Araştırma Makalesi
BibTex RIS Kaynak Göster

Basamak Patlatma Tasarımı ve Analizi Yapabilen Bir Mobil Uygulama Yazılımının Geliştirilmesi

Yıl 2025, Cilt: 40 Sayı: 3, 725 - 741, 26.09.2025
https://doi.org/10.21605/cukurovaumfd.1708218

Öz

Bu çalışmada, patlatma tasarımı ve analizleri süreçlerini bütünleşik bir şekilde gerçekleştirilebilen mobil bir uygulama yazılımı geliştirilmiştir. iRockBlast adı verilen bu uygulama, kullanıcıdan alınan saha verileri ile birincil patlatma tasarımı yapabilmekte; yer titreşimi, hava şoku, kaya savrulması gibi çevresel etkileri ve parça boyut dağılım oranlarını tahmin edebilmektedir. Uygulama, Flutter uygulama geliştirme aracı ve Dart programlama dili kullanılarak iOS ve Android mobil işletim sistemlerinde çalışabilecek biçimde geliştirilmiştir. Literatür bilgiler ile oluşturulan algoritmalar üzerine inşa edilmiştir. Bir vaka çalışması ile uygulamanın doğruluğu test edilmiş ve saha sonuçları ile yüksek düzeyde uyum sağladığı gösterilmiştir. Geliştirilen yazılım, mevcut diğer uygulamalardan farklı olarak tasarım ve analiz aşamalarında yenilikler sunmaktadır. Bu uygulama, patlatma operasyonlarının planlanması aşamasında zaman verimliliği ve karar desteği sağlamaktadır.

Kaynakça

  • 1. Ceylanoğlu, A., Kahriman, A. ve Demirci, A. (1993). Delme patlatmanın önemi, kullanıldığı alanlar ve maden mühendisliği ile ilgisi. 1. Delme ve Patlatma Sempozyumu, Ankara, Türkiye.
  • 2. MacKenzie, A.S. (1966). Cost of Explosives – Do You Evaluate it Properly? Mining Congress Journal, 52(5), 32-41.
  • 3. ISEE (International Society of Explosives Engineers), (2015). Field practice guidelines for blasting seismographs. International Society of Explosives Engineers, Cleveland, USA.
  • 4. Jimeno, C.L., Jimeno, E.L. & Carcedo, F.J.A. (1995). Drilling and Blasting of Rocks. Ramiro, Y.V. (Çev.), A.A. Balkema Publishers, Brookfield.
  • 5. Karadoğan, A. (2008). Patlatmadan kaynaklanan titreşimler için ulusal yapı hasar kriterlerinin oluşturulabilirliğinin araştırılması. Doktora tezi, İstanbul Üniversitesi Fen Bilimleri Enstitüsü, 187.
  • 6. Kalaycı Şahinoğlu, Ü. (2024). Patlatma sonucu meydana gelen hava şoku ve partikül madde yayılımı arasındaki ilişkinin araştırılması. Çukurova Üniversitesi, Mühendislik Fakültesi Dergisi, 39(3), 831-837.
  • 7. Ercins, S. ve Tosun, A. (2022). Bir taş ocağındaki patlatma uygulamalarına ait en yüksek parçacık hızı ile frekans ilişkisi. Çukurova Üniversitesi, Mühendislik Fakültesi Dergisi, 37(3), 827-834.
  • 8. Olofsson, S.O. (1990). Applied Explosives Technology for Construction and Mining. 2nd Ed., Applex, Arla, Sweden.
  • 9. Konya, C.J. & Walter, E.J. (1990). Surface Blast Design. Prentice Hall, New Jersey.
  • 10. Duvall, W.I. & Fogelson, D.E. (1962). Review of Criteria for Estimating Damage to Residences from Blasting Vibrations. U.S. Department of the Interior, Bureau of Mines, 19.
  • 11. Lundborg, N., Persson, A., Ladegaard-Pedersen, A. & Holmberg, R. (1975). Keeping the lid on flyrock in open-pit blasting. Engineering & Mining Journal, 176, 95-100.
  • 12. Richards, A. & Moore, A. (2004). Flyrock control-by chance or design. The Annual Conference on Explosives and Blasting Technique, 1, ISEE.
  • 13. McKenzie, C.K. (2009). Flyrock range and fragment size prediction. 35th Annual Conference on Explosives and Blasting Technique, 2, ISEE, Denver, CO.
  • 14. Siskind, D.E., Stagg, M.S., Kopp, J.W. & Dowding, C.H. (1980). Structure response and damage produced by ground vibration from surface mine blasting. Rapor, RI 8507, Bureau of Mines, 118.
  • 15. Cunningham, C.V.B. (1983). The Kuz-Ram model for prediction of fragmentation from blasting. 1st International Symposium on Rock Fragmentation by Blasting, Lulea, Sweden.
  • 16. Ullah, S., Ren, G., Ge, Y., Fissha, Y., Kinyua, E.M. & Zhang, L. (2025). Machine learning-based prediction of blast-induced ground vibration in open-pit mining. Journal of Vibration Engineering & Technologies, 13, 293.
  • 17. Fissha, Y., Khatti, J., Ikeda, H., Grover, K.S., Owada, N., Toriya, H., Adachi, T. & Kawamura, Y. (2024). Predicting ground vibration during rock blasting using relevance vector machine improved with dual kernels and metaheuristic algorithms. Scientific Reports, 14, 20026.
  • 18. Chen, L., Fissha, Y., Hasanipanah, M., Ghodhbani, R., Dehghani, H. & Khatti, J. (2025). Accurate prediction of blast-induced ground vibration intensity using optimized machine learning models. Defence Technology, 1-15.
  • 19. Fattahi, H. ve Hasanipanah, M. (2021). Prediction of blast-induced ground vibration in a mine using relevance vector regression optimized by metaheuristic algorithms. Natural Resources Research, 30, 1849-1863.
  • 20. Mohamed, M.T. (2009). Artificial neural network for prediction and control of blasting vibrations in Assiut (Egypt) limestone quarry. International Journal of Rock Mechanics and Mining Sciences, 46(2), 426-431.
  • 21. Temeng, V.A., Ziggah, Y.Y. & Arthur, C.K. (2021). Blast-induced noise level prediction model based on brain inspired emotional neural network. Journal of Sustainable Mining, 20.
  • 22. He, Z., Jahed Armaghani, D., Masoumnezhad, M., Khandelwal, M., Zhou, J. & Murlidhar, B.R. (2021). A combination of expert-based system and advanced decision-tree algorithms to predict air-overpressure resulting from quarry blasting. Natural Resources Research, 30, 1889-1903.
  • 23. Ramesh Murlidhar, B., Yazdani Bejarbaneh, B., Armaghani, D.J., Mohammed, A.S. & Mohamad, E.T. (2021). Application of tree-based predictive models to forecast air overpressure induced by mine blasting. Natural Resources Research, 30(2), 1865-1887.
  • 24. Gao, W., Alqahtani, A.S., Mubarakali, A., Mavaluru, D. & Khalafi, S. (2020). Developing an innovative soft computing scheme for prediction of air overpressure resulting from mine blasting using GMDH optimized by GA. Engineering with Computers, 36, 647-654.
  • 25. Nguyen, H., Bui, X.N., Bui, H.B. & Mai, N.L. (2020). A comparative study of artificial neural networks in predicting blast-induced air-blast overpressure at Deo Nai open-pit coal mine, Vietnam. Neural Computing and Applications, 32(8), 3939-3955.
  • 26. Hasanipanah, M., Jahed Armaghani, D., Khamesi, H., Bakhshandeh Amnieh, H. & Ghoraba, S. (2016). Several non-linear models in estimating air-overpressure resulting from mine blasting. Engineering with Computers, 32, 441-455.
  • 27. Trivedi, R., Singh, T.N. & Gupta, N. (2015). Prediction of blast-induced flyrock in opencast mines using ANN and ANFIS. Geotechnical and Geological Engineering, 33(4), 875-891.
  • 28. Monjezi, M., Bahrami, A., Varjani, A.Y. & Sayadi, A.R. (2011). Prediction and controlling of flyrock in blasting operation using artificial neural network. Arabian Journal of Geosciences, 4(3), 421-425.
  • 29. Han, H., Armaghani, D.J., Tarinejad, R., Zhou, J. & Tahir, M.M. (2020). Random forest and bayesian network techniques for probabilistic prediction of flyrock induced by blasting in quarry sites. Natural Resources Research, 29(2), 655-667.
  • 30. Barkhordari, M.S., Armaghani, D.J. & Fakharian, P. (2022). Ensemble machine learning models for prediction of flyrock due to quarry blasting. International Journal of Environmental Science and Technology, 19(9), 8661-8676.
  • 31. Hosseini, S., Poormirzaee, R., Hajihassani, M. & Kalatehjari, R. (2022). An ANN-fuzzy cognitive map-based Z-number theory to predict flyrock induced by blasting in open-pit mines. Rock Mechanics and Rock Engineering, 55(7), 4373-4390.
  • 32. Kulatilake, P.H.S.W., Hudaverdi, T. & Wu, Q. (2012). New prediction models for mean particle size in rock blast fragmentation. Geotechnical and Geological Engineering, 30(3), 665-684.
  • 33. Bahrami, A., Monjezi, M., Goshtasbi, K. & Ghazvinian A. (2011). Prediction of rock fragmentation due to blasting using artificial neural network. Engineering with Computers, 27, 177-181.
  • 34. Miao, Y., Zhang, Y., Wu, D., Li, K., Yan, X. & Lin, J. (2021). Rock fragmentation size distribution prediction and blasting parameter optimization based on the muck-pile model. Mining, Metallurgy & Exploration, 38(2), 1071-1080.
  • 35. Xie, C., Nguyen, H., Bui, X.N., Choi, Y., Zhou, J. & Nguyen-Trang, T. (2021). Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms. Geoscience Frontiers, 12(3), 101108.
  • 36. Li, E., Yang, F., Ren, M., Zhang, X., Zhou, J. & Khandelwal, M. (2021). Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms. Journal of Rock Mechanics and Geotechnical Engineering, 13(6), 1380-1397.
  • 37. Aruna, M., Vardhan, H., Tripathi, A. K., Parida, S., Reddy, N.V.R.S., Sivalingam, K.M., Yingqiu, L. & Elumalai, P.V. (2025). Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning. Scientific Reports, 15, 3999.
  • 38. Kadem, B. (2024). Bölgesel patlatma tasarımı ve analizi yapabilen bir mobil uygulama yazılımının geliştirilmesi. Yüksek Lisans Tezi, İstanbul Üniversitesi–Cerrahpaşa Lisansüstü Eğitim Enstitüsü, 117.
  • 39. Özyurt, M.C., Arslan, A., Mutlu, H.E. ve Odabaşı, T.C. (2024). Trakya bölgesinde gerçekleştirilen patlatmalı kazı çalışmalarının verimlilik açısından değerlendirilmesi. Sonuç Raporu, TÜBİTAK 2209/A Üniversite Öğrencileri Araştırma Projeleri Destek Programı.
  • 40. O-Pit Blast, (2024). O-Pit Blast Guide uygulaması tanıtım sayfası. https://www.o-pitblast.com /products/o-pitblasting-guide Erişim tarihi: 11.05.2024.
  • 41. Orica-Nitro, (2024). Pocket Blast Guide uygulaması tanıtım sayfası. https://www.oricaminin gservices.com/au/en/page/products_and_services/pocket_blast_guide_app/pocket_blast_guide_mobile_app, Erişim tarihi: 12.05.2024.
  • 42. Dyno-Nobel, (2024). Explosives Engineers' Mobile App uygulaması tanıtım sayfası. https://dynonobel. com/practical-innovations/recent-innovation/mobile-app, Erişim tarihi: 11.05.2024.
  • 43. Nelson Brothers, (2024). Nelson Brothers uygulaması Google Play store mağaza sayfası. https://play.google.com/store/apps/details?id=com.nelsonbrothers.mobile&hl=en_US&pli=1 Erişim tarihi: 12.05.2024.
  • 44. Bulk Mining Explosive, 2025. BME Guide uygulama tanıtım sayfası. http://bme.co.za/blast-alliance/blasting-guide-app/, Erişim tarihi: 27.04.2025.
  • 45. MineExcellence, (2024). Smart Blasting App uygulaması tanıtım sayfası. https://www.mineexcellence. com/blasting-mobile-app-for-mining/, Erişim tarihi: 11.05.2024.
  • 46. Sakcalı, A., Yavuz, H. ve Cevizci, H. (2016). Basamak patlatmasında kullanılmak üzere geliştirilen bir android uygulaması. 8. Uluslararası Kırmataş Sempozyumu, 13-14 Ekim 2016, Kütahya, Türkiye.

Development of a Mobile Application Software Capable of Bench Blast Design and Analysis

Yıl 2025, Cilt: 40 Sayı: 3, 725 - 741, 26.09.2025
https://doi.org/10.21605/cukurovaumfd.1708218

Öz

In this study, a mobile application software capable of performing integrated blast design and analysis processes has been developed. Named iRockBlast, the application enables users to carry out primary bench blast designs using field data provided on-site. It also allows for the prediction of environmental impacts such as ground vibration, air overpressure, and fly rock, as well as fragment size distribution. The application was developed using the Flutter framework and Dart programming language, making it compatible with both iOS and Android operating systems. It is built upon algorithms derived from well-established literature models. The accuracy of the application was verified through a case study, demonstrating a high degree of consistency between the predicted and actual field results. Unlike existing solutions, the developed software introduces innovative features in both the design and analysis phases. This tool offers significant time efficiency and decision support during the planning of blasting operations.

Kaynakça

  • 1. Ceylanoğlu, A., Kahriman, A. ve Demirci, A. (1993). Delme patlatmanın önemi, kullanıldığı alanlar ve maden mühendisliği ile ilgisi. 1. Delme ve Patlatma Sempozyumu, Ankara, Türkiye.
  • 2. MacKenzie, A.S. (1966). Cost of Explosives – Do You Evaluate it Properly? Mining Congress Journal, 52(5), 32-41.
  • 3. ISEE (International Society of Explosives Engineers), (2015). Field practice guidelines for blasting seismographs. International Society of Explosives Engineers, Cleveland, USA.
  • 4. Jimeno, C.L., Jimeno, E.L. & Carcedo, F.J.A. (1995). Drilling and Blasting of Rocks. Ramiro, Y.V. (Çev.), A.A. Balkema Publishers, Brookfield.
  • 5. Karadoğan, A. (2008). Patlatmadan kaynaklanan titreşimler için ulusal yapı hasar kriterlerinin oluşturulabilirliğinin araştırılması. Doktora tezi, İstanbul Üniversitesi Fen Bilimleri Enstitüsü, 187.
  • 6. Kalaycı Şahinoğlu, Ü. (2024). Patlatma sonucu meydana gelen hava şoku ve partikül madde yayılımı arasındaki ilişkinin araştırılması. Çukurova Üniversitesi, Mühendislik Fakültesi Dergisi, 39(3), 831-837.
  • 7. Ercins, S. ve Tosun, A. (2022). Bir taş ocağındaki patlatma uygulamalarına ait en yüksek parçacık hızı ile frekans ilişkisi. Çukurova Üniversitesi, Mühendislik Fakültesi Dergisi, 37(3), 827-834.
  • 8. Olofsson, S.O. (1990). Applied Explosives Technology for Construction and Mining. 2nd Ed., Applex, Arla, Sweden.
  • 9. Konya, C.J. & Walter, E.J. (1990). Surface Blast Design. Prentice Hall, New Jersey.
  • 10. Duvall, W.I. & Fogelson, D.E. (1962). Review of Criteria for Estimating Damage to Residences from Blasting Vibrations. U.S. Department of the Interior, Bureau of Mines, 19.
  • 11. Lundborg, N., Persson, A., Ladegaard-Pedersen, A. & Holmberg, R. (1975). Keeping the lid on flyrock in open-pit blasting. Engineering & Mining Journal, 176, 95-100.
  • 12. Richards, A. & Moore, A. (2004). Flyrock control-by chance or design. The Annual Conference on Explosives and Blasting Technique, 1, ISEE.
  • 13. McKenzie, C.K. (2009). Flyrock range and fragment size prediction. 35th Annual Conference on Explosives and Blasting Technique, 2, ISEE, Denver, CO.
  • 14. Siskind, D.E., Stagg, M.S., Kopp, J.W. & Dowding, C.H. (1980). Structure response and damage produced by ground vibration from surface mine blasting. Rapor, RI 8507, Bureau of Mines, 118.
  • 15. Cunningham, C.V.B. (1983). The Kuz-Ram model for prediction of fragmentation from blasting. 1st International Symposium on Rock Fragmentation by Blasting, Lulea, Sweden.
  • 16. Ullah, S., Ren, G., Ge, Y., Fissha, Y., Kinyua, E.M. & Zhang, L. (2025). Machine learning-based prediction of blast-induced ground vibration in open-pit mining. Journal of Vibration Engineering & Technologies, 13, 293.
  • 17. Fissha, Y., Khatti, J., Ikeda, H., Grover, K.S., Owada, N., Toriya, H., Adachi, T. & Kawamura, Y. (2024). Predicting ground vibration during rock blasting using relevance vector machine improved with dual kernels and metaheuristic algorithms. Scientific Reports, 14, 20026.
  • 18. Chen, L., Fissha, Y., Hasanipanah, M., Ghodhbani, R., Dehghani, H. & Khatti, J. (2025). Accurate prediction of blast-induced ground vibration intensity using optimized machine learning models. Defence Technology, 1-15.
  • 19. Fattahi, H. ve Hasanipanah, M. (2021). Prediction of blast-induced ground vibration in a mine using relevance vector regression optimized by metaheuristic algorithms. Natural Resources Research, 30, 1849-1863.
  • 20. Mohamed, M.T. (2009). Artificial neural network for prediction and control of blasting vibrations in Assiut (Egypt) limestone quarry. International Journal of Rock Mechanics and Mining Sciences, 46(2), 426-431.
  • 21. Temeng, V.A., Ziggah, Y.Y. & Arthur, C.K. (2021). Blast-induced noise level prediction model based on brain inspired emotional neural network. Journal of Sustainable Mining, 20.
  • 22. He, Z., Jahed Armaghani, D., Masoumnezhad, M., Khandelwal, M., Zhou, J. & Murlidhar, B.R. (2021). A combination of expert-based system and advanced decision-tree algorithms to predict air-overpressure resulting from quarry blasting. Natural Resources Research, 30, 1889-1903.
  • 23. Ramesh Murlidhar, B., Yazdani Bejarbaneh, B., Armaghani, D.J., Mohammed, A.S. & Mohamad, E.T. (2021). Application of tree-based predictive models to forecast air overpressure induced by mine blasting. Natural Resources Research, 30(2), 1865-1887.
  • 24. Gao, W., Alqahtani, A.S., Mubarakali, A., Mavaluru, D. & Khalafi, S. (2020). Developing an innovative soft computing scheme for prediction of air overpressure resulting from mine blasting using GMDH optimized by GA. Engineering with Computers, 36, 647-654.
  • 25. Nguyen, H., Bui, X.N., Bui, H.B. & Mai, N.L. (2020). A comparative study of artificial neural networks in predicting blast-induced air-blast overpressure at Deo Nai open-pit coal mine, Vietnam. Neural Computing and Applications, 32(8), 3939-3955.
  • 26. Hasanipanah, M., Jahed Armaghani, D., Khamesi, H., Bakhshandeh Amnieh, H. & Ghoraba, S. (2016). Several non-linear models in estimating air-overpressure resulting from mine blasting. Engineering with Computers, 32, 441-455.
  • 27. Trivedi, R., Singh, T.N. & Gupta, N. (2015). Prediction of blast-induced flyrock in opencast mines using ANN and ANFIS. Geotechnical and Geological Engineering, 33(4), 875-891.
  • 28. Monjezi, M., Bahrami, A., Varjani, A.Y. & Sayadi, A.R. (2011). Prediction and controlling of flyrock in blasting operation using artificial neural network. Arabian Journal of Geosciences, 4(3), 421-425.
  • 29. Han, H., Armaghani, D.J., Tarinejad, R., Zhou, J. & Tahir, M.M. (2020). Random forest and bayesian network techniques for probabilistic prediction of flyrock induced by blasting in quarry sites. Natural Resources Research, 29(2), 655-667.
  • 30. Barkhordari, M.S., Armaghani, D.J. & Fakharian, P. (2022). Ensemble machine learning models for prediction of flyrock due to quarry blasting. International Journal of Environmental Science and Technology, 19(9), 8661-8676.
  • 31. Hosseini, S., Poormirzaee, R., Hajihassani, M. & Kalatehjari, R. (2022). An ANN-fuzzy cognitive map-based Z-number theory to predict flyrock induced by blasting in open-pit mines. Rock Mechanics and Rock Engineering, 55(7), 4373-4390.
  • 32. Kulatilake, P.H.S.W., Hudaverdi, T. & Wu, Q. (2012). New prediction models for mean particle size in rock blast fragmentation. Geotechnical and Geological Engineering, 30(3), 665-684.
  • 33. Bahrami, A., Monjezi, M., Goshtasbi, K. & Ghazvinian A. (2011). Prediction of rock fragmentation due to blasting using artificial neural network. Engineering with Computers, 27, 177-181.
  • 34. Miao, Y., Zhang, Y., Wu, D., Li, K., Yan, X. & Lin, J. (2021). Rock fragmentation size distribution prediction and blasting parameter optimization based on the muck-pile model. Mining, Metallurgy & Exploration, 38(2), 1071-1080.
  • 35. Xie, C., Nguyen, H., Bui, X.N., Choi, Y., Zhou, J. & Nguyen-Trang, T. (2021). Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms. Geoscience Frontiers, 12(3), 101108.
  • 36. Li, E., Yang, F., Ren, M., Zhang, X., Zhou, J. & Khandelwal, M. (2021). Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms. Journal of Rock Mechanics and Geotechnical Engineering, 13(6), 1380-1397.
  • 37. Aruna, M., Vardhan, H., Tripathi, A. K., Parida, S., Reddy, N.V.R.S., Sivalingam, K.M., Yingqiu, L. & Elumalai, P.V. (2025). Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning. Scientific Reports, 15, 3999.
  • 38. Kadem, B. (2024). Bölgesel patlatma tasarımı ve analizi yapabilen bir mobil uygulama yazılımının geliştirilmesi. Yüksek Lisans Tezi, İstanbul Üniversitesi–Cerrahpaşa Lisansüstü Eğitim Enstitüsü, 117.
  • 39. Özyurt, M.C., Arslan, A., Mutlu, H.E. ve Odabaşı, T.C. (2024). Trakya bölgesinde gerçekleştirilen patlatmalı kazı çalışmalarının verimlilik açısından değerlendirilmesi. Sonuç Raporu, TÜBİTAK 2209/A Üniversite Öğrencileri Araştırma Projeleri Destek Programı.
  • 40. O-Pit Blast, (2024). O-Pit Blast Guide uygulaması tanıtım sayfası. https://www.o-pitblast.com /products/o-pitblasting-guide Erişim tarihi: 11.05.2024.
  • 41. Orica-Nitro, (2024). Pocket Blast Guide uygulaması tanıtım sayfası. https://www.oricaminin gservices.com/au/en/page/products_and_services/pocket_blast_guide_app/pocket_blast_guide_mobile_app, Erişim tarihi: 12.05.2024.
  • 42. Dyno-Nobel, (2024). Explosives Engineers' Mobile App uygulaması tanıtım sayfası. https://dynonobel. com/practical-innovations/recent-innovation/mobile-app, Erişim tarihi: 11.05.2024.
  • 43. Nelson Brothers, (2024). Nelson Brothers uygulaması Google Play store mağaza sayfası. https://play.google.com/store/apps/details?id=com.nelsonbrothers.mobile&hl=en_US&pli=1 Erişim tarihi: 12.05.2024.
  • 44. Bulk Mining Explosive, 2025. BME Guide uygulama tanıtım sayfası. http://bme.co.za/blast-alliance/blasting-guide-app/, Erişim tarihi: 27.04.2025.
  • 45. MineExcellence, (2024). Smart Blasting App uygulaması tanıtım sayfası. https://www.mineexcellence. com/blasting-mobile-app-for-mining/, Erişim tarihi: 11.05.2024.
  • 46. Sakcalı, A., Yavuz, H. ve Cevizci, H. (2016). Basamak patlatmasında kullanılmak üzere geliştirilen bir android uygulaması. 8. Uluslararası Kırmataş Sempozyumu, 13-14 Ekim 2016, Kütahya, Türkiye.
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Kaya Mühendisliği Yapılarında Delme ve Patlatma
Bölüm Makaleler
Yazarlar

Barış Kadem 0009-0004-2518-7681

Abdulkadir Karadoğan 0000-0001-7321-3320

Yayımlanma Tarihi 26 Eylül 2025
Gönderilme Tarihi 28 Mayıs 2025
Kabul Tarihi 25 Eylül 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 40 Sayı: 3

Kaynak Göster

APA Kadem, B., & Karadoğan, A. (2025). Basamak Patlatma Tasarımı ve Analizi Yapabilen Bir Mobil Uygulama Yazılımının Geliştirilmesi. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 40(3), 725-741. https://doi.org/10.21605/cukurovaumfd.1708218