Periodica Polytechnica (Budapest University of Technology and Economics)
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Developing High-strength, Flowable Sand Concrete by Adding Combined Industrial Ceramic and Granite Waste with Seashell Bio-waste as Fine Aggregates
Full text linkDue to its large consumption of raw materials and high construction work rates, the building industry presents one of the most effective potentials for the use of recycled materials. In an attempt to maximize landfill waste valorization and enhance concrete properties, this study investigates the combined use of industrial ceramic waste (CW) and granite waste (GW) with seashell bio-waste (SW) and their effect on the physical and mechanical properties of flowable sand concrete (FSC). For this, seven FSC mixtures were manufactured by partially replacing natural sand with different amounts of CW, GW, and SW combinations (0, 5, 10, 15, 20, 25, and 30 wt%). The results showed that up to 30% recycled aggregates could be utilized while maintaining the fresh properties of all FSC mixes. Compressive and flexural strengths as well as ultrasonic pulse velocity were significantly improved by 40%, 90%, and 6%, respectively. Both water absorption and porosity were reduced by 20% with the simultaneous addition of 30% recycled aggregates, compared to the reference concrete. Furthermore, the scanning electron microscopy analysis of some FSC mixes showed that the microstructure of FSC was enhanced with a stronger bond between the cement paste and aggregates when the three recycled aggregates were included in amounts of up to 30%. Finally, the results are encouraging when CW and GW are used simultaneously with SW in developing high-strength FSC, allowing the replacement of up to 30% of fine aggregates for sustainable construction
Comparing Vehicle Trajectories Generated by Microscopic Traffic Simulation and Vehicle Dynamic Simulation
Full text linkThis paper presents a comparative study between microscopic traffic simulation and vehicle dynamics simulation to evaluate their consistency and applicability for driver behavior analysis. The study focuses on four representative driving scenarios: roundabouts, four-way intersection, highway overtake, and U-turn. Traffic simulations were conducted using SUMO, while vehicle dynamics simulations utilized the double-track vehicle model in MATLAB SIMULINK, driven by the Pure Pursuit control algorithm. Trajectories were visually compared using x-y plots, and the maximum positional deviations were calculated. Speed profiles and heading angles were analyzed as functions of distance, complemented by a quantitative metric based on phase, amplitude, and topology errors. This metric, developed in earlier work, provides a method for comparing vehicle behaviors. The research results highlight the need to incorporate detailed vehicle dynamics into traffic simulations for improved realism, especially in scenarios with high lateral acceleration and abrupt steering inputs. Refining traffic simulations with improved vehicle behavior will also make road traffic flow predictions more realistic and reliable
Reconstruction of 3D Floating Body Motion on Shallow Water Flows Using the Smoothed Particle Hydrodynamics Method
Full text linkThe investigation of floating body motions is a frequently visited topic in the areas of wave energy converters and coastal engineering. In fluvial conditions, the design process of floating platforms and the forecast of ice jamming events are also parts of relevant applications. Apparently, the two-way coupling of the fluid and floating body forces is often a fundamental requirement in such applications leading to computationally expensive studies. In cases of open surface flow modeling, where the water depth is sufficiently small compared to the horizontal extensions of a water body, the depth-averaged shallow water equations (SWE) offer an efficient alternative of the 3D Navier-Stokes equations. Utilizing the benefits of the SWEs, we aim to reduce the 3D problem of floating body motions to the 2D shallow water framework utilizing the smoothed particle hydrodynamic (SPH) method. However, the task is not straightforward due to the explicit nature of the SWE-SPH model. As an additional constraint, the presence of a floating object determines the local water depth, which is otherwise purely driven by the equation of motion and continuity. In our model, this constraint is defined by an additional penalty term in the equation of motion to accurately predict the water depth as well as the forces acting on the floating object. As a result, a two-way coupled fluid structure interaction model is established. The proposed method is easy to be implemented and offers an efficient alternative approach to the fully resolved computations, with a reasonable loss of accuracy
Enhanced CNN-LSTM Feature Extraction and Ensemble Learning for Anomaly Detection in Photovoltaic Data
Full text linkThis study proposes an anomaly detection framework that combines CNN–LSTM feature extraction with a boosting-based ensemble strategy to improve the reliability of photovoltaic (PV) system monitoring. Real multi-source PV operational data are first preprocessed using the ISODATA clustering algorithm, which automatically adjusts the number of clusters and reduces redundancy. Principal component analysis (PCA) is then applied to lower data dimensionality while retaining key variability. A hybrid CNN-LSTM network is developed, where CNNs extract spatial features from heterogeneous PV measurements and LSTMs capture temporal dependencies in power sequences. Based on the learned representations, an ensemble model integrates the outputs of Gaussian Mixture Models (GMM), Isolation Forest (IF), and Interquartile Range (IQR) through a boosting-inspired weighting mechanism to enhance robustness under complex operating conditions. Experiments conducted on real PV datasets show that the proposed method achieves nearly 97% anomaly detection accuracy, with an average F1-score of 0.89 ± 0.03 and a recall rate of 0.91 ± 0.02. Compared with single-model baselines, the framework provides more stable performance and maintains a false positive rate below 2.1%, demonstrating its practical value for real-world PV anomaly detection
Evaluation of Jojoba Oil Biodiesel as a Potential Fuel for Combustion Application
Full text linkThe demand for efficient energy systems is rising due to environmental issues and the decline of fossil fuels. Therefore, the studies are exploring the use of biofuels as an alternative fuel. The focus of this study is to produce biodiesel from jojoba oil and use it along with other fuels in internal combustion engines. The transesterification method was used for the production of biodiesel using methanol and a catalyst (sodium hydroxide), which yielded long-chain fatty acid methyl esters (C16–C20) and physicochemical properties were investigated. Gas chromatography-mass spectrometry and nuclear magnetic resonance were used to analyze raw jojoba oil and biodiesel. Moreover, the ignition delay (ID) time and derived cetane number (DCN) were measured by an ignition quality tester (IQT). The density (870 kg m−3) and viscosity (4.21 mm2 s−1) of the biodiesel were comparable to ASTM D6751-24 requirements and were also closely aligned with US 2D petrodiesel quality. The IQT test demonstrated that biodiesel produced from jojoba oil has a higher DCN and shorter ID than US 2D petro-diesel. Thus, the overall results adequately illustrate the potential to use biodiesel as a sustainable energy application
Study of the Microstructure and Permeability of Building Stone Using X-ray Micro-tomography
Full text linkFluid transport and storage properties of porous rocks are closely related to their microstructure. Porosity is one of the most important microstructural parameters due to its importance for transport of water, gases and dissolved salts, but also for mechanical, deformation and durability properties of geomaterials used in constructions. In this study, the X-ray computed micro-tomography (XCT) was used to study the spatial distribution of porosity and permeability within the Kocbeře sandstone, which represents a very well-known and long-term used building stone in the territory of the Czech Republic. The microstructure and composition of the Kocbeře sandstone were characterized by a complex of methods, including optical polarization microscopy, scanning electron microscopy coupled with energy dispersive spectroscopy, X-ray powder diffraction, X-ray fluorescence spectroscopy and mercury intrusion porosimetry (MIP). Values of porosity and permeability of the Kocbeře sandstone derived from XCT were compared with results of MIP as well as laboratory measurements of open porosity, hydraulic conductivity and gas permeability. A very good compliance was found between the average values of sandstone porosity determined by the XCT imaging analysis, MIP and experimentally determined open porosity. However, considerable heterogeneity of porosity in the individual analyzed subvolumes was detected using XCT. Very significant inhomogeneity was also found in the spatial distribution of permeability tensors calculated for individual subvolumes. The considerable dispersion of porosity and permeability values of sandstone at the microscale is given by its microstructure. The main role here is played by intense secondary silicification, which unevenly affects the clay matrix of the sandstone
Analysis of the Impact of Static and Dynamic Driving Factors on the Consumption Difference Between LNG-and Diesel-Powered Heavy-Duty Trucks in Test Track Environment
Full text linkThe present study builds upon the authors′ previous research, which highlighted the fuel consumption advantage of LNG-powered (liquefied natural gas) trucks over conventional diesel vehicles. Expanding on this topic, the aim of this research is to analyze the influence of static and dynamic driving factors on the consumption advantage of LNG vehicles. The study was conducted in a test-track environment, ensuring optimal reproducibility with minimal external influencing factors, allowing for various types of measurements. In this research, fuel consumption values were recorded indirectly through the fleet management system (FMS) using controller area network (CAN) messages. Data distribution analysis, the Shapiro-Wilk test, and ANOVA were employed to validate the research hypotheses. Our study is unique in the field of heavy-duty vehicles (HDVs) as the measurements were performed at the test-track level, providing precise data for emission differences. The results indicate that the static driving environment (represented by different test track modules) has a stronger influence on the consumption advantage of LNG vehicles. In contrast, driving mode has a lesser effect on the consumption difference between LNG and diesel trucks
Investigating Rotating Noise Sources Using Uniform Circular Arrays: Theoretical Limits and Self-similar Beamforming Maps
Full text linkPhased microphone array measurements combined with beamforming signal processing is a widely used approach for localizing and quantifying noise sources, which can be used for turbomachinery applications. Among the various array configurations, uniform circular arrays (UCAs) are frequently employed for rotating sources due to their geometric simplicity and the practical advantage that they can be installed around a free jet or a duct without disturbing the flow. The present article investigates this array design with the aim of providing guidelines for planning proper measurement setups. Particular attention is given to two interdependent parameters: the array diameter and the measurement distance. For a simplified turbomachinery test case, a suitable measurement range is defined within the parameter plane spanned by these variables. The lower and upper bounds of this range are established through the constraints of achieving sufficient spatial resolution and avoiding spatial aliasing, for the estimation of which straightforward formulas are derived herein. Furthermore, it is shown that the parameter plane defined by array diameter and measurement distance can be regarded as the extrusion of one of its cross-sections along specific curves, referred to herein as self-similar curves, as the beamforming maps along these curves are self-similar. This property is advantageous, as conclusions can easily be drawn for the entire parameter space under investigation by carrying out a few simple calculations that utilize the formulas derived herein
Methodology for Improving Passenger Applications in Public Transport
Full text linkPublic transport plays a key role in the mobility of the population and in the efficient functioning of both urban and suburban areas. Continuous technological advancement and the changing needs of passengers create new challenges and opportunities in the development of digital solutions for public transport. Mobile applications have become an integral part of travel, enabling users′ easier access to transport information, route planning, and ticket purchase. The aim of this article is to propose a methodology that systematically analyses existing digital solutions, identifies their shortcomings, and suggests new functionalities that will enhance the comfort and efficiency of public transport. The process includes a comprehensive approach ranging from the analysis of passenger behaviour and evaluation of existing applications to the proposal of innovative solutions, followed by their development, testing, and implementation. This systematic approach ensures that new technological solutions will be optimized for a wide range of users – from daily commuters to tourists and individuals with specific needs. The proposed solution is necessary in the context of future implementation of EU directives, and its results can contribute to increasing the competitiveness of public transport and its efficient use. The article provides a comprehensive methodology that serves as a key tool for innovation in public transport applications. This methodology contributes to improving the user experience, increasing the efficiency of transport services, and supporting the overall development of public transport
Analysis of the Possibility of Introducing a Traffic Sign with a Green Border in Poland
Full text linkRoad traffic accidents constitute a significant societal challenge, leading to substantial losses in human life and material resources. The escalating number of vehicles, driven by increasing motorization rates and population growth, has exacerbated this problem. Although traffic collisions are stochastic events in temporal and spatial dimensions, their global impact remains severe, with millions of fatalities and injuries recorded annually.A survey-based methodology was employed to assess public perception of this proposed traffic management solution. The findings indicate that the introduction of such signage could contribute to a reduction in accident frequency on Polish roads. Despite isolated dissenting opinions, statistical analysis reveals majority support among respondents for adopting green-bordered advisory speed signs.The research underscores the potential efficacy of non-binding speed recommendations as a supplementary measure to enhance road safety while highlighting the importance of aligning traffic regulations with driver behavior and preferences.The article analyzes the possibility of introducing a traffic sign with a green border in Poland. The survey showed that the majority of respondents (63%) support the introduction of a sign with a green border indicating the recommended speed on Polish roads. The sign is seen as a tool that can improve traffic safety, educate drivers and increase the smoothness of driving. Among the advantages of the proposed solution, respondents pointed out to the following: educating drivers on safe speed (38%), reducing the stress of mandatory speed limits (23%), increasing traffic flow (18%) and reducing exhaust emissions (10%)