Modeling of the NO x trap and experimental validation using ultra-fast NO x analyzers

The present paper employs and validates a NO _x trap model which attempts an optimum compromise between complexity and predictive accuracy. It is shown that using the same set of kinetic data, the model is able to predict the storage rates and the maximum storage amounts as function of temperature. Moreover, the model predicts with reasonable accuracy the NO breakthrough during rich-mode regeneration and the spontaneous/thermal NO₂ release when the temperature is increased in a saturated catalyst. The experimental findings highlight the importance of transient O₂ adsorption/desorption phenomena which are incorporated in the model. The use of ultra-fast responding NO/NO _x analyzers was necessary for the study and modeling of the transient operation following inlet composition switches.     

Study of the acid pretreatment and biodiesel production from olive pomace oil

The objective of this work was to study the two‐step acid base homogenous catalyzed transesterification of olive pomace oil, with the ultimate purpose of producing biodiesel under mild reaction conditions by optimizing the process. Optimization of the experimental procedure was conducted by a factorial design of 2³ under the acidic pretreatment step and during the basic transesterification. The optimal production of methyl esters (97.8%) was achieved for the experimental conditions H₂SO₄ = 20 wt%/CH₃OH = 35:1/T = 40^°C and KOH = 0.6+ fatty acid value /CH₃OH = 9:1/ T = 60^°C, in the acidic and basic stage of the process, respectively. Finally, to properly assess the quality of the biofuel produced, it was tested for all the European Standard properties.     

The Menpo Benchmark for Multi-pose 2D and 3D Facial Landmark Localisation and Tracking

International Journal of Computer Vision - In this article, we present the Menpo 2D and Menpo 3D benchmarks, two new datasets for multi-pose 2D and 3D facial landmark localisation and tracking. In...     

Innovative microwave-assisted hydrolysis of ellagitannins and quantification as ellagic acid equivalents

The health-promoting effects of ellagic acid and its intestinal degradation products are well-known. In plants, ellagic acid mainly appears in the form of its precursors, the so-called ellagitannins. Therefore, determination of total ellagic acid content has been accomplished by cleaving ellagitannins with high temperatures and strong acids. Microwave-assisted extraction (MAE) has been shown to be a very effective and quick extraction technique. The aim of the present study was to establish an MAE-based method for a rapid hydrolysis of ellagitannins and to compare this method with a conventional acid hydrolysis. For this purpose, strawberries (Fragaria x ananassa), which have been identified as a major source of ellagitannins in human diet, were used as a model. The newly developed MAE method was quicker, less chemical-consuming and more effective in hydrolysing ellagitannins.     

Design of biomass district heating systems

The biomass exploitation takes advantage of the agricultural, forest, and manure residues and in extent, urban and industrial wastes, which under controlled burning conditions, can generate heat and electricity, with limited environmental impacts.Biomass can – significantly – contribute in the energy supplying system, if the engineers will adopt the necessary design changes to the traditional systems and become more familiar with the design details of the biomass heating systems.The aim of this paper is to present a methodology of the design of biomass district heating systems taking into consideration the optimum design of building structure and urban settlement around the plant. The essential energy parameters are presented for the size calculations of a biomass burning-district heating system, as well as for the environmental (i.e. Greenhouse Gas Emissions) and economic evaluation (i.e. selectivity and viability of the relevant investment). Emphasis has been placed upon the technical parameters of the biomass system, the economic details of the boiler, the heating distribution network, the heat exchanger and the Greenhouse Gas Emissions.     

Sustainable energy planning by using multi-criteria analysis application in the island of Crete

The sustainable energy planning includes a variety of objectives, as the decision-making is directly related to the processes of analysis and management of different types of information (technological, environmental, economic and social). Very often, the traditional evaluation methods, such as the cost-benefit analysis and macro-economic indicators, are not sufficient to integrate all the elements included in an environmentally thorough energy plan. On the contrary the multiple criteria methods provide a tool, which is more appropriate to assemble and to handle a wide range of variables that is evaluated in different ways and thus offer valid decision support.     

A mode I fracture analysis of a center-cracked infinite shape memory alloy plate under plane stress

The problem of a center plane crack in an infinite, thin, pseudoelastic Shape Memory Alloy (SMA) plate subjected to an in-plane uniform tensile stress at infinity is analyzed. The analysis follows closely the Dugdale?CBarenblatt model developed for conventional metals. It is found for low remote stress values??less than a critical value??that the SMA is not fully transformed in the vicinity of a crack tip. Closed form expressions for the size of the partial transformation zone, crack opening displacement and J-integral are given for this case. For remote stress levels above the critical value, the fully-transformed material near a crack tip is assumed to yield plastically. The sizes of the transformed (both partially and fully) and plastic regions are numerically evaluated by solving a system of integral equations and their sensitivity to the transformation characteristics (i.e., maximum transformation strain and temperature) is determined. Moreover, a relationship between the J-integral and the crack-tip opening displacement is derived. The results obtained are important in understanding the effect of stress-induced phase transformation in the fracture behavior of SMAs in the presence of static cracks, and subsequently in formulating conditions for initiation of crack propagation.     

Evaluation of on-board diagnosis methods for three-way catalytic converters

On-board diagnosis (OBD) aims at detecting malfunctions of emission-related components of road vehicles. It is required by legislation in United States and the European Union, as it is considered to be beneficial for the reduction of vehicle-related air pollution. On-board diagnosis of the catalytic converter is a challenging task, as it relies on indirect assessments of catalyst activity. Several methods have been proposed for catalyst diagnosis, presenting a varying degree of correlation between the quantities used as OBD indexes and the actual tailpipe emissions. This paper evaluates two methods, with the support of mathematical modeling; in the first one, which is commonly used by vehicle manufacturers, malfunction detection relies on the oxygen storage properties of the catalyst, while in the second, detection relies on the heat released by the chemical reactions in the catalyst. Both are found to be sufficient for the diagnosis of catalytic converters for current legislation requirements. However, the thermal method presents higher sensitivity to low levels of catalyst deactivation and could therefore be more suitable for diagnosis of future, ultra-low-emitting vehicles.     

An adaptive personalized news dissemination system

With the explosive growth of the Word Wide Web, information overload became a crucial concern. In a data-rich information-poor environment like the Web, the discrimination of useful or desirable information out of tons of mostly worthless data became a tedious task. The role of Machine Learning in tackling this problem is thoroughly discussed in the literature, but few systems are available for public use. In this work, we bridge theory to practice, by implementing a web-based news reader enhanced with a specifically designed machine learning framework for dynamic content personalization. This way, we get the chance to examine applicability and implementation issues and discuss the effectiveness of machine learning methods for the classification of real-world text streams. The main features of our system named PersoNews are: (a) the aggregation of many different news sources that offer an RSS version of their content, (b) incremental filtering, offering dynamic personalization of the content not only per user but also per each feed a user is subscribed to, and (c) the ability for every user to watch a more abstracted topic of interest by filtering through a taxonomy of topics. PersoNews is freely available for public use on the WWW ().