Results for “accelerator simulation” — Page 51

DOE OSTI2018

Dose Rate Evaluation for the ES-3100 Package with HEU Content Using MCNP, ADVANTG, Monaco, and MAVRIC

Here, this paper presents a comparative study of dose rate calculations for the ES-3100 package with highly enriched uranium (HEU) content for different source configurations using computer codes: (1) MCNP; (2) Automated Variance Reduction Generator (ADVANTG)/MCNP; (3) Monaco; and (4) Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). The Model ES-3100 package was developed at the Y-12 National Security Complex for domestic and international transportation of Type B fissile radioactive material. In this study, six different source configurations (i.e., solid cylinder, cylindrical hemi-shell, cylindrical shell, rectangular plate, cylindrical rod, or cylindrical segment form) having 36 kg of HEU metal inside the package containment vessel (based on configurations in the ES-3100/HEU safety analysis report for packaging) are evaluated. Dose rates at the package surfaces and 1 m from the package surfaces are calculated for these different source configurations. MCNP and Monaco cases are run without any biasing options to accelerate the convergence. Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods developed at the Oak Ridge National Laboratory are implemented in ADVANTG/MCNP and MAVRIC codes to accelerate the convergence. ADVANTG generates variance reduction parameters using Denovo code, and MCNP is used with the variance reduction parameters to accelerate the convergence. MAVRIC uses Denovo code to construct an importance map and a biased source distribution that are supplied to Monaco to accelerate the Monte Carlo simulation. The FW-CADIS option in ADVANTG and MAVRIC is used to accelerate the convergence in this study. The accelerated convergence cases (ADVANTG/MCNP and MAVRIC) are about 100 times faster with 100 times less particle simulation than those cases run without biasing options (analog MCNP and analog Monaco). Lastly, the MCNP, ADVANTG/MCNP, Monaco, and MAVRIC calculated dose rates at the package surfaces and at 1 m from the package surfaces for the different source configurations are compared and are found to be in general agreement.

42 ENGINEERING↗

DOE OSTI2018

Dose Rate Evaluation for the ES-3100 Package with HEU Content Using MCNP, ADVANTG, Monaco, and MAVRIC

This paper presents a comparative study of dose rate calculations for the ES-3100 package with highly enriched uranium (HEU) content for different source configurations using computer codes: (1) MCNP; (2) Automated Variance Reduction Generator (ADVANTG)/MCNP; (3) Monaco; and (4) Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). The Model ES-3100 package was developed at the Y-12 National Security Complex for domestic and international transportation of Type B fissile radioactive material. In this study, six different source configurations (i.e., solid cylinder, cylindrical hemi-shell, cylindrical shell, rectangular plate, cylindrical rod, or cylindrical segment form) having 36 kg of HEU metal inside the package containment vessel (based on configurations in the ES-3100/HEU safety analysis report for packaging) are evaluated. Dose rates at the package surfaces and 1 m from the package surfaces are calculated for these different source configurations. MCNP and Monaco cases are run without any biasing options to accelerate the convergence. Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods developed at the Oak Ridge National Laboratory are implemented in ADVANTG/MCNP and MAVRIC codes to accelerate the convergence. ADVANTG generates variance reduction parameters using Denovo code, and MCNP is used with the variance reduction parameters to accelerate the convergence. MAVRIC uses Denovo code to construct an importance map and a biased source distribution that are supplied to Monaco to accelerate the Monte Carlo simulation. The FW-CADIS option in ADVANTG and MAVRIC is used to accelerate the convergence in this study. The accelerated convergence cases (ADVANTG/MCNP and MAVRIC) are about 100 times faster with 100 times less particle simulation than those cases run without biasing options (analog MCNP and analog Monaco). The MCNP, ADVANTG/MCNP, Monaco, and MAVRIC calculated dose rates at the package surfaces and at 1 m from the package surfaces for the different source configurations are compared and are found to be in general agreement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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

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, Ryan M.↗

DOE OSTI2013

Electron acceleration by Z-mode and whistler-mode waves

We carried out a series of particle simulations to study electron acceleration by Z-mode and whistler-mode waves generated by an electron ring distribution. The electron ring distribution leads to excitations of X-mode waves mainly in the perpendicular direction, Z-mode waves in the perpendicular and parallel directions, and whistler-mode waves mainly in the parallel direction. The parallel Z- and whistler-mode waves can lead to an effective acceleration of ring electrons. The electron acceleration is mainly determined by the wave amplitude and phase velocity, which in turn is affected by the ratio of electron plasma to cyclotron frequencies. For the initial kinetic energy ranging from 100 to 500 keV, the peak energy of the accelerated electrons is found to reach 2–8 times the initial kinetic energy. We further study the acceleration process by test-particle calculations in which electrons interact with one, two, or four waves. The electron trajectories in the one-wave case are simple diffusion curves. In the multi-wave cases, electrons are accelerated simultaneously by counter-propagating waves and can have a higher final energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

Ion pre-acceleration in fully self-consistent particle-in-cell simulations of supercritical perpendicular reforming shocks in multiple ion species plasmas

Supernova remnant and heliopause termination shock plasmas may contain significant populations of minority heavy ions, with relative number densities n{sub α}/n{sub i} up to 50%. Preliminary kinetic simulations of collisionless shocks in these environments showed that the reformation cycle and acceleration mechanisms at quasi-perpendicular shocks can depend on the value of n{sub α}/n{sub i} . Shock reformation unfolds on ion spatio-temporal scales, requiring fully kinetic simulations of particle dynamics, together with the self-consistent electric and magnetic fields. This paper presents the first set of particle-in-cell simulations for two ion species, protons (n{sub p} ) and α-particles (n{sub α}), with differing mass and charge-to-mass ratios, that spans the entire range of n{sub α}/n{sub i} from 0% to 100%. The interplay between the differing gyro length scales and timescales of the ion species is crucial to the time-evolving phenomenology of the shocks, the downstream turbulence, and the particle acceleration at different n{sub α}/n{sub i} . We show how the overall energization changes with n{sub α}/n{sub i} , and relate this to the processes individual ions undergo in the shock region and in the downstream turbulence, and to the power spectra of magnetic field fluctuations. The crossover between shocks dominated by the respective ion species happens when n{sub α}/n{sub i} = 25%, and minority ion energization is strongest in this regime. Energization of the majority ion species scales with injection energy. The power spectrum of the downstream turbulence includes peaks at sequential ion cyclotron harmonics, suggestive of ion ring-beam collective instability.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Small-angle X-ray scattering characteristics of mouse brain: Planar imaging measurements and tomographic imaging simulations

Small-angle x-ray scattering (SAXS) imaging can differentiate tissue types based on their nanoscale molecular structure. However, characterization of the coherent scattering cross-section profile of relevant tissues is needed to optimally design SAXS imaging techniques for a variety of biomedical applications. Reported measured nervous tissue x-ray scattering cross sections under a synchrotron source have had limited agreement. We report a set of x-ray cross-section measurements obtained from planar SAXS imaging of 1 mm thick mouse brain (APP/PS1 wild-type) coronal slices using an 8 keV laboratory x-ray source. Two characteristic peaks were found at 0.96 and 1.60 nm -1 attributed to myelin. The peak intensities varied by location in the slice. We found that regions of gray matter, white matter, and corpus callosum could be segmented by their increasing intensities of myelin peaks respectively. Measured small-angle x-ray scattering cross sections were then used to define brain tissue scattering properties in a GPU-accelerated Monte Carlo simulation of SAXS computed tomography (CT) using a higher monochromatic x-ray energy (20 keV) to study design trade-offs for noninvasive in vivo SAXS imaging on a small-animal head including radiation dose, signal-to-noise ratio (SNR), and the effect of skull presence on the previous two metrics. Simulation results show the estimated total dose to the mouse head for a single SAXS-CT slice was 149.4 mGy. The pixel SNR was approximately 30.8 for white matter material whether or not a skull was present. In this early-stage proof-of-principle work, we have demonstrated our brain cross-section data and simulation tools can be used to assess optimal instrument parameters for dedicated small-animal SAXS-CT prototypes.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2000

Simulated Space Environmental Testing on Thin Films

An exploratory program has been conducted, to irradiate some mature commercial and some experimental polymer films with radiation simulating certain Earth orbits, and to obtain data about the response of each test film's reflective and tensile properties. Protocols to conduct optimized tests were considered and developed to a "prototype" level during this program. Fifteen polymer film specimens were arranged on a specially designed test fixture. The fixture featured controlled exposure areas, and protected the ends of the samples for later gripping in tensile tests. The fixture featured controlled exposure areas, and protected the ends of the samples for later gripping in tensile tests. The fixture containing the films was installed in a clean vacuum chamber where protons, electrons and solar ultraviolet (UV) radiation could simultaneously irradiate the specimens. Near realtime UV rates were used, whereas proton and electron rates were accelerated appreciably to simulate 5 years in orbit during a two month test. Periodically, the spectral reflectance of each film was measured in situ. After the end of the irradiation, final reflectance measurements were made in situ, and solar absorptance values were derived for each specimen. These samples were then measured in air for thermal emittance and for tensile strength. Most specimens withstood the irradiation intact, but with reduced reflectance (increased solar absorptance). Thermal emittance changed slightly in several materials, as did their tensile strength and elongation at break. Conclusions are drawn about the performance of the films. Simulated testing to an expected 5 year dose of electrons and protons consistent with those expected at L2 and 0.98 AU orbits and 100 equivalent solar hours exposure.

Russell, Dennis A.↗

DOE OSTI2013

Numerical simulation study of positron production by intense laser-accelerated electrons

Positron production by ultra-intense laser-accelerated electrons has been studied with two-dimensional particle-in-cell and Monte Carlo simulations. The dependence of the positron yield on plasma density, plasma length, and converter thickness was investigated in detail with fixed parameters of a typical 100 TW laser system. The results show that with the optimal plasma and converter parameters a positron beam containing up to 1.9 × 10{sup 10} positrons can be generated, which has a small divergence angle (10°), a high temperature (67.2 MeV), and a short pulse duration (1.7 ps)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Reduced bandwidth Compton photons from a laser-plasma accelerator using tailored plasma channels

It has been demonstrated experimentally that laser plasma accelerators can produce multi-100 MeV electron bunches with a few percent energy spread, and from these electrons, multi-MeV quasi-monoenergetic photons have been demonstrated based on Compton up-scattering from a counter-propagating laser. This offers the potential of a high-quality, narrow-bandwidth, compact, photon source with broad application. The bandwidth of the resulting photons depends directly on the distribution of the electron bunch and is limited, in particular, by the bunch divergence (i.e., the spread in transverse velocity angle). At the same time, the ability to decelerate electrons after scattering is important to source deployment. We describe a series of plasma structures that expand and then collimate the electron bunch, reducing its divergence and thus reducing the bandwidth of the scattered photons while enabling both high performance scattering and deceleration. Furthermore, these plasma structures are demonstrated in simulations of the accelerator system, showing the potential to reach few-percent photon spread which is important for applications using nuclear resonance fluorescence.

42 ENGINEERING↗

DOE OSTI2024

Enabling Parallel Performance and Portability of Solid Mechanics Simulations Across CPU and GPU Architectures

Efficiently simulating solid mechanics is vital across various engineering applications. As constitutive models grow more complex and simulations scale up in size, harnessing the capabilities of modern computer architectures has become essential for achieving timely results. This paper presents advancements in running parallel simulations of solid mechanics on multi-core CPUs and GPUs using a single-code implementation. This portability is made possible by the C++ matrix and array (MATAR) library, which interfaces with the C++ Kokkos library, enabling the selection of fine-grained parallelism backends (e.g., CUDA, HIP, OpenMP, pthreads, etc.) at compile time. MATAR simplifies the transition from Fortran to C++ and Kokkos, making it easier to modernize legacy solid mechanics codes. We applied this approach to modernize a suite of constitutive models and to demonstrate substantial performance improvements across different computer architectures. This paper includes comparative performance studies using multi-core CPUs along with AMD and NVIDIA GPUs. Results are presented using a hypoelastic–plastic model, a crystal plasticity model, and the viscoplastic self-consistent generalized material model (VPSC-GMM). The results underscore the potential of using the MATAR library and modern computer architectures to accelerate solid mechanics simulations.

Morgan, Nathaniel (ORCID:0000000276118449)↗

DOE OSTI2012

Survey and evaluate Uncertainty Quantification Methodologies

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models with uncertainty quantification, optimization, risk analysis and decision making capabilities. The CCSI Toolset will incorporate commercial and open-source software currently in use by industry and will also develop new software tools as necessary to fill technology gaps identified during execution of the project. The CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. The goal of CCSI is to deliver a toolset that can simulate the scale-up of a broad set of new carbon capture technologies from laboratory scale to full commercial scale. To provide a framework around which the toolset can be developed and demonstrated, we will focus on three Industrial Challenge Problems (ICPs) related to carbon capture technologies relevant to U.S. pulverized coal (PC) power plants. Post combustion capture by solid sorbents is the technology focus of the initial ICP (referred to as ICP A). The goal of the uncertainty quantification (UQ) task (Task 6) is to provide a set of capabilities to the user community for the quantification of uncertainties associated with the carbon capture processes. As such, we will develop, as needed and beyond existing capabilities, a suite of robust and efficient computational tools for UQ to be integrated into a CCSI UQ software framework.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2012

LLNL ARRA Report on CCSI Uncertainty Quantification Capabilities with Applications on MEA Process Models

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models with uncertainty quantification, optimization, risk analysis and decision making capabilities. The CCSI Toolset will incorporate commercial and open-source software currently in use by industry and will also develop new software tools as necessary to fill technology gaps identified during execution of the project. The CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. The goal of CCSI is to deliver a toolset that can simulate the scale-up of a broad set of new carbon capture technologies from laboratory scale to full commercial scale. To provide a framework around which the toolset can be developed and demonstrated, we will focus on three Industrial Challenge Problems (ICPs) related to carbon capture technologies relevant to U.S. pulverized coal (PC) power plants. Post combustion capture by solid sorbents is the technology focus of the initial ICP (referred to as ICP A). The goal of the uncertainty quantification (UQ) task (Task 6) is to provide a set of capabilities to the user community for the quantification of uncertainties associated with the carbon capture processes. As such, we will develop, as needed and beyond existing capabilities, a suite of robust and efficient computational tools for UQ to be integrated into a CCSI UQ software framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

Annual Report: Carbon Capture Simulation Initiative

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools as necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools as necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Quantum computing for fusion energy science applications

This is a review of recent research exploring and extending present-day quantum computing capabilities for fusion energy science applications. We begin with a brief tutorial on both ideal and open quantum dynamics, universal quantum computation, and quantum algorithms. Then, we explore the topic of using quantum computers to simulate both linear and nonlinear dynamics in greater detail. Because quantum computers can only efficiently perform linear operations on the quantum state, it is challenging to perform nonlinear operations that are generically required to describe the nonlinear differential equations of interest. In this work, we extend previous results on embedding nonlinear systems within linear systems by explicitly deriving the connection between the Koopman evolution operator, the Perron–Frobenius evolution operator, and the Koopman–von Neumann evolution (KvN) operator. We also explicitly derive the connection between the Koopman and Carleman approaches to embedding. Extension of the KvN framework to the complex-analytic setting relevant to Carleman embedding, and the proof that different choices of complex analytic reproducing kernel Hilbert spaces depend on the choice of Hilbert space metric are covered in the appendixes. Finally, we conclude with a review of recent quantum hardware implementations of algorithms on present-day quantum hardware platforms that may one day be accelerated through Hamiltonian simulation. We discuss the simulation of toy models of wave–particle interactions through the simulation of quantum maps and of wave–wave interactions important in nonlinear plasma dynamics.

Joseph, I. (ORCID:0000000255400840)↗

NASA NTRS2025

Rheology of Lunar Regolith Simulant Under Varying Gravitational Conditions

Understanding structure-property-process relationship aka rheology of regolith in varying gravity conditions is critical for exploration and future missions. In this work, a framework for studying rheology of lunar regolith simulant in varying gravity conditions (Terrestrial, Lunar and Martian) is described theoretically/numerically, where the driving force of flow of simulants was gravitational acceleration. In the analysis particle-particle interaction forces were included. It was found that the dynamic behavior of granular material is extremely sensitive to external conditions by virtue of the myriad of forces present between particle grains. The results obtained were validated against results obtained in earth and Lunar gravity conditions. The theoretical/numerical and experimental results showed that the complex interaction of these forces can drastically change the dynamics of the material, which is not captured by standard design rules, generally used in industry, for variable gravity applications.

Simulation↗

DOE OSTI2014

SU-E-T-66: Characterization of Radiation Dose Associated with Dark Currents During Beam Hold for Respiratory-Gated Electron Therapy

Purpose: The main objective of this study was to estimate the radiation dose contributed by dark currents associated with the respiratory-gated electron therapy during beam hold. The secondary aim was to determine clinical benefits of using respiratory-gated electron therapy for left-sided breast cancer patients with positive internal mammary nodes (IMN). Methods: Measurements of the dark current-induced dose in all electron modes were performed on multiple Siemens and Varian linear accelerators by manually simulating beam-hold during respiratory gating. Dose was quantified at the machine isocenter by comparing the collected charge to the known output for all energies ranging from 6 to 18 MeV for a 10cm × 10cm field at 100 SSD with appropriate solid-water buildup. Using the Eclipse treatment planning system, we compared the additional dose associated with dark current using gated electron fields to the dose uncertainties associated with matching gated photon fields and ungated electron fields. Dose uncertainties were seen as hot and cold spots along the match line of the fields. Results: The magnitude of the dose associated with dark current is highly correlated to the energy of the beam and the amount of time the beam is on hold. For lower energies (6–12 MeV), there was minimal dark current dose (0.1–1.3 cGy/min). Higher energies (15–18 MeV) showed measurable amount of doses. The dark current associated with the electron beam-hold varied between linear accelerator vendors and depended on dark current suppression and the age of the linear accelerator. Conclusion: For energies up to 12 MeV, the dose associated with the dark current for respiratorygated electron therapy was shown to be negligible, and therefore should be considered an option for treating IMN positive left-sided breast cancer patients. However, at higher energies the benefit of respiratory gating may be outweighed by dose due to the dark current.

60 APPLIED LIFE SCIENCES↗