Effects of limestone replacement ratio on the sulfate resistance of Portland limestone cement mortars exposed to extraordinary high sulfate concentrations

A comparative study has been performed on the sulfate resistance of Portland limestone cement (PLC) mortars exposed to extraordinary high sulfate concentrations (200 g/l). PLCs have been prepared by using two types of clinkers having different C₃S/C₂S ratios and interstitial phase morphologies. Blended cements have been prepared by replacing 5%, 10%, 20% and 40% of clinker with limestone. Cubic (50 × 50 × 50 mm) and prismatic (25 × 25 × 285 mm) cement mortars were prepared. After two months initial water curing, these samples were exposed to three different sulfate solutions (Na₂SO₄ at 20 °C and 5 °C, MgSO₄ at 5 °C). Solutions were not refreshed and pH values of solutions were monitored during the testing stage. The compressive strength and length changes of samples have been monitored for a period of 1 year. Additional microstructural analyses have been conducted by XRD and SEM/EDS studies. Results indicated that in general, limestone replacement ratio and low temperature negatively affect the sulfate resistance of cement mortars. Additionally, clinkers of high C₃S/C₂S ratios with dendritic interstitial phase structure were found to be more prone to sulfate attack in the presence of high amounts of limestone.From the results, it is postulated that in the absence of solution change, extraordinary high sulfate content modified the mechanism of sulfate reactions and formation of related products. At high limestone replacement ratios, XRD and SEM/EDS studies revealed that while ettringite is the main deterioration product for the samples exposed to Na₂SO₄, gypsum and thaumasite formation were dominant products of deterioration in the case of MgSO₄ attack. It can be concluded that, the difference between reaction mechanisms of Na₂SO₄ and MgSO₄ attack to limestone cement mortars strongly depends on the pH change of sulfate solutions.     

Designing a Collaborative Visual Analytics Tool for Social and Technological Change Prediction

This paper discussed about GreenOracle which an interdisciplinary team designed and developed. GreenOracle is a collaborative visual analytics tool for predicting global climate change's impact on US power grids and its implications for society and national security. These future scenarios provide critical assessments and information to help policymakers and stakeholders formulate a coherent and unified strategy toward shaping a safe and secure society.     

Inter-organisational knowledge transfer in social networks: A definition of intermediate ties

A social network perspective helps identify and analyse informal knowledge transfer among people and organisations with the aim to recommend organisational interventions and improvements, for example in the form of Information and Communication Technology (ICT) support. This paper particularly focuses on a key concept of social network analysis (SNA), the concept of tie strength, in an inter-organisational knowledge transfer context. Tie strength describes the strength of a social relationship. In the past, SNA literature with a knowledge management context has often emphasized the importance of strong and/or weak ties rather than of intermediate (medium strong) ties in a social network. Nevertheless, in this study, intermediate ties are identified as the dominant links among key groups of organisation in a social network. Intermediate ties also help connect otherwise weakly linked organisations. Moreover, a definition of intermediate ties in the context of knowledge management is introduced. With the help of cluster analysis and an investigation into the levels of reciprocity, intermediate ties can be clearly defined in a social network. Due to their importance for knowledge transfer in a social network, intermediate ties should be primarily supported, for example by appropriate ICT.     

Role of Learning Algorithm in Neural Network-Based Backcalculation of Flexible Pavements

Nondestructive testing (NDT) methods are widely used for the performance evaluation of flexible pavements. Falling weight deflectometer (FWD), which measures time-domain deflections resulting from applied impulse loads, is the most popular technique among all NDT methods. The evaluation of the FWD data requires the inversion of mechanical pavement properties using a backcalculation tool that includes both a forward pavement response model and an optimization algorithm. Neural networks (NNs) have also emerged as alternative tools that can be employed for pavement backcalculation problems relative to their real-time processing abilities. However, there have been no comprehensive analyses in previous studies that focus on the learning algorithm and the architecture of a NN model, which considerably affect backcalculation results. In this study, 284 different NN models were developed using synthetic training and testing databases obtained by layered elastic theory. Results indicated that both the learning algorithm and network architecture play important roles in the performance of the NN based backcalculation process.     

An application of polarized domains in ferroelectric thin films using scanning probe microscope

The feasibility of utilizing PZT films as future data storage media was investigated using a modified AFM. Applying voltages between a conductive AFM tip and the PZT films causes the switching of ferroelectric domains. The domains are observed using an EFM imaging technique. The experimental results and calculations revealed that the electrostatic force generated between the polarized area and the tip is a main contributor for the imaging of the polarized domains. The written features on ferroelectric films were less than 100 nm in diameter, implying the possibility of realizing data storage devices with ultra-high area density. The disappearance of the polarized images without any applied voltage was observed, which is a drawback in this application of PZT thin films.