Publications

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Uncertainty quantification in climate models is challenged by the sparsity of the available climate data due to the high computational cost of the model runs. Another feature that prevents classical uncertainty analyses from being easily applicable is the bifurcative behavior in the climate data with respect to certain parameters. A typical example is the Meridional Overturning Circulation in the Atlantic Ocean. The maximum overturning stream function exhibits discontinuity across a curve in the space of two uncertain parameters, namely climate sensitivity and CO2 forcing. We develop a methodology that performs uncertainty quantification in this context in the presence of limited data.

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This paper reviews the PVUSA power rating method [1-6] and presents two additional methods that seek to improve this method in terms of model precision and increased seasonal applicability. It presents the results of an evaluation of each method based upon regression analysis of over 12 MW of operating photovoltaic (PV) systems located in a wide variety of climates. These systems include a variety of PV technologies, mounting configurations, and array sizes to ensure the conclusions are applicable to a wide range of PV designs and technologies. The work presented in this paper will be submitted to ASTM for use in the development of a standard test method for certifying the power rating of PV projects. ©2009 IEEE.

We propose a method to automatically defeature a CAD model by detecting irrelevant features using a geometry-based size field and a method to remove the irrelevant features via facet-based operations on a discrete representation. A discrete B-Rep model is first created by obtaining a faceted representation of the CAD entities. The candidate facet entities are then marked for reduction by using a geometry-based size field. This is accomplished by estimating local mesh sizes based on geometric criteria. If the field value at a facet entity goes below a user specified threshold value then it is identified as an irrelevant feature and is marked for reduction. The reduction of marked facet entities is primarily performed using an edge collapse operator. Care is taken to retain a valid geometry and topology of the discrete model throughout the procedure. The original model is not altered as the defeaturing is performed on a separate discrete model. Associativity between the entities of the discrete model and that of original CAD model is maintained in order to decode the attributes and boundary conditions applied on the original CAD entities onto the mesh via the entities of the discrete model. Example models are presented to illustrate the effectiveness of the proposed approach.

This report summarizes the findings for phase one of the agent review and discusses the review methods and results. The phase one review identified a short list of agent systems that would prove most useful in the service architecture of an information management, analysis, and retrieval system. Reviewers evaluated open-source and commercial multi-agent systems and scored them based upon viability, uniqueness, ease of development, ease of deployment, and ease of integration with other products. Based on these criteria, reviewers identified the ten most appropriate systems. The report also mentions several systems that reviewers deemed noteworthy for the ideas they implement, even if those systems are not the best choices for information management purposes.

The Alternative Liquid Fuels Simulation Model (AltSim) is a high-level dynamic simulation model which calculates and compares the production and end use costs, greenhouse gas emissions, and energy balances of several alternative liquid transportation fuels. These fuels include: corn ethanol, cellulosic ethanol from various feedstocks (switchgrass, corn stover, forest residue, and farmed trees), biodiesel, and diesels derived from natural gas (gas to liquid, or GTL), coal (coal to liquid, or CTL), and coal with biomass (CBTL). AltSim allows for comprehensive sensitivity analyses on capital costs, operation and maintenance costs, renewable and fossil fuel feedstock costs, feedstock conversion ratio, financial assumptions, tax credits, CO{sub 2} taxes, and plant capacity factor. This paper summarizes the structure and methodology of AltSim, presents results, and provides a detailed sensitivity analysis. The Energy Independence and Security Act (EISA) of 2007 sets a goal for the increased use of biofuels in the U.S., ultimately reaching 36 billion gallons by 2022. AltSim's base case assumes EPA projected feedstock costs in 2022 (EPA, 2009). For the base case assumptions, AltSim estimates per gallon production costs for the five ethanol feedstocks (corn, switchgrass, corn stover, forest residue, and farmed trees) of $1.86, $2.32, $2.45, $1.52, and $1.91, respectively. The projected production cost of biodiesel is $1.81/gallon. The estimates for CTL without biomass range from $1.36 to $2.22. With biomass, the estimated costs increase, ranging from $2.19 per gallon for the CTL option with 8% biomass to $2.79 per gallon for the CTL option with 30% biomass and carbon capture and sequestration. AltSim compares the greenhouse gas emissions (GHG) associated with both the production and consumption of the various fuels. EISA allows fuels emitting 20% less greenhouse gases (GHG) than conventional gasoline and diesels to qualify as renewable fuels. This allows several of the CBTL options to be included under the EISA mandate. The estimated GHG emissions associated with the production of gasoline and diesel are 19.80 and 18.40 kg of CO{sub 2} equivalent per MMBtu (kgCO{sub 2}e/MMBtu), respectively (NETL, 2008). The estimated emissions are significantly higher for several alternatives: ethanol from corn (70.6), GTL (51.9), and CTL without biomass or sequestration (123-161). Projected emissions for several other alternatives are lower; integrating biomass and sequestration in the CTL processes can even result in negative net emissions. For example, CTL with 30% biomass and 91.5% sequestration has estimated production emissions of -38 kgCO{sub 2}e/MMBtu. AltSim also estimates the projected well-to-wheel, or lifecycle, emissions from consuming each of the various fuels. Vehicles fueled with conventional diesel or gasoline and driven 12,500 miles per year emit 5.72-5.93 tons of CO{sub 2} equivalents per year (tCO{sub 2}e/yr). Those emissions are significantly higher for vehicles fueled with 100% ethanol from corn (8.03 tCO{sub 2}e/yr) or diesel from CTL without sequestration (10.86 to 12.85 tCO{sub 2}/yr). Emissions could be significantly lower for vehicles fueled with diesel from CBTL with various shares of biomass. For example, for CTL with 30% biomass and carbon sequestration, emissions would be 2.21 tCO{sub 2}e per year, or just 39% of the emissions for a vehicle fueled with conventional diesel. While the results presented above provide very specific estimates for each option, AltSim's true potential is as a tool for educating policy makers and for exploring 'what if?' type questions. For example, AltSim allows one to consider the affect of various levels of carbon taxes on the production cost estimates, as well as increased costs to the end user on an annual basis. Other sections of AltSim allow the user to understand the implications of various polices in terms of costs to the government or land use requirements. AltSim's structure allows the end user to explore each of these alternatives and understand the sensitivities implications associated with each assumption as well as the implications for bottom line economics, energy use, and greenhouse gas emissions.

The objective of this work is to perform an uncertainty quantification (UQ) and model validation analysis of simulations of tests in the cross-wind test facility (XTF) at Sandia National Laboratories. In these tests, a calorimeter was subjected to a fire and the thermal response was measured via thermocouples. The UQ and validation analysis pertains to the experimental and predicted thermal response of the calorimeter. The calculations were performed using Sierra/Fuego/Syrinx/Calore, an Advanced Simulation and Computing (ASC) code capable of predicting object thermal response to a fire environment. Based on the validation results at eight diversely representative TC locations on the calorimeter the predicted calorimeter temperatures effectively bound the experimental temperatures. This post-validates Sandia's first integrated use of fire modeling with thermal response modeling and associated uncertainty estimates in an abnormal-thermal QMU analysis.

This report summarizes the strategy and preparations for the first phase in the pressurized water reactor (PWR) ignition experimental program. During this phase, a single full length, prototypic 17×17 PWR fuel assembly will simulate a severe loss-of-coolant-accident in the spent fuel pool whereby the fuel is completely uncovered and heats up until ignition of the cladding occurs. Electrically resistive heaters with zircaloy cladding will substitute for the spent nuclear fuel. The assembly will be placed in a single pool cell with the outer wall well insulated. This boundary condition will imitate the situation of an assembly surrounded by assemblies of similar offload age.

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