Journal of Experimental and Theoretical Analyses

In this paper, we introduce the Levy Flight-enhanced Whale Optimization Algorithm with Tabu Search elements (LWOATS), an innovative hybrid optimization approach that enhances the standard Whale Optimization Algorithm (WOA) with advanced local search techniques and elite solution management to improve performance on global optimization problems. Techniques from the Tabu Search algorithm are adopted to balance the exploration and exploitation phases, while an elite reintroduction strategy is implemented to retain and refine the best solutions. The efficient optimization of LWOATS is further aided by the utilization of Levy flights and local search based on the Nelder–Mead simplex method. An Orthogonal Experimental Design (OED) analysis was employed to fine-tune the algorithm’s parameters. LWOATS was tested against three different algorithm sets: fundamental algorithms, advanced Differential Evolution (DE) variants, and improved WOA variants. Wilcoxon tests demonstrate the promising performance of LWOATS, showing improvements in convergence speed, accuracy, and robustness compared to traditional WOA and other metaheuristic algorithms. After extensive testing against a challenging set of benchmark functions and engineering optimization problems, we conclude that our proposed method is well suited for tackling high-dimensional optimization tasks and constrained optimization problems, providing substantial computational efficiency gains and improved overall solution quality. Full article

Springback represents the deflection of a workpiece after releasing the forming tools or dies, which influences the quality and precision of the final products. It is basically governed by the elastic strain recovery of the material after unloading. Most approaches only implement reverse bending to determine the final shape of the formed product. However, stretch plays significant role whe the blank is held by a blank holder. In this paper, an algorithm is presented to calculate the contributions of both stretch loads and bending moments to elastic deformation during springback for each element, and to combine them mathematically and geometrically to achieve the final shape of the product. Comparing the results of this algorithm for different sheet metal forming processes with experimental measurements demonstrates that this technique successfully predicts a wide range of springback with reasonable accuracy. The advantage of this approach is its accuracy, which is not sensitive to hardening and softening mechanisms, the magnitude of plastic deformation during the forming process, or the size of the object. The application of the proposed formulation is limited to long profiles (plane-strain cases). However, it can be extended to more general applications by adding the effect of torsion and developing equations in 3D space. Due to the explicit nature of the calculations, data-processing time would be reduced significantly compared to the sophisticated algorithms used in commercial software. Full article

This study introduced a systematic framework to develop practical design guidelines specifically for filament-based material extrusion of metals (MEX/M), an additive manufacturing (AM) process defined by ISO/ASTM 52900. MEX/M provides a cost-efficient alternative to conventional manufacturing methods, which is particularly valuable for rapid prototyping. Although AM offers significant design flexibility, the MEX/M process imposes distinct geometric and process constraints requiring targeted optimization. The research formulates and validates design guidelines tailored for the MEX/M using an austenitic steel 316L (1.4404) alloy filament. The feedstock consists of a uniform blend of 316L stainless steel powder and polymeric binder embedded within a thermoplastic matrix, extruded and deposited layer by layer. Benchmark parts were fabricated to examine geometric feasibility, such as minimum printable wall thickness, feature inclination angles, borehole precision, overhang stability, and achievable resolution of horizontal and vertical gaps. After fabrication, the as-built (green-state) components undergo a two-step thermal post-processing treatment involving binder removal (debinding), followed by sintering at elevated temperatures to reach densification. Geometric accuracy was quantitatively assessed through a 3D scan by comparing the manufactured parts to their original CAD models, allowing the identification of deformation patterns and shrinkage rates. Finally, the practical utility of the developed guidelines was demonstrated by successfully manufacturing an impeller designed according to the established geometric constraints. These design guidelines apply specifically to the machine and filament type utilized in this study. Full article

Hydrostatic transmissions are essential in applications demanding variable torque and speed, such as mining and agricultural machinery, due to their compact design, high power-to-weight ratio, and efficient variable speed control. Despite these advantages, their inherent nonlinearities and susceptibility to parametric uncertainties pose significant challenges for precise motion control. This study presents a comparative analysis of classical PID and robust H-infinity controllers for regulating the speed of hydraulic motors under varying torsional loads. A linearized uncertain system model is developed using upper Linear Fractional Transformations (LFTs) to capture key parametric uncertainties. A simplified H-infinity controller is designed to robustly manage system dynamics, particularly addressing phase lags induced by uncertain loads. Simulation results demonstrate that the H-infinity controller offers superior performance over the PID controller in terms of stability, disturbance rejection, and robustness to load fluctuations. This work contributes a practically viable robust control solution for improving the reliability and precision of electro-hydraulic systems, particularly in demanding, real-world environments. Full article

The Dynamic Stiffness Matrix (DSM) of a structure is a frequency-dependent stiffness matrix relating the actions (forces and moments) and displacements (translations and rotations) when the structure vibrates at a given frequency. The DSM may be used to find the natural frequencies, modes, and structural response. For many structures, including skeletal frames of prismatic members, exact transcendental expressions for the DSM are readily available. This paper presents a mathematical proof of a linear determinantal relationship between the DSM of a skeletal frame when it is undamaged, cracked, and hinged at the crack location. The rotational stiffness or flexibility of the crack also appears as a linear term. This relationship gives, for the first time, an explicit equation to directly calculate the stiffness of the rotational spring representing a crack from measured natural frequencies for any potential crack location. Numerical examples demonstrate that computing the DSM of the intact and hinged structures gives an efficient solution method for the inverse problem of identifying crack location and severity. This paper also shows that an approximate DSM based on a finite element model can be used in the same way, making this procedure more versatile. Furthermore, new approximate expressions for the natural frequencies of structures with very small or very severe cracks are derived. An interesting relationship between the square of the bending moment in an undamaged beam and the determinant of the DSM of a hinged beam is also derived. This relationship, which can also be inferred from previous work, leads to a better understanding of the effect of crack location in specific vibration modes. Full article

Additive manufacturing (AM) technologies have witnessed remarkable advancements, offering opportunities to produce complex components across various industries. This paper explores the potential of AM for fabricating bipolar plates (BPPs) in fuel cell or electrolysis cell applications. BPPs play a critical role in the performance and efficiency of such cells, and conventional manufacturing methods often face limitations, particularly concerning the complexity and customization of geometries. The focus here lies in two specific AM methods: the laser powder bed fusion of metals (PBF-LB/M) and material extrusion of metals (MEX/M). PBF-LB/M, tailored for high-performance applications, enables the creation of highly complex geometries, albeit at increased costs. On the other hand, MEX/M excels in rapid prototyping, facilitating the swift production of diverse geometries for real-world testing. This approach can facilitate the evaluation of geometries suitable for mass production via sinter-based manufacturing processes. The geometric deviations of different BPPs were identified by evaluating 3D scans. The PBF-LB/M method is more suitable for small features, while the MEX/M method has lower deviations for geometrically less complex BPPs. Through this investigation, the limits of the capabilities of these AM methods became clear, knowledge that can potentially enhance the design and production of BPPs, revolutionizing the energy conversion and storage landscape and contributing to the design of additive manufacturing technologies. Full article

This paper presents a new computational library for pneumatic circuits, written in the specialized circuit-oriented language “Modelica”, and executed within an open-source IDE, “OpenModelica”, freely available for downloading on the Internet. The library focuses on the problem of energy efficiency and energy savings (two different concepts, that we intend to clarify in the text). The idea is to use the Modelica scripts to simulate typical circuits, known by their energy-efficient designs. We reason that air throttling within valves is one of the great challenges when it comes to energy losses. Also, we argue that compressed air reuse can be seen as a means of increasing efficiency, basically through replacing air throttling with counter-pressure velocity control. A simplified version of the developed Modelica library is made available to the reader in the ^{Appendix A}, to be used with new scripts and adapted to different realities. In our view, in many situations, open-code Modelica programs may constitute an alternative to proprietary software, where the mathematical models of components are mostly hidden from the end user. Theoretical experiments are carried out, focusing on energy management. The results show that the Modelica library hereby presented is solid, with great prospects of future development. They also show that energy efficiency in pneumatic circuits, at times, comes with the cost of poorly controlled velocity and pressure at the actuator, which requires a careful analysis by the designer, before an actual implementation. Full article

Pillar-to-pillar dashboards have become common in modern electric vehicles. These dashboards are made of liquid crystal displays (LCDs), of which backlight units (BLUs) are an integral part. Particulate contamination inside BLUs can lead to either an aesthetic or functional failure and is in consequence a part of quality control. Automatic optical inspection (AOI) was used to detect particulate matter to enable a process chain analysis to be carried out. The investigation showed that a high percentage of all contaminants originated from the assembly of the edge/side lightguide. The implementation of an additional cleaning process was the favored countermeasure to reduce the contaminants. The objective (cleanliness requirement) was to remove all contaminants larger than 100 µm from the lightguide with contactless (non-destructive) cleaning methods. The preferred cleaning methods of choice were compressed air and CO₂ snow jet cleaning. This work investigates the cleaning efficacy of both cleaning methods under consideration of the following impact factors: distance, orientation (inclination) and speed. The central question of this paper was as follows: would cleaning with compressed air be sufficient to meet the cleanliness requirements? In order to answer this question, a cleaning validation was carried out, based on a Box–Behnken design of experiments (DoE). To do so, representative test contaminants had to be selected in step one, followed by the selection of an appropriate measurement technology to be able to count the contaminants on the lightguide. In the third step, a test rig had to be designed and built to finally carry out the experiments. The data revealed that CO₂ was able to achieve a cleaning efficacy of 100% in five of the experiments, while the best cleaning efficacy of compressed air was 89.87%. The cleaning efficacy of compressed air could be improved by a parameter optimization to 94.19%. In contrast, a 100% cleaning efficacy is achievable with CO₂ after parameter optimization, which is what is needed to meet the cleanliness requirements. Full article

The vibration response of a component, particularly the frequency response of the component, can be used in the determination of the loss factor damping, η, due to energy dissipation and the elastic modulus (E). The ASTM E756-04 standard provides the methodology and the guidance for the determination of the loss factor damping and elastic modulus experimentally. This standard specifically calls for the use of a beam with a rectangular cross-section. Also, the theoretical formulation developed there is based on such a beam cross-section. Here, in this paper, the theoretical formulation and numerical simulation for determining the loss factor damping and elastic modulus are a derivation of the methodology used in the ASTM standard and other R&D work, but for a circular plate configuration. The delta change derivation, both theoretically and numerically, is proven to be accurate and validated here. This method is useful in the characterization of materials that have applications in structural vibration, aerospace subcomponents, micro and mini sensory devices, medical devices, and many other areas. Similar to the ASTM standard, the materials could include metals, ceramics, rubbers, plastics, reinforced epoxy matrices, composites, and woods. This paper mainly formulates the technique via numerical and computational methods. It is the intention of the author to also, as a future research agenda, experimentally produce data that can be correlated with this theoretical and numerical methodology. Full article

Precise flow measurement is crucial in fluid power systems. Especially in combination with pressure, hydraulic power can be particularly beneficial for predictive maintenance and control applications. However, conventional flow sensors in fluid power systems are often invasive, thus disrupting the flow and yielding unreliable measurements, especially under transient conditions. A common alternative is to estimate the flow rate using pressure differentials along a pipe and the Hagen–Poiseuille law, which is limited to steady, laminar, and incompressible flows. This study advances a previously introduced analytical soft sensor, demonstrating its ability to accurately determine the transient pipe flow beyond laminar conditions, without requiring a dedicated flow rate sensor. This method provides a robust and computationally efficient solution for real-world hydraulic systems by applying two pressure transducers. A key contribution of this work is the investigation of signal filtering, revealing that even a simple first-order low-pass filter with a 100 Hz cutoff frequency significantly improves accuracy, which is demonstrated for pulsation frequencies of 5, 10, and 15 Hz, where the filtered results closely match experimental data from a test rig. These findings underscore the soft sensor’s potential as a reliable alternative to traditional flow sensors, offering high accuracy with minimal computational overhead for a wide range of flow conditions. Full article

Stress is a natural response of the organism to challenging situations, but its accurate detection is challenging due to its subjective nature. This study proposes a model based on depth-separable convolutional neural networks (DSCNN) to analyze heart rate variability (HRV) and detect stress. Electrocardiogram (ECG) signals are pre-processed to remove noise and ensure data quality. The signals are then transformed into two-dimensional images using the continuous wavelet transform (CWT) to identify pattern recognition in the time–frequency domain. These representations are classified using the DSCNN model to determine the presence of stress. The methodology has been validated using the SWELL-KW dataset, achieving an accuracy of 99.9% by analyzing the variability in three states (neutral, time pressure, and interruptions) of the 25 samples in the experiment, scanning the acquired signal every 5 s for 45 min per state. The proposed approach is characterized by its ability to transform ECG signals into time–frequency representations by means of short duration sampling, achieving an accurate classification of stress states without the need for complex feature extraction processes. This model is an efficient and accurate tool for stress analysis from biomedical signals. Full article

Accurate flow measurement is critical for hydraulic systems because it represents a crucial parameter in the control of fluid power systems and enables the calculation of hydraulic power when combined with pressure data, which is valuable for applications such as predictive maintenance. Existing flow sensors in fluid power systems typically operate invasively, disturbing the flow and providing inaccurate results, especially under transient conditions. A conventional method involves calculating the flow rate using the pressure difference along a pipe via the Hagen–Poiseuille law, which is limited to steady, laminar, incompressible flow. This paper presents a novel soft sensor with an analytical model for transient pipe flow based on two pressure signals, thus eliminating the need for an actual volumetric flow sensor. The soft sensor was derived in previous research and validated with a distributed parameter simulation. This work uses a constructed test rig to validate the soft sensor with real-world experiments. The results highlight the potential of the soft sensor to accurately and computationally efficiently measure transient pipe volumetric flow based on two pressure signals. Full article

Regular aircraft engine inspections play a crucial role in aviation safety. However, traditional inspections are often performed manually, relying heavily on the judgment and experience of operators. This paper presents a data-driven deep learning framework capable of automatically detecting defects on reactor blades. Specifically, this study develops Deep Neural Network models to detect defects in borescope images using various datasets, based on Computer Vision and YOLOv8n object detection techniques. Firstly, reactor blade images are collected from public resources and then annotated and preprocessed into different groups based on Computer Vision techniques. In addition, synthetic images are generated using Deep Convolutional Generative Adversarial Networks and a manual data augmentation approach by randomly pasting defects onto reactor blade images. YOLOv8n-based deep learning models are subsequently fine-tuned and trained on these dataset groups. The results indicate that the model trained on wide-shot blade images performs better overall at detecting defects on blades compared to the model trained on zoomed-in images. The comparison of multiple models’ results reveals inherent uncertainties in model performance that while some models trained on data enhanced by Computer Vision techniques may appear more reliable in some types of defect detection, the relationship between these techniques and subsequent results cannot be generalized. The impact of epochs and optimizers on the model’s performance indicates that incorporating rotated images and selecting an appropriate optimizer are key factors for effective model training. Furthermore, models trained solely on artificially generated images from collages perform poorly at detecting defects in real images. A potential solution is to train the model on both synthetic and real images. Future work will focus on improving the framework’s performance and conducting a more comprehensive uncertainty analysis by utilizing larger and more diverse datasets, supported by enhanced computational power. Full article

The climate crisis represents one of the greatest contemporary global challenges, requiring actions to mitigate its impacts and sustainable solutions to meet the growing demands for clean energy and coastal protection. Therefore, the study of devices such as the submerged plate (SP), which simultaneously acts as a breakwater (BW) and wave energy converter (WEC), is especially relevant. In this context, the present numerical study compares the efficiency of an SP device under regular waves across different geometric configurations considering inclination angles. To achieve this, a horizontal SP was adopted as a reference. Its thickness and total material volume were kept constant while ten alternative geometries, each with a different inclination for the SP, were proposed and investigated. The computational domain was modeled as a full-scale regular wave channel with each SP positioned below the free surface. The volume of fluid (VOF) multiphase model was employed to represent the interaction between water and air. The finite volume method (FVM) was applied to solve the transport equations for volume fraction, momentum, and mass. The SP’s efficiency as a BW was evaluated by assessing the free surface elevation upstream and downstream of the SP, while its efficiency as a WEC was measured by evaluating the axial velocity below the SP. Results indicated that the efficiency of the SP can vary significantly depending on its inclination, with the optimal case at θ = 15° showing improvements of 11.95% and 16.59%, respectively, as BW and WEC. Full article

Tunneling in loose soil and urban areas presents numerous challenges. One effective solution is the use of Earth Pressure Balance Shields (EPBSs). Maintaining the correct balance of pressure at the tunnel face is critical, as applying too little pressure can cause a collapse, while excessive pressure may result in a blow-out. Therefore, a key aspect of using EPBSs in urban environments is determining the optimal pressure required to stabilize the tunnel face, taking into account the existing soil in the excavation chamber and controlling the screw conveyor’s rotation rate. This study focuses on a section of the second line of the Tabriz subway to evaluate the minimum pressure needed for tunnel face stability using empirical, analytical, and numerical approaches. The analytical methods involve evaluating the limit equilibrium of forces and considering soil buckling due to overburden, while the numerical methods employ 3D finite element analysis. Additionally, a sensitivity analysis of the parameters affecting the required pressure was conducted and compared across the three approaches. The results revealed that the formation of a pressure arch mitigates the full impact of overburden pressure on the tunnel face. For soil cohesion values below 20 kPa, the numerical results aligned well with the empirical and analytical findings. For a tunnel depth of 22.5 m and a water table 2 m below the surface, the estimated minimum pressure ranged from 150 to 180 kPa. Moreover, the analytical methods were deemed more suitable for determining the required support pressure at the tunnel face. These methods considered wedge and semi-circular mechanisms as the most probable failure modes. Also, for cohesive ground, the pressure from the finite element analysis was found to be almost always equal to or greater than the values obtained with the analytical solutions. Full article

Nowadays, electromobility has a significant role in transportation; different electrically driven vehicles are spreading continuously. Due to this form of drivetrain, fire safety hazards have also changed when compared to those of conventional vehicles. Lately, electric vehicle fires have become more common; thus, we have chosen to investigate the negative impacts of these fires on humans and the environment, in addition to the toxic properties of the resulting combustion products. In our research work, we conducted a full-scale fire experiment on an electric passenger car. Fire extinguishing was executed with fire-fighting foam, and its efficiency was examined. After extinguishing the fire, we took samples from the combustion gases and soil. Samples were subjected to laboratory investigations. Our results and experiences are presented in this article. Full article

The accurate design of tribological contacts, such as those in bearings and gearboxes, makes them highly efficient and helps reduce emission in all driven systems. Traditionally, this process requires more lubricant data than data sheets typically provide, mainly kinematic viscosity at 40 °C and 100 °C and density, which limits the design process. This study introduces a simplified methodology for determining lubricant film thickness, one of the main design critical parameters, using minimal viscosity measurements obtained with a high-pressure viscometer. The researchers demonstrate that essential lubricant parameters can be derived effectively from a few measurements. By combining state-of-the-art models for film thickness with practical measurements from an EHL tribometer, this study confirms that reliable film thickness predictions can be made from basic viscosity data. This approach streamlines the design process, making tribological simulations more accessible and cost-effective, and enhances the design of tribological contacts under extreme conditions. Full article

Many applications involve condensation in annuli; therefore, accurate prediction of heat transfer is important. While there have been a large number of experimental studies on condensation in tubes and several well-verified correlations are available for them, there have been very few experimental studies on annuli, and no well-verified correlation is available for prediction of heat transfer during condensation in annuli. This research was done to identify reliable correlations for this purpose and to develop a new one if needed. Literature was surveyed to identify experimental studies, test data, and predictive methods. Test data was compared to general correlations which have had considerable verification with data for condensation in channels. None of them was found fully satisfactory. A new correlation was developed by modifying the present author’s published correlation for condensation in tubes. It gives a MAD of 19.2% with available data from eight sources. Deviations of other correlations were much higher. The occurrence of surface tension effects and mini/macro channel boundary are investigated. The results of this research are presented and discussed. Full article