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At least 163 records · Page 9

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DOE OSTI2011

Gasification Studies Task 4 Topical Report, Utah Clean Coal Program

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2012

An approach for estimating the uncertainty in ParaDiS predictions

This report outlines an approach for computing the uncertainties in the predictions of computationally expensive models. While general, we use ParaDiS , a dislocation dynamics simulator originating in Lawrence Livermore National Laboratory, as the target application. ParaDiS is a mesoscale model, and uses submodels constructed/upscaled from microscale (molecular statics and dynamics) simulations. ParaDiS outputs, in turn, are upscaled and used in continuum (macroscale) simulations, e.g., those performed by ALE3D. This report addresses how one may quantify the uncertainties introduced by upscaling (both from microscale to mesoscale, and mesoscale to continuum), and the dependence of uncertainties in ParaDiS predictions on those of the inputs. This dependence is established via sensitivity analysis, and we address how this may be performed with a minimum of ParaDiS runs, given its immense computational cost. This includes constructing a smaller version of the model, sparse sampling of the parameter space, and exploiting the asymptotic nature of the time-evolution of the model outputs. The report concludes with a discussion of the computational resources required to perform this uncertainty quantification study.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Wind Tunnel Model of the Turner-Fairbank Highway Research Center Aerodynamics Laboratory [TFHRC Project Report]

The computational fluid dynamics (CFD) and computational structural mechanics (CSM) focus areas at Argonne’s Transportation Research and Analysis Computing Center (TRACC) initiated a project to support and compliment the experimental programs at the Turner-Fairbank Highway Research Center (TFHRC) with high performance computing based analysis capabilities in August 2010. The project was established with a new interagency agreement between the Department of Energy and the Department of Transportation to provide collaborative research, development, and benchmarking of advanced three-dimensional computational mechanics analysis methods to the aerodynamics and hydraulics laboratories at TFHRC for a period of five years, beginning in October 2010. The analysis methods employ well benchmarked and supported commercial computational mechanics software. Computational mechanics encompasses the areas of Computational Fluid Dynamics (CFD), Computational Wind Engineering (CWE), Computational Structural Mechanics (CSM), and Computational Multiphysics Mechanics (CMM) applied in Fluid-Structure Interaction (FSI) problems. This report documents one of the tasks in this project. In this task, a detailed CFD model of the wind tunnel laboratory at TFHRC was built and tested to provide a means to assess the air flow uniformity provided by the tunnel to the test zone and assess room geometry effects. Considerable effort went into the construction and testing of the model and various submodels, such as the screens in the wind tunnel. The model is available for use in further studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

Efficient uncertainty quantification methodologies for high-dimensional climate land models

In this report, we proposed, examined and implemented approaches for performing efficient uncertainty quantification (UQ) in climate land models. Specifically, we applied Bayesian compressive sensing framework to a polynomial chaos spectral expansions, enhanced it with an iterative algorithm of basis reduction, and investigated the results on test models as well as on the community land model (CLM). Furthermore, we discussed construction of efficient quadrature rules for forward propagation of uncertainties from high-dimensional, constrained input space to output quantities of interest. The work lays grounds for efficient forward UQ for high-dimensional, strongly non-linear and computationally costly climate models. Moreover, to investigate parameter inference approaches, we have applied two variants of the Markov chain Monte Carlo (MCMC) method to a soil moisture dynamics submodel of the CLM. The evaluation of these algorithms gave us a good foundation for further building out the Bayesian calibration framework towards the goal of robust component-wise calibration.

54 ENVIRONMENTAL 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↗

DOE OSTI2014

Gasification Studies: Task 4 Topical Report, Utah Clean Coal Program

A key objective of the Task 4 activities has been to develop simulation tools to support development, troubleshooting and optimization of pressurized entrained-flow coal gasifiers. The overall gasifier models (Subtask 4.1) combine submodels for fluid flow (Subtask 4.2) and heat transfer (Subtask 4.3) with fundamental understanding of the chemical processes (Subtask 4.4) processes that take place as coal particles are converted to synthesis gas and slag. However, it is important to be able to compare predictions from the models against data obtained from actual operating coal gasifiers, and Subtask 4.6 aims to provide an accessible, non-proprietary system, which can be operated over a wide range of conditions to provide well-characterized data for model validation. Highlights of this work include: (1) Verification and validation activities performed with the Arches coal gasification simulation tool on experimental data from the CANMET gasifier (Subtask 4.1). (2) The simulation of multiphase reacting flows with coal particles including detailed gas-phase chemistry calculations using an extension of the one-dimensional turbulence model’s capability (Subtask 4.2). (3) The demonstration and implementation of the Reverse Monte Carlo ray tracing (RMCRT) radiation algorithm in the ARCHES code (Subtask 4.3). (4) Determination of steam and CO 2 gasification kinetics of bituminous coal chars at high temperature and elevated pressure under entrained-flow conditions (Subtask 4.4). In addition, attempts were made to gain insight into the chemical structure differences between young and mature coal soot, but both NMR and TEM characterization efforts were hampered by the highly reacted nature of the soot. (5) The development, operation, and demonstration of in-situ gas phase measurements from the University of Utah’s pilot-scale entrained-flow coal gasifier (EFG) (Subtask 4.6). This subtask aimed at acquiring predictable, consistent performance and characterizing the environment within the gasifier.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2011

Modeling of Heat Transfer in Rooms in the Modelica "Buildings" Library

This paper describes the implementation of the room heat transfer model in the free open-source Modelica \Buildings" library. The model can be used as a single room or to compose a multizone building model. We discuss how the model is decomposed into submodels for the individual heat transfer phenomena. We also discuss the main physical assumptions. The room model can be parameterized to use different modeling assumptions, leading to linear or non-linear differential algebraic systems of equations. We present numerical experiments that show how these assumptions affect computing time and accuracy for selected cases of the ANSI/ASHRAE Standard 140- 2007 envelop validation tests.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Complete Evaluation of Available Laboratory-scale Data for the Independence Model

Year 1 Objectives (August 2016 – December 2016) – The original Independence model is a sequentially regressed set of parameters from numerous data sets in the Aspen Plus modeling framework. The immediate goal with the basic data model is to collect and evaluate those data sets relevant to the thermodynamic submodels (pure substance heat capacity, solvent mixture heat capacity, loaded solvent heat capacities, and volatility data). These data are informative for the thermodynamic parameters involved in both vapor-liquid equilibrium, and in the chemical equilibrium of the liquid phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Calibration and Propagation of Uncertainty for Independence

This document reports on progress and methods for the calibration and uncertainty quantification of the Independence model developed at UT Austin. The Independence model is an advanced thermodynamic and process model framework for piperazine solutions as a high-performance CO 2 capture solvent. Progress is presented in the framework of the CCSI standard basic data model inference framework. Recent work has largely focused on the thermodynamic submodels of Independence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Understanding Water and Thermal Management in Polymer-Electrolyte Fuel Cells

The Parties developed understanding of water and thermal management in fuel cells using a detailed 1-D model for the through-plane direction, a gas-channel relation model for the flow-channel direction, and a method to account for the rib/channel direction. The model simulates and predicts the water transport phenomena occurring within the fuel-cell sandwich, including the complex interplay among the various phases. This model enables optimum designs, operating conditions, and material properties for use in commercial PEFCs for automotive applications. In addition, novel advanced diagnostic methods and submodels were developed to determine the critical properties and model parameters and explore specific phenomena (e.g., ionomer thin films).

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2016

Lake Roosevelt White Sturgeon Modeling Support

This report contains summarized progress on the construction, validation, and calibration of a hydrodynamic and water temperature model, and individual-based sturgeon model, for the Transboundary Reach of the Columbia River and Lake Roosevelt. A 1-dimensional hydrodynamic and water temperature model, the Modular Aquatic Simulation System in 1-dimension (MASS1), was constructed using existing bathymetry data from the U.S.-Canada international border to Grand Coulee Dam, and validated using velocity, temperature, and water elevation data collected by staff of the CTCR during three distinct hydrodynamic periods occurring in early spring, late spring, and summer in the study area. Parameters of MASS1 were then calibrated so that model simulations matched empirical data of water surface elevations collected in 2016. Several years of MASS1 data were archived and are available for use with the sturgeon IBM: 1975–2001, 2004, 2005, 2007–2015, and April–August 2016. An individual-based simulation model was concomitantly constructed to simulate four of the early life stages of white sturgeon: spawning, embryo incubation, free embryos, and early larvae. Submodels for each of the four life stages contain mathematical algorithms that primarily describe the growth, development, and movement of individuals based on outputs from MASS1. Sturgeon simulations were then run for two historical years where limited recruitment may have occurred (1997 and 2011) and two years in which recruitment likely did not occur (2004 and 2005).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

The Unsteady Aerodynamics Module For FAST8

The new modularization framework of FAST v.8 (Jonkman 2013) was accompanied by a complete overhaul of the aerodynamics routines. AeroDyn is an aerodynamics module comprised of four submodels: rotor wake/induction, blade airfoil aerodynamics, tower influence on the blade nodes, and tower drag. Throughout the software overhaul, several improvements to the original theoretical treatments were achieved, including more accurate skewed-wake and unsteady airfoil aerodynamics, and the possibility of modeling highly flexible and curved blades. Under asymmetric conditions, such as wind shear, yawed, and tilted flow, the individual blade elements undergo variations in angle of attack that lead to unsteady aerodynamics phenomena, which can no longer be captured through the static airfoil lift and drag look-up tables. This document covers the main theory and the organization of the modularization framework of the new unsteady aerodynamics submodule (UAM)1, which includes unsteady aerodynamics under attached flow conditions and dynamic stall. The UAM can be called by either blade element momentum theory (only interface discussed in this report), or other future wake models (e.g., dynamic blade element momentum theory, or generalized dynamic wake).

17 WIND ENERGY↗

DOE OSTI2019

Development and Validation of Predictive Models for In-Cylinder Radiation and Wall Heat Transfer

The lack of accurate submodels for in-cylinder radiation and heat transfer has been identified as a key shortcoming in developing truly predictive, physics-based computational fluid dynamics (CFD) models that can be used to develop and design combustion systems for advanced high-efficiency, low-emissions engines. Measurements of wall boundary layers in engines show discrepancies of up to 100% with respect to standard CFD boundary layer models. And analysis of in-cylinder radiation based on the most recent spectral property databases and high-fidelity radiative transfer equation solvers has shown that at operating pressures and exhaust-gas recirculation levels typical of modern compression-ignition truck engines, molecular gas radiation (mainly carbon dioxide and water vapor) can be more important than soot particle radiation, and that a significant fraction of the emitted radiation (50% or more) can be reabsorbed before reaching the walls, thereby acting to redistribute energy in the combustion chamber. In this project, an integrated experimental and simulation approach has been used to generate new physical insight into in-cylinder heat-transfer processes in engines, and to develop computationally practicable CFD-based models that accurately represent the physics. New experimental data have been taken in an optically accessible single-cylinder research engine, and in a multi-cylinder production engine. Those data have provided new insight into the radiative environment in engines. New CFD models have been developed and validated for in-cylinder heat transfer, focusing mainly on radiative heat transfer and coupling between turbulent boundary layer wall heat transfer and radiative heat transfer. The CFD models have been developed and implemented in an open-source software framework that can be shared with other researchers. The models are compatible both with unsteady Reynolds-averaged Navier Stokes (URANS) formulations and with large-eddy simulations (LES) of in-cylinder processes in engines.

02 PETROLEUM↗

DOE OSTI2020

Development and Validation of Physics-Based Sub-Models of High-Pressure Supercritical Fuel Injection at Diesel Conditions Insert

The project sought to develop and validate accurate, physics-based, numerical submodels and implement them in computational fluid dynamics (CFD) software codes to enable accurate predictions of diesel sprays at pressures higher than the current systems. The combined experimental-computational effort has four main objectives: (1) acquire spatially and temporally resolved scalar measurements of fuel-oxidizer mixing in the near field of the fuel jet, (2) develop software modules to calculate thermo-physical properties of diesel surrogates and their mixtures with oxidizer of interest in real-gas operating regime, (3) integrate the real-fluid model into a commercial and an open-source CFD code to simulate fuel-air mixing in high-pressure diesel sprays, and (4) assess the robustness, accuracy, and uncertainty of the integrated CFD solvers in computing diesel sprays. Project accomplishments are consistent with the original goals of the project. Although we acquired spatially and temporally resolved scalar measurements, they were limited to refractive index difference and not to thermodynamic properties such as temperature and equivalence ratio. However, we successfully developed the theoretical background needed to acquire such measurements at diesel conditions and demonstrated the capability of the RSD for scalar measurements in a canonical turbulent jet flow replicating features of the diesel jet. Additional work will be needed to implement these procedures at high-pressure, high-temperature engine-like conditions of the CPFR. Mainly, we did not anticipate the need to find the liquid boundary and its statistical features or the state relationships between refractive index and thermodynamic properties, assuming the widely known Dale-Gladstone equation would suffice. Still, efforts devoted to these tasks were essential to fulfil the goals of the project and serves as the foundation on which many of the conclusions and key contributions of this project are based. Further assessment and application of the developed CFD codes is recommended to fully realize the benefits of this research.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Solar Field Layout and Aimpoint Strategy Optimization

The existing methods that determine heliostat aiming strategies for concentrating solar power (CSP) central receiver plants typically use heuristics and/or are computationally expensive, and they lack flexibility for different desired flux profiles and receiver geometries. Because of the interaction between layout and aimpoint strategy, considering the former without accounting for the latter may yield solutions with superfluous heliostats that cannot be used efficiently without compromising receiver flux constraints. To that end, we develop a software decision tool that uses innovative optimization methods to both optimize aimpoint strategies and improve candidate layouts for the solar collection field of a CSP central receiver plant. A CSP plant’s effectiveness relies on the optical efficiency of the solar field, which may be limited by losses due to (i) the cosine effect, (ii) atmospheric attenuation, (iii) interference (i.e., shading and blocking) between heliostats, (iv) spillage as a result of heliostat positioning and geometry, and (iv) some heliostats’ inability to direct irradiance to the receiver without damage due to excessive thermal flux. The goal of this work is to obtain optimized aiming strategies and improved solar field layouts that reduce capital cost and increase field optical efficiency and utilization, while meeting the power requirements of a given CSP receiver design. We formulate the aimpoint optimization problem as a mixed-integer linear programming model, which we then decompose into submodels that we solve in parallel. The decomposition subdivides the solar field into sections, and aimpoint strategies for each section are obtained independently of the others. To improve existing layouts, we develop a utilization-weighted efficiency metric that we use to relocate heliostats to sections of the solar field with similar efficiency and higher utilization. Finally, to connect our software to high-fidelity flux models, we develop a Python application programming interface for SolarPILOT, a mature software package that characterizes solar field performance and generates the heliostat layouts and flux maps that serve as input to our models.

14 SOLAR ENERGY↗

DOE OSTI2022

Model Package Report: Composite Analysis Solid Waste Release Model (CASWR Model)

This document describes the implementation of a solid waste form release model in GoldSim for the Hanford Site Composite Analysis (CA) Update. This Composite Analysis Solid Waste Release model (CASWR model) was designed to generate deterministic radionuclide release rates for Hanford’s Central Plateau solid waste disposal sites using single realizations of release model coefficients. Five generalized waste form types are used for the conceptual model of waste release: surplus reactor block, cement, soil-debris, grouted residual waste, and ancillary equipment. The surplus reactor block waste form consists of radionuclide leaching from surplus production graphite reactor core blocks via unspecified processes (White et al., 1984 as cited in PNNL-15965). The cement waste form represents solidified wastes whose permeability is much lower than that of the surrounding soil. The soil-debris waste form type is defined as unconsolidated waste mixed with soil material. Tanks and canyon complexes comprise the grouted residual waste form such that their solid waste will be grouted and capped with a surface barrier at the completion of their cleanup. Finally, the ancillary equipment waste form constitutes contaminant releases from ancillary and auxiliary waste form residues associated with tank farms at closure. Individual sub-models are implemented to numerically represent a respective waste form within the CASWR Model: Surplus Reactor Block Sub-model, Cement Sub-model, SoilDebris Sub-model, Grouted Residual Waste Sub-model, and Ancillary Equipment Submodel. Advection is assumed to be the primary transport process governing the release of radionuclides in the Ancillary Equipment and Soil-Debris Sub-models. Diffusion is assumed to be the primary release process in the Grouted Residual Waste and Cement Sub-models. An unspecified zero-order release process is considered in the Surplus Reactor Block Sub-model due to the lack of information regarding actual processes involved in irradiated graphite leaching. The Surplus Reactor Block, Cement, and SoilDebris Sub-models were compared against analytical solutions (PNNL-11800, Composite Analysis for Low-Level Waste Disposal in the 200 Area Plateau of the Hanford Site). The agreement between results of these analytical solutions and the corresponding waste form models verified their correct implementation in GoldSim. A 1-D modeling abstraction approach for the Grouted Residual Waste and Ancillary Equipment Sub-models was adopted from existing Performance Assessment (PA) models. Despite the simplifications made in these sub-models, they were found to be appropriate representations of the waste forms, similar to what was used in the Waste Management Area C PA model (RPP-ENV-58782, Performance Assessment of Waste Management Area C, Hanford Site, Washington, Rev. 0). A sensitivity analysis was conducted to identify the most influential parameters in each waste form sub-model. Suggestions for considering pH-dependent and redox-dependent release mechanisms are formulated through the development of a conditional constant approach in GoldSim.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Sequential Monte Carlo for Cut-Bayesian Posterior Computation

We propose a sequential Monte Carlo (SMC) method to efficiently and accurately compute cut-Bayesian posterior quantities of interest, variations of standard Bayesian approaches constructed primarily to account for model misspecification. We prove finite sample concentration bounds for estimators derived from the proposed method along with a linear tempering extension and apply these results to a realistic setting where a computer model is misspecified. We then illustrate the SMC method for inference in a modular chemical reactor example that includes submodels for reaction kinetics, turbulence, mass transfer, and diffusion. The samples obtained are commensurate with a direct-sampling approach that consists of running multiple Markov chains, with computational efficiency gains using the SMC method. Overall, the SMC method presented yields a novel, rigorous approach to computing with cut-Bayesian posterior distributions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

DECOVALEX-2023: Task F2-Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2-(salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗