scholarly journals Optimal Design of Bacterial Carpets for Fluid Pumping

Fluids ◽  
2022 ◽  
Vol 7 (1) ◽  
pp. 25
Author(s):  
Minghao W. Rostami ◽  
Weifan Liu ◽  
Amy Buchmann ◽  
Eva Strawbridge ◽  
Longhua Zhao
Keyword(s):  
Genetic Algorithm ◽  
Fluid Flow ◽  
Optimal Design ◽  
Phase Shift ◽  
High Performance ◽  
Optimization Problem ◽  
Phase Shifts ◽  
Flow Meter ◽  
Gradient Based ◽  
Regularized Stokeslets

In this work, we outline a methodology for determining optimal helical flagella placement and phase shift that maximize fluid pumping through a rectangular flow meter above a simulated bacterial carpet. This method uses a Genetic Algorithm (GA) combined with a gradient-based method, the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm, to solve the optimization problem and the Method of Regularized Stokeslets (MRS) to simulate the fluid flow. This method is able to produce placements and phase shifts for small carpets and could be adapted for implementation in larger carpets and various fluid tasks. Our results show that given identical helices, optimal pumping configurations are influenced by the size of the flow meter. We also show that intuitive designs, such as uniform placement, do not always lead to a high-performance carpet.

scholarly journals Study on the Design of an Underwater Chain Trencher via a Genetic Algorithm

2019 ◽  
Vol 7 (12) ◽  
pp. 429
Author(s):  
Jaebum Kim ◽  
O Soon Kwon ◽  
Nguyen Le Dang Hai ◽  
Jin Hwan Ko
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Parametric Analysis ◽  
Optimization Problem ◽  
Soft Rock ◽  
Analytic Model ◽  
Multi Objective Optimization ◽  
Nose Radius ◽  
Performance Requirements ◽  
Parametric Studies

In this study, a genetic algorithm (GA) with an analytic model is adopted to conduct multi-objective optimization for design of an underwater chain trencher. The optimization problem is defined as minimizing a product of the chain power and weight subject to the uniaxial compressive strength, coefficient of traction, bar length (L), nose radius (R) and ratio of the chipping depth over the spacing (l/S), of which the ranges are determined based on the specifications of commercial trenchers satisfying established performance requirements and previous parametric studies. It is found that an optimal design of the GA was obtained with L and l/S close to their low bound and R far from its low bound while that of a simple parametric analysis was acquired with the three parameters close to their low bounds. Moreover, in the most severe soft rock and traction conditions, the power and weight in the optimal design obtained by the GA are turn to be within the feasible ranges of targeted commercial trenchers.

An Optimal Design Method for Reducing Brake Squeal in Disc Brake Systems

2007 ◽  
Author(s):  
Toru Matsushima ◽  
Shinji Nishiwaki ◽  
Shintarou Yamasaki ◽  
Kazuhiro Izui ◽  
Masataka Yoshimura
Keyword(s):  
Optimal Design ◽  
High Performance ◽  
Optimization Problem ◽  
Design Method ◽  
Performance Measure ◽  
Disc Brake ◽  
Analysis Model ◽  
Brake Squeal ◽  
Element Analysis ◽  
Optimal Design Method

Minimizing brake squeal is one of the most important issues in the development of high performance braking systems. Recent advances in numerical analysis, such as finite element analysis, have enabled sophisticated analysis of brake squeal phenomena, but current design methods based on such numerical analyses still fall short in terms of providing concrete performance measures for minimizing brake squeal in high performance design drafts at the conceptual design phase. This paper proposes an optimal design method for disc brake systems that specifically aims to reduce brake squeal by appropriately modifying the shapes of the brake system components. First, the relationships between the occurrence of brake squeal and the geometry and characteristics of various components is clarified, using a simplified analysis model. Next, a new design performance measure is proposed for evaluating brake squeal performance and an optimization problem is then formulated using this performance measure as an objective function. The optimization problem is solved using Genetic Algorithms. Finally, a design example is presented to examine the features of the optimal solutions and confirm that the proposed method can yield useful design information for the development of high performance braking systems that minimize brake squeal.

Activity Analysis: Simplifying Optimal Design Problems Through Qualitative Partitioning

1995 ◽  
Author(s):  
Brian C. Williams ◽  
Jonathan Cagan
Keyword(s):  
Numerical Analysis ◽  
Optimal Design ◽  
Design Problem ◽  
Optimization Problem ◽  
Activity Analysis ◽  
Design Problems ◽  
Gradient Based ◽  
Monotonicity Analysis

Abstract Activity analysis is introduced as a means to strategically cut away subspaces of a design problem that can quickly be ruled out as suboptimal. This results in focused regions of the space in which additional symbolic or numerical analysis can take place. Activity analysis is derived from a qualitative abstraction of the Karush-Kuhn-Tucker conditions of optimality, used to partition an optimization problem into regions which are nonstationary and qualitatively stationary (qstationary). Activity analysis draws from the fields of gradient-based optimization, conflict-based approaches of combinatorial satisficing search, and monotonicity analysis.

scholarly journals Optimal Design by Genetic Algorithm for Maximum Fundamental Frequency of Laminated Shallow Shells

1996 ◽  
Vol 5 (1) ◽  
pp. 096369359600500 ◽  
Author(s):  
Y Narita ◽  
M Itoh ◽  
X Zhao
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Fundamental Frequency ◽  
Shallow Shell ◽  
Optimization Problem ◽  
Optimization Process ◽  
Laminated Shell ◽  
Shallow Shells

A genetic algorithm (GA) is applied to the optimization problem for maximizing the fundamental frequency of laminated shallow shells. A frequency formula is derived for the shallow shell supported by shear diaphrams, and is used in the GA optimization process. The advantage of using GA approach in the laminated shell problem is demonstrated.

Multi-Objective Optimization of a Piezoelectric Sandwich Ultrasonic Transducer by Using Elitist Non-Dominated Sorting Genetic Algorithm

2011 ◽  
Vol 474-476 ◽  
pp. 1808-1812
Author(s):  
Bo Fu ◽  
Yi Jing ◽  
Xuan Fu ◽  
Tobias Hemsel
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Ultrasonic Transducer ◽  
Analytical Models ◽  
Continuous Variables ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective

The multi-objective optimal design of a piezoelectric sandwich ultrasonic transducer is studied. The maximum vibration amplitude and the minimum electrical input power are considered as optimization objectives. Design variables involve continuous variables (dimensions of the transducer) and discrete variables (material types). Based on analytical models, the optimal design is formulated as a constrained multi-objective optimization problem. The optimization problem is then solved by using the elitist non-dominated sorting genetic algorithm (NSGA-II) and Pareto-optimal designs are obtained. The optimized results are analyzed and the preferred design is proposed. The optimization procedure presented in this contribution can be applied in multi-objective optimization problems of other piezoelectric transducers.

Sign in / Sign up

Export Citation Format

Share Document