It is important to predict chlorine decay with different water purification processes and distribution pipeline materials, especially because chlorine decay is in direct relationship with the stability of water quality. The degree of chlorine decay may affect the water quality at the end of the pipeline: it may produce disinfection by-products or cause unpleasant odor and taste. Sand filtrate and dual media filtrate were used as influents in this study, and cast iron (CI), polyvinyl chloride (PVC), and stainless steel (SS) were used as pipeline materials. The results were analyzed via chlorine decay models by comparing the experimental and model parameters. The models were then used to estimate rechlorination time and chlorine decay time. The results indicated that water quality (e.g. organic matter and alkalinity) and pipeline materials were important factors influencing bulk decay and sand filtrate exhibited greater chlorine decay than dual media filtrate. The two-component second-order model was more applicable than the first decay model, and it enabled the estimation of chlorine decay time. These results are expected to provide the basis for modeling chlorine decay of different water purification processes and pipeline materials.

This paper deals with the theory for rotational motion of a two-layer Earth model (an inelastic mantle and liquid core) including the dissipation in the mantle-core boundary(CMB) along with tidal effects produced by Moon and Sun. An analytical solution being derived using Hori's perturbation technique at a second order Hamiltonian. Numerical nutation series will be deduced from the theory.

EPC seeks to minimize variability by transferring the output variable to a related process input(controllable) variable, while SPC seeks to reduce variability by detecting and eliminating assignable causes of variation. In the case of product control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We consider an alternative EPC model with second-order autoregressive disturbance. We compare three control systems; EPC, EPC combined with EWMA. This paper shows through simulation that tlhe performance of the integrated model of EPC and EWMA is more preferable than that of EPC.

EPC seeks to minimize variability by transferring the output variable to a related process input(controllable) variable, while SPC seeks to reduce variability by detecting and eliminating assignable causes of variation. Tn the case of product control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We consider an alternative EPC model with second-order autoregressed disturbance. We compare three control systems; EPC, EPC combined system with EWMA, CUSUM and Shewhart. This paper shows through simulation that the performance of the integrated model of EPC and SPC is more preferable than that of EPC.

EPC seeks to minimize variability by transferring the output variable to a related process input(controllable) variable, while SPC seeks to reduce variability by detecting and eliminating assignable causes of variation. In the case of product control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We consider an alternative EPC model with second-order autoregressive disturbance. We compare three control systems； EPC, EPC combined with EWMA, and Shewhart. This paper shows through simulation that the performance of the integrated model of EPC and SPC is more preferable than that of EPC.