# Influence of Loess-Mudstone Strata Structure on Slope Seismic Stability of Loess Plateau in China
## 4 Discussion  
From the above, it can be seen that the strata structure had a significant impact on the seismic stability of the loess slopes. In this paper, four strata factors, namely, slope height, slope angle, loess cover thickness, and mudstone dip angle, were considered. The impact of these factors on the seismic stability of the loess-mudstone slopes was not entirely the same; if each factor was fully considered in the seismic design of the loess-mudstone slopes, the workload would have been large. Therefore, a sensitivity analysis of these striatal factors that affected the seismic stability of loess-mudstone slopes could classify the degree of influence of each factor and determine the key factor. There are many methods of conducting a sensitivity analysis, and [PERSON] [49] and [PERSON] et al. [50] summarized the sensitivity analysis methods of influencing factors of slope stability. The sensitivity of strata factors on the seismic stability of a loess-mudstone slope based on the orthogonal test was studied in this paper. The orthogonal test is a scientific method of studying the sensitivity of multiple factors. This method uses an orthogonal table as a tool to arrange a scheme and analyze its result, so as to find the optimal-level combination of various factors; it can not only reflect the influence of many factors, but also reduce the workload as much as possible on the premise of ensuring the calculation results. The distribution range of each strata factor is shown in Table 3 and varied at equal intervals within their respective intervals. It was a four-factor and four-level test. The orthogonal test was selected as L\({}_{16}\) (4\({}^{\circ}\)). The pseudostatic method was used to carry out the orthogonal test with safety factors. Figure 11: Error of safety factors between pure loess slope and loess-mudstone slope: (**a**) relationship between slope height and error of safety factor; (**b**) relationship between slope angle and error of safety factor; (**c**) relationship between loess cover thickness and error of safety factor; (**d**) relationship between mudstone dip angle and error of safety factor. For the above orthogonal test results, the range analysis method was used to compare the sensitivity of different influencing factors. The analysis results are shown in Table 4. \(K_{i}\) represents the sum of the response values corresponding to the level combination of all factors when a factor was at the \(i_{th}\) level; \(R_{j}\) represents the range of factor \(j\), and its value reflects the influence of factor \(j\) on the research object. The expression was:  
\[\mathrm{R}_{j}=\mathrm{max}\{\overline{\mathrm{K}_{1}},\overline{\mathrm{K}_{2 }},\overline{\mathrm{K}_{3}},\overline{\mathrm{K}_{4}}\}\ -\ \mathrm{min}\{\overline{\mathrm{K}_{1}},\overline{\mathrm{K}_{2}}, \overline{\mathrm{K}_{3}},\overline{\mathrm{K}_{4}}\} \tag{4}\]  
where \(\overline{\mathrm{K}_{i}}\) is the average value corresponding to \(\mathrm{K}_{i}\). It can be seen from Table 4 that the sensitivity influence of the above four factors on slope stability, from high to low, was the slope angle, loess cover thickness, slope height, and mudstone dip angle. Figure 12 shows the factor average in each level. It can be seen that, in addition to the mudstone dip angle, of which the best level was the fourth level, the other three factors were the best at the first level.