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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Soft Real-Time PID Control on a VME Computer

microPID (uPID) is a computer program for real-time proportional + integral + derivative (PID) control of a translation stage in a Fourier-transform ultraviolet spectrometer. microPID implements a PID control loop over a position profile at sampling rate of 8 kHz (sampling period 125microseconds). The software runs in a strippeddown Linux operating system on a VersaModule Eurocard (VME) computer operating in real-time priority queue using an embedded controller, a 16-bit digital-to-analog converter (D/A) board, and a laser-positioning board (LPB). microPID consists of three main parts: (1) VME device-driver routines, (2) software that administers a custom protocol for serial communication with a control computer, and (3) a loop section that obtains the current position from an LPB-driver routine, calculates the ideal position from the profile, and calculates a new voltage command by use of an embedded PID routine all within each sampling period. The voltage command is sent to the D/A board to control the stage. microPID uses special kernel headers to obtain microsecond timing resolution. Inasmuch as microPID implements a single-threaded process and all other processes are disabled, the Linux operating system acts as a soft real-time system.

Karayan, Vahag↗
NASA NTRS1974

Capacity of noncoherent MFSK channels

Performance limits theoretically achievable over noncoherent channels perturbed by additive Gaussian noise in hard decision, optimal, and soft decision receivers are computed as functions of the number of orthogonal signals and the predetection signal-to-noise ratio. Equations are derived for orthogonal signal capacity, the ultimate MFSK capacity, and the convolutional coding and decoding limit. It is shown that performance improves as the signal-to-noise ratio increases, provided the bandwidth can be increased, that the optimum number of signals is not infinite (except for the optimal receiver), and that the optimum number decreases as the signal-to-noise ratio decreases, but is never less than 7 for even the hard decision receiver.

Bar-David, I.↗
NASA NTRS1996

Dose equivalent near the bone-soft tissue interface from nuclear fragments produced by high-energy protons

During manned space missions, high-energy nucleons of cosmic and solar origin collide with atomic nuclei of the human body and produce a broad linear energy transfer spectrum of secondary particles, called target fragments. These nuclear fragments are often more biologically harmful than the direct ionization of the incident nucleon. That these secondary particles increase tissue absorbed dose in regions adjacent to the bone-soft tissue interface was demonstrated in a previous publication. To assess radiological risks to tissue near the bone-soft tissue interface, a computer transport model for nuclear fragments produced by high energy nucleons was used in this study to calculate integral linear energy transfer spectra and dose equivalents resulting from nuclear collisions of 1-GeV protons transversing bone and red bone marrow. In terms of dose equivalent averaged over trabecular bone marrow, target fragments emitted from interactions in both tissues are predicted to be at least as important as the direct ionization of the primary protons-twice as important, if recently recommended radiation weighting factors and "worst-case" geometry are used. The use of conventional dosimetry (absorbed dose weighted by aa linear energy transfer-dependent quality factor) as an appropriate framework for predicting risk from low fluences of high-linear energy transfer target fragments is discussed.

NASA Discipline Number 45-10↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
NASA NTRS2001

Finite Element Methods for real-time Haptic Feedback of Soft-Tissue Models in Virtual Reality Simulators

We have applied the linear elastic finite element method to compute haptic force feedback and domain deformations of soft tissue models for use in virtual reality simulators. Our results show that, for virtual object models of high-resolution 3D data (>10,000 nodes), haptic real time computations (>500 Hz) are not currently possible using traditional methods. Current research efforts are focused in the following areas: 1) efficient implementation of fully adaptive multi-resolution methods and 2) multi-resolution methods with specialized basis functions to capture the singularity at the haptic interface (point loading). To achieve real time computations, we propose parallel processing of a Jacobi preconditioned conjugate gradient method applied to a reduced system of equations resulting from surface domain decomposition. This can effectively be achieved using reconfigurable computing systems such as field programmable gate arrays (FPGA), thereby providing a flexible solution that allows for new FPGA implementations as improved algorithms become available. The resulting soft tissue simulation system would meet NASA Virtual Glovebox requirements and, at the same time, provide a generalized simulation engine for any immersive environment application, such as biomedical/surgical procedures or interactive scientific applications.

Frank, Andreas O.↗
NASA NTRS1967

Spacecraft control

Spacecraft control studies on antenna pointing, capsule sterilization, propulsive lander, optical sensing for soft landing spacecraft, and gyro data reduction computer programs

SPACECRAFT CONTROL↗
NASA NTRS1984

Generating soft shadows with a depth buffer algorithm

Computer-synthesized shadows used to appear with a sharp edge when cast onto a surface. At present the production of more realistic, soft shadows is considered. However, significant costs arise in connection with such a representation. The current investigation is concerned with a pragmatic approach, which combines an existing shadowing method with a popular visible surface rendering technique, called a 'depth buffer', to generate soft shadows resulting from light sources of finite extent. The considered method represents an extension of Crow's (1977) shadow volume algorithm.

Brotman, L. S.↗
NASA NTRS2003

Reconfigurable Hardware Adapts to Changing Mission Demands

A new class of computing architectures and processing systems, which use reconfigurable hardware, is creating a revolutionary approach to implementing future spacecraft systems. With the increasing complexity of electronic components, engineers must design next-generation spacecraft systems with new technologies in both hardware and software. Derivation Systems, Inc., of Carlsbad, California, has been working through NASA s Small Business Innovation Research (SBIR) program to develop key technologies in reconfigurable computing and Intellectual Property (IP) soft cores. Founded in 1993, Derivation Systems has received several SBIR contracts from NASA s Langley Research Center and the U.S. Department of Defense Air Force Research Laboratories in support of its mission to develop hardware and software for high-assurance systems. Through these contracts, Derivation Systems began developing leading-edge technology in formal verification, embedded Java, and reconfigurable computing for its PF3100, Derivational Reasoning System (DRS ), FormalCORE IP, FormalCORE PCI/32, FormalCORE DES, and LavaCORE Configurable Java Processor, which are designed for greater flexibility and security on all space missions.

Source record↗
NASA NTRSDate not supplied

Recommended DSMC Collision Model Parameters for Planetary Entry

Hybrid simulation frameworks combining Computational Fluid Dynamics (CFD) and Direct Simulation Monte Carlo (DSMC) are frequently employed to efficiently perform high-fidelity simulations of environments consisting of both continuum and rarified flow. DSMC is a stochastic, particle-based method which solves the fundamental Boltzmann equation and is therefore necessary for high-Knudsen flow where continuum-based assumptions governing CFD break down. However, the DSMC methodology is generally computationally inefficient to model the continuum regime. In a CFD/DSMC hybrid approach, obtaining an accurate, high-fidelity solution hinges on the consistent treatment of transport properties and the thermo-chemical models employed within the two solvers. In principle, in regions where CFD and DSMC are both employed, the same gas mixture under the same conditions should have the same properties, regardless of simulation type. Observed differences should be due to non-equilibrium processes, rather than differences in physical models. The goal of this work is to provide a comprehensive DSMC transport database encompassing the vast majority of known gas species encountered during Earth or other planetary atmospheric entry. This goal is largely possible due to recently performed ab initio quantum chemistry calculations. Combined with other high-fidelity data, the planned database will consist of collision integral data for over 200 neutral and ionized species and over 20000 binary collisions. From these collision integrals, Nelder-Mead optimization is used to compute collision-specific Variable Soft Sphere (VSS) collision model parameters, fitted from 300 K to 20000 K. Initial comparisons of transport properties of relevant equilibrium gas mixtures show great agreement between CFD and DSMC-derived results. The completed database can be readily applied to model binary collisions of any gas mixture containing the included species over the specified temperature range, making it a valuable tool for future planetary probe modeling efforts. An example is shown below in Fig. 1. Equilibrium mixture transport properties for a 35-species mixture composed originally of 10% air and 90% pyrolysis species of a carbon-phenolic ablator material [4] are computed using both fitted VSS Parameters and the original CFD collision integral values. Deviations in computed properties between the two approaches are less than 5% for the entire temperature range.

M. R. Gosma↗
NASA NTRS1975

Analytical and experimental vibration studies of a 1/8-scale shuttle orbiter

Natural frequencies and mode shapes for four symmetric vibration modes and four antisymmetric modes are compared with predictions based on NASTRAN finite-element analyses. Initial predictions gave poor agreement with test data; an extensive investigation revealed that the major factors influencing agreement were out-of-plane imperfections in fuselage panels and a soft fin-fuselage connection. Computations with a more refined analysis indicated satisfactory frequency predictions for all modes studied, within 11 percent of experimental values.

Pinson, L. D.↗
NASA NTRS1976

Design criteria for noncoherent Gaussian channels with MFSK signaling and coding

This paper presents data and criteria to assess and guide the design of modems for coded noncoherent communication systems subject to practical system constraints of power, bandwidth, noise spectral density, coherence time, and number of orthogonal signals M. Three basic receiver types are analyzed for the noncoherent multifrequency-shift keying (MFSK) additive white Gaussian noise channel: hard decision, unquantized (optimum), and quantized (soft decision). Channel capacity and computational cutoff rate are computed for each type and presented as functions of the predetection signal-to-noise ratio and the number of orthogonal signals. This relates the channel constraints of power, bandwidth, coherence time, and noise power to the optimum choice of signal duration and signal number.

Butman, S. A.↗
NASA NTRS1992

Binary weight distributions of some Reed-Solomon codes

The binary weight distributions of the (7,5) and (15,9) Reed-Solomon (RS) codes and their duals are computed using the MacWilliams identities. Several mappings of symbols to bits are considered and those offering the largest binary minimum distance are found. These results are then used to compute bounds on the soft-decoding performance of these codes in the presence of additive Gaussian noise. These bounds are useful for finding large binary block codes with good performance and for verifying the performance obtained by specific soft-coding algorithms presently under development.

Pollara, F.↗
NASA NTRS1993

Static Computer Memory Integrity Testing (SCMIT): An experiment flown on STS-40 as part of GAS payload G-616

This experiment investigated the integrity of static computer memory (floppy disk media) when exposed to the environment of low earth orbit. The experiment attempted to record soft-event upsets (bit-flips) in static computer memory. Typical conditions that exist in low earth orbit that may cause soft-event upsets include: cosmic rays, low level background radiation, charged fields, static charges, and the earth's magnetic field. Over the years several spacecraft have been affected by soft-event upsets (bit-flips), and these events have caused a loss of data or affected spacecraft guidance and control. This paper describes a commercial spin-off that is being developed from the experiment.

Hancock, Thomas↗