ARPN Journal of Engineering and Applied Sciences              ISSN 1819-6608 (Online)
 

 
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ARPN Journal of Engineering and Applied Sciences                        October 2021  |  Vol. 16  No. 19
   
Title: Assessment of viscous models on the simulation of low cut-off wind turbine blade
Author (s): Zahir U. Ahmed, Mohammad Mashud and Shabnoor M. Joty
Abstract:

Renewable energy has received large attention in both developed and developing countries in the world as an alternative to the fossil fuel based energy. Wind energy is becoming one of the popular means to harness energy from renewable sources. Although abundant research had previously been undertaken for high Reynolds number, research on different viscous models at low Reynolds number is limited in the world. As such, in this paper a numerical study is performed for low speed wind turbine blades where five viscous models such as laminar, RNG k-ε model, SST k-ω, Transitional SST, and Transitional k-kl-ω, and four airfoils, namely NACA-4412, NACA-4421, NACA-4418 and NACA-2412 are chosen for comparative study. Numerical simulation was done via finite volume based software. The result shows that laminar, RNG k-ε and SST k-ω models are able to predict general behavior of both profiles, whereby laminar and SST k-ω models are able to capture stall angle. Whilst all the viscous models predicts well the pressure coefficient on lower surface of the airfoil, but only laminar and RNG k-ε models perform better in the upper surface of airfoil. The drag is found to be higher with the increase of angle of attack (AOA). The lift to drag ratio increases with increase of AOA but decrease after a certain point.

   

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Title: Effect of operating temperature on biodiesel production from Palm Fatty Acid Distillate by using the Amberlyst catalyst
Author (s): Rondang Tambun, Anggara Dwita Burmana and Vikram Alexander
Abstract:

The purpose of this study is to determine the effect of operating temperatures on biodiesel production from Palm Fatty Acid Distillate (PFAD) by using Amberlyst DPT 2 UPS catalyst. Amberlyst DPT 2 UPS catalyst is a heterogeneous catalyst whose performance is strongly influenced by operating temperature. In this study, Amberlyst DPT 2 UPS catalyzes the reaction between PFAD and methanol. The molar ratio of PFAD to methanol is 1: 5, and the reaction time is 8 hours. Operating temperature variations performed are 120˚C, 125˚C, 130˚C and 135˚C. Analysis carried out in the study included analysis of acid value, flash point, kinematic viscosity, density, and composition of biodiesel. The acid value, the flash point, the kinematic viscosity, the density, and the biodiesel composition is analyzed by the ASTM Standards. The results showed that the highest conversion of 99.85% is obtained at an operating temperature of 130˚C, while the analysis results of acid values, flash points, kinematic viscosity, and densities have met the ASTM standard for all variations in operating temperature.

   

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Title: Characterization of tribological and mechanical properties of SS-304 coated with Co-Cr-Mo alloy with 5% HCL solution
Author (s): Abdul Munaf Shaik, K. L. Narayana, K. V. Durga Rajesh, M. Kedar Mallik and Y. Pratapa Reddy
Abstract:

The service life of a component may be affected by friction and wear. A study was implemented to examine the dry sliding wear at room temperature on commercially available SS-304 grade steel coated with Co-Cr-Mo alloy is done in the present investigation. Specimens were machined and tested with ASTM standards. Cylindrical samples of 6 mm diameter were taken for the experimentation. Electroplating has been carried out using a 5V regulated DC supply under a 5% HCl environment with different time intervals. The coated surface has been subjected to wear resistance testing and observed a noticeable increase in wear resistance for coated specimens under defined test parameters. Co-Cr-Mo alloy exhibits a specific effect on the tribological properties of SS-304. It may be used as a temporary biomedical implant.

   

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Title: Relationship between macroscopic and microscopic energies near g-to-b  phase transition for g-RbAg4I5
Author (s): H. Correa, D. Peña Lara and Daniel Suescún-Díaz
Abstract:

In this paper, we are reporting on specific heat and complex conductivity measurements in crystalline g-RbAg4I5  close to the g-to-b phase transition at 120 K. Using the electric modulus formalism for analysis of ionic conductivity relaxation in g-RbAg4I5, microscopic interaction energy for a single-mobile ion whose temperature derivative is proportional to the specific heat was found. The results suggest that a common ion-ion and ion-lattice mechanism for both ionic migration and thermodynamic energy (i.e., the enthalpy) of mobile defects are present in this highly-dense system. The cooperative behavior observed in this transition region drives the phase transition at 120 K in g-RbAg4I5.

   

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Title: Development of real-time LoRa-based air pollution monitoring system
Author (s): Ida Syafiza M. Isa, Nur Syahirah Kamaruzaman and N. Latif A. Shaari
Abstract:

Air pollution can cause long-term health effects on humans, such as heart disease, lung cancers, and respiratory disease. There are many forms of contamination induced by smoke or gas emissions due to fossil fuel burning from transportation. Furthermore, manufacturing operations also negatively impact the air quality, where the production of plastics, electronics, and rubber, has contributed to a rise in organic carbon, inorganic carbon, and dust contaminations. Therefore, in this work, a real-time air pollution monitoring system has been developed to monitor air quality considering three types of gas sensors which are MQ2, MQ7 and MQ135. Also, LoRa communication technology is used as the communication modules between the sensor node located at the site and the gateway. The system is also equipped with an additional notification system to send the monitored air concentration data to the control room via the Telegram application. For monitoring purposes, the monitored data from the sensors will be updated every 5 minutes in the server using the Node-Red platform. The performance of the developed system has been evaluated considering six different distances between the sensor node and gateway, and the results show that the system has high reliability. The results also indicate that the average received signal strength indicator (RRSI) value of the LoRa module between the sensors and gateway reduced with the increasing distance between the sensor node and gateway. However, this does not affect the performance of the developed system.

   

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Title: Effect of initial moisture content of wheat grain on its drying time in a rotary dryer
Author (s): N. Perekopsky, A. Zakharov, A. Zykov and V. Ynin
Abstract:

In the North-West Region of the Russian Federation, the major part of harvested grain seeds and fodder grain undergoes the post-harvest treatment at special multipurpose stations to prepare it for storing. Since the characteristics of raw materials supplied from the fields differ significantly, the traditional grain treatment technologies require certain upgrading in terms of both target grain use and its moisture content. Study aim. The presented study focused on the drying process of wheat grain seeds and fodder grain, more specifically, the dynamic pattern of drying time depending on the grain layer thickness. The study object was the drying process of wheat grain in a rotary dryer. Materials and methods. The experiments were performed on a rotary (carousel) drying plant. The study used a stationary “FAUNA-P” in-stream meter with two sensors installed in the carousel dryer and BV-40 silo. It provided the real-time measuring of grain moisture content and temperature and accurate tracking of the dynamic pattern of drying wheat grain seeds and fodder grain in the layer of 0.45 m, which was conveniently divided into three zones of 0.15 m each. Results and conclusions. According to the experiments results, each grain layer dried at a different rate. To reduce the drying time of above 25% moisture grain the drying layer of 0.3 m was found most rational, in contrast to the average initial grain moisture content of 20% and a structurally specified layer height of 0.45 m. The grain layer height in the carousel dryer was considered rational if, having passed it, the heat carrier was completely saturated with moisture. The initial moisture content and the grain drying regime affected not only the drying time, but also, as a consequence, the production capacity and specific energy consumption of the rotary dryer. Thus, with the initial grain moisture content of 21.5%, the production capacity of the dryer in the grain seed drying mode decreased by 1.9 times, and per ton costs increased by 1.45 times as compared to the fodder grain drying mode.

   

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Title: Thermal-Hydraulic processes in air and carbon dioxide gas turbines
Author (s): Kindra V., Komarov I., Osipov S., Makhmutov B. and Naumov V.
Abstract:

The continuous increase of the anthropogenic emission of carbon dioxide and toxic agents causes the development of oxy-fuel combustion power cycles. This development involves the improvement of the advanced approach to the design of the carbon dioxide operating power production equipment. This paper discloses the influence of the thermodynamic and thermal-physical performance of gas turbine cooling agents upon the efficiency of the thermal-hydraulic process in the flow path and cooling system channels.

   

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Title: Securing and optimizing sensor network using deep learning algorithms
Author (s): Vimal Kumar Stephen, Robin Rohit Vincent and Mohammed Tauqeer Ullah
Abstract:

Wireless sensor network (WSN) is a collection of sensor nodes that can sense various physical properties and communicate with one another in various ways. Security is a major concern in many real-world WSN applications. The goal of this work is to improve WSN security by identifying and countering adversarial denial-of-service (DoS) attacks. WSNs are subject to a variety of DoS assaults, depending on the layer they're attacking. This research employs neural network (NN) & support vector machine (SVM) machine learning approaches to detect denial-of-service (DoS) assaults on the MAC layer. After that, it assesses the effectiveness of the two approaches. Securing the MAC layer is critical because it allows sensor nodes to access wireless channels. The results revealed that these algorithms performs well in securing and optimizing the sensor networks.

   

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Title: Inverse point kinetics with feedback effects depending on the history of neutron density using the first bernoulli number
Author (s): Daniel Suescún-Díaz, Geraldyne Ule-Duque and Gilberto Espinosa-Paredes
Abstract:

In this work, it is proposed to study the calculation of reactivity using the inverse point kinetic equation, considering the Doppler effect due to temperature feedback in a nuclear reactor. Different numerical experiments are performed assuming an exponential form in the neutron density, with different time steps and different initial conditions for the temperature. The results found allow establishing an interval of validity of the proposed method compared to the analytical solution.

   

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Title: Spectral image classification from compressive measurements based on singular value decomposition
Author (s): Ferley Medina Rojas, Juan A. Castro Silva and Faiber Robayo Betancourt
Abstract:

Classification consists of categorizing image pixels, specifically, in a spectral image (SI) it is used to determine environmental pollution agents, to stable land use, and to monitor crops. Due to the high dimensionality of the SI, classification is inefficient. However, compressive sampling (CS) has been established as a sampling protocol of SI allowing the reduction of data. Recently, CS classification is a promising research area, but it has only been tested on some specific systems. This paper proposes a general classification algorithm in compressive spectral imaging which uses singular value decomposition for estimating sparse dictionary of the data. From this dictionary, the algorithm performs a rough estimation which allows the classification of every spectral pixel in known classes by using discriminant analysis. The estimation is made by solving the inverse problem. Simulations with three state of the art compressive imagers show the outstanding performance of the proposed algorithm even in presence of noise.

   

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Title: GA based reactive power procurement cost optimization of deregulated electricity market
Author (s): Vishnu B. Patel and Rajesh M. Patel
Abstract:

RPP is one of the most essential ancillary service. In VIU, the single monopoly company took charge of operations such as generation, transmission and distribution, so the supply of ancillary service and its charging was not a crucial concern as it was included in the energy price. Different entities conducted various tasks such as generation, transmission and distribution in the deregulated industry, so that the supply of reactive power to sustain voltage security became a critical problem. For their facilities, the reactive electricity provided from multiple suppliers needs to be remunerated. In order to ensure the efficient and safe functioning of the whole power grid, the correct reactive power procurement process and proper handling of RP support must be taken care of by ISO. The emphasis of this paper was on RPP and the estimation of the optimal overall market payment for the procurement of reactive capacity. The GA used to solve anticipated method and implemented on IEEE 24 bus system.

   

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Title: Pressure and pressure derivative determination of the average reservoir pressure for vertical wells in naturally fractured reservoirs from buildup, drawdown and multi-rate tests
Author (s): Freddy Humberto Escobar, Angela Maria Palomino and Daniel Suescun-Diaz
Abstract:

The late-time well pressure solution for a homogeneous reservoir changes when the well has been fractured. Same situation happens in a naturally fracture reservoir. Then, the average reservoir pressure ought to be changed. In this work, both average reservoir pressure and reservoir shape factor equations are provided for hydraulically-fractured vertical wells in naturally fractured occurring formations bearing hydrocarbons. The expressions are given for buildup, drawdown and multi-rate tests in both oil and gas tests. These expressions are successfully tested with synthetic examples and compared to calculations from a commercial well test software given absolute deviation errors lower than 1.3 %.

   

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Title: COINIC-PH: A Philippine new generation series of coin intelligent classification inference approach for visually impaired
Author (s): Alvin Alon, Catherine Alimboyong, Philip Ermita, Jaime Pulumbarit and Marlon Hernandez
Abstract:

Object detection experiences widespread use in many technology-related fields nowadays. This paper uses computer vision to execute object detection of the new series of coins of the Philippine peso. Compared to the coin designs of the previous series, these coins are much more identical to each other, which can be hard to distinguish for people with bad eyesight. Through the use of object detection, these coins can then be classified into their respective amounts just by an image or video sample. The machine learning model used in this paper performed sufficiently, with it being able to distinguish the one, five, ten, and twenty-peso coins from each other from image and video samples.

   

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