An Optimal Design Model of Furrow Irrigation

2021 ◽  
Author(s):  
Kaveh Ostad-Ali-Askari
Keyword(s):  
Optimal Design ◽  
Furrow Irrigation ◽  
Design Model

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.

Optimal Design of Furrow Irrigation Systems

1981 ◽  
Vol 24 (3) ◽  
pp. 0617-0623 ◽  
Author(s):  
J. Mohan Reddy ◽  
Wayne Clyma
Keyword(s):  
Optimal Design ◽  
Furrow Irrigation ◽  
Irrigation Systems

An optimal design model for the wall thickness of the propellant tank

2019 ◽  
Vol 234 (2) ◽  
pp. 445-456
Author(s):  
Tengda Xin ◽  
Hua Wang ◽  
Cunyan Cui ◽  
Jiguang Zhao
Keyword(s):  
Optimal Design ◽  
Wall Thickness ◽  
Equivalent Stress ◽  
Design Model ◽  
Bottom Wall ◽  
Cylinder Wall ◽  
Significant Research ◽  
Maximum Equivalent Stress ◽  
Liquid Rocket ◽  
Propellant Tank

The propellant tank is a vital part for the liquid rocket, and the optimal design of the propellant tank is a significant research to develop the heavy rocket. This paper aims at providing an optimal design model for tank wall thickness. Through establishing the tank mathematical model, analyzing the stress distributions of tank, and defining the equivalent stress of tank, the wall thickness parameters of tank roof, cylinder, and bottom are obtained. The effects of tank parameters on the wall thickness are analyzed to determine the distribution rules of tank roof, cylinder, and bottom wall thickness parameters. Combined with the safety factor that is defined as the ratio of the material's ultimate stress to the maximum equivalent stress, the optimal design model with invariable tank roof and bottom wall thicknesses and variable tank cylinder wall thickness is established. Finally, the optimal design model is verified by comparing the optimal tank with the original tank. The results show that the optimal design model can effectively decrease the mass of the tank and improve the stress distribution of the tank.

scholarly journals Prediction Model of Mechanical Extending Limits in Horizontal Drilling and Design Methods of Tubular Strings to Improve Limits

2017 ◽  
Vol 2017 ◽  
pp. 1-18
Author(s):  
Wenjun Huang ◽  
Deli Gao ◽  
Yinghua Liu
Keyword(s):  
Optimal Design ◽  
Horizontal Well ◽  
Weight Ratio ◽  
Design Model ◽  
Constraint Factor ◽  
Horizontal Drilling ◽  
Buckling Loads ◽  
Drilling Parameters ◽  
Helical Buckling

Mechanical extending limit in horizontal drilling means the maximum horizontal extending length of a horizontal well under certain ground and down-hole mechanical constraint conditions. Around this concept, the constrained optimization model of mechanical extending limits is built and simplified analytical results for pick-up and slack-off operations are deduced. The horizontal extending limits for kinds of tubular strings under different drilling parameters are calculated and drawn. To improve extending limits, an optimal design model of drill strings is built and applied to a case study. The results indicate that horizontal extending limits are underestimated a lot when the effects of friction force on critical helical buckling loads are neglected. Horizontal extending limits firstly increase and tend to stable values with vertical depths. Horizontal extending limits increase faster but finally become smaller with the increase of horizontal pushing forces for tubular strings of smaller modulus-weight ratio. Sliding slack-off is the main limit operation and high axial friction is the main constraint factor constraining horizontal extending limits. A sophisticated installation of multiple tubular strings can greatly inhibit helical buckling and increase horizontal extending limits. The optimal design model is called only once to obtain design results, which greatly increases the calculation efficiency.

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