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Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm

Yıl 2020, Cilt: 31 Sayı: 4, 10167 - 10188, 01.07.2020
https://doi.org/10.18400/tekderg.509468

Öz

Mechanically
stabilized earth walls are among
the most commonly used soil-retaining structural systems in the
construction
industry. This study addresses the optimum design problem of
mechanically
stabilized earth walls using a recently developed metaheuristic
optimization
algorithm, namely adaptive dimensional search. For a cost efficient
design,
different types of steel reinforcement as well as reinforced backfill
soil are
treated as discrete design variables. The performance of the adaptive
dimensional search algorithm is investigated through cost optimization
instances of mechanically stabilized earth walls under realistic design
criteria specified by standard design codes. The numerical results
demonstrate
the efficiency and robustness of the adaptive dimensional search
algorithm in
minimum cost design of mechanically stabilized earth walls and further
highlight
the usefulness of design optimization in engineering practice.

Kaynakça

  • [1] Coduto, D.P., Foundation Design Principles and Practices, 2nd Edition, 2001.
  • [2] Berg R.R., Christopher B.R. and Samtani N.C. Design of Mechanically Stabilized Earth Walls and Reinforced Soil Slopes – Volume I, Department of Transportation FHWA, Washington, D.C., USA, 2009.
  • [3] Berg R.R., Christopher B.R. and Samtani N.C. Design of Mechanically Stabilized Earth Walls and Reinforced Soil Slopes – Volume II, Department of Transportation FHWA, Washington, D.C., USA, 2009.
  • [4] H. Ghiassian, K. Aladini, Optimum design of reinforced earth walls with metal strips; simulation-optimization approach, Asian Journal of Civil Engineering (Building and Housing), 10 (6): 641–655, 2009.
  • [5] P.K. Basudhar A. Vashistha K. Deb, A. Dey, Cost optimization of reinforced earth walls, Geotech. Geol. Eng., 26: 1–12, 2008.
  • [6] Goldberg DE, Samtani MP. Engineering optimization via genetic algorithm. Proceeding of the Ninth Conference on Electronic Computation, ASCE, pp. 471–482, 1986.
  • [7] Kirkpatrick S, Gerlatt CD, Vecchi MP. Optimization by simulated annealing, Science, 220: 671–680, 1983.
  • [8] Kennedy J, Eberhart R. Particle swarm optimization. In: IEEE international conference on neural networks, IEEE Press, pp. 1942–1948, 1995.
  • [9] Colorni A, Dorigo M, Maniezzo V. Distributed optimization by ant colony. In: Proceedings of the first European conference on artificial life, USA, pp. 134–142, 1991.
  • [10]Dorigo M. Optimization, learning and natural algorithms, PhD thesis. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy, 1992.
  • [11]Lee KS, Geem ZW. A new structural optimization method based on the harmony search algorithm, Comput. Struct., 82: 781–798, 2004.
  • [12]Yang X-S. Nature-inspired metaheuristic algorithms, Luniver Press, UK, 2008.
  • [13]Erbatur F, Al-Hussainy MM. Optimum design of frames, Comput. Struct. 45: 887–891, 1992.
  • [14]Tabak EI, Wright PM. Optimality criteria method for building frames, J. Struct. Div., 107: 1327–1342, 1981.
  • [15]Lamberti L, Pappalettere C. Metaheuristic design optimization of skeletal structures: a review, Computational Technology Reviews, pp. 1–32, 2011.
  • [16]Saka MP. Optimum design of steel frames using stochastic search techniques based in natural phenomena: a review, in: B.H.V. Topping (Ed.), Civil Engineering Computations: Tools and Techniques, Saxe-Coburg Publications, Stirlingshire, UK, pp. 105–147, 2007.
  • [17]O. Hasançebi, S. Kazemzadeh Azad, Adaptive dimensional search: A new metaheuristic algorithm for discrete truss sizing optimization, Comput. Struct. 154, 1–16, 2005.
  • [18]American Association of State Highway and Transportation Officials (AASHTO), LRFD Bridge Design Specifications, 5th Edition, 2010.

Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm

Yıl 2020, Cilt: 31 Sayı: 4, 10167 - 10188, 01.07.2020
https://doi.org/10.18400/tekderg.509468

Öz

Mechanically stabilized earth walls are among
the most commonly used soil-retaining structural systems in the construction
industry. This study addresses the optimum design problem of mechanically
stabilized earth walls using a recently developed metaheuristic optimization
algorithm, namely adaptive dimensional search. For a cost efficient design,
different types of steel reinforcement as well as reinforced backfill soil are
treated as discrete design variables. The performance of the adaptive dimensional search algorithm is investigated through cost optimization
instances of mechanically stabilized earth walls under realistic design
criteria specified by standard design codes. The numerical results demonstrate
the efficiency and robustness of the adaptive dimensional search algorithm in
minimum cost design of mechanically stabilized earth walls and further highlight
the usefulness of design optimization in engineering practice.

Kaynakça

  • [1] Coduto, D.P., Foundation Design Principles and Practices, 2nd Edition, 2001.
  • [2] Berg R.R., Christopher B.R. and Samtani N.C. Design of Mechanically Stabilized Earth Walls and Reinforced Soil Slopes – Volume I, Department of Transportation FHWA, Washington, D.C., USA, 2009.
  • [3] Berg R.R., Christopher B.R. and Samtani N.C. Design of Mechanically Stabilized Earth Walls and Reinforced Soil Slopes – Volume II, Department of Transportation FHWA, Washington, D.C., USA, 2009.
  • [4] H. Ghiassian, K. Aladini, Optimum design of reinforced earth walls with metal strips; simulation-optimization approach, Asian Journal of Civil Engineering (Building and Housing), 10 (6): 641–655, 2009.
  • [5] P.K. Basudhar A. Vashistha K. Deb, A. Dey, Cost optimization of reinforced earth walls, Geotech. Geol. Eng., 26: 1–12, 2008.
  • [6] Goldberg DE, Samtani MP. Engineering optimization via genetic algorithm. Proceeding of the Ninth Conference on Electronic Computation, ASCE, pp. 471–482, 1986.
  • [7] Kirkpatrick S, Gerlatt CD, Vecchi MP. Optimization by simulated annealing, Science, 220: 671–680, 1983.
  • [8] Kennedy J, Eberhart R. Particle swarm optimization. In: IEEE international conference on neural networks, IEEE Press, pp. 1942–1948, 1995.
  • [9] Colorni A, Dorigo M, Maniezzo V. Distributed optimization by ant colony. In: Proceedings of the first European conference on artificial life, USA, pp. 134–142, 1991.
  • [10]Dorigo M. Optimization, learning and natural algorithms, PhD thesis. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy, 1992.
  • [11]Lee KS, Geem ZW. A new structural optimization method based on the harmony search algorithm, Comput. Struct., 82: 781–798, 2004.
  • [12]Yang X-S. Nature-inspired metaheuristic algorithms, Luniver Press, UK, 2008.
  • [13]Erbatur F, Al-Hussainy MM. Optimum design of frames, Comput. Struct. 45: 887–891, 1992.
  • [14]Tabak EI, Wright PM. Optimality criteria method for building frames, J. Struct. Div., 107: 1327–1342, 1981.
  • [15]Lamberti L, Pappalettere C. Metaheuristic design optimization of skeletal structures: a review, Computational Technology Reviews, pp. 1–32, 2011.
  • [16]Saka MP. Optimum design of steel frames using stochastic search techniques based in natural phenomena: a review, in: B.H.V. Topping (Ed.), Civil Engineering Computations: Tools and Techniques, Saxe-Coburg Publications, Stirlingshire, UK, pp. 105–147, 2007.
  • [17]O. Hasançebi, S. Kazemzadeh Azad, Adaptive dimensional search: A new metaheuristic algorithm for discrete truss sizing optimization, Comput. Struct. 154, 1–16, 2005.
  • [18]American Association of State Highway and Transportation Officials (AASHTO), LRFD Bridge Design Specifications, 5th Edition, 2010.
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İnşaat Mühendisliği
Bölüm Makale
Yazarlar

Saeid Kazemzadeh Azad 0000-0001-9309-607X

Ebru Akış 0000-0001-8417-2405

Yayımlanma Tarihi 1 Temmuz 2020
Gönderilme Tarihi 7 Ocak 2019
Yayımlandığı Sayı Yıl 2020 Cilt: 31 Sayı: 4

Kaynak Göster

APA Kazemzadeh Azad, S., & Akış, E. (2020). Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm. Teknik Dergi, 31(4), 10167-10188. https://doi.org/10.18400/tekderg.509468
AMA Kazemzadeh Azad S, Akış E. Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm. Teknik Dergi. Temmuz 2020;31(4):10167-10188. doi:10.18400/tekderg.509468
Chicago Kazemzadeh Azad, Saeid, ve Ebru Akış. “Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm”. Teknik Dergi 31, sy. 4 (Temmuz 2020): 10167-88. https://doi.org/10.18400/tekderg.509468.
EndNote Kazemzadeh Azad S, Akış E (01 Temmuz 2020) Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm. Teknik Dergi 31 4 10167–10188.
IEEE S. Kazemzadeh Azad ve E. Akış, “Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm”, Teknik Dergi, c. 31, sy. 4, ss. 10167–10188, 2020, doi: 10.18400/tekderg.509468.
ISNAD Kazemzadeh Azad, Saeid - Akış, Ebru. “Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm”. Teknik Dergi 31/4 (Temmuz 2020), 10167-10188. https://doi.org/10.18400/tekderg.509468.
JAMA Kazemzadeh Azad S, Akış E. Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm. Teknik Dergi. 2020;31:10167–10188.
MLA Kazemzadeh Azad, Saeid ve Ebru Akış. “Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm”. Teknik Dergi, c. 31, sy. 4, 2020, ss. 10167-88, doi:10.18400/tekderg.509468.
Vancouver Kazemzadeh Azad S, Akış E. Cost Efficient Design of Mechanically Stabilized Earth Walls Using Adaptive Dimensional Search Algorithm. Teknik Dergi. 2020;31(4):10167-88.