Aeronautical Engineering Research Articles

Integrating Python and MATLAB for Digital Twin Applications in Aeroservoelasticity

The development of Digital Twin (DT) applications in intricate engineering areas has been greatly accelerated by the incorporation of sophisticated computational tools like Python and MATLAB. The goal of this research is to model, simulate, and analyze aeroservoelastic systems for Digital Twin implementations by utilizing the combined powers of Python and MATLAB. In order to achieve the real-time predictive skills needed for Digital Twins, aeroservoelasticity—which involves the coupled interplay of aerodynamic, structural, and control forces—presents special obstacles. This work successfully tackles these issues by fusing MATLAB's strong numerical and control system capabilities with Python's adaptability and library ecosystem. Using real-time sensor data streaming, and feedback control system implementation is used in this work. High-fidelity state-space modeling, sophisticated control design (such as PID and state feedback controllers), and system dynamics visualization are all done concurrently with MATLAB. In order to simulate and stabilize a highly flexible aeroelastic system, a continuous feedback loop was modeled in both environments, highlighting the platforms' complimentary advantages. Through the MATLAB Engine API for Python, the integrated method facilitates smooth data transmission between Python and MATLAB, guaranteeing real-time communication and model parameter synchronization. The efficiency of this dual-platform system is demonstrated by case studies on wing flutter suppression, limit cycle oscillation (LCO) mitigation, and control input optimization. The method is well suited for the dynamic needs of aeroservoelastic Digital Twins because of the results, which demonstrate a shorter error convergence time, improved stability, and computational economy. By utilizing MATLAB and Python's interoperability, this work establishes the groundwork for scalable, real-time Digital Twin solutions in aeronautical engineering. It highlights how crucial hybrid computational ecosystems are for bridging the gap between high- fidelity simulations and real-time predictive capabilities, opening the door for improvements in fault prediction, control optimization, and aeronautical system monitoring.

Aerodynamic Challenges and Innovations in Wing Designs for Supersonic Flight: A Comprehensive Review

Supersonic flight has been of interest for decades due to the advantages it offers in speed and efficiency of transport, which are advantageous to both commercial and military aircraft. This paper covers a comprehensive review of various wing configurations for supersonic flight. We explore the aerodynamic and structural challenges associated with the various wing types. Supersonic flight offers significant benefits, but also poses complex engineering challenges including concerns with drag, stability, and sonic booms. This review examines the performance of straight, low-sweep, swept-back, delta, forward-swept, and oblique wings and highlights their respective advantages and limitations across different regimes. Straight and low-sweep wings excel at subsonic speeds, but struggle with high drag at supersonic velocities, while swept-back wings and delta wings offer superior performance at high speeds but come with trade-offs in lift and low-speed efficiency. Forward-swept wings provide potential for noise reduction and overall favorable supersonic flight characteristics, but face challenges like aeroelastic instability. Oblique wings, though promising in reducing drag and sonic booms, have significant structural challenges at high Mach numbers. Ongoing research in materials science and aerodynamic modeling continues to advance supersonic aircraft design. These studies and development efforts are paving the way for next-generation supersonic aircraft. Keywords: Aerospace and Aeronautical Engineering; Computation and Theory; Supersonic Flight; Wing Design; Aerodynamics and Sonic Booms

Damage Localization and Severity Assessment in Composite Structures Using Deep Learning Based on Lamb Waves.

In composite structures, the precise identification and localization of damage is necessary to preserve structural integrity in applications across such fields as aeronautical, civil, and mechanical engineering. This study presents a deep learning (DL)-assisted framework for simultaneous damage localization and severity assessment in composite structures using Lamb waves (LWs). Previous studies have often focused on either damage detection or localization in composite structures. In contrast, this study aims to perform damage detection, severity assessment, and localization using independent DL models. Three DL models, namely the artificial neural network (ANN), convolutional neural network (CNN), and gated recurrent unit (GRU), are compared. To assess their damage detection and localization capabilities. Moreover, zero-mean Gaussian noise is introduced as a data augmentation technique to address the variability and noise inherent in LW signals, improving the generalization capability of the DL models. The proposed framework is validated on a composite plate with four piezoelectric transducers, one at each corner, and achieves high accuracy in both damage localization and severity assessment, offering an effective solution for real-time structural health monitoring. This dual-function approach provides a scalable data-driven method to evaluate composite structures, with applications in predictive maintenance and reliability assurance in critical engineering systems.

Light metal alloys used in the aeronautical industry suitable for FSW welding/ FSP processing

This study presents light metal alloys used in the aeronautical industry, specifically focusing on their suitability for Friction Stir Welding (FSW) and Friction Stir Processing (FSP). These innovative techniques play an important role in improving the mechanical properties and performance of aluminum, magnesium, and titanium alloys, which are extensively utilized in aerospace applications due to their superior strength-to-weight ratios. FSW and FSP offer significant advantages in joining and processing materials, including enhanced weld integrity, defect reduction, and refined microstructural properties. The integration of light metal alloys by these methods within the aeronautical sector fosters the production of lighter and stronger structures, contributing to reduced fuel consumption and improved overall performance in aeronautical engineering.

Modal analysis of laminated composite beams reinforced with randomly oriented fibers for aeronautical engine applications

Turbine blades are integral components of aircraft engines, directly influencing performance, efficiency, and safety. These blades operate under extreme conditions, facing high temperatures, significant mechanical stresses, and corrosive environments. Therefore, the selection of appropriate materials for turbine blades is crucial to ensure their reliability, engine efficiency and longevity. The present paper is focused on modal analysis of the laminate beam in layers’ carbon (mast) / ceramic. In this study, we use the Euler-Bernoulli hypothesis for the fins which considered the fin as a simple beam. The simulation was performed using Ansys software to assess the natural frequencies and mode shapes of the laminated beam under bending loads. The results compared to those of beams made from supper alloys used in aircraft engines. The findings reveal that the laminate composite beam exhibits greater dynamic stability than its alloy counterparts. This enhanced stability suggests that laminated composite materials are particularly suited for high-pressure applications, where performance and reliability are critical. Notably, the composite material with carbon mast (HM) demonstrates superior mechanical properties, including increased rigidity, reduced micro-cracking, improve efficiency and performance of flight engines and increased lifetime. Finally, this study underscores the importance of innovative materials in aeronautical engineering, highlighting the advantages of laminated composites in dynamic applications.

Enhancing UAV Propulsion: Insights into Toroidal Propeller Dynamics through CFD Simulations

Toroidal propellers have emerged as a transformative breakthrough in aeronautical propulsion, promising enhanced efficiency, maneuverability, and notably, noise reduction. Utilizing Fluent/ANSYS for computational fluid dynamics (CFD) simulations, this study endeavors to delve into the performance dynamics of toroidal propellers in aeronautical applications, with a specific focus on assessing thrust generation, efficiency, and acoustic pressure, especially pertinent in the context of unmanned aerial vehicles (UAVs).The simulations meticulously modeled the intricate airflow dynamics around toroidal propellers, using Fluent/ANSYS's steady, turbulent flow solver, incorporating parameters such as airspeed, propeller rotational speed, and toroidal rotor geometry. The comprehensive three-dimensional computational domains accurately represented the propeller geometry and airflow interactions, facilitating a nuanced analysis of performance metrics.Through comparative analyses of toroidal propellers against a conventional design, aerodynamic advantages emerged, notably in noise reduction. The unique closed-loop structure of toroidal propellers minimizes drag effects from swirling air tunnels, significantly attenuating the propeller's acoustic signature. These findings represent a pivotal step forward in our understanding of toroidal propeller aerodynamics, underscoring their immense potential in UAV applications. Moreover, they serve as a compass for future design refinement and practical integration into aeronautical engineering practices. With the groundwork laid for experimental validation and real-world deployment, the prospect of using toroidal propellers in both commercial and military aviation appears increasingly tangible.

Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer

Metaheuristic algorithms (MAs) now are the standard in engineering optimization. Progress in computing power has favored the development of new MAs and improved versions of existing methods and hybrid MAs. However, most MAs (especially hybrid algorithms) have very complicated formulations. The present study demonstrated that it is possible to build a very simple hybrid metaheuristic algorithm combining basic versions of classical MAs, and including very simple modifications in the optimization formulation to maximize computational efficiency. The very simple hybrid metaheuristic algorithm (SHGWJA) developed here combines two classical optimization methods, namely the grey wolf optimizer (GWO) and JAYA, that are widely used in engineering problems and continue to attract the attention of the scientific community. SHGWJA overcame the limitations of GWO and JAYA in the exploitation phase using simple elitist strategies. The proposed SHGWJA was tested very successfully in seven “real-world” engineering optimization problems taken from various fields, such as civil engineering, aeronautical engineering, mechanical engineering (included in the CEC 2020 test suite on real-world constrained optimization problems) and robotics; these problems include up to 14 optimization variables and 721 nonlinear constraints. Two representative mathematical optimization problems (i.e., Rosenbrock and Rastrigin functions) including up to 1000 variables were also solved. Remarkably, SHGWJA always outperformed or was very competitive with other state-of-the-art MAs, including CEC competition winners and high-performance methods in all test cases. In fact, SHGWJA always found the global optimum or a best cost at most 0.0121% larger than the target optimum. Furthermore, SHGWJA was very robust: (i) in most cases, SHGWJA obtained a 0 or near-0 standard deviation and all optimization runs practically converged to the target optimum solution; (ii) standard deviation on optimized cost was at most 0.0876% of the best design; (iii) the standard deviation on function evaluations was at most 35% of the average computational cost. Last, SHGWJA always ranked 1st or 2nd for average computational speed and its fastest optimization runs outperformed or were highly competitive with their counterpart recorded for the best MAs.

Assessing Aircraft Engine Wear through Simulation Techniques

In the field of aeronautical engineering, understanding and simulating aircraft engine performance is critical, especially for improving operational safety, efficiency, and sustainability. At Safran Aircraft Engines, we were able to demonstrate the effectiveness of using time series collected from the engines after each flight to build a digital twin that provides a dynamic virtual model able to mirror the real engine’s state by using a transformer-based conditional generative adversarial network. This virtual representation allows for advanced simulations under diverse operational scenarios like flight conditions and controls, aiding in understanding the impact of different factors on engine health. It is, therefore, possible for us to provide virtual flights performed by our engines in their actual state of wear. This research paper presents a machine learning model that effectively simulates and monitors the state of aircraft engines in real-time, enabling us to track the evolution of the engines’ health over their life cycle. The model’s adaptability to incorporate new data ensures its applicability throughout the engine’s lifespan, marking a step forward in proactive aeronautic maintenance and potentially enhancing engine longevity through timely diagnostics and interventions.

A fast-aware multi-target response prediction approach and its application in aeronautical engineering

Response prediction is a fundamental yet challenging task in aeronautical engineering, requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunately, in large-scale structures, the rigorous selection of reliable sensor candidates for multi-target responses remains largely unexplored. In this paper, we propose a flexible and generalized framework for selecting the most relevant sensors to the multi-target response and predicting the target response, referred to as the Fast-aware Multi-Target Response Prediction (FMTRP) approach in the spirit of divide-and-conquer. Specifically, first, a multi-task learning module is designed to predict multi-point response tasks at the same time. Simultaneously, we meticulously devise adaptive mechanisms to facilitate loss-term reweighting and encourage prioritization of challenging tasks in multiple prediction tasks. Second, to ensure ease of interpretation, we introduce a hybrid penalty to select sensors at the group-sparsity, individual-sparsity and element-sparsity levels. Finally, due to the substantial number of candidate sensors posing a significant computational burden, we develop a more efficient search strategy and support computation to make the proposed approach applicable in practice, leading to substantial runtime improvements. Extensive experiments on aircraft standard model response datasets and large airliner test flight datasets validate the effectiveness of the proposed approach in identifying sensor locations and simultaneously predicting responses at multiple points. Compared to state-of-the-art methods, the proposed approach achieves an accuracy of over 99% in sinusoidal excitation and exhibits the shortest runtime (3.514 s).

Study on cross effect of mesh and turbulence model on separated flow prediction using a tandem cylinder case

Abstract Low dissipative separated flow prediction is still a great challenge in aeronautics engineering. An open-source CFD code named SU2 is employed to study the cross effect of mesh as well as turbulence model on the numerical resolution of separated flow for a tandem cylinder case. Firstly, a nonlinear variation of the numerical resolution for the separated flow is found by comparing the mean surface pressure distribution, mean streamwise velocity profile, the instantaneous vorticity magnitude as well as the aerodynamic forces on the rear cylinder. The resolution of separated flow from the medium mesh is the best compared to those getting from the coarse and fine mesh. Secondly, the reason causing the nonlinear variation of flow resolution is analyzed considering the influence of spatial discretization error and turbulent viscosity locally. A finer mesh would lead to a low spatial discretization error and then a high turbulent viscosity and then causes nonlinear variation of flow resolution. Finally, the existence of a “density boundary” of the mesh is proposed which could balance the spatial precision as well as turbulent viscosity and achieve the prediction of separated flow with a good resolution employing the RANS method.

Deformation Evolution and Perceptual Prediction for Additive Manufacturing of Lightweight Composite Driven by Hybrid Digital Twins

This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins (HDT). In order to improve manufacturing quality of irregular lightweight composite through boosting conceptual design in aeronautic and aerospace engineering, the HDT meaning hybridization of physical and digital domains, including deformation and energy efficiency can be built, where the essential parameters can be perceptually predicted in advance, by virtue of the fusion of physical sensors and digital information. The long short term memory (LSTM) can be employed to void vanishing gradient problem and improve predicting precision via Recurrent Neural Networks, thereby laying a foundation for the HDT. The diverse manufacturing requirements of different regions are integrated into the parameters designing phase by attaching region weights confirmed via empiricism and in-service simulation. The effects of slicing strategy and external support structures on manufacturing quality are considered from the perspective of improving dimensional accuracy. The manufacturing efficiency and comprehensive costs are accounted as consideration factors, which are perceptually predicted via LSTM. The designed manufacturing parameters through HDT were virtually examined by evaluating the deformation and equivalent stress distributions of fabricated lightweight component with composite material through AM process simulation. The physical experiments were conducted to verify the HDT-based pre-designing and optimization method of manufacturing parameters via fused deposition modeling (FDM). The energy consumption of actual manufacturing process was measured via digital power meter and applied to evaluate accuracy of perceptual prediction outcomes. The dimensional accuracy and distortion distribution of the manufactured lightweight prototype made with composite material were measured through the coordinate measuring machine (CMM) and 3D optical scanner. The proposed method demonstrates effectiveness in improving manufacturing quality and accurately predicting energy consumption, which have been verified with a three-way solenoid valve element, in which the maximum deformation was reduced by 39.78% and the mean absolute percentage error for perceptual prediction was 3.76%.

Plane dilatational and shear waves in a chiral porous thermoelastic medium under strain gradient theory

PurposeThis study aims to investigate time-harmonic wave propagation in a chiral porous thermoelastic solid under strain gradient theory (SGT), focusing on identifying and characterizing distinct wave modes within the medium.Design/methodology/approachUsing Iesan's gradient theory, which incorporates chiral effects and accommodates second sound phenomena, the authors derive mathematical formulations for the velocities and attenuations of eight propagating waves: four dilatational waves and two pairs of coupled shear waves (one left circularly polarized, the other right). Numerical simulations are performed for a specific model, exploring the influence of various parameters on wave propagation.FindingsThe authors establish that the medium supports four dilatational waves, including a microstretch-associated wave, and four shear waves, distinguished by their chiral-induced characteristics. The results highlight the frequency-dependent dispersive nature of all propagating waves and establish connections with existing theoretical frameworks, demonstrating the broader applicability of our findings.Practical implicationsThe characteristics of wave propagation in chiral media examined here can enhance our understanding of chiral medium behavior. This knowledge is crucial for developing materials with pronounced chiral effects, surpassing those found in natural chiral materials like bone, quartz, sugar and wood. Advances in artificial chiral materials are driven by their superior toughness, durability and other beneficial properties. Consequently, this study has potential applications across various fields, including the design of chiral broadband absorbers and filters, the production of artificial bones and medical devices, aeronautical engineering and beyond.Originality/valueThis research extends existing theories and deepens the understanding by exploring wave behaviors in chiral media, advancing this emerging field.

Numerical study on transonic shock wave buffeting of airfoil

Abstract Modern transportation aircraft typically cruise at transonic speeds. However, under a specific combination of incoming flow Mach numbers and angles of attack, periodic self-excited oscillations of shock waves can lead to unsteady aerodynamic loads, causing sustained vibrations in the aircraft, which is known as transonic shock wave buffeting. Buffeting loads significantly impact the fatigue life of the aircraft’s structural materials and its handling performance. In severe cases, it causes structural damage or even leads to flight safety incidents, so we should pay more attention to transonic shock wave buffeting when focusing on aeronautical engineering. This paper employs computational fluid dynamics technology for calculations to solve the Navier-Stokes equations, using the SST k-ω turbulence model to numerically simulate the steady flow field, and further employing the detached eddy simulation (DES) method to study and analyze the buffeting initiation mechanism and flow field characteristics of the NACA0012 airfoil’s transonic unsteady flow. By applying the DES method, the results demonstrate an accurate prediction of the buffeting onset boundary of the airfoil compared to wind tunnel experimental data. The research findings on the initiation mechanism and load characteristics of transonic buffeting provide a theoretical basis for optimizing the aerodynamic performance of aircraft during transonic flight and offer guidance for engineering issues such as buffeting load mitigation.

Effects of new nonlinear curvature models and non-local elasticity on buckling investigation of FG tapered nano-beams locating on elastic foundations

New nonlinear curvature models are proposed to show their effects on the compressive critical buckling load on functionally graded (FG) tapered nano-beams locating on elastic foundations in the presence of non-local elasticity. Fourth and fifth orders finite difference methods (bvp4c and bvp5c) are applied on the governing differential equation which is a highly non-linear, due to curvature and has variable coefficients, due to properties. Dimensional analyses have been applied on the governing system together with the problem conditions to produce their dimensionless forms. For different considered parameters, the critical buckling load is computed using the eigenvalue theorem. The effects of nonlinear curvature, variable Young modulus, variable moment inertia and foundation parameters are studied and displayed in tables and figures. The stability and convergence of the present solution are tested using more than one strategy as: comparison with available results, comparison between bvp4c and bvp5c with different mesh intervals and tolerances of truncation errors. These comparisons show that, the new curvature model affects the critical buckling with different ratios depending on variability of properties and foundation parameters. The new results show that the nonlinear curvature model reduces the critical buckling load in comparison with the classical linear model, which, leads to decreasing in factor of safety in design of structures. The new results show that the design of structures will be influenced with the new reduction of the compressive critical buckling load, since it may affect the factor of safety in design of structures. The new results can lead, generally, to more reduction of critical buckling load for large or small input parameters and it will affect other critical values such that frequencies. The introduced Tables and Figures of the present problem with comparisons of previously exact, analytical and numerical works establish the higher accuracy and stability of current findings using bvp4c or bvp5c with preferable of the later. This study is related to some practical applications such as aeronautical and structural engineering.

Influence of space conjugate temperature varying non-uniform heat sink/source on hydromagnetic slip water-EG (50:50) nanofluid

Significant cooling is an essential requirement in the field of aeronautical and bio-medical engineering, nuclear reactor system, solar collectors, and in development of electronic chips etc. Involving rotating conical geometries. In view of this, flow and heat transfer over conical geometries subject to different constraints of motion are highly needed. Implementation of magnetic field subject to flow pattern controls the fluid motion thereby imparting better cooling. Consideration of nanofluid instead of regular fluid yields prominent cooling of the associated surface. Such relevance has motivated the authors to work on magnetohydrodynamics and heat transfer investigation of water-EG (50:50) mixture based Al2O3 and Fe3O4 past heated and rotating down-pointing upright cone subject to impact of space and temperature varying non-uniform heat source or sink. Numerical solution of dimensionless governing equations is accomplished by implementing Runge-Kutta method. The findings indicate that swirl and axial velocities peter out with rise in magnetic parameter while both exhibit opposite impact in response to slip parameter. Temperature profiles upgrade due to amplification of space and temperature dependent parameters. Skin friction and heat transportation upsurge with growth of solid volume fraction of nanoparticle.

Evolving trends and advanced applications of engineering materials in contemporary aircraft: a review

This review article discusses the engineering materials used in aircraft, with a focus on aluminum alloys, titanium alloys and composite materials, including where and why they are most used in aircraft. There are many research papers that deal in detail with materials such as aluminum alloys, titanium alloys and composites used in an aircraft, including theoretical and experimental results. However, the author felt that a review of aircraft materials was necessary, both for himself and to help others interested in similar topics. In addition, the author felt the need of thinking back to the past on what materials used to be prevalent and what materials have superseded them. One such example written in this study is the case of Aluminum that used to be the predominant material in aircraft structural components, has been increasingly supplanted by polymer composites in recent years due to their advantageous properties. It is hoped that from this review article the reader will be able to understand the general trend of recent developments in aeronautical engineering materials and be able to choose which path to follow and which area to focus on in their future research.

Review of Solar Sail Propulsion Mechanisms and Missions for Space Travel

Since solar sailing employs the speed of sunlight to drive spacecraft, it is an efficient and environmentally friendly alternative to traditional propulsion technologies. The physics of photon compression, the significance of novel materials and systems that enhance sailing performance, and the appropriate testing of solar sailing systems are all covered in this research paper. The main solar sailing projects— LightSail, NEA Scout, and IKAROS—are examined in this paper, and their merits, demerits, and contributions to the field are discussed. Potential solar sailing technology for extended space travel are also covered, along with space sustainability. Consider how crucial it is for space exploration in the future. The goal of this research is to demonstrate the transformative potential of navigation and to spark further developments in the exciting field of space aerospace engineering by effectively integrating mission data and current research in the ever-changing landscape of space exploration. Since solar sailing employs the speed of sunlight to drive spacecraft, it is a practical and environmentally friendly alternative to traditional propulsion technologies. The physics of photon compression, the significance of novel materials and systems that enhance sailing performance, and the appropriate testing of solar sailing systems are all covered in this research paper. The main solar sailing projects—LightSail, NEA Scout, and IKAROS—are examined in this paper, and their merits, demerits, and contributions to the field are discussed. Potential solar sailing technology for extended space travel are also covered, along with space sustainability. Pay attention to how crucial it is for future space exploration. Through the efficient integration of mission data and current research, this project seeks to address the dynamic landscape of space exploration in the industry and encourage future advancements in the exciting field of space aeronautical engineering. Additionally, it aims to illustrate how navigation can have a transforming effect. Keywords: Space Exploration, Propulsion Technology, Interstellar Travel, Spacecraft Navigation, Attitude control, Trajectory optimization, Material Durability, Deep Space Missions, Interplanetary Travel, Solar Radiation Effect, Photon Pressure, Solar sail Deployment, Orbital Mechanics, Continues Thrust.

Trihybrid nanofluid flow through nozzle of a rocket engine: Numerical solution and irreversibility analysis

Research Problem: The research investigates the process of heat transmission and the production of entropy within the regenerative cooling channel of a rocket engine. The primary focus of the investigation is on the use of nanoparticles (titanium dioxide, copper oxide, and alumina dioxide) that are dispersed in water as the base fluid. Within the context of the cooling system, the research endeavors to gain an understanding of the influence that these nanofluids have on hydrothermal performance and entropy production. Methodology: The investigation transforms similarity to reduce the governing equations to a non-dimensional form. We solve the altered equations using a shooting technique and the reduced Kutta-4 (RK-4) numerical method. With a particular focus on the Nusselt number and entropy generation number, graphic representations highlight the important parameters affecting hydrothermal performance. Implications: The results emphasize how well water-based nanofluids work, especially titanium dioxide (TiO2), as a coolant in rocket engines. The work also clarifies how different parameters affect the entropy creation in the system. The importance of this study is in its possible use to improve the design of regenerative cooling systems in aeronautical engineering, therefore raising overall performance and efficiency. Future work: More investigation into the manipulation of fluid characteristics and nanoparticle concentrations should improve rocket engine cooling efficiency even more. Alternative nanoparticle materials and their impact on entropy generation and heat transport might also be investigated. Moreover, experimental validation of the numerical results can offer important information for the practical use and validation of the suggested approaches.

Preface

It is our great pleasure to present the proceedings of the 8th International Conference on Mechanical, Aeronautical, and Automotive Engineering (ICMAA 2024), held virtually from February 2-4, 2024. We are happy to report that the meeting went exceptionally smoothly, safety protocols were followed, and an enjoyable and stimulating meeting was held. This year, ICMAA is sponsored by Singapore Institute of Electronics (SIE), with support from Sichuan Institute of Electronics, China, National Taiwan University of Science and Technology and Multimedia University, Malaysia, with an emphasis on theoretical and practical aspects, ICMAA 2024 provided a comprehensive platform for researchers and scholars to share their knowledge, insights, and experiences. The Proceedings of the conference contain many excellent papers representing the participants’ research and innovative thinking. All the papers have been checked through rigorous review and processes to meet the requirements of publication. These papers featured a wide range of topics, including but not limited to Applied Mechanics, Automation, Aerospace Propulsion, Computational Fluid Dynamics, Combustion and Emission Control, and Energy Management. We want to express our sincere gratitude to all the authors who contributed their papers to ICMAA 2024. We would also like to thank the members of the organizing committee, the technical program committee, and the reviewers for their hard work and dedication in ensuring the quality of the conference. We hope that the papers included in these proceedings will serve as a valuable resource for researchers and practitioners in mechanical, aeronautical, and automotive engineering. We also hope that ICMAA 2024 has provided a platform for fruitful collaborations and new research initiatives. We look forward to welcoming you to future editions of ICMAA and continuing our journey of exploration and discovery in mechanical, aeronautical, and automotive engineering. Prof. Jia-Yush Yen National Taiwan University of Science and Technology, Taiwan Conference Chair of ICMAA2024 List of Organizing Committees and Peer Review Statement are available in this Pdf.

Influence of hybrid nanofiller on elastic behavior and stiffness of basalt/E-glass MWCNTs/SiO2 hybrid nanocomposites

Sustainable material development techniques help in finding and employing sustainable materials without compromising quality. Composite materials are crucial in structural design, automotive manufacture, and aeronautical engineering. Advanced materials that use reinforcement and filler ingredients must be developed strategically to improve strength and performance. Hence, this study develops hybrid nanocomposites with hybrid nanofillers (MWCNTs and SiO2) and hybrid fibers (basalt and E-glass) and optimizes the competition to maximize elastic behavior and stiffness. Using a hand layup approach, composite samples were made by altering mass fractions of two filler materials (0%, 1%, 1.5%, and 2% by weight) and epoxy matrices (40%, 38%, 37%, and 36%). Shore D hardness and dynamic mechanical analysis (DMA) were used to evaluate the composites. The storage modulus, loss modulus, and damping coefficients are examined using DMA. Specifically, the largest storage modulus is 4.86 × 1010 Pa at 61 °C, while the peak loss modulus is 1.01 × 1010 Pa at 80 °C. The highest damping coefficient is 0.25. Note that 1.5% MWCNTs and SiO2 filler materials independently contribute to the excellent storage and loss modulus. However, an outstanding damping coefficient was achieved without filler materials. The highest achieved shore D hardness value is 88. Filler materials are used to achieve this high hardness.