ABSTRACT
Chitosan (CS) aerogels are highly porous (â¼99 %), exhibit ultralow density, and are excellent sorbents for removing ionic pollutants and oils/organic solvents from water. Their abundant hydroxyl and amino groups facilitate the adsorption of ionic pollutants through electrostatic interaction, complexation and chelation mechanisms. Selection of suitable surface wettability is the way to separate oils/organic solvents from water. This review summarizes the most recent developments in improving the adsorption performance, mechanical strength and regeneration of CS aerogels. The structure of the paper follows the extraction of chitosan, preparation and sorption characteristics of CS aerogels for heavy metal ions, organic dyes, and oils/organic solvents, sequentially. A detailed analysis of the parameters that influence the adsorption/absorption performance of CS aerogels is carried out and their effective control for improving the performance is suggested. The analysis of research outcomes of the recently published data came up with some interesting facts that the unidirectional pore structure and characteristics of the functional group of the aerogel and pH of the adsorbate have led to the enhanced adsorption performance of the CS aerogel. Finally, the excerpts of the literature survey highlighting the difficulties and potential of CS aerogels for water remediation are proposed.
ABSTRACT
Modern automobiles have evolved from just being mechanical machines to having full-fledged electronics systems that enhance vehicle dynamics and driver experience. However, these complex hardware and software systems, if not properly designed, can experience failures that can compromise the safety of the vehicle, its occupants, and the surrounding environment. For example, a system to activate the brakes to avoid a collision saves lives when it functions properly, but could lead to tragic outcomes if the brakes were applied in a way that's inconsistent with the design. Broadly speaking, the analysis performed to minimize such risks falls into a systems engineering domain called Functional Safety. In this paper, we present SafetyLens, a visual data analysis tool to assist engineers and analysts in analyzing automotive Functional Safety datasets. SafetyLens combines techniques including network exploration and visual comparison to help analysts perform domain-specific tasks. This paper presents the design study with domain experts that resulted in the design guidelines, the tool, and user feedback.
ABSTRACT
Providing actionable insights through interactive visual analytics is essential to effective decision making. Yet, many complex systems engineering (SE) domains still lack such tools. Design reviews are often still based on static snapshots of data, without any dynamic interaction, data curation, and view creation capabilities to answer salient analysis questions. In this study, we report on a tool called DataHawk that helps answer common questions associated with one prominent SE context, namely failure mode and effect analysis (FMEA). The tool provides powerful exploration capabilities that enable system engineers, designers, and managers to probe FMEA data from multiple starting points, build questions dynamically, and find triangulated answers using multiple views rapidly. Field results are illustrated through a usage scenario from the automotive industry and show that the tool demonstrates the needed versatility, scalability, and effectiveness for real-world engineering data.
