Performance-based optimization of structures: theory and applications

Performance-based Optimization of Structures introduces a method to bridge the gap between optimization theory and its practical applications to structural engineering. The performance-based optimization (PBO) method combines modern structural optimization theory with performance-based design concepts to produce a powerful technique for use in structural design. This book provides the latest PBO techniques for achieving optimal topologies and shapes of continuum structures with stress, displacement and mean compliance constraints. The emphasis is strongly placed on practical applications of automated PBO techniques to the strut-and-tie modeling of structural concrete, which includes reinforced and prestressed concrete structures. Basic concepts underlying the development of strut-and-tie models, design optimization procedure, and detailing of structural concrete are described in detail. The design optimization of lateral load resisting systems for multi-story steel and steel-concrete composite buildings is also presented. Numerous practical design examples are given which illustrate the nature of the load transfer mechanisms of structures

Sharp interface limit for a phase field model in structural optimization

We formulate a general shape and topology optimization problem in structural optimization by using a phase field approach. This problem is considered in view of well-posedness and we derive optimality conditions. We relate the diffuse interface problem to a perimeter penalized sharp interface shape optimization problem in the sense of $\Gamma$-convergence of the reduced objective functional. Additionally, convergence of the equations of the first variation can be shown. The limit equations can also be derived directly from the problem in the sharp interface setting. Numerical computations demonstrate that the approach can be applied for complex structural optimization problems

Determination of effective microscopic models for the frustrated antiferromagnets Cs2_2CuCl4_4 and Cs2_2CuBr4_4 by density functional methods

We investigate the electronic and magnetic properties of the frustrated triangular-lattice antiferromagnets Cs$_2$CuCl$_4$ and Cs$_2$CuBr$_4$ in the framework of density functional theory. Analysis of the exchange couplings J and J' using the available X-ray structural data corroborates the values obtained from experimental results for Cs$_2$CuBr$_4$ but not for Cs$_2$CuCl$_4$. In order to understand this discrepancy, we perform a detailed study of the effect of structural optimization on the exchange couplings of Cs$_2$CuCl$_4$ employing different exchange-correlation functionals. We find that the exchange couplings depend on rather subtle details of the structural optimization and that only when the insulating state (mediated through spin polarization) is present in the structural optimization, we do have good agreement between the calculated and the experimentally determined exchange couplings. Finally, we discuss the effect of interlayer couplings as well as longer-ranged couplings in both systems.Comment: Phys. Rev. B in pres

On a New Type of Information Processing for Efficient Management of Complex Systems

It is a challenge to manage complex systems efficiently without confronting NP-hard problems. To address the situation we suggest to use self-organization processes of prime integer relations for information processing. Self-organization processes of prime integer relations define correlation structures of a complex system and can be equivalently represented by transformations of two-dimensional geometrical patterns determining the dynamics of the system and revealing its structural complexity. Computational experiments raise the possibility of an optimality condition of complex systems presenting the structural complexity of a system as a key to its optimization. From this perspective the optimization of a system could be all about the control of the structural complexity of the system to make it consistent with the structural complexity of the problem. The experiments also indicate that the performance of a complex system may behave as a concave function of the structural complexity. Therefore, once the structural complexity could be controlled as a single entity, the optimization of a complex system would be potentially reduced to a one-dimensional concave optimization irrespective of the number of variables involved its description. This might open a way to a new type of information processing for efficient management of complex systems.Comment: 5 pages, 2 figures, to be presented at the International Conference on Complex Systems, Boston, October 28 - November 2, 200

The role of non-spherical double counting in DFT+DMFT: total energy and structural optimization of pnictide superconductors

A simple scheme for avoiding non-spherical double counting in the combination of density func- tional theory with dynamical mean-field theory (DFT+DMFT)is developed. It is applied to total- energy calculations and structural optimization of the pnictide superconductor LaFeAsO. The results are compared to a recently proposed "exact" double-counting formulation. Both schemes bring the optimized Fe-As interatomic distance close to the experimental value. This resolves the long stand- ing controversy between DFT+DMFT and experiment for the structural optimization of LaFeAsO.Comment: 4 pages 2 figure

Structural design optimization

Guest Editorial, Special Issue on Structural Design Optimization, Advances in Structural Engineering, An International Journal, 2007, Vol. 10, No.6

Optimization of structures on the basis of fracture mechanics and reliability criteria

Systematic summary of factors which are involved in optimization of given structural configuration is part of report resulting from study of analysis of objective function. Predicted reliability of performance of finished structure is sharply dependent upon results of coupon tests. Optimization analysis developed by study also involves expected cost of proof testing

Applications of artificial neural nets in structural mechanics

A brief introduction to the fundamental of Neural Nets is given, followed by two applications in structural optimization. In the first case, the feasibility of simulating with neural nets the many structural analyses performed during optimization iterations was studied. In the second case, the concept of using neural nets to capture design expertise was studied

Mol-CycleGAN - a generative model for molecular optimization

Designing a molecule with desired properties is one of the biggest challenges in drug development, as it requires optimization of chemical compound structures with respect to many complex properties. To augment the compound design process we introduce Mol-CycleGAN - a CycleGAN-based model that generates optimized compounds with high structural similarity to the original ones. Namely, given a molecule our model generates a structurally similar one with an optimized value of the considered property. We evaluate the performance of the model on selected optimization objectives related to structural properties (presence of halogen groups, number of aromatic rings) and to a physicochemical property (penalized logP). In the task of optimization of penalized logP of drug-like molecules our model significantly outperforms previous results