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All Journal Jurnal Teknik ITS JMES The International Journal of Mechanical Engineering and Sciences
Fungky Dyan Pertiwi
Institut Teknologi Sepuluh Nopember Surabaya
Energy Engineering Materials Science & Nanotechnology Mechanical Engineering

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Pengaruh Penambahan PWM (Pulse Width Modulation) Pada Generator HHO Tipe Dry Cell Fungky Dyan Pertiwi; Djoko Sungkono Kawano
Jurnal Teknik ITS Vol 2, No 2 (2013)
Publisher : Direktorat Riset dan Pengabdian Masyarakat (DRPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (400.061 KB) | DOI: 10.12962/j23373539.v2i2.4442

Abstract

Generator HHO memanfaatkan proses elektrolisis air agar mendapatkan gas H2. Namun, pada praktiknya pemakaian arus dari aki yang besar dan temperatur tinggi membuat bejana generator menjadi cepat rusak, sehingga dibutuhkan tambahan rangkaian elektronika PWM pada pengujian generator HHO guna mengatasi permasalahan tersebut. Penelitian menggunakan elektroda plat berjumlah 9 berdimensi 120mm 120mm, tebal 1mm dan dibatasi oleh o-ring dengan diameter 126mm, tebal 3mm. Pengujian dilakukan secara eksperimen dengan 2 kelompok yaitu kelompok control yang mana pengujian tanpa menggunakan PWM serta kelompok uji dimana pengujian menggunakan PWM dengan variasi duty cycle 30%, 50% dan 70%. Pengujian dilakukan hingga temperatur elektrolit 93oC. Hasil uji didapatkan bahwa arus, laju produksi dan efisiensi terbesar didapatkan pada pengujian tanpa PWM yang mencapai 60,6A, 6,033 10-6kg/s dan 25,69%. Namun, pada pengambilan data kedua efisiensi turun menjadi 19,74%. Penambahan PWM pada pengujian berpengaruh pada arus dan temperatur yang stabil meskipun laju produksi dan efisiensi lebih kecil daripada pengujian tanpa PWM. Pengujian dengan PWM pada duty cycle 70% menghasilkan laju produksi dan efisiensi terbesar yang mencapai 1,843 10-6 kg/s dan 15,19%.
Numerical Study of Blended Winglet Geometry Variations on Unmanned Aerial Vehicle Aerodynamic Performance Fungky Dyan Pertiwi; Arif Wahjudi
JMES The International Journal of Mechanical Engineering and Sciences Vol 6, No 1 (2022)
Publisher : LPPM, Institut Teknologi Sepuluh Nopember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25807471.v6i1.12317

Abstract

An unmanned aerial vehicle (UAV) is an unmanned aircraft that can be controlled remotely or flown automatically. Nowadays, the use of UAVs is extensive, not only limited to the military field but also in civilian tasks such as humanitarian search and rescue (SAR) tasks, railroad inspections, and environmental damage inspections. Therefore, study on UAV becomes essential to answer the challenges of its increasingly widespread use. This study explores the addition of a blended winglet on the swept-back wing of the UAV. It is to predict the effect of the aerodynamic performance. The backpropagation neural network (BPNN) method helps to predict the aerodynamic performance of the UAV in the form of a lift-drag coefficient ratio (CL/CD) and drag coefficient at 0O angle of attack (CD0). It is based on blended winglet parameters such as height, tip chord, and cant angle. The obtained BPNN modeling has a network architecture of 3 inputs, 2 hidden layers, and 1 output with a mean square error (MSE) of 4.9462e-08 and 4.4756e-06 for the relationships between blended winglet parameters with CL/CD and CD0, respectively.
Co-Authors Arif Wahjudi Sungkono, B.J. Santosa