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Abstract
The manufacture of High-Performance Concrete (HPC) in bridge deck construction is part of an experimental framework that is also developing in the numerical domain to fill the existing gaps in understanding its behavior. However, the numerical modeling of HPC for bridge decks remains largely under-explored. It is precisely this gap that has sparked our interest in this research area, thus giving our work its innovative character.
This study primarily aims to deepen the understanding of the behavior of HPC bridge decks while manufacturing an efficient and economical HPC using local materials possessing very high properties (mechanical, physical, elastic, durability, and implementation) and advanced numerical modeling. This modeling has enabled us to study the behavior of HPC bridge decks in relation to cracking through the Extended Finite Element Method (X-FEM), an innovative solution that enables the modeling of discontinuities without complicating the process. This has been confirmed by the quality of the results, which show an excellent correlation with experimental data, underscoring the accuracy of the modeling. These results also reveal that the use of HPC in bridge construction can significantly reduce degradation risks while enhancing their performance. Consequently, the adoption of HPC stands out as a beneficial strategy, not only to minimize bridge degradation but also to extend their durability.
Abstract
Spatial data management is crucial for applications like urban planning and environmental monitoring. While traditional relational databases are commonly used, they struggle with large and complex spatial data. NoSQL databases provide support for unstructured data and scalability. This article compares the performance and disk space usage of SQL Server (a relational database) and MongoDB (NoSQL database) using an open-source library. Experiments conducted with the OpenStreetMap dataset from Central America show that the MongoDB database outperformed the relational SQL Server database in most cases, offering practical advantages for spatial data management in Geographic Information System applications.
Abstract
This study is devoted to condition-based maintenance using vibration analysis. It proposes a numerical and experimental methodology to assist in the detection and vibratory monitoring of chipping faults on gear teeth.
The aim of this work is to model the dynamic behavior of the gear link and to treat the vibration behavior of gear flaws theoretically and experimentally. This article is going to study the case of a breast gear, a defect located on the wheel, another defect on the pinion and the wheel and the insufficient center distance defect based on experiments carried out on a test bench manufactured in the laboratory.
Abstract
Climate change manifested its adverse impacts last year, with an extreme drought leading to a drastically low water level in Lake Velence, Hungary. Nature-based solutions have the potential to alleviate these impacts locally. While a few initiatives have been implemented in Hungary, widespread adoption of these solutions is expected to be a goal for the more distant future.
This research focuses on one catchment at Lake Velence to evaluate decision-maker's readiness and urban water management infrastructure for broadly implementing nature-based solutions. Methods include delineating the stormwater system and creating a numerical model to evaluate rainfall-runoff processes and the possible impacts of nature-based retentions. Surveys among local mayors were conducted to assess their perception of existing water infrastructures and implementations of nature-based solutions. Its widespread use may become significant, but its effect on the lake's water level remains negligible.
Abstract
This study focuses on the optimization dynamics of racing go-karts, which is heavily influenced by the frame's stiffness. Lacking suspensions and differentials, go-karts rely on the frame stiffness for wheel balancing and skid prevention by lifting the inner rear wheel during turns. Utilizing a rigid-flexible model in MSC Software ADAMS View, validated by frame deformation measurements, this research integrates finite element analysis with multibody techniques. The model, leverages computer aided design files for frame geometry and employs finite element analysis for frame validation. It facilitates evaluating go-kart dynamics through simulations, aiding in maneuver testing and design optimization. This approach provides a comprehensive framework for advancing go-kart designs.
Abstract
In China, the decline of industrial communities suffering from both the aging of physical space and the breakdown of social relations. How to make marginalized and closed industrial communities actively integrate into the development of urban renewal has gradually become an issue of concern.
The paper takes the “Jingzhou New Town Industrial Park Urban Design Project” as an opportunity to explore a transformation path suitable for China's national conditions through the study of the history, culture, current problems, and renewal strategies of this heritage-type industrial community.
The study finally proposes three renewal strategies for industrial communities, which provide samples with certain reference value for the renewal of old industrial communities.
Abstract
With the development of time, people have more emotional needs for interior spaces. Interior lighting design is an extremely important part of interior design, especially in children's healthcare. In order to meet the needs of child patients and healthcare professionals for ward lighting, it is necessary to comply with various standards while also designing emotionally, emphasizing the positive effects of light on the psychology and health of the user. A literature research approach was used to combine the current status of interior lighting in healthcare spaces, culminating in the integration of the concept of emotional design into the lighting design of children's wards.
Abstract
This study combines theoretical research and practical case studies to explore effective methods for renovating rural architecture within the context of Chinese new rural construction. By analyzing the current state of existing rural architectures, identifying their characteristics and shortcomings, and applying the theory of architectural semiotics, this study proposes an innovative model for rural architecture renovation. The aim of this research is to provide valuable insights and optimization strategies for the revitalization of rural architectures in China, ultimately contributing to the sustainable development of rural areas and the preservation of regional culture.
Abstract
Multi-layered walls are commonly used building elements that have the potential to reduce cooling loads by improving thermal insulation. This paper investigates the potential of reducing cooling load using different types of multi-layered. For this purpose, a model of a small room (1.15 × 1 × 1 m) was constructed. A software code based on the radiant time series method was developed using MATLAB to extract heat gain results. The results were verified with other researchers, and there was a 0.89% error. Overall, the results show that using solid or hollow bricks in construction can be an effective way to reduce heat gain, where Wall-C achieved the minimum heat gain of 60.8 W m−2 compared to 66.207 and 71.225 W m−2 for Wall-A and Wall-B respectively. The reasons for this could be due to the insulation hollow area provided by the bricks, which tends to reduce heat transfer through the wall.
Abstract
In artificial intelligence, combating overfitting and enhancing model generalization is crucial. This research explores innovative noise-induced regularization techniques, focusing on natural language processing tasks. Inspired by gradient noise and Dropout, this study investigates the interplay between controlled noise, model complexity, and overfitting prevention. Utilizing long short-term memory and bidirectional long short term memory architectures, this study examines the impact of noise-induced regularization on robustness to noisy input data. Through extensive experimentation, this study shows that introducing controlled noise improves model generalization, especially in language understanding. This contributes to the theoretical understanding of noise-induced regularization, advancing reliable and adaptable artificial intelligence systems for natural language processing.
