Missouri University of Science and Technology

About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Artificial neural network & Control theory. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.

Improving flexural performance of ultra-high-performance concrete by rheology control of suspending mortar

Abstract: This study develops a rheology control method to improve steel fiber distribution and flexural performance of ultra-high-performance concrete (UHPC) by adjusting the rheological properties of the suspending mortar of UHPC before steel fibers are added. Correlations among the plastic viscosity of the suspending mortar, the resulting steel fiber distribution, and flexural properties of UHPC are established. This was done by changing the dosage of viscosity modified admixture (VMA) for investigated UHPC mixtures. The optimal plastic viscosity of the suspending mortar that allows for the optimized fiber distribution and flexural performance of UHPC is determined. The plastic viscosity is correlated with the mini V-funnel flow time, which provides a simple alternative to evaluate the plastic viscosity. For a UHPC mixture with 2% micro steel fibers, by volume, the optimal mini V-funnel flow time of suspending motar was determined to be 46 ± 2 s, which corresponded to the optimal plastic viscosity (53 ± 3 Pa s) that ensures the greatest fiber dispersion uniformity and flexural performance of UHPC. However, increasing the VMA dosage retarded the hydration kinetics and reduced the degree of hydration, compressive strength, and the bond properties of the fiber-matrix interface of UHPC.

A Brokerage-Based Approach for Cloud Service Selection

Abstract: great opportunities for consumers to find the best service and best pricing, which however raises new challenges on how to select the best service out of the huge pool. It is time-consuming for consumers to collect the necessary information and analyze all service providers to make the decision. This is also a highly demanding task from a computational perspective, because the same computations may be conducted repeatedly by multiple consumers who have similar requirements. Therefore, in this paper, we propose a novel brokerage-based architecture in the Cloud, where the Cloud brokers is responsible for the service selection. In particular, we design a unique indexing technique for managing the information of a large number of Cloud service providers. We then develop efficient service selection algorithms that rank potential service providers and aggregate them if necessary. We prove the efficiency and effectiveness of our approach through an experimental study with the real and synthetic Cloud data.