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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 NTRS2005

Radiation Dosimetry via Automated Fluorescence Microscopy

A developmental instrument for assessment of radiation-induced damage in human lymphocytes includes an automated fluorescence microscope equipped with a one or more chargecoupled- device (CCD) video camera(s) and circuitry to digitize the video output. The microscope is also equipped with a three-axis translation stage that includes a rotation stage, and a rotary tray that holds as many as thirty specimen slides. The figure depicts one version of the instrument. Once the slides have been prepared and loaded into the tray, the instrument can operate unattended. A computer controls the operation of the stage, tray, and microscope, and processes the digital fluorescence-image data to recognize and count chromosomes that have been broken, presumably by radiation. The design and method of operation of the instrument exploit fluorescence in situ hybridization (FISH) of metaphase chromosome spreads, which is a technique that has been found to be valuable for monitoring the radiation dose to circulating lymphocytes. In the specific FISH protocol used to prepare specimens for this instrument, metaphase lymphocyte cultures are chosen for high mitotic index and highly condensed chromosomes, then several of the largest chromosomes are labeled with three of four differently colored whole-chromosome-staining dyes. The three dyes, which are used both individually and in various combinations, are fluorescein isothiocyanate (FITC), Texas Red (or equivalent), and Cy5 (or equivalent); The fourth dye 4',6-diamidino- 2-phenylindole (DAPI) is used as a counterstain. Under control by the computer, the microscope is automatically focused on the cells and each slide is scanned while the computer analyzes the DAPI-fluorescence images to find the metaphases. Each metaphase field is recentered in the field of view and refocused. Then a four-color image (more precisely, a set of images of the same view in the fluorescent colors of the four dyes) is acquired. By use of pattern-recognition software developed specifically for this instrument, the images in the various colors are processed to recognize the metaphases and count the chromosome fragments of each color within the metaphases. The intermediate results are then further processed to estimate the proportion of cells that have suffered genetic damage. The prototype instrument scans at an average areal rate of 4.7 mm2/h in unattended operation, finding about 14 metaphases per hour. The false-alarm rate is typically less than 3 percent, and the metaphase-miss rate has been estimated to be less than 5 percent. The counts of chromosomes and fragments thereof are 50 to 70 percent accurate.

Castleman, Kenneth R.↗
NASA NTRS2016

Light Microscopy Module: International Space Station Premier Automated Microscope

The Light Microscopy Module (LMM) was launched to the International Space Station (ISS) in 2009 and began hardware operations in 2010. It continues to support Physical and Biological scientific research on ISS. During 2016, if all goes as planned, three experiments will be completed: [1] Advanced Colloids Experiments with Heated base-2 (ACE-H2) and [2] Advanced Colloids Experiments with Temperature control (ACE-T1). Preliminary results, along with an overview of present and future LMM capabilities will be presented; this includes details on the planned data imaging processing and storage system, along with the confocal upgrade to the core microscope. [1] a consortium of universities from the State of Kentucky working through the Experimental Program to Stimulate Competitive Research (EPSCoR): Stuart Williams, Gerold Willing, Hemali Rathnayake, et al. and [2] from Chungnam National University, Daejeon, S. Korea: Chang-Soo Lee, et al.

Microgravity Biology Research↗
NASA NTRS2005

NASA Tech Briefs, December 2005

Topics covered include: Video Mosaicking for Inspection of Gas Pipelines; Shuttle-Data-Tape XML Translator; Highly Reliable, High-Speed, Unidirectional Serial Data Links; Data-Analysis System for Entry, Descent, and Landing; Hybrid UV Imager Containing Face-Up AlGaN/GaN Photodiodes; Multiple Embedded Processors for Fault-Tolerant Computing; Hybrid Power Management; Magnetometer Based on Optoelectronic Microwave Oscillator; Program Predicts Time Courses of Human/ Computer Interactions; Chimera Grid Tools; Astronomer's Proposal Tool; Conservative Patch Algorithm and Mesh Sequencing for PAB3D; Fitting Nonlinear Curves by Use of Optimization Techniques; Tool for Viewing Faults Under Terrain; Automated Synthesis of Long Communication Delays for Testing; Solving Nonlinear Euler Equations With Arbitrary Accuracy; Self-Organizing-Map Program for Analyzing Multivariate Data; Tool for Sizing Analysis of the Advanced Life Support System; Control Software for a High-Performance Telerobot; Java Radar Analysis Tool; Architecture for Verifiable Software; Tool for Ranking Research Options; Enhanced, Partially Redundant Emergency Notification System; Close-Call Action Log Form; Task Description Language; Improved Small-Particle Powders for Plasma Spraying; Bonding-Compatible Corrosion Inhibitor for Rinsing Metals; Wipes, Coatings, and Patches for Detecting Hydrazines; Rotating Vessels for Growing Protein Crystals; Oscillating-Linear-Drive Vacuum Compressor for CO2; Mechanically Biased, Hinged Pairs of Piezoelectric Benders; Apparatus for Precise Indium-Bump Bonding of Microchips; Radiation Dosimetry via Automated Fluorescence Microscopy; Multistage Magnetic Separator of Cells and Proteins; Elastic-Tether Suits for Artificial Gravity and Exercise; Multichannel Brain-Signal-Amplifying and Digitizing System; Ester-Based Electrolytes for Low-Temperature Li-Ion Cells; Hygrometer for Detecting Water in Partially Enclosed Volumes; Radio-Frequency Plasma Cleaning of a Penning Malmberg Trap; Reduction of Flap Side Edge Noise - the Blowing Flap; and Preventing Accidental Ignition of Upper-Stage Rocket Motors.

Source record↗
NASA NTRS2015

Light Microsopy Module, International Space Station Premier Automated Microscope

The Light Microscopy Module (LMM) was launched to the International Space Station (ISS) in 2009 and began science operations in 2010. It continues to support Physical and Biological scientific research on ISS. During 2015, if all goes as planned, five experiments will be completed: [1] Advanced Colloids Experiments with a manual sample base -3 (ACE-M-3), [2] the Advanced Colloids Experiment with a Heated Base -1 (ACE-H-1), [3] (ACE-H-2), [4] the Advanced Plant Experiment -03 (APEX-03), and [5] the Microchannel Diffusion Experiment (MDE). Preliminary results, along with an overview of present and future LMM capabilities will be presented; this includes details on the planned data imaging processing and storage system, along with the confocal upgrade to the core microscope. [1] New York University: Paul Chaikin, Andrew Hollingsworth, and Stefano Sacanna, [2] University of Pennsylvania: Arjun Yodh and Matthew Gratale, [3] a consortium of universities from the State of Kentucky working through the Experimental Program to Stimulate Competitive Research (EPSCoR): Stuart Williams, Gerold Willing, Hemali Rathnayake, et al., [4] from the University of Florida and CASIS: Anna-Lisa Paul and Rob Ferl, and [5] from the Methodist Hospital Research Institute from CASIS: Alessandro Grattoni and Giancarlo Canavese.

Microscopy↗
NASA NTRS2001

Compact Microscope Imaging System Developed

The Compact Microscope Imaging System (CMIS) is a diagnostic tool with intelligent controls for use in space, industrial, medical, and security applications. The CMIS can be used in situ with a minimum amount of user intervention. This system, which was developed at the NASA Glenn Research Center, can scan, find areas of interest, focus, and acquire images automatically. Large numbers of multiple cell experiments require microscopy for in situ observations; this is only feasible with compact microscope systems. CMIS is a miniature machine vision system that combines intelligent image processing with remote control capabilities. The software also has a user-friendly interface that can be used independently of the hardware for post-experiment analysis. CMIS has potential commercial uses in the automated online inspection of precision parts, medical imaging, security industry (examination of currency in automated teller machines and fingerprint identification in secure entry locks), environmental industry (automated examination of soil/water samples), biomedical field (automated blood/cell analysis), and microscopy community. CMIS will improve research in several ways: It will expand the capabilities of MSD experiments utilizing microscope technology. It may be used in lunar and Martian experiments (Rover Robot). Because of its reduced size, it will enable experiments that were not feasible previously. It may be incorporated into existing shuttle orbiter and space station experiments, including glove-box-sized experiments as well as ground-based experiments.

McDowell, Mark↗
NASA NTRS1994

IMIS: An intelligence microscope imaging system

Until recently microscope users in space relied on traditional microscopy techniques that required manual operation of the microscope and recording of observations in the form of written notes, drawings, or photographs. This method was time consuming and required the return of film and drawings from space for analysis. No real-time data analysis was possible. Advances in digital and video technologies along with recent developments in article intelligence will allow future space microscopists to have a choice of three additional modes of microscopy: remote coaching, remote control, and automation. Remote coaching requires manual operations of the microscope with instructions given by two-way audio/video transmission during critical phases of the experiment. When using the remote mode of microscopy, the Principal Investigator controls the microscope from the ground. The automated mode employs artificial intelligence to control microscope functions and is the only mode that can be operated in the other three modes as well. The purpose of this presentation is to discuss the advantages and disadvantages of the four modes of of microscopy and how the IMIS, a proposed intelligent microscope imaging system, can be used as a model for developing and testing concepts, operating procedures, and equipment design of specifications required to provide a comprehensive microscopy/imaging capability onboard Space Station Freedom.

Caputo, Michael↗
NASA NTRS2014

NASA Tech Briefs, January 2014

Topics include: Multi-Source Autonomous Response for Targeting and Monitoring of Volcanic Activity; Software Suite to Support In-Flight Characterization of Remote Sensing Systems; Visual Image Sensor Organ Replacement; Ultra-Wideband, Dual-Polarized, Beam-Steering P-Band Array Antenna; Centering a DDR Strobe in the Middle of a Data Packet; Using a Commercial Ethernet PHY Device in a Radiation Environment; Submerged AUV Charging Station; Habitat Demonstration Unit (HDU) Vertical Cylinder Habitat; Origami-Inspired Folding of Thick, Rigid Panels; A Novel Protocol for Decoating and Permeabilizing Bacterial Spores for Epifluorescent Microscopy; Method and Apparatus for Automated Isolation of Nucleic Acids from Small Cell Samples; Enabling Microliquid Chromatography by Microbead Packing of Microchannels; On-Command Force and Torque Impeding Devices (OC-FTID) Using ERF; Deployable Fresnel Rings; Transition-Edge Hot-Electron Microbolometers for Millimeter and Submillimeter Astrophysics; Spacecraft Trajectory Analysis and Mission Planning Simulation (STAMPS) Software; Cross Support Transfer Service (CSTS) Framework Library; Arbitrary Shape Deformation in CFD Design; Range Safety Flight Elevation Limit Calculation Software; Frequency-Modulated, Continuous-Wave Laser Ranging Using Photon-Counting Detectors; Calculation of Operations Efficiency Factors for Mars Surface Missions; GPU Lossless Hyperspectral Data Compression System; Robust, Optimal Subsonic Airfoil Shapes; Protograph-Based Raptor-Like Codes; Fuzzy Neuron: Method and Hardware Realization; Kalman Filter Input Processor for Boresight Calibration; Organizing Compression of Hyperspectral Imagery to Allow Efficient Parallel Decompression; and Temperature Dependences of Mechanisms Responsible for the Water-Vapor Continuum Absorption.

Source record↗
NASA NTRS2004

Space Station Biological Research Project (SSBRP) Cell Culture Unit (CCU) and incubator for International Space Station (ISS) cell culture experiments

The CCU and Incubator are habitats under development by SSBRP for gravitational biology research on ISS. They will accommodate multiple specimen types and reside in either Habitat Holding Racks, or the Centrifuge Rotor, which provides selectable gravity levels of up to 2 g. The CCU can support multiple Cell Specimen Chambers, CSCs (18, 9 or 6 CSCs; 3, 10 or 30 mL in volume, respectively). CSCs are temperature controlled from 4-39 degrees C, with heat shock to 45 degrees C. CCU provides automated nutrient supply, magnetic stirring, pH/O2 monitoring, gas supply, specimen lighting, and video microscopy. Sixty sample containers holding up to 2 mL each, stored at 4-39 degrees C, are available for automated cell sampling, subculture, and injection of additives and fixatives. CSCs, sample containers, and fresh/spent media bags are crew-replaceable for long-term experiments. The Incubator provides a 4-45 degrees C controlled environment for life science experiments or storage of experimental reagents. Specimen containers and experiment unique equipment are experimenter-provided. The Specimen Chamber exchanges air with ISS cabin and has 18.8 liters of usable volume that can accommodate six trays and the following instrumentation: five relocatable thermometers, two 60 W power outlets, four analog ports, and one each relative humidity sensor, video port, ethernet port and digital input/output port.

NASA Center ARC↗
NASA NTRS1989

Ecology of micro-organisms in a small closed system - Potential benefits and problems for Space Station

The probable sources and implications of microbial contamination on the proposed Space Station are discussed. Because of the limited availability of material, facilities and time on the Space Station, we are exploring the feasibility of replacing traditional incubation methods for assessing microbial contamination with rapid, automated methods. Some possibilities include: ATP measurement, microscopy and telecommunications, and molecular techniques such as DNA probes or monoclonal antibodies. Some of the important ecological factors that could alter microbes in space include microgravity, exposure to radiation, and antibiotic resistance.

Rodgers, E. B.↗
NASA NTRS2003

The Fluids Integrated Rack and Light Microscopy Module Integrated Capabilities

The Fluids Integrated Rack (FIR), a facility class payload, and the Light Microscopy Module (LMM), a subrack payload, are scheduled to be launched in 2005. The LMM integrated into the FIR will provide a unique platform for conducting fluids and biological experiments on ISS. The FIR is a modular, multi-user scientific research facility that will fly in the U.S. laboratory module, Destiny, of the International Space Station (ISS). The first payload in the FIR will be the Light Microscopy Module (LMM). The LMM is planned as a remotely controllable, automated, on-orbit microscope subrack facility, allowing flexible scheduling and control of fluids and biology experiments within the FIR. Key diagnostic capabilities for meeting science requirements include video microscopy to observe microscopic phenomena and dynamic interactions, interferometry to make thin film measurements with nanometer resolution, laser tweezers for particle manipulation, confocal microscopy to provide enhanced three-dimensional visualization of structures, and spectrophotometry to measure photonic properties of materials. The LMM also provides experiment sample containment for frangibles and fluids. This paper will provide a description of the current FIR and LMM designs, planned capabilities and key features. In addition a brief description of the initial five experiments planned for LMM/FIR will be provided.

Motil, Susan M.↗
NASA NTRS2002

Light Microscopy Module: On-Orbit Microscope Planned for the Fluids Integrated Rack on the International Space Station

The Light Microscopy Module (LMM) is planned as a remotely controllable, automated, on-orbit facility, allowing flexible scheduling and control of physical science and biological science experiments within the Fluids Integrated Rack (FIR) on the International Space Station. Initially four fluid physics experiments in the FIR will use the LMM the Constrained Vapor Bubble, the Physics of Hard Spheres Experiment-2, Physics of Colloids in Space-2, and Low Volume Fraction Entropically Driven Colloidal Assembly. The first experiment will investigate heat conductance in microgravity as a function of liquid volume and heat flow rate to determine, in detail, the transport process characteristics in a curved liquid film. The other three experiments will investigate various complementary aspects of the nucleation, growth, structure, and properties of colloidal crystals in microgravity and the effects of micromanipulation upon their properties.

Motil, Susan M.↗
NASA NTRS2004

Light Microscopy Module Imaging Tested and Demonstrated

The Fluids Integrated Rack (FIR), a facility-class payload, and the Light Microscopy Module (LMM), a subrack payload, are integrated research facilities that will fly in the U.S. Laboratory module, Destiny, aboard the International Space Station. Both facilities are being engineered, designed, and developed at the NASA Glenn Research Center by Northrop Grumman Information Technology. The FIR is a modular, multiuser scientific research facility that is one of two racks that make up the Fluids and Combustion Facility (the other being the Combustion Integrated Rack). The FIR has a large volume dedicated for experimental hardware; easily reconfigurable diagnostics, power, and data systems that allow for unique experiment configurations; and customizable software. The FIR will also provide imagers, light sources, power management and control, command and data handling for facility and experiment hardware, and data processing and storage. The first payload in the FIR will be the LMM. The LMM integrated with the FIR is a remotely controllable, automated, on-orbit microscope subrack facility, with key diagnostic capabilities for meeting science requirements--including video microscopy to observe microscopic phenonema and dynamic interactions, interferometry to make thin-film measurements with nanometer resolution, laser tweezers to manipulate micrometer-sized particles, confocal microscopy to provide enhanced three-dimensional visualization of structures, and spectrophotometry to measure the photonic properties of materials. Vibration disturbances were identified early in the LMM development phase as a high risk for contaminating the science microgravity environment. An integrated FIR-LMM test was conducted in Glenn's Acoustics Test Laboratory to assess mechanical sources of vibration and their impact to microscopic imaging. The primary purpose of the test was to characterize the LMM response at the sample location, the x-y stage within the microscope, to vibration emissions from the FIR and LMM support structures.

Gati, Frank↗
NASA NTRS2004

Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

Hoover, Richard B.↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗
NASA NTRS1982

Large-area silicon sheet task

A set of computer models was used to define a growth system configuration that was then built and used to grow web with lower thermally generated stress. Aspects of research in the edge-defined film-fed growth (EFG) method of making Si ribbon are reported. A technique was developed to determine base resistivity and carrier lifetime in semicrystalline wafers. Automated growth of 150 kg of 15 cm-dia ingot material per crucible is reviewed. Scanning transmisson electron microscopy (STEM) and microprobe investigations of processed EFG ribbon are reported. The chemical composition of the large precipitates was studied. The structural arrangement and the electrical activity of distentions or close to the central twin plane in processed material were studied. The electrical and structural properties of grain boundaries in silicon are discussed. Temperature-dependence measurements of zero-bias conductance, a photoconductivity technique, and deep-level transient spectroscopy (DLTS) were developed. A grooving and staining technique, secondary ion mass spectroscopy, and EBIC measurements in scanning electron microscopy were used to study enhanced diffusion of phosphorus at grain boundaries in polycrystaline silicon. The fundamental mechanisms of abrasion and wear and the deformation of Si by a diamond in various fluid environments are described. The efficiency of solar cells made from EFG ribbon and Semix Inc. material is reported.

Morrison, A. D.↗
NASA NTRSDate not supplied

An Electron Backscatter Diffraction (EBSD)-Based Automated Tool for Ceramic Capacitor Grain Size Analysis

Ceramic capacitors continue to be recurring problem parts for NASA, despite best efforts to screen out potential defects and failures through environmental and electrical testing and nondestructive inspection techniques such as acoustic microscopy. The physical properties of ceramic capacitors necessitates thin dielectric layers capable of withstanding significant electric fields. Any defects in those ceramic layers can result in reduced insulation resistance failure modes including short circuit failures, so the quality and consistency of the dielectric material is critical. The size of the individual ceramic grains in the dielectric material is a critical parameter. However, judging “grain size” is not so simple—in a single capacitor there can be wide variation in grain sizes observed. It is theorized that by studying the grain size distributions of “known good” and “known bad” lots of capacitors, some conclusions could be drawn that would allow us to better predict to the reliability of future lots based on grain size distributions. The initial goal of this effort was to find or develop an automated tool that could inspect a capacitor and return grain size distribution results.

Robert Hodson↗
NASA NTRS2012

Face-Sheet Quality Analysis and Thermo-Physical Property Characterization of OOA and Autoclave Panels

Increased application of polymer matrix composite (PMC) materials in large vehicle structures requires consideration of non-autoclave manufacturing technology. The NASA Composites for Exploration project, and its predecessor, Lightweight Spacecraft Structures and Materials project, were tasked with the development of materials and manufacturing processes for structures that will perform in a heavy-lift-launch vehicle environment. Both autoclave and out of autoclave processable materials were considered. Large PMC structures envisioned for such a vehicle included the payload shroud and the interstage connector. In this study, composite sandwich panels representing 1/16th segments of the barrel section of the Ares V rocket fairing were prepared as 1.8 m x 2.4 m sections of the 10 m diameter arc segment. IM7/977-3 was used as the face-sheet prepreg of the autoclave processed panels and T40-800B/5320-1 for the out of autoclave panels. The core was 49.7 kilograms per square meters (3.1 pounds per cubic feet (pcf)) aluminum honeycomb. Face-sheets were fabricated by automated tape laying 153 mm wide unidirectional tape. This work details analysis of the manufactured panels where face-sheet quality was characterized by optical microscopy, cured ply thickness measurements, acid digestion, and thermal analysis.

Miller, Sandi G.↗