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All Journal J-Sil (Jurnal Teknik Sipil dan Lingkungan) TEKNIK KAPAL Jurnal Ilmu Pengetahuan dan Teknologi Kelautan Jurnal Geodesi Undip Journal of Applied Geospatial Information JURNAL ILMIAH GEOMATIKA MAJALAH ILMIAH GLOBE Elipsoida : Jurnal Geodesi dan Geomatika Jambura Geoscience Review Jurnal Pasopati : Pengabdian Masyarakat dan Inovasi Pengembangan Teknologi Jurnal Marine Inside J-Sil (Jurnal Teknik Sipil dan Lingkungan)
Bandi Sasmito
Departemen Teknik Geodesi, Fakultas Teknik, Univeristas Diponegoro
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Transportation

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Journal : J-Sil (Jurnal Teknik Sipil dan Lingkungan)

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Analisis Pengukuran Kecepatan Aliran Permukaan Sungai Dengan Metode “Large Scale Particle Image Velocimetry” Menggunakan Fotogrametri Terestris, Studi Kasus : Sungai Mungkung, Kabupaten Sragen Sheehan Maladzi, Havi; Bashit, Nurhadi; Sasmito, Bandi
Jurnal Teknik Sipil dan Lingkungan Vol. 9 No. 1: April 2024
Publisher : Departemen Teknik Sipil dan Lingkungan, IPB University and The Institut of ENgineering Indonesia (PII), Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jsil.9.1.83-92

Abstract

Purpose – The infeasibility and impracticality of using intrusive measurement equipment to collect information on flow velocities in complex environments created a compelling need for alternative, nonintrusive velocimetry approaches. Several studies have already demonstrated that drone-borne imaging techniques allow for quick, safe and comprehensive quantification of surface flow velocities. Despite the efforts of the existing studies, there is still limited experience in using such techniques. Within this context, this research aimed to assess the feasibility of using drone-borne imaging techniques and large-scale particle image velocimetry (LSPIV) to infer surface flow velocities within large-scale fluvial applications. This research also aimed to provide a process-based explanation as to why or how certain methods are effective or ineffective when applying LSPIV. A fundamental requirement in LSPIV is that the surface of the flow must be seeded with tracers. This research investigated whether it is feasible to apply LSPIV in flows seeded by naturally occurring features, such as foam and air bubbles generated by turbulent activities in the flow. Methods and materials – A detailed workflow was developed to guide the LSPIV analyses performed in this study. The LSPIV workflow can be characterised by four main stages, including (1) data acquisition and preparatory work; (2) image pre-processing; (3) image evaluation; and (4) post-processing. The first stage involved the collection of video recordings of the flowing water near hydraulic structures at two study areas in the Netherlands, namely the Dinkel River at Lattrop-Breklenkamp and Meuse River at Sambeek. These recordings were collected by both a drone and terrestrial camera system. In the second stage, images obtained from the field campaign were processed through the application of image stabilisation and orthorectification to reduce the effects of image distortions, deformations and instabilities; the imagery was also enhanced with various filters to improve the detectability and traceability of features on the water surface. Subsequently, the LSPIV algorithm was applied to the pre-processed imagery to obtain a vector field representing the surface water flow velocities at both study areas. The LSPIV algorithm essentially attempts to estimate the displacement of distinct features on the water surface through the application of a statistical pattern matching technique; more specifically, the cross-correlation function is computed to achieve this. The algorithm then relates therecorded displacements to the velocity field of the observed flow. In the final stage, spurious vectors in the vector field were corrected, and an accuracy assessment was performed using reference velocity measurements obtained from the so-called float method. This research further explored the influence of various experimental configurations and image processing parameters on the LSPIV outputs through an extensive sensitivity analysis. Finally, this study performed a comparative analysis of drone-based LSPIV with conventional, fixed camera LSPIV implementations. Results and discussion – Naturally occurring features on the water surface were found to be omnipresent in the Dinkel River study area at the time of the field campaign; the seeding density was estimated to be around 10%, and overall adequate seeding homogeneity was observed. The LSPIV derived surface water flow velocities for the Dinkel River case were in relatively good agreement with the reference velocity measurements, with mean absolute velocity deviations in the order of 10-2 m/s and normalised root mean squared values ranging between 5% and 9%. The velocity fields could accurately describe the bulk flow behaviour and capture horizontal flow structures at different spatial scales. The LSPIV analysis in the case of the Meuse River study area yielded comparatively worse agreement with the reference measurements; the accuracy assessment revealed mean absolute deviations from the reference values in the order of 10-1 m/s and a normalised root mean squared error value around 35%; the poor performance was attributed to the low seeding densities (±5%) and strong seeding inhomogeneity. The sensitivity analysis highlighted the importance of specifying the appropriate sampling frequency at which the images are collected. In low flow conditions, it was required to resample the data to lower sampling frequencies (2-5 Hz) to achieve adequate LSPIV performance. Other key parameters in LSPIV implementations are the image sequence duration, interrogation area size and image resolution. The appropriate image sequence duration is highly case-specific and should be selected with extreme care prior to the LSPIV analysis; durations of only several seconds may not be sufficient to obtain satisfactory results. The interrogation area size and image resolution are particularly important for flows that contain relatively large surface features. Based on experimental observations, the inclination of the camera axis with respect to the water surface must be kept as small as possible to minimise error associated with perspective distortions. Furthermore, the comparative analysis of drone-based LSPIV with fixed camera LSPIV implementations strongly favoured the use of drones in large-scale fluvial applications; the significant inclination of the camera axis and improper positioning of the stationary camera setup resulted in significant measurement error. Above all, low seeding densities (<10%) and seeding inhomogeneity were found to be detrimental for the measurement accuracy. Inthe case of tracer scarcity and seeding inhomogeneity, it is recommended that the LSPIV analysis is performed on the video portions that exhibit the best seeding conditions instead of the full video. Conclusion – Based on the findings of this research, it can be argued that drone-based LSPIV offers a promising method for capturing the spatial and temporal structure of fluid motions without the need for artificial flow seeding. However, one must realise that the successful application of LSPIV requires a thorough understanding of its underlying principles and the parameters associated with data collection and image processing. Under the right conditions and by carefully selecting the appropriate experimental configurations and input parameters, accurate surface water flow velocity estimations may be obtained. Future research should focus attention on further establishing the validity of drone-based LSPIV; this can done by rigorously testing drone-based LSPIV implementations in different environments at different spatial scales under varying seeding and flow conditions.
Co-Authors ., Hani'ah Abdi Sukmono, Abdi Adiasti Rizqi Hardini Adib Fahrul Arifin Ahmad Faishal Matazah Putra Ahmad Hidayat Ahmad Iqbal Maulana Lubis Akbar Kurniawan Alan Aji Bintang Alfian Putra Setiadarma Almira Delarizka Alvatara Partogi Hutagalung Amirul Hajri An Nisa Tri Rahmawati Andi Trimulyono Andri Suprayogi Andri Yanto Parulian Tamba Anggi Karismawati Anggoro Wahyu Utomo Angkoso Dewantoro Arfina Kusuma Putra Arief Laila Nugraha Arief Laila Nugraha Arief Laila Nugraha Ariella Arima Aniendra Armenda Bagas Ramadhony Arnita Ikke Sari Arwan Putra Wijaya Arwan Putra Wijaya Asih, Nevi Tri Lestiyo Aulia Budi Andari Aulia Hafizh Aulia, Fatah Avini Sekha Rasina Ayu Hapsari Aditiyanti Bambang Darmo Yuwono Bambang Darmo Yuwono Bambang Sudarsono Bambang Sudarsono Bashit, Nurhadi Bekti Noviana Bella Riskyta Arinda Bram Ferdinand Saragih Chusni Ansori David Jefferson Baris Denni Apriliyanto Desvandri Gunawan Devi Irsanti Devi Nilam Sari Deviana Putri Sunarernanda Dian Ika Aryani DIKA NUZUL RACHMAWATI Dimas Bagus Dita Ariani DITHO TANJUNG PRAKOSO Dwi Nugroho Eko Andik Saputro Eko Didik Purwanto, Eko Didik Elsa Regina Rizkitasari Esa Agustin Alawiyah Ety Parwati Fadhlan Hamdi Fajar Dwi Hastono Farrah - Istiqomah, Farrah - Fauzi Janu Amarrohman, Fauzi Janu Fauzi Janu Ammarohman Firman Hadi Firman Hadi Firman Hadi Fitra S Pandia Frandi Barata Simamora Fuad Hari Aditya Gabriel Yedaya Immanuel Ryadi Galih Pratiwi Galuh Fitriarestu Santoso Ghazian Hazazi Gilang Yudistira Hilman Gunita Mustika Hati Hadi, Firman Hana Sugiastu Firdaus Hana Sugiastu Firdaus Hani&#039;ah . Hani&#039;ah Hani&#039;ah Hani'ah, Hani'ah Haniah Haniah Hani’ah Hani’ah Harianto Harianto Harmeydi Akbar Hartomo Haryo Kuncoro Haryo Daruwedho Hasan Mustofa Amirudin, Hasan Mustofa Hayu Rianasari Hestiningsih Hestiningsih Indah Prasasti Indriyanto, Ignatius Wahyu Innong Pratikina Akbaruddin Jaka Gumelar Jerson Otniel Purba Jhonson Paruntungan Matondang Johan Irawan Kalinda, Icha Oktaviana Putri Khofifatul Azizah Kurniantoro, Ridhwan L. M. Sabri Laode M Sabri Latifah Rahmadany LM. Sabri M. Alfarisi Handifa M. Andu Agjy Putra Mamei Saumidin Meiska Firstiara Maudi Miftakhul ‘Ulya Rimadhani Moehammad Awaluddin Moehammad Awwaluddin Mohamad Jorgie Prasetyo Monica Apriliana Pertiwi Monika Maharani, Shang Bhetari Muchammad Misbachul Munir, Muchammad Misbachul Muhamad Dicky H. Muhammad Agam Cakra Donya Muhammad Al Kautsar Muhammad Dimas Aji N. Muhammad Fadhli Auliarahman Muhammad Helmi Muhammad Hudayawan Nur L Muhammad Ilman Fanani Muhammad Luthfi Ramadhan Muhammad Nur Khafidlin Mulawarman, Reza Al Arif Muna, Nailatul Mutiah Nurul Handayani Nainggolan, Yohana Christie Nanang Noviantoro Prasetyo Nandia Meitayusni Nabila Nasrul Arfianto Nevy Dyah Rustikasari Nila Hapsari Nawangwulan Nilasari, Monica NIRTANTO, ILHAAM CAHYA Niswatul Adibah NOFIANA DIAN RAHAYU Noviar Afrizal Wahyuananto Nur Itsnaini Nurfajrin Dhuha Andani Nurhadi Bashit Nurhadi Bashit Nurhadi Bashit Nurul Huda Patriot Ginanjar Satriya Pinastika Nurandani Pitto Yuniar Maharsayanto Pratama Irfan Hidayat Prathanazal, Naufal Maziakiko Prya Adhi Surya Nugraha Putra, Muhammad Adisyah Putri Auliya Putri Mariasari Sukendar, Putri Mariasari Putri, Alifa Salsabilla Raditya Wahyu Utomo Ratih Kumala Dewi Restu Maheswara Ayyar Lamarolla Rina Emelyana Risa Bruri Utami Ryandana Adhiwuryan Bayuaji Sabri, L M Sabri, L.M. Sabri, LM Samuel Samuel Sari, Devi Nilam Sawitri Subiyanto Sawitri Suprayogi Selli Angelita Sitepu Seprila Putri Darlina Setiaji Nanang Handriyanto Sheehan Maladzi, Havi Shofiyatul Qoyimah, Shofiyatul Sinabutar, Julio Jeremia Sindi Rahma Erwanti Sitepu, Selli Angelita Siti Rahayuningsih Sri Purwatik Sutomo Kahar Sutomo Kahar Sutomo Kahar Sutomo Kahar Syafiri Krisna Murti Syarif Budhiman Theresia Niken Kurnianingsih Tika Murni Asih Tistariawan, Adji Chandra Titis Ismayanti Vauzul Rahmat Victor Andreas Tarigan Vira Febianti Wahyu Eko Saputro Wahyu Setianingsih Wenang Triwibowo, Wenang Wili Setiadi Wilma Amiruddin Wiryawan, Ainun Pujo Wisnu Wahyu Wijonarko Yenny Paras Dasuka Yoga Triardhana Yosevel Lyhardo Sidabutar Yudo Prasetyo Yugi Limantara