Acta Mechanica et Automatica Feed

Time-Dependent Experimental and Trefftz–HPM Analysis of Flow Boiling in Parallel Minichannels

Sat, 05 Sep 2026 00:00:00 GMT

This study investigates flow resistance and heat transfer during flow boiling of three low-boiling refrigerants (HFE-649, HFE-7100, and HFE-7200) in a system of five parallel horizontal minichannels (length 43 mm, depth 1 mm, width 6 mm). The research combines time-resolved experimental measurements with numerical reconstruction of transient heat transfer processes based on Trefftz-type methods. The working fluid flowed over a 0.1-mm-thick Haynes-230 alloy foil, which formed the heated channel wall and served as the electrical heat source. The experimental procedure provided both input and validation data for the numerical analysis. Measurements acquired at 1 Hz included inlet and outlet pressures and temperatures, infrared thermography of the external wall-temperature field, electrical parameters of the heated foil, and mass flow rate. Experiments at mass flow rates of 20, 40, and 60 kg/h (measured for the entire module) were analysed for the central minichannel, assuming equal flow distribution among the five parallel channels. The measured thermal and flow data were used to reconstruct transient wall and fluid temperature fields by solving an inverse heat transfer problem governed by the transient energy equation with prescribed boundary conditions. The numerical analysis employed two Trefftz-based approaches: the classical Trefftz method and a hybrid method combining the homotopy perturbation method with time-dependent Trefftz functions. Reconstructed foil temperatures agreed well with infrared measurements, with a mean relative difference below 0.5%, confirming the reliability of the numerical procedure. Pressure-signal stability was evaluated using statistical time-series metrics. Frictional pressure losses were predicted using a separated-flow approach, and a new correlation for the Fanning friction factor was proposed and evaluated against experimental data, with more than 75% of predictions falling within ±35% of the measurements. The study provides time-dependent distributions of wall temperature, pressure drop, and Nusselt number for flow boiling in parallel minichannel systems.

An Explainable AI Ensemble Model for Acquired Vitelliform Lesion Identification

Sat, 05 Sep 2026 00:00:00 GMT

Retinal diseases gradually weaken eyesight and may even potentially lead to blindness. Recognizing changes in the retina based on OCT imaging allows for the detection of diseases at their early stages and thus for making an appropriate diagnosis. In this study, acquired vitelliform lesions (AVL), drusen, and healthy cases are identified utilizing various CNN-based architectures, such as the Convolutional Gated Recurrent Units U-Net, Deep CNN-GRU Network, Residual Attention CNN. The dataset consisting of OCT images was created using photographs gathered from two research centres and publicly available OCT database. The single models obtained to be very effective in recognition the retinal diseases, obtaining the accuracy of 93.80%, 94.03%, and 95.18% for the Convolutional Gated Recurrent Units U-Net, Deep CNN-GRU Network, Residual Attention CNN, respectively. These models outperformed the pre-trained deep learning architectures, VGG-16, ResNet-18, InceptionV3, and DenseNet-121. In order to further enhance the performance of AVL, drusen, and normal cases identification up to 97.09% accuracy, bagging, boosting, and stacking of ensemble learning methods for all models are applied. Moreover, in order to eliminate the black box effect and indicate on what basis the classifier makes conclusions, two interpretability techniques are employed: Gradient Weighted Class Activation Maps (Grad-CAM) and Shap values. This study gives the in-depth insight into AVL, Drusen, and normal cases identification. Moreover, it provides the most effective CNN-based architecture with high accuracy to support ophthalmologists.

Comparative Analysis of Inspection Methods for Underground Crude Oil Transmission Pipelines Using Metal Memory Diagnostics and Ultrasonic Inline Inspection

Sat, 05 Sep 2026 00:00:00 GMT

A comparative analysis of inspection results for underground crude oil transmission pipelines was conducted using two diagnostic methods: Metal Magnetic Memory Non-Contact Magnetic Diagnostic (MMM- NCMD) and ultrasonic inline inspection tools (ILI). The results demonstrate that both methods provide complementary information on pipeline condition. The MMM- NCMD method enables identification of stress concentration zones within the pipeline wall, which is critical for prioritizing indications obtained from ILI inspections. Ultrasonic ILI tools exhibit limitations in detecting defects in circumferential welds and discontinuities oriented at large angles (greater than 15–20°) relative to the pipeline axis. Although MMM- NCMD is a qualitative method, it significantly enhances the interpretation of ILI results. The study confirms that MMM- NCMD is an effective complementary diagnostic technique for assessing the operational condition of underground crude oil transmission pipelines.

The Influence of the Inclination of the Crack Plane Relative the Annual Rings Direction on the Cracking Process of Pine Wood

Sat, 05 Sep 2026 00:00:00 GMT

A methodology for determining the critical parameters of pine wood cracking at different angles of inclination of the crack plane relative to the arrangement of early and late wood layers has been developed. The relevant results known to date from scientific literature concerned only two angles of layer arrangement (horizontal RL and vertical TL).To determine the strain energy release rate dependence of susceptibility on crack length for different angles crack plane was used, obtained numerically using the finite elements method. Experimental studies allowed the development of critical relationships between strain energy release rate, crack tip opening width and length of the fracture process zone from the crack plane orientation. Critical values for the strain energy release rate, crack tip opening width, and fracture process zone length were determined. Verification of the results obtained in specific cases of layer arrangement with known literature data showed good agreement.

Non-Linearity of Connections in the Equivalent Cantilever Beam Method (Ecbm) for Stressed Skin Diaphragms Modelling

Sat, 05 Sep 2026 00:00:00 GMT

Stressed-skin diaphragm action occurs when cladding, typically thin steel sheets or two sheets encapsulating insulation, significantly contributes to a structure’s global stiffness. Ignoring this effect in design can lead to inaccurate assessment, particularly under horizontal loads. The Equivalent Cantilever Beam Method (ECBM), considered an extension of the Component Method, models the flexibility of connections using equivalent cantilever beams composed of standard finite element members available in engineering analysis software. Earlier applications of the ECBM were limited to the elastic range of connector behaviour. This study introduces a nonlinear extension of the method by incorporating material yielding into the equivalent beams, enabling plastic redistribution of forces without specialised nonlinear springs. A hierarchical validation is presented: single-connector behaviour, a diaphragm panel against tests and ECCS predictions, and a full 3D building against an advanced reference model. Results demonstrate excellent agreement, indicating that the proposed method provides a practical and deployable solution for including stressed-skin effects in routine structural design models. The ECBM still follows the analytical framework of ECCS Recommendations No. 88, extending its applicability while maintaining its original simplifications and assumptions. Despite these limitations, the method may support the practical assessment of clad steel structures, including cases involving parasitic diaphragm action and the possible reduction or elimination of roof-plane bracing.

Performance Evaluation of Smart Hybrid Composites Incorporating Shape Memory Alloy Elements

Sat, 05 Sep 2026 00:00:00 GMT

Smart materials such as shape memory alloys offer innovative solutions in industry, based on their main characteristic of returning to their initial shape after deformation, in response to a temperature difference. When SMAs are combined with other materials, they give rise to the formation of smart composites. The composites were manufactured from epoxy resin, reinforced with Ti-Ni SMA wires, by studying their mechanical properties. This study presents the stress-strain relationships of a composite incorporating SMA wires. The study highlights, in a first part, the impact of SMA wires on the mechanical behavior of a composite plate, then analyzes the adaptation capacity and reliability of hybrid shape memory composites.

Method for Improving Muscular Activations During Exoskeleton-Aided Therapy with Intelligent Algorithms and VR-Based Teleoperation

Sat, 05 Sep 2026 00:00:00 GMT

Population ageing, neurological and orthopaedical diseases, and shortages in medical staff result in the need to develop tools for minimally supervised therapy. To guarantee effective kinesiotherapy in high doses, rehabilitation robots are required. However, they require additional technologies for automating treatment and monitoring patients’ safety. This paper presents and assesses such technologies integrated with the SmartEx-Twin exoskeleton of a lower extremity and its digital twin in virtual reality (VR) for teleoperation during emergency cases. The intelligent algorithms were proven to increase the effectiveness of the therapy, as assessed based on the EMG measured. The VR system was validated as also increasing the effectiveness, but reducing the perception of tiring exercises, based on EEG tracking. Additionally, the accuracy of controlling exoskeleton movements was measured. It was found out that the poor operation skills of the physiotherapist in the VR environment can increase motion inaccuracies by as much as 30 degrees per joint. Additional emergency tools triggered by spastic cramps detected and risk of pain were assessed as fully reliable and working with the delay of up to 125 ms and 2 s, respectively. The whole system was implemented for the exoskeleton and will undergo further tests to minimize control inaccuracies and teleoperation delays.

Design, Development, and Performance Evaluation of a Mechatronic V-Shaped Climbing Robot for Date Palm Trees

Sat, 05 Sep 2026 00:00:00 GMT

The mechanization of date palm (Phoenix dactylifera) cultivation is essential for improving worker safety and reducing the labor-intensive nature of tree maintenance and harvesting. In this study, a new climbing mechanism with a V-shaped folding chassis and concave rubber-coated wheels was designed, constructed, and evaluated. The motors were operated via independent switches, with future versions planned to feature integrated electronic control for fully autonomous functionality. The prototype was tested under three spring contact forces (425, 584, and 743 N), two wheel diameters (0.16 and 19 m), and three vertical load conditions (0, 120, and 220 N). Performance indices including climbing speed, slippage, and energy efficiency were measured and statistically analyzed using a full factorial design. The results showed that increasing the spring contact force from 425 to 743 N reduced slippage by 12.4% and increased climbing speed by 18.7%. Maximum climbing speed reached to 0.131 m/s. The highest tractive efficiency (78.1%) was achieved at a spring force of 584 N and a wheel diameter of 0.19 m. Analysis of variance (ANOVA) revealed significant effects (p < 0.05) of wheel diameter and spring force on both slippage and speed, while load had a minor influence. The proposed design exhibited stable trunk adhesion, smooth climbing motion, and low power consumption, indicating its potential for safe and efficient mechanized operations in date palm cultivation. Future work will focus on field-scale validation across multiple trees and optimization of motor power and control systems.

Virtual Strain Sensing in a Type IV COPV Burst Test

Sat, 05 Sep 2026 00:00:00 GMT

This study evaluates data-driven virtual strain sensing in the cylindrical region of a Type IV composite overwrapped pressure vessel (COPV) using the open synchronized record of one vessel and one hydraulic burst test. The analysis is intentionally framed as a single-test comparative case study rather than a general reference standard. Twelve cylinder channels, representing six positions with axial and hoop gauges, were examined through position-holdout reconstruction within the same burst record, pressure-conditioned reconstruction without explicit time, and a within-record high-pressure stress test above 125 bar. Direction-wise same-time, pressure-bin, and isotonic baselines were compared with linear regression, ridge regression, random forest, and multilayer perceptron (MLP) models. The 115,308 long-format rows originate from one synchronized experiment and were therefore treated as correlated observations, not independent experimental replications. Within the cylinder subset, the same-time mean achieved R²=0.9915, while the MLP without coordinates achieved R²=0.9906±0.0002. When explicit time was removed, the pressure-bin baseline remained stronger than the time-free MLP. In the high-pressure stress test, all models deteriorated and the time-free MLP fell to R²=-1.8043. A supplementary dome analysis also showed substantially poorer reconstruction for hoop gauges. These findings indicate that replacement of a missing cylinder gauge is feasible within an already instrumented burst test, but they do not establish cross-vessel or cross-test generalization. Practical deployment will require repeated tests, multiple vessels, mechanics-aware models, and calibrated uncertainty estimates.

Hybrid Control Approach for a Three-Tank Non-Interacting System

Sat, 05 Sep 2026 00:00:00 GMT

This article presents a control strategy that combines a super-twisting sliding-mode reaching law with a fuzzy inference system to regulate the liquid level in the third tank of a three-tank non-interacting process. This type of plant is widely used in contemporary industrial process automation, particularly in applications such as petroleum refining, distillation operations, and pulp manufacturing. To obtain the target liquid level, a sliding-mode controller employing the super-twisting algorithm is formulated to guarantee finite-time convergence of the tank level to the reference value, thereby improving robustness and tracking precision while inherently mitigating chattering. The fuzzy system is incorporated to estimate the parameters of the super-twisting reaching law adaptively. System stability under the proposed control scheme is demonstrated through Lyapunov analysis with explicit gain conditions. MATLAB/Simulink simulations are carried out and benchmarked against a conventional fuzzy logic controller, a Proportional-Integral-Derivative (PID) fuzzy logic controller, a PID controller using the Amigo tuning rule, and a neural network-based predictive controller. Compared with the selected benchmark controllers, the proposed method achieves faster transient response, zero overshoot, zero steady-state error, and a significantly reduced integral time absolute error (ITAE), while maintaining a competitive integral absolute error (IAE). The rise time is 1.6385 s, the settling time is 3.0398 s, and the IAE and ITAE values are 12.37 and 19.58, respectively.

High-Speed Machining of Nickel-Based Alloy INVAR 36: Optimization of Machining Vibration, Tool, and Alloy Surface Characteristics

Sat, 05 Sep 2026 00:00:00 GMT

INVAR 36 is considered a difficult to machine alloy because of its physical properties, but it has a low coefficient of thermal expansion and good dimensional stability that makes it suitable for aerospace, precision engineering, and tooling applications. Dry turning experiments have been done on INVAR 36 based on different cutting speeds (vc), feed rates (vf), and depth of cuts (ap) with respect to their influences on surface roughness (Ra), maximum flank wear (VBmax), and machining vibrations, Root Mean Square. Through Response Table Analysis, feed rate was found to be the highest influencing parameter for surface roughness, while cutting speed was the highest influencing parameter for tool wear and vibrations. Further, the vibration data have been studied through Fast Fourier Transform in frequency, domain with the dominant frequency being 105.6 Hz at optimal machining conditions. The optimization was carried out through multi-criteria decision-making by employing Grey Relational Analysis, Evaluation based on Distance from Average Solution, and Additive Ratio Assessment. It is seen that all three approaches gave the same optimum machining parameters, and hence the validity of the optimum machining parameters can be said to be reliable. The optimum combination of the parameters was found to be vc = 150 m/min, vf = 0.18 mm/rev, and ap = 1.2 mm, giving the minimum RMS vibration value of 14.246 g and flank wear of 0.110 mm.

Modal Origin of the Temperature-Dependent DMA Phase Shift in Polymer Beams

Sat, 05 Sep 2026 00:00:00 GMT

Dynamic mechanical analysis is widely used to characterize viscoelastic materials, yet the physical origin of the measured phase shift remains only partially understood for structurally extended specimens. Its standard interpretation typically assumes a single, effective phase shift between applied stress and strain. In this work, we investigate the temperature-dependent viscoelastic response of medical-grade acrylonitrile butadiene styrene (ABS) fabricated by fused filament fabrication and injection molding, combining DMA measurements, fractographic analysis, and analytical modeling. Rectangular beam specimens were subjected to three-point bending DMA over a temperature range spanning the glass transition region. The storage modulus, loss modulus, and phase shift were determined as functions of temperature and compared between manufacturing routes. While both materials exhibit nearly identical glass transition temperatures, the 3D-printed samples exhibit a modest reduction in storage modulus, reflecting microstructural heterogeneity introduced by the layer-wise fabrication process. Fractographic observations reveal characteristic interlayer features and microvoids that correlate with the observed mechanical response. To interpret the temperature-dependent phase shift, we develop a theoretical model of a damped vibrating beam in which each eigenmode contributes with its own phase shift. By introducing a temperature-dependent effective damping coefficient, the model’s mode-averaged phase shift reproduces the experimental DMA data with high accuracy. By linking DMA phase measurements to the mode dynamics of the tested structure, the proposed framework establishes DMA as a structure-sensitive dynamical probe and is applicable to a broad class of polymer, composite, and additively manufactured materials.

Machine Learning Integration in Additive Manufacturing: From Process Optimization to Biomedical Implant Applications

Sat, 05 Sep 2026 00:00:00 GMT

Machine learning (ML) is accelerating the advancement of additive manufacturing (AM) into an intelligent, autonomous technology, spanning basic process optimization to specialized biomedical implant fabrication. Based on a systematic literature review encompassing 103 screened studies from 2014 to 2025 in accordance with PRISMA-P guidelines, this research maps how ML augments AM workflows in design, in-situ monitoring, and material performance. Supervised techniques like support vector machines, artificial neural networks, and convolutional neural networks are used extensively to forecast melt pool behavior, identify defects, and optimize parameters. Analysis of comparative studies within the reviewed cohort shows that while traditional data-driven models are foundational, physics-informed neural network (PINN) architectures provide a 10–12% increase in microstructural and thermal history prediction accuracy by embedding explicit physical conservation laws relative to purely empirical black-box configurations. Emerging frameworks, including large-scale generative models and federated learning, are evaluated not as immediate clinical solutions, but as experimental methodologies that facilitate advanced inverse design, biomimetic lattice synthesis, and decentralized collaborative manufacturing protocols. Ti-based alloys, particularly Ti–6Al–4V, lead the clinical domain due to structural performance, fine-tuned through ML for site-specific characteristics. The findings conclude that transitioning from ‘black-box’ models to explainable AI represents the definitive path forward for meeting FDA/CE regulatory standards in clinical validation.

Human Hand Kinematic Models for Sensor Glove-Based HMI: A Review

Sat, 05 Sep 2026 00:00:00 GMT

The human hand contains 27 bones, 36 articulations, 39 active muscles, and is commonly represented by approximately 20–27 functional degrees of freedom, depending on the adopted kinematic model. Accurate reconstruction of hand motion is essential for sensor glove-based human–machine interfaces (HMIs) used in robotics, rehabilitation, teleoperation, virtual and augmented reality, prosthetics, and gesture-based interaction. This review analyzes human hand kinematic models and their integration with sensor glove technologies for motion capture and hand pose reconstruction. Rigid-body, musculoskeletal, data-driven, and hybrid modeling approaches are compared with respect to anatomical fidelity, computational complexity, and suitability for real-time applications. The review also examines sensing technologies, including flex sensors, inertial measurement units, optical tracking systems, and multimodal sensing architectures, together with calibration and sensor fusion methods. The reviewed literature indicates that rigid-body models remain the most widely used approach because of their computational efficiency and compatibility with wearable sensing systems, whereas musculoskeletal models provide greater anatomical realism at higher computational cost. The review identifies hybrid modeling, standardized calibration procedures, multimodal sensor fusion, and benchmark datasets for hand motion reconstruction as key directions for future research in sensor glove-based HMIs.

Impact of Multi-Length Capillary Tubes on Low-Gwp Refrigerant Performance in VCR Systems

Thu, 16 Jul 2026 00:00:00 GMT

Traditional synthetic refrigerants like R134a are under increasing regulatory pressure due to their environmental impact, hence the need for ecologically friendly alternatives. The present study experimentally investigates and predicts the performance of a natural low-GWP refrigerant, R600a (isobutane), for household refrigeration with R134a. In the study, measurements and modeling of COP, power consumption, and cooling performance were done for capillary tube lengths of 2.43-4.26 m and ambient temperatures between 25 °C and 37 °C. Predictive correlations are developed from the experimental data to estimate system behavior for a wide range of working conditions. The results indicate that while R600a provides a cooling performance close to R134a, it requires a 66% lower charge compared to R134a (50 g vs. 150 g), leading to a reduction in cost and risk of flammability. RR134a delivers better COP values when the capillary tube is short and the operating temperature is relatively low (around 25–30 °C), showing an improvement of about 7.9–24.5%. However, as the capillary length increases and the temperature rises, R600a starts to outperform R134a. At a capillary length of 4.26 m and temperatures between 35–37 °C, the COP improvement with R600a can reach as high as 50.5%. These observations are further supported by predictive analysis, which helps validate the trends and offers reliable guidance for choosing the right refrigerant–capillary combinations across different thermal conditions. Overall, the study offers practical guidelines to optimize the design of household refrigeration systems to strike a balance among efficiency, safety, and environmental sustainability.

A Comparative Study of Conventional and Advanced PI Controllers for Induction Motor Speed Regulation Under Parameter Variations

Thu, 16 Jul 2026 00:00:00 GMT

This paper presents a comparative study of various Proportional-Integral (PI) controller strategies applied to the speed regulation of a squirrel-cage induction motor under Indirect Field-Oriented Control (IFOC). The classical PI controller is benchmarked against three enhanced versions: the Hyperbolic PI (HPI), the Variable Gain PI (VGPI), and the Anti-Windup PI. Each controller is evaluated in terms of dynamic response, steady-state error, robustness to parameter variations and disturbance rejection. In addition, various numerical simulations under MATLAB/Simulink are carried out to evaluate the motor’s performance through different operating conditions, including load disturbances and reference speed changes. The obtained numerical results conclude that, among the modified PI variants, the VGPI and Anti-Windup PI demonstrate superior performance in terms of robustness, adaptability, and transient behaviour. The obtained numerical results highlight the advantages and limitations of the control strategy, providing valuable insights for selecting an appropriate speed regulator in industrial applications.

Thermal Performance Enhancement for Buildings Using Phase Change Materials (PCMs)

Thu, 16 Jul 2026 00:00:00 GMT

The residential sector in Egypt is one of the largest energy consumers, exacerbating the energy crisis due to reliance on fossil fuels and the growing gap between supply and demand. This study aims to enhance energy efficiency in the integration of Phase Change Materials (PCMs) into residential buildings for thermal energy storage. The impact of PCM was analyzed using Energy Plus, the simulation engine for Design Builder, focusing on five major Egyptian cities representing different climate conditions. The CondFD algorithm was applied to simulate heat transfer and assess Reinforced building components with PCMs to lower energy use while maintaining indoor thermal comfort. Initially, three potential PCM options are assessed for a baseline residential unit, with M91/Q23 featuring a melting point of 23°C and a thickness of 37 mm was determined to be the most effective configuration when applied to the exterior layers of the building envelope. This PCM is subsequently incorporated into a standard single-story, multi zone residential buildings for further analysis. The average energy savings per month of 17.55% is achieved in Assiut, 16.28% in South Sinai, 16% in Alexandria, 15.68% in Ismailia, and 14.8% in Aswan. It was found that the use of PCMs to improve energy efficiency in residential buildings depends on different types of PCMs and how to select the best type with the best thickness based on their physical properties.

Fully Automatic Simulation of Crack Propagation in Plane Structures

Thu, 16 Jul 2026 00:00:00 GMT

In this paper, advanced fully automatic computations of curved crack propagation in combination with the analysis of the plastic limit loading by the lower bound theorem of plasticity in plane structures with multiple cracks are presented. For this purpose a simulation program based on the finite element method (FEM) is developed. A Coffin-Manson-model is implemented to include additionally initiated cracks into the model during the crack growth simulation process. To show the accuracy of the simulation program numerical results of multiple crack growth under proportional loading configurations are presented and compared with experimental data. The results indicate that the proposed solution algorithm provides a powerful tool for flaw assessment with the failure assessment diagram (FAD) procedure in combination with a numerical crack path simulation. Furthermore, it can be observed that local plastic failure occurs in the ligament between two approaching crack tips, which does not lead immediately to a complete loss of load-bearing capacity of the damaged structure.

Application of Two–Dimensional Entropy Measures for Detecting Signs of Pharyngeal Lymphoid Hyperplasia in Equine Endoscopic Images

Thu, 16 Jul 2026 00:00:00 GMT

Background: The proliferation and growth of lymphoid follicles in equine pharyngeal mucosa is assessed and graded using resting endoscopy into grades 0–4 pharyngeal lymphoid hyperplasia (PLH). Grade 0 indicates a healthy mucosa with no visible lymphoid follicles, while grades 1–4 are represented by more numerous and enlarged follicles reflecting ongoing or recent respiratory tract inflammation. Objective: Implementation of the multi–scale two–dimensional entropy measures to quantify the endoscopic signs of PLH as a step forward in incorporating computer–aided diagnosis (CAD) of active respiratory tract inflammation in horses. Methods: Endoscopic pharynx images were collected from 70 horses clinically assessed as having PLH grades 0–4. The images were segmented, converted to grayscale, and filtered using Normalize, Mean, Median, and Laplacian filters. Texture features were calculated using the following two–dimensional entropy measures across five scales: sample entropy (SampEn2D), fuzzy entropy (FuzzEn2D), dispersion entropy (DispEn2D), distribution entropy (DistEn2D), Espinosa entropy (EspEn2D), and permutation entropy (PermEn2D). Entropy measures were compared between PLH grades, considering the filtering method and scales used. Features were transformed using Linear Discriminant Analysis (LDA) and classified using the Random Forest (RF) algorithm. Finally, the classification metrics were calculated. RESULTS: Studied entropy measures varied between individual PLH grades; however, they did not increase or decrease gradually with the consecutive PLH grades. Considering single–scale measures, the highest importance for classification was brought by FuzzEn2D and DispEn2D, achieving accuracy of 0.47 for Normalize and Mean filtering. Considering multi–scale measures, high classification metrics (0.86 accuracy, 0.88 precision, 0.87 recall, and 0.85 F1 score) were achieved for Median filtering, with the highest importance given to FuzzEn2D and DispEn2D. Conclusions: Combining multi–scale two– dimensional entropy measures–particularly FuzzEn2D and DispEn2D–and Median filtering enables the best discrimination of endoscopic signs of PLH, supporting CAD of active respiratory tract inflammation in equine veterinary medicine.

Durability Test of Transport Platforms for Recovery Vehicles with a Coupling Functionsupported by Strength Testing and Fracture Inspection

Thu, 16 Jul 2026 00:00:00 GMT

This paper is focused on various experimental stages for engineering, science, and approval processes, including: (a) details of tested objects such as transport-overrun platforms with a coupling ball for vehicle connections and their installation in the T-slot testing area, (b) fatigue cracks and zones across different sections of the examined object types, (c) results of mechanical tests on specimens for the approval process. It highlights differences in platform mounting caused by supports and screws, as well as the vehicle axle, with transport belts used for coverage during operation. Cracks are illustrated in macro-photographs of the platform stringers and subframes, which are made of aluminium alloy and structural steel grades. Fracture regions are depicted in approved coupling balls after durability tests, illustrating characteristic features caused by applied cyclic force components in two directions: vertical and horizontal. The results of tests on specimens include the response of the 6005 T6 weld aluminium alloy under tensile force, and follow the Wöhler curve of S700MC high-strength steel with its welded joint, at SEM observations for fatigue region features. All results cover the efforts made for the Polish automotive industry for type approval and product sales within and outside the European Union.