PNNL-13501 - Pacific Northwest National Laboratory

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Roberts AL, LA Totten, WA Arnold, DR Burris, and TJ Campbell. 1996. “Reductive elimination of chlorinated ethylenes by zero-valent metals.” Environ. Sci Technol. 30, 2654-2659. Singh J, SD Comfort and PJ Shea. 1999. “Iron-mediated remediation of RDX-contaminated water and soil under controlled Eh/pH.” Environ. Sci. Technol. 33, 1488-1494. Tratnyek PG. 1996. “Putting corrosion to use: remediating contaminated groundwater with zero-valent metals.” Chem & Ind, July 1, 499-503. 258 FY 2000 <strong>Laboratory</strong> Directed Research and Development Annual Report Wilson EK. 1995. “Zero-valent metals provide possible solution to groundwater problems.” Chem Eng News, 73, 19-22. Yamane CL, SD Warner, JD Gallinatti, FS Szerdy, TA Delfino, DA Hankins, and JL Vogan. 1995. “Installation of a subsurface groundwater treatment wall composed of granular zero-valent iron.” Preprint of Extended Abstracts from the 209th ACS <strong>National</strong> Meeting, Anaheim, California, 35, 792-795. Div of Environ Chem, Am Chem Soc, Washington, D.C.
Study Control Number: PN99076/1404 Vadose Zone and Pore-Scale Process Modeling Mark D. White, Jim A. Fort, Matt Rosing Numerical simulation on massively parallel computers provides scientists and engineers with the analytical tools necessary to assess risks and devise effective remediation schemes for subsurface contamination. Computational tools are being developed on this project that allow researchers to accurately represent geologic and engineered subsurface features, while maintaining the efficiencies of parallel computing. Project Description The objective of this project is to develop computational capabilities for massively parallel computers for modeling multifluid flow and transport in the subsurface on physical domains that contain complex geologic features and engineered structures. Of particular interest are preferential pathways, such as clastic dikes in the deep vadose zone at the Hanford Site, which potentially provide conduits for fluid and contaminate migration to the groundwater. Conventional methods for modeling complex geometries in the subsurface involve computing on unstructured grids using finite-element discretization of the mathematical equations that describe multifluid flow and transport through geologic media. In an attempt to maintain scalability and parallel computing efficiency, this project is directed at solving subsurface flow and transport problems using multiple grid blocks, where each grid block (sub-grid) is a curvilinear orthogonal structured grid. The critical issues are to develop parallel computing schemes that balance the computational load and minimize communications across the processors on a massively parallel computer. We have implemented capabilities for computing on curvilinear coordinate systems into a suite of subsurface flow and transport simulators and developed FORTRAN preprocessor (Rosing 1999) directives and interpreters for multi-block grids of structured blocks. When applied to environmental restoration and stewardship, the resulting software will provide a stronger scientific rationale for management decisions concerning the vadose zone, particularly at the Hanford Site, where preferential pathways and subsurface structures are critical issues. Introduction The vadose zone is defined as the hydrologic region that extends from the soil surface to the water table. Preferential pathways within the vadose zone include natural geologic structures (clastic dikes), engineered structures (monitoring wells and boreholes), and unstable multifluid systems (high density brines migrating through freshwater aquifers). Heterogeneous subsurface environments of particular concern to this project include geologic discontinuities (faults and embedded structures) and engineered structures (underground storage tanks). Accurate representations of the geologic structure, stratigraphy, and buried engineered structures are critical to numerically modeling subsurface flow and transport behavior. Scientists and engineers interested in assessing risks and devising remediation strategies for contaminants migrating through the vadose zone toward the groundwater need high performance analytical tools with capabilities for modeling subsurface complexities. Numerical models of subsurface flow and transport operate on tellesations of the physical domain, where hydrologic and thermodynamic properties are computed at discrete points (grid cells), as an approximation to the continuum of physical space. Analyses of contaminant migration through three-dimensional, field-scale domains requires the computational capacity of massively parallel computers. For example, to numerically model a cluster of six underground storage tanks, (typical of those on the Hanford Site, which are known to have leaked radioactive contaminants into the vadose zone) at 1-m resolution in three-dimensions, requires approximately 1 million grid cells. Depending on the assumptions taken to develop the conceptual model for the simulation, each grid cell can have between one and five unknowns which must be solved implicitly to resolve the system nonlinearities. Memory and execution-speed limitations make executing this scale of problem prohibitive on sequential computers. However, these types of problems have been successfully solved on a distributed-memory 512-processor IBM-SP parallel computer using 64 processors. Incorporating subsurface complexities into the computational domain by increasing the grid resolution within the region of the complexity (clastic dike, underground storage tank) can increase computational requirements beyond the range of Earth System Science 259
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Laboratory Directed Research and De
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Laboratory Directed Research and De
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Computational Science and Engineeri
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Policy and Management Sciences Asse
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Introduction Department of Energy O
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5. After reviews by the Technical a
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• The Technical Council peer revi
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methods applicable to combustion, s
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Summary Each national laboratory mu
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Study Control Number: PN0004/1411 A
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Table 1. Positive and negative ions
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m/z Arbitrary Units Figure 1. Mass
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introduce low-volatility compounds
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arrangement, but the charge is reta
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two liquid chromatographic gradient
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Integrated Microfabricated Devices
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Matrix Assisted Laser Desorption/Io
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Molecular Beam Synthesis and Charac
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temperature distribution of the des
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expected to result in significant a
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Study Control Number: PN99069/1397
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Seuss DT and KA Prather. 1999. “M
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Analysis of Receptor-Modulated Ion
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laboratory (Lu and Xie 1997; Lu et
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Automated DNA Fingerprinting Microa
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Comparison of 4 Xanthomonas Isolate
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Approach Hematopoietic (bone marrow
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Anti-Human lgG Human lgG Protein G
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Characterization of Global Gene Reg
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PCR products for immobilization on
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identify novel proteins of importan
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Immunoprecipitaton of tyrosinephosp
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Coupled NMR and Confocal Microscopy
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In the optical microscopy image, th
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Development and Applications of a M
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Figure 3. Hepa-1 cells undergoing a
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cellular processing (such as post-t
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8. Initial demonstration of an off-
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expression systems for several year
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accumulation of protein products, i
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Fungal Conversion of Agricultural W
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Fungal Conversion of Waste Glucose/
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Summary and Conclusions We demonstr
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are shown in Figure 1(a) and 1(b),
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Anchorage-Independent Growth (% con
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selection of seedlings demonstratin
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NMR-Based Structural Genomics Micha
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Solution-State Structure and Fold-C
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Plant Root Exudates and Microbial G
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Summary and Conclusions • The gre
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Jones-Oliveira JB, JS Oliveira, HE
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• securely moves files to a targe
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Plenary invited lecture, “The Ele
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Figure 1. X3DGEN tetrahedral mesh o
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Figure 5a. OSO volume rendering of
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Development of Models of Cell-Signa
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SOS p 23 EGFR Professor Rodland at
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Oliveira JS, JB Jones-Oliveira, and
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Figure 2. Associating a dataset mar
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to 1) incorporate three-dimensional
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shown in Figure 1. Simulated result
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HostBuilder: A Tool for the Combina
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Invariant Discretization Methods fo
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Graphics, Inc., workstation. The co
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Mixed Hamiltonian Methods for Geoch
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guyanaite, and grimaldiite (see Fig
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in the Environmental Molecular Scie
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Simulation and Modeling of Electroc
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Summary and Conclusions We implemen
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Since the implementation of the gen
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asis of previous performance, perce
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Bioinformatics for High-Throughput
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Summary and Conclusions In previous
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User Cat - Supervisor (client) Anal
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The second goal was to research way
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Figure 1. A visualization technique
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and interactions. The flexibility o
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Figure 4. A filtered version of Fig
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Development of Modeling Tools for J
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Figure 2. Schematic of experimental
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Integrated Modeling and Simulation
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(a) (b) (c) (d) Figure 1. Results o
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Thurman DA. August 2000. Collaborat
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MARC Input initial m esh and result
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(Johnson 1999; Colligan 1999; Gould
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Modeling of High-Velocity Forming f
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Global divergence error 1 10 -14 0
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that users were unlikely to appreci
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Earth System Science
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the lateral extent of the plume so
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Biogeochemical Processes and Microb
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Analyses of populations of viable a
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The first task was to establish fiv
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purged for 2 minutes. The gas sampl
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Page 226 and 227: Enhancing Emissions Pre-Processing
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Promising chemical durability, as m
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Study Control Number : PN98028/1274
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High Power Density Solid Oxide Fuel
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Hybrid Plasma Process for Vacuum De
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Matson DW, PM Martin, WD Bennett, J
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We showed the proof-of-principle ap
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Bandgap Energy (eV) 2.9 2.85 2.8 2.
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Ultrathin Electrolyte Test Results
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Detailed Investigations on Hydrogen
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identified low energy step structur
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Development of Novel Photo-Catalyst
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-2 -1 Energy (eV) 0 1 2 Cu2O SrTiO3
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Here, we perform adsorption and des
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exceed those in the all-metal devic
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Intensity (a.u.) 0 100 200 300 400
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integrated voltage (V) 0.10 0.08 0.
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The first step was to implement thi
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Spontaneous Formation of Cu2O Nano-
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Actinide Chemistry at the Aqueous-M
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Figure 5. Close-up atomic force mic
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to 300°C and 400°C. Unfortunately
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Summary and Conclusions Transmutati
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Advanced Calibration/Registration T
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Figure 1a. Violet filter Figure 1b.
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Autonomous Ultrasonic Probe for Pro
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containing nitrous oxide, an optica
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Chemical Detection Using Cavity Enh
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Figure 3 is a color rendered simula
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appropriate study has been performe
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Exploitation of Conventional Chemic
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Figures 3 and 4 illustrate the impa
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enefits of using a modified spread-
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Single Channel Signal 0.0025 0.0020
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Therefore, in order to extract the
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A next-generation technology is nee
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Wind Dir. Figure 2. Negative ion co
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Volumetric Imaging of Materials by
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amplitude and peak frequency change
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Figure 3. 13 C NMR spectrum of corn
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Approach Two flow loops, one that o
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Modification of Ion Exchange Resins
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Permanganate Treatment for the Deco
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minimized by medium exchange. After
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Figure 1. Thermogravimetric analysi
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Validation and Scale-Up of Monosacc
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Concentration (g/100g solution) Con
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Analysis of High-Volume, Hyper-Dime
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ecent figure of merit values. Shoul
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Probabilistic Methods Development f
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a) Traditional PCA-based process co
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Acronyms and Abbreviations 2-D two-
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