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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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Survey and Assessment of Computational Capabilities for Advanced (non-LWR) Reactor Mechanistic Source Term Analysis
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EQMU & ECMF Advanced Simulations and Computing for Engineering Quantification
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Evaluation of the shear rate effect on the interfacial forces acting on a single bubble
Owing to the outstanding characteristics of mass and heat transfer efficiency, two-phase bubbly flows have wide applications in the nuclear engineering fields. However, the physics behind the bubbly flows phenomenon can be very complex due to the various parameters and phenomena involved. Thanks to the increasing computing power and advanced algorithms, computational fluid dynamics (CFD) approach has emerged as an effective tool for exploring the bubbly flows. In typical laminar channel or pipe flow, the flow field develops a parabolic velocity profile due to the wall friction. Assuming the shear rate across the bubble diameter is constant, the bubble will encounter various shear rates depending on its transverse position. Different shear rates may lead to the acceleration of transverse migration speed and influence the bubble rising velocity. In this summary, we evaluate the effect of shear rate on the interfacial forces (lift and drag) acting on a single bubble with the shear rate ranging from 3.8 to 8.3 s{sup -1} and the Eotvos number ranging from 2.58 to 4.45.
Exploratory study on potential safeguards applications for shared ledger technology
The International Atomic Energy Agency (IAEA) is responsible for providing credible assurance that countries are meeting their obligations not to divert or misuse nuclear materials and facilities for non-peaceful purposes. To this end, the IAEA integrates information about States’ nuclear material inventories and transactions with other types of data to draw its safeguards conclusions. As the amount and variety of data and information has increased, the IAEA’s data acquisition, management, and analysis processes have greatly benefited from advancements in computer science, data management, and cybersecurity during the last 20 years. Despite these advancements, inconsistent use of advanced computer technologies as well as political concerns among certain IAEA Member States centered on trust, transparency, and IAEA authorities limit the overall effectiveness and efficiency of IAEA safeguards. As a result, there is an ongoing need to strengthen the effectiveness and efficiency of IAEA safeguards while improving Member State cooperation and trust in the safeguards system. These chronic safeguards needs could be met with some emerging technologies, specifically those associated with the digital currency bitcoin.
Generalized dynamic engine simulation techniques for the digital computer
Recently advanced simulation techniques have been developed for the digital computer and used as the basis for development of a generalized dynamic engine simulation computer program, called DYNGEN. This computer program can analyze the steady state and dynamic performance of many kinds of aircraft gas turbine engines. Without changes to the basic program DYNGEN can analyze one- or two-spool turbofan engines. The user must supply appropriate component performance maps and design-point information. Examples are presented to illustrate the capabilities of DYNGEN in the steady state and dynamic modes of operation. The analytical techniques used in DYNGEN are briefly discussed, and its accuracy is compared with a comparable simulation using the hybrid computer. The impact of DYNGEN and similar all-digital programs on future engine simulation philosophy is also discussed.
Generalized dynamic engine simulation techniques for the digital computer
Recently advanced simulation techniques have been developed for the digital computer and used as the basis for development of a generalized dynamic engine simulation computer program, called DYNGEN. This computer program can analyze the steady state and dynamic performance of many kinds of aircraft gas turbine engines. Without changes to the basic program, DYNGEN can analyze one- or two-spool turbofan engines. The user must supply appropriate component performance maps and design-point information. Examples are presented to illustrate the capabilities of DYNGEN in the steady state and dynamic modes of operation. The analytical techniques used in DYNGEN are briefly discussed, and its accuracy is compared with a comparable simulation using the hybrid computer. The impact of DYNGEN and similar all-digital programs on future engine simulation philosophy is also discussed.
Generalized dynamic engine simulation techniques for the digital computers
Recently advanced simulation techniques have been developed for the digital computer and used as the basis for development of a generalized dynamic engine simulation computer program, called DYNGEN. This computer program can analyze the steady state and dynamic performance of many kinds of aircraft gas turbine engines. Without changes to the basic program, DYNGEN can analyze one- or two-spool turbofan engines. The user must supply appropriate component performance maps and design point information. Examples are presented to illustrate the capabilities of DYNGEN in the steady state and dynamic modes of operation. The analytical techniques used in DYNGEN are briefly discussed, and its accuracy is compared with a comparable simulation using the hybrid computer. The impact of DYNGEN and similar digital programs on future engine simulation philosophy is also discussed.
Modeling Protein–Protein and Protein–Ligand Interactions by the ClusPro Team in CASP16
ABSTRACT In the CASP16 experiment, our team employed hybrid computational strategies to predict both protein–protein and protein–ligand complex structures. For protein–protein docking, we combined physics‐based sampling—using ClusPro FFT docking and molecular dynamics—with AlphaFold (AF)‐based sampling, followed by AF‐based refinement. Our method produced numerous high‐accuracy complex models, including cases where AF alone failed, underscoring the critical role of physics‐based sampling alongside deep learning‐based refinement. For protein–ligand docking, we integrated the ClusPro LigTBM template‐based approach with a machine learning‐based confidence model for rescoring. The method preserves conserved interaction fragments derived from homologous complexes, followed by local resampling using physics‐based sampling and a diffusion model. Our template‐based strategy achieved a mean lDDT‐PLI of 0.69 across 233 targets, which was highly competitive. These results demonstrate that combining physics‐based modeling with AI‐driven refinement can significantly enhance the accuracy of both protein–protein and protein–ligand structure predictions.
Chemical and Conformational Control of the Spectroscopic Properties of Multi-Layer and Multi-Defect Carbon Dots
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Computational Requirements in Clean Energy and Manufacturing: Summary report of the virtual workshop held on June 28-29, 2021
On June 28–29, 2021, the US Department of Energy’s (DOE’s) Advanced Scientific Computing Research (ASCR) program in the Office of Science convened a workshop with the Energy Efficiency and Renew able Energy (EERE) program offices to assess the future need for advanced computing resources in the areas of clean energy and advanced manufacturing. In part, this discussion served as an update to earlier workshops and townhalls. ASCR is guided by DOE mission needs as it develops research programs, computers, and networks at the leading edge of technologies. As the exascale computing era dawns, technology changes are creating new opportunities for those who must use high-performance computing (HPC) and data systems effectively. The ASCR computing facilities are augmenting their strategy to adapt to changing science needs and emerging technologies and to leverage the utility of exascale computing across the federal government.
Computing technology in the 1980's
Advances in computing technology have been led by consistently improving semiconductor technology. The semiconductor industry has turned out ever faster, smaller, and less expensive devices since transistorized computers were first introduced 20 years ago. For the next decade, there appear to be new advances possible, with the rate of introduction of improved devices at least equal to the historic trends. The implication of these projections is that computers will enter new markets and will truly be pervasive in business, home, and factory as their cost diminishes and their computational power expands to new levels. The computer industry as we know it today will be greatly altered in the next decade, primarily because the raw computer system will give way to computer-based turn-key information and control systems.
An Overview of NASA's Intelligent Systems Program
NASA and the Computer Science Research community are poised to enter a critical era. An era in which - it seems - that each needs the other. Market forces, driven by the immediate economic viability of computer science research results, place Computer Science in a relatively novel position. These forces impact how research is done, and could, in worst case, drive the field away from significant innovation opting instead for incremental advances that result in greater stability in the market place. NASA, however, requires significant advances in computer science research in order to accomplish the exploration and science agenda it has set out for itself. NASA may indeed be poised to advance computer science research in this century much the way it advanced aero-based research in the last.
A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions
Modeling of heterogeneous materials and media is a problem of fundamental importance to a wide class of phenomena and systems, ranging from condensed matter physics, soft materials, and composite media to porous media, biological systems, geosystems, ceramic engineering, pharmaceutical science and even in space discoveries. Among the most important materials are granular systems, which have received intense interest from the engineering, physics, and mathematics communities. In this review paper, the recent developments and new advances in experimental, and computational methods on a variety of scales and physics that extend understanding to a wide range of materials and phenomena are reviewed. Experimental advances include computed neutron and nanometer-scale tomography, magnetic resonance imaging, refractive index matching, digital image correlation, acoustic emission analysis, and the most recent 4D techniques. Furthermore, a tremendous shift has occurred from the continuum scale to micro-scale and developing multiscale approaches. As such, various computational methods, including, constitutive modeling, discrete modeling, and multiscale approaches, have been developed. In conclusion, aside from all these evolutions, more complicated modeling called coupled, or multiphysics, systems representing a simultaneous presence of heat, fluid, chemical variation, and mechanical effect are also explored.
Combining Modeling and Gaming for Predictive Analytics
Many of our most significant challenges involve people. While human behavior has long been studied, there are recent advances in computational modeling of human behavior. With advances in computational capabilities come increases in the volume and complexity of data that humans must understand in order to make sense of and capitalize on these modeling advances. Ultimately, models represent an encapsulation of human knowledge. One inherent challenge in modeling is efficient and accurate transfer of knowledge from humans to models, and subsequent retrieval. The simulated real-world environment of games presents one avenue for these knowledge transfers. In this paper we describe our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for modeling.
Coding the Computing Continuum: Fluid Function Execution in Heterogeneous Computing Environments
Advances in network technologies have greatly decreased barriers to accessing physically distributed computers. This newfound accessibility coincides with increasing hardware specialization, creating exciting new opportunities to dispatch workloads to the best resource for a specific purpose, rather than those that are closest or most easily accessible. We present Delta, a service designed to intelligently schedule function-based workloads across a distributed set of heterogeneous computing resources. Delta implements an extensible architecture in which different predictors and scheduling algorithms can be integrated to provide dynamically evolving estimates of function execution times on different resources-estimates that can be used to determine the most appropriate location for execution. We describe predictors for function runtime, data transfer time, and cold-start resource provisioning and configuration delay; dynamic learning methods that update predictor models over time; and scheduling strategies that take into account both function and endpoint information. We show that these methods can halve workload makespan when compared with a strategy that selects the fastest resource, and decrease makespan by a factor of five when compared to a round robin strategy, when deployed on a heterogeneous testbed with resources ranging from a Raspberry Pi to a GPU node in an academic cloud.
Advances and trends in computational structures technology
The major goals of computational structures technology (CST) are outlined, and recent advances in CST are examined. These include computational material modeling, stochastic-based modeling, computational methods for articulated structural dynamics, strategies and numerical algorithms for new computing systems, multidisciplinary analysis and optimization. The role of CST in the future development of structures technology and the multidisciplinary design of future flight vehicles is addressed, and the future directions of CST research in the prediction of failures of structural components, the solution of large-scale structural problems, and quality assessment and control of numerical simulations are discussed.