Homepage / Modelling the Deterioration of Infrastructure

Project description: This research project aims at developing machine learning methods suited for the network-scale degradation analysis of transportation infrastructure. The outcome of the project will be a set of methods that will help monitoring and maintaining existing transportation infrastructure. These techniques will enable tracking the performance of structural elements, forecasting the degradation, assessing the degradation rate changes with time and provide assistance in comparing different maintenance strategies.

Funding: Quebec Transportation Ministry (MTQ)

Development Methods: Kalman Filter & Smoother, Conditional Distribution of MVN, Kernel Regression, Gaussian Mixture Reduction, Gradient Optimization, Baysian Neural Networks

Development Tools: MATLAB (Including: App Designer, GPU compute), Github, MS Access

Open-source Software: OpenIPDM

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Resources

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[2023]:

Analytical Inference for the Inspectors Uncertainty Using Network-Scale Visual Inspections.
B. Laurent, B. Deka, Z. Hamida, J-A. Goulet
Journal of Computing in Civil Engineering
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Bayesian Neural Networks for Large-Scale Infrastructure Deterioration Models.
S.A.K. Fakhri, Z. Hamida, J-A. Goulet
14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP14, Dublin, Ireland.
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OpenIPDM: Une librairie ouverte pour modéliser la dégradation d’un parc d’infrastructures.
Z. Hamida, J-A. Goulet
29e Colloque sur la progression de la recherche québécoise concernant les ouvrages d’art, Montreal, Canada.
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[2022]:

Estimating the Bias Associated with Inspectors in the Context of Visual Inspections on Infrastructures.
B. Laurent, Z. Hamida, J-A. Goulet
11th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-11), Montreal, Canada.

Modelling the Deterioration of Infrastructures Using Network-Scale Visual Inspections.
Z. Hamida, J-A. Goulet
11th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-11), Montreal, Canada.

OpenIPDM: A Probabilistic Framework for Estimating the Deterioration and Effect of Interventions on Bridges
Z. Hamida, B. Laurent and J-A. Goulet
SoftwareX
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A Stochastic Model for Estimating the Network-Scale Deterioration and Effect of Interventions on Bridges
Z. Hamida, J-A. Goulet
Structural Control and Health Monitoring, e2916
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[2021]:

Quantifying the Effects of Interventions Based on Visual Inspections from a Network of Bridges
Z. Hamida, J-A. Goulet
Structure and Infrastructure Engineering
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Network-Scale Deterioration Modelling of Bridges Based on Visual Inspections and Structural Attributes
Z. Hamida, J-A. Goulet
Structural Safety 88
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[2020]:

Stochastic Modelling of Infrastructures Deterioration and Interventions based on Network-Scale Visual Inspections.
Z. Hamida
Ph.D. Thesis, Polytechnique Montreal, Canada.

Modeling infrastructure degradation from visual inspections using network‐scale state‐space models
Z. Hamida, J-A. Goulet
Structural Control and Health Monitoring 27 (9), e2582
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[2019]:

State-Space Models for Network-Scale Analysis of Bridge Inspection Data.
Z. Hamida, J-A. Goulet
13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13), Seoul, South Korea.

Modeling Infrastructure Degradation from Visual Inspections Using Network-Scale State-Space Models.
Z. Hamida, J-A. Goulet
Modeling and Numerical Methods for Uncertainty Quantification (MNMUQ 2019), Porquerolles Island, France.