Cellular automata simulation of recrystallization at hot crack surfaces

In this paper, we study 2-dimensional nite cellular automata dened by hexagonal local rule with periodic boundary over the eld Z3.We construct the rule matrix corresponding to the hexagonal cellular automata.For some given coecients and the number of columns of hexagonal information matrix, we prove that the hexagonal cellular automata are reversible.

Cellular Automata (CA) is used in pseudo-random number generators (PRNG) to produce high-rate random numbers. The randomness of such numbers directly depends upon the CA rules and the number of neighbor cells. The two-dimensional (2D) CA has several limitations such as, finding the best CA rules, boundary cell problems, etc. To address the problems existing in the 2D CA, we propose a random number generator based on 3D cellular automata. The proposed generator is based on rule numbers 43, 85, 170, and 201, and incremental boundary conditions. The rules are randomly changed after each cycle depending on a clock bit mechanism. The output bits are then passed to the Diehard and ENT test suites to test its randomness [1]. The results reveal that the bit stream generated by the proposed scheme passes all the tests present in the test suites.

The non-orthogonal multiple access-passive optical network (NOMA-PON) is facing the dual security threats of primary user interference and unauthorized third-party user eavesdropping, so efficient data security enhancement techniques are crucial. To solve these problems, we propose a fixed-point extended (FE)-logistic chaotic mapping to reduce the computational complexity while employing a two-dimensional (2D) cellular automata (CA) and Turing pattern (TP) cascading scramble (CA-TPCS) encryption algorithm to further improve the sensitivity of the NOMA-PON system. The CA-TPCS consists of 2D-CA dynamic bit encryption and Turing symbol substitution (TSS). By using FE chaos to construct 2D-CA and adopting index sort to extract the TSS matrix, dynamic diffusion of bits and scrambling of a 2D symbol matrix are achieved. To ensure the key privacy, we employ a dual key mechanism, and uplink data is introduced as the private key. To verify the feasibility of the proposed method, a simulation validation is built on a 17.6 Gb/s power division multiplexing-orthogonal frequency division multiplexing (PDM-OFDM) NOMA-PON system transmitted over 25 km standard single mode fiber (SSMF). The results show that the proposed scheme has no effect on the optimal power allocation rate (PAR) values and the values are all 3. Meanwhile, the receiver sensitivity gains of 0.2 and 0.3 dB are obtained for high-power and low-power users after encryption. The ciphertext has good diffusion and statistical properties, and the key space is flexibly controlled by the FE precision f, the length l of the transmitted bit, and the size T of the TP, with the value of 22f+l+T×T. The results show that the proposed scheme is not only very compatible with PDM technology but also can realize the dual defense of internal aggression and external aggression. It has a good application prospect in the future NOMA-PON.

The defects responsible for the permanent component observed in negative bias temperature (NBT) stressed metal-oxide-semiconductor field effect transistors with an oxynitride gate insulator were investigated by using isochronal annealing experiments, spin dependent recombination (SDR), and spin dependent tunneling (SDT) technique. Two defects were found in the permanent component after light NBT stresses; interface states (Dit) and fixed positive charges (Dpc), which are closely related. The data support a model where hydrogen emitted from interfacial Si-H bonds by NBT stresses reacts with Si-X-Si structures (X = oxygen or nitrogen) in the gate insulator, which leaves silicon dangling bonds (Dit) and leads to the generation of Si-X+H-Si (overcoordinated oxygen or nitrogen, Dpc). Heavy NBT stresses simultaneously accelerate the formation and generation of new defects, which act as additional Dit and Dpc. Moreover, these defects cause stress-induced leakage current. Concerning their origin, defects similar to K- and E′γ-centers were detected by using SDR and SDT. They are unrelated to hydrogen and can be formed through the breaking of Si-X bonds. On the basis of these results, we propose a model for the generation and recovery behavior of defects and present a comparison with the previous studies.

Feature Extraction is a long active topic in image processing, and it attracts lots of attention over the last five decades due to its uses in real-life applications. Edge detection method allows users to discover the features of an image for a notable change in the gray level. This texture indicates an ending of one region and the beginning of another in the image. Likewise, over the last few decades, researchers have been exploring to exploit the simple computing model of Cellular Automata (CA) with local neighborhood structure in image processing techniques. The usage of CA in applications of medical image-processing is identified by Kendall Preston [1] in 1979. It is found that edge detection using CA has a potential advantage over traditional approaches for its lightweight nature and computational efficiency. This paper introduces a new technique for image edge detection using two-dimensional CA. The method can use specific rule sets of CA using the Von Neumann neighborhood for edge detection with null boundary conditions. The performance analysis of the scheme is done and compared with some existing standard edge detection techniques. The results obtained from the proposed technique is very promising for feature extraction.

An approach based on an application of cellular automata (CA) to the problem of two-dimensional (2D) patterns or images reconstruction from ones with only partial information available is presented in the paper. 2D CA are used to process patterns/images, and genetic algorithm (GA) is applied to discover CA rules, which will be able to reconstruct original patterns/images from, e.g. destroyed or modified ones. A number of experiments have been conducted to reconstruct patterns and human face images with use of the proposed approach. Results of experiments show that CA rules discovered by GA in the learning process allow to reconstruct images with large number of damaged pixels.

Freestanding nanocrystalline Au films, subjected to nominally elastic loads at 25–110 °C, demonstrated high primary (10−7–10−4 s−1) and steady-state creep rates (10−8–10−5 s−1). The deformation mechanisms for creep were strongly temperature dependent: grain boundary sliding-based creep dominated at room temperature and 50 °C, while the contribution of dislocation-mediated creep increased at 80 and 110 °C. The effect of applied stress on primary and steady-state creep strain at different temperatures was captured well by a non-linear model that was based on the kinetics of thermal activation. Multi-cycle creep experiments showed that at room temperature virtually all the primary strain accumulated during each forward creep cycle was recovered upon complete unloading. As the contribution of dislocation-mediated creep increased with temperature, the ratio of strain recovery to primary strain accumulated during each cycle was reduced due to the accumulation of plastic strain at higher temperatures. Notably, at all temperatures, the steady-state creep rate decreased after the first creep cycle. Moreover, the entire creep response remained virtually unchanged in all subsequent cycles, which implies that the first creep cycle resulted in mechanical annealing. This conclusion was further supported by calculations of the activation entropy: A reduction in its magnitude between the first and all subsequent creep cycles at all temperatures pointed out to mechanical annealing of initial material defects during the first loading cycle. The negative values of the calculated activation entropy indicated that entropy changes due to annihilation of defects-dominated entropy changes associated with the generation of new defects. Finally, the activation entropy for steady-state creep was temperature insensitive, but increased with stress, which is consistent with an increase in defect generation at higher stresses.

A cellular automation method is one of calculation methods, which allows for modeling of complex joint phenomena that take place in material during and after the deformation in the meso‐ and micro‐scale. The phenomena, which can be taken into consideration with high precision, are processes connected with microstructure evolution. For modeling by cellular automata (CA) are mainly used two‐dimensional ones, because of more expensive calculations by three‐dimensional CA. But three‐dimensional phenomena cannot be generally reduced to two‐dimensional solution. In the paper a description of a modified three‐dimensional CA is presented. The model of microstructure contains three parts: deformation of grains, recrystallization and grains growth after recrystallization. Recrystallization is considered as a process without division on the different kinds (dynamic, metadynamic or static). It consists of two stages: nucleation and new grains growth. Nucleation rate and grain growth rate are dependent on parameters of deformation. In the model such parameters as temperature, strain, strain rate, dislocation density, crystallographic orientation and some others are taken into account. Along with calculation of microstructure evolution, model allows for prediction of mechanical properties, for example flow stress. A flow stress calculations reckon processes of hardening and softening using model of the dislocation density development in consideration with an effect of the recrystallization. Some results of simulations based on 3D cellular automaton are presented in the paper.

Cellular automata (CA) are known for their capability in exhibiting interesting emergent behaviour and capacity to generate complex and often aesthetically appealing patterns through the local interaction of rules. Mean information gain has been suggested as a measure of discriminating structurally different two-dimensional (2D) patterns. This paper addresses quantitative evaluation of the complexity of CA generated configurations. In particular, we examine information gain as a spatial complexity measure for discriminating multi-state 2D CA generated configurations. This information-theoretic quantity, also known as conditional entropy, takes into account conditional and joint probabilities of cell states in a 2D plane. The effectiveness of the measure is shown in a series of experiments for multi-state 2D patterns generated by CA. The results of the experiments show that the measure is capable of distinguishing the structural characteristics including symmetries and randomness of 2D CA patterns.

A novel agent based, artificial life model, for the evolution of mimicry is presented. This model is a predator-prey co-evolution scenario where pattern representation phenotype is simulated with Cellular Automata, while behaviors of pattern recognition is configured with Hopfield Network. A visual three dimensional toroidal cube is used to construct a universe in which agents have complete freedom of mobility, genetic representation of behavior and reproduction capability to evolve new behaviors in successive generations. These agents are classified into categories of predator and prey species. Genome of prey species control their mobility and palatability, while 2D Cellular Automata (CA) is used to represent a pattern, where the rule to generate the CA is also genetically represented. Through evolution, successive generations of prey species develop new patterns to represent them both visually and to the predators. Predators are agents with the primary purpose of providing selection pressure for the evolution of mimicry. They are equipped with Hopfield Network memory to recognize new CA pattern and make intelligent decisions to consume the prey based on their level of palatability. Using the above construction of ideas, successful emulation of the natural process of mimicry is achieved. Also complex behavior pattern of Batesian and Mullerian mimicry is simulated and studied.

We propose a transient recombination-enhanced defect-generation model to analyze the degradation of optical output powers of blue-green II–VI light-emitting diodes (LEDs). We find an analytical solution and discover a set of universal curves for the time dependence of optical output power, which agree very well with the experimental data for strained CdZnSe quantum-well structures. Our model shows that the optical power can be non-exponential in character and its long-time behavior has a 1/t dependence. This 1/t dependence is also related to the growth of the defect density, which should behave as a t1/2 dependence. The generation of new defects due to electron-hole recombination at the defect sites is found to be the dominant degradation mechanism for II–VI LEDs.

Doping-induced strains in 4H-SiC epilayers may lead to the generation of new defects which could degrade the performance and reliability of devices. In materials or devices of 4H-SiC doped by N or Al ion implantation, interfacial dislocations on the basal plane at the bottom of implanted layers after activation annealing have been reported in the literature. However, the formation mechanism remains unclear. In this paper, the resolved shear stress on the basal plane contributed by ion implantation and annealing processes is analyzed. The c-lattice and a-lattice strains induced by N and Al ion implantation into 4H-SiC epilayers before and after activation annealing are measured by high-resolution X-ray diffraction. The conditions of interfacial dislocation formation after ion implantation and activation annealing are discussed.

Statistical model and structural reliability analysis for onshore gas transmission pipelines

Basic idea of encryption is to encrypt the pixels of an image in such a manner that the image becomes chaotic and indistinguishable. In this paper, we have done exploratory study on image encryption techniques through 2D cellular automata (single layer and double layer) which create chaos on pixels of considered image. A comparative analysis on effectiveness of scrambling technique is provided by scrambling degree measurement parameters, i.e., gray difference degree (GDD) and correlation coefficient. Experimental results showed that the 2D cellular automata (single layer)-based encryption gives better result than 2D cellular automata (double layer).

A cellular automaton finite volume method for microstructure evolution during additive manufacturing