Systeme Ga2S3FeS — Diagramme de phase — etude cristallographique

The system was studied by DTA, X-ray diffraction and in particular by the Guinier-Lenné method. Eight intermediate phases are described. 1) Three solid solutions in the Ga₂S₃ region : a) a wurtzite-type solid solution (T > 1000° C ; 0.05 < n < 0.23) (n = Fe $\text{at}\text{Fe}$ at+Ga at), b) a blende-type solid solution (700°C < T < 980°C ; 0.10 < n < 0.20) with many stacking faults, c) a non-stoichiometric hexagonal phase α'Ga₂S₃ type (T < 700°C, 0.07 < n < 0.12). 2) for n = 0.20 and T = 540°C a superstructure of orthorhombic wurtzite-like array FeGa₄S₇. 3) From n = 0.20 through n = 0.27, a non stoichiometric superstructure of tetragonal-like array has the CdGa₂S₄ type (600°C < T < 1030°C). 4) For n = 0.33, the FeGa₂S₄ has two forms depending from the temperature : a) a low temperature form is trigonal ; b) a high temperature form is orthorhombic type ZnAl₂S₄. Transition temperature is 1010°C. 5) For n = 0.50, Fe₂Ga₂S₅ polytypes : a) Fe₂Ga₂S₅α 1T type Mn₂Ga₂S₅ ; b) Fe₂Ga₂S₅ 2H ; c) Fe₂Ga₂S₅ 3R type Mn₂Al₂Se₅. A phase diagram is proposed.     

Identification of pneumatic artificial muscle manipulators by a MGA-based nonlinear NARX fuzzy model

This study investigates the technique of modeling and identification of a new dynamic NARX fuzzy model by means of genetic algorithms. In conventional identification techniques, there are difficulties such as poor knowledge of the process, inaccurate process or complexity of the resulting mathematical model. All these factors deteriorate the identification performance when dealing with dynamic nonlinear industrial processes. To overcome these difficulties, this paper proposes a novel approach by using a modified genetic algorithm (MGA) combined with the predictive capability of nonlinear ARX (NARX) model for generating the dynamic NARX Takagi–Sugeno (TS) fuzzy model. The MGA algorithm processes the experimental input–output training data from the real system and optimizes the NARX fuzzy model parameters. This is referred to as fuzzy identification, which automatically generates the appropriate fuzzy if-then rules to characterize the dynamic nonlinear features of the real plant. The prototype pneumatic artificial muscle (PAM) manipulator, being a typical nonlinear and time-varying system, is used as a test system for this novel approach. This result shows that, with this MGA-based modeling and identification, the novel NARX fuzzy model identification approach to the PAM manipulator achieved highly outstanding performance and high precision as well. The accuracy of the proposed MGA-based NARX fuzzy model proves excellent in comparison with the MGA-based TS fuzzy model and the conventional GA-based TS fuzzy model.     

Performance Bound for LDPC Coded Unitary Space–Time Modulation

This paper is concerned with the bit error probability (BEP) of coded unitary space–time modulation systems based on finite-length low density parity check (LDPC) codes. The union bound on the BEP of the maximum likelihood (ML) decoding is derived for any code rate, unitary space–time constellation and mapping. The tightness of the bound is checked with simulation results of the ordered statistic decoding (OSD). Numerical and simulation results show that the union bound is also close to the error performance of the sum–product (SP) decoding at low BEP levels when Gray mapping is employed. The derived bound is useful to benchmark the error performance of finite-length coded unitary space–time modulation systems, especially for those that employ short-to-medium length LDPC codes.

On the Catalytic Activity of Sn Monomers and Dimers at Graphene Edges and the Synchronized Edge Dependence of Diffusing Atoms in Sn Dimers

In this study, in situ transmission electron microscopy is performed to study the interaction between single (monomer) and paired (dimer) Sn atoms at graphene edges. The results reveal that a single Sn atom can catalyze both the growth and etching of graphene by the addition and removal of C atoms respectively. Additionally, the frequencies of the energetically favorable configurations of an Sn atom at a graphene edge, calculated using density functional theory calculations, are compared with experimental observations and are found to be in good agreement. The remarkable dynamic processes of binary atoms (dimers) are also investigated and is the first such study to the best of the knowledge. Dimer diffusion along the graphene edges depends on the graphene edge termination. Atom pairs (dimers) involving an armchair configuration tend to diffuse with a synchronized shuffling (step-wise shift) action, while dimer diffusion at zigzag edge terminations show a strong propensity to collapse the dimer with each atom diffusing in opposite directions (monomer formation). Moreover, the data reveals the role of C feedstock availability on the choice a single Sn atom makes in terms of graphene growth or etching. This study advances the understanding single atom catalytic activity at graphene edges.     

Development of ensemble machine learning approaches for designing fiber-reinforced polymer composite strain prediction model

Engineering with Computers - Over the past few decades, it has been observed a remarkable progression in the development of computer aid models in the field of civil engineering. Machine learning...     

Ultrawideband high‐gain dual‐polarized antenna with anti‐interference capability

In this article, a high‐gain dual‐polarized antenna with band‐rejection capability for ultrawideband (UWB) applications is proposed. Tapered dipoles are chosen as a primary radiator to achieve UWB operation and it is reflected by a metallic cavity reflector for high gain radiation. A notch at WLAN band is realized by etching a set of four bent slots in the radiating elements. The measured results demonstrate that the proposed design with overall dimensions of 0.69λ _L × 0.69λ _L × 0.16λ _L (λ _L is free‐space wavelength at the lowest operating frequency) has operating bandwidth of 95.1% (3.2‐9.0 GHz) and the rejected frequency band from 5.0 to 5.9 GHz. Additionally, good unidirectional radiation patterns with a broadside gain from 8.1 to 11.5 dBi and radiation efficiency of better than 90% are also achieved.     

Ultrawideband circularly polarized antenna with dual band‐notched characteristics

This article presents an ultrawideband (UWB) crossed dipole antenna with circularly polarized (CP) and dual band‐notched characteristics. The proposed design is based on two orthogonal tapered dipoles for UWB CP operation and a square‐shaped cavity for high broadside gain over the entire operating bandwidth (BW). To generate dual band‐notched characteristics, two separated slots are inserted into each dipole's arm. This antenna yields measured impedance BW of 100% (3.2‐9.6 GHz) with dual‐band rejection centered at 5.2 and 5.8 GHz. Correspondingly, dual rejected bands are also observed in the original UWB CP band, which ranges from 3.2 to 8.2 GHz. Additionally, the proposed antenna exhibits high broadside gains better than 6.2 dBic and radiation efficiency greater than 82%.     

Broadband circularly polarized Fabry‐Perot antenna utilizing Archimedean spiral radiator and multi‐layer partially reflecting surface

This article presents a method to design broadband circularly polarized (CP) Fabry‐Perot Resonator (FPR) antenna. The proposed antenna is based on multi‐layer thin dielectric slabs arranged in close proximity as a partially reflecting surface (PRS) and an Archimedean spiral as a CP radiating source. Experimental results show a broadband operation from 6 to 13 GHz, in which the reflection coefficient is less than ?10 dB and the axial ratio (AR) is lower than 3 dB. In addition, good radiation patterns and high broadside gain of better than 10.8 dBic are achieved over the operating bandwidth. The proposed antenna can be used for C‐ and X‐band satellite communications.     

A calibration framework for discrete element model parameters using genetic algorithms

In this research, a universal framework for automated calibration of microscopic properties of modeled granular materials is proposed. The proposed framework aims at industrial scale applications, where optimization of the computational time step is important. It can be generally applied to all types of DEM simulation setups. It consists of three phases: data base generation, parameter optimization, and verification. In the first phase, DEM simulations are carried out on a multi-dimensional grid of sampled input parameter values to generate a database of macroscopic material responses. The database and experimental data are then used to interpolate the objective functions with respect to an arbitrary set of parameters. In the second phase, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the calibration multi-objective optimization problem. In the third phase, the DEM simulations using the results of the calibrated input parameters are carried out to calculate the macroscopic responses that are then compared with experimental measurements for verification and validation.The proposed calibration framework has been successfully demonstrated by a case study with two-objective optimization for the model accuracy and the simulation time. Based on the concept of Pareto dominance, the trade-off between these two conflicting objectives becomes apparent. Through verification and validation steps, the approach has proven to be successful for accurate calibration of material parameters with the optimal simulation time.