Determination of Mass Properties in Floor Slabs from the Dynamic Response Using Artificial Neural Networks

Carlos Alberto González-Pérez, Jaime De-la-Colina


Most of the research on accidental eccentricity is directed at both the evaluation of accidental eccentricity design code recommendations and the study of building torsional response. In contrast, this paper addresses how the mass properties of each of the levels of a building could be determined from the dynamic response of a building. Using the dynamic response of buildings, this paper presents the application of multilayer feed forward artificial neural networks (ANNs) to determine the magnitude, the radial distance, and the polar moment of inertia of the mass for each level of reinforced concrete (RC) buildings. Analytical models were developed for three regular buildings. Live-load magnitude and mass position are considered as random variables. Seven load cases were generated for the 1, 2 and 4-story models using two excitations. As for the input parameters of the ANNs, three different choices of input data to the network were used. The developed ANN models are able to predict with adequate accuracy the radial position, magnitude, and polar moment of inertia of masses of each level. The implementation of this method based on ANNs would allow the monitoring, either permanently or temporarily, of changes in mass properties at each building floor slab.


Doi: 10.28991/CEJ-2022-08-08-01

Full Text: PDF


Neural Networks; Accidental Torsion; Live Loads; Reinforced Concrete Buildings; System Identification.


Meli, R., & Rosenblueth, E. (1986). The 1985 Earthquake causes and effects in Mexico City. Concrete International, American Concrete Institute, 8(5), 23-24.

Georgoussis, G. K., & Mamou, A. (2019). Mass eccentricity effects on the torsional response of inelastic buildings. Vibroengineering Procedia, 23, 66–71. doi:10.21595/vp.2019.20553.

De-la-Colina, J., & Valdés-González, J. (2021). New Proposal to Incorporate Seismic Accidental Torsion in the Design of Buildings. International Journal of Civil Engineering, 19(1), 1–16. doi:10.1007/s40999-020-00556-x.

ASCE/SEI 7-16 (2017). Minimum design loads and associated criteria for buildings and other structures. American Society of Civil Engineers (ASCE), Reston, United States. doi:10.1061/9780784414248.

NTC-DS. (2021). Complementary Technical Standards for Earthquake Design: Construction Regulations of the CDMX. (In Spanish).

EN 1998-1. (2004). Eurocode 8: Design of structures for earthquake resistance. European Committee for Standardization, Brussels, Belgium.

Basu, D., & Giri, S. (2015). Accidental eccentricity in multistory buildings due to torsional ground motion. Bulletin of Earthquake Engineering, 13(12), 3779–3808. doi:10.1007/s10518-015-9788-0.

Zarza-González, J., De-La-colina, J., & Valdés-González, J. (2021). Evaluation of an accidental-torsion design proposal considering firm-soil ground motions. Revista Internacional de Metodos Numericos Para Calculo y Diseno En Ingenieria, 37(1), 1–16. doi:10.23967/j.rimni.2020.10.009.

Bourahla, N. (2015). Seismic accidental eccentricity: origins, effects and evaluation. Proceedings of the International Conference on innovations on structural engineering, 14-16 December 2015, Hyderabad, India.

Zakaria, A., Shiva Rama Krishna, M., Vamsi Krishna, T. G. N. C., & Baig, M. M. (2019). Effects of the accidental eccentricity on regular and irregular buildings. International Journal of Innovative Technology and Exploring Engineering, 8(11), 2157–2163. doi:10.35940/ijitee.K2030.0981119.

Bourahla, N., Boukhamacha, T., & Tafraout, S. (2006). Detection of the eccentricity variation in nonlinear response using artificial neural networks. 1st European Conference on Earthquake Engineering and Seismology, 3-8 September, 2006, Geneva, Switzerland.

De-la-Llera, J. C., & Chopra, A. K. (1994). Accidental torsion in buildings due to stiffness uncertainty. Earthquake Engineering & Structural Dynamics, 23(2), 117–136. doi:10.1002/eqe.4290230202.

De-la-Llera, J. C., & Chopra, A. K. (1994). Accidental torsion in buildings due to base rotational excitation. Earthquake Engineering & Structural Dynamics, 23(9), 1003–1021. doi:10.1002/eqe.4290230906.

Wong, C. M., & Tso, W. K. (1994). Inelastic seismic response of torsionally unbalanced systems designed using elastic dynamic analysis. Earthquake Engineering & Structural Dynamics, 23(7), 777–798. doi:10.1002/eqe.4290230707.

Shakib, H., & Tohidi, R. Z. (2002). Evaluation of accidental eccentricity in buildings due to rotational component of earthquake. Journal of Earthquake Engineering, 6(4), 431–445. doi:10.1080/13632460209350424.

Stathopoulos, K. G., & Anagnostopoulos, S. A. (2005). Inelastic torsion of multistorey buildings under earthquake excitations. Earthquake Engineering and Structural Dynamics, 34(12), 1449–1465. doi:10.1002/eqe.486.

De-la-Colina, J., González-Pérez, C. A., & Valdés-González, J. (2016). Accidental eccentricities, frame shear forces and ductility demands of buildings with uncertainties of stiffness and live load. Engineering Structures, 124, 113–127. doi:10.1016/j.engstruct.2016.06.012.

Badaoui, M., Bourahla, N., & Bensaibi, M. (2019). Estimation of accidental eccentricities for multi-storey buildings using artificial neural networks. Asian Journal of Civil Engineering, 20, 703–711. doi:10.1007/s42107-019-00137-x.

Andam, K. A. (1986). Floor live loads for office buildings. Building and Environment, 21(3–4), 211–219. doi:10.1016/0360-1323(86)90032-6.

Ruiz, S. E., & Sampayo-Trujillo, A. (1997). Design Live Loads for Classrooms in United States and Mexico. Journal of Structural Engineering, 123(12), 1652–1657. doi:10.1061/(asce)0733-9445(1997)123:12(1652).

Ruiz, S. E., & Soriano, A. (1997). Design Live Loads for Office Buildings in Mexico and the United States. Journal of Structural Engineering, 123(6), 816–822. doi:10.1061/(asce)0733-9445(1997)123:6(816).

Kumar, S. (2002). Live loads in office buildings: Point-in-time load intensity. Building and Environment, 37(1), 79–89. doi:10.1016/S0360-1323(00)00074-3.

Culver, C. G. (1976). Live-Load Survey Results for Office Buildings. Journal of the Structural Division, 102(12), 2269–2284. doi:10.1061/jsdeag.0004492.

Harris, J. C., & Corotis, R. B. (1978). Hospital Inventory Load Survey. Journal of the Structural Division, 104(12), 1859–1868. doi:10.1061/jsdeag.0005052.

Tapia-Hernández, E., Dominguez-Palacios, A. C., & Martínez-Ruíz, M. (2019). Live loads on floors of libraries and newspaper archive buildings. International Journal of Advanced Structural Engineering, 11(2), 285–296. doi:10.1007/s40091-019-0230-8.

Aggarwal, C. C. (2018). Neural Networks and Deep Learning. Springer, Cham, Switzerland. doi:10.1007/978-3-319-94463-0.

Atiya, A. F. (1991). Learning algorithms for neural networks. PhD Thesis, California Institute of Technology, Pasadena, United States.

González-Pérez, C., & Valdés-González, J. (2011). Identification of structural damage in a vehicular bridge using artificial neural networks. Structural Health Monitoring, 10(1), 33–48. doi:10.1177/1475921710365416.

Haykin, S. (2009). Neural Networks: a Comprehensive Foundation. Prentice-Hall, Hoboken, United States.

Jia, D. W., & Wu, Z. Y. (2022). Structural probabilistic seismic risk analysis and damage prediction based on artificial neural network. Structures, 41, 982–996. doi:10.1016/j.istruc.2022.05.056.

Bourahla, N., Derbal, I., & Allal, N. (2014). Neural network for localization of mass and rigidity centers from dynamic responses of buildings. 10th U.S. National Conference on Earthquake Engineering: Frontiers of Earthquake Engineering, 21-25 July 2014, Alaska, United States.

Abambres, M., & Lantsoght, E. O. L. (2020). Neural network-based formula for shear capacity prediction of one-way slabs under concentrated loads. Engineering Structures, 211, 1–9. doi:10.1016/j.engstruct.2020.110501.

Mohammed, S. J., Abdel-khalek, H. A., & Hafez, S. M. (2021). Predicting Performance Measurement of Residential Buildings Using an Artificial Neural Network. Civil Engineering Journal, 7(3), 461–476. doi:10.28991/cej-2021-03091666.

Pizarro, P. N., & Massone, L. M. (2021). Structural design of reinforced concrete buildings based on deep neural networks. Engineering Structures, 241, 1–15. doi:10.1016/j.engstruct.2021.112377.

Vijyalakshmi Pai, G. A., & Rajasekaran, S. (2004). Neural networks, fuzzy logic and genetic algorithms. Prentice-Hall of India, Delhi, India.

Demuth, H., Beale, M., & Hagan, M. (1992). Neural network toolbox. For Use with MATLAB. The MathWorks Inc., California, United States.

Norgaard, M., Ravn, O., Poulsen, N., and Hansen, L. (2000). Neural Networks for Modelling and Control of Dynamic System. Springer-Verlag, London, United Kingdom.

MacKay, D. J. C. (1992). Bayesian Interpolation. Neural Computation, 4(3), 415–447. doi:10.1162/neco.1992.4.3.415.

Yu, H., & Wilamowski, B. (2011). Levenberg–Marquardt Training. Industrial Electronics Handbook, Intelligent Systems, CRC Press, Boca Raton, United States.

Dan Foresee, F., & Hagan, M. T. (1997). Gauss-Newton approximation to Bayesian learning. Proceedings of International Conference on Neural Networks (ICNN’97). doi:10.1109/icnn.1997.614194.

Kramer, S. L. (1996). Geotechnical earthquake engineering (1st Ed.). Pearson Education India, Noida, India.

Villaverde, R. (2009). Fundamental concepts of earthquake engineering (1st Ed.). CRC Press, Boca Raton, United States. doi:10.1201/9781439883112.

Full Text: PDF

DOI: 10.28991/CEJ-2022-08-08-01


  • There are currently no refbacks.

Copyright (c) 2022 Carlos Alberto González-Pérez

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.