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Introduction There are many factors influencing the yarn hairiness of ring spinning [1-3] because ring spinning yarn production is a complex multi-step technological process, and the structure of yarns is complicated.
However, the fuzzy and complex relationships between these factors and yarn hairiness [4-5] are nonlinear so that it is necessary to find an accurate and effective approach to characterize the ring spinning yarn producing process in order to realize the yarn virtual producing.
Therefore, it can be well used to predict yarn properties quantitatively.Over the past decades, researchers [6-10] have established artificial neural network for modelling various textile nonlinear problems.
The ring spun yarn property under study is the yarn hairiness.
The momentum factor is 0.67.

Design Research on Working Mechanism of Beam Pumping Unit Jun Liu 1,a and Jiang Zhu 2,b 1 School of Mechanical Engineering, Huaihai Institute of Technology, Lianyungang, 222005, China 2 School of Mechanical and Electrical Engineering, Changzhou College of Information Technology, Changzhou, 213164, China a liujun600322@sina.com, b zhujxq@126.com Keywords: Beam pumping unit, Evolutionary solver, Design model Abstract.
In design optimization on the beam pumping unit, the defined design objective is the most important factor, as it not only influence design scheme quality, also can affect the design course.
Instead, a penalty factor was applied to each design if the constraints were violated.
The fitness function is： ，where R—penalty factor，R=25000.
Wei: Mechanical Research and Application, (2008), pp. 159-162

Introduction Magnesium and its alloys have excellent physical and mechanical properties for a number of applications [1,2].
It generally applies that the silicides of metals and non-metals have outstanding anticorrosion properties.
The present paper addresses the question of research in the preparation of silicon layers by the WSP-H 500© plasma spraying system, the effect of such parameters like a feeding distance (FD), the structure of layers and the measurement of the layers properties by electrochemical impedance spectroscopy.
The feeding distance affects the pre-heating temperature of silicon powder and the improvement of adhesive properties of silicon plasma coatings.
The interpretation of the measurement results from the electrochemical impedance spectroscopy is difficult for plasma coatings and there are plenty of factors affecting the result.

In particular the distributed reinforcement, consisting of silicon carbide (SiC) or aluminum oxide (Al2O3), evokes especially high mechanical loads.
In case of ‘smeared modeling’ the composite is described as homogeneous material with averaged mechanical and thermal properties.
Results and Discussion In general during cutting large stresses and high temperatures occur, which cause interesting effects when machining MMC-materials because of different thermo-physical properties of the participating material ingredients.
Thereby, a precise prognosis of the stresses, deformations, temperatures and the resulting forces to the tools affecting the process areas can be executed, so the influence of different process parameters and geometric values on the resulting specific forces has been examined and discussed.
O´Reilly: Factors affecting the machinability of an Al/SiC metal-matrix composite, in: Journal of Materials Processing Technology, Vol. 43 (1994), pp. 21-36 [2] P.

Ontology technology can be used to express various parameters factors that affect tree growth management, and develop resource domain ontology standardization of tree growth management.
The content of resource information of tree growth management are many, which includes the selection, optimization of operating measures and technology, and the decision-making of efficiency, they are decided by factors such as long cycle of tree growth and resource management, complex influencing factors and diverse business objectives, the economic benefits of tree growth management decisions has been the major object of tree growth, and it has a broad research base from the perspective of theory and practice.
The ontology of tree growth resource management decision-making consists of concepts, properties, axioms and instances.
Resource information engine needs the support of the resource information database, the exiting knowledge ontology of agricultural science and technology literature are used to construct the tree growth management resource ontology, the decision-making ontology based on the waterfall model which is built by ontology, then establish standardized tree growth management resources knowledge conceptual system, determine the various logical relationship between the concept and provide prerequisites for the properties for tree growth management organizations as well as the construction of growth model of the resource information of tree.
The growth simulation of tree mainly performs qualitative observations of different growth conditions and stages, then judges the growth mode, determines the overall framework of the morphology of description, measures the tree topology, geometry, mechanical properties, extracts the tree morphology rules model based on the growth rules, and simulate trees growth, finally establishes tree growth model based on a variety of competitive factors.

It’s the key point to determine the parts layer and parameters layer, and affected by their feedback at the same time, in this way to further improve their structure.
Parameter layer: Describing the final overall properties of the design process model of the product, its main modeling objects are the parameters which can reflect the performance of the product’s process model.
P={pt1,pt2,pt3,pt4,pt5,pt6……} represent the sets of each components included in the component level Pt={aa1,aa2,aa3,aa4,aa5,aa6……} represent the sets of the properties of each part.
(In Chinese) [4] DARLINGTON MJ，CULLEY SJ．A Model of Factors Influencing the Design Requirement[J]．Design Studies，2004，25(4): 329-350
Conceptual design of mechanical system[M].

Adding Nano SiO2 into it can improve the frost resistance of EPS lightweight concrete, so that it can improve the microstructure and mechanical properties of concrete.
Comparing with micron of SiO2 materials, the special structure of Nano SiO2 exhibits the unique properties: good dispersibility, with large specific surface area, excellent optical performance and chemical stability.
Nano SiO2 not only can fill the gap of cement and improve the fluidity of concrete, but also can improve the interface structure of water debris and aggregate in concrete, so that it can improve the concrete strength, impermeability and durability[3] .Hardened concrete’s main properties are with sufficient strength and durability.
The experiment EPS lightweight concrete durability of the external force factors are complex,which is one of the common freeze-thaw cycle effects fresh water and salt erosion.
The stand or fall of EPS lightweight concrete frost resistance to a certain extent affect the quality of freeze-thaw cycle, experimental research of nano SiO2 of EPS lightweight concrete frost resistance.

Based on the properties of the orthogonal polynomials, a Fourier neural network can be established, which is a feed-forward network consisting of three layers, that is, input layer, single hidden layer and output layer, as shown in Fig. 1.
The reliability probabilistic constraints are imposed in order to take into account various random parameters which affect the reliability of the structure.
When the reliability index is calculated, the variables which affect the reliability of the structure are considered as the inputs of the neural network, and the performance function is taken as the outputs of the network, thus the neural network can be established.
Table 2 Optimum results for the five-bar truss compared with RBDO method Proposed method RBDO method Cross-sections at the optimum (mm2) A1 613.473 613.499 A2 200 200 A3 613.473 613.499 A4 200 200 A5 200 200 -value at the optimum 3.0000 3.000 Cost function value (mm3) 1.9926×106 1.9927×106 Conclusions The deterministic optimum cannot be considered as a realistic optimum design since the random factors affect the structures.
Marti: Reliability-based design optimization for elastoplastic mechanical structures.

Carbon black content is the key factor to affect the synthesis of MgO-SiC composite powders.
Introduction MgO-C refractory with excellent slag corrosion and penetration resistance and good thermal shock properties is widely used in steel making application.
Carbon was added to the refractories to enhance their non-wetting properties.
MgO-SiC-C refractory composite has good mechanical properties and thermal shock resistance [9], so it can be used as the substitute of MgO-C refractories.

Wahab Mechanical Engineering, department, Higher institute of General professions – Alkhums, Libya ammo20062010@yahoo.com, elhupbashir@yahoo.com, abas@uthm.edu.my Keywords: rifled tube, smooth tube Abstract.
During the experiment, it was found that at 360 mins for the smooth tube, an increase in flow rate does not affect the time for the fluid (water) to attain a temperature of 33oC.
Thermal-hydraulic analysis is a key factor for the successful design and operation of water walls.
From the cited reasons and analysis, it can be found that the rifled tube has greatly enhanced properties in achieving greater and better aim than the smooth tube.
Describing uncertainties on single – sample experiments, Mechanical engineering, 57 (1953) 3 – 8