Thursday, 13 February 2025

Emerging 2D Materials for Future Electronics

 Emerging and future 2D electronic materials such as graphene have the potential to exceed the capabilities of modern components in terms of carrier capacity, strength, and versatility. This article will discuss some of the potential advantages of two-dimensional electronics and the materials from which they will be constructed.

Materials for Future Electronics, 2D Materials, 2D Materials for Electronics

Image Credit: Golubovy/Shutterstock.com

Silicon has been the primary material used in the construction of transistors, semiconductors, and other electronic components since the 1950s, selected over competitors owing to favorable material and electronic properties and low cost. Since this time, Moore’s law, the observation that the number of transistors on an integrated circuit doubles every two (roughly) years, has vaguely held true, and silicon-based electronics have become increasingly powerful. However, since around 2010, the rate of progress has observably slowed, mainly owing to transistors reaching an almost atomic density that suffers from quantum effects such as electron transfer (tunneling) to neighboring components. 

Why are 2D Electronic Materials Needed?

Silicon-based transistors have reached a scale in the order of nanometers, with numerous innovations having allowed them to reach this scale thus far; copper interconnects, the incorporation of dielectric materials, complementary metal oxide semiconductor field effect transistors (CMOS), and so on. Nanometer-thick silicon sheets provide individual charge carrier channels, though making them thinner significantly limits carrier mobility within the channel when approaching around 3 nm.

2D semiconductors of atomic thickness below 1 nm thick are innately thinner than possible for silicon sheets with superior carrier mobility; they are self-passivated in the third dimension and thus do not require any additional shielding in this direction and can be fine-tuned using layering strategies. Layered 2D materials with differing properties can be combined and connected via various gating methods to produce novel electronic heterostructures with precise electronic functions.

What are the Applications of 2D Electronics?

2D electronic materials are highly touted in sensing applications, mainly owing to their large and highly customizable surface chemistry. Any particle or molecule capable of adsorbing or chemically absorbing to the surface of a 2D electronic material may induce a change in electronic properties, namely impedance and, thus, current. The surface can be functionalized with complimentary molecules to one of interest, such as an antibody specific to a pathogenic antigen, and thus act as a highly sensitive and selective detector in a variety of mediums, both gas and liquid phase.

Two-dimensional electronic materials may be the solution to neuromorphic computing in the future; circuitry inspired by the architecture of brains. Within these devices, synapses and neurons are mimicked using computing-in-memory and memristive devices, the latter of which relates electric charge to magnetic flux linkage. These devices are rarely used in modern electronics and remain under intense development, but they have powerful potential applications as memory devices in quantum computing, physical neural networks, and reconfigurable computing.

Reconfigurable computing is a computer architecture that allows substantial changes to the datapath and control of flow through the circuit, allowing them to be configured for a specific task and then reconfigured for another, unlike ordinary microprocessors. Layered 2D heterostructures are ideally suited to reconfigurable computing, as they have the potential to be broken down layer-by-layer and the gating between layers adjusted. Complex overlapping circuitry is possible using 2D electronic materials owing to the aforementioned shielding in the third dimension, allowing the space to be utilized optimally.

What 2D Materials Will Be Used in Future Electronics?

Graphene may be amongst the most popular two-dimensional materials with potentially exciting applications in future electronics; it is constructed only from carbon atoms arranged in a hexagonal lattice that shares an extensive conjugated electron system. This is a common feature of 2D electronic materials, such as hexagonal boron nitride, which is structured similarly to graphene but contains alternating boron and nitrogen atoms.

This material is typically used in lubrication and coating applications where high temperature and chemical resistivity is desired, and unlike graphene, it acts as an insulator, though it can be used in short sections within 2D electronic circuits to act as a tunneling barrier.

Another 2D material with potential applications in future electronics is tungsten diselenide, which, rather than forming a one-atom thick planar structure, has a repeating monomeric unit containing two selenium atoms connected above and below one tungsten atom. This material is employed in solar cell applications, as it has a high bandgap and relatively low-efficiency loss with increasing temperature, and is used in particular gating components of 2D electronics, such as in reconfigurable computing.

Another inorganic 2D electronic material is black phosphorous, which exhibits a unique electronic structure, allowing for high charge carrier mobility. Of all the forms of phosphorous, black phosphorous is most thermodynamically stable at room temperature and again possesses a hexagonal lattice structure that allows overlapping p-type orbitals between atoms and contributes to high electrical conductivity.

Black phosphorous is of particular interest owing to its tunable bandgap by adjusting layer thickness, which fills the range between the aforementioned large bandgap of tungsten diselenide and other transition metal dichalcogenide monolayers and the zero band gap graphene.

Emerging System-on-a-Chip Trends to Watch Out For

References and Further Reading 

Lemme, M. C., Akinwande, D., Huyghebaert, C., & Stampfer, C. (2022). 2D materials for future heterogeneous electronics. Nature Communications13(1). https://doi.org/10.1038/s41467-022-29001-4

Fei, W., Trommer, J., Lemme, M. C., Mikolajick, T., & Heinzig, A. (2022). Emerging reconfigurable electronic devices based on two‐dimensional materials: A review. Infomat4(10). https://doi.org/10.1002/inf2.12355

Cheng, J., Gao, L., Li, T., Mei, S., Wang, C., Wen, B., Huang, W., Li, C., Zheng, G., Wang, H., & Zhang, H. (2020). Two-Dimensional Black Phosphorus Nanomaterials: Emerging Advances in Electrochemical Energy Storage Science. Nano-micro Letters12(1). https://doi.org/10.1007/s40820-020-00510-

Wednesday, 12 February 2025

Sensor technology for medical devices: How fiber optic and electromechanical sensors can be used to improve patient outcomes

 

Medical procedures continue to advance with the development of new technology and manufacturing capabilities. These advancements led to a need for more device feedback and data during procedures to help guide clinicians to more successful patient outcomes. There are several different types of sensors that can be integrated into medical devices to measure critical inputs such as pressure, strain, and temperature. The integration of these sensors has become more challenging as devices increase in complexity and decrease in size. Resonetics can support companies that are looking to add sensor capabilities to their device through the design, manufacturing, and integration of fiber optic and electromechanical sensors.

Fiber Optic Sensors

Fiber optic sensors are comprised of a sensor, fiber optic cable, and a signal conditioner. The signal conditioner sends light through the fiber optic cable to the sensor, which contains a mirror to reflect the light back to the signal conditioner. The change in light from the sensor is measured by the signal conditioner and converted into a measurement. There are many applications where a fiber optic sensor would be the best sensor choice. One example is catheter delivery systems where the thin glass fiber requires very limited space inside the catheter. The flexibility of the fiber will resist kinking while going through tortuous anatomy inside the body. Fiber optics sensors are commonly used to measure pressure and temperature at the tip of a catheter.

Advantages of Fiber Optic Sensors:

Resonetics has been manufacturing fiber optic sensor products that are used in FDA and CE Mark approved devices for over 15 years. The company offers a variety of off-the-shelf sensors and readout units that can purchased for immediate testing and use. Resonetics can also customize the fiber optic sensors to meet specific measurement requirements.

Electromechanical Sensors

Electromechanical sensors are circuits that can be used to measure specific parameters such as stress, strain, and temperature. An electrical current is passed through the circuit and the resistance of the circuit is measured and then converted into the desired data output. Electromechanical sensors can contain multiple sensors per circuit, which can measure different inputs simultaneously. The sensors also have a small footprint which is ideal for use in minimally invasive surgery. Resonetics has an engineering team that can design custom electromechanical sensors, integrate them into a device, and develop testing protocols to ensure measurement accuracy. Resonetics’ electromechanical sensors also require low power consumption and can be combined with contactless data transmission.

Advantages of Electromechanical Sensors

In addition to electromechanical sensors for measurement, Resonetics can also manufacture Near Field Communication (NFC) wireless connectors. These are inductive coupling coils that are used for contactless secure data transmission. These are beneficial for applications where a wire connection is not possible such an implant inside the body.

With leading industry experts and light-speed design and manufacturing processes, we enable limitless innovation for unique and complex medical device applications. Committed to providing customers with innovative and reliable solutions for various measuring parameters in harsh environments and challenging applications, Resonetics accelerates time-to-market with unmatched efficiency and flexibility in the industry.

Tuesday, 11 February 2025


 

Holding Tools and Vices

Holding tools and vices are essential in various industries, particularly in manufacturing, construction, and craftsmanship. These tools provide stability and precision when working on materials such as metal, wood, and plastic. A vice is a mechanical device used to securely clamp a workpiece, ensuring it remains in place while it is being worked on. Vices come in various types, including bench vices, which are mounted to workbenches, and machinist vices, used in more specialized settings like metalworking. Vices are typically made from durable materials such as steel or cast iron, ensuring they can withstand heavy-duty usage.

The function of a vice extends beyond simple holding; it often has additional features like adjustable jaws, allowing it to accommodate a variety of shapes and sizes. In addition, some vices come with swiveling bases, enabling the user to reposition the workpiece without removing it from the vice. Proper use of vices allows workers to execute precise cuts, drills, and other operations with a high degree of accuracy, making them indispensable tools in most workshops.

Another important holding tool is the clamp, which, like vices, is used to secure materials in place. Clamps are often more versatile than vices, as they can be used for a wide range of tasks. For example, C-clamps and bar clamps are useful in woodworking for holding joints together during glue-up processes. Additionally, spring clamps offer a quick solution for lighter tasks where temporary holding is necessary.



Cleaning Tools

Cleaning tools are indispensable for maintaining a safe and efficient work environment. These tools are designed to ensure that work areas, tools, and equipment remain free from debris, dust, and contaminants, which can affect the quality of the work and the longevity of the equipment.

One of the most common cleaning tools is the brush. Brushes come in various forms, including wire brushes for cleaning metal surfaces and paint brushes for applying finishes or coatings. For more delicate tasks, squeegees are often used to remove excess liquids from surfaces, such as glass or countertops. Sponges and rags are also commonly used to wipe down surfaces, especially in areas where liquid spills might occur.

For cleaning machinery and tools, air compressors and vacuum cleaners are popular. Air compressors blow dust and debris out of hard-to-reach places, while industrial vacuum cleaners collect dirt and small particles from workshop floors and surfaces. In some environments, specialized cleaning solutions may be needed, such as degreasers or solvents for removing grease and oil from equipment.

In both cases, proper maintenance of holding tools, vices, and cleaning tools is essential for ensuring their longevity and effectiveness. Regular inspection, cleaning, and lubrication of vices and clamps will help to maintain their function, while proper care of cleaning tools ensures that they continue to meet the demands of a clean, safe working environment.


Monday, 10 February 2025

 

Two-Dimensional Concepts in Mechanical Engineering:



In mechanical engineering, two-dimensional (2D) analysis plays a crucial role in various design and simulation processes. A two-dimensional system is one where motion, stress, or deformation occurs primarily in a plane, ignoring variations in the third dimension. These systems are commonly analyzed in structural mechanics, fluid mechanics, and kinematics to simplify complex three-dimensional problems.

Applications in Structural Mechanics

In structural analysis, 2D stress-strain relationships help engineers evaluate the integrity of components like beams, plates, and thin-walled structures. The plane stress and plane strain assumptions simplify calculations by considering only two principal stress components, making them applicable for thin materials or structures with uniform thickness. Finite element analysis (FEA) often begins with 2D models to predict stress distributions before extending to full 3D simulations.

Fluid Flow in Two Dimensions

In fluid mechanics, 2D flow analysis is vital for understanding aerodynamics and hydrodynamics. The Navier-Stokes equations are often solved under 2D laminar and turbulent flow conditions for applications such as airfoil design and pipeline flow. Engineers use potential flow theory and stream function analysis to model fluid behavior in constrained environments, reducing computational complexity while maintaining accuracy.

Kinematics and Dynamics of 2D Motion

In machine design, mechanisms such as linkages, cams, and gears are often analyzed in a two-dimensional plane to determine velocity, acceleration, and force transmission. The kinematics of planar motion simplifies robotic arm movements, engine crankshaft rotations, and vehicle suspensions, ensuring optimal mechanical performance.

By leveraging two-dimensional analysis, mechanical engineers efficiently design and optimize systems before transitioning to more complex three-dimensional modeling, reducing computational costs and enhancing problem-solving accuracy.

Sunday, 9 February 2025

Global Fluid Mechanics Simulation Software Market Imapct of AI and Automation

 

Global Fluid Mechanics Simulation Software Market Imapct of AI and Automation

Global Fluid Mechanics Simulation Software Market Imapct of AI

Fluid Mechanics Simulation Software Market Impact of AI and Automation
In 2022, the global Fluid Mechanics Simulation Software Market was valued at approximately $1.5 billion. The market is projected to grow at a compound annual growth rate (CAGR) of 7.8% from 2023 to 2028. This growth is driven by increasing demand for accurate and efficient simulations in various industries such as automotive, aerospace, and manufacturing. The integration of artificial intelligence (AI) and automation technologies has significantly influenced the market dynamics. AI-powered tools enhance simulation accuracy and speed by optimizing complex calculations and predicting fluid behavior more effectively.

The impact of automation is equally transformative, streamlining workflows and reducing the time required for simulation tasks. Advanced algorithms and machine learning models enable automation of repetitive processes, allowing engineers to focus on more strategic aspects of their projects. As a result, the efficiency gains and cost reductions associated with AI and automation are accelerating the adoption of fluid mechanics simulation software. This trend is expected to drive further market expansion, underscoring the growing importance of these technologies in the field.

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The importance of Fluid Mechanics Simulation Software Market research reports lies in their ability to aid strategic planning, helping businesses develop effective strategies by understanding market trends and dynamics. They play a crucial role in risk management by identifying potential risks and challenges, allowing businesses to mitigate them proactively. These reports offer a competitive advantage by providing insights into competitors' strategies and Fluid Mechanics Simulation Software Market positioning. For investors, they provide critical data for making informed decisions by highlighting market forecasts and growth potential. Additionally, market research reports guide product development by understanding consumer needs and preferences, ensuring products meet market demands and drive business growth.

What are the Type driving the growth of the Fluid Mechanics Simulation Software Market?

Growing demand for below Type around the world has had a direct impact on the growth of the Fluid Mechanics Simulation Software Market:

Cloud Based, Web Based

What are the Applications of Fluid Mechanics Simulation Software Market available in the Market?

Based on Application the Market is categorized into Below types that held the largest Fluid Mechanics Simulation Software Market share In 2024.

Aerospace, Ocean Ship, Ground Transportation, Achitechive, Others

Who is the largest Manufacturers of Fluid Mechanics Simulation Software Market worldwide?

Siemens, Dassault Systèmes, SimScale GmbH, Ansys, SIMFLOW Technologies, CFDRC, Autodesk, Cadence, OpenCFD, COMSOL, Maya HTT, Shanghai Suochen Information Technology, ShonCloud Technology, Tianfu, CLABSO

Short Description About Fluid Mechanics Simulation Software Market:

The global Fluid Mechanics Simulation Software Market is anticipated to rise at a considerable rate during the forecast period, between 2023 and 2031. In 2022, the market is growing steadily, and with the increasing adoption of strategies by key players, the market is expected to rise over the projected horizon.

North America, particularly the United States, will continue to play a pivotal role in the market's development. Any changes in the United States could significantly impact the Fluid Mechanics Simulation Software Market growth trends. The market in North America is projected to grow considerably during the forecast period, driven by the high adoption of advanced technology and the presence of major industry players, creating ample growth opportunities.

Europe is also expected to experience significant growth in the global market, with a strong CAGR during the forecast period from 2024 to 2031.

Despite intense competition, the clear global recovery trend keeps investors optimistic about the Fluid Mechanics Simulation Software Market, with more new investments expected to enter the field in the future.

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Which regions are leading the Fluid Mechanics Simulation Software Market?

• North America (United States, Canada and Mexico)
• Europe (Germany, UK, France, Italy, Russia and Turkey etc.)
• Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam)
• South America (Brazil, Argentina, Columbia etc.)
• Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

This Fluid Mechanics Simulation Software Market Research/Analysis Report Contains Answers to your following Questions

• What are the global trends in the Fluid Mechanics Simulation Software Market? Would the market witness an increase or decline in the demand in the coming years?
• What is the estimated demand for different types of products in Fluid Mechanics Simulation Software Market? What are the upcoming industry applications and trends for the Fluid Mechanics Simulation Software Market?
• What Are Projections of Global Fluid Mechanics Simulation Software Market Industry Considering Capacity, Production and Production Value? What Will Be the Estimation of Cost and Profit? What Will Be Market Share, Supply and Consumption? What about imports and Export?
• Where will the strategic developments take the industry in the mid to long-term?
• What are the factors contributing to the final price of Fluid Mechanics Simulation Software Market? What are the raw materials used for Fluid Mechanics Simulation Software Market manufacturing?
• How big is the opportunity for the Fluid Mechanics Simulation Software Market? How will the increasing adoption of Fluid Mechanics Simulation Software Market for mining impact the growth rate of the overall market?
• How much is the global Fluid Mechanics Simulation Software Market worth? What was the value of the market In 2020?
• Who are the major players operating in the Fluid Mechanics Simulation Software Market? Which companies are the front runners?
• Which are the recent industry trends that can be implemented to generate additional revenue streams?
• What Should Be Entry Strategies, Countermeasures to Economic Impact, and Marketing Channels for Fluid Mechanics Simulation Software Market Industry?

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Our expertise encompasses strategic and growth analyses, providing the crucial data and insights required to make informed corporate decisions and achieve key revenue goals.

With a dedicated team of 250 Analysts and Subject Matter Experts, we excel in data collection and governance, utilizing advanced industrial techniques to gather and analyze data across more than 25,000 high-impact and niche markets. Our analysts are adept at integrating modern data collection methods with superior research methodologies, ensuring the production of precise and insightful research based on years of collective experience and specialized knowledge.

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Saturday, 8 February 2025

Mechanism of Strain Burst by Laboratory and Numerical Analysis

 Strain burst is often considered to be a type of failure related to brittle rock material; therefore, many studies on strain burst focus on the brittleness of rock. However, the laboratory experiments show that strain burst can not only occur in hard brittle rock-like granite but also in the relatively ductile rock-like argillaceous sandstone. This result proves that behavior of rock material is not the only factor influencing the occurrence of strain burst. What must also be considered is the relative stiffness between the excavation wall/ore body and the surrounding rock mass. In order to further studying the mechanism of strain burst considering the whole system, the engineering geomechanial model and numerical model of strain burst due to excavation are built, respectively. In a series of numerical tests, the rock mass involving the excavation wall as well as roof and floor is biaxially loaded to the in situ stress state before one side of the excavation wall is unloaded abruptly to simulate the excavation in the field. With various system stiffness determined by the microproperties including the contact moduli of particles and parallel bond moduli in the models of roof and floor, the different failure characteristics are obtained. Based on the failure phenomenon, deformation, and released energy from the roof and floor, this study proves that the system stiffness is a key factor determining the violence of the failure, and strain burst is prone to happen when the system is soft. Two critical Young’s moduli ratios and stiffness ratios are identified to assess the violence of failure.

1. Introduction

Hoek [1] mentioned that “Rockbursts are explosive failures of rock which occurs when very high stress concentrations are induced around underground openings. The problem is particularly acute in deep level mining in hard brittle rock.” And “A characteristic of almost all rockbursts is that they occur in highly stressed, brittle rock.” Strain burst is often considered as a violent failure closely related to the hard brittle rock due to excavation, and many researches focus on the mechanical behavior of the rock material-like brittleness: the ratio of uniaxial compressive strength to tensile strength of rock was applied by Zhang et al. [2] and Khanlari and Ghaderi-Meybodi [3], as well as Q1 = (σc − σt)/(σc + σt) and Q2 = sin φ have been employed by Singh [4], while Qu =  (u1+u2)/u1 by Tan [5] to assess the violence of rock burst, where σc and σt are the uniaxial compressive and tensile strengths, respectively; φ is the frictional angle of the rock; and u1 and u2 are the permanent and elastic axial deformation of the rock specimen in a loading-unloading cycling uniaxial test.

Hucka and Das [6] concluded some observations associated with higher brittleness involving low values of elongation, fracture failure, formation of fines, high ratio of compressive to tensile strength, high resilience, and large angle of internal friction and formation of cracks in indentation. Rock brittleness is defined by Andreev [7] as the ability of a rock material to deform continuously and perpetually without apparent permanent deformations along with the application of stress surpassing the necessary stresses for microcracking of the material. On the contrary, Handin [8] defined ductility as the ability to undergo large permanent deformation without fracture. Apparently, strain burst does not belong to the ductile behavior, and at the meantime, it is not simply a conventional brittle failure, as strain burst happens around an excavation in a sudden or violent manner, associated with the excess energy from the surrounding rock mass, and may lead to rock bulking, ejection, etc. Brittleness cannot cover the nature of strain burst, and there should be some other factors determining the energy release and violence of strain burst.

The in situ stress and the excavation-induced stress lead to the strain energy stored in the rock mass, which may result in the failure of rock and may supply the excess energy for the strain burst. Meanwhile, strain energy will also be stored in the surrounding rock mass due to the abovementioned stresses and may release when the rock fails and become a source of the excess energy if the stiffness of the surrounding rock mass is relatively low compared with the failing rock. Sometimes, the seismic events owing to collapse, blast, or fault slip near the tunnel may also supply the excess energy to form a violent failure. The excess energy from the surrounding rock mass due to the low system stiffness is the focus in this work.

Cook [9] increased the stiffness of the testing machine by loading a steel tube and carried out the uniaxial compressive tests on the specimens of Tennessee marble and St. Cloud granite. He mentioned that rock burst could be regarded as a stability problem similar to the behavior of the rock specimen in a lab test, i.e., whether the specimen will fail violently or not depend on the relative stiffness between the sample and loading system. Based on the complete stress-strain curve obtained by the stiff test machine, Salamon [10] discussed the relationship between the stability of the specimen and the system stiffness in the perspective of energy and equilibrium in detail and expanded this relationship to the stability of pillar workings. Blake [11] also pointed out that if the rock structure is stiffer than the loading system, the strain energy stored in the loading system will load the rock structure further suddenly when failure happens and causes the occurrence of rock burst and studied the stability of the stope pillar at Galena Mine based on this knowledge. Hedley [12] mentioned the energy driving the rock burst to happen. Aglawe [13] demonstrated that system stiffness, stress level, and released energy are the three important parameters that must be considered together to assess the unstable failure. Similar discussions on the system stiffness and rock burst or violent failure can also be found in many studies [1417].

The theory based on system stiffness helps us understand more about the mechanism of strain burst; however, up to date, it is not easy to be practical in the field due to the complex geological conditions. Numerical tools have been employed to assess the stability of the underground excavation considering the system stiffness in many studies. Brady and Brown [14] studied the stability of the pillars with different width/high ratios and different spans of the adjacent stopes based on boundary element analysis. The mine local stiffness and pillar stiffness were calculated according to the load-convergence relationship in the numerical models, and the postfailure stiffness of the pillars was obtained from published empirical relationship between the elastic/postpeak stiffness ratio and width/height ratio determined from field and lab tests on rock specimens. Numerical method combining the techniques of both finite element and boundary element were employed by Simon et al. [18] to analyze the stability of a cut-and-fill stope. The Hoek–Brown failure criterion was applied in the model to identify the area that may become unstable (safety factor < 1.0) firstly, and then the mine local stiffness was calculated based on the stress and convergence in the model, as well as the postpeak stiffness of the pillar was obtained with an empirical equation involving a modified brittle index. The studies above are only based on the basic theory of stiffness comparison, but the mutual effect of the pillar and surrounding rock mass could not be analyzed directly in the continuum models which are limited when analyzing the problem of rock failure.

Kaiser and Tang [19] used RFPA models to study the failure process, stress-strain response, seismic events, and seismic energy release during the laboratory uniaxial compression tests and field pillar failure considering different system stiffness. This paper just tested a few conditions of various system stiffness and did not give a critical value for violent failure. Aglawe and Prataprao [13] studied the stability of a single opening with the FLAC model. The results show that the system stiffness determines the nature of the failure process, the stress level and the releasable energy define the potential and the violence of the failure, and the stress level and system stiffness should be considered together to assess the violence of failure process. This work also analyzed the factors influencing the system stiffness. However, this study used an elastic continuum model to research failure problems; what is more, the author only considered the stiffness of the surrounding rock mass while omitted the stiffness of the failure slab. Kias et al. [17] employed three different numerical tools to carry out uniaxial compression tests with variable platen stiffness and obtained the corresponding system response, including the stress-strain behavior of the specimen and loading system, while did not give the failure modes or process.

With a series of laboratory strain burst experiments on different rock types and numerical tests (by particle flow code) considering various system stiffness of the surrounding rock mass, this paper will give some discussion on the mechanism of strain burst and assessment on the violence of strain burst in a perspective of the complete system.

2. Laboratory Experiments on Strain Burst

2.1. Experimental System

The laboratory strain burst experiments [20] are conducted with the deep rock burst test system developed in China University of Mining and Technology, Beijing. This experimental system is composed of the main machine, hydraulic controlling, and data acquisition equipment. The main machine is a true triaxial compressive apparatus in which one surface of the prismatic specimen can be unloaded abruptly to simulate the excavation in the field. This feature helps this system have the function to obtain the strain burst phenomenon in the laboratory, and a series of tests [21] have been conducted to study the burst behavior and mechanism.

2.2. Strain Burst Experiments and Discussions

Two types of rock, granite and argillaceous sandstone, have been applied to conduct the strain burst tests. The mechanical properties and micromineral contents of the two rock types are listed in Tables 1 and 2. The granite from a quarry in Laizhou, Shandong Province, has a higher uniaxial compressive strength and Young’s modulus and lower content of clay mineral. The argillaceous sandstone [22] from Xingcun Coal Mine, Shandong Province, has a lower strength, Young’s modulus, and higher content of clay mineral.

Table 1. Mechanical properties of the granite and argillaceous sandstone.
Rock typeUCS (MPa)Young’s modulus (GPa)Poisson’s ratio
Granite16566.70.33
Argillaceous sandstone12539.10.36
Table 2. Microcomponents of the samples by X-ray diffraction analysis.
SampleMineral components and contents (%)Clay mineral content (%)
QuartzK-feldsparPlagioclaseCalcsparDolomiteSideritePyrite
Granite27.037.031.0----5.0
A-sandstone (a)57.78.713.80.5--1.517.8
A-sandstone (b)23.44.63.022.55.1200.920.5

The samples of the two types of rock with the nominal dimensions of 150 mm × 60 mm × 30 mm have been prepared for the strain burst tests. In both tests, the specimens were loaded to a true triaxial stress state and then one side was unloaded suddenly to simulate the excavation. At the meantime, the vertical stress was increased to simulate the stress concentration due to the opening. If failure does not occur in 15 minutes after unloading, the unloaded surface would be reloaded and the sample would be applied to a higher true triaxial stress state and stay for another 15 minutes. The process of unloading and reloading would be repeated until the failure occurs. Figure 1 shows the stress-time curves of the tests on the two types of rock.

Details are in the caption following the image
Figure 1 (a)
Open in figure viewerPowerPoint
Stress-time curves of (a) granite and (b) argillaceous sandstone [22] in the laboratory strain burst experiments.
Details are in the caption following the image
Figure 1 (b)
Open in figure viewerPowerPoint
Stress-time curves of (a) granite and (b) argillaceous sandstone [22] in the laboratory strain burst experiments.

Strain burst occurred on the granite after the first unloading and showed a violent failure. Figure 2 exhibits the process of the burst captured by a high-speed camera. At first, crack propagation and spalling were observed on the unloading surface, followed by a buckling and two slices of fragments as well as some particles ejection. At the end, a complete failure happened on the full surface with large amounts of fragments ejecting violently with loud noise. The bursting process [22] of the argillaceous sandstone is presented in Figure 3. Failure mainly happened on the top of the specimen, and lots of fragments ejected with high speed. The argillaceous sandstone failed at a higher peak strength comparing with the granite, and as an explanation, it may be owing to the different loading paths.

Details are in the caption following the image
Details are in the caption following the image

Strain burst happens on both the granite and argillaceous sandstone samples, which means that not only the hard brittle rock but also relatively ductile rock may burst. The key factor is whether the loading system, corresponding to the surrounding rock mass in the field, is soft enough compared with the rock material in the area where failure may occur. This result accords with the points mentioned in Section 1 that the unstable failure is related to the relative stiffness between the surrounding rock mass (corresponding to the loading system in the laboratory test) and the excavation wall/ore body (corresponding to the specimen in the laboratory test). The burst of argillaceous sandstone in this study shows that the test machine is soft enough for this type of rock.

However, although strain burst occurs on both rock types, it can be found that the granite fails more violently than the argillaceous sandstone. The reason is as follows: as the test machine is the same, the stiffness of the loading system is the same. But comparing the hard brittle granite with the relatively ductile argillaceous sandstone, the former specimen is suffering relatively softer system and higher strain energy release than the latter one.

It proves that the relationship between the stiffness of the loading system and the rock specimen, i.e., the stiffness of the surrounding rock mass and the excavation or ore body in the field, is a key factor of strain burst intensity. A series of tests considering different system stiffness should be carried out to make clear this relationship to guide the field opening and support. As it is not financially possible to change the stiffness of the test machine for many times, and it is not easy to control the stiffness of the specimen due to the complexity of the rock material, it is very difficult to conduct a group of laboratory strain burst experiments to complete this study. However, the numerical test can overcome the shortcomings mentioned above. A series of numerical tests with particle flow code (PFC) will be carried out in the next sections.

3. Numerical Tests on Strain Burst

3.1. Engineering Geological Model and Geomechanical Model

Usually, the surrounding rock mass near an underground opening may involve different types of rock strata with various stiffness, as schematically illustrated in the engineering geological model in Figure 4. During the excavation and stress redistribution on the surrounding rock mass, different amounts of strain energy will be stored and then will be released when the excavation wall fails, which can lead to distinct types of failure around the opening.

Details are in the caption following the image

In Figure 4, it is assumed that the roof and floor have the same stiffness Ke, and the rock stratum which will be excavated has the stiffness of Kr. Theoretically, the stiffness ratio (Ke/Kr) may influence the energy release and violence of failure after excavation. However, how does this ratio influence the failure characteristics and what is the critical value for the violent failure?

The geomechanical model presented in Figure 4 has been built based on the engineering geological model to study the problem described above. In this plane strain problem, the rock mass involving various rock strata suffers vertical and horizontal stress before excavation, and the horizontal stress on one side of a rock stratum is removed to simulate the excavation, while both the roof and floor are still be confined.

Based on the engineering geological model and geomechanical model, the numerical model was built and a series of numerical strain burst tests with various parameters were carried out.

3.2. Numerical Model

3.2.1. Selection of the Numerical Method

The continuous and discontinuous numerical methods both were used to simulate the rock failure [23]. When simulating the broken rock masses, it is not easy to say whether the former or the latter is superior. The main difference between the two methods is that the contact between the blocks or particles remains unchanged in the continuous method. The contact between blocks or particles in a discontinuous method requires continuous operation and renewal using the principle of contact mechanics. For the discontinuous method, the fracture in the rock mass allows large-scale displacement or motion, including rotation and complete separation. These features cannot be implemented in a continuous approach. Additionally, the main influence area of rock mass rupture is concentrated near the surface of tunnel or roadway. Therefore, the discontinuous method is more suitable for near-field rock mass simulation around excavated body, and the equivalent continuity method is more suitable for the far-field simulation.

The strain burst is a typical near-field rock mechanic and engineering problem; therefore, the discontinuous method is more suitable for the research needs of this paper. And the PFC (particle flow code) is one of the most popular discontinuous methods, which was developed by ITASCA. The bonded particle model (BPM) [24] is a basic model that is widely used in the particle flow program to simulate the mechanical properties of rock and soil. The basic unit of this model is a circular or spherical rigid body particle. These nonuniform scale particles are bonded together at their contact points to form assemblies, and the mechanical properties of the geological material are simulated by the mechanical behavior of the assemblies with certain properties.

Many researchers [2530] have used the BMP model to simulate the rock behaviors including elasticity, fracturing, acoustic emission, and damage accumulation producing material anisotropy, hysteresis, dilation, postpeak softening, and strength increase with confinement. What is more, the behavior of this model is based on the calibration of the microproperties of the particles and bonds which follow the basic Newton’s law of motion instead of a prescribed constitutive model. Consequently, PFC is a good selection to study the strain burst behavior under various system stiffness.

3.2.2. Building and Calibration of Numerical Model

Similar to the geomechanical model in Figure 4, the numerical model is built as shown in Figure 5. The particle assemblies with different colors represent the roof (red), excavation wall (blue), and floor (red), respectively, with different stiffness by defining different contact moduli of the particles and parallel bond moduli.

Details are in the caption following the image

A model with the dimension of 40 mm × 100 mm is built and calibrated according to the physical and mechanical parameters of argillaceous sandstone. The calibrated microproperties are presented in Table 3. The process of calibration is loaded by a pair of walls in the PFC program with a loading rate of 0.05 m/s, so this test is under an ideal stiff condition. The loading rate of 0.05 m/s is not identical to that in the physical world, and Cho et al. [31] have explained that the time step in each calculation cycle is chosen to be infinitely small value; therefore, these physically unreasonably high loading rates are slow enough in the PFC analysis. The failure feature and the calculated stress-strain curve are shown in Figure 6, respectively. The calibrated specimen consists of 3427 balls and has a uniaxial compressive strength of 136.2 MPa, Young’s modulus of 38.3 GPa, and Possion’s ratio of 0.36, and then the prepeak stiffness can be obtained as 0.01544 GN/m based on the size of the specimen (the thickness of this 2-dimensional model is assumed to be unity).

Table 3. Microparameters of the calibrated PFC model in the UC test and excavation wall model in the strain burst test.
EcEc¯48 GPaRmin0.42 mm
kn/ksk¯n/k¯s6.0Rmax/Rmin1.66
σ¯n110 ± 27.5 MPaλ¯1.0
σ¯s110 ± 27.5 MPaμ0.5
Details are in the caption following the image
Figure 6 (a)
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(a) Uniaxial compressive test on an intact specimen and (b) stress-strain curve for the intact rock and the calculated stiffness.
Details are in the caption following the image
Figure 6 (b)
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(a) Uniaxial compressive test on an intact specimen and (b) stress-strain curve for the intact rock and the calculated stiffness.

3.3. Numerical Tests on Strain Burst

Two-particle assemblies with the size of 40 mm × 25 mm simulating the roof and floor are built at the top and bottom of the 40 mm × 100 mm model of the excavation wall. The contact moduli of the particles and parallel bond moduli in the roof and floor models are given to be various values to simulate the conditions with different stiffness, while the normal and shear bond strengths of the bonds between the grains are set to be a quite high value to guarantee that failure only occurs in the excavation wall. The microparameters of the roof and floor in the strain burst model are listed in Table 4, while those for the excavation wall just use the parameters in Table 3. The interfaces between the roof/floor and the excavation wall use the joint model with 0 frictional coefficient and 0 cohesion [24]; however, the interfaces cannot be absolutely smooth due to the roughness of the models composed of assemblies of circular particles.

Table 4. Parameters in the PFC model for the roof and floor in the strain burst.
EcE¯cVaries from 0.27 to 5000 GPaRmin0.42 mm
kn/ksk¯n/k¯s6.0Rmax/Rmin1.66
σ¯n1000000 ± 0 MPaλ¯1.0
σ¯s1000000 ± 0 MPaμ0.5

Considering the mining depth of 1170 m [22], we obtain the in situ stress state of σ1 = 35.7 MPa, σ2 = 30.0 MPa, and σ3 = 22.1 MPa. We assume that σ2 = 30.0 MPa is along the direction of opening. In the PFC model, the in situ stress state is applied biaxially (σ1 and σ3 in this two-dimensional model) with the loading rate of 0.05 m/s before one side of the excavation wall is unloaded abruptly. After the removing of the horizontal stress on one side which simulates the excavation, the stress concentration will occur in the vertical direction and the rate of concentration is set to be 0.2 m/s in this study.

3.4. Definition of System Stiffness Ratio

The system of the PFC model in this study includes the excavation wall where strain burst may occur and the surrounding rock involving roof and floor, which is defined as “environment” in this paper. The stiffness ratio of the abovementioned two parts is employed here to describe the system stiffness.

4. Numerical Test Results and Discussions

4.1. Failure Characteristics

The calculated failure modes after excavation are demonstrated in Figure 7. The numbers (e.g., 0.0082/0.0163) under each model are Young’s modulus ratio (RE) and stiffness ratio (RK), respectively. It is obviously observed that the failure tend to be more violent with decreasing Young’s modulus ratio and system stiffness ratio. The failure is quite violent in the scope from A to D1; buckling occurs on the unloading side of the excavation wall, and large blocks eject at high speed; from D2 to D4, fragment ejection can still be seen as well as the bulking; the failure turns to be less violent from D5 to F4, though there are still some small particle ejections and tensile cracks near the unloading face; from F5 to I, no ejection is observed and the localized shear is the main failure mode.

Details are in the caption following the image

Based on the test results under different system stiffness, we can obtain the two critical Young’s moduli ratios and stiffness ratios for this type of rock: (1) at point D4, Young’s modulus ratio is 0.1368 and stiffness ratio is 0.2736. If RE and RK are lower than this critical condition, the failure will be very violent with buckling and fragment ejections; (2) at point F4, Young’s modulus ratio is 9.8870 and stiffness ratio is 19.7741. If RE and RK are lower than this critical condition, the failure will be a little violent, and particle ejections will be observed. If the ratios are higher than this critical condition, the failure will be stable, and the main failure mode is shear. In this condition, the failure is just like the test result in a stiff test machine.

The failure processes in two typical tests are presented in Figures 8 and 9. Eight points are selected at 90%, 80%, 70%, 60%, 50%, 40%, 30%, and 20% of the peak stress in the postpeak region for each test in sequence. The processes show us very different crack propagation and failure characteristics under different system stiffness:

Details are in the caption following the image
Figure 8 (a)
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Failure process of #B strain burst test (RE = 0.0091 and RK = 0.0182). (a) Step 609944. (b) Step 617644. (c) Step 624744. (d) Step 629644. (e) Step 634844. (f) Step 639444. (g) Step 645544. (h) Step 655844.
Details are in the caption following the image
Figure 8 (b)
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Failure process of #B strain burst test (RE = 0.0091 and RK = 0.0182). (a) Step 609944. (b) Step 617644. (c) Step 624744. (d) Step 629644. (e) Step 634844. (f) Step 639444. (g) Step 645544. (h) Step 655844.
Details are in the caption following the image
Figure 8 (c)
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Failure process of #B strain burst test (RE = 0.0091 and RK = 0.0182). (a) Step 609944. (b) Step 617644. (c) Step 624744. (d) Step 629644. (e) Step 634844. (f) Step 639444. (g) Step 645544. (h) Step 655844.
Details are in the caption following the image
Figure 8 (d)
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Failure process of #B strain burst test (RE = 0.0091 and RK = 0.0182). (a) Step 609944. (b) Step 617644. (c) Step 624744. (d) Step 629644. (e) Step 634844. (f) Step 639444. (g) Step 645544. (h) Step 655844.
Details are in the caption following the image
Figure 8 (e)
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Failure process of #B strain burst test (RE = 0.0091 and RK = 0.0182). (a) Step 609944. (b) Step 617644. (c) Step 624744. (d) Step 629644. (e) Step 634844. (f) Step 639444. (g) Step 645544. (h) Step 655844.
Details are in the caption following the image
Figure 8 (f)
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Failure process of #B strain burst test (RE = 0.0091 and RK = 0.0182). (a) Step 609944. (b) Step 617644. (c) Step 624744. (d) Step 629644. (e) Step 634844. (f) Step 639444. (g) Step 645544. (h) Step 655844.
Details are in the caption following the image
Figure 8 (g)
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Failure process of #B strain burst test (RE = 0.0091 and RK = 0.0182). (a) Step 609944. (b) Step 617644. (c) Step 624744. (d) Step 629644. (e) Step 634844. (f) Step 639444. (g) Step 645544. (h) Step 655844.
Details are in the caption following the image
Figure 8 (h)
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Failure process of #B strain burst test (RE = 0.0091 and RK = 0.0182). (a) Step 609944. (b) Step 617644. (c) Step 624744. (d) Step 629644. (e) Step 634844. (f) Step 639444. (g) Step 645544. (h) Step 655844.
Details are in the caption following the image
Figure 9 (a)
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Failure process of #F4 strain burst test (RE = 9.8870 and RK = 19.7741). (a) Step 49881. (b) Step 51481. (c) Step 52881. (d) Step 54681. (e) Step 56281. (f) Step 57681. (g) Step 60181. (h) Step 80181.
Details are in the caption following the image
Figure 9 (b)
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Failure process of #F4 strain burst test (RE = 9.8870 and RK = 19.7741). (a) Step 49881. (b) Step 51481. (c) Step 52881. (d) Step 54681. (e) Step 56281. (f) Step 57681. (g) Step 60181. (h) Step 80181.
Details are in the caption following the image
Figure 9 (c)
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Failure process of #F4 strain burst test (RE = 9.8870 and RK = 19.7741). (a) Step 49881. (b) Step 51481. (c) Step 52881. (d) Step 54681. (e) Step 56281. (f) Step 57681. (g) Step 60181. (h) Step 80181.
Details are in the caption following the image
Figure 9 (d)
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Failure process of #F4 strain burst test (RE = 9.8870 and RK = 19.7741). (a) Step 49881. (b) Step 51481. (c) Step 52881. (d) Step 54681. (e) Step 56281. (f) Step 57681. (g) Step 60181. (h) Step 80181.
Details are in the caption following the image
Figure 9 (e)
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Failure process of #F4 strain burst test (RE = 9.8870 and RK = 19.7741). (a) Step 49881. (b) Step 51481. (c) Step 52881. (d) Step 54681. (e) Step 56281. (f) Step 57681. (g) Step 60181. (h) Step 80181.
Details are in the caption following the image
Figure 9 (f)
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Failure process of #F4 strain burst test (RE = 9.8870 and RK = 19.7741). (a) Step 49881. (b) Step 51481. (c) Step 52881. (d) Step 54681. (e) Step 56281. (f) Step 57681. (g) Step 60181. (h) Step 80181.
Details are in the caption following the image
Figure 9 (g)
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Failure process of #F4 strain burst test (RE = 9.8870 and RK = 19.7741). (a) Step 49881. (b) Step 51481. (c) Step 52881. (d) Step 54681. (e) Step 56281. (f) Step 57681. (g) Step 60181. (h) Step 80181.
Details are in the caption following the image
Figure 9 (h)
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Failure process of #F4 strain burst test (RE = 9.8870 and RK = 19.7741). (a) Step 49881. (b) Step 51481. (c) Step 52881. (d) Step 54681. (e) Step 56281. (f) Step 57681. (g) Step 60181. (h) Step 80181.

The series of numerical tests prove that strain burst is not simply determined by the rock material itself but is related to the complete system. The study based on the stress and strength can only predict when the failure may happen rather than how violent it will be. The previous researches focused on the characteristics of the rock material like brittleness are also limited without considering the properties of the surrounding rock mass. In this study, if the environmental system is relatively softer, there will be more strain energy released from the roof and floor, and hence, the failure is prone to be more violent, while if the environmental system is relatively stiffer, less energy will be released and the failure will be more stable. In the next section, the energy release from the roof and floor will be calculated and analyzed to find out how does the system stiffness influence the violence of failure.

4.2. Energy Release from the Roof and Floor

During the numerical tests, two particle gauges lying at the central of the upper and lower edges of the roof and another two ones of the floor have been set to monitor their vertical strains. Figure 10 presents the vertical stress-strain curves of the roof and floor after unloading on one side of the excavation wall (the sizes of the roof and floor at the unloading point are considered as the original sizes, so their vertical strains at this point are 0). In the prepeak region, both the roof and floor are compressed and their vertical strains increase with the increasing vertical stress. With lower Young’s moduli ratio and stiffness ratio, both the roof and floor show larger vertical strains. In the postpeak region, with the decreasing vertical stress, the roof and floor deform inversely and their vertical strains go down. It is observed that with lower Young’s moduli ratio and stiffness ratio, the roof and floor also have larger inverse vertical strains, which are applied to the failing rock and induce larger strain and more violent burst. The relationship between the vertical strains of the roof/floor and the stiffness ratio is plotted in Figure 11(a).

Details are in the caption following the image
Details are in the caption following the image
Figure 11 (a)
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(a) Relationship between the strain variation of roof and floor after peak strength and the system stiffness ratio (RE). (b) Relationship between the strain energy densities of roof and floor after peak strength and the system stiffness ratio (RK).
Details are in the caption following the image
Figure 11 (b)
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(a) Relationship between the strain variation of roof and floor after peak strength and the system stiffness ratio (RE). (b) Relationship between the strain energy densities of roof and floor after peak strength and the system stiffness ratio (RK).

The areas below the vertical stress-strain curves of the roof and floor in the postpeak zone can be calculated with Microsoft Excel, and the areas represent the released strain energy density from the roof and floor in each numerical strain burst test. As the volume of each model is the same, the released strain energy density can be used to represent the energy release for comparison. The relationship between the released strain energy density and stiffness ratio is plotted in Figure 11(b), and the curves have the similar decreasing trend.

The two critical stiffness ratios are also pointed in Figures 11(a) and 11(b). When the stiffness ratio is lower than the first critical point, both the vertical strains and the released strain energy density of the roof and floor are quite high, decrease abruptly with the increasing stiffness ratio, and then go down gradually between the two critical points. When the stiffness ratio is higher than the second critical value, the vertical strains and released energy density turn almost constant, and the values are quite low. These observations can well explain the different failure modes in the three regions divided by the two critical stiffness ratios.

5. Discussion

Details are in the caption following the image
Figure 12 (a)
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(a) Elements of the strain burst main machine [20] and (b) the schematic of the stiffness calculation in vertical direction.
Details are in the caption following the image
Figure 12 (b)
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(a) Elements of the strain burst main machine [20] and (b) the schematic of the stiffness calculation in vertical direction.

Table 5 lists some results of strain burst tests with different stiffness ratios. The intensity of strain burst was classified as four grades (strong, moderate, light, and no burst) according to the sound, failure phenomena [33]. Three key values (0.85, 1.18, and 1.73) of stiffness ratio were determined. According to those key points, the axis of the stiffness ratio can be divided into four parts (I∼IV, as shown in Figure 13), which corresponds to the strong, moderate, light strain burst, and no burst, respectively. Additionally, if strain burst occurs, the strain energy released by the roof is larger than 347.2 kJ/m3. Moreover, the statistical results of the experimental tests also show that strain burst more likely occurs when the stiffness ratio is lower enough (no more than 1.73).

Table 5. Results of strain burst tests for different specimens.
LithologyNumber of testsSampling spotsMean Young’s modulus (GPa)Stiffness (GN/m)Stiffness ratioStrain burst intensity
Peridotite2Garson mine60.10.720.75Strong
Dolomite7Heishiling tunnel52.70.630.82Strong
Granite20Laizhou51.00.610.85Strong
Marble 113Jingpin II tunnel43.10.521.01Moderate
Basalt3Baijiao coal mine42.80.511.01Moderate
Sandstone8Xingcun coal mine39.10.471.11Moderate
Limestone3Jiahe coal mine36.70.441.18Moderate
Fine sandstone6Antaibao coal mine29.00.351.49Light
Marble 27Jingpin I tunnel25.00.301.73Light
Sandy mudstone4Antaibao coal mine22.90.271.89No burst
Shale4Jiahe coal mine15.20.182.85No burst
Slate4Tengchong tunnel13.50.163.21No burst
Details are in the caption following the image

However, the stiffness ratio of the critical point (D4: 0.27) is smaller than the key point (1.73) of experimental tests. The strain burst results are influenced by many factors, such as loading path, loading rate, specimen dimension, and internal structural, and some factors are difficult to keep unchanged; however, the numerical tests are consistent. Additionally, the stiffness of hydrocylinder is omitted during the stiffness calculation of the experiment system. Moreover, the experiment tests are three-dimensional while numerical tests are two-dimensional, which also leads to this gap. In the future, the three-dimensional numerical analysis of strain burst will be conducted.

6. Conclusions

Laboratory strain burst experiments are conducted to find the relationship between the failure mode and system stiffness. In order to further study this relationship quantificationally, engineering geological model, geomechanical model, and numerical model are built, respectively, and a series of strain burst tests have been carried out considering various system stiffness with the PFC (particle flow code) program. In this study, the whole system including the excavation wall as well as roof and floor is biaxially loaded to the in situ stress state, and then one side of the excavation wall is unloaded abruptly to simulate the excavation in the field. With various system stiffness determined by the microproperties of the contact moduli of the particles and parallel bond moduli in the models of roof and floor, the different failure characteristics are obtained. The conclusions can be drawn as follows:

Nomenclature

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

Financial support from the National Key Research and Development Program (Grant No. 2016YFC0600901) and National Natural Science Foundation of China (Grant No. 51704298) are gratefully acknowledged.

    Open Research

    References

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