A PRELIMINARY STUDY ON THE 3DVAR ASSIMILATION OF THE AMSU-A DATA IN SPACE-TIME MULTISCALE ANALYSIS SYSTEM

Assimilating satellite radiances into Numerical Weather Prediction(NWP) models has become an important approach to increase the accuracy of numerical weather forecasting. In this study, the assimilation technique scheme was employed in NOAA's STMAS(Space-Time Multiscale Analysis System) to assimilate AMSU-A radiances data.Channel selection sensitivity experiments were conducted on assimilated satellite data in the first place. Then, real case analysis of AMSU-A data assimilation was performed. The analysis results showed that, following assimilating of AMSU-A channels 5-11 in STMAS, the objective function quickly converged, and the channel vertical response was consistent with the AMSU-A weighting function distribution, which suggests that the channels can be used in the assimilation of satellite data in STMAS. With the case of the Typhoon Morakot in Taiwan Island in August 2009 as an example, experiments on assimilated and unassimilated AMSU-A radiances data were designed to analyze the impact of the assimilation of satellite data on STMAS. The results demonstrated that assimilation of AMSU-A data provided more accurate prediction of the precipitation region and intensity, and especially, it improved the 0-6h precipitation forecast significantly.

Multiscale analysis of the contents of palmatine in the Nature populations of Phellodendron amurense in Northeast China

Palmatine is a valuable ingredient in Chinese medicine that is produced by Phellodendron amurense Rupr. The contents of palmatine content in root bark, trunk bark, perennial branch bark, annual branches, and leaves of the trees with different ages and geographies in Northeast China were measured by high-performance liquid chromatography. The contents of palmatine in the barks of root, trunk, and perennial branch were significantly higher than those in annual branches and leaves. The contents of palmatine in trunk bark and root bark from Lesser Khingan Mountains increased with age, which is significantly opposite to other three vegetation types. The contents of palmatine in perennial branch bark, annual bark and leaves had no significant reg- ularity. Moreover, the contents of palmatine in samples of root bark, trunk bark, perennial branch bark and annual bark varied significantly with latitude. The nature populations of P. amurense growing at low latitude contained significantly more palmatine than those growing at high latitude. These results provide a scientific basis for the reasonable cultivation and efficient utilization of P. amurense.

Multiscale Analysis of the Effect of Debris on Fretting Wear Process Using a Semi-Concurrent Method

Fretting wear is a phenomenon,in which wear happens between two oscillatory moving contact surfaces in microscale amplitude.In this paper,the effect of debris between pad and specimen is analyzed by using a semi-concurrent multiscale method.Firstly,the macroscale fretting wear model is performed.Secondly,the part with the wear profile is imported from the macroscale model to a microscale model after running in stage.Thirdly,an effective pad’s radius is extracted by analyzing the contact pressure in order to take into account the effect of the debris.Finally,the effective radius is up-scaled from the microscale model to the macroscale model,which is used after running in stage.In this way,the effect of debris is considered by changing the radius of the pad in the macroscale model.Due to the smaller number of elements in the microscale model compared with the macroscale model containing the debris layer,the semi-concurrent method proposed in this paper is more computationally efficient.Moreover,the results of this semi-concurrent method show a better agreement with experimental data,compared to the results of the model ignoring the effect of debris.

Multiscale analysis of single- and multiple-pulse laser-induced damages in HfO_2/SiO_2 multilayer dielectric films at 532 nm

Nanosecond single- and multiple-pulse laser damage studies on HfOffSiO2 high-reflection （HR） coatings are performed at 532 nm. For single-pulse irradiation, the damage is attributed to the defects and the electric intensity distribution in the multilayer thin films. When the defect density in the irradiated area is high, delami- nation is observed. Other than the 1064 nm laser damage, the plasma scalding of the 532 nm laser damage is not pits-centered for normal incidence, and the size of the plasma scalding has no relation to the defect density and position, but increases with the laser fluence. For multiple-pulse irradiations, some damage sites show deeper precursors than those from the single-shot irradiation due to the accumulation effects. The cumulative laser- induced damages behave as pits without the presence of plasma scalding, which is unaffected by the laser fluence and shot numbers. The damage morphologies and depth information both confirm the fatigue effect of a HfO2/SiO2 HR coating under 532 nm laser irradiation.

Microstructural Modeling and Multiscale Mechanical Properties Analysis of Cancellous Bone

This paper is devoted to the microstructure geometric modeling and mechanical properties computation of cancellous bone.The microstructure of the cancellous bone determines its mechanical properties and a precise geometric modeling of this structure is important to predict the material properties.Based on the microscopic observation,a new microstructural unit cell model is established by introducing the Schwarz surface in this paper.And this model is very close to the real microstructure and satisfies the main biological characteristics of cancellous bone.By using the unit cell model,the multiscale analysis method is newly applied to predict the mechanical properties of cancellous bone.The effective stiffness parameters are calculated by the up-scaling multi-scale analysis.And the distribution of microscopic stress in cancellous bone is determined through the down-scaling procedure.In addition,the effect of porosity on the stiffness parameters is also investigated.The predictive mechanical properties are in good agreement with the available experimental results,which verifies the applicability of the proposed unit cell model and the validness of the multiscale analysis method to predict the mechanical properties of cancellous bone.

Multiscale analysis of composite material reinforced by randomly-dispersed particles

A multiscale analysis method is presented in which detailed information on the microscopic level is incorporated into macroscopic models capable of simulating damage evolution and ultimate failure.The composite considered is reinforced by randomly-dispersed particles,which reflects the statistical characteristics of real materials,such as cement-based materials.Specifically,a three-dimensional material body is decomposed into many unit cells.Each unit cell is reinforced by a cylindrical particle,the orientation of which is characterized by three Euler angles generated by the random number generator.Based on a detailed finite element analysis,the material properties of the representative volume element are obtained.As verification,the properties of the cylindrical particles are set equal to those of the matrix and the computed‘composite’properties reduce exactly to those of the‘isotropic’material,as expected.Through coordinate transformation,the effective material properties of each unit cell are calculated.The assembly of stiffness matrices of all unit cells leads to the stiffness matrix of the whole specimen.Under the simple tension loading condition,the initial damaged unit cell can be identified according to the vonMises yield criterion.The stiffness of the damaged unit cell will then be reduced to zero and it will cause stress redistribution and trigger further damage.It was found that the reinforcement is effective to mitigate and arrest the damage propagation,and therefore prolongs the material’s lifetime.These results suggest that the hierarchical coupling approaches used here may be useful for material design and failure protection in composites.

A Multiscale Method for Damage Analysis of Quasi-Brittle Heterogeneous Materials

A novel multiscale algorithm based on the higher-order continuum at both micro-and macrostructural level is proposed for the consideration of the quasi-brittle damage response of heterogeneous materials.Herein,the microlevel damage is modelled by the degradation of the homogenized stress and tangent stiffness tensors,which are then upscaled to govern the localization at the macrolevel.The C^1 continuity finite element employing a modified case of Mindlin’s form II strain energy density is derived for the softening analysis.To the authors’knowledge,the finite element discretization based on the strain gradient theory is applied for the modeling of damage evolution at the microstructural level for heterogeneous materials for the first time.The advantage of the novel C1 finite element formulation in comparison with the standard finite element discretization in terms of the regularization efficiency as well as the objectivity has been shown.An isotropic damage law is used for the reduction of the constitutive and nonlocal material behaviour,which is necessary for the physically correct description of the localization formation in quasi-brittle materials.The capabilities of the derived finite element to capture the fully developed localization zones are tested on a random representative volume element(RVE)for several different loading cases.By employing the conventional second-order computational homogenization,the microstructural material constitutive response is averaged over the whole RVE area.In order to model the loss of structural integrity when sharp localization is formed across RVE,the specific conditions which detect a completely formed localization zone are developed.A new failure criterion at the microstructural level has been proposed.The derived finite element formulation,as well as the multiscale damage algorithm,are implemented into the finite element program ABAQUS.The capabilities of the presented multiscale scheme to capture the effects of the deformation localization are demonstrated by few benchmark numerical examples.

Multiscale Nonlinear Thermo-Mechanical Coupling Analysis of Composite Structures with Quasi-Periodic Properties

This paper reports a multiscale analysis method to predict the thermomechanical coupling performance of composite structures with quasi-periodic properties.In these material structures,the configurations are periodic,and the material coefficients are quasi-periodic,i.e.,they depend not only on the microscale information but also on the macro location.Also,a mutual interaction between displacement and temperature fields is considered in the problem,which is our particular interest in this study.The multiscale asymptotic expansions of the temperature and displacement fields are constructed and associated error estimation in nearly pointwise sense is presented.Then,a finite element-difference algorithm based on the multiscale analysis method is brought forward in detail.Finally,some numerical examples are given.And the numerical results show that the multiscale method presented in this paper is effective and reliable to study the nonlinear thermo-mechanical coupling problem of composite structures with quasiperiodic properties.

The spatial multiscale variability of heavy metals based on factorial kriging analysis: A case study in the northeastern Beibu Gulf

Factorial kriging analysis is applied to the research on the spatial multiscale variability of heavy metals in submarine. It is used to analyze the multiscale spatial structures of seven heavy metals, Ni, Cu, Zn, Pb, Cr, As and Cd in the surface sediment from the northeastern of Beibu Gulf, identify and separate spatial variations at different scales of heavy metals, and discuss the provenance of heavy metals and the influencing factors. The results show that the existence of three-scale spatial variations those consist of nugget effect, a spherical structure with range of 30 km（short-range scale） and a spherical structure with range of 140 km（long-range scale） in the linear model of coregionalization fitted. The spatial distribution features of seven heavy metals at short-range scale reflect ＂spot-like＂ or ＂stripe-like＂ local-scale spatial variations; the spatial distribution features of the seven heavy metals at long-range scale represent ＂slice-like＂ regional-scale spatial variations. At local scale, Zn, Cr, Ni,Cu, Pb and Cd are derived primarily from parent materials of Hainan Island, Leizhou Peninsula and Guangxi land, whose spatial distribution characteristics are controlled by granularity of sediments, while As is influenced dominantly by human pollution components from Hainan Island and Leizhou Peninsula. At regional scale, Zn,Cr, Ni and Cu originate primarily from parent rock materials of Leizhou Peninsula and Hainan Island, secondly from Guangxi land; As originated primarily from parent rock materials from Hainan Island, secondly from Leizhou Peninsula and Guangxi land. These metals are transported and migrated with sediments dominated by the anticlockwise circulation of Beibu Gulf year-round, deposited in ＂convergence center＂, forming the whole sedimentary pattern in direction of NWW-NNW at regional scale. The difference in distribution type between As and other metals at regional scale is mainly due to their different geochemical behavior.

A multiscale 3D finite element analysis of fluid/solute transport in mechanically loaded bone

The transport of fluid, nutrients, and signaling molecules in the bone lacunar-canalicular system （LCS） is critical for osteocyte survival and function. We have applied the fluorescence recovery after photobleaching （FRAP） approach to quantify load-induced fluid and solute transport in the LCS in situ, but the measurements were limited to cortical regions 30-50 μm underneath the periosteum due to the constrains of laser penetration. With this work, we aimed to expand our understanding of load-induced fluid and solute transport in both trabecular and cortical bone using a multiscaled image-based finite element analysis （FEA） approach. An intact murine tibia was first re-constructed from microCT images into a three-dimensional （3D） linear elastic FEA model, and the matrix deformations at various locations were calculated under axial loading. A segment of the above 3D model was then imported to the biphasic poroelasticity analysis platform （FEBio） to predict load-induced fluid pressure fields, and interstitial solute/fluid flows through LCS in both cortical and trabecular regions. Further, secondary flow effects such as the shear stress and/or drag force acting on osteocytes, the presumed mechano-sensors in bone, were derived using the previously developed ultrastructural model of Brinkman flow in the canaliculi. The material properties assumed in the FEA models were validated against previously obtained strain and FRAP transport data measured on the cortical cortex. Our results demonstrated the feasibility of this computational approach in estimating the fluid flux in the LCS and the cellular stimulation forces （shear and drag forces） for osteocytes in any cortical and trabecular bone locations, allowing further studies of how the activation of osteocytes correlates with in vivo functional bone formation. The study provides a promising platform to reveal potential cellular mechanisms underlying the anabolic power of exercises and physical activities in treating patients with skeletal deficiencies.

A spillover network analysis of the global crude oil market:Evidence from the post-financial crisis era

The frequent occurrence of geopolitical crises in the post-financial crisis era is driving the rethinking behind whether the global crude oil market is still a highly connected"great pool".Using the spillover network model suggested by Baruník and Krehlík(2018),and the daily data of 31 global crude oil markets from 2009 to 2019,this study examines the return and volatility spillover effects and their timevarying behavior in six crude oil market segments at different timescales.The findings indicate that heterogeneity exists in the co-movements between global crude oil markets in the post-financial crisis era.In the medium term,both return and volatility spillover effects are not significant,which makes the diversified portfolio strategy useful.Prices in the Europe and Central Asian regions take the lead in return spillovers.In contrast,Asia-Pacific regional prices contribute the most in terms of volatility spillovers.Long-term volatility spillovers increase sharply when confronted with oil-related events in the postfinancial crisis era.Therefore,policymakers should take effective measures to prevent any large-scale risk transmission in the long run.

Multiscale Failure Mechanism Analysis of SiC Fiber‑Reinforced TC17 Composite Subjected to Transverse Tensile Loading at Elevated Temperature

This study presents a multiscale method to evaluate the transverse tensile strength and failure mechanism of SiC_(f)/TC17 cruciform specimen machined from a large-size ring.The mechanical properties and failure of the specimen were evaluated through a macroscale model under transverse tensile loading at 200°C.A mesoscale model was developed to analyze the transverse tensile behavior and failure of the composite specimen.Interfacial debonding,plastic deformation of matrix and cladding,and damage to the composite core were incorporated into the mesoscopic and macroscopic models.The stress–strain curves and fracture modes obtained from the numerical simulation showed good agreement with the experimental curves,acoustic emission test results,and fracture morphology.The simulation results suggested that the damage to the central region interface and the plastic deformation of the matrix initiated first and propagated outwards.Subsequently,the interfacial failure,matrix failure,and formation of macro-crack developed,which led to the crack of the titanium matrix composite core.Finally,cladding was plastically deformed and crack developed,which led to the severe failure of the cruciform specimen.

Detection of healthy and pathological heartbeat dynamics in ECG signals using multivariate recurrence networks with multiple scale factors

The electrocardiogram(ECG)is one of the physiological signals applied in medical clinics to determine health status.The physiological complexity of the cardiac system is related to age,disease,etc.For the investigation of the effects of age and cardiovascular disease on the cardiac system,we then construct multivariate recurrence networks with multiple scale factors from multivariate time series.We propose a new concept of cross-clustering coefficient entropy to construct a weighted network,and calculate the average weighted path length and the graph energy of the weighted network to quantitatively probe the topological properties.The obtained results suggest that these two network measures show distinct changes between different subjects.This is because,with aging or cardiovascular disease,a reduction in the conductivity or structural changes in the myocardium of the heart contributes to a reduction in the complexity of the cardiac system.Consequently,the complexity of the cardiac system is reduced.After that,the support vector machine(SVM)classifier is adopted to evaluate the performance of the proposed approach.Accuracy of 94.1%and 95.58%between healthy and myocardial infarction is achieved on two datasets.Therefore,this method can be adopted for the development of a noninvasive and low-cost clinical prognostic system to identify heart-related diseases and detect hidden state changes in the cardiac system.

Research on Wavelet-Based Algorithm for Image Contrast Enhancement

A novel wavelet-based algorithm for image enhancement is proposed in the paper. On the basis of multiscale analysis, the proposed algorithm solves efficiently the problem of noise over-enhancement, which commonly occurs in the traditional methods for contrast enhancement. The decomposed coefficients at same scales are processed by a nonlinear method, and the coefficients at different scales are enhanced in different degree. During the procedure, the method takes full advantage of the properties of Human visual system so as to achieve better performance. The simulations demonstrate that these characters of the proposed approach enable it to fully enhance the content in images, to efficiently alleviate the enhancement of noise and to achieve much better enhancement effect than the traditional approaches. Key words wavelet transform - image contrast enhancement - multiscale analysis CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (69931010)Biography: Wu Ying-qian (1974-), male, Ph. D, research direction: image processing, image compression and wavelet.

A generic approach to the dynamical interpretation of ocean-atmosphere processes

This paper summarizes the recent development of a portable self-contained system to unravel the intricate multiscale dynamical processes from real oceanic flows, which are in nature highly nonlinear and intermittent in space and time. Of particular focus are the interactions among largescale, mesoscale, and submesoscale processes.We firsu introduce the concept of scale window, and an orthogonal subspace decomposition technigue called multiscale window transform (MWT). Established on MWT is a rigorous formalism of multiscale transport, perfect transfer, and multiscale conversion, which makes a new methodology, multiscale energy and vorticity analysis (MS-EVA). A direct application of the MS-EVA is the development of a novel localized instability analysis, generalizing the classical notion of hydrodynamic instability to finite amplitude processes on irregularly variable domains. The theory is consistent with the analytical solutions of Eady's model and Kuo's model, the benchmark models of baroclinic instability and barotropic instability; it is further validated with a vortex shedding control problem. We have put it to application with a variety of complicated real ocean problems, which would be otherwise very difficult, if not impossible, to tackle. Briefly shown in this paper include the dynamical studies of a highly variable open ocean front, and a complex coastal ocean circulation. In the former, it is found that underlying the frontal meandering is a convective instability followed by an absolute instability, and correspondingly a rapid spatially amplifying mode locked into a temporally growing mode; in the latter, we see a real ocean example of how upwelling can be driven by winds through nonlinear instability, and how winds may excite the ocean via an avenue which is distinctly different from the classical paradigms. This system is mathematically rigorous, physically robust, and practically straightforward.

Multiscale classification and its application to process monitoring

Multiscale classification has potential advantages for monitoring industrial processes generally driven by events in different time and frequency domains.In this study, we adopt stationary wavelet transform for multiscale analysis and propose an applicable scale selection method to obtain the most discriminative scale features.Then using the multiscale features, we construct two classifiers:(1) a supported vector machine(SVM) classifier based on classification distance, and(2) a Bayes classifier based on probability estimation.For the SVM classifier, we use 4-fold cross-validation and grid-search to obtain the optimal parameters.For the Bayes classifier, we introduce dimension reduction techniques including kernel Fisher discriminant analysis(KFDA) and principal component analysis(PCA) to investigate their influence on classification accuracy.We tested the classifiers with two simulated benchmark processes:the continuous stirred tank reactor(CSTR) process and the Tennessee Eastman(TE) process.We also tested them on a real polypropylene production process.The performance comparison among the classifiers in different scales and scale combinations showed that when datasets present typical scale features, the multiscale classifier had higher classification accuracy than conventional single scale classifiers.We also found that dimension reduction can generally contribute to a better classification in our tests.

A Multiscale Algorithm for Heat Conduction-Radiation Problems in Porous Materials with Quasi-Periodic Structures

This paper develops a second-order multiscale asymptotic analysis and numerical algorithms for predicting heat transfer performance of porous materials with quasi-periodic structures.In these porousmaterials,they have periodic configurations and associated coefficients are dependent on the macro-location.Also,radiation effect at microscale has an important influence on the macroscopic temperature fields,which is our particular interest in this study.The characteristic of the coupled multiscale model between macroscopic scale and microscopic scale owing to quasi-periodic structures is given at first.Then,the second-ordermultiscale formulas for solving temperature fields of the nonlinear problems are constructed,and associated explicit convergence rates are obtained on some regularity hypothesis.Finally,the corresponding finite element algorithms based on multiscale methods are brought forward and some numerical results are given in detail.Numerical examples including different coefficients are given to illustrate the efficiency and stability of the computational strategy.They show that the expansions to the second terms are necessary to obtain the thermal behavior precisely,and the local and global oscillations of the temperature fields are dependent on the microscopic and macroscopic part of the coefficients respectively.

Advances of physics-based precision modeling and simulation for manufacturing processes

The development of manufacturing process concerns precision, comprehensiveness, agileness, high efficiency and low cost. The numerical simulation has become an important method for process design and optimization. Physics-based modeling was proposed to promote simulations with a high accuracy. In this paper, three cases, on material properties, precise boundary conditions, and micro-scale physical models, have been discussed to demonstrate how physics-based modeling can improve manufacturing simulation. By using this method, manu- facturing process can be modeled precisely and optimized for getting better performance.

Weave geometry generation avoiding interferences for mesoscale RVEs

An algorithm which allows the generation of representative volume elements(RVEs) for complex woven and warp-interlaced fiber-reinforced composite topologies while avoiding unphysical tow intersections is presented. This is achieved by extending an existing RVE generation strategy in two significant ways:(1) the local cross section shape of the tow is adjusted depending on the local tow curvature in a way that preserves the cross sectional area of the tow, and(2) the elementary crimp interval is separated into a planar and a transition region. The modifications facilitate the generation of a wide range of elaborate textile topologies without tow intersections, which are present without the proposed modifications unless complex tow to tow contact models are introduced. The mechanical properties of plain weaves were predicted based on the topology generated with the proposed algorithm as well as based on RVEs which were constructed based on actual micrographs, i.e. a "digital twin" of the actual microstructure. A comparison of the predicted mechanical properties based on finite element and Multiscale Generalized Method of Cells techniques shows close agreement. However, some differences exist with respect to experimentally determined material parameters due to the finite dimensions of the specimens. Lastly,mechanical properties of multilayered weaves are predicted with the finite element method. The considered material systems are carbon fiber in epoxy matrix as well as C/C-SiC. However, the procedure is applicable to a wide range of material systems.