Failure risk of brazilian tailings dams: a data mining approach

SANTOS, TATIANA B.; OLIVEIRA, RUDINEI M.

doi:10.1590/0001-3765202120201242

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ENGINEERING SCIENCES • An. Acad. Bras. Ciênc. 93 (4) • 2021 • https://doi.org/10.1590/0001-3765202120201242 copy

Failure risk of brazilian tailings dams: a data mining approach

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

This paper proposes the use of a hybrid method that combines Biased Random Key Genetic Algorithm (BRKGA) with a local search heuristic to separate Brazilian tailing dam data into groups. The goal was identifying dams similar to Fundão and B1 failed dams. The groups were created by solving the clustering problem by BRKGA. The clustering problem consists in separating a set of objects into groups such that members of each group are similar to each other. The data was composed by 427 dams, with the actual 425 dams of Brazilian Register of Tailing Dams and the two Brazilian failed dams from the last years. Computational experiments considering real data available are presented to demonstrate the efficacy of the proposed method producing feasible solutions. Thus, it is expected that the good results can be applied in the identification of tailings dams with risk potentials, assisting in the identification of these dams.

Key words
Tailing dams; clustering problem; biased random key genetic algorithm; mining

	Variable
	Method of construction
Description	Undefined	Downstream	Centerline	Upstream or unknown	Single dyke
Rating	5	4	3	2	1
	Risk category
Description	High	Medium			Low
Rating	3	2			1
	Associated potential damage
Description	High	Medium			Low
Rating	3	2			1
	Actual volume (millions of m³)
	Actual height (meters)

ID	Dam	Method of construction	Risk category	Associated potential damage	Volume in the failure moment (m³)	Height in the failure moment (m)
426	Fundão (Germano)	Upstream	Low	High	91866000	130
427	B1 (Córrego do Feijão)	Upstream	Low	High	11700000	86

ID	Dam	Method of construction x1	Risk category x2	Associated potential damage x3	Actual volume (m³) x4	Actual height (m) x5
1	0-1	1	1	2	27700000	22
2	103 (Cruz)	1	1	2	924000	10.30
3	111 (Índio)	1	1	2	48873	5
4	158 A-1	2	1	3	53380000	30
5	161 A-2	1	1	2	1018054	22
6	444 A-3	1	1	2	886241	14.70
7	81-1	1	1	2	75522	4
8	Pau D’Arco	1	1	2	52800	18
9	Barragem da cava	2	1	2	1755555	25
10	Mario Cruz	3	2	2	25366731	28

ID	Dam	Method of construction z1	Risk category z2	Associated potential damage z3	Actual volume (m³) z4	Actual height (m) z5
1	0-1	0.2500	0.5000	1.0000	0.135802	0.069413
2	103 (Cruz)	0.2500	0.5000	1.0000	0.063580	0.002315
3	111 (Índio)	0.2500	0.5000	1.0000	0.030864	0.000122
4	158 A-1	0.5000	0.5000	1.5000	0.185185	0.133765
5	161 A-2	0.2500	0.5000	1.0000	0.135802	0.002551
6	444 A-3	0.2500	0.5000	1.0000	0.090741	0.002221
7	81-1	0.2500	0.5000	1.0000	0.024691	0.000189
8	Pau D’Arco	0.2500	0.5000	1.0000	0.111111	0.000132
9	Barragem da cava	0.5000	0.5000	1.0000	0.154321	0.004399
10	Mario Cruz	1.0000	1.0000	1.0000	0.172840	0.063566

Index	1	2	3	4	5	6	7	8	9	10
Random keys	0.69	0.22	0.99	0.45	0.01	0.86	0.19	0.55	0.15	0.70

Index	2	4	5	7	9	1	3	6	8	10
Random keys	0.22	0.45	0.01	0.19	0.15	0.69	0.99	0.86	0.55	0.70
Clusters	1	1	1	1	1	2	2	2	2	2

Parameters BRKGA	Meaning	Value
P	Number of individuals in population	1000
Gen	Number of generations	1000
p _e	Size of the elite set in population	0.2
p _m	Number of mutants to be introduced in population at each generation	0.4
ρ _e	Probability that an allele is inherited	0.6

Clusters	Euclidean	Manhattan	Cosine	Pearson
2	105.612806	144.162819	9.471279	20.510861
3	84.608211	117.372262	5.918690	12.333456
4	74.439174	102.581991	4.237784	8.813047
5	63.586627	87.250852	3.783845	7.294127
6	54.872264	82.436485	3.052754	6.709703
6	51.707632	65.781028	2.931459	5.253705
8	47.912183	56.900554	2.681774	5.079224
9	42.319854	53.334356	2.160351	4.772565
10	40.945731	48.186336	2.116750	4.282325

Emergency Level	Tailing dam	Company	City	ID	Source
Level 3	B3/B4	Minerações Brasileiras Reunidas Sa Filial: MBR Paraopeba	Nova Lima	55	(Neves et al. 2020NEVES LP, GONÇALVES JÚNIOR ES, SANTOS AAG, SOUSA GDB, SANTOS ACB, CRUZ CO, AMORIM MC, SANTOS JB & FREITAS AR. 2020. Report Semanal Barragens de Mineração 02 - 08/06/2020. http://www.anm.gov.br/assuntos/barragens/boletim-semanal-de-barragens-de-mineracao/boletim-semanal-2020-06-08-v5. http://www.anm.gov.br/assuntos/barragens... )
	Forquilha I	Vale S A Filial: Vale Itabiritos	Ouro Preto	195
	Forquilha III	Vale S A Filial: Vale Itabiritos	Ouro Preto	197
	Sul superior	Vale S A Filial: Vale Minas Centrais	Barão de cocais	243
Level 2	Barragem de Rejeitos	Arcelormittal Mineração Serra Azul S.a.	Itatiaiuçu	119
	Capitão do mato	Vale S A Filial: Vale Vargem Grande	Nova Lima	150
	Doutor	Vale S A Filial: Vale Mariana	Ouro Preto	191
	Forquilha II	Vale S A Filial: Vale Itabiritos	Ouro Preto	196
	Grupo	Vale S A Filial: Vale Itabiritos	Ouro Preto	201
	Sul Inferior	Vale S A Filial: Vale Minas Centrais	Barão de Cocais	242

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[1] Correspondence to: Tatiana B. Santos E-mail: tatiana.santos@ufop.edu.br