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Data show that OPS concrete is very sensitive to curing, especially when GGBFS is used as a supplementary cementitious material.
Because of the vast amount of concrete produced today, even a small reduction in the environmental impact per ton of concrete will result in considerable benefits to the environment [2].
Hence, the significant increase in strength gain from 1 to 3 days is due to the GGBFS, which, being finer than OPC, can cause a significant reduction in the volume of the pores of the concrete.
The advantages of using lower cement content is clear where reductions in the emissions in the cement industry such as CO2, SO2, NOx, dust and heavy metals and also huge amount of natural resources, energy, fossil fuels, water can be realized [16].
However, after 7 days, for GGBFS concrete, a significant reduction in the strength of specimens under air drying appeared at the ages of 28 and 56 days compared to those that were water cured.

Compared with a similarly rated silicon (Si) IGBT version, the SiC converter exhibits a 3% improvement in peak efficiency, 2.6 times reduction in total losses, and three times improvement in power density.
This is due to lower overdrive voltage at room temperature and reduction in the gate threshold voltage with temperature.
From this data the conduction loss for each switch in the DAB is estimated to be 25.7W under nominal conditions at a 25kW power transfer level.

Rainfall-Induced Slope Instability Rock Mixture Fluid - Structure Interaction Numerical Simulation Xiaonian She1,a , Helin Fu2,b , Zhong Zhou2,c 1Hunan Administration of Highway, Changsha, Hunan, 410007, China 2School of Civil Engineering, Central South University, Changsha, Hunan, 410075, China a sxn123@sina.com, b fuhelin100@yahoo.com.cn, c zhouz785@yahoo.com.cn Key words: Rainfall, Rock mixture, Slope instability, Fluid-structure interaction, Simulation Abstract: In this paper, did the numerical calculation of the mixture slope’s development and changes of the stress field, seepage field ,displacement field under fluid - solid coupling effects at different levels, researching and analyzing the water-rock interaction mechanisms of the mixture slope ,and based on strength reduction , calculated the slope safety factor at different water levels, revealed the failure mechanisms of a mixture of earth and rock slope when it considers the rainfall.
Introduction In this paper, numerical calculation of the different water flow when the mixture slope - solid coupling of the stress field, seepage field, displacement field of development and changes, research and analysis mixture slope of the water-rock interaction mechanisms, and based on strength reduction was calculated slope safety factor when different water levels, rainfall revealed a mixture of earth and rock slope failure mechanisms. 1 Model and calculation conditions for numerical analysis The literature [1] mixture slope field for the numerical simulation of artificial rainfall experiment object, engineering geological profile shown in Figure 4.
In laboratory and field test and field survey data, based on the slope of geotechnical parameters selected in Table 1.

To collect relative data of energy consumption and emission which were produced in the stages of units operating, the resources obtaining and manufacturing, then the obtained data were arranged into inventory analysis table.
Data Sources.
Data sources for this study mainly include the datas of trade association, scientific literature, enterprise actually production running, national statistics and research reports etc
Meanwhile according to the data in table 5, the environmental impact potential of three projects was calculated and the results are shown in table 6.
Data normalization was to illustrate the relative size of potential effect.

Using activities like Genba investigation, data collection, trials and data analysis, the root causes of the problem were identified.
Examples of primary data are factorial experiments conducted throughout the project.
Internal reports and data automatically collected by a production monitoring system are examples of secondary data.
To deal with the internal validity, statistical analysis of the data has been used.
Minitab program was used to analyze the data resulted from the designed experiments.

Furthermore, according to Fig. 1 the standard reduction potential for Cu and Mn is–0.045VSHE and –1.18 VSHE, respectively [13].
The discharge potential of Cu2+ (about–0.045VSHE) is close to the calculated Cu2+ reduction equilibrium potential (–0.03 VSHE) based on the Nernst equation.
The addition of ammonium sulfate probably leads to shift in Cu2+cations discharging potential to a more negative levels and shifts Mn2+ reduction reactions to more positive potentials, indicating that reduction potentials of Cu and Mn get closer to each other.
These data are related to co-deposition of Cu and Mn.
The grain size of the coatings was calculated using Scherrer equation (Eq. 1) according to the data of major peak Mn (101) as follows: D=0.9λ/βcosθ (1) where l, b, and a are associated with the wave length of Cu ka1 (1.5406 Å), the integral width, and the diffraction angle of the XRD spectra, respectively.

Results and Discussion Figure 1 shows the pressure distribution exerted on the die-wall for the solid cylinders in single-action pressings at 50.0% reduction in height (initial height to diameter, i.e.
The pressure build-up on the stationary punch is not significant until the compaction process reaches at 55% reduction in height.
Sometimes the consideration of average pressure is of interest since it simplifies both experimental techniques and the interpretation of the results. 166.7 204.7 195.4 274.0 221.6 216.9 357.8 279.2259.3 481.1359.1 293.0 636.8 468.6 167.6 143.3 108.1 120.8 120.4 82.2 91.2 111.8 69.1 82.3 92.1 60.666.284.6 48.0 56.2 �=0.05 �=0.10 �=0.15 �=0.20 �=0.25 136.9 232.3 161.9 224.0404.6 295.9 376.2 675.2 495.9 820.4 1565.8 1234.6 5.9 5.7 5.8 9.7 7.7 8.4 28.7 18.1 20.8 109.5 60.3 91.2 Fig. 1 The predicted pressure [MPa] distributions Fig. 2 The predicted pressure [MPa] along die and punches at 50.0% reduction in distributions along die and punches height with various friction coefficients at 25, 35, 45 and 55% reduction in (Init L/D=4.5) height with µ= 0.2 (Init L/D=8.0) The results of predicted
Experimental data by Duwez et al. [3] are compared to those from simulation (see Fig. 3(a)) and shows good agreement with the simulation results for available experimental data.
Vol. 185 (1949), p.561 100 200 300 400 500 600 700 0 5 10 15 20 25 Distance from Center [mm] Pressure on Moving Punch [MPa] µ=0.25 µ=0.20 µ=0.15 µ=0.10 µ=0.05 (a) Pressure on moving punch 0 20 40 60 80 100 120 140 160 0 5 10 15 20 25 Distance from Center [mm] Pressure on Fixed Punch [MPa] µ=0.25 µ=0.20 µ=0.15 µ=0.10 µ=0.05 (b) Pressure on fixed punch 0 50 100 150 200 250 300 350 400 450 500 0 10 20 30 40 50 Distance from Fixed Punch [mm] Pressure on Side Wall [MPa] at 551MPa at 482MPa at 413MPa µ=0.25 µ=0.20 µ=0.15 µ=0.10 µ=0.05 413MPa 482MPa 551MPa experiment [3] (c) Pressure on sidewall Fig. 3 Pressure exerted on the die and punches (50% reduction in height and Init L/D = 4.5)

However, in every case, it is fundamental to build a solid correlation between fatigue and the loading parameters based on limited experimental data.
Actually, fatigue test are time and money consuming and, consequently, there are not so many experimental data available.
Experimental data taken from [12] Fig. 2.
Experimental data taken from [12] In the present work, a model describing the fatigue behaviour of composite materials under spectrum loading is presented.
The model requires a limited set of fatigue data and, by fitting them through Eq. (1), it is possible to obtain the two parameters, α and β.

Calculated values of effective thresholds are in a good agreement with experimental data.
When the micro-roughness of the crack path becomes comparable to the crack tip opening displacement, processes as kinking and branching of the crack front can cause a further reduction of the SIF range ahead the crack tip [6].
In eq. (2) the reduction of the local SIF caused by crack branching was assessed by a factor of 0.5 [7] .Thus, the second term in parenthesis expresses a weighted average of both the roughness- and branching-induced shielding of the crack front.
Table 1 Experimental data Estimation of Effective and Intrinsic thresholds Values of both the statistical factor η and the effective SIF range , cal eff thK∆ calculated according to eqs. (1), (3)-(5) are displayed in Table 2.
(ii) The calculated values of effective thresholds (closure corrected) are in a good agreement with experimental data.

Relying on experimental test data ,the model of the nonlinear relationship between fine bundle the rebar tensile force and the exposed segment frequency was established.
Considering the design tensile force cannot meet design requirements, the code[6]prescribes that the reduction factor 0.6 is multiplied when vertical prestressing force is calculated.The tensile force of vertical prestressing finishing rolling rebar doesn’t meet requirements is largely caused by human factors, such as nuts are not tightened, installation errors are large, these factors can cause tensile force reduction.
A) Model structural map (unit: cm) B） Model after pouring Fig 3 Model test The theoretical value of k can be solved based on test data and formula (7).
The following conclusions can be drawn from test data: (1) Because the occlusion of the reinforcement and nut in anchoring range is increasingly tight, the value k is non-linear increase along the effective tensioning force, (2) The first-order mode frequency w is non-linear decrease along the length increasing of the exposed segment reinforcement under the same level of tensioning force.