Concrete is the world's most utilized material for production of the structural elements employed in civil construction. Due to its low tensile strength and brittle nature it is reinforced with steel bars forming ...
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Concrete is the world's most utilized material for production of the structural elements employed in civil construction. Due to its low tensile strength and brittle nature it is reinforced with steel bars forming the reinforced concrete (RC structure). linear elements of reinforced concrete are commonly employed in multi-story buildings, bridges, industrial sheds, among others. In this study an optimization algorithm is presented to define the amount of steel and its location within a concrete polygonal section subjected to biaxial bending with axial force, so that the amount of steel would be the minimum needed to resist the soliciting forces. Therefore, the project variables are: location, diameter and number of steel bars to be distributed within the concrete polygonal section. The sequential linear programming method is used to determine the optimized section. In this method, the non-linear problem of determining the resistance forces of the section in relation to the project variables is approximated by a sequence of linear problems, which would have its optimal point defined for each step using the Simplex method. Formulation validation is done through results of examples found in literature, and also by means of analytical solutions of simple problems, such as rectangular sections under axial force and moment in only one axis of symmetry. The results show the efficiency of the algorithm implemented in the optimized determination of the quantity and position of the bars of a given diameter in the polygonal section of reinforced concrete under biaxial bending with axial force.
This study investigates the optimal power flow (OPF) problem for distribution networks with the integration of distributed generation (DG). By considering the objectives of minimal line loss, minimal voltage deviation...
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This study investigates the optimal power flow (OPF) problem for distribution networks with the integration of distributed generation (DG). By considering the objectives of minimal line loss, minimal voltage deviation and maximum DG active power output, the proposed OPF formulation is a multi-object optimisation problem. Through normalisation of each objective function, the multi-objective optimisation is transformed to single-objective optimisation. To solve such a non-convex problem, the trust-region sequential quadratic programming (TRSQP) method is proposed, which iteratively approximates the OPF by a quadratic programming with the trust-region guidance. The TRSQP utilises the sensitivity analysis to approximate all the constraints with linear ones, which will reduce the optimisation scale. Active set method is utilised in TRSQP to solve quadratic programming sub-problem. Numerical tests on IEEE 33-, PG&E 69- and actual 292-, 588-, 1180-bus systems show the applicability of the proposed method, and comparisons with the primal–dual interior point method and sequential linear programming method are provided. The initialisation and convergence condition of the proposed method are also discussed. The computational result indicates that the proposed algorithm for DG control optimisation in distribution system is feasible and effective.
In this paper, we present a method for preventing numerical instabilities such as checkerboards, mesh-dependencies and local minima occurring in the topology optimization which is formulated by the homogenization desi...
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In this paper, we present a method for preventing numerical instabilities such as checkerboards, mesh-dependencies and local minima occurring in the topology optimization which is formulated by the homogenization design method and in which the SLP method is used as optimizer. In the present method, a function based on the concept of gravity (which we named "the gravity control function") is added to the objective function. The density distribution of the topology is concentrated by maximizing this function, and as a result, checkerboards and intermediate densities are eliminated. Some techniques are introduced in the optimization procedure for preventing the local minima. The validity of the present method is demonstrated by numerical examples of both the short cantilever beam and the MBB beam.
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