Abstract: The accurate evaluation of the structural health of in-service fibre-reinforced polymer components is particularly interesting. Acoustic emission has been widely studied for monitoring damage initiation and propagation in such materials. However, the accurate identification of exact damage modes together with the accurate quantification of damage severity through analysis of acoustic emission signals remain challenging. The present study explores the applicability of frequency-based multi-variant analysis for identifying damage modes and quantifying the level of sustained damage in fibre-reinforced composites, highlighting the limitations of existing methods.

Abstract: The paper provides an analysis of the energy efficiency of the swing drive system of hydraulic excavators, which integrally includes a hydraulic motor and a planetary reducer. The indicator of the drive’s energy efficiency is determined based on the efficiency of the hydraulic motor and the planetary reducer. The efficiency of the hydraulic motor is defined as a function of the specific flow, pressure, and the number of revolutions of the hydraulic motor. The efficiency of the reducer is determined using structural analysis of planetary gearboxes and the moment method. As an example, the results of a comparative analysis of the energy efficiency of the swing drive of a tracked hydraulic excavator, weighing 16,000 kg and having a bucket volume of 0.6 m³, are presented. From the set of possible generated variant solutions of the drive, obtained through the synthesis process based on the required torque and platform rotation speed, two extreme drive variants were selected for the analysis. The first drive variant uses a hydraulic motor with low specific flow and a three-stage reducer with a higher transmission ratio, while the second variant uses a hydraulic motor with high specific flow and a two-stage reducer with a lower transmission ratio. The obtained results of the comparative analysis of the drive's energy efficiency are presented depending on the change in the required torque and the number of revolutions of the platform.

Abstract: This study presents a systematic optimization of GTAW welding parameters to achieve a pipe-to-pipe butt weld with a root height consistently below 2 mm when joining stainless steel 316L material, employing the Taguchi design of experiments. The input parameters considered include GTAW welding current, voltage, welding speed, and root gap configurations of 1 mm, 1.5 mm, and 2 mm. Welding was performed according to the Taguchi L-09 experimental design. All 9 welded samples were evaluated using liquid penetrant testing to detect surface-breaking defects such as porosity, laps, and cracks; X-ray radiography to identify internal defects; and profile radiography to assess erosion, corrosion, and root height. Among the nine welded plate samples, the optimal root height (less than 2 mm) was selected and further validated through the welding of a one-pipe sample. An additional macro examination was conducted to confirm the root height and assess the overall root weld integrity and quality.

Abstract: The detection of ceramic surface defects is of great significance for product quality. Traditional detection methods have limitations, while deep learning methods bring new opportunities. This article first introduces the basic steps and current situation of data preparation. Secondly, it explores the imbalanced sample problem faced in ceramic surface defect detection based on methods such as data augmentation, sample distribution optimization, network structure improvement, and loss function design. It also reviews the small sample problem in ceramic surface defect detection through methods like data augmentation, transfer learning, unsupervised learning, and network structure optimization. The methods to improve the detection accuracy of small target defects on ceramic surfaces are elaborated, including adding attention mechanisms, feature improvement, network structure optimization, etc. The improvement of the real - time performance of model defect detection is analyzed from two aspects: the improvement of lightweight models and the integration and optimization of network modules. Finally, the solutions that can be used in the implementation of ceramic surface defect detection technology are summarized, and the future research directions of ceramic surface defect detection are prospected.

Abstract: A common test configuration used to produce mixed mode I/II in composite materials is the Asymmetric Double Cantilever Beam (ADCB), which consists of two sublaminates with different thickness or elastic properties. This situation usually occurs in bimaterial adhesive joints. During this test, the sample undergoes rotation. In this work, the influence of the rotation of the ADCB samples on the calculation of the energy release rate (ERR) in modes I and II has been studied. When the rotation of the specimen is not negligible, it is important to take this rotation into account in the calculation of modes I and II. This study has been developed using the Finite Element Method (FEM). Several models with different degrees of asymmetry (different thickness ratio and/or elastic modulus ratio) and different applied displacements were prepared to obtain different degrees of rotation during the test. As is known, the concept of modes I and II refers to the components of the energy release rate calculated in the direction perpendicular and tangential to the delamination plane respectively. If the model suffers large rotation during the application of the load, this nonlinearity must be considered in the calculation of the mode partition I/ II. In this work, appreciable differences have been observed in the values ​​of modes I and II depending on their calculation in a global system or a local system that rotates with the sample. Currently, this correction is not usually implemented in finite element calculation codes or in analytical developments. The purpose of this article is to draw attention to this aspect when the rotation of the specimen is not negligible.

Abstract: Aortic stenosis is a valvular heart disease characterised by the narrowing of the valve opening area. Calcific and rheumatic aortic stenosis (AS) have distinctly different valve morphologies. The haemodynamic environment of generic calcific and rheumatic aortic valves of various severities is analysed through the use of 3D FSI modelling techniques. For moderate (AVA = 1-1.5 cm²), severe (AVA <1 cm²), and very severe (AVA ≪1 cm²) cases of calcific and rheumatic AS, larger TPGs with higher velocity magnitudes are estimated in the rheumatic cases compared to the calcific cases. The additional work required by the left ventricle to overcome the TPG caused by the moderate, severe, and very severe rheumatic valve lesions are 6.6 %, 42.5 %, and 58.3 % higher compared to the calcific valves of the same severity. The clinical approximation of the TPG is determined according to the simplified Bernoulli approximation and compared to the ground-truth TPG from the FSI results. The insensitivity of the clinical TPG approximation to the type and severity of stenosis is evident. Overall, the clinical approximation of the TPG either over or under predicts the TPG depending on the type and severity of the lesion, with smaller errors in the rheumatic cases compared to the calcific cases.

Abstract: Nearly one million people in Amazon still don't have reliable access to electricity. Moreover, the rural electricity grid is mostly single-phase, ground-return type, with poor energy quality and high expenses. This study examines very low head micro hydro power (MHP) installations in Amazon, emphasizing the integration of multiple axial-flow turbines. It includes an analysis of flow duration curves and key curves, both upstream and downstream, to design an MHP with two or more units aimed at maximizing annual energy generation. The presence of multiple turbines is crucial due to the substantial annual flow variation in the Amazon rivers. This research supports the design of small, cost-effective axial-flow hydraulic turbines. The design applies the minimum pressure coefficient criterion to increase turbine efficiency. Computational Fluid Dynamics (CFD) simulations forecast turbine efficiency and flow behavior. The CFD model is validated against an existing experimental study from the literature on a propeller turbine with a curved plate blade, which is similarly used in this study due to cost reasons. The study also explores the implications of including inlet guide vanes (IGV). A case study is showcased for a location at a small bridge in Vila do Janari, situated in the southeastern part of Pará state, where heads range from 1.4 to 2.4 m and turbine flow rates span from 0.23 to 0.92 m³/s. The optimal configuration shows the potential to generate 63 MWh/year.

Abstract: Polyetheretherketone (PEEK) is a high-performance thermoplastic widely used in aerospace, automotive, and medical applications due to its exceptional strength, heat resistance, and chemical stability. However, warpage and mechanical property variations remain significant challenges in 3D printing PEEK parts. This study investigates the effect of key printing parameters, including nozzle temperature, layer thickness, platform temperature, and infill rate, on the mechanical properties and warpage of 3D-printed PEEK components. By systematically analyzing tensile and compressive loading conditions, this research aims to optimize printing settings to improve dimensional accuracy and structural integrity. Experimental results indicate that mechanical properties, such as tensile and compressive stress at break, vary significantly with printing conditions. The highest tensile strength of 71.4 MPa and compressive strength of 167 MPa were achieve. Meanwhile, lower tensile (45.36 MPa) and compressive strengths (72.5 MPa) were recorded. Higher nozzle and platform temperatures, coupled with increased infill rates, enhance layer adhesion, leading to improved tensile and compressive strength. However, with a nozzle temperature of 400°C, platform temperature of 130°C, and 60% infill rate, demonstrating optimal bonding between layers and leads to reduction in warpage. Considering warpage in all four corners and mechanical properties, 400°C nozzle temperature, 0.16 layer thickness, 130°C platform temperatures, coupled with 60% infill rates, shows optimal printing conditions. The 10% carbon fiber-reinforced PEEK composites exhibit improved tensile strength 1.68 times compared to pure PEEK. To emphasize the importance of thermal and structural settings, the findings highlight the crucial role of printing parameters in minimizing warpage and enhancing mechanical properties in 3D-printed PEEK parts that is analyzed by muti multi-objective optimization method. The Scanning Electron Microscopy Analysis were carried out to analyze the fracture morphology and printing layers orientation.

Abstract: One of the methods to lower CO2 emissions from an existing coal plant is the implementation of biomass co-firing. Thus the carbon emission level of gas-fired power plants (550 kg/MWh) can be achieved. The result is a significant increase of the fuel volumes that are acquired, handled and finally supplied to the power plant units. A necessary extension of a complex logistic system for transporting biomass may increase noise emissions. Environmental regulations require to analyze the impact of this expansion on possible exceedance of the allowed noise thresholds. For a comprehensive assessment of the concept of expanding the power plant's biofuel supply system (BSS), a digital simulation model was built to dimension system elements and verify its correctness of the proposed solutions. Then, a dedicated noise emission model was built for the purposes of mandatory environmental impact assessment procedures for the planned expansion of the BSS, which showed the possibility of exceeding the permissible noise levels at night in selected locations. The article presents the results of a simulation analysis of the efficiency of the BSS in a power plant located in an urbanized environment, taking into account optional shutdowns of facilities generating too much noise at night. The results of the simulation indicate the possibility of securing fuel supplies also under strict restrictions. The use of digital, spatial simulation models of a complex, cyclical-continuous transport system to control its operation in conditions of constraints is an effective method of solving environmental conflicts at the design stage of the extension of industrial installations in urbanized areas.

Abstract: Pressure vessels are widely used equipment in several industries, and can operate at high pressure and temperature, which can cause major accidents in the event of a failure. The objective of this work is to analyze the behavior of longitudinal and circumferential stresses at three specific points on the wall of a pressure vessel, two distant points of geometric discontinuity (at the top and side) and one close to geometric discontinuity (at the intersection of the top and the connection) through theoretical, numerical and experimental analyses. The pressure vessel in this work is a piece of equipment used on offshore oil platforms and is part of a natural gas dehydration system. The results showed that the longitudinal and circumferential stresses at the intersection of the top and the connection were higher than the stress values at the top and side for the experimental and numerical analyses, due to the emergence of bending stresses in regions of geometric discontinuity. Another important point was the good correlation of the results between the experimental and numerical analyses using the FEM in the ANSYS software, showing that this methodology is a powerful and reliable tool in the analysis of stresses in pressure vessels.

Abstract: Printed electronics utilize traditional printing techniques to develop low-cost, flexible electronic devices such as batteries, supercapacitors or sensors. This review concentrates on the role of screen printing in the production of energy storage devices, emphasizing its adaptability to meet the requirements for customizable electronic devices for daily, medical, and industrial applications. Key aspects of the screen printing process, including ink viscosity, mesh selection, and squeegee dynamics, are discussed in detail due to their significant influence on the quality and functionality of the final products. The review explores the use of advanced materials, such as graphene, carbon nano-onions, carbon nanotubes and graphite, which enhance the mechanical and electrical properties of batteries. Advances in substrates are also examined, highlighting their ability to accommodate diverse device geometries and enhance the versatility of applications, as well as, the sustainability of materials and methods used in screen printing, advocating for environmentally friendly practices. Overall, this paper provides a comprehensive overview of screen printing in the context of printed battery production, underscoring its potential to fulfill future requirements for high-performance, flexible, and eco-friendly electronic devices. The findings aim to guide potential research and optimize screen printing techniques and materials to enhance device performance in various applications.

Abstract: This paper presents the PRONOBIS project, an ultrasound-only, robotically navigated prostate scanning and biopsy treatment planning. The proposed system addresses the challenges of precise prostate reconstruction and inter-operator variability by performing fully automated prostate scanning, real-time ultrasound image processing, 3D prostate reconstruction, and biopsy needle position planning. Fully automated prostate scanning is achieved by using a robotic arm with an ultrasound system. Real-time ultrasound image processing utilizes deep learning algorithms for precise prostate segmentation. To create a high-quality prostate segmentation dataset, this paper proposes a deep-learning based medical annotation platform - MedAP. For precise segmentation of the entire prostate sweep, DAF3D and MicroSegNet models are evaluated, and additional computer vision postprocessing methods are proposed. The 3D visualization and prostate reconstruction are performed based on the segmentation results and robotic positional data, enabling robust and user-friendly biopsy treatment planning. The real-time sweep scanning and segmentation operates at 30Hz, which enables full sweep scanning in 15 to 20 seconds, depending on the prostate size. The system is evaluated on prostate phantoms by reconstructing the sweep and by performing dimensional analysis, which indicates 92\% and 98\% volumetric accuracy on used phantoms. 3D prostate reconstruction takes approximately 3 seconds and enables a fast and detailed insight for precise biopsy needle position planning.

Abstract: Accurate fatigue prediction is essential for ensuring the reliability and durability of engineering systems. Suitable predictive performance was achieved by artificial neural networks trained on the FatLim dataset, however further improvements are needed due to its small sample size. This study explored the impact of dataset augmentation on model performance by exemplarily expanding the FatLim dataset and comparing results against the original dataset. The dataset was augmented by generating additional uniaxial stress scenarios and applying tensor transformations to simulate varied stress orientations. Neural network models are trained separately on the original and expanded datasets, and their predictive performance is evaluated. The results demonstrated that the model trained on the augmented dataset achieved better accuracy, confirming the effectiveness of dataset expansion in improving fatigue prediction. This research underscores the potential of data augmentation techniques to enhance machine learning models for fatigue analysis.

Abstract: This study unveils an AI-orchestrated HVAC system for a 10,000 sq ft ISO 7 cleanroom, tailored to Mars’ extreme conditions: 3.72 m/s² gravity, 0.6 kPa pressure, 95% CO2 atmosphere (Pr ≈ 0.73), and temperatures down to -140°C. Using Revit MEP and synthetic datasets, the design reduces airflow by 50% (80,000 to 40,000 CFM), energy use by 60% (50 to 20 kW), and design time by 90% (30 to 3 days), while maintaining 97% pressure stability (25 Pa, ±0.015 inWG) and ±0.8°C thermal uniformity. Aligned with BS EN 16798 and ASHRAE 2022, it ensures GMP-grade sterility for 10^6 annual pharmaceutical doses, surpassing terrestrial benchmarks (80 kW) by 75%. The system adapts to Mars’ 24.6-hour Sol, 605 W/m² solar flux, and dust storms (τ ≤ 5), with scalability for lunar outposts and Earth’s polar labs. Validated through 15,000 simulations, these theoretical results await physical prototyping to confirm resilience under severe Martian conditions (e.g., τ > 5). This framework paves the way for self-sufficient Martian colonies by 2050 with up to 75% energy savings over terrestrial standards.

Abstract: The future fusion power plant EU DEMO will generate its own tritium fuel through the use of segmented breeding blankets (BBs), which must be replaced from time to time due to material damage caused by high-energy neutrons from the plasma. A vertical maintenance architecture has been proposed, using a robotic remote handling tool (transporter) to disengage the 125t and 180t outboard and inboard segments and manipulate them through an upper port. Safe disengagement without damaging the support structures requires the use of high-capacity tilting joints in the transporter. The trolley tilting mechanism (TTM) is proposed as a novel, compact, high-capacity robotic joint consisting of a 5-bar spatial mechanism integrated in the BB transporter trolley link. A kinematic model of the TTM is established, and the analytical input-output relationships, including position-dependent transmission ratio, are derived and used to guide the design and optimization of the mechanism. The model predictions are compared to an ADAMS multibody simulation, and to the results of an experiment conducted on a down-scaled prototype, both of which validate the model accuracy.

Abstract: Quaternions are used in various applications, especially in those where it is necessary to model and represent rotational movements, both in the plane and in space, such as in the modeling of the movements of robots and mechanisms. In this article, a methodology to model the rigid rotations of coupled bodies by means of unit quaternions is presented. Two parallel robots were modeled: a planar RRR robot and a spatial motion PRRS robot using the proposed methodology. Inverse kinematic problems were formulated for both models. The planar RRR robot model generated a system of 21 nonlinear equations and 18 unknowns, and a system of 36 nonlinear equations and 33 unknowns for the case of space robot PRRS; both systems of equations were of the polynomial algebraic type. The systems of equations were solved using the Broyden-Fletcher-Goldfarb-Shanno nonlinear programming algorithm and Mathematica V12 symbolic computation software. The modeling methodology and the algebra of unitary quaternions allowed the systematic study of the movements of both robots and the generation of mathematical models clearly and functionally.

Abstract: The development of chip manufacturing and advanced packaging technologies has significantly changed redistribution layers (RDLs), leading to shrinking line width/spacing, increasing the number of build-up layers and package size, and introducing organic materials such as polyimide (PI) for dielectric. The fineness and complexity of structures, combined with the temperature-dependent and viscoplastic properties of organic materials, make it increasingly difficult to predict the thermo-mechanical behavior of wafer-level Cu-PI RDL structures, posing a severe challenge in warpage prediction. This study models and simulates the thermo-mechanical response during the manufacturing process of Cu-PI RDL at the wafer level. A cross-scale wafer-level equivalent model was constructed using a two-level partitioning method, while PI material properties were extracted via inverse fitting based on thermal warpage measurements. Warpage prediction results were compared against experimental data using maximum warpage as the indicator to validate the extracted PI properties, yielding errors under less than 10% at typical process temperatures. The contribution of RDL build-up, wafer backgrinding, chemical mechanical polishing (CMP), and TSV/TGV interposers to the warpage was also analyzed through simulation, providing insight for process risk evaluation. Finally, an artificial neural network was developed to correlate copper ratios of four RDL layers with wafer warpages for a specific process scenario, offering a potential direction for layout design optimization.

Abstract: In this study, a cantilever beam with a tip mass under base excitation was analyzed, with system damping modeled using a fractional derivative approach. By applying the Rayleigh-Ritz method, the governing equation was decomposed into spatial and temporal components. Analytical solutions for the temporal equation were derived; however, their complexity posed challenges for practical application. To address this, convergence acceleration techniques were employed to efficiently evaluate slowly converging series representations. Additionally, two methods for identifying the parameters of a classical model approximating the fractional system were investigated: a geometric approach based on waveform shape analysis and an optimization procedure utilizing a genetic algorithm.

Abstract: Tools with microtextures have found wide application in cutting difficult machining materials. The cutting performance of tools is closely related to the arrangement, morphology, and size parameters of microtextures. In this research micro-pit tools were used in turning GH4169 in spray cooling. The effect of micro-pit parameters on tool wear was investigated through simulation and cutting experiment. In simulation, a model of cutting GH4169 in spray cooling was built to analyze the wear of micro-textured tools with different parameters, and the optimal combination of micro-pit parameters with excellent anti-wear performance was obtained. In cutting experiment, micro-pit textures with different parameters were fabricated by femtosecond laser, and cutting experiments were conducted in spray cooling to analyze the wear on the rake face of micro-textured tools. Furthermore, Ansys Fluent was used to simulate the dynamic pressure of oil film on the surface of micro-pits and the anti-wear mechanism of micro-textured tools was verified. This research provides technical reference for the design and development of micro-textured tools.

Abstract: The researchers looks at process characteristics in order to improve color choices and create more accurate simulation models, in this research paper. The processing factors evaluated were speed (Sp), temperature (T), and feed rate (FRate). We used Box-Behnken Design (BBD) and the three-Level-Full-Factorial Design (3LFFD) response surface techniques to adjust uniform processing settings. This study employed an experimental approach to optimize process parameters while holding all other variables constant. Statistical and numerical optimization were both made possible by the Design Expert software, which also helped with experimental design. We used this technique to generate a statistical equation for simulated regression models. The optimal tristimulus color values have the smallest color variance (dE*). The created model and experimental data passed all diagnostic tests, showing that the model is statistically valid. The three examined parameters had a significant effect on the color parameters dL*, da*, and db*, as well as specific mechanical energy (SME), according to the Analysis of Variance (ANOVA). Furthermore, we calculated specific mechanical energy for the experimental trials and found that it decreased as the FRate increased. The study concludes by comparing the two design models to determine which produces the best color quality. Choosing the right process settings is crucial for reducing color fluctuations (dE*). Furthermore, during the experimental trials, we performed microscopic characterization, including agglomeration level assessments. To determine pigment dispersion, the collected data was analyzed using Scanning-Electron Microscopy (SEM) as well as Micro-CT-scanner pictures (MCT). This work contributes to addressing potential design and manufacturing difficulties that affect color variability and waste minimization for diverse chemical grades, thereby encouraging environmentally friendly operations. Regarding the BBD. The processing circumstances indicate that 728.38 rpm, 274.23 °C, and 24.44 kg/hr are closest to the target specifications. In addition, overall the lowest deviation=0.26 while 87% is the maximum design attractiveness. We are discussing the three-Level Full Factorial Design (3LFFD). Generally the a maximum desirability of 77% and a minimum tolerable color variation (dE*) of 0.25, we determined that 741.27 rpm, 245.26 °C, and 24.72 kg/hr were the ideal process parameters. These results show that the processing parameters used to generate the output have a significant impact on its quality. To reduce the variation and improve appeal more modifications This study compares the two generated designs and discovers that both sets of process parameters were statistically significant, with BBD being the preferred option for selection needed, resulting in even better outcomes in future experiments.