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DOE OSTI2025

PDPTW-DB: MILP-Based Offline Route Planning for PDPTW with Driver Breaks

The Pickup and Delivery Problem with Time Windows (PDPTW) involves optimizing routes for vehicles to meet pickup and delivery requests within specific time constraints, a challenge commonly faced in logistics and transportation. Microtransit, a flexible and demand-responsive service using smaller vehicles within defined zones, can be effectively modeled as a PDPTW. Yet, the need for driver breaks—a key human constraint—is frequently overlooked in PDPTW solutions, despite being necessary for regulatory compliance. This study presents a novel mixed-integer linear programming formulation for the Pickup and Delivery Problem with Time Windows and Driver Breaks (PDPTW-DB). To the best of our knowledge this formulation is the first to consider mandatory periodic driver breaks within optimized Microtransit routes. The proposed model incorporates regulatory compliant break scheduling directly within the vehicle routing optimization framework. By considering driver break requirements as an integral component of the optimization process, rather than as a post-processing step, the model enables the generation of routes that respect hours of service regulations while minimizing operational costs. This integrated approach facilitates the generation of schedules that are operationally efficient and prioritize driver welfare through driver breaks. We work with a public transit agency from the southern USA, and highlight the specific nuances of driver break optimization, and present a Pickup and Delivery Problem with Time Windows formulation for optimizing Microtransit operations and scheduling driver breaks. We validate our approach using real-world data from the transit agency. Our results validate our formulation in producing cost-effective, and regulation-compliant solutions.

Applied Computing, Transportation↗

DOE OSTI2025

Computing material volume fractions on a superimposed mesh as applied to Monte Carlo particle transport simulations

Here, we present a newly implemented ray tracing algorithm in OpenMC for efficiently computing material volume fractions on superimposed meshes in complex geometries. By firing rays along each coordinate direction through the geometry, the approach accumulates track-length data in each mesh element, thereby determining the fractional composition of each material. Scaling studies on three different models—a random tetrahedra configuration, the Frascati Neutron Generator ITER dose rate benchmark, and a stellarator design—show excellent parallel performance, with nearly linear speedup on modern multi-threaded and distributed-memory systems. An analysis of the residual error relative to high-resolution reference solutions demonstrated that under optimal conditions it decreases as 1/R, where R is the number of rays fired, making it straightforward to achieve user-prescribed accuracy. This new functionality enables practical, mesh-based approaches for detailed nuclear analyses in production Monte Carlo workflows without resorting to expensive, fully conformal or unstructured meshing.

Monte Carlo↗

DOE OSTI2023

Pressure-driven tearing and thermal transport in finite-beta reversed field pinch computations

In this work, nonlinear resistive-magnetohydrodynamics (MHD) computation with heating and anisotropic transport is applied to examine the interaction between thermal energy and magnetic fluctuations in inductively driven reversed-field pinches (RFPs). The magnetic fluctuations underlie magnetic field reversal through dynamo-like correlations, and they enhance thermal energy transport through fluctuations of parallel heat flux density. With the unfavorable magnetic curvature that exists across the RFP profile, thermal energy also affects the magnetic fluctuations. Computations with the NIMROD code [Sovinec et al., J. Comput. Phys. 195, 355–386 (2004)] integrate nonlinear MHD dynamics with energy transport and reproduce an RFP state with experimentally relevant values of plasma-β. Equilibria constructed from results of the 3D computations are analyzed to assess the sources of free energy in the saturated nonlinear state. Linear computations for these profiles show unstable modes of tearing parity. Their eigenfunctions are used to evaluate and compare stabilizing and destabilizing contributions to the kinetic energy integral. An assessment of the drives in the integral reveals that the pressure gradient drive is of comparable magnitude to the parallel current drive, and only the sum of the two surpasses the stabilizing contributions. Correlation of magnetic and parallel heat flux density fluctuations in the nonlinear computations shows that fluctuation-induced thermal conduction is the dominant mode of energy loss, as expected from experimental evidence. Decomposition of the fluctuating heat flux density shows that second-order correlations, alone, do not explain the total energy transport. Higher-order correlations are also important.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Export of macroinvertebrate prey from tidal freshwater wetlands provides a significant energy subsidy for outmigrating juvenile salmon

Tidal freshwater wetlands linking terrestrial, riverine, and saline habitats are critical areas for material processing and exchange. Once historically widespread, herbaceous marsh and forested tidal freshwater wetlands especially are now highly degraded worldwide. Additionally, quantitative assessments of hydrology and material exchange from these systems are lacking compared to lotic and estuarine (saltmarsh) habitats. Here we investigate macroinvertebrate and energy export from tidal marsh and forested wetlands and consider potential benefits from this ecological process to endangered Pacific salmon in a large tidal freshwater system, the Columbia River (USA). Macroinvertebrate (salmon prey) concentration, water velocity, and discharge were measured at several wetland habitat types (forested swamp, emergent marsh, and restored marsh). We used these data to compute prey flux and transport metrics. Then, applying literature values to calculate prey energy equivalents and juvenile salmon metabolic requirements, we estimated the potential energy subsidy available to juvenile salmon. Numerically, larval stages of aquatic insects were the predominant type of prey exported from the wetlands, with Diptera chironomid fly abundance exceeding other groups. Energetically, however, non-chironomid dipterans and hemipteran prey comprised most of energy transport due to their higher energetic content (energy density × mean weight). We determined the prey energy transported from the sampled tidal channels was sufficient to meet energetic needs of tens to thousands of juvenile salmon per day, depending on prey production and hydrography. The prey taxonomic composition differed among organisms exiting forested swamp, emergent marsh, and restored marsh habitats with corresponding differences in energy transport, but all habitat types supported similar numbers of juvenile salmon. We conclude that macroinvertebrate prey exported from varied tidal freshwater wetlands likely provide significant benefits to juvenile salmon over a larger ecological footprint than the wetland area would suggest.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Nonvolatile Electric Field Control of Thermal Magnons in the Absence of an Applied Magnetic Field

Spin transport through magnetic insulators has been demonstrated in a variety of materials and is an emerging pathway for next-generation spin-based computing. To modulate spin transport in these systems, one typically applies a sufficiently strong magnetic field to allow for deterministic control of magnetic order. Here, we make use of the well-known multiferroic magnetoelectric, BiFeO 3 , to demonstrate nonvolatile, hysteretic, electric-field control of thermally excited magnon current in the absence of an applied magnetic field. The findings in this work are an important step toward magnon-based devices, where electric-field-only control is highly desirable.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Dynamic Structure of Magnetized High Energy Density Plasmas (Final Report)

This report summarizes results of project DE-SC0022202 ``Dynamic Structure of Magnetized High Energy Density Plasmas,'' which was originally funded for the period 08/01/2021 - 7/31/2022, but was no-cost extended to 7/31/2023. The primary objectives of the work, as stated in the original proposal, were ``develop a theory to describe a novel state of magnetized high energy density plasmas, benchmark the theory using first-principles molecular dynamics simulations, and apply the results to develop a means to interpret x-ray scattering measurements in future experiments.'' These were the goals of the original project proposal, which was for a 3 year project. The project was ultimately funded for 1 year, and so the work completed focused on the goals described for only the first year of the proposed work. This included further developing a kinetic theory for strongly magnetized plasmas, applying it to compute fluid-scale (MHD) transport coefficients, and to test the predictions using molecular dynamics simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Disentangling cation effects on ion mobility and structure in ionic liquid electrolytes

Ionic liquids (ILs) are low-temperature molten salts, where ion transport is primarily governed by ion–ion interactions. Yet, the impact of organic IL cations on critical electrolyte properties such as ion dissociation and overall transport behavior in lithium-salt-doped ILs remains poorly understood. Moreover, despite their critical role in designing IL-based electrolytes for energy storage applications, ion–ion interactions and ion-specific transport under an applied electrical potential are seldom quantified, largely due to the unique experimental and computational challenges involved. Herein, we compare transport properties obtained using 1 H, 7 Li, and 19 F pulsed-field gradient nuclear magnetic resonance (NMR) and electrophoretic NMR (eNMR) with those measured by electrochemical impedance spectroscopy. Non-equilibrium molecular dynamics (MD) simulations and eNMR confirm the presence of negatively charged [Li(TFSI) n ] (1−n) aggregates that migrate towards the positive electrode, resulting in negative lithium transference numbers. Equilibrium MD simulations reveal a vehicular Li ion transport mechanism facilitated by long-lived aggregates with Li + cations strongly bound to multiple TFSI − anions. Finally, we observe an inverse relationship between the apparent charge of the TFSI − anion in the neat IL, which is dictated by the IL cation, and Li + transport in the salt-doped systems. This highlights the opportunity to tune electrolyte performance by tailoring cation chemistry.

Li-ion batteries↗

DOE OSTI2025

Permeate fluxes from desalination of brines and produced waters: A reactive transport modeling study

The increasing interest in the use of membrane systems to desalinate inland brackish water, agricultural drainage, and industrially produced wastewater demands improved means of predicting desalination system performance under variable feedwater compositions. The interaction among water flow, solute transport, and chemical composition in these systems impacts permeate flux evolution. Here, an established multicomponent reactive transport simulator that accounts for these coupled processes is applied to compute osmotic pressure and permeate fluxes in reverse osmosis (RO) systems. The model is first validated by predicting permeate fluxes for a set of benchtop crossflow experiments subject to a range of feed flow rates and compositions, under fouling and non-fouling conditions. Results compare favorably with measured data that show that solutions with similar total dissolved solids concentrations but different compositions result in different permeate fluxes. The model is then applied to predict permeate fluxes from the desalination of produced waters using a commercial spiral wound RO module. For NaCl-dominant brines, at total dissolved salt concentrations (TDS) below about 70 g/L, permeate fluxes are inversely proportional to water mole fraction as the latter is a reasonable approximation of water activity (i.e. ideal mixing). In the case of Ca–Cl-, Na–CO3- and Na–SO4-dominant brines below about 70 g/L TDS, this relationship does not hold as well and tends to overpredict osmotic pressure and thus underpredict permeate fluxes. However, the opposite becomes true at higher TDS values for typical produced waters. The scaling potential of these waters is also computed by allowing the precipitation of minerals above their saturation limit on the RO membrane. This work demonstrates how reactive transport models developed for the analysis of waters from geological systems can be extended to improve process design, optimization, and control in desalination systems from produced waters and beyond.

Molins, Sergi↗

DOE OSTI2026

Preliminary Investigation of Target keff Search for Fuel Feed in MSRs

Fluid fuel molten salt reactor (MSR) concepts may achieve continuous-at-power operation with continuous or batch fresh fuel feed to counter reactivity loss from fuel burnup and fission product buildup. Accurate modeling and simulation of MSRs requires consideration of online fuel feed during depletion as well as a capability to determine the required feed amount to maintain a target multiplication factor (keff). As a first step supporting a full implementation of a new search capability into the SCALE code system’s TRITON reactor physics and depletion sequence, a preliminary investigation was performed to identify the best approach for a critical feed search capability considering computation time and accuracy. Using a simple iterative approach in which initial feed amounts were guessed based on previous depletion steps, the main drivers of computation time were found as the Monte Carlo neutron transport settings and the applied tolerance for the target keff. In the applied model, with tight convergence criteria (keff convergence to 8 pcm and a tolerance of ±15 pcm), the critical search calculation required twice the number of neutron transport calculations compared to a depletion calculation without critical search. In contrast, with a relaxed tolerance of ±50 pcm, the overall computation time for the critical search for merely increased by 30-40%. Further studies will be performed before implementing the critical search capability into TRITON.

Faulkner, Jonathon [ORNL]↗

DOE OSTI2022

Computer Vision-Enabled Smart Traffic Monitoring for Sustainable Transportation Management

Transportation accounts for a significant portion of total global energy consumption. Excessive energy consumption usually occurs in urban traffic environments with congestion and travel delays. With the advancement of remote sensing and computer vision technologies, real-time traffic conditions can be monitored. Therefore, sustainable transportation management strategies can be developed to optimize the overall energy and environment performance and reduce congestion and emissions. This work presents a smart traffic monitoring system based on remote camera sensors. Real-time and historical traffic conditions at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) were monitored and analyzed to develop optimal transportation management strategies for sustainability. Computer vision algorithms were developed and applied to process the real-time camera data to obtain complete traffic information across the ORNL campus. Weeks of historical data were collected and processed to analyze the traffic and identify bottlenecks. The proposed traffic monitoring and management approach can be applied and extended to benefit other campuses or urban areas.

Shao, Yunli↗

DOE OSTI2024

Probing coherence in nanoscale energy transport with high spatial-temporal resolution. Final Technical Report for DOE Award Number DE-SC0019244

The overarching goal of this project is to understand how the phase coherence of phonons and the interaction of phonons with other microscopic degrees of freedom in nanomaterials, such as 2D materials, can affect the energy transport properties and eventually lead to control of energy transport by manipulating phonon interference and phonon scatterings. On the computational side, we are developing and applying first-principles methods to study emerging phonon properties in nanomaterials, including coherent phonons, resonant bonding and gate-tunable phonon-electron scatterings, which hold the promise of enabling significant tunability of energy transport processes with external fields for a wide range of applications. On the experimental side, we are developing ultrafast transient grating spectroscopy and scanning ultrafast electron microscopy (SUEM) to directly probe the coherent phonon transport and phonon-electron interaction processes in nanomaterials with high combined spatial-temporal resolutions. This program will not only provide new insights into the microscopic transport and interaction processes of fundamental energy carriers, but also open new venue towards energy-relevant applications such as thermal switches and coherent energy harvesters.

42 ENGINEERING↗

DOE OSTI2026

Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon

Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.

Data-driven framework↗

DOE OSTI2021

Transport in Stochastic Media with Random Chord Length Distributions

Thermal radiation transport computations in binary Markovian random mixtures rely almost exclusively on the Levermore-Pomraning (LP) model which is obtained by applying a heuristic closure to the ensemble averaged random medium transport equation. The validity of this model has been extensively tested by comparing numerical results over a broad parameter range (material types and mixing parameters) against benchmark solutions in planar geometry. The conditions under which the LP-model provides useful results and when it breaks down are now well established, but work to date has been largely restricted to homogeneous mixing statistics, i.e., the mean chord lengths of both materials are taken to be spatially constant. In recent work, this limitation was relaxed by allowing the mean chord lengths and, in a consistent fashion, the volume fractions in the LP-model to vary spatially and in a follow-up investigation benchmark solutions were obtained by ensemble averaging results over material realizations sampled from a nonhomogeneous Poisson process (NHPP). Numerical experiments in rod geometry with specifically linear and quadratic spatial dependence of chord lengths showed that the material averaged radiation intensities vary nonmonotonically with depth into the medium, in stark contrast to solutions obtained assuming uniform chord lengths. Moreover, depending on the local optical thickness and strength of scattering, the LP-model results showed locally more nuanced deviations from the benchmark solutions than was the case with constant chord lengths. These limited numerical investigations highlight the nontrivial qualitative and quantitative consequences of nonhomogeneous mixing statistics, in particular that closure approximations may not be uniformly valid or invalid over the problem domain.

42 ENGINEERING↗

DOE OSTI2025

A review of low-rank methods for time-dependent kinetic simulations

Time-dependent kinetic models are ubiquitous in computational science and engineering. The underlying integro-differential equations in these models are high-dimensional, comprised of a six–dimensional phase space, making simulations of such phenomena extremely expensive. In this article we demonstrate that in many situations, the solution to kinetics problems lives on a low dimensional manifold that can be described by a low-rank matrix or tensor approximation. We then review the recent development of so-called low-rank methods that evolve the solution on this manifold. The two classes of methods we review are the dynamical low-rank (DLR) method, which derives differential equations for the low-rank factors, and a Step-and-Truncate (SAT) approach, which projects the solution onto the low-rank representation after each time step. Thorough discussions of time integrators, tensor decompositions, and method properties such as structure preservation and computational efficiency are included. We further show examples of low-rank methods as applied to particle transport and plasma dynamics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Emulation of radiation transport in 3D stochastic media using 1D planar Monte Carlo stochastic media radiation transport algorithms

A subset of stochastic media radiation transport problems involves those in which radiation is incident on a thin slab of stochastic material. Particle tracking in 3D for such problems is expensive, and 1D planar models lack accuracy because they only allow the material to change in one dimension. Therefore, we propose dimensional emulation, which through a slight modification allows existing 1D planar geometry stochastic media radiation transport models to reproduce results from the equivalent 3D models by allowing the material to change in all three dimensions, reproducing the fidelity of the 3D model for the low computational cost of the 1D planar model. In this work, we apply dimensional emulation to three Monte Carlo stochastic media radiation transport models: Chord Length Sampling (CLS), the Local Realization Preserving method (LRP), and a variant of Conditional Point Sampling (CoPS). For a common Markovian benchmark set, the 3D emulation variants of these algorithms are numerically verified to reproduce the results of the 3D variants within statistics while running 1.3 to 2 times faster in the implementation within Sandia National Laboratories open-source research code PlaybookMC. The 3D emulation variants are also shown to yield a 72%–92% reduction in error for the thin slab problems in comparison to the 1D benchmark. As a result, the 3D emulation variant of CLS and CoPS-1 are shown to reproduce 3D CLS results that were used to approximate results for a 3D spherical inclusion geometry benchmark set.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Monte-Carlo Neutrino Transport in Neutron Star Merger Simulations

Gravitational waves and electromagnetic signals from merging neutron star binaries provide valuable information about the the properties of dense matter, the formation of heavy elements, and high-energy astrophysics. To fully leverage observations of these systems, we need numerical simulations that provide reliable predictions for the properties of the matter unbound in these mergers. An important limitation of current simulations is the use of approximate methods for neutrino transport that do not converge to a solution of the transport equations as numerical resolution increases, and thus have errors that are impossible to quantify. Here, we report on a first simulation of a binary neutron star merger that directly solves the transport equations using Monte-Carlo techniques. We demonstrate that a computationally cheap Monte-Carlo transport can be implemented without ill effects from sampling noise. We apply Monte-Carlo transport to an unequal mass neutron star binary merger up to 5ms past merger, and report on the properties of the matter and neutrino outflows. Finally, we compare our results to the output of our best approximate `M1' transport scheme, demonstrating that an M1 scheme that carefully approximates the neutrino energy spectrum only leads to ~10% uncertainty in the composition and velocity of the ejecta, and ~20% uncertainty in the electron (anti)neutrino luminosities and energies. Here, the most significant disagreement found between M1 and Monte-Carlo results is a factor of ~2 difference in the luminosity of heavy-lepton neutrinos.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The Transient Multi-Level method for Monte Carlo reactor statics calculations

The Transient Multi-Level (TML) method is applied to a time-dependent Monte Carlo transport solver to offload some of the computational burden of the expensive Monte Carlo solve to lower-order Coarse Mesh Finite Difference (CMFD) and Exact Point Kinetics Equations (EPKE) solvers via factorization of the neutron flux at the transport and CMFD levels using the Predictor Corrector Quasi-Static Method (PCQM). The Monte Carlo transient is solved by a modified fission source iteration scheme that introduces a single transient source bank. The method is implemented in the production-level Monte Carlo code, Shift, and verified with prescribed reactivity ramps from the two-dimensional version of the C5G7-TD reactor benchmark. The results show that, as compared to other quasi-static methods, the TML reduces the stochastic noise inherent to the transient Monte Carlo solver by factors of ~2 to 6 for various norm comparisons of the reactor power amplitude. Finally, the TML additionally reduces the number of Monte Carlo evaluations needed to simulate the transient, leading to roughly an order of magnitude improvement in CPU time relative to the standard PCQM for the problems tested.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Preservation of kinetics parameters generated by Monte Carlo calculations in two-step deterministic calculations

The generation of accurate kinetic parameters such as mean generation time Λ and effective delayed neutron fraction β eff via Monte Carlo codes is established. Employing these in downstream deterministic codes warrants another step to ensure no additional error is introduced by the low-order transport operator when computing forward and adjoint fluxes for bilinear weighting of these parameters. Another complexity stems from applying superhomogenization (SPH) equivalence in non-fundamental mode approximations, where reference and low-order calculations rely on a 3D full core model. In these cases, SPH factors can optionally be computed for only part of the geometry while preserving reaction rates and K-effective, but the impact of such approximations on kinetics parameters has not been thoroughly studied. This paper aims at studying the preservation of bilinearly-weighted quantities in the Serpent–Griffin calculation procedure. Diffusion and transport evaluations of IPEN/MB-01, Godiva, and Flattop were carried out with the Griffin reactor physics code, testing available modeling options using Serpent-generated multigroup cross sections and equivalence data. Verifying Griffin against Serpent indicates sensitivities to multigroup energy grid selection and regional application of SPH equivalence, introducing significant errors; these were demonstrated to be reduced through the use of a transport method together with a finer energy grid.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗