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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Investigating Local Buckling and Plastic Collapse in Multifunctional Sandwich Composite Cores using a Unit Cell Method

The primary goal of developing analytical models of composite sandwich cores has been to obtain simple expressions for elastic and failure response to improve the rapid analysis of composite structures. An earlier investigation by the authors was made to verify the accuracy of widely-used analytical models that calculate equivalent elastic moduli of a uniform homogeneous single layer of material in place of the complex honeycomb core properties in sandwich composites. This transformation of elastic properties permits a coarsening of the finite element model (FEM) of the core to a fraction of the computational cost in simulating the original complex core architecture. In addition, the core was assumed constructed of multi-layered isotropic walls to support potential additional functionality beyond simple load-carrying capability.

Erik Saether↗
NASA NTRS2016

Development of a Subcell Based Modeling Approach for Modeling the Architecturally Dependent Impact Response of Triaxially Braided Polymer Matrix Composites

Understanding the high velocity impact response of polymer matrix composites with complex architectures is critical to many aerospace applications, including engine fan blade containment systems where the structure must be able to completely contain fan blades in the event of a blade-out. Despite the benefits offered by these materials, the complex nature of textile composites presents a significant challenge for the prediction of deformation and damage under both quasi-static and impact loading conditions. The relatively large mesoscale repeating unit cell (in comparison to the size of structural components) causes the material to behave like a structure rather than a homogeneous material. Impact experiments conducted at NASA Glenn Research Center have shown the damage patterns to be a function of the underlying material architecture. Traditional computational techniques that involve modeling these materials using smeared homogeneous, orthotropic material properties at the macroscale result in simulated damage patterns that are a function of the structural geometry, but not the material architecture. In order to preserve heterogeneity at the highest length scale in a robust yet computationally efficient manner, and capture the architecturally dependent damage patterns, a previously-developed subcell modeling approach where the braided composite unit cell is approximated as a series of four adjacent laminated composites is utilized. This work discusses the implementation of the subcell methodology into the commercial transient dynamic finite element code LS-DYNA (Livermore Software Technology Corp.). Verification and validation studies are also presented, including simulation of the tensile response of straight-sided and notched quasi-static coupons composed of a T700/PR520 triaxially braided [0deg/60deg/-60deg] composite. Based on the results of the verification and validation studies, advantages and limitations of the methodology as well as plans for future work are discussed.

finite element method↗
NASA NTRS1987

Mapping a battlefield simulation onto message-passing parallel architectures

Perhaps the most critical problem in distributed simulation is that of mapping: without an effective mapping of workload to processors the speedup potential of parallel processing cannot be realized. Mapping a simulation onto a message-passing architecture is especially difficult when the computational workload dynamically changes as a function of time and space; this is exactly the situation faced by battlefield simulations. This paper studies an approach where the simulated battlefield domain is first partitioned into many regions of equal size; typically there are more regions than processors. The regions are then assigned to processors; a processor is responsible for performing all simulation activity associated with the regions. The assignment algorithm is quite simple and attempts to balance load by exploiting locality of workload intensity. The performance of this technique is studied on a simple battlefield simulation implemented on the Flex/32 multiprocessor. Measurements show that the proposed method achieves reasonable processor efficiencies. Furthermore, the method shows promise for use in dynamic remapping of the simulation.

Nicol, David M.↗
NASA NTRS2014

Direct Energy Conversion for Nuclear Propulsion at Low Specific Mass

The project will continue the FY13 JSC IR&D (October-2012 to September-2013) effort in Travelling Wave Direct Energy Conversion (TWDEC) in order to demonstrate its potential as the core of a high potential, game-changing, in-space propulsion technology. The TWDEC concept converts particle beam energy into radio frequency (RF) alternating current electrical power, such as can be used to heat the propellant in a plasma thruster. In a more advanced concept (explored in the Phase 1 NIAC project), the TWDEC could also be utilized to condition the particle beam such that it may transfer directed kinetic energy to a target propellant plasma for the purpose of increasing thrust and optimizing the specific impulse. The overall scope of the FY13 first-year effort was to build on both the 2012 Phase 1 NIAC research and the analysis and test results produced by Japanese researchers over the past twenty years to assess the potential for spacecraft propulsion applications. The primary objective of the FY13 effort was to create particle-in-cell computer simulations of a TWDEC. Other objectives included construction of a breadboard TWDEC test article, preliminary test calibration of the simulations, and construction of first order power system models to feed into mission architecture analyses with COPERNICUS tools. Due to funding cuts resulting from the FY13 sequestration, only the computer simulations and assembly of the breadboard test article were completed. The simulations, however, are of unprecedented flexibility and precision and were presented at the 2013 AIAA Joint Propulsion Conference. Also, the assembled test article will provide an ion current density two orders of magnitude above that available in previous Japanese experiments, thus enabling the first direct measurements of power generation from a TWDEC for FY14. The proposed FY14 effort will use the test article for experimental validation of the computer simulations and thus complete to a greater fidelity the mission analysis products originally conceived for FY13.

Scott, John H.↗
NASA NTRS2000

Geoid Recovery Using Geophysical Inverse Theory Applied to Satellite to Satellite Tracking Data

This report describes a new method for determination of the geopotential, or the equivalent geoid. It is based on Satellite-to-Satellite Tracking (SST) of two co-orbiting low earth satellites separated by a few hundred kilometers. The analysis is aimed at the GRACE Mission, though it is generally applicable to any SST data. It is proposed that the SST be viewed as a mapping mission. That is, the result will be maps of the geoid or gravity, as contrasted with determination of spherical harmonics or Fourier coefficients. A method has been developed, based on Geophysical Inverse Theory (GIT), that can provide maps at a prescribed (desired) resolution and the corresponding error map from the SST data. This computation can be done area by area avoiding simultaneous recovery of all the geopotential information. The necessary elements of potential theory, celestial mechanics, and Geophysical Inverse Theory are described, a computation architecture is described, and the results of several simulations presented. Centimeter accuracy geoids with 50 to 100 km resolution can be recovered with a 30 to 60 day mission.

Gaposchkin, E. M.↗
NASA NTRS2022

Predicting Unreinforced Fabric Mechanical Behavior with Recurrent Neural Networks

Unreinforced woven fabrics are widely employed in various high-performance applications, including parachute deployment systems, airbags, and ballistic armor. The analysis of such materials is inherently complex due to the multiscale structure of these materials, and the dependence of macroscale behavior on changes that occur at lower scales. Previously, NASA’s Multiscale Analysis Tool (NASMAT) showed its capability in predicting unreinforced fabric behavior at the macroscale by capturing finite rotations that occur at the mesoscale. Though effective, the tool can face high computational cost for large, complex problems, motivating the need for the development of a surrogate model that can capture the same behavior. A recurrent neural network (RNN) was developed and trained on virtual NASMAT data to mimic the physics-based solutions while improving the computational runtime. The architecture of the RNN to best simulate the fabric behavior was carefully crafted based on heuristic knowledge of predicting physics-based temporal data, manual hyperparameter case studies, and Hyperband optimization.. The resultant model was able to predict a variety of stress-strain curves for fabrics with different mesoscale geometries, and was further validated by comparing to experimental data for the K706 style Kevlar plain-weave fabric, demonstrating the ability of the model to effectively capture the geometric changes in the fabric without explicitly calculating them, as is done in NASMAT. Furthermore, the tool showed its ability to improve on the runtime by a factor of 10 for fabric solutions compared to the multiscale tool, which would further enable the simulation of complex loading scenarios on unreinforced fabrics.

Fabric↗
NASA NTRS1993

Computational Controls Workstation: Algorithms and hardware

The Computational Controls Workstation provides an integrated environment for the modeling, simulation, and analysis of Space Station dynamics and control. Using highly efficient computational algorithms combined with a fast parallel processing architecture, the workstation makes real-time simulation of flexible body models of the Space Station possible. A consistent, user-friendly interface and state-of-the-art post-processing options are combined with powerful analysis tools and model databases to provide users with a complete environment for Space Station dynamics and control analysis. The software tools available include a solid modeler, graphical data entry tool, O(n) algorithm-based multi-flexible body simulation, and 2D/3D post-processors. This paper describes the architecture of the workstation while a companion paper describes performance and user perspectives.

Venugopal, R.↗
NASA NTRS2003

Mission Simulation Facility: Simulation Support for Autonomy Development

The Mission Simulation Facility (MSF) supports research in autonomy technology for planetary exploration vehicles. Using HLA (High Level Architecture) across distributed computers, the MSF connects users autonomy algorithms with provided or third-party simulations of robotic vehicles and planetary surface environments, including onboard components and scientific instruments. Simulation fidelity is variable to meet changing needs as autonomy technology advances in Technical Readiness Level (TRL). A virtual robot operating in a virtual environment offers numerous advantages over actual hardware, including availability, simplicity, and risk mitigation. The MSF is in use by researchers at NASA Ames Research Center (ARC) and has demonstrated basic functionality. Continuing work will support the needs of a broader user base.

Pisanich, Greg↗
NASA NTRS1994

Cluster Computation of Flight Reynolds Number Flows

The performance of a workstation cluster used for the solution of the Reynolds-averaged Navier-Stokes equations is compared with a conventional vector supercomputer architecture. The application simulation of the steady flowfield about a transonic transport was computed using an implicit diagonal scheme in an overset mesh framework. Static load balancing was used, while coarse grain decomposition was achieved by solution of a grid zone per processor. Price/performance ratios are estimated for several scenarios in which such clusters may be utilized.

Atwood, Christopher A.↗
NASA NTRS2003

HYDRA : High-speed simulation architecture for precision spacecraft formation simulation

e Hierarchical Distributed Reconfigurable Architecture- is a scalable simulation architecture that provides flexibility and ease-of-use which take advantage of modern computation and communication hardware. It also provides the ability to implement distributed - or workstation - based simulations and high-fidelity real-time simulation from a common core. Originally designed to serve as a research platform for examining fundamental challenges in formation flying simulation for future space missions, it is also finding use in other missions and applications, all of which can take advantage of the underlying Object-Oriented structure to easily produce distributed simulations. Hydra automates the process of connecting disparate simulation components (Hydra Clients) through a client server architecture that uses high-level descriptions of data associated with each client to find and forge desirable connections (Hydra Services) at run time. Services communicate through the use of Connectors, which abstract messaging to provide single-interface access to any desired communication protocol, such as from shared-memory message passing to TCP/IP to ACE and COBRA. Hydra shares many features with the HLA, although providing more flexibility in connectivity services and behavior overriding.

formation flying↗
NASA NTRS1991

Computer-aided system design

A technique has been developed for combining features of a systems architecture design and assessment tool and a software development tool. This technique reduces simulation development time and expands simulation detail. The Architecture Design and Assessment System (ADAS), developed at the Research Triangle Institute, is a set of computer-assisted engineering tools for the design and analysis of computer systems. The ADAS system is based on directed graph concepts and supports the synthesis and analysis of software algorithms mapped to candidate hardware implementations. Greater simulation detail is provided by the ADAS functional simulator. With the functional simulator, programs written in either Ada or C can be used to provide a detailed description of graph nodes. A Computer-Aided Software Engineering tool developed at the Charles Stark Draper Laboratory (CSDL CASE) automatically generates Ada or C code from engineering block diagram specifications designed with an interactive graphical interface. A technique to use the tools together has been developed, which further automates the design process.

Walker, Carrie K.↗
NASA NTRS1997

The Application of New Software Technology to the Architecture of the National Cycle Program

As part of the Numerical Propulsion System Simulation (NPSS) effort of NASA Lewis in conjunction with the United States aeropropulsion industry, a new system simulation framework, the National Cycle Program (NCP), capable of combining existing empirical engine models with new detailed component-based computational models is being developed. The software architecture of the NCP program involves a generalized object- oriented framework and a base-set of engine component models along with supporting tool kits which will support engine simulation in a distributed environment. As the models are extended to contain two and three dimensions the computing load increases rapidly and it is intended that this load be distributed across multiple work stations executing concurrently in order to get acceptably fast results. The research carried out was directed toward performance analysis of the distributed object system. More specifically, the performance of the actor-based distributed object design I created earlier was desired. To this end, the research was directed toward the design and implementation of suitable performance-analysis techniques and software to demonstrate those techniques. There were three specific results which are reported in two separate reports submitted separately as NASA Technical Memoranda. The results are: (1) Design, implementation, and testing of a performance analysis program for a set of active objects (actor based objects) which allowed the individual actors to be assigned to arbitrary processes on an arbitrary set of machines. (2) The global-balance-equation approach has the fundamental limitation that the number of equations increases exponentially with the number of actors. Hence, unlike many approximate approaches to this problem, the nearest-neighbor approach allows checking of the solution and an estimate of the error. The technique was demonstrated in a prototype analysis program as part of this research. The results of the program were checked against the global-balance solution discussed above. Late during the grant, a much better approximation was developed and this is discussed in result below. As a consequence, a proposal was submitted to continue the research by developing the new approximation including development of a complete program from the prototype. (3) The source of approximation in the nearest-neighbor algorithm is the requirement for estimating some joint probabilities from some marginal distributions. A completely ad hoc estimate was used in the prototype.

Schoeffler, James D.↗
NASA NTRS1972

Space Ultrareliable Modular Computer (SUMC) instruction simulator

The design principles, description, functional operation, and recommended expansion and enhancements are presented for the Space Ultrareliable Modular Computer interpretive simulator. Included as appendices are the user's manual, program module descriptions, target instruction descriptions, simulator source program listing, and a sample program printout. In discussing the design and operation of the simulator, the key problems involving host computer independence and target computer architectural scope are brought into focus.

Curran, R. T.↗
NASA NTRS1977

Computers for real time flight simulation: A market survey

An extensive computer market survey was made to determine those available systems suitable for current and future flight simulation studies at Ames Research Center. The primary requirement is for the computation of relatively high frequency content (5 Hz) math models representing powered lift flight vehicles. The Rotor Systems Research Aircraft (RSRA) was used as a benchmark vehicle for computation comparison studies. The general nature of helicopter simulations and a description of the benchmark model are presented, and some of the sources of simulation difficulties are examined. A description of various applicable computer architectures is presented, along with detailed discussions of leading candidate systems and comparisons between them.

Bekey, G. A.↗
NASA NTRS1990

An ICAI architecture for troubleshooting in complex, dynamic systems

Ahab, an intelligent computer-aided instruction (ICAI) program, illustrates an architecture for simulator-based ICAI programs to teach troubleshooting in complex, dynamic environments. The architecture posits three elements of a computerized instructor: the task model, the student model, and the instructional module. The task model is a prescriptive model of expert performance that uses symptomatic and topographic search strategies to provide students with directed problem-solving aids. The student model is a descriptive model of student performance in the context of the task model. This student model compares the student and task models, critiques student performance, and provides interactive performance feedback. The instructional module coordinates information presented by the instructional media, the task model, and the student model so that each student receives individualized instruction. Concept and metaconcept knowledge that supports these elements is contained in frames and production rules, respectively. The results of an experimental evaluation are discussed. They support the hypothesis that training with an adaptive online system built using the Ahab architecture produces better performance than training using simulator practice alone, at least with unfamiliar problems. It is not sufficient to develop an expert strategy and present it to students using offline materials. The training is most effective if it adapts to individual student needs.

Fath, Janet L.↗
NASA NTRS2012

Variable Vector Countermeasure Suit (V2Suit) for Space Habitation and Exploration

The "Variable Vector Countermeasure Suit (V2Suit) for Space Habitation and Exploration" is a visionary system concept that will revolutionize space missions by providing a platform for integrating sensors and actuators with daily astronaut intravehicular activities to improve human health and performance. The V2Suit uses control moment gyroscopes (CMGs) within a miniaturized module placed on body segments to provide a "viscous resistance" during movements and a countermeasure to the sensorimotor and musculoskeletal adaptation performance decrements that manifest themselves while living and working in microgravity and during gravitational transitions during long-duration spaceflight, including post-flight recovery and rehabilitation. Through an integrated design, system initialization, and control systems approach the V2Suit is capable of generating this "viscous resistance" along an arbitrarily specified direction of "down." When movements are made, for example, parallel to that "down" direction a resistance is applied, and when the movement is perpendicular to that direction no resistance is applied. The V2Suit proposes to be a countermeasure to this spaceflight-related adaptation and de-conditioning and the unique sensorimotor characteristics associated with living and working in 0-G, which are critical for future long-duration space missions.This NIAC Phase I project focused on detailing several aspects of the V2Suit concept, including human-system integration, system architecture, computer aided design (CAD) modeling, and closed-loop simulation and analysis. In addition, early-stage breadboard prototyping of several aspects of the V2Suit system modules enabled characterization of expected performance and identified areas for further research and development to enable operational implementation of the V2Suit. In particular, potential challenges with integration of commercial-off-the-shelf components were identified. The key enabler for operational use and adoption of the V2Suit is a low-profile body worn form factor that does not interfere with normal, everyday movements and interfaces adequately with the body as to provide the generated gyroscopic torque for the perceptions of movement with a "viscous resistance." These aspects were investigated through mockups using a life-size mannequin, and through body attachment mechanisms on the breadboard prototype. Through the evaluation and investigation of commercially-available components, as well as an identification of desirable form factors, CAD models of the V2Suit modules were developed. These models included all of the required elements and spin motors, flywheel masses, gimbal motors, slip rings, inertial measurement units, motor controllers, and the required mounting brackets/hardware and cabling. The configuration and orientation of the control moment gyroscopes (CMGs) was specified according to results from the modeling, simulation and analysis. Two revisions of the CAD model were investigated through closed-loop simulation of the CMGs, and their ability to generate a resultant reaction force during movement and null undesirable torques due to changes in the direction of the angular momentum vector as a result of the normal body movements.

space missions↗
NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗
NASA NTRS1991

Simulating motivated cognition

A research effort to develop a sophisticated computer model of human behavior is described. A computer framework of motivated cognition was developed. Motivated cognition focuses on the motivations or affects that provide the context and drive in human cognition and decision making. A conceptual architecture of the human decision-making approach from the perspective of information processing in the human brain is developed in diagrammatic form. A preliminary version of such a diagram is presented. This architecture is then used as a vehicle for successfully constructing a computer program simulation Dweck and Leggett's findings that relate how an individual's implicit theories orient them toward particular goals, with resultant cognitions, affects, and behavior.

Gevarter, William B.↗