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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Simulation Framework for Regional Geologic CO 2 Storage Along Arches Province of Midwestern United States

This report presents final technical results for the project Simulation Framework for Regional Geologic CO 2 Storage Infrastructure along Arches Province of the Midwest United States . The Arches Simulation project was a three year effort designed to develop a simulation framework for regional geologic carbon dioxide (CO 2 ) storage infrastructure along the Arches Province through development of a geologic model and advanced reservoir simulations of large-scale CO 2 storage. The project included five major technical tasks: (1) compilation of geologic, hydraulic and injection data on Mount Simon, (2) development of model framework and parameters, (3) preliminary variable density flow simulations, (4) multi-phase model runs of regional storage scenarios, and (5) implications for regional storage feasibility. The Arches Province is an informal region in northeastern Indiana, northern Kentucky, western Ohio, and southern Michigan where sedimentary rock formations form broad arch and platform structures. In the province, the Mount Simon sandstone is an appealing deep saline formation for CO 2 storage because of the intersection of reservoir thickness and permeability. Many CO 2 sources are located in proximity to the Arches Province, and the area is adjacent to coal fired power plants along the Ohio River Valley corridor. Geophysical well logs, rock samples, drilling logs, and geotechnical tests were evaluated for a 500,000 km2 study area centered on the Arches Province. Hydraulic parameters and historical operational information was also compiled from Mount Simon wastewater injection wells in the region. This information was integrated into a geocellular model that depicts the parameters and conditions in a numerical array. The geologic and hydraulic data were integrated into a three-dimensional grid of porosity and permeability, which are key parameters regarding fluid flow and pressure buildup due to CO 2 injection. Permeability data were corrected in locations where reservoir tests have been performed in Mount Simon injection wells. The geocellular model was used to develop a series of numerical simulations designed to support CO 2 storage applications in the Arches Province. Variable density fluid flow simulations were initially run to evaluate model sensitivity to input parameters. Two dimensional, multiple-phase simulations were completed to evaluate issues related to arranging injection fields in the study area. A basin-scale, multiple-phase model was developed to evaluate large scale injection effects across the region. Finally, local scale simulations were also completed with more detailed depiction of the Eau Claire formation to investigate to the potential for upward migration of CO 2 . Overall, the technical work on the project concluded that injection large-scale injection may be achieved with proper field design, operation, siting, and monitoring. Records from Mount Simon injection wells were compiled, documenting more than 20 billion gallons of injection into the Mount Simon formation in the Arches Province over the past 40 years, equivalent to approximately 60 million metric tons CO 2 . The multi-state team effort was useful in delineating the geographic variability in the Mount Simon reservoir properties. Simulations better defined potential well fields, well field arrangement, CO 2 pipeline distribution system, and operational parameters for large-scale injection in the Arches Province. Multiphase scoping level simulations suggest that injection fields with arrays of 9 to 50+ wells may be used to accommodate large injection volumes. Individual wells may need to be separated by 3 to 10 km. Injection fields may require spacing of 25 to 40 km to limit pressure and saturation front interference. Basin-scale multiple-phase simulations in STOMP reflect variability in the Mount Simon. While simulations suggest a total injection rate of 100 million metric tons per year (approximately to a 40% reduction of CO 2 emissions from large point sources across the Arches Province) may be feasible, some areas are more suitable due to favorable geology. Sustainable injection rates were higher in areas where there was higher thickness and reservoir permeability. Distribution of injection across well fields is an effective method to reduce pressure and CO 2 saturation front interference.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects

Abstract. A previous study on the use of nudging in E3SM Atmosphere Model version 1 (EAMv1) had an unresolved issue; i.e., a simulation nudged to EAMv1's own meteorology showed non-negligible deviations from the free-running baseline simulation over some of the subtropical marine stratocumulus and trade cumulus regions. Here, we demonstrate that the deviations can be substantially reduced by (1) changing where the nudging tendency is calculated in the time integration loop of a nudged EAM simulation so as to improve consistency with the free-running baseline and (2) increasing the frequency of the constraining data so as to better capture strong sub-diurnal variations. The fact that modification (2) improves the climate representativeness of the nudged simulations has motivated us to investigate whether the use of newer reanalysis products with higher data frequency can help improve nudged hindcast simulations by better capturing the observed weather events. To answer this question, we present simulations conducted at EAMv1's standard horizontal resolution (approximately 1∘) with nudging towards 6-hourly ERA-Interim reanalysis or 6-hourly, 3-hourly, or hourly ERA5 reanalysis. These simulations are evaluated against the climatology of free-running EAMv1 simulations as well as reanalyses, satellite retrievals, and in situ measurements from the Atmospheric Radiation Measurement user facility. For the 1∘ EAMv1 simulations, we recommend using the relocated nudging tendency calculation and the ERA5 reanalysis at 3-hourly or higher frequency. Simulations used for estimating the anthropogenic aerosol effects often use nudging to help discern signal from noise. The sensitivity of such estimates to the configuration of nudging is investigated in EAMv1, again using the standard 1∘ horizontal resolution. We find that, when estimating the global mean effects, the frequency of constraining data has relatively small impacts, while the choice of nudged variables can change the results substantially. The nudging of air temperature (in addition to horizontal winds) has two non-negligible effects. First, when the constraining data come from reanalysis, the nudging-induced mean bias correction can cause significant changes in the simulated clouds and hence substantially different estimates of the aerosol effects. The impact of the mean bias correction on ice cloud formation has been noted in previous studies and is also seen in EAMv1. For applications like ours, where the preferred configurations of nudging are those capable of providing results consistent with the multi-year free-running simulations, the consequence of the mean bias correction is undesirable. The second important impact of temperature nudging is a significant suppression of adjustments to aerosol forcing, which also causes changes in the estimated aerosol effects. This effect can be seen in simulations nudged to either reanalysis or EAM's own meteorology. These results suggest that nudging horizontal winds but not temperature is a better choice for estimating the anthropogenic aerosol effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Simulated meteorological impacts of offshore wind turbines and sensitivity to the amount of added turbulence kinetic energy

Offshore wind energy projects are currently in development off the east coast of the United States and may influence the local meteorology of the region. Wind power production and other commercial uses in this area are related to atmospheric conditions, and so it is important to understand how future wind plants may change the local meteorology. In the absence of measurements of potential wind plant impacts on meteorology, simulations offer the next-best possible insight into wake effects on boundary layer height, temperature, fluxes, and wind speeds. However, simulation tools that capture these effects offer multiple options for representing the amount of turbine-added turbulence that may impact assessments of micrometeorological effects. To explore this sensitivity, we compare 1 year of simulations from the Weather Research and Forecasting (WRF) model with and without wind plants incorporated, focusing on the lease area south of Massachusetts and Rhode Island. The simulations with wind plants are repeated to include both the maximum and minimum amounts of added turbulence to provide bounds on the potential impacts. We assess changes in wind speeds, 2 m temperature, surface heat flux, turbulence kinetic energy (TKE), and boundary layer height during different stability classifications and ambient wind speeds over the entire year and compare results for the degree of added turbulence in the wind plant simulations. Because the wake behavior may be a function of boundary layer stability, in this paper, we also present a machine learning algorithm to quantify the area and distance of the wake generated by the wind plant. This analysis enables us to identify the relationship between wake extent and boundary layer height. We find that hub-height wind speed is reduced within and downwind of the wind plant, with the strongest impacts occurring during stable conditions and faster wind speeds in region 3 of the turbine power curve, although impacts lessen as wind speeds increase past 15 m s−1. In contrast, wind speeds near the surface decrease when no turbine-added turbulence is included but can increase for stably stratified conditions when 100 % of possible TKE is included in the simulations. TKE increases at hub height in the simulations with added TKE for all stability classes, suggesting that atmospheric stability does not immediately modify the TKE generated by turbines. Negligible changes in hub-height TKE manifest in the simulations without the added TKE. At the surface, TKE increases in the simulations with maximum added turbulence only for unstable conditions. In the no-added-turbulence simulations, surface TKE decreases slightly in neutral and unstable simulations. Differences in 2 m temperatures and surface heat fluxes are small but vary considerably with atmospheric stability and the amount of added TKE. Boundary layer heights increase within the wind plant when turbine-added turbulence is included and decrease slightly downwind during stable conditions. In contrast, with no added turbulence, the boundary layer height is in general reduced in stable conditions with wind speeds less than 15 m s −1 and slightly increased in neutral conditions. Finally, shallower upwind boundary layer heights tend to correlate with larger wake areas and distances, though other factors likely also play a role in determining the extent of the wind plant wake. These simulation-based results provide a bound for micrometeorological impacts of wind plant wakes: simulations that couple the atmosphere to the ocean may reduce these impacts, and we await observational verification.

17 WIND ENERGY↗
DOE OSTI2013

Adaptive Sampling Algorithms for Probabilistic Risk Assessment of Nuclear Simulations

Nuclear simulations are often computationally expensive, time-consuming, and high-dimensional with respect to the number of input parameters. Thus exploring the space of all possible simulation outcomes is infeasible using finite computing resources. During simulation-based probabilistic risk analysis, it is important to discover the relationship between a potentially large number of input parameters and the output of a simulation using as few simulation trials as possible. This is a typical context for performing adaptive sampling where a few observations are obtained from the simulation, a surrogate model is built to represent the simulation space, and new samples are selected based on the model constructed. The surrogate model is then updated based on the simulation results of the sampled points. In this way, we attempt to gain the most information possible with a small number of carefully selected sampled points, limiting the number of expensive trials needed to understand features of the simulation space. We analyze the specific use case of identifying the limit surface, i.e., the boundaries in the simulation space between system failure and system success. In this study, we explore several techniques for adaptively sampling the parameter space in order to reconstruct the limit surface. We focus on several adaptive sampling schemes. First, we seek to learn a global model of the entire simulation space using prediction models or neighborhood graphs and extract the limit surface as an iso-surface of the global model. Second, we estimate the limit surface by sampling in the neighborhood of the current estimate based on topological segmentations obtained locally. Our techniques draw inspirations from topological structure known as the Morse-Smale complex. We highlight the advantages and disadvantages of using a global prediction model versus local topological view of the simulation space, comparing several different strategies for adaptive sampling in both contexts. One of the most interesting models we propose attempt to marry the two by obtaining a coarse global representation using prediction models, and a detailed local representation based on topology. Our methods are validated on several analytical test functions as well as a small nuclear simulation dataset modeled after a simplified Pressurized Water Reactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Voronoi Meshing to Accurately Capture Geological Structure in Subsurface Simulations

Mesh generation lies at the interface of geological modeling and reservoir simulation. Highly skewed or very small grid cells may be necessary to accurately capture the geometry of geological features, but the resulting poorly scaled or small grid cells can have a substantial negative impact on simulator accuracy and speed. One way to minimize numerical errors caused by gridding complex structures is to simulate on high-quality Voronoi meshes, which reduce grid orientation effects in fluid flow. This work presents a complete methodology to create Voronoi simulation grids, model fluid flow in complex geological systems, and visualize the results. A recently developed Voronoi meshing method that can automatically generate provably good unstructured meshes that conform to input surfaces creating closed volumes is used. Initially an analytical benchmark simulation is presented to validate the quality of the meshes and simulation results and demonstrate the superiority of simulation results using Voronoi meshes over flexed-hexahedral meshes on a domain with internal features. Next, meshes are created for test structures representing four of the most common geological features in the subsurface: layering, pinch-out, an interior lens that tapers to zero thickness on all sides and a fault with offset. Two benchmark flow simulations are run for each test structure. Finally, a realistic geological example for CO 2 injection into an anticline is simulated. Three realizations of the Voronoi mesh at the same resolution are generated for the simulations. Each mesh is highly refined near the injection wells and coarse in areas of less interest. These three meshes are used to model the CO 2 plume in the subsurface as it migrates to the top of the structure and then fills downward. Simulations on the meshes with randomly generated elements inside the input volumes each give slightly different fingering patterns for the viscous-unstable buoyant gas flow. The results presented in this work show a promising step towards utilizing fully automated Voronoi meshing for subsurface flow simulations in complex geology.

58 GEOSCIENCES↗
DOE OSTI2012

Application of new simulation algorithms for modeling rf diagnostics of electron clouds

Traveling wave rf diagnostics of electron cloud build-up show promise as a non-destructive technique for measuring plasma density and the efficacy of mitigation techniques. However, it is very difficult to derive an absolute measure of plasma density from experimental measurements for a variety of technical reasons. Detailed numerical simulations are vital in order to understand experimental data, and have successfully modeled build-up. Such simulations are limited in their ability to reproduce experimental data due to the large separation of scales inherent to the problem. Namely, one must resolve both rf frequencies in the GHz range, as well as the plasma modulation frequency of tens of MHz, while running for very long simulations times, on the order of microseconds. The application of new numerical simulation techniques allow us to bridge the simulation scales in this problem and produce spectra that can be directly compared to experiments. The first method is to use a plasma dielectric model to measure plasma-induced phase shifts in the rf wave. The dielectric is modulated at a low frequency, simulating the effects of multiple bunch crossings. This allows simulations to be performed without kinetic particles representing the plasma, which both speeds up the simulations as well as reduces numerical noise from interpolation of particle charge and currents onto the computational grid. Secondly we utilize a port boundary condition model to simultaneously absorb rf at the simulation boundaries, and to launch the rf into the simulation. This method improves the accuracy of simulations by restricting rf frequencies better than adding an external (finite) current source to drive rf, and absorbing layers at the boundaries. We also explore the effects of non-uniform plasma densities on the simulated spectra.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

A gradient based method for modeling baryons and matter in halos of fast simulations

Fast N-body PM simulations with a small number of time steps such as FastPM or COLA have been remarkably successful in modeling the galaxy statistics, but their lack of small scale force resolution and long time steps cannot give accurate halo matter profiles or matter power spectrum. High resolution N-body simulations can improve on this, but lack baryonic effects, which can only be properly included in hydro simulations. Here we present a scheme to calibrate the fast simulations to mimic the precision of the hydrodynamic simulations or high resolution N-body simulations. The scheme is based on a gradient descent of either effective gravitational potential, which mimics the short range force, or of effective enthalpy, which mimics gas hydrodynamics and feedback. The scheme is fast and differentiable, and can be incorporated as a post-processing step into any simulation. It gives very good results for the matter power spectrum for several of the baryonic feedback and dark matter simulations, and also gives improved dark matter halo profiles. The scheme is even able to find the large subhalos, and increase the correlation coefficient between the fast simulations and the high resolution N-body or hydro simulations. It can also be used to add baryonic effects to the high resolution N-body simulations. While the method has free parameters that can be calibrated on various simulations, they can also be viewed as astrophysical nuisance parameters describing baryonic effects that can be marginalized over during the data analysis. In this view these parameters can be viewed as an efficient parametrization of baryonic effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SU-D-9A-03: STAMP: Simulator for Texture Analysis in MRI/PET

Purpose: To develop a convenient simulation platform to facilitate PET/MR image analysis with the prospect of gaining a better understanding of the influence of acquisition parameters on PET/MRI textural features. The simulation platform is demonstrated by showing textural variations of a representative case study using different image acquisition parameters. Methods: The simulation platform is composed of MRI simulators JEMRIS and SIMRI to achieve simulations of customized MRI sequences on sample tumor models. The PET simulator GATE is used to get 2D and 3D Monte Carlo acquisitions of voxelized PET sources using a phantom geometry and a customized scanner architecture. The platform incorporates a series of graphical user interfaces written in Matlab. Two GUIs are used to facilitate communication with the simulation executables installed on a computer cluster. A third GUI is used to collect and display the clinical and simulated images, as well as fused PET/MRI images, and perform computation of textural features.To illustrate the capabilities of this platform, one FDG-PET and T1-weighted (T1w) digitized tumor models were generated from clinical images of a soft-tissue sarcoma patient. Numerically simulated MR images were produced using 3 different echo times (TE) and 5 different repetition times (TR). PET 2D images were simulated using an OSEM algorithm with 1 to 32 iterations and a post-reconstruction Gaussian filter of 0, 2, 4 or 6 mm width. Results: STAMP was successfully used to produce numerically simulated FDG-PET and MRI images, and to calculate their corresponding textures. Three typical textures (GLCM-Contrast, GLSZM-ZSV and NGTDM-Coarseness) were found to vary by a range of 45% on average compared to reference scanning conditions in the case of FDG-PET, and by a range of 40% in the case of T1w MRI. Conclusion: We have successfully developed a Matlab-based simulation platform to facilitate PET/MRI texture image analysis for outcome prediction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Wide-range fission chambers signal simulator - 373

Fission chambers (FC) signal simulators are a useful means to test neutron flux instrumentation channels of the reactors control and protection systems (CPS). Well-known signal simulators do not provide a secondary equipment testing in all modes of measurement. A wide range simulator that simulates a full range of FC signal changes (pulse, fluctuation, current) was designed. The simulator takes into account the statistical nature of neutrons detection in the FC, including the shape of the pulse and the spectrum of the pulse amplitude distribution. The simulator uses the principle of mathematical simulation of the fission chambers signal with realtime calculations using the FPGA. The wide-range simulator reproduces a FC signal in the range of ten orders without switching ranges or playback modes while ensuring very good linearity. It allows to generate both static and dynamic test signals such as: stair-step, linearly and exponential varying signals, exponential varying signals with a linearly changing period or a signal change simulating the response of the nuclear reactor power to a given reactivity response. Continuity of reproduced signals and the ability to playback dynamic effects makes it possible the simulator using to check the algorithms of cross-linking of measuring paths, reactivity and period measuring tools and to monitor the operation of interlocking and alarm CPS functions. This article discusses the simulator's software and hardware, its features and specifications, user interface and example of the simulator using to check the neutron flux monitoring channels. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

An ultrahigh-resolution E3SM land model simulation framework and its first application to the Seward Peninsula in Alaska

The availability of supercomputers and state-of-science datasets has made it possible to conduct large-scale land simulations at an ultrahigh-resolution. This study reported a computational framework for land surface simulation using the E3SM land model (ELM) at an unprecedented resolution (1 km x 1 km gridcell). The ultrahigh-resolution ELM (uELM) simulation framework includes three parts: (1) high-resolution atmospheric forcing and surface properties dataset generation, (2) massive gridcell-based simulation, and (3) large-scale simulation results analysis. Additionally, we implemented the uELM simulation framework and completed the first 1 km x 1 km terrestrial ecosystem simulation (from 1850 to 2014) over the Seward Peninsula in Alaska (78,000 km 2 ). The experiment contained two phases: a spin-up simulation and a transient simulation, and required five weeks of calculations using 320 cores in a 44-node Linux HPC computer. It created approximately 1.3 TB of data from the transient simulation alone (1850 - present). We selected sample results (monthly and daily simulation outputs) to illustrate the temporal and spatial variations of several variables in high-latitude Arctic ecosystems’ water, energy, and carbon cycles. At last, we summarized the lessons learned and proposed new developments for full-scale uELM simulations over the entire North American continent (approximately 22,000,000 km 2 ).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Direct Dynamics Simulation of Dissociation of the [CH3--I--OH]- Ion-Molecule Complex

Direct dynamics simulations were used to study dissociation of the [CH3--I--OH]- complex ion, which was observed in a previous study of the OH- + CH3I gas phase reaction (J. Phys. Chem. A 2013, 117, 7162). Restricted B97-1 simulations were performed to study dissociation at 65, 75 and 100 kcal/mol and the [CH3--I--OH]- ion dissociated exponentially, in accord with RRKM theory. For these energies the major dissociation products are CH3I + OH-, CH2I- + H2O, and CH3OH + I-. Unrestricted B97-1 and restricted and unrestricted CAM-B3LYP simulations were also performed at 100 kcal/mol to compare with the restricted B97-1 results. The {CH3I + OH-}:{CH2I- + H2O}:{CH3OH + I-} product ratio is 0.72 : 0.15 : 0.13, 0.81 : 0.05 : 0.14, 0.71 : 0.19 : 0.10 , and 0.83 : 0.13 : 0.04 for the restricted B97-1, unrestricted B97-1, restricted CAM-B3LYP, and unrestricted CAM-B3LYP simulations, respectively. Other product channels found are CH2 + I- + H2O, CH2 + I-(H2O), CH4 + IO-, CH3 - + IOH, and CH3 + IOH-. The CH3 - + IOH singlet products are only given by the restricted B97-1 simulation and the lower energy CH3 + IOH- doublet products are only formed by the unrestricted B97-1 simulation. Also studied were the direct and indirect atomic-level mechanisms for forming CH3I + OH-, CH2I- + H2O, and CH3OH + I-. The majority of CH3I + OH- were formed through a direct mechanism. For both CH2I- + H2O and CH3OH + I-, the direct mechanism is overall more important than the indirect mechanisms, with the round-about like mechanism the most important indirect mechanism at high excitation energies. Mechanism comparisons between the B97-1 and CAM-B3LYP simulations showed that formation of the CH3OH---I- complex is favored for the B97-1 simulations, while formation of the HO----HCH2I complex is favored for the CAM-B3LYP simulations. The unrestricted simulations give a higher percentage of indirect mechanisms than the restricted simulations. The possible role of the self-interaction error in the simulations is also discussed. The work presented here gives a detailed picture of the [CH3--I--OH]- dissociation dynamics, and is very important for unraveling the role of [CH3--I--OH]- in the dynamics of the OH-(H2O)n=1,2 + CH3I reactions.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2012

Parameter Sweep and Optimization of Loosely Coupled Simulations Using the DAKOTA Toolkit

The increasing availability of large scale computing capabilities has accelerated the development of high-fidelity coupled simulations. Such simulations typically involve the integration of models that implement various aspects of the complex phenomena under investigation. Coupled simulations are playing an integral role in fields such as climate modeling, earth systems modeling, rocket simulations, computational chemistry, fusion research, and many other computational fields. Model coupling provides scientists with systematic ways to virtually explore the physical, mathematical, and computational aspects of the problem. Such exploration is rarely done using a single execution of a simulation, but rather by aggregating the results from many simulation runs that, together, serve to bring to light novel knowledge about the system under investigation. Furthermore, it is often the case (particularly in engineering disciplines) that the study of the underlying system takes the form of an optimization regime, where the control parameter space is explored to optimize an objective functions that captures system realizability, cost, performance, or a combination thereof. Novel and flexible frameworks that facilitate the integration of the disparate models into a holistic simulation are used to perform this research, while making efficient use of the available computational resources. In this paper, we describe the integration of the DAKOTA optimization and parameter sweep toolkit with the Integrated Plasma Simulator (IPS), a component-based framework for loosely coupled simulations. The integration allows DAKOTA to exploit the internal task and resource management of the IPS to dynamically instantiate simulation instances within a single IPS instance, allowing for greater control over the trade-off between efficiency of resource utilization and time to completion. We present a case study showing the use of the combined DAKOTA-IPS system to aid in the design of a lithium ion battery (LIB) cell, by studying a coupled system involving the electrochemistry and ion transport at the lower length scales and thermal energy transport at the device scales. The DAKOTA-IPS system provides a flexible tool for use in optimization and parameter sweep studies involving loosely coupled simulations that is suitable for use in situations where changes to the constituent components in the coupled simulation are impractical due to intellectual property or code heritage issues.

IPS CAEBAT Coupled Battery Simulations↗
DOE OSTI2012

Risk Reduction and Training using Simulation Based Tools - 12180

Process Modeling and Simulation (M and S) has been used for many years in manufacturing and similar domains, as part of an industrial engineer's tool box. Traditionally, however, this technique has been employed in small, isolated projects where models were created from scratch, often making it time and cost prohibitive. Newport News Shipbuilding (NNS) has recognized the value of this predictive technique and what it offers in terms of risk reduction, cost avoidance and on-schedule performance of highly complex work. To facilitate implementation, NNS has been maturing a process and the software to rapidly deploy and reuse M and S based decision support tools in a variety of environments. Some examples of successful applications by NNS of this technique in the nuclear domain are a reactor refueling simulation based tool, a fuel handling facility simulation based tool and a tool for dynamic radiation exposure tracking. The next generation of M and S applications include expanding simulation based tools into immersive and interactive training. The applications discussed here take a tool box approach to creating simulation based decision support tools for maximum utility and return on investment. This approach involves creating a collection of simulation tools that can be used individually or integrated together for a larger application. The refueling simulation integrates with the fuel handling facility simulation to understand every aspect and dependency of the fuel handling evolutions. This approach translates nicely to other complex domains where real system experimentation is not feasible, such as nuclear fuel lifecycle and waste management. Similar concepts can also be applied to different types of simulation techniques. For example, a process simulation of liquid waste operations may be useful to streamline and plan operations, while a chemical model of the liquid waste composition is an important tool for making decisions with respect to waste disposition. Integrating these tools into a larger virtual system provides a tool for making larger strategic decisions. The key to integrating and creating these virtual environments is the software and the process used to build them. Although important steps in the direction of using simulation based tools for nuclear domain, the applications described here represent only a small cross section of possible benefits. The next generation of applications will, likely, focus on situational awareness and adaptive planning. Situational awareness refers to the ability to visualize in real time the state of operations. Some useful tools in this area are Geographic Information Systems (GIS), which help monitor and analyze geographically referenced information. Combined with such situational awareness capability, simulation tools can serve as the platform for adaptive planning tools. These are the tools that allow the decision maker to react to the changing environment in real time by synthesizing massive amounts of data into easily understood information. For the nuclear domains, this may mean creation of Virtual Nuclear Systems, from Virtual Waste Processing Plants to Virtual Nuclear Reactors. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Parallel Simulation of Quantum Networks with Distributed Quantum State Management

Quantum network simulators offer the opportunity to cost-efficiently investigate potential avenues for building networks that scale with the number of users, communication distance, and application demands by simulating alternative hardware designs and control protocols. Several quantum network simulators have been recently developed with these goals in mind. As the size of the simulated networks increases, however, sequential execution becomes time-consuming. Parallel execution presents a suitable method for scalable simulations of large-scale quantum networks, but the unique attributes of quantum information create unexpected challenges. In this work, we identify requirements for parallel simulation of quantum networks and develop the first parallel discrete-event quantum network simulator by modifying the existing serial simulator SeQUeNCe. Our contributions include the design and development of a quantum state manager (QSM) that maintains shared quantum information distributed across multiple processes. We also optimize our parallel code by minimizing the overhead of the QSM and decreasing the amount of synchronization needed among processes. Using these techniques, we observe a speedup of 2 to 25 times when simulating a 1,024-node linear network topology using 2 to 128 processes. We also observe an efficiency greater than 0.5 for up to 32 processes in a linear network topology of the same size and with the same workload. We repeat this evaluation with a randomized workload on a caveman network. We also introduce several methods for partitioning networks by mapping them to different parallel simulation processes. We have released the parallel SeQUeNCe simulator as an open source tool alongside the existing sequential version.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

ASPIRES: Airport Shuttle Planning and Improved Routing Event-driven Simulation

Most of the existing traffic simulation packages require significant calibration work to be able to reflect reality. To evaluate special operations including emerging technologies, a microscopic simulation that tracks detailed interactions of all the elements of the traffic systems is usually needed. This type of simulation is usually computationally demanding. This work developed an Airport Shuttle Planning and Improved Routing Event-driven Simulation (ASPIRES) package to simulate and evaluate current, potential, and future airport shuttle operations. Here, the simulation was driven by data and thus did not require much calibration effort. The discrete-event simulation nature of ASPIRES makes the simulation computationally efficient. Simulating 1 day of shuttle operations takes less than 2s. The study site of this work is the Dallas/Fort Worth International Airport in the U.S. The shuttle service that connects the five terminals of the airport and the rental car center was studied. Travel times, dwell times, and passenger arrivals were simulated using empirical distributions derived mainly from real data to capture the stochastic nature of the rental car center shuttle bus operations. Data on bus miles traveled, bus energy consumption, passenger wait times, and passengers left behind at stops were collected to study the trade-off between energy use and passenger experience. Electric bus and on-demand bus operations were also included. The simulation outputs can show passengers statistics at terminals, shuttles statistics, and charging station statistics. ASPIRES cannot be used to model a generic traffic system but is well-suited for fleet systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2012

Taming Wild Horses: The Need for Virtual Time-based Scheduling of VMs in Network Simulations

The next generation of scalable network simulators employ virtual machines (VMs) to act as high-fidelity models of traffic producer/consumer nodes in simulated networks. However, network simulations could be inaccurate if VMs are not scheduled according to virtual time, especially when many VMs are hosted per simulator core in a multi-core simulator environment. Since VMs are by default free-running, on the outset, it is not clear if, and to what extent, their untamed execution affects the results in simulated scenarios. Here, we provide the first quantitative basis for establishing the need for generalized virtual time scheduling of VMs in network simulators, based on an actual prototyped implementations. To exercise breadth, our system is tested with multiple disparate applications: (a) a set of message passing parallel programs, (b) a computer worm propagation phenomenon, and (c) a mobile ad-hoc wireless network simulation. We define and use error metrics and benchmarks in scaled tests to empirically report the poor match of traditional, fairness-based VM scheduling to VM-based network simulation, and also clearly show the better performance of our simulation-specific scheduler, with up to 64 VMs hosted on a 12-core simulator node.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Performance evaluation of an agent-based occupancy simulation model

Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types were first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Assessment of a Detailed Biomass Pyrolysis Kinetic Scheme in Multiscale Simulations of a Single-Particle Pyrolyzer and a Pilot-Scale Entrained Flow Pyrolyzer

A detailed biomass pyrolysis kinetic scheme was assessed in the multiscale simulations of a single-particle pyrolyzer with slow pyrolysis and a pilot-scale entrained flow pyrolyzer with fast pyrolysis. The detailed kinetic scheme of biomass pyrolysis developed by the CRECK group consists of 32 reactions and 58 species. A multiscale simulation model was developed, where the CRECK kinetics was employed to simulate biomass pyrolysis reactions, a one-dimensional particle model was utilized to simulate the intraparticle transport phenomena, and the particle-in-cell (PIC) model was employed to simulate the hydrodynamics. The multiscale model was first applied to simulate a single-particle pyrolysis experiment. The simulation with nonisothermal particles matched the experimental data better than the simulation with isothermal particles. Then the multiscale model was applied to simulate the pilot-scale entrained flow pyrolyzer. In this case, the simulation with isothermal particles matched the experimental data better than the simulation with nonisothermal particles. The reason for this difference might be that the kinetics itself already partially included the intraparticle transport effect as it was fitted using both TGA data (slow pyrolysis of small size biomass) and fluidized bed data (fast pyrolysis of relatively large size biomass). This study provides some insights into biomass pyrolysis kinetics development and pyrolyzer multiscale simulation for a future study.

09 BIOMASS FUELS↗