Quantum Statistics of Light Emitted from a Pillar Microcavity

A quantum behavior of the light emitted by exciton polaritons excited in a pillar semiconductor microcavity with embedded quantum well is investigated. Considering the bare excitons and photon modes as coupled quantum oscillators allows for an accurate accounting of the nonlinear and dissipative effects. In particular, using the method of quantum states presentation in a quantum phase space via quasiprobability functions (namely, a P-function and a Wigner function), we study the effect of the laser and the exciton-photon detuning on the second order correlation function of the emitted photons. We determine the conditions for the phenomena of bunching, giant bunching, and antibunching of the emitted light. In particular, we predict the effect of a giant bunching for the case of a large exciton to photon population ratio. Within the domain of parameters supporting a bistability regime we demonstrate the effect of bunching of photons.

Best Architecture of an Artificial Neural Network to Model Prefilming Airblast Atomization: Not So Deep Learning

A fully connected Artificial Neural Network (ANN) is used to predict the mean spray characteristics of prefilming airblast atomization. The model is trained from the planar prefilmer experiment from the PhD thesis of Gepperth (2020). The output of the ANN model are the Sauter Mean Diameter, the mean droplet axial velocity, the mean ligament length and the mean ligament deformation velocity. The training database contains 322 different operating points. Two types of model input quantities are investigated and compared. First, nine dimensional parameters are used as inputs for the model. Second, nine non-dimensional groups commonly used for liquid atomization are derived from the first set of inputs. The best architecture is determined after testing over 10000 randomly drawn ANN architectures, with up to 10 layers and up to 128 neurons per layer. The striking results is that for both types of model, the best architectures consist of only 3 hidden layer in the shape of a diabolo. This shape recalls the shape of an autoencoder, where the middle layer would be the feature space of reduced dimensionality. It was found that the model with dimensional input quantities always shows a lower test and validation errors than the one with non-dimensional input quantities. In general, the two types of models provide comparable accuracy, better than typical correlations of SMD and droplet velocity. Finally the extrapolation capability of the models was assessed by a training them on a confined domain of parameters and testing them outside this domain.

Interactive α-satisfactory method for multi-objective optimization with fuzzy parameters and linguistic preference

An interactive α-satisfactory method via relaxed order of desirable α-satisfactory degrees is proposed for multi-objective optimization with fuzzy parameters and linguistic preference in this paper. Fuzzy parameters existing in objectives and constraints of multi-objective optimization are defined as fuzzy numbers and α-level set is used to build the feasible domain of parameters. On the basis, the original problem with fuzzy parameters is transformed into multi-objective optimization with fuzzy goals. Linguistic preference of decision-maker is modelled by the relaxed order of desirable α-satisfactory degrees of all the objectives. In order to achieve a compromise between optimization and preference, the multi-objective optimization problem is divided into two single-objective sub-problems: the preliminary optimization and the linguistic preference optimization. A preferred solution can be found by parameter adjustment of inner-outer loop. The minimum stable relaxation algorithm of parameter is developed for calculating the relaxation bound of maximum desirable satisfaction difference. The M-α-Pareto optimality of solution is guaranteed by the test model. The effectiveness, flexibility and sensitivity of the proposed method are well demonstrated by numerical example and application example to heat conduction system.

Constrained Unscented Kalman Filter for Structural Identification of Bouc–Wen Hysteretic System

The Bouc–Wen hysteresis model has been extensively used to identify earthquake damage on civil structures where hysteretic behavior is expected. One of the challenging problems in the identification of Bouc–Wen parameters is overfitting, which is caused by too many nonphysical model parameters. Limit on the search domain of parameters helps to solve the problem. The unscented Kalman filter (UKF) is widely developed to find Bouc–Wen parameters. In order to improve the accuracy and convergence speed of conventional UKF, this study developed a constrained UKF (CUKF) which can be used for the simultaneous identification of the Bouc–Wen hysteretic model. The proposed CUKF is very helpful when certain parameters can be constrained in a physical sense. We compare the proposed CUKF with conventional UKF to validate its robustness and efficacy in identifying Bouc–Wen parameters.

Experimentally Accessible Orbits Near a Bykov Cycle

This paper reports numerical experiments done on a two-parameter family of vector fields which unfold an attracting heteroclinic cycle linking two saddle-foci. We investigated both local and global bifurcations due to symmetry breaking in order to detect either hyperbolic or chaotic dynamics. Although a complete understanding of the corresponding bifurcation diagram and the mechanisms underlying the dynamical changes is still out of reach, using a combination of theoretical tools and computer simulations we have uncovered some complex patterns. We have selected suitable initial conditions to analyze the bifurcation diagrams, and regarding these solutions we have located: (a) an open domain of parameters with regular dynamics; (b) infinitely many parabolic-type curves associated to homoclinic Shilnikov cycles which act as organizing centers; (c) a crisis region related to the destruction or creation of chaotic attractors; (d) a large Lebesgue measure set of parameters where chaotic regimes are dominant, though sinks and chaotic attractors may coexist, and in whose complement we observe shrimps.

New Improvement of the Domain of Parameters for Newton’s Method

There is a need to extend the convergence domain of iterative methods for computing a locally unique solution of Banach space valued operator equations. This is because the domain is small in general, limiting the applicability of the methods. The new idea involves the construction of a tighter set than the ones used before also containing the iterates leading to at least as tight Lipschitz parameters and consequently a finer local as well as a semi-local convergence analysis. We used Newton’s method to demonstrate our technique. However, our technique can be used to extend the applicability of other methods too in an analogous manner. In particular, the new information related to the location of the solution improves the one in previous studies. This work also includes numerical examples that validate the proven results.

Vibrational Heat Transfer Intensification in an Annulus with a Deformable Boundary

An experimental study is carried out on heat transfer in a horizontal liquid annulus at boundary oscillations. The inner boundary is formed by a copper rod that is heated using electric current. The outer boundary is made of an elastic silicone tube brought to oscillations by two electrodynamic vibrators situated symmetrically on the opposite sides. In the absence of vibrations, a classic natural convection is observed. Vibrations excite steady time-average flows in the fluid. The steady flows make the gravity-induced flow structure transform, and the heat transfer is intensified. In the analysis, it is shown that the heat transfer in the studied system is determined by a competition between the natural convection and steady streaming. A domain of parameters is found where the latter dominates.

Diversity of occupants’ activity impact on indoor air

The problem of indoor air quality (IAQ) has attracted a great deal of attention recently. One of interesting aspects of this problem is the characterization of human impact on IAQ. This work presents a method which allows to determine the diversity of building occupants influence on indoor air. The method is based on the supervised clustering of the indoor air measurement data in domains of various indoor air parameters. The introduced approach was applied to examine the exemplary data set. The diversity of impact was studied in the domain of air parameters which characterize thermal conditions indoors and in the domain of chemical parameters of indoor air. The obtained results showed that the diversity of impact was greatly related to the fact that occupants’ activities occurred in combinations, rather than individually. It was also demonstrated that the diversity of impact was domain dependent. Most of examined activities showed greater diversity of influence in the domain of parameters which characterize thermal conditions. This shows that the activity-specific impacts would be rather associated with the domain of chemical parameters of indoor air. The proposed method allows to obtain information which can be useful in the diagnostics of IAQ and for the control of ventilation.