Search

The Interconnections Seam Study examines the potential economic value of increasing electricity transfer between the Eastern and Western Interconnections using high-voltage direct-current (HVDC) transmission and cost-optimizing both generation and transmission resources across the United States, proposing, assessing, justifying, and illustrating a major infrastructure change involving two of the world's largest power grids. The study conducted a multi-model analysis that used co-optimized generation and transmission expansion planning and production cost modeling. Four transmission designs under eight scenarios were developed and studied to estimate costs and potential benefits. The results show benefit-to-cost ratios that reach as high as 2.5, indicating significant value to increasing the transmission capacity between the interconnections under the cases considered, realized through sharing generation resources and flexibility across regions. [ABSTRACT FROM AUTHOR]

We refer to the national infrastructure necessary to provide electric energy in the U.S. as the National Electric Energy System (NEES). It includes the three primary energy production and transportation subsystems: electric, natural gas, and coal. In order to facilitate the study of very large-scale disruptions within the NEES, we have developed a multiperiod network flow model able to simulate the movements of bulk energy flows through the network and represent large-scale disruptions on critical infrastructure. This paper describes the model with focus on special features necessary to analyze large-scale disruptions. In order to validate our approach, we have collected disruption data following the 2005 Gulf-coast Hurricanes Katrina and Rita and then incorporated these data into the model. By comparing the results with and without the hurricanes, the additional operational costs as a result of them are estimated to be $10.5 billion from September to December 2005. [ABSTRACT FROM PUBLISHER]

Human life expectancy has risen in most developed countries over several decades, causing observed demographic shifts. Many researchers have developed models to determine the expectancy of life at birth. Yet due to the complexity of the real-world mortality data, and recent global economy impacts, there is a great demand to search for new models to accurately predict the life expectancy, especially in the United States. In this paper, we focus on the analysis of mortality rate in the United States over a period of six decades (data from 1946 to 2005) with considerations of the six most common distribution functions in the mortality area. These functions are: Gompertz, Gompertz-Makeham, logistic, log logistic, loglog, and Weibull. Given complex mortality data, we develop models including algorithms to compute the mortality measures such as mortality rate, and then select the best function for predicting the life expectancy in the United States. The modeling results include life expectancy at birth, life expectancy at each age, mortality rate, and forecasting models. We also discuss a new risk-cost function with respect to life expectancy, and determine the optimal threshold lifetime level that maximizes the expected risk cost. Numerical examples are given to illustrate the expected risk-cost results. The proposed risk-cost optimization model, and the optimal lifetime threshold value can help the policy-decision makers of related healthcare organizations including insurance companies to carefully perform the tradeoff between the cost and benefits. This approach can affect both short term and long term related healthcare policies and plans. The results show that the logistic distribution uniquely out performs other distributions based on the mean square error criterion. We find that on average the life expectancy at birth in the United States in 2005 for both sexes, males, and females are 84.0, 81.9, and 84.6 years, respectively. This new result shows that the true life expectancy on average in the U.S. is significantly larger than in existing reports. Life expectancy obviously changes as one will get older. By late adulthood, a person's chances of living longer increase as is reflected by the life expectancy function. For example, although the life expectancy from birth in the United States in 2005 is 84.0 years, those who live to age 65 will have an average of 20.4 additional years left to live, making their life expectancy almost 85.4 years. Similarly, those who live to age 75 will gain an additional few years, making their life expectancy almost 87.6 years. On average, a child who will be born in the US in 2015 can expect to live 85.5 years, and in 2025 a child born can expect to live nearly 87 years. [ABSTRACT FROM AUTHOR]

Software-driven hardware configurations account for the majority of modern safety-critical complex systems. The often costly failures of such systems can be attributed to software specific, hardware specific, or software/hardware interaction failures. The understanding of how failures propagate in such complex systems might provide critical information to designers, because, while a software component may not fail in terms of loss of function, a software operational state can cause an associated hardware failure. The least expensive phase of the product life cycle to address failures is during the design stage. This research presents a means to evaluate how a combined software/hardware system behaves and how such failures propagate to result in potential failures downstream, during the conceptual design stage. In particular, this paper proposes the use of high-level system modeling and model-based reasoning approaches to model failure propagation in combined software-hardware systems, introducing the Function-Failure Identification and Propagation (FFIP) analysis framework to help formalize the design of safety-critical systems. The fact that the hardware and software designers do not share the same background, knowledge, methods, or language contributes significantly to software/hardware interaction failures. A high-level systems analysis method, such as FFIP, is geared toward the unification of language and modeling concepts and may help to more seamlessly bridge such a gap. The technique is applied to the design of the Reaction Control System Jet Selection of the NASA space shuttle to evaluate failure propagation within the Reaction Control System Jet selection, specifically for the redundancy management system. The paper concludes with the extensions and mappings to the software domain that are required for a truly integrated methodology. [ABSTRACT FROM AUTHOR]

Innovation is seen today as an indispensable practice if an organization wishes to achieve competitive advantage and sustainable success in the marketplace. The development of new products and services and new technologies that enable those products and services seem to be the crown jewel of innovation. The management of these technologies, more specifically the process through which technologies are transferred, has been the focus of scholarly debates and studies for several decades. Currently, there are no quantitative, comprehensive, and easily applicable models in the literature that researchers and practitioners can use to assess organizations’ technology transfer capabilities. This article has sought to delineate important factors and perspectives applicable to technology transfer, and to use those in order to assess an organization's capabilities, through the application of a hierarchical decision modeling model to create a technology transfer score. The research model is applied to a utility company in the Pacific Northwest of the United States, and the results provide insights on how to measure and interpret technology transfer capabilities as well as a starting point for technology managers to improve those capabilities. [ABSTRACT FROM AUTHOR]

Previous analytical work [16], [17] on the resilience of P2P networks has been restricted to disconnection arising from simultaneous failure of all neighbors in routing tables of participating users. In this paper, we focus on a different technique for maintaining consistent graphs—Chord's successor sets and periodic stabilizations—under both static and dynamic node failure. We derive closed-form models for the probability that Chord remains connected under both types of node failure and show the effect of using different stabilization interval lengths (i.e., exponential, uniform, and constant) on the probability of partitioning in Chord. [ABSTRACT FROM AUTHOR]

Using the observed or desired stability results of each decision maker (DM) and the equilibrium of a conflict, an algorithm is proposed that determines whether the Nash, general metarationality, symmetric metarationality or sequential stability definition best explains the observations or how to achieve the desired equilibrium. The matrix representation of the graph model for conflict resolution, normally used to determine stabilities that reflect different models of human interaction in conflict, is utilized here to keep track of available one-step moves for each DM, as well as the DMs’ relative preferences among states. A key theorem involving matrix representation of graph models determines which stability types are consistent with the observations or achievement of the desired equilibrium, taking into account specified preferences of the DMs, for the case of two or more DMs. To illustrate the use of the algorithm in practice, behavioral analysis is applied to a softwood lumber dispute between Canada and the USA. [ABSTRACT FROM AUTHOR]