• Structural Engineering and Mechanics
• /
• 제47권5호
• /
• pp.661-678
• /
• 2013

As a new type of vibration reduction, the ladder track system has been successfully used in engineering. In this paper, a numerical model of the train-track-viaduct system is established to study the dynamic responses of an elevated bridge with ladder track. The system is composed of a vehicle submodel, a track submodel and a bridge submodel, with the measured track irregularities as the system self-excitation. The whole time histories of a train running through an elevated bridge with $3{\times}27m$ continuous PC box girders are simulated. The dynamic responses of the bridge such as deflections, lateral and vertical accelerations, and the vehicle responses such as derailment factors, offload factors and car-body accelerations are calculated. The calculated results are partly validated through the comparison with the experimental data. Compared to the common slab track, adapting the ladder sleeper can effectively reduce the accelerations of the bridge girder, and also reduce the car-body accelerations and offload factors of the train vehicle.

• 한국국방경영분석학회지
• /
• 제13권1호
• /
• pp.1-18
• /
• 1987

This paper presents several adaptive linear predictive coding techniques based upon extension of recursive ladder filters. A 2-D recursive ladder filter is extended to a 3-D case which can adaptively track the variation of both spatial and temporal changes of moving images. Using the 2-D/3-D ladder filter and a previous farme predictor, two types of adaptive predictor-control schemes are proposed in which the prediction error at each pel can be obtained at or close to a minimum level. We also investigate several modifications of the basic encoding methods. Performance of the 2-D/3-D ladder filters, their adaptive control schemes, and variations in coding methods are evaluated by computer simulations on a real sequence and compared to the results of motion compensation and frame differential coders. As a validity test of the ladder filters developed, the error signals for the different predictors are compared and evaluated.