Hydro-mechanical modeling of the first and second hydraulic stimulations in a fractured geothermal reservoir in Pohang, South Korea
Not Available
15 GEOTHERMAL ENERGY↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Plasma response impact on RMP divertor footprint modeling for KSTAR
Not Available
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Assessing the Effects of Temperature and Oxygen Vacancy on Band Gap Renormalization in LaCrO 3-δ : First-Principles and Experimental Corroboration [plus supplemental information]
Understanding the temperature dependence of functional properties in high-temperature gas sensors is vital for applications in combustion environments. Temperature effect on the electronic structure due to electron-phonon coupling is a key property of interest as this influences other responses of sensors. In this work, we assess the impact of temperature on band gap renormalization of pristine and oxygen-vacant LaCrO 3–δ perovskite employing Allen–Heine–Cardona theory with first-principles simulations and corroborate with experimental observation. Antiferromagnetic cubic LaCrO 3 shows a direct ground-state band gap of 2.62 eV that is reduced by over 1 eV due to the presence of oxygen vacancies, which can form endothermically. We find excellent agreement in temperature-dependent band gap shift in LaCrO 3 between theory and an in-house experiment, proving that the theory can adequately predict renormalization on the band gap in a magnetic system. Band gaps in cubic LaCrO 3–δ are found to monotonically narrow by 1.13 eV in pristine and by around 0.62 eV in oxygen-vacant structures as temperature increases from 0 to 1500 K. The predicted band gap variations are rationalized using an analytical model. Furthermore, the experimental zero-temperature band gaps are extracted from the model fits that can provide useful insights on the simulated band gaps.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Lattice Boltzmann simulation of the dissolution of slag in alkaline solution using real-shape particles
Highlights: • A dissolution numerical model was proposed to capture the real dissolution kinetics of slag in alkaline solution. • The log forward dissolution rate of Si was described as a function of NBO/T and solution pH. • A threshold solid volume fraction of 0.688 was found for a voxel in 3D, 63.8% larger than that for a pixel in 2D. • The proposed dissolution numerical model provides a reliable alternative to study the dissolution kinetics of slag. A dissolution numerical model was proposed in this study to capture the real dissolution kinetics of slag in alkaline solution. It consists of three modules, i.e. (i) simulation of the initial particle parking structure of slag in alkaline solution using real-shape particles of slag, (ii) simulation of the chemical reactions between slag and solution based on the transition state theory, and (iii) simulation of the physical transport of aqueous ions using the lattice Boltzmann method. This dissolution numerical model was verified using experimental results, showing reasonable accuracy. After verification, the dissolution numerical model was implemented to study the influences of temperature and particle shape using a proper recipe of slag in alkaline solution. This recipe was designed to avoid solid phase precipitation or gel formation via thermodynamic analysis. The simulation results showed faster dissolution kinetics of slag when using higher temperatures and more irregular particle shapes.
36 MATERIALS SCIENCE↗
Critically assessing sodium-ion technology roadmaps and scenarios for techno-economic competitiveness against lithium-ion batteries
Sodium-ion batteries have garnered notable attention as a potentially low-cost alternative to lithium-ion batteries, which have experienced supply shortages and price volatility for key minerals. Here we assess their techno-economic competitiveness against incumbent lithium-ion batteries using a modelling framework incorporating componential learning curves constrained by minerals prices and engineering design floors. We compare projected sodium-ion and lithium-ion price trends across over 6,000 scenarios while varying Na-ion technology development roadmaps, supply chain scenarios, market penetration and learning rates. Assuming that substantial progress can be made along technology roadmaps via targeted research and development, we identify several sodium-ion pathways that might reach cost-competitiveness with low-cost lithium-ion variants in the 2030s. In addition, we show that timelines are highly sensitive to movements in critical minerals supply chains—namely that of lithium, graphite and nickel. Our modelled outcomes suggest that being price advantageous against low-cost lithium-ion variants in the near term is challenging and increasing sodium-ion energy densities to decrease materials intensity is among the most impactful ways to improve competitiveness.
25 ENERGY STORAGE↗
Distinguishing Electron and Hole Dynamics in Functionalized CdSe/CdS Core/Shell Quantum Dots Using Complementary Ultrafast Spectroscopies and Kinetic Modeling
The evolution of excitation energy and photogenerated charges in semiconductor quantum dots (QDs) functionalized with molecular acceptors can be probed on ultrafast time scales using techniques such as transient absorption (TA) spectroscopy. However, historical interpretations that the 1S(e)-1S 3/2 (h) transition in Cd-chalcogenide QDs is fully attributable to electrons may be misleading, and multiexponential models used to fit TA kinetics do not correspond directly to specific photophysical processes. Here, we present visible-wavelength and mid-IR TA and time-resolved photoluminescence measurements to inform a comprehensive kinetic model of the photoexcited CdSe/CdS core/shell QDs functionalized with passivating oleic acid (OA), hole-accepting ferrocene, or electron-accepting naphthalene bisimide (NBI). We show that ~30% of the 1S signal and 72% of the IR signal can originate from holes in well-passivated core/shell QDs. We also demonstrate evidence of electron trapping in OA-capped core/shell QDs, with additional electron transfer and hole trapping in the QDs functionalized with NBI. Electron (hole) trapping and detrapping occur in 450 ± 100 ps (430 ± 70 ps) and 340 ± 100 ps (1.1 ± 0.4 ns) respectively, while the time constant for electron transfer to NBI is ~1.8 ns. The comprehensive picture of photophysical processes provided by the complementary ultrafast techniques and kinetic modeling can accelerate both the fundamental science and application development of nanostructured and molecular systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Recent Advanced Reactor Multiphysics Model Highlights in the Virtual Test Bed (VTB)
The Virtual Test Bed (VTB) host over 30 distinct simulations that showcase state-of-the art capabilities across the national lab complex. An update on the status of models on the VTB is summarized here, along with a more detailed overview of select recent new capabilities to showcase. All of the major advanced reactor types are represented in the VTB. The first example consists of a multiphysics simulation to track the transport of species in Molten Salt Reactors using depletion, advection, and thermochemical calculations. The second consists of a coupled neutronic and thermal hydraulic simulation to validate a gas cooled reactor. The third consist of pebble-bed equilibrium model for a fluoride high-temperature reactor. The fourth is a high-fidelity neutronic and thermal hydraulic model of a liquid metal reactor assembly. And lastly the fifth consists of transient multiphysics simulations of heat pipe microreactors.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
2010-2012 California Household Travel Survey
The 2010-2012 California Household Travel Survey (CHTS) was administered by the California Department of Transportation, which collected demographic and travel behavior characteristics for residents across the entire state. At the time, it was the largest such regional or statewide survey ever conducted in the United States. Detailed travel behavior information was obtained from more than 42,500 households via multiple data-collection methods, including computer-assisted telephone interviewing, online and mail surveys, wearable (7,574 participants) and in-vehicle (2,910 vehicles) global positioning system devices, and on-board diagnostic sensors that gathered data directly from a vehicle's engine. Details of personal travel behavior were gathered within the region of residence, inter-regionally within the state, and in adjoining states and Mexico. The survey sampling plan was designed to ensure an accurate representation of the entire population of the state. The CHTS included additional features, such as vehicle-acquisition decisions, parking choices, work schedules and flexibility, use of toll lanes/priced facilities, and walk and bicycle trips, to support advanced model development.
1Hz data↗
Model-free control for frequency response support in microgrids utilizing wind turbines
Islanded microgrids integrated with renewable energy resources bring additional challenges to the primary frequency control due to their power-electronic interfaced generations. Developing an efficient control strategy for inertia emulation and frequency response support of microgrids is becoming an important issue. Wind turbine dynamics, however, will degrade the emulated inertial and primary responses with most traditional control strategies. On the other hand, compensation methods often require the knowledge of system models at the design stage and state estimation for feedback once deployed online. To overcome these challenges, this paper explores a model-free control (MFC) strategy to emulate the desired inertia and support the frequency response of a diesel-wind microgrid system. Additionally, the proposed MFC strategy utilizes a model reference concept to obtain guaranteed inertial response and improve the frequency response of microgrids. This work considers different control strategies with different operating points. The proposed controller is implemented and verified using the modified 33-bus full nonlinear model of the three-phase diesel-wind system in Simulink. Simulation results demonstrate the improved frequency response by precisely emulating the desired inertia using the MFC strategy.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Investigating biomass composition and size effects on fast pyrolysis using global sensitivity analysis and CFD simulations
It is notoriously difficult to build an accurate universal model for biomass pyrolysis due to its sensitivity to a wide number of critical material attributes such as chemical species and physical sizes. In this work, a biomass pyrolysis kinetics with 32 heterogeneous reactions and 59 species was implemented in an open-source multiphase computational fluid dynamics (CFD) software MFiX and validated against two different experimental pyrolysis data sets that provided detailed data describing chemical component yields. The reaction scheme was then used to build a surrogate model and assess the sensitivity of pyrolysis yields to feedstock compositions. The sensitivity analysis determined that the yield of bio-char showed a strong positive sensitivity to the carbon-rich lignin and tannin pseudo-species in the reaction scheme while the bio-oil and bio-gas were correlated to oxygen-rich lignin pseudo-species. The reaction scheme was then integrated into a coarse-grained discrete element model to simulate fast pyrolysis in a bubbling fluidized bed over a range of feedstock particle sizes. The reactor simulations showed further sensitivity to particle size and hydrodynamics. Notably, particles under 0.5 mm have small heat transfer limitations but left the reactor before completely converting and thus reduced the bio-oil yield. Results from this study can be used to guide future development of highly accurate models for fast pyrolysis reactors with a variety of feedstock properties and operating conditions.
09 BIOMASS FUELS↗
Moving from 2D to 3D Flow Modeling for the Waste Isolation Pilot Plant Performance Assessment.
Abstract not provided.
LaForce, Tara↗
Modeling and Benchmarking Geologic Hydrogen Processes with the Dusty Gas Model
Explore the source record for details and available documents.
Fukuyama, David Erik [Sandia National Laboratories↗
Moving from 2D to 3D Flow Modeling for the Waste Isolation Pilot Plant Performance Assessment.
Abstract not provided.
LaForce, Tara↗
Eco-driving Profile Optimization by Dynamic Programming for Battery Electric Vehicles
Although full automation has not yet been achieved, automated vehicles are a valid research area. Not only would automated vehicles provide ultimate driver convenience, but they would maximize energy efficiency by eliminating undesired human driving behaviors and optimally controlling the powertrain. From the perspective of control related to energy saving, speed profile optimization is important for improving system efficiency and satisfying passenger demands. This study employs Dynamic Programming (DP) to solve the constrained optimal problem for travel time, distance, and speed limit by exploring all possible control options. The solutions obtained by DP demonstrate consistent control patterns combining four control modes-acceleration, cruising, coasting, and braking, with cruising or coasting being selective depending on the boundary conditions. Further, this study introduces DP-based simulation results and attempts to provide comprehensive interpretations of the optimal policy by analyzing the essential factors that affect the control problem, including boundary conditions, road load, and powertrain characteristics. Based on these interpretations, the control concepts can be explained as the optimal policy selecting the best control option based on system efficiency and boundary conditions. The results of DP are compared with a human-like driver model to show that the optimal speed profiles can effectively reduce energy consumption.
Autonomous vehicles↗
High fidelity multiphysics tightly coupled model for a lead cooled fast reactor concept and application to statistical calculation of hot channel factors
A tightly coupled multiphysics code system is established using the MOOSE framework for hot channel factor (HCF) evaluation on a Lead Fast Reactor (LFR) concept. The coupled system is driven by the Griffin multiphysics coupling capability under which the MOOSE Heat Transfer module and NekRS computational fluid dynamics solver are coupled for conjugate heat transfer using the Cardinal application. The coupled capability is demonstrated on an LFR assembly model based on materials and geometry of a prototypical lead-cooled fast reactor design by Westinghouse Electric Company, LLC. Moreover, the work integrates the Multiphysics Object Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM) to perform calculations for statistical analysis of HCF. Furthermore, the coupling strategy and workflow demonstrated in this paper is not only useful for predicting accurate hot channel factors for different kinds of advanced reactors but also for other engineering applications such as control rod worth assessment, generation of high-fidelity database for Artificial intelligence (AI)/machine learning (ML) training, design optimization and multi-resolution modeling.
Cardinal↗
Anisotropic angular scattering models of elastic electron-neutral collisions for Monte Carlo plasma simulations
Many laboratory and industrial plasma applications require accurate modeling techniques to understand the interplay between microscopic and macroscopic processes. A prime example of this interplay is how particle and Monte Carlo (MC) simulation codes describe angular scattering of electrons following elastic scattering events. The forward peaked nature of high energy electron elastic scattering is relatively trivial to accurately describe in plasma simulations. However, for lower energy collisions, which produce near isotropic or backward peaked differential cross sections, there is not a strong consensus among the plasma modeling community on how to best describe these angular scattering trends. Here, in this study, we propose a systematic method to approximate the aforementioned non-trivial angular scattering behavior with a formula that can be readily implemented in particle-in-cell (PIC) and/or MC plasma simulation codes. The present approach is specifically applied to fusion relevant atomic hydrogen and helium, as well as for molecular hydrogen, and results are also applicable to the atomic isotopes and homonuclear molecular isotopologues of these species. Comparisons between the present angular distribution function and benchmark scattering data were used to validate the proposed models. In addition, two-term Boltzmann calculations and PIC direct simulation MC simulations revealed that the proposed angular distribution function is accurate, agreeing very well with benchmark convergent close-coupling scattering calculations, and electron transport measurements. These studies confirmed that the present angular distribution function model can be utilized without the need of renormalization to the momentum transfer cross section (as opposed to using the elastic scattering integrated cross section), which has been suggested by several studies in order to correct for deficient angular scattering models, and to agree with transport measurements. Hence, the present anisotropic angular scattering model can be utilized to accurately model the momentum transfer as well as the electron trajectories of elastic collisions.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
CMB distance priors revisited: effects of dark energy dynamics, spatial curvature, primordial power spectrum, and neutrino parameters
As a physical and sufficient compression of the full CMB data, the CMB distance priors, or shift parameters, have been widely used and provide a convenient way to include CMB data when obtaining cosmological constraints. In this paper, we revisit this data vector and examine its stability under different cosmological models. We find that the CMB distance priors are an accurate substitute for the full CMB data when probing dark energy dynamics. This is true when the primordial power spectrum model is directly generalized from the power spectrum of the model used in the derivation of the distance priors from the CMB data. We discover a difference when a non-flat model with the untilted primordial inflation power spectrum is used to measure the distance priors. This power spectrum is a radical change from the more conventional tilted primordial power spectrum and violates fundamental assumptions for the reliability of the CMB shift parameters. We also investigate the performance of CMB distance priors when the sum of neutrino masses Σm ν and the effective number of relativistic species N eff are allowed to vary. Our findings are consistent with earlier results: the neutrino parameters can change the measurement of the sound horizon from CMB data, and thus the CMB distance priors. We find that when the neutrino model is allowed to vary, the cold dark matter density ω c and N eff need to be included in the set of parameters that summarize CMB data, in order to reproduce the constraints from the full CMB data. As a result, we present an updated and expanded set of CMB distance priors which can reproduce constraints from the full CMB data within 1σ, and are applicable to models with massive neutrinos, as well as non-standard cosmologies.
79 ASTRONOMY AND ASTROPHYSICS↗