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Pregled bibliografske jedinice broj: 1139260

Influence of Meteorological Parameters on Explosive Charge and Stemming Length Predictions in Clay Soil during Blasting Using Artificial Neural Networks


Leskovar, Karlo; Težak, Denis; Mesec, Josip; Biondić, Ranko
Influence of Meteorological Parameters on Explosive Charge and Stemming Length Predictions in Clay Soil during Blasting Using Artificial Neural Networks // Applied Sciences-Basel, 11 (2021), 16; 1307646, 17 doi:10.3390/app11167317 (međunarodna recenzija, članak, znanstveni)


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Naslov
Influence of Meteorological Parameters on Explosive Charge and Stemming Length Predictions in Clay Soil during Blasting Using Artificial Neural Networks

Autori
Leskovar, Karlo ; Težak, Denis ; Mesec, Josip ; Biondić, Ranko

Izvornik
Applied Sciences-Basel (2076-3417) 11 (2021), 16; 1307646, 17

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
clay soil ; blasting ; meteorological parameters ; Artificial Neural Networks ; LSTM

Sažetak
The influence of the meteorological parameters (precipitation and air temperature) during blasting in clay has a direct impact on the success of blasting. In the case of large amounts of precipitation (rain and snow) recorded in the subject area, blasting in clays cannot be carried out due to the grain of the clay and the inability to access the subject area. Moreover, the air temperature in the subject area affects the blasting performance. The most ideal temperature for blasting in clays is between 15 and 25 °C because then the clay has the best geotechnical characteristics. The research was conducted on the exploitation field Cukavec II, which is located near the city of Varaždin in the Republic of Croatia. Amount of precipitation and air temperature were considered to obtain the best blasting effect. Influence of meteorological parameters on the amount of the explosive charge and stemming length when blasting in clays was demonstrated via models based on Artificial Neural Networks (ANN). The ANN model network consists of a Long Short-term Memory (LSTM) part to process time dependent meteorological data, and fully connected layers to process blasting input data. Two types of explosive charges were compared, Pakaex and Permonex V19.

Izvorni jezik
Engleski

Znanstvena područja
Građevinarstvo, Računarstvo, Rudarstvo, nafta i geološko inženjerstvo, Interdisciplinarne tehničke znanosti



POVEZANOST RADA


Ustanove:
Geotehnički fakultet, Varaždin

Profili:

Avatar Url Josip Mesec (autor)

Avatar Url Ranko Biondić (autor)

Avatar Url Denis Težak (autor)

Avatar Url Karlo Leskovar (autor)

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Leskovar, Karlo; Težak, Denis; Mesec, Josip; Biondić, Ranko
Influence of Meteorological Parameters on Explosive Charge and Stemming Length Predictions in Clay Soil during Blasting Using Artificial Neural Networks // Applied Sciences-Basel, 11 (2021), 16; 1307646, 17 doi:10.3390/app11167317 (međunarodna recenzija, članak, znanstveni)
Leskovar, K., Težak, D., Mesec, J. & Biondić, R. (2021) Influence of Meteorological Parameters on Explosive Charge and Stemming Length Predictions in Clay Soil during Blasting Using Artificial Neural Networks. Applied Sciences-Basel, 11 (16), 1307646, 17 doi:10.3390/app11167317.
@article{article, author = {Leskovar, Karlo and Te\v{z}ak, Denis and Mesec, Josip and Biondi\'{c}, Ranko}, year = {2021}, pages = {17}, DOI = {10.3390/app11167317}, chapter = {1307646}, keywords = {clay soil, blasting, meteorological parameters, Artificial Neural Networks, LSTM}, journal = {Applied Sciences-Basel}, doi = {10.3390/app11167317}, volume = {11}, number = {16}, issn = {2076-3417}, title = {Influence of Meteorological Parameters on Explosive Charge and Stemming Length Predictions in Clay Soil during Blasting Using Artificial Neural Networks}, keyword = {clay soil, blasting, meteorological parameters, Artificial Neural Networks, LSTM}, chapternumber = {1307646} }
@article{article, author = {Leskovar, Karlo and Te\v{z}ak, Denis and Mesec, Josip and Biondi\'{c}, Ranko}, year = {2021}, pages = {17}, DOI = {10.3390/app11167317}, chapter = {1307646}, keywords = {clay soil, blasting, meteorological parameters, Artificial Neural Networks, LSTM}, journal = {Applied Sciences-Basel}, doi = {10.3390/app11167317}, volume = {11}, number = {16}, issn = {2076-3417}, title = {Influence of Meteorological Parameters on Explosive Charge and Stemming Length Predictions in Clay Soil during Blasting Using Artificial Neural Networks}, keyword = {clay soil, blasting, meteorological parameters, Artificial Neural Networks, LSTM}, chapternumber = {1307646} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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