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At least 1,603 records · Page 89

Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions

Abstract This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three‐dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R ‐squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically‐informed estimates. The results of this work are used to inform a follow‐on study that tests additional data‐driven approaches in multiple basins within the contiguous United States.

54 ENVIRONMENTAL SCIENCES↗

Initial Comparison of Direct and Legacy Modeling Approaches for Radial Core Expansion Analysis

Radial core expansion in sodium-cooled fast reactors provides an important reactivity feedback effect. As the reactor power increases due to normal start up conditions or accident scenarios, the core and surrounding materials heat up, causing both grid plate expansion and bowing of the assembly ducts. When the core restraint system is designed correctly, the resulting structural deformations introduce negative reactivity which decreases the reactor power. Historically, an indirect procedure has been used to estimate the reactivity feedback due to structural deformation which relies upon perturbation theory and coupling legacy physics codes with limited geometry capabilities. With advancements in modeling and simulation, radial core expansion phenomena can now be modeled directly, providing an assessment of the accuracy of the reactivity feedback coefficients generated by indirect legacy methods. Recently a new capability was added to the PROTEUS-SN unstructured geometry neutron transport solver to analyze deformed meshes quickly and directly. By supplying the deformed mesh in addition to the base configuration input files, PROTEUS-SN automatically processes material adjustments including calculation of region densities to conserve mass, calculation of isotopic densities according to material models (for example, sodium density as a function of temperature), and subsequent re-homogenization of materials. To verify the new capability of directly simulating deformed meshes, PROTEUS-SN was used to compute reactivity feedback for a series of contrived yet representative deformed configurations for the Advanced Burner Test Reactor design. The indirect legacy procedure was also performed to generate reactivity feedback coefficients for the same deformed configurations. Interestingly, the legacy procedure consistently overestimated reactivity feedbacks by 35% compared to direct simulations by PROTEUS-SN. This overestimation indicates that the legacy procedures are in fact not conservative and could be overestimating reactivity feedback effects that are closely tied to reactor safety. We conclude that there is indeed value in performing direct simulation of deformed meshes despite the increased computational expense. PROTEUS-SN is already part of the SHARP multi-physics toolkit where both thermal hydraulics and structural mechanical feedback modeling can be applied but this is the first comparison of direct simulation to legacy techniques for radial core expansion.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗

Energy deposition validation results for the evaluated electron data library in FRENSIE - 25357

The Framework for Research in Nuclear Science and Engineering (FRENSIE) is a collection of packages written in C++ that are designed primarily to aid in methods development. A recent development in FRENSIE is the modeling of single scattering electron interactions using the data in the Evaluated Electron Data Library (EEDL) from Lawrence Livermore National Laboratory (LLNL). Preliminary verification and validation (V and V) results using the well-known Lockwood energy deposition experiment and a comparison with MCNP6.2 were performed using several bivariate grid policies (Unit-base, Correlated, Unit-base Correlated), interpolation schemes (lin-lin, log-log, lin-log), and physics options (Coupled and Decoupled Elastic Scattering). The results show an agreement to within 0.5% between MCNP6.2 and FRENSIE when using the same bivariate grid policy (Correlated) and interpolation scheme (log-log). When compared to the experimental results of the Lockwood experiment, it was found that a Unit-base bivariate grid policy, lin-lin interpolation scheme, and lin-log interpolation scheme did not produce accurate results for the energy deposition in test problems. The log-log Correlated and Unit-base Correlated results showed the greatest agreement with the Lockwood experiment. The total energy deposition matched the experimental data to within 3%. Both the Correlated and Unit-base Correlated results had a tendency to estimate a higher energy deposition near the peaks and a lower energy deposition near the tails. The differences between coupled elastic scattering and decoupled scattering models were shown to be more prominent at higher energies with the results of the coupled elastic scattering being more accurate for the peak and less accurate for the tail of the energy deposition profiles. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

ML-Based Power System Stability Assessment Considering Network Topology Changes: WECC 20,000+ Bus System Case Study

Modern power grids are fast-changing and thus require real-time monitoring and online stability assessment. With the rapid development of machine learning (ML) techniques, using data-driven models to provide fast and accurate estimations of power system stability marginal information, such as frequency nadir for frequency stability and critical clearing time (CCT) for transient stability, have become possible. However, despite the numerous research on ML-based methods for frequency nadir and CCT prediction, there is limited work on the impact of different network topology changes. Furthermore, most previous studies only focused on small or synthetic systems, and there is a lack of research on actual large power system models. In this paper, the above issues are addressed by studying the actual U.S. Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. Massive simulations are conducted in PowerWorld Simulator to study the impact of various topology change scenarios on both frequency stability and transient stability. System operating information is extracted from the success dispatch cases of various network topologies to generate a comprehensive dataset for ML-based models. Two ML methods, random forest (RF) and multilayer perceptron (MLP) neural network, are trained and tested for both frequency nadir prediction and CCT prediction. Test results have proven the models are capable of online stability assessment for large power networks such as the WECC system with sufficient accuracy.

critical clearing time↗

Spacecraft Internal Acoustic Environment Modeling

Acoustic modeling can be used to identify key noise sources, determine/analyze sub-allocated requirements, keep track of the accumulation of minor noise sources, and to predict vehicle noise levels at various stages in vehicle development, first with estimates of noise sources, later with experimental data. In FY09, the physical mockup developed in FY08, with interior geometric shape similar to Orion CM (Crew Module) IML (Interior Mode Line), was used to validate SEA (Statistical Energy Analysis) acoustic model development with realistic ventilation fan sources. The sound power levels of these sources were unknown a priori, as opposed to previous studies that RSS (Reference Sound Source) with known sound power level was used. The modeling results were evaluated based on comparisons to measurements of sound pressure levels over a wide frequency range, including the frequency range where SEA gives good results. Sound intensity measurement was performed over a rectangular-shaped grid system enclosing the ventilation fan source. Sound intensities were measured at the top, front, back, right, and left surfaces of the and system. Sound intensity at the bottom surface was not measured, but sound blocking material was placed tinder the bottom surface to reflect most of the incident sound energy back to the remaining measured surfaces. Integrating measured sound intensities over measured surfaces renders estimated sound power of the source. The reverberation time T6o of the mockup interior had been modified to match reverberation levels of ISS US Lab interior for speech frequency bands, i.e., 0.5k, 1k, 2k, 4 kHz, by attaching appropriately sized Thinsulate sound absorption material to the interior wall of the mockup. Sound absorption of Thinsulate was modeled in three methods: Sabine equation with measured mockup interior reverberation time T60, layup model based on past impedance tube testing, and layup model plus air absorption correction. The evaluation/validation was carried out by acquiring octave band microphone data simultaneously at ten fixed locations throughout the mockup. SPLs (Sound Pressure Levels) predicted by our SEA model match well with measurements for our CM mockup, with a more complicated shape. Additionally in FY09, background NC noise (Noise Criterion) simulation and MRT (Modified Rhyme Test) were developed and performed in the mockup to determine the maximum noise level in CM habitable volume for fair crew voice communications. Numerous demonstrations of simulated noise environment in the mockup and associated SIL (Speech Interference Level) via MRT were performed for various communities, including members from NASA and Orion prime-/sub-contractors. Also, a new HSIR (Human-Systems Integration Requirement) for limiting pre- and post-landing SIL was proposed.

Chu, SShao-sheng R.↗

Emulating climate extreme indices

We use simple pattern scaling and time-shift to emulate changes in a set of climate extreme indices under future scenarios, and evaluate the emulators' accuracy. We propose a metric for the error in emulation in the context of initial condition ensembles, to specifically characterize the role of internal variability in the emulation performance. Our metric separates systematic emulation errors from unavoidable discrepancies between emulated and target values due to internal variability. We compute the metricis at grid-point scale, and we show geographically resolved results, or aggregate them at global scale. We demonstrate the use of our error metric in the emulation of a suite of temperature and precipitation extreme indices. We test and compare simple pattern scaling and time-shift using a range of trajectories spanning targets inspired by the Paris agreement -- warming to 1.5C and 2.0C from the pre-industrial baseline -- and two of the longer-established trajectories, RCP4.5 and RCP8.5. With this suite of scenarios we can test the effects on the performance of the size of the temperature gap between emulation origin and target. We find that for most indices emulation the dominant source of discrepancy is internal variability. For at least one index, however, counting exceedances of a high temperature threshold, significant portions of the globally aggregated discrepancy and its regional pattern originate from the systematic emulation error. This error exceeds internal variability of both the target and the emulated quantities in large coherent regions at low latitudes, and the explanation can be found in the differential behavior of temperature distributions across latitudes. The metric also highlights a fundamental difference in the two methods related to the simulation of internal variability, which is dampened significantly by simple pattern scaling. This aspect is of consequence when using these methods for specific applications, where preserving variability for uncertainty quantification is deemed important. With this study we offer our metric as a diagnostic tool, facilitating the formulation of scientific hypotheses on the reasons for the error. In the meantime, we show that for many impact relevant indices by now traditional emulation techniques can be accurate within the variations unavoidably introduced by internal variability, establishing the fundamental condition for using their emulation in impact modeling.

54 ENVIRONMENTAL SCIENCES↗

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗

Validation and Demonstration of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an integrated energy system (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. The new RAVEN plugin for grid and capacity optimization (HERON) only addresses the limits that affect the production variables and the corresponding rates of variation (explicit constraints). However, other variables are subject to constraints, and the associated limits should be accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response affects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. To obtain a more accurate approximation of the nonlinear dynamic behavior, a parametric version of the dynamic mode decomposition with control (DMDc) algorithm was developed to derive the state-space representation matrices of the IES components at different scheduling parameter. Thanks to this approach, a more accurate approximation of the system response can be obtained, the limits imposed by thermal mechanical implicit constraints can be translated into power dispatch limits, and the feedbacks to HERON power dispatcher can be provided. To assess the developed methodology, a power dispatching test case composed of three power generating and storage units (Balance of Plant, Secondary Energy Source, Thermal Energy Storage) was developed. The power output of each one of the three units was optimized to meet the imposed time-dependent load demand trajectory and to maximize the IES profitability by meeting both the explicit and implicit constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Virtual machine provisioning, code management, and data movement design for the Fermilab HEPCloud Facility

The Fermilab HEPCloud Facility Project has as its goal to extend the current Fermilab facility interface to provide transparent access to disparate resources including commercial and community clouds, grid federations, and HPC centers. This facility enables experiments to perform the full spectrum of computing tasks, including data-intensive simulation and reconstruction. We have evaluated the use of the commercial cloud to provide elasticity to respond to peaks of demand without overprovisioning local resources. Full scale data-intensive workflows have been successfully completed on Amazon Web Services for two High Energy Physics Experiments, CMS and NOνA, at the scale of 58000 simultaneous cores. This paper describes the significant improvements that were made to the virtual machine provisioning system, code caching system, and data movement system to accomplish this work. The virtual image provisioning and contextualization service was extended to multiple AWS regions, and to support experiment-specific data configurations. A prototype Decision Engine was written to determine the optimal availability zone and instance type to run on, minimizing cost and job interruptions. We have deployed a scalable on-demand caching service to deliver code and database information to jobs running on the commercial cloud. It uses the frontiersquid server and CERN VM File System (CVMFS) clients on EC2 instances and utilizes various services provided by AWS to build the infrastructure (stack). We discuss the architecture and load testing benchmarks on the squid servers. We also describe various approaches that were evaluated to transport experimental data to and from the cloud, and the optimal solutions that were used for the bulk of the data transport. Finally, we summarize lessons learned from this scale test, and our future plans to expand and improve the Fermilab HEP Cloud Facility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Application of the CloudSat and NEXRAD Radars Toward Improvements in High Resolution Operational Forecasts

As computational power increases, operational forecast models are performing simulations with higher spatial resolution allowing for the transition from sub-grid scale cloud parameterizations to an explicit forecast of cloud characteristics and precipitation through the use of single- or multi-moment bulk water microphysics schemes. investments in space-borne and terrestrial remote sensing have developed the NASA CloudSat Cloud Profiling Radar and the NOAA National Weather Service NEXRAD system, each providing observations related to the bulk properties of clouds and precipitation through measurements of reflectivity. CloudSat and NEXRAD system radars observed light to moderate snowfall in association with a cold-season, midlatitude cyclone traversing the Central United States in February 2007. These systems are responsible for widespread cloud cover and various types of precipitation, are of economic consequence, and pose a challenge to operational forecasters. This event is simulated with the Weather Research and Forecast (WRF) Model, utilizing the NASA Goddard Cumulus Ensemble microphysics scheme. Comparisons are made between WRF-simulated and observed reflectivity available from the CloudSat and NEXRAD systems. The application of CloudSat reflectivity is made possible through the QuickBeam radiative transfer model, with cautious application applied in light of single scattering characteristics and spherical target assumptions. Significant differences are noted within modeled and observed cloud profiles, based upon simulated reflectivity, and modifications to the single-moment scheme are tested through a supplemental WRF forecast that incorporates a temperature dependent snow crystal size distribution.

Molthan, A. L.↗

Experimental and Computational Aerothermodynamics of a Mars Entry Vehicle

An aerothermodynamic database has been generated through both experimental testing and computational fluid dynamics simulations for a 70 deg sphere-cone configuration based on the NASA Mars Pathfinder entry vehicle. The aerothermodynamics of several related parametric configurations were also investigated. Experimental heat-transfer data were obtained at hypersonic test conditions in both a perfect gas air wind tunnel and in a hypervelocity, high-enthalpy expansion tube in which both air and carbon dioxide were employed as test gases. In these facilities, measurements were made with thin-film temperature-resistance gages on both the entry vehicle models and on the support stings of the models. Computational results for freestream conditions equivalent to those of the test facilities were generated using an axisymmetric/2D laminar Navier-Stokes solver with both perfect-gas and nonequilibrium thermochemical models. Forebody computational and experimental heating distributions agreed to within the experimental uncertainty for both the perfect-gas and high-enthalpy test conditions. In the wake, quantitative differences between experimental and computational heating distributions for the perfect-gas conditions indicated transition of the free shear layer near the reattachment point on the sting. For the high enthalpy cases, agreement to within, or slightly greater than, the experimental uncertainty was achieved in the wake except within the recirculation region, where further grid resolution appeared to be required. Comparisons between the perfect-gas and high-enthalpy results indicated that the wake remained laminar at the high-enthalpy test conditions, for which the Reynolds number was significantly lower than that of the perfect-gas conditions.

Hollis, Brian R.↗

Subtask 1.5 – CO2 Injection Monitoring with an Optimized Scalable, Automated, Semipermanent Seismic Array

The scalable, automated, semipermanent seismic array (SASSA) method is a flexible and relatively cost-effective surface geophysical method for regular time-lapse monitoring of the movement of injected carbon dioxide (CO2) in a reservoir for CO2 enhanced oil recovery (EOR) or geologic CO2 storage operations. It has the advantages of a low-environmental-footprint while monitoring regions of a reservoir from the surface without the need for a regular grid distribution of receivers. Automated data collection is possible. As only time-lapse amplitude changes at the reservoir level due to CO2 movement within the reservoir are monitored, the turnaround time to deliver results from the SASSA method can be short, without the need for long, time-consuming data-processing workflows. As data is collected and processed, incremental information can be provided to the field operator. The Energy & Environmental Research Center (EERC) conducted a SASSA field test from September 2018 to November 2020 in a portion of the Bell Creek Field in Montana, which implemented new CO2 EOR field activities during the study period. Lessons learned from a proof-of-concept study were incorporated to improve the data quality of the SASSA method and demonstrate the viability of the technology. The EERC implemented several enhancements to improve data quality, including 1) an iterative survey design, which allowed placing the receivers in strategic locations where the movement of the CO2 in the reservoir could be tracked with minimum interference by the cultural noise in the study area; 2) the use of powerful seismic sources in the form of surface orbital vibrators, and 3) data acquisition during optimal periods. History-matched reservoir simulation was performed to predict gas saturation and pressure response induced by CO2 injection in the study area. The results were compared with the SASSA-measured responses to CO2 injection as a partial validation technique. A match between the two methods was observed for most of the SASSA points predicted to have intersected a CO2 saturation change. The validated results provide confidence that the SASSA method can be used independently as a CO2 saturation monitoring technique. As data are collected and processed, incremental information can be provided to the field operator. The critical components of the SASSA workflow for a successful application of the method are the following: Iterative survey design with information about CO2 injection activities from the oilfield operator. A detailed CO2 injection plan is the key driver to select the strategic monitoring location of the SASSA sensors. After this information is incorporated in the initial distribution of sources and receivers in the study area, high-resolution satellite images are used to identify ground locations not affected by cultural noise sources, such as power lines, pipelines/flow lines, or roadways. In the next iteration of the survey design, a scouting trip to the study area is needed to understand more details of the noise sources identified in the previous step and the intensity of the field activities that can also generate noise during the monitoring. Integrating the information from the scouting trip into the survey design to select the optimum source and receiver locations is the final step. Noise attenuation. The variety of noise types during seismic monitoring of an oil field is enormous. Tailored noise characterization and processing at a node-by-node level can enhance the performance and sensitivity of the SASSA technique. Future advancements that could improve the efficiency and application of the SASSA technology include: Gaining a better understanding of the noise field produced by the seismic source to aid the choice of receiver location. Surface noise from the source can overwhelm the small signal changes due to CO2 that the SASSA method measures. Improved data-processing workflow to automatically analyze and adapt to dynamic noise conditions associated with industrial settings. This subtask was funded through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE- FE0024233.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

E1 Illumination of a Substation Protection System

Sandia’s CRADA partnership with EPRI for calendar year 2017 helped further the technical basis of understanding on the effects to the electric power distribution system infrastructure (i.e., the grid), from a high altitude electromagnetic pulse (HEMP) event. This joint effort yielded evaluation of multiple SCADA relays to very high transient electric fields that were comparable in frequency content to a HEMP event, in multiple equipment configurations that are representative to how the units are fielded and utilized. Both Sandia and EPRI benefit from the data collected. Sandia directly benefits the LDRD effort to address EMP on electrical system infrastructures. EPRI direct benefits the stakeholders they are representing in the power industry. Stakeholders are power generation and distribution companies and equipment manufactures. The results would be used for product improvement and EMP hardening as well as informing the customer base of potential shortfalls of the product to a HEMP event.To better understand the impacts of HEMP on supervisory control and data acquisition (SCADA) systems in typical use at bulk power facilities, Sandia and EPRI has brought together their unique skills and equipment/facilities. EPRI, representing the stakeholders of the power industry, brings technical experience of how supervisory control and data acquisition (SCADA) systems are typically fielded and utilized in real-world applications. With this, EPRI will provides field hardware relating to the SCADA systems. Sandia National Laboratories (Sandia) provides unique test facilities (Sandia’s Electromagnetic Environment Simulator (EMES) and Large Gigahertz Transverse Electromagnetic (GTEM)) and test equipment capabilities to evaluate the SCADA systems to a simulated HEMP event. Sandia brings hands on experience of conducting susceptibility and vulnerability assessments for critical components and systems to high power incident HEMP illumination.

Molina, Luis↗

An unconditionally stable, time-implicit algorithm for solving the one-dimensional Vlasov–Poisson system

The development of an implicit, unconditionally stable, numerical method for solving the Vlasov–Poisson system in one dimension using a phase-space grid is presented. The algorithm uses the Crank–Nicolson discretization scheme and operator splitting allowing for direct solution of the finite difference equations. This method exactly conserves particle number, enstrophy and momentum. A variant of the algorithm which does not use splitting also exactly conserves energy but requires the use of iterative solvers. This algorithm has no dissipation and thus fine-scale variations can lead to oscillations and the production of negative values of the distribution function. We find that overall, the effects of negative values of the distribution function are relatively benign. We consider a variety of test cases that have been used extensively in the literature where numerical results can be compared with analytical solutions or growth rates. We examine higher-order differencing and construct higher-order temporal updates using standard composition methods.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-Frequency Signature-Based Fault Detection for Future MV Distribution Grids: Preprint

Increased deployment of Distributed Energy Resources (DERs) and microgrids are significantly changing the operation of distribution grid. Increasing penetration of power electronics based DERs also raise several operational problems such as protection coordination issues, voltage raise, recloser synchronization, stability, and frequency control. Legacy systems are designed for unidirectional power flow. Bidirectional power flows, and varying short circuit levels are some of the major challenges in implementing these legacy protection schemes for future power grid with high penetration of power electronics based DERs. Inverter based DER’s can contribute to a maximum of 2 p.u. fault current. Interconnection standards might require even lower fault current contribution. If these protection related challenges are not addressed, it will result in limiting the penetration of DERs in distribution feeders. In this paper, the feasibility of high frequency signature generated by transients is evaluated to identify and locate faults in a distribution system. The paper will discuss the need for an accurate line modeling approach to accurately capture the high frequency signatures. These high frequency signatures are naturally occurring electromagnetic transients for events such as switching events in the network, faults events, etc. This is different than that implemented in transmission systems as the proposed approach utilizes advanced signal processing techniques to retrieve valuable information from the high frequency signatures generated during faults and does not just rely on time delay measurements between reflections of the high frequency signals. In the full paper, information of a modified IEEE distribution feeder test system to accurately model the high frequency signatures will be provided. The distribution lines will be modeled using universal line modeling (ULM) technique in an electromagnetic transients program (EMTP) modeling platform. Different test cases will be simulated and these test cases will include different fault types, multiple fault locations, capacitor bank switching, etc. The feeder system modeled for these simulations will also include power electronics based DERs. Additionally, experimental results demonstrating the high frequency signatures generated due to a transient event in a medium voltage (13.8 kV) distribution line will also be presented in the full paper. Furthermore, the analysis combined with simulation and experimental results in the full paper will help demonstrate the feasibility and efficacy of the proposed protection scheme. The developed protection scheme will not just help solve problems generated by bidirectional current flow, varying short-circuit current capacity, but also help in proliferation of DERs in distribution systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Assessment of the CTF subchannel code for modeling a large-break loss-of-coolant accident reflood transient

With increased industry interest in extending reactor operating cycles, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has been investigating the behavior of high-burnup fuel during design basis accidents such as the large-break loss-of-coolant accident (LBLOCA) with consideration for risk of fuel fragmentation, relocation, and dispersal (FFRD). As part of that activity, the NEAMS subchannel thermal/ hydraulics (T/H) code, CTF, is being used for modeling of LBLOCA and to determine the impact of subchannel resolution on results. Although CTF includes a wide range of models for LBLOCA conditions, the code has not been used for this application while maintained at Oak Ridge National Laboratory (ORNL) until now. Therefore, here, in this work, a preliminary assessment of several of these models was performed using openly available reflood experimental data from the Flooding Experiments in Blocked Arrays (FEBA) tests. One coarse mesh and one fine mesh model were set up in CTF for high and low flooding rate tests performed in the unblocked FEBA facility. A coarse TRACE model was set up to be as consistent as possible with the coarse CTF model to allow for code-to-code benchmarking. The assessment shows a tendency of the codes to over-predict peak cladding temperature (PCT) near the top of the bundle and to quench early. Advanced spacer grid models were shown to improve upper bundle predictions in CTF. The resolved CTF model over-predicted PCT by a larger degree in the center channels in the low-flooding rate test, and it is believed that the radiative heat transfer model, which was not used in this study, may be needed to correct this over-prediction. Finally, this work demonstrates the importance of the droplet model in determining quench time and vapor temperature and PCT prediction, which necessitates a more in-depth validation of these models in the future.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Image Collection Simulation Using High-Resolution Atmospheric Modeling

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

54 ENVIRONMENTAL SCIENCES↗