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DOE OSTI2012

Response function of the magnetic spectrometer PRISMA for the multinucleon transfer reaction {sup 40}Ar+{sup 208}Pb

Multinucleon transfer reaction {sup 40}Ar+{sup 208}Pb has been investigated with the PRISMA-CLARA experimental setup in LNL, INFN, Italy. The experimental differential cross sections have been obtained for different transfer channels by measuring more than {Delta}{theta}{sub lab} = 20 Degree-Sign covered by three angular settings of PRISMA. Results have been compared with the semiclassical calculation GRAZING. Since the understanding of the reaction mechanism depends strongly on the determination of absolute cross section, effect of transport of ions through PRISMA has been studied via a Monte Carlo simulation code.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Transport model predictions of 225 Ac production cross sections via energetic p, d and α irradiation of 232 Th targets

Monte Carlo transport codes PHITS and MCNP6 were used to calculate the production cross sections of 225,227 Ac, 227,229 Th, 223,225 Ra, and 229,230,231 Pa via the bombardment of a 232 Th target with energetic protons, deuterons, and α-particles. The incident projectile energies ranged between 10 and 800 MeV/nucleon. When possible, the predicted production cross sections were compared with the available experimental data and other predictions. Here, the degree of the codes’ abilities to match the measured data provides a qualitative assessment of the codes’ abilities to predict data from similar, but unmeasured, projectile/target systems. In addition, a comparison between calculated cross sections and data may provide insight into possible improvements in the physics models employed by those transport codes.

223Ra↗

DOE OSTI2017

WARP

WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currently not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.

Bergmann, RyanM. [University of California - Berke↗

DOE OSTI2017

WARP

Bergmann, Ryan M.↗

DOE OSTI2019

MPRAD: A Monte Carlo and ray-tracing code for the proton radiography in high-energy-density plasma experiments

Proton radiography is used in various high-energy-density (HED) plasma experiments. In this paper, we describe a Monte Carlo and raytracing simulation tool called multimegaelectronvolt proton radiography (MPRAD) that can be used for modeling the deflection of proton beams in arbitrary three dimensional electromagnetic fields as well as the diffusion of the proton beams by Coulomb scattering and stopping power. Specifically, the Coulomb scattering and stopping power models in cold matter and fully ionized plasma are combined using interpolation. We discuss the application of MPRAD in a few setups relevant to HED plasma experiments where the plasma density can play a role in diffusing the proton beams and affecting the prediction and interpretation of the proton images. It is shown how the diffusion due to plasma density can affect the resolution and dynamical range of the proton radiography.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2012

Calculation of heating values for the high flux isotope reactor

Calculating the amount of energy released by a fission reaction (fission Q value) and the heating rate distribution in a nuclear reactor is an important part of the safety analysis. However, these calculations can become very complex. One of the codes that can be used for this type of analyses is the Monte Carlo transport code MCNP5. Currently it is impossible to calculate the Q value and heating rate disposition for delayed beta and delayed gamma particles directly from MCNP5. The purpose of this paper is to outline a rigorous method for indirectly calculating the Q values and heating rates in the High Flux Isotope Reactor (HFIR), based on previous similar studies carried out for very high-temperature reactor configurations. This method has been applied in this study to calculate heating rates for the beginning of cycle (BOC) and end-of-cycle (EOC) states of HFIR. In addition, the BOC results obtained for HFIR are compared with corresponding results for the Advanced Test Reactor. The fission Q value for HFIR was calculated as 200.2 MeV for the BOC and 201.3 MeV for the EOC. It was also determined that 95.1% and 95.4% of the heat was deposited within the HFIR fuel plates for the BOC and EOC models, respectively. This methodology can also be used for heating rate calculations for HFIR experiments. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2015

Thermal neutron filter design for the neutron radiography facility at the LVR-15 reactor

In 2011 a decision was made to build a neutron radiography facility at one of the unused horizontal channels of the LVR-15 research reactor in Rez, Czech Republic. One of the key conditions for operating an effective radiography facility is the delivery of a high intensity, homogeneous and collimated thermal neutron beam at the sample location. Additionally the intensity of fast neutrons has to be kept as low as possible as the fast neutrons may damage the detectors used for neutron imaging. As the spectrum in the empty horizontal channel roughly copies the spectrum in the reactor core, which has a high ratio of fast neutrons, neutron filter components have to be installed inside the channel in order to achieve desired beam parameters. As the channel design does not allow the instalment of complex filters and collimators, an optimal solution represent neutron filters made of large single-crystal ingots of proper material composition. Single-crystal silicon was chosen as a favorable filter material for its wide availability in sufficient dimensions. Besides its ability to reasonably lower the ratio of fast neutrons while still keeping high intensities of thermal neutrons, due to its large dimensions, it suits as a shielding against gamma radiation from the reactor core. For designing the necessary filter dimensions the Monte-Carlo MCNP transport code was used. As the code does not provide neutron cross-section libraries for thermal neutron transport through single-crystalline silicon, these had to be created by approximating the theory of thermal neutron scattering and modifying the original cross-section data which are provided with the code. Carrying out a series of calculations the filter thickness of 1 m proved good for gaining a beam with desired parameters and a low gamma background. After mounting the filter inside the channel several measurements of the neutron field were realized at the beam exit. The results have justified the expected calculated values. After the successful filter installing and a series of measurements, first test neutron radiography attempts with test samples could been carried out. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Monte Carlo/CFD Coupling for Accurate Modeling of the Delayed Neutron Precursors and Compressibility Effects in Molten Salt Reactors

Multiphysics reactor analysis has become one of the leading activities of most nuclear engineering research groups. Coupled neutronics and thermal/hydraulics (T/H) simulations have traditionally been performed by adopting deterministic transport tools and reactor system T/H codes. The main reason for avoiding higher fidelity numerical methods like continuous-energy Monte Carlo analysis has been the high computational cost of coupled, full-scale simulations. Nowadays, high fidelity multiphysics simulations represent a hot research topic, with several applications involving advanced nuclear systems. Liquid fuel Molten Salt Reactors (MSRs) feature peculiar physical phenomena that are not present in solid fuel reactors. Some of these phenomena are not correctly resolved by legacy reactor physics tools, and require specific treatments. This work focuses in particular on the analysis of the effect of the delayed neutron precursors drift and the impact of liquid fluid thermal expansion and compressibility in postulated criticality excursion transients in fast-spectrum MSRs. A new modeling tool based on a Monte Carlo approach for neutronics (Serpent code) coupled to a Computational Fluid Dynamic (CFD) analysis (OpenFOAM) was developed to obtain accurate modeling and simulation of these phenomena. The development of the Serpent Monte Carlo code [1] at VTT in the past few years has made this code particularly attractive for performing multiphysics studies. The availability of a flexible multiphysics interface, on-the-fly Doppler broadening and density-based collision rejection, and Delta-tracking, proved of paramount importance for the computationally efficient performance of coupled Monte Carlo/CFD calculations [2]. OpenFOAM is a C++ multiphysics toolkit featured by automatic matrix construction and solution capabilities for scalar and vector partial differential equations (PDEs), adopting several possible differencing and interpolation schemes, based on the Finite-Volume method. The ease of implementing the constitutive equations of different physical phenomena makes OpenFOAM particularly suitable for the modeling of complex coupled phenomena. In the past, several research activities proposed the adoption of both Serpent and OpenFOAM for the modeling and simulation of MSRs and the associated fuel cycles. In this work, these tools have been internally coupled for the steady-state and transient analysis of fast-spectrum systems, accounting for the effect of delayed neutron precursors transport and the salt thermal expansion and compressibility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2014

MCNP6 Gets Correlated with CGM 3.4 - Paper 41

Version 3.4 of the Cascading Gamma-ray Multiplicity (CGM) code has been integrated into version 6 of the Monte Carlo radiation transport code MCNP. The current release is MCNP6 which is the merger of MCNPX 2.7.0 and MCNP5. MCNP6 is a general purpose Monte Carlo radiation transport code that can transport 34 different particles and heavy ions. CGM was originally integrated into MCNPX 2.7.0 as an undocumented feature, but was never released to the public. With the integration of CGM into MCNP6 the code now has the capability of producing correlated secondary particle/gamma emissions and should be available in future release of MCNP. Before the integration of CGM, MCNP only used libraries that contain the total multiplicity but not the multiplicity distribution or the correlations. Lacking this information requires the code to use integer sampling to determine the multiplicity. In the example of thermal neutron capture on Cl-35, presented in the results section, MCNP does integer sampling. This means MCNP would produce one gamma 17% of the time and two gammas 82% giving a mean multiplicity of 1.83. Using CGM, MCNP can now produce a spectrum of multiplicities. The use of CGM has several advantages over the use of ACE data libraries in MCNP6: 1) it has correlated gamma production, 2) it produces a distribution of gamma multiplicities per interaction, whereas ACE produces an average between two integer multiplicities, 3) it is a theoretical model that may predict experimentally unmeasured physical quantities that may not be in experimental based data libraries. CGM conserves energy and angular momentum internally to CGM; however, angular emission information is not currently sent back to MCNP6. Future work will include the integration of correlated neutrons from CGM. Also, the reaction type will be passed to CGM to set the spin and parity for a particular reaction when possible. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS2003

Oversight and Development of a Community Monte Carlo Radiative Transfer Model

Under this grant we have developed a Monte Carlo radiative transfer code that will act as the nucleus for the 13RC Community Monte Carlo Model. All code is written in ANSI-compliant Fortran-95. Many modules define public type and procedures to manipulate them, but do not allow access to the type's internal components. This allows each module to do its own exhaustive error checking up-front, then proceed in a streamlined way. Many modules can read and write the state of their objects to persistent files. The code has been tested on a Macintosh running OS 10.2.4 and the Absoft Fortran compiler, and on Sun UltraSparcs running Solaris 5.8 and Forte V8 compilers. The code exposed bugs in the Intel Fortran Compiler (ifc) on the 13RC Linux host, and we are waiting for a resolution of these bugs before finished the port. the code base is under CVS versions control. The code base consists of the core code (nine modules providing the infrastructure), example integrators, and a suite of utilities and examples.

Source record↗

DOE OSTI2020

Impact of uranium oxide (UO 2 ) fuel with molybdenum (Mo) inserts on pressurized water reactor performance and safety

This work investigates nuclear reactor performance and safety characteristics of UO 2 with high thermal conductivity Mo insert structures by using multiphysics modeling techniques. Additionally, the purpose of this study is to use scoping analyses to quantify the impact of using Mo inserts from neutronic and heat transfer standpoints. Attention is given to reactor performance parameters, such as cycle length, maximum fuel temperature, temperature gradients in the fuel, and stored energy in the fuel. The finite-element code BISON and the Monte Carlo particle transport code Serpent were used to perform sensitivity analyses on the Mo insert geometry to optimize the insert design and inform larger scale modeling that required the homogenization of the UO 2 and Mo. Although BISON is often used as a fuel performance analysis tool, it is used in this context for heat transfer analysis only. Fuel performance optimization is outside the scope of the current study, but would be important for future work focused on this concept. The results showed that the insert had little impact on neutronic performance and that homogenizing the UO 2 and Mo was acceptable for reactor physics calculations. Reactivity temperature coefficients calculated using homogeneous UO 2 -Mo were shown to be relatively similar to UO 2 , but higher Mo content and 235 U enrichment can reduce the worth of soluble boron and control rods. The effect of insert geometry on heat transfer was much greater, and an approximately 15–20% difference in maximum fuel temperature was predicted between the best and worst performing heat transfer geometries. Furthermore, thermal conductivity calibration based on the finite element analysis results was performed to improve the accuracy of temperature predictions in reactor analysis models that homogenized the UO 2 -Mo fuel. Compared with UO 2 in a pressurized water reactor (PWR), the optimized UO 2 -Mo design increased the margin to fuel melt by 13–32% across the fuel cycle, but it requires the 235U enrichment to exceed 5% to match the cycle length of conventional UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Software Quality Assurance for the MOOSE-Based Open-Source Multiphysics Code Cardinal - An Expanded CI Testing Suite

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing and, maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as a safety analysis tool. These gaps have been captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents a snapshot of the verification test cases currently available for Cardinal and NekRS in their assimilation into a Continuous Integration (CI) platform. Following the CI practice permits the integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. It should be noted that the SQA program itself, including the program plans, procedures, configuration management, and testing strategies, need to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Progress Towards NQA-1 for Cardinal in FY25

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing,and maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program was initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as an analysis tool. These gaps were captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents the progress made towards NQA-1 for Cardinal in the Fiscal Year 2025 (FY25). All cases in the expanded Continuous Integration (CI) suite of NekRS are included in this report which test the solvers and modules available in NekRS exhaustively. The NekRS tests are integrated with the Cardinal CI suite and made available in publicly accessible Github documentation. Following the CI practice permits integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. Also in this report is a brief overview of the development of the Cardinal Software Quality Assurance Plan (SQAP) that was done in FY25, though it should be noted that the rest of the documentation for the SQA program needs to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

PCMS: Parallel Coupler For Multimodel Simulations

This paper presents the Parallel Coupler for Multimodel Simulations (PCMS), a new GPU accelerated generalized coupling framework for coupling simulation codes on leadership class supercomputers. PCMS includes distributed control and field mapping methods for up to five dimensions. For field mapping PCMS can utilize discretization and field information to accommodate physics constraints. PCMS is demonstrated with a coupling of the gyrokinetic microturbulence code XGC with a Monte Carlo neutral transport code DEGAS2 and with a 5D distribution function coupling of an energetic particle transport code (GNET) to a gyrokinetic microturbulence code (GTC). Weak scaling is also demonstrated on up to 2,080 GPUs of Frontier with a weak scaling efficiency of 85%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2012

Calculation of Heating Values for the High Flux Isotope Reactor

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Computational Astrophysics Consortium (2006 - 2013)

The Computational Astrophysics Consortium was a SciDAC Science Application Project that operated during the period 2006 - 2013. The collaboration was headed by Stan Woosley at UC Santa Cruz, and (initially) included partners at UC Berkeley (UCB), LLNL, LANL, LBNL, Stonybrook, Arizona, Stanford, and Johns Hopkins. This report summarizes activities at UCB over the project period. More detailed information about the project accomplishments can be found in the collaboration final report submitted by PI Stan Woosley, and attached to this document. The CAC effort at UCB was originally led by PI Chris Mckee, and included participating faculty members Jon Arons, Peter Nugent, and Eliot Quataert. In 2010, Daniel Kasen moved from UCSC to a faculty position at UCB, and took over as UCB institution PI. The project supported several graduate students (Michael Childress, Siva Dharba, Andrew Myers, Janos Botyanszki, Jeffery Silverman) and postdocs (Dovi Poznanski, Antonino Cucchiarra, Jeffrey Oishi, Bradley Cenko, Eric Hsiao and Jason Dexter). Several codes were further developed by the UCB CAC group. The Orion code is a 3-dimensional radiation hydrodynamics code, used by McKee’s group and often applied to problems in star formation. As part of the CAC, an adaptive ray tracing ionization scheme was implemented, and a chemistry solver was incorporated for coupling the ionization state of the gas to its thermodynamics. The Sedona code is 3-dimensional monte carlo radiation transport code for calculation the light curves and spectra. As part of the CAC, the physics of the code was improved and domain decomposition techniques were implemented for scaling on massively parallel systems.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Investigation of Portable Event-Based Monte Carlo Transport Using the NVIDIA Thrust Library

Power consumption considerations are driving future high performance computing platforms toward many-core computing architectures. Los Alamos National Laboratory's Trinity machine, available in 2016, will use both Intel Xeon Haswell processors and Intel Xeon Phi Knights Landing many integrated core (MIC) architecture coprocessors. Lawrence Livermore National Laboratory's Sierra machine, available in 2018, will use an IBM PowerPC architecture along with Nvidia graphics processing unit (GPU) architecture accelerators. These different advanced architectures make the computing landscape in upcoming years complex. Traditional approaches to Monte Carlo transport do not work efficiently on these new computing platforms. MIC architectures require vectorization to operate efficiently, and vectorization is difficult to achieve in Monte Carlo transport. GPU architectures require additional code to explicitly use the hardware, requiring significant code changes or hardware specific branches in the source code. A significant challenge for Monte Carlo transport projects is to simultaneously support within a single source code base efficient simulations for both the current generation of architectures and the different advanced computing architectures. In order to address these challenges, two important changes are typically required: a new algorithmic approach for solving Monte Carlo transport, and explicit use of hardware specific software. In this paper, we describe initial research investigations of an event-based Monte Carlo transport algorithm implemented using the Nvidia Thrust library on a GPU for a Monte Carlo test code. The event-based algorithm targets many-core architectures by increasing SIMD (single instruction multiple data) parallelism, while Thrust potentially provides portable performance by allowing one source code base to compile code targeted for both CPUs and GPUs. We described preliminary investigations of portable event-based Monte Carlo algorithms implemented using the Nvidia Thrust library in a research Monte Carlo test code. We found that an explicit CUDA implementation of an event-based Monte Carlo algorithm performed significantly more efficiently than a Thrust implementation on GPU platforms, most likely as a result of additional flexibility in access to different memory spaces on the GPU. Additionally, we showed that on GPU platforms and at large enough problem sizes the event-based implementations perform more efficiently than the serial history-based implementation running on the host CPU. While investigating this problem, we also discovered that the performance of the event-based algorithm is affected by what tallies are being used. A zonal scalar flux tally requires atomic operations that significantly impacted the performance of the code, in some cases producing slowdowns instead of speedups. We decided to remove the tally in order to focus on the effectiveness of the event-based algorithm. Future work will be required to research more effective ways of handling such tallies. Additionally, we would like to consider new ways for optimizing both the Thrust and CUDA versions, in order to see how much performance we have yet to achieve. The potential trade-off between portability and performance was demonstrated in this investigation. Thrust provides both CPU and GPU versions of the code in one code base, but it does so at a cost. We discovered approximately a factor of 2-5 performance difference between Thrust and CUDA on each GPU platform we tested. Thrust provides a tool to access the GPUs with less effort and specialization, but it does so by giving up fine grained control where extra performance can be found for this application. Future work will be required to determine whether this performance differential between Thrust and CUDA can be reduced for event-based Monte Carlo transport. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

In Situ Visualization of Radiation Transport Geometry

The ultimate goal for radiation transport is to perform full-core reactor modelling and simulation. Advances in computational simulation bring this goal close to reality and the newest Monte Carlo transport codes have begun to shift to using accelerators that have become a stalwart in the supercomputing and HPC space. Within the reactor modelling and simulation community, Monte Carlo transport simulations are considered the gold standard for simulation. Through the use of "combinatorial geometry" (constructive solid geomtry), complex models can be used with fewer approximation compromises while at the same time scale to run on some of the largest supercomputers in the world.Unfortunately, the state-of-the-art for "combinatorial geometry" visualization is to decompose the geometry into a mesh. This approach could require a significant amount of memory which is antithetical to in situ visualization. To address this issue, we introduce a ray caster for visualizing combinatorial geometry in radiation transport code. By only using the accelerators for the radiation transport code and leaving the CPU cores idle, there is an opportunity to conduct on node in situ visualization with the idle CPU cores, something domain experts have up to this point been unable to do. By utilizing VTK-m, the visualization can be run on the CPU as this particular application demands, but also run on any architecture that is supported by VTK-m, enabling future re-use across different platforms.

Kim, Mark B.↗