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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 37 records · Page 2

Usability of Operational Performance Support Tools - Findings from Sea Test II

Sea Test II, aka NASA Extreme Environment Mission Operations 17(NEEMO 17) took place in the Florida Aquarius undersea habitat. This confined underwater environment provides a excellent analog for space habitation providing similarities to space habitation such as hostile environment, difficult logistics, autonomous operations, and remote communications. This study collected subjective feedback on the usability of two performance support tools during the Sea Test II mission, Sept 10‐14, 2013; Google Glass and iPAD. The two main objectives: - Assess the overall functionality and usability of each performance support tool in a mission analog environment. - Assess the advantages and disadvantages of each tool when performing operational procedures and Just‐In‐Time‐Training (JITT).

Byrne, Vicky↗

Tools Assessing Performance

For the distributed wind industry, it can be challenging to accurately predict the performance and annual energy production of projects prior to their installation. The U.S. Department of Energy’s Tools Assessing Performance (TAP) project aims to improve wind resource characterization, thereby reducing the uncertainty of project performance and financing costs, increasing consumer confidence, and lowering the levelized cost of distributed wind energy. A collaborative effort among DOE National Laboratories, TAP will create a computational framework that provides the distributed wind community with access to newly developed wind resource data and modeling capabilities. These capabilities will allow users to perform timely and accurate performance assessments for distributed wind projects at locations across the United States.

wind, distributed, tools, performance↗

Performance Support Tools for Space Medical Operations

The early Constellation space missions are expected to have medical capabilities very similar to those currently on the Space Shuttle and International Space Station (ISS). For Crew Exploration Vehicle (CEV) missions to ISS, medical equipment will be located on ISS, and carried into CEV in the event of an emergency. Flight Surgeons (FS) on the ground in Mission Control will be expected to direct the Crew Medical Officer (CMO) during medical situations. If there is a loss of signal and the crew is unable to communicate with the ground, a CMO would be expected to carry out medical procedures without the aid of a FS. In these situations, performance support tools can be used to reduce errors and time to perform emergency medical tasks. Human factors personnel at Johnson Space Center have recently investigated medical performance support tools for CMOs on-orbit, and FSs on the ground. This area of research involved the feasibility of Just-in-time (JIT) training techniques and concepts for real-time medical procedures. In Phase 1, preliminary feasibility data was gathered for two types of prototype display technologies: a hand-held PDA, and a Head Mounted Display (HMD). The PDA and HMD were compared while performing a simulated medical procedure using ISS flight-like medical equipment. Based on the outcome of Phase 1, including data on user preferences, further testing was completed using the PDA only. Phase 2 explored a wrist-mounted PDA, and compared it to a paper cue card. For each phase, time to complete procedures, errors, and user satisfaction were captured. Information needed by the FS during ISS mission support, especially for an emergency situation (e.g. fire onboard ISS), may be located in many different places around the FS s console. A performance support tool prototype is being developed to address this issue by bringing all of the relevant information together in one place. The tool is designed to include procedures and other information needed by a FS during an emergency, as well as procedures and information to be used after the emergency is resolved. Several walkthroughs of the prototype with FSs have been completed within a mockup of an ISS FS console. Feedback on the current tool design as well as recommendations for existing ISS FS displays were captured.

Byrne, Vicky E.↗

ESMValTool (v1.0) – a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP

A community diagnostics and performance metrics tool for the evaluation of Earth system models (ESMs) has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations. The priority of the effort so far has been to target specific scientific themes focusing on selected essential climate variables (ECVs), a range of known systematic biases common to ESMs, such as coupled tropical climate variability, monsoons, Southern Ocean processes, continental dry biases, and soil hydrology–climate interactions, as well as atmospheric CO 2 budgets, tropospheric and stratospheric ozone, and tropospheric aerosols. The tool is being developed in such a way that additional analyses can easily be added. A set of standard namelists for each scientific topic reproduces specific sets of diagnostics or performance metrics that have demonstrated their importance in ESM evaluation in the peer-reviewed literature. The Earth System Model Evaluation Tool (ESMValTool) is a community effort open to both users and developers encouraging open exchange of diagnostic source code and evaluation results from the Coupled Model Intercomparison Project (CMIP) ensemble. This will facilitate and improve ESM evaluation beyond the state-of-the-art and aims at supporting such activities within CMIP and at individual modelling centres. Ultimately, we envisage running the ESMValTool alongside the Earth System Grid Federation (ESGF) as part of a more routine evaluation of CMIP model simulations while utilizing observations available in standard formats (obs4MIPs) or provided by the user.

58 GEOSCIENCES↗

Performance Support Tools for Space Medical Operations

Early Constellation space missions are expected to have medical capabilities similar to those currently on board the Space Shuttle and International Space Station (ISS). Flight surgeons on the ground in Mission Control will direct the Crew Medical Officer (CMO) during medical situations. If the crew is unable to communicate with the ground, the CMO will carry out medical procedures without the aid of a flight surgeon. In these situations, use of performance support tools can reduce errors and time to perform emergency medical tasks. The research presented here is part of the Human Factors in Training Directed Research Project of the Space Human Factors Engineering Project under the Space Human Factors and Habitability Element of the Human Research Program. This is a joint project consisting of human factors teams from the Johnson Space Center (JSC) and the Ames Research Center (ARC). Work on medical training has been conducted in collaboration with the Medical Training Group at JSC and with Wyle that provides medical training to crew members, biomedical engineers (BMEs), and flight surgeons under the Bioastronautics contract. Human factors personnel at Johnson Space Center have investigated medical performance support tools for CMOs and flight surgeons.

Byrne, Vicky↗

PATHA: Performance Analysis Tool for HPC Applications

Large science projects rely on complex workflows to analyze terabytes or petabytes of data. These jobs are often running over thousands of CPU cores and simultaneously performing data accesses, data movements, and computation. It is difficult to identify bottlenecks or to debug the performance issues in these large workflows. In order to address these challenges, we have developed Performance Analysis Tool for HPC Applications (PATHA) using the state-of-art open source big data processing tools. Our framework can ingest system logs to extract key performance measures, and apply the most sophisticated statistical tools and data mining methods on the performance data. Furthermore, it utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of PATHA, we conduct a case study on the workflows from an astronomy project known as the Palomar Transient Factory (PTF). This study processed 1.6 TB of system logs collected on the NERSC supercomputer Edison. Using PATHA, we were able to identify performance bottlenecks, which reside in three tasks of PTF workflow with the dependency on the density of celestial objects.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Tools Assessing Performance (TAP) 2.0

Dmitry Duplyakin will be presenting on the latest research and results in the Tools Assessing Performance (TAP) 2.0 project. This presentation will include updates on the latest data the group has produced, integration of obstacle models in the computational pipeline for distributed wind siting, and the plans for the near-term analysis and validation efforts. The talk will acknowledge the work of collaborators from NREL and three other national labs - ANL, LANL, and PNNL - all contributing to this multi-year project.

distributed wind↗

Application of Performance Analysis Tools on SNL ASC Codes

This milestone 1) exercised a broad set of performance profiling and analysis tools, including tools whose development has been promoted by the ASC program; 2) exercised the tools on two different SNL ASC codes, one Sierra code (Sierra/Aria, a C++ codebase) and one RAMSES code (ITS, a Fortran codebase); and 3) exercised the tools on multiple platforms, including the CTS-1 (e.g., Serrano) and ATS-1 Trinity (e.g., Mutrino) platforms. The milestone generated a plethora of strong and weak scaling, trend and profile data for multiple versions and problem cases for each of the two codes. A wealth of experience was gained with the various tools that included identification of problems, an improved understanding of feature sets, enhanced usage documentation, and insights for future tool-development. Results are provided from a large number and variety of performance analysis runs with the target codes, together with instructions for how to make use of the tools with the codes.

97 MATHEMATICS AND COMPUTING↗

Influence of Laser Surface Texturing on Tribological Performance of Tool Steels

This paper deals with the influence of laser surface texturing on tribological performance of two different tool steels: (a) Böhler K100 produced by conventional production technology and (b) Böhler K390 Microclean{sup ®} produced by powder metallurgy. The surface of heat-treated tool steels was modified using three different texture patterns. Impact of laser surface texturing was analyzed after different treatments. Furthermore, selected samples were borided to evaluate the combined influence of laser surface texturing and boriding on tribological performance of surface-treated samples. The results show that boriding was not beneficial for wavy surface type, and the steel production technology had a certain influence on the spinning tool. The laser surface texturing had an effect on decreasing the coefficient of friction on the K100 tool steel; however, it did not influence the tribological performance of the K390 Microclean{sup ®} tool steel. Boriding process was efficient in decreasing the coefficient of friction for both steels. The low coefficient of friction values did not have a positive influence on the wear depth.

36 MATERIALS SCIENCE↗

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation↗

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Registration↗

ARES v1.x - Performance Portable Tool to Simulate Supernovae based on Parthenon Framework

Historically, codes for simulating supernovae (such as Arepo, FLASH or LEAFS) have been at the forefront of scientific high-performance computing to the immense computational resources required for full 3D simulations. However, given the shift towards heterogenous HPC architectures, many current-generation codes are at the risk of losing their competitiveness as they are only designed to run on homogeneous CPU-only systems. There exist several efforts to enable these codes for GPU’s, however, these efforts only consider specific architectures or vendors (e.g., implement only CUDA or HIP), limiting themselves to a small range of exascale computing systems. Frameworks such as Kokkos aim to provide a framework which is agnostic of the targeted architecture, enabling the development of performant and portable code. In the Ares code, we develop a performance portable tool to simulate supernovae based on the Parthenon Framework, which in turn uses Kokkos in the background. Here, the Parthenon Framework provides an interface to the underlying mesh-refinement routines, which form the backbone of our code. In addition, we incorporate the already existing Singularity-EOS toolkit to provide us with various equations of state, primarily the Helmholtz equation of state. We also include the JINA Reaclib as a basis for our nuclear network solver. Finally, we implement a gravity solver to complete the required physics. This setup will provide us with a minimal code base to simulate supernova in a similar style to the tried-and-tested Arepo code, but in a futureproof performance portable framework.

Lim, Hyun↗

Space mission scenario development and performance analysis tool

This paper discusses a new and innovative approach for a rapid spacecraft multi-disciplinary performance analysis using a tool called the Mission Scenario Development Workbench (MSDW). To meet the needs of new classes of space missions, analysis tools with proven models were developed and integrated into a framework to enable rapid trades and analyses between spacecraft designs and operational scenarios during the formulation phase of a mission. Generally speaking, spacecraft resources are highly constrained on deep space missions and this approach makes it possible to maximize the use of existing resources to attain the best possible science return. This approach also has the potential benefit of reducing the risk of costly design changes made later in the design cycle necessary to meet the mission requirements by understanding system design sensitivities early and adding appropriate margins. This paper will describe the approach used by the Mars Science Laboratory Project to accomplish this result.

performance analysis↗

Performance Evaluation Tools for Next Generation Scalable Computing Platforms

The Federal High Performance and Communications (HPCC) Program continue to focus on R&D in a wide range of high performance computing and communications technologies. Using its accomplishments in the past four years as building blocks towards a Global Information Infrastructure (GII), an Implementation Plan that identifies six Strategic Focus Areas for R&D has been proposed. This white paper argues that a new generation of system software and programming tools must be developed to support these focus areas, so that the R&D we invest today can lead to technology pay-off a decade from now. The Global Computing Infrastructure (GCI) in the Year 2000 and Beyond would consists of thousands of powerful computing nodes connected via high-speed networks across the globe. Users will be able to obtain computing in formation services the GCI with the ease of using a plugging a toaster into the electrical outlet on the wall anywhere in the country. Developing and managing the GO requires performance prediction and monitoring capabilities that do not exist. Various accomplishments in this field today must be integrated and expanded to support this vision.

Yan, Jerry C.↗

PRIMA-X - Performance Retargeting of Instrumentation, Measurement, and Analysis Technologies for Exascale Computing

The PRIMA-X (Performance Retargeting of Instrumentation, Measurement, and Analysis Technologies for Exascale Computing) project is the successor of the DOE PRIMA (Performance Refactoring of Instrumentation, Measurement, and Analysis Technologies for Petascale Computing) project, which addressed the challenge of creating a core measurement infrastructure that would serve as a common platform for both integrating leading parallel performance systems (notably TAU and Scalasca) and developing next-generation scalable performance tools. The PRIMA-X project shifts the focus away from refactorization of robust performance tools towards a re-targeting of the parallel performance measurement and analysis architecture for extreme scales. The massive concurrency, asynchronous execution dynamics, hardware heterogeneity, and multi-objective prerequisites (performance, power, resilience) that identify exascale systems introduce fundamental constraints on the ability to carry forward existing performance methodologies. In particular, there must be a deemphasis of per-thread observation techniques to significantly reduce the otherwise unsustainable flood of redundant performance data. Instead, it will be necessary to assimilate multi-level resource observations into macroscopic performance views, from which resilient performance metrics can be attributed to the computational features of the application. This requires a scalable framework for node-level and system-wide monitoring and runtime analyses of dynamic performance information. Also, the interest in optimizing parallelism parameters with respect to performance and energy drives the integration of tool capabilities in the exascale environment further. Initially, PRIMA-X was a collaborative project between the University of Oregon (lead institution) and the German Research School for Simulation Sciences (GRS). Because Prof. Wolf, the PI at GRS, accepted a position as full professor at Technische Universitaet Darmstadt (TU Darmstadt) starting February 1st, 2015, the work of GRS was continued at TU Darmstadt. This report covers the work at TU Darmstadt after the transition. The first main accomplishment of TU Darmstadt is the development of different techniques to aggregate performance data on the level of threads. TU Darmstadt evaluated different schemes designed at GRS during the first phase of this project and integrated them into Score-P, a widely used performance measurement framework for HPC applications. The second main accomplishment is a substantial increase of Score-P’s scalability, achieved by improving its internal representation of the underlying system. Third, we extended our performance-modeling tool Extra-P to automatically create models with more than one input parameter (e.g., process count and input size), which was previously impossible. These models allow the performance behavior of an application to be extrapolated to larger machines. Specific applications of the new multi-parameter capability realized in this project include modeling the isoefficiency function of task-based applications and a novel co-design methodology. Further extensions of Extra-P comprise online modeling functionality, automatic refinement of the model search space, and segmented performance modeling. Further contributions include new locality metrics for both shared- and distributed-memory applications, a new way of measuring the impact of inter-application inference on the execution time of an application, and finally an automatic method that selects appropriate OpenMP constructs for the parallelization of sequential code and classifies the affected variables based on their sharing semantics.

97 MATHEMATICS AND COMPUTING↗

In-Situ Ion Irradiation to Add Irradiation Assisted Grain Growth to the Marmot Tool

In the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the MARMOT mesoscale fuel performance tool is used to inform the development of mechanistic materials models for the BISON fuel performance tool. The grain size of the fuel has a large impact on its performance, directly impacting heat conduction, fission gas release, creep, and fracture. Thus, atomistic and mesoscale MARMOT simulations have been used to investigate grain boundary migration and grain growth in UO 2 . However, the current grain growth models in MARMOT does not consider the effect of irradiation on causing grain growth. This research project experimentally studied and implemented irradiation effects on grain growth of UO 2 into MARMOT.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗