Multi-rotor wake propagation and flow development modeling: A review

Many years after construction, a number of existing old tunnels and underground structures are deteriorating with time as evidenced by cracks, large deformations, water leakage and so forth, which usually require regular site inspections to record their structural deterioration by taking high-pixel, high-overlap images along miles of a tunnel network. For complex underground structures (e.g., long tunnels and large caves), unmanned aerial vehicles (UAVs) may be adaptive in acquiring images at multiple heights and angles with low operational costs. So far, UAV underground structural health monitoring has become mature for open-air surveying with rapid developments in robotic software and hardware. However, the UAV image acquisition for underground working conditions still faces a number of key challenges. This paper aims to provide an overview of UAV navigation techniques in confined dark spaces for geotechnical engineers, geologists, drone developers and other interdisciplinary researchers & professionals in the structural health monitoring field. It specifies the challenges for UAV application in underground space, mainly including lack of Global Navigation Satellite System (GNSS) signals, poor lighting conditions, weak features and obstacle avoidance and then followed by strategic solutions. For example, in light of poor GNSS signals, the fusion of multi-sensors (e.g., laser imaging, detection and ranging (LiDAR) and multi-cameras) can enhance localization accuracy in low-luminance underground conditions. To address obstacle avoidance, computer vision (CV)-based navigation algorithms (e.g., deep reinforced learning [DRL]) enable effective navigation in complex 3D spaces, but their adaptability is limited by arithmetic power and pre-training needs. The review of relevant previous studies concludes that further development for UAVs in underground space inspection may focus on operation in large-scale geometric inspection environments, obstacle avoidance, features and semantic recognition. 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/gj.4763

Unmanned aerial vehicle navigation in underground structure inspection: A review

The mining industry has recently shown increased interest in drones for routine activities in underground and surface mines. Designing a drone for coal mines is extremely complicated since the Mine Safety and Health Administration (MSHA) has tight guidelines for any equipment that can be used in underground coal mines. Due to these criteria, designing a drone for underground coal mining is exceedingly difficult. This paper explores the challenges of creating an intrinsically safe drone propulsion system. To address the challenges of designing an intrinsically safe drone’s propulsion system for an underground coal mine, this work aims to investigate the potential approaches to enhance efficiency and mitigate the heat. The study begins with the drone’s sizing approach before moving on to the experimental setup that is utilized to test the drone’s propulsion system. Finally, answers to numerous issues arising during the inquiry are offered, and these solutions are empirically explored.

/pdf/intrinsically-safe-drone-propulsion-system-for-underground-30zc74nf.pdf

Intrinsically Safe Drone Propulsion System for Underground Coal Mining Applications: Computational and Experimental Studies

This paper presents the design and manufacturing process of an innovative quadcopter drone structure prototype with two approaches to solving two barriers related to quadcopter drone systems: design, and accessibility. The first barrier is the need for a methodology to optimize conventional drone structural design that improves efficiency and flight time capacity or endurance. The second barrier is the lack of access to aerospace technology in underdeveloped countries. It is causing a significant impact on technological, educational, scientific, and industrial development that affects the countries' capacity to confront real-world problems and people's life quality. Therefore, two approaches have been used to solve the issues mentioned above by designing and manufacturing an innovative modular quadcopter structure prototype that meets all the required mechanical needs as lightweight and strength to improve efficiency. To achieve this first approach, the authors conducted topological optimization with two purposes: weight reduction and high energy efficiency thanks to the weight-to-energy consumption ratio considering aerodynamic performance and manufacturability. Furthermore, the generative design process allowed topology optimization as the starting analysis in the first iteration to be re-optimized in terms of several variables like stiffness maximization, mass minimization, von misses stress, and manufacturing materials and methods using Artificial Intelligence and Machine Learning to generate high-performing outcomes. As a result, this research provides a design and manufacturing method to empower new educational and industrial programs in the aerospace field in underdeveloped countries, encouraging a significant change in the country's quality of life with aerospace technology, education, and research and development. 

Topological Optimization, Generative Design and Validation of Drone Structures

Design an Intrinsically Safe Drone Propulsion System for Underground Mining: Thermal Aspects

Design and Optimization of an Encased Drone for Underground Mining Applications

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Design and Optimization of an Encased Drone for Underground Mining Applications