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At least 613 records · Page 34

Multi-Scale Modeling of Thermal-Fluid Phenomena Related to Loss of Forced Circulation Transient in HTGRs

Under the support of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS), an effort had been pursued to support High Temperature Gas-cooled Reactors (HTGR) technology development and its modeling and simulation needs. There was a particular need for advanced modeling & simulation tools to predict thermal-fluid behavior in the nuclear reactor primary system, especially the core and lower and upper plena, during safety-related transients. In this report, two main such activities were presented: 1) system level HTGR simulations using system analysis code SAM for both normal operating and accident conditions; and 2) three-dimensional (3D) computational fluid dynamics (CFD) simulations on Deteriorated Turbulent Heat Transfer (DTHT) of interest to HTGR transients, including code benchmark and closure correlation development. In this work, Modular High Temperature Gas-cooled Reactor (MHTGR) full loop simulations were performed using System Analysis Module (SAM) code. Two approaches were used to model the reactor core; (i) unit-cell or lumped parameter model, and (ii) detailed ring model, to address the different needs under different reactor conditions. Aside from the core model changes other reactor components in the primary system, such as upper/lower plenum, heat exchanger and blower etc, were kept the same. In the unit-cell core model, the lumped parameter approach was used to model the coolant channels and the heat structures using 1-D and 2-D components, respectively. The fuel assembly heat structure was modeled based on unit-cell thickness approximation. In normal and controlled operating conditions, the calculated maximum temperatures for both coolant and heat structures were within the designed limits. The unit-cell model is, however, not able to capture the radial heat conduction through fuel assemblies, which is the dominant heat transfer mechanism during accident transients, such as pressurized conduction cooldown (PCC) event. To address this modeling challenge, ring models were developed. A simplified ring model was developed first. In this simplified model, the active core was simulated with 9 circular rings consists of 6 rings for homogenized fuel heat structure and 3 rings for gas coolant. It was quickly found that this model gives rather large simulation error as it was not able to correctly capture the solid structure representative geometries. A detailed ring model was developed to address this issue. The active core was simulated with 99 circular rings consists of 66 rings for homogenized fuel heat structure and 33 rings for gas coolant. In both ring models, six additional rings were included to represent inner reflector, outer reflector, core barrel, Reactor Pressure Vessel (RPV), RPV coolant channel, and Reactive Cavity Cooling System (RCCS). The detailed ring model was applied in two different SAM simulations; (i) normal operating conditions, and (ii) accident scenarios (more specifically, PCC event), for MHTGR design. In both simulations, the SAM calculated results for coolant and heat structure temperatures were within the reactor designed limits. The newly proposed detailed ring model approach in this work has proved to be a promising method to address the challenging modeling and simulation needs in the MHTGR design. As demonstrated in this work, this model was suitable for MHTGR simulations under both normal and accident conditions. Apart from the SAM model development for gas-cooled reactors, 3D Computational Fluid Dynamics (CFD) models were developed and validated with relaminarized Deteriorated Turbulent Heat Transfer (DTHT) MIT benchmark test. Two different CFD codes, Nek5000 and STAR-CCM+, were used for this benchmark activity. Compared with MIT data, Nek5000 shows very good agreement between its simulated and experimentally measured wall temperatures. In contrast, STAR-CCM+ under-predicted wall temperature due to over predicted turbulence in the wall region. The Nek5000 code was also used to develop wall-heat transfer correlations for laminar flow in cylindrical tube. Several simulations were performed for various Reynolds flow and wall heat fluxes. Significant deviations were found when compared the predicted heat transfer coefficient and the Sieder-Tate correlation. A new set of heat transfer correlation was proposed for laminar flow which is valid for 400<Re<2000.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Fuel/Basket Degradation and Waste Package Pressure Effects Modeling (Progress Report)

Progress is reported on development and testing of the Fuel/Basket Degradation Model, and the Waste Package Breach Model. The work follows on reported FY19 model development (SNL-ICG 2019). Modeling has addressed questions framed in the deliverable description: 1) how fuel/basket damage, including from seismic ground motion, could impact reactivity; 2) whether dynamic degradation processes (e.g., caused by seismic ground motion) should be targets for further model development; and 3) what are the key model parameters and how do they affect the likelihood and energy of criticality events. For basket structure made from aluminum-based metal-matrix composite material, basket collapse would coincide with loss of neutron absorbers, and would occur within a few hundred years after waste package breach. Degradation models discussed in this report have thus far focused on a generic 32-PWR (pressurized water reactor fuel) basket with aluminum-based plates

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Additional Data Focused on Phase 1 Geared Toward Computational Fluid Dynamics (CFD) validation

A new validation campaign was developed within the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) to better understand the complex interactions between components of a floating wind system (e.g., columns, pontoons, etc.) in a more generic sense, and to validate modeling approaches for a variety of floating designs. A set of cylinders based on the Offshore Code Comparison Collaboration Continuation (OC4)-DeepCwind semidesign were tested under wave loading, both individually and in different combinations (including the attachment of heave plates of different sizes). The cylinders were held rigid, and pressure sensors were used to measure the distributed loading on the structures, while load cells measured the total integrated hydrodynamic loads.

17 WIND ENERGY↗

Assessment of frequency and amplitude dependence on the cyclic degradation of polyurethane foams

Many energy absorption applications utilize flexible polymeric foams for their viscoelastic properties. It is desired that the material will perform consistently across repeated compression cycles. This study examines the effect of fatigue at low strain rates on the viscoelasticity of open-cell polyurethane foam. Six polyurethanes of the same base composition with two porosities (70% and 80%) and three chemical indexes (79i, 100i, and 121i) are tested. Large deformation cyclic compression of the foams is conducted on a universal testing system (UTS). These data are then post-processed leveraging dynamic mechanical analysis Fourier transform rheology to characterize changes in the viscoelasticity of the materials over fatigue cycles. Results show that foams can increase or decrease in stiffness up to 10% over 10 4 cycles. Specifically, higher chemical index, higher excitation frequency, and larger excitation amplitude correlate with a more pronounced decrease in stiffness. Damping can also change by 15% and correlates with chemical index and excitation frequency. Consequently, the findings suggest that internal foam structure and bulk material properties as well as applied loading parameters affect the viscoelastic fatigue response of flexible polymeric foams.

36 MATERIALS SCIENCE↗

When SLIPS meets TIPS: An endogenous lubricant-infused surface by taking the diluent as the lubricant

Slippery lubricant-infused porous surfaces (SLIPSs) hold great promise in fields requiring adhesion resistance such as self-cleaning, anti-fouling, anti-icing, and anti-scaling. However, their road to practical application is still blocked by the complicated fabrication process and the restricted coating area. To address these challenges, we propose a new concept of endogenous SLIPS in which the porous structure grows from the solution coating of polypropylene/caprylyl methicone undergoing a thermally induced phase separation (TIPS) process. Caprylyl methicone serves as the diluent during TIPS as well as the lubricant in the SLIPS so that the coating can be fabricated in one step and unrestrictedly. Furthermore, the dissolution and phase separation mechanisms have been revealed by molecular dynamic simulation and in situ microscopic observation. Such SLIPSs exhibits impressive sliding property even for sticky and viscous liquids and exhibit extremely low ice adhesion in anti-icing tests.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gravitation and Mesh Adaption

The Gravitation and Mesh Adaptation (GaMA) toolbox consists of a set of Matlab classes for modeling the environment around asteroids and comets. A variety of gravitational models and supporting algorithms from are consolidated alongside a custom meshing utility tailored for the application. This allows the user to work within a single streamlined environment to import and manipulate surface definitions, probe the dynamical environment, integrate trajectories, and post-process results. For other applications, modified surface meshes can be exported. Gravity Models: 1) Werner's analytic polyhedron model 2) Mascon model 3) Gottlieb's spherical harmonic model 4) Approximate polyhedron models 5) Curvilinear surface models 6) Custom composite models Meshing Features: 1) Array-based half-edge data structure 2) Supports curvilinear surface definitions up to degree 4 3) Ray-tracing 4) Coarsening 5) Feature-based refinement 6) Projection 7) Smoothing 8) Mesh quality validity tests 9) Mesh repair Additional Features: 1) Solar radiation pressure model 2) Distant 3rd body model 3) Collision detection 4) Trajectory integration and post-processing 5) Visualization of surface fields

Pearl, Jason↗

Assessment of Survey Results from Advanced Reactor Industry Domain Experts on Nonlinear Soil-Structure Interaction Analysis Software Verification and Validation

The seismic load case has a significant impact on the design and cost of nuclear power plants. Given the need to substantially reduce cost, advanced reactor designers are looking to leverage numerical tools that enable seismic analysis of an integrated vessel/support/structure/soil system. Modern nonlinear analysis tools provide a solution, capturing dynamic coupling between components (including soil-structure interaction (SSI)) concurrent with nonlinear behavior in one or more parts of the system. Although these methods have a rich history of technical development and implementation, software quality assurance (SQA) following nuclear industry standards remains a significant burden for those wishing to adopt such methods for advanced reactor design and licensing. To reduce the SQA burden, this project will develop the guidance for SQA verification and validation (V&V) of coupled nonlinear SSI analysis tools, to include a test matrix of software features and test problems to support commercial grade dedication (CGD). The guidance is intended to be technology-neutral: supporting designers of all advanced reactors. To maximize the value of the project to reactor designers, the project team performed focused surveys of and interviews with advanced reactor designers. Additionally, the project surveyed members of the broader industry involved in reactor design and licensing. The aggregated industry feedback consists of written survey responses, live polling responses, focused interviews, and informal feedback provided after outreach presentations, collectively referred to as “survey results”. Herein, the survey results are reported, reviewed, and assessed to inform follow-on project activities. The survey results confirmed the familiarity of the industry with the coupled nonlinear SSI analysis. They also affirm the project need based upon the expressed intent to (1) incorporate nonlinear features and (2) pursue the coupled nonlinear SSI analysis to reduce seismic demands and construction costs. All reactor designers indicated their intent to incorporate two or more nonlinear features, and all reactor designer respondents opined that the coupled nonlinear SSI analysis would allow for the optimization of the reactor design and construction. However, the programmatic challenges, whether real or perceived, present a significant barrier to reactor designers. The barrier most commonly identified by the reactor designer population was regulatory risk, with 70% citing this as a reason not to pursue the approach. The perceived regulatory risk identified by the reactor designers underscores the importance of regulator engagement and dialogue in this project. Additionally, half of the reactor designers identified cost and lack of guidance as a deterrent. The survey results also provide insights to tailor specific aspects of the guidance document and test matrix. The project plans to prepare both a formal referenceable guidance document and a collaborative, web-based test matrix and problem set. The project will focus on more complete test problem definitions for the prioritized nonlinear features over shallower problem descriptions for a larger set of features. The nonlinearities prioritized as high based upon survey feedback include fluid-structure interaction and seismic isolation and energy dissipation devices. The nonlinearities prioritized as intermediate include nonlinear geomaterials, nonlinear concrete, nonlinear steel, and interface/contact nonlinearity. Deep embedment and the associated nonlinear phenomena are assigned the lowest priority based upon survey feedback.

42 ENGINEERING↗

Modeling Mesoscale Processes of Scalable Synthesis Final Scientific/Technical Report

This is the final scientific and technical report for this award. Molecular dynamics (MD) is a powerful tool to study biomolecules at the nanoscale. One of its main limitations however is that such simulations typically require a timestep of 1 femtosecond while reactions and conformational changes typically happen on the time scale of 1 microsecond or more. This discrepancy severely restricts the impact of this method. We have developed a series of algorithms to mitigate this problem and allow predicting long-time scale events using much shorter simulations. The method is based on the concurrent adaptive sampling method. It consists in using probabilistic weights for trajectories and biasing the sampling such that rare but important trajectories, e.g., those that go over energy barriers and lead to relevant conformational changes in the molecule, are observed with much higher frequency that in a standard MD simulation. We will demonstrate below that this approach has been very successful. In collaboration with Jay Grate at PNNL we have applied this novel method to the study the triazine polymers, which can be con gured using different types of side chains in order to adopt different 3-dimensional structures. We have found novel stable con- formations and have analyzed the impact of side chain modifcations on the native folded shape of the polymer. Direct MD simulations would have been untractable for this problem. The method of replica exchange was also used successfully to calculate free energy profiles, in particular for cis-trans torsional angle changes with high energy barriers. Studying molecules at the atomistic scale is essential to design new molecules in chemical engineering, such as the triazine polymers developed by Grate, in material science to study the strength of metals for examples (e.g., dislocation dynamics), or in biochemistry to understand how proteins fold and how they interact with ligands (a key step in designing drugs). Although new hardware makes these simulations increasingly faster (e.g., GPU, Anton from DE Shaw Research), new algorithms are key to making these methods more tractable and increase their impact. At this point, because of limitations in modeling, one of the main techniques for advancing science remains to a large extent numerous and costly experiments. For exam- ple, when designing drug, where multiple variants must be screened, the ability to run tests on a computer rather than experimentally testing with high throughput methods thousands of compounds would represent a signi cant advance with broad benefits for the public at large.

36 MATERIALS SCIENCE↗

A dynamic data-driven method for dealing with model structural error in soil moisture data assimilation

Attributing to the flexibility in considering various types of observation error and model error, data assimilation has been increasingly applied to dynamically improve soil moisture modeling in many hydrological practices. However, accurate characterization of model error, especially the part caused by defective model structure, presents a significant challenge to the successful implementation of data assimilation. Model structural error has received limited attention relative to parameter and input errors, mainly due to our poor understanding of structural inadequacy and the difficulties in parameterizing structural error. In this paper, we present a dynamic data-driven approach to estimate the model structural error in soil moisture data assimilation without the need for identifying error generation mechanism or specifying particular form for the error model. The error model is based on the Gaussian process regression and then integrated into the ensemble Kalman filter (EnKF) to form a hybrid method for dealing with multi-source model errors. Two variants of the hybrid method in terms of two different error correction manners are proposed. The effectiveness of the proposed method is tested through a suit of synthetic cases and a real-world case. Results demonstrate the potential of the proposed hybrid method for estimating model structural error and providing improved model predictions. Compared to the traditional EnKF without explicitly considering the model structural error, parameter compensation issue is obviously reduced and soil moisture retrieval is substantially improved.

54 ENVIRONMENTAL SCIENCES↗

The role of composition in the structure and water-binding in alkali-silica reaction sol and gel

The discrepancy between alkali cation (Na + ) used in accelerated assessments of potential alkali-silica reactivity (ASR) and those predominant in portland cements (larger amounts of K + than Na + ) leads to questions regarding the reliability of standardized test methods to predict concrete field performance. To better understand the role of alkali cation type in ASR, this study investigates the influence of alkali cation type on the structure and water-binding ability of ASR sols and gels of varying composition. Results obtained by small-angle neutron scattering, 1H NMR relaxometry, and rheological measurements indicate the formation of densified agglomerate structures with increasing silica-to-alkali molar mass ratios (S/A). However, Na-based sols exhibit a greater tendency to agglomerate and a higher dynamic viscosity than K-based ones. Furthermore, at high S/A, 1 H NMR relaxometry shows the greater ability of K-based gels to bind water, suggesting the better dispersion of siliceous structures and the development of finer porosities.

36 MATERIALS SCIENCE↗

Effect of Internal Structure on Warpage in a Large-Scale Additive Manufacturing Process With Bio-Derived Composites

Extrusion-based large-format additive manufacturing (LFAM) often results in unintended deformation and failures due to thermal residual stress between layers. This LFAM involves a hot molten polymer deposited on a previously deposited and cooled layer, generating a temperature mismatch between the layers. The temperature discrepancy causes a thermal contraction mismatch, generating thermal residual stress. Due to the residual stress, printed structures experience warpage and delamination Therefore, understanding the heat distribution behavior is essential to preventing undesired deformation and failures. The goal of this study is to investigate the effect of infill patterns on heat distribution and deformation in an LFAM system. Wood fiber-reinforced polylactic acid was used as a sustainable and low-cost reinforcement material. A numerical model was developed to predict the temperature and deformation field with thermo-mechanical properties, which were measured by a dynamic mechanical analysis and a thermal expansion test. Simulations were performed on a box geometry with three different infill patterns. The simulation model was verified with temperature data gathered from an infrared camera. The results show good agreement between predicted and measured temperature profiles. The developed simulation model was applied to a roof tray with different infill patterns for a case study. We found that the different thermal mass distributions resulting from the various infill patterns affected the heat distribution and deformation. These findings contribute to a better understanding of the thermal and mechanical behavior of LFAM.

Jo, Eonyeon↗

Evaluation of Common Thermoplastic Polymers in High-Pressure Cycling Hydrogen Under Ambient and Cold Environments as Applicable to the Hydrogen Infrastructure

Thermoplastic polymers are required to perform unfailingly under stringent conditions of changing pressures (35 MPa to 70 MPa) and temperatures (-40°C to +85°C) in storage and fueling operations. Although diffusivity in glassy polymers appear to be an order of magnitude lower than elastomers, polymer microstructural attributes such as degree of crystallinity and presence of polar and non-polar groups on the main chain with and without branching can play a substantial role in influencing their behaviors in hydrogen environments. In the work described here, the effect of high-pressure hydrogen cycling on PEEK, PTFE, PA11, HDPE, POM (and different commercial grades of these polymers) under ambient and cold (-40°C) conditions is addressed. Ex-situ characterization for polymer changes included density measurements for impact of hydrogen retention, hardness changes using nanoindentation, storage modulus and glass transition changes using dynamic mechanical and thermal analysis (DMTA), degree of crystallization with Differential Scanning Calorimetry (DSC) and tensile testing following ASTM D412. In other evaluations, solid-state nuclear magnetic resonance (NMR), attenuated total reflectance Fourier transform infra-red spectroscopy (ATRFTIR), X-ray diffraction (XRD), and X-ray CT results are presented. The overall impact of these evaluations is to establish a technical basis for the behaviors of common thermoplastics in cycling hydrogen environments under ambient and cold temperatures while establishing the relationship between polymer structure-based properties and hydrogen transport effects.

Menon, Nalini C.↗

Novel Transparent Phosphor Conversion Matrix with High Thermal Conductivity for Next Generation Phosphor-Converted LED-based Solid State Lighting

The low thermal conductivity of state-of-the-art polymer encapsulants (k ~ 0.15 Wm-1K-1) limits the efficiency and power density of current phosphor conversion light emitting diodes (pc-LEDs). The technical objective of this project was to demonstrate synthesis and processing schemes for the fabrication of polymer hybrid encapsulants with a thermal conductivity exceeding k = 0.4 Wm-1K-1 for LED applications. The ‘hybrid polymer’ approach encompasses the dispersion of high thermal conductivity particle fillers (zinc oxide, ZnO as well as the alpha-polymorph of alumina, Al2O3) within a polysiloxane matrix (poly(dimethylsiloxane), PDMS as well as poly(phenyl methyl siloxane), PPMS) to increase the thermal conductivity while maintaining optical transparency and photothermal stability at levels consistent with LED applications. To accomplish this goal, a novel synthesis method for the fabrication of nanosized ZnO particles was developed and a novel surface chemistry was established to modify the surface of zinc oxide particle fillers and thus to enable their dispersion in poly(dimethyl siloxane) (PDMS) matrix polymers. Molecular dynamics and Mie simulations were used to optimize ligand structure and to enable the concurrent mixing of particles in PDMS/PPMS embedding media while also minimizing the thermal boundary resistance as well as optical scattering of particle fillers. Using this approach the synthesis of PDMS/ZnO hybrid encapsulants exhibiting a thermal conductivity of 0.64 Wm-1K-1 and optical transparency > 0.7 mm-1 was demonstrated. A forming process based on micromolding was developed to demonstrate the forming of particle filled PDMS into film and lens shapes. Photothermal stability testing revealed stability of the materials for approximately 4000 min when exposed to blue light LED (450 nm, 30 W/cm2). One postgraduate and seven graduate students were supported by the project. The research performed within this project led to fifteen publications in peer-reviewed journals and one patent application. The grant stimulated a multi-investigator research collaborations among seven investigators at Carnegie Mellon University to address the challenge of encapsulants in pc-LED applications. The grant also catalyzed the future collaboration between researchers at Carnegie Mellon University and OSRAM Sylvania to address challenges associated with the use if polymers in LED applications.

36 MATERIALS SCIENCE↗

Light-Driven Charge Transfer in Face-to-Face Donor-Spacer-Acceptor Supramolecular Systems

The efficient conversion of sunlight to a useful form of energy both in green plants and in manmade dye-sensitized solar cells requires the efficient separation of a positive and negative charge. The charge separation process begins with the absorption of visible or ultraviolet light by a pigment such as chlorophyll or a dye such as a transition metal complex followed by fast electron transfer to a neighboring molecule to form a pair of ionized molecules with opposite charges. At that point, one of the two opposite charges must rapidly move away from the other one by the process of charge separation. Once the migrating charge reaches its destination, it can be converted to electrical or chemical energy. The overall efficiency of charge separation in these systems is determined by the competition between charge separation and charge recombination at each stage in the process. Whereas most investigations of photoinduced charge separation have employed synthetic polymers or covalent linkages to separate the photoactive molecular and charge acceptor, we have employed the natural biopolymer DNA for this purpose. DNA possesses a unique structure consisting of a hydrophobic core of hydrogen-bonded base pairs which form a one-dimensional π-stacked array. The possibility that the π-stacked base pairs of DNA might function as a one-dimensional conductor or molecular wire was first advanced over 50 years ago. However, systematic measurements of the dynamics and efficiency of charge separation in DNA-based systems were not undertaken prior to the initiation of our studies 22 years ago. A variety of organic chromophores can be attached to one or both ends of the base pair domain of DNA or at any location within the domain. The length and base sequence of the base pair domain can also be varied. The structures of these synthetic derivatives of DNA have been determined using a combination of X-ray diffraction, NMR spectroscopy, and molecular modeling. Selective excitation with UV or visible light of the appropriate chromophore can effect injection of either positive charge (holes) or negative charge (electrons) into the base pair domain. The dynamics of hole or electron injection can be studied by a combination of fluorescence quenching and transient absorption measurements. Moreover, the simple design of our systems is amenable to theoretical modeling, allowing the development and testing of models which may prove applicable to more complex systems. Our initial studies of hole transport in short synthetic DNA with either repeating or alternating base sequences showed it to be strongly distance dependent, seemingly contradicting claims that DNA might serve as a wire in molecular electron devices. Further research on the base-sequence dependence of hole transport dynamics showed that significant enhancement in hole transport dynamics could be achieved by the used of special sequences designed to prevent the photo-generated charges from recombining. More recent experimental research and theoretical modelling has served to define each stage of the charge-separation process: electronic excitation, hole injection, hole transport, hole transport, and charge recombination. DNA is less effective as a carrier for electron transport; however, many of these details have also been determined for this process. In summary, a combination of molecular design and synthesis, spectroscopy, and theory have made possible the most complete study of photoinduced charge separation on any complex donor-bridge-acceptor system studied to date. These results serve as a benchmark to which related studies can be compared.

14 SOLAR ENERGY↗

Evolution of Precipitation Structure During the November DYNAMO MJO Event: Cloud-Resolving Model Inter-comparison and Cross-Validation using Radar Observations

Evolution of precipitation structures are simulated and compared with radar observations for the November Madden-Julian Oscillation (MJO) event during the DYNAmics of the MJO (DYNAMO) field campaign. Three ground-based, ship-borne, and space-borne precipitation radars and three Cloud-Resolving Models (CRMs) driven by observed large-scale forcing are used to study precipitation structures at different locations over the central equatorial Indian Ocean. Convective strength is represented by 0-dBZ echo-top heights, and convective organization by contiguous 17-dBZ areas. The multi-radar and multi-model framework allows for more stringent model validations. The emphasis is on testing models’ ability to simulate subtle differences observed at different radar sites when the MJO event passed through. The results show that CRMs forced by site-specific large-scale forcing can reproduce not only common features in cloud populations, but also subtle variations observed by different radars. The comparisons also revealed common deficiencies in CRM simulations where they underestimate radar echo-top heights for the strongest convection within large, organized precipitation features. Cross-validations with multiple radars and models also enable quantitative comparisons in CRM sensitivity studies using different large-scale forcing, microphysical schemes and parameters, resolutions, and domain sizes. In terms of radar echo-top height temporal variations, many model sensitivity tests have better correlations than radar/model comparisons, indicating robustness in model performance on this aspect. It is further shown that well-validated model simulations could be used to constrain uncertainties in observed echo-top heights when the low-resolution surveillance scanning strategy is used.

54 ENVIRONMENTAL SCIENCES↗

An Improved Formulation for Hybridizable Discontinuous Galerkin Fluid-Structure Interaction Modeling with Reduced Computational Expense

Here, this work presents two computational efficiency improvements for the hybridizable discontinuous Galerkin (HDG) fluid-structure interaction (FSI) model presented by Sheldon et al. A new formulation for the solid is presented that eliminates the global displacement, resulting in the velocity being the only global solid variable. This necessitates a change to the solid-mesh displacement coupling, which is accounted for by coupling the local solid displacement to the global mesh displacement. Additionally, the mesh basis and test functions are restricted to linear polynomials, rather than being equal-order with the fluid and solid. This change increases the computational efficiency dynamically, with greater benefit the higher order the computation, when compared to an equal-order formulation. These two improvements result in a 50% reduction in the number of global degrees of freedom for high-order simulations for both the fluid and solid domains, as well as an approximately 50% reduction in the number of local fluid domain degrees of freedom for high-order simulations. Finally, the new, more efficient formulation is compared against that from Sheldon et al. and negligible change of accuracy is found.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Computing water flow through complex landscapes – Part 2: Finding hierarchies in depressions and morphological segmentations

Depressions – inwardly draining regions of digital elevation models – present difficulties for terrain analysis and hydrological modeling. Analogous “depressions” also arise in image processing and morphological segmentation, where they may represent noise, features of interest, or both. Here we provide a new data structure – the depression hierarchy – that captures the full topologic and topographic complexity of depressions in a region. We treat depressions as networks in a way that is analogous to surface-water flow paths, in which individual sub-depressions merge together to form meta-depressions in a process that continues until they begin to drain externally. This hierarchy can be used to selectively fill or breach depressions or to accelerate dynamic models of hydrological flow. Complete, well-commented, open-source code and correctness tests are available on GitHub and Zenodo.

54 ENVIRONMENTAL SCIENCES↗

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗