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NASA NTRS2011

Computational Electromagnetic Modeling of SansEC(Trade Mark) Sensors

This paper describes the preliminary effort to apply computational design tools to aid in the development of an electromagnetic SansEC resonant sensor composite materials damage detection system. The computational methods and models employed on this research problem will evolve in complexity over time and will lead to the development of new computational methods and experimental sensor systems that demonstrate the capability to detect, diagnose, and monitor the damage of composite materials and structures on aerospace vehicles.

Smith, Laura J.↗

NASA NTRS1986

Multidisciplinary analysis of actively controlled large flexible spacecraft

The control of Flexible Structures (COFS) program has supported the development of an analysis capability at the Langley Research Center called the Integrated Multidisciplinary Analysis Tool (IMAT) which provides an efficient data storage and transfer capability among commercial computer codes to aid in the dynamic analysis of actively controlled structures. IMAT is a system of computer programs which transfers Computer-Aided-Design (CAD) configurations, structural finite element models, material property and stress information, structural and rigid-body dynamic model information, and linear system matrices for control law formulation among various commercial applications programs through a common database. Although general in its formulation, IMAT was developed specifically to aid in the evaluation of the structures. A description of the IMAT system and results of an application of the system are given.

Cooper, Paul A.↗

NASA NTRS1986

International SAMPE Symposium and Exhibition, 31st, Los Angeles, CA, April 7-10, 1986, Proceedings

The present conference on the development status of advanced structural materials considers topics arising in such areas as automated structural manufacturing, advanced material and structure design techniques, environmental effects on materials, composite matrix processing, computer modeling for materials and processes, materials development trends in Europe and in Japan, fiber and whisker reinforcement development status, and novel thermoplastic materials and their applications. Also discussed are pressure-sensitive adhesive systems, materials suitable for space applications, polyimide resin systems, electronic materials, novel resin chemistries, ceramic and metallic systems, and the impact performance of state-of-the-art materials.

Bauer, J. L.↗

NASA NTRSDate not supplied

Automation of the ICME Workflow Incorporating Material Digital Twins at Different Length Scales Within a Robust Information Management System

Recent successes in Integrated Computational Materials Engineering (ICME) have demonstrated the potential in designing fit-for-purpose materials for a given application in a cost and time efficient manner. However, the material design process must contain a level of automation in the material decision process, implementing some optimization algorithms, to truly enable the full benefits of ICME, particularly when considering materials at multiple length/time scales. In this work, we will demonstrate how the GRC ICME schema and Python framework automates a workflow that captures, analyzes, maintains, and disseminates the digital footprint in the context of tailoring resin material at the nanoscale of a woven composite Y-joint at the macroscale for an Aurora D8 double bubble fuselage. This digital footprint incorporates the interaction of both structural digital twins and material twins at various length scales.

Brandon L. Hearley↗

NASA NTRSDate not supplied

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↗

NASA NTRS2024

Automation of the ICME Workflow Incorporating Material Digital Twins at Different Length Scales Within a Robust Information Management System

Recent successes in Integrated Computational Materials Engineering (ICME) have demonstrated the potential in designing ‘fit-for-purpose’ materials for a given application in a cost and time efficient manner. However, the material design process must contain a level of judicious automation in the material decision process; that is implementing some optimization algorithms to truly enable the benefits of ICME, particularly when considering materials at multiple length and time scales. Furthermore, the ability to effectively store developed material models, experimental data used for validation, and link models at multiple length and time scales must be implemented to ensure traceability across the material design process, such that the data gathered can be leveraged towards efficient material design. To enable such an optimization scheme a robust framework must exist: (1) that can capture changes made at a given length scale, (2) automatically propagate changes upstream to the highest scale, and (3) evaluate the material’s performance at the structural level. In this work, a developed framework for tracking material changes, automatically running the necessary simulations to determine the properties at the next highest scale, and saving each iteration of the design process to maintain the application’s digital thread is presented for polymer matrix composites (PMCs). The Automated Information Management Across Organizations and Scales (AIMAOS) program offers users an interactive graphical user interface (GUI) for defining constituent materials, building lamina and laminates, and applying effective laminate properties to finite element and composite optimization third party software. At each length scale, the necessary input files are automatically written, and subsequent analysis tools are called to solve for effective properties at the next scale, which are then read by the AIMAOS tool and displayed to the user. As changes are made to the material at lower length scales, information is automatically propagated upstream to higher length scales, and changes made are automatically tracked and versioned to maintain traceability during the design process. The AIMAOS tools serves as the first step in enabling optimized design of composites from the nano to the macroscale for a given application.

Brandon L Hearley↗

NASA NTRS2019

2040 Vision Study: an Enlargement of Model Based Engineering

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will briefly review the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); associated critical gaps and actions to close those gaps; and major recommendations). The study, NASA CR 2018- 219771, envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that marries two non-mutually exclusive paradigms _ "design of the materials" (material scientist viewpoint) and "design with the materials" (structural analyst viewpoint) _ into a concurrent transformational paradigm that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT's hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness.

Arnold, Steven M.↗

NASA NTRS1988

Specialty three-dimensional finite element analysis codes

General purpose finite element computer codes that can model inelastic material behavior have been available for more than a decade. However, these codes have not been accurate enough for use in analyzing hot section engine components. To correct this problem, General Electric developed a series of nine new stand-alone computer codes for NASA. Because of the large temperature excursions associated with hot section engine components, these codes have been designed to accommodate broad variations in material behavior, including plasticity and creep. The capabilities of these computer codes are summarized.

Lackney, Joseph J.↗

NASA NTRSDate not supplied

2040 Vision Study: NASA’s T3 Implementation Activities

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. As a result, NASA’s Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will briefly review the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); associated critical gaps and actions to close those gaps; and major recommendations) and discuss NASA’s TTT implementation activities, with special emphasis on recent accomplishments. The study, NASA CR 2018- 219771, envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that marries two non-mutually exclusive paradigms – “design of the materials” (material scientist viewpoint) and “design with the materials” (structural analyst viewpoint) – into a concurrent transformational paradigm that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT’s hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United State's global competitiveness

Materials↗

NASA NTRS2017

Assessment of Intralaminar Progressive Damage and Failure Analysis Using an Efficient Evaluation Framework

Reducing the timeline for development and certification for composite structures has been a long standing objective of the aerospace industry. This timeline can be further exacerbated when attempting to integrate new fiber-reinforced composite materials due to the large number of testing required at every level of design. computational progressive damage and failure analysis (PDFA) attempts to mitigate this effect; however, new PDFA methods have been slow to be adopted in industry since material model evaluation techniques have not been fully defined. This study presents an efficient evaluation framework which uses a piecewise verification and validation (V&V) approach for PDFA methods. Specifically, the framework is applied to evaluate PDFA research codes within the context of intralaminar damage. Methods are incrementally taken through various V&V exercises specifically tailored to study PDFA intralaminar damage modeling capability. Finally, methods are evaluated against a defined set of success criteria to highlight successes and limitations.

Hyder, Imran↗

NASA NTRS1981

Coal conversion systems design and process modeling. Volume 1: Application of MPPR and Aspen computer models

The development of a coal gasification system design and mass and energy balance simulation program for the TVA and other similar facilities is described. The materials-process-product model (MPPM) and the advanced system for process engineering (ASPEN) computer program were selected from available steady state and dynamic models. The MPPM was selected to serve as the basis for development of system level design model structure because it provided the capability for process block material and energy balance and high-level systems sizing and costing. The ASPEN simulation serves as the basis for assessing detailed component models for the system design modeling program. The ASPEN components were analyzed to identify particular process blocks and data packages (physical properties) which could be extracted and used in the system design modeling program. While ASPEN physical properties calculation routines are capable of generating physical properties required for process simulation, not all required physical property data are available, and must be user-entered.

Source record↗

NASA NTRS1991

Design of a fast computer-based partial discharge diagnostic system

Partial discharges cause progressive deterioration of insulating materials working in high voltage conditions and may lead ultimately to insulator failure. Experimental findings indicate that deterioration increases with the number of discharges and is consequently proportional to the magnitude and frequency of the applied voltage. In order to obtain a better understanding of the mechanisms of deterioration produced by partial discharges, instrumentation capable of individual pulse resolution is required. A new computer-based partial discharge detection system was designed and constructed to conduct long duration tests on sample capacitors. This system is capable of recording large number of pulses without dead time and producing valuable information related to amplitude, polarity, and charge content of the discharges. The operation of the system is automatic and no human supervision is required during the testing stage. Ceramic capacitors were tested at high voltage in long duration tests. The obtained results indicated that the charge content of partial discharges shift towards high levels of charge as the level of deterioration in the capacitor increases.

Oliva, Jose R.↗

NASA NTRS1990

Artificial intelligence and design: Opportunities, research problems and directions

The issues of industrial productivity and economic competitiveness are of major significance in the U.S. at present. By advancing the science of design, and by creating a broad computer-based methodology for automating the design of artifacts and of industrial processes, we can attain dramatic improvements in productivity. It is our thesis that developments in computer science, especially in Artificial Intelligence (AI) and in related areas of advanced computing, provide us with a unique opportunity to push beyond the present level of computer aided automation technology and to attain substantial advances in the understanding and mechanization of design processes. To attain these goals, we need to build on top of the present state of AI, and to accelerate research and development in areas that are especially relevant to design problems of realistic complexity. We propose an approach to the special challenges in this area, which combines 'core work' in AI with the development of systems for handling significant design tasks. We discuss the general nature of design problems, the scientific issues involved in studying them with the help of AI approaches, and the methodological/technical issues that one must face in developing AI systems for handling advanced design tasks. Looking at basic work in AI from the perspective of design automation, we identify a number of research problems that need special attention. These include finding solution methods for handling multiple interacting goals, formation problems, problem decompositions, and redesign problems; choosing representations for design problems with emphasis on the concept of a design record; and developing approaches for the acquisition and structuring of domain knowledge with emphasis on finding useful approximations to domain theories. Progress in handling these research problems will have major impact both on our understanding of design processes and their automation, and also on several fundamental questions that are of intrinsic concern to AI. We present examples of current AI work on specific design tasks, and discuss new directions of research, both as extensions of current work and in the context of new design tasks where domain knowledge is either intractable or incomplete. The domains discussed include Digital Circuit Design, Mechanical Design of Rotational Transmissions, Design of Computer Architectures, Marine Design, Aircraft Design, and Design of Chemical Processes and Materials. Work in these domains is significant on technical grounds, and it is also important for economic and policy reasons.

Amarel, Saul↗

NASA NTRS1998

Arcjet Semi-Elliptic Nozzle Simulations and Validation in Support of TPS Testing

Much of the ground based testing of advanced thermal protection system (TPS) components for the X33 program is done in arc-heated wind tunnels such as those located in the Arc-Jet Complex at NASA Ames Research Center. These facilities are capable of simulating the high temperature, chemically reacting flow environment experienced by the vehicle during flight. This allows one to test critical design issues such as maximum reuse temperatures, seals, gaps, and increases in heating due to interfaces between different materials. Computational fluid dynamics (CFD) has evolved to the point where it now can be used in the vehicle design process for accurate and timely prediction of trajectory based aerothermal heating environments for re-entry vehicles. It can also be used for simulation of the flow environments in ground based facilities such as arcjets. By utilization of the same CFD code and solution methodology, the important differences between ground test and flight may be quantified. The goal of this paper is to utilize CFD to provide validated simulations of the flow environment in the NASA-Ames semi elliptic nozzle arcjet facilities. The validation of the ground simulations will come From comparison to existing calibration data. Specific tests in support of the X33 TPS test program will ilso be simulated. In this manner, the differences between the ground test simulation and the flight environment can be identified for a measure of ground test to flight traceability.

Loomis, Mark↗

NASA NTRS2008

New Insights into the Composition and Texture of Lunar Regolith Using Ultrafast Automated Electron-Beam Analysis

Sieved grain mounts of Apollo 16 drive tube samples have been examined using QEMSCAN - an innovative electron beam technology. By combining multiple energy-dispersive X-ray detectors, fully automated control, and off-line image processing, to produce digital mineral maps of particles exposed on polished surfaces, the result is an unprecedented quantity of mineralogical and petrographic data, on a particle-by-particle basis. Experimental analysis of four size fractions (500-250 microns, 150-90 microns, 75-45 microns and < 20 microns), prepared from two samples (64002,374 and 64002,262), has produced a robust and uniform dataset which allows for the quantification of mineralogy; texture; particle shape, size and density; and the digital classification of distinct particle types in each measured sample. These preliminary data show that there is a decrease in plagioclase modal content and an opposing increase in glass modal content, with decreasing particle size. These findings, together with data on trace phases (metals, sulphides, phosphates, and oxides), provide not only new insights into the make-up of lunar regolith at the Apollo 16 landing site, but also key physical parameters which can be used to design lunar simulants, and compute Figures of Merit for each material produced.

Rickman, Doug↗

NASA NTRS2011

Mars Exploration Rover Heatshield Observation Campaign

For the first time ever, engineers were able to observe a heatshield on the surface of another planet after a successful entry through the atmosphere. A three-week heatshield observation campaign was conducted in December 2004 after the Mars Exploration Rover Opportunity exited "Endurance Crater." By utilizing the rover's scientific instruments, data was collected to make a qualitative assessment of the performance of the heatshield. This data was gathered to gain a better understanding of how the heatshield performed during entry through the Martian atmosphere. In addition, this unprecedented look at the heatshield offered engineers the opportunity to assess if any unexpected anomalies occurred. Once a survey of the heatshield debris was completed, multiple targets of interest were chosen for the collection of imaging data. This data was then used to assess the char depth of the thermal protection material, which compared well with design and post-flight computational predictions. Extensive imaging data was collected and showed the main seal in pristine conditions, and no observable indications of structure overheating. Additionally, unexpected vehicle dynamics during the atmospheric entry were explained by the observation of thermal blanket remnants attached to the heatshield.

Thermal Protection System (TPS)↗

NASA NTRS2011

Mars Exploration Rover Heatshield Observation Campaign

Mars Exploration Rovers↗

NASA NTRSDate not supplied

Computationally Guided Development of Components for High Energy Density Solid-State Lithium-Sulfur Batteries

All electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria1. The performance metrics for eVTOL craft, such as specific energy, specific power, and safety, exceed those of electric automobiles by a factor of two to four. Current state-of-the-art (SOA) lithium-ion batteries are incapable of meeting the key performance criteria of energy and safety for eVTOL. Therefore, next generation advanced chemistries and designs must be developed to meet required performance metrics for electric aviation2. Beyond lithium-ion chemistries, such as lithium-sulfur, show promise in their high energy, while limitations exist in their power and cyclability due to low electrical conductivity and high intermediate solubility in organic liquid electrolytes. Several strategies to overcome the low electrical conductivity involve the use of selenium as a dopant in the active sulfur material, along with the incorporation of 2-dimensional electron-conducting holey-graphene to improve the composite cathodes electronic conductivity. Furthermore, combining this chemistry with a solid-electrolyte avoids the components’ dissolution issues3. However, the development of composite solid-state cathodes is non-trivial as several components must be intimately mixed so that the active component has sufficient access to both electrons and lithium ions to undergo full electrochemical conversion. Mathematical modeling of battery components can assist experimental design through a robust and rigorous combination of computational modeling techniques covering multiple length scales. The objective is to leverage modern computational materials methods combined with battery multiphysics tools to develop radically advanced compatible cathode and electrolyte materials, build and test solid state lithium-sulfur cells and packs. A NASA-based cross-organizational team of high-powered experts combined integrated computational predictive modeling, fundamental chemistry analysis, advanced material science, and battery cell development to tackle this very challenging, multidisciplinary problem. This presentation will show a multiscale computational modeling approach that has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM modeling targets the 1-10 µm scale structures and provides electromechanical and grain interactions for predictive design guidelines for the manufacturing of solid-state components. Parameters such as particle size and volume fraction of the constituent materials were modeled and experimentally fabricated to optimize electrochemical performance through improved microstructure design. Experimental feedback was provided through ionic and electronic conductivity assessment and structural analysis of developed materials and cell components.

battery↗