Search NASA⌕ Search

SEARCH · Search NASA

Results for “aerospace computing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

NASA and CFD - Making investments for the future

From a NASA perspective, CFD is a new tool for fluid flow simulation and prediction with virtually none of the inherent limitations of other ground-based simulation techniques. A primary goal of NASA's CFD research program is to develop efficient and accurate computational techniques for utilization in the design and analysis of aerospace vehicles. The program in algorithm development has systematically progressed through the hierarchy of engineering simplifications of the Navier-Stokes equations, starting with the inviscid formulations such as transonic small disturbance, full potential, and Euler.

Hessenius, Kristin A.↗
NASA NTRS1993

Probabilistic material degradation under high temperature, fatigue, and creep

A methodology has been developed and embodied in two computer codes for quantitatively characterizing the material strength degradation of aerospace propulsion system structural components that are subjected to various random effects over the course of their service lives. The codes, PROMISS and PROMISC, constitute a material-resistance model that is used in the NESSUS aerospace structural-reliability program. NESSUS addresses the service life-reducing effects of high temperature, mechanical fatigue, and creep.

Boyce, L.↗
NASA NTRS1995

At the intersection of automation and culture

The crash of an automated passenger jet at Nagoya, Japan, in 1995, is used as an example of crew error in using automatic systems. Automation provides pilots with the ability to perform tasks in various ways. National culture is cited as a factor that affects how a pilot and crew interact with each other and equipment.

NASA Discipline Space Human Factors↗
NASA NTRS1997

Developing Interim Systems

One of the recent challenges in the aerospace industry has been to smoothly transition operations-oriented computer systems to meet increasing demands on smaller budgets. Sometimes the best solution is not affordable, but the current situation is equally untenable.

limitations resource-scavenging↗
NASA NTRS2010

Tools Automate Spacecraft Testing, Operation

"NASA began the Small Explorer (SMEX) program to develop spacecraft to advance astrophysics and space physics. As one of the entities supporting software development at Goddard Space Flight Center, the Hammers Company Inc. (tHC Inc.), of Greenbelt, Maryland, developed the Integrated Test and Operations System to support SMEX. Later, the company received additional Small Business Innovation Research (SBIR) funding from Goddard for a tool to facilitate the development of flight software called VirtualSat. NASA uses the tools to support 15 satellites, and the aerospace industry is using them to develop science instruments, spacecraft computer systems, and navigation and control software."

Source record↗
NASA NTRS2017

Evaluation of Full Reynolds Stress Turbulence Models in FUN3D

Full seven-equation Reynolds stress turbulence models are promising tools for today’s aerospace technology challenges. This paper examines two such models for computing challenging turbulent flows including shock-wave boundary layer interactions, separation and mixing layers. The Wilcox and the SSG/LRR full second-moment Reynolds stress models have been implemented into the FUN3D (Fully Unstructured Navier-Stokes Three Dimensional) unstructured Navier-Stokes code and were evaluated for four problems: a transonic two-dimensional diffuser, a supersonic axisymmetric compression corner, a compressible planar shear layer, and a subsonic axisymmetric jet. Simulation results are compared with experimental data and results computed using the more commonly used Spalart-Allmaras (SA) one-equation and the Menter Shear Stress Transport (SST-V) two-equation turbulence models.

reynolds averaging↗
NASA NTRS2019

Modern Modal Testing: A Cautionary Tale

Over the past 50 years, great advances have been achieved in both analytical modal analysis (i.e. finite element models and analysis) and experimental modal analysis (i.e. modal testing) in aerospace and other fields. With the advent of more powerful computers, higher performance instrumentation and data acquisition systems, and powerful linear modal extraction tools, analysts and test engineers have a breadth and depth of technical resources only dreamed of by our predecessors. However, some observed recent trends indicate that hard lessons learned are being forgotten or ignored, and possibly fundamental concepts are not being understood. These trends have the potential of leading to the degradation of the quality of and confidence in both analytical and test results. These trends are a making of our own doing, and directly related to having ever more powerful computers, programmatic budgetary pressures to limit analysis and testing, and technical capital loss due to the retirement of the senior component of a bimodal workforce. This paper endeavors to highlight some of the most important lessons learned, common pitfalls to hopefully avoid, and potential steps that may be taken to help reverse this trend.

bimodal workforce↗
NASA NTRS2019

Modern Modal Testing: A Cautionary Tale IMAC XXVII

Over the past 50 years, great advances have been achieved in both analytical modal analysis (i.e. finite element models and analysis) and experimental modal analysis (i.e. modal testing) in aerospace and other fields. With the advent of more powerful computers, higher performance instrumentation and data acquisition systems, and powerful linear modal extraction tools, analysts and test engineers have a breadth and depth of technical resources only dreamed of by our predecessors. However, some observed recent trends indicate that hard lessons learned are being forgotten or ignored, and possibly fundamental concepts are not being understood. These trends have the potential of leading to the degradation of the quality of and confidence in both analytical and test results. These trends are a making of our own doing, and directly related to having ever more powerful computers, programmatic budgetary pressures to limit analysis and testing, and technical capital loss due to the retirement of the senior component of a bimodal workforce. This paper endeavors to highlight some of the most important lessons learned, common pitfalls to hopefully avoid, and potential steps that may be taken to help reverse this trend.

bimodal workforce↗
NASA NTRS2018

Optimization of Elastodynamic Finite Integration Technique on Intel Xeon Phi Knights Landing Processors

This work describes the development and optimization of an implementation of an isotropic elastodynamic finite integration technique (EFIT) code for parallelized computation on Intel Knights Landing (KNL) hardware. EFIT is a numerical approach resulting in standard staggered-grid finite difference equations for the elastodynamic equations of motion to simulate bulk waves is solids. The computationally efficient simulation of elastodynamic wave propagation and interactions in aerospace materials is of high-interest in the fields of nondestructive evaluation (NDE) and structural health monitoring (SHM). Ultrasonic inspection uses an ultrasonic signal, generated at the surface of the material/structure via use of a piezoelectric transducer, to propagate sound waves into the material where it interacts with any existing defects, as well as with structural boundaries and any material inhomogeneity. Reflections from defects and boundaries are then measured by a transducer. Realistic ultrasound simulation tools can significantly aid the development and optimization of inspection techniques and can assist in the interpretation of experimental data. The optimization of an elastodynamics simulation code for the KNL Many Integrated Core processor was performed. The optimization focused on data locality and vectorization. Results show that tiling of the data to exploit the cache behavior and allow for significant utilization of the KNL hardware. The MPI implementation allows for a scalable implementation enabling large problems to be simulated. The model results were validated against theoretical dispersion curves to within 2% of the group velocity, and within 0.5% of the phase velocity of the A0 mode. Aggressive use of tiling, threading, and vectorization techniques allowed for dramatically improved time to solution.

William C. Schneck↗
NASA NTRSDate not supplied

Extended Duration: The SIRIUS 21 Crew Perspective

The SIRIUS (Scientific International Research In a Unique terrestrial Station) missions represent a collaborative effort between NASA and Russia’s Institute for Biomedical Problems (IBMP) to conduct a series of long duration isolation and confinement spaceflight analog missions. Three missions of 17-day, 4-month, and 8-month duration (SIRIUS 17, 19, and 21) have been completed at IBMP’s Ground-Based Experimental Complex / Nazemnyy eksperimental'nyy kompleks (NEK) in Moscow, Russia. The international SIRIUS 21 crew comprising representatives from the United States, United Arab Emirates and Russia recently completed the 8-month analog lunar mission. The extended duration mission included simulated lunar transit, orbital, and surface operations with corresponding deep space communication delay, during which the crew participated in nearly 70 studies, eight of which were sponsored by NASA’s Human Research Program. The studies examined the effect of isolation and confinement on the behavioral health of research subjects, and investigated medical countermeasures, team performance, crew dynamics, crew autonomy, food system risks, consequences of confinement and associated physiological stressors. SIRIUS 21 crewmembers also participated in operational tasks such as Rover and CubeSat assembly, simulated lunar sample assessment, VR activities, robotic arm training, environmental systems monitoring, exercise, greenhouse maintenance and 3D printing. Communication with Mission Control was limited to 30-minute periods every two hours. Since access to the internet and email was restricted, simulated ground support provided the Crew’s primary source of daily news and mission information. This panel discussion will include presentations from the US SIRIUS 21 crewmembers – William Brown and Ashley Kowalski – about their experience participating in the mission and science. A facilitated question and answer session will follow with attendees encouraged to ask questions and join in discussion with the SIRIUS 21 crewmembers about their experiences. William Brown came to SIRIUS 21 with experience spread across multiple industries, including the military, defense contracting, healthcare consulting, software engineering, and logistics. He has lived in the Middle East, Central Asia, and Russia. A former Boren Scholar, Brown is fluent in Russian. He holds a Master of International Business degree from the University of South Carolina’s Darla Moore School of Business. Prior to that, he earned a bachelor’s degree in Russian language, literature, and culture from the University of South Carolina. There, he also completed additional undergraduate coursework in computer science. Ashley Kowalski is a Project Leader in The Aerospace Corporation’s International Partnerships Department, where she works with, represents, and provides technical support to the the U.S. Space Force Space Systems Command International Affairs (SSC/IA) office. Through her numerous national and international assignments (Russia, China, and Germany), she has worked on topics related to international space systems, national security space systems, civil systems (including human spaceflight and civil launch projects), space policy, satellite industry analysis, and satellite manufacturing start-ups. She is proficient in Russian and German, and fluent in Polish. Kowalski received her Bachelor of Science and Master of Science degrees in mechanical and aerospace engineering from George Washington University in 2011 and 2012, respectively.

S. E. Whiting↗
NASA NTRSDate not supplied

Comparison of the NAIRAS Trajectory Dose Model With ISS Measurements: Effects of Trapped Particles and Solar Energetic Particle Events.

The NAIRAS(Nowcast of Aerospace Ionizing RAdiation system) model was initially developed for fast computation of GCR and SEP events in the Earth's atmosphere. It was recently improved for computing the effects of trapped particles and its domain of validity was extended to the near space environments, which notably includes the international space station (ISS). To validate the new capabilities of the model, we compared its outputs with some measurements made in the ISS. Historical data contained several SEP events while newer measurements made with the ARMAS instrument flying in the experience bay of KIBO show the influence of trapped particles and GCR over the total dose received.

Guillaume Gronoff↗
NASA NTRS1987

Methods for design and evaluation of integrated hardware/software systems for concurrent computation

Two testbed programming environments to support the evaluation of a large range of parallel architectures have been implemented under the program Parallel Implementation of Scientific Computing Environments (PISCES). The PISCES 1 environment was applied to two areas of aerospace interest: a sparse matrix iterative equation solver and a dynamic scene analysis system. Currently, the NICE/SPAR testbed system for structural analysis is being modified for parallel operation under PISCES 2; the PISCES 1 applications are also being adapted for PISCES 2. A new formal model of concurrent computation has been developed, based on the mathematical system known as H graph semantics together with a timed Petri net model of the parallel aspects of a system.

Pratt, Terrence W.↗
NASA NTRS2012

Creation of a Rapid High-Fidelity Aerodynamics Module for a Multidisciplinary Design Environment

In the traditional aerospace vehicle design process, each successive design phase is accompanied by an increment in the modeling fidelity of the disciplinary analyses being performed. This trend follows a corresponding shrinking of the design space as more and more design decisions are locked in. The correlated increase in knowledge about the design and decrease in design freedom occurs partly because increases in modeling fidelity are usually accompanied by significant increases in the computational expense of performing the analyses. When running high fidelity analyses, it is not usually feasible to explore a large number of variations, and so design space exploration is reserved for conceptual design, and higher fidelity analyses are run only once a specific point design has been selected to carry forward. The designs produced by this traditional process have been recognized as being limited by the uncertainty that is present early on due to the use of lower fidelity analyses. For example, uncertainty in aerodynamics predictions produces uncertainty in trajectory optimization, which can impact overall vehicle sizing. This effect can become more significant when trajectories are being shaped by active constraints. For example, if an optimal trajectory is running up against a normal load factor constraint, inaccuracies in the aerodynamic coefficient predictions can cause a feasible trajectory to be considered infeasible, or vice versa. For this reason, a trade must always be performed between the desired fidelity and the resources available. Apart from this trade between fidelity and computational expense, it is very desirable to use higher fidelity analyses earlier in the design process. A large body of work has been performed to this end, led by efforts in the area of surrogate modeling. In surrogate modeling, an up-front investment is made by running a high fidelity code over a Design of Experiments (DOE); once completed, the DOE data is used to create a surrogate model, which captures the relationships between input variables and responses into regression equations. Depending on the dimensionality of the problem and the fidelity of the code for which a surrogate model is being created, the initial DOE can itself be computationally prohibitive to run. Cokriging, a modeling approach from the field of geostatistics, provides a desirable compromise between computational expense and fidelity. To do this, cokriging leverages a large body of data generated by a low fidelity analysis, combines it with a smaller set of data from a higher fidelity analysis, and creates a kriging surrogate model with prediction fidelity approaching that of the higher fidelity analysis. When integrated into a multidisciplinary environment, a disciplinary analysis module employing cokriging can raise the analysis fidelity without drastically impacting the expense of design iterations. This is demonstrated through the creation of an aerodynamics analysis module in NASA’s OpenMDAO framework. Aerodynamic analyses including Missile DATCOM, APAS, and USM3D are leveraged to create high fidelity aerodynamics decks for parametric vehicle geometries, which are created in NASA’s Vehicle Sketch Pad (VSP). Several trade studies are performed to examine the achieved level of model fidelity, and the overall impact to vehicle design is quantified.

Aerodynamic Properties↗
NASA NTRS1992

The F-18 systems research aircraft facility

To help ensure that new aerospace initiatives rapidly transition to competitive U.S. technologies, NASA Dryden Flight Research Facility has dedicated a systems research aircraft facility. The primary goal is to accelerate the transition of new aerospace technologies to commercial, military, and space vehicles. Key technologies include more-electric aircraft concepts, fly-by-light systems, flush airdata systems, and advanced computer architectures. Future aircraft that will benefit are the high-speed civil transport and the National AeroSpace Plane. This paper describes the systems research aircraft flight research vehicle and outlines near-term programs.

Sitz, Joel R.↗
NASA NTRS1982

Mixed time integration methods for transient thermal analysis of structures

The computational methods used to predict and optimize the thermal structural behavior of aerospace vehicle structures are reviewed. In general, two classes of algorithms, implicit and explicit, are used in transient thermal analysis of structures. Each of these two methods has its own merits. Due to the different time scales of the mechanical and thermal responses, the selection of a time integration method can be a different yet critical factor in the efficient solution of such problems. Therefore mixed time integration methods for transient thermal analysis of structures are being developed. The computer implementation aspects and numerical evaluation of these mixed time implicit-explicit algorithms in thermal analysis of structures are presented. A computationally useful method of estimating the critical time step for linear quadrilateral element is also given. Numerical tests confirm the stability criterion and accuracy characteristics of the methods. The superiority of these mixed time methods to the fully implicit method or the fully explicit method is also demonstrated.

Liu, W. K.↗
DOE OSTI2025

Optimization of Functionally Graded Materials Using Additive Manufacturing: An Integrated Experimental and Computational Approach (Abbreviated Final Report)

Many advanced technologies, such as next-generation energy systems, aerospace vehicles, and defense platforms, require materials that can withstand extreme environments, including high temperatures, corrosion, and radiation, while remaining strong and lightweight. Traditionally, joining different materials to achieve these properties introduces weak, failure-prone interfaces and defects that limit performance. Our research aimed to overcome this challenge by using additive manufacturing, specifically directed energy deposition, to create functionally graded materials—components with smooth transitions between different metals. This approach eliminates sharp boundaries and allows for tailored material properties throughout a part.

36 MATERIALS SCIENCE↗