Anthropometric profile and upper-limbs strength of bull rider s competitors

A força de preensão manual tem sido relatada como determinante no desempenho de empunhadura em modalidades como lutas e escalada. Este estudo teve por propósito avaliar a aptidão de força isotônica máxima e de preensão manual em praticantes e não praticantes de montaria em touros, a fim de obter parâmetros de referência desta população. Foram avaliados 20 sujeitos em dois grupos, sendo 10 classificados como atletas de montaria e 10 não-atletas. A avaliação da força de preensão manual foi realizada em dinamômetro em posição convencional (DP) e específica (DE), com ambas as mãos (D e E). A força isotônica máxima foi determinada pelo teste de uma repetição máxima (1RM) e também foram obtidas medidas de circunferência dos segmentos, bem como a composição corporal por protocolo de dobras cutâneas. Os valores das variáveis foram comparados pelo teste-t (ρ ≤ 0,05) para dados independentes. As relações entre os valores de força e características antropométricas foram traçadas pelo coeficiente de Pearson. Os resultados para AMT em DPD (43.8±6.8 kgf), DPE (39.4±7.7 kgf), DED (44.9±5.6 kgf) e DEE (39.8±8.3 kgf) comparados aos apresentados por n-AMT em DPD (47.0±3.0 kgf), DPE (42.2±6.1 kgf), DED (49.2±1.5 kgf) e DEE (46.2±4.1 kgf) apresentaram diferenças apenas para DED e DEE. A força nos testes de 1RM (supino reto: 73.2±12.0 kg e 82.0±12.0 kg; rosca direta: 45.2±8.9 kg e 43.8±8.9 kg; tríceps pulley: 67.0±6.3 kg e 72.0±6.3 kg; e puxada posterior: 73.5±8.5 kg e 73.7±7.5 kg) não mostram diferenças entre os grupos. A influência sobre a dinamometria apresenta-se diferente entre os grupos, sendo relevante a força de flexão do cotovelo em AMT e a antropometria e força isotônica para n-AMT. Conclui-se que as características morfo-funcionais de membros superiores não demandam especificidade à montaria em touros.

Reactive power dispatch and planning using a non-linear branch-and-bound algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

HOW TO EFFICIEN TLY INCORPORATE FACTS DEVICES IN OPTIMAL ACTIVE POWER FLOW MODEL

This paper presents for the first time how to easily incorporate facts devices in an optimal active power flow model such that an efficient interior-point method may be applied. The optimal active power flow model is based on a network flow approach instead of the traditional nodal formulation that allows the use of an efficiently predictor-corrector interior point method speed up by sparsity exploitation. The mathematical equivalence between the network flow and the nodal models is addressed, as well as the computational advantages of the former considering the solution by interior point methods. The adequacy of the network flow model for representing facts devices is presented and illustrated on a small 5-bus system. The model was implemented using Matlab and its performance was evaluated with the 3,397-bus and 4,075-branch Brazilian power system which show the robustness and efficiency of the formulation proposed. The numerical results also indicate an efficient tool for optimal active power flow that is suitable for incorporating facts devices.

A Constructive Heuristic Algorithm for Distribution System Planning

A constructive heuristic algorithm (CHA) to solve distribution system planning (DSP) problem is presented. The DSP is a very complex mixed binary nonlinear programming problem. A CHA is aimed at obtaining an excellent quality solution for the DSP problem. However, a local improvement phase and a branching technique were implemented in the CHA to improve its solution. In each step of the CHA, a sensitivity index is used to add a circuit or a substation to the distribution system. This sensitivity index is obtained by solving the DSP problem considering the numbers of circuits and substations to be added as continuous variables (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an efficient nonlinear optimization solver. Results of two tests systems and one real distribution system are presented in this paper in order to show the ability of the proposed algorithm.

A Strategy to Solve the Multistage Transmission Expansion Planning Problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Imposing Radiality Constraints in Distribution System Optimization Problems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Efficient heuristic algorithm used for optimal capacitor placement in distribution systems

An efficient heuristic algorithm is presented in this work in order to solve the optimal capacitor placement problem in radial distribution systems. The proposal uses the solution from the mathematical model after relaxing the integrality of the discrete variables as a strategy to identify the most attractive bus to add capacitors to each step of the heuristic algorithm. The relaxed mathematical model is a nonlinear programming problem and is solved using a specialized interior point method, The algorithm still incorporates an additional strategy of local search that enables the finding of a group of quality solutions after small alterations in the optimization strategy. Proposed solution methodology has been implemented and tested in known electric systems getting a satisfactory outcome compared with metaheuristic methods.The tests carried out in electric systems known in specialized literature reveal the satisfactory outcome of the proposed algorithm compared with metaheuristic methods. (C) 2009 Elsevier Ltd. All rights reserved.

Artificial neural networks for load flow and external equivalents studies

In this paper an artificial neural network (ANN) based methodology is proposed for (a) solving the basic load flow, (b) solving the load flow considering the reactive power limits of generation (PV) buses, (c) determining a good quality load flow starting point for ill-conditioned systems, and (d) computing static external equivalent circuits. An analysis of the input data required as well as the ANN architecture is presented. A multilayer perceptron trained with the Levenberg-Marquardt second order method is used. The proposed methodology was tested with the IEEE 30- and 57-bus, and an ill-conditioned 11-bus system. Normal operating conditions (base case) and several contingency situations including different load and generation scenarios have been considered. Simulation results show the excellent performance of the ANN for solving problems (a)-(d). (C) 2010 Elsevier B.V. All rights reserved.

Parâmetros sanguíneos de cavalos alimentados com concentrados lipídicos submetidos a treinos aeróbicos montados

Avaliou-se o fornecimento de concentrados com baixo e alto teor de óleo de soja a cavalos atletas, submetidos a duas intensidades de treinos aeróbicos montados, sobre a resposta metabólica de parâmetros bioquímicos do sangue, de importância ao desempenho esportivo. Foram utilizados quatro cavalos, em delineamento experimental quadrado latino, com tratamentos em esquema fatorial 2x2 (duas inclusões de óleo de soja e duas rotinas de treinos aeróbicos). Os tratamentos foram compostos por teores de 5 e 15% de óleo de soja nos concentrados e duas intensidades de treinos montados por 40 e 60min, classificadas como aeróbicas. As amostras de sangue foram colhidas após o último treino de 40 ou 60min, de cada período experimental. Monitorou-se, após o exercício, os parâmetros bioquímicos, triglicerídeos (TG), colesterol total (CT), glicose (GLI) e lactato (LAC). Houve redução no teor TG (P<0,05) para cavalos consumindo 15% de óleo e treinados aerobicamente por 60 min., o CT elevou-se em função do aumento da inclusão de óleo (P<0,05), incremento LAC (P<0,05) em cavalos treinados por 60min., independente do nível de óleo ingerido (1,48mmol/L), bem como não se verificou efeito (P>0,05) dos tratamentos sobre GLI. Concluiu-se que, para cavalos atletas em atividade aeróbica, o oferecimento de concentrado com alto teor óleo de soja deve ser associado ao treino montado de maior intensidade.

A metaheuristic to solve the transmission expansion planning

In this letter, a genetic algorithm (GA) is applied to solve - the static and multistage transmission expansion planning (TEP) problem. The characteristics of the proposed GA to solve the TEP problem are presented. Results using some known systems show that the proposed GA solves a smaller number of linear programming problems in order to find the optimal solutions and obtains a better solution for the multistage TEP problem.

Transmission network expansion planning with security constraints

A mathematical model and a methodology to solve the transmission network expansion planning problem with security constraints are presented. The methodology allows one to find an optimal and reliable transmission network expansion plan using a DC model to represent the electrical network. The security (n-1) criterion is used. The model presented is solved using a genetic algorithm designed to solve the reliable expansion planning in an efficient way. The results obtained for several known systems from literature show the excellent performance of the proposed methodology. A comparative analysis of the results obtained with the proposed methodology is also presented.

Power system transmission network expansion planning using AC model

An optimisation technique to solve transmission network expansion planning problem, using the AC model, is presented. This is a very complex mixed integer nonlinear programming problem. A constructive heuristic algorithm aimed at obtaining an excellent quality solution for this problem is presented. An interior point method is employed to solve nonlinear programming problems during the solution steps of the algorithm. Results of the tests, carried out with three electrical energy systems, show the capabilities of the method and also the viability of using the AC model to solve the problem.

Transmission network expansion planning considering uncertainty in demand

This paper presents two mathematical models and one methodology to solve a transmission network expansion planning problem considering uncertainty in demand. The first model analyzed the uncertainty in the system as a whole; then, this model considers the uncertainty in the total demand of the power system. The second one analyzed the uncertainty in each load bus individually. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The models presented are solved using a specialized genetic algorithm. The results obtained for several known systems from literature show that cheaper plans can be found satisfying the uncertainty in demand.

Transmission-expansion planning using the DC model and nonlinear-programming technique

The paper presents a constructive heuristic algorithm (CHA) for solving directly the long-term transmission-network-expansion-planning (LTTNEP) problem using the DC model. The LTTNEP is a very complex mixed-integer nonlinear-programming problem and presents a combinatorial growth in the search space. The CHA is used to find a solution for the LTTNEP problem of good quality. A sensitivity index is used in each step of the CHA to add circuits to the system. This sensitivity index is obtained by solving the relaxed problem of LTTNEP, i.e. considering the number of circuits to be added as a continuous variable. The relaxed problem is a large and complex nonlinear-programming problem and was solved through the interior-point method (IPM). Tests were performed using Garver's system, the modified IEEE 24-Bus system and the Southern Brazilian reduced system. The results presented show the good performance of IPM inside the CHA.

Transmission system expansion planning by a branch-and-bound algorithm

A branch and bound (B& B) algorithm using the DC model, to solve the power system transmission expansion planning by incorporating the electrical losses in network modelling problem is presented. This is a mixed integer nonlinear programming (MINLP) problem, and in this approach, the so-called fathoming tests in the B&B algorithm were redefined and a nonlinear programming (NLP) problem is solved in each node of the B& B tree, using an interior-point method. Pseudocosts were used to manage the development of the B&B tree and to decrease its size and the processing time. There is no guarantee of convergence towards global optimisation for the MINLP problem. However, preliminary tests show that the algorithm easily converges towards the best-known solutions or to the optimal solutions for all the tested systems neglecting the electrical losses. When the electrical losses are taken into account, the solution obtained using the Garver system is better than the best one known in the literature.