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After single pass deformation of 25% reduction at 1070oC, the austenite grain size coarsened to 80 microns upon cooling at 1K/s to 1000oC.
Upon 25% reduction at 1000oC, steel exhibited uniform grain size of 13 microns at the end of 3 seconds.
Table-1: Effect of austenite grain size and % reduction below temperature of no recrystallization (TNR) on Sv factor and ferrite grain size.
The analysis of Kozasu’s data-base inter-relating parent austenite grain size, total reduction below temperature of no recrystallization and ferrite grain size shows that by refining the austenite grain size before pancaking, it is feasible to obtain the same Sv factor with less total reduction below temperature of no recrystallization than obtained by large reduction on coarse austenite grain size.
A comprehensive experimental data base on solute niobium in retarding grain coarsening of austenite as a function of temperature is required to advance near net shape processing of high Nb steels using Compact Strip Rolling (CSP). 6.

To reduce these damages, stormwater runoff reduction facilities were deemed necessary.
Surface runoff, precipitation runoff and temperature were recorded with 5 second interval of data logger measurement.
Schematic diagram of experiment device Results Water-quantity reduction The averages of water-quantity reduction rate in each permeable pavement are presented in Table 1 when rainfall rate with hydraulic pump set 25 and 50 mm/h for the duration 30 minutes.
Surface Flow rate Valve Artificial rainfall Pump Precipitation runoff Artificial sunset Surface runoff Permeable pavement Data logger measurement M Storage vessel Temperature sensor runoff means the effluent of pavement non-filtered and precipitation runoff means the effluent of pavement filtered in system.
Type B pavement obtained runoff reduction rate of 95.8 and 81.4 % in 25 and 50 mm/h of rainfall condition, respectively.

Ali et al. [6] presented a new system which can be appropriate for rating tunnel sites to evaluate the potential of groundwater inflow according to the preliminary site investigation data based on the fuzzy Delphi AHP method.
On the basis of the relevant data, the permeability coefficients of the lining is 1.03×10-4 m/d, and that of the surrounding rock is 0.54 m/d.
According to the exploration data, the water head (h) of the model is 60m.
According to the Fig. 7, with the reduction of h, Q decreased sharply at the beginning, and then, the reduction trend gets inconspicuous.
(3) Based on the Fig. 7, with the reduction of ground water level, the seepage discharge decreased sharply at the beginning, and then, the reduction trend gets inconspicuous.

This paper selected the data base from laboratory experiments and applied the multiple regression statistical method to establish a series of empirical calculation models for delimiting the debris flow hazardous areas on the alluvial fan.
This paper selected the data base from laboratory experiments and applied the multiple regression statistical method to establish a series of empirical calculation models for delimiting the debris flow hazardous areas on the alluvial fan.
Data Preparation To establish the empirical prediction model of debris flow deposition on its alluval fan, twenty laboratory empriments under the condition of different debris flow volumes (V), densities (rm) and slopes of accumulation area (θd) were carried out.
Therefore, we collected data from literatures and filed investigation to carry out verification analysis.
Based on the multiple line regression analysis of experimental data, the empirical models for predicting the maximum deposition length (Lc), the maximum deposition width (Bmax) and the maximum deposition thichness (Z0) were establised.

To get the nephogram of sound intensity and sound power spectrum, we used the sound intensity probe and Multi-channel Data Acquisition Regulation System B&K 3560-D and Pulse Data Processing Analysis Software.
The measurement results will serve as a reference for the car noise reduction. 1.
The main instruments were used in testing, as follows: (1) Multi-channel Data Acquisition Regulation System B & K 3560-D, and Pulse Data Processing Analysis Software; (2) One set of 3559 sound intensity probe, and the sensitivity and the model of it is shown in Table 1; (3) A computer; (4) Some cable.
The measurement results will serve as a reference for the car noise reduction

Besides real time data transmission, the BAN system can also store data in its onboard memory.
The data is saved in binary file format and then exported to ASCII file before opening the data file in third party software applications such as Excel.
The data acquisition software of the BAN system transferred real-time data to the computer and plot three linear acceleration graphs in time domain.
Total of 50 sets of data is collected.
More data will be collected in our future work.

Over 50 percent of CO2 emissions come from coal-fired power in the power sector[3], implementation of the energy-saving and emission-reduction policy in power sector has an important significance to the whole society’s energy saving and emission reduction.
Model for calculating pollution reduction and its value after power generation exchange The reduction of the kth kind of pollutant from power generation: (3) The value of the kth kind of pollutant’s reduction from power generation: (4) The total value of various pollutants’ reduction from power generation: (5) In the formula: is the emission reduction of kth kind of pollutant after power generation exchange, is the add-value brought by the kth kind of pollutant’s reduction after power generation exchange, is the total value of various pollutants’ reduction from power generation, is kth kind of pollutant’s emission coefficient of per unit of coal consumption, is the price of kth kind of pollutant of power purchasing side, is the price of kth kind of pollutant of power supply side.
Basic data This paper collected basic power generation information about area A and area B to start the case analysis; details as shown in table 1.
According the data above, we can see a significant benefit for inter-regional power generation exchange.
In order to deal with this situation, the energy-saving and emission-reduction measures are necessary to be applied in the power industry.

A mathematical model about the relationship between the parameters, which were tensile strength of small diameter cold-rolled steel rebar product and raw materials’ tensile strength, reduction of area, speed of cold-rolling and coefficient of extension, was built.
The appropriate genetic parameters were determined and the data optimization of small diameter cold-rolled steel rebar’s main technological parameters was calculated.
System Modeling The major factors that influence the function of small diameter cold-rolled reinforced bar vary with raw materials’ tensile, reduction of area, speed of cold-rolling and coefficient of extension and so on.
To obtain the small diameter cold-rolled reinforced bar with larger tensile strength, the key is to ensure the exact match for the raw materials’ tensile strength, reduction of area, speed of cold-rolling and coefficient of extension [4].
After optimization, when raw materials’ tensile strength is 452.8Mpa, speed of cold-rolling is 2.57m/s, reduction of area is 25.6%, coefficient of extension is 1.60, standard small diameter cold-rolled steel rebar can be produced.

The hot-rolled plates were symmetrically cold-rolled to 65-95% reduction in thickness and then asymmetrically warm-rolled to 20-40% reduction by one pass at 473 K on a condition of roll speed ratio of 1.5.
To reveal a change in texture during solution treatment, the area fraction of representative orientations were determined from EBSD data by using the samples annealed at 813 K for some short periods within 90 s and immediately water-quenched.
In addtion, the microstructure in an as-rolled state before solution treating was observed by a transmission electron microscope (TEM) and the misorientation in deformed structure was determined from EBSD data of the as-rolled sample.
Results and Discussion Effect of rolling reduction on recrystallization texture.
The near-{111}<110> recrystallization texture, which has a peak in the center of a {111} pole figure, can be observed at relatively low reductions of AWR, while the {111} texture components hardly exist at all CR reductions on a condition of 40% AWR reduction and the principal component is expressed by {013}<631>.

However such equations, although describing the experimental data adequately, lack on the mechanistic approach which is needed in order to describe the effect of other factors, such as the solution pH, the effect of competing co-ions etc.
Cr(VI) reduction A wide-range of microorganisms are capable of enzymatic reduction of Cr(VI),[23].
U(VI) reduction Microbial reduction of soluble U(VI) to insoluble U(IV) by microorganisms such as D.
Mo(VI) reduction Enzymatic reduction of Mo(VI) (as molybdate, MoO42) to Mo(IV) is done by D. desulfuricans with both lactate and hydrogen as electron donors, [29, 32].
More information and application data can be found in literature, [48, 49] .