Detailed Model Research Articles

Comparative study between sliding mode and DTC of doubly fed induction machine

Although the great advance in term of AC machine construction, control strategies are also necessary to be developed and improved continuously satisfying output torque/power. Hence the Doubly fed induction motor (DFIM)is widely used in industry, since it can operates in wide range of speed variation around the synchronous speed and the control of flux and torque is independent. In this paper, control of doubly fed induction motor (DFIM) has been investigated, which two control strategies have been studied and compared: the first strategy uses a sliding mode control (SMC); the second employs Direct Torque Control (DTC). Modeling of DFIM and details of both control strategies have been presented. the mathematical description of different basic dynamic models of the DFIM have been carried out The performances in terms of torque tracking, accuracy and robustness of both control techniques under normal and various speed and load conditions have been demonstrated and compared.

NLKFill: high-resolution image inpainting with a novel large kernel attention

AbstractThe integration of convolutional neural network (CNN) and transformer enhances the network’s capacity for concurrent modeling of texture details and global structures. However, training challenges with transformer limit their effectiveness to low-resolution images, leading to increased artifacts in slightly larger images. In this paper, we propose a single-stage network utilizing large kernel attention (LKA) to address high-resolution damaged images. LKA enables the capture of both global and local details, akin to transformer and CNN networks, resulting in high-quality inpainting. Our method excels in: (1) reducing parameters, improving inference speed, and enabling direct training on 1024$$\times $$ × 1024 resolution images; (2) utilizing LKA for enhanced extraction of global high-frequency and local details; (3) demonstrating excellent generalization on irregular mask models and common datasets such as Places2, Celeba-HQ, FFHQ, and the random irregular mask dataset Pconv from NVIDIA.

Dynamic-Linearization-Based Predictive Control of a Voltage-Source Inverter

In pursuit of accurate and fast trajectory tracking of power converters, an explicit model is commonly used in the finite control-set model predictive control (FCS-MPC) framework to predict precise behaviors of controlled variables. In reality, however, the model mismatch is inevitable, which causes the inherent challenges of parameter sensitivity and model uncertainties of the FCS-MPC method. This article proposes a dynamic-linearization-based predictive control architecture to circumvent such model dependence while keeping the attractive features of the conventional FCS-MPC method. By integrating the data-driven feature of the dynamic-linearization approach, the detailed model used in the FCS-MPC controller is replaced by a virtual equivalent data model, creating a data-driven predictive control architecture. The suggested method selects optimal control action solely based on the input-output data, exhibiting strong rejection against parameter variations whilst inheriting the distinctive property of the conventional FCS-MPC method. Finally, the proposed design is validated through comparative simulation and experimental results on a three-level neutral-point-clamped inverter.

The visible and thermal light curve of the large Kuiper belt object (50000) Quaoar

Recent stellar occultations have allowed accurate instantaneous size and apparent shape determinations of the large Kuiper belt object (50000) Quaoar and the detection of two rings with spatially variable optical depths. In this paper we present new visible range light curve data of Quaoar from the Kepler/K2 mission, and thermal light curves at 100 and 160 µm obtained with Herschel/PACS. The K2 data provide a single-peaked period of 8.88 h, very close to the previously determined 8.84 h, and it favours an asymmetric double-peaked light curve with a 17.76 h period. We clearly detected a thermal light curve with relative amplitudes of ~ 10% at 100 and at 160 µm. A detailed thermophysical modelling of the system shows that the measurements can be best fit with a triaxial ellipsoid shape, a volume-equivalent diameter of 1090 km, and axis ratios of a/b = 1.19 and b/c = 1.16. This shape matches the published occultation shape, as well as visual and thermal light curve data. The radiometric size uncertainty remains relatively large (±40 km) as the ring and satellite contributions to the system-integrated flux densities are unknown. In the less likely case of negligible ring or satellite contributions, Quaoar would have a size above 1100 km and a thermal inertia ≤ 10 J m−2K−1s−1/2. A large and dark Weywot in combination with a possible ring contribution would lead to a size below 1080 km in combination with a thermal inertia ≳10 J m−2K−1s−1/2, notably higher than that of smaller Kuiper belt objects with similar albedo and colours. We find that Quaoar’s density is in the range 1.67–1.77 g cm−3, significantly lower than previous estimates. This density value closely matches the relationship observed between the size and density of the largest Kuiper belt objects.

Routing and Scheduling in Multigraphs With Time Constraints—A Memetic Approach for Airport Ground Movement

Routing and scheduling problems with increasingly realistic modelling approaches often entail the consideration of multiple objectives, time constraints, and modelling the system as a multigraph. This detailed modelling approach has increased computational complexity and may also lead to violation of the additivity property of the costs. In the worst scenario, increased complexity makes the problem intractable for exact algorithms. Even when the problem is solvable, exact algorithms may not provide solutions within the given time budget, and the found solutions are not guaranteed to be optimal due to the additivity property violation. Approximate solution methods become more suitable in this case. This paper focuses on one particular real-world application, the Airport Ground Movement Problem, where both time constraints and parallel arcs are involved. We introduce a novel Memetic Algorithm for Routing in Multigraphs with Time constraints (MARMT) and present a comprehensive study of its different variants based on diverse genetic representation methods. We propose a local search operator that enhances search efficiency and effectiveness. MARMT is tested on real data based on two airports of different sizes. Our results show that MARMT does not suffer from the non-additivity property problem as it outperforms the state-of-the-art exact algorithm when allowed to converge. When a time budget of 10 seconds is imposed on MARMT, it is able to provide solutions with quality comparable (within 1-5% degradation) to the ones given by the exact algorithm with respect to the aggregated objective values. MARMT can be adapted for other applications, such as train operations.

Role of virtual reality in advancing forensic medical examination in cases of occupational safety violations: a review

This article discusses the prospects for introducing innovative technologies in the form of virtual and augmented reality when conducting forensic examinations of certain categories of criminal cases, such as violations of labor protection rules. Problematic aspects are revealed when conducting inspections of crime scenes in hard-to-reach areas with possible risks to people.
 Based on a generalization of scientific works and practical experience of foreign countries, the application of innovations in scientific and technological progress in forensic examinations were analyzed.
 The authors proposed an algorithm for conducting forensic examination in the field of labor protection using virtual reality technology, as well as its further application in legal proceedings. The proposed algorithm can serve as basis for the development of more effective and safe methods for conducting forensic examinations in virtual reality.
 The development of detailed 3D injury models that simulate real-life accident scenarios will enable more accurate and objective injury assessments. Moreover, compared to traditional forensics, the use of virtual reality technology ensures high accuracy of measurements and coverage of the entire object under investigation, significantly reduces operating time, and stores all received information in its original state, which is an excellent opportunity to recreate the scene of an incident in real time.
 The introduction of virtual reality into forensic examination in cases of violation of labor protection rules will contribute to efficiency, objectivity, completeness, and ensuring the reliability of not only the conclusions of forensic examinations but also legal proceedings in general. Additionally, this direction of technology development represents significant benefits for the judicial system, contributing to the reduction of time and fair trials in the field of labor protection and in other categories of criminal cases.

Numerical simulation of single-well enhanced geothermal power generation system based on discrete fracture model

This study proposes a single-well enhanced geothermal system (SEGS) to mitigate the high-risk of traditional Enhanced Geothermal Systems (ESGs) with two or more wells and enhance the general applicability. A detailed thermodynamic model that couples the wellbore, reservoir, and organic Rankine cycle is built. For the reservoir, a three-dimensional flow and heat transfer model featuring a discrete fracture network is employed. The effects of injection flow rate, injection temperature, branch well length, and branch well spacing on net output work, pump power consumption, thermal efficiency, and exergy efficiency have been investigated. The results indicate that an increase in the injection flow rate improves the shaft power of the expander and the power consumption of the injection pump. An optimal flow rate of 30 kg/s is identified, which maximizes the annual net power output to 1221.2 kW. Additionally, an increase in the injection temperature is found to enhance the buoyancy effect, thereby improving both thermal and exergy efficiency, and reducing the power consumption of the injection pump. The maximum net output power is achieved at an injection temperature of 60 °C. The study also notes that the branch well length has a negligible effect on thermal and exergy efficiency and expander shaft work. However, a longer branch well length contributes to a decrease in the power consumption of the injection pump and an increase in the net power output. Finally, it is observed that increasing the lateral well spacing slows the rate decay of the production temperature. A spacing of 360 m is found to yield a maximum annual net output power of 1259.4 kW. In conclusion, this study offers significant insights and practical guidance for the development and utilization of SEGS, demonstrating its potential as an effective alternative to conventional EGS methodologies.

Synaptic and dendritic architecture of different types of hippocampal somatostatin interneurons.

GABAergic inhibitory neurons fundamentally shape the activity and plasticity of cortical circuits. A major subset of these neurons contains somatostatin (SOM); these cells play crucial roles in neuroplasticity, learning, and memory in many brain areas including the hippocampus, and are implicated in several neuropsychiatric diseases and neurodegenerative disorders. Two main types of SOM-containing cells in area CA1 of the hippocampus are oriens-lacunosum-moleculare (OLM) cells and hippocampo-septal (HS) cells. These cell types show many similarities in their soma-dendritic architecture, but they have different axonal targets, display different activity patterns in vivo, and are thought to have distinct network functions. However, a complete understanding of the functional roles of these interneurons requires a precise description of their intrinsic computational properties and their synaptic interactions. In the current study we generated, analyzed, and make available several key data sets that enable a quantitative comparison of various anatomical and physiological properties of OLM and HS cells in mouse. The data set includes detailed scanning electron microscopy (SEM)-based 3D reconstructions of OLM and HS cells along with their excitatory and inhibitory synaptic inputs. Combining this core data set with other anatomical data, patch-clamp electrophysiology, and compartmental modeling, we examined the precise morphological structure, inputs, outputs, and basic physiological properties of these cells. Our results highlight key differences between OLM and HS cells, particularly regarding the density and distribution of their synaptic inputs and mitochondria. For example, we estimated that an OLM cell receives about 8,400, whereas an HS cell about 15,600 synaptic inputs, about 16% of which are GABAergic. Our data and models provide insight into the possible basis of the different functionality of OLM and HS cell types and supply essential information for more detailed functional models of these neurons and the hippocampal network.

Numerical Analysis of Ground Surcharge Effects on Deformation Characteristics in Shield Tunnel Linings

To investigate the deformation characteristics of shield tunnel linings under ground surcharge, finite element software was employed to create a detailed three-dimensional model of the staggered assembly of the shield tunnel lining. This model includes components such as precast concrete segments, reinforcements, and joints (comprising bent bolts, washers, and bolt sleeves). Additionally, the model accounts for interface frictions between segments and the interactions between different rings. The reliability of the numerical model was verified based on the results of a full-scale model test. Additionally, the model accounts for interface frictions between segments and the interactions between different rings. Changes in tunnel convergence, joint tensioning, bolt stresses, reinforcement stresses, and concrete crack development were systematically analyzed. The results indicate the following: (1) the deformation mode of the lining structure under ground surcharge resembles a “transverse ellipse”. Joints located near the haunch opened along the outer arc, while those near the vault and bottom opened along the inner arc. The restraining effect of the bolts on joints opening in the inner arc was greater than that on the outer arc. Notably, when the opening of the inner arc reached 4.9 mm, the bolt stress escalated to the yield strength of 640 Mpa. (2) Under larger loads, the lining structure’s joints are susceptible to greater deformation, resulting in the tensile yielding of local reinforcement within these joints. (3) Cracks predominantly occur near the haunch, vault, and bottom of the lining structure, with the central angle of crack distribution ranging between 70° and 85°.

A hybrid model-data method for seismic response reconstruction of instrumented buildings

This study presents a two-step hybrid (model-data fusion) method for reconstructing the seismic response of instrumented buildings at their non-instrumented floors. Over the past couple of decades, seismic data recorded within instrumented buildings have yielded invaluable insights into the behavior of civil structures, which were arguably impossible to obtain through numerical simulations, laboratory-scale experiments, or even in-situ testing. Recently, advances in sensing technology have opened new pathways for structural health monitoring (SHM) and rapid post-earthquake assessment. However, data-driven techniques tend to lack accuracy when structures have sparse instrumentation. In addition, creating detailed numerical models for the monitored structures is labor-intensive and time-consuming, often unsuitable for rapid post-event assessments. The common approach to address these challenges has been to use simple interpolation techniques over the sparse measurements. However, uncertainties associated with such estimates are usually overlooked, and these methods have certain physical limitations. In this study, we propose a two-step approach for reconstructing seismic responses. In the initial step, a coupled shear–flexural beam model is calibrated using data collected from instrumented floors. Next, the residual, representing the difference between measurements and the beam model’s predictions, is used to train a Gaussian process regression model. The combination of these two models provides both the mean and variance of the response at the non-instrumented floors. This new approach is verified by using simulated acceleration responses of a tall building. Validation is attained by using real seismic data recorded in two tall buildings and comparing the method’s predictions with actual measurements on floors not used for training. Finally, data recorded in a 52-story building during multiple earthquakes are used for demonstrating the practical application of the proposed approach in real-world scenarios.

A Road Map to the Structural Optimization of a Type-C Composite UAV

The present paper investigates the design process and the dimensioning of a tailless type-C composite sandwich unmanned aerial vehicle (UAV). The objective is to investigate an innovative aircraft configuration which exceeds the standard approach of ribs and spars and replaces them with a sandwich structure for future unmanned aerial systems. The necessity of carbon fiber-reinforced materials arose due to the weight constraint of a Class C UAV, i.e., the whole vehicle must be under 25 kg, which limits the mass of the structure to 9 kg. The structural design of composite structures differs from the one of traditional isotropic structures. The number of holes should be limited, as drilling down the composite aerostructure would conclude to the generation of delaminations. In addition, the joints between sections with different thicknesses could lead to stress concentrations and disbands. Therefore, the present report is crucial for the continuance of the present project as it has contributed both to the structural design and assessment of the UAV. This work focusses on the computation of loads, the process of structural sizing through a multi-disciplinary optimization approach, and the simulation-based structural proof. Particular attention is paid to the specifically developed semi-analytical method for predicting the aero-elastic load. Based on the detailed finite element model of the global structure, the applicability of the minimum number of bolts as a major structural joining variant is proven. The design process from single components to the assembly of the overall aircraft results in the realization of the demonstrator structure.

Hybrid Mode: Routinization of the Transition Mode as the Third Common Mode for Compound VTOL Drones

Fixed-wing Vertical Takeoff and Landing (VTOL) drones have been widely researched and applied because they combine the advantages of both rotorcraft and fixed-wing drones. However, the research on the transition mode of this type of drone has mainly focused on completing the process quickly and stably, and the application potential of this mode has not been given much attention. The objective of this paper is to routinize the transition mode of compound VTOL drones, i.e., this mode works continuously for a longer period of time as a third commonly used mode besides multi-rotor and fixed-wing modes, which is referred to as the hybrid mode. For this purpose, we perform detailed dynamics modeling of the drone in this mode and use saturated PID controllers to control the altitude, velocity, and attitude of the drone. In addition, for more stable altitude control in hybrid mode, we identify the relevant parameters for the lift of the fixed-wings and the thrust of the actuators. Simulation and experimental results show that the designed control method can effectively control the compound VTOL drone in hybrid mode. Moreover, it is proven that flight in hybrid mode can reduce the flight energy consumption to some extent.

A ‘MeerKAT-meets-LOFAR’ study of the complex multi-component (mini-)halo in the extreme sloshing cluster Abell 2142

Clusters of galaxies are known to be turbulent environments, whether they are merging systems where turbulence is injected via the conversion of gravitational potential energy into the intracluster medium (ICM), or whether they are relaxed systems in which small-scale core sloshing is occurring within the potential well. In many such systems, diffuse radio sources associated with the ICM are found: radio haloes and mini-haloes. Abell 2142 is a rich cluster undergoing an extreme episode of core sloshing, which has given rise to four cold fronts and a complex multi-component radio halo. Recent work revealed that there are three primary components to the halo that spans a distance of up to around 2.4\,Mpc. The underlying physics of particle acceleration on these scales is poorly explored, and requires high-quality multi-frequency data with which to perform precision spectral investigation. We aim to perform such an investigation. We used new deep MeerKAT L-band (1283\,MHz) observations in conjunction with LOFAR HBA (143\,MHz) data as well as X-ray data from XMM-Newton and Chandra to study the spectrum of the halo and the connection between the thermal and non-thermal components of the ICM. We confirm the presence of the third halo component, detecting it for the first time at 1283\,MHz and confirming its ultra-steep spectrum nature, as we recovered an integrated spectrum of $ H3, \, total 0.10$. All halo components follow power-law spectra with increasingly steep spectra moving towards the cluster outskirts. We profiled the halo in three directions, finding evidence of asymmetry and spectral steepening along an axis perpendicular to the main axis of the cluster. Our investigation of the thermal non-thermal connection shows sub-linear correlations that are steeper at 1283\,MHz than 143\,MHz, and we find evidence of different connections in different components of the halo. In particular, we find both a moderate anti-correlation (H1, the core) and positive correlation (H2, the ridge) between the radio spectral index and X-ray temperature. Our results are broadly consistent with an interpretation of turbulent (re-)acceleration following an historic minor cluster merger scenario in which we must invoke some inhomogeneities. However, the anti-correlation between the radio spectral index and X-ray temperature in the cluster core is more challenging to explain; the presence of three cold fronts and a generally lower temperature may provide the foundations of an explanation, but detailed modelling is required to study this further.

Case Studies about Finite Element Modeling and Wireless Sensing of Three Pennsylvania Bridges.

Three Pennsylvanian bridges were studied using finite element and wireless sensor technology. A detailed finite element model of each bridge was created using a commercial software in order to calculate the strains generated by a load that simulates the presence of a standard truck. Pristine and damage scenarios were simulated, and the computed strains were compared to the experimental strains measured with proprietary wireless sensors during a truck test performed by companies not involved in the study presented in this article. The comparison demonstrated the accuracy of the model and the presence of a few non-critical anomalies in terms of load redistribution. In addition, the comparison proved the reliability of the wireless sensing system installed on the bridges, although some drift was observed. The structural monitoring program for the three bridges was also evaluated by processing more than two years of data streamed to a repository.

Efficient homogenization of honeycomb sandwich panels using orthotropic core simplification and Finite Element-based method: A comparative study

Composite materials, particularly honeycomb composites, are widely utilized in various industries, including aerospace, due to their high energy absorption against the impact and exceptional strength-to-weight ratio. This study aims to leverage the plastic and elastic properties of these materials to develop a simplified numerical model that incorporates orthotropic properties for core modeling. By doing so, the need for detailed honeycomb structure modeling is eliminated, resulting in reduced computational costs and time. A comprehensive three-dimensional finite element model, accounting for structural intricacies, is presented based on experimental data from a reputable source (isotropic model) and its equivalent finite element model (orthotropic model). The model is validated by the experimental results, demonstrating good agreement. The study also investigates parameters such as energy absorption, the internal energy of the core and faces, maximum displacement, and maximum contact force under low-velocity impact scenarios with spherical and cylindrical projectiles. These findings highlight the effectiveness of the orthotropic model, particularly in showcasing greater energy absorption in the core of the sandwich panel when subjected to a cylindrical impactor.

Strategic Placement of Accelerometers for Structural Health Monitoring of a Complex Unreinforced Stone Masonry Hindu Mandir

ABSTRACT The BAPS Hindu Mandir, recently constructed in Abu Dhabi, UAE, is a complex unreinforced stone masonry structure built from thousands of sculpted sandstone and marble pieces employing ancient Indian techniques called Shilp Shastra. The entire structure is substantially large with a footprint size of 5,100 m 2 and unique so that it is not covered by modern seismic design standards. Its performance was verified by conducting dynamic field tests presented herein. The most vulnerable substructure was identified based on both engineering judgement and modal analysis of the entire structure employing a detailed 3D finite element model, which was validated via the field experiments. A “local” model was developed for the identified vulnerable substructure which significantly reduced model complexity and allowed to overcome computational limitations. Based on the response of the local model, the relative importance of the sensor locations was determined via a Displacement Index method in addition to a reduction of the total variance of spectral accelerations using conditional probability theory. Through this approach, a methodology for selecting the optimal sensor placement with application on the complex unreinforced stone masonry Hindu Mandir is proposed.

Covering-based $$(\alpha , \beta )$$-multi-granulation bipolar fuzzy rough set model under bipolar fuzzy preference relation with decision-making applications

AbstractThe rough set (RS) and multi-granulation rough set (MGRS) theories have been successfully extended to accommodate preference analysis by substituting the equivalence relation (ER) with the dominance relation (DR). On the other hand, bipolarity refers to the explicit handling of positive and negative aspects of data. In this paper, with the help of bipolar fuzzy preference relation (BFPR) and bipolar fuzzy preference $$\delta $$ δ -covering (BFP$$\delta $$ δ C), we put forward the idea of BFP$$\delta $$ δ C based optimistic multi-granulation bipolar fuzzy rough set (BFP$$\delta $$ δ C-OMG-BFRS) model and BFP$$\delta $$ δ C based pessimistic multi-granulation bipolar fuzzy rough set (BFP$$\delta $$ δ C-PMG-BFRS) model. We examine several significant structural properties of BFP$$\delta $$ δ C-OMG-BFRS and BFP$$\delta $$ δ C-PMG-BFRS models in detail. Moreover, we discuss the relationship between BFP$$\delta $$ δ C-OMG-BFRS and BFP$$\delta $$ δ C-PMG-BFRS models. Eventually, we apply the BFP$$\delta $$ δ C-OMG-BFRS model for solving multi-criteria decision-making (MCDM). Furthermore, we demonstrate the effectiveness and feasibility of our designed approach by solving a numerical example. We further conduct a detailed comparison with certain existing methods. Last but not least, theoretical studies and practical examples reveals that our suggested approach dramatically enriches the MGRS theory and offers a novel strategy for knowledge discovery, which is practical in real-world circumstances.

Co-optimization of power and water distribution systems for simultaneous hydropower generation and water pressure regulation

Water Distribution Systems (WDSs) are gravitational systems supplying water, mainly. Little research has been conducted on harnessing the great amount of energy that is currently dissipated during water pressure regulation, usually performed with “passive” devices like Pressure Reduction Valves (PRVs). This paper develops a co-optimization framework between Water and Power Distribution Systems (PDS) and introduces the concept of Integrated Power-Water Distribution System (IPWDS). Under this framework, PRVs are replaced by hydro-turbines, which form the interconnecting links between the two systems. They regulate pressure at the WDS while injecting the power resulting from their action to PDS. The complete WDS and PDS mathematical models are adopted and the detailed turbine design and performance model that accounts for turbines feasible operational range is considered. The suggested method optimizes the power generation of the hydro-turbines subject to the hydraulic restrictions and power flow constraints imposed by each network. Optimal Power Flow (OPF) has been extended in order to accommodate turbine’s model and constraints imposed by the varying daily flows of the WDS and PDS. Results taken under the suggested framework from a typical WDS, demonstrated that more than 393 MWh (approximately $40 K) of clean power could be produced per year. However, the violation of the unified set of constraints from the IPWDS may reduce the amount of renewable power generation by a significant 7%. This paper focuses mainly on the technical aspect of such an approach. Future work will focus on the economic assessment and viability of such joint projects, resulting from co-optimization and on social-technical aspects that aim on maximizing the penetration of turbines within existing PDS.

Modelling of Multi-Storey Cross-Laminated Timber Buildings for Vibration Serviceability

In this study, the vibration serviceability of multi-storey timber buildings is addressed. The core of this study pertains to the preparation of a comprehensive finite element model to predict modal properties for an accurate vibration serviceability checking. To that end, findings obtained from studying three multi-storey timber buildings are summarized and discussed. Two of the buildings (of seven and eight storeys) consist entirely of cross-laminated timber (CLT), while the third is a five-storey hybrid CLT-concrete building. Thanks to the detailed finite element models and modal testing results, one has the capability to conduct sensitivity analyses, classical and Bayesian model updating, and uncertainty quantifications. With these methodologies, influential modelling parameters as well as the sources of modelling error were identified. This allowed for conclusions to be drawn about the in-plane shear stiffness of the constructed walls (whose higher value causes the natural frequencies to increase by up to 25%), the soil deformability (which may cause the natural frequencies to drop by up to 20%), and the perpendicular-to-the-grain deformation of floor slabs (which may lead to an overestimation of a fundamental frequency by up to 8%).

Effect of loading rate on mode I fracture behavior of red sandstone: Insights from AE and DIC techniques

The loading rate is an essential factor that influences the fracture characteristics and behavior of rock materials. In the study, a series of mode I fracture tests were performed on semi-circular bending (SCB) specimens of red sandstone under a range of static loading rates (0.005 mm/min–2 mm/min). The results showed that fracture toughness increases linearly with the logarithm of loading rates but the critical crack mouth opening displacement (CMODc) almost keeps constant. The fracture processes of rock were monitored using the acoustic emission (AE) and digital image correlation (DIC) techniques. The accumulated ringing counts increases with the loading rates at a natural logarithm relationship. The quantitative analysis for RA-AF data reveals that the contribution of shear cracks to mode I fracture increases with the loading rates. Prior to the DIC analysis, the DIC parameters were firstly calibrated by comparing the CMOD obtained from the clip gauge with that from the DIC data. By virtue of the strain and displacement fields, the fracture process, including post-peak fracture behavior, was analyzed using the cohesion zone model (CZM) in detail. Some fracture parameters, such as fracture process zone (FPZ) length and width, critical crack tip opening displacement (CTODc) were identified. The results indicate that FPZ length decreases with the loading rates but FPZ width and CTODc are nearly unaffected. The FPZ length at post-peak stage is lower than that at peak, regardless of the loading rate. Finally, the FPZ length measured by DIC is compared to that estimated by five theoretical models. The results show that the FPZ length calculated by the modified Irwin model is very closed to that from DIC.