Electrospinning: a fascinating fiber fabrication technique.

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Heat transfer characteristics of nanofluids: a review

Nanofluids are potential heat transfer fluids with enhanced thermophysical properties and heat transfer performance can be applied in many devices for better performances (i.e. energy, heat transfer and other performances). In this paper, a comprehensive literature on the applications and challenges of nanofluids have been compiled and reviewed. Latest up to date literatures on the applications and challenges in terms of PhD and Master thesis, journal articles, conference proceedings, reports and web materials have been reviewed and reported. Recent researches have indicated that substitution of conventional coolants by nanofluids appears promising. Specific application of nanofluids in engine cooling, solar water heating, cooling of electronics, cooling of transformer oil, improving diesel generator efficiency, cooling of heat exchanging devices, improving heat transfer efficiency of chillers, domestic refrigerator-freezers, cooling in machining, in nuclear reactor and defense and space have been reviewed and presented. Authors also critically analyzed some of the applications and identified research gaps for further research. Moreover, challenges and future directions of applications of nanofluids have been reviewed and presented in this paper. Based on results available in the literatures, it has been found nanofluids have a much higher and strongly temperature-dependent thermal conductivity at very low particle concentrations than conventional fluids. This can be considered as one of the key parameters for enhanced performances for many of the applications of nanofluids. Because of its superior thermal performances, latest up to date literatures on this property have been summarized and presented in this paper as well. However, few barriers and challenges that have been identified in this review must be addressed carefully before it can be fully implemented in the industrial applications.

/pdf/a-review-on-applications-and-challenges-of-nanofluids-ibdekzmmqr.pdf

A review on applications and challenges of nanofluids

Suspended nanoparticles in conventional fluids, called nanofluids, have been the subject of intensive study worldwide since pioneering researchers recently discovered the anomalous thermal behavior of these fluids. The enhanced thermal conductivity of these fluids with small-particle concentration was surprising and could not be explained by existing theories. Micrometer-sized particle-fluid suspensions exhibit no such dramatic enhancement. This difference has led to studies of other modes of heat transfer and efforts to develop a comprehensive theory. This article presents an exhaustive review of these studies and suggests a direction for future developments. The review and suggestions could be useful because the literature in this area is spread over a wide range of disciplines, including heat transfer, material science, physics, chemical engineering and synthetic chemistry.

https://www.tandfonline.com/doi/pdf/10.1080/01457630600904593

Heat Transfer in Nanofluids—A Review

Investigation on characteristics of thermal conductivity enhancement of nanofluids

Development of high efficiency nanofilters made of nanofibers

The main objective of the research reported herein has been to develop an approach to analyze and quantify the spatial and temporal patterns of meteorological droughts based on annual precipitation data. By using a nonparametric spatial analysis neural network algorithm, the normalized and standardized precipitation data are classified into certain degrees of drought severity (for example, extreme drought, severe drought, mild drought, and nondrought) based on a number of truncation levels corresponding to specified quantiles of the standard normal distribution (the 15%, 35%, and 50% quantiles were used here for illustration). Then posterior probabilities of drought severity at any given point in the region are determined and the point is assigned a Bayesian Drought Severity Index depending on whether the maximum posterior probabilities correspond to extreme, severe, mild, or nondrought. This index may be useful for constructing drought severity maps that display the spatial variability of drought severity for the whole region on a yearly basis. Furthermore, the severity of the drought event for the region as a whole and the sequence and duration of drought episodes through time can be determined. The proposed regional drought analysis approach was applied to analyze and quantify regional droughts for the southwestern region of Colorado. The results were useful for deriving maps of precipitation fields for the entire region, maps of posterior probability of drought severity, and maps of drought severity indices. They were useful for visualizing the spatial pattern of droughts and for deriving other drought properties such as duration. The results obtained suggest that the proposed approach is a viable tool for analyzing and synthesizing droughts on a regional basis.

Regional Drought Analysis Based on Neural Networks

Significant advances have been made in understanding the importance of the factors involved in reservoir sedimentation. However, predicting the accumulation of sediment in a reservoir is still a complex problem. In estimating reservoir sedimentation and accumulation, a number of uncertainties arise. These are related to quantity of streamflow, sediment load, sediment particle size, and specific weight, trap efficiency, and reservoir operation. In this study, Monte Carlo simulation and Latin hypercube sampling are used to quantify the uncertainty of annual reservoir sedimentation and accumulated reservoir sedimentation through time. In addition, sensitivity analysis was performed to examine the importance of various factors on the uncertainty of annual reservoir sedimentation. The proposed procedures have been applied to the Kenny Reservoir at the White River Basin in Colorado. The uncertainty of annual reservoir sedimentation and the effect of each uncertain factor, taken individually and in combinations,...

Hyun-Suk Shin

Papers

Investigation on characteristics of thermal conductivity enhancement of nanofluids

Development of high efficiency nanofilters made of nanofibers

Regional Drought Analysis Based on Neural Networks

Uncertainty analysis of reservoir sedimentation

Predicting Streamflows Based on Neural Networks