From this fit, first estimates are obtained for key material parameters, namely the interfacial term and the internal length, that are required for the theoretical formulation.
By using finite element FE) and Taguchi method, the effects and significance of five key material parameters, namely, anisotropic index in thickness direction, yield strength, hardening exponent, strengthening factor and elastic modulus on the formability of inner rib, tendency of wall fracture and degree of inhomogeneous deformation of finished spun parts were obtained.
With these understanding of interatomic potential in SiC, we have four material parameters, namely, modified ionic charge, hardness, range, force parameter [Z m, b, ρ, f(r)].
With these understanding of interatomic potential in SrX, we have four material parameters, namely, modified ionic charge; hardness, range, force parameter [Z m, b, ρ, f(r)].
The constitutive equations contain eleven material parameters, namely, E, ν, k, b, Q, C 1, a 1, C 2, a 2, Z and n.
The phase stability of cubic 3C SiC under high pressures is essentially based on material parameters namely hardness (b), range, non-central many body forces as charge transfer force (f cti) and covalency parameter (f cov).
The relationship between dislocation density and strain during uniform deformation was described by a dislocation model, and two critical materials parameters, namely dislocation mean free path and dynamic recovery coefficient, were determined as a function of temperature.
The scratch depth and shoulder height of the groove formed during scratch, which has been shown to be directly related to the scratch visibility resistance of polymers, is simulated by varying a set of material constitutive parameters, namely, yield stress, strain softening slope, strain hardening slope, strain at stress recovery, and strain before hardening.
In the case of a cubic material the latter relation fails to hold such that the material possesses three independent parameters, namely E, G, and ν need to be measured independently.
In this study, the adaptive neuro-fuzzy inference system (ANFIS) is designed and adapted to estimate the energy consumption of buildings according to the main building envelope parameters, namely material thickness and insulation K-value.
In order to obtain the chemical and structural information of iron-containing materials, three main hyperfine parameters, namely the isomer shift, quadrupole splitting and magnetic splitting, need to be investigated.
