esa-sceva/satcom-chunk-collection huggingface dataset:
# Safety Analysis of Buried Corrosion-Defect Gas Pipeline in Ceramic Soil Layer Under Blasting Action
## 4 Numerical Simulation of Corroded Defective Gas Pipelines
### Analysis of the Effect of Blasting on the Stress of Corroded Gas Pipelines of Different Thicknesses  
With the acceleration of urbanization, blasting operations are becoming more and more frequent in urban construction. However, the vibration effect of blasting may pose a potential safety threat to nearby buried pipelines, especially corroded gas pipelines. As an important index to measure the structural strength of the pipeline, the thickness of the pipeline has a significant influence on the stress change of the pipeline under blasting vibration. The stress changes of corroded gas pipelines with different thicknesses caused by blasting are shown in Figure 11 below.  
Under the same blasting parameters, the stress response experiments were carried out on corroded gas pipelines with different thicknesses (2 mm to 6 mm). The experimental results show that with the increase of pipe thickness, the maximum axial stress and the maximum circumferential stress both show a significant decreasing trend. Specifically, when the pipe thickness is increased from 2 mm to 6 mm, the maximum axial stress is reduced from 320 MPa to 140 MPa, a reduction of about 56.3%, and the maximum circumferential stress is reduced from 290 MPa to 125 MPa, a reduction of about 56.9%. This change law shows that thicker pipes can better absorb and disperse the energy generated by blasting vibration, reduce stress concentration and deformation, and thus improve their structural strength and stiffness.  
Further analysis shows that with the increase of pipe thickness, the rate of stress reduction gradually slows down. This may be because with the increase of thickness, the  
Figure 10: Stress changes of corroded gas pipelines under different elastic moduli caused by blasting.  
deformation resistance of the pipe is gradually enhanced, so that the effect of additional thickness on stress reduction is gradually weakened. In addition, thicker pipes also have better fatigue resistance and can more effectively resist fatigue damage caused by blasting vibration, thus extending the service life of the pipes.
## Appendix A Proof of \(V(\mathbf{x})\) Being Positive Definite  
It follows directly from the construction of \(V(\mathbf{x})\) that \(V(\mathbf{0})=\mathbf{0}\). Moreover, by using Lemma 1, it is easy to show that  
\[V_{2}(\mathbf{x}) =\sum_{i=1}^{n}\int_{x_{2i}^{*}(x_{1i})}^{x_{2i}}\left(s^{\frac{ 1}{1+\kappa_{1}}}-x_{2i}^{*\frac{1}{1+\kappa_{1}}}(x_{1i})\right)^{1-\kappa_{ 1}}ds\] \[\geq\sum_{i=1}^{n}c_{i}\left(x_{2i}-x_{2i}^{*}(x_{1i})\right)^{ \frac{2}{1+\kappa_{1}}}\]  
Figure 3: Convergence times for different initial states.  
where  
\[c_{i}=2^{\frac{\kappa_{1}(1-\kappa_{1})}{1+\kappa_{1}}}\left(\frac{1+\kappa_{1}}{ 2}\right).\]  
This shows that  
\[V(\mathbf{x})\geq V_{1}(\mathbf{x}_{1})+\sum_{i=1}^{n}c_{i}\left(x_{2i}-x_{2i}^ {*}(x_{1i})\right)^{\frac{2}{1+\kappa_{1}}}. \tag{10}\]  
As \(x_{2i}^{*}(0)=0\) and \(V_{1}(\mathbf{x}_{1})\) is positive definite and proper, the remaining proof can be divided into two cases.  
_Case 1:_ If \(\mathbf{x}=(\mathbf{x}_{1}^{T},\mathbf{x}_{2}^{T})\
eq\mathbf{0}\) with \(\mathbf{x}_{1}\
eq\mathbf{0}\), we have  
\[V(\mathbf{x}) \geq V_{1}(\mathbf{x}_{1})+\sum_{i=1}^{n}c_{i}\left(x_{2i}-x_{2i}^ {*}(x_{1i})\right)^{\frac{2}{1+\kappa_{1}}}\] \[\geq V_{1}(\mathbf{x}_{1})\] \[>0.\]  
_Case 2:_ In the case when \(\mathbf{x}=(\mathbf{0}^{T},\mathbf{x}_{2}^{T})\
eq\mathbf{0}\), it follows from (10) that  
\[V(\mathbf{x}) \geq V_{1}(\mathbf{x}_{1})+\sum_{i=1}^{n}c_{i}\left(x_{2i}-x_{2i}^ {*}(x_{1i})\right)^{\frac{2}{1+\kappa_{1}}}\] \[\geq c_{i}x_{2i}^{\frac{2}{1+\kappa_{1}}}\] \[>0.\]  
Hence, one can conclude that \(V(\mathbf{x})\) is positive definite.
# MCPSHA: A New Tool for Probabilistic Seismic Hazard Analysis Based on Monte Carlo Simulation
## 3 Geological Setting and Seismic Activity Parameters  
Baoji City, situated in Shaanxi Province, is encompassed by the Loess Plateau, Qinling Mountain, and Weihe Basin (Figure 5). The Weihe River traverses the region from west to east. The Baoji area is influenced by three tectonic units, namely the QinLing fold belt, the Fen-Wei fault-depression zone, and the southern margin of the Ordos block [42]. Extensive seismic events have been recorded in this locale, with data sourced from the Catalogue of Shaanxi Earthquakes, 1189 BC-2001 AD (2015) ([[http://news.ceic.ac.cn/index.html?time=15-24648589](http://news.ceic.ac.cn/index.html?time=15-24648589)]([http://news.ceic.ac.cn/index.html?time=15-24648589](http://news.ceic.ac.cn/index.html?time=15-24648589)), accessed on 13 May 2019). Figure 5 shows the historical earthquake distribution around the Baoji area, spanning from 780 BC to 2015 AD. Notably, since 1973, the region has experienced numerous moderate and small earthquakes characterized by periodicity, migration, and recurrence.  
A total of 7 seismic belts may affect the Baoji area. In each background seismicity zone, tectonic feature zones are recognized and classified (Figure 6). The seismic activity parameters and the upper limit of magnitude for each seismic belt are measured based on the results of the \"seismic microzonation of 4 cities in the Guan-Zhong\" project (Figure 6). The background seismicity zone and tectonic feature zone parameters are obtained based on the results of the 5 th National Seismic Zoning Map of China [43]. Seismic motion attenuation relations are based on the results of the \"seismic microzonation of four cities in the Guan-Zhong\" project (Figure 7) [44; 45].  
Figure 5: Map depicting the topography, tectonic settings, and historical earthquakes (within 150 km around Baoji city from 870 AD to 2015) distribution in the Baoji area. HYF: the Haiyuan fault; NWQLF: the North Margin of West Qinling fault; LTDCF: the Lintan-Dangchang fault; PWQCF: the Pingwu-Qingchuan fault; MJF: the Minjiang fault; BCYXF: the Beichuan-Yingxiu fault; SYF: the Shanyang fault; SXDFF: the Shangxian-Danfeng fault.
## 6 Evaluation Process for Spare Parts Support Capacity  
Firstly, an evaluation indicator system for the spare parts support capacity of civil aircrafts was established from four aspects: the task capability indicator, emergency support capacity indicator, cost-effectiveness indicator, and service capacity indicator. Second, the indicator weights were calculated. Specifically, the evaluation data from experts were collected, arranged, and aggregated first, and the weight of each indicator was calculated via T2 HPFE. Next, an evaluation model was established, which mainly aimed to calculate the weighted distance and closeness, and the alternative solutions were sorted accordingly. Finally, the evaluation results were analyzed. The specific evaluation flowchart is exhibited in Figure 2.  
Figure 2: Evaluation process of spare parts support capacity.
## 3 Results and Discussion
### Synthetic Data
#### 3.2.1 Mean Absolute Error  
By Equation (10), we calculate mean absolute error (MAE), which is the measure of absolute error between the original and the generated synthetic data.  
\[MAE=\frac{1}{n}\sum_{i=1}^{n}|Ori_{i}-Syn_{i}|. \tag{10}\]
# Performance of Stone Masking Asphalt Mixtures Fabricated by Different Compaction Methods
## 3 Results
### Road Performance Comparison  
Table 13 shows the road performances of the SMA-13 mixtures designed by different methods. Here, S (M), S (S), and S (V) represent the road performances of the asphalt mixtures designed by the Marshall method, the SGC method, and the VVTM, respectively.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Road Performance**} & \multirow{2}{*}{**Indices**} & \multicolumn{3}{c}{**Design Methods**} & \multirow{2}{*}{**S(V)/S(M)**} & \multirow{2}{*}{**S(V)/S(S)**} \\ \cline{3-3} \cline{5-7}  & & **Marshall** & & & & \\ \hline Anti-rut ability & DS (times/mm) & 5756 & 6914 & 7450 & 1.30 & 1.08 \\ Anti-crack ability & \(R_{\text{b}}\) (MPa) & 11.8 & 12.1 & 14.2 & 1.20 & 1.17 \\ \(\varepsilon_{i}\) (\(\mu\)\(\xi\)) & 3215 & 3287 & 3080 & 0.96 & 0.94 \\ Water stability & \(\text{MS}_{\text{0}}\) (\%) & 90 & 91 & 94 & 1.04 & 1.03 \\  & TSR (\%) & 85 & 87 & 88 & 1.04 & 1.01 \\ \hline \hline \end{tabular}
\end{table}
Table 13: Comparison of Road performances of SMA-13 mixtures designed by different methods.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Mechanical Indices**} & \multirow{2}{*}{**Test Temperature**} & \multicolumn{3}{c}{**Design Methods**} & \multirow{2}{*}{**R(V)/R(M)**} & \multirow{2}{*}{**R(V)/R(S)**} \\ \cline{3-3} \cline{5-7}  & & **Marshall** & & & & \\ \hline \(R_{\text{c}}\) & 25 & 6.5 & 6.6 & 7.9 & 1.22 & 1.20 \\ \(\tau_{\text{d}}\) & 60 & 1.19 & 1.48 & 1.71 & 1.44 & 1.16 \\ \(R_{\text{i}}\) & \(-\)10 & 3.37 & 4.18 & 4.37 & 1.30 & 1.05 \\ \hline \hline \end{tabular}
\end{table}
Table 12: Comparison of mechanical properties of the SMA-13 mixtures designed by different methods.  
In the VVTM-designed SMA-13 mixture, the high-temperature rutting resistance, low-temperature crack resistance and water stability were respectively 30%, 20%, and 4% higher than in the Marshall-designed mixture, and respectively 8%, 17% and 3% higher than in the SGC-designed mixture. This result is attributable to the different compaction mechanisms of the three methods. By virtue of its vibration-compaction mechanism, the VVTM better arranges the coarse aggregates in the mixture than the other methods, thereby forming a stronger framework. Under the squeezing force, the skeleton is more easily filled with horseshoe fat, and the mixture can more easily resist deformation; accordingly, the VVTM-designed mixture has strong high-temperature rutting resistance and low-temperature crack resistance. The reduced amount of asphalt also reduces the occurrence of high-temperature rutting. Meanwhile, because the VVTM-designed SMA-13 mixture is denser with a lower air void volume (VV) than the other mixtures, water cannot easily enter the road interior, so the SMA-13 mixture can be formed into pavements with improved water stability.
# TSINet: A Semantic and Instance Segmentation Network for 3D Tomato Plant Point Clouds
## 3 Experimental Results and Analysis
### Model Evaluating Indicator  
In terms of the task of semantic segmentation for point clouds of tomato plants, the model performance is evaluated using four widely used assessment indicators, including Precision, Recall, F1-score, and Intersection over Union (IoU). These metrics are defined as follows:  
\[Precision=\frac{TP}{TP+FP} \tag{9}\]  
\[Recall=\frac{TP}{TP+FN} \tag{10}\]  
\[F1=2\cdot\frac{Precision\cdot Recall}{Precision+Recall} \tag{11}\]  
\[IoU=\frac{TP}{TP+FP+FN} \tag{12}\]  
where _FP_ stands for the number of false positive points, _FN_ for the number of false negative points, and _TP_ for the number of true positive points for a particular semantic class.  
Four assessment metrics are used for the instance segmentation task, both at the instance and point levels: mean precision (mPrec), mean recall (mRec), mean coverage (mCov), and mean weighted coverage (mWCov). Descriptions for these metrics are given below:  
\[mPrec=\frac{1}{N}\sum_{i=1}^{N}\frac{|TP_{i}|}{|P_{i}|} \tag{13}\]  
\[mRec=\frac{1}{N}\sum_{i=1}^{N}\frac{|TP_{i}|}{|G_{i}|} \tag{14}\]  
\[mCov=\frac{1}{I}\sum_{m=1}^{I}max_{n}\ IoU(G_{m},P_{n}) \tag{15}\]  
\[mWCov=\sum_{n=1}^{I}w_{m}max_{n}\ IoU(G_{m},P_{n}) \tag{16}\]  
where \(N\) denotes the number of semantic classes involved in the calculation of _mPrec_ and _mRec_. In this study, all points are categorized into two classes: stem and leaf, so \(N\) is set to 2. The term \(|TP_{i}|\) is used to describe how many anticipated instances in semantic class \(i\) have an _IoU_ greater than 0.5 with any ground truth instance. \(|P_{i}|\) represents the overall count of predicted instances in class \(i\), and \(|G_{i}|\) indicates the total count of ground truth instances in class \(i\). \(G_{m}\) denotes the point set of the m-th ground truth instance for a given semantic class, and \(P_{n}\) denotes the point set of the n-th predicted instance in the same class.
# Reliability-Aware Cooperative Node Sleeping and Clustering in Duty-Cycled Sensors Networks
## 6 Performance Evaluation
### The Impact of \(k\) and \(\mu\) on Reliability and ETE Delay in RCR  
In the simulation whose results are presented in this section, \(f\) was fixed to 0.3 and \(k\) varied from one to 10. Figure 7(a) shows the impact of \(f\) and \(\mu\) on reliability under the variations of \(\mu\) from 0.1 to 0.9 with a step of 0.2. The simulation results are compatible with the theoretical results shown in Figure 7(b). Moreover, the simulation results presented in Figure 7(b) show that the larger \(\mu\) is, the longer the ETE delay is. Once \(\mu\) is fixed, with the increase of \(k\), the ETE delay converges to a certain value.
# Lightweight, Secure, Similar-Document Retrieval over Encrypted Data
## 4 Scheme Overview
### Initialization Stage
#### 5.1.1 Secure Inverted Index.
Initially, [PERSON]'s algorithm was used to hash the K-gram set in a secure and efficient manner. Then, the Winnowing algorithm selects the most important fingerprint among hash codes. For further security, these hash codes are protected using the parameters \(b\) and \(M\) of Equations (1) and (3) as a secret key \(K_{1}=(b,M)\), whereas the Paillier cryptosystem is adopted to encrypt the posting lists. The inverted index structure is often used to achieve fast and efficient data retrieval, and facilitates quick access to files in file management systems [20; 21]. This paper implemented a Winnowing algorithm to reduce the fingerprint terms of the document collection, facilitating their management and maintenance. Practically, the Winnowing algorithm allows a query document search using only a portion of the fingerprint set, depending on the terms of the query document. ```
1:the document collection \(D=\{d_{1},d_{2},\ldots,d_{m}\}\), Paillier encryption and decryption functions \(Enc_{kpub}\) and \(Dec_{kpriv}\). Output:
2:Start;
3:\(F=\varnothing\)
4:For each \(d_{i}\in D\)
5: Use equations 1 and 3 to generate the fingerprint
6:\(df_{i}=\{f_{i1},f_{i2},\ldots,f_{ia}\}\);
7:\(F=\cup df_{i}\);
8:End for
9:For each \(f_{i}\in F\)
10:For \(i=1\ldots m\)
11: If \(f_{i}\in df_{i}\)
11: Set \(P_{j}(ID(d_{i}))=Enc_{kpub}(1)\);
12: Else
13: Set \(P_{j}(ID(d_{i}))=Enc_{kpub}(0)\);
14: End if
15:End for
16: Store \((f_{j},P_{j})\) in \(I\);
17:End for
18: Add some fake records in \(I\) to hide the number of fingerprint items;
19: End;
```  
**Algorithm 1** Shows the building of the secure searchable inverted index.
## 5 Conclusions  
To construct a self-developed micro-groove cutter dry-cut AISI 304 stainless steel surface roughness prediction model and optimize the cutting parameters, a surface roughness prediction method based on GA-GBRT is proposed. The cutting speed \(V\), the feed amount \(f\), and the cutting depth \(ap\) are taken as model variables to predict the surface roughness. The optimized GBRT model is compared against the optimized ANN (LM, BR, and SCG) and SVR on the test set. The following conclusions are drawn:  
1. In comparison to the GBRT model with default parameters, the combination of GA and GBRT improved the generalization performance on training datasets and test datasets. The experimental results demonstrate that the minimum evaluation index of the GA-GBRT model is RMSE of 0.087. The other three indicators evidence the superior predictive performance of the model as well. It is thus concluded that GA-GBRT is a reasonable and promising surface roughness prediction method. The model is also capable of being applied to the surface of milling, drilling and grinding.
2. Based on the established GA-GBRT model, the Pareto optimal solution with the highest cutting efficiency and the best machining surface quality was obtained and analyzed. The optimal solution set that reaches a balance between the two was obtained (the value of area B in Table 7). The optimum process parameters for the multi-target conditions were determined for dry cutting of AISI 304 stainless steel for microgroove cutters. As indicated by the results of multi-objective optimization, the cutting efficiency can be enhanced by increasing the cutting speed and depth in a small range of surface quality variations.
3. The 3D surface map demonstrates that the feed rate has a significant effect on the surface roughness, followed by the depth of cut. Besides, the cutting speed exerted the most insignificant effect on the roughness. Through analysis, it was discovered that, compared with the traditional tool, the self-developed micro-groove tool could achieve a superior surface finish with any combination of cutting speed and cut of depth and in the low to moderate range of the feed rate machining process.  
Conceptualization, T.Z.; formal analysis, L.H.; funding acquisition, L.H.; investigation, L.H. and J.W.; methodology, T.Z.; software, J.W.; visualization, F.D.; writing--original draft, F.D. and Z.Z., writing--review and editing, Z.Z.  
This research was funded by National Natural Science Foundation of China, grant number 51765009 and 51665007, and Science and Technology Planning Project of Guizhou, grant number 20175788 and 20172596.  
The authors acknowledge the technical support provided by the Engineering Training Center of Guizhou University.  
The authors declare no conflicts of interest.
# Speed-Gradient Adaptive Control for Parametrically Uncertain UAVs in Formation
## 2 Point-Mass Model of UAV Dynamics
### Feedback Linearization  
Models (1)-(3) use a common approach to the design of the control algorithm, namely, the feedback linearization method, cf. [49]. This results in an equivalent linear system of the form  
\[\begin{split}\ddot{x}&=v_{1},\\ \ddot{y}&=v_{2},\\ \ddot{h}&=v_{3},\end{split} \tag{4}\]  
where \(v_{1}\), \(v_{2}\), \(v_{3}\) are virtual controls which can be uniquely converted into real ones. This approach was used in [39; 40; 42; 43], and, appears indirectly in [26]. A rigorous justification for the applicability of this approach follows from the theory of _flat systems_[50; 51]. It can be shown that outputs \(x(t)\), \(y(t)\), \(h(t)\) of systems (1)-(3) are flat (in the sense of [50; 51]) and that variables \(V_{g}\), \(\psi\), \(\gamma\) can be expressed in terms of \(x\), \(y\), \(h\) and their derivatives, as well as in terms of control signals. Let the real control signals in (1) be in the form \(u=[F_{\text{thrust}},F_{\text{lift}},\varphi]^{\tau}\); here, \(F_{\text{lift}}\) is used instead of \(C_{L}\). Such a replacement is admissible because it follows from the seventh equation in (1) that the required value of \(C_{L}\) can be uniquely obtained from \(F_{\text{lift}}\). Then, the inverse transformations of the control by dynamic feedback linearization can be obtained in the following form:  
Option 1.  
\[\begin{split}& F_{\text{thrust}}=F_{\text{drag}}+m\cos\gamma(v_{1} \cos\psi+v_{2}\sin\psi)+m\sin\gamma(g+v_{3}),\\ & F_{\text{lift}}=m\sqrt{\big{(}(g+v_{3})\cos\gamma-\sin\gamma( v_{1}\cos\psi-v_{2}\sin\psi)\big{)}^{2}+(v_{2}\cos\psi-v_{1}\sin\psi\big{)}^{2}},\\ &\varphi=\arctan\bigg{(}\frac{v_{2}\,\cos\psi-v_{1}\sin\psi}{(g +v_{3})\cos\gamma-(v_{1}\cos\psi+v_{2}\sin\psi)\sin\gamma}\bigg{)}.\end{split} \tag{5}\]  
Option 2.  
\[\begin{split}& F_{\text{thrust}}=F_{\text{drag}}+m\,\frac{\dot{x}v_{1}+ \dot{y}v_{2}+h(g+v_{3})}{V_{g}}\\ & F_{\text{lift}}=m\,\frac{(g+v_{3})\cos\gamma-(v_{1}\cos\psi+v_ {2}\sin\psi)\sin\gamma}{\cos\varphi},\\ &\varphi=\arctan\bigg{(}\frac{v_{2}\cos\psi-v_{1}\sin\psi}{(g+v _{3})\cos\gamma-(v_{1}\cos\psi+v_{2}\sin\psi)\sin\gamma}\bigg{)}\end{split} \tag{6}\]  
Option 3.  
\[\begin{split}& F_{\text{thrust}}=F_{\text{drag}}+m\,\cos\gamma(v_{1} \cos\psi+v_{2}\,\sin\psi)+m\,\sin\gamma\,(g+v_{3}),\\ & F_{\text{lift}}=m\,\frac{(g+v_{3})\cos\gamma-(v_{1}\cos\psi+v_ {2}\sin\psi))\sin\gamma}{\cos\varphi},\\ &\varphi=\arctan\bigg{(}\frac{v_{2}\cos\psi-v_{1}\sin\psi}{(g+v _{3})\cos\gamma-(v_{1}\cos\psi+v_{2}\sin\psi)\,\sin\gamma}\bigg{)}.\end{split} \tag{7}\]  
Note that the respective expressions for \(F_{\text{thrust}}\) and \(F_{\text{lift}}\) in all three options are equivalent.  
The admissible region in the phase space of the UAV model, in which the obtained expressions (5)-(7) are defined for (1), is provided by the following inequalities:  
\[V_{g}>0,\quad|\gamma|<\pi/2,\quad|\varphi|<\pi/2. \tag{8}\]  
Similar expressions for systems (2) and (3) can be obtained to transform the virtual control signals \(v_{1}\), \(v_{2}\), and \(v_{3}\) into the real ones.
# Experimental Investigation into Failure Modes of Low-Yield-Point Steel Plate Shear Walls
## 2 Horizontal Cyclic Loading Test
### Test Scheme
#### 2.1.2 Material Property Test  
The uniaxial tensile test on steel coupons were carried out to obtain fundamental mechanical properties of the materials, including the yield strength, ultimate tensile strength, modulus of elasticity, elongation, and yield ratios. The typical steel coupons designed in the shape of the plate shown in Figure 5 for the material tensile test were cut from the base metals. Table 2 presents the detailed sizes of different geometric parameters of the coupons, and three tensile coupons were tested for the LYP steel with the nominal yield strength of 100 MPa.  
Figure 4: Connection of infill panel in specimen 1 (units: mm): (**a**) Welding connection between column and infill panel; (**b**) Welding connection between infill panel and beam.  
Figure 3: Detailed drawing of 30 mm thick small bottom plate (units: mm).  
Figure 2: Detailed drawing of 60 mm thick large bottom plate (units: mm).  
These three steel coupons for tensile tests were respectively installed on the electro-hydraulic universal material-testing machine, which can automatically record the maximum load, yield strength, and ultimate strength at the end of the test (Figure 6). The tensile coupons of LYP steel were observed to stretch considerably long, from the initial elasticity to the yield and then to the strain hardening stage until the necking fracture. The cross-sectional area was reduced to a sufficiently small section, and the fractured surface was uneven and jagged after the tensile fracture of LYP steel coupons, as shown in Figure 7, which indicates that this LYP steel exhibits superior ductile performance.  
Table 3 presents the different mechanical behaviors of low-yield-point and ordinary steel specimens under quasi-static tensile tests. In comparison, the ratios of yield strength, ultimate tensile strength, and yield ratio of LYP steel to Q235 steel were approximately 0.41, 0.64, and 0.63, respectively, whereas the elongation of LYP steel was approximately 1.36 times that of Q235 steel. The actual engineering stress-strain curves of LYP steel could then be calculated and achieved based on the test results, as shown in Figure 8.