Comfort level identification for irregular multi-storey building

Alqado, Tarek Edrees; Nikolakopoulos, George; Jonasson, Jan-Erik

doi:10.1016/j.autcon.2014.10.009

Cited by 8 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Modern structures involve not only energy management [4,5] but also condition assessment and safety management, whereby the integration of modeling, control and health monitoring is of crucial importance [6]. In quake-prone areas, building structures often undergo vibrations in response to the ground motion caused by the seismic energy and fail to dissipate inelastic energy due to excessive lateral motion, resulting in structural deformation [7], [8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Low-energy structures embedded with smart dampers

Royel

Balaguer

2018

Energy and Buildings

View full text Add to dashboard Cite

Building structures, subject to dynamic loadings or external disturbances, may undergo destructive vibrations and encounter different degrees of deformation.Modeling and control techniques can be applied to effectively damp out these vibrations and maintain structural health with a low energy cost. Smart structures embedded with semi-active control devices, offer a promising solution to the problem. The smart damping concept has been proven to be an effective approach for input energy shaping and suppressing unwanted vibrations in structural control for buildings embedded with magnetorheological fluid dampers (MRDs). In this paper, the dissipation energy in MRD is studied by using results from induced hysteretic effect of structural vibrations while the fluid is placed under a controlled magnetic field. Then, a frequency-shaped second-order sliding mode controller (FS2SMC) is designed along with a low-pass filter to implement the desired dynamic sliding surface, wherein the frequency responses of the hysteretic MRD is represented by its magnitude and phase describing functions. The proposed controller can thus shape the frequency characteristics of the equivalent dynamics for the MRD-embedded structure against induced vibrations, and hence, dissipate the energy flow within the smart devices to prevent structural damage. Simulation results for a 10-floor building model equipped with current-controlled MRDs, subject to horizontal seismic excita-

show abstract

Section: Introductionmentioning

confidence: 99%

“…for example, to get a steeper roll-off of |L(jω)|, ω ∈ [0, ∞) for large values of frequency ω. Herein, L(s) = b0 s 2 +a1s+a0 gives a |L(jω)| with an asymptotic slope of −40 dB/decade above cut-off frequency. The algebraic manipulation of(6) …”

mentioning

confidence: 99%

Low-energy structures embedded with smart dampers

Royel

Balaguer

2018

Energy and Buildings

View full text Add to dashboard Cite

show abstract

“…Nonlinear model has been used and presented for Stochastic Optimal Control of Structural Systems [1,7]. Saaed Alqado et al [8] have developed five methods for structural identification approach, specifically ARX, ARMAX, BJ, OE, and state-space models, and have implemented them for the identification process. Furthermore, the paper shows that the ARMAX and the output error models have indicated an excellent performance to predict the mathematical models of vibration's propagation in the building.…”

Section: Introductionmentioning

confidence: 99%

Generalized Minimum Variance Control for MDOF Structures under Earthquake Excitation

Guenfaf

Mohamed

2016

Journal of Control Science and Engineering

View full text Add to dashboard Cite

Control of a multi-degree-of-freedom structural system under earthquake excitation is investigated in this paper. The control approach based on the Generalized Minimum Variance (GMV) algorithm is developed and presented. Our approach is a generalization to multivariable systems of the GMV strategy designed initially for single-input-single-output (SISO) systems. Kanai-Tajimi and Clough-Penzien models are used to generate the seismic excitations. Those models are calculated using the specific soil parameters. Simulation tests using a 3DOF structure are performed and show the effectiveness of the control method.

show abstract

“…In the first case, the fundamental behavior is evaluated by involving solely collected data (Celebi, 2007;Mikael et al, 2013;Saaed Alqado et al, 2015;Loh and Chen, 2017). This can be seen as a "black-box" approach, where the supporting framework does not allow clear explanation of the observed results.…”

Section: Introductionmentioning

confidence: 99%

System Identification of Tunnel Response to Ground Motion Considering a Simplified Model

Alonso‐Rodríguez

Nikitas

Knappett

et al. 2018

Front. Built Environ.

View full text Add to dashboard Cite

This paper presents a simplified model using coupled Bernoulli and shear beams supported by Winkler-type springs for system identification of tunnels subjected to earthquake-induced ground motions. The model formulation is introduced and closed-form solutions to the modal characteristic equation and mode shapes are derived. The latter are verified against the results of numerical models. Then, the system identification algorithm is presented, showcasing its ability to recover model parameters when recorded acceleration time histories along the tunnel are compromised by noise and sensor locations are varied. The presented framework can be used to initially and, simply, recover tunnel response when monitoring data is available, or to plan for monitoring campaigns in newly constructed or existing tunnels.

show abstract

Comfort level identification for irregular multi-storey building

Cited by 8 publications

References 22 publications

Low-energy structures embedded with smart dampers

Low-energy structures embedded with smart dampers

Generalized Minimum Variance Control for MDOF Structures under Earthquake Excitation

System Identification of Tunnel Response to Ground Motion Considering a Simplified Model

Contact Info

Product

Resources

About