Abstract

Due to the increasing demand for metals, the extractable grade of metal deposits has been decreasing and caused an increase in the amount of tailings. Increase in the volume of tailings requires proper attention to tailings disposal, the establishment of tailings dams, water consumption and prevention of environmental and groundwater pollution. Since tailings disposal consists of many stages such as discharge, thickening technology and location, and transportation, selection of the best disposal method is a complicated task. Nowadays, decision-making methods are widely used and they are very reliable and efficient. Therefore, a model based on fuzzy analytic hierarchy process (AHP) has been developed in this study to optimize tailings disposal method selection. In the model, 21 criteria and a wide range of alternatives have been introduced. The model has been applied to the Sangan Iron Ore Project (SIOP). The concentrator plant of SIOP will produce 75 million tons of tailings during the mine lifetime. Since the current disposal method wastes 1.5 million cubic metres of water annually and the project is located in a dry region, the proposed model has been used to investigate other options and the results show the filtered technique is the best alternative.

INTRODUCTION

Water crisis in the present century is a fundamental and global problem. Undoubtedly, water is one of the main bases of industrial development in any country. Due to the fact that Iran is located in an arid to semi-arid region, the importance of the issue is multiplied. The supply of water coming from natural resources cannot fulfill the needs of the industry single-handedly since mineral processing requires 1–2 tons of water to process (concentrate) each ton of minerals. Thereby, this problem gives rise to the inevitable recycling of water, which is done by tailings disposal systems (Watson et al. 2010). Hydrological studies in the region indicate that water is the most important and limiting factor for the development of Sangan City. Low air humidity coupled with the low amount of rainfall prevent the creation of permanent surface flows in the area. At the moment, a conventional tailings disposal system is in operation in the Sangan Iron Ore Project (SIOP). As a result, due to a very high rate of water loss, a daily volume of about 4,000 m³ (52 million cubic metres in the lifetime of project) of water is needed to compensate for the lost water at the tailings disposal site. Due to the climatic conditions of the location of the mine and the high demand of the project for water, the application of a tailings disposal method which minimizes water loss and recycles the water back to the concentrator is essential (Danieli Co. 2008).

In recent years, extensive studies have been carried out on the disposal of tailings and related subjects. Adiansyah et al. (2015) showed that existing frameworks for mine tailings management have significant weaknesses. Mine tailings management needs better factors in sustainability considerations. Barrera et al. (2015) evaluated the existing tailings management techniques in different tailings dams in Chile and compared different ways of reducing water consumption and dam failure prevention methods in seismic areas. Schoenberger (2016) studied the different tailings disposal methods with the aim of sustainable mining from environmental aspects. In the same year, another study reviewed the method of paste tailings disposal in tropical regions, and revealed the benefits of using this technology instead of conventional methods (Liu et al. 2016). Today, many mines are thinking about changing their tailings disposal method or using new technologies as an auxiliary system alongside their used thickeners. As can be seen, tailings management and water consumption are both vitally important in sustainable mining; however, the latter seems to be of primary importance. To overcome the shortcomings of tailings management, fuzzy analytic hierarchy process (AHP) has been proposed in the present research to optimize the decision-making procedure in this problem. Fuzzy AHP is one of the most famous and reliable methods among the multi-attribute decision-making (MADM) methods, and which has been widely used over managerial problems (Masoumi et al. 2014). Also, MADM techniques have been commonly used in mine management issues, as in Golestanifar & Bazzazi (2010), who applied this method to select a tailings impoundment site. Alavi & Akbari (2011) used the fuzzy AHP method to select suitable vegetation for the rehabilitation of the Sarcheshmeh copper mine. Shahba et al. (2017) applied MADM methods for mine waste management. Masoumi et al. (2014, 2017, 2018a, 2018b) have employed various MADM methods for mine reclamation project management and geotechnical improvement of embankments.

Since the purpose of this study is to develop a model using fuzzy AHP to select the best tailings disposal procedure among the possible methods, firstly, all the effective criteria and possible alternatives in this field have been identified to form a comprehensive resource, and then a framework based on fuzzy AHP has been proposed to solve the problem. Also, the performance of the method has been examined using a real case study.

MATERIALS AND METHODS

Determination of tailings disposal process alternatives

There are different methods that are mainly used in a whole tailings disposal process. These methods can be generally introduced as follows:

  • 1.

    Filtered tailings disposal: In this method, materials are thickened to more than 85% by weight (solid weight divided by total weight), which is done by vacuum filters or filter-pressed technologies. The filtered material is transferred to the tailing storage location by the conveyor or a truck (Caldwell & Crystal 2015).

  • 2.

    Paste disposal: These tailings are produced in special paste thickeners or in thickeners with ultra-high density and transferred by displacement pumps. The paste is a very useful tool for underground mine backfilling. Paste backfilling requires a high pumping pressure to transfer high-density backfill materials into the underground voids. The percentage of solids in this type of tailing is in the range 70–85% (Williams et al. 2008; Yilmaz & Mamadou 2017).

  • 3.

    Thickened tailings disposal: Tailings are thickened by high-density thickeners up to 65–72% by weight of solids. In this case, highly stable tailings are produced for disposal in tailings dams with low segregation and water release. In this method, integrating the design of the thickener, transport system and disposal strategy is really important and the key link between these three disciplines is the rheology of the tailings (Thompson & Moreno 2017).

  • 4.

    Conventional tailings disposal: Tailings are injected into conventional thickeners with up to 40–60% by weight of solids and transmitted to the dam in slurry form. Tailings particles during disposal go under segregation and a large amount of water is released via storage and accumulates in ponds. The conventional disposal methods require the use of dams, embankments or surface inhibitors as well as the use of cyclones or spigots for storage (Rashidinejad & Raoufsheibani 2004).

It should be noted that the options in this problem are not only classified based on tailings thickening technology, but also the place that they should be kept, discharge methods and transportation form several alternatives. Therefore, all possible alternatives in the tailings disposal process have been gathered in Table 1, which includes their abbreviations. One can combine various options in different steps and form a wide range of alternatives.

Table 1

Different parts of the tailings disposal process and their abbreviations

Parts of tailings disposal process Sub-group Abbr. 
Thickening technology Conventional thickener CON 
Paste thickener PAS 
High-density thickener TKN 
Filter FIL 
High-rate and paste thickener HXS 
Thickening place Concentrator COR 
Tailings storage facility TSF 
Concentrator and Facility CXF 
Transportation Pipe line PIP 
Truck TRU 
Conveyor COV 
Discharge Embankment EMK 
Cell CEL 
Paddock PDK 
Central tailings discharge CTD 
Parts of tailings disposal process Sub-group Abbr. 
Thickening technology Conventional thickener CON 
Paste thickener PAS 
High-density thickener TKN 
Filter FIL 
High-rate and paste thickener HXS 
Thickening place Concentrator COR 
Tailings storage facility TSF 
Concentrator and Facility CXF 
Transportation Pipe line PIP 
Truck TRU 
Conveyor COV 
Discharge Embankment EMK 
Cell CEL 
Paddock PDK 
Central tailings discharge CTD 

As shown in Table 1, the tailings disposal process consists of different parts and each part is divided into different sub-groups. There are various alternatives for tailings disposal; therefore, these could be applied in each project regarding the differences in climate, geotechnics, economy, geography, and other criteria.

Determination of effective criteria

Considering previous research and related reports, the most important factors in the case of selecting the best method of tailings disposal in mine projects are as follows:

  • 1.

    Technical factors

  • 2.

    Environmental factors

  • 3.

    Economic factors.

Upon investigating and studying the various tailings disposal methods as well as the various reports related to different projects, the factors have been divided into 21 criteria, which can be seen in Table 2.

Table 2

Categorization of effective factors to select the best tailings disposal alternatives

No. Description Abbr. No. Description Abbr. 
Technical Environmental 
Total tailing tt 14 Biological problems biop 
Slurry rheology reh 15 Ground water pollution gwp 
Thickening technology th 16 Surface water pollution swp 
Transportation technology tr 17 Earth pollution ep 
Separate discharge ds 18 Air pollution ap 
Water recovery wr Economic 
Air distance from concentrator ad 19 Study cost sc 
Climate cl 20 Capital cost cc 
Topography tp 21 Operating cost oc 
10 Geotechnics geo    
11 Earthquake eq    
12 Hydrology hl    
13 Hydrogeology hgeo    
No. Description Abbr. No. Description Abbr. 
Technical Environmental 
Total tailing tt 14 Biological problems biop 
Slurry rheology reh 15 Ground water pollution gwp 
Thickening technology th 16 Surface water pollution swp 
Transportation technology tr 17 Earth pollution ep 
Separate discharge ds 18 Air pollution ap 
Water recovery wr Economic 
Air distance from concentrator ad 19 Study cost sc 
Climate cl 20 Capital cost cc 
Topography tp 21 Operating cost oc 
10 Geotechnics geo    
11 Earthquake eq    
12 Hydrology hl    
13 Hydrogeology hgeo    

Decision-making model based on fuzzy AHP

The AHP method facilitates judgments and calculation preferences using pair-wise comparisons. It is also the best procedure to carry out pair-wise judgment comparisons. Nonetheless, human judgments are commonly imprecise, hence the priorities are not determined by a precise numeric amount. Fuzzy theory was developed by Zadeh to overcome imprecise judgments and preferences. Many of the weighing methods of attributes and alternatives are intellectually carried out by qualitative scales, whereas logical determination of the priorities is difficult for decision-makers in general. Therefore, in order to carry out precise pair-wise judgment comparisons and decision-making, fuzzy sets theory and the AHP method were combined (Masoumi et al. 2014).

Considering the use of fuzzy AHP with triangular fuzzy numbers, their mathematical operations are defined as Equations (1)–(3): 
formula
(1)
 
formula
(2)
 
formula
(3)
where M is a triangular fuzzy number, M1 = (l1, m1, u1) and M2 = (l2, m2, u2), l, m and u are lower, mean and upper limits of a triangular fuzzy number, respectively.
After creating a pair-wise comparison matrix, the synthetic extent value is calculated by Equation (4): 
formula
(4)
Si is also a triangular fuzzy number; i and k are rows and j is columns.
The next step is to calculate the degree of possibility with Equation (5). Note that to compare S1 and S2 it needs both values of V (S1S2) and V (S2S1) 
formula
(5)
The degree of possibility for a convex fuzzy number greater than k is then calculated, and the convex fuzzy numbers can be defined by: 
formula
(6)
for k = 1, 2,…, n and ki. Then the normalized weight vector of criteria is given by Equation (7) and finally the ranking of alternatives is given by Equation (8): 
formula
(7)
 
formula
(8)
where W is a non-fuzzy number, A is an alternative and Equation (8) should be implemented for all alternatives so they can be comparable, and C is each criterion (Masoumi et al. 2018b). Table 3 represents the scale for pair-wise comparison in fuzzy AHP. It should be noted that the numbers used in this table are not the only optimal numbers available and the does not cause any errors in the results as long as the order of the priorities does not change (Akdoğan et al. 2015).
Table 3

Triangular fuzzy conversion scale (Akdoğan et al. 2015)

Definition Triangular fuzzy scale Triangular fuzzy reciprocal scale 
Just equal (1, 1, 1) (1, 1, 1) 
Rather equal preference (1/2, 1, 3/2) (2/3, 1, 2) 
Weak preference (1, 3/2, 2) (1/2, 2/3, 1) 
Strong preference (3/2, 2, 5/2) (2/5, 1/2, 2/3) 
Very strong preference (2, 5/2, 3) (1/3, 2/5, 1/2) 
Absolute preference (5/2, 3, 7/2) (2/7, 1/3, 2/5) 
Definition Triangular fuzzy scale Triangular fuzzy reciprocal scale 
Just equal (1, 1, 1) (1, 1, 1) 
Rather equal preference (1/2, 1, 3/2) (2/3, 1, 2) 
Weak preference (1, 3/2, 2) (1/2, 2/3, 1) 
Strong preference (3/2, 2, 5/2) (2/5, 1/2, 2/3) 
Very strong preference (2, 5/2, 3) (1/3, 2/5, 1/2) 
Absolute preference (5/2, 3, 7/2) (2/7, 1/3, 2/5) 

The procedure of the tailings disposal decision-making model is presented in Figure 1. It simplifies the understanding of the model procedure.

Figure 1

Tailings disposal decision-making model procedure.

Figure 1

Tailings disposal decision-making model procedure.

RESULTS AND DISCUSSION

Description of SIOP as a case study

Sangan Iron Ore mines are situated in three adjacent mineral areas on the western, central and eastern sides at longitude 60°16′ E and latitude 34°24′ N, in Khorasan Razavi province (300 km southeast of Mashhad) and 16 km north of Sangan city. The relative humidity of the area in the rainy months is more than 55% (about 57% to 59%) and in dry and non-rainy seasons it drops to about 26% to 28%. The average rainfall has been reported to be about 60 mm per year, which indicates an arid climate in addition to a general lack of moisture and precipitation (Danieli Co. 2008).

The concentration plant is designed with a productivity of 1.3 million tons (based on dry concentrate) per year. Thickeners treat slurry from the factory with a nominal capacity of 3,000 cubic metres per hour. In order to improve the concentration process and achieve a suitable concentration of slurry (density of solids up to 60%), coagulants are added to the thickeners. Conventional thickeners at the concentration plant are shown in Figure 2. The thickener residual slurry is sent to the discharge pump tank and the final tailing is pumped to the tailings dam (Kanikavan Sharq Engineering Co. 2010).

Figure 2

Concentrator and thickeners.

Figure 2

Concentrator and thickeners.

The tailings storage facility (TSF) is located in the southeastern part of the concentration site. The level of the crown in the first phase is 1,080 m, which after completion of this phase in a 5 year period will be raised in three stages, as at each stage 5 metres is added to the crown height. The ultimate level of the dam is approximately 1,100 m. The total capacity of the disposal cells is 15 million tons (Danieli Co. 2007). Figure 3 shows the operation of the tailings dam in the first phase.

Figure 3

First phase of tailings dam.

Figure 3

First phase of tailings dam.

Identification of the applicable alternatives for SIOP

For SIOP, after investigation of different methods from Table 1, five applicable methods are identified. These methods are described in Table 4.

Table 4

Applicable tailings disposal procedures for SIOP

Alternative number Disposal method Evaluating its feasibility to be implemented in Sangan 
Disposal of the slurry in the valley, using the TSF and surrounding wall (embankment barrier) via down-stream, up-stream and central-line methods. In the country, there are plenty of TSF for base-metal mines using a retaining wall. Due to the dry weather of the region and the very low precipitation rate versus evaporation, this method is technically possible for SIOP. But because of the flat topography of the region, an integrated embankment is also required. 
Discharging slurry tailings within consecutive cells with stepwise evacuation of tailings between cells to increase the density and dryness. This method has been recommended for Sangan by well-known and expert companies. 
Paste tailings disposal method using a central drain at a relatively flat surface with a floating water accumulation system on the back of a surrounding wall. Regarding the topography of the area and surface conditions, this method can be used in Sangan. 
Thickened tailings disposal method, the density of tailing in this method is between the conventional slurry and paste tailings. This method can be used in Sangan and given the region's conditions and water recovery problems, it should be studied further. 
Filtered tailings disposal. The rate of water recovery in this method is very high and given the climatic conditions of this area, it is a good method. 
Alternative number Disposal method Evaluating its feasibility to be implemented in Sangan 
Disposal of the slurry in the valley, using the TSF and surrounding wall (embankment barrier) via down-stream, up-stream and central-line methods. In the country, there are plenty of TSF for base-metal mines using a retaining wall. Due to the dry weather of the region and the very low precipitation rate versus evaporation, this method is technically possible for SIOP. But because of the flat topography of the region, an integrated embankment is also required. 
Discharging slurry tailings within consecutive cells with stepwise evacuation of tailings between cells to increase the density and dryness. This method has been recommended for Sangan by well-known and expert companies. 
Paste tailings disposal method using a central drain at a relatively flat surface with a floating water accumulation system on the back of a surrounding wall. Regarding the topography of the area and surface conditions, this method can be used in Sangan. 
Thickened tailings disposal method, the density of tailing in this method is between the conventional slurry and paste tailings. This method can be used in Sangan and given the region's conditions and water recovery problems, it should be studied further. 
Filtered tailings disposal. The rate of water recovery in this method is very high and given the climatic conditions of this area, it is a good method. 

Since the paste disposal method (alternative number 3) and filtered tailings disposal method (alternative number 5) can be implemented in different ways in the present case and each of them has its own characteristics, for more accuracy in choosing and selecting the optimal system, each of these two methods is subdivided into three individual alternatives as shown in Table 5. Also, for the filtered tailings disposal method, the paddock method is considered.

Table 5

Categorization of paste and filtered tailings disposal methods into subgroups

Main method Alternative number Subgroups 
Disposal of paste tailings 3-1 Thickening by paste thickener at TSF 
3-2 Thickening by high-rate thickener at the place of concentrator and with paste thickener at TSF 
3-3 Thickening by paste thickener at concentrator 
Disposal of filtered tailings 5-1 Filtration at concentrator and transportation of the tailing cake to the depot location by truck 
5-2 Filtration at concentrator and transportation of the tailing cake to the depot location by conveyor 
5-3 Filtration at TSF 
Main method Alternative number Subgroups 
Disposal of paste tailings 3-1 Thickening by paste thickener at TSF 
3-2 Thickening by high-rate thickener at the place of concentrator and with paste thickener at TSF 
3-3 Thickening by paste thickener at concentrator 
Disposal of filtered tailings 5-1 Filtration at concentrator and transportation of the tailing cake to the depot location by truck 
5-2 Filtration at concentrator and transportation of the tailing cake to the depot location by conveyor 
5-3 Filtration at TSF 

According to Tables 4 and 5, all the applicable strategies for SIOP are finally introduced in an abbreviated form in Table 6 as model alternatives.

Table 6

Nomination of the alternatives for tailings disposal in the Sangan project

Alternatives Technique no. 
CON-COR-PIP-EMK 
CON-COR-PIP-CEL 
PAS-TSF-PIP-CTD 3-1 
HXS-CXF-PIP-CTD 3-2 
PAS-COR-PIP-CTD 3-3 
TKN-COR-PIP-CEL 
FIL-COR-TRU-PDK 5-1 
FIL-COR-COV-PDK 5-2 
FIL-TSF-COV-PDK 5-3 
Alternatives Technique no. 
CON-COR-PIP-EMK 
CON-COR-PIP-CEL 
PAS-TSF-PIP-CTD 3-1 
HXS-CXF-PIP-CTD 3-2 
PAS-COR-PIP-CTD 3-3 
TKN-COR-PIP-CEL 
FIL-COR-TRU-PDK 5-1 
FIL-COR-COV-PDK 5-2 
FIL-TSF-COV-PDK 5-3 

Application of decision model to select the best alternative

There is a decision hierarchy in fuzzy AHP problems from goal to alternatives, where criteria are situated between them. As for this research, the first level is the purpose (selection of the best method for tailings disposal), the second level is the criteria and the third level is the alternatives. In Figure 4, the hierarchy structure of the decision-making process used in this project is represented. As shown in this figure, all criteria are directly connected to the goal. On the other hand, every alternative is connected to all criteria, which is their route to the goal. It should be noted that every alternative should have connection to all criteria but the authors have avoided drawing these for the other options so as not to cause confusion. In order to achieve the purpose of the research, first of all, the weight of all criteria must be determined (arrows of criteria to the goal). Simultaneously, the weights of the alternatives should be determined in relation to every individual criterion (arrows of alternatives to criterion). At last, in order to determine the final weight of each alternative and rank them based on their importance weights, Equation (8) should be used.

Figure 4

Hierarchy of decision-making in this research.

Figure 4

Hierarchy of decision-making in this research.

According to the number of the criteria in this model, a total of 22 matrices are formed. The initial matrix is 21 × 21, which has been used to compare the degree of importance of different criteria in relation to the goal, and 21 sets of 9 × 9 matrices that have been used to compare alternatives in relation to different criteria.

As shown in Table 7 and as expected, the rate of water recycling criteria has the highest level of importance in the selection of tailings disposal method and regarding the importance of environmental issues, and groundwater pollution resources are at second place. The ranking of criteria is also shown in Figure 5 based on their importance weights.

Table 7

Normalized weights of criteria

Wi Weight of criteria Wi Weight of criteria 
Wcl 0.05332 Wgwp 0.05989 
Wtp 0.05716 Wswp 0.05283 
Wgeo 0.03955 Wep 0.04880 
Weq 0.05882 Wap 0.0481 
Whl 0.04655 sc 0.00932 
Whgeo 0.04523 Wcc 0.04264 
Wbiop 0.05003 Woc 0.05157 
Wtt 0.04553 Wtr 0.04593 
Wreh 0.0499 Wds 0.04399 
Wth 0.05823 Wwr 0.06043 
Wad 0.03209   
Wi Weight of criteria Wi Weight of criteria 
Wcl 0.05332 Wgwp 0.05989 
Wtp 0.05716 Wswp 0.05283 
Wgeo 0.03955 Wep 0.04880 
Weq 0.05882 Wap 0.0481 
Whl 0.04655 sc 0.00932 
Whgeo 0.04523 Wcc 0.04264 
Wbiop 0.05003 Woc 0.05157 
Wtt 0.04553 Wtr 0.04593 
Wreh 0.0499 Wds 0.04399 
Wth 0.05823 Wwr 0.06043 
Wad 0.03209   
Figure 5

Rankings of criteria importance weights.

Figure 5

Rankings of criteria importance weights.

Above, the importance weights of the criteria have been obtained. As mentioned, the procedure should be repeated in order to calculate the importance weights of alternatives regarding every criterion. Finally, to get the final weight of each alternative, the weight of each arrow (in the second row of Figure 4) should be multiplied by the weight of its symmetric arrow (in the first row of Figure 4) and the results must be added. This operation has been described with Equation (8). Alternatives' weights are shown in Table 8.

Table 8

Final weights of alternatives

Alternatives Technique no. Final weight 
EMK-COR-CON-PIP 0.070614 
CEL-COR-CON-PIP 0.07198 
CTD-TSF-PAS-PIP 3-1 0.107417 
CTD-CXF-HXS-PIP 3-2 0.099642 
CTD-COR-PAS-PIP 3-3 0.09436 
CEL-COR-TKN-PIP 0.08813 
PDK-COR-FIL-TRU 5-1 0.150366 
PDK-COR-FIL-COV 5-2 0.1637587 
PDK-TSF-FIL-COV 5-3 0.153644 
Alternatives Technique no. Final weight 
EMK-COR-CON-PIP 0.070614 
CEL-COR-CON-PIP 0.07198 
CTD-TSF-PAS-PIP 3-1 0.107417 
CTD-CXF-HXS-PIP 3-2 0.099642 
CTD-COR-PAS-PIP 3-3 0.09436 
CEL-COR-TKN-PIP 0.08813 
PDK-COR-FIL-TRU 5-1 0.150366 
PDK-COR-FIL-COV 5-2 0.1637587 
PDK-TSF-FIL-COV 5-3 0.153644 

The higher importance weight an alternative has, the better an alternative it is. As shown in Table 8, considering the benefits of the filtered tailings disposal method and also the paste disposal, these methods take priority over the other applicable methods in the SIOP. Their prioritization changes only in terms of their transport system. The method that is currently underway in the project (due to the high water loss and ensuing environmental problems), as well as the high cost of the implementation of the tailings dam, is in the penultimate position. Finally, the filtering option at the concentrator and transferring the tailings cake via the conveyor to the storage site is recommended for the Sangan project.

CONCLUSION

In order to optimize the selection of the most compatible tailings disposal method, a decision-making model based on fuzzy AHP has been developed in this research. The model has introduced various methods as alternatives for tailings disposal. In addition, the most important criteria, which affect choosing the best alternative, have been classified. Finally, SIOP has been used by the model as a case study to assess its performance. Regarding use of the model, the following has been concluded:

  • 1.

    Due to the disadvantages of the conventional tailings disposal methods (methods 1 and 2 in this project), such as low water recovery, low tailings stabilization and safety, high occupancy and low reconstruction potential, the model properly shows this method has a low score for implementation in the SIOP.

  • 2.

    Considering the benefits of the filtered tailings disposal method, such as the highest degree of water recovery, better environmental conditions in the storage site, less contamination of groundwater due to the lack of water with tailings and the least penetration and also the faster vegetation stability after reconstruction, as predicted, it was the best option for implementation from technical, economic and environmental points of view in the SIOP, which has the highest importance weights among the alternatives.

  • 3.

    One of the most important results of this research is to provide a ranking for effective criteria in the selection of the tailings disposal method for processing, which will be very useful for future studies.

REFERENCES

REFERENCES
Adiansyah
J. S.
,
Rosano
M.
,
Vink
S.
&
Keir
G.
2015
A framework for a sustainable approach to mine tailings management: disposal strategies
.
Journal of Cleaner Production
108
(
Part A
),
1050
1062
.
Akdoğan
A. A.
,
Doğan
N. O.
&
Cingöz
A.
2015
Coopetition as a business strategy: determining the effective partner selection criteria using fuzzy AHP
.
International Review of Management and Business Research
4
,
137
151
.
Alavi
I.
&
Akbari
A. D.
2011
Plant type selection for Sarcheshmeh Copper Mine reclamation by Fuzzy-AHP method
. In:
22nd World Mining Congress & Expo
,
Aydoğdu Ofset, Ankara, Turkey
, pp.
665
673
.
Barrera
S.
,
Cacciuttolo
C.
&
Caldwell
J.
2015
Reassessment of best available tailings management practices
. In:
Proceedings Tailings and Mine Waste 2015
,
Vancouver, BC, Canada
.
Caldwell
J. A.
&
Crystal
C.
2015
Filter-pressed tailings facility design, construction and operating guidelines
. In:
Proceedings Tailings and Mine Waste 2015
,
Vancouver, BC, Canada
.
Danieli Co.
2007
Tailings Dams Design Report for SIOP
.
Prepared by AMEC America Limited
.
Danieli Co.
2008
Mining Report for SIOP
.
Prepared by AMEC America Limited
.
Golestanifar
M.
&
Bazzazi
A. A.
2010
TISS: A decision framework for tailing impoundment site selection
.
Environmental Earth Sciences
61
(
7
),
1505
1513
.
Kanikavan Sharq Engineering Co.
2010
Tailing Dam Design Evaluation Report
.
SIOP
,
Iran
.
Liu
Q.
,
Liu
D.
,
Liu
X.
,
Gao
F.
&
Li
S.
2016
Research and application of surface paste disposal for clay-sized tailings in tropical rainy climate
.
International Journal of Mineral Processing
157
,
227
235
.
Masoumi
I.
,
Naraghi
S.
,
Rashidinejad
F.
&
Masoumi
S.
2014
Application of fuzzy multi-attribute decision-making to select and to rank the post-mining land-use
.
Environmental Earth Sciences
72
(
1
),
221
231
.
doi: 10.1007/s12665-013-2948-0
.
Masoumi
I.
,
Ahangari
K.
&
Noorzad
A.
2017
Reliable monitoring of embankment dams with optimal selection of geotechnical instruments
.
Structural Monitoring and Maintenance
4
(
1
),
85
105
.
doi:10.12989/smm.2017.4.1.085
.
Masoumi
I.
,
Ahangari
K.
&
Noorzad
A.
2018a
Optimal monitoring instruments selection using innovative decision support system framework
.
Smart Structures and Systems
21
(
1
),
123
137
. doi: 10.12989/sss.2018.21.1.123.
Masoumi
I.
,
Ahangari
K.
&
Noorzad
A.
2018b
Integrated fuzzy decision approach for reliability improvement of dam instrumentation and monitoring
.
Journal of Structural Integrity and Maintenance
3
(
2
),
114
125
.
doi: 10.1080/24705314.2018.1461546
.
Rashidinejad
F.
&
Raoufsheibani
F.
2004
Tailings Disposal Options Study at Sungun Copper Mine
.
MPES
,
Wroclaw
,
Poland
, pp.
857
863
.
Thompson
N.
,
Moreno
P.
2017
Thickened tailings deposition for closure
. In:
20th International Seminar on Paste and Thickened Tailings
(
Wu
A.
&
Jewell
R.
, eds),
Beijing, China
, pp.
226
234
.
Watson
A. H.
,
Corser
P. G.
,
Garces Pardo
E. E.
,
Lopez Christian
T. E.
,
Vandekeybus
J.
2010
A comparison of alternative tailings disposal methods – the promises and realities
. In:
Proceedings of the First International Seminar on the Reduction of Risk in the Management of Tailings and Mine Waste
(
Jewell
R.
&
Fourie
A. B.
, eds),
Australian Centre for Geomechanics
,
Perth, Australia
, pp.
499
514
.
Williams
M. P. A.
,
Seddon
K. D.
,
Fitton
T. G.
2008
Surface disposal of paste and thickened tailings: a brief history and current confronting issues
. In:
Eleventh International Seminar on Paste and Thickened Tailings
(
Jewell
R.
,
Fourie
A. B.
,
Slatter
P.
&
Paterson
A.
, eds),
Australian Centre for Geomechanics
,
Perth, Australia
, pp.
143
164
.
Yilmaz
E.
&
Mamadou
F.
2017
Paste Tailings Management
.
Springer
,
Cham, Switzerland
.