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Abstract

Worldwide, precast and hybrid construction methods are becoming increasingly popular in the construction industry. But many problems occur during the fabrication, such as segregation, bleeding, scaling, plastic shrinkage, dust formation, honeycombing, sintering, high sorptivity, and high permeability and transportation. This problem may be caused by an ineffective curing process that affects the quality of concrete and construction. In addition, it provides inadequate and incomplete cement hydration that has a 20% negative effect on the desired properties of the concrete. Various researchers have demonstrated the components of self-curing lightweight concrete that can enhance strength and physicochemical properties, and address the above-mentioned issues. In this review, the role of the self-curing mechanism in lightweight concrete based on the various self-curing chemical admixtures such as polyethylene glycol (PEG), superabsorbent polymer (SAP), polyvinyl alcohol (PVA), sodium lignosulfonate and calcium lignosulfonate as self-curing agents are discussed in detail. Also, this paper briefly reports on the scope, significance, mechanisms, and tests for self-curing lightweight concrete. Overall, this review analyzes the possibilities of future research perspectives on self-curing lightweight concrete with sustainable materials and fibres with comparative technical information.

Open access

Abstract

Sensors are the main components in Cyber-Physical Systems (CPS), which transmit large amounts of physical values and big data to computing platforms for processing. On the other hand, the embedded processors (as edge devices in fog computing) spend most of their time reading the sensor signals as compared with computing time. The impact of sensors on the performance of fog computing is very great, thus, the enhancement of the reading time of sensors will positively affect the performance of fog computing, and solves the CPS challenges such as delay, timed precision, temporal behavior, energy, and cost. In this paper, we propose an algorithm based on the 1st derivative of the sensor signal to generate an adaptive sampling frequency. The proposed algorithm uses an adaptive frequency to capture the sudden and rapid change in sensor signal in the steady state. Finally, we realize and tested it using the Ptolemy II Modeling Environment.

Open access

Abstract

This study examines the economic optimisation of existing district heating systems. A new approach has been taken to solving a long-standing problem. The authors describe the input-output model of the system, the balance equations for the thermal equilibrium of the system, and the heat transfer system. From the balance equations of the series-connected system elements, the resultant heat transfer balance equation and the resultant power transmission equation are derived. In an example, the authors detailed how perturbations in some input variables can be corrected with other variables. The equations presented and the concepts introduced form absolutely new scientific results.

Open access

Abstract

Selecting the construction delivery method during the contracting period is one of the most important decisions determining the quality of large-scale infrastructure projects. Infrastructure projects have the most complex production processes in civil engineering. Infrastructure projects are among the most complex and resource-intensive endeavours in civil engineering due to their size, scope, multidisciplinary nature, regulatory requirements, financing challenges, environmental considerations, and the need for long-term planning and maintenance. Effective project management, collaboration, and a deep understanding of these challenges are crucial for the successful execution of infrastructure projects. Implementing such projects inevitably demands proper quality management throughout the project lifecycle. Two primary types of construction contracts are under implementation worldwide: Design-Bid-Build (DBB) and Design–and–Build (DB) contracts. In the Western Balkans region, both types of contracts are utilized for infrastructure projects, A noticeable trend is emerging toward transitioning from DBB to DB contracts. This paper provides a comprehensive analysis of quality management within the context of construction contracts with a focus on the roles and responsibilities of key stakeholders and how these factors affect the achievement of quality objectives while managing constraints related to cost and time. This research aims to improve construction practices by selecting an adequate type of contract for construction practices and ensuring successful project outcomes.

Open access

Abstract

In this study, nonlinear control design is presented for trajectory tracking of Tricopter system. A Fractional Order Proportional Derivative (FOPD) controller has been developed. The performance of controlled Tri-copter system can be enhanced by suggesting modern optimization technique to optimally tune the design parameters of FOPD controller. The Spotted Hyena Optimizer (SHO) is proposed as an optimization method for optimal tuning of FOPD's parameters. To verify the performance of controlled Tricopter system based on optimal SHO-based FOPD controller, computer simulation is implemented via MATLAB codes. Moreover, a comparison study between SHO and Particle Swarm Optimization (PSO) has been made in terms of robustness and transient behavior characteristics of FOPD controller.

Open access

Abstract

This paper introduces a stereoscopic image and depth dataset created using a deep learning model. It addresses the challenge of obtaining accurate and annotated stereo image pairs with irregular boundaries for deep learning model training. Stereoscopic image and depth dataset provides a unique resource for training deep learning models to handle irregular boundary stereoscopic images, which are valuable for real-world scenarios with complex shapes or occlusions. The dataset is created using monocular depth estimation, a state-of-the-art depth estimation model, and it can be used in applications like rectifying images, estimating depth, detecting objects, and autonomous driving. Overall, this paper presents a novel dataset that demonstrates its effectiveness and potential for advancing stereo vision and developing deep learning models for computer vision applications.

Restricted access

Abstract

Scour around the bridge piers is the main cause of bridge failure below any bridge pier placed within the waterways. It is more than hundred years back a number of researchers described the vortex shedding phenomenon and the resulting Aeolian tones from a circular cylinder. Since then there have been a large number of investigations dealing with various aspects of this phenomenon. In many practical works and situations, flow takes place around more than one obstruction and objects in close proximity. Invariably in all these cases, interference effects occur and the forces on the obstructions are much influenced by these effects. These effects play a key role in the structures like flow-induced vibration of TV and transmission towers, and in many other practical situations. In this research paper the changes in the flow field that occur due to the interference effects are shown, analysed and the results as given in literature are compared with the present experimental work. The features have been brought out in this paper mainly make use of stand and geometry of circular cylinders in close proximity and the flow part of geometry in side by side arrangement.

Restricted access
Pollack Periodica
Authors:
Nándor Vincze
,
Kristóf Roland Horváth
,
István Kistelegdi
,
Tamás Storcz
, and
Zsolt Ercsey

Abstract

As part of the energy design synthesis method, complex dynamic building simulation database was created with IDA ICE code for all family house building configurations for a considered problem. In this paper, the annual heat energy demand output parameter is considered to serve as basis of a building energy design investigation. The sensitivity analysis performed by Morris' elementary effect method was used. As the result of the sensitivity analysis of the output parameter, the most important input parameters can be identified, that influence the buildings' energy efficiency, that can support further building designs.

Open access

Abstract

The aim of the research was to carry out the One-at-a-Time sensitivity analysis of a tree burning experiment simulation with a novel fuzzy logic-based method. It was observed that the precent of the remaining tree is sensitive to the moisture content, the crown-base diameter and the tree height. The other variables, which are maximum mass loss rate, maximum heat release rate, and maximum temperature at the top of the tree are moderately sensitive or not sensitive to the selected parameters. The presented results can be used in sensitivity studies and wildfire simulations.

Open access

Abstract

This study uses a three-layer backpropagation neural network combined with particle swarm optimization to control the foamed bitumen in cold recycling technology. The foaming process of bitumen is non-linear and depends on dynamic temperature. By developing a neural network model, this study effectively captures the complex relationships between temperature, water content, air pressure, and the expansion ratio and half-life of foamed bitumen. The integration of particle swarm optimization enhances the accuracy and convergence of the neural network model by optimizing the initial weights. This optimization process improves the model's ability to predict and control the quality of foamed bitumen accurately. It serves as a valuable tool for the rapid development of high-quality cold asphalt design.

Open access