Multiscale Numerical Study of Enhanced Ductility Ratios and Capacity in Carbon Fiber-Reinforced Polymer Concrete Beams for Safety Design

Polymers, Journal Year: 2025, Volume and Issue: 17(2), P. 234 - 234

Published: Jan. 17, 2025

Rigid reinforced concrete (RC) frames are generally adopted as stiff elements to make the building structures resistant seismic forces. However, a method has yet be fully sought provide earthquake resistance through optimizing beam and column performance in rigid frame. Due its high corrosion resistance, integration of CFRP offers an opportunity reduce frequent repairs increase durability. This paper presents structural response beams integrated into when subjected events. Without any design provision for systems extreme events, multiscale simulations parametric analyses were performed optimize residual state global performance. Macroparameters, represented by ductility ratio microfactors, have been analyzed using customized version modified compression field theory (MCFT). The main parameters considered reinforcement under tension compression, strength concrete, height-to-width ratio, section cover, confinement level, all which important understand their influence on analysis results highlight increased higher load-carrying capacity CFRP-reinforced tested component compared RC component. These shed light possibility designing components that could improve ductile with energy dissipation suitable applications non-corrosive seismic-resistant buildings. also shows reduced brittleness enhancement failure mode. Numerical experimental showed strong correlation deviation about 8.3%, underlining reliability proposed approach structures.

Language: Английский

---

Advances in the structural performance of reinforced concrete flat plate-column connections under gravity and seismic loads

Journal of Building Pathology and Rehabilitation, Journal Year: 2025, Volume and Issue: 10(1)

Published: Jan. 26, 2025

Language: Английский

---

A Novel Deep Learning Approach for Real-Time Critical Assessment in Smart Urban Infrastructure Systems

Electronics, Journal Year: 2024, Volume and Issue: 13(16), P. 3286 - 3286

Published: Aug. 19, 2024

The swift advancement of communication and information technologies has transformed urban infrastructures into smart cities. Traditional assessment methods face challenges in capturing the complex interdependencies temporal dynamics inherent these systems, risking resilience. This study aims to enhance criticality geographic zones within cities by introducing a novel deep learning architecture. Utilizing Convolutional Neural Networks (CNNs) for spatial feature extraction Long Short-Term Memory (LSTM) networks dependency modeling, proposed framework processes inputs such as total electricity use, flooding levels, population, poverty rates, energy consumption. CNN component constructs hierarchical maps through successive convolution pooling operations, while LSTM captures sequence-based patterns. Fully connected layers integrate features generate final predictions. Implemented Python using TensorFlow Keras on an Intel Core i7 system with 32 GB RAM NVIDIA GTX 1080 Ti GPU, model demonstrated superior performance. It achieved mean absolute error 0.042, root square 0.067, R-squared value 0.935, outperforming existing methodologies real-time adaptability resource efficiency.

Language: Английский

---

Multi-Scale Integrated Corrosion-Adjusted Seismic Fragility Framework for Critical Infrastructure Resilience

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(19), P. 8789 - 8789

Published: Sept. 29, 2024

This study presents a novel framework for integrating corrosion effects into critical infrastructure seismic risk assessment, focusing on reinforced concrete (RC) structures. Unlike traditional fragility curves, which often overlook time-dependent degradation such as corrosion, this methodology introduces an approach incorporating corrosion-induced curves. combines simulation with numerical modeling, using the finite–discrete element method (FDEM) to assess reduction in structural capacity. These results are used adjust capturing increased vulnerability due corrosion. A key novelty of work is development comprehensive assessment that merges corrosion-adjusted curves hazard data estimate long-term risk, introducing cumulative ratio quantify total over structure’s lifecycle. demonstrated through case one-story RC moment frame building, evaluating its under various scenarios and locations. The showed good fit, 3% 14% difference between simulations up 75 years. fitness highlights model’s accuracy predicting Furthermore, findings reveal significant increase particularly moderate intensive environments, by 59% 100%, respectively. insights emphasize importance assessments, offering more accurate effective strategy enhance resilience throughout

Language: Английский

---

Assessing Project Resilience Through Reference Class Forecasting and Radial Basis Function Neural Network

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(22), P. 10433 - 10433

Published: Nov. 13, 2024

A project needs to be able anticipate potential threats, respond effectively adverse events, and adapt environmental changes. This overall capability is known as resilience. In order make efficient decisions when the subjected disruption, such adjusting budget, reformulating work plan, rationalizing allocation of resources, it necessary quantitatively understand level Therefore, this paper develops a novel approach for forecasting performance, illustrating changes in performance levels during disruption recovery phases thus assessing While there are several methods resilience existing research, majority assessment approaches originate from within projects highly subjective, which makes difficult objectively reflect Moreover, availability samples limited, forecast performance. view fact that Reference Class Forecasting (RCF) technique avoids subjectivity Radial Basis Function (RBF) neural network better at small sample datasets, therefore combines RCF RBF construct model forecasts current after experiencing further Specifically, first presents conceptual assessment; subsequently, an takes into account duration, risk before based on developed disruption; finally, assessed through calculating ratio loss The trained validated using 64 completed construction with disruptions datasets. results show average relative errors between schedule index (SPI) real values less than 5%, R2 training set testing 0.991 0.964, respectively, discrepancy forecasted 10%. These illustrate performs well feasible quantifying resilience, clarifying its impact situations, facilitating decision-makers reasonable decisions.

Language: Английский

---

Integrating Building- and Site-Specific and Generic Fragility Curves into Seismic Risk Assessment: A PRISMA-Based Analysis of Methodologies and Applications

CivilEng, Journal Year: 2024, Volume and Issue: 5(4), P. 1011 - 1041

Published: Nov. 8, 2024

Fragility curves are fundamental tools in seismic risk assessments, providing insights into the vulnerability of structures to earthquake-induced damages. These curves, which plot probability a structure reaching or exceeding various damage states against earthquake intensity, critical for developing effective modification strategies. This review aims present characteristics between building- and site-specific fragility incorporate detailed local characteristics, generic that apply broader, more generalized parameters. We utilize PRISMA (Preferred Reporting Items Systematic Reviews Meta-Analyses) methodology systematically literature address key research questions about methodological differences, applications, implications these curve types assessing risks. The methods involved comprehensive search combination existing studies on topic, focusing how developed applied real-world scenarios. results from this show while precise, require extensive data therefore complex costly develop. In contrast, though less accurate, offer cost-effective solution preliminary assessments over large areas. conclusions drawn suggest each type has its merits, choice should be guided by specific requirements assessment task, including available resources need precision estimations.

Language: Английский

---

The Use of Externally Bonded Fibre Reinforced Polymer Composites to Enhance the Seismic Resilience of Single Shear Walls: A Nonlinear Time History Assessment

Journal of Composites Science, Journal Year: 2024, Volume and Issue: 8(6), P. 229 - 229

Published: June 17, 2024

In medium- to high-rise buildings, single shear walls (SSWs) are often used resist lateral force due wind and earthquakes. They designed dissipate seismic energy mainly through plastic hinge zones at the base. However, they display large post-earthquake deformations that can give rise many economic safety concerns within buildings. Hence, primary objective of this research study is minimize residual in existing SSWs located Western Eastern Canada, thereby enhancing their resilience self-centering capacity. To end, four 20 15 stories, Vancouver Montreal, were meticulously detailed per latest Canadian standards codes. The assessed impact three innovative strengthening schemes on response these 2D nonlinear time history (NLTH) analysis. All involved application Externally Bonded Fiber Reinforced Polymer (EB-FRP) walls. Accordingly, a total 208 NLTH analyses conducted assess effectiveness all configurations. findings unveiled most efficient technique for reducing drift applying layers vertical FRP sheets extreme edges wall, full wrapping walls, zone. Nevertheless, it noteworthy implementing may lead an increase bending moment base demands

Language: Английский

---