Impact Analysis of Microscopic Defect Types on the Macroscopic Crack Propagation in Sintered Silver Nanoparticles

Sintered silver nanoparticles(AgNPs)arewidely used in high-power electronics due to their exceptional properties.However,the material reliability is significantly affected by various microscopic defects.In this work,the three primary micro-defect types at potential stress concentrations in sintered AgNPs are identified,categorized,and quantified.Molecular dynamics(MD)simulations are employed to observe the failure evolution of different microscopic defects.The dominant mechanisms responsible for this evolution are dislocation nucleation and dislocation motion.At the same time,this paper clarifies the quantitative relationship between the tensile strain amount and the failure mechanism transitions of the three defect types by defining key strain points.The impact of defect types on the failure process is also discussed.Furthermore,traction-separation curves extracted from microscopic defect evolutions serve as a bridge to connect the macro-scale model.The validity of the crack propagation model is confirmed through tensile tests.Finally,we thoroughly analyze how micro-defect types influence macro-crack propagation and attempt to find supporting evidence from the MD model.Our findings provide a multi-perspective reference for the reliability analysis of sintered AgNPs.

GA-BP模型在HSS模型参数取值中的应用

小应变硬化土(HSS)模型可以有效反映土的压缩硬化特性和小应变特性,非常适合黄土基坑的数值模拟计算。但是,HSS模型包含了11个硬化土(HS)模型参数和2个小应变参数,而这2个小应变参数往往需要采用试验方法确定,获取过程复杂。为了探讨小应变参数的预测方法,采用经过遗传算法优化的BP神经网络模型,即GA-BP神经网络模型,首先根据预设的小应变参数水平经过数值模拟计算得到49组位移数据,然后将得到的数据用于GA-BP神经网络的训练,待GA-BP神经网络的预测误差达到要求之后,再使用实际的位移数据反演得到小应变参数,最后基于预测得到的小应变参数进行数值模拟。结果显示,GA-BP神经网络模型预测的小应变参数在基坑围护结构最大水平位移和地表最大沉降计算方面表现良好,可以应用于实际工程。

Two-Layer Coupled Network Model for Topic Derivation in Public Opinion Propagation

In view of the fact that news can generate derivative topics when it spreads through micro-blogs,a two-layer coupled SEIR public opinion propagation model is proposed in this paper.The model divides the process of public opinion propagation into two layers:the original topic layer and the derived topic layer.Messages are transmitted separately by the SEIR model in the two topic layers,which are independent and interactive.The influence of the topic derivation rate on the propagation trend is established by solving for the equilibrium point and propagation threshold.Further,we establish the relationship between the original topic and the derived topic by simulation.This paper uses the Baidu index to demonstrate the correctness of the model.The relationship between the derived topic and the original topic is verified by adjusting the parameters by the control variable method.The results show that the proposed model is consistent with the propagation of actual public opinion.

Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine

Presented is a multiple model soft sensing method based on Affinity Propagation （AP）, Gaussian process （GP） and Bayesian committee machine （BCM）. AP clustering arithmetic is used to cluster training samples according to their operating points. Then, the sub-models are estimated by Gaussian Process Regression （GPR）. Finally, in order to get a global probabilistic prediction, Bayesian committee mactnne is used to combine the outputs of the sub-estimators. The proposed method has been applied to predict the light naphtha end point in hydrocracker fractionators. Practical applications indicate that it is useful for the online prediction of quality monitoring in chemical processes.

Crack evolution behavior of rocks under confining pressures and its propagation model before peak stress

The understanding of crack propagation characteristics and law of rocks during the loading process is of great significance for the exploitation and support of rock engineering.In this study,the crack propagation behavior of rocks in triaxial compression tests was investigated in detail.The main conclusions were as follows:1)According to the evolution characteristics of crack axial strain,the differential stress?strain curve of rocks under triaxial compressive condition can be divided into three phases which are linear elastic phase,crack propagation phase,post peak phase,respectively;2)The proposed models are applied to comparison with the test data of rocks under triaxial compressive condition and different temperatures.The theoretical data calculated by the models are in good agreement with the laboratory data,indicating that the proposed model can be applied to describing the crack propagation behavior and the nonlinear properties of rocks under triaxial compressive condition;3)The inelastic compliance and crack initiation strain in the proposed model have a decrease trend with the increase of confining pressure and temperature.Peak crack axial strain increases nonlinearly with the inelastic compliance and the increase rate increases gradually.Crack initiation strain has a linear relation with peak crack axial strain.

Damage Initiation and Propagation in Composites Subjected to Low-Velocity Impact:Experimental Results,3D Dynamic Damage Model,and FEM Simulations

A three-dimensional dynamic damage model that fits both small and large damage sizes is developed to predict impact damage initiation and propagation for each lamina of T300-carbon/epoxy laminations.First,13 specimens of the same lamination sequence are subjected to three different impact energies(10 J,15 J,and 20 J).After the impact,the laminates are inspected by the naked eye to observe the damage in the outer layers,and subsequently X-rayed to detect the inner damage.Next,the stress analysis of laminates subjected to impact loading is presented,based on the Hertz contact law and virtual displacement principle.Based on the analysis results,a three-dimensional dynamic damage model is proposed,including the Hou failure criteria and Camanho stiffness degradation model,to predict the impact damage shape and area.The numerical predictions of the damage shape and area show a relatively reasonable agreement with the experiments.Finally,the impact damage initiation and propagation for each lamina are investigated using this damage model,and the results improve the understanding of the impact process.

Applications of A Numerical Model to Wave Propagation on Mild Slopes

Based on the mild slope equation that has heen deeomposed inlo three equations related to wave phase function, wave amplitude and wave approach angle, a refraction-diffraction model is developed. The finite difference method has been selected as the solution method. The model results are compared with experimental results and the model is applied to coastal waters of the Fethiye Bay, whieh is located at the Mediterranean Sea of Turkey.

A FEM-DFN model for the interaction and propagation of multi-cluster fractures during variable fluid-viscosity injection in layered shale oil reservoir

To investigate the height growth of multi-cluster fractures during variable fluid-viscosity fracturing in a layered shale oil reservoir,a two-dimensional finite element method(FEM)-discrete fracture network(DFN)model coupled with flow,stress and damage is proposed.A traction-separation law is used to describe the mixed-mode response of the damaged adhesive fractures,and the cubic law is used to describe the fluid flow within the fractures.The rock deformation is controlled by the in-situ stress,fracture cohesion and fluid pressure on the hydraulic fracture surface.The coupled finite element equations are solved by the explicit time difference method.The effects of the fracturing treatment parameters including fluid viscosity,pumping rate and cluster spacing on the geometries of multifractures are investigated.The results show that variable fluid-viscosity injection can improve the complexity of the fracture network and height of the main fractures simultaneously.The pumping rate of15 m^(3)/min,variable fluid-viscosity of 3-9-21-36-45 mPa s with a cluster spacing of 7.5 m is the ideal treatment strategy.The field application shows that the peak daily production of the application well with the optimized injection procedu re of variable fluid-viscosity fracturing is 171 tons(about 2.85 times that of the adjacent well),which is the highest daily production record of a single shale oil well in China,marking a strategic breakthrough of commercial shale oil production in the Jiyang Depression,Shengli Oilfield.The variable fluid-viscosity fracturing technique is proved to be very effective for improving shale oil production.

Correlation and trust mechanism-based rumor propagation model in complex social networks

In real life, the rumor propagation is influenced by many factors. The complexity and uncertainty of human psychology make the diffusion model more challenging to depict. In order to establish a comprehensive propagation model, in this paper, we take some psychological factors into consideration to mirror rumor propagation. Firstly, we use the Ridenour model to combine the trust mechanism with the correlation mechanism and propose a modified rumor propagation model. Secondly, the mean-field equations which describe the dynamics of the modified SIR model on homogenous and heterogeneous networks are derived. Thirdly, a steady-state analysis is conducted for the spreading threshold and the final rumor size. Fourthly, we investigate rumor immunization strategies and obtain immunization thresholds. Next, simulations on different networks are carried out to verify the theoretical results and the effectiveness of the immunization strategies.The results indicate that the utilization of trust and correlation mechanisms leads to a larger final rumor size and a smaller terminal time. Moreover, different immunization strategies have disparate effectiveness in rumor propagation.

New model of propagation rates of long crack due to structure fatigue

By comparison of the characteristics of existing models for long fatigue crack propagation rates, a new model, called the generalized passivation-lancet model for long fatigue crack propagation rates （GPLFCPR）, and a general formula for characterizing the process of crack growth rates are proposed based on the passivation-lancet theory. The GPLFCPR model overcomes disadvantages of the existing models and can describe the rules of the entire fatigue crack growth process from the cracking threshold to the critical fracturing point effectively with explicit physical meaning. It also reflects the influence of material characteristics, such as strength parameters, fracture parameters and heat treatment. Experimental results obtained by testing LZ50 steel, AlZnMgCu0.5, 0.5Cr0.5Mo0.25V steel, etc., show good consistency with the new model. The GPLFCPR model is valuable in theoretical research and practical applications.

Heat front propagation in shale oil reservoirs during air injection:Experimental and numerical studies

Air injection technique for developing shale oil has gained significant attention. However, the ability of the heat front to consistently propagate within the shale during air injection remains uncertain. To address this, we investigated the heat front propagation within oil-detritus mixtures, shale cores, and fractured shale cores using a self-designed combustion tube(CT) and experimental schemes. By integrating the results obtained from high-pressure differential scanning calorimetry and CT, we developed a comprehensive reaction kinetics model to accurately analyze the main factors influencing the heat front propagation within fractured shale. The findings revealed that in the absence of additional fractures, the heat front failed to propagate within the tight shale. The flow of gases and liquids towards the shale core was impeded, resulting in the formation of a high-pressure zone at the front region of the shale. This pressure buildup significantly hindered air injection, leading to inadequate oxygen supply and the extinguishment of the heat front. However, the study demonstrated the stable propagation of the heat front within the oil-detritus mixtures, indicating the good combustion activity of the shale oil.Furthermore, the heat front successfully propagated within the fractured shale, generating a substantial amount of heat that facilitated the creation of fractures and enhanced gas injection and shale oil flow. It was important to note that after the heat front passed through the shale, the combustion intensity decreased. The simulation results indicated that injecting air into the main fracturing layers of the shale oil reservoir enabled the establishment of a stable heat front. Increasing the reservoir temperature(from 63 to 143℃) and oxygen concentration in the injected gas(from 11% to 21%) promoted notable heat front propagation and increased the average temperature of the heat front. It was concluded that temperature and oxygen concentration had the most important influence on the heat front propagation, followed by pressure and oil saturation.

3D Model Retrieval Method Based on Affinity Propagation Clustering

In order to improve the accuracy and efficiency of 3D model retrieval,the method based on affinity propagation clustering algorithm is proposed. Firstly,projection ray-based method is proposed to improve the feature extraction efficiency of 3D models. Based on the relationship between model and its projection,the intersection in 3D space is transformed into intersection in 2D space,which reduces the number of intersection and improves the efficiency of the extraction algorithm. In feature extraction,multi-layer spheres method is analyzed. The two-layer spheres method makes the feature vector more accurate and improves retrieval precision. Secondly,Semi-supervised Affinity Propagation ( S-AP) clustering is utilized because it can be applied to different cluster structures. The S-AP algorithm is adopted to find the center models and then the center model collection is built. During retrieval process,the collection is utilized to classify the query model into corresponding model base and then the most similar model is retrieved in the model base. Finally,75 sample models from Princeton library are selected to do the experiment and then 36 models are used for retrieval test. The results validate that the proposed method outperforms the original method and the retrieval precision and recall ratios are improved effectively.

Simulation of phytoplankton biomass in Quanzhou Bay using a back propagation network model and sensitivity analysis for environmental variables

Prediction and sensitivity models,to elucidate the response of phytoplankton biomass to environmental factors in Quanzhou Bay,Fujian,China,were developed using a back propagation(BP) network.The environmental indicators of coastal phytoplankton biomass were determined and monitoring data for the bay from 2008 was used to train,test and build a three-layer BP artificial neural network with multi-input and single-output.Ten water quality parameters were used to forecast phytoplankton biomass(measured as chlorophyll-a concentration).Correlation coefficient between biomass values predicted by the model and those observed was 0.964,whilst the average relative error of the network was-3.46% and average absolute error was 10.53%.The model thus has high level of accuracy and is suitable for analysis of the influence of aquatic environmental factors on phytoplankton biomass.A global sensitivity analysis was performed to determine the influence of different environmental indicators on phytoplankton biomass.Indicators were classified according to the sensitivity of response and its risk degree.The results indicate that the parameters most relevant to phytoplankton biomass are estuary-related and include pH,sea surface temperature,sea surface salinity,chemical oxygen demand and ammonium.

CRACK PROPAGATION IN POLYCRYSTALLINE ELASTIC-VISCOPLASTIC MATERIALS USING COHESIVE ZONE MODELS

Cohesive zone model was used to simulate two-dimensional plane strain crack propagation at the grain level model including grain boundary zones. Simulated results show that the original crack-tip may not be separated firstly in an elastic-viscoplastic polycrystals. The grain interior＇s material properties （e.g. strain rate sensitivity） characterize the competitions between plastic and cohesive energy dissipation mechanisms. The higher the strain rate sensitivity is, the larger amount of the external work is transformed into plastic dissipation energy than into cohesive energy, which delays the cohesive zone rupturing. With the strain rate sensitivity decreased, the material property tends to approach the elastic-plastic responses. In this case, the plastic dissipation energy decreases and the cohesive dissipation energy increases which accelerates the cohesive zones debonding. Increasing the cohesive strength or the critical separation displacement will reduce the stress triaxiality at grain interiors and grain boundaries. Enhancing the cohesive zones ductility can improve the matrix materials resistance to void damage.

Numerical Simulations for Stochastic Computer Virus Propagation Model

We are presenting the numerical simulations for the stochastic computer virus propagation model in this manuscript.We are comparing the solutions of stochastic and deterministic computer virus models.Outcomes of a threshold number R0 hold in stochastic computer virus model.If R_(0)<1 then in such a condition virus controlled in the computer population while R_(0)>1 shows virus rapidly spread in the computer population.Unfortunately,stochastic numerical techniques fail to cope with large step sizes of time.The suggested structure of the stochastic non-standard finite difference technique can never violate the dynamical properties.On this basis,we can suggest a collection of strategies for removing virus’s propagation in the computer population.

Modeling of Malicious Code Propagations in Internet of Things

Nowadays, the main communication object of Internet is human-human. But it is foreseeable that in the near future any object will have a unique identification and can be addressed and con- nected. The Internet will expand to the Internet of Things. IPv6 is the cornerstone of the Internet of Things. In this paper, we investigate a fast active worm, referred to as topological worm, which can propagate twice to more than three times faster tl^an a traditional scan-based worm. Topological worm spreads over AS-level network topology, making traditional epidemic models invalid for modeling the propagation of it. For this reason, we study topological worm propagation relying on simulations. First, we propose a new complex weighted network mod- el, which represents the real IPv6 AS-level network topology. And then, a new worm propagation model based on the weighted network model is constructed, which descries the topological worm propagation over AS-level network topology. The simulation results verify the topological worm model and demonstrate the effect of parameters on the propagation.

Propagation modeling of ocean-scattered low-elevation GPS signals for maritime tropospheric duct inversion

The maritime tropospheric duct is a low-altitude anomalous refractivity structure over the ocean surface,and it can significantly affect the performance of many shore-based/shipboard radar and communication systems.We propose the idea that maritime tropospheric ducts can be retrieved from ocean forward-scattered low-elevation global positioning system（GPS） signals.Retrieval is accomplished by matching the measured power patterns of the signals to those predicted by the forward propagation model as a function of the modified refractivity profile.On the basis of a parabolic equation method and bistatic radar equation,we develop such a forward model for computing the trapped propagation characteristics of an ocean forward-scattered GPS signal within a tropospheric duct.A new GPS scattering initial field is defined for this model to start the propagation modeling.A preliminary test on the performance of this model is conducted using measured data obtained from a 2009-experiment in the South China Sea.Results demonstrate that this model can predict GPS propagation characteristics within maritime tropospheric ducts and serve as a forward model for duct inversion.

Dynamic 3-D Indoor Radio Propagation Model and Applications with Radios from 433 MHZ to 2.4 GHz

Proliferation of indoor sensor infrastructure has created a new niche for mobile communications, yet research in indoor radio propagation still has not generated a definite model that is able to 1) precisely capture radio signatures in 3-D environments and 2) effectively apply to radios at a wide range of frequency bands. This paper first introduces the impact of wall obstructions on indoor radio propagation by experimental results through a full cycle of an indoor construction process;it then exploits a dynamic 3-D indoor radio propagation model in a two-story building using radio technologies at both 433 MHz and 2.4 GHz. Experimental measurements and evaluation results show that the proposed 3-D model generates accurate signal strength values at all data evaluation positions. Comparing the two radio technologies, this study also indicates that low frequency radios (such as 433 MHz) might not be attractive for indoor mobile computing applications because of larger experimental errors or constant absence of measurement data.

Global SH-wave propagation in a 2D whole Moon model using the parallel hybrid PSM/FDM method

We present numerical modeling of SH-wave propagation for the recently proposed whole Moon model and try to improve our understanding of lunar seismic wave propagation. We use a hybrid PSM/FDM method on staggered grids to solve the wave equations and implement the calculation on a parallel PC cluster to improve the computing efficiency. Features of global SH-wave propagation are firstly discussed for a 100-km shallow and900-km deep moonquakes, respectively. Effects of frequency range and lateral variation of crust thickness are then investigated with various models. Our synthetic waveforms are finally compared with observed Apollo data to show the features of wave propagation that were produced by our model and those not reproduced by our models. Our numerical modeling show that the low-velocity upper crust plays significant role in the development of reverberating wave trains. Increasing frequency enhances the strength and duration of the reverberations.Surface multiples dominate wavefields for shallow event.Core–mantle reflections can be clearly identified for deep event at low frequency. The layered whole Moon model and the low-velocity upper crust produce the reverberating wave trains following each phases consistent with observation. However, more realistic Moon model should be considered in order to explain the strong and slow decay scattering between various phases shown on observation data.

Path loss modelling and comparison based on the radio propagation measurement at 3.5GHz

Wideband IMT-Advanced mobile communication systems tend to operate in the high frequency bands due to a relatively large capacity available. Thus, Measurement and modelling methods of radio propaga- tion eharaeteristics are proposed for the field test of Chinese 4th generation （4G） trial system. The mea- surement system is established for 3.5GHz based on the sophistieated measurement instruments and the virtual instrument teehnology. The characteristic parameters of radio propagation sueh as path loss （PL） exponent and shadow fading standard deviation are extracted from measurement data, which result in the path loss model finally. The comparisons with other existing international models results validate our mea- surement in terms of path loss model. Based on the analysis of the existing extension model assumed for the microwave frequency at 3.5GHz, we find that the Stanford University Interim （SUI） model fits very well with the measurement result in the hotspot scenario, while the COST 231 model is closer to the mea- surement result in the suburban scenario. This result provides a measurement-based channel referenee for the development of the future IMT-Advanced systems in China.