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At least 595 records · Page 33

TAS: 89 0227: TAS Recovery Act - Optimization and Control of Electric Power Systems: ARRA

The name SuperOPF is used to refer several projects, problem formulations and soft-ware tools intended to extend, improve and re-define some of the standard methods of optimizing electric power systems. Our work included applying primal-dual interior point methods to standard AC optimal power flow problems of large size, as well as extensions of this problem to include co-optimization of multiple scenarios. The original SuperOPF problem formulation was based on co-optimizing a base scenario along with multiple post-contingency scenarios, where all AC power flow models and constraints are enforced for each, to find optimal energy contracts, endogenously determined locational reserves and appropriate nodal energy prices for a single period optimal power flow problem with uncertainty. This led to example non-linear programming problems on the order of 1 million constraints and half a million variables. The second generation SuperOPF formulation extends this by adding multiple periods and multiple base scenarios per period. It also incorporates additional variables and constraints to model load following reserves, ramping costs, and storage resources. A third generation of the multi-period SuperOPF, adds both integer variables and a receding horizon framework in which the problem type is more challenging (mixed integer), the size is even larger, and it must be solved more frequently, pushing the limits of currently available algorithms and solvers. The consideration of transient stability constraints in optimal power flow (OPF) problems has become increasingly important in modern power systems. Transient stability constrained OPF (TSCOPF) is a nonlinear optimization problem subject to a set of algebraic and differential equations. Solving a TSCOPF problem can be challenging due to (i) the differential-equation constraints in an optimization problem, (ii) the lack of a true analytical expression for transient stability in OPF. To handle the dynamics in TSCOPF, the set of differential equations can be approximated or converted into equivalent algebraic equations before they are included in an OPF formulation. In Chapter 4, a rigorous evaluation of using a predefined and fixed threshold for rotor angles as a mean to determine transient stability of the system is developed. TSCOPF can be modeled as a large-scale nonlinear programming problem including the constraints of differential-algebraic equations (DAE). Solving a TSCOPF problem can be challenging due to (i) the differential-equation constraints in an optimization problem, (ii) the lack of a true analytical expression for transient stability constraint in OPF. Unfortunately, even the current best TSCOPF solvers still suffer from the curse of dimensionality and unacceptable computational time, especially for large-scale power systems with multiple contingencies. In chapter 5, thse issues will be addressed and a new method to incorporate the transient stability constraints will be presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

M3MS-19IN0101201 Modeling Intra-granular Fission Gas Bubble Evolution in Uranium Dioxide during Transients

The SciDAC milestone M3MS-19IN0101201 on Modeling Intra-granular Fission Gas Bubble Evolution in Uranium Dioxide during Transients was completed with the development, testing and implementation in the Bison code of an engineering model for intra-granular fission gas bubble evolution that is applicable to transient conditions. The model extends the previous work on modeling bubble evolution during normal operating conditions to include additional complexity that arises during transient situations, in particular, the so-called intra-granular bubble coarsening. This phenomenon refers to the appearance of a second population of coarsened bubbles with diameters of tens to hundreds of nm, which co-exist with nanometric bubbles present also during normal operating conditions and are responsible for a large portion of transient fuel swelling. The developed model considers growth of bubbles along dislocations, associated with the absorption of vacancies available in the dislocation core region, and favored by pipe diffusion of fission gas atoms. The model also utilizes the formulation for the gas atom resolution rate developed in the present SciDAC project through molecular dynamics simulations by other institutions. The present work therefore demonstrates an operational multiscale approach, based on collaboration within the project. The model is validated to an extensive experimental dataset of ramp tested uranium dioxide fuel samples. Additionally, we present new applications of the base model for bubble evolution during normal operating conditions to Bison engineering simulations of Cr2O3-doped fuel rods irradiated in the Halden reactor. Simulation results in terms of integral fission gas release in the fuel rods are compared to the available experimental data, pointing out significant improvements in the engineering predictions compared to application of the empirical model that was available in Bison before the SciDAC developments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Joint Development of SAS4A Code in Application to Oxide-fueled LFR Severe Accident Analysis

The scope of this project was to pursue specific SAS4A liquid-metal cooled reactor (LMR) safety analysis software extensions to simulate postulated accidents with fuel failures for oxide-fueled Lead-cooled Fast Reactors (LFRs). Since most U.S. LMR experience is on sodium-cooled fast reactor options based on past testing and operation experience with EBR-II and FFTF, the DOE’s legacy fast reactor safety analysis capabilities were focused on metal-fueled pool-type concepts with sodium coolant. In recent years, Westinghouse Electric Company (WEC) has decided to pursue an LFR design as one of their next generation nuclear technology options because of its favorable safety and economics attributes. Oxide fuel is considered among other fuel options due to previous WEC experience with this fuel form. Development of this new technology requires the availability of adequately accurate computational tools, some of which can be adapted from versions of similar software used for analysis of other LMRs. Although Argonne National Laboratory’s (ANL) SAS4A/SASSYS-1 safety analysis software suite (shortened as SAS4A code hereafter for brevity) has the basic capabilities to model LFR system designs, the SAS4A code modules used in the analysis of accidents with fuel/cladding failures lack appropriate models for the unique phenomena that govern as-irradiated oxide-fuel damage mechanisms in lead coolant. Therefore, the objective of this project was to extend the capabilities of SAS4A with mechanistic oxide-fuel failure models in lead coolant for margin to failure assessments, analysis of failure modes, location and timing of failures under different accident scenarios consistent with the whole-plant dynamic response including the reactivity feedback, and assessment of the potential for fuel damage propagation due to potential fission gas jet and fuel-fragment/molten fuel impingement to neighboring fuel pins in an assembly. This report provides mainly a summary of Argonne’s technical contributions in the joint project, but the reports and publications by the Participant team are included as references at the end of the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Validation of energetic particle transport models for time-dependent integrated simulations of burning plasmas (Final ST Report)

The major goal of this project is to deliver a suite of validated energetic particle (EP) modeling tools for time-dependent integrated tokamak simulations (with the code TRANSP) that can be used for modeling plasma discharges featuring a substantial EP content, such as burning plasmas. During FY20, issues were resolved with an energetic particle transport model called TGLF-EP, with improvements made to the TGLF-EP workflow, generation of input files, and interpretation of runs on the NERSC supercomputing cluster. The recipient also gave input on simulations with the code TRANSP to reproduce the reference JET discharge, and assessed the accuracy and uncertainties of the simulated B field, current evolution, thermal plasma profiles, stored energy, etc. Input was also given on interpretation of fast-ion instability calculations and recommendations for modifications to JET afterglow discharge for the upcoming DT campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

RAVEN: a GUI and an Artificial Intelligence Engine in a Dynamic PRA Framework

Increases in computational power and pressure for more accurate simulations and estimations of accident scenario consequences are driving the need for Dynamic Probabilistic Risk Assessment (PRA) [1] of very complex models. While more sophisticated algorithms and computational power address the back end of this challenge, the front end is still handled by engineers that need to extract meaningful information from the large amount of data and build these complex models. Compounding this problem is the difficulty in knowledge transfer and retention, and the increasing speed of software development. The above-described issues would have negatively impacted deployment of the new high fidelity plant simulator RELAP-7 (Reactor Excursion and Leak Analysis Program) at Idaho National Laboratory. Therefore, RAVEN that was initially focused to be the plant controller for RELAP-7 will help mitigate future RELAP-7 software engineering risks. In order to accomplish this task, Reactor Analysis and Virtual Control Environment (RAVEN) has been designed to provide an easy to use Graphical User Interface (GUI) for building plant models and to leverage artificial intelligence algorithms in order to reduce computational time, improve results, and help the user to identify the behavioral pattern of the Nuclear Power Plants (NPPs). In this paper we will present the GUI implementation and its current capability status. We will also introduce the support vector machine algorithms and show our evaluation of their potentiality in increasing the accuracy and reducing the computational costs of PRA analysis. In this evaluation we will refer to preliminary studies performed under the Risk Informed Safety Margins Characterization (RISMC) project of the Light Water Reactors Sustainability (LWRS) campaign [3]. RISMC simulation needs and algorithm testing are currently used as a guidance to prioritize RAVEN developments relevant to PRA.

97 MATHEMATICS AND COMPUTING↗

Beyond Widgets: Validated Systems Energy Savings and Utility Custom Incentive Program Systems Trends

Energy efficiency upgrades to buildings to date through avenues such as utility incentive programs have been largely limited to component-based products (e.g., lamps, RTUs). While some utilities do provide ‘custom’ incentive programs with whole building and system level technical assistance, these programs require deeper levels of analysis, resulting in higher program costs. This results in custom programs being restricted to utilities with greater resources, and are typically applied mainly to large or energy-intensive facilities, leaving much of the market without cost effective access and incentives for these solutions. In addition, with increasingly stringent energy codes, cost effective component-based solutions that achieve significant savings are dwindling. Integrated building systems (e.g., integrated façade, HVAC and/or lighting solutions) can deliver higher savings (Regnier et al. 2017) that translate into large sector-wide savings if deployed at the scale of these programs. However, systems application poses a number of challenges – energy savings assessments are inherently more complex and are not easily suited to the deemed measure model, and implementation of systems can be more disruptive. This paper presents the outcomes of a project to develop validated utility incentive program packages for three specific integrated building systems, in collaboration with ComEd, a consortium of California Public Owned Utilities (CA POUs) (Northern California Power Agency(NCPA) and the Southern California Public Power Authority(SCPPA)), and Xcel Energy (CO, MN). Previous work described the potential for energy savings of these systems at the individual and market level, early test findings for the task-ambient lighting system, and described the work products to develop utility incentive programs (Regnier et al. 2016). This paper presents validated end use energy savings of all three systems showing energy savings of ~20% for automated shading combined with daylight dimming (does not include light fixture retrofit savings); 30-46% for task-ambient lighting systems combined with plug load occupancy controls, depending on technology package and office building size (no daylight dimming impacts); and ~94% in the south-façade daylit zone for workstation specific lighting systems with daylight dimming (including lighting retrofit and task tuning). Using a U.S. Department of Energy (DOE) reference building model (DOE 2018), this translates to whole building savings of 2-5% (large-medium commercial), 12-23% (large-small commercial), and 13-15% (medium-large commercial) for these systems respectively. Early findings from the utilities in deploying these systems through their incentive programs indicate that deployment methods such as direct install programs might be best suited for these integrated systems. Further, early findings from a scoping study across custom utility programs and federal retrofit programs indicate that component level retrofits are still prevalent even in these programs, pointing towards an opportunity for deeper energy savings deployment. High performance retrofit case studies demonstrate that deeper energy savings is possible through integrated approaches. Market stakeholder interviews indicate however that there is generally a low level of awareness of the potential for energy savings of these three integrated systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration

Abstract With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs) for electronic, optoelectronic, and energy storage applications, we present a dataset of predicted electronic structure properties for thousands of MOFs carried out using multiple density functional approximations. Compared to more accurate hybrid functionals, we find that the widely used PBE generalized gradient approximation (GGA) functional severely underpredicts MOF band gaps in a largely systematic manner for semi-conductors and insulators without magnetic character. However, an even larger and less predictable disparity in the band gap prediction is present for MOFs with open-shell 3 d transition metal cations. With regards to partial atomic charges, we find that different density functional approximations predict similar charges overall, although hybrid functionals tend to shift electron density away from the metal centers and onto the ligand environments compared to the GGA point of reference. Much more significant differences in partial atomic charges are observed when comparing different charge partitioning schemes. We conclude by using the dataset of computed MOF properties to train machine-learning models that can rapidly predict MOF band gaps for all four density functional approximations considered in this work, paving the way for future high-throughput screening studies. To encourage exploration and reuse of the theoretical calculations presented in this work, the curated data is made publicly available via an interactive and user-friendly web application on the Materials Project.

36 MATERIALS SCIENCE↗

MELCOR Accident Progression and Source Term Demonstration Calculations for a Heat Pipe Reactor

MELCOR is an integrated thermal hydraulics, accident progression, and source term code for reactor safety analysis that has been developed at Sandia National Laboratories for the United States Nuclear Regulatory Commission (NRC) since the early 1980s. Though MELCOR originated as a light water reactor (LWR) code, development and modernization efforts have expanded its application scope to includ e non-LWR reactor concepts. Current MELCOR development efforts include providing the NRC with the analytical capabilities to support regulatory readiness for licensing non-LWR techno logies under Strategy 2 of the NRC?s near- term Implementation Action Plans. Beginning with the Next Generation Nuclear Project (NGNP), MELCOR has undergone a range of enha ncements to provide analytical capabilities for modeling the spectrum of advanced non-LWR concepts. This report describes the generic plant model developed to demonstrate MELCOR capabilities to perform heat pipe reactor (HPR) safety evaluations. The generic plant mode l is based on a publicly-available Los Alamos National Laboratory (LANL) Megapower design as modified in the Idaho National Laboratory (INL) Design A description. For plant aspects (e.g., reactor building size and leak rate) that are not described in the LANL and INL references , the analysts made assumptions needed to construct a MELCOR full-plant model. The HP R uses high assay, low-enrichment uranium (HALEU) fuel with steel cladding that uses heat pipes to transfer heat to a secondary Brayton air cycle. The core region is surrounded by a stainless-steel shroud, alumina reflector, core barrel and boron carbide neutron shield. The reactor is secured inside a below-grade cavity, with the operating floor located above the cavity. Example calculations are performed to show the plant response and MELCOR capabilities to characterize a range of accident conditions. The accidents selected for evaluation consider a range of degraded and failed modes of operation for key safety functions providing re activity control, the primary and secondary system heat removal, and the effectiveness of th e confinement natural circulation flow into the reactor cavity (i.e., a flow blockage).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DCMIP2016: the splitting supercell test case

Abstract. This paper describes the splitting supercell idealized test case used in the 2016 Dynamical Core Model Intercomparison Project (DCMIP2016). These storms are useful test beds for global atmospheric models because the horizontal scale of convective plumes is O(1 km), emphasizing non-hydrostatic dynamics. The test case simulates a supercell on a reduced-radius sphere with nominal resolutions ranging from 4 to 0.5 km and is based on the work of Klemp et al. (2015). Models are initialized with an atmospheric environment conducive to supercell formation and forced with a small thermal perturbation. A simplified Kessler microphysics scheme is coupled to the dynamical core to represent moist processes. Reference solutions for DCMIP2016 models are presented. Storm evolution is broadly similar between models, although differences in the final solution exist. These differences are hypothesized to result from different numerical discretizations, physics–dynamics coupling, and numerical diffusion. Intramodel solutions generally converge as models approach 0.5 km resolution, although exploratory simulations at 0.25 km imply some dynamical cores require more refinement to fully converge. These results can be used as a reference for future dynamical core evaluation, particularly with the development of non-hydrostatic global models intended to be used in convective-permitting regimes.

Zarzycki, Colin M.↗

The Potosi Reservoir Model 2013

As a part of a larger project co-funded by the United States Department of Energy (US DOE) to evaluate the potential of formations within the Cambro-Ordovician strata above the Mt. Simon as potential targets for carbon sequestration in the Illinois and Michigan Basins, the Illinois Clean Coal Institute (ICCI) requested Schlumberger to evaluate the potential injectivity and carbon dioxide (CO2) plume size of the Cambrian Potosi Formation. The evaluation of this formation was accomplished using wireline data, core data, pressure data, and seismic data from the US DOE-funded Illinois Basin–Decatur Project (IBDP) being conducted by the Midwest Geological Sequestration Consortium in Macon County, Illinois. In 2010, technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the VW1 and the CCS1 wells, structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. Intention was for two million tons per annum (MTPA) of CO2 to be injected for 20 years. In the preceding, the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010" in this topical report) was re-run using a new injection scenario; 3.2 MTPA for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. It was not sufficiently large enough to accommodate the evolution of the plume. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 miles x 30 miles (48.3km x48.3km), while preserving all property modeling workflows and layering. This model was retained as the base case of Potosi Dynamic Model 2013a. The Potosi reservoir model was updated to take into account the new data from the verification well VW2 which was drilled in 2012. The new porosity and permeability modeling was performed to take into account the log data from the new well. Revisions of the 2010 modeling assumptions were also done on relative permeability, capillary pressures, formation water salinity, and the maximum allowable well bottomhole pressure. Dynamic simulations were run using the injection target of 3.2 MTPA for 30 years. This new dynamic model was named Potosi Dynamic Model 2013b. Due to the major uncertainties on the vugs permeability, two models were built; the Pessimistic and Optimistic Cases. The Optimistic Case assumes vugs permeability of 9,000 mD, which is analog to the vugs permeability identified in the pressure fall off test of a waste water injector in the Tuscola site, approx. 40 miles (64.4km) away from the IBDP area. The Pessimistic Case assumes that the vugs permeability is equal to the log data, which does not take into account the permeability from secondary porosity. The probability of such case is deemed low and could be treated as the worst case scenario, since the contribution of secondary porosity to the permeability is neglected and the loss circulation events might correspond to a much higher permeability. It is considered important, however, to identify the range of possible reservoir performance since there are no rigorous data available for the vugs permeability. The Optimistic Case gives an average CO2 injection rate of 0.8 MTPA and cumulative injection of 26 MT in 30 years, which corresponds to 27% of the injection target. The injection rate is approx. 3.2 MTPA in the first year as the well is injecting into the surrounding vugs, and declines rapidly to 0.8 MTPA in year 4 once the surrounding vugs are full and the CO2 start to reach the matrix. This implies that according to this preliminary model, a minimum of four (4) wells could be required to achieve the injection target. This result is lower than the injectivity estimated in the Potosi Dynamic Model 2013a (43 MT in 30 years), since the permeability model applied in the Potosi Dynamic Model 2013b is more conservative. This revision was deemed necessary to treat the uncertainty in a more appropriate manner. As the CO2 follows the paths where vugs interconnection exists, a reasonably large and irregular plume extent was created. For the Optimistic Case, the plume extends 17 miles (27.4km) in E-W and 14 miles (22.5km) in N-S directions after 30 years. After injection is completed, the plume continues to migrate laterally, mainly driven by the remaining pressure gradient. After 100 years post injection, the plume extends 20 miles (32.2km) in E-W and 15.5 miles (24.9km) in N-S directions. Should the targeted cumulative injection of 96 MT be achieved; a much larger plume extent could be expected. For the Optimistic Case, the increase of reservoir pressure at the end of injection is approximately 1200 psia (8,274 kPa) around the injector and gradually decreases away from the well. The reservoir pressure increase is less than 30 psia (206.8 kPa) beyond 14 miles (22.5km) away from injector. Should the targeted cumulative injection of 96 MT be achieved; a much larger areal pressure increase could be expected. The initial reservoir pressure is nearly restored after approximately 100 years post injection. The presence of matrix slows down the pressure dissipations. The Pessimistic Case gives an average CO2 injection rate of 0.2 MTPA and cumulative injection of 7 MT in 30 years, which corresponds to 7% of the injection target. This implies that in the worst case scenario, a minimum of sixteen (16) wells could be required to achieve the injection target. The present evaluation is mainly associated with uncertainty on the vugs permeability, distribution, and interconnectivity. The different results indicated by the Optimistic and Pessimistic Cases signify the importance of vugs permeability characterization. Therefore, injection test and pressure interference test among the wells could be considered to evaluate the local vugs permeability, extent, and interconnectivity. Porosity mapping derived from the seismic inversion could also be used in the succeeding task to characterize the lateral porosity distribution within the reservoir. With or without seismic inversion porosity mapping, it is worth exploring whether increased lateral heterogeneity plays a significant role in Potosi injectivity. Investigations on vugular, dolomitic outcrops suggest that there may be significantly greater lateral heterogeneity than what has been modeled here. Facies modeling within the Potosi has yet to be thoroughly addressed. The carbonates during the time of deposition are believed to be regionally extensive. However, it may be worth delineating the reservoir with other regional wells or modern day analogues to understand the extent of the Potosi. More specifically, the model could incorporate lateral changes or trends if deemed necessary to represent facies transition. Data acquisitions to characterize the fracture pressure gradient, the formation water properties, the relative permeability, and the capillary pressure could also be considered in order to allow a more rigorous evaluation of the Potosi storage performance. A simulation using several injectors could also be considered to determine the required number of wells to achieve the injection target while taking into account the pressure interference.

Adushita, Yasmin↗

DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested using new and existing geoscientific exploration datasets at Newberry Volcano. This GDR submission includes images, data, and models related to the 3D favorability and uncertainty models and the 2D favorability and uncertainty maps. The DEEPEN PFA Methodology, detailed in the journal article below, is based on the method proposed by Poux & O'brien (2020), which uses the Leapfrog Geothermal software with the Edge extension to conduct PFA in 3D. This method uses all available data to build a 3D geodata model which can be broken down into smaller blocks and analyzed with advanced geostatistical methods. Each data set is imported into a 3D model in Leapfrog and divided into smaller blocks. Conditional queries can then be used to assign each block an index value which conditionally ranks each block's favorability, from 0-5 with 5 being most favorable, for each model (e.g., lithologic, seismic, magnetic, structural). The values between 0-5 assigned to each block are referred to as index values. The final step of the process is to combine all the index models to create a favorability index. This involves multiplying each index model by a given weight and then summing the resulting values. The DEEPEN PFA Methodology follows this approach, but split up by the specific geologic components of each play type. These components are defined as follows for each magmatic play type: 1. Conventional hydrothermal plays in magmatic environments: Heat, fluid, and permeability 2. Superhot EGS plays: Heat, thermal insulation, and producibility (the ability to create and sustain fractures suitable for and EGS reservoir) 3. Supercritical plays: Heat, supercritical fluid, pressure seal, and producibility (the proper permeability and pressure conditions to allow production of supercritical fluid) More information on these components and their development can be found in Kolker et al., (2022). For the purposes of subsurface imaging, it is easier to detect a permeable fluid-filled reservoir than it is to detect separate fluid and permeability components. Therefore, in this analysis, we combine fluid and permeability for conventional hydrothermal plays, and supercritical fluid and producibility for supercritical plays. We also project the 3D favorability volumes onto 2D surfaces for simplified joint interpretation, and we incorporate an uncertainty component. Uncertainty was modeled using the best approach for the dataset in question, for the datasets where we had enough information to do so. Identifying which subsurface parameters are the least resolved can help qualify current PFA results and focus future efforts in data collection. Where possible, the resulting uncertainty models/indices were weighted using the same weights applied to the respective datasets, and summed, following the PFA methodology above, but for uncertainty.

15 GEOTHERMAL ENERGY↗

A reduced basis approach for PDEs on parametrized geometries based on the shifted boundary finite element method and application to a Stokes flow

Here we propose a model order reduction technique integrating the Shifted Boundary Method (SBM) with a POD-Galerkin strategy. This approach allows to deal with complex parametrized domains in an efficient and straightforward way. The impact of the proposed approach is threefold. First, problems involving parametrizations of complex geometrical shapes and/or large domain deformations can be efficiently solved at full-order by means of the SBM. This unfitted boundary method permits to avoid remeshing and the tedious handling of cut cells by introducing an approximate surrogate boundary. Second, the computational effort is reduced by the development of a Reduced Order Model (ROM) technique based on a POD-Galerkin approach. Third, the SBM provides a smooth mapping from the true to the surrogate domain, and for this reason, the stability and performance of the reduced order basis are enhanced. This feature is the net result of the combination of the proposed ROM approach and the SBM. Similarly, the combination of the SBM with a projection-based ROM gives the great advantage of an easy and fast to implement algorithm considering geometrical parametrization with large deformations. The transformation of each geometry to a reference geometry (morphing) is in fact not required. These combined advantages will allow the solution of PDE problems more efficiently. We illustrate the performance of this approach on a number of two-dimensional Stokes flow problems.

42 ENGINEERING↗

INL Results for Phases I and III of the OECD/NEA MHTGR-350 Benchmark

The Idaho National Laboratory (INL) Very High Temperature Reactor (VHTR) Technology Development Office (TDO) Methods Core Simulation group led the construction of the Organization for Economic Cooperation and Development (OECD) Modular High Temperature Reactor (MHTGR) 350 MW benchmark for comparing and evaluating prismatic VHTR analysis codes. The benchmark is sponsored by the OECD's Nuclear Energy Agency (NEA), and the project will yield a set of reference steady-state, transient, and lattice depletion problems that can be used by the Department of Energy (DOE), the Nuclear Regulatory Commission (NRC), and vendors to assess their code suits. The Methods group is responsible for defining the benchmark specifications, leading the data collection and comparison activities, and chairing the annual technical workshops. This report summarizes the latest INL results for Phase I (steady state) and Phase III (lattice depletion) of the benchmark. The INSTANT, Pronghorn and RattleSnake codes were used for the standalone core neutronics modeling of Exercise 1, and the results obtained from these codes are compared in Section 4. Exercise 2 of Phase I requires the standalone steady-state thermal fluids modeling of the MHTGR-350 design, and the results for the systems code RELAP5-3D are discussed in Section 5. The coupled neutronics and thermal fluids steady-state solution for Exercise 3 are reported in Section 6, utilizing the newly developed Parallel and Highly Innovative Simulation for INL Code System (PHISICS)/RELAP5-3D code suit. Finally, the lattice depletion models and results obtained for Phase III are compared in Section 7. The MHTGR-350 benchmark proved to be a challenging simulation set of problems to model accurately, and even with the simplifications introduced in the benchmark specification this activity is an important step in the code-to-code verification of modern prismatic VHTR codes. A final OECD/NEA comparison report will compare the Phase I and III results of all other international participants in 2014, while the remaining Phase II transient case results will be reported in 2015.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NGEE Arctic Tram: Overview of Tram-mounted Instruments, Co-located Data, Measurement Position, Elevation and Polygon Characterization, Utqiagvik (Barrow), Alaska, 2014-2018

The NGEE-Arctic Tram operated from 2014 - 2018. It was installed on the Barrow Environmental Observatory in Barrow, Alaska in late May of 2014 and operated through mid-November 2014. The subsequent 2015 through 2018 years followed a similar schedule, but with different deployment dates and data gaps, with the goal always to capture the surface dynamics of the snow melt, growing, and freeze-up seasons. This Tram overview dataset has three objectives: (1) provide new data users with a brief description of the Tram system and its research purposes; (2) provide generally useful Tram site characterization details, including measurement position ground surface elevation, characteristics of the Arctic polygonal tundra under the Tram, vegetation community composition (future), and derived image products; and (3) reference all of the data products and archived datasets that were collected with the Tram-mounted sensors and co-located instruments. This dataset contains two csv files, two zipped files, one tif file, and one pdf file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets

This dataset contains turbine- and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in Steady State (FLORIS) model, version 2.3.0. The 252,500 cases include 500 unique wind plants generated randomly by a specialized Plant Layout Generator (PLayGen) that samples randomized realizations of wind plant layouts from one of four canonical configurations: (i) cluster, (ii) single string, (iii) multiple string, (iv) parallel string. Other wind plant layout parameters were also randomly sampled, including the number of turbines (25-200) and the mean turbine spacing (3D-10D, where D denotes the turbine rotor diameter). For each layout, 500 different sets of atmospheric conditions were randomly sampled. These include wind speed in 0-25 m/s, wind direction in 0 deg.-360 deg., and turbulence intensity chosen from low (6%), medium (8%), and high (10%). For each atmospheric inflow scenario, the individual turbine yaw angles were randomly sampled from a one-sided truncated Gaussian on the interval 0 deg.-30 deg. oriented relative to wind inflow direction. This random data is supplemented with a collection of yaw-optimized samples where FLORIS was used to determine turbine yaw angles that maximize power production for the entire plant. To generate this data, a subset of cases were selected (50 atmospheric conditions from 50 layouts each for a total of additional 2,500 cases) for which FLORIS was re-run with wake steering control optimization. The IEA onshore reference turbine, which has a 130 m rotor diameter, a 110 m hub height, and a rated power capacity of 3.4 MW was used as the turbine for all simulations. The simulations were performed using NREL's Eagle high performance computing system in February 2021 as part of the Spatial Analysis for Wind Technology Development project funded by the U.S. Department of Energy Wind Energy Technologies Office. The data was collected, reformatted, and preprocessed for this OEDI submission in May 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub repository under explore_wind_plant_data_h5.ipynb.

AI↗

DEEPEN 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. Part of the DEEPEN project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested using new and existing geoscientific exploration datasets at Newberry Volcano. This GDR submission includes images, data, and models related to the 3D favorability and uncertainty models and the 2D favorability and uncertainty maps. The DEEPEN PFA Methodology is based on the method proposed by Poux et al. (2020), which uses the Leapfrog Geothermal software with the Edge extension to conduct PFA in 3D. This method uses all available data to build a 3D geodata model which can be broken down into smaller blocks and analyzed with advanced geostatistical methods. Each data set is imported into a 3D model in Leapfrog and divided into smaller blocks. Conditional queries can then be used to assign each block an index value which conditionally ranks each block's favorability, from 0-5 with 5 being most favorable, for each model (e.g., lithologic, seismic, magnetic, structural). The values between 0-5 assigned to each block are referred to as index values. The final step of the process is to combine all the index models to create a favorability index. This involves multiplying each index model by a given weight and then summing the resulting values. The DEEPEN PFA Methodology follows this approach, but split up by the specific geologic components of each play type. These components are defined as follows for each magmatic play type: 1. Conventional hydrothermal plays in magmatic environments: Heat, fluid, and permeability 2. Superhot EGS plays: Heat, thermal insulation, and producibility (the ability to create and sustain fractures suitable for and EGS reservoir) 3. Supercritical plays: Heat, supercritical fluid, pressure seal, and producibility (the proper permeability and pressure conditions to allow production of supercritical fluid) More information on these components and their development can be found in Kolker et al., 2022. For the purposes of subsurface imaging, it is easier to detect a permeable fluid-filled reservoir than it is to detect separate fluid and permeability components. Therefore, in this analysis, we combine fluid and permeability for conventional hydrothermal plays, and supercritical fluid and producibility for supercritical plays. More information on this process is described in the following sections. We also project the 3D favorability volumes onto 2D surfaces for simplified joint interpretation, and we incorporate an uncertainty component. Uncertainty was modeled using the best approach for the dataset in question, for the datasets where we had enough information to do so. Identifying which subsurface parameters are the least resolved can help qualify current PFA results and focus future efforts in data collection. Where possible, the resulting uncertainty models/indices were weighted using the same weights applied to the respective datasets, and summed, following the PFA methodology above, but for uncertainty. There are two different versions of the Leapfrog model and associated favorability models: - v1.0: The first release in June 2023 - v2.1: The second release, with improvements made to the earthquake catalog (included additional identified events, removed duplicate events), to the temperature model (fixed a deep BHT), and to the index models (updated the seismicity-heat source index models for supercritical and EGS, and the resistivity-insulation index models for all three play types). Also uses the jet color map rather than the magma color map for improved interpretability. - v2.1.1: Updated to include v2.0 uncertainty results (see below for uncertainty model versions) There are two different versions of the associated uncertainty models: - v1.0: The first release in June 2023 - v2.0: The se...

15 GEOTHERMAL ENERGY↗

The Potosi Reservoir Model 2013c, Property Modeling Update

As part of a larger project co-funded by the United States Department of Energy (US DOE) to evaluate the potential of formations within the Cambro-Ordovician strata above the Mt. Simon as potential targets for carbon sequestration in the Illinois and Michigan Basins, the Illinois Clean Coal Institute (ICCI) requested Schlumberger to evaluate the potential injectivity and carbon dioxide (CO2) plume size of the Cambrian Potosi Formation. The evaluation of this formation was accomplished using wireline data, core data, pressure data, and seismic data from this project as well as two other separately funded projects: the US DOE-funded Illinois Basin–Decatur Project (IBDP) being conducted by the Midwest Geological Sequestration Consortium (MGSC) in Macon County, Illinois, and the Illinois Industrial Carbon Capture and Sequestration (ICCS) project funded through the American Recovery and Reinvestment Act. In 2010, technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the Verification Well #1 (VW1) and the Injection Well (CCS1), structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. The intention was for 2.2 million tons per annum (2 million tonnes per annum [MTPA]) of CO2 to be injected for 20 years. In the Task Error! Reference source not found., the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010") was re-run using a new injection scenario of 3.5 million tons per annum (3.2 MTPA) for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. The models size was insufficient to accommodate the evolution of the plume. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 by 30 mi (48 by 48 km), while preserving all property modeling workflows and layering. This model was retained as the base case. In the preceding Task [1], the Potosi reservoir model was updated to take into account the new data from the Verification Well #2 (VW2) which was drilled in 2012. The porosity and permeability modeling was revised to take into account the log data from the new well. Revisions of the 2010 modeling assumptions were also done on relative permeability, capillary pressures, formation water salinity, and the maximum allowable well bottomhole pressure. Dynamic simulations were run using the injection target of 3.5 million tons per annum (3.2 MTPA) for 30 years. This dynamic model was named Potosi Dynamic Model 2013b. In this Task, a new property modeling workflow was applied, where seismic inversion data guided the porosity mapping and geobody extraction. The static reservoir model was fully guided by PorosityCube interpretations and derivations coupled with petrophysical logs from three wells. The two main assumptions are: porosity features in the PorosityCube that correlate with lost circulation zones represent vugular zones, and that these vugular zones are laterally continuous. Extrapolation was done carefully to populate the vugular facies and their corresponding properties outside the seismic footprint up to the boundary of the 30 by 30 mi (48 by 48 km) model. Dynamic simulations were also run using the injection target of 3.5 million tons per annum (3.2 MTPA) for 30 years. This new dynamic model was named Potosi Dynamic Model 2013c. Reservoir simulation with the latest model gives a cumulative injection of 43 million tons (39 MT) in 30 years with a single well, which corresponds to 40% of the injection target. The injection rate is approx. 3.2 MTPA in the first six months as the well is injecting into the surrounding vugs, and declines rapidly to 1.8 million tons per annum (1.6 MTPA) in year 3 once the surrounding vugs are full and the CO2 start to reach the matrix. After, the injection rate declines gradually to 1.2 million tons per annum (1.1 MTPA) in year 18 and stays constant. This implies that a minimum of three (3) wells could be required in the Potosi to reach the injection target. The injectivity evaluated in this Task was higher compared to the preceding Task, since the current facies modeling (guided by the porosity map from the seismic inversion) indicated a higher density of vugs within the vugular zones. 5 As the CO2 follows the paths where vugs interconnection exists, a reasonably large and irregular plume extent was created. After 30 years of injection, the plume extends 13.7 mi (22 km) in E-W and 9.7 mi (16 km) in N-S directions. After injection finishes, the plume continues to migrate laterally, mainly driven by the remaining pressure gradient. After 60 years post-injection, the plume extends 14.2 mi (22.8 km) in E-W and 10 mi (16 km) in N-S directions, and remains constant as the remaining pressure gradient has become very low. Should the targeted cumulative injection of 106 million tons (96 MT) be achieved; a much larger plume extent could be expected. The increase of reservoir pressure at the end of injection is approximately 1,200 psia (8,274 kPa) around the injector and gradually decreases away from the well. The reservoir pressure increase is less than 10 psia (69 kPa) beyond 14 mi (23 km) away from injector. Should the targeted cumulative injection of 106 million tons (96 MT) be achieved; a much larger areal pressure increase could be expected. The reservoir pressure declines rapidly during the first 30 years post injection and the initial reservoir pressure is nearly restored after 100 years post-injection. The present evaluation is mainly associated with uncertainty on the vugs permeability and interconnectivity. The use of porosity mapping from seismic inversion might have reduced the uncertainty on the lateral vugs body distributions. However, major uncertainties on the Potosi vugs permeability remains. Therefore, injection test and pressure interference test among the wells could be considered to evaluate the local vugs permeability, extent, and interconnectivity. Facies modeling within the Potosi has yet to be thoroughly addressed. The carbonates during the time of deposition are believed to be regionally extensive. However, it may be worth delineating the reservoir with other regional wells or modern day analogues to understand the extent of the Potosi. More specifically, the model could incorporate lateral changes or trends if deemed necessary to represent facies transition. Data acquisitions to characterize the fracture pressure gradient, the formation water properties, the relative permeability, and the capillary pressure could also be considered in order to allow a more rigorous evaluation of the Potosi storage performance. A simulation using several injectors could also be considered to determine the required number of wells and appropriate spacing to achieve the injection target while taking into account the pressure interference.

Adushita, Yasmin↗

STEADY STATE MODELING OF THE MINIMUM CRITICAL CORE OF THE TRANSIENT REACTOR TEST FACILITY

With the advent of next generation reactor systems and new fuel designs, the U.S. Department of Energy (DOE) has identified the need for the resumption of transient testing of nuclear fuels. The DOE has decided that the Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) is best suited for future testing. TREAT is a thermal neutron spectrum, air-cooled, nuclear test facility that is designed to test nuclear fuels in transient scenarios. These specific scenarios range from simple temperature transients to full fuel melt accidents. DOE has expressed a desire to develop a simulation capability that will accurately model the experiments before they are irradiated at the facility. It is the aim for this capability to have an emphasis on effective and safe operation while minimizing experimental time and cost. The multi physics platform MOOSE has been selected as the framework for this project. The goals for this work are to identify the fundamental neutronics properties of TREAT and to develop an accurate steady state model for future multiphysics transient simulations. In order to minimize computational cost, the effect of spatial homogenization and angular discretization are investigated. It was found that significant anisotropy is present in TREAT assemblies and to capture this effect, explicit modeling of cooling channels and inter-element gaps is necessary. For this modeling scheme, single element calculations at 293 K gave power distributions with a root mean square difference of 0.076% from those of reference SERPENT calculations. The minimum critical core configuration with identical gap and channel treatment at 293 K resulted in a root mean square, total core, radial power distribution 2.423% different than those of reference SERPENT solutions.

Critical↗