scholarly journals Optimization of well field management to mitigate groundwater contamination using a simulation model and evolutionary algorithm

2022 ◽  
Vol 807 ◽  
pp. 150811
Author(s):  
Mitja Janža
Keyword(s):  
Simulation Model ◽  
Evolutionary Algorithm ◽  
Groundwater Contamination ◽  
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 Simultaneous Identification of Number, Location, and Release History of Groundwater Contamination Sources

2021 ◽  
Author(s):  
Jiuhui Li ◽  
Wenxi Lu ◽  
Zhengfang Wu ◽  
Hongshi He
Keyword(s):  
Simulation Model ◽  
Groundwater Contamination ◽  
Surrogate Model ◽  
Solution Process ◽  
Mixed Integer ◽  
Continuous Variables ◽  
Integer Variable ◽  
Contamination Sources ◽  
History Of ◽  
Learning Machine

Abstract In previous studies, a 0-1 mixed integer nonlinear programming optimization model (0-1MINLPOM) could only identify the location and release intensity for groundwater contamination sources (GCSs), and the location of each GCS was regarded as a 0-1 integer variable, selected from several locations determined in advance. However, in actual situations, the locations usually cannot be accurately isolated to a few GCSs and the number of GCSs is often unknown, so 0-1MINLPOM was improved in this study. Based on the estimation that there is a maximum of three GCSs in the study area, an improved 0-1 MINLPOM was established to simultaneously identify the number of GCSs (treated as 0-1 integer variable), the location (treated as integer variable) and release history of GCS (treated as continuous variables). The simulation model was constructed as an equality constraint embedded improved 0-1 MINLPOM. In the improved 0-1 MINLPOM solution process, repeatedly calling the simulation model would have incurred a massive computational load and taken a long time. Thus, a surrogate model based on kriging and extreme learning machine (ELM) was established respectively for the simulation model to avoid this shortcoming. The results show that the accuracy of the kriging surrogate model (Krig-SM) was higher compared with the ELM surrogate model (ELM-SM). The improved 0-1 MINLPOM could identify the number, location, and release history of GCSs simultaneously. The accuracy of identifying the number of GCSs was 100%, and the accuracies of identifying the locations and release history were above 91.67% and 90.14%, respectively.

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

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

A hybrid evolutionary algorithm for tuning a cloth-simulation model

2012 ◽  
Vol 12 (1) ◽  
pp. 266-273 ◽  
Author(s):  
D. Mongus ◽  
B. Repnik ◽  
M. Mernik ◽  
B. Žalik
Keyword(s):  
Simulation Model ◽  
Evolutionary Algorithm ◽  
Cloth Simulation ◽  
Hybrid Evolutionary Algorithm
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