Computational modeling of cardiac electrophysiology: A novel finite element approach

The key objective of this work is the design of an unconditionally stable, robust, efficient, modular, and easily expandable finite element‐based simulation tool for cardiac electrophysiology. In contrast to existing formulations, we propose a global–local split of the system of equations in which the global variable is the fast action potential that is introduced as a nodal degree of freedom, whereas the local variable is the slow recovery variable introduced as an internal variable on the integration point level. Cell‐specific excitation characteristics are thus strictly local and only affect the constitutive level. We illustrate the modular character of the model in terms of the FitzHugh–Nagumo model for oscillatory pacemaker cells and the Aliev–Panfilov model for non‐oscillatory ventricular muscle cells. We apply an implicit Euler backward finite difference scheme for the temporal discretization and a finite element scheme for the spatial discretization. The resulting non‐linear system of equations is solved with an incremental iterative Newton–Raphson solution procedure. Since this framework only introduces one single scalar‐valued variable on the node level, it is extremely efficient, remarkably stable, and highly robust. The features of the general framework will be demonstrated by selected benchmark problems for cardiac physiology and a two‐dimensional patient‐specific cardiac excitation problem. Copyright © 2009 John Wiley & Sons, Ltd.     

The optimal deployment of synergistic antibiotics: a control-theoretic approach

Medical and pharmacological communities have long searched for antimicrobial drugs that increase their effect when used in combination, an interaction known as synergism. These drug combinations, however, impose selective pressures in favour of multi-drug resistance and as a result, the benefit of synergy may be lost after only a few bacterial generations. Furthermore, there is experimental evidence that antibiotic treatment can disrupt colonization resistance by shifting the balance between enteropathogenic and commensal bacteria in favour of the pathogens, with the potential to increase the risk of infections. So, we ask, what is the best way of using synergistic drugs? We pose an evolutionary model of commensal and pathogenic bacteria competing in a continuous culture device for a single limiting carbon source under the effect of two bacteriostatic and synergistic antibiotics. This model allows us to evaluate the efficacy of different drug deployment strategies and, using ideas from optimal control theory, to understand whether there are circumstances in which other types of therapy might be favoured over those based on fixed-dose multi-drug combinations. Our main result can be stated thus: the optimal deployment of synergistic antibiotics to remove a pathogen in the presence of commensal bacteria in our model system occurs not in combination, but by deploying them sequentially.     

Effects of Nanoparticle Electrostatics and Protein–Protein Interactions on Corona Formation: Conformation and Hydrodynamics

All‐atom molecular dynamics simulations of plasma proteins (human serum albumin, fibrinogen, immunoglobulin gamma‐1 chain‐C, complement C3, and apolipoprotein A‐I) adsorbed onto 10 nm sized cationic, anionic, and neutral polystyrene (PS) particles in water are performed. In simulations of a single protein with a PS particle, proteins eventually bind to all PS particles, regardless of particle charge, in agreement with experiments showing the binding between anionic proteins and particles, which is further confirmed by calculating the binding free energies from umbrella sampling simulations. Simulations of mixtures of multiple proteins and a PS particle show the formation of the protein layer on the surface via the adsorption competition between proteins, which influences the binding affinity and structure of adsorbed proteins. In particular, diffusivities are much higher for proteins bound to the particle surface or to the boundary of the protein layer than for those bound to both the particle surface and other proteins, indicating the dependence of protein mobility on their positions in the layer. These findings help to explain in detail experimental observations regarding the replacement of plasma proteins at the early stage of corona formation and the difference in the binding strength of proteins in inner and outer protein‐layers.     

Optimising risk reduction: An expected utility approach for marginal risk reduction during regulatory decision making

In practice, risk and uncertainty are essentially unavoidable in many regulation processes. Regulators frequently face a risk-benefit trade-off since zero risk is neither practicable nor affordable. Although it is accepted that cost–benefit analysis is important in many scenarios of risk management, what role it should play in a decision process is still controversial. One criticism of cost–benefit analysis is that decision makers should consider marginal benefits and costs, not present ones, in their decision making. In this paper, we investigate the problem of regulatory decision making under risk by applying expected utility theory and present a new approach of cost–benefit analysis. Directly taking into consideration the reduction of the risks, this approach achieves marginal cost–benefit analysis. By applying this approach, the optimal regulatory decision that maximizes the marginal benefit of risk reduction can be considered. This provides a transparent and reasonable criterion for stakeholders involved in the regulatory activity. An example of evaluating seismic retrofitting alternatives is provided to demonstrate the potential of the proposed approach.     

Sustainable Synthesis of Co@NC Core Shell Nanostructures from Metal Organic Frameworks via Mechanochemical Coordination Self‐Assembly: An Efficient Electrocatalyst for Oxygen Reduction Reaction

Herein, a new type of cobalt encapsulated nitrogen‐doped carbon (Co@NC) nanostructure employing Zn_xCo_1?x(C₃H₄N₂) metal–organic framework (MOF) as precursor is developed, by a simple, ecofriendly, solvent‐free approach that utilizes a mechanochemical coordination self‐assembly strategy. Possible evolution of Zn_xCo_1?x(C₃H₄N₂) MOF structures and their conversion to Co@NC nanostructures is established from an X‐ray diffraction technique and transmission electron microscopy analysis, which reveal that MOF‐derived Co@NC core–shell nanostructures are well ordered and highly crystalline in nature. Co@NC–MOF core–shell nanostructures show excellent catalytic activity for the oxygen reduction reaction (ORR), with onset potential of 0.97 V and half‐wave potential of 0.88 V versus relative hydrogen electrode in alkaline electrolyte, and excellent durability with zero degradation after 5000 potential cycles; whereas under similar experimental conditions, the commonly utilized Pt/C electrocatalyst degrades. The Co@NC–MOF electrocatalyst also shows excellent tolerance to methanol, unlike the Pt/C electrocatalyst. X‐ray photoelectron spectroscopy (XPS) analysis shows the presence of ORR active pyridinic‐N and graphitic‐N species, along with CoN_x? C_y and Co? N_x ORR active (M–N–C) sites. Enhanced electron transfer kinetics from nitrogen‐doped carbon shell to core Co nanoparticles, the existence of M–N–C active sites, and protective NC shells are responsible for high ORR activity and durability of the Co@NC–MOF electrocatalyst.     

Comparative Study of Strain‐Dependent Structural Changes of Silkworm Silks: Insight into the Structural Origin of Strain‐Stiffening

Structure–property relationships of silk is an intriguing topic for silk‐based biomaterials research since these features are related to biomimicking the processing in natural silk fiber formation which results in excellent mechanical properties. Strain‐stiffening is common for spider silks and nonmulberry silkworm silks. However, the structural origin of strain‐stiffening remains unclear. In this paper, the strain‐dependent structural change of Antheraea pernyi silkworm silk is studied by X‐ray fiber diffraction and Fourier transform infrared spectroscopy under stretching. Based on a combination of mechanical and structural analysis, the molecular origins of strain‐stiffening in A. pernyi silk were determined. The relatively high content of the β‐sheets within the amorphous domains in A. pernyi silk is responsible for strain‐stiffening, where “molecular spindles” enhance the extensibility and toughness of the fiber.     

Rotating‐Electric‐Field‐Induced Carbon‐Nanotube‐Based Nanomotor in Water: A Molecular Dynamics Study

Using molecular dynamics simulations, it is shown that a carbon nanotube (CNT) suspended in water and subjected to a rotating electric field of proper magnitude and angular speed can be rotated with the aid of water dipole orientations. Based on this principle, a rotational nanomotor structure is designed and the system is simulated in water. Use of the fast responsiveness of electric‐field‐induced CNT orientation in water is employed and its operation at ultrahigh‐speed (over 10¹¹ r.p.m.) is shown. To explain the basic mechanism, the behavior of the rotational actuation, originated from the water dipole orientation, is also analyzed . The proposed nanomotor is capable of rotating an attached load (such as CNT) at a precise angle as well as nanogear‐based complex structures. The findings suggest a potential way of using the electric‐field‐induced CNT rotation in polarizable fluids as a novel tool to operate nanodevices and systems.     

A Lagrangian finite element approach for the analysis of fluid–structure interaction problems

A Lagrangian finite element method for the analysis of incompressible Newtonian fluid flows, based on a continuous re‐triangulation of the domain in the spirit of the so‐called Particle Finite Element Method, is here revisited and applied to the analysis of the fluid phase in fluid–structure interaction problems. A new approach for the tracking of the interfaces between fluids and structures is proposed. Special attention is devoted to the mass conservation problem. It is shown that, despite its Lagrangian nature, the proposed combined finite element‐particle method is well suited for large deformation fluid–structure interaction problems with evolving free surfaces and breaking waves. The method is validated against the available analytical and numerical benchmarks. Copyright © 2010 John Wiley & Sons, Ltd.     

A 3D finite element approach for the coupled numerical simulation of electrochemical systems and fluid flow

A comprehensive finite element method for three‐dimensional simulations of stationary and transient electrochemical systems including all multi‐ion transport mechanisms (convection, diffusion and migration) is presented. In addition, non‐linear phenomenological electrode kinetics boundary conditions are accounted for. The governing equations form a set of coupled non‐linear partial differential equations subject to an algebraic constraint due to the electroneutrality condition. The advantage of a convective formulation of the ion‐transport equations with respect to a natural application of homogeneous flux boundary conditions is emphasized. For one of the numerical examples, an analytical solution for the coupled problem is provided, and it is demonstrated that the proposed computational approach is robust and provides accurate results. Copyright © 2011 John Wiley & Sons, Ltd.     

CVD growth of cubic boron nitride: A theoretical/experimental approach

Similarities and dissimilarities in the growth of diamond vs. c-BN, in the present series of investigations, have been studied using quantum mechanical calculations. Hydrogen species have been observed to be very effective in stabilising both types of compounds. Very large similarities have also been observed when considering the adsorption of various growth species to these materials. However, it was found necessary to avoid mixtures of B- and N-containing species in the gas phase during c-BN growth, since they should most probably result in a mixture of these species also on the (111) and (110) surfaces. In addition, a careful gas phase design was found necessary in order to avoid a preferential initial growth of h-BN. These theoretical results can be used as guide lines in striving towards a thin film deposition of cubic boron nitride using gentle CVD methods like atomic layer deposition.     

A study of the strength of carbon–carbon brake disks for automotive applications

Carbon–carbon composites are often used in high-temperature applications due to their high specific modulus, high specific strength, excellent heat resistance, high thermal shock resistance and chemical inertness. In this paper, the strength of carbon/carbon brake disks for automotive applications were tested and evaluated. The laminate material properties of carbon/carbon composites were evaluated via tension, compression and shear tests. The strengths of mechanically fastened composite joints for brake disks were tested and their failure criterion was established based on the maximum stress theory. Additionally, torsion tests of carbon/carbon brake disks were performed and the results were compared with those from a finite element analysis.     

A numerical approach for limit analysis of orthotropic composite laminates

A numerical approach for limit analysis of structures whose constituent material exhibits orthotropic behaviour is presented and discussed. Attention is focused on orthotropic composite laminates under plane stress conditions. The proposed approach is an extension, in the context of orthotropic materials, of the linear matching method (LMM). The latter is based on a sequence of linear analyses performed on the analysed structure made of a fictitious linear viscous material with spatially varying moduli. Here the LMM is applied to structures made of materials obeying the Tsai–Wu criterion. An appropriate choice of the fictitious material, which in this case is assumed linear, viscous, orthotropic and suffering a distribution of assigned initial stresses, reduces the number of parameters to be spatially varied thus rendering the whole procedure applicable and reliable. The results obtained are highly promising as witnessed by a number of numerical examples which are carried out to verify the effectiveness of the proposed approach. Copyright © 2006 John Wiley & Sons, Ltd.     

A reduced‐order representation of the Poincaré–Steklov operator: an application to coupled multi‐physics problems

This work investigates a model reduction method applied to coupled multi‐physics systems. The case in which a system of interest interacts with an external system is considered. An approximation of the Poincaré–Steklov operator is computed by simulating, in an offline phase, the external problem when the inputs are the Laplace–Beltrami eigenfunctions defined at the interface. In the online phase, only the reduced representation of the operator is needed to account for the influence of the external problem on the main system. An online basis enrichment is proposed in order to guarantee a precise reduced‐order computation. Several test cases are proposed on different fluid–structure couplings. Copyright © 2016 John Wiley & Sons, Ltd.     

A neural-network approach to describe the scatter of cyclic stress–strain curves

In order to predict a product’s durability in the early phases of development it is necessary to know the stress–strain behaviour of the material, its resistance to fatigue and the loading states in the material. These parameters, however, tend to exhibit a considerable degree of uncertainty. Due to a lack of knowledge of the actual circumstances in which the product is used, during the early development phase, simulations based on statistical methods are used. The results of the experiments show that the cyclic stress–strain curves demonstrate not only a large amount of scatter, but also a dependence on the temperature, the size of the cross-section, the content of alloying elements, the loading rate, etc.This article presents a method for modelling cyclic stress–strain curve scatter using a hybrid neural network for an arbitrary selection of the influencing factors. In an example of the measured data for a high pressure die-cast aluminium alloy it is clear that the suggested method is suitable for describing cyclic stress–strain curves. The main advantage of a hybrid neural network in comparison with a conventional method is the neural network’s ability to precisely describe the influence of various factors, and their combinations, based on the form and scatter of the cyclic stress–strain curve families. Defining the model parameters, i.e., training the neural network, is a procedure that does not require any additional user interventions; however, it enables us to gather knowledge that would otherwise require a lot of research. Thus, the trained neural network is a robust tool that can be used to predict cyclic stress–strain curves for random values of influencing factors. The capabilities of the presented method are only limited by the quantity of the measured data used for the neural-network training.     

A study of tensile properties in Al–Si–Cu and Al–Si–Mg alloys: Effect of β-iron intermetallics and porosity

The effect of β-iron intermetallics and porosity on the tensile properties in cast Al–Si–Cu and Al–Si–Mg alloys were investigated for this research study, using experimental and industrial 319.2 alloys, and industrial A356.2 alloys. The results showed that the alloy ductility and ultimate tensile strength (UTS) were subject to deterioration as a result of an increase in the size of β-iron intermetallics, most noticeable up to β-iron intermetallic lengths of 100 μm in 319.2 alloys, or 70 μm in A356.2 alloys. An increase in the size of the porosity was also deleterious to alloy ductility and UTS. Although tensile properties are interpreted by means of UTS vs. log elongation plots in the present study, the properties for all sample conditions were best interpreted by means of log UTS vs. log elongation plots, where the properties increased linearly between conditions of low cooling rate–high Fe and high cooling rate–low Fe. The results are explained in terms of the β-Al₅FeSi platelet size and porosity values obtained.