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Material Thermal Conductivity [W/mK] Specific Heat Capacity [kJ/kgK] Mass Density [kg/m3] Tuff 0.630 1.300 1500 Concrete 1.263 1.000 2000 Brick 0.500 0.840 840 Roof’s spruce beam 0.120 1.600 450 Plaster 0.900 0.910 1800 Perforated brick 0.325 0.840 1070 Insulating material 0.170 0.920 1200 Shingle 1.000 0.840 2000 Tile 0.840 0.840 1700 Table 2 – Building geometrical characteristics Walkable Inner Area 1252 m2 Building Volume 2364 m3 Total Glazed Area 83 m2 Surface Area Connected to the Ground 210 m2 Results and Discussion Starting from these objective data, simulations under dynamic conditions were performed with the TRNSYS.
Seeing Table 3, it is possible to observe a progressive reduction of the thermal transmittance that is important to decrease the heating energy demand and, at the same time, a solar gain factor reduction that is important to decrease the cooling energy demand.
Energy demands reduction ranges from 20.8% to 27.8% regarding heating and from 6.6% to 26.3% regarding cooling.
It is clear that the highest cooling reduction value (26.3%) is related to the lowest triple glazing g-value.
The highest cooling reduction value (26.3%) is connected to the lowest triple glazing g-value.

There is a lack in literature data about welding of these steels, particularly regarding to laser beam welding [6].
The increased hardness of the welded regions elevated the levels of tensile strength, but reduced the ductility; this reduction was associated with increasing the hardness of the welded region and the formation of small defects.
In both types of steel used there was a reduction in fatigue performance.
The welded steel 300M has reduction fatigue life more pronounced than the steel 4340 due to the difference in chemical composition.
The fatigue limit of the 300M steel was reduced to around 50% after welding while for 4340 steel the reduction was around 15%.

CaO•MgO, and ferrosilicon into retorts inside reduction furnaces.
The briquettes after the MgO reduction are discharged from the retorts as a by-product or waste.
Some of the agent data are listed in Table 1.
Fig. 2: XRD pattern of original Mg slag (a) and sintered slag-borate mixture with 0.53% DB (b) Fig. 3: Equilibrium phase distribution, in gram or weight percent, during cooling of the Mg slag in temperature range of 1300-100°C calculated by FactSage 6.2 The composition of Mg slag in Table 2 was adjusted in Table 3 as input data for the thermodynamic calculation using FactSage 6.2.
There was also a volume reduction of 20-30% for the sintered slag-borate briquettes.

Based on the geophysical data, temperatures measured in the geothermal field, an analysis of soil mercury, and an electrical resistivity survey and other information, it is possible to say that Rehai is a hot water system with a magmatic heat source of about 400-600ºC.
Cost reduction The capital cost is considerably high and is required to be available when the geothermal power plant is going to be built.
The R&D effort such as the geothermal technology localization and O&M technique will contribute to reduction of capital cost.
Conclusion Geothermal power in Tengchong does not only mean contribute to CO2 reduction, but it is also reduced coal import dependence in the future and increase in export opportunities, sustainable local economic growth, more job opportunity and so on.
Most of the countries in the world have integrated emission reduction as crucial national strategy.

The results showed that the contour of springback simulation with the proposed elastic modulus model is closer to that of the experimental data than results of constant elastic modulus simulation.
Reduction of the elastic modulus was observed at low strain levels, and saturation remained at a constant value under a moderate plastic strain [[] Kim H, Kim C, Barlat F, et al.
Journal of engineering materials and technology, 2003, 125(4): 237-246. ]; the reduction usually varied from 20% to 30% for high strength steels.
Fitting curve of the calculated elastic modulus data is displayed in Fig. 1c.
The reduction of the elastic modulus reaches a maximum of 16.7% when total elongation is achieved.

GIS enables the spatial analysis of emissions data.
The data include the historical data of GDP, population, energy consumption, green finance index, and carbon emissions from 2002-2019.Complete dataset only includes 18 years of carbon emission data and the four input variables.
To obtain more training data for the neural network, linear interpolation is applied to expand the yearly 18 data points to monthly 216 data points.
To improve generalization performance of ELM-ARIMA composite model, the 18-year four variable data is split into train and test data in a 5:1.
The training set has data from 2002 to 2016 (months 1–180) while the testing set has data from 2017 to 2019 (months 181–216).

The procedure of the proposed neural network incidence rate prediction model based on the rough set theory in this paper is as follows: · Construct the decision table on the incidence rate of history data and related information historical data
Set the number of sample data set is, divided it into small zones.
We first division the sample data from childhood in this article, then choose the cent point in turn, make the number of the fall sample data of each interval is.
The original data is obtained from Qinghai Haixizhou first people's hospital, incidence rate data and meteorological data from January 2003 to December 2009.
Finally, we using the original historical data to train the network, and set the learning times as 1000, the learning curve is shown in figure 2.

The fraction recrystallized calculated from the experimental softening data was then verified by quantitative metallography at 300°C.
Excellent agreement was observed between the fraction recrystallized calculated from the mechanical testing data and estimated from the quantitative metallography results.
Recrystallized grain size: The CC material produces a finer recrystallized grain size as compared to the recrystallized IC material (20μm for the CC material as compared to 30μm for the IC material for 40% cold reduction).
Using equations (2) and (3), it then possible to calculate that the change in electrical resistivity expected from a reduction in dislocation density as 0.4nΩm which is again within the margin of error for the experimentally measured value of 0.5±0.2nΩm (all data shown in Table 5).
We would also like to acknowledge Johnson Go of UBC for providing softening data for ingot cast AA5754 material.

The tool path generated by this method are also compared with that of the long edge of surface as the MCP, the results of simulation show that the method can yield a reduction in line segments of tool path .
MCPs along the locus of maximum convex curvature lead to a considerable reduction in machining time while those for minimum curvature yield a reduction in CL data file size.

Experimental results show that the abrasive grains size reduction was proportional to the improvement of the surface quality during the lapping, after 45min the abrasive size change tends to be uniform, the participation rate of abrasives grains in lapping process was between 0.2% and 16%.
According to the characteristics of the experimental data, we can judged from Fig.3, after 45min, the lapping process belongs to the stage of uniformly stage, this has been demonstrated from average results of roughness as shown in Fig.4, in the period of the first 45min, roughness Rt decline faster, after 45min Rt roughness is essentially retain the same, on the one hand, can test the processing limits of 280 # abrasive, after 120min, the declining of the roughness was mainly due to the breakage of abrasive grain in the process, tended to be uniform.
This shows the correlation between surface quality and abrasive size, in other words, size reduction resulted from abrasive wear would improve the surface quality.
It indicated that the improvement of sapphire surface quality was proportional to the reduction of abrasive particle size.