Introducing deep learning algorithms into the field of structural health monitoring (SHM) has contributed to automatic extraction damage-sensitive features, but type and architecture these are still in dispute. This paper proposes a hybrid framework entitled time-distributed one-dimensional convolutional neural network (1D CNN) long short-term memory (LSTM) model, which utilizes raw multisensor time histories detect damages. Using sliding window that moves along temporal dimension, data...

Nowadays, vibration control of structures is considered as a challenging field among scientists and engineers. Structural damage financial losses due to recent earthquakes in different countries have more than ever before accentuated the importance controlling earthquake-induced vibrations. In years, semi-active has been introduced an efficient reliable type structural which provides reliability passive flexibility active systems at same time. this study, performance tuned mass damper (TMD)...

Purpose Today, using lightweight structural concrete plays a major role in reducing the damage to structures. On other hand, concretes have lower compressive and flexural strengths with impact resistance compared ordinary concretes. The aim of this study is investigate effect simultaneous use waste glass powder, microsilica polypropylene fibers make sustainable that has high strengths, ductility resistance. Design/methodology/approach In article, studied compensate for strength concrete....

Abstract Concrete is one of the most extensively utilized building materials that can be produced, and has potential to release a significant quantity CO 2 into environment. In this research, through studying lightweight (LW) concrete, attempts are made produce environmentally friendly LW concrete with high strength using nanosilica rather than part cement waste glass powder instead aggregates. Recycled polypropylene fibers used increase concrete’s compressive nonlinear behavior. The use was...

Because of the occurrence severe and large magnitude earthquakes each year, earthquake-prone countries suffer considerable financial damage loss life. Teaching essential safety measures will lead to a generation that can perform basic procedures during an earthquake, which is important effective solution in preventing life this natural disaster. In recent years, virtual reality technology tool has been used educate people on matters. This paper evaluates effect education premonition...

This research presents designing a control system to reduce seismic responses of structures. Semi-active magnetorheological (MR) damper is used improve behavior 3-story building implementing neural-fuzzy controller made adaptive neuro-fuzzy inference (ANFIS) determine input voltage. Both premise and consequent parameters fuzzy membership output functions ANFIS have the ability for training improvement but most researchers focused on just parameters. In order optimize performance, an approach...

The effectiveness of tuned liquid column–gas damper, TLCGD, on the suppression seismic-induced vibrations steel jacket platforms is evaluated in this study. TLCGD an interesting choice case because it possible to use structural elements as horizontal column TLCGD. In study, optimum parameters are obtained, considering nonlinear damping and water–structure interaction between platform sea water. Equation motions other related formulas derived, using a SimuLink model, frequency head loss...

Wire and arc additive manufacturing (WAAM), also known as wire directed energy deposition (WA-DED), offers valuable capabilities not only for but strengthening repairing aging components. This paper employs the finite element (FE) method to investigate influence of parameters on efficiency damaged steel plates strengthened by WAAM material. The study calibrates inherent strain (ISM) with thermo-mechanical analysis accurately predict residual stresses (RS) in manufactured samples,...

Abstract The primary objective of this study is to introduce a novel adaptive fractional order proportional–integral–derivative (FOPID) controller. FOPID controller’s parameters are dynamically adjusted in real-time using five distinct multilayer perceptron neural networks. extended Kalman filter (EKF) employed facilitate the parameter-tuning process. A network, trained error Backpropagation algorithm, identify structural system and estimate plant. estimated Jacobian applied controller...

The objective of the present investigation is to introduce a novel adaptive fractional‐order proportional‐integral‐derivative controller, which characterized by online tuning its parameters utilizing five distinct multilayer perceptron neural networks employing extended Kalman filter. Utilizing backpropagation algorithm in training network deemed effective identifying structural system and estimating plant. controller applied using Jacobian derived from estimated model. utilization interval...

The main contribution pursued in this investigation is to propose a generic optimal methodology for designing multiple tuned mass damper (MTMD) systems efficiently suppress the response of uncertain structures harmonic excitations. This comprises quantitative indexing MTMD effectiveness and robustness as performance criteria, implementing two-objective optimization presenting solutions set non-dominated designs. Within three-step framework, utilization new index proposed, advantages...