Engineered geopolymer composites: a comprehensive state-of-the-art review on materials' perspective
KK Yaswanth, KHK Reddy, N Anusha… - Archives of Civil and …, 2024 - Springer
Engineered geopolymer composite (EGC) is considered an excellent innovation in imparting
the high ductility to the concrete composites with 100% eco-friendly and sustainable …
the high ductility to the concrete composites with 100% eco-friendly and sustainable …
Machine learning and interactive GUI for concrete compressive strength prediction
Concrete compressive strength (CS) is a crucial performance parameter in concrete
structure design. Reliable strength prediction reduces costs and time in design and prevents …
structure design. Reliable strength prediction reduces costs and time in design and prevents …
Settlement prediction of immersed tunnel considering time-dependent foundation modulus
SY He, C Tang, WH Zhou - Tunnelling and Underground Space …, 2024 - Elsevier
The focus of immersed tunnel research has primarily revolved around settlement monitoring
or prediction. However, there has been a lack of discussion regarding the time-dependent …
or prediction. However, there has been a lack of discussion regarding the time-dependent …
Machine learning-based acoustic emission technique for corrosion-induced damage monitoring in reinforced concrete structures
A Thirumalaiselvi, S Sasmal - Engineering Applications of Artificial …, 2024 - Elsevier
Early-stage detection of corrosion in reinforcement embedded inside concrete, generally
considered as the major problem in structures under extreme marine environments, can …
considered as the major problem in structures under extreme marine environments, can …
Solving partial differential equations using large-data models: a literature review
AM Hafiz, I Faiq, M Hassaballah - Artificial Intelligence Review, 2024 - Springer
Abstract Mathematics lies at the heart of engineering science and is very important for
capturing and modeling of diverse processes. These processes may be naturally-occurring …
capturing and modeling of diverse processes. These processes may be naturally-occurring …
Data-driven and physics-informed neural network for predicting tunnelling-induced ground deformation with sparse data of field measurement
Accurately predicting tunnelling-induced ground deformation (TIGD) is crucial for the safety
of tunnel construction and protection of surrounding environment. Existing analytical studies …
of tunnel construction and protection of surrounding environment. Existing analytical studies …
[HTML][HTML] Unmasking air quality: A novel image-based approach to align public perception with pollution levels
TC Lin, SY Wang, ZY Kung, YH Su, PT Chiueh… - Environment …, 2023 - Elsevier
In the quest to reconcile public perception of air pollution with scientific measurements, our
study introduced a pioneering method involving a gradient boost-regression tree model …
study introduced a pioneering method involving a gradient boost-regression tree model …
Machine learning approach for predicting compressive strength in foam concrete under varying mix designs and curing periods
Efforts to reduce the weight of buildings and structures, counteract the seismic threat to
human life, and cut down on construction expenses are widespread. A strategy employed to …
human life, and cut down on construction expenses are widespread. A strategy employed to …
Approximating families of sharp solutions to Fisher's equation with physics-informed neural networks
FM Rohrhofer, S Posch, C Gößnitzer… - Computer Physics …, 2025 - Elsevier
This paper employs physics-informed neural networks (PINNs) to solve Fisher's equation, a
fundamental reaction-diffusion system with both simplicity and significance. The focus is on …
fundamental reaction-diffusion system with both simplicity and significance. The focus is on …
A least squares–support vector machine for learning solution to multi-physical transient-state field coupled problems
X Han, X Zhao, Y Wu, Z Qu, G Li - Engineering Applications of Artificial …, 2024 - Elsevier
The least squares–support vector machine (LS-SVM) method has achieved remarkable
success in solving electromagnetic equations. However, the boundaries of the entire …
success in solving electromagnetic equations. However, the boundaries of the entire …