Design optimization of infill pattern structure and continuous fiber path for CFRP-AM- Simultaneous optimization of topology and fiber arrangement for minimum material cost

2021 ◽  
Author(s):  
Koki Jimbo ◽  
Toshitake Tateno
Keyword(s):  
Design Optimization ◽  
Simultaneous Optimization ◽  
Continuous Fiber ◽  
Pattern Structure ◽  
Material Cost ◽  
Fiber Arrangement ◽  
Fiber Path

scholarly journals Mathematical Strategies for Design Optimization of Multiphase Materials

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Rick Catania ◽  
Abdalla Diraz ◽  
Dominic Maier ◽  
Armani Tagle ◽  
Pınar Acar
Keyword(s):  
Design Optimization ◽  
Phase Distribution ◽  
Control Point ◽  
Structural Performance ◽  
Computational Time ◽  
Critical Set ◽  
Multiphase Materials ◽  
Analysis Scheme ◽  
Fiber Path ◽  
Spatially Varying

This work addresses various mathematical solution strategies adapted for design optimization of multiphase materials. The goal is to improve the structural performance by optimizing the distribution of multiple phases that constitute the material. Examples include the optimization of multiphase materials and composites with spatially varying fiber paths using a finite element analysis scheme. In the first application, the phase distribution of a two-phase material is optimized to improve the structural performance. A radial basis function (RBF) based machine learning algorithm is utilized to perform a computationally efficient design optimization and it is found to provide equivalent results with the physical model. The second application concentrates on the optimization of spatially varying fiber paths of a composite material. The fiber paths are described by the Non-Uniform Rational Bezier (B)-Spline Surface (NURBS) using a bidirectional control point representation including 25 parameters. The optimum fiber path is obtained for various loading configurations by optimizing the NURBS parameters that control the overall distribution of fibers. Next, a direct sensitivity analysis is conducted to choose the critical set of parameters from the design point to improve the computational time efficiency. The optimized fiber path obtained with the reduced number of NURBS parameters is found to provide similar structural properties compared to the optimized fiber path that is modeled with a full NURBS representation with 25 parameters.

Multidisciplinary co-design optimization of the structure and control systems for large cable shovel considering cross-disciplinary interaction

2020 ◽  
Vol 234 (22) ◽  
pp. 4353-4365
Author(s):  
Xueguan Song ◽  
Tianci Zhang ◽  
Yongliang Yuan ◽  
Xiaobang Wang ◽  
Wei Sun
Keyword(s):  
Energy Consumption ◽  
Design Optimization ◽  
Integrated Design ◽  
Structure Design ◽  
Sequential Design ◽  
Simultaneous Optimization ◽  
Open Pit ◽  
Structure Control ◽  
Cable Shovel ◽  
And Control

Large cable shovel is a complex mechatronic system used for primary production in the open pit mine. For such structure-control highly coupled system, the conventional sequential design strategy (structure design followed by the control optimization in sequence) cannot manage this interaction adequately and explicitly. In addition, the large cable shovel consists of large number of sub-systems and/or disciplines, which also poses challenges to the global optimal design for large cable shovel. To enhance large cable shovel’s performance, an integrated design optimization strategy combining the structure-control simultaneous design (co-design) and the multidisciplinary design optimization is established in this study to perform the global optimization for the large cable shovel. In this proposed multidisciplinary co-design, the point-to-point trajectory planning method is extended to achieve the simultaneous optimization of the structure and control system. Besides the structure and control, the dynamics/vibration and energy consumption are taken into account in this multidisciplinary co-design. The objectives are to minimize the energy consumption per volume of ore and to minimize the excavating time. By comparing the multidisciplinary co-design and the conventional sequential design, it is found that the multidisciplinary co-design can not only make large cable shovel’s structure more compact with relatively small vibration, but also generate more flexible control speeds by making the best of the power motors.

Simultaneous Requirement and Design Optimization of an Industrial Robot Family Using Multi-Objective Optimization

2011 ◽  
Author(s):  
Daniel Wa¨ppling ◽  
Xiaolong Feng ◽  
Hans Andersson ◽  
Marcus Pettersson ◽  
Bjo¨rn Lunden ◽  
...  
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Industrial Robot ◽  
Simultaneous Optimization ◽  
Engineering Practice ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Research Experience ◽  
Requirement Specification ◽  
Multi Objective

Simultaneous development of an industrial robot family, consisting typically of 2–10 robots, has been an engineering practice in robotics industry. In this process, significant scenario studies on defining product requirement specifications and associated design change are conducted. This implies that understanding the relation between product requirements and design of the robot family is of critical importance. However, in the current engineering practice, any change in requirement specification results in tremendous efforts in the re-design of the robot family. This discloses the need for efficient methodology and tools for simultaneously optimizing product requirements and design of an industrial robot family. In this work, methodology and tools have been successfully developed for simultaneously optimizing product requirements and design of an industrial robot family in a fully automated way. This problem is formulated to a multi-objective optimization problem and solved using multi-objective genetic algorithm (MOGA). Results of this work have demonstrated clearly the efficiency of this approach and the insight obtained on the relation between product requirement and product design. The developed methodology and results of simultaneous requirement specification and design optimization will be detailed in this paper. In addition, research experience and future work will also be discussed. To our best knowledge, the simultaneous optimization of product requirement and product design has not been widely investigated and explored in academia. The trade-off information explored by such approach is crucial in product development in industrial practice. Such approach will further increase the complexity of traditional design optimization approach where product requirement is normally pre-defined and used as constraint. It is certain that discussions of the addressed problem and developed methodology will contribute to promoting the significance of efforts in the research society of multi-objective design optimization, multi-objective design optimization of product families, and design automation.

scholarly journals Multidisciplinary Design Optimization and Analysis of Hydrazine Monopropellant Propulsion System

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Amirhossein Adami ◽  
Mahdi Mortazavi ◽  
Mehran Nosratollahi ◽  
Mohammadreza Taheri ◽  
Jalal Sajadi
Keyword(s):  
Design Optimization ◽  
Attitude Control ◽  
Multidisciplinary Design Optimization ◽  
Total Mass ◽  
Dry Mass ◽  
Propulsion System ◽  
Simultaneous Optimization ◽  
Multidisciplinary Design ◽  
Nozzle Geometry ◽  
Design Algorithm

Monopropellant propulsion systems are widely used especially for low cost attitude control or orbit correction (orbit maintenance). To optimize the total propulsion system, subsystems should be optimized. Chemical decomposition, aerothermodynamics, and structure disciplines demand different optimum condition such as tank pressure, catalyst bed length and diameter, catalyst bed pressure, and nozzle geometry. Subsystem conflicts can be solved by multidisciplinary design optimization (MDO) technique with simultaneous optimization of all subsystems with respect to any criteria and limitations. In this paper, monopropellant propulsion system design algorithm is presented and the results of the proposed algorithm are validated. Then, multidisciplinary design optimization of hydrazine propulsion system is proposed. The goal of optimization can be selected as minimizing the total mass (including propellant), minimizing the propellant mass (maximizing the Isp), or minimizing the dry mass. Minimum total mass, minimum propellant mass, and minimum dry mass are derived using MDO technique. It is shown that minimum total mass, minimum dry mass, and minimum propellant mass take place in different conditions. The optimum parameters include bed-loading, inlet pressure, mass flow, nozzle geometry, catalyst bed length and diameter, propellant tank mass, specific impulse (Isp), and feeding mass which are derived using genetic algorithm (GA).

A novel multiobjective lognormal-beta differential evolution approach for the transformer design optimization

2018 ◽  
Vol 35 (2) ◽  
pp. 955-978 ◽  
Author(s):  
Marina Tsili ◽  
Eleftherios I. Amoiralis ◽  
Jean Vianei Leite ◽  
Sinvaldo R. Moreno ◽  
Leandro dos Santos Coelho
Keyword(s):  
Differential Evolution ◽  
Design Optimization ◽  
Numerical Results ◽  
Simultaneous Optimization ◽  
Manufacturing Cost ◽  
Convergence Criteria ◽  
Content Type ◽  
Real World Applications ◽  
Transformer Design ◽  
Beta Differential Evolution

Purpose Real-world applications in engineering and other fields usually involve simultaneous optimization of multiple objectives, which are generally non-commensurable and conflicting with each other. This paper aims to treat the transformer design optimization (TDO) as a multiobjective problem (MOP), to minimize the manufacturing cost and the total owing cost, taking into consideration design constraints. Design/methodology/approach To deal with this optimization problem, a new method is proposed that combines the unrestricted population-size evolutionary multiobjective optimization algorithm (UPS-EMOA) with differential evolution, also applying lognormal distribution for tuning the scale factor and the beta distribution to adjust the crossover rate (UPS-DELFBC). The proposed UPS-DELFBC is useful to maintain the adequate diversity in the population and avoid the premature convergence during the generational cycle. Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria. Findings Numerical results using UPS-DELFBC applied to the transform design optimization of 160, 400 and 630 kVA are promising in terms of spacing and convergence criteria. Originality/value This paper develops a promising UPS-DELFBC approach to solve MOPs. The TDO problems for three different transformer specifications, with 160, 400 and 630 kVA, have been addressed in this paper. Optimization results show the potential and efficiency of the UPS-DELFBC to solve multiobjective TDO and to produce multiple Pareto solutions.

Sign in / Sign up

Export Citation Format

Share Document