World Academy of Science, Engineering and Technology

Authors: Trudon Kabangu Mpinga, Ruth Mutala, Shaloom Mbambu, Yvette Kalubi Kashama, Kabeya Mukeba Yakasham

Abstract:

A mathematical model is developed to describe the contact dynamics between the landing gear wheels of an aircraft and a wet pavement during landing. The model is based on nonlinear partial differential equations, using the Yakam Matrix to account for the interaction between solid, liquid, and solid phases. This framework incorporates the influence of environmental factors, particularly water or rain on the runway, on braking performance and aircraft stability. Given the absence of exact analytical solutions, our approach enhances the understanding of key physical phenomena, including Coulomb friction forces, hydrodynamic effects, and the deformation of the pavement under the aircraft's load. Additionally, the dynamics of aquaplaning are simulated numerically to estimate the braking performance limits on wet surfaces, thereby contributing to strategies aimed at minimizing risk during landing on wet runways.

Keywords: aircraft, modeling, simulation, yakam matrix, contact, wet runway

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Authors: Bhaargav Gupta P., Vignesh N., Nithish Kumar R., Rahul J., Nivetha Ruvah D.

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Delivering essential medical supplies to rural and underserved areas is challenging due to infrastructure limitations and logistical barriers, often resulting in inefficiencies and delays. Traditional delivery methods are hindered by poor road networks, long distances, and difficult terrains, compromising timely access to vital resources, especially in emergencies. This paper introduces an autonomous drone system engineered to optimize last-mile delivery. By utilizing advanced navigation and object-detection algorithms, such as region-based convolutional neural networks (R-CNN), our drones efficiently avoid obstacles, identify safe landing zones, and adapt dynamically to varying environments. Equipped with high-precision GPS and autonomous capabilities, the drones effectively navigate complex, remote areas with minimal dependence on established infrastructure. The system includes a dedicated mobile application for secure order placement and real-time tracking, and a secure payload box with OTP verification ensures tamper-resistant delivery to authorized recipients. This project demonstrates the potential of automated drone technology in healthcare logistics, offering a scalable and eco-friendly approach to enhance accessibility and service delivery in underserved regions. By addressing logistical gaps through advanced automation, this system represents a significant advancement toward sustainable, accessible healthcare in remote areas.

Keywords: region-based convolutional neural network, one time password, global positioning system, autonomous drones, healthcare logistics

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Authors: Mars Burke, Alvin Gatto

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Rotary-wing aircraft serve as indispensable components in the advancement of aviation, valued for their ability to operate in diverse and challenging environments without the need for conventional runways. This versatility makes them ideal for applications like environmental conservation, precision agriculture, emergency medical support, and rapid-response operations in rugged terrains. However, although highly maneuverable, rotary-wing platforms generally have lower aerodynamic efficiency than fixed-wing aircraft. This study takes the view of improving aerodynamic performance by examining a 1/7th scale rotor blade model with a NACA0012 airfoil using CROTOR software. The analysis focuses on optimal spanwise locations for separating morphing and fixed blade sections at 85%, 90%, and 95% of the blade radius (r/R) with up to +20 degrees of twist incorporated to the design.. Key performance metrics assessed include lift coefficient (CL), drag coefficient (CD), lift-to-drag ratio (CL / CD), Mach number, power, thrust coefficient, and Figure of Merit (FOM). Results indicate that the 0.90 r/R position is optimal for dividing the morphing and fixed sections, achieving a significant improvement of over 7% in both lift-to-drag ratio and FOM. These findings underscoring the substantial impact on overall performance of the rotor system and rotational aerodynamics that geometric modifications through the inclusion of a morphing capability can ultimately realise.

Keywords: rotary morphing, rotational aerodynamics, rotorcraft morphing, rotor blade, twist morphing

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Authors: Piotr Żabicki, Paweł Skutta

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The project of a glider with an electric motor charged by solar power is an step toward the future of Polish gliding. Due to the popularity of the SZD-50-3 glider and its type of usage, the project was developed based on this model. By placing an auxiliary engine in the glider, the pilot is guaranteed a safe return to the airport. Since it is a training glider, and routes are mainly flown by student pilots and instructors, the guarantee of returning to the airport allows flights in more challenging thermal conditions, which contributes to better pilot training. In case of worsening weather, the pilot has a reliable return option, which prevents time loss due to field landings and saves money by avoiding delays in training. The glider uses the NOVA 15 LW engine, a solar installation, and technical modifications to reduce the glider's weight. This includes the Misztal spar solution, previously used in the PZL 19 aircraft. Additionally, the use of lighter coverings and materials that handle loads from pulling, straining, and sharing improves the aerodynamic performance of the glider, enhancing its overall efficiency. Every component added to the glider's construction (battery, engine, etc.) has been placed to avoid shifting loads along the axis, thus preventing unintended spins and flat spins. Safety concerns were also addressed. In the event of a battery or engine fire, the pilot's cabin is designed as a detachable part of the structure and is made of composites covered with non-flammable resin. The batteries are also enclosed in separate boxes located in the former "luggage" compartment. Access to the installation connecting the engine, panel, and battery is convenient due to the detachable cabin from the structure and the fact that the entire installation runs under the structure. The batteries also have easy access due to the current closed hatch. Cooling for the battery is provided this way.

Keywords: engineering, girder, glider, solar, spar

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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Authors: Vishal Shetty, Pranjal Khasnis, Saptarshi Mandal

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This work explores the design and fabrication of a fundamental pulse detonation engine (PDE) prototype on the basis of pressure and temperature pulse obtained from numerical simulation of the same. PDE is an advanced propulsion system that utilizes detonation waves for thrust generation. PDEs use a fuel-air mixture ignited to create a supersonic detonation wave, resulting in rapid energy release, high pressures, and high temperatures. The operational cycle includes fuel injection, ignition, detonation, exhaust of combustion products, and purging of the chamber for the next cycle. This work presents details of the core operating principles of a PDE, highlighting its potential advantages over traditional jet engines that rely on continuous combustion. The design focuses on a straightforward, valve-controlled system for fuel and oxidizer injection into a detonation tube. The detonation was initiated using an electronically controlled spark plug or similar high-energy ignition source. Following the detonation, a purge valve was employed to expel the combusted gases and prepare the tube for the next cycle. Key considerations for the design include material selection for the detonation tube to withstand the high temperatures and pressures generated during detonation. Fabrication techniques prioritized readily available machining methods to create a functional prototype. This work detailed the testing procedures for verifying the functionality of the PDE prototype. Emphasis was given to the measurement of thrust generation and capturing of pressure data within the detonation tube. The numerical analysis presents performance evaluation and potential areas for future design optimization.

Keywords: pulse detonation engine, ignition, detonation, combustion

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Authors: Hrishit Mitra, Saptarshi Mandal

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The study of aerodynamics for Formula 1 cars is very crucial in determining their performance. In the current F1 industry, when each engine manufacturer exhibits a torque and peak speed that differ by less than 5%, the emphasis on maximizing performance is dependent heavily on the utilization of aerodynamics. This work examines the aerodynamic characteristics of an F1 car by utilizing computational fluid dynamics in order to substantiate the hypothesis that an F1 car can go upside down in a tunnel without any external assistance, only due to the downforce it produces. In addition to this, this study also suggests the implementation of a 'flexi-wing' front in F1 cars to optimize downforce and reduce drag. Furthermore, this paper provides a concise overview of the historical development of aerodynamics in F1, with a specific emphasis on the progression of aerodynamics and the impact of downforce on the dynamics of vehicles. Next, an examination of wings has been provided, comparing the performance of the suggested wing at high speeds and low speeds. Three simulations have been conducted: one to test the complete aerodynamics and validate the hypothesis discussed above, and two specifically focused on the flexi wing, one at high speed and one at low speed. The collected results have been examined to analyze the performance of the front flexi wing. Performance analysis was conducted from the measurement of downforce and drag coefficient, as well as the pressure and velocity distributions.

Keywords: high speed flexi wing, low speed flexi wing, F1 car aerodynamics, F1 car drag reduction

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Authors: Suhani Srivastava

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This research delves into the classification of orbital debris through machine learning (ML): it will categorize the intensity of the threat orbital debris poses through multiple ML models to gain an insight into effectively estimating the danger specific orbital debris can pose to future space missions. As the space industry expands, orbital debris becomes a growing concern in Low Earth Orbit (LEO) because it can potentially obfuscate space missions due to the increased orbital debris pollution. Moreover, detecting orbital debris and identifying its characteristics has become a major concern in Space Situational Awareness (SSA), and prior methods of solely utilizing physics can become inconvenient in the face of the growing issue. Thus, this research focuses on approaching orbital debris concerns through machine learning, an efficient and more convenient alternative, in detecting the potential threat certain orbital debris pose. Our findings found that the Logistic regression machine worked the best with a 98% accuracy and this research has provided insight into the accuracies of specific machine learning models when classifying orbital debris. Our work would help provide space shuttle manufacturers with guidelines about mitigating risks, and it would help in providing Aerospace Engineers facilities to identify the kinds of protection that should be incorporated into objects traveling in the LEO through the predictions our models provide.

Keywords: aerospace, orbital debris, machine learning, space, space situational awareness, nasa

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Authors: Pratyush Agnihotri

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This paper presents a comprehensive overview of the conceptual design process for a fixed-wing vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV). Fixed-wing VTOL UAVs combine the advantages of rotary-wing aircraft, such as vertical take-off and landing capabilities, with the efficiency and speed of fixed-wing flight. The primary objective of this study is to explore the aerodynamic design principles that optimize performance parameters, including range, endurance, and stability while maintaining the VTOL capability. The design process involves selecting appropriate airfoils, optimizing wing configurations, and integrating propulsion systems suitable for both hovering and forward flight. Analytical methods are employed to evaluate aerodynamic performance, with a focus on lift-to-drag ratio, power requirements, and control strategies. The results highlight the challenges and trade-offs inherent in designing such hybrid aircraft, particularly in balancing the conflicting requirements of VTOL and fixed-wing flight. This study contributes to the development of efficient, versatile UAVs capable of operating in diverse environments.

Keywords: fixed wing, hybrid, VTOL, UAV

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Authors: Thien Bach Nguyen, Nhu-Van Nguyen, Phi-Minh Nguyen, Minh Hien Dao

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The external store safe separation evaluation process implementing CFD and MIL-HDBK-1763 is proposed to support the evaluation and compliance of the external store safe separation with the extensive using CFD and the criteria from MIL-HDBK-1763. The criteria of safe separation are researched and investigated for the various standards and handbooks such as MIL-HDBK-1763, MIL-HDBK-244A, AGARD-AG-202 and AGARD-AG-300 to acquire the appropriate and tailored values and limits for the typical applications of external carriages and aircraft fighters. The CFD and 6DOF simulations are extensively used in ANSYS 2023 R1 Software for verification and validation of moving unstructured meshes and solvers by calibrating the position, aerodynamic forces and moments of the existing air-to-ground missile models. The verified CFD and 6DoF simulation separation process is applied and implemented for the investigation of the typical munition separation phenomena and compliance with the tailored requirements of MIL-HDBK-1763. The prediction of munition trajectory parameters under aircraft aerodynamics interference and specified rack unit consideration after munition separation is provided and complied with the tailored requirements to support the safe separation evaluation of improved and newly external store munition before the flight test performed. The proposed process demonstrates the effectiveness and reliability in providing the understanding of the complicated store separation and the reduction of flight test sorties during the improved and new munition development projects by extensively using the CFD and tailoring the existing standards.

Keywords: external store separation, MIL-HDBK-1763, CFD, moving meshes, flight test data, munition.

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Authors: Taylan Ozturk, Osama Maklad

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This study examines the aerodynamic and flow properties of a multi-element airfoil using computational fluid dynamics (CFD) research. This computational analysis aims to optimize slat design concerning lift-drag coefficients and to determine the ideal gap size between the main airfoil and the front flap. It examines the influence of varying angles of attack and the effects of varied Reynolds numbers. A NACA 2412 airfoil, equipped with custom-designed front and rear flaps, was modeled in SolidWorks and simulated in ANSYS Fluent utilizing the k-ω SST turbulence model. This study quantifies lift and drag coefficients, turbulent kinetic energy, and vorticity magnitude across various configurations. The results clearly indicate that the slat-optimized design geometry featuring a 4 mm gap provides the best performance regarding both lift and drag, with maximum efficiency achieved at a 4-degree angle of attack. Furthermore, the results indicate the initiation of stall conditions beyond 20 degrees and demonstrate how an increase in Reynolds numbers influences flow separation and turbulence patterns. In addition, the maximum L/D ratio which is 36.18 achieved. These findings enhance the comprehension of multi-element airfoil behavior, directly impacting aircraft design and operation, particularly in high-lift situations.

Keywords: multi-element airfoil, CFD simulation, aerodynamic characteristics, Reynolds number analysis

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Authors: Bernabeo R. Alberto

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With the tremendous improvements in the processing power of computers, the possibilities of artificial intelligence will increasingly be used in aviation and make autonomous flights, preventive maintenance, ATM (Air Traffic Management) optimization, pilots, cabin crew, ground staff, and airport staff training possible in a cost-saving, less time-consuming and less polluting way. Through the use of artificial intelligence, we foresee an interviewing scenario where the interviewee will interact with the artificial intelligence tool to contextualize the character and the necessary information in a way that aligns reasonably with the character and the scenario. We are creating simulated scenarios connected with either an aviation incident or accident to enhance also the training of future accident/incident investigators integrating artificial intelligence and augmented reality tools. The project's goal is to improve the learning and teaching scenario through academic and professional expertise in aviation and in the artificial intelligence field. Thus, we intend to contribute to the needed high innovation capacity, skills, and training development and management of artificial intelligence, supported by appropriate regulations and attention to ethical problems.

Keywords: artificial intelligence, aviation accident, aviation incident, risk, safety

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Authors: Rohan Sarker, Jon P. Conlon

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The Bombardier Challenger 605 SN 5769 is a versatile business jet known for its superior range, advanced avionics, and spacious cabin. Powered by two General Electric CF34-3B engines, each producing 8,729 pounds of thrust, the aircraft offers a maximum range of 4,000 nautical miles, allowing for non-stop transcontinental flights. It operates at a maximum cruising speed of Mach 0.82 (541 mph) and a service ceiling of 41,000 feet, ensuring efficient, high-altitude travel. The aircraft’s avionics suite is equipped with the Rockwell Collins Pro Line 21, offering advanced navigation, communication, and weather systems. The cockpit features dual Flight Management Systems (FMS) and GPS to enhance operational safety and precision. Inside, the Challenger 605 boasts a luxurious and customizable cabin that accommodates up to 12 passengers. The aircraft also provides ample baggage space, excellent short-field performance, and impressive fuel efficiency, making it ideal for business or personal long-range travel.

Keywords: aircraft, airframe, Bombardier, engines

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Authors: Hanyue Shen, Jiaying Zhang, Xingwei Kong

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Growing research on cross-domain vehicles (CDVs) has addressed the requirement to balance airfoil efficiency in air and water. No existing airfoil is specifically developed to adapt to the large Reynold’s number range CDVs operate in. This research proposes a supercritical airfoil biologically inspired by Atlantic Puffins. The initial airfoil is parameterized with the composite Karman-Trefftz method, optimized with a series of multi-stage gradient descend procedures, and compared with other airfoils with Xfoil. Results from Xfoil are also validated via Fluent and experiment considering curvatures on the designed airfoil might affect the accuracy of Xfoil. The results indicate that while CFD and Xfoil results closely align, Xfoil produces results closest to the experimental value. The bionic airfoil demonstrates superior performance in the range Re = 2·10⁴ to Re = 2·10⁵ compared to other studied airfoils, satisfying design requirements. This airfoil and its future counterparts are probable solutions to be implemented on fixed-wing CDVs desiring to glide in the given working conditions, providing an efficient and structurally simple pathway.

Keywords: fluid dynamics, airfoil design, biomimicry, cross domain vehicle

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Authors: Bernabeo R. Alberto

Abstract:

Unmanned aerial vehicles (UAV) platforms or remotely piloted aircraft system (Rpas) - with dedicated sensors - are fundamental support to the planning, running, and control of the territory in which public safety is or may be at risk for post-disaster assessments such as flooding or landslides, for searching lost people, for crime and accident scene photography, for assisting traffic control at major events, for teaching geography, history, natural science and all those subjects that require a continuous cyclical process of observation, evaluation and interpretation. Through the use of proximal remote sensing information related to anthropic landscape and nature integration, there is an opportunity to improve knowledge and management decision-making for the safeguarding of the environment, for farming, wildlife management, land management, mapping, glacier monitoring, atmospheric monitoring, for the conservation of archeological, historical, artistic and architectural sites, allowing an exact delimitation of the site in the territory. This paper will go over many different mission types. Within each mission type, it will give a broad overview to familiarize the reader but not make them an expert. It will also give detailed information on the payloads and other testing parameters the Unmanned Aerial Vehicles (UAV) use to complete a mission. The project's goal is to improve satellite maps about the stress of the plants, air quality monitoring, and related health issues.

Keywords: proximal remote sensing, remotely piloted aircraft system, risk, safety, unmanned aerial vehicle

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Authors: Natcha Laethongkham, Gayan Ramanayake, Philip Charlesworth, Leshan Uggalla

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The throttling process in hybrid rocket engines (HREs) poses challenges due to inherent instability, impacting the engine’s reliability and robustness. Identifying and advancing existing technology is crucial to meet the demands of complex mission profiles required for next-generation launch vehicles. This paper reviews the current literature, focusing on oxidiser flow control for throttling purposes in HREs. Covered areas include oxidiser choices, commonly used throttle valves, and literature trends. Common oxidisers for throttling are hydrogen peroxide, nitrous oxide, and liquid oxygen. Two frequently chosen valves for throttling are the ball and variation pintle valves. The review identifies two primary research focuses: flow control valve studies and control system design. The current research stage is highlighted, and suggestions for future directions are proposed to advance thrust control systems in HREs. This includes further studies in existing research focuses and exploring new approaches such as system scheme design, numerical modelling, and applications.

Keywords: hybrid rocket engines, oxidiser flow control, thrust control, throttle valve, review

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Authors: Thandar Zaw Win, Cho Win Aung, Gaurav Khandal, Sabyasachi Ghosh

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Systematic and comparative research on Lorenz ratios for graphene and nonrelativistic systems has been studied to identify their Wiedemann-Franz law violation domain. Fermi energy and temperature are the main governing parameters for deciding the values of the Lorenz ratio, which is basically thermal conductivity divided by electrical conductivity times temperature times Lorenz number. Metals as three-dimensional nonrelativistic electron gas are located at higher Fermi-energy by temperature domain, where Lorenz ratio remains one. Hence, they obey the Wiedemann-Franz law. By creating higher doping in a two-dimensional graphene system, one can again reach a higher Fermi-energy by temperature domain and get a constant Lorenz ratio. For both graphene and nonrelativistic systems, the Lorenz ratio goes below one if we go lower Fermi-energy by temperature domain, which is possible for the graphene system by decreasing the doping concentration. Experimentally observed greater than one Lorenz ratio in this lower Fermi-energy by temperature domain or Dirac Fluid domain indicates that nonfluid expressions of Lorenz ratio should be replaced by fluidtype expressions. We have noticed a divergent trend of Lorenz ratio in the Dirac Fluid domain using its fluid-type expression, and it matches the trend of experimental data.

Keywords: graphene, Lorentz ratio, specific heat, Wiedeann-Franz law

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Authors: Sani Isa, Ali Musa

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Burgers’ fluid with a fractional derivatives model in an annulus was analyzed. Combining appropriately the basic equations, with the fractionalized fractional Burger’s fluid model allow us to determine the velocity field, temperature and shear stress. The governing partial differential equation was solved using the combine Laplace transformation method and Riemann sum approximation to give velocity field, temperature and shear stress on the fluid flow. The influence of various parameters like fractional parameters, relaxation time and retardation time, are drawn. The results obtained are simulated using Mathcad software and presented graphically. From the graphical results, we observed that the relaxation time and time helps the flow pattern, on the other hand, other material constants resist the fluid flow while fractional parameters effect on fluid flow is opposite to each other.

Keywords: sani isa, Ali musaburger’s fluid, Laplace transform, fractional derivatives, annulus

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Authors: Jiangwan Xu, Chunyu Ding

Abstract:

Lunar exploration is of significant importance in the development and utilization of in-situ lunar resources, water ice exploration, space and astronomical science, as well as in political and military strategy. In recent years, ground-based radar (GBR) has gained increasing attention in the field of lunar exploration due to its flexibility, low cost, and penetrating capabilities. This paper reviews the scientific research on lunar exploration using GBR, outlining the basic principles of GBR and the progress made in lunar exploration studies. It introduces the fundamental principles of lunar imaging using GBR, and systematically reviews studies on lunar surface layer detection, inversion of lunar regolith dielectric properties, and polar water ice detection using GBR. In particular, the paper summarizes the current development status of Chinese GBR and forecasts future development trends in China. This review will enhance the understanding of lunar exploration results using GBR radar, systematically demonstrate the main applications and scientific achievements of GBR in lunar exploration, and provide a reference for future GBR radar lunar exploration missions.

Keywords: ground-based radar, lunar exploration, radar imaging, lunar surface/subsurface detection

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

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In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

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Authors: Siva Teja Golla, B. Venkatesham

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The recent technologies in hybrid and high-end cars have subsided the noise from major sources like engines and transmission systems. This resulted in the unmasking of the previously subdued noises. These noises are becoming noticeable to the passengers, causing annoyance to them and affecting the perceived quality of the vehicle. Sloshing in the fuel tank is one such source of noise. Sloshing occurs due to the excitations undergone by the fuel tank due to the vehicle's movement. Sloshing noise occurs due to the interaction of the fluid with the surrounding tank walls or with the fluid itself. The noise resulting from the interaction of the fluid with the structure is ‘Hit noise’, and the noise due to fluid-fluid interaction is ‘Splash noise’. The type of interactions the fluid undergoes inside the tank, and the type of noise generated depends on a variety of factors like the fill level of the tank, type of fluid, presence of objects like baffles inside the tank, type and strength of the excitation, etc. There have been studies done to understand the effect of each of these parameters on the generation of different types of sloshing noises. But little work is done in the psychoacoustic aspect of these sounds. The psychoacoustic study of the sloshing noises gives an understanding of the level of annoyance it can cause to the passengers and helps in taking necessary measures to address it. In view of this, the current paper focuses on the calculation of the psychoacoustic parameters like loudness, sharpness, roughness and fluctuation strength for the sloshing noise. As the noise generation mechanisms for the hit and splash noises are different, these parameters are calculated separately for them. For this, the fluid flow regimes that predominantly cause the hit-and-splash noises are to be separately emulated inside the tank. This is done through a reciprocating test rig, which imposes reciprocating excitation to a rectangular tank filled with the fluid. By varying the frequency of excitation, the fluid flow regimes with the predominant generation of hit-and-splash noises can be separately created inside the tank. These tests are done in a quiet room and the noise generated is captured using microphones and is used for the calculation of psychoacoustic parameters of the sloshing noise. This study also includes the effect of fill level and the presence of baffles inside the tank on these parameters.

Keywords: sloshing, hit noise, splash noise, sound quality

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Authors: Wei Wang, Yaohua Zhao, Yanhua Diao

Abstract:

The exponential growth of the lighting industry has rendered traditional thermal technologies inadequate for addressing the thermal management challenges inherent to high-power light-emitting diode (LED) technology. To enhance the thermal management of LEDs, this study proposes a heat sink configuration that integrates a miniature heat pipe array based on phase change technology with rectangular channels. The thermal performance of the heat sink was evaluated through experimental testing, and the results demonstrated that when the input power was 100W, 150W, and 200W, the temperatures of the LED substrate were 47.64℃, 56.78℃, and 69.06℃, respectively. Additionally, the maximum temperature difference of the MHPA in the vertical direction was observed to be 0.32℃, 0.30℃, and 0.30℃, respectively. The results demonstrate that the heat sink not only effectively dissipates the heat generated by the LEDs, but also exhibits excellent temperature uniformity. In consideration of the experimental measurement outcomes, a corresponding numerical model was developed as part of this study. Following the model validation, the effect of the structural parameters of the heat sink on its heat dissipation efficacy was examined through the use of response surface methodology (RSM) analysis. The rectangular channel width, channel height, channel length, number of channel cross-sections, and channel cross-section spacing were selected as the input parameters, while the LED substrate temperature and the total mass of the heat sink were regarded as the response variables. Subsequently, the response was subjected to an analysis of variance (ANOVA), which yielded a regression model that predicted the response based on the input variables. This offers some direction for the design of the radiator.

Keywords: light-emitting diodes, heat transfer, heat pipe, natural convection, response surface methodology

Procedia PDF Downloads 34

Authors: Changzhi Jiang, Chunyu Ding, Yan Su, Jiawei Li, Ravi Sharma, Yuanzhou Liu, Jiangwan Xu

Abstract:

Early Mars is believed to have had extensive liquid water activity, which has now predominantly transitioned to a frozen state, with the majority of water stored in polar ice caps. It has long been deemed that the shallow subsurface of Mars' mid-to-low latitudes is devoid of liquid water. However, geological features observed at the Tianwen-1 landing site hint potential subsurface water. Our research indicates that the shallow subsurface at the Tianwen-1 landing site consists primarily of diluvium deposits containing liquid brine and brine ice, which exhibits diurnal thermal convection processes. Here we report the relationship between the loss tangent and temperature of materials within 5 meters depth of the subsurface at the Tianwen-1 landing site, as in-situ detected by high-frequency radar and climate station onboard the Zhurong rover. When the strata temperature exceeds ~ 240 K, the mixed brine ice transitions to liquid brine, significantly increasing the loss tangent from an average of ~ 0.0167 to a maximum of ~ 0.0448. This finding indicates the presence of substantial subsurface water in Mars' mid-to-low latitudes, influencing the shallow subsurface heat distribution and contributing to the current Martian hydrological cycle.

Keywords: water on mars, mars exploration, in-situ radar detection, tianwen-1 mission

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Authors: Mennatallah M. Hussein, Olivier de Weck

Abstract:

The advancement of space exploration demands a robust space launch services program capable of reliably propelling payloads into orbit. Despite rigorous testing and quality assurance, launch failures still occur, leading to significant financial losses and jeopardizing mission objectives. Traditional failure prediction methods often lack the sophistication to account for multi-mode failure scenarios, as well as the predictive capability in complex dynamic systems. Traditional approaches also rely on expert judgment, leading to variability in risk prioritization and mitigation strategies. Hence, there is a pressing need for robust approaches that enhance launch vehicle reliability from lift-off until it reaches its parking orbit through comprehensive simulation techniques. In this study, the developed model proposes a multi-mode launch vehicle simulation framework for predicting failure scenarios when incorporating new technologies, such as new propulsion systems or advanced staging separation mechanisms in the launch system. To this end, the model combined a 6-DOF system dynamics with comprehensive data analysis to simulate multiple failure modes impacting launch performance. The simulator utilizes high-fidelity physics-based simulations to capture the complex interactions between different subsystems and environmental conditions.

Keywords: launch vehicle, failure prediction, propulsion anomalies, rocket launch simulation, rocket dynamics

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Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

Abstract:

Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

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Authors: Irfan Nazir Wani, Pushpendra Kumar Shukla, Manoj Kumar

Abstract:

Debris, also called waste or junk, present in orbit of Earth or orbital debris, offers a substantial challenge to space exploration. Satellite operations and other space-based activities. This research paper delves into the causes and effects of space debris accumulation, explores current mitigation techniques, and presents a hopeful outlook on the potential for future sustainable space activities. The paper emphasizes the necessity of addressing planetary fragments to ensure durable sustainability in universe exploration and utilization. It examines various strategies for mitigating space debris, including debris removal technologies, spacecraft design improvements, and international collaboration efforts. Additionally, the paper highlights the importance of space debris monitoring and tracking systems in preventing collisions and minimizing the growth of orbital debris. By comprehending the complexities of space debris and implementing effective mitigation measures, the space industry can work towards a future where sustainable space activities are achievable.

Keywords: space shuttle, debris, space junk, satellite, fragments, orbit

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Authors: Kamal Hammad, Alexey Fedorenko, Ivan Sergeichev

Abstract:

This study uses analytical modeling, experimental testing, and explicit numerical simulations to evaluate failure and spall damage in Carbon Fiber-Reinforced Polymer (CFRP) composite confinement vessels. It investigates the response of composite materials to explosive loading dynamic impact, revealing varied failure modes. Hashin damage was used to model inplane failure, while the Virtual Crack Closure Technique (VCCT) modeled inter-laminar damage. Results show moderate agreement between simulations and experiments regarding free surface velocity and failure stresses, with discrepancies due to wire alignment imperfections and wave reverberations in the experimental test. The findings can improve design and risk-reduction strategies in high-risk scenarios, leading to enhanced safety and economic efficiency in material assessment and structural design processes.

Keywords: explicit, numerical, spall, damage, CFRP, composite, vessels, explosive, dynamic, impact, Hashin, VCCT

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Authors: Thais Cardoso Franco, Caio Nahuel Sousa Fagonde, Willer Gomes dos Santos

Abstract:

Aurora Borealis is an optical phenomenon composed of luminous events observed in the night skies in the polar regions resulting from disturbances in the magnetosphere due to the impact of solar wind particles with the Earth's upper atmosphere, channeled by the Earth's magnetic field, which causes atmospheric molecules to become excited and emit electromagnetic spectrum, leading to the display of lights in the sky. However, there are still different implications of this phenomenon under study: high intensity auroras are often accompanied by geomagnetic storms that cause blackouts on Earth and impair the transmission of signals from the Global Navigation Satellite Systems (GNSS). Auroras are also known to occur on other planets and exoplanets, so the activity is an indication of active space weather conditions that can aid in learning about the planetary environment. In order to improve understanding of the phenomenon, this research aims to design a satellite formation flying solution for collecting and transmitting data for monitoring aurora borealis in northern hemisphere, an approach that allows studying the event with multipoint data collection in a reduced time interval, in order to allow analysis from the beginning of the phenomenon until its decline. To this end, the ideal number of satellites, the spacing between them, as well as the ideal topology to be used will be analyzed. From an orbital study, approaches from different altitudes, eccentricities and inclinations will also be considered. Given that at large relative distances between satellites in formation, controllers tend to fail, a study on the efficiency of nonlinear adaptive control methods from the point of view of position maintenance and propellant consumption will be carried out. The main orbital perturbations considered in the simulation: non-homogeneity terrestrial, atmospheric drag, gravitational action of the Sun and the Moon, accelerations due to solar radiation pressure and relativistic effects.

Keywords: formation flying, nonlinear adaptive control method, aurora borealis, adaptive SDRE method

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Authors: Olaniyi Awe, Adelana R. Adetunji, Abraham Adeleke

Abstract:

Mining of alluvial gold ore by artisanal miners has been going on for decades at Itagunmodi, Southwestern Nigeria. In order to optimize the traditional panning gravity separation method commonly used in the area, a mineral particle size analysis study is critical. This study analyzed alluvial gold ore samples collected at identified five different locations in the area with a view to determine the ore particle size distributions. 500g measured of as-received alluvial gold ore sample was introduced into the uppermost sieve of an electrical sieve shaker consisting of sieves arranged in the order of decreasing nominal apertures of 5600μm, 3350μm, 2800μm, 355μm, 250μm, 125μm and 90μm, and operated for 20 minutes. The amount of material retained on each sieve was measured and tabulated for analysis. A screen analysis graph using the Gaudin Schuman method was drawn for each of the screen tests on the alluvial samples. The study showed that the percentages of fine particle size -125+90 μm fraction were 45.00%, 36.00%, 39.60%, 43.00% and 36.80% for the selected samples. These primary ore characteristic results provide reference data for the alluvial gold ore processing method selection, process performance measurement and optimization.

Keywords: alluvial gold ore, sieve shaker, particle size, Gaudin Schumann

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Authors: César Coelho, Nikolai Wiegand

Abstract:

The advancement of nanosatellite technology has opened new avenues for cost-effective and faster space missions. The NanoSat MO Framework (NMF) from the European Space Agency (ESA) provides a modular and simpler approach to the development of flight software and operations of small satellites. This paper presents a methodology using the NMF together with Docker for simulating constellations of satellites. By leveraging Docker containers, the software environment of individual satellites can be easily replicated within a simulated constellation. This containerized approach allows for rapid deployment, isolation, and management of satellite instances, facilitating comprehensive testing and development in a controlled setting. By integrating the NMF lightweight simulator in the container, a comprehensive simulation environment was achieved. A significant advantage of using Docker containers is their inherent scalability, enabling the simulation of hundreds or even thousands of satellites with minimal overhead. Docker's lightweight nature ensures efficient resource utilization, allowing for deployment on a single host or across a cluster of hosts. This capability is crucial for large-scale simulations, such as in the case of mega-constellations, where multiple traditional virtual machines would be impractical due to their higher resource demands. This ability for easy horizontal scaling based on the number of simulated satellites provides tremendous flexibility to different mission scenarios. Our results demonstrate that leveraging Docker containers with the NanoSat MO Framework provides a highly efficient and scalable solution for simulating satellite constellations, offering not only significant benefits in terms of resource utilization and operational flexibility but also enabling testing and validation of ground software for constellations. The findings underscore the importance of taking advantage of already existing technologies in computer science to create new solutions for future satellite constellations in space.

Keywords: containerization, docker containers, NanoSat MO framework, satellite constellation simulation, scalability, small satellites

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