Simulation of Fracture Process of Lightweight Aggregate Concrete Based on Digital Image Processing Technology

The mechanical properties and failure mechanism of lightweight aggregate concrete(LWAC)is a hot topic in the engineering field,and the relationship between its microstructure and macroscopic mechanical properties is also a frontier research topic in the academic field.In this study,the image processing technology is used to establish a micro-structure model of lightweight aggregate concrete.Through the information extraction and processing of the section image of actual light aggregate concrete specimens,the mesostructural model of light aggregate concrete with real aggregate characteristics is established.The numerical simulation of uniaxial tensile test,uniaxial compression test and three-point bending test of lightweight aggregate concrete are carried out using a new finite element method-the base force element method respectively.Firstly,the image processing technology is used to produce beam specimens,uniaxial compression specimens and uniaxial tensile specimens of light aggregate concrete,which can better simulate the aggregate shape and random distribution of real light aggregate concrete.Secondly,the three-point bending test is numerically simulated.Thirdly,the uniaxial compression specimen generated by image processing technology is numerically simulated.Fourth,the uniaxial tensile specimen generated by image processing technology is numerically simulated.The mechanical behavior and damage mode of the specimen during loading were analyzed.The results of numerical simulation are compared and analyzed with those of relevant experiments.The feasibility and correctness of the micromodel established in this study for analyzing the micromechanics of lightweight aggregate concrete materials are verified.Image processing technology has a broad application prospect in the field of concrete mesoscopic damage analysis.

Optimization study of station track utilization in high-speed railroad based on constraints of control in random origin and process

Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.

Correlations between mineral composition and mechanical properties of granite using digital image processing and discrete element method

This study investigated the correlations between mechanical properties and mineralogy of granite using the digital image processing(DIP) and discrete element method(DEM). The results showed that the X-ray diffraction(XRD)-based DIP method effectively analyzed the mineral composition contents and spatial distributions of granite. During the particle flow code(PFC2D) model calibration phase, the numerical simulation exhibited that the uniaxial compressive strength(UCS) value, elastic modulus(E), and failure pattern of the granite specimen in the UCS test were comparable to the experiment. By establishing 351 sets of numerical models and exploring the impacts of mineral composition on the mechanical properties of granite, it indicated that there was no negative correlation between quartz and feldspar for UCS, tensile strength(σ_(t)), and E. In contrast, mica had a significant negative correlation for UCS, σ_(t), and E. The presence of quartz increased the brittleness of granite, whereas the presence of mica and feldspar increased its ductility in UCS and direct tensile strength(DTS) tests. Varying contents of major mineral compositions in granite showed minor influence on the number of cracks in both UCS and DTS tests.

Analysis of morphological characteristics of gravels based on digital image processing technology and self-organizing map

A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.

An Edge-Fog-Cloud Computing-Based Digital Twin Model for Prognostics Health Management of Process Manufacturing Systems

The prognostics health management(PHM)fromthe systematic viewis critical to the healthy continuous operation of processmanufacturing systems(PMS),with different kinds of dynamic interference events.This paper proposes a three leveled digital twinmodel for the systematic PHMof PMSs.The unit-leveled digital twinmodel of each basic device unit of PMSs is constructed based on edge computing,which can provide real-time monitoring and analysis of the device status.The station-leveled digital twin models in the PMSs are designed to optimize and control the process parameters,which are deployed for the manufacturing execution on the fog server.The shop-leveled digital twin maintenancemodel is designed for production planning,which gives production instructions fromthe private industrial cloud server.To cope with the dynamic disturbances of a PMS,a big data-driven framework is proposed to control the three-level digital twin models,which contains indicator prediction,influence evaluation,and decisionmaking.Finally,a case study with a real chemical fiber system is introduced to illustrate the effectiveness of the digital twin model with edge-fog-cloud computing for the systematic PHM of PMSs.The result demonstrates that the three-leveled digital twin model for the systematic PHM in PMSs works well in the system’s respects.

Swedish digitised solutions at Techtextil and Texprocess 24

Members of TMAS–the Swedish textile machinery association–displayed technologies completely in alignment with the major digitalisation theme of Techtextil and Texprocess 2024 exhibitions taking place in Frankfurt from April 23-26th.

Dynamic experimental study on rock meso-cracks growth by digital image processing technique

A new meso-mechanical testing scheme based on SEM was developed to carry out the experiment of microfracturing process of rocks. The microfracturing process of the pre-crack marble sample on surrounding rock in the immerged Long-big tunnel in Jinping Cascade II Hydropower Station under uniaxial compression was recorded by using the testing scheme. According to the stereology theory, the propagation and coalescent of cracks at meso-scale were quantitatively investigated with digital technology. Therefore, the basic geometric information of rock microcracks such as area, angle, length, width, perimeter, was obtained from binary images after segmentation. The failure mechanism of specimen under uniaxial compression with the quantitative information was studied from macro and microscopic point of view. The results show that the image of microfracturing process of the specimen can be observed and recorded digitally. During the damage of the specimen, the distribution of microcracks in the specimen is still subjected to exponential distribution with some microcracks concentrated in certain regions. Finally, the change law of the fractal dimension of the local element in marble sample under different external load conditions is obtained by means of the statistical calculation of the fractal dimension.

Shape characterization of sand particles based on digital image processing technology

To characterize the shape of sand particles for concrete,a new method is proposed based on digital image processing(known as the DIP method).By analyzing sand particles projection,the length,width and thickness of sand were measured to characterize particle form.The area and perimeter were measured to characterize particle angularity.The results of the DIP method and Vernier caliper were compared to examine the accuracy of the DIP method.The sample size test was conducted to show the statistical significance of shape results measured by the DIP method.The practicality of the DIP method was verified by instance analysis.The results show that aspect ratios and roundness measured by the DIP method are equal to ones by the Vernier caliper.Results by DIP are dependent on the sand particle number,and at least 350 particles should be measured to represent the overall shape property of sand.The results show that the DIP method is able to distinguish the differences in the shape of sand particles.It achieves the direct measurement of sand particle thickness,and the characterization results of sand aspect ratios and roundness are accurate,statistically significant and practical.Therefore,the DIP method is suitable for sand particle shape characterization.

Digital Signal Processing Based Real Time Vehicular Detection System

Traffic monitoring is of major importance for enforcing traffic management policies.To accomplish this task,the detection of vehicle can be achieved by exploiting image analysis techniques.In this paper,a solution is presented to obtain various traffic parameters through vehicular video detection system(VVDS).VVDS exploits the algorithm based on virtual loops to detect moving vehicle in real time.This algorithm uses the background differencing method,and vehicles can be detected through luminance difference of pixels between background image and current image.Furthermore a novel technology named as spatio-temporal image sequences analysis is applied to background differencing to improve detection accuracy.Then a hardware implementation of a digital signal processing (DSP) based board is described in detail and the board can simultaneously process four-channel video from different cameras. The benefit of usage of DSP is that images of a roadway can be processed at frame rate due to DSP′s high performance.In the end,VVDS is tested on real-world scenes and experiment results show that the system is both fast and robust to the surveillance of transportation.

Numerical simulation of direct shear tests on mechanical properties of talus deposits based on self-adaptive PCNN digital image processing

The macro mechanical properties of materials with characteristics of large scale and complicated structural composition can be analyzed through its reconstructed meso-structures.In this work,the meso-structures of talus deposits that widely exist in the hydro-power engineering in the southwest of China were first reconstructed by small particles according to the in-situ photographs based on the self-adaptive PCNN digital image processing,and then numerical direct shear tests were carried out for studying the mechanical properties of talus deposits.Results indicate that the reconstructed meso-structures of talus deposits are more consistent with the actual situation because the self-adaptive PCNN digital image processing has a higher discrimination in the details of soil-rock segmentation.The existence and random distribution of rock blocks make the initial shear stiffness,the peak strength and the residual strength higher than those of the "pure soil" with particle size less than 1.25 cm apparently,but reduce the displacements required for the talus deposits reaching its peak shear strength.The increase of rock proportion causes a significant improvement in the internal friction angle of talus deposit,which to a certain degree leads to the characteristics of shear stress-displacement curves having a changing trend from the plastic strain softening deformation to the nonlinear strain hardening deformation,while an unconspicuous increase in cohesion.The uncertainty and heterogeneity of rock distributions cause the differences of rock proportion within shear zone,leading to a relatively strong fluctuation in peak strengths during the shear process,while movement features of rock blocks,such as translation,rotation and crossing,expand the scope of shear zone,increase the required shear force,and also directly lead to the misjudgment that the lower shear strength is obtained from the samples with high rock proportion.That,however,just explains the reason why the shear strength gained from a small amount of indoor test data is not consistent with engineering practice.

Kravchenko atomic transforms in digital signal processing

The modified atomic transformations are constructed and proved. On their basis the new complex analytic wavelets are obtained. The proof of the Fourier transforms existence in L~ and L2 on the basis of the theory of atomic functions （AF） are presented. The numerical experiments of digital time series processing and physical analysis of the results confirm the efficiency of the proposed transforms.

Analysis of key technologies and development of integrated digital processing system for cast blasting design

Casting blast can greatly reduce the stripping cost and improve the production capacity of opencast coal mines. Key technologies including high bench blasting, inclined hole, millisecond blasting, pre-splitting blasting and casting blast parameters determination which have influence on the effect of casting blast have been researched with the combination of the ballistic theory and experience in mines. The integrated digital processing system of casting blast was developed in order to simplify the design process of casting blast, improve working efficiency and veracity of design result and comprehensively adopt the software programming method and the theory of casting blast. This system has achieved five functions, namely, the 3D visualization graphics management, the intelligent management of geological information, the intelligent design of casting blast, the analysis and prediction of the blasting effect and the automatic output of the design results. Long-term application in opencast coal mines has shown that research results can not only reduce the specific explosive consumption and improve the blasting effect, but also have high value of popularization and application.

Bayesian and Geostatistical Approaches to Combining Categorical Data Derived from Visual and Digital Processing of Remotely Sensed Images

This paper seeks a synthesis of Bayesian and geostatistical approaches to combining categorical data in the context of remote sensing classification. By experiment with aerial photographs and Landsat TM data, accuracy of spectral, spatial, and combined classification results was evaluated. It was confirmed that the incorporation of spatial information in spectral classification increases accuracy significantly. Secondly, through test with a 5-class and a 3-class classification schemes, it was revealed that setting a proper semantic framework for classification is fundamental to any endeavors of categorical mapping and the most important factor affecting accuracy. Lastly, this paper promotes non-parametric methods for both definition of class membership profiling based on band-specific histograms of image intensities and derivation of spatial probability via indicator kriging, a non-parametric geostatistical technique.

Online Data Processing Methods in Xlet Applications for Seismic Early Warning and Emergency Services on Interactive Digital Television

In this paper, I described the methods that I used for the creation of Xlets, which are Java applets that are developed for the IDTV environment;and the methods for online data retrieval and processing that I utilized in these Xlets. The themes that I chose for the Xlets of the IDTV applications are Earthquake and Tsunami Early Warning;Recent Seismic Activity Report;and Emergency Services. The online data regarding the Recent Seismic Activity Report application are provided by the Kandilli Observatory and Earthquake Research Institute (KOERI) of Bogazici University in Istanbul;while the online data for the Earthquake and Tsunami Early Warning and the Emergency Services applications are provided by the Godoro website which I used for storing (and retrieving by the Xlets) the earthquake and tsunami early warning simulation data, and the DVB network subscriber data (such as name and address information) for utilizing in the Emergency Services (Police, Ambulance and Fire Department) application. I have focused on the methodologies to use digital television as an efficient medium to convey timely and useful information regarding seismic warning data to the public, which forms the main research topic of this paper.

New WA-system of kravchenko functions in digital signal processing

On the basis of modified atomic transformations the new WA-systems of Kravchenko functions are constructed.As an example the digital processing of time series of the various physical nature processing is considered.The numerical experiments and physical analysis of the results confirm the efficiency of the proposed WA-systems of Kravchenko functions.

Bitumen Removal Determination on Asphalt Pavement Using Digital Imaging Processing and Spectral Analysis

This research aims to define an efficient and fast quantification of bitumen removal on the road surface by Digital Imaging Processing (DIP) and spectral analysis. The retrieval of bitumen removal is an important issue for road management and environmental studies related to asphalt wear and environmental pollution. The calculation of the Exposed Aggregate Index (EAI), based on DIP, allows to quantify in each frame the superficial removal of bitumen and the exposure of aggregates. A procedure, based on non-parametric classification process of digital images, gives a fast response of EAI. A correlation among EAI and spectral data, between 390 nm and 900 nm range, is evaluated. Results show a good correlation between spectral data at different wavelength and EAI. Finally, this work evaluates the possibility to retrieve asphalt bitumen removal through remote sensed imagery.

Improvements of Traditional Laser Fraunhofer Diffraction Experiment Using Digital Image Processing Method

We present an improved digital image processing(DIP)method to calculate the widths of single slits.Different from the traditional laser Fraunhofer diffraction experiment in college physical experiments,by performing fast Fourier transform,inverse fast Fourier transform and the nonlinear leastsquare fitting on the diffraction pattern taken by a camera,the DIP method can quickly return an analytic expression,whose period is used to calculate widths of single slits.By comparing the measured results by the DIP method and the successional difference(SD)method,we find that for a single slit whose width is 60372μm,the DIP method is more accurate.Experimental results show that for single slits with widths between 40μm and 160μm,the relative error of the DIP method is less than 2.78%.Also,the DIP method can be used to measure the diameter of filament and fibres online in real time.

An acquisition system of digital nuclear signal processing for the algorithm development

A principle and method of constructing the digital acquisition system is presented in this work,which is convenient for the study on the theories and algorithms of digital nuclear signal processing.The hardware system of the digital acquisition system consists of front-end controller,waveform digitizer and PC workstation,on which the software system has been developed based on Visual C++under Windows environment.The alterable-frequency sampling(AFS)algorithm and the alterable-frequency trapezoidal filter(AFTF)algorithm have also been studied in the real-time environment,along with a digital nuclear spectrum acquisition system being set up based on the new algorithms and theγ-ray spectra of 241Am being shown.A useful experimental platform could be provided by this work for the successive work such as the development of global digitized nuclear measurement system and the study of digital nuclear signal processing.

A new digital pulse processing method for 2πa and 2πb emitter measurement

Digital pulse processing has developed rapidly during recent years.Moreover,it has been widely applied in many fields.In this study,we introduce a digital pulse processing method for 2πa and 2πb emitter measurement.Our digital pulse processing method for 2πa and 2πb emitter measurement is comprised of a field-programmable gate-array-based acquisition card and a pulse-height analysis routine.We established two channels(one for the a emitter and one for the b emitter) on an acquisition board using an analog-to-digital converter with a 16-bit resolution at a speed of 100 million samples per second.In this study,we used captured and stored data to analyze emission rate counts and spectrums.The method we established takes into account noise cancelation,dead-time correction,background subtraction,and zero-energy extrapolation.We carefully designed control procedures in order to simplify pulse-width fitting and threshold-level setting.We transmitted data and commands through a universal serial bus between the acquisition board and the computer.The results of our tests prove that our method performs well in pulse reconstruction fidelity and amplitude measurement accuracy.Compared with the current standard method for measuring 2πa and 2πb emission rates,our system demonstrates excellent precision in emission rate counting.

DIGITAL PROCESSING OF THE POLARIZATION STATE OF GEOPHYSICAL ULF SIGNALS

In this paper, the evaluation by running window smoothing is used for the digital processing of the polarization of geophysical ULF signals. The observed signals are resolved into two orthogonal complex components so that it is no longer necessary to consider the phase and amplitude of the signals simultaneously.