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At least 739 records · Page 41

The theoretical aspects of UrQMD & AMPT models

The field of high energy physics is very challenging in carrying out theories and experiments to unlock the secrets of heavy ion collisions and still not cracked and solved completely. There are many theoretical queries; some may be due to the inherent causes like the non-perturbative nature of QCD in the strong coupling limit, also due to the multi-particle production and evolution during the heavy ion collisions which increase the complexity of the phenomena. So for the purpose of understanding the phenomena, variety of theories and ideas are developed which are usually implied in the form of Monte-Carlo codes. The UrQMD model and the AMPT model are discussed here in detail. These methods are useful in modeling the nuclear collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Production of energetic light fragments in extensions of the CEM and LAQGSM event generators of the Monte Carlo transport code MCNP6 [Production of energetic light fragments in CEM, LAQGSM, and MCNP6]

We extend the cascade-exciton model (CEM), and the Los Alamos version of the quark-gluon string model (LAQGSM), event generators of the Monte Carlo N-particle transport code version 6 (MCNP6), to describe production of energetic light fragments (LF) heavier than 4 He from various nuclear reactions induced by particles and nuclei at energies up to about 1 TeV/nucleon. In these models, energetic LF can be produced via Fermi breakup, preequilibrium emission, and coalescence of cascade particles. Initially, we study several variations of the Fermi breakup model and choose the best option for these models. Then, we extend the modified exciton model (MEM) used by these codes to account for a possibility of multiple emission of up to 66 types of particles and LF (up to 28 Mg) at the preequilibrium stage of reactions. Then, we expand the coalescence model to allow coalescence of LF from nucleons emitted at the intranuclear cascade stage of reactions and from lighter clusters, up to fragments with mass numbers A ≤ 7, in the case of CEM, and A ≤ 12, in the case of LAQGSM. Next, we modify MCNP6 to allow calculating and outputting spectra of LF and heavier products with arbitrary mass and charge numbers. The improved version of CEM is implemented into MCNP6. Lastly, we test the improved versions of CEM, LAQGSM, and MCNP6 on a variety of measured nuclear reactions. The modified codes give an improved description of energetic LF from particle- and nucleus-induced reactions; showing a good agreement with a variety of available experimental data. They have an improved predictive power compared to the previous versions and can be used as reliable tools in simulating applications involving such types of reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Parallel scaling analysis for explicit solid dynamics in ALEGRA

Weak scaling studies were performed for the explicit solid dynamics component of the ALEGRA code on two Cray supercomputer platforms during the period 2012-2015, involving a production-oriented hypervelocity impact problem. Results from these studies are presented, with analysis of the performance, scaling, and throughput of the code on these machines. The analysis demonstrates logarithmic scaling of the average CPU time per cycle up to core counts on the order of 10,000. At higher core counts, variable performance is observed, with significant upward excursions in compute time from the logarithmic trend. However, for core counts less than 10,000, the results show a 3 × improvement in simulation throughput, and a 2 × improvement in logarithmic scaling. This improvement is linked to improved memory performance on the Cray platforms, and to significant improvements made over this period to the data layout used by ALEGRA.

97 MATHEMATICS AND COMPUTING↗

Plans for Assimilating AQUA data at NASA's DAO

NASA's Data Assimilation Office (DAO) is expanding its work with TIROS Operational Vertical Sounder (TOVS) to assimilate data from the advanced instruments which will fly on NASA's AQUA satellite in early 2002. The Atmospheric Infrared Sounder (AIRS), which has over 2000 channels, together with the Advanced Microwave Sounding Unit-A (AMSU-A) and the Humidity Sounder Brazil (HSB) will provide many technical challenges for data assimilation centers. One of the primary concerns is how best to subset the data in order to efficiently extract information about the Earth's atmosphere and surface. This includes static and dynamic channel selection as well as pixel thinning. The DAO is currently experimenting with simulated AIRS/AMSU/HSB radiances within the framework of our finite volume data assimilation system (NDAS) using the OPTRAN radiative transfer code developed as part of the NOAA/NASA Joint Center for Satellite Data Assimilation. The short-term goals include the assessment of the cost of processing various data subsets and preparation for near-real-time assimilation within a few months of launch. We will also discuss plans and tools for evaluating the quality of AIRS data including radiances and level 2 products from the AIRS science team.

Frank, Donald↗

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗

Multiphysics Coupling Methods for Molten Salt Reactor Modeling and Simulation in VERA

New multiphysics coupling capabilities for molten salt reactor (MSR) analysis have been developed in the Virtual Environment for Reactor Applications (VERA). This development consisted of two main efforts. First, a generic species transport module was added in the CTF code, which is the thermal-hydraulics (TH) code for VERA. This module uses the velocity fields for which CTF solves during the TH calculation to transport species through the core and around the primary loop. Additionally, a gas sparging model has been added to CTF to model the movement of certain species, namely, fission products such as xenon gas, to transport between the molten salt and gas bubbles present in the salt. The second effort in this development was coupling this capability to VERA’s neutron transport code MPACT. This effort focused on coupling the detailed TH transport models in CTF to MPACT to account for feedback effects in the neutron transport calculations. Finally, the thermochemistry code Thermochimica has also been coupled to VERA. Thermochimica performs pointwise calculations for chemical potential and Gibbs free energy and determines what phases are produced by the temperature, pressure, and elemental concentrations at different locations in the primary loop. These capabilities are demonstrated using a model of the Molten Salt Reactor Experiment (MSRE). Furthermore, this reactor operated at Oak Ridge National Laboratory in the 1960s, providing sources of experimental data that were used to develop the model. Various combinations of species were modeled using VERA’s new multiphysics coupling capabilities. Species distributions and reactivity effects behaved as expected for the MSRE model, demonstrating that the coupling is behaving correctly and causing appropriate feedback. The results of these calculations show the potential for VERA to be used for a wide variety of MSR analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

RT_BUILD: An expert programmer for implementing and simulating Ada real-time control software

The RT BUILD is an expert control system programmer that creates real-time Ada code from block-diagram descriptions of control systems. Since RT BUILD embodies substantial knowledge about the implementation of real-time control systems, it can perform many, if not most of the functions normally performed by human real-time programmers. Though much basic research was done in automatic programming, RT BUILD appears to be the first application of this research to an important problem in flight control system development. In particular, RT BUILD was designed to directly increase productivity and reliability for control implementations of large complex systems.

Lehman, Larry L.↗

3D modeling of missing pellet surface defects in BWR fuel

One of the important roles of cladding in light water reactor fuel rods is to prevent the release of fission products. To that end, it is essential that the cladding maintain its integrity under a variety of thermal and mechanical loading conditions. Local geometric irregularities in fuel pellets caused by manufacturing defects known as missing pellet surfaces (MPS) can in some circumstances lead to elevated cladding stresses that are sufficiently high to cause cladding failure. Accurate modeling of these defects can help prevent these types of failures. The BISON nuclear fuel performance code developed at Idaho National Laboratory can be used to simulate the global thermo-mechanical fuel rod behavior, as well as the local response of regions of interest, in either 2D or 3D. In either case, a full set of models to represent the thermal and mechanical properties of the fuel, cladding and plenum gas is employed. A procedure for coupling 2D full-length fuel rod models to detailed 3D models of the region of the rod containing a MPS defect is detailed in this paper. The global and local model each contain appropriate physics and behavior models for nuclear fuel. This procedure is demonstrated on a simulation of a boiling water reactor (BWR) fuel rod containing a pellet with an MPS defect, subjected to a variety of transient events, including a control blade withdrawal and a ramp to high power. The importance of modeling the local defect using a 3D model is highlighted by comparing 3D and 2D representations of the defective pellet region. Finally, parametric studies demonstrate the effects of the choice of gaseous swelling model and of the depth and geometry of the MPS defect on the response of the cladding adjacent to the defect.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparison of Fission Product Release Predictions Using PARFUME with Results from the AGR-1 Irradiation Experiment

This report documents comparisons between post-irradiation examination measurements and model predictions of silver (Ag), cesium (Cs), and strontium (Sr) release from selected tristructural isotropic (TRISO) fuel particles and compacts during the first irradiation test of the Advanced Gas Reactor program that occurred from December 2006 to November 2009 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The modeling was performed using the particle fuel model computer code PARFUME (PARticle FUel ModEl) developed at INL. PARFUME is an advanced gas-cooled reactor fuel performance modeling and analysis code (Miller 2009). It has been developed as an integrated mechanistic code that evaluates the thermal, mechanical, and physico-chemical behavior of fuel particles during irradiation to determine the failure probability of a population of fuel particles given the particle-to-particle statistical variations in physical dimensions and material properties that arise from the fuel fabrication process, accounting for all viable mechanisms that can lead to particle failure. The code also determines the diffusion of fission products from the fuel through the particle coating layers, and through the fuel matrix to the coolant boundary. The subsequent release of fission products is calculated at the compact level (release of fission products from the compact) but it can be assessed at the particle level by adjusting the diffusivity in the fuel matrix to very high values. Furthermore, the diffusivity of each layer can be individually set to a high value (typically 10-6 m2/s) to simulate a failed layer with no capability of fission product retention. In this study, the comparison to PIE focused on fission product release and because of the lack of failure in the irradiation, the probability of particle failure was not calculated. During the AGR-1 irradiation campaign, the fuel kernel produced and released fission products, which migrated through the successive layers of the TRISO-coated particle and potentially through the compact matrix. The release of these fission products was measured in PIE and modeled with PARFUME.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Influences of Neutron Irradiation on Aggregate Induced Degradation of Concrete

Reactor cavity concrete, the primary support structure for the reactor pressure vessel (RPV), is exposed to chronic neutron/gamma radiation during normal operation. During long term operation, the interaction of neutron irradiation with the concrete’s constituents may cause premature degradation of the concrete structure, as highlighted by a review of concrete properties in nuclear power plant environments. At high fluence levels, as in biological shielding, neutron irradiation may cause amorphization of the crystalline components of concrete, i.e., mineral aggregates, and volume changes, which are typically expansive in nature. Volume expansion can generate tensile stresses within concrete which can induce microcracking and/or result in debonding of aggregate with the matrix. On the other hand, structural disordering can result in changes in the stability of the phase in aqueous environments. This report presents the findings of investigations performed over 3 years through the collaboration of researchers from University of California, Los Angeles, Arizona State University, and Oak Ridge National Laboratory. The first part of the study addresses the effect of neutron irradiation on the durability of aggregates. Comparisons of aqueous dissolution rates, as a function of pH and temperature, were performed for aggregates that are either pristine (i.e., non-irradiated) or exposed to Ar+ ion irradiation at specified doses. These experimental results were coupled with molecular dynamics simulations of atomic scale changes in the crystallographic structure of the mineral and any resulting changes in physical properties (e.g., density) that result. The second section focuses on macroscopic effects of such changes in aggregate behavior in concrete degradation, primarily through changes in the concrete’s microstructure. Particularly, the effects akin to those originating from alkali-silica reaction (ASR) were evaluated. The project is structured to encompass 6 main tasks, as follows: Task 1: Selection of aggregates in relation to their abundance and mineralogy, and their irradiation Task 2: Molecular dynamics (MD): The effects of irradiation on the atomic disordering of aggregates Task 3: The influences of irradiation on aggregate reactivity Task 4: Reactive-transport simulation of expansive product formation in concrete microstructures Task 5: X-FEM-based modeling of damage evolution due to irradiation-induced aggregates reactions Task 6: Benchmarking, verification and validation of the simulation modules Thus, a rigorous understanding of irradiation-assisted mineral alterations was used to develop a mechanistic degradation model for concrete exposed to neutrons, while considering aspects of: chemical reaction (dissolution and precipitation), mass and ion transport, and damage evolutions. The models developed were embedded in a multi-physics aging code for nuclear components and structures called Grizzly, which allows for benchmarking, verification, and validation against expansion data acquired on concrete undergoing alkali-silica reaction, a physically/chemically equivalent form of degradation that develops in the absence of radiation. These findings provide insight into the sensitivities of minerals to irradiation, by highlighting characteristics of concretes and power plants subject to such risks. The research will aid the nuclear power industry to anticipate and mitigate such risks in light of second license renewals.

36 MATERIALS SCIENCE↗

Advancing Understanding of Fission Gas Behavior in Nuclear Fuel through Leadership Class Computing

This report describes the outcome of the pilot SciDAC project jointly funded by the DOE Office of Nuclear Energy and the DOE Office of Science, Advanced Scientific Computing Research to advance understanding of fission gas behavior in nuclear fuel. The computational approach involved utilizing both a bottom up and top down multiscale materials modeling to evaluate the processes of xenon fission gas diffusion, xenon clustering and precipitation and the mechanisms of fission gas resolution by energetic fission fragments in uranium dioxide nuclear fuel. The computer science and applied mathematics research activities were focused on optimizing the uranium – oxygen – xenon interatomic potential implementation in the LAMMPS molecular dynamics code for large-scale simulations of fission gas resolution, in addition to improvements in visualization of accelerated molecular dynamics simulations and performance optimization of the Xolotl continuum cluster dynamics with a new grouping scheme to reduce the computational cost of modeling very large fission gas bubbles containing more than 10,000 xenon atoms. The most impactful result from this project stems from a systematic series of atomistic molecular dynamics to evaluate fission gas resolution from xenon bubbles that, combined with the fission product yields and consideration of electron-phonon coupling, informed a first principles model that predicts the magnitude of fission gas resolution in good agreement with empirical estimates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advancing Coal Catalytic Gasification to Promote Optimum Syngas Production

An investigation was pursued to improve the use of low rank sub-bituminous coal by using suitable catalysts to advance gasification and create cleaner synthesis gas. Bench- and pilot-scale experiments were performed to measure key reactive properties and verify the use of red mud catalyst. The experiments provided reaction data for the development of kinetic models and validation data for CFD simulations. The reaction kinetics were analyzed to provide an understanding of the major pathways involved and identify the necessary reaction mechanisms needed for the computational models. The reaction kinetics model was implemented into the computational fluid dynamics (CFD) code MFiX to simulate, predict and validate the chemistry model with the experiments. It was shown that red mud as a catalyst lowered methane formation during coal gasification. Additional benefits were that red mud destroyed tars formation, promoted water gas shift reaction resulting in a syngas rich in hydrogen. In the presence of red mud catalyst, biomass feedstocks high in ash did not form clinker in the fluidized bed because it prevented the formation of eutectic mixtures. The reaction kinetics model was reasonably robust and the CFD predictions using the model were in good agreement with the experiments.

01 COAL, LIGNITE, AND PEAT↗

Testing the Delayed Gamma Capability in MCNP6 - Paper 86

The mission of the Domestic Nuclear Detection Office (DNDO) is to quickly and reliably detect unauthorized attempts to import or transport special nuclear material (SNM) for use against the United States. Developing detection equipment to meet this objective requires accurate simulation of both the detectable signature and detection mechanism. MCNP6 is capable of transporting the various types of radiation encountered in these scenarios; however, the accuracy of MCNP6 must be quantified such that we can be confident in the results of the simulations. Delayed gamma transport is one important component of these detection scenarios. Delayed gamma transport is defined as the combination of gamma emission from radioactive and subsequent transport through matter. MCNP always possessed the ability to emit delayed neutrons from fission; however, these delayed neutron spectra and intensity were functional fits and not directly sampled from the created fission products. Furthermore, there existed no method to emit the decay photons from radioactive fission products (or any radioactive nucleus) A delayed particle capability was initially added to MCNPX 2.6.A in 2005 to sample the radioactive fission product parents and emit decay particles resulting from the decay chain. At the point of capture, a residual nucleus is created and decayed using the CINDER90 depletion code. MCNP only sends CINDER90 a residual radioactive nucleus and not a flux (i.e. capture rate). As a result, the Bateman equations for the solution are coupled first order differential equations with constant coefficients. Theoretically, these equations could be solved analytically; however, CINDER90 employs a numerical Markov linear chain scheme to solve these equations. This paper addresses a more simplified approach to benchmarking in order to best assess: (1) whether or not deficiencies exist in the current methodology for certain types of decay chains; and (2) paths forward for improving the delayed particle emission capability. We utilize closed form analytic solutions to the granddaughter equations for particular sets of isotope systems to compare the accuracy of the delayed gamma capability in MCNP6. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Linear dependence of surface expansion speed on initial plasma temperature in warm dense matter

Recent progress in laser-driven quasi-monoenergetic ion beams enabled the production of uniformly heated warm dense matter. Matter heated rapidly with this technique is under extreme temperatures and pressures, and promptly expands outward. While the expansion speed of an ideal plasma is known to have a square-root dependence on temperature, computer simulations presented here show a linear dependence of expansion speed on initial plasma temperature in the warm dense matter regime. The expansion of uniformly heated 1–100 eV solid density gold foils was modeled with the RAGE radiation-hydrodynamics code, and the average surface expansion speed was found to increase linearly with temperature. The origin of this linear dependence is explained by comparing predictions from the SESAME equation-of-state tables with those from the ideal gas equation-of-state. In conclusion, these simulations offer useful insight into the expansion of warm dense matter and motivate the application of optical shadowgraphy for temperature measurement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Pre-Equilibrium De-Excitations in Neutrino-Nucleus Interactions

Pre-equilibrium de-excitation is a well-established stage of nucleon-induced nuclear reactions but has not previously been incorporated into neutrino event generators. This work implements the Koning-Duijvestijn exciton model within the MARLEY neutrino event generator to simulate energy redistribution and particle emission before compound nucleus equilibrium. The implementation includes modular calculations of particle-hole state densities, internal transition rates, emission rates, and Monte Carlo cascade sampling, and is validated against the TALYS-2.2 nuclear reaction code. A new event record is also proposed to enable future uncertainty reweighting studies. This work establishes the first framework for studying pre-equilibrium effects in neutrino-induced reactions, with the goal of improving predictions of particle multiplicities, γ-ray production, and MeV-scale detector signals relevant to experiments such as DUNE.

Visser, Erin [Michigan State U., East Lansing (mai↗

κ -distributed protons in the solar wind and their charge-exchange coupling to energetic hydrogen

The interaction between the solar wind and the interstellar medium represents a collision between two plasma flows, resulting in a heliosphere with an extended tail. While the solar wind is mostly ionized material from the corona, the interstellar medium is only partially ionized. The ion and neutral populations are coupled through charge-exchange collisions that operate on length scales of tens to hundreds of astronomical units. About half the interstellar hydrogen flows into the heliosphere where it may charge-exchange with solar wind protons. This process gives rise to a nonthermal proton, known as a pickup ion, which joins the plasma. In this paper we investigate the effects of approximating the total ion distribution of the subsonic solar wind as a generalized Lorentzian, or κ distribution, using an MHD neutral code. We illustrate the effect different values of the κ parameter have on both the structure of the heliosphere and the energetic neutral atom flux at 1 AU. We find that using a κ distribution in our simulations yields levels of energetic neutral atom flux that are within a factor of about 2 or 3 over the IBEX-Hi range of energies from 0.5 to 6 keV. In conclusion, while the presence of a suprathermal tail in the proton distribution leads to the production of high-energy neutrals, the sharp decline in the charge-exchange cross section around 10 keV mitigates the enhanced transfer of energy from the ions to the neutrals that might otherwise be expected.

79 ASTRONOMY AND ASTROPHYSICS↗

A New Standard DNA Damage (SDD) Data Format

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called “indirect” damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates intermodel comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to significantly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Potential Ideas for an El Capitan Center of Excellence (COE) Around Intelligent Simulation

Proposing a Center of Excellence under the CORAL-2 NRE is a mandatory requirement. The current Sierra COE (CORAL-1) is largely focused on helping LLNL applications make the disruptive transition to a heterogeneous GPU-based system by 2018. We expect a continuation of COE activities around optimizing our broad and diverse application base (of so-called “traditional” simulation codes) optimized for the El Capitan architecture, as well as supporting the underlying software stack (compilers, tools, programming models, etc.) – but do not expect this to require as much effort in the El Capitan COE (assuming a heterogeneous node architecture). What follows are some thoughts on 3 potential topics of interest for an El Capitan COE at LLNL – largely focused around AI and machine learning and the concept of advancing our goal of intelligent simulation or cognitive computing in the timeframe of deployment and production use of El Capitan (2023-2038). We believe vendor engagement through a COE in this area will provide a natural point-of-interest between LLNL and our vendor partner for common advancement of machine learning capabilities focused on scientific data – potentially greatly broadening the ecosystem around HPC architectures and the supporting software stack for scientific simulation-based AI.

97 MATHEMATICS AND COMPUTING↗