David W. Engel

Uncertainty in integrated assessment models: modeling with MiniCAM 1.0

Abstract Human-initiated climate change remains one of the major science-based public policy issues facing the nations of the world. One feature of the issue that inhibits effective decisions is the ubiquity of uncertainty: many if not most of the parameters of mathematical relationships that forecast emissions, atmospheric processes, impacts, and effectiveness of countermeasures are uncertain. We have added a stochastic simulation capability to the commonly used integrated assessment model MiniCAM 1.0 to analyze the sources of uncertainty and their relative importance and to help devise strategies for depicting and coping with uncertainty. The analysis shows that: (1) the projected range of uncertainty in global temperature increase during the next century is greater than previously supposed, but the central tendency is not dramatically higher; (2) many of the major sources of uncertainty previously discussed in the literature remain significant, but not all; (3) an adaptive policy of “act, then learn, then act” appears to offer better prospects for balancing uncertain costs and benefits of controlling greenhouse gas emissions than do rigid precautionary measures; and (4) current targets for atmospheric stabilization appear excessively ambitious.

Carbon Capture Simulation Initiative: A Case Study in Multiscale Modeling and New Challenges

Advanced multiscale modeling and simulation have the potential to dramatically reduce the time and cost to develop new carbon capture technologies. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry, and universities that is developing, demonstrating, and deploying a suite of such tools, including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamics (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk-analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.

An Uncertainty Quantification Framework for Studying the Effect of Spatial Heterogeneity in Reservoir Permeability on CO2 Sequestration

A new uncertainty quantification framework is adopted for carbon sequestration to evaluate the effect of spatial heterogeneity of reservoir permeability on CO2 migration. Sequential Gaussian simulation is used to generate multiple realizations of permeability fields with various spatial statistical attributes. In order to deal with the computational difficulties, the following ideas/approaches are integrated. First, different efficient sampling approaches (probabilistic collocation, quasi-Monte Carlo, and adaptive sampling) are used to reduce the number of forward calculations, explore effectively the parameter space, and quantify the input uncertainty. Second, a scalable numerical simulator, extreme-scale Subsurface Transport Over Multiple Phases, is adopted as the forward modeling simulator for CO2 migration. The framework has the capability to quantify input uncertainty, generate exploratory samples effectively, perform scalable numerical simulations, visualize output uncertainty, and evaluate input-output relationships. The framework is demonstrated with a given CO2 injection scenario in heterogeneous sandstone reservoirs. Results show that geostatistical parameters for permeability have different impacts on CO2 plume radius: the mean parameter has positive effects at the top layers, but affects the bottom layers negatively. The variance generally has a positive effect on the plume radius at all layers, particularly at middle layers, where the transport of CO2 is highly influenced by the subsurface heterogeneity structure. The anisotropy ratio has weak impacts on the plume radius, but affects the shape of the CO2 plume.

Survey and Evaluate Uncertainty Quantification Methodologies

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy 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, optimization, risk analysis and decision making capabilities. The CCSI Toolset will incorporate commercial and open-source software currently in use by industry and will also develop new software tools as necessary to fill technology gaps identified during execution of the project. 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. The goal of CCSI is to deliver a toolset that can simulate the scale-up of a broad set of new carbon capture technologies from laboratory scale to full commercial scale. To provide a framework around which the toolset can be developed and demonstrated, we will focus on three Industrial Challenge Problems (ICPs) related to carbon capture technologies relevant to U.S. pulverized coal (PC) power plants. Post combustion capture by solid sorbents is the technology focus of the initial ICP (referred to as ICP A). The goal of the uncertainty quantification (UQ) task (Task 6) is to provide a set of capabilities to the user community for the quantification of uncertainties associated with the carbon capture processes. As such, we will develop, as needed and beyond existing capabilities, a suite of robust and efficient computational tools for UQ to be integrated into a CCSI UQ software framework.

Risk Analysis and Decision Making FY 2013 Milestone Report

Risk analysis and decision making is one of the critical objectives of CCSI, which seeks to use information from science-based models with quantified uncertainty to inform decision makers who are making large capital investments. The goal of this task is to develop tools and capabilities to facilitate the development of risk models tailored for carbon capture technologies, quantify the uncertainty of model predictions, and estimate the technical and financial risks associated with the system. This effort aims to reduce costs by identifying smarter demonstrations, which could accelerate development and deployment of the technology by several years.

Release Data Package for Hanford Site Assessments

Beginning in fiscal year (FY) 2003, the U.S. Department of Energy (DOE) Richland Operations Office initiated activities, including the development of data packages, to support a Hanford assessment. This report describes the data compiled in FY 2003 through 2005 to support the Release Module of the System Assessment Capability (SAC) for the updated composite analysis. This work was completed as part of the Characterization of Systems Project, part of the Remediation and Closure Science Project, the Hanford Assessments Project, and the Characterization of Systems Project managed by Pacific Northwest National Laboratory. Related characterization activities and data packages for the vadose zone and groundwater are being developed under the remediation Decision Support Task of the Groundwater Remediation Project managed by Fluor Hanford, Inc. The Release Module applies release models to waste inventory data from the Inventory Module and accounts for site remediation activities as a function of time. The resulting releases to the vadose zone, expressed as time profiles of annual rates, become source terms for the Vadose Zone Module. Radioactive decay is accounted for in all inputs and outputs of the Release Module. The Release Module is implemented as the VADER (Vadose zone Environmental Release) computer code. Key components of the Release Module are numerical models (i.e., liquid, soil-debris, cement, saltcake, and reactor block) that simulate contaminant release from the different waste source types found at the Hanford Site. The Release Module also handles remediation transfers to onsite and offsite repositories.

User Instructions for the Systems Assessment Capability, Rev. 0, Computer Codes Volume 1: Inventory, Release, and Transport Modules

One activity of the Department of Energys Groundwater/Vadose Zone Integration Project is an assessment of cumulative impacts from Hanford Site wastes on the subsurface environment and the Columbia River. Through the application of a system assessment capability (SAC), decisions for each cleanup and disposal action will be able to take into account the composite effect of other cleanup and disposal actions. The SAC has developed a suite of computer programs to simulate the migration of contaminants (analytes) present on the Hanford Site and to assess the potential impacts of the analytes, including dose to humans, socio-cultural impacts, economic impacts, and ecological impacts. The general approach to handling uncertainty in the SAC computer codes is a Monte Carlo approach. Conceptually, one generates a value for every stochastic parameter in the code (the entire sequence of modules from inventory through transport and impacts) and then executes the simulation, obtaining an output value, or result. This document provides user instructions for the SAC codes that handle inventory tracking, release of contaminants to the environment, and transport of contaminants through the unsaturated zone, saturated zone, and the Columbia River.

Source-Term Comparison Using the Arest and Syvac-Vault Models: Effects of Decay-Chain In-Growth and Precipitation

A series of calculations of radionuclide release was performed with the AREST and SYVAC-Vault models (SVM) in order to assess concurrance. Specifically, the effects of precipitation and decay chain in-growth on the predicted release of nuclides from waste packages containing spent nuclear fuel were compared between each code. The results for maximum release rates generally agreed within a factor of 10. The differences in results can be explained based on the differences in geometry and boundary conditions between the two codes. Both codes showed nearly identical enhancement factors in release rates of uranium-series nuclides (U-238, U-234, Th-230, Ra-226) arising from the effect of decay-chain in-growth. Calculated enhancement factors in release rates for precipitation of a new uranium-bearing solid within the waste package were also in good agreement between AREST and SVM.

Hierarchical multi-scale approach to validation and uncertainty quantification of hyper-spectral image modeling

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

TRL Computer System User’s Guide

We have developed a wiki-based graphical user-interface system that implements our technology readiness level (TRL) uncertainty models. This document contains the instructions for using this wiki-based system.