Phase-selection algorithms to minimize cost and imbalance in U.S. synthetic distribution systems
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Postigo, Fernando↗
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BlueCRAB Multiphysics in Support of the U.S.NRC
This presentation provides an overview of the nonLWR modeling and simulation project at INL. It includes a discussion of the various reference plant models developed since 2019 and a more detailed view at results from a monolith-based heat pipe cooled micro reactor.
21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios
The National Renewable Energy Laboratory (NREL) in collaboration with Massachusetts Institute of Technology (MIT), Universidad Pontificia Comillas (Comillas-IIT, Spain) and GE Grid Solutions, is working on an ARPA-E GRID DATA project, titled Smart-DS, to create: 1) High-quality, realistic, synthetic distribution network models, and 2) Advanced tools for automated scenario generation based on high-resolution weather data and generation growth projections. Through these advancements, the Smart-DS project is envisioned to accelerate the development, testing, and adoption of advanced algorithms, approaches, and technologies for sustainable and resilient electric power systems, especially in the realm of U.S. distribution systems. This talk will present the goals and overall approach of the Smart-DS project, including the process of creating the synthetic distribution datasets using reference network model (RNM) and the comprehensive validation process to ensure network realism, feasibility, and applicability to advanced use cases. The talk will provide demonstrations of early versions of synthetic models, along with the lessons learnt from expert engagements to enhance future iterations. Finally, the scenario generation framework, its development plans, and co-ordination with GRID DATA repository teams to house these datasets for public access will also be discussed.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Applying 3D Geologic Modeling Workflows to the Argillite Reference Case (Rev. 1)
The objective of this short report is to document the application of our 3D geologic modeling workflow to an argillite (shale) host rock. Over the past four years, our team at Los Alamos National Laboratory has developed a geologic modeling workflow that can be applied to generic alluvial basins such as those found in the western United States. In “frontier” or “exploratory” basins where data are sparse, the first steps are to collect, evaluate and integrate available subsurface data into conceptual geologic models. Those models form the basis for constructing the geologic framework model, a 3D geocellular model ideally constrained by seismic and borehole data. To date we have constructed our models using “synthetic” well data derived from conceptual models, without the prospect of validating our workflow using “real” subsurface data. We were tasked to investigate whether our workflow designed for alluvial basin sediments could be applied to other potential repository host rocks. This task also provided the opportunity to work with high-quality subsurface data collected specifically for siting and evaluating a nuclear waste repository. Nagra, the Swiss governmental agency responsible for the disposal of the nation’s radioactive waste, generously provided us with data from two deep boreholes drilled through their argillaceous target formation. The aim of our proof-of-concept demonstration is to evaluate whether geostatistical methods offer a viable approach to property modeling in argillaceous rocks. Nagra provided us with the well data on the condition that we maintain confidentiality with all transferred information and results. Fortunately, Nagra posts numerous technical reports on its public website that describe the subsurface geology in great detail. All of the information and illustrations in this report related to the Swiss repository enterprise are taken from the Nagra public website.
58 GEOSCIENCES↗
Separating Dynamic and Thermodynamic Impacts of Climate Change on Daytime Convective Development over Land
Climate change affects the dynamics and thermodynamics of moist convection. Changes in the dynamics concern, for instance, an increase of convection strength due to increases of convective available potential energy (CAPE). Thermodynamics involve increases in water vapor that the warmer atmosphere can hold and convection can work with. Small-scale simulations are conducted to separate these two components for daytime development of unorganized convection over land. The simulations apply a novel modeling technique referred to as the piggybacking (or master–slave) approach and consider the global climate model (GCM)-predicted change of atmospheric temperature and moisture profiles in the Amazon region at the end of the century under a business-as-usual scenario. The simulations show that the dynamic impact dominates because changes in cloudiness and rainfall come from cloud dynamics considerations, such as the change in CAPE and convective inhibition (CIN) combined with the impact of environmental relative humidity (RH) on deep convection. The small RH reduction between the current and future climate significantly affects the mean surface rain accumulation as it changes from a small reduction to a small increase when the RH decrease is eliminated. The thermodynamic impact on cloudiness and precipitation is generally small, with the extreme rainfall intensifying much less than expected from an atmospheric moisture increase. These results are discussed in the context of previous studies concerning climate change–induced modifications of moist convection. Future research directions applying the piggybacking method are discussed.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Advanced trust region optimization strategies for glass box / black box models
We present an improved trust region filter (TRF) method for optimization of combined glass box/black box systems. Glass box systems refer to models that are easily expressed in an algebraic modeling language, providing cheap and accurate derivative information. By contrast, black box systems may be computationally expensive and derivatives are unavailable. The TRF method, as first introduced in our previous work (Eason and Biegler, AIChE J . 2016; 62:3124–3136), is able to handle hybrid systems containing both glass and black box components, which can frequently arise in chemical engineering, for example, when a multiphase reactor model is included in a flow sheet optimization problem. We discuss several recent modifications in the algorithm such as the sampling region, which maintains the algorithm's global convergence properties without requiring the trust region to shrink to zero in the limit. To benchmark the development of this optimization method, a test set of problems is generated based on modified problems from the CUTEr and COPS sets. The modified algorithm demonstrates improved performance using the test problem set. Finally, the algorithm is implemented within the Pyomo environment and demonstrated on a rigorous process optimization case study for carbon capture. © 2018 American Institute of Chemical Engineers AIChE J , 64: 3934–3943, 2018
Eason, John P.↗
HST/STIS ULTRAVIOLET SPECTROSCOPY OF THE COMPONENTS OF THE MASSIVE TRIPLE STAR δ ORI A
The multiple star system of δ Orionis is one of the closest examples of a system containing a luminous O-type, bright giant star (component Aa1). It is often used as a spectral-type standard and has the highest observed X-ray flux of any hot-star binary. The main component Aa1 is orbited by two lower mass stars, faint Aa2 in a 5.7 day eclipsing binary, and Ab, an astrometric companion with an estimated period of 346 years. Generally the flux from all three stars is recorded in ground-based spectroscopy, and the spectral decomposition of the components has proved difficult. Here we present Hubble Space Telescope/Space Telescope Imaging Spectrograph ultraviolet spectroscopy of δ Ori A that provides us with spatially separated spectra of Aa and Ab for the first time. We measured radial velocities for Aa1 and Ab in two observations made near the velocity extrema of Aa1. We show tentative evidence for the detection of the Aa2 component in cross-correlation functions of the observed and model spectra. We discuss the appearance of the UV spectra of Aa1 and Ab with reference to model spectra. Both stars have similar effective temperatures, but Ab is fainter and is a rapid rotator. The results will help in the interpretation of ground-based spectroscopy and in understanding the physical and evolutionary parameters of these massive stars.
79 ASTRONOMY AND ASTROPHYSICS↗
Advanced Models and Fast Simulation Algorithms for MARS Plants
With the successful commercialization of modular multilevel converters (MMC) and rapid increase in photovoltaic (PV) penetration and energy storage systems (ESS), one of the research areas being explored dynamically is integration of PV systems and ESS systems to MMCs. On this front, an integrated development of PV plants, ESS, and alternating- and direct-current (ac/dc) systems through Multi-Port Autonomous Reconfigurable Solar (MARS) plant is proposed and being researched upon. However, simulation of MARS systems on traditional existing software takes very long time (order of days) due to the presence of a large number of states and non-linear devices. Therefore, development of fast high fidelity models is of paramount importance to test the hardware design, control design and planning of power system expansions. In this context, two research objectives are addressed in this paper: firstly, an ultra fast single- or multi- CPU simulation algorithm to simulate the MARS system based on state-space models, hybrid discretization algorithm with a relaxation technique that reduces the imposed computational burden and a multi-rate method is presented. Secondly, a reduced order model of MARS is also presented. Both the developed techniques are validated with respect to reference PSCAD/EMTDC model.
Marthi, Phani Ratna Vanamali↗
Validation and Calibration of Energy Models with Real Vehicle Data from Chassis Dynamometer Experiments
Accurate estimation of vehicle fuel consumption typically requires detailed modeling of complex internal powertrain dynamics, often resulting in computationally intensive simulations. However, many transportation applications-such as traffic flow modeling, optimization, and control-require simplified models that are fast, interpretable, and easy to implement, while still maintaining fidelity to physical energy behavior. This work builds upon a recently developed model reduction pipeline that derives physics-like energy models from high-fidelity Autonomie vehicle simulations. These reduced models preserve essential vehicle dynamics, enabling realistic fuel consumption estimation with minimal computational overhead. While the reduced models have demonstrated strong agreement with their Autonomie counterparts, previous validation efforts have been confined to simulation environments. This study extends the validation by comparing the reduced energy model's outputs against real-world vehicle data. Focusing on the MidSUV category, we tune the baseline Autonomie model to closely replicate the characteristics of a Toyota RAV4. We then assess the accuracy of the resulting reduced model in estimating fuel consumption under actual drive conditions. Our findings suggest that, when the reference Autonomie model is properly calibrated, the simplified model produced by the reduction pipeline can provide reliable, semi-principled fuel rate estimates suitable for large-scale transportation applications.
42 ENGINEERING↗
WindPACT Reference Wind Turbines
To fully understand how loads and turbine cost scale with turbine size, it is necessary to have identical turbine models that have been scaled to different rated powers. The report presents the WindPACT baseline models, which are a series of four baseline models that were designed to facilitate investigations into the scalings of loads and turbine cost with size. The models have four different rated powers (750 kW, 1.5 MW, 3.0 MW, and 5.0 MW), and each model was designed to its specified rated power using the same design methodology. The models were originally implemented in FAST_AD, the predecessor to NREL's open-source wind turbine simulator FAST, but have yet to be implemented in FAST. This report contains the specifications for all four WindPACT baseline models - including structural, aerodynamic, and control specifications - along with the inherent assumptions and equations that were used to calculate the model parameters. It is hoped that these baseline models will serve as extremely useful resources for investigations into the scalings of costs, loads, or optimization routines.
17 WIND ENERGY↗
Multiscale solute transport upscaling for a three‐dimensional hierarchical porous medium
Abstract A laboratory‐generated hierarchical, fully heterogeneous aquifer model (FHM) provides a reference for developing and testing an upscaling approach that integrates large‐scale connectivity mapping with flow and transport modeling. Based on the FHM, three hydrostratigraphic models (HSMs) that capture lithological (static) connectivity at different resolutions are created, each corresponding to a sedimentary hierarchy. Under increasing system ln K variances (0.1, 1.0, 4.5), flow upscaling is first conducted to calculate equivalent hydraulic conductivity for individual connectivity (or unit) of the HSMs. Given the computed flow fields, an instantaneous, conservative tracer test is simulated by all models. For the HSMs, two upscaling formulations are tested based on the advection‐dispersion equation (ADE), implementing space versus time‐dependent macrodispersivity. Comparing flow and transport predictions of the HSMs against those of the reference model, HSMs capturing connectivity at increasing resolutions are more accurate, although upscaling errors increase with system variance. Results suggest: (1) by explicitly modeling connectivity, an enhanced degree of freedom in representing dispersion can improve the ADE‐based upscaled models by capturing non‐Fickian transport of the FHM; (2) when connectivity is sufficiently resolved, the type of data conditioning used to model transport becomes less critical. Data conditioning, however, is influenced by the prediction goal; (3) when aquifer is weakly‐to‐moderately heterogeneous, the upscaled models adequately capture the transport simulation of the FHM, despite the existence of hierarchical heterogeneity at smaller scales. When aquifer is strongly heterogeneous, the upscaled models become less accurate because lithological connectivity cannot adequately capture preferential flows; (4) three‐dimensional transport connectivities of the hierarchical aquifer differ quantitatively from those analyzed for two‐dimensional systems.
Zhang, Mingkan↗
Global centroid moment tensor solutions in a heterogeneous earth: the CMT3D catalogue
SUMMARY For over 40 yr, the global centroid-moment tensor (GCMT) project has determined location and source parameters for globally recorded earthquakes larger than magnitude 5.0. The GCMT database remains a trusted staple for the geophysical community. Its point-source moment-tensor solutions are the result of inversions that model long-period observed seismic waveforms via normal-mode summation for a 1-D reference earth model, augmented by path corrections to capture 3-D variations in surface wave phase speeds, and to account for crustal structure. While this methodology remains essentially unchanged for the ongoing GCMT catalogue, source inversions based on waveform modelling in low-resolution 3-D earth models have revealed small but persistent biases in the standard modelling approach. Keeping pace with the increased capacity and demands of global tomography requires a revised catalogue of centroid-moment tensors (CMT), automatically and reproducibly computed using Green's functions from a state-of-the-art 3-D earth model. In this paper, we modify the current procedure for the full-waveform inversion of seismic traces for the six moment-tensor parameters, centroid latitude, longitude, depth and centroid time of global earthquakes. We take the GCMT solutions as a point of departure but update them to account for the effects of a heterogeneous earth, using the global 3-D wave speed model GLAD-M25. We generate synthetic seismograms from Green's functions computed by the spectral-element method in the 3-D model, select observed seismic data and remove their instrument response, process synthetic and observed data, select segments of observed and synthetic data based on similarity, and invert for new model parameters of the earthquake’s centroid location, time and moment tensor. The events in our new, preliminary database containing 9382 global event solutions, called CMT3D for ‘3-D centroid-moment tensors’, are on average 4 km shallower, about 1 s earlier, about 5 per cent larger in scalar moment, and more double-couple in nature than in the GCMT catalogue. We discuss in detail the geographical and statistical distributions of the updated solutions, and place them in the context of earlier work. We plan to disseminate our CMT3D solutions via the online ShakeMovie platform.
58 GEOSCIENCES↗
Accurate prediction of diradical chemistry from a single-reference density-matrix method: Model application to the bicyclobutane to gauche-1,3-butadiene isomerization
Multireference correlation in diradical molecules can be captured by a single-reference 2-electron reduced-density-matrix (2-RDM) calculation with only single and double excitations in the 2-RDM parametrization. The 2-RDM parametrization is determined by N-representability conditions that are non-perturbative in their treatment of the electron correlation. Conventional single-reference wave function methods cannot describe the entanglement within diradical molecules without employing triple- and potentially even higher-order excitations of the mean-field determinant. In the isomerization of bicyclobutane to gauche-1,3-butadiene the parametric 2-RDM (p2-RDM) method predicts that the diradical disrotatory transition state is 58.9 kcal/mol above bicyclobutane. This barrier is in agreement with previous multireference calculations as well as recent Monte Carlo and higher-order coupled cluster calculations. The p2-RDM method predicts the Nth natural-orbital occupation number of the transition state to be 0.635, revealing its diradical character. The optimized geometry from the p2-RDM method differs in important details from the complete-active-space self-consistent-field geometry used in many previous studies including the Monte Carlo calculation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
An interlaboratory collaboration to determine consensus 231 Pa/ 235 U model ages of a uranium certified reference material for nuclear forensics
Application of the 231 Pa/ 235 U radiochronometer for nuclear forensic investigations is challenged by a lack of certified reference materials with 231 Pa/ 235 U model purification dates. The Japan Atomic Energy Agency, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory completed an interlaboratory study measuring 231 Pa/ 235 U model ages of New Brunswick Laboratory CRM U100. Results from independent laboratories were combined to calculate a consensus 231 Pa/ 235 U model purification date for CRM U100 of March 26, 1959 ± 237 days. This 231 Pa/ 235 U consensus date for CRM U100 may be used by the nuclear forensic community for quality control of 231 Pa/ 235 U radiochronometry measurements of unknown materials.
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
A Methodology and Implementation of Automated Emissions Harmonization for Use in Integrated Assessment Models
Emissions harmonization refers to the process used to match greenhouse gas (GHG) and air pollutant results from Integrated Assessment Models (IAMs) against a common source of historical emissions. To date, harmonization has been performed separately by individual modeling teams. For the hand-over of emission data for the Shared Socio-economic Pathways (SSPs) to climate model groups, a new automated approach based on commonly agreed upon algorithms was developed. This work describes the novel methodology for determining such harmonization methods and an open-source Python software library implementing the methodology. Results are shown for two example scenarios (with and without climate policy cases) using the MESSAGE-GLOBIOM IAM that satisfactorily harmonize over 96% of the total emissions trajectories while having a negligible eect on key long-term climate indicators. This new capability enhances the comparability across dierent models, increases transparency and robustness of results, and allows other teams to easily participate in intercomparison exercises by using the same, openly available harmonization mechanism.
intergrated assessment, climate change, Harmonizat↗
Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling
AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.
54 ENVIRONMENTAL SCIENCES↗
SU-E-J-113: The Influence of Optimizing Pediatric CT Simulator Protocols On the Treatment Dose Calculation in Radiotherapy
Purpose: To investigate the possibility of applying optimized scanning protocols for pediatric CT simulation by quantifying the dosimetric inaccuracy introduced by using a fixed HU to density conversion. Methods: The images of a CIRS electron density reference phantom (Model 062) were acquired by a Siemens CT simulator (Sensation Open) using the following settings of tube voltage and beam current: 120 kV/190mA (the reference protocol used to calibrate CT for our treatment planning system (TPS)); Fixed 190mA combined with all available kV: 80, 100, and 140; fixed 120 kV and various current from 37 to 444 mA (scanner extremes) with interval of 30 mA. To avoid the HU uncertainty of point sampling in the various inserts of known electron densities, the mean CT numbers of the central cylindrical volume were calculated using DICOMan software. The doses per 100 MU to the reference point (SAD=100cm, Depth=10cm, Field=10X10cm, 6MV photon beam) in a virtual cubic phantom (30X30X30cm) were calculated using Eclipse TPS (calculation model: AcurosXB-11031) by assigning the CT numbers to HU of typical materials acquired by various protocols. Results: For the inserts of densities less than muscle, CT number fluctuations of all protocols were within the tolerance of 10 HU as accepted by AAPM-TG66. For more condensed materials, fixed kV yielded stable HU with any mA combination where largest disparities were found in 1750mg/cc insert: HU{sub reference}=1801(106.6cGy), HU{sub minimum}=1799 (106.6cGy, error{sub dose}=0.00%), HU{sub maximum}=1815 (106.8cGy, error{sub dose}=0.19%). Yet greater disagreements were observed with increasing density when kV was modified: HU{sub minimum}=1646 (104.5cGy, error{sub dose}=- 1.97%), HU{sub maximum}=2487 (116.4cGy, error{sub dose}=9.19%) in 1750mg/cc insert. Conclusion: Without affecting treatment dose calculation, personalized mA optimization of CT simulator can be conducted by fixing kV for a better cost-effectiveness of imaging dose and quality especially for children. Unless recalibrated, kV should be constant for all anatomical sites if diagnostic CT scanner is used as a simulator. This work was partially supported by Capital Medical Development Scientific Research Fund of China.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
The Method of Finite Averages
The Method of Finite Averages (MoFA) is a rigorous multiscale modeling methodology for efficiently modeling multi-physical phenomena in heterogeneous porous media. The code developed in this project aims to perform the numerical calculations required to formulate, implement, and verify MoFA models for Earth and Energy systems (i.e., model verification refers to performing fully-resolved simulations of the systems and comparing their results to those of the models). In general, MoFA transforms partial differential equations (PDEs) describing the fine-scale physics of a system into coupled ordinary differential equations (ODEs)---in time---that describe the coarse-scale---or "average"---physical behaviors of the system. This transformation significantly expedites system simulation, as the coarse-scale ODEs involve vastly fewer degrees of freedom than the fine-scale PDEs. The code developed under this project will allow users to 1.) generate system geometries and numerical meshes, 2.) solve the PDE and ODE systems required for MoFA model formulation and implementation, 3.) solve the PDE systems required to obtain fully-resolved simulation results for model verification, and 4.) compare and plot results (e.g., the model and fully-resolved simulation solutions, the error between the solutions, etc.).
Pietrzyk, KyleM [Lawrence Livermore National Labor↗