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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 NTRS2008

Documentation for Three Wake Vortex Model Data Sets from Simulation of Flight 587 Wake Vortex Encounter Accident Case

This document contains a general description for data sets of a wake vortex system in a turbulent environment. The turbulence and thermal stratification of the environment are representative of the conditions on November 12, 2001 near John F. Kennedy International Airport. The simulation assumes no ambient winds. The full three dimensional simulation of the wake vortex system from a Boeing 747 predicts vortex circulation levels at 80% of their initial value at the time of the proposed vortex encounter. The linked vortex oval orientation showed no twisting, and the oval elevations at the widest point were about 20 meters higher than where the vortex pair joined. Fred Proctor of NASA?s Langley Research Center presented the results from this work at the NTSB public hearing that started 29 October 2002. This document contains a description of each data set including: variables, coordinate system, data format, and sample plots. Also included are instructions on how to read the data.

Switzer, George F.↗
NASA NTRS1991

Computerized reduction of elementary reaction sets for combustion modeling

If the entire set of elementary reactions is to be solved in the modeling of chemistry in computational fluid dynamics, a set of stiff ordinary differential equations must be integrated. Some of the reactions take place at very high rates, requiring short time steps, while others take place more slowly and make little progress in the short time step integration. The goal is to develop a procedure to automatically obtain sets of finite rate equations, consistent with a partial equilibrium assumptions, from an elementary set appropriate to local conditions. The possibility of computerized reaction reduction was demonstrated. However, the ability to use the reduced reaction set depends on the ability of the CFD approach in incorporate partial equilibrium calculations into the computer code. Therefore, the results should be tested on a code with partial equilibrium capability.

Wikstrom, Carl V.↗
NASA NTRS2008

An Integrated Approach to Damage Accommodation in Flight Control

In this paper we present an integrated approach to in-flight damage accommodation in flight control. The approach is based on Multiple Models, Switching and Tuning (MMST), and consists of three steps: In the first step the main objective is to acquire a realistic aircraft damage model. Modeling of in-flight damage is a highly complex problem since there is a large number of issues that need to be addressed. One of the most important one is that there is strong coupling between structural dynamics, aerodynamics, and flight control. These effects cannot be studied separately due to this coupling. Once a realistic damage model is available, in the second step a large number of models corresponding to different damage cases are generated. One possibility is to generate many linear models and interpolate between them to cover a large portion of the flight envelope. Once these models have been generated, we will implement a recently developed-Model Set Reduction (MSR) technique. The technique is based on parameterizing damage in terms of uncertain parameters, and uses concepts from robust control theory to arrive at a small number of "centered" models such that the controllers corresponding to these models assure desired stability and robustness properties over a subset in the parametric space. By devising a suitable model placement strategy, the entire parametric set is covered with a relatively small number of models and controllers. The third step consists of designing a Multiple Models, Switching and Tuning (MMST) strategy for estimating the current operating regime (damage case) of the aircraft, and switching to the corresponding controller to achieve effective damage accommodation and the desired performance. In the paper present a comprehensive approach to damage accommodation using Model Set Design,MMST, and Variable Structure compensation for coupling nonlinearities. The approach was evaluated on a model of F/A-18 aircraft dynamics under control effector damage, augmented by nonlinear cross-coupling terms and a structural dynamics model. The proposed approach achieved excellent performance under severe damage effects.

Boskovic, Jovan D.↗
NASA NTRS2004

An Integrated Fuselage-Sting Balance for a Sonic-Boom Wind-Tunnel Model

Measured and predicted pressure signatures from a lifting wind-tunnel model can be compared when the lift on the model is accurately known. The model's lift can be set by bending the support sting to a desired angle of attack. This method is simple in practice, but difficult to accurately apply. A second method is to build a normal force/pitching moment balance into the aft end of the sting, and use an angle-of-attack mechanism to set model attitude. In this report, a method for designing a sting/balance into the aft fuselage/sting of a sonic-boom model is described. A computer code is given, and a sample sting design is outlined to demonstrate the method.

Mack, Robert J.↗
NASA NTRS2006

Can MODIS Data Calibrate and Validate Coastal Sediment Transport Models? Rapid Prototyping Using 250 m Data and the ECOMSED Model for Lake Pontchartrain, LA USA

Field measurements from small boats and sparse arrays of instrumented buoys often do not provide sufficient data to capture the dynamic nature of biogeophysical parameters in may coastal aquatic environments. Several investigators have shown the MODIS 250 m images can provide daily synoptic views of suspended sediment concentration in coastal waters to determine sediment transport and fate. However, the use of MODIS for coastal environments can be limited due to a lack of cloud-free images. Sediment transport models are not constrained by sky conditions but often suffer from a lack of in situ observations for model calibration or validation. We demonstrate here the utility of MODIS 250 m to calibrate (set model parameters), validate output, and set or reset initial conditions of a hydrodynamic and sediment transport model (ECOMSED) developed for Lake Pontchartrain, LA USA. We present our approach in the context of how to quickly assess of 'prototype' an application of NASA data to support environmental managers and decision makers. The combination of daily MODIS imagery and model simulations offer a more robust monitoring and prediction system of suspended sediments than available from either system alone.

Miller, Richard L.↗
DOE OSTI2026

Machine learning of factors for improving oyster hatchery production

Oyster aquaculture and restoration in the Chesapeake Bay are vital, yet hatcheries frequently struggle with inconsistent larval growth and sudden mass mortality events. Unpredictable disruptions in larval production cause large economic losses, represent a perceived risk to growers, and impede industry expansion. To better understand associations between production yield and its potential predictors, we applied machine learning (random forest, and neural network) and statistical (generalized additive model) models to a comprehensive dataset of environmental, water quality, and operational parameters from a Maryland oyster hatchery, aiming to identify key yield predictors and develop a robust forecasting tool. We used recursive Boruta algorithm for variable selection, pinpointing critical predictors, and employed cross-validation to fine-tune model settings. Shapley value analysis offered crucial insights into model interpretations, highlighting week number, Normalized Difference Vegetation Index, salinity, turbidity, and fecundity as primary drivers of yield variability. For low-yield cases, salinity-related variables were particularly important. Our findings provide an early warning system for potential production downturns, empowering hatchery operators to make data-driven decisions for optimizing water conditions, feeding schedules, and broodstock management. By boosting predictability and efficiency, this research directly supports economic stability of the oyster industry and ecological health of the Chesapeake Bay.

Vishwakarma, Srishti [Oak Ridge National Laborator↗
NASA NTRS2011

2008 GEM Modeling Challenge: Metrics Study of the Dst Index in Physics-Based Magnetosphere and Ring Current Models and in Statistical and Analytic Specifications

In this paper the metrics-based results of the Dst part of the 2008-2009 GEM Metrics Challenge are reported. The Metrics Challenge asked modelers to submit results for 4 geomagnetic storm events and 5 different types of observations that can be modeled by statistical or climatological or physics-based (e.g. MHD) models of the magnetosphere-ionosphere system. We present the results of over 25 model settings that were run at the Community Coordinated Modeling Center (CCMC) and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations we use comparisons of one-hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of one-minute model data with the one-minute Dst index calculated by the United States Geologic Survey (USGS).

Rastaetter, L.↗
NASA NTRSDate not supplied

Earth Entry System Atmosphere Model Study

The Mars Sample Return Campaign has the ambitious goal of returning Mars samples back to Earth [1]. The Earth Entry System (EES), containing the samples, conducts entry, descent, and landing (EDL) on a direct Earth trajectory. During EDL, the EES traverses through many regions of Earth’s atmosphere before impacting the ground at Utah Test and Training Range (UTTR). This poster highlights preliminary results from a study that assessed the flight mechanics simulation sensitivity to atmosphere model settings and investigated the validity of current atmosphere models as compared to available atmospheric data measurements.

Rohan Deshmukh↗
NASA NTRS1979

Performability modeling with continuous accomplishment sets

A general modeling framework that permits the definition, formulation, and evaluation of performability is described. It is shown that performability relates directly to system effectiveness, and is a proper generalization of both performance and reliability. A hierarchical modeling scheme is used to formulate the capability function used to evaluate performability. The case in which performance variables take values in a continuous accomplishment set is treated explicitly.

Meyer, J. F.↗
NASA NTRS2009

The 2nd Generation Real Time Mission Monitor (RTMM) Development

The NASA Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decisionmaking for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery and orbit data, radar and other surface observations (e.g., lightning location network data), airborne navigation and instrument data sets, model output parameters, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. In order to improve the usefulness and efficiency of the RTMM system, capabilities are being developed to allow the end-user to easily configure RTMM applications based on their mission-specific requirements and objectives. This second generation RTMM is being redesigned to take advantage of the Google plug-in capabilities to run multiple applications in a web browser rather than the original single application Google Earth approach. Currently RTMM employs a limited Service Oriented Architecture approach to enable discovery of mission specific resources. We are expanding the RTMM architecture such that it will more effectively utilize the Open Geospatial Consortium Sensor Web Enablement services and other new technology software tools and components. These modifications and extensions will result in a robust, versatile RTMM system that will greatly increase flexibility of the user to choose which science data sets and support applications to view and/or use. The improvements brought about by RTMM 2nd generation system will provide mission planners and airborne scientists with enhanced decision-making tools and capabilities to more efficiently plan, prepare and execute missions, as well as to playback and review past mission data. To paraphrase the old television commercial RTMM doesn t make the airborne science, it makes the airborne science easier.

Blakeslee, Richard↗
NASA NTRS2020

Clouds and Convective Self-Aggregation in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective56equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climatecsensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique amongst intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than un-aggregated simulations. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The dataset of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We don’t find a conclusive result for how cloud clustering changes as the climate warms.

Allison A. Wing↗
DOE OSTI2025

Virtual Engineering: Python framework for engineering process design

Virtual Engineering (VE) is a Python software framework designed to accelerate the research and development of engineering processes that are fundamentally defined by multiple unit operations executed in series. VE supports a wide variety of different multi-physics models and integrates them to simulate a complete end-to-end process. To automate the execution of this model sequence, VE provides (i) a robust method to communicate between models, (ii) a high-level, user-friendly interface to set model parameters and enable optimization, and (iii) an overall model-agnostic approach that allows new computational units to be swapped in and out of workflows. Although the VE framework was developed to support the biochemical conversion of biomass to fuel, we have designed each component to easily accommodate new domains and unit models.

09 BIOMASS FUELS↗
NASA NTRS2011

Evaluating the Impact of AIRS Observations on Regional Forecasts at the SPoRT Center

NASA Short-term Prediction Research and Transition (SPoRT) Center collaborates with operational partners of different sizes and operational goals to improve forecasts using targeted projects and data sets. Modeling and DA activities focus on demonstrating utility of NASA data sets and capabilities within operational systems. SPoRT has successfully assimilated the Atmospheric Infrared Sounder (AIRS) radiance and profile data. A collaborative project is underway with the Joint Center for Satellite Data Assimilation (JCSDA) to use AIRS profiles to better understand the impact of AIRS radiances assimilated within Gridpoint Statistical Interpolation (GSI) in hopes of engaging the operational DA community in a reassessment of assimilation methodologies to more effectively assimilate hyperspectral radiances.

Zavodsky, Bradley↗
NASA NTRS1991

A Variational Assimilation Method for Satellite and Conventional Data: Model 2 (version 1)

The Model II variational data assimilation model is the second of the four variational models designed to blend diverse meteorological data into a dynamically constrained data set. Model II differs from Model I in that it includes the thermodynamic equation as the fifth dynamical constraint. Thus, Model II includes all five of the primative equations that govern atmospheric flow for a dry atmosphere.

Achtemeier, Gary L.↗
NASA NTRS1988

Fault diagnosis in sparse multiprocessor systems

The problem of fault diagnosis in multiprocessor systems is considered under a uniformly probabilistic model in which processors are faulty with probability p. This work focuses on minimizing the number of tests that must be conducted in order to correctly diagnose the state of every processor in the system with high probability. A diagnosis algorithm that can correctly diagnose the state of every processor with probability approaching one in a class of systems performing slightly greater than a linear number of tests is presented. A nearly matching lower bound on the number of tests required to achieve correct diagnosis in arbitrary systems is also proven. The number of tests required under this probabilistic model is shown to be significantly less than under a bounded-size fault set model. Because the number of tests that must be conducted is a measure of the diagnosis overhead, these results represent a dramatic improvement in the performance of system-level diagnosis technique.

Blough, Douglas M.↗
NASA NTRS1989

Efficient diagnosis of multiprocessor systems under probabilistic models

The problem of fault diagnosis in multiprocessor systems is considered under a probabilistic fault model. The focus is on minimizing the number of tests that must be conducted in order to correctly diagnose the state of every processor in the system with high probability. A diagnosis algorithm that can correctly diagnose the state of every processor with probability approaching one in a class of systems performing slightly greater than a linear number of tests is presented. A nearly matching lower bound on the number of tests required to achieve correct diagnosis in arbitrary systems is also proven. Lower and upper bounds on the number of tests required for regular systems are also presented. A class of regular systems which includes hypercubes is shown to be correctly diagnosable with high probability. In all cases, the number of tests required under this probabilistic model is shown to be significantly less than under a bounded-size fault set model. Because the number of tests that must be conducted is a measure of the diagnosis overhead, these results represent a dramatic improvement in the performance of system-level diagnosis techniques.

Blough, Douglas M.↗