Publications

@article{jesus-mojtabaei2025_spatial_compr_sensin_field_recon,

title = {Spatial Compressed Sensing for Field Reconstruction 

 in Full-Scale Structural Systems},

author = {Andre Jesus and Seyed Mohammed Mojtabaei},

url = {http://dx.doi.org/10.1680/jstbu.24.00057},

doi = {10.1680/jstbu.24.00057},

year  = {2025},

date = {2025-01-01},

journal = {Proceedings of the Institution of Civil Engineers - 

 Structures and Buildings},

volume = {178},

number = {11},

pages = {1018-1025},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ike-jesus-mojtabaei2025_exper_inves_moist_depen_behav,

title = {Experimental Investigation of the Moisture-Dependent 

 Behaviour of Norway Spruce Glulam Beams},

author = {Vincent Ifeanyi Ike and Andre Jesus and Seyed Mohammad Mojtabaei},

url = {http://dx.doi.org/10.1016/j.conbuildmat.2025.143807},

doi = {10.1016/j.conbuildmat.2025.143807},

year  = {2025},

date = {2025-01-01},

journal = {Construction and Building Materials},

volume = {497},

number = {nil},

pages = {143807},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{xu-jesus-et_al2024_stoch_model_framew_predic_flexur,

title = {A Stochastic Modelling Framework for Predicting 

 Flexural Properties of Ultra-Thin Randomly Oriented 

 Strands},

author = {Xiaodong Xu and André Jesus and Yi Wan and Jun Takahashi},

url = {http://dx.doi.org/10.1080/09243046.2024.2351667},

doi = {10.1080/09243046.2024.2351667},

year  = {2024},

date = {2024-01-01},

journal = {Advanced Composite Materials},

volume = {34},

number = {1},

pages = {1-15},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jesus-xu2023_rapid_predic_fibre_domin_tensil,

title = {Rapid Prediction of Fibre-Dominant Tensile Failure 

 in Randomly Oriented Strands},

author = {André Jesus and Xiaodong Xu},

url = {https://doi.org/10.1177/07316844221107927},

doi = {10.1177/07316844221107927},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Reinforced Plastics and Composites},

volume = {42},

number = {5-6},

pages = {205-212},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jesus-zivanovic2023_modal_testin_with_pedes_as_vibrat_excit,

title = {Modal Testing With a Pedestrian As a Vibration 

 Exciter},

author = {André Jesus and Stana Živanović},

url = {https://www.sciencedirect.com/science/article/pii/S0888327022011505},

doi = {10.1016/j.ymssp.2022.110082},

issn = {0888-3270},

year  = {2023},

date = {2023-01-01},

journal = {Mechanical Systems and Signal Processing},

volume = {189},

pages = {110082},

abstract = {A novel approach, for identification of modal 

 properties using a dynamic excitation induced by a 

 human walker, has previously been proposed to 

 identify natural frequencies, damping ratios and 

 modal masses. The developed approach is now expanded 

 to also estimate vibration mode shapes, thus fully 

 characterising the dynamic behaviour of a structure 

 in a simple and affordable way. Additionally, the 

 reliability of the method is parametrically analysed 

 and validated against simulated and real world data 

 of a footbridge. Results indicate that, given a 

 reasonable initial estimate of the target modal 

 properties values and with careful consideration of 

 the number and location of measured responses, it is 

 possible to estimate all modal properties of a 

 structure in a reliable and simpler way than 

 conventional modal testing methods: handheld impact 

 hammer, electrodynamic shaker or ambient vibration 

 tests.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{moravej-chan-et_al2020_comput_effec_struc_perfor_asses,

title = {Computation-Effective Structural Performance 

 Assessment Using Gaussian Process-Based Finite 

 Element Model Updating and Reliability 

 Analysis},

author = {Hans Moravej and Tommy H. T. Chan and Andre Jesus and Khac-Duy Nguyen},

doi = {10.1142/S0219455420420031},

issn = {0219-4554, 1793-6764},

year  = {2020},

date = {2020-09-01},

journal = {International Journal of Structural Stability and 

 Dynamics},

volume = {20},

number = {10},

pages = {2042003},

abstract = {Structural health monitoring data has been widely 

 acknowledged as a significant source for evaluating 

 the performance and health conditions of 

 structures. However, a holistic framework that 

 efficiently incorporates monitored data into 

 structural identification and, in turn, provides a 

 realistic life-cycle performance assessment of 

 structures is yet to be established. There are 

 different sources of uncertainty, such as structural 

 parameters, computer model bias and measurement 

 errors. Neglecting to account for these factors 

 results in unreliable structural identifications, 

 consequent financial losses, and a threat to the 

 safety of structures and human lives. This paper 

 proposes a new framework for structural performance 

 assessment that integrates a comprehensive 

 probabilistic finite element model updating 

 approach, which deals with various structural 

 identification uncertainties and structural 

 reliability analysis. In this framework, Gaussian 

 process surrogate models are replaced with a finite 

 element model and its associate discrepancy function 

 to provide a computationally efficient and all-round 

 uncertainty quantification. Herein, the structural 

 parameters that are most sensitive to measured 

 structural dynamic characteristics are investigated 

 and used to update the numerical 

 model. Sequentially, the updated model is applied to 

 compute the structural capacity with respect to 

 loading demand to evaluate its as-is 

 performance. The proposed framework's feasibility is 

 investigated and validated on a large lab-scale box 

 girder bridge in two different health states, 

 undamaged and damaged, with the latter state 

 representing changes in structural parameters 

 resulted from overloading actions. The results from 

 the box girder bridge indicate a reduced structural 

 performance evidenced by a significant drop in the 

 structural reliability index and an increased 

 probability of failure in the damaged state. The 

 results also demonstrate that the proposed 

 methodology contributes to more reliable judgment 

 about structural safety, which in turn enables more 

 informed maintenance decisions to be made.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jesus-zivanovic-alani2019_spect_pedes_based_approac_modal_ident,

title = {A Spectral Pedestrian-Based Approach for Modal 

 Identification},

author = {André Jesus and Stana Živanović and Amir Alani},

doi = {10.1016/j.jsv.2019.115157},

issn = {0022460X},

year  = {2019},

date = {2019-12-01},

journal = {Journal of Sound and Vibration},

volume = {470},

pages = {115157},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{moravej-chan-et_al2019_vibrat_based_bayes_model_updat,

title = {Vibration-Based Bayesian Model Updating of Civil 

 Engineering Structures Applying Gaussian Process 

 Metamodel},

author = {Hossein Moravej and Tommy HT Chan and Khac-Duy Nguyen and Andre Jesus},

doi = {10.1177/1369433219858723},

issn = {1369-4332, 2048-4011},

year  = {2019},

date = {2019-12-01},

journal = {Advances in Structural Engineering},

volume = {22},

number = {16},

pages = {3487–3502},

abstract = {Structural health monitoring plays a significant 

 role in providing information regarding the 

 performance of structures throughout their life 

 spans. However, information that is directly 

 extracted from monitored data is usually susceptible 

 to uncertainties and not reliable enough to be used 

 for structural investigations. Finite element model 

 updating is an accredited framework that reliably 

 identifies structural behavior. Recently, the 

 modular Bayesian approach has emerged as a 

 probabilistic technique in calibrating the finite 

 element model of structures and comprehensively 

 addressing uncertainties. However, few studies have 

 investigated its performance on real structures. In 

 this article, modular Bayesian approach is applied 

 to calibrate the finite element model of a 

 lab-scaled concrete box girder bridge. This study is 

 the first to use the modular Bayesian approach to 

 update the initial finite element model of a real 

 structure for two states— undamaged and 

 damaged conditions— in which the damaged 

 state represents changes in structural parameters as 

 a result of aging or overloading. The application of 

 the modular Bayesian approach in the two states 

 provides an opportunity to examine the performance 

 of the approach with observed evidence. A 

 discrepancy function is used to identify the 

 deviation between the outputs of the experimental 

 and numerical models. To alleviate computational 

 burden, the numerical model and the model 

 discrepancy function are replaced by Gaussian 

 processes. Results indicate a significant reduction 

 in the stiffness of concrete in the damaged state, 

 which is identical to cracks observed on the body of 

 the structure. The discrepancy function reaches 

 satisfying ranges in both states, which implies that 

 the properties of the structure are predicted 

 accurately. Consequently, the proposed methodology 

 contributes to a more reliable judgment about 

 structural safety.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jesus-brommer-et_al2019_modul_bayes_damag_detec_compl_civil_infras,

title = {Modular Bayesian Damage Detection for Complex 

 Civil Infrastructure},

author = {Andre Jesus and Peter Brommer and Robert Westgate and Ki Koo and James Brownjohn and Irwanda Laory},

doi = {10.1007/s13349-018-00321-8},

issn = {2190-5452, 2190-5479},

year  = {2019},

date = {2019-02-01},

journal = {Journal of Civil Structural Health Monitoring},

volume = {9},

number = {2},

pages = {201–215},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zhu-ni-et_al2018_therm_strain_extrac_method_bridg,

title = {Thermal Strain Extraction Methodologies for Bridge 

 Structural Condition Assessment},

author = {Yanjie Zhu and Yi-Qing Ni and Andre Jesus and Jingliang Liu and Irwanda Laory},

doi = {10.1088/1361-665X/aad5fb},

issn = {0964-1726, 1361-665X},

year  = {2018},

date = {2018-10-01},

journal = {Smart Materials and Structures},

volume = {27},

number = {10},

pages = {105051},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jesus-brommer-et_al2018_bayes_struc_ident_long_suspen,

title = {Bayesian Structural Identification of a Long 

 Suspension Bridge Considering Temperature and 

 Traffic Load Effects},

author = {Andre Jesus and Peter Brommer and Robert Westgate and Ki Koo and James Brownjohn and Irwanda Laory},

doi = {10.1177/1475921718794299},

issn = {1475-9217, 1741-3168},

year  = {2018},

date = {2018-08-01},

journal = {Structural Health Monitoring},

volume = {18},

number = {4},

pages = {1310–1323},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jesus-brommer-et_al2017_compr_bayes_struc_ident_using_temper_variat,

title = {Comprehensive Bayesian Structural Identification 

 Using Temperature Variation},

author = {Andre Jesus and Peter Brommer and Yanjie Zhu and Irwanda Laory},

doi = {10.1016/j.engstruct.2017.01.060},

issn = {0141-0296},

year  = {2017},

date = {2017-06-01},

journal = {Engineering Structures},

volume = {141},

pages = {75–82},

abstract = {bibtex: Jesus201775},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jesus-dimitrovova-silva2014_statis_analy_dynam_respon_railw_viaduc,

title = {A Statistical Analysis of the Dynamic Response of a 

 Railway Viaduct},

author = {André H. Jesus and Zuzana Dimitrovová and Manuel A. G. Silva},

doi = {10.1016/j.engstruct.2014.04.012},

issn = {01410296},

year  = {2014},

date = {2014-07-01},

journal = {Engineering Structures},

volume = {71},

pages = {244–259},

abstract = {bibtex: jesus_statistical_2014},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jesus-dimitrovova-silva2012_qualit_influen_model_param_dynam_respon_viaduc,

title = {The Qualitative Influence of Model 

 Parameters on the Dynamic Response of a 

 Viaduct},

author = {A. H. Jesus and Z. Dimitrovová and M. A. G. Silva},

doi = {10.4203/ijrt.1.2.5},

issn = {2049-5358},

year  = {2012},

date = {2012-01-01},

journal = {International Journal of Railway Technology},

volume = {1},

number = {2},

pages = {89–113},

abstract = {bibtex: jesus_qualitative_2012},

keywords = {},

pubstate = {published},

tppubtype = {article}

}