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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Software Released by LEWICE 2.0 Ice Accretion Software Development Project

Computational icing simulation methods are making the transition from the realm of research to commonplace use in design and certification. As such, standards of software management, design, validation, and documentation must be adjusted to accommodate the increased expectations of the user community with respect to accuracy, reliability, capability, and usability. With this in mind, in collaboration with Glenn's Engineering Design and Analysis Division, the Icing Branch of the NASA Glenn Research Center at Lewis Field began a software improvement project focused on the two-dimensional ice accretion simulation tool LEWICE. This project is serving as an introduction to the concepts of software management and is intended to serve as a pilot project for future icing simulation code development. The LEWICE 2.0 Software Development Project consisted of two major elements: software management and software validation. The software management element consisted of identifying features of well-designed and well-managed software that are appropriate for an analytical prediction tool such as LEWICE and applying them to a revised version of the code. This element included tasks such as identification of software requirements, development and implementation of coding standards, and implementation of software revision control practices. With the application of these techniques, the LEWICE ice accretion code became a more stable and reliable software product. In addition, the lessons learned about software development and maintenance can be factored into future software projects at the outset. The software validation activity was an integral part of our effort to make LEWICE a more accurate and reliable analysis tool. Because of the efforts taken to extensively validate this software, LEWICE 2.0 is more robust than previous releases and can reproduce results accurately across several computing platforms. It also differs from previous versions in the extensive quantitative comparisons of its results with a data base of ice shapes that were generated in Glenn's Icing Research Tunnel. The results of the shape comparisons were analyzed to determine the range of meteorological conditions under which LEWICE 2.0 is within the repeatability found for ice shapes obtained from experiments. These comparisons show that the average variation of LEWICE 2.0 from experimental data is 7.2 percent, whereas the overall variability of the experimental data is 2.5 percent. The LEWICE 2.0 Software Development Project resulted in the release, at the recent Icing Branch LEWICE Workshop, of a more useful and robust analysis tool than was previously available to the icing community. The lessons learned from this project will be applied to the Icing Branch s future software development efforts.

Potapczuk, Mark G.↗
NASA NTRS2002

Bandwidth Enabled Flight Operations: Examining the Possibilities

The Bandwidth Enabled Flight Operations project is a research effort at the NASA Ames Research Center to investigate the use of satellite communications to improve aviation safety and capacity. This project is a follow on to the AeroSAPIENT Project, which demonstrated methods for transmitting high bandwidth data in various configurations. For this research, we set a goal to nominally use only 10 percent of the available bandwidth demonstrated by AeroSAPIENT or projected by near-term technology advances. This paper describes the results of our research, including available satellite bandwidth, commercial and research efforts to provide these services, and some of the limiting factors inherent with this communications medium. It also describes our investigation into the needs of the stakeholders (Airlines, Pilots, Cabin Crews, ATC, Maintenance, etc). The paper also describes our development of low-cost networked flight deck and airline operations center simulations that were used to demonstrate two application areas: Providing real time weather information to the commercial flight deck, and enhanced crew monitoring and control for airline operations centers.

Pisanich, Greg↗
NASA NTRS2006

Ten Commandments of Formal Methods...Ten Years Later

More than a decade ago, in "Ten Commandments of Formal Methods," we offered practical guidelines for projects that sought to use formal methods. Over the years, the article, which was based on our knowledge of successful industrial projects, has been widely cited and has generated much positive feedback. However, despite this apparent enthusiasm, formal methods use has not greatly increased, and some of the same attitudes about the infeasibility of adopting them persist. Formal methodists believe that introducing greater rigor will improve the software development process and yield software with better structure, greater maintainability, and fewer errors.

Bowen, Jonathan P.↗
NASA NTRS1992

Transverse Mercator Projection Via Elliptic Integrals

Improved method of construction of U.S. Army's universal transverse Mercator grid system based on Gauss-Kruger transverse Mercator projection and on use of elliptic integrals of second kind. Method can be used to map entire northern or southern hemisphere with respect to single principal meridian.

Wallis, David E.↗
NASA NTRS1973

Implementation and extension of the impulse transfer function method for future application to the space shuttle project. Volume 2: Program description and user's guide

The data processing procedures and the computer programs were developed to predict structural responses using the Impulse Transfer Function (ITF) method. There are three major steps in the process: (1) analog-to-digital (A-D) conversion of the test data to produce Phase I digital tapes (2) processing of the Phase I digital tapes to extract ITF's and storing them in a permanent data bank, and (3) predicting structural responses to a set of applied loads. The analog to digital conversion is performed by a standard package which will be described later in terms of the contents of the resulting Phase I digital tape. Two separate computer programs have been developed to perform the digital processing.

Patterson, G.↗
NASA NTRS2007

Space Radiation Cancer Risks

Space radiation presents major challenges to astronauts on the International Space Station and for future missions to the Earth s moon or Mars. Methods used to project risks on Earth need to be modified because of the large uncertainties in projecting cancer risks from space radiation, and thus impact safety factors. We describe NASA s unique approach to radiation safety that applies uncertainty based criteria within the occupational health program for astronauts: The two terrestrial criteria of a point estimate of maximum acceptable level of risk and application of the principle of As Low As Reasonably Achievable (ALARA) are supplemented by a third requirement that protects against risk projection uncertainties using the upper 95% confidence level (CL) in the radiation cancer projection model. NASA s acceptable level of risk for ISS and their new lunar program have been set at the point-estimate of a 3-percent risk of exposure induced death (REID). Tissue-averaged organ dose-equivalents are combined with age at exposure and gender-dependent risk coefficients to project the cumulative occupational radiation risks incurred by astronauts. The 95% CL criteria in practice is a stronger criterion than ALARA, but not an absolute cut-off as is applied to a point projection of a 3% REID. We describe the most recent astronaut dose limits, and present a historical review of astronaut organ doses estimates from the Mercury through the current ISS program, and future projections for lunar and Mars missions. NASA s 95% CL criteria is linked to a vibrant ground based radiobiology program investigating the radiobiology of high-energy protons and heavy ions. The near-term goal of research is new knowledge leading to the reduction of uncertainties in projection models. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. The current model for projecting space radiation cancer risk relies on the three assumptions of linearity, additivity, and scaling along with the use of population averages. We describe uncertainty estimates for this model, and new experimental data that sheds light on the accuracy of the underlying assumptions. These methods make it possible to express risk management objectives in terms of quantitative metrics, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits. The resulting methodology is applied to several human space exploration mission scenarios including lunar station, deep space outpost, and a Mars mission. Factors that dominate risk projection uncertainties and application of this approach to assess candidate mitigation approaches are described.

Cucinotta, Francis A.↗
NASA NTRS2002

Space Radiation Cancer Risk Projections for Exploration Missions: Uncertainty Reduction and Mitigation

In this paper we discuss expected lifetime excess cancer risks for astronauts returning from exploration class missions. For the first time we make a quantitative assessment of uncertainties in cancer risk projections for space radiation exposures. Late effects from the high charge and energy (HZE) ions present in the galactic cosmic rays including cancer and the poorly understood risks to the central nervous system constitute the major risks. Methods used to project risk in low Earth orbit are seen as highly uncertain for projecting risks on exploration missions because of the limited radiobiology data available for estimating HZE ion risks. Cancer risk projections are described as a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Monte-Carlo sampling from subjective error distributions represents the lack of knowledge in each factor to quantify risk projection overall uncertainty. Cancer risk analysis is applied to several exploration mission scenarios. At solar minimum, the number of days in space where career risk of less than the limiting 3% excess cancer mortality can be assured at a 95% confidence level is found to be only of the order of 100 days.

Cucinotta, Francis↗
NASA NTRS2011

Gripping Mechanisms for Microgravity and Extreme Terrain and Vertical Climbing Micro Ground Vehicle

Asteroids and comets may provide insight into the origins of our solar system and the precursors to life on our planet. Near Earth objects offer an accessible target of opportunity, but are small and lack the gravity necessary for conventional wheeled travel. Therefore, it is necessary to develop alternative methods for maneuvering in these environments. This project researched and developed a method for gripping rock surfaces. Work has been completed on the design and prototyping of several possible hooked gripping mechanisms. Future work includes quantitative testing, downselection to a final design, and attachment to the robotic platform, Lemur IIb. A second project focuses on the development of a 100g, crash-proof robot capable of climbing vertical surfaces using a novel silicone adhesive. Capable of carrying video/audio payloads the robot may serve as a surveillance tool for the Department of Defense or as a method of pre-flight spacecraft inspections. A specialized track was developed to provide the specific loading conditions necessary for proper engagement of the adhesive. Both of these projects rely heavily on the shape deposition manufacturing process, being researched at JPL, and 3D printing.

robotic locomotion↗
NASA NTRS2013

Orion Exploration Flight Test-1 Contingency Drogue Deploy Velocity Trigger

As a backup to the GPS-aided Kalman filter and the Barometric altimeter, an "adjusted" velocity trigger is used during entry to trigger the chain of events that leads to drogue chute deploy for the Orion Multi-Purpose Crew Vehicle (MPCV) Exploration Flight Test-1 (EFT-1). Even though this scenario is multiple failures deep, the Orion Guidance, Navigation, and Control (GN&C) software makes use of a clever technique that was taken from the Mars Science Laboratory (MSL) program, which recently successfully landing the Curiosity rover on Mars. MSL used this technique to jettison the heat shield at the proper time during descent. Originally, Orion use the un-adjusted navigated velocity, but the removal of the Star Tracker to save costs for EFT-1, increased attitude errors which increased inertial propagation errors to the point where the un-adjusted velocity caused altitude dispersions at drogue deploy to be too large. Thus, to reduce dispersions, the velocity vector is projected onto a "reference" vector that represents the nominal "truth" vector at the desired point in the trajectory. Because the navigation errors are largely perpendicular to the truth vector, this projection significantly reduces dispersions in the velocity magnitude. This paper will detail the evolution of this trigger method for the Orion project and cover the various methods tested to determine the reference "truth" vector; and at what point in the trajectory it should be computed.

Gay, Robert S.↗
NASA NTRS1987

Cloud cover over the equatorial eastern Pacific derived from July 1983 International Satellite Cloud Climatology Project data using a hybrid bispectral threshold method

A set of visible and IR data obtained with GOES from July 17-31, 1983 is analyzed using a modified version of the hybrid bispectral threshold method developed by Minnis and Harrison (1984). This methodology can be divided into a set of procedures or optional techniques to determine the proper contaminate clear-sky temperature or IR threshold. The various optional techniques are described; the options are: standard, low-temperature limit, high-reflectance limit, low-reflectance limit, coldest pixel and thermal adjustment limit, IR-only low-cloud temperature limit, IR clear-sky limit, and IR overcast limit. Variations in the cloud parameters and the characteristics and diurnal cycles of trade cumulus and stratocumulus clouds over the eastern equatorial Pacific are examined. It is noted that the new method produces substantial changes in about one third of the cloud amount retrieval; and low cloud retrievals are affected most by the new constraints.

Minnis, Patrick↗
NASA NTRS2015

Method for Producing Launch/Landing Pads and Structures Project

Current plans for deep space exploration include building landing-launch pads capable of withstanding the rocket blast of much larger spacecraft that that of the Apollo days. The proposed concept will develop lightweight launch and landing pad materials from in-situ materials, utilizing regolith to produce controllable porous cast metallic foam brickstiles shapes. These shapes can be utilized to lay a landing launch platform, as a construction material or as more complex parts of mechanical assemblies.

Technology Portfolio System↗
NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗
NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗
NASA NTRS2016

Implementing Effective Mission Systems Engineering Practices During Early Project Formulation Phases

Developing and implementing a plan for a NASA space mission can be a complicated process. The needs, goals, and objectives of any proposed mission or technology must be assessed early in the Project Life Cycle. The key to successful development of a space mission or flight project is the inclusion of systems engineering in early project formulation, namely during Pre-phase A, Phase A, and Phase B of the NASA Project Life Cycle. When a space mission or new technology is in pre-development, or "pre-Formulation", feasibility must be determined based on cost, schedule, and risk. Inclusion of system engineering during project formulation is key because in addition to assessing feasibility, design concepts are developed and alternatives to design concepts are evaluated. Lack of systems engineering involvement early in the project formulation can result in increased risks later in the implementation and operations phases of the project. One proven method for effective systems engineering practice during the pre-Formulation Phase is the use of a mission conceptual design or technology development laboratory, such as the Mission Design Lab (MDL) at NASA's Goddard Space Flight Center (GSFC). This paper will review the engineering process practiced routinely in the MDL for successful mission or project development during the pre-Formulation Phase.

Processes↗
NASA NTRS2006

NASA EVM Overview and Case Study

The presentation gives an overview of the National Aeronautics and Space Administration (NASA) Earned Value Management (EVM) structure. We briefly talk about the current EVM high-level policies within NASA and the EVM governing structure. It touches on the roles and responsibilities of EVM Focal Points within the Agency. We will also discuss the approach that MSFC followed in implementing EVM and better data analysis within the Habitat Holding Racks (HHR) Project. We will address the approach used at the Marshall Space Flight Center (MSFC) to effectively equip and support MSFC projects in applying a sound EVM and data analysis process. In addition, we will show metrics associated with the HHR project before and after the implementation of EVM on the project. We will discuss the monthly report, using sample data, that the project manager used each month to assess the performance of the project. The data received from EVM helped create a solid method for assessing the project s performance. The use of EVM data analysis can be an effective and efficient tool in today s environment with increasing workloads and downsizing workforces. EVM provides project managers with information that can be used in the decision making process.

Kerby, Jerald G.↗
NASA NTRS1988

Summary of analytical model improvement method and related technology

The research project which resulted in the AMI (Analytical Model Improvement) method was funded by the Langley Research Center from 1979 through 1985. The objective was to develop a method for obtaining improved dynamic models of structures by using both test data and numerical analysis. The research was successfully performed and the method was applied to a real structure having a realistic NASTRAN model with over 500 degrees of freedom. The method and its application are briefly discussed as well as other indirect benefits in related technical areas.

Berman, Alex↗
NASA NTRS1986

A spectral element method for the simulation of unsteady incompressible flows with heat transfer

The spectral element method is a high-order finite element technique for solution of the Navier-Stokes and energy equations. In the isoparametric spectral element discretization, the domain is broken up into general brick elements, and the dependent and independent variables represented as high-order tensor-product Lagrangian interpolants through Chebyshev collocation points. The nonlinear and convective terms in the governing equations are treated with explicit collocation, while the pressure and diffusive contributions are handled implicitly using variational projection operators. The method is applied to flow past a cylinder, flow in grooved channels, and natural convection in an enclosure.

Karniadakis, George E.↗
NASA NTRSDate not supplied

Characterizing Spatiotemporal Uncertainty in Interpolated Meteorological Data

Interpolated meteorological data invariably contain errors. These errors have structure in time and space, particularly autocorrelation, which can cause the effects of errors to compound when model outputs are aggregated temporally or spatially. One way to account for this uncertainty is with a probabilistic model from which samples can be drawn that are coherent with respect to underlying spatial and temporal covariance structure. This work describes a probabilistic method for spatial interpolation of point-wise meteorological time series. Observational data from weather stations are generally sparse in space and dense in time (but sometimes missing). The method works by projecting time series onto orthogonal basis vectors and spatially interpolating each resulting component independently. Under suitable assumptions, and data transformations to better satisfy those assumptions, Gaussian process regression provides a complete description of the joint predictive distribution over a Gaussian random field. Spatiotemporally coherent realizations are generated as the sum of conditional (spatial) simulations of each orthogonal (temporal) component. Data-derived and generic orthogonal bases are considered. In addition to spatial interpolation, imputation of missing observational data is examined. The method is applied using near-surface air temperature over the Western United States and validated by comparing theoretical versus actual coverage of predictive distributions and analyzing the degree to which spatial and temporal covariance structure is reproduced. Computational considerations, relating to conditional simulation of random fields, are also addressed.

Conor T Doherty↗