Mechanism of microstructural modification of the interfacial transition zone by using blended materials

Applying blended materials with finer particle size or high reactivity could be an effective and economic way for improving the microsturcture of interfacial transition zone (ITZ). In this study, the porosity characteristics of ITZ in concrete made with OPC and blended binders were determined quantitatively by using backscattered electron microscopy (BSE) image analysis and mercury intrusion porosimetry (MIP) measurements. This paper especially focused on the effects of slag and limestone filler on the thickness and pore structure of the ITZ. Results indicated that the porosity at each distance reduces with increasing limestone filler from 0 to 5%, and a significant increase is observed in the sample with 10% of limestone filler. The addition of 5% of limestone filler is able to densify the pore structure of both ITZ and bulk matrix. The reduction in pore volume in the range coarser than 100 nm contributed to the largest decrease in the total pores. Increasing the incorporation level of limestone filler to 10% resulted in an increase in the total porosity. The influences of slag on the porosity characteristics were highly dependent on the replacement level and the determined pore size regions. The addition of 35% of slag reduces the porosity at all distances and produces a denser microstructure both in the ITZ and bulk cement matrix. However, this improvement disappears when the substitution amount reaches to 70%. The incorporation of slag as a partial substitute for Portland cement tends to refine the pore structure

Investigation of the deterioration of blended cement concrete under sulfate attack in terms of interfacial transition zone

The importance of the porous interfacial transition zone to the chemical aggression of concrete is obvious when one considers the relations existing between porosity, permeability, chemical composition and the sulfate attack. In this study, the effect of ITZ quantity through varying aggregate content on the deterioration of blended cement concrete under sulfate attack, was determined to understand better the relationship between sulfate ions and concrete microstructure. The ITZ quantity was directly proportional to the aggregate volume fraction. Therefore, the effect of ITZ on sulfate resistance ability of concrete made with pure OPC and blended binders was evaluated by a comparison among mortars with systematically varied aggregate volume fraction. The porosity distribution with the ITZ was determined by using a quantitative backscattered electron microscopy (BSE) image analysis. It was found that the incorporation of moderate amount of Limestone filler is able to compact the microstructure of both ITZ and bulk matrix by filling effect and nucleation sites effect. The effects of slag on the porosity of ITZ were dependent on the replacement rate. The degree of deterioration had a slight tendency to increase for the samples prepared with higher aggregate volume content, which means high ITZ volume fraction. For the sulfate to reach the interior of the samples, it must move through the bulk cement matrix. The effect of aggregate and ITZ can only be notable when the interior structure was exposed to the sulfate ions. The presence of ITZ was normally accompanied by a denser bulk cement matrix. This could limit the ingress of sulfate ions and delay the formation of expansive products in initial stage. After the sulfate penetrates into the interior of the samples, the inner structure was expected to exert more significant influences on the deterioration

Deep Learning Based on Orthogonal Approximate Message Passing for CP-Free OFDM

Channel estimation and signal detection are very challenging for an orthogonal frequency division multiplexing (OFDM) system without cyclic prefix (CP). In this article, deep learning based on orthogonal approximate message passing (DL-OAMP) is used to address these problems. The DL-OAMP receiver includes a channel estimation neural network (CE-Net) and a signal detection neural network based on OAMP, called OAMP-Net. The CE-Net is initialized by the least square channel estimation algorithm and refined by minimum mean-squared error (MMSE) neural network. The OAMP-Net is established by unfolding the iterative OAMP algorithm and adding some trainable parameters to improve the detection performance. The DL-OAMP receiver is with low complexity and can estimate time-varying channels with only a single training. Simulation results demonstrate that the bit-error rate (BER) of the proposed scheme is lower than those of competitive algorithms for high-order modulation.Comment: 5 pages, 4 figures, updated manuscript, International Conference on Acoustics, Speech and Signal Processing (ICASSP 2019). arXiv admin note: substantial text overlap with arXiv:1903.0476