Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …
techniques capable of delivering elegant and affordable solutions which can surpass those …
Brief communication: Critical infrastructure impacts of the 2021 mid-July western European flood event
Germany, Belgium and The Netherlands were hit by extreme precipitation and flooding in
July 2021. This Brief Communication provides an overview of the impacts to large-scale …
July 2021. This Brief Communication provides an overview of the impacts to large-scale …
Mechanistically informed machine learning and artificial intelligence in fire engineering and sciences
MZ Naser - Fire Technology, 2021 - Springer
Fire is a chaotic and extreme phenomenon. While the past few years have witnessed the
success of integrating machine intelligence (MI) to tackle equally complex problems in …
success of integrating machine intelligence (MI) to tackle equally complex problems in …
Evaluating structural response of concrete-filled steel tubular columns through machine learning
Concrete-filled steel tubular (CFST) columns are unique structural members that capitalize
on the synergy between steel and concrete materials. Due to complexities arising from the …
on the synergy between steel and concrete materials. Due to complexities arising from the …
Emergency management systems after disastrous earthquakes using optimization methods: A comprehensive review
Considering the continuous growth of optimization methods and its importance to
Emergency Management (EM) systems, this review paper introduces and discusses the …
Emergency Management (EM) systems, this review paper introduces and discusses the …
Explainable machine learning using real, synthetic and augmented fire tests to predict fire resistance and spalling of RC columns
This paper presents the development of systematic machine learning (ML) approach to
enable explainable and rapid assessment of fire resistance and fire-induced spalling of …
enable explainable and rapid assessment of fire resistance and fire-induced spalling of …
[HTML][HTML] Learning from failure propagation in steel truss bridges
Although truss-type bridge collapses usually have catastrophic consequences, their analysis
present opportunities for improving different aspects in the field of bridge engineering, such …
present opportunities for improving different aspects in the field of bridge engineering, such …
Digital twin for next gen concretes: On-demand tuning of vulnerable mixtures through Explainable and Anomalous Machine Learning
MZ Naser - Cement and Concrete Composites, 2022 - Elsevier
This paper presents a framework for integrating Explainable and Anomalous Machine
Learning (EAML) into a digital twin to enable finetuning of mixtures as a mean to realize next …
Learning (EAML) into a digital twin to enable finetuning of mixtures as a mean to realize next …
RAI: Rapid, Autonomous and Intelligent machine learning approach to identify fire-vulnerable bridges
M Abedi, MZ Naser - Applied Soft Computing, 2021 - Elsevier
Recent surveys have noted that the majority of bridges continue to serve for a prolonged
period of time (+ 40 years) that far exceeds its intended operational lifespan. Given our …
period of time (+ 40 years) that far exceeds its intended operational lifespan. Given our …
Potential of surrogate modelling for probabilistic fire analysis of structures
The interest in probabilistic methodologies to demonstrate structural fire safety has
increased significantly in recent times. However, the evaluation of the structural behavior …
increased significantly in recent times. However, the evaluation of the structural behavior …