Energy optimization of water supply system scheduling: Novel MINLP model and efficient global optimization algorithm

AIChE Journal ◽  
2016 ◽  
Vol 62 (12) ◽  
pp. 4277-4296 ◽  
Author(s):  
Hanyu Shi ◽  
Fengqi You
Keyword(s):  
Global Optimization ◽  
Water Supply ◽  
Optimization Algorithm ◽  
Energy Optimization ◽  
Supply System ◽  
Water Supply System ◽  
Efficient Global Optimization ◽  
Global Optimization Algorithm ◽  
Minlp Model

scholarly journals Topological Optimization of Under-Platform Dampers With Moving Morphable Components and Global Optimization Algorithm for Nonlinear Frequency Response

2021 ◽  
Vol 143 (2) ◽  
Author(s):  
E. Denimal ◽  
F. El Haddad ◽  
C. Wong ◽  
L. Salles
Keyword(s):  
Global Optimization ◽  
Optimization Algorithm ◽  
Nonlinear Behavior ◽  
Topological Optimization ◽  
Efficient Global Optimization ◽  
Nonlinear Frequency ◽  
Global Optimization Algorithm ◽  
Nonlinear Frequency Response ◽  
The Impact ◽  
Moving Morphable Components

Abstract To limit the risk of high cycle fatigue, underplatform dampers (UDPs) are traditionally used in aircraft engines to control the level of vibration. Many studies demonstrate the impact of the geometry of the damper on its efficiency, thus the consideration of topological optimization (TO) to find the best layout of the damper seems natural. Because of the nonlinear behavior of the structure due to the friction contact interface, classical methods of TO are not usable. This study proposes to optimize the layout of an UDP to reduce the level of nonlinear vibrations computed with the multiharmonic balance method (MHBM). The approach of TO employed is based on the moving morphable components (MMC) framework together with the Kriging and the efficient global optimization algorithm to solve the optimization problem. The results show that the level of vibration of the structure can be reduced to 30% and allow for the identification of different efficient geometries.

Designing a Morphable Parabolic Reflector Antenna Using Origami-Inspired Discretization and Efficient Global Optimization

2020 ◽  
Author(s):  
Gregory Wilson ◽  
Dimitris Lagoudas ◽  
Darren Hartl
Keyword(s):  
United States ◽  
Global Optimization ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Radiation Pattern ◽  
Optimization Algorithm ◽  
The United States ◽  
Lessons Learned ◽  
Efficient Global Optimization ◽  
Global Optimization Algorithm

Abstract This research explores a segmented parabolic antenna that can change its physical shape via shape memory alloy actuators, thereby altering its radiation pattern when transmitting a signal. The parabolic dish has been discretized into an origami pattern to make use of the naturally compliant fold regions, about which shape memory alloy wires create moments. Modeling of antenna deformation is accomplished via Abaqus considering SMA wires contracting due to temperature change as a manifestation of the shape memory effect. An electromagnetic analysis of the deformed antenna follows in ANSYS-HFSS to determine the antenna gain in all directions around the structure. The computed radiation pattern is projected onto a goal shape (e.g. the contiguous United States) to determine the degree to which the shaped broadcast pattern matches that of a desired broadcast area. Finally, the design is iterated using an efficient global optimization algorithm to ascertain an actuation schedule that generates the most conformal broadcast pattern. Traditional optimization algorithms such as genetic or particle swarm may require thousands of designs, particularly when many design variables are considered. The efficient global optimization algorithm employs far fewer designs by fitting surrogate models to the data and only testing points where large improvement is expected, thus reducing design optimization time. The evolution and improvement to an antenna will be discussed for an antenna making use of eight, 16, and 24 SMA linear actuators to most optimally broadcast to only the United States while avoiding signal spill-over into other regions, and the lessons learned can then applied to match broadcast pattern based on other countries as well.

scholarly journals A multiple-data-based efficient global optimization algorithm and its parallel implementation for automotive body design

2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879434 ◽  
Author(s):  
Bing Xu ◽  
Yong Cai
Keyword(s):  
Global Optimization ◽  
Optimization Algorithm ◽  
Graphics Processing Unit ◽  
Optimization Method ◽  
Efficient Global Optimization ◽  
Processing Unit ◽  
Global Optimization Algorithm ◽  
Multiple Data ◽  
Practical Engineering ◽  
Graphics Processing

The purpose of this article is to improve the convergence efficiency of the traditional efficient global optimization method. Furthermore, we try a graphics processing unit–based parallel computing method to improve the computing efficiency of the efficient global optimization method for both mathematical and practical engineering problems. First, we propose a multiple-data-based efficient global optimization algorithm instead of the multiple-surrogates-based efficient global optimization algorithm. Second, a novel graphics processing unit–based general-purpose computing technology is adopted to accelerate the solution efficiency of our multiple-data-based efficient global optimization algorithm. Third, a hybrid parallel computing approach using the OpenMP and compute unified device architecture is adopted to further improve the solution efficiency of forward problems in practical application. This is accomplished by integrating the graphics processing unit–based finite element method numerical analysis system into the optimization software. The numerical results show that for the same problem, the optimal result of the multiple-data-based efficient global optimization algorithm is consistently better than the multiple-surrogates-based efficient global optimization algorithm with the same optimization iterations. In addition, the graphics processing unit–based parallel simulation system helps in the reduction of the calculation time for practical engineering problems. The multiple-data-based efficient global optimization method performs stably in both high-order mathematical functions and large-scale nonlinear practical engineering optimization problems. An added benefit is that the computational time and accuracy are no longer obstacles.

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