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At least 1,675 records · Page 93

CalWave's xWave Design for PacWave (Final Technical Report)

CalWave Inc. (CalWave) is developing a wave energy converter (WEC) technology that can generate electricity from ocean waves. CalWave’s design offers a unique approach to wave energy conversion that operates fully submerged and can actively adjust the wave excitation. This capability gives the architecture enhanced survivability in ocean storms without adding significant costs. Prior to this project, CalWave had completed a demonstration of a fully functional WEC system in an open ocean demonstration at nominal 1:5 scale under FOA 1663. The goal of this project was the detailed design, following relevant standards and industry best-practices, of a variant of the xWave WEC technology that can safely and efficiently operate at the DOE’s PacWave South test site for a targeted deployment of up two years. The WEC design and associated review processes proceeded in two distinct project phases: a ‘Preliminary’ and a ‘Final’ design phase. The first phase of the project consisted of the systematic design of the WEC’s key features with regards to appropriate IEC standards. The work resulted in a preliminary design of the xWave hull including structural and Power Take-Off (PTO) load estimates, as well as performance estimates for all ocean conditions the WEC would operate in at PacWave South. Following the first open-water demonstration of CalWave’s small-scale “x1” device under FOA 1663, lessons learned were fed directly into a comprehensive review of the xWave design in the second design phase of this FOA project. CalWave’s work was supported by Sandia National Lab (SNL) and the National Renewable Energy Lab (NREL) on the holistic WEC design, and detailed feedback from specialized partners on hull design, mooring and anchoring specification, and electrical grid interconnection. Optimization of the WEC system was performed using a novel numerical optimization tool developed by Sandia and optimization trends were confirmed via an experimental model scale tank test campaign. Performance estimates for PacWave and a detailed xWave design including integration of all relevant system components were concluded. The mooring design was also concluded in the Final design phase using the most up to date sea floor characterization (CPT) data.

16 TIDAL AND WAVE POWER↗

EARLY STAR-FORMING PROCESSES IN DENSE MOLECULAR CLOUD L328; IDENTIFICATION OF L328-IRS AS A PROTO-BROWN DWARF

This paper presents the results of millimeter to sub-millimeter observations of CO, HCN, N{sub 2}H{sup +}, and HCO{sup +} lines in the dense molecular cloud L328, which harbors L328-IRS, a Very Low Luminosity Object (VeLLO). Our analysis of the line width finds that {sup 13}CO and N{sub 2}H{sup +} lines are broadened right over the smallest sub-core S2 where L328-IRS is located, while they are significantly narrower in other regions of L328. Thus, L328-IRS has a direct association with the sub-core. CO observations show a bipolar outflow from this VeLLO with an extent of ∼0.08 pc. The outflow momentum flux and efficiency are much less than those of low-mass protostars. The most likely mass accretion rate (∼3.6 × 10{sup –7} M{sub ☉} yr{sup –1}) inferred from the analysis of the CO outflow is an order of magnitude smaller than the canonical value for a protostar. If the main accretion lasts during the typical Class 0 period of a protostar, L328-IRS will accrete the mass of a brown dwarf, but not that of a star. Given that its envelope mass is small (∼0.09 M{sub ☉}) and 100% star formation rate is unlikely, we suggest that L328-IRS is likely a proto-brown dwarf. Inward motions are found in global scale in the L328 cloud and its sub-cores with a typical infall speed found in starless cores. L328 is found to be fairly well isolated from other nearby clouds and seems to be forming three sub-cores simultaneously through a gravitational fragmentation process. Altogether, these all leave L328-IRS as the best example supporting the idea that a brown dwarf forms like a normal star.

79 ASTRONOMY AND ASTROPHYSICS↗

Updates to the ATLAS Data Carousel Project

The High Luminosity upgrade to the LHC (HL-LHC) is expected to deliver scientific data at the multi-exabyte scale. In order to address this unprecedented data storage challenge, the ATLAS experiment launched the Data Carousel project in 2018. Data Carousel is a tape-driven workflow whereby bulk production campaigns with input data resident on tape are executed by staging and promptly processing a sliding window to disk buffer such that only a small fraction of inputs are pinned on disk at any one time. Data Carousel is now in production for ATLAS in Run3. In this paper, we provide updates on recent Data Carousel R&D projects, including data-on-demand and tape smart writing. Data-on-demand removes from disk data that has not been accessed for a predefined period, when users request them, they will be either staged from tape or recreated by following the original production steps. Tape smart writing employs intelligent algorithms for file placement on tape in order to retrieve data back more efficiently, which is our long term strategy to achieve optimal tape usage in Data Carousel.

42 ENGINEERING↗

Parameterization and analysis of 3-D radiative transfer in clouds

This report provides a summary of major accomplishments from the project. The project examines the impact of radiative interactions between neighboring atmospheric columns, for example clouds scattering extra sunlight toward nearby clear areas. While most current cloud models don't consider these interactions and instead treat sunlight in each atmospheric column separately, the resulting uncertainties have remained unknown. This project has provided the first estimates on the way average solar heating is affected by interactions between nearby columns. These estimates have been obtained by combining several years of cloud observations at three DOE Atmospheric Radiation Measurement (ARM) Climate Research Facility sites (in Alaska, Oklahoma, and Papua New Guinea) with simulations of solar radiation around the observed clouds. The importance of radiative interactions between atmospheric columns was evaluated by contrasting simulations that included the interactions with those that did not. This study provides lower-bound estimates for radiative interactions: It cannot consider interactions in cross-wind direction, because it uses two-dimensional vertical cross-sections through clouds that were observed by instruments looking straight up as clouds drifted aloft. Data from new DOE scanning radars will allow future radiative studies to consider the full three-dimensional nature of radiative processes. The results reveal that two-dimensional radiative interactions increase overall day-and-night average solar heating by about 0.3, 1.2, and 4.1 Watts per meter square at the three sites, respectively. This increase grows further if one considers that most large-domain cloud simulations have resolutions that cannot specify small-scale cloud variability. For example, the increases in solar heating mentioned above roughly double for a fairly typical model resolution of 1 km. The study also examined the factors that shape radiative interactions between atmospheric columns and found that local effects were often much larger than the overall values mentioned above, and were especially large for high sun and near convective clouds such as cumulus. The study also found that statistical methods such as neural networks appear promising for enabling cloud models to consider radiative interactions between nearby atmospheric columns. Finally, through collaboration with German scientists, the project found that new methods (especially one called stepwise kriging) show great promise in filling gaps between cloud radar scans. If applied to data from the new DOE scanning cloud radars, these methods can yield large, continuous three-dimensional cloud structures for future radiative simulations.

58 GEOSCIENCES↗

Treatment of Oil & Gas Produced Water.

Production of oil and gas reserves in the New Mexico Four Corners Region results in large volumes of "produced water". The common method for handling the produced water from well production is re-injection in regulatory permitted salt water disposal wells. This is expensive (%7E $5/bbl.) and does not recycle water, an ever increasingly valuable commodity. Previously, Sandia National Laboratories and several NM small business tested pressure driven membrane-filtration techniques to remove the high TDS (total dissolved solids) from a Four Corners Coal Bed Methane produced water. Treatment effectiveness was less than optimal due to problems with pre-treatment. Inadequate pre-treatment allowed hydrocarbons, wax and biological growth to foul the membranes. Recently, an innovative pre-treatment scheme using ozone and hydrogen peroxide was pilot tested. Results showed complete removal of hydrocarbons and the majority of organic constituents from a gas well production water. ACKNOWLEDGEMENTS This report was made possible through funding from the New Mexico Small Business Administration (NMSBA) Program at Sandia National Laboratories. Special thanks to Juan Martinez and Genaro Montoya for guidance and support from project inception to completion. Also, special thanks to Frank McDonald, the small businesses team POC, for laying the ground work for the entire project; Teresa McCown, the gas well owner and very knowledgeable- fantastic site host; Lea and Tim Phillips for their tremendous knowledge and passion in the oil & gas industry.; and Frank Miller and Steve Addleman for providing a pilot scale version of their proprietary process to facilitate the pilot testing.

54 ENVIRONMENTAL SCIENCES↗

Graphite fiber textile preform/copper matrix composites

Graphite fiber reinforced/copper matrix composites have sufficiently high thermal conduction to make them candidate materials for critical heat transmitting and rejection components. The term textile composites arises because the preform is braided from fiber tows, conferring three-dimensional reinforcement and near net shape. The principal issues investigated in the past two years have centered on developing methods to characterize the preform and fabricated composite and on braidability. It is necessary to have an analytic structural description for both processing and final property modeling. The structure of the true 3-D braids used is complex and has required considerable effort to model. A structural mapping has been developed as a foundation for analytic models for thermal conduction and mechanical properties. The conductivity has contributions both from the copper and the reinforcement. The latter is accomplished by graphitization of the fibers, the higher the amount of graphitization the greater the conduction. This is accompanied by an increase in the fiber modulus, which is desirable from a stiffness point of view but decreases the braidability; the highest conductivity fibers are simply too brittle to be braided. Considerable effort has been expended on determining the optimal braidability--conductivity region. While a number of preforms have been fabricated, one other complication intervenes; graphite and copper are immiscible, resulting in a poor mechanical bond and difficulties in infiltration by molten copper. The approach taken is to utilize a proprietary fiber coating process developed by TRA, of Salt Lake City, Utah, which forms an itermediary bond. A number of preforms have been fabricated from a variety of fiber types and two sets of these have been infiltrated with OFHC copper, one with the TRA coating and one without. Mechanical tests have been performed using a small-scale specimen method and show the coated specimens to have superior mechanical properties. Final batches of preforms, including a finned, near net shape tube, are being fabricated and will be infiltrated before summer.

Gilatovs, G. J.↗

Thermal Emission Spectra of Silica-coated Basalt and Considerations for Martian Surface Mineralogy

Among the most important discoveries made during the Mars Global Surveyor (MGS) mission was that the rocky materials of Mars are broadly divisible into two distinct rock types. The geological significance of this finding is dependent on the mineralogy of these rock types as well as their geographic and stratigraphic positions. Much work has yet to be done to understand these relationships and the small-scale variability of these units. For now, it is worth considering various scenarios that could have resulted in Mars global-scale mineralogical dichotomy. Such work will make clearer what must be looked for in Thermal Emission Spectrometer (TES) and Thermal Imaging Spectrometer (THEMIS) data, what to test with other data sets, and what geological processes can be considered or ruled out as we advance with interpreting Martian geologic history. Here, we suggest that exogenic coatings of secondary silica on basaltic rocks may provide a plausible explanation for the newly discovered distribution of rock types.

Kraft, M. D.↗

Propulsion Trade Studies for Spacecraft Swarm Mission Design

Spacecraft swarms constitute a challenge from an orbital mechanics standpoint. Traditional mission design involves the application of methodical processes where predefined maneuvers for an individual spacecraft are planned in advance. This approach does not scale to spacecraft swarms consisting of many satellites orbiting in close proximity; non-deterministic maneuvers cannot be preplanned due to the large number of units and the uncertainties associated with their differential deployment and orbital motion. For autonomous small sat swarms in LEO, we investigate two approaches for controlling the relative motion of a swarm. The first method involves modified miniature phasing maneuvers, where maneuvers are prescribed that cancel the differential delta V of each CubeSat's deployment vector. The second method relies on artificial potential functions (APFs) to contain the spacecraft within a volumetric boundary and avoid collisions. Performance results and required delta V budgets are summarized, indicating that each method has advantages and drawbacks for particular applications. The mini phasing maneuvers are more predictable and sustainable. The APF approach provides a more responsive and distributed performance, but at considerable propellant cost. After considering current state of the art CubeSat propulsion systems, we conclude that the first approach is feasible, but the modified APF method of requires too much control authority to be enabled by current propulsion systems.

CubeSat↗

Numerical Simulation of No-Vent Chill and Fill of a Large Liquid Hydrogen Tank

To enable the design of future in-space cryogenic propellant transfer vehicles, high accuracy models of the cryogenic propellant transfer process are desired. For in-space refueling applications, accurate simulations are desired of the propellant tank chilldown and no-vent fill (NVF) process in order to estimate the amount of propellant required, to determine the maximum sustainable flow rate to fill the tank, and to establish a timeline for the filling process. NVF is a complex process that involves numerous two-phase heat and mass transfer phenomena, such as boiling at the wall and evaporation and condensation at the liquid/vapor interface. In recent years, progress has been made in developing a numerical modeling technique using the Generalized Fluid System Simulation Program (GFSSP) that has been validated against several small-scale liquid nitrogen NVF tests. This paper presents GFSSP numerical model validation against three liquid hydrogen NVF tests on a large-scale propellant tank. Comparing the GFSSP model to the data for pressure, fill level, and wall temperature, the mean absolute percentage error is below 20% across the range of simulated conditions, indicating very good predictive agreement for this large-scale hydrogen NVF test series.

Alok Majumdar↗

Numerical Simulation of No-Vent Chill and Fill of a Large Liquid Hydrogen Tank

To enable the design of future in-space cryogenic propellant transfer vehicles, high accuracy models of the cryogenic propellant transfer process are desired. For in-space refueling applications, accurate simulations are desired of the propellant tank chilldown and no-vent fill (NVF) process in order to estimate the amount of propellant required, to determine the maximum sustainable flow rate to fill the tank, and to establish a timeline for the filling process. NVF is a complex process that involves numerous two-phase heat and mass transfer phenomena, such as boiling at the wall and evaporation and condensation at the liquid/vapor interface. In recent years, progress has been made in developing a numerical modeling technique using the Generalized Fluid System Simulation Program (GFSSP) that has been validated against several small-scale liquid nitrogen NVF tests. This paper presents GFSSP numerical model validation against three liquid hydrogen NVF tests on a large-scale propellant tank. Comparing the GFSSP model to the data for pressure, fill level, and wall temperature, the mean absolute percentage error is below 20% across the range of simulated conditions, indicating very good predictive agreement for this large-scale hydrogen NVF test series.

Alok Majumdar↗

Exploration of the Application of Machine Learning to the improvement of Interatomic Potentials

Current methods for atomistic simulations of material systems suffer from limitations which restrict the ability of the simulation to correctly characterize certain material behavior and physical phenomena. Small scale ab initio (AIMD) modeling is highly accurate but is computationally expensive. Classical molecular dynamics (CMD) simulations use interatomic potentials (IPs) to describe larger systems at a reduced computational cost, but with a reduced accuracy. Creating more robust IPs enable more precise CMD simulations. In this thesis, the application of a specific machine learning process,artifical neural networks (ANNs), to the improvement of IPs and MD simulation is discussed.

O'Connor, Sean↗

Peregrine 100-km Sounding Rocket Project

The Peregrine Sounding Rocket Program is a joint basic research program of NASA Ames Research Center, NASA Wallops, Stanford University, and the Space Propulsion Group, Inc. (SPG). The goal is to determine the applicability of this technology to a small launch system. The approach is to design, build, and fly a stable, efficient liquefying fuel hybrid rocket vehicle to an altitude of 100 km. The program was kicked off in October of 2006 and has seen considerable progress in the subsequent 18 months. This research group began studying liquifying hybrid rocket fuel technology more than a decade ago. The overall goal of the research was to gain a better understanding of the fundamental physics of the liquid layer entrainment process responsible for the large increase in regression rate observed in these fuels, and to demonstrate the effect of increased regression rate on hybrid rocket motor performance. At the time of this reporting, more than 400 motor tests were conducted with a variety of oxidizers (N2O, GOx, LOx) at ever increasing scales with thrust levels from 5 to over 15,000 pounds (22 N to over 66 kN) in order to move this technology from the laboratory to practical applications. The Peregrine program is the natural next step in this development. A number of small sounding rockets with diameters of 3, 4, and 6 in. (7.6, 10.2, and 15.2 cm) have been flown, but Peregrine at a diameter of 15 in. (38.1 cm) and 14,000-lb (62.3-kN) thrust is by far the largest system ever attempted and will be one of the largest hybrids ever flown. Successful Peregrine flights will set the stage for a wide range of applications of this technology.

Zilliac, Gregory↗

Dilute Alloys Based on Au, Ag, or Cu for Efficient Catalysis: From Synthesis to Active Sites

The development of new catalyst materials for energy-efficient chemical synthesis is critical as over 80% of industrial processes rely on catalysts, with many of the most energy-intensive processes specifically using heterogeneous catalysis. Catalytic performance is a complex interplay of phenomena involving temperature, pressure, gas composition, surface composition and structure over multiple length and time scales. In response to this complexity, the integrated approach to heterogeneous dilute-alloy catalysis reviewed here brings together materials synthesis, mechanistic surface chemistry, reaction kinetics, in-situ and operando characterization, and theoretical calculations in a coordinated effort to develop design principles to predict and improve catalytic selectivity. Dilute alloy catalysts—in which isolated atoms or small ensembles of the minority metal on the host metal lead to enhanced reactivity while retaining selectivity—are particularly promising as selective catalysts. Several dilute alloy materials using Au, Ag and Cu as the majority host element, including more recently introduced support-free nanoporous metals and oxide-supported nanoparticle "raspberry colloid templated (RCT)" materials, are reviewed for selective oxidation and hydrogenation reactions. Progress in understanding how such dilute alloy catalysts can be used to enhance selectivity of key synthetic reactions is reviewed, including quantitative scaling from model studies to catalytic conditions. The dynamic evolution of catalyst structure and composition studied in surface science and catalytic conditions and their relationship to catalytic function are also discussed, followed by advanced characterization and theoretical modeling that have been developed to determine the distribution of minority metal atoms at or near the surface. Furthermore, the integrated approach demonstrates the success of bridging the divide between fundamental knowledge and design of catalytic processes in complex catalytic systems, which can accelerate the development of new and efficient catalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

3D printing via ambient reactive extrusion

Here, Additive Manufacturing (AM) has the potential to offer many benefits over traditional manufacturing methods in the fabrication of complex parts with advantages such as low weight, complex geometry, and embedded functionality. In practice, today’s AM technologies are limited by their slow speed and highly directional properties. To address both issues, we have developed a reactive mixture deposition approach that can enable 3D printing of polymer materials at over 100X the volumetric deposition rate, enabled by a greater than 10X reduction in print head mass compared to existing large-scale thermoplastic deposition methods, with material chemistries that can be tuned for specific properties. Additionally, the reaction kinetics and transient rheological properties are specifically designed for the target deposition rates, enabling the synchronized development of increasing shear modulus and extensive cross linking across the printed layers. This ambient cure eliminates the internal stresses and bulk distortions that typically hamper AM of large parts, and yields a printed part with inter-layer covalent bonds that significantly improve the strength of the part along the build direction. The fast cure kinetics combined with the fine-tuned viscoelastic properties of the mixture enable rapid vertical builds that are not possible using other approaches. Through rheological characterization of mixtures that were capable of printing in this process as well as materials that have sufficient structural integrity for layer-on-layer printing, a “printability” rheological phase diagram has been developed, and is presented here. We envision this approach implemented as a deployable manufacturing system, where manufacturing is done on-site using the efficiently-shipped polymer, locally-sourced fillers, and a small, deployable print system. Unlike existing additive manufacturing approaches which require larger and slower print systems and complex thermal management strategies as scale increases, liquid reactive polymers decouple performance and print speed from the scale of the part, enabling a new class of cost-effective, fuel-efficient additive manufacturing.

36 MATERIALS SCIENCE↗

SLOAVx: Scalable LOgarithmic AlltoallV Algorithm for Hierarchical Multicore Systems

Scientific applications use collective communication operations in Message Passing Interface (MPI) for global synchronization and data exchanges. Alltoall and AlltoallV are two important collective operations. They are used by MPI jobs to exchange messages among all of MPI processes. AlltoallV is a generalization of Alltoall, supporting messages of varying sizes. However, the existing MPI AlltoallV implementation has linear complexity, i.e., each process has to send messages to all other processes in the job. Such linear complexity can result in sub optimal scalability of MPI applications when they are deployed on millions of cores. To address above challenge, in this paper, we introduce a new Scalable LOgarithmic AlltoallV algorithm, named SLOAV, for MPI AlltoallV collective operation. SLOAV aims to achieve global exchange of small messages of different sizes in a logarithmic number of rounds. Furthermore, given the prevalence of multicore systems with shared memory, we design a hierarchical AlltoallV algorithm based on SLOAV by leveraging the advantages of shared memory, which is referred to as SLOAVx. Compared to SLOAV, SLOAVx significantly reduces the inter-node communication, thus improving the entire system performance and mitigating the impact of message latency. We have implemented and embedded both algorithms in Open MPI. Our evaluation on large-scale computer systems shows that for the 8-byte and 1024-process MPI Alltoallv operation, the SLOAV can reduce the latency by as much as 86.4%, when compared to the state-of-the-art, and SLOAVx can further optimize the SLOAV by up to 83.1% in terms of message latency on multicore systems. In addition, experiments with NAS Parallel Benchmark (NPB) demonstrate that our algorithms are very effective for real-world applications.

Computer Science↗

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in situ and remote sensing data sets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

Cheng, Yanyan↗

A study on the entrainment and mixing process in the continental stratocumulus clouds measured during the RACORO campaign

Entrainment and mixing processes and their effects on cloud microphysics in the continental stratocumulus clouds observed in Oklahoma during the RACORO campaign are analyzed in the frame of homogeneous and inhomogeneous mixing concepts by combining the approaches of microphysical correlation, mixing diagram, and transition scale (number). A total of 110 horizontally penetrated cloud segments is analyzed in this paper. Mixing diagram and cloud microphysical relationship analyses show homogeneous mixing trait of positive relationship between liquid water content (L) and mean volume of droplets (V) (i.e., smaller droplets in more diluted parcel) in most cloud segments. Relatively small temperature and humidity differences between the entraining air from above the cloud top and cloudy air and relatively large turbulent dissipation rate are found to be responsible for this finding. The related scale parameters (i.e., transition length and transition scale number) are relatively large, which also indicates high likelihood of homogeneous mixing. Finally, clear positive relationship between L and vertical velocity (W) for some cloud segments is suggested to be evidence of vertical circulation mixing, which may further enhance the positive relationship between L and V created by homogeneous mixing.

54 ENVIRONMENTAL SCIENCES↗

A GPU Accelerated Mixed‐Precision Finite Difference Informed Random Walker (FDiRW) Solver for Strongly Inhomogeneous Diffusion Problems

In nature, many complex multi‐physics coupling problems exhibit significant diffusivity inhomogeneity, where one process occurs several orders of magnitude faster than others temporally. Simulating rapid diffusion alongside slower processes demands intensive computational resources due to the necessity for small time steps. To address these computational challenges, we have developed an efficient numerical solver named Finite Difference informed Random Walker (FDiRW). In this study, we propose a GPU‐accelerated, mixed‐precision configuration for the FDiRW solver to maximize efficiency through GPU multi‐threaded parallel computation and lower precision computation. Numerical evaluation results reveal that the proposed GPU‐accelerated mixed‐precision FDiRW solver can achieve a 117× speedup over the CPU baseline, while an additional 1.75× speedup is achieved by employing lower precision GPU computation. Notably, for large model sizes, the GPU‐accelerated mixed‐precision FDiRW solver demonstrates strong scaling with the number of nodes used in simulation. When simulating radionuclide absorption processes by porous wasteform particles with a medium‐sized model of 192 × 192 × 192, this approach reduces the total computational time to 10 min, enabling the simulation of larger systems with strongly inhomogeneous diffusivity.

97 MATHEMATICS AND COMPUTING↗