Multiscale Modeling Methods Research Articles

Multi-Scale Models of Genomic Bacterial DNA

Detailed structural models of genomic bacterial DNA were developed using multi-scale modeling methods. Initial models were generated using a coarse-grained representation of supercoiled plectonemic DNA informed by experimental data. Conformational sampling was carried out using a Monte Carlo procedure to generate ensembles of nucleoid structures for complete genomic DNA within the constraints of known nucleoid sizes. The resulting models suggest that nucleoids are porous structures that may allow the diffusion of most proteins and protein complexes, in particular those involved in transcription and replication. The coarse-grained models were further refined with increasingly detailed representations of helical DNA up to quasi-atomistic models to serve as starting structures for realistic models of cellular environments.

멀티스케일 모델링 기법을 이용한 섬유강화 복합재료의 미시역학적 파손예측 및 검증

In this paper, a micro-mechanical failure prediction program is developed based on SIFT (Strain Invariant Failure Theory) by using the multi-scale modeling method for fiber-reinforced composite materials. And the failure analysis are performed for open-hole composite laminate specimen in order to verify the developed program. First of all, the critical strain invariants are obtained through the tensile tests for three types of specimens. Also, the matrices of strain amplification factors are determined through the finite element analysis for micro-mechanical model, RVE (Representative Volume Element). Finally, the microscopic failure analysis is performed for the open-hole composite laminate specimen model by applying a failure load obtained from tensile test, and the predicted failure indices are evaluated for verification of the developed program.

A new multiscale modeling method for simulating the loss processes in polymer solar cell nanodevices

The photoelectric power conversion efficiency of polymer solar cells is till now, compared to conventional inorganic solar cells, still relatively low with maximum values ranging from 7% to 8%. This essentially relates to the existence of exciton and charge carrier loss phenomena, reducing the performance of polymer solar cells significantly. In this paper we introduce a new computer simulation technique, which permits to explore the causes of the occurrence of such phenomena at the nanoscale and to design new photovoltaic materials with optimized opto-electronic properties. Our approach consists in coupling a mesoscopic field-theoretic method with a suitable dynamic Monte Carlo algorithm, to model the elementary photovoltaic processes. Using this algorithm, we investigate the influence of structural characteristics and different device conditions on the exciton generation and charge transport efficiencies in case of a novel nanostructured polymer blend. More specifically, we find that the disjunction of continuous percolation paths leads to the creation of dead ends, resulting in charge carrier losses through charge recombination. Moreover, we observe that defects are characterized by a low exciton dissociation efficiency due to a high charge accumulation, counteracting the charge generation process. From these observations, we conclude that both the charge carrier loss and the exciton loss phenomena lead to a dramatic decrease in the internal quantum efficiency. Finally, by analyzing the photovoltaic behavior of the nanostructures under different circuit conditions, we demonstrate that charge injection significantly determines the impact of the defects on the solar cell performance.

Analysis and assessment of bridge health monitoring mass data—progress in research/development of “Structural Health Monitoring”

The “Structural Health Monitoring” is a project supported by National Natural Science Foundation for Distinguished Young Scholars of China (Grant No. 50725828). To meet the urgent requirements of analysis and assessment of mass monitoring data of bridge environmental actions and structural responses, the monitoring of environmental actions and action effect modeling methods, dynamic performance monitoring and early warning methods, condition assessment and operation maintenance methods of key members are systematically studied in close combination with structural characteristics of long-span cablestayed bridges and suspension bridges. The paper reports the progress of the project as follows. (1) The environmental action modeling methods of long-span bridges are established based on monitoring data of temperature, sustained wind and typhoon. The action effect modeling methods are further developed in combination with the multi-scale baseline finite element modeling method for long-span bridges. (2) The identification methods of global dynamic characteristics and internal forces of cables and hangers for long-span cable-stayed bridges and suspension bridges are proposed using the vibration monitoring data, on the basis of which the condition monitoring and early warning methods of bridges are developed using the environmental-condition-normalization technique. (3) The analysis methods for fatigue loading effect of welded details of steel box girder, temperature and traffic loading effect of expansion joint are presented based on long-term monitoring data of strain and beam-end displacement, on the basis of which the service performance assessment and remaining life prediction methods are developed.

A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.

A multi-scale modeling method for thermal-degraded image

This paper proposes a multi-scale modeling method for thermal-degraded image. The method adopts the least-squares fitting method to model the thermal degradation characteristics of simulation degraded images at multi-scale, and then uses the obtained modeling results to correct the degraded images in real aerodynamic thermal environment. The experimental results show that this method is effective in thermal-degraded image correction, and improves the image quality.

Method for Multi-Scale Modeling and Simulation of Assembly Systems

This paper presents the on-going research steps aiming at the development of a Method for Multi-scale Modeling and Simulation of Assembly System. The focus lies on the Assembly System Base Model and its integration into the whole method. After motivating the research, the developed method and the conceived model of the assembly system is introduced, by using the proposed methodology. The presented approach aims at the manageability of the systems complexity and the acceleration of optimization and adaption processes. It concludes with a roadmap shaping the next steps and activities.

Tunnel structure analysis using the multi-scale modeling method

Structure analysis of the long tunnel is difficult due to the lack of available computing power. Water hammer simulation in the water conveyance tunnel is also complicated because of strong fluid structure interactions (FSIs). In this paper, the multi-scale modeling method is used to simulate water hammer impacts in the long tunnel. The method can not only yield water hammer simulations along the full tunnel length, but also the detailed structural responses of the segment linings. In the proposed partitioned approach, the structural field is solved with the finite-element program LS-DYNA. The fluid field is solved with the CFD software package FLUENT. The interaction between two physical fields is realized using ALE description. A practical case study is presented and the results are discussed in detail. The results provide us with a better understanding of water hammers and their effects on tunnel linings.

Multi-scale analysis of high-speed dynamic friction

Friction occurring at the interface between dissimilar metallic components as a result of high velocity impact or explosive loading can have a profound effect on the subsequent motion. A comprehensive understanding of the involved processes across a wide range of initial conditions remains outstanding. Dry sliding of single crystal silver on copper at high pressure is investigated for a range of sliding speeds using a multi-scale modelling method based upon the domain decomposition approach (molecular dynamics in the near interface region and continuum mechanics elsewhere). The transient solutions reveal detailed observations of the processes that lead to phenomena such as the growth of epitaxial layers of the softer material, shifting of the sliding interface due to formation of shear-bands, development of amorphous structures, and ultimately the resultant motion of the components. Analysis of the results also links these processes to the changes in the state of the material through growth of dislocations and thermal effects.

A Multiscale Dynamic Model of DNA Supercoil Relaxation by Topoisomerase IB

In this study, we report what we believe to be the first multiscale simulation of the dynamic relaxation of DNA supercoils by human topoisomerase IB (topo IB). We leverage our previous molecular dynamics calculations of the free energy landscape describing the interaction between a short DNA fragment and topo IB. Herein, this landscape is used to prescribe boundary conditions for a computational, elastodynamic continuum rod model of a long length of supercoiled DNA. The rod model, which accounts for the nonlinear bending, twisting, and electrostatic interaction of the (negatively charged) DNA backbone, is extended to include the hydrodynamic drag induced by the surrounding physiological buffer. Simulations for a 200-bp-long DNA supercoil in complex with topo IB reveal a relaxation timescale of ∼0.1–1.0 μs. The relaxation follows a sequence of cascading reductions in the supercoil linking number ( Lk), twist ( Tw), and writhe ( Wr) that follow companion cascading reductions in the supercoil elastic and electrostatic energies. The novel (to our knowledge) multiscale modeling method may enable simulations of the entire experimental setup that measures DNA supercoiling and relaxation via single molecule magnetic trapping.

Force field parameter estimation of functional perfluoropolyether lubricants

The head disk interface in a hard disk drive can be considered to be one of the hierarchical multiscale systems, which require the hybridization of multiscale modeling methods with coarse-graining procedure. However, the fundamental force field parameters are required to enable the coarse-graining procedure from atomistic/molecular scale to mesoscale models. In this paper, we investigate beyond molecular level and perform ab initio calculations to obtain the force field parameters. Intramolecular force field parameters for Zdol and Ztetraol were evaluated with truncated PFPE molecules to allow for feasible quantum calculations while still maintaining the characteristic chemical structure of the end groups. Using the harmonic approximation to the bond and angle potentials, the parameters were derived from the Hessian matrix, and the dihedral force constants are fit to the torsional energy profiles generated by a series of constrained molecular geometry optimization.

3H0924 マルチスケールアンサンブルモデリングのp53全体構造への適用(3H 蛋白質_物性4,日本生物物理学会第49回年会)

3H0924 マルチスケールアンサンブルモデリングのp53全体構造への適用(3H 蛋白質_物性4,日本生物物理学会第49回年会)

Top down and bottom up engineering of bone

The goal of this retrospective article is to place the body of my lab′s multiscale mechanobiology work in context of top-down and bottom-up engineering of bone. We have used biosystems engineering, computational modeling and novel experimental approaches to understand bone physiology, in health and disease, and across time ( in utero, postnatal growth, maturity, aging and death, as well as evolution) and length scales (a single bone like a femur, m; a sample of bone tissue, mm–cm; a cell and its local environment, μm; down to the length scale of the cell's own skeleton, the cytoskeleton, nm). First we introduce the concept of flow in bone and the three calibers of porosity through which fluid flows. Then we describe, in the context of organ–tissue, tissue–cell and cell–molecule length scales, both multiscale computational models and experimental methods to predict flow in bone and to understand the flow of fluid as a means to deliver chemical and mechanical cues in bone. Addressing a number of studies in the context of multiple length and time scales, the importance of appropriate boundary conditions, site specific material parameters, permeability measures and even micro-nanoanatomically correct geometries are discussed in context of model predictions and their value for understanding multiscale mechanobiology of bone. Insights from these multiscale computational modeling and experimental methods are providing us with a means to predict, engineer and manufacture bone tissue in the laboratory and in the human body.

Demonstration of a multiscale modeling technique: prediction of the stress–strain responseof light activated shape memory polymers

Presented is a multiscale modeling method applied to light activated shape memorypolymers (LASMPs). LASMPs are a new class of shape memory polymer (SMPs) beingdeveloped for adaptive structures applications where a thermal stimulus is undesirable.LASMP developmental emphasis is placed on optical manipulation of Young’s modulus. Amultiscale modeling approach is employed to anticipate the soft and hard statemoduli solely on the basis of a proposed molecular formulation. Employing such amodel shows promise for expediting down-selection of favorable formulations forsynthesis and testing, and subsequently accelerating LASMP development. Anempirical adaptation of the model is also presented which has applications insystem design once a formulation has been identified. The approach employsrotational isomeric state theory to build a molecular scale model of the polymerchain yielding a list of distances between the predicted crosslink locations, orr-values.The r-values are then fitted with Johnson probability density functions and used withBoltzmann statistical mechanics to predict stress as a function of the strain of thephantom polymer network. Empirical adaptation for design adds junction constrainttheory to the modeling process. Junction constraint theory includes the effects ofneighboring chain interactions. Empirical fitting results in numerically accurateYoung’s modulus predictions. The system is modular in nature and thus lends itselfwell to being adapted to other polymer systems and development applications.

Three dimensional multi-scale modelling and analysis of cell damage in cell-encapsulated alginate constructs

One of the major challenges in scaffold guided regenerative therapies is identifying the essential cues such as mechanical forces that induce cellular responses to form functional tissue. Developing multi-scale modelling methods would facilitate in predicting responses of encapsulated cells for controlling and maintaining the cell phenotype in an engineered tissue construct, when mechanical loads are applied. The objective of this study is to develop a 3D multi-scale numerical model for analyzing the stresses and deformations of the cell when the tissue construct is subjected to macro-scale mechanical loads and to predict load-induced cell damage. Specifically, this methodology characterizes the macro-scale structural behavior of the scaffold, and quantifies 3D stresses and deformations of the cells at the micro-scale and at a cellular level, wherein individual cell components are incorporated. Assuming that cells have inherent ability to sustain a critical load without damage, a damage criterion is established and a stochastic simulation is employed to predict the percentage cell viability within the tissue constructs. Bio-printed cell-alginate tissue constructs were tested with 1%, 5% and 10% compression strain applied and the cell viability were characterized experimentally as 23.2±16.8%, 9.0±5.4% and 4.6±2.1%. Using the developed method, the corresponding micro-environments of the cells were analyzed, the mean critical compressive strain was determined as 0.5%, and the cell viability was predicted as 26.6±7.0, 13.3±4.5, and 10.1±2.8. The predicted results capture the trend of the damage observed from the experimental study.

MOLECULAR AND MULTISCALE MODELING: REVIEW ON THE THEORIES AND APPLICATIONS IN CHEMICAL ENGINEERING

We call molecular modeling to the application of suitable laws in the analysis of phenomena occurred at scales less than those accounted for by the macroscopic world. Such different scales (including micro-, meso- and macroscales), can be linked and integrated in order to improve understanding and predictions of complex physical chemistry phenomena, thus originating a global or multiscale analysis. A considerable amount of chemical engineering phenomena are complex due to the interrelation among these different realms of length and time. Multiscale modeling rises as an alternative for an outstanding mathematical and conceptual representation of such phenomena. This adequate representation may help to design and optimize chemical and petrochemical processes from a microscopic point of view. Herein we present a brief introduction to both molecular and multiscale modeling methods. We also comment and examine opportunities for applying the different levels of modeling to the analysis of industrial problems. The fundamental mathematical machinery of the molecular modelling theories is presented in order to motivate the study of these new engineering tools. Finally, we show a classification of different strategies for applying multilevel analysis, illustrating various examples of each methodology.

A Concurrent Multiscale Method for Coupling Atomistic and Continuum Models at Finite Temperatures

AbstractA concurrent multi-scale modeling method for finite temperature simulation of solids is introduced. The objective is to represent far from equilibrium phenomena using an atomistic model and near equilibrium phenomena using a continuum model, the domain being partitioned in discrete and continuum regions, respectively. An interface sub-domain is defined between the two regions to provide proper coupling between the discrete and continuum models. While in the discrete region the thermal and mechanical processes are intrinsically coupled, in the continuum region they are treated separately. The interface region partitions the energy transferred from the discrete to the continuum into mechanical and thermal components by splitting the phonon spectrum into “low” and “high” frequency ranges. This is achieved by using the generalized Langevin equation as the equation of motion for atoms in the interface region. The threshold frequency is selected such to minimize energy transfer between the mechanical and thermal components. Mechanical coupling is performed by requiring the continuum degrees of freedom (nodes) to follow the averaged motion of the atoms. Thermal coupling is ensured by imposing a flux input to the atomistic region and using a temperature boundary condition for continuum. This makes possible a thermodynamically consistent, bi-directional coupling of the two models.

Prediction of protein loop conformations using multiscale modeling methods with physical energy scoring functions

This article examines ab initio methods for the prediction of protein loops by a computational strategy of multiscale conformational sampling and physical energy scoring functions. Our approach consists of initial sampling of loop conformations from lattice-based low-resolution models followed by refinement using all-atom simulations. To allow enhanced conformational sampling, the replica exchange method was implemented. Physical energy functions based on CHARMM19 and CHARMM22 parameterizations with generalized Born (GB) solvent models were applied in scoring loop conformations extracted from the lattice simulations and, in the case of all-atom simulations, the ensemble of conformations were generated and scored with these models. Predictions are reported for 25 loop segments, each eight residues long and taken from a diverse set of 22 protein structures. We find that the simulations generally sampled conformations with low global root-mean-square-deviation (RMSD) for loop backbone coordinates from the known structures, whereas clustering conformations in RMSD space and scoring detected less favorable loop structures. Specifically, the lattice simulations sampled basins that exhibited an average global RMSD of 2.21 +/- 1.42 A, whereas clustering and scoring the loop conformations determined an RMSD of 3.72 +/- 1.91 A. Using CHARMM19/GB to refine the lattice conformations improved the sampling RMSD to 1.57 +/- 0.98 A and detection to 2.58 +/- 1.48 A. We found that further improvement could be gained from extending the upper temperature in the all-atom refinement from 400 to 800 K, where the results typically yield a reduction of approximately 1 A or greater in the RMSD of the detected loop. Overall, CHARMM19 with a simple pairwise GB solvent model is more efficient at sampling low-RMSD loop basins than CHARMM22 with a higher-resolution modified analytical GB model; however, the latter simulation method provides a more accurate description of the all-atom energy surface, yet demands a much greater computational cost.

Multi-scale modelling and canonical dual finite element method in phase transitions of solids

This paper presents a multi-scale model in phase transitions of solid materials with both macro and micro effects. This model is governed by a semi-linear nonconvex partial differential equation which can be converted into a coupled quadratic mixed variational problem by the canonical dual transformation method. The extremality conditions of this variational problem are controlled by a triality theory, which reveals the multi-scale effects in phase transitions. Therefore, a potentially useful canonical dual finite element method is proposed for the first time to solve the nonconvex variational problems in multi-scale phase transitions of solids. Applications are illustrated. Results shown that the canonical duality theory developed by the first author in nonconvex mechanics can be used to model complicated physical phenomena and to solve certain difficult nonconvex variational problems in an easy way. The canonical dual finite element method brings some new insights into computational mechanics.

An integrative approach to understanding mechanosensation

The ability for a living organism to sense and respond to its external environment is crucial to its survival. Understanding mechanosensation, the mechanism by which organisms react in response to mechanical stimuli, presents many interesting and challenging problems for both experimental and computational biologists. A major difficulty in studying mechanosensors is their inherent multiscale nature. The systems involved in mechanosesnsing can span eight orders of magnitude in length scale and up to 10 orders of magnitude in time scale. Trying to ascertain information across these length and time scales simultaneously is challenging. This problem has led to the need to approach these types of problems using an integrative approach, combining both computational and experimental biology. This review classifies the major types of mechanosensors and explains methods that have been employed in understanding their behavior, both using modeling and experimental techniques. Multiscale modeling methods combined with experimental techniques in an integrative approach are suggested as ways of undertaking the study of such systems.