Modeling Of Multilayer Structures Research Articles

Plasticity analysis and a homogenized constitutive model of compressible multi-layer structure of battery

A homogenized constitutive model for the compressible multi-layer structure of battery (CMLSB) under external loading is essential for optimizing the structural design of electric assemblies. Currently, there is no specific constitutive model that is both mechanically explanatory and operationally applicable to CMLSB under varied loading conditions. In this study, due to limited understanding of the in-plane behavior of CMLSB, an analytical model was developed to investigate plasticity in this specific direction using the strain probing method. The observed plastic characteristics inspired the formulation of a novel two-dimensional constitutive framework for CMLSB in the in-plane direction.By integrating this new constitutive framework with one-dimensional plastic descriptions, a hybrid constitutive model was introduced and implemented in finite element software. Calibration and validation of the model were performed using a commercial pouch cell battery and its segments under various loading conditions. Finite element simulations with the hybrid model demonstrated remarkable accuracy in predicting the mechanical behavior of the cell under various in-plane and out-of-plane compression scenarios. Additionally, simulations were carried out to analyze the impact of cell packaging and air pressure. The new hybrid battery model is considered a user-friendly, physically interpretable, and high-fidelity tool, poised to significantly facilitate the comprehensive design of electric devices.

N-level complex helical structure modeling method

This paper primarily explores the modeling method of n-level complex helical structures with coal mining machine cables as the research object. The paper first elaborately introduces the modeling method of n-level helix curves based on parametric equations and coordinate transformations, and compensates for the n-level helix curves with corrected pitch, which can obtain more accurate n-level helix curves and improve the accuracy of n-level helix curves modeling. Subsequently, based on this high-precision n-level helix curves modeling method, the paper elaborates on the method of solving pitch and twisting radius of multi-layer helical structure. Calculation scripts were written based on the above methods, which can be used to batch calculate the twisting radius and pitch of each layer structure in multi-layer structures when satisfying the conditions of in-layer tangency, inter-layer tangency, and extrusion deformation, and retain the actual results through logical judgment. Then, based on the above two methods, the paper developed a modeling method for braided structures based on piecewise functions containing fifth-order polynomials, which can effectively avoid the problem of insufficiently dense arrangement of braided lines and easy interference in traditional methods. Finally, a set of modeling tools was developed using C# and Python in Grasshopper to implement the modeling algorithm. Taking the MCPT-1.9/3.3 3120 + 170 + 4 * 10 coal mining machine cable as an example. The cable was modeled using both the method proposed in this paper and the traditional method. Comparative data shows that the method proposed in this paper can reduce errors by 3.31E6 times in the second-level and above helical structures. In addition this paper compares the standard line length, measured line length, and the line length established by the proposed model, showing that the relative errors are both less than 0.1941%. This paper provides a new, systematic, high-precision, and full-process cable modeling method, in which all parameters except the process parameters are accurately solved by equations. It lays a theoretical foundation for the high-precision simulation and intelligent sensing cables, which is of great significance for improving the safety, stability, and efficient development of the coal mining industry. The research results of the paper can not only be applied to the modeling of coal mining machine cables but also can be extended to the modeling of other complex multi-layer helical structures.

Research on accident early warning of metallurgical enterprises based on grey DEMATEL/ISM and Bayesian network

To clarify the complex relationship between the factors causing safety accidents in metallurgical enterprises and predict the risk of accidents in enterprises, a correlation analysis model of the factors causing safety accidents in metallurgical enterprises based on grey Decision-Making Trial and Evaluation Laboratory/Interpretative Structural Modeling (DEMATEL/ISM) was established, and a Bayesian network early warning model was constructed on this basis. The relationship and action path of accident-causing factors in metallurgical enterprises were clarified. The factors were hierarchically divided and a multi-layer hierarchical structure model was established to obtain the neighboring cause, transitional cause, and essential cause of the accident. The results showed that the employee violation rate, the hazardous substances reserves, the toxic gas and dust pollution control compliance rate, the pass rate for equipment maintenance, and the qualification rate of special equipment were the neighboring causes of the accident. The perfection of the safety production management system was the essential cause. The Bayesian network early warning model was applied to the Fuxin Jiuxing Titanium work site. The expected risk probability of an accident was 17.9%, which was in a comparatively safe state (State2). The results obtained by the Bayesian model are consistent with those obtained by AHP and fuzzy comprehensive evaluation method, which proved the accuracy of the early warning model. The Bayesian model can give the risk probability value of the accident and the risk probability value of the accident cause factors at the same time, and include the causal relationship and conditional correlation relationship among the indicator variables in the reasoning process, which can provide targeted technical support for the construction of the emergency system of risk classification management and control.

Research on the virtual design and implementation of colored glass for BIPV

In this study, we proposed a design and implementation method to display various high-saturation colors of Building Integrated Photovoltaics (BIPV) modules. The color reproduction results were compared and analyzed through simulations, using two methods, physical thickness and reflectance spectrum to reproduce RGB colors of Fraunhofer ISE’s (Germany) color BIPV module, a leading research institute. To achieve colored glass, a single-layer structure of Nb2O5 was simulated on the glass and deposited by the PVD sputtering method. Through this approach, we successfully produced an array of clear color glass. We performed simulations to attain RGB colors through a multi-layer structure model. We investigated the effects of key factors such as material, thickness, and the number of layers (SiO2, Si3N4, Nb2O5, TiO2) on reflectance and color attainment. Finally, assuming a color module deposited with a triple-layer structure of Nb2O5/SiO2/Nb2O5 was installed in a real building, the expected annual power generation was simulated and compared with the normal BIPV module.

An intelligent financial data mining system using a fuzzy clustering multimedia approach

In order to improve the effect of financial data mining, this paper analyzes the financial data mining system combined with fuzzy clustering multimedia tool algorithm, builds an intelligent model to intelligently process financial data, and studies a multi-layer financial data protection structure model. According to the propagation characteristics of the financial data signal at the uniform cutoff and the theoretical knowledge of the electron microscopic motion, this paper analyzes the calculation formulas of the reflected power and the absorbed power of the financial data to the cutoff. Moreover, this paper improves the effect of fuzzy analysis of financial data and builds a financial data mining system based on fuzzy clustering multimedia tool. The simulation study shows that the financial data mining system based on fuzzy clustering multimedia tool proposed in this paper can effectively improve the effect of financial data mining.

Embedding model of multilayer networks structure and its application to identify influential nodes

At present, there are many indexes used to quantify the structure of single layer complex networks, but multilayer networks are affected by the number of layers, which are difficult to represent the structure and complicated to calculate. In this paper, we propose a network embedding method to represent the structure information of multilayer networks, which reduces the computational complexity. After the structure of the multilayer networks is expressed, the key nodes in the network are mined to help control the spread of the epidemic, suppress the spread of rumors, and optimize the structure of the network. However, it is difficult to quantify this problem precisely because of the difference of judgment indexes. On the basis of representing the structure of multilayer networks, we propose a fuzzy Tsallis eXtropy (FTE) method for quantifying influential nodes in multilayer networks by combining fuzzy theory and entropy. In addition, FTE is tested by some practical networks and compared with other methods. The results reveal that the proposed method is effective.

A safety dynamic evaluation method for missile mission based on multi-layered safety control structure model

A safety dynamic evaluation method for missile mission based on multi-layered safety control structure model

Research on the Path of High-Quality Development of Student Management under the Explanatory Structural Model Oriented to Solve the Dilemma of Collaborative Governance of Student Management in Colleges and Universities

Abstract This paper firstly studies the student management model, analyzes the mechanism of explaining the operation of the structural model, and proposes the DEMATEL method. Secondly, the ISM model is established on the basis of DEMATEL, and the cross-matrix multiplication method is introduced to explore the diffusion of interrelationships among factors in the system. And finally, the construction of the DEMATEL-ISM model is completed. Then, 11 experts were selected to set up an ISM group to construct the relevant reachability matrix after determining the key factors of the problem, and a multi-layer recursive order structure model was established based on the high-quality management influencing factors. Finally, an empirical examination was conducted to examine the overall effect of student management quality in S colleges and universities. Among the key factors of student management, classroom management was identified as the most critical factor affecting the quality of student management, with the ratio of the most important and the important summed up to 76.1%. Among the classroom student participation in higher education, the highest score was given to participatory behavior, with an interval between [2,5] and a mean value of 3.4808. The quality of student management in higher education was characterized by a high level of dissatisfaction among students and teachers, which was 41.94% and 51.28%, respectively. It can be seen that daily management, moral education, teacher management, and teacher competence are insufficient. Colleges and universities need to strengthen the construction of these 4 aspects and put forward relative coping strategies for the deficiencies that exist.

What and how influence the safety knowledge sharing of new generation of construction workers in China: a study based on DEMATEL and ISM

PurposeNew generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.Design/methodology/approachBased on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.FindingsThe results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.Research limitations/implicationsThe number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.Practical implicationsThe influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.Originality/valueThis paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.

Modeling of Multilayer Structures with Tunable Optical Characteristics

Modeling of Multilayer Structures with Tunable Optical Characteristics

Modeling of Multilayer Structures with Tunable Optical Characteristics

Modeling of Multilayer Structures with Tunable Optical Characteristics

Deep learning-based inverse design optimization of efficient multilayer thermal emitters in the near-infrared broad spectrum.

This study proposes a deep learning architecture for automatic modeling and optimization of multilayer thin film structures to address the need for specific spectral emitters and achieve rapid design of geometric parameters for an ideal spectral response. Multilayer film structures are ideal thermal emitter structures for thermophotovoltaic application systems because they combine the advantages of large area preparation and controllable costs. However, achieving good spectral response performance requires stacking more layers, which makes it more difficult to achieve fine spectral inverse design using forward calculation of the dimensional parameters of each layer of the structure. Deep learning is the main method for solving complex data-driven problems in artificial intelligence and provides an efficient solution for the inverse design of structural parameters for a target waveband. In this study, an eight-layer thin film structure composed of SiO2/Ti and SiO2/W is rapidly reverse engineered using a deep learning method to achieve a structural design with an emissivity better than 0.8 in the near-infrared band. Additionally, an eight-layer thin film structure composed of 3 × 3 cm SiO2/Ti is experimentally measured using magnetron sputtering, and the emissivity in the 1-4 µm band was better than 0.68. This research provides implications for the design and application of micro-nano structures, can be widely used in the fields of thermal imaging and thermal regulation, and will contribute to developing a new paradigm for optical nanophotonic structures with a fast target-oriented inverse design of structural parameters, such as required spectral emissivity, phase, and polarization.

Application of Gob-Side Entry Driving in Fully Mechanized Caving Mining: A Review of Theory and Technology

China has abundant coal resources, and the distribution of coal seams is complex. Thick coal seams account for more than 45% of all coal seams. Fully mechanized top coal caving mining has the advantages of large production, high efficiency, and low cost. In fully mechanized caving mining, especially in fully mechanized caving mining of extra-thick coal seams, the mining space is ample, the mine pressure is severe, and the roadway maintenance is complex. As a result, it is necessary to summarize and discuss the gob-side entry driving of fully mechanized caving in theory and technology, which will help to promote the further development of fully mechanized caving gob-side entry driving technology. First, in recent years, the research hotspots of gob-side entry driving have focused on the deformation mechanism and the control method of the roadway surrounding rock. Secondly, this paper discusses the theoretical models of the “triangle-block” and “beam” for the activity law of the overlying strata in gob-side entry driving, including the lateral breaking “large structure” model, compound key triangle block structure model in the middle and low position, the high and low right angle key block stability mechanics model, elastic foundation beam model, low-level combined cantilever beam + high-level multilayer masonry beam structure model, and the vertical triangular slip zone structure model. It introduces the “internal and external stress field theory” and the “stress limit equilibrium zone model”. Thirdly, it summarizes several numerical simulation analysis methods in different conditions or research focuses and selects appropriate constitutive models and simulation software. Finally, it introduces surrounding rock control technology, including two ribs, the roof, and under challenging conditions. It provides a method reference for support in similar projects.

Kernel Function-Based Inverting Algorithm for Structure Parameters of Horizontal Multilayer Soil

A multilayer soil structure model is fundamental to design grounding systems. A new method is presented to invert the structure parameters of horizontal multilayer soil. The structure parameters of soil are determined by analyzing the kernel function of the integral equation of the apparent resistivity. The essence of the proposed method avoids the difficulties encountered in general optimization methods; namely, the calculation of the apparent resistivity and its derivative.

Research on ultrasonic phased array detection algorithm for TA15/Ti2AlNb multi-layer gradient material structure

Conventional ultrasonic detection methods can detect a TA15/Ti2AlNb gradient material multi-layer structure with many layers; the reflection and refraction phenomena of ultrasonic waves at the partition interface result in considerable attenuation of ultrasonic energy. It is difficult to achieve accurate focusing control of multi-array element synthetic beams, and internal defects cannot be detected. We explored the ‘ultrasonic velocity scale coefficient K’ algorithm to determine the ultrasonic beam propagation refraction path of a multi-layer gradient material structure. The algorithm makes full use of the refraction characteristics of ultrasonic waves on each material layer interface, establishes the acoustic ray-tracing model, analyzes the acoustic ray-tracing propagation path of each array element, and quickly obtains the focusing law. A TA15/Ti2AlNb gradient material specimen was prepared using laser melting deposition (LMD) technology, and a multi-layer structure model was established based on the finite difference time domain (FDTD) method to verify the focusing law. The experimental results of the ultrasonic phased array showed that the proposed algorithm effectively improved the defect detection signal-to-noise ratio (SNR) and imaging quality of the TA15/Ti2AlNb gradient material.

Key influencing factors of vertical integration of electronic health records in medical consortiums

BackgroundSimilar to other countries around the world, China has incorporated the recording of electronic health data into its national strategy. After the completion of the decentralized construction phase, the construction of electronic health records in China has reached the stages of integration, sharing, and utilization. “Vertical integration” is the premise and foundation of “shared utilization” of electronic health records within the medical consortium, but it is also a bottleneck in realizing this goal. ObjectiveThe main purpose of this paper is to find out the key factors affecting the vertical integration of electronic health records in the medical consortiums, and to clarify the impact mechanism of these key factors, so as to provide reference for improving relevant policies. MethodsIn this study, an index system of influencing factors is established for cross-institutional vertical integration of electronic health records within a medical consortium, identifying key influencing factors using the combined fuzzy-DEMATEL-ASIM method and revealing the influence relationship and action mechanism among the key influencing factors using a multi-layer hierarchical influence structure model. ResultsThere are 32 factors influencing the vertical integration of electronic health records in the medical consortium, 17 of which are key factors. According to the hierarchical structure of key influencing factors, they can be divided into three categories: surface-level factors, middle-level factors and deep-level factors. ConclusionsIn practice, these key factors should be prioritized for improvement and optimization to promote integration projects. In the future, we should focus on key influencing factors to precisely implement policies, such as introducing special promotion policies, unifying development planning, changing health insurance payment methods, establishing sharing standards, and raising public awareness.

Enhanced tunable dielectric properties of Ba0.6Sr0.4TiO3/PVDF composites through dual-gradient structural engineering

Materials with tunable dielectric properties were expected to be applied in electronic devices such as phased array antennas, tunable filters and phase shifters. The dielectric tunability of material greatly depends on the dielectric constant and breakdown strength. Herein, two kinds of Ba0.6Sr0.4TiO3/PVDF (BST/PVDF) composite materials with different dual-gradient structures were designed to obtain the serialized relative permittivity and improved breakdown strength. The numerical simulation based on Yamada theory confirmed that the multilayer dual-gradient structure design was beneficial to improve the dielectric constant, and the enhancement of breakdown strength was further identified by finite element simulation. The optimal composition has a high dielectric tunability of 78.27 % which is 45 % higher than the ungraded composite due to the high permittivity of 33.8 and high breakdown strength of 1900 kV/cm. The dielectric theoretical model of multilayer structure was developed by introducing the effect factor of layer number m into the Yamada model, and the calculated results are consistent with the experimental results especially m= 1.6–1.7. This work provides a new strategy to effectively improve the dielectric tunability of ceramic/polymer composite materials.

Hazard identification, risk assessment and management of industrial system: Process safety in mining industry

Hazard identification, risk assessment and management are of great significance for the safe and efficient production of industrial system. However, due to the lack of quantitative methods, the production of industrial systems still lacks safety guarantees. Firstly, we revise the accident causation model of mining industry based on the “Swiss-Cheese” model and construct a three-dimensional multi-granular structure model applied to the mining industry. To identify hazards of mining industry, a multi-layer hierarchical structure model and a system safety assessment model are established according to finite covering theorem. Then, the hazard identification is carried out based on the multi-layer hierarchical model and the risk matrix method, and a quantitative method is proposed to calculate the process indicators. Subsequently, the weighted grey relational analysis method is used for risk assessment on the driving system in mining industry. To improve the safety level of the driving system, the Hazard Identification-Assessment-Check-Action risk closed-loop management mode is used for risk management in the purpose of obtaining hazard rectification measures. Risk assessment is carried out again after risk rectification, and the safety level of the driving system can reach higher level. This research can provide guidance for the process safety improvement of industrial systems.

Evaluation of industrial development quality and analysis of influencing factors in Xi'an, China.

Industry is the lifeblood of the national economy, and it is the inevitable course of sustainability for China to promote the high-quality development of industry. A theoretical framework of industrial development quality (IDQ) was constructed, and 32 influencing factors were selected based on complex system theory. The IDQ in Xi'an from 2004 to 2019 was evaluated, and the influencing mechanisms of each IDQ factor were analyzed through an integrated maximum generalized information entropy (MGIE)-self-organizing feature mapping (SOFM) neural network-decision-making trial and evaluation laboratory (DEMATEL)-interpretive structural modeling (ISM) approach. The results show that the IDQ in Xi'an is on the rise, but the development of internal subsystems is uneven, with the technology subsystem contributing the most and the social subsystem contributing the least. There is a multi-layer hierarchical structure among the influencing factors of IDQ, and the multi-layer structure model can be divided into 10 layers. The first layer is the investment intensity of industrial pollution control, which is the most direct factor that affects IDQ. The tenth layer is the industrial wastewater discharge intensity, industrial waste gas emission intensity, water consumption per unit of industrial added value, highway density, and energy consumption per unit of industrial added value, which are the root factors affecting IDQ. This study can provide a theoretical basis and reference for the promotion of high-quality industrial development.

High-speed multi-camera 3D DIC measurement of the deformation of cassette structure with large shaking table

Vision-based deformation measurement methods have been proposed to overcome the disadvantages of laborious, time-consuming measurement data that are difficult to accurately obtain using contact sensors in three directions. However, such methods remain a challenge for large-scale applications owing to difficulties in full-field imaging, stereo calibration, and measurement resolution, among other factors. To the best of our knowledge, there are no reports on the three-dimensional (3D) full-field measurement of a large shaking table structure with multiple cameras. In this paper, a multi-camera 3D DIC method using four high-speed cameras to measure the multi-layer structure model in a shaking table is proposed. To calibrate the stereo cameras with a large field of view, a speckle-based calibration method and a coordinate system unification method are proposed. The implementation of the proposed method is illustrated with a shaking table test for a 1/8 scaled 15-story high-rise cassette concrete structure with several different intensity levels of ground motions. The results of displacement, velocity, and acceleration of the structure measured using the proposed method correspond well with those of a laser displacement meter and accelerometer. The experiment results show that this method can guarantee full-field measurements in the range of tens of square meters and realize a sub-millimeter displacement measurement accuracy. They also indicate that the proposed multi-camera 3D DIC method has high potential for understanding the failure mechanism of structures and improving the structural design.