Expansion Characteristics and Shear Behavior of Reinforced Concrete Beams Under Non-Uniform Expansion Induced by Alkali–Silica Reaction

Materials, Journal Year: 2025, Volume and Issue: 18(2), P. 312 - 312

Published: Jan. 11, 2025

Alkali–silica reaction (ASR) is an important factor that seriously affects the durability of reinforced concrete (RC) structures. The current research on alkali-aggregate mainly focuses deterioration mechanism materials and mechanical properties standard specimens. However, there a gap in field effect damage level RC In this study, five beams were tested, depth location alkali solution immersion used as test variables, with aim investigating how steel reinforcement suppresses expansion caused by ASR evaluating shear behavior after non-uniform damage. results study showed increase accelerated rate development, while inhibited development. Compared undamaged beams, initially generates stresses within concrete, which cracking yield loads delay reduces ultimate load-carrying capacity ductility due to disruption microstructure. Finally, chemo-mechanical analysis method proposed based experimental results, incorporate model pore mechanics model. efficacy precision are validated through comparison results.

Language: Английский

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FS-DDPG: Optimal Control of a Fan Coil Unit System Based on Safe Reinforcement Learning

Buildings, Journal Year: 2025, Volume and Issue: 15(2), P. 226 - 226

Published: Jan. 14, 2025

To optimize the control of fan coil unit (FCU) systems under model-free conditions, researchers have integrated reinforcement learning (RL) into processes system pumps and fans. However, traditional RL methods can lead to significant fluctuations in flow fans, posing a safety risk. address this issue, we propose novel FCU method, Fluctuation Suppression–Deep Deterministic Policy Gradient (FS-DDPG). The key innovation lies applying constrained Markov decision process model problem, where penalty term for constraints is incorporated reward function, constraint tightening introduced limit action space. In addition, validate performance proposed established variable operating conditions simulation platform based on parameters actual ten years historical weather data. platform’s correctness effectiveness were verified from three aspects: heat transfer, air side water side, different dry wet conditions. experimental results show that compared with DDPG, FS-DDPG avoids 98.20% pump 95.82% fluctuations, ensuring equipment. Compared DDPG RBC, achieves 11.9% 51.76% energy saving rates, respectively, also shows better terms operational satisfaction. future, will further improve scalability apply method more complex environments.

Language: Английский

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Sensorless Position Estimation in Electromagnetic Launchers Using Recurrent Neural Networks with Repeated k-Fold Cross-Validation

Arabian Journal for Science and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 17, 2025

Language: Английский

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Development of Robust Machine Learning Models for Predicting Flexural Strengths of Fiber-Reinforced Polymeric Composites

Hybrid Advances, Journal Year: 2025, Volume and Issue: unknown, P. 100385 - 100385

Published: Jan. 1, 2025

Language: Английский

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Robust graph contrastive learning with multi-hop views for node classification

Applied Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 112783 - 112783

Published: Jan. 1, 2025

Language: Английский

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