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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 397 records · Page 22

Validation Metrics for Deterministic and Probabilistic Data

Computational modeling and simulation are paramount to modern science. Computational models often replace physical experiments that are prohibitively expensive, dangerous, or occur at extreme scales. Thus, it is critical that these models accurately represent and can be used as replacements for reality. This paper provides an analysis of metrics that may be used to determine the validity of a computational model. While some metrics have a direct physical meaning and a long history of use, others, especially those that compare probabilistic data, are more difficult to interpret. Furthermore, the process of model validation is often application-specific, making the procedure itself challenging and the results difficult to defend. We therefore provide guidance and recommendations as to which validation metric to use, as well as how to use and decipher the results. Furthermore an example is included that compares interpretations of various metrics and demonstrates the impact of model and experimental uncertainty on validation processes.

97 MATHEMATICS AND COMPUTING↗

Teaching Computational Reproducibility for Neuroimaging

We describe a project-based introduction to reproducible and collaborative neuroimaging analysis. Traditional teaching on neuroimaging usually consists of a series of lectures that emphasize the big picture rather than the foundations on which the techniques are based. The lectures are often paired with practical workshops in which students run imaging analyses using the graphical interface of specific neuroimaging software packages. Our experience suggests that this combination leaves the student with a superficial understanding of the underlying ideas, and an informal, inefficient, and inaccurate approach to analysis. To address these problems, we based our course around a substantial open-ended group project. This allowed us to teach: (a) computational tools to ensure computationally reproducible work, such as the Unix command line, structured code, version control, automated testing, and code review and (b) a clear understanding of the statistical techniques used for a basic analysis of a single run in an MR scanner. The emphasis we put on the group project showed the importance of standard computational tools for accuracy, efficiency, and collaboration. The projects were broadly successful in engaging students in working reproducibly on real scientific questions. We propose that a course on this model should be the foundation for future programs in neuroimaging. We believe it will also serve as a model for teaching efficient and reproducible research in other fields of computational science.

60 APPLIED LIFE SCIENCES↗

1996 NASA-ASEE-Stanford Summer Faculty Fellowship Program

As is customary, the final technical report for the NASA-ASEE Summer Faculty Fellowship Program at the Ames Research Center, Dryden Flight Research Center and Stanford University essentially consists of a compilation of the summary technical reports of all the fellows. More extended versions done either as NASA publications, archival papers, or other laboratory reports are not included here. The reader will note that the areas receiving emphasis were the life sciences, astronomy, remote sensing, aeronautics, fluid dynamics/aerophysics, and computer science. Of course, the areas of emphasis vary somewhat from year to year depending on the interests of the most qualified applicants. Once again, the work is of especially high quality. The reports of the first and second year fellows are grouped separately and are arranged alphabetically within each group.

Source record↗

Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations

The growing gap between sustained and peak performance for scientific applications has become a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to bridge this gap for a significant number of computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines a full spectrum of low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks using some simple optimizations. Finally, we evaluate the perfor- mance of several numerical codes from key scientific computing domains. Overall results demonstrate that the SX6 achieves high performance on a large fraction of our application suite and in many cases significantly outperforms the RISC-based architectures. However, certain classes of applications are not easily amenable to vectorization and would likely require extensive reengineering of both algorithm and implementation to utilize the SX6 effectively.

Oliker, Leonid↗

Rocket Engine Numerical Simulator (RENS)

Work is being done at three universities to help today's NASA engineers use the knowledge and experience of their Apolloera predecessors in designing liquid rocket engines. Ground-breaking work is being done in important subject areas to create a prototype of the most important functions for the Rocket Engine Numerical Simulator (RENS). The goal of RENS is to develop an interactive, realtime application that engineers can utilize for comprehensive preliminary propulsion system design functions. RENS will employ computer science and artificial intelligence research in knowledge acquisition, computer code parallelization and objectification, expert system architecture design, and object-oriented programming. In 1995, a 3year grant from the NASA Lewis Research Center was awarded to Dr. Douglas Moreman and Dr. John Dyer of Southern University at Baton Rouge, Louisiana, to begin acquiring knowledge in liquid rocket propulsion systems. Resources of the University of West Florida in Pensacola were enlisted to begin the process of enlisting knowledge from senior NASA engineers who are recognized experts in liquid rocket engine propulsion systems. Dr. John Coffey of the University of West Florida is utilizing his expertise in interviewing and concept mapping techniques to encode, classify, and integrate information obtained through personal interviews. The expertise extracted from the NASA engineers has been put into concept maps with supporting textual, audio, graphic, and video material. A fundamental concept map was delivered by the end of the first year of work and the development of maps containing increasing amounts of information is continuing. Find out more information about this work at the Southern University/University of West Florida. In 1996, the Southern University/University of West Florida team conducted a 4day group interview with a panel of five experts to discuss failures of the RL10 rocket engine in conjunction with the Centaur launch vehicle. The discussion was recorded on video and audio tape. Transcriptions of the entire proceedings and an abbreviated video presentation of the discussion highlights are under development. Also in 1996, two additional 3year grants were awarded to conduct parallel efforts that would complement the work being done by Southern University and the University of West Florida. Dr. Prem Bhalla of Jackson State University in Jackson, Mississippi, is developing the architectural framework for RENS. By employing the Rose Rational language and Booch Object Oriented Programming (OOP) technology, Dr. Bhalla is developing the basic structure of RENS by identifying and encoding propulsion system components, their individual characteristics, and cross-functionality and dependencies. Dr. Ruknet Cezzar of Hampton University, located in Hampton, Virginia, began working on the parallelization and objectification of rocket engine analysis and design codes. Dr. Cezzar will use the Turbo C++ OOP language to translate important liquid rocket engine computer codes from FORTRAN and permit their inclusion into the RENS framework being developed at Jackson State University. The Southern University/University of West Florida grant was extended by 1 year to coordinate the conclusion of all three efforts in 1999.

Davidian, Kenneth O.↗

Women in Science: Fermilab Scientific Computing Specialist Krista Majewski

With February 11 marking the International Day of Women and Girls in Science, female physicists, engineers and computer scientists from CERN and Fermilab share their experiences of building careers in science. Krista Majewski came to Fermilab nine years ago as a software developer and now works in an operations role. She is a computing services specialist and part of the grid and cloud operations group, which manages computing clusters for the CMS experiment and other intensity frontier experiments at the lab. "My typical day would be maintaining the services that our group is responsible for and the machines that they run on. So if there are problems with a computing cluster where a user can't run their jobs, or they're trying to run on resources on the grid and they're unable to, then our group would be responsible for helping debug some of those issues," Krista says. Her path to programming at Fermilab has been winding. After receiving a degree in biomedical engineering, she went to work doing web development and programming for a large consulting firm, then moved to the financial industry. But programming called her back, and she earned a master's degree in computer science to start her new career. For Krista, programming is similar to something she enjoyed as child: solving puzzles. "I think it's a skill that you use in a lot of different ways," she says. Credits: Video production - Fermilab Creative Services Music Copyright: Universal Production Music Astral Light Chevalier Idea originally conceived by Tanya Levshina, Fermilab and Maria Dimou, CERN.

99 GENERAL AND MISCELLANEOUS↗

Classical optimization with imaginary-time block encoding on quantum computers: The MaxCut problem

Optimization problems in finance, physics, and computer science are typically very hard to tackle in classical computing; quantum computing could help speed up computations and provide efficient methods for tackling large problems. Typically, to treat a problem with a quantum computer, the optimal solution is cast as the ground state of a diagonal Hamiltonian. Here, we develop a method, called imaginary-time evolution block encoding (ITE-BE), based on a recent imaginary-time algorithm, which requires no variational parameter optimization, as all parameters can be derived analytically from the target Hamiltonian. We also demonstrate that our method can be successfully combined with other quantum algorithms such as the quantum approximate optimization algorithm (QAOA). For illustration, here we study the MaxCut problem. We find that the QAOA ansatz increases the postselection success of ITE-BE, and shallow QAOA circuits, when boosted with ITE-BE, achieve better performance than deeper QAOA circuits. For the special case of the transverse initial state, we adapt our block-encoding scheme to allow for a deterministic application of the first layer of the circuit.

Zhong, Dawei [University of Southern California, L↗

The future of computing beyond Moore’s Law

Moore’s Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon lithography have enabled this exponential miniaturization of electronics, but, as transistors reach atomic scale and fabrication costs continue to rise, the classical technological driver that has underpinned Moore’s Law for 50 years is failing and is anticipated to flatten by 2025. Here, this article provides an updated view of what a post-exascale system will look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also discusses the tapering of historical improvements, and how it affects options available to continue scaling of successors to the first exascale machine. Lastly, this article covers the many different opportunities and strategies available to continue computing performance improvements in the absence of historical technology drivers. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

97 MATHEMATICS AND COMPUTING↗

Visualization and Simulation of Carbon Structures with Higher Genus

The Computational Science Initiative (CSI) department at Brookhaven National Laboratory involves varied and interdisciplinary work through out all sciences. In particular, we worked within the realm of computational chemistry through the means of studying carbon nanotori structures via their visualization and simulation. Compounds like graphene and other carbon allotropes,such as the nanotorus, have been in the eye of scientists for several years due to their unique polyhex structures which provide unique topologies and therefore possibly unique material properties. C++ code to generate Cartesian coordinates for an arbitrary torus was utilized to allow the use of molecular editing and modeling programs, such as Avogadro or Visual Molecular Dynamics (VMD) to design multiple genus nanocarbon toroidal structures. Several files were generated that contained multiple genus to them, namely a double torus, triple torus, and quadruple torus, all based off of a single genus carbon nanotorus from previous said code. Bond angle information was then utilized through .report files generated from structures files (.xyz or .cml) to allow for vertices and thereby neighboring atoms to the vertices to be identified. With these identified atoms for the above multiple genus structures, as well as for the C240 buckyball fullerene and carbon nanotorus, we wrote C++ code to generate an adjacency matrix for each respective one. These matrices were then subsequently used to generate eigenvalues and eigenvectors through a Mathmatica function for each structure. Using these values we can study the energies of these systems and thereby its functionalities and properties.

97 MATHEMATICS AND COMPUTING↗

NASA Aeronautics Multidisciplinary Analysis and Design Fellowship Program

For a number of years, Virginia Tech had been on the forefront of research in the area of multidisciplinary analysis and design. In June of 1994, faculty members from aerospace and ocean engineering, engineering science and mechanics, mechanical engineering, industrial engineering, mathematics and computer sciences, at Virginia Tech joined together to form the Multidisciplinary Analysis and Design (MAD) Center for Advanced Vehicles. The center was established with the single goal: to perform research that is relevant to the needs of the US industry and to foster collaboration between the university, government and industry. In October of 1994, the center was chosen by NASA headquarters as one of the five university centers to establish a fellowship program to develop a graduate program in multidisciplinary analysis and design. The fellowship program provides full stipend and tuition support for seven U. S. students per year during their graduate studies. To advise us regarding the problems faced by the industry, an industrial advisory board has been formed consisting of representatives from industry as well as government laboratories. The function of the advisory board is to channel information from its member companies to faculty members concerning problems that need research attention in the general area of multidisciplinary design optimization (MDO). The faculty and their graduate students make proposals to the board on how to address these problems. At the annual board meeting in Blacksburg, the board discusses the proposals and suggests which students get funded under the NASA fellowship program. All students participating in the program are required to spend 3-6 months in industry working on their research projects. We are completing the third year of the fellowship program and have had three advisory board meetings in Blacksburg.

Grossman, B.↗

NASA Aeronautics Multidisciplinary Analysis and Design Fellowship Program

This program began as a grant from NASA Headquarters, NGT-10025, which was in effect from 10/l/93 until 10/31/96. The remaining funding for this effort was transferred from NASA Headquarters to NASA Langley and a new grant NGT-1-52155 was issued covering the period II/l/96 to 5/15/99. This report serves as the final report of NGT-1-52155. For a number of years, Virginia Tech had been on the forefront of research in the area of multidisciplinary analysis and design. In June of 1994, faculty members from aerospace and ocean engineering, engineering science and mechanics, mechanical engineering, industrial engineering, mathematics and computer sciences, at Virginia Tech joined together to form the Multidisciplinary Analysis and Design (MAD) Center for Advanced Vehicles. The center was established with the single goal: to perform research that is relevant to the needs of the US industry and to foster collaboration between the university, government and industry. In October of 1994, the center was chosen by NASA headquarters as one of the five university centers to establish a fellowship program to develop a graduate program in multidisciplinary analysis and design. The fellowship program provides full stipend and tuition support for seven U. S. students per year during their graduate studies. The grant is currently being administered by the NMO Branch of NASA Langley. To advise us regarding the problems faced by the industry, an industrial advisory board has been formed consisting of representatives from industry as well as government laboratories. The present membership includes major aerospace companies: Aurora Flight Sciences, Boeing: Philadelphia, Boeing: Long Beach, Boeing: Seattle, Boeing: St. Louis, Cessna, Ford, General Electric, Hughes, Lockheed-Martin: Palo Alto, Northrop-Grumman, Sikorsky, smaller, aerospace software companies: Aerosoft, Phoenix Integration and Proteus Engineering, along with representatives from government agencies, including: NASA Ames, Langley and Lewis. The function of the advisory board is to channel information from its member companies to faculty members concerning problems that need research attention in the general area of multidisciplinary design optimization (MDO). The faculty and their graduate students make presentations to the board on their research. The board makes recommendations on the research and suggests new areas and problems which need attention. Many students participating in the program spend 3-6 months in industry working on their research projects. We are completing the fifth year of the fellowship program and have had four advisory board meetings in Blacksburg. Ten students have spent the three month periods in industry. In addition to the research element of the MAD Center efforts we also have an academic component. We have developed a menu of design-related graduate courses and two new courses: one in Aerospace Manufacturing and another in MDO. Some of the MAD Center activities are described on the world-wide web at http://www.aoe.vt.edu/mads.html The MAD Center represents an innovative approach for joint Industry-Government-University cooperation in the development of a comprehensive program in engineering education which addresses the design needs of industry. The following charts list detail of the grant: mission of the MAD center, faculty members, purpose of the advisory board, board members, summary of the graduate and undergraduate program, history of the fellowship program, mission of the fellowship program, requirements of MAD fellows, course requirements, students supported, advisory board participants, and MAD center research papers

Grossman, B.↗

High-Performance Java Codes for Computational Fluid Dynamics

The computational science community is reluctant to write large-scale computationally -intensive applications in Java due to concerns over Java's poor performance, despite the claimed software engineering advantages of its object-oriented features. Naive Java implementations of numerical algorithms can perform poorly compared to corresponding Fortran or C implementations. To achieve high performance, Java applications must be designed with good performance as a primary goal. This paper presents the object-oriented design and implementation of two real-world applications from the field of Computational Fluid Dynamics (CFD): a finite-volume fluid flow solver (LAURA, from NASA Langley Research Center), and an unstructured mesh adaptation algorithm (2D_TAG, from NASA Ames Research Center). This work builds on our previous experience with the design of high-performance numerical libraries in Java. We examine the performance of the applications using the currently available Java infrastructure and show that the Java version of the flow solver LAURA performs almost within a factor of 2 of the original procedural version. Our Java version of the mesh adaptation algorithm 2D_TAG performs within a factor of 1.5 of its original procedural version on certain platforms. Our results demonstrate that object-oriented software design principles are not necessarily inimical to high performance.

Riley, Christopher↗

Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics

The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their as- sociated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.

Parete-Koon, Suzanne↗

Circuit complexity and functionality: A statistical thermodynamics perspective

Circuit complexity, defined as the minimum circuit size required for implementing a particular Boolean computation, is a foundational concept in computer science. Determining circuit complexity is believed to be a hard computational problem. Recently, in the context of black holes, circuit complexity has been promoted to a physical property, wherein the growth of complexity is reflected in the time evolution of the Einstein-Rosen bridge (“wormhole”) connecting the two sides of an anti-de Sitter “eternal” black hole. Here, we are motivated by an independent set of considerations and explore links between complexity and thermodynamics for functionally equivalent circuits, making the physics-inspired approach relevant to real computational problems, for which functionality is the key element of interest. In particular, our thermodynamic framework provides an alternative perspective on the obfuscation of programs of arbitrary length—an important problem in cryptography—as thermalization through recursive mixing of neighboring sections of a circuit, which can be viewed as the mixing of two containers with “gases of gates.” This recursive process equilibrates the average complexity and leads to the saturation of the circuit entropy, while preserving functionality of the overall circuit. The thermodynamic arguments hinge on ergodicity in the space of circuits which we conjecture is limited to disconnected ergodic sectors due to fragmentation. The notion of fragmentation has important implications for the problem of circuit obfuscation as it implies that there are circuits of same size and functionality that cannot be connected via a polynomial number of local moves. Furthermore, we argue that fragmentation is unavoidable unless the complexity classes NP and coNP coincide, a statement that implies the collapse of the polynomial hierarchy of computational complexity theory to its first level.

Science & Technology - Other Topics↗

VERAIn

CASL's modeling and simulation technology, the Virtual Environment for Reactor Applications (VERA), incorporates coupled physics and science-based models, state-of-the-art numerical methods, modern computational science, integrated uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single-effect experiments, and integral tests. The computational simulation component of VERA is the VERA Core Simulator (VERA-CS). The core simulator is the specific collection of multi-physics computer codes used to model and deplete a LWR core over multiple cycles. The core simulator has a single common input file that drives all of the different physics codes. The parser code, VERAIn, converts VERA Input into an XML file that is used as input to different VERA codes.

Simunovic, Srdjan↗

VERAIn

CASL's modeling and simulation technology, the Virtual Environment for Reactor Applications (VERA), incorporates coupled physics and science-based models, state-of-the-art numerical methods, modern computational science, integrated uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single-effect experiments, and integral tests. The computational simulation component of VERA is the VERA Core Simulator (VERA-CS). The core simulator is the specific collection of multi-physics computer codes used to model and deplete a LWR core over multiple cycles. The core simulator has a single common input file that drives all of the different physics codes. The parser code, VERAIn, converts VERA Input into an XML file that is used as input to different VERA codes.

Simunovic, Srdjan↗

Dehydration pathways of 1-propanol on HZSM-5 in the presence and absence of water

The Brønsted acid-catalyzed gas-phase dehydration of 1-propanol (0.075-4 kPa) was studied on zeolite H-MFI (Si/Al = 26, containing minimal amounts of extraframework Al moieties) in the absence and presence of co-fed water (0-2.5 kPa) at 413-443 K. It is shown that propene can be formed from monomeric and dimeric adsorbed 1-propanol. The stronger adsorption of 1-propanol relative to water indicates that the reduced dehydration rates in the presence of water are not a consequence of the competitive adsorption between 1-propanol and water. Instead, the deleterious effect is related to the different extents of stabilization of adsorbed intermediates and the relevant elimination/substitution transition states by water. Water stabilizes the adsorbed 1-propanol monomer significantly more than the elimination transition state, leading to a higher activation barrier and a greater entropy gain for the rate-limiting step, which eventually leads to propene. In a similar manner, an excess of 1-propanol stabilizes the adsorbed state of 1-propanol more than the elimination transition state. In comparison with the monomer-mediated pathway, adsorbed dimer and the relevant transition states for propene and ether formation are similarly, while less effectively, stabilized by intrazeolite water molecules. This work was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences, and was performed in part using the Molecular Sciences Computing Facility (MSCF) in the William R. Wiley Environmental Molecular Sciences Laboratory, a DOE national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located and the Pacific Northwest National Laboratory (PNNL). PNNL is operated by Battelle for DOE.

1-propanol↗

Engineering Computational Practices (Rev. 1)

This manual will attempt to motivate the use of an automated build system for the purposes of computational science and engineering. As part of this motivation, the surrounding computational practices of version control, documen tation, compute environment management, and regression testing will also be addressed as applied to the practice of computational engineering. Specifically, this manual intends to motivate the adoption of these traditional software engineering practices for use in research and production engineering simulation projects. This manual is not the first such effort in the greater scientific computing community. In fact, the authors relied heavily on the lesson plans of the Software Carpentry, established to teach computing skills to researchers in 1998. As the intention for this manual is to lay out fundamental practices of engineering computing, it will not attempt to fully teach the underlying concepts and will instead reference the well designed lesson plans of the Software Carpentry. Where possible, this manual will explain to general computing practices and concepts and limit discussion of specific software implementations to examples or vehicles for practice in concrete application. The specific software taught by the Software Carpentry curriculum is an excellent starting point to learn the core concepts of computational engi neering. However, the authors have found that applications to engineering simulation and analysis require translation of these software development concepts into the language and workflows of computational engineers. Adopting these computational tools may require engineers to re-imagine their workflows in some combination of traditional engineer ing and software concepts. It has also been necessary to extend existing software build systems for engineering practices beyond the simple wrap ping of engineering software execution. Where necessary, examples of specific software and their method of extension to engineering simulations will be given, with reference to the User Manual for recommended practical use. Where this manual relies on specific implementation examples, it should be understood that the practicing engineer may find that different software is more amenable to their specific work. It is always the overall collection of computational practices is more important than any specific software implementation. The ability to recognize which concepts are implemented by a software package will make a practicing engineer agile to changing project needs, computing resources, numeric solvers, programming languages, and even available funding.

42 ENGINEERING↗