Grey correlation analysis between strength of slag cement and particle fractions of slag powder

Zhang, Yongjuan; Zhang, Xiong

doi:10.1016/j.cemconcomp.2007.02.004

Cited by 59 publications

(22 citation statements)

References 13 publications

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“…To evaluate the degrees of influence of the nine factors (subarray) on soil evaporation (main array) in different freeze–thaw stages, GCA was applied, and the grey correlation degree was compared among the factors. The higher the absolute value of the grey correlation degree, the greater the relevance of that factor to soil evaporation (Fu et al, 2001; Zhang & Zhang, 2007; Zheng et al, 2019). The top three ranked factors in grey correlation degree were considered the major factors influencing soil evaporation in this research.…”

Section: Resultsmentioning

confidence: 99%

“…Because the grey correlation polarity | Y o ( k ) − Y i ( k )| cannot be separated in Equation ), the formulas below are used to judge the grey correlation polarity among all factors (Zhang & Zhang, 2007).

Q_{0} = \sum_{k = 1}^{m} {kY}_{0} ((), k) - \frac{1}{m} \sum_{k = 1}^{m} k \sum_{k = 1}^{m} Y_{0} ((), k),

Q_{i} = \sum_{k = 1}^{m} {kY}_{i} ((), k) - \frac{1}{m} \sum_{k = 1}^{m} k \sum_{k = 1}^{m} Y_{i} ((), k),

Q_{k} = \sum_{k = 1}^{m} k^{2} - \frac{1}{m} {({false\sum}_{k = 1}^{m} k)}^{2} .

…”

Section: Methodsmentioning

confidence: 99%

“…When sign (

\frac{Q_{i}}{Q_{k}}

)/sign (

\frac{Q_{0}}{Q_{k}}

) = 1, Y 0 and Y i have a positive correlation. When sign (

\frac{Q_{i}}{Q_{k}}

)/sign (

\frac{Q_{0}}{Q_{k}}

) = −1, Y 0 and Y i have a negative correlation, which indicates that the sub‐array will weaken the main array (Zhang & Zhang, 2007).…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Effects of sand‐mulch thickness on soil evaporation during the freeze–thaw period

Chen

Xue

Zheng

et al. 2020

Hydrological Processes

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Control of evaporation from seasonally frozen soil is an important method for alleviating water shortages in arid and semi‐arid areas. To investigate the inhibition of soil evaporation by sand and the major factors that influence soil evaporation, a series of field experiments with five sand‐mulch thicknesses (0 cm, bare soil [BS], 1 cm [T1], 2 cm [T2], 3 cm [T3] and 4 cm [T4], with an average diameter of 1 mm) were conducted during the freeze–thaw period in Northern China. Soil evaporation characteristics in the three freeze–thaw stages were revealed and the major factors influencing soil evaporation were analysed using grey correlation analysis. The results showed that the cumulative soil evaporation decreased with increasing sand‐mulch thickness during the freeze–thaw period, and only small differences in soil evaporation were observed between the T3 and T4 treatments. The reduction in soil evaporation under different sand‐mulch thicknesses was 19.2–62.6% in the unstable freezing stage (P1), 2.0–28.3% in the stable freezing stage (P2) and 4.8–20.4% in the thawing stage (P3). In P1, solar radiation was a major factor influencing soil evaporation in all treatments and vapour pressure was a major factor in the sand‐mulch treatments, and the influence of relative humidity on soil evaporation decreased in the T4 treatment. During the coldest P2, solar radiation was lowest so that relative humidity and wind speed became the more dominant influence factors on soil evaporation in all treatments, and surface soil water content was a major factor in the sand‐mulch treatments. In P3, average air temperature and solar radiation were major factor influencing soil evaporation in all treatments and vapour pressure was a major factor in the BS and T1 treatments, whereas water surface evaporation was the major factor in the T2, T3 and T4 treatments. The results suggest that the addition of sand mulch in agricultural fields may be a beneficial practice to reduce water stress in arid and semi‐arid areas.

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Section: Resultsmentioning

confidence: 99%

Q_{0} = \sum_{k = 1}^{m} {kY}_{0} ((), k) - \frac{1}{m} \sum_{k = 1}^{m} k \sum_{k = 1}^{m} Y_{0} ((), k),

Q_{i} = \sum_{k = 1}^{m} {kY}_{i} ((), k) - \frac{1}{m} \sum_{k = 1}^{m} k \sum_{k = 1}^{m} Y_{i} ((), k),

Q_{k} = \sum_{k = 1}^{m} k^{2} - \frac{1}{m} {({false\sum}_{k = 1}^{m} k)}^{2} .

…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Effects of sand‐mulch thickness on soil evaporation during the freeze–thaw period

Chen

Xue

Zheng

et al. 2020

Hydrological Processes

View full text Add to dashboard Cite

show abstract

“…Similar to the correlation efficient, a positive value means that the subfactors will enhance the major factor. Otherwise, it will weaken the major factor (Zhang and Zhang 2007). Detailed information about GCA can be referenced to (Jia et al 2010;Qin et al 2014).…”

Section: Methods and Available Data Brief Introduction To Methodsmentioning

confidence: 99%

A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China

Qin

Liu

et al. 2015

Environ Sci Pollut Res

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Given the large expenditures by households on goods and services that contribute a large proportion of global CO 2 emissions, increasing attention has been paid to household CO 2 emissions (HCEs). However, compared with industrial CO 2 emissions, efforts devoted to mitigating HCEs are relatively small. A good understanding of the effects of some driving factors (i.e., urbanization rate, per capita GDP, per capita income/disposable income, Engel coefficient, new energy ratio, carbon intensity, and household size) is urgently needed prior to considering policies for reducing HCEs. Given this, in the study, the direct and indirect per capita HCEs were quantified in rural and urban areas of China over the period 2000-2012. Correlation analysis and gray correlation analysis were initially used to identify the prime drivers of per capita HCEs. Our results showed that per capita income/disposable income, per capita GDP, urbanization rate, and household size were the most significantly correlated with per capita HCEs in rural areas. Moreover, the conjoint effects of the potential driving factors on per capita HCEs were determined by performing principal component regression analysis for all cases. Based on the combined analysis strategies, alternative polices were also examined for controlling and mitigating HCEs growth in China.

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“…The correlation value had a power function relation with pore size. The larger the pore size was, the lower the strength of the material was Zhang and Zhang (2007), Li et al (2018b). In addition, the influence coefficient was zero when the pore size was zero.…”

Section: The Effect Of Pore Size Distribution On the Damage Factormentioning

confidence: 99%

Experimental-Computational Approach to Investigate Nanoindentation of Magnesium Potassium Phosphate Hexahydrate (MKP) With X-CT Technique and Finite Element Analysis

Zhang

Wang

2020

Front. Mater.

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The magnesium phosphate cement (MPC) is a carbon-free cementitious material, widely used in solidification of nuclear waste, heavy metals, and repair and reinforcement. The magnesium potassium phosphate hexahydrate (MgKPO 4 ·6H 2 O, MKP) is the main hydration product of MPC, seriously affecting the mechanical properties of the MPC. Therefore, this paper presented an experimental-computational approach to investigate the mechanical properties of the MKP through nanoindentation with X-ray Computed Tomography (X-CT) technique and finite element analysis. Firstly, the micro-mechanical properties and structural distribution characteristics of the MKP were tested based on the nanoindentation and the X-CT technique, respectively. Then, the 3D structure grid model of the MKP was obtained based on X-CT data, imported into the ABAQUS software for the finite element simulation. Besides, considering the effect of porosity and pore distribution on the damage, the modified MKP constitutive relation was proposed and input into the X-CT nanoindentation model and the RAP nanoindentation model, respectively. It was found that those two models can effectively describe the mechanical and deformation characteristics of the MKP, which verified the correctness of the modified constitutive relationship of MKP. Finally, the influence of pore distribution on the nanoindentation results was predicted based on the RAP nanoindentation model.

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Grey correlation analysis between strength of slag cement and particle fractions of slag powder

Cited by 59 publications

References 13 publications

Effects of sand‐mulch thickness on soil evaporation during the freeze–thaw period

Effects of sand‐mulch thickness on soil evaporation during the freeze–thaw period

A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China

Experimental-Computational Approach to Investigate Nanoindentation of Magnesium Potassium Phosphate Hexahydrate (MKP) With X-CT Technique and Finite Element Analysis

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