A modified model for concurrent topology optimization of structures and materials

This paper presents a study on the concur- rent topology optimization of a structure and its material microstructure. A modified optimization model is proposed by introducing microstructure orientation angles as a new type of design variable. The new model is based on the assumptions that a structure is made of a material with the same microstructure, and the material may have a different orientation within the design domain of the structure. The homogenization theory is applied to link the material and structure scales. An additional post-processing technique is developed for modifying the obtained design to avoid local optima caused by the use of orientation angle variables. Numerical examples are presented to illustrate the viabil- ity and effectiveness of the proposed model. It is found that significant improvement in structural performance can be achieved by optimizing the orientation of microstructures in concurrent topology optimization of structures and materials.

Reliability-based concurrent subspace optimization method

To avoid the high computational cost and much modification in the process of applying traditional reliability-based design optimization method, a new reliability-based concurrent subspace optimization approach is proposed based on the comparison and analysis of the existing multidisciplinary optimization techniques and reliability assessment methods. It is shown through a canard configuration optimization for a three-surface transport that the proposed method is computationally efficient and practical with the least modification to the current deterministic optimization process.

An Efficient Method for Reliability-based Multidisciplinary Design Optimization

Design for modem engineering system is becoming multidisciplinary and incorporates practical uncertainties; therefore, it is necessary to synthesize reliability analysis and the multidisciplinary design optimization （MDO） techniques for the design of complex engineering system. An advanced first order second moment method-based concurrent subspace optimization approach is proposed based on the comparison and analysis of the existing multidisciplinary optimization techniques and the reliability analysis methods. It is seen through a canard configuration optimization for a three-surface transport that the proposed method is computationally efficient and practical with the least modification to the current deterministic optimization process.

Strategic mining options optimization:Open pit mining, underground mining or both

Near-surface deposits that extend to considerable depths are often amenable to both open pit mining and/or underground mining. This paper investigates the strategy of mining options for an orebody using a Mixed Integer Linear Programming(MILP) optimization framework. The MILP formulation maximizes the Net Present Value(NPV) of the reserve when extracted with(i) open pit mining,(ii) underground mining, and(iii) concurrent open pit and underground mining. Comparatively, implementing open pit mining generates a higher NPV than underground mining. However considering the investment required for these mining options, underground mining generates a better return on investment than open pit mining. Also, in the concurrent open pit and underground mining scenario, the optimizer prefers extracting blocks using open pit mining. Although the underground mine could access ore sooner, the mining cost differential for open pit mining is more than compensated for by the discounting benefits associated with earlier underground mining.

CONCURRENT PRODUCT PORTFOLIO PLANNING AND MIXED PRODUCT ASSEMBLY LINE BALANCING

Reconfigurable products and manufacturing systems have enabled manufacturers to provide ＂cost effective＂ variety to the market. In spite of these new technologies, the expense of manufacturing makes it infeasible to supply all the possible variants to the market for some industries. Therefore, the determination of the right number of product variantsto offer in the product portfolios becomes an important consideration. The product portfolio planning problem had been independently well studied from marketing and engineering perspectives. However, advantages can be gained from using a concurrent marketing and engineering approach. Concurrent product development strategies specifically for reconfigurable products and manufacturing systems can allow manufacturers to select best product portfolios from marketing, product design and manufacturing perspectives. A methodology for the concurrent design of a product portfolio and assembly system is presented. The objective of the concurrent product portfolio planning and assembly system design problem is to obtain the product variants that will make up the product portfolio such that oversupply of optional modules is minimized and the assembly line efficiency is maximized. Explicit design of the assembly system is obtained during the solution of the problem. It is assumed that the demand for optional modules and the assembly times for these modules are known a priori. A genetic algorithm is used in the solution of the problem. The basic premise of this methodology is that the selected product portfolio has a significant impact on the solution of the assembly line balancing problem. An example is used to validate this hypothesis. The example is then further developed to demonstrate how the methodology can be used to obtain the optimal product portfolio. This approach is intended for use by manufacturers during the early design stages of product family design.

Concurrent Analysis and Design of Structure and Its Periodic Material

The specific good properties of cellular materials and composite materials, such as low density and high permeability, make the optimal design of such materials necessary and at- tractive. However, the given materials for the structures may not be optimal or suitable, since the boundary condition and applied loads vary in practical applications; hence the macro-structure and its material micro-structure should be considered simultaneously. Although abundant studies have been reported on the structural and material optimization at each level, very few of them considered the mutual coordination on both scales. In this paper, two FE models are built for the macro-structure and the micro-structure, respectively; and the effective elastic properties of the periodic micro-structure are blended into the analysis of macro-structure by the homogenization theory. Here, a topological optimum is obtained by gradually re-distributing the constituents within the micro-structure and updating the topological shape at the macro-structure until converges are achieved on both scales. The mutual coordination between the roles of micro-scale and macro-scale is considered. Some numerical examples are presented, which illustrate that the proposed optimization algorithm is effective and highly efficient for the micro-structure design and macro-structure optimization. For the composite design, one can see reasonable effects of the stiffness of base materials on the resultant topologies.

A Task Execution Framework for Cloud-Assisted Sensor Networks

As sensor networks are increasingly being deployed, there will be more sensors available in the same region, making it strategic to select the suitable ones to execute users＇ applications. We propose a task execution framework, named sTaskAlloc, to execute application energy efficiently by two main parts. First, considering that the energy consumption of an application is inversely proportional to the utilization rate of sensors, we present a hot sensor selection algorithm, HotTasking, to minimize the energy consumption of new added applications by selecting the most suitable sensor. Second, when a sensor is shared by multiple applications, proposed MergeOPT （a concurrent tasks optimization algorithm） is used to optimize energy consumption further by eliminating redundant sampling tasks. Experimental results show that sTaskAlloc can save more than 76% of energy for new added applications compared with existing methods and reduce up to 72% of sampling tasks when a sensor is shared by more than 10 applications.