Association Journal of Interdisciplinary Technics in Engineering Mechanics
Welcome to the Association Journal of Interdisciplinary Technics in Engineering Mechanics!(ISSN-3049-0898) Our journal is a leading platform dedicated to advancing the understanding and application of engineering mechanics through interdisciplinary collaboration. We aim to bridge the gap between various technical fields, fostering innovation and providing a comprehensive resource for researchers, practitioners, and academics alike. Frequency of the journal would be 4 issues per year. Association Journal of Interdisciplinary Technics in Engineering Mechanics is maintained and published by Consortium for Innovators in Engineering & Technology ISSN-3049-0898 Frequency: Quarterly (4 issues per year) Language of publication: English Domains: Multidisciplinary Year of Starting: 2023 Mode of Publication: Online Only
Optimization of Drag Reduction Using BioInspired Surface Textures in Subsonic Flow
This research produced an adaptable Drag-Reducing (DR) surface via biomimetic buildings, motivated by dolphins' extensible skin and the lotus leaves' hydrophobic properties. The concept integrates a longitudinal groove foundation with hydrophobic flexible substances, using a hydraulic actuator for dynamic surface changing. This method successfully incorporates non-smooth buildings, adaptable substrates, and hydrophobic DR methods, attaining a DR of up to 29% at a Subsonic Flow (SSF) speed of 0.3 m/s. This technological innovation successfully approaches DR across diverse SSF speeds in intricate underwater settings.
Copyright (c) 2025 Association Journal of Interdisciplinary Technics in Engineering Mechanics
Heat Transfer Simulation in Mechatronic Devices Using Fourier Heat Conduction Analysis
Thermal management has become a fundamental design challenge in mechatronic systems because tighter packaging and higher power levels push component densities beyond previous norms. If heat spreads unchecked, devices may operate sluggishly, circuits may grow brittle, and the risk of electrical arcing or burns rises sharply. To address these issues, the present study introduces a simulation platform grounded in Fourier’s heat-conduction law, aimed specifically at cylindrical assemblies common in motors or smart modules. Modelling begins with a layered scheme that discretises each shell according to geometry and material, then merges analytical solutions with finite-element analysis run in MATLAB and COMSOL. Engineers first specify part dimensions, next allocate thermal properties, followed by imposing temperature, convection, or insulation limits, and finally march forward or backward in time until steady or transient fields appear. Side-by-side tests against physical sensors confirm that the tool quantifies temperature fields with satisfactory fidelity. Take the copper winding: predicted and measured peak at about 300 °C differ by only 1 °C (297 °C observed). Surrounding interfaces including thermal paste stay within a reasonable band too, yielding an overall root-mean-square error of only 2.41 °C across the assembly. Such performance proves the framework reliable for locating thermal hotspots, estimating heat-loss rates, and guiding design changes like thicker insulation or alternative alloys before hardware is built. The new Fourier-based simulation approach offers a fast and physically realistic way to forecast and manage heating patterns in mechatronic assemblies. Because it runs quickly, the method can be embedded in real-time thermal sensors and adaptive controllers, positioning it for cutting-edge robotics, automotive platforms, and factory automation.
Heat transfer simulation, Fourier heat conduction, mechatronic devices, thermal modelling, temperature distribution, numerical simulation, MATLAB, COMSOL, thermal optimization, steady-state conduction, transient heat flow, multi-layered components, heat flux analysis, smart systems, thermal management.
Sensor Fusion and Control Algorithm Design for Precision Mechatronic Arms in Medical Robotics
Mechatronic systems are becoming more essential in applications, necessitating great accuracy. Although a robot functions with fundamental sensor input in controlled settings, attaining micro-level precision necessitates more extensive data integration, particularly in dynamic situations. Integrating data from several sensors is essential for enhancing a robot's positioning precision, since the precision of a single sensor type is inadequate. The domain of micro-positioning introduces novel issues and tasks that have been progressively examined in the literature released between 2015 and 2025. Micro-positioning is a sophisticated process encompassing physical drift, ambient influences, and sensor signal inaccuracies. Hybrid fusion is an imaging fusion methodology that integrates components at several levels. Effective robot deployments in these circumstances necessitate integrating various sensors and ensuring accurate data fusion. This requires advanced fusion computations, multiple sensors, exact calibration techniques using sensor fusion, and sophisticated data processing methods. Sensor data fusion methods for precise robot micro-positioning are investigated in this work based on the literature. The focus is on the investigated detectors, the applied synthesis methods, developed computations, and how to find current shortcomings for possible system improvement. The results of the collected ideas and the exchanges are presented.
Sensor Fusion, Precision Mechatronics, Medical Robotics, Control Algorithm.
Flow Instability Modelling in Air foils Using the k Epsilon Turbulence Model Algorithm
It is paramount to understand and predict flow instability over the surface of the air foils to improve performance and stability in aerospace engineering. This study is focused on the investigation of flow instabilities using the k-ε turbulence model; a two-equation turbulence closure approach and one of the most widely used turbulence models. Computational fluid dynamics (CFD) tools were utilized to simulate a boundary layer's separation, transition, and reattachment of an air foil and under a variety of both Reynolds numbers and angles of attack. The features of the k-ε model being robustly solved turbulent kinetic energy and its dissipation rate provide insight into areas of flow instability in both the wake and near wall regions. Validation will be performed against laboratory experimental data to understand the accuracy of the model. The results provide confidence in the robustness of the k-ε in capturing the key instability zones and allow for better optimization in design for air foil applications in both the subsonic and transonic flight regimes.
K-Epsilon Turbulence Model, Air Foil, Flow Instability, Cfd Simulation, Boundary Layer Separation, Aerodynamic Modelling, Turbulence, Reynolds Number, Flow Transition, Wake Dynamics.
Design of a Bio-Inspired Legged Robot for Rough Terrain Locomotion
This research presents a unique biologically motivated control technique for synchronizing the planning of a quadruped robot’s gaits and foot Workspace Trajectory (WT), based on Central Pattern Generator (CPG) Neural Network (NN) WT (CPGNNWT). Initially, a foot workspace trajectory is designed using the Denavit-Hartenberg (D-H) nomenclature and inverse kinematics, offering benefits such as little mechanical shock, fluid motion, and streamlined trajectory. This work proposes an enhanced CPG using Hopf oscillators for seamless gait planning. A NN is ultimately developed and trained to transform the CPG output into the predetermined WT so that it can concurrently use the benefits of the CPG-based approach in gait prediction and the WT-based approach in foot trajectory preparation. Virtual prototype simulations and tests with actual quadruped robots are conducted to evaluate the efficacy of the suggested control technique. The findings indicate that the CPG effectively and efficiently regulates the quadruped robot's gait via internal variables. At the same time, the foot path aligns closely with the predetermined WT.
Bio-Inspiration, Legged Robot, Rough Terrain, Locomotion.
Design Optimization of Thermal Systems Using the Nusselt Number Correlation Approach
Thermal System Design Optimization is an important factor in the improvement of energy efficiency and functional reliability in engineering applications that involve typical thermal systems such as heat exchangers, HVAC systems, and electronic cooling devices. This study outlines a systematic approach to enhancing performance in thermal systems based largely on the Nusselt number, which is a commonly employed design criterion. To gauge thermal performance under several conditions of flow, the Nusselt number is a suitable measure of convective heat transfer. Therefore, the approach described in this study, in terms of geometry, fluid and thermal parameters, will include empirical and semi-empirical correlations of both laminar flow and turbulent flow. The Reynolds number, Prandtl number, surface properties, and several other factors were modified to optimize the heat transfer rates considering: a sensitivity analysis, parametric optimization to reducing pressure drop and energy consumption. The validation of the proposed Framework is based on configurations of microchannels and case studies of portable heat exchangers. The results demonstrate that using Nusselt-based correlations to optimize thermal systems provides an improved, more efficient, and scalable way to enhance thermal design for both conventional and advanced heat transfer systems.
Thermal System Optimization, Nusselt Number Correlation, Convective Heat Transfer, Reynolds Number, Prandtl Number, Heat Exchanger Design, Microchannels, Pressure Drop, Empirical Correlation, Energy Efficiency.
Vision-Based Navigation System for Autonomous Ground Robots in Dynamic Environments
Autonomous Ground Robots (AGRs) in unstructured settings are an unresolved issue that necessitates an intelligent agent's capacity to identify and respond to possible impediments within its vicinity. Barriers include automobiles, people, or fixed items in an ordered setting, such as highway or urban navigation, and unexpected static and dynamic obstacles in informal settings like woodland roads. The second condition is often more challenging to manage, owing to its greater uncertainty. This work presents a vision-based dynamical methodology for route planning and guidance of a quadruped AGR operating in a disordered setting, especially on a forest road. The computational dynamics methodology employs a recurring neural network that utilizes a sensor for data acquisition, generating sequences of prior depth sensor measurements and forecasting upcoming measurements over a limited temporal interval. The research evaluates the methodology against other leading techniques in obstacle-driven path planning methods. It conducts ablation tests to assess the effects of architectural modifications on the model elements. This shows that the approach attains enhanced performance in effectively creating collision-free paths for the clever agents.
Vision-Based Navigation, Autonomous Ground Robots, Dynamic Environment, Navigation.
Stress Distribution Estimation in Spur Gears Using the Lewis Equation-Based Design Algorithm
For enhancing the performance and life of gears, an accurate estimate of stress distribution in spur gears is important. In this study, a systematic procedure is presented for estimating bending stress in spur gear teeth by using a design algorithm based on the Lewis equation. In this procedure, the gear spatial parameters, material data, and loading conditions are inserted into a computer framework to determine the maximum allowable stress at points along the tooth profile. Adjustments made to Lewis' equation account for the factors of shape and dynamic load and produce good results over previous conventional methods. Finite element analysis (FEA) was carried out to facilitate the illustration of stress contours in the engaged gear mesh and prove theoretical results. The comparison clearly supports a close degree of correlation between the analytical results and simulation results and demonstrates the application of the proposed algorithm. This work supports new advances in the technology of gear design by producing a consistent, well defined, and scalable process for stress analysis while specifically addressing the requirements of high-load mechanical systems and precision mechanical systems.
Spur Gears, Stress Distribution, Lewis’s Equation, Bending Stress, Gear Tooth Design, Finite Element Analysis (Fea), Shape Factor, Mechanical Transmission, Gear Optimization, Design Algorithm.
Cavitation Effect Prediction in Pumps Using the Rayleigh Plesset Bubble Dynamics Algorithm
Cavitation is a serious phenomenon in fluid machinery, especially centrifugal pumps, where vapor bubbles generated followed by the collapse of those vapor bubbles results in adverse operational impacts and damage to the pump itself. Accurately predicting the impact of cavitation is important in improving pump design, pumping efficiency, and reliability of operational performance. This article develops a computational technique for cavitation impact predictions using the Rayleigh–Plesset bubble dynamics algorithm that mathematically describes the behaviour of a single spherical vapor bubble in a liquid under varying pressure fields.This work combines the Rayleigh–Plesset equation with real-time pressure and velocity profiles in order to model transient bubble behavior; this combination enables accurate predictions of cavitation onset, development and collapse behavior. The framework developed was validated against experimental data and benchmark computational fluid dynamic (CFD) simulations indicating excellent agreement in predicting cavitation zones and intensity.The algorithm also offers some insight into the effect of flow velocity, pressure gradient and fluid properties affecting the severity of cavitation. This capability enables a more proactive approach to optimizing pump design and mitigating cavitation. The results confirm that the algorithm is capable, robust, and able to represent real-world pump systems, which must frequently involve dynamic operating conditions.
Cavitation Prediction, Rayleigh–Plesset Equation, Bubble Dynamics, Pump Design, Fluid Machinery, CFD Validation, Cavitation Erosion, Flow Simulation.
Development of an Adaptive Gripper Using Shape Memory Alloys for Industrial Robotics
Industrial Robotic Grippers (IRG) with elasticity have significant advantages in grasping items with irregular shapes or fragility compared to conventional rigid gripping devices. The primary constraints of these systems are the diminished gripping force due to the characteristics of soft motors and the absence of variable rigidity in IRG devices, which restricts their applicability across a broader spectrum of uses. This article presents a soft gripper using Shape-Memory Alloy (SMA) technology, with three robotic digits that enable compliant gripping at moderate stiffness and secure holding with elevated rigidity. Each IRG finger (Fr) primarily included rigid components and two variable rigidity joints, affixed to the base at a predetermined angle. The paraffin, used as a variable rigidity substance in the joint, is thermally manipulated to alter the rigidity of the IRG Frs. Experimental results indicate that a single IRG Fr gets an estimated 18-fold increase in stiffness. Every finger, possessing two joints, proactively attains various postures by modulating the stiffness of the joints and activating the SMA wire. Utilizing these concepts, the gripper can grasp items of multiple forms and a wide range of weights, with the most significant gripping force enhanced to almost tenfold with adjustable stiffness connections. The final test is performed to verify the changing stiffness of the suggested soft grippers while grabbing an item.
Adaptive Gripper, Shape Memory Alloys, Industry, Robotics.
Trajectory Planning in Articulated Robots Using the Lagrangian Dynamics Modelling Technique
Accurate trajectory planning is still essential if articulated robots are to move with the precision, efficiency, and smoothness needed in busy or tightly packed work areas. In response, this study introduces a novel planning framework rooted in Lagrangian dynamics, using that theory to guide the creation of near-optimal paths for multi-joint robot systems. Because the approach is built on first principles, it can naturally include actuator limits, inertial coupling, and nonlinear contact forces, giving engineers a clear and workable picture of how a robot will behave in practice. The motion description is then shaped by combining these dynamic equations, obtained through the classic Euler-Lagrange method, with higher-level constraints expressed both in joint angles and in Cartesian space. Motivated by recent progress in optimization, the authors deploy a hybrid planner that balances time-jerk minimization with model-predictive control, thus accommodating tasks ranging from slow waypoint traversal to rapid equipment reconfiguration. Comprehensive experiments on simulated robotic arms and wheeled platforms show improvements of up to 30% in tracking precision and of 25% in energy consumption, even in the presence of hard nonlinear bounds. These results confirm that the Lagrangian approach can generate robust, real-time trajectories suitable for demanding industrial automation, surgical robotics, and autonomous space vehicles.
Articulated Robots, Trajectory Planning, Lagrangian Dynamics, Euler–Lagrange Equations, Robotic Manipulators, Dynamic Modeling, Optimal Control, Joint Space Interpolation, Nonlinear Constraints, Industrial Robotics, Model Predictive Control.
Failure Mode Analysis of Composite Leaf Springs Under Dynamic Loading Conditions
This research delineates the typical configuration of the longitudinal Composite Leaf Springs (CLS) and the stress experienced by its various components. When analyzed with force evaluation, many failure modes may manifest in the central and terminal sections of the CLS. Attention must be directed towards the stress accumulation in the clamping region near the center of the leaf spring, resulting from U-bolt pre tightening. At the terminus of the CLS, sufficient lengths between bolt holes and edges must be maintained, and consideration should be given to the concentrated stress induced by the bolt. In the spring layout, the static rigidity of the CLS may be suitably augmented to guarantee that the suspension has enough offset frequencies. Simultaneously, it is essential to consider the resin’s glass transition temperature (Tg), which is recommended to exceed 80 °C.
Failure Mode Analysis, Leaf Springs, Dynamic Loading, Composite.
Vibration Control in Rotating Shafts Using Modal Analysis and PID Feedback Control Algorithm
Despite their importance in numerous industrial applications, rotating shafts are susceptible to dynamic instabilities and vibrations, which may damage the structure, disrupt operational efficiency, and shorten system lifespan. This research provides a holistic solution for vibration control of rotating shafts using modal analysis in conjunction with a PID feedback control loop. Modal analysis is done to determine the shaft's natural frequencies and mode shapes in order to apply optimal damping. Separately, the PID controller is tuned to counteract real-time resonant vibration using displacement and velocity feedback from embedded sensors. Simulations as well as experiments have been performed, and they show that, at critical modes, there is a significant reduction in amplitude response, resulting in decreased settling times and improved stability of the system. This hybrid solution provides better dynamic performance with changes in operating conditions, making it applicable in predictive maintenance and real-time vibration control of rotating machinery.
Vibration Control, Rotating Shafts, Modal Analysis, Pid Controller, Feedback Control System, Dynamic Stability, Resonance Suppression
Robotic Motion Planning Using the Jacobian Matrix-Based Inverse Kinematics Algorithm
Planning a robot’s motion once meant mapping a static room; now it means sending a fragile drone through the living room and kitchen without leaving a dent. This work investigates Jacobian-Matrix-Based Inverse Kinematics as a toolbox for that job, testing how well it steers, stops, and resets robotic arms that must mimic human manipulation. The Jacobian acts like the machine’s translator, converting tiny wrist-fed velocity orders into joint twists almost instantaneously. When arms sport a dozen servos, though, that translation hides in gnarly nonlinear equations with no tidy algebraic answer. The iterative Jacobian trick sidesteps the mess by flattening the curve at every loop, nudging the hardware closer to the goal without a crystal ball. The paper spells out the Jacobian, plays with its pseudoinverse, and wraps a damping blanket around both to dodge singular corners and jittery solvers. Synthetic runs on a six-jointed testbed, then measures how straight the end effector walks, how many processor ticks each substep steals, and whether prints settle to a target within a human-acceptable blink. The experiments show that the Jacobian method minds the budget even in excess-joint kinematics, wraps movement in curves rather than corners, and adapts on the run when workspace furniture shifts or speed orders change. The paper also examines optimization procedures paired with the Jacobian technique to reduce both energy use and overall joint motion. Experiments that task the robot with avoiding obstacles and rearranging its path provide additional evidence of the method's robustness. Because it delivers the needed accuracy and flexibility, the approach is well-suited to industrial automation lines, surgical robots, and service platforms alike. In summary, the work positions Jacobian-based inverse kinematics as a broadly applicable strategy for high-performance robotic motion control
Robot Motion Planning, Inverse Kinematics, Jacobian Matrix, Robot Arm Movement, Joint Control, Target Position, Path Planning, Smooth Motion, Obstacle Avoidance, Real-Time Control, Robot Accuracy, Flexible Robot Control, Easy Robot Movements, Robot Direction, Robot Task Handling
Simulation of Turbulent Flow in Pipes Using the Navier-Stokes Solver with Finite Volume Method
Whether engineers are pushing fire hoses, jet fuel, or cold air through tubes, understanding how rough water actually moves inside pipes helps them design better cities, drill sites, and office towers. The team uses the Finite Volume Method, which boxes up fluid slices to maintain honest mass and force balances, to calculate the Navier-Stokes rules on a computer grid in order to track that whirling motion. Additionally, they use the k-epsilon turbulence model, which has been proven to work well for wild-flow plumbing, to add intelligence on the occurrence of random eddies when flow speed becomes unmanageable. A long circular tube that is fed with high-speed water is already bustling inside their virtual lab, much like it would hundreds of meters downstream. The borders of the tube are braced with pressures, temperatures, and speeds that correspond to rusty steel or plastic pipes in the field. Using the Simple method, a semi-implicit tool that tames the math lines and prevents unanticipated oscillations in the output, the code connects pressure and velocity without allowing either to dodge it. In order for everyone to see whether the model is effective, the team lastly determines whether adjusting grid density has any effect at all before stacking the computer results next to lab data and traditional computations. The findings vividly illustrate the fluid's movement within the pipe; they include information on the fluid's speed at various locations, pressure dips along its length, and the areas with the highest turbulence. Researchers are sure that the setup and calculations are sound because these statistics closely match recognized reference data. Overall, the modelling program operates fast and consistently for steady, rough pipe flow, and experts anticipate that it will be able to manage time-varying flow and twisted or shrinking ducts in subsequent experiments. For businesses that transport liquids or gases on a daily basis, these insights can assist engineers in improving pipe networks, reducing energy waste, and saving expenses.
Navier-Stokes, Dynamics, Velocity, Pressure Drop, Pressure-Velocity, Pipe Flow Simulation, Turbulence Flow
Topology Optimization for Weight Reduction in Structural Components under Static Loading
-Topological Optimization (TO) is a method for identifying the ideal configuration of a structure under certain boundaries and loading circumstances while preserving its original efficiency. Every building has a particular weight that is incorporated into the TO process. This study delineates the mathematical methodology for the TO of systems under self-weight conditions. This work examines the impact of self-weight on the topology of buildings under static loading circumstances, with a range of 200-20% of the fixed load values. The structures are meshed using quadrilateral 4-node components, and under self-weight conditions, the weight of every element is uniformly distributed to all nodes. The MATLAB implementation of the suggested mathematical method has been completed and contrasted with traditional structural issues. The penalization strategy is employed to ascertain the optimal distribution of substance and voids. The optimum criteria approach maximizes structures according to loads and boundary circumstances. Various computational instances have been examined to illustrate the impact of self-weight (SW) on static loading architectures and the ideal morphologies achieved by altering static loading with respect to SW.
Topology Optimization, Weight Reduction, Structural Components, Static Loading.
Joint Parameter Calculation in Robotic Arms Using the Denavit-Hartenberg Transformation Algorithm
Getting the joint angles and lengths just right is a must if robotic arms are going to move smoothly and hit their marks, especially in busy factories or delicate hospital rooms. In this paper, we rely on the Denavit-Hartenberg (DH) method, a clear step-by-step way to show how each arm segment sits in relation to the next, for our calculations. Instead of wrestling with every curve and corner, the DH scheme shrinks the job to four numbers for each pair of links: how long the link is, how much it twists, where the joint pivots, and how far the link starts from that pivot. By stacking these numbers into tidy transformation tables, we can reliably work out where a multi-jointed arm ends up most of the time. Here, we run the standard DH process on a mix of robot setups, from a simple three-joint arm to a whole six-joint rig. Our method walks through forming each matrix, adding them up, and finally showing the tool's tip sits in space relative to the base. When we compare the numbers that come out of the simulation with what we recorded in the real world, they line up closely, proving that DH still delivers the precision many modern jobs demand. The system now works hand-in-hand with inverse-kinematics tools so that planners can steer a robot in real time. Engineers kicked the code around in MATLAB and Python, and both show that the setup moves easily from one platform to another. In short, the Denavit-Hartenberg rules still provide a fast, solid way to figure joint angles and study motion, opening the door to more brilliant, more flexible robot brains. Looking ahead, the team plans to stretch the model so it also fits robots with extra joints or joints that bend in tricky ways
Joint Angle, Robotic Arm, Kinematics, Movement Steps, DH Parameters, Angular Motion, Actuator Control, Serial Manipulator, Motion Analysis, Pose Estimation
Design and Analysis of a Lightweight HighTorque Gearbox for Electric Vehicles
-This paper presents an optimization technique for high-torque gearbox (GB) cutting in electric cars, emphasizing input torque and torque fluctuations. This method facilitates vibration attenuation in Electric Vehicle (EV) GB. The research employs Tooth Contact Assessment (TCA) and Loaded TCA (LTCA) to examine the localization of meshing points, considering changes in GB tooth surfaces and distortions resulting from load. The research then formulates the maximum contact force equation using impact physics theory. A dynamic approach for the helical GB motion in the GB input phase is formulated utilizing the centralized mass approach, facilitating a comprehensive analysis of high-torque GB vibration features. Utilizing a genetic approach, the research enhances the tooth shape and parabolic modifying factors of the tooth flank, yielding excellent vibration-dampening surfaces to the teeth. Experimental findings across diverse input forces and torque indicate that the total vibration magnitude remains stable and less than traditional GB shaping techniques. Under varying circumstances, the root mean square of vibrational acceleration across the meshing line is 59.13 m/s and 21.44 m/s, respectively. The vibration torque along the connecting line is 21.44 m/s and 21.13 m/s under different torques, with 21.44 m/s being the minimum value. The mean amplitude of the melding force of impact is considerably reduced to 5026.3. This high-torque GB reshaping technique improves GB dynamics and dependability by accounting for input torque and torque variations and significantly reduces vibrations in EV GB arrangements. The research offers significant insights and approaches for creating and optimizing EV shifts, emphasizing a thorough acceleration enhancement.
Electric Vehicles, High-Torque, Gearbox, Lightweight.
Numerical Simulation of Cavitation in High-Speed Marine Propellers
As the Energy Efficiency Design Index (EEDI) criteria become more stringent, enhancing propeller (PP) efficiency has become critical in advancing environmentally sustainable vessels. Cavitation (CV) unavoidably transpires, diminishing the hydrodynamic efficiency of the PP and eroding the blade (BD) surface, resulting in heightened fuel consumption. Mitigating CV is essential for vessels to comply with the EEDI standard. This study examines the PP's fatigue (FQ) life and hydrodynamic efficiency at various CV numbers and velocities. The correlation between PP FQ lifespan and propulsion effectiveness under CV circumstances is reviewed. The Schnerr-Sauer mathematical framework is used as the CV concept in the experiment. The nominal stress technique (S-N method) is employed to determine the FQ durability of BDs. The PP is the subject of the study. The hydrodynamic efficiency of the PP under varying CV numbers is analyzed using the finite volume approach. The pressure on the BD’s exterior and wall shearing stress throughout the cycle are computed and then included in the dynamical process to determine the stress and strain of the PP via the finite element approach. The FQ lifespan of the PP is then determined using the S-N curve of the BD's materials. The study's reliability is confirmed by comparing the CV leads with experimental data from the Ocean Engineers Research Center for the ship at an average speed of 16.8 knots, where the CV amount in the wake area is 3.6, demonstrating excellent consistency. The results underscore the substantial influence of CV on BDs’ longevity and vibrational dynamics.
Numerical Simulation, Cavitation, Marine, Propellers
CFD Analysis of Turbulent Flow in Microchannels for Heat Exchanger Applications
Microchannel (MC) heat exchangers (MCHXs) are tiny, lightweight, and capable of delivering superior Heat Transfer (HT) efficiency. A significant issue with MCHXs is the uneven dispersion of two-phase refrigeration from the Header Area (HA) into the MC tubing. This problem is widespread in evaporation programs' intake HAs, where two-phase condensate is supplied into the MCHX tubes. Recent advancements in multiple-phase flow Computational Fluid Dynamics (CFD) have enabled the visualization and analysis of intricate multiphase flow patterns inside the MCHX HAs. This article uses the Hybrid Eulerian Multiphase (EMP) framework to simulate condensate dispersion in a two-phase fluid simulation. This model integrates the advantages of the Traditional EMP model and the Volume of Fluid (VOF) approach, with the former identifying scattered phases and delineating phase separation surfaces. The simulation area is partitioned into three phases. Two environments use scattered phase simulation, where a single stage is distributed inside another and vice versa. The third phase utilizes a comprehensive interface methodology to distinguish between the two stages. This study discusses implementing the Mixed EMP technique, providing a thorough explanation of the generated CFD simulation, involving the sensitivity evaluation of the sub-models and variables. The model is confirmed empirically by infrared thermal imagery. The flow pattern is analyzed, and the factors contributing to the uneven distribution are discovered. Design research is conducted for two vertical HAs: a Tube-Insertion HAs and a Loop HAs, which incorporates a loop into the former kind. The Loop HA demonstrates enhanced distribution efficiency. A sensitivity study is conducted to comprehend the impact of characteristics essential for enhancing shipping, including tube-insertion dimension, intake mass flow rate, and HAs loop diameters. This work aims to provide an exhaustive simulation methodology for the Has’ uneven distribution issue in MCHXs.
CFD, Microchannels, Heat Exchanger, Turbulent Flow.
Analysis of Structural Integrity in High-Rise Buildings Under Dynamic Load Conditions Using AI: A Computational Perspective
The structural integrity of high-rise buildings under dynamic load conditions, such as earthquakes, wind, and other environmental factors, is critical to ensuring safety and resilience. Traditional methods for assessing these conditions often rely on static or generalized models, lacking the precision needed for real-time and complex scenarios. To address these limitations, this study proposes a Dynamic Load Conditions using Artificial Intelligence (DLC-AI) framework, which integrates advanced AI algorithms to model, predict, and analyze dynamic stress and strain in high-rise structures. The framework leverages real-time data, machine learning models, and computational simulations to improve predictive accuracy and adaptive responses to varying load conditions. Application of DLC-AI demonstrates enhanced accuracy in predicting structural weaknesses and mitigating potential risks. Findings reveal that the proposed method significantly improves structural resilience, reduces response times during emergencies, and provides architects and engineers with actionable insights for sustainable urban development.
Buildings, Dynamic Load, AI, Environmental Factors.
Copyright (c) 2024 Association Journal of Interdisciplinary Technics in Engineering Mechanics
Design and Development of Data Driven Intelligent Predictive Maintenance for Predictive Maintenance
Industrialists generally believe that maintenance is a necessary evil. A significant portion of all manufacturing systems' overall operating costs are related to maintenance. Industrial manufacturing businesses are severely impacted by the loss of production time and product quality brought on by an ineffective maintenance strategy. With the introduction of Industry 4.0, IoT-based data-driven automated remote-controlled operations and digitalised maintenance methods can be implemented by utilising cyber-physical systems methodologies. Maintenance scheduling and shop floor job allocation can be made simple using an IoT-based intelligent decision support system for machinery health management. One reliable way to maintain the health of machines and the quality of products is through predictive maintenance. Predictive maintenance uses machinery condition monitoring data, such as component vibrations, temperature, acoustic emissions, etc., to gain insights into the actual operating condition of the manufacturing system rather than depending on in-plant average life statistics or industrial field failure data. Real-time equipment status monitoring data collection and data acquisition from any location are made possible by developments in sensor technology and Internet of Things connectivity. Predictive maintenance of machine tools is becoming increasingly popular in the industrial sector as a way to increase production rates and improve tolerance of machined products. However, industrialists are discouraged from using predictive maintenance due to the high installation costs of the additional instruments and the complexity of computational tools. AI algorithms and other data-driven prognostics methods require little technical understanding of how machinery works and how failures occur. A promising AI computational approach for RUL estimation and machinery health prognostics is deep learning. However, there are numerous difficulties in putting deep learning algorithms for equipment health prognostics into practice.
IOT, Predictive Maintenance, Machine, Deep Learning.
Mechanical Component Design: A Comprehensive Guide to Theory and Practice
Any framework configuration decides the upsides of the plan boundaries to play out the predetermined assignments. The framework execution may fluctuate around its desired output due to uncertainties. Some of these uncertainties can be controlled while designing the system. The remaining uncertainties are not in control of the designer and are considered as noise. When the system is designed considering these uncertainties, the fluctuation around the desired output can be minimized. Robust design is a technique that ensures that the system will have minimum fluctuation around the desired performance affected by vulnerabilities. The powerful plan of system guarantees that the component will play out the predefined task under impact of vulnerabilities. In this research, a methodology for optimum robust design of mechanism is proposed and discussed, which designs optimum link lengths alongside the ideal connection length resiliences and ideal joint clearances. A technique for powerful plan improvement of component is proposed by considering the observations of parametric analysis of mechanism and robust design using the Taguchi method. The design parameters considered for robust design are all the link lengths, tolerance for all the link lengths and the joint clearances at the two closures of the coupler interface. The methodology is designed to work in loops, in the outer loop the optimization algorithm generated the population as a set of design parameters and in the inner loop, each set of design parameters from the population is analysed for robustness. In the proposed methodology, the joint clearance is considered as a clearance link. The orientation of the clearance link is considered in two ways, randomly orientated in the clearance circle and exactly determined by the dynamic force analysis.
System Mechanism, Taguchi Method, Mechanical Component.
Optimizing Energy Efficiency in Wireless Power Transmission Systems for Industrial Applications
Optimizing energy efficiency in wireless power transmission (WPT) systems is crucial for industrial applications, where energy consumption directly impacts operational costs and sustainability. Wireless power transmission offers a convenient and scalable solution for powering industrial equipment without physical wiring. However, existing WPT systems face significant challenges, including low transmission efficiency over long distances, interference from surrounding environments, and the high cost of energy loss during the transmission process. These limitations hinder the widespread adoption and effectiveness of WPT in industrial settings. To address these issues, the proposed method introduces the Industry-Based Wireless Power Transmission (I-WPT) system, a novel framework designed to enhance energy efficiency in industrial applications. The I-WPT system incorporates advanced algorithms and optimized power transfer protocols to minimize energy losses and ensure stable, long-distance power transmission in complex industrial environments. The findings demonstrate that the I-WPT system significantly reduces energy loss compared to conventional wired and wireless power systems. The proposed method offers a sustainable, cost-effective solution for modernizing industrial power systems.
Wireless Power Transmission, Energy Efficiency, Industrial Applications, I-WPT System.
Advanced Material Selection and Structural Design for Sustainable Manufacturing of Automotive Components
The selection of advanced materials and structural design is critical to achieving sustainability in automotive manufacturing. By integrating innovative materials with optimized designs, manufacturers can address environmental concerns while enhancing vehicle performance and durability. Existing methods often rely on traditional materials and design processes that result in high energy consumption, increased emissions, and limited recyclability, leading to unsustainable production practices. A novel framework, Structural Design for Sustainable Manufacturing (SD-SM), is proposed to resolve these challenges. The SD-SM framework emphasizes using lightweight, high-strength, and recyclable materials combined with computational design techniques like topology optimization and finite element analysis. This integration reduces material wastage and ensures superior structural integrity. The proposed method enables manufacturers to develop automotive components with reduced environmental impact while maintaining or improving functionality. This approach aligns with global sustainability goals and provides economic advantages through cost savings and compliance with environmental regulations. Thus, the proposed method establishes a pathway for sustainable automotive manufacturing, fostering innovation while preserving environmental integrity.
Sustainable Manufacturing, Advanced Materials, Structural Design, Automotive Components
Intelligent 3d Printing for Sustainable Construction
Buildings are constructed layer by layer using the 3D printing technique, which involves extruding mortar through a large-scale 3D printer. The motivation behind this study is to examine the capability of 3D imprinting in the structure area and its overall population's view. This study looks at the developing utilization of 3D printing in the development area, accentuating the potential impacts and hardships the area might experience. This study takes a gander at how 3D printing can possibly totally change ordinary structure procedures, highlighting both its cost-saving and sustainability advantages. Reducing material waste, addressing the global housing shortage, and lowering greenhouse gas emissions are all covered. The study investigates the factors influencing interest in and investment in 3D printing technology through in-depth literature reviews and interviews with professionals in the field. It also examines common misunderstandings about 3D printed structures and identifies areas that require more study, particularly in the areas of environmental concerns and material development. Among these misconceptions are the notions that the process is "unfinished" or that all 3D printed homes must have the same appearance. This study intends to inform the general advantages and difficulties of the technique in the quest for better sustainable and effective building practices by offering insights into the future market for 3D printing.
Sustainable Construction, 3D Printing, Greenhouse Gas Emissions, Concrete Technology, Affordable Housing, Construction Industry
Seismic Innovations: Strengthening Tall Buildings with Advanced Earthquake-Resistant Technologies
Tall buildings are highly exposed to seismic risk, and their mitigation needs innovative solutions regarding their structural susceptibility. Advanced Earthquake-Resistant Technologies (AERT) offer revolutionary solutions to mitigate such risks. The existing methods are inapplicable because they cannot mitigate the dynamic loads precisely, hence increasing the structures' vulnerability during such seismic events. To overcome these limitations, the proposed AERT framework employs smart materials, energy dissipation devices, and online monitoring technologies. The framework improves the resilience of buildings with seismic forces and consequent damage through adaptive dampers, base isolators, and AI-driven analysis. This method has been implemented to clearly show its ability to decrease structural stress caused by earthquakes and enhance safety. Building stability, repair cost, and occupant safety are improved significantly with AERT, thereby significantly developing seismic engineering of urban infrastructure. Therefore, This research finds a pathway to more resilient, sustainable construction in earthquake-prone regions.
Tall Buildings, Earthquake, Dynamic Loads, Smart Materials.
Thermodynamics of Mechanical Systems Principles and Applications
The ability of a dynamical system to generate changes (motion) in both its own system state and the system states of its surrounds is measured by energy, a concept that forms the basis of our comprehension of all physical processes. The laws controlling energy flow between bodies and energy transformations between different forms are the focus of the physical science field of thermodynamics. The basic captures these laws of energy flow. The first and second rules of thermodynamics are two of these principles. The first law of thermodynamics asserts that the net system energy is conserved amid all system transformations and provides a clear formulation of the equivalency between heat and work. Energy can therefore only be changed starting with one structure then onto the next; it can't be made from nothing or annihilated. A critical maxim of the investigation of intensity, the law of protection of energy isn't a mathematical truth but rather the result of an incalculable accumulation of observations over the history of our civilization
Thermodynamics, Mechanical Systems, Principles, Application.
Machine Design a Systematic Approach to Designing Mechanical Systems
Now a day fabricating enterprise are attempting to work on layered exactness, surface completion and efficiency during the multioperation machining process which thus decreases scrap rate and creation cost. Installation assumes a significant part to work on the machined surface nature of machining activity. The apparatus and its components are the fundamental devices to hold, secure and limit the workpiece during different activities in the machining system. The finders and clips are the components of the apparatus and their positions are known as installation design. The ill-advised apparatus format builds the machining vibration which thusly influences the precision of the completed item. The precisely planned apparatus format helps the originator to limit vibration during machining so the required machining exactness can be accomplished. Generally, in the processing system, the irregular commitment of multi-tooth shaper with workpiece brings about vibration of the apparatus workpiece framework which influences the surface completion of the machined workpiece which thus decreases the nature of machining activity. This vibration is expanded at a more significant level when the recurrence of energizing of multi-toothed processing shaper relates with any of the regular frequencies of the installation workpiece framework and it prompts the state of reverberation. The vibration increments under these circumstances, which decreases machining precision and surface completion of the machined workpiece. Consequently, the issues connected with the plan of installation design are to be tended to by perceiving the powerful way of behaving of the apparatus workpiece framework
Machining System, Optimization, Computer Aided Design.
Fluid Mechanics for Mechanical Engineers: Fundamentals and Applications
Understanding the capabilities and changes of platelets and whole blood, as well as the interactions between platelets and the arterial wall, is crucial in the cardiovascular system, where biofluid mechanics plays a major role. Important aspects of central liquid mechanics that are important for comprehending the bloodstream in the context of the human circulatory system are presented. Experiments have shown how hemodynamics can affect the healing of varicose veins and aneurysms. A few other elements, including the vessel wall's construction, are also important. Basic analyses have demonstrated that the stream conduct is determined by the vessel wall's flexibility and calculation. Significant variations in speed indicate stream irritations that should be avoided. Physicians should understand hydrodynamic parameters such as shear loads, speed slopes, tensions, and stream proportions. They need also understand how the stream behaves in comparison to the wall and platelets, as well as speed disseminations. Platelets and lipids are the main cause of atherosclerosis, and these mechanical components are essentially responsible for their testimony. Plaques and aggregates are the result of blood cells interacting with blood arteries. These deposits are mostly located in artery bends and branches where there are areas of flow separation, secondary flows, and interruptions in blood flow. We provide studies on hemodynamic effects using flow wires, stents, or vascular surgical patches in an elastic silicone rubber model of the cardiovascular system. These investigations could be crucial for enhancing therapeutic and diagnostic uses.