Sustainable urban energy planning: The case study of a tropical city

The urbanization of modern societies has imposed to the planners and decision-makers a more precise attention to facts not considered before. Several aspects, such as the energy availability and the deleterious effect of pollution on the populations, must be considered in the policy decisions of cities urbanization. The current paradigm presents centralized power stations supplying a city, and a combination of technologies may compose the energy mix of a country, such as thermal power plants, hydroelectric plants, wind systems and solar-based systems, with their corresponding emission pattern. A goal programming multi-objective optimization model is presented for the electric expansion analysis of a tropical city, and also a case study for the city of Guaratinguetá, Brazil, considering a particular wind and solar radiation patterns established according to actual data and modeled via the time series analysis method. Scenarios are proposed and the results of single environmental objective, single economic objective and goal programming multi-objective modeling are discussed. The consequences of each dispatch decision, which considers pollutant emission exportation to the neighborhood or the need of supplementing electricity by purchasing it from the public electric power grid, are discussed. The results revealed energetic dispatch for the alternatives studied and the optimum environmental and economic solution was obtained. © 2012 Elsevier Ltd.

A hybrid multi-population genetic algorithm applied to solve the multi-level capacitated lot sizing problem with backlogging

The present paper proposes a new hybrid multi-population genetic algorithm (HMPGA) as an approach to solve the multi-level capacitated lot sizing problem with backlogging. This method combines a multi-population based metaheuristic using fix-and-optimize heuristic and mathematical programming techniques. A total of four test sets from the MULTILSB (Multi-Item Lot-Sizing with Backlogging) library are solved and the results are compared with those reached by two other methods recently published. The results have shown that HMPGA had a better performance for most of the test sets solved, specially when longer computing time is given. © 2012 Elsevier Ltd.

Anaerobic running capacity determined from the critical velocity model is not significantly associated with maximal accumulated oxygen deficit in army runners

Purpose: The aim of this study was to verify whether there is an association between anaerobic running capacity (ARC) values, estimated from two-parameter models, and maximal accumulated oxygen deficit (MAOD) in army runners. Methods: Eleven, trained, middle distance runners who are members of the armed forces were recruited for the study (20 ± 1 years). They performed a critical velocity test (CV) for ARC estimation using three mathematical models and an MAOD test, both tests were applied on a motorized treadmill. Results: The MAOD was 61.6 ± 5.2 mL/kg (4.1 ± 0.3 L). The ARC values were 240.4 ± 18.6 m from the linear velocity-inverse time model, 254.0 ± 13.0 m from the linear distance-time model, and 275.2 ± 9.1 m from the hyperbolic time-velocity relationship (nonlinear 2-parameter model), whereas critical velocity values were 3.91 ± 0.07 m/s, 3.86 ± 0.08 m/s and 3.80 ± 0.09 m/s, respectively. There were differences (P < 0.05) for both the ARC and the CV values when compared between velocity-inverse time linear and nonlinear 2-parameter mathematical models. The different values of ARC did not significantly correlate with MAOD. Conclusion: In conclusion, estimated ARC did not correlate with MAOD, and should not be considered as an anaerobic measure of capacity for treadmill running. © 2013 Elsevier Masson SAS. All rights reserved.

Genetic variability for temperament indicators of Nellore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Control design applied to a non-ideal structural system with behavior chaotic

In this paper we study the behavior of a structure vulnerable to excessive vibrations caused by an non-ideal power source. To perform this study, the mathematical model is proposed, derive the equations of motion for a simple plane frame excited by an unbalanced rotating machine with limited power (non-ideal motor). The non-linear and non-ideal dynamics in system is demonstrated with a chaotic behavior. We use a State-Dependent Riccati Equation Control technique for regulate the chaotic behavior, in order to obtain a periodic orbit small and to decrease its amplitude. The simulation results show the identification by State-Dependent Riccati Equation Control is very effective. © 2013 Academic Publications, Ltd.

Damage detection in nonlinear structures using discrete-time volterra series

Structural damage identification is basically a nonlinear phenomenon; however, nonlinear procedures are not used currently in practical applications due to the complexity and difficulty for implementation of such techniques. Therefore, the development of techniques that consider the nonlinear behavior of structures for damage detection is a research of major importance since nonlinear dynamical effects can be erroneously treated as damage in the structure by classical metrics. This paper proposes the discrete-time Volterra series for modeling the nonlinear convolution between the input and output signals in a benchmark nonlinear system. The prediction error of the model in an unknown structural condition is compared with the values of the reference structure in healthy condition for evaluating the method of damage detection. Since the Volterra series separate the response of the system in linear and nonlinear contributions, these indexes are used to show the importance of considering the nonlinear behavior of the structure. The paper concludes pointing out the main advantages and drawbacks of this damage detection methodology. © (2013) Trans Tech Publications.

Produção de matéria seca da braquiária de acordo com os atributos químicos de um Latossolo em Selvíria, Mato Grosso do Sul

Rustic forages as the signal-grass are predominant in areas of Cerrado in extensive livestock systems that favor soil degradation. However, with time, not even these forages can have a good development in those areas. The objective of this study was to analyze the variability of plant and soil attributes; to define the linear and spatial correlations between signal-grass yield and the chemical attributes of the studied soil, and to evaluate, among the chemical attributes of the soil, which one that best explain the variability in this forage yield. The experiment was conducted in an area that had been under pasture for more than 30 years, belonging to UNESP - Ilha Solteira Campus, located in Selvíria - MS. A geostatistical grid was installed in an oxisol, for soil and plant data collection, with 121 sampling stations, consisted of eleven transections with 160 m width in the direction of the Cartesian axes. The dry mass yield of signal-grass was low, presenting high variation. The attributes MSr, N, PB, MO1, MO2, pHa1, pHa2, pHk1 and pHk2 did not vary at random. They presented data variability from low to high and followed clearly defined spatial patterns, ranging between 17.7-162.9 m. There was significant linear correlation at 1% between MSr and N leaf, and between MSr and PB. The cross semivariograms MSr=f(N) and MSr=f(PB) confirmed that the dry matter can be estimated from data of nitrogen leaf and crude protein content of this forage.

Estimativas da radiação global incidente em superfícies inclinadas com base na razáo de insolação

Estimating equations of global radiation based on the sunshine duration were proposed for horizontal surface and with inclination of 12.85, 22.85 and 32.85° facing the North in Botucatu, SP, Brazil, in monthly, seasonal and annual groupings of data. Simple linear correlations were applied (for definition of the linear and angular coefficients of Angstrom-Prescott model), in a database measured in all three inclinations in different periods (22.85°: 04/1998 to 07/2001; 12.85°: 08/2011 to 02/2003; and 32.85°: 03/2003 to 12/2007) concomitant with horizontal measures and sunshine duration. The statistical performance of the model was analysed by the means absolute error (MBE), the square root of the mean square error (RMSE) and the index adjustment (d). The minimum global radiation transmissivity varied from 14.35% in August (12.85°) to 27.86% in December (32.85°) and the maximum transmissivity ranged between 62.10% and 78.90%, for June (32.85°) and December (12.85°). Increasing the angle of inclination surface increased the scattering and decreased the index of adjustment and performance. The worst results were found for application of the seasonal and annual models in the months of autumn and winter for 32.85° (RMSE below 42.93% and adjustment superior to 0.4693).