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Fast and Universal Kohn-Sham Density Functional Theory Algorithm for Warm Dense Matter to Hot Dense Plasma
Understanding many processes, e.g., fusion experiments, planetary interiors, and dwarf stars, depends strongly on microscopic physics modeling of warm dense matter and hot dense plasma. This complex state of matter consists of a transient mixture of degenerate and nearly free electrons, molecules, and ions. This regime challenges both experiment and analytical modeling, necessitating predictive ab initio atomistic computation, typically based on quantum mechanical Kohn-Sham density functional theory (KS-DFT). However, cubic computational scaling with temperature and system size prohibits the use of DFT through much of the warm dense matter regime. A recently developed stochastic approach to KS-DFT can be used at high temperatures, with the exact same accuracy as the deterministic approach, but the stochastic error can converge slowly and it remains expensive for intermediate temperatures (< 50 eV). Here we have developed a universal mixed stochastic-deterministic algorithm for DFT at any temperature. This approach leverages the physics of KS-DFT to seamlessly integrate the best aspects of these different approaches. We demonstrate that this method significantly accelerated self-consistent field calculations for temperatures from 3 to 50 eV, while producing stable molecular dynamics and accurate diffusion coefficients.
Efficient Langevin dynamics for “noisy” forces
Efficient Boltzmann-sampling using first-principles methods is challenging for extended systems due to the steep scaling of electronic structure methods with the system size. Additionally, stochastic approaches provide a gentler system-size dependency at the cost of introducing “noisy” forces, which could limit the efficiency of the sampling. When the forces are deterministic, the first-order Langevin dynamics (FOLD) offers efficient sampling by combining a well-chosen preconditioning matrix S with a time-step-bias-mitigating propagator [G. Mazzola and S. Sorella, Phys. Rev. Lett. 118, 015703 (2017)]. However, when forces are noisy, S is set equal to the force-covariance matrix, a procedure that severely limits the efficiency and the stability of the sampling. Here, we develop a new, general, optimal, and stable sampling approach for FOLD under noisy forces. We apply it for silicon nanocrystals treated with stochastic density functional theory and show efficiency improvements by an order-of-magnitude.
Status of EM Pump Modeling Capability for VTR
SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. Most recently, SAS4A/SASSYS-1 has been selected as the safety analysis software for the Versatile Test Reactor (VTR), a new materials testing Sodium Fast Reactor (SFR) to be built by the Department of Energy. In order to support analysis of the VTR, which will utilize ElectroMagnetic (EM) pumps as the primary coolant pumps, the development of new EM pump modeling capabilities has been initiated for SAS4/SASSYS-1. The new physics-based EM pump model captures systems-level transient performance based on equivalent circuit theory and is highly flexible to model a wide range of electromagnetic pumps of the three-phase linear induction type subject to changes in power supply and plant conditions. Within the equivalent circuit framework, two sub-models are developed to provide options for analysts both with and without a detailed geometric characterization of their pump such that minimal information is required to achieve a realistic working model, but specific details of a particular pump design may be captured if sufficient information is provided. In addition, heat generated from pump operation and its transport through the plant system can be modeled to better capture the behavior of certain transients. This paper will outline the model and derive the governing equations of the new EM pump model. An initial comparison between the simple EM pump model and experimental data is made. This comparison shows that the equivalent circuit model can capture pump performance, with greater accuracy near the rated conditions. In order to demonstrate the transient behavior of the new model, a simple transient with an EM pump replacing the centrifugal pumps in the Advanced Burner Test Reactor is included.
Status of EM Pump Modeling Capability for VTR
SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. Most recently, SAS4A/SASSYS-1 has been selected as the safety analysis software for the Versatile Test Reactor (VTR), a new materials testing Sodium Fast Reactor (SFR) to be built by the Department of Energy. In order to support analysis of the VTR, which will utilize ElectroMagnetic (EM) pumps as the primary coolant pumps, the development of new EM pump modeling capabilities has been initiated for SAS4/SASSYS-1. The new physics-based EM pump model captures systems-level transient performance based on equivalent circuit theory and is highly flexible to model a wide range of electromagnetic pumps of the three-phase linear induction type subject to changes in power supply and plant conditions. Within the equivalent circuit framework, two sub-models are developed to provide options for analysts both with and without a detailed geometric characterization of their pump such that minimal information is required to achieve a realistic working model, but specific details of a particular pump design may be captured if sufficient information is provided. In addition, heat generated from pump operation and its transport through the plant system can be modeled to better capture the behavior of certain transients. This paper will outline the model and derive the governing equations of the new EM pump model. An initial comparison between the simple EM pump model and experimental data is made. This comparison shows that the equivalent circuit model can capture pump performance, with greater accuracy near the rated conditions. In order to demonstrate the transient behavior of the new model, a simple transient with an EM pump replacing the centrifugal pumps in the Advanced Burner Test Reactor is included.
Controlled patterning of crystalline domains by frontal polymerization
Materials with hierarchical architectures that combine soft and hard material domains with coalesced interfaces possess superior properties compared with their homogeneous counterparts. These architectures in synthetic materials have been achieved through deterministic manufacturing strategies such as 3D printing, which require an a priori design and active intervention throughout the process to achieve architectures spanning multiple length scales. Here we harness frontal polymerization spin mode dynamics to autonomously fabricate patterned crystalline domains in poly(cyclooctadiene) with multiscale organization. This rapid, dissipative processing method leads to the formation of amorphous and semi-crystalline domains emerging from the internal interfaces generated between the solid polymer and the propagating cure front. The size, spacing and arrangement of the domains are controlled by the interplay between the reaction kinetics, thermochemistry and boundary conditions. Small perturbations in the fabrication conditions reproducibly lead to remarkable changes in the patterned microstructure and the resulting strength, elastic modulus and toughness of the polymer. Furthermore, this ability to control mechanical properties and performance solely through the initial conditions and the mode of front propagation represents a marked advancement in the design and manufacturing of advanced multiscale materials. Drawing inspiration from biological systems in which structural complexity develops through dissipative reaction–diffusion processes, this study explores a transformative synthetic manufacturing strategy aimed at harnessing the principles underpinning morphogenic growth, unlocking new avenues for advanced materials design and fabrication. Synthetic coupled reaction-transport processes offer a versatile yet relatively underexplored method to manipulate the spatial attributes of synthetic materials10. Here we introduce an innovative manufacturing approach based on frontal ring-opening metathesis polymerization (FROMP) that draws parallels with morphogenic growth and development, enabling the formation of patterned microstructures within polymeric materials.
Model Package Report: Composite Analysis Solid Waste Release Model (CASWR Model)
This document describes the implementation of a solid waste form release model in GoldSim for the Hanford Site Composite Analysis (CA) Update. This Composite Analysis Solid Waste Release model (CASWR model) was designed to generate deterministic radionuclide release rates for Hanford’s Central Plateau solid waste disposal sites using single realizations of release model coefficients. Five generalized waste form types are used for the conceptual model of waste release: surplus reactor block, cement, soil-debris, grouted residual waste, and ancillary equipment. The surplus reactor block waste form consists of radionuclide leaching from surplus production graphite reactor core blocks via unspecified processes (White et al., 1984 as cited in PNNL-15965). The cement waste form represents solidified wastes whose permeability is much lower than that of the surrounding soil. The soil-debris waste form type is defined as unconsolidated waste mixed with soil material. Tanks and canyon complexes comprise the grouted residual waste form such that their solid waste will be grouted and capped with a surface barrier at the completion of their cleanup. Finally, the ancillary equipment waste form constitutes contaminant releases from ancillary and auxiliary waste form residues associated with tank farms at closure. Individual sub-models are implemented to numerically represent a respective waste form within the CASWR Model: Surplus Reactor Block Sub-model, Cement Sub-model, SoilDebris Sub-model, Grouted Residual Waste Sub-model, and Ancillary Equipment Submodel. Advection is assumed to be the primary transport process governing the release of radionuclides in the Ancillary Equipment and Soil-Debris Sub-models. Diffusion is assumed to be the primary release process in the Grouted Residual Waste and Cement Sub-models. An unspecified zero-order release process is considered in the Surplus Reactor Block Sub-model due to the lack of information regarding actual processes involved in irradiated graphite leaching. The Surplus Reactor Block, Cement, and SoilDebris Sub-models were compared against analytical solutions (PNNL-11800, Composite Analysis for Low-Level Waste Disposal in the 200 Area Plateau of the Hanford Site). The agreement between results of these analytical solutions and the corresponding waste form models verified their correct implementation in GoldSim. A 1-D modeling abstraction approach for the Grouted Residual Waste and Ancillary Equipment Sub-models was adopted from existing Performance Assessment (PA) models. Despite the simplifications made in these sub-models, they were found to be appropriate representations of the waste forms, similar to what was used in the Waste Management Area C PA model (RPP-ENV-58782, Performance Assessment of Waste Management Area C, Hanford Site, Washington, Rev. 0). A sensitivity analysis was conducted to identify the most influential parameters in each waste form sub-model. Suggestions for considering pH-dependent and redox-dependent release mechanisms are formulated through the development of a conditional constant approach in GoldSim.
Sensitivity Analysis of Irradiated Fueled Experiments using the MOOSE Framework [Slides]
Modeling and simulation (M&S) methods are able to predict uncertainties in experimental parameters (e.g., power and fission density) during irradiation. A shortfall exists in predicting how sensitive some of the parameters will behave during the experimental process. Sensitivity and Uncertainty Quantification (SUQ) is critical in support of qualification and licensing reactor fuels. The application of a method to quantify the uncertainty in these experiments is critical to the prediction of their performance. In this work, we propose the use of a polynomial chaos expansion (PCE) method to quantify the sensitive parameters in these simulations and, in an extension, their experimental surrogates. We propose to perform M&S using PCE uncertainty quantification on a previously irradiated fueled experiment in order to provide a validation case for Griffin and expand its use as a verification and validation (V&V) tool for experiments with a neutronics component. Griffin is an advanced, deterministic neutronics analysis code built using the MOOSE (multiphysics object-oriented simulation environment) framework which can provide state-of-the-art neutronic analysis on M&S of experiments. We will use the stochastic tools module (STM) in MOOSE to provide PCE uncertainty quantification on the proposed experimental setup. Idaho National Laboratory (INL) does not yet have an in-house developed code with V&V approval for experiments performed on-site; this work would provide a necessary addition of support for experiments performed at INL. The Nuclear Regulatory Commission (NRC) has explicitly requested uncertainties in calculated values such as fuel power and burnup, and the development of this capability would benefit the relationship between INL and the NRC.
Singular value decomposition of adjoint flux distributions for Monte Carlo variance reduction
Monte Carlo (MC) shielding calculations often use weight windows (WWs) and biased sources formed from a deterministic estimate of the adjoint flux to improve the convergence rate of tallies. This requires a significant amount of computer memory, which can limit the memory available for high-resolution tally output. A new method is proposed for reducing these memory requirements by using singular value decomposition (SVD) in linear or logarithmic space to approximate the adjoint flux. This method’s performance is evaluated using the Shift and Denovo codes for streaming and diffusion base case problems, followed by problems using the Westinghouse AP1000 and the Joint European Torus. The log SVD reduced WW memory requirements by an order of magnitude in all cases without a significant performance penalty. Additionally, the linear SVD reduced biased source memory requirements by an order of magnitude, but further investigation is needed to account for observed limitations.
Nonlinear Elimination Applied to Radiation Diffusion
We apply a nonlinearly preconditioned, quasi-Newton framework to accelerate the numerical solution of the thermal radiative transfer (TRT) equations. This framework was inspired by the unpublished method that has existed for years in Teton, Lawrence Livermore National Laboratory’s deterministic TRT code. In this paper, we cast this iteration scheme within a formal nonlinear preconditioning framework and compare its performance against other iteration schemes in the framework. With proper choices of iteration controls for the various levels of the solver, we can recover the standard linearized one-step method, a full nonlinear Newton scheme, as well as the method in Teton. In brief, the nonlinear preconditioning TRT scheme formally eliminates the material temperature equation from the nonlinear system in a nonlinear analog of a Schur complement. This nonlinear elimination step involves solving a decoupled nonlinear equation for each spatial degree of freedom and is therefore inexpensive. By applying a quasi-Newton iteration scheme on the new system, we obtain a three-level iteration scheme that is at least as efficient as commonly used TRT schemes. The new method allows full convergence to the nonlinear backward Euler time-discretized system, increasing accuracy and robustness, while using a similar number of linear iterations as the more common linearized one-step methods Eq. (4).
Cascading economic losses from port disruptions under capacity constrained multimodal freight networks
This study quantifies how throughput disruptions at major seaports cascade through capacity-constrained multimodal freight networks and interregional production systems. We couple an agent-based model (ABM) multimodal freight simulation that resolves rerouting, terminal queueing, and inventory drawdown under binding modal and facility capacities with a multiregional output loss input-output (MRIIM) model that propagates realized delivery shortfalls across regions and sectors. The framework is demonstrated for the Port of Los Angeles using Freight Analysis Framework flows and Bureau of Economic Analysis input-output accounts and is evaluated over a 52-week horizon under deterministic sector targeted shocks and stochastic disruption realizations with uncertain severity and duration. Results indicate nonlinear amplification: realized national losses concentrate in manufacturing and transportation/warehousing even when exogenous port shocks are dispersed, suggesting that congestion spillback and limited short-run substitution can dominate the initial shock allocation. We further evaluate a tabular reinforcement-learning (Q-learning) intervention layer that selects among a small set of implementable system level levers (truck-to-rail and truck-to-barge shift settings) without overriding shipper routing, finding that such interventions reduce total losses for moderate disruptions but yield diminishing returns once substitute modes approach capacity. By linking operational freight behavior to system wide impacts under uncertainty, the proposed ABM-MRIIM pipeline provides a reusable workflow for port disruption stress testing, identification of structurally critical sectors/corridors, and evaluation of resilience interventions under realistic capacity limits.
Three-Dimensional Bubble Fluidics in Architected Porous Media
Gas bubble flows in porous media often exhibit complex and seemingly unpredictable behaviors that are difficult to control. This lack of control limits the ability to design effective devices which manage multiphase flows. Here, we show how the design of 3D printed pores can deterministically control the flow path of an injected gas stream. Open cell structures can be designed to shape the gas/liquid interface with fidelity to control how the two phases are distributed throughout a porous material. The distributed gas volume is free to interact physically and chemically with the surrounding liquid phase, an effect we exploit to create a logical control gate to redirect flows within a lattice. This also allows us to design architectures for reactive capture and aerating bioreactors, resulting in patterned boundaries which can make more effective use of the liquid and gas reagents.
Techno-Economic Impact of Diesel Fuel, Labor, and Interest Rates on Bulk-Format and Round Bale Logistics Expenses for Switchgrass
Highlights System-wide sensitivity of bulk-format and round bale logistics responded to different degrees of expense inputs. Biomass size-reduction expenses for bulk-format were consistently less than round-bale chopping. Stack/reclaim operations with high-density-capacity equipment for bulk-format were the highest expenses. Clean-sheet design of stacker/reclaimer and self-compacting bulk trailer may significantly reduce expenses. Abstract . Deterministic cost analyses were conducted for a harvest, storage, preprocessing, and supply system providing 371,870 dry Mg (dMg) year-1 of milled switchgrass (SG) to a biorefinery from 21,929 ha of production fields within 72 km of the biorefinery. Varied input costs of diesel fuel, labor, and interest rate were input into a highly detailed cost analysis for bulk-format and baseline round bale logistics. These operational input factors, potentially reflecting an evolving economic climate or paradigm shift, were examined to provide insight into the cost to deliver preprocessed biomass feedstock for centralized commercial-scale conversions. Total annual costs per dry unit of SG were determined for all combinations of diesel fuel prices of $0.53 L-1, $0.92 L-1, and $1.32 L-1; total labor costs of $20.00 h-1, $28.85 h-1, and $40.00 h-1 singly and uniformly applied across all labor inputs; and three representative interest rates of 6%, 8%, and 12%. Increases in total cost most depended on increases in diesel fuel cost, followed by labor rate, and finally interest rate. Increases in fuel costs from $0.53 L-1 to $1.32 L-1 yielded a total cost increase of about $11.56 dMg-1 and $13.36 dMg-1 for bulk-format and round bale logistics, respectively, for all combinations of labor and interest rates. The overall increase in labor rate ($20.00 h-1 to $40.85 h-1) resulted in increased total costs of about $10.32 dMg-1 for bulk-format logistics and $9.94 dMg-1 for round bale logistics for all fuel and interest rates. The overall increase in interest rate (6% to 12%) resulted in increased total costs of about $6.72 dMg-1 for bulk-format logistics and $4.21 dMg-1 for round bale logistics for all fuel and labor rates. Increases in total costs for combined increases in fuel cost, labor rate, and interest rate were $28.60 dMg-1 and $27.48 dMg-1, yielding maximum total costs of $87.87 dMg-1 and $86.53 dMg-1 for bulk-format and round bale logistics, respectively. Costs were determined for existing equipment systems, including novel use of waste compaction and ejector semi-trailers. The highest potential for cost reductions may require clean-sheet equipment designs specifically tailored for SG, such as forage harvesters that direct-cut standing SG, mobilized stacker-reclaimer technology to not inhibit stack-area footprint, self-compacting ejector trailer technology, and bale grinding technology incorporating controlled mass feeding and shear failure elements. Keywords: Bales, Bioenergy, Bulk-format, Densification, Field chop, Logistics, Transportation