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At least 559 records · Page 31

Simulation toolkit for digital material characterization of large image-based microstructures

In this paper, an efficient image-based simulation toolkit for material characterization is presented, which is scalable to work from personal computers to workstations. The effective thermal conductivity, elasticity, and permeability are evaluated employing a computational homogenization framework based on the Finite Element Method (FEM). Two complementary open-source packages are presented: one developed in Python, which can convert digital images into voxel meshes (pyTomoviewer); the other developed in Julia, that can run numerical simulations to compute effective material properties (chpack). Also, a CUDA C version of chpack is provided (chfem_gpu). They were designed to deal with large multi-phase models, so strategies were devised to minimize their memory footprint, while avoiding a high toll on execution time. The voxel-based approach significantly simplifies the FEM meshes and allows efficient matrix-free implementations. In that sense, to handle large linear systems of equations, the element-by-element (EBE) technique is adopted, in conjunction with a low-memory implementation of the Preconditioned Conjugate Gradient (PCG) method. Finally, the code was thoroughly tested on an artificial geometry made of a square array of cylinders, for which analytical solutions exist, as well as on a real micro-tomographic reconstruction of FiberForm TM , a carbon preform commonly used in thermal protection systems.

36 MATERIALS SCIENCE↗

Combining Physics and Machine Learning for the Next Generation of Molecular Simulation

Simulating molecules and atomic systems at quantum accuracy is a grand challenge for science in the 21 st century. Quantum-accurate simulations would enable the design of new medicines and the discovery of new materials. The defining problem in this challenge is that quantum calculations on large molecules, like proteins or DNA, are fundamentally impossible with current algorithms. In this work, we explore a range of different methods that aim to make large, quantum-accurate simulations possible. We show that using advanced classical models, we can accurately simulate ion channels, an important biomolecular system. We show how advanced classical models can be implemented in an exascale-ready software package. Lastly, we show how machine learning can learn the laws of quantum mechanics from data and enable quantum electronic structure calculations on thousands of atoms, a feat that is impossible for current algorithms. Altogether, this work shows that combining advances in physics models, computing, and machine learning, we are moving closer to the reality of accurately simulating our molecular world.

74 ATOMIC AND MOLECULAR PHYSICS↗

Design of a Cryogenic Scintillation Neutrino Detector at the Spallation Neutron Source

We successfully verified in the following three aspects the feasibility of using a cryogenic scintillating crystal-based neutrino detector at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory, for the detection of low-mass dark matter particles and non-standard neutrino interactions (NSIs), as part of the detector R&D effort of the COHERENT experiment. First, we demonstrated the possibility of using silicon photomultipliers (SiPMs) at cryogenic temperatures to replace traditional photomultiplier tubes (PMTs) as light sensors. Second, we verified that the high light yield of undoped CsI crystals measured above 13 keVee at 77 K still holds down to 5.9 keVee. Third, we successfully measured nuclear quenching factor of undoped cryogenic CsI at the Triangle Universities Nuclear Laboratory with the help from our Duke collaborators. The first achievement resulted in a publication in European Physics Journal C. The second resulted in an arXiv pre-print, which is under journal review. The last one indicates that the performance of the proposed detector may be better than what was assumed in the literature. The analysis is in the final stage and will result in another journal publication. In addition, two graduate students involved in this project graduated with master’s degrees during the project period. Both decided to continue their research as PhD students. One open-source data analysis code package was created and is publicly available on GitHub. A set of tutorials about Monte Carlo simulation of radiation interacting with detectors were created on YouTube, receiving more than 100,000 views.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production

Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farquhar–von Caemmerer–Berry model for C 3 photosynthesis with an optimality principle for the carbon assimilation–transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C 3 vegetation type. The model builds on the theory developed in Prentice et al. (2014) and Wang et al. (2017a) and is extended to include low temperature effects on the intrinsic quantum yield and an empirical soil moisture stress factor. The model is forced with site-level data of the fraction of absorbed photosynthetically active radiation (fAPAR) and meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs, the R 2 for predicted versus observed GPP based on the full model setup is 0.75 (8 d mean, 126 sites) – similar to comparable satellite-data-driven GPP models but without predefined vegetation-type-specific parameters. The R 2 is reduced to 0.70 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R 2 for the P-model-predicted LUE is 0.32 (means by site) and 0.48 (means by vegetation type). Applying this model for global-scale simulations yields a total global GPP of 106–122 Pg C yr –1 (mean of 2001–2011), depending on the fAPAR forcing data. The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosynthesis across a wide range of conditions. The model is available as an R package (rpmodel).

54 ENVIRONMENTAL SCIENCES↗

TRANSLATE - a Monte Carlo simulation of electron transport in liquid argon

Here, the microphysics of electron and photon propagation in liquid argon is a key component of detector design and calibrations needed to construct and perform measurements within a wide range of particle physics experiments. As experiments grow in scale and complexity, and as the precision of their intended measurements increases, the development of tools to investigate important microphysics effects impacting such detectors becomes necessary. In this paper we present a new time-domain Monte Carlo simulation of electron transport in liquid argon. The simulation models the TRANSport in Liquid Argon of near-Thermal Electrons (TRANSLATE) with the aim of providing a multi-purpose software package for the study and optimization of detector environments, with a particular focus on ongoing and next generation liquid argon neutrino experiments utilizing the time projection chamber technology. TRANSLATE builds on previous work of Wojcik and Tachiya, amongst others, introducing additional processes, including ionization, thus modeling the full range of drift electron scattering interactions. The simulation is validated by benchmarking its performance with swarm parameters from data collected in experimental setups operating in gas and liquid.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The XFaster Power Spectrum and Likelihood Estimator for the Analysis of Cosmic Microwave Background Maps

We present the XFaster analysis package, XFaster is a fast, iterative angular power spectrum estimator based on a diagonal approximation to the quadratic Fisher matrix estimator. XFaster uses Monte Carlo simulations to compute noise biases and filter transfer functions and is thus a hybrid of both Monte Carlo and quadratic estimator methods. In contrast to conventional pseudo-C ℓ based methods, the algorithm described here requires a minimal number of simulations, and does not require them to be precisely representative of the data to estimate accurate covariance matrices for the bandpowers. The formalism works with polarization-sensitive observations and also data sets with identical, partially overlapping, or independent survey regions. The method was first implemented for the analysis of BOOMERanG data (Netterfield et al. 2002; Jones et al. 2006), and also used as part of the Planck analysis (Rocha et al. 2011). Here, we describe the full, publicly available analysis package, written in Python, as developed for the analysis of data from the 2015 flight of the SPIDER instrument (SPIDER Collaboration 2021). The package includes extensions for self-consistently estimating null spectra and for estimating fits for Galactic foreground contributions. We show results from the extensive validation of XFaster using simulations, and its application to the SPIDER data set.

79 ASTRONOMY AND ASTROPHYSICS↗

Auto-BLAST (AutoBLAST) [SWR-20-93]

Battery life modeling often involves a lot of manual parameter fitting and is not easy for users to adopt the model and use it. To reduce the difficulties for users to adopt battery lifetime models, an automatic battery lifetime modeling analysis and simulation tool suite, Auto-BLAST, has been developed. Auto-BLAST includes a lithium-loss-base life model, a battery electric model, and an algorithm which automatically fits all key parameters in the electric and life models using user provided data. The models and algorithm are packaged into two user-friendly GUIs, Auto-LifeMod, for easy battery life prognostic model fitting and Auto-LifeSim, for easy battery lifetime simulation. The lithium-loss-based life model adopts a similar model framework that models degradations using aging rate models, using battery cycling data to predict battery degradation and expected lifetime. The electric model is an equivalent circuit model which simulates battery voltage responses based on current/power demand profiles. The auto-fitting algorithm uses the user-input data to generate custom battery life model(s). Two GUIs, wrapping around the life model and the auto-fitting algorithm, provide friendly interfaces for users to generate a life model and use it for case study. One GUI requires summary data from accelerated battery life degradation tests as an input and produces battery life models predicting (a) capacity degradation, and (b) resistance growth of the battery. The GUI displays the electrical model response and the input experimental data against the life model predictions with fitted model parameters and fitting error. The GUI also generates an output file to save the fitted model parameters. The second GUI uses the life model from the first GUI and a user-defined battery cycling profile to predict battery lifetime degradation and expected lifetime. Predicted capacity and resistance vs. time are plotted in the GUI and saved to output file. There is a user guide for both GUIs

Mishra, Partha↗

A Double-side Cooled SiC MOSFET Power Module with Sintered-silver Interposers: I. Design, Simulation, Fabrication, and Performance Characterization

Planar, double-side cooled power modules are emerging in electric-drive inverters because of their low profile, better heat extraction, and lower package parasitic inductances. However, there is still concern about their reliability due to the rigid interconnection between the device chips and two substrates of the power module. In this paper, a porous interposer made of low-temperature sintered silver is introduced to reduce the thermo-mechanical stresses in the module. A double-side cooled half-bridge module consisting of two 1200 V, 149 A SiC MOSFETs was designed, fabricated, and characterized. By using the sintered-Ag instead of solid copper interposers, our simulation results showed that at a total power loss of 200 W, the thermo-mechanical stress at the most vulnerable interfaces (interposer-attach layer) was reduced by 42 % and in the SiC MOSFET by 50 % with a trade-off of only 3.6 % increase in junction temperature. The sintered-Ag interposers were readily fabricated into desired dimensions without post-machining and did not require any surface finishing for die-bonding and substrate interconnection by silver sintering. Here, the porous interposers were also deformable under a low force or pressure, which helped to accommodate chip thickness and/or substrate-to-substrate gap variations in the planar module structure, thus simplifying module fabrication. Experimental results on the electrical performance of the fabricated SiC modules validated the success of using the porous silver interposers for fabricating planar, double-side cooled power modules.

42 ENGINEERING↗

CTRAMER: An open-source software package for correlating interfacial charge transfer rate constants with donor/acceptor geometries in organic photovoltaic materials

In this paper, we present CTRAMER (Charge-Transfer RAtes from Molecular dynamics, Electronic structure, and Rate theory)—an opensource software package for calculating interfacial charge-transfer (CT) rate constants in organic photovoltaic (OPV) materials based on ab initio calculations and molecular dynamics simulations. The software is based on identifying representative donor/acceptor geometries within interfacial structures obtained from molecular dynamics simulation of donor/acceptor blends and calculating the corresponding Fermi’s golden rule CT rate constants within the framework of the linearized-semiclassical approximation. While the methods used are well established, the integration of these state-of-the-art tools originating from different disciplines to study photoinduced CT processes with explicit treatment of the environment, in our opinion, makes this package unique and innovative. The software also provides tools for investigating other observables of interest. After outlining the features and implementation details, the usage and performance of the software are demonstrated with results from an example OPV system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

pymatgen-analysis-defects: A Python package for analyzing point defects in crystalline materials

Point defects can often determine the properties of semiconductor and optoelectronic materials. Due to the large simulation cell and the higher-cost density functionals required for defect simulations, the computational cost of defect calculations is often orders of magnitude higher than that of bulk calculations. As such, managing and curating the results of the defect calculations generated by a single user has the potential to save a significant amount of computational resources. Moreover, eventually building a high-quality, persistent defects database will significantly reduce the computational cost of defect calculations for the entire community.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A fast particle-mesh simulation of non-linear cosmological structure formation with massive neutrinos

Quasi-N-body simulations, such as FastPM, provide a fast way to simulate cosmological structure formation, but have yet to adequately include the effects of massive neutrinos. In this work, we present a method to include neutrino particles in FastPM, enabling computation of the CDM and total matter power spectra to percent-level accuracy in the non-linear regime. The CDM-neutrino cross-power can also be computed at a sufficient accuracy to constrain cosmological observables. To avoid the shot noise that typically plagues neutrino particle simulations, we employ a quasi-random algorithm to sample the relevant Fermi-Dirac distribution when setting the initial neutrino thermal velocities. We additionally develop an effective distribution function to describe a set of non-degenerate neutrinos as a single particle to speed up non-degenerate simulations. The simulation is accurate for the full range of physical interest, M ν ≲ 0.6eV, and applicable to redshifts z ≲ 2. Such accuracy can be achieved by initializing particles with the two-fluid approximation transfer functions (using the REPS package). Convergence can be reached in ~ 25 steps, with a starting redshift of z=99. Probing progressively smaller scales only requires an increase in the number of CDM particles being simulated, while the number of neutrino particles can remain fixed at a value less than or similar to the number of CDM particles. In turn, the percentage increase in runtime-per-step due to neutrino particles is between ~ 5-20% for runs with 1024 3 CDM particles, and decreases as the number of CDM particles is increased. The code has been made publicly available, providing an invaluable resource to produce fast predictions for cosmological surveys and studying reconstruction.

79 ASTRONOMY AND ASTROPHYSICS↗

Hanford Composite Analysis Special Studies FY2025 - Groundwater Flow Simulation for use in a Comparison of Simulated Concentrations in the Saturated Zone Estimated by the Plateau-to-River Model Versions 8.3 and 9.1

In order to meet the requirements of U.S. Department of Energy (DOE) in DOE O 435.1, Radioactive Waste Management, a composite analysis (CA) must be completed for the Central Plateau at the Hanford Site. The CA requires estimates of fate and transport of radionuclides in the groundwater from multiple sources within the modeling domain. This Environmental Calculation File (ECF) details the application of the Plateau-to-River (P2R) Model (CP-57037, Rev. 3, Model Package Report for the P2R Model: Version 9.1) to predict the flow of groundwater on the Central Plateau for the 10,000-year simulation to support a special analysis associated with the Hanford Site CA. The simulated flow field will support the simulation of fate and transport of contaminants for comparison to the results obtained as part of the CA to evaluate impact of the updated version of the P2R Model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Object-space optimization of tomographic reconstructions for additive manufacturing

Volumetric 3D printing motivated by computed axial lithography enables rapid printing of homogeneous parts but requires a high dimensionality gradient-descent optimization to calculate image sets. Here we introduce a new, simpler approach to image-computation that algebraically optimizes a model of the printed object, significantly improving print accuracy of complex parts under imperfect material and optical precision by improving optical dose contrast between the target and surrounding regions. Quality metrics for volumetric printing are defined and shown to be significantly improved by the new algorithm. The approach is extended beyond binary printing to grayscale control of conversion to enable functionally graded materials. The flexibility of the technique is digitally demonstrated with realistic projector point spread functions, printing around occluding structures, printing with restricted angular range, and incorporation of materials chemistry such as inhibition. Finally, simulations show that the method facilitates new printing modalities such as printing into flat, rather than cylindrical packages to extend the applications of volumetric printing.

36 MATERIALS SCIENCE↗

Commissioning a time-gated camera for fast neutron beamline spatial-energy characterization at LANSCE-WNR spallation source

An energy-resolved fast neutron beam imaging diagnostic has been successfully commissioned at the Weapons Neutron Research (WNR) spallation source within the Los Alamos Neutron Science Center (LANSCE) facility. This diagnostic replaces the existing analog phosphor image plates, which integrate across all neutron energies, as well as other particles, with a near-real-time energy-sensitive imaging capability. The system uses a fast plastic scintillator coupled with an intensified CCD camera. Specifically, the Teledyne Pi-MAX4 camera is coupled with either a 4 mm thick Eljen (EJ) 204 or 228 plastic scintillator. These scintillators are most sensitive to the fast neutrons (0.8-800 MeV) directly from the spallation source rather than low energy background radiation. Experimentally, these plastic scintillators were shown to have sufficiently fast decay to differentiate the bright gamma flash from the spallation neutrons. The spatial resolution is dominated by neutron beam divergence, with minimal additional contributions from scatter and light divergence. The system successfully resolved changes in neutron beam characteristics caused by intentional proton steering variations. Additionally, simulations of scintillator light yield as a function of thickness conducted using PHITS (with Scinful-QMD package) found that increasing scintillator thickness from 4 mm to 6 or 8 mm could potentially increase brightness ~ 3x. This may be explored if there is a need to reduce image acquisition time from several minutes to under one minute.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Incident beam optics optimization for the single crystal neutron diffractometer Pioneer with a polarized beam option

Pioneer, a next-generation single-crystal neutron diffractometer, is under development for Oak Ridge National Laboratory’s Second Target Station. Designed to address a wide range of scientific questions, Pioneer will deliver homogeneous neutron beams with customizable size and divergence and provide a polarized beam option. This article introduces its incident beam optics, highlighting the optimization methodology and the simulated performance. Pioneer will utilize a modified elliptical-straight guide for neutron transport and deploy slit packages and insertable apertures to control beam size and divergence. The optimized guide geometry matches the optimal-and-full-sample-illumination condition, and the beam control system effectively filters out unwanted neutrons while preserving the desired ones. In addition, we have found that polygon-approximated guides provide satisfactory transport efficiency and beam homogeneity, eliminating the need for truly curved guides. Further, to enhance neutronics performance and reduce cost, the coatings of supermirror elements are individually optimized to the lowest half-integer m-values that are sufficient to deliver the desired neutrons. After evaluating polarizing V-cavities and 3 He spin filters over the default polarized wavelength band of 1.2–5.5 Å, we selected a translatable multichannel polarizing V-cavity as the incident beam polarizer. Strategically placed at a location where the beam divergence is low and a large in-guide gap has negligible impact on transport efficiency, the optimized V-cavity achieves an average P 2 T of ~35%.

47 OTHER INSTRUMENTATION↗

Inference of experimental radial impurity transport on Alcator C-Mod: Bayesian parameter estimation and model selection

We present a fully Bayesian approach for the inference of radial profiles of impurity transport coefficients and compare its results to neoclassical, gyrofluid and gyrokinetic modeling. Using nested sampling, the Bayesian Impurity Transport InferencE (BITE) framework can handle complex parameter spaces with multiple possible solutions, offering great advantages in interpretative power and reliability with respect to previously demonstrated methods. BITE employs a forward model based on the pySTRAHL package, built on the success of the well-known STRAHL code [Dux, IPP Report, 2004], to simulate impurity transport in magnetically-confined plasmas. In this paper, we focus on calcium (Ca, Z=20) Laser Blow-Off injections into Alcator C-Mod plasmas. Multiple Ca atomic lines are diagnosed via high-resolution X-ray Imaging Crystal Spectroscopy and Vacuum Ultra-Violet measurements. We analyze a sawtoothing I-mode discharge for which neoclassical and turbulent (quasilinear and nonlinear) predictions are also obtained. Here, we find good agreement in diffusion across the entire radial extent, while turbulent convection and density profile peaking are estimated to be larger in experiment than suggested by theory. Efforts and challenges associated with the inference of experimental pedestal impurity transport are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

What is the Right Size for a Residential Building Parcel Locker?

Common-carrier parcel lockers present a solution for decreasing delivery times, traffic congestion, and emissions in dense urban areas through consolidation of deliveries. Multi-story residential buildings with large number of residents, and thus a high volume of online package orders, are one of the best venues for installing parcel lockers. But what is the right size for a residential building locker that would suit the residents’ and building managers’ needs? Because of the novelty of parcel lockers, there is no clear guideline for determining the right locker size and configuration for a residential building given the resident population. A small locker would result in packages exceeding capacity and being left in the lobby, increasing the building manager’s workload and confusing and inconveniencing users. On the other hand, a large locker is more expensive, more difficult to install, and unappealing to residents. To answer this question, we installed a common-carrier parcel locker in a residential building in downtown Seattle, WA, U.S.A. Through collecting detailed data on locker usage from the locker provider company, we studied and quantified carriers’ delivery patterns and residents’ online shopping and package pickup behaviors. We then used this information to model the locker delivery and pickup process, and simulated several locker configurations to find the one that best suits the delivery needs of the building. These findings could aid urban planners and building managers in choosing the right size for residential building lockers that meet delivery demand while minimizing costs and contributing to environmental benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗