Effect of upgrading concrete strength class on fire performance of reinforced concrete columns

peer reviewedHigh strength concrete (HSC) provides several advantages over normal strength concrete (NSC) and is being used in multi-story buildings for reducing the dimensions of the columns sections and increasing the net marketable area. However, upgrading of concrete strength class in a building may affect the fire performance, due to higher rates of strength loss with temperature and higher susceptibility to spalling of HSC compared with NSC. Reduction of columns sections also leads to increased member slenderness and faster temperature increase in the section core. These detrimental effects are well known, but their impact on fire performance of structures has not been established in terms of comparative advantage between NSC and HSC. In other words, it is not clear whether the consideration of fire resistance limits the opportunities for use of HSC for reducing the dimensions of columns sections in multi-story buildings. This research aims to address this question by comparing the fire behaviour of reinforced concrete columns made of NSC and HSC using nonlinear finite element modelling. The evolution of load bearing capacity of the columns is established as a function of the fire exposure duration. A 15-story car park structure is adopted as a case study with alternative designs for the columns based on strength classes ranging from C30 to C90. Results show that, although the replacement of NSC by HSC accelerates the reduction rate of columns capacity under fire, the columns generally have significant reserves in resistance leading to sufficient fire resistance. This study gives an insight into the impact of replacing stocky sections in NSC by more slender sections in HSC on fire resistance rating for multi-story structures

DPCM with Forward Gain-Adaptive Quantizer and Simple Switched Predictor for High Quality Speech Signals

In this article DPCM (Differential Pulse Code Modulation) speech coding scheme with a simple switched first order predictor is presented. Adaptation of the quantizer to the signal variance is performed for each particular frame. Each frame is classified as high or low correlated, based on the value of the correlation coefficient, then the selection of the appropriate predictor coefficient and bitrate is performed. Low correlated frames are encoded with a higher bitrate, while high correlated frames are encoded with a lower bitrate without the objectionable loss in quality. Theoretical model and experimental results are provided for the proposed algorithm

Switched adaptive quantiser for speech compression based on optimal companding and correlation

This study describes a novel adaptive quantiser based on the optimal companding technique. Adaptation is achieved by adjusting the input of the fixed or non-adaptive quantiser according to the estimated and quantised gain on each particular frame. In such a way better quantiser adaptation to the varying input statistics is provided. Selection of the appropriate bit rate is performed depending on the value of the correlation coefficient ρ on each frame. The decision thresholds for ρ are determined under the condition that the signal to quantisation noise ratio does not drop under 34.3ρdB, satisfying the G.712 standard quality of speech, while decreasing the bit rate. The information about the gain and about the chosen bit rate is then transferred as a side information to a decoder. Although this slightly increases the side information, the overall savings in the bit rate have shown to be substantial. Theoretical and experimental results are provided, which point out the benefits that can be achieved using the proposed algorithm