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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 721 records · Page 40

GPU/MIC Acceleration of the LHC High Level Trigger to Extend the Physics Reach at the LHC

The quest for rare new physics phenomena leads the PI to propose evaluation of coprocessors based on Graphics Processing Units (GPUs) and the Intel Many Integrated Core (MIC) architecture for integration into the trigger system at LHC. This will require development of a new massively parallel implementation of the well known Combinatorial Track Finder which uses the Kalman Filter to accelerate processing of data from the silicon pixel and microstrip detectors and reconstruct the trajectory of all charged particles down to momentums of 100 MeV. It is expected to run at least one order of magnitude faster than an equivalent algorithm on a quad core CPU for extreme pileup scenarios of 100 interactions per bunch crossing. The new tracking algorithms will be developed and optimized separately on the GPU and Intel MIC and then evaluated against each other for performance and power efficiency. The results will be used to project the cost of the proposed hardware architectures for the HLT server farm, taking into account the long term projections of the main vendors in the market (AMD, Intel, and NVIDIA) over the next 10 years. Extensive experience and familiarity of the PI with the LHC tracker and trigger requirements led to the development of a complementary tracking algorithm that is described in [arxiv: 1305.4855], [arxiv: 1309.6275] and preliminary results accepted to JINST.

97 MATHEMATICS AND COMPUTING↗

Electrical and Electronics Technical Team Roadmap

The Electrical and Electronics Technical Team’s (EETT's) mission is to enable cost-effective, smaller, lighter, and efficient power electronics and electric motors for electric traction drive systems (ETDSs) while maintaining performance of internal combustion engine (ICE)-based vehicles. The EETT also identifies technology gaps, establishes R&D targets, develops a roadmap to achieve technical targets and goals, and evaluates the R&D progress toward meeting the established R&D targets and goals.

electric motors↗

New Platform Provides Innovation

Sky Bridge is the primary unclassified scientific computing platform at Sandia, serving all Mission Areas within the Laboratories. At the formal ribbon cutting in December 2014, Laboratories Director Paul Hommert emphasized the importance of the Institutional Computing Program in providing a critical core Laboratories capability. The deployment of Sky Bridge more than doubled the computing cycles available in Sandia’s restricted computing environment, while incorporating the same underlying architecture as the existing ASC/TLCC2 compute clusters, thus allowing many existing computer codes to run on the system without any major modifications. Sky Bridge immediately addressed the shortfall in projected computing cycles for Sandia’s programs of energy and environment, nuclear weapons life expectancy program (NW LEP), and Applied Laboratory Technology (ALT). From a technological perspective, Sky Bridge is contributing to the readiness of the data center facility and operations personnel for a transition to liquid cooling in future HPC systems and other high-density systems. By comparing the performance and energy costs of Sky Bridge to similar systems (e.g., Dark Bridge) that are air-cooled rather than liquid-cooled, it will also provide valuable data for making return on investment decisions for future purchases. Installation of Sky Bridge enables decommissioning of the Red Sky supercomputer, reduce energy and support costs, and make room for future HPC systems already planned through the ASC and Institutional Computing programs. Sky Bridge’s use of liquid cooling (cold plate to the systems processors) and more efficient power distribution (480 V direct to the rack) saved over $\$$700, 000 in construction costs while reducing annual operating costs by $\$$120,000.

97 MATHEMATICS AND COMPUTING↗

Advanced Supercritical Carbon Dioxide Brayton Cycle Development

Fluids operating in the supercritical state have promising characteristics for future high efficiency power cycles. In order to develop power cycles using supercritical fluids, it is necessary to understand the flow characteristics of fluids under both supercritical and two-phase conditions. In this study, a Computational Fluid Dynamic (CFD) methodology was developed for supercritical fluids flowing through complex geometries. A real fluid property module was implemented to provide properties for different supercritical fluids. However, in each simulation case, there is only one species of fluid. As a result, the fluid property module provides properties for either supercritical CO 2 (S-CO 2 ) or supercritical water (SCW). The Homogeneous Equilibrium Model (HEM) was employed to model the two-phase flow. HEM assumes two phases have same velocity, pressure, and temperature, making it only applicable for the dilute dispersed two-phase flow situation. Three example geometries, including orifices, labyrinth seals, and valves, were used to validate this methodology with experimental data. For the first geometry, S-CO 2 and SCW flowing through orifices were simulated and compared with experimental data. The maximum difference between the mass flow rate predictions and experimental measurements is less than 5%. This is a significant improvement as previous works can only guarantee 10% error. In this research, several efforts were made to help this improvement. First, an accurate real fluid module was used to provide properties. Second, the upstream condition was determined by pressure and density, which determines supercritical states more precise than using pressure and temperature. For the second geometry, the flow through labyrinth seals was studied. After a successful validation, parametric studies were performed to study geometric effects on the leakage rate. Based on these parametric studies, an optimum design strategy for the see-through labyrinth seals was proposed. A stepped labyrinth seal, which mimics the behavior of the labyrinth seal used in the Sandia National Laboratory (SNL) S-CO 2 Brayton cycle, was also tested in the experiment along with simulations performed. The rest of this study demonstrates the difference of valves' behavior under supercritical fluid and normal fluid conditions. A small-scale valve was tested in the experiment facility using S-CO 2 . Different percentages of opening valves were tested, and the measured mass flow rate agreed with simulation predictions. Two transients from a real S-CO 2 Brayton cycle design provided the data for valve selection. The selected valve was studied using numerical simulation, as experimental data is not available.

42 ENGINEERING↗

10 MW, L-Band Klystron for Accelerators

This program developed a 10 MW, pulsed, Annular Beam Klystron (ABK) for accelerator applications. This is an alternative RF source to multiple beam klystrons MBKs), which are more complex and considerably more expensive. The ABK uses a single, annular cathode and a single beam tunnel with fundamental mode cavities. The operating specifications (voltage, efficiency, power, bndwidth, duty, etc.) are the same as for comparable MBKs.

43 PARTICLE ACCELERATORS↗

Instability of a witness bunch in a plasma bubble

The stability of a trailing witness bunch, accelerated by a plasma wake accelerator (PWA) in a blow-out regime, is discussed. The instability growth rate as well as the energy spread, required for BNS damping, are obtained. A relationship between the PWA power efficiency and the BNS energy spread is derived.

43 PARTICLE ACCELERATORS↗

The Institute for Sustained Performance, Energy, and Resilience Final Project Report

Over the course of the five years of the Scientific Discovery through Advanced Computation (SciDAC-3) program, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) exploited a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry, and materials science. The computing systems underpinning this work increased in performance potential from tens to hundreds of PFlop/s, but in the process evolving significantly from architectures in 2011, when SciDAC-3 began. Although Moore's law continues unabated, the end of Dennard scaling has necessitated a fundamental shift in computer architecture focused on power efficiency. To that end, processors are increasingly varied as they strive to satisfy performance, productivity, reliability, and energy efficiency in the face of divergent computational requirements. The diversity among these machines presents a number of challenges to merely porting today's scientific applications, much less achieving good performance. Therefore, at the beginning of SciDAC-3, USC and its collaborators anticipated that both vastly increased scale (e.g., more chips, more cores per chip, wider SIMD) and heterogeneity would exacerbate performance optimization challenges while simultaneously promoting the issues of energy and heterogeneity will exacerbate performance optimization challenges while simultaneously promoting the issues of energy consumption and resilience to the forefront. To ensure that DOE's computational scientists could successfully exploit emerging high performance computing (HPC) systems, DOE SC’s Advanced Scientific Computing Research Program (ASCR) funded the SciDAC-3 Institute for Sustained Performance, Energy, and Resilience (SUPER). Led by USC, this was a broadly based project with expertise in compilers and system tools, performance engineering, energy management, and resilience. SUPER followed the successful model developed in the previous SciDAC-2 Performance Engineering Research Institute (PERI) of leveraging the research investments DOE and others have made and integrating the results to create new capabilities beyond the reach of any one group. To accomplish this, SUPER was organized into multi-institution teams conducting the research activities in performance portability, energy efficiency, exascale resilience, and overall optimization. SUPER researchers also collaborated with other SciDAC-3 institutes, 13 of the 19 Scientific Computation Application Partnerships (SAP), as well as the broader DOE computational sciences community. These collaborations both focused our research on the real challenges facing petascale scientific computing as well as ensured the broad and immediate impact of the results of our research.

97 MATHEMATICS AND COMPUTING↗

Fluid Stratification Separate Effects Analysis, Testing and Benchmarking

High Temperature Gas Reactors (HTGRs) are positioned to disrupt local and global markets via their unique ability to produce carbon-free process heat, high efficiency power generation, and passively safe operational features. However, significant impediments still exist to delay deployment of this particular technology, including a lack of experimental data, verified code application, and lack of consensus with regards to severe accident progression. In particular, air ingress accidents represent a particular challenge to designers and engineers, as they represent low probability, but highly complex, accident scenarios. Including phenomena such as molecular diffusion, free convection, and complex heat and mass transfer paths, experimental and traceable data is essential to maturing the state of the industry. Therefore, this work presents an experimental investigation of the transition to natural convection in HTGR applications using the Stratified Flow Separate Effects Test Facility, housed at Oregon State University. In particular, this work will present data that challenges the assumption that molecular diffusion is a significant factor in this severe accident in the reference facility of the General Atomic 600 MW th Gas Turbine-Modular Helium Reactor (GT-MHR). Rather, experimentally produced data shows a statistically suggestive retardant effect of cross duct orientation, indicating that ingress mechanics may be fundamentally altered via facility geometry. Experimentally, this is achieved using a simplified cross duct that may be positioned in one of two ways so as to provide either horizontal or vertical access to the lower plenum area. Onset of natural convection (ONC) is measured using an oxygen sensor probe, immersed in the helium working fluid, so as to provide direct indication of air presence in the upper plenum. This document will present the doctoral dissertation produced by this work, along with its analysis, experimental data, observations, and conclusions, in addition to select documents that will highlight critical changes during the development process. Those documents will include the quality assurance plan, all subsequent change requests, and the engineering transfer from Harris Thermal in order to establish the most complete quality record possible.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Exascale Operating Systems and Runtime Software Report

Here U.S. Department of Energy (DOE) workshops and reports have identified four key exascale challenges: dramatically improving power efficiency; improving resilience in the presence of increasing faults; enabling efficient data movement across deepening memory hierarchies and new storage technologies; and managing dramatically increased parallelism, especially at the node level. Software solutions that address these challenges must also improve programmability, expanding the community of computational scientists who can use leadership-class platforms. To address these challenges, DOE must develop new techniques, novel designs, and advanced software architectures for next-generation exascale software infrastructure. In this report, we discuss challenges and approaches to exascale operating system and runtime (OS/R) software. The Exascale Operating Systems and Runtime (OS/R) Software Technical Council canvassed hardware architects, application programmers, parallel tool developers, DOE high-performance computing (HPC) facilities, and the vendors that sell and support integrated platforms. After considering the collective requirements of these constituents and examining the future research challenges and current software gaps, the council recommends that DOE invest in targeted advanced computer science research and in specific coordinating activities to enable the effective and successful development of anticipated exascale systems.

97 MATHEMATICS AND COMPUTING↗

Active and Nonreciprocal Radio-Frequency Acoustic Microsystems

Radio frequency (RF) devices are becoming more multi-band, increasing the number of filters and other front-end components while simultaneously pushing towards reduced cost, size, weight, and power (CSWaP). One approach to reducing CSWaP is to augment the achievable functionalities of electromechanical/acoustic filtering chips to include "active" and nonlinear functionalities, such as gain and mixing. The acoustoelectric (AE) effect could enable such active acoustic wave devices. We have examined the AE effect with a leaky surface acoustic wave (LSAW) in a monolithic structure of epitaxial indium gallium arsenide (In GaAs) on lithium niobate (LiNb0 3 ). This lead to experimentally demonstrated state-of-the-art SAW amplifier performance in terms of gain per acoustic wavelength, reduced power consumption, and increased power efficiency. We quantitatively compare the amplifier performance to previous notable works and discuss the outlook of active acoustic wave components using this material platform. Ultimately, this could lead to smaller, higher-performance RF signal processors for communications applications.

42 ENGINEERING↗

Fast Data Processing for Hyperspectral Sensors on Small Platforms

Hyperspectral imaging is a very promising technology for nuclear proliferation detection. However, due to size and weight restrictions, small hyperspectral platforms such as satellites and small drones lack the on-board computing resources for accurate, real-time analysis of the enormous flow of data that a continuously operating hyperspectral sensor generates. This severely limits satellite systems, which can collect far more data than what they can telemeter, and hinders the ability of all platforms to adapt their missions on the fly in response to observations. This program addresses the hyperspectral data processing challenge through development of new, fast and accurate algorithms that produce data products in real time. The algorithms circumvent the major computational bottlenecks in existing processing streams, and would be incorporated in lightweight, power-efficient single-board computer systems. The toolkit of fast algorithms will be immediately useful in current and future hyperspectral systems being built by the Government and by private industry, including drone-based systems and satellite constellations that acquire timely global imagery.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Current possibilities and future opportunities for erasure coded computations

The key capability established through the research funded by this award are erasure coded computations for linear systems, in serial and in parallel. This capability enables powerful efficient and scalable alternatives to existing linear system solvers in fault-prone computational systems.

97 MATHEMATICS AND COMPUTING↗

Supporting Co-Design of Extreme-Scale Systems with In Situ Visual Analysis of Event-Driven Simulations (Final Report)

Extreme-scale systems for compute- and data-centric science are pushing the boundaries of system architectures in order to achieve ambitious goals in terms of computing capability, resilience, and power efficiency. Future systems necessitate emerging designs that incorporate new technologies, system organizations, and computer science techniques, and these changes are not yet well understood. Discrete-event-driven simulation of computing system architectures and subsystems has emerged as a productive and cost-effective means to evaluating potential designs, along with capabilities for executing these simulations of extreme-scale systems. However, techniques for analyzing the behavior of these simulations have not kept pace with our ability to perform the simulations, preventing us from extracting the most value from this promising approach. The objective of this project is to support the codesign of extreme-scale system architectures for compute and data-centric science through research and development of novel methods for analysis and visualization of large-scale event-driven simulations.

97 MATHEMATICS AND COMPUTING↗

Gallium Nitride Superjunction Fin Field Effect Transistor (Continued Funding Report)

The goal of this project is to develop the gallium vacancy assisted diffusion (GAID) method in GaN and apply it to demonstrate 2-terminal, 3-terminal, and large area Superjunction-enhanced modules. These devices will find use in high efficiency power conversion applications with the capability of operating at higher voltages, higher frequency, and less loss than comparable stat-of- the-art devices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High Voltage Regrown GaN P-N Diodes Enabled by Defect and Doping Control

This project studied and implemented methods to form GaN p-n diodes using selective area regrowth to achieve selective area doping. Successful selective area doping of GaN p-n diodes is an enabling factor to realize more advanced devices such as vertical transistors. The general challenge to selective area regrowth of GaN is that the primary etch method, inductively coupled plasma (ICP), damages the crystal and causes high leakage when didoes are formed by regrowth on the etched surface. Our approach used low damage etch methods following ICP etch to remove crystal damage and reduced leakage in the regrown diode. This project demonstrated 1.6 kV etched-and-regrown GaN p-n diodes using planar (non-selective) regrowth and 840 V etched-and-regrown p-n diodes using selective area regrown. Enabling factors were use of a low-damage reactive ion etch (RIE) to remove damage caused by the primary ICP etch combined with a multi-step junction terminal extension (JTE) process. Deep level defect investigation quantitatively correlated a deep level near the middle of the GaN band gap with ICP etch-induced leakage that was greatly mitigated by using a slow, low damage RIE process. This research is economically feasible for commercialization because the processes used in this project, including substrate type and source, epitaxial crystal growth and fabrication techniques are all standard to the GaN semiconductor industry. The fundamental understanding and foundational ability to produce kV-class GaN p-n diodes through etch-and-regrowth provides a path to realize high power, high efficiency GaN power switches that can significantly outperform commercial devices for next-generation electrical power conversion and transmission systems.

36 MATERIALS SCIENCE↗

Gallium Nitride Superjunction Transistor (Continued Funding Report)

The initial goal of this project is to develop the gallium vacancy assisted diffusion (GAID) method in GaN and apply it to demonstrate 2-terminal, 3-terminal, and large area Superjunction-enhanced modules. These devices will find use in high efficiency power conversion applications with the capability of operating at higher voltages, higher frequency, and less loss than comparable stat-ofthe-art devices. The approach of this project has been to utilize simulation tools to drive diffusion experiments and inform semiconductor device fabrication processes. VASP has been relied upon to simulate first principles diffusion mechanisms while SILVACO TCAD has been utilized to understand tradeoffs of the the critical dimensions in GaN devices.

42 ENGINEERING↗

Rechargeable Micro-Batteries

The quest for efficient power sources for small sensors has led to a growing interest in rechargeable micro-batteries, offering the potential to harness energy from various sources for extended periods. This project delves into a multifaceted project aimed at enhancing the performance and viability of rechargeable micro-batteries in this context. The Pacific Northwest National Laboratory (PNNL) has leveraged its expertise in primary micro-battery development, evolving into a software-driven approach for designing cylindrical micro-batteries. This project addresses the cycle life issue through innovative cell design, electrode optimization, and electrolyte refinement. A case study of the MB1842 rechargeable micro-battery demonstrates the promising outcomes of these advancements, showcasing a capacity of 0.32 mAh at ~1C (0.35 mA) and remarkable cycle performance, extending the cycle life to 510-570 cycles at 80% end-of-life (EOL), 710-760 cycles at 70% EOL and 840-940 cycles at 60% EOL, thereby ensuring a service life of 10 years for these rechargeable micro-batteries. This endeavor represents a significant stride towards unlocking the full potential of rechargeable micro-batteries, paving the way for their widespread application in small sensor technologies. The outcome from this project also successfully supports the award of a new project: 80621 - Self-Powered Modular Acoustic Telemetry System with Sensing.

25 ENERGY STORAGE↗

Celeritas R&D Report: Accelerating Geant4

Celeritas is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a Graphics Processing Unit (GPU)-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.4, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling straightforward integration of Celeritas into the high energy physics (HEP) experimental frameworks CMSSW and ATLAS FullSimLight. On the Perlmutter supercomputer, Celeritas performs EM physics between 3× and 18× faster using the machine’s Nvidia GPUs compared to using only CPUs, corresponding to an electrical power efficiency up to a factor of 5. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.7–2.2× on GPU and 1.2× on CPU. In a CMS test application using tt¯ events and the prototype Run 4 configuration, compared to Geant4 CPU, Celeritas with a Nvidia A100 improves overall throughput up to a factor of 2.7× but cannot be efficiently shared with more than 8 cores.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗