Iran University of Science and Technology

About: Iran University of Science and Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Finite element method. The organization has 12917 authors who have published 24965 publications receiving 372013 citations. The organization is also known as: Governmental Technical Institute & Advanced Art College.

Stability and extraction study of phenolic wastewater treatment by supported liquid membrane using tributyl phosphate and sesame oil as liquid membrane

Abstract: Phenols pose a risk to the environment and to human health. Phenol and its derivatives are toxic pollutants, frequently found in surface and tap waters, and in aqueous effluents from various manufacturing processes. In this paper, an experimental study regarding transport of phenol through a supported liquid membrane (SLM) using tributyl phosphate (TBP) and sesame oil as liquid membrane (LM) was performed. Factors affecting permeation of phenol such as initial phenol concentration, carrier concentration, feed phase pH and stripping phase concentration were analyzed using Taguchi method. Optimal experimental condition of phenol transport was obtained using analysis of variance (ANOVA) after 7 h extraction (feed concentration: 200 mg/L; carrier concentration (%TBP): 40%; feed pH: 2; strip phase concentration: 1.1 M). Mass transfer coefficient for this system was evaluated, and compared with similar works, and it was shown that it has the highest mass transfer rate. In addition to transport study, stability of the membrane was investigated by examination of stripping phase concentration, carrier concentration and salt concentration effects.

On the Monitoring of Autocorrelated Linear Profiles

Abstract: Control charts are commonly used to monitor quality of a process or product characterized by a quality characteristic or a vector of quality characteristics. However, in many practical situations the quality of a process or product can be characterized by a function or profile. Here we consider a linear function and investigate the violation of common independence assumption implicitly considered in most control charting applications. We specifically consider the case when profiles are not independent from each other over time. In this article, the effect of autocorrelation between profiles is investigated using average run length (ARL) criterion. Simulation results indicate significant impact on the ARL values when autocorrelation is overlooked. In addition, three methods based on time series approach are used to eliminate the effect of autocorrelation. Their performances are compared using ARL criterion.