Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “future of 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 325 records · Page 18

Parallel Computational Fluid Dynamics: Current Status and Future Requirements

One or the key objectives of the Applied Research Branch in the Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Allies Research Center is the accelerated introduction of highly parallel machines into a full operational environment. In this report we discuss the performance results obtained from the implementation of some computational fluid dynamics (CFD) applications on the Connection Machine CM-2 and the Intel iPSC/860. We summarize some of the experiences made so far with the parallel testbed machines at the NAS Applied Research Branch. Then we discuss the long term computational requirements for accomplishing some of the grand challenge problems in computational aerosciences. We argue that only massively parallel machines will be able to meet these grand challenge requirements, and we outline the computer science and algorithm research challenges ahead.

Simon, Horst D.↗

Future requirements of wind tunnels for Computational Fluid Dynamics code verification

The role of experiment in the development of Computational Fluid Dynamics (CFD) for external aerodynamic flow-field prediction is discussed. Requirements for code verification from two sources pacing the development of CFD are described: (1) the need for developing adequate flow modeling, and (2) the need for establishing confidence in the use of CFD for predicting complex flows. The type of data needed to meet these needs differs in detail and scope and leads to definite wind tunnel requirements. Recent examples of testing to assess and develop turbulence models, and to verify code development are used to establish future requirements of wind tunnel testing for CFD verification.

Marvin, J. G.↗

New computing systems and their impact on structural analysis and design

A review is given of the recent advances in computer technology that are likely to impact structural analysis and design. The computational needs for future structures technology are described. The characteristics of new and projected computing systems are summarized. Advances in programming environments, numerical algorithms, and computational strategies for new computing systems are reviewed, and a novel partitioning strategy is outlined for maximizing the degree of parallelism. The strategy is designed for computers with a shared memory and a small number of powerful processors (or a small number of clusters of medium-range processors). It is based on approximating the response of the structure by a combination of symmetric and antisymmetric response vectors, each obtained using a fraction of the degrees of freedom of the original finite element model. The strategy was implemented on the CRAY X-MP/4 and the Alliant FX/8 computers. For nonlinear dynamic problems on the CRAY X-MP with four CPUs, it resulted in an order of magnitude reduction in total analysis time, compared with the direct analysis on a single-CPU CRAY X-MP machine.

Noor, Ahmed K.↗

New computing systems and their impact on structural and fracture mechanics calculations

Advances made in computer technology and their impact on structural and fracture mechanics calculations are reviewed, and the computational needs for future structural systems are discussed. Special attention is given to the computer hardware, the network technology, the performance of new computing systems, and the supersystems and parallel processing and their impact on structure technology. The differences between different machines are identified.

Liebowitz, Harold↗

Autoignition of Premixed Liquefied Petroleum Gas in a Rapid Compression Machine: Experimental Results and Chemical Kinetic Mechanism Reduction

Liquefied petroleum gas (LPG) has many properties that make it an attractive alternative fuel such as lower cost than conventional fuels and an established distribution infrastructure. The development of high efficiency, spark ignited LPG engines is currently limited by engine knock and misfire. The knock and misfire limits are further complicated by the wide range of chemical reactivity in LPG, particularly in international markets. In this study, a rapid compression machine (RCM) was used to characterize the effects of variation in LPG fuel reactivity, equivalence ratio, and exhaust gas recirculation (EGR) on autoignition of LPG/oxidizer/inert/EGR blends. Experiments were conducted with 100% propane (C3H8) and blends of propane with propene, ethane, isobutane, and n-butane. EGR was simulated with mixtures of Ar, CO2, CO, and NO at substitution percentages from 0 to 30 mass percent. Equivalence ratio was varied from 0.75 to 1.5. Ignition delay period under homogeneous autoignition conditions was measured at compressed pressures and temperatures of 23 to 25 bar and 701 to 921 K, respectively. Zero-dimensional simulations of the RCM experiments were performed using Chemkin with several detailed chemical kinetic mechanisms to determine their suitability at predicting ignition delay periods. Multiple reduced chemical kinetic mechanisms were created from the NUIGMech1.1 mechanism to determine the optimal balance between accuracy and computational efficiency for future three-dimensional, time-dependent spark-ignited engine computations.

42 ENGINEERING↗

Efficient Use of Distributed Systems for Scientific Applications

Distributed computing has been regarded as the future of high performance computing. Nationwide high speed networks such as vBNS are becoming widely available to interconnect high-speed computers, virtual environments, scientific instruments and large data sets. One of the major issues to be addressed with distributed systems is the development of computational tools that facilitate the efficient execution of parallel applications on such systems. These tools must exploit the heterogeneous resources (networks and compute nodes) in distributed systems. This paper presents a tool, called PART, which addresses this issue for mesh partitioning. PART takes advantage of the following heterogeneous system features: (1) processor speed; (2) number of processors; (3) local network performance; and (4) wide area network performance. Further, different finite element applications under consideration may have different computational complexities, different communication patterns, and different element types, which also must be taken into consideration when partitioning. PART uses parallel simulated annealing to partition the domain, taking into consideration network and processor heterogeneity. The results of using PART for an explicit finite element application executing on two IBM SPs (located at Argonne National Laboratory and the San Diego Supercomputer Center) indicate an increase in efficiency by up to 36% as compared to METIS, a widely used mesh partitioning tool. The input to METIS was modified to take into consideration heterogeneous processor performance; METIS does not take into consideration heterogeneous networks. The execution times for these applications were reduced by up to 30% as compared to METIS. These results are given in Figure 1 for four irregular meshes with number of elements ranging from 30,269 elements for the Barth5 mesh to 11,451 elements for the Barth4 mesh. Future work with PART entails using the tool with an integrated application requiring distributed systems. In particular this application, illustrated in the document entails an integration of finite element and fluid dynamic simulations to address the cooling of turbine blades of a gas turbine engine design. It is not uncommon to encounter high-temperature, film-cooled turbine airfoils with 1,000,000s of degrees of freedom. This results because of the complexity of the various components of the airfoils, requiring fine-grain meshing for accuracy. Additional information is contained in the original.

Taylor, Valerie↗

Center for Advanced Computational Technology

The Center for Advanced Computational Technology (ACT) was established to serve as a focal point for diverse research activities pertaining to application of advanced computational technology to future aerospace systems. These activities include the use of numerical simulations, artificial intelligence methods, multimedia and synthetic environments, and computational intelligence, in the modeling, analysis, sensitivity studies, optimization, design and operation of future aerospace systems. The Center is located at NASA Langley and is an integral part of the School of Engineering and Applied Science of the University of Virginia. The Center has four specific objectives: 1) conduct innovative research on applications of advanced computational technology to aerospace systems; 2) act as pathfinder by demonstrating to the research community what can be done (high-potential, high-risk research); 3) help in identifying future directions of research in support of the aeronautical and space missions of the twenty-first century; and 4) help in the rapid transfer of research results to industry and in broadening awareness among researchers and engineers of the state-of-the-art in applications of advanced computational technology to the analysis, design prototyping and operations of aerospace and other high-performance engineering systems. In addition to research, Center activities include helping in the planning and coordination of the activities of a multi-center team of NASA and JPL researchers who are developing an intelligent synthesis environment for future aerospace systems; organizing workshops and national symposia; as well as writing state-of-the-art monographs and NASA special publications on timely topics.

Noor, Ahmed K.↗

An FPGA-Based Neuromorphic Processor with All-to-All Connectivity

Neuromorphic computing is a promising paradigm for future energy-efficient computing. At present, however, it is in its nascent stages—most hardware implementations are research-grade, commercial products are not available, and the software tools are not production-ready. The lack of hardware and software tools makes neuromorphic computing inaccessible to researchers around the globe. To this extent, we intend to build a low-cost, open-source, FPGA-based digital neuromorphic processor that can be used by researchers worldwide. In this paper, we present a preliminary implementation of the processor on a Xilinx Artix-7 FPGA using SystemVerilog. Our implementation supports the integrate-and-fire neuron with two parameters each for neurons and synapses. It also features all-to-all connectivity among neurons on the hardware. We test our implementation on four cases: bars and stripes datasets, shortest path algorithm, logic gates, and 8-3 encoder. We also perform a scalability study to understand the resource utilization of the FPGA as the number of all-to-all connected neurons increases. With our implementation, the Artix- 7 supports 65 neurons with all-to-all connectivity. Moreover, all the test cases mentioned above achieve 100% accuracy.

Maheshwari, Disha↗

Payload/orbiter contamination control requirement study: Computer interface

The MSFC computer facilities, and future plans for them are described relative to characteristics of the various computers as to availability and suitability for processing the contamination program. A listing of the CDC 6000 series and UNIVAC 1108 characteristics is presented so that programming requirements can be compared directly and differences noted.

Bareiss, L. E.↗

Antenna analysis using neural networks

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern shaping. The interesting thing about D-C synthesis is that the side lobes have the same amplitude. Five-element arrays were used. Again, 41 pattern samples were used for the input. Nine actual D-C patterns ranging from -10 dB to -30 dB side lobe levels were used to train the network. A comparison between simulated and actual D-C techniques for a pattern with -22 dB side lobe level is shown. The goal for this research was to evaluate the performance of neural network computing with antennas. Future applications will employ the backpropagation training algorithm to drastically reduce the computational complexity involved in performing EM compensation for surface errors in large space reflector antennas.

Smith, William T.↗

Application of Quantum Computing to Biochemical Systems: A Look to the Future

Chemistry is considered as one of the more promising applications to science of near-term quantum computing. Recent work in transitioning classical algorithms to a quantum computer has led to great strides in improving quantum algorithms and illustrating their quantum advantage. Because of the limitations of near-term quantum computers, the most effective strategies split the work over classical and quantum computers. There is a proven set of methods in computational chemistry and materials physics that has used this same idea of splitting a complex physical system into parts that are treated at different levels of theory to obtain solutions for the complete physical system for which a brute force solution with a single method is not feasible. These methods are variously known as embedding, multi-scale, and fragment techniques and methods. We review these methods and then propose the embedding approach as a method for describing complex biochemical systems, with the parts not only treated with different levels of theory, but computed with hybrid classical and quantum algorithms. Such strategies are critical if one wants to expand the focus to biochemical molecules that contain active regions that cannot be properly explained with traditional algorithms on classical computers. While we do not solve this problem here, we provide an overview of where the field is going to enable such problems to be tackled in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimentally Validated Numerical Models of Non-Isothermal Turbulent Mixing in High Temperature Reactors

In the Very High Temperature Reactor (VHTR), the non-uniform heat generation and flow maldistribution of coolant in the core generates conditions leading into the lower plenum with many jets at different temperatures and velocities. The hope is that the combined flow becomes fully mixed in a short distance so that the fluctuating temperatures in the mixing region do not cause unwanted thermal stresses in the supporting structures. These cyclic thermal stresses can cause degradation of the wall microstructure including crack initiation and growth, ultimately leading to the fatigue failure in the lower plenum, and can be accelerated by the high temperature environment in the VHTR. The focus of this project was to provide experimental data for future validation of computational efforts aimed at capturing the turbulent mixing in the lower plenum. Computational fluid dynamics (CFD) is also used as part of this effort to assess the requirements to model fundamental flows with application to the lower plenum as well at the applied flow conditions that mimic the experimental facilities. These efforts will lay the groundwork for future incorporation of stress analysis as well as fatigue and failure studies for multiple VHTR components. An additional emphasis is placed on reduced order models (ROM) using canonical flows, which will help to balance computational expense and accuracy and enable future work in uncertainty quantification. The flow in the lower plenum is extremely complex with hundreds of cooling jets entering and then being forced to change directions by 90° while navigating through an array of cylindrical support posts. Generating experimental data for such a complicated flow is difficult, not to mention that the computational requirements to generate an adequate temporal and spatial sampling is extremely expensive and time consuming. Therefore, the ultimate focus of this research is a “unit cell” which consists of six jets in the presence of a crossflow, and seven cylindrical support posts. It is scaled to achieve similar ranges of key dimensionless numbers. This serves to mimic flow conditions in different regions of the lower plenum by adjusting velocities, temperatures, and orientations, and represents a compromise between the complexity inside the full-scale application and the ideal conditions of a more fundamental study. In addition to the unit cell experiments and simulations, the complex flows in the VHTR lower plenum are broken down into a number of simplified (in some cases even fundamental) flows, two of which are turbulent jets and flow past cylinders. Each of these are studied, computationally and experimentally for isothermal and non-isothermal conditions. Flows where trusted experimental data is available in the literature (e.g., turbulent free jet), additional experiments are not needed. The result of these efforts is a database of experimental data and multiple computational studies, which provide an outlook to the requirements, needed to capture turbulent mixing flow physics The ROM results provide assessments for appropriate resource-light models that balance accuracy with reduced computational burdens.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

U.S. aerospace industry opinion of the effect of computer-aided prediction-design technology on future wind-tunnel test requirements for aircraft development programs

A survey of the U.S. aerospace industry in late 1977 suggests that there will be an increasing use of computer-aided prediction-design technology (CPD Tech) in the aircraft development process but that, overall, only a modest reduction in wind-tunnel test requirements from the current level is expected in the period through 1995. Opinions were received from key spokesmen in 23 of the 26 solicited major companies or corporate divisions involved in the design and manufacture of nonrotary wing aircraft. Development programs for nine types of aircraft related to test phases and wind-tunnel size and speed range were considered.

Treon, S. L.↗

Pathways and Challenges to Innovation in Aerospace

This paper explores impediments to innovation in aerospace and suggests how successful pathways from other industries can be adopted to facilitate greater innovation. Because of its nature, space exploration would seem to be a ripe field of technical innovation. However, engineering can also be a frustratingly conservative endeavor when the realities of cost and risk are included. Impediments like the "find the fault" engineering culture, the treatment of technical risk as almost always evaluated in terms of negative impact, the difficult to account for expansive Moore's Law growth when making predictions, and the stove-piped structural organization of most large aerospace companies and federally funded research laboratories tend to inhibit cross-cutting technical innovation. One successful example of a multi-use cross cutting application that can scale with Moore's Law is the Evolutionary Computational Methods (ECM) technique developed at the Jet Propulsion Lab for automated spectral retrieval. Future innovations like computational engineering and automated design optimization can potentially redefine space exploration, but will require learning lessons from successful innovators.

Terrile, Richard J.↗

Emerging computer technologies and the news media of the future

The media environment of the future may be dramatically different from what exists today. As new computing and communications technologies evolve and synthesize to form a global, integrated communications system of networks, public domain hardware and software, and consumer products, it will be possible for citizens to fulfill most information needs at any time and from any place, to obtain desired information easily and quickly, to obtain information in a variety of forms, and to experience and interact with information in a variety of ways. This system will transform almost every institution, every profession, and every aspect of human life--including the creation, packaging, and distribution of news and information by media organizations. This paper presents one vision of a 21st century global information system and how it might be used by citizens. It surveys some of the technologies now on the market that are paving the way for new media environment.

Vrabel, Debra A.↗

Scalable quantum computational science: A perspective from block-encodings and polynomial transformations

Significant developments made in quantum hardware and error correction recently have been driving quantum computing toward practical utility. However, gaps remain between abstract quantum algorithmic development and practical applications in computational sciences. In this perspective article, we propose several properties that scalable quantum computational science methods should possess. We further discuss how block-encodings and polynomial transformations can potentially serve as a unified framework with the desired properties. Recent advancements on these topics are presented, including the construction and assembly of block-encodings, and various generalizations of quantum signal processing (QSP) algorithms to perform polynomial transformations. The scalability of QSP methods on parallel and distributed quantum architectures is also highlighted. Promising applications in simulation and observable estimation in chemistry, physics, and optimization problems are presented. We hope this perspective serves as a gentle introduction to state-of-the-art quantum algorithms for the computational science community and inspires future development of scalable quantum computational science methodologies that bridge theory and practice.

Bayesian inference↗

Computer graphics in aerodynamic analysis

The use of computer graphics and its application to aerodynamic analyses on a routine basis is outlined. The mathematical modelling of the aircraft geometries and the shading technique implemented are discussed. Examples of computer graphics used to display aerodynamic flow field data and aircraft geometries are shown. A future need in computer graphics for aerodynamic analyses is addressed.

Cozzolongo, J. V.↗