A NEURAL NETWORK APPROACH FOR THE ANALYSIS OF LIMIT BEARING CAPACITY OF CONTINUOUS BEAMS DEPENDING ON THE CHARACTER OF THE LOAD

Miloš D Bogdanović, Žarko Petrović, Bojan Milošević, Marina Mijalković, Leonid Stoimenov

DOI Number
https://doi.org/10.2298/FUEE1801115B
First page
115
Last page
130

Abstract


Being a part of civil engineering, limit state analysis represents a structural analysis with a goal of developing efficient methods to directly estimate collapse load for a particular structural model. As a theoretical foundation, limit state analysis uses a set of bound (limit) theorems. Limit theorems are based on the law of conservation of energy and are used for a direct definition of the limit state function for failure by plastic collapse or by inadaptation. This study proposes an artificial neural network (ANN) model in order to approximate the residual bending moment, limit and the incremental failure force of continuous beams. The neural network structure applied here is a radial-Gaussian network architecture (RGIN) and complementary training procedure. This structure is intended to be used for civil engineering purposes and it is demonstrated on the example of the two-span continuous beam loaded in the middle of the span that the limit and the incremental failure force can be obtained using neural network approach with sufficient precision and is especially suitable in analysis when some of the model parameters are variable.

Keywords

Continuous beam; incremental force; limit failure force; neural network; radial-Gaussian network architecture

Full Text:

PDF

References


J. McCarthy, "What is Artificial Intelligence?", Computer Science Department of Stanford University, California, United States of America, 2007, available from: http://www-formal.stanford.edu/jmc/whatisai/.

C.T. Leondes, Expert Systems, Volume I. Academic Press, San Diego, California 92101-4495, USA, 2002.

P. Lu, S. Chen and Y. Zheng, "Artificial intelligence in civil engineering", Mathematical Problems in Engineering, vol. 2012, Article ID 145974, pp. 22, 2012.

M.Y. Rafiq, G. Bugmann and D.J. Easterbrook, "Neural Network Design for Engineering Applications", Computers & Structures, vol. 79, issue 17, pp. 1541-1552, 2001.

Z. Waszczyszyn and L. Ziemianski, "Neural Networks in Mechanics of Structures and Materials-New Results and Prospects of Applications", Computers & Structures, vol. 79, issue 22, pp. 2261-2276, 2001.

N. Ahmadi, R. Kamyab Moghadas and A. Lavaei, "Dynamic analysis of structures using neural networks", American Journal of Applied Sciences, vol. 5.9, pp. 1251-1256, 2008.

I. Lou and Y. Zhao, "Sludge bulking prediction using principle component regression and artificial neural network", Mathematical Problems in Engineering, Article ID 237693, pp. 17, 2012.

E. Bojórquez, J. Bojórquez, S.E. Ruiz and A. Reyes-Salazar, "Prediction of inelastic response spectra using artificial neural networks", Mathematical Problems in Engineering, Article ID 937480, 2012.

J.H. Garrett, "Where and why artificial neural networks are applicable in civil engineering", Journal of Computing in Civil Engineering, pp.129-130, 1994.

G.V. Kazinczy, Kiserletek befalazott tartokkal.Betonszemle, 2, 1914.

N.C. Kist, Leidt een Sterkteberekening, die Uitgaat van de Evenredigheid van Kracht en Vormverandering, tot een goede Constructie van Ijzeren Bruggen en gebouwen. Inaugural Dissertation, Polytechnic Institute, Delft, 1917.

A.A. Gvozdev, "The determination of the value of the collapse load for statically indeterminate systems undergoing plastic deformation", In Proceedings of the Conference on Plastic Deformations / Akademiia Nauk S.S.S.R., Moscow-Leningrad, 1398, 19, (tr., R.M.Haythornthwaite, Int. J. Mech.Sci., 1, (1960), 332).

R. Hill, "On the state of stress in a plastic rigid body at the yield point", Philosophical Magazine, vol. 42, pp. 868-875, 1951.

D.C. Drucker, W. Prager and H.J. Greenberg, "Extended limit design theorems for continuous media", Quarterly of Applied Mathematics, vol. 9, pp.381-392, 1952

M.R. Horne, "Fundamental propositions in the plastic theory of structures", Journal of the Institution of Civil Engineers, vol. 34, pp. 174-177, 1950

H.J. Greenberg and W. Prager, "On limit design of beams and frames", Transactions of the American Society of Civil Engineers, (First published as Tech. Rep. A18-1, Brown Univ., 1949), pp.117-447, 1952.

B.G. Neal and P.S. Symonds, "The Calculation of Collapse Loads for Framed Structures", Journal of the Institution of Civil Engineers, vol. 35, pp.21-40, 1950-51.

P.G. Hodge, Plastic Analysis of Structures, New York: McGraw-Hill, 1959.

J. Baker and J. Heyman, Plastic Design of Frames. Vol 1. Fundamentals, London: Cambridge University Press, 1969.

M. Zyczkowski, Combined loadings in the theory of plasticity, Springer Netherlands, 1981.

M. Save, Atlas of limit loads of metal plates shells and disks. Elsevier Science BV, 1995.

B.G. Neal, The Plastic Methods of Structural Analysis. London: Chapman and Hall, 1977.

M. Jirásek and Z.P. Baţant, Inelastic Analysis of Structures. John Wiley & Sons, 2002.

E. Melan, "Zur Plastizitat des raumlichen continuum", Ing. Arch. vol. 9, pp.116–126, 1938.

W.T. Koiter, General theorems for elastic–plastic solids. Amsterdam: North-Holland, 1960. pp. 165– 221.

J. Ghaboussi, J.H. Garrett and X. Wu, "Knowledge-based modeling of material behavior with neural networks", Journal of Engineering Mechanics, vol. 117, pp.132–151, 1991.

S. Arangio and J. Beck, "Bayesian neural networks for bridge integrity assessment", Structural Control & Health Monitoring, vol. 19, no. 1, pp. 3–21, 2012.

P.B. Cachim, "Using artificial neural networks for calculation of temperatures in timber under fire loading", Construction and Building Materials, vol. 25, no. 11, pp. 4175–4180, 2011.

J. Liu, H. Li and C. He, "Concrete Compressive Strength Prediction Using Rebound Method with Artificial Neural Network", Advanced Materials Research, vols. 443-444, pp. 34-39, 2012.

M.Y. Cheng, H.C. Tsai and E. Sudjono, "Evaluating subcontractor performance using evolutionary fuzzy hybrid neural network", International Journal of Project Management, vol. 29, no. 3, pp. 349– 356, 2011.

X.Z. Wang, X.C. Duan and J.Y. Liu, "Application of neural network in the cost estimation of highway engineering", Journal of Computers, vol. 5, no. 11, pp. 1762–1766, 2010.

X. Gui, X. Zheng, J. Song and X. Peng, "Automation bridge design and structural optimization", Applied Mechanics and Materials, vol. 63-64, pp. 457–460, 2011.

D.R. Parhi and A.K. Dash, "Application of neural networks and finite elements for condition monitoring of structures", Journal of Mechanical Engineering Science, vol. 225, no. 6, pp. 1329–1339, 2011.

S.N. Alacali, B. Akba and B. Doran, "Prediction of lateral confinement coefficient in reinforced concrete columns using neural network simulation", Applied Soft Computing Journal, vol. 11, no. 2, pp. 2645– 2655, 2011.

H. Rahman, K. Alireza and G. Reza, "Application of artificial neural network, kriging, and inverse distance weighting models for estimation of scour depth around bridge pier with bed sill", Journal of Software Engineering and Applications, vol. 3, no. 10, 2010.

J. Zhang and F. Haghighat, "Development of Artificial Neural Network based heat convection algorithm for thermal simulation of large rectangular cross-sectional area Earth-to-Air Heat Exchangers", Energy and Buildings, vol. 42, no. 4, pp. 435–440, 2010.

S. Narasimhan, "Robust direct adaptive controller for the nonlinear highway bridge benchmark", Structural Control Health Monitoring, vol. 16, pp. 599–612, 2009.

T.L. Lee, H.M. Lin and Y.P. Lu, "Assessment of highway slope failure using neural networks", Journal of Zhejiang University: Science A, vol. 10, no. 1, pp. 101–108, 2009.

S. Laflamme and J.J. Connor, "Application of self-tuning Gaussian networks for control of civil structures equipped with magnetorheological dampers", In Proceedings of the SPIE, The International Society for Optical Engineering, March 2009.

A. Bilgil and H. Altun, "Investigation of flow resistance in smooth open channels using artificial neural networks", Flow Measurement and Instrumentation, vol. 19, no. 6, pp. 404–408, 2008.

I. Flood, "Towards the next generation of artificial neural networks for civil engineering", Advanced Engineering Informatics, vol. 22, no. 1, pp. 4–14, 2008.

A. J. Konig, Shakedown of Elastic-Plastic Structures, North Holland, 1987.

L.M. Kachanov, Foundations of the Theory of plasticity. Amsterdam-London: North-Holland publishing company, 1971.

B. Milošević, M. Mijalković, Ţ. Petrović and M. Hadţimujović, "The Application of the Limit Analysis Theorem and the Adaptation Theorem for Determining the Failure Load of Continuous Beams", Scientific Tehnical Review, vol 60, no 3-4, pp. 82-92, 2010.

N. Kartam, I. Flood and J. H. Garrett, Artificial Neural Networks for Civil Engineering: Fundamentals and Applications. New York: American Society of Civil Engineering, 1997, pp. 19-43.

R. Hecht-Nielsen, Neurocomputing. New York : Addison-Wesley, 1990.

C.R. Alavala, Fuzzy Logic and Neural Networks: Basic Concepts & Applications, New Age International Pvt Ltd Publishers, December 2008.

N. Gagarin, I. Flood and P. Albrech, "Computing truck attributes with artificial neural network", Journal of Computing in Civil Engineering, vol. 8(2), pp.179–200, 1994

S. Chen, C.F.N. Cowan and P.M. Grant, "Orthogonal Least Squares Learning Algorithm for Radial Basis Function Networks", IEEE Transactions on Neural Networks, vol. 2, no. 2, 1991.

I. Flood, "A Gaussian-based feedforward network architecture and complementary training algorithm", In Proceedings of International Joint Conference on Neural Networks, IEEE and INNS / Singapore, 1991, pp. 171-176.


Refbacks

  • There are currently no refbacks.


ISSN: 0353-3670