SEQUENTIAL SPARSITY ITERATIVE OPTIMAL DESIGN MODEL FOR CALIBRATION OF COMPLEX SYSTEMS WITH EPISTEMIC UNCERTAINTY

2016 ◽  
Vol 6 (2) ◽  
pp. 175-193
Author(s):  
Weifeng Li ◽  
Xiaojun Duan ◽  
Chang Li
Keyword(s):  
Optimal Design ◽  
Complex Systems ◽  
Epistemic Uncertainty ◽  
Design Model

scholarly journals Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems

2014 ◽  
Author(s):  
Bo Yang Yu ◽  
Tomonori Honda ◽  
Syed Zubair ◽  
Mostafa H. Sharqawy ◽  
Maria C. Yang
Keyword(s):  
Optimal Design ◽  
Complex Systems ◽  
Design Optimization ◽  
Reverse Osmosis ◽  
Large Scale ◽  
Analytical Target Cascading ◽  
Total Water ◽  
Target Cascading ◽  
Desalination Plants ◽  
Functional Components

Large-scale desalination plants are complex systems with many inter-disciplinary interactions and different levels of sub-system hierarchy. Advanced complex systems design tools have been shown to have a positive impact on design in aerospace and automotive, but have generally not been used in the design of water systems. This work presents a multi-disciplinary design optimization approach to desalination system design to minimize the total water production cost of a 30,000m3/day capacity reverse osmosis plant situated in the Middle East, with a focus on comparing monolithic with distributed optimization architectures. A hierarchical multi-disciplinary model is constructed to capture the entire system’s functional components and subsystem interactions. Three different multi-disciplinary design optimization (MDO) architectures are then compared to find the optimal plant design that minimizes total water cost. The architectures include the monolithic architecture multidisciplinary feasible (MDF), individual disciplinary feasible (IDF) and the distributed architecture analytical target cascading (ATC). The results demonstrate that an MDF architecture was the most efficient for finding the optimal design, while a distributed MDO approach such as analytical target cascading is also a suitable approach for optimal design of desalination plants, but optimization performance may depend on initial conditions.

scholarly journals Optimal Design of a Residential Photovoltaic Renewable System in South Korea

2019 ◽  
Vol 9 (6) ◽  
pp. 1138 ◽  
Author(s):  
Hyunkyung Shin ◽  
Zong Geem
Keyword(s):  
Optimal Design ◽  
South Korea ◽  
Piecewise Linear ◽  
Design Model ◽  
Design Solution ◽  
Maintenance Cost ◽  
Pv System ◽  
Local Optima ◽  
Pv Systems ◽  
Electricity Bill

An optimal design model for residential photovoltaic (PV) systems in South Korea was proposed. In the optimization formulation, the objective function is composed of three costs, including the monthly electricity bill, the PV system construction cost (including the government’s subsidy), and the PV system maintenance cost. Here, because the monthly electricity bill is not differentiable (it is a stepped piecewise linear function), it cannot be solved by using traditional gradient-based approaches. For details considering the residential electric consumption in a typical Korean household, consumption was broken down into four types (year-round electric appliances, seasonal electric appliances, lighting appliances, and stand-by power). For details considering the degree of PV generation, a monthly generation dataset with different PV tilt angles was analyzed. The optimal design model was able to obtain a global design solution (PV tilt angle and PV size) without being trapped in local optima. We hope that this kind of practical approach will be more frequently applied to real-world designs in residential PV systems in South Korea and other countries.

Cans’ Optimization Design Model

2011 ◽  
Vol 109 ◽  
pp. 368-371
Author(s):  
Jun Er Ma ◽  
Meng Yuan Li
Keyword(s):  
Optimal Design ◽  
Circular Cylinder ◽  
Optimum Design ◽  
Optimization Design ◽  
Design Model ◽  
Extreme Problem ◽  
Programming Knowledge

We gradually improve the shape of cans by using geometry, derivative and programming knowledge. Firstly suppose the shape of cans is a circular cylinder and both of the thickness of the side and under bottom of it are b, the thickness of the upper bottom is . Then establish a Binary function’s extreme problem with a condition, through the programming we finally get the optimal design for which the ratio of Radius r and Height h is 1:(1+ ).Secondly, design the cans is a connection of circular cylinder and frustum of a cone, the thickness of the surface is like the same assumptions as before, establish a multi-function’s extreme problem with a condition, through the programming we can get the optimum design size.

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