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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

Li, Zhijin↗
DOE OSTI2023

System and method for predicting the presence of rare earth elements

A system for predicting rare earth elements (REEs) in a feedstock sample includes a measurement instrument that records a measurement for a sample, a processor communicatively coupled to the measuring instrument, and a memory communicatively coupled to the processor and containing machine readable instructions that, when executed by the processor, cause the processor to correlate the measurement series using a model; and predict a presence of one or more rare earth element based at least in part on the correlation. A method for predicting rare earth elements includes measuring feedstock samples via XRF or PGNAA, to generate a measurements of elements of interest with a lower atomic weight than REEs; correlating the measurements with a model; and predicting a presence of one or more rare earth elements based at least in part on the correlation.

Fuka, Matthew↗
NASA NTRS1998

Automated System Checkout to Support Predictive Maintenance for the Reusable Launch Vehicle

The Propulsion Checkout and Control System (PCCS) is a predictive maintenance software system. The real-time checkout procedures and diagnostics are designed to detect components that need maintenance based on their condition, rather than using more conventional approaches such as scheduled or reliability centered maintenance. Predictive maintenance can reduce turn-around time and cost and increase safety as compared to conventional maintenance approaches. Real-time sensor validation, limit checking, statistical anomaly detection, and failure prediction based on simulation models are employed. Multi-signal models, useful for testability analysis during system design, are used during the operational phase to detect and isolate degraded or failed components. The TEAMS-RT real-time diagnostic engine was developed to utilize the multi-signal models by Qualtech Systems, Inc. Capability of predicting the maintenance condition was successfully demonstrated with a variety of data, from simulation to actual operation on the Integrated Propulsion Technology Demonstrator (IPTD) at Marshall Space Flight Center (MSFC). Playback of IPTD valve actuations for feature recognition updates identified an otherwise undetectable Main Propulsion System 12 inch prevalve degradation. The algorithms were loaded into the Propulsion Checkout and Control System for further development and are the first known application of predictive Integrated Vehicle Health Management to an operational cryogenic testbed. The software performed successfully in real-time, meeting the required performance goal of 1 second cycle time.

Patterson-Hine, Ann↗
DOE OSTI2023

Methods and systems for coordinating predictive cruise control, engine-off coasting, and hybrid power split

The enclosed disclosure relates to hybrid vehicles and systems with an engine, a drivetrain with a clutch and a transmission, an electric machine, and a controller. The controller receives lookahead information within a lookahead window and present state information of the hybrid vehicle. The controller determines a predicted coasting opportunity exceeding a predetermined threshold within the lookahead window and determines a cruise control reference speed, a power split between the engine and the electric machine, and a timing of enabling engine-off coasting during the coasting opportunity. The controller deactivates the engine and disengages the clutch at a start of the coasting opportunity when the engine-off coasting is enabled.

Gupta, Rohinish↗
NASA NTRS1994

Effects of Mistuning on the Forced Response of Turbomachinery Rotors

The basic purpose of this research has been to develop a fundamental understanding of the effects of blade-to-blade dissimilarities, or mistuning, on the dynamics of nearly cyclic bladed-disk assemblies. This topic is of importance as mistuning has been shown to increase the forced response amplitudes of some blades significantly, and even to lead to blade failure. Furthermore, the current trend toward high performance propulsion turbomachinery designed for finite service life demands an accurate prediction of system performance and dynamics at the design stage. This objective has been achieved by carrying out the following tasks. First, the investigation of the free and forced responses of representative, yet sufficiently simple blade assembly models that capture all the important characteristics of typical turbomachinery rotors. Second, the development of computational methods that predict the effects of mistuning in a systematic and reliable way, along with the development, of a systematic reduced-order modeling procedure for mistuned bladed disks. Third, the application of these findings and the tools developed to an industrial rotor, namely the first stage of turbine blades of the oxidizer turbopump in the space shuttle main rocket engine (SSME). The research supported by NASA has led to the development of a coherent theory for mistuned blade assemblies. The further implementation of these computational tools into the forced response prediction system currently under development in the Structural Dynamics Branch Forced Response Prediction System (FREPS) would enable the designer and the analyst (1) to identify types of blade assemblies highly sensitive to mistuning in various frequency and other parameter ranges and (2), to characterize mistuning effects on their forced response by predicting true response amplitudes and fatigue life estimates.

Stefko, George L.↗
DOE OSTI2020

Predictive valve control system

A pressure control system may include a plurality of inflatable objects, each of the inflatable objects having a respective pressure sensor and a respective inflation valve, wherein each of the inflation valves has a behavior profile predictive of an amount of current used by the valve when operated. A valve controller of the system may have a pressure management circuit that receives information from the pressure sensors and is configured to automatically maintain a respective selected pressure in each of the inflatable objects by issuing commands to operate the inflation valves. An electrical current management circuit of the valve controller may be configured to predict, based on the valve behavior profiles, what effect the command would have on a total current usage, when executed, and automatically prevent any command that would cause the total current usage to exceed a maximum allowable current.

Piraner, Alexander↗
NASA NTRS1981

Airframe-propulsion system aerodynamic interference predictions at high transonic Mach numbers including off-design engine airflow effects

The transonic speed regime for airplanes at conditions where inlet spillage takes place is discussed. A wind tunnel test program to evaluate aerodynamic performance penalties associated with propulsion system installation and operation at subsonic through low supersonic speeds was conducted. The accuracy of analytic methods for predicting transonic engine airframe interference effects was assessed. Study variables included Mach number, angle of attack, relative nacelle location, and nacelle mass flow ratio. Results include test theory comparisons of forces as well as induced pressure fields. Prediction capability of induced shock wave strength and locations is assessed. It was found that large interference forces due to engine location and flow spillage occur at transonic speeds, that theory explains these effects; and that theory can predict quantitatively these effects.

Kulfan, R. M.↗
DOE OSTI2024

Simulating Crystallization in a Colloidal System Using State Predictive Information Bottleneck Based Enhanced Sampling

Here, we investigate crystal nucleation in supersaturated colloid suspensions using enhanced molecular dynamics simulations augmented with machine learning techniques. The simulations reveal that crystallization in the model colloidal system studied here, with particles interacting through a repulsive screened Coulomb Yukawa potential, proceeds from vapor to dense liquid droplet to crystalline phases across multiple high barriers. Employing a one-dimensional reaction coordinate derived from the State Predictive Information Bottleneck framework, our simulations capture back-and-forth phase transitions across multiple barriers effectively in biased metadynamics simulations. We obtain relative free energy differences between different phases and also quantify the roles of different molecular level features in driving the phase changes.

Chemistry↗
NASA NTRS2011

High-Resolution Modeling of the Predictability of Convective Systems, and Influences by Absorbing Aerosols Over Northern India and the Himalayas Foothills During Boreal Summer

The Himalayas foothills region (HFR) is an important component of the South Asian monsoon. To the south, the HFR borders the fertile, populous, and heavily polluted Indo-Gangetic Plain (IGP). To the north, it rises to great height (approx. 4-5 km) to the Tibetan Plateau over a distance of less than 100 km. The HFR itself consists of complex mountainous terrain, with strong orographic forcing for precipitation. During the late spring and early summer, dust aerosol from the Thar and Middle East deserts , as well as moisture from the Arabian Sea were transported to the western part of the western part of the IGP and foothills spurs pre-monsoon severe thunderstorm over the region. During the monsoon season (mid June -August) convection from the Bay of Bengal, spread along the foothills northwestward to northern Pakistan. Recent climate model studies and preliminary observations have indicted not only the importance of dynamical forcing of precipitation in the HFR, but also possible strong impacts by the dense aerosols, from both local sources, and remote transport, that blanket the IGP from late spring up to the onset of the monsoon in June, and during monsoon breaks in July. In this work, we use the NASA Unified Weather Research and Forecasting (Nu-WRF) model to study the predictability ( 1-7 days) South Asian monsoon rainfall system. Results of 7 -day forecast experiments using an embedded domain of 27 km and 9 km resolution were conducted for the period June 11- July 15, 2008, with and without aerosol forcing are carried out to assess the intrinsic predictability of rainfall over the HFR, and possible impacts by aerosol direct effect, and possible connection of large-scale South Asian monsoon system.

Kim, Kyu-Myong↗
NASA NTRS1989

Prediction of full system helicopter noise for a MDHC 500E helicopter using the Rotonet program

The long-term goal of the NASA/U.S. helicopter industry program designated 'Rotonet' is the achievement of a helicopter noise signature-prediction capability on the basis of helicopter geometry and operating condition data. A prediction-validation data base is being compiled through flight testing of an MDHC 500E helicopter; the data base will encompass acoustic spectra, noise-level time histories, and effective perceived noise levels incorporating actual meteorological conditions and helicopter dynamics. An evaluation is made of the Rotonet system as currently defined, with a view to prospective developments.

Weir, D. S.↗
NASA NTRS2009

Fan Noise Prediction with Applications to Aircraft System Noise Assessment

This paper describes an assessment of current fan noise prediction tools by comparing measured and predicted sideline acoustic levels from a benchmark fan noise wind tunnel test. Specifically, an empirical method and newly developed coupled computational approach are utilized to predict aft fan noise for a benchmark test configuration. Comparisons with sideline noise measurements are performed to assess the relative merits of the two approaches. The study identifies issues entailed in coupling the source and propagation codes, as well as provides insight into the capabilities of the tools in predicting the fan noise source and subsequent propagation and radiation. In contrast to the empirical method, the new coupled computational approach provides the ability to investigate acoustic near-field effects. The potential benefits/costs of these new methods are also compared with the existing capabilities in a current aircraft noise system prediction tool. The knowledge gained in this work provides a basis for improved fan source specification in overall aircraft system noise studies.

Nark, Douglas M.↗
DOE OSTI2021

Online System ID for Predicting Power Plant Performance Throughout Cycling Operations

This presentation represents a review of the background research conducted by NETL to apply artificial intelligence, i.e. auto-recursive algorithms and data analytics to detect leaks in utility scale boilers and laboratory power systems. The new project being funded by the Advanced Sensors and Controls Program is part of the Field Work Proposal funded in EY21 as Task 53 to demonstrate the application of these techniques on a utility scale power system.

Shadle, Lawrence↗
NASA NTRS1990

The integration of automated knowledge acquisition with computer-aided software engineering for space shuttle expert systems

A prediction was made that the terms expert systems and knowledge acquisition would begin to disappear over the next several years. This is not because they are falling into disuse; it is rather that practitioners are realizing that they are valuable adjuncts to software engineering, in terms of problem domains addressed, user acceptance, and in development methodologies. A specific problem was discussed, that of constructing an automated test analysis system for the Space Shuttle Main Engine. In this domain, knowledge acquisition was part of requirements systems analysis, and was performed with the aid of a powerful inductive ESBT in conjunction with a computer aided software engineering (CASE) tool. The original prediction is not a very risky one -- it has already been accomplished.

Modesitt, Kenneth L.↗
NASA NTRS2003

Observing System Simulation Experiments to Determine the Potential Impact of Space-Based Lidar Wind Profiles on Weather Prediction

Observing system simulation experiments (OSSE's) provide an effective means to evaluate the potential impact of a proposed observing system, as well as to determine tradeoffs in their design, and to evaluate data assimilation methodology. Great care must be taken to ensure realism of the OSSE's, and in the interpretation of OSSE results. All of the OSSE's that have been conducted to date have demonstrated tremendous potential for space-based wind profile data to improve atmospheric analyses, forecasts, and research. This has been true for differing data assimilation systems, analysis methodology, and model resolutions. OSSE's clearly show much greater potential for observations of the complete wind profile than for single-level wind data or observations of the boundary layer alone.

Atlas, Robert↗
DOE OSTI2021

Revolutionizing observations and predictability of Arctic system dynamics through next-generation dense, heterogeneous and intelligent wireless sensor networks with embedded AI

The Arctic region is a complex and dynamic system, where changes in temperature and partitioning between water in solid, liquid and vapor phase are fundamentally reshaping hydro-biogeochemical fluxes from the bedrock to the atmosphere. The increasing temperature and frequency of extreme heat, precipitation and fire events (Wang et al., 2017; Meredith et al., 2019) have critical consequences for the Arctic ecosystems and people, as well as for the global climate system. Although many observational and remote sensing activities have been on-going, detailed ecosystem processes – particularly related to controls on and impacts of permafrost thaw – are difficult to detect or measure. To improve the understanding and prediction of these extreme events and their consequences, we need a revolution in the way we collect ground-based observations from hillslope to pan-Arctic scales and couple them with satellite imagery and models to deliver rich, actionable, and scale-appropriate data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Meteorology & Atmospheric Sciences↗