Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “high performance space 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 505 records · Page 28

Research and Development Annual Report, 1992

Issued as a companion to Johnson Space Center's Research and Technology Annual Report, which reports JSC accomplishments under NASA Research and Technology Operating Plan (RTOP) funding, this report describes 42 additional JSC projects that are funded through sources other than the RTOP. Emerging technologies in four major disciplines are summarized: space systems technology, medical and life sciences, mission operations, and computer systems. Although these projects focus on support of human spacecraft design, development, and safety, most have wide civil and commercial applications in areas such as advanced materials, superconductors, advanced semiconductors, digital imaging, high density data storage, high performance computers, optoelectronics, artificial intelligence, robotics and automation, sensors, biotechnology, medical devices and diagnosis, and human factors engineering.

Source record↗

The JSC Research and Development Annual Report 1993

Issued as a companion to Johnson Space Center's Research and Technology Annual Report, which reports JSC accomplishments under NASA Research and Technology Operating Plan (RTOP) funding, this report describes 47 additional projects that are funded through sources other than the RTOP. Emerging technologies in four major disciplines are summarized: space systems technology, medical and life sciences, mission operations, and computer systems. Although these projects focus on support of human spacecraft design, development, and safety, most have wide civil and commercial applications in areas such as advanced materials, superconductors, advanced semiconductors, digital imaging, high density data storage, high performance computers, optoelectronics, artificial intelligence, robotics and automation, sensors, biotechnology, medical devices and diagnosis, and human factors engineering.

Source record↗

Proceedings of the 4th International Conference and Exhibition: World Congress on Superconductivity, volume 1

The papers presented at the 4th International Conference Exhibition: World Congress on Superconductivity held at the Marriott Orlando World Center, Orlando, Florida, are contained in this document and encompass the research, technology, applications, funding, political, and social aspects of superconductivity. Specifically, the areas covered included: high-temperature materials; thin films; C-60 based superconductors; persistent magnetic fields and shielding; fabrication methodology; space applications; physical applications; performance characterization; device applications; weak link effects and flux motion; accelerator technology; superconductivity energy; storage; future research and development directions; medical applications; granular superconductors; wire fabrication technology; computer applications; technical and commercial challenges, and power and energy applications.

Krishen, Kumar↗

Proceedings of the 4th International Conference and Exhibition: World Congress on Superconductivity, Volume 2

This document contains papers presented at the 4th International Conference Exhibition: World Congress on Superconductivity held June 27-July 1, 1994 in Orlando, Florida. These documents encompass research, technology, applications, funding, political, and social aspects of superconductivity. The areas covered included: high-temperature materials; thin films; C-60 based superconductors; persistent magnetic fields and shielding; fabrication methodology; space applications; physical applications; performance characterization; device applications; weak link effects and flux motion; accelerator technology; superconductivity energy; storage; future research and development directions; medical applications; granular superconductors; wire fabrication technology; computer applications; technical and commercial challenges; and power and energy applications.

Krishen, Kumar↗

METAShield: Hot Metallic Aeroshell Concept for RLV/SOV

An innovative fuselage design approach that combines many desirable operational features with a simple and efficient structural approach is being developed by NASA. The approach, named METAShield for MEtallic TransAtmospheric Shield, utilizes lightly loaded, hot aeroshell structures surrounding integral propellant tanks that carry the primary structural loads. The aeroshells are designed to withstand the local pressure loads, transmitting them to the tanks with minimal restraint of thermal growth. No additional thermal protection system protects the METAShield, and a fibrous or multilayer insulation blanket, located in the space between the aeroshell and the tanks, serves as both high temperature and cryogenic insulation for the tanks. The concept is described in detail, and the performance and operational features are highlighted. Initial design results and analyses of the structural, thermal, and thermal-structural performance are described. Computational results evaluating resistance to hypervelocity impact damage, as well as some supporting aerothermal wind tunnel results. are also presented. Future development needs are summarized.

Scotti, Stephen J.↗

Development of a low-cost virtual reality workstation for training and education

Virtual Reality (VR) is a set of breakthrough technologies that allow a human being to enter and fully experience a 3-dimensional, computer simulated environment. A true virtual reality experience meets three criteria: (1) it involves 3-dimensional computer graphics; (2) it includes real-time feedback and response to user actions; and (3) it must provide a sense of immersion. Good examples of a virtual reality simulator are the flight simulators used by all branches of the military to train pilots for combat in high performance jet fighters. The fidelity of such simulators is extremely high -- but so is the price tag, typically millions of dollars. Virtual reality teaching and training methods are manifestly effective, but the high cost of VR technology has limited its practical application to fields with big budgets, such as military combat simulation, commercial pilot training, and certain projects within the space program. However, in the last year there has been a revolution in the cost of VR technology. The speed of inexpensive personal computers has increased dramatically, especially with the introduction of the Pentium processor and the PCI bus for IBM-compatibles, and the cost of high-quality virtual reality peripherals has plummeted. The result is that many public schools, colleges, and universities can afford a PC-based workstation capable of running immersive virtual reality applications. My goal this summer was to assemble and evaluate such a system.

Phillips, James A.↗

Non-Blind Deblurring for Fluorescence: A Deformable Latent Space Approach with Kernel Parameterization

We report N\non-blind deblurring (NBD) is a modeling method of the image deblurring problem in computer vision, where the blurring kernel is known or can be externally estimated. In this paper, we attempt to solve a parametric NBD problem, inspired by the simultaneous acquisition of ptychography and fluorescent imaging (FI). Ptychography is an imaging method that favors larger probes, i.e. convolutional kernels, while FI relies on a small probe for high resolution. Also, the kernel can be solved during ptychographic reconstruction. With Ptycho-FI using the same larger kernel, we can perform NBD on the blurred fluorescent images to achieve high-resolution FI, and thus speed up the experiments. To this end, we design a deep latent space deformation network that is directly parameterized by the kernel. The network consists of three components: encoder, deformer, and decoder, where the deformer is specifically meant to rectify the latent space representations of blurred images to a standard latent space, regardless of the kernel. The deformation network is trained with a two-stage training scheme. We conduct extensive experiments to confirm that our parametric model can adapt to drastically different blurring kernels and perform robust deblurring.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

On decoupling the integrals of cosmological perturbation theory

ABSTRACT Perturbation theory (PT) is often used to model statistical observables capturing the translation and rotation-invariant information in cosmological density fields. PT produces higher order corrections by integration over linear statistics of the density fields weighted by kernels resulting from recursive solution of the fluid equations. These integrals quickly become high dimensional and naively require increasing computational resources the higher the order of the corrections. Here, we show how to decouple the integrands that often produce this issue, enabling PT corrections to be computed as a sum of products of independent 1D integrals. Our approach is related to a commonly used method for calculating multiloop Feynman integrals in quantum field theory, the Gegenbauer Polynomial x-Space Technique. We explicitly reduce the three terms entering the 2-loop power spectrum, formally requiring 9D integrations, to sums over successive 1D radial integrals. These 1D integrals can further be performed as convolutions, rendering the scaling of this method Nglog Ng with Ng the number of grid points used for each fast Fourier transform. This method should be highly enabling for upcoming large-scale structure redshift surveys where model predictions at an enormous number of cosmological parameter combinations will be required by Monte Carlo Markov Chain searches for the best-fitting values.

Slepian, Zachary↗

An open-source framework for balancing computational speed and fidelity in production cost models

Studies of bulk power system operations need to incorporate uncertainty and sensitivity analyses, especially around exposure to weather and climate variability and extremes, but this remains a computational modeling challenge. Commercial production cost models (PCMs) have shorter runtimes, but also important limitations (opacity, license restrictions) that do not fully support stochastic simulation. Open-source PCMs represent a potential solution. They allow for multiple, simultaneous runs in high-performance computing environments and offer flexibility in model parameterization. Yet, developers must balance computational speed (i.e. runtime) with model fidelity (i.e. accuracy). In this paper, we present Grid Operations (GO), a framework for instantiating open-source, scale-adaptive PCMs. GO allows users to search across parameter spaces to identify model versions that appropriately balance computational speed and fidelity based on experimental needs and resource limits. Results provide generalizable insights on how to navigate the fidelity and computational speed tradeoff through parameter selection. We show that models with coarser network topologies can accurately mimic market operations, sometimes better than higher-resolution models. It is thus possible to conduct large simulation experiments that characterize operational risks related to climate and weather extremes while maintaining sufficient model accuracy.

42 ENGINEERING↗

Space Shuttle Main Engine

Significant features of the Space Shuttle Main Engine (SSME) include a staged combustion power cycle developing chamber pressure in excess of 3000 psia, high area ratio nozzle expansion, throttling capability, and a computer-operated engine control system. This paper examines the current status of the SSME with attention given to engine performance, system characteristics, and test results. A comparison of the SSME development and certification programs with engines successfully used in the Saturn Program is presented.

Thompson, J. R., Jr.↗

Optimization of V-groove radiator configuration

In the design of spacecraft radiators intended to provide cryogenic cooling, it is important to minimize the space occupied by radiator shielding while satisfying the performance requirements. This study develops and tests the first step toward optimizing radiator shield configurations and examines the design of the highly effective V-groove radiator concept. This investigation, which makes use of a special purpose Monte Carlo/ray tracing computer program, directly identifies the two shield configuration which minimizes radiator footprint for a given temperature drop. Furthermore, multiple shield configurations may be analyzed through a combination of analysis and program statistics. The results presented demonstrate the sensitivity of intershield temperature drop to shield angle and/or offset and provide a comparison of angled and parallel shield configurations. Good agreement with experimental data is shown for a multiple shield configuration.

Schember, Helene R.↗

Multi-Dimensional High Order Essentially Non-Oscillatory Finite Difference Methods in Generalized Coordinates

This project is about the development of high order, non-oscillatory type schemes for computational fluid dynamics. Algorithm analysis, implementation, and applications are performed. Collaborations with NASA scientists have been carried out to ensure that the research is relevant to NASA objectives. The combination of ENO finite difference method with spectral method in two space dimension is considered, jointly with Cai [3]. The resulting scheme behaves nicely for the two dimensional test problems with or without shocks. Jointly with Cai and Gottlieb, we have also considered one-sided filters for spectral approximations to discontinuous functions [2]. We proved theoretically the existence of filters to recover spectral accuracy up to the discontinuity. We also constructed such filters for practical calculations.

Shu, Chi-Wang↗

Slosh-Induced Ullage Collapse Validation by Computational Fluid Dynamics and Application to In-space Propellant Dynamics

Ullage collapse predictions made using Computational Fluid Dynamics (CFD) were validated then made for an in-space cryogenic propellant unsettling application. Ullage collapse is the decrease in propellant tank pressure due to cooling of the ullage gas, which can be significant for cryogenic propulsion systems. Vehicles may be developed that are robust to temperature and pressure changes caused by heat leaks, e.g., propellant tanks with high maximum operation pressures, technologies yielding active thermal conditioning, and systems with ample pressurant for conditioning. These methods are robust because additional mass, cost, and complexity are used to address cryogenic fluid management (CFM). As vehicles are optimized for increased payload capacity, tracking of events such as ullage collapse and self-pressurization in tanks will become increasingly important for propellant inventory calculations. Some ullage collapse events can be studied through ground experimentation, but propellant unsettling in and around in-space coast mission phases must be studied in the absence of an acceleration field. Computational Fluid Dynamics is a powerful tool to address this need, enabling prediction of complex physics prior to flight. Validation of the chosen CFD tool and modeling methodology was done using data from a previously conducted subscale slosh-induced ullage collapse ground test performed in part by the Japan Aerospace Exploration Agency (JAXA). A small tank was partially filled with liquid nitrogen and pressurized with gaseous nitrogen at various temperatures. The tank was oscillated laterally to induce high amplitude slosh dynamics resulting in wave breakup. Successful qualitative validation of slosh wave dynamics and quantitative validation of ullage collapse promoted confidence in extending ullage collapse predictions to a flight application. Mechanisms of ullage collapse caused by main engine cutoff while in-space were identified. Both slosh dynamics leading to engine shutdown and body dynamics following shutdown were shown to contribute to propellant unsettling and ullage collapse.

J M Brodnick↗

Laminar-Turbulent Transition Behind Discrete Roughness Elements in a High-Speed Boundary Layer

Computations are performed to study the flow past an isolated roughness element in a Mach 3.5, laminar, flat plate boundary layer. To determine the effects of the roughness element on the location of laminar-turbulent transition inside the boundary layer, the instability characteristics of the stationary wake behind the roughness element are investigated over a range of roughness heights. The wake flow adjacent to the spanwise plane of symmetry is characterized by a narrow region of increased boundary layer thickness. Beyond the near wake region, the centerline streak is surrounded by a pair of high-speed streaks with reduced boundary layer thickness and a secondary, outer pair of lower-speed streaks. Similar to the spanwise periodic pattern of streaks behind an array of regularly spaced roughness elements, the above wake structure persists over large distances and can sustain strong enough convective instabilities to cause an earlier onset of transition when the roughness height is sufficiently large. Time accurate computations are performed to clarify additional issues such as the role of the nearfield of the roughness element during the generation of streak instabilities, as well as to reveal selected details of their nonlinear evolution. Effects of roughness element shape on the streak amplitudes and the interactions between multiple roughness elements aligned along the flow direction are also investigated.

Choudhari, Meelan M.↗

Portable Flow Device Using Fourier Ptychography Microscopy and Deep Learning for Detection of Biosignatures

A proof-of-concept, compact, portable Fourier Ptychographic Microscope (FPM) to perform wide field-of-view, high spatial resolution imaging (<1 μm) for biosignature motility in liquid samples, is presented. The FPM has the potential to be developed as a space-based payload for future landers destined to the Ocean Worlds. A portable FPM using an existing Fourier ptychography (FP) algorithm adapted for reconstruction is demonstrated. A NVIDIA Jetson Nano board and camera combined with FP, is used to computationally reconstruct sub-micron resolution images. Additionally, deep learning was employed to perform inferencing prediction which enables the on-edge FPM device.

Fourier↗

Advanced Technologies for Future Spacecraft Cockpits and Space-based Control Centers

The National Aeronautics and Space Administration (NASA) is embarking on a new era of Space Exploration, aimed at sending crewed spacecraft beyond Low Earth Orbit (LEO), in medium and long duration missions to the Lunar surface, Mars and beyond. The challenges of such missions are significant and will require new technologies and paradigms in vehicle design and mission operations. Current roles and responsibilities of spacecraft systems, crew and the flight control team, for example, may not be sustainable when real-time support is not assured due to distance-induced communication lags, radio blackouts, equipment failures, or other unexpected factors. Therefore, technologies and applications that enable greater Systems and Mission Management capabilities on-board the space-based system will be necessary to reduce the dependency on real-time critical Earth-based support. The focus of this paper is in such technologies that will be required to bring advance Systems and Mission Management capabilities to space-based environments where the crew will be required to manage both the systems performance and mission execution without dependence on the ground. We refer to this concept as autonomy. Environments that require high levels of autonomy include the cockpits of future spacecraft such as the Mars Exploration Vehicle, and space-based control centers such as a Lunar Base Command and Control Center. Furthermore, this paper will evaluate the requirements, available technology, and roadmap to enable full operational implementation of onboard System Health Management, Mission Planning/re-planning, Autonomous Task/Command Execution, and Human Computer Interface applications. The technology topics covered by the paper include enabling technology to perform Intelligent Caution and Warning, where the systems provides directly actionable data for human understanding and response to failures, task automation applications that automate nominal and Off-nominal task execution based on human input or integrated health state-derived conditions. Shifting from Systems to Mission Management functions, we discuss the role of automated planning applications (tactical planning) on-board, which receive data from the other cockpit automation systems and evaluate the mission plan against the dynamic systems and mission states and events, to provide the crew with capabilities that enable them to understand, change, and manage the timeline of their mission. Lastly, we discuss the role of advanced human interface technologies that organize and provide the system md mission information to the crew in ways that maximize their situational awareness and ability to provide oversight and control of aLl the automated data and functions.

Garcia-Galan, Carlos↗

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗

Inverse Analysis with Variational Autoencoders: A Comparison of Shallow and Deep Networks

Inverse problems are applied to determine unknown properties by matching observational data with a physical model that often takes many parameters as input. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented involving regularization with a technique known as a variational autoencoder (VAE), which is trained to map a high-dimensional parameter space with a complex structure to a low-dimensional latent space with a simple structure. We apply this approach to unconditioned realizations of the parameters (heterogeneous hydraulic fields) for a hydrogeological inverse problem. Two types of hydraulic conductivity fields are used to evaluate the characterization for the different levels of heterogeneity complexity of the physical inputs. This approach keeps the computational cost of generating the training data low. The reason is unconditioned realizations neither rely on the observational data used to perform the inverse analysis nor require any groundwater flow model forward runs. In addition, this approach applies regularization on a low-dimensional latent space from the VAE and increases optimization efficiency through automatic differentiation. Furthermore, two different neural network (NN) structures are tested for their utility in using the VAE for inverse analysis. The performance of a deep, convolutional neural network strongly depends on the dimensionality of the latent space, which requires tuning. In contrast, a shallow, dense neural network provides consistently accurate characterization without tuning. Furthermore, our approach evaluates the advantages of the shallow, dense neural network over the deep, convolutional one and enables future application to a wide range of inverse problems.

97 MATHEMATICS AND COMPUTING↗