Structural lightweight concrete (SLWC) has superior properties that allow the optimization of super tall structure systems for the process of design. Because of the limited supply of lightweight aggregates in Korea, the development of structural lightweight concrete without lightweight aggregates is needed. The physical and mechanical properties of specimens that were cast using normal coarse aggregates and different mixing ratios of foaming agent to evaluate the possibility of creating structural lightweight concrete were investigated. The results show that the density of SLWC decreases as the dosage of foaming agent increases up to a dosage of 0.6%, as observed by SEM. It was also observed that the foaming agent induced well separated pores, and that the size of the pores ranged from 50 to 100 μm. Based on the porosity of concrete specimens with foaming agent, compressive strength values of structural lightweight foam concrete (SLWFC) were obtained. It was also found that the estimated values from proposed equations for compressive strength and modulus of elasticity of SLWFC, and values obtained by actual measurements were in good agreement. Thus, this study confirms that new structural lightweight concrete using normal coarse aggregates and foaming agent can be developed successfully.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5455924PMC
http://dx.doi.org/10.3390/ma7064536DOI Listing

Publication Analysis

Top Keywords

structural lightweight
24
foaming agent
24
lightweight concrete
20
normal coarse
12
development structural
8
lightweight
8
concrete normal
8
lightweight aggregates
8
coarse aggregates
8
compressive strength
8

Similar Publications

FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n.

Sensors (Basel)

December 2024

School of Mechanical and Power Engineering, Zhengzhou University, Zhengzhou 450000, China.

To address the limitations of existing deep learning-based algorithms in detecting surface defects on brake pipe ends, a novel lightweight detection algorithm, FP-YOLOv8, is proposed. This algorithm is developed based on the YOLOv8n framework with the aim of improving accuracy and model lightweight design. First, the C2f_GhostV2 module has been designed to replace the original C2f module.

View Article and Find Full Text PDF

Disturbance Robust Attitude Stabilization of Multirotors with Control Moment Gyros.

Sensors (Basel)

December 2024

Department of Aerospace Engineering, Chosun University, Gwangju 61452, Republic of Korea.

This paper presents a novel control framework for enhancing the attitude stabilization of multirotor UAVs using Control Moment Gyros (CMGs) and a Disturbance Robust Drive Law (DRDL). Due to their lightweight and compact structure, multirotor UAVs are highly susceptible to disturbances such as wind, making it challenging to achieve stable attitude control using rotor thrust alone. To address this issue, we employ CMGs to provide robust attitude control and apply Fast Terminal Sliding Mode Control (FTSMC) to ensure fast and accurate convergence within a finite time.

View Article and Find Full Text PDF

Binary Transformer Based on the Alignment and Correction of Distribution.

Sensors (Basel)

December 2024

Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.

Transformer is a powerful model widely used in artificial intelligence applications. It contains complex structures and has extremely high computational requirements that are not suitable for embedded intelligent sensors with limited computational resources. The binary quantization technology takes up less memory space and has a faster calculation speed; however, it is seldom studied for the lightweight transformer.

View Article and Find Full Text PDF

Cascaded Feature Fusion Grasping Network for Real-Time Robotic Systems.

Sensors (Basel)

December 2024

College of Engineering, Huaqiao University, Quanzhou 362021, China.

Grasping objects of irregular shapes and various sizes remains a key challenge in the field of robotic grasping. This paper proposes a novel RGB-D data-based grasping pose prediction network, termed Cascaded Feature Fusion Grasping Network (CFFGN), designed for high-efficiency, lightweight, and rapid grasping pose estimation. The network employs innovative structural designs, including depth-wise separable convolutions to reduce parameters and enhance computational efficiency; convolutional block attention modules to augment the model's ability to focus on key features; multi-scale dilated convolution to expand the receptive field and capture multi-scale information; and bidirectional feature pyramid modules to achieve effective fusion and information flow of features at different levels.

View Article and Find Full Text PDF

Investigation of Damping Properties of Natural Fiber-Reinforced Composites at Various Impact Energy Levels.

Polymers (Basel)

December 2024

Department of Automotive Engineering, Faculty of Technology, Afyon Kocatepe University, Afyonkarahisar 03200, Turkey.

Natural fiber-reinforced composites are composite materials composed of natural fibers, such as plant fibers and synthetic biopolymers. These environmentally friendly composites are biodegradable, renewable, cheap, lightweight, and low-density, attracting attention as eco-friendly alternatives to synthetic fiber-reinforced composites. In this study, natural fiber-reinforced polymer foam core layered composites were produced for the automotive industry.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!