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Vibration Analysis and Evaluation of the Indoor Spiral Steel Stair Bin Zhou1,a , Xiaosong Ren2,b and Xilin Lu1,c 1State Key Laboratory of Disaster Reduction in Cilvil Engineering, Tongji University, Shanghai 200092, China 2Research Institute of Structural Engineering and Disaster Reduction, Tongji University, Shanghai 200092, China aemail: ebinzb@163.com, bemail: rxs@tongji.edu.cn, cemail: lxlst@tongji.edu.cn Keywords: Indoor Spiral Steel Stair; Analysis; Load Model; Evaluation; Natural Frequency; Peak Value; Weighted Root-Mean-Square (R.M.S) Value Abstract.
The experimental data suggested that the frequency of walking in ascending or descending the stair is about 1.6Hz, while the frequency of running in ascending and descending the stair is about 3.5Hz and 4.3Hz respectively[1].
Table5 The calculation parameters in vibration analysis Parameters Content Value G Static weight of person 750N fpw Frequency of one person walking in the process of ascending or descending the stair 1.6Hz σpw Reference variance of one person walking 0.2Hz fpr-a Frequency of one person running in the process of ascending the stair 3.5Hz fpr-d Frequency of one person running in the process of descending the stair 4.3Hz σpr Reference variance of one person running 0.4Hz aw1-a Value of the first Fourier coefficient of walking ascending the stair 0.43 aw2-a Value of the first Fourier coefficient of walking ascending the stair 0.18 aw1-d Value of the first Fourier coefficient of walking ascending the stair 0.59 aw2-d Value of the first Fourier coefficient of walking ascending the stair 0.23 ar1-a Value of the first Fourier coefficient of running ascending the stair 0.92 ar1-d Value of the first Fourier coefficient of running descending the stair 0.87 According to the distribution data presented

The pressure effects in parent manganite compound and Ga-doped manganite are also the effects of orbital ordering reduction.
The dilution of the JT manganese ions sublattice by non-JT and non-magnetic gallium ions leads to reduction of JT distortions and spin-glass [6] or ferromagnetic ordering [1-5].
Pressure dependence of Qq Circles—calculation based on our experiment, squares—experimental data of papers [1, 2] (open and filled symbols, correspondingly) Fig. 2.
Open circles denote calculation using crystal structure of the paper [2]; black squares denote calculation using our experimental data.

Prior experiment, investigated alloy was subjected to a preliminary thermomechanical treatment, which includes a cold rolling to 60% thickness reduction and subsequent 1 hour recrystallization annealing at 1000 °C.
• KAM – for a given data point the average misorientation between the data point and all of its neighbors is calculated (exclude misorientations greater than some prescribed value - 5° in this case).
Results and discussion Results of the structural analysis have shown that the cold rolling (to 60% of thickness reduction) followed by the proposed heat treatment (annealing at 1000 °C) leads to a refinement of the matrix grain size to d=20mm with a large fraction of high angle grain boundary (~90%) (Fig. 1).

The reduction of the vital dye MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) by the mitochondrial succinate dehydrogenases of the living cells was modified from Katic et al. method [4].
Each data print represents a mean ± standard error of 3 replicates.
Data with the same letter are not significantly different at p ≤ 0.05.
Both UV radiated and filter sterilized medium with clinoptilolite treatment showed a gradual reduction of medium pH with further addition in clinoptilolite concentration.

Process research Take parameters of quality evaluation of CWR modeling results for comparison with experimental data.
Reduction ratio [7, 9] under wedge rolling for the current workpiece: δ=Dd=2818=1.55 (1) As reduction ratio comes to 1<1,55<1,6 [9], the current process is possible to implement.
As a result, after the data processing, dependence between a relative slipping rate and a friction factor was obtained (Fig. 4).

Introduction Magnesium-based alloys in physical and mechanical characteristics successfully compete with other lightweight construction materials, primarily in those areas where weight reduction is of paramount importance [1].
Based on the experimental data on pressing of non-porous blanks, three modes - 300, 350, 400 ° C were chosen as the working temperatures of the extrusion process.
As follows from these data, the hardness values ranged from 75 to 100 HBW, and the residual porosity ranged from 0.5 to 1.7%.
The higher the temperature, the more pressure must be applied to break the specimens, and the smaller the reduction (the larger the die diameter), the higher the tensile strength.

Modeling Flow Description and New SiC MOSFET Layout Proposal Simulation approach A modelling strategy based on the concept of system complexity reduction has been applied to SiC power MOSFET [2], [3].
Table I Switching losses data for STD and new layout at 25°C Table II Switching losses data for STD and new layout at 200°C (a) (b) Fig. 5.
Greco, System complexity reduction approach in the modelling of a discrete power, in Proceedings of the 2018, Power Conversion and Intelligent Motion (International Conference on Power Control)

This paper discusses the application of the rammed pedestal pile in thin stiff stratum in soft soil based on the engineering practice, presents the strengthening design of adopting thin stiff stratum as bearing stratum, and provides guidance for the strengthening of thin stiff stratum which has great economic significance on the reduction of engineering cost.
With the construction technology of no pile toe, there exists obvious variation of penetration by sinking pipe because of the relative poor soil layer above the thin stiff stratum, and considers the exploration data, it is clear to determine whether the pile reaches the stiff bearing stratum.
After the project finished, the static-load pressure test on three piles was carried out, the Q-S curve and data are shown in Table 2 and Fig. 2.
Table 2 Data of static-load pressure test pile number load P(kN) settlement S(mm) critical load Pu(kN) pile 1 600 7.52 600 pile 2 600 8.93 600 pile 3 600 8.68 600 Annotation: the pile 3 is strengthened.
Fig. 2 Q-S curve of 1# pile, 2# pile and 3# pile By analyzing the data, following conclusion can be obtained.

The reduction effects on elemental mercury emission by different control devices are shown in Fig. 1
Fig.1 Reduction effects of different control technologies on elemental mercury emission （5）Analysis of mercury emissions of the different coal byproducts Mercury proportions in coal by-products of total mercury are shown in Fig.2.
Sample name Hg (ng/g) Cement plant 1 Iron ore powder 11.9859 Limestone 30.0545 Silicon waste rock 7.0601 Fly ash 369.7598 Precipitator ash 6.0901 Cement plant 2 Limestone 11.0420 Silicon waste rock 6.5373 Limestone slag 27.8678 Sulfuric acid residue 166.1396 Cement plant 3 Iron ore powder 9.5362 Limestone 12.1612 Silicon waste rock 11.7516 Fly ash 664.1089 Cement plant 4 Ore slag 10.5384 Steel slag 7.5743 Bauxite 47.0390 Rock 797.8275 Limestone 6.7505 Coke powder 169.1279 Fig.4 Mercury concentration test results of the cement kiln flue gas Through the analysis of the data the following conclusions can be obtained: （1）For the limestone one of cement raw materials, mercury content was only 5.4% to 7.5% of the average mercury content of coal.
[5] He S, Zhou J S, Zhu Y Q, et al., Mercury Oxidation over a Vanadia-based Selective Catalytic Reduction Catalyst[J].
[10] Wo J J, Zhang M, Cheng X Y, et al., Hg2+ reduction and re-emission from simulated wet flue gas desulfurization liquors[J].

Flow rate data from the amplifier into the second meter reading can be easily and rapidly read.
During the experiment, if the reduction of formation variation coefficient after ball blocking is less than 40%, it is defined bad effect.
If the reduction is from 40% to 60%, it is defined moderate effect.
If the reduction is greater than 60%, it is defined good effect.
Table 5 Effect of total flow rate on diversion Flow rate ratio Total flow rate (m3/h) Injected ball number Blocking ball number of layer Flow rate of layer (m3/h) Variation coefficient before ball blocking Variation coefficient after ball blocking Variation coefficient reduction (%) Diversion effect 1 2 3 1 2 3 6:3:1 3.5 42 12 5 4 1.37 1.29 0.84 0.62 0.20 67.74 good 4.2 48 14 4 0 1.62 1.42 1.16 0.62 0.13 79.03 good 5 48 14 4 2 2.01 1.76 1.23 0.62 0.11 82.26 good 1:3:6 3.5 54 1 4 12 0.92 1.15 1.43 0.62 0.18 70.97 good 4.2 54 1 4 13 1.15 1.46 1.59 0.62 0.13 79.03 good 5 48 2 6 14 1.47 1.66 1.87 0.62 0.10 83.87 good Conclusions (1) Simulation lateral well for ball sealer diversion was established.