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This software includes the Jupyter notebooks, model pretraining and evaluation code for the EXPERT 2.0 Human-AI Reasoning Engine V0.1. It supports pre-training a Human-AI model for reasoning over multi-layer network representations. It includes prompt-based evaluation framework in a Jupyter notebook for AI reasoning and Jupyter widgets with AI-based techniques for evidence generation and uncertainty quantification to support human-AI reasoning.
The IMB 50V software provides functionality for design of impedance measurement tests or sequences of tests, execution of these tests or sequences, processing measured responses and displaying and saving of the results. The software consists of a Graphical User Interface that allows configuration of measurement parameters and test sequencing, a core engine that controls test sequencing, execution of measurements, processing and storage of results and a hardware/software data acquisition interface with the IMB hardware system.
An inexpensive commercially available handheld energy dispersive x‐ray fluorescence spectrometer is used to provide a rapid non‐destructive estimate of coating and/or cladding thickness in situ . The portable XRF instrument contains a battery‐operated low‐power polychromatic source coupled with a Peltier‐cooled silicon drift detector; built‐in analysis software based upon the Method of Fundamental Parameters converts measured spectral intensities to elemental concentrations, reported as normalized weight percentages. Using detected signals from elements unique to the base material and coating or cladding materials, calibration curves and associated empirical algorithms for determining the thickness of the high‐purity zirconium coating on an RERTR fuel element prior to cladding with aluminum, and for determining the thickness of the Al‐6061 cladding after HIP for a known zirconium layer thickness, are constructed. For Zr over bare DU‐10Mo, agreement between the measured and the calculated thickness is ± 5% or better. For the multilayer system consisting of Al‐6061 over Zr over Du‐10Mo, agreement between calculated and measured thickness is ± 10‐15% over the thickness range of interest. Simultaneous estimates for the Al cladding and underlying Zr coating can be made using the elemental composition output only when the Mo signal is in the quasi‐static range (corresponding to Al thicknesses of ~15 mils (0.381 mm) and greater) and not so low that measurement error is greater than the signal itself; under these conditions, accuracy is on the order of ±15 – 20%. More accurate determination of both Zr and Al thickness simultaneously may be possible if the count‐rates associated with individual fluorescent lines in the multilayer sample are available rather than just the weight percent composition currently output by the XRF analyzer software.
Started in 2008, the Mulitphysics Object Oriented Simulation Environment (MOOSE) project delivers a comprehensive framework for development of parallel, multiphysics simulation tools. MOOSE provides an object-oriented interface that allows scientists and engineers to quickly and efficiently describe all aspects of a physical system relevant to numerical modeling. The MOOSE software development strategy has been quite successful: over thirty different MOOSE-based applications are under development both internally and outside the DOE complex, and over forty different external institutions have licensed MOOSE. Several NEAMS products have been built using MOOSE, including BISON (Williamson et. al., 2012), MARMOT (Tonks et. al., 2012), RELAP-7 (Zou et. al., 2013) and RAVEN (Rabiti, 2013).
Enhancing the performance of SciDAC applications on petascale systems had high priority within DOE SC at the start of the second phase of the SciDAC program, SciDAC-2, as it continues to do so today. Achieving expected levels of performance on high-end computing (HEC) systems is growing ever more challenging due to enormous scale, increasing architectural complexity, and increasing application complexity. To address these challenges, the University of Southern California's Information Sciences Institute organized the Performance Engineering Research Institute (PERI). PERI implemented a unified, tripartite research plan encompassing: (1) performance modeling and prediction; (2) automatic performance tuning; and (3) performance engineering of high profile applications. Within PERI, USC's primary research activity was automatic tuning (autotuning) of scientific software. This activity was spurred by the strong user preference for automatic tools and was based on previous successful activities such as ATLAS, which automatically tuned components of the LAPACK linear algebra library, and other recent work on autotuning domain-specific libraries. Our other major component was application engagement, to which we devoted approximately 30% of our effort to work directly with SciDAC-2 applications. This report is a summary of the overall results of the USC PERI effort.
KIVA is a family of Fortran-based computational fluid dynamics software developed by LANL. The software predicts complex fuel and air flows as well as ignition, combustion, and pollutant-formation processes in engines. The KIVA models have been used to understand combustion chemistry processes, such as auto-ignition of fuels, and to optimize diesel engines for high efficiency and low emissions. Fuel economy is heavily dependent upon engine efficiency, which in turn depends to a large degree on how fuel is burned within the cylinders of the engine. Higher in-cylinder pressures and temperatures lead to increased fuel economy, but they also create more difficulty in controlling the combustion process. Poorly controlled and incomplete combustion can cause higher levels of emissions and lower engine efficiencies.
The 8th American Conference on Neutron Scattering (ACNS) was held July 10-14, 2016 in Long Beach California, marking the first time the meeting has been held on the west coast. The meeting was coordinated by the Neutron Scattering Society of America (NSSA), and attracted 285 attendees. The meeting was chaired by NSSA vice president Patrick Woodward (the Ohio State University) assisted by NSSA president Stephan Rosenkranz (Argonne National Laboratory) together with the local organizing chair, Brent Fultz (California Institute of Technology). As in past years the Materials Research Society assisted with planning, logistics and operation of the conference. The science program was divided into the following research areas: (a) Sources, Instrumentation, and Software; (b) Hard Condensed Matter; (c) Soft Matter; (d) Biology; (e) Materials Chemistry and Materials for Energy; (f) Engineering and Industrial Applications; and (g) Neutron Physics.
This document introduces Version 2 of the Dynamic Contingency Analysis Tool (DCAT) software package developed by Pacific Northwest National Laboratory and serves as a guide for using this package to conduct cascading failure simulations for the electric power system. The DCAT is an open-platform and publicly available software; it is intended to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will support finding mitigating actions to reduce the risk of cascading outages in technically sound and effective ways. This manual provides detailed instructions on how to use this tool on multicore Windows workstations or servers. In the public version of DCAT, several improvements have been made over the previous version: (1) it was modularized; (2) a graphical user interface (GUI) was developed; (3) a new version of the MPjobs parallel processing module was incorporated; and (4) a batch-processing function was added. The features of the DCAT GUI are described, including some examples of how to use the GUI to perform simulations. A full explanation of the DCAT methodology is available in the Phase 1 report.
This document contains 6 use cases generated from the model contained in Rational Software Architect.
This document contains 1 use case generated from the model contained in Rational Software Architect.
This document contains 1 use cases generated from the model contained in Rational Software Architect.
This document contains 10 use cases generated from the model contained in Rational Software Architect.
This document contains 10 use cases generated from the rnodel contained in Rational Software Architect.
Biofouling is a well-documented problem in naval engineering, but little is known about its effect on wave energy converter (WEC) performance. In this study, the software WEC-Sim is used to simulate the performance of a point absorber WEC that has been biofouled by “hard” species (e.g., mussels, barnacles) to varying degrees. Specifically, biofouling is assumed to change the nonlinear drag forces acting on the WEC, which have quantifiable effects on key performance characteristics such as optimal damping conditions, power, peak displacement, and peak velocity. The results of this analysis are then used to discuss strategies for WEC control as it relates to biofouling. Furthermore, the results show that average power production can decrease by as much as 15% with heavy biofouling and require an adjustment of the optimal control law by up to 20%.
A new approach is proposed to the geometric synthesis of noncircular gears for a rotary hydraulic machine. The corresponding procedure employs universally available mathematical software and standard graphics programs.
Internal combustion engine (ICE) downsizing through various turbocharging configurations is generally known by the powertrain design community as an effective means to reduce frictional losses, increase waste heat recovery, and improve fuel efficiency while increasing engine power density. However, often is the case that turbocharging strategies, including variable geometry turbochargers, and regulated two-stage turbochargers, incur the performance tradeoff between transient response and fuel economy (pumping losses) at high engine speeds. For off-highway vehicles having particularly transient and high-powered duty cycles, efforts to improve this tradeoff and increase operational flexibility have turned to evaluating various electrified air system architectures. In this study, a 4.5 L diesel-ICE configured with an electrically driven compressor (eBooster ® ) is placed in series with a conventional turbocharger and integrated into a 48 V mild-hybrid powertrain architecture. The objective of this powertrain configuration is to enable engine downsizing by 34%, replacing the current 6.8 L ICE platform with the hybridized 4.5 L ICE concept. The commercial 1-D simulation software GT-SUITE is used for powertrain system development and system optimization. Development and validation of the GT-SUITE model and air system controls is concurrently supported through experimental data collection. The simulation model development includes using machine learning methods for optimizing exhaust gas dilution, injection timing, and eBooster ® power to improve steady-state and transient brake-specific fuel consumption while minimizing criteria pollutant emissions. It was found that total specific fluid consumption over the standardized non-road transient engine duty cycle could be reduced by 18% over the current 6.8 L engine by using an optimized eBoosted 4.5 L engine. The hybridized 4.5 L engine concept concurrently showed sufficient transient response capability and nearly an order of magnitude reduction in duty cycle total soot production.
The purpose of this report was to review pertinent literature and studies to identify current state-of-the-art models and analytical tools that optimize the siting, sizing, and economic value of energy storage in a smart grid infrastructure. In recent decades, research and development has significantly improved the cost and reliability of energy storage systems. However, a relatively small percentage of that work has focused on engineering tools for integrating energy storage into existing or future electric grids. This literature review revealed that only a small number of software tools exist, and that those tools only partially address the needs for placement, sizing, and overall control strategies of stationary energy storage within a smart grid infrastructure. None of the tools comprehensively captures the benefits of energy storage, which would reveal all of the potential values. None of the tools or models provides optimization features that identify optimal placement and sizing options within a transmission or distribution system context. This review identifies a need for tool development to fill the gap in the grid analytics and provides some recommendations of guiding principles for advancing the analytical capabilities needed for the engineering and grid planning communities.