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At least 577 records · Page 32

Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in RMCProfile

Structure refinement with reverse Monte Carlo (RMC) is a powerful tool for interpreting experimental diffraction data. To ensure that the under-constrained RMC algorithm yields reasonable results, the hybrid RMC approach applies interatomic potentials to obtain solutions that are both physically sensible and in agreement with experiment. To expand the range of materials that can be studied with hybrid RMC, we have implemented a new interatomic potential constraint in RMCProfile that grants flexibility to apply potentials supported by the Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) molecular dynamics code. This includes machine learning interatomic potentials, which provide a pathway to applying hybrid RMC to materials without currently available interatomic potentials. To this end, we present a methodology to use RMC to train machine learning interatomic potentials for hybrid RMC applications.

Cuillier, Paul↗

High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory

The ability to track simulated cancer cells through the circulatory system, important for developing a mechanistic understanding of metastatic spread, pushes the limits of today's supercomputers by requiring the simulation of large fluid volumes at cellular-scale resolution. To overcome this challenge, we introduce a new adaptive physics refinement (APR) method that captures cellular-scale interaction across large domains and leverages a hybrid CPU-GPU approach to maximize performance. Through algorithmic advances that integrate multi-physics and multi-resolution models, we establish a finely resolved window with explicitly modeled cells coupled to a coarsely resolved bulk fluid domain. In this work we present multiple validations of the APR framework by comparing against fully resolved fluid-structure interaction methods and employ techniques, such as latency hiding and maximizing memory bandwidth, to effectively utilize heterogeneous node architectures. Collectively, these computational developments and performance optimizations provide a robust and scalable framework to enable system-level simulations of cancer cell transport.

59 BASIC BIOLOGICAL SCIENCES↗

CPU Isosurface Ray Tracing of Adaptive Mesh Refinement Data

Adaptive mesh refinement (AMR) is a key technology for large-scale simulations that allows for adaptively changing the simulation mesh resolution, resulting in significant computational and storage savings. However, visualizing such AMR data poses a significant challenge due to the difficulties introduced by the hierarchical representation when reconstructing continuous field values. Here, we detail a comprehensive solution for interactive isosurface rendering of block-structured AMR data. We contribute a novel reconstruction strategy—the octant method—which is continuous, adaptive and simple to implement. Furthermore, we present a generally applicable hybrid implicit isosurface ray-tracing method, which provides better rendering quality and performance than the built-in sampling-based approach in OSPRay. Finally, we integrate our octant method and hybrid isosurface geometry into OSPRay as a module, providing the ability to create high-quality interactive visualizations combining volume and isosurface representations of BS-AMR data. Lastly, we evaluate the rendering performance, memory consumption and quality of our method on two gigascale block-structured AMR datasets.

97 MATHEMATICS AND COMPUTING↗

Characterization and differentiation of aluminum powders used in improvised explosive devices. Part 2: Micromorphometric method refinement and preliminary statistical analysis

Abstract Aluminum (Al) powder is commonly encountered in improvised explosive devices (IEDs) as a metallic fuel due to its availability and low cost. Although available commercially in powder form, amateur bomb‐makers also produce their own Al powder via simple methods found online. In order to provide investigative leads and forensic intelligence, it is important to evaluate not only the composition of homemade devices, but also to distinguish between the various forms of Al powder they contain. To achieve this goal, a method using automated microscopy in combination with statistical techniques has been demonstrated to have the potential to provide source discrimination and investigative leads in source attribution of Al powders in IEDs. The present research refined this method and investigated 59 industrially and amateurly produced Al powder sources with seven subsamples per source using two traditional linear discriminant analyses (LDA), one with a standard data split for training and testing, and another using leave‐one‐out cross‐validation. Averaging the classification accuracies for the two LDA‐based analyses, LDA has the ability to correctly classify 59.26%, 83.35%, and 80.69% of the samples based on their powder source, type, and production method, respectively. This classification accuracy represents a 3407%, 317%, and 61.38% increase in accuracy from random class assignment, respectively. Further, in most instances of incorrect data attribution to a particular source, the subsample has been misidentified with another sample of the same powder type or production method.

Ommen, Danica M.↗

Development of evaluation models of manpower needs for dismantling the dry conversion process-related equipment in uranium refining and conversion plant (URCP)

Evaluation models for determining the manpower needs for dismantling various types of equipment in uranium refining and conversion plant (URCP) have been developed. The models are widely applicable to other uranium handling facilities. Additionally, a simplified model was developed for easily and accurately calculating the manpower needs for dismantling dry conversion process-related equipment (DP equipment). It is important to evaluate beforehand project management data such as manpower needs to prepare an optimized decommissioning plan and implement effective dismantling activity. The Japan Atomic Energy Agency (JAEA) has developed the project management data evaluation system for dismantling activities (PRODIA code), which can generate project management data using evaluation models. For preparing an optimized decommissioning plan, these evaluation models should be established based on the type of nuclear facility and actual dismantling data. In URCP, the dry conversion process of reprocessed uranium and others was operated until 1999, and the equipment related to the main process was dismantled from 2008 to 2011. Actual data such as manpower for dismantling were collected during the dismantling activities, and evaluation models were developed using the collected actual data on the basis of equipment classification considering the characteristics of uranium handling facility. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Improving IMRT-plan quality with MLC leaf position refinement post plan optimization

Purpose: In intensity-modulated radiation therapy (IMRT) planning, reducing the pencil-beam size may lead to a significant improvement in dose conformity, but also increase the time needed for the dose calculation and plan optimization. The authors develop and evaluate a postoptimization refinement (POpR) method, which makes fine adjustments to the multileaf collimator (MLC) leaf positions after plan optimization, enhancing the spatial precision and improving the plan quality without a significant impact on the computational burden. Methods: The authors' POpR method is implemented using a commercial treatment planning system based on direct aperture optimization. After an IMRT plan is optimized using pencil beams with regular pencil-beam step size, a greedy search is conducted by looping through all of the involved MLC leaves to see if moving the MLC leaf in or out by half of a pencil-beam step size will improve the objective function value. The half-sized pencil beams, which are used for updating dose distribution in the greedy search, are derived from the existing full-sized pencil beams without need for further pencil-beam dose calculations. A benchmark phantom case and a head-and-neck (HN) case are studied for testing the authors' POpR method. Results: Using a benchmark phantom and a HN case, the authors have verified that their POpR method can be an efficient technique in the IMRT planning process. Effectiveness of POpR is confirmed by noting significant improvements in objective function values. Dosimetric benefits of POpR are comparable to those of using a finer pencil-beam size from the optimization start, but with far less computation and time. Conclusions: The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency.

60 APPLIED LIFE SCIENCES↗

Investigation of various energy deposition kernel refinements for the convolution/superposition method

Purpose: Several simplifications used in clinical implementations of the convolution/superposition (C/S) method, specifically, density scaling of water kernels for heterogeneous media and use of a single polyenergetic kernel, lead to dose calculation inaccuracies. Although these weaknesses of the C/S method are known, it is not well known which of these simplifications has the largest effect on dose calculation accuracy in clinical situations. The purpose of this study was to generate and characterize high-resolution, polyenergetic, and material-specific energy deposition kernels (EDKs), as well as to investigate the dosimetric impact of implementing spatially variant polyenergetic and material-specific kernels in a collapsed cone C/S algorithm.Methods: High-resolution, monoenergetic water EDKs and various material-specific EDKs were simulated using the EGSnrc Monte Carlo code. Polyenergetic kernels, reflecting the primary spectrum of a clinical 6 MV photon beam at different locations in a water phantom, were calculated for different depths, field sizes, and off-axis distances. To investigate the dosimetric impact of implementing spatially variant polyenergetic kernels, depth dose curves in water were calculated using two different implementations of the collapsed cone C/S method. The first method uses a single polyenergetic kernel, while the second method fully takes into account spectral changes in the convolution calculation. To investigate the dosimetric impact of implementing material-specific kernels, depth dose curves were calculated for a simplified titanium implant geometry using both a traditional C/S implementation that performs density scaling of water kernels and a novel implementation using material-specific kernels.Results: For our high-resolution kernels, we found good agreement with the Mackie et al. kernels, with some differences near the interaction site for low photon energies (<500 keV). For our spatially variant polyenergetic kernels, we found that depth was the most dominant factor affecting the pattern of energy deposition; however, the effects of field size and off-axis distance were not negligible. For the material-specific kernels, we found that as the density of the material increased, more energy was deposited laterally by charged particles, as opposed to in the forward direction. Thus, density scaling of water kernels becomes a worse approximation as the density and the effective atomic number of the material differ more from water. Implementation of spatially variant, polyenergetic kernels increased the percent depth dose value at 25 cm depth by 2.1%–5.8% depending on the field size, while implementation of titanium kernels gave 4.9% higher dose upstream of the metal cavity (i.e., higher backscatter dose) and 8.2% lower dose downstream of the cavity.Conclusions: Of the various kernel refinements investigated, inclusion of depth-dependent and metal-specific kernels into the C/S method has the greatest potential to improve dose calculation accuracy. Implementation of spatially variant polyenergetic kernels resulted in a harder depth dose curve and thus has the potential to affect beam modeling parameters obtained in the commissioning process. For metal implants, the C/S algorithms generally underestimate the dose upstream and overestimate the dose downstream of the implant. Implementation of a metal-specific kernel mitigated both of these errors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Rheological Properties of Enzymatically Hydrolyzed Corn Stover Pretreated via Deacetylation and Mechanical Refining

Lignocellulosic biomass is a feedstock for fuels and chemicals that does not compete with food resources and has less contaminants than refuse-derived biomass feedstocks. To convert lignocellulosics to biofuels or value-added products, multiple processing steps are typically necessary. One method of producing biofuels from lignocellulosic biomass utilizes a deacetylation and mechanical refining pretreatment and an enzymatic hydrolysis reaction to produce fermentable sugars from cellulose and hemicellulose. The rheological properties of biomass, such as yield stress and plastic viscosity, change during enzymatic hydrolysis and alter the energy requirements for pumping and mixing, an important consideration for the design of processing equipment. The dynamic changes in rheological properties that occur in a corn stover feedstock undergoing enzymatic hydrolysis are characterized in this work, and the influence on pressure losses in piping systems is estimated. Two rheometer geometries were fabricated with stereolithography 3D printing to reduce wall slip and sample ejection. The slurries have complex rheological behaviors that include shear-thinning behavior. Shear stress ramps were performed on samples at 20 and 50 degrees C using the custom geometries, and the Herschel-Bulkley model was fit to the data. The dynamic nature of the rheological properties is correlated with changes in the average fiber length at various extents of reaction, and the influence of solids concentration on the observed rheology and piping pressure losses is discussed.

09 BIOMASS FUELS↗

Refinement of the composition and structure of YBaCo{sub 4-x}Al{sub x}O{sub 7+{delta}} crystals

YBa(Co{sub 4-x}Al{sub x})O{sub 7+{delta}} (114Y) crystals have been grown in the Y-Ba-Co-O system by spontaneous crystallization from a slowly cooled nonstoichiometric melt. To change the oxygen content, the crystals were isothermally annealed in air in the range of 280-490 Degree-Sign C. The crystals grown were characterized by scanning electron microscopy and powder X-ray diffraction. According to the data of an X-ray spectroscopic quantitative microprobe analysis, the average compositions of 'as-grown' and oxygen-saturated crystals were Y{sub 1.04}Ba{sub 1}Co{sub 3.54}Al{sub 0.50}O{sub 7.8} and Y{sub 1.02}Ba{sub 1}Co{sub 3.55}Al{sub 0.51}O{sub 8.4}, respectively. The refinement of the crystal structure after saturation on an automatic Bruker X8APEX diffractometer with a CCD detector (MoK{alpha} radiation, graphite monochromator, {theta}{sub max} = 32.54 Degree-Sign , sp. gr. P6{sub 3}mc, a = 6.2746(9), c = 10.257(3) Angstrom-Sign , V = 349.71(13) Angstrom-Sign {sup 3}, Z = 2, d{sub calcd} = 5.220 g/cm{sup 3}) reveals the location of Al in two independent positions of Co atoms and yields the general formula of the compound as YBaCo{sub 3.26}Al{sub 0.74}O{sub 7}. Problems related to the difference in the compositions obtained by different methods are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Crystallization, crystal-structure refinement, and IR spectroscopy of a synthetic hexahydroborite analog

The crystal structure of the hexahydroborite analog Ca[B(OH){sub 4}]{sub 2} {center_dot} 2H{sub 2}O (a = 7.9941(3) Angstrom-Sign , b = 6.6321(2) Angstrom-Sign , c = 7.9871(3) Angstrom-Sign , {beta} = 104.166(4) Degree-Sign , V = 410.58(3) Angstrom-Sign {sup 3}, sp. gr. P2/c, Z = 2, {rho}{sub calc} = 1.891 g/cm{sup 3}; Xcalibur S CCD automated diffractometer, 1196 reflections with I > 2{sigma}(I), {lambda}MoK{sub {alpha}}), which was synthesized by the hydrothermal method via the recrystallization of calciborite CaB{sub 2}O{sub 4} (M) in the M - B{sub 2}O{sub 3} - H{sub 2}O system (t = 250 Degree-Sign C and P = 70-80 atm), was refined by the least-squares method with anisotropic displacement parameters (H atoms were located; R{sub 1} = 0.0260). The structure of synthetic hexahydroborite consists of infinite columns running along the c axis. The columns are formed by Ca polyhedra linked together and to [B(OH){sub 4}] orthotetrahedra by sharing edges. Along the two other axes, the translationally equivalent columns are linked only by hydrogen bonds. The presence of a stronger bond between the discrete (Ca-B-O) columns along the shortest (b = 6.6 Angstrom-Sign ) axis accounts for the possibility of the shift of the columns by 1/2T{sub b} and the formation of the second modification of Ca[B(OH){sub 4}]{sub 2} {center_dot} 2H{sub 2}O. The crystals of synthetic hexahydroborite were studied by IR spectroscopy. A crystal-chemical analysis was performed for a series of natural metaborates with the general formula CaB{sub 2}O{sub 4} {center_dot} nH{sub 2}O (CaO: B{sub 2}O{sub 3} = 1: 1, n = 0-6), including calciborite CaB{sub 2}O{sub 4} and hexahydroborite CaB{sub 2}O{sub 4} {center_dot} 6H{sub 2}O as the end members.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Synthesis, crystal structure refinement, and nonlinear-optical properties of CaB{sub 3}O{sub 5}(OH): Comparative crystal chemistry of calcium triborates

Calcium triborate CaB{sub 3}O5(OH) obtained by hydrothermal synthesis in the Ca(OH){sub 2}–H{sub 3}BO{sub 3}–Na{sub 2}CO{sub 3}–KCl system is studied by single-crystal X-ray diffraction. The parameters of the orthorhombic unit cell are as follows: a = 13.490(1), b = 6.9576(3), and c = 4.3930(2) Å; V = 412.32(3) Å{sup 3} and space group Pna2{sub 1}. The structure is refined in the anisotropic approximation of the atomic displacement parameters to R = 4.28% using 972 vertical bar F vertical bar > 4σ(F). It is confirmed that the crystal structure of Ca triborate CaB{sub 3}O{sub 5}(OH) is identical to that described earlier. The hydrogen atom is localized. An SHG signal stronger than that of the quartz standard is registered. The phase transition of calcium triborate into calciborite is found on heating. The comparative crystal-chemical analysis of a series of borates with the general chemical formula 2CaO · 3B{sub 2}O{sub 3} · nH{sub 2}O (n = 0–13) with the constant CaO: B{sub 2}O{sub 3}= 2: 3 ratio and variable content of water is performed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fast and effective reordering of columns within supernodes using partition refinement

In this paper, we consider the problem of computing a triangular factorization of a sparse symmetric matrix using Gaussian elimination. We assume that the sparse matrix has been permuted using a fill-reducing ordering algorithm. When the matrix is symmetric positive definite, the sparsity structure of the triangular factor can be determined once the fill-reducing ordering has been computed. Thus, an efficient numerical factorization scheme can be designed so that only the nonzero entries are stored and operated on. On modern architectures, the positions of the nonzero entries in the triangular factor play a big role in determining the efficiency. It is desirable to have dense blocks in the factor so that the computation can be cast in terms of level-3 BLAS as much as possible. On architectures with GPUs, for example, it is also desirable for these dense blocks to be as large as possible in order to reduce the times to transfer data between the main CPU and the GPUs. We address the problem of locally refining the ordering so that the number of dense blocks is reduced and the sizes of these dense blocks are increased in the triangular factor.

Jacquelin, Mathias↗

Landau Collision Integral Solver with Adaptive Mesh Refinement on Emerging Architectures

The Landau collision integral is an accurate model for the small-angle dominated Coulomb collisions in fusion plasmas. Here, we investigate a high order accurate, fully conservative, finite element discretization of the nonlinear multispecies Landau integral with adaptive mesh refinement using the PETSc library (ulwww.mcs.anl.gov/petsc). We develop algorithms and techniques to efficiently utilize emerging architectures with an approach that minimizes memory usage and movement and is suitable for vector processing. The Landau collision integral is vectorized with Intel AVX-512 intrinsics and the solver sustains as much as 22% of the theoretical peak flop rate of the Second Generation Intel Xeon Phi (``Knights Landing'') processor.

97 MATHEMATICS AND COMPUTING↗

Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts

Simulations of cancer cell transport require accurately modeling mm-scale and longer trajectories through a circulatory system containing trillions of deformable red blood cells, whose intercellular interactions require submicron fidelity. Using a hybrid CPU-GPU approach, we extend the advanced physics refinement (APR) method to couple a finely-resolved region of explicitly-modeled red blood cells to a coarsely-resolved bulk fluid domain. We further develop algorithms that: capture the dynamics at the interface of differing viscosities, maintain hematocrit within the cell-filled volume, and move the finely-resolved region and encapsulated cells while tracking an individual cancer cell. Comparison to a fully-resolved fluid-structure interaction model is presented for verification. Finally, we use the advanced APR method to simulate cancer cell transport over a mm-scale distance while maintaining a local region of RBCs, using a fraction of the computational power required to run a fully-resolved model.

Roychowdhury, Sayan↗

AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications

As supercomputers advance towards exascale capabilities, computational intensity increases significantly, and the volume of data requiring storage and transmission experiences exponential growth. Adaptive Mesh Refinement (AMR) has emerged as an effective solution to address these two challenges. Concurrently, error-bounded lossy compression is recognized as one of the most efficient approaches to tackle the latter issue. Despite their respective advantages, few attempts have been made to investigate how AMR and error-bounded lossy compression can function together. To this end, this study presents a novel in-situ lossy compression framework that employs the HDF5 filter to improve both I/O costs and boost compression quality for AMR applications. We implement our solution into the AMReX framework and evaluate on two real-world AMR applications, Nyx and WarpX, on the Summit supercomputer. Experiments with 512 cores demonstrate that AMRIC improves the compression ratio by 81X and the I/O performance by 39X over AMReX's original compression solution.

Wang, Daoce↗

Synthesis of CdSe/ZnS and CdTe/ZnS Quantum Dots: Refined Digestive Ripening

We report synthesis of CdSe and CdTe quantum dots (QDs) from the bulk CdSe and CdTe material by evaporation/co‐condensation using the solvated metal atom dispersion (SMAD) technique and refined digestive ripening. The outcomes of this new process are (1) the reduction of digestive ripening time by employing ligands (trioctylphosphine oxide (TOPO) and oleylamine (OA)) as capping agent as well as digestive ripening solvent, (2) ability to tune the photoluminescence (PL) from 410 nm to 670 nm, (3) demonstrate the ability of SMAD synthesis technique for other semiconductors (CdTe), (4) direct comparison of CdSe QDs growth with CdTe QDs growth based on digestive ripening times, and (5) enhanced PL quantum yield (QY) of CdSe QDs and CdTe QDs upon covering with a ZnS shell. Further, the merit of this synthesis is the use of bulk CdSe and CdTe as the starting materials, which avoids usage of toxic organometallic compounds, eliminates the hot injection procedure, and size selective precipitation processes. It also allows the possibility of scale up. These QDs were characterized by UV‐vis, photoluminescence (PL), transmission electron microscopy (TEM), high‐resolution transmission electron microscopy (HRTEM), X‐ray photoelectron spectroscopy (XPS), and powder XRD.

Cingarapu, Sreeram↗

ARCS: Agentic Retrieval-Augmented Code Synthesis with Iterative Refinement

Agentic Retrieval-Augmented Code Synthesis with Iterative RefinementIn supercomputing, efficient and optimized code generation is essential to leverage high-performance systems effectively. We have developed Agentic Retrieval-Augmented Code Synthesis (ARCS), an advanced framework for accurate, robust, and efficient code generation, completion, and translation. ARCS integrates Retrieval-Augmented Generation (RAG) with Chain-of-Thought (CoT) reasoning to systematically break down and iteratively refine complex programming tasks. An agent-based RAG mechanism retrieves relevant code snippets, while real-time execution feedback drives the synthesis of candidate solutions. This process is formalized as a state-action search tree optimization, balancing code correctness with editing efficiency. Evaluations on the Geeks4Geeks and HumanEval benchmarks demonstrate that ARCS significantly outperforms traditional prompting methods in translation and generation quality. By enabling scalable and precise code synthesis, ARCS offers transformative potential for automating and optimizing code development in supercomputing applications, enhancing computational resource utilization

Bhattarai, Manish [Los Alamos National Labs]↗

AMReX: Block-structured adaptive mesh refinement for multiphysics applications

Block-structured adaptive mesh refinement (AMR) provides the basis for the temporal and spatial discretization strategy for a number of Exascale Computing Project applications in the areas of accelerator design, additive manufacturing, astrophysics, combustion, cosmology, multiphase flow, and wind plant modeling. AMReX is a software framework that provides a unified infrastructure with the functionality needed for these and other AMR applications to be able to effectively and efficiently utilize machines from laptops to exascale architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multiphysics algorithms. AMReX supports algorithms that solve systems of partial differential equations in simple or complex geometries and those that use particles and/or particle–mesh operations to represent component physical processes. In this article, we will discuss the core elements of the AMReX framework such as data containers and iterators as well as several specialized operations to meet the needs of the application projects. In addition, we will highlight the strategy that the AMReX team is pursuing to achieve highly performant code across a range of accelerator-based architectures for a variety of different applications.

Zhang, Weiqun↗