scispace - formally typeset
K

Kevin J. Maki

Researcher at University of Michigan

Publications -  95
Citations -  1321

Kevin J. Maki is an academic researcher from University of Michigan. The author has contributed to research in topics: Computational fluid dynamics & Computer science. The author has an hindex of 16, co-authored 83 publications receiving 882 citations.

Papers
More filters
Journal ArticleDOI

Disease transmission through expiratory aerosols on an urban bus

TL;DR: In this article, a combined experimental and numerical analysis was performed to identify transmission mechanisms on an urban bus and assess strategies to reduce risk of SARS-CoV-2 transmission.
Journal ArticleDOI

Hydroelastic analysis of bodies that enter and exit water

TL;DR: In this paper, the entry and exit of flexible bodies through an air-water interface is studied using a tightly coupled fluid-structure interaction solver, where the fluid domain is modeled using finite-volume CFD and the flexible structure is represented by a modal basis.
Journal ArticleDOI

System design of a wind turbine using a multi-level optimization approach

TL;DR: In this paper, a multi-level system design (MLS) algorithm is presented and utilized for a wind turbine system analysis, which guides the decision making process for designing a complex system where many alternatives and many mutually competing objectives and disciplines need to be considered and evaluated.
Journal ArticleDOI

Hydroelastic impact of a wedge-shaped body

TL;DR: In this paper, the impact of an elastic wedge-shaped body on a calm free-surface is modeled using a wet modal model, which is then transferred to a rigid-body model to predict the stress field on the fluid-structure interface.
Journal ArticleDOI

An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM

TL;DR: An optimization framework that consists of an efficient discrete adjoint implementation for computing derivatives and a Python interface to multiple numerical optimization packages is developed and validated, demonstrating that the developed techniques have the potential to be a useful tool in a wide range of engineering design applications.