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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Analysis of MMU FDIR expert system

This paper describes the analysis of a rulebase for fault diagnosis, isolation, and recovery for NASA's Manned Maneuvering Unit (MMU). The MMU is used by a human astronaut to move around a spacecraft in space. In order to provide maneuverability, there are several thrusters oriented in various directions, and hand-controlled devices for useful groups of them. The rulebase describes some error detection procedures, and corrective actions that can be applied in a few cases. The approach taken in this paper is to treat rulebases as symbolic objects and compute correctness and 'reasonableness' criteria that use the statistical distribution of various syntactic structures within the rulebase. The criteria should identify awkward situations, and otherwise signal anomalies that may be errors. The rulebase analysis agorithms are derived from mathematical and computational criteria that implement certain principles developed for rulebase evaluation. The principles are Consistency, Completeness, Irredundancy, Connectivity, and finally, Distribution. Several errors were detected in the delivered rulebase. Some of these errors were easily fixed. Some errors could not be fixed with the available information. A geometric model of the thruster arrangement is needed to show how to correct certain other distribution nomalies that are in fact errors. The investigations reported here were partially supported by The Aerospace Corporation's Sponsored Research Program.

Landauer, Christopher↗
NASA NTRS1994

Bolt cutter functional evaluation

The Aerospace Corporation has been implementing finite difference and finite element codes for the analysis of a variety of explosive ordnance devices. Both MESA-2D and DYNA3D have been used to evaluate the role of several design parameters on the performance of a satellite separation system bolt cutter. Due to a lack of high strain rate response data for the materials involved, the properties for the bolt cutter and the bolt were selected to achieve agreement between computer simulation and observed characteristics of the recovered test hardware. The calculations provided insight into design parameters such as the cutter blade kinetic energy, the preload on the bolt, the relative position of the anvil, and the anvil shape. Modeling of the cutting process clarifies metallographic observation of both cut and uncut bolts obtained from several tests. Understanding the physical processes involved in bolt cutter operation may suggest certain design modifications that could improve performance margin without increasing environmental shock response levels.

S. Goldstein↗
NASA NTRS2012

Characterization of the Vectron PX-570 Crystal Oscillator for Use in Harsh Environments

Computing hardware, data-acquisition systems, communications systems, and many electronic control systems require well-controlled timing signals for proper and accurate operation. These signals are, in most cases, provided by circuits that employ crystal oscillators due to availability, cost, ease of operation, and accuracy. In some cases, the electronic systems are expected to survive and operate under harsh conditions that include exposure to extreme temperatures. These applications exist in terrestrial systems as well as in aerospace products. Well-logging, geothermal systems, and industrial process control are examples of ground-based applications, while distributed jet engine control in aircraft, space-based observatories (such as the James Webb Space Telescope), satellites, and lunar and planetary landers are typical environments where electronics are exposed to harsh operating conditions. To ensure these devices produce reliable results, the digital heartbeat from the oscillator must deliver a stable signal that is not affected by external temperature or other conditions. One such solution is a recently introduced commercial-off-the-shelf (COTS) oscillator, the PX-570 series from Vectron International. The oscillator was designed for high-temperature applications and as proof, the crystal oscillator was subjected to a wide suite of tests to determine its ruggedness for operation in harsh environments. The tests performed by Vectron included electrical characterization under wide range of temperature, accelerated life test/aging, shock and vibration, internal moisture analysis, ESD threshold, and latch-up testing. The parametric evaluation was performed on the oscillator's frequency, output signal rise and fall times, duty cycle, and supply current over the temperature range of -125 C to +230 C. The evaluations also determined the effects of thermal cycling and the oscillator's re-start capability at extreme hot and cold temperatures. These thermal cycling and restart tests were performed at the NASA Glenn Research Center. Overall, the crystal oscillator performed well and demonstrated very good frequency stability. This paper will discuss the test procedures and present details of the performance results.

Li, Jacob↗
NASA NTRSDate not supplied

The Nasa Multiscale Analysis Tool: an Enabling Platform for Achieving Vision 2040

Vision 2040 is a community-driven consensus document, written in 2018, aimed at defining the potential 25-year future state required for performing integrated multiscale modeling of materials and systems for future aerospace and aeronautical applications. Nine Vision Key Elements (KEs) were defined along with associated technical gaps. This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT). This paper will specifically focus on NASMAT’s ability to address gaps in three of the nine Vision 2040 KEs: 1) Models and Methods, 2) Multiscale Measurements and Characterization Tools and Methods, and 6) Data, Informatics, and Visualization. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials. NASMAT offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. NASMAT can also be coupled with external software and used to perform multiscale analyses of more complex structures. The paper will include a recent application of NASMAT to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis. Since typical NASMAT analyses can be completed in on the order of seconds to minutes, a second example will demonstrate NASMAT’s ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on developing multiscale data visualization tools will also be addressed along with the challenges associated with and proposed solutions for sifting through large amounts of data. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Vision 2040↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗
DOE OSTI2021

Mechanical analysis of heterogeneous materials with higher-order parameters

Abstract Even though heterogeneous porous materials are widely used in a variety of engineering and scientific fields, such as aerospace, energy-storage technology, and bio-engineering, the relationship between effective material properties of porous materials and their underlying morphology is still not fully understood. To contribute to this knowledge gap, this paper adopts a higher-order asymptotic homogenization method to numerically investigate the effect of complex micropore morphology on the effective mechanical properties of a porous system. Specifically, we use the second-order scheme that is an extension of the first-order computational homogenization framework, where a generalized continuum enables us to introduce length scale into the material constitutive law and capture both pore size and pore distribution. Through several numerical case studies with different combinations of porosity, pore shapes, and distributions, we systematically studied the relationship between the underlying morphology and effective mechanical properties. The results highlight the necessity of higher-order homogenization in understanding the mechanical properties and reveal that higher-order parameters are required to capture the role of realistic pore morphologies on effective mechanical properties. Furthermore, for specific pore shapes, higher-order parameters exhibit dominant influence over the first-order continuum.

42 ENGINEERING↗
NASA NTRS1974

Application of IPAD to missile design

The application of an integrated program for aerospace-vehicle design (IPAD) to the design of a tactical missile is examined. The feasibility of modifying a proposed IPAD system for aircraft design work for use in missile design is evaluated. The tasks, cost, and schedule for the modification are presented. The basic engineering design process is described, explaining how missile design is achieved through iteration of six logical problem solving functions throughout the system studies, preliminary design, and detailed design phases of a new product. Existing computer codes used in various engineering disciplines are evaluated for their applicability to IPAD in missile design.

Santa, J. E.↗
NASA NTRS1988

Laminar-turbulent transition calculations of heat transfer at hypersonic Mach numbers over sharp cones

Computations of the hypersonic flow around sharp cones were carried out using the PNS code with attention given to the heat transfer predictions around the transition region. Results of calculations performed over 5, 8, and 10 deg half-angle sharp cones in the Mach number range of 7 to 10 are presented. It is noted that calculations of this type have become an integral part of the general design procedure for hypersonic vehicles such as the National Aerospace Plane and the Space Shuttle.

Kaul, U. K.↗
NASA NTRS1992

The Proteus Navier-Stokes code

An effort is currently underway at NASA Lewis to develop two and three dimensional Navier-Stokes codes, called Proteus, for aerospace propulsion applications. Proteus solves the Reynolds-averaged, unsteady, compressible Navier-Stokes equations in strong conservation law form. Turbulence is modeled using a Baldwin-Lomax based algebraic eddy viscosity model. In addition, options are available to solve thin layer or Euler equations, and to eliminate the energy equation by assuming constant stagnation enthalpy. An extensive series of validation cases have been run, primarily using the two dimensional planar/axisymmetric version of the code. Several flows were computed that have exact solution such as: fully developed channel and pipe flow; Couette flow with and without pressure gradients; unsteady Couette flow formation; flow near a suddenly accelerated flat plate; flow between concentric rotating cylinders; and flow near a rotating disk. The two dimensional version of the Proteus code has been released, and the three dimensional code is scheduled for release in late 1991.

Towne, Charles E.↗
NASA NTRS2013

Analysis of an Aircraft Honeycomb Sandwich Panel with Circular Face Sheet/Core Disbond Subjected to Ground-Air Pressurization

The ground-air pressurization of lightweight honeycomb sandwich structures caused by alternating pressure differences between the enclosed air within the honeycomb core and the ambient environment is a well-known and controllable loading condition of aerospace structures. However, initial face sheet/core disbonds intensify the face sheet peeling effect of the internal pressure load significantly and can decrease the reliability of the sandwich structure drastically. Within this paper, a numerical parameter study was carried out to investigate the criticality of initial disbonds in honeycomb sandwich structures under ground-air pressurization. A fracture mechanics approach was used to evaluate the loading at the disbond front. In this case, the strain energy release rate was computed via the Virtual Crack Closure Technique. Special attention was paid to the pressure-deformation coupling which can decrease the pressure load within the disbonded sandwich section significantly when the structure is highly deformed.

Rinker, Martin↗
NASA NTRS2015

Space Technology Mission Directorate: Game Changing Development

NASA and the aerospace community have deep roots in manufacturing technology and innovation. Through it's Game Changing Development Program and the Advanced Manufacturing Technology Project NASA develops and matures innovative, low-cost manufacturing processes and products. Launch vehicle propulsion systems are a particular area of interest since they typically comprise a large percentage of the total vehicle cost and development schedule. NASA is currently working to develop and utilize emerging technologies such as additive manufacturing (i.e. 3D printing) and computational materials and processing tools that could dramatically improve affordability, capability, and reduce schedule for rocket propulsion hardware.

Gaddis, Stephen W.↗
DOE OSTI2024

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

14 SOLAR ENERGY↗
NASA NTRS1997

Innovative Educational Aerospace Research at the Northeast High School Space Research Center

Northeast High Magnet School of Philadelphia, Pennsylvania is a proud sponsor of the Space Research Center (SPARC). SPARC, a model program of the Medical, Engineering, and Aerospace Magnet school, provides talented students the capability to successfully exercise full simulations of NASA manned missions. These simulations included low-Earth Shuttle missions and Apollo lunar missions in the past, and will focus on a planetary mission to Mars this year. At the end of each scholastic year, a simulated mission, lasting between one and eight days, is performed involving 75 students as specialists in seven teams The groups are comprised of Flight Management, Spacecraft Communications (SatCom), Computer Networking, Spacecraft Design and Engineering, Electronics, Rocketry, Robotics, and Medical teams in either the mission operations center or onboard the spacecraft. Software development activities are also required in support of these simulations The objective of this paper is to present the accomplishments, technology innovations, interactions, and an overview of SPARC with an emphasis on how the program's educational activities parallel NASA mission support and how this education is preparing student for the space frontier.

Audra Luyet↗
NASA NTRS2003

A New Modular Approach for Tightly Coupled Fluid/Structure Analysis

Static aeroelastic computations are made using a C++ executive suitable for closely coupled fluid/structure interaction studies. The fluid flow is modeled using the Euler/Navier Stokes equations and the structure is modeled using finite elements. FORTRAN based fluids and structures codes are integrated under C++ environment. The flow and structural solvers are treated as separate object files. The data flow between fluids and structures is accomplished using I/O. Results are demonstrated for transonic flow over partially flexible surface that is important for aerospace vehicles. Use of this development to accurately predict flow induced structural failure will be demonstrated.

Guruswamy, Guru↗
NASA NTRS2005

A Proposed Role of Aeroelasticity in NASA's New Exploration Vision

On 14 January 2004, NASA received a mandate to return astronauts to the Moon, evolve a sustained presence there, then head out into the solar system to Mars and perhaps beyond. This new space exploration initiative directs NASA to develop human and robotic technologies that can deliver payloads larger than Apollo to the Moon, to Mars, and bring astronauts and samples safely back to Earth at costs much lower than Apollo. These challenges require creative aerospace systems. On proposed technology for safely delivering payloads to the surface of Mars and returning samples to Earth involves deployed flexible and inflatable decelerators for atmospheric entry. Because inflatable decelerators provide the entry vehicle more drag surface area at smaller mass than traditional ablative devices, this class of decelerators can potentially accomodate larger mass payloads. The flexibility of these lightweight aeroshells can pose both vehicle and aeroelastic stability problems if not properly designed for the expected flight regimes. Computational tools need to be developed for modelling the large and nonlinear deformations of these highly flexible structures. Unlike wind tunnel testing, an integrated and efficient aeroelastic analysis tool can explore the entire flight environment. This paper will provide some background on flexible deployable decelerators, survey the current state of technology and outline the proposed development of an aeroelastic analysis and capability.

Bartels, Robert E.↗
NASA NTRS2005

High Resolution Aerospace Applications using the NASA Columbia Supercomputer

This paper focuses on the parallel performance of two high-performance aerodynamic simulation packages on the newly installed NASA Columbia supercomputer. These packages include both a high-fidelity, unstructured, Reynolds-averaged Navier-Stokes solver, and a fully-automated inviscid flow package for cut-cell Cartesian grids. The complementary combination of these two simulation codes enables high-fidelity characterization of aerospace vehicle design performance over the entire flight envelope through extensive parametric analysis and detailed simulation of critical regions of the flight envelope. Both packages. are industrial-level codes designed for complex geometry and incorpor.ats. CuStomized multigrid solution algorithms. The performance of these codes on Columbia is examined using both MPI and OpenMP and using both the NUMAlink and InfiniBand interconnect fabrics. Numerical results demonstrate good scalability on up to 2016 CPUs using the NUMAIink4 interconnect, with measured computational rates in the vicinity of 3 TFLOP/s, while InfiniBand showed some performance degradation at high CPU counts, particularly with multigrid. Nonetheless, the results are encouraging enough to indicate that larger test cases using combined MPI/OpenMP communication should scale well on even more processors.

Mavriplis, Dimitri J.↗
DOE OSTI2024

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. Our ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

artificial intelligence↗