Abstract

Automated optimization-driven analyses may lead to an emersion of innovative design approaches, while investigating the potentials in design, analysis and control of high-performance engineering structures and adaptive architecture. In the present study, an optimum motion sequence for the reconfiguration of a 9-bar linkage is succeeded through a robust automated optimization-driven approach of the metaheuristic algorithm, Pity Beetle Algorithm (PBA). The project explores the loadbearing behavior of the structure in different states of the 'effective 4-bar' reconfiguration sequences considering its self-weight and a uniform distributed vertical load of 2.5 kN/m. A principal planar 9-bar linkage with initial and target configurations are defined on the basis of a quasi-ellipsoid shape of 5.42 and 4.49 m height respectively and 4.66 m span. The 9-bar linkage uses a sequence of one degree-of-freedom (DOF) motion steps by selectively releasing four joints of the primary members at a time and engaging brakes on each individual joint. The system is actuated by only one geared electrical motor detached from the structure and positioned on the ground. Different intermediate configurations depend on the automated optimization-driven analysis, in order to adjust the system's joints to the desired values during the motion steps involved from the predefined initial to the target position. The optimization aims at minimizing the brake torques in the locked joints of the structure. The work-minimization problem has been solved by PBA, inspired by the aggregation behavior, of nest and food finding, of the beetle named Pityogenes chalcographus, also known as six-toothed spruce bark beetle. PBA can be applied to NP-hard optimization problems regardless of the scale, since PBA has the ability to search for possible solutions into large spaces and to find the global optimum solution overcoming local optima. The numerical studies have been conducted with the software MATLAB and Simulink for a Model Based-Design considering the geometrical, mass and inertia characteristics of the planar system. The obtained results demonstrate that the design of reconfigurable engineering structures and adaptive architecture can benefit from an automated optimization-driven analysis of the reconfiguration determination, in view of achieving improved performance and energy efficiency.

Highlights

  • Current optimization and energy concerns have been embedded into the design process of highperformance engineering structures and adaptive architecture to pursue optimal solutions in complex systems through usage of an increasingly available computational power

  • The metaheuristic search algorithm called Pity Beetle Algorithm (PBA) is implemented in the automated optimization-driven analysis aiming to investigate a plethora of possible sequences of a planar arch-like 9-bar linkage based on the “effective 4-bar” approach

  • This paper presents the automated optimization sequence process of a predefined initial configuration of the 9-bar linkage to the target configuration involving six different intermediate steps

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Summary

Introduction

Current optimization and energy concerns have been embedded into the design process of highperformance engineering structures and adaptive architecture to pursue optimal solutions in complex systems through usage of an increasingly available computational power. The metaheuristic search algorithm called PBA is implemented in the automated optimization-driven analysis aiming to investigate a plethora of possible sequences of a planar arch-like 9-bar linkage based on the “effective 4-bar” approach.

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