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DOE OSTI2016

SU-C-BRA-06: Automatic Brain Tumor Segmentation for Stereotactic Radiosurgery Applications

Purpose: Stereotactic radiosurgery (SRS), which delivers a potent dose of highly conformal radiation to the target in a single fraction, requires accurate tumor delineation for treatment planning. We present an automatic segmentation strategy, that synergizes intensity histogram thresholding, super-voxel clustering, and level-set based contour evolving methods to efficiently and accurately delineate SRS brain tumors on contrast-enhance T1-weighted (T1c) Magnetic Resonance Images (MRI). Methods: The developed auto-segmentation strategy consists of three major steps. Firstly, tumor sites are localized through 2D slice intensity histogram scanning. Then, super voxels are obtained through clustering the corresponding voxels in 3D with reference to the similarity metrics composited from spatial distance and intensity difference. The combination of the above two could generate the initial contour surface. Finally, a localized region active contour model is utilized to evolve the surface to achieve the accurate delineation of the tumors. The developed method was evaluated on numerical phantom data, synthetic BRATS (Multimodal Brain Tumor Image Segmentation challenge) data, and clinical patients’ data. The auto-segmentation results were quantitatively evaluated by comparing to ground truths with both volume and surface similarity metrics. Results: DICE coefficient (DC) was performed as a quantitative metric to evaluate the auto-segmentation in the numerical phantom with 8 tumors. DCs are 0.999±0.001 without noise, 0.969±0.065 with Rician noise and 0.976±0.038 with Gaussian noise. DC, NMI (Normalized Mutual Information), SSIM (Structural Similarity) and Hausdorff distance (HD) were calculated as the metrics for the BRATS and patients’ data. Assessment of BRATS data across 25 tumor segmentation yield DC 0.886±0.078, NMI 0.817±0.108, SSIM 0.997±0.002, and HD 6.483±4.079mm. Evaluation on 8 patients with total 14 tumor sites yield DC 0.872±0.070, NMI 0.824±0.078, SSIM 0.999±0.001, and HD 5.926±6.141mm. Conclusion: The developed automatic segmentation strategy, which yields accurate brain tumor delineation in evaluation cases, is promising for its application in SRS treatment planning.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-I-76: Fluoroscopic X-Ray Beam Profiles for Spectra Incorporating Copper Filtration

Purpose: The purpose of this investigation is to characterize and quantify X-ray beam profiles for fluoroscopic x-ray beam spectra incorporating spectral (copper) filtration. Methods: A PTW (Freiburg, Germany) type 60016 silicon diode detector and PTW MP3 water tank were used to measure X-ray beam profiles for 60, 80, 100 and 120 kVp x-ray beams at five different copper filtration thicknesses ranging from 0–0.9 mm at 22 and 42 cm fields of view and depths of 1, 5, and 10 cm in both the anode-cathode axis (inplane) and cross-plane directions. All measurements were acquired on a Siemens (Erlangen, Germany) Artis ZeeGo fluoroscope inverted from the typical orientation providing an x-ray beam originating from above the water surface with the water level set at 60 cm from the focal spot. Results: X-ray beam profiles for beam spectra without copper filtration compared well to previously published data by Fetterly et al. [Med Phys, 28, 205 (2001)]. Our data collection benefited from the geometric orientation of the fluoroscope, providing a beam perpendicular to the tank water surface, rather than through a thin side wall as did the previously mentioned study. Profiles for beams with copper filtration were obtained which have not been previously investigated and published. Beam profiles in the anode-cathode axis near the surface and at lower x-ray energy exhibited substantial heel effect, which became less pronounced at greater depth. At higher energy with copper filtration in the beam, the dose falloff out-of-field became less pronounced, as would be anticipated given higher scatter photon energy. Conclusion: The x-ray beam profile data for the fluoroscopic x-ray beams incorporating copper filtration are intended for use as reference data for estimating doses to organs or soft tissue, including fetal dose, involving similar beam qualities or for comparison with mathematical models.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-93: Automated Segmentation of High-Resolution 3D WholeBrain Spectroscopic MRI for Glioblastoma Treatment Planning

Purpose: We report on an automated segmentation algorithm for defining radiation therapy target volumes using spectroscopic MR images (sMRI) acquired at nominal voxel resolution of 100 microliters. Methods: Wholebrain sMRI combining 3D echo-planar spectroscopic imaging, generalized auto-calibrating partially-parallel acquisitions, and elliptical k-space encoding were conducted on 3T MRI scanner with 32-channel head coil array creating images. Metabolite maps generated include choline (Cho), creatine (Cr), and N-acetylaspartate (NAA), as well as Cho/NAA, Cho/Cr, and NAA/Cr ratio maps. Automated segmentation was achieved by concomitantly considering sMRI metabolite maps with standard contrast enhancing (CE) imaging in a pipeline that first uses the water signal for skull stripping. Subsequently, an initial blob of tumor region is identified by searching for regions of FLAIR abnormalities that also display reduced NAA activity using a mean ratio correlation and morphological filters. These regions are used as starting point for a geodesic level-set refinement that adapts the initial blob to the fine details specific to each metabolite. Results: Accuracy of the segmentation model was tested on a cohort of 12 patients that had sMRI datasets acquired pre, mid and post-treatment, providing a broad range of enhancement patterns. Compared to classical imaging, where heterogeneity in the tumor appearance and shape across posed a greater challenge to the algorithm, sMRI’s regions of abnormal activity were easily detected in the sMRI metabolite maps when combining the detail available in the standard imaging with the local enhancement produced by the metabolites. Results can be imported in the treatment planning, leading in general increase in the target volumes (GTV60) when using sMRI+CE MRI compared to the standard CE MRI alone. Conclusion: Integration of automated segmentation of sMRI metabolite maps into planning is feasible and will likely streamline acceptance of this new acquisition modality in clinical practice.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-BRA-01: Abdominal Synthetic CT Generation in Support of Liver SBRT Dose Calculation

Purpose: To demonstrate and validate a technique for generating MRI-derived synthetic CT volumes (MRCTs) in support of adaptive liver SBRT. Methods: Under IRB approval, ten hepatocellular carcinoma patients were scanned using a single MR sequence (T1 Dixon-VIBE), yielding inherently-registered water, fat, and T1-weighted images. Air-containing voxels were identified by intensity thresholding. The envelope of the anterior vertebral bodies was segmented from the fat image by fitting a shape model to vertebral body candidate voxels, then using level sets to expand the contour outward. Fuzzy-C-Means (FCM) was then used to classify each non-air voxel in the image as fat, water, bone, or marrow. Bone and marrow only were classified within the vertebral body envelope. The MRCT was created by integrating the product of the FCM class probability with the assigned class density for each voxel. The resulting MRCTs were deformably aligned with planning CTs and 2-ARC SBRT VMAT plans were optimized on the MRCT density maps. Fluence was copied onto the CT density grids and dose recalculated. Results: The MRCTs faithfully reproduced most of the features visible in the corresponding CT image volumes, with exceptions of ribs and posterior spinous processes. The liver, vertebral bodies, kidneys, spleen and cord all had median HU differences of less than 75 between MRCT and CT images. PTV D99% values had an average 0.2% difference (standard deviation: 0.46%) between calculations on MRCT and CT density grids. The maximum difference in dose to 0.1cc of the PTV was 0.25% (std:0.49%). OAR dose differences were similarly small (mean:0.03Gy, std:0.26Gy). The largest normal tissue complication percentage (NTCP) difference was 1.48% (mean:0.06%, std:0.54%). Conclusions: MRCTs from a single abdominal imaging sequence are promising for use in SBRT dose calculation. Future work will focus on extending models to better define bones in the upper abdomen. Supported by NIHR01EB016079 and NIH1L30CA199594-01.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-CD-206-08: An Anthropopathic Deformable Phantom for Geometric and Dose Accumulation Accuracy Validation of Deformable Image Registration

Purpose: To design and construct a three-dimensional (3D) anthropopathic abdominal phantom for evaluating deformable image registration (DIR) accuracy on images and dose deformation in adaptive radiation therapy (ART). Method: Organ moulds, including liver, kidney, spleen, stomach, vertebra and two metastasis tumors, are 3D printed using the contours from an ovarian cancer patient. The organ moulds are molded with deformable gels that made of different mixtures of polyvinyl chloride (PVC) and the softener dioctyl terephthalate. Gels with different densities are obtained by a polynomial fitting curve which describes the relation between the CT number and PVC-softener blending ratio. The rigid vertebras are constructed by moulding with white cement. The final abdominal phantom is assembled by arranging all the fabricated organs inside a hollow dummy according to their anatomies and sealed with deformable gel with averaged CT number of muscle and fat. Geometric and dosimetric landmarks are embedded inside the phantom for spatial accuracy and dose accumulation accuracy studies. Three DIR algorithms available in the open source DIR toolkit-DIRART, including the Demons, the Horn-Schunck and Lucas-Kanade method and the Level-Set Motion method, are tested using the constructed phantom. Results: Viscoelastic behavior is observed in the constructed deformable gel, which serves as an ideal material for the deformable phantom. The constructed abdominal phantom consists of highly realistic anatomy and the fabricated organs inside have close CT number to its reference patient. DIR accuracy studies conducted on the constructed phantom using three DIR approaches indicate that geometric accuracy of a DIR algorithm has achieved does not guarantee accuracy in dose accumulation. Conclusions: We have designed and constructed an anthropopathic abdominal deformable phantom with satisfactory elastic property, realistic organ density and anatomy. This physical phantom is recyclable and can be used for routine validations of DIR geometric accuracy and dose accumulation accuracy in ART. This work is supported in part by grant from VARIAN MEDICAL SYSTEMS INC, the National Natural Science Foundation of China (no 81428019 and no 81301940), the Guangdong Natural Science Foundation (2015A030313302) and the 2015 Pearl River S&T Nova Program of Guangzhou (201506010096).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Search for heavy resonances that decay into a vector boson and a Higgs boson in hadronic final states at $\sqrt{s} = 13$ $\,\text {TeV}$

A search for heavy resonances with masses above 1 $\,\text {TeV}$ , decaying to final states containing a vector boson and a Higgs boson, is presented. The search considers hadronic decays of the vector boson, and Higgs boson decays to b quarks. The decay products are highly boosted, and each collimated pair of quarks is reconstructed as a single, massive jet. The analysis is performed using a data sample collected in 2016 by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 $\,\text {TeV}$ , corresponding to an integrated luminosity of 35.9 $\,\text {fb}^{-1}$ . The data are consistent with the background expectation and are used to place limits on the parameters of a theoretical model with a heavy vector triplet. In the benchmark scenario with mass-degenerate $\mathrm{W^{'}}$ and $\mathrm{Z}' $ bosons decaying predominantly to pairs of standard model bosons, for the first time heavy resonances for masses as high as 3.3 $\,\text {TeV}$ are excluded at 95% confidence level, setting the most stringent constraints to date on such states decaying into a vector boson and a Higgs boson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Virtual Flow Simulator

Virtual Flow Simulator (VFS) is a state-of-the-art computational fluid mechanics (CFD) package that is capable of simulating multi-physics/multi-phase flows with the most advanced turbulence models (RANS, LES) over complex terrains. The flow solver is based on the Curvilinear Immersed Boundary (CURVIB) method to handle geometrically complex and moving domains. Different modules of the VFS package can provide different simulation capabilities for specific applications ranging from the fluid-structure interaction (FSI) of solid and deformable bodies, the two-phase free surface flow solver based on the level set method for ocean waves, sediment transport models in rivers and the large-scale models of wind farms based on actuator lines and surfaces. All numerical features of VFS package have been validated with known analytical and experimental data as reported in the related journal articles. VFS package is suitable for a broad range of engineering applications within different industries. VFS has been used in different projects with applications in wind and hydrokinetic energy, offshore and near-shore ocean studies, cardiovascular and biological flows, and natural streams and river morphodynamics. Over the last decade, the development of VFS has been supported and assisted with the help of various United States companies and federal agencies that are listed in the sponsor lists. In this version, VFS-Wind contains all the necessary modeling tools for wind energy applications, including land-based and offshore wind farms. VFS is highly scalable to run on either desktop computers or high performance clusters (up to 16,000 CPUs). This released version comes with a detailed user’s manual and a set of case studies designed to facilitate the learning of the various aspects of the code in a comprehensive manner. The included documentation and support material has been elaborated in a collaboration effort with Sandia National Labs under the contract DE-EE0005482. The VFS-Wind source code is distributed under the GNU General Public License (GPL 2.0), offering to the community the flexibility to use and expand the capabilities of the package. We note that future publications including academic journals that result from the use of VFS must be cited appropriately under the GPL v.2 license agreement.

Yang, Xiaolei↗

DOE OSTI2022

BDEM (Discrete-element-simulator for high-solids granular flows) [SWR-22-72]

BDEM is a discrete element method based simulation tool developed specifically for modeling high-solids granular flows that include polydispersity, heat-transfer, moving boundaries and chemistry. Our solver provides facilities for simulating spherical/non-spherical particles with modified contact and friction models in complex dynamic geometries defined using level-sets or triangulated files. The solver is developed on top of NREL's open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Simulations at the scale of several millions to billion particles have been performed using this software on large scale computing resources. This software can be applied to non-reacting solids dominant flows in silos, hoppers and screw conveyors as well as in high temperature reacting systems such as screw kilns and auger reactors.

Sitaraman, Hariswaran↗

DOE OSTI2021

idaholab/malamute

MALAMUTE combines MOOSE module functionality with realistic materials and geometries for arbitrary-Eulerian-Lagrangian (ALE) and level-set based laser melting and welding applications and electric-field assisted sintering (EFAS) applications.

Icenhour, Casey [Idaho National Lab. (INL), Idaho ↗

DOE OSTI2021

Moose Application Library For Advanced Manufacturing Utilities

Lindsay, AlexanderD.↗

DOE OSTI2026

JGI Archive and Metadata Organizer (JAMO) v2.0.0

JAMO (JGI Archive and Metadata Organizer) helps researchers keep large collections of scientific files organized, findable, and safe. It lets you submit files with consistent, template-driven metadata, bundle related files into sets, and track them as a group instead of one by one. As data ages, JAMO automatically moves it from fast disk to cost-saving tape and can bring it back when needed, keeping storage lean without losing access. A simple web/CLI workflow supports submitting, checking status, retrying, and updating metadata. Compared with generic storage, JAMO's strengths are: clear, searchable metadata tuned for science; set-level organization that mirrors real projects; and built-in lifecycle care (archive, purge, restore) so you don't have to manage those steps yourself.

Cassol, Daniela [Lawrence Berkeley National Labora↗

DOE OSTI2024

Batched sparse direct solver design and evaluation in SuperLU_DIST

Over the course of interactions with various application teams, the need for batched sparse linear algebra functions has emerged in order to make more efficient use of the GPUs for many small and sparse linear algebra problems. In this paper, we present our recent work on a batched sparse direct solver for GPUs. The sparse LU factorization is computed by the levels of the elimination tree, leveraging the batched dense operations at each level and a new batched Scatter GPU kernel. The sparse triangular solve is computed by the level sets of the directed acyclic graph (DAG) of the triangular matrix. Batched operations overcome the large overhead associated with launching many small kernels. For medium sized matrix batches with not-so-small bandwidth, using an NVIDIA A100 GPU, our new batched sparse direct solver is orders of magnitude faster than a batched banded solver and uses less than one-tenth of the memory.

Boukaram, Wajih↗

DOE OSTI2024

A Million Person Study Innovation: Evaluating Cognitive Impairment and other Morbidity Outcomes from Chronic Radiation Exposure Through Linkages with the Centers for Medicaid and Medicare Services Assessment and Claims Data

Here, the study of One Million U.S. Radiation Workers and Veterans, the Million Person Study (MPS), examines the health consequences, both cancer and non-cancer, of exposure to ionizing radiation received gradually over time. Recently the MPS has focused on mortality patterns from neurological and behavioral conditions, e.g., Parkinson's disease, Alzheimer's disease, dementia, and motor neuron disease such as amyotrophic lateral sclerosis. A fuller picture of radiation-related late effects comes from studying both mortality and the occurrence (incidence) of conditions not leading to death. Accordingly, the MPS is identifying neurocognitive diagnoses from fee-for-service insurance claims from the Centers for Medicare and Medicaid Services (CMS), among Medicare beneficiaries beginning in 1999 (the earliest date claims data are available). Linkages to date have identified ∼540,000 workers with available health information. Such linkages provide individual information on important co-factor and confounding variables such as smoking, alcohol consumption, blood pressure, obesity, diabetes and many other health and demographic characteristics. The total person-level set of time-dependent variables, outcomes, organ-specific dose measures, co-factors, and demographics will be massive and much too large to be evaluated with standard software. Thus, development of specialized open-source software designed for large datasets (Colossus) is nearly complete. The wealth of information available from CMS claims data, coupled with individual dose reconstructions, will thus greatly enhance the quality and precision of health evaluations for this new field of low-dose radiation and neurocognitive effects.

Dauer, Lawrence T.↗

DOE OSTI2021

Computational Fluid Dynamics (CFD) Simulations of Taylor Bubbles in Vertical and Inclined Pipes with Upward and Downward Liquid Flow

Summary Two-phase flow is a common occurrence in pipes of oil and gas developments. Current predictive tools are based on the mechanistic two-fluid model, which requires the use of closure relations to predict integral flow parameters such as liquid holdup (or void fraction) and pressure gradient. However, these closure relations carry the highest uncertainties in the model. In particular, significant discrepancies have been found between experimental data and closure relations for the Taylor bubble velocity in slug flow, which has been determined to strongly affect the mechanistic model predictions (Lizarraga-García 2016). In this work, we study the behavior of Taylor bubbles in vertical and inclined pipes with upward and downward flow using a validated 3D computational fluid dynamics (CFD) approach with level set method implemented in a commercial code. A total of 56 cases are simulated, covering a wide range of fluid properties, pipe diameters, and inclination angles: Eo ∈ [10, 700]; Mo ∈ [1×10–6, 5×103]; ReSL ∈ [–40, 10]; θ ∈ [5°, 90°]. For bubbles in vertical upward flows, the simulated distribution parameter, C0, is successfully compared with an existing model. However, the C0 values of downward and inclined slug flows where the bubble becomes asymmetric are shown to be significantly different from their respective vertical upward flow values, and no current model exists for the fluids simulated here. The main contributions of this work are (1) the relatively large 3D numerical database generated for this type of flow, (2) the study of the asymmetric nature of inclined and some vertical downward slug flows, and (3) the analysis of its impact on the distribution parameter, C0.

Engineering↗

DOE OSTI2013

HERMES Model Modifications and Applications 2012

HERMES was developed to meet requirements for a model to describe explosive response to impacts that do not produce prompt detonation, but can include delayed detonations such as DDT and XDT. Such response is termed High Explosive Violent Response (HEVR). The HERMES model includes a constitutive description of strength as a function of pressure, strain-rate, strain, and ambient temperature; the development of damage including fragmentation and porosity; the conditions leading to ignition; the propagation of a burning reaction through the volume of damaged explosive; the burn-up of the damaged and undamaged explosive; and the development of detonation using the Computational Reaction Evolution dependent on Entropy (S) and Time (CREST) detonation model. CREST can distinguish gradual pressure increases from shock waves, and also predict the increase in shock sensitivity to detonation that results from increased porosity. This year HERMES has been implemented as a User Defined Function in ALE 3D. As a result, modifications to the model can be implemented in a timely fashion asynchronously from the ALE 3D distribution process. There are differences between the implementation of HERMES in ALE 3D and the implementation in LS DYNA. The major difference is the propagation of an ignition front from an element that has started to burn. In LS DYNA, the time at which an element begins to burn is based on the minimum line-of-sight distance between the element and any previously ignited element. In ALE 3D the time to burn is based on a level-set method that propagates the ignition front from all elements that were previously ignited. The ALE 3D implementation modifies the time of ignition when element deformation changes the distance from the element to the source. The LS DYNA implementation does not. There are also differences in the implementation of artificial viscosity, which is important for CREST since the artificial viscosity increases the element entropy in a shock. In general, however, the differences have proven minor. In collaboration with the Atomic Weapons Establishment, UK (AWE), we have characterized two additional explosives – PETN and Composition B, a mixture of 60% RDX and 40% TNT by weight. Applications of HERMES to these explosives are described below.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

An interface tracking model for droplet electrocoalescence.

This report describes an Early Career Laboratory Directed Research and Development (LDRD) project to develop an interface tracking model for droplet electrocoalescence. Many fluid-based technologies rely on electrical fields to control the motion of droplets, e.g. microfluidic devices for high-speed droplet sorting, solution separation for chemical detectors, and purification of biodiesel fuel. Precise control over droplets is crucial to these applications. However, electric fields can induce complex and unpredictable fluid dynamics. Recent experiments (Ristenpart et al. 2009) have demonstrated that oppositely charged droplets bounce rather than coalesce in the presence of strong electric fields. A transient aqueous bridge forms between approaching drops prior to pinch-off. This observation applies to many types of fluids, but neither theory nor experiments have been able to offer a satisfactory explanation. Analytic hydrodynamic approximations for interfaces become invalid near coalescence, and therefore detailed numerical simulations are necessary. This is a computationally challenging problem that involves tracking a moving interface and solving complex multi-physics and multi-scale dynamics, which are beyond the capabilities of most state-of-the-art simulations. An interface-tracking model for electro-coalescence can provide a new perspective to a variety of applications in which interfacial physics are coupled with electrodynamics, including electro-osmosis, fabrication of microelectronics, fuel atomization, oil dehydration, nuclear waste reprocessing and solution separation for chemical detectors. We present a conformal decomposition finite element (CDFEM) interface-tracking method for the electrohydrodynamics of two-phase flow to demonstrate electro-coalescence. CDFEM is a sharp interface method that decomposes elements along fluid-fluid boundaries and uses a level set function to represent the interface.

Erickson, Lindsay Crowl↗

DOE OSTI2015

A Kinetic Approach to Modeling the Manufacture of High Density Polyurethane Structural Foam: Foaming and Polymerization

This report details the study of PMDI structural foam and the development of a computational model to represent it. This polyurethane has a fast catalyst, such that foaming and polymerization occur simultaneously. The foam is over-packed to twice or more of its free rise density to reach the density of interest. Our approach is to combine model development closely with experiments to discover underlying physical phenomena, to parameterize models, and to validate the models once they have been developed. The model must be able to represent the expansion, filling of molds, curing, and final foam properties. PMDI is a chemically blown foam, where carbon dioxide is produced via the reaction of water and isocyanate. The isocyanate also reacts with polyol in a competing reaction, which produces the polymer. A new kinetic model is developed and implemented, which follows a simplified mathematical formalism that decouples these two reactions. The model predicts the polymerization reaction via condensation chemistry, where vitrification and glass transition temperature evolution must be included to correctly predict the temperature dependence of the kinetics. The foam gas generation kinetics are determined by tracking the molar concentration of both water and carbon dioxide. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics and material properties are all sensitive to temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. We assume generalized-Newtonian rheology that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations are combined with a level set method to determine the location of the free surface over time. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including a mock encapsulation part, two configurations of a mock structural part, and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2016

SIERRA Multimechanics Module: Aria User Manual – Version 4.40

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number (Re < 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton’s method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic ℎ-adaptivity and dynamic load balancing are some of Aria’s more advanced capabilities. Aria is based upon the Sierra Framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗