Design search and optimization in aerospace engineering

In this paper, we take a design-led perspective on the use of computational tools in the aerospace sector. We briefly review the current state-of-the-art in design search and optimization (DSO) as applied to problems from aerospace engineering, focusing on those problems that make heavy use of computational fluid dynamics (CFD). This ranges over issues of representation, optimization problem formulation and computational modelling. We then follow this with a multi-objective, multi-disciplinary example of DSO applied to civil aircraft wing design, an area where this kind of approach is becoming essential for companies to maintain their competitive edge. Our example considers the structure and weight of a transonic civil transport wing, its aerodynamic performance at cruise speed and its manufacturing costs. The goals are low drag and cost while holding weight and structural performance at acceptable levels. The constraints and performance metrics are modelled by a linked series of analysis codes, the most expensive of which is a CFD analysis of the aerodynamics using an Euler code with coupled boundary layer model. Structural strength and weight are assessed using semi-empirical schemes based on typical airframe company practice. Costing is carried out using a newly developed generative approach based on a hierarchical decomposition of the key structural elements of a typical machined and bolted wing-box assembly. To carry out the DSO process in the face of multiple competing goals, a recently developed multi-objective probability of improvement formulation is invoked along with stochastic process response surface models (Krigs). This approach both mitigates the significant run times involved in CFD computation and also provides an elegant way of balancing competing goals while still allowing the deployment of the whole range of single objective optimizers commonly available to design teams.     

Carbon Nanotubes and Nanofluidic Transport

Recent strides have been made in both the modeling and measurement of fluid flow on the nanoscale. Carbon nanotubes, with their atomic dimensions and atomic smoothness, are ideal materials for studying such flows. This Progress Report describes recent modeling and experimental advances concerning fluid transport in carbon nanotubes. The varied flow characteristics predicted by molecular dynamics are described, as are the roles of defects and chirality on transport. Analytical models are increasingly being used to describe nanofluidic transport by relaxing many of the assumptions commonly used to describe bulk water. Recent experimental studies examine the size dependence of flow enhancements through carbon nanotubes and use varied spectroscopies to probe water structure and dynamics in these systems. Carbon nanotubes are finding increasing applications in biology, from protein filters to platforms for cell interrogation.     

Formal Approach to Workflow Application Fragmentations Over Cloud Deployment Models

Workflow management technologies have been dramatically improving their deployment architectures and systems along with the evolution and proliferation of cloud distributed computing environments. Especially, such cloud computing environments ought to be providing a suitable distributed computing paradigm to deploy very large-scale workflow processes and applications with scalable on-demand services. In this paper, we focus on the distribution paradigm and its deployment formalism for such very large-scale workflow applications being deployed and enacted across the multiple and heterogeneous cloud computing environments. We propose a formal approach to vertically as well as horizontally fragment very large-scale workflow processes and their applications and to deploy the workflow process and application fragments over three types of cloud deployment models and architectures. To concretize the formal approach, we firstly devise a series of operational situations fragmenting into cloud workflow process and application components and deploying onto three different types of cloud deployment models and architectures. These concrete approaches are called the deployment-driven fragmentation mechanism to be applied to such very large-scale workflow process and applications as an implementing component for cloud workflow management systems. Finally, we strongly believe that our approach with the fragmentation formalisms becomes a theoretical basis of designing and implementing very large-scale and maximally distributed workflow processes and applications to be deployed on cloud deployment models and architectural computing environments as well.     

A rheological interface model and its space–time finite element formulation for fluid–structure interaction

This contribution discusses extended physical interface models for fluid–structure interaction problems and investigates their phenomenological effects on the behavior of coupled systems by numerical simulation. Besides the various types of friction at the fluid–structure interface the most interesting phenomena are related to effects due to additional interface stiffness and damping. The paper introduces extended models at the fluid–structure interface on the basis of rheological devices (Hooke, Newton, Kelvin, Maxwell, Zener). The interface is decomposed into a Lagrangian layer for the solid‐like part and an Eulerian layer for the fluid‐like part. The mechanical model for fluid–structure interaction is based on the equations of rigid body dynamics for the structural part and the incompressible Navier–Stokes equations for viscous flow. The resulting weighted residual form uses the interface velocity and interface tractions in both layers in addition to the field variables for fluid and structure. The weak formulation of the whole coupled system is discretized using space–time finite elements with a discontinuous Galerkin method for time‐integration leading to a monolithic algebraic system. The deforming fluid domain is taken into account by deformable space–time finite elements and a pseudo‐structure approach for mesh motion. The sensitivity of coupled systems to modification of the interface model and its parameters is investigated by numerical simulation of flow induced vibrations of a spring supported fluid‐immersed cylinder. It is shown that the presented rheological interface model allows to influence flow‐induced vibrations. Copyright © 2010 John Wiley & Sons, Ltd.     

低轨道系绳卫星展开过程仿真分析

就空间系绳卫星系统ＴＳＳ展开过程特别是系绳子卫星初始展开阶段,对动力学特性及张力控制规律进行了研究,在此基础上进行了多参数仿真,由于采用了尽可能真实的参数及可靠的初始条件,仿真结果具有较高的可信度,为进一步研究和开发ＴＳＳ提供了依据。     

A coupled molecular dynamics and extended finite element method for dynamic crack propagation

A multiscale method is presented which couples a molecular dynamics approach for describing fracture at the crack tip with an extended finite element method for discretizing the remainder of the domain. After recalling the basic equations of molecular dynamics and continuum mechanics, the discretization is discussed for the continuum subdomain where the partition‐of‐unity property of finite element shape functions is used, since in this fashion the crack in the wake of its tip is naturally modelled as a traction‐free discontinuity. Next, the zonal coupling method between the atomistic and continuum models is recapitulated. Finally, it is discussed how the stress has been computed in the atomic subdomain, and a two‐dimensional computation is presented of dynamic fracture using the coupled model. The result shows multiple branching, which is reminiscent of recent results from simulations on dynamic fracture using cohesive‐zone models. Copyright © 2009 John Wiley & Sons, Ltd.     

Modeling transient absorption and thermal conductivity in a simple nanofluid

Molecular dynamics simulations are used to simulate the thermal properties of a model fluid containing nanoparticles (nanofluid). By modeling transient absorption experiments, we show that they provide a reliable determination of interfacial resistance between the particle and the fluid. The flexibility of molecular simulation allows us to consider separately the effect of confinement, particle mass, and Brownian motion on the thermal transfer between fluid and particle. Finally, we show that in the absence of collective effects, the heat conductivity of the nanofluid is well described by the classical Maxwell Garnet equation model.     

Multiscale sequentially-coupled arterial FSI technique

Multiscale versions of the Sequentially-Coupled Arterial Fluid–Structure Interaction (SCAFSI) technique are presented. The SCAFSI technique was introduced as an approximate FSI approach in arterial fluid mechanics. It is based on the assumption that the arterial deformation during a cardiac cycle is driven mostly by the blood pressure. First we compute a “reference” arterial deformation as a function of time, driven only by the blood pressure profile of the cardiac cycle. Then we compute a sequence of updates involving mesh motion, fluid dynamics calculations, and recomputing the arterial deformation. The SCAFSI technique was developed and tested in conjunction with the stabilized space–time FSI (SSTFSI) technique. Beyond providing a computationally more economical alternative to the fully coupled arterial FSI approach, the SCAFSI technique brings additional flexibility, such as being able to carry out the computations in a spatially or temporally multiscale fashion. In the test computations reported here for the spatially multiscale versions of the SCAFSI technique, we focus on a patient-specific middle cerebral artery segment with aneurysm, where the arterial geometry is based on computed tomography images. The arterial structure is modeled with the continuum element made of hyperelastic (Fung) material.     

A simultaneous solution procedure for strong interactions of generalized Newtonian fluids and viscoelastic solids at large strains

The paper presents a methodology for numerical analyses of coupled systems exhibiting strong interactions of viscoelastic solids and generalized Newtonian fluids. In the monolithic approach, velocity variables are used for both solid and fluid, and the entire set of model equations is discretized with stabilized space–time finite elements. A viscoelastic material model for finite deformations, which is based on the concept of internal variables, describes the stress‐deformation behaviour of the solid. In the generalized Newtonian approach for the fluid, the viscosity depends on the shear strain rate, leading to common non‐Newtonian fluid models like the power‐law. The consideration of non‐linear constitutive equations for solid and fluid documents the capability of the monolithic space–time finite element formulation to deal with complex material models. The methodology is applied to fluid‐conveying cantilevered pipes in order to determine the influence of material non‐linearities on stability characteristics of coupled systems. Copyright © 2005 John Wiley & Sons, Ltd.     

A new constant-pressure ab initio/classical molecular dynamics method: simulation of pressure-induced amorphization in a Si35H36 cluster

We present here a new constant-pressure ab initio molecular dynamics method, suitable, e.g., for studying pressure-induced structural transformations in finite non-periodic systems such as clusters. In order to apply external isotropic pressure on the cluster, we immerse an ab initio treated cluster in a model classical liquid, described by a repulsive soft-sphere potential, which acts as a pressure reservoir. The extended system cluster + liquid is simulated by a coupled Car–Parrinello and classical molecular dynamics. The pressure is varied by tuning the parameter of the liquid potential. We apply the method to a Si₃₅H₃₆ cluster, which undergoes a pressure-induced amorphization at 35 GPa, and remains in a disordered state even upon pressure release. The properties of cluster at different pressures are analyzed by means of maximally localized Wannier functions method. In the high-pressure phase, a considerable reduction of the Kohn–Sham energy gap as well as an increase of electronic delocalization is observed, which represents an analogue of metallization of bulk Si upon transition from diamond to β-tin phase.     

Influence of model particle size and spatial resolution in coarse-graining DEM-CFD simulation

The discrete element method (DEM) coupled with computational fluid dynamics (CFD) is a powerful tool for exploring the detailed behaviors of dense particle–fluid interaction problems such as fluidized beds. Coarse-graining models have been proposed to decrease the computational cost by increasing the model particle size. In this study, we examine the influence of the model particle size and the spatial resolution on the average size and number of bubbles in coarse-graining DEM-CFD calculations of bubbling fluidized beds. Calculation results indicate that the bubble size is scaled by the model particle size if parameters are following similarity laws defined in a particle scale, as well as the geometric similarity of the whole system is maintained. The usage of coarse spatial resolution increases the bubble size and decreases the number of bubbles. The countervailing influence of the model particle size and the spatial resolution in a practical coarse-graining scenario results in nearly the same bubble size.     

Bipolar disorder dynamics: affective instabilities,relaxation oscillations and noise

Bipolar disorder is a chronic, recurrent mental illness characterized by extreme episodes of depressed and manic mood, interspersed with less severe but highly variable mood fluctuations. Here, we develop a novel mathematical approach for exploring the dynamics of bipolar disorder. We investigate how the dynamics of subjective experience of mood in bipolar disorder can be understood using a relaxation oscillator (RO) framework and test the model against mood time-series fluctuations from a set of individuals with bipolar disorder. We show that variable mood fluctuations in individuals diagnosed with bipolar disorder can be driven by the coupled effects of deterministic dynamics (captured by ROs) and noise. Using a statistical likelihood-based approach, we show that, in general, mood dynamics are described by two independent ROs with differing levels of endogenous variability among individuals. We suggest that this sort of nonlinear approach to bipolar disorder has neurobiological, cognitive and clinical implications for understanding this mental illness through a mechacognitive framework.     

Modelling glioma progression,mass effect and intracranial pressure in patient anatomy

Increased intracranial pressure is the source of most critical symptoms in patients with glioma, and often the main cause of death. Clinical interventions could benefit from non-invasive estimates of the pressure distribution in the patient''s parenchyma provided by computational models. However, existing glioma models do not simulate the pressure distribution and they rely on a large number of model parameters, which complicates their calibration from available patient data. Here we present a novel model for glioma growth, pressure distribution and corresponding brain deformation. The distinct feature of our approach is that the pressure is directly derived from tumour dynamics and patient-specific anatomy, providing non-invasive insights into the patient''s state. The model predictions allow estimation of critical conditions such as intracranial hypertension, brain midline shift or neurological and cognitive impairments. A diffuse-domain formalism is employed to allow for efficient numerical implementation of the model in the patient-specific brain anatomy. The model is tested on synthetic and clinical cases. To facilitate clinical deployment, a high-performance computing implementation of the model has been publicly released.     

Rates of coalescence for common epidemiological models at equilibrium

Coalescent theory provides a mathematical framework for quantitatively interpreting gene genealogies. With the increased availability of molecular sequence data, disease ecologists now regularly apply this body of theory to viral phylogenies, most commonly in attempts to reconstruct demographic histories of infected individuals and to estimate parameters such as the basic reproduction number. However, with few exceptions, the mathematical expressions at the core of coalescent theory have not been explicitly linked to the structure of epidemiological models, which are commonly used to mathematically describe the transmission dynamics of a pathogen. Here, we aim to make progress towards establishing this link by presenting a general approach for deriving a model''s rate of coalescence under the assumption that the disease dynamics are at their endemic equilibrium. We apply this approach to four common families of epidemiological models: standard susceptible-infected-susceptible/susceptible-infected-recovered/susceptible-infected-recovered-susceptible models, models with individual heterogeneity in infectivity, models with an exposed but not yet infectious class and models with variable distributions of the infectious period. These results improve our understanding of how epidemiological processes shape viral genealogies, as well as how these processes affect levels of viral diversity and rates of genetic drift. Finally, we discuss how a subset of these coalescent rate expressions can be used for phylodynamic inference in non-equilibrium settings. For the ones that are limited to equilibrium conditions, we also discuss why this is the case. These results, therefore, point towards necessary future work while providing intuition on how epidemiological characteristics of the infection process impact gene genealogies.     

The enriched space–time finite element method (EST) for simultaneous solution of fluid–structure interaction

The paper introduces a weighted residual‐based approach for the numerical investigation of the interaction of fluid flow and thin flexible structures. The presented method enables one to treat strongly coupled systems involving large structural motion and deformation of multiple‐flow‐immersed solid objects. The fluid flow is described by the incompressible Navier–Stokes equations. The current configuration of the thin structure of linear elastic material with non‐linear kinematics is mapped to the flow using the zero iso‐contour of an updated level set function. The formulation of fluid, structure and coupling conditions uniformly uses velocities as unknowns. The integration of the weak form is performed on a space–time finite element discretization of the domain. Interfacial constraints of the multi‐field problem are ensured by distributed Lagrange multipliers. The proposed formulation and discretization techniques lead to a monolithic algebraic system, well suited for strongly coupled fluid–structure systems. Embedding a thin structure into a flow results in non‐smooth fields for the fluid. Based on the concept of the extended finite element method, the space–time approximations of fluid pressure and velocity are properly enriched to capture weakly and strongly discontinuous solutions. This leads to the present enriched space–time (EST) method. Numerical examples of fluid–structure interaction show the eligibility of the developed numerical approach in order to describe the behavior of such coupled systems. The test cases demonstrate the application of the proposed technique to problems where mesh moving strategies often fail. Copyright © 2007 John Wiley & Sons, Ltd.     

Nearly exact solution for coupled continuum/MD fluid simulation

A general statistical approach is described to couple the continuum with molecular dynamics in fluid simulation. Arbitrary thermodynamic field boundary conditions can be imposed on an MD system while minimally disturbing the particle dynamics of the system. And by acting away from the region of interest through a feedback control mechanism, across a buffer zone where the disturbed dynamics are allowed to relax, we can eliminate that disturbance entirely. The field estimator, based on maximum likelihood inference, serves as the detector of the control loop, which infers smooth instantaneous fields from the particle data. The optimal particle controller, defined by an implicit relation, can be proved mathematically to give the correct distribution with least disturbance to the dynamics. A control algorithm compares the estimated current fields with the desired fields at the boundary and modifies the action of the particle controller far way, until they eventually agree. This method, combined with a continuum code in a Schwarz iterative domain-decomposition formalism, provides a mutually consistent solution for steady-state problems, as particles in the MD region of interest have no way to tell any difference from reality. Finally, we explain the importance of using a higher order single-particle distribution function, in light of the Chapman–Enskog development for shear flow. This revised version was published online in July 2006 with corrections to the Cover Date.     

Two‐fluid model with interface sharpening

Two‐fluid models are applicable for simulations of all types of two‐phase flows ranging from separated flows with large characteristic interfacial length scales to highly dispersed flows with very small characteristic interfacial length scales. The main drawback of the two‐fluid model, when used for simulations of stratified flows, is the numerical diffusion of the interface. Stratified flows can be easily and more accurately solved with interface tracking methods; however, these methods are limited to the flows, that do not develop into dispersed types of flows. The present paper describes a new approach, where the advantage of the two‐fluid model is combined with the conservative level set method for interface tracking. The advection step of the volume fraction transport equation is followed by the interface sharpening, which preserves the thickness of the interface during the simulation. The proposed two‐fluid model with interface sharpening was found to be more accurate than the existing two‐fluid models. The mixed flow with both: stratified and dispersed flow, is simulated with the coupled model in this paper. In the coupled model, the dispersed two‐fluid model and two‐fluid model with interface sharpening are used locally, depending on the parameter which recognizes the flow regime. Copyright © 2010 John Wiley & Sons, Ltd.     

迁移预测模型中扩散系数的研究

详细介绍了3种典型的半经验化的扩散系数公式,分析其使用范围和局限性.同时,对通过直接计算机模拟得到扩散系数的分子动力学方法进行介绍.与半经验的扩散系数方程相比,分子动力学方法直接地给出了小分子在聚合物中的扩散系数,而且揭示了影响扩散的分子机理.     

An iterative BEM/FVM protocol for steady-state multi-dimensional conjugate heat transfer in compressible flows

A BEM-based temperature forward/flux back (TFFB) coupling algorithm is developed to solve the conjugate heat transfer (CHT), which arises naturally in analysis of systems exposed to a convective environment. Here, heat conduction within a structure is coupled to heat transfer to the external fluid, which is convecting heat into or out of the solid structure. There are two basic approaches for solving coupled fluid-structural systems. The first is a direct coupling where the solution of the different fields is solved simultaneously in one large set of equations. The second approach is a loose coupling strategy where each set of field equations is solved to provide boundary conditions for the other. The equations are solved in turn until an iterated convergence criterion is met at the fluid–solid interface. The loose coupling strategy is particularly attractive when coupling auxiliary field equations to computational fluid dynamics codes. We adopt the latter method in which the BEM is used to solve heat conduction inside a structure which is exposed to a convective field which in turn is resolved by solving the Navier–Stokes equations by finite volume methods. Interface of flux and temperature is enforced at the solid/fluid interface.