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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Fatigue Resistance of Liquid-assisted Self-repairing Aluminum Alloys Reinforced with Shape Memory Alloys

A self-repairing aluminum-based composite system has been developed using a liquid-assisted healing theory in conjunction with the shape memory effect of wire reinforcements. The metal-metal composite was thermodynamically designed to have a matrix with a relatively even dispersion of a low-melting eutectic phase, allowing for repair of cracks at a predetermined temperature. Additionally, shape memory alloy (SMA) wire reinforcements were used within the composite to provide crack closure. Investigators focused the research on fatigue cracks propagating through the matrix in order to show a proof-of-concept Shape Memory Alloy Self-Healing (SMASH) technology for aeronautical applications.

Wright, M. Clara↗
NASA NTRS2014

Processing and Characterization of Basalt Fiber Reinforced Ceramic Composites for High Temperature Applications Using Polymer Precursors

The development of high temperature structural composite materials has been very limited due to the high cost of the materials and the processing needed. Ceramics can take much higher temperatures, but they are difficult to produce and form in bulk volumes. Polymer Derived Ceramics (PDCs) begin as a polymer matrix, allowing a shape to be formed and cured and then to be pyrolized in order to obtain a ceramic with the associated thermal and mechanical properties. The two PDCs used in this development are polysiloxane and polycarbosilane. Polysiloxanes contain a silicon oxycarbide backbone when pyrolized up to 1000C. Polycarbosilane, an organosilicon polymer, contain a silicon-carbon backbone; around 1200C, beta-SiC begins to crystallize. The use of basalt in structural and high temperature applications has been under development for over 50 years, yet there has been little published research on the incorporation of basalt fibers as a reinforcement in composites. Basalt is a naturally occurring material found in volcanic rock. Continuous basalt fiber reinforced PDCs have been fabricated and tested for the applicability of this composite system as a high temperature structural composite material. Thermal and mechanical testing includes oxyacetylene torch testing and three point bend testing.

Ceramic Matrix Composites↗
NASA NTRS2014

Processing and Characterization of Basalt Fiber Reinforced Ceramic Composites for High Temperature Applications Using Polymer Precursors

The development of high temperature structural composite materials has been very limited due to the high cost of the materials and the processing needed. Ceramics can take much higher temperatures, but they are difficult to produce and form in bulk volumes. Polymer Derived Ceramics (PDCs) begin as a polymer matrix, allowing a shape to be formed and cured and then to be pyrolized in order to obtain a ceramic with the associated thermal and mechanical properties. The two PDCs used in this development are polysiloxane and polycarbosilane. Polysiloxanes contain a silicon oxycarbide backbone when pyrolized up to 1000 deg C. Polycarbosilane, an organosilicon polymer, contain a silicon-carbon backbone; around 1200 deg C, Beta-SiC begins to crystallize. The use of basalt in structural and high temperature applications has been under development for over 50 years, yet there has been little published research on the incorporation of basalt fibers as a reinforcement in composites. Basalt is a naturally occurring material found in volcanic rock. Continuous basalt fiber reinforced PDCs have been fabricated and tested for the applicability of this composite system as a high temperature structural composite material. Thermal and mechanical testing includes oxyacetylene torch testing and three point bend testing.

Polymer Derived Ceramics↗
NASA NTRS1961

Development of Ceramic Fibers for Reinforcement in Composite Materials

Refinements of the vertical arc fiberizing apparatus resulted in its ability to fiberize very different refractory glasses having wide ranges of properties. Although the apparatus, was originally designed as a laboratory research tool for the evaluation of many compositions daily, up to one quarter pound of fibers of a single composition could be produced in an 8-hour day. Fibers up to six and a half feet long were produced with the apparatus. Studies were conducted of two methods of fiberizing refractory glasses requiring rapid freezing from the melt. The first method consisted of fiberizing droplets of molten glass passing through an annular nozzle. The second method consisted of reconstructing the annular nozzle in. the shape of a horseshoe to achieve a shorter delay in blasting a molten droplet from the tip of a rod. Both methods were judged feasible for producing fibers of glasses requiring rapid freezing. The first method would be more amenable to volume fiber production. Studies of induction heating for fiber formation did not lead to its designation as a very efficient heating method. Problems. remain to be solved, in the design of a suitable susceptor for a higher heating rate, in protecting the susceptor from oxidation with an inert gas, in contamination of the melt from a refractory crucible, and in the protective radiation shielding of the induction concentrator coil. It is not considered practical to continue studies of this heating method. In the course of this program 151 refractory glass compositions were evaluated for fiber, forming characteristics. Of the various types of materials studied, the following showed promise in producing acceptable refractory fibers: sIlica- spinel (magnesium aluminate), silica- spinel-zirconia, silica-zirconia, silica-zinc spinel, aluminum phosphate glasses, and fluoride glasses. Compositions which did not produce acceptable fibers were high zirconia materials, barium spinels, and calcium aluminates. Improvements in the. testing apparatus for single fiber tensile strength increased the precision. of tests conducted on nine fibers. The highest mean tensile strength, a value of 295,000 pounds per square inch, was obtained with R-141 fibers. Treatment of R-74 fibers with anhydrous Linde A-1100 silane finish improved its mean fiber tensile strength by 25 percent. The lapse of time after fiber formation had no measurable effect on tensile strength. A static heating test conducted with various high melting fibers indicated that Fiberfrax and R-108 underwent no significant changes in bulk volume or resiliency on exposure to 2750 degrees Fahrenheit (1510 degrees Centigrade) in an oxidizing atmosphere. For fiber-resin composition fabrication, ten fiber materials were selected on the bases of high fiber yield, fusion temperature, and type of composition. Fiberfrax, a commercial ceramic fiber, was included for comparison. A new, more effective method of removing pellets from blown fibers was developed. The de-pelletized fibers were treated with a silane finish and felted into ten-inch diameter felts prior to resin impregnation. Composites containing 30 percent by weight of CTL 91-LD phenolic resin were molded under high pressure from the impregnated felts and post-cured to achieve optimum properties. Flexural strength, flexural modules of elasticity, and punch shear strength tests were conducted on the composite specimens. The highest average flexural strength obtained was 19,958 pounds per square inch with the R-74-fiber-resin composite. This compares very favorably with the military specification of 13,000 pounds per square inch flexural strength for randomly oriented fiber reinforced composites. The highest punch shear strength (11,509 pounds per square inch) was obtained with the R-89 fiber-resin composite. The effects of anhydrous fiber finishes on composite strength were not clearly indicated. Plasma arc tests at a heat flux of 550 British Thermal Units per square foot per second on eight composite materials indicated ablation rates generally equivalent to Fiberglas-Micarta No. 259-2. The composite reinforced with R-99 fibers had an average ablation rate of 0.008 inch per second and appears quite promising on the basis of these tests. Preliminary studies for processing fibers into yarn and fabric were conducted with R-99 fibers. The use of certain organic gums aided in 2 fabricating by hand several relatively strong yarns and a crude fabric swatch. This indicated the practicality of developing techniques for processing these fibers into yarn and fabric without significant damage to the fibers.

Gates, L. E.↗
NASA NTRS2016

Process for Preparing Epoxy-Reinforced Silica Aerogels

One-pot reaction process for preparing epoxy-reinforced monolithic silica aerogels comprising the reaction of at least one silicon compound selected from the group consisting of alkoxysilanes, orthosilicates and combination thereof in any ratio with effective amounts of an epoxy monomer and an aminoalkoxy silane to obtain an epoxy monomer-silica sol in solution, subsequently preparing an epoxy-monomer silica gel from said silica sol solution followed by initiating polymerization of the epoxy monomer to obtain the epoxy-reinforced monolithic silica aerogel.

Meador, Mary Ann B↗
NASA NTRS2015

Reinforcement Learning with Autonomous Small Unmanned Aerial Vehicles in Cluttered Environments

We present ongoing work in the Autonomy Incubator at NASA Langley Research Center (LaRC) exploring the efficacy of a data set aggregation approach to reinforcement learning for small unmanned aerial vehicle (sUAV) flight in dense and cluttered environments with reactive obstacle avoidance. The goal is to learn an autonomous flight model using training experiences from a human piloting a sUAV around static obstacles. The training approach uses video data from a forward-facing camera that records the human pilot's flight. Various computer vision based features are extracted from the video relating to edge and gradient information. The recorded human-controlled inputs are used to train an autonomous control model that correlates the extracted feature vector to a yaw command. As part of the reinforcement learning approach, the autonomous control model is iteratively updated with feedback from a human agent who corrects undesired model output. This data driven approach to autonomous obstacle avoidance is explored for simulated forest environments furthering autonomous flight under the tree canopy research. This enables flight in previously inaccessible environments which are of interest to NASA researchers in Earth and Atmospheric sciences.

Tran, Loc↗
NASA NTRS2016

Additive Manufacturing and Characterization of Polylactic Acid (PLA) Composites Containing Metal Reinforcements

Additive manufacturing of polymeric systems using 3D printing has become quite popular recently due to rapid growth and availability of low cost and open source 3D printers. Two widely used 3D printing filaments are based on polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS) systems. PLA is much more environmentally friendly in comparison to ABS since it is made from renewable resources such as corn, sugarcane, and other starches as precursors. Recently, polylactic acid-based metal powder containing composite filaments have emerged which could be utilized for multifunctional applications. The composite filaments have higher density than pure PLA, and the majority of the materials volume is made up of polylactic acid. In order to utilize functionalities of composite filaments, printing behavior and properties of 3-D printed composites need to be characterized and compared with the pure PLA materials. In this study, pure PLA and composite specimens with different metallic reinforcements (Copper, Bronze, Tungsten, Iron, etc) were 3D printed at various layer heights and resulting microstructures and properties were characterized. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) behavior of filaments with different reinforcements were studied. The microscopy results show an increase in porosity between 3-D printed regular PLA and the metal composite PLA samples, which could produce weaker mechanical properties in the metal composite materials. Tensile strength and fracture toughness behavior of specimens as a function of print layer height will be presented.

brass↗
NASA NTRS2016

Influence of Aerogel Morphology and Reinforcement Architecture on Gas Convection in Aerogel Composites

A variety of thermal protection applications require lightweight insulation capable of withstanding temperatures well above 900 C. Aerogels offer extremely low-density thermal insulation due to their mesoporous structure, which inhibits both gas convection and solid conduction. Silica aerogel systems are limited to use temperatures of 600-700 C, above which they sinter. Alumina aerogels maintain a porous structure to higher temperatures than silica, before transforming to -alumina and densifying. We have synthesized aluminosilicate aerogels capable of maintaining higher surface areas at temperatures above 1100 C than an all-alumina aerogel using -Boehmite as the aluminum source and tetraethoxysilane (TEOS) as the silicon source. The pore structure of these aerogels varies with thermal exposure temperature and time, as the aluminosilicate undergoes a variety of phase changes to form transition aluminas. Transformation to -alumina is inhibited by incorporation of silica into the alumina lattice. The aerogels are fragile, but can be reinforced using a large variety of ceramic papers, felts or fabrics. The objective of the current study is to characterize the influence of choice of reinforcement and architecture on gas permeability of the aerogel composites in both the as fabricated condition and following thermal exposure, as well as understand the effects of incorporating hydrophobic treatments in the composites.

aerogels↗
NASA NTRS2018

Hybrid Fiber Layup and Fiber-Reinforced Polymeric Composites Produced Therefrom

Embodiments of a hybrid fiber layup used to form a fiber-reinforced polymeric composite, and a fiber-reinforced polymeric composite produced therefrom are disclosed. The hybrid fiber layup comprises one or more dry fiber strips and one or more prepreg fiber strips arranged side by side within each layer, wherein the prepreg fiber strips comprise fiber material impregnated with polymer resin and the dry fiber strips comprise fiber material without impregnated polymer resin.

Barnell, Thomas J.↗
NASA NTRS2019

Hybrid Fiber Layup and Fiber-Reinforced Polymeric Composites Produced Therefrom

Embodiments of a hybrid fiber layup used to form a fiber-reinforced polymeric composite, and a fiber-reinforced polymeric composite produced therefrom are disclosed. The hybrid fiber layup comprises one or more dry fiber strips and one or more prepreg fiber strips arranged side by side within each layer, wherein the prepreg fiber strips comprise fiber material impregnated with polymer resin and the dry fiber strips comprise fiber material without impregnated polymer resin.

Barnell, Thomas J.↗
NASA NTRS2014

Ground Delay Program Analytics with Behavioral Cloning and Inverse Reinforcement Learning

We used historical data to build two types of model that predict Ground Delay Program implementation decisions and also produce insights into how and why those decisions are made. More specifically, we built behavioral cloning and inverse reinforcement learning models that predict hourly Ground Delay Program implementation at Newark Liberty International and San Francisco International airports. Data available to the models include actual and scheduled air traffic metrics and observed and forecasted weather conditions. We found that the random forest behavioral cloning models we developed are substantially better at predicting hourly Ground Delay Program implementation for these airports than the inverse reinforcement learning models we developed. However, all of the models struggle to predict the initialization and cancellation of Ground Delay Programs. We also investigated the structure of the models in order to gain insights into Ground Delay Program implementation decision making. Notably, characteristics of both types of model suggest that GDP implementation decisions are more tactical than strategic: they are made primarily based on conditions now or conditions anticipated in only the next couple of hours.

Bloem, Michael↗
NASA NTRSDate not supplied

Adaptive Stress Testing: Using Reinforcement Learning to Find Failures in Safety-Critical Systems

Emerging applications in artificial intelligence, such as driverless cars and autonomous aircraft promise to be more efficient, cheaper to operate, and always available. However, ensuring the safety of these systems remains a major challenge to their certification and adoption. These autonomous systems are expected to routinely make safety-critical decisions where failures can have serious consequences including loss of life and property. Testing and validation techniques aim to identify and diagnose potential failures before the system is deployed. However, finding failure scenarios in autonomous systems can be very challenging due to high-dimensional and continuous state spaces, interaction with large environments over many time steps, and the rarity of failures. This talk presents Adaptive Stress Testing (AST), a simulation-based testing framework for finding the most likely path to a failure event of a safety-critical system. The key idea of AST is that stress testing can be formulated as a Partially Observable Markov Decision Process (POMDP), which enables reinforcement learning techniques to be used for finding failure events. Reinforcement learning algorithms can efficiently explore the search space and have been shown to scale to very large systems. We present applications of AST to find failures in various safety-critical systems including the aircraft collision avoidance systems, autonomous cars, and small unmanned aerial vehicles.

autonomous vehicles↗
NASA NTRS2020

A Reinforcement Learning Framework for Space Missions in Unknown Environments

A land-and-traverse mission to icy worlds such as Europa and Enceladus is challenging due to lack of prior knowledge regarding the terrain conditions. Previous work [1] showed that rovers with high degrees of freedom (DoF) can achieve robust traversal by leveraging redundant modes for mobility to counter terrain uncertainty (e.g. walking, driving, or inch-worming). This paper presents a generic and scalable reinforcement learning scheme for enabling on-board decision making on rovers to automatically switch between modes of traversal based on online performance feedback. The objective is to maximize energy efficiency, minimize operator input and successfully negotiate unstructured terrain conditions without relying on exhaustive prior knowledge. The proposed methodology is well grounded in the literature on reinforcement learning and has been adapted to address conformance to validation and verification requirements and JPL flight operations history of using per-sol prescribed sequences for a space mission.

Tavallali, Peyman↗
NASA NTRS2020

Scheduling Mission Reconfiguration for an Interferometry Synthetic Aperture Radar Using Deep Reinforcement Learning

This paper presents a method to intelligently adapt the baseline of a synthetic aperture radar based on Deep Rein- forcement Learning to help create plans for missions that use formation flight for Earth observation purposes. The main contribution of this paper is the initial results we have found from applying the tool to a toy mission: measuring the ver- tical structure of forests by using a synthetic aperture radar mounted on a formation of 7 satellites orbiting the Earth in a Sun Synchronous Orbit. We have found that with a reward function based on expected science return over time and fuel usage, the Deep Reinforcement Learning planner is able to create plans with positive scientific returns while minimizing fuel usage. We also find that fuel usage and collision avoid- ance planning is better done with traditional methods, as Deep Reinforcement Learning does not converge to optimal solutions.

Viros-i-Martin, Antoni↗
NASA NTRS2022

Effects of Debulking on the Fiber Microstructure and Void Distribution in Carbon Fiber Reinforced Plastics

Carbon Fiber Reinforced Plastics (CFRPs) are widely used due to their high stiffness to weight ratios. A common process manufacturers use to increase the strength to weight ratio is debulking. Debulking is the process of compacting a dry fibrous reinforcement prior to resin infusion. This process is meant to decrease the average inter-fiber distance, effectively increasing the fiber volume fraction of the sample. While this process is widely understood macroscopically its effects on fibrous microstructures have not yet been well characterized. The aim of this work is to compare the microstructures of three CFRP laminates, varying only the debulking step in the manufacturing process. High resolution serial sections of all three laminates were taken for analysis. Using these scans, the fiber positions were reconstructed. Statistical descriptors such as local fiber and void volume fractions, fiber orientation, and void distribution and morphology were then generated for each sample. Fiber clusters present within the material were identified and analyzed for each level of debulking applied. Using these descriptors, the effects of debulking on the morphology and organization of the composite microstructure was evaluated.

carbon fiber↗
NASA NTRS2026

Micromechanical Design of Carbon Nanotube Ribbon Reinforced Polymer Composite Materials

Lightweight materials are an important component of the design of aerospace structures. Carbon nanotube materials have been considered for this purpose due to the strength and stiffness of individual nanotubes, and the commercial availability of bulk formats such as fibers. These fibers can have a ribbon cross section which results in a different design space for their composites relative to traditional reinforcements which have a round cross section. This work applies brick-and-mortar micromechanical models and classical lamination theory with an inverse approach to investigate the design space of these composites. Using this approach, the influences of fiber geometry and axial and transverse mechanical properties are mapped. Finally, a sensitivity study is performed and the relative impacts of ±10% variations in the constituent material and geometric properties are ranked. Lamina axial moduli were found to range from a maximum of 3x to 1x minimum relative to a target quasi-isotropic laminate modulus depending on the anisotropy and shear modulus of the lamina. The fiber targets depended strongly on the fiber volume fraction in the lamina and the fiber axial modulus target was found to range from 4.8x to 3.2x the quasi-isotropic laminate target. The sensitivity analysis found that the largest driver of performance was the volume fraction, followed by the fiber axial modulus. While bio-based brick-and-mortar composites, such as nacre, can benefit from reinforcement aspect ratios above 10, for carbon nanotube ribbon (or carbon fiber)/polymer composites the sensitivity study indicated that the optimal cross-sectional aspect ratio was relatively smaller, potentially less than three.

Micromechanics↗
DOE OSTI2014

Rigid spine reinforced polymer microelectrode array probe and method of fabrication

A rigid spine-reinforced microelectrode array probe and fabrication method. The probe includes a flexible elongated probe body with conductive lines enclosed within a polymeric material. The conductive lines connect microelectrodes found near an insertion end of the probe to respective leads at a connector end of the probe. The probe also includes a rigid spine, such as made from titanium, fixedly attached to the probe body to structurally reinforce the probe body and enable the typically flexible probe body to penetrate and be inserted into tissue, such as neural tissue. By attaching or otherwise fabricating the rigid spine to connect to only an insertion section of the probe body, an integrally connected cable section of the probe body may remain flexible.

47 OTHER INSTRUMENTATION↗