Na-feldspar (F) and kaolinite (K) system at high temperature: Resulting phase composition,micro-structural features and mullite-glass Gibbs energy of formation,as a function of F/K ratio and kaolinite crystallinity

The system Na-feldspar (F) and kaolinite (K) was investigated at temperatures of interest in ceramic applications (1200–1280 °C) to study the effects of F/K ratios by weight and crystallinity degree of kaolinite on the final product, micro-structural features and mullite-glass Gibbs energy of formation (ΔG^eff). Mullite and glass are the dominant phases; in general, the higher the temperature, the larger the former. An F/K increase promotes the formation of glass and secondary mullite, appearing along with the primary one. ΔG^eff was modelled by α(T) × (F/K)² + β(T) × F/K + γ(T), α, β and γ being linear functions of temperature whose coefficients were determined by fitting the ΔG^eff-theoretical to the ΔG^eff-obtained from the measured phase compositions. ΔG^eff is less affected by temperature than by F/K, whose increase shifts equilibrium towards glass phases. The ΔG^eff-curves for ordered and disordered kaolinite intersect one another at F/K ～0.5, a ratio close to that used in industrial practice.     

Case-Base Maintenance in a Multimodal Reasoning System

The definition of suitable case-base maintenance policies is widely recognized as a major key to success for case-based systems; underestimating this issue may lead to systems that either do not fulfill their role of knowledge management and preservation or that do not perform adequately under performance dimensions, namely, computation time and competence and quality of solutions. The goal of this article is to analyze some automatic case-base management strategies in the context of a multimodal architecture combining case-based reasoning and model-based reasoning. We propose and compare two different methodologies, the first one, called replace , is a competence-based strategy aimed at replacing a set of stored cases with the current one, if the latter exhibits an estimated competence comparable with the estimated competence of the considered set of stored cases. The second one, called learning by failure with forgetting (LFF), is based on incremental learning of cases interleaved with off-line processes of forgetting (deleting) cases whose usage does not fulfill specific utility conditions. Results from an extensive experimental analysis in an industrial plant diagnosis domain are reported, showing the usefulness of both strategies with respect to the maintenance of suitable performance levels for the target system.     

In situ spectroelectrochemical measurements during the electro-oxidation of ethanol on WC-supported Pt-black. Part II: Monitoring of catalyst aging by in situ Fourier transform infrared spectroscopy

As a continuation of a project on the spectroelectrochemical analysis of long-term behaviour of WC-supported Pt electrocatalysts (for SFG results, see part I: [1]), in this paper we report in situ FT-IR spectroscopy experiments, carried out during prolonged electro-oxidation of ethanol on Pt-black. From the analytical point of view, as expected, FT-IR spectra showed the presence of adsorbed acetic acid and ethanol, in addition to the well-known, dominant species: linearly adsorbed CO (2044-2063 cm⁻¹) and solution-phase CO₂ (2345 cm⁻¹). As far as quantitative spectroscopic results are concerned, a notable sensitivity of the interfacial chemistry to catalyst aging could be highlighted by this approach. The spectra recorded in three subsequent series of potential-cycling experiments showed a clear-cut dependence of spectral patterns and peak intensities, on the applied potential and on the oxidation duration. Qualitative spectral changes seem to suggest - coherently with in situ SFG results obtained with the same system [1] - that electrocatalyst aging correlates with a higher surface coverage with ethanol as compared with acetic acid. Quantitative analysis, based on fitting with Lorentzian lineshapes, yields information that can be used as a molecular-level diagnostic of the modification of the catalyst-adsorbate structure.     

Learning concurrently data and rule bases of Mamdani fuzzy rule-based systems by exploiting a novel interpretability index

Interpretability of Mamdani fuzzy rule-based systems (MFRBSs) has been widely discussed in the last years, especially in the framework of multi-objective evolutionary fuzzy systems (MOEFSs). Here, multi-objective evolutionary algorithms (MOEAs) are applied to generate a set of MFRBSs with different trade-offs between interpretability and accuracy. In MOEFSs interpretability has often been measured in terms of complexity of the rule base and only recently partition integrity has also been considered. In this paper, we introduce a novel index for evaluating the interpretability of MFRBSs, which takes both the rule base complexity and the data base integrity into account. We discuss the use of this index in MOEFSs, which generate MFRBSs by concurrently learning the rule base, the linguistic partition granularities and the membership function parameters during the evolutionary process. The proposed approach has been experimented on six real world regression problems and the results have been compared with those obtained by applying the same MOEA, with only accuracy and complexity of the rule base as objectives. We show that our approach achieves the best trade-offs between interpretability and accuracy.     

Assessment of bioenergy potential in Sicily: A GIS-based support methodology

A Geographical Information System (GIS) supported methodology has been developed in order to assess the technical and economic potential of biomass exploitation for energy production in Sicily. The methodology was based on the use of agricultural, economic, climatic, and infrastructural data in a GIS. Data about land use, transportation facilities, urban cartography, regional territorial planning, terrain digital model, lithology, climatic types, and civil and industrial users have been stored in the GIS to define potential areas for gathering the residues coming from the pruning of olive groves, vineyards, and other agricultural crops, and to assess biomass available for energy cultivation. Further, it was possible to assess the potential of biodiesel production, supposing the cultivation of rapeseed in arable crop areas. For the biomass used for direct combustion purposes, the economic availability has been assessed assuming a price of the biomass and comparing it with other fuels. This assessment has shown the strong competitiveness of firewood in comparison with traditional fossil fuels when the collection system is implemented in an efficient way. Moreover, the economic potential of biodiesel was assessed considering the on-going financial regime for fuel. At the same time, the study has shown a significant competitiveness of the finished biomass (pellets), and good potential for a long-term development of this market. An important result was the determination of biofuel production potential in Sicily. An outcome of the study was to show the opportunities stemming from the harmonisation of Energy Policy with the Waste Management System and Rural Development Plan.     

On the non-linear Maxwell–Cattaneo equation with non-constant diffusivity: Shock and discontinuity waves

A numerical study on a non-linear hyperbolic diffusion equation is proposed. The Hartree hybrid method combining finite difference techniques with the method of characteristics is used in the presence of discontinuities between initial and boundary conditions. The technique proved to be an useful tool to overcome oscillation problems and spurious solutions in case of strong non-linearities related to both attractive or repulsive interactions between diffusing species. Two different expressions for the diffusion coefficient are used in order to compare our results with the ones obtained in previous studies relying upon the Laplace transform technique and the MacCormack predictor–corrector method. Finally, an analytic approach based on the singular surface theory is proposed to motivate the numerical results and to clarify some controversial aspects concerning the penetration depth of a diffusive front in the presence of interactions.     

Feasibility of horizon-switching predictive control under positional and incremental input saturations

This paper proves the validity of a basic feasibility property which makes it possible to extend, to the case of set-point tracking in ANCBI systems under joint positional and incremental input saturations, the approach in [Mosca, E. (2005). Predictive switching supervisory control of persistently disturbed input-saturated plants. Automatica, 41, 55-67] restricted to positional input saturation and the pure regulation problem. An example on the use of the proposed technique is considered.     

Land Subsidence Spreading Factor of the Northern Adriatic Gas Fields, Italy

The land subsidence spreading factor χ provides a useful straightforward indication on how much of a gas/oil reservoir compaction induced by field development migrates to ground surface with a possible adverse impact on the stability of low‐lying coastal areas. This factor depends primarily on the ratio between the depth of burial and a representative horizontal dimension of the reservoir. However, an important influence is also exerted by the active bottom/lateral aquifer hydraulically connected to the field (called “waterdrive” in reservoir engineering) that may undergo an extensive depressurization also after the field abandonment, thus contributing to enhance the overall land settlement. In the Northern Adriatic basin, Italy, χ is evaluated using a nonlinear finite element model of three representative gas reservoirs (Chioggia Mare, Dorotea, and Dosso degli Angeli) surrounded by important bottom/lateral aquifers in the interval depth between 1000 and 3300 m. Results show that χ may easily approach and even exceed one for the deepest field as well, contrary to the prediction of land subsidence based on the compaction of the gas‐bearing formations alone, that can thus be largely underestimated.     

Measuring Statistical Geometric Properties of Tomographic Images of Soils

Porous media modeling is relevant in several applications, such as agricultural engineering, where soil compaction analysis requires the estimation of soil transport properties. For example, the prediction of root growing patterns and their environmental impact is usually measured by analyzing soil fluid infiltration capacity and water retention. Recently, tomographic images have been used in nondestructive tests of soil. However, using such images is challenging for two reasons: (1) Tomographic images are usually noisy, which complicates their segmentation, and (2) modeling the soil structure requires establishing adjacency relations among neighboring tomographic slices, which has a significant computational cost due to the combinatorial nature of this problem. In this paper, we propose a solution for both problems. The experimental results show that soil samples can be analyzed and classified with significant accuracy using our proposed approach.     

Synthesis of Yb nanoparticles by laser ablation of ytterbium target in sodium bis(2-ethylhexyl)sulfosuccinate reverse micellar solution

Surfactant-coated ytterbium nanoparticles were produced by Nd:YAG laser ablation of a Yb bulk target immersed in sodium bis(2-ethylhexyl)sulfosuccinate (AOT)/n-heptane micellar solution. In our experimental conditions, as highlighted by IR spectroscopy, AOT molecules are not decomposed by the intense laser pulses but play a pivotal role in the stabilisation of Yb nanoparticles. The formation of Yb nanoparticles in the liquid phase was monitored by UV-Vis spectroscopy whereas the Yb/AOT composites obtained by evaporation of the organic solvent were characterised by XPS and TEM. Data analysis consistently shows the presence of surfactant-coated, nearly spherical and non-interacting Yb nanoparticles of mean diameter of 3 nm.Moreover, the presence of bigger polycrystalline nanoparticles (about 30%) in coexistence with smaller mono crystalline ones indicates that, after the rapid formation of the pristine Yb nanoparticles from plume condensation, two processes effectively compete for their size distribution: nanoparticle agglomeration and surfactant adsorption.