[{"content":" Neptune Wave Flume — An in-house piston-type wave flume HOTLAB\u0026rsquo;s own piston-type wave flume used for dam-break, greenwater and coastal-structure impact experiments.\nSpecifications, dimensions, and image gallery to be added.\n","externalUrl":null,"permalink":"/en/resources/neptune-flume/","section":"Research Resources","summary":"","title":"Neptune Wave Flume","type":"resources"},{"content":" Technology Overview OilWATCH oil pollution detection technology integrates Long-Wave Infrared Polarimetric Imaging with deep learning recognition. By combining a UAV aerial platform, intelligent image analysis, and real-time data transmission, the system establishes an oil pollution monitoring capability for marine areas, harbors, and nearshore waters.\nThe system can support rapid inspection, pollution hotspot interpretation, and quantitative analysis of oil pollution extent, improving real-time monitoring and response capability for marine oil pollution incidents. It also helps address the limitations of satellite and radar remote sensing for small-scale oil slick detection, complex nearshore environments, and low signal-to-noise conditions, strengthening spatial resolution and detection performance for marine pollution monitoring.\nSystem Architecture and Applications The OilWATCH system architecture consists of a UAV platform, a long-wave infrared polarimetric imaging sensor module, a real-time data transmission system, a ground monitoring station, and a backend intelligent analysis platform. Through modular and scalable design, the system can be flexibly configured for harbor inspection, aquatic environmental monitoring, emergency pollution response, marine research surveys, and technology validation.\nIn addition to real-time image monitoring and automatic oil pollution recognition, the system can integrate geographic information systems, mission management platforms, and historical databases to provide comprehensive oil pollution monitoring and decision-support functions.\nOilWATCH system architecture and application scenarios. Dapeng Bay Flight and Telemetry Test To validate the operational capability of a UAV system equipped with a long-wave infrared polarimetric camera in real marine environments, flight validation and wireless data transmission tests were conducted at Dapeng Bay. The tests covered autonomous route planning and execution, flight stability validation, image data acquisition, real-time data return, and ground station monitoring.\nThrough field testing, the system\u0026rsquo;s operational stability, communication reliability, and mission execution efficiency in marine environments can be evaluated, while establishing standard operating procedures and a deployment basis for oil pollution inspection and monitoring missions.\nDay and Night Oil Detection Experiment OilWATCH provides daytime and nighttime oil pollution detection capability. Long-wave infrared polarimetric imaging can effectively enhance the contrast between oil films and the seawater background. Results show that the system can maintain stable oil pollution recognition capability during daytime, nighttime, and low-light conditions, demonstrating application potential for pollution incident response, nighttime inspection, and all-weather marine environmental monitoring.\nComparison of daytime and nighttime oil detection results. Open in Google Drive. If playback still fails, use the browser menu to open it externally. OilWATCH daytime oil detection demonstration. Open in Google Drive. If playback still fails, use the browser menu to open it externally. OilWATCH nighttime oil detection demonstration. ","externalUrl":null,"permalink":"/en/research/oilwatch/","section":"Research","summary":"","title":"OilWATCH Oil Pollution Detection Technology","type":"research"},{"content":" Focused Wave Generation Collaboration with Prof. Ting-Chieh Lin at the Department of Harbor and River Engineering, National Taiwan Ocean University (NTOU).\nMethodology and image gallery to be added.\n","externalUrl":null,"permalink":"/en/resources/focused-wave/","section":"Research Resources","summary":"","title":"Focused Wave Generation","type":"resources"},{"content":" Technology Overview MODISQ is an AI-based intelligent recognition and analysis platform developed for marine environmental monitoring and smart inspection applications. It integrates image data management, artificial intelligence inference, target recognition, spatial information display, and result analysis to provide intelligent interpretation capability for marine pollution monitoring, coastal structure inspection, vessel activity monitoring, and marine survey missions.\nThe platform supports multi-source image inputs, including UAV aerial imagery, fixed surveillance equipment, shipborne sensing systems, and other optical image sources. Through a standardized analysis workflow, it can rapidly generate monitoring outputs and effectively improve marine environmental monitoring efficiency and decision-support capability.\nAI Inference and Result Visualization The MODISQ platform uses deep learning and computer vision as its core technologies to establish a complete AI inference workflow, automatically performing target detection, classification, segmentation, and quantity statistics. The system converts recognition results into intuitive visual outputs, including target annotations, hotspot distribution maps, statistical charts, and geographic information display interfaces, helping users quickly understand monitoring-area conditions.\nThe platform also provides data management and result query functions, enabling research analysis, monitoring missions, and response operations to establish a consistent and traceable interpretation workflow while improving the utility and analysis efficiency of monitoring data.\nMODISQ backend AI inference platform. MODISQ detection result display. Real-Time Recognition Demonstration MODISQ can demonstrate real-time recognition results for oil pollution, vessels, and other maritime targets, and it supports integration with UAVs, edge AI computing devices, and wireless data transmission systems to enable on-site real-time analysis and data return.\nDuring mission execution, the system can complete target detection, position marking, and result display simultaneously, then transmit recognition outputs in real time to a ground monitoring station or backend platform so operators can quickly understand field conditions. Through real-time monitoring and intelligent analysis, the system can support marine pollution incident inspection, vessel activity monitoring, coastal facility inspection, and emergency response applications.\nOpen in Google Drive. If playback still fails, use the browser menu to open it externally. Real-time recognition of oil pollution and vessels. ","externalUrl":null,"permalink":"/en/research/modisq/","section":"Research","summary":"","title":"MODISQ Marine Intelligent Detection, Identification, and Quantitative Analysis Platform","type":"research"},{"content":" Technology Overview Atmospheric Motion Vector (AMV) retrieval technology uses cloud-motion features in sequential satellite imagery and combines Particle Image Velocimetry (PIV) concepts with image tracking techniques to estimate atmospheric flow-field motion vectors. By calculating cloud displacement across sequential images, the method obtains large-area and spatially continuous wind-field distributions that serve as an important basis for atmospheric dynamics analysis and cloud-drift wind product generation.\nThis technology can be applied to weather monitoring, typhoon analysis, severe convective system tracking, numerical weather prediction data validation, and atmospheric environmental research, improving large-scale atmospheric motion observation and analysis capability.\nTechnical Architecture The technical architecture covers satellite image acquisition, image preprocessing, cloud feature recognition, displacement tracking analysis, atmospheric motion vector retrieval, and result visualization. The system extracts cloud-motion information from sequential satellite imagery and uses correlation matching and vector calculation methods to estimate cloud-layer movement direction and speed.\nThe complete workflow establishes an analysis chain from raw satellite observation data to atmospheric motion vector outputs, supporting cloud-drift wind product generation and subsequent atmospheric dynamics analysis.\nCloud-Drift Wind Retrieval Results Cloud-drift wind retrieval results show cloud-motion tracking and vector-field distributions from sequential satellite imagery, visualizing atmospheric flow direction and speed characteristics across different regions. Through cloud-drift wind product analysis, users can effectively understand the development trends and spatial distribution characteristics of large-scale weather systems.\nThese results can be used not only for weather monitoring and forecasting operations, but also as important reference information for atmospheric circulation research, typhoon dynamics analysis, and extreme weather event monitoring.\nCloud-drift wind retrieval results from two sequential satellite-image demonstrations. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Validation Results Validation results present comparative analysis between atmospheric motion vector retrieval outputs and reference data, including wind speed, wind direction, and vector distribution assessment. Through statistical analysis and error evaluation, the stability, accuracy, and applicable range of the retrieval workflow can be examined.\nThe validation results show that this technology can effectively extract cloud-motion information and reconstruct atmospheric flow-field characteristics. It can serve as a reliable tool for cloud-drift wind product generation and atmospheric dynamics research, while providing a basis for subsequent algorithm optimization and application development.\nValidation results comparing retrieved atmospheric motion vectors with reference data. ","externalUrl":null,"permalink":"/en/research/amv-derivation/","section":"Research","summary":"","title":"Atmospheric Motion Vector Retrieval Technology","type":"research"},{"content":" Combined Bubble Image Velocimetry (BIV) and Particle Image Velocimetry (PIV) A hybrid velocimetry technique for simultaneously resolving aerated and single-phase flow regions in violent free-surface flows. Developed and applied extensively in HOTLAB\u0026rsquo;s greenwater and wave-impact experiments.\nImage and video gallery to be added.\n","externalUrl":null,"permalink":"/en/resources/combined-biv-piv/","section":"Research Resources","summary":"","title":"Combined BIV-PIV","type":"resources"},{"content":" Instruments \u0026amp; Sensors HOTLAB maintains a suite of hydrodynamic instrumentation for laboratory and field deployment.\nImaging \u0026amp; velocimetry High-speed cameras DSLR cameras Laser illumination systems for BIV / PIV Fiber optic reflectometers (FOR) Wave \u0026amp; free-surface measurement Ultrasonic surface gauges Capacitance wave probes Force \u0026amp; pressure Piezo-electric pressure transducers Piezo-resistive pressure transducers In-line load cells Motion \u0026amp; control Manual linear stages Electrical linear stages Programmable motion controllers Data acquisition \u0026amp; signal NI multifunction I/O devices Oscilloscopes Function generators Hydraulic facilities Neptune wave flume (in-house piston-type) Dam-break simulation flume Falling-impact simulation tank Close-circulating multifunction flume Field equipment Multi-rotor drones (UAS) Workshop \u0026amp; fabrication 3D printers Table drill machine Table cutter For collaborative use, calibration, or rental enquiries, please contact us.\n","externalUrl":null,"permalink":"/en/resources/instruments/","section":"Research Resources","summary":"","title":"Instruments \u0026 Sensors","type":"resources"},{"content":" Technology Overview UAV water quality sampling technology combines an unmanned aerial vehicle with an independently developed water sampling module to establish a sampling system with high mobility, high spatial resolution, and low contamination risk. The system can be applied in wetlands, estuaries, nearshore waters, and ship-based operating environments where conventional sampling is difficult, supporting surface water sample collection missions.\nCompared with traditional manual sampling, UAV sampling technology can effectively improve operational safety and sampling efficiency, reduce personnel exposure to complex environments, and minimize disturbance and contamination of monitored areas during sampling, providing more representative water quality monitoring data.\nSystem Architecture and Specifications The system architecture mainly includes a UAV platform, an autonomous sampling module, a mission control system, and field operation workflows. The sampling module can be rapidly deployed and replaced according to mission requirements, and it works with the flight control system to execute fixed-point hovering, automatic sampling, and return procedures.\nThe technical specifications cover vehicle configuration, sampling capacity, operating altitude, positioning accuracy, and mission execution workflow. Together, they present the system design architecture and key performance indicators as a basis for operational planning and application across different monitoring sites.\nUAV water quality sampling system architecture. UAV water quality sampling specifications. Field Validation Records To validate operational capability under different environmental conditions, this technology has completed multiple field tests at Qigu Wetland, Sizihwan, and offshore Linyuan. The tests covered shoreline sampling, wetland environmental sampling, shipboard takeoff and landing, and fixed-point offshore sampling to evaluate flight stability, sampling success rate, and field operation workflows.\nThe test results show that the system can perform sampling missions reliably across diverse aquatic environments. With advantages in rapid deployment, precise positioning, and safe operation, it can serve as an effective tool for marine environmental monitoring, water quality surveys, pollution tracking, and research sampling.\nOpen in Google Drive. If playback still fails, use the browser menu to open it externally. Water quality sampling field record at Qigu Wetland. Water quality sampling field record at Sizihwan. Shipboard takeoff and Linyuan offshore water quality sampling record. ","externalUrl":null,"permalink":"/en/research/uav-water-sampling/","section":"Research","summary":"","title":"UAV Water Quality Sampling Technology","type":"research"},{"content":" Technology Overview Ultra-nearshore underwater bathymetry mapping technology integrates image observation, flow-field analysis, and bathymetry inversion to establish a rapid mapping method for shallow nearshore areas. Through non-contact measurement, the method can obtain terrain information in areas where conventional survey vessels or underwater instruments are difficult to operate, providing efficient and spatially continuous underwater bathymetry data.\nThis technology can be applied to coastal terrain monitoring, erosion and deposition change analysis, coastal engineering assessment, wave propagation research, and environmental surveys, improving the ability and efficiency of bathymetric data acquisition in ultra-nearshore areas.\nTechnical Architecture The technical architecture covers the main processing workflow, including image data acquisition, velocity information extraction, hydrodynamic analysis, and bathymetry inversion. The system first uses optical imagery to observe sea-surface wave motion features, then applies image analysis to estimate surface velocity and wave information, and combines wave-current theory with inversion algorithms to estimate underwater terrain distribution.\nThe complete workflow establishes a data chain from observation data to bathymetric results, effectively supporting terrain mapping and long-term monitoring needs in ultra-nearshore areas.\nUltra-nearshore bathymetry mapping architecture. Bathymetry Inversion Results Bathymetry inversion results display nearshore depth distribution and terrain characteristics, clearly presenting underwater geomorphic information such as sandbars, scour channels, and terrain variations. In addition to serving as bathymetry mapping outputs, the results can provide foundational data for wave numerical simulation, coastal change analysis, and engineering planning.\nThrough periodic monitoring and result comparison, the method can further support understanding of nearshore terrain evolution trends and environmental change.\nBathymetry inversion result showing nearshore depth distribution. Image and Velocity Overlay The source image and velocity overlay results demonstrate the integrated use of image observation data and flow-field analysis outputs. By presenting velocity vectors, flow-field distribution, and field imagery together, the results help examine nearshore wave-current dynamics and their relationship with bathymetric distribution.\nThese outputs can serve as a quality check for bathymetry inversion and also help explain nearshore wave-current mechanisms, improving the reliability and application value of inversion results.\nOpen in Google Drive. If playback still fails, use the browser menu to open it externally. Source imagery and velocity overlay result. Bathymetry inversion result used with the image and velocity overlay. ","externalUrl":null,"permalink":"/en/research/nearshore-bathymetry-mapping/","section":"Research","summary":"","title":"Ultra-Nearshore Underwater Bathymetry Mapping Technology","type":"research"},{"content":" Water entry of a flat plate on pure and aerated water Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Plunging breaking wave impacts on a deck structure Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Typical types of greenwater events on a rectangular structure Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Experiment modeling of greenwater in a deep-water wave basin Plunging breaking wave impacts on a unconstrained TLP Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Tsunami bore impacts on a box structure at different angles Open in Google Drive. If playback still fails, use the browser menu to open it externally. ","externalUrl":null,"permalink":"/en/research/extreme-wave-impacts/","section":"Research","summary":"","title":"Extreme Wave Impacts on Marine Structure","type":"research"},{"content":" Wave Generation System and Focused Wave Generation Technology Wave generation system: The Neptune Wave Flume is a wave testing facility with high-precision control capability. It supports the generation of regular waves, irregular waves, focused waves, and other wave conditions. Through wave-group focusing technology, the system controls wave components of different frequencies to converge at a specified location and time, reproducing the instantaneous high-energy impact characteristics of extreme wave events.\nFocused wave generation technology: This technology provides high repeatability, high stability, and strong controllability. It can precisely control breaking-wave location, breaker type, and impact intensity, reproducing extreme waves and breaking-wave events observed in real marine environments. The technology can be applied to coastal engineering, hydraulic structures, offshore facilities, and wave impact loading research, providing a high-quality scaled physical model testing environment.\nThe system supports related hydrodynamic experiments and numerical model validation, providing experimental baseline data for marine engineering design and disaster prevention assessment.\nNeptune wave flume. Focused wave generation. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Open in Google Drive. If playback still fails, use the browser menu to open it externally. Image Velocimetry Technology Image velocimetry technology uses high-speed imagery and digital image processing methods to perform non-contact measurement of flow-field velocity and flow structures. The technology covers Particle Image Velocimetry (PIV) for single-phase flow-field analysis and Bubble Image Velocimetry (BIV) for bubbly, multiphase, and breaking-wave flow-field analysis.\nThe system integrates PIV and BIV analysis algorithms to automatically identify different tracer features in the flow field, calculate velocity vectors, and reconstruct flow fields. In addition to obtaining instantaneous velocity distributions, it can further analyze vortex structures, turbulence characteristics, flow-field evolution, and wave-current interaction, providing important hydrodynamic information.\nThe technology can be applied to wave flume experiments, breaking-wave flow-field research, multiphase flow analysis, river and marine flow measurement, and environmental fluid mechanics research, providing high-spatiotemporal-resolution flow-field measurement results.\npyCCV Image Velocimetry Software pyCCV (Python Cross-Correlation Velocimetry) is an independently developed image velocimetry software platform built on Fast Fourier Transform (FFT)-based cross-correlation analysis, providing an efficient and extensible flow-field measurement platform.\nThe software supports PIV, BIV, and related image tracking analysis functions, including image preprocessing, cross-correlation calculation, vector validation, flow-field post-processing, and result visualization. Through a modular architecture, analysis functions and data processing workflows can be extended according to different research needs.\npyCCV is developed on the Python platform and supports multicore CPU parallel computing, effectively improving processing efficiency for large image datasets. The system combines usability, flexibility, and high performance, making it suitable for academic research, engineering experiments, and flow-field measurement applications.\n","externalUrl":null,"permalink":"/en/research/fluid-mechanics-measurement/","section":"Research","summary":"","title":"Fluid Mechanics Measurement Technology","type":"research"},{"content":"The Hydrodynamics \u0026amp; Ocean Technology Laboratory (HOTLAB) sits within the Department of Marine Environment and Engineering at National Sun Yat-sen University. We investigate the physics of violent water — breaking waves, greenwater, dam-break impacts, oil spreading — and develop unmanned and AI-driven technologies to measure and monitor the water environment.\nPrincipal Investigator — Dr. Wei-Liang Chuang, Associate Professor Team — Staff, graduate students, and alumni ","externalUrl":null,"permalink":"/en/about/","section":"About HOTLAB","summary":"","title":"About HOTLAB","type":"about"},{"content":"","externalUrl":null,"permalink":"/en/categories/","section":"categories","summary":"","title":"categories","type":"categories"},{"content":" Primary contacts HOTLAB office — HOTLab.nsysu@gmail.com Dr. Wei-Liang Chuang (PI) — wlchuang@mail.nsysu.edu.tw Phone — +886-7-5252-000 ext. 5184 Address No.70 Lien-hai Rd., Gushan Dist., Kaohsiung 80424, Taiwan Department of Marine Environment and Engineering, National Sun Yat-sen University\nGetting here By public transport — Take Kaohsiung MRT to Sizihwan Station (Orange Line, transfer at Formosa Boulevard). NSYSU campus is a short walk from the station.\nBy car / more directions — NSYSU Campus Map\n","externalUrl":null,"permalink":"/en/contact/","section":"Contact","summary":"","title":"Contact","type":"contact"},{"content":"From Lab to Field — Advancing Water Environment Observation and Monitoring, Delivering Engineering Solutions\nHOTLAB Highlights OilWATCH Oil Pollution Detection Technology MODISQ Marine Intelligent Detection, Identification, and Quantitative Analysis Platform UAV Water Quality Sampling Technology Current Research Topics ","externalUrl":null,"permalink":"/en/","section":"HOTLAB","summary":"","title":"HOTLAB","type":"page"},{"content":" Lab Staff Po-Hsien KUO\nEngineer Graduate Students Sheng-Mei LIN\nPhD Student / Research Assistant Tsung-Han CHENG\nMaster Student / Research Assistant Yan-Yi KUO\nMaster Student Former Students Year Student Master Thesis Current Affiliation 2025 Chiu, Ting-Hsiang Development of a coastal water sampling system integrated with an unmanned aircraft system Taiwan Semiconductor Manufacturing Company Limited 2024 Pan, Xing-Yu Measurement and analysis of the velocity field in typical greenwater events Pan-Cheng Engineering Consultants Co., Ltd. 2023 Chen, Sheng-Yuan Experimental investigation of plunging dam break wave impact on square prism Taiwan Marine Survey Technology Co., Ltd. ","externalUrl":null,"permalink":"/en/members/","section":"Members","summary":"","title":"Members","type":"members"},{"content":"","externalUrl":null,"permalink":"/en/news/","section":"News","summary":"","title":"News","type":"news"},{"content":" Wei-Liang CHUANG, PhD Associate Professor \u0026 Distinguished Young Scholar\nDepartment of Marine Environment and Engineering\nNational Sun Yat-sen University\nEducation 2012–2017 PhD, Dept of Civil \u0026amp; Environmental Engineering, Texas A\u0026amp;M University 2008–2010 MSc, Dept of Hydraulic \u0026amp; Ocean Engineering, National Cheng Kung University 2004–2008 BSc, Dept of Hydraulic \u0026amp; Ocean Engineering, National Cheng Kung University Academic Experience 2024/08 – Present Associate Professor, Department of Marine Environment and Engineering, National Sun Yat-sen University 2019/08 – 2024/07 Assistant Professor, Department of Marine Environment and Engineering, National Sun Yat-sen University 2018/03 – 2019/07 Postdoctoral Researcher, Department of Civil and Environmental Engineering, Texas A\u0026amp;M University 2017/09 – 2017/12 Teaching Assistant, Department of Civil and Environmental Engineering, Texas A\u0026amp;M University 2017/01 – 2017/05 Teaching Assistant, Department of Ocean Engineering, Texas A\u0026amp;M University 2012/08 – 2017/12 Research Assistant, Department of Civil and Environmental Engineering, Texas A\u0026amp;M University 2011/08 – 2012/07 Research Assistant, Tainan Hydraulics Laboratory, National Cheng Kung University Honors 2024 Distinguished Young Scholar, NSYSU 2023 Industry–Academia Incentive (Emerging Category), NSYSU 2022 Outstanding Team Teacher, NSYSU — for intramural project \u0026ldquo;Drift-control technology for waterline devices in intertidal zones\u0026rdquo; 2020 Coastal Engineering Journal Reviewer Award 2020–2025 Einstein Program for Young Scholars, National Science and Technology Council 2019–2021 New Faculty Award, NSYSU Services 2023–Present Supervisor, Taiwan Marine Pollution Prevention Association 2021–2023 Consultant, Kaohsiung Marine Technology Zone 2021–2023 Topic Editor, Water Journal Reviewer Archives of Mechanics Coastal Engineering Journal Experimental Thermal and Fluid Science Flow Measurement and Instrumentation Fluids International Journal of Naval Architecture and Ocean Engineering Journal of Engineering Mechanics Journal of Earthquake and Tsunami Journal of the Brazilian Society of Mechanical Sciences and Engineering Ocean Engineering Physics of Fluids Remote Sensing The European Physical Journal Plus Water Teaching Fall Semester Code Course MAEV402 Numerical Methods MAEV410 Computer-Aided Drafting MAEV420 Oceanographic Cruise Practice MAEV501 Water Resources Engineering OWP502 Seminar in Offshore Wind Power I Seminar in Marine Environment I Spring Semester Code Course MAEV320 Hydrology MAEV221 Fluid Mechanics Laboratory MAEV361 Probability and Statistics MAEV511 Numerical Methods MAEV463 Numerical Analysis MRSC115 Applied Marine Sciences MAEV502 Seminar in Marine Environment II ","externalUrl":null,"permalink":"/en/about-pi/","section":"Principal Investigator","summary":"","title":"Principal Investigator","type":"about-pi"},{"content":" Refereed Journal Papers Hsieh, M.-C., Chuang, W.-L., Lin, T.-C. (2026). Greenwater due to plunging breaking wave impingement on a deck structure. Part 2: Impact pressure and air fraction. Ocean Engineering, 364, Part 3, 127102. Chuang, W.-L. (2026). Laboratory observation of impact pressure and air fraction in three common types of greenwater impacts. Physics of Fluids, 38(4), 04128. Lin, S.-M. \u0026amp; Chuang, W.-L. (2026). Experimental investigation of impact pressures and air entrainment effects during flat plate water entry at varying impact speeds and aeration levels. Ocean Engineering, 348, 124027. Chuang, W.-L. \u0026amp; Chen S.-Y. (2025). Laboratory observation of impact pressure, fluid velocity, and air fraction during dam-break impacts on a square prism. Physics of Fluids, 37(7), 077129. Wang, S. \u0026amp; Chuang, W.-L. (2025). Dynamic analysis of breaking wave impact on a floating offshore wind turbine via smoothed particle hydrodynamics. Marine Structures, 100, 103731. Chuang, W.-L. (2024). On the fluid kinematics of common types of greenwater events: An experimental study. Applied Ocean Research, 153, 104235. Chiu, M.-C., Chuang, L. Z.-H., Chuang, W.-L., Wu, L.-C., Huang, C.-J., \u0026amp; Zhang, Y. J. (2023). Utilizing ocean hydrodynamic modeling to enhance information management for emergency response to oil spill incidents in Taiwan waters. Journal of Marine Science and Engineering, 11(11), 2094. Chuang, W.-L., Lin, T.-C., \u0026amp; Wang, Y.-J. (2023). Greenwater due to plunging breaking wave impingement on a deck structure. Part 1: Experimental investigation on fluid kinematics. Ocean Engineering, 287, Part 2, 115859. Miller, K., Chuang, W.-L., Kim, K., Chang, K.-A., \u0026amp; Chellam, S. (2023). Simultaneous in situ characterization of turbulent flocculation and reactor mixing using image analysis and particle image velocimetry in unison. ACS ES\u0026amp;T Engineering, 3(2), 295-305. Chuang, W.-L. (2022). Experimental investigation on fluid kinematics and impact pressure of flat plate impacts on pure and aerated water. Ocean Engineering, 266, Part 3, 112837. Chuang, W.-L., \u0026amp; Lin, S.-M. (2022). A PIV based algorithm for determining multiple velocity fields from crossflows in single field of view. Water, 14(12), 1877. Chuang, W.-L., Chang, K.-A., Kaihatu, J., Cienfuegos, R., \u0026amp; Mokrani, C. (2020). Experimental study of force, pressure, and fluid velocity on a simplified coastal building under tsunami bore impact. Natural Hazards, 103, 1093-1120. Do, J., Chuang, W.-L., \u0026amp; Chang, K.-A. (2020). Oil droplet sizing and velocity determination using fiber optic reflectometer. Measurement Science and Technology, 31, 065301. Hsu, W.-Y., Huang, Z.-C., Na, B., Chang, K.-A., Chuang, W.-L., \u0026amp; Yang, R.-Y. (2019). Laboratory observation of turbulence and wave shear stresses under large scale breaking waves over a mild slope. Journal of Geophysical Research: Oceans, 124, 7486-7512. Sun, S.-H., Chuang, W.-L., Chang, K.-A., Kim, J.Y., Kaihatu, J., Huff, T., \u0026amp; Feagin, R. (2019). Imaging based nearshore bathymetry measurement using an unmanned aerial system. Journal of Waterway, Port, Coastal and Ocean Engineering, 145(2), 04018044. Chuang, W.-L., Chou, C.-B., Chang, K.-A., Chang, Y.-C., \u0026amp; Chin, H.-L. (2019). Atmospheric motion vectors derived from an infrared window channel of a geostationary satellite using particle image velocimetry. Journal of Applied Meteorology and Climatology, 58, 199-211. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2018). Kinematics and dynamics of green water on a fixed platform in a large wave basin in focusing wave and random wave conditions. Experiments in Fluids, 59, 100. Na, B., Chang, K.-A., Huang, Z.-C., Hsu, W.-Y., Chuang, W.-L., \u0026amp; Chen, Y.Y. (2018). Large-scale laboratory observation of fluid properties in plunging breaking waves. Coastal Engineering, 138, 66-79. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2017). Impact pressure and void fraction due to plunging breaking wave impact on a 2D TLP structure. Experiments in Fluids, 58(6), 68. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2015). Green water velocity due to breaking wave impingement on a tension leg platform. Experiments in Fluids, 56(7), 139. Chuang, W.-L., Hsiao, S.-C., \u0026amp; Hwang, K.-S. (2014). Numerical and experimental study of pump sump flows. Mathematical Problems in Engineering, 735416. Chuang, W.-L., \u0026amp; Hsiao, S.-C. (2011). Three-dimensional numerical simulation of intake model with cross flow. Journal of Hydrodynamics, 23(3), 314-324. Conference Proceedings Huang, T.-C., Lin, T.-C., Hsu, T.-W., Chuang, W.-L., Hsieh, C.-M., \u0026amp; Yang, C.-W. (2026). On Class II Bragg Reflection Induced by the Interaction Between Bichromatic Waves and Semi-Sinusoidal Ripple Beds. 45th International Conference on Ocean, Offshore and Arctic Engineering, Tokyo, Japan. Lin, S.-M., Chuang, W.-L., \u0026amp; Lin, T.-C. (2026). Experimental Modeling of Impact Pressures Due to Plate Water Entry at Varying Drop Heights and Aeration Levels. 45th International Conference on Ocean, Offshore and Arctic Engineering, Tokyo, Japan. Lin, T.-C., Chuang, W.-L., Wang, Y.-J., \u0026amp; Hsu, T.-W. (2024). Numerical modeling of fluid kinematics due to plunging breaking wave impingement on a deck structure. 43rd International Conference on Ocean, Offshore and Arctic Engineering, Singapore. Chuang, W.-L., Pan, X.-Y., \u0026amp; Lin, T.-C. (2023). Experimental modeling of typical types of green water events. 42nd International Conference on Ocean, Offshore and Arctic Engineering, Melbourne, Australia. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2019). Review of experimental modeling of green water in laboratories. 29th International Ocean and Polar Engineering Conference, Honolulu, Hawaii, USA. Chuang, W.-L., Chang, K.-A., Kaihatu, J., Cienfuegos, R., \u0026amp; Mokrani, C. (2018). Experimental modeling of tsunami bore impingement on a simplified coastal building. 37th International Conference on Coastal Engineering, Baltimore, Maryland. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2018). Green water flow on a fixed model structure in a large wave basin under random waves. 37th International Conference on Ocean, Offshore and Arctic Engineering, Madrid, Spain. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2017). Green water on a fixed model in a large wave basin: flow velocity, void fraction, and impact pressure distributions. 36th International Conference on Ocean, Offshore and Arctic Engineering, Trondheim, Norway. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2016). Impact pressure, void fraction, and green water velocity due to plunging breaking wave impingement on a 2D tension-leg structure. 35th International Conference on Ocean, Offshore and Arctic Engineering, Busan, South Korea. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2015). Application of dam-break flow solution to predict the green water velocity on a 2D tension-leg platform. 25th International Ocean and Polar Engineering Conference, Kona, Big Island, Hawaii, USA. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2015). Void fraction and impact pressure caused by breaking wave impingement on a 2D tension-leg structure. 25th International Ocean and Polar Engineering Conference, Kona, Big Island, Hawaii, USA. Chuang, W.-L., Chang, K.-A., \u0026amp; Mercier, R. (2014). Experimental modeling of breaking wave impingement on a tension-leg platform. 24th International Ocean and Polar Engineering Conference, Busan, South Korea. Chuang, W.-L., Hsiao, S.-C., Wu, H.-R., \u0026amp; Wu, T.-R. (2010). Three-dimensional numerical simulation on intake model with cross flow. 17th National Computational Fluid Dynamics Conference, Jhongli, Taiwan. Chuang, W.-L., Hsiao, S.-C., Hwang, K.-S., \u0026amp; Lin, C.-P. (2009). Numerical and experimental study of pump sump flows. 33rd Conference on Theoretical and Applied Mechanics, Miaoli, Taiwan. ","externalUrl":null,"permalink":"/en/publications/","section":"Publications","summary":"","title":"Publications","type":"publications"},{"content":"","externalUrl":null,"permalink":"/pyxis/","section":"HOTLAB","summary":"","title":"Pyxis LWIR 偵測範圍估算工具","type":"pyxis"},{"content":" OilWATCH Oil Pollution Detection Technology MODISQ Marine Intelligent Detection, Identification, and Quantitative Analysis Platform UAV Water Quality Sampling Technology Ultra-Nearshore Underwater Bathymetry Mapping Technology Extreme Wave Impacts on Marine Structures Atmospheric Motion Vector Retrieval Technology Fluid Mechanics Measurement Technology ","externalUrl":null,"permalink":"/en/research/","section":"Research","summary":"","title":"Research","type":"research"},{"content":" Experimental Platforms Neptune Wave Flume — in-house piston-type wave flume Focused Wave Generation — collaboration with NTOU Combined BIV-PIV — hybrid bubble and particle velocimetry Instrument \u0026amp; Equipment List — velocimetry, pressure, and imaging instruments Aerial Platforms Multi-rotor UAVs — for coastal and marine environmental monitoring and water sampling Mission payloads — optical cameras, multispectral imaging, water sampling mechanisms Computing Resources GPU workstations / servers — for AI image recognition, deep-learning training and inference CPU compute cluster — for CFD and particle-tracking simulations Software \u0026amp; Tools Fluid simulation — OpenFOAM, ANSYS Fluent Image and measurement analysis — MATLAB, DaVis, in-house BIV / PIV tools AI and data processing — PyTorch, TensorFlow, scientific Python stack For collaboration or resource-use enquiries: wlchuang@mail.nsysu.edu.tw\n","externalUrl":null,"permalink":"/en/resources/","section":"Research Resources","summary":"","title":"Research Resources","type":"resources"},{"content":"","externalUrl":null,"permalink":"/en/tags/","section":"tags","summary":"","title":"tags","type":"tags"}]