scholarly journals Tower Crane Location Optimization for Heavy Unit Lifting in High-Rise Modular Construction

Buildings ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 121
Author(s):  
Hosang Hyun ◽  
Moonseo Park ◽  
Dowan Lee ◽  
Jeonghoon Lee
Keyword(s):  
Low Cost ◽  
Modular Construction ◽  
Algorithm Optimization ◽  
Location Selection ◽  
Project Completion ◽  
High Rise ◽  
Tower Crane ◽  
Proposed Model ◽  
Study Results ◽  
Crane Selection

Modular construction, which involves unit production in factories and on-site work, has benefits such as low cost, high quality, and short duration, resulting from the controlled factory environment utilized. An efficient tower crane lifting plan ensures successful high-rise modular project completion. For improved efficiency, the lifting plan should minimize the reaching distance of the tower crane, because this distance directly affects the tower crane capacity, which is directly related to crane operation cost. In situations where units are lifted from trailers, the trailer-to-tower crane distance can have a significant impact on the tower crane operation efficiency. However, optimization of this distance to improve efficiency has not been sufficiently considered. This research proposes a genetic algorithm optimization model that suggests optimized tower crane and trailer locations. The case study results show that through the proposed model, the project manager can reflect the optimal location selection and optimal tower crane selection options with minimal cost.

POTENTIAL EVALUATION OF YELLOW COTTON (COCHLOSPERMUM REGIUM) PIGMENTS FOR DYE SENSITIZED SOLAR CELLS APPLICATION

2020 ◽  
pp. 16-21
Author(s):  
PHITCHAPHORN KHAMMEE ◽  
YUWALEE UNPAPROM ◽  
UBONWAN SUBHASAEN ◽  
RAMESHPRABU RAMARAJ
Keyword(s):  
Solar Cells ◽  
Low Cost ◽  
Dye Sensitized Solar Cells ◽  
Photoelectric Conversion Efficiency ◽  
Photoelectric Conversion ◽  
Plant Materials ◽  
Natural Pigments ◽  
Dye Sensitized ◽  
Study Results ◽  
Sensitized Solar Cells

Recently, dye-sensitized solar cells (DSSC) have concerned significant attention attributable to their material preparation process, architectural and environmental compatibility, also low cost and effective photoelectric conversion efficiency. Therefore, this study aimed to use potential plant materials for DSSC. This research presents the extraction of natural pigments from yellow cotton flowers (Cochlospermum regium). In addition, the natural pigments were revealed that outstanding advantages, including a wide absorption range (visible light), easy extraction method, safe, innocuous pigments, inexpensive, complete biodegradation and ecofriendly. Methanol was used as a solvent extraction for the yellow cotton flower. The chlorophylls and carotenoid pigments extractions were estimated by a UV-visible spectrometer. The chlorophyll-a, chlorophyll-b, and carotenoid yield were 0.719±0.061 µg/ml, 1.484±0.107 µg/ml and 7.743±0.141 µg/ml, respectively. Thus, this study results suggested that yellow cotton flowers containing reasonable amounts appealable in the DSSC production.

Drug Target Group Prediction with Multiple Drug Networks

2020 ◽  
Vol 23 (4) ◽  
pp. 274-284 ◽  
Author(s):  
Jingang Che ◽  
Lei Chen ◽  
Zi-Han Guo ◽  
Shuaiqun Wang ◽  
Aorigele
Keyword(s):  
Drug Target ◽  
Low Cost ◽  
Machine Learning Algorithms ◽  
Classification Model ◽  
Support Vector ◽  
Multiple Drug ◽  
Property A ◽  
Multiple Networks ◽  
Proposed Model ◽  
The One

Background: Identification of drug-target interaction is essential in drug discovery. It is beneficial to predict unexpected therapeutic or adverse side effects of drugs. To date, several computational methods have been proposed to predict drug-target interactions because they are prompt and low-cost compared with traditional wet experiments. Methods: In this study, we investigated this problem in a different way. According to KEGG, drugs were classified into several groups based on their target proteins. A multi-label classification model was presented to assign drugs into correct target groups. To make full use of the known drug properties, five networks were constructed, each of which represented drug associations in one property. A powerful network embedding method, Mashup, was adopted to extract drug features from above-mentioned networks, based on which several machine learning algorithms, including RAndom k-labELsets (RAKEL) algorithm, Label Powerset (LP) algorithm and Support Vector Machine (SVM), were used to build the classification model. Results and Conclusion: Tenfold cross-validation yielded the accuracy of 0.839, exact match of 0.816 and hamming loss of 0.037, indicating good performance of the model. The contribution of each network was also analyzed. Furthermore, the network model with multiple networks was found to be superior to the one with a single network and classic model, indicating the superiority of the proposed model.

Study on Selection and Optimization of Vertical Transportation Equipment for High-Rise Construction

2010 ◽  
Vol 168-170 ◽  
pp. 2376-2381
Author(s):  
Xi Jing Qi ◽  
Xiao Hu Zhou ◽  
Ming Liang Song ◽  
Feng Ming Li
Keyword(s):  
Project Management ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Close Attention ◽  
Transportation Equipment ◽  
High Rise ◽  
Practical Project ◽  
Study Results ◽  
Objective System ◽  
Comprehensive Evaluation System

High-rise buildings in China has developed rapidly in recent years and problems such as construction and vertical transportation have been paid close attention more and more by society. The safety project management objective system mentioned in this article has comprehensively considered the characteristics of high-rise construction and vertical transportation and provided a comprehensive evaluation system for vertical transportation equipment for high-rise construction, which may be used for guiding equipment selection and optimization of equipment use. Meanwhile, the study results are applied in practical project to verify its effectiveness and practicability, so as to guide the enterprises to reasonably select and use vertical transportation equipment for high-rise construction and to realize the integration benefits of the project.

Concept to Support the Flexibility of Manufacturing System through Reconfigurable Structure Based on Modular Design

2015 ◽  
Vol 816 ◽  
pp. 536-546
Author(s):  
Vladimír Rudy ◽  
Andrea Lešková
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Structural Changes ◽  
Modular Design ◽  
Production Systems ◽  
Low Cost ◽  
Modular Construction ◽  
Production Platform ◽  
Flexible Adaptation ◽  
Reconfigurable Structure

This article deals about the challenges of structural changes in manufacturing conditions. The objective of this paper is to present the modular workstations concept based on miniaturization and re-configurability trends. The article is aimed at problems of designing of production systems with a modular construction structure. The modular structure allows an individual and flexible adaptation to varying requirements but also the realization of low-cost solutions for creation of new or modernized production base. The goal is to present the example of modular workstations solutions that correspond with new designing approach. The specification of basics principles, which should help to designing flexible manufacturing systems, discussed in this paper are: modularity; integrability; convertibility; diagnosability; customization. The theoretical part provides an overview of fundamental design principles in manufacturing structures. In the first part of this article are discussed the specification of basic flexibility types in production system and the main impacts influencing design of manufacturing structures. The closing section of the article provides the specification of example solution of adjustable production platform with modular frame (called desktop factory).

scholarly journals Monitoring and Analysis of Dynamic Characteristics of Super High-rise Buildings using GB-RAR: A Case Study of the WGC under Construction, China

2020 ◽  
Vol 10 (3) ◽  
pp. 808 ◽  
Author(s):  
Lv Zhou ◽  
Jiming Guo ◽  
Xuelin Wen ◽  
Jun Ma ◽  
Fei Yang ◽  
...  
Keyword(s):  
Wavelet Analysis ◽  
Dynamic Characteristics ◽  
Horizontal Displacement ◽  
Dynamic Monitoring ◽  
High Rise ◽  
The North ◽  
Study Results ◽  
Under Construction ◽  
East West

Accurate dynamic characteristics of super high-rise buildings serve as a guide in their construction and operation. Ground-based real aperture radar (GB-RAR) techniques have been applied in monitoring and analyzing the dynamic characteristics of different buildings, but only few studies have utilized them to derive the dynamic characteristics of super high-rise buildings, especially those higher than 400 m and under construction. In this study, we proposed a set of technical methods for monitoring and analyzing the dynamic characteristics of super high-rise buildings based on GB-RAR and wavelet analysis. A case study was conducted on the monitoring and analysis of the dynamic characteristics of the Wuhan Greenland Center (WGC) under construction (5–7 July 2017) with a 636 m design height. Displacement time series was accurately derived through GB-RAR and wavelet analysis, and the accuracy reached the submillimeter level. The maximum horizontal displacement amplitudes at the top of the building in the north–south and east–west directions were 18.84 and 15.94 mm, respectively. The roof displacement trajectory of the WGC was clearly identified. A certain negative correlation between the temperature and displacement changes at the roof of the building was identified. Study results demonstrate that the proposed method is effective for the dynamic monitoring and analysis of super high-rise buildings with noninvasive and nondestructive characteristics.

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