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Based on probability distribution of the residual strength of concrete under fatigue loading, the P-R-N curves are obtained based on test data, the empirical expressions of the residual strength corresponding to the number of cycles were obtained.
Fatigue life data of specimens subjecting to stress S, the initial compressive strength of specimens and the residual strength of the unfailed specimens are all listed in Table 1.
All the data are listed in increasing order of magnitude.
The probabilistic distribution of the fatigue residual strength is found out, the P-R-N curves are obtained based on test data, the curves can be used to predict the residual strength with reliability.
Q20091119), also supported by Wuhan University of Science and Technology Research Center of Green Manufacturing and Energy-Saving & Emission Reduction Technology (contract No.

This establishes the need for a concerted effort to expand the data base for natural materials, which include all potential fibre sources.
Mahogany gave a reduction of about 20%.
Afara gave 48% reduction while Caeser-weed reduced the strain value by 88%.
At break, addition of Mahogany dust resulted in a reduction of 12%, Afara dust reduced the value with 46%, while Caeser-weed fibre gave a reduction of 85% .
The reduction given by the Caeser-weed was highest of the three biological materials.

The strong and smart grid can be divided into five links as power generation, transmission, transformation, distribution and utilization; the information and communication data platform, equipment manufacturing, software and hardware development, design and installation of construction and professional service industries would permeate into every link of the industry chain, and the vast users are the final service objects of the strong and smart grid.
The environmental value mainly comes from the reduction of greenhouse gases emissions and pollution.
As shown in Table 1, includes all its value calculation models such as emissions reduction, industry development, employment increased and etc.
Talbe 1 Value Calculation Model of Large-scale Clean Energy Grid Combination Project Whole industry chain value Value Calculation Model Environmental value Emission reduction of carbon dioxide ①BCO2=∆EC ×βCO2×PCO2 Emission reduction of sulfur dioxide ②BSO2=∆EC ×βSO2×PSO2 Emission reduction of nitric oxide ③BNOx=∆EC ×βNOx×PNOx Economical value Power generation of clean energy ④Bclean energy=Ecombination×Pselling Drive the industry ⑤V industry=Cpurchase+Cconstruction Social value Drive the employment ⑥Bemployment=Ｖindustry／εindustry Intelligent Electric Vehicle Charging and Transportation Network Project.
As shown in Table 2, includes all its value calculation models such as emissions reduction, increased income for grid from power selling, employment increased and etc.

For each external iteration the search space is reduced around the optimal solution found in the internal iteration, this reduction is defined by a coefficient.
For all version of LJ algorithm it is used the reduction coefficient (rc = 0.1).
The circles in the Fig.2 are considered outliers, which represents points much higher or smaller than the next nearest data point.
This occurred because the search space was refined after its reduction on each iteration of this algorithm.
Jaakola, Optimization by direct search and systematic reduction of the size of search region.

Based on these findings, this study outlines future research directions, including the development of IoT-enabled systems for real-time data sharing, advanced simulation models using detailed building spatial data, evacuation facilitation systems informed by active shooter dynamics, and training systems grounded in real-world building spatial data.
Cho et al. [10] developed an agent-based model using Building Information Modeling (BIM)-enabled spatial data of buildings and human monitoring to simulate an active shooting incident and evacuation.
Secondly, a sophisticated simulation model can be developed using BIM-based spatial data from actual buildings.
By utilizing spatial data from actual structures, this methodology is expected to significantly enhance individual self-efficacy and overall evacuation effectiveness in genuine active shooting situations.
The facilitation system overlooks key active shooter data, such as shooter location and movement.

For the UAV monitoring and inspection data that are quantitative,the data are assessed and scored by the fuzzy AHP method,while for the extent of the data that are non-quantitative,the data will be directly assessed and scored according to the expert system.
Depending on the different kinds of the assessment content ,we take real-time monitoring , regular monitoring and artificial inspect to obtain these data evaluation.
The main manual inspection to the naked eye or a portable instrument bridges the apparent state of regular checks made to quantify the extent of the description of the data or status .
For manual inspection and other non- quantitative data , based on existing UAV system maintenance practices and expert described the results directly to quantify the extent of score draw assessment scores , as shown in Table 3.
Such as severe emergencies ( such as when recovering a large impact strength , strong winds task interference ) occurs , according to real-time data acquisition system , to assess the state of the UAV incident after incident assessment form reports.

We have proposed the method for error calculation using measurement data and then their correction experimentally up to 10 nm.
Tiziani: Fast algorithms for data reduction in modern optical three-dimensional profile measurement system with MMX technology.
Optoelectronic, Instrumentation and Data Processing, Vol. 43, No. 1 (2007)

The modeling of necking using a modified Norton power-law allows lifetime predictions in agreement with experimental data up to a few thousand hours only.
The extrapolation of these curves obtained at high stress leads to overestimated lifetimes which differ by a factor of five at low stress with respect to experimental data.
Other experimental data beyond 50·103h are necessary in order to validate long term creep predictions.
Abe, NIMS Invited Researcher, and the Japan Institute NIMS, for providing the creep rupture data of 18Cr-12Ni-Mo-middle N-low C [8].
Auzoux, ‘Reheat cracking of austenitic stainless steels – influence of work hardening on intergranular damage’, PhD thesis, MINES ParisTech and CEA Sacaly. (2004) [8] NIMS, Creep data sheet, No. 45, Data sheets on the elevated-temperature properties of 18Cr-12Ni-Mo-middle N-low C hot rolled stainless steel plate (SUS 316HP), Japan. (1997) [9] C.R.

Because of the diversification of terrain,in order to avoid data conflict and attribute mapping errors,drilling data coding should be done at the very beginning.The geographic data is composed by spatial data and attributa data,and in order to realize the data processing,attributes match and texture mapping, spatial data and attributa data should be established a unique identifier.The original data is organized in Table.1: 1 2 3 4 Table.1 Data storage table Primary identification code Secondary identification code Project name Project location Pile code Core code Drill code drill code X Y Z D H P In the code above,XY stands for planar coordinate of drilling data，Z stands for the elevation of the terrane,D stands for the terrane that the drilling data belongs to,Hstands for auxiliary information and P stands for Image texture information.
Interpolation data is imported and integrated with the raw data until the interpolation precision is satisfactory.The grid data of Three-Dimensional geological model (X,Y,Z)will be composed of all the ready-processed data.
The surface modeling method of geological body generate virtual data through adopting reasonable data interpolation method.
Attribute data and texture data are added to constructe an approximate model of the geological body by simplified surface.
Visualization method is described as below: Use the advanced modelling nodes of VRML to to construct complex irregular graphics.First of all, elicit and elicit the interpolation data of the drill data, and process the data according to the VRML specification data format.

Simultaneously, the Auger and XPS data show a decrease in Si intensity.
At each step, again LEED, AES and XPS data were taken to monitor changes to the chemical and structural properties of the surface.
For comparison, the plot also shows AES data from the fresh polished sample (top curve) and a polished sample prepared by the RCA recipe (second curve).
With increasing temperature the (1×1) periodic spots become brighter accompanied by a reduction of the background intensity.
Simultaneously, the Auger and XPS data show a decrease in Si intensity.