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All Journal Rekayasa Mesin DINAMIKA Jurnal Ilmiah Teknik Mesin Journal of Mechanical Engineering Science and Technology Jurnal Rekayasa Material, Manufaktur & Energi CARADDE: Jurnal Pengabdian Kepada Masyarakat ABDIMAS SILIWANGI Infotekmesin Scientific Journal of Mechanical Engineering Kinematika Jurnal Dinamis Community Empowerment Mechanical Engineering for Society and Industry Automotive Experiences Jurnal Pengabdian Masyarakat Abdimas Dinamis
Hendry Y. Nanlohy
Department Of Mechanical Engineering, Jayapura University Of Science And Technology, Jayapura, 99351, Indonesia
Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Transportation Other

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Journal : Journal of Mechanical Engineering Science and Technology

 1 
Machine Vision for the Various Road Surface Type Classification Based on Texture Feature Susi Marianingsih; Widodo Widodo; Marla Sheilamita S. Pieter; Evanita Veronica Manullang; Hendry Y. Nanlohy
Journal of Mechanical Engineering Science and Technology (JMEST) Vol 6, No 1 (2022)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um016v6i12022p040

Abstract

The mechanized ability to specify the way surface type is a piece of key enlightenment for autonomous transportation machine navigation like wheelchairs and smart cars. In the present work, the extracted features from the object are getting based on structure and surface evidence using Gray Level Co-occurrence Matrix (GLCM). Furthermore, K-Nearest Neighbor (K-NN) Classifier was built to classify the road surface image into three classes, asphalt, gravel, and pavement. A comparison of KNN and Naïve Bayes (NB) was used in present study. We have constructed a road image dataset of 450 samples from real-world road images in the asphalt, gravel, and pavement. Experiment result that the classification accuracy using the K-NN classifier is 78%, which is better as compared to Naïve Bayes classifier which has a classification accuracy of 72%. The paving class has the smallest accuracy in both classifier methods. The two classifiers have nearly the same computing time, 3.459 seconds for the KNN Classifier and 3.464 seconds for the Naive Bayes Classifier.
Gasohol Engine Performance with Various Ignition Timing Hendry Y. Nanlohy; Suyatno Arief; Helen Riupassa; Martina Mini; Trismawati Trismawati; Mebin Samuel Panithasan
Journal of Mechanical Engineering Science and Technology (JMEST) Vol 6, No 1 (2022)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um016v6i12022p048

Abstract

Experimental research has been conducted on the effect of ignition timings on the characteristics and performance of gasohol engines such as power, torque, specific fuel consumption, and thermal efficiency. The fuel used in this research is pure gasoline and a mixture of 50% bioethanol (BE50). The results show that the ignition timing that gives the maximum effect occurs at the top and bottom dead points of 9 degrees for gasoline and 12 degrees for BE50 fuel. Furthermore, the maximum power is obtained at 6,500 rpm, and at an ignition time of 12 degrees BTDC the maximum power generated is 4.63 hp, while for an ignition time of 9 degrees BTDC the power generated is 3.38 hp which occurs at 6500 rpm. These results indicate that there is an increase in power of 6.4%. Moreover, the results also show that for optimal gasoline conditions, the amount of energy consumed at an engine speed of 7000 rpm is around 15705.78 kcal/hour, and for BE-50 it is around 12582.03 kcal/hour, where there is a reduction of about 25.44 %. However, in general, it can be seen that during optimal ignition, there is a saving in fuel consumption in the gasoline-BE50 mixture, while at the same time producing a fairly large thermal efficiency. These results indicate that BE50 has the potential to be used as an alternative fuel in small gasoline engines.
Comparative Studies on Combustion Characteristics of Blended Crude Jatropha Oil with Magnetic Liquid Catalyst and DEX under Normal Gravity Condition Nanlohy, Hendry Y.
Journal of Mechanical Engineering Science and Technology (JMEST) Vol 5, No 2 (2021)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um016v5i22021p079

Abstract

A comparative study on the combustion characteristics of a single droplet fueled by DEX, crude jatropha oil (CJO), and a mixture of CJO with a magnetic liquid catalyst of rhodium trisulfate has been carried out under normal gravity conditions. The high viscosity of crude jatropha oil makes it difficult to burn under normal conditions (room temperature and atmospheric pressure), therefore the addition of a magnetic liquid catalyst rhodium trisulfate is needed to improve the properties of crude jatropha oil. As a catalyst, rhodium trisulfate has the potential to improve combustion performance while improving the physical properties of crude jatropha oil as an alternative fuel for the better. Furthermore, performance tests were also carried out with DEX fuel with a cetane number (CNs) 53. The results showed that compared to DEX, it was seen that the liquid metal catalyst rhodium trisulfate succeeded in making crude jatropha oil more charged so that the combustion process was better. This is evidenced by a significant change in the dimensions of the flame and an increase in the combustion temperature. Moreover, it is also seen that the burning rate increases and the ignition delay become faster.
Artificial Neural Network-Based Modeling of Performance Spark Ignition Engine Fuelled with Bioethanol and Gasoline Marianingsih, Susi; Mar’i, Farhanna; Nanlohy, Hendry Y.
Journal of Mechanical Engineering Science and Technology (JMEST) Vol 7, No 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um016v7i22023p190

Abstract

Machine learning technology can distinguish the relationship between engine characteristics and performances. Therefore, the goal of the present work is to predict the performance parameters of a single-cylinder 4-stroke gasoline engine at different ignition timings using a blended mixture of gasoline and bioethanol by an artificial neural network (ANN). Experimental data for training and testing in the proposed ANN was obtained at a dynamic speed and full load condition. An ANN model was developed based on standard Back-Propagation algorithm for the spark ignition engine. Multi-layer perception network (MLP) was used for non-linear mapping between the input and output parameters. An optimizer in the family of quasi-Newton methods (lbfgs) and the rectified linear unit function were used to assess the percentage error between the desired and the predicted values. The network input parameters are engine speed, fuel, and ignition timing. Furthermore, torque, power, specific fuel consumption (SFC), thermal efficiency (ηth), and energy consumption (EC) are taken as output parameters. The results show that ANN is the proper method for predicting SIE performance because it has accurate prediction results that are very similar to experimental results. Moreover, from the observation results, the ANN model can predict the engine performance quite well with correlation coefficient (R)=0.962139 and MSE=0.003967 for data testing.
Computational Fluid Dynamics Analysis of Temperature Distribution in Solar Distillation Panel with Various Flat Plate Materials Trismawati, Trismawati; Nanlohy, Hendry Y.; Riupassa, Helen; Marianingsih, Susi
Journal of Mechanical Engineering Science and Technology (JMEST) Vol 8, No 1 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um0168i12024p108

Abstract

As the world population continues to grow, the demand for clean water is increasing daily, making it a crucial resource to access. However, there are ways to harness abundant resources like solar energy and seawater to produce clean water. The present studies have conducted experimental investigations to convert seawater into freshwater using solar stills, where solar energy is utilized as the primary heat source for evaporation. The temperature distribution inside the solar stills was analyzed using a flat plate made of three different materials: copper, stainless steel, and aluminum. To examine the temperature distribution and performance of the solar stills, researchers employed computational fluid dynamics simulations (Ansys R15.0). The results showed variations in temperature distribution among the three plate materials. Copper flat plates achieved the highest temperature, approximately 44.5 Celsius, followed by aluminum at 43.91 Celsius, while stainless steel exhibited the lowest temperature at around 42.01 Celsius. The average heat flux across the three materials was approximately 581 W/m2. Additionally, observations indicated that the amount of convection occurring in copper flat plates was 121.108 Watts; in aluminum, it was 118.517 Watts; and in stainless steel, it was 105.05 Watts. The radiation energy for stainless steel flat plates was 29.93 W; for copper, 16.14 W; and for aluminum, 13.49 W.
Captivating Combustion Traits of Bio-Oil Droplets Enriched with Bio-Additives from the Areca Shell Waste Raehan, Muhammad Alif; Riupassa, Helen; Nanlohy, Hendry Yoshua
Journal of Mechanical Engineering Science and Technology (JMEST) Vol 8, No 2 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um016v8i22024p384

Abstract

Fuel derived from crude vegetable oil, such as coconut oil, holds promise as an alternative energy source to mitigate the increasing reliance on fossil fuels driven by population growth and industrial activities. The experiment involved suspending a single droplet of crude coconut oil mixed with activated carbon from areca shell waste and placed at the junction on R-type thermocouple (Pt/Pt-Rh13%). The droplets were ignited using a hot wire and subjected to atmospheric pressure and room temperature. Coconut oil comprises a saturated triglyceride carbon chain compound of approximately 91%, and areca shell waste possesses a porous structure that fosters favorable interactions between fuel molecules. The droplet combustion method was selected to streamline the process and enhance the contact area between air and fuel, thereby boosting the reactivity of fuel molecules. The research found that adding activated carbon shortens the carbon chain, making it more reactive and easier for the fuel to ignite. Specifically, activated carbon significantly enhances fuel performance at a concentration of two parts per million (ppm). At this level, the fuel absorbs heat more effectively and ignites faster compared to one ppm and three ppm levels. Moreover, the results show that heat absorption occurs slowly at one ppm, while at three ppm, the increased molecular mass of the fuel can strengthen carbon-bonding forces. These factors contribute to a longer ignition time for the fuel. The findings suggest that the activated carbon from areca shell waste can play a good role as a combustion catalyst, where overall, fuel performance increases.
Co-Authors Abdul Basit Abdul Basit Andi Sanata Andika Prasetya Armanda Putri, Fellicia Roshita Asyhar, Muhammad Maulana Bambang Suhartawan Basri Katjo Bonefasius Bao Bosta Sihombing Calvin R. Rumansara Dani Hari Tunggal Prasetiyo Fadliyanur Fairuddin, Fairuddin Feri Oktapiyanor Gazpar BAO Harsanta, Bagus E. Haurissa, Jusuf Helen Riupassa Herman Tjolleng Taba Hotnida Nainggolan I Made Rasta Imam Sholahuddin Indrati, Wahyu Iriyanto, Santje M Iriyanto, Santje Magdalena Klinus Toker Kristianta, Franciscus Xaverius Kurnia Iswardani Manullang, Evanita Veronica Mar'i, Farhanna Marianingsih, susi Marla Sheilamita Shalin Pieter Marthina Mini Marthina Mini Marthina Mini, Marthina Martina Mini Masaki Yamaguchi Masaki Yamaguchi Mastina Maksin Mebin Samuel Panithasan Mini, Mathina Muchsin Muchsin Muhammad Akhlis Rizza Muhammad Dimyati Nashrullah Muji Setiyo Mustafafi, Wanda Zahratul Nasrul Ilminnafik Nevada M.J. Nanulaitta Novitasari, Riza Panithasan, Mebin Samuel Peday, Harold Thijs Nadyo Rachmat Subagyo Raehan, Muhammad Alif Renny Chandra Puspitadewi Safira, Meilani Sarikoc, Selcuk Satworo Adiwidodo Selcuk Sarikoc Sialana, Jufri Susi Marianingsih Suyatno Suyatno Suyatno Suyatno Syamsudin Usman Takuya Tomidokoro Timang, Rison Sando trismawati Trismawati Trismawati Trismawati Trismawati Trismawati, Trismawati Usman, Syamsudin Utaminingrum, Fitri Walintukan, Akbar Vicky V Widodo Widodo Yamaguchi, Masaki