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Considering all the factors involving heating of materials by a laser, absorptivity is of utmost relevance.
Guthrie, The physical properties of liquid metal alloys, Oxford Science Publ., Oxford, 1988, p. 232
Astarita, Effect of welding parameters on morphology and mechanical properties of Ti–6Al–4V laser beam welded butt joints, Journal of Materials Processing Technology 212 (2012) 427-436. ] studied the microstructural and mechanical characteristics of a laser beam welded Ti-6Al-4V alloy.
This is the reason the welded aluminum alloys present soft fusion zone and post-welding treatment is usually required to recover original mechanical properties [[] R.H.M.
The authors found two factors to affect cracking susceptibility.

ST depends on several interrelated processes and factors [9].
Therefore, many factors affect the capacity and performance of ST: solids characteristics, fluid characteristics, and design parameters such as tank type, solids loading rate, surface loading rate, hydraulic retention time, weir placement, and solids removal mechanism [10].
The particle properties of multisized slurry were obtained from the image processing.
The obtained values of particle properties (CF, y, κ) indicate that SS cooling water RNPP has a crystal structure containing sharp edges and is relatively hard [21].
The findings provide critical insights into the physicochemical properties of SS and their implications for the design and operation of water treatment facilities.

Introduction Characteristics of flexural motion of a bar depend on the mechanical properties such as density, stiffness and damping factor of the substrate material.
Once any one of these properties is modified, the wave characteristics of the motion will change.
In this case, the bar resembles the cantilever assembly with non-uniform mechanical properties due to heating.
Initially the substrate material is assumed to be at a reference temperature, To, therefore, the initial condition becomes: 0 at t TT o = = The thermal properties of the bar material used are given as: 53 W/m.K for thermal conductivity and 520 J/kg.k for specific heat.
The structural material properties are given as: 7880 kg/m3 for density, 0.015 for damping coefficient and 1.5 × 10-5 1/K for thermal expansion coefficient.

Bond proposed a method of determining the blast ability of rock by means of the index of the work of crushing; Northeastern University in 1984 through the blasting funnel test and acoustic wave test using multiple regression analysis method to derive the rock burst ability index formula, with the rock burst ability index to comprehensively evaluate the rock burst ability[1], the method can reflect the intrinsic law affecting the burst ability of the rock between the various factors, but the workload of field measurements is large, the calculation is complex.
In the self-learning process of the rig, the rig produces different mechanical responses to different rock interfaces, stops drilling when it encounters a rock interface, and manually enters the rock type identification code based on the characteristics of the rock cuttings and the principles of rock type identification, and at the same time, records the drilling machine's mechanical response to the rock layer and the rock type identification code.
l After collecting self-learning data sets of a certain size, regression analyses were performed to derive a mathematical modelling of rock type deterministic codes and the rig mechanical response parameters.
Improvements in Lithological Identification The lithology identification method requires a large amount of data as the basis, and at the same time, it is more dependent on the operator's judgement of the lithology of the ore rock, with high human factors, and different regression equations are obtained in different mining areas, and the correlation coefficients are between 0.60 and 0.82, which also indicates that the convergence of this method is insufficient to support a large range of applications. we propose a KNN method based on machine learning for lithology identification with drilling. 1.1 KNN The k-Nearest Neighbors (KNN) algorithm is a machine learning classification algorithm[12-14].
The method is not limited by the perforation process, and the requirement for geological conditions is as long as the ore rock has some difference in mechanical properties.

Preparation of experiment Mechanical Property of Raw Materials for Test .
Table 2 The property of adhesives No.
Table 10 The experiment results of concrete test cubes with strengths of C50 Diameter of anchorage bar Implanting depths of anchorage bar Ultimate drawing force(kN) Bond strength (MPa) 12 5d 22.66 8.02 30.13 9.75 22.15 7.64 20 5d 82.55 9.07 72.09 9.73 76.61 8.49 The Analysis of Factor Which Affect on Bond Properties Concrete Strength.
Other influencing factors.Transverse compressive stress can make the friction resistance of glue which between concrete interface and reinforcement interface increased, and then it can improve the capacity of bond anchorage.
Conclusions Through the analysis, main factors influencing the post-anchoring property of inorganic materials are concrete strength, concrete cover thickness, internal reinforcement cage(transverse reinforcement), reinforcement diameter etc. which shall be taken into consideration in the preparation of Technical specification for post-anchoring used in concrete structure with inorganic anchoring material to guarantee the application of post-anchoring technology of inorganic materials in the actual engineering.

FRA Tri-hydroxide (Al2O3) 15-20 wt % in the polyamide 11 have better performance of mechanical properties than other nano-clay FRA[14].
FDM printing products consist of 80 wt% of PLA, 17.0 wt % of APP, and 3 wt % lignin is investigated to evaluate improvement of the flame retardant-characteristic and mechanical properties [3].
FDM printing products consist of 80 wt% of PLA, 17.0 wt % of APP, and 3 wt % lignin is investigated to evaluate improvement of the flame retardant-characteristic and mechanical properties[3].
The small fraction of SDO will significantly affect the viscosity and mechanical characteristics.
Vahidi, Deterioration in the physico-mechanical and thermal properties of biopolymers due to reprocessing, Polymers (Basel). 11 (2019) 1–17. https://doi.org/10.3390/polym11010058

It is the subjective assessment of the strategy maker and also the objective reflection of the physical properties of the target.
Influence of Social Factors.
Comprehensive layer: the factors influencing stability of agro-ecosystem productivity mainly include natural factors and social economic factors.
Natural factors mainly refer to soil, climate and environment.
It is the most stable factor in the 6 factors.

In addition to rich sources, it has very good chemical and physical properties, such as a wide band gap (3.37eV) and high excition binding energy about 60meV [1].
Nanowires have a very good mechanical strength, thermal stability and chemical stability.
In addition to good optical and electrical properties, its structure causes many special optoelectronic applications, and thus it is considered to be the most promising materials to replace carbon nanotubes.
This study will focus on this part of using hydrothermal synthesis method to improve the dispersion of control, mainly to change the time of hydrothermal growth, with the zinc-doped such as hybridization to identify the main factors to improve the dispersion.
Intrinsic Properties of Group IV Elements and III–V, II–VI and I–VII Compounds, Berlin:/ Springer- Verlag,/ 1987

Up to now, many researchers have achieved different kinds of silicone rubber materials with excellent properties by filling diversified packing [4-6].
The complete curing time of RTV silicone rubber strengthened by fumed silica is affected.
The catalyst diffusion in the silicone rubber spends more time and is the dominant factor affecting the curing time.
Pho, RTV silicone elastomers in hand prosthetics: Properties, applications and techniques, Prosthet.
Wagner, Mechanical properties of carbon nanoparticle-reinforced elastomers, Compos.

In austenite and ferrite dual-phase region, because of different properties of dual-phase microstructure, deformation occurres incongruously in dual-phase microstructure.
These two sides affects deformation resistance.
Mathematic model of deformation resistance The relationship between deformation resistance and its influencing factors is shown as follows
is influencing factors of chemical composition and structural state.
This mathematic model provides basis for calculation of mechanical property parameters of micro-carbon steel rolled in ferrite region.