Computational studies of some fuzzy mathematical problems

In modelling and optimizing real world systems and processes, one usually ends up with a linear or nonlinear programming problem, namely maximizing one or more objective functions subject to a set of constraint equations or inequalities. For many cases, the constraints do not need to be satisfied exactly, and the coefficients involved in the model are imprecise in nature and have to be described by fuzzy numbers to reflect the real world nature. The resulting mathematical programming problem is referred to as a fuzzy mathematical programming problem.Over the past decades, a great deal of work has been conducted to study fuzzy mathematical programming problems and a large volume of results have been obtained. However, many issues have not been resolved. This research is thus undertaken to study two types of fuzzy mathematical programming problems. The first type of problems is fuzzy linear programming in which the objective function contains fuzzy numbers. To solve this type of problems, we firstly introduce the concept of fuzzy max order and non-dominated optimal solution to fuzzy mathematical programming problems within the framework of fuzzy mathematics. Then, based on the new concept introduced, various theorems are developed, which involve converting the fuzzy linear programming problem to a four objective linear programming problem of non-fuzzy members. The theoretical results and methods developed are then validated and their applications for solving fuzzy linear problems are demonstrated through examples.The second type of problems which we tackle in this research is fuzzy linear programming in which the constraint equations or inequalities contain fuzzy numbers. For this work, we first introduce a new concept, the α-fuzzy max order. Based on this concept, the general framework of an α-fuzzy max order method is developed for solving fuzzy linear programming problems with fuzzy parameters in the constraints. For the special cases in which the constraints consist of inequalities containing fuzzy numbers with isosceles triangle or trapezoidal membership functions, we prove that the feasible solution space can be determined by the respective 3n or 4n non-fuzzy inequalities. For the general cases in which the constraints contain fuzzy numbers with any other form of membership functions, robust numerical algorithms have been developed for the determination of the feasible solution space and the optimal solution to the fuzzy linear programming problem in which the constraints contain fuzzy parameters. Further, by using the results for both the first and second types of problems, general algorithms have also been developed for the general fuzzy linear programming problems in which both the objective function and the constraint inequalities contain fuzzy numbers with any forms of membership functions. Some examples are then presented to validate the theoretical results and the algorithms developed, and to demonstrate their applications

Flue Gas Desulfurization Apparatus

An apparatus is provided for removing sulfur oxides from a flue gas stream. That apparatus includes an absorber tower having an upper section and a lower section. A packed bed unit is provided in the upper section of the absorber tower. A first recycling circuit is provided for recycling lime water to the lower section of the absorber. Further the apparatus includes a second recycling circuit for recycling caustic solution to the packed bed unit

Linking microbial diversity and functionality of Arctic glacial surface habitats

Distinct microbial habitats on glacial surfaces are dominated by snow and ice algae, which are the critical players and the dominant primary colonisers and net producers during the melt season. Here we have for the first time evaluated the role of these algae in association with the full microbial community composition (i.e., algae, bacteria, archaea) in distinct surface habitats and on twelve glaciers and permanent snow fields in Svalbard and Arctic Sweden. We cross-correlated these data with the analyses of specific metabolites such as fatty acids and pigments, and a full suite of potential critical physico-chemical parameters including major and minor nutrients, and trace metals. We show that correlations between single algal species, metabolites, and specific geochemical parameters can be used to unravel mixed metabolic signals in complex communities, further assign them to single species and infer their functionality. The data also clearly show that the production of metabolites in snow and ice algae is driven mainly by nitrogen and less so by phosphorus limitation. This is especially important for the synthesis of secondary carotenoids, which cause a darkening of glacial surfaces leading to a decrease in surface albedo and eventually higher melting rates. This article is protected by copyright. All rights reserved

Roadway System Assessment Using Bluetooth-Based Automatic Vehicle Identification Travel Time Data

This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection systems. This includes considerations in the physical setup of the collection system as well as the interpretation of the data. An extended discussion is provided, with examples, demonstrating data techniques for converting the raw data into more concise metrics and views. Examples of statistical before-after tests are also provided. A series of case studies were presented that focus on various real-world applications, including the impact of winter weather on freeway operations, the economic benefit of traffic signal retiming, and the estimation of origin-destination matrices from travel time data. The technology used in this report is Bluetooth MAC address matching, but the concepts are extendible to other AVI data sources

Variations of algal communities cause darkening of a Greenland glacier

We have assessed the microbial ecology on the surface of Mittivakkat glacier in SE-Greenland during the exceptional high melting season in July 2012 when the so far most extreme melting rate for the Greenland Ice Sheet has been recorded. By employing a complementary and multi-disciplinary field sampling and analytical approach, we quantified the dramatic changes in the different microbial surface habitats (green snow, red snow, biofilms, grey ice, cryoconite holes). The observed clear change in dominant algal community and their rapidly changing cryo-organic adaptation inventory was linked to the high melting rate. The changes in carbon and nutrient fluxes between different microbial pools (from snow to ice, cryoconite holes and glacial forefronts) revealed that snow and ice algae dominate the net primary production at the onset of melting, and that they have the potential to support the cryoconite hole communities as carbon and nutrient sources. A large proportion of algal cells is retained on the glacial surface and temporal and spatial changes in pigmentation contribute to the darkening of the snow and ice surfaces. This implies that the fast, melt-induced algal growth has a high albedo reduction potential, and this may lead to a positive feedback speeding up melting processes

Method of Inhibiting Nitrosation of an Aqueous Amine Solution Used in a Process of Removing Carbon Dioxide from a Flue Gas

A method is provided for inhibiting nitrosation of an aqueous amine solution used in a process of removing carbon dioxide from a flue gas. That method includes a step of adding an effective amount of an antioxidant to the aqueous amine solution being circulated between an absorber and a stripper of a carbon dioxide capture system

Solvent and Method for Removal of an Acid Gas from a Fluid Stream

A solvent for removal of an acid gas from a fluid stream includes a promoter amine with a pKa of between 6.5 and 10.5 and a tertiary amine with a pKa of between 8.5 and 10.5