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An asphalt modified by epoxy resin and rubber has the following improved properties: the softening point is 70, elastic recovery rate is 80%, and kinematic viscosity at 175 is 2879.1mm2 /s.
The components are all good asphalt modifier, which can improve the asphalt properties at high and low temperatures, anti-aging performance, prolong the pavement life, and reduce the road noise.
Taking the construction factors into account, 20% curing agent content is suitable, that is, the epoxy resin began to curing after cooled one hour.
Rutting is the main diseases of asphalt pavements because it reduce pavements’ service life, and seriously affect the traffic safety.
Taking the construction factor into account, 20%-25% curing agent content is suitable.

The material properties are summarized in Table 2.
Table 2 - Mechanical properties of implant models components Composant Material Properties Young’s modulus (GPa) Poisson’s ratio Tensile stress (MPa) Strenght stress (MPa) Ref.
Mechanical properties of cancellous bone in the human mandibular condyle are anisotropic.
Mechanical loading of Brånemark implants affects interfacial bone modeling and remodeling.
A comparative analysis based on different strength criteria for evaluation of risk factor for dental implants.

Practical aspects of the technique and some properties of the composites are discussed.
For instance, metals can be considered "nano" already when the grain size decreases down to a fraction of a micrometer where their mechanical properties show distinct size dependence.
The low limit is determined by the properties of the solid pressure medium, which becomes plastic only well above 1 GPa.
In this way one can modify the phase composition and structure of the grain boundaries getting materials with novel properties.
Perspective applications of such materials are related to their mechanical, electrical, optical and magnetic properties, in particular those which show a dependence on the size of grains in the nano-range.

The basic strategy of this model is driving design induction chain is the center of the core entity or the host factory, cloudy domain resource access based on the expression of different views and mapping of product design can spread out quickly own information and resource demand, When the cloud environment product is observed and analyzed in their point of view, the structure is more objective, more precisely, the circulation of information is more convenient, interactive resources is more symmetrical, decision-making errors and unstable factors is relatively reduced, design risk is greatly reduced.
T_role describes role set involved in task, T_property describes attribute set of the task, T_resource describes resources set executing the task.
S_property describes the state set in their current attribute, S_condition is constraint condition set when the state occurs migration
Mapping decomposition is operation that one demand is decomposed into several sub one which decomposes mapping with function RC_decompose(R_CloudID,｛ID,P_id｝), its mapping features is as follows: The parameter R_CloudID is the cloud property identification decomposing demand, ID is demand identification, P_id is signature decomposing demand, after the demand is decomposed sub-demand inherit cloud properties of father-demand, the return value is the list signature of sub-demand｛P_id1,P_id2,P_id3,…,P_idn｝. ②Aggregation mapping is the mapping operation that aggregates two or more demand into a new demand which is described with function RC_aggregate (R_CloudID, {ID1, ID2, ID3,..., IDn}), its mapping features is as follows: The parameter R_CloudID is cloud properties, IDX is identification of aggregated demand, feature ReqProp of new demand of RC_aggregate produced by the polymerization inherits all the features in RC polymerization, and can combine these features into a new feature of its
The parameter is ID of RC, the return value is ID of RC_instance. 3 Serialization integration of discrete design resources Demand mapping solution not only have levels of granularity because the particle size of information itself is different, but also have complex, dynamic, decentralized and uncertain characteristics because the scene and the environment of cloud properties are different.

Further research is needed to fully comprehend how important process parameters affect surface roughness.
One of its key strengths lies in its ability to prevent thermal distortion, thanks to the cooling properties of water as a technological agent.
Materials exhibit varying machinability characteristics owing to their distinct mechanical and chemical properties.
· Process parameters significantly impact AWJC quality, with various factors influencing the precision of the cuts
· Materials AWJ machinability varies due to mechanical and chemical properties, and AWJC technology offers a versatile solution for cutting challenging materials

Introduction Commonly, a Yoke flange is manufactured by a hot forging process because the advantages of this process are superior product strength, high production rate, excellent mechanical property and low cost.
The known parameters were the parameters determined directly from the real process, such as the die geometry, material properties, and cycle time of the process, while the unknown parameters were the parameters those cannot be measured directly from the process, such as the heat transfer coefficient and friction value.
The heat transfer coefficient would affect the temperature distributions, the forming load and the metal flow [3].
The frictional shear assumptions between the billet and tools were used with the friction shear factor (m).
Therefore, the friction shear factor value of m = 0.3 could be assumed [5].

Mixture D-Optimal Design of Electrolyte Composition in ECH of Bevel Gears J P Misraa#, P K Jainb, D K Dwivedic and N K Mehtad Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India ajoyprakash.misra@gmail.com, bpjainfme@iitr.ernet.in, cdkd04fme@iitr.ernet.in, mehtafme@iitr.ernet.in # Corresponding Author Keywords: Gear Finishing, ECH, Electrolyte, Bearing Ratio, Mixture D-Optimal Design.
The machining chamber is made of perspex for its corrosion resistance property and to obtain a better visibility of the operation.
In short, in mixture design, the level of one factor affects the level of another factor and thus, it differs from Taguchi’s technique or response surface methodology. 2.
In mixture D-Optimal design, the design space is defined by the low and high level constraints on each factor and any multifactor constraints [9-10].
[6] Davis JR (2005) Gear Materials, Properties, and Manufacture.

At the first phase of the DARE2C project, new low-CO2 cement recipes have been developed with good mechanical properties and compatibility of several aluminium alloy candidates.
The factors affecting the cohesion vary from the chemical interaction between two materials, strength class of concrete, and the structural design such as the cover layer thickness, and so on [7].
Tensile testing was conducted to evaluate the properties of the aluminium alloys after heat treatment with an MTS 810 tensile machine with a laser extensometer. 2 mm / min loading rate was used.
The tensile curve of the heat-treated aluminium is shown in Figure 5 and the tensile properties are given in Table 3.
The tensile properties of the aluminium rebars   Al-9Si-2Cu (T6) Al-9Si-0.3Mg (T6) AA6082 (T6) AA5052 (as extruded) fo [MPa] 273 225 218 52 fu [MPa] 390 294 257 179 E [MPa] 60790 89812 56838 77526 Failure strain (at UTS point) 0.103 0.078 0.065 0.210 Pull-out tests.

At present, the research on superalloys mainly focuses on the correlation between their mechanical properties and microstructure and properties, and there are few studies on the forming properties of superalloys, and there is no systematic study on the spinning properties of superalloys based on actual parts, therefore, this paper focuses on the spinning forming performance of GH3044, GH3625, GH3536 and GH4169 superalloy materials, and the detailed basic research on the high-temperature alloy powerful spinning forming process have been studied in this paper.
This parameter is usually a key parameter that affects the spinning process.
However, due to factors such as the material's circumferential flow and springback, the high-temperature alloy workpiece cannot be completely attached to the mold under various process parameters, that is, there is a certain amount of diameter expansion.
The corrugation of the outer surface of the GH4169 alloy workpiece is affected by this process, and is related to the heating method, the feed speed of the rotary wheel, the corner radius of the rotary wheel, and the machine tool system.

The model derivation is presented as well as its basic properties.
That means that the combination doesn’t affect the material.
In this paper we are proposing a new damage accumulation model that can be formulated with the use of the formula presented in the form: , (9) where: i - given load cycle, m'– amount of information being memorized, , (10) where: λ’ – the level of permanent memory, φ – power exponent, b – forgetting factor, t – time, d – the inverse ratio of the forgetting factor 1/b.
Fatemi, Cumulative fatigue damage assessment and life predictions of as-forged vs QT V-based MA steels using two-step loading experiments, Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, vol. 217 no. 2, 2003, pp. 145-155