Exciton-polariton transition induced by elastic exciton-exciton collisions in ultrahigh quality AIGaAs alloys

The stationary and time-resolved polariton radiation in ultrahigh quality AIGaAs layers have been studied. It has been found that elastic exciton-exciton collisions lead to the appearance of a low-energy line of polariton radiation. We show that the rate of exciton-to-polariton transitions caused by elastic exciton-exciton collisions is determined not only by the density of the excitonic gas, but also by its temperature; this is in accordance with existing theoretical predictions. The text was submitted by the authors in English.     

Empirical modelling of shear strength of RC deep beams by genetic programming

This paper investigates the feasibility of using genetic programming (GP) to create an empirical model for the complicated non-linear relationship between various input parameters associated with reinforced concrete (RC) deep beams and their ultimate shear strength. GP is a relatively new form of artificial intelligence, and is based on the ideas of Darwinian theory of evolution and genetics. The size and structural complexity of the empirical model are not specified in advance, but these characteristics evolve as part of the prediction. The engineering knowledge on RC deep beams is also included in the search process through the use of appropriate mathematical functions.The model produced by GP is constructed directly from a set of experimental results available in the literature. The validity of the obtained model is examined by comparing its response with the shear strength of the training and other additional datasets. The developed model is then used to study the relationships between the shear strength and different influencing parameters. The predictions obtained from GP agree well with experimental observations.     

Design optimization of supersonic jet pumps using high fidelity flow analysis

Supersonic jet pumps are simple devices with no moving parts, where a high velocity (primary) flow is used to pump a second fluid. In this paper, Computational Fluid Dynamics (CFD) is combined with an optimization framework in order to develop a tool for the rapid generation of jet pump designs. A key feature of the problem formulation is the transformation of the jet pump design parameters in terms of geometric ratios. This approach dramatically reduces the number of unrealistic designs covered by the Design of Experiments. Optimal Latin Hypercubes for surrogate model building and model validation points are constructed using a permutation genetic algorithm and design points are evaluated using CFD. Surrogate models of primary and entrained flow rates are built using a Moving Least Squares approach. A series of optimizations for various pump sizes are performed using a genetic algorithm and Sequential Quadratic Programming, with responses calculated from the surrogates. This approach results in a set of optimized designs, from which pumps for a wide range of flow rates can be interpolated.     

A source of a reference spherical wave based on a single mode optical fiber with a narrowed exit aperture

A new type of a reference spherical wave source (SWS) based on a single mode optical fiber with a narrowed down up to the submicrometer size exit aperture is proposed. It is intended for the precision point diffraction interferometers as a source of a reference wave. Systematic experimental errors which influence the measurement accuracy of the quality of the wave fronts generated by the SWSs are considered. Experimental data on wave front deformations are given. The combined root-mean-square (rms) wave deformation for a couple of the SWSs measured in a numerical aperture of NA=0.27 reaches the value of rms=0.36 nm that corresponds to rms=0.25 nm of a single SWS or about lambda2500 for the red He-Ne laser.     

Detailed design of a lattice composite fuselage structure by a mixed optimization method

In this article, a procedure for designing a lattice fuselage barrel is developed. It comprises three stages: first, topology optimization of an aircraft fuselage barrel is performed with respect to weight and structural performance to obtain the conceptual design. The interpretation of the optimal result is given to demonstrate the development of this new lattice airframe concept for the fuselage barrel. Subsequently, parametric optimization of the lattice aircraft fuselage barrel is carried out using genetic algorithms on metamodels generated with genetic programming from a 101-point optimal Latin hypercube design of experiments. The optimal design is achieved in terms of weight savings subject to stability, global stiffness and strain requirements, and then verified by the fine mesh finite element simulation of the lattice fuselage barrel. Finally, a practical design of the composite skin complying with the aircraft industry lay-up rules is presented. It is concluded that the mixed optimization method, combining topology optimization with the global metamodel-based approach, allows the problem to be solved with sufficient accuracy and provides the designers with a wealth of information on the structural behaviour of the novel anisogrid composite fuselage design.     

Dropout prediction in e-learning courses through the combination of machine learning techniques

In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to accurately classify some e-learning students, whereas another may succeed, three decision schemes, which combine in different ways the results of the three machine learning techniques, were also tested. The method was examined in terms of overall accuracy, sensitivity and precision and its results were found to be significantly better than those reported in relevant literature.     

Gradient based hyper-parameter optimisation for well conditioned kriging metamodels

In this work a two step approach to efficiently carrying out hyper parameter optimisation, required for building kriging and gradient enhanced kriging metamodels, is presented. The suggested approach makes use of an initial line search along the hyper-diagonal of the design space in order to find a suitable starting point for a subsequent gradient based optimisation algorithm. During the optimisation an upper bound constraint is imposed on the condition number of the correlation matrix in order to keep it from being ill conditioned. Partial derivatives of both the condensed log likelihood function and the condition number are obtained using the adjoint method, the latter has been derived in this work. The approach is tested on a number of analytical examples and comparisons are made to other optimisation approaches. Finally the approach is used to construct metamodels for a finite element model of an aircraft wing box comprising of 126 thickness design variables and is then compared with a sub-set of the other optimisation approaches.     

Multiparameter structural optimization using FEM and multipoint explicit approximations

A unified approach to various problems of structural optimization, based on approximation concepts, is presented. The approach is concerned with the development of the iterative technique, which uses in each iteration the information gained at several previous design points (multipoint approximations) in order to better fit constraints and/or objective functions and to reduce the total number of FE analyses needed to solve the optimization problem. In each iteration, the subregion of the initial region in the space of design variables, defined by move limits, is chosen. In this subregion, several points (designs) are selected, for which response analyses and design sensitivity analyses are carried out using FEM. The explicit expressions are formulated using the weighted least-squares method. The explicit expressions obtained then replace initial problem functions. They are used as functions of a particular mathematical programming problem. Several particular forms of the explicit expressions are considered. The basic features of the presented approximations are shown by means of classical test examples, and the method is compared with other optimization techniques.Presented at NATO ASI Optimization of Large Strucutral Systems, held in Berchtesgarden, Germany, Sept. 23 — Oct. 4, 1991     

Heavy-ion-induced luminescence of amorphous SiO2 during nanoparticle formation

Silica glass was implanted with negative 60 keV Cu ions at an ion flux from 5 to 75 μA/cm² up to a fluence of 1 × 10¹⁷ ions/cm² at initial sample temperatures of 300, 573 and 773 K. Spectra of ion-induced photon emission (IIPE) were collected in situ in the range from 250 to 850 nm. Optical absorption spectra of implanted specimens were ex situ measured in the range from 190 to 2500 nm.

IIPE spectra showed a broad band centered around 560 nm (2.2 eV) that was assigned to Cu⁺ solutes. The band appeared at the onset of irradiation, increased in intensity up to a fluence of about 5 × 10¹⁵ ions/cm² and then gradually decreased indicating three stage of the ion beam synthesis of nanoclusters: accumulation of implants, nucleation and growth nanoclusters. The IIPE intensity normalized on the ion flux is independent on the ion flux below 20 μA/cm²at higher fluences. The intensity of the band increased with increasing samples temperature, when optical absorption spectra reveal the increase of Cu nanoparticles size.