Chaste: using agile programming techniques to develop computational biology software

Cardiac modelling is the area of physiome modelling where the available simulation software is perhaps most mature, and it therefore provides an excellent starting point for considering the software requirements for the wider physiome community. In this paper, we will begin by introducing some of the most advanced existing software packages for simulating cardiac electrical activity. We consider the software development methods used in producing codes of this type, and discuss their use of numerical algorithms, relative computational efficiency, usability, robustness and extensibility. We then go on to describe a class of software development methodologies known as test-driven agile methods and argue that such methods are more suitable for scientific software development than the traditional academic approaches. A case study is a project of our own, Cancer, Heart and Soft Tissue Environment, which is a library of computational biology software that began as an experiment in the use of agile programming methods. We present our experiences with a review of our progress thus far, focusing on the advantages and disadvantages of this new approach compared with the development methods used in some existing packages. We conclude by considering whether the likely wider needs of the cardiac modelling community are currently being met and suggest that, in order to respond effectively to changing requirements, it is essential that these codes should be more malleable. Such codes will allow for reliable extensions to include both detailed mathematical models--of the heart and other organs--and more efficient numerical techniques that are currently being developed by many research groups worldwide.     

Gas dynamics modelling for particle accelerators

Design of an accelerator vacuum chamber requires an input from different scientific disciplines such as surface science, material science, gas dynamics, particle beam dynamics, and many others. Although vacuum scientists work on the boundary field between these disciplines, gas dynamics is the one that allows joining them to the vacuum science for particle accelerators. The vacuum requirements (usually UHV or XHV) in particle accelerators are defined by beam-gas interactions that should be negligible compared to other phenomena that limit the quality of the beam. At such low pressures the main source of gas in the vacuum chamber is a molecular desorption from materials used for the vacuum chamber and its components. The outgassing rates vary over a very wide range and depend on material, cleaning procedure, treatments, temperature, bombardment by particles and accumulated irradiation dose. The gas dynamics is used to design the research facilities to accurately measure and to study outgassing rates at different conditions. By applying these data to the accelerator vacuum design, one would have to consider that outgassing is often non-uniform and changes with time with different functions. The most time-efficient way of beam vacuum optimization is using a 1D diffusion model where all parameters are defined as a function of longitudinal coordinate (along the beam path). A full 3D modelling with TPMC codes provides much more accurate results, however, being time consuming work is not ideal for pumping and design optimization and is used for complex components and for finalized design.     

Status and future directions for turbulence modelling

Progress in the development of a hierarchy of turbulence models for Reynolds-averaged Navier-Stokes codes used in aerodynamic applications is discussed. Although steady progress is demonstrated, transfer of the modelling technology has not kept pace with the development and demands of the CFD tools. An examination of the process of model development leads to recommendations for a better process involving close coordination between modellers, CFD developers and application engineers. In instances where the process is changed and cooperation enhanced, timely transfer is realized. A turbulence modelling information database is proposed to refine the process and open it to greater participation among modelling and CFD practitioners. The citations in this paper are not in our usual format     

Coupling atomistics and continuum in solids: status, prospects, and challenges

The recent focus of the scientific community on multiscale computer modeling techniques of nano-engineered materials stems from the desire to develop more realistic methodologies that are capable of accurately describing the varied time and length scales associated with this class of materials. Of importance is the ability to model the atomistic region using the appropriate techniques such as quantum mechanics/molecular dynamics, and the continuum region using homogenized properties. The continuity of atomistic and continuum regions in a solid necessitates a seamless coupling between these two regions. This is carried out using a transition region. In view of the large discrepancy between length and time scales in atomistic and continuum regions, the development of the transition region has been the main concern of the research community. It is the purpose of this review to critically discuss the issues concerning the transition region and the efforts made by the scientific community in treating them. In particular, this review addresses issues concerning the coupling of molecular dynamics to finite element modeling techniques. Three aspects of this review are accordingly considered. The first is concerned with the current state of atomistic–continuum coupling techniques in computational mechanics. The second is concerned with present the research conducted in the Engineering Mechanics and Design Laboratory at the University of Toronto in the field of nano-reinforced interfaces. Finally, we present the limitations of the current techniques and suggestions for improvements.     

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.     

Biocharts: a visual formalism for complex biological systems

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis.     

Electron tomography: An imaging method for materials deformation dynamics

The combination of in-situ and three-dimensional (3D) in transmission electron microscopy (TEM) is one of the emerging topics of recent advanced electron microscopy research. However, to date, there have been only handful examples of in-situ 3D TEM for material deformation dynamics. In this article, firstly, the authors briefly review technical developments in fast tilt-series dataset acquisition, which is a crucial technique for in-situ electron tomography (ET). Secondly, the authors showcase a recent successful example of in-situ specimen-straining and ET system development and its applications to the deformation dynamics of crystalline materials. The system is designed and developed to explore, in real-time and at sub-microscopic levels, the internal behavior of polycrystalline materials subjected to external stresses, and not specifically targeted for atomic resolution (although it may be possible). Technical challenges toward the in-situ ET observation of 3D dislocation dynamics are discussed for commercial structural crystalline materials, including some of the early studies on in-situ ET imaging and 3D modeling of dislocation dynamics. A short summary of standing technical issues and a proposed guideline for further development in the 3D imaging method for dislocation dynamics are then discussed.     

Towards a lessons learned system for critical software

Failure can be a major driver for the advance of any engineering discipline and Software Engineering is no exception. But failures are useful only if lessons are learned from them. In this article we aim to make a strong defence of, and set the requirements for, lessons learned systems for safety-critical software. We also present a prototype lessons learned system that includes many of the features discussed here. We emphasize that, apart from individual organizations, lessons learned systems should target industrial sectors and even the Software Engineering community. We would like to encourage the Software Engineering community to use this kind of systems as another tool in the toolbox, which complements or enhances other approaches like, for example, standards and checklists.     

Walking dynamics are symmetric (enough)

Many biological phenomena such as locomotion, circadian cycles and breathing are rhythmic in nature and can be modelled as rhythmic dynamical systems. Dynamical systems modelling often involves neglecting certain characteristics of a physical system as a modelling convenience. For example, human locomotion is frequently treated as symmetric about the sagittal plane. In this work, we test this assumption by examining human walking dynamics around the steady state (limit-cycle). Here, we adapt statistical cross-validation in order to examine whether there are statistically significant asymmetries and, even if so, test the consequences of assuming bilateral symmetry anyway. Indeed, we identify significant asymmetries in the dynamics of human walking, but nevertheless show that ignoring these asymmetries results in a more consistent and predictive model. In general, neglecting evident characteristics of a system can be more than a modelling convenience—it can produce a better model.     

Predictability in a highly stochastic system: final size of measles epidemics in small populations

A standard assumption in the modelling of epidemic dynamics is that the population of interest is well mixed, and that no clusters of metapopulations exist. The well-known and oft-used SIR model, arguably the most important compartmental model in theoretical epidemiology, assumes that the disease being modelled is strongly immunizing, directly transmitted and has a well-defined period of infection, in addition to these population mixing assumptions. Childhood infections, such as measles, are prime examples of diseases that fit the SIR-like mechanism. These infections have been well studied for many systems with large, well-mixed populations with endemic infection. Here, we consider a setting where populations are small and isolated. The dynamics of infection are driven by stochastic extinction–recolonization events, producing large, sudden and short-lived epidemics before rapidly dying out from a lack of susceptible hosts. Using a TSIR model, we fit prevaccination measles incidence and demographic data in Bornholm, the Faroe Islands and four districts of Iceland, between 1901 and 1965. The datasets for each of these countries suffer from different levels of data heterogeneity and sparsity. We explore the potential for prediction of this model: given historical incidence data and up-to-date demographic information, and knowing that a new epidemic has just begun, can we predict how large it will be? We show that, despite a lack of significant seasonality in the incidence of measles cases, and potentially severe heterogeneity at the population level, we are able to estimate the size of upcoming epidemics, conditioned on the first time step, to within reasonable confidence. Our results have potential implications for possible control measures for the early stages of new epidemics in small populations.     

Benchmark tests for verifying discrete element modelling codes at particle impact level

Over the past 30 years, the Discrete Element Method (DEM) has rapidly gained popularity as a tool for modelling the behaviour of granular assemblies and is being used extensively in both scientific and industrial applications. However, it is far from clear from reviewing the literature whether the large number of DEM codes have been verified and checked against fundamental benchmark problems. DEM simulates the dynamics of each particle in an assembly by calculating the acceleration resulting from all the contact forces and body forces. It is clearly necessary that such a model be validated or verified by comparing with experimental results, analytical solutions or other numerical results (e.g. Finite Element Analysis (FEA) results) at particle impact level. There appears to be no standard benchmark tests against which DEM codes can be verified. It is thus essential and useful to establish a set of standard benchmark tests to confirm that these DEM codes are modelling the particle dynamics as intended. This paper proposes a set of benchmark tests to verify DEM codes at particle impact level for spherical particles. The analytical solutions derived from elasticity theory for elastic normal collision of two spheres or a sphere with a rigid plane are first reviewed. These analytical solutions apply only to the elastic regime for normal impact. Secondly, the analytical solutions of frictional oblique impact between two spheres or a sphere with a rigid plane are scrutinized and derived. These analytical solutions originate from the dynamics principles and should be satisfied for any DEM contact force model with prescribed friction and restitution coefficients. A set of eight benchmark tests are designed and performed using commercial DEM codes. Test 1 and Test 2 consider the elastic normal impact of two spheres or a sphere with a rigid plane, whereas the other tests (Test 3–Test 8) investigate the energy dissipation due to the collision. These benchmark tests also involve different types of material. The DEM results were compared with the analytical solutions, experimental or FEA results found in the literature. All benchmark tests showed good to excellent match, providing a quantitative verification for the codes used in this study. These benchmark tests not only verify DEM codes but also enhance the understanding of fundamental impact phenomena for modelling a large number of particles.     

Chemomechanics of complex materials: challenges and opportunities in predictive kinetic timescales

What do nanoscopic biomolecular complexes between the cells that line our blood vessels have in common with the microscopic silicate glass fiber optics that line our communication highways, or with the macroscopic steel rails that line our bridges? To be sure, these are diverse materials which have been developed and studied for years by distinct experimental and computational research communities. However, the macroscopic functional properties of each of these structurally complex materials pivots on a strong yet poorly understood interplay between applied mechanical states and local chemical reaction kinetics. As is the case for many multiscale material phenomena, this chemomechanical coupling can be abstracted through computational modeling and simulation to identify key unit processes of mechanically altered chemical reactions. In the modeling community, challenges in predicting the kinetics of such structurally complex materials are often attributed to the so-called rough energy landscape, though rigorous connection between this simple picture and observable properties is possible for only the simplest of structures and transition states. By recognizing the common effects of mechanical force on rare atomistic events ranging from molecular unbinding to hydrolytic atomic bond rupture, we can develop perspectives and tools to address the challenges of predicting macroscopic kinetic consequences in complex materials characterized by rough energy landscapes. Here, we discuss the effects of mechanical force on chemical reactivity for specific complex materials of interest, and indicate how such validated computational analysis can enable predictive design of complex materials in reactive environments.     

Group dynamics and record signals in the ant Temnothorax albipennis

Many purely physical complex systems, in which there are both stochasticity and local interactions between the components, exhibit record dynamics. The temporal statistics of record dynamics is a Poisson process operating on a logarithmic rather than a linear time scale (i.e. a log-Poisson process). Record dynamics often drive substantial changes in complex systems when new high water marks in partially stochastic processes trigger new events. Social insect colonies are exemplary complex biological systems in which many of the local interactions of the components have been moulded by natural selection for the common good. Here, we combine experimental manipulation of ant colony demography with modelling to test the hypothesis that social interactions are the mechanism underlying the record dynamics. We found that compared with the control, log-Poisson statistics were disrupted in colonies in which the pattern of interactions was modified by the removal of the brood, and disappeared completely in ‘callow’ colonies composed entirely of very young workers from the same age cohort. We conclude that a subtle interplay between the demography of the society and the pattern of the interactions between the ants is crucial for the emergence of record dynamics. This could help identify what makes an ant colony a cohesive society.     

印刷机仿真平台的研究与设计

为了满足印刷机原理教学和培训的要求,解决实物教学面临的资金及设备数量的不足,选用基于模型的虚拟环境建立方法,采用Solidworks、3DsMax、director等三维设计及多媒体制作软件,探索了功能分组的机械建模方法和虚拟驱动的动态仿真,构建了虚拟印刷机使用平台,获得了比实物印刷机教学更好的效果.     

Review of semantic modelling technologies in support of virtual factory design

Comprehensive data models and standardised terminologies are required across tools and their developers to rapidly design and prototype digitised virtual factories. Also, various types of software are required to be integrated for cost-effective modelling exercises. To meet this requirement, semantic modelling technologies involving ontologies have featured prominently in many manufacturing applications. This paper considers, extensively, the current semantic requirements for digitised virtual factory design and prototyping and compares them with the capabilities of existing semantic technologies. As a result, a review of methodologies, tools and languages for creating ontologies has been reported. The review concludes with the next generation requirements for methodologies, tools and languages for creating ontologies suitable for the virtual factory design process, and further explains ongoing work associated with the creation of ontologies and reasoning mechanisms through the integrated use of ObjectLogic, OntoStudio and OntoBroker.     

The importance of accurate muscle modelling for biomechanical analyses: a case study with a lizard skull

Computer-based simulation techniques such as multi-body dynamics analysis are becoming increasingly popular in the field of skull mechanics. Multi-body models can be used for studying the relationships between skull architecture, muscle morphology and feeding performance. However, to be confident in the modelling results, models need to be validated against experimental data, and the effects of uncertainties or inaccuracies in the chosen model attributes need to be assessed with sensitivity analyses. Here, we compare the bite forces predicted by a multi-body model of a lizard (Tupinambis merianae) with in vivo measurements, using anatomical data collected from the same specimen. This subject-specific model predicts bite forces that are very close to the in vivo measurements and also shows a consistent increase in bite force as the bite position is moved posteriorly on the jaw. However, the model is very sensitive to changes in muscle attributes such as fibre length, intrinsic muscle strength and force orientation, with bite force predictions varying considerably when these three variables are altered. We conclude that accurate muscle measurements are crucial to building realistic multi-body models and that subject-specific data should be used whenever possible.     

On the effect of linear algebra implementations in real-time multibody system dynamics

This paper compares the efficiency of multibody system (MBS) dynamic simulation codes that rely on different implementations of linear algebra operations. The dynamics of an N-loop four-bar mechanism has been solved with an index-3 augmented Lagrangian formulation combined with the trapezoidal rule as numerical integrator. Different implementations for this method, both dense and sparse, have been developed, using a number of linear algebra software libraries (including sparse linear equation solvers) and optimized sparse matrix computation strategies. Numerical experiments have been performed in order to measure their performance, as a function of problem size and matrix filling. Results show that optimal implementations can increase the simulation efficiency in a factor of 2–3, compared with our starting classical implementations, and in some topics they disagree with widespread beliefs in MBS dynamics. Finally, advices are provided to select the implementation which delivers the best performance for a certain MBS dynamic simulation.     

Modelling materials driven far from equilibrium

Materials driven from equilibrium offer a challenging field for both time and space multiscale modelling. In materials under irradiation the elementary damaging process, that is, the nuclear collision leading to the displacement cascade, is modelled by molecular dynamics (≈ 10 ps, 10³ nm³), whereas the later stage recovery process is modelled by kinetic Monte Carlo (≈ years, 10⁴ nm³); at still a coarser scale, grain boundary segregations are modelled by a meanfield approximation of the very same atomistic model as used in kinetic Monte Carlo modelling. Connecting this broad range of time scales helps to elucidate basic issues on the criteria for alloy stability under irradiation. Irradiation effects on plasticity are beginning to be modelled in the same spirit; a first molecular dynamics study of the interaction of cascade debris with gliding dislocations has been reported together with the first results of mesoscale modelling of dislocation dynamics in the course of a nanoindentation test. Such studies can be extended to materials processed by ball milling.     

A two‐dimensional stochastic algorithm for the solution of the non‐linear Poisson–Boltzmann equation: validation with finite‐difference benchmarks

This paper presents a two‐dimensional floating random walk (FRW) algorithm for the solution of the non‐linear Poisson–Boltzmann (NPB) equation. In the past, the FRW method has not been applied to the solution of the NPB equation which can be attributed to the absence of analytical expressions for volumetric Green's functions. Previous studies using the FRW method have examined only the linearized Poisson–Boltzmann equation. No such linearization is needed for the present approach. Approximate volumetric Green's functions have been derived with the help of perturbation theory, and these expressions have been incorporated within the FRW framework. A unique advantage of this algorithm is that it requires no discretization of either the volume or the surface of the problem domains. Furthermore, each random walk is independent, so that the computational procedure is highly parallelizable. In our previous work, we have presented preliminary calculations for one‐dimensional and quasi‐one‐dimensional benchmark problems. In this paper, we present the detailed formulation of a two‐dimensional algorithm, along with extensive finite‐difference validation on fully two‐dimensional benchmark problems. The solution of the NPB equation has many interesting applications, including the modelling of plasma discharges, semiconductor device modelling and the modelling of biomolecular structures and dynamics. Copyright © 2005 John Wiley & Sons, Ltd.