Reliability and sensitivity analysis of cold-bent curtain wall glass

Li, Honglei; Huang, Xianzhen; Jin, Shujun; Jiang, Zhiyuan; Wang, Bingxiang

doi:10.1016/j.jobe.2022.104116

“…(x i , y i ) is defined as the position coordinates of grid k, where x i and y i denote its horizontal and vertical coordinates, respectively. To facilitate the calculation and processing, each grid attribute is assigned a value, as shown in Equation (2). The three values of 0, 1, and 2 are used to represent the three states of the grid: obstacle, uncovered, and covered grids, respectively, so the position attribute of grid k can be represented as (x i , y i , f k ).…”

Section: Wall Griddingmentioning

confidence: 99%

“…At present, with the rapid development of the social economy and the improvement in people's living standards, the application of glass curtain walls in buildings is becoming increasingly popular [1][2][3]. These glass walls need to be regularly cleaned to prolong building service life [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A Full-Coverage Path-Planning Algorithm for a Glass-Curtain-Wall-Cleaning Robot Driven by Ropes

Zhang

¹

,

Li

²

,

Jia

³

et al. 2023

Applied Sciences

1

0

View full text Add to dashboard Cite

Rope-driven robots are increasingly being applied for the efficiently cleaning of glass curtain walls. However, increasingly complex wall surfaces and the various shapes of obstacles may block the robot and reduce coverage. In this study, three-DOF rope-driven cleaning robots and a full-coverage path-planning algorithm were developed to achieve global operation. The robot adopts a five-rope parallel configuration, and four winches are mounted on the wall and one on the ground to produce 3D motion performance. We used a grid method to build the wall model to mark obstacles, and then we decomposed it according to the wall curvature to better access cleaning subareas. To further increase the cleaning coverage rate, a full-coverage path-planning algorithm based on an improved priority heuristic was designed, which does not ignore the inset area of U-shaped obstacles. By introducing two sets of priority criteria to judge the forward direction, the robot can switch directions to cover a whole area when encountering U-shaped obstacles. Furthermore, by planning a return route requiring the least amount of time when entering a dead zone, an escape strategy was developed to prevent the robot from being unable to choose a direction. The experimental results show that the robot, after applying the proposed path-planning algorithm, could complete the global cleaning of complex glass walls with various obstacles.

show abstract

“…Considering the influence of random factors, Li et al [9] adopted Monte Carlo and adaptive Krieger-Monte Carlo simulation methods to analyze the reliability of cold-formed curtain wall glass. Based on this, a reliability sensitivity analysis of the curtain wall glass was conducted to evaluate the influence of random changes in different parameters on the reliability of the curtain wall.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on HMM model

Yafeng,

Yan,

Yongheng

et al. 2024

Preprint

0

View full text Add to dashboard Cite

To address the shortcomings of traditional reliability theory in characterizing the stability of deep underground structures, the advanced first order second moment of reliability was improved to obtain fuzzy random reliability, which is more consistent with the working conditions. The traditional sensitivity analysis model was optimized using fuzzy random optimization, and an analytical calculation model of the mean and standard deviation of the fuzzy random reliability sensitivity was established. A big data hidden Markov model and expectation-maximization algorithm were used to improve the digital characteristics of fuzzy random variables. The fuzzy random sensitivity optimization model was used to confirm the effect of concrete compressive strength, thick-diameter ratio, reinforcement ratio, uncertainty coefficient of calculation model, and soil depth on the overall structural reliability of a reinforced concrete double-layer wellbore in deep alluvial soil. Through numerical calculations, these characteristics were observed to be the main influencing factors. Furthermore, while the soil depth was negatively correlated, the other influencing factors were all positively correlated with the overall reliability. This study provides an effective reference for the safe construction of deep underground structures in the future.

show abstract

“…Xiao et al 8 proposed a new effective sampling method to estimate the fault conditions and reliability sensitivity indices using a two-stage Markov chain Monte Carlo simulation. Considering the influence of random factors, Li et al 9 adopted Monte Carlo and adaptive Krieger-Monte Carlo simulation methods to analyze the reliability of cold-formed curtain wall glass. Based on this, a reliability sensitivity analysis of the curtain wall glass was conducted to evaluate the influence of random changes in different parameters on the reliability of the curtain wall.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on hidden Markov model

Yao,

Zhu,

Li

et al. 2024

Sci Rep

0

View full text Add to dashboard Cite

To address the shortcomings of traditional reliability theory in characterizing the stability of deep underground structures, the advanced first order second moment of reliability was improved to obtain fuzzy random reliability, which is more consistent with the working conditions. The traditional sensitivity analysis model was optimized using fuzzy random optimization, and an analytical calculation model of the mean and standard deviation of the fuzzy random reliability sensitivity was established. A big data hidden Markov model and expectation-maximization algorithm were used to improve the digital characteristics of fuzzy random variables. The fuzzy random sensitivity optimization model was used to confirm the effect of concrete compressive strength, thick-diameter ratio, reinforcement ratio, uncertainty coefficient of calculation model, and soil depth on the overall structural reliability of a reinforced concrete double-layer wellbore in deep alluvial soil. Through numerical calculations, these characteristics were observed to be the main influencing factors. Furthermore, while the soil depth was negatively correlated, the other influencing factors were all positively correlated with the overall reliability. This study provides an effective reference for the safe construction of deep underground structures in the future.

show abstract

Reliability and sensitivity analysis of cold-bent curtain wall glass

Cited by 6 publications

References 35 publications

A Full-Coverage Path-Planning Algorithm for a Glass-Curtain-Wall-Cleaning Robot Driven by Ropes

A Full-Coverage Path-Planning Algorithm for a Glass-Curtain-Wall-Cleaning Robot Driven by Ropes

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on HMM model

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on hidden Markov model

Contact Info

Product

Resources

About