Investigation of Load Path Based Topology Optimization
Abstract
The next generation of aircraft are required to have low weight combined with structuralresponses tailored to meet different operational requirements. Inspired by the performance-tailoredstructures of living organisms, such as bones, which develop and modify structure in response to loads, we propose an innovative topology optimization method based on the load patterns and growth mechanism. The load paths incorporated in growth mechanism assist in establishing the governing criteria for depositing weight resources and guiding the growth process to determine the optimal structure. A novel technique is proposed for the visualization and identification of structural load paths for various types of loading conditions based on the streamline concept in fluid mechanics. The proposed load-path algorithm provides critical insights into structural performance, functionality, and efficiency. These physical insights are implemented in a topology optimization framework to tailor the material to passively control the global and local objective functions under multiple load cases. We plan to evaluate the optimal design’s structural responses and the predicted behavior by conducting static, buckling, and vibration experimental studies aswell as comparing it to current topology and shape optimization methods. This research is expected to have two major outcomes: (1) an efficient and robust load-path algorithm and (2) an experimentally-validated, load path-based topology optimization method. With the proposed load-path algorithm, the visualization and identification of load paths will no longer be susceptible to the interpretation of engineers and designers. The development of a topology optimization framework will enable designers to evaluate potential complex layouts that are optimized for particular design conditions, resulting in significant material savings for a wide range of applications, from aircraft and launch vehicles to automobiles and ocean-going vehicles.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 02, 2017
- Source ID
- FA95501710171
Entities
People
- Ali A Tamijani
Organizations
- Air Force Office of Scientific Research
- Embry–Riddle Aeronautical University
- United States Air Force