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Therefore, proper points coordinates will minimize matrix condition number and , which will affect the inertia parameters test error directly.
The excitation and response points coordinates accuracy are found to be the main influence factors based on the error analysis using matrix condition number.
[2] R.A.B.Almeida, A.P.V.Urgueira and N.M.M.Maia, Identification of rigid body properties from vibration measurements, Journal of Sound and Vibration, 2007, 299, 884-899
Schedlinski, A survey of current inertia parameter identification methods, Mechanical Systems and Signal Processing, 2001, 15(1), 189-211
Response and excitation points selection for accurate rigid body inertia properties identification, Mechanical Systems and Signal Processing, 1999, 13(4), 571-592

Study on Thermal Conductivities of Composite Adsorbents for Adsorption Refrigeration Lin Yan1 , Gao Jiao1 The College of Mechanical and Electrical Engineering, QUST University, Qing dao266061 China Key words: adsorption refrigeration thermal conductivity curing density anisotropy Abstract.
For this, the development of an adsorbent with low regeneration temperature and high heat-transfer property has become one of the hot topics in the adsorption refrigeration field [1].
This indicates that curing density and quality, the two factors that affect the heat conductivity coefficient of Cacl2/ENG molding compound adsorbent, do not exist in isolation.
(3)The curing density and the mass ratio between calcium chloride and expanded graphite that affect the heat-conducting property of compound adsorbent are coupled with each other.
Experimental Study on Permeability and Heat-conducting Property of Compound Adsorbent [D].

The results show that the rheological properties of the resin significantly affect the composites’ formability.
The mechanical properties of these thermoplastics are listed in Table 2.
However, they don’t affect the quality of the wingtip.
The experiment results show that the rheological characteristics of thermoplastic resin, the size and its yarn orientation of the composite blank are very important factors in the thermoforming of the thermoplastic carbon woven fabric composites.
The rheological properties of thermoplastics, blank size and fiber orientation are very important to the thermoforming process.

Most of the shape memory polymer composites are made with polyurethane resin, which has poor mechanical properties.
Thus it is blend with epoxy resin (EP), because epoxy resin has got good mechanical properties.
The reinforcements impart their special mechanical and physical properties to enhance the matrix properties.Nano composites based on attapulgite clay and shape-memory polyurethane were fabricated by mechanical mixing.
Mechanical properties of attapulgite clay reinforced polyurethane shape-memory Nano composites shows with treated clay the properties are improved [2].
The shape memory properties of Epoxy and Polyurethane are preserved at the same time mechanical properties are improved as the reinforcement of nanoclay particles are restricted to 5%.

This idea emphasizes the urgent need for levodopa nanoparticles with sustained drug release properties in which this study first aims based on.
Formulation parameters such as concentration of stabilizer, the molecular weight of the polymer, the ratio of polymer/drug are the key factors to obtain the desired size, PDI, and EE.
The degradation rate of PLGA depends on many factors, including the composition (e.g. lactic/glycolic acid ratio), the molecular weight of the polymer.
The rate of degradation of PLGA depends on many factors including composition (eg lactic/glycolic acid ratio), the molecular weight of the polymer.
Different parameters were evaluated for modification of A8a, A2 formulas with optimum properties.

The performance of coating tools is determined by coating material, substrate material, coating method, coating thickness and other factors.
So, the bonding strength of coating and substrate directly affects tools’ life.
There are many factors affecting the bonding strength of coating and substrate, such as pretreatment condition on substrate surface, spray distance, arc voltage and current, etc[1,2].
Periodicity and amplitude are two factors which have three levels. 5 combinations are selected for next experiments.
Mechanical Research & Application. 44 (2010) 1-4

The products were analysed using the metallographic and CT analyses and the leak tightness was tested Introduction The design of the die casting mould and especially the placement and dimensioning of the tempering system is one of the most important factors affecting the final quality of the castings.
This system also does not provide the mould preheating, which adversely affects its service life.
After the first testing of system functionality the area affected by the unconventional cooling was found to be too small and two other expansion chamber were added to the core.
Pasko, Influence of technological factors of die casting on mechanical properties of castings from silumin, Lecture Notes in Electrical Engineering, 240 LNEE, (2013), pp. 713-722

The volumes of fct structures are one of reason to affect the damping capacity in M2052 alloy.
%Fe) alloy is one of developed Mn-Cu-based alloys recently, which show superior combination property [1].
While the mechanical behaviors of Mn-Cu alloys perform worse as the increasing Mn content.
Most researchers conclude that the damping capacity have a relationship of lattice distortion, which affects the properties of twinning structure [11].
The damping capacities originate from the irreversible slip of twinning boundaries, so the properties and quantities of twinning boundaries affect the damping capacity directly.

Introduction The product quality which satisfy and exceed even expect of customer is the key factor for enterprise to success in competitive market.
The method can identify the features of producing welded ball defect and determine the notable features of affecting product quality.
Sterjovski [6] proposed a back-propagation neural networks model to predict mechanical property of steel in all kinds of applications.
The purpose of ARMS is to obtain distributed process data from different process, transform data into knowledge in the form of association rules, and propose advices on the correct combination of process parameters for producing active affect on product quality improvement.
Artificial neural networks for modeling the mechanical properties of steels in various applications [J].

Instruction Many factors have impacts on PCD diamond tool wear, including the physical characteristics of the tool, the physical properties of the stone, and cutting parameters in the machining process.
The physical properties of the stone mainly refer to: stone hardness and fracture toughness, which has a great influence on the tool wear.
Generally speaking, the mechanical load on the diamond abrasive wear plays a major role when processing at low speed, however, in high-speed machining, impact wear does. 1).
The first stage of wear as the initial wear stage is broken and the overall fall off of the abrasive grains, the reason of which is the abrasive grains on the working surface of the tool after trimming is affected by the impact of the dressing tool and cracks.
Conclusion: Cutting parameters (tool speed, work-piece speed, depth of cut) that derived by single factor experiment have a greater impact on cutting ratio in the cutting process.