Emergency shutdown valve reliability function test by automated Partial Stroke Testing System

Partial stroke testing (PST) is a technique that is regularly practiced in oil and gas industries to test the emergency shutdown (ESD) valve by closing a certain percentage of the valve position and stop any flow through the pipeline. Generally, it only functions when there is an emergency occurring in the production system. When the ESD valve remains in one position for a long period, there is a risk and potential of fail on demand which is, the ESD valve fail to operate during the emergency shutdown. This testing can reveal approximately 75 of unrevealed failures in valves. It can also provide predictive maintenance data that can contribute to the extension of the preventive maintenance for the ESD valve. The objectives of this paper are to design, simulate, build and test the performance of the automated PST system based on PLC. Four guidelines and methodology are used in this work. First, understanding the operation of the PST system. Then, the utilization of the capability of MATLAB-Simulink software as the simulation tool for the PST design system. Next, designing the PST automated system based on PLC design and lastly, testing the performance of the PST design system using lab scale PST system prototype that has been built. Results of the project shows that the PST system is successfully designed and simulated via MATLAB-Simulink and the PLC programming is working in the correct order as performed on the prototype

Modeling of Filtration Process Using PSO-Neural Network

Modeling of membrane filtration process is a challenging task because it involves many interactions from biological and physical operation behavior. Membrane fouling in filtration process is too complex to understand and to derive a robust model become very difficult. The aim of this paper is to study the potential of neural network based dynamic model for submerged membrane filtration process. The purpose of the model is to represent the dynamic behavior of the filtration process therefore the model can be utilized in the prediction and control. The neural network model was trained using particle swarm optimization (PSO) technique. Three methods of PSO are compared to obtained an optimal model which are random PSO (RPSO), constriction factor PSO (CPSO) and inertia weight PSO (IW-PSO). In the data collection, a random step was applied to the suction pump in order to obtained the permeate flux and transmembrane pressure (TMP) dynamic. The model was evaluated in term of %R2, root mean square error (RMSE,) and mean absolute deviation (MAD). The result of proposed modeling technique showed that the neural network with PSO is capable to model the dynamic behavior of the filtration process

Vibrational mechanics in an optical lattice: controlling transport via potential renormalization

We demonstrate theoretically and experimentally the phenomenon of vibrational resonance in a periodic potential, using cold atoms in an optical lattice as a model system. A high-frequency (HF) drive, with frequency much larger than any characteristic frequency of the system, is applied by phase-modulating one of the lattice beams. We show that the HF drive leads to the renormalization of the potential. We used transport measurements as a probe of the potential renormalization. The very same experiments also demonstrate that transport can be controlled by the HF drive via potential renormalization.Comment: Phys. Rev. Lett., in pres

Current reversals in a rocking ratchet: the frequency domain

Motivated by recent work [D. Cubero et al., Phys. Rev. E 82, 041116 (2010)], we examine the mechanisms which determine current reversals in rocking ratchets as observed by varying the frequency of the drive. We found that a class of these current reversals in the frequency domain are precisely determined by dissipation-induced symmetry breaking. Our experimental and theoretical work thus extends and generalizes the previously identified relationship between dynamical and symmetry-breaking mechanisms in the generation of current reversals

Empirical modelling of activated sludge process via system identification

Activated sludge process is an important stage in Wastewater Treatment Plant (WWTP). In this study, model of the activated sludge process from Bunus Regional Sewage Treatment Plant Kuala Lumpur, Malaysia is developed. This paper focuses on modelling and model reduction of the WWTP system. The model with best fits of higher than 80 and the order of less than 10 is selected. For modelling purposes, data obtained is stimulated and modelled using System Identification technique which employ linear model ARX. For model reduction purposes, the high order model is reduced using model order reduction (MOR) of a combination of Singular Perturbation Approximation (SPA) and Frequency Domain Gramian based Model Reduction (FDIG) method. From the modelling results obtained, the ARX model with best fit of 85.11 is selected. Meanwhile, for the MOR FD-SPA technique, a 9th order model is selected with 2.5 x 10-2 reduction error between frequencies 0.05 rad/s and 1.4 rad/s

Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

Generating systems are said to be adequately reliable when they can satisfy the load demand. Meanwhile, the reliability of electrical systems is currently being influenced by the increasing acceptance of "Wind Energy Conversion System" (WECS) in power systems compared to other conventional sources. This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). The DEOA technique is used to improve the assessment of the reliability and adequacy of the generation systems by incorporating wind energy from a WECS. The basis of DEOA is the meta- heuristic searching used to simulate the generation systems operation and considering the random failures of existing systems and the unstable character of WECS- sourced wind energy. The effectiveness of the suggested algorithm to assess the reliability and adequacy of power generation systems with WECS was demonstrated. Additionally, the efficiency of the planned algorithm in numerical simulation was compared to that of the "Monte Carlo simulation" (MCS)

The Effects of Principals’ Digital Leadership on Teachers’ Digital Teaching during the Covid-19 Pandemic in Malaysia

Education involving digital technology is the latest transformation of the education system, especially during the occurrence of the COVID-19 pandemic. The Malaysian Ministry of Education (MOE) has taken the initiative to spearhead efforts to develop the skills and potential of students in the use of digital technology. The main purpose of this study was to identify the level of digital leadership displayed by principals, the level of teachers' digital teaching practices and the elements of principals' digital leadership that predict the level of teachers' digital teaching. About 400 secondary school teachers in Hulu Langat District, Selangor were involved in this study. The findings of this study show that the level of digital leadership displayed by principals and teachers’ digital teaching practice are both at a high level. However, the positive correlation between the two is moderate. Multiple regression found that only digital citizenship is a strong predictor of teachers' digital teaching. The findings show that the ability to plan and organize digital leadership programs is important and can help improve students' academic performance, despite the COVID-19 pandemic crisis

Validation of requirements for transformation of an urban district to a smart city

The concept of a smart city is still debatable and yet gives attention to every country around the globe to provide their community with a better quality of life. New ideas for the development of a smart city have always evolved to enhance the quality, performance, and interactivity of services. This paper presents a model of a smart city based on the comparison of the chosen smart cities in the world and used the model to validate the requirements for the transformation of an urban district to a smart city. The proposed model for a smart city in this paper focuses on two major components, which are by utilizing IoTs (Internet of Things) in forming a model for a smart city and incorporating culture diversity. The relationship of components and culture influence are the foundation of designing the model of a smart city. In this research, the model of a smart city has been validated based on the requirements analysis from the survey instrument and the results show that the average mean of each element used is more than 4 out of 5. The model of a smart city can be used as a guideline for transformation of an urban district to a smart city

Toxic effect of high concentration of sonochemically synthesized polyvinylpyrrolidone-coated silver nanoparticles on Citrobacter sp. A1 and Enterococcus sp. C1

Background/Purpose Currently, silver nanoparticles (AgNPs) have gained importance in various industrial applications. However, their impact upon release into the environment on microorganisms remains unclear. The aim of this study was to analyze the effect of polyvinylpyrrolidone-capped AgNPs synthesized in this laboratory on two bacterial strains isolated from the environment, Gram-negative Citrobacter sp. A1 and Gram-positive Enterococcus sp. C1. Methods Polyvinylpyrrolidone-capped AgNPs were synthesized by ultrasound-assisted chemical reduction. Characterization of the AgNPs involved UV–visible spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, transmission electron microscopy, and energy dispersive X-ray spectroscopy. Citrobacter sp. A1 and Enterococcus sp. C1 were exposed to varying concentrations of AgNPs, and cell viability was determined. Scanning electron microscopy was performed to evaluate the morphological alteration of both species upon exposure to AgNPs at 1000 mg/L. Results The synthesized AgNPs were spherical in shape, with an average particle size of 15 nm. The AgNPs had different but prominent effects on either Citrobacter sp. A1 or Enterococcus sp. C1. At an AgNP concentration of 1000 mg/L, Citrobacter sp. A1 retained viability for 6 hours, while Enterococcus sp. C1 retained viability only for 3 hours. Citrobacter sp. A1 appeared to be more resistant to AgNPs than Enterococcus sp. C1. The cell wall of both strains was found to be morphologically altered at that concentration. Conclusion Minute and spherical AgNPs significantly affected the viability of the two bacterial strains selected from the environment. Enterococcus sp. C1 was more vulnerable to AgNPs, probably due to its cell wall architecture and the absence of silver resistance-related genes