Estimating the absorptivity in laser processing by inverse methodology

A three-dimensional finite element analysis of the temperature field during laser melting of metal powders in additive layer manufacturing

“…[12][13][14]. The absorptance of metal powders is known to vary between the in-coupling absorptance as proposed by Kruth et al [14] to a few percent when the metal melts [10].…”

Identification of the heat source and thermal material model parameters for the laser engineered net shaping

“…The laser absorption coefficient is an important parameter in AM modelling. Due to the material of the powder and type of the absorption parameter (e.g., substrate, flat surface, spheres, and substrate), its values may vary even from 0.01 to 1 (Chen et al, 2007). In the current work, Inconel 718 was used.…”

Inverse estimation for unknown fouling geometry on inner wall of forced-convection pipe

“…However, the observed temperature data contains measurement errors; as a result, the inverse solution will tend to approach the perturbed input data, and the solution will exhibit an oscillatory behavior as the number of iteration increases [19] . Computational experience has shown that it is advisable to use the discrepancy principle [14] for terminating the iteration process in the CGM. Assume that T s2 (x i , r m ) − Y (x i , r m ) ∼ = σ, the stopping criterion η by the discrepancy principle can be obtained from Eq.…”

“…This technique can be used in a warning system to call for pipe maintenance when the thickness of fouling exceeds a predefined criterion. In this article, we present the conjugate gradient method (CGM) [11][12][13][14][15] and the discrepancy principle [16] solving the inverse geometry problem to determine the fouling layer configuration in the pipe system. The CGM with an adjoint equation, also called Alifanov's iterative regularization method, belongs to a class of iterative regularization techniques, which means that the regularization procedure is performed during the iterative processes.…”