MULTI-SCALE CHARACTERISTICS STUDY ON THE FREQUENCY OF FOGGY DAYS OCCURRING IN NANJING IN DECEMBER 2007

Based on the number of foggy days in Nanjing in December from 1980 to 2011, we analyzed the surface temperature and atmospheric circulation characteristics of foggy years and less-foggy years. Positive anomalies of the Arctic Oscillation(AO) were found to weaken the East Asian trough, which is not conducive to the southward migration of cold air. Simultaneously, this atmospheric condition favors stability as a result of a high-pressure anomaly from the middle Yangtze River Delta region. A portion of La Nia events increases the amount of water vapor in the South China Sea region, so this phenomenon could provide the water vapor condition required for foggy days in Nanjing.Based on the data in December 2007, which contained the greatest number of foggy days for the years studied, the source of fog vapor in Nanjing was primarily from southern China and southwest Taiwan Island based on a synoptic scale study. The water vapor in southern China and in the southwestern flow increased, and after a period of 2-3 days,the humidity in Nanjing increased. Simultaneously, the water vapor from the southwestern of Taiwan Island was directly transported to Nanjing by the southerly wind. Therefore, these two areas are the most important sources of water vapor that results in heavy fog in Nanjing. Using the bivariate Empirical Orthogonal Function(EOF) mode on the surface temperature and precipitable water vapor, the first mode was found to reflect the seasonal variation from early winter to late winter, which reduced the surface temperature on a large scale. The second mode was found to reflect a large-scale,northward, warm and humid airflow that was accompanied by the enhancement of the subtropical high, particularly between December 15-21, which is primarily responsible for the consecutive foggy days in Nanjing.

A semi-analytical model for coupled flow in stress-sensitive multi-scale shale reservoirs with fractal characteristics

A large number of nanopores and complex fracture structures in shale reservoirs results in multi-scale flow of oil. With the development of shale oil reservoirs, the permeability of multi-scale media undergoes changes due to stress sensitivity, which plays a crucial role in controlling pressure propagation and oil flow. This paper proposes a multi-scale coupled flow mathematical model of matrix nanopores, induced fractures, and hydraulic fractures. In this model, the micro-scale effects of shale oil flow in fractal nanopores, fractal induced fracture network, and stress sensitivity of multi-scale media are considered. We solved the model iteratively using Pedrosa transform, semi-analytic Segmented Bessel function, Laplace transform. The results of this model exhibit good agreement with the numerical solution and field production data, confirming the high accuracy of the model. As well, the influence of stress sensitivity on permeability, pressure and production is analyzed. It is shown that the permeability and production decrease significantly when induced fractures are weakly supported. Closed induced fractures can inhibit interporosity flow in the stimulated reservoir volume (SRV). It has been shown in sensitivity analysis that hydraulic fractures are beneficial to early production, and induced fractures in SRV are beneficial to middle production. The model can characterize multi-scale flow characteristics of shale oil, providing theoretical guidance for rapid productivity evaluation.

Nonlinear Flap-Wise Vibration Characteristics ofWind Turbine Blades Based onMulti-Scale AnalysisMethod

This work presents a novel approach to achieve nonlinear vibration response based on the Hamilton principle.We chose the 5-MW reference wind turbine which was established by the National Renewable Energy Laboratory(NREL),to research the effects of the nonlinear flap-wise vibration characteristics.The turbine wheel is simplified by treating the blade of a wind turbine as an Euler-Bernoulli beam,and the nonlinear flap-wise vibration characteristics of the wind turbine blades are discussed based on the simplification first.Then,the blade’s large-deflection flap-wise vibration governing equation is established by considering the nonlinear term involving the centrifugal force.Lastly,it is truncated by the Galerkin method and analyzed semi-analytically using the multi-scale analysis method,and numerical simulations are carried out to compare the simulation results of finite elements with the numerical simulation results using Campbell diagram analysis of blade vibration.The results indicated that the rotational speed of the impeller has a significant impact on blade vibration.When the wheel speed of 12.1 rpm and excitation amplitude of 1.23 the maximum displacement amplitude of the blade has increased from 0.72 to 3.16.From the amplitude-frequency curve,it can be seen that the multi-peak characteristic of blade amplitude frequency is under centrifugal nonlinearity.Closed phase trajectories in blade nonlinear vibration,exhibiting periodic motion characteristics,are found through phase diagrams and Poincare section diagrams.

Multi-scale pore fractal characteristics of differently ranked coal and its impact on gas adsorption

Well-developed pores and cracks in coal reservoirs are the main venues for gas storage and migration.To investigate the multi-scale pore fractal characteristics,six coal samples of different rankings were studied using high-pressure mercury injection(HPMI),low-pressure nitrogen adsorption(LPGA-N2),and scanning electron microscopy(SEM)test methods.Based on the Frankel,Halsey and Hill(FHH)fractal theory,the Menger sponge model,Pores and Cracks Analysis System(PCAS),pore volume complexity(D_(v)),coal surface irregularity(Ds)and pore distribution heterogeneity(D_(p))were studied and evaluated,respectively.The effect of three fractal dimensions on the gas adsorption ability was also analyzed with high-pressure isothermal gas adsorption experiments.Results show that pore structures within these coal samples have obvious fractal characteristics.A noticeable segmentation effect appears in the Dv1and Dv2fitting process,with the boundary size ranging from 36.00 to 182.95 nm,which helps differentiate diffusion pores and seepage fractures.The D values show an asymmetric U-shaped trend as the coal metamorphism increases,demonstrating that coalification greatly affects the pore fractal dimensions.The three fractal dimensions can characterize the difference in coal microstructure and reflect their influence on gas adsorption ability.Langmuir volume(V_(L))has an evident and positive correlation with Dsvalues,whereas Langmuir pressure(P_(L))is mainly affected by the combined action of Dvand Dp.This study will provide valuable knowledge for the appraisal of coal seam gas reservoirs of differently ranked coals.

Grain Yield,Biomass Accumulation,and Leaf Photosynthetic Characteristics of Rice under Combined Salinity-Drought Stress

Simultaneous stresses of salinity and drought often coincide during rice-growing seasons in saline lands,primarily due to insufficient water resources and inadequate irrigation facilities.Consequently,combined salinity-drought stress poses a major threat to rice production.In this study,two salinity levels(NS,non-salinity;HS,high salinity)along with three drought treatments(CC,control condition;DJ,drought stress imposed at jointing;DH,drought stress imposed at heading)were performed to investigate their combined influences on leaf photosynthetic characteristics,biomass accumulation,and rice yield formation.Salinity,drought,and their combination led to a shortened growth period from heading to maturity,resulting in a reduced overall growth duration.Grain yield was reduced under both salinity and drought stress,with a more substantial reduction under the combined salinity-drought stress.The combined stress imposed at heading caused greater yield losses in rice compared with the stress imposed at jointing.Additionally,the combined salinity-drought stress induced greater decreases in shoot biomass accumulation from heading to maturity,as well as in shoot biomass and nonstructural carbohydrate(NSC)content in the stem at heading and maturity.However,it increased the harvest index and NSC remobilization reserve.Salinity and drought reduced the leaf area index and SPAD value of flag leaves and weakened the leaf photosynthetic characteristics as indicated by lower photosynthetic rates,transpiration rates,and stomatal conductance.These reductions were more pronounced under the combined stress.Salinity,drought,and especially their combination,decreased the activities of ascorbate peroxidase,catalase,and superoxide dismutase,while increasing the contents of malondialdehyde,hydrogen peroxide,and superoxide radical.Our results indicated a more significant yield loss in rice when subjected to combined salinity-drought stress.The individual and combined stresses of salinity and drought diminished antioxidant enzyme activities,inhibited leaf photosynthetic functions,accelerated leaf senescence,and subsequently lowered assimilate accumulation and grain yield.

Investigation of hydroxyl-terminated polybutadiene propellant breaking characteristics and mechanism impacted by submerged cavitation water jet

A submerged cavitation water jet(SCWJ)is an effective method to recycle solid propellant from obsolete solid engines by the breaking method.Solid propellant's breaking modes and mechanical process under SCWJ impact are unclear.This study aims to understand those impact breaking mechanisms.The hydroxyl-terminated polybutadiene(HTPB)propellant was chosen as the research material,and a self-designed test system was used to conduct impact tests at four different working pressures.The high-speed camera characterized crack propagation,and the DIC method calculated strain change during the impact process.Besides,micro and macro fracture morphologies were characterized by scanning electron microscope(SEM)and computed tomography(CT)scanning.The results reveal that the compressive strain concentration region locates right below the nozzle,and the shear strain region distributes symmetrically with the jet axis,which increases to 4% at first 16th ms,the compressive strain rises to 2% and 6% in the axial and transverse direction,respectively.The two tensile cracks formed first at the compression strain concentrate region,and there generate many shear cracks around the tensile cracks,and those shear cracks that develop and aggregate cause the cracks to become wider and cut through the tensile cracks,forming the tensile-shear cracks and the impact parts eventually fail.The HTPB propellant forms a breaking hole shaped conical after impact 10 s.The mass loss increases by 17 times at maximum,with the working pressure increasing by three times.Meanwhile,the damage value of the breaking hole remaining on the surface increases by 7.8 times while 2.9 times in the depth of the breaking hole.The breaking efficiency is closely affected by working pressures.The failure modes of HTPB impacted by SCWJ are classified as tensile crack-dominated and tensile-shear crack-dominated damage mechanisms.

Morphological and biochemical characteristics associated with autophagy in gastrointestinal diseases

Autophagy is a cellular catabolic process characterized by the formation of double-membrane autophagosomes.Transmission electron microscopy is the most rigorous method to clearly visualize autophagic engulfment and degradation.A large number of studies have shown that autophagy is closely related to the digestion,secretion,and regeneration of gastrointestinal(GI)cells.However,the role of autophagy in GI diseases remains controversial.This article focuses on the morphological and biochemical characteristics of autophagy in GI diseases,in order to provide new ideas for their diagnosis and treatment.

Liquefaction susceptibility and deformation characteristics of saturated coral sandy soils subjected to cyclic loadings-a critical review

Coral sandy soils widely exist in coral island reefs and seashores in tropical and subtropical regions.Due to the unique marine depositional environment of coral sandy soils,the engineering characteristics and responses of these soils subjected to monotonic and cyclic loadings have been a subject of intense interest among the geotechnical and earthquake engineering communities.This paper critically reviews the progress of experimental investigations on the undrained behavior of coral sandy soils under monotonic and cyclic loadings over the last three decades.The focus of coverage includes the contractive-dilative behavior,the pattern of excess pore-water pressure(EPWP)generation and the liquefaction mechanism and liquefaction resistance,the small-strain shear modulus and strain-dependent shear modulus and damping,the cyclic softening feature,and the anisotropic characteristics of undrained responses of saturated coral sandy soils.In particular,the advances made in the past decades are reviewed from the following aspects:(1)the characterization of factors that impact the mechanism and patterns of EPWP build-up;(2)the identification of liquefaction triggering in terms of the apparent viscosity and the average flow coefficient;(3)the establishment of the invariable form of strain-based,stress-based,or energy-based EPWP ratio formulas and the unique relationship between the new proxy of liquefaction resistance and the number of cycles required to reach liquefaction;(4)the establishment of the invariable form of the predictive formulas of small strain modulus and strain-dependent shear modulus;and(5)the investigation on the effects of stress-induced anisotropy on liquefaction susceptibility and dynamic deformation characteristics.Insights gained through the critical review of these advances in the past decades offer a perspective for future research to further resolve the fundamental issues concerning the liquefaction mechanism and responses of coral sandy sites subjected to cyclic loadings associated with seismic events in marine environments.

Low-temperature characteristicsof rubbers and performance testsof type 120 emergencyvalve diaphragms

Purpose–The type 120 emergency valve is an essential braking component of railway freight trains,butcorresponding diaphragms consisting of natural rubber(NR)and chloroprene rubber(CR)exhibit insufficientaging resistance and low-temperature resistance,respectively.In order to develop type 120 emergency valverubber diaphragms with long-life and high-performance,low-temperatureresistant CR and NR were processed.Design/methodology/approach–The physical properties of the low-temperature-resistant CR and NRwere tested by low-temperature stretching,dynamic mechanical analysis,differential scanning calorimetryand thermogravimetric analysis.Single-valve and single-vehicle tests of type 120 emergency valves werecarried out for emergency diaphragms consisting of NR and CR.Findings–The low-temperature-resistant CR and NR exhibited excellent physical properties.The elasticityand low-temperature resistance of NR were superior to those of CR,whereas the mechanical properties of thetwo rubbers were similar in the temperature range of 0℃–150℃.The NR and CR emergency diaphragms metthe requirements of the single-valve test.In the low-temperature single-vehicle test,only the low-temperaturesensitivity test of the NR emergency diaphragm met the requirements.Originality/value–The innovation of this study is that it provides valuable data and experience for futuredevelopment of type 120 valve rubber diaphragms.

Gravel hardness effect on compaction characteristics of gravelly soil

The compaction characteristics of gravelly soil are affected by gravel hardness.To investigate the evolution and influencing mechanism of different gravel hardness on the compaction characteristics of gravelly soil,heavy compaction tests and crushing tests were conducted on gravelly soils with gravels originated from hard,soft and extremely soft rocks.According to orthogonal experiments and variance analysis,it was found that hardness has a significant impact on the maximum dry density of gravelly soil,followed by gravel content,and lastly,moisture content.For gravel compositions with an average saturated uniaxial compressive strength less than 60 MPa,the order of compacted maximum dry density is soft gravels>hard gravels>extremely soft gravels.Each type of gravelly soil has a threshold for gravel content,with 60%for hard and soft gravels and 50%for extremely soft gravels.Beyond these thresholds,the compacted dry density decreases significantly.There is a certain interaction between hardness,gravel content,and moisture content.Higher hardness increases the influence of gravel content,whereas lower hardness increases the influence of moisture content.Gravelly soils with the coarse aggregate(CA)between 0.7 and 0.8 typically achieve higher dry densities after compaction.In addition,the prediction equations for the particle breakage rate and CA ratio in the Bailey method were proposed to estimate the compaction performance of gravelly soil preliminarily.The results further revealed the compaction mechanism of different gravelly soils and can provide reference for subgrade filling construction.

Transfer learning framework for multi-scale crack type classification with sparse microseismic networks

Rock fracture mechanisms can be inferred from moment tensors(MT)inverted from microseismic events.However,MT can only be inverted for events whose waveforms are acquired across a network of sensors.This is limiting for underground mines where the microseismic stations often lack azimuthal coverage.Thus,there is a need for a method to invert fracture mechanisms using waveforms acquired by a sparse microseismic network.Here,we present a novel,multi-scale framework to classify whether a rock crack contracts or dilates based on a single waveform.The framework consists of a deep learning model that is initially trained on 2400000+manually labelled field-scale seismic and microseismic waveforms acquired across 692 stations.Transfer learning is then applied to fine-tune the model on 300000+MT-labelled labscale acoustic emission waveforms from 39 individual experiments instrumented with different sensor layouts,loading,and rock types in training.The optimal model achieves over 86%F-score on unseen waveforms at both the lab-and field-scale.This model outperforms existing empirical methods in classification of rock fracture mechanisms monitored by a sparse microseismic network.This facilitates rapid assessment of,and early warning against,various rock engineering hazard such as induced earthquakes and rock bursts.

MSD-Net: Pneumonia Classification Model Based on Multi-Scale Directional Feature Enhancement

Computer-aided diagnosis of pneumonia based on deep learning is a research hotspot.However,there are some problems that the features of different sizes and different directions are not sufficient when extracting the features in lung X-ray images.A pneumonia classification model based on multi-scale directional feature enhancement MSD-Net is proposed in this paper.The main innovations are as follows:Firstly,the Multi-scale Residual Feature Extraction Module(MRFEM)is designed to effectively extract multi-scale features.The MRFEM uses dilated convolutions with different expansion rates to increase the receptive field and extract multi-scale features effectively.Secondly,the Multi-scale Directional Feature Perception Module(MDFPM)is designed,which uses a three-branch structure of different sizes convolution to transmit direction feature layer by layer,and focuses on the target region to enhance the feature information.Thirdly,the Axial Compression Former Module(ACFM)is designed to perform global calculations to enhance the perception ability of global features in different directions.To verify the effectiveness of the MSD-Net,comparative experiments and ablation experiments are carried out.In the COVID-19 RADIOGRAPHY DATABASE,the Accuracy,Recall,Precision,F1 Score,and Specificity of MSD-Net are 97.76%,95.57%,95.52%,95.52%,and 98.51%,respectively.In the chest X-ray dataset,the Accuracy,Recall,Precision,F1 Score and Specificity of MSD-Net are 97.78%,95.22%,96.49%,95.58%,and 98.11%,respectively.This model improves the accuracy of lung image recognition effectively and provides an important clinical reference to pneumonia Computer-Aided Diagnosis.

YOLO-MFD:Remote Sensing Image Object Detection with Multi-Scale Fusion Dynamic Head

Remote sensing imagery,due to its high altitude,presents inherent challenges characterized by multiple scales,limited target areas,and intricate backgrounds.These inherent traits often lead to increased miss and false detection rates when applying object recognition algorithms tailored for remote sensing imagery.Additionally,these complexities contribute to inaccuracies in target localization and hinder precise target categorization.This paper addresses these challenges by proposing a solution:The YOLO-MFD model(YOLO-MFD:Remote Sensing Image Object Detection withMulti-scale Fusion Dynamic Head).Before presenting our method,we delve into the prevalent issues faced in remote sensing imagery analysis.Specifically,we emphasize the struggles of existing object recognition algorithms in comprehensively capturing critical image features amidst varying scales and complex backgrounds.To resolve these issues,we introduce a novel approach.First,we propose the implementation of a lightweight multi-scale module called CEF.This module significantly improves the model’s ability to comprehensively capture important image features by merging multi-scale feature information.It effectively addresses the issues of missed detection and mistaken alarms that are common in remote sensing imagery.Second,an additional layer of small target detection heads is added,and a residual link is established with the higher-level feature extraction module in the backbone section.This allows the model to incorporate shallower information,significantly improving the accuracy of target localization in remotely sensed images.Finally,a dynamic head attentionmechanism is introduced.This allows themodel to exhibit greater flexibility and accuracy in recognizing shapes and targets of different sizes.Consequently,the precision of object detection is significantly improved.The trial results show that the YOLO-MFD model shows improvements of 6.3%,3.5%,and 2.5%over the original YOLOv8 model in Precision,map@0.5 and map@0.5:0.95,separately.These results illustrate the clear advantages of the method.

Multi-scale physics-informed neural networks for solving high Reynolds number boundary layer flows based on matched asymptotic expansions

Multi-scale system remains a classical scientific problem in fluid dynamics,biology,etc.In the present study,a scheme of multi-scale Physics-informed neural networks is proposed to solve the boundary layer flow at high Reynolds numbers without any data.The flow is divided into several regions with different scales based on Prandtl's boundary theory.Different regions are solved with governing equations in different scales.The method of matched asymptotic expansions is used to make the flow field continuously.A flow on a semi infinite flat plate at a high Reynolds number is considered a multi-scale problem because the boundary layer scale is much smaller than the outer flow scale.The results are compared with the reference numerical solutions,which show that the msPINNs can solve the multi-scale problem of the boundary layer in high Reynolds number flows.This scheme can be developed for more multi-scale problems in the future.

MSC-YOLO:Improved YOLOv7 Based on Multi-Scale Spatial Context for Small Object Detection in UAV-View

Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in thefield of small object detection on unmanned aerial vehicles(UAVs).This task is challenging due to variations inUAV flight altitude,differences in object scales,as well as factors like flight speed and motion blur.To enhancethe detection efficacy of small targets in drone aerial imagery,we propose an enhanced You Only Look Onceversion 7(YOLOv7)algorithm based on multi-scale spatial context.We build the MSC-YOLO model,whichincorporates an additional prediction head,denoted as P2,to improve adaptability for small objects.We replaceconventional downsampling with a Spatial-to-Depth Convolutional Combination(CSPDC)module to mitigatethe loss of intricate feature details related to small objects.Furthermore,we propose a Spatial Context Pyramidwith Multi-Scale Attention(SCPMA)module,which captures spatial and channel-dependent features of smalltargets acrossmultiple scales.This module enhances the perception of spatial contextual features and the utilizationof multiscale feature information.On the Visdrone2023 and UAVDT datasets,MSC-YOLO achieves remarkableresults,outperforming the baseline method YOLOv7 by 3.0%in terms ofmean average precision(mAP).The MSCYOLOalgorithm proposed in this paper has demonstrated satisfactory performance in detecting small targets inUAV aerial photography,providing strong support for practical applications.

Molecular Epidemiology and Clinical Characteristics of Hand, Foot and Mouth Disease in North Sichuan Region, China, 2018-2023: A Descriptive Study

Background: Hand, foot and mouth disease (HFMD) remains an important public health problem in China. Many studies on the epidemiological characteristics of HFMD have been reported, but studies in North Sichuan region have been neglected. Methods: HFMD-related enterovirus infected cases were clinically confirmed and underwent real-time RT-PCR (rRT-PCR) from May 2018 to October 2023 in Guangyuan Central Hospital. Results: During 2018-2023, other EV (437 cases, 81.08%) was the most predominant serotype followed by CV-A16 (94 cases, 17.44%), EV-A71 (8 cases, 1.48%) was the least predominant serotype. Peak infections occurred in July and October. There were no significant differences in gender, age and serotypes. HFMD was concentrated in children under 47 months of age, with the highest incidence in children aged 12 - 23 months and the highest proportion of other EV infections in the whole age group. COVID-19 did not cause significant changes in gender, age and serotype. Overall, there was a significant increase in the proportion of children aged 12 - 23 months infected with CV-A16, and an increase in the proportion of children aged over 36 months infected with other EVs. Conclusions: The incidence of HFMD caused by EV-A71 has decreased significantly, and other EVs have become the main pathogens of HFMD in North Sichuan region in recent years. In the prevention and control of CV-A16, more attention should be paid to children aged 12 - 23 months and the dominant serotype should be closely monitored. Our study highlights the importance of developing of new diagnostic reagents and vaccines for the prevention and control of enterovirus infection. This study for the first time provides insights into district interventions to local conditions.

Sleep quality and characteristics of older adults with acute cardiovascular disease

Sleep plays a vital role in restoring the physical and mental health of people with cardiovascular disease.However,the hospital setting is not a conducive environment for sleep.Sleep interruptions by members of the care team,including vital sign checks,medication delivery,and blood draws for laboratory investigations,are routinely done in many hospitals.Frequent interruptions by staff and noise by other patients have been cited as barriers to restorative sleep in the hospital.

Combined Insights from Leachate Structure and Microstructure Characteristics for Eating Quality of Convenience Rice Processed by Super-Heated and Pressurized Steam Technologies

Convenience rice has become widely popular due to its easy availability for cooking. This study investigated the starch structure and composition of leachate and the microstructure of reheated convenience rice using novel processing technologies: super-heated steaming(SHS), auto-electric cooking(AEC), and pressurized-steam cooking(PSC). Additionally, the effect of two different target water contents(58% and 63%) was also evaluated. The PSC_63% sample had the highest total solids and amylopectin amount in the leachate. The amylopectin amount in the leachate differed significantly based on the targeted water content. Morphological characterization revealed that the swelling of starch and the coated layer on the surface of rice grains were most pronounced in the PSC_63% sample due to the pressure processing. The textural hardness of the AEC_58% sample was much higher than that of the other samples. The PSC_63% sample had the highest textural adhesiveness value, which can be attributed to the highest amylopectin amount in the leachate. Sensory characterization showed that the PSC_63% sample had the highest glossiness, whiteness, moistness, and overall acceptability. The principal component analysis score plots presented substantial differences in the leachate and textural and sensory characteristics of reheated convenience rice among the different processing technologies.

Some of the Chemical and Physical Characteristics of the Graff River in Kut City, Iraq

Some of the chemical and physical water qualities of the Graff River in the city of Kut were studied, and for two sites of the river, One was at the Crimea site, the other in the Jihad district, and for the period from October/2018 to March/2019, Seven variables of river water have been analyzed: temperature PH, electrical conductivity, TDS, turbidity, alkaline, and chloride. The results showed that most of the chemical and physical water properties of the river were in normal proportions and did not rise, except for the turbidity, which was at a very high level, and that the pH values were close to the basal side. The results of the statistical analysis revealed positive significant relationships between the pH and (chloride and TDS). On the other hand, between electrical conductivity and both previous variables as well. And a negative significant connection between temperature and alkaline.

Multi-scale Modeling and Finite Element Analyses of Thermal Conductivity of 3D C/SiC Composites Fabricating by Flexible-Oriented Woven Process

Thermal conductivity is one of the most significant criterion of three-dimensional carbon fiber-reinforced SiC matrix composites(3D C/SiC).Represent volume element(RVE)models of microscale,void/matrix and mesoscale proposed in this work are used to simulate the thermal conductivity behaviors of the 3D C/SiC composites.An entirely new process is introduced to weave the preform with three-dimensional orthogonal architecture.The 3D steady-state analysis step is created for assessing the thermal conductivity behaviors of the composites by applying periodic temperature boundary conditions.Three RVE models of cuboid,hexagonal and fiber random distribution are respectively developed to comparatively study the influence of fiber package pattern on the thermal conductivities at the microscale.Besides,the effect of void morphology on the thermal conductivity of the matrix is analyzed by the void/matrix models.The prediction results at the mesoscale correspond closely to the experimental values.The effect of the porosities and fiber volume fractions on the thermal conductivities is also taken into consideration.The multi-scale models mentioned in this paper can be used to predict the thermal conductivity behaviors of other composites with complex structures.