Periodica Polytechnica (Budapest University of Technology and Economics)
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Assessment of Defect Severity in Wooden Pillars Using Ultrasonic Testing
Full text linkWooden structures are prone to internal defects, particularly cracks, which can significantly compromise their structural integrity over time. While ultrasonic testing is widely used, the relationship between ultrasonic wave behavior and crack severity is not well established. This study introduces a graded defect severity classification based on crack size and depth and evaluates its correlation with ultrasonic wave velocity, frequency, and attenuation in Abies alba (whitewood) pillars. Ultrasonic measurements were conducted on pillars with cracks of varying severity, including both defective (ranging from small to large cracks) and defect-free regions, using a digital oscilloscope and ultrasonic transducer system. Statistical analyses, including one-way ANOVA and Tukey HSD post-hoc tests, revealed significant differences in ultrasonic properties across severity classes. Among the parameters, wave velocity showed the greatest sensitivity to defect severity and correlated strongly with structural integrity, while frequency and attenuation provided supplementary but less distinct information. These findings confirm wave velocity as a reliable indicator of crack severity, and the proposed classification enhances ultrasonic data interpretation for more accurate assessment of structural degradation. This study advances the quantitative application of ultrasonic testing in timber evaluation, offering a refined approach to crack assessment in wooden pillars
Modified Component-based Model for Single and Double-angle Bolted Connections Used in Braced Steel Frames at Elevated Temperature
Full text linkThe article presents a modified component-based model for single and double-angle bolted connections used in braced steel frames under possible fire hazards. The study presents numerical models using finite element software ANSYS and a parametric analysis carried out on assemblies designed using Eurocode 3 considering bolt grade, number of bolts, angle size, and single/double angle. The analytical approach adopted for the component-based model (CBM) for the connection is used to predict the force-displacement relationships and the ultimate resistance for bolt shear failure and angle bearing. The numerical predictions showed excellent accuracy when evaluating the resistance of bolted angle steel connections at ambient and elevated temperatures. Also, the results revealed that the modified component-based model can effectively estimate the tensile resistance and the ultimate displacement of single and double-angle bolted connections. The modified component-based models can be used to investigate other failure modes like block shear fracture, bearing, and net section failure
Metaheuristic-optimized Machine Learning for Mechanical Property Prediction in Eco-friendly Rubberized Concrete
Full text linkThe disposal of discarded tires presents a global environmental challenge, but recycling them into rubber particles for concrete offers a sustainable solution, reducing waste while creating eco-friendly construction materials. However, experimental studies in this field are resource-intensive, requiring significant time and financial investment. This research develops 99 machine learning (ML) models, optimized using three improved metaheuristic algorithms, to predict the mechanical properties of rubberized concrete. The eight ML models include Adaptive Boosting, Artificial Neural Networks, Decision Tree, Gradient Boosting, K-Nearest Neighbors, Random Forest, Support Vector Machines, and Extreme Gradient Boosting, refined through the Improved Hybrid Growth Optimizer, Improved Ray Optimization, and Improved Sand Cat Swarm Optimization algorithms. A dataset of 315 experimental cases, incorporating six input variables, rubber size, rubber weight, cement content, water content, coarse aggregate, and fine aggregate, was analyzed. In addressing missing data for certain mechanical properties, a two-level sequential artificial neural network was employed. The study revealed that the XGBoost-IRO hybrid model excelled in predicting compressive and tensile strength, while the AdaBoost-ISCSO ensemble was best for flexural strength, and the XGBoost-IHGO model performed optimally for modulus of elasticity. Partial Dependence Plots and SHAP analysis highlighted the complex relationships between input variables and mechanical properties, confirming the significance of all input features. Validation through Taylor diagrams and error distribution further confirmed the reliability of the models in predicting all mechanical properties
The Role of Management Theories and Tools in Creating Added Value: Insights from the Prefabricated Residential Building Sector
Full text linkThe study investigates how management tools impact value creation across different approaches. It identifies key value-creating trends, analyses relevant tools, and provides a framework to support companies in selecting optimal strategies. A unique concept of value creation was developed, incorporating consumer expectations, corporate innovation, and competitiveness. Furthermore, cross-disciplinary concept of added value was developed. The research examined 27 management theories and tools using narrative literature review and thematic analysis, demonstrating how classical models enhance efficiency, while modern approaches prioritise adaptability and employee motivation. Classical management theories primarily improve value creation by optimising organisational processes and increasing productivity. Meanwhile, contemporary approaches focus on fostering innovation, customer engagement, and corporate social responsibility. Management tools play a crucial role in improving organisational efficiency, competitiveness, and sustainability. Techniques such as CRM systems, SWOT analysis, and Porter’s competitive strategies help companies optimise operations, enhance decision-making, and drive strategic growth. Additionally, process improvement methodologies contribute to increased customer satisfaction, innovation capabilities, and strengthened corporate relationships. The study also explores the prefabricated residential building sector, highlighting the widespread adoption of the Lean Construction approach. This method supports efficiency, waste reduction, and sustainability, making it preferred strategy in the industry. The findings conclude that continuous development and integration of management tools are essential for long-term competitiveness. Companies that strategically apply these tools within their governance structures achieve qualitative growth, market advantage, and sustainable business practices. By aligning management strategies with value creation, organisations can enhance adaptability, optimise performance, and reinforce their commitment to innovation and customer satisfaction
Hybrid and Hexagonal Planar Arrays with Discrete Ring-based Amplitude Distributions for Sidelobe Minimization
Full text linkHexagonal planar arrays are useful in radar, sonar, and wireless communications due to their ability to provide complete coverage in the azimuth plane. On the other hand, hybrid arrays that combine two different array structures, like a small central square subarray surrounded by a number of rings, are capable of providing better performance than the conventional array architectures. This paper introduces two new planar array structures that are efficiently optimized to best cope with these aforementioned applications. The first proposed design is a planar array with hexagonal structure based on discrete hexagonal-ring amplitude distributions, while the second design structure is the hybrid array architecture with a small central square subarray surrounded by a number of elements in the shape of a ring. The idea of first design structure is to re-represent the conventional element-based excitation amplitudes by discrete hexagonal-based excitation amplitudes in which they are ordered in descending from the center to the array edges. By this way, the amplitude excitations of the array elements become more compatible and practicable with the needed real-life discrete RF attenuators or amplifiers that are used for configuring the targeted excitation amplitudes. Moreover, the discrete hexagonal-based excitation amplitudes need a simpler feeding network than its element-based counterpart, thus, the array cost and complexity are greatly reduced. An optimization scheme based on a genetic algorithm is used to optimize these two proposed array structures to achieve ultra-low sidelobe levels while preserving mainlobe directivity. Simulation results confirm the effectiveness of the proposed array structures
Identification of the Transient Phase of Cutting by the Specific Cutting Force and Acoustic Emission During Metal Cutting
Full text linkThe stability of material processing during cutting concerns the continuity and coherence of the material processing conditions. A stable process results in predictable outputs such as cutting force and surface quality (roughness, integrity, texture). However, cutting processes encounter a transient phase before the cutting conditions reach their expected state. For example, during microcutting, material temporarily accumulates before the cutting edge is removed, resulting in outputs that differ significantly from what was anticipated. The aim of this paper is to provide a set of in-process parameters that can effectively indicate the transient phase of cutting. A statistical exploratory approach was utilized: face grooving tests were repeatedly conducted under the same nominal conditions and evaluated based on data deviation around the dataset's local mean. The specific cutting force and specific acoustic emission (AE) were chosen as indicative in-process parameters; additionally, the former is a common parameter used to describe the machinability of metal alloys, and the latter relates to the dynamic conditions (vibrations) of the material processing. The null hypothesis was that the specific cutting force and specific AE, as functions of the uncut chip thickness, have a uniform deviation from the predicted value within given ranges of the uncut chip thickness. A one-sample Student's t-statistic was performed on the datasets to assess the acceptability of the null hypothesis. Results of the t-statistic and the corresponding confidence intervals (CIs) indicate that there is a significant change in data distribution below what the literature describes as the minimum uncut chip thickness
Real-time Object Positioning in Vibrating Environments Using DeepLabV3+ and ResNet50-based Semantic Segmentation
Full text linkIn environments where both objects and imaging systems experience mechanical vibrations, accurate position measurement poses a significant challenge. Conventional techniques, such as laser-based, contact-based, or image-based methods, often fail under such conditions, particularly when motion artifacts eliminate stable reference points within the image. This work presents a generalized and robust method for object localization under controlled vibration, improving previous approaches by using a single semantic segmentation network (DeepLabV3+ with a ResNet50 backbone) to simultaneously segment both the object and a static reference. This unified architecture eliminates the need for separate models or manual handling of regions of interest. The method retains the use of a local coordinate system anchored at the reference centroid for vibration-resilient position estimation, but extends it to a wider variety of object shapes and configurations. Validation with ten distinct objects under induced vibrations (5–10 Hz) showed reliable performance, with submillimeter localization accuracy (MAE < 0.23 mm, RMSE < 0.29 mm) and strong correlation with ground truth (PCC > 0.99). The system also maintained real-time operation at 94 fps, supporting scalability to dynamic applications. These findings demonstrate that the proposed framework enables fast, precise, and vibration-robust object tracking, supporting applications in automated manufacturing, robotic systems, and industrial quality assurance where vibration has traditionally limited the effectiveness of image-based techniques
Compressive Properties of Al99.5 Matrix Syntactic Foams Reinforced by SiC Particles in the Matrix
Full text linkReinforced metal matrix syntactic foams (rMMSFs) were produced by liquid-state, low-pressure vacuum infiltration. Technical purity Al99.5 aluminum alloy was used as the matrix material, and ceramic hollow spheres (CHSs) with Ø2.24±0.13 mm diameter were applied as a filler material. The matrix was reinforced by 0.6 nominal size SiC with seven different volume fractions of the reinforcing material relative to the matrix material’s volume: 0 vol%, 5 vol%, 10 vol%, 15 vol%, 20 vol%, 25 vol%, and 30 vol%, respectively. The samples were investigated structurally and mechanically. Based on the microscopic investigation, the liquid-state, low-pressure vacuum infiltration was found to be a good production method of the rMMSFs; no traces of reactions between the components had been found. Based on the results of the standardized compressive test, the specific compressive strength and specific structural stiffness of rMMSFs were significantly increased for each reinforcement volume fraction, and even a 63.2±8.1% improvement can be achieved in the specific compressive strength compared to the unreinforced (UR) samples. The specific plateau strength and the specific energy absorption were improved with a 15 vol% or above reinforcement volume fraction compared to the UR foams. The decrement was caused by the stress-concentrating particles, and this effect could only be equalized by higher reinforcement content. The failure modes of the MMSFs were dependent on the dual composite properties of rMMSFs. The failure of the reinforced samples was indicated by plastic collapse followed by the appearance of a cleavage band and its widening
A Systematic Literature Review: Traffic Management for Motorcycles to Improve Urban Road Air Quality
Full text linkMotorcycles are a popular mode of transportation for many people. Their simple design makes them easier to maneuver than other types of vehicles. However, the increasing ownership of motorcycles has the potential to increase conflicts with other road users, especially in heterogeneous traffic. Motorcycle movements, especially in urban areas, can affect road performance and ultimately lead to higher levels of vehicle emissions. This research paper is a systematic literature review (SLR) examining evidence from studies on motorcycle demand management policies implemented in various countries. The focus is to evaluate the effectiveness of these policies, especially in countries with high motorcycle usage rates. To address the problem of vehicle emissions on roads with significant motorcycle traffic, several policies have been implemented by relevant authorities. These include banning motorcycles from certain areas or time periods, introducing congestion price, electronic motorcycles, using eco- friendly fuels, and promoting mode shift. The research finding is that a combination of congestion/electronic road pricing policies and a mode shift to public transportation is the most effective traffic management strategy for reducing air pollution
Examination of Relationship Between Railway Noise, Lifestyle Activities and Passive Noise Protection Solutions Among the Population Living Near the Train Marshalling Yard of Sopron
Full text linkNoise pollution from traffic is a growing social challenge. The effects of railway noise are concentrated in transport hubs, such as marshalling yards. Various sources of vehicle noise negatively affect quality of life and can disrupt everyday activities. Despite this, protection against sound effects at the individual level is practically limited to the use of passive noise protection solutions. The purpose of this article was therefore to examine the subjective correlations between railway noise events, disrupted daily activities and passive noise protection solutions found in households by means of a questionnaire survey among the population living in the vicinity of the train marshalling yard of Sopron, Hungary. The received binary (yes or no) answers were evaluated using Fisher tests, first between noise events and disturbed activities, and then between activities and noise protection solutions. The correlation values included in tables were also supplemented with correlations between the groups, combined from answer options. It could be concluded that the role of passenger and freight trains in this environment goes far beyond train marshalling. In addition, the effects on resting and recreation are outstanding, and effective solutions are to plant vegetation and use thermal insulation to reduce them. To expand the results above in the future, it is necessary to compare the answers with objective acoustic parameters with independence tests and to repeat the questionnaire survey in similar living environments in other cities to recognize regional trends