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Wyświetlanie 1-2 z 2
Tytuł:
Evaluation of Tunnel Contour Quality Index on the Basis of Terrestrial Laser Scanning Data
Autorzy:
Dybeł, Piotr
Dybeł, Katarzyna
Cieślik, Jerzy
Powiązania:
https://bibliotekanauki.pl/articles/1845142.pdf
Data publikacji:
2021
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
TCI
tunnel
contour quality
terrestrial laser scanning
TLS
overbreak
contour roughness
Opis:
The Tunnel Contour Quality Index (TCI) is an index established by Kim and Bruland for an effective management of a tunnel contour quality. It is estimated on a basis of measurements of two contour profiles within a single blasting round, using a laser profiler. However, the representativeness of measurement results obtained that way for the assessment of a contour quality of the entire blasting round is disputable. Terrestrial laser scanning (TLS) technology, combined with available numerical surface modeling tools, enables development of three-dimensional models of a monitored surface. The article reports results of TCI calculations based on TLS data. The presented TLS technique is based not only on selected cross-sections of the tunnel contour but also on the description of the morphology of the tunnel contour surface. The case study concerns measurements of the "Mały Luboń" tunnel niche, located in Naprawa, Poland. The TCI values for three blasting rounds were determined in accordance with Kim and Bruland’s guidelines and were compared to TCI values determined with the proposed TLS technique. On a basis of this comparison, it can be concluded that the results obtained with the TLS technique are more reliable and representative for description of the contour quality of the entire blasting round than results obtained with the laser profiling technique.
Źródło:
Studia Geotechnica et Mechanica; 2021, 43, 3; 255-269
0137-6365
2083-831X
Pojawia się w:
Studia Geotechnica et Mechanica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Unplanned dilution prediction in open stope mining: developing new design charts using Artificial Neural Network classifier
Autorzy:
Korigov, Sultan
Adoko, Amoussou Coffi
Sengani, Fhatuwani
Powiązania:
https://bibliotekanauki.pl/articles/2201390.pdf
Data publikacji:
2022
Wydawca:
Główny Instytut Górnictwa
Tematy:
open stope
dilution graph
stope overbreak
neural network classifier
system otwartych komór
klasyfikator sieci neuronowej
Opis:
Minimizing dilution is essential in open stope mine design as excessive unplanned dilution can compromise the operation's profitability. One of the main challenges associated with the empirical dilution graph method used to design open stopes is how to determine the boundary of the dilution zones objectively. Hence, this paper explores the implementation of machine learning classifiers to bridge this gap in the conventional dilution graph method. Stope performance data consisting of the stope dilution (unplanned dilution), the modified stability number, and the hydraulic radius were compiled from a mine located in Kazakhstan. First, the conventional dilution graph methods were used to assess the dilution. Next, a Feed-Forward Neural Network (FFNN) classifier was implemented to predict each level of dilution. Overall, the FFNN results indicated that 97% of the stope surfaces were correctly classified, indicating an excellent classification performance, while the conventional dilution graph method did not show a good performance. In addition, the outputs of the FFNN were used to plot new dilution graphs with a probabilistic interpretation illustrating its practicability. It was concluded that the FFNN-based classifier could be a useful tool for open stope design in underground mines.
Źródło:
Journal of Sustainable Mining; 2022, 21, 2; 157--168
2300-1364
2300-3960
Pojawia się w:
Journal of Sustainable Mining
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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