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As the number of combined-cycle units increases, efficient modeling approaches for these units play important roles for independent system operators (ISOs). Based on various combinations of combustion turbines (CTs) and steam turbines (STs), the combined-cycle unit could work at different configurations (modes) with different efficiencies. In this paper, we propose an edge-based formulation for the combined-cycle units in the unit commitment problem to improve the accuracy and effectiveness of current modeling approaches. Our formulation can 1) clearly describe the transition processes among different configurations so as to satisfy the ISO financial offer submission requirements and (2) capture physical constraints of each turbine, including the exact min-up/down time and time dependent startup cost, in the combined-cycle units so as to increase the operational flexibility while ensuring system feasibility. This model fits well with the current U.S. deregulated electricity market. The final numerical studies show that our approaches perform better than the current configuration-based modeling approach. [ABSTRACT FROM AUTHOR]

The American automobile industry is facing substantial environmental and energy challenges driving the pursuit of alternative powertrain technologies—“The intervening mechanism by which power is transmitted from an engine to a propeller or axle that it drives,” which nominally includes engine, transmission, drive shafts, differentials, and the final drive. Emerging alternative fuel vehicles are showing their potential to address these challenges. However, diffusion of new technologies has many complications. This paper uses system dynamics modeling to investigate the impacts of individual and organizational parameters. This model embeds two traditional modeling methods for technology adoption, the Bass diffusion model and multinomial logit regression method. Five types of powertrain systems and three major stakeholders are considered. Mathematical relationships among different variables are elaborated. The qualitative impacts of government feebate, manufacturer willingness, and consumer purchasing preferences on economic and environmental issues are addressed using scenario analysis. [ABSTRACT FROM AUTHOR]

Many scholars suggest that visa restrictions push individuals who would have otherwise migrated legally toward illegal channels. This expectation is difficult to test empirically for three reasons. First, unauthorized migration is clandestine and often unobservable. Second, interpersonal ties between migrants and would-be migrants form a self-perpetuating system, which adapts in ways that are difficult to observe or predict. Third, empirical evaluations of immigration policy are vulnerable to endogeneity and other issues of causal inference. In this paper, we pair tailor-made empirical designs with an agent-based computational model (ABM) to capture the dynamics of a migration system that often elude empirical analysis, while grounding agent rules and characteristics with primary data collected in Jamaica, an origin country. We find that some government-imposed restrictions on migrants can deter total migration, but others are ineffective. Relative to a system of free movement, the minimal eligibility conditions required to classify migrants into visa categories alone make migration inaccessible for many. Restrictive policies imposed on student and high-skilled visa categories have little added effect because eligible individuals are likely able to migrate through alternative legal categories. Meanwhile, restrictions on family-based visas result in significant reductions in total migration. However, they also produce the largest reorientation toward unauthorized channels--an unintended consequence that even the highest rates of apprehension do not effectively eliminate. [ABSTRACT FROM AUTHOR]

The United States ITER Project Office (USIPO) is responsible for fabrication of the Central Solenoid (CS) for International Thermonuclear Experimental Reactor (ITER). The CS Insert (CSI) project should provide verification of the conductor performance in relevant conditions of temperature, field, currents and mechanical strain. The USIPO will build the CSI that will be tested at the Central Solenoid Model Coil (CSMC) Test Facility at JAEA, Naka, Japan. This paper presents three-dimensional mathematical model of CSI based on the design. Simulations were performed in order to verify structural integrity and compliance with the Japanese High Gas Pressure Safety Law. Numerical simulations lead to the design of the CSI that produced a required strain levels during operation on the superconductor cable, while simultaneously satisfy the ITER magnet structural design criteria. [ABSTRACT FROM PUBLISHER]

Cold-formed steel (CFS) framed construction has been widely adopted and used toward a modern, lightweight, and cost-efficient engineering practice across the United States. The primary objective of this work is to numerically assess the performance of CFS-framed shear walls sheathed with oriented strand board (OSB) and subjected to seismic events. A robust three-dimensional high-fidelity shell finite element model is developed and aims to provide a benchmark modeling approach able to accurately capture strength, stiffness, and failure mechanisms in these systems. Particular attention is given to the fundamental role of the connections between the CFS members and the OSB sheathing to the overall shear wall lateral response. To understand the variability in this critical connection, a series of 30 identical connection tests are performed. The robustness of the proposed computational model is validated by nine different CFS shear wall experimental studies and by a parametric analysis. The developed model is applied to provide an accurate experimentally-derived fastener-based computational tool of CFS-framed shear walls with potential use in design code expansion. [ABSTRACT FROM AUTHOR]

A computational model of political attitudes and beliefs is developed that incorporates contemporary psychological theory with well-documented findings from electoral behavior. We compare this model, John Q. Public (JQP), to a Bayesian learning model via computer simulations of observed changes in candidate evaluations over the 2000 presidential campaign. In these simulations, JQP reproduces responsiveness, persistence, and polarization of political attitudes, while the Bayesian learning model has difficulty accounting for persistence and polarization. We conclude that “motivated reasoning”—the discounting of information that challenges priors along with the uncritical acceptance of attitude-consistent information—is the reason our model can better account for persistence and polarization in candidate evaluations. [ABSTRACT FROM AUTHOR]

A growing body of research in political science has uncovered evidence of a ‘split personality’ among Americans when it comes to racial attitudes—people express different attitudes in public than they personally hold. At present no theoretical model can account for the emergence of this discrepancy. This article proposes a simple neural model of racial attitude formation that makes an important distinction between socially shared and idiosyncratic racial attitudes. A computational model based on Kimura's (1983) Neutral Theory of Evolution predicts that socially shared racist attitudes may be able to coexist with, and eventually be replaced by, more favorable idiosyncratic racial attitudes. Results of a laboratory-based study (N = 555) involving reaction-time-based implicit measures of socially shared and idiosyncratic attitudes are consistent with the predictions derived from the computational model. The implications of the theoretical model and the empirical findings are discussed. [ABSTRACT FROM AUTHOR]

Background: Local mosquito-borne Zika virus (ZIKV) transmission has been reported in two counties in the contiguous United States (US), prompting the issuance of travel, prevention, and testing guidance across the contiguous US. Large uncertainty, however, surrounds the quantification of the actual risk of ZIKV introduction and autochthonous transmission across different areas of the US.Methods: We present a framework for the projection of ZIKV autochthonous transmission in the contiguous US during the 2015-2016 epidemic using a data-driven stochastic and spatial epidemic model accounting for seasonal, environmental, and detailed population data. The model generates an ensemble of travel-related case counts and simulates their potential to have triggered local transmission at the individual level in the 2015-2016 ZIKV epidemic.Results: We estimate the risk of ZIKV introduction and local transmission at the county level and at the 0.025° × 0.025° cell level across the contiguous US. We provide a risk measure based on the probability of observing local transmission in a specific location during a ZIKV epidemic modeled after the epidemic observed during the years 2015-2016. The high spatial and temporal resolution of the model allows us to generate statistical estimates of the number of ZIKV introductions leading to local transmission in each location. We find that the risk was spatially heterogeneously distributed and concentrated in a few specific areas that account for less than 1% of the contiguous US population. Locations in Texas and Florida that have actually experienced local ZIKV transmission were among the places at highest risk according to our results. We also provide an analysis of the key determinants for local transmission and identify the key introduction routes and their contributions to ZIKV transmission in the contiguous US.Conclusions: This framework provides quantitative risk estimates, fully captures the stochasticity of ZIKV introduction events, and is not biased by the under-ascertainment of cases due to asymptomatic cases. It provides general information on key risk determinants and data with potential uses in defining public health recommendations and guidance about ZIKV risk in the US. [ABSTRACT FROM AUTHOR]