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Wang 1,e 1College of Mechanical and Electrical Engineering , Nanjing University of Aeronautics and Astronautics , Nanjing 210016, China 2 Beijing Institute of Aeronautics Materials, Beijing 100095, China a meemhchen@nuaa.edu.cn, bmeelgao@nuaa.edu.cn, czhishouzhu@biam.ac.cn, d meedwzuo@nuaa.edu.cn, emeemwang@nuaa.edu.cn Keywords: Fuzzy neural network, Calescent superplastic bulge forming, Titanium alloy, Optimization Abstract.
Among superplastic materials, titanium alloys such as Ti-6Al-4V (TC4) have found wide applications in the aerospace industry because of their superior properties such as a high strength-to-weight ratio, high temperature tolerance and excellent corrosion resistance [2].
Because of the characteristic of SPF process, the thickness distribution of final product becomes non-uniform and the influence of final thickness distribution in SPF processes on mechanical properties of the product becomes very critical as the geometry of the product becomes more complicated.
Experimental Method and Procedure It is desirable to design the process to improve the final thickness distribution to become more uniform and to raise productivity in the CSPBF, which is well understood that the final thickness distribution are strongly influenced by its technological parameters like the SPF starting temperature, strain rate, loading method, friction-factor and so on, and productivity mainly is affected by forming time.
In which, the β is friction-factor.

Thus, the introduction of a certain amount of highly reactive highly dispersed carbon additives into the composition of the CWS to intensify the formation of stable spatial structures will provide the desired properties of the VEG. with a size <250 µm, fine particles <50 µm are also present.
The consumer properties of the starting materials were determined by the phase composition, physicochemical and physicomechanical properties, as well as compliance with the technical conditions of the subsequent processes of redistribution of the obtained products.
The hydrodynamic properties of polyelectrolytes are largely determined by the intramolecular and intermolecular electrostatic interaction of charged sections of the chain, which leads to the formation of expanded conformations.
The efficiency of vibro-impact on the surface properties of the solid phase of CWS is determined primarily by the characteristics of coal (ash content, mineral composition, degree of surface oxidation, stage of metamorphism), as well as the conditions of the system (temperature, water composition, etc.).
Immediately after switching on the unit under the action of combined plasma torch factors (t, min, generation of active radicals, electrode processes), the conversion of the organic component of wastewater begins with the formation of carbon microparticles.

Introduction The machining of composites is governed by different factors such as fiber and matrix properties, fiber orientation and fiber volume fraction.
However, most techniques are hindered by challenges such as delamination, large burr formation, dimensional inaccuracy due to heat affected zone.
Abrasive water jet (AWJ) is a non-traditional machining method that can overcome above disadvantages, since it is a cold working process and does not induce any heat affected defects in the composites [2].
The main input parameters that govern these outputs are jet pressure, water flow rate, mixing tube geometry, abrasive flow rate, abrasive particle properties, standoff distance, and traverse speed.
Cutting Parameter Selection Standoff distance, traverse speed jet pressure, water flow rate, mixing tube geometry, abrasive flow rate and abrasive particle properties are certain parameters plays vital role to achieve high quality and productivity.

The cutting temperature is a key factor which directly affects cutting tool wear, workpiece surface integrity, main cutting force and machining precision according to the relative motion between the tool and workpiece during metal cutting.
RSM is a dynamic and foremost important tool of design of experiment (DOE), wherein the relationship between responses of a process with its input decision variable is mapped to achieve the objective of maximization or minimization of the response properties [5,6,7].
The Grey Relation Coefficients provide the relationship between the process and the factors considered for the optimization problem [8-9].
In their study, cutting speed, feed rate and depth of cut were the primary factors investigated.
Güney, Investigation of cutting parameters affecting on tool wear and surface roughness in dry turning of Ti-6Al-4V using CVD and PVD coated tools, J Braz Soc Mech Sci Eng, (2016), pp1-9

These interlayer defects degrade mechanical properties and structural integrity, potentially causing crack propagation under load and jeopardizing aircraft safety [3].
Due to the physical properties of the material, the elastic stiffness matrixis a symmetric matrix, that is,.
Material parameters, including CFRP anisotropy and fluid acoustic properties, were precisely defined [21].
Considering the coupling effects of multiple influencing factors, the distribution range of API-based defect characterization is significantly reduced.
Fujii, "An Optical Method for Evaluating the Mechanical Properties of Wires Under Impact Tensile Load," in IEEE Transactions on Instrumentation and Measurement, 73 (2024) 1-11, doi: 10.1109/TIM.2023.3332347

It is observed that at large tool edge radii the influence of the ploughing effect become more significant factor on the chip morphology.
The material constants for the Johnson-Cook constitutive equation for AISI 4340 steel and the temperature dependent mechanical and physical material properties are given in [11].
The workpiece geometry, mesh, material properties and boundary conditions are kept the same as the model in [11].
As investigated in [12], the run-out affects the stability lobes obtained for edge radius of 3.5 μm and needs to be considered in the real cases.
Mativenga: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture Vol. 223 (2009), p.337 [5] A.

As a consequence, free volume increases and glass transition temperature decreases which significantly affects their mechanical properties [64, 65].
McCarthy, Factors influencing the physicochemical, morphological, thermal and rheological properties of some chemically modified starches for food applications-A review, Food Hydrocolloids 21 (2007) 1-22
Cuq, Water and glycerol as plasticizers affect the mechanical and water vapour barrier properties of an edible wheat gluten film, J.
Noomhorm, Effect of Plasticizers on Mechanical and Barrier Properties of Rice Starch film, Starch 56(8) (2004) 348-356
Structure, mechanical and barrier properties of amylose and amylopectin films, Carbohydr.

A multivariate analysis investigating different factors important for the interaction between liposomes and pectin, Colloids Surf.
Berry pectins: Microwave-assisted extraction and rheological properties, Food Bioprocess Technol., 5(3) (2012) 1100–1105
H Liang., et al., Extraction of pectin from Premna microphylla turcz leaves and its physicochemical properties, Carbohydr.
[15] P Di Pierro, Marquez, G Rossi, et al., Effect of transglutaminase on the mechanical and barrier properties of whey protein/pectin films prepared at complexation pH, J.
Influence of intrinsic and extrinsic factors on rheology of pectin–calcium gels, Food Hydrocolloids, 23(8), 2069–2077

The results show lighweight steel frame have good aseismatic property and good energy dissipation at node domain.
Table 1 Light steel frame specimens list structural form span(mm) floor height (mm) beam sectional dimension (mm) column sectional dimension (mm) two-bay two-story 2000 1500 175Í125Í3Í6 200Í140Í3Í6 According to (the People's Republic of China Standard GB228-87) making plate specimens, the specimens material average properties in table 2.
The dynamic properties of specimens mainly show in the steel plate shear hysteretic performance under the effect of axial load.
Skeleton curve can reflect the yield of load and displacement, limit load and displacement feature points of element, at the same time can reflect structure or element’s absorb energy consumption and ductility ，strength and stiffness, degradation and other mechanical characteristics, under positive and negative alternating load affect.
Displacement ductility factor is a index that Evaluation components or the performance of structure ductility, It reflects the node ductility performance.

Introduction Lead dioxides have been used frequently in industry because of their excellent properties such as good conductivity, low cost, high stability and relatively high service life [1].
Coating bath and processing conditions The composition and processing conditions of PbO2 coating bath were demonstrated as follows [6]: litharge PbO was added into 4 mol/L NaOH solution till saturation, anodic current density of 0.5 ~ 2 A/dm2, temperature 20~50℃, electroplating time 1 ~ 4 h, CeO2 0 ~ 20 g/L , Co3O4 0 ~ 40 g/L and coating solution was mixed by mechanical stirrer.
Taken various factors into consideration, the current density should be controlled in 1.5A/dm2.
Its deposition mechanism is similar to the Co3O4 mechanism, and which is affected by particles diffusion in the coating solution and collision of the anode.However, the inert particles of CeO2 are not affected by electric field in electroplating solution, so that it is less easily to deposit on the anode than that of Co3O4 which has good conductivity.
Table 5 Effect of electroplating time on composition and performance of composite coating Time h Binding force deposition rate g/h·dm2 Appearance  morphology w(CeO2) % w(Co3O4) % 1 worse 1.54 rough loose 3.56 4.79 2 fine 3.97 smooth dense 4.64 5.43 3 fine 5.25 smooth dense 4.87 5.87 4 shedding 4.74 rough loose 3.02 4.59 SEM Through the study of effects of various factors on the coating performance, optimum conditions are selected to prepare α-PbO2 coating, α-PbO2-5.44wt%Co3O4 coating, α-PbO2-4.63wt%CeO2 coating and α-PbO2-5.43wt%Co3O4-4.64wt%CeO2 coating.