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Ergonomics Standards in Ancient China
Published in Waldemar Karwowski, Anna Szopa, Marcelo M. Soares, Handbook of Standards and Guidelines in Human Factors and Ergonomics, 2021
The Song dynasty military was composed of six troop levels. The first level—the imperial army (Jin Jun)—was the standard army for fighting. The role of the imperial army was replaced by the central army (Tun Zhu Da Bing) and the new army (Xin Jun) in the Southern Song (Toktoghan, 1345; Zhou, Yang, and Wang, 1998; Wang & Yang, 2001). Height was one of the major criteria for the soldier selection in the Song imperial army, as recorded in the military section (Bin Zhi) of the official imperial history of the Song dynasty (Toktoghan, 1345). The unit of measurement was the ancient Chinese length unit (Chi); this gets larger as the years passed by. One Chi was officially recorded to equal about 29.6 cm in the Sui dynasty (581–618) and Tang dynasty (618–907) (Wei et al., 636; Qiu, 1994; Zheng, Tang, et al., 2000). But the excavated Song rulers were about 31.2 cm (Zheng, Tang, et al., 2000). The ancient Chinese inch (Cun) was one-tenth of one ancient Chinese meter.
The Granular Column Collapse
Published in James Fern, Alexander Rohe, Kenichi Soga, Eduardo Alonso, The Material Point Method for Geotechnical Engineering, 2019
James Fern, Alexander Rohe, Kenichi Soga, Eduardo Alonso
Tatsuoka [291], followed by Jefferies and Been [149,150], pointed out that the conversion of state indices to dilatancy angles is fabric dependent. This means that the conversion factor used in stress-dilatancy theories can change depending on the orientation of the soil grains (see Chapter 7). Fern [101] showed that this dilatancy coefficient could change substantially for sands with elongated grains but remained somewhat constant for spherical-grained sands. Fig. 9.14 shows the final deposition profile of a column with an initial aspect ratio of a=2.0 $ a=2.0 $ for different dilatancy coefficients for dense sand; the effect of the dilatancy coefficient is density dependent and is better illustrated for the dense sand case. The results show that an increase in the dilatancy coefficient, which increases the peak strength and the stiffness, steepens the failure surface, changes the final height of the static cone, and shortens a little the run-out distance. The avalanching process at the end of the simulations is more significant for χ=4.6 $ \chi = 4.6 $ than for χ=1.6 $ \chi = 1.6 $ .
Study on Methodology of Repair by Disassembly: The Case of Buyi Ethnic Construction Techniques of a Timber Granary in Guizhou Province, China
Published in International Journal of Architectural Heritage, 2023
Han Xu, Yongjie Pan, Tong Zhang, Yuxi Yang
The tradition of using human scaled measurements to determine the size of dwellings or construction details is common in wooden architecture in Asian countries. The carpenters’ body size and human scale were used as the standards for measurements and construction of the timber granary (Oranratmanee 2018). Occasionally, some construction behavior habits of Buyi carpenters gesture with their human body parts to measure without tools. The frequently used human-scaled measurements in this research are based on the traditional terms of construction tradition in China (Funo 2011), such as xun, zhang, chi, wo, and cun, which correspond to the wingspan, hand-to-elbow length, the bottom of palm-to-middle finger length, clenched fist width, and finger width (Figure 21). The form and function of timber components and the properties of the wooden materials determine the uses of these measurements. Thus, the relationship among these human-scaled sizes forms a modulus system in this timber granary. For example, the diameter of the column is approximately 2 chi and the width of the timber boards is 1 wo. The width of mortises in the column is 2–3 cun and the length is 4–5 times. If the beam has to hang over the structure, the length of the cantilevered part is limited to 1–2 zhang. Altogether, the distance between the two timber frames is about 1.5 xun. Although Buyi carpenters also use their rulers to accurately measure and cut timber components, they depend on their vernacular experience from long-term construction activities to evaluate the work in advance.
The time-dependent multi-depot fleet size and mix green vehicle routing problem: improved adaptive large neighbourhood search
Published in Optimization, 2022
Mahdi Alinaghian, Maryam Jamshidian, Erfan Babaee Tirkolaee
In order to have a confident comparison of the algorithms in large-scale problems, it is necessary to conduct a comparative assessment using the statistical test between the proposed IALNS algorithm and the other algorithms. Due to this, the Friedman rank test is utilized under a 95% confidence level. For more information, please see Costa and Fernandes [32]. SPSS software is used to implement the test and the obtained results are given by Table 7. In this table, N, df, Asymp. Sig. and Chi-Square stand for the number of samples, degree of freedom, significant level and value of Chi-Square statistic, respectively. The algorithm with the lowest mean rank is known as the best algorithm. Hence, IALNS is selected as the best algorithm to solve the problem.
Attitudes, personality traits and private parking space owners’ willingness to engage in shared parking schemes: a hybrid prospect theoretic model
Published in Transportmetrica A: Transport Science, 2022
Qianqian Yan, Tao Feng, Harry Timmermans
Table 5 shows the goodness of fit of the model after factor analysis. Chi-Square is 630.7 and df (degree of freedom) is 296. The relative Chi-Square (χ2/df) is 2.131, below the empirical value of three indicating good fit (Hair et al. 2010). RMSEA, short for root mean square error of approximation, assesses the extent to which a model fits reasonably well the population. The value 0.043 is below the 0.08 required for good fit (Byrne 1998). SRMR, short for standardised root mean square residual, is an index for measuring the average discrepancy between the correlations observed in the input matrix and the correlations predicted by the model. A rule of thumb, suggested by Hair et al. (2010), is that the SRMR should be lower than 0.10. The value 0.031 satisfied the criteria. CFI, short for comparative fit index, benefits from its property that it is relatively insensitive to model complexity and sample size and is therefore one of the most widely used indices. A value of CFI above 0.90 is commonly associated with a well-fitting model (Hu and Bentler 1999). Another similar and widely used index is TLI, which is short for Tucker-Lewis index. Again, a value above 0.90 is commonly suggested as an indication of a good model fit (Forza and Filippini 1998). Table 5 shows that all commonly used cut-off criteria are met, supporting the scale construction processes.