Sandia Low-Temperature Plasma Research Facility: Modeling & Simulation Update.
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The dispositioning of nuclear waste generated at facilities across the country is an ongoing battle that affects us all. National laboratories and research centers dealing in medical research, clean energy, and other nuclear activities such as the Department of Energy (DOE) facilities face the need to properly manage and dispose of nuclear waste. A dynamic modeling solution would enable the DOE and others to make decisions on waste disposal and technological options. In doing so, this research explores modeling techniques using available data to address these situations. The focus being on developing an initial robust and adaptable discrete event model using the ExtendSim tool. This modeling effort will target the dispositioning of transuranic waste at the Savannah River National Laboratory (SRNL) which can be expanded to represent the current state of disposition process for waste generated at other DOE facilities. The model aims to assess resource allocation and waste processing options to stabilize productivity and cut the backlog of nuclear waste. By assessing the results of different scenarios, this research aims to provide actionable insights for the DOE. This approach has the potential to significantly improve the management of radioactive waste, offering the capability of evaluating options for optimizing the process for nuclear waste disposal. The findings of this study can serve as a valuable resource for decision-makers and other national laboratories, or research entities engaged in nuclear operations by enabling them to make more informed choices.
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Environmental management problems associated with contamination of groundwater resources with heavy metals (such as chromium) typically require complex biogeochemical model simulations and analysis of in situ remediation. Frequently, the in situ remediation is the only viable treatment option. In these cases, a three-dimensional reactive transport model of relevant biogeochemical processes is invaluable. Recently, we have developed a novel unique biogeochemical simulator called CHROTRAN (http://chrotran.lanl.gov; Hansen et al. 2017, Vesselinov et al. 2018a) capable to represent the full three-dimensional dynamics of processes associated with in situ biogeochemical remediation of heavy metals in heterogeneous aquifers. CHROTRAN accounts for spatial and temporal transients of (1) the heavy metal to be remediated, (2) introduced amendments (e.g., through well injection), and (3) biomass growth and decay. The introduced amendments can include (1) an electron donor (e.g., molasses), (2) a nontoxic-conservative bio-inhibitor (e.g., ethanol), and (3) a biocide (e.g., dithionite). In addition, direct abiotic reduction by donor-metal interaction as well as donor-driven biomass growth and bio-reduction are modeled in CHROTRAN. Other critical processes, such as donor sorption, bio-fouling and biomass death are also modeled. CHROTRAN can simulate the groundwater flow dynamics introduced due a series of injection and extraction wells and account for reduction of aquifer permeability near the wells due bio clogging. CHROTRAN is based on the existing PFLOTRAN (http://pflotran.org; Lichtner et al, 2017a) code framework, taking advantage of the reaction interface allowing for implementation of complex model features and leverage other facets of PFLOTRAN, such as multi-component geochemistry and high-performance computing. Here, we present numerical simulations and model analyses related to the Los Alamos National Laboratory (LANL) chromium site. The analyses are performed by coupling of CHROTRAN with MADS (Model Analysis and Decision Support; http://mads.lanl.gov; Vesselinov et al., 2018b). We present analyses related to uncertainty quantification of model predictions, sensitivity of model parameters and remedial decision support. (authors)
Almost half of the total energy used in the U.S. buildings is consumed by heating, ventilation and air conditionings (HVAC) according to EIA statistics. Among various driving factors to energy performance of building, operations and maintenance play a significant role. Many researches have been done to look at design efficiencies and operational controls for improving energy performance of buildings, but very few study the impacts of HVAC systems maintenance. Different practices of HVAC system maintenance can result in substantial differences in building energy use. If a piece of HVAC equipment is not well maintained, its performance will degrade. If sensors used for control purpose are not calibrated, not only building energy usage could be dramatically increased, but also mechanical systems may not be able to satisfy indoor thermal comfort. Properly maintained HVAC systems can operate efficiently, improve occupant comfort, and prolong equipment service life. In the paper, maintenance practices for HVAC systems are presented based on literature reviews and discussions with HVAC engineers, building operators, facility managers, and commissioning agents. We categorize the maintenance practices into three levels depending on the maintenance effort and coverage: 1) proactive, performance-monitored maintenance; 2) preventive, scheduled maintenance; and 3) reactive, unplanned or no maintenance. A sampled list of maintenance issues, including cooling tower fouling, boiler/chiller fouling, refrigerant over or under charge, temperature sensor offset, outdoor air damper leakage, outdoor air screen blockage, outdoor air damper stuck at fully open position, and dirty filters are investigated in this study using field survey data and detailed simulation models. The energy impacts of both individual maintenance issue and combined scenarios for an office building with central VAV systems and central plant were evaluated by EnergyPlus simulations using three approaches: 1) direct modeling with EnergyPlus, 2) using the energy management system feature of EnergyPlus, and 3) modifying EnergyPlus source code. The results demonstrated the importance of maintenance for HVAC systems on energy performance of buildings. The research is intended to provide a guideline to help practitioners and building operators to gain the knowledge of maintaining HVAC systems in efficient operations, and prioritize HVAC maintenance work plan. The paper also discusses challenges of modeling building maintenance issues using energy simulation programs.
Microclimate acts as a strong filter on species performance in restored and regenerating forests, particularly in seasonally dry tropical forests (SDTF). Yet few studies have measured microclimate patterns across succession in SDTF. Furthermore, although dynamic vegetation models simulate microclimate, evaluation of these simulated variables with field observations has been relatively uncommon. Here, we investigated the seasonal patterns of soil temperature and soil water in naturally regenerated and planted successional vegetation in SDTF in Costa Rica and Puerto Rico, using complementary approaches of intensive field observations and simulation modeling with the Ecosystem Demography model. We found that plots representing later successional stages were wetter on average, but only during the dry season. During the wet season, mean soil water did not differ across vegetation types, but open, early successional vegetation experienced more frequent extreme wet and dry conditions than older forest and plantations. Soil temperature tended to decline with forest structure, and later successional vegetation also experienced less extreme daily temperature fluctuations. Basal area and leaf area index were the best predictors of differences in soil water and temperature across plots. Model simulations were consistent with observations of wet season soil temperature and soil water, but the model failed to reproduce dry season soil moisture dynamics, suggesting that further work is needed to reduce model biases in microclimate variables. Collectively, our results imply that common assumptions about how microclimates influence successional processes in SDTF should be revisited.
Compression molded SMC composed of chopped carbon fiber and resin polymer which balances the mechanical performance and manufacturing cost presents a promising solution for vehicle lightweight strategy. However, the performance of the SMC molded parts highly depends on the compression molding process and local microstructure, which greatly increases the cost for the part level performance testing and elongates the design cycle. ICME (Integrated Computational Material Engineering) approaches are thus necessary tools to reduce the number of experiments required during part design and speed up the deployment of the SMC materials. As the fundamental stage of the ICME workflow, commercial software packages for SMC compression molding exist yet remain not fully validated especially for chopped fiber systems. In this study, SMC plaques are prepared through compression molding process. The corresponding simulation models are built in Autodesk Moldflow with the same part geometry and processing conditions as in the molding tests. The output variables of the compression molding simulations, including press force history and fiber orientation of the part, are compared with experimental data. Influence of the processing conditions to the fiber orientation of the SMC plaque is also discussed. It is found that generally Autodesk Moldflow can achieve a good simulation of the compression molding process for chopped carbon fiber SMC, yet quantitative discrepancies still remain between predicted variables and experimental results.
Dynamic position (DP) control and pipeline dynamics are the two main parts of the deepwater S-lay simulation model. In this study, a fully coupled analysis tool for deepwater S-lay deployment by dynamically positioned vessels is developed. The method integrates the major aspects related to numerical simulation, including coupled pipeline motion and roller contact forces. The roller–pipe interaction is incorporated in the S-lay pipeline model using a contact search method based on a lumped-mass (LM) formulation in global coordinates. A proportional-integration-differentiation (PID) controller and a Kalman filter are applied in the vessel motion equation to calculate the thrust allocation of the DP system in time domain. Numerical simulation results showed that the dynamic effects add a significant contribution to the tension, but have little influence on the maximum pipe stress and strain. The dynamic response of the coupled S-lay and DP pipeline deployment system increases the demand on the tensioner load carrying capability as well as the maximum DP thruster power.
The California building code requires all new or renovated residential dwelling units to have kitchen exhaust ventilation to manage air pollutants and moisture generated during cooking. Current performance requirements are specified as a minimum airflow and maximum sound level. This report presents an analysis to support consideration of adding a capture efficiency requirement to the code. The analysis uses a physics-based simulation model to calculate air pollutant concentrations in homes that result from cooking and the inflow of outdoor air, mediated by loss and removal process including deposition, dwelling unit ventilation, and the use of a range hood with varying levels of capture efficiency. Calculated pollutant concentrations are compared to relevant, health-based guidelines. The analysis considers the highest 1-hour concentration of nitrogen dioxide (NO 2 ), which is a product of natural gas combustion and the highest 24-hour concentrations of fine particulate matter (PM 2.5 ) which is emitted in substantial quantities from frying, broiling and grilling among other cooking activities. For NO 2 , the analysis considers cooking of a dinner for 3-4 persons consisting of pasta, meat sauce, a par-boiled vegetable, and baked garlic bread. For PM 2.5 , the analysis considers a day in which breakfast emitted particles at the 80th percentile and lunch and dinner entailed particle emissions at the 50th percentile of cooking emission events reported in the literature. Model simulations were performed to determine the level of range hood capture efficiency that will allow these cooking scenarios to occur in the vast majority (>99%) of new homes being built in California while maintaining pollutant concentrations below the health-based guidelines, if the range hood is used throughout cooking. All homes were assumed to have dwelling unit ventilation at the rate required in the building code. Simulation model input parameters were specified using a Monte Carlo approach to represent a range of housing characteristics, outdoor conditions, and indoor pollutant dynamics. Simulation results suggest that requiring a minimum capture efficiency of at least 70% is needed to avoid unacceptably high NO 2 (1-h average concentration of 100 ppb or higher) and at least 60% to avoid unacceptably high PM 2.5 (24-h average of 25 μg/m³ or higher). These results were driven by multi-family homes, which have a smaller volume of air to dilute any pollutants not captured and removed at the cooking area, resulting in higher concentrations.
Newport News Shipbuilding (NNS) is the sole designer and provider of nuclear powered aircraft carriers and one of only two companies in the United States to build nuclear powered submarines. As part of the upkeep of aircraft carriers, the ships return to NNS once in their lifetime for a complex overhaul and to be refueled. In support of overhaul operations NNS maintains a state of the art Special Nuclear Material (SNM) handling facility. Due to the complex nature of the operations that occur within this facility, during the design and initial operation of the building NNS developed a facility simulation model to provide decision support during the project planning and operational phases. This tool allows users to experiment with process times, process order, equipment utilization, personnel utilization and spatial utilization. By capturing the planned operations, time distributions for operations, equipment sizes and uses and personnel requirements, the tool accurately reflects the planned use of the facility. This realism allows the user to experiment with any aspect of the facility, in a controlled and cost effective space, and determine how changes or potential delays may impact overall facility operations. Thus the model allows for rapid exploration of multiple scenarios to determine likely outcomes, allowing a user to identify risks well ahead of their realization and explore mitigation strategies in a controlled space, to determine the ideal path forward. The tool was successful during the initial operation of the facility in helping to identify and mitigate risks related to the complex operations occurring during SNM handling. The tool is now in use to support planning for the next series of operations that will occur within the facility. The initial operations the model supported occurred during the deactivation of the USS Enterprise, and future operation will focus on the overhaul of Nimitz class aircraft carriers. The NNS planning team is currently using the tool to assess potential risks and challenges that are identified as potentially impacting the schedule and timelines for these overhaul processes. In addition, the NNS development team is working to add new operational steps to the model, capturing work that is occurring near the facility, but which directly impacts the facilities operational abilities. In conjuncture with the engineering planning division, the NNS development team has run over 20 complex scenarios through the tool. The team has provided output from these scenarios to both NNS personnel and government representatives. To date the model has successfully supported the identification of several feasible paths to incorporate new processes, dictated by the work to support a overhaul vs a deactivation. The model also provides a spatial arrangement component that allows users to experiment with different equipment placement within the facility. Due to the fidelity of the model, arranging equipment with the spatial component allows a user to set up the facility in an experimental layout and run the processes inside the facility to determine if the layout will be feasible, or if it would impact operational capabilities. Additionally, the spatial component allows for visual collaboration between stakeholders to ensure all operational personnel are aware of the current and planned layout, and that they do not locate equipment or work stations in locations that would interfere with facility operations. The spatial component, in combination with the simulation component, has resulted in several documented improvements in process. These include: the identification of additional equipment which could be stored outside the facility, without impacting operations, to increase space; confirmation of the ideal placement of a large water tank; and identification of several risks related to planned equipment storage area, allowing the team to develop new plans and avoid realizing the risk. (authors)
This updated simulation model at the EERC is now capable of reproducing (with a global history-matching error of around 7%) not only the continuous pressure response but also the well logging monitoring data such as CO 2 flow distributions at the injection well and the CO 2 breakthrough profile at the observation well. The first arrival of CO 2 at the observation well is not known. The PNL data collected in February 2016 showed clear evidence of CO 2 presence with saturation values as high as 60% at the observation well while a monitoring logging event (a pulsed-neutron decay [PND]) prior to that one, performed on December 4, 2015, showed no sign of CO 2 . The history-matching results indicate that CO 2 appears to have first arrived at the iv observation well around mid-December 2015, after approximately 8 months of injection. At the end of the history-matching process, the simulated CO 2 plume extent appears the largest in Perforation 2 with a diameter of 540 m around the injection well.
Simulation models can greatly improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, then on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.
Brief overview of the highlights of work done on the integration of a surrogate reduced order model into the FEM solver code MOOSE under the eXtremeMAT: Modeling and Simulation project
REVEAL is a software framework for building reduced order models (surrogate models) for high fidelity complex scientific simulations. REVEAL is designed to do reduced order modeling and sensitivity analysis for scientific simulations. REVEAL incorporates a range of sampling and regression methods. It provides complete user environment and is adaptable to new simulators, runs jobs on any computing platform of choice, automatically post processes simulation results and provides a range of data analysis tools. The software is generic and can easily be extended to incorporate new methods, simulators.
In developing countries, agriculture generally represents a large fraction of GHG emissions reported in National Inventories, and emissions are typically estimated using Tier 1 IPCC guidelines. However, field data and locally adapted simulation models can improve the accuracy of IPCC estimations. In this report we aimed to quantify anthropogenic N2O emissions from croplands of Argentina through field measurements, model simulations and IPCC guidelines. Here we measured N 2 O emissions and their controlling factors in 62 plots of the Pampas Region with corn, soybean and wheat/soybean crops and in unmanaged grasslands. We accounted for gross emissions from crops and background emissions from unmanaged grasslands to calculate net anthropogenic emissions from crops as the difference between them. We calibrated and evaluated the DayCent model and then simulated different weather and management scenarios. Finally, we applied IPCC guidelines to estimate anthropogenic N 2 O emissions at the same plots. The DayCent model accurately simulated annual N 2 O emission for all crops as compared to measured data (RMSE = 1.4 g N ha -1 day -1 ). Measured and simulated emissions in soybean crops were higher than in corn and wheat/soybean crops. Gross N 2 O emissions ranged from 1.4 to 5.1 kg N ha -1 yr -1 for current environmental (soil and weather) and management (crops and fertilizer doses) conditions. Background emissions ranged between 1.1 and 1.3 kg N ha -1 yr -1 , and therefore net anthropogenic emissions ranged from 0.3 to 4.0 kg N ha-1 yr -1 . IPCC Tier 1 emission factors underestimated N2O releases from soybean, that were on average 4.87 times greater when estimated with DayCent and observations (0.53 vs 2.47 and 2.69 kg N ha -1 yr -1 , respectively). On the contrary, IPCC estimates for corn and wheat/soybean crops were similar to modeled and measured values. Our results suggest that N 2 O emissions from the vast 15 million ha of soybean croplands in the Pampas Region may be substantially underestimated.