An order verification method for truncated asymptotic expansion solutions to initial value problems

Mungkasi, Sudi

doi:10.1016/j.aej.2021.04.068

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…With the success of our strategies involved in the proposed model and method, we believe that these results could be extended further in other fluid mechanics and heat transfer areas as well as initial-boundary value problems. One could implement our strategies to various problems (to mention some of them, see Alawi and Kamar [19], Bindu et al, [20], Ewis [21], Ferdows et al, [22], Ghani and Jami [23], Giap and Kosuke [24], Jamil et al, [25], Mohamed et al, [26], Sahak et al, [27] and the work of Mungkasi [28,29] as well as Mungkasi and Roberts [30]). Each of these problems could be explored and solved in their own rights.…”

Section: Results and Discussion For The Proposed Modelmentioning

confidence: 99%

Modelling And Simulation of Topical Drug Diffusion in The Dermal Layer of Human Body

Mungkasi

2021

ARFMTS

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We consider the problem of drug diffusion in the dermal layer of human body. Two existing mathematical models of the drug diffusion problem are recalled. We obtain that the existing models lead to inconsistent equations for the steady state condition. We also obtain that solutions to the existing models are unrealistic for some cases of the unsteady state condition, because negative drug concentrations occur due to the inappropriate assumption of the model. Therefore, in this paper, we propose a modified mathematical model, so that the model is consistent, and the solution is nonnegative for both steady and unsteady state conditions of the drug diffusion problem in the dermal layer of human body. For the steady state condition, the exact solution to the proposed model is given. For unsteady state condition, we use a finite difference method for solving the models numerically, where the discretisation is centred in space and forward in time. Simulation results confirm that our proposed model and method preserve the non-negativity of the solution to the problem, so the solution is more realistic than that of the old model.

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Section: Results and Discussion For The Proposed Modelmentioning

confidence: 99%

Modelling And Simulation of Topical Drug Diffusion in The Dermal Layer of Human Body

Mungkasi

2021

ARFMTS

View full text Add to dashboard Cite

show abstract

An order verification method for truncated asymptotic expansion solutions to initial value problems

Cited by 1 publication

References 23 publications

Modelling And Simulation of Topical Drug Diffusion in The Dermal Layer of Human Body

Modelling And Simulation of Topical Drug Diffusion in The Dermal Layer of Human Body

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