Wind turbine system reliability is a critical factor in the success of a wind energy project. Poor reliability directly affects both the project's revenue stream through increased operation and maintenance (O&M) costs and reduced availability to generate power due to turbine downtime. Indirectly, the acceptance of wind-generated power by the financial and developer communities as a viable enterprise is influenced by the risk associated with the capital equipment reliability; increased risk, or at least the perception of increased risk, is generally accompanied by increased financing fees or interest rates. Cost of energy (COE) is a key project evaluation metric, both in commercial applications and in the U.S. federal wind energy program. To reflect this commercial reality, the wind energy research community has adopted COE as a decision-making and technology evaluation metric. The COE metric accounts for the effects of reliability through levelized replacement cost and unscheduled maintenance cost parameters. However, unlike the other cost contributors, such as initial capital investment and scheduled maintenance and operating expenses, costs associated with component failures are necessarily speculative. They are based on assumptions about the reliability of components that in many cases have not been operated for a complete life cycle. Due to the logistical and practical difficulty of replacing major components in a wind turbine, unanticipated failures (especially serial failures) can have a large impact on the economics of a project. The uncertainty associated with long-term component reliability has direct bearing on the confidence level associated with COE projections. In addition, wind turbine technology is evolving. New materials and designs are being incorporated in contemporary wind turbines with the ultimate goal of reducing weight, controlling loads, and improving energy capture. While the goal of these innovations is reduction in the COE, there is a potential impact on reliability whenever new technologies are introduced. While some of these innovations may ultimately improve reliability, in the short term, the technology risks and the perception of risk will increase. The COE metric used by researchers to evaluate technologies does not address this issue. This paper outlines the issues relevant to wind turbine reliability for wind turbine power generation projects. The first sections describe the current state of the industry, identify the cost elements associated with wind farm O&M and availability and discuss the causes of uncertainty in estimating wind turbine component reliability. The latter sections discuss the means for reducing O&M costs and propose O&M related research and development efforts that could be pursued by the wind energy research community to reduce COE.
This paper builds upon previous work [Sprigg and Ehlen, 2004] by introducing a bond market into a model of production and employment. The previous paper described an economy in which households choose whether to enter the labor and product markets based on wages and prices. Firms experiment with prices and employment levels to maximize their profits. We developed agent-based simulations using Aspen, a powerful economic modeling tool developed at Sandia, to demonstrate that multiple-firm economies converge toward the competitive equilibria typified by lower prices and higher output and employment, but also suffer from market noise stemming from consumer churn. In this paper we introduce a bond market as a mechanism for household savings. We simulate an economy of continuous overlapping generations in which each household grows older in the course of the simulation and continually revises its target level of savings according to a life-cycle hypothesis. Households can seek employment, earn income, purchase goods, and contribute to savings until they reach the mandatory retirement age; upon retirement households must draw from savings in order to purchase goods. This paper demonstrates the simultaneous convergence of product, labor, and savings markets to their calculated equilibria, and simulates how a disruption to a productive sector will create cascading effects in all markets. Subsequent work will use similar models to simulate how disruptions, such as terrorist attacks, would interplay with consumer confidence to affect financial markets and the broader economy.
The Hydrogen Futures Simulation Model (H{sub 2}Sim) is a high level, internally consistent, strategic tool for exploring the options of a hydrogen economy. Once the user understands how to use the basic functions, H{sub 2}Sim can be used to examine a wide variety of scenarios, such as testing different options for the hydrogen pathway, altering key assumptions regarding hydrogen production, storage, transportation, and end use costs, and determining the effectiveness of various options on carbon mitigation. This User's Guide explains how to run the model for the first time user.
In preparation for developing a Z-pinch IFE power plant, the interaction of ferritic steel with the coolant, FLiBe, must be explored. Sandia National Laboratories Fusion Technology Department was asked to drop molten ferritic steel and FLiBe in a vacuum system and determine the gas byproducts and ability to recycle the steel. We tried various methods of resistive heating of ferritic steel using available power supplies and easily obtained heaters. Although we could melt the steel, we could not cause a drop to fall. This report describes the various experiments that were performed and includes some suggestions and materials needed to be successful. Although the steel was easily melted, it was not possible to drip the molten steel into a FLiBe pool Levitation melting of the drop is likely to be more successful.
To establish strength criteria of Big Hill salt, a series of quasi-static triaxial compression tests have been completed. This report summarizes the test methods, set-up, relevant observations, and results. The triaxial compression tests established dilatant damage criteria for Big Hill salt in terms of stress invariants (I{sub 1} and J{sub 2}) and principal stresses ({sigma}{sub a,d} and {sigma}{sub 3}), respectively: {radical}J{sub 2}(psi) = 1746-1320.5 exp{sup -0.00034I{sub 1}(psi)}; {sigma}{sub a,d}(psi) = 2248 + 1.25 {sigma}{sub 3} (psi). For the confining pressure of 1,000 psi, the dilatant damage strength of Big Hill salt is identical to the typical salt strength ({radical}J{sub 2} = 0.27 I{sub 1}). However, for higher confining pressure, the typical strength criterion overestimates the damage strength of Big Hill salt.
Poly(ethylene oxide) (PEO) is the quintessential biocompatible polymer. Due to its ability to form hydrogen bonds, it is soluble in water, and yet is uncharged and relatively inert. It is being investigated for use in a wide range of biomedical and biotechnical applications, including the prevention of protein adhesion (biofouling), controlled drug delivery, and tissue scaffolds. PEO has also been proposed for use in novel polymer hydrogel nanocomposites with superior mechanical properties. However, the phase behavior of PEO in water is highly anomalous and is not addressed by current theories of polymer solutions. The effective interactions between PEO and water are very concentration dependent, unlike other polymer/solvent systems, due to water-water and water-PEO hydrogen bonds. An understanding of this anomalous behavior requires a careful examination of PEO liquids and solutions on the molecular level. We performed massively parallel molecular dynamics simulations and self-consistent Polymer Reference Interaction Site Model (PRISM) calculations on PEO liquids. We also initiated MD studies on PEO/water solutions with and without an applied electric field. This work is summarized in three parts devoted to: (1) A comparison of MD simulations, theory and experiment on PEO liquids; (2) The implementation of water potentials into the LAMMPS MD code; and (3) A theoretical analysis of the effect of an applied electric field on the phase diagram of polymer solutions.
A vegetation study was conducted in Technical Area 3 at Sandia National Laboratories, Albuquerque, New Mexico in 2003 to assist in the design and optimization of vegetative soil covers for hazardous, radioactive, and mixed waste landfills at Sandia National Laboratories/New Mexico and Kirtland Air Force Base. The objective of the study was to obtain site-specific, vegetative input parameters for the one-dimensional code UNSAT-H and to identify suitable, diverse native plant species for use on vegetative soil covers that will persist indefinitely as a climax ecological community with little or no maintenance. The identification and selection of appropriate native plant species is critical to the proper design and long-term performance of vegetative soil covers. Major emphasis was placed on the acquisition of representative, site-specific vegetation data. Vegetative input parameters measured in the field during this study include root depth, root length density, and percent bare area. Site-specific leaf area index was not obtained in the area because there was no suitable platform to measure leaf area during the 2003 growing season due to severe drought that has persisted in New Mexico since 1999. Regional LAI data was obtained from two unique desert biomes in New Mexico, Sevilletta Wildlife Refuge and Jornada Research Station.
A decomposition chemistry and heat transfer model to predict the response of removable epoxy foam (REF) exposed to fire-like heat fluxes is described. The epoxy foam was created using a perfluorohexane blowing agent with a surfactant. The model includes desorption of the blowing agent and surfactant, thermal degradation of the epoxy polymer, polymer fragment transport, and vapor-liquid equilibrium. An effective thermal conductivity model describes changes in thermal conductivity with reaction extent. Pressurization is modeled assuming: (1) no strain in the condensed-phase, (2) no resistance to gas-phase transport, (3) spatially uniform stress fields, and (4) no mass loss from the system due to venting. The model has been used to predict mass loss, pressure rise, and decomposition front locations for various small-scale and large-scale experiments performed by others. The framework of the model is suitable for polymeric foams with absorbed gases.
In the search for ''good'' parallel programming environments for Sandia's current and future parallel architectures, they revisit a long-standing open question. Can the PRAM parallel algorithms designed by theoretical computer scientists over the last two decades be implemented efficiently? This open question has co-existed with ongoing efforts in the HPC community to develop practical parallel programming models that can simultaneously provide ease of use, expressiveness, performance, and scalability. Unfortunately, no single model has met all these competing requirements. Here they propose a parallel programming environment, PRAM C, to bridge the gap between theory and practice. This is an attempt to provide an affirmative answer to the PRAM question, and to satisfy these competing practical requirements. This environment consists of a new thin runtime layer and an ANSI C extension. The C extension has two control constructs and one additional data type concept, ''shared''. This C extension should enable easy translation from PRAM algorithms to real parallel programs, much like the translation from sequential algorithms to C programs. The thin runtime layer bundles fine-grained communication requests into coarse-grained communication to be served by message-passing. Although the PRAM represents SIMD-style fine-grained parallelism, a stand-alone PRAM C environment can support both fine-grained and coarse-grained parallel programming in either a MIMD or SPMD style, interoperate with existing MPI libraries, and use existing hardware. The PRAM C model can also be integrated easily with existing models. Unlike related efforts proposing innovative hardware with the goal to realize the PRAM, ours can be a pure software solution with the purpose to provide a practical programming environment for existing parallel machines; it also has the potential to perform well on future parallel architectures.
A laser hazard analysis and safety assessment was performed for the LASIRISTM Model MAG-501L-670M-1000-45o-K diode laser associated with the High Resolution Pulse Scanner based on the ANSI Standard Z136.1-2000, American National Standard for the Safe Use of Lasers and the ANSI Standard Z136.6-2000, American National Standard for the Safe Use of Lasers Outdoors. The laser was evaluated for both indoor and outdoor use.
A particular engineering aspect of distributed sensor networks that has not received adequate attention is the system level hardware architecture of the individual nodes of the network. A novel hardware architecture based on an idea of task specific modular computing is proposed to provide for both the high flexibility and low power consumption required for distributed sensing solutions. The power consumption of the architecture is mathematically analyzed against a traditional approach, and guidelines are developed for application scenarios that would benefit from using this new design. Furthermore a method of decentralized control for the modular system is developed and analyzed. Finally, a few policies for power minimization in the decentralized system are proposed and analyzed.
The effect of polymer-polymer and solvent-polymer interactions on the behavior of the interdiffusion of a solvent in to an entangled polymer matrix was studied. The state of the polymer was changed from melt to glassy by varying polymer-polymer interaction. From simulation of equilibrated solvent-polymer solution, it was found that the glassy system with Berthelot's rule applied for the cross term is immiscible except in the dilute limit. Increasing the solvent-polymer interaction enhanced the solubility of the system without changing the nature of the diffusion process.
The high mobility of two dimensional electron system in the second Landau level was discussed. In the second level, the larger extent of the wave function as compared to the lowest LL and its additional zero allows for a much broader range of electron correlations to be favorable. An example of electron correlations encountered in the second LL is the even-denominator v=2+1/2 fractional quantum hall effect (FQHE) state. With a varying filling factor, it was observed that quantum liquids of different origins compete with several insulating phases leading to an irregular pattern in the transport parameters.
The Design through Analysis Realization Team (DART) will provide analysts with a complete toolset that reduces the time to create, generate, analyze, and manage the data generated in a computational analysis. The toolset will be both easy to learn and easy to use. The DART Roadmap Vision provides for progressive improvements that will reduce the Design through Analysis (DTA) cycle time by 90-percent over a three-year period while improving both the quality and accountability of the analyses.
We present a two-step approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only sparse distance constraints, such as those derived from chemical cross-linking, dipolar EPR and FRET experiments. In Step 1, using an algorithm, we developed, the conformational space of membrane protein folds matching a set of distance constraints is explored to provide initial structures for local conformational searches. In Step 2, these structures refined against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. We begin by describing the statistical analysis of the solved membrane protein structures from which the theoretical portion of the penalty function was derived. We then describe the penalty function, and, using a set of six test cases, demonstrate that it is capable of distinguishing helical bundles that are close to the native bundle from those that are far from the native bundle. Finally, using a set of only 27 distance constraints extracted from the literature, we show that our method successfully recovers the structure of dark-adapted rhodopsin to within 3.2 Å of the crystal structure.
This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence model, computation of bounds on distribution functions under a specified dependence model, formulation of parametric and empirical dependence models, and bounding approaches that can be used when information about the intervariable dependence is incomplete. The report also reviews several of the most pervasive and dangerous myths among risk analysts about dependence in probabilistic models.
A case study is reported to document the details of a validation process to assess the accuracy of a mathematical model to represent experiments involving thermal decomposition of polyurethane foam. The focus of the report is to work through a validation process. The process addresses the following activities. The intended application of mathematical model is discussed to better understand the pertinent parameter space. The parameter space of the validation experiments is mapped to the application parameter space. The mathematical models, computer code to solve the models and its (code) verification are presented. Experimental data from two activities are used to validate mathematical models. The first experiment assesses the chemistry model alone and the second experiment assesses the model of coupled chemistry, conduction, and enclosure radiation. The model results of both experimental activities are summarized and uncertainty of the model to represent each experimental activity is estimated. The comparison between the experiment data and model results is quantified with various metrics. After addressing these activities, an assessment of the process for the case study is given. Weaknesses in the process are discussed and lessons learned are summarized.
The sequential probability ratio test (SPRT) minimizes the expected number of observations to a decision and can solve problems in sequential pattern recognition. Some problems have dependencies between the observations, and Markov chains can model dependencies where the state occupancy probability is geometric. For a non-geometric process we show how to use the effective amount of independent information to modify the decision process, so that we can account for the remaining dependencies. Along with dependencies between observations, a successful system needs to handle the unknown class in unconstrained environments. For example, in an acoustic pattern recognition problem any sound source not belonging to the target set is in the unknown class. We show how to incorporate goodness of fit (GOF) classifiers into the Markov SPRT, and determine the worse case nontarget model. We also develop a multiclass Markov SPRT using the GOF concept.
Matching a set of 3D points to another set of 3D points is an important part of any 3D object recognition system. The Hausdorff distance is known for it robustness in the face of obscuration, clutter, and noise. We show how to approximate the 3D Hausdorff fraction with linear time complexity and quadratic space complexity. We empirically demonstrate that the approximation is very good when compared to actual Hausdorff distances.
A decomposition model has been developed to predict the response of removable syntactic foam (RSF) exposed to fire-like heat fluxes. RSF consists of glass micro-balloons (GMB) in a cured epoxy polymer matrix. A chemistry model is presented based on the chemical structure of the epoxy polymer, mass transport of polymer fragments to the bulk gas, and vapor-liquid equilibrium. Thermophysical properties were estimated from measurements. A bubble nucleation, growth, and coalescence model was used to describe changes in properties with the extent of reaction. Decomposition of a strand of syntactic foam exposed to high temperatures was simulated.
A coupled Euler-Lagrange solution approach is used to model the response of a buried reinforced concrete structure subjected to a close-in detonation of a high explosive charge. The coupling algorithm is discussed along with a set of benchmark calculations involving detonations in clay and sand.
Genetic programming (GP) has proved to be a highly versatile and useful tool for identifying relationships in data for which a more precise theoretical construct is unavailable. In this project, we use a GP search to develop trading strategies for agent based economic models. These strategies use stock prices and technical indicators, such as the moving average convergence/divergence and various exponentially weighted moving averages, to generate buy and sell signals. We analyze the effect of complexity constraints on the strategies as well as the relative performance of various indicators. We also present innovations in the classical genetic programming algorithm that appear to improve convergence for this problem. Technical strategies developed by our GP algorithm can be used to control the behavior of agents in economic simulation packages, such as ASPEN-D, adding variety to the current market fundamentals approach. The exploitation of arbitrage opportunities by technical analysts may help increase the efficiency of the simulated stock market, as it does in the real world. By improving the behavior of simulated stock markets, we can better estimate the effects of shocks to the economy due to terrorism or natural disasters.
The primary goals of the present study are to: (1) determine how and why MEMS-scale friction differs from friction on the macro-scale, and (2) to begin to develop a capability to perform finite element simulations of MEMS materials and components that accurately predicts response in the presence of adhesion and friction. Regarding the first goal, a newly developed nanotractor actuator was used to measure friction between molecular monolayer-coated, polysilicon surfaces. Amontons law does indeed apply over a wide range of forces. However, at low loads, which are of relevance to MEMS, there is an important adhesive contribution to the normal load that cannot be neglected. More importantly, we found that at short sliding distances, the concept of a coefficient of friction is not relevant; rather, one must invoke the notion of 'pre-sliding tangential deflections' (PSTD). Results of a simple 2-D model suggests that PSTD is a cascade of small-scale slips with a roughly constant number of contacts equilibrating the applied normal load. Regarding the second goal, an Adhesion Model and a Junction Model have been implemented in PRESTO, Sandia's transient dynamics, finite element code to enable asperity-level simulations. The Junction Model includes a tangential shear traction that opposes the relative tangential motion of contacting surfaces. An atomic force microscope (AFM)-based method was used to measure nano-scale, single asperity friction forces as a function of normal force. This data is used to determine Junction Model parameters. An illustrative simulation demonstrates the use of the Junction Model in conjunction with a mesh generated directly from an atomic force microscope (AFM) image to directly predict frictional response of a sliding asperity. Also with regards to the second goal, grid-level, homogenized models were studied. One would like to perform a finite element analysis of a MEMS component assuming nominally flat surfaces and to include the effect of roughness in such an analysis by using a homogenized contact and friction models. AFM measurements were made to determine statistical information on polysilicon surfaces with different roughnesses, and this data was used as input to a homogenized, multi-asperity contact model (the classical Greenwood and Williamson model). Extensions of the Greenwood and Williamson model are also discussed: one incorporates the effect of adhesion while the other modifies the theory so that it applies to the case of relatively few contacting asperities.
This report discusses a set of verification test cases for the frequency-domain, boundary-element, electromagnetics code Eiger based on the analytical solution of plane wave scattering from a sphere. Three cases will be considered: when the sphere is made of perfect electric conductor, when the sphere is made of lossless dielectric and when the sphere is made of lossy dielectric. We outline the procedures that must be followed in order to carefully compare the numerical solution to the analytical solution. We define an error criterion and demonstrate convergence behavior for both the analytical and numerical cases. These problems test the code's ability to calculate the surface current density and secondary quantities, such as near fields and far fields.
