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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 NTRS1980

Flexible body stability analysis of Space Shuttle ascent flight control system by using lambda matrix solution techniques

A lambda matrix solution technique is being developed to perform an open loop frequency analysis of a high order dynamic system. The procedure evaluates the right and left latent vectors corresponding to the respective latent roots. The latent vectors are used to evaluate the partial fraction expansion formulation required to compute the flexible body open loop feedback gains for the Space Shuttle Digital Ascent Flight Control System. The algorithm is in the final stages of development and will be used to insure that the feedback gains meet the design specification.

Bown, R. L.↗

NASA NTRS2015

Terminal Sequencing and Spacing (TSS)

The Federal Aviation Administration's (FAA) Next Generation Air Transportation System (or NextGen) is being designed to support the predicted increases in traffic volume and to increase the capacity, efficiency and safety of the National Airspace System (NAS). The Federal Aviation Administration (FAA) identifies Performance-Based Navigation (PBN) as a key enabling capability of NextGen and is actively publishing PBN procedures at major airports throughout the United States. Standard Terminal Arrival Routes (STARs), procedures, and approaches are designed to facilitate fuel-efficient continuous descent operations. However, their use is limited during periods of high traffic demand due to the complexity of merging multiple streams of aircraft to the same airport. As a result, most arrivals in the Terminal Radar Approach Control (TRACON) area continue to be controlled using radar vectoring and step-down descents, resulting in high workload for controllers and diverting aircraft from efficient PBN trajectories. To address this issue, NASA developed the Terminal Sequencing and Spacing (TSS) system, an advanced arrival management technology that combines time-based scheduling and controller-based precision spacing tools. TSS is a ground-based controller automation tool that facilitates sequencing and merging arrivals on Performance-Based Navigation (PBN) routes, especially during highly congested demand periods. The two main components of TSS are: 1) a scheduler that de-conflicts merging arrivals in the terminal area by computing appropriate arrival times to the runway threshold and upstream terminal merge points, and 2) a set of Controller-Managed Spacing (CMS) decision support tools to efficiently assist schedule conformance. Sixteen high-fidelity human-in-the-loop simulations involving more than five hundred hours of evaluation time, were conducted to mature TSS from proof-of-concept design to a fully functional prototype. Results indicate high controller use and acceptability of the CMS tools as well as improved PBN route conformance (Figure 2). The TSS technology was transferred to the FAA in 2014, and it is targeted for deployment to several busy airports in the U.S. starting in 2018. Potential enhancements to TSS using DataComm will also be presented.

controller-managed spacing↗

NASA NTRS2016

Optical Error Budgeting Using Linearized Ray-Trace Models

The Root-Sum-Squared, or “RSS” wavefront error model is a simple, scalar tool, commonly used for space telescope error budgeting. At the same time, much more detailed models, combining ray-trace and Fourier optics with optical alignments and wavefront controls, can provide accurate, high -resolution simulations for detailed system and subsystem design. This paper makes a connection between the two modeling approaches by deriving RSS model coefficients from ray-trace models, including the effects of wavefront controls, for computing system performance from component error statistics. It is shown that, properly constructed, the simple RSS error budget is a covariance analysis, and can be as accurate as high-resolution wavefront models for statistical wavefront error prediction. A notional segmented-aperture space telescope is used to illustrate this error modeling process.

Wavefront error↗

NASA NTRS2002

Incompressible Navier-Stokes Solvers in Primative Variables and their Applications to Steady and Unsteady Flow Simulations

This paper reviews recent progress made in incompressible Navier-Stokes simulation procedures and their application to problems of engineering interest. Discussions are focused on the methods designed for complex geometry applications in three dimensions, and thus are limited to primitive variable formulation. A summary of efforts in flow solver development is given followed by numerical studies of a few example problems of current interest. Both steady and unsteady solution algorithms and their salient features are discussed. Solvers discussed here are based on a structured-grid approach using either a finite -difference or a finite-volume frame work. As a grand-challenge application of these solvers, an unsteady turbopump flow simulation procedure has been developed which utilizes high performance computing platforms. In the paper, the progress toward the complete simulation capability of the turbo-pump for a liquid rocket engine is reported. The Space Shuttle Main Engine (SSME) turbo-pump is used as a test case for evaluation of two parallel computing algorithms that have been implemented in the INS3D code. The relative motion of the grid systems for the rotorstator interaction was obtained using overact grid techniques. Unsteady computations for the SSME turbo-pump, which contains 114 zones with 34.5 million grid points, are carried out on SCSI Origin 3000 systems at NASA Ames Research Center. The same procedure has been extended to the development of NASA-DeBakey Ventricular Assist Device (VAD) that is based on an axial blood pump. Computational, and clinical analysis of this device are presented.

Kiris, Cetin C.↗

NASA NTRSDate not supplied

Thermal Protection Materials and Systems at NASA Ames Research Center

Thermal Protection Systems (TPS) are critical for enabling NASA missions involving high-speed atmospheric flight where the entries usually include descending into the atmosphere followed by a trajectory that aims to burn off energy and result in a controlled landing. NASA Ames focuses on qualifying and certifying TPS for current missions, sustaining TPS for future missions, and developing new TPS for upcoming missions where a heritage solution is not viable. More recently there is also a focus on advancing and transferring technologies that can benefit both commercial and government space needs. Developing mature thermal protection systems is a lengthy process involving advanced tools, extensive research, and testing. Design and analysis tools are used to predict aerothermal environments, aid the design of test and flight hardware, and support the testing for the thermal/mechanical response of thermal protection systems. More recently, advances in computational methods help reduce the time and cost of technological advances, aid in optimized material architecture design, and improve material properties and performance. While high-enthalpy testing that simulates the conditions of space flight remains essential for the evaluation and development of TPS materials, computational tools are already showing promise in reducing the need for widespread testing and can help fast-track the design cycle. With the exploration of new destinations EDL instrumentation remains an important element of the heatshield and NASA Ames and partners have developed and delivered instrumentation flight hardware in support of recent Mars missions (MSL and M2020) as well as Artemis Orion. Sensors installed on the heatshield and backshell of spacecraft provide coveted information about the aerodynamic and aerothermal environment during entry. Over the years NASA Ames has brought several reusable and ablative TPS materials to a level of readiness to hand off to missions and the branch continues to serve as a TPS steward for the agency. This presentation will cover current developments in the above areas that have enabled recent missions, and look to future TPS needs for missions such as Ice Giants.

thermal protection materials↗

NASA NTRS1998

First- and Second-Order Sensitivity Analysis of a P-Version Finite Element Equation Via Automatic Differentiation

Sensitivity analysis is a technique for determining derivatives of system responses with respect to design parameters. Among many methods available for sensitivity analysis, automatic differentiation has been proven through many applications in fluid dynamics and structural mechanics to be an accurate and easy method for obtaining derivatives. Nevertheless, the method can be computational expensive and can require a high memory space. This project will apply an automatic differentiation tool, ADIFOR, to a p-version finite element code to obtain first- and second- order then-nal derivatives, respectively. The focus of the study is on the implementation process and the performance of the ADIFOR-enhanced codes for sensitivity analysis in terms of memory requirement, computational efficiency, and accuracy.

Hou, Gene↗

NASA NTRS1998

High End Computer Network Testbedding at NASA Goddard Space Flight Center

The Earth & Space Data Computing (ESDC) Division, at the Goddard Space Flight Center, is involved in development and demonstrating various high end computer networking capabilities. The ESDC has several high end super computers. These are used to run: (1) computer simulation of the climate systems; (2) to support the Earth and Space Sciences (ESS) project; (3) to support the Grand Challenge (GC) Science, which is aimed at understanding the turbulent convection and dynamos in stars. GC research occurs in many sites throughout the country, and this research is enabled by, in part, the multiple high performance network interconnections. The application drivers for High End Computer Networking use distributed supercomputing to support virtual reality applications, such as TerraVision, (i.e., three dimensional browser of remotely accessed data), and Cave Automatic Virtual Environments (CAVE). Workstations can access and display data from multiple CAVE's with video servers, which allows for group/project collaborations using a combination of video, data, voice and shared white boarding. The ESDC is also developing and demonstrating the high degree of interoperability between satellite and terrestrial-based networks. To this end, the ESDC is conducting research and evaluations of new computer networking protocols and related technologies which improve the interoperability of satellite and terrestrial networks. The ESDC is also involved in the Security Proof of Concept Keystone (SPOCK) program sponsored by National Security Agency (NSA). The SPOCK activity provides a forum for government users and security technology providers to share information on security requirements, emerging technologies and new product developments. Also, the ESDC is involved in the Trans-Pacific Digital Library Experiment, which aims to demonstrate and evaluate the use of high performance satellite communications and advanced data communications protocols to enable interactive digital library data access between the U. S. Library of Congress, the National Library of Japan and other digital library sites at 155 MegaBytes Per Second. The ESDC participation in this program is the Trans-Pacific access to GLOBE visualizations in real time. ESDC is participating in the Department of Defense's ATDNet with Multiwavelength Optical Network (MONET) a fully switched Wavelength Division Networking testbed. This presentation is in viewgraph format.

Gary, James Patrick↗

NASA NTRS1988

Ice/frost/debris assessment for space shuttle mission STS-26R

An Ice/Frost/Debris Assessment was conducted for Space Shuttle Mission STS-26R. Debris inspections of the flight elements and launch pad are performed before and after launch. Ice/Frost conditions are assessed by use of computer programs, nomographs, and infrared scanner data during cryogenic loading of the vehicle followed by an on-pad visual inspection. High speed photography is viewed after launch to identify ice/debris sources and evaluate potential vehicle damage. The Ice/Frost/Debris conditions of Mission 26R and their effect on the Space Shuttle Program is documented.

Stevenson, Charles G.↗

NASA NTRS1988

Fault tolerant system performance modeling

With the proliferation of complex digital systems on aircraft, the need to accurately predict system performance early in the system design cycle becomes imperative. In the past, system designers have relied on ad hoc methods for evaluating performance issues. This has produced systems that have not always worked as originally intended. To alleviate these design deficiencies, formal methods, with supporting tools, must be adhered to during the system design process. The use of performance modeling tools is becoming widely accepted as a way to address timing considerations of system design. An additional incentive for the use of these tools is that they allow the system architect to analyze system component interactions (i.e., bus contention, contention of functions for a processing site, and system repair activity on application performance). This inherent flexibility can result in an explicit specification of the system architecture. This paper addresses a method that supports performance modeling of fault tolerant systems using a discrete event simulation tool. An additional focus is on lessons learned from analyzing these classes of problems. The methodology and supporting work provide system architects with the capability to specify candidate architectures and accurately predict their performance in the early stages of design, where changes to system design is most cost effective. The work has been supported under NASA contract NAS1-18099. Integrated Airframe Propulsion Control System Architecture (IAPSA II). This contract addresses methodology, analysis, and detailed design of integrated control system architectures suitable for high-performance aircraft of the 1990's.

Discrete event simulation↗

NASA NTRS2021

Benchmarking Planning Applications on the Qualcomm Snapdragon

We benchmark several space planning/scheduling applications on the Qualcomm Snapdragon 855 Handheld Development Kit (HDK), a high performance embedded processor used in many mobile phones.We are flying 2 Snapdragon HDKs onboard the International Space Station (ISS) where they are hosted by the the Spaceborne Computer-2 by Hewlett Packard Enterprise linked by USB and 12V power delivery. We run computational benchmarks using three planner/ schedulers that are used for several space missions: Multi- Mission Executive (MEXEC), Compressed Large-scale Activity Scheduling and Planning (CLASP), and M2020 Ground Scheduler (Surrogate). We compare the Snapdragon performance to a performance baseline on Linux workstations. In addition, we are currently working on benchmarking the same applications on other space flight processors, such as the LEON4 Processor on the Sabertooth card, the LEON3 Processor on the Sphinx card, and the RAD750 processor.

Chien, Steve↗

NASA NTRSDate not supplied

Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development

Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.

Adrienne Hoarfrost↗

NASA NTRS2012

Comparison of Computed and Measured Performance of a Pulsed Inductive Thruster Operating on Argon Propellant

Pulsed inductive plasma accelerators are electrodeless space propulsion devices where a capacitor is charged to an initial voltage and then discharged through a coil as a high-current pulse that inductively couples energy into the propellant. The field produced by this pulse ionizes the propellant, producing a plasma near the face of the coil. Once a plasma is formed if can be accelerated and expelled at a high exhaust velocity by the Lorentz force arising from the interaction of an induced plasma current and the magnetic field. A recent review of the developmental history of planar-geometry pulsed inductive thrusters, where the coil take the shape of a flat spiral, can be found in Ref. [1]. Two concepts that have employed this geometry are the Pulsed Inductive Thruster (PIT)[2, 3] and the Faraday Accelerator with Radio-frequency Assisted Discharge (FARAD)[4]. There exists a 1-D pulsed inductive acceleration model that employs a set of circuit equations coupled to a one-dimensional momentum equation. The model was originally developed and used by Lovberg and Dailey[2, 3] and has since been nondimensionalized and used by Polzin et al.[5, 6] to define a set of scaling parameters and gain general insight into their effect on thruster performance. The circuit presented in Fig. 1 provides a description of the electrical coupling between the current flowing in the thruster I1 and the plasma current I2. Recently, the model was upgraded to include an equation governing the deposition of energy into various modes present in a pulsed inductive thruster system (acceleration, magnetic flux generation, resistive heating, etc.)[7]. An MHD description of the plasma energy density evolution was tailored to the thruster geometry by assuming only one-dimensional motion and averaging the plasma properties over the spatial dimensions of the current sheet to obtain an equation for the time-evolution of the total energy. The equation set governing the dynamics of the coupled electrodynamic-current sheet system is composed of first-order, coupled ordinary differential equations that can be easily solved numerically without having to resort to much more complex 2-D finite element plasma simulations.

Polzin, Kurt A.↗

NASA NTRS2005

Cold Flow Plume Entrainment Test Final Report NTF Test Number 2456

As part of the Space Shuttle Return to Flight (RTF) program, Marshall Space Flight Center (MSFC) performed computational fluid dynamics (CFD) analysis to define the velocity flowfields around the Shuttle stack at liftoff. These CFD predicted velocity flowfields were used in debris transport analysis (DTA). High speed flows such as plumes induce or 'entrain' mass from the surrounding environment. Previous work had shown that CFD analysis over-predicts plume induced flows. Therefore, the DTA would tend to 1) predict more debris impacts, and 2) the debris velocity (and kinetic energy) of those impacts would be too high. At a November, 2004 peer-review it was recommended that the Liftoff DTA team quantify the uncertainty in the DTA caused by the CFD's over prediction of plume induced flow. To do so, the Liftoff DTA team needed benchmark quality data for plume induced flow to quantify the CFD accuracy and its effect on the DTA. MSFC's Nozzle Test Facility (NTF) conducted the "Nozzle Induced Flows test, P#2456" to obtain experimental data for plume induced flows for nozzle flow exhausting into q quiescent freestream. Planning for the test began in December, 2004 and the experimental data was obtained in February and March of 2005. The funding for this test was provided by MSFC's Space Shuttle Propulsion Systems Integration and Engineering office.

Ruf, Joseph H.↗

NASA NTRS1989

Ice/frost/debris assessment for space shuttle mission STS-27R, December 2, 1988

An Ice/Frost/Debris assessment was conducted for Space Shuttle Mission STS-27R. Debris inspections of the flight elements and launch pad are performed before and after launch. Ice/frost conditions are assessed by the use of computer programs, nomographs, and infrared scanner data during cryogenic loading of the vehicle followed by an on-pad visual inspection. High speed photography is viewed after launch to identify ice/debris sources and evaluate potential vehicle damage. The Ice/Frost/Debris conditions of Mission STS-27R and their effect on the Space Shuttle Program are documented.

Katnik, Gregory N.↗

NASA NTRS2014

An Experimental and Computational Study on Soot Formation in a Coflow Jet Flame Under Microgravity and Normal Gravity

Upon the completion of the Structure and Liftoff in Combustion Experiment (SLICE) in March 2012, a comprehensive and unique set of microgravity coflow diffusion flame data was obtained. This data covers a range of conditions from weak flames near extinction to strong, highly sooting flames, and enabled the study of gravitational effects on phenomena such as liftoff, blowout and soot formation. The microgravity experiment was carried out in the Microgravity Science Glovebox (MSG) on board the International Space Station (ISS), while the normal gravity experiment was performed at Yale utilizing a copy of the flight hardware. Computational simulations of microgravity and normal gravity flames were also carried out to facilitate understanding of the experimental observations. This paper focuses on the different sooting behaviors of CH4 coflow jet flames in microgravity and normal gravity. The unique set of data serves as an excellent test case for developing more accurate computational models.Experimentally, the flame shape and size, lift-off height, and soot temperature were determined from line-of-sight flame emission images taken with a color digital camera. Soot volume fraction was determined by performing an absolute light calibration using the incandescence from a flame-heated thermocouple. Computationally, the MC-Smooth vorticity-velocity formulation was employed to describe the chemically reacting flow, and the soot evolution was modeled by the sectional aerosol equations. The governing equations and boundary conditions were discretized on an axisymmetric computational domain by finite differences, and the resulting system of fully coupled, highly nonlinear equations was solved by a damped, modified Newtons method. The microgravity sooting flames were found to have lower soot temperatures and higher volume fraction than their normal gravity counterparts. The soot distribution tends to shift from the centerline of the flame to the wings from normal gravity to microgravity.

microgravity↗

NASA NTRS1989

Transportable telemetry workstation for future distributed system environments

A Transportable Telemetry Workstation (TTW) has been developed to meet the need for reduction in size and cost per station while maintaining high performance specifications in distributed system environments. The TTW consists primarily of the adaptation of NASA's Goddard Space Flight Center VLSI components and system architecture to a personal computer and its architecture. The overall system, the architecture, the TTW Controller Card, TTW Synchronizer Card, custom backplane bus, and system software structure are described.

Collins, Aaron↗

NASA NTRS1989

Advanced high area ratio nozzles

The objective is to develop computational techniques for the design of high-area-ratio nozzles and to validate these models by comparison with experiments and computations using other codes. Performance computations were added to the PARC2D code and the performance of the space shuttle main engine (SSME) nozzle was computed for inviscid, laminar and turbulent flow assuming a perfect gas with gamma = 1.2. The PARC2D code was modified in a non-CASP (Center for Advanced Space Propulsion) project to compute equilibrium flow about hypersonic blunt bodies. Progress has been made toward modifying this code to compute equilibrium H2/O2 flow through the SSME and related nozzles.

Raiszadeh, Farhad↗

NASA NTRS2017

Classification of Wildfires from MODIS Data Using Neural Networks

Wildfires are destructive to both life and property, which necessitates an approach to quickly and autonomously detect these events from orbital observatories. This talk will introduce a neural network based approach for classifying wildfires in MODIS multispectral data, and will show how it could be applied to a constellation of low-cost CubeSats. The approach combines training a deep neural network on the ground using high performance consumer GPUs, with a highly optimized inference system running on a flight-proven embedded processor. Normally neural networks execute on hardware orders of magnitude more powerful than anything found in a space-based computer, therefore the inference system is designed to be performance even on the most modest of platforms. This implementation is able to be significantly more accurate than previous neural network implementations, while also approaching the accuracy of the state-of-the-art MODFIRE data products.

Artificial Intelligence↗