Axial Capacity of FRP-Reinforced Concrete Columns: Computational Intelligence-Based Prognosis for Sustainable Structures

Buildings, Journal Year: 2022, Volume and Issue: 12(12), P. 2137 - 2137

Published: Dec. 5, 2022

Due to the corrosion problem in reinforced concrete structures, use of fiber-reinforced polymer (FRP) bars may be preferred place traditional reinforcing steel. FRP are used constructions boost strength structural elements and retain their longevity. In this study, axial load carrying capacity (ALCC) FRP-reinforced columns has been evaluated using analytical, as well machine learning, models. A total fourteen popular analytical models one proposed learning-based model were estimate ALCC columns. The learning is based on an artificial neural network (ANN) method. performance ANN, models, assessed six different indices. R-value developed ANN 0.9758, followed by NS value 0.9513. It found that mean absolute percentage error best-fitted 328.71% higher than model, root-mean-square 211.97% model. data demonstrate performs better other quick easy-to-use

Language: Английский

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Computational Intelligence-Based Structural Health Monitoring of Corroded and Eccentrically Loaded Reinforced Concrete Columns

Shock and Vibration, Journal Year: 2023, Volume and Issue: 2023, P. 1 - 21

Published: Feb. 21, 2023

Corrosion of embedded steel reinforcement is the prime influencing factor that deteriorates structural performance and reduces serviceability reinforced concrete (RC) structures, especially during earthquakes. In elements, RC columns play a vital role in transferring superstructure’s load to substructure. The deterioration can affect structures’ overall performance. Hence, it becomes essential estimate remaining life deteriorated columns. literature, only limited analytical models are available calculate corroded eccentrically loaded As number dependent parameters increases, assessing residual elements providing practically applicable suitable model become very complex. Machine learning (ML)-based prediction beneficial dealing with such complex databases. this article, an ML-based artificial neural network (ANN), Gaussian process regression (GPR), support vector machine (SVM) algorithms have been applied strength ML accessed using commonly used indices, namely, coefficient determination (R2), root mean square error (RMSE), absolute (MAE), percentage (MAPE), a-20 index, Nash–Sutcliffe (NS). results proposed ANN compared existing identify suitability best model. Based on analysis, precision GPR SVM lower than processed revealed R2 value for training, testing, validation datasets 0.9908, 0.9757, 0.9855, respectively. MAPE, MAE, RMSE, NS, index all 8.31%, 48.35 kN, 72.53 0.9886, 0.8978, terms 225.77% higher sensitivity analysis demonstrates compressive plays most significant load-carrying capacity reliable, accurate, fast, cost effective. This also be as health-monitoring tool detect early damages

Language: Английский

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A Critical Review on the Indoor Air Quality Status of Schools in India

Current World Environment, Journal Year: 2025, Volume and Issue: 19(3), P. 1061 - 1076

Published: Jan. 10, 2025

The quality air in the indoor environment significantly impacts anthropological health and well-being. Suboptimal environmental can lead to respiratory other diseases among students worldwide. objective of this study is scientifically evaluate summarize available data on Indoor Air Quality Indian school settings, based a review relevant research papers. From 172 articles analysed, there are only 36 related perspectives quality. In an scenario, thermal comfort inside classroom directly proportional natural ventilation. illustrates that occupants all over India adapted temperature range 17 - 33.70 C, with difference climate. Case studies schools have consistently identified eight key pollutants concern: Carbon monoxide (CO), Particulate matter (PM), Nitrogen dioxide (NO2), Sulphur (SO2), Ozone (O3), Volatile Organic Compounds (VOCs), Bioaerosols. Climate change may worsen cause new problems as frequency adverse outdoor conditions changes. Further essential pollution its associated impacts, utilizing standardized protocols methodologies ensure comparable reliable

Language: Английский

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School built environment and children’s health: a scientometric analysis

Reviews on Environmental Health, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Abstract The school built environment is closely related to children’s health, and research on this topic increasing. However, bibliometric analyses seeking provide a comprehensive understanding of the landscape key themes in field are lacking. This study comprehensively explored global trends hotspots associations between health. We used scientometric analysis review progress. temporal distribution publications, scientific collaborations, hotspots, frontiers, co-citations over past 30 years were analyzed. results show that number publications rose significantly 1987 2025, with focusing physical activity, performance, behavior, perception, thermal comfort, indoor air quality. Environmental health fall into four main groups: activities, intelligent learning environments, environments interiors, natural environments. Health outcomes measures reflect physiological, psychological, cognitive, behavioral, factors discussed. provides broad issues

Language: Английский

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Digital twin-enhanced predictive maintenance for indoor climate: A parallel LSTM-autoencoder failure prediction approach

Energy and Buildings, Journal Year: 2023, Volume and Issue: 301, P. 113738 - 113738

Published: Nov. 10, 2023

Language: Английский

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Event-Specific Transmission Forecasting of SARS-CoV-2 in a Mixed-Mode Ventilated Office Room Using an ANN

International Journal of Environmental Research and Public Health, Journal Year: 2022, Volume and Issue: 19(24), P. 16862 - 16862

Published: Dec. 15, 2022

The emerging novel variants and re-merging old of SARS-CoV-2 make it critical to study the transmission probability in mixed-mode ventilated office environments. Artificial neural network (ANN) curve fitting (CF) models were created forecast R-Event. R-Event is defined as anticipated number new infections that develop particular events occurring over course time any space. In spring summer 2022, real-time data for an environment collected India a space composite climate. performances proposed CF ANN compared with respect traditional statistical indicators, such correlation coefficient, RMSE, MAE, MAPE, NS index, a20-index, order determine merit two approaches. Thirteen input features, namely indoor temperature (TIn), relative humidity (RHIn), area opening (AO), occupants (O), per person (AP), volume (VP), CO2 concentration (CO2), air quality index (AQI), outer wind speed (WS), outdoor (TOut), (RHOut), fan (FS), conditioning (AC), selected target. main objective was relationship between level R-Event, ultimately producing model forecasting building coefficients this case 0.7439 0.9999, respectively. This demonstrates more accurate prediction than model. results show reliable significantly values offices.

Language: Английский

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Prediction of Indoor Air Quality Using Artificial Intelligence

Published: Feb. 10, 2023

For well-being and good health, indoor air quality (IAQ) is an important concern as most of the people spend almost total their time in different types buildings. Research IAQ gaining momentum multidisciplinary interest rapidly. Artificial intelligence (AI) methods have significantly transformed research area prediction due to outstanding performance. Due increasing availability data rapid expansion AI techniques, it vital investigate development forecasting using techniques a complete quantitative manner. Therefore, overview presented first portion this chapter. Further, relevant parameters its effects sources are mentioned next section. In process, frontier carried out domain with application was explored by adopting state-of-the-art literature. This chapter gives useful information on future AI-based forecasting. Readers will benefit from more integrated view associated within built environment.

Language: Английский

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Indoor Environmental Quality, Pupils’ Health, and Academic Performance—A Literature Review

Buildings, Journal Year: 2023, Volume and Issue: 13(9), P. 2172 - 2172

Published: Aug. 27, 2023

Classrooms have more students per square meter than other buildings such as offices, making them crowded. In addition, children respire adults and are in contact with one another often. For appropriate student comfort, wellbeing, health, including reducing the risk of transferring communicable diseases (for example, COVID-19) school setting, adequate ventilation thermal comfort is recommended, along regular cleaning, especially high-contact surfaces. However, this may lead to increased energy usage, mechanically ventilated schools. While natural conserves energy, its usage be limited temperate regions, during cold seasons, will required for heating order achieve comfort. tropics, alone insufficient students’ due possibility unconditioned warm or outdoor air entering classroom environment. Additionally, difficult control, there overventilation underventilation rate being dependent on environmental condition windspeed. This current traditional literature review appraises previous indoor quality (IEQ) ventilation, moisture mold, cleanliness Furthermore, a further was performed effect IEQ (indoor comfort) health academic outcomes summarize existing knowledge that can help researchers avoid research duplication identify gaps future studies.

Language: Английский

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Air quality modeling for smart cities of India by nature inspired AI—A sustainable approach

Advances in computers, Journal Year: 2024, Volume and Issue: unknown, P. 129 - 154

Published: Jan. 1, 2024

Language: Английский

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Overcooling in UAE homes: health issues and implications for learning efficiency

Architectural Science Review, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 14

Published: June 3, 2024

From 1990 to 2016, , air conditioning usage in the UAE increased from 25 125 terawatt hours, making up 70% of country's electricity consumption. Overcooling 18°C homes is common, leading health issues and reduced learning efficiency during Covid-19 pandemic. This study uses Electroencephalograms (EEG) examine indoor thermal environments' impact on efficiency. An artificial climate chamber set at 24°C or 20.5°C monitored 64 healthy males aged 21–29 a 70-minute EEG session. Participants took Visual Continuous Performance test had their academic performance evaluated. Seven brain areas were analyzed for attention power frequency. Results showed lower temperatures (20.5°C) frequency, indicating better than 24°C. Statistical analysis revealed that concentration was achieved faster temperatures. highlights importance optimizing improved well-being.

Language: Английский

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