Stored process data in the form of high fidelity time trends are a resource for data-driven process analyses such as statistical monitoring, minimum variance control loop benchmarking, fault detection, data reconciliation and development of inferential sensors. However, many commercial data historians compress the data before archiving it and a question therefore arises of how useful the compressed data are for the intended purposes.This article examines the impact of compression on data-driven methods and presents an automated algorithm by which the presence of piecewise linear compression may be inferred during the pre-processing phase of a data-driven analysis.The results show that compression interferes with many types of data-driven analyses and the paper strongly recommends caution in the use of compressed process data archives.
Plant-wide oscillations are common in many processes. Their effects propagate to many units and mayimpact the overall process performance. It is important to detect and diagnose the cause of suchoscillations in order to rectify the situation and maintain the proper profitability of the plant. This paperproposes a new procedure to detect and diagnose plant-wide oscillations using routine operating data. Themethod has been developed based on the nonlinearity information in the process data. A new TotalNonlinearity Index (TNLI) has been defined to quantify nonlinearities. The method is based on theassumption that the nonlinearity is highest near the source and decreases as one moves away from thesource. This assumption is true because chemical processes have the nature of low-pass filters and theyfilter out gradually higher order harmonics of the signals. Signals with higher order harmonics aregenerally more nonlinear. The proposed diagnostic method has already been successfully applied fortroubleshooting many industrial plant-wide oscillation problems. Two of such case studies have beenpresented in this paper.Journal of Chemical Engineering Vol.ChE 24 2006 50-60
Clean air is a basic need of human beings for its existence. In recent years, air pollution in city areas, especially in Dhaka and Chittagong, has become a significant threat to health and well-being. Dhaka is found to suffer a high level of pollution during the dry season, which is from November to April, especially for Particulate Matter, PM2.5, concentration. From December to February this situation is found to be the worst crossing the WHO guidelines and National Ambient Air Quality Standard. Bangladesh is surrounded by countries with the fastest-growing economy like India and China who use coal-burning technologies for different purposes such as producing power and running mills. They release the lion’s share of the air pollutants in South Asia and these pollutants easily get transported to neighboring countries. This is known as transboundary pollution. This study investigates the contribution of transboundary transportation of PM-2.5 in the air quality of Dhaka city. Ninety-Six hours of air mass back trajectories were computed using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT-4) model and those trajectories were grouped into 6 clusters. Probability calculation showed that Dhaka city air has a higher probability of getting pollutants from long-range sources when air masses traveled through North, West, and North-West direction covering the North Eastern and North-Western territories of India, Nepal, and its neighboring areas. Concentration Weighted Trajectory (CWT) analysis also supported that those areas could be potential sources of getting unwanted PM-2.5 on our atmosphere. Chemical Engineering Research Bulletin 21(2020) 114-120
Split type room air conditioners (RACs) are very common nowadays. In Bangladesh, RAC manufacturers employ trial-error prototyping techniques in their design to increase the efficiency of RACs and the profitability of the plant. Computer modeling can be a great help to reduce the cost in the R&D stage to find the optimum design of RACs. In this study, modeling of heat transfer in the condenser of split type RACs employing the techniques of Computational Fluid Dynamics (CFD) was performed. To reduce the computational load the geometry was divided into small sections and geometric symmetries were also taken into account. For the simulation, the geometry and other relevant data were set in such a way so that they commensurate closely with real industrial data. An example data set for validation of simulation results were obtained from an AC manufacturer company, Elite Hitech Industries Ltd. The geometry was built using meshing techniques. Copper and aluminum were selected as materials for tubes and fins, respectively. R-22 was chosen as the refrigerant. Heat transfer and fluid flow were modeled using non-isothermal flow in a multi-physics environment. The main assumptions employed are laminar flow, extra coarse mesh size, constant air inlet temperature, perfect insulation between system and surroundings, and thin layer fins. The temperature distribution and heat transfer efficiency in the condenser, the impact of different refrigerant flow arrangements in the tubes have been studied in detail. This study leads to the finding of efficient refrigerant flow arrangements from the viewpoint of maximum heat transfer. Chemical Engineering Research Bulletin 21(2020) 20-25
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