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Metaheuristic algorithms are extensively employed to solve high-dimensional optimization problems, with particle swarm optimization (PSO) garnering considerable attention for its computational efficiency and simplicity. In tackling time-consuming and complex engineering optimization tasks, PSO typically utilizes cluster computing techniques to aggregate substantial computing resources, thereby accelerating the optimization process. However, this approach may face computational interruptions due to power failures, program crashes, or network instability, thereby impeding the optimization process. Moreover, the dynamic nature of cluster computing resources necessitates efficient resource utilization methods, such as adaptive population size adjustment. In this study, we propose a recoverable PSO to address interruptions during prolonged optimization processes. Building upon this, we further develop an enhanced PSO with adaptive swarm size reduction. The study begins by reviewing and categorizing existing population size reduction strategies and introducing several novel approaches. The effectiveness of these strategies is evaluated using the CEC benchmark test suite, comparing their convergence speed and accuracy. Furthermore, the optimal strategy is validated through three real-world engineering optimization problems under constrained computing resources. The results demonstrate that the proposed method significantly enhances PSO performance, offering valuable insights for future research on population size control in PSO and its engineering applications.

The evolutionary algorithms with shuffling concept divide a population into several groups and then each group try to evolve its members in an independent evolutionary process. In an attempt to increase and diversify search moves and preventing the premature convergence of such algorithms, this paper proposes a meta-heuristic technique by employing several evolutionary processes for different groups. In this strategy, different groups can be evolved using a randomly selected evolutionary process. In accordance with this purpose and to provide an ability of jumping out of local optima, which can be useful for finding global optima in complex optimization problems, four different evolutionary strategies inspired from shuffled frog leaping (SFL), shuffled complex evolution (SCE), shuffled differential evolution (SCE) and opposition-based learning (OBL) are incorporated into a new structure called the shuffled multi-evolutionary algorithm (SMEA). The SMEA is extended with linear population size reduction (LPSR) known as L-SMEA, which continually decreases the population size and number of groups according to a linear function. The SMEA is evaluated on CEC2014 and CEC2017 benchmark functions. The obtained results are compared with SFL, SCE and SDE and other state-of-the-art algorithms proposed in the literatures. Performing the statistical analysis of the obtained results demonstrate that the proposed L-SMEA is superior to other three algorithms including SFL, SCE and SDE and some other state-of-the-art algorithms. Also, the performed experiments indicate the contribution of employing multiple evolutionary strategies beside of linear population size reduction leads to achieving a more effective and robust algorithm than those used single evolutionary strategy.

The fault gouge, a crushed fault rock resulting from seismic slip, exhibits variations in crystallinity and particle size contingent on the magnitude of deformation. Therefore, the fabrication of fault gouge analogues with carefully controlled properties such as crystallinity, grain size, and mineral composition is necessary to systematically study their role in a range of fault slips. While the single mineral fault gouge analogues have been reproduced using a milling method, the fabrication methods for multi-mineralic fault gouge analogues with varying particle size and crystallinity are rarely reported, yet. In this study, we propose two methodologies for fabricating multi-mineralic fault gouges controlling the degree of amorphization and the particle size using a high-energy ball mill: mixing-grinding (MG) and grinding-mixing (GM) types. The MG type was designed to simulate the fault gouge that the same grinding energy is applied to all the constituent minerals, while the GM type can be controlled the degree of deformation of each mineral according to the research objective. To investigate the effects of these methodologies on the reduction in crystallinity and particle size, we compared the characteristics of MG type_6h and GM type_6h samples, both ground for 6 h. Consequently, despite undergoing the same grinding duration, the GM type_6h sample exhibited more significant reduction in crystallinity and more heterogeneous particle size. Additionally, we fabricated the GM type_Xc50 sample, where the crystallinity of all constituent minerals was reduced to < 50%. For this, each mineral was ground for an optimized duration that reduced its crystallinity to < 50%, after which the samples were mixed. Consequently, the GM type_Xc50 sample demonstrated the greatest reduction in crystallinity and the most uniform particle size distribution. To fabricate the generation process of natural fault gouge, it is appropriate to use the MG type to apply the same energy to constituent mineral, resulting the deformation reflecting its hardness. The GM type is recommended for use in fabricating the characteristics of the fault gouge that has undergone intense deformation at the slip surface, which allows for controlling the uniform crystallinity and particle size reduction of each constituent mineral. Our results suggest that the diverse nature of naturally occurring fault gouges can be fabricated in laboratory settings by adjusting the grinding conditions. This study offers effective methods for fabricating fault gouge analogue for frictional experiments for fault slip and potential applications in simulating geochemical reactions in fault zones.

Mineral deformation and rock flow mechanism in the lithosphere are related to the rheological behavior and weakening mechanism of the continent. Natural deformation behaviors of feldspars are not well understood due to the complexity of their mineral compositions, crystal structures, as well as changing deformation conditions. The refined microstructure, fabric and composition of major minerals in the deformed granitic rocks within the Gaoligong shear zone (GLGSZ), southwestern Yunnan, China, were studied. With increasing mylonitization, two fabric types of end-members have been distinguished (type-I banded granitic mylonite and type-II banded ultramylonite). The two types of deformed granitic rocks have the same mineral assemblage, but different mineral modes. The type-I banded granitic mylonite has a greater proportion of K-feldspar (mostly present as porphyroclasts)>plagioclase>quartz±biotite, however, the type-II banded ultramylonite has a greater proportion of fine-grained plagioclase>K-feldspar>quartz±biotite. The crystallographic preferred orientation (CPO) patterns of quartz combined with two-feldspar geothermometer, confirm that the quartz grains in the type-I and type-II granitic rock have undergone high-temperature dislocation creep deformation. The K-feldspar grains in the matrix of type-II banded ultramylonite show a dominant (100) [010] slip system with dislocation creep recrystallization, while the fine-grained plagioclase grains present a weak CPO pattern with superplastic flow. The K-feldspar porphyroclasts show grain-size reduction associated with mineral composition and fabric transformation. The myrmekite formation with the fine-grained neocrystallization of plagioclase and quartz significally replaced the K-feldspar porphyroclasts. Finally, the fine-grained neocrystallization plagioclases were formed further into the high strain localized ultramylonites with superplastic flow.

Particle size reduction by ultrasound is more favorable than conventional grinding due to its tendency to preserve the material’s crystal structure. For palygorskite clay, the optimization was carried out using response surface methodology for the variables of sonication time, power, duty cycle, and clay loading. A 2FI model was fit to the dimensionless size number to navigate the design space of the model with an r -squared value of 0.9662. We found that the most optimal conditions for the size reduction were 45 min of sonication time, 110 W of sonication power, 90% duty cycle and 0.06 g/mL of clay loading. The loading and duty cycle terms had a positive effect on the particle size reduction, while an increase in power increased the particle size of the clay. The effect of time was found to be dependent on the values of the clay loading as well as the duty cycle. The XRD analysis of palygorskite clay for the untreated and treated samples indicated that ultrasound causes minimal changes to the crystal structure of the clay. The overall outcome of the study suggests that at optimal ultrasound conditions, particle size is reduced to ~ 1/16 times the initial value and the electric power input in the ultrasound generator takes an energy requirement of ~ 0.0124 kWh/g of solids processed for size reduction.

An adaptive key of He’s scheme is generated based on the minimum coded unit histogram (MCUH) of an original image, which can improve the ability against the known-plaintext attack while achieving file size preservation and format compatibility. However, it is vulnerable to the chosen-plaintext attack (CPA) since the MCUH, which is unchanged during encryption, can be used to reproduce the adaptive key. To change the MCUH and reduce file size, some alternating current codes (ACCs) are randomly removed and reversibly embedded into the image by variable length code (VLC) mapping. Firstly, the threshold T , i.e., the maximum number of ACCs that can be removed while ensuring a reduced file size of encrypted JPEG image, is adaptively calculated after the monotonicity of VLC mapping is discussed. And then, according to the user’s key, the actual number of ACCs to be removed is randomly selected in the integer interval [1, T ] to reduce the possibility of reproducing the adaptive key under CPA. Experimental results demonstrate that the proposed scheme effectively improves the ability against CPA since the adaptive-key reproduction probability of the proposed scheme is reduced from 100% of He’s scheme to smaller than 1.15 × 10 - 1398 . Moreover, the file size of the encrypted JPEG generated by the proposed scheme is smaller than that of He’s scheme and the original image.

In this paper, we have highlighted some selected significant developments that have taken place during the last ten years or so in our understanding the size reduction of the particulate materials in ball mills using the traditional population balance model. These developments relate to experimental technique and design of experiments, nature of grinding kinetics, estimation of the model parameters, energy–size reduction relationship, and mill scale-up design. The new insight obtained into the ball mill grinding operation can help develop improved approaches to the design and scale-up of ball mills.

Comparison of dry and wet grinding process in an electromagnetic mill is presented in this paper. The research was conducted in a batch copper ore grinding. Batch mode allows for precise parametrization and constant repetitive conditions of the experiments. The following key aspects were tested: processing time, feed size, size of the grinding media, mass of the material and graining media, and density of the pulp. The particles size distribution of the product samples was analyzed in the laboratory after each experiment. The paper discusses the experimental results as well as the concept of dry and wet grinding and classification circuits for the electromagnetic mill. The main points of the discussion are the size reduction effectiveness and power consumption of the entire system.

The roller press crushing of ore is a complex process involving the interplay of multiple factors. Roller dimensions, gap settings, and rotational speed all influence this process, which in turn affects the comprehensive crushing performance of the high-pressure grinding rolls (HPGR). Therefore, to simultaneously enhance the HPGR’s size reduction effectiveness (SRE) and throughput while controlling its energy consumption, wear, and edge effect, multi-objective parameter optimization of the HPGR is required. This study utilizes the Discrete Element Method (DEM) to simulate ore comminution within an HPGR. By first dividing the release zone into segments, the particle size distribution of the crushed product at different locations within this zone is investigated. Then, the influence of various factors on the SRE at different locations within HPGR is examined through single-factor experiments. Subsequently, the relative influence of roller diameter, roller width, roller speed, and roll gap on the comprehensive crushing performance of the HPGR is determined through signal-to-noise ratio (SNR) analysis and analysis of variance (ANOVA). Finally, multi-objective parameter optimization of the roller press crushing is conducted based on grey relational analysis (GRA), incorporating the weights assigned to different response target. The results indicate that the proportion of unbroken ore particles is relatively significant, primarily due to the edge effect. Further analysis reveals that along the horizontal diameter of the rollers, regions closer to the roller surface exhibit better SRE. Additionally, roller speed is identified as the most influential factor affecting the uniformity of SRE in the HPGR. The application of GRA to the multi-objective optimization of roller press crushing enables effective balancing of the comprehensive crushing performance in HPGR.

Wheat bran consumption is associated with several health benefits, but its incorporation into food products remains low because of sensory and technofunctional issues. Besides, its full beneficial potential is probably not achieved because of its recalcitrant nature and inaccessible structure. Particle size reduction can affect both technofunctional and nutrition-related properties. Therefore, in this study, wet milling and cryogenic milling, two techniques that showed potential for extreme particle size reduction, were used. The effect of the milling techniques, performed on laboratory and large scale, was evaluated on the structure and physicochemical properties of wheat bran. With a median particle size (d50) of 6 µm, the smallest particle size was achieved with cryogenic milling on a laboratory scale. Cryogenic milling on a large scale and wet milling on laboratory and large scale resulted in a particle size reduction to a d50 of 28–38 µm. In the milled samples, the wheat bran structure was broken down, and almost all cells were opened. Wet milling on laboratory and large scale resulted in bran with a more porous structure, a larger surface area and a higher capacity for binding water compared to cryogenic milling on a large scale. The extensive particle size reduction by cryogenic milling on a laboratory scale resulted in wheat bran with the highest surface area and strong water retention capacity. Endogenous enzyme activity and mechanical breakdown during the different milling procedures resulted in different extents of breakdown of starch, sucrose, β-glucan, arabinoxylan and phytate. Therefore, the diverse impact of the milling techniques on the physicochemical properties of wheat bran could be used to target different technofunctional and health-related properties.