Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Task analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Risk Analysis and Decision Making FY 2013 Milestone Report

Risk analysis and decision making is one of the critical objectives of CCSI, which seeks to use information from science-based models with quantified uncertainty to inform decision makers who are making large capital investments. The goal of this task is to develop tools and capabilities to facilitate the development of risk models tailored for carbon capture technologies, quantify the uncertainty of model predictions, and estimate the technical and financial risks associated with the system. This effort aims to reduce costs by identifying smarter demonstrations, which could accelerate development and deployment of the technology by several years.

Engel, David W.↗
DOE OSTI2013

Modeling Ternary Pumped Storage Units

This report is one of a series of documents to be issued in the course of a U.S. Department of Energy (DOE) project titled “Modeling and Analysis of Value of Advanced Pumped Storage Hydropower in the United States.” The objective of this overall effort is to investigate the advantages of recent advances in the design of pumped storage hydro plants. The objective of the first task of this project, “Develop Prototype Models of Advanced Pumped Storage Hydro (PSH) and Conventional Hydro (CH) Plants,” is to develop vendor-neutral dynamic simulation models for both fixed speed and adjustable speed PSH plants.

Koritarov, Vladimir↗
DOE OSTI2012

Integrated Data Collection Analysis (IDCA) Program - Final Review September 12, 2012 at DHS

The Integrated Data Collection Analysis (IDCA) program conducted a final program review at the Department of Homeland Security on September 12, 2012. The review was focused on the results of the program over the complete performance period. A summary presentation delineating the accomplished tasks started the meeting, followed by technical presentations on various issues that arose during the performance period. The presentations were completed with a statistical evaluation of the testing results from all the participants in the IDCA Proficiency Test study. The meeting closed with a discussion of potential sources of funding for continuing work to resolve some of these technical issues. This effort, funded by the Department of Homeland Security (DHS), put the issues of safe handling of these materials in perspective with standard military explosives. The study added Small-Scale Safety and Thermal (SSST) testing results for a broad suite of different HMEs to the literature, and suggested new guidelines and methods to develop safe handling practices for HMEs. Each participating testing laboratory used identical test materials and preparation methods wherever possible. Note, however, the test procedures differ among the laboratories. The results were compared among the laboratories and then compared to historical data from various sources. The testing performers involved were Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Naval Surface Warfare Center, Indian Head Division (NSWC IHD), Sandia National Laboratories (SNL), and Air Force Research Laboratory, Tyndall AFB (AFRL/RXQL). These tests were conducted as a proficiency study in order to establish some consistency in test protocols, procedures, and experiments and to compare results when these testing variables cannot be made consistent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Highly Integrated WBG Power Module for Next Generation Plug-In Vehicles

Current inverter technologies used in electric vehicles (EVs) are bulky, heavy, and expensive. The performance of the inverter is also limited by the traditional Si-based semiconductor and packaging technology. These constraints are responsible for extra weight and volume in the vehicle that reduces the driving range along with usable space within the vehicle. Moreover, operating temperature restrictions, and boundaries on the inverter location within the vehicle drastically reduces the inverter performance. Thus an improved inverter design is required for next generation electric vehicles. The objective of this project was to research, develop and demonstrate a highly integrated WBG power module targeting the next generation of plugin hybrid electric vehicles (PHEVs). This power module needed to be functionally and mechanically optimized for General Motors (GM) traction inverter architecture. General Motors was the prime contractor, led the project, and oversaw the design, build, and test of the integrated power module. Virginia Polytechnic Institute and State University (VT) performed modeling and simulation tasks as well as power module design support. Monolith Semiconductor, Inc provided SiC dies and consulted on devices for the inverter. Oak Ridge National Laboratory (ORNL) performed power module technology evaluations, design evaluations of interconnect options, and performed material analysis and cross-sectioning of die activities.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

DXT: Darshan eXtended Tracing

As modern supercomputers evolve to exascale, their I/O subsystems are becoming increasingly complex, making optimization of I/O for scientific applications a daunting task. Although I/O profiling tools facilitate the process of optimizing application I/O performance, legacy profiling tools lack flexibility in their level of detail and ability to correlate traces with other sources of data. Additionally, a lack of robust trace analysis tools makes it difficult to derive actionable insights from large-scale I/O traces. Darshan is an HPC I/O characterization tool that records statistics in a lightweight manner that makes it appropriate for full-time production deployment. However, Darshan’s default characterization mechanism records information at a fixed granularity. We augment Darshan by proposing Darshan eXtended Tracing (DXT) for more detailed profiling of I/O software stacks. DXT enables users and administrators to vary the level of fidelity captured by Darshan at run time without modifying or recompiling applications. This capability facilitates systematic analysis on the I/O behavior of applications and can provide useful application kernel I/O traces to help advance parallel I/O research. We have demonstrated the power of DXT by obtaining a wide range of useful statistics for multiple case studies, and we further show that DXT is able to do so same with negligible overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Electrical Substation Configuration Effect on Substation Reliability

It is crucial that the U.S. electrical grid be reliable, due to its critical role in the economy and our national defense/security. Many common tasks and industrial operations rely on proper electrical power distribution. In designing new bus systems or evaluating existing ones, the type of configuration employed affects the level of risk, reliability, maintenance, and cost involved. The present work utilizes Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) to perform a probabilistic risk assessment (PRA)-based sensitivity study on substation reliability in regard to different bus configurations. This study examines single bus, main and transfer, breaker and a half, double bus/double breaker, and ring bus configurations applied to busses with different numbers of lines. The case variances, methods, and rankings presented herein can help guide bus configurations for electrical grid design/analysis in the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization

Abstract Background Microbiome studies have uncovered associations between microbes and human, animal, and plant health outcomes. This has led to an interest in developing microbial interventions for treatment of disease and optimization of crop yields which requires identification of microbiome features that impact the outcome in the population of interest. That task is challenging because of the high dimensionality of microbiome data and the confounding that results from the complex and dynamic interactions among host, environment, and microbiome. In the presence of such confounding, variable selection and estimation procedures may have unsatisfactory performance in identifying microbial features with an effect on the outcome. Results In this manuscript, we aim to estimate population-level effects of individual microbiome features while controlling for confounding by a categorical variable. Due to the high dimensionality and confounding-induced correlation between features, we propose feature screening, selection, and estimation conditional on each stratum of the confounder followed by a standardization approach to estimation of population-level effects of individual features. Comprehensive simulation studies demonstrate the advantages of our approach in recovering relevant features. Utilizing a potential-outcomes framework, we outline assumptions required to ascribe causal, rather than associational, interpretations to the identified microbiome effects. We conducted an agricultural study of the rhizosphere microbiome of sorghum in which nitrogen fertilizer application is a confounding variable. In this study, the proposed approach identified microbial taxa that are consistent with biological understanding of potential plant-microbe interactions. Conclusions Standardization enables more accurate identification of individual microbiome features with an effect on the outcome of interest compared to other variable selection and estimation procedures when there is confounding by a categorical variable.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Development and Refinement of Bison Models for Higher Burnup Application

Electric Power Research Institute (EPRI) is an international research organization funded by organizations in the energy and government sectors. The company conducts research to tackle the energy challenges of its member organizations. In support of the U.S. nuclear industry, EPRI and Idaho National Laboratory were awarded a U.S. Department of Energy Technology Commercialization Fund to develop a loss of coolant accident (LOCA) analysis tool. This tool was developed to support burnup extension activities by supplementing the existing capabilities of operators of existing large light-water reactor plants. The tool couples INL developed codes Bison and RELAP5-3D for advanced simulation of LOCA behavior. The project consists of seven major tasks, one of which is the development and refinement of Bison models for higher burnup applications. This task is broken down into six targeted areas of development and refinement including: formation of high burnup structure, fuel fracture and pulverization, transient fission gas release, axial gas communication within a fuel rod, cladding ballooning and burst, and axial fuel relocation. This report summarizes the models for both the fuel and cladding in Bison for high burnup application, identifies the areas of development and refinement necessary to enhance the Bison capabilities to be used in the coupled simulation tool with RELAP5-3D. Integration and regression testing to demonstrate proper implementation of the new features in Bison is highlighted.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Energy Resilience for Mission Assurance, Agile Co-simulation for Cyber Energy System Security (ACCESS) Model Advancements for Resilience Analysis (Version 3, July 2023)

Agile Co-simulation for Cyber Energy System Security (ACCESS) is a co-simulation platform developed by Lawrence Livermore National Laboratory (LLNL). The primary high-level use-case for ACCESS is to study existing or new cyber-physical critical infrastructure systems, with a heavy emphasis on 1) systems that utilize communication networks, and 2) studies that seek to understand cyber-related system impacts. ACCESS is currently used for several energy system resilience projects at LLNL. In the Energy Resilience for Mission Assurance (ERMA) project, ACCESS is used in the Mod eling for Metric Calculation task (specifically, subtask 4.3, Communications and Cyber Modeling) to model and simulate the cyber and communication system aspects of Defense Critical Electric Infrastructure (DCEI) systems, with a focus on computing specific communication system metrics that can impact system resilience and mission performance. Simulated communication system per formance will be fed back to other ERMA system components so that mission performance can be evaluated holistically. This report describes several enhancements to the ACCESS platform that were implemented during the execution of the ERMA project in support of reslience analysis. This includes the addition of new models and subsystems, enhancements to existing models, and integration with external systems. The remainder of this report is structured as follows. In Section 2, a brief background description of the ACCESS platform is provided, including an outline of ACCESS components, example use cases, and a set of communication network resilience metrics that can be computed with ACCESS. Section 3 describes the ACCESS model enhancements for ERMA in detail. Finally, Section 4 briefly outlines future integration opportunities between ACCESS and project participant capabilities identified during the progression of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Technoeconomic Analysis of Infrastructure Buildout Scenarios

The success of CCUS deployment in the southeast will depend on the optimized pipeline network from CO 2 point sources to geologic sinks for CO 2 storage. An optimal pipeline framework will reduce both environmental impacts and pipeline building cost. However, finding an optimal pipeline/transport infrastructure design is a non-trivial task and requires simultaneous usage of large volumes of data, computational resources, and a state-of-the-art simulator. Such a transport infrastructure model must consider point sources for CO 2 capture and associated volumes, sinks for CO 2 storage, and transportation from source to sink via pipeline networks. These considerations must be addressed simultaneously and systemically in an optimization process, in which a defined objective function (i.e., capital, variable CO 2 capture, transport, and storage cost function) is required to be minimized with the consideration of practical constraints (e.g., CO 2 flow through pipelines is less than the maximum capacity). Although optimization has been widely used in subsurface resources production and CO 2 storage, its application in large scale CCUS infrastructure design is rarely reported in the literature. SimCCS, developed by Los Alamos National Laboratory, is an open-source CCUS pipeline infrastructure design toolset that facilitates the optimization of pipeline infrastructure networks.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

A vacuum microgripping tool with integrated vibration releasing capability

Pick-and-place of micro-objects is a basic task in various micromanipulation demands. Reliable releasing of micro-objects is usually disturbed due to strong scale effects. This paper focuses on a vacuum micro-gripper with vibration releasing functionality, which was designed and assembled for reliable micromanipulation tasks. Accordingly, a vibration releasing strategy of implementing a piezoelectric actuator on the vacuum microgripping tool is presented to address the releasing problem. The releasing mechanism was illustrated using a dynamic micro contact model. This model was developed via theoretical analysis, simulations and pull-off force measurement using atomic force microscopy. Micromanipulation experiments were conducted to verify the performance of the vacuum micro-gripper. The results show that, with the assistance of the vibration releasing, the vacuum microgripping tool can achieve reliable release of micro-objects. A releasing location accuracy of 4.5±0.5 μm and a successful releasing rate of around 100% (which is based on 110 trials) were achieved for manipulating polystyrene microspheres with radius of 35–100 μm.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Heralded-qubit amplifiers for practical device-independent quantum key distribution

Device-independent quantum key distribution does not need a precise quantum mechanical model of employed devices to guarantee security. Despite its beauty, it is still a very challenging experimental task. We compare a recent proposal by Gisin et al.[Phys. Rev. Lett. 105, 070501 (2010)] to close the detection loophole problem with that of a simpler quantum relay based on entanglement swapping with linear optics. Our full-mode analysis for both schemes confirms that, in contrast to recent beliefs, the second scheme can indeed provide a positive key rate which is even considerably higher than that of the first alternative. The resulting key rates and required detection efficiencies of approximately 95% for both schemes, however, strongly depend on the underlying security proof.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations

Phase field (PF) simulations are computationally expensive but remain a key analysis tool to understand the complex mechanisms of additive manufacturing (AM) processes. Each PF simulation-aided analysis requires thousands of node hours on leadership-class supercomputers. One of the main goals of these analyses is the study of microstructure evolution during the build process which begins with the onset of nucleation. Nucleation occurs under certain thermomechanical conditions which are not known a priori and many PF simulations are required to identify ranges of input thermo-mechanical parameters that can result in the onset of nucleation. Since many of the simulations do not result in nucleation, an analysis campaign often ends up wasting tremendous amounts of precious computing resources executing nucleation-absent simulations. The goal of this work is to design and train deep learning models to inform a PF simulation about the likelihood of the occurrence of nucleation in a future simulation time-step based on the state summary over a finite number of past time-steps of a running simulation. If the prediction determines that the running simulation is unlikely to reach nucleation in the allotted time, then its execution is stopped immediately ultimately resulting in vast reduction in wasted computations when accrued over all the PF simulations typically performed in a single or multiple analysis campaign(s). The paper presents the performance of a machine learning pipeline that uses a convolutional neural network (CNN) model to learn an embedding which is then used with a self-attention network to build a multi-task deep learning model to predict the likelihood of nucleation. The model also predicts the input parameters used in a simulation. Performance is compared with a baseline pipeline that uses an off-the-shelf LeNet-5 model to learn the initial embedding. Despite their smaller size, performance results indicate significant improvement in accuracy of the proposed models compared to the larger baseline models.

Kannan, Ramakrishnan {ramki}↗
DOE OSTI2012

Case Study of the Maplewood Park Multifamily Retrofit for Energy Efficiency

Maplewood Park (Maplewood), a 110-unit multifamily apartment complex in Union City, Georgia, completed major renovations under the guidance of a third-party green building certification program in October 2012. Oak Ridge National Laboratory (ORNL) partnered with Southface Energy Institute (Southface) to use this project as a case study of energy retrofits in low-rise, garden-style, multifamily buildings in the southeastern United States. This report provides a comprehensive profile of this project including the project economics, findings of the building audit, and results of the analysis of energy retrofit measures specific to this project. With a main focus of energy retrofits, this report aims to discuss other aspects of multifamily building retrofit that would benefit future projects in terms of improved building audit process, streamlined tasks, and higher energy savings in low-rise, garden-style apartments. Maplewood received Low Income Housing Tax Credit (LIHTC) financing via the 2010 Georgia Qualified Allocation Plan (QAP). To be eligible for QAP funds in Georgia, all major renovations must incorporate energy-efficiency measures and adopt a third-party green building certification. Because of the unique demands of this financing, including requirements for long-term ownership, property owners were also especially motivated to invest in upgrades that will increase durability and comfort while reducing the energy cost for the tenants.

Kim, Euy-Jin↗
DOE OSTI2014

SL12-GADRAS-PD2Ka Annual Report

The GADRAS Development project comprises several elements that are all related to the Detector Response Function (DRF), which is the core of GADRAS. An ongoing activity is implementing continuous improvements in the accuracy and versatility of the DRF. The ability to perform rapid computation of the response of gammaray detectors for 3-D descriptions of source objects and their environments is a good example of a recent utilization of this versatility. The 3-D calculations, which execute several orders of magnitude faster than competing techniques, compute the response as an extension of the DRF so the radiation transport problem is never solved explicitly, thus saving considerable computational time. Maintenance of the Graphic User Interface (GUI) and extension of the GUI to enable construction of the 3-D source models is included in tasking for the GADRAS Development project. Another aspect of this project is application of the isotope identification algorithms for search applications. Specifically, SNL is tasked with development of an isotope-identification based search capability for use with the RSL-developed AVID system, which supports simultaneous operation of numerous radiation search assets. A Publically Available (PA) GADRAS-DRF application, which eliminates sensitive analysis components, will soon be available so that the DRF can be used by researchers at universities and corporations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

2016 High Performance Computing Annual Report

Sandia National Laboratories’ California site is celebrating its 60th anniversary (1956 to 2016), and high performance computing has been a key enabler for its scientists and engineers throughout much of its history. Since its founding, Sandia California has helped pioneer the use of HPC platforms including hosting Sandia’s first Cray-1 supercomputer in the 1970s and supporting development of scalable cluster computing platforms to create a new paradigm for cost-effective supercomputing in the 1990s. Recent decades of investment in creation of scalable application frameworks for scientific computing have also enabled new generations of modeling and simulation codes. These resources have facilitated computational analysis of complex phenomena in diverse applications spanning national defense, energy, and homeland security. Today, Sandia California researchers work with partners in academia, industry, and national labs to evolve the state-of-the-art in HPC, modeling, and data analysis (including foundational capabilities for exascale computing platforms) and apply them in transformational ways. Research efforts include mitigating the effects of silent hardware failures that can jeopardize the results of large-scale computations, developing exascale-capable asynchronous task-parallel programming models and runtime systems, formulating new techniques to better explore and analyze extreme-scale data sets, and increasing our understanding of materials and chemical sciences which has applications spanning nuclear weapons stockpile stewardship to more efficient automobile engines. The following section highlights some of these research and applications projects and further illustrates the breadth of our HPC capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

UNM High Energy Physics: Task B

The High Altitude Water Cherenkov (HAWC) observatory provides a unique window into the "TeV" gamma-ray universe. HAWC provides an important 1 TeV to 1000 TeV high-mass window for indirect searches for dark matter (DM) annihilation or decay. Additional fundamental physics studies benefit from HAWC's sensitivity to variable and/or transient sources. Such transient sources include: gamma ray bursts (GRBs), temporal studies of super massive black holes (specifically Markarian (Mrk) 421 and 501), and most recently searches for gamma-ray counterparts to PeV neutrino sources (observed by IceCube) and gravitational wave sources (observed by LIGO/Virgo). The UNM (Task B) research program includes leadership of the HAWC detector and of HAWC science. During this final reporting period the UNM group includes Professor John Matthews and graduate student Zhixiang Ren with the research goal focused on the development of analysis tools to enhance the sensitivity of HAWC to <1 TeV, gamma rays. This program began in 2016 with an initial focus to work to resolve known problems with the low energy analysis bins in the HAWC data. In 2017 this evolved to the development of new analysis tools to optimize current HAWC <1 TeV sensitivity as well as how HAWC (or a future HAWC-like detector) could be modified to be significantly more sensitive to <1 TeV gamma rays. In these studies Ren lead the development and evaluation of new HAWC <1 TeV analysis tools and Matthews lead the study of possible experimental modifications to HAWC to improve the <1 TeV sensitivity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Quantification of morphological change in materials based on image data utilizing machine learning techniques

Computed tomography (CT) resolution has become high enough to monitor morphological changes due to aging in materials in long-term applications. We explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images visually reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect. Both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗