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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 37 records · Page 2

Adhesive-bonded scarf and stepped-lap joints

Continuum mechanics solutions are derived for the static load-carrying capacity of scarf and stepped-lap adhesive-bonded joints. The analyses account for adhesive plasticity and adherend stiffness imbalance and thermal mismatch. The scarf joint solutions include a simple algebraic formula which serves as a close lower bound, within a small fraction of a per cent of the true answer for most practical geometries and materials. Digital computer programs were developed and, for the stepped-lap joints, the critical adherend and adhesive stresses are computed for each step. The scarf joint solutions exhibit grossly different behavior from that for double-lap joints for long overlaps inasmuch as that the potential bond shear strength continues to increase with indefinitely long overlaps on the scarf joints. The stepped-lap joint solutions exhibit some characteristics of both the scarf and double-lap joints. The stepped-lap computer program handles arbitrary (different) step lengths and thickness and the solutions obtained have clarified potentially weak design details and the remedies. The program has been used effectively to optimize the joint proportions.

Hart-Smith, L. J.↗

Evaluation of the airborne visible-infrared imaging spectrometer for mapping subtle lithological variation

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), flown aboard the NASA ER-2 aircraft in 1987 and 1989, used four linear arrays and four individual spectrometers to collect data simultaneously from the 224 bands in a scanned 614 pixel-wide swath perpendicular to the aircraft direction. The research had two goals. One was to evaluate the AVIRIS data. The other was to look at the subtle lithological variation at the two test sites to develop a better understanding of the regional geology and surficial processes. The geometric characteristics of the data, adequacy of the spatial resolution, and adequacy of the spectral sampling interval are evaluated. Geologic differences at the test sites were mapped. They included lithological variation caused by primary sedimentary layering, facies variation, and weathering; and subtle mineralogical differences caused by hydrothermal alterations of igneous and sedimentary rocks. The investigation used laboratory, field, and aircraft spectral measurements; known properties of geological materials; digital image processing and spectrum processing techniques; and field geologic data to evaluate the selected characteristics of the AVIRIS data.

Kruse, Fred A.↗

Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS)

To meet the needs of future deep space exploration, NASA is interested in large-scale hardware systems in the agency’s thrust areas of solar power, communications, habitats and science interests. Scalable in-space assembly of physical systems is critical to massless exploration and in-space reliance goals. The ARMADAS project demonstrates the autonomous assembly of digital materials and structures. This provides automation technologies with potential for meeting long duration and deep space infrastructure needs, such as construction and maintenance of long duration spaceport, surface infrastructure, and habitat scale systems. Project demonstrations to date include a system that can fit into a small satellite-sized payload, which automatically assembles into primary structures, such as a small habitat module or array/antenna, using onboard robotic assemblers.

In Space Assembly↗

Study of random process theory aids digital data processing

Study of techniques for all random process technology, including stationary, nonstationary, and Gaussian bivariate, aids digital data processing. It presents material on digital filtering, correlation function, optimal spectral smoothing, deterministic data processing, and nonstationary spectrum and correlation analyses.

Bordner, G. W.↗

Digital flight controls

Materials illustrating a presentation on digital flight controls for electric flight systems are presented. System architecture and design criteria are outlined, and components described.

Hall, J. C.↗

Digital flight controls

Materials illustrating the presentation on digital flight controls are presented. Technology issues, the role of NASA, and steps in the development of flight controls are outlined.

Dove, B.↗

Analysis of the Measurement and Modeling of a Digital Inverter Based on a Ferroelectric Transistor

The use of ferroelectric materials for digital memory devices is widely researched and implemented, but ferroelectric devices also possess unique characteristics that make them have interesting and useful properties in digital circuits. Because ferroelectric transistors possess the properties of hysteresis and nonlinearity, a digital inverter containing a FeFET has very different characteristics than one with a traditional FET. This paper characterizes the properties of the measurement and modeling of a FeFET based digital inverter. The circuit was set up using discrete FeFETs. The purpose of this circuit was not to produce a practical integrated circuit that could be inserted directly into existing digital circuits, but to explore the properties and characteristics of such a device and to look at possible future uses. Input and output characteristics are presented, as well as timing measurements. Comparisons are made between the ferroelectric device and the properties of a standard digital inverter. Potential benefits and possible uses of such a device are presented.

MacLeod, Todd C.↗

Managing the Digital Thread for Structural Applications With Fit for Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.

Digital Transformation↗

Capacitive connectors for digital-data lines

Proposed connector consisting of twin metal films separated by thin layers of insulating material transmits digital pulses capacitively. There is no direct contact between metal films; therefore, there is no ohmic contact drop and no wear when connections are changed. Since metal films are sealed in insulating material, there is no corrosion from exposure to atmosphere.

Studer, P. A.↗

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗

Cell Libraries

A NASA contract led to the development of faster and more energy efficient semiconductor materials for digital integrated circuits. Gallium arsenide (GaAs) conducts electrons 4-6 times faster than silicon and uses less power at frequencies above 100-150 megahertz. However, the material is expensive, brittle, fragile and has lacked computer automated engineering tools to solve this problem. Systems & Processes Engineering Corporation (SPEC) developed a series of GaAs cell libraries for cell layout, design rule checking, logic synthesis, placement and routing, simulation and chip assembly. The system is marketed by Compare Design Automation.

Source record↗

Modeling of Tunable Elastic Ultralight Aircraft

Aircraft weight is one of the most critical factors in the design and operation of modern vehicles. The ability to integrate ultra-light materials into the primary load bearing structures has the potential to reduce aircraft weight significantly. Ultralight materials tend to be lattice-based meta-materials that are difficult and computationally expensive to model. One of the advantages of meta-materials is to be able to tune or "program" their bulk material properties through the placement of heterogeneous components in the material. A large amount of time devoted to the simulation in the development time for the tuning of the material can be a barrier to the adoption of large scale lattice materials. In this paper, we present a workflow and analysis tool-set to provide first-order estimates for rapid development of engineered lattice materials for aerospace applications. We present results for estimating the displacement and maximum structural stresses.

cellular solids↗

Crystal growth of ZnSe and related ternary compound semiconductors by physical vapor transport

The materials to be investigated are ZnSe and related ternary semiconducting alloys (e.g., ZnS(x)Se(1-x), ZnTe(x)Se(1-x), and Zn(1-x)Cd(x)Se). These materials are useful for opto-electronic applications such as high efficient light emitting diodes and low power threshold and high temperature lasers in the blue-green region of the visible spectrum. The recent demonstration of its optical bistable properties also makes ZnSe a possible candidate material for digital optical computers. The investigation consists of an extensive ground-based study followed by flight experimentation, and involves both experimental and theoretical work. The objectives of the ground-based work are to establish the characteristics of the crystals grown on Earth as a basis for subsequent comparative evaluations of the crystals grown in a low gravity environment and to obtain the experimental data and perform the analyses required to define the optimum parameters for the flight experiments. During the six months of the Preliminary Definition Phase, the research efforts were concentrated on the binary compound ZnSe - the purification of starting materials of Se by zone refining, the synthesis of ZnSe starting materials, the heat treatments of the starting materials, the vapor transport rate measurements, the vapor partial pressure measurements of ZnSe, the crystal growth of ZnSe by physical vapor transport, and various characterization on the grown ZnSe crystals.

Su, Ching-Hua↗

Nondestructive Evaluation for the Space Shuttle's Wing Leading Edge

The loss of the Space Shuttle Columbia highlighted concerns about the integrity of the Shuttle's thermal protection system, which includes Reinforced Carbon-Carbon (RCC) on the leading edge. This led NASA to investigate nondestructive evaluation (NDE) methods for certifying the integrity of the Shuttle's wing leading edge. That investigation was performed simultaneously with a large study conducted to understand the impact damage caused by errant debris. Among the many advanced NDE methods investigated for applicability to the RCC material, advanced digital radiography, high resolution computed tomography, thermography, ultrasound, acoustic emission and eddy current systems have demonstrated the maturity and success for application to the Shuttle RCC panels. For the purposes of evaluating the RCC panels while they are installed on the orbiters, thermographic detection incorporating principal component analysis (PCA) and eddy current array scanning systems demonstrated the ability to measure the RCC panels from one side only and to detect several flaw types of concern. These systems were field tested at Kennedy Space Center (KSC) and at several locations where impact testing was being conducted. Another advanced method that NASA has been investigating is an automated acoustic based detection system. Such a system would be based in part on methods developed over the years for acoustic emission testing. Impact sensing has been demonstrated through numerous impact tests on both reinforced carbon-carbon (RCC) leading edge materials as well as Shuttle tile materials on representative aluminum wing structures. A variety of impact materials and conditions have been evaluated including foam, ice, and ablator materials at ascent velocities as well as simulated hypervelocity micrometeoroid and orbital debris impacts. These tests have successfully demonstrated the capability to detect and localize impact events on Shuttle's wing structures. A first generation impact sensing system has been designed for the next Shuttle flight and is undergoing final evaluation for deployment on the Shuttle's first return to flight. This system will employ wireless accelerometer sensors that were qualified for other applications on previous Shuttle flights. These sensors will be deployed on the wing's leading edge to detect impacts on the RCC leading edge panels. The application of these methods will help to insure the continued integrity of the Shuttle wing's leading edge system as the Shuttle flights resume and until their retirement.

Eric I Madaras↗

Aircraft jolts from lightning bolts

The trend toward the use of composite materials and digital electronics has renewed the need to quantify the effects of lightning strikes to airplanes, since composite structures do not provide shielding equivalent to that of metal aircraft, and digital systems are potentially more susceptible to upset by electrical transients than are analog electronic systems. A research program, called the Storm Hazards Program, has been run by the National Aeronautics and Space Administration (NASA) for the past eight years and has provided the first statistically significant measurements of the electromagnetic interaction between lightning and aircraft. A NASA-owned F-106B airplane has been flown through thunderstorms about 1500 times at altitudes between 5,000 and 40,000 feet (1,500 to 12,000 meters). The airplane, lightning-hardened and outfitted with special instruments, was hit by lightning 714 times. The types of measurements made and the results are described.

Pitts, Felix L.↗