Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “TOOLS”

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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Radiological Recovery Logistics Tool - 20161

Argonne is building and testing a tool, the Radiological Recovery Logistics Tool (RRLT), that can be used during the response and recovery from a radiological or nuclear incident to effectively allocate appropriate commercial and public works equipment to mitigate, remove, and contain radiological contamination. The requirements for this tool - as well as development of the resulting software - is overseen by a steering committee of stakeholders from DHS's National Urban Security Technology Laboratory (NUSTL), the Federal Emergency Management Agency (FEMA), and the Environmental Protection Agency (EPA). One essential requirement is for RRLT to support the efficient and appropriate allocation of resources for a radiological response. Subsequent discussions between ANL and stakeholders have solidified the nature of this support to include identification of the types of resources to be allocated. The study reported in this paper has both factored fundamental concepts and connections out of this identification process and created a Knowledge Base detailing support goals, response scenarios, and efficacy information on dozens of equipment types. In short, RRLT will dynamically apply these findings to situational conditions surrounding contamination incidents. RRLT's Domain, the model of elements, ideas and relationships with which the tool will work, draws concepts from technical reports and stakeholder vocabularies to connect response goals and scenarios to types of equipment that offer utility towards those goals in those scenarios. RRLT's Knowledge Base will contain details on dozens of equipment types and facilitate the operator's discovery and consumption of these details most pertinent to a dynamically selected subset of goals. The core of its Domain Model is based on a report authored by this team. This report [1] contains a comprehensive list of proposed equipment to accomplish various missions or scenarios that might arise after a large-scale radiological contamination incident in an urban environment or critical infrastructure. The report divides potential response and recovery efforts into five support goals: Survey and monitoring of the contaminated area; Mitigation of received dose to first responders: Decontamination (gross and final) of buildings, vehicles, roadways, parks, and other surfaces: Waste management of solid waste generated during recovery operations: and Containment of wastewater and other waste generated during the response and recovery phases. RRLT's development is driven by use cases. A use case is an intention with which a user approaches the software. Use cases are grouped into delivery increments to schedule development, testing, and presentation to stakeholders. This model partitions the system into seven increments: User Arrival and Authentication, Search and Navigation, Equipment Recommendation, Plan Management, Content Management, and Expanded Access. Once a user 15 authenticated, RRLT will present the user with a dashboard that allows them to explore or search RRLT's content. The dashboard will also include a 'Plan' panel for collecting decisions and relevant observations about an incident at hand to facilitate development of an equipment list. RRLT will offer three general modes of access to items in the knowledge base: - Keyword search for direct discovery of items, - Navigation along predetermined paths from recovery goal towards equipment types, and - Interactive guidance towards equipment types by an autonomous software agent: the Equipment Recommendation Wizard. This presentation will detail progress in the development of the RRLT and also discuss opportunities for those interested in providing feedback on its content and functionality. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Panel Session 129: Perspectives (US and Non-US) on the Use of Risk and Dose Assessment Tools (R9.3)

This panel focused on various dose and risk assessment tools for assessments, Deactivation and Decommissioning, remediation, and closure of sites of chemical and radioactive wastes. Representatives from the US government agencies, non-US countries and their representative regulatory bodies or authorities, as well as performance/risk assessment practitioners compared and contrasted the various guidance from regulatory agencies and authorities on how tools such as the Preliminary Remediation Goals (PRG) calculator, the Dose Compliance Concentrations (DCC) calculator, and Residual Radioactivity (RESRAD) should be used in support of analyses and decisions for environmental cleanup activities. Panelists with presentations: Cumulative Impact Evaluation: Innovative Tools for Evaluation of Groundwater Protection (Alaa Aly); Superfund Evaluation Process for Alternative Risk and Dose Models (with Focus on EPA and DOE Tools) (Stuart Walker); NRC Staff Perspective on Risk-Informed Approach and Reasonable Safety Assurance in D and D and LLW (Rateb (Boby) Abu Eid)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Tool for Developing Integrated Strategies for Decontamination and Waste Management - 20291

Management of waste from chemical, biological, and radiological incidents is complicated by the fact that decontamination decisions have a profound impact on the characteristics of resulting waste streams. Wide-area biological and radiological incidents could produce massive quantities of waste that may need to be treated on-site and sent for subsequent disposal as non-contaminated materials, or else be directly disposed of as contaminated materials. The EPA has developed the Waste Estimation Support Tool (WEST) for characterizing and quantifying biological and radiological waste that may be generated from decontamination efforts. This paper focuses on the WEST's uses for radiological incidents. WEST combines Geographic Information System (GIS)-based analysis of externally-supplied plume data, infrastructure databases derived from the Federal Emergency Management Agency's (FEMA's) Hazus tool [1], and satellite imagery surface recognition algorithms to combine the composition and square footage of the buildings in the plume with estimates of the materials between the buildings in the plume. The resulting GIS data files are then imported into a Microsoft Access database application, where they are combined with information about the nature and concentration of contaminants, and then subjected to decontamination strategies for different contaminated surfaces. The tool provides estimates of the type and quantities of potential wastes resulting from simulated decontamination and/or demolition activities and includes estimates of the remaining contamination levels including residual contamination contained within each waste stream. Estimates are presented at several levels of detail, allowing users to obtain needed data at the desired resolution. These include estimates for the total affected area, estimates by contamination zone, estimates by decontamination method(s), and estimates by building type (occupancy classification). EPA is currently developing the next version of WEST which will include several substantial enhancements. The most significant improvement for the next version of WEST will include the ability for users to develop contamination scenarios and waste estimates based on previously developed, readily available, and geographically specific infrastructure data. Instead of using WEST's default infrastructure data based on FEMA's Hazus tool, users will be able to import their own building data specific to the geographically affected area. This capability may substantially decrease uncertainties in the resulting waste estimates because the results will be based on actual building data (numbers of each type, square footage, building height, etc.). Two other significant enhancements will be the ability to generate waste estimates for vehicles and biomass. In addition to building debris and building decontamination waste, vehicles and biomass will likely constitute a significant percentage of the total waste which may result from wide area contamination events. This presentation will present the most recent version of WEST, which includes such considerations as affected biomass (e.g., trees), vehicles, and the ability to replace the default Hazus infrastructure databases with custom infrastructure databases. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Development of Advanced Numerical Tools for the Nonlinear Seismic Analysis of Nuclear Systems

In the framework of Probabilistic Risk Assessment (PRA) of nuclear facilities, a rigorous dynamic characterization of all structural and non-structural components is of paramount concern. The common features of nuclear facilities lies in the combination of three characteristics: 1. low aspect ratio; 2. large mass; and 3. significant embedment in soil. These characteristics make the interaction between the structural system and the surrounding soil a key aspect to consider for seismic risk evaluations. The methodologies and numerical tools currently in use for simulating the seismic response of a nuclear facility with significant Soil Structure Interaction (SSI) date back to the 1970's and rely on a number of simplifying idealizations, mainly related to the characterization of the incident seismic waveforms, the assumption of linear-elastic behavior of the superstructures, and idealization of equivalent linear behavior of the supporting soils. Given this background and taking advantage of the substantial progress in computational mechanics in the last decades, the ongoing research aims at developing advanced numerical tools for the nonlinear, time history simulation of nuclear facilities. This translates into the availability of a robust nonlinear time-domain simulation tool that can accurately model the nonlinearities of coupled soil-structure systems, and whose development includes robust verification and validation. The work described herein is supported by the U.S. Department of Energy (DOE) and focuses on delivering the next-generation, high performance simulation tool in support of DOE needs and mission. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Radiation Mapping at JET and ITER using advanced computational acceleration techniques and tools - Paper 63

The Applied Radiation Physics group at the Culham Centre for Fusion Energy (CCFE) have developed and applied state-of-the-art radiation mapping methods and tools to enable complex shielding calculations in fusion devices during plasma operations, and associated maintenance in the device and surrounding areas. Here, we present the description and application of those tools to produce radiation maps both to support the JET safety case (the EU experimental tokamak device based at Culham) and the planned DT campaign in the next few years; and the ITER device. Radiation mapping of fusion facilities are essential for assessing radiation hardness of electronics during operations, and to define safe working dose limits to staff during routine maintenance. At CCFE the Monte Carlo radiation transport code MCNP6 is one of the codes used to perform radiation transport calculations. Due to the size and complexity of the JET and ITER devices, and their surrounding buildings, a suite of tools have been created at CCFE to reduce the computational requirements of the calculations. This paper describes three of these tools, which have been developed and applied to nuclear and radiological field mapping in fusion devices. The results presented in this paper highlight the application of three methods that have been used to improve the computational efficiency and capabilities for radiation mapping in fusion devices such as JET and ITER. These methods are Global Variance Reduction, the Surface Source Mesh routine and the Smeared Source routine. This paper demonstrates the three techniques used in combination, enabling a very computationally challenging fusion problem to become tractable (with acceptable computing effort), also enabling improved capability to allow the mapping of radiations fields during transport operations for activated materials. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Development of the MCNP-ORIGEN activation automation tool

This paper introduces the MCNP-ORIGEN activation automation tool for streamlining the calculation of experiment source terms. This tool couples the Monte-Carlo radiation-transport solver, MCNP to the depletion tool, ORIGEN-S. To showcase its current capabilities, this paper presents an activation analysis exercise, which is conducted with Serpent, and the results are com- pared. The experiment consists in a 90%-enriched uranium sphere surrounded by light water. A non-fissile cylinder is placed in the water, representing an irradiation experiment. We conducted simulations for 2 different cylinder materials: iron and cobalt at two different temperatures: 300 K and 900 K. The exercise consists of an irradiation of 50 days at a constant power of 5 MW, followed by a decay of 50 days. These studies highlight the discrepancies between how the different tools handle nuclear data. Finally, the results underscore multiple areas of possible improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

The PHASE Project: New Research and Tools to Inform Pollinator Habitat on Utility-Scale Solar

The solar industry is responding to demand for building a clean energy future. At the same time, pollinator declines and habitat losses are resulting in listing consideration for once-common species like monarch butterflies, plus petitions to list bees and other species. How can projects responsibly co-locate pollinator plantings at solar facilities? What ecological and performance benefits can be realized from pollinator plantings? How do developers and owners weigh the costs and challenges of maintaining pollinator plantings and determine the effects it has on power generation, community acceptance, and operations? The Pollinator Habitat Aligned with Solar Energy (PHASE) project is a four-year research project that aims to answer these questions and better support the solar industry in successfully implementing pollinator plantings. This project is funded by the U.S. Department of Energy's Solar Energy Technologies Office. In collaboration with an advisory group composed of industry and technical professionals, the PHASE team developed methodologies to evaluate the impacts of plantings on both biodiversity and the facility operations, including the diversity of plant and insect communities, pollinator services being provided by the site, and the effects of pollinator vegetation on panel temperature and efficiency. The PHASE team also used data to develop tools designed to better support solar industry decision-making on pollinator vegetation including a Pollinator Planting Implementation Manual, a Cost Comparison Tool, a Seed Selection Tool, and Habitat Assessment Module Guidance. Final versions of the four tools will be released this year.

agrivoltaic↗
DOE OSTI2022

The Virtual Test Bed (VTB) Repository: A Library of Multiphysics Reference Reactor Models using NEAMS Tools

With the next generation of nuclear reactors under development, modeling and simulation (M&S) tools are being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in order to support their design, licensing, and future operation. Mirroring the physical test beds currently under construction (i.e., EBR-II and ZPPR), the Virtual Test Bed (VTB) was launched by the National Reactor Innovation Center (NRIC) in collaboration with NEAMS to support the advanced reactor community. This collaborative effort, which involves multiple teams at both Idaho National Laboratory and Argonne National Laboratory aims to use NEAMS tools to model a wide range of reactor designs. Those models are automatically tested to ensure their continued functionality as the tools are further developed. Examples are extensively documented, each acting as a tutorial for applying the relevant NEAMS tools to that reactor design. Currently, five advanced reactor types (with a total of eight specific design variants) are simulated by a variety of different models. These models range from steady-state, core multiphysics simulations to integrated plant analysis during loss-of-flow transients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

PVDeg: Development of a Streamlined Tool for PV Degradation Modeling

The photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 to 50 years. research efforts aim to achieve this while keeping performance degradation at a minimum for decades. This puts considerable pressure on improving the accuracy of long-term durability and reliability assessments. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. The tool will simplify many of the routine computational operations that are common to many degradation studies. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. This repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors.

degradation↗
DOE OSTI2025

The Empty DOESC Handling Tool Verification and Redesign

The handling tool for the Department of Energy Standard Canister (DOESC) is made of six simultaneously movable jaws to apply pressure to the inside surface of the DOESC to allow for their transport when empty (Figure 1). The verification of the handling tool requires analyzing the point of contact of the tool and the canister to see how the roundness effects the handling tool.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2020

Variability and Diversity Load Model Tool [SWR-20-03]

The motivation for the development of this tool and the underlying algorithms and methods was to enable the development of high-temporal resolution, realistic time-series data for quasi-static time-series (QSTS) analysis of distribution systems. Often, aggregated load profile data for a distribution circuit is available (e.g. feeder loading data collected via SCADA at the utility substation) and, while this data is typically accurate it masks the considerable variability of the 100’s or 1000’s of individual loads connected on the circuit. This tool was developed to model both the increased variability expected for these individual loads (e.g. the load of a single distribution transformer connected to 8-12 houses) and the expected diversity between loads on the circuit. It is important to note that the difference in variability and diversity, in the context of this tool, is that variability modeling only adds representative variability due to disaggregated load characteristics (e.g. the presence in the load profile of loads turning off and on like an air conditioner/oven) while the average energy profile remains the same as the user supplied power profile. Diversity modeling generates multiple individual load profiles which, in aggregate, sum to the user supplied power profile. Diversity is effectively variability in the energy usage over longer periods of time than seen in the variability model. Put another way, variability modeling supplies the expected variability due to the operation of various end-use loads and diversity modeling supplies the usage differences due to human behavior, schedules, etc. This load modeling tool was developed for use in generating data for distribution systems. Modeling is summarized by two major functions: 1) taking low resolution load profiles and adding intra-seconds variability onto the profiles, and 2) taking a user supplied load profile and distribution factors and adding both diversity and variability to the user supplied profile.

Zhu, Xiangqi↗
DOE OSTI2022

Generalizability analysis of tool condition monitoring ensemble machine learning models

Tool condition monitoring (TCM) is an essential research area for the optimization and automation of metal machining processes, and could help manufacturers reduce costs, production time, machine downtime, energy use, and part scrappage. However, TCM systems developed in prior studies have struggled to reach the high level of generalizability which is necessary for industrial applications. This study addresses TCM system generalizability to new machining conditions, how variations in machining and environmental conditions may be used to improve model generalizability, and ensemble machine learning techniques for TCM. Further, milling tool life experiments were conducted using various machining conditions, and the processes' sound, spindle power, and axial load signals were collected. Different machine learning models were evaluated for the prediction of tool wear levels, including four individual models and five ensemble models. Changes in cutting speed were found to display a large effect on model performance, while the chip load showed some effect, and the feed rate had little effect. A simulated noise data augmentation technique for model improvement is applied within TCM for the first time, and resulted in increased model generalizability and reduced overfitting. Across several performance metrics the extremely randomized trees ensemble machine learning model generally performed the best for this application, achieving a leave-one-group-out cross validation accuracy score of 92.4 %, a 10-fold cross validation score of 98.9 %, and an averaged accuracy across 11 generalizability tests of 87.3 %.

42 ENGINEERING↗
DOE OSTI2020

Environmental Life Cycle Assessment Spreadsheet tool for Deep Direct-Use Geothermal at the University of Illinois at Urbana-Champaign Campus

A Life Cycle Assessment (LCA) spreadsheet tool was developed to analyze potential environmental benefits of a deep direct-use (DDU) geothermal energy system (GES) at the University of Illinois at Urbana-Champaign (U of IL) campus. The LCA spreadsheet tool is a unique contribution to the feasibility study that provides further insight into the cradle-to-grave environmental impacts associated with the GES over the operating life time, as well as other DDU GES with similar objectives. The tool allows for a more in-depth analysis of the feasibility of DDU GES with respect to the overall environmental impacts. For the U of IL assessment, a doublet (two-well) system is evaluated, which is connected to aboveground mechanical system to supply heating to six agricultural research facilities. The additional of new equipment are assessed for the technical and economic feasibility. The results from this study will also allow geothermal resources from the entirety of the Illinois Basin (ILB) to be assessed and allow the DDU technology to be extended to additional areas of the ILB and other low-temperature sedimentary basins with similar characteristics.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Mapping Inquiry Tool (MapIT) Database

The Mapping Inquiry Tool (MapIT) database consists of a geodatabase and data catalog of geologic, geophysical, structural, hydrologic, and contextual data, based on the data types to support geologic carbon storage activities and other subsurface energy systems resource assessments. The database was aggregated from publicly available data across the USA from state and federal entities. The database is structured by categories including rock unit geology, boundaries, national CS datasets, geophysical data, faults and structural data, infrastructure, surface hydrology, groundwater, and more. The data described in the data catalog is also available in the Mapping Inquiry Tool (https://edx.netl.doe.gov/dataset/mapping-inquiry-tool). Version 3 of the geodatabase and data catalog have been updated as of 5/17/2024. The database was published with a limited number of layers. The Catalog V3 contains many more resources than the geodatabase, documenting all layers that will be included in MapIT, and includes links to the original sources of the data. Within the catalog, in the final column, there is information about if the file is included in the geodatabase or not. Use the links provided in the catalog to download data directly from the original source if not included in the geodatabase. Four resources are included in this submission: 1. Geodatabase 2. ReadMe file 3. Catalog of data layers and additional data resources 4. Web link to a resource describing the motivation and reviewing the content of the geodatabase - DOE NETL Carbon Storage Site Mapping Inquiry Tool Database

carbon storage↗
DOE OSTI2024

Optimizing Residential HVAC Systems: Evaluating How the Usage of Smart Diagnostic Tools for Quality Installation and Commissioning Impacts System Performance and HVAC Contractor Businesses

The adoption of digital quality installation and fault detection tools has the potential to transform the $14 billon residential heating, ventilating, and air conditioning (HVAC) service and installation industry. Increased market penetration can be accelerated by providing an increased understanding of the energy and economic value proposition of the usage of these tools. In tandem with energy and HVAC system performance impact research and analysis, the Southface Team investigated the economic business implications for HVAC service and installation contractors adopting the use of measureQuick (mQ), a smart diagnostic app that aids in quality installation and fault detection and works agnostically with Bluetooth-enabled HVAC technician tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Wear resistance of cutting tools with a plasma-modified surface layer

An analytical model is obtained for calculating the working life of a cutting tool with a plasmamodified surface layer. It permits calculation of the conditions ensuring increased wear resistance of the tool and hence increased reliability in manufacturing on numerically controlled machine tools.

42 ENGINEERING↗
DOE OSTI2019

Improving the Performance of Multipurpose Machine Tools

Attention focuses on means of improving the efficiency and capabilities of multipurpose machine tools by expanding the range of available tools and the methods of surface machining. As an example, new approaches are applied to the manufacture of complex parts by means of a multipurpose machine tool. The machining efficiency is improved.

42 ENGINEERING↗
DOE OSTI2020

National Grid: Using the LEAD Tool Data to Target Energy Affordability Services to Eligible Customers in New York

In the following use case, investor-owned utility company, National Grid, used the Low-Income Energy Affordability Data (LEAD) Tool to support the implementation of its Home Energy Affordability Team (HEAT), a weatherization program for income-eligible residential natural gas customers in its service territory in Long Island, New York. Using LEAD Tool data, National Grid was able to determine how many households may be eligible for the program to inform additional marketing efforts. This use case is an example of how utilities of all sizes and types in the United States can use the LEAD Tool in similar ways to gain insights and better address customer energy affordability needs.

Low-Income Energy Affordability Data Tool, LEAD To↗