Machine Learning for Fluid Mechanics

The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from field measurements, experiments and large-scale simulations at multiple spatiotemporal scales. Machine learning offers a wealth of techniques to extract information from data that could be translated into knowledge about the underlying fluid mechanics. Moreover, machine learning algorithms can augment domain knowledge and automate tasks related to flow control and optimization. This article presents an overview of past history, current developments, and emerging opportunities of machine learning for fluid mechanics. It outlines fundamental machine learning methodologies and discusses their uses for understanding, modeling, optimizing, and controlling fluid flows. The strengths and limitations of these methods are addressed from the perspective of scientific inquiry that considers data as an inherent part of modeling, experimentation, and simulation. Machine learning provides a powerful information processing framework that can enrich, and possibly even transform, current lines of fluid mechanics research and industrial applications.Comment: To appear in the Annual Reviews of Fluid Mechanics, 202

Investigation of dyeing based on pandanus amaryllifolius for superhydrophobic coating in cotton-polyester blended in textile application

Natural dyes are derived from natural resources. Colouring materials obtained from natural resources of plant, animal, mineral, and microbial origins were used for colouration of various textile materials. Use of natural dyes started fall after the invention of synthetic dyes in the second half of the nineteenth century. The synthetic dyes were rapidly industrialization of textile production resulted in almost complete replacement of natural dyes by synthetic dyes because their easy availability simple application process, better fastness properties and consistency of shades [1]. Recent environmental awareness has again revived interest in natural dyes mainly among environmentally conscious people. Natural pigments are considered eco-friendly as these are renewable and biodegradable which is skin friendly and provide healthier benefits to the wearer [2]. Pandanus amaryllifolius also called as pandan leaf is a tropical plant that under screw pine genus and it can be easily found all around in Malaysia. It is a genus monocotyledon plants with over 750 accepted species. Extraction of green pigments from pandanus amaryllifolius to produce an organic pigment for fabric dyeing can become an alternative of synthetic pigments. Organic pigments also can be classified as a biochrome substance which is produced by living organisms. These biological pigments include flower and plant pigments [3]