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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Magnetoencephalographic/Encephalographic (MEG/EEG) Brain-Computer Interface Driver for Interactive iOS Mobile Videogame Applications Utilizing the Hadoop Ecosystem, MongoDB, and Cassandra NoSQL Databases

In Phase I, we collected data on five subjects yielding over 90% positive performance in Magnetoencephalographic (MEG) mid-and post-movement activity. In addition, a driver was developed that substituted the actions of the Brain Computer Interface (BCI) as mouse button presses for real-time use in visual simulations. The process was interfaced to a flight visualization demonstration utilizing left or right brainwave thought movement, the user experiences, the aircraft turning in the chosen direction, or on iOS Mobile Warfighter Videogame application. The BCI’s data analytics of a subject’s MEG brain waves and flight visualization performance videogame analytics were stored and analyzed using the Hadoop Ecosystem as a quick retrieval data warehouse. In Phase II portion of the project involves the Emotiv Encephalographic (EEG) Wireless Brain–Computer interfaces (BCIs) allow for people to establish a novel communication channel between the human brain and a machine, in this case, an iOS Mobile Application(s). The EEG BCI utilizes advanced and novel machine learning algorithms, as well as the Spark Directed Acyclic Graph (DAG), Cassandra NoSQL database environment, and also the competitor NoSQL MongoDB database for housing BCI analytics of subject’s response and users’ intent illustrated for both MEG/EEG brainwave signal acquisition. The wireless EEG signals that were acquired from the OpenVibe and the Emotiv EPOC headset can be connected via Bluetooth to an iPhone utilizing a thin Client architecture. The use of NoSQL databases were chosen because of its schema-less architecture and Map Reduce computational paradigm algorithm for housing a user’s brain signals from each referencing sensor. Thus, in the near future, if multiple users are playing on an online network connection and an MEG/EEG sensor fails, or if the connection is lost from the smartphone and the webserver due to low battery power or failed data transmission, it will not nullify the NoSQL document-oriented (MongoDB) or column-oriented Cassandra databases. Additionally, NoSQL databases have fast querying and indexing methodologies, which are perfect for online game analytics and technology. In Phase II, we collected data on five MEG subjects, yielding over 90% positive performance on iOS Mobile Applications with Objective-C and C++, however on EEG signals utilized on three subjects with the Emotiv wireless headsets and (n < 10) subjects from the OpenVibe EEG database the Variational Bayesian Factor Analysis Algorithm (VBFA) yielded below 60% performance and we are currently pursuing extending the VBFA algorithm to work in the time-frequency domain referred to as VBFA-TF to enhance EEG performance in the near future. The novel usage of NoSQL databases, Cassandra and MongoDB, were the primary main enhancements of the BCI Phase II MEG/EEG brain signal data acquisition, queries, and rapid analytics, with MapReduce and Spark DAG demonstrating future implications for next generation biometric MEG/EEG NoSQL databases.

McClay, Wilbert↗
DOE OSTI2026

Reductions in wind farm main bearing rating lives resulting from wake impingement

This paper studies the impacts of wake impingement on main bearing rating lives predicted during the wind turbine design stage. A computational tool chain was developed to explore and quantify these effects across a wind farm populated by 10 MW wind turbines. Wind field and turbine load modelling was undertaken using the Dynamiks Python package, including application of a dynamic wake meandering model. The ISO 281 basic bearing rating life formulation was subsequently applied in order to evaluate impacts from wake effects. Analyses included a two-turbine parametric analysis, followed by a full wind farm analysis undertaken for the TotalControl 32-turbine reference wind farm, including full wind rose simulations across all operational wind speeds. Site conditions were accounted for using a Weibull wind speed distribution and a range of parametric wind direction rose models. Results indicate that wind farm main bearing rating lives are negatively impacted by the effects of wake impingement, resulting in rating life reductions for the analysed wind farm of the order of 16 % on average and as much as 20 %–25 %, both for the locating main bearing. Despite these high sensitivities, it is important to note that these resultant rating lives (i.e. the predicted lives) still far exceed the standard wind turbine operational lifetimes of 20–30 years. Wake impacts were also found to be asymmetrically related to the side on which the rotor is impinged, suggesting that, for the main bearing, there may be a “better” side for wake impingement to occur. Rating life sensitivities to wind rose shape were also observed. While these findings must be interpreted with due consideration for the various methodological limitations present, they provide compelling evidence that wake effects at the wind farm level should necessarily be included when undertaking main bearing operational load modelling, rating life assessment, or other load-related analyses.

17 WIND ENERGY↗
DOE OSTI2015

Better Buildings NW Ohio

When the Toledo Lucas County Port Authority (TLCPA) filed for the Department of Energy EECBG grant in late 2009, it was part of a strategic and Board backed objective to expand the organization’s economic development and financing programs into alternative energy and energy efficiency. This plan was filed with the knowledge and support of the areas key economic development agencies. The City of Toledo was also a key partner with the Mayor designating a committee to develop a Strategic Energy Policy for the City. This would later give rise to a Community Sustainability Strategic Plan for Toledo, Lucas County and the surrounding region with energy efficiency as a key pillar. When the TLCPA signed the grant documents with the DOE in June of 2010, the geographic area was severely distressed economically, in the early stages of a recovery from over a 30% drop in business activity and high unemployment. The TLCPA and its partners began identifying potential project areas well before the filing of the application, continuing to work diligently before the formal award and signing of the grant documents. Strong implementation and actions plans and business and financing models were developed and revised throughout the 3 year grant period with the long term goal of creating a sustainable program. The TLCPA and the City of Toledo demonstrated early leadership by forming the energy improvement district and evaluating buildings under their control including transportation infrastructure and logistics, government services buildings and buildings which housed several for profit and not for profit tenants while completing significant energy efficiency projects that created public awareness and confidence and solid examples of various technologies and energy savings. As was stated in the DOE Award Summary, the undertaking was focused as a commercial program delving into Alternative Energy Utility Districts; what are referred to in Ohio Statute as Energy Special Improvement Districts or ESIDs and what is nationally known as Property Assessed Clean Energy or PACE districts and PACE financing. The project methodology followed the identify, develop, implement, monitor and measure format. These districts began in Toledo and adjoining areas and are expanding to TLCPA’s 28 county financing agency geographic footprint. What began as the Toledo Ohio Advanced Energy Improvement Corporation is now doing business as the Northwest Ohio Advanced Energy Improvement District recognizing it expansion into creating and financing other districts in NW Ohio. The program has been sought out as an advisor by major communities and states in the process of developing similar legislation and programs and has become one of the largest most successful PACE energy improvement and financing districts in the US. The program and the energy district focused on transforming energy use, delivery, conservation and renewable energy as “options of first choice”. The significant energy savings paid for many of the improvements and created a financially viable program well beyond the grant period. The program has become a model within the State of Ohio and Nationally on how to implement and finance projects in broad energy districts including how to evolve and integrate several financing methodologies. It is a unique utilization of revolving loan funds and energy bond pooling with revenue backing primarily from energy improvement special assessments on commercial properties along with some power purchase agreement (PPA) and loan agreement revenue. The program has also incorporated Qualified Energy Conservation Bonds, State of Ohio Energy Loans (SEP), utility rebates, solar and renewable energy certificates, renewable tax incentives and grants, and owner funded equity as additional program leverage and funding. Other keys to this success have been a continual simplification and refinement of the application and documentation process to make funding available easily and quickly to building owners when they are prepared to commit to the project as well as act as a trusted facilitator and advisor to both building owners and other stakeholders. Taking a flexible and pragmatic approach to project evaluation and implementation that matches time and expense to the complexity of the project has been another key learning. To date the program has closed 3 energy bond issues through the TLCPA sponsored and managed NW Ohio Bond Fund totaling $16.54 million (of which $3.34 million were QECB qualified). The program has turned over its $3.0 million revolving loan fund twice as construction financing in advance of bond issuance and currently has issued $1.25 million in revolving term loans. The program has $1.66 million of remaining capacity for QECB qualified bonds. The program can issue an additional $13.46 million in energy bonds continuing to utilize its DOE EECBG loan loss reserves. In addition, the program has available $3.6 million of loan loss reserves from the State of Ohio, as an eligible Port Authority, that can back the issuance of an additional $7.2 to $14.4 million of energy bonds. This does not include additional bond capacity is available from the NW Ohio Bond Fund. The program is the master escrow agent for $18 million of loan loss reserves from the State of Ohio for eligible Port Authorities that can be utilized to assist the formation of energy districts and financing programs in major metropolitan areas and regions around the State of Ohio. Other leveraged funds now total $10 million; placing the total project value completed and financed at over $30 million. In addition that program has generated an active pipeline of projects in various stages that total $25 – $30 million.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Measuring alpha eigenvalue of a subcritical system by a intense pulsed neutron source

Intense-Pulsed-Neutron-Source (IPNS) technique is a new approach to measure the subcriticality of a reactor system, which has been theoretically analyzed by us while not been verified in experiment in other reference. In INPS technique the reactivity is derived via the system response to a prompt pulsed neutron source. The method utilizes very intense neutron pulses (about 1010 neutrons/pulse) with the duration ranging from 10 ns to 100 ns, which are generated by the dense plasma focus (DPF) device filled with pure DT mixture as the working gas. The neutron pulse in high intensity provides the opportunity to measure the signal using a scintillator and a photo-multiplier tube (PMT) (the intense pulse radiation measure method) with the flight distance of only twenty centimeters. The attenuation of the dense plasma focus device must be faster than the subcritical system so that the attenuation of the system can be researched. In this paper, after a neutron pulse is injected into the subcritical reactor, the subcriticality is determined by measuring the instantaneous characteristics of the leaking reactor neutron. The Monte Carlo analysis shows that, with the linear arrangement of the dense plasma focus, the subcritical system and the detector, the signal-to-noise ratio at the measure point meets the investigate requirement, in which the 14 MeV neutrons are attenuated by the subcritical system. The detector is close with the subcritical system to reduce the influence of the outer background and the spread of time-of-flight of the neutrons. The measure system utilizing gated detection technology is characterized with fast attenuation time and large linear current, the a value obtained with this method is 2.05 μs{sup -1} while the measurements using the {sup 252}Cf stochastic pulsed source method and the Rossi-a method were 2.18μs{sup -1} and 2.16μs{sup -1}.It showed that the measured result obtained with dense plasma focus instantaneous pulsed source is consistent with those obtained with the other two traditional methods. This new method utilized only a single-shot pulse to determine the a value of the reactor system. Therefore, this quick measure method is recommendable. The influence caused by energy response of the detector should been taken into account since the measured result reflects the time behavior of group particle. The influence is discussed preliminarily in this paper. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Lateral Gene Transfer in a Heavy Metal-Contaminated-Groundwater Microbial Community

ABSTRACT Unraveling the drivers controlling the response and adaptation of biological communities to environmental change, especially anthropogenic activities, is a central but poorly understood issue in ecology and evolution. Comparative genomics studies suggest that lateral gene transfer (LGT) is a major force driving microbial genome evolution, but its role in the evolution of microbial communities remains elusive. To delineate the importance of LGT in mediating the response of a groundwater microbial community to heavy metal contamination, representative Rhodanobacter reference genomes were sequenced and compared to shotgun metagenome sequences. 16S rRNA gene-based amplicon sequence analysis indicated that Rhodanobacter populations were highly abundant in contaminated wells with low pHs and high levels of nitrate and heavy metals but remained rare in the uncontaminated wells. Sequence comparisons revealed that multiple geochemically important genes, including genes encoding Fe 2+ /Pb 2+ permeases, most denitrification enzymes, and cytochrome c 553 , were native to Rhodanobacter and not subjected to LGT. In contrast, the Rhodanobacter pangenome contained a recombinational hot spot in which numerous metal resistance genes were subjected to LGT and/or duplication. In particular, Co 2+ /Zn 2+ /Cd 2+ efflux and mercuric resistance operon genes appeared to be highly mobile within Rhodanobacter populations. Evidence of multiple duplications of a mercuric resistance operon common to most Rhodanobacter strains was also observed. Collectively, our analyses indicated the importance of LGT during the evolution of groundwater microbial communities in response to heavy metal contamination, and a conceptual model was developed to display such adaptive evolutionary processes for explaining the extreme dominance of Rhodanobacter populations in the contaminated groundwater microbiome. IMPORTANCE Lateral gene transfer (LGT), along with positive selection and gene duplication, are the three main mechanisms that drive adaptive evolution of microbial genomes and communities, but their relative importance is unclear. Some recent studies suggested that LGT is a major adaptive mechanism for microbial populations in response to changing environments, and hence, it could also be critical in shaping microbial community structure. However, direct evidence of LGT and its rates in extant natural microbial communities in response to changing environments is still lacking. Our results presented in this study provide explicit evidence that LGT played a crucial role in driving the evolution of a groundwater microbial community in response to extreme heavy metal contamination. It appears that acquisition of genes critical for survival, growth, and reproduction via LGT is the most rapid and effective way to enable microorganisms and associated microbial communities to quickly adapt to abrupt harsh environmental stresses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Simplified predictive models for CO 2 sequestration performance assessment

CO2 sequestration in deep saline formations is increasingly being considered as a viable strategy for the mitigation of greenhouse gas emissions from anthropogenic sources. In this context, detailed numerical simulation based models are routinely used to understand key processes and parameters affecting pressure propagation and buoyant plume migration following CO2 injection into the subsurface. As these models are data and computation intensive, the development of computationally-efficient alternatives to conventional numerical simulators has become an active area of research. Such simplified models can be valuable assets during preliminary CO2 injection project screening, serve as a key element of probabilistic system assessment modeling tools, and assist regulators in quickly evaluating geological storage projects. We present three strategies for the development and validation of simplified modeling approaches for CO2 sequestration in deep saline formations: (1) simplified physics-based modeling, (2) statisticallearning based modeling, and (3) reduced-order method based modeling. In the first category, a set of full-physics compositional simulations is used to develop correlations for dimensionless injectivity as a function of the slope of the CO2 fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Furthermore, the dimensionless average pressure buildup after the onset of boundary effects can be correlated to dimensionless time, CO2 plume footprint, and storativity contrast between the reservoir and caprock. In the second category, statistical “proxy models” are developed using the simulation domain described previously with two approaches: (a) classical Box-Behnken experimental design with a quadratic response surface, and (b) maximin Latin Hypercube sampling (LHS) based design with a multidimensional kriging metamodel fit. For roughly the same number of simulations, the LHS-based metamodel yields a more robust predictive model, as verified by a k-fold cross-validation approach (with data split into training and test sets) as well by validation with an independent dataset. In the third category, a reduced-order modeling procedure is utilized that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) in order to represent system response at new control settings from a limited number of training runs. Significant savings in computational time are observed with reasonable accuracy from the PODTPWL reduced-order model for both vertical and horizontal well problems – which could be important in the context of history matching, uncertainty quantification and optimization problems. The simplified physics and statistical learning based models are also validated using an uncertainty analysis framework. Reference cumulative distribution functions of key model outcomes (i.e., plume radius and reservoir pressure buildup) generated using a 97-run full-physics simulation are successfully validated against the CDF from 10,000 sample probabilistic simulations using the simplified models. The main contribution of this research project is the development and validation of a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Transfer Factors for the FRMAC Assessment Manual and Turbo FRMAC to Improve Radiological Dose Assessment

The Turbo FRMAC analysis tool is used to perform complex calculations to quickly evaluate radiological consequences and aid in decision making during an emergency response by assessing impacts to the public, workers, and the food supply. Turbo FRMAC calculations are based on methods established by the Federal Radiological Monitoring and Assessment Center (FRMAC). To be able to assess impacts, input data called transfer factors that describe radionuclide uptake by local plants and animals are required. During the code application exercises in late 2016, identifying, finding, and validating nonstandard transfer factors proved to be time consuming and diverted the teams’ activity away from other critical tasks. As a result, a task was undertaken to dramatically expand the list of available transfer factors (food and non-food) and incorporate these factors into Turbo FRMAC. This will ultimately result in improved efficiency of the assessment team to perform calculations during times when the FRMAC is activated and provide more defensible, vetted data from which to calculate results. As a result of these and subsequent exercises, transfer factors were needed for the following items: bell peppers, Christmas tree, deer, flowers, fresh cucumbers, tomatoes, grapefruit, lichens, mushrooms, oranges, snap beans, squash, strawberries, sugarcane for sugar and seed, sweet corn, tea, tobacco, tree bark, and watermelon. To expand the applicability of the information tables, generic transfer data were also provided for common categories and recommendations were made for expanding the list of chemicals based on chemical similarity. The data presented in this report were compiled from recent literature with most of the data encompassing the period from 2000 to 2018. The following radionuclides were targeted during the literature search: elements associated with reactor accidents or nuclear detonations (Sr 89/90, Cs 134/137, Ce 141/144, Ru 103/106, I 129/131/133, Pu 238/239, Am 241, Zr 95, and Nb 95) and elements associated with industrial accidents or dirty bombs (Ir 192 and Co 60). Data from other elements were evaluated if they were identified during the literature search. In addition, reports were evaluated that were recommended by the research consultants. For each plant or animal transfer factor, the goal was to determine the geometric mean, the geometric standard deviation, the minimum, the maximum, and the number of measurements used. If only one measurement was available that was presented as the mean. Concentration ratios with large geometric standard deviations (GSDs) were generally the result of a paucity of measurements or a few disparate measurements. Measurement disparity was observed for data from different soil types. The geometric mean (GM) is a good reference value for planning and responses purposes, but the location-specific concentrations are unlikely to be similar to the model results. Recommendations for further work include: segregating the data to reflect the influence of soil type, developing approaches to incorporate animal data based on aggregated transfer measurements, and including data for foliar deposition on plants.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Integrated PET/MR breast cancer imaging: Attenuation correction and implementation of a 16-channel RF coil

Purpose: This study aims to develop, implement, and evaluate a 16-channel radiofrequency (RF) coil for integrated positron emission tomography/magnetic resonance (PET/MR) imaging of breast cancer. The RF coil is designed for optimized MR imaging performance and PET transparency and attenuation correction (AC) is applied for accurate PET quantification. Methods: A 16-channel breast array RF coil was designed for integrated PET/MR hybrid imaging of breast cancer lesions. The RF coil features a lightweight rigid design and is positioned with a spacer at a defined position on the patient table of an integrated PET/MR system. Attenuation correction is performed by generating and applying a dedicated 3D CT-based template attenuation map. Reposition accuracy of the RF coil on the system patient table while using the positioning frame was tested in repeated measurements using MR-visible markers. The MR, PET, and PET/MR imaging performances were systematically evaluated using modular breast phantoms. Attenuation correction of the RF coil was evaluated with difference measurements of the active breast phantoms filled with radiotracer in the PET detector with and without the RF coil in place, serving as a standard of reference measurement. The overall PET/MR imaging performance and PET quantification accuracy of the new 16-channel RF coil and its AC were then evaluated in first clinical examinations on ten patients with local breast cancer. Results: The RF breast array coil provides excellent signal-to-noise ratio and signal homogeneity across the volume of the breast phantoms in MR imaging and visualizes small structures in the phantoms down to 0.4 mm in plane. Difference measurements with PET revealed a global loss and thus attenuation of counts by 13% (mean value across the whole phantom volume) when the RF coil is placed in the PET detector. Local attenuation ranging from 0% in the middle of the phantoms up to 24% was detected in the peripheral regions of the phantoms at positions closer to attenuating hardware structures of the RF coil. The position accuracy of the RF coil on the patient table when using the positioning frame was determined well below 1 mm for all three spatial dimensions. This ensures perfect position match between the RF coil and its three-dimensional attenuation template during the PET data reconstruction process. When applying the CT-based AC of the RF coil, the global attenuation bias was mostly compensated to ±0.5% across the entire breast imaging volume. The patient study revealed high quality MR, PET, and combined PET/MR imaging of breast cancer. Quantitative activity measurements in all 11 breast cancer lesions of the ten patients resulted in increased mean difference values of SUV{sub max} 11.8% (minimum 3.2%; maximum 23.2%) between nonAC images and images when AC of the RF breast coil was applied. This supports the quantitative results of the phantom study as well as successful attenuation correction of the RF coil. Conclusions: A 16-channel breast RF coil was designed for optimized MR imaging performance and PET transparency and was successfully integrated with its dedicated attenuation correction template into a whole-body PET/MR system. Systematic PET/MR imaging evaluation with phantoms and an initial study on patients with breast cancer provided excellent MR and PET image quality and accurate PET quantification.

60 APPLIED LIFE SCIENCES↗
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↗