POLYCHAR-10 World Forum on Polymer Applications &; Theory in 2002

A report from POLYCHAR-10 is provided. An introduction to the following papers presented at the POLYCHAR-10 Forum is given. A small selection of the authors and titles of the papers presented is listed. Prizes awarded are listed along with the composition of the Prize Committee. Some research groups of high activity which are represented at POLYCHAR every year are named. Electronic Publication     

Nonlinearizable single-input control systems do not admit stationary symmetries

The main result of the paper states that almost any analytic single-input control system, which is truly nonlinear, that is not feedback linearizable, with controllable linearization at an equilibrium point, does not admit any symmetry preserving that point. By almost any system, we mean that we exclude a small class of odd systems, that admit just one nontrivial symmetry conjugated to minus identity. The obtained results are based on a recent classification of nonlinear single-input systems under formal feedback. We also describe symmetries of feedback linearizable systems.     

A hybrid continuous-discrete approach to large discrete structural optimization problems

Many optimum structural designs are based on searching for the best of all combinations, arising from the number of structural members, and parameters of listed rolled profiles. Even, in a relatively simple design, the number of such combinations is of an order higher than ten. All known methods of finding discrete minimum of structural weight require very large number of analyses often of an order of four. In this study, a relatively simple method of solving such problems is presented. It is based on a tree graph, representing discrete values of the structural volume. The structure can be subjected to multi static loadings with constraints imposed on displacements and stresses. The number of analyses, in the proposed algorithm, is limited to the order of two. The knowledge needed to apply the method is limited to FEM and graph representation. The paper is illustrated with two examples with numbers of combinations up to 42³⁸.     

Electron beam for LHC

A method of delivering a small energy spread electron beam to the LHC interaction points is proposed. In this method, heavy ions are used as carriers of projectile electrons. Acceleration, storage and collision-stability aspects of such a hybrid beam is discussed and a new beam-cooling method is presented. This discussion is followed by a proposal of the Parasitic Ion–Electron collider at LHC (PIE@LHC). The PIE@LHC provides an opportunity, for the present LHC detectors, to enlarge the scope of their research program by including the program of electron–proton and electron–nucleus collisions with minor machine and detector investments.     

A Comparative Study of Mechanical Properties,Thermal Conductivity,Residual Stresses,and Wear Resistance of Aluminum-Alumina Composites Obtained by Squeeze Casting and Powder Metallurgy

Squeeze casting and powder metallurgy techniques were employed to fabricate AlSi12/Al₂O₃ composites, which are lightweight structural materials with potential applications in the automotive industry. The impact of the processing route on the material properties was studied. Comparative analyses were conducted for the Vickers hardness, flexural strength, fracture toughness, thermal conductivity, thermal residual stresses, and frictional wear. Our results show that the squeeze cast composite exhibits superior properties to those obtained using powder metallurgy.

     

Correction to: A Comparative Study of Mechanical Properties,Thermal Conductivity,Residual Stresses,and Wear Resistance of Aluminum-Alumina Composites Obtained by Squeeze Casting and Powder Metallurgy

Metallurgical and Materials Transactions A -     

Studies on the usefulness of Cucurbita maxima for the production of ready-to-eat dried vegetable snacks with a high carotenoid content

Recent research indicates a beneficial influence of a diet rich in β-carotene on human health. For that reason, experiments were undertaken to process winter squash with a high carotenoid content into ready-to-eat dried snacks. Sensory quality and dietary value of chips and crispy cubes made from different cultivars were investigated.The suitability of winter squash for drying purposes depended mainly on the dry matter content in the raw material. Although all the investigated cultivars can be used for producing chips, obtaining high quality porous cubes requires at least 15% of dry matter. ‘Justynka F1’ emerged as the most suitable cultivar for processing; both chips and cubes produced from its fruits were characterized by a high sensory quality and contained significant amounts of beta-carotene (225- 253 μg g-1). Also, the cultivar ‘Amazonka’ could be considered for the production of chips as it allowed us to obtain a product with a high beta-carotene content (200 μg g-1) and good sensory properties. The dried ready-to-eat crispy vegetable snacks made from the new cultivars of winter squash could be exploited as a novel attractive product with the attractive taste and colour to serve as a valuable source of carotenoids in human diet.     

Hybrid fuzzy set-based polynomial neural networks and their development with the aid of genetic optimization and information granulation

We introduce a new architecture of feed-forward neural networks called hybrid fuzzy set-based polynomial neural networks (HFSPNNs) that are composed of heterogeneous feed-forward neural networks such as polynomial neural networks (PNNs) and fuzzy set-based polynomial neural networks (FSPNNs). We develop their comprehensive design methodology by embracing mechanisms of genetic optimization and information granulation. The construction of information granulation-driven HFSPNN exploits fundamental technologies of computational intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms (GAs). The architecture of the resulting information granulation-driven genetically optimized HFSPNN results from a synergistic usage of the hybrid system generated by combining original fuzzy set-based polynomial neurons (FSPNs)-based FSPNN with polynomial neurons (PNs)-based PNN. The design of the conventional genetically optimized HFPNN exploits the extended Group Method of Data Handling (GMDH) whose some essential parameters of the network being tuned with the use of genetic algorithms throughout the overall development process. Two general optimization mechanisms are explored. First, the structural optimization is realized via GAs while the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFSPNN is quantified through extensive experimentation where we considered a number of modeling benchmarks (synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling).