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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 73 records · Page 4

Performance Analysis of Traditional and Data-Parallel Primitive Implementations of Visualization and Analysis Kernels

Measurements of absolute runtime are useful as a summary of performance when studying parallel visualization and analysis methods on computational platforms of increasing concurrency and complexity. We can obtain even more insights by measuring and examining more detailed measures from hardware performance counters, such as the number of instructions executed by an algorithm implemented in a particular way, the amount of data moved to/from memory, memory hierarchy utilization levels via cache hit/miss ratios, and so forth. This work focuses on performance analysis on modern multi-core platforms of three different visualization and analysis kernels that are implemented in different ways: one is "traditional", using combinations of C++ and VTK, and the other uses a data-parallel approach using VTK-m. Our performance study consists of measurement and reporting of several different hardware performance counters on two different multi-core CPU platforms. The results reveal interesting performance differences between these two different approaches for implementing these kernels, results that would not be apparent using runtime as the only metric.

97 MATHEMATICS AND COMPUTING↗

TESTING AND PERFORMANCE ANALYSIS OF NASA 5 CM BY 5 CM BI-SUPPORTED SOLID OXIDE ELECTROLYSIS CELLS OPERATED IN BOTH FUEL CELL AND STEAM ELECTROLYSIS MODES

A series of 5 cm by 5 cm bi-supported Solid Oxide Electrolysis Cells (SOEC) were produced by NASA for the Idaho National Laboratory (INL) and tested under the INL High Temperature Steam Electrolysis program. The results from the experimental demonstration of cell operation for both hydrogen production and operation as fuel cells is presented. An overview of the cell technology, test apparatus and performance analysis is also provided. The INL High Temperature Steam Electrolysis laboratory has developed significant test infrastructure in support of single cell and stack performance analyses. An overview of the single cell test apparatus is presented. The test data presented in this paper is representative of a first batch of NASA's prototypic 5 cm by 5 cm SOEC single cells. Clearly a significant relationship between the operational current density and cell degradation rate is evident. While the performance of these cells was lower than anticipated, in-house testing at NASA Glenn has yielded significantly higher performance and lower degradation rates with subsequent production batches of cells. Current post-test microstructure analyses of the cells tested at INL will be published in a future paper. Modification to cell compositions and cell reduction techniques will be altered in the next series of cells to be delivered to INL with the aim to decrease the cell degradation rate while allowing for higher operational current densities to be sustained. Results from the testing of new batches of single cells will be presented in a future paper.

08 HYDROGEN↗

New machine protection system at the Spallation Neutron Source – design process and performance analysis

A New Machine Protection System (MPS) at the Spallation Neutron Source (SNS) was developed and implemented on µTCA-based hardware platforms. The system monitors more than 2500 field inputs and shuts off the beam within 10 µs if adverse events occur. We will present system level design process of various firmware and software components as well as the system integration into EPICS environment. The performance analysis of the MPS after two SNS run cycles will also be presented.

Bobrek, Miljko [ORNL] (ORCID:0000000332763451)↗

Performance Analysis of a Ground Source Heat Pump System Using Mine Water as Heat Sink and Source

This paper summarizes a case study of an innovative ground source heat pump (GSHP) system that uses flooded mines as a heat source and heat sink. This GSHP system provides space conditioning to a 56,000 sq ft 2 (5,203 m 2 ) newly constructed research facility, in conjunction with supplementary existing steam heating and air-cooled chiller systems. Heat transfer performance and overall efficiency of the GSHP system were analysed using the available measured data from January through July 2014. The performance analysis identified some issues with using mine water for cooling and the integration of the GSHP system with the existing steam heating system. Recommendations were made to improve the control and operation of the GSHP system. These recommendations, in conjunction with the available measured data, were used to predict the annual energy use of the system. Finally, the energy and cost savings and CO 2 emission reduction potential of the GSHP system were estimated by comparing with a baseline scenario. This case study provides insights into the performance of and potential issues with the mine-water source heat pump system, which is relatively under-explored compared to other GSHP system designs and configurations.

42 ENGINEERING↗

A Cost-Performance Analysis of a Sodium Heat Engine for Distributed Concentrating Solar Power

We present that a sodium thermal electrochemical converter (Na-TEC) generates electricity directly from heat through isothermal expansion of sodium ions across a beta"-alumina solid-electrolyte. This heat engine has been considered for use with conventional concentrating solar power (CSP) systems before. However, unlike previous single-stage devices, the improved design uses two stages with an interstage reheat, allowing more economical and efficient conversion up to 29% at a hot side temperature of 850 °C. Herein, a cost-performance analysis for this improved design assesses opportunities for distributed-CSP in the context of micro-combined heat and power systems. A high-level techno-economic analysis (TEA) is presented that explores four scenarios where a Na-TEC is used as the heat engine for a distributed-CSP system. Overnight capital cost and levelized cost of electricity (LCOE) are estimated for a system lifetime of 30 years, revealing that overnight capital costs in a range from $3.57 to $17.71 per W e are feasible, which equate to LCOEs from 6.9 to 17.2 cents kWh e -1 . This analysis makes a significant contribution by concurrently quantifying the efficiency and unit costs for a range of multistage configurations, and demonstrating that a Na-TEC may be a promising alternative to Stirling engines for distributed-CSP systems at residential scale of 1–5 kW e .

14 SOLAR ENERGY↗

A Divergence Statistics Extension to VTK for Performance Analysis

This report follows the series of previous documents ([PT08, BPRT09b, PT09, BPT09, PT10, PB13], where we presented the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k -means, order and auto-correlative statistics engines which we developed within the Visualization Tool Kit ( VTK ) as a scalable, parallel and versatile statistics package. We now report on a new engine which we developed for the calculation of divergence statistics, a concept which we hereafter explain and whose main goal is to quantify the discrepancy, in a stasticial manner akin to measuring a distance, between an observed empirical distribution and a theoretical, "ideal" one. The ease of use of the new diverence statistics engine is illustrated by the means of C++ code snippets. Although this new engine does not yet have a parallel implementation, it has already been applied to HPC performance analysis, of which we provide an example.

97 MATHEMATICS AND COMPUTING↗

High-performance analysis of filtered semantic graphs

High performance is a crucial consideration when executing a complex analytic query on a massive semantic graph. In a semantic graph, vertices and edges carry "attributes" of various types. Analytic queries on semantic graphs typically depend on the values of these attributes; thus, the computation must either view the graph through a filter that passes only those individual vertices and edges of interest, or else must first materialize a subgraph or subgraphs consisting of only the vertices and edges of interest. The filtered approach is superior due to its generality, ease of use, and memory efficiency, but may carry a performance cost. In the Knowledge Discovery Toolbox (KDT), a Python library for parallel graph computations, the user writes filters in a high-level language, but those filters result in relatively low performance due to the bottleneck of having to call into the Python interpreter for each edge. In this work, we use the Selective Embedded JIT Specialization (SEJITS) approach to automatically translate filters defined by programmers into a lower-level efficiency language, bypassing the upcall into Python. We evaluate our approach by comparing it with the high-performance C++ /MPI Combinatorial BLAS engine, and show that the productivity gained by using a high-level filtering language comes without sacrificing performance.

97 MATHEMATICS AND COMPUTING↗

Reducing the Carbon Footprint of Commercial Refrigeration Systems Using Life Cycle Climate Performance Analysis: From System Design to Refrigerant Options

In this paper, Life Cycle Climate Performance (LCCP) analysis is used to estimate lifetime direct and indirect carbon dioxide equivalent gas emissions of various refrigerant options and commercial refrigeration system designs, including the multiplex DX system with various hydrofluorocarbon (HFC) refrigerants, the HFC/R744 cascade system incorporating a medium-temperature R744 secondary loop, and the transcritical R744 booster system. The results of the LCCP analysis are presented, including the direct and indirect carbon dioxide equivalent emissions for each refrigeration system and refrigerant option. Based on the results of the LCCP analysis, recommendations are given for the selection of low GWP replacement refrigerants for use in existing commercial refrigeration systems, as well as for the selection of commercial refrigeration system designs with low carbon dioxide equivalent emissions, suitable for new installations.

Fricke, Brian A↗

Dynamic Analysis of Hybrid Energy Systems under Flexible Operation and Variable Renewable Generation -- Part I: Dynamic Performance Analysis and Part II: Dynamic Cost

Dynamic analysis of hybrid energy systems (HES) under flexible operation and variable renewable generation is considered in order to better understand various challenges and opportunities associated with the high system variability arising from the integration of renewable energy into the power grid. Unique consequences are addressed by devising advanced HES solutions in which multiple forms of energy commodities, such as electricity and chemical products, may be exchanged. Dynamic models of various unit operations are developed and integrated within two different HES options. One HES option, termed traditional, produces electricity only and consists of a primary heat generator (PHG) (e.g., a small modular reactor), a steam turbine generator, a wind farm, and a battery storage. The other HES option, termed advanced, includes not only the components present in the traditional option but also a chemical plant complex to repurpose excess energy for non-electricity services, such as for the production of chemical goods (e.g., transportation fuel). In either case, a given HES is connected to the power grid at a point of common coupling and requested to deliver a certain electricity generation profile as dictated by a regional power grid operator based on a predicted demand curve. Dynamic analysis of these highly-coupled HES are performed to identify their key dynamical properties and limitations and to prescribe solutions for best managing and mitigating the high variability introduced from incorporating renewable energy into the energy mix. A comparative dynamic cost analysis is also conducted to determine best HES options. The cost function includes a set of metrics for computing fixed costs, such as fixed operations and maintenance (O&M) and overnight capital costs, and also variable operational costs, such as cost of variability, variable O&M cost, and cost of environmental impact, together with revenues. Assuming different options for implementing PHG (e.g., natural gas, coal, nuclear), preliminary results identify the level of renewable penetration at which a given advanced HES option (e.g., a nuclear hybrid) becomes increasingly more economical than a traditional electricity-only generation solution. Conditions are also revealed under which carbon resources may be better utilized as carbon sources for chemical production rather than as combustion material for electricity generation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of Accelerated Steady-state Test Capsule Experiments to Replicate EBR-II Fuel Behavior Using BISON Fuel Performance Analysis

Here in this work, BISON fuel performance calculations were performed to predict the fuel behavior of accelerated burnup U-Pu-Zr fuel, with temperature operation conditions of the fuel and the cladding mirroring conditions within EBR-II fuel pins. The temperature operating conditions within the FAST accelerated burnup rods were aimed at replicating EBR-II X447/X447A fuel surface and inner cladding surface temperatures. Due to the FAST capsule design, these temperatures can be replicated with fission rate densities being significantly increased. fuel performance modeling has not been assessed for novel experiments such as accelerated burnup utilizing the FAST capsule within ATR. This is an important step in understanding accelerated irradiation methods as many performance models are empirical models conforming to the results of PIE but do not always include physical models that would represent the changes in irradiation tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

The characterization, modeling, analysis, and tuning of software performance has been a central topic in High Performance Computing (HPC) since its early beginnings. The overall goal is to make HPC software run faster on particular hardware, either through better scheduling, on-node resource utilization, or more efficient distributed communication.

97 MATHEMATICS AND COMPUTING↗

Refining HPCToolkit for application performance analysis at exascale

As part of the US Department of Energy’s Exascale Computing Project (ECP), Rice University has been refining its HPCToolkit performance tools to better support measurement and analysis of applications executing on exascale supercomputers. To efficiently collect performance measurements of GPU-accelerated applications, HPCToolkit employs novel non-blocking data structures to communicate performance measurements between tool threads and application threads. To attribute performance information in detail to source lines, loop nests, and inlined call chains, HPCToolkit performs parallel analysis of large CPU and GPU binaries involved in the execution of an exascale application to rapidly recover mappings between machine instructions and source code. To analyze terabytes of performance measurements gathered during executions at exascale, HPCToolkit employs distributed-memory parallelism, multithreading, sparse data structures, and out-of-core streaming analysis algorithms. To support interactive exploration of profiles up to terabytes in size, HPCToolkit’s hpcviewer graphical user interface uses out-of-core methods to visualize performance data. The result of these efforts is that HPCToolkit now supports collection, analysis, and presentation of profiles and traces of GPU-accelerated applications at exascale. These improvements have enabled HPCToolkit to efficiently measure, analyze and explore terabytes of performance data for executions using as many as 64K MPI ranks and 64K GPU tiles on ORNL’s Frontier supercomputer. HPCToolkit’s support for measurement and analysis of GPU-accelerated applications has been employed to study a collection of open-science applications developed as part of ECP. This paper reports on these experiences, which provided insight into opportunities for tuning applications, strengths and weaknesses of HPCToolkit itself, as well as unexpected behaviors in executions at exascale.

Adhianto, Laksono↗

Performance Analysis of an Optimization Algorithm for Metamaterial Design on the Integrated High-Performance Computing and Quantum Systems

Optimizing metamaterials with complex geometries is a big challenge. Although an active learning algorithm, combining machine learning (ML), quantum computing, and optical simulation, has emerged as an efficient optimization tool, it still faces difficulties in optimizing complex structures that have potentially high performance. In this work, we comprehensively analyze the performance of an optimization algorithm for metamaterial design on the integrated HPC and quantum systems. We demonstrate significant time advantages through message-passing interface (MPI) parallelization on the high-performance computing (HPC) system showing approximately 54% faster ML tasks and 67 times faster optical simulation against serial workloads. Furthermore, we analyze the performance of a quantum algorithm designed for optimization, which runs with various quantum simulators on a local computer or HPC-quantum system. Results showcase ~24 times speedup when executing the optimization algorithm on the HPC-quantum hybrid system. This study paves a way to optimize complex metamaterials using the integrated HPC-quantum system.

Kim, Seongmin↗

Fuel performance analysis of FeCrAl cladding during LWR operation

This work focuses on modeling the integral thermo-mechanical performance of FeCrAl cladded fuel during normal operation in light-water reactors. Preliminary analysis has been performed to assess FeCrAl alloys (namely Alkrothal 720 and APMT) as a suitable fuel cladding replacement for Zr-alloys, using the MOOSE-based, finite-element fuel performance code BISON. These simulations identify the effects of the mechanical-stress and irradiation responses of FeCrAl and provide a comparison with Zr-alloys. In comparing these clad materials, fuel rods have been simulated for normal reactor operation and simple steady-state operation. Normal reactor operating conditions target the cladding performance over the rod lifetime (∼4 cycles) for the highest-power rod in the highest-power fuel assembly under reactor power maneuvering. The power histories and axial temperature profiles input into BISON were generated from a neutronics study on full-core reactivity equivalence for FeCrAl using the 3D full core simulator NESTLE. Evolution of the FeCrAl cladding behavior over time is evaluated by using steady-state operating conditions such as a simple axial power profile, a constant cladding surface temperature, and a constant fuel power history. The fuel rod designs and operating conditions used are based off the Peach Bottom BWR and design consideration was given to minimize the neutronic penalty of the FeCrAl cladding by changing fuel enrichment and cladding thickness. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Performance Analysis and Optimization for Scientific Data Workloads

Scientific data generated at experimental and observational facilities are increasingly being processed on large-scale compute systems. Most of the experimental data analysis workflows are not designed or implemented to run on large scale environments and take full advantage of HPC compute and storage resources. These applications are unlike the traditional tightly-coupled scientific applications and hence face significant performance and scalability challenges as the volume of data increases exponentially. In this paper, we conduct a performance and scalability analysis for experimental analysis applications and workflows operating on data from light sources. Our analysis detects and quantifies I/O performance, scalability and runtime bottlenecks for three data analysis applications that run on NERSC resources. Based on our analysis we propose and implement a set of optimizations that lead to reducing the amount of time spent on I/O operations by almost 90%.

97 MATHEMATICS AND COMPUTING↗

Idaho National Laboratory Quarterly Performance Analysis

This report is published quarterly by the Idaho National Laboratory (INL) Quality and Performance Management Organization. The Department of Energy (DOE) Occurrence Reporting and Processing System (ORPS), as prescribed in DOE Order 232.2, “Occurrence Reporting and Processing of Operations Information,” requires a quarterly analysis of events, both reportable and not reportable, for the previous 12 months. This report is the analysis of 60 reportable events (23 from the 4th Qtr FY14 and 37 from the prior three reporting quarters) as well as 58 other issue reports (including not reportable events and Significant Category A and B conditions) identified at INL from July 2013 through October 2014. Battelle Energy Alliance (BEA) operates the INL under contract DE AC07 051D14517.

99 GENERAL AND MISCELLANEOUS↗

Idaho National Laboratory Quarterly Performance Analysis - 2nd Quarter FY2014

This report is published quarterly by the Idaho National Laboratory (INL) Performance Assurance Organization. The Department of Energy Occurrence Reporting and Processing System (ORPS), as prescribed in DOE Order 232.2, “Occurrence Reporting and Processing of Operations Information,” requires a quarterly analysis of events, both reportable and not reportable, for the previous 12 months. This report is the analysis of occurrence reports and other deficiency reports (including not reportable events) identified at INL from January 2014 through March 2014.

99 GENERAL AND MISCELLANEOUS↗