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RISS 인기검색어
- 검색키워드
- 저자 : Lalthlamuana, R. (검색결과 4 건)
- 무료
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Effect of vehicle flexibility on the vibratory response of bridge
Lalthlamuana, R.,Talukdar, Sudip Techno-Press 2014 Coupled systems mechanics Vol.3 No.2
In the recent times, dimensions of heavy load carrying vehicle have changed significantly incorporating structural flexibility in vehicle body. The present paper outlines a procedure for the estimation of bridge response statistics considering structural bending modes of the vehicle. Bridge deck roughness has been considered to be non homogeneous random process in space. Influence of pre cambering of bridge surface and settlement of approach slab on the dynamic behavior of the bridge has been studied. A parametric study considering vehicle axle spacing, mass, speed, vehicle flexibility, deck unevenness and eccentricity of vehicle path have been conducted. Dynamic amplification factor (DAF) of the bridge response has been obtained for several of combination of bridge-vehicle parameters. The present study reveals that flexible modes of vehicle can reduce dynamic response of the bridge to the extent of 30-37% of that caused by rigid vehicle model. However, sudden change in the bridge surface profile leads to significant amount of increment in the bridge dynamic response even if flexible bending modes remain active. The eccentricity of vehicle path and flexural/torsional rigidity ratios plays a significant role in dynamic amplification of bridge response.
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Rating of steel bridges considering fatigue and corrosion
Lalthlamuana, R.,Talukdar, S. Techno-Press 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.47 No.5
In the present work, the capacity ratings of steel truss bridges have been carried out incorporating dynamic effect of moving vehicles and its accumulating effect as fatigue. Further, corrosion in the steel members has been taken into account to examine the rating factor. Dynamic effect has been considered in the rating procedure making use of impact factors obtained from simulation studies as well as from codal guidelines. A steel truss bridge has been considered to illustrate the approach. Two levels of capacity ratings- the upper load level capacity rating (called operating rating) and the lower load level capacity rating (called inventory rating) were found out using Load and Resistance Factor Design (LRFD) method and a proposal has been made which incorporates fatigue in the rating formula. Random nature of corrosion on the steel member has been taken into account in the rating by considering reduced member strength. Partial safety factor for each truss member has been obtained from the fatigue reliability index considering random variables on the fatigue parameters, traffic growth rate and accumulated number of stress cycle using appropriate probability density function. The bridge has been modeled using Finite Element software. Regressions of rating factor versus vehicle gross weight have been obtained. Results show that rating factor decreases when the impact factor other than those in the codal provisions are considered. The consideration of fatigue and member corrosion gives a lower value of rating factor compared to those when both the effects are ignored. In addition to this, the study reveals that rating factor decreases when the vehicle gross weight is increased.
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Rating of steel bridges considering fatigue and corrosion
R. Lalthlamuana,S. Talukdar 국제구조공학회 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.47 No.5
In the present work, the capacity ratings of steel truss bridges have been carried out incorporating dynamic effect of moving vehicles and its accumulating effect as fatigue. Further, corrosion in the steel members has been taken into account to examine the rating factor. Dynamic effect has been considered in the rating procedure making use of impact factors obtained from simulation studies as well as from codal guidelines. A steel truss bridge has been considered to illustrate the approach. Two levels of capacity ratings- the upper load level capacity rating (called operating rating) and the lower load level capacity rating (called inventory rating) were found out using Load and Resistance Factor Design (LRFD) method and a proposal has been made which incorporates fatigue in the rating formula. Random nature of corrosion on the steel member has been taken into account in the rating by considering reduced member strength. Partial safety factor for each truss member has been obtained from the fatigue reliability index considering random variables on the fatigue parameters, traffic growth rate and accumulated number of stress cycle using appropriate probability density function. The bridge has been modeled using Finite Element software. Regressions of rating factor versus vehicle gross weight have been obtained. Results show that rating factor decreases when the impact factor other than those in the codal provisions are considered. The consideration of fatigue and member corrosion gives a lower value of rating factor compared to those when both the effects are ignored. In addition to this, the study reveals that rating factor decreases when the vehicle gross weight is increased.
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Identification of flexible vehicle parameters on bridge using particle filter method
S. Talukdar,R. Lalthlamuana 국제구조공학회 2016 Structural Engineering and Mechanics, An Int'l Jou Vol.57 No.1
A conditional probability based approach known as Particle Filter Method (PFM) is a powerful tool for system parameter identification. In this paper, PFM has been applied to identify the vehicle parameters based on response statistics of the bridge. The flexibility of vehicle model has been considered in the formulation of bridge-vehicle interaction dynamics. The random unevenness of bridge has been idealized as non homogeneous random process in space. The simulated response has been contaminated with artificial noise to reflect the field condition. The performance of the identification system has been examined for various measurement location, vehicle velocity, bridge surface roughness factor, noise level and assumption of prior probability density. Identified vehicle parameters are found reasonably accurate and reconstructed interactive force time history with identified parameters closely matches with the simulated results. The study also reveals that crude assumption of prior probability density function does not end up with an incorrect estimate of parameters except requiring longer time for the iterative process to converge.
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