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At least 1,459 records · Page 81

Prediction and uncertainty quantification of shale well performance using multifidelity Monte Carlo

Uncertainty quantification is an integral component of reservoir management, especially considering the inherent uncertainty in subsurface systems. While a standard practice to estimate the uncertainty, Monte Carlo (MC) simulation is computationally intense when the sampling population comprises high-fidelity simulations. Alternatively, the Multi-fidelity Monte Carlo (MFMC) simulation overcomes this computational intensity by integrating low- and high-fidelity simulations. Our goal is to minimize the number of expensive high-fidelity simulations while maintaining accuracy and using numerous fast and cheap low-fidelity simulations to efficiently sample to input parameter space of interest. We selected gas production from unconventional wells to demonstrate the potential speedups and accuracy of the MFMC approach. The model fidelity usually determines the trade-off between accuracy and efficiency. While the high-fidelity model is more accurate, the low-fidelity model is more efficient. Our high-fidelity simulation includes reservoir simulations of a hydraulically fractured well. On the other hand, our low-fidelity model comprises the parallel-plate flow model. We used differential programming to efficiently solve the 1D flow model, where automatic differentiation is used to efficiently compute the gradients. We matched the production profile of high-fidelity simulations with our low-fidelity simulations. Then, we used a support vector regression to map the high- and low-fidelity input parameters. The mapping function is essential to tune the low-dimensional parameter space of the low-fidelity model to the high-dimensional parameter space of the high-fidelity model. We found that we can use a combination of 9 high fidelity and 10,000 low fidelity simulations to efficiently and accurately simulate pressure management. This method is at least two orders of magnitude faster than only using high-fidelity simulations. Finally, from a broader perspective, MFMC could efficiently estimate the uncertainty of various systems and models, integrating low- and high-fidelity models.

04 OIL SHALES AND TAR SANDS↗

Investigation of the continuous-energy sensitivity methods in scale 6.2 using Tsunami-3D - 14579

The SCALE 6.1 code system includes a multigroup (MG) method for three-dimensional (3D) sensitivity analyses via the Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI), and the upcoming release of SCALE 6.2 will feature the system's first implementation of continuous-energy (CE) sensitivity methods. Detailed information regarding the CE TSUNAMI-3D eigenvalue sensitivity methods is provided in a companion paper. This work compares the results of TSUNAMI-3D calculations using the traditional MG approach to the new CE CLUTCH method in SCALE 6.2. The systems examined in this study include combinations of fast, thermal, and mixed spectra with metal, compound, and solution material forms. The primary fissile species include low-enriched uranium, intermediate-enriched uranium, high-enriched uranium, plutonium, and mixed uranium and plutonium. This broad range of systems expands the experience base with the CE CLUTCH method, identifies best practices for using the code, and provides generic user guidance for utilizing this new capability. Additionally, the study demonstrates the accuracy and usefulness of the CE CLUTCH method, especially for systems for which MG methods perform poorly. (authors)

42 ENGINEERING↗

Computational Study of Variable Fuel-Air Ratio and Hydrogen Doping in a Rotating Detonation Engine

Rotating detonation engines (RDEs) hold great promise as a technology for powering aviation engines. The pressure gain that results from continuously traversing detonation waves enables high theoretical performance compared to deflagration-based combustion. However, the harsh operating conditions inside an RDE restrict the availability of suitable experimental diagnostics to study these systems in detail and the range of spatial and temporal scales render numerical simulations of these systems difficult. In this study, we have combined adaptive mesh refinement and a robust shock-capturing approach to study RDE systems computationally using the compressible, reactive solver PeleC. Multi-species transport along with compressible Navier-Stokes equations are solved in the model along with finite-rate chemistry. Complex geometries are represented using an embedded boundary method with second-order spatial accuracy and the system is evolved in time using a second-order Runge-Kutta method. We present studies of a methane-air RDE system that is doped with varying levels of hydrogen. Our analysis focusses on how fuel mixture and doping levels effect the detonation flame structure and the generation of multiple wave modes.

ADVANCED PROPULSION SYSTEMS↗

CO 2 Hydrogenation to Methanol over ZrO 2 -Containing Catalysts: Insights into ZrO 2 Induced Synergy

Catalytic hydrogenation of CO 2 with renewable H 2 to methanol represents a promising pathway for reducing anthropogenic CO 2 emissions. Catalysts play a key role in enhancing both the hydrogenation rate and methanol selectivity. ZrO 2 is a promising catalyst support, promoter and even active species for CO 2 hydrogenation due to its versatile properties and weak hydrophilic character. Over the past decades substantial progress has been made in designing high performance catalysts and understanding the hydrogenation mechanisms over ZrO 2 -supported catalysts. ZrO 2 interacts with metals and/or other oxides and consequently may affect the CO 2 adsorption and activation, enhance the dissociation of H 2 and spillover of atomic hydrogen, change the reaction pathways and/or the binding of key reaction intermediates for further conversion. The synergistic effects induced by ZrO 2 could be achieved by improving the metal dispersion, modifying surface basicity and interacting with other components (metals, cosupports or promoters). However, although experimental and computational investigations have been extensively performed, the multiple roles of ZrO 2 in the catalytic process are still under debate. In the current Perspective, we use ZrO 2 -containing catalysts as a model system to elucidate the governing principles for designing high performance catalysts with multiple active components for CO 2 hydrogenation to methanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessment and Improvement of Fission Product Transport Predictions of Particle Fuel in BISON

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. This study was motivated by the need to incorporate more physics-based models in BISON in order to foster tri-structural isotropic (TRISO) applications. This document details the integration of new modeling capabilities in BISON, including (1) development of pyrolytic carbon (PyC) and silicon carbide (SiC) layer anisotropic thermal and mass transport capabilities, (2) verification of the mass diffusion solution in TRISO modeling, (3) calibration of fission product diffusivity using Advanced Gas Reactor (AGR) experiments, (4) improved fission product release modeling by developing compact diffusion modeling capabilities, and (5) documentation of accelerated failure analysis on the BISON website. Improvements made to the diffusion models and parameters were documented and validated against AGR-1 and -2 experiment data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Expert Meeting: Recommended Approaches to Humidity Control in High Performance Homes

This meeting was held on October 16, 2012, in Westford, MA, and brought together experts in the field of residential humidity control to address modeling issues for dehumidification. The presentations and discussions centered on computer simulation and field experience with these systems, with the goal of developing foundational information to support the development of a Building America Measure Guideline on this topic.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Scalable self attraction and loading calculations for unstructured ocean tide models

Self attraction and earth-loading effects are important for accurately modeling global tides. A common approach of handling this forcing is to expand mass anomalies into spherical harmonics, which are scaled by load Love numbers to account for elastic earth deformation. We investigate two different approaches to perform these calculations for ocean models that employ unstructured meshes and distributed memory parallelization. The first approach leverages a highly efficient spherical harmonics library, but requires all-to-one and one-to-all communications and interpolation operations between the unstructured and a structured mesh. This approach is compared to a parallel algorithm that computes the spherical harmonic transformations directly on the unstructured mesh with an all-reduce communication. Here, our results show that although the unstructured mesh calculations are more expensive, the scalability of the unstructured mesh approach allows for more efficient spherical harmonics transforms for high-resolution meshes and large processor counts. This methodology enables the efficient inclusion of tidal dynamics large-scale Earth system model simulations.

54 ENVIRONMENTAL SCIENCES↗

GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit

In this study, molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. As a result, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.

97 MATHEMATICS AND COMPUTING↗

Parallel accelerated Custom Correlation Coefficient calculations for genomics applications

The massive quantities of genomic data being made available through gene sequencing techniques are enabling breakthroughs in genomic science in many areas such as medical advances in the diagnosis and treatment of diseases. Analyzing this data, however, is a computational challenge insofar as the computational costs of the relevant algorithms can grow with quadratic, cubic or higher complexity—leading to the need for leadership scale computing. In this paper we describe a new approach to calculations of the Custom Correlation Coefficient (CCC) between Single Nucleotide Polymorphisms (SNPs) across a population, suitable for parallel systems equipped with graphics processing units (GPUs) or Intel Xeon Phi processors. We describe the mapping of the algorithms to accelerated processors, techniques used for eliminating redundant calculations due to symmetries, and strategies for efficient mapping of the calculations to many-node parallel systems. Results are presented demonstrating high per-node performance and near-ideal parallel scalability with rates of more than nine quadrillion (9 × 10 15 ) elementwise comparisons achieved per second with the latest optimized code on the ORNL Titan system, this being orders of magnitude faster than rates achieved using other codes and platforms as reported in the literature. Also it is estimated that as many as 90 quadrillion (90 × 10 15 ) comparisons per second may be achievable on the upcoming ORNL Summit system, an additional 10X performance increase. Finally, in a companion paper we describe corresponding techniques applied to calculations of the Proportional Similarity metric for comparative genomics applications.

97 MATHEMATICS AND COMPUTING↗

A scalable Euler–Lagrange approach for multiphase flow simulation on spectral elements

Multiphase flow can be difficult to simulate with high accuracy due to the wide range of scales associated with various multiphase phenomena. These scales may range from the size of individual particles to the entire domain of interest. Traditionally, large scale systems can only be simulated using averaging approaches that filter out the locations of individual particles. In this work, the Euler–Lagrange method is used to simulate large-scale dense particle systems in which each individual particle is tracked. In order to accomplish this, the highly scalable spectral element code nek5000 has been extended to handle the multiple levels of multiphase coupling in these systems. These levels include what has been called one-, two-, and four-way coupling. Here, each level has been separated to detail the computational impact of each stage. A binned ghost particle algorithm has also been developed to efficiently handle the challenges of two- and four-way coupling in a parallel processing context. The algorithms and their implementations are then shown to scale to 65,536 Message Passing Interface (MPI) ranks in both the strong and weak limits. After this, validation is performed through simulation of a small-scale fluidized bed. Lastly, a large-scale fluidized bed is simulated with 65,536 MPI ranks and is able to capture the unique physics of the onset of fluidization.

Computer Science↗

Hard Disk/Solid State Drive Synergy in Support of Data-Intensive Computing [Slides]

Data-intensive applications are becoming increasingly common in high-performance computing. Examples include combustion simulation, human genome analysis, and satellite image processing. Efficient access of data sets is critical to the performance of these applications. Because of the size of the data today's economically feasible approach is to store the data files on an array of hard disks or data servers equipped with hard disks and managed by a parallel file system such as PVFS or Lustre wherein the data is striped over a (large) number of disks for high aggregate I/O throughout. With file striping, a request for a segment of logically contiguous file space is decomposed into multiple sub-requests, each to a different server. While the data unit for this striping is usually reasonably large to benefit disk efficiency, the first and/or last sub-requests can be much smaller than the striping unit if the request does not align with the striping pattern, severely compromising hard disk efficiency and thus application performance. We propose to exploit solid state drives (SSD), whose efficiency is much less sensitive to small random accesses, to enable the alignment of requests to disk with the data striping pattern. In this scheme hard disks mainly serve large, aligned, sequential requests, with SSDs serving small or unaligned requests, thus respecting the relative cost, performance, and durability characteristics of the two media, and thereby achieving synergy in performance/cost. We will describe the design of the proposed scheme, its implementation on CCS-7's Darwin cluster, and performance results.

97 MATHEMATICS AND COMPUTING↗

Performance of a high-sensitivity dedicated cardiac SPECT scanner for striatal uptake quantification in the brain based on analysis of projection data

Purpose: The authors have previously reported the advantages of high-sensitivity single-photon emission computed tomography (SPECT) systems for imaging structures located deep inside the brain. DaTscan (Isoflupane I-123) is a dopamine transporter (DaT) imaging agent that has shown potential for early detection of Parkinson disease (PD), as well as for monitoring progression of the disease. Realizing the full potential of DaTscan requires efficient estimation of striatal uptake from SPECT images. They have evaluated two SPECT systems, a conventional dual-head gamma camera with low-energy high-resolution collimators (conventional) and a dedicated high-sensitivity multidetector cardiac imaging system (dedicated) for imaging tasks related to PD. Methods: Cramer-Rao bounds (CRB) on precision of estimates of striatal and background activity concentrations were calculated from high-count, separate acquisitions of the compartments (right striata, left striata, background) of a striatal phantom. CRB on striatal and background activity concentration were calculated from essentially noise-free projection datasets, synthesized by scaling and summing the compartment projection datasets, for a range of total detected counts. They also calculated variances of estimates of specific-to-nonspecific binding ratios (BR) and asymmetry indices from these values using propagation of error analysis, as well as the precision of measuring changes in BR on the order of the average annual decline in early PD. Results: Under typical clinical conditions, the conventional camera detected 2 M counts while the dedicated camera detected 12 M counts. Assuming a normal BR of 5, the standard deviation of BR estimates was 0.042 and 0.021 for the conventional and dedicated system, respectively. For an 8% decrease to BR = 4.6, the signal-to-noise ratio were 6.8 (conventional) and 13.3 (dedicated); for a 5% decrease, they were 4.2 (conventional) and 8.3 (dedicated). Conclusions: This implies that PD can be detected earlier with the dedicated system than with the conventional system; therefore, earlier identification of PD progression should be possible with the high-sensitivity dedicated SPECT camera.

60 APPLIED LIFE SCIENCES↗

Evaluation of CHO Benchmarks on the Arria 10 FPGA using Intel FPGA SDK for OpenCL

The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. Benchmarking of OpenCL-based framework is an effective way for analyzing the performance of system by studying the execution of the benchmark applications. CHO is a suite of benchmark applications that provides support for OpenCL [1]. The authors presented CHO as an OpenCL port of the CHStone benchmark. Using Altera OpenCL (AOCL) compiler to synthesize the benchmark applications, they listed the resource usage and performance of each kernel that can be successfully synthesized by the compiler. In this report, we evaluate the resource usage and performance of the CHO benchmark applications using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board that features an Arria 10 FPGA device. The focus of the report is to have a better understanding of the resource usage and performance of the kernel implementations using Arria-10 FPGA devices compared to Stratix-5 FPGA devices. In addition, we also gain knowledge about the limitations of the current compiler when it fails to synthesize a benchmark application.

97 MATHEMATICS AND COMPUTING↗

Effects of increasing tip velocity on wind turbine rotor design.

A reduction in cost of energy from wind is anticipated when maximum allowable tip velocity is allowed to increase. Rotor torque decreases as tip velocity increases and rotor size and power rating are held constant. Reduction in rotor torque yields a lighter weight gearbox, a decrease in the turbine cost, and an increase in the capacity for the turbine to deliver cost competitive electricity. The high speed rotor incurs costs attributable to rotor aero-acoustics and system loads. The increased loads of high speed rotors drive the sizing and cost of other components in the system. Rotor, drivetrain, and tower designs at 80 m/s maximum tip velocity and 100 m/s maximum tip velocity are created to quantify these effects. Component costs, annualized energy production, and cost of energy are computed for each design to quantify the change in overall cost of energy resulting from the increase in turbine tip velocity. High fidelity physics based models rather than cost and scaling models are used to perform the work. Results provide a quantitative assessment of anticipated costs and benefits for high speed rotors. Finally, important lessons regarding full system optimization of wind turbines are documented.

17 WIND ENERGY↗

Fast equilibration protocol for million atom systems of highly entangled linear polyethylene chains

Equilibrated systems of entangled polymer melts cannot be produced using direct brute force equilibration due to the slow reptation dynamics exhibited by high molecular weight chains. Instead, these dense systems are produced using computational techniques such as Monte Carlo-Molecular Dynamics hybrid algorithms, though the use of soft potentials has also shown promise mainly for coarse-grained polymeric systems. Through the use of soft-potentials, the melt can be equilibrated via molecular dynamics at intermediate and long length scales prior to switching to a Lennard-Jones potential. We will outline two different equilibration protocols, which use various degrees of information to produce the starting configurations. In one protocol, we use only the equilibrium bond angle, bond length, and target density during the construction of the simulation cell, where the information is obtained from available experimental data and extracted from the force field without performing any prior simulation. In the second protocol, we moreover utilize the equilibrium radial distribution function and dihedral angle distribution. This information can be obtained from experimental data or from a simulation of short unentangled chains. Both methods can be used to prepare equilibrated and highly entangled systems, but the second protocol is much more computationally efficient. These systems can be strictly monodisperse or optionally polydisperse depending on the starting chain distribution. Our protocols, which utilize a soft-core harmonic potential, will be applied for the first time to equilibrate a million particle system of polyethylene chains consisting of 1000 united atoms at various temperatures. Calculations of structural and entanglement properties demonstrate that this method can be used as an alternative towards the generation of entangled equilibrium structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational discovery of stable and metastable ternary oxynitrides

Materials design from first principles enables exploration of uncharted chemical spaces. Extensive computational searches have been performed for mixed-cation ternary compounds, but mixed-anion systems are gaining increased interest as well. Central to computational discovery is the crystal structure prediction, where the trade-off between reliance on prototype structures and size limitations of unconstrained sampling has to be navigated. We approach this challenge by letting two complementary structure sampling approaches compete. We use the kinetically limited minimization approach for high-throughput unconstrained crystal structure prediction in smaller cells up to 21 atoms. On the other hand, ternary—and, more generally, multinary—systems often assume structures formed by atomic ordering on a lattice derived from a binary parent structure. Thus, we additionally sample atomic configurations on prototype lattices with cells up to 56 atoms. Using this approach, we searched 65 different charge-balanced oxide–nitride stoichiometries, including six known systems as the control sample. The convex hull analysis is performed both for the thermodynamic limit and for the case of synthesis with activated nitrogen sources. We identified 34 phases that are either on the convex hull or within a viable energy window for potentially metastable phases. We further performed structure sampling for “missing” binary nitrides whose energies are needed for the convex hull analysis. Among these, we discovered metastable Ce3N4 as a nitride analog of the tetravalent cerium oxide, which becomes stable under slightly activated nitrogen condition µN > +0.07 eV. Given the outsize role of CeO2 in research and application, Ce3N4 is a potentially important discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Xenon Recovery at Room Temperature using Metal-Organic Frameworks

Xenon is known to be a very efficient anesthetic gas but its cost prohibits the wider use in medical industry and other potential applications. It has been shown that Xe recovery and recycle from anesthetic gas mixture can significantly reduce its cost as anesthetic. The current technology uses series of adsorbent columns followed by low temperature distillation to recover Xe, which is expensive to use in medical facilities. Herein, we propose much efficient and simpler system to recover and recycle Xe from simulant exhale anesthetic gas mixture at room temperature using metal organic frameworks. Among the MOFs tested, PCN-12 exhibits unprecedented performance with high Xe capacity, Xe/N2 and Xe/O2 selectivity at room temperature. The in-situ synchrotron measurements suggest the Xe is occupied in the small pockets of PCN-12 compared to unsaturated metal centers (UMCs). Computational modeling of adsorption further supports our experimental observation of Xe binding sites in PCN-12.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GWAS identifies candidate genes controlling adventitious rooting in Populus trichocarpa

Adventitious rooting (AR) is critical to the propagation, breeding, and genetic engineering of trees. The capacity for plants to undergo this process is highly heritable and of a polygenic nature; however, the basis of its genetic variation is largely uncharacterized. To identify genetic regulators of AR, we performed a genome-wide association study (GWAS) using 1148 genotypes of Populus trichocarpa. GWASs are often limited by the abilities of researchers to collect precise phenotype data on a high-throughput scale; to help overcome this limitation, we developed a computer vision system to measure an array of traits related to adventitious root development in poplar, including temporal measures of lateral and basal root length and area. GWAS was performed using multiple methods and significance thresholds to handle non-normal phenotype statistics and to gain statistical power. These analyses yielded a total of 277 unique associations, suggesting that genes that control rooting include regulators of hormone signaling, cell division and structure, reactive oxygen species signaling, and other processes with known roles in root development. Numerous genes with uncharacterized functions and/or cryptic roles were also identified. These candidates provide targets for functional analysis, including physiological and epistatic analyses, to better characterize the complex polygenic regulation of AR.

59 BASIC BIOLOGICAL SCIENCES↗