Scale-effects on mean and standard deviation of the mechanical properties of condensed matter: an energy-based unified approach

The size effects on the mean values of the mechanical properties of condensed matter and on the related variances are analysed by means of a unified approach based on the multiscale character of energy dissipation. In particular, the scaling law for fragmentation energy density is obtained taking into account the self-similarity of fragments. It is based on a generalization of the three classical comminution laws that has been performed to evaluate the energy dissipation, computing volume and surface area of the particles for one- two- and three-dimensional fragmented objects. The result is general and can be applied to different fractal energy dissipation mechanisms, e.g., plasticity. Based on this approach, the scaling laws for mean and standard deviation values of the main mechanical properties of materials can be derived, like Young's and shear elastic moduli, ultimate normal and shear stresses and strains, fracture energy and toughness.     

Hydrocarbon exploration risk evaluation through uncertainty and sensitivity analyses techniques

The evaluation of the exploration risk in the oil industry is a fundamental component of the decision process related to the exploratory phase. In this paper the two basic components of the exploratory risk: trap geometry and trapped hydrocarbon quantities (fluid), are compounded in a single coherent uncertainty and sensitivity approach. The results clarify that the model geometry influences each Petroleum System Modeling step and that the geometric uncertainty is correlated with the fluid uncertainty. The geometric uncertainty evaluation makes use of geostatistical techniques that produce a number of possible realizations of the trap geometry, all compatible with available data. The evaluation of the fluid uncertainty, through a Monte Carlo methodology, allows us to compute the possible quantities of oil and gas, generated in a basin and migrated from the hydrocarbon source location to each single trap. The final result is the probability distribution of oil and gas for each trap in the basin, together with other useful indicators like: the hydrocarbon filling probability map, the closure probability map, the drainage area probability map, the spilling paths probabilities, the trap-filling scenarios.     

Hydrodechlorination of 3-chloropyridine and chlorobenzene in methanol solution over alkali-modified zirconia-supported palladium catalysts

The liquid-phase hydrodechlorination of 3-chloropyridine and chlorobenzene has been studied over alkali-modified zirconia-supported palladium catalysts. The modification of the ZrO₂ with alkali metal carbonates improves the catalytic activity of the final palladium catalyst. Therefore, the larger the ionic radii (Li⁺ < Na⁺ < K⁺), the greater the catalytic activity (TOF) of the palladium catalyst. For 3-chloropyridine, hydrodechlorination proceeds without catalyst deactivation. This is explained as the result of the interaction of reaction products (pyridine and HCl) forming pyridinium chloride, thus avoiding the detrimental effect of HCl on the palladium particles. Catalytic hydrodechlorination of chlorobenzene over Pd catalysts exhibits an initial catalytic activity (TOF) much lower than that of 3-chloropyridine and the Pd catalysts deactivate as the reaction proceeds. Finally, chlorobenzene hydrodehalogenation has also been carried out in the presence of an equimolecular amount of pyridine resulting in a decrease in the initial reaction rate on the one hand, but also in an increase in final conversion on the other.     

Comments on “Is the cause of size effect on structural strength fractal or energetic-statistical?” by Ba?ant & Yavari [Engng Fract Mech 2005;72:1-31]

Aim of this letter to the Editor is at replying to the criticisms raised by Ba?ant and Yavari [Ba?ant ZP, Yavari A. Is the cause of size effect on structural strength fractal or energetic - statistical? Engng Fract Mech 2005;72:1-31] against the fractal approach to the size-scale effects on the mechanical properties of materials and the concept of the Multi-Fractal Scaling Law presented by Carpinteri [Carpinteri A. Scaling laws and renormalization groups for strength and toughness of disordered materials. Int J Solids Struct 1994;31:291-302]. These criticisms will be analysed thoroughly, showing how they also contain some mistakes and misunderstandings. The presented elucidations should redirect the discussion to a more correct scientific debate.     

FDTD simulation of 30 /spl mu/m diameter polymer micro-ring

Numerical results on polymer surrounded by an air micro-ring coupled to waveguides are presented. The FDTD method predicts a filter width of 1.4 nm and an extraction efficiency of almost 80% for a gap of 0.15 /spl mu/m.     

Analysis of run-in process for PC manufacturing

This paper gives a review of the methodology used to tune the run-in process of a PC manufacturing line. It shows in some detail the analysis carried-out on the test data gathered on the manufacturing line and presents a clear picture of the run-in process in order to choose the best compromise between process efficiency and costs.     

Novel aspects of the microstructure of PP/PA blends prepared by reactive compounding as studied by microhardness

The microhardness of injection-moulded i-polypropylene/polyamide (iPP/PA) blends prepared by reactive compounding was determined. The formulation rules and processing technology for the preparation of these alloys was reported previously. iPP/PA compositions between 100/0 and 50/50 using functionalized PP with various degrees of mainchain grafting, were investigated. It is shown that the deviation of microhardness from the additivity law of the single components is mainly due to a decrease in the crystallinity of the iPP phase. The results are discussed in the light of the microstructural variations as revealed by X-ray diffraction methods.     

Step response classification for model-based autotuning via polygonal curve approximation

A model-based autotuning method consists of an identification and a regulator tuning phase. To achieve satisfactory performance and robustness, it is advisable that both phases be tailored a priori to the characteristics of the observed process dynamics. Such characteristics include, but are not limited to, the model structure. For example, overdamped and underdamped models with the same pole-zero structure are parametrised and controlled in different ways. Step response data, that are typically used for the identification phase in the autotuning context, can also be pre-processed to reveal those characteristics. This paper presents a step response classification method suitable for the above purpose. The method is based on a polygonal curve approximation technique for data pre-processing, followed by a neural network classifier. Only normalised I/O data are employed, so that the neural network can be trained off-line with simulated data. Simulation results are reported to show the effectiveness of the proposed classification method in terms of the achievable tuning results.