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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Dual-Doppler lidar measurement of winds in the JAWS experiment

The use of coherent Doppler lidar measurements for analysis of wind fields near airports was investigated during the Joint Airport Weather Studies (JAWS) project of NASA and NOAA. Periodic lidar scans were made with two 10.6-micron CO2-pulsed Doppler lidars spaced 15 km apart in order to calculate the Cartesian wind fields near Marshall Space Flight Center (MSFC). Analyses were also carried out for the flow behind gust fronts, with the desired flow fields corresponding both to surface winds measured by a Portable Automated Mesonet (PAM), and numerical models of Great Plains thunderstorm outflows. Comparison of low elevation scans carried out using the lidar instruments and a CP-4 Doppler radar showed distinct differences due to a bias toward weaker velocities in the radar measurements. The rms difference between the radar and the lidar measurements was 3.1 m/s. The experimental results were consistent with those of a previous study comparing Wave Propagation Laboratory (WPL) lidar with the CP-3 5.5-cm radar operated by the National Center for Atmospheric Research (NCAR).

Rothermel, J.↗
NASA NTRS1989

Piloted simulation of a ground-based time-control concept for air traffic control

A joint simulation was carried out using a piloted simulator and an advanced-concept air traffic control simulation to study the acceptability and accuracy of the ground-based four-dimensional descent advisor (DA), an automation aid based on accurate models of aircraft performance and weather conditions. In the piloted simulation, airline crews executed controller-issued descent advisories along standard curved-path arrival routes and were able to achieve an arrival-time precision of plus or minus 20 s at the metering fix. An analysis of errors generated in turns resulted in a further enhancement of the DA algorithm.

Davis, Thomas J.↗
NASA NTRS1991

NASA/ASEE Summer Faculty Fellowship Program. 1991 Research Reports

Reports from the NASA/ASEE Summer Faculty Fellowship Program are presented. The editors are responsible for selecting appropriately qualified faculty to address some of the many problems of current interest to NASA Kennedy. Some representative titles are as follows: Development of an Accelerated Test Method for the Determination of Susceptibility to Atmospheric Corrosion; Hazardous Gas Leak Analysis in the Space Shuttle; Modeling and Control of the Automated Radiator Inspection Device; Study of the Finite Element Software Packages at KSC; Multispectral Image Processing for Plants; Algorithms for Contours Depicting Static Electric Fields during Adverse Weather Conditions; Transient Study of a Cryogenic Hydrogen Filling System; and Precision Cleaning Verification of Nonvolatile Residues by using Water, Ultrasonics, and Turbidity Analyses.

Hosler, E. Ramon↗
NASA NTRS1994

Cost and schedule analytical techniques development

This contract provided technical services and products to the Marshall Space Flight Center's Engineering Cost Office (PP03) and the Program Plans and Requirements Office (PP02) for the period of 3 Aug. 1991 - 30 Nov. 1994. Accomplishments summarized cover the REDSTAR data base, NASCOM hard copy data base, NASCOM automated data base, NASCOM cost model, complexity generators, program planning, schedules, NASA computer connectivity, other analytical techniques, and special project support.

Source record↗
NASA NTRS1996

Meshing of a Spiral Bevel Gearset with 3D Finite Element Analysis

Recent advances in spiral bevel gear geometry and finite element technology make it practical to conduct a structural analysis and analytically roll the gearset through mesh. With the advent of user specific programming linked to 3D solid modelers and mesh generators, model generation has become greatly automated. Contact algorithms available in general purpose finite element codes eliminate the need for the use and alignment of gap elements. Once the gearset is placed in mesh, user subroutines attached to the FE code easily roll the gearset through mesh. The method is described in detail. Preliminary results for a gearset segment showing the progression of the contact lineload is given as the gears roll through mesh.

Bibel, George D.↗
NASA NTRS2002

Design and Stress Analysis of Low-Noise Adjusted Bearing Contact Spiral Bevel Gears

An integrated computerized approach for design and stress analysis of low-noise spiral bevel gear drives with adjusted bearing contact has been developed. The computation procedure is an iterative process, requiring four separate steps that provide: (a) a parabolic function of transmission errors that is able to reduce the effect of errors of alignment, and (b) reduction of the shift of bearing contact caused by misalignment. Application of finite element analysis permits the contact and bending stresses to be determined and investigate the formation of the bearing contact. The design of finite element models and boundary conditions is automated and does not require an intermediate CAD computer program. A commercially available finite element analysis computer program with contact capability was used to conduct the stress analysis. The theory developed is illustrated with numerical examples.

Litvin, Faydor L.↗
NASA NTRS1997

Space Biosensor Systems: Implications for Technology Transfer

To meet the need for continuous, automated monitoring of animal subjects, including; humans, during space flight, NASA is developing advanced physiologic sensor and biotelemetry system technologies. The ability to continuously track basic physiological parameters, such as heart rate, blood pH, and body temperature, in untethered subjects in space is a challenging task. At NASA's Ames Research Center, where a key focus is gravitational biology research, engineers have teamed with life scientists to develop wireless sensor systems for automated physiologic monitoring of animal models as small as the rat. This technology is also being adapted, in collaboration with medical professionals, to meet human clinical monitoring needs both in space and on the ground. Thus, these advanced monitoring technologies have important dual-use functions; they meet space flight data collection requirements and constraints, while concurrently addressing a number of monitoring and data acquisition challenges on the ground in areas of clinical monitoring and biomedical research. Additional applications for these and related technologies are being sought and additional partnerships established that enhance development efforts, reduce costs and facilitate technology infusion between the public and private sectors. This paper describes technology transfer and co-development projects that have evolved out of NASA's miniaturized, implantable chemical sensor development efforts.

Hines, J. W.↗
NASA NTRS2002

Design and Stress Analysis of Low-Noise Adjusted Bearing Contact Spiral Bevel Gears

An integrated computerized approach for design and stress analysis of low-noise spiral bevel gear drives with adjusted bearing contact is proposed. The procedure of computations is an iterative process that requires four separate procedures and provide: (a) a parabolic function of transmission errors that is able to reduce the effect of errors of alignment on noise and vibration, and (b) reduction of the shift of bearing contact caused by misalignment. Application of finite element analysis enables us to determine the contact and bending stresses and investigate the formation of the bearing contact. The design of finite element models and boundary conditions is automated and does not require intermediate CAD computer programs for application of general purpose computer program for finite element analysis.

Fuentes, A.↗
NASA NTRS1991

NASA's Software Bank (General Thermal Analysis)

The COSMIC program - The General Thermal Analyzer Program - assisted Salem Automation in evaluating technology and modeling reheat furnaces to determine energy efficiency and quality.

Source record↗
NASA NTRS2005

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

MCKissick, Burnell T.↗
NASA NTRS2007

Blurring the Inputs: A Natural Language Approach to Sensitivity Analysis

To document model parameter uncertainties and to automate sensitivity analyses for numerical simulation codes, a natural-language-based method to specify tolerances has been developed. With this new method, uncertainties are expressed in a natural manner, i.e., as one would on an engineering drawing, namely, 5.25 +/- 0.01. This approach is robust and readily adapted to various application domains because it does not rely on parsing the particular structure of input file formats. Instead, tolerances of a standard format are added to existing fields within an input file. As a demonstration of the power of this simple, natural language approach, a Monte Carlo sensitivity analysis is performed for three disparate simulation codes: fluid dynamics (LAURA), radiation (HARA), and ablation (FIAT). Effort required to harness each code for sensitivity analysis was recorded to demonstrate the generality and flexibility of this new approach.

Kleb, William L.↗
NASA NTRS2011

Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems

A technique based on Evolutionary Computational Methods (ECMs) was developed that allows for the automated optimization of complex computationally modeled systems, such as autonomous systems. The primary technology, which enables the ECM to find optimal solutions in complex search spaces, derives from evolutionary algorithms such as the genetic algorithm and differential evolution. These methods are based on biological processes, particularly genetics, and define an iterative process that evolves parameter sets into an optimum. Evolutionary computation is a method that operates on a population of existing computational-based engineering models (or simulators) and competes them using biologically inspired genetic operators on large parallel cluster computers. The result is the ability to automatically find design optimizations and trades, and thereby greatly amplify the role of the system engineer.

Terrile, Richard J.↗
NASA NTRS2015

Technical Challenges and Opportunities of Centralizing Space Science Mission Operations (SSMO) at NASA Goddard Space Flight Center

The NASA Goddard Space Science Mission Operations project (SSMO) is performing a technical cost-benefit analysis for centralizing and consolidating operations of a diverse set of missions into a unified and integrated technical infrastructure. The presentation will focus on the notion of normalizing spacecraft operations processes, workflows, and tools. It will also show the processes of creating a standardized open architecture, creating common security models and implementations, interfaces, services, automations, notifications, alerts, logging, publish, subscribe and middleware capabilities. The presentation will also discuss how to leverage traditional capabilities, along with virtualization, cloud computing services, control groups and containers, and possibly Big Data concepts.

Science↗
NASA NTRS2009

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Terrile, Richard J.↗
NASA NTRS2015

Data-Driven Surface Traversability Analysis for Mars 2020 Landing Site Selection

The objective of this paper is three-fold: 1) to describe the engineering challenges in the surface mobility of the Mars 2020 Rover mission that are considered in the landing site selection processs, 2) to introduce new automated traversability analysis capabilities, and 3) to present the preliminary analysis results for top candidate landing sites. The analysis capabilities presented in this paper include automated terrain classification, automated rock detection, digital elevation model (DEM) generation, and multi-ROI (region of interest) route planning. These analysis capabilities enable to fully utilize the vast volume of high-resolution orbiter imagery, quantitatively evaluate surface mobility requirements for each candidate site, and reject subjectivity in the comparison between sites in terms of engineering considerations. The analysis results supported the discussion in the Second Landing Site Workshop held in August 2015, which resulted in selecting eight candidate sites that will be considered in the third workshop.

Ono, Masahiro↗
NASA NTRS2019

Extratropical Cyclone Clouds in the GFDL Climate Model: Diagnosing Biases and the Associated Causes

The clouds in southern hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of AM4, a model GFDL will utilize for CMIP6, the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low-levels (again by differing amounts), especially in the post-cold frontal (PCF) region, when compared to observations. Focusing on only the models, their differences in high and mid-level clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.

Catherine M Naud↗
NASA NTRSDate not supplied

AI Curation Methods for NASA Scientific Data

The NASA Open Science Data Repository (OSDR) serves as a central hub for sharing and accessing NASA's vast collection of scientific data, supporting researchers across diverse fields. To enhance the efficiency, accuracy, and accessibility of this data, we are leveraging advanced artificial intelligence (AI) techniques as part of the AI for Curation project. By integrating large language models (LLMs) into our data curation workflow, we aim to streamline the entire process—from data submission to user interaction. This initiative focuses on improving key areas, including data ingestion, curation, and user engagement with curated datasets, impacting multiple domains and a wide user base. First, we are developing tools that can automatically parse data in various formats, using LLMs to convert unstructured data into structured, standardized formats. This reduces the manual effort required for curation, allowing curators to focus on more critical scientific analyses. Additionally, AI and machine learning (ML) models are being implemented to automate data validation and verification, ensuring the highest standards of data quality and reliability. Finally, we are creating a conversational AI agent to interact with the curated scientific studies in OSDR, helping users easily navigate the repository and access relevant data. By enhancing data discoverability and accessibility, these advancements will foster new research opportunities and promote the principles of open science.

Walter Alvarado↗
NASA NTRSDate not supplied

AI-Enhanced Computational Tools for Entry Systems Modeling

To advance the understanding of complex atmospheric entry phenomena, NASA’s Entry Systems Modeling (ESM) team [1] has developed high-fidelity computational tools addressing multiscale challenges, from material microstructures to full-scale heatshield response. This abstract highlights a subset of ESM tools, focusing on AI integration to enhance workflows and predictive modeling. - PuMA [2] computes effective material properties from high-resolution micro-CT scans, supporting TPS analysis for NASA missions. - TomoSAM [3] automates 3D tomography dataset segmentation for PuMA using the Segment Anything Model, reducing manual effort and improving accuracy. - PATO [4] models porous reactive materials under extreme conditions, with advancements such as unified solvers, mechanical erosion, and TPS coatings for NASA missions. - arcjetCV [5] employs deep learning to analyze arc jet test footage, measuring recession rates, shape changes, and shock standoff distances, bridging simulations, and experiments to reveal TPS ablation behavior. - ARCHeS [6] simulates arc heater plasma flows, modeling turbulence, radiation, and electromagnetic interactions to optimize arc heater performance, validate TPS under extreme conditions, and serve as a foundation for developing digital twins of arc heater facilities. - SPARTA [7] simulates rarefied hypersonic flows and gas-surface interactions for planetary entry missions, leveraging GPU architectures for scalable and efficient aerothermal and ablation analyses. AI-driven solutions, such as deep learning segmentation, have streamlined workflows in ESM tools and still hold significant potential to further accelerate processes and enhance automation in entry systems modeling. [1] Haskins, J.B. (2023), [2] Ferguson, J.C. (2018), [3] Meurisse, J.B.E. (2018), [4] Semeraro, F. (2023), [5] Quintart, A. (2024) [6] Meurisse, J.B.E. (2022), [7] Plimpton, S.J. (2019)

Predictive Modeling↗