scholarly journals A convex programming framework for optimal and bounded suboptimal well field management

2012 ◽  
Vol 48 (6) ◽  
Author(s):  
G. F. Dorini ◽  
F. Ö. Thordarson ◽  
P. Bauer-Gottwein ◽  
H. Madsen ◽  
D. Rosbjerg ◽  
...  
Keyword(s):  
Convex Programming ◽  
Programming Framework ◽  
Well Field ◽  
Field Management

An expert system for real-time well field management

2012 ◽  
Vol 12 (5) ◽  
pp. 699-706 ◽  
Author(s):  
B. S. Marti ◽  
G. Bauser ◽  
F. Stauffer ◽  
U. Kuhlmann ◽  
H.-P. Kaiser ◽  
...  
Keyword(s):  
Drinking Water ◽  
Expert System ◽  
Knowledge Base ◽  
Real Time ◽  
Urban Areas ◽  
Industrial Sites ◽  
Water Wells ◽  
Well Field ◽  
Field Management ◽  
Historical Management

Well field management in urban areas faces challenges such as pollution from old waste deposits and former industrial sites, pollution from chemical accidents along transport lines or in industry, or diffuse pollution from leaking sewers. One possibility to protect the drinking water of a well field is the maintenance of a hydraulic barrier between the potentially polluted and the clean water. An example is the Hardhof well field in Zurich, Switzerland. This paper presents the methodology for a simple and fast expert system (ES), applies it to the Hardhof well field, and compares its performance to the historical management method of the Hardhof well field. Although the ES is quite simplistic it considerably improves the water quality in the drinking water wells. The ES knowledge base is crucial for successful management application. Therefore, a periodic update of the knowledge base is suggested for the real-time application of the ES.

Well-Field Management

1978 ◽  
Vol 70 (3) ◽  
pp. 151-152 ◽  
Author(s):  
C. Leon Simpson
Keyword(s):  
Well Field ◽  
Field Management

Well Field Management Using Multi-Objective Optimization

2013 ◽  
Vol 27 (3) ◽  
pp. 629-648 ◽  
Author(s):  
Annette K. Hansen ◽  
Harrie-Jan Hendricks Franssen ◽  
Peter Bauer-Gottwein ◽  
Henrik Madsen ◽  
Dan Rosbjerg ◽  
...  
Keyword(s):  
Multi Objective Optimization ◽  
Multi Objective ◽  
Well Field ◽  
Field Management

scholarly journals Optimal Splines for Rigid Motion Systems: Benchmarking and Extensions

2009 ◽  
Vol 131 (10) ◽  
Author(s):  
B. Demeulenaere ◽  
J. De Caigny ◽  
G. Pipeleers ◽  
J. De Schutter ◽  
J. Swevers
Keyword(s):  
Convex Programming ◽  
Case Studies ◽  
Rigid Motion ◽  
Companion Paper ◽  
Upper And Lower Bounds ◽  
Driven Systems ◽  
Programming Framework ◽  
Optimization Study ◽  
Driven System ◽  
Time Optimal

This paper illustrates the power and versatility of the convex programming framework for optimal spline synthesis that was developed in a companion paper (Demeulenaere, Pipeleers, De Caigny, Swevers, De Schutter, and Vandenberghe, 2009, “Optimal Spines for Rigid Motion Systems: A Convex Programming Framework”, ASME J. Mech. Des., 131, p. 101005.). Two case studies concerning rigid motion systems illustrate the ability of the framework to improve upon recent (2005) literature results: (i) a numerical optimization study concerning kinematic optimization of uniform quintic splines for cam systems and (ii) an analytical study concerning time optimal quartic splines for motion systems driven by servomotors and subject to kinematic constraints. In a third study, the versatility of the framework is illustrated by generating time optimal and time-energy optimal motions for a rigid servomotor driven system under torque constraints. Based on these three case studies, the convex programming framework of the companion paper is extended with the following generic aspects: (i) a bisection to generate time optimal motions, (ii) a direct expression of the upper and lower bounds on motor torque, and (iii) a convex quadratic energy objective function for servomotor driven systems.

scholarly journals Joint Secure AF Relaying and Artificial Noise Optimization: A Penalized Difference-of-Convex Programming Framework

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 10076-10095 ◽  
Author(s):  
Jiaxin Yang ◽  
Qiang Li ◽  
Yunlong Cai ◽  
Yulong Zou ◽  
Lajos Hanzo ◽  
...  
Keyword(s):  
Convex Programming ◽  
Artificial Noise ◽  
Programming Framework ◽  
Noise Optimization ◽  
Difference Of Convex Programming ◽  
Difference Of Convex ◽  
Af Relaying

Well‐Field Management for Energy Efficiency

1991 ◽  
Vol 117 (10) ◽  
pp. 1290-1303 ◽  
Author(s):  
Billy J. Claborn ◽  
Ken A. Rainwater
Keyword(s):  
Energy Efficiency ◽  
Well Field ◽  
Field Management
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