Journal of Engineering and Technological Sciences
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Design and Characterization of Ultrasonic Langevin Transducer 20 kHz Using a Stepped Horn Front-Mass
Get PDFUltrasonication is a method that is widely used in various fields. One of its applications is to accelerate the process of homogenization, emulsification, and extraction. In the ultrasonicator system, the transducer is an extremely important device. The resonant frequency, longitudinal vibration amplitude, and electromechanical coupling are the targets in designing an ultrasonic transducer. In this investigation, the main contribution was the development of a simple and effective method for mechanically tuning the resonant frequency of the transducer by adding mass to the front end of the mass or stepped horn. This study also aimed to obtain optimal results by examining the effects of geometric dimensions, bolt prestress, stress distribution, resonant frequency, amplitude, and electrical impedance. The ultrasonic transducer model was designed with a resonant frequency of 20 kHz and simulated using the finite element analysis. The steps involved included calculating the dimensions and geometric structure of the transducer, modeling using the finite-element method, and experimental validation. The simulation results and measurements showed that the series resonant frequency, electrical impedance, and effective electromechanical coupling of the Model-4 transducer 16∙13 mm radiator configuration were 20.15 kHz, 100 Ω, and 0.2229 from the simulation results, and 20.17 kHz, 24.91 Ω, and 0.2033 from the measurement results. A percentage difference, or relative error, of 0.1% was obtained between the simulation and the experimental results for this Model-4 with bolt prestressing at 15 kN
Selection of Material and Manufacturing Technology for Batik Canting Stamps Based on Multi-Criteria Decision-Making Methods
Get PDFThis study aimed to develop alternative materials and technologies for making canting stamps used in producing batik canting (stamped batik) to transfer hot wax from the pan to the fabric. Previous researchers have studied materials such as wood, aluminum, multiplex, acrylic, and acrylonitrile butadiene styrene (ABS). Manufacturing technologies have also been analyzed, including manual manufacturing, computer numerical control (CNC) milling, laser cutting, and additive manufacturing. However, none of these materials and technologies were considered suitable alternatives for copper canting stamps. This paper proposes Conductive ABS-Electroformed By Copper (CABS-EBC) through additive manufacturing and electroforming processes as alternative material for canting stamps. A multi-criteria decision-making (MCDM) approach was used to assess alternative materials and technologies. The alternatives and criteria were calculated using the Simple Additive Weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Preference Ranking Organization Method of Enrichment Evaluation (PROMETHEE) techniques. Besides this, assessment was also carried out based on expert opinions. The results showed that copper was the most suitable material, with Closeness = 1.000, Yi = 0.995, and Phi = +1.00. Meanwhile, CABS-EBC ranked second, with Closeness = 0.627, Yi = 0.864, and Phi = +0.50. The selected technology was additive manufacturing combined with electroforming, with Closeness = 0.700, Yi = 0.895, and Phi = +0.39. By using MCDM on the material-technology development candidates it was found that CABS-EBC processed with additive manufacturing is capable of substituting copper as a canting stamp material. It is expected that the production capacity of the traditional manufacturing process can be enhanced by adopting these new materials and technologies
Performance of Moving Bed Biofilm Reactor Integrated Septic Tank in Treating Office Building Wastewater
Get PDFThis research aimed to find the effect of initial concentration and hydraulic retention time (HRT) on modified septic tank (MST) performance in treating wastewater from an office building. The synthetic wastewater used had an average COD:TN:TP ratio of 84:28:1, adjusted to office building wastewater characteristics. The experiment was executed under steady conditions using three variations of HRT (12, 24, and 36 hours) and different initial concentrations of COD (106, 252 and 432 mg COD/L), TN (35, 85 and 146 mg N/L) and TP (1.26, 3 and 5.14 mg P/L). The result showed that the MST removed 82% to 92% of COD, 41% to 60% of TN, 45% to 61% of NH4, and 39% to 55% of TP. The maximum removal was achieved at 36 h of HRT, COD:TN (3:1), and COD:TP (84:1). One-way ANOVA showed that the initial concentration and HRT had significant effects on the performance of MST (p < 0.05). This suggests that appropriate control of the initial concentration and HRT in the MST can effectively remove organics and nutrients from office building wastewater
Progress and Challenges of Biological Leaching of Heavy Metal in Coal Ash from a Power Plant
Get PDFBioleaching is a technique for reducing the heavy metal content of coal ash by using bacteria, fungi, or yeast. Previous studies in heavy metal bioleaching of coal ash discussed the factors affecting the process, but as yet there is little information on the challenges of using microorganisms. Therefore, this study aimed to obtain comprehensive information regarding the use of microorganisms in heavy metal bioleaching. Heavy metal concentrations in coal ash are low, and the metals are diverse. The components of coal ash are complexes that cannot leach certain heavy metals according to previous studies. These low concentrations and complex components make it difficult to investigate the bioleaching mechanism. The combination of biological and chemical interactions involves various components in this system. The high concentration of iron and heavy metal leached could be toxic for microorganisms. The process is influenced by several factors, such as particle size, pH, and pulp density. Most heavy metal bioleaching studies on coal ash have been conducted on a small scale to control conditions affecting the process. Bioleaching kinetics in coal is a liquid-solid reaction that can be represented by the shrinking core model, which was mainly used in this study
Physical and Chemical Properties of Indonesian Coffee Beans for Different Postharvest Processing Methods
Get PDFThe purpose of this study was to identify the physical and chemical properties of Indonesian coffee beans for different postharvesting methods after being roasted. Several types of Indonesian export coffee, i.e., Gayo Luwak coffee, Wamena coffee, Toraja coffee, Gayo coffee, Flores coffee and Kintamani coffee, were used in the present study. Each coffee has its own aroma and taste according to the location, soil type, and land elevation. The roasting process started with preheating the roasting machine, after which the samples were roasted for about 15 minutes at 215℃ to obtain the medium-to-dark (MTD) roasting level. The physical properties measured included density, mass loss, porosity, water content, and morphology using a scanning electron microscope. The transmittance spectrum was observed by Fourier transform infrared spectroscopy (FTIR). The physical properties of the coffee were successfully measured. The bulk density varied from 0.6 to 0.7 g/cm3, and particle density was about 0.9 g/cm3 for green beans. The roasting process reduced the bulk and particle density to 0.3 g/cm3 on average and 0.8 g/cm3, respectively. The fully-washed condition gave an overlapping spectrum for green and roasted beans, which shows that the roasting process did not affect the spectrum. The results can be used to study the coffee quality resulting from different postharvest processing methods
Development of Non-Intrusive Load Monitoring of Electricity Load Classification with Low-Frequency Sampling Based on Support Vector Machine
Get PDFNon-intrusive load monitoring (NILM) is a promising approach to provide energy consumption monitoring of electrical appliances and analysis of current and voltage data with less instrumentation. This paper proposes an electrical load classification model using support vector machine (SVM). SVM was chosen to keep the computational cost low and be able to implement an embedded system. The SVM model was utilized to classify the on/off state of air conditioners, light bulbs, other uncategorized electronics, and their combinations. It utilizes low-frequency sampling data captured every minute, or at a 0.0167 Hz rate. Utilization change in active and reactive power was used as a feature in the model training. The optimal kernel for the model was the radial basis function (RBF) kernel with C and gamma values of 88.587 and 2.336 as hyperparameters, producing a highly accurate model. In testing with real-time conditions, the model classified the on/off state of the electrical loads with 0.93 precision, 0.91 recall, and 0.91 f-score. The results of testing proved that the model can be applied in real time with high accuracy and with an acceptable performance in field implementation using an embedded system
