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This paper aims to propose a deployment optimization and efficient synchronous acquisition method for compressive stress sensors used by stress distribution law research based on the genetic algorithm and numerical simulations. The authors established a new method of collecting the mining compressive stress-strain distribution data to address the problem of the number of sensors and to optimize the sensor locations in physical similarity simulations to improve the efficiency and accuracy of data collection.

First, numerical simulations were used to obtain the compressive stress distribution curve under specific mining conditions. Second, by comparing the mean square error between a fitted curve and simulation data for different numbers of sensors, a genetic algorithm was used to optimize the three-dimensional (3D) spatial deployment of sensors. Third, the authors designed an efficient synchronous acquisition module to allow distributed sensors to achieve synchronous and efficient acquisition of hundreds of data points through a built-in on-board database and a synchronous sampling communication structure.

The sensor deployment scheme was established through the genetic algorithm, A synchronous and selective data acquisition method was established for reduced the amount of sensor data required under synchronous acquisition and improved the system acquisition efficiency. The authors obtained a 3D compressive stress distribution when the advancement was 200 m on a large-scale 3D physical similarity simulation platform.

The proposed method provides a new optimization method for sensor deployment in physical similarity simulations, which improves the efficiency and accuracy of system data acquisition, providing accurate acquisition data for experimental data analysis.

In this study, a physical similarity simulation plays a significant role in the study of crack evolution and the gas migration mechanism. A sensor is deployed inside a comparable artificial rock formation to assure the accuracy of the experiment results. During the building of the simulated rock formation, a huge volume of acidic gas is released, causing numerous sensor measurement mistakes. Additionally, the gas concentration estimation approach is subject to uncertainty because of the complex rock formation environment. As a result, the purpose of this study is to introduce an adaptive Kalman filter approach to reduce observation noise, increase the accuracy of the gas concentration estimation model and, finally, determine the gas migration law.

First, based on the process of gas floatation-diffusion and seepage, the gas migration model is established according to Fick’s second law, and a simplified modeling method using diffusion flux instead of gas concentration is presented. Second, an adaptive Kalman filter algorithm is introduced to establish a gas concentration estimation model, taking into account the model uncertainty and the unknown measurement noise. Finally, according to a large-scale physical similarity simulation platform, a thorough experiment about gas migration is carried out to extract gas concentration variation data with certain ventilation techniques and to create a gas chart of the time-changing trend.

This approach is used to determine the changing process of gas distribution for a certain ventilation mode. The results match the rock fissure distribution condition derived from the microseismic monitoring data, proving the effectiveness of the approach.

For the first time in large-scale three-dimensional physical similarity simulations, the adaptive Kalman filter data processing method based on the inverse Wishart probability density function is used to solve the problem of an inaccurate process and measurement noise, laying the groundwork for studying the gas migration law and determining the gas migration mechanism.

This study aims to clarify the evolution law of stress field and fracture field during the mining process of inclined coal seam, to prevent the occurrence of roof burst water and impact ground pressure accident during the advancing process of working face.

The evolution law of stress-fracture field under different mining conditions of inclined coal seam was studied by using discrete element method and similar material simulation method.

The overburden stress at the lower end of the coal seam was mainly transmitted to the deep rock mass on the left side, and the overburden stress at the upper end was mainly transmitted to the floor direction. With the increase of the inclined length of the mining coal seam, the development of the fracture zone gradually evolves from the “irregular arch” form to the “transversely developed trapezoid” form. The development range of the fracture zone was always in the internal area of the stress concentration shell.

An original element of this paper is based on the condition that the dip angle of coal seam is 35°, and the evolution law of overburden stress-fracture field during the excavation of coal seam with different lengths was analyzed by UDEC numerical simulation software. The coupling relationship between stress shell and fracture field was proposed, and the development range of fracture zone was determined by stress. The value of this paper is to provide technical support and practical basis for the safety production of a mine working face.

The main purpose of this paper is to present a comprehensive upscale theory of the thermo-mechanical coupling particle simulation for three-dimensional (3D) large-scale non-isothermal problems, so that a small 3D length-scale particle model can exactly reproduce the same mechanical and thermal results with that of a large 3D length-scale one.

The objective is achieved by following the scaling methodology proposed by Feng and Owen (2014).

After four basic physical quantities and their similarity-ratios are chosen, the derived quantities and its similarity-ratios can be derived from its dimensions. As the proposed comprehensive 3D upscale theory contains five similarity criteria, it reveals the intrinsic relationship between the particle-simulation solution obtained from a small 3D length-scale (e.g. a laboratory length-scale) model and that obtained from a large 3D length-scale (e.g. a geological length-scale) one. The scale invariance of the 3D interaction law in the thermo-mechanical coupled particle model is examined. The proposed 3D upscale theory is tested through two typical examples. Finally, a practical application example of 3D transient heat flow in a solid with constant heat flux is given to illustrate the performance of the proposed 3D upscale theory in the thermo-mechanical coupling particle simulation of 3D large-scale non-isothermal problems. Both the benchmark tests and application example are provided to demonstrate the correctness and usefulness of the proposed 3D upscale theory for simulating 3D non-isothermal problems using the particle simulation method.

The paper provides some important theoretical guidance to modeling 3D large-scale non-isothermal problems at both the engineering length-scale (i.e. the meter-scale) and the geological length-scale (i.e. the kilometer-scale) using the particle simulation method directly.

The purpose of this paper is to present an upscale theory of the thermal-mechanical coupling particle simulation for non-isothermal problems in two-dimensional quasi-static system, under which a small length-scale particle model can exactly reproduce the same mechanical and thermal results with that of a large length-scale one.

The objective is achieved by extending the upscale theory of particle simulation for two-dimensional quasi-static problems from an isothermal system to a non-isothermal one.

Five similarity criteria, namely geometric, material (mechanical and thermal) properties, gravity acceleration, (mechanical and thermal) time steps, thermal initial and boundary conditions (Dirichlet/Neumann boundary conditions), under which a small-length-scale particle model can exactly reproduce both the mechanical and thermal behavior with that of a large length-scale model for non-isothermal problems in a two-dimensional quasi-static system are proposed. Furthermore, to test the proposed upscale theory, two typical examples subjected to different thermal boundary conditions are simulated using two particle models of different length scale.

The paper provides some important theoretical guidances to modeling thermal-mechanical coupled problems at both the engineering length scale (i.e. the meter scale) and the geological length scale (i.e. the kilometer scale) using the particle simulation method directly. The related simulation results from two typical examples of significantly different length scales (i.e. a meter scale and a kilometer scale) have demonstrated the usefulness and correctness of the proposed upscale theory for simulating non-isothermal problems in two-dimensional quasi-static system.

In today's knowledge-based economy, the ability to produce highly novel and practical ideas is critical to an organization's survival. This paper draws upon social perspectives of creativity (Perry-Smith & Shalley, 2003) and the vital role of recombinant information in creative development (Barron & Harrington, 1981; Hargadon, 2003) to explore information exchange probabilities; exchanges among group members who are deep-level similar fosters incremental creative potential while information exchanges among group members who are deep-level dissimilar fosters radical creative potential. The dynamics of attraction suggest group members are most likely to interact with people who are least likely to facilitate radical creativity. Using a computer simulation we examine how proximity may be used to facilitate information exchanges among deep-level diverse group members to increase the potential for radical creativity. Results suggest the use of proximity to create strong ties among deep-level dissimilar group members may facilitate radical creativity in groups.

While each genre and gender has been revealed as significant moderators for esports gameplay intention, exploring the interaction effects between genre and gender could broaden our understanding of the drivers’ relative effects on esports gameplay intention. Thus, the purpose of this study is to examine the interaction effects of gender and genre in the relationship between esports gameplay intention and its drivers (i.e. hedonic motivation, habit, price value, effort expectancy, social influence and flow).

The hypothesized model was examined using data from a sample (N = 1,194). For the purposes of data analysis, confirmatory factor analysis and structural equation modeling were used to examine the hypothesized model. Then, a series of structural invariance tests were conducted to compare the interrelationship between the six determinants and esports gameplay for the six-group model.

The results of the six-group model comparison indicated that the interaction between gender and genre moderates the relationship between drivers and esports gameplay intention. In particular, the following moderation effects were observed: (1) “social influence-esports gameplay intention” between “male-physical enactment” and “female-physical enactment”; (2) “habit-esports gameplay intention” and (3) “effort expectancy-esports gameplay intention” between “female-imagination” and “female-physical enactment”; (4) “hedonic motivation-esports gameplay intention” and (5) “effort expectancy-esports gameplay intention” between “female-physical enactment” and “female-sport simulation.”

The findings of this current study contributed to clarifying the genre and gender effects in esports gameplay intention and thus the extension of the Esports Consumption (ESC) model (Jang et al., 2020a) and the technology adoption literature. Since the ESC model grounded the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the improvement of the ESC model extended UTAUT2. In consumer behavior research in the esports context, this current study contributed to the extension of UTAUT2 on the new moderating mechanisms by adding the interaction between gender and esports game genre.

The purpose of this work is to investigate the similarity requirements for the application of multifidelity modeling (MFM) for the prediction of airfoil dynamic stall using computational fluid dynamics (CFD) simulations.

Dynamic stall is modeled using the unsteady Reynolds-averaged Navier–Stokes equations and Menter's shear stress transport turbulence model. Multifidelity models are created by varying the spatial and temporal discretizations. The effectiveness of the MFM method depends on the similarity between the high- (HF) and low-fidelity (LF) models. Their similarity is tested by computing the prediction error with respect to the HF model evaluations. The proposed approach is demonstrated on three airfoil shapes under deep dynamic stall at a Mach number 0.1 and Reynolds number 135,000.

The results show that varying the trust-region (TR) radius (λ) significantly affects the prediction accuracy of the MFM. The HF and LF simulation models hold similarity within small (λ ≤ 0.12) to medium (0.12 ≤ λ ≤ 0.23) TR radii producing a prediction error less than 5%, whereas for large TR radii (0.23 ≤ λ ≤ 0.41), the similarity is strongly affected by the time discretization and minimally by the spatial discretization.

The findings of this work present new knowledge for the construction of accurate MFMs for dynamic stall performance prediction using LF model spatial- and temporal discretization setup and the TR radius size. The approach used in this work is general and can be used for other unsteady applications involving CFD-based MFM and optimization.

The purpose of this paper is to develop a similarity evaluation method between virtual and actual clothing.

The paper analyzes the subjective and objective evaluation results of virtual and actual clothing.

In this paper, significant factors affecting the evaluation of similarity between actual and virtual clothing have been found.

Evaluation experiment was performed only for a skirt. However, the method can be easily applied for other types of garments.

The evaluation of similarity between actual and virtual garment will be facilitated.

The garment design process can be facilitated by simulating garments in virtual space.

There has not been any quantitative evaluation method for the similarity of virtual and actual garment.

This paper aims to clarify the relationship between mechanical behaviors and the underlying geometry of periodic cellular structures. Particularly, the answer to the following research question is investigated: Can seemingly different geometries of the repeating unit cells of periodic cellular structure result in similar functional behaviors? The study aims to cluster the geometry-functional behavior relationship into different categories.

Specifically, the effects of the geometry on the compressive deformation (mechanical behavior) responses of multiple standardized cubic periodic cellular structures (CPCS) at macro scales are investigated through both physical tests and finite element simulations of three-dimensional (3D) printed samples. Additionally, these multiple CPCS can be further nested into the shell of 3D models of various mechanical domain parts to demonstrate the influence of their geometries in practical applications.

The paper provides insights into how different CPCS (geometrically different unit cells) influence their compressive deformation behaviors. It suggests a standardized strategy for comparing mechanical behaviors of different CPCS.

This paper is the first work in the research domain to investigate if seemingly different geometries of the underlying unit cell can result in similar mechanical behaviors. It also fulfills the need to infill and lattify real functional parts with geometrically complex unit cells. Existing work mainly focused on simple shapes such as basic trusses or cubes with spherical holes.