Cloud properties are critical for understanding the Earth’s radiation budget and cloud feedbacks. At NASA Langley Research Center, the Satellite ClOud and Radiative Property retrieval System (SatCORPS) provides real-time and historical analyses of clouds derived from Geostationary satellite (GEOsat) data for weather and climate applications. For the Clouds and the Earth’s Radiant Energy System (CERES) program, the global constellation of GEOsats has been analyzed since 2000 to help characterize and account for the diurnal cycle of clouds and their radiative impacts in the CERES climate data record. Obtaining consistent cloud properties over the GEOsat data record during the CERES era is a major objective but a significant challenge considering the diversity of imaging capabilities deployed during that time. The GEOsat data analysis approach for the current CERES Edition-4 (Ed4) data products was focused on accuracy and consistency with MODIS by employing as much spectral information as possible from each satellite. However, the inconsistent use of spectral information across GEOsats led to marked discontinuities in the spatial and temporal record of cloud properties that had to be accounted for post facto in downstream CERES processing. This paper reports progress in developing a new GEOsat analysis system for the next CERES edition (Ed5) that has potential to improve cross-platform consistency and continuity. In this approach, the spectral channel complement is limited to just 3-channels during daytime, ~0.65 µm (VIS), ~3.9 µm (NIR), and ~10.8 µm (IR), common to nearly all of the satellites in the record. At night, a 2-channel approach is taken with the NIR and IR, and ~6.7 µm bands that includes a machine learning approach for optically thick cloud properties. A tradeoff is the potential for reduced accuracy particularly using data from the more advanced satellites that have more spectral channels (e.g. SEVIRI, AHI and ABI) that are known to help improve thin cirrus detection, cloud-aerosol discrimination and estimates in other difficult conditions that challenge cloud remote sensing. The new continuity approach is applied to one month of global GEOSat data for each year of the CERES record since 2000 and compared with the Ed4 GEO and MODIS cloud property time series in order to evaluate the level of improved consistency in the GEOsat record and to assess the accuracy impacts. Cloud fraction will also be assessed with CALIPSO data. Outstanding issues and challenges will be discussed. The results are expected to guide future work needed to develop a more robust GEOsat cloud data record for CERES.

CERES CDR↗
DOE OSTI2026

Mitigating Data Center Impact on Grid Stability: A Coordinated Control Strategy Using Verrus StabiliGrid Architecture

Large data centers, which now represent a significant and growing share of the total U.S. grid load, can inadvertently destabilize the electrical grid when they disconnect simultaneously during brief voltage disturbances. The July 10, 2024, Eastern Interconnection incident, in which a sub-100-millisecond transmission fault triggered the cascading loss of approximately 1,500 MW of data center load, illustrates this vulnerability. While commercial battery energy storage systems (BESS) deployed in data centers provide device-level fault ride-through per IEEE 1547, they lack coordination with facility protection logic and uninterruptible power supplies (UPS), limiting their effectiveness as grid-stabilizing assets. This report presents the Verrus StabiliGrid architecture, a coordinated control framework that integrates BESS, UPS, and point-of-interconnection (POI) protection settings to enable data centers to ride through both undervoltage and overvoltage grid contingencies without disconnecting. The four-step strategy encompasses: (1) high-resolution power quality monitoring to detect the grid state during events such as undervoltage, overvoltage, underfrequency, and overfrequency; (2) POI protection settings that allow for extended ride-through and grid-connected operation during grid contingencies; (3) grid state-driven autonomous dispatch of assets to improve grid resilience by reducing power draw during undervoltage or absorbing more power during overvoltage events; and (4) coordinated post-recovery dispatch of data center assets to restore firm load to pre-contingency levels. Validated through controller-hardware-in-the-loop (C-HIL) simulations at the National Laboratory of the Rockies, results show grid import restoration to pre-fault levels within 100 milliseconds of voltage recovery. This work advances the ability of data centers to transition from passive, disturbance-sensitive loads to active participants in grid stability, a capability increasingly required by emerging NERC and ERCOT regulatory frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Addressing Critical Knowledge Gaps on Wildland Fires with UAS Technology

To better predict and respond to extreme fire behavior, wind shear, and superheated gases, there is a need for enhanced tactical microclimate wind forecasting. Collecting real-time or near-real-time three-dimensional atmospheric data during wildland fire suppression is vital for both ground firefighters and aviation safety. The use of balloons for soundings is not allowed due to aircraft operations, so new technology must be used. To address this need, the NASA FireSense Project has invested in co-developing and transitioning advanced technologies for atmospheric data collection to operational platforms to support decisions for wildland fire management. One of these technology investments has been with Uninhabited Aerial Systems (UAS) for atmospheric soundings. In collaboration with MITRE Corporation, a technology demonstration of Uninhabited Aerial Systems (UAS) for atmospheric soundings was held in Missoula, MT. This demonstration featured a NASA-designed payload on a Freefly Alta-X UAS, consistent with USFS UAS operations, balloon-borne soundings for data validation, and microscale modeling efforts. Results of this effort will be presented including comparison of forecasted conditions to data collection values as well as the impact on forecasts given real-time mixing heights and dispersion levels.

Jennifer Fowler↗
DOE OSTI2022

Lighting System Control Data to Improve Design and Operation: Tunable Lighting System Data from NICU Patient Rooms

The advancement of LED and controls technology, computing capacity, and software provides new opportunities for researchers and designers to work together to further optimize spaces for occupant benefit. Here, lighting system control data from five neonatal intensive care unit patient rooms was collected over a 25-week monitoring period and analyzed to better understand occupant response to a tunable lighting system with automatic transitions throughout the day. Lighting systems are very rarely refined after installation based on actual use. Objective data detailing how the lighting system is used by the actual occupants highlights the opportunities for optimization after installation and provides insight for improving the next design. As use of the data becomes more commonplace, it can be leveraged for design recommendations. The collection of the data required no additional cost beyond the time for examining the data. The analysis revealed several clear opportunities for improvement, including adjustments to the default control setting at night, re-labeling of the control stations, and adjustments to the nighttime fade rate. The patient room occupants were active users of the different zones, dimming options, and manual overrides made available by the lighting system.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2019

The Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) Mission: Status, Science, Advances

The PACE mission represents NASA’s next investment in ocean color, cloud, and aerosol data records to enable continued and advanced insight into oceanographic and atmospheric responses to Earth’s changing climate. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission represents NASA’s next investment in satellite ocean color and the study of Earth’s ocean-atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth's changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave infrared, with a ground sample distance of 1-km at nadir. This payload is complemented by two multi-angle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022-to-early 2023, the PACE observatory will enable significant advances in the study of Earth’s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean-atmosphere-land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products.

P Jeremy Werdell↗
NASA NTRS1994

Development of an Advanced Animal Habitat for Spaceflight

It is necessary to fly a group-housed animals for many Life Science spaceflight studies. Currently, group-housed rodents are flown aboard the shuttle in the Animal Enclosure Module (AEM). Although the AEM has been used successfully for a number of flights, it has significant limitations in the number of animals it can accommodate, limited flight duration, passive temperature control and limited in flight data acquisition capability. An Advanced Animal Habitat (AAH) is being developed, which can be flown on the shuttle middeck, both spacelab and spacehab shuttle payload modules, and the space station. The AAH is designed to house 12 rats or 30 mice for up to 30 days. The AAH will have active temperature control, a window mechanism to facilitate video monitoring/recording of the animals, and biotelemetry capabilities. In addition, the design will permit access to the animals for experimental manipulations in space. The AAH can be refitted to experiment-specific requirements as needed. In initial 7-day hardware tests 12 male rats and 10 female mice show no adverse affects with respect to final body and organ weights as compared to vivarium. controls. The Advanced Animal Habitat will provide the science community opportunities to perform a greater variety of studies for longer duration in the microgravity environment than the current Animal Enclosure Module.

Baer, L.↗
DOE OSTI2025

Advancements in NEAMS Tool Capabilities for Multiphysics Simulation of Fast Reactor Core Bowing and Identification of Validation Test Data

Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism in liquid metal-cooled fast reactors and involves Multiphysics effects including radiation transport, fluid flow, heat transfer, and mechanical response to temperature and flux gradients. This report summarizes recent progress on developing a multiphysics, MOOSE-based workflow to predict core bowing and associated reactivity feedback. Last year, thermal fluids and mechanics were coupled on a multi-assembly benchmark problem based on ABR-1000 design. This year, the reactor physics code Griffin was assessed for readiness of core bowing calculations. Preliminary integration of Griffin’s ring-heterogeneous model with thermal fluids and thermal mechanics solvers was performed. Specifically, thermal-mechanics and reactor physics were coupled for single- and multi-assembly problems, and reactor physics and subchannel methods were coupled for a single assembly model. Finally, the workflow of all three physics was preliminarily demonstrated on a single assembly model. Caveats and future development needed have been identified. To supplement the multiphysics demonstration, verification and assessment efforts of thermos-mechanical capabilities for modeling thermo-mechanical core bowing behavior were continued by analyzing IAEA Verification Problem 5 which includes radiation swelling and creep. Additionally, a small core reactor physics benchmark defined by Japan Atomic Energy Agency (JAEA) was performed to assess neutronics models for estimating reactivity feedback. Finally, Fast Flux Test Facility (FFTF) validation test data for core bowing phenomena has been identified and summarized, with a recommended path forward for validation once this capability is mature.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Mnemosyne

SAND2024-08570O Mnemosyne is an interactive tool for finding, retrieving, and exploring information about U.S. nuclear tests documented in the National Nuclear Security Administration’s NV-209 report. It also acts as an information architecture and codebase for integrating additional information and computational tools related to these tests at the unclassified and classified levels. Users can search by any number of nuclear test attributes—name, yield range, altitude ranges, purpose of a test—and find all matching tests. Users can also retrieve specific test information published in NV-209. The tool displays geospatial and topological data about test location, and it provides an information architecture for storing additional contextual material, such as photographs. Mnemosyne provides a capability of interfacing with HYCHEM, Sandia's nuclear detonation optical waveform tool. The software is designed for use by government, academia, military, and research institutions. The software will likely be advanced to integrate seismic data and the nuclear detonation optical signal simulation code radCTH. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fisher, Dustin↗
DOE OSTI2025

The Satellite Image Simulation Toolkit

The Satellite Image Simulation Toolkit (SatIST) is a python software package designed to generate diverse and realistic satellite imaging scenarios. It serves as a toolkit for simulating data that supports the development and testing of algorithms used in satellite detection, calibration, and characterization. SIST provides a suite of simulation tools that allow users to replicate various satellite observation conditions, including sidereal and target tracking. By enabling the creation of scenarios that mimic real-world satellite operations, SIST facilitates advancements in satellite image data processing and the study of satellite behavior under different observational parameters.

Perloff, AlexxS [Lawrence Livermore National Labor↗
DOE OSTI2020

Alternative Fuels Data Center and Related Technology Integration Tools

The U.S. Department of Energy's (DOE) Office of Energy Efficiency and Renewable Energy's Vehicle Technologies Office (VTO) facilitates national coordination of the Clean Cities coalitions through its Technology Integration Program. VTO's Technology Integration Program supports a broad technology portfolio that can reduce transportation energy costs for businesses and consumers. Fleets, cities, and regions can use the tools featured in this guide to implement alternative fuels and advanced vehicles. Also learn how Clean Cities coalitions and their stakeholders across the country have used the tools.

AFDC↗
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↗