Periodica Polytechnica (Budapest University of Technology and Economics)
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Calibration of Hypoplastic Parameters – Two Different Aspects
Get PDFNumerical modeling serves as a widely utilized method for addressing geotechnical concerns. A pivotal aspect of this modeling process is the accurate characterization of material behavior. The connection between stress and strain tensors within soil is explicated by the soil constitutive equation, which is reliant on factors like soil type and deformation circumstances. One notable model is hypoplasticity, which has been in use for more than three decades. This research aims to calibrate the hypoplastic parameters for Danube sand using the SoilTest Module of PLAXIS. The constitutive hypoplastic model for Danube sand was fine-tuned through a series of numerical simulations. The parameter calibration occurred twice: initially according to 5 cycles of hysteresis loop of stress–strain diagram of cyclic triaxial testing, and then subsequently in accordance with strain trends observed after ten thousand cycles. A comparison was drawn between parameters determined from the overall strain trends and those calibrated based on the five cycles. The findings indicate that while the model calibrated during a specific segment of testing can accurately predict strain values during compression and extension, it falls short in forecasting the accumulated settlement following prolonged cyclic loading. This suggests the model’s limited capability in anticipating long-term cyclic load effects on settlement behavior
Meso-scale Study of Bond Behavior between Ribbed Steel Rebar and Fiber-reinforced Cementitious Composite Considering Rebar Rib Geometry
Get PDFThis study aims to develop a meso-scale finite element approach to investigate the pull-out behavior of ribbed steel rebar and fiber-reinforced cement composites. We considered separately the three phases of steel fibers, cement composite matrix, and rebar within the meso-scale finite element model. A random distribution of fibers was generated in the matrix based on the geometric characteristics of the fibers and their volume fraction. By employing the interfacial transition zone (ITZ) model, the interaction between rebar and fibers with cement composite was simulated. Experimental pull-out tests were conducted to determine the parameters of the model. A meso-scale finite element model was validated and the effect of rebar diameter and fiber volume fraction on the bond behavior of rebar with fiber-reinforced cement composites was examined. In accordance with the experimental results, the bond-slip curve obtained with the meso-scale finite element model can be divided into five areas: non-slip, slight slip, splitting, decreasing, and residual. Additionally, it can be observed that fiber-free cement composites fail by splitting, whereas specimens containing fibers fail by sliding. This numerical model is therefore able to predict and estimate the influence of a variety of parameters on the pull-out response between fiber-reinforced cement composite and ribbed bar and failure mechanisms without the need for expensive and time-consuming testing
Competition of Three Chaotic Meta-heuristic Algorithms with Physical Inspiration for Optimal Design of Truss Structures
Get PDFChaos maps create a significant improvement in the optimization results of meta-heuristic algorithms by creating a balance between the stages of exploration and exploitation. The optimization algorithms of structures are strongly non-linear and non-convex, having several local optima. Chaotic functions, while creating chaotic jumps, provide the conditions for escaping from local optima to global optima. Most of the meta-heuristic algorithms fall into the trap of local optima and suffer some kind of premature convergence. In this paper, by forming three scenarios, chaos functions can be embedded into the exploration, exploitation or both stages at the same time, and improve the results of meta-heuristic algorithms. The considered algorithms are inspired by physical phenomena, with the possibility of accessing classical and regular relations, the effectiveness of chaos functions in meta-heuristic algorithms are increased. Nowadays, chaotic algorithms are widely utilized by researchers and are considered as a challenging topic. In the present research, the effects of logistic and Gaussian chaos functions on the optimization results of three physically inspired meta-heuristic algorithms are investigated. These algorithms include Chaotic Thermal Exchange Optimization (CTEO), Chaotic Big Bang-Big Crunch (CBB-BC), and Chaotic Tug-of-War Optimization (CTWO)
Seismic Performance Assessment of Corroded Reinforced Concrete Columns Based on Codal Provision and Empirical Formulations
Get PDFCorrosion is a major threat to the early degradation of reinforced concrete (RC) structures. This deterioration leads to a reduction in the overall ductility and load-carrying capacity of RC structures. In RC structures, columns play a crucial role as columns take both structural and seismic loads. When columns are affected by corrosion and subjected to seismic events simultaneously, columns may collapse suddenly. This sudden failure poses risks to human beings as well as the surrounding environment. Hence, evaluating the residual capacity of corroded RC columns is essential to implement preventive and rehabilitation measures before a catastrophic failure occurs. The objective of the current study was to assess the performance and reliability of existing design guidelines and analytical models in estimating the residual lateral load-carrying capacity of corroded RC columns. A dataset containing 157 rectangular corroded RC columns was analyzed using various design guidelines and analytical models, and their performances were evaluated using performance indices. Among all the design guidelines and analytical models, the EM-3 model (GB 50010–2010 design guideline) and the EM-7 model respectively demonstrated superior performance. Moreover, the EM-7 model excelled among all the considered design guidelines and analytical models, revealing significant values for various performance indices
The Urban Walking Tour as an Experience-based Methodology for Built Environment Education in Budapest
Get PDFBuilt Environment Education (BEE) plays an important role in urban sustainability as citizens who are more aware of the surrounding architectural heritage have better opportunities to develop a sense of place and place attachment. Themes and stories make the architectural fabric of a city more legible that is why urban walking tours are such a popular format for BEE initiatives. These experience-based educative events are originally constructed for visitors (mainly tourists) of a city to receive in-situ impressions of the built heritage during their visit. But in recent years, the new phenomenon of proximity tourism appeared, inviting locals to participate in walking tours to discover their own neighbourhood, rendering this tourist-focused activity into a BEE tool for adults.Urban walks have been used in architectural education at the university level for quite some time, and recently organisations focusing on BEE have adapted the format as well, which therefore can reach a wide range of audiences. This research presents the quantitative and geo-referenced analysis of 449 photos taken during the walking tours by participants and a qualitative content analysis of the photos. The results of a questionnaire completed by 119 students upon the end of their walking tour are presented and analysed to determine the effectiveness of this BEE methodology. Results show that the experience-based format of urban walking tours in the context of BEE can contribute to the forming of sense of place for participants, and therefore should be considered as an educational tool
Comparative Analysis of Traditional and Modern Religious Buildings in Terms of Materials and Construction Techniques: The Turkish Mosques Cases
Get PDFReligious buildings are cultural symbols of societies in urban life. Mosque architecture, one of the religious structures that entered Turkish history and architectural culture with the acceptance of Islam by the Turks, developed over time and reached its peak in terms of architectural formation during the Ottoman period. Although religious buildings are thought to be less affected by social change throughout history, unlike other architectural structures, mosques are seen to be affected by the social and cultural structure that changes over time. Religious buildings, apart from being places of worship in social life, are also meeting points and social sharing areas. This situation shows that it will not be possible for religious buildings to remain indifferent to the changing needs, building materials and living standards over time. The aim of the study is to explain the use of developing and transforming materials and construction techniques in mosques in Türkiye. Within the scope of the study, the reflection of traditional and modern architecture in mosques was discussed and the transformation of buildings in different periods was examined. In this context, examples of traditional and modern mosques built in different periods were discussed with the comparative analysis method. By examining how the classical, iconic elements of mosque architecture were handled in a modern style, their changes in terms of materials and construction techniques were questioned. As a result, it is aimed to be a reference for future studies by looking at the architectural variations of changing religious buildings from past to present
Ovarian Cancer Detection Based on Elman Recurrent Neural Network
Get PDFThe early detection of cancers increases the possibility of health recovery and prevents the disease from becoming a silent killer. This study introduces an effective method for identifying ovarian cancer (OC) using Elman Recurrent Neural Network (ERNN), which can recognize cancer via mass spectrometry data. The network has a topology of 100 input neurons for receiving data, five neurons for hidden and context layers, and two output nodes to indicate the status. The proposed method uses reduced-size features, including ion concentration levels at specific mass/charge values, which are trained using various learning algorithms to determine the suitable one that achieves the best results. The experimental results show that all the training algorithms achieve about 100% performance rate, with the Levenberg Marquardt (LM) being the most accurate and fastest algorithm, which converges after six epochs and achieves 0.0035, 0.0045 and 0.0045 mean square errors for training, validation, and test performances, respectively. Based on comparative results, the proposed LM-ERNN method outperforms other OC detection methods and holds promise for detecting other types of cancer
Investigation of the Replication Quality of Microstructures on Injection Moulded Specimens Made from Recycled Polypropylene Composites Reinforced with Carbon Nanotubes
Get PDFDuring the research, functional microstructures were created on the cavity surface of the injection moulding tool using femtosecond laser technology. Automotive-grade polypropylene (PP), as well as its recycled and carbon nanotube-reinforced composites, were used as the raw materials. The replicated structures were examined using confocal microscopy. It is expected that by optimizing the process parameters, the filling of the structured cavity surface with nanocomposite materials can reach a quality level comparable to plastic specimens made from non-reinforced raw materials. The aim is to provide results of scientific and industrial value to demonstrate the influence of the modified mould surface on the flow of the polymer melt and thus on the filling of the injection moulded products
Assessing Job Accessibility and Sustainable Mobility among Low-income Groups in Penang, Malaysia
Get PDFSustainable mobility emerges as a more viable approach for addressing urban mobility challenges and enhancing overall quality of life. The primary cause of urban mobility issues may be attributed to the urban built environment, wherein various physical features such as buildings, public infrastructure, and transit systems have significantly contributed to the reliance on private vehicles. Hence, this study examines job accessibility and the background of mobility among the low-income groups who are the urban workers in Penang Island, Malaysia to determine the factor of this target group's dominant transport mode choice. Using the quantitative method, this study was conducted using a questionnaire with 306 respondents selected by stratified random sampling based upon a ratio to represent the low-income households in the northeast and southwest districts of Penang. The study revealed that individuals from low-income backgrounds exhibit a significant reliance on privately owned vehicles. Furthermore, individuals in question exhibit a preference for owning and utilising economically viable, temporally expedient modes of transportation that optimise spatial efficiency, such as motorbikes, for their daily commute to their place of employment. Policymakers may take into account the factors of affordability and punctuality when formulating a transport system that is characterised by both cost-effectiveness and efficiency, thereby addressing the mobility requirements of low-income groups
Exploring an Interaction Model for Land Used Intensity-traffic Congestion
Get PDFTraffic flow is a result of the connection between the derived demand and land use. The derived demand varies in space and time, this study explores how traffic congestion is correlated with land use patterns. Historically, statistical models were used to predict and analyze these patterns. The methodology of this study is to investigate this interaction by statistical methods such as linear regression modeling. This analysis was performed using various land use types that could influence the demand. From the regression analysis, the best influence variables that affect the model are land use variables. The strong statistical parameter is commercial land use, which affects traffic volume, and causes the highest traffic congestion. In addition, correlation values are negative, meaning that as commercial land use increases, traffic flow increases and road capacity decreases. When modeling with the commercial land use variable, we conclude the value of R-Squared = 0.87 and that the relationship is an inverse strong relationship between traffic volumes and commercial land use. Mostly, land use govern traffic demand