Comparison between Newton and response-surface methods

A supporting-point placement scheme is presented that is used for calculating function derivatives by the method of differences as well as a quadratic response-surface approximation. The placement scheme unifies the Newton (NM) and response-surface (RSM) methods in the limiting case when the point-set distance parameter for the RSM is chosen as small as that for obtaining the derivatives needed by the NM. Two new RSM minimization strategies with and without line searches are presented. The numerical performance of the algorithms is studied by using well-known test functions and the paths through the two-dimensional variables space are plotted for easier interpretation of the performance results. The results are compared with results of numerical experiments found in the literatur

Evolutionary truss topology optimization using a graph-based parameterization concept

A novel parameterization concept for the optimization of truss structures by means of evolutionary algorithms is presented. The main idea is to represent truss structures as mathematical graphs and directly apply genetic operators, i.e., mutation and crossover, on them. For this purpose, new genetic graph operators are introduced, which are combined with graph algorithms, e.g., Cuthill-McKee reordering, to raise their efficiency. This parameterization concept allows for the concurrent optimization of topology, geometry, and sizing of the truss structures. Furthermore, it is absolutely independent from any kind of ground structure normally reducing the number of possible topologies and sometimes preventing innovative design solutions. A further advantage of this parameterization concept compared to traditional encoding of evolutionary algorithms is the possibility of handling individuals of variable size. Finally, the effectiveness of the concept is demonstrated by examining three numerical example

Development of CFRP racing motorcycle rims using a heuristic evolutionary algorithm approach

The scope of this paper is the application of evolutionary optimization methods to the development of composite fibre reinforced plastics (CFRP) racing motorcycle rims. The mass and the moment of inertia of a front and a rear CFRP rim are minimized subject to manufacturing, strength, and stiffness constraints. The stacking sequence of the composite laminates is optimized by applying a sophisticated parameterization concept making an excellent compromise between a huge variety of structure properties and a reasonable number of optimization parameters. The mechanical properties are simulated using the finite element analysis package ANSYS . Resulting displacement and Tsai-Wu index values are combined with the mass of the rim in order to assign a fitness value to each different design solution. The smart formulation of the fitness function allows the exploration of solutions close to the required strength and stiffness properties. The proprietary software DynOPS is utilized as an optimization engine. It links an evolutionary algorithm to arbitrary simulation programs and controls the entire optimization process. The sophisticated parameterization concept, together with the fitness function formulation, are the basis for the development of CFRP motorcycle rims decisively lighter than state-of-the-art magnesium alloy rim

A graph-based parameterization concept for global laminate optimization

A new graph-based parameterization concept aimed at the global optimization of laminated structures by the means of evolutionary algorithms and finite element analysis is introduced. The motivation to develop this novel parameterization concept is twofold. First, the entire design space is accessible to optimi zation down to the smallest entity, which is a single finite element, and secondly, this concept guarantees greatest flexibility in terms of laminate layer shape and placement. The finite element mesh of a structure is represented as a mathematical graph. Substructures of this graph form fiber reinforced and possibly overlapping patches and are affiliated to virtual graph vertices representing their properties. Adapted genetic variation operators are directly applied on this graph. The method allows for concurrent optimization of number, size, shape, and position of the patches and an arbitrary number of material related properties for each of them. The novel concept overcomes the limits of traditional geometry-based approaches, as it is able to represent almost arbitrary patch shapes even on curved surfaces. Two numerical examples demonstrate the efficiency of the metho

Experimental Determination of the Transversal and Longitudinal Fibre Bundle Permeability

In the resin transfer moulding process, fabrics are very often used as reinforcement. These fabrics consist of fibre bundles. In this context, both the permeability of the macroscopic fabric and the permeability of the fibre bundle are the key parameters to accurately predict the impregnation of the fabrics, the impregnation time and resulting void content. The fibre bundle permeability can be either predicted theoretically or experimentally. Whereas the theoretical determination lacks on accuracy as the realistic packing of the fibres in the bundles is not integrated in the models. In this work, we present an experimental setup to measure the longitudinal and transversal permeability of fibre bundles. The results are compared to model prediction

Complex-shaped beam element and graph-based optimization of compliant mechanisms

Compliant mechanisms are designed to be intentionally flexible, providing hingeless mechanisms. This work contributes a complex-shaped beam element formulation in conjunction with the ground structure approach. We identify compliant mechanism design solutions by using evolutionary topology optimization and increase flexibility by using a parametrization concept based on graph theory. The new operators for evolutionary optimization are also explained and sample problems are used to address the question of how our contribution increases design solutions spac

Concurrent design and flight mission optimization of morphing airborne wind energy wings

Morphing wings are expected to have transformative impact on future transportation and energy systems. To enable analysis and optimization of morphing wings, efficient numerical models are critically important. In this work, we present an accurate and tractable reduced-order model embedded in a genetic-algorithm-based optimization framework. The modeling and optimization framework allows concurrent aerostructural design and flight trajectory optimization of morphing wings considering complete flight missions. The approach is demonstrated on a camber-morphing wing airborne wind energy (AWE) system. The system’s power production capability is improved by enabling wing shape changes, and thus adaptation of the aerodynamic properties through morphing at different flight conditions and operating modes. The results of this study highlight the potential of the proposed modeling and optimization approach: 1) the power production capability of the investigated AWE system is improved by 46.0% compared to a sequentially optimized wing design; and 2) by exploiting camber morphing to adapt the aerodynamic properties of the wing at different flight conditions, the power production is further increased by 7.8%

High load carrying structures made from folded composite materials

Large design and manufacturing effort for high load carrying composite structures results from anisotropic material behavior, tedious curing or forming conditions as well as high sensitivity to manufacturing defects. Such challenges limit the design freedom and result in large cost and time effort. A novel design approach is proposed to realize load carrying structures based on the utilization of the outstanding flexibility of thin composite shells and the “complexity for free” approach of additive manufacturing. To this purpose, highly integrated structures are created by folding cured and thin composite shells around additively manufactured internal core topologies. The developed structures do not require complex molding approaches, while maintaining a high degree of manufacturing quality. A multidisciplinary design optimization is used to fully exploit the design freedom and the load carrying capabilities of the structure. Following the design concept, a UAV wing structure that carries more than 100 times its own weight is developed, optimized and tested to validate the design approach and demonstrate load carrying ability and manufacturing quality