Search Results - "Naser, M. Z."

Observational Analysis of Fire-Induced Spalling of Concrete through Ensemble Machine Learning and Surrogate Modeling by Naser, M. Z

“…AbstractDespite ongoing research efforts, we continue to fall short of arriving at a consistent representation of fire-induced spalling of concrete. This is…”
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Autonomous Fire Resistance Evaluation by Naser, M. Z

“…AbstractThe structural fire engineering community has been slowly evolving over the past few decades. While we continue to favor a classical stand toward…”
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Integrating Machine Learning Models into Building Codes and Standards: Establishing Equivalence through Engineering Intuition and Causal Logic by Naser, M. Z.

“…AbstractThe traditional approach to formulating building codes often is slow and labor-intensive, and may struggle to keep pace with the rapid evolution of…”
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Discovering Graphical Heuristics on Fire-Induced Spalling of Concrete Through Explainable Artificial Intelligence by Tapeh, Arash Teymori Gharah, Naser, M. Z.

“…Fire-induced spalling of concrete continues to be an intriguing and intricate research problem. A deep dive into the open literature highlights the alarming…”
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Importance factor for design of bridges against fire hazard by Kodur, V.K.R., Naser, M.Z.

“…•Importance factor (IF) for overcoming fire hazard in bridges is developed.•Validity of the proposed approach to importance factor is established.•Importance…”
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Experimental Investigation and Modeling of the Thermal Effect on the Mechanical Properties of Polyethylene-Terephthalate FRP Laminates by Mhanna, Haya H, Hawileh, Rami A, Abuzaid, Wael, Naser, M. Z, Abdalla, Jamal A

“…AbstractRecent advancements in material sciences have led to the development of new fiber-reinforced polymer (FRP) systems that, unlike traditional FRPs, are…”
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Evaluating Urban Stream Flooding with Machine Learning, LiDAR, and 3D Modeling by Bolick, Madeleine M., Post, Christopher J., Naser, M. Z., Forghanparast, Farhang, Mikhailova, Elena A.

“…Flooding in urban streams can occur suddenly and cause major environmental and infrastructure destruction. Due to the high amounts of impervious surfaces in…”
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Predicting Wildfire Ember Hot-Spots on Gable Roofs via Deep Learning by Al-Bashiti, Mohammad Khaled, Nguyen, Dac, Naser, M. Z., Kaye, Nigel B.

“…Ember accumulation on and around homes can lead to spot fires and home ignition. Post wildland fire assessments suggest that this mechanism is one of the…”
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Mechanistically Informed Machine Learning and Artificial Intelligence in Fire Engineering and Sciences by Naser, M. Z.

“…Fire is a chaotic and extreme phenomenon. While the past few years have witnessed the success of integrating machine intelligence (MI) to tackle equally…”
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Thermal-stress analysis of RC beams reinforced with GFRP bars by Hawileh, R.A., Naser, M.Z.

“…This paper aims to develop a 3D nonlinear finite element (FE) model that is capable of accurately predicting the performance of reinforced concrete (RC) beams…”
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CLEMSON: An Automated Machine-Learning Virtual Assistant for Accelerated, Simulation-Free, Transparent, Reduced-Order, and Inference-Based Reconstruction of Fire Response of Structural Members by Naser, M. Z.

“…AbstractThis paper introduces CLEMSON, an automated machine-learning (AutoML) virtual assistant (VA) that enables engineers to carry acCeLErated,…”
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Artificial Intelligence, Machine Learning, and Deep Learning in Structural Engineering: A Scientometrics Review of Trends and Best Practices by Tapeh, Arash Teymori Gharah, Naser, M. Z.

“…Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging techniques capable of delivering elegant and affordable solutions…”
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Heuristic machine cognition to predict fire-induced spalling and fire resistance of concrete structures by Naser, M.Z.

“…The exceptional behavior of concrete under fire conditions is often jeopardized by concrete's propensity to spall. While published works seem to agree on the…”
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An engineer's guide to eXplainable Artificial Intelligence and Interpretable Machine Learning: Navigating causality, forced goodness, and the false perception of inference by Naser, M.Z.

“…While artificial intelligence (AI), and by extension machine learning (ML), continues to be adopted in parallel engineering disciplines, the integration of…”
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Extraterrestrial construction materials by Naser, M.Z.

“…In recognition of the 50th anniversary of the first manned lunar landing, the National Aeronautics and Space Administration (NASA), together with the European…”
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Causality and causal inference for engineers: Beyond correlation, regression, prediction and artificial intelligence by Naser, M. Z.

“…In order to engineer new materials, structures, systems, and processes that address persistent challenges, engineers seek to tie causes to effects and…”
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Demystifying Ten Big Ideas and Rules Every Fire Scientist & Engineer Should Know About Blackbox, Whitebox and Causal Artificial Intelligence by Naser, M. Z.

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Fire hazard in transportation infrastructure: Review, assessment, and mitigation strategies by KODUR, Venkatesh, NASER, M. Z.

“…This paper reviews the fire problem in critical transportation infrastructures such as bridges and tunnels. The magnitude of the fire problem is illustrated,…”
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Machine learning framework for predicting failure mode and shear capacity of ultra high performance concrete beams by Solhmirzaei, Roya, Salehi, Hadi, Kodur, Venkatesh, Naser, M.Z.

“…•A machine learning framework is developed to predict failure mode of UHPC beams.•Genetic programing algorithms is applied for predicting shear capacity of…”
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Can past failures help identify vulnerable bridges to extreme events? A biomimetical machine learning approach by Naser, M. Z.

“…With limited resources to properly maintain and upgrade transportation infrastructure, bridges often end up exceeding their expected service lifespan; thus,…”
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