Development of a Three-Dimensional CFD Model and OpenCV Code by Comparing with Experimental Data for Spillway Model Studies

Varçin, Hakan; Üneş, Fatih; Gemici, Ercan; Zeleňáková, Martina

doi:10.3390/w15040756

Cited by 3 publications

(1 citation statement)

References 36 publications

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“…According to References [60,61], this study utilizes a feature extraction algorithm based on convolutional neural networks (CNNs) because they offer the following advantages:…”

Section: Feature Extraction Algorithmmentioning

confidence: 99%

Design and Control of an Ultra-Low-Cost Logistic Delivery Fixed-Wing UAV

Zhang,

Zhao,

Mao

et al. 2024

Applied Sciences

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In contemporary logistics, the deployment of fixed-wing unmanned aerial vehicles (UAVs) as a transportation platform is experiencing rapid advancements, garnering substantial application within numerous logistic operations with pronounced efficacies. There are notable impediments to the utilization of commercial logistic-oriented fixed-wing UAVs, including elevated procurement and maintenance costs, extensive maintenance intervals, and unsuitability for small-volume, low-altitude transport tasks. These factors collectively exacerbate the risk associated with enterprise procurement and elevate the cost–benefit ratio. This study introduces the design and fabrication of a cost-efficient UAV for logistic delivery purposes, constructed primarily from cost-effective wood materials. This UAV is engineered to ferry payloads of up to 1000 g across a predefined aerial route at an altitude of 40 m. Upon reaching the designated location, the UAV is programmed to initiate the identification of the drop zone, thereafter descending to facilitate the release of the cargo. To mitigate the impact force during the landing phase, the payload was encapsulated within a sponge-damping layer, thereby preserving the integrity of the transported items. The empirical findings from outdoor delivery trials underscore the UAV’s ability to precisely execute payload drops at the targeted locations, confirming its potential to fulfill the logistical requirements for the transportation and delivery of small-volume items in a cost-effective, low-altitude framework. This investigation contributes to the burgeoning discourse on leveraging ultra-low-cost UAVs in logistics, offering a feasible solution to the challenges of cost and efficiency in UAV-operated delivery systems.

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“…According to References [60,61], this study utilizes a feature extraction algorithm based on convolutional neural networks (CNNs) because they offer the following advantages:…”

Section: Feature Extraction Algorithmmentioning

confidence: 99%

Design and Control of an Ultra-Low-Cost Logistic Delivery Fixed-Wing UAV

Zhang,

Zhao,

Mao

et al. 2024

Applied Sciences

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Simulation of urban flooding using 3D computational fluid dynamics with turbulence model

Saleem,

Rashid,

Haider

et al. 2025

Results in Engineering

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Non-invasive measurement of wall shear stress in microfluidic chip for osteoblast cell culture using improved depth estimation of defocus particle tracking method

Aung,

Pothipan,

Aswakool

et al. 2024

Biomicrofluidics

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The development of a non-invasive method for measuring the internal fluid behavior and dynamics of microchannels in microfluidics poses critical challenges to biological research, such as understanding the impact of wall shear stress (WSS) in the growth of a bone-forming osteoblast. This study used the General Defocus Particle Tracking (GDPT) technique to develop a non-invasive method for quantifying the fluid velocity profile and calculated the WSS within a microfluidic chip. The GDPT estimates particle motion in a three-dimensional space by analyzing two-dimensional images and video captured using a single camera. However, without a lens to introduce aberration, GDPT is prone to error in estimating the displacement direction for out-of-focus particles, and without knowing the exact refractive indices, the scaling from estimated values to physical units is inaccurate. The proposed approach addresses both challenges by using theoretical knowledge on laminar flow and integrating results obtained from multiple analyses. The proposed approach was validated using computational fluid dynamics (CFD) simulations and experimental video of a microfluidic chip that can generate different WSS levels under steady-state flow conditions. By comparing the CFD and GDPT velocity profiles, it was found that the Mean Pearson Correlation Coefficient is 0.77 (max = 0.90) and the Mean Intraclass Correlation Coefficient is 0.66 (max = 0.82). The densitometry analysis of osteoblast cells cultured on the designed microfluidic chip for four days revealed that the cell proliferation rate correlates positively with the measured WSS values. The proposed analysis can be applied to quantify the laminar flow in microfluidic chip experiments without specialized equipment.

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Development of a Three-Dimensional CFD Model and OpenCV Code by Comparing with Experimental Data for Spillway Model Studies

Cited by 3 publications

References 36 publications

Design and Control of an Ultra-Low-Cost Logistic Delivery Fixed-Wing UAV

Design and Control of an Ultra-Low-Cost Logistic Delivery Fixed-Wing UAV

Simulation of urban flooding using 3D computational fluid dynamics with turbulence model

Non-invasive measurement of wall shear stress in microfluidic chip for osteoblast cell culture using improved depth estimation of defocus particle tracking method

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