Abstract: We study chance-constrained problems in which the constraints involve the probability of a rare event. We discuss the relevance of such problems and show that the existing sampling-based algorithms cannot be applied directly in this case, since they require an impractical number of samples to yield reasonable solutions. We argue that importance sampling (IS) techniques, combined with a Sample Average Approximation (SAA) approach, can be effectively used in such situations, provided that variance can be reduced uniformly with respect to the decision variables. We give sufficient conditions to obtain such uniform variance reduction, and prove asymptotic convergence of the combined SAA-IS approach. As it often happens with IS techniques, the practical performance of the proposed approach relies on exploiting the structure of the problem under study; in our case, we work with a telecommunications problem with Bernoulli input distributions, and show how variance can be reduced uniformly over a suitable approximation of the feasibility set by choosing proper parameters for the IS distributions. Although some of the results are specific to this problem, we are able to draw general insights that can be useful for other classes of problems. We present numerical results to illustrate our findings.

Abstract: Experiments and modeling aimed at assessing the mechanical response of latex balloons in the inflation test are presented. To this end, the hyperelastic Yeoh material model is firstly characterized via tensile test and, then, used to numerically simulate via finite elements the stress-strain evolution during the inflation test. The numerical pressure-displacement curves are validated with those obtained experimentally. Moreover, this analysis is extended to a biomedical problem of an eyeball under glaucoma conditions.

Abstract: We present a transit equilibrium model in which boarding decisions are stochastic. The model incorporates congestion, reflected in higher waiting times at bus stops and increasing in-vehicle travel time. The stochastic behavior of passengers is introduced through a probability for passengers to choose boarding a specific bus of a certain service. The modeling approach generates a stochastic common-lines problem, in which every line has a chance to be chosen by each passenger. The formulation is a generalization of deterministic transit assignment models where passengers are assumed to travel according to shortest hyperpaths. We prove existence of equilibrium in the simplified case of parallel lines (stochastic common-lines problem) and provide a formulation for a more general network problem (stochastic transit equilibrium). The resulting waiting time and network load expressions are validated through simulation. An algorithm to solve the general stochastic transit equilibrium is proposed and applied to a sample network; the algorithm works well and generates consistent results when considering the stochastic nature of the decisions, which motivates the implementation of the methodology on a real-size network case as the next step of this research. (C) 2013 Elsevier Ltd. All rights reserved.

Abstract: We propose a stochastic methodology for risk assessment of a large earthquake when a long time has elapsed from the last large seismic event. We state an approximate probability distribution for the occurrence time of the next large earthquake, by knowing that the last large seismic event occurred a long time ago. We prove that, under reasonable conditions, such a distribution is exponential with a rate depending on the asymptotic slope of the cumulative intensity function corresponding to a nonhomogeneous Poisson process. As it is not possible to obtain an empirical cumulative distribution function of the waiting time for the next large earthquake, an estimator of its cumulative distribution function based on existing data is derived. We conduct a simulation study for detecting scenario in which the proposed methodology would perform well. Finally, a real-world data analysis is carried out to illustrate its potential applications, including a homogeneity test for the times between earthquakes.

Abstract: This article investigates the feasibility of achieving higher performance from ground-source heat-pumps (GSHP) in space heating mode through the use of solar thermal collectors. A novel simulation tool for solar-assisted ground-source heat-pumps (SGSHP) is presented with an analysis of the influence of solar collectors on the improvement of heat pump performance. Solar radiation and climate temperature data of 19 European cities were used to perform simulations of SGSHP and GSHP systems considering a typical residential house. Overall performance coefficients (COPsys) varied from northern to southern locations between 4.4 and 5.8 for SGSHP and between 4.3 and 5.1 for GSHP. Results show that solar collectors coupling has more impact on performance improvement in regions that benefit from higher irradiance. However, greater running cost savings are achieved in milder climate conditions. Both heat-pump systems are able to effectively contribute to carbon footprint reductions for residential buildings, especially in countries where fossil fuels are the primary source of electricity generation. SGSHP payback periods are found between 8.5 and 23 years from northern to southern localities, making such heating system an economic heating option. SGSHPs are best suited for high irradiance and cool climate locations such as the mountainous regions in southern Europe. (C) 2015 Elsevier Ltd. All rights reserved.

Abstract: Stereotypes is one of the most researched topics in social psychology. Within this context, negative self-stereotypes pose a particular challenge for theories. In the current work, we propose a model that suggests that negative self-stereotypes can theoretically be accounted for by the need to communicate in a social system made up by groups with unequal power. Because our theory is dynamic, probabilistic, and interactionist, we use a computational simulation technique to show that the proposed model is able to reproduce the phenomenon of interest, to provide novel accounts of related phenomena, and to suggest novel empirical predictions. We describe our computational model, our variables' dynamic behavior and interactions, and link our analyses to the literature on stereotypes and self-stereotypes, the stability of stereotypes (in particular, gender and racial stereotypes), the effects of power asymmetries, and the effects of intergroup contact.

Abstract: Assessing environmental risk is useful for preventing adverse effects on human health in highly polluted cities. We design a criterion for environmental monitoring based on an attribute control chart for the number of dangerous contaminant levels when the concentration to be monitored follows a Birnbaum-Saunders distribution. This distribution is being widely applied to environmental data. We provide a novel justification for its usage in environmental sciences. The control coefficient and the minimum inspection concentration for the designed criterion are determined to yield the specified in-control average run length, whereas the out-of-control case is obtained according to a shift in the target mean. A simulation study is conducted to evaluate the proposed criterion, which reports its performance to provide earlier alerts of out-of-control processes. An application with real-world environmental data is carried out to validate its coherence with what is reported by the health authority. Copyright (c) 2015 John Wiley & Sons, Ltd.

Abstract: The Birnbaum-Saunders distribution is receiving considerable attention due to its good properties. One of its extensions is the class of scale-mixture Birnbaum-Saunders (SBS) distributions, which shares its good properties, but it also has further properties. The autoregressive conditional duration models are the primary family used for analyzing high-frequency financial data. We propose a methodology based on SBS autoregressive conditional duration models, which includes in-sample inference, goodness-of-fit and out-of-sample forecast techniques. We carry out a Monte Carlo study to evaluate its performance and assess its practical usefulness with real-world data of financial transactions from the New York stock exchange. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: Univariate Birnbaum-Saunders models have been widely applied to fatigue studies. Calculation of fatigue life is of great importance in determining the reliability of materials. We propose and derive new multivariate generalized Birnbaum-Saunders regression models. We use the maximum likelihood method and the EM algorithm to estimate their parameters. We carry out a simulation study to evaluate the performance of the corresponding maximum likelihood estimators. We illustrate the new models with real-world multivariate fatigue data.

Abstract: This paper presents a thermal power plant retrofitting approach focused on improvements in the operational flexibility of existing combined cycle power plants dedicated to providing thermal energy for medium and low-temperature processes in copper mining facilities. The main motivation for this research was aimed at evaluating the operational flexibility of the electrical industry through sector coupling and its effect on solving the energy sector decarbonization issues. The research evaluates the advantages of hybridization systems for supporting the electrical and mining industries to better predict operations. The proposed approach is based on a dynamic simulation scheme that finds the optimal operating parameters of the combined heat and power (CHP) system, such as location, type, and arrangement of each component of the CHP system. The power plant dynamic simulation model was validated against data available in the literature; it was also characterized by real operational data of the San Isidro II power plant installed in Chile. Several alternatives for the cogeneration plant location, as well as the splitter system design, were investigated and then compared. A cogeneration plant design with two heating modules was selected based on the comparative study performed in this work and its CHP system was evaluated for a load reduction case study. The results were compared against a reference model. The proposed CHP system exhibited improved performance: a minimum of 15% of the exhaust gases are required to supply the thermal energy demand of the electrowinning process when a full load is considered. It was also found that an average decrease of 5% of the mechanical power at each steam turbine stage noted. Finally, the proposed CHP system's average thermodynamic efficiency is found to be 19% greater than the power plant average efficiency. Consequently, an average decrease of 32 500 tons of carbon dioxide emissions per year is predicted.