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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2011

Discretization error estimation and exact solution generation using the method of nearby problems.

The Method of Nearby Problems (MNP), a form of defect correction, is examined as a method for generating exact solutions to partial differential equations and as a discretization error estimator. For generating exact solutions, four-dimensional spline fitting procedures were developed and implemented into a MATLAB code for generating spline fits on structured domains with arbitrary levels of continuity between spline zones. For discretization error estimation, MNP/defect correction only requires a single additional numerical solution on the same grid (as compared to Richardson extrapolation which requires additional numerical solutions on systematically-refined grids). When used for error estimation, it was found that continuity between spline zones was not required. A number of cases were examined including 1D and 2D Burgers equation, the 2D compressible Euler equations, and the 2D incompressible Navier-Stokes equations. The discretization error estimation results compared favorably to Richardson extrapolation and had the advantage of only requiring a single grid to be generated.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

Investigations on Repository Near-Field Thermal Modeling - Repository Science/Thermal Load Management & Design Concepts (M41UF033302) (Rev.1)

The modeling tools generated in MathCAD, Excel, and MatLab were used to calculate the temperature evolution for combinations of waste form and geologic medium, assuming a particular emplacement layout for each concept (Sutton et al. 2011). Two types of spent nuclear fuel assemblies (SNFA) were considered, namely UOX from an open fuel cycle and MOX from a modified-­‐open fuel cycle. Four types of high level waste (HLW) canisters were considered, namely “co-­‐extraction” glass from a modified-­‐open fuel cycle and “new extraction” glass, electrochemical ceramic (EC-­‐C) and electrochemical metal (EC-­‐M) from a closed fuel cycle. While the “coextraction” process is similar in function to the industrial Co-­‐Extraction™ (COEX) process deployed by AREVA, the two processes assume different processing methods and steps and so the product and waste streams cannot be directly compared. Similar is true for the “new extraction” process documented in this report and the NUEX industrial process proposed by Energy Solutions, which also cannot be directly compared.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

C++ Tensor Toolbox User Manual (V.1.0)

The C++ Tensor Toolbox is a software package for computing tensor decompositions. It is based on the Matlab Tensor Toolbox, and is particularly optimized for sparse data sets. This user manual briefly overviews tensor decomposition mathematics, software capabilities, and installation of the package. Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis. The Tensor Toolbox provides classes for manipulating dense, sparse, and structured tensors in C++. The Toolbox compiles into libraries and is intended for use with custom applications written by users.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Final Progress Report: Internship at Los Alamos National Laboratory

Originally I was tasked fluidized bed modeling, however, I changed projects. While still working with ANSYS Fluent, I performed a study of particle tracks in glove boxes. This is useful from a Health-Physics perspective, dealing respirable particles that can be hazardous to the human body. I iteratively tested different amounts of turbulent particles in a steady-state flow. The goal of this testing was to discover how Fluent handles built-in Rosin-Rammler distributions for particle injections. I worked on the health physics flow problems and distribution analysis under the direction of two mentors, Bruce Letellier and Dave Decroix. I set up and ran particle injection calculations using Fluent. I tried different combinations of input parameters to produce sets of 500,000, 1 million, and 1.5 million particles to determine what a good test case would be for future experiments. I performed a variety of tasks in my work as an Undergraduate Student Intern at LANL this summer, and learned how to use a powerful CFD application in addition to expanding my skills in MATLAB. I enjoyed my work at LANL and hope to be able to use the experience here to further my career in the future working in a security-conscious environment. My mentors provided guidance and help with all of my projects and I am grateful for the opportunity to work at Los Alamos National Laboratory.

36 MATERIALS SCIENCE↗
DOE OSTI2012

A Comparison of Image Quality Evaluation Techniques for Transmission X-Ray Microscopy

Beamline 6-2c at Stanford Synchrotron Radiation Lightsource (SSRL) is capable of Transmission X-ray Microscopy (TXM) at 30 nm resolution. Raw images from the microscope must undergo extensive image processing before publication. Since typical data sets normally contain thousands of images, it is necessary to automate the image processing workflow as much as possible, particularly for the aligning and averaging of similar images. Currently we align images using the 'phase correlation' algorithm, which calculates the relative offset of two images by multiplying them in the frequency domain. For images containing high frequency noise, this algorithm will align noise with noise, resulting in a blurry average. To remedy this we multiply the images by a Gaussian function in the frequency domain, so that the algorithm ignores the high frequency noise while properly aligning the features of interest (FOI). The shape of the Gaussian is manually tuned by the user until the resulting average image is sharpest. To automatically optimize this process, it is necessary for the computer to evaluate the quality of the average image by quantifying its sharpness. In our research we explored two image sharpness metrics, the variance method and the frequency threshold method. The variance method uses the variance of the image as an indicator of sharpness while the frequency threshold method sums up the power in a specific frequency band. These metrics were tested on a variety of test images, containing both real and artificial noise. To apply these sharpness metrics, we designed and built a MATLAB graphical user interface (GUI) called 'Blur Master.' We found that it is possible for blurry images to have a large variance if they contain high amounts of noise. On the other hand, we found the frequency method to be quite reliable, although it is necessary to manually choose suitable limits for the frequency band. Further research must be performed to design an algorithm which automatically selects these parameters.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

Space Charge Correction on Emittance Measurement of Low Energy Electron Beams

The goal of any particle accelerator is to optimize the transport of a charged particle beam along a set path by confining the beam to a small region close to the design trajectory and directing it accurately along the beamline. To do so in the simplest fashion, accelerators use a system of magnets that exert approximately linear electromagnetic forces on the charged beam. These electromagnets bend the beam along the desired path, in the case of bending magnets, and constrain the beam to the desired area through alternating focusing and defocusing effects, in the case of quadrupole magnets. We can model the transport of such a beam through transfer matrices representing the actions of the various beamline elements. However, space charge effects, produced from self electric fields within the beam, defocus the beam and must be accounted for in the calculation of beam emittance. We present below the preliminary results of a MATLAB code built to model the transport of a charged particle beam through an accelerator and measure the emittance under the influence of space charge effects. We demonstrate the method of correctly calculating the emittance of a beam under space charge effects using a least square fit to determine the initial properties of the beam given the beam size measured at a specific point after transport.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

Graphite Oxidation Simulation in HTR Accident Conditions (3 rd Year and Final Technical Report)

Massive air and water ingress, following a pipe break or leak in steam-generator tubes, is a design-basis accident for high-temperature reactors (HTRs). Analysis of these accidents in both prismatic and pebble bed HTRs requires state-of-the-art capability for predictions of: 1) oxidation kinetics, 2) air helium gas mixture stratification and diffusion into the core following the depressurization, 3) transport of multi-species gas mixture, and 4) graphite corrosion. This project will develop a multi-dimensional, comprehensive oxidation kinetics model of graphite in HTRs, with diverse capabilities for handling different flow regimes. The chemical kinetics/multi-species transport model for graphite burning and oxidation will account for temperature-related changes in the properties of graphite, oxidants (O 2 , H 2 O, CO), reaction products (CO, CO 2 , H 2 , CH 4 ) and other gases in the mixture (He and N2). The model will treat the oxidation and corrosion of graphite in geometries representative of HTR core component at temperatures of 900°C or higher. The developed chemical reaction kinetics model will be user-friendly for coupling to full core analysis codes such as MELCOR and RELAP, as well as computational fluid dynamics (CFD) codes such as CD-adapco. The research team will solve governing equations for the multi-dimensional flow and the chemical reactions and kinetics using Simulink, an extension of the MATLAB solver, and will validate and benchmark the model's predictions using reported experimental data. Researchers will develop an interface to couple the validated model to a commercially available CFD fluid flow and thermal-hydraulic model of the reactor , and will perform a simulation of a pipe break in a prismatic core HTR, with the potential for future application to a pebble-bed type HTR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Unique Methodologies for Nano/Micro Manufacturing Job Training Via Desktop Supercomputer Modeling and Simulation

This project establishes an initiative in high speed (Teraflop)/large-memory desktop supercomputing for modeling and simulation of dynamic processes important for energy and industrial applications. It provides a training ground for employment of current students in an emerging field with skills necessary to access the large supercomputing systems now present at DOE laboratories. It also provides a foundation for NIU faculty to quantum leap beyond their current small cluster facilities. The funding extends faculty and student capability to a new level of analytic skills with concomitant publication avenues. The components of the Hewlett Packard computer obtained by the DOE funds create a hybrid combination of a Graphics Processing System (12 GPU/Teraflops) and a Beowulf CPU system (144 CPU), the first expandable via the NIU GAEA system to ~60 Teraflops integrated with a 720 CPU Beowulf system. The software is based on access to the NVIDIA/CUDA library and the ability through MATLAB multiple licenses to create additional local programs. A number of existing programs are being transferred to the CPU Beowulf Cluster. Since the expertise necessary to create the parallel processing applications has recently been obtained at NIU, this effort for software development is in an early stage. The educational program has been initiated via formal tutorials and classroom curricula designed for the coming year. Specifically, the cost focus was on hardware acquisitions and appointment of graduate students for a wide range of applications in engineering, physics and computer science.

Kimball, Clyde↗
DOE OSTI2012

Reprocessing plant scale model integration

The national laboratory complex contains a number of niche modeling capabilities for fuel cycle facilities, at different scales and utilizing a range of codes or modeling platforms. The goal of this work has been to integrate modeling capabilities for reprocessing plants to develop a plant scale model. The Separations and Safeguards Performance Model (SSPM), developed in Matlab Simulink, has been used as a base to integrate more detailed codes. In the past, both the AMUSE and SEPHIS solvent extraction codes were integrated into the SSPM to provide more realistic modeling of the separations in aqueous reprocessing plants. For this work, the AMUSE integration was expanded to include time dependence and more fully integrated for both UREX and TRUEX contactor banks. The Nitron code is a new continuous dissolver model which has been examined for integration in the SSPM as well. Finally, in order to improve the model run time, a parallel processing capability was added. The integration progress along with initial results from testing are presented.

Cipiti, Benjamin B.↗
DOE OSTI2012

Foundations of Feature Selection and Classification for Non-Gaussian Distributed Targets

This report describes the author’s research toward creating algorithms for selecting useful statistical features in pattern/target classification problems in which the features are non-Gaussian distributed. In engineering practice, it is common to either (1) Not perform any feature selection procedure, or (2) Use a feature selection algorithm that assumes the features are Gaussian distributed. This process can be far from optimal if the data are actually non-Gaussian, as they frequently are in practice. This research has the goal of mitigating that problem by creating a useful algorithm that can be used in practice. The approach is to focus on the performance indices used in common feature selection algorithms, such as Branch and Bound algorithms and the Sequential Forward Selection Algorithm. Ordinarily, the performance index used to measure the class separation in feature space involves assuming the data are Gaussian and deriving tractable performance indices that use closed form equations that represent the probability density functions of the class data. The advantage of this approach is that it produces feature selection algorithms that have low computational complexity and do not require knowledge of the actual data densities. The disadvantage is that these algorithms may not perform reasonably when the data are non-Gaussian, as they commonly are in practice. This research examines the use of information-theoretic class separability measures that can deal with the non-Gaussian case. In particular, this work shows that the Hellinger Distance (a divergence measure), has very desirable mathematical properties and can be useful for feature selection. The work in this paper employs a multivariate kernel density estimator along with the Hellinger Distance and an optimal subset selection algorithm to do feature selection. This report (1) Defines the classification and feature selection problems, (2) Describes the continuous variable Hellinger distance in one dimension and discusses its mathematical properties in comparison with other distance measures, (3) Develops the discrete variable Hellinger distance expression for one and two dimensions, and shows that the discrete Hellinger distance for multiple dimensions is a straightforward extension, and (4) Presents experimental density estimation results using a new MATLAB implementation of a multivariate kernel density estimator. The draft of this report served as a starting point for Ensign Matthew Wilder’s MSEE thesis work at the Naval Postgraduate School (NPS) in 2010 and 2011. Ensign Wilder completed his thesis and graduated from NPS in June 2011 (M. J. Wilder, “Automatic Target Recognition: Statistical Feature Selection of Non-Gaussian Distributed Target Classes,” MSEE Thesis, Naval Postgraduate School, Thesis Advisor: Grace A. Clark, Second Reader: Monique P. Fargues, June 2011). In the thesis, Ensign Wilder created implementations of the Branch and Bound and Sequential Feature Selection algorithms, extended the multivariate kernel density estimator code, and evaluated the performance of Hellinger Distance-based feature selection algorithms using both simulated data and data from a real-world benchmark data set. The new algorithm was shown to be very effective for both Gaussian and non-Gaussian data sets. The advantages gained for non-Gaussian data come at the cost of increased computational complexity. Using a laptop computer for practical problems, we generally use initial feature vectors containing no more than about ten or twelve features. Proposed future research lies in creating faster kernel density estimator algorithms that would allow for the use of higher dimensional data.

42 ENGINEERING↗
DOE OSTI2012

Modeling and Design of Integrated Safeguards and Security for an Electrochemical Reprocessing Facility

Electrochemical reprocessing of spent nuclear fuel may be an alternative to aqueous processing and is considered more attractive for fast reactor fuel cycles. Molten salt processing of the fuel may simplify the number of processing steps, but the nuclear industry worldwide has much less operational experience with this technology, including safeguards and security. As interest in electrochemical processing grows in the U.S. and other countries, it is important to understand how to address materials accountancy and security in this unique environment. For this work, a model of a commercial-scale electrochemical plant was developed in Matlab Simulink for design and analysis of integrated safeguards and security systems. The model tracks the mass flow rates of the fuel and salt through the various unit operations and simulates materials accountancy, process monitoring measurements, and physical protection. These measurements are then used to calculate inventory balances during normal operation and diversion scenarios. The model analysis enables one to identify various strategies and options for safeguarding nuclear material, contingent upon the feasibility of the measurement technology. This paper describes the model development, measurement options and strategies, and performance under diversion scenarios.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2012

Automated Thermal Image Processing for Detection and Classification of Birds and Bats (FY2012 Annual Report)

Surveying wildlife at risk from offshore wind energy development is difficult and expensive. Infrared video can be used to record birds and bats that pass through the camera view, but it is also time consuming and expensive to review video and determine what was recorded. We proposed to conduct algorithm and software development to identify and to differentiate thermally detected targets of interest that would allow automated processing of thermal image data to enumerate birds, bats, and insects. During FY2012 we developed computer code within MATLAB to identify objects recorded in video and extract attribute information that describes the objects recorded. We tested the efficiency of track identification using observer-based counts of tracks within segments of sample video. We examined object attributes, modeled the effects of random variability on attributes, and produced data smoothing techniques to limit random variation within attribute data. We also began drafting and testing methodology to identify objects recorded on video. We also recorded approximately 10 hours of infrared video of various marine birds, passerine birds, and bats near the Pacific Northwest National Laboratory (PNNL) Marine Sciences Laboratory (MSL) at Sequim, Washington. A total of 6 hours of bird video was captured overlooking Sequim Bay over a series of weeks. An additional 2 hours of video of birds was also captured during two weeks overlooking Dungeness Bay within the Strait of Juan de Fuca. Bats and passerine birds (swallows) were also recorded at dusk on the MSL campus during nine evenings. An observer noted the identity of objects viewed through the camera concurrently with recording. These video files will provide the information necessary to produce and test software developed during FY2013. The annotation will also form the basis for creation of a method to reliably identify recorded objects.

Bats↗
DOE OSTI2013

Developing Load Cell Monitoring on the Mock UF 6 Feed and Withdrawal System

A proof-of-concept load cell monitoring system has been developed for the Mock Feed and Withdrawal (F&W) System at Oak Ridge National Laboratory (ORNL). This system leverages industry-standard commercial off-the-shelf (COTS) hardware and software in a modular and scalable design. The Mock F&W System was designed to simulate operations at a uranium hexafluoride (UF 6 ) gas centrifuge enrichment plant F&W area. It provides a test bed for process-monitoring technologies. Water, used as a surrogate for UF 6 , is pumped from three feed tanks, through a process surge tank, and is then cut between two tails tanks and three product tanks. The weight of the each tank is continuously monitored using a load cell monitoring system. In addition to the F&W stations, large and small accountancy stations are monitored. The Mock F&W System allows ORNL to test and evaluate capabilities of industry-standard process monitoring hardware and software. A variety of commonly used weighing indicators are connected to the load cells to monitor the weight at each station. These weighing indicators are representative of the types likely found in operating facilities. A data center modeled after those currently used for international safeguards was installed to collect and manage the weight data. This data center provides a robust and flexible test bed for testing and developing software solutions. COTS software packages that leverage industry-standard communication protocols provide a data flow architecture that is modular, interoperable, and scalable. One software package provides communication drivers to collect the raw weight data from the weighing indicators. A data historian is used to store the raw data. Custom in-house algorithms have been developed using MATLAB to analyze the raw historical data and to automatically identify process information. This information includes the number of cycles completed and the mass of material transferred from stations to the process. The process information identified by the analysis is stored in a Microsoft SQL Server database. Visualization concepts have been developed that display the analyzed process information alongside visually compelling plots and animations of the raw data. The load cell monitoring system developed on the Mock F&W System was designed as a proof of concept that could be scaled to a field trial at an operating facility. This system, built with industry standard hardware and software, has allowed ORNL to develop capabilities that provide confidence in the ability to leverage existing operator load cell monitoring equipment with minimal impact on operations. The international safeguards community is evaluating the use of load cell monitoring as an additional safeguards measure; this system demonstrates a practical solution to collect, store, analyze, and visualize load cell weight data.

commercial off the shelf↗
DOE OSTI2013

User Interface Design and Development for the Enhanced Radiological Nuclear Inspection and Evaluation (ERNIE) Tool Internship Report

There are radioactive and nuclear threats that affect the security of the United States. The Enhanced Radiological Nuclear Inspection Evaluation project aims to develop better methods for finding these threats. The general user interface of ERNIE needs to efficiently and clearly display all the necessary information that is used to support the decision of the Customs and Border Patrol officers. The Vehicle Presence Sensors (VPS) are located in various entry points all around the nation to detect any nuclear or radiological threat. The main purpose of my job in the internship is to transform MATLAB code to Java, and to create and develop a general user interface (GUI) for ERNIE using Java as the main programming language. All the tasks will be performed in the Lawrence Livermore National Laboratory in Livermore, California.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Incorporating Cold Cap Behavior in a Joule-heated Waste Glass Melter Model

In this paper, an overview of Joule-heated waste glass melters used in the vitrification of high level waste (HLW) is presented, with a focus on the cold cap region. This region, in which feed-to-glass conversion reactions occur, is critical in determining the melting properties of any given glass melter. An existing 1D computer model of the cold cap, implemented in MATLAB, is described in detail. This model is a standalone model that calculates cold cap properties based on boundary conditions at the top and bottom of the cold cap. Efforts to couple this cold cap model with a 3D STAR-CCM+ model of a Joule-heated melter are then described. The coupling is being implemented in ModelCenter, a software integration tool. The ultimate goal of this model is to guide the specification of melter parameters that optimize glass quality and production rate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

GIS-and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development

The Colorado School of Mines (CSM) was awarded a grant by the National Energy Technology Laboratory (NETL), Department of Energy (DOE) to conduct a research project en- titled GIS- and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development in October of 2008. The ultimate goal of this research project is to develop a water resource geo-spatial infrastructure that serves as “baseline data” for creating solutions on water resource management and for supporting decisions making on oil shale resource development. The project came to the end on September 30, 2012. This final project report will report the key findings from the project activity, major accomplishments, and expected impacts of the research. At meantime, the gamma version (also known as Version 4.0) of the geodatabase as well as other various deliverables stored on digital storage media will be send to the program manager at NETL, DOE via express mail. The key findings from the project activity include the quantitative spatial and temporal distribution of the water resource throughout the Piceance Basin, water consumption with respect to oil shale production, and data gaps identified. Major accomplishments of this project include the creation of a relational geodatabase, automated data processing scripts (Matlab) for database link with surface water and geological model, ArcGIS Model for hydrogeologic data processing for groundwater model input, a 3D geological model, surface water/groundwater models, energy resource development systems model, as well as a web-based geo-spatial infrastructure for data exploration, visualization and dissemination. This research will have broad impacts of the devel- opment of the oil shale resources in the US. The geodatabase provides a “baseline” data for fur- ther study of the oil shale development and identification of further data collection needs. The 3D geological model provides better understanding through data interpolation and visualization techniques of the Piceance Basin structure spatial distribution of the oil shale resources. The sur- face water/groundwater models quantify the water shortage and better understanding the spatial distribution of the available water resources. The energy resource development systems model reveals the phase shift of water usage and the oil shale production, which will facilitate better planning for oil shale development. Detailed descriptions about the key findings from the project activity, major accomplishments, and expected impacts of the research will be given in the sec- tion of “ACCOMPLISHMENTS, RESULTS, AND DISCUSSION” of this report.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2013

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools as necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Application of Crunch-Flow Routines to Constrain Present and Past Carbon Fluxes at Gas-Hydrate Bearing Sites

In November 2012, Oregon State University initiated the project entitled: Application of Crunch-Flow routines to constrain present and past carbon fluxes at gas-hydrate bearing sites. Within this project we developed Crunch-Flow based modeling modules that include important biogeochemical processes that need to be considered in gas hydrate environments. Our modules were applied to quantify carbon cycling in present and past systems, using data collected during several DOE-supported drilling expeditions, which include the Cascadia margin in US, Ulleung Basin in South Korea, and several sites drilled offshore India on the Bay of Bengal and Andaman Sea. Specifically, we completed modeling efforts that: 1) Reproduce the compositional and isotopic profiles observed at the eight drilled sites in the Ulleung Basin that constrain and contrast the carbon cycling pathways at chimney (high methane flux) and non-chimney sites (low methane, advective systems); 2) Simulate the Ba record in the sediments to quantify the past dynamics of methane flux in the southern Hydrate Ridge, Cascadia margin; and 3) Provide quantitative estimates of the thickness of individual mass transport deposits (MTDs), time elapsed after the MTD event, rate of sulfate reduction in the MTD, and time required to reach a new steady state at several sites drilled in the Krishna-Godavari (K-G) Basin off India. In addition we developed a hybrid model scheme by coupling a home-made MATLAB code with CrunchFlow to address the methane transport and chloride enrichment at the Ulleung Basins chimney sites, and contributed the modeling component to a study focusing on pore-scale controls on gas hydrate distribution in sediments from the Andaman Sea. These efforts resulted in two manuscripts currently under review, and contributed the modeling component of another pare, also under review. Lessons learned from these efforts are the basis of a mini-workshop to be held at Oregon State University (Feb 2014) to instruct graduate students (OSU and UW) as well as DOE staff from the NETL lab in Albany on the use of Crunch Flow for geochemical applications.

03 NATURAL GAS↗