Some remarks on the inverse Smoluchowski problem for cluster-cluster aggregation

Abstract

It is proposed to revisit the inverse problem associated with Smoluchowski's coagulation equation. The objective is to reconstruct the functional form of the collision kernel from observations of the time evolution of the cluster size distribution. A regularised least squares method originally proposed by Wright and Ramkrishna (1992) based on the assumption of self-similarity is implemented and tested on numerical data generated for a range of different collision kernels. This method expands the collision kernel as a sum of orthogonal polynomials and works best when the kernel can be expressed exactly in terms of these polynomials. It is shown that plotting an "L-curve" can provide an a-priori understanding of the optimal value of the regularisation parameter and the reliability of the inversion procedure. For kernels which are not exactly expressible in terms of the orthogonal polynomials it is found empirically that the performance of the method can be enhanced by choosing a more complex regularisation function.

Nonlinear least-squares method for the inverse droplet coagulation problem

“…This curve satisfies Eq. (16). Given that Φ(z) is known, the corresponding inverse problem for κ(z 1 , z 2 ) is structurally almost identical to the stationary inverse problem which we have already discussed in Sec.IV.…”

“…These authors address the problem of ill-posedness using a procedure known as Tikhonov regularisation. In a previous note [16] we explored the ability of the method in [15] to solve the inverse problem for kernels of the form,…”