A new identification model SATSO-GWT has been developed based on the OOA and SATS-GWT for solving the transient source release problem. The OOA is used to find good solutions effectively for a problem with a large amount of unknowns.
The SATSO-GWT combines the merit of SA, TS, OOA, and roulette wheel method to solve the complex source information identification problem effectively and accurately. The SATSO-GWT utilized the spatial data to identify the source information.
SATSO-GWT gives correct estimated location and good estimated release periods and concentrations in eight cases with different initial guess location. In addition, the SATSO-GWT gives fairly good results when the sampling concentration having measurement errors, even the error level is up to 10%. For a large target area with a complex release history which has six release periods with six different concentrations, the SATSO-GWT can also give excellent results demonstrating its capability in dealing with such the problem. According to the result of the final scenario, the more complex release history problem could also be solved as long as the computing time is long enough. The model SATSO-GWT provides effective measures in solving the complex groundwater contaminated identification problem.
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Table 1 The sampling points and measured concentrations when the real source is located at the depth of -9 m.
Sampling point Measured concentration (ppm)
A2 2.231E-01 B1 1.536E-01 C2 1.930E-01 D4 1.215E-01 E3 6.441E-02 F2 1.195E-01 G1 1.675E-01 H3 1.213E-01
Table 2 Results of 8 cases for sifting the top two locations Initial guess
value Sifted results
Case Guess source location
Note that the target source is located at (110m, 270m, -9m).
Table 3 Analyzed results from the SATS-GWT and SATSO-GWT
Table 4 Results of 8 cases for studying the effect of different initial locations Initial guess
value Result
Case Guess source location
Note that the real source is located at (110m, 270m, -9m), real release concentration is 100 ppm over the first 180 days, and 50 ppm over the second 180 days.
Table 5 Results of the cases when sampling concentrations have measurement error
Note that the real source is located at (110m, 270m, -9m), real release concentration is 100 ppm over the first 180 days, and 50 ppm over the second 180 days.
Table 6 The sampling points and measured concentrations when the real source is located at the depth of -9 m.
Measured concentration (ppm) Sampling point
T = 360 (day) T = 390 (day)
A2 3.467E-01 2.981E-01
B1 2.124E-01 1.997E-01
C2 2.882E-01 2.496E-01
D4 1.586E-01 1.553E-01
E3 9.521E-02 9.418E-02
F2 1.710E-01 1.608E-01
G1 2.103E-01 1.998E-01
H3 1.671E-01 1.587E-01
Table 7 Results of the larger suspicious areas and more release periods Sifted results
Initial guess
source location Rank Sifted location (m) Current objective function value ( ×10-4 )
60.012 56.509 66.845 55.070 61.556 60.587
Optimal
105.53 194.59 147.29 56.852 97.929 70.829
8.191 2 days 23 hours
Note that the real source is located at (110m, 270m, -9m), real release concentration is 100 ppm over the first 60 days, 200 ppm over the second 60 days, 150 ppm over the third 60 days, 50 ppm over the fourth 60 days, 100 ppm over the fifth 60 days, and 70 ppm over the sixth 60 days.
Figure 1 Flowchart of SA algorithm.
No
Move CUSOL to tabu list
BNBS < GOOV ? Regenerate
NBSOLs
Figure 2 Flowchart of TS algorithm. The CUSOL represents the current solution, GOSOL represents the global optimal solution, NBSOL represents the neighborhood solution, BNBS represents the best NBSOL, and GOOV represents the global optimal objective value.
3 times OFV
OFVCULO
Do TS process in SATSO-GWT (Figure 4)
Do OOA process in SATSO-GWT (Figure 5) Yes
No
Yes Yes No
No
Figure 3 Flowchart of SATSO-GWT. The OFV represents the objective function value, CALO represents the candidate location, and OFVCULO represents the optimal objective function value at current location.
Figure 4 Flowchart of TS process in SATSO-GWT. The OFVGO represents the current global optimal objective function value, OFVCULO represents the optimal objective function value at current location, GOLO represents the global optimal location, CALO represents the candidate location, and CULO represents the current location.
Figure 5 Flowchart of OOA in SATSO-GWT. The CALO represents the candidate location.
S1 A D
Figure 6 The groundwater flow system has an area of 540m by 540m and the problem domain is divided into three areas with different hydraulic conductivities and recharge rates. The real source is located at S1 and A to H represents the monitoring wells.
The slash grids represent no flow boundary.
S1 A D
Figure 7 A larger suspicious areas delineated by the broken lines with totally 100 suspicious areas (5 rows × 5 columns × 4 layers). The hydrogeological conditions of the flow system are the same as those shown in Figure 6.
個人資料
姓名：楊博傑
生日：民國73年3月29日 出生地：嘉義市
電話：03-3759611
住址：桃園市樹林八街9號6樓
學歷：民國95年畢業於國立中興大學環境工程學系 民國97年畢業於國立交通大學環境工程研究所