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Rungnapa Kaewthongrach

Researcher at King Mongkut's University of Technology Thonburi

Publications -  7
Citations -  31

Rungnapa Kaewthongrach is an academic researcher from King Mongkut's University of Technology Thonburi. The author has contributed to research in topics: Phenology & Dry season. The author has an hindex of 2, co-authored 3 publications receiving 5 citations.

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Journal ArticleDOI

Importance of exponentially falling variability in heat generation on chemically reactive von kármán nanofluid flows subjected to a radial magnetic field and controlled locally by zero mass flux and convective heating conditions: A differential quadrature analysis

TL;DR: In this article , a comprehensive examination aimed to explore the important features of spinning flows of chemically reactive Newtonian nanofluids over a uniformly revolving disk in the presence of a radially applied magnetic field along with an exponentially decaying space-dependent heat source, in the case where the disk surface is heated convectively and unaffected by the vertical nanoparticles' mass flux.
Journal ArticleDOI

Impact of Severe Drought during the Strong 2015/2016 El Nino on the Phenology and Survival of Secondary Dry Dipterocarp Species in Western Thailand

TL;DR: The results highlight that dieback and mortality during El Nino were increased by 45 and 50%, respectively, compared to non-El Nino events, pointing at the importance of such events to shape DDF ecosystems.

Carbon and Water Cycling in Two Rubber Plantations and a Natural Forest in Mainland Southeast Asia

TL;DR: In this paper , the authors compared eddy-covariance measurements of carbon and water fluxes from two rubber monoculture plantations (at a northern marginal site and a southern traditional plantation site) with a second-growth natural forests (NFs) between 2015 and 2018, and their responses to a prolonged drought during 2015/2016.
Proceedings ArticleDOI

Clustering of Leaf Characteristics in Secondary Dry Dipterocarp Forest based on Particle Swarm Optimization

TL;DR: In this article, the authors applied particle swarm optimization (PSO) to cluster the leaf characteristic patterns in secondary dry dipterocarp forest, and the results showed the main patterns of leaf characteristics in the forest can be extracted by PSO.