Multi-Attribute Analysis of the Most Appropriate Flue Gas Desulfurization (FGD) Technologies

The decision maker in environmental planning problems usually faces a complex system of interrelated components, such as resources, objectives, persons or groups of persons, etc. Often a decision maker has to choose among a finite number of alternatives according to some criteria. One of the problems in development decision making is to account for the interaction between knowledge and politics. In some circumstances political goals and power rather than knowledge easily dominate development decisions but in other circumstances the reverse may be true. In parallel with quantitative estimations the qualitative and relative estimations of parameters are available for the decision maker. So there is a problem to combine different types of estimations. There is also the problem of missing and uncertain data. In recent years some approaches were proposed to support the decision making process for such complex problems. We can mention Bayesian decision analysis, fuzzy-set based decision analysis, and the Analytic Hierarchy Process (AHP) as outranking methods. There is corresponding software based on these approaches to support decision making process such as Supertree, COPE, Expert Choice, Rank Master, Trigger, etc. Here we consider the problem of choosing of the most appropriate flue gas desulfurization (FGD) technologies for implementation on a power plant as a good example of a complex semistructural problem. The purpose of this work to solve this problem as a test problem using a software package CHOICE designed in the Glushkov Institute of Cybernetics of the Ukrainian Academy of Sciences. This package is intended to analyze the structure of the problem and then present it and support the decision making process. As Kaplan notes: "A theory is not just the discovery of a hidden fact; the theory is a way of looking at the facts, of organizing and representing them"

Stochastic Nonlinear Programming System

This paper contains a detailed description of the Stochastic Nonlinear Programming System (SNLP) intended for solving stochastic optimization problems with simple recourse. This system is a result of collaboration between the Glushkov Institute of Cybernetics (Kiev, USSR) and the International Institute for Applied System Analysis (IIASA) within the framework of the Adaptation and Optimization Project in the System and Decision Sciences Program

Negative Barnett effect, negative moment of inertia of (quark-)gluon plasma and thermal evaporation of chromomagnetic condensate

We discuss the negativity of the moment of inertia of (quark-)gluon plasma in a window of ``supervortical'' range of temperatures above the deconfining phase transition, $T \simeq (1\dots 1.5) T_c$ found recently in numerical Monte Carlo simulations by two independent methods. In our work, we confirm numerically that the origin of this effect is rooted in the thermal evaporation of the non-perturbative chromomagnetic condensate. We argue that the negative moment of inertia of gluon plasma indicates the presence of a novel effect, the negative spin-vortical coupling for gluons resulting in a negative gluonic Barnett effect: the spin polarization of gluons exceeds the total angular momentum of rotating plasma thus forcing the orbital angular momentum to take negative values in the supervortical range of temperatures.Comment: 9 pages, 3 figure

Treatment of rising damp in historical buildings: wall base ventilation

Intervention in older buildings increasingly requires extensive and objective knowledge of what one will be working with. The multifaceted aspect of work carried out on buildings tends to encompass a growing number of specialities, with marked emphasis on learning the causes of many of the problems that affect these buildings and the possible treatments that can solve them. Moisture transfer in walls of old buildings, which are in direct contact with the ground, leads to a migration of soluble salts responsible for many building pathologies.http://www.sciencedirect.com/science/article/B6V23-4H7T0H7-1/1/f5e8a4ec173c5dadf120770678facf4