Relap-7: Advanced Nuclear Reactor Systems Analysis Software Package
Advanced Nuclear Reactor Systems Analysis Software Package
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Advanced Nuclear Reactor Systems Analysis Software Package
A deterministic state-of-charge (SOC) balancing approach software control code is introduced as an integral secondary management to primary control layer of an islanded small microgrid or nanogrid system made up of multiple grid-forming inverter/battery/solar combination systems, where each set of batteries with each inverter are on independent DC buses (i.e. non-paralleled on the DC sides). A DERMS-level control approach, algorithm and automation controller program was developed to improve coordination and enable microgrid asset compliance and SOC balancing, enabling provision of a system-level power stability support architecture, load support, and asset scalability. The architecture is configured to treat each unit or micro/nano-grid as a node in a microgrid network, allowing for autonomous DERMS control regarding load and SOC balancing and power stability. As the network grows with the addition of units, greater coordination efforts may be required. The ideal small network microgrid ranges from 2-10 inverter/battery units before additional control parameters must be considered in the existing architecture. The control approach focuses on a deterministic state-of-charge analysis as the primary level control process followed by a secondary control loop using a forced frequency-watt droop strategy to conform off-the-shelf components into behaving under a leader-follower configuration. Adopting this control scheme has been shown to allow for a balanced, unit-coordinated microgrid network, enabling stable power flow. The deterministic state-of-charge approach is introduced as an integral primary control layer of an islanded small network microgrid. A standard strategy for SOC balancing is implementing a battery management system (BMS) to control SOC on the DC side. An alternative approach is to determine how to coordinate sending and receiving power on the AC side with multiple units. The latter approach assesses all the integrated units in the microgrid network. Once the individual units are identified, further system data is required to calculate each unit's total kWh, provided information about its capability to supply or consume kWh and availability. The secondary control layer in the multi-layered small network microgrid methodology uses the primary layer’s decision to initiate frequency setpoint changes, initializing the SOC balancing. The secondary control layer considers numerous system-dependent variables to enable a charging and discharging profile based on adjustable frequency setpoints. The combined architecture will result in stable, coordinated power flow enhancing an AC microgrid's functionalities.
SF-26-078 This software provides a high-level workflow for satellite-based flood and surface-water mapping using Sentinel-1 SAR and Sentinel-2 multispectral imagery. It supports preparation of remote-sensing data, training and evaluation of deep-learning models, and generation of high-resolution water extent predictions, including methods to improve robustness to SAR speckle noise and cross-sensor image misalignment.
The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages—C, C++, and Fortran—and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.
Abstract We develop an automatic and objective method to measure and correct residual aberrations in atomic-resolution HRTEM complex exit waves for crystalline samples aligned along a low-index zone axis. Our method uses the approximate rotational point symmetry of a column of atoms or single atom to iteratively calculate a best-fit numerical phase plate for this symmetry condition, and does not require information about the sample thickness or precise structure. We apply our method to two experimental focal series reconstructions, imaging a β-Si 3 N 4 wedge with O and N doping, and a single-layer graphene grain boundary. We use peak and lattice fitting to evaluate the precision of the corrected exit waves. We also apply our method to the exit wave of a Si wedge retrieved by off-axis electron holography. In all cases, the software correction of the residual aberration function improves the accuracy of the measured exit waves.
Earth System Models (ESMs) are excellent tools for quantifying many aspects of future climate dynamics but are too computationally expensive to produce large collections of scenarios for downstream users of ESM data. In particular, many researchers focused on the impacts of climate change require large collections of ESM runs to rigorously study the impacts to both human and natural systems of low-frequency high-importance events, such as multi-year droughts. Climate model emulators provide an effective mechanism for filling this gap, reproducing many aspects of ESMs rapidly but with lower precision. The fldgen v1.0 R package quickly generates thousands of realizations of gridded temperature fields by randomizing the residuals of pattern scaling temperature output from any single ESM, retaining the spatial and temporal variance and covariance structures of the input data at a low computational cost. The fldgen v2.0 R package described here extends this capability to produce joint realizations of multiple variables, with a focus on temperature and precipitation in an open source software package available for community use (https://github.com/jgcri/fldgen). This substantially improves the fldgen package by removing the requirement that the ESM variables be normally distributed, and will enable researchers to quickly generate covarying temperature and precipitation data that are synthetic but faithful to the characteristics of the original ESM.
This repository contains data and processing scripts necessary to train the object detection models utilized in the underwater target detection software demonstration on the RivGen turbine project and to produce performance metrics (precision, recall, mAP50, mAP50-95). - Contents - Data consist of "images" and "labels". Each image has an associated label, both share the same time string in its file name (e.g., 2024_05_25_09_01_57.98.jpg and 2024_05_25_09_01_57.98.txt). Time strings have the format %yyyy_%mm_%dd_%HH_%MM_%SS.%3f. Images and labels were curated from 2021 and 2024 smolt outmigration periods at the project site in Igiugig, AK. Images are monochrome 8-bit images of objects (smolt, debris, and other) passing through the field of view of the deployed cameras during various operational stages of the RivGen turbine. Labels are text files indicating the class and bounding polygon of each object in an image. The provided labels use the "YOLO" label format. - Requirements - Python3.8+ is required to install and run the train and validation script. The README.md provides instruction for installing the requirements from the requirements.py file. - Instructions - The "example_train.py" file ingests the provided data, trains a model, and produces model performance metrics at completion. NOTE: model performance metrics will vary from run to run as a consequence of the random selection of training and validation data.
This data package contains raw gas chromatography–mass spectrometry (GC-MS) data for isoprene/monoterpene emission rates used to support the publication "Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin," Phytochemistry, in-press. The attached data files require use of the Agilent MassHunter software. Alternatively, data has been exported into Excel files and can be accessed at [DOI]. For further information on how to Raw isoprene and monoterpene emission rates data
Fermilab is undergoing the most ambitious upgrade to its accelerator control system of the 21st century. As part of the ACORN project, hundreds of legacy control system applications written in C/C++ will be re-imagined and developed from the ground up. In addition, applications to support Fermilab’s new super-conducting linear accelerator are already under construction. To manage the development of modern controls applications, the Controls department has adopted an Agile software development process based on eXtreme Programming. In this paper we will describe our process and detail our experience applying it to the development of two case studies.
This paper discusses model-driven setup of the Continuous Electron Beam Accelerator Facility (CEBAF) for the 12GeV era, focusing on qsUtility. qsUtility is a set of software tools created to perform emittance measurements, analyze those measurements, and compute optics corrections based upon the measurements.qsUtility was developed as a toolset to facilitate reducing machine configuration time and reproducibility by way of an accurate accelerator model, and to provide Operations staff with tools to measure and correct machine optics with little or no assistance from optics experts.
Most existing buildings have sub-optimal heating, ventilation, and air conditioning (HVAC) controls, resulting in wasted energy and occupant discomfort. Retro-commissioning (RCx) addresses many of these issues, but it is a lengthy and highly customized process. Limited capabilities of existing building automation system hardware restricts the scope of most RCx projects. Incentive programs consider building automation system (BAS) hardware retrofits to be high-capital investments and do not allow them in typical RCx programs. This paper describes work that the authors are leading to facilitate technical and market innovation in the BAS industry to unlock large savings in existing commercial buildings through deep retrofits of BAS hardware and software. California and New York research projects are demonstrating BAS retrofits leveraging the American Society of Heating, Refrigeration, and Air Conditioning Engineers’ (ASHRAE) new Guideline 36 high performance sequences of operation to achieve greater than 20 percent whole building energy savings, while saving costs and reducing risk through streamlined processes and standardization across BAS manufacturer product lines and across implementation practices. This paper describes market barriers that impede achieving deep savings from BAS retrofits in custom incentive and traditional RCx programs and presents a new maximum potential BAS retrofit model that addresses these barriers. The new model leverages the authors’ efforts in market enablement through open standards, BAS industry partnerships, and tools for cost-effective scaling that includes tools for project screening, savings calculations, and measurement and verification (M&V). This approach is widely applicable and will be ready for at-scale implementation within two years.
Voids are expansive regions in the universe containing significantly fewer galaxies than surrounding galaxy clusters and filaments. They are a fundamental feature of the cosmic web and provide important information about galaxy physics and cosmology. For example, correlations between voids and luminous tracers of large-scale structure improve constraints on the expansion of the universe as compared to using tracers alone, and numerous studies have shown that the void environment influences the evolution of galaxies. However, what constitutes a void is vague and formulating a concrete definition to use in a void-finding algorithm is not trivial. As a result, several different algorithms exist to identify these cosmic underdensities. Our Void Analysis Software Toolkit, or VAST, provides Python 3 implementations of two such algorithms: VoidFinder and V 2 . This consolidation of two popular void-finding algorithms allows the user to, for example, easily compare the results of their analysis using different void definitions.
Idaho National Laboratory, in collaboration with Invensys, performed a laboratory assessment on Invensys Foxboro Control Software. During this assessment, vulnerabilities were discovered, evaluated, and mitigation strategies developed.
This document reviews the verification of the basic shape quantification attributes in the MAMA software against hand calculations in order to show that the calculations are implemented mathematically correctly and give the expected quantification results.
This document reviews the size and shape attributes that are quantified by the MAMA software, shows how they are calculated, and then gives some visual example shapes.
This document shows examples of the results from quantifying objects of certain sizes and types in the software. It is intended to give users a better feel for some of the quantification calculations, and, more importantly, to help users understand the challenges with using a small set of ‘shape’ quantification calculations for objects that can vary widely in shapes and features. We will add more examples to this in the coming year.
The table on the following pages lists a set of morphology terms for describing materials. We have organized these terms by categories. Software uses are welcome to suggest other terms that are needed to accurately describe materials. This list is intended as a initial starting point to generating a consensus terminology list.
• To provide an overview of the MC Tablet Hybrid software. • To communicate changes in Work Order (WO) generation and distribution. • Provide step by step process for electronic WO data entry for sampler inspection forms.