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The types, characteristics and application of new building wall materials As for the building structure, the wall is the most important part of building, and it is also the key factors to the performance and service life of building.
Due to the light wall materials are mostly processed using industrial waste, and the physical and mechanical difference in properties such as thermal conductivity, temperature conductivity and the strength, it will produce certain tensile, compressive stress in masonry surface, resulting in the crack of the plaster easily and empty drum.
But it should be uniform, continuous when concreted, or the polystyrene boards may deform because of the effect of the lateral pressure of concrete which will affect the subsequent construction.
It is also not affected by structural quality differences.

This happens as a result of variation of intrinsic factors i.e.: 2.
Fig. 7: SEM image of fracture surface of Zr47.5Cu45.5Al5Co2 [26] 3.1.9 Mechanical Properties Like microstructure, the mechanical properties of BMGMC are a strong function of composition.
This can effectively be used for evolution of preferred phases and thereby affect the alloys properties.
Thadhani, Mechanical properties of bulk metallic glasses.
Shiflet, Mechanical properties of iron-based bulk metallic glasses.

Lamb Wave Based Monitoring of Fatigue Crack Growth Using Principal Component Analysis Ye Lu1, a, Mingyu Lu2, b, Lin Ye3, c, Dong Wang4, d, Limin Zhou2, e and Zhongqing Su2, f 1 Department of Civil Engineering Monash University Clayton, VIC 3800, Australia 2 Department of Mechanical Engineering The Hong Kong Polytechnic University Hong Kong SAR People’s Republic of China 3 Laboratory of Smart Materials and Structures (LSMS) Centre for Advanced Materials Technology (CAMT) School of Aerospace, Mechanical and Mechatronic Engineering The University of Sydney, NSW 2006, Australia 4 Beijing Aeronautical Science & Technology Research Institute Beijing 102211, People’s Republic of China a ye.lu@monash.edu (corresponding author), b 08900426r@polyu.edu.hk, c lin.ye@sydney.edu.au, d wangdong1@comac.cc, e mmlmzhou@inet.polyu.edu.hk, f mmsu@polyu.edu.hk Key Words: Fatigue crack growth, Principal component analysis, Lamb waves, Structural health monitoring Abstract
As a result, the crack may be undetectable due to the marginal difference in comparison with the baseline signals, or the characteristics of the received signal, e.g. the damage index, may exhibit nonlinear properties.
Ten circular piezoelectric (PZT) wafers with mechanical properties listed in Table 1 were surface-mounted on the plate, in which wafers P1-P5 functioned as actuators and wafers P6-P10 were corresponding sensors in a pitch-catch configuration, detailed in Figure 2.
Crack growth (a) (b) (c) Figure 4 Distribution of the first two principal components of different crack lengths for sensing paths (a) P1-P6; (b) P3-P8; (c) P5-P10 The main reason for the different properties of the principal components for sensing paths P1-P6 and P3-P8 was the fact that generation and acquisition of Lamb wave signals were completed in the unloading condition.
For sensing path P1-P6, which was the first path affected by crack propagation, the hairline fatigue crack always evolved from closing or semi-contact to full opening, even under the unloading condition.

Therefore, comparing concrete mixes with different mechanical properties only makes sense within the whole structure.
If the user enters the concrete strength class according to EN 1992 [1], the values ​​of the mechanical properties given in EN 1992 are automatically used for the calculation.
However, it is also possible to enter custom values ​​of mechanical properties.
This can be used, for example, for high-strength concrete, which mechanical properties are not given in EN 1992.
In case of entering custom values ​​of mechanical properties, the concrete composition must be also entered.

At high speed, the temperature rise arising from friction can cause thermal elongation to affect the positioning accuracy of the screw [2].
(16) 2.2 The relation between traction coefficient and sliding ratio To analyze the lubricating property of lubricating oil and the relation between traction coefficient and sliding ratio, the following assumptions can be adopted: the stratified flow of lubricating oil; regardless of inertia force and volume force; no slipping between lubricating oil and surfaces; pressure and viscosity are still in the same direction along the oil film thickness and correspond to Barus relation; the impact imposed by temperature on viscosity [10] is negligible.
Therefore, the increase of rotation speed can facilitate full fluid film lubrication, but the reasonable load bearing is a key factor for the full fluid film lubrication. 5.Acknowledgments This work was supported by the National Natural Science Funds in China (No. 50875153).
[6]Lingfeng Li,Cai-fen Liu.Study on Axial Deformation of Ball Screw.China Mechanical Engineering. 2011,22(7):762-766
Jounal of Mechanical Engineering,2004,47(4) :123-1127

China began studies on NC machining parameter optimization during 1980's, cutting database was established in the same time.However, the application of the cutting database in practice still has many problems, because the current use of cutting database is affected by the differences from production conditions and the limited cutting process data.
Cutting parameters optimization for NC milling based on BP Neural Network Cutting parameter optimization techniques for NC machining have the properties of multi-objective, multi-constraint and multi-variable, so the optimal cutting parameters can't get by traditional optimization algorithm.Artificial neural network with the advantages of parallel computing,distributed associative storage,better fault tolerance and adaptive learning features is in the forward position to deal with complex nonlinear problems and artificial intelligence, which has penetrated into many fields in recent years, and the range of applications is growing, especially the applications in mechanical engineering are extremely broad, such as the researches and applications in error compensation of the machine motion, thermal deformation control, the assessment of process parameters,process parameters optimization, processing error prediction and tool wear estimation have made certain achievements.
According to apecific process issues, the number of network layers, the neurons, fitting error, learning rate and sample data should be required to determine for the application of BP neural network, all these are closely related to the network's prediction accuracy and training time, which will directly affect the network's predictive effect and computation efficiency[5].
BP neural network model of cutting parameters optimization of aluminum alloy shell structure adopts 3 layers, the input layer neurons are the tool type,tool extended lengths,tool diameter,tool diameter ratio,basic dimensions,cutting width,cutting depth,dimensional accuracy and surface finish; the output layer neurons are the spindle speed, feedrate and processing time, for considering the processing time is a value factor of milling efficiency, the neural network structure is 9-36-3, which is shown in Fig.1.
The studies of cutting parameter optimization technique for NC Machining have shown that: taking the neural network technology into the optimization process of cutting parameters is very appropriate, using BP neural network, milling parameters optimization model of aluminum alloy shell structure was built, the prediction and optimization options of cutting parameters of aluminum alloy shell structure was realized , the human factor of craftsmen in the process of cutting parameters selected was avoided, making the choice of cutting parameters with higher reliability, and the optimization effect is obvious.

In the latter, the SMG structure is replaced by a coarse grain size by rapid growth of a few grains which drastically reduces the mechanical properties of the material [1].
In addition to a fine grain size in SMG alloys, there are two notable factors affecting the growth of a cell or subgrain within a deformation substructure.

From one hand this is due to the fact that hydrogen in titanium has high mobility and hydrogen accumulation leads to significant changing of mechanical properties of titanium alloys.
Since the samples were hydrogenated up to concentrations varying from 0.9 at.% to 31.5 at.%, the hydrogen accumulation is not the only factor that affects the formation of defects.
Another factor is a phase transformation process.
Since the hydrogenation are carried out in hydrogen at 873 K and was followed by vacuum cooling to room temperature, the processes of defect formation is highly affected, not only by the hydrogen accumulation, but also by the phase transformation processes.

Study of building structural system for the external thermal insulation technology, many foreign engineers developed dozens of different wall insulation system, such as EIFS(exterior insulation finishing system), in the mid 1980s in China, under the influence of insulation enterprise in foreign countries, the external insulation technology began to research, At present, China prepare the industry standard issued by the recommended industry standard exterior insulation systems: EPS thin plaster external thermal insulation system, insulating mortar consisting of gelatinous powder and EPS pellets insulation system, cast-in-situ concrete composite no nets EPS exterior insulation system, cast-in-situ concrete composite EPS wire rack boards exterior insulation system, mechanical fixed EPS steel mesh exterior wall insulation system [2].
The temperature change is the same in the coating system with the internal surface of the box, while less in the tile system; it means that the properties of materials of finish coat would affect the external insulation system on a certain degree [6, 7].
(2) Under the stage of heat- rain cycles, during the sprinkler the cooling influence of the tile system and the coating system is greater than the heating influence, which indicates the temperature difference between layers was less affected by external temperature ,and the time when the external temperature arrived to the interface layer is shorter.
This shows environment of the weather fastness box is complex under the stage of hot-cold cycles, which is influenced by factors such as low radiation and cold air convection.

As the statistical analysis shows, quality level, quality assurance cost, quality failure cost can affect each other and they can change with the positive direction of quality assurance cost and change with the negative direction of quality failure cost[7-9].
The increase and decrease of prevention cost and appraisal cost can affect internal failure cost and external failure cost.
The stable design is for the purpose to make the mean value of product quality characteristics reach the target value as much as possible and minimize the variance of functional characteristics fluctuation caused by various interference factors to minimize quality loss: (6) If it is recorded as, then: (7) If it is defined that Cpm is the second generation of process capability index and Cpmk is the third generation of process capability index, then: (8) It is thus clear that the relation between quality loss function and process capability index is as follows: (9) In case of, namely, , substitute K1 value to obtain the average quality loss of each product as follows: (
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