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DOE OSTI2024

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗

DOE OSTI2024

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

42 ENGINEERING↗

DOE OSTI2021

Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways

Abstract The National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Hexagonal Lattices of HIV Capsid Proteins Explored by Simulations Based on a Thermodynamically Consistent Model

HIV capsid proteins (CAs) may self-assemble into a variety of shapes under in vivo and in vitro conditions. Here, we employed simulations based on a residue-level coarse-grained (CG) model with full conformational flexibility to investigate hexagonal lattices, which are the underlying structural pattern for CA aggregations. Facilitated by enhanced sampling simulations to rigorously calculate CA dimerization and polymerization affinities, we calibrated our model to reproduce the experimentally measured affinities. Here using the calibrated model, we performed unbiased simulations on several large systems consisting of 1512 CA subunits, allowing reversible binding and unbinding of the CAs in a thermodynamically consistent manner. In one simulation, a preassembled hexagonal CA sheet developed spontaneous curvatures reminiscent of those observed in experiments, and the edges of the sheet exhibited local curvatures larger than those of the interior. In other simulations starting with randomly distributed CAs at different concentrations, existing CA assemblies grew by binding free capsomeres to the edges and by merging with other assemblies. At high CA concentrations, rapid establishment of predominant aggregates was followed by much slower adjustments toward more regular hexagonal lattices, with increasing numbers of intact CA hexamers and pentamers being formed. Our approach of adapting a general CG model to specific systems by using experimental binding data represents a practical and effective strategy for simulating and elucidating intricate protein aggregations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

High-Latitude, Low-Altitude SAI: Overview of G6-1.5K-HiLLA Simulations in E3SMv3

This report details a contribution of Energy Exascale Earth System Model version 3 (E3SMv3) simulations to a proposed model intercomparison project funded and organized by Reflective, a nonprofit group studying the possible global impacts of SAI. Using annual feedback control and seasonally-variable injection sites to achieve a desired global near-surface temperature target, the simulated SAI campaign indicates robust maintenance of the 2020-2039 climatic state over 60 years into the future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Extending a land-surface model with <i>Sphagnum</i> moss to simulate responses of a northern temperate bog to whole ecosystem warming and elevated CO<sub>2</sub>

Abstract. Mosses need to be incorporated into Earth system models to better simulate peatland functional dynamics under the changing environment. Sphagnum mosses are strong determinants of nutrient, carbon, and water cycling in peatland ecosystems. However, most land-surface models do not include Sphagnum or other mosses as represented plant functional types (PFTs), thereby limiting predictive assessment of peatland responses to environmental change. In this study, we introduce a moss PFT into the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. The model was parameterized and independently evaluated against observations from an ombrotrophic forested bog as part of the Spruce and Peatland Responses Under Changing Environments (SPRUCE) project. The inclusion of a Sphagnum PFT with some Sphagnum-specific processes in ELM allows it to capture the observed seasonal dynamics of Sphagnum gross primary production (GPP) albeit with an underestimate of peak GPP. The model simulated a reasonable annual net primary production (NPP) for moss but with less interannual variation than observed, and it reproduced aboveground biomass for tree PFTs and stem biomass for shrubs. Different species showed highly variable warming responses under both ambient and elevated atmospheric CO2 concentrations, and elevated CO2 altered the warming response direction for the peatland ecosystem. Microtopography is critical: Sphagnum mosses on hummocks and hollows were simulated to show opposite warming responses (NPP decreasing with warming on hummocks but increasing in hollows), and hummock Sphagnum was modeled to have a strong dependence on water table height. The inclusion of this new moss PFT in global ELM simulations may provide a useful foundation for the investigation of northern peatland carbon exchange, enhancing the predictive capacity of carbon dynamics across the regional and global scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Multiscale modeling of microwave-heated multiphase systems

Modeling of microwave heating of multiphase systems requires resolving the electromagnetic field from the single particle to the entire cavity. We introduce a multiscale methodology for computationally affordable simulations of microwave heating of multiphase systems consisting of one phase dispersed in a continuum phase. The methodology homogenizes the original multiphase system, by taking advantage of the large separation of length scales, to calculate the effective permittivity, effective thermal conductivity, and volumetric power absorbed in each phase. The methodology is rigorously assessed against particle-resolved detailed numerical simulations of model systems. We demonstrate a significant reduction in computational cost while retaining the accuracy of detailed simulations. Lastly, the present methodology enables high throughput exploration of novel multiphase system designs utilizing microwave heating.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

COVID 19 vaccine distribution solution to the last mile challenge: Experimental and simulation studies of ultra-low temperature refrigeration system

Most COVID-19 vaccines require ambient temperature control for transportation and storage. Both Pfizer and Moderna vaccines are based on mRNA and lipid nanoparticles requiring low temperature storage. The Pfizer vaccine requires ultra-low temperature storage (between -80 °C and -60 °C), while the Moderna vaccine requires -30 °C storage. Pfizer has designed a reusable package for transportation and storage that can keep the vaccine at the target temperature for 10 days. However, the last stage of distribution is quite challenging, especially for rural or suburban areas, where local towns, pharmacy chains and hospitals may not have the infrastructure required to store the vaccine. Also, the need for a large amount of ultra-low temperature refrigeration equipment in a short time period creates tremendous pressure on the equipment suppliers. In addition, there is limited data available to address ancillary challenges of the distribution framework for both transportation and storage stages. As such, there is a need for a quick, effective, secure, and safe solution to mitigate the challenges faced by vaccine distribution logistics. The study proposes an effective, secure, and safe ultra-low temperature refrigeration solution to resolve the vaccine distribution last mile challenge. Furthermore, the approach is to utilize commercially available products, such as refrigeration container units, and retrofit them to meet the vaccine storage temperature requirement. Both experimental and simulation studies are conducted to evaluate the technical merits of this solution with the ability to control temperature at -30 °C or -70 °C as part of the last mile supply chain for vaccine candidates.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

A Computational Framework for Simulations of Dissipative Nonadiabatic Dynamics on Hybrid Oscillator-Qubit Quantum Devices

Here, we introduce a computational framework for simulating nonadiabatic vibronic dynamics on circuit quantum electrodynamics (cQED) platforms. Our approach leverages hybrid oscillator-qubit quantum hardware with midcircuit measurements and resets, enabling the incorporation of environmental effects such as dissipation and dephasing. To demonstrate its capabilities, we simulate energy transfer dynamics in a triad model of photosynthetic chromophores inspired by natural antenna systems. We specifically investigate the role of dissipation during the relaxation dynamics following photoexcitation, where electronic transitions are coupled to the evolution of quantum vibrational modes. Our results indicate that hybrid oscillator-qubit devices, operating with noise levels below the intrinsic dissipation rates of typical molecular antenna systems, can achieve the simulation fidelity required for practical computations on near-term and early fault-tolerant quantum computing platforms.

Hamiltonians↗

DOE OSTI2024

Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis

The nodal admittance matrix (NAM)-based approach is suitable for analyzing the small-signal stability of large-scale power electronics-based power systems (PEPSs) as it preserves the system structure by utilizing the admittance matrix. Previously, NAM-based area partition has been proposed, which divides the system into various subareas and interconnections for easier analysis of the low-dimension matrix compared to the entire system-based high-dimension matrix. However, no partition algorithm has been presented for the NAM-based area partition method. This paper focuses on implementing the spectral partitioning algorithm for partitioning large-scale PEPSs into a low-dimension matrix to reduce the computation complexity of the analysis. These spectral components facilitate data transformation into a new space, enabling the application of traditional clustering methods like k-means. To evaluate the performance of the partitioning method, the subareas and interconnections obtained from the spectral clustering algorithm are incorporated into the NAM-based area partition method for a large system with 140 buses. The computational times of the original method, where the NAM-based criterion is directly applied to the entire system, are compared with those of the NAM-based partition method in MATLAB. PSCAD simulations of the whole system and the obtained subareas are conducted to validate the effectiveness of the proposed algorithm.

Nupur, Nupur↗

DOE OSTI2021

Electrification Futures Study: Power Systems Operation with Newly Electrified and Flexible Loads

The Electrification Futures Study (EFS) is a multi-year study designed to analyze the impacts of widespread electrification in the U.S. energy system. In this webinar we present the detailed power systems operational analysis from the final report in the EFS series. For this analysis, we simulate multiple 2050 power systems for the conterminous United States to assess how variations in the magnitude and shape of electricity demand driven by electrification, and the extent of load participation to more-actively provide grid services, might impact the hourly operation, operational costs, and emissions of various power systems in 2050. The impacts of electrification and demand flexibility are overlayed across systems with significantly greater penetrations of variable renewable energy than today. Overall, we find that the high electrification scenarios envisioned in the EFS with significant VRE penetration (66% of annual national generation) can be operated to meet future increased levels of electrified demand. We also find that demand-side flexibility can enhance operational efficiency and reduce overall annual production costs by $5-$10 billion. The complementary relationship between flexible electric vehicle charging loads and solar generation is particularly pronounced, but in the absence of demand-side flexibility electrification can lead to increased wind and solar curtailment. By helping to reduce renewable curtailment, flexibility can also reduce power sector CO2 emissions. The analysis highlights the value of increased integration and coordination of demand- and supply-side resources in future electric system planning and operations—particularly under high electrification futures.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory

Renewably driven, electrochemical conversion of carbon dioxide into value-added products is expected to be a critical tool in global decarbonization. However, theoretical studies based on the computational hydrogen electrode largely ignore the nonlinear effects of the applied potential on the calculated results, leading to inaccurate predictions of catalytic behavior or mechanistic pathways. Here, we use grand canonical density functional theory (GC-DFT) to model electrochemical CO2 reduction (CO2R) over metal- and nitrogen-doped graphene catalysts (MNCs) and explicitly include the effects of the applied potential. We used GC-DFT to compute the CO2 to CO reaction intermediate energies at -0.3, -0.7, and -1.2 VSHE catalyzed by MNCs each doped with 1 of the 10 3d block metals coordinated by four pyridinic nitrogen atoms. Our results predict that Sc-, Ti-, Co-, Cu-, and Zn-N4Cs effectively catalyze CO2R at moderate to large reducing potentials (-0.7 to -1.2 VSHE). ZnN4C is a particularly promising electrocatalyst for CO2R to CO both at low and moderate applied potentials based on our thermodynamic analysis. Our findings also explain the observed pH independence of CO production over FeN4C and predict that the rate-determining step of CO2R over FeN4C is not *CO2- formation but rather *CO desorption. Additionally, the GC-DFT-computed density of states analysis illustrates how the electronic states of MNCs and adsorbates change non-uniformly with applied potential, resulting in a significantly increased *CO2- stability relative to other intermediates and demonstrating that the formation of the adsorbed *CO2- anion is critical to CO2R activation. This work demonstrates how GC-DFT paves the way for physically realistic and accurate theoretical simulations of reacting electrochemical systems.

CO2 reduction↗

DOE OSTI2025

Microreactor Automated Control System Test Bed Digital Architecture for Real-Time, Hardware-in-the-Loop Simulation

This work describes progress made towards the development of a real-time hardware-in-the-loop (HIL) test bed for non-nuclear testing of microreactor control schemes and failure modes. Non-nuclear testing is a crucial step in developing robust control algorithms for managing microreactor dynamics. The creation of an HIL simulation harnesses the realistic dynamics of physical analogue systems while additionally considering the challenges of variable communication delay. This collaborative effort between Oak Ridge National Laboratory and Idaho National Laboratory has resulted in a LabVIEW-based gRPC communication protocol which couples a TRANSFORM Modelica simulation of nuclear components to the ViBRANT physical hardware for realistic feedback and visual representation of control action in real time. A modular python client structure is developed to manage FMU-based Modelica simulation and real-time gRPC communication. HIL testing suggests that the modeled reactor with natural convection molten salt loop coolant configuration responds well to PID control of drum positioning for modulation of reactor core power, however, future efforts will be made to explore the added thermal inertial delay of system level control and downstream demand changes. Development of this platform with a generalized methodology provides a foundation for exploring a variety of reactor configurations and failure modes in rapid order to provide insight into the most effective avenues of study for further research and development.

McConnell, Jono [ORNL] (ORCID:0000000238984741)↗

DOE OSTI2022

Anomalous phase separation in a correlated electron system: Machine-learning–enabled large-scale kinetic Monte Carlo simulations

Significance Phase separation is crucial to the functionalities of many correlated electron materials with notable examples including colossal magnetoresistance in manganites and high- T c superconductivity in cuprates. However, the nonequilibrium phase-separation dynamics in such systems are poorly understood theoretically, partly because the required multiscale modeling is computationally very demanding. With the aid of machine-learning methods, we have achieved large-scale dynamical simulations in a representative correlated electron system. We observe an unusual relaxation process that is beyond the framework of classical phase-ordering theories. We also uncover a correlation-induced freezing behavior, which could be a generic feature of phase separation in correlated electron systems.

Zhang, Sheng↗

DOE OSTI2021

Kinetic simulation study of magnetized collisionless shock formation on a terawatt laser system

Perpendicular, magnetized, collisionless shocks in hydrogen and neon plasmas are studied with 2-D particle-in-cell simulations for parameters accessible to experiments on OMEGA EP. The simulations are performed with realistic ion-electron mass ratios by which the relative importance of different micro-instabilities can be accurately captured. The dispersion relation of the modified two-stream instability (MTSI), the main dissipation mechanism for these shocks, is used to find suitable parameters for upcoming experiments. Simulations show that magnetized collisionless shocks can be readily formed within a few tenths of an ion gyro-period in both hydrogen and neon gases, with a background magnetic field of 50 T, achievable using the magneto-inertial fusion electrical discharge system (MIFEDS). Here, a portion of the ions are reflected to the upstream region and accelerated in both shock normal and tangential directions, indicating the formation of a supercritical shock. Shock front reformation is seen in longer time 1-D simulations. The results show that the formation time and width of these shocks are determined by MTSI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Convergence Criteria for Multiphysics Simulations

The behavior of engineered systems is often influenced by multiple physical phenomena, such as mechanical deformation, heat transfer, and chemical species transport and reactions. There are often strong interactions between these phenomena, and there is increasing interest in applying coupled-physics models to improve understanding of physical behavior under complex environmental conditions. Multiple simulation frameworks that facilitate coupled-physics simulations are in widespread use, and these employ a variety of techniques to account for interactions between those physics. Many frameworks solve the physics models independently and transfer results between them. Alternatively, a single monolithic system of equations for every physics model can be formed and solved. Each of these approaches has its benefits and drawbacks, and the optimal approach varies depending on the nature of the problem. The open-source MOOSE framework was developed targeting solution of large-scale multiphysics problems. Although it provides options for all these coupling approaches, its standard approach for multiphysics solutions is to form and solve a single monolithic system of equations containing the unknowns for all physics models. MOOSE provides a streamlined approach for users to define the solution variables, the terms in the partial differential equations pertaining to each variable, and interactions between solution variables. One aspect of the monolithic solution approach that can be problematic, however, is defining appropriate convergence criteria for the nonlinear system. A standard approach is to determine convergence is to simply take a norm of the residual vector corresponding to the full vector of unknowns. However, if the residual vector contains variables for multiple physics models, the magnitudes of those variables can differ significantly, and the variables can converge at significantly different rates from each other. It is important to ensure that the variables for each of the physics are converged, and also ensure that the convergence criteria are not excessively stringent in cases when there is little change in the solution. This talk presents representative multiphysics problems to highlight these issues, and shows strategies for convergence criteria in MOOSE that are robust for multiphysics models under a variety of conditions.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Influence of Markovianity and self-consistency on time-resolved spectral functions of driven quantum systems

We present a systematic comparison of the real-time Dyson expansion (RTDE) with established nonequilibrium Green's function (GF) approaches for simulating driven, interacting quantum systems. Focusing on density matrix dynamics, time-off-diagonal GFs, and time-resolved photoemission spectra, we benchmark RTDE against fully self-consistent Kadanoff-Baym equation (KBE) calculations, the generalized Kadanoff-Baym ansatz, and exact diagonalization for small systems using second-order many-body perturbation theory. Using a driven two-band Hubbard model, we show that mean-field single-particle density matrix trajectories provide a reliable baseline for RTDE across a broad range of interaction strengths and excited-carrier populations. Further, RTDE accurately captures correlation effects in the GFs, including long-lived oscillations and revivals that are strongly suppressed by the overdamping inherent to self-consistent KBE schemes. As a consequence, RTDE resolves rich nonequilibrium spectral structure in time-resolved photoemission, such as interaction- and population-dependent quasiparticle splittings and band gap renormalization, which are largely washed out in self-consistent approaches yet are present in exact solutions. Furthermore, our results demonstrate that RTDE bridges the gap between mean-field propagation and full two-time KBE simulations, retaining favorable linear scaling while capturing essential dynamical correlations relevant for ultrafast spectroscopy.

Electronic structure↗

DOE OSTI2022

Power HIL Validation of a MW-Scale Grid-Forming Inverter's Stabilization of Otherwise Unstable Cases of the Maui Transmission System

This presentation summarizes MW-scale power hardware-in-the-loop experiments using a 2.2 MW grid-forming inverter connected to a real-time electromagnetic transient simulation of the Maui transmission system. The hardware inverter used is a commercially available "off-the-shelf" inverter from a major manufacturer that is capable of operating in grid-forming mode or grid-following mode. The hardware inverter was connected via power hardware-in-the-loop to a real-time model of the year-2023 Maui power system, which consists of a networked transmission system with diverse generation sources. The results of the simulations indicate that with sufficient synchronous machines online, the system is stable without grid-forming inverters, but that as the amount of synchronous machines is reduced, the system becomes unstable. Changing the hardware inverter (scaled up to represent a 30 MW plant) into grid-forming mode mitigates the instability in various low-inertia cases, including a zero-inertia scenario with 100% of generation from PV and wind. This result broadly agrees with pure simulation results.

battery energy storage system↗