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Zain, Muhammad / Dackermann, Ulrike / Prasittisopin, Lapyote (2024): Machine learning (ML) algorithms for seismic vulnerability assessment of school buildings in high-intensity seismic zones. Dans: Structures, v. 70 (décembre 2024).
https://doi.org/10.1016/j.istruc.2024.107639
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Keshmiry, Ayoub / Hassani, Sahar / Dackermann, Ulrike / Li, Jianchun (2024): Assessment, repair, and retrofitting of masonry structures: A comprehensive review. Dans: Construction and Building Materials, v. 442 (septembre 2024).
https://doi.org/10.1016/j.conbuildmat.2024.137380
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Khademi, Pooria / Mousavi, Mohsen / Dackermann, Ulrike / Gandomi, Amir H. (2024): Enhancing load prediction for structures with concrete overlay using transfer learning of time–frequency feature-based deep models. Dans: Engineering Structures, v. 305 (avril 2024).
https://doi.org/10.1016/j.engstruct.2024.117734
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Hassani, Sahar / Dackermann, Ulrike / Mousavi, Mohsen / Li, Jianchun (2024): Enhanced damage detection for noisy input signals using improved reptile search algorithm and data analytics techniques. Dans: Computers & Structures, v. 296 (juin 2024).
https://doi.org/10.1016/j.compstruc.2024.107293
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Khademi, Pooria / Mousavi, Mohsen / Dackermann, Ulrike / Gandomi, Amir H. (2023): Time–frequency analysis of ultrasonic signals for quality assessment of bonded concrete. Dans: Construction and Building Materials, v. 403 (novembre 2023).
https://doi.org/10.1016/j.conbuildmat.2023.133062
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Hassani, Sahar / Dackermann, Ulrike (2023): Optimization-based damage detection in composite structures using incomplete measurements. Dans: Structures, v. 56 (octobre 2023).
https://doi.org/10.1016/j.istruc.2023.07.015
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Keshmiry, Ayoub / Hassani, Sahar / Mousavi, Mohsen / Dackermann, Ulrike (2023): Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review. Dans: Buildings, v. 13, n. 4 (24 mars 2023).
https://doi.org/10.3390/buildings13040918
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Dackermann, Ulrike / Skinner, Bradley / Li, Jianchun (2014): Guided wave–based condition assessment of in situ timber utility poles using machine learning algorithms. Dans: Structural Health Monitoring, v. 13, n. 4 (février 2014).
https://doi.org/10.1177/1475921714521269
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Dackermann, Ulrike / Smith, Wade A. / Randall, Robert B. (2014): Damage identification based on response-only measurements using cepstrum analysis and artificial neural networks. Dans: Structural Health Monitoring, v. 13, n. 4 (février 2014).
https://doi.org/10.1177/1475921714542890
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Yu, Yang / Dackermann, Ulrike / Li, Jianchun / Niederleithinger, Ernst (2017): Wavelet packet energy–based damage identification of wood utility poles using support vector machine multi-classifier and evidence theory. Dans: Structural Health Monitoring, v. 18, n. 1 (décembre 2017).
https://doi.org/10.1177/1475921718798622
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Dackermann, Ulrike / Smith, Wade A. / Makki Alamdari, Mehrisadat / Li, Jianchun / Randall, Robert B. (2017): Cepstrum-based damage identification in structures with progressive damage. Dans: Structural Health Monitoring, v. 18, n. 1 (décembre 2017).
https://doi.org/10.1177/1475921718804730
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Nguyen, Van Vu / Li, Jianchun / Erkmen, Emre / Makki Alamdari, Mehrisadat / Dackermann, Ulrike (2018): FRF Sensitivity-Based Damage Identification Using Linkage Modeling for Limited Sensor Arrays. Dans: International Journal of Structural Stability and Dynamics, v. 18, n. 8 (août 2018).
https://doi.org/10.1142/s0219455418400023
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Yu, Yang / Dackermann, Ulrike / Li, Jianchun / Subhani, Mahbube (2016): Condition Assessment of Timber Utility Poles Based on a Hierarchical Data Fusion Model. Dans: Journal of Computing in Civil Engineering, v. 30, n. 5 (septembre 2016).
https://doi.org/10.1061/(asce)cp.1943-5487.0000563
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Li, Jianchun / Dackermann, Ulrike / Xu, You-Lin / Samali, Bijan (2011): Damage identification in civil engineering structures utilizing PCA-compressed residual frequency response functions and neural network ensembles. Dans: Structural Control and Health Monitoring, v. 18, n. 2 (mars 2011).
https://doi.org/10.1002/stc.369
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Dackermann, Ulrike / Elsener, Roman / Li, Jianchun / Crews, Keith (2016): A comparative study of using static and ultrasonic material testing methods to determine the anisotropic material properties of wood. Dans: Construction and Building Materials, v. 102 (janvier 2016).
https://doi.org/10.1016/j.conbuildmat.2015.07.195
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Dackermann, Ulrike / Li, Jianchun / Rijal, Rajendra / Crews, Keith (2016): A dynamic-based method for the assessment of connection systems of timber composite structures. Dans: Construction and Building Materials, v. 102 (janvier 2016).
https://doi.org/10.1016/j.conbuildmat.2015.10.009
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Dackermann, Ulrike / Crews, Keith / Kasal, Bohumil / Li, Jianchun / Riggio, Mariapaola / Rinn, Frank / Tannert, Thomas (2014): In situ assessment of structural timber using stress-wave measurements. Dans: Materials and Structures, v. 47, n. 5 (mai 2014).
https://doi.org/10.1617/s11527-013-0095-4
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Samali, Bijan / Dackermann, Ulrike / Li, Jianchun (2012): Location and Severity Identification of Notch-Type Damage in a Two-Storey Steel Framed Structure Utilising Frequency Response Functions and Artificial Neural Network. Dans: Advances in Structural Engineering, v. 15, n. 5 (mai 2012).
https://doi.org/10.1260/1369-4332.15.5.743
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Dackermann, Ulrike / Li, Jianchun / Samali, Bijan (2010): Dynamic-Based Damage Identification Using Neural Network Ensembles and Damage Index Method. Dans: Advances in Structural Engineering, v. 13, n. 6 (décembre 2010).
https://doi.org/10.1260/1369-4332.13.6.1001
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Krause, Martin / Dackermann, Ulrike / Li, Jianchun (2015): Elastic wave modes for the assessment of structural timber: ultrasonic echo for building elements and guided waves for pole and pile structures. Dans: Journal of Civil Structural Health Monitoring, v. 5, n. 2 (février 2015).
https://doi.org/10.1007/s13349-014-0087-2
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Yu, Yang / Li, Jianchun / Yan, Ning / Dackermann, Ulrike / Samali, Bijan (2016): Load capacity prediction of in-service timber utility poles considering wind load. Dans: Journal of Civil Structural Health Monitoring, v. 6, n. 3 (juillet 2016).
https://doi.org/10.1007/s13349-016-0156-9