Periodica Polytechnica (Budapest University of Technology and Economics)
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Enhancing Sustainability in Construction: Water Effect on Jute Fiber Composite Mortar
Get PDFThe use and application of natural fiber in the Construction and Building sector is gaining momentum due to its various advantages over synthetic fibers, mainly in terms of sustainability, recyclability, and biodegradability.In this paper, two aspects of the jute fiber composite mortar have been discussed. Firstly, the effect of water on the mechanical performance of the jute fiber composite mortar samples has been presented here. Secondly, the Digital Image Correlation (DIC) method has been used to analyze and determine the crack openings (mm), in the deformed specimens that occurred during the flexural tests.Notably, for 0.5% (fiber lengths: 30 mm, 10 mm, 5 mm) and 1.0% (fiber length: 30mm) fiber (with respect to the dry mortar mass) composite mortar samples prepared with the same water amount, exactly the same used for the mortar (without fiber). The reduction in flexural (−1.47 to −2.79 MPa) and compression strengths (−5.4 to −14.01 MPa) have been observed when compared with similar combinations (fiber % and fiber lengths) prepared with different amounts of water for every mixture. Whereas, when these composite mortars are compared with samples prepared with the same average water, increment in flexural strengths (0.24 to 1.45 MPa), while changes in compressive strengths ranging from −1.67 and 6.22 MPa have been noticed.The percentage of water used for the grout preparation is an important factor in influencing the mechanical performance of the composite sample. Therefore, whenever fiber is used during the composite mortar fabrication some amount of extra water is necessary for the mixture preparation
A Two-stage Method for Damage Detection in Z24 Bridge Based on K-nearest Neighbor and Artificial Neural Network
Get PDFIn this paper, we propose an effective approach for identifying damages in the Z24 bridge, a large-scale bridge in Switzerland. The dataset of the Z24 bridge is evaluated as a benchmark, reflecting the behavior of a real structure that has been used for numerous studies. However, most of the previous studies have only addressed the issues of updating the model or estimating the location and severity of damages. The core idea behind our proposed approach is to leverage the strengths of two effective Machine Learning (ML) algorithms: K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN), to assess both the location and severity of damages in the Z24 bridge. First, we employ KNN, an unsupervised learning algorithm, for pinpointing the damage location. This strategy proves highly efficient, significantly reducing computation time by circumventing the need for a loss function during KNN training. By adopting this approach, KNN effectively mitigates the risk of encountering local minima in the ANN optimization process. Subsequently, we deploy ANN to determine the damage severity. When compared to previous studies on the Z24 bridge, our proposed method (KNN-ANN) exhibits promising results. Furthermore, our results illustrate that KNN-ANN consistently outperforms traditional ANN methodologies
Failure Mechanism and Structural Safety Assessment of the Primary Support Structure of Soft Rock Tunnel: A Case Study
Get PDFBased on a soft rock tunnel in a mountainous area of northwest Yunnan Province, a refined numerical model of different support forms considering structural interaction is established to comprehensively evaluate the structural failure mechanisms and mechanical responses of different support forms. Research shows that compared to steel rib structures, the axial force and bending moment of sprayed concrete structures is larger under different combinations of support structures. Compared with a single-layer support structure, the stress distribution at each position of the double-layer I-shaped steel structure is more uniform, and the sprayed concrete structure only experiences compression damage at the corner of the side wall. As the strength of sprayed concrete increases, the stress distribution of sprayed concrete at the arch waist becomes more uniform. The stress concentration state of sprayed concrete at the corner of the tunnel wall and the plastic yield state of the steel rib structure have also been improved. The higher the concrete strength, the lower the stress ratio on the steel rib’s inner and outer sides
Shear Lag Effect and Its Additional Deflection Contribution of Composite Beam Bridges
Get PDFThe composite beam structure is widely used in the engineering field because it benefits from the advantages of two materials, presenting outstanding advantages for construction purposes. However, at present, there are issues with the analysis and solution of the composite beam structure, such as the difficulty in developing a suitable analytical theory and the low degree of refinement achieved by simulation analysis. To accurately grasp the mechanical behavior of the composite beam structure and achieve its refined analysis, this paper proposes a refined spatial grid element analysis method that can simultaneously obtain the internal forces, displacements, and stresses of various parts of a composite beam. Based on the above new method, the effects of geometrical structural factors such as wide-span ratio, high-span ratio, and web thickness with respect to the shear lag effect are analyzed. The distribution law of the shear lag coefficient and its additional deflection are analyzed. The results demonstrate that using this analysis method to calculate and analyze steel-concrete duplex type composite beams can directly obtain the internal forces and displacements of the joints of the composite beam roof, floor, and web. The spatial grid element analysis method provides both the theoretical and practical means to achieve both the overall and local refinement analysis of the composite beam structure
Direct Drive Permanent Magnet Synchronous Generator: Design, Modeling, and Control for Wind Energy Applications
Get PDFThe prominent trend in wind turbine technology centers on the adoption of direct-drive permanent magnet synchronous generators (DD-PMSG), a choice driven by their capacity to deliver superior efficiency through the elimination of gearboxes.This paper presents a comprehensive exploration of the design, modeling, and control aspects of a DD-PMSG intended for harnessing wind energy conversion. Initially, the geometrical design of the generator is meticulously carried out, adhering to predefined technical specifications and constraints. Subsequently, an in-depth internal modeling, focusing on the electromagnetic behavior of the designed generator, is executed using finite element analysis (FEA) through the Ansys Maxwell RMXpert software. Finally, the external modeling and control system integration of the designed generator, connected to the grid through power electronic converters, are simulated using the Matlab/Simulink software suite. The resulting findings underscore the efficacy and viability of the proposed generator for wind turbine applications, affirming its potential to enhance wind energy conversion systems
Technological Development of Automated Harvesting for Cultivated Button Mushroom Using Image Processing
Get PDFThe amount of mushrooms cultivated around the world is constantly increasing, and the most commonly consumed species in Europe is the white button mushroom (Agaricus bisporus). Mushroom producers are facing a permanent challenge to provide the labour for harvesting, with increasing wage demands. Due to high market quality requirements, early automatized technologies are currently not able to replace manual picking. Our research therefore aims at facilitating the automated picking of button mushrooms and improving the technology via image processing. We aim to develop a method that can select the right size of mushrooms from field images and produce their picking position. We used Python programming language, along with the OpenCV and NumPy libraries, to implement image processing on real scenario images. The development considered factors such as fused- or overlapping mushroom heads, emergence of mushrooms from under caps, fallen or laterally visible stumps, cover soil contamination, and white mycelia which make detection significantly more difficult. We managed a solution for handling fruiting bodies that extend beyond the edge of the image due to the small field of view. The results indicated that the quality of photographs is crucial for the program's performance, as improper lighting, the presence of shadows. The efficiency of the algorithm was significantly affected by the 82% accuracy of the OpenCV Watershed segmentation algorithm, which in some cases could not separate objects. The program processed the images at an average speed of 0.78 seconds and produced the coordinates with a 92% success rate
The Potential of Steam Generating by The PMMA Fresnel Lens Concentrator for Indoor Solar Cooker Application
Get PDFSolar power is an alternative energy source that can be used for cooking. It is a simple, secure, and useful way to cook food without using conventional fuels that pollute the air. Solar cookers offer various benefits to the user’s health, productivity, and income as well as to the environment. Solar energy is abundant in a tropical country like Indonesia, making it a dependable and sustainable of energy resource. The study’s goal is to analyze the potency of steam produced by a solar cooker that uses a Fresnel lens concentrator. The thermal performance of the Fresnel lens concentrator with a conical receiver on the solar cooker prototype is discussed in this research. In the construction of solar cookers, PMMA (Polymethyl-Methacrylate) Fresnel lenses, manual trackers, and conical receiver types are used. The research conducts an experimental analysis of the thermal performance of the prototype solar cooker using a Fresnel lens concentrator with a conical receiver. This empirical approach provides valuable data on the efficiency and effectiveness of the solar cooker design. The experiment result shows the cumulative average solar irradiation, the average collection of solar energy per time of Fresnel lens concentrator, and the heat utilized of steam from conical receiver are 709.09 W/m², 456.14 Watt, and 383.88 Watt, respectively. The results of this study suggest that Fresnel lens concentrators are a promising development for indoor solar cookers and therefore provide a pathway for increased utilization of solar cooking technology
Innovative Work Order Planning with Process Optimization Using Computer Simulation in the Automotive Industry, in the Case of Repair Workshops
Get PDFThis article introduces a novel approach to enhance the efficiency of work schedule management in automotive repair shops during the planning phase, leveraging computer simulation techniques. The primary focus of this study is the optimization of the scheduling process, specifically the sequencing of car repairs, aimed at minimizing the average repair time. The proposed simulation model harnesses the power of the FlexSim simulation environment, incorporating an embedded optimization module. The article outlines the fundamental stages involved in constructing the simulation model, encompassing essential input data and information. Furthermore, the article presents empirical results demonstrating the significant impact of various simulation scenarios on resource utilization, production costs, and process duration
Applying Cluster Analysis for the Investigation of Travel Behavior and User Profiles
Get PDFUrbanization leads to a surge in demand for transportation and infrastructure improvements. In this context, understanding and optimizing travel behavior are crucial for effective transportation planning. This research investigates travel behavior patterns and user profiles in the realm of urban mobility. The study adopts an approach utilizing real-world data from an activity-based dataset collected through a survey. The methodological framework is characterized by a multi-step process which includes data preprocessing, cleaning, and aggregation, as well as principal component analysis and k-means cluster analysis with inertia evaluation for an optimal number of clusters. The cluster analysis unveils seven distinct clusters. Stability lovers are elderly people who prefer public transport, happiness seekers are attraction-driven car users, weekend shoppers, park goers, and sports practitioners rely on their cars for their activities, too. Furthermore, inflexible travelers value the service quality and "routine enthusiasts" stick to travel routines. Notably, bicycle usage prevails among stability lovers and routine enthusiasts, while shared transportation gets little attention in any of the clusters. By recognizing the adaptability of this methodology to specific city contexts, current research provides a way to understand travel behavior thus offering valuable insights for informed transportation policy planners
Learning from Failure and Factors Influencing Failure
Get PDFFailure is a ubiquitous and inescapable element of life, thus sooner or later we will all have to deal with failure-possible scenarios. It is impossible to avoid failure and blunders, even with stringent procedures, employee education, and/or the implementation of the latest technology. This holds true even for persons who are incredibly successful and well-respected, since most effective leaders have more professional failures than triumphs. Their capacity to learn from their mistakes is a key factor in determining how successful they are, and this has led to, learning from failure becoming a more popular topic for research into organisational learning and individual development. In this article, we have compiled many studies how to learn from failure effectively and the variables that may affect this process