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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 721 records · Page 40

NASA Tech Briefs, December 2007

Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions

Source record↗

Micro-Detection System for Determination of the Biotic or Abiotic Origin of Amino Acids

The research carried out under this PIDDP involves the development of a breadboard version of a spacecraft-based system for the detection of amino acid chirality (molecular handedness) on solar system bodies. Chirality provides an unambiguous way of distinguishing between abiotic and biotic origins since only one mirror-image form is used in the functional molecules of life. Recent advances in a variety of nano-fabrication technologies have resulted in concepts for enabling miniaturized chemical and biological analytical systems. These are complete application-specific systems that integrate fluid micro handling systems for extracting and reacting target molecules, micro-separation technologies for enhanced sensitivity and resolution, and advanced detection technologies. This effort makes use of a relatively new technology that shows demonstrated promise for spacecraft-based amino acid analysis: microchip-based capillary electrophoresis (μCE). The μCE system is capable of analyzing the type of amino acids present as well as the relative amounts of their mirror image forms. The system we developed will be able to chirally resolve all of the major amino acids found in extraterrestrial material (Gly, Ala, Val, Pro, Asp, Glu, a-aminoisobutyric acid, and isovaline) at sub-part-per-billion levels. The -CE analysis requires that the amino acids be extracted from the sample and derivatized for either optical or electrochemical detection. In our implementation, the amino acids are released from the sample by sublimation and prepared for μCE analysis using a microfluidic circuit. In addition, we have investigated the use of a microfluidic circuit for the release of amino acids from samples in which sublimation has proven to be problematic.

Jeffrey L Bada↗

Analysis of Process Gases and Trace Contaminants in Membrane-Aerated Gaseous Effluent Streams.

In membrane-aerated biofilm reactors (MABRs), hollow fibers are used to supply oxygen to the biofilms and bulk fluid. A pressure and concentration gradient between the inner volume of the fibers and the reactor reservoir drives oxygen mass transport across the fibers toward the bulk solution, providing the fiber-adhered biofilm with oxygen. Conversely, bacterial metabolic gases from the bulk liquid, as well as from the biofilm, move opposite to the flow of oxygen, entering the hollow fiber and out of the reactor. Metabolic gases are excellent indicators of biofilm vitality, and can aid in microbial identification. Certain gases can be indicative of system perturbations and control anomalies, or potentially unwanted biological processes occurring within the reactor. In confined environments, such as those found during spaceflight, it is important to understand what compounds are being stripped from the reactor and potentially released into the crew cabin to determine the appropriateness or the requirement for additional mitigation factors. Reactor effluent gas analysis focused on samples provided from Kennedy Space Center's sub-scale MABRs, as well as Johnson Space Center's full-scale MABRs, using infrared spectroscopy and gas chromatography techniques. Process gases, such as carbon dioxide, oxygen, nitrogen, nitrogen dioxide, and nitrous oxide, were quantified to monitor reactor operations. Solid Phase Microextraction (SPME) GC-MS analysis was used to identify trace volatile compounds. Compounds of interest were subsequently quantified. Reactor supply air was examined to establish target compound baseline concentrations. Concentration levels were compared to average ISS concentration values and/or Spacecraft Maximum Allowable Concentration (SMAC) levels where appropriate. Based on a review of to-date results, current trace contaminant control systems (TCCS) currently on board the ISS should be able to handle the added load from bioreactor systems without the need for secondary mitigation.

Gaseous Effluent Streams↗

River Dissolved Oxygen Prediction Using Machine Learning Models and Wireless Sensor Measurements

Simultaneous flooding&heat and droughts&heat events can potentially destabilize hydro-meteorological conditions to deteriorate the water quality of Neches River. Machine learning (ML) models utilizing wireless sensor measurements have been applied to predict water quality and optimize various water management strategies. This study aims to develop ML models to predict dissolved oxygen (DO) prediction under various hydro-meteorological conditions and enhance water management decision-making. Wireless sensor measurements of DO, water temperature, sample depth, conductivity, turbidity, and pH, along with discharge from the United States Geological Survey stations, are collected for model inputs at the Pine Island Bayou C749 station (PIB-C749) and Neches River Saltwater Barrier (SWB). Multilayer perceptron neural networks, recurrent neural networks, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) with and without attention mechanism (AT) are tested to determine the best model, which is applied the rolling forecast method to predict 14-day DO. Traditional and recurrent transfer learning (TL and RTL) methods are adopted to overcome insufficient data at the SWB. The input feature importance analysis using the integrated gradients (IG) algorithm is applied to determine dominant inputs. The results show LSTM-based models are capable handling long sequential data. AT-BiLSTM and RTL-LSTM demonstrate the best performance at the PIB-C749 (RMSE=0.054) and the SWB (RMSE=0.028), respectively. TL and RTL methods significantly improve model performance at the SWB. DO, temperature, and pH show higher importance, consistent with hydrodynamics and water chemistry. Both best models are applied to predict 14-day DO and demonstrate reasonable performance for decision-making. Hydro-meteorological conditions of 2017 flood and 2012 drought events are simulated and reveal that possible hypoxia occurs after flooding due to increasing temperature and turbidity, and DO concentration decreases significantly under heat and drought conditions. In conclusion, LSTM-based models utilizing wireless sensor data can be a timely and effective approach to make appropriate decisions on water resource management.

54 ENVIRONMENTAL SCIENCES↗

MapsTorch : automatic differentiation for X-ray fluorescence data analysis

X-ray fluorescence (XRF) is a popular spectroscopy technique for elemental analysis. Spectrum fitting and parameter tuning are at the core of XRF analysis and are conventionally manually intensive, especially for synchrotron experiments involving large amounts of diverse samples. This work introduces the automatic differentiation (AD) technique to XRF and an open-source package called MapsTorch. By transforming an analytical model of the XRF spectrum into a differentiable computation graph with AD, MapsTorch enables robust optimization of parameters and elemental intensities. We evaluate MapsTorch by conducting computational experiments on a large number of historical synchrotron XRF datasets and compare its performance with the currently practiced fitting tool NLopt. The results show that MapsTorch consistently achieves high-quality fits and often leads to better fitting quality than NLopt, particularly in tasks such as initial spectrum fitting and elemental intensity refinement. The robust performance of MapsTorch paves the way for developing automated and high-throughput XRF data analysis workflows to handle the increasing data volumes expected from next-generation synchrotron facilities.

X-ray fluorescence↗

Phenology satellite experiment

The author has identified the following significant results. The detection of a phenological event (the Brown Wave-vegetation sensescence) for specific forest and crop types using ERTS-1 imagery is described. Data handling techniques including computer analysis and photointerpretation procedures are explained. Computer analysis of multspectral scanner digital tapes in all bands was used to give the relative changes of spectral reflectance with time of forests and specified crops. These data were obtained for a number of the twenty-four sites located within four north-south corridors across the United States. Analysis of ground observation photography and ERTS-1 imagery for sites in the Appalachian Corridor and Mississippi Valley Corridor indicates that the recession of vegetation development can be detected very well. Tentative conclusions are that specific phenological events such as crop maturity or leaf fall can be mapped for specific sites and possible for different regions. Preliminary analysis based on a number of samples in mixed deciduous hardwood stands indicates that as senescence proceeds both the rate of change and differences in color among species can be detected. The results to data show the feasibility of the development and refinement of phenoclimatic models.

Dethier, B. E.↗

Focal plane infrared readout circuit with automatic background suppression

A circuit for reading out a signal from an infrared detector includes a current-mode background-signal subtracting circuit having a current memory which can be enabled to sample and store a dark level signal from the infrared detector during a calibration phase. The signal stored by the current memory is subtracted from a signal received from the infrared detector during an imaging phase. The circuit also includes a buffered direct injection input circuit and a differential voltage readout section. By performing most of the background signal estimation and subtraction in a current mode, a low gain can be provided by the buffered direct injection input circuit to keep the gain of the background signal relatively small, while a higher gain is provided by the differential voltage readout circuit. An array of such readout circuits can be used in an imager having an array of infrared detectors. The readout circuits can provide a high effective handling capacity.

Pain, Bedabrata↗

Syringe filtration methods for examining dissolved and colloidal trace element distributions in remote field locations

It is well-established that sampling and sample processing can easily introduce contamination into dissolved trace element samples if precautions are not taken. However, work in remote locations sometimes precludes bringing bulky clean lab equipment into the field and likewise may make timely transport of samples to the lab for processing impossible. Straightforward syringe filtration methods are described here for collecting small quantities (15 mL) of 0.45- and 0.02-microm filtered river water in an uncontaminated manner. These filtration methods take advantage of recent advances in analytical capabilities that require only small amounts of waterfor analysis of a suite of dissolved trace elements. Filter clogging and solute rejection artifacts appear to be minimal, although some adsorption of metals and organics does affect the first approximately 10 mL of water passing through the filters. Overall the methods are clean, easy to use, and provide reproducible representations of the dissolved and colloidal fractions of trace elements in river waters. Furthermore, sample processing materials can be prepared well in advance in a clean lab and transported cleanly and compactly to the field. Application of these methods is illustrated with data from remote locations in the Rocky Mountains and along the Yukon River. Evidence from field flow fractionation suggests that the 0.02-microm filters may provide a practical cutoff to distinguish metals associated with small inorganic and organic complexes from those associated with silicate and oxide colloids.

Colloids/analysis↗

Decision Making In A High-Tech World: Automation Bias and Countermeasures

Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.

Mosier, Kathleen L.↗

Probabilistic Modeling of a Three-Stage Human Landing System Architecture

Unmitigated uncertainties are known to have previously led to failed development programs; in order to combat these uncertainties, risks and their impacts must be understood and handled to ensure program success. In this paper, a probabilistic methodology to handle uncertainties is demonstrated on a three-element Human Landing System (HLS) concept, which allows tracking of current best estimates of the vehicle’s performance and assessment of its robustness against uncertainties. This methodology has two key parts: first, the creation of a dynamic architecture model of a three-element HLS concept; and second, its use with surrogate modeling and range estimating techniques to capture and propagate uncertainties. The DYnamic Rocket EQuation Tool (DYREQT), a space systems synthesis and sizing framework used by NASA, was used as to model the HLS architecture. For the probabilistic analysis, uncertainties of interest within the HLS concept were enumerated and represented as parameters within the DYREQT model as inputs for vehicle stages or mission profile events. Range estimating — a probabilistic method that combines Monte Carlo sampling, focus on critical parameters, and heuristics to assess risk and opportunities — is then adapted with operational parameters as well as vehicle parameters in the DYREQT model to capture mission uncertainty alongside vehicle uncertainty. To perform the range estimation portion of this methodology, the DYREQT model was sampled using a Design of Experiments (DoE) to efficiently explore the architecture design space with respect to the set of uncertainty parameters. Then, the results were used to create surrogate models, multivariate regressions that can visualize hypercube trends in the design space, of the architecture with respect to the uncertainty parameters. Using a correlation matrix constructed for the uncertainty parameters, previously independent samples were transformed to perform a Correlated Monte Carlo on the surrogate models. This probabilistic methodology was proved to provide insight into the underlying uncertainties of the three-element HLS architecture.

Stephanie Y Zhu↗

Probabilistic Modeling of a Three-Stage Human Landing System Architecture

Unmitigated uncertainties are known to have previously led to failed development programs; in order to combat these uncertainties, risks and their impacts must be understood and handled to ensure program success. In this paper, a probabilistic methodology to handle uncertainties is demonstrated on a three-element Human Landing System (HLS) concept, which allows tracking of current best estimates of the vehicle’s performance and assessment of its robustness against uncertainties. This methodology has two key parts: first, the creation of a dynamic architecture model of a three-element HLS concept; and second, its use with surrogate modeling and range estimating techniques to capture and propagate uncertainties. The DYnamic Rocket EQuation Tool (DYREQT), a space systems synthesis and sizing framework used by NASA, was used as to model the HLS architecture. For the probabilistic analysis, uncertainties of interest within the HLS concept were enumerated and represented as parameters within the DYREQT model as inputs for vehicle stages or mission profile events. Range estimating — a probabilistic method that combines Monte Carlo sampling, focus on critical parameters, and heuristics to assess risk and opportunities — is then adapted with operational parameters as well as vehicle parameters in the DYREQT model to capture mission uncertainty alongside vehicle uncertainty. To perform the range estimation portion of this methodology, the DYREQT model was sampled using a Design of Experiments (DoE) to efficiently explore the architecture design space with respect to the set of uncertainty parameters. Then, the results were used to create surrogate models, multivariate regressions that can visualize hypercube trends in the design space, of the architecture with respect to the uncertainty parameters. Using a correlation matrix constructed for the uncertainty parameters, previously independent samples were transformed to perform a Correlated Monte Carlo on the surrogate models. This probabilistic methodology was proved to provide insight into the underlying uncertainties of the three-element HLS architecture.

Stephanie Y. Zhu↗

Alpha-Imaging Detector System Development for Large Area Monitoring

Effective management and disposal of legacy nuclear waste are essential for ensuring safe work environments and minimizing environmental impacts. Monitoring airborne actinide contamination is particularly critical due to the high internal dose potential of alpha-emitting radionuclides. Traditional continuous air monitoring systems (CAMs) used in the industry are limited in the volume of air they can sample, potentially leading to inaccurate radiation detection over large areas. For example, in 2018, elevated levels of airborne Plutonium-239 were detected beyond the controlled areas of the Hanford Plutonium Finishing Plant, highlighting the potential risks to both plant workers and nearby residents. To address these challenges, high-efficiency particulate absorbing (HEPA) air purifiers can enhance air flow by up to 1.5 orders of magnitude, thereby increasing monitoring efficiency and providing a cost-effective solution for large-area surveillance. To quantify the activities of alpha-emitting radionuclides on HEPA filters, the Savannah River National Laboratory is developing an advanced alpha-imaging detection system. This system includes scintillating materials combined with a digital scientific camera. A significant concern in operating such a large-area airborne monitoring system is the handling of HEPA filters, which may be contaminated with radioactive particles. To mitigate these hazards, it is crucial to ensure that any contamination is securely fixed onto the filters. Efforts have been made to optimize the sensitivity of scintillator-epoxy composites and apply them to HEPA filters. These materials were characterized using fluoroscence spectroscopy. These techniques confirmed the purity of the raw materials, the dispersion of scintillators in the epoxy matrix, and the stability of their optical and structural properties post-modification. The optimal scintillator-epoxy composite was selected for use on alpha-spiked HEPA filters to evaluate the efficiency of the sprayer. HEPA filters, embedded with alpha particles collected by an air purifier deployed in an airborne radiation area, have been tested to assess detection efficiency. Future work will focus on employing multiple imaging sensors simultaneously to enhance sensitivity across different regions of the HEPA filter.

Pham, Phuong [Savannah River National Laboratory (↗

Deployable Aeroshell Flexible Thermal Protection System Testing

Deployable aeroshells offer the promise of achieving larger aeroshell surface areas for entry vehicles than otherwise attainable without deployment. With the larger surface area comes the ability to decelerate high-mass entry vehicles at relatively low ballistic coefficients. However, for an aeroshell to perform even at the low ballistic coefficients attainable with deployable aeroshells, a flexible thermal protection system (TPS) is required that is capable of surviving reasonably high heat flux and durable enough to survive the rigors of construction handling, high density packing, deployment, aerodynamic loading and aerothermal heating. The Program for the Advancement of Inflatable Decelerators for Atmospheric Entry (PAIDAE) is tasked with developing the technologies required to increase the technology readiness level (TRL) of inflatable deployable aeroshells, and one of several of the technologies PAIDAE is developing for use on inflatable aeroshells is flexible TPS. Several flexible TPS layups were designed, based on commercially available materials, and tested in NASA Langley Research Center's 8 Foot High Temperature Tunnel (8ft HTT). The TPS layups were designed for, and tested at three different conditions that are representative of conditions seen in entry simulation analyses of inflatable aeroshell concepts. Two conditions were produced in a single run with a sting-mounted dual wedge test fixture. The dual wedge test fixture had one row of sample mounting locations (forward) at about half the running length of the top surface of the wedge. At about two thirds of the running length of the wedge, a second test surface drafted up at five degrees relative to the first test surface established the remaining running length of the wedge test fixture. A second row of sample mounting locations (aft) was positioned in the middle of the running length of the second test surface. Once the desired flow conditions were established in the test section the dual wedge test fixture, oriented at 5 degrees angle of attack down, was injected into the flow. In this configuration the aft sample mounting location was subjected to roughly twice the heat flux and surface pressure of the forward mounting location. The tunnel was run at two different conditions for the test series: 1) 'Low Pressure', and 2) 'High Pressure'. At 'Low Pressure' conditions the TPS layups were tested at 6W/cm2 and 11W/cm2 while at 'High Pressure' conditions the TPS layups were tested at 11W/cm2 and 20W/cm2. This paper details the test configuration of the TPS samples in the 8Ft HTT, the sample holder assembly, TPS sample layup construction, sample instrumentation, results from this testing, as well as lessons learned.

Hughes, Stephen J.↗

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗

High fidelity blade-resolved and actuator line data from a 16 turbine wind farm simulation using ExaWind

This data was generated with the ExaWind code suite (https://github.com/Exawind) as a demonstration of a large, 16 turbine wind farm simulation, calculated using two different levels of fidelity. The lower level of fidelity approach uses an actuator line approach to represent the turbines, and was simulated with AMR-Wind (https://github.com/Exawind/amr-wind/) as the background flow solver, coupled to OpenFAST (https://github.com/OpenFAST/openfast). The higher level of fidelity simulation uses a blade-resolved approach, and is done using AMR-Wind, Nalu-Wind (https://github.com/Exawind/nalu-wind), OpenFAST, and TIOGA (https://github.com/Exawind/tioga). In the blade-resolved simulation, ExaWind couples together a background flow solver, AMR-Wind, and a near-body solver, Nalu-Wind, through an overset technique from the TIOGA application. OpenFAST handles the structural dynamics of the turbine blades and towers, which informs the fluid-structure interaction of the wind turbines with the flow solvers. In the actuator line simulation, a mesh of 295M elements was used for a 5km x 5km domain, and it was simulated using 256 nodes (2048 GPU's) on the Oak Ridge Leadership Computing Facility Frontier supercomputer. For the blade-resolved simulation, 1.5B element mesh was used in the AMR-Wind background 5km x 5km domain, and 16M elements were used for each turbine in the Nalu-Wind domains, for a total of 1.7B elements. This was simulated using 384 nodes on Frontier, with each node using 56 cores for Nalu-Wind and 8 GPU cores. The data in this archive includes the turbine outputs from OpenFAST, 2D sampling planes from AMR-Wind, and full-field solution files from AMR-Wind and Nalu-Wind.

17 WIND ENERGY↗

Wide Temperature Core Loss Characteristics of Transverse Magnetically Annealed Amorphous Tapes for High Frequency Aerospace Magnetics

100 kHz core loss properties of sample transverse magnetically annealed, cobalt-based amorphous and iron-based nanocrystalline tape wound magnetic cores are presented over the temperature range of -150 C to 150 C, at selected values of B(sub peak). For B-fields not close to saturation, the core loss is not sensitive to temperature in this range and is as low as seen in the best MnZn power ferrites at their optimum temperatures. Frequency resolved characteristics are given over the range of 50 kHz to 1 MHz, but at B(sub peak) = 0.1 T and 50 C only. For example, the 100 kHz specific core loss ranged from 50 - 70 mW/cubic cm for the 3 materials, when measured at 0.1 T and 50 C. This very low high frequency core loss, together with near zero saturation magnetostriction and insensitivity to rough handling, makes these amorphous ribbons strong candidates for power magnetics applications in wide temperature aerospace environments.

Niedra, Janis M.↗

Riding and handling qualities of light aircraft: A review and analysis

Design procedures and supporting data necessary for configuring light aircraft to obtain desired responses to pilot commands and gusts are presented. The procedures employ specializations of modern military and jet transport practice where these provide an improvement over earlier practice. General criteria for riding and handling qualities are discussed in terms of the airframe dynamics. Methods available in the literature for calculating the coefficients required for a linearized analysis of the airframe dynamics are reviewed in detail. The review also treats the relation of spin and stall to airframe geometry. Root locus analysis is used to indicate the sensitivity of airframe dynamics to variations in individual stability derivatives and to variations in geometric parameters. Computer programs are given for finding the frequencies, damping ratios, and time constants of all rigid body modes and for generating time histories of aircraft motions in response to control inputs. Appendices are included presenting the derivation of the linearized equations of motion; the stability derivatives; the transfer functions; approximate solutions for the frequency, damping ratio, and time constants; an indication of methods to be used when linear analysis is inadequate; sample calculations; and an explanation of the use of root locus diagrams and Bode plots.

Smetana, F. O.↗

A modular suite of hardware enabling spaceflight cell culture research

BioServe Space Technologies, a NASA Research Partnership Center (RPC), has developed and operated various middeck payloads launched on 23 shuttle missions since 1991 in support of commercial space biotechnology projects. Modular cell culture systems are contained within the Commercial Generic Bioprocessing Apparatus (CGBA) suite of flight-qualified hardware, compatible with Space Shuttle, SPACEHAB, Spacelab and International Space Station (ISS) EXPRESS Rack interfaces. As part of the CGBA family, the Isothermal Containment Module (ICM) incubator provides thermal control, data acquisition and experiment manipulation capabilities, including accelerometer launch detection for automated activation and thermal profiling for culture incubation and sample preservation. The ICM can accommodate up to 8 individually controlled temperature zones. Command and telemetry capabilities allow real-time downlink of data and video permitting remote payload operation and ground control synchronization. Individual cell culture experiments can be accommodated in a variety of devices ranging from 'microgravity test tubes' or standard 100 mm Petri dishes, to complex, fed-batch bioreactors with automated culture feeding, waste removal and multiple sample draws. Up to 3 levels of containment can be achieved for chemical fixative addition, and passive gas exchange can be provided through hydrophobic membranes. Many additional options exist for designing customized hardware depending on specific science requirements.

manned↗