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At least 883 records · Page 49

Measurement and modeling of proton-induced reactions on arsenic from 35 to 200 MeV

72 As is a promising positron emitter for diagnostic imaging that can be employed locally using a 72 Se generator. However, current reaction pathways to 72 Se have insufficient nuclear data for efficient production using regional 100–200 MeV high-intensity proton accelerators. In order to address this deficiency, stacked-target irradiations were performed at LBNL, LANL, and BNL to measure the production of the 72 Se/ 72 As positron emission tomography (PET) generator system via 75 As (p, x) between 35 and 200 MeV. This work provides the most well-characterized excitation function for 75 As ( p , 4 n ) 72 Se starting from threshold. Additional focus was given to report the first measurements of 75 As (p, x) 68 Ge and bolster an already robust production capability for the highly valuable 68 Ge/ 68 Ga PET generator. Thick target yield comparisons with prior established formation routes to both generators are made. In total, high-energy proton-induced cross sections are reported for 55 measured residual products from 75 As, nat Cu , and nat Ti targets, where the latter two materials were present as monitor foils. These results were compared with literature data as well as the default theoretical calculations of the nuclear model codes TALYS, COH, EMPIRE, and ALICE. Reaction modeling at these energies is typically unsatisfactory due to few prior published data and many interacting physics models. Therefore, a detailed assessment of the talys code was performed with simultaneous parameter adjustments applied according to a standardized procedure. Particular attention was paid to the formulation of the two-component exciton model in the transition between the compound and preequilibrium regions, with a linked investigation of level density models for nuclei off of stability and their impact on modeling predictive power. This paper merges experimental work and evaluation techniques for high-energy charged-particle isotope production in an extension to an earlier study of this kind.

43 PARTICLE ACCELERATORS↗

SYS-5620-Project - Achieving Robust Laser Performance utilizing Historical Shot Experiments - A Systems Engineering Proposal

The National Ignition Facility (NIF) at Lawrence Livermore National Laboratory precisely guides, amplifies, reflects, and focuses 192 powerful laser beams into a target about the size of a pencil eraser in a few billionths of a second, delivering more than 2 million joules of ultraviolet energy and 500 trillion watts of peak power. A crucial goal of the system is to trigger precise implosions of fuel capsules. This is achieved by delivering all 192 beams at user-specified times and locations on the target, minimizing any deviation from the requested performance. Power requirements can vary substantially on each experiment and the facility supports numerous amplifier pumping configurations and their attendant nonlinear effects. To achieve the tight performance required across such a broad array of configurations, constant comparison of measured and requested power delivery are tracked and long-term trends analyzed as a guide to understanding future performance. A very common question asked is given the current state of the laser today – how well would a similar experiment from the past perform today? Additionally, if one were to specify an alternate amplifier configuration using today’s model would and damage limits be exceeded and would there be an increase in performance. The physics model used to make these predictions and equipment protection checks is called the Virtual Beamline (VBL). VBL is used with an incoming desired pulse shape and energy to be delivered on target, and then does an iterative solve to predict the needed injected pulse in the front-end of the system to achieve this result. To effectively guide and predict future NIF experiment performance, laser scientists explore current amplifier configurations and compare them with historical data utilizing a tool called the Reverify Toolbox.

42 ENGINEERING↗

Rotating-fluid experiments with an atmospheric general circulation model

In order to determine features of rotating fluid flow that are dependent on the geometry, rotating annulus-type experiments are carried out with a numerical model in spherical coordinates. Rather than constructing and testing a model expressly for this purpose, it is found expedient to modify an existing general circulation model of the atmosphere by removing the model physics and replacing the lower boundary with a uniform surface. A regime diagram derived from these model experiments is presented; its major features are interpreted and contrasted with the major features of rotating annulus regime diagrams. Within the wave regime, a narrow region is found where one or two zonal wave numbers are dominant. The results reveal no upper symmetric regime; wave activity at low rotation rates is thought to be maintained by barotropic rather than baroclinic processes.

Geisler, J. E.↗

Emissions Prediction and Measurement for Liquid-Fueled TVC Combustor with and without Water Injection

An investigation is performed to evaluate the performance of a computational fluid dynamics (CFD) tool for the prediction of the reacting flow in a liquid-fueled combustor that uses water injection for control of pollutant emissions. The experiment consists of a multisector, liquid-fueled combustor rig operated at different inlet pressures and temperatures, and over a range of fuel/air and water/fuel ratios. Fuel can be injected directly into the main combustion airstream and into the cavities. Test rig performance is characterized by combustor exit quantities such as temperature and emissions measurements using rakes and overall pressure drop from upstream plenum to combustor exit. Visualization of the flame is performed using gray scale and color still photographs and high-frame-rate videos. CFD simulations are performed utilizing a methodology that includes computer-aided design (CAD) solid modeling of the geometry, parallel processing over networked computers, and graphical and quantitative post-processing. Physical models include liquid fuel droplet dynamics and evaporation, with combustion modeled using a hybrid finite-rate chemistry model developed for Jet-A fuel. CFD and experimental results are compared for cases with cavity-only fueling, while numerical studies of cavity and main fueling was also performed. Predicted and measured trends in combustor exit temperature, CO and NOx are in general agreement at the different water/fuel loading rates, although quantitative differences exist between the predictions and measurements.

Brankovic, A.↗

The FLUKA code for space applications: recent developments

The FLUKA Monte Carlo transport code is widely used for fundamental research, radioprotection and dosimetry, hybrid nuclear energy system and cosmic ray calculations. The validity of its physical models has been benchmarked against a variety of experimental data over a wide range of energies, ranging from accelerator data to cosmic ray showers in the earth atmosphere. The code is presently undergoing several developments in order to better fit the needs of space applications. The generation of particle spectra according to up-to-date cosmic ray data as well as the effect of the solar and geomagnetic modulation have been implemented and already successfully applied to a variety of problems. The implementation of suitable models for heavy ion nuclear interactions has reached an operational stage. At medium/high energy FLUKA is using the DPMJET model. The major task of incorporating heavy ion interactions from a few GeV/n down to the threshold for inelastic collisions is also progressing and promising results have been obtained using a modified version of the RQMD-2.4 code. This interim solution is now fully operational, while waiting for the development of new models based on the FLUKA hadron-nucleus interaction code, a newly developed QMD code, and the implementation of the Boltzmann master equation theory for low energy ion interactions. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Non-NASA Center↗

Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm

Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.

Liechty, Derek S.↗

Gas-Particle Interaction Model Development in Plume Surface Interaction Erosion and Cratering

The development of a predictive simulation capability for extra-terrestrial Plume Surface Interaction (PSI) environments is undertaken by the Fluid Dynamics Branch at NASA/MSFC under the Game Changing Development (GCD) Program funded by NASA’s Space Technology Mission Directorate (STMD). Predictive simulation capability for propulsive Martian and Lunar landing PSI requires accurate modeling of the complex high-speed plume impingement and resulting gas/particle-cloud and ejecta stream formation. Physics modeling gap analysis during formulation of the PSI project scope identified two particular phenomena of first order importance in gas-particle interactions that lacked existing modeling formulations. The first arises from the lack of models capturing the unsteady drag forces imparted on particles by the rapidly expanding supersonic compressible flow. The second addresses the fluctuating forces and dispersions imparted on both the particle and the fluid resulting from the interference and wake turbulence generated by close proximity particle clouds, dubbed the Particle Turbulent Kinetic Energy(PTKE). Their first order significance has been identified in experiments, but simulation models currently do not exist for either effect. The development of models and the eventual implementation into the Eulerian Gas-Granular Flow Solver (GGFS) simulation tools was constructed as one of four major tasks of the PSI project. In this process, data on particle kinetics and gas-particle interactions are collected from carefully designed experiments of particles embedded in jets. The effects observed in the experiments are then replicated in high-fidelity particle-resolved CFD simulations to inform the formulation of improvements to particle phase drag models for implementations in the more efficient Eulerian-Lagrangian CFD simulations. The resulting models are ultimately ported to the Eulerian-Eulerian models applied for most efficient simulations in PSI production application tools. This paper describes the activities and accomplishments of the past year in the gas-particle interaction modeling task of the PSI project.

Jeff West↗

e + e – → ZH process in the SMEFT beyond leading order

We systematically study potential effects of Beyond the Standard Model physics in the e + e – → ZH process. To this end, we include all relevant dimension-6 Standard Model Effective Field Theory operators and work to next-to-leading order (NLO) accuracy in the electroweak coupling. We consider both polarized and unpolarized electron and positron beams and present results for $\sqrt {s}$ = 240, 365 and 500 GeV, emphasizing contributions where the NLO predictions differ significantly from the leading order results. At NLO, a sensitivity arises to operators that do not contribute at tree level, such as the Higgs tri-linear coupling, CP-violating operators, and dimension-6 operators involving the top quark, among many others. We compare the prospects of future e + e – colliders to explore these new physics effects with existing measurements from the LHC, electron EDMs (for CP violating operators), and Z pole measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Time-dependent density-functional-theory calculations of the nonlocal electron stopping range for inertial confinement fusion applications

Nonlocal electron transport is important for understanding laser-target coupling for laser-direct-drive (LDD) inertial confinement fusion (ICF) simulations. Current models for the nonlocal electron mean free path in radiation-hydrodynamic codes are based on plasma-physics models developed decades ago; improvements are needed to accurately predict the electron conduction in LDD simulations of ICF target implosions. Here we utilized time-dependent density functional theory (TD-DFT) to calculate the electron stopping power (SP) in the so-called conduction-zone plasmas of polystyrene in a wide range of densities and temperatures relevant to LDD. Compared with the modified Lee-More model, the TD-DFT calculations indicated a lower SP and a higher stopping range for nonlocal electrons. We fit these electron SP calculations to obtain a global analytical model for the electron stopping range as a function of plasma conditions and the nonlocal electron kinetic energy. This model was implemented in the one-dimensional radiation-hydrodynamic code LILAC to perform simulations of LDD ICF implosions, which are further compared with simulations by the standard modified Lee-More model. In conclusion, results from these integrated simulations are discussed in terms of the implications of this TD-DFT-based mean-free-path model to ICF simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data-driven Whitney forms for structure-preserving control volume analysis

Control volume analysis models physics via the exchange of generalized fluxes between subdomains. Here, we introduce a scientific machine learning framework adopting a partition of unity architecture to identify physically-relevant control volumes, with generalized fluxes between subdomains encoded via Whitney forms. The approach provides a differentiable parameterization of geometry which may be trained in an end-to-end fashion to extract reduced models from full field data while exactly preserving physics. The architecture admits a data-driven finite element exterior calculus allowing discovery of mixed finite element spaces with closed form quadrature rules. An equivalence between Whitney forms and graph networks reveals that the geometric problem of control volume learning is equivalent to an unsupervised graph discovery problem. The framework is developed for manifolds in arbitrary dimension, with examples provided for H(div) problems in $\mathbb{R}$ establishing convergence and structure preservation properties. Finally, we consider a lithium-ion battery problem where we discover a reduced finite element space encoding transport pathways from high-fidelity microstructure resolved simulations. The approach reduces the 5.89M finite element simulation to 136 elements while reproducing pressure to under 0.1% error and preserving conservation.

97 MATHEMATICS AND COMPUTING↗

Update On the Status of the FLUKA Monte Carlo Transport Code*

The FLUKA Monte Carlo transport code is a well-known simulation tool in High Energy Physics. FLUKA is a dynamic tool in the sense that it is being continually updated and improved by the authors. We review the progress achieved since the last CHEP Conference on the physics models, some technical improvements to the code and some recent applications. From the point of view of the physics, improvements have been made with the extension of PEANUT to higher energies for p, n, pi, pbar/nbar and for nbars down to the lowest energies, the addition of the online capability to evolve radioactive products and get subsequent dose rates, upgrading of the treatment of EM interactions with the elimination of the need to separately prepare preprocessed files. A new coherent photon scattering model, an updated treatment of the photo-electric effect, an improved pair production model, new photon cross sections from the LLNL Cullen database have been implemented. In the field of nucleus-- nucleus interactions the electromagnetic dissociation of heavy ions has been added along with the extension of the interaction models for some nuclide pairs to energies below 100 MeV/A using the BME approach, as well as the development of an improved QMD model for intermediate energies. Both DPMJET 2.53 and 3 remain available along with rQMD 2.4 for heavy ion interactions above 100 MeV/A. Technical improvements include the ability to use parentheses in setting up the combinatorial geometry, the introduction of pre-processor directives in the input stream. a new random number generator with full 64 bit randomness, new routines for mathematical special functions (adapted from SLATEC). Finally, work is progressing on the deployment of a user-friendly GUI input interface as well as a CAD-like geometry creation and visualization tool. On the application front, FLUKA has been used to extensively evaluate the potential space radiation effects on astronauts for future deep space missions, the activation dose for beam target areas, dose calculations for radiation therapy as well as being adapted for use in the simulation of events in the ALICE detector at the LHC.

Ferrari, A.↗

Implementation of Triply Periodic Minimal Surfaces (TPMS) as surface objects in OpenMC

Triply Periodic Minimal Surfaces (TPMS) represent a promising geometry for future fuel designs due to their significant surface-to-volume ratio, which facilitates efficient cooling of nuclear fuel, a crucial factor for safety and efficiency. Demonstrating the remarkable capabilities of TPMS fuel requires initial modeling and simulation. This paper presents an implementation of TPMS in the Monte Carlo code OpenMC, enabling reactor physics modeling of TPMS. Here, the primary advantages over traditional methods using CAD files include reduced memory requirements for computations and high-fidelity implementation. This implementation has been tested against CAD files loaded in Serpent2, yielding promising results with low biases in the $k_{\textrm{eff}}$, comparable to biases in the material balance sheet. The implementation presented in this work will be used in future reactor physics computations related to new reactor designs involving TPMS-based fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Automatic Differentiation in MetaPhysicL and Its Applications in MOOSE

Efficient solution via Newton’s method of nonlinear systems of equations requires an accurate representation of the Jacobian, corresponding to the derivatives of the component residual equations with respect to the degrees of freedom. In practice these systems of equations often arise from spatial discretization of partial differential equations used to model physical phenomena. These equations may involve domain motion or material equations that are complex functions of the systems’ degrees of freedom. Computing the Jacobian by hand in these situations is arduous and prone to error. Finite difference approximations of the Jacobian or its action are prone to truncation error, especially in multiphysics settings. Symbolic differentiation packages may be used, but often result in an excessive number of terms in realistic model scenarios. An alternative to symbolic and numerical differentiation is automatic differentiation (AD), which propagates derivatives with every elementary operation of a computer program, corresponding to continual application of the chain rule. Automatic differentiation offers the guarantee of an exact Jacobian at a relatively small overhead cost. In this work, we outline the adoption of AD in the Multiphysics Object Oriented Simulation Environment (MOOSE) via the MetaPhysicL package. We describe the application of MOOSE’s AD capability to several sets of physics that were previously infeasible to model via hand-coded or Jacobian-free simulation techniques, including arbitrary Lagrangian-Eulerian and level-set simulations of laser melt pools, phase-field simulations with free energies provided through neural networks, and metallic nuclear fuel simulations that require inner Newton loop calculation of nonlinear material properties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of biomechanical models for human factors evaluations

Computer aided design (CAD) techniques are now well established and have become the norm in many aspects of aerospace engineering. They enable analytical studies, such as finite element analysis, to be performed to measure performance characteristics of the aircraft or spacecraft long before a physical model is built. However, because of the complexity of human performance, CAD systems for human factors are not in widespread use. The purpose of such a program would be to analyze the performance capability of a crew member given a particular environment and task. This requires the design capabilities to describe the environment's geometry and to describe the task's requirements, which may involve motion and strength. This in turn requires extensive data on human physical performance which can be generalized to many different physical configurations. PLAID is developing into such a program. Begun at Johnson Space Center in 1977, it was started to model only the geometry of the environment. The physical appearance of a human body was generated, and the tool took on a new meaning as fit, access, and reach could be checked. Specification of fields-of-view soon followed. This allowed PLAID to be used to predict what the Space Shuttle cameras or crew could see from a given point.

Woolford, Barbara↗

Understanding Subsurface Fracture Evolution Dynamics Using Time‐Lapse Full Waveform Inversion of Continuous Active‐Source Seismic Monitoring Data

Abstract Predicting the behavior, geometry, and flow properties of subsurface fractures remains a challenging problem. Seismic models that can characterize fractures usually suffer from low spatiotemporal resolution. Here, we develop a correlative double‐difference time‐lapse full waveform inversion of continuous active source seismic monitoring data for determining high‐spatiotemporal‐resolution time‐lapse V p models of in‐situ fracture evolution at a shallow contamination site in Wyoming, USA. Assisted by rock physics modeling, we find that (a) rapidly increasing pore pressure initializes and grows the fracture, increasing the porosity slightly (from ∼13.7% to ∼14.6%) in the tight clay formation, thus decreasing V p (∼50 m/s); (b) the fluid injection continues decreasing V p , likely through the introduction of gas bubbles in the injectate; and (c) final V p reductions reach over ∼150 m/s due to a posited ∼4.5% gas saturation. Our results demonstrate that high‐resolution V p changes are indicative of mechanical and fluid changes within the fracture zone during hydrofracturing.

58 GEOSCIENCES↗

TEAL

TEAL is a financial performance calculator plugin for the RAVEN code, framework, resolving around the computation of Net Present Value and associated financial metrics. TEAL can make use of inflation rates, taxation, escalation factors, capital expenditure economy of scale scaling factors. The unique feature of TEAL is the capability to be linked with RAVEN external models and build corresponding cash flows using the variables computed by those external models. In addition to be able to use the capability to generate cash flows derived from complex physical models generated by RAVEN, another distinctive feature of TEAL is the capability to provide financial risk/probabilistic metrics that can empower RAVEN to perform optimization/analysis driven by financial risk augmentations. Optimization, robust optimization, parametric studies, large parallel simulations, sensitivity analysis, data mining, etc. are just some of the capabilities that can be leveraged.

Alfonsi, Andrea↗

The LBNF/DUNE Complex for Neutrino Science

The Long Baseline Neutrino Facility (LBNF) provides the underground detector caverns, the beamline to deliver a 1.2MW proton beam, and a target station to produce neutrinos for the international Deep Underground Neutrino Experiment (DUNE). A mile underground, caverns are being excavated and outfitted at the Sanford Underground Research Facility in South Dakota. The beamline facility and an additional near detector facility will be constructed on the Fermilab site in Illinois. DUNE will make precision neutrino oscillation physics measurements and will be sensitive to neutrinos from supernova bursts, nucleon decay, and beyond-standard-model physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗