Search NASA⌕ Search

SEARCH · Search NASA

Results for “manage simulation input data”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Development of an Integrated Hydrological Model for Simulation of Surface Runoff and Stream Flow in Tims Branch Watershed, Savannah River Site, South Carolina - 16203

This research is part of continued efforts to develop an integrated transport model to predict the distribution of tin within the overland flow in Tims Branch Watershed (TBW) at Savannah River Site (SRS), South Carolina. Tin was introduced into TBW during the application of an innovative mercury remediation technology implemented by the U.S. Department of Energy's Office of Environmental Management, which involved the injection of stannous (tin) chloride into mercury contaminated groundwater. Understanding the fate and transport of tin and its compounds is of primary importance due to their potential impact on the environment. In this study, we developed an overland hydrology model (MIKE SHE) capable of simulating surface hydrology throughout the TBW. The modeling application used historical precipitation, groundwater levels, geological data, and river discharges that were retrieved from government databases and input to the model. The model was developed to simulate spatio-temporal distribution of flow discharges, flow duration, and water levels in the TBW. The preliminary simulation results indicated that the model was capable of predicting flow depth and velocity within the study area during extreme climate events. The developed hydrology model will later on be coupled with transport model to simulate tin distribution within Tims Branch stream during seasonal storm events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Radiological Performance Modeling: Platform Comparison

Zapadnoe Uranium Mill Tailings Site, Pridneprovsky Chemical Plant Ukraine: Two exposure scenarios were utilized to develop performance assessment models in GoldSim and NORMALYSA. The first scenario is an onsite worker exposed to radioactivity through external ground irradiation as well as radon and radioactive dust inhalation. The second being an offsite Resident 300 years after institutional control exposed through the ingestion of garden vegetables irrigated by contaminated ground water, ingestion of fish from Konoplyanka River, and agricultural activities in contaminated garden. NORMALYSA utilizes a modular interface to connect extensive pre-created modules to develop contaminant transport and risk assessment models for safety assessments and performance assessments at NORM and legacy sites. Developed by Facilia AB, the program was tested with the creation of the Zapadnoe model under the International Atomic Energy Agency MODARIA Il Working Group 1 (WG1). Default values are provided for input parameters where site specific data and distributions lack. Probabilistic simulations and inputs are limited to parameters with assigned Gaussian probability functions. Similar results for transient worker inhalation dose were found in comparison with the Zapadnoe GoldSim model. However, the NORMALYSA model has results larger by an order of magnitude for external radiation in the transient worker and for aquatic food ingestion, inhalation, and garden food ingestion to the resident. Performance Assessment Modeling: Radiological performance models promote good management and support in remediation and environmental decision making by optimizing radioactive waste disposal site performance. a performance assessment model of the Zapadnoe uranium mill tailings site and a model for calculating authorized limits at Los Alamos National Laboratory are created to demonstrate and highlight the respective capabilities of three modeling platforms: GoldSim, NORMALYSA, and RESRAD-Onsite. GoldSim is a general-purpose modeling platform with the ability to simulate site-specific FT radionuclide transport and risk assessment using a graphical interface to create and link elements that act as indivisible building blocks of the model. The Zapadnoe performance assessment model created in GoldSim is composed of input parameters collected from site specific parameters from WG1 as well as standard assumptions seen in the Generic PA Model from Neptune and Company. The multivariate Zapadnoe simulation contains both deterministic and probabilistic simulation capabilities with the ability to quantitatively represent the uncertainty and associated risks of the site via the Monte Carlo simulation method. Model parameters, documentation, and assumptions are built directly into the model creating a transparent, reproducible, and more purposeful site specific model. To demonstrate this, an ingestion of water pathway was included in addition to the exposure pathways included in the NORMALYSA model. GoldSim offers a wide variety of probability distributions to choose from as well as many tools to visualize the uncertainty of the models and explore which pathways and radionuclides dominate dose. In contrast to the NORMALYSA model, the GoldSim model uses dynamic simulation to calculate tritium concentrations. Authorized limits support the evaluation of radiological health effects from radionuclides present in bulk contaminated soil in order to assist in the process of clearing land for release under different uses. Calculations of authorized limits in RESRAD-Onsite and GoldSim models support the evaluation for 15 radionuclides using a residential exposure scenario, indoor and outdoor inhalation of dust and vapor phase radionuclides (tritium), incidental soil ingestion, and ingestion grown fruits and Vegetables. RESRAD-Onsite, developed by Argonne National Laboratory is a dedicated computer code for calculating radiation doses and cancer risks to an individual located on top of radioactively contaminated soils. It can also be used to provide guidelines for deriving radionuclide soil levels corresponding to a specific dose criterion. The menu driven user interface facilitates selection of radionuclides and soil concentrations, as well as defines parameter values related to materials, environmental factors, and exposure pathways. The program contains radionuclide-specific data such as dose conversion factors and risk coefficients, as well as soil-water partition coefficients and transfer factors for biotic media. The GoldSim model successfully emulates the RESRAD-Onsite code using identical radiological decay and ingrowth factors, radiation dose conversion factors, and other input parameters. DE EEDE ETS Each model supports dynamic modeling of radionuclide ingrowth and decay over time, and integrate this capability with the transport of radionuclides in the environment via processes such as advection and/or diffusion in fluids, or within porous solid media, The applicability of each program is heavily dependent on project context. In the context of developing Authorized Limits, RESRAD-Onsite may be a more desirable option as it was developed for this particular application. For simple disposal or legacy sites or sites that do not need site-specific model structure, NORMALYSA may be a desirable modeling platform, GoldSim can be used to model any problem for which RESRAD or NORMALYSA is applicable, but its strength lies in its flexibility, analytical, and probabilistic capabilities.

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

PDQ Users Manual Version 1 for PDQ Code Version 1.12

PDQ is a tool for the management of the input and execution of batch jobs for simulation codes that use a text based input system. It accomplishes this goal by operating at two levels. First, it takes input file templates (commonly known at LANL as input deck templates) and creates multiple instantiations by performing substitutions of data from table files into symbols (variables) found in the template. Second, it provides commands to submit the created files to the SLURM batch system for execution. These two activities taken together produce a whole that is greater than the sum of its parts and provides an elegant way of executing studies across multiple similar simulations while minimizing the risk of typographical errors in the input files.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS)

This will be licensed via RSICC. A new, integrated data and analysis system has been designed to simplify and automate the performance of accurate and efficient evaluations for characterizing the input to the overall nuclear waste management system -UNF-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). A relational database within UNF-ST&DARDS provides a standard means by which UNF-ST&DARDS can succinctly store and retrieve modeling and simulation (M&S) parameters for specific spent nuclear fuel analysis. A library of various analysis model templates provides the ability to communicate the various set of M&S parameters to the most appropriate M&S application. Interactive visualization capabilities facilitate data analysis and results interpretation. UNF-ST&DARDS current analysis capabilities include (1) assembly-specific depletion and decay, (2) and spent nuclear fuel cask-specific criticality and shielding. Currently, UNF-ST&DARDS uses SCALE nuclear analysis code system for performing nuclear analysis.

Banerjee, Kaushik↗
DOE OSTI2026

Assessing shellfish water exposure to fecal bacteria pollution in Salish Sea: three-dimensional modeling and implications for monitoring

Fecal bacteria (FB) contamination poses significant risks to shellfish safety and management in coastal and estuarine waters. Despite extensive pollution identification and correction efforts, FB contamination in shellfish-growing areas persists in the Salish Sea, highlighting the need to identify overlooked sources and better understand FB transport from riverine and shoreline inputs to shellfish beds. To address this, a high-resolution three-dimensional hydrodynamic model coupled with FB kinetics was developed and applied to a case study site in Salish Sea—Portage Bay—to simulate freshwater plume circulation, flushing dynamics, and bacterial transport. Daily FB loading from the major freshwater inflow—Nooksack River was generated by both linear interpolation and integrating a machine learning approach (XGBoost), trained on historical hydrological and meteorological data. The model successfully reproduced both the magnitude and seasonal variation of FB concentrations in Portage Bay for the year of 2021, demonstrating that simplified FB kinetics with first-order decay due to mortality was effective in this dynamic coastal environment with short flushing time. Model results identified the Nooksack River as the dominant far-field FB source, while scenario simulations showed that near-field coastal stormwater outfalls elevated local FB levels following rainfall, particularly under low-flow conditions. The XGBoost prediction provided comparable or superior accuracy to linear interpolation, particularly during periods of missing observational data, by capturing short-term variability and event-driven loading more effectively. Integrating data-driven riverine FB inputs with mechanistic coastal numerical modeling provides a robust framework for operational forecasting of shellfish bed exposure risk and supports adaptive monitoring and management of shellfish growing areas in the Salish Sea and similar coastal systems.

Salish Sea↗
DOE OSTI2025

Coupling Remote Sensing With a Process Model for the Simulation of Rangeland Carbon Dynamics

Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well as limited data availability. We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long-term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C-cycle processes. Bayesian calibration was conducted using quality-controlled C flux data sets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern US rangelands to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass-shrub mixture, and grass-tree mixture). The resulting RCTM system produced higher model accuracy for estimating annual cumulative gross primary productivity (GPP) (R 2 > 0.6, RMSE <390 g C m -2 ) relative to net ecosystem exchange of CO 2 (NEE) (R 2 > 0.4, RMSE <180 g C m -2 ). Model performance in estimating rangeland C fluxes varied by season and vegetation type. The RCTM captured the spatial variability of SOC stocks with R 2 = 0.6 when validated against SOC measurements across 13 NEON sites. Model simulations indicated slightly enhanced SOC stocks for the flux tower sites during the past decade, which is mainly driven by an increase in precipitation. Future efforts to refine the RCTM system will benefit from long-term network-based monitoring of vegetation biomass, C fluxes, and SOC stocks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

ExtendSim Scenario Manager Overview

ExtendSim® is an advanced simulation environment used to model processes using either discrete event, continuous, discrete rate or agent-based modeling techniques. The process models created are comprised of blocks that are linked together to simulate the logic and sequence of the process being evaluated. These blocks can communicate with each other via messages. This ensures that required information is communicated throughout the model as needed. In addition, ExtendSim has a number of data management techniques, including integrated databases that can be used to store input and output information from the model.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Coordinated Thermal Safety Attack and Defense on EV Battery Management Systems

Battery temperature sensor and battery current sensor data which are key sensing inputs to the Battery Management Controllers in electric vehicles, are vulnerable to possible cyber/ physical manipulation due to known vulnerabilities inherited from CAN bus technology that is used for in-vehicle communications between electronic control units that transfer sensing and control data. In this paper, we first create a simulation that enables us to evaluate impact of cyber physical attacks on electric vehicle battery management system in a controlled environment that violates thermal safety. Specifically, we emulate a Level 3 - DC fast charging system with SAE J1772/CCS, integrated with standard charging controls and thermal safety controls on EVs, and various sensing data flows. Second, we propose a coordinated current and battery temperature attack that has crippling economic, and safety impacts. Third, we quantify the usability, economic and safety impacts of such attacks as a function of the extent of data manipulation. Finally, we propose a physics model driven detection technique to detect presence of such attacks.

25 ENERGY STORAGE↗
DOE OSTI2025

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Composite Analysis Solid Waste Release Data Reduction of Activity Flux from Waste Sites to the Vadose Zone for Baseline Assessment

This environmental calculation file (ECF) describes the data reduction methodology for the solid waste release datasets generated by the Composite Analysis Solid Waste Release (CASWR) model (CP-62766, Model Package Report: Composite Analysis Solid Waste Release Model [CASWR Model]) and documents the resulting reduced datasets for the updated Composite Analysis (CA) baseline assessment. This ECF is in support of the updated Hanford Site CA. The purpose of the updated Hanford Site CA is to provide an estimate of the cumulative radiological impacts from active and planned low-level radioactive waste disposals and other potentially interacting radioactive waste disposal sources that will remain following Hanford Site closure. The vadose zone modeling activities associated with the CA includes solid waste forms as contaminant sources. To support the modeling of solid waste transport from the vadose zone to the groundwater at the Hanford Site, the CASWR model was designed to generate deterministic radionuclide release rates for the Hanford Site Central Plateau solid waste disposal sites. The complete CASWR model-generated dataset for the CA Baseline Assessment consists of 2,378,831 sets of time and release rates (1,073,869 sets for the 200 East Area and 1,304,962 sets for the 200 West Area), representing a course of the simulation from year 1953 to year 12,069, 16 radiological contaminants of potential concern (COPCs), and 237 solid waste sources as documented in ECFHANFORD- 19-0112, Solid Waste Release Calculations for the Composite Analysis Baseline Assessment. For several of the STOMP vadose zone models, the number of release rate data pairs required for release at all waste sites would exceed the limitations imposed by the STOMP modelling software package used to simulate contaminant transport through the vadose zone. As a result, a data reduction of the CASWR dataset is required prior to its use as a source input for the CA vadose zone modeling activities.

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

Simulating Regional Groundwater Flow in the Vicinity of the Nevada National Security Site, Nye County, Nevada - 16104

The Death Valley Regional Groundwater Flow System (DVRFS) occupies an area of about 70,000 km{sup 2} in south-central Nevada and southeastern California. Interest in this system stems from the need to (1) understand the groundwater flow paths and travel times associated with potential migration of radioactive material from the Nevada National Security Site (NNSS) where underground nuclear testing was conducted from 1956 to 1992; (2) characterize the groundwater system in the vicinity of the proposed high-level radioactive waste repository at Yucca Mountain, Nev.; and (3) address a variety of potential effects from NNSS activities on users down gradient from the NNSS and Yucca Mountain. A single groundwater flow model of the DVRFS has been developed that integrates data and results of two previous regional-scale models and supports Department of Energy (DOE) programs at the NNSS. The numerical model was constrained by organizing hydrogeologic data and interpretations in three-dimensional (3D) geographic information systems and constructing a digital three-dimensional (3D) hydrogeologic framework model (HFM) to represent 27 hydrogeologic units (HGUs) and major structures in the DVRFS region. The 3D hydrogeologic data sets were discretized to 1,500 meters (m) grid cell resolution for input arrays required for the model. The DVRFS was simulated using the USGS 3D groundwater-flow modeling code MODFLOW-2000. Two examples showing how the DVRFS regional model is used by the DOE as part of waste management activities at the NNSS: (1) use of the regional model to provide the boundary conditions for site-scale models, and (2) use of the regional model to assess changes in hydraulic gradient and flow paths in the regional flow system resulting from changes in pumping in various areas of interest. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Tiamat

Tiamat is the driver program for coupling three application codes together to simulate a nuclear reactor core. This code is used to study pellet clad interaction failures in commercial nuclear light water It generates stress plots and temperature profiles for fuel rods in the reactor core. The driver program initializes the underlying applications, initiates the overall solve process, generates consistent input files and manages the data transfers between the applications. It contains the top level driver code, the data transfer code, input file parsing and corresponding unit tests. Tiamat was developed under the CASL Energy Innovation Hub. The Tiamat code DOES NOT include any source code for the actual coupled physics application components or solvers. The application codes and solver libraries must be obtained separately from the Tiamat source code. Tiamat will be released open source under a BSD license.

Source record↗
DOE OSTI2013

Multiphysics Integrated Coupling Environment (MICE) User Manual

The complex, multi-part nature of waste glass melters used in nuclear waste vitrification poses significant modeling challenges. The focus of this project has been to couple a 1D MATLAB model of the cold cap region within a melter with a 3D STAR-CCM+ model of the melter itself. The Multiphysics Integrated Coupling Environment (MICE) has been developed to create a cohesive simulation of a waste glass melter that accurately represents the cold cap. The one-dimensional mathematical model of the cold cap uses material properties, axial heat, and mass fluxes to obtain a temperature profile for the cold cap, the region where feed-to-glass conversion occurs. The results from Matlab are used to update simulation data in the three-dimensional STAR-CCM+ model so that the cold cap is appropriately incorporated into the 3D simulation. The two processes are linked through ModelCenter integration software using time steps that are specified for each process. Data is to be exchanged circularly between the two models, as the inputs and outputs of each model depend on the other.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Final Project Report CFA-14-6357: A New Paradigm for Understanding Multiphase Ceramic Waste Form Performance

This project fabricated model multiphase ceramic waste forms with processing-controlled microstructures followed by advanced characterization with synchrotron and electron microscopy-based 3D tomography to provide elemental and chemical state-specific information resulting in compositional phase maps of ceramic composites. Details of 3D microstructural features were incorporated into computer-based simulations using durability data for individual constituent phases as inputs in order to predict the performance of multiphase waste forms with varying microstructure and phase connectivity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Nitrogen rate and landscape impacts on life cycle energy use and emissions from switchgrass-derived ethanol

Switchgrass-derived ethanol has been proposed as an alternative to fossil fuels to improve sustainability of the US energy sector. In this study, life cycle analysis (LCA) was used to estimate the environmental benefits of this fuel. To better define the LCA environmental impacts associated with fertilization rates and farm-landscape topography, results from a controlled experiment were analyzed. Data from switchgrass plots planted in 2008, consistently managed with three nitrogen rates (0, 56, and 112 kg N ha –1 ), two landscape positions (shoulder and footslope), and harvested annually (starting in 2009, the year after planting) through 2014 were used as input into the Greenhouse gases, Regulated Emissions and Energy use in transportation (GREET) model. Simulations determined nitrogen (N) rate and landscape impacts on the life cycle energy and emissions from switchgrass ethanol used in a passenger car as ethanol–gasoline blends (10% ethanol:E10, 85% ethanol:E85s). Results indicated that E85s may lead to lower fossil fuels use (58 to 77%), greenhouse gas (GHG) emissions (33 to 82%), and particulate matter (PM2.5) emissions (15 to 54%) in comparison with gasoline. However, volatile organic compounds (VOCs) and other criteria pollutants such as nitrogen oxides (NOx), particulate matter (PM10), and sulfur dioxides (SO x ) were higher for E85s than those from gasoline. Nitrogen rate above 56 kg N ha –1 yielded no increased biomass production benefits; but did increase (up to twofold) GHG, VOCs, and criteria pollutants. Lower blend (E10) results were closely similar to those from gasoline. The landscape topography also influenced life cycle impacts. Biomass grown at the footslope of fertilized plots led to higher switchgrass biomass yield, lower GHG, VOCs, and criteria pollutants in comparison with those at the shoulder position. Lastly, results also showed that replacing switchgrass before maximum stand life (10–20 years.) can further reduce the energy and emissions reduction benefits.

09 BIOMASS FUELS↗
DOE OSTI2015

Interoperability format translation and transformation between IFC architectural design file and simulation file formats

Automatically translating a building architecture file format (Industry Foundation Class) to a simulation file, in one aspect, may extract data and metadata used by a target simulation tool from a building architecture file. Interoperability data objects may be created and the extracted data is stored in the interoperability data objects. A model translation procedure may be prepared to identify a mapping from a Model View Definition to a translation and transformation function. The extracted data may be transformed using the data stored in the interoperability data objects, an input Model View Definition template, and the translation and transformation function to convert the extracted data to correct geometric values needed for a target simulation file format used by the target simulation tool. The simulation file in the target simulation file format may be generated.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2012

A decision support system prototype including human factors based on the TOGA meta-theory approach

The human contribution to the risk of operation of complex technological systems is often not negligible and sometimes tends to become significant, as shown by many reports on incidents and accidents occurred in the past inside Nuclear Power Plants (NPPs). An error of a human operator of a NPP can derive by both omission and commission. For instance, complex commission errors can also lead to significant catastrophic technological accidents, as for the case of the Three Mile Island accident. Typically, the problem is analyzed by focusing on the single event chain that has provoked the incident or accident. What is needed is a general framework able to include as many parameters as possible, i.e. both technological and human factors. Such a general model could allow to envisage an omission or commission error before it can happen or, alternatively, suggest preferred actions to do in order to take countermeasures to neutralize the effect of the error before it becomes critical. In this paper, a preliminary Decision Support System (DSS) based on the so-called (-) TOGA meta-theory approach is presented. The application of such a theory to the management of nuclear power plants has been presented in the previous ICAPP 2011. Here, a human factor simulator prototype is proposed in order to include the effect of human errors in the decision path. The DSS has been developed using a TRIGA research reactor as reference plant, and implemented using the LabVIEW programming environment and the Finite State Machine (FSM) model The proposed DSS shows how to apply the Universal Reasoning Paradigm (URP) and the Universal Management Paradigm (UMP) to a real plant context. The DSS receives inputs from instrumentation data and gives as output a suggested decision. It is obtained as the result of an internal elaborating process based on a performance function. The latter, describes the degree of satisfaction and efficiency, which are dependent on the level of responsibility related to each professional role. As an application, we present the simulation of the discussed error, e.g. the unchecked extraction of the control rods during a power variation maneuver and we show how the effect of human errors can affect the performance function, giving rise to different countermeasures which could call different operator figures into play, potentially not envisaged in the standard procedure. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗