Article
Construction & Building Technology
M. Z. Naser
Summary: The research demonstrates the importance of utilizing modern computing techniques, such as data science and machine learning algorithms, in structural fire engineering applications for analyzing and predicting fire-induced spalling phenomenon.
JOURNAL OF MATERIALS IN CIVIL ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Arash Teymori Gharah Tapeh, M. Z. Naser
Summary: Fire-induced spalling of concrete is a complex research problem, and existing theories on predicting spalling show discrepancy and inconsistency. This paper uses explainable Artificial Intelligence (XAI) to validate existing theories and discover solutions to predict concrete spalling. The proposed solutions are presented in the form of graphs and nomograms, enabling researchers and engineers to easily identify the propensity of concrete mixtures to spalling.
Article
Automation & Control Systems
Yuming Li, Wei Zhang, Yanyan Liu, Rudong Jing, Changsong Liu
Summary: This paper proposes an object detection model based on DETR for fire and smoke detection, which simplifies the detection pipeline and builds an end-to-end detector. By adding a normalization-based attention module in the feature extraction stage and using multiscale deformable attention in the encoder-decoder structure, the model achieves improved detection performance while reducing complexity.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Construction & Building Technology
Bruno Fernandes, Helene Carre, Jean-Christophe Mindeguia, Celine Perlot, Christian La Borderie
Summary: Concrete made with recycled aggregates (RCA) has specific properties and a higher risk of spalling under fire conditions compared to concrete made with natural aggregates (NA). Increasing the replacement rate of recycled coarse aggregates in concrete leads to a higher spalling degree up to a certain point, beyond which further increase in replacement rate does not result in higher spalling. The use of RCA also alters the physical properties of concrete, particularly water content, which can trigger spalling.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Construction & Building Technology
Katarzyna Mroz, Izabela Hager
Summary: The paper introduces a new method for identifying the form and intensity of concrete spalling by analyzing the acoustic signal emitted. The intensity of spalling is assessed and monitored during fire exposure by analyzing recorded sound from the furnace chamber. Signal amplitude and frequency values are used to categorize different types of spalling phenomena.
CEMENT AND CONCRETE RESEARCH
(2021)
Article
Construction & Building Technology
Mohammad Khaled al-Bashiti, M. Z. Naser
Summary: This paper adopts eXplainable Artificial Intelligence (XAI) to identify key factors and extract new insights into fire-induced spalling of concrete. A validated XAI model is developed, which not only accurately predicts spalling but also explains the reasoning behind its predictions. The study reveals eight key factors that heavily influence spalling and quantifies their contributions.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Construction & Building Technology
Zilong Wang, Tianhang Zhang, Xiqiang Wu, Xinyan Huang
Summary: This study explores the real-time prediction of transient fire scenarios using deep learning algorithms and external smoke images, demonstrating the potential of deep learning in determining hidden fire information and its application in smart firefighting.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Construction & Building Technology
Bruno Fernandes, Helene Carre, Jean-Christophe Mindeguia, Celine Perlot, Christian La Borderie
Summary: The use of recycled concrete aggregates (RCA) has been proven as a good solution for sustainable concrete production, but its performance at high temperatures is critical for building structures. This paper reviews and discusses the mechanical and thermal properties of concrete made with RCA at high temperatures to identify future research needs.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Alessandra De Paola, Salvatore Gaglio, Andrea Giammanco, Giuseppe Lo Re, Marco Morana
Summary: Modern smart environments present challenges in designing intelligent algorithms to assist users, such as trajectory recommendations and itinerary planning in the face of diverse points of interest. A multi-agent itinerary suggestion system is proposed to address these challenges, utilizing reinforcement learning to provide high-quality suggestions and overcome issues like cold-start and preference elicitation. Real-life deployments have shown the effectiveness of the approach in scenarios such as smart campuses and theme parks.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2021)
Article
Construction & Building Technology
Andre Klimek, Ludwig Stelzner, Sascha Hothan, Andreas Rogge
Summary: The size effect plays an important role in concrete spalling, and different specimen sizes have different impacts on spalling. This study investigates six different concrete mixtures and three specimen sizes, and finds that smaller specimen sizes significantly reduce spalling.
MATERIALS AND STRUCTURES
(2022)
Article
Chemistry, Physical
Rujia Qiao, Yinbo Guo, Hang Zhou, Huihui Xi
Summary: This study aims to establish an analytical model to estimate the influence of concrete spalling on fire-damage depth prediction. Through conducting fire tests, the spalling phenomenon and characteristics of concrete were observed. Based on experimental results, the moisture content of concrete was identified as one of the key factors of spalling. By using the proposed analytical model, the spalling depth related to the temperature rise of tunnel fire could be predicted.
Article
Construction & Building Technology
Mohammad Khaled al-Bashiti, M. Z. Naser
Summary: This paper presents a comprehensive statistical investigation of the largest database on fire-induced spalling of concrete collected to date, examining 43 factors and proposing future research directions.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Review
Multidisciplinary Sciences
Shujaat Hussain Buch, Umesh Kumar Sharma
Summary: This article reviews various methods for predicting the fire resistance of reinforced concrete (RC) columns and examines the influence of structural, material, mechanical, and heating-related parameters on their fire resistance. The feasibility of these methods in determining the fire resistance of RC columns is also discussed. The role of spalling of concrete on fire resistance is emphasized, and a systematic review of experimental data on fire resistance of RC columns is conducted. Parametric variability and experimental discrepancy are studied for determining the fire resistance of RC columns.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Construction & Building Technology
Jianqing Lin, Yuli Dong, Jintao Duan, Dashan Zhang, Wei Zheng
Summary: The study on single-tunnel fires in concrete immersed tunnels revealed that fires can impact unexposed tunnels, causing deformation and cracking. Cracks in the immersed tunnel consisted mainly of circumferential and longitudinal cracks, with the former connected in places without stirrups. Analysis of basic AE parameters and 3D scanner results showed that concrete spalling was caused by different mechanisms, with a maximum depth of 110 mm.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Construction & Building Technology
Jin Jiang, Ming Wu, Mao Ye
Summary: This study introduces two artificial neural network (ANN) models to assess the resistance of fiber reinforced concrete containing polypropylene (PP) fiber and steel fiber to fire spalling at elevated temperature. The models achieve a predictive accuracy of 89.6% and 84.4% respectively, indicating the feasibility of using ANN for predicting the explosive spalling threat of hybrid fiber reinforced concrete.
MAGAZINE OF CONCRETE RESEARCH
(2023)
Review
Computer Science, Interdisciplinary Applications
Arash Teymori Gharah Tapeh, M. Z. Naser
Summary: This review aims to promote the integration of artificial intelligence techniques into the field of structural engineering. It provides a comprehensive analysis and review of commonly used algorithms, techniques, and best practices, with a focus on applications in earthquake, wind, fire engineering, etc.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Materials Science, Multidisciplinary
Aditya Daware, Abdul Basit Peerzada, M. Z. Naser, Prasada Rangaraju, Brad Butman
Summary: Investigated the fire-induced degradation of compressive strength in masonry and found a lower level of degradation, as well as higher retention of strength under post-fire conditions.
FIRE AND MATERIALS
(2023)
Article
Engineering, Civil
Huanting Zhou, Huaidong Li, Han Qin, Tianfu Liang, M. Z. Naser
Summary: Prestressed steel-concrete composite beams can improve their fire resistance by reinforcing the webs with concrete, preventing buckling and horizontal deflection. Finite element models further revealed the mechanisms of fire response.
ENGINEERING STRUCTURES
(2023)
Article
Materials Science, Multidisciplinary
Ghada Karaki, Mohannad Z. Naser
Summary: Probabilistic approaches provide a realistic assessment of structures under fire conditions and overcome limitations of traditional methods. This paper presents a methodology to develop temperature-dependent probabilistic models for commonly used construction materials. The newly derived models are compared against fire codes and machine learning models.
FIRE AND MATERIALS
(2023)
Article
Green & Sustainable Science & Technology
M. Z. Naser
Summary: Machine learning presents attractive opportunities in engineering by bypassing the limitations of traditional methods, but also brings unique challenges such as heavy reliance on large datasets and computing facilities. This paper emphasizes the importance of energy consumption and carbon emissions in ML modeling and proposes the concept of Green ML. By examining different ML algorithms on a large dataset, it is found that adopting simple models can significantly reduce energy consumption and carbon emissions while maintaining comparable accuracy.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Construction & Building Technology
M. Z. Naser, Aybike Ozyuksel Ciftcioglu
Summary: Experiments are the most reliable way to understand fire-related phenomena. The goal of tests is to uncover the process behind the data we observe and determine the causes of these observations. This paper introduces an approach that combines causal discovery and causal inference to evaluate the fire resistance of structural members.
STRUCTURAL CONCRETE
(2023)
Article
Engineering, Multidisciplinary
M. Z. Naser, Aybike Ozyuksel Ciftcioglu
Summary: The expensive and unique facilities required for fire testing make it difficult to conduct comprehensive experimental campaigns, resulting in limited testing of specimens. Addressing causal and hypothetical questions about fire response becomes challenging for statistical and machine learning methods. To overcome this, this paper presents a causal approach to answer such questions by adopting principles of causal inference to reconstruct the deformation-time history of reinforced concrete (RC) columns and propose an idealized fire response. The findings highlight the significant influence of loading level, aggregate type, and longitudinal steel ratio on the deformation history of fire-exposed RC columns.
Review
Construction & Building Technology
Balamurali Kanagaraj, N. Anand, Diana Andrushia, M. Z. Naser
Summary: This article provides a detailed study of different RSC materials suitable for radiation shielding and evaluates their shielding performance, hardening characteristics, and serviceability. It also comprehensively reviews the potential of RSC as an innovative building material for radiation protection and highlights current knowledge gaps and future research directions in this field.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Construction & Building Technology
Mohammad Khaled al-Bashiti, M. Z. Naser
Summary: This paper presents a comprehensive statistical investigation of the largest database on fire-induced spalling of concrete collected to date, examining 43 factors and proposing future research directions.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Engineering, Civil
Ahmad Tarawneh, Eman Saleh, Abdullah Alghossoon, M. Z. Naser
Summary: Existing shear design models for reinforced concrete are not accurate and conservative. A modified shear design model consistent with the current ACI 318-19 model is proposed, which accounts for FRP axial stiffness and has higher accuracy. The proposed model outperformed the ACI 318-19 model in statistical measures when applied to steel-RC concrete beams.
ENGINEERING STRUCTURES
(2023)
Article
Materials Science, Multidisciplinary
Rami A. A. Hawileh, Syed Shah Quadri, Jamal A. A. Abdalla, Maha Assad, Blessen Skariah Thomas, Deanna Craig, M. Z. Naser
Summary: This research investigated the residual mechanical properties of normal and recycled aggregate concrete under elevated temperatures. Concrete specimens with different percentages of recycled aggregates (0%, 50%, 75%, and 100%) were exposed to various temperatures (25°C, 200°C, 400°C, and 600°C) in a muffle furnace. The study found that the increase in recycled aggregate content did not have a significant effect on the mechanical strength degradation of concrete. However, a linear decrease in density was observed at 400°C with increasing percentage of recycled aggregates. Simplified equations were proposed to estimate the degradation of mechanical properties of recycled aggregate concrete at higher temperatures, and the incorporation of recycled aggregates resulted in satisfactory residual performance.
FIRE AND MATERIALS
(2023)
Article
Engineering, Industrial
Zhiyuan Qin, M. Z. Naser
Summary: This paper presents a novel framework for quantifying the uncertainty in the inverse problems of suspended nonstructural systems. The framework combines machine learning and model-driven stochastic Gaussian process model calibration to account for geometric complexity through Bayesian inference. The proposed framework is validated using a large-scale shaking table test and simulated data, showing computational soundness, scalability, and optimal generalizability.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Review
Construction & Building Technology
Deanna Craig, M. Z. Naser
Summary: This paper discusses the unique nature of structural fire engineering and highlights the reliance on expensive fire tests and outdated procedures. It compares global efforts in performance-based fire design and finds that European and Oceanian efforts are more advanced. Most performance-based fire designs are related to steel and composite structures.
JOURNAL OF STRUCTURAL FIRE ENGINEERING
(2023)
Article
Construction & Building Technology
Maha Assad, Rami Hawileh, Ghada Karaki, Jamal Abdalla, M. Z. Naser
Summary: This research investigates the behavior of reinforced concrete walls under fire conditions and identifies the thermal and mechanical factors that affect their performance. A 3D finite element model is developed to predict the response of the walls and is validated through experimental tests. The study finds that the fire resistance of the walls is compromised under hydrocarbon fire, and the minimum wall thickness specified by current regulations may not be sufficient.
JOURNAL OF STRUCTURAL FIRE ENGINEERING
(2023)
Article
Construction & Building Technology
Haley Hostetter, M. Z. Naser
Summary: This paper examines the architectural engineering features of psychiatric hospitals from the perspective of fire hazards, and analyzes the common causes and mitigation strategies of structural fires in these hospitals. By studying the shortcomings of past designs, it aims to enhance the understanding of current and future professionals in mitigating fire risks for vulnerable populations in healthcare facilities.
JOURNAL OF ARCHITECTURAL ENGINEERING
(2023)