A multiscale filter for noise reduction of low-dose cone beam projections

NASA Astrophysics Data System (ADS)

Yao, Weiguang; Farr, Jonathan B.

2015-08-01

The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, \\text{exp}≤ft(-{{x}2}/2σ f2\\right) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of {σf} , which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ f2 is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024   ×   768 pixels.

Towards practical multiscale approach for analysis of reinforced concrete structures

NASA Astrophysics Data System (ADS)

Moyeda, Arturo; Fish, Jacob

2017-12-01

We present a novel multiscale approach for analysis of reinforced concrete structural elements that overcomes two major hurdles in utilization of multiscale technologies in practice: (1) coupling between material and structural scales due to consideration of large representative volume elements (RVE), and (2) computational complexity of solving complex nonlinear multiscale problems. The former is accomplished using a variant of computational continua framework that accounts for sizeable reinforced concrete RVEs by adjusting the location of quadrature points. The latter is accomplished by means of reduced order homogenization customized for structural elements. The proposed multiscale approach has been verified against direct numerical simulations and validated against experimental results.

On Multiscale Modeling: Preserving Energy Dissipation Across the Scales with Consistent Handshaking Methods

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Arnold, Steven M.; Waas, Anthony M.

2013-01-01

A mesh objective crack band model was implemented within the generalized method of cells micromechanics theory. This model was linked to a macroscale finite element model to predict post-peak strain softening in composite materials. Although a mesh objective theory was implemented at the microscale, it does not preclude pathological mesh dependence at the macroscale. To ensure mesh objectivity at both scales, the energy density and the energy release rate must be preserved identically across the two scales. This requires a consistent characteristic length or localization limiter. The effects of scaling (or not scaling) the dimensions of the microscale repeating unit cell (RUC), according to the macroscale element size, in a multiscale analysis was investigated using two examples. Additionally, the ramifications of the macroscale element shape, compared to the RUC, was studied.

Multiscale Modeling: A Review

NASA Astrophysics Data System (ADS)

Horstemeyer, M. F.

This review of multiscale modeling covers a brief history of various multiscale methodologies related to solid materials and the associated experimental influences, the various influence of multiscale modeling on different disciplines, and some examples of multiscale modeling in the design of structural components. Although computational multiscale modeling methodologies have been developed in the late twentieth century, the fundamental notions of multiscale modeling have been around since da Vinci studied different sizes of ropes. The recent rapid growth in multiscale modeling is the result of the confluence of parallel computing power, experimental capabilities to characterize structure-property relations down to the atomic level, and theories that admit multiple length scales. The ubiquitous research that focus on multiscale modeling has broached different disciplines (solid mechanics, fluid mechanics, materials science, physics, mathematics, biological, and chemistry), different regions of the world (most continents), and different length scales (from atoms to autos).

Stretchable conducting materials with multi-scale hierarchical structures for biomedical applications

NASA Astrophysics Data System (ADS)

Kim, Hyun; Shim, Bong Sup

2014-08-01

Electrogenetic tissues in human body such as central and peripheral nerve systems, muscular and cardiomuscular systems are soft and stretchable materials. However, most of the artificial materials, interfacing with those conductive tissues, such as neural electrodes and cardiac pacemakers, have stiff mechanical properties. The rather contradictory properties between natural and artificial materials usually cause critical incompatibility problems in implanting bodymachine interfaces for wide ranges of biomedical devices. Thus, we developed a stretchable and electrically conductive material with complex hierarchical structures; multi-scale microstructures and nanostructural electrical pathways. For biomedical purposes, an implantable polycaprolactone (PCL) membrane was coated by molecularly controlled layer-bylayer (LBL) assembly of single-walled carbon nanotubes (SWNTs) or poly(3,4-ethylenedioxythiophene) (PEDOT). The soft PCL membrane with asymmetric micro- and nano-pores provides elastic properties, while conductive SWNT or PEDOT coating preserves stable electrical conductivity even in a fully stretched state. This electrical conductivity enhanced ionic cell transmission and cell-to-cell interactions as well as electrical cellular stimulation on the membrane. Our novel stretchable conducting materials will overcome long-lasting challenges for bioelectronic applications by significantly reducing mechanical property gaps between tissues and artificial materials and by providing 3D interconnected electro-active pathways which can be available even at a fully stretched state.

Robust visual tracking via multiscale deep sparse networks

NASA Astrophysics Data System (ADS)

Wang, Xin; Hou, Zhiqiang; Yu, Wangsheng; Xue, Yang; Jin, Zefenfen; Dai, Bo

2017-04-01

In visual tracking, deep learning with offline pretraining can extract more intrinsic and robust features. It has significant success solving the tracking drift in a complicated environment. However, offline pretraining requires numerous auxiliary training datasets and is considerably time-consuming for tracking tasks. To solve these problems, a multiscale sparse networks-based tracker (MSNT) under the particle filter framework is proposed. Based on the stacked sparse autoencoders and rectifier linear unit, the tracker has a flexible and adjustable architecture without the offline pretraining process and exploits the robust and powerful features effectively only through online training of limited labeled data. Meanwhile, the tracker builds four deep sparse networks of different scales, according to the target's profile type. During tracking, the tracker selects the matched tracking network adaptively in accordance with the initial target's profile type. It preserves the inherent structural information more efficiently than the single-scale networks. Additionally, a corresponding update strategy is proposed to improve the robustness of the tracker. Extensive experimental results on a large scale benchmark dataset show that the proposed method performs favorably against state-of-the-art methods in challenging environments.

Fusion of infrared polarization and intensity images based on improved toggle operator

NASA Astrophysics Data System (ADS)

Zhu, Pan; Ding, Lei; Ma, Xiaoqing; Huang, Zhanhua

2018-01-01

Integration of infrared polarization and intensity images has been a new topic in infrared image understanding and interpretation. The abundant infrared details and target from infrared image and the salient edge and shape information from polarization image should be preserved or even enhanced in the fused result. In this paper, a new fusion method is proposed for infrared polarization and intensity images based on the improved multi-scale toggle operator with spatial scale, which can effectively extract the feature information of source images and heavily reduce redundancy among different scale. Firstly, the multi-scale image features of infrared polarization and intensity images are respectively extracted at different scale levels by the improved multi-scale toggle operator. Secondly, the redundancy of the features among different scales is reduced by using spatial scale. Thirdly, the final image features are combined by simply adding all scales of feature images together, and a base image is calculated by performing mean value weighted method on smoothed source images. Finally, the fusion image is obtained by importing the combined image features into the base image with a suitable strategy. Both objective assessment and subjective vision of the experimental results indicate that the proposed method obtains better performance in preserving the details and edge information as well as improving the image contrast.

Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics

PubMed Central

Zhang, Peng; Gao, Chao; Zhang, Na; Slepian, Marvin J.; Deng, Yuefan; Bluestein, Danny

2014-01-01

We developed a multiscale particle-based model of platelets, to study the transport dynamics of shear stresses between the surrounding fluid and the platelet membrane. This model facilitates a more accurate prediction of the activation potential of platelets by viscous shear stresses - one of the major mechanisms leading to thrombus formation in cardiovascular diseases and in prosthetic cardiovascular devices. The interface of the model couples coarse-grained molecular dynamics (CGMD) with dissipative particle dynamics (DPD). The CGMD handles individual platelets while the DPD models the macroscopic transport of blood plasma in vessels. A hybrid force field is formulated for establishing a functional interface between the platelet membrane and the surrounding fluid, in which the microstructural changes of platelets may respond to the extracellular viscous shear stresses transferred to them. The interaction between the two systems preserves dynamic properties of the flowing platelets, such as the flipping motion. Using this multiscale particle-based approach, we have further studied the effects of the platelet elastic modulus by comparing the action of the flow-induced shear stresses on rigid and deformable platelet models. The results indicate that neglecting the platelet deformability may overestimate the stress on the platelet membrane, which in turn may lead to erroneous predictions of the platelet activation under viscous shear flow conditions. This particle-based fluid-structure interaction multiscale model offers for the first time a computationally feasible approach for simulating deformable platelets interacting with viscous blood flow, aimed at predicting flow induced platelet activation by using a highly resolved mapping of the stress distribution on the platelet membrane under dynamic flow conditions. PMID:25530818

Multiscale geometric modeling of macromolecules I: Cartesian representation

NASA Astrophysics Data System (ADS)

Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei

2014-01-01

This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the polarized curvature, for the prediction of protein binding sites.

Multiscale topo-morphologic opening of arteries and veins: a validation study on phantoms and CT imaging of pulmonary vessel casting of pigs

NASA Astrophysics Data System (ADS)

Gao, Zhiyun; Holtze, Colin; Sonka, Milan; Hoffman, Eric; Saha, Punam K.

2010-03-01

Distinguishing pulmonary arterial and venous (A/V) trees via in vivo imaging is a critical first step in the quantification of vascular geometry for purposes of determining, for instance, pulmonary hypertension, detection of pulmonary emboli and more. A multi-scale topo-morphologic opening algorithm has recently been introduced by us separating A/V trees in pulmonary multiple-detector X-ray computed tomography (MDCT) images without contrast. The method starts with two sets of seeds - one for each of A/V trees and combines fuzzy distance transform, fuzzy connectivity, and morphologic reconstruction leading to multi-scale opening of two mutually fused structures while preserving their continuity. The method locally determines the optimum morphological scale separating the two structures. Here, a validation study is reported examining accuracy of the method using mathematically generated phantoms with different levels of fuzziness, overlap, scale, resolution, noise, and geometric coupling and MDCT images of pulmonary vessel casting of pigs. After exsanguinating the animal, a vessel cast was generated using rapid-hardening methyl methacrylate compound with additional contrast by 10cc of Ethiodol in the arterial side which was scanned in a MDCT scanner at 0.5mm slice thickness and 0.47mm in plane resolution. True segmentations of A/V trees were computed from these images by thresholding. Subsequently, effects of distinguishing A/V contrasts were eliminated and resulting images were used for A/V separation by our method. Experimental results show that 92% - 98% accuracy is achieved using only one seed for each object in phantoms while 94.4% accuracy is achieved in MDCT cast images using ten seeds for each of A/V trees.

Coherent structures shed by multiscale cut-in trailing edge serrations on lifting wings

NASA Astrophysics Data System (ADS)

Prigent, S. L.; Buxton, O. R. H.; Bruce, P. J. K.

2017-07-01

This experimental study presents the effect of multiscale cut-in trailing edge serrations on the coherent structures shed into the wake of a lifting wing. Two-probe span-wise hot-wire traverses are performed to study spectra, coherence, and phase shift. In addition, planar particle image velocimetry is used to study the spatio-temporal structure of the vortices shed by the airfoils. Compared with a single tone sinusoidal serration, the multiscale ones reduce the vortex shedding energy as well as the span-wise coherence. Results indicate that the vortex shedding is locked into an arch-shaped cell structure. This structure is weakened by the multiscale patterns, which explains the reduction in both shedding energy and coherence.

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2012-01-01

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2011-01-01

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

Modified DFA and DCCA approach for quantifying the multiscale correlation structure of financial markets

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2013-12-01

We use multiscale detrended fluctuation analysis (MSDFA) and multiscale detrended cross-correlation analysis (MSDCCA) to investigate auto-correlation (AC) and cross-correlation (CC) in the US and Chinese stock markets during 1997-2012. The results show that US and Chinese stock indices differ in terms of their multiscale AC structures. Stock indices in the same region also differ with regard to their multiscale AC structures. We analyze AC and CC behaviors among indices for the same region to determine similarity among six stock indices and divide them into four groups accordingly. We choose S&P500, NQCI, HSI, and the Shanghai Composite Index as representative samples for simplicity. MSDFA and MSDCCA results and average MSDFA spectra for local scaling exponents (LSEs) for individual series are presented. We find that the MSDCCA spectrum for LSE CC between two time series generally tends to be greater than the average MSDFA LSE spectrum for individual series. We obtain detailed multiscale structures and relations for CC between the four representatives. MSDFA and MSDCCA with secant rolling windows of different sizes are then applied to reanalyze the AC and CC. Vertical and horizontal comparisons of different window sizes are made. The MSDFA and MSDCCA results for the original window size are confirmed and some new interesting characteristics and conclusions regarding multiscale correlation structures are obtained.

Taylor-Aris Dispersion: An Explicit Example for Understanding Multiscale Analysis via Volume Averaging

ERIC Educational Resources Information Center

Wood, Brian D.

2009-01-01

Although the multiscale structure of many important processes in engineering is becoming more widely acknowledged, making this connection in the classroom is a difficult task. This is due in part because the concept of multiscale structure itself is challenging and it requires the students to develop new conceptual pictures of physical systems,…

Statistical CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang Shaojie; Tang Xiangyang; School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121

2012-09-15

Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation ofmore » interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of 'salt-and-pepper' noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain multiscale decomposition, the proposed method is anticipated to be useful in advanced clinical and preclinical applications where the interview sampling rate varies.« less

Bio-inspired configurable multiscale extracellular matrix-like structures for functional alignment and guided orientation of cells.

PubMed

Bae, Won-Gyu; Kim, Jangho; Choung, Yun-Hoon; Chung, Yesol; Suh, Kahp Y; Pang, Changhyun; Chung, Jong Hoon; Jeong, Hoon Eui

2015-11-01

Inspired by the hierarchically organized protein fibers in extracellular matrix (ECM) as well as the physiological importance of multiscale topography, we developed a simple but robust method for the design and manipulation of precisely controllable multiscale hierarchical structures using capillary force lithography in combination with an original wrinkling technique. In this study, based on our proposed fabrication technology, we approached a conceptual platform that can mimic the hierarchically multiscale topographical and orientation cues of the ECM for controlling cell structure and function. We patterned the polyurethane acrylate-based nanotopography with various orientations on the microgrooves, which could provide multiscale topography signals of ECM to control single and multicellular morphology and orientation with precision. Using our platforms, we found that the structures and orientations of fibroblast cells were greatly influenced by the nanotopography, rather than the microtopography. We also proposed a new approach that enables the generation of native ECM having nanofibers in specific three-dimensional (3D) configurations by culturing fibroblast cells on the multiscale substrata. We suggest that our methodology could be used as efficient strategies for the design and manipulation of various functional platforms, including well-defined 3D tissue structures for advanced regenerative medicine applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

An approach to multiscale modelling with graph grammars.

PubMed

Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

2014-09-01

Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.

An approach to multiscale modelling with graph grammars

PubMed Central

Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

2014-01-01

Background and Aims Functional–structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. Methods A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Key Results Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. Conclusions The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models. PMID:25134929

Multiscale study on stochastic reconstructions of shale samples

NASA Astrophysics Data System (ADS)

Lili, J.; Lin, M.; Jiang, W. B.

2016-12-01

Shales are known to have multiscale pore systems, composed of macroscale fractures, micropores, and nanoscale pores within gas or oil-producing organic material. Also, shales are fissile and laminated, and the heterogeneity in horizontal is quite different from that in vertical. Stochastic reconstructions are extremely useful in situations where three-dimensional information is costly and time consuming. Thus the purpose of our paper is to reconstruct stochastically equiprobable 3D models containing information from several scales. In this paper, macroscale and microscale images of shale structure in the Lower Silurian Longmaxi are obtained by X-ray microtomography and nanoscale images are obtained by scanning electron microscopy. Each image is representative for all given scales and phases. Especially, the macroscale is four times coarser than the microscale, which in turn is four times lower in resolution than the nanoscale image. Secondly, the cross correlation-based simulation method (CCSIM) and the three-step sampling method are combined together to generate stochastic reconstructions for each scale. It is important to point out that the boundary points of pore and matrix are selected based on multiple-point connectivity function in the sampling process, and thus the characteristics of the reconstructed image can be controlled indirectly. Thirdly, all images with the same resolution are developed through downscaling and upscaling by interpolation, and then we merge multiscale categorical spatial data into a single 3D image with predefined resolution (the microscale image). 30 realizations using the given images and the proposed method are generated. The result reveals that the proposed method is capable of preserving the multiscale pore structure, both vertically and horizontally, which is necessary for accurate permeability prediction. The variogram curves and pore-size distribution for both original 3D sample and the generated 3D realizations are compared. The result indicates that the agreement between the original 3D sample and the generated stochastic realizations is excellent. This work is supported by "973" Program (2014CB239004), the Key Instrument Developing Project of the CAS (ZDYZ2012-1-08-02) and the National Natural Science Foundation of China (Grant No. 41574129).

Multi-scale Material Appearance

NASA Astrophysics Data System (ADS)

Wu, Hongzhi

Modeling and rendering the appearance of materials is important for a diverse range of applications of computer graphics - from automobile design to movies and cultural heritage. The appearance of materials varies considerably at different scales, posing significant challenges due to the sheer complexity of the data, as well the need to maintain inter-scale consistency constraints. This thesis presents a series of studies around the modeling, rendering and editing of multi-scale material appearance. To efficiently render material appearance at multiple scales, we develop an object-space precomputed adaptive sampling method, which precomputes a hierarchy of view-independent points that preserve multi-level appearance. To support bi-scale material appearance design, we propose a novel reflectance filtering algorithm, which rapidly computes the large-scale appearance from small-scale details, by exploiting the low-rank structures of Bidirectional Visible Normal Distribution Functions and pre-rotated Bidirectional Reflectance Distribution Functions in the matrix formulation of the rendering algorithm. This approach can guide the physical realization of appearance, as well as the modeling of real-world materials using very sparse measurements. Finally, we present a bi-scale-inspired high-quality general representation for material appearance described by Bidirectional Texture Functions. Our representation is at once compact, easily editable, and amenable to efficient rendering.

Covariance, correlation matrix, and the multiscale community structure of networks.

PubMed

Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing

2010-07-01

Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.

Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

PubMed

Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

2017-04-01

This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

Nonlocal variational model and filter algorithm to remove multiplicative noise

NASA Astrophysics Data System (ADS)

Chen, Dai-Qiang; Zhang, Hui; Cheng, Li-Zhi

2010-07-01

The nonlocal (NL) means filter proposed by Buades, Coll, and Morel (SIAM Multiscale Model. Simul. 4(2), 490-530, 2005), which makes full use of the redundancy information in images, has shown to be very efficient for image denoising with Gauss noise added. On the basis of the NL method and a striver to minimize the conditional mean-square error, we design a NL means filter to remove multiplicative noise, and combining the NL filter to regularity method, we propose a NL total variational (TV) model and present a fast iterated algorithm for it. Experiments demonstrate that our algorithm is better than TV method; it is superior in preserving small structures and textures and can obtain an improvement in peak signal-to-noise ratio.

Crustal architecture and tectonic evolution of the Cauvery Suture Zone, southern India

NASA Astrophysics Data System (ADS)

Chetty, T. R. K.; Yellappa, T.; Santosh, M.

2016-11-01

The Cauvery suture zone (CSZ) in southern India has witnessed multiple deformations associated with multiple subduction-collision history, with incorporation of the related accretionary belts sequentially into the southern continental margin of the Archaean Dharwar craton since Neoarchean to Neoproterozoic. The accreted tectonic elements include suprasubduction complexes of arc magmatic sequences, high-grade supracrustals, thrust duplexes, ophiolites, and younger intrusions that are dispersed along the suture. The intra-oceanic Neoarchean-Neoproterozoic arc assemblages are well exposed in the form of tectonic mélanges dominantly towards the eastern sector of the CSZ and are typically subjected to complex and multiple deformation events. Multi-scale analysis of structural elements with detailed geological mapping of the sub-regions and their structural cross sections, geochemical and geochronological data and integrated geophysical observations suggest that the CSZ is an important zone that preserves the imprints of multiple cycles of Precambrian plate tectonic regimes.

Multiscale Path Metrics for the Analysis of Discrete Geometric Structures

DTIC Science & Technology

2017-11-30

Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release

Active-Vision Control Systems for Complex Adversarial 3-D Environments

DTIC Science & Technology

2009-03-01

Control Systems MURI Final Report 36 51. D. Nain, S. Haker , A. Bobick, A. Tannenbaum, "Multiscale 3D shape representation and segmentation using...Conference, August 2008. 99. L. Zhu, Y. Yang, S. Haker , and A. Tannenbaum, "An image morphing technique based on optimal mass preserving mapping," IEEE

A Technique for Mapping Characteristic Lengths to Preserve Energy Dissipated via Strain Softening in a Multiscale Analysis

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Arnold, Steven M.

2014-01-01

It is often advantageous to account for the microstructure of the material directly using multiscale modeling. For computational tractability, an idealized repeating unit cell (RUC) is used to capture all of the pertinent features of the microstructure. Typically, the RUC is dimensionless and depends only on the relative volume fractions of the different phases in the material. This works well for non-linear and inelastic behavior exhibiting a positive-definite constitutive response. Although, once the material exhibits strain softening, or localization, a mesh objective failure theories, such as smeared fracture theories, nodal and element enrichment theories (XFEM), cohesive elements or virtual crack closure technique (VCCT), can be utilized at the microscale, but the dimensions of the RUC must then be defined. One major challenge in multiscale progressive damage modeling is relating the characteristic lengths across the scales in order to preserve the energy that is dissipated via localization at the microscale. If there is no effort to relate the size of the macroscale element to the microscale RUC, then the energy that is dissipated will remain mesh dependent at the macroscale, even if it is regularized at the microscale. Here, a technique for mapping characteristic lengths across the scales is proposed. The RUC will be modeled using the generalized method of cells (GMC) micromechanics theory, and local failure in the matrix constituent subcells will be modeled using the crack band theory. The subcell characteristic lengths used in the crack band calculations will be mapped to the macroscale finite element in order to regularize the local energy in a manner consistent with the global length scale. Examples will be provided with and without the regularization, and they will be compared to a baseline case where the size and shape of the element and RUC are coincident (ensuring energy is preserved across the scales).

Multiresolution generalized N dimension PCA for ultrasound image denoising

PubMed Central

2014-01-01

Background Ultrasound images are usually affected by speckle noise, which is a type of random multiplicative noise. Thus, reducing speckle and improving image visual quality are vital to obtaining better diagnosis. Method In this paper, a novel noise reduction method for medical ultrasound images, called multiresolution generalized N dimension PCA (MR-GND-PCA), is presented. In this method, the Gaussian pyramid and multiscale image stacks on each level are built first. GND-PCA as a multilinear subspace learning method is used for denoising. Each level is combined to achieve the final denoised image based on Laplacian pyramids. Results The proposed method is tested with synthetically speckled and real ultrasound images, and quality evaluation metrics, including MSE, SNR and PSNR, are used to evaluate its performance. Conclusion Experimental results show that the proposed method achieved the lowest noise interference and improved image quality by reducing noise and preserving the structure. Our method is also robust for the image with a much higher level of speckle noise. For clinical images, the results show that MR-GND-PCA can reduce speckle and preserve resolvable details. PMID:25096917

American Society of Composites, 32nd Technical Conference

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aitharaju, Venkat; Wollschlager, Jeffrey; Plakomytis2, Dimitrios

This paper will present a general methodology by which weave draping manufacturing simulation results can be utilized to include the effects of weave draping and scissor angle in a structural multiscale simulation. While the methodology developed is general in nature, this paper will specifically demonstrate the methodology applied to a truncated pyramid, utilizing manufacturing simulation weave draping results from ESI PAM-FORM, and multiscale simulation using Altair Multiscale Designer (MDS) and OptiStruct. From a multiscale simulation perspective, the weave draping manufacturing simulation results will be used to develop a series of woven unit cells which cover the range of weave scissormore » angles existing within the part. For each unit cell, a multiscale material model will be developed, and applied to the corresponding spatial locations within the structural simulation mesh. In addition, the principal material orientation will be mapped from the wave draping manufacturing simulation mesh to the structural simulation mesh using Altair HyperMesh mapping technology. Results of the coupled simulation will be compared and verified against experimental data of the same available via General Motors (GM) Department of Energy (DOE) project.« less

Multiscale time-dependent density functional theory: Demonstration for plasmons.

PubMed

Jiang, Jiajian; Abi Mansour, Andrew; Ortoleva, Peter J

2017-08-07

Plasmon properties are of significant interest in pure and applied nanoscience. While time-dependent density functional theory (TDDFT) can be used to study plasmons, it becomes impractical for elucidating the effect of size, geometric arrangement, and dimensionality in complex nanosystems. In this study, a new multiscale formalism that addresses this challenge is proposed. This formalism is based on Trotter factorization and the explicit introduction of a coarse-grained (CG) structure function constructed as the Weierstrass transform of the electron wavefunction. This CG structure function is shown to vary on a time scale much longer than that of the latter. A multiscale propagator that coevolves both the CG structure function and the electron wavefunction is shown to bring substantial efficiency over classical propagators used in TDDFT. This efficiency follows from the enhanced numerical stability of the multiscale method and the consequence of larger time steps that can be used in a discrete time evolution. The multiscale algorithm is demonstrated for plasmons in a group of interacting sodium nanoparticles (15-240 atoms), and it achieves improved efficiency over TDDFT without significant loss of accuracy or space-time resolution.

Multiscale structure of time series revealed by the monotony spectrum.

PubMed

Vamoş, Călin

2017-03-01

Observation of complex systems produces time series with specific dynamics at different time scales. The majority of the existing numerical methods for multiscale analysis first decompose the time series into several simpler components and the multiscale structure is given by the properties of their components. We present a numerical method which describes the multiscale structure of arbitrary time series without decomposing them. It is based on the monotony spectrum defined as the variation of the mean amplitude of the monotonic segments with respect to the mean local time scale during successive averagings of the time series, the local time scales being the durations of the monotonic segments. The maxima of the monotony spectrum indicate the time scales which dominate the variations of the time series. We show that the monotony spectrum can correctly analyze a diversity of artificial time series and can discriminate the existence of deterministic variations at large time scales from the random fluctuations. As an application we analyze the multifractal structure of some hydrological time series.

Pre-set extrusion bioprinting for multiscale heterogeneous tissue structure fabrication.

PubMed

Kang, Donggu; Ahn, Geunseon; Kim, Donghwan; Kang, Hyun-Wook; Yun, Seokhwan; Yun, Won-Soo; Shim, Jin-Hyung; Jin, Songwan

2018-06-06

Recent advances in three-dimensional bioprinting technology have led to various attempts in fabricating human tissue-like structures. However, current bioprinting technologies have limitations for creating native tissue-like structures. To resolve these issues, we developed a new pre-set extrusion bioprinting technique that can create heterogeneous, multicellular, and multimaterial structures simultaneously. The key to this ability lies in the use of a precursor cartridge that can stably preserve a multimaterial with a pre-defined configuration that can be simply embedded in a syringe-based printer head. The multimaterial can be printed and miniaturized through a micro-nozzle without conspicuous deformation according to the pre-defined configuration of the precursor cartridge. Using this system, we fabricated heterogeneous tissue-like structures such as spinal cords, hepatic lobule, blood vessels, and capillaries. We further obtained a heterogeneous patterned model that embeds HepG2 cells with endothelial cells in a hepatic lobule-like structure. In comparison with homogeneous and heterogeneous cell printing, the heterogeneous patterned model showed a well-organized hepatic lobule structure and higher enzyme activity of CYP3A4. Therefore, this pre-set extrusion bioprinting method could be widely used in the fabrication of a variety of artificial and functional tissues or organs.

Stacked competitive networks for noise reduction in low-dose CT

PubMed Central

Du, Wenchao; Chen, Hu; Wu, Zhihong; Sun, Huaiqiang; Liao, Peixi

2017-01-01

Since absorption of X-ray radiation has the possibility of inducing cancerous, genetic and other diseases to patients, researches usually attempt to reduce the radiation dose. However, reduction of the radiation dose associated with CT scans will unavoidably increase the severity of noise and artifacts, which can seriously affect diagnostic confidence. Due to the outstanding performance of deep neural networks in image processing, in this paper, we proposed a Stacked Competitive Network (SCN) approach to noise reduction, which stacks several successive Competitive Blocks (CB). The carefully handcrafted design of the competitive blocks was inspired by the idea of multi-scale processing and improvement the network’s capacity. Qualitative and quantitative evaluations demonstrate the competitive performance of the proposed method in noise suppression, structural preservation, and lesion detection. PMID:29267360

Variational Integrators for Interconnected Lagrange-Dirac Systems

NASA Astrophysics Data System (ADS)

Parks, Helen; Leok, Melvin

2017-10-01

Interconnected systems are an important class of mathematical models, as they allow for the construction of complex, hierarchical, multiphysics, and multiscale models by the interconnection of simpler subsystems. Lagrange-Dirac mechanical systems provide a broad category of mathematical models that are closed under interconnection, and in this paper, we develop a framework for the interconnection of discrete Lagrange-Dirac mechanical systems, with a view toward constructing geometric structure-preserving discretizations of interconnected systems. This work builds on previous work on the interconnection of continuous Lagrange-Dirac systems (Jacobs and Yoshimura in J Geom Mech 6(1):67-98, 2014) and discrete Dirac variational integrators (Leok and Ohsawa in Found Comput Math 11(5), 529-562, 2011). We test our results by simulating some of the continuous examples given in Jacobs and Yoshimura (2014).

Multiscale Pressure-Balanced Structures in Three-dimensional Magnetohydrodynamic Turbulence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Liping; Zhang, Lei; Feng, Xueshang

2017-02-10

Observations of solar wind turbulence indicate the existence of multiscale pressure-balanced structures (PBSs) in the solar wind. In this work, we conduct a numerical simulation to investigate multiscale PBSs and in particular their formation in compressive magnetohydrodynamic turbulence. By the use of the higher-order Godunov code Athena, a driven compressible turbulence with an imposed uniform guide field is simulated. The simulation results show that both the magnetic pressure and the thermal pressure exhibit a turbulent spectrum with a Kolmogorov-like power law, and that in many regions of the simulation domain they are anticorrelated. The computed wavelet cross-coherence spectra of themore » magnetic pressure and the thermal pressure, as well as their space series, indicate the existence of multiscale PBSs, with the small PBSs being embedded in the large ones. These multiscale PBSs are likely to be related to the highly oblique-propagating slow-mode waves, as the traced multiscale PBS is found to be traveling in a certain direction at a speed consistent with that predicted theoretically for a slow-mode wave propagating in the same direction.« less

Structural and Practical Identifiability Issues of Immuno-Epidemiological Vector-Host Models with Application to Rift Valley Fever.

PubMed

Tuncer, Necibe; Gulbudak, Hayriye; Cannataro, Vincent L; Martcheva, Maia

2016-09-01

In this article, we discuss the structural and practical identifiability of a nested immuno-epidemiological model of arbovirus diseases, where host-vector transmission rate, host recovery, and disease-induced death rates are governed by the within-host immune system. We incorporate the newest ideas and the most up-to-date features of numerical methods to fit multi-scale models to multi-scale data. For an immunological model, we use Rift Valley Fever Virus (RVFV) time-series data obtained from livestock under laboratory experiments, and for an epidemiological model we incorporate a human compartment to the nested model and use the number of human RVFV cases reported by the CDC during the 2006-2007 Kenya outbreak. We show that the immunological model is not structurally identifiable for the measurements of time-series viremia concentrations in the host. Thus, we study the non-dimensionalized and scaled versions of the immunological model and prove that both are structurally globally identifiable. After fixing estimated parameter values for the immunological model derived from the scaled model, we develop a numerical method to fit observable RVFV epidemiological data to the nested model for the remaining parameter values of the multi-scale system. For the given (CDC) data set, Monte Carlo simulations indicate that only three parameters of the epidemiological model are practically identifiable when the immune model parameters are fixed. Alternatively, we fit the multi-scale data to the multi-scale model simultaneously. Monte Carlo simulations for the simultaneous fitting suggest that the parameters of the immunological model and the parameters of the immuno-epidemiological model are practically identifiable. We suggest that analytic approaches for studying the structural identifiability of nested models are a necessity, so that identifiable parameter combinations can be derived to reparameterize the nested model to obtain an identifiable one. This is a crucial step in developing multi-scale models which explain multi-scale data.

Multi-Scale Sizing of Lightweight Multifunctional Spacecraft Structural Components

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.

2005-01-01

This document is the final report for the project entitled, "Multi-Scale Sizing of Lightweight Multifunctional Spacecraft Structural Components," funded under the NRA entitled "Cross-Enterprise Technology Development Program" issued by the NASA Office of Space Science in 2000. The project was funded in 2001, and spanned a four year period from March, 2001 to February, 2005. Through enhancements to and synthesis of unique, state of the art structural mechanics and micromechanics analysis software, a new multi-scale tool has been developed that enables design, analysis, and sizing of advance lightweight composite and smart materials and structures from the full vehicle, to the stiffened structure, to the micro (fiber and matrix) scales. The new software tool has broad, cross-cutting value to current and future NASA missions that will rely on advanced composite and smart materials and structures.

Multiscale Magnetic Underdense Regions on the Solar Surface: Granular and Mesogranular Scales

NASA Astrophysics Data System (ADS)

Berrilli, F.; Scardigli, S.; Giordano, S.

2013-02-01

The Sun is a non-equilibrium, dissipative system subject to an energy flow that originates in its core. Convective overshooting motions create temperature and velocity structures that show a temporal and spatial multiscale evolution. As a result, photospheric structures are generally considered to be a direct manifestation of convective plasma motions. The plasma flows in the photosphere govern the motion of single magnetic elements. These elements are arranged in typical patterns, which are observed as a variety of multiscale magnetic patterns. High-resolution magnetograms of the quiet solar surface revealed the presence of multiscale magnetic underdense regions in the solar photosphere, commonly called voids, which may be considered to be a signature of the underlying convective structure. The analysis of such patterns paves the way for the investigation of all turbulent convective scales, from granular to global. In order to address the question of magnetic structures driven by turbulent convection at granular and mesogranular scales, we used a voids-detection method. The computed distribution of void length scales shows an exponential behavior at scales between 2 and 10 Mm and the absence of features at mesogranular scales. The absence of preferred scales of organization in the 2 - 10 Mm range supports the multiscale nature of flows on the solar surface and the absence of a mesogranular convective scale.

Riparian ecosystems and buffers - multiscale structure, function, and management: introduction

Treesearch

Kathleen A. Dwire; Richard R. Lowrance

2006-01-01

Given the importance of issues related to improved understanding and management of riparian ecosystems and buffers, the American Water Resources Association (AWRA) sponsored a Summer Specialty Conference in June 2004 at Olympic Valley, California, entitled 'Riparian Ecosystems and Buffers: Multiscale Structure, Function, and Management.' The primary objective...

Multispectral Image Enhancement Through Adaptive Wavelet Fusion

DTIC Science & Technology

2016-09-14

13. SUPPLEMENTARY NOTES 14. ABSTRACT This research developed a multiresolution image fusion scheme based on guided filtering . Guided filtering can...effectively reduce noise while preserving detail boundaries. When applied in an iterative mode, guided filtering selectively eliminates small scale...details while restoring larger scale edges. The proposed multi-scale image fusion scheme achieves spatial consistency by using guided filtering both at

Multiscale Modeling of Structurally-Graded Materials Using Discrete Dislocation Plasticity Models and Continuum Crystal Plasticity Models

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.

2012-01-01

A multiscale modeling methodology that combines the predictive capability of discrete dislocation plasticity and the computational efficiency of continuum crystal plasticity is developed. Single crystal configurations of different grain sizes modeled with periodic boundary conditions are analyzed using discrete dislocation plasticity (DD) to obtain grain size-dependent stress-strain predictions. These relationships are mapped into crystal plasticity parameters to develop a multiscale DD/CP model for continuum level simulations. A polycrystal model of a structurally-graded microstructure is developed, analyzed and used as a benchmark for comparison between the multiscale DD/CP model and the DD predictions. The multiscale DD/CP model follows the DD predictions closely up to an initial peak stress and then follows a strain hardening path that is parallel but somewhat offset from the DD predictions. The difference is believed to be from a combination of the strain rate in the DD simulation and the inability of the DD/CP model to represent non-monotonic material response.

Developing a novel hierarchical approach for multiscale structural reliability predictions for ultra-high consequence applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emery, John M.; Coffin, Peter; Robbins, Brian A.

Microstructural variabilities are among the predominant sources of uncertainty in structural performance and reliability. We seek to develop efficient algorithms for multiscale calcu- lations for polycrystalline alloys such as aluminum alloy 6061-T6 in environments where ductile fracture is the dominant failure mode. Our approach employs concurrent multiscale methods, but does not focus on their development. They are a necessary but not sufficient ingredient to multiscale reliability predictions. We have focused on how to efficiently use concurrent models for forward propagation because practical applications cannot include fine-scale details throughout the problem domain due to exorbitant computational demand. Our approach begins withmore » a low-fidelity prediction at the engineering scale that is sub- sequently refined with multiscale simulation. The results presented in this report focus on plasticity and damage at the meso-scale, efforts to expedite Monte Carlo simulation with mi- crostructural considerations, modeling aspects regarding geometric representation of grains and second-phase particles, and contrasting algorithms for scale coupling.« less

Development of Semantic Description for Multiscale Models of Thermo-Mechanical Treatment of Metal Alloys

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Regulski, Krzysztof

2016-08-01

We present a process of semantic meta-model development for data management in an adaptable multiscale modeling framework. The main problems in ontology design are discussed, and a solution achieved as a result of the research is presented. The main concepts concerning the application and data management background for multiscale modeling were derived from the AM3 approach—object-oriented Agile multiscale modeling methodology. The ontological description of multiscale models enables validation of semantic correctness of data interchange between submodels. We also present a possibility of using the ontological model as a supervisor in conjunction with a multiscale model controller and a knowledge base system. Multiscale modeling formal ontology (MMFO), designed for describing multiscale models' data and structures, is presented. A need for applying meta-ontology in the MMFO development process is discussed. Examples of MMFO application in describing thermo-mechanical treatment of metal alloys are discussed. Present and future applications of MMFO are described.

Hi-fidelity multi-scale local processing for visually optimized far-infrared Herschel images

NASA Astrophysics Data System (ADS)

Li Causi, G.; Schisano, E.; Liu, S. J.; Molinari, S.; Di Giorgio, A.

2016-07-01

In the context of the "Hi-Gal" multi-band full-plane mapping program for the Galactic Plane, as imaged by the Herschel far-infrared satellite, we have developed a semi-automatic tool which produces high definition, high quality color maps optimized for visual perception of extended features, like bubbles and filaments, against the high background variations. We project the map tiles of three selected bands onto a 3-channel panorama, which spans the central 130 degrees of galactic longitude times 2.8 degrees of galactic latitude, at the pixel scale of 3.2", in cartesian galactic coordinates. Then we process this image piecewise, applying a custom multi-scale local stretching algorithm, enforced by a local multi-scale color balance. Finally, we apply an edge-preserving contrast enhancement to perform an artifact-free details sharpening. Thanks to this tool, we have thus produced a stunning giga-pixel color image of the far-infrared Galactic Plane that we made publicly available with the recent release of the Hi-Gal mosaics and compact source catalog.

Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

PubMed Central

Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

2012-01-01

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues. PMID:22403724

Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

NASA Astrophysics Data System (ADS)

Yang, Qiu

Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

Foreword to 'Multiscale structural biology: biophysical principles and mechanisms underlying the action of bio-nanomachines', a special issue in Honour of Fumio Arisaka's 70th birthday.

PubMed

Hall, Damien; Takagi, Junichi; Nakamura, Haruki

2018-04-01

This issue of Biophysical Reviews, titled 'Multiscale structural biology: biophysical principles and mechanisms underlying the action of bio-nanomachines', is a collection of articles dedicated in honour of Professor Fumio Arisaka's 70th birthday. Initially, working in the fields of haemocyanin and actin filament assembly, Fumio went on to publish important work on the elucidation of structural and functional aspects of T4 phage biology. As his career has transitioned levels of complexity from proteins (hemocyanin) to large protein complexes (actin) to even more massive bio-nanomachinery (phage), it is fitting that the subject of this special issue is similarly reflective of his multiscale approach to structural biology. This festschrift contains articles spanning biophysical structure and function from the bio-molecular through to the bio-nanomachine level.

Joint seismic data denoising and interpolation with double-sparsity dictionary learning

NASA Astrophysics Data System (ADS)

Zhu, Lingchen; Liu, Entao; McClellan, James H.

2017-08-01

Seismic data quality is vital to geophysical applications, so that methods of data recovery, including denoising and interpolation, are common initial steps in the seismic data processing flow. We present a method to perform simultaneous interpolation and denoising, which is based on double-sparsity dictionary learning. This extends previous work that was for denoising only. The original double-sparsity dictionary learning algorithm is modified to track the traces with missing data by defining a masking operator that is integrated into the sparse representation of the dictionary. A weighted low-rank approximation algorithm is adopted to handle the dictionary updating as a sparse recovery optimization problem constrained by the masking operator. Compared to traditional sparse transforms with fixed dictionaries that lack the ability to adapt to complex data structures, the double-sparsity dictionary learning method learns the signal adaptively from selected patches of the corrupted seismic data, while preserving compact forward and inverse transform operators. Numerical experiments on synthetic seismic data indicate that this new method preserves more subtle features in the data set without introducing pseudo-Gibbs artifacts when compared to other directional multi-scale transform methods such as curvelets.

Multi-scale structural community organisation of the human genome.

PubMed

Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin

2017-04-11

Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.

Modeling Framework for Fracture in Multiscale Cement-Based Material Structures

PubMed Central

Qian, Zhiwei; Schlangen, Erik; Ye, Guang; van Breugel, Klaas

2017-01-01

Multiscale modeling for cement-based materials, such as concrete, is a relatively young subject, but there are already a number of different approaches to study different aspects of these classical materials. In this paper, the parameter-passing multiscale modeling scheme is established and applied to address the multiscale modeling problem for the integrated system of cement paste, mortar, and concrete. The block-by-block technique is employed to solve the length scale overlap challenge between the mortar level (0.1–10 mm) and the concrete level (1–40 mm). The microstructures of cement paste are simulated by the HYMOSTRUC3D model, and the material structures of mortar and concrete are simulated by the Anm material model. Afterwards the 3D lattice fracture model is used to evaluate their mechanical performance by simulating a uniaxial tensile test. The simulated output properties at a lower scale are passed to the next higher scale to serve as input local properties. A three-level multiscale lattice fracture analysis is demonstrated, including cement paste at the micrometer scale, mortar at the millimeter scale, and concrete at centimeter scale. PMID:28772948

Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

PubMed

Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W

2017-12-05

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.

Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

NASA Technical Reports Server (NTRS)

Pisani, William A.; Radue, Matthew; Chinkanjanarot, Sorayot; Bednarcyk, Brett A.; Pineda, Evan J.; King, Julia A.; Odegard, Gregory M.

2018-01-01

Polyether ether ketone (PEEK) is a high-performance, semi-crystalline thermoplastic that is used in a wide range of engineering applications, including some structural components of aircraft. The design of new PEEK-based materials requires a precise understanding of the multiscale structure and behavior of semi-crystalline PEEK. Molecular Dynamics (MD) modeling can efficiently predict bulk-level properties of single phase polymers, and micromechanics can be used to homogenize those phases based on the overall polymer microstructure. In this study, MD modeling was used to predict the mechanical properties of the amorphous and crystalline phases of PEEK. The hierarchical microstructure of PEEK, which combines the aforementioned phases, was modeled using a multiscale modeling approach facilitated by NASA's MSGMC. The bulk mechanical properties of semi-crystalline PEEK predicted using MD modeling and MSGMC agree well with vendor data, thus validating the multiscale modeling approach.

A Micromechanics-Based Method for Multiscale Fatigue Prediction

NASA Astrophysics Data System (ADS)

Moore, John Allan

An estimated 80% of all structural failures are due to mechanical fatigue, often resulting in catastrophic, dangerous and costly failure events. However, an accurate model to predict fatigue remains an elusive goal. One of the major challenges is that fatigue is intrinsically a multiscale process, which is dependent on a structure's geometric design as well as its material's microscale morphology. The following work begins with a microscale study of fatigue nucleation around non- metallic inclusions. Based on this analysis, a novel multiscale method for fatigue predictions is developed. This method simulates macroscale geometries explicitly while concurrently calculating the simplified response of microscale inclusions. Thus, providing adequate detail on multiple scales for accurate fatigue life predictions. The methods herein provide insight into the multiscale nature of fatigue, while also developing a tool to aid in geometric design and material optimization for fatigue critical devices such as biomedical stents and artificial heart valves.

The topology of the cosmic web in terms of persistent Betti numbers

NASA Astrophysics Data System (ADS)

Pranav, Pratyush; Edelsbrunner, Herbert; van de Weygaert, Rien; Vegter, Gert; Kerber, Michael; Jones, Bernard J. T.; Wintraecken, Mathijs

2017-03-01

We introduce a multiscale topological description of the Megaparsec web-like cosmic matter distribution. Betti numbers and topological persistence offer a powerful means of describing the rich connectivity structure of the cosmic web and of its multiscale arrangement of matter and galaxies. Emanating from algebraic topology and Morse theory, Betti numbers and persistence diagrams represent an extension and deepening of the cosmologically familiar topological genus measure and the related geometric Minkowski functionals. In addition to a description of the mathematical background, this study presents the computational procedure for computing Betti numbers and persistence diagrams for density field filtrations. The field may be computed starting from a discrete spatial distribution of galaxies or simulation particles. The main emphasis of this study concerns an extensive and systematic exploration of the imprint of different web-like morphologies and different levels of multiscale clustering in the corresponding computed Betti numbers and persistence diagrams. To this end, we use Voronoi clustering models as templates for a rich variety of web-like configurations and the fractal-like Soneira-Peebles models exemplify a range of multiscale configurations. We have identified the clear imprint of cluster nodes, filaments, walls, and voids in persistence diagrams, along with that of the nested hierarchy of structures in multiscale point distributions. We conclude by outlining the potential of persistent topology for understanding the connectivity structure of the cosmic web, in large simulations of cosmic structure formation and in the challenging context of the observed galaxy distribution in large galaxy surveys.

Multiplex lithography for multilevel multiscale architectures and its application to polymer electrolyte membrane fuel cell

NASA Astrophysics Data System (ADS)

Cho, Hyesung; Moon Kim, Sang; Sik Kang, Yun; Kim, Junsoo; Jang, Segeun; Kim, Minhyoung; Park, Hyunchul; Won Bang, Jung; Seo, Soonmin; Suh, Kahp-Yang; Sung, Yung-Eun; Choi, Mansoo

2015-09-01

The production of multiscale architectures is of significant interest in materials science, and the integration of those structures could provide a breakthrough for various applications. Here we report a simple yet versatile strategy that allows for the LEGO-like integrations of microscale membranes by quantitatively controlling the oxygen inhibition effects of ultraviolet-curable materials, leading to multilevel multiscale architectures. The spatial control of oxygen concentration induces different curing contrasts in a resin allowing the selective imprinting and bonding at different sides of a membrane, which enables LEGO-like integration together with the multiscale pattern formation. Utilizing the method, the multilevel multiscale Nafion membranes are prepared and applied to polymer electrolyte membrane fuel cell. Our multiscale membrane fuel cell demonstrates significant enhancement of performance while ensuring mechanical robustness. The performance enhancement is caused by the combined effect of the decrease of membrane resistance and the increase of the electrochemical active surface area.

A complete categorization of multiscale models of infectious disease systems.

PubMed

Garira, Winston

2017-12-01

Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.

Multi-scale structure, pasting and digestibility of heat moisture treated red adzuki bean starch.

PubMed

Wang, Hongwei; Wang, Zhaoyuan; Li, Xiaoxi; Chen, Ling; Zhang, Binjia

2017-09-01

The pasting and digestibility of a red adzuki bean starch were simultaneously modulated by heat-moisture treatment (HMT) through altering the multi-scale structure. HMT, especially at high moisture content, could disrupt the granule integrity, semicrystalline lamellae, molecular order (crystallites) and molecular chains. Also, certain rearrangement of starch molecules occurred to form ordered structures with increased thermal stability as shown by DSC. This concomitant disordering and reassembly in the multi-scale structure converted the fractions of resistant starch (RS) and rapidly digestible starch (RDS) into that of slowly digestible starch (SDS). Furthermore, the emergence of thermally-stable orders increased the pasting temperature but suppressed the swelling of granules during heating. Hence, HMT-modified red adzuki starch may serve as a potential thickener/gelling agent with slow digestion rate for various foods. Copyright © 2017. Published by Elsevier B.V.

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

2017-10-01

Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

An analytical coarse-graining method which preserves the free energy, structural correlations, and thermodynamic state of polymer melts from the atomistic to the mesoscale.

PubMed

McCarty, J; Clark, A J; Copperman, J; Guenza, M G

2014-05-28

Structural and thermodynamic consistency of coarse-graining models across multiple length scales is essential for the predictive role of multi-scale modeling and molecular dynamic simulations that use mesoscale descriptions. Our approach is a coarse-grained model based on integral equation theory, which can represent polymer chains at variable levels of chemical details. The model is analytical and depends on molecular and thermodynamic parameters of the system under study, as well as on the direct correlation function in the k → 0 limit, c0. A numerical solution to the PRISM integral equations is used to determine c0, by adjusting the value of the effective hard sphere diameter, dHS, to agree with the predicted equation of state. This single quantity parameterizes the coarse-grained potential, which is used to perform mesoscale simulations that are directly compared with atomistic-level simulations of the same system. We test our coarse-graining formalism by comparing structural correlations, isothermal compressibility, equation of state, Helmholtz and Gibbs free energies, and potential energy and entropy using both united atom and coarse-grained descriptions. We find quantitative agreement between the analytical formalism for the thermodynamic properties, and the results of Molecular Dynamics simulations, independent of the chosen level of representation. In the mesoscale description, the potential energy of the soft-particle interaction becomes a free energy in the coarse-grained coordinates which preserves the excess free energy from an ideal gas across all levels of description. The structural consistency between the united-atom and mesoscale descriptions means the relative entropy between descriptions has been minimized without any variational optimization parameters. The approach is general and applicable to any polymeric system in different thermodynamic conditions.

Multiscale analysis of structure development in expanded starch snacks

NASA Astrophysics Data System (ADS)

van der Sman, R. G. M.; Broeze, J.

2014-11-01

In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the moisture content, where the glass transition and the boiling line intersect. In our analysis we make use of several tools, (1) time scale analysis from the field of physical transport phenomena, (2) the scale separation map (SSM) developed within a multiscale simulation framework of complex automata, (3) the supplemented state diagram (SSD), depicting phase transition and glass transition lines, and (4) a multiscale simulation model for the bubble expansion. Results of the time scale analysis are plotted in the SSD, and give insight into the dominant physical processes involved in expansion. Furthermore, the results of the time scale analysis are used to construct the SSM, which has aided us in the construction of the multiscale simulation model. Simulation results are plotted in the SSD. This clearly shows that the hypothesis of Kokini is qualitatively true, but has to be refined. Our results show that bubble expansion is optimal for moisture content, where the boiling line for gas pressure of 4 bars intersects the isoviscosity line of the critical viscosity 106 Pa.s, which runs parallel to the glass transition line.

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

A Fusion Algorithm for GFP Image and Phase Contrast Image of Arabidopsis Cell Based on SFL-Contourlet Transform

PubMed Central

Feng, Peng; Wang, Jing; Wei, Biao; Mi, Deling

2013-01-01

A hybrid multiscale and multilevel image fusion algorithm for green fluorescent protein (GFP) image and phase contrast image of Arabidopsis cell is proposed in this paper. Combining intensity-hue-saturation (IHS) transform and sharp frequency localization Contourlet transform (SFL-CT), this algorithm uses different fusion strategies for different detailed subbands, which include neighborhood consistency measurement (NCM) that can adaptively find balance between color background and gray structure. Also two kinds of neighborhood classes based on empirical model are taken into consideration. Visual information fidelity (VIF) as an objective criterion is introduced to evaluate the fusion image. The experimental results of 117 groups of Arabidopsis cell image from John Innes Center show that the new algorithm cannot only make the details of original images well preserved but also improve the visibility of the fusion image, which shows the superiority of the novel method to traditional ones. PMID:23476716

A concurrent multiscale micromorphic molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Shaofan, E-mail: shaofan@berkeley.edu; Tong, Qi

2015-04-21

In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from firstmore » principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation.« less

Complex, multi-scale small intestinal topography replicated in cellular growth substrates fabricated via chemical vapor deposition of Parylene C.

PubMed

Koppes, Abigail N; Kamath, Megha; Pfluger, Courtney A; Burkey, Daniel D; Dokmeci, Mehmet; Wang, Lin; Carrier, Rebecca L

2016-08-22

Native small intestine possesses distinct multi-scale structures (e.g., crypts, villi) not included in traditional 2D intestinal culture models for drug delivery and regenerative medicine. The known impact of structure on cell function motivates exploration of the influence of intestinal topography on the phenotype of cultured epithelial cells, but the irregular, macro- to submicron-scale features of native intestine are challenging to precisely replicate in cellular growth substrates. Herein, we utilized chemical vapor deposition of Parylene C on decellularized porcine small intestine to create polymeric intestinal replicas containing biomimetic irregular, multi-scale structures. These replicas were used as molds for polydimethylsiloxane (PDMS) growth substrates with macro to submicron intestinal topographical features. Resultant PDMS replicas exhibit multiscale resolution including macro- to micro-scale folds, crypt and villus structures, and submicron-scale features of the underlying basement membrane. After 10 d of human epithelial colorectal cell culture on PDMS substrates, the inclusion of biomimetic topographical features enhanced alkaline phosphatase expression 2.3-fold compared to flat controls, suggesting biomimetic topography is important in induced epithelial differentiation. This work presents a facile, inexpensive method for precisely replicating complex hierarchal features of native tissue, towards a new model for regenerative medicine and drug delivery for intestinal disorders and diseases.

Effect of film multi-scale structure on the water vapor permeability in hydroxypropyl starch (HPS)/Na-MMT nanocomposites.

PubMed

Liu, Siyuan; Cai, Panfu; Li, Xiaoxi; Chen, Ling; Li, Lin; Li, Bing

2016-12-10

To improve the water vapor resistance of starch-based films, Na-MMT (Na-montmorillonite) as nanofillers were fabricated into hydroxypropyl starch and the multi-scale structural changes (including intermolecular interaction, short-range conformation, long-range ordered structure and the aggregated structure of the film) were revealed. The elongation of the water vapor molecule pathway by tortuous path is generally recognized as the main reason for the improvement of water resistance. However this study observed the lowest water vapor permeability (WVP) was at the 3% Na-MMT/hydroxypropyl starch (HPS) ratio instead of 5% even nanofillers were partially exfoliated at both ratio. Except for the "tortuous path" caused by nanofillers, this observation proposed that the short-range conformation of HPS chains, long-range ordered structure and the aggregated structure likely influenced the water barrier property. The relationship between WVP and multi-scale structure of the film was investigated. The results suggested that a good balance of short-range conformationin the amorphous region, long-range ordered structure and the aggregated structure of the film was required for the improvement of water vapor barrier property. Copyright © 2016 Elsevier Ltd. All rights reserved.

An optimized algorithm for multiscale wideband deconvolution of radio astronomical images

NASA Astrophysics Data System (ADS)

Offringa, A. R.; Smirnov, O.

2017-10-01

We describe a new multiscale deconvolution algorithm that can also be used in a multifrequency mode. The algorithm only affects the minor clean loop. In single-frequency mode, the minor loop of our improved multiscale algorithm is over an order of magnitude faster than the casa multiscale algorithm, and produces results of similar quality. For multifrequency deconvolution, a technique named joined-channel cleaning is used. In this mode, the minor loop of our algorithm is two to three orders of magnitude faster than casa msmfs. We extend the multiscale mode with automated scale-dependent masking, which allows structures to be cleaned below the noise. We describe a new scale-bias function for use in multiscale cleaning. We test a second deconvolution method that is a variant of the moresane deconvolution technique, and uses a convex optimization technique with isotropic undecimated wavelets as dictionary. On simple well-calibrated data, the convex optimization algorithm produces visually more representative models. On complex or imperfect data, the convex optimization algorithm has stability issues.

Multiplex lithography for multilevel multiscale architectures and its application to polymer electrolyte membrane fuel cell

PubMed Central

Cho, Hyesung; Moon Kim, Sang; Sik Kang, Yun; Kim, Junsoo; Jang, Segeun; Kim, Minhyoung; Park, Hyunchul; Won Bang, Jung; Seo, Soonmin; Suh, Kahp-Yang; Sung, Yung-Eun; Choi, Mansoo

2015-01-01

The production of multiscale architectures is of significant interest in materials science, and the integration of those structures could provide a breakthrough for various applications. Here we report a simple yet versatile strategy that allows for the LEGO-like integrations of microscale membranes by quantitatively controlling the oxygen inhibition effects of ultraviolet-curable materials, leading to multilevel multiscale architectures. The spatial control of oxygen concentration induces different curing contrasts in a resin allowing the selective imprinting and bonding at different sides of a membrane, which enables LEGO-like integration together with the multiscale pattern formation. Utilizing the method, the multilevel multiscale Nafion membranes are prepared and applied to polymer electrolyte membrane fuel cell. Our multiscale membrane fuel cell demonstrates significant enhancement of performance while ensuring mechanical robustness. The performance enhancement is caused by the combined effect of the decrease of membrane resistance and the increase of the electrochemical active surface area. PMID:26412619

Data fusion of multi-scale representations for structural damage detection

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-01-01

Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

Fast multiview three-dimensional reconstruction method using cost volume filtering

NASA Astrophysics Data System (ADS)

Lee, Seung Joo; Park, Min Ki; Jang, In Yeop; Lee, Kwan H.

2014-03-01

As the number of customers who want to record three-dimensional (3-D) information using a mobile electronic device increases, it becomes more and more important to develop a method which quickly reconstructs a 3-D model from multiview images. A fast multiview-based 3-D reconstruction method is presented, which is suitable for the mobile environment by constructing a cost volume of the 3-D height field. This method consists of two steps: the construction of a reliable base surface and the recovery of shape details. In each step, the cost volume is constructed using photoconsistency and then it is filtered according to the multiscale. The multiscale-based cost volume filtering allows the 3-D reconstruction to maintain the overall shape and to preserve the shape details. We demonstrate the strength of the proposed method in terms of computation time, accuracy, and unconstrained acquisition environment.

Logarithmic profile mapping multi-scale Retinex for restoration of low illumination images

NASA Astrophysics Data System (ADS)

Shi, Haiyan; Kwok, Ngaiming; Wu, Hongkun; Li, Ruowei; Liu, Shilong; Lin, Ching-Feng; Wong, Chin Yeow

2018-04-01

Images are valuable information sources for many scientific and engineering applications. However, images captured in poor illumination conditions would have a large portion of dark regions that could heavily degrade the image quality. In order to improve the quality of such images, a restoration algorithm is developed here that transforms the low input brightness to a higher value using a modified Multi-Scale Retinex approach. The algorithm is further improved by a entropy based weighting with the input and the processed results to refine the necessary amplification at regions of low brightness. Moreover, fine details in the image are preserved by applying the Retinex principles to extract and then re-insert object edges to obtain an enhanced image. Results from experiments using low and normal illumination images have shown satisfactory performances with regard to the improvement in information contents and the mitigation of viewing artifacts.

A New Feature-Enhanced Speckle Reduction Method Based on Multiscale Analysis for Ultrasound B-Mode Imaging.

PubMed

Kang, Jinbum; Lee, Jae Young; Yoo, Yangmo

2016-06-01

Effective speckle reduction in ultrasound B-mode imaging is important for enhancing the image quality and improving the accuracy in image analysis and interpretation. In this paper, a new feature-enhanced speckle reduction (FESR) method based on multiscale analysis and feature enhancement filtering is proposed for ultrasound B-mode imaging. In FESR, clinical features (e.g., boundaries and borders of lesions) are selectively emphasized by edge, coherence, and contrast enhancement filtering from fine to coarse scales while simultaneously suppressing speckle development via robust diffusion filtering. In the simulation study, the proposed FESR method showed statistically significant improvements in edge preservation, mean structure similarity, speckle signal-to-noise ratio, and contrast-to-noise ratio (CNR) compared with other speckle reduction methods, e.g., oriented speckle reducing anisotropic diffusion (OSRAD), nonlinear multiscale wavelet diffusion (NMWD), the Laplacian pyramid-based nonlinear diffusion and shock filter (LPNDSF), and the Bayesian nonlocal means filter (OBNLM). Similarly, the FESR method outperformed the OSRAD, NMWD, LPNDSF, and OBNLM methods in terms of CNR, i.e., 10.70 ± 0.06 versus 9.00 ± 0.06, 9.78 ± 0.06, 8.67 ± 0.04, and 9.22 ± 0.06 in the phantom study, respectively. Reconstructed B-mode images that were developed using the five speckle reduction methods were reviewed by three radiologists for evaluation based on each radiologist's diagnostic preferences. All three radiologists showed a significant preference for the abdominal liver images obtained using the FESR methods in terms of conspicuity, margin sharpness, artificiality, and contrast, p<0.0001. For the kidney and thyroid images, the FESR method showed similar improvement over other methods. However, the FESR method did not show statistically significant improvement compared with the OBNLM method in margin sharpness for the kidney and thyroid images. These results demonstrate that the proposed FESR method can improve the image quality of ultrasound B-mode imaging by enhancing the visualization of lesion features while effectively suppressing speckle noise.

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iliopoulos, AS; Sun, X; Floros, D

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less

A Deep Machine Learning Method for Classifying Cyclic Time Series of Biological Signals Using Time-Growing Neural Network.

PubMed

Gharehbaghi, Arash; Linden, Maria

2017-10-12

This paper presents a novel method for learning the cyclic contents of stochastic time series: the deep time-growing neural network (DTGNN). The DTGNN combines supervised and unsupervised methods in different levels of learning for an enhanced performance. It is employed by a multiscale learning structure to classify cyclic time series (CTS), in which the dynamic contents of the time series are preserved in an efficient manner. This paper suggests a systematic procedure for finding the design parameter of the classification method for a one-versus-multiple class application. A novel validation method is also suggested for evaluating the structural risk, both in a quantitative and a qualitative manner. The effect of the DTGNN on the performance of the classifier is statistically validated through the repeated random subsampling using different sets of CTS, from different medical applications. The validation involves four medical databases, comprised of 108 recordings of the electroencephalogram signal, 90 recordings of the electromyogram signal, 130 recordings of the heart sound signal, and 50 recordings of the respiratory sound signal. Results of the statistical validations show that the DTGNN significantly improves the performance of the classification and also exhibits an optimal structural risk.

Multiscale modeling of a low magnetostrictive Fe-27wt%Co-0.5wt%Cr alloy

NASA Astrophysics Data System (ADS)

Savary, M.; Hubert, O.; Helbert, A. L.; Baudin, T.; Batonnet, R.; Waeckerlé, T.

2018-05-01

The present paper deals with the improvement of a multi-scale approach describing the magneto-mechanical coupling of Fe-27wt%Co-0.5wt%Cr alloy. The magnetostriction behavior is demonstrated as very different (low magnetostriction vs. high magnetostriction) when this material is submitted to two different final annealing conditions after cold rolling. The numerical data obtained from a multi-scale approach are in accordance with experimental data corresponding to the high magnetostriction level material. A bi-domain structure hypothesis is employed to explain the low magnetostriction behavior, in accordance with the effect of an applied tensile stress. A modification of the multiscale approach is proposed to match this result.

Multiscale Space-Time Computational Methods for Fluid-Structure Interactions

DTIC Science & Technology

2015-09-13

prescribed fully or partially, is from an actual locust, extracted from high-speed, multi-camera video recordings of the locust in a wind tunnel . We use...With creative methods for coupling the fluid and structure, we can increase the scope and efficiency of the FSI modeling . Multiscale methods, which now...play an important role in computational mathematics, can also increase the accuracy and efficiency of the computer modeling techniques. The main

Integrated chemical and multi-scale structural analyses for the processes of acid pretreatment and enzymatic hydrolysis of corn stover.

PubMed

Chen, Longjian; Li, Junbao; Lu, Minsheng; Guo, Xiaomiao; Zhang, Haiyan; Han, Lujia

2016-05-05

Corn stover was pretreated with acid under moderate conditions (1.5%, w/w, 121°C, 60min), and kinetic enzymolysis experiments were performed on the pretreated substrate using a mixture of Celluclast 1.5L (20FPU/g dry substrate) and Novozyme 188 (40CBU/g dry substrate). Integrated chemical and multi-scale structural methods were then used to characterize both processes. Chemical analysis showed that acid pretreatment removed considerable hemicellulose (from 19.7% in native substrate to 9.28% in acid-pretreated substrate) and achieved a reasonably high conversion efficiency (58.63% of glucose yield) in the subsequent enzymatic hydrolysis. Multi-scale structural analysis indicated that acid pretreatment caused structural changes via cleaving acetyl linkages, solubilizing hemicellulose, relocating cell wall surfaces and enlarging substrate porosity (pore volume increased from 0.0067cm(3)/g in native substrate to 0.019cm(3)/g in acid-pretreated substrate), thereby improving the polysaccharide digestibility. Copyright © 2016 Elsevier Ltd. All rights reserved.

Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2010-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multifactor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.

Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multi-factor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.

Multiscale characterization and mechanical modeling of an Al-Zn-Mg electron beam weld

NASA Astrophysics Data System (ADS)

Puydt, Quentin; Flouriot, Sylvain; Ringeval, Sylvain; Parry, Guillaume; De Geuser, Frédéric; Deschamps, Alexis

Welding of precipitation hardening alloys results in multi-scale microstructural heterogeneities, from the hardening nano-scale precipitates to the micron-scale solidification structures and to the component geometry. This heterogeneity results in a complex mechanical response, with gradients in strength, stress triaxiality and damage initiation sites.

Incremental Testing of the Community Multiscale Air Quality (CMAQ) Modeling System Version 4.7

EPA Science Inventory

This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to obse...

Data-Driven Hierarchical Structure Kernel for Multiscale Part-Based Object Recognition

PubMed Central

Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Zheng, Yuan F.

2017-01-01

Detecting generic object categories in images and videos are a fundamental issue in computer vision. However, it faces the challenges from inter and intraclass diversity, as well as distortions caused by viewpoints, poses, deformations, and so on. To solve object variations, this paper constructs a structure kernel and proposes a multiscale part-based model incorporating the discriminative power of kernels. The structure kernel would measure the resemblance of part-based objects in three aspects: 1) the global similarity term to measure the resemblance of the global visual appearance of relevant objects; 2) the part similarity term to measure the resemblance of the visual appearance of distinctive parts; and 3) the spatial similarity term to measure the resemblance of the spatial layout of parts. In essence, the deformation of parts in the structure kernel is penalized in a multiscale space with respect to horizontal displacement, vertical displacement, and scale difference. Part similarities are combined with different weights, which are optimized efficiently to maximize the intraclass similarities and minimize the interclass similarities by the normalized stochastic gradient ascent algorithm. In addition, the parameters of the structure kernel are learned during the training process with regard to the distribution of the data in a more discriminative way. With flexible part sizes on scale and displacement, it can be more robust to the intraclass variations, poses, and viewpoints. Theoretical analysis and experimental evaluations demonstrate that the proposed multiscale part-based representation model with structure kernel exhibits accurate and robust performance, and outperforms state-of-the-art object classification approaches. PMID:24808345

Multiscale X-ray and Proton Imaging of Bismuth-Tin Solidification

NASA Astrophysics Data System (ADS)

Gibbs, P. J.; Imhoff, S. D.; Morris, C. L.; Merrill, F. E.; Wilde, C. H.; Nedrow, P.; Mariam, F. G.; Fezzaa, K.; Lee, W.-K.; Clarke, A. J.

2014-08-01

The formation of structural patterns during metallic solidification is complex and multiscale in nature, ranging from the nanometer scale, where solid-liquid interface properties are important, to the macroscale, where casting mold filling and intended heat transfer are crucial. X-ray and proton imaging can directly interrogate structure, solute, and fluid flow development in metals from the microscale to the macroscale. X-rays permit high spatio-temporal resolution imaging of microscopic solidification dynamics in thin metal sections. Similarly, high-energy protons permit imaging of mesoscopic and macroscopic solidification dynamics in large sample volumes. In this article, we highlight multiscale x-ray and proton imaging of bismuth-tin alloy solidification to illustrate dynamic measurement of crystal growth rates and solute segregation profiles that can be that can be acquired using these techniques.

Multiscale structural gradients enhance the biomechanical functionality of the spider fang

PubMed Central

Bar-On, Benny; Barth, Friedrich G.; Fratzl, Peter; Politi, Yael

2014-01-01

The spider fang is a natural injection needle, hierarchically built from a complex composite material comprising multiscale architectural gradients. Considering its biomechanical function, the spider fang has to sustain significant mechanical loads. Here we apply experiment-based structural modelling of the fang, followed by analytical mechanical description and Finite-Element simulations, the results of which indicate that the naturally evolved fang architecture results in highly adapted effective structural stiffness and damage resilience. The analysis methods and physical insights of this work are potentially important for investigating and understanding the architecture and structural motifs of sharp-edge biological elements such as stingers, teeth, claws and more. PMID:24866935

Multi-scale signed envelope inversion

NASA Astrophysics Data System (ADS)

Chen, Guo-Xin; Wu, Ru-Shan; Wang, Yu-Qing; Chen, Sheng-Chang

2018-06-01

Envelope inversion based on modulation signal mode was proposed to reconstruct large-scale structures of underground media. In order to solve the shortcomings of conventional envelope inversion, multi-scale envelope inversion was proposed using new envelope Fréchet derivative and multi-scale inversion strategy to invert strong contrast models. In multi-scale envelope inversion, amplitude demodulation was used to extract the low frequency information from envelope data. However, only to use amplitude demodulation method will cause the loss of wavefield polarity information, thus increasing the possibility of inversion to obtain multiple solutions. In this paper we proposed a new demodulation method which can contain both the amplitude and polarity information of the envelope data. Then we introduced this demodulation method into multi-scale envelope inversion, and proposed a new misfit functional: multi-scale signed envelope inversion. In the numerical tests, we applied the new inversion method to the salt layer model and SEG/EAGE 2-D Salt model using low-cut source (frequency components below 4 Hz were truncated). The results of numerical test demonstrated the effectiveness of this method.

Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering.

PubMed

Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki

2015-09-10

In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments.

Suppression of chaos at slow variables by rapidly mixing fast dynamics through linear energy-preserving coupling

NASA Astrophysics Data System (ADS)

Abramov, R. V.

2011-12-01

Chaotic multiscale dynamical systems are common in many areas of science, one of the examples being the interaction of the low-frequency dynamics in the atmosphere with the fast turbulent weather dynamics. One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely predictable at the slow variables through increasing chaos and turbulence at the fast variables. This result contradicts the common sense intuition, where, naturally, one would think that coupling a slow weakly chaotic system with another much faster and much stronger chaotic system would result in general increase of chaos at the slow variables.

Multiscale-Driven approach to detecting change in Synthetic Aperture Radar (SAR) imagery

NASA Astrophysics Data System (ADS)

Gens, R.; Hogenson, K.; Ajadi, O. A.; Meyer, F. J.; Myers, A.; Logan, T. A.; Arnoult, K., Jr.

2017-12-01

Detecting changes between Synthetic Aperture Radar (SAR) images can be a useful but challenging exercise. SAR with its all-weather capabilities can be an important resource in identifying and estimating the expanse of events such as flooding, river ice breakup, earthquake damage, oil spills, and forest growth, as it can overcome shortcomings of optical methods related to cloud cover. However, detecting change in SAR imagery can be impeded by many factors including speckle, complex scattering responses, low temporal sampling, and difficulty delineating boundaries. In this presentation we use a change detection method based on a multiscale-driven approach. By using information at different resolution levels, we attempt to obtain more accurate change detection maps in both heterogeneous and homogeneous regions. Integrated within the processing flow are processes that 1) improve classification performance by combining Expectation-Maximization algorithms with mathematical morphology, 2) achieve high accuracy in preserving boundaries using measurement level fusion techniques, and 3) combine modern non-local filtering and 2D-discrete stationary wavelet transform to provide robustness against noise. This multiscale-driven approach to change detection has recently been incorporated into the Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3) using radiometrically terrain corrected SAR images. Examples primarily from natural hazards are presented to illustrate the capabilities and limitations of the change detection method.

Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering

PubMed Central

Kang, Wonseok; Yu, Soohwan; Seo, Doochun; Jeong, Jaeheon; Paik, Joonki

2015-01-01

In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments. PMID:26378532

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

Multiscale Simulation of Microbe Structure and Dynamics

PubMed Central

Joshi, Harshad; Singharoy, Abhishek; Sereda, Yuriy V.; Cheluvaraja, Srinath C.; Ortoleva, Peter J.

2012-01-01

A multiscale mathematical and computational approach is developed that captures the hierarchical organization of a microbe. It is found that a natural perspective for understanding a microbe is in terms of a hierarchy of variables at various levels of resolution. This hierarchy starts with the N -atom description and terminates with order parameters characterizing a whole microbe. This conceptual framework is used to guide the analysis of the Liouville equation for the probability density of the positions and momenta of the N atoms constituting the microbe and its environment. Using multiscale mathematical techniques, we derive equations for the co-evolution of the order parameters and the probability density of the N-atom state. This approach yields a rigorous way to transfer information between variables on different space-time scales. It elucidates the interplay between equilibrium and far-from-equilibrium processes underlying microbial behavior. It also provides framework for using coarse-grained nanocharacterization data to guide microbial simulation. It enables a methodical search for free-energy minimizing structures, many of which are typically supported by the set of macromolecules and membranes constituting a given microbe. This suite of capabilities provides a natural framework for arriving at a fundamental understanding of microbial behavior, the analysis of nanocharacterization data, and the computer-aided design of nanostructures for biotechnical and medical purposes. Selected features of the methodology are demonstrated using our multiscale bionanosystem simulator DeductiveMultiscaleSimulator. Systems used to demonstrate the approach are structural transitions in the cowpea chlorotic mosaic virus, RNA of satellite tobacco mosaic virus, virus-like particles related to human papillomavirus, and iron-binding protein lactoferrin. PMID:21802438

Models, Databases, and Simulation Tools Needed for the Realization of Integrated Computational Materials Engineering. Proceedings of the Symposium Held at Materials Science and Technology 2010

NASA Technical Reports Server (NTRS)

Arnold, Steven M. (Editor); Wong, Terry T. (Editor)

2011-01-01

Topics covered include: An Annotative Review of Multiscale Modeling and its Application to Scales Inherent in the Field of ICME; and A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures.

Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

NASA Astrophysics Data System (ADS)

Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

2017-10-01

A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

A FSI computational framework for vascular physiopathology: A novel flow-tissue multiscale strategy.

PubMed

Bianchi, Daniele; Monaldo, Elisabetta; Gizzi, Alessio; Marino, Michele; Filippi, Simonetta; Vairo, Giuseppe

2017-09-01

A novel fluid-structure computational framework for vascular applications is herein presented. It is developed by combining the double multi-scale nature of vascular physiopathology in terms of both tissue properties and blood flow. Addressing arterial tissues, they are modelled via a nonlinear multiscale constitutive rationale, based only on parameters having a clear histological and biochemical meaning. Moreover, blood flow is described by coupling a three-dimensional fluid domain (undergoing physiological inflow conditions) with a zero-dimensional model, which allows to reproduce the influence of the downstream vasculature, furnishing a realistic description of the outflow proximal pressure. The fluid-structure interaction is managed through an explicit time-marching approach, able to accurately describe tissue nonlinearities within each computational step for the fluid problem. A case study associated to a patient-specific aortic abdominal aneurysmatic geometry is numerically investigated, highlighting advantages gained from the proposed multiscale strategy, as well as showing soundness and effectiveness of the established framework for assessing useful clinical quantities and risk indexes. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Multi-scale modelling of elastic moduli of trabecular bone

PubMed Central

Hamed, Elham; Jasiuk, Iwona; Yoo, Andrew; Lee, YikHan; Liszka, Tadeusz

2012-01-01

We model trabecular bone as a nanocomposite material with hierarchical structure and predict its elastic properties at different structural scales. The analysis involves a bottom-up multi-scale approach, starting with nanoscale (mineralized collagen fibril) and moving up the scales to sub-microscale (single lamella), microscale (single trabecula) and mesoscale (trabecular bone) levels. Continuum micromechanics methods, composite materials laminate theory and finite-element methods are used in the analysis. Good agreement is found between theoretical and experimental results. PMID:22279160

Probabilistic Multi-Scale, Multi-Level, Multi-Disciplinary Analysis and Optimization of Engine Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2000-01-01

Aircraft engines are assemblies of dynamically interacting components. Engine updates to keep present aircraft flying safely and engines for new aircraft are progressively required to operate in more demanding technological and environmental requirements. Designs to effectively meet those requirements are necessarily collections of multi-scale, multi-level, multi-disciplinary analysis and optimization methods and probabilistic methods are necessary to quantify respective uncertainties. These types of methods are the only ones that can formally evaluate advanced composite designs which satisfy those progressively demanding requirements while assuring minimum cost, maximum reliability and maximum durability. Recent research activities at NASA Glenn Research Center have focused on developing multi-scale, multi-level, multidisciplinary analysis and optimization methods. Multi-scale refers to formal methods which describe complex material behavior metal or composite; multi-level refers to integration of participating disciplines to describe a structural response at the scale of interest; multidisciplinary refers to open-ended for various existing and yet to be developed discipline constructs required to formally predict/describe a structural response in engine operating environments. For example, these include but are not limited to: multi-factor models for material behavior, multi-scale composite mechanics, general purpose structural analysis, progressive structural fracture for evaluating durability and integrity, noise and acoustic fatigue, emission requirements, hot fluid mechanics, heat-transfer and probabilistic simulations. Many of these, as well as others, are encompassed in an integrated computer code identified as Engine Structures Technology Benefits Estimator (EST/BEST) or Multi-faceted/Engine Structures Optimization (MP/ESTOP). The discipline modules integrated in MP/ESTOP include: engine cycle (thermodynamics), engine weights, internal fluid mechanics, cost, mission and coupled structural/thermal, various composite property simulators and probabilistic methods to evaluate uncertainty effects (scatter ranges) in all the design parameters. The objective of the proposed paper is to briefly describe a multi-faceted design analysis and optimization capability for coupled multi-discipline engine structures optimization. Results are presented for engine and aircraft type metrics to illustrate the versatility of that capability. Results are also presented for reliability, noise and fatigue to illustrate its inclusiveness. For example, replacing metal rotors with composites reduces the engine weight by 20 percent, 15 percent noise reduction, and an order of magnitude improvement in reliability. Composite designs exist to increase fatigue life by at least two orders of magnitude compared to state-of-the-art metals.

Comparative Study of Speckle Filtering Methods in PolSAR Radar Images

NASA Astrophysics Data System (ADS)

Boutarfa, S.; Bouchemakh, L.; Smara, Y.

2015-04-01

Images acquired by polarimetric SAR (PolSAR) radar systems are characterized by the presence of a noise called speckle. This noise has a multiplicative nature, corrupts both the amplitude and phase images, which complicates data interpretation, degrades segmentation performance and reduces the detectability of targets. Hence, the need to preprocess the images by adapted filtering methods before analysis.In this paper, we present a comparative study of implemented methods for reducing speckle in PolSAR images. These developed filters are: refined Lee filter based on the estimation of the minimum mean square error MMSE, improved Sigma filter with detection of strong scatterers based on the calculation of the coherency matrix to detect the different scatterers in order to preserve the polarization signature and maintain structures that are necessary for image interpretation, filtering by stationary wavelet transform SWT using multi-scale edge detection and the technique for improving the wavelet coefficients called SSC (sum of squared coefficients), and Turbo filter which is a combination between two complementary filters the refined Lee filter and the wavelet transform SWT. One filter can boost up the results of the other.The originality of our work is based on the application of these methods to several types of images: amplitude, intensity and complex, from a satellite or an airborne radar, and on the optimization of wavelet filtering by adding a parameter in the calculation of the threshold. This parameter will control the filtering effect and get a good compromise between smoothing homogeneous areas and preserving linear structures.The methods are applied to the fully polarimetric RADARSAT-2 images (HH, HV, VH, VV) acquired on Algiers, Algeria, in C-band and to the three polarimetric E-SAR images (HH, HV, VV) acquired on Oberpfaffenhofen area located in Munich, Germany, in P-band.To evaluate the performance of each filter, we used the following criteria: smoothing homogeneous areas, preserving edges and polarimetric information.Experimental results are included to illustrate the different implemented methods.

“Skin-Core-Skin” Structure of Polymer Crystallization Investigated by Multiscale Simulation

PubMed Central

Ruan, Chunlei

2018-01-01

“Skin-core-skin” structure is a typical crystal morphology in injection products. Previous numerical works have rarely focused on crystal evolution; rather, they have mostly been based on the prediction of temperature distribution or crystallization kinetics. The aim of this work was to achieve the “skin-core-skin” structure and investigate the role of external flow and temperature fields on crystal morphology. Therefore, the multiscale algorithm was extended to the simulation of polymer crystallization in a pipe flow. The multiscale algorithm contains two parts: a collocated finite volume method at the macroscopic level and a morphological Monte Carlo method at the microscopic level. The SIMPLE (semi-implicit method for pressure linked equations) algorithm was used to calculate the polymeric model at the macroscopic level, while the Monte Carlo method with stochastic birth-growth process of spherulites and shish-kebabs was used at the microscopic level. Results show that our algorithm is valid to predict “skin-core-skin” structure, and the initial melt temperature and the maximum velocity of melt at the inlet mainly affects the morphology of shish-kebabs. PMID:29659516

Multiscale modelling of hydraulic conductivity in vuggy porous media

PubMed Central

Daly, K. R.; Roose, T.

2014-01-01

Flow in both saturated and non-saturated vuggy porous media, i.e. soil, is inherently multiscale. The complex microporous structure of the soil aggregates and the wider vugs provides a multitude of flow pathways and has received significant attention from the X-ray computed tomography (CT) community with a constant drive to image at higher resolution. Using multiscale homogenization, we derive averaged equations to study the effects of the microscale structure on the macroscopic flow. The averaged model captures the underlying geometry through a series of cell problems and is verified through direct comparison to numerical simulations of the full structure. These methods offer significant reductions in computation time and allow us to perform three-dimensional calculations with complex geometries on a desktop PC. The results show that the surface roughness of the aggregate has a significantly greater effect on the flow than the microstructure within the aggregate. Hence, this is the region in which the resolution of X-ray CT for image-based modelling has the greatest impact. PMID:24511248

A New Age-Structured Multiscale Model of the Hepatitis C Virus Life-Cycle During Infection and Therapy With Direct-Acting Antiviral Agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quintela, Barbara de M.; Conway, Jessica M.; Hyman, James M.

Here, the dynamics of hepatitis C virus (HCV) RNA during translation and replication within infected cells were added to a previous age-structured multiscale mathematical model of HCV infection and treatment. The model allows the study of the dynamics of HCV RNA inside infected cells as well as the release of virus from infected cells and the dynamics of subsequent new cell infections. The model was used to fit in vitro data and estimate parameters characterizing HCV replication. This is the first model to our knowledge to consider both positive and negative strands of HCV RNA with an age-structured multiscale modelingmore » approach. Using this model we also studied the effects of direct-acting antiviral agents (DAAs) in blocking HCV RNA intracellular replication and the release of new virions and fit the model to in vivo data obtained from HCV-infected subjects under therapy.« less

A New Age-Structured Multiscale Model of the Hepatitis C Virus Life-Cycle During Infection and Therapy With Direct-Acting Antiviral Agents

DOE PAGES

Quintela, Barbara de M.; Conway, Jessica M.; Hyman, James M.; ...

2018-04-04

Here, the dynamics of hepatitis C virus (HCV) RNA during translation and replication within infected cells were added to a previous age-structured multiscale mathematical model of HCV infection and treatment. The model allows the study of the dynamics of HCV RNA inside infected cells as well as the release of virus from infected cells and the dynamics of subsequent new cell infections. The model was used to fit in vitro data and estimate parameters characterizing HCV replication. This is the first model to our knowledge to consider both positive and negative strands of HCV RNA with an age-structured multiscale modelingmore » approach. Using this model we also studied the effects of direct-acting antiviral agents (DAAs) in blocking HCV RNA intracellular replication and the release of new virions and fit the model to in vivo data obtained from HCV-infected subjects under therapy.« less

A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

NASA Astrophysics Data System (ADS)

Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

2017-12-01

Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

Biological materials by design.

PubMed

Qin, Zhao; Dimas, Leon; Adler, David; Bratzel, Graham; Buehler, Markus J

2014-02-19

In this topical review we discuss recent advances in the use of physical insight into the way biological materials function, to design novel engineered materials 'from scratch', or from the level of fundamental building blocks upwards and by using computational multiscale methods that link chemistry to material function. We present studies that connect advances in multiscale hierarchical material structuring with material synthesis and testing, review case studies of wood and other biological materials, and illustrate how engineered fiber composites and bulk materials are designed, modeled, and then synthesized and tested experimentally. The integration of experiment and simulation in multiscale design opens new avenues to explore the physics of materials from a fundamental perspective, and using complementary strengths from models and empirical techniques. Recent developments in this field illustrate a new paradigm by which complex material functionality is achieved through hierarchical structuring in spite of simple material constituents.

Enhancement of IVR images by combining an ICA shrinkage filter with a multi-scale filter

NASA Astrophysics Data System (ADS)

Chen, Yen-Wei; Matsuo, Kiyotaka; Han, Xianhua; Shimizu, Atsumoto; Shibata, Koichi; Mishina, Yukio; Mukuta, Yoshihiro

2007-11-01

Interventional Radiology (IVR) is an important technique to visualize and diagnosis the vascular disease. In real medical application, a weak x-ray radiation source is used for imaging in order to reduce the radiation dose, resulting in a low contrast noisy image. It is important to develop a method to smooth out the noise while enhance the vascular structure. In this paper, we propose to combine an ICA Shrinkage filter with a multiscale filter for enhancement of IVR images. The ICA shrinkage filter is used for noise reduction and the multiscale filter is used for enhancement of vascular structure. Experimental results show that the quality of the image can be dramatically improved without any blurring in edge by the proposed method. Simultaneous noise reduction and vessel enhancement have been achieved.

Identity in agent-based models : modeling dynamic multiscale social processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ozik, J.; Sallach, D. L.; Macal, C. M.

Identity-related issues play central roles in many current events, including those involving factional politics, sectarianism, and tribal conflicts. Two popular models from the computational-social-science (CSS) literature - the Threat Anticipation Program and SharedID models - incorporate notions of identity (individual and collective) and processes of identity formation. A multiscale conceptual framework that extends some ideas presented in these models and draws other capabilities from the broader CSS literature is useful in modeling the formation of political identities. The dynamic, multiscale processes that constitute and transform social identities can be mapped to expressive structures of the framework

Rough Set Approach to Incomplete Multiscale Information System

PubMed Central

Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu

2014-01-01

Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852

The multiscale nature of magnetic pattern on the solar surface

NASA Astrophysics Data System (ADS)

Scardigli, S.; Del Moro, D.; Berrilli, F.

Multiscale magnetic underdense regions (voids) appear in high resolution magnetograms of quiet solar surface. These regions may be considered a signature of the underlying convective structure. The study of the associated pattern paves the way for the study of turbulent convective scales from granular to global. In order to address the question of magnetic pattern driven by turbulent convection we used a novel automatic void detection method to calculate void distributions. The absence of preferred scales of organization in the calculated distributions supports the multiscale nature of flows on the solar surface and the absence of preferred convective scales.

Multi-scale thermal stability of a hard thermoplastic protein-based material

NASA Astrophysics Data System (ADS)

Latza, Victoria; Guerette, Paul A.; Ding, Dawei; Amini, Shahrouz; Kumar, Akshita; Schmidt, Ingo; Keating, Steven; Oxman, Neri; Weaver, James C.; Fratzl, Peter; Miserez, Ali; Masic, Admir

2015-09-01

Although thermoplastic materials are mostly derived from petro-chemicals, it would be highly desirable, from a sustainability perspective, to produce them instead from renewable biopolymers. Unfortunately, biopolymers exhibiting thermoplastic behaviour and which preserve their mechanical properties post processing are essentially non-existent. The robust sucker ring teeth (SRT) from squid and cuttlefish are one notable exception of thermoplastic biopolymers. Here we describe thermoplastic processing of squid SRT via hot extrusion of fibres, demonstrating the potential suitability of these materials for large-scale thermal forming. Using high-resolution in situ X-ray diffraction and vibrational spectroscopy, we elucidate the molecular and nanoscale features responsible for this behaviour and show that SRT consist of semi-crystalline polymers, whereby heat-resistant, nanocrystalline β-sheets embedded within an amorphous matrix are organized into a hexagonally packed nanofibrillar lattice. This study provides key insights for the molecular design of biomimetic protein- and peptide-based thermoplastic structural biopolymers with potential biomedical and 3D printing applications.

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity.

PubMed

Al-Awami, Ali K; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W; Pfister, Hanspeter; Hadwiger, Markus

2014-12-01

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

Multiscale structure in eco-evolutionary dynamics

NASA Astrophysics Data System (ADS)

Stacey, Blake C.

In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

A mixed parallel strategy for the solution of coupled multi-scale problems at finite strains

NASA Astrophysics Data System (ADS)

Lopes, I. A. Rodrigues; Pires, F. M. Andrade; Reis, F. J. P.

2018-02-01

A mixed parallel strategy for the solution of homogenization-based multi-scale constitutive problems undergoing finite strains is proposed. The approach aims to reduce the computational time and memory requirements of non-linear coupled simulations that use finite element discretization at both scales (FE^2). In the first level of the algorithm, a non-conforming domain decomposition technique, based on the FETI method combined with a mortar discretization at the interface of macroscopic subdomains, is employed. A master-slave scheme, which distributes tasks by macroscopic element and adopts dynamic scheduling, is then used for each macroscopic subdomain composing the second level of the algorithm. This strategy allows the parallelization of FE^2 simulations in computers with either shared memory or distributed memory architectures. The proposed strategy preserves the quadratic rates of asymptotic convergence that characterize the Newton-Raphson scheme. Several examples are presented to demonstrate the robustness and efficiency of the proposed parallel strategy.

Integrative computational models of cardiac arrhythmias -- simulating the structurally realistic heart

PubMed Central

Trayanova, Natalia A; Tice, Brock M

2009-01-01

Simulation of cardiac electrical function, and specifically, simulation aimed at understanding the mechanisms of cardiac rhythm disorders, represents an example of a successful integrative multiscale modeling approach, uncovering emergent behavior at the successive scales in the hierarchy of structural complexity. The goal of this article is to present a review of the integrative multiscale models of realistic ventricular structure used in the quest to understand and treat ventricular arrhythmias. It concludes with the new advances in image-based modeling of the heart and the promise it holds for the development of individualized models of ventricular function in health and disease. PMID:20628585

Multiscale Analysis of Structurally-Graded Microstructures Using Molecular Dynamics, Discrete Dislocation Dynamics and Continuum Crystal Plasticity

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.; Mishin, Yuri

2014-01-01

A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.

Coherent multiscale image processing using dual-tree quaternion wavelets.

PubMed

Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G

2008-07-01

The dual-tree quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant tight frame representation whose coefficients sport a magnitude and three phases: two phases encode local image shifts while the third contains image texture information. The QWT is based on an alternative theory for the 2-D Hilbert transform and can be computed using a dual-tree filter bank with linear computational complexity. To demonstrate the properties of the QWT's coherent magnitude/phase representation, we develop an efficient and accurate procedure for estimating the local geometrical structure of an image. We also develop a new multiscale algorithm for estimating the disparity between a pair of images that is promising for image registration and flow estimation applications. The algorithm features multiscale phase unwrapping, linear complexity, and sub-pixel estimation accuracy.

Versatile Micromechanics Model for Multiscale Analysis of Composite Structures

NASA Astrophysics Data System (ADS)

Kwon, Y. W.; Park, M. S.

2013-08-01

A general-purpose micromechanics model was developed so that the model could be applied to various composite materials such as reinforced by particles, long fibers and short fibers as well as those containing micro voids. Additionally, the model can be used with hierarchical composite materials. The micromechanics model can be used to compute effective material properties like elastic moduli, shear moduli, Poisson's ratios, and coefficients of thermal expansion for the various composite materials. The model can also calculate the strains and stresses at the constituent material level such as fibers, particles, and whiskers from the composite level stresses and strains. The model was implemented into ABAQUS using the UMAT option for multiscale analysis. An extensive set of examples are presented to demonstrate the reliability and accuracy of the developed micromechanics model for different kinds of composite materials. Another set of examples is provided to study the multiscale analysis of composite structures.

Tunable Multiscale Nanoparticle Ordering by Polymer Crystallization

PubMed Central

2017-01-01

While ∼75% of commercially utilized polymers are semicrystalline, the generally low mechanical modulus of these materials, especially for those possessing a glass transition temperature below room temperature, restricts their use for structural applications. Our focus in this paper is to address this deficiency through the controlled, multiscale assembly of nanoparticles (NPs), in particular by leveraging the kinetics of polymer crystallization. This process yields a multiscale NP structure that is templated by the lamellar semicrystalline polymer morphology and spans NPs engulfed by the growing crystals, NPs ordered into layers in the interlamellar zone [spacing of (10–100 nm)], and NPs assembled into fractal objects at the interfibrillar scale, (1–10 μm). The relative fraction of NPs in this hierarchy is readily manipulated by the crystallization speed. Adding NPs usually increases the Young’s modulus of the polymer, but the effects of multiscale ordering are nearly an order of magnitude larger than those for a state where the NPs are not ordered, i.e., randomly dispersed in the matrix. Since the material’s fracture toughness remains practically unaffected in this process, this assembly strategy allows us to create high modulus materials that retain the attractive high toughness and low density of polymers. PMID:28776017

Multiscale geometric modeling of macromolecules II: Lagrangian representation

PubMed Central

Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei

2013-01-01

Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599

Freezing does not alter multiscale tendon mechanics and damage mechanisms in tension.

PubMed

Lee, Andrea H; Elliott, Dawn M

2017-12-01

It is common in biomechanics to use previously frozen tissues, where it is assumed that the freeze-thaw process does not cause consequential mechanical or structural changes. We have recently quantified multiscale tendon mechanics and damage mechanisms using previously frozen tissue, where damage was defined as an irreversible change in the microstructure that alters the macroscopic mechanical parameters. Because freezing has been shown to alter tendon microstructures, the objective of this study was to determine if freezing alters tendon multiscale mechanics and damage mechanisms. Multiscale testing using a protocol that was designed to evaluate tendon damage (tensile stress-relaxation followed by unloaded recovery) was performed on fresh and previously frozen rat tail tendon fascicles. At both the fascicle and fibril levels, there was no difference between the fresh and frozen groups for any of the parameters, suggesting that there is no effect of freezing on tendon mechanics. After unloading, the microscale fibril strain fully recovered, and interfibrillar sliding only partially recovered, suggesting that the tendon damage is localized to the interfibrillar structures and that mechanisms of damage are the same in both fresh and previously frozen tendons. © 2017 New York Academy of Sciences.

A strain energy filter for 3D vessel enhancement with application to pulmonary CT images.

PubMed

Xiao, Changyan; Staring, Marius; Shamonin, Denis; Reiber, Johan H C; Stolk, Jan; Stoel, Berend C

2011-02-01

The traditional Hessian-related vessel filters often suffer from detecting complex structures like bifurcations due to an over-simplified cylindrical model. To solve this problem, we present a shape-tuned strain energy density function to measure vessel likelihood in 3D medical images. This method is initially inspired by established stress-strain principles in mechanics. By considering the Hessian matrix as a stress tensor, the three invariants from orthogonal tensor decomposition are used independently or combined to formulate distinctive functions for vascular shape discrimination, brightness contrast and structure strength measuring. Moreover, a mathematical description of Hessian eigenvalues for general vessel shapes is obtained, based on an intensity continuity assumption, and a relative Hessian strength term is presented to ensure the dominance of second-order derivatives as well as suppress undesired step-edges. Finally, we adopt the multi-scale scheme to find an optimal solution through scale space. The proposed method is validated in experiments with a digital phantom and non-contrast-enhanced pulmonary CT data. It is shown that our model performed more effectively in enhancing vessel bifurcations and preserving details, compared to three existing filters. Copyright © 2010 Elsevier B.V. All rights reserved.

Capturing Multiscale Phenomena via Adaptive Mesh Refinement (AMR) in 2D and 3D Atmospheric Flows

NASA Astrophysics Data System (ADS)

Ferguson, J. O.; Jablonowski, C.; Johansen, H.; McCorquodale, P.; Ullrich, P. A.; Langhans, W.; Collins, W. D.

2017-12-01

Extreme atmospheric events such as tropical cyclones are inherently complex multiscale phenomena. Such phenomena are a challenge to simulate in conventional atmosphere models, which typically use rather coarse uniform-grid resolutions. To enable study of these systems, Adaptive Mesh Refinement (AMR) can provide sufficient local resolution by dynamically placing high-resolution grid patches selectively over user-defined features of interest, such as a developing cyclone, while limiting the total computational burden of requiring such high-resolution globally. This work explores the use of AMR with a high-order, non-hydrostatic, finite-volume dynamical core, which uses the Chombo AMR library to implement refinement in both space and time on a cubed-sphere grid. The characteristics of the AMR approach are demonstrated via a series of idealized 2D and 3D test cases designed to mimic atmospheric dynamics and multiscale flows. In particular, new shallow-water test cases with forcing mechanisms are introduced to mimic the strengthening of tropical cyclone-like vortices and to include simplified moisture and convection processes. The forced shallow-water experiments quantify the improvements gained from AMR grids, assess how well transient features are preserved across grid boundaries, and determine effective refinement criteria. In addition, results from idealized 3D test cases are shown to characterize the accuracy and stability of the non-hydrostatic 3D AMR dynamical core.

Multiscale solutions of radiative heat transfer by the discrete unified gas kinetic scheme

NASA Astrophysics Data System (ADS)

Luo, Xiao-Ping; Wang, Cun-Hai; Zhang, Yong; Yi, Hong-Liang; Tan, He-Ping

2018-06-01

The radiative transfer equation (RTE) has two asymptotic regimes characterized by the optical thickness, namely, optically thin and optically thick regimes. In the optically thin regime, a ballistic or kinetic transport is dominant. In the optically thick regime, energy transport is totally dominated by multiple collisions between photons; that is, the photons propagate by means of diffusion. To obtain convergent solutions to the RTE, conventional numerical schemes have a strong dependence on the number of spatial grids, which leads to a serious computational inefficiency in the regime where the diffusion is predominant. In this work, a discrete unified gas kinetic scheme (DUGKS) is developed to predict radiative heat transfer in participating media. Numerical performances of the DUGKS are compared in detail with conventional methods through three cases including one-dimensional transient radiative heat transfer, two-dimensional steady radiative heat transfer, and three-dimensional multiscale radiative heat transfer. Due to the asymptotic preserving property, the present method with relatively coarse grids gives accurate and reliable numerical solutions for large, small, and in-between values of optical thickness, and, especially in the optically thick regime, the DUGKS demonstrates a pronounced computational efficiency advantage over the conventional numerical models. In addition, the DUGKS has a promising potential in the study of multiscale radiative heat transfer inside the participating medium with a transition from optically thin to optically thick regimes.

Effects of Subscale Size and Shape on Global Energy Dissipation in a Multiscale Model of a Fiber-Reinforced Composite Exhibiting Post-Peak Strain Softening Using Abaqus and FEAMAC

NASA Technical Reports Server (NTRS)

Pineda, Evan, J.; Bednarcyk, Brett, A.; Arnold, Steven, M.

2012-01-01

A mesh objective crack band model is implemented in the generalized method of cells (GMC) micromechanics model to predict failure of a composite repeating unit cell (RUC). The micromechanics calculations are achieved using the MAC/GMC core engine within the ImMAC suite of micromechanics codes, developed at the NASA Glenn Research Center. The microscale RUC is linked to a macroscale Abaqus/Standard finite element model using the FEAMAC multiscale framework (included in the ImMAC suite). The effects of the relationship between the characteristic length of the finite element and the size of the microscale RUC on the total energy dissipation of the multiscale model are investigated. A simple 2-D composite square subjected to uniaxial tension is used to demonstrate the effects of scaling the dimensions of the RUC such that the length of the sides of the RUC are equal to the characteristic length of the finite element. These results are compared to simulations where the size of the RUC is fixed, independent of the element size. Simulations are carried out for a variety of mesh densities and element shapes, including square and triangular. Results indicate that a consistent size and shape must be used to yield preserve energy dissipation across the scales.

A Multiscale Vision Model applied to analyze EIT images of the solar corona

NASA Astrophysics Data System (ADS)

Portier-Fozzani, F.; Vandame, B.; Bijaoui, A.; Maucherat, A. J.; EIT Team

2001-07-01

The large dynamic range provided by the SOHO/EIT CCD (1 : 5000) is needed to observe the large EUV zoom of coronal structures from coronal homes up to flares. Histograms show that often a wide dynamic range is present in each image. Extracting hidden structures in the background level requires specific techniques such as the use of the Multiscale Vision Model (MVM, Bijaoui et al., 1998). This method, based on wavelet transformations optimizes detection of various size objects, however complex they may be. Bijaoui et al. built the Multiscale Vision Model to extract small dynamical structures from noise, mainly for studying galaxies. In this paper, we describe requirements for the use of this method with SOHO/EIT images (calibration, size of the image, dynamics of the subimage, etc.). Two different areas were studied revealing hidden structures: (1) classical coronal mass ejection (CME) formation and (2) a complex group of active regions with its evolution. The aim of this paper is to define carefully the constraints for this new method of imaging the solar corona with SOHO/EIT. Physical analysis derived from multi-wavelength observations will later complete these first results.

Wavefield complexity and stealth structures: Resolution constraints by wave physics

NASA Astrophysics Data System (ADS)

Nissen-Meyer, T.; Leng, K.

2017-12-01

Imaging the Earth's interior relies on understanding how waveforms encode information from heterogeneous multi-scale structure. This relation is given by elastodynamics, but forward modeling in the context of tomography primarily serves to deliver synthetic waveforms and gradients for the inversion procedure. While this is entirely appropriate, it depreciates a wealth of complementary inference that can be obtained from the complexity of the wavefield. Here, we are concerned with the imprint of realistic multi-scale Earth structure on the wavefield, and the question on the inherent physical resolution limit of structures encoded in seismograms. We identify parameter and scattering regimes where structures remain invisible as a function of seismic wavelength, structural multi-scale geometry, scattering strength, and propagation path. Ultimately, this will aid in interpreting tomographic images by acknowledging the scope of "forgotten" structures, and shall offer guidance for optimising the selection of seismic data for tomography. To do so, we use our novel 3D modeling method AxiSEM3D which tackles global wave propagation in visco-elastic, anisotropic 3D structures with undulating boundaries at unprecedented resolution and efficiency by exploiting the inherent azimuthal smoothness of wavefields via a coupled Fourier expansion-spectral-element approach. The method links computational cost to wavefield complexity and thereby lends itself well to exploring the relation between waveforms and structures. We will show various examples of multi-scale heterogeneities which appear or disappear in the waveform, and argue that the nature of the structural power spectrum plays a central role in this. We introduce the concept of wavefield learning to examine the true wavefield complexity for a complexity-dependent modeling framework and discriminate which scattering structures can be retrieved by surface measurements. This leads to the question of physical invisibility and the tomographic resolution limit, and offers insight as to why tomographic images still show stark differences for smaller-scale heterogeneities despite progress in modeling and data resolution. Finally, we give an outlook on how we expand this modeling framework towards an inversion procedure guided by wavefield complexity.

Intercomparison of Multiscale Modeling Approaches in Simulating Subsurface Flow and Transport

NASA Astrophysics Data System (ADS)

Yang, X.; Mehmani, Y.; Barajas-Solano, D. A.; Song, H. S.; Balhoff, M.; Tartakovsky, A. M.; Scheibe, T. D.

2016-12-01

Hybrid multiscale simulations that couple models across scales are critical to advance predictions of the larger system behavior using understanding of fundamental processes. In the current study, three hybrid multiscale methods are intercompared: multiscale loose-coupling method, multiscale finite volume (MsFV) method and multiscale mortar method. The loose-coupling method enables a parallel workflow structure based on the Swift scripting environment that manages the complex process of executing coupled micro- and macro-scale models without being intrusive to the at-scale simulators. The MsFV method applies microscale and macroscale models over overlapping subdomains of the modeling domain and enforces continuity of concentration and transport fluxes between models via restriction and prolongation operators. The mortar method is a non-overlapping domain decomposition approach capable of coupling all permutations of pore- and continuum-scale models with each other. In doing so, Lagrange multipliers are used at interfaces shared between the subdomains so as to establish continuity of species/fluid mass flux. Subdomain computations can be performed either concurrently or non-concurrently depending on the algorithm used. All the above methods have been proven to be accurate and efficient in studying flow and transport in porous media. However, there has not been any field-scale applications and benchmarking among various hybrid multiscale approaches. To address this challenge, we apply all three hybrid multiscale methods to simulate water flow and transport in a conceptualized 2D modeling domain of the hyporheic zone, where strong interactions between groundwater and surface water exist across multiple scales. In all three multiscale methods, fine-scale simulations are applied to a thin layer of riverbed alluvial sediments while the macroscopic simulations are used for the larger subsurface aquifer domain. Different numerical coupling methods are then applied between scales and inter-compared. Comparisons are drawn in terms of velocity distributions, solute transport behavior, algorithm-induced numerical error and computing cost. The intercomparison work provides support for confidence in a variety of hybrid multiscale methods and motivates further development and applications.

Multiscale pore structure and its effect on gas transport in organic-rich shale

NASA Astrophysics Data System (ADS)

Wu, Tianhao; Li, Xiang; Zhao, Junliang; Zhang, Dongxiao

2017-07-01

A systematic investigation of multiscale pore structure in organic-rich shale by means of the combination of various imaging techniques is presented, including the state-of-the-art Helium-Ion-Microscope (HIM). The study achieves insight into the major features at each scale and suggests the affordable techniques for specific objectives from the aspects of resolution, dimension, and cost. The pores, which appear to be isolated, are connected by smaller pores resolved by higher-resolution imaging. This observation provides valuable information, from the microscopic perspective of pore structure, for understanding how gas accumulates and transports from where it is generated. A comprehensive workflow is proposed based on the characteristics acquired from the multiscale pore structure analysis to simulate the gas transport process. The simulations are completed with three levels: the microscopic mechanisms should be taken into consideration at level I; the spatial distribution features of organic matter, inorganic matter, and macropores constitute the major issue at level II; and the microfracture orientation and topological structure are dominant factors at level III. The results of apparent permeability from simulations agree well with the values acquired from experiments. By means of the workflow, the impact of various gas transport mechanisms at different scales can be investigated more individually and precisely than conventional experiments.

A Facile Method to Fabricate Anisotropic Hydrogels with Perfectly Aligned Hierarchical Fibrous Structures.

PubMed

Mredha, Md Tariful Islam; Guo, Yun Zhou; Nonoyama, Takayuki; Nakajima, Tasuku; Kurokawa, Takayuki; Gong, Jian Ping

2018-03-01

Natural structural materials (such as tendons and ligaments) are comprised of multiscale hierarchical architectures, with dimensions ranging from nano- to macroscale, which are difficult to mimic synthetically. Here a bioinspired, facile method to fabricate anisotropic hydrogels with perfectly aligned multiscale hierarchical fibrous structures similar to those of tendons and ligaments is reported. The method includes drying a diluted physical hydrogel in air by confining its length direction. During this process, sufficiently high tensile stress is built along the length direction to align the polymer chains and multiscale fibrous structures (from nano- to submicro- to microscale) are spontaneously formed in the bulk material, which are well-retained in the reswollen gel. The method is useful for relatively rigid polymers (such as alginate and cellulose), which are susceptible to mechanical signal. By controlling the drying with or without prestretching, the degree of alignment, size of superstructures, and the strength of supramolecular interactions can be tuned, which sensitively influence the strength and toughness of the hydrogels. The mechanical properties are comparable with those of natural ligaments. This study provides a general strategy for designing hydrogels with highly ordered hierarchical structures, which opens routes for the development of many functional biomimetic materials for biomedical applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural health monitoring using DOG multi-scale space: an approach for analyzing damage characteristics

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-03-01

Measurement noise is inevitable in practice; thus, it is difficult to identify defects, cracks or damage in a structure while suppressing noise simultaneously. In this work, a novel method is introduced to detect multiple damage in noisy environments. Based on multi-scale space analysis for discrete signals, a method for extracting damage characteristics from the measured displacement mode shape is illustrated. Moreover, the proposed method incorporates a data fusion algorithm to further eliminate measurement noise-based interference. The effectiveness of the method is verified by numerical and experimental methods applied to different structural types. The results demonstrate that there are two advantages to the proposed method. First, damage features are extracted by the difference of the multi-scale representation; this step is taken such that the interference of noise amplification can be avoided. Second, a data fusion technique applied to the proposed method provides a global decision, which retains the damage features while maximally eliminating the uncertainty. Monte Carlo simulations are utilized to validate that the proposed method has a higher accuracy in damage detection.

A multiscale-based approach for composite materials with embedded PZT filaments for energy harvesting

NASA Astrophysics Data System (ADS)

El-Etriby, Ahmed E.; Abdel-Meguid, Mohamed E.; Hatem, Tarek M.; Bahei-El-Din, Yehia A.

2014-03-01

Ambient vibrations are major source of wasted energy, exploiting properly such vibration can be converted to valuable energy and harvested to power up devices, i.e. electronic devices. Accordingly, energy harvesting using smart structures with active piezoelectric ceramics has gained wide interest over the past few years as a method for converting such wasted energy. This paper provides numerical and experimental analysis of piezoelectric fiber based composites for energy harvesting applications proposing a multi-scale modeling approach coupled with experimental verification. The multi-scale approach suggested to predict the behavior of piezoelectric fiber-based composites use micromechanical model based on Transformation Field Analysis (TFA) to calculate the overall material properties of electrically active composite structure. Capitalizing on the calculated properties, single-phase analysis of a homogeneous structure is conducted using finite element method. The experimental work approach involves running dynamic tests on piezoelectric fiber-based composites to simulate mechanical vibrations experienced by a subway train floor tiles. Experimental results agree well with the numerical results both for static and dynamic tests.

Divergence Free High Order Filter Methods for Multiscale Non-ideal MHD Flows

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sjoegreen, Bjoern

2003-01-01

Low-dissipative high order filter finite difference methods for long time wave propagation of shock/turbulence/combustion compressible viscous MHD flows has been constructed. Several variants of the filter approach that cater to different flow types are proposed. These filters provide a natural and efficient way for the minimization of the divergence of the magnetic field (Delta . B) numerical error in the sense that no standard divergence cleaning is required. For certain 2-D MHD test problems, divergence free preservation of the magnetic fields of these filter schemes has been achieved.

Temporal Changes in Forest Contexts at Multiple Extents: Three Decades of Fragmentation in the Gran Chaco (1979-2010), Central Argentina.

PubMed

Frate, Ludovico; Acosta, Alicia T R; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura

2015-01-01

The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979-2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (Pf) and structural connectivity (Pff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting Pf vs. Pff mean values and were compared across spatial extents. The distributions of Pf across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of Pf's variability along with the increment of the mean slope of the Pf 's scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored.

Temporal Changes in Forest Contexts at Multiple Extents: Three Decades of Fragmentation in the Gran Chaco (1979-2010), Central Argentina

PubMed Central

Frate, Ludovico; Acosta, Alicia T. R.; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura

2015-01-01

The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979–2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (P f) and structural connectivity (P ff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting P f vs. P ff mean values and were compared across spatial extents. The distributions of P f across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of P f’s variability along with the increment of the mean slope of the P f ‘s scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored. PMID:26630387

Generalized multiscale finite-element method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Kai; Fu, Shubin; Gibson, Richard L.

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Kai, E-mail: kaigao87@gmail.com; Fu, Shubin, E-mail: shubinfu89@gmail.com; Gibson, Richard L., E-mail: gibson@tamu.edu

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

Generalized multiscale finite-element method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

DOE PAGES

Gao, Kai; Fu, Shubin; Gibson, Richard L.; ...

2015-04-14

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less

Detecting Multi-scale Structures in Chandra Images of Centaurus A

NASA Astrophysics Data System (ADS)

Karovska, M.; Fabbiano, G.; Elvis, M. S.; Evans, I. N.; Kim, D. W.; Prestwich, A. H.; Schwartz, D. A.; Murray, S. S.; Forman, W.; Jones, C.; Kraft, R. P.; Isobe, T.; Cui, W.; Schreier, E. J.

1999-12-01

Centaurus A (NGC 5128) is a giant early-type galaxy with a merger history, containing the nearest radio-bright AGN. Recent Chandra High Resolution Camera (HRC) observations of Cen A reveal X-ray multi-scale structures in this object with unprecedented detail and clarity. We show the results of an analysis of the Chandra data with smoothing and edge enhancement techniques that allow us to enhance and quantify the multi-scale structures present in the HRC images. These techniques include an adaptive smoothing algorithm (Ebeling et al 1999), and a multi-directional gradient detection algorithm (Karovska et al 1994). The Ebeling et al adaptive smoothing algorithm, which is incorporated in the CXC analysis s/w package, is a powerful tool for smoothing images containing complex structures at various spatial scales. The adaptively smoothed images of Centaurus A show simultaneously the high-angular resolution bright structures at scales as small as an arcsecond and the extended faint structures as large as several arc minutes. The large scale structures suggest complex symmetry, including a component possibly associated with the inner radio lobes (as suggested by the ROSAT HRI data, Dobereiner et al 1996), and a separate component with an orthogonal symmetry that may be associated with the galaxy as a whole. The dust lane and the x-ray ridges are very clearly visible. The adaptively smoothed images and the edge-enhanced images also suggest several filamentary features including a large filament-like structure extending as far as about 5 arcminutes to North-West.

Adaptation of a Fast Optimal Interpolation Algorithm to the Mapping of Oceangraphic Data

NASA Technical Reports Server (NTRS)

Menemenlis, Dimitris; Fieguth, Paul; Wunsch, Carl; Willsky, Alan

1997-01-01

A fast, recently developed, multiscale optimal interpolation algorithm has been adapted to the mapping of hydrographic and other oceanographic data. This algorithm produces solution and error estimates which are consistent with those obtained from exact least squares methods, but at a small fraction of the computational cost. Problems whose solution would be completely impractical using exact least squares, that is, problems with tens or hundreds of thousands of measurements and estimation grid points, can easily be solved on a small workstation using the multiscale algorithm. In contrast to methods previously proposed for solving large least squares problems, our approach provides estimation error statistics while permitting long-range correlations, using all measurements, and permitting arbitrary measurement locations. The multiscale algorithm itself, published elsewhere, is not the focus of this paper. However, the algorithm requires statistical models having a very particular multiscale structure; it is the development of a class of multiscale statistical models, appropriate for oceanographic mapping problems, with which we concern ourselves in this paper. The approach is illustrated by mapping temperature in the northeastern Pacific. The number of hydrographic stations is kept deliberately small to show that multiscale and exact least squares results are comparable. A portion of the data were not used in the analysis; these data serve to test the multiscale estimates. A major advantage of the present approach is the ability to repeat the estimation procedure a large number of times for sensitivity studies, parameter estimation, and model testing. We have made available by anonymous Ftp a set of MATLAB-callable routines which implement the multiscale algorithm and the statistical models developed in this paper.

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE PAGES

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin; ...

2018-03-15

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Multi-Scale Microstructural Thermoelectric Materials: Transport Behavior, Non-Equilibrium Preparation, and Applications.

PubMed

Su, Xianli; Wei, Ping; Li, Han; Liu, Wei; Yan, Yonggao; Li, Peng; Su, Chuqi; Xie, Changjun; Zhao, Wenyu; Zhai, Pengcheng; Zhang, Qingjie; Tang, Xinfeng; Uher, Ctirad

2017-05-01

Considering only about one third of the world's energy consumption is effectively utilized for functional uses, and the remaining is dissipated as waste heat, thermoelectric (TE) materials, which offer a direct and clean thermal-to-electric conversion pathway, have generated a tremendous worldwide interest. The last two decades have witnessed a remarkable development in TE materials. This Review summarizes the efforts devoted to the study of non-equilibrium synthesis of TE materials with multi-scale structures, their transport behavior, and areas of applications. Studies that work towards the ultimate goal of developing highly efficient TE materials possessing multi-scale architectures are highlighted, encompassing the optimization of TE performance via engineering the structures with different dimensional aspects spanning from the atomic and molecular scales, to nanometer sizes, and to the mesoscale. In consideration of the practical applications of high-performance TE materials, the non-equilibrium approaches offer a fast and controllable fabrication of multi-scale microstructures, and their scale up to industrial-size manufacturing is emphasized here. Finally, the design of two integrated power generating TE systems are described-a solar thermoelectric-photovoltaic hybrid system and a vehicle waste heat harvesting system-that represent perhaps the most important applications of thermoelectricity in the energy conversion area. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Multiscale Analysis of Delamination of Carbon Fiber-Epoxy Laminates with Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Riddick, Jaret C.; Frankland, SJV; Gates, TS

2006-01-01

A multi-scale analysis is presented to parametrically describe the Mode I delamination of a carbon fiber/epoxy laminate. In the midplane of the laminate, carbon nanotubes are included for the purposes of selectively enhancing the fracture toughness of the laminate. To analyze carbon fiber epoxy carbon nanotube laminate, the multi-scale methodology presented here links a series of parameterizations taken at various length scales ranging from the atomistic through the micromechanical to the structural level. At the atomistic scale molecular dynamics simulations are performed in conjunction with an equivalent continuum approach to develop constitutive properties for representative volume elements of the molecular structure of components of the laminate. The molecular-level constitutive results are then used in the Mori-Tanaka micromechanics to develop bulk properties for the epoxy-carbon nanotube matrix system. In order to demonstrate a possible application of this multi-scale methodology, a double cantilever beam specimen is modeled. An existing analysis is employed which uses discrete springs to model the fiber bridging affect during delamination propagation. In the absence of empirical data or a damage mechanics model describing the effect of CNTs on fracture toughness, several tractions laws are postulated, linking CNT volume fraction to fiber bridging in a DCB specimen. Results from this demonstration are presented in terms of DCB specimen load-displacement responses.

Multiscale virtual particle based elastic network model (MVP-ENM) for normal mode analysis of large-sized biomolecules.

PubMed

Xia, Kelin

2017-12-20

In this paper, a multiscale virtual particle based elastic network model (MVP-ENM) is proposed for the normal mode analysis of large-sized biomolecules. The multiscale virtual particle (MVP) model is proposed for the discretization of biomolecular density data. With this model, large-sized biomolecular structures can be coarse-grained into virtual particles such that a balance between model accuracy and computational cost can be achieved. An elastic network is constructed by assuming "connections" between virtual particles. The connection is described by a special harmonic potential function, which considers the influence from both the mass distributions and distance relations of the virtual particles. Two independent models, i.e., the multiscale virtual particle based Gaussian network model (MVP-GNM) and the multiscale virtual particle based anisotropic network model (MVP-ANM), are proposed. It has been found that in the Debye-Waller factor (B-factor) prediction, the results from our MVP-GNM with a high resolution are as good as the ones from GNM. Even with low resolutions, our MVP-GNM can still capture the global behavior of the B-factor very well with mismatches predominantly from the regions with large B-factor values. Further, it has been demonstrated that the low-frequency eigenmodes from our MVP-ANM are highly consistent with the ones from ANM even with very low resolutions and a coarse grid. Finally, the great advantage of MVP-ANM model for large-sized biomolecules has been demonstrated by using two poliovirus virus structures. The paper ends with a conclusion.

Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samala, Ravi K., E-mail: rsamala@umich.edu; Chan, Heang-Ping; Lu, Yao

Purpose: Develop a computer-aided detection (CADe) system for clustered microcalcifications in digital breast tomosynthesis (DBT) volume enhanced with multiscale bilateral filtering (MSBF) regularization. Methods: With Institutional Review Board approval and written informed consent, two-view DBT of 154 breasts, of which 116 had biopsy-proven microcalcification (MC) clusters and 38 were free of MCs, was imaged with a General Electric GEN2 prototype DBT system. The DBT volumes were reconstructed with MSBF-regularized simultaneous algebraic reconstruction technique (SART) that was designed to enhance MCs and reduce background noise while preserving the quality of other tissue structures. The contrast-to-noise ratio (CNR) of MCs was furthermore » improved with enhancement-modulated calcification response (EMCR) preprocessing, which combined multiscale Hessian response to enhance MCs by shape and bandpass filtering to remove the low-frequency structured background. MC candidates were then located in the EMCR volume using iterative thresholding and segmented by adaptive region growing. Two sets of potential MC objects, cluster centroid objects and MC seed objects, were generated and the CNR of each object was calculated. The number of candidates in each set was controlled based on the breast volume. Dynamic clustering around the centroid objects grouped the MC candidates to form clusters. Adaptive criteria were designed to reduce false positive (FP) clusters based on the size, CNR values and the number of MCs in the cluster, cluster shape, and cluster based maximum intensity projection. Free-response receiver operating characteristic (FROC) and jackknife alternative FROC (JAFROC) analyses were used to assess the performance and compare with that of a previous study. Results: Unpaired two-tailedt-test showed a significant increase (p < 0.0001) in the ratio of CNRs for MCs with and without MSBF regularization compared to similar ratios for FPs. For view-based detection, a sensitivity of 85% was achieved at an FP rate of 2.16 per DBT volume. For case-based detection, a sensitivity of 85% was achieved at an FP rate of 0.85 per DBT volume. JAFROC analysis showed a significant improvement in the performance of the current CADe system compared to that of our previous system (p = 0.003). Conclusions: MBSF regularized SART reconstruction enhances MCs. The enhancement in the signals, in combination with properly designed adaptive threshold criteria, effective MC feature analysis, and false positive reduction techniques, leads to a significant improvement in the detection of clustered MCs in DBT.« less

Simultaneous formation of multiscale hierarchical surface morphologies through sequential wrinkling and folding

NASA Astrophysics Data System (ADS)

Wang, Yu; Sun, Qingyang; Xiao, Jianliang

2018-02-01

Highly organized hierarchical surface morphologies possess various intriguing properties that could find important potential applications. In this paper, we demonstrate a facile approach to simultaneously form multiscale hierarchical surface morphologies through sequential wrinkling. This method combines surface wrinkling induced by thermal expansion and mechanical strain on a three-layer structure composed of an aluminum film, a hard Polydimethylsiloxane (PDMS) film, and a soft PDMS substrate. Deposition of the aluminum film on hard PDMS induces biaxial wrinkling due to thermal expansion mismatch, and recovering the prestrain in the soft PDMS substrate leads to wrinkling of the hard PDMS film. In total, three orders of wrinkling patterns form in this process, with wavelength and amplitude spanning 3 orders of magnitude in length scale. By increasing the prestrain in the soft PDMS substrate, a hierarchical wrinkling-folding structure was also obtained. This approach can be easily extended to other thin films for fabrication of multiscale hierarchical surface morphologies with potential applications in different areas.

Viscous Fingering in Multiport Hele Shaw Cell for Controlled Shaping of Fluids.

PubMed

Islam, Tanveer Ul; Gandhi, Prasanna S

2017-11-30

The pursuit of mimicking complex multiscale systems has been a tireless effort with many successes but a daunting task ahead. A new perspective to engineer complex cross-linked meshes and branched/tree-like structures at different scales is presented here. Control over Saffman-Taylor instability which otherwise randomly rearranges viscous fluid in a 'lifted Hele-Shaw cell' is proposed for the same. The proposed control employs multiple-ports or source-holes in this cell, to spontaneously shape a stretched fluid film into a network of well defined webs/meshes and ordered multiscale tree-like patterns. Use of multiple ports enables exercising strong control to fabricate such structures, in a robust and repeated fashion, which otherwise are completely non-characteristic to viscous fingering process. The proposed technique is capable of fabricating spontaneously families of wide variety of structures over micro and very large scale in a period of few seconds. Thus the proposed method forms a solid foundation to new pathways for engineering multiscale structures for several scientific applications including efficient gas exchange, heat transport, tissue engineering, organ-on-chip, and so on. Proposal of multi-port Hele-Shaw cell also opens new avenues for investigation of complex multiple finger interactions resulting in interesting fluid patterns.

Multiscale morphological filtering for analysis of noisy and complex images

NASA Astrophysics Data System (ADS)

Kher, A.; Mitra, S.

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

Multiscale Morphological Filtering for Analysis of Noisy and Complex Images

NASA Technical Reports Server (NTRS)

Kher, A.; Mitra, S.

1993-01-01

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

Self adaptive multi-scale morphology AVG-Hat filter and its application to fault feature extraction for wheel bearing

NASA Astrophysics Data System (ADS)

Deng, Feiyue; Yang, Shaopu; Tang, Guiji; Hao, Rujiang; Zhang, Mingliang

2017-04-01

Wheel bearings are essential mechanical components of trains, and fault detection of the wheel bearing is of great significant to avoid economic loss and casualty effectively. However, considering the operating conditions, detection and extraction of the fault features hidden in the heavy noise of the vibration signal have become a challenging task. Therefore, a novel method called adaptive multi-scale AVG-Hat morphology filter (MF) is proposed to solve it. The morphology AVG-Hat operator not only can suppress the interference of the strong background noise greatly, but also enhance the ability of extracting fault features. The improved envelope spectrum sparsity (IESS), as a new evaluation index, is proposed to select the optimal filtering signal processed by the multi-scale AVG-Hat MF. It can present a comprehensive evaluation about the intensity of fault impulse to the background noise. The weighted coefficients of the different scale structural elements (SEs) in the multi-scale MF are adaptively determined by the particle swarm optimization (PSO) algorithm. The effectiveness of the method is validated by analyzing the real wheel bearing fault vibration signal (e.g. outer race fault, inner race fault and rolling element fault). The results show that the proposed method could improve the performance in the extraction of fault features effectively compared with the multi-scale combined morphological filter (CMF) and multi-scale morphology gradient filter (MGF) methods.

Action detection by double hierarchical multi-structure space-time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-03-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Action detection by double hierarchical multi-structure space–time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-06-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

An investigation into preserving spatially-distinct pore systems in multi-component rocks using a fossiliferous limestone example

NASA Astrophysics Data System (ADS)

Jiang, Zeyun; Couples, Gary D.; Lewis, Helen; Mangione, Alessandro

2018-07-01

Limestones containing abundant disc-shaped fossil Nummulites can form significant hydrocarbon reservoirs but they have a distinctly heterogeneous distribution of pore shapes, sizes and connectivities, which make it particularly difficult to calculate petrophysical properties and consequent flow outcomes. The severity of the problem rests on the wide length-scale range from the millimetre scale of the fossil's pore space to the micron scale of rock matrix pores. This work develops a technique to incorporate multi-scale void systems into a pore network, which is used to calculate the petrophysical properties for subsequent flow simulations at different stages in the limestone's petrophysical evolution. While rock pore size, shape and connectivity can be determined, with varying levels of fidelity, using techniques such as X-ray computed tomography (CT) or scanning electron microscopy (SEM), this work represents a more challenging class where the rock of interest is insufficiently sampled or, as here, has been overprinted by extensive chemical diagenesis. The main challenge is integrating multi-scale void structures derived from both SEM and CT images, into a single model or a pore-scale network while still honouring the nature of the connections across these length scales. Pore network flow simulations are used to illustrate the technique but of equal importance, to demonstrate how supportable earlier-stage petrophysical property distributions can be used to assess the viability of several potential geological event sequences. The results of our flow simulations on generated models highlight the requirement for correct determination of the dominant pore scales (one plus of nm, μm, mm, cm), the spatial correlation and the cross-scale connections.

Overcoming Challenges in Kinetic Modeling of Magnetized Plasmas and Vacuum Electronic Devices

NASA Astrophysics Data System (ADS)

Omelchenko, Yuri; Na, Dong-Yeop; Teixeira, Fernando

2017-10-01

We transform the state-of-the art of plasma modeling by taking advantage of novel computational techniques for fast and robust integration of multiscale hybrid (full particle ions, fluid electrons, no displacement current) and full-PIC models. These models are implemented in 3D HYPERS and axisymmetric full-PIC CONPIC codes. HYPERS is a massively parallel, asynchronous code. The HYPERS solver does not step fields and particles synchronously in time but instead executes local variable updates (events) at their self-adaptive rates while preserving fundamental conservation laws. The charge-conserving CONPIC code has a matrix-free explicit finite-element (FE) solver based on a sparse-approximate inverse (SPAI) algorithm. This explicit solver approximates the inverse FE system matrix (``mass'' matrix) using successive sparsity pattern orders of the original matrix. It does not reduce the set of Maxwell's equations to a vector-wave (curl-curl) equation of second order but instead utilizes the standard coupled first-order Maxwell's system. We discuss the ability of our codes to accurately and efficiently account for multiscale physical phenomena in 3D magnetized space and laboratory plasmas and axisymmetric vacuum electronic devices.

A systematic multiscale modeling and experimental approach to protect grain boundaries in magnesium alloys from corrosion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horstemeyer, Mark R.; Chaudhuri, Santanu

2015-09-30

A multiscale modeling Internal State Variable (ISV) constitutive model was developed that captures the fundamental structure-property relationships. The macroscale ISV model used lower length scale simulations (Butler-Volmer and Electronics Structures results) in order to inform the ISVs at the macroscale. The chemomechanical ISV model was calibrated and validated from experiments with magnesium (Mg) alloys that were investigated under corrosive environments coupled with experimental electrochemical studies. Because the ISV chemomechanical model is physically based, it can be used for other material systems to predict corrosion behavior. As such, others can use the chemomechanical model for analyzing corrosion effects on their designs.

Superhydrophobic gecko feet with high adhesive forces towards water and their bio-inspired materials.

PubMed

Liu, Kesong; Du, Jiexing; Wu, Juntao; Jiang, Lei

2012-02-07

Functional integration is an inherent characteristic for multiscale structures of biological materials. In this contribution, we first investigate the liquid-solid adhesive forces between water droplets and superhydrophobic gecko feet using a high-sensitivity micro-electromechanical balance system. It was found, in addition to the well-known solid-solid adhesion, the gecko foot, with a multiscale structure, possesses both superhydrophobic functionality and a high adhesive force towards water. The origin of the high adhesive forces of gecko feet to water could be attributed to the high density nanopillars that contact the water. Inspired by this, polyimide films with gecko-like multiscale structures were constructed by using anodic aluminum oxide templates, exhibiting superhydrophobicity and a strong adhesive force towards water. The static water contact angle is larger than 150° and the adhesive force to water is about 66 μN. The resultant gecko-inspired polyimide film can be used as a "mechanical hand" to snatch micro-liter liquids. We expect this work will provide the inspiration to reveal the mechanism of the high-adhesive superhydrophobic of geckos and extend the practical applications of polyimide materials. This journal is © The Royal Society of Chemistry 2012

Multiscale Morphology of Nanoporous Copper Made from Intermetallic Phases

DOE PAGES

Egle, Tobias; Barroo, Cédric; Janvelyan, Nare; ...

2017-07-11

Many application-relevant properties of nanoporous metals critically depend on their multiscale architecture. For example, the intrinsically high step-edge density of curved surfaces at the nanoscale provides highly reactive sites for catalysis, whereas the macroscale pore and grain morphology determines the macroscopic properties, such as mass transport, electrical conductivity, or mechanical properties. Here, in this work, we systematically study the effects of alloy composition and dealloying conditions on the multiscale morphology of nanoporous copper (np-Cu) made from various commercial Zn–Cu precursor alloys. Using a combination of X-ray diffraction, electron backscatter diffraction, and focused ion beam cross-sectional analysis, our results reveal thatmore » the macroscopic grain structure of the starting alloy surprisingly survives the dealloying process, despite a change in crystal structure from body-centered cubic (Zn–Cu starting alloy) to face-centered cubic (Cu). The nanoscale structure can be controlled by the acid used for dealloying with HCl leading to a larger and more faceted ligament morphology compared to that of H 3PO 4. Finally, anhydrous ethanol dehydrogenation was used as a probe reaction to test the effect of the nanoscale ligament morphology on the apparent activation energy of the reaction.« less

Multiscale Morphology of Nanoporous Copper Made from Intermetallic Phases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Egle, Tobias; Barroo, Cédric; Janvelyan, Nare

Many application-relevant properties of nanoporous metals critically depend on their multiscale architecture. For example, the intrinsically high step-edge density of curved surfaces at the nanoscale provides highly reactive sites for catalysis, whereas the macroscale pore and grain morphology determines the macroscopic properties, such as mass transport, electrical conductivity, or mechanical properties. Here, in this work, we systematically study the effects of alloy composition and dealloying conditions on the multiscale morphology of nanoporous copper (np-Cu) made from various commercial Zn–Cu precursor alloys. Using a combination of X-ray diffraction, electron backscatter diffraction, and focused ion beam cross-sectional analysis, our results reveal thatmore » the macroscopic grain structure of the starting alloy surprisingly survives the dealloying process, despite a change in crystal structure from body-centered cubic (Zn–Cu starting alloy) to face-centered cubic (Cu). The nanoscale structure can be controlled by the acid used for dealloying with HCl leading to a larger and more faceted ligament morphology compared to that of H 3PO 4. Finally, anhydrous ethanol dehydrogenation was used as a probe reaction to test the effect of the nanoscale ligament morphology on the apparent activation energy of the reaction.« less

Multiscale Multifunctional Progressive Fracture of Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Minnetyan, L.

2012-01-01

A new approach is described for evaluating fracture in composite structures. This approach is independent of classical fracture mechanics parameters like fracture toughness. It relies on computational simulation and is programmed in a stand-alone integrated computer code. It is multiscale, multifunctional because it includes composite mechanics for the composite behavior and finite element analysis for predicting the structural response. It contains seven modules; layered composite mechanics (micro, macro, laminate), finite element, updating scheme, local fracture, global fracture, stress based failure modes, and fracture progression. The computer code is called CODSTRAN (Composite Durability Structural ANalysis). It is used in the present paper to evaluate the global fracture of four composite shell problems and one composite built-up structure. Results show that the composite shells. Global fracture is enhanced when internal pressure is combined with shear loads. The old reference denotes that nothing has been added to this comprehensive report since then.

Constraining OCT with Knowledge of Device Design Enables High Accuracy Hemodynamic Assessment of Endovascular Implants.

PubMed

O'Brien, Caroline C; Kolandaivelu, Kumaran; Brown, Jonathan; Lopes, Augusto C; Kunio, Mie; Kolachalama, Vijaya B; Edelman, Elazer R

2016-01-01

Stacking cross-sectional intravascular images permits three-dimensional rendering of endovascular implants, yet introduces between-frame uncertainties that limit characterization of device placement and the hemodynamic microenvironment. In a porcine coronary stent model, we demonstrate enhanced OCT reconstruction with preservation of between-frame features through fusion with angiography and a priori knowledge of stent design. Strut positions were extracted from sequential OCT frames. Reconstruction with standard interpolation generated discontinuous stent structures. By computationally constraining interpolation to known stent skeletons fitted to 3D 'clouds' of OCT-Angio-derived struts, implant anatomy was resolved, accurately rendering features from implant diameter and curvature (n = 1 vessels, r2 = 0.91, 0.90, respectively) to individual strut-wall configurations (average displacement error ~15 μm). This framework facilitated hemodynamic simulation (n = 1 vessel), showing the critical importance of accurate anatomic rendering in characterizing both quantitative and basic qualitative flow patterns. Discontinuities with standard approaches systematically introduced noise and bias, poorly capturing regional flow effects. In contrast, the enhanced method preserved multi-scale (local strut to regional stent) flow interactions, demonstrating the impact of regional contexts in defining the hemodynamic consequence of local deployment errors. Fusion of planar angiography and knowledge of device design permits enhanced OCT image analysis of in situ tissue-device interactions. Given emerging interests in simulation-derived hemodynamic assessment as surrogate measures of biological risk, such fused modalities offer a new window into patient-specific implant environments.

Highly Coarse-Grained Representations of Transmembrane Proteins

PubMed Central

2017-01-01

Numerous biomolecules and biomolecular complexes, including transmembrane proteins (TMPs), are symmetric or at least have approximate symmetries. Highly coarse-grained models of such biomolecules, aiming at capturing the essential structural and dynamical properties on resolution levels coarser than the residue scale, must preserve the underlying symmetry. However, making these models obey the correct physics is in general not straightforward, especially at the highly coarse-grained resolution where multiple (∼3–30 in the current study) amino acid residues are represented by a single coarse-grained site. In this paper, we propose a simple and fast method of coarse-graining TMPs obeying this condition. The procedure involves partitioning transmembrane domains into contiguous segments of equal length along the primary sequence. For the coarsest (lowest-resolution) mappings, it turns out to be most important to satisfy the symmetry in a coarse-grained model. As the resolution is increased to capture more detail, however, it becomes gradually more important to match modular repeats in the secondary structure (such as helix-loop repeats) instead. A set of eight TMPs of various complexity, functionality, structural topology, and internal symmetry, representing different classes of TMPs (ion channels, transporters, receptors, adhesion, and invasion proteins), has been examined. The present approach can be generalized to other systems possessing exact or approximate symmetry, allowing for reliable and fast creation of multiscale, highly coarse-grained mappings of large biomolecular assemblies. PMID:28043122

Application Perspective of 2D+SCALE Dimension

NASA Astrophysics Data System (ADS)

Karim, H.; Rahman, A. Abdul

2016-09-01

Different applications or users need different abstraction of spatial models, dimensionalities and specification of their datasets due to variations of required analysis and output. Various approaches, data models and data structures are now available to support most current application models in Geographic Information System (GIS). One of the focuses trend in GIS multi-dimensional research community is the implementation of scale dimension with spatial datasets to suit various scale application needs. In this paper, 2D spatial datasets that been scaled up as the third dimension are addressed as 2D+scale (or 3D-scale) dimension. Nowadays, various data structures, data models, approaches, schemas, and formats have been proposed as the best approaches to support variety of applications and dimensionality in 3D topology. However, only a few of them considers the element of scale as their targeted dimension. As the scale dimension is concerned, the implementation approach can be either multi-scale or vario-scale (with any available data structures and formats) depending on application requirements (topology, semantic and function). This paper attempts to discuss on the current and new potential applications which positively could be integrated upon 3D-scale dimension approach. The previous and current works on scale dimension as well as the requirements to be preserved for any given applications, implementation issues and future potential applications forms the major discussion of this paper.

Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite while the effect on the axial properties is shown to be insignificant.

Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

Mechanical Properties of Graphene Nanoplatelet Carbon Fiber Epoxy Hybrid Composites: Multiscale Modeling and Experiments

NASA Technical Reports Server (NTRS)

Hadden, Cameron M.; Klimek-McDonald, Danielle R.; Pineda, Evan J.; King, Julie A.; Reichanadter, Alex M.; Miskioglu, Ibrahim; Gowtham, S.; Odegard, Gregory M.

2015-01-01

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

Adaptive Low Dissipative High Order Filter Methods for Multiscale MHD Flows

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sjoegreen, Bjoern

2004-01-01

Adaptive low-dissipative high order filter finite difference methods for long time wave propagation of shock/turbulence/combustion compressible viscous MHD flows has been constructed. Several variants of the filter approach that cater to different flow types are proposed. These filters provide a natural and efficient way for the minimization of the divergence of the magnetic field [divergence of B] numerical error in the sense that no standard divergence cleaning is required. For certain 2-D MHD test problems, divergence free preservation of the magnetic fields of these filter schemes has been achieved.

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth.

PubMed

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Z.; Bessa, M. A.; Liu, W.K.

A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical andmore » concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about 43,000 is achieved by using the SCA method, as opposed to FE2, enabling the solution of an otherwise computationally intractable problem. The second example uses a crystal plasticity constitutive law and computes the fatigue potency of extrinsic microscale features such as voids. This shows that local stress and strain are capture sufficiently well by SCA. This model has been incorporated in a process-structure-properties prediction framework for process design in additive manufacturing.« less

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

NASA Astrophysics Data System (ADS)

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Ground roll attenuation by synchrosqueezed curvelet transform

NASA Astrophysics Data System (ADS)

Liu, Zhao; Chen, Yangkang; Ma, Jianwei

2018-04-01

Ground roll is a type of coherent noise in land seismic data that has low frequency, low velocity and high amplitude. It damages reflection events that contain important information about subsurface structures, hence the removal of ground roll is a crucial step in seismic data processing. A suitable transform is needed for removal of ground roll. Curvelet transform is an effective sparse transform that optimally represents seismic events. In addition, the curvelets can provide a multiscale and multidirectional decomposition of the input data in time-frequency and angular domain, which can help distinguish between ground roll and useful signals. In this paper, we apply synchrosqueezed curvelet transform (SSCT) for ground roll attenuation. The synchrosqueezing technique in SSCT is used to precisely reallocate the energy of local wave vectors in order to separate ground roll from the original data with higher resolution and higher fidelity. Examples of synthetic and field seismic data reveal that SSCT performs well in the suppression of aliased and non-aliased ground roll while preserving reflection waves, in comparison with high-pass filtering, wavelet and curvelet methods.

Integration of ground-penetrating radar, ultrasonic tests and infrared thermography for the analysis of a precious medieval rose window

NASA Astrophysics Data System (ADS)

Nuzzo, L.; Calia, A.; Liberatore, D.; Masini, N.; Rizzo, E.

2010-04-01

The integration of high-resolution, non-invasive geophysical techniques (such as ground-penetrating radar or GPR) with emerging sensing techniques (acoustics, thermography) can complement limited destructive tests to provide a suitable methodology for a multi-scale assessment of the state of preservation, material and construction components of monuments. This paper presents the results of the application of GPR, infrared thermography (IRT) and ultrasonic tests to the 13th century rose window of Troia Cathedral (Apulia, Italy), affected by widespread decay and instability problems caused by the 1731 earthquake and reactivated by recent seismic activity. This integrated approach provided a wide amount of complementary information at different scales, ranging from the sub-centimetre size of the metallic joints between the various architectural elements, narrow fractures and thin mortar fillings, up to the sub-metre scale of the internal masonry structure of the circular ashlar curb linking the rose window to the façade, which was essential to understand the original building technique and to design an effective restoration strategy.

Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

NASA Astrophysics Data System (ADS)

Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

2010-04-01

Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a Critical Filtration Size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

NASA Astrophysics Data System (ADS)

Perrier, E. M. A.; Bird, N. R. A.; Rieutord, T. B.

2010-10-01

Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a critical filtration size (CFS) delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009). Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

Not All Larvae Stay Close to Home: Insights into Marine Population Connectivity with a Focus on the Brown Surgeonfish (Acanthurus nigrofuscus)

PubMed Central

Eble, Jeff A.; Rocha, Luiz A.; Craig, Matthew T.; Bowen, Brian W.

2014-01-01

Recent reports of localized larval recruitment in predominately small-range fishes are countered by studies that show high genetic connectivity across large oceanic distances. This discrepancy may result from the different timescales over which genetic and demographic processes operate or rather may indicate regular long-distance dispersal in some species. Here, we contribute an analysis of mtDNA cytochrome b diversity in the widely distributed Brown Surgeonfish (Acanthurus nigrofuscus; N = 560), which revealed significant genetic structure only at the extremes of the range (ΦCT = 0.452; P < .001). Collections from Hawaii to the Eastern Indian Ocean comprise one large, undifferentiated population. This pattern of limited genetic subdivision across reefs of the central Indo-Pacific has been observed in a number of large-range reef fishes. Conversely, small-range fishes are often deeply structured over the same area. These findings demonstrate population connectivity differences among species at biogeographic and evolutionary timescales, which likely translates into differences in dispersal ability at ecological and demographic timescales. While interspecific differences in population connectivity complicate the design of management strategies, the integration of multiscale connectivity patterns into marine resource planning will help ensure long-term ecosystem stability by preserving functionally diverse communities. PMID:25505914

Multi-Scale Analyses of Three Dimensional Woven Composite 3D Shell With a Cut Out Circle

NASA Astrophysics Data System (ADS)

Nguyen, Duc Hai; Wang, Hu

2018-06-01

A composite material are made by combining two or more constituent materials to obtain the desired material properties of each product type. The matrix material which can be polymer and fiber is used as reinforcing material. Currently, the polymer matrix is widely used in many different fields with differently designed structures such as automotive structures and aviation, aerospace, marine, etc. because of their excellent mechanical properties; in addition, they possess the high level of hardness and durability together with a significant reduction in weight compared to traditional materials. However, during design process of structure, there will be many interruptions created for the purpose of assembling the structures together or for many other design purposes. Therefore, when this structure is subject to load-bearing, its failure occurs at these interruptions due to stress concentration. This paper proposes multi-scale modeling and optimization strategies in evaluation of the effectiveness of fiber orientation in an E-glass/Epoxy woven composite 3D shell with circular holes at the center investigated by FEA results. A multi-scale model approach was developed to predict the mechanical behavior of woven composite 3D shell with circular holes at the center with different designs of material and structural parameters. Based on the analysis result of laminae, we have found that the 3D shell with fiber direction of 450 shows the best stress and strain bearing capacity. Thus combining several layers of 450 fiber direction in a multi-layer composite 3D shell reduces the stresses concentrated on the cuts of the structures.

Rippled Quasiperpendicular Shock Observed by the Magnetospheric Multiscale Spacecraft.

PubMed

Johlander, A; Schwartz, S J; Vaivads, A; Khotyaintsev, Yu V; Gingell, I; Peng, I B; Markidis, S; Lindqvist, P-A; Ergun, R E; Marklund, G T; Plaschke, F; Magnes, W; Strangeway, R J; Russell, C T; Wei, H; Torbert, R B; Paterson, W R; Gershman, D J; Dorelli, J C; Avanov, L A; Lavraud, B; Saito, Y; Giles, B L; Pollock, C J; Burch, J L

2016-10-14

Collisionless shock nonstationarity arising from microscale physics influences shock structure and particle acceleration mechanisms. Nonstationarity has been difficult to quantify due to the small spatial and temporal scales. We use the closely spaced (subgyroscale), high-time-resolution measurements from one rapid crossing of Earth's quasiperpendicular bow shock by the Magnetospheric Multiscale (MMS) spacecraft to compare competing nonstationarity processes. Using MMS's high-cadence kinetic plasma measurements, we show that the shock exhibits nonstationarity in the form of ripples.

Rippled Quasiperpendicular Shock Observed by the Magnetospheric Multiscale Spacecraft

NASA Technical Reports Server (NTRS)

Johlander, A.; Schwartz, S. J.; Vaivads, A.; Khotyaintsev, Yu. V.; Gingell, I.; Peng, I. B.; Markidis, S.; Lindqvist, P.-A.; Ergun, R. E.; Marklund, G. T.;

Advanced Aerospace Materials by Design

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Djomehri, Jahed; Wei, Chen-Yu

2004-01-01

The advances in the emerging field of nanophase thermal and structural composite materials; materials with embedded sensors and actuators for morphing structures; light-weight composite materials for energy and power storage; and large surface area materials for in-situ resource generation and waste recycling, are expected to :revolutionize the capabilities of virtually every system comprising of future robotic and :human moon and mars exploration missions. A high-performance multiscale simulation platform, including the computational capabilities and resources of Columbia - the new supercomputer, is being developed to discover, validate, and prototype next generation (of such advanced materials. This exhibit will describe the porting and scaling of multiscale 'physics based core computer simulation codes for discovering and designing carbon nanotube-polymer composite materials for light-weight load bearing structural and 'thermal protection applications.

Study of a brittle and precious medieval rose-window by means of the integration of GPR, stress wave tests and infrared thermography

NASA Astrophysics Data System (ADS)

Nuzzo, L.; Masini, N.; Rizzo, E.

2009-04-01

The correct management and restoration of architectural monuments of high cultural interest requires a comprehensive understanding of their status of preservation, the detection of the building features, the localization of damages and possibly the identification of their causes, nature and extent. To this aim, in recent times there is a growing interest on non-destructive and non-invasive geophysical methods as an invaluable tool for correlating spatially the information gained through destructive tests, which are restricted to a few locations of the investigated structure, and to optimize the choice of their position in order to minimize their impact on the monument structural stability. Moreover, the integration of the classical geophysical techniques with emerging surface and subsurface sensing techniques (acoustics, thermography) provides a suitable methodology for a multi-scale assessment of the monument state of preservation and its material and building components, which is vital for addressing maintenance and restoration issues. The present case study focuses on the application of Ground Penetrating Radar (GPR), infrared thermography (IRT), sonic and ultrasonic tests to analyze a 13th century precious rose window in Southern Italy, affected by widespread decay and instability problems. The Cathedral of Troia (Apulia, Italy) is the masterpiece of the Apulian Romanesque architecture. Its façade is adorned with an astonishing 6 m diameter rose window consisting of 11 twin columns, in various stone and reused marbles, connected to a central oculus and to a ring of trapezoidal elements decorated with arched ribworks. Between the twin columns there are 11 triangular carved panels with different and strongly symbolic geometrical patterns. According to visual inspection, mineralogical and petrographic studies, different materials have been used for the different architectural elements: fine grained limestone for the central oculus, medium-fine grained calcarenite for the carved panels and coarse grained calcarenite for the elements with arched ribworks. The various elements are supposedly joined together by iron bolts and melted lead, as exposed at the base of a damaged column. As a consequence of the 1731 earthquake, the upper part of the façade underwent rotational strains which induced severe out-of-plane deformation in the rose window and caused disconnection and rotation of the capitals, compression failures, cracks and detachments in various architectural elements. Despite the 19th century consolidation works, the progressing of strains caused by the recent seismic activity made necessary further structural rehabilitation to preserve the historical rose window. The geometrical and structural complexity of the monument and the multiplicity of issues to be addressed required an integrated approach using various Non-Destructive Testing (NDT) techniques to complement the laboratory analyses for the material characterization. Being based on different theoretical principles, the NDT techniques are sensitive to different physical parameters of the structure, which are in turn interpreted in terms of its engineering properties based on some calibrations or assumptions. Therefore, especially in case of monuments having exceptional artistic value or structural complexity, the integration of several methods becomes mandatory in order to compensate the limitations of each single method thus reducing interpretation ambiguities and the risk of failure in detecting structural defects. In our case the combination of GPR, IRT and sonic/ultrasonic tests was deemed the best strategy to obtain information on different physical parameter and to achieve different depths of penetration and resolution capabilities. A multi-scale integrated approach was necessary since the aspects to be investigated were themselves of different scales, ranging from the sub-centimeter size of small metallic joints, narrow fractures and thin mortar fillings up to the decimeter-meter scale of the masonry structure of the circular ashlar curb linking the rose window to the façade. This multi-technique NDT approach provided a wide amount of high-resolution complementary information on the internal and surface characteristics, materials, state of conservation and building techniques, which were essential for the design of an effective restoration strategy.

Glycoscience@Synchrotron: Synchrotron radiation applied to structural glycoscience

PubMed Central

de Sanctis, Daniele

2017-01-01

Synchrotron radiation is the most versatile way to explore biological materials in different states: monocrystalline, polycrystalline, solution, colloids and multiscale architectures. Steady improvements in instrumentation have made synchrotrons the most flexible intense X-ray source. The wide range of applications of synchrotron radiation is commensurate with the structural diversity and complexity of the molecules and macromolecules that form the collection of substrates investigated by glycoscience. The present review illustrates how synchrotron-based experiments have contributed to our understanding in the field of structural glycobiology. Structural characterization of protein–carbohydrate interactions of the families of most glycan-interacting proteins (including glycosyl transferases and hydrolases, lectins, antibodies and GAG-binding proteins) are presented. Examples concerned with glycolipids and colloids are also covered as well as some dealing with the structures and multiscale architectures of polysaccharides. Insights into the kinetics of catalytic events observed in the crystalline state are also presented as well as some aspects of structure determination of protein in solution. PMID:28684994

Structure-based multiscale approach for identification of interaction partners of PDZ domains.

PubMed

Tiwari, Garima; Mohanty, Debasisa

2014-04-28

PDZ domains are peptide recognition modules which mediate specific protein-protein interactions and are known to have a complex specificity landscape. We have developed a novel structure-based multiscale approach which identifies crucial specificity determining residues (SDRs) of PDZ domains from explicit solvent molecular dynamics (MD) simulations on PDZ-peptide complexes and uses these SDRs in combination with knowledge-based scoring functions for proteomewide identification of their interaction partners. Multiple explicit solvent simulations ranging from 5 to 50 ns duration have been carried out on 28 PDZ-peptide complexes with known binding affinities. MM/PBSA binding energy values calculated from these simulations show a correlation coefficient of 0.755 with the experimental binding affinities. On the basis of the SDRs of PDZ domains identified by MD simulations, we have developed a simple scoring scheme for evaluating binding energies for PDZ-peptide complexes using residue based statistical pair potentials. This multiscale approach has been benchmarked on a mouse PDZ proteome array data set by calculating the binding energies for 217 different substrate peptides in binding pockets of 64 different mouse PDZ domains. Receiver operating characteristic (ROC) curve analysis indicates that, the area under curve (AUC) values for binder vs nonbinder classification by our structure based method is 0.780. Our structure based method does not require experimental PDZ-peptide binding data for training.

Multiscale modeling of three-dimensional genome

NASA Astrophysics Data System (ADS)

Zhang, Bin; Wolynes, Peter

The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

Multiscale polar theory of microtubule and motor-protein assemblies

DOE PAGES

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; ...

2015-01-27

Microtubules and motor proteins are building blocks of self-organized subcellular biological structures such as the mitotic spindle and the centrosomal microtubule array. These same ingredients can form new “bioactive” liquid-crystalline fluids that are intrinsically out of equilibrium and which display complex flows and defect dynamics. It is not yet well understood how microscopic activity, which involves polarity-dependent interactions between motor proteins and microtubules, yields such larger-scale dynamical structures. In our multiscale theory, Brownian dynamics simulations of polar microtubule ensembles driven by cross-linking motors allow us to study microscopic organization and stresses. Polarity sorting and cross-link relaxation emerge as two polar-specificmore » sources of active destabilizing stress. On larger length scales, our continuum Doi-Onsager theory captures the hydrodynamic flows generated by polarity-dependent active stresses. Finally, the results connect local polar structure to flow structures and defect dynamics.« less

The Structure of Borders in a Small World

PubMed Central

Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk

2010-01-01

Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity. PMID:21124970

The structure of borders in a small world.

PubMed

Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk

2010-11-18

Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity.

A Multiscale Model for the Quasi-Static Thermo-Plastic Behavior of Highly Cross-Linked Glassy Polymers

DOE PAGES

Vu-Bac, N.; Bessa, M. A.; Rabczuk, Timon; ...

2015-09-10

In this paper, we present experimentally validated molecular dynamics predictions of the quasi- static yield and post-yield behavior for a highly cross-linked epoxy polymer under gen- eral stress states and for different temperatures. In addition, a hierarchical multiscale model is presented where the nano-scale simulations obtained from molecular dynamics were homogenized to a continuum thermoplastic constitutive model for the epoxy that can be used to describe the macroscopic behavior of the material. Three major conclusions were achieved: (1) the yield surfaces generated from the nano-scale model for different temperatures agree well with the paraboloid yield crite- rion, supporting previous macroscopicmore » experimental observations; (2) rescaling of the entire yield surfaces to the quasi-static case is possible by considering Argon’s theoretical predictions for pure compression of the polymer at absolute zero temperature; (3) nano- scale simulations can be used for an experimentally-free calibration of macroscopic con- tinuum models, opening new avenues for the design of materials and structures through multi-scale simulations that provide structure-property-performance relationships.« less

Micromechanics-Based Structural Analysis (FEAMAC) and Multiscale Visualization within Abaqus/CAE Environment

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Bednarcyk, Brett A.; Hussain, Aquila; Katiyar, Vivek

2010-01-01

A unified framework is presented that enables coupled multiscale analysis of composite structures and associated graphical pre- and postprocessing within the Abaqus/CAE environment. The recently developed, free, Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software couples NASA's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with Abaqus/Standard and Abaqus/Explicit to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. The Graphical User Interfaces (FEAMAC-Pre and FEAMAC-Post), developed through collaboration between SIMULIA Erie and the NASA Glenn Research Center, enable users to employ a new FEAMAC module within Abaqus/CAE that provides access to the composite microscale. FEA IAC-Pre is used to define and store constituent material properties, set-up and store composite repeating unit cells, and assign composite materials as sections with all data being stored within the CAE database. Likewise FEAMAC-Post enables multiscale field quantity visualization (contour plots, X-Y plots), with point and click access to the microscale i.e., fiber and matrix fields).

Towards the design of 3D multiscale instructive tissue engineering constructs: Current approaches and trends.

PubMed

Oliveira, Sara M; Reis, Rui L; Mano, João F

2015-11-01

The design of 3D constructs with adequate properties to instruct and guide cells both in vitro and in vivo is one of the major focuses of tissue engineering. Successful tissue regeneration depends on the favorable crosstalk between the supporting structure, the cells and the host tissue so that a balanced matrix production and degradation are achieved. Herein, the major occurring events and players in normal and regenerative tissue are overviewed. These have been inspiring the selection or synthesis of instructive cues to include into the 3D constructs. We further highlight the importance of a multiscale perception of the range of features that can be included on the biomimetic structures. Lastly, we focus on the current and developing tissue-engineering approaches for the preparation of such 3D constructs: top-down, bottom-up and integrative. Bottom-up and integrative approaches present a higher potential for the design of tissue engineering devices with multiscale features and higher biochemical control than top-down strategies, and are the main focus of this review. Copyright © 2015 Elsevier Inc. All rights reserved.

Investigating lithium-ion battery materials during overcharge-induced thermal runaway: an operando and multi-scale X-ray CT study.

PubMed

Finegan, Donal P; Scheel, Mario; Robinson, James B; Tjaden, Bernhard; Di Michiel, Marco; Hinds, Gareth; Brett, Dan J L; Shearing, Paul R

2016-11-16

Catastrophic failure of lithium-ion batteries occurs across multiple length scales and over very short time periods. A combination of high-speed operando tomography, thermal imaging and electrochemical measurements is used to probe the degradation mechanisms leading up to overcharge-induced thermal runaway of a LiCoO 2 pouch cell, through its interrelated dynamic structural, thermal and electrical responses. Failure mechanisms across multiple length scales are explored using a post-mortem multi-scale tomography approach, revealing significant morphological and phase changes in the LiCoO 2 electrode microstructure and location dependent degradation. This combined operando and multi-scale X-ray computed tomography (CT) technique is demonstrated as a comprehensive approach to understanding battery degradation and failure.

Simulating and mapping spatial complexity using multi-scale techniques

USGS Publications Warehouse

De Cola, L.

1994-01-01

A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ortoleva, Peter J.

Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.

Modeling Impact-induced Failure of Polysilicon MEMS: A Multi-scale Approach.

PubMed

Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Zerbini, Sarah

2009-01-01

Failure of packaged polysilicon micro-electro-mechanical systems (MEMS) subjected to impacts involves phenomena occurring at several length-scales. In this paper we present a multi-scale finite element approach to properly allow for: (i) the propagation of stress waves inside the package; (ii) the dynamics of the whole MEMS; (iii) the spreading of micro-cracking in the failing part(s) of the sensor. Through Monte Carlo simulations, some effects of polysilicon micro-structure on the failure mode are elucidated.

Multiscale Genetic Structure of Yellowstone Cutthroat Trout in the Upper Snake River Basin.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cegelski, Christine C.; Campbell, Matthew R.

2006-05-30

Populations of Yellowstone cutthroat trout Oncorhynchus clarkii bouvierii have declined throughout their native range as a result of habitat fragmentation, overharvest, and introductions of nonnative trout that have hybridized with or displaced native populations. The degree to which these factors have impacted the current genetic population structure of Yellowstone cutthroat trout populations is of primary interest for their conservation. In this study, we examined the genetic diversity and genetic population structure of Yellowstone cutthroat trout in Idaho and Nevada with data from six polymorphic microsatellite loci. A total of 1,392 samples were analyzed from 45 sample locations throughout 11 majormore » river drainages. We found that levels of genetic diversity and genetic differentiation varied extensively. The Salt River drainage, which is representative of the least impacted migration corridors in Idaho, had the highest levels of genetic diversity and low levels of genetic differentiation. High levels of genetic differentiation were observed at similar or smaller geographic scales in the Portneuf River, Raft River, and Teton River drainages, which are more altered by anthropogenic disturbances. Results suggested that Yellowstone cutthroat trout are naturally structured at the major river drainage level but that habitat fragmentation has altered this structuring. Connectivity should be restored via habitat restoration whenever possible to minimize losses in genetic diversity and to preserve historical processes of gene flow, life history variation, and metapopulation dynamics. However, alternative strategies for management and conservation should also be considered in areas where there is a strong likelihood of nonnative invasions or extensive habitat fragmentation that cannot be easily ameliorated.« less

Prediction of water loss and viscoelastic deformation of apple tissue using a multiscale model.

PubMed

Aregawi, Wondwosen A; Abera, Metadel K; Fanta, Solomon W; Verboven, Pieter; Nicolai, Bart

2014-11-19

A two-dimensional multiscale water transport and mechanical model was developed to predict the water loss and deformation of apple tissue (Malus × domestica Borkh. cv. 'Jonagold') during dehydration. At the macroscopic level, a continuum approach was used to construct a coupled water transport and mechanical model. Water transport in the tissue was simulated using a phenomenological approach using Fick's second law of diffusion. Mechanical deformation due to shrinkage was based on a structural mechanics model consisting of two parts: Yeoh strain energy functions to account for non-linearity and Maxwell's rheological model of visco-elasticity. Apparent parameters of the macroscale model were computed from a microscale model. The latter accounted for water exchange between different microscopic structures of the tissue (intercellular space, the cell wall network and cytoplasm) using transport laws with the water potential as the driving force for water exchange between different compartments of tissue. The microscale deformation mechanics were computed using a model where the cells were represented as a closed thin walled structure. The predicted apparent water transport properties of apple cortex tissue from the microscale model showed good agreement with the experimentally measured values. Deviations between calculated and measured mechanical properties of apple tissue were observed at strains larger than 3%, and were attributed to differences in water transport behavior between the experimental compression tests and the simulated dehydration-deformation behavior. Tissue dehydration and deformation in the high relative humidity range ( > 97% RH) could, however, be accurately predicted by the multiscale model. The multiscale model helped to understand the dynamics of the dehydration process and the importance of the different microstructural compartments (intercellular space, cell wall, membrane and cytoplasm) for water transport and mechanical deformation.

Multi-scale structures of turbulent magnetic reconnection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakamura, T. K. M., E-mail: takuma.nakamura@oeaw.ac.at; Nakamura, R.; Narita, Y.

2016-05-15

We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in whichmore » modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.« less

Multi-scale structures of turbulent magnetic reconnection

NASA Astrophysics Data System (ADS)

Nakamura, T. K. M.; Nakamura, R.; Narita, Y.; Baumjohann, W.; Daughton, W.

2016-05-01

We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in which modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.

Low-Frequency Oscillations and Transport Processes Induced by Multiscale Transverse Structures in the Polar Wind Outflow: A Three-Dimensional Simulation

NASA Technical Reports Server (NTRS)

Ganguli, Supriya B.; Gavrishchaka, Valeriy V.

1999-01-01

Multiscale transverse structures in the magnetic-field-aligned flows have been frequently observed in the auroral region by FAST and Freja satellites. A number of multiscale processes, such as broadband low-frequency oscillations and various cross-field transport effects are well correlated with these structures. To study these effects, we have used our three-dimensional multifluid model with multiscale transverse inhomogeneities in the initial velocity profile. Self-consistent-frequency mode driven by local transverse gradients in the generation of the low field-aligned ion flow and associated transport processes were simulated. Effects of particle interaction with the self-consistent time-dependent three-dimensional wave potential have been modeled using a distribution of test particles. For typical polar wind conditions it has been found that even large-scale (approximately 50 - 100 km) transverse inhomogeneities in the flow can generate low-frequency oscillations that lead to significant flow modifications, cross-field particle diffusion, and other transport effects. It has also been shown that even small-amplitude (approximately 10 - 20%) short-scale (approximately 10 km) modulations of the original large-scale flow profile significantly increases low-frequency mode generation and associated cross-field transport, not only at the local spatial scales imposed by the modulations but also on global scales. Note that this wave-induced cross-field transport is not included in any of the global numerical models of the ionosphere, ionosphere-thermosphere, or ionosphere-polar wind. The simulation results indicate that the wave-induced cross-field transport not only affects the ion outflow rates but also leads to a significant broadening of particle phase-space distribution and transverse particle diffusion.

Multiscale sensorless adaptive optics OCT angiography system for in vivo human retinal imaging.

PubMed

Ju, Myeong Jin; Heisler, Morgan; Wahl, Daniel; Jian, Yifan; Sarunic, Marinko V

2017-11-01

We present a multiscale sensorless adaptive optics (SAO) OCT system capable of imaging retinal structure and vasculature with various fields-of-view (FOV) and resolutions. Using a single deformable mirror and exploiting the polarization properties of light, the SAO-OCT-A was implemented in a compact and easy to operate system. With the ability to adjust the beam diameter at the pupil, retinal imaging was demonstrated at two different numerical apertures with the same system. The general morphological structure and retinal vasculature could be observed with a few tens of micrometer-scale lateral resolution with conventional OCT and OCT-A scanning protocols with a 1.7-mm-diameter beam incident at the pupil and a large FOV (15 deg× 15 deg). Changing the system to a higher numerical aperture with a 5.0-mm-diameter beam incident at the pupil and the SAO aberration correction, the FOV was reduced to 3 deg× 3 deg for fine detailed imaging of morphological structure and microvasculature such as the photoreceptor mosaic and capillaries. Multiscale functional SAO-OCT imaging was performed on four healthy subjects, demonstrating its functionality and potential for clinical utility. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Dynamics of a neural system with a multiscale architecture

PubMed Central

Breakspear, Michael; Stam, Cornelis J

2005-01-01

The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448

Bioaccessibility of nutrients and micronutrients from dispersed food systems: impact of the multiscale bulk and interfacial structures.

PubMed

Marze, Sébastien

2013-01-01

Many food systems are dispersed systems, that is, they possess at least two immiscible phases. This is generally due to the coexistence of domains with different physicochemical properties separated by many interfaces which control the apparent thermodynamic equilibrium. This feature was and is still largely studied to design pharmaceutical delivery systems. In food science, the recent intensification of in vitro digestion tests to complement the in vivo ones holds promises in the identification of the key parameters controlling the bioaccessibility of nutrients and micronutrients. In this review, we present the developments of in vitro digestion tests for dispersed food systems (mainly emulsions, dispersions and gels). We especially highlight the evidences detailing the roles of the constituting multiscale structures. In a perspective section, we show the potential of structured interfaces to allow controlled bioaccessibility.

Application of the multi-scale finite element method to wave propagation problems in damaged structures

NASA Astrophysics Data System (ADS)

Casadei, F.; Ruzzene, M.

2011-04-01

This work illustrates the possibility to extend the field of application of the Multi-Scale Finite Element Method (MsFEM) to structural mechanics problems that involve localized geometrical discontinuities like cracks or notches. The main idea is to construct finite elements with an arbitrary number of edge nodes that describe the actual geometry of the damage with shape functions that are defined as local solutions of the differential operator of the specific problem according to the MsFEM approach. The small scale information are then brought to the large scale model through the coupling of the global system matrices that are assembled using classical finite element procedures. The efficiency of the method is demonstrated through selected numerical examples that constitute classical problems of great interest to the structural health monitoring community.

Computational Modeling of Airway and Pulmonary Vascular Structure and Function: Development of a “Lung Physiome”

PubMed Central

Tawhai, M. H.; Clark, A. R.; Donovan, G. M.; Burrowes, K. S.

2011-01-01

Computational models of lung structure and function necessarily span multiple spatial and temporal scales, i.e., dynamic molecular interactions give rise to whole organ function, and the link between these scales cannot be fully understood if only molecular or organ-level function is considered. Here, we review progress in constructing multiscale finite element models of lung structure and function that are aimed at providing a computational framework for bridging the spatial scales from molecular to whole organ. These include structural models of the intact lung, embedded models of the pulmonary airways that couple to model lung tissue, and models of the pulmonary vasculature that account for distinct structural differences at the extra- and intra-acinar levels. Biophysically based functional models for tissue deformation, pulmonary blood flow, and airway bronchoconstriction are also described. The development of these advanced multiscale models has led to a better understanding of complex physiological mechanisms that govern regional lung perfusion and emergent heterogeneity during bronchoconstriction. PMID:22011236

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

Multiplexed and scalable super-resolution imaging of three-dimensional protein localization in size-adjustable tissues.

PubMed

Ku, Taeyun; Swaney, Justin; Park, Jeong-Yoon; Albanese, Alexandre; Murray, Evan; Cho, Jae Hun; Park, Young-Gyun; Mangena, Vamsi; Chen, Jiapei; Chung, Kwanghun

2016-09-01

The biology of multicellular organisms is coordinated across multiple size scales, from the subnanoscale of molecules to the macroscale, tissue-wide interconnectivity of cell populations. Here we introduce a method for super-resolution imaging of the multiscale organization of intact tissues. The method, called magnified analysis of the proteome (MAP), linearly expands entire organs fourfold while preserving their overall architecture and three-dimensional proteome organization. MAP is based on the observation that preventing crosslinking within and between endogenous proteins during hydrogel-tissue hybridization allows for natural expansion upon protein denaturation and dissociation. The expanded tissue preserves its protein content, its fine subcellular details, and its organ-scale intercellular connectivity. We use off-the-shelf antibodies for multiple rounds of immunolabeling and imaging of a tissue's magnified proteome, and our experiments demonstrate a success rate of 82% (100/122 antibodies tested). We show that specimen size can be reversibly modulated to image both inter-regional connections and fine synaptic architectures in the mouse brain.

Integration of High-Resolution Laser Displacement Sensors and 3D Printing for Structural Health Monitoring

PubMed Central

Chang, Shu-Wei; Kuo, Shih-Yu; Huang, Ting-Hsuan

2017-01-01

This paper presents a novel experimental design for complex structural health monitoring (SHM) studies achieved by integrating 3D printing technologies, high-resolution laser displacement sensors, and multiscale entropy SHM theory. A seven-story structure with a variety of composite bracing systems was constructed using a dual-material 3D printer. A wireless Bluetooth vibration speaker was used to excite the ground floor of the structure, and high-resolution laser displacement sensors (1-μm resolution) were used to monitor the displacement history on different floors. Our results showed that the multiscale entropy SHM method could detect damage on the 3D-printed structures. The results of this study demonstrate that integrating 3D printing technologies and high-resolution laser displacement sensors enables the design of cheap, fast processing, complex, small-scale civil structures for future SHM studies. The novel experimental design proposed in this study provides a suitable platform for investigating the validity and sensitivity of SHM in different composite structures and damage conditions for real life applications in the future. PMID:29271937

Integration of High-Resolution Laser Displacement Sensors and 3D Printing for Structural Health Monitoring.

PubMed

Chang, Shu-Wei; Lin, Tzu-Kang; Kuo, Shih-Yu; Huang, Ting-Hsuan

2017-12-22

This paper presents a novel experimental design for complex structural health monitoring (SHM) studies achieved by integrating 3D printing technologies, high-resolution laser displacement sensors, and multiscale entropy SHM theory. A seven-story structure with a variety of composite bracing systems was constructed using a dual-material 3D printer. A wireless Bluetooth vibration speaker was used to excite the ground floor of the structure, and high-resolution laser displacement sensors (1-μm resolution) were used to monitor the displacement history on different floors. Our results showed that the multiscale entropy SHM method could detect damage on the 3D-printed structures. The results of this study demonstrate that integrating 3D printing technologies and high-resolution laser displacement sensors enables the design of cheap, fast processing, complex, small-scale civil structures for future SHM studies. The novel experimental design proposed in this study provides a suitable platform for investigating the validity and sensitivity of SHM in different composite structures and damage conditions for real life applications in the future.

A Multi-Scale, Multi-Physics Optimization Framework for Additively Manufactured Structural Components

NASA Astrophysics Data System (ADS)

El-Wardany, Tahany; Lynch, Mathew; Gu, Wenjiong; Hsu, Arthur; Klecka, Michael; Nardi, Aaron; Viens, Daniel

This paper proposes an optimization framework enabling the integration of multi-scale / multi-physics simulation codes to perform structural optimization design for additively manufactured components. Cold spray was selected as the additive manufacturing (AM) process and its constraints were identified and included in the optimization scheme. The developed framework first utilizes topology optimization to maximize stiffness for conceptual design. The subsequent step applies shape optimization to refine the design for stress-life fatigue. The component weight was reduced by 20% while stresses were reduced by 75% and the rigidity was improved by 37%. The framework and analysis codes were implemented using Altair software as well as an in-house loading code. The optimized design was subsequently produced by the cold spray process.

Nonlinear helicons bearing multi-scale structures

NASA Astrophysics Data System (ADS)

Abdelhamid, Hamdi M.; Yoshida, Zensho

2017-02-01

The helicon waves exhibit varying characters depending on plasma parameters, geometry, and wave numbers. Here, we elucidate an intrinsic multi-scale property embodied by the combination of the dispersive effect and nonlinearity. The extended magnetohydrodynamics model (exMHD) is capable of describing a wide range of parameter space. By using the underlying Hamiltonian structure of exMHD, we construct an exact nonlinear solution, which turns out to be a combination of two distinct modes, the helicon and Trivelpiece-Gould (TG) waves. In the regime of relatively low frequency or high density, however, the combination is made of the TG mode and an ion cyclotron wave (slow wave). The energy partition between these modes is determined by the helicities carried by the wave fields.

Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Zhang, Hong; Gao, You

2017-01-01

Identifying the mutual interaction in aero-engine gas path system is a crucial problem that facilitates the understanding of emerging structures in complex system. By employing the multiscale multifractal detrended cross-correlation analysis method to aero-engine gas path system, the cross-correlation characteristics between gas path system parameters are established. Further, we apply multiscale multifractal detrended cross-correlation distance matrix and minimum spanning tree to investigate the mutual interactions of gas path variables. The results can infer that the low-spool rotor speed (N1) and engine pressure ratio (EPR) are main gas path parameters. The application of proposed method contributes to promote our understanding of the internal mechanisms and structures of aero-engine dynamics.

Multiscale modeling and distributed computing to predict cosmesis outcome after a lumpectomy

NASA Astrophysics Data System (ADS)

Garbey, M.; Salmon, R.; Thanoon, D.; Bass, B. L.

2013-07-01

Surgery for early stage breast carcinoma is either total mastectomy (complete breast removal) or surgical lumpectomy (only tumor removal). The lumpectomy or partial mastectomy is intended to preserve a breast that satisfies the woman's cosmetic, emotional and physical needs. But in a fairly large number of cases the cosmetic outcome is not satisfactory. Today, predicting that surgery outcome is essentially based on heuristic. Modeling such a complex process must encompass multiple scales, in space from cells to tissue, as well as in time, from minutes for the tissue mechanics to months for healing. The goal of this paper is to present a first step in multiscale modeling of the long time scale prediction of breast shape after tumor resection. This task requires coupling very different mechanical and biological models with very different computing needs. We provide a simple illustration of the application of heterogeneous distributed computing and modular software design to speed up the model development. Our computational framework serves currently to test hypothesis on breast tissue healing in a pilot study with women who have been elected to undergo BCT and are being treated at the Methodist Hospital in Houston, TX.

Individual-specific multi-scale finite element simulation of cortical bone of human proximal femur

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ascenzi, Maria-Grazia, E-mail: mgascenzi@mednet.ucla.edu; Kawas, Neal P., E-mail: nealkawas@ucla.edu; Lutz, Andre, E-mail: andre.lutz@hotmail.de

2013-07-01

We present an innovative method to perform multi-scale finite element analyses of the cortical component of the femur using the individual’s (1) computed tomography scan; and (2) a bone specimen obtained in conjunction with orthopedic surgery. The method enables study of micro-structural characteristics regulating strains and stresses under physiological loading conditions. The analysis of the micro-structural scenarios that cause variation of strain and stress is the first step in understanding the elevated strains and stresses in bone tissue, which are indicative of higher likelihood of micro-crack formation in bone, implicated in consequent remodeling or macroscopic bone fracture. Evidence that micro-structuremore » varies with clinical history and contributes in significant, but poorly understood, ways to bone function, motivates the method’s development, as does need for software tools to investigate relationships between macroscopic loading and micro-structure. Three applications – varying region of interest, bone mineral density, and orientation of collagen type I, illustrate the method. We show, in comparison between physiological loading and simple compression of a patient’s femur, that strains computed at the multi-scale model’s micro-level: (i) differ; and (ii) depend on local collagen-apatite orientation and degree of calcification. Our findings confirm the strain concentration role of osteocyte lacunae, important for mechano-transduction. We hypothesize occurrence of micro-crack formation, leading either to remodeling or macroscopic fracture, when the computed strains exceed the elastic range observed in micro-structural testing.« less

Multiscale Analysis of Open-Cell Aluminum Foam for Impact Energy Absorption

NASA Astrophysics Data System (ADS)

Kim, Ji Hoon; Kim, Daeyong; Lee, Myoung-Gyu; Lee, Jong Kook

2016-09-01

The energy-absorbing characteristics of crash members in automotive collision play an important role in controlling the amount of damage to the passenger compartment. Aluminum foams have high strength-to-weight ratio and high deformability, thus good crashworthiness is expected while maintaining or even saving weights when foams are implemented in crash members. In order to investigate the effect of the open-cell aluminum foam fillers on impact performance and weight saving, a multiscale framework for evaluating the crashworthiness of aluminum foam-filled members is used. To circumvent the difficulties of mechanical tests on foams, a micromechanical model of the aluminum foam is constructed using the x-ray micro tomography and virtual tests are conducted for the micromechanical model to characterize the behavior of the foam. In the macroscale, the aluminum foam is represented by the crushable foam constitutive model, which is then incorporated into the impact test simulation of the foam-filled crash member. The multiscale foam-filled crash member model was validated for the high-speed impact test, which confirms that the material model characterized by the micromechanical approach represents the behavior of the open-cell foam under impact loading well. Finally, the crash member design for maximizing the energy absorption is discussed by investigating various designs from the foam-only structure to the hollow tube structure. It was found that the foam structure absorbs more energy than the hollow tube or foam-filled structure with the same weight.

The upside-down water collection system of Syntrichia caninervis.

PubMed

Pan, Zhao; Pitt, William G; Zhang, Yuanming; Wu, Nan; Tao, Ye; Truscott, Tadd T

2016-06-06

Desert plants possess highly evolved water conservation and transport systems, from the root structures that maximize absorption of scarce ground water(1-5), to the minimization of leaf surface area(6) to enhance water retention. Recent attention has focused on leaf structures that are adapted to collect water and promote nucleation from humid air(7-9). Syntrichia caninervis Mitt. (Pottiaceae) is one of the most abundant desert mosses in the world and thrives in an extreme environment with multiple but limited water resources (such as dew, fog, snow and rain), yet the mechanisms for water collection and transport have never been completely revealed. S. caninervis has a unique adaptation: it uses a tiny hair (awn) on the end of each leaf to collect water, in addition to that collected by the leaves themselves. Here we show that the unique multiscale structures of the hair are equipped to collect and transport water in four modes: nucleation of water droplets and films on the leaf hair from humid atmospheres; collection of fog droplets on leaf hairs; collection of splash water from raindrops; and transportation of the acquired water to the leaf itself. Fluid nucleation is accomplished in nanostructures, whereas fog droplets are gathered in areas where a high density of small barbs are present and then quickly transported to the leaf at the base of the hair. Our observations reveal nature's optimization of water collection by coupling relevant multiscale physical plant structures with multiscale sources of water.

Simulated shift work in rats perturbs multiscale regulation of locomotor activity

PubMed Central

Hsieh, Wan-Hsin; Escobar, Carolina; Yugay, Tatiana; Lo, Men-Tzung; Pittman-Polletta, Benjamin; Salgado-Delgado, Roberto; Scheer, Frank A. J. L.; Shea, Steven A.; Buijs, Ruud M.; Hu, Kun

2014-01-01

Motor activity possesses a multiscale regulation that is characterized by fractal activity fluctuations with similar structure across a wide range of timescales spanning minutes to hours. Fractal activity patterns are disturbed in animals after ablating the master circadian pacemaker (suprachiasmatic nucleus, SCN) and in humans with SCN dysfunction as occurs with aging and in dementia, suggesting the crucial role of the circadian system in the multiscale activity regulation. We hypothesized that the normal synchronization between behavioural cycles and the SCN-generated circadian rhythms is required for multiscale activity regulation. To test the hypothesis, we studied activity fluctuations of rats in a simulated shift work protocol that was designed to force animals to be active during the habitual resting phase of the circadian/daily cycle. We found that these animals had gradually decreased mean activity level and reduced 24-h activity rhythm amplitude, indicating disturbed circadian and behavioural cycles. Moreover, these animals had disrupted fractal activity patterns as characterized by more random activity fluctuations at multiple timescales from 4 to 12 h. Intriguingly, these activity disturbances exacerbated when the shift work schedule lasted longer and persisted even in the normal days (without forced activity) following the shift work. The disrupted circadian and fractal patterns resemble those of SCN-lesioned animals and of human patients with dementia, suggesting a detrimental impact of shift work on multiscale activity regulation. PMID:24829282

Multi-Scale Morphological Analysis of Conductance Signals in Vertical Upward Gas-Liquid Two-Phase Flow

NASA Astrophysics Data System (ADS)

Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying

2016-11-01

The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

NASA Astrophysics Data System (ADS)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

Multi-scale statistical analysis of coronal solar activity

DOE PAGES

Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.

2016-07-08

Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.

3D hierarchical geometric modeling and multiscale FE analysis as a base for individualized medical diagnosis of bone structure.

PubMed

Podshivalov, L; Fischer, A; Bar-Yoseph, P Z

2011-04-01

This paper describes a new alternative for individualized mechanical analysis of bone trabecular structure. This new method closes the gap between the classic homogenization approach that is applied to macro-scale models and the modern micro-finite element method that is applied directly to micro-scale high-resolution models. The method is based on multiresolution geometrical modeling that generates intermediate structural levels. A new method for estimating multiscale material properties has also been developed to facilitate reliable and efficient mechanical analysis. What makes this method unique is that it enables direct and interactive analysis of the model at every intermediate level. Such flexibility is of principal importance in the analysis of trabecular porous structure. The method enables physicians to zoom-in dynamically and focus on the volume of interest (VOI), thus paving the way for a large class of investigations into the mechanical behavior of bone structure. This is one of the very few methods in the field of computational bio-mechanics that applies mechanical analysis adaptively on large-scale high resolution models. The proposed computational multiscale FE method can serve as an infrastructure for a future comprehensive computerized system for diagnosis of bone structures. The aim of such a system is to assist physicians in diagnosis, prognosis, drug treatment simulation and monitoring. Such a system can provide a better understanding of the disease, and hence benefit patients by providing better and more individualized treatment and high quality healthcare. In this paper, we demonstrate the feasibility of our method on a high-resolution model of vertebra L3. Copyright © 2010 Elsevier Inc. All rights reserved.

Image-based multiscale mechanical modeling shows the importance of structural heterogeneity in the human lumbar facet capsular ligament.

PubMed

Zarei, Vahhab; Liu, Chao J; Claeson, Amy A; Akkin, Taner; Barocas, Victor H

2017-08-01

The lumbar facet capsular ligament (FCL) primarily consists of aligned type I collagen fibers that are mainly oriented across the joint. The aim of this study was to characterize and incorporate in-plane local fiber structure into a multiscale finite element model to predict the mechanical response of the FCL during in vitro mechanical tests, accounting for the heterogeneity in different scales. Characterization was accomplished by using entire-domain polarization-sensitive optical coherence tomography to measure the fiber structure of cadaveric lumbar FCLs ([Formula: see text]). Our imaging results showed that fibers in the lumbar FCL have a highly heterogeneous distribution and are neither isotropic nor completely aligned. The averaged fiber orientation was [Formula: see text] ([Formula: see text] in the inferior region and [Formula: see text] in the middle and superior regions), with respect to lateral-medial direction (superior-medial to inferior-lateral). These imaging data were used to construct heterogeneous structural models, which were then used to predict experimental gross force-strain behavior and the strain distribution during equibiaxial and strip biaxial tests. For equibiaxial loading, the structural model fit the experimental data well but underestimated the lateral-medial forces by [Formula: see text]16% on average. We also observed pronounced heterogeneity in the strain field, with stretch ratios for different elements along the lateral-medial axis of sample typically ranging from about 0.95 to 1.25 during a 12% strip biaxial stretch in the lateral-medial direction. This work highlights the multiscale structural and mechanical heterogeneity of the lumbar FCL, which is significant both in terms of injury prediction and microstructural constituents' (e.g., neurons) behavior.

Dark-field X-ray microscopy for multiscale structural characterization

NASA Astrophysics Data System (ADS)

Simons, H.; King, A.; Ludwig, W.; Detlefs, C.; Pantleon, W.; Schmidt, S.; Snigireva, I.; Snigirev, A.; Poulsen, H. F.

2015-01-01

Many physical and mechanical properties of crystalline materials depend strongly on their internal structure, which is typically organized into grains and domains on several length scales. Here we present dark-field X-ray microscopy; a non-destructive microscopy technique for the three-dimensional mapping of orientations and stresses on lengths scales from 100 nm to 1 mm within embedded sampling volumes. The technique, which allows ‘zooming’ in and out in both direct and angular space, is demonstrated by an annealing study of plastically deformed aluminium. Facilitating the direct study of the interactions between crystalline elements is a key step towards the formulation and validation of multiscale models that account for the entire heterogeneity of a material. Furthermore, dark-field X-ray microscopy is well suited to applied topics, where the structural evolution of internal nanoscale elements (for example, positioned at interfaces) is crucial to the performance and lifetime of macro-scale devices and components thereof.

A multiscale cerebral neurochemical connectome of the rat brain

PubMed Central

Schöttler, Judith; Ercsey-Ravasz, Maria; Cosa-Linan, Alejandro; Varga, Melinda; Toroczkai, Zoltan; Spanagel, Rainer

2017-01-01

Understanding the rat neurochemical connectome is fundamental for exploring neuronal information processing. By using advanced data mining, supervised machine learning, and network analysis, this study integrates over 5 decades of neuroanatomical investigations into a multiscale, multilayer neurochemical connectome of the rat brain. This neurochemical connectivity database (ChemNetDB) is supported by comprehensive systematically-determined receptor distribution maps. The rat connectome has an onion-type structural organization and shares a number of structural features with mesoscale connectomes of mouse and macaque. Furthermore, we demonstrate that extremal values of graph theoretical measures (e.g., degree and betweenness) are associated with evolutionary-conserved deep brain structures such as amygdala, bed nucleus of the stria terminalis, dorsal raphe, and lateral hypothalamus, which regulate primitive, yet fundamental functions, such as circadian rhythms, reward, aggression, anxiety, and fear. The ChemNetDB is a freely available resource for systems analysis of motor, sensory, emotional, and cognitive information processing. PMID:28671956

Progressive transmission of road network

NASA Astrophysics Data System (ADS)

Ai, Bo; Ai, Tinghua; Tang, Xinming; Li, Zhen

2009-10-01

The progressive transmission of vector map data requires efficient multi-scale data model to process the data into hierarchical structure. This paper presents such a data structure of road network without redundancy of geometry for progressive transmission. For a given scale, the road network display has to settle two questions. One is which road objects to be represented and the other is what geometric details to be visualized for the selected roads. This paper combines the Töpfer law and the BLG-tree structure into a multi-scale representation matrix to answer simultaneously the above two questions. In the matrix, rows from top to bottom represent the roads in the sequence of descending classification of traffic and length, which can support the Töpfer law to retrieve the more important roads. In a row, columns record one road by a linear BLG-tree to provide good line graphics.

Hierarchical multiscale hyperporous block copolymer membranes via tunable dual-phase separation

PubMed Central

Yoo, Seungmin; Kim, Jung-Hwan; Shin, Myoungsoo; Park, Hyungmin; Kim, Jeong-Hoon; Lee, Sang-Young; Park, Soojin

2015-01-01

The rational design and realization of revolutionary porous structures have been long-standing challenges in membrane science. We demonstrate a new class of amphiphilic polystyrene-block-poly(4-vinylpyridine) block copolymer (BCP)–based porous membranes featuring hierarchical multiscale hyperporous structures. The introduction of surface energy–modifying agents and the control of major phase separation parameters (such as nonsolvent polarity and solvent drying time) enable tunable dual-phase separation of BCPs, eventually leading to macro/nanoscale porous structures and chemical functionalities far beyond those accessible with conventional approaches. Application of this BCP membrane to a lithium-ion battery separator affords exceptional improvement in electrochemical performance. The dual-phase separation–driven macro/nanopore construction strategy, owing to its simplicity and tunability, is expected to be readily applicable to a rich variety of membrane fields including molecular separation, water purification, and energy-related devices. PMID:26601212

Shrink-induced silica multiscale structures for enhanced fluorescence from DNA microarrays.

PubMed

Sharma, Himanshu; Wood, Jennifer B; Lin, Sophia; Corn, Robert M; Khine, Michelle

2014-09-23

We describe a manufacturable and scalable method for fabrication of multiscale wrinkled silica (SiO2) structures on shrink-wrap film to enhance fluorescence signals in DNA fluorescence microarrays. We are able to enhance the fluorescence signal of hybridized DNA by more than 120 fold relative to a planar glass slide. Notably, our substrate has improved detection sensitivity (280 pM) relative to planar glass slide (11 nM). Furthermore, this is accompanied by a 30-45 times improvement in the signal-to-noise ratio (SNR). Unlike metal enhanced fluorescence (MEF) based enhancements, this is a far-field and uniform effect based on surface concentration and photophysical effects from the nano- to microscale SiO2 structures. Notably, the photophysical effects contribute an almost 2.5 fold enhancement over the concentration effects alone. Therefore, this simple and robust method offers an efficient technique to enhance the detection capabilities of fluorescence based DNA microarrays.

Shrink-Induced Silica Multiscale Structures for Enhanced Fluorescence from DNA Microarrays

PubMed Central

2015-01-01

We describe a manufacturable and scalable method for fabrication of multiscale wrinkled silica (SiO2) structures on shrink-wrap film to enhance fluorescence signals in DNA fluorescence microarrays. We are able to enhance the fluorescence signal of hybridized DNA by more than 120 fold relative to a planar glass slide. Notably, our substrate has improved detection sensitivity (280 pM) relative to planar glass slide (11 nM). Furthermore, this is accompanied by a 30–45 times improvement in the signal-to-noise ratio (SNR). Unlike metal enhanced fluorescence (MEF) based enhancements, this is a far-field and uniform effect based on surface concentration and photophysical effects from the nano- to microscale SiO2 structures. Notably, the photophysical effects contribute an almost 2.5 fold enhancement over the concentration effects alone. Therefore, this simple and robust method offers an efficient technique to enhance the detection capabilities of fluorescence based DNA microarrays. PMID:25191785

Multi-scale model for the hierarchical architecture of native cellulose hydrogels.

PubMed

Martínez-Sanz, Marta; Mikkelsen, Deirdre; Flanagan, Bernadine; Gidley, Michael J; Gilbert, Elliot P

2016-08-20

The structure of protiated and deuterated cellulose hydrogels has been investigated using a multi-technique approach combining small-angle scattering with diffraction, spectroscopy and microscopy. A model for the multi-scale structure of native cellulose hydrogels is proposed which highlights the essential role of water at different structural levels characterised by: (i) the existence of cellulose microfibrils containing an impermeable crystalline core surrounded by a partially hydrated paracrystalline shell, (ii) the creation of a strong network of cellulose microfibrils held together by hydrogen bonding to form cellulose ribbons and (iii) the differential behaviour of tightly bound water held within the ribbons compared to bulk solvent. Deuterium labelling provides an effective platform on which to further investigate the role of different plant cell wall polysaccharides in cellulose composite formation through the production of selectively deuterated cellulose composite hydrogels. Copyright © 2016 Elsevier Ltd. All rights reserved.

On the Theory and Numerical Simulation of Cohesive Crack Propagation with Application to Fiber-Reinforced Composites

NASA Technical Reports Server (NTRS)

Rudraraju, Siva Shankar; Garikipati, Krishna; Waas, Anthony M.; Bednarcyk, Brett A.

2013-01-01

The phenomenon of crack propagation is among the predominant modes of failure in many natural and engineering structures, often leading to severe loss of structural integrity and catastrophic failure. Thus, the ability to understand and a priori simulate the evolution of this failure mode has been one of the cornerstones of applied mechanics and structural engineering and is broadly referred to as "fracture mechanics." The work reported herein focuses on extending this understanding, in the context of through-thickness crack propagation in cohesive materials, through the development of a continuum-level multiscale numerical framework, which represents cracks as displacement discontinuities across a surface of zero measure. This report presents the relevant theory, mathematical framework, numerical modeling, and experimental investigations of through-thickness crack propagation in fiber-reinforced composites using the Variational Multiscale Cohesive Method (VMCM) developed by the authors.

Multiscale Information Transfer in Functional Corticomuscular Coupling Estimation Following Stroke: A Pilot Study

PubMed Central

Chen, Xiaoling; Xie, Ping; Zhang, Yuanyuan; Chen, Yuling; Yang, Fangmei; Zhang, Litai; Li, Xiaoli

2018-01-01

Recently, functional corticomuscular coupling (FCMC) between the cortex and the contralateral muscle has been used to evaluate motor function after stroke. As we know, the motor-control system is a closed-loop system that is regulated by complex self-regulating and interactive mechanisms which operate in multiple spatial and temporal scales. Multiscale analysis can represent the inherent complexity. However, previous studies in FCMC for stroke patients mainly focused on the coupling strength in single-time scale, without considering the changes of the inherently directional and multiscale properties in sensorimotor systems. In this paper, a multiscale-causal model, named multiscale transfer entropy, was used to quantify the functional connection between electroencephalogram over the scalp and electromyogram from the flexor digitorum superficialis (FDS) recorded simultaneously during steady-state grip task in eight stroke patients and eight healthy controls. Our results showed that healthy controls exhibited higher coupling when the scale reached up to about 12, and the FCMC in descending direction was stronger at certain scales (1, 7, 12, and 14) than that in ascending direction. Further analysis showed these multi-time scale characteristics mainly focused on the beta1 band at scale 11 and beta2 band at scale 9, 11, 13, and 15. Compared to controls, the multiscale properties of the FCMC for stroke were changed, the strengths in both directions were reduced, and the gaps between the descending and ascending directions were disappeared over all scales. Further analysis in specific bands showed that the reduced FCMC mainly focused on the alpha2 at higher scale, beta1 and beta2 across almost the entire scales. This study about multi-scale confirms that the FCMC between the brain and muscles is capable of complex and directional characteristics, and these characteristics in functional connection for stroke are destroyed by the structural lesion in the brain that might disrupt coordination, feedback, and information transmission in efferent control and afferent feedback. The study demonstrates for the first time the multiscale and directional characteristics of the FCMC for stroke patients, and provides a preliminary observation for application in clinical assessment following stroke. PMID:29765351

Label-free, multi-scale imaging of ex-vivo mouse brain using spatial light interference microscopy

NASA Astrophysics Data System (ADS)

Min, Eunjung; Kandel, Mikhail E.; Ko, Chemyong J.; Popescu, Gabriel; Jung, Woonggyu; Best-Popescu, Catherine

2016-12-01

Brain connectivity spans over broad spatial scales, from nanometers to centimeters. In order to understand the brain at multi-scale, the neural network in wide-field has been visualized in detail by taking advantage of light microscopy. However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer pathlength sensitivity without the use of exogenous contrast agents. Combining wide-field imaging and a mosaic algorithm developed in-house, we show the detailed architecture of cells and myelin, within coronal olfactory bulb and cortical sections, and from sagittal sections of the hippocampus and cerebellum. Our technique is well suited to identify laminar characteristics of fiber tract orientation within white matter, e.g. the corpus callosum. To further improve the macro-scale contrast of anatomical structures, and to better differentiate axons and dendrites from cell bodies, we mapped the tissue in terms of its scattering property. Based on our results, we anticipate that spatial light interference microscopy can potentially provide multiscale and multicontrast perspectives of gross and microscopic brain anatomy.

Multiscale Poincaré plots for visualizing the structure of heartbeat time series.

PubMed

Henriques, Teresa S; Mariani, Sara; Burykin, Anton; Rodrigues, Filipa; Silva, Tiago F; Goldberger, Ary L

2016-02-09

Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincaré (MSP) plots. Starting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system's dynamics in a different time scale. Next, the Poincaré plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency. We illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation. This generalized multiscale approach to Poincaré plots may be useful in visualizing other types of time series.

Structural Damage Detection Using Slopes of Longitudinal Vibration Shapes

DOE PAGES

Xu, W.; Zhu, W. D.; Smith, S. A.; ...

2016-03-18

While structural damage detection based on flexural vibration shapes, such as mode shapes and steady-state response shapes under harmonic excitation, has been well developed, little attention is paid to that based on longitudinal vibration shapes that also contain damage information. This study originally formulates a slope vibration shape for damage detection in bars using longitudinal vibration shapes. To enhance noise robustness of the method, a slope vibration shape is transformed to a multiscale slope vibration shape in a multiscale domain using wavelet transform, which has explicit physical implication, high damage sensitivity, and noise robustness. These advantages are demonstrated in numericalmore » cases of damaged bars, and results show that multiscale slope vibration shapes can be used for identifying and locating damage in a noisy environment. A three-dimensional (3D) scanning laser vibrometer is used to measure the longitudinal steady-state response shape of an aluminum bar with damage due to reduced cross-sectional dimensions under harmonic excitation, and results show that the method can successfully identify and locate the damage. Slopes of longitudinal vibration shapes are shown to be suitable for damage detection in bars and have potential for applications in noisy environments.« less

Transient slowing down relaxation dynamics of the supercooled dusty plasma liquid after quenching.

PubMed

Su, Yen-Shuo; Io, Chong-Wai; I, Lin

2012-07-01

The spatiotemporal evolutions of microstructure and motion in the transient relaxation toward the steady supercooled liquid state after quenching a dusty plasma Wigner liquid, formed by charged dust particles suspended in a low pressure discharge, are experimentally investigated through direct optical microscopy. It is found that the quenched liquid slowly evolves to a colder state with more heterogeneities in structure and motion. Hopping particles and defects appear in the form of clusters with multiscale cluster size distributions. Via the structure rearrangement induced by the reduced thermal agitation from the cold thermal bath after quenching, the temporarily stored strain energy can be cascaded through the network to different newly distorted regions and dissipated after transferring to nonlinearly coupled motions with different scales. It leads to the observed self-similar multiscale slowing down relaxation with power law increases of structural order and structural relaxation time, the similar power law decreases of particle motions at different time scales, and the stronger and slower fluctuations with increasing waiting time toward the new steady state.

Hierarchical Multiscale Modeling of Macromolecules and their Assemblies

PubMed Central

Ortoleva, P.; Singharoy, A.; Pankavich, S.

2013-01-01

Soft materials (e.g., enveloped viruses, liposomes, membranes and supercooled liquids) simultaneously deform or display collective behaviors, while undergoing atomic scale vibrations and collisions. While the multiple space-time character of such systems often makes traditional molecular dynamics simulation impractical, a multiscale approach has been presented that allows for long-time simulation with atomic detail based on the co-evolution of slowly-varying order parameters (OPs) with the quasi-equilibrium probability density of atomic configurations. However, this approach breaks down when the structural change is extreme, or when nearest-neighbor connectivity of atoms is not maintained. In the current study, a self-consistent approach is presented wherein OPs and a reference structure co-evolve slowly to yield long-time simulation for dynamical soft-matter phenomena such as structural transitions and self-assembly. The development begins with the Liouville equation for N classical atoms and an ansatz on the form of the associated N-atom probability density. Multiscale techniques are used to derive Langevin equations for the coupled OP-configurational dynamics. The net result is a set of equations for the coupled stochastic dynamics of the OPs and centers of mass of the subsystems that constitute a soft material body. The theory is based on an all-atom methodology and an interatomic force field, and therefore enables calibration-free simulations of soft matter, such as macromolecular assemblies. PMID:23671457

A New Multiscale Model for the Madden-Julian Oscillation.

NASA Astrophysics Data System (ADS)

Biello, Joseph A.; Majda, Andrew J.

2005-06-01

A multiscale model of the MJO is developed here that accounts, in a simplified fashion, for both the upscale transfer from synoptic to planetary scales of momentum and temperature from wave trains of thermally driven equatorial synoptic-scale circulations in a moving convective envelope as well as direct mean heating on planetary scales. This model involves idealized thermally driven congestus synoptic-scale fluctuations in the eastern part of the moving wave envelope and convective superclusters in the western part of the envelope. The model self-consistently reproduces qualitatively many of the detailed structural features of the planetary circulation in the observations of the MJO, including the vertical structure in both the westerly onset region and the strong westerly wind burst region, as well as the horizontal quadrupole planetary vortex structure. The westerly midlevel inflow in the strong westerly region and the quadrupole vortex are largely produced in the model by the upscale transport of momentum to the planetary scales, while the midlevel easterly jet in the westerly onset region is substantially strengthened by this process. The role of wave trains of tilted organized synoptic-scale circulations is crucial for this fidelity with observations. The appeal of the multiscale models developed below is their firm mathematical underpinnings, simplicity, and analytic tractability while remaining self-consistent with many of the features of the observational record.

Multiscale modeling methods in biomechanics.

PubMed

Bhattacharya, Pinaki; Viceconti, Marco

2017-05-01

More and more frequently, computational biomechanics deals with problems where the portion of physical reality to be modeled spans over such a large range of spatial and temporal dimensions, that it is impossible to represent it as a single space-time continuum. We are forced to consider multiple space-time continua, each representing the phenomenon of interest at a characteristic space-time scale. Multiscale models describe a complex process across multiple scales, and account for how quantities transform as we move from one scale to another. This review offers a set of definitions for this emerging field, and provides a brief summary of the most recent developments on multiscale modeling in biomechanics. Of all possible perspectives, we chose that of the modeling intent, which vastly affect the nature and the structure of each research activity. To the purpose we organized all papers reviewed in three categories: 'causal confirmation,' where multiscale models are used as materializations of the causation theories; 'predictive accuracy,' where multiscale modeling is aimed to improve the predictive accuracy; and 'determination of effect,' where multiscale modeling is used to model how a change at one scale manifests in an effect at another radically different space-time scale. Consistent with how the volume of computational biomechanics research is distributed across application targets, we extensively reviewed papers targeting the musculoskeletal and the cardiovascular systems, and covered only a few exemplary papers targeting other organ systems. The review shows a research subdomain still in its infancy, where causal confirmation papers remain the most common. WIREs Syst Biol Med 2017, 9:e1375. doi: 10.1002/wsbm.1375 For further resources related to this article, please visit the WIREs website. © 2017 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

Multiscale solvers and systematic upscaling in computational physics

NASA Astrophysics Data System (ADS)

Brandt, A.

2005-07-01

Multiscale algorithms can overcome the scale-born bottlenecks that plague most computations in physics. These algorithms employ separate processing at each scale of the physical space, combined with interscale iterative interactions, in ways which use finer scales very sparingly. Having been developed first and well known as multigrid solvers for partial differential equations, highly efficient multiscale techniques have more recently been developed for many other types of computational tasks, including: inverse PDE problems; highly indefinite (e.g., standing wave) equations; Dirac equations in disordered gauge fields; fast computation and updating of large determinants (as needed in QCD); fast integral transforms; integral equations; astrophysics; molecular dynamics of macromolecules and fluids; many-atom electronic structures; global and discrete-state optimization; practical graph problems; image segmentation and recognition; tomography (medical imaging); fast Monte-Carlo sampling in statistical physics; and general, systematic methods of upscaling (accurate numerical derivation of large-scale equations from microscopic laws).

Multicontrast reconstruction using compressed sensing with low rank and spatially varying edge-preserving constraints for high-resolution MR characterization of myocardial infarction.

PubMed

Zhang, Li; Athavale, Prashant; Pop, Mihaela; Wright, Graham A

2017-08-01

To enable robust reconstruction for highly accelerated three-dimensional multicontrast late enhancement imaging to provide improved MR characterization of myocardial infarction with isotropic high spatial resolution. A new method using compressed sensing with low rank and spatially varying edge-preserving constraints (CS-LASER) is proposed to improve the reconstruction of fine image details from highly undersampled data. CS-LASER leverages the low rank feature of the multicontrast volume series in MR relaxation and integrates spatially varying edge preservation into the explicit low rank constrained compressed sensing framework using weighted total variation. With an orthogonal temporal basis pre-estimated, a multiscale iterative reconstruction framework is proposed to enable the practice of CS-LASER with spatially varying weights of appropriate accuracy. In in vivo pig studies with both retrospective and prospective undersamplings, CS-LASER preserved fine image details better and presented tissue characteristics with a higher degree of consistency with histopathology, particularly in the peri-infarct region, than an alternative technique for different acceleration rates. An isotropic resolution of 1.5 mm was achieved in vivo within a single breath-hold using the proposed techniques. Accelerated three-dimensional multicontrast late enhancement with CS-LASER can achieve improved MR characterization of myocardial infarction with high spatial resolution. Magn Reson Med 78:598-610, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Bridging scales through multiscale modeling: a case study on protein kinase A.

PubMed

Boras, Britton W; Hirakis, Sophia P; Votapka, Lane W; Malmstrom, Robert D; Amaro, Rommie E; McCulloch, Andrew D

2015-01-01

The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.

Bayesian inference on multiscale models for poisson intensity estimation: applications to photon-limited image denoising.

PubMed

Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

2009-08-01

We present an improved statistical model for analyzing Poisson processes, with applications to photon-limited imaging. We build on previous work, adopting a multiscale representation of the Poisson process in which the ratios of the underlying Poisson intensities (rates) in adjacent scales are modeled as mixtures of conjugate parametric distributions. Our main contributions include: 1) a rigorous and robust regularized expectation-maximization (EM) algorithm for maximum-likelihood estimation of the rate-ratio density parameters directly from the noisy observed Poisson data (counts); 2) extension of the method to work under a multiscale hidden Markov tree model (HMT) which couples the mixture label assignments in consecutive scales, thus modeling interscale coefficient dependencies in the vicinity of image edges; 3) exploration of a 2-D recursive quad-tree image representation, involving Dirichlet-mixture rate-ratio densities, instead of the conventional separable binary-tree image representation involving beta-mixture rate-ratio densities; and 4) a novel multiscale image representation, which we term Poisson-Haar decomposition, that better models the image edge structure, thus yielding improved performance. Experimental results on standard images with artificially simulated Poisson noise and on real photon-limited images demonstrate the effectiveness of the proposed techniques.

3-D discrete shearlet transform and video processing.

PubMed

Negi, Pooran Singh; Labate, Demetrio

2012-06-01

In this paper, we introduce a digital implementation of the 3-D shearlet transform and illustrate its application to problems of video denoising and enhancement. The shearlet representation is a multiscale pyramid of well-localized waveforms defined at various locations and orientations, which was introduced to overcome the limitations of traditional multiscale systems in dealing with multidimensional data. While the shearlet approach shares the general philosophy of curvelets and surfacelets, it is based on a very different mathematical framework, which is derived from the theory of affine systems and uses shearing matrices rather than rotations. This allows a natural transition from the continuous setting to the digital setting and a more flexible mathematical structure. The 3-D digital shearlet transform algorithm presented in this paper consists in a cascade of a multiscale decomposition and a directional filtering stage. The filters employed in this decomposition are implemented as finite-length filters, and this ensures that the transform is local and numerically efficient. To illustrate its performance, the 3-D discrete shearlet transform is applied to problems of video denoising and enhancement, and compared against other state-of-the-art multiscale techniques, including curvelets and surfacelets.

The effect of modified Blalock-Taussig shunt size and coarctation severity on coronary perfusion after the Norwood operation.

PubMed

Corsini, Chiara; Biglino, Giovanni; Schievano, Silvia; Hsia, Tain-Yen; Migliavacca, Francesco; Pennati, Giancarlo; Taylor, Andrew M

2014-08-01

The size of the modified Blalock-Taussig shunt and the additional presence of aortic coarctation can affect the hemodynamics of the Norwood physiology. Multiscale modeling was used to gather insight into the effects of these variables, in particular on coronary perfusion. A model was reconstructed from cardiac magnetic resonance imaging data of a representative patient, and then simplified with computer-aided design software. Changes were systematically imposed to the semi-idealized three-dimensional model, resulting in a family of nine models (3-, 3.5-, and 4-mm shunt diameter; 0%, 60%, and 90% coarctation severity). Each model was coupled to a lumped parameter network representing the remainder of the circulation to run multiscale simulations. Simulations were repeated including the effect of preserved cerebral perfusion. The concomitant presence of a large shunt and tight coarctation was detrimental in terms of coronary perfusion (13.4% maximal reduction, 1.07 versus 0.927 mL/s) and oxygen delivery (29% maximum reduction, 422 versus 300 mL·min(-1)·m(-2)). A variation in the ratio of pulmonary to systemic blood flow from 0.9 to 1.6 also indicated a "stealing" phenomenon to the detriment of the coronary circulation. A difference could be further appreciated in the computational ventricular pressure-volume loops, with augmented systolic pressures and decreased stroke volumes for tighter coarctation. Accounting for constant cerebral perfusion did not produce substantially different results. Multiscale simulations performed in a parametric fashion revealed a reduction in coronary perfusion in the presence of a large modified Blalock-Taussig shunt and severe coarctation in Norwood patients. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Independent and collective roles of surface structures at different length scales on pool boiling heat transfer

PubMed Central

Li, Calvin H.; Rioux, Russell P.

2016-01-01

Spherical Cu nanocavity surfaces are synthesized to examine the individual role of contact angles in connecting lateral Rayleigh-Taylor wavelength to vertical Kevin-Helmholtz wavelength on hydrodynamic instability for the onset of pool boiling Critical Heat Flux (CHF). Solid and porous Cu pillar surfaces are sintered to investigate the individual role of pillar structure pitch at millimeter scale, named as module wavelength, on hydrodynamic instability at CHF. Last, spherical Cu nanocavities are coated on the porous Cu pillars to create a multiscale Cu structure, which is studied to examine the collective role and relative significance of contact angles and module wavelength on hydrodynamic instability at CHF, and the results indicate that module wavelength plays the dominant role on hydrodynamic instability at CHF when the height of surface structures is equal or above ¼ Kelvin-Helmholtz wavelength. Pool boiling Heat Transfer Coefficient (HTC) enhancements on spherical Cu nanocavity surfaces, solid and porous Cu pillar surfaces, and the integrated multiscale structure have been investigated, too. The experimental results reveal that the nanostructures and porous pillar structures can be combined together to achieve even higher enhancement of HTC than that of individual structures. PMID:27841322

CNNH_PSS: protein 8-class secondary structure prediction by convolutional neural network with highway.

PubMed

Zhou, Jiyun; Wang, Hongpeng; Zhao, Zhishan; Xu, Ruifeng; Lu, Qin

2018-05-08

Protein secondary structure is the three dimensional form of local segments of proteins and its prediction is an important problem in protein tertiary structure prediction. Developing computational approaches for protein secondary structure prediction is becoming increasingly urgent. We present a novel deep learning based model, referred to as CNNH_PSS, by using multi-scale CNN with highway. In CNNH_PSS, any two neighbor convolutional layers have a highway to deliver information from current layer to the output of the next one to keep local contexts. As lower layers extract local context while higher layers extract long-range interdependencies, the highways between neighbor layers allow CNNH_PSS to have ability to extract both local contexts and long-range interdependencies. We evaluate CNNH_PSS on two commonly used datasets: CB6133 and CB513. CNNH_PSS outperforms the multi-scale CNN without highway by at least 0.010 Q8 accuracy and also performs better than CNF, DeepCNF and SSpro8, which cannot extract long-range interdependencies, by at least 0.020 Q8 accuracy, demonstrating that both local contexts and long-range interdependencies are indeed useful for prediction. Furthermore, CNNH_PSS also performs better than GSM and DCRNN which need extra complex model to extract long-range interdependencies. It demonstrates that CNNH_PSS not only cost less computer resource, but also achieves better predicting performance. CNNH_PSS have ability to extracts both local contexts and long-range interdependencies by combing multi-scale CNN and highway network. The evaluations on common datasets and comparisons with state-of-the-art methods indicate that CNNH_PSS is an useful and efficient tool for protein secondary structure prediction.

Laser induced hierarchical calcium phosphate structures.

PubMed

Kurella, Anil; Dahotre, Narendra B

2006-11-01

The surface properties of biomedical implant materials control the dynamic interactions at tissue-implant interfaces. At such interfaces, if the nanoscale features influence protein interactions, those of the microscale and mesoscale aid cell orientation and provide tissue integration, respectively. It seems imperative that the synthetic materials expected to replace natural hard tissues are engineered to mimic the complexity of their hierarchical assembly. However, the current surface engineering approaches are single scaled. It is demonstrated that using laser surface engineering a controlled multiscale surface can be synthesized for bioactive functions. A systematic organization of bioactive calcium phosphate coating with multiphase composition on Ti-alloy substrate ranging from nano- to mesoscale has been achieved by effectively controlling the thermo physical interactions during laser processing. The morphology of the coating consisted of a periodic arrangement of Ti-rich and Ca-P-deficient star-like phases uniformly distributed inside a Ca-P-rich self-assembled cellular structure with the presence of CaO, alpha-tricalcium phosphate, CaTiO(3), TiO(2) and Ti phase in the coating matrix. The cellular structures ranged in diameter from 2.5 microm to 10 microm as an assembly of cuboid shaped particles of dimensions of approximately 200 nm x 1 microm. The multiscale texture also included nanoscale particles that are the precursors for many of these phases. The rapid cooling associated with the laser processing resulted in formation, organization and controlling dimensions of the Ca-P-rich glassy phase into a micron scale cellular morphology and submicron scale clusters of CaTiO(3) phase inside the cellular structures. The self-assembly of the coating into multiscale structure was influenced by chemical and physical interactions among the multiphases that evolved during laser processing.

Simulated shift work in rats perturbs multiscale regulation of locomotor activity.

PubMed

Hsieh, Wan-Hsin; Escobar, Carolina; Yugay, Tatiana; Lo, Men-Tzung; Pittman-Polletta, Benjamin; Salgado-Delgado, Roberto; Scheer, Frank A J L; Shea, Steven A; Buijs, Ruud M; Hu, Kun

2014-07-06

Motor activity possesses a multiscale regulation that is characterized by fractal activity fluctuations with similar structure across a wide range of timescales spanning minutes to hours. Fractal activity patterns are disturbed in animals after ablating the master circadian pacemaker (suprachiasmatic nucleus, SCN) and in humans with SCN dysfunction as occurs with aging and in dementia, suggesting the crucial role of the circadian system in the multiscale activity regulation. We hypothesized that the normal synchronization between behavioural cycles and the SCN-generated circadian rhythms is required for multiscale activity regulation. To test the hypothesis, we studied activity fluctuations of rats in a simulated shift work protocol that was designed to force animals to be active during the habitual resting phase of the circadian/daily cycle. We found that these animals had gradually decreased mean activity level and reduced 24-h activity rhythm amplitude, indicating disturbed circadian and behavioural cycles. Moreover, these animals had disrupted fractal activity patterns as characterized by more random activity fluctuations at multiple timescales from 4 to 12 h. Intriguingly, these activity disturbances exacerbated when the shift work schedule lasted longer and persisted even in the normal days (without forced activity) following the shift work. The disrupted circadian and fractal patterns resemble those of SCN-lesioned animals and of human patients with dementia, suggesting a detrimental impact of shift work on multiscale activity regulation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Length scale effects and multiscale modeling of thermally induced phase transformation kinetics in NiTi SMA

NASA Astrophysics Data System (ADS)

Frantziskonis, George N.; Gur, Sourav

2017-06-01

Thermally induced phase transformation in NiTi shape memory alloys (SMAs) shows strong size and shape, collectively termed length scale effects, at the nano to micrometer scales, and that has important implications for the design and use of devices and structures at such scales. This paper, based on a recently developed multiscale model that utilizes molecular dynamics (MDs) simulations at small scales and MD-verified phase field (PhF) simulations at larger scales, reports results on specific length scale effects, i.e. length scale effects in martensite phase fraction (MPF) evolution, transformation temperatures (martensite and austenite start and finish) and in the thermally cyclic transformation between austenitic and martensitic phase. The multiscale study identifies saturation points for length scale effects and studies, for the first time, the length scale effect on the kinetics (i.e. developed internal strains) in the B19‧ phase during phase transformation. The major part of the work addresses small scale single crystals in specific orientations. However, the multiscale method is used in a unique and novel way to indirectly study length scale and grain size effects on evolution kinetics in polycrystalline NiTi, and to compare the simulation results to experiments. The interplay of the grain size and the length scale effect on the thermally induced MPF evolution is also shown in this present study. Finally, the multiscale coupling results are employed to improve phenomenological material models for NiTi SMA.

Turbulence sources, character, and effects in the stable boundary layer: Insights from multi-scale direct numerical simulations and new, high-resolution measurements

NASA Astrophysics Data System (ADS)

Fritts, Dave; Wang, Ling; Balsley, Ben; Lawrence, Dale

2013-04-01

A number of sources contribute to intermittent small-scale turbulence in the stable boundary layer (SBL). These include Kelvin-Helmholtz instability (KHI), gravity wave (GW) breaking, and fluid intrusions, among others. Indeed, such sources arise naturally in response to even very simple "multi-scale" superpositions of larger-scale GWs and smaller-scale GWs, mean flows, or fine structure (FS) throughout the atmosphere and the oceans. We describe here results of two direct numerical simulations (DNS) of these GW-FS interactions performed at high resolution and high Reynolds number that allow exploration of these turbulence sources and the character and effects of the turbulence that arises in these flows. Results include episodic turbulence generation, a broad range of turbulence scales and intensities, PDFs of dissipation fields exhibiting quasi-log-normal and more complex behavior, local turbulent mixing, and "sheet and layer" structures in potential temperature that closely resemble high-resolution measurements. Importantly, such multi-scale dynamics differ from their larger-scale, quasi-monochromatic gravity wave or quasi-horizontally homogeneous shear flow instabilities in significant ways. The ability to quantify such multi-scale dynamics with new, very high-resolution measurements is also advancing rapidly. New in-situ sensors on small, unmanned aerial vehicles (UAVs), balloons, or tethered systems are enabling definition of SBL (and deeper) environments and turbulence structure and dissipation fields with high spatial and temporal resolution and precision. These new measurement and modeling capabilities promise significant advances in understanding small-scale instability and turbulence dynamics, in quantifying their roles in mixing, transport, and evolution of the SBL environment, and in contributing to improved parameterizations of these dynamics in mesoscale, numerical weather prediction, climate, and general circulation models. We expect such measurement and modeling capabilities to also aid in the design of new and more comprehensive future SBL measurement programs.

Leveraging unsupervised training sets for multi-scale compartmentalization in renal pathology

NASA Astrophysics Data System (ADS)

Lutnick, Brendon; Tomaszewski, John E.; Sarder, Pinaki

2017-03-01

Clinical pathology relies on manual compartmentalization and quantification of biological structures, which is time consuming and often error-prone. Application of computer vision segmentation algorithms to histopathological image analysis, in contrast, can offer fast, reproducible, and accurate quantitative analysis to aid pathologists. Algorithms tunable to different biologically relevant structures can allow accurate, precise, and reproducible estimates of disease states. In this direction, we have developed a fast, unsupervised computational method for simultaneously separating all biologically relevant structures from histopathological images in multi-scale. Segmentation is achieved by solving an energy optimization problem. Representing the image as a graph, nodes (pixels) are grouped by minimizing a Potts model Hamiltonian, adopted from theoretical physics, modeling interacting electron spins. Pixel relationships (modeled as edges) are used to update the energy of the partitioned graph. By iteratively improving the clustering, the optimal number of segments is revealed. To reduce computational time, the graph is simplified using a Cantor pairing function to intelligently reduce the number of included nodes. The classified nodes are then used to train a multiclass support vector machine to apply the segmentation over the full image. Accurate segmentations of images with as many as 106 pixels can be completed only in 5 sec, allowing for attainable multi-scale visualization. To establish clinical potential, we employed our method in renal biopsies to quantitatively visualize for the first time scale variant compartments of heterogeneous intra- and extraglomerular structures simultaneously. Implications of the utility of our method extend to fields such as oncology, genomics, and non-biological problems.

Energy Landscape of All-Atom Protein-Protein Interactions Revealed by Multiscale Enhanced Sampling

PubMed Central

Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

2014-01-01

Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES) simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape. PMID:25340714

A Novel Multiscale Physics Based Progressive Failure Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.; Bednarcyk, Brett A.; Collier, Craig S.; Yarrington, Phillip W.

2008-01-01

A variable fidelity, multiscale, physics based finite element procedure for predicting progressive damage and failure of laminated continuous fiber reinforced composites is introduced. At every integration point in a finite element model, progressive damage is accounted for at the lamina-level using thermodynamically based Schapery Theory. Separate failure criteria are applied at either the global-scale or the microscale in two different FEM models. A micromechanics model, the Generalized Method of Cells, is used to evaluate failure criteria at the micro-level. The stress-strain behavior and observed failure mechanisms are compared with experimental results for both models.

Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hou, Thomas; Efendiev, Yalchin; Tchelepi, Hamdi

2016-05-24

Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scalemore » basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics.« less

Multiscale analysis and computation for flows in heterogeneous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Efendiev, Yalchin; Hou, T. Y.; Durlofsky, L. J.

Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scalemore » basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.« less

Multiscale Investigation from Subcellular to Tissue Scale of Onion Epidermal Plant Cell Wall Mechanical Properties

NASA Astrophysics Data System (ADS)

Zamil, Mohammad Shafayet

The physical and mechanical properties of cell walls, their shape, how they are arranged and interact with each other determine the architecture of plant organs and how they mechanically respond to different environmental and loading conditions. Due to the distinctive hierarchy from subcellular to tissue scale, plant materials can exhibit remarkably different mechanical properties. To date, how the subcellular scale arrangement and the mechanical properties of plant cell wall structural constituents give rise to macro or tissue scale mechanical responses is not yet well understood. Although the tissue scale plant cell wall samples are easy to prepare and put to different types of mechanical tests, the hierarchical features that emerge when moving towards a higher scale make it complicated to link the macro scale results to micro or subcellular scale structural components. On the other hand, the microscale size of cell brings formidable challenges to prepare and grip samples and carry mechanical tests under tensile loading at subcellular scale. This study attempted to develop a set of test protocols based on microelectromechanical system (MEMS) tensile testing devices for characterizing plant cell wall materials at different length scales. For the ease of sample preparation and well established database of the composition and conformation of its structural constituents, onion epidermal cell wall profile was chosen as the study material. Based on the results and findings of multiscale mechanical characterization, a framework of architecture-based finite element method (FEM) computational model was developed. The computational model laid the foundation of bridging the subcellular or microscale to the tissue or macroscale mechanical properties. This study suggests that there are important insights of cell wall mechanics and structural features that can only be investigated by carrying tensile characterization of samples not confounded by extracellular parameters. To the best of our knowledge, the plant cell wall at subcellular scale was never characterized under tensile loading. By coupling the structure based multiscale modeling and mechanical characterizations at different length scales, an attempt was made to provide novel insights towards understanding the mechanics and architecture of cell wall. This study also suggests that a multiscale investigation is essential for garnering fundamental insights into the hierarchical deformation of biological systems.

Money circulation networks reveal emerging geographical communities

NASA Astrophysics Data System (ADS)

Brockmann, D.; Theis, F.; David, V.

2008-03-01

Geographical communities and their boundaries are key determinants of various spatially extended dynamical phenomena. Examples are migration dynamics of species, the spread of infectious diseases, bioinvasive processes, and the spatial evolution of language. We address the question to what extend multiscale human transportation networks encode geographical community structures, how they differ from geopolitical classifications, whether they are spatially coherent, and analyse their structure as a function of length scale. Our analysis is based on a proxy network for human transportation obtained from the geographic circulation of more than 10 million dollar bills in the United States recorded at the bill tracking website www.wheresgeorge.com. The data extends that of a previous study (Brockmann et al., Nature 2006) on the discovery of scaling laws of human travel by an order of magnitude and permits an approach to multiscale human transportation from a network perspective.

Multi-scale quantum point contact model for filamentary conduction in resistive random access memories devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lian, Xiaojuan, E-mail: xjlian2005@gmail.com; Cartoixà, Xavier; Miranda, Enrique

2014-06-28

We depart from first-principle simulations of electron transport along paths of oxygen vacancies in HfO{sub 2} to reformulate the Quantum Point Contact (QPC) model in terms of a bundle of such vacancy paths. By doing this, the number of model parameters is reduced and a much clearer link between the microscopic structure of the conductive filament (CF) and its electrical properties can be provided. The new multi-scale QPC model is applied to two different HfO{sub 2}-based devices operated in the unipolar and bipolar resistive switching (RS) modes. Extraction of the QPC model parameters from a statistically significant number of CFsmore » allows revealing significant structural differences in the CF of these two types of devices and RS modes.« less

Magnetospheric Multiscale Satellite Observations of Parallel Electron Acceleration in Magnetic Field Reconnection by Fermi Reflection from Time Domain Structures

NASA Technical Reports Server (NTRS)

Mozer, F. S.; Agapitov, O. A.; Artemyev, A.; Burch, J. L.; Ergun, R. E.; Giles, B. L.; Mourenas, D.; Torbert, R. B.; Phan, T. D.; Vasko, I.

2016-01-01

The same time domain structures (TDS) have been observed on two Magnetospheric Multiscale Satellites near Earth's dayside magnetopause. These TDS, traveling away from the X line along the magnetic field at 4000 km/s, accelerated field-aligned approx. 5 eV electrons to approx. 200 eV by a single Fermi reflection of the electrons by these overtaking barriers. Additionally, the TDS contained both positive and negative potentials, so they were a mixture of electron holes and double layers. They evolve in approx.10 km of space or 7 ms of time and their spatial scale size is 10-20 km, which is much larger than the electron gyroradius (less than1km) or the electron inertial length (4 km at the observation point, less nearer the X line).

Photocurable high internal phase emulsions (HIPEs) containing hydroxyapatite for additive manufacture of tissue engineering scaffolds with multi-scale porosity.

PubMed

Wang, Ai-Juan; Paterson, Thomas; Owen, Robert; Sherborne, Colin; Dugan, James; Li, Jun-Ming; Claeyssens, Frederik

2016-10-01

Porous composites containing hydroxyapatite (HA) were templated from high internal phase emulsions (HIPEs) and were further structured using direct-write UV stereolithography to produce composite scaffolds with multi-scale porosity. FTIR, TGA and SEM analyses confirmed that HA was retained after photocuring and subsequent treatments and was incorporated within the polymerised HIPE (polyHIPE). The addition of HA particles to the polyHIPE caused changes in the mechanical properties of the material. An increase in both the Young's modulus and maximum stress at yield was observed compared with the pure polyHIPE from 1.544±0.231 to 4.614±0.775 and 0.177±0.009 to 0.267±0.034MPa, respectively. Except at very high concentrations, adding HA did not adversely cause the phase separation of the HIPE or the porous microstructure of the resulting polyHIPE. In combination with a photoinitiator, the HIPE emulsion containing HA was investigated as a photocurable resin for stereolithography-based additive manufacturing. The material was readily processable into "woodpile" structures via direct-write UV stereolithography, producing scaffolds with multi-scale porosity which may be useful for medical applications such as tissue engineering. In conclusion, HA was successfully added into polyHIPEs, producing a similar porous structure to that of the pure polyHIPE whilst improving the mechanical performance. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiscale analysis of potential fields by a ridge consistency criterion: the reconstruction of the Bishop basement

NASA Astrophysics Data System (ADS)

Fedi, M.; Florio, G.; Cascone, L.

2012-01-01

We use a multiscale approach as a semi-automated interpreting tool of potential fields. The depth to the source and the structural index are estimated in two steps: first the depth to the source, as the intersection of the field ridges (lines built joining the extrema of the field at various altitudes) and secondly, the structural index by the scale function. We introduce a new criterion, called 'ridge consistency' in this strategy. The criterion is based on the principle that the structural index estimations on all the ridges converging towards the same source should be consistent. If these estimates are significantly different, field differentiation is used to lessen the interference effects from nearby sources or regional fields, to obtain a consistent set of estimates. In our multiscale framework, vertical differentiation is naturally joint to the low-pass filtering properties of the upward continuation, so is a stable process. Before applying our criterion, we studied carefully the errors on upward continuation caused by the finite size of the survey area. To this end, we analysed the complex magnetic synthetic case, known as Bishop model, and evaluated the best extrapolation algorithm and the optimal width of the area extension, needed to obtain accurate upward continuation. Afterwards, we applied the method to the depth estimation of the whole Bishop basement bathymetry. The result is a good reconstruction of the complex basement and of the shape properties of the source at the estimated points.

Phase Separation and d Electronic Orbitals on Cyclic Degradation in Li-Mn-O Compounds: First-Principles Multiscale Modeling and Experimental Observations.

PubMed

Kim, Duho; Lim, Jin-Myoung; Park, Min-Sik; Cho, Kyeongjae; Cho, Maenghyo

2016-07-06

A combined study involving experiments and multiscale computational approaches is conducted to propose a theoretical solution for the suppression of the Jahn-Teller distortion which causes severe cyclic degradation. As-synthesized pristine and Al-doped Mn spinel compounds are the focus to understand the mechanism of the cyclic degradation in terms of the Jahn-Teller distortion, and the electrochemical performance of the Al-doped sample shows enhanced cyclic performance compared with that of the pristine one. Considering the electronic structures of the two systems using first-principles calculations, the pristine spinel suffers entirely from the Jahn-Teller distortion by Mn(3+), indicating an anisotropic electronic structure, but the Al-doped spinel exhibits an isotropic electronic structure, which means the suppressed Jahn-Teller distortion. A multiscale phase field model in nanodomain shows that the phase separation of the pristine spinel occurs to inactive Li0Mn2O4 (i.e., fully delithiated) gradually during cycles. In contrast, the Al-doped spinel does not show phase separation to an inactive phase. This explains why the Al-doped spinel maintains the capacity of the first charge during the subsequent cycles. On the basis of the mechanistic understanding of the origins and mechanism of the suppression of the Jahn-Teller distortion, fundamental insight for making tremendous cuts in the cyclic degradation could be provided for the Li-Mn-O compounds of Li-ion batteries.

Multiscale field-aligned current analyzer

NASA Astrophysics Data System (ADS)

Bunescu, C.; Marghitu, O.; Constantinescu, D.; Narita, Y.; Vogt, J.; Blǎgǎu, A.

2015-11-01

The magnetosphere-ionosphere coupling is achieved, essentially, by a superposition of quasi-stationary and time-dependent field-aligned currents (FACs), over a broad range of spatial and temporal scales. The planarity of the FAC structures observed by satellite data and the orientation of the planar FAC sheets can be investigated by the well-established minimum variance analysis (MVA) of the magnetic perturbation. However, such investigations are often constrained to a predefined time window, i.e., to a specific scale of the FAC. The multiscale field-aligned current analyzer, introduced here, relies on performing MVA continuously and over a range of scales by varying the width of the analyzing window, appropriate for the complexity of the magnetic field signatures above the auroral oval. The proposed technique provides multiscale information on the planarity and orientation of the observed FACs. A new approach, based on the derivative of the largest eigenvalue of the magnetic variance matrix with respect to the length of the analysis window, makes possible the inference of the current structures' location (center) and scale (thickness). The capabilities of the FAC analyzer are explored analytically for the magnetic field profile of the Harris sheet and tested on synthetic FAC structures with uniform current density and infinite or finite geometry in the cross-section plane of the FAC. The method is illustrated with data observed by the Cluster spacecraft on crossing the nightside auroral region, and the results are cross checked with the optical observations from the Time History of Events and Macroscale Interactions during Substorms ground network.

Resolution Measurement from a Single Reconstructed Cryo-EM Density Map with Multiscale Spectral Analysis.

PubMed

Yang, Yu-Jiao; Wang, Shuai; Zhang, Biao; Shen, Hong-Bin

2018-06-25

As a relatively new technology to solve the three-dimensional (3D) structure of a protein or protein complex, single-particle reconstruction (SPR) of cryogenic electron microscopy (cryo-EM) images shows much superiority and is in a rapidly developing stage. Resolution measurement in SPR, which evaluates the quality of a reconstructed 3D density map, plays a critical role in promoting methodology development of SPR and structural biology. Because there is no benchmark map in the generation of a new structure, how to realize the resolution estimation of a new map is still an open problem. Existing approaches try to generate a hypothetical benchmark map by reconstructing two 3D models from two halves of the original 2D images for cross-reference, which may result in a premature estimation with a half-data model. In this paper, we report a new self-reference-based resolution estimation protocol, called SRes, that requires only a single reconstructed 3D map. The core idea of SRes is to perform a multiscale spectral analysis (MSSA) on the map through multiple size-variable masks segmenting the map. The MSSA-derived multiscale spectral signal-to-noise ratios (mSSNRs) reveal that their corresponding estimated resolutions will show a cliff jump phenomenon, indicating a significant change in the SSNR properties. The critical point on the cliff borderline is demonstrated to be the right estimator for the resolution of the map.

A preliminary investigation of the growth of an aneurysm with a multiscale monolithic Fluid-Structure interaction solver

NASA Astrophysics Data System (ADS)

Cerroni, D.; Manservisi, S.; Pozzetti, G.

2015-11-01

In this work we investigate the potentialities of multi-scale engineering techniques to approach complex problems related to biomedical and biological fields. In particular we study the interaction between blood and blood vessel focusing on the presence of an aneurysm. The study of each component of the cardiovascular system is very difficult due to the fact that the movement of the fluid and solid is determined by the rest of system through dynamical boundary conditions. The use of multi-scale techniques allows us to investigate the effect of the whole loop on the aneurysm dynamic. A three-dimensional fluid-structure interaction model for the aneurysm is developed and coupled to a mono-dimensional one for the remaining part of the cardiovascular system, where a point zero-dimensional model for the heart is provided. In this manner it is possible to achieve rigorous and quantitative investigations of the cardiovascular disease without loosing the system dynamic. In order to study this biomedical problem we use a monolithic fluid-structure interaction (FSI) model where the fluid and solid equations are solved together. The use of a monolithic solver allows us to handle the convergence issues caused by large deformations. By using this monolithic approach different solid and fluid regions are treated as a single continuum and the interface conditions are automatically taken into account. In this way the iterative process characteristic of the commonly used segregated approach, it is not needed any more.

Characterisation of Organic Matter Preserved in Earths Using Micromorphological and Chemical Analysis. Initial Results from Two Prehistoric French Sites : Les Bossats and Régismont-le-Haut.

NASA Astrophysics Data System (ADS)

Lejay, Mathieu; Alexis, Marie; Quenea, Katell; Sellami, Farid; Bodu, Pierre; Naton, Henri-Georges; Vassiliu, Ligia; Dumarçay, Gaëlle; Bon, François; Mensan, Romain

2014-05-01

The Upper Paleolithic (ca. 40 - 10 Ka BP) of Western Europe coincides with the emergence of what are often termed "fully modern" human cultures in a glacial environment (Late Pleistocene, Weichselian glaciation). During this period the increasing structuration of living-spaces, as well as favorable preservational contexts, allows for the investigation of the spatial organization of habitats. Within this field of research hearths have traditionally played a key interpretational role through the use of ethnographic analogy. While such analyses do provide reasonable hypotheses little is known about the precise use and function of hearths during remote prehistory and thus such analogies should be treated prudently.. Using two open-air sites currently being excavated in France, Régismont-le-Haut (Aurignacian) and Les Bossats (Gravettian), we applied a multi-scale and multi-step analysis to a sample of prehistoric hearths. The main objectives of this study were to underline mechanisms involved in the conservation (taphonomic processes) and the operation (anthropogenic technical processes) of these structures. Ultimately, the aim is both a chronological and evidence based palethnological interpretation of these remains through the integration of our results with ongoing research at sites. As hearths are a ubiquitous archaeological feature spanning a multiplicity of contexts and variables, we concentrated here only on those affected by organic matter conservation in the hopes of revealing activities previously invisible to standard archaeological investigation. Field observations of these hearths show the preservation of structured organic matter (eg. charcoal, burned bones) and in some cases a darkening of the associated sediments.. Micromorphological and experimental investigations led to the attribution of this to an impregnation by amorphous organic matter in a semi-liquid state as it percolates through sediments. Microcontextual observations confirm the in-situ character of this feature and its direct association with hearth use. Following these observations we sampled several structures and facies in order to characterize this amorphous organic matter at the molecular scale. We first used C/N Elemental Analysis to quantify the organic carbon contained. The most promising samples have been selected for further detailed analyses (including pyrolysis, gas chromatography, mass spectrometry, and lipid analysis) in the hopes determining their exact molecular composition. Preliminary results indicate the conservation of long chain fatty acids, probably linked to higher plants, and cholesterol, so of animal origin. While the former can probably be explained by the nature of the fuel used (wood), the latter may in fact be implicated in the impregnation of sediments by amorphous organic matter. Although this research is still in its early stages, preliminary results are extremely encouraging. Our methodology seems effective as analysis at multiple scales allows us to trace features from the field to the lab and avoid on-site contamination issues. The flexibility of this methodology is also extremely positive, as analyses can be modified in view of the preceding step's results. Keywords : Micromorphology ; Organic chemistry ; Organic matter preservation ; Prehistoric hearths ; Upper Palaeolithic

Reconfiguration of Cortical Networks in MDD Uncovered by Multiscale Community Detection with fMRI.

PubMed

He, Ye; Lim, Sol; Fortunato, Santo; Sporns, Olaf; Zhang, Lei; Qiu, Jiang; Xie, Peng; Zuo, Xi-Nian

2018-04-01

Major depressive disorder (MDD) is known to be associated with altered interactions between distributed brain regions. How these regional changes relate to the reorganization of cortical functional systems, and their modulation by antidepressant medication, is relatively unexplored. To identify changes in the community structure of cortical functional networks in MDD, we performed a multiscale community detection algorithm on resting-state functional connectivity networks of unmedicated MDD (uMDD) patients (n = 46), medicated MDD (mMDD) patients (n = 38), and healthy controls (n = 50), which yielded a spectrum of multiscale community partitions. we selected an optimal resolution level by identifying the most stable community partition for each group. uMDD and mMDD groups exhibited a similar reconfiguration of the community structure of the visual association and the default mode systems but showed different reconfiguration profiles in the frontoparietal control (FPC) subsystems. Furthermore, the central system (somatomotor/salience) and 3 frontoparietal subsystems showed strengthened connectivity with other communities in uMDD but, with the exception of 1 frontoparietal subsystem, returned to control levels in mMDD. These findings provide evidence for reconfiguration of specific cortical functional systems associated with MDD, as well as potential effects of medication in restoring disease-related network alterations, especially those of the FPC system.

Information Management Workflow and Tools Enabling Multiscale Modeling Within ICME Paradigm

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Bednarcyk, Brett A.; Austin, Nic; Terentjev, Igor; Cebon, Dave; Marsden, Will

2016-01-01

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Fortunately, material information management systems and physics-based multiscale modeling methods have kept pace with the growing user demands. Herein, recent efforts to establish workflow for and demonstrate a unique set of web application tools for linking NASA GRC's Integrated Computational Materials Engineering (ICME) Granta MI database schema and NASA GRC's Integrated multiscale Micromechanics Analysis Code (ImMAC) software toolset are presented. The goal is to enable seamless coupling between both test data and simulation data, which is captured and tracked automatically within Granta MI®, with full model pedigree information. These tools, and this type of linkage, are foundational to realizing the full potential of ICME, in which materials processing, microstructure, properties, and performance are coupled to enable application-driven design and optimization of materials and structures.

Multi-Scale Modeling of the Gamma Radiolysis of Nitrate Solutions.

PubMed

Horne, Gregory P; Donoclift, Thomas A; Sims, Howard E; Orr, Robin M; Pimblott, Simon M

2016-11-17

A multiscale modeling approach has been developed for the extended time scale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages: radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modeling. The first three components model the physical and chemical evolution of an isolated radiation chemical track and provide radiolysis yields, within the extremely low dose isolated track paradigm, as the input parameters for a bulk deterministic chemistry model. This approach to radiation chemical modeling has been tested by comparison with the experimentally observed yield of nitrite from the gamma radiolysis of sodium nitrate solutions. This is a complex radiation chemical system which is strongly dependent on secondary reaction processes. The concentration of nitrite is not just dependent upon the evolution of radiation track chemistry and the scavenging of the hydrated electron and its precursors but also on the subsequent reactions of the products of these scavenging reactions with other water radiolysis products. Without the inclusion of intratrack chemistry, the deterministic component of the multiscale model is unable to correctly predict experimental data, highlighting the importance of intratrack radiation chemistry in the chemical evolution of the irradiated system.

Identifying seasonal mobility profiles from anonymized and aggregated mobile phone data. Application in food security.

PubMed

Zufiria, Pedro J; Pastor-Escuredo, David; Úbeda-Medina, Luis; Hernandez-Medina, Miguel A; Barriales-Valbuena, Iker; Morales, Alfredo J; Jacques, Damien C; Nkwambi, Wilfred; Diop, M Bamba; Quinn, John; Hidalgo-Sanchís, Paula; Luengo-Oroz, Miguel

2018-01-01

We propose a framework for the systematic analysis of mobile phone data to identify relevant mobility profiles in a population. The proposed framework allows finding distinct human mobility profiles based on the digital trace of mobile phone users characterized by a Matrix of Individual Trajectories (IT-Matrix). This matrix gathers a consistent and regularized description of individual trajectories that enables multi-scale representations along time and space, which can be used to extract aggregated indicators such as a dynamic multi-scale population count. Unsupervised clustering of individual trajectories generates mobility profiles (clusters of similar individual trajectories) which characterize relevant group behaviors preserving optimal aggregation levels for detailed and privacy-secured mobility characterization. The application of the proposed framework is illustrated by analyzing fully anonymized data on human mobility from mobile phones in Senegal at the arrondissement level over a calendar year. The analysis of monthly mobility patterns at the livelihood zone resolution resulted in the discovery and characterization of seasonal mobility profiles related with economic activities, agricultural calendars and rainfalls. The use of these mobility profiles could support the timely identification of mobility changes in vulnerable populations in response to external shocks (such as natural disasters, civil conflicts or sudden increases of food prices) to monitor food security.

Development of an integrated generic model for multi-scale assessment of the impacts of agro-ecosystems on major ecosystem services in West Africa.

PubMed

Belem, Mahamadou; Saqalli, Mehdi

2017-11-01

This paper presents an integrated model assessing the impacts of climate change, agro-ecosystem and demographic transition patterns on major ecosystem services in West-Africa along a partial overview of economic aspects (poverty reduction, food self-sufficiency and income generation). The model is based on an agent-based model associated with a soil model and multi-scale spatial model. The resulting Model for West-Africa Agro-Ecosystem Integrated Assessment (MOWASIA) is ecologically generic, meaning it is designed for all sudano-sahelian environments but may then be used as an experimentation facility for testing different scenarios combining ecological and socioeconomic dimensions. A case study in Burkina Faso is examined to assess the environmental and economic performances of semi-continuous and continuous farming systems. Results show that the semi-continuous system using organic fertilizer and fallowing practices contribute better to environment preservation and food security than the more economically performant continuous system. In addition, this study showed that farmers heterogeneity could play an important role in agricultural policies planning and assessment. In addition, the results showed that MOWASIA is an effective tool for designing, analysing the impacts of agro-ecosystems. Copyright © 2017. Published by Elsevier Ltd.

Turbulent Flow Structure Inside a Canopy with Complex Multi-Scale Elements

NASA Astrophysics Data System (ADS)

Bai, Kunlun; Katz, Joseph; Meneveau, Charles

2015-06-01

Particle image velocimetry laboratory measurements are carried out to study mean flow distributions and turbulent statistics inside a canopy with complex geometry and multiple scales consisting of fractal, tree-like objects. Matching the optical refractive indices of the tree elements with those of the working fluid provides unobstructed optical paths for both illuminations and image acquisition. As a result, the flow fields between tree branches can be resolved in great detail, without optical interference. Statistical distributions of mean velocity, turbulence stresses, and components of dispersive fluxes are documented and discussed. The results show that the trees leave their signatures in the flow by imprinting wake structures with shapes similar to the trees. The velocities in both wake and non-wake regions significantly deviate from the spatially-averaged values. These local deviations result in strong dispersive fluxes, which are important to account for in canopy-flow modelling. In fact, we find that the streamwise normal dispersive flux inside the canopy has a larger magnitude (by up to four times) than the corresponding Reynolds normal stress. Turbulent transport in horizontal planes is studied in the framework of the eddy viscosity model. Scatter plots comparing the Reynolds shear stress and mean velocity gradient are indicative of a linear trend, from which one can calculate the eddy viscosity and mixing length. Similar to earlier results from the wake of a single tree, here we find that inside the canopy the mean mixing length decreases with increasing elevation. This trend cannot be scaled based on a single length scale, but can be described well by a model, which considers the coexistence of multi-scale branches. This agreement indicates that the multi-scale information and the clustering properties of the fractal objects should be taken into consideration in flows inside multi-scale canopies.

Multiscale multimodal fusion of histological and MRI volumes for characterization of lung inflammation

NASA Astrophysics Data System (ADS)

Rusu, Mirabela; Wang, Haibo; Golden, Thea; Gow, Andrew; Madabhushi, Anant

2013-03-01

Mouse lung models facilitate the investigation of conditions such as chronic inflammation which are associated with common lung diseases. The multi-scale manifestation of lung inflammation prompted us to use multi-scale imaging - both in vivo, ex vivo MRI along with ex vivo histology, for its study in a new quantitative way. Some imaging modalities, such as MRI, are non-invasive and capture macroscopic features of the pathology, while others, e.g. ex vivo histology, depict detailed structures. Registering such multi-modal data to the same spatial coordinates will allow the construction of a comprehensive 3D model to enable the multi-scale study of diseases. Moreover, it may facilitate the identification and definition of quantitative of in vivo imaging signatures for diseases and pathologic processes. We introduce a quantitative, image analytic framework to integrate in vivo MR images of the entire mouse with ex vivo histology of the lung alone, using lung ex vivo MRI as conduit to facilitate their co-registration. In our framework, we first align the MR images by registering the in vivo and ex vivo MRI of the lung using an interactive rigid registration approach. Then we reconstruct the 3D volume of the ex vivo histological specimen by efficient group wise registration of the 2D slices. The resulting 3D histologic volume is subsequently registered to the MRI volumes by interactive rigid registration, directly to the ex vivo MRI, and implicitly to in vivo MRI. Qualitative evaluation of the registration framework was performed by comparing airway tree structures in ex vivo MRI and ex vivo histology where airways are visible and may be annotated. We present a use case for evaluation of our co-registration framework in the context of studying chronic inammation in a diseased mouse.

Fabricating Superhydrophobic and Superoleophobic Surfaces with Multiscale Roughness Using Airbrush and Electrospray

NASA Astrophysics Data System (ADS)

AL-Milaji, Karam N.

Examples of superhydrophobic surfaces found in nature such as self-cleaning property of lotus leaf and walking on water ability of water strider have led to an extensive investigation in this area over the past few decades. When a water droplet rests on a textured surface, it may either form a liquid-solid-vapor composite interface by which the liquid droplet partially sits on air pockets or it may wet the surface in which the water replaces the trapped air depending on the surface roughness and the surface chemistry. Super water repellent surfaces have numerous applications in our daily life such as drag reduction, anti-icing, anti-fogging, energy conservation, noise reduction, and self-cleaning. In fact, the same concept could be applied in designing and producing surfaces that repel organic contaminations (e.g. low surface tension liquids). However, superoleophobic surfaces are more challenging to fabricate than superhydrophobic surfaces since the combination of multiscale roughness with re-entrant or overhang structure and surface chemistry must be provided. In this study, simple, cost-effective and potentially scalable techniques, i.e., airbrush and electrospray, were employed for the sake of making superhydrophobic and superoleophobic coatings with random and patterned multiscale surface roughness. Different types of silicon dioxide were utilized in this work to in order to study and to characterize the effect of surface morphology and surface roughness on surface wettability. The experimental findings indicated that super liquid repellent surfaces with high apparent contact angles and extremely low sliding angles were successfully fabricated by combining re-entrant structure, multiscale surface roughness, and low surface energy obtained from chemically treating the fabricated surfaces. In addition to that, the experimental observations regarding producing textured surfaces in mask-assisted electrospray were further validated by simulating the actual working conditions and geometries using COMSOL Multiphysics.

Multiscale characteristics of mechanical and mineralogical heterogeneity using nanoindentation and Maps Mineralogy in Mancos Shale

NASA Astrophysics Data System (ADS)

Yoon, H.; Mook, W. M.; Dewers, T. A.

2017-12-01

Multiscale characteristics of textural and compositional (e.g., clay, cement, organics, etc.) heterogeneity profoundly influence the mechanical properties of shale. In particular, strongly anisotropic (i.e., laminated) heterogeneities are often observed to have a significant influence on hydrological and mechanical properties. In this work, we investigate a sample of the Cretaceous Mancos Shale to explore the importance of lamination, cements, organic content, and the spatial distribution of these characteristics. For compositional and structural characterization, the mineralogical distribution of thin core sample polished by ion-milling is analyzed using QEMSCAN® with MAPS MineralogyTM (developed by FEI Corporoation). Based on mineralogy and organic matter distribution, multi-scale nanoindentation testing was performed to directly link compositional heterogeneity to mechanical properties. With FIB-SEM (3D) and high-magnitude SEM (2D) images, key nanoindentation patterns are analyzed to evaluate elastic and plastic responses. Combined with MAPs Mineralogy data and fine-resolution BSE images, nanoindentation results are explained as a function of compositional and structural heterogeneity. Finite element modeling is used to quantitatively evaluate the link between the heterogeneity and mechanical behavior during nanoindentation. In addition, the spatial distribution of compositional heterogeneity, anisotropic bedding patterns, and mechanical anisotropy are employed as inputs for multiscale brittle fracture simulations using a phase field model. Comparison of experimental and numerical simulations reveal that proper incorporation of additional material information, such as bedding layer thickness and other geometrical attributes of the microstructures, may yield improvements on the numerical predictions of the mesoscale fracture patterns and hence the macroscopic effective toughness. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Engineered disc-like angle-ply structures for intervertebral disc replacement.

PubMed

Nerurkar, Nandan L; Sen, Sounok; Huang, Alice H; Elliott, Dawn M; Mauck, Robert L

2010-04-15

To develop a construction algorithm in which electrospun nanofibrous scaffolds are coupled with a biocompatible hydrogel to engineer a mesenchymal stem cell (MSC)-based disc replacement. To engineer a disc-like angle-ply structure (DAPS) that replicates the multiscale architecture of the intervertebral disc. Successful engineering of a replacement for the intervertebral disc requires replication of its mechanical function and anatomic form. Despite many attempts to engineer a replacement for ailing and degenerated discs, no prior study has replicated the multiscale hierarchical architecture of the native disc, and very few have assessed the mechanical function of formed neo-tissues. A new algorithm for the construction of a disc analogue was developed, using agarose to form a central nucleus pulposus (NP) and oriented electrospun nanofibrous scaffolds to form the anulus fibrosus region (AF). Bovine MSCs were seeded into both regions and biochemical, histologic, and mechanical maturation were evaluated with in vitro culture. We show that mechanical testing in compression and torsion, loading methods commonly used to assess disc mechanics, reveal equilibrium and time-dependent behaviors that are qualitatively similar to native tissue, although lesser in magnitude. Further, we demonstrate that cells seeded into both AF and NP regions adopt distinct morphologies that mirror those seen in native tissue, and that, in the AF region, this ordered community of cells deposit matrix that is organized in an angle-ply configuration. Finally, constructs demonstrate functional development with long-term in vitro culture. These findings provide a new approach for disc tissue engineering that replicates multi-scale form and function of the intervertebral disc, providing a foundation from which to build a multi-scale, biologic, anatomically and hierarchically relevant composite disc analogue for eventual disc replacement.

Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gearhart, Jared Lee; Kurtz, Nolan Scot

2014-09-01

The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance aremore » investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.« less

Discrete-continuum multiscale model for transport, biomass development and solid restructuring in porous media

NASA Astrophysics Data System (ADS)

Ray, Nadja; Rupp, Andreas; Prechtel, Alexander

2017-09-01

Upscaling transport in porous media including both biomass development and simultaneous structural changes in the solid matrix is extremely challenging. This is because both affect the medium's porosity as well as mass transport parameters and flow paths. We address this challenge by means of a multiscale model. At the pore scale, the local discontinuous Galerkin (LDG) method is used to solve differential equations describing particularly the bacteria's and the nutrient's development. Likewise, a sticky agent tightening together solid or bio cells is considered. This is combined with a cellular automaton method (CAM) capturing structural changes of the underlying computational domain stemming from biomass development and solid restructuring. Findings from standard homogenization theory are applied to determine the medium's characteristic time- and space-dependent properties. Investigating these results enhances our understanding of the strong interplay between a medium's functional properties and its geometric structure. Finally, integrating such properties as model parameters into models defined on a larger scale enables reflecting the impact of pore scale processes on the larger scale.

Insights into the multi-scale structure and digestibility of heat-moisture treated rice starch.

PubMed

Wang, Hongwei; Liu, Yufan; Chen, Ling; Li, Xiaoxi; Wang, Jun; Xie, Fengwei

2018-03-01

The digestibility and structural changes of rice starch induced by heat-moisture treatment (HMT) were investigated, and the relationships among the moisture content-starch structure-starch digestibility were revealed. HMT could simultaneously disorder and reassemble the rice starch molecules across multi-scale lengths and convert some fractions of rapidly-digestible starch (RDS) into slowly-digestible starch (SDS) and resistant starch (RS). In particular, the HMT rice starch with less than 30% moisture content showed a higher SDS+RS content (25.0%). During HMT, SDS and RS were preferably formed by the degraded starch molecules with M w between 4×10 5 and 4×10 6 g/mol, single helices and amylose-lipids complexes that were formed by degraded starch chains with higher thermal stability and crystalline lamellae with greater thicknesses. Thus, our research suggests a potential approach using HMT to control the digestion of starch products with desired digestibility. Copyright © 2017. Published by Elsevier Ltd.

A Framework for Performing Multiscale Stochastic Progressive Failure Analysis of Composite Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2006-01-01

A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis - Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.

A Framework for Performing Multiscale Stochastic Progressive Failure Analysis of Composite Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2007-01-01

A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis-Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.

Calibration of Response Data Using MIRT Models with Simple and Mixed Structures

ERIC Educational Resources Information Center

Zhang, Jinming

2012-01-01

It is common to assume during a statistical analysis of a multiscale assessment that the assessment is composed of several unidimensional subtests or that it has simple structure. Under this assumption, the unidimensional and multidimensional approaches can be used to estimate item parameters. These two approaches are equivalent in parameter…

A light-trapping strategy for nanocrystalline silicon thin-film solar cells using three-dimensionally assembled nanoparticle structures.

PubMed

Ha, Kyungyeon; Jang, Eunseok; Jang, Segeun; Lee, Jong-Kwon; Jang, Min Seok; Choi, Hoseop; Cho, Jun-Sik; Choi, Mansoo

2016-02-05

We report three-dimensionally assembled nanoparticle structures inducing multiple plasmon resonances for broadband light harvesting in nanocrystalline silicon (nc-Si:H) thin-film solar cells. A three-dimensional multiscale (3DM) assembly of nanoparticles generated using a multi-pin spark discharge method has been accomplished over a large area under atmospheric conditions via ion-assisted aerosol lithography. The multiscale features of the sophisticated 3DM structures exhibit surface plasmon resonances at multiple frequencies, which increase light scattering and absorption efficiency over a wide spectral range from 350-1100 nm. The multiple plasmon resonances, together with the antireflection functionality arising from the conformally deposited top surface of the 3D solar cell, lead to a 22% and an 11% improvement in power conversion efficiency of the nc-Si:H thin-film solar cells compared to flat cells and cells employing nanoparticle clusters, respectively. Finite-difference time-domain simulations were also carried out to confirm that the improved device performance mainly originates from the multiple plasmon resonances generated from three-dimensionally assembled nanoparticle structures.

Laser Scanning Holographic Lithography for Flexible 3D Fabrication of Multi-Scale Integrated Nano-structures and Optical Biosensors

PubMed Central

Yuan, Liang (Leon); Herman, Peter R.

2016-01-01

Three-dimensional (3D) periodic nanostructures underpin a promising research direction on the frontiers of nanoscience and technology to generate advanced materials for exploiting novel photonic crystal (PC) and nanofluidic functionalities. However, formation of uniform and defect-free 3D periodic structures over large areas that can further integrate into multifunctional devices has remained a major challenge. Here, we introduce a laser scanning holographic method for 3D exposure in thick photoresist that combines the unique advantages of large area 3D holographic interference lithography (HIL) with the flexible patterning of laser direct writing to form both micro- and nano-structures in a single exposure step. Phase mask interference patterns accumulated over multiple overlapping scans are shown to stitch seamlessly and form uniform 3D nanostructure with beam size scaled to small 200 μm diameter. In this way, laser scanning is presented as a facile means to embed 3D PC structure within microfluidic channels for integration into an optofluidic lab-on-chip, demonstrating a new laser HIL writing approach for creating multi-scale integrated microsystems. PMID:26922872

Evaluation of multiple-scale 3D characterization for coal physical structure with DCM method and synchrotron X-ray CT.

PubMed

Wang, Haipeng; Yang, Yushuang; Yang, Jianli; Nie, Yihang; Jia, Jing; Wang, Yudan

2015-01-01

Multiscale nondestructive characterization of coal microscopic physical structure can provide important information for coal conversion and coal-bed methane extraction. In this study, the physical structure of a coal sample was investigated by synchrotron-based multiple-energy X-ray CT at three beam energies and two different spatial resolutions. A data-constrained modeling (DCM) approach was used to quantitatively characterize the multiscale compositional distributions at the two resolutions. The volume fractions of each voxel for four different composition groups were obtained at the two resolutions. Between the two resolutions, the difference for DCM computed volume fractions of coal matrix and pores is less than 0.3%, and the difference for mineral composition groups is less than 0.17%. This demonstrates that the DCM approach can account for compositions beyond the X-ray CT imaging resolution with adequate accuracy. By using DCM, it is possible to characterize a relatively large coal sample at a relatively low spatial resolution with minimal loss of the effect due to subpixel fine length scale structures.

Local contrast-enhanced MR images via high dynamic range processing.

PubMed

Chandra, Shekhar S; Engstrom, Craig; Fripp, Jurgen; Neubert, Ales; Jin, Jin; Walker, Duncan; Salvado, Olivier; Ho, Charles; Crozier, Stuart

2018-09-01

To develop a local contrast-enhancing and feature-preserving high dynamic range (HDR) image processing algorithm for multichannel and multisequence MR images of multiple body regions and tissues, and to evaluate its performance for structure visualization, bias field (correction) mitigation, and automated tissue segmentation. A multiscale-shape and detail-enhancement HDR-MRI algorithm is applied to data sets of multichannel and multisequence MR images of the brain, knee, breast, and hip. In multisequence 3T hip images, agreement between automatic cartilage segmentations and corresponding synthesized HDR-MRI series were computed for mean voxel overlap established from manual segmentations for a series of cases. Qualitative comparisons between the developed HDR-MRI and standard synthesis methods were performed on multichannel 7T brain and knee data, and multisequence 3T breast and knee data. The synthesized HDR-MRI series provided excellent enhancement of fine-scale structure from multiple scales and contrasts, while substantially reducing bias field effects in 7T brain gradient echo, T 1 and T 2 breast images and 7T knee multichannel images. Evaluation of the HDR-MRI approach on 3T hip multisequence images showed superior outcomes for automatic cartilage segmentations with respect to manual segmentation, particularly around regions with hyperintense synovial fluid, across a set of 3D sequences. The successful combination of multichannel/sequence MR images into a single-fused HDR-MR image format provided consolidated visualization of tissues within 1 omnibus image, enhanced definition of thin, complex anatomical structures in the presence of variable or hyperintense signals, and improved tissue (cartilage) segmentation outcomes. © 2018 International Society for Magnetic Resonance in Medicine.

Multiscale mechanical integrity of human supraspinatus tendon in shear after elastin depletion.

PubMed

Fang, Fei; Lake, Spencer P

2016-10-01

Human supraspinatus tendon (SST) exhibits region-specific nonlinear mechanical properties under tension, which have been attributed to its complex multiaxial physiological loading environment. However, the mechanical response and underlying multiscale mechanism regulating SST behavior under other loading scenarios are poorly understood. Furthermore, little is known about the contribution of elastin to tendon mechanics. We hypothesized that (1) SST exhibits region-specific shear mechanical properties, (2) fiber sliding is the predominant mode of local matrix deformation in SST in shear, and (3) elastin helps maintain SST mechanical integrity by facilitating force transfer among collagen fibers. Through the use of biomechanical testing and multiphoton microscopy, we measured the multiscale mechanical behavior of human SST in shear before and after elastase treatment. Three distinct SST regions showed similar stresses and microscale deformation. Collagen fiber reorganization and sliding were physical mechanisms observed as the SST response to shear loading. Measures of microscale deformation were highly variable, likely due to a high degree of extracellular matrix heterogeneity. After elastase treatment, tendon exhibited significantly decreased stresses under shear loading, particularly at low strains. These results show that elastin contributes to tendon mechanics in shear, further complementing our understanding of multiscale tendon structure-function relationships. Copyright © 2016 Elsevier Ltd. All rights reserved.

The role of continuity in residual-based variational multiscale modeling of turbulence

NASA Astrophysics Data System (ADS)

Akkerman, I.; Bazilevs, Y.; Calo, V. M.; Hughes, T. J. R.; Hulshoff, S.

2008-02-01

This paper examines the role of continuity of the basis in the computation of turbulent flows. We compare standard finite elements and non-uniform rational B-splines (NURBS) discretizations that are employed in Isogeometric Analysis (Hughes et al. in Comput Methods Appl Mech Eng, 194:4135 4195, 2005). We make use of quadratic discretizations that are C 0-continuous across element boundaries in standard finite elements, and C 1-continuous in the case of NURBS. The variational multiscale residual-based method (Bazilevs in Isogeometric analysis of turbulence and fluid-structure interaction, PhD thesis, ICES, UT Austin, 2006; Bazilevs et al. in Comput Methods Appl Mech Eng, submitted, 2007; Calo in Residual-based multiscale turbulence modeling: finite volume simulation of bypass transition. PhD thesis, Department of Civil and Environmental Engineering, Stanford University, 2004; Hughes et al. in proceedings of the XXI international congress of theoretical and applied mechanics (IUTAM), Kluwer, 2004; Scovazzi in Multiscale methods in science and engineering, PhD thesis, Department of Mechanical Engineering, Stanford Universty, 2004) is employed as a turbulence modeling technique. We find that C 1-continuous discretizations outperform their C 0-continuous counterparts on a per-degree-of-freedom basis. We also find that the effect of continuity is greater for higher Reynolds number flows.

Multiscale Macromolecular Simulation: Role of Evolving Ensembles

PubMed Central

Singharoy, A.; Joshi, H.; Ortoleva, P.J.

2013-01-01

Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin timestep is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers. PMID:22978601

Non-Markovian properties and multiscale hidden Markovian network buried in single molecule time series

NASA Astrophysics Data System (ADS)

Sultana, Tahmina; Takagi, Hiroaki; Morimatsu, Miki; Teramoto, Hiroshi; Li, Chun-Biu; Sako, Yasushi; Komatsuzaki, Tamiki

2013-12-01

We present a novel scheme to extract a multiscale state space network (SSN) from single-molecule time series. The multiscale SSN is a type of hidden Markov model that takes into account both multiple states buried in the measurement and memory effects in the process of the observable whenever they exist. Most biological systems function in a nonstationary manner across multiple timescales. Combined with a recently established nonlinear time series analysis based on information theory, a simple scheme is proposed to deal with the properties of multiscale and nonstationarity for a discrete time series. We derived an explicit analytical expression of the autocorrelation function in terms of the SSN. To demonstrate the potential of our scheme, we investigated single-molecule time series of dissociation and association kinetics between epidermal growth factor receptor (EGFR) on the plasma membrane and its adaptor protein Ash/Grb2 (Grb2) in an in vitro reconstituted system. We found that our formula successfully reproduces their autocorrelation function for a wide range of timescales (up to 3 s), and the underlying SSNs change their topographical structure as a function of the timescale; while the corresponding SSN is simple at the short timescale (0.033-0.1 s), the SSN at the longer timescales (0.1 s to ˜3 s) becomes rather complex in order to capture multiscale nonstationary kinetics emerging at longer timescales. It is also found that visiting the unbound form of the EGFR-Grb2 system approximately resets all information of history or memory of the process.

Multiscale 3-D shape representation and segmentation using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2007-04-01

This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details.

Multiscale 3-D Shape Representation and Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron

2013-01-01

This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details. PMID:17427745

Fluorescence Across Space and Time (2017 FAST Campaign): Investigating the multiscale links between fluorescence and photosynthesis

NASA Astrophysics Data System (ADS)

Porcar-Castell, A.; Atherton, J.; Rajewicz, P. A.; Riikonen, A.; Gebre, S.; Liu, W.; Aalto, J.; Bendoula, R.; Burkart, A.; Chen, H.; Erkkilä, K. M.; Feret, J. B.; Fernández-Marín, B.; García-Plazaola, J. I.; Hakala, T.; Hartikainen, S.; Honkavaara, E.; Ihalainen, J.; Julitta, T.; Kolari, P.; Kooijmans, L.; Levula, J.; Loponen, M.; Mac Arthur, A.; Magney, T.; Maseyk, K. S.; Mottus, M.; Neimane, S.; Oksa, E.; Osterman, G. B.; Robinson, I.; Robson, M. T.; Sabater, N.; Solanki, T.; Tikkanen, M.; Mäkipää, R.; Aro, E. M.; Rascher, U.; Frankenberg, C.; Kulmala, M. T.; Vesala, T.; Back, J. K.

2017-12-01

The use of solar-induced chlorophyll fluorescence (ChlF) as a tracer of photosynthesis is rapidly expanding with increasing numbers of measurements from towers, drones, aircrafts, or satellites. But how to integrate all the informative potential of these multiscale datasets? The connection between ChlF and photosynthesis takes place via multiple mechansisms that depend on the scale. At the leaf level, diurnal variations in ChlF may indicate changes in photochemical or non-photochemical quenching processes, whereas seasonal variations may indicate changes in the protein structure or pigment composition of the photosynthetic apparatus. At the canopy level, variations in ChlF may also reflect changes in total leaf area, canopy structure, species composition, changes in illumination or sun-target-sensor geometry, background properties, etc. At the pixel level, the dynamics of the atmosphere are also important. It is therefore essential to characterize the impact of factors that control ChlF and photosynthesis at each scale. A combination of multiscale and continuous experimentation and modelling is probably the best option to close the remaining knowledge gaps. The goal of the FAST campaign was to characterize the processes that control the ChlF signal dynamics at each scale, establishing a comprehensive dataset for multiscale hypothesis and model validation. The campaign took place in Hyytiälä (Southern Finland) and lasted for 6 months. Measurements expanded from the molecular to the satellite pixel level and from the picosecond to the seasonal scale, including multiple species, and providing a unique optical and phenomenological record of the multiscale spring recovery of photosynthesis in a boreal forest. Amongst others we measured and registered: leaf ChlF spectra, OJIP kinetics, PSI and PSII activity, photosynthetic gas exchange, carbonyl sulphide (COS), volatile organic compounds (VOCs), total leaf absorption, pigment concentrations, photosynthetic proteins, fluorescence lifetime, canopy SIF, CO2, water, COS, and VOC fluxes, as well as vertical profiles of forest SIF using a drone and target OCO-2 observations at 1x2km pixel resolution. We here present preliminary results from the FAST campaign which emphasize the variability and role of different controls across scales.

Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

PubMed Central

Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614

Cardiac Light-Sheet Fluorescent Microscopy for Multi-Scale and Rapid Imaging of Architecture and Function

NASA Astrophysics Data System (ADS)

Fei, Peng; Lee, Juhyun; Packard, René R. Sevag; Sereti, Konstantina-Ioanna; Xu, Hao; Ma, Jianguo; Ding, Yichen; Kang, Hanul; Chen, Harrison; Sung, Kevin; Kulkarni, Rajan; Ardehali, Reza; Kuo, C.-C. Jay; Xu, Xiaolei; Ho, Chih-Ming; Hsiai, Tzung K.

2016-03-01

Light Sheet Fluorescence Microscopy (LSFM) enables multi-dimensional and multi-scale imaging via illuminating specimens with a separate thin sheet of laser. It allows rapid plane illumination for reduced photo-damage and superior axial resolution and contrast. We hereby demonstrate cardiac LSFM (c-LSFM) imaging to assess the functional architecture of zebrafish embryos with a retrospective cardiac synchronization algorithm for four-dimensional reconstruction (3-D space + time). By combining our approach with tissue clearing techniques, we reveal the entire cardiac structures and hypertrabeculation of adult zebrafish hearts in response to doxorubicin treatment. By integrating the resolution enhancement technique with c-LSFM to increase the resolving power under a large field-of-view, we demonstrate the use of low power objective to resolve the entire architecture of large-scale neonatal mouse hearts, revealing the helical orientation of individual myocardial fibers. Therefore, our c-LSFM imaging approach provides multi-scale visualization of architecture and function to drive cardiovascular research with translational implication in congenital heart diseases.

Collaborative Multi-Scale 3d City and Infrastructure Modeling and Simulation

NASA Astrophysics Data System (ADS)

Breunig, M.; Borrmann, A.; Rank, E.; Hinz, S.; Kolbe, T.; Schilcher, M.; Mundani, R.-P.; Jubierre, J. R.; Flurl, M.; Thomsen, A.; Donaubauer, A.; Ji, Y.; Urban, S.; Laun, S.; Vilgertshofer, S.; Willenborg, B.; Menninghaus, M.; Steuer, H.; Wursthorn, S.; Leitloff, J.; Al-Doori, M.; Mazroobsemnani, N.

2017-09-01

Computer-aided collaborative and multi-scale 3D planning are challenges for complex railway and subway track infrastructure projects in the built environment. Many legal, economic, environmental, and structural requirements have to be taken into account. The stringent use of 3D models in the different phases of the planning process facilitates communication and collaboration between the stake holders such as civil engineers, geological engineers, and decision makers. This paper presents concepts, developments, and experiences gained by an interdisciplinary research group coming from civil engineering informatics and geo-informatics banding together skills of both, the Building Information Modeling and the 3D GIS world. New approaches including the development of a collaborative platform and 3D multi-scale modelling are proposed for collaborative planning and simulation to improve the digital 3D planning of subway tracks and other infrastructures. Experiences during this research and lessons learned are presented as well as an outlook on future research focusing on Building Information Modeling and 3D GIS applications for cities of the future.

3D multiscale crack propagation using the XFEM applied to a gas turbine blade

NASA Astrophysics Data System (ADS)

Holl, Matthias; Rogge, Timo; Loehnert, Stefan; Wriggers, Peter; Rolfes, Raimund

2014-01-01

This work presents a new multiscale technique to investigate advancing cracks in three dimensional space. This fully adaptive multiscale technique is designed to take into account cracks of different length scales efficiently, by enabling fine scale domains locally in regions of interest, i.e. where stress concentrations and high stress gradients occur. Due to crack propagation, these regions change during the simulation process. Cracks are modeled using the extended finite element method, such that an accurate and powerful numerical tool is achieved. Restricting ourselves to linear elastic fracture mechanics, the -integral yields an accurate solution of the stress intensity factors, and with the criterion of maximum hoop stress, a precise direction of growth. If necessary, the on the finest scale computed crack surface is finally transferred to the corresponding scale. In a final step, the model is applied to a quadrature point of a gas turbine blade, to compute crack growth on the microscale of a real structure.

Multiscale analysis of the correlation of processing parameters on viscidity of composites fabricated by automated fiber placement

NASA Astrophysics Data System (ADS)

Han, Zhenyu; Sun, Shouzheng; Fu, Yunzhong; Fu, Hongya

2017-10-01

Viscidity is an important physical indicator for assessing fluidity of resin that is beneficial to contact resin with the fibers effectively and reduce manufacturing defects during automated fiber placement (AFP) process. However, the effect of processing parameters on viscidity evolution is rarely studied during AFP process. In this paper, viscidities under different scales are analyzed based on multi-scale analysis method. Firstly, viscous dissipation energy (VDE) within meso-unit under different processing parameters is assessed by using finite element method (FEM). According to multi-scale energy transfer model, meso-unit energy is used as the boundary condition for microscopic analysis. Furthermore, molecular structure of micro-system is built by molecular dynamics (MD) method. And viscosity curves are then obtained by integrating stress autocorrelation function (SACF) with time. Finally, the correlation characteristics of processing parameters to viscosity are revealed by using gray relational analysis method (GRAM). A group of processing parameters is found out to achieve the stability of viscosity and better fluidity of resin.

Multifractality of stock markets based on cumulative distribution function and multiscale multifractal analysis

NASA Astrophysics Data System (ADS)

Lin, Aijing; Shang, Pengjian

2016-04-01

Considering the diverse application of multifractal techniques in natural scientific disciplines, this work underscores the versatility of multiscale multifractal detrended fluctuation analysis (MMA) method to investigate artificial and real-world data sets. The modified MMA method based on cumulative distribution function is proposed with the objective of quantifying the scaling exponent and multifractality of nonstationary time series. It is demonstrated that our approach can provide a more stable and faithful description of multifractal properties in comprehensive range rather than fixing the window length and slide length. Our analyzes based on CDF-MMA method reveal significant differences in the multifractal characteristics in the temporal dynamics between US and Chinese stock markets, suggesting that these two stock markets might be regulated by very different mechanism. The CDF-MMA method is important for evidencing the stable and fine structure of multiscale and multifractal scaling behaviors and can be useful to deepen and broaden our understanding of scaling exponents and multifractal characteristics.

Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

PubMed

Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

Detecting the Reconnection Electron Diffusion Regions in Magnetospheric MultiScale mission high resolution data

NASA Astrophysics Data System (ADS)

Shimoda, E.; Eriksson, S.; Ahmadi, N.; Ergun, R.; Wilder, F. D.; Goodrich, K.

2017-12-01

The Magnetospheric Multi-Scale (MMS) mission resolves the small-scale structure of the Reconnection Electron Diffusion Regions (EDRs) using four spacecraft. We have surveyed two years of MMS data to find the candidates for the EDRs. We searched all the high-resolution segments when Fast Plasma Investigation (FPI) instrument was on. The search criteria are based on measuring the dissipation rate, agyrotropy, a reversal in jet velocity and magnetic field. Once these events were found for MMS1 data, the burst period for the other spacecraft was analyzed. We present our results of the best possible EDR candidates.

Varying electric charge in multiscale spacetimes

NASA Astrophysics Data System (ADS)

Calcagni, Gianluca; Magueijo, João; Fernández, David Rodríguez

2014-01-01

We derive the covariant equations of motion for Maxwell field theory and electrodynamics in multiscale spacetimes with weighted Laplacian. An effective spacetime-dependent electric charge of geometric origin naturally emerges from the theory, thus giving rise to a varying fine-structure constant. The theory is compared with other varying-coupling models, such as those with a varying electric charge or varying speed of light. The theory is also confronted with cosmological observations, which can place constraints on the characteristic scales in the multifractional measure. We note that the model considered here is fundamentally different from those previously proposed in the literature, either of the varying-e or varying-c persuasion.

Energy transfer between a nanosystem and its host fluid: A multiscale factorization approach

NASA Astrophysics Data System (ADS)

Sereda, Yuriy V.; Espinosa-Duran, John M.; Ortoleva, Peter J.

2014-02-01

Energy transfer between a macromolecule or supramolecular assembly and a host medium is considered from the perspective of Newton's equations and Lie-Trotter factorization. The development starts by demonstrating that the energy of the molecule evolves slowly relative to the time scale of atomic collisions-vibrations. The energy is envisioned to be a coarse-grained variable that coevolves with the rapidly fluctuating atomistic degrees of freedom. Lie-Trotter factorization is shown to be a natural framework for expressing this coevolution. A mathematical formalism and workflow for efficient multiscale simulation of energy transfer is presented. Lactoferrin and human papilloma virus capsid-like structure are used for validation.

Multiscale assembly for tissue engineering and regenerative medicine

PubMed Central

Inci, Fatih; Tasoglu, Savas; Erkmen, Burcu; Demirci, Utkan

2015-01-01

Our understanding of cell biology and its integration with materials science has led to technological innovations in the bioengineering of tissue-mimicking grafts that can be utilized in clinical and pharmaceutical applications. Bio-engineering of native-like multiscale building blocks provides refined control over the cellular microenvironment, thus enabling functional tissues. In this review, we focus on assembling building blocks from the biomolecular level to the millimeter scale. We also provide an overview of techniques for assembling molecules, cells, spheroids, and microgels and achieving bottom-up tissue engineering. Additionally, we discuss driving mechanisms for self- and guided assembly to create micro-to-macro scale tissue structures. PMID:25796488

Multiscale simulations on conformational dynamics and membrane interactions of the non-structural 2 (NS2) transmembrane domain.

PubMed

Hung, Huynh Minh; Hang, Tran Dieu; Nguyen, Minh Tho

2016-09-09

Hepatitis C virus (HCV) is one of the most crucial global health issues, in which the HCV non-structural protein 2 (NS2), particularly its three transmembrane segments, plays a crucial role in HCV assembly. In this context, multiscale MD simulations have been applied to investigate the preferred orientation of transmembrane domain of NS2 protein (TNS2) in a POPC bilayer, structural stability and characteristic of intramembrane protein-lipid and protein-protein interaction. Our study indicates that NS2 protein adopts three trans-membrane segments with highly stable α-helix structure in a POPC bilayer and a short helical luminal segment. While the first and second TM segment involved in continuous helical domain, the third TM segment is however cleaved into two sub-segments with different tilt angles via a kink at L87G88. Salt bridges K81-E45, R32-PO4 and R43-PO4 are determined as the key factor to stabilize the structure of TM2 and TM3 which consist of charged residues located in the hydrophobic region of the membrane. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiscale Pores in TBCs for Lower Thermal Conductivity

NASA Astrophysics Data System (ADS)

Zhang, Wei-Wei; Li, Guang-Rong; Zhang, Qiang; Yang, Guan-Jun

2017-08-01

The morphology and pattern (including orientation and aspect ratio) of pores in thermal barrier coatings (TBCs) significantly affect their thermal insulation performance. In this work, finite element analysis was used to comprehensively understand the thermal insulation effect of pores and correlate the effective thermal conductivity with the structure. The results indicated that intersplat pores, and in particular their aspect ratio, dominantly affect the heat transfer in the top coat. The effective thermal conductivity decreased as a function of aspect ratio, since a larger aspect ratio often corresponds to a greater proportion of effective length of the pores. However, in conventional plasma-sprayed TBCs, intersplat pores often fail to maximize thermal insulation due to their distinct lower aspect ratios. Therefore, considering this effect of aspect ratio, a new structure design with multiscale pores is proposed and a corresponding structural model developed to correlate the thermal properties with this pore-rich structure. The predictions of the model are well consistent with experimental data. This study provides comprehensive understanding of the effect of pores on the thermal insulation performance, shedding light on the possibility of structural tailoring to obtain advanced TBCs with lower thermal conductivity.

Molecular systems biology of ErbB1 signaling: bridging the gap through multiscale modeling and high-performance computing.

PubMed

Shih, Andrew J; Purvis, Jeremy; Radhakrishnan, Ravi

2008-12-01

The complexity in intracellular signaling mechanisms relevant for the conquest of many diseases resides at different levels of organization with scales ranging from the subatomic realm relevant to catalytic functions of enzymes to the mesoscopic realm relevant to the cooperative association of molecular assemblies and membrane processes. Consequently, the challenge of representing and quantifying functional or dysfunctional modules within the networks remains due to the current limitations in our understanding of mesoscopic biology, i.e., how the components assemble into functional molecular ensembles. A multiscale approach is necessary to treat a hierarchy of interactions ranging from molecular (nm, ns) to signaling (microm, ms) length and time scales, which necessitates the development and application of specialized modeling tools. Complementary to multiscale experimentation (encompassing structural biology, mechanistic enzymology, cell biology, and single molecule studies) multiscale modeling offers a powerful and quantitative alternative for the study of functional intracellular signaling modules. Here, we describe the application of a multiscale approach to signaling mediated by the ErbB1 receptor which constitutes a network hub for the cell's proliferative, migratory, and survival programs. Through our multiscale model, we mechanistically describe how point-mutations in the ErbB1 receptor can profoundly alter signaling characteristics leading to the onset of oncogenic transformations. Specifically, we describe how the point mutations induce cascading fragility mechanisms at the molecular scale as well as at the scale of the signaling network to preferentially activate the survival factor Akt. We provide a quantitative explanation for how the hallmark of preferential Akt activation in cell-lines harboring the constitutively active mutant ErbB1 receptors causes these cell-lines to be addicted to ErbB1-mediated generation of survival signals. Consequently, inhibition of ErbB1 activity leads to a remarkable therapeutic response in the addicted cell lines.

Magnetospheric Multiscale Observation of Plasma Velocity-Space Cascade: Hermite Representation and Theory.

PubMed

Servidio, S; Chasapis, A; Matthaeus, W H; Perrone, D; Valentini, F; Parashar, T N; Veltri, P; Gershman, D; Russell, C T; Giles, B; Fuselier, S A; Phan, T D; Burch, J

2017-11-17

Plasma turbulence is investigated using unprecedented high-resolution ion velocity distribution measurements by the Magnetospheric Multiscale mission (MMS) in the Earth's magnetosheath. This novel observation of a highly structured particle distribution suggests a cascadelike process in velocity space. Complex velocity space structure is investigated using a three-dimensional Hermite transform, revealing, for the first time in observational data, a power-law distribution of moments. In analogy to hydrodynamics, a Kolmogorov approach leads directly to a range of predictions for this phase-space transport. The scaling theory is found to be in agreement with observations. The combined use of state-of-the-art MMS data sets, novel implementation of a Hermite transform method, and scaling theory of the velocity cascade opens new pathways to the understanding of plasma turbulence and the crucial velocity space features that lead to dissipation in plasmas.

Automation of Hessian-Based Tubularity Measure Response Function in 3D Biomedical Images.

PubMed

Dzyubak, Oleksandr P; Ritman, Erik L

2011-01-01

The blood vessels and nerve trees consist of tubular objects interconnected into a complex tree- or web-like structure that has a range of structural scale 5 μm diameter capillaries to 3 cm aorta. This large-scale range presents two major problems; one is just making the measurements, and the other is the exponential increase of component numbers with decreasing scale. With the remarkable increase in the volume imaged by, and resolution of, modern day 3D imagers, it is almost impossible to make manual tracking of the complex multiscale parameters from those large image data sets. In addition, the manual tracking is quite subjective and unreliable. We propose a solution for automation of an adaptive nonsupervised system for tracking tubular objects based on multiscale framework and use of Hessian-based object shape detector incorporating National Library of Medicine Insight Segmentation and Registration Toolkit (ITK) image processing libraries.

Hydrophobic duck feathers and their simulation on textile substrates for water repellent treatment.

PubMed

Liu, Yuyang; Chen, Xianqiong; Xin, J H

2008-12-01

Inspired by the non-wetting phenomena of duck feathers, the water repellent property of duck feathers was studied at the nanoscale. The microstructures of the duck feather were investigated by a scanning electron microscope (SEM) imaging method through a step-by-step magnifying procedure. The SEM results show that duck feathers have a multi-scale structure and that this multi-scale structure as well as the preening oil are responsible for their super hydrophobic behavior. The microstructures of the duck feather were simulated on textile substrates using the biopolymer chitosan as building blocks through a novel surface solution precipitation (SSP) method, and then the textile substrates were further modified with a silicone compound to achieve low surface energy. The resultant textiles exhibit super water repellent properties, thus providing a simple bionic way to create super hydrophobic surfaces on soft substrates using flexible material as building blocks.

Multiscale structural characterizations of mixed U(iv)-An(iii) oxalates (An(iii) = Pu or Am) combining XAS and XRD measurements.

PubMed

Arab-Chapelet, B; Martin, P M; Costenoble, S; Delahaye, T; Scheinost, A C; Grandjean, S; Abraham, F

2016-04-28

Mixed actinide(III,IV) oxalates of the general formula M2.2UAn(C2O4)5·nH2O (An = Pu or Am and M = H3O(+) and N2H5(+)) have been quantitatively precipitated by oxalic precipitation in nitric acid medium (yield >99%). Thorough multiscale structural characterization using XRD and XAS measurements confirmed the existence of mixed actinide oxalate solid solutions. The XANES analysis confirmed that the oxidation states of the metallic cations, tetravalent for uranium and trivalent for plutonium and americium, are maintained during the precipitation step. EXAFS measurements show that the local environments around U(+IV), Pu(+III) and Am(+III) are comparable, and the actinides are surrounded by ten oxygen atoms from five bidentate oxalate anions. The mean metal-oxygen distances obtained by XAS measurements are in agreement with those calculated from XRD lattice parameters.

Adaptive resolution simulation of oligonucleotides

NASA Astrophysics Data System (ADS)

Netz, Paulo A.; Potestio, Raffaello; Kremer, Kurt

2016-12-01

Nucleic acids are characterized by a complex hierarchical structure and a variety of interaction mechanisms with other molecules. These features suggest the need of multiscale simulation methods in order to grasp the relevant physical properties of deoxyribonucleic acid (DNA) and RNA using in silico experiments. Here we report an implementation of a dual-resolution modeling of a DNA oligonucleotide in physiological conditions; in the presented setup only the nucleotide molecule and the solvent and ions in its proximity are described at the atomistic level; in contrast, the water molecules and ions far from the DNA are represented as computationally less expensive coarse-grained particles. Through the analysis of several structural and dynamical parameters, we show that this setup reliably reproduces the physical properties of the DNA molecule as observed in reference atomistic simulations. These results represent a first step towards a realistic multiscale modeling of nucleic acids and provide a quantitatively solid ground for their simulation using dual-resolution methods.

Multi-scale Modeling of Radiation Damage: Large Scale Data Analysis

NASA Astrophysics Data System (ADS)

Warrier, M.; Bhardwaj, U.; Bukkuru, S.

2016-10-01

Modification of materials in nuclear reactors due to neutron irradiation is a multiscale problem. These neutrons pass through materials creating several energetic primary knock-on atoms (PKA) which cause localized collision cascades creating damage tracks, defects (interstitials and vacancies) and defect clusters depending on the energy of the PKA. These defects diffuse and recombine throughout the whole duration of operation of the reactor, thereby changing the micro-structure of the material and its properties. It is therefore desirable to develop predictive computational tools to simulate the micro-structural changes of irradiated materials. In this paper we describe how statistical averages of the collision cascades from thousands of MD simulations are used to provide inputs to Kinetic Monte Carlo (KMC) simulations which can handle larger sizes, more defects and longer time durations. Use of unsupervised learning and graph optimization in handling and analyzing large scale MD data will be highlighted.

Multiscale modelling and experimentation of hydrogen embrittlement in aerospace materials

NASA Astrophysics Data System (ADS)

Jothi, Sathiskumar

Pulse plated nickel and nickel based superalloys have been used extensively in the Ariane 5 space launcher engines. Large structural Ariane 5 space launcher engine components such as combustion chambers with complex microstructures have usually been manufactured using electrodeposited nickel with advanced pulse plating techniques with smaller parts made of nickel based superalloys joined or welded to the structure to fabricate Ariane 5 space launcher engines. One of the major challenges in manufacturing these space launcher components using newly developed materials is a fundamental understanding of how different materials and microstructures react with hydrogen during welding which can lead to hydrogen induced cracking. The main objective of this research has been to examine and interpret the effects of microstructure on hydrogen diffusion and hydrogen embrittlement in (i) nickel based superalloy 718, (ii) established and (iii) newly developed grades of pulse plated nickel used in the Ariane 5 space launcher engine combustion chamber. Also, the effect of microstructures on hydrogen induced hot and cold cracking and weldability of three different grades of pulse plated nickel were investigated. Multiscale modelling and experimental methods have been used throughout. The effect of microstructure on hydrogen embrittlement was explored using an original multiscale numerical model (exploiting synthetic and real microstructures) and a wide range of material characterization techniques including scanning electron microscopy, 2D and 3D electron back scattering diffraction, in-situ and ex-situ hydrogen charged slow strain rate tests, thermal spectroscopy analysis and the Varestraint weldability test. This research shows that combined multiscale modelling and experimentation is required for a fundamental understanding of microstructural effects in hydrogen embrittlement in these materials. Methods to control the susceptibility to hydrogen induced hot and cold cracking and to improve the resistance to hydrogen embrittlement in aerospace materials are also suggested. This knowledge can play an important role in the development of new hydrogen embrittlement resistant materials. A novel micro/macro-scale coupled finite element method incorporating multi-scale experimental data is presented with which it is possible to perform full scale component analyses in order to investigate hydrogen embrittlement at the design stage. Finally, some preliminary and very encouraging results of grain boundary engineering based techniques to develop alloys that are resistant to hydrogen induced failure are presented. Keywords: Hydrogen embrittlement; Aerospace materials; Ariane 5 combustion chamber; Pulse plated nickel; Nickel based super alloy 718; SSRT test; Weldability test; TDA; SEM/EBSD; Hydrogen induced hot and cold cracking; Multiscale modelling and experimental methods.

Iterative Self-Dual Reconstruction on Radar Image Recovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martins, Charles; Medeiros, Fatima; Ushizima, Daniela

2010-05-21

Imaging systems as ultrasound, sonar, laser and synthetic aperture radar (SAR) are subjected to speckle noise during image acquisition. Before analyzing these images, it is often necessary to remove the speckle noise using filters. We combine properties of two mathematical morphology filters with speckle statistics to propose a signal-dependent noise filter to multiplicative noise. We describe a multiscale scheme that preserves sharp edges while it smooths homogeneous areas, by combining local statistics with two mathematical morphology filters: the alternating sequential and the self-dual reconstruction algorithms. The experimental results show that the proposed approach is less sensitive to varying window sizesmore » when applied to simulated and real SAR images in comparison with standard filters.« less

Synthesis, Characterization And Modeling Of Functionally Graded Multifunctional Hybrid Composites For Extreme Environments

DTIC Science & Technology

2017-04-04

research thrust areas are designed to enable the development of reliable, damage tolerant, lightweight structures with excellent thermal management...46 2. RESEARCH THRUST AREA: MULTISCALE CHARACTERIZATION AND MODELING .................................... 56 2.1 DESIGN OF MATERIALS...The research thrust areas are designed to enable the development of reliable, damage tolerant, lightweight structures with excellent thermal

A structure preserving Lanczos algorithm for computing the optical absorption spectrum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao, Meiyue; Jornada, Felipe H. da; Lin, Lin

2016-11-16

We present a new structure preserving Lanczos algorithm for approximating the optical absorption spectrum in the context of solving full Bethe-Salpeter equation without Tamm-Dancoff approximation. The new algorithm is based on a structure preserving Lanczos procedure, which exploits the special block structure of Bethe-Salpeter Hamiltonian matrices. A recently developed technique of generalized averaged Gauss quadrature is incorporated to accelerate the convergence. We also establish the connection between our structure preserving Lanczos procedure with several existing Lanczos procedures developed in different contexts. Numerical examples are presented to demonstrate the effectiveness of our Lanczos algorithm.

Multiscale Dynamics of Solar Magnetic Structures

NASA Technical Reports Server (NTRS)

Uritsky, Vadim M.; Davila, Joseph M.

2012-01-01

Multiscale topological complexity of the solar magnetic field is among the primary factors controlling energy release in the corona, including associated processes in the photospheric and chromospheric boundaries.We present a new approach for analyzing multiscale behavior of the photospheric magnetic flux underlying these dynamics as depicted by a sequence of high-resolution solar magnetograms. The approach involves two basic processing steps: (1) identification of timing and location of magnetic flux origin and demise events (as defined by DeForest et al.) by tracking spatiotemporal evolution of unipolar and bipolar photospheric regions, and (2) analysis of collective behavior of the detected magnetic events using a generalized version of the Grassberger-Procaccia correlation integral algorithm. The scale-free nature of the developed algorithms makes it possible to characterize the dynamics of the photospheric network across a wide range of distances and relaxation times. Three types of photospheric conditions are considered to test the method: a quiet photosphere, a solar active region (NOAA 10365) in a quiescent non-flaring state, and the same active region during a period of M-class flares. The results obtained show (1) the presence of a topologically complex asymmetrically fragmented magnetic network in the quiet photosphere driven by meso- and supergranulation, (2) the formation of non-potential magnetic structures with complex polarity separation lines inside the active region, and (3) statistical signatures of canceling bipolar magnetic structures coinciding with flaring activity in the active region. Each of these effects can represent an unstable magnetic configuration acting as an energy source for coronal dissipation and heating.

Synergic Investigation Of The Self-Assembly Structure And Mechanism Of Retroviral Capsid Proteins By Solid State NMR, Transmission Electron Microscopy And Multiscale simulation

DTIC Science & Technology

2017-03-29

310 helix. Green: this work. Cyans: solution NMR RSV CA structure in PDB entry 1D1D.[18] Magentas: X-ray crystallography structure of flat hexameric...to combine cryo-electron microscopy and X-ray crystallography , Methods, 49 (2009) 174-180. [8] K.Y. Chan, J. Gumbart, R. McGreevy, J.M. Watermeyer

Multi-scale structures and pasting characteristics of starch in whole-wheat flour treated by superfine grinding.

PubMed

Niu, Meng; Zhang, Binjia; Jia, Caihua; Zhao, Siming

2017-11-01

The multi-scale structures and pasting properties of starch in WWF were investigated after superfine grinding. Five particle size distributions of WWF and their corresponding starch were obtained. The grinding process reduced the particle size of WWF and starch. However, a slight increase of fragments from starch granules was observed with enhanced grinding strength because of the small decrease in starch particle size and the existence of other WWF components that undertook some of shearing force and friction during grinding. A prominent reduction in starch crystallinity was resulted due to the destruction of crystalline structure by grinding. Small-angle X-ray scattering analyses indicated the disordering in starch semi-crystalline lamellae with thinner lamellae thickness. Additionally, the 13 C Nuclear Magnetic Resonance spectra demonstrated the alterations in starch chain conformation by varying peak areas of starch carbons (C1 and C4). Along with these structural changes, Starch pasting characteristics showed substantial variations, indicating decreased viscosities and higher pasting stability. The results suggest that the grinding treatments influenced the structures and pasting properties of starch even at a non-separated state, the changes in starch structures were related to the variations in starch gelatinization characteristics. Copyright © 2017 Elsevier B.V. All rights reserved.

Ecological homogenization of residential macrosystems

Treesearch

Peter M. Groffman; Meghan Avolio; Jeannine Cavender-Bares; Neil D. Bettez; J. Morgan Grove; Sharon J. Hall; Sarah E. Hobbie; Kelli L. Larson; Susannah B. Lerman; Dexter H. Locke; James B. Heffernan; Jennifer L. Morse; Christopher Neill; Kristen C. Nelson; Jarlath O' Neil-Dunne; Diane E. Pataki; Colin Polsky; Rinku Roy Chowdhury; Tara L. E. Trammell

2017-01-01

Similarities in planning, development and culture within urban areas may lead to the convergence of ecological processes on continental scales. Transdisciplinary, multi-scale research is now needed to understand and predict the impact of human-dominated landscapes on ecosystem structure and function.

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

DOE PAGES

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

2015-03-11

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Multi-fluid Dynamics for Supersonic Jet-and-Crossflows and Liquid Plug Rupture

NASA Astrophysics Data System (ADS)

Hassan, Ezeldin A.

Multi-fluid dynamics simulations require appropriate numerical treatments based on the main flow characteristics, such as flow speed, turbulence, thermodynamic state, and time and length scales. In this thesis, two distinct problems are investigated: supersonic jet and crossflow interactions; and liquid plug propagation and rupture in an airway. Gaseous non-reactive ethylene jet and air crossflow simulation represents essential physics for fuel injection in SCRAMJET engines. The regime is highly unsteady, involving shocks, turbulent mixing, and large-scale vortical structures. An eddy-viscosity-based multi-scale turbulence model is proposed to resolve turbulent structures consistent with grid resolution and turbulence length scales. Predictions of the time-averaged fuel concentration from the multi-scale model is improved over Reynolds-averaged Navier-Stokes models originally derived from stationary flow. The response to the multi-scale model alone is, however, limited, in cases where the vortical structures are small and scattered thus requiring prohibitively expensive grids in order to resolve the flow field accurately. Statistical information related to turbulent fluctuations is utilized to estimate an effective turbulent Schmidt number, which is shown to be highly varying in space. Accordingly, an adaptive turbulent Schmidt number approach is proposed, by allowing the resolved field to adaptively influence the value of turbulent Schmidt number in the multi-scale turbulence model. The proposed model estimates a time-averaged turbulent Schmidt number adapted to the computed flowfield, instead of the constant value common to the eddy-viscosity-based Navier-Stokes models. This approach is assessed using a grid-refinement study for the normal injection case, and tested with 30 degree injection, showing improved results over the constant turbulent Schmidt model both in mean and variance of fuel concentration predictions. For the incompressible liquid plug propagation and rupture study, numerical simulations are conducted using an Eulerian-Lagrangian approach with a continuous-interface method. A reconstruction scheme is developed to allow topological changes during plug rupture by altering the connectivity information of the interface mesh. Rupture time is shown to be delayed as the initial precursor film thickness increases. During the plug rupture process, a sudden increase of mechanical stresses on the tube wall is recorded, which can cause tissue damage.

Multiscale study for stochastic characterization of shale samples

NASA Astrophysics Data System (ADS)

Tahmasebi, Pejman; Javadpour, Farzam; Sahimi, Muhammad; Piri, Mohammad

2016-03-01

Characterization of shale reservoirs, which are typically of low permeability, is very difficult because of the presence of multiscale structures. While three-dimensional (3D) imaging can be an ultimate solution for revealing important complexities of such reservoirs, acquiring such images is costly and time consuming. On the other hand, high-quality 2D images, which are widely available, also reveal useful information about shales' pore connectivity and size. Most of the current modeling methods that are based on 2D images use limited and insufficient extracted information. One remedy to the shortcoming is direct use of qualitative images, a concept that we introduce in this paper. We demonstrate that higher-order statistics (as opposed to the traditional two-point statistics, such as variograms) are necessary for developing an accurate model of shales, and describe an efficient method for using 2D images that is capable of utilizing qualitative and physical information within an image and generating stochastic realizations of shales. We then further refine the model by describing and utilizing several techniques, including an iterative framework, for removing some possible artifacts and better pattern reproduction. Next, we introduce a new histogram-matching algorithm that accounts for concealed nanostructures in shale samples. We also present two new multiresolution and multiscale approaches for dealing with distinct pore structures that are common in shale reservoirs. In the multiresolution method, the original high-quality image is upscaled in a pyramid-like manner in order to achieve more accurate global and long-range structures. The multiscale approach integrates two images, each containing diverse pore networks - the nano- and microscale pores - using a high-resolution image representing small-scale pores and, at the same time, reconstructing large pores using a low-quality image. Eventually, the results are integrated to generate a 3D model. The methods are tested on two shale samples for which full 3D samples are available. The quantitative accuracy of the models is demonstrated by computing their morphological and flow properties and comparing them with those of the actual 3D images. The success of the method hinges upon the use of very different low- and high-resolution images.

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.

Structural and metamorphic evolution of serpentinites and rodingites recycled in the Alpine subduction wedge

NASA Astrophysics Data System (ADS)

Zanoni, D.; Rebay, G.; Spalla, M. I.

2015-12-01

Hydration-dehydration of mantle rocks affects the viscosity of the mantle wedge and plays a prominent role in subduction zone tectonics, facilitating marble cake-type instead of large-slice dynamics. An accurate structural and petrologic investigation of serpentinites from orogenic belts, supported by their long-lived structural memory, can help to recognize pressure-sensitive mineral assemblages for deciphering their P-prograde and -retrograde tectonic trajectories. The European Alps preserve large volumes of the hydrated upper part of the oceanic lithosphere that represents the main water carrier into the Alpine subduction zone. Therefore, it is important to understand what happens during subduction when these rocks reach P-T conditions proximal to those that trigger the break-down of serpentine, formed during oceanic metamorphism, to produce olivine and clinopyroxene. Rodingites associated with serpentinites are usually derived from metasomatic ocean floor processes but rodingitization can also happen in subduction environments. Multiscale structural and petrologic analyses of serpentinites and enclosed rodingites have been combined to define the HP mineral assemblages in the Zermatt-Saas ophiolites. They record 3 syn-metamorphic stages of ductile deformation during the Alpine cycle, following the ocean floor history that is testified by structural and metamorphic relics in both rock types. D1 and D2 developed under HP to UHP conditions and D3 under lower P conditions. Syn-D2 assemblages in serpentinites and rodingites indicate conditions of 2.5 ± 0.3 GPa and 600 ± 20°C. This interdisciplinary approach shows that the dominant structural and metamorphic imprint of the Zermatt-Saas eclogitized serpentinites and rodingites developed during the Alpine subduction and that subduction-related serpentinite de-hydration occurred exclusively at Pmax conditions, during D2 deformation. In contrast, in the favourable rodingite bulk composition (Ca-rich), hydrated minerals such as vesuvianite are stable up to the estimated P-climax conditions.

Visualization of Morse connection graphs for topologically rich 2D vector fields.

PubMed

Szymczak, Andrzej; Sipeki, Levente

2013-12-01

Recent advances in vector field topologymake it possible to compute its multi-scale graph representations for autonomous 2D vector fields in a robust and efficient manner. One of these representations is a Morse Connection Graph (MCG), a directed graph whose nodes correspond to Morse sets, generalizing stationary points and periodic trajectories, and arcs - to trajectories connecting them. While being useful for simple vector fields, the MCG can be hard to comprehend for topologically rich vector fields, containing a large number of features. This paper describes a visual representation of the MCG, inspired by previous work on graph visualization. Our approach aims to preserve the spatial relationships between the MCG arcs and nodes and highlight the coherent behavior of connecting trajectories. Using simulations of ocean flow, we show that it can provide useful information on the flow structure. This paper focuses specifically on MCGs computed for piecewise constant (PC) vector fields. In particular, we describe extensions of the PC framework that make it more flexible and better suited for analysis of data on complex shaped domains with a boundary. We also describe a topology simplification scheme that makes our MCG visualizations less ambiguous. Despite the focus on the PC framework, our approach could also be applied to graph representations or topological skeletons computed using different methods.

Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression

PubMed Central

Poole, William; Leinonen, Kalle; Shmulevich, Ilya

2017-01-01

Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C. PMID:28170390

Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression.

PubMed

Poole, William; Leinonen, Kalle; Shmulevich, Ilya; Knijnenburg, Theo A; Bernard, Brady

2017-02-01

Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C.

Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

NASA Astrophysics Data System (ADS)

Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun

2017-11-01

The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.

A Unified Multi-scale Model for Cross-Scale Evaluation and Integration of Hydrological and Biogeochemical Processes

NASA Astrophysics Data System (ADS)

Liu, C.; Yang, X.; Bailey, V. L.; Bond-Lamberty, B. P.; Hinkle, C.

2013-12-01

Mathematical representations of hydrological and biogeochemical processes in soil, plant, aquatic, and atmospheric systems vary with scale. Process-rich models are typically used to describe hydrological and biogeochemical processes at the pore and small scales, while empirical, correlation approaches are often used at the watershed and regional scales. A major challenge for multi-scale modeling is that water flow, biogeochemical processes, and reactive transport are described using different physical laws and/or expressions at the different scales. For example, the flow is governed by the Navier-Stokes equations at the pore-scale in soils, by the Darcy law in soil columns and aquifer, and by the Navier-Stokes equations again in open water bodies (ponds, lake, river) and atmosphere surface layer. This research explores whether the physical laws at the different scales and in different physical domains can be unified to form a unified multi-scale model (UMSM) to systematically investigate the cross-scale, cross-domain behavior of fundamental processes at different scales. This presentation will discuss our research on the concept, mathematical equations, and numerical execution of the UMSM. Three-dimensional, multi-scale hydrological processes at the Disney Wilderness Preservation (DWP) site, Florida will be used as an example for demonstrating the application of the UMSM. In this research, the UMSM was used to simulate hydrological processes in rooting zones at the pore and small scales including water migration in soils under saturated and unsaturated conditions, root-induced hydrological redistribution, and role of rooting zone biogeochemical properties (e.g., root exudates and microbial mucilage) on water storage and wetting/draining. The small scale simulation results were used to estimate effective water retention properties in soil columns that were superimposed on the bulk soil water retention properties at the DWP site. The UMSM parameterized from smaller scale simulations were then used to simulate coupled flow and moisture migration in soils in saturated and unsaturated zones, surface and groundwater exchange, and surface water flow in streams and lakes at the DWP site under dynamic precipitation conditions. Laboratory measurements of soil hydrological and biogeochemical properties are used to parameterize the UMSM at the small scales, and field measurements are used to evaluate the UMSM.

Multiscale study of metal nanoparticles

NASA Astrophysics Data System (ADS)

Lee, Byeongchan

Extremely small structures with reduced dimensionality have emerged as a scientific motif for their interesting properties. In particular, metal nanoparticles have been identified as a fundamental material in many catalytic activities; as a consequence, a better understanding of structure-function relationship of nanoparticles has become crucial. The functional analysis of nanoparticles, reactivity for example, requires an accurate method at the electronic structure level, whereas the structural analysis to find energetically stable local minima is beyond the scope of quantum mechanical methods as the computational cost becomes prohibitingly high. The challenge is that the inherent length scale and accuracy associated with any single method hardly covers the broad scale range spanned by both structural and functional analyses. In order to address this, and effectively explore the energetics and reactivity of metal nanoparticles, a hierarchical multiscale modeling is developed, where methodologies of different length scales, i.e. first principles density functional theory, atomistic calculations, and continuum modeling, are utilized in a sequential fashion. This work has focused on identifying the essential information that bridges two different methods so that a successive use of different methods is seamless. The bond characteristics of low coordination systems have been obtained with first principles calculations, and incorporated into the atomistic simulation. This also rectifies the deficiency of conventional interatomic potentials fitted to bulk properties, and improves the accuracy of atomistic calculations for nanoparticles. For the systematic shape selection of nanoparticles, we have improved the Wulff-type construction using a semi-continuum approach, in which atomistic surface energetics and crystallinity of materials are added on to the continuum framework. The developed multiscale modeling scheme is applied to the rational design of platinum nanoparticles in the range of 2.4 nm to 3.1 nm: energetically favorable structures have been determined in terms of semi-continuum binding energy, and the reactivity of the selected nanoparticle has been investigated based on local density of states from first principles calculations. The calculation suggests that the reactivity landscape of particles is more complex than the simple reactivity of clean surfaces, and the reactivity towards a particular reactant can be predicted for a given structure.

Toward a multiscale modeling framework for understanding serotonergic function

PubMed Central

Wong-Lin, KongFatt; Wang, Da-Hui; Moustafa, Ahmed A; Cohen, Jeremiah Y; Nakamura, Kae

2017-01-01

Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels. At each level of organization, we will discuss the experimental work accompanied by related computational modeling work. We then suggest that a multiscale modeling approach that integrates the various levels of neurobiological organization could potentially transform the way we understand the complex functions associated with serotonin. PMID:28417684

Multi-scale evaporator architectures for geothermal binary power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sabau, Adrian S; Nejad, Ali; Klett, James William

2016-01-01

In this paper, novel geometries of heat exchanger architectures are proposed for evaporators that are used in Organic Rankine Cycles. A multi-scale heat exchanger concept was developed by employing successive plenums at several length-scale levels. Flow passages contain features at both macro-scale and micro-scale, which are designed from Constructal Theory principles. Aside from pumping power and overall thermal resistance, several factors were considered in order to fully assess the performance of the new heat exchangers, such as weight of metal structures, surface area per unit volume, and total footprint. Component simulations based on laminar flow correlations for supercritical R134a weremore » used to obtain performance indicators.« less

Multiscale Modeling in Computational Biomechanics: Determining Computational Priorities and Addressing Current Challenges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tawhai, Merryn; Bischoff, Jeff; Einstein, Daniel R.

2009-05-01

Abstract In this article, we describe some current multiscale modeling issues in computational biomechanics from the perspective of the musculoskeletal and respiratory systems and mechanotransduction. First, we outline the necessity of multiscale simulations in these biological systems. Then we summarize challenges inherent to multiscale biomechanics modeling, regardless of the subdiscipline, followed by computational challenges that are system-specific. We discuss some of the current tools that have been utilized to aid research in multiscale mechanics simulations, and the priorities to further the field of multiscale biomechanics computation.

Structural Technology Evaluation and Analysis Program (STEAP). Delivery Order 0046: Multiscale Modeling of Composite Structures Subjected to Cyclic Loading

DTIC Science & Technology

2012-09-01

on transformation field analysis [19], proper orthogonal decomposition [63], eigenstrains [23], and others [1, 29, 39] have brought significant...commercial finite element software (Abaqus) along with the user material subroutine utility ( UMAT ) is employed to solve these problems. In this section...Symmetric Coefficients TFA: Transformation Field Analysis UMAT : User Material Subroutine

Multiscale tomography of buried magnetic structures: its use in the localization and characterization of archaeological structures

NASA Astrophysics Data System (ADS)

Saracco, Ginette; Moreau, Frédérique; Mathé, Pierre-Etienne; Hermitte, Daniel; Michel, Jean-Marie

2007-10-01

We have previously developed a method for characterizing and localizing `homogeneous' buried sources, from the measure of potential anomalies at a fixed height above ground (magnetic, electric and gravity). This method is based on potential theory and uses the properties of the Poisson kernel (real by definition) and the continuous wavelet theory. Here, we relax the assumption on sources and introduce a method that we call the `multiscale tomography'. Our approach is based on the harmonic extension of the observed magnetic field to produce a complex source by use of a complex Poisson kernel solution of the Laplace equation for complex potential field. A phase and modulus are defined. We show that the phase provides additional information on the total magnetic inclination and the structure of sources, while the modulus allows us to characterize its spatial location, depth and `effective degree'. This method is compared to the `complex dipolar tomography', extension of the Patella method that we previously developed. We applied both methods and a classical electrical resistivity tomography to detect and localize buried archaeological structures like antique ovens from magnetic measurements on the Fox-Amphoux site (France). The estimates are then compared with the results of excavations.

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

PubMed Central

Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

2016-01-01

A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

Compressibility-aware media retargeting with structure preserving.

PubMed

Wang, Shu-Fan; Lai, Shang-Hong

2011-03-01

A number of algorithms have been proposed for intelligent image/video retargeting with image content retained as much as possible. However, they usually suffer from some artifacts in the results, such as ridge or structure twist. In this paper, we present a structure-preserving media retargeting technique that preserves the content and image structure as best as possible. Different from the previous pixel or grid based methods, we estimate the image content saliency from the structure of the content. A block structure energy is introduced with a top-down strategy to constrain the image structure inside to deform uniformly in either x or y direction. However, the flexibilities for retargeting are quite different for different images. To cope with this problem, we propose a compressibility assessment scheme for media retargeting by combining the entropies of image gradient magnitude and orientation distributions. Thus, the resized media is produced to preserve the image content and structure as best as possible. Our experiments demonstrate that the proposed method provides resized images/videos with better preservation of content and structure than those by the previous methods.

Multiscale molecular dynamics simulations of rotary motor proteins.

PubMed

Ekimoto, Toru; Ikeguchi, Mitsunori

2018-04-01

Protein functions require specific structures frequently coupled with conformational changes. The scale of the structural dynamics of proteins spans from the atomic to the molecular level. Theoretically, all-atom molecular dynamics (MD) simulation is a powerful tool to investigate protein dynamics because the MD simulation is capable of capturing conformational changes obeying the intrinsically structural features. However, to study long-timescale dynamics, efficient sampling techniques and coarse-grained (CG) approaches coupled with all-atom MD simulations, termed multiscale MD simulations, are required to overcome the timescale limitation in all-atom MD simulations. Here, we review two examples of rotary motor proteins examined using free energy landscape (FEL) analysis and CG-MD simulations. In the FEL analysis, FEL is calculated as a function of reaction coordinates, and the long-timescale dynamics corresponding to conformational changes is described as transitions on the FEL surface. Another approach is the utilization of the CG model, in which the CG parameters are tuned using the fluctuation matching methodology with all-atom MD simulations. The long-timespan dynamics is then elucidated straightforwardly by using CG-MD simulations.

Multiscale Computational Design Optimization of Copper-Strengthened Steel for High Cycle Fatigue

DTIC Science & Technology

2010-03-19

strain energy) and (3) modeling of a slip band (of PSB ladder underlying structure) and attendant crack initiation process. 15. SUBJECT TERMS 16...energy). (C) A modeling of a slip band (of PSB ladder underlying structure) and attendant crack initiation process. Major results obtained are...differentiate the morphology from others, e.g., vein and planar structures of dislocations. Results and Discussion for (C) (C-1) Modeling PSB For modeling

Extended Multiscale Image Segmentation for Castellated Wall Management

NASA Astrophysics Data System (ADS)

Sakamoto, M.; Tsuguchi, M.; Chhatkuli, S.; Satoh, T.

2018-05-01

Castellated walls are positioned as tangible cultural heritage, which require regular maintenance to preserve their original state. For the demolition and repair work of the castellated wall, it is necessary to identify the individual stones constituting the wall. However, conventional approaches using laser scanning or integrated circuits (IC) tags were very time-consuming and cumbersome. Therefore, we herein propose an efficient approach for castellated wall management based on an extended multiscale image segmentation technique. In this approach, individual stone polygons are extracted from the castellated wall image and are associated with a stone management database. First, to improve the performance of the extraction of individual stone polygons having a convex shape, we developed a new shape criterion named convex hull fitness in the image segmentation process and confirmed its effectiveness. Next, we discussed the stone management database and its beneficial utilization in the repair work of castellated walls. Subsequently, we proposed irregular-shape indexes that are helpful for evaluating the stone shape and the stability of the stone arrangement state in castellated walls. Finally, we demonstrated an application of the proposed method for a typical castellated wall in Japan. Consequently, we confirmed that the stone polygons can be extracted with an acceptable level. Further, the condition of the shapes and the layout of the stones could be visually judged with the proposed irregular-shape indexes.

Multiscale Multiphysics Caprock Seal Analysis: A Case Study of the Farnsworth Unit, Texas, USA

NASA Astrophysics Data System (ADS)

Heath, J. E.; Dewers, T. A.; Mozley, P.

2015-12-01

Caprock sealing behavior depends on coupled processes that operate over a variety of length and time scales. Capillary sealing behavior depends on nanoscale pore throats and interfacial fluid properties. Larger-scale sedimentary architecture, fractures, and faults may govern properties of potential "seal-bypass" systems. We present the multiscale multiphysics investigation of sealing integrity of the caprock system that overlies the Morrow Sandstone reservoir, Farnsworth Unit, Texas. The Morrow Sandstone is the target injection unit for an on-going combined enhanced oil recovery-CO2 storage project by the Southwest Regional Partnership on Carbon Sequestration (SWP). Methods include small-to-large scale measurement techniques, including: focused ion beam-scanning electron microscopy; laser scanning confocal microscopy; electron and optical petrography; core examinations of sedimentary architecture and fractures; geomechanical testing; and a noble gas profile through sealing lithologies into the reservoir, as preserved from fresh core. The combined data set is used as part of a performance assessment methodology. The authors gratefully acknowledge the U.S. Department of Energy's (DOE) National Energy Technology Laboratory for sponsoring this project through the SWP under Award No. DE-FC26-05NT42591. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Multi-Scale Computational Modeling of Two-Phased Metal Using GMC Method

NASA Technical Reports Server (NTRS)

Moghaddam, Masoud Ghorbani; Achuthan, A.; Bednacyk, B. A.; Arnold, S. M.; Pineda, E. J.

2014-01-01

A multi-scale computational model for determining plastic behavior in two-phased CMSX-4 Ni-based superalloys is developed on a finite element analysis (FEA) framework employing crystal plasticity constitutive model that can capture the microstructural scale stress field. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, GMC as stand-alone is validated by analyzing a repeating unit cell (RUC) as a two-phased sample with 72.9% volume fraction of gamma'-precipitate in the gamma-matrix phase and comparing the results with those predicted by finite element analysis (FEA) models incorporating the same crystal plasticity constitutive model. The global stress-strain behavior and the local field quantity distributions predicted by GMC demonstrated good agreement with FEA. High computational saving, at the expense of some accuracy in the components of local tensor field quantities, was obtained with GMC. Finally, the capability of the developed multi-scale model linking FEA and GMC to solve real life sized structures is demonstrated by analyzing an engine disc component and determining the microstructural scale details of the field quantities.

Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

PubMed

Gao, Guangwei; Yang, Jian; Jing, Xiaoyuan; Huang, Pu; Hua, Juliang; Yue, Dong

2016-01-01

In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

Towards a new multiscale air quality transport model using the fully unstructured anisotropic adaptive mesh technology of Fluidity (version 4.1.9)

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-10-01

An integrated method of advanced anisotropic hr-adaptive mesh and discretization numerical techniques has been, for first time, applied to modelling of multiscale advection-diffusion problems, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been set up for two-dimensional (2-D) advection phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes. Performance achieved in 3-D simulation of power plant plumes indicates that this new adaptive multiscale model has the potential to provide accurate air quality modelling solutions effectively.

Automatic analysis of diabetic peripheral neuropathy using multi-scale quantitative morphology of nerve fibres in corneal confocal microscopy imaging.

PubMed

Dabbah, M A; Graham, J; Petropoulos, I N; Tavakoli, M; Malik, R A

2011-10-01

Diabetic peripheral neuropathy (DPN) is one of the most common long term complications of diabetes. Corneal confocal microscopy (CCM) image analysis is a novel non-invasive technique which quantifies corneal nerve fibre damage and enables diagnosis of DPN. This paper presents an automatic analysis and classification system for detecting nerve fibres in CCM images based on a multi-scale adaptive dual-model detection algorithm. The algorithm exploits the curvilinear structure of the nerve fibres and adapts itself to the local image information. Detected nerve fibres are then quantified and used as feature vectors for classification using random forest (RF) and neural networks (NNT) classifiers. We show, in a comparative study with other well known curvilinear detectors, that the best performance is achieved by the multi-scale dual model in conjunction with the NNT classifier. An evaluation of clinical effectiveness shows that the performance of the automated system matches that of ground-truth defined by expert manual annotation. Copyright © 2011 Elsevier B.V. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, W.; Zhu, W. D.; Smith, S. A.

While structural damage detection based on flexural vibration shapes, such as mode shapes and steady-state response shapes under harmonic excitation, has been well developed, little attention is paid to that based on longitudinal vibration shapes that also contain damage information. This study originally formulates a slope vibration shape for damage detection in bars using longitudinal vibration shapes. To enhance noise robustness of the method, a slope vibration shape is transformed to a multiscale slope vibration shape in a multiscale domain using wavelet transform, which has explicit physical implication, high damage sensitivity, and noise robustness. These advantages are demonstrated in numericalmore » cases of damaged bars, and results show that multiscale slope vibration shapes can be used for identifying and locating damage in a noisy environment. A three-dimensional (3D) scanning laser vibrometer is used to measure the longitudinal steady-state response shape of an aluminum bar with damage due to reduced cross-sectional dimensions under harmonic excitation, and results show that the method can successfully identify and locate the damage. Slopes of longitudinal vibration shapes are shown to be suitable for damage detection in bars and have potential for applications in noisy environments.« less

Design of microcamera for field curvature and distortion correction in monocentric multiscale foveated imaging system

NASA Astrophysics Data System (ADS)

Wu, Xiongxiong; Wang, Xiaorui; Zhang, Jianlei; Yuan, Ying; Chen, Xiaoxiang

2017-04-01

To realize large field of view (FOV) and high-resolution dynamic gaze of the moving target, this paper proposes the monocentric multiscale foveated (MMF) imaging system based on monocentric multiscale design and foveated imaging. First we present the MMF imaging system concept. Then we analyze large field curvature and distortion of the secondary image when the spherical intermediate image produced by the primary monocentric objective lens is relayed by the microcameras. Further a type of zoom endoscope objective lens is selected as the initial structure and optimized to minimize the field curvature and distortion with ZEMAX optical design software. The simulation results show that the maximum field curvature in full field of view is below 0.25 mm and the maximum distortion in full field of view is below 0.6%, which can meet the requirements of the microcamera in the proposed MMF imaging system. In addition, a simple doublet is used to design the foveated imaging system. Results of the microcamera together with the foveated imager compose the results of the whole MMF imaging system.

A coupling method for a cardiovascular simulation model which includes the Kalman filter.

PubMed

Hasegawa, Yuki; Shimayoshi, Takao; Amano, Akira; Matsuda, Tetsuya

2012-01-01

Multi-scale models of the cardiovascular system provide new insight that was unavailable with in vivo and in vitro experiments. For the cardiovascular system, multi-scale simulations provide a valuable perspective in analyzing the interaction of three phenomenons occurring at different spatial scales: circulatory hemodynamics, ventricular structural dynamics, and myocardial excitation-contraction. In order to simulate these interactions, multiscale cardiovascular simulation systems couple models that simulate different phenomena. However, coupling methods require a significant amount of calculation, since a system of non-linear equations must be solved for each timestep. Therefore, we proposed a coupling method which decreases the amount of calculation by using the Kalman filter. In our method, the Kalman filter calculates approximations for the solution to the system of non-linear equations at each timestep. The approximations are then used as initial values for solving the system of non-linear equations. The proposed method decreases the number of iterations required by 94.0% compared to the conventional strong coupling method. When compared with a smoothing spline predictor, the proposed method required 49.4% fewer iterations.

Multi-scale damage modelling in a ceramic matrix composite using a finite-element microstructure meshfree methodology

PubMed Central

2016-01-01

The problem of multi-scale modelling of damage development in a SiC ceramic fibre-reinforced SiC matrix ceramic composite tube is addressed, with the objective of demonstrating the ability of the finite-element microstructure meshfree (FEMME) model to introduce important aspects of the microstructure into a larger scale model of the component. These are particularly the location, orientation and geometry of significant porosity and the load-carrying capability and quasi-brittle failure behaviour of the fibre tows. The FEMME model uses finite-element and cellular automata layers, connected by a meshfree layer, to efficiently couple the damage in the microstructure with the strain field at the component level. Comparison is made with experimental observations of damage development in an axially loaded composite tube, studied by X-ray computed tomography and digital volume correlation. Recommendations are made for further development of the model to achieve greater fidelity to the microstructure. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242308

Asymmetric multiscale multifractal analysis of wind speed signals

NASA Astrophysics Data System (ADS)

Zhang, Xiaonei; Zeng, Ming; Meng, Qinghao

We develop a new method called asymmetric multiscale multifractal analysis (A-MMA) to explore the multifractality and asymmetric autocorrelations of the signals with a variable scale range. Three numerical experiments are provided to demonstrate the effectiveness of our approach. Then, the proposed method is applied to investigate multifractality and asymmetric autocorrelations of difference sequences between wind speed fluctuations with uptrends or downtrends. The results show that these sequences appear to be far more complex and contain abundant fractal dynamics information. Through analyzing the Hurst surfaces of nine difference sequences, we found that all series exhibit multifractal properties and multiscale structures. Meanwhile, the asymmetric autocorrelations are observed in all variable scale ranges and the asymmetry results are of good consistency within a certain spatial range. The sources of multifractality and asymmetry in nine difference series are further discussed using the corresponding shuffled series and surrogate series. We conclude that the multifractality of these series is due to both long-range autocorrelation and broad probability density function, but the major source of multifractality is long-range autocorrelation, and the source of asymmetry is affected by the spatial distance.

High-Efficiency Multiscale Modeling of Cell Deformations in Confined Microenvironments in Microcirculation and Microfluidic Devices

NASA Astrophysics Data System (ADS)

Lu, Huijie; Peng, Zhangli

2017-11-01

Our goal is to develop a high-efficiency multiscale modeling method to predict the stress and deformation of cells during the interactions with their microenvironments in microcirculation and microfluidic devices, including red blood cells (RBCs) and circulating tumor cells (CTCs). There are more than 1 billion people in the world suffering from RBC diseases, e.g. anemia, sickle cell diseases, and malaria. The mechanical properties of RBCs are changed in these diseases due to molecular structure alternations, which is not only important for understanding the disease pathology but also provides an opportunity for diagnostics. On the other hand, the mechanical properties of cancer cells are also altered compared to healthy cells. This can lead to acquired ability to cross the narrow capillary networks and endothelial gaps, which is crucial for metastasis, the leading cause of cancer mortality. Therefore, it is important to predict the deformation and stress of RBCs and CTCs in microcirculations. We are developing a high-efficiency multiscale model of cell-fluid interaction to study these two topics.

TreeNetViz: revealing patterns of networks over tree structures.

PubMed

Gou, Liang; Zhang, Xiaolong Luke

2011-12-01

Network data often contain important attributes from various dimensions such as social affiliations and areas of expertise in a social network. If such attributes exhibit a tree structure, visualizing a compound graph consisting of tree and network structures becomes complicated. How to visually reveal patterns of a network over a tree has not been fully studied. In this paper, we propose a compound graph model, TreeNet, to support visualization and analysis of a network at multiple levels of aggregation over a tree. We also present a visualization design, TreeNetViz, to offer the multiscale and cross-scale exploration and interaction of a TreeNet graph. TreeNetViz uses a Radial, Space-Filling (RSF) visualization to represent the tree structure, a circle layout with novel optimization to show aggregated networks derived from TreeNet, and an edge bundling technique to reduce visual complexity. Our circular layout algorithm reduces both total edge-crossings and edge length and also considers hierarchical structure constraints and edge weight in a TreeNet graph. These experiments illustrate that the algorithm can reduce visual cluttering in TreeNet graphs. Our case study also shows that TreeNetViz has the potential to support the analysis of a compound graph by revealing multiscale and cross-scale network patterns. © 2011 IEEE

SU-E-I-87: Automated Liver Segmentation Method for CBCT Dataset by Combining Sparse Shape Composition and Probabilistic Atlas Construction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Dengwang; Liu, Li; Chen, Jinhu

2014-06-01

Purpose: The aiming of this study was to extract liver structures for daily Cone beam CT (CBCT) images automatically. Methods: Datasets were collected from 50 intravenous contrast planning CT images, which were regarded as training dataset for probabilistic atlas and shape prior model construction. Firstly, probabilistic atlas and shape prior model based on sparse shape composition (SSC) were constructed by iterative deformable registration. Secondly, the artifacts and noise were removed from the daily CBCT image by an edge-preserving filtering using total variation with L1 norm (TV-L1). Furthermore, the initial liver region was obtained by registering the incoming CBCT image withmore » the atlas utilizing edge-preserving deformable registration with multi-scale strategy, and then the initial liver region was converted to surface meshing which was registered with the shape model where the major variation of specific patient was modeled by sparse vectors. At the last stage, the shape and intensity information were incorporated into joint probabilistic model, and finally the liver structure was extracted by maximum a posteriori segmentation.Regarding the construction process, firstly the manually segmented contours were converted into meshes, and then arbitrary patient data was chosen as reference image to register with the rest of training datasets by deformable registration algorithm for constructing probabilistic atlas and prior shape model. To improve the efficiency of proposed method, the initial probabilistic atlas was used as reference image to register with other patient data for iterative construction for removing bias caused by arbitrary selection. Results: The experiment validated the accuracy of the segmentation results quantitatively by comparing with the manually ones. The volumetric overlap percentage between the automatically generated liver contours and the ground truth were on an average 88%–95% for CBCT images. Conclusion: The experiment demonstrated that liver structures of CBCT with artifacts can be extracted accurately for following adaptive radiation therapy. This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)« less

Community Multiscale Air Quality Model

EPA Science Inventory

The U.S. EPA developed the Community Multiscale Air Quality (CMAQ) system to apply a “one atmosphere” multiscale and multi-pollutant modeling approach based mainly on the “first principles” description of the atmosphere. The multiscale capability is supported by the governing di...

Seismic Velocity Structure of the Pacific Upper Mantle in the NoMelt Region from Finite-Frequency Traveltime Tomography

NASA Astrophysics Data System (ADS)

Hung, S. H.; Lin, P. Y.; Gaherty, J. B.; Russell, J. B.; Jin, G.; Collins, J. A.; Lizarralde, D.; Evans, R. L.; Hirth, G.

2017-12-01

Surface wave dispersion and magnetotelluric survey from the NoMelt Experiment conducted on 70 Ma central Pacific seafloor revealed an electrically resistive, high shear wave velocity lid of 80 km thick underlain by a non-highly conductive, low-velocity layer [Sarafian et al., 2015; Lin et al., 2016]. The vertical structure of the upper mantle consistent with these observational constraints suggests a plausible convection scenario, where the seismically fast, dehydrated lithosphere preserving very strong fossil spreading fabric moves at a constant plate speed over the hydrated, melt-free athenospheric mantle with the presence of either pressure-driven return flow or thermally-driven small scale circulation. To explore 3-D variations in compressional shear wave velocities related to the lithospheric and asthenospheric mantle dynamics, we employ a multichannel cross correlation method to measure relative traveltime residuals based on the vertical P and traverse S waveforms filtered at 10-33 s from telseismic earthquakes at epicentral distance between 30 and 98 degrees. The obtained P and S residuals show on average peak-to-peak variations of ±0.5 s and ±1 s, respectively, across the NoMelt OBS array. Particularly, the P residuals for most of the events display an asymmetrical pattern with respect to an axis oriented nearly N-S to NE-SW through the array. Preliminary ray-based P tomography results reveal similar asymmetric variations in the uppermost 100 km mantle. To verify the resulting structural features, we will further perform both the P and S traveltime tomography and resolution tests based on a multiscale finite-frequency approach which properly takes into account both the 3D off-path sensitivities of the measured residuals and data-adaptive resolution of the model.

Bioinspired Omnidirectional Self-Stable Reflectors with Multiscale Hierarchical Structures.

PubMed

Han, Zhiwu; Mu, Zhengzhi; Li, Bo; Feng, Xiaoming; Wang, Ze; Zhang, Junqiu; Niu, Shichao; Ren, Luquan

2017-08-30

Structured surfaces, demonstrating various wondrous physicochemical performances, are ubiquitous phenomena in nature. Butterfly wings with impressive structural colors are an interesting example for multiscale hierarchical structures (MHSs). However, most natural structural colors are relatively unstable and highly sensitive to incident angles, which limit their potential practical applications to a certain extent. Here, we reported a bioinspired color reflector with omnidirectional reflective self-stable (ORS) properties, which is inspired by the wing scales of Papilio palinurus butterfly. Through experimental exploration and theoretical analysis, it was found that the vivid colors of such butterfly wings are structure-based and possess novel ORS properties, which attributes to the multiple optical actions between light and the complex structures coupling the inverse opal-like structures (IOSs) and stacked lamellar ridges (SLRs). On the basis of this, we designed and successfully fabricated the SiO 2 -based bioinspired color reflectors (BCRs) through a facile and effective biotemplate method. It was confirmed that the MHSs in biotemplate are inherited by the obtained SiO 2 -based BCRs. More importantly, the SiO 2 -based BCRs also demonstrated the similar ORS properties in a wide wavelength range. We forcefully anticipate that the reported MHS-based ORS performance discovered in butterfly wing scales here could offer new thoughts for scientists to solve unstable reflection issues in particular optical field. The involved biotemplate fabrication method offers a facile and effective strategy for fabricating functional nanomaterials or bioinspired nanodevices with 3D complex nanostructures, such as structured optical devices, displays, and optoelectronic equipment.

Developing Higher-Order Materials Knowledge Systems

NASA Astrophysics Data System (ADS)

Fast, Anthony Nathan

2011-12-01

Advances in computational materials science and novel characterization techniques have allowed scientists to probe deeply into a diverse range of materials phenomena. These activities are producing enormous amounts of information regarding the roles of various hierarchical material features in the overall performance characteristics displayed by the material. Connecting the hierarchical information over disparate domains is at the crux of multiscale modeling. The inherent challenge of performing multiscale simulations is developing scale bridging relationships to couple material information between well separated length scales. Much progress has been made in the development of homogenization relationships which replace heterogeneous material features with effective homogenous descriptions. These relationships facilitate the flow of information from lower length scales to higher length scales. Meanwhile, most localization relationships that link the information from a from a higher length scale to a lower length scale are plagued by computationally intensive techniques which are not readily integrated into multiscale simulations. The challenge of executing fully coupled multiscale simulations is augmented by the need to incorporate the evolution of the material structure that may occur under conditions such as material processing. To address these challenges with multiscale simulation, a novel framework called the Materials Knowledge System (MKS) has been developed. This methodology efficiently extracts, stores, and recalls microstructure-property-processing localization relationships. This approach is built on the statistical continuum theories developed by Kroner that express the localization of the response field at the microscale using a series of highly complex convolution integrals, which have historically been evaluated analytically. The MKS approach dramatically improves the accuracy of these expressions by calibrating the convolution kernels in these expressions to results from previously validated physics-based models. These novel tools have been validated for the elastic strain localization in moderate contrast dual-phase composites by direct comparisons with predictions from finite element model. The versatility of the approach is further demonstrated by its successful application to capturing the structure evolution during spinodal decomposition of a binary alloy. Lastly, some key features in the future application of the MKS approach are developed using the Portevin-le Chaterlier effect. It has been shown with these case studies that the MKS approach is capable of accurately reproducing the results from physics based models with a drastic reduction in computational requirements.

Glimpse: Sparsity based weak lensing mass-mapping tool

NASA Astrophysics Data System (ADS)

Lanusse, F.; Starck, J.-L.; Leonard, A.; Pires, S.

2018-02-01

Glimpse, also known as Glimpse2D, is a weak lensing mass-mapping tool that relies on a robust sparsity-based regularization scheme to recover high resolution convergence from either gravitational shear alone or from a combination of shear and flexion. Including flexion allows the supplementation of the shear on small scales in order to increase the sensitivity to substructures and the overall resolution of the convergence map. To preserve all available small scale information, Glimpse avoids any binning of the irregularly sampled input shear and flexion fields and treats the mass-mapping problem as a general ill-posed inverse problem, regularized using a multi-scale wavelet sparsity prior. The resulting algorithm incorporates redshift, reduced shear, and reduced flexion measurements for individual galaxies and is made highly efficient by the use of fast Fourier estimators.

Experimental evaluation of multiscale tendon mechanics.

PubMed

Fang, Fei; Lake, Spencer P

2017-07-01

Tendon's primary function is a mechanical link between muscle and bone. The hierarchical structure of tendon and specific compositional constituents are believed to be critical for proper mechanical function. With increased appreciation for tendon importance and the development of various technological advances, this review paper summarizes recent experimental approaches that have been used to study multiscale tendon mechanics, includes an overview of studies that have evaluated the role of specific tissue constituents, and also proposes challenges/opportunities facing tendon study. Tendon has been demonstrated to have specific structural characteristics (e.g., multi-level hierarchy, crimp pattern, helix) and complex mechanical properties (e.g., non-linearity, anisotropy, viscoelasticity). Physical mechanisms including uncrimping, fiber sliding, and collagen reorganization have been shown to govern tendon mechanical responses under both static and dynamic loading. Several tendon constituents with relatively small quantities have been suggested to play a role in its mechanics, although some results are conflicting. Further research should be performed to understand the interplay and communication of tendon mechanical properties across levels of the hierarchical structure, and further show how each of these components contribute to tendon mechanics. The studies summarized and discussed in this review have helped elucidate important aspects of multiscale tendon mechanics, which is a prerequisite for analyzing stress/strain transfer between multiple scales and identifying key principles of mechanotransduction. This information could further facilitate interpreting the functional diversity of tendons from different species, different locations, and even different developmental stages, and then better understand and identify fundamental concepts related to tendon degeneration, disease, and healing. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:1353-1365, 2017. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Hyperlipidemia affects multiscale structure and strength of murine femur.

PubMed

Ascenzi, Maria-Grazia; Lutz, Andre; Du, Xia; Klimecky, Laureen; Kawas, Neal; Hourany, Talia; Jahng, Joelle; Chin, Jesse; Tintut, Yin; Nackenhors, Udo; Keyak, Joyce

2014-07-18

To improve bone strength prediction beyond limitations of assessment founded solely on the bone mineral component, we investigated the effect of hyperlipidemia, present in more than 40% of osteoporotic patients, on multiscale structure of murine bone. Our overarching purpose is to estimate bone strength accurately, to facilitate mitigating fracture morbidity and mortality in patients. Because (i) orientation of collagen type I affects, independently of degree of mineralization, cortical bone׳s micro-structural strength; and, (ii) hyperlipidemia affects collagen orientation and μCT volumetric tissue mineral density (vTMD) in murine cortical bone, we have constructed the first multiscale finite element (mFE), mouse-specific femoral model to study the effect of collagen orientation and vTMD on strength in Ldlr(-/-), a mouse model of hyperlipidemia, and its control wild type, on either high fat diet or normal diet. Each µCT scan-based mFE model included either element-specific elastic orthotropic properties calculated from collagen orientation and vTMD (collagen-density model) by experimentally validated formulation, or usual element-specific elastic isotropic material properties dependent on vTMD-only (density-only model). We found that collagen orientation, assessed by circularly polarized light and confocal microscopies, and vTMD, differed among groups and that microindentation results strongly correlate with elastic modulus of collagen-density models (r(2)=0.85, p=10(-5)). Collagen-density models yielded (1) larger strains, and therefore lower strength, in simulations of 3-point bending and physiological loading; and (2) higher correlation between mFE-predicted strength and 3-point bending experimental strength, than density-only models. This novel method supports ongoing translational research to achieve the as yet elusive goal of accurate bone strength prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of Multiscale Method of Cells-Based Models for Predicting Elastic Properties of Filament Wound C/C-SiC

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Fassin, Marek; Bednarcyk, Brett A.; Reese, Stefanie; Simon, Jaan-Willem

2017-01-01

Three different multiscale models, based on the method of cells (generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute.

Multiscale Modeling and Characterization of the Effects of Damage Evolution on the Multifunctional Properties of Polymer Nanocomposites

DTIC Science & Technology

2016-07-27

the mechanical and electrical properties of carbon nanotube -polymer nanocomposites. Focus was placed on understanding and capturing the key... nanotube nanocomposite piezoresistive sensing in performing structural health monitoring in epoxy-based energetic materials. The focus was to...Carbon Nanotube , Nanocomposite, Structural Health Monitoring, Strain Sensing, Damage Sensing 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU

Engineered Multifunctional Nanophotonic Materials for Ultrafast Optical Switching

DTIC Science & Technology

2012-11-02

and Co3 + placed at tetrahedral and octahedral sites, respectively. Single -layer thin films of Co3O4 nanoparticles have large optical nonlinearity and...the first two methodologies in systems having weakly resonant structures, including 3-D and/or 1-D photonic crystal structures (i.e. nonlinear Bragg...Nonlinear optical transmission of lead phthalocyanine-doped nematic liquid crystal composites for multiscale nonlinear switching from nanosecond to

Representative Structural Element - A New Paradigm for Multi-Scale Structural Modeling

DTIC Science & Technology

2016-07-05

developed by NASA Glenn Research Center based on Aboudi’s micromechanics theories [5] that provides a wide range of capabilities for modeling ...to use appropriate models for related problems based on the capability of corresponding approaches. Moreover, the analyses will give a general...interface of heterogeneous materials but also help engineers to use appropriate models for related problems based on the capability of corresponding

Quantifying the Hierarchical Order in Self-Aligned Carbon Nanotubes from Atomic to Micrometer Scale.

PubMed

Meshot, Eric R; Zwissler, Darwin W; Bui, Ngoc; Kuykendall, Tevye R; Wang, Cheng; Hexemer, Alexander; Wu, Kuang Jen J; Fornasiero, Francesco

2017-06-27

Fundamental understanding of structure-property relationships in hierarchically organized nanostructures is crucial for the development of new functionality, yet quantifying structure across multiple length scales is challenging. In this work, we used nondestructive X-ray scattering to quantitatively map the multiscale structure of hierarchically self-organized carbon nanotube (CNT) "forests" across 4 orders of magnitude in length scale, from 2.0 Å to 1.5 μm. Fully resolved structural features include the graphitic honeycomb lattice and interlayer walls (atomic), CNT diameter (nano), as well as the greater CNT ensemble (meso) and large corrugations (micro). Correlating orientational order across hierarchical levels revealed a cascading decrease as we probed finer structural feature sizes with enhanced sensitivity to small-scale disorder. Furthermore, we established qualitative relationships for single-, few-, and multiwall CNT forest characteristics, showing that multiscale orientational order is directly correlated with number density spanning 10 9 -10 12 cm -2 , yet order is inversely proportional to CNT diameter, number of walls, and atomic defects. Lastly, we captured and quantified ultralow-q meridional scattering features and built a phenomenological model of the large-scale CNT forest morphology, which predicted and confirmed that these features arise due to microscale corrugations along the vertical forest direction. Providing detailed structural information at multiple length scales is important for design and synthesis of CNT materials as well as other hierarchically organized nanostructures.

Rapid prototyping of multi-scale biomedical microdevices by combining additive manufacturing technologies.

PubMed

Hengsbach, Stefan; Lantada, Andrés Díaz

2014-08-01

The possibility of designing and manufacturing biomedical microdevices with multiple length-scale geometries can help to promote special interactions both with their environment and with surrounding biological systems. These interactions aim to enhance biocompatibility and overall performance by using biomimetic approaches. In this paper, we present a design and manufacturing procedure for obtaining multi-scale biomedical microsystems based on the combination of two additive manufacturing processes: a conventional laser writer to manufacture the overall device structure, and a direct-laser writer based on two-photon polymerization to yield finer details. The process excels for its versatility, accuracy and manufacturing speed and allows for the manufacture of microsystems and implants with overall sizes up to several millimeters and with details down to sub-micrometric structures. As an application example we have focused on manufacturing a biomedical microsystem to analyze the impact of microtextured surfaces on cell motility. This process yielded a relevant increase in precision and manufacturing speed when compared with more conventional rapid prototyping procedures.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

Multiscale crack initiator promoted super-low ice adhesion surfaces.

PubMed

He, Zhiwei; Xiao, Senbo; Gao, Huajian; He, Jianying; Zhang, Zhiliang

2017-09-27

Preventing icing on exposed surfaces is important for life and technology. While suppressing ice nucleation by surface structuring and local confinement is highly desirable and yet to be achieved, a realistic roadmap of icephobicity is to live with ice, but with lowest possible ice adhesion. According to fracture mechanics, the key to lower ice adhesion is to maximize crack driving forces at the ice-substrate interface. Herein, we present a novel integrated macro-crack initiator mechanism combining nano-crack and micro-crack initiators, and demonstrate a new approach to designing super-low ice adhesion surfaces by introducing sub-structures into smooth polydimethylsiloxane coatings. Our design promotes the initiation of macro-cracks and enables the reduction of ice adhesion by at least ∼50% regardless of the curing temperature, weight ratio and size of internal holes, reaching a lowest ice adhesion of 5.7 kPa. The multiscale crack initiator mechanisms provide an unprecedented and versatile strategy towards designing super-low ice adhesion surfaces.

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images.

PubMed

Lu, Donghuan; Popuri, Karteek; Ding, Gavin Weiguang; Balachandar, Rakesh; Beg, Mirza Faisal

2018-04-09

Alzheimer's Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1-3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature.

Multiscale Modeling of Plasmon-Enhanced Power Conversion Efficiency in Nanostructured Solar Cells.

PubMed

Meng, Lingyi; Yam, ChiYung; Zhang, Yu; Wang, Rulin; Chen, GuanHua

2015-11-05

The unique optical properties of nanometallic structures can be exploited to confine light at subwavelength scales. This excellent light trapping is critical to improve light absorption efficiency in nanoscale photovoltaic devices. Here, we apply a multiscale quantum mechanics/electromagnetics (QM/EM) method to model the current-voltage characteristics and optical properties of plasmonic nanowire-based solar cells. The QM/EM method features a combination of first-principles quantum mechanical treatment of the photoactive component and classical description of electromagnetic environment. The coupled optical-electrical QM/EM simulations demonstrate a dramatic enhancement for power conversion efficiency of nanowire solar cells due to the surface plasmon effect of nanometallic structures. The improvement is attributed to the enhanced scattering of light into the photoactive layer. We further investigate the optimal configuration of the nanostructured solar cell. Our QM/EM simulation result demonstrates that a further increase of internal quantum efficiency can be achieved by scattering light into the n-doped region of the device.

Multiscaling for systems with a broad continuum of characteristic lengths and times: Structural transitions in nanocomposites.

PubMed

Pankavich, S; Ortoleva, P

2010-06-01

The multiscale approach to N-body systems is generalized to address the broad continuum of long time and length scales associated with collective behaviors. A technique is developed based on the concept of an uncountable set of time variables and of order parameters (OPs) specifying major features of the system. We adopt this perspective as a natural extension of the commonly used discrete set of time scales and OPs which is practical when only a few, widely separated scales exist. The existence of a gap in the spectrum of time scales for such a system (under quasiequilibrium conditions) is used to introduce a continuous scaling and perform a multiscale analysis of the Liouville equation. A functional-differential Smoluchowski equation is derived for the stochastic dynamics of the continuum of Fourier component OPs. A continuum of spatially nonlocal Langevin equations for the OPs is also derived. The theory is demonstrated via the analysis of structural transitions in a composite material, as occurs for viral capsids and molecular circuits.

De novo design of recombinant spider silk proteins for material applications.

PubMed

Zheng, Ke; Ling, Shengjie

2018-05-21

Spider silks are well known for their superior mechanical properties that are stronger and tougher than steel despite being assembled at close to ambient conditions and using water as the solvent. However, it is a significant challenge to utilize spider silks for practical applications due to their limited sources. Fortunately, genetic engineering techniques offer a promising approach to produce useable amounts of spider silk variants. Starting from these recombinant spider silk proteins, a series of experiments and simulations strategies were developed to improve the recombinant spider silk proteins (RSSP) material design and fabrication with the aim of biomimicking the structure-property-function relationships of spider silks. Accordingly, in this review, we first introduce the structure-property-function relationship of spider silks. Then, we discuss the recent progress in the genetic synthesis of RSSPs and summarize their related multiscale self-assembly behaviors. Finally, we outline works utilizing multiscale modeling to assist RSSP material design. This article is protected by copyright. All rights reserved.

Multi-scale multi-point observation of dipolarization in the near-Earth's magnetotail

NASA Astrophysics Data System (ADS)

Nakamura, R.; Varsani, A.; Genestreti, K.; Nakamura, T.; Baumjohann, W.; Birn, J.; Le Contel, O.; Nagai, T.

2017-12-01

We report on evolution of the dipolarization in the near-Earth plasma sheet during two intense substorms based on observations when the four spacecraft of the Magnetospheric Multiscale (MMS) together with GOES and Geotail were located in the near Earth magnetotail. These multiple spacecraft together with the ground-based magnetogram enabled to obtain the location of the large- scale substorm current wedge (SCW) and overall changes in the plasma sheet configuration. MMS was located in the southern hemisphere at the outer plasma sheet and observed fast flow disturbances associated with dipolarizations. The high time-resolution measurements from MMS enable us to detect the rapid motion of the field structures and the flow disturbances separately and to resolve signatures below the ion-scales. We found small-scale transient field-aligned current sheets associated with upward streaming cold plasmas and Hall-current layers in the fast flow shear region. Observations of these current structures are compared with simulations of reconnection jets.

Programming Nanoparticles in Multiscale: Optically Modulated Assembly and Phase Switching of Silicon Nanoparticle Array.

PubMed

Wang, Letian; Rho, Yoonsoo; Shou, Wan; Hong, Sukjoon; Kato, Kimihiko; Eliceiri, Matthew; Shi, Meng; Grigoropoulos, Costas P; Pan, Heng; Carraro, Carlo; Qi, Dongfeng

2018-03-27

Manipulating and tuning nanoparticles by means of optical field interactions is of key interest for nanoscience and applications in electronics and photonics. We report scalable, direct, and optically modulated writing of nanoparticle patterns (size, number, and location) of high precision using a pulsed nanosecond laser. The complex nanoparticle arrangement is modulated by the laser pulse energy and polarization with the particle size ranging from 60 to 330 nm. Furthermore, we report fast cooling-rate induced phase switching of crystalline Si nanoparticles to the amorphous state. Such phase switching has usually been observed in compound phase change materials like GeSbTe. The ensuing modification of atomic structure leads to dielectric constant switching. Based on these effects, a multiscale laser-assisted method of fabricating Mie resonator arrays is proposed. The number of Mie resonators, as well as the resonance peaks and dielectric constants of selected resonators, can be programmed. The programmable light-matter interaction serves as a mechanism to fabricate optical metasurfaces, structural color, and multidimensional optical storage devices.

Enhanced water repellency of surfaces coated with multiscale carbon structures

NASA Astrophysics Data System (ADS)

Marchalot, Julien; Ramos, Stella. M. M.; Pirat, Christophe; Journet, Catherine

2018-01-01

Low cost and well characterized superhydrophobic surfaces are frequently required for industrial applications. Materials are commonly structured at the micro or nano scale. Surfaces decorated with nanotube derivatives synthesized by plasma enhanced chemical vapor deposition (PECVD) are of particular interest, since suitable modifications in the growth parameters can lead to numerous designs. In this article, we present surfaces that are selected for their specific wetting features with patterns ranging from dense forests to jungles with concave (re-entrant) surface such as flake-like multiscale roughness. Once these surfaces are functionalized adequately, their wetting properties are investigated. Their ability to sustain a superhydrophobic state for sessile water drops is examined. Finally, we propose a design to achieve a robust so-called ;Fakir; state, even for micrometer-sized drops, whereas with classic nanotubes forests it is not achievable. Thus, the drop remains on the apex of the protrusions with a high contact angle and a low contact angle hysteresis, while the surface features demonstrate good mechanical resistance against capillary forces.

Modeling defect cluster evolution in irradiated structural materials: Focus on comparing to high-resolution experimental characterization studies

DOE PAGES

Wirth, Brian D.; Hu, Xunxiang; Kohnert, Aaron; ...

2015-03-02

Exposure of metallic structural materials to irradiation environments results in significant microstructural evolution, property changes, and performance degradation, which limits the extended operation of current generation light water reactors and restricts the design of advanced fission and fusion reactors. Further, it is well recognized that these irradiation effects are a classic example of inherently multiscale phenomena and that the mix of radiation-induced features formed and the corresponding property degradation depend on a wide range of material and irradiation variables. This inherently multiscale evolution emphasizes the importance of closely integrating models with high-resolution experimental characterization of the evolving radiation-damaged microstructure. Lastly,more » this article provides a review of recent models of the defect microstructure evolution in irradiated body-centered cubic materials, which provide good agreement with experimental measurements, and presents some outstanding challenges, which will require coordinated high-resolution characterization and modeling to resolve.« less

New multi-scale perspectives on the stromatolites of Shark Bay, Western Australia.

PubMed

Suosaari, E P; Reid, R P; Playford, P E; Foster, J S; Stolz, J F; Casaburi, G; Hagan, P D; Chirayath, V; Macintyre, I G; Planavsky, N J; Eberli, G P

2016-02-03

A recent field-intensive program in Shark Bay, Western Australia provides new multi-scale perspectives on the world's most extensive modern stromatolite system. Mapping revealed a unique geographic distribution of morphologically distinct stromatolite structures, many of them previously undocumented. These distinctive structures combined with characteristic shelf physiography define eight 'Stromatolite Provinces'. Morphological and molecular studies of microbial mat composition resulted in a revised growth model where coccoid cyanobacteria predominate in mat communities forming lithified discrete stromatolite buildups. This contradicts traditional views that stromatolites with the best lamination in Hamelin Pool are formed by filamentous cyanobacterial mats. Finally, analysis of internal fabrics of stromatolites revealed pervasive precipitation of microcrystalline carbonate (i.e. micrite) in microbial mats forming framework and cement that may be analogous to the micritic microstructures typical of Precambrian stromatolites. These discoveries represent fundamental advances in our knowledge of the Shark Bay microbial system, laying a foundation for detailed studies of stromatolite morphogenesis that will advance our understanding of benthic ecosystems on the early Earth.

Strain Sensing Based on Multiscale Composite Materials Reinforced with Graphene Nanoplatelets.

PubMed

Moriche, Rocío; Prolongo, Silvia G; Sánchez, María; Jiménez-Suárez, Alberto; Campo, Mónica; Ureña, Alejandro

2016-11-07

The electrical response of NH2-functionalized graphene nanoplatelets composite materials under strain was studied. Two different manufacturing methods are proposed to create the electrical network in this work: (a) the incorporation of the nanoplatelets into the epoxy matrix and (b) the coating of the glass fabric with a sizing filled with the same nanoplatelets. Both types of multiscale composite materials, with an in-plane electrical conductivity of ~10 -3 S/m, showed an exponential growth of the electrical resistance as the strain increases due to distancing between adjacent functionalized graphene nanoplatelets and contact loss between overlying ones. The sensitivity of the materials analyzed during this research, using the described procedures, has been shown to be higher than commercially available strain gauges. The proposed procedures for self-sensing of the structural composite material would facilitate the structural health monitoring of components in difficult to access emplacements such as offshore wind power farms. Although the sensitivity of the multiscale composite materials was considerably higher than the sensitivity of metallic foils used as strain gauges, the value reached with NH2 functionalized graphene nanoplatelets coated fabrics was nearly an order of magnitude superior. This result elucidated their potential to be used as smart fabrics to monitor human movements such as bending of fingers or knees. By using the proposed method, the smart fabric could immediately detect the bending and recover instantly. This fact permits precise monitoring of the time of bending as well as the degree of bending.

Optimization of a hydrodynamic separator using a multiscale computational fluid dynamics approach.

PubMed

Schmitt, Vivien; Dufresne, Matthieu; Vazquez, Jose; Fischer, Martin; Morin, Antoine

2013-01-01

This article deals with the optimization of a hydrodynamic separator working on the tangential separation mechanism along a screen. The aim of this study is to optimize the shape of the device to avoid clogging. A multiscale approach is used. This methodology combines measurements and computational fluid dynamics (CFD). A local model enables us to observe the different phenomena occurring at the orifice scale, which shows the potential of expanded metal screens. A global model is used to simulate the flow within the device using a conceptual model of the screen (porous wall). After validation against the experimental measurements, the global model was used to investigate the influence of deflectors and disk plates in the structure.

Adaptive Multi-scale PHM for Robotic Assembly Processes

PubMed Central

Choo, Benjamin Y.; Beling, Peter A.; LaViers, Amy E.; Marvel, Jeremy A.; Weiss, Brian A.

2017-01-01

Adaptive multiscale prognostics and health management (AM-PHM) is a methodology designed to support PHM in smart manufacturing systems. As a rule, PHM information is not used in high-level decision-making in manufacturing systems. AM-PHM leverages and integrates component-level PHM information with hierarchical relationships across the component, machine, work cell, and production line levels in a manufacturing system. The AM-PHM methodology enables the creation of actionable prognostic and diagnostic intelligence up and down the manufacturing process hierarchy. Decisions are made with the knowledge of the current and projected health state of the system at decision points along the nodes of the hierarchical structure. A description of the AM-PHM methodology with a simulated canonical robotic assembly process is presented. PMID:28664161

Multiscale recurrence quantification analysis of order recurrence plots

NASA Astrophysics Data System (ADS)

Xu, Mengjia; Shang, Pengjian; Lin, Aijing

2017-03-01

In this paper, we propose a new method of multiscale recurrence quantification analysis (MSRQA) to analyze the structure of order recurrence plots. The MSRQA is based on order patterns over a range of time scales. Compared with conventional recurrence quantification analysis (RQA), the MSRQA can show richer and more recognizable information on the local characteristics of diverse systems which successfully describes their recurrence properties. Both synthetic series and stock market indexes exhibit their properties of recurrence at large time scales that quite differ from those at a single time scale. Some systems present more accurate recurrence patterns under large time scales. It demonstrates that the new approach is effective for distinguishing three similar stock market systems and showing some inherent differences.

Analysis of Hepatitis C Virus Decline during Treatment with the Protease Inhibitor Danoprevir Using a Multiscale Model

DOE PAGES

Rong, Libin; Guedj, Jeremie; Dahari, Harel; ...

2013-03-14

The current paradigm for studying hepatitis C virus (HCV) dynamics in patients utilizes a standard viral dynamic model that keeps track of uninfected (target) cells, infected cells, and virus. The model does not account for the dynamics of intracellular viral replication, which is the major target of direct-acting antiviral agents (DAAs). In this paper, we describe and study a recently developed multiscale age-structured model that explicitly considers the potential effects of DAAs on intracellular viral RNA production, degradation, and secretion as virus into the circulation. We show that when therapy significantly blocks both intracellular viral RNA production and virus secretion,more » the serum viral load decline has three phases, with slopes reflecting the rate of serum viral clearance, the rate of loss of intracellular viral RNA, and the rate of loss of intracellular replication templates and infected cells, respectively. We also derive analytical approximations of the multiscale model and use one of them to analyze data from patients treated for 14 days with the HCV protease inhibitor danoprevir. Analysis suggests that danoprevir significantly blocks intracellular viral production (with mean effectiveness 99.2%), enhances intracellular viral RNA degradation about 5-fold, and moderately inhibits viral secretion (with mean effectiveness 56%). Finally, the multiscale model can be used to study viral dynamics in patients treated with other DAAs and explore their mechanisms of action in treatment of hepatitis C.« less

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Hierarchical assembly strategy and multiscale structural origin of exceptional mechanical performance in nacre

NASA Astrophysics Data System (ADS)

Huang, Zaiwang

Nacre (mother of pearl) is a self-assembled hierarchical nanocomposite in possession of exquisite multiscale architecture and exceptional mechanical properties. Previous work has shown that the highly-ordered brick-mortar-like structure in nacre is assembled via epitaxial growth and the aragonite platelets are pure single-crystals. Our results challenge this conclusion and propose that nacre's individual aragonite platelets are constructed with highly-aligned aragonite nanoparticles mediated by screw dislocation and amorphous aggregation. The underlying physics mechanism why the aragonite nanoparticles choose highly-oriented attachment as its crystallization pathway is rationalized in terms of thermodynamics. The aragonite nanoparticle order-disorder transformation can be triggered by high temperature and mechanical deformation, which in turn confirms that the aragonite nanoparticles are basic building blocks for aragonite platelets. Particularly fascinating is the fracture toughness enhancement of nacre through exquisitely collecting mechanically inferior calcium carbonate (CaCO3) and biomolecules. The sandwich-like microarchitecture with a geometrically staggered arrangement can induce crack deflection along its biopolymer interface, thus significantly enhancing nacre's fracture toughness. Our new findings ambiguously demonstrate that, aside from crack deflection, the advancing crack can invade aragonite platelet, leaving a zigzag crack propagation pathway. These unexpected experimental observations disclose, for the first time, the inevitable structural role of aragonite platelets in enhancing nacre's fracture toughness. Simultaneously, the findings that the crack propagates in a zigzag manner within individual aragonite platelets overturn the previously well-established wisdom that considers aragonite platelets as brittle single-crystals. Moreover, we investigated the dynamical mechanical response of nacre under unixial compression. Our results show that the high strain rate sensitivity reaching ˜0.1 can be directly related to the localized plastic activation volume. Nacre's hierarchical energy-dissipation mechanism under dynamic compression loading comes from a mechanical optimization derived from its inherently multiscale functional structure design.

A multi-disciplinary approach for the structural monitoring of Cultural Heritages in a seismic area

NASA Astrophysics Data System (ADS)

Fabrizia Buongiorno, Maria; Musacchio, Massimo; Guerra, Ignazio; Porco, Giacinto; Stramondo, Salvatore; Casula, Giuseppe; Caserta, Arrigo; Speranza, Fabio; Doumaz, Fawzi; Giovanna Bianchi, Maria; Luzi, Guido; Ilaria Pannaccione Apa, Maria; Montuori, Antonio; Gaudiosi, Iolanda; Vecchio, Antonio; Gervasi, Anna; Bonali, Elena; Romano, Dolores; Falcone, Sergio; La Piana, Carmelo

2014-05-01

In the recent years, the concepts of seismic risk vulnerability and structural health monitoring have become very important topics in the field of both structural and civil engineering for the identification of appropriate risk indicators and risk assessment methodologies in Cultural Heritages monitoring. The latter, which includes objects, building and sites with historical, architectural and/or engineering relevance, concerns the management, the preservation and the maintenance of the heritages within their surrounding environmental context, in response to climate changes and natural hazards (e.g. seismic, volcanic, landslides and flooding hazards). Within such a framework, the complexity and the great number of variables to be considered require a multi-disciplinary approach including strategies, methodologies and tools able to provide an effective monitoring of Cultural Heritages form both scientific and operational viewpoints. Based on this rationale, in this study, an advanced, technological and operationally-oriented approach is presented and tested, which enables measuring and monitoring Cultural Heritage conservation state and geophysical/geological setting of the area, in order to mitigate the seismic risk of the historical public goods at different spatial scales*. The integration between classical geophysical methods with new emerging sensing techniques enables a multi-depth, multi-resolution, and multi-scale monitoring in both space and time. An integrated system of methodologies, instrumentation and data-processing approaches for non-destructive Cultural Heritage investigations is proposed, which concerns, in detail, the analysis of seismogenetic sources, the geological-geotechnical setting of the area and site seismic effects evaluation, proximal remote sensing techniques (e.g. terrestrial laser scanner, ground-based radar systems, thermal cameras), high-resolution aerial and satellite-based remote sensing methodologies (e.g. aeromagnetic surveys, synthetic aperture radar, optical, multispectral and panchromatic measurements), static and dynamic structural health monitoring analysis (e.g. screening tests with georadar, sonic instruments, sclerometers and optic fibers). The final purpose of the proposed approach is the development of an investigation methodology for short- and long-term Cultural Heritages preservation in response to seismic stress, which has specific features of scalability, modularity and exportability for every possible monitoring configuration. Moreover, it allows gathering useful information to furnish guidelines for Institution and local Administration to plan consolidation actions and therefore prevention activity. Some preliminary results will be presented for the test site of Calabria Region, where some architectural heritages have been properly selected as case studies for monitoring purposes. *The present work is supported and funded by Ministero dell'Università, dell'Istruzione e della Ricerca (MIUR) under the research project PON01-02710 "MASSIMO" - "Monitoraggio in Area Sismica di Sistemi Monumentali".

Symptoms of change in multi-scale observations of arctic ecosystem carbon cycling

NASA Astrophysics Data System (ADS)

Stoy, P. C.; Williams, M. D.; Hartley, I. P.; Street, L.; Hill, T. C.; Prieto-Blanco, A.; Wayolle, A.; Disney, M.; Evans, J.; Fletcher, B.; Poyatos, R.; Wookey, P.; Merbold, L.; Wade, T. J.; Moncrieff, J.

2009-12-01

Arctic ecosystems are responding rapidly to observed climate change. Quantifying the magnitude of these changes, and their implications for the climate system, requires observations of their current structure and function, as well as extrapolation and modelling (i.e. ‘upscaling’) across time and space. Here, we describe the major results of the International Polar Year (IPY) ABACUS project, a multi-scale investigation across arctic Fennoscandia that couples plant and soil process studies, isotope analyses, flux and micrometeorological measurements, process modelling, and aircraft and satellite observations to improve predictions of the response of the arctic terrestrial biosphere to global change. We begin with a synthesis of eddy covariance observations from the global FLUXNET database. We demonstrate that a simple model parameterized using pan-arctic chamber measurements explains over 80% of the variance of half-hourly CO2 fluxes during the growing season across most arctic and montane tundra ecosystems given accurate measurements of leaf area index (LAI), which agrees with the recently proposed ‘functional convergence’ paradigm for tundra vegetation. The ability of MODIS to deliver accurate LAI estimates is briefly discussed and an adjusted algorithm is presented and validated using direct observations. We argue for an Information Theory-based framework for upscaling in Earth science by conceptualizing multi-scale research as a transfer of information across scales. We then demonstrate how error in upscaled arctic C flux estimates can be reduced to less than 4% from their high-resolution counterpart by formally preserving the information content of high spatial and spectral resolution aircraft and satellite imagery. Jaynes’ classic Maximum Entropy (MaxEnt) principle is employed to incorporate logical, biological and physical constraints to reduce error in downscaled flux estimates. Errors are further reduced by assimilating flux, biological and remote sensing data into the DALEC ecosystem model using the ensemble Kalman filter. We use a flux footprint analysis to demonstrate that the ABACUS study ecosystems display functional convergence at chamber, tower and aircraft scales. The importance of the rapidly changing cold and ‘shoulder’ seasons to annual CO2 flux is emphasized; these represent over 20% of annual C exchange at our field sites. The role of moss in determining non-growing season C uptake and loss is highlighted using direct chamber-based observations. We demonstrate ‘priming’ of the decomposition of older forest soil during the period of vegetative activity using 14CO2 observations, and show that tundra ecosystems paradoxically store more C than birch forests in the region. This biological priming of older C stocks is not included in current models of the arctic C cycle.

Multiscale pore networks and their effect on deformation and transport property alteration associated with hydraulic fracturing

NASA Astrophysics Data System (ADS)

Daigle, Hugh; Hayman, Nicholas; Jiang, Han; Tian, Xiao; Jiang, Chunbi

2017-04-01

Multiple lines of evidence indicate that, during a hydraulic fracture stimulation, the permeability of the unfractured matrix far from the main, induced tensile fracture increases by one to two orders of magnitude. This permeability enhancement is associated with pervasive shear failure in a large region surrounding the main induced fracture. We have performed low-pressure gas sorption, mercury intrusion, and nuclear magnetic resonance measurements along with high-resolution scanning electron microscope imaging on several preserved and unpreserved shale samples from North American basins before and after inducing failure in confined compressive strength tests. We have observed that the pore structure in intact samples exhibits multiscale behavior, with sub-micron-scale pores in organic matter connected in isolated, micron-scale clusters which themselves are connected to each other through a network of microcracks. The organic-hosted pore networks are poorly connected due to a significant number of dead-end pores within the organic matter. Following shear failure, we often observe an increase in pore volume in the sub-micron range, which appears to be related to the formation of microcracks that propagate along grain boundaries and other planes of mechanical strength contrast. This is consistent with other experimental and field evidence. In some cases these microcracks cross or terminate in organic matter, intersecting the organic-hosted pores. The induced microcrack networks typically have low connectivity and do not appreciably increase the connectivity of the overall pore network. However, in other cases the shear deformation results in an overall pore volume decrease; samples which exhibit this behavior tend to have more clay minerals. Our interpretation of these phenomena is as follows. As organic matter is converted to hydrocarbons, organic-hosted pores develop, and the hydrocarbons contained in these pores are overpressured. The disconnected nature of these clusters of organic-hosted pores prevents the overpressure from dissipating, resulting in localized overpressure at the micron scale. When the rock is subjected to a hydraulic fracture stimulation, the rock surrounding the main induced fracture experiences shear deformation. Those parts of the rock that contain overpressured fluids in the organic-hosted pores will be more likely to experience dilatancy in the form of brittle deformation; the portions of the rock lacking in organic-hosted pores will tend to experience compactive shear failure since the effective normal stresses are larger. The microcrack networks that propagate into the regions of organic-hosted porosity allow the hydrocarbons resident in those pores to migrate to the main induced tensile fractures. The disconnected nature of the microcrack networks causes only a slight increase in permeability, which is consistent with other observations. Our work illustrates how multiscale pore networks in shale interact with in situ stresses to affect the bulk shale rheology.

Guide for Use of Wood Preservatives in Historic Structures

Treesearch

Stan Lebow; Ronald W. Anthony

2012-01-01

This document provides guidance on wood preservation options in the context of historic preservation. Preserving wooden building materials is critical to historic preservation practitioners. Biodeterioration can be minimized through design, construction practices, maintenance, and, if necessary, by use of wood preservatives. Moisture is the primary cause of...

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stander, Nielen; Basudhar, Anirban; Basu, Ushnish

2015-09-14

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project tomore » develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.« less

Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Michalik, Kazimierz

2016-10-01

Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.

Modeling the Role of Alkanes, Polycyclic Aromatic Hydrocarbons, and Their Oligomers in Secondary Organic Aerosol Formation

EPA Science Inventory

A computationally efficient method to treat secondary organic aerosol (SOA) from various length and structure alkanes as well as SOA from polycyclic aromatic hydrocarbons (PAHs) is implemented in the Community Multiscale Air Quality (CMAQ) model to predict aerosol concentrations ...

A multi-scale controlled tissue engineering scaffold prepared by 3D printing and NFES technology

NASA Astrophysics Data System (ADS)

Yan, Feifei; Liu, Yuanyuan; Chen, Haiping; Zhang, Fuhua; Zheng, Lulu; Hu, Qingxi

2014-03-01

The current focus in the field of life science is the use of tissue engineering scaffolds to repair human organs, which has shown great potential in clinical applications. Extracellular matrix morphology and the performance and internal structure of natural organs are required to meet certain requirements. Therefore, integrating multiple processes can effectively overcome the limitations of the individual processes and can take into account the needs of scaffolds for the material, structure, mechanical properties and many other aspects. This study combined the biological 3D printing technology and the near-field electro-spinning (NFES) process to prepare a multi-scale controlled tissue engineering scaffold. While using 3D printing technology to directly prepare the macro-scaffold, the compositing NFES process to build tissue micro-morphology ultimately formed a tissue engineering scaffold which has the specific extracellular matrix structure. This scaffold not only takes into account the material, structure, performance and many other requirements, but also focuses on resolving the controllability problems in macro- and micro-forming which further aim to induce cell directed differentiation, reproduction and, ultimately, the formation of target tissue organs. It has in-depth immeasurable significance to build ideal scaffolds and further promote the application of tissue engineering.

Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.

PubMed

Costa, Madalena D; Peng, Chung-Kang; Goldberger, Ary L

2008-06-01

Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.

Multiscale Analysis of Heart Rate Dynamics: Entropy and Time Irreversibility Measures

PubMed Central

Peng, Chung-Kang; Goldberger, Ary L.

2016-01-01

Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and nonequilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools— multiscale entropy and multiscale time irreversibility—are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs. PMID:18172763

Bayesian Multiscale Modeling of Closed Curves in Point Clouds

PubMed Central

Gu, Kelvin; Pati, Debdeep; Dunson, David B.

2014-01-01

Modeling object boundaries based on image or point cloud data is frequently necessary in medical and scientific applications ranging from detecting tumor contours for targeted radiation therapy, to the classification of organisms based on their structural information. In low-contrast images or sparse and noisy point clouds, there is often insufficient data to recover local segments of the boundary in isolation. Thus, it becomes critical to model the entire boundary in the form of a closed curve. To achieve this, we develop a Bayesian hierarchical model that expresses highly diverse 2D objects in the form of closed curves. The model is based on a novel multiscale deformation process. By relating multiple objects through a hierarchical formulation, we can successfully recover missing boundaries by borrowing structural information from similar objects at the appropriate scale. Furthermore, the model’s latent parameters help interpret the population, indicating dimensions of significant structural variability and also specifying a ‘central curve’ that summarizes the collection. Theoretical properties of our prior are studied in specific cases and efficient Markov chain Monte Carlo methods are developed, evaluated through simulation examples and applied to panorex teeth images for modeling teeth contours and also to a brain tumor contour detection problem. PMID:25544786

A framework for multi-scale simulation of crystal growth in the presence of polymers.

PubMed

Mandal, Taraknath; Huang, Wenjun; Mecca, Jodi M; Getchell, Ashley; Porter, William W; Larson, Ronald G

2017-03-01

We present a multi-scale simulation method for modeling crystal growth in the presence of polymer excipients. The method includes a coarse-grained (CG) model for small molecules of known crystal structure whose force field is obtained using structural properties from atomistic simulations. This CG model is capable of stabilizing the molecular crystal structure and capturing the crystal growth from the melt for a wide range of small organic molecules, as demonstrated by application of our method to the molecules isoniazid, urea, sulfamethoxazole, prilocaine, oxcarbazepine, and phenytoin. This CG model can also be used to study the effect of additives, such as polymers, on the inhibition of crystal growth by polymers, as exemplified by our simulation of suppression of the rate of crystal growth of phenytoin, an active pharmaceutical ingredient (API), by a cellulose excipient, functionalized with acetate (Ac), hydroxy-propyl (Hp) and succinate (Su) groups. We show that the efficacy of the cellulosic polymers in slowing crystal growth of small molecules strongly depends on the functional group substitution on the cellulose backbone, with the acetate substituent group slowing crystal growth more than does the deprotonated succinate group, which we confirm by experimental drug supersaturation studies.

Time-localized wavelet multiple regression and correlation

NASA Astrophysics Data System (ADS)

Fernández-Macho, Javier

2018-02-01

This paper extends wavelet methodology to handle comovement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multiscale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds. The method is illustrated with a multiscale analysis of the comovements of Eurozone stock markets during this century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along time and across timescales featuring an acute divide across timescales at about the quarterly scale. At longer scales, evidence from the long-term correlation structure can be interpreted as stable perfect integration among Euro stock markets. On the other hand, at intramonth and intraweek scales, the short-term correlation structure has been clearly evolving along time, experiencing a sharp increase during financial crises which may be interpreted as evidence of financial 'contagion'.

Vertical transport in graphene-hexagonal boron nitride heterostructure devices

PubMed Central

Bruzzone, Samantha; Logoteta, Demetrio; Fiori, Gianluca; Iannaccone, Giuseppe

2015-01-01

Research in graphene-based electronics is recently focusing on devices based on vertical heterostructures of two-dimensional materials. Here we use density functional theory and multiscale simulations to investigate the tunneling properties of single- and double-barrier structures with graphene and few-layer hexagonal boron nitride (h-BN) or hexagonal boron carbon nitride (h-BC2N). We find that tunneling through a single barrier exhibit a weak dependence on energy. We also show that in double barriers separated by a graphene layer we do not observe resonant tunneling, but a significant increase of the tunneling probability with respect to a single barrier of thickness equal to the sum of the two barriers. This is due to the fact that the graphene layer acts as an effective phase randomizer, suppressing resonant tunneling and effectively letting a double-barrier structure behave as two single-barriers in series. Finally, we use multiscale simulations to reproduce a current-voltage characteristics resembling that of a resonant tunneling diode, that has been experimentally observed in single barrier structure. The peak current is obtained when there is perfect matching between the densities of states of the cathode and anode graphene regions. PMID:26415656

Beyond Frangi: an improved multiscale vesselness filter

NASA Astrophysics Data System (ADS)

Jerman, Tim; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

2015-03-01

Vascular diseases are among the top three causes of death in the developed countries. Effective diagnosis of vascular pathologies from angiographic images is therefore very important and usually relies on segmentation and visualization of vascular structures. To enhance the vascular structures prior to their segmentation and visualization, and to suppress non-vascular structures and image noise, the filters enhancing vascular structures are used extensively. Even though several enhancement filters are widely used, the responses of these filters are typically not uniform between vessels of different radii and, compared to the response in the central part of vessels, their response is lower at vessels' edges and bifurcations, and vascular pathologies like aneurysm. In this paper, we propose a novel enhancement filter based on ratio of multiscale Hessian eigenvalues, which yields a close-to-uniform response in all vascular structures and accurately enhances the border between the vascular structures and the background. The proposed and four state-of-the-art enhancement filters were evaluated and compared on a 3D synthetic image containing tubular structures and a clinical dataset of 15 cerebral 3D digitally subtracted angiograms with manual expert segmentations. The evaluation was based on quantitative metrics of segmentation performance, computed as area under the precision-recall curve, signal-to-noise ratio of the vessel enhancement and the response uniformity within vascular structures. The proposed filter achieved the best scores in all three metrics and thus has a high potential to further improve the performance of existing or encourage the development of more advanced methods for segmentation and visualization of vascular structures.

Multiscale 2D Inversions of Active-source First-arrival Times in Taiwan

NASA Astrophysics Data System (ADS)

Lin, Y. P.; Zhao, L.; Hung, S. H.

2015-12-01

In this study, we make use of the active-source records collected by the TAIGER (TAiwan Integrated GEodynamics Research) project in 2008 at nearly 1400 locations on the island of Taiwan and the surrounding ocean bottom. We manually picked the first-arrival times from the waveform records to obtain a set of highly accurate P-wave traveltimes. Among the 1400 receivers, more than 1000 were deployed along four almost linear cross-island profiles with inter-seismometer spacing down to 200 m. This ground-truth dataset provides strong constrains on the structure between the exactly known active sources and densely distributed receivers, which can be used to calibrate the seismic structure in the upper crust in Taiwan. In this study, we use this dataset to image the two-dimensional P-wave structure along the four linear profiles. A wavelet parameterization of the model is adopted to achieve an objective and data-adaptive multiscale resolution to the 2D structures. Rigorous estimations of resolution lengths were also conducted to quantify the spatial resolutions of the tomography inversions. The resulting 2D models yield first-arrival time predictions that are in excellent agreement with the observations. The seismic structures along the 2D profiles display strong lateral variations (up to 80% relative to regional average) with more realistic amplitudes of velocity perturbations and spatial patterns consistent with geological zonations of Taiwan

Towards Characterization, Modeling, and Uncertainty Quantification in Multi-scale Mechanics of Oragnic-rich Shales

NASA Astrophysics Data System (ADS)

Abedi, S.; Mashhadian, M.; Noshadravan, A.

2015-12-01

Increasing the efficiency and sustainability in operation of hydrocarbon recovery from organic-rich shales requires a fundamental understanding of chemomechanical properties of organic-rich shales. This understanding is manifested in form of physics-bases predictive models capable of capturing highly heterogeneous and multi-scale structure of organic-rich shale materials. In this work we present a framework of experimental characterization, micromechanical modeling, and uncertainty quantification that spans from nanoscale to macroscale. Application of experiments such as coupled grid nano-indentation and energy dispersive x-ray spectroscopy and micromechanical modeling attributing the role of organic maturity to the texture of the material, allow us to identify unique clay mechanical properties among different samples that are independent of maturity of shale formations and total organic content. The results can then be used to inform the physically-based multiscale model for organic rich shales consisting of three levels that spans from the scale of elementary building blocks (e.g. clay minerals in clay-dominated formations) of organic rich shales to the scale of the macroscopic inorganic/organic hard/soft inclusion composite. Although this approach is powerful in capturing the effective properties of organic-rich shale in an average sense, it does not account for the uncertainty in compositional and mechanical model parameters. Thus, we take this model one step forward by systematically incorporating the main sources of uncertainty in modeling multiscale behavior of organic-rich shales. In particular we account for the uncertainty in main model parameters at different scales such as porosity, elastic properties and mineralogy mass percent. To that end, we use Maximum Entropy Principle and random matrix theory to construct probabilistic descriptions of model inputs based on available information. The Monte Carlo simulation is then carried out to propagate the uncertainty and consequently construct probabilistic descriptions of properties at multiple length-scales. The combination of experimental characterization and stochastic multi-scale modeling presented in this work improves the robustness in the prediction of essential subsurface parameters in engineering scale.

Multiscale complex network analysis: An approach to study spatiotemporal rainfall pattern in south Germany

NASA Astrophysics Data System (ADS)

Agarwal, Ankit; Marwan, Norbert; Rathinasamy, Maheswaran; Oeztuerk, Ugur; Merz, Bruno; Kurths, Jürgen

2017-04-01

Understanding of the climate sytems has been of tremendous importance to different branches such as agriculture, flood, drought and water resources management etc. In this regard, complex networks analysis and time series analysis attracted considerable attention, owing to their potential role in understanding the climate system through characteristic properties. One of the basic requirements in studying climate network dynamics is to identify connections in space or time or space-time, depending upon the purpose. Although a wide variety of approaches have been developed and applied to identify and analyse spatio-temporal relationships by climate networks, there is still further need for improvements in particular when considering precipitation time series or interactions on different scales. In this regard, recent developments in the area of network theory, especially complex networks, offer new avenues, both for their generality about systems and for their holistic perspective about spatio-temporal relationships. The present study has made an attempt to apply the ideas developed in the field of complex networks to examine connections in regional climate networks with particular focus on multiscale spatiotemporal connections. This paper proposes a novel multiscale understanding of regional climate networks using wavelets. The proposed approach is applied to daily precipitation records observed at 543 selected stations from south Germany for a period of 110 years (1901-2010). Further, multiscale community mining is performed on the same study region to shed more light on the underlying processes at different time scales. Various network measure and tools so far employed provide micro-level (individual station) and macro-level (community structure) information of the network. It is interesting to investigate how the result of this study can be useful for future climate predictions and for evaluating climate models on their implementation regarding heavy precipitation. Keywords: Complex network, event synchronization, wavelet, regional climate network, multiscale community mining

A novel method of multi-scale simulation of macro-scale deformation and microstructure evolution on metal forming

NASA Astrophysics Data System (ADS)

Huang, Shiquan; Yi, Youping; Li, Pengchuan

2011-05-01

In recent years, multi-scale simulation technique of metal forming is gaining significant attention for prediction of the whole deformation process and microstructure evolution of product. The advances of numerical simulation at macro-scale level on metal forming are remarkable and the commercial FEM software, such as Deform2D/3D, has found a wide application in the fields of metal forming. However, the simulation method of multi-scale has little application due to the non-linearity of microstructure evolution during forming and the difficulty of modeling at the micro-scale level. This work deals with the modeling of microstructure evolution and a new method of multi-scale simulation in forging process. The aviation material 7050 aluminum alloy has been used as example for modeling of microstructure evolution. The corresponding thermal simulated experiment has been performed on Gleeble 1500 machine. The tested specimens have been analyzed for modeling of dislocation density, nucleation and growth of recrystallization(DRX). The source program using cellular automaton (CA) method has been developed to simulate the grain nucleation and growth, in which the change of grain topology structure caused by the metal deformation was considered. The physical fields at macro-scale level such as temperature field, stress and strain fields, which can be obtained by commercial software Deform 3D, are coupled with the deformed storage energy at micro-scale level by dislocation model to realize the multi-scale simulation. This method was explained by forging process simulation of the aircraft wheel hub forging. Coupled the results of Deform 3D with CA results, the forging deformation progress and the microstructure evolution at any point of forging could be simulated. For verifying the efficiency of simulation, experiments of aircraft wheel hub forging have been done in the laboratory and the comparison of simulation and experiment result has been discussed in details.

Canonical symplectic structure and structure-preserving geometric algorithms for Schrödinger–Maxwell systems

DOE PAGES

Chen, Qiang; Qin, Hong; Liu, Jian; ...

2017-08-24

An infinite dimensional canonical symplectic structure and structure-preserving geometric algorithms are developed for the photon–matter interactions described by the Schrödinger–Maxwell equations. The algorithms preserve the symplectic structure of the system and the unitary nature of the wavefunctions, and bound the energy error of the simulation for all time-steps. Here, this new numerical capability enables us to carry out first-principle based simulation study of important photon–matter interactions, such as the high harmonic generation and stabilization of ionization, with long-term accuracy and fidelity.

Understanding Prairie Fen Hydrology - a Hierarchical Multi-Scale Groundwater Modeling Approach

NASA Astrophysics Data System (ADS)

Sampath, P.; Liao, H.; Abbas, H.; Ma, L.; Li, S.

2012-12-01

Prairie fens provide critical habitat to more than 50 rare species and significantly contribute to the biodiversity of the upper Great Lakes region. The sustainability of these globally unique ecosystems, however, requires that they be fed by a steady supply of pristine, calcareous groundwater. Understanding the hydrology that supports the existence of such fens is essential in preserving these valuable habitats. This research uses process-based multi-scale groundwater modeling for this purpose. Two fen-sites, MacCready Fen and Ives Road Fen, in Southern Michigan were systematically studied. A hierarchy of nested steady-state models was built for each fen-site to capture the system's dynamics at spatial scales ranging from the regional groundwater-shed to the local fens. The models utilize high-resolution Digital Elevation Models (DEM), National Hydrologic Datasets (NHD), a recently-assembled water-well database, and results from a state-wide groundwater mapping project to represent the complex hydro-geological and stress framework. The modeling system simulates both shallow glacial and deep bedrock aquifers as well as the interaction between surface water and groundwater. Aquifer heterogeneities were explicitly simulated with multi-scale transition probability geo-statistics. A two-way hydraulic head feedback mechanism was set up between the nested models, such that the parent models provided boundary conditions to the child models, and in turn the child models provided local information to the parent models. A hierarchical mass budget analysis was performed to estimate the seepage fluxes at the surface water/groundwater interfaces and to assess the relative importance of the processes at multiple scales that contribute water to the fens. The models were calibrated using observed base-flows at stream gauging stations and/or static water levels at wells. Three-dimensional particle tracking was used to predict the sources of water to the fens. We observed from the multi-scale simulations that the water system that supports the fens is a much larger, more connected, and more complex one than expected. The water in the fen can be traced back to a network of sources, including lakes and wetlands at different elevations, which are connected to a regional mound through a "cascade delivery mechanism". This "master recharge area" is the ultimate source of water not only to the fens in its vicinity, but also for many major rivers and aquifers. The implication of this finding is that prairie fens must be managed as part of a much larger, multi-scale groundwater system and we must consider protection of the shorter and long-term water sources. This will require a fundamental reassessment of our current approach to fen conservation, which is primarily based on protection of individual fens and their immediate surroundings. Clearly, in the future we must plan for conservation of the broad recharge areas and the multiple fen complexes they support.

Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention.

PubMed

Zhang, Yanhang; Barocas, Victor H; Berceli, Scott A; Clancy, Colleen E; Eckmann, David M; Garbey, Marc; Kassab, Ghassan S; Lochner, Donna R; McCulloch, Andrew D; Tran-Son-Tay, Roger; Trayanova, Natalia A

2016-09-01

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications.

Multiscale Simulations of Dynamics of Ferroelectric Domains

NASA Astrophysics Data System (ADS)

Liu, Shi

Ferroelectrics with switchable polarization have many important technological applications, which heavily rely on the interactions between the polarization and external perturbations. Understanding the dynamical response of ferroelectric materials is crucial for the discovery and development of new design principles and engineering strategies for optimized and breakthrough applications of ferroelectrics. We developed a multiscale computational approach that combines methods at different length and time scales to elucidate the connection between local structures, domain dynamics, and macroscopic finite-temperature properties of ferroelectrics. We started from first-principles calculations of ferroelectrics to build a model interatomic potential, enabling large-scale molecular dynamics (MD) simulations. The atomistic insights of nucleation and growth at the domain wall obtained from MD were then incorporated into a continuum model within the framework of Landau-Ginzburg-Devonshire theory. This progressive theoretical framework allows for the first time an efficient and accurate estimation of macroscopic properties such as the coercive field for a broad range of ferroelectrics from first-principles. This multiscale approach has also been applied to explore the effect of dipolar defects on ferroelectric switching and to understand the origin of giant electro-strain coupling. ONR, NSF, Carnegie Institution for Science.

A 3D Hermite-based multiscale local active contour method with elliptical shape constraints for segmentation of cardiac MR and CT volumes.

PubMed

Barba-J, Leiner; Escalante-Ramírez, Boris; Vallejo Venegas, Enrique; Arámbula Cosío, Fernando

2018-05-01

Analysis of cardiac images is a fundamental task to diagnose heart problems. Left ventricle (LV) is one of the most important heart structures used for cardiac evaluation. In this work, we propose a novel 3D hierarchical multiscale segmentation method based on a local active contour (AC) model and the Hermite transform (HT) for LV analysis in cardiac magnetic resonance (MR) and computed tomography (CT) volumes in short axis view. Features such as directional edges, texture, and intensities are analyzed using the multiscale HT space. A local AC model is configured using the HT coefficients and geometrical constraints. The endocardial and epicardial boundaries are used for evaluation. Segmentation of the endocardium is controlled using elliptical shape constraints. The final endocardial shape is used to define the geometrical constraints for segmentation of the epicardium. We follow the assumption that epicardial and endocardial shapes are similar in volumes with short axis view. An initialization scheme based on a fuzzy C-means algorithm and mathematical morphology was designed. The algorithm performance was evaluated using cardiac MR and CT volumes in short axis view demonstrating the feasibility of the proposed method.

Application of optimized multiscale mathematical morphology for bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Gong, Tingkai; Yuan, Yanbin; Yuan, Xiaohui; Wu, Xiaotao

2017-04-01

In order to suppress noise effectively and extract the impulsive features in the vibration signals of faulty rolling element bearings, an optimized multiscale morphology (OMM) based on conventional multiscale morphology (CMM) and iterative morphology (IM) is presented in this paper. Firstly, the operator used in the IM method must be non-idempotent; therefore, an optimized difference (ODIF) operator has been designed. Furthermore, in the iterative process the current operation is performed on the basis of the previous one. This means that if a larger scale is employed, more fault features are inhibited. Thereby, a unit scale is proposed as the structuring element (SE) scale in IM. According to the above definitions, the IM method is implemented on the results over different scales obtained by CMM. The validity of the proposed method is first evaluated by a simulated signal. Subsequently, aimed at an outer race fault two vibration signals sampled by different accelerometers are analyzed by OMM and CMM, respectively. The same is done for an inner race fault. The results show that the optimized method is effective in diagnosing the two bearing faults. Compared with the CMM method, the OMM method can extract much more fault features under strong noise background.

Multi-scale Modeling of the Cardiovascular System: Disease Development, Progression, and Clinical Intervention

PubMed Central

Zhang, Yanhang; Barocas, Victor H.; Berceli, Scott A.; Clancy, Colleen E.; Eckmann, David M.; Garbey, Marc; Kassab, Ghassan S.; Lochner, Donna R.; McCulloch, Andrew D.; Tran-Son-Tay, Roger; Trayanova, Natalia A.

2016-01-01

Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications. PMID:27138523

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

Infrared and visible image fusion based on visual saliency map and weighted least square optimization

NASA Astrophysics Data System (ADS)

Ma, Jinlei; Zhou, Zhiqiang; Wang, Bo; Zong, Hua

2017-05-01

The goal of infrared (IR) and visible image fusion is to produce a more informative image for human observation or some other computer vision tasks. In this paper, we propose a novel multi-scale fusion method based on visual saliency map (VSM) and weighted least square (WLS) optimization, aiming to overcome some common deficiencies of conventional methods. Firstly, we introduce a multi-scale decomposition (MSD) using the rolling guidance filter (RGF) and Gaussian filter to decompose input images into base and detail layers. Compared with conventional MSDs, this MSD can achieve the unique property of preserving the information of specific scales and reducing halos near edges. Secondly, we argue that the base layers obtained by most MSDs would contain a certain amount of residual low-frequency information, which is important for controlling the contrast and overall visual appearance of the fused image, and the conventional "averaging" fusion scheme is unable to achieve desired effects. To address this problem, an improved VSM-based technique is proposed to fuse the base layers. Lastly, a novel WLS optimization scheme is proposed to fuse the detail layers. This optimization aims to transfer more visual details and less irrelevant IR details or noise into the fused image. As a result, the fused image details would appear more naturally and be suitable for human visual perception. Experimental results demonstrate that our method can achieve a superior performance compared with other fusion methods in both subjective and objective assessments.

3D Digital Surveying and Modelling of Cave Geometry: Application to Paleolithic Rock Art.

PubMed

González-Aguilera, Diego; Muñoz-Nieto, Angel; Gómez-Lahoz, Javier; Herrero-Pascual, Jesus; Gutierrez-Alonso, Gabriel

2009-01-01

3D digital surveying and modelling of cave geometry represents a relevant approach for research, management and preservation of our cultural and geological legacy. In this paper, a multi-sensor approach based on a terrestrial laser scanner, a high-resolution digital camera and a total station is presented. Two emblematic caves of Paleolithic human occupation and situated in northern Spain, "Las Caldas" and "Peña de Candamo", have been chosen to put in practise this approach. As a result, an integral and multi-scalable 3D model is generated which may allow other scientists, pre-historians, geologists…, to work on two different levels, integrating different Paleolithic Art datasets: (1) a basic level based on the accurate and metric support provided by the laser scanner; and (2) a advanced level using the range and image-based modelling.

Plant trait detection with multi-scale spectrometry

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Wang, R.

2017-12-01

Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.

Content Preserving Watermarking for Medical Images Using Shearlet Transform and SVD

NASA Astrophysics Data System (ADS)

Favorskaya, M. N.; Savchina, E. I.

2017-05-01

Medical Image Watermarking (MIW) is a special field of a watermarking due to the requirements of the Digital Imaging and COmmunications in Medicine (DICOM) standard since 1993. All 20 parts of the DICOM standard are revised periodically. The main idea of the MIW is to embed various types of information including the doctor's digital signature, fragile watermark, electronic patient record, and main watermark in a view of region of interest for the doctor into the host medical image. These four types of information are represented in different forms; some of them are encrypted according to the DICOM requirements. However, all types of information ought to be resulted into the generalized binary stream for embedding. The generalized binary stream may have a huge volume. Therefore, not all watermarking methods can be applied successfully. Recently, the digital shearlet transform had been introduced as a rigorous mathematical framework for the geometric representation of multi-dimensional data. Some modifications of the shearlet transform, particularly the non-subsampled shearlet transform, can be associated to a multi-resolution analysis that provides a fully shift-invariant, multi-scale, and multi-directional expansion. During experiments, a quality of the extracted watermarks under the JPEG compression and typical internet attacks was estimated using several metrics, including the peak signal to noise ratio, structural similarity index measure, and bit error rate.

Intelligent Multi-scale Sensors for Damage Identification and Mitigation in Woven Composites for Aerospace Structural Applications

DTIC Science & Technology

2012-08-15

Bragg grating ( FBG ) sensors within these composite structures allows one to correlate sensor response features to “critical damage events” within the...material. The unique capabilities of this identification strategy are due to the detailed information obtained from the FBG sensors and the... FBG sensors relate to damage states not merely strain amplitudes. The research objectives of this project were therefore to:  demonstrate FBG

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-06-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Automated Pathogenesis-Based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning.

PubMed

Han, Zhongyi; Wei, Benzheng; Leung, Stephanie; Nachum, Ilanit Ben; Laidley, David; Li, Shuo

2018-02-15

Pathogenesis-based diagnosis is a key step to prevent and control lumbar neural foraminal stenosis (LNFS). It conducts both early diagnosis and comprehensive assessment by drawing crucial pathological links between pathogenic factors and LNFS. Automated pathogenesis-based diagnosis would simultaneously localize and grade multiple spinal organs (neural foramina, vertebrae, intervertebral discs) to diagnose LNFS and discover pathogenic factors. The automated way facilitates planning optimal therapeutic schedules and relieving clinicians from laborious workloads. However, no successful work has been achieved yet due to its extreme challenges since 1) multiple targets: each lumbar spine has at least 17 target organs, 2) multiple scales: each type of target organ has structural complexity and various scales across subjects, and 3) multiple tasks, i.e., simultaneous localization and diagnosis of all lumbar organs, are extremely difficult than individual tasks. To address these huge challenges, we propose a deep multiscale multitask learning network (DMML-Net) integrating a multiscale multi-output learning and a multitask regression learning into a fully convolutional network. 1) DMML-Net merges semantic representations to reinforce the salience of numerous target organs. 2) DMML-Net extends multiscale convolutional layers as multiple output layers to boost the scale-invariance for various organs. 3) DMML-Net joins a multitask regression module and a multitask loss module to prompt the mutual benefit between tasks. Extensive experimental results demonstrate that DMML-Net achieves high performance (0.845 mean average precision) on T1/T2-weighted MRI scans from 200 subjects. This endows our method an efficient tool for clinical LNFS diagnosis.

Standard Model in multiscale theories and observational constraints

NASA Astrophysics Data System (ADS)

Calcagni, Gianluca; Nardelli, Giuseppe; Rodríguez-Fernández, David

2016-08-01

We construct and analyze the Standard Model of electroweak and strong interactions in multiscale spacetimes with (i) weighted derivatives and (ii) q -derivatives. Both theories can be formulated in two different frames, called fractional and integer picture. By definition, the fractional picture is where physical predictions should be made. (i) In the theory with weighted derivatives, it is shown that gauge invariance and the requirement of having constant masses in all reference frames make the Standard Model in the integer picture indistinguishable from the ordinary one. Experiments involving only weak and strong forces are insensitive to a change of spacetime dimensionality also in the fractional picture, and only the electromagnetic and gravitational sectors can break the degeneracy. For the simplest multiscale measures with only one characteristic time, length and energy scale t*, ℓ* and E*, we compute the Lamb shift in the hydrogen atom and constrain the multiscale correction to the ordinary result, getting the absolute upper bound t*<10-23 s . For the natural choice α0=1 /2 of the fractional exponent in the measure, this bound is strengthened to t*<10-29 s , corresponding to ℓ*<10-20 m and E*>28 TeV . Stronger bounds are obtained from the measurement of the fine-structure constant. (ii) In the theory with q -derivatives, considering the muon decay rate and the Lamb shift in light atoms, we obtain the independent absolute upper bounds t*<10-13 s and E*>35 MeV . For α0=1 /2 , the Lamb shift alone yields t*<10-27 s , ℓ*<10-19 m and E*>450 GeV .

Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-03-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Multiscale analysis: a way to investigate laser damage precursors in materials for high power applications at nanosecond pulse duration

NASA Astrophysics Data System (ADS)

Natoli, J. Y.; Wagner, F.; Ciapponi, A.; Capoulade, J.; Gallais, L.; Commandré, M.

2010-11-01

The mechanism of laser induced damage in optical materials under high power nanosecond laser irradiation is commonly attributed to the presence of precursor centers. Depending on material and laser source, the precursors could have different origins. Some of them are clearly extrinsic, such as impurities or structural defects linked to the fabrication conditions. In most cases the center size ranging from sub-micrometer to nanometer scale does not permit an easy detection by optical techniques before irradiation. Most often, only a post mortem observation of optics permits to proof the local origin of breakdown. Multi-scale analyzes by changing irradiation beam size have been performed to investigate the density, size and nature of laser damage precursors. Destructive methods such as raster scan, laser damage probability plot and morphology studies permit to deduce the precursor densities. Another experimental way to get information on nature of precursors is to use non destructive methods such as photoluminescence and absorption measurements. The destructive and non destructive multiscale studies are also motivated for practical reasons. Indeed LIDT studies of large optics as those used in LMJ or NIF projects are commonly performed on small samples and with table top lasers whose characteristics change from one to another. In these conditions, it is necessary to know exactly the influence of the different experimental parameters and overall the spot size effect on the final data. In this paper, we present recent developments in multiscale characterization and results obtained on optical coatings (surface case) and KDP crystal (bulk case).

A Multiscale Computational Model Combining a Single Crystal Plasticity Constitutive Model with the Generalized Method of Cells (GMC) for Metallic Polycrystals.

PubMed

Ghorbani Moghaddam, Masoud; Achuthan, Ajit; Bednarcyk, Brett A; Arnold, Steven M; Pineda, Evan J

2016-05-04

A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level, i.e. , each individual grain. Two-three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities.

A Multiscale Computational Model Combining a Single Crystal Plasticity Constitutive Model with the Generalized Method of Cells (GMC) for Metallic Polycrystals

PubMed Central

Ghorbani Moghaddam, Masoud; Achuthan, Ajit; Bednarcyk, Brett A.; Arnold, Steven M.; Pineda, Evan J.

2016-01-01

A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level, i.e., each individual grain. Two–three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities. PMID:28773458

Multiscale Informatics for Low-Temperature Propane Oxidation: Further Complexities in Studies of Complex Reactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burke, Michael P.; Goldsmith, C. Franklin; Klippenstein, Stephen J.

2015-07-16

We have developed a multi-scale approach (Burke, M. P.; Klippenstein, S. J.; Harding, L. B. Proc. Combust. Inst. 2013, 34, 547–555.) to kinetic model formulation that directly incorporates elementary kinetic theories as a means to provide reliable, physics-based extrapolation to unexplored conditions. Here, we extend and generalize the multi-scale modeling strategy to treat systems of considerable complexity – involving multi-well reactions, potentially missing reactions, non-statistical product branching ratios, and non-Boltzmann (i.e. non-thermal) reactant distributions. The methodology is demonstrated here for a subsystem of low-temperature propane oxidation, as a representative system for low-temperature fuel oxidation. A multi-scale model is assembled andmore » informed by a wide variety of targets that include ab initio calculations of molecular properties, rate constant measurements of isolated reactions, and complex systems measurements. Active model parameters are chosen to accommodate both “parametric” and “structural” uncertainties. Theoretical parameters (e.g. barrier heights) are included as active model parameters to account for parametric uncertainties in the theoretical treatment; experimental parameters (e.g. initial temperatures) are included to account for parametric uncertainties in the physical models of the experiments. RMG software is used to assess potential structural uncertainties due to missing reactions. Additionally, branching ratios among product channels are included as active model parameters to account for structural uncertainties related to difficulties in modeling sequences of multiple chemically activated steps. The approach is demonstrated here for interpreting time-resolved measurements of OH, HO2, n-propyl, i-propyl, propene, oxetane, and methyloxirane from photolysis-initiated low-temperature oxidation of propane at pressures from 4 to 60 Torr and temperatures from 300 to 700 K. In particular, the multi-scale informed model provides a consistent quantitative explanation of both ab initio calculations and time-resolved species measurements. The present results show that interpretations of OH measurements are significantly more complicated than previously thought – in addition to barrier heights for key transition states considered previously, OH profiles also depend on additional theoretical parameters for R + O2 reactions, secondary reactions, QOOH + O2 reactions, and treatment of non-Boltzmann reaction sequences. Extraction of physically rigorous information from those measurements may require more sophisticated treatment of all of those model aspects, as well as additional experimental data under more conditions, to discriminate among possible interpretations and ensure model reliability. Keywords: Optimization, Uncertainty quantification, Chemical mechanism, Low-Temperature Oxidation, Non-Boltzmann« less

Synthetic fossilization of soft biological tissues and their shape-preserving transformation into silica or electron-conductive replicas

DOE PAGES

Townson, Jason L.; Lin, Yu-Shen; Chou, Stanley S.; ...

2014-12-08

Structural preservation of complex biological systems from the subcellular to whole organism level in robust forms, enabling dissection and imaging while preserving 3D context, represents an enduring grand challenge in biology. Here we report a simple immersion method for structurally preserving intact organisms via conformal stabilization within silica. This self-limiting process, which we refer to as silica bioreplication, occurs by condensation of water-soluble silicic acid proximally to biomolecular interfaces throughout the organism. Conformal nanoscopic silicification of all biomolecular features imparts structural rigidity enabling the preservation of shape and nano-to-macroscale dimensional features upon drying to form a biocomposite and further highmore » temperature oxidative calcination to form silica replicas or reductive pyrolysis to form electrically conductive carbon replicas of complete organisms. Ultimately, the simplicity and generalizability of this approach should facilitate efforts in biological preservation and analysis and could enable the development of new classes of biomimetic composite materials.« less

Towards a Multiscale Approach to Cybersecurity Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogan, Emilie A.; Hui, Peter SY; Choudhury, Sutanay

2013-11-12

We propose a multiscale approach to modeling cyber networks, with the goal of capturing a view of the network and overall situational awareness with respect to a few key properties--- connectivity, distance, and centrality--- for a system under an active attack. We focus on theoretical and algorithmic foundations of multiscale graphs, coming from an algorithmic perspective, with the goal of modeling cyber system defense as a specific use case scenario. We first define a notion of \\emph{multiscale} graphs, in contrast with their well-studied single-scale counterparts. We develop multiscale analogs of paths and distance metrics. As a simple, motivating example ofmore » a common metric, we present a multiscale analog of the all-pairs shortest-path problem, along with a multiscale analog of a well-known algorithm which solves it. From a cyber defense perspective, this metric might be used to model the distance from an attacker's position in the network to a sensitive machine. In addition, we investigate probabilistic models of connectivity. These models exploit the hierarchy to quantify the likelihood that sensitive targets might be reachable from compromised nodes. We believe that our novel multiscale approach to modeling cyber-physical systems will advance several aspects of cyber defense, specifically allowing for a more efficient and agile approach to defending these systems.« less

Filters for Improvement of Multiscale Data from Atomistic Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, David J.; Reynolds, Daniel R.

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less

Filters for Improvement of Multiscale Data from Atomistic Simulations

DOE PAGES

Gardner, David J.; Reynolds, Daniel R.

2017-01-05

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due tomore » sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.« less

Soft-Bodied Fossils Are Not Simply Rotten Carcasses - Toward a Holistic Understanding of Exceptional Fossil Preservation: Exceptional Fossil Preservation Is Complex and Involves the Interplay of Numerous Biological and Geological Processes.

PubMed

Parry, Luke A; Smithwick, Fiann; Nordén, Klara K; Saitta, Evan T; Lozano-Fernandez, Jesus; Tanner, Alastair R; Caron, Jean-Bernard; Edgecombe, Gregory D; Briggs, Derek E G; Vinther, Jakob

2018-01-01

Exceptionally preserved fossils are the product of complex interplays of biological and geological processes including burial, autolysis and microbial decay, authigenic mineralization, diagenesis, metamorphism, and finally weathering and exhumation. Determining which tissues are preserved and how biases affect their preservation pathways is important for interpreting fossils in phylogenetic, ecological, and evolutionary frameworks. Although laboratory decay experiments reveal important aspects of fossilization, applying the results directly to the interpretation of exceptionally preserved fossils may overlook the impact of other key processes that remove or preserve morphological information. Investigations of fossils preserving non-biomineralized tissues suggest that certain structures that are decay resistant (e.g., the notochord) are rarely preserved (even where carbonaceous components survive), and decay-prone structures (e.g., nervous systems) can fossilize, albeit rarely. As we review here, decay resistance is an imperfect indicator of fossilization potential, and a suite of biological and geological processes account for the features preserved in exceptional fossils. © 2017 The Authors. BioEssays Published by WILEY Periodicals, Inc.

Multiscale Modelling of the 2011 Tohoku Tsunami with Fluidity: Coastal Inundation and Run-up.

NASA Astrophysics Data System (ADS)

Hill, J.; Martin-Short, R.; Piggott, M. D.; Candy, A. S.

2014-12-01

Tsunami-induced flooding represents one of the most dangerous natural hazards to coastal communities around the world, as exemplified by Tohoku tsunami of March 2011. In order to further understand this hazard and to design appropriate mitigation it is necessary to develop versatile, accurate software capable of simulating large scale tsunami propagation and interaction with coastal geomorphology on a local scale. One such software package is Fluidity, an open source, finite element, multiscale, code that is capable of solving the fully three dimensional Navier-Stokes equations on unstructured meshes. Such meshes are significantly better at representing complex coastline shapes than structured meshes and have the advantage of allowing variation in element size across a domain. Furthermore, Fluidity incorporates a novel wetting and drying algorithm, which enables accurate, efficient simulation of tsunami run-up over complex, multiscale, topography. Fluidity has previously been demonstrated to accurately simulate the 2011 Tohoku tsunami (Oishi et al 2013) , but its wetting and drying facility has not yet been tested on a geographical scale. This study makes use of Fluidity to simulate the 2011 Tohoku tsunami and its interaction with Japan's eastern shoreline, including coastal flooding. The results are validated against observations made by survey teams, aerial photographs and previous modelling efforts in order to evaluate Fluidity's current capabilities and suggest methods of future improvement. The code is shown to perform well at simulating flooding along the topographically complex Tohoku coast of Japan, with major deviations between model and observation arising mainly due to limitations imposed by bathymetry resolution, which could be improved in future. In theory, Fluidity is capable of full multiscale tsunami modelling, thus enabling researchers to understand both wave propagation across ocean basins and flooding of coastal landscapes down to interaction with individual defence structures. This makes the code an exciting candidate for use in future studies aiming to investigate tsunami risk elsewhere in the world. Oishi, Y. et al. Three-dimensional tsunami propagation simulations using an unstructured mesh finite element model. J. Geophys. Res. [Solid Earth] 118, 2998-3018 (2013).

Towards a Multi-Scale Understanding of Thermoacoustic Fatigue in Aerospace Materials and Structure

DTIC Science & Technology

2016-05-31

for public release: distribution unlimited. 3.1.3 Pulsed laser Litron Nano This is a commercially available laser (Nano L200-10, Litron, Rugby , England...to disseminate recent research support by AFOSR and EOARD and associated work supported via European Union FP7 grants entitled ‘AD- VISE’ (Grant no

MULTI-SCALE CONTROLS ON AND CONSEQUENCES OF AEOLIAN PROCESSES IN LANDSCAPE CHANGE IN ARID AND SEMI-ARID ENVIRONMENTS

EPA Science Inventory

This paper reviews the controls on aeolian processes and their consequences at plant-interspace, patch-landscape, and regional-global scales. Based on this review, we define the requirements for a cross-scale model of wind erosion in structurally complex arid and semiarid ecosyst...

Multiscale Concrete Modeling of Aging Degradation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammi, Yousseff; Gullett, Philipp; Horstemeyer, Mark F.

In this work a numerical finite element framework is implemented to enable the integration of coupled multiscale and multiphysics transport processes. A User Element subroutine (UEL) in Abaqus is used to simultaneously solve stress equilibrium, heat conduction, and multiple diffusion equations for 2D and 3D linear and quadratic elements. Transport processes in concrete structures and their degradation mechanisms are presented along with the discretization of the governing equations. The multiphysics modeling framework is theoretically extended to the linear elastic fracture mechanics (LEFM) by introducing the eXtended Finite Element Method (XFEM) and based on the XFEM user element implementation of Ginermore » et al. [2009]. A damage model that takes into account the damage contribution from the different degradation mechanisms is theoretically developed. The total contribution of damage is forwarded to a Multi-Stage Fatigue (MSF) model to enable the assessment of the fatigue life and the deterioration of reinforced concrete structures in a nuclear power plant. Finally, two examples are presented to illustrate the developed multiphysics user element implementation and the XFEM implementation of Giner et al. [2009].« less

Influence of Temperature on Transdermal Penetration Enhancing Mechanism of Borneol: A Multi-Scale Study

PubMed Central

Yin, Qianqian; Wang, Ran; Yang, Shufang; Wu, Zhimin; Guo, Shujuan; Dai, Xingxing; Qiao, Yanjiang; Shi, Xinyuan

2017-01-01

The influence of temperature on the transdermal permeation enhancing mechanism of borneol (BO) was investigated using a multi-scale method, containing a coarse-grained molecular dynamic (CG-MD) simulation, an in vitro permeation experiment, and a transmission electron microscope (TEM) study. The results showed that BO has the potential to be used as a transdermal penetration enhancer to help osthole (OST) penetrate into the bilayer. With the increasing temperature, the stratum corneum (SC) becomes more flexible, proving to be synergistic with the permeation enhancement of BO, and the lag time (TLag) of BO and OST are shortened. However, when the temperature increased too much, with the effect of BO, the structure of SC was destroyed; for example, a water pore was formed and the micelle reversed. Though there were a number of drugs coming into the SC, the normal bilayer structure was absent. In addition, through comparing the simulation, in vitro experiment, and TEM study, we concluded that the computer simulation provided some visually detailed information, and the method plays an important role in related studies of permeation. PMID:28106833

Spatial vision processes: From the optical image to the symbolic structures of contour information

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1988-01-01

The significance of machine and natural vision is discussed together with the need for a general approach to image acquisition and processing aimed at recognition. An exploratory scheme is proposed which encompasses the definition of spatial primitives, intrinsic image properties and sampling, 2-D edge detection at the smallest scale, the construction of spatial primitives from edges, and the isolation of contour information from textural information. Concepts drawn from or suggested by natural vision at both perceptual and physiological levels are relied upon heavily to guide the development of the overall scheme. The scheme is intended to provide a larger context in which to place the emerging technology of detector array focal-plane processors. The approach differs from many recent efforts in edge detection and image coding by emphasizing smallest scale edge detection as a foundation for multi-scale symbolic processing while diminishing somewhat the importance of image convolutions with multi-scale edge operators. Cursory treatments of information theory illustrate that the direct application of this theory to structural information in images could not be realized.

Fourth-power law structure of the shock wave fronts in metals and ceramics

NASA Astrophysics Data System (ADS)

Bayandin, Yuriy; Naimark, Oleg; Saveleva, Natalia

2017-06-01

The plate impact experiments were performed for solids during last fifty years. It was established that the dependence between the strain rate and the shock wave amplitude for metals and ceramics expressed by a fourth-power law. Present study is focused on the theoretical investigation and numerical simulation of plane shock wave propagation in metals and ceramics. Statistically based constitutive model of solid with defects (microcracks and microshears) was developed to provide the relation between damage induced mechanisms of structural relaxation, thermally activated plastic flow and material reactions for extreme loading conditions. Original approach based on the wide range constitutive equations was proposed for the numerical simulation of multiscale damage-failure transition mechanisms and plane shock wave propagation in solids with defects in the range of strain rate 103 -108s-1 . It was shown that mechanisms of plastic relaxation and damage-failure transitions are linked to the multiscale kinetics of defects leading to the self-similar nature of shock wave fronts in metals and ceramics. The work was supported by the Russian Science Foundation (Project No. 14-19-01173).

The effect of large-scale model time step and multiscale coupling frequency on cloud climatology, vertical structure, and rainfall extremes in a superparameterized GCM

DOE PAGES

Yu, Sungduk; Pritchard, Michael S.

2015-12-17

The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2) and longwave cloud forcing (~5 W/m 2) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation ismore » more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.« less

The effect of large-scale model time step and multiscale coupling frequency on cloud climatology, vertical structure, and rainfall extremes in a superparameterized GCM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Sungduk; Pritchard, Michael S.

The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2) and longwave cloud forcing (~5 W/m 2) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation ismore » more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.« less

Modelling approaches for evaluating multiscale tendon mechanics

PubMed Central

Fang, Fei; Lake, Spencer P.

2016-01-01

Tendon exhibits anisotropic, inhomogeneous and viscoelastic mechanical properties that are determined by its complicated hierarchical structure and varying amounts/organization of different tissue constituents. Although extensive research has been conducted to use modelling approaches to interpret tendon structure–function relationships in combination with experimental data, many issues remain unclear (i.e. the role of minor components such as decorin, aggrecan and elastin), and the integration of mechanical analysis across different length scales has not been well applied to explore stress or strain transfer from macro- to microscale. This review outlines mathematical and computational models that have been used to understand tendon mechanics at different scales of the hierarchical organization. Model representations at the molecular, fibril and tissue levels are discussed, including formulations that follow phenomenological and microstructural approaches (which include evaluations of crimp, helical structure and the interaction between collagen fibrils and proteoglycans). Multiscale modelling approaches incorporating tendon features are suggested to be an advantageous methodology to understand further the physiological mechanical response of tendon and corresponding adaptation of properties owing to unique in vivo loading environments. PMID:26855747

Multiscale Homogenization Theory: An Analysis Tool for Revealing Mechanical Design Principles in Bone and Bone Replacement Materials

NASA Astrophysics Data System (ADS)

Hellmich, Christian; Fritsch, Andreas; Dormieux, Luc

Biomimetics deals with the application of nature-made "design solutions" to the realm of engineering. In the quest to understand mechanical implications of structural hierarchies found in biological materials, multiscale mechanics may hold the key to understand "building plans" inherent to entire material classes, here bone and bone replacement materials. Analyzing a multitude of biophysical hierarchical and biomechanical experiments through homogenization theories for upscaling stiffness and strength properties reveals the following design principles: The elementary component "collagen" induces, right at the nanolevel, the mechanical anisotropy of bone materials, which is amplified by fibrillar collagen-based structures at the 100-nm scale, and by pores in the micrometer-to-millimeter regime. Hydroxyapatite minerals are poorly organized, and provide stiffness and strength in a quasi-brittle manner. Water layers between hydroxyapatite crystals govern the inelastic behavior of the nanocomposite, unless the "collagen reinforcement" breaks. Bone replacement materials should mimic these "microstructural mechanics" features as closely as possible if an imitation of the natural form of bone is desired (Gebeshuber et al., Adv Mater Res 74:265-268, 2009).

Dynamical glucometry: Use of multiscale entropy analysis in diabetes

NASA Astrophysics Data System (ADS)

Costa, Madalena D.; Henriques, Teresa; Munshi, Medha N.; Segal, Alissa R.; Goldberger, Ary L.

2014-09-01

Diabetes mellitus (DM) is one of the world's most prevalent medical conditions. Contemporary management focuses on lowering mean blood glucose values toward a normal range, but largely ignores the dynamics of glucose fluctuations. We probed analyte time series obtained from continuous glucose monitor (CGM) sensors. We show that the fluctuations in CGM values sampled every 5 min are not uncorrelated noise. Next, using multiscale entropy analysis, we quantified the complexity of the temporal structure of the CGM time series from a group of elderly subjects with type 2 DM and age-matched controls. We further probed the structure of these CGM time series using detrended fluctuation analysis. Our findings indicate that the dynamics of glucose fluctuations from control subjects are more complex than those of subjects with type 2 DM over time scales ranging from about 5 min to 5 h. These findings support consideration of a new framework, dynamical glucometry, to guide mechanistic research and to help assess and compare therapeutic interventions, which should enhance complexity of glucose fluctuations and not just lower mean and variance of blood glucose levels.

Multilayer Brain Networks

NASA Astrophysics Data System (ADS)

Vaiana, Michael; Muldoon, Sarah Feldt

2018-01-01

The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

Magnetospheric Multiscale Mission Observations of Magnetic Flux Ropes in the Earth's Plasma Sheet

NASA Astrophysics Data System (ADS)

Slavin, J. A.; Akhavan-Tafti, M.; Poh, G.; Le, G.; Russell, C. T.; Nakamura, R.; Baumjohann, W.; Torbert, R. B.; Gershman, D. J.; Pollock, C. J.; Giles, B. L.; Moore, T. E.; Burch, J. L.

2017-12-01

A major discovery by the Cluster mission and the previous generation of science missions is the presence of earthward and tailward moving magnetic flux ropes in the Earth's plasma sheet. However, the lack of high-time resolution plasma measurements severely limited progress concerning the formation and evolution of these reconnection generated structures. We use high-time resolution magnetic and electric field and plasma measurements from the Magnetospheric Multiscale mission's first tail season to investigate: 1) the distribution of flux rope diameters relative to the local ion and electron inertial lengths; 2) the internal force balance sustaining these structures; and 3) the magnetic connectivity of the flux ropes to the Earth and/or the interplanetary medium; 4) the specific entropy of earthward moving flux ropes and the possible effect of "buoyancy" on how deep they penetrate into the inner magnetosphere; and 5) evidence for coalescence of adjacent flux ropes and/or the division of existing flux ropes through the formation of secondary X-lines. The results of these initial analyses will be discussed in terms of their implications for reconnection-driven magnetospheric dynamics and substorms.

Structural setting and kinematics of Nubian fault system, SE Western Desert, Egypt: An example of multi-reactivated intraplate strike-slip faults

NASA Astrophysics Data System (ADS)

Sakran, Shawky; Said, Said Mohamed

2018-02-01

Detailed surface geological mapping and subsurface seismic interpretation have been integrated to unravel the structural style and kinematic history of the Nubian Fault System (NFS). The NFS consists of several E-W Principal Deformation Zones (PDZs) (e.g. Kalabsha fault). Each PDZ is defined by spectacular E-W, WNW and ENE dextral strike-slip faults, NNE sinistral strike-slip faults, NE to ENE folds, and NNW normal faults. Each fault zone has typical self-similar strike-slip architecture comprising multi-scale fault segments. Several multi-scale uplifts and basins were developed at the step-over zones between parallel strike-slip fault segments as a result of local extension or contraction. The NNE faults consist of right-stepping sinistral strike-slip fault segments (e.g. Sin El Kiddab fault). The NNE sinistral faults extend for long distances ranging from 30 to 100 kms and cut one or two E-W PDZs. Two nearly perpendicular strike-slip tectonic regimes are recognized in the NFS; an inactive E-W Late Cretaceous - Early Cenozoic dextral transpression and an active NNE sinistral shear.

Multi-scale analysis and characterization of the ITER pre-compression rings

NASA Astrophysics Data System (ADS)

Foussat, A.; Park, B.; Rajainmaki, H.

2014-01-01

The toroidal field (TF) system of ITER Tokamak composed of 18 "D" shaped Toroidal Field (TF) coils during an operating scenario experiences out-of-plane forces caused by the interaction between the 68kA operating TF current and the poloidal magnetic fields. In order to keep the induced static and cyclic stress range in the intercoil shear keys between coils cases within the ITER allowable limits [1], centripetal preload is introduced by means of S2 fiber-glass/epoxy composite pre-compression rings (PCRs). Those PCRs consist in two sets of three rings, each 5 m in diameter and 337 × 288 mm in cross-section, and are installed at the top and bottom regions to apply a total resultant preload of 70 MN per TF coil equivalent to about 400 MPa hoop stress. Recent developments of composites in the aerospace industry have accelerated the use of advanced composites as primary structural materials. The PCRs represent one of the most challenging composite applications of large dimensions and highly stressed structures operating at 4 K over a long term life. Efficient design of those pre-compression composite structures requires a detailed understanding of both the failure behavior of the structure and the fracture behavior of the material. Due to the inherent difficulties to carry out real scale testing campaign, there is a need to develop simulation tools to predict the multiple complex failure mechanisms in pre-compression rings. A framework contract was placed by ITER Organization with SENER Ingenieria y Sistemas SA to develop multi-scale models representative of the composite structure of the Pre-compression rings based on experimental material data. The predictive modeling based on ABAQUS FEM provides the opportunity both to understand better how PCR composites behave in operating conditions and to support the development of materials by the supplier with enhanced performance to withstand the machine design lifetime of 30,000 cycles. The multi-scale stress analysis has revealed a complete picture of the stress levels within the fiber and the matrix regarding the static and fatigue performance of the rings structure including the presence of a delamination defect of critical size. The analysis results of the composite material demonstrate that the rings performance objectives under all loading and strength conditions are met.

Multiscale Materials Modeling Workshop Summary

DOT National Transportation Integrated Search

2013-12-01

This report summarizes a 2-day workshop held to share information on multiscale material modeling. The aim was to gain expert feedback on the state of the art and identify Exploratory Advanced Research (EAR) Program opportunities for multiscale mater...

A Multi-Scale Structural Health Monitoring Approach for Damage Detection, Diagnosis and Prognosis in Aerospace Structures

DTIC Science & Technology

2012-01-20

ultrasonic Lamb waves to plastic strain and fatigue life. Theory was developed and validated to predict second harmonic generation for specific mode... Fatigue and damage generation and progression are processes consisting of a series of interrelated events that span large scales of space and time...strain and fatigue life A set of experiments were completed that worked to relate the acoustic nonlinearity measured with Lamb waves to both the

Integration of multi-source and multi-scale datasets for 3D structural modeling for subsurface exploration targeting, Luanchuan Mo-polymetallic district, China

NASA Astrophysics Data System (ADS)

Wang, Gongwen; Ma, Zhenbo; Li, Ruixi; Song, Yaowu; Qu, Jianan; Zhang, Shouting; Yan, Changhai; Han, Jiangwei

2017-04-01

In this paper, multi-source (geophysical, geochemical, geological and remote sensing) datasets were used to construct multi-scale (district-, deposit-, and orebody-scale) 3D geological models and extract 3D exploration criteria for subsurface Mo-polymetallic exploration targeting in the Luanchuan district in China. The results indicate that (i) a series of region-/district-scale NW-trending thrusts controlled main Mo-polymetallic forming, and they were formed by regional Indosinian Qinling orogenic events, the secondary NW-trending district-scale folds and NE-trending faults and the intrusive stock structure are produced based on thrust structure in Caledonian-Indosinian orogenic events; they are ore-bearing zones and ore-forming structures; (ii) the NW-trending district-scale and NE-trending deposit-scale normal faults were crossed and controlled by the Jurassic granite stocks in 3D space, they are associated with the magma-skarn Mo polymetallic mineralization (the 3D buffer distance of ore-forming granite stocks is 600 m) and the NW-trending hydrothermal Pb-Zn deposits which are surrounded by the Jurassic granite stocks and constrained by NW-trending or NE-trending faults (the 3D buffer distance of ore-forming fault is 700 m); and (iii) nine Mo polymetallic and four Pb-Zn targets were identified in the subsurface of the Luanchuan district.

A multiphysics and multiscale model for low frequency electromagnetic direct-chill casting

NASA Astrophysics Data System (ADS)

Košnik, N.; Guštin, A. Z.; Mavrič, B.; Šarler, B.

2016-03-01

Simulation and control of macrosegregation, deformation and grain size in low frequency electromagnetic (EM) direct-chill casting (LFEMC) is important for downstream processing. Respectively, a multiphysics and multiscale model is developed for solution of Lorentz force, temperature, velocity, concentration, deformation and grain structure of LFEMC processed aluminum alloys, with focus on axisymmetric billets. The mixture equations with lever rule, linearized phase diagram, and stationary thermoelastic solid phase are assumed, together with EM induction equation for the field imposed by the coil. Explicit diffuse approximate meshless solution procedure [1] is used for solving the EM field, and the explicit local radial basis function collocation method [2] is used for solving the coupled transport phenomena and thermomechanics fields. Pressure-velocity coupling is performed by the fractional step method [3]. The point automata method with modified KGT model is used to estimate the grain structure [4] in a post-processing mode. Thermal, mechanical, EM and grain structure outcomes of the model are demonstrated. A systematic study of the complicated influences of the process parameters can be investigated by the model, including intensity and frequency of the electromagnetic field. The meshless solution framework, with the implemented simplest physical models, will be further extended by including more sophisticated microsegregation and grain structure models, as well as a more realistic solid and solid-liquid phase rheology.

Understanding physicochemical properties changes from multi-scale structures of starch/CNT nanocomposite films.

PubMed

Liu, Siyuan; Li, Xiaoxi; Chen, Ling; Li, Lin; Li, Bing; Zhu, Jie

2017-11-01

From the view of multi-scale structures of hydroxypropyl starch (HPS)/carbon nanotube (CNT) nanocomposite films, the film physicochemical properties were affected by comprehensive factors including molecular interaction, short range molecular conformation, crystalline structure and aggregated structure. The less original HPS hydrogen bonding that was broken, less decreased order of HPS short range molecular conformation, lower film crystallinity and larger size of micro-ordered regions contributed to higher tensile strength and Young's modulus of the film with CNT content of 0.5% (g/g, CNT in HPS). The higher film overall crystallinity and larger size of micro-ordered regions of the film with CNT content of 0.05%-0.3% compared with those of control contributed to better film barrier property. The addition of CNT with the content of 0.05%-0.5% broke the original HPS hydrogen bonding and decreased the order of starch short range molecular conformation, which counteracted the positive effect of CNT on the thermal stability of the material, thus thermal degradation temperature of these nanocomposite films did not increase. But the sharp increase of film crystallinity increased film thermal degradation temperature. This study provided a better understanding of film physicochemical properties changes which guides to rational design of starch-based nanocomposite films for packaging and coating application. Copyright © 2017. Published by Elsevier B.V.

Environmental degradation of composites for marine structures: new materials and new applications

PubMed Central

2016-01-01

This paper describes the influence of seawater ageing on composites used in a range of marine structures, from boats to tidal turbines. Accounting for environmental degradation is an essential element in the multi-scale modelling of composite materials but it requires reliable test data input. The traditional approach to account for ageing effects, based on testing samples after immersion for different periods, is evolving towards coupled studies involving strong interactions between water diffusion and mechanical loading. These can provide a more realistic estimation of long-term behaviour but still require some form of acceleration if useful data, for 20 year lifetimes or more, are to be obtained in a reasonable time. In order to validate extrapolations from short to long times, it is essential to understand the degradation mechanisms, so both physico-chemical and mechanical test data are required. Examples of results from some current studies on more environmentally friendly materials including bio-sourced composites will be described first. Then a case study for renewable marine energy applications will be discussed. In both cases, studies were performed first on coupons at the material level, then during structural testing and analysis of large components, in order to evaluate their long-term behaviour. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242304

Multi-scale analysis of bone chemistry, morphology and mechanics in the oim model of osteogenesis imperfecta.

PubMed

Bart, Zachary R; Hammond, Max A; Wallace, Joseph M

2014-08-01

Osteogenesis imperfecta is a congenital disease commonly characterized by brittle bones and caused by mutations in the genes encoding Type I collagen, the single most abundant protein produced by the body. The oim model has a natural collagen mutation, converting its heterotrimeric structure (two α1 and one α2 chains) into α1 homotrimers. This mutation in collagen may impact formation of the mineral, creating a brittle bone phenotype in animals. Femurs from male wild type (WT) and homozygous (oim/oim) mice, all at 12 weeks of age, were assessed using assays at multiple length scales with minimal sample processing to ensure a near-physiological state. Atomic force microscopy (AFM) demonstrated detectable differences in the organization of collagen at the nanoscale that may partially contribute to alterations in material and structural behavior obtained through mechanical testing and reference point indentation (RPI). Changes in geometric and chemical structure obtained from µ-Computed Tomography and Raman spectroscopy indicate a smaller bone with reduced trabecular architecture and altered chemical composition. Decreased tissue material properties in oim/oim mice are likely driven by changes in collagen fibril structure, decreasing space available for mineral nucleation and growth, as supported by a reduction in mineral crystallinity. Multi-scale analyses of this nature offer much in assessing how molecular changes compound to create a degraded, brittle bone phenotype.

Using multi-scale distribution and movement effects along a montane highway to identify optimal crossing locations for a large-bodied mammal community.

PubMed

Schuster, Richard; Römer, Heinrich; Germain, Ryan R

2013-01-01

Roads are a major cause of habitat fragmentation that can negatively affect many mammal populations. Mitigation measures such as crossing structures are a proposed method to reduce the negative effects of roads on wildlife, but the best methods for determining where such structures should be implemented, and how their effects might differ between species in mammal communities is largely unknown. We investigated the effects of a major highway through south-eastern British Columbia, Canada on several mammal species to determine how the highway may act as a barrier to animal movement, and how species may differ in their crossing-area preferences. We collected track data of eight mammal species across two winters, along both the highway and pre-marked transects, and used a multi-scale modeling approach to determine the scale at which habitat characteristics best predicted preferred crossing sites for each species. We found evidence for a severe barrier effect on all investigated species. Freely-available remotely-sensed habitat landscape data were better than more costly, manually-digitized microhabitat maps in supporting models that identified preferred crossing sites; however, models using both types of data were better yet. Further, in 6 of 8 cases models which incorporated multiple spatial scales were better at predicting preferred crossing sites than models utilizing any single scale. While each species differed in terms of the landscape variables associated with preferred/avoided crossing sites, we used a multi-model inference approach to identify locations along the highway where crossing structures may benefit all of the species considered. By specifically incorporating both highway and off-highway data and predictions we were able to show that landscape context plays an important role for maximizing mitigation measurement efficiency. Our results further highlight the need for mitigation measures along major highways to improve connectivity between mammal populations, and illustrate how multi-scale data can be used to identify preferred crossing sites for different species within a mammal community.

A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations

DOE PAGES

Scheibe, Timothy D.; Yang, Xiaofan; Chen, Xingyuan; ...

2015-06-01

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, ormore » system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.« less

Peridynamic Multiscale Finite Element Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Timothy; Bond, Stephen D.; Littlewood, David John

The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic andmore » local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.« less

Alternative transitions between existing representations in multi-scale maps

NASA Astrophysics Data System (ADS)

Dumont, Marion; Touya, Guillaume; Duchêne, Cécile

2018-05-01

Map users may have issues to achieve multi-scale navigation tasks, as cartographic objects may have various representations across scales. We assume that adding intermediate representations could be one way to reduce the differences between existing representations, and to ease the transitions across scales. We consider an existing multiscale map on the scale range from 1 : 25k to 1 : 100k scales. Based on hypotheses about intermediate representations design, we build custom multi-scale maps with alternative transitions. We will conduct in a next future a user evaluation to compare the efficiency of these alternative maps for multi-scale navigation. This paper discusses the hypotheses and production process of these alternative maps.

Electron Heating at Kinetic Scales in Magnetosheath Turbulence

NASA Technical Reports Server (NTRS)

Chasapis, Alexandros; Matthaeus, W. H.; Parashar, T. N.; Lecontel, O.; Retino, A.; Breuillard, H.; Khotyaintsev, Y.; Vaivads, A.; Lavraud, B.; Eriksson, E.;

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

DOE PAGES

Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.

2018-03-27

In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.

In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less

Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix and Polymer Matrix Composite Structures

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Bednarcyk, Brett A.; Pineda, Evan J.; Walton, Owen J.; Arnold, Steven M.

2016-01-01

Stochastic-based, discrete-event progressive damage simulations of ceramic-matrix composite and polymer matrix composite material structures have been enabled through the development of a unique multiscale modeling tool. This effort involves coupling three independently developed software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/ Life), and (3) the Abaqus finite element analysis (FEA) program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating unit cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC. Abaqus is used at the global scale to model the overall composite structure. An Abaqus user-defined material (UMAT) interface, referred to here as "FEAMAC/CARES," was developed that enables MAC/GMC and CARES/Life to operate seamlessly with the Abaqus FEA code. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events, which incrementally progress and lead to ultimate structural failure. This report describes the FEAMAC/CARES methodology and discusses examples that illustrate the performance of the tool. A comprehensive example problem, simulating the progressive damage of laminated ceramic matrix composites under various off-axis loading conditions and including a double notched tensile specimen geometry, is described in a separate report.

Structural dynamics of the lac repressor-DNA complex revealed by a multiscale simulation.

PubMed

Villa, Elizabeth; Balaeff, Alexander; Schulten, Klaus

2005-05-10

A multiscale simulation of a complex between the lac repressor protein (LacI) and a 107-bp-long DNA segment is reported. The complex between the repressor and two operator DNA segments is described by all-atom molecular dynamics; the size of the simulated system comprises either 226,000 or 314,000 atoms. The DNA loop connecting the operators is modeled as a continuous elastic ribbon, described mathematically by the nonlinear Kirchhoff differential equations with boundary conditions obtained from the coordinates of the terminal base pairs of each operator. The forces stemming from the looped DNA are included in the molecular dynamics simulations; the loop structure and the forces are continuously recomputed because the protein motions during the simulations shift the operators and the presumed termini of the loop. The simulations reveal the structural dynamics of the LacI-DNA complex in unprecedented detail. The multiple domains of LacI exhibit remarkable structural stability during the simulation, moving much like rigid bodies. LacI is shown to absorb the strain from the looped DNA mainly through its mobile DNA-binding head groups. Even with large fluctuating forces applied, the head groups tilt strongly and keep their grip on the operator DNA, while the remainder of the protein retains its V-shaped structure. A simulated opening of the cleft of LacI by 500-pN forces revealed the interactions responsible for locking LacI in the V-conformation.

Brain vascular image segmentation based on fuzzy local information C-means clustering

NASA Astrophysics Data System (ADS)

Hu, Chaoen; Liu, Xia; Liang, Xiao; Hui, Hui; Yang, Xin; Tian, Jie

2017-02-01

Light sheet fluorescence microscopy (LSFM) is a powerful optical resolution fluorescence microscopy technique which enables to observe the mouse brain vascular network in cellular resolution. However, micro-vessel structures are intensity inhomogeneity in LSFM images, which make an inconvenience for extracting line structures. In this work, we developed a vascular image segmentation method by enhancing vessel details which should be useful for estimating statistics like micro-vessel density. Since the eigenvalues of hessian matrix and its sign describes different geometric structure in images, which enable to construct vascular similarity function and enhance line signals, the main idea of our method is to cluster the pixel values of the enhanced image. Our method contained three steps: 1) calculate the multiscale gradients and the differences between eigenvalues of Hessian matrix. 2) In order to generate the enhanced microvessels structures, a feed forward neural network was trained by 2.26 million pixels for dealing with the correlations between multi-scale gradients and the differences between eigenvalues. 3) The fuzzy local information c-means clustering (FLICM) was used to cluster the pixel values in enhance line signals. To verify the feasibility and effectiveness of this method, mouse brain vascular images have been acquired by a commercial light-sheet microscope in our lab. The experiment of the segmentation method showed that dice similarity coefficient can reach up to 85%. The results illustrated that our approach extracting line structures of blood vessels dramatically improves the vascular image and enable to accurately extract blood vessels in LSFM images.

Geophysics and Nanosciences: Nano to Micro to Meso to Macro Scale Swelling Soils

NASA Astrophysics Data System (ADS)

Cushman, J.

2003-04-01

We use statistical mechanical simulations of nanoporous materials to motivate a choice of independent constitutive variables for a multiscale mixture theory of swelling soils. A video will illustrate the structural behavior of fluids in nanopores when they are adsorbed from a bulk phase vapor to form capillaries on the nanoscale. These simulations suggest that when a swelling soil is very dry, the full strain tensor for the liquid phase should be included in the list of independent variables in any mixture theory. We use this information to develop a three-scale (micro, meso, macro) mixture theory for swelling soils. For a simplified case, we present the underlying multiscale field equations and constitutive theory, solve the resultant well posed system numerically, and present some graphical results for a drying and shrinking body.

Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics.

PubMed

Chabiniok, Radomir; Wang, Vicky Y; Hadjicharalambous, Myrianthi; Asner, Liya; Lee, Jack; Sermesant, Maxime; Kuhl, Ellen; Young, Alistair A; Moireau, Philippe; Nash, Martyn P; Chapelle, Dominique; Nordsletten, David A

2016-04-06

With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.

A new multiscale air quality transport model (Fluidity, 4.1.9) using fully unstructured anisotropic adaptive mesh technology

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-06-01

A new anisotropic hr-adaptive mesh technique has been applied to modelling of multiscale transport phenomena, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been setup for two-dimensional (2-D) transport phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes.

From seconds to months: an overview of multi-scale dynamics of mobile telephone calls

NASA Astrophysics Data System (ADS)

Saramäki, Jari; Moro, Esteban

2015-06-01

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

Integral-geometry characterization of photobiomodulation effects on retinal vessel morphology

PubMed Central

Barbosa, Marconi; Natoli, Riccardo; Valter, Kriztina; Provis, Jan; Maddess, Ted

2014-01-01

The morphological characterization of quasi-planar structures represented by gray-scale images is challenging when object identification is sub-optimal due to registration artifacts. We propose two alternative procedures that enhances object identification in the integral-geometry morphological image analysis (MIA) framework. The first variant streamlines the framework by introducing an active contours segmentation process whose time step is recycled as a multi-scale parameter. In the second variant, we used the refined object identification produced in the first variant to perform the standard MIA with exact dilation radius as multi-scale parameter. Using this enhanced MIA we quantify the extent of vaso-obliteration in oxygen-induced retinopathic vascular growth, the preventative effect (by photobiomodulation) of exposure during tissue development to near-infrared light (NIR, 670 nm), and the lack of adverse effects due to exposure to NIR light. PMID:25071966

Mapping reactive flow patterns in monolithic nanoporous catalysts

DOE PAGES

Falcucci, Giacomo; Succi, Sauro; Montessori, Andrea; ...

2016-07-06

The development of high-efficiency porous catalyst membranes critically depends on our understanding of where the majority of the chemical conversions occur within the porous structure. This then requires mapping of chemical reactions and mass transport inside the complex nanoscale architecture of porous catalyst membranes which is a multiscale problem in both the temporal and spatial domains. In order to address this problem, we developed a multiscale mass transport computational framework based on the lattice Boltzmann method that allows us to account for catalytic reactions at the gas–solid interface by introducing a new boundary condition. In good agreement with experiments, themore » simulations reveal that most catalytic reactions occur near the gas-flow facing side of the catalyst membrane if chemical reactions are fast compared to mass transport within the porous catalyst membrane.« less

Robust segmentation of trabecular bone for in vivo CT imaging using anisotropic diffusion and multi-scale morphological reconstruction

NASA Astrophysics Data System (ADS)

Chen, Cheng; Jin, Dakai; Zhang, Xiaoliu; Levy, Steven M.; Saha, Punam K.

2017-03-01

Osteoporosis is associated with an increased risk of low-trauma fractures. Segmentation of trabecular bone (TB) is essential to assess TB microstructure, which is a key determinant of bone strength and fracture risk. Here, we present a new method for TB segmentation for in vivo CT imaging. The method uses Hessian matrix-guided anisotropic diffusion to improve local separability of trabecular structures, followed by a new multi-scale morphological reconstruction algorithm for TB segmentation. High sensitivity (0.93), specificity (0.93), and accuracy (0.92) were observed for the new method based on regional manual thresholding on in vivo CT images. Mechanical tests have shown that TB segmentation using the new method improved the ability of derived TB spacing measure for predicting actual bone strength (R2=0.83).

Multiscale characterization and analysis of shapes

DOEpatents

Prasad, Lakshman; Rao, Ramana

2002-01-01

An adaptive multiscale method approximates shapes with continuous or uniformly and densely sampled contours, with the purpose of sparsely and nonuniformly discretizing the boundaries of shapes at any prescribed resolution, while at the same time retaining the salient shape features at that resolution. In another aspect, a fundamental geometric filtering scheme using the Constrained Delaunay Triangulation (CDT) of polygonized shapes creates an efficient parsing of shapes into components that have semantic significance dependent only on the shapes' structure and not on their representations per se. A shape skeletonization process generalizes to sparsely discretized shapes, with the additional benefit of prunability to filter out irrelevant and morphologically insignificant features. The skeletal representation of characters of varying thickness and the elimination of insignificant and noisy spurs and branches from the skeleton greatly increases the robustness, reliability and recognition rates of character recognition algorithms.

The original colours of fossil beetles

PubMed Central

McNamara, Maria E.; Briggs, Derek E. G.; Orr, Patrick J.; Noh, Heeso; Cao, Hui

2012-01-01

Structural colours, the most intense, reflective and pure colours in nature, are generated when light is scattered by complex nanostructures. Metallic structural colours are widespread among modern insects and can be preserved in their fossil counterparts, but it is unclear whether the colours have been altered during fossilization, and whether the absence of colours is always real. To resolve these issues, we investigated fossil beetles from five Cenozoic biotas. Metallic colours in these specimens are generated by an epicuticular multi-layer reflector; the fidelity of its preservation correlates with that of other key cuticular ultrastructures. Where these other ultrastructures are well preserved in non-metallic fossil specimens, we can infer that the original cuticle lacked a multi-layer reflector; its absence in the fossil is not a preservational artefact. Reconstructions of the original colours of the fossils based on the structure of the multi-layer reflector show that the preserved colours are offset systematically to longer wavelengths; this probably reflects alteration of the refractive index of the epicuticle during fossilization. These findings will allow the former presence, and original hue, of metallic structural colours to be identified in diverse fossil insects, thus providing critical evidence of the evolution of structural colour in this group. PMID:21957131

The original colours of fossil beetles.

PubMed

McNamara, Maria E; Briggs, Derek E G; Orr, Patrick J; Noh, Heeso; Cao, Hui

2012-03-22

Structural colours, the most intense, reflective and pure colours in nature, are generated when light is scattered by complex nanostructures. Metallic structural colours are widespread among modern insects and can be preserved in their fossil counterparts, but it is unclear whether the colours have been altered during fossilization, and whether the absence of colours is always real. To resolve these issues, we investigated fossil beetles from five Cenozoic biotas. Metallic colours in these specimens are generated by an epicuticular multi-layer reflector; the fidelity of its preservation correlates with that of other key cuticular ultrastructures. Where these other ultrastructures are well preserved in non-metallic fossil specimens, we can infer that the original cuticle lacked a multi-layer reflector; its absence in the fossil is not a preservational artefact. Reconstructions of the original colours of the fossils based on the structure of the multi-layer reflector show that the preserved colours are offset systematically to longer wavelengths; this probably reflects alteration of the refractive index of the epicuticle during fossilization. These findings will allow the former presence, and original hue, of metallic structural colours to be identified in diverse fossil insects, thus providing critical evidence of the evolution of structural colour in this group.

Trial guidelines for the conservation of Virginia's historic bridges.

DOT National Transportation Integrated Search

1986-01-01

Interest in the preservation of historic engineering structures has increased dramatically over the past decade. Because civil engineering structures primarily serve functions in the public domain, their preservation focuses attention on what appear ...

Modes of fossil preservation

USGS Publications Warehouse

Schopf, J.M.

1975-01-01

The processes of geologic preservation are important for understanding the organisms represented by fossils. Some fossil differences are due to basic differences in organization of animals and plants, but the interpretation of fossils has also tended to be influenced by modes of preservation. Four modes of preservation generally can be distinguished: (1) Cellular permineralization ("petrifaction") preserves anatomical detail, and, occasionally, even cytologic structures. (2) Coalified compression, best illustrated by structures from coal but characteristic of many plant fossils in shale, preserves anatomical details in distorted form and produces surface replicas (impressions) on enclosing matrix. (3) Authigenic preservation replicates surface form or outline (molds and casts) prior to distortion by compression and, depending on cementation and timing, may intergrade with fossils that have been subject to compression. (4) Duripartic (hard part) preservation is characteristic of fossil skeletal remains, predominantly animal. Molds, pseudomorphs, or casts may form as bulk replacements following dissolution of the original fossil material, usually by leaching. Classification of the kinds of preservation in fossils will aid in identifying the processes responsible for modifying the fossil remains of both animals and plants. ?? 1975.

Computational modeling of the obstructive lung diseases asthma and COPD

PubMed Central

2014-01-01

Asthma and chronic obstructive pulmonary disease (COPD) are characterized by airway obstruction and airflow limitation and pose a huge burden to society. These obstructive lung diseases impact the lung physiology across multiple biological scales. Environmental stimuli are introduced via inhalation at the organ scale, and consequently impact upon the tissue, cellular and sub-cellular scale by triggering signaling pathways. These changes are propagated upwards to the organ level again and vice versa. In order to understand the pathophysiology behind these diseases we need to integrate and understand changes occurring across these scales and this is the driving force for multiscale computational modeling. There is an urgent need for improved diagnosis and assessment of obstructive lung diseases. Standard clinical measures are based on global function tests which ignore the highly heterogeneous regional changes that are characteristic of obstructive lung disease pathophysiology. Advances in scanning technology such as hyperpolarized gas MRI has led to new regional measurements of ventilation, perfusion and gas diffusion in the lungs, while new image processing techniques allow these measures to be combined with information from structural imaging such as Computed Tomography (CT). However, it is not yet known how to derive clinical measures for obstructive diseases from this wealth of new data. Computational modeling offers a powerful approach for investigating this relationship between imaging measurements and disease severity, and understanding the effects of different disease subtypes, which is key to developing improved diagnostic methods. Gaining an understanding of a system as complex as the respiratory system is difficult if not impossible via experimental methods alone. Computational models offer a complementary method to unravel the structure-function relationships occurring within a multiscale, multiphysics system such as this. Here we review the current state-of-the-art in techniques developed for pulmonary image analysis, development of structural models of the respiratory system and predictions of function within these models. We discuss application of modeling techniques to obstructive lung diseases, namely asthma and emphysema and the use of models to predict response to therapy. Finally we introduce a large European project, AirPROM that is developing multiscale models to investigate structure-function relationships in asthma and COPD. PMID:25471125

Application of process tomography in gas-solid fluidised beds in different scales and structures

NASA Astrophysics Data System (ADS)

Wang, H. G.; Che, H. Q.; Ye, J. M.; Tu, Q. Y.; Wu, Z. P.; Yang, W. Q.; Ocone, R.

2018-04-01

Gas-solid fluidised beds are commonly used in particle-related processes, e.g. for coal combustion and gasification in the power industry, and the coating and granulation process in the pharmaceutical industry. Because the operation efficiency depends on the gas-solid flow characteristics, it is necessary to investigate the flow behaviour. This paper is about the application of process tomography, including electrical capacitance tomography (ECT) and microwave tomography (MWT), in multi-scale gas-solid fluidisation processes in the pharmaceutical and power industries. This is the first time that both ECT and MWT have been applied for this purpose in multi-scale and complex structure. To evaluate the sensor design and image reconstruction and to investigate the effects of sensor structure and dimension on the image quality, a normalised sensitivity coefficient is introduced. In the meantime, computational fluid dynamic (CFD) analysis based on a computational particle fluid dynamic (CPFD) model and a two-phase fluid model (TFM) is used. Part of the CPFD-TFM simulation results are compared and validated by experimental results from ECT and/or MWT. By both simulation and experiment, the complex flow hydrodynamic behaviour in different scales is analysed. Time-series capacitance data are analysed both in time and frequency domains to reveal the flow characteristics.

Year 2 Report: Protein Function Prediction Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, C E

2012-04-27

Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fullymore » automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.« less

Multiscale Processes in Magnetic Reconnection

NASA Astrophysics Data System (ADS)

Surjalal Sharma, A.; Jain, Neeraj

The characteristic scales of the plasma processes in magnetic reconnection range from the elec-tron skin-depth to the magnetohydrodynamic (MHD) scale, and cross-scale coupling among them play a key role. Modeling these processes requires different physical models, viz. kinetic, electron-magnetohydrodynamics (EMHD), Hall-MHD, and MHD. The shortest scale processes are at the electron scale and these are modeled using an EMHD code, which provides many features of the multiscale behavior. In simulations using initial conditions consisting of pertur-bations with many scale sizes the reconnection takes place at many sites and the plasma flows from these interact with each other. This leads to thin current sheets with length less than 10 electron skin depths. The plasma flows also generate current sheets with multiple peaks, as observed by Cluster. The quadrupole structure of the magnetic field during reconnection starts on the electron scale and the interaction of inflow to the secondary sites and outflow from the dominant site generates a nested structure. In the outflow regions, the interaction of the electron outflows generated at the neighboring sites lead to the development of electron vortices. A signature of the nested structure of the Hall field is seen in Cluster observations, and more details of these features are expected from MMS.

Design and control of a multi-DOF micromanipulator dedicated to multiscale micromanipulation

NASA Astrophysics Data System (ADS)

Yang, Yi-Ling; Wei, Yan-Ding; Lou, Jun-Qiang; Fu, Lei; Fang, Sheng

2017-11-01

This paper presents the design, implementation and control of a new piezoelectrically actuated compliant micromanipulator dedicated to multiscale, precision and reliable operations. To begin with, the manipulator is devised to obtain multi degrees of freedom and large workspace ranges. Two-stage amplification mechanisms (consists of the leverage and the rocker mechanisms) and composite parallelogram mechanisms are combined to construct the lower microstage. Meanwhile, the structure design of the upper dual-driven microgripper is based on the bridge-type mechanism and the unilateral parallelogram mechanism. Through finite-element analysis, the structural parameters of the micromanipulator are optimized and the structural interaction performances are examined. Moreover, a cooperative control strategy is proposed to achieve the synchronous control of the motion trajectory, the gripper position and the contact force. Precision motion control in terms of the hysteresis phenomenon and system disturbances is ensured by using an adaptive sliding mode control (SMC). In particular, an improved nonsymmetrical Bouc-Wen model and a fuzzy regulator are proposed in the SMC. Several experimental investigations are conducted to validate the effectiveness of the developed micromanipulator by performing transferring operations of a micro-object. Experimental results demonstrate that the micromanipulator presents good characteristics, and precision and robust operation can be acquired using the cooperative controller.

Chaotic Behaviuor of the Navier-Stokes Solutions, Gyroscopes and Storm Surging

NASA Astrophysics Data System (ADS)

Tchiguirinskaia, Ioulia; Schertzer, Daniel

2015-04-01

Storm surges are phenomena inflicting wide damages all over the planet. Unfortunately they are badly represented in classical forecast model schemes because their multiscale nature is at odd with the scale truncation of these models. For similar reasons, classical data analysis often compelled to considered them as 'outliers' of the normal atmospheric activity, whereas as in fact they result from the same physical mechanisms that create less extreme behavior. A better representation of storm surges requires a multicale understanding of how a cascade of seemingly harmless instabilities can generate major ones. This correspond to the conjectured, outstanding intermittency.of the chaotic behaviour of the Navier-Stokes solutions. However, our limited, mathematical understanding of the Navier-Stokes equations prevent us to directly use them to investigate this question. We therefore use the most relevant cascade model to theoretically tackle this question of intermittency, i.e. the Scaling Gyroscopes Cascade (SGC). Indeed, this model is obtained with the help of a non trivial tree-decomposition of the Lie structure of the Navier-Stokes equations. the SGC model is deduced from these equations by preserving only a certain type of direct interactions, while the resulting indirect interactions are built dynamically along the tree-structure of the cascade. Because its fundamental element corresponds to a 'top' -i.e., an object with which almost anyone began to discover the puzzling nonlinear properties of rotation!- the SGC model remains rather simple, yet not simplistic! In particular, the SGC model enables us to investigate in details the occurrence of the critical singularity of a first order multifractal phase transition, which theoretically define storm surges. Overall, these theoretical findings could significantly reduce numerous uncertainties of environmental risk assessments.