Assessment of machine learning models trained by molecular dynamics simulations results for inferring ethanol adsorption on an aluminium surface.

Molecular dynamics (MD) simulations can reduce our need for experimental tests and provide detailed insight into the chemical reactions and binding kinetics. There are two challenges while dealing with MD simulations: one is the time and length scale limitations, and the latter is efficiently processing the massive amount of data resulting from the MD simulations and generating the proper reaction rates. In this work, we evaluated the use of regression machine learning (ML) methods to solve these two challenges by developing a framework for ethanol adsorption on an Aluminium (Al) slab. This framework comprises three main stages: first, an all-atom molecular dynamics model; second, ML regression models; and third, validation and testing. In stage one, the adsorption of ethanol molecules on the Al surface for various temperatures, velocities and concentrations is simulated using the large-scale atomic/molecular massively parallel simulator (LAMMPS) and ReaxFF. The outcome of stage one is utilised for training, testing, and validating the predictive models in stages two and three. We developed and evaluated 28 different ML models for predicting the number of adsorbed molecules over time, including linear regression, support vector machine (SVM), decision trees, ensemble, Gaussian process regression (GPR), neural network (NN) and Bayesian hyper-parameter optimisation models. Based on the results, the Bayesian-based GPR showed the highest accuracy and the lowest training time. The developed model can predict the number of adsorbed molecules for new cases within seconds, while MD simulations take a few weeks. This adsorption rate can then be used in macroscale simulations to tackle the time and length scale limitations. The proposed numerical framework has the potential to be generalised and, therefore, contribute to future low-cost binding reaction estimations, providing a valuable tool for industry and experimentalists.

Enhancing the implantation of mechanical circulatory support devices using computational simulations.

Introduction: Patients with end-stage heart failure (HF) may need mechanical circulatory support such as a left ventricular assist device (LVAD). However, there are a range of complications associated with LVAD including aortic regurgitation (AR) and thrombus formation. This study assesses whether the risk of developing aortic conditions can be minimised by optimising LVAD implantation technique. Methods: In this work, we evaluate the aortic flow patterns produced under different geometrical parameters for the anastomosis of the outflow graft (OG) to the aorta using computational fluid dynamics (CFD). A three-dimensional aortic model is created and the HeartMate III OG positioning is simulated by modifying (i) the distance from the anatomic ventriculo-arterial junction (AVJ) to the OG, (ii) the cardinal position around the aorta, and (iii) the angle between the aorta and the OG. The continuous LVAD flow and the remnant native cardiac cycle are used as inlet boundaries and the three-element Windkessel model is applied at the pressure outlets. Results: The analysis quantifies the impact of OG positioning on different haemodynamic parameters, including velocity, wall shear stress (WSS), pressure, vorticity and turbulent kinetic energy (TKE). We find that WSS on the aortic root (AoR) is around two times lower when the OG is attached to the coronal side of the aorta using an angle of 45° ± 10° at a distance of 55 mm. Discussion: The results show that the OG placement may significantly influence the haemodynamic patterns, demonstrating the potential application of CFD for optimising OG positioning to minimise the risk of cardiovascular complications after LVAD implantation.

Smoothed particle hydrodynamics based FSI simulation of the native and mechanical heart valves in a patient-specific aortic model.

The failure of the aortic heart valve is common, resulting in deterioration of the pumping function of the heart. For the end stage valve failure, bi-leaflet mechanical valve (most popular artificial valve) is implanted. However, due to its non-physiological behaviour, a significant alteration is observed in the normal haemodynamics of the aorta. While in-vivo experimentation of a human heart valve (native and artificial) is a formidable task, in-silico study using computational fluid dynamics (CFD) with fluid structure interaction (FSI) is an effective and economic tool for investigating the haemodynamics of natural and artificial heart valves. In the present work, a haemodynamic model of a natural and mechanical heart valve has been developed using meshless particle-based smoothed particle hydrodynamics (SPH). In order to further enhance its clinical relevance, this study employs a patient-specific vascular geometry and presents a successful validation against traditional finite volume method and 4D magnetic resonance imaging (MRI) data. The results have demonstrated that SPH is ideally suited to simulate the heart valve function due to its Lagrangian description of motion, which is a favourable feature for FSI. In addition, a novel methodology for the estimation of the wall shear stress (WSS) and other related haemodynamic parameters have been proposed from the SPH perspective. Finally, a detailed comparison of the haemodynamic parameters has been carried out for both native and mechanical aortic valve, with a particular emphasis on the clinical risks associated with the mechanical valve.

Exergy destruction in atrial fibrillation and a new 'Exergy Age Index'.

The concept of exergy in living organisms has been widely used to explore correlations between exergy and different physiological conditions. Atrial fibrillation (AF) is an abnormal physiological condition that takes place inside the heart and is recognised as a common supraventricular arrhythmia. AF can significantly undermine heart function and subsequently circulatory system. Thus, exergy analysis of cardiac flow during AF is a procedure to quantify the long-term impact of persistent AF. The present study adopts the lumped modelling approach for considering cardiovascular circulation and thermoregulation of the body to evaluate the exergy consumption and destruction of the heart in AF. In order to assess the impact of AF, four common AF-associated characteristics including lack of atrial kick, left atrial remodelling, left ventricular systolic dysfunction, and high-frequency fibrillation are examined. The results show that among AF deficiencies, high-frequency fibrillation is the main cause of exergy destruction of the heart during AF. Moreover, a novel 'exergy age index' is proposed which has shown that high fibrillatory conditions in AF can significantly accelerate the heart ageing process, which in turn substantiates AF's adverse impact on the heart.

Multi-Objective Optimisation of a Novel Bypass Graft with a Spiral Ridge.

The low long-term patency of bypass grafts is a major concern for cardiovascular treatments. Unfavourable haemodynamic conditions in the proximity of distal anastomosis are closely related to thrombus creation and lumen lesions. Modern graft designs address this unfavourable haemodynamic environment with the introduction of a helical component in the flow field, either by means of out-of-plane helicity graft geometry or a spiral ridge. While the latter has been found to lack in performance when compared to the out-of-plane helicity designs, recent findings support the idea that the existing spiral ridge grafts can be further improved in performance through optimising relevant design parameters. In the current study, robust multi-objective optimisation techniques are implemented, covering a wide range of possible designs coupled with proven and well validated computational fluid dynamics (CFD) algorithms. It is shown that the final set of suggested design parameters could significantly improve haemodynamic performance and therefore could be used to enhance the design of spiral ridge bypass grafts.

A Molecular Dynamics Model for Biomedical Sensor Evaluation: Nanoscale Numerical Simulation of an Aluminum-Based Biosensor.

Metallic nanostructured-based biosensors provide label-free, multiplexed, and real-time detections of chemical and biological targets. Aluminum-based biosensors are favored in this category, due to their enhanced stability and profitability. Despite the recent advances in nanotechnology and the significant improvement in development of these biosensors, some deficiencies restrict their utilization. Hence a detailed insight into their behavior in different conditions would be crucial, which can be achieved with nanoscale numerical simulation. With this aim, an Aluminum-based biosensor is chosen to be analyzed with the help of all-atom molecular dynamics model (AA-MD), using large-scale atomic/molecular massively parallel simulator (LAMMPS). The surface properties and adsorption process through different flow conditions and various concentration of the target, are investigated in this study. In the future work, the results of this study will be used for developing a predictive model for surface properties of the biosensor. Clinical Relevance- The role of biosensors in clinical applications and early diagnosis is evident. This work provides a model for predicting the binding behavior of the target molecules on the biosensor surface in different conditions. Results demonstrate an increase in the adsorption of ethanol on the biosensor surface of 7% up to 80% with changing the velocity from 0.001 m/s to 1 m/s Although for cases with higher concentration this trend becomes complicated necessitating the implementation of machine learning models in the future works.

Identification of the haemodynamic environment permissive for plaque erosion.

Endothelial erosion of atherosclerotic plaques is the underlying cause of approximately 30% of acute coronary syndromes (ACS). As the vascular endothelium is profoundly affected by the haemodynamic environment to which it is exposed, we employed computational fluid dynamic (CFD) analysis of the luminal geometry from 17 patients with optical coherence tomography (OCT)-defined plaque erosion, to determine the flow environment permissive for plaque erosion. Our results demonstrate that 15 of the 17 cases analysed occurred on stenotic plaques with median 31% diameter stenosis (interquartile range 28-52%), where all but one of the adherent thrombi located proximal to, or within the region of maximum stenosis. Consequently, all flow metrics related to elevated flow were significantly increased (time averaged wall shear stress, maximum wall shear stress, time averaged wall shear stress gradient) with a reduction in relative residence time, compared to a non-diseased reference segment. We also identified two cases that did not exhibit an elevation of flow, but occurred in a region exposed to elevated oscillatory flow. Our study demonstrates that the majority of OCT-defined erosions occur where the endothelium is exposed to elevated flow, a haemodynamic environment known to evoke a distinctive phenotypic response in endothelial cells.

Effects of Ageing on Aortic Circulation During Atrial Fibrillation; a Numerical Study on Different Aortic Morphologies.

Atrial fibrillation (AF) can alter intra-cardiac flow and cardiac output that subsequently affects aortic flow circulation. These changes may become more significant where they occur concomitantly with ageing. Aortic ageing is accompanied with morphological changes such as dilation, lengthening, and arch unfolding. While the recognition of AF mechanism has been the subject of numerous studies, less focus has been devoted to the aortic circulation during the AF and there is a lack of such investigation at different ages. The current work aims to address the present gap. First, we analyse aortic flow distribution in three configurations, which attribute to young, middle and old people, using geometries constructed via clinical data. We then introduce two transient inlet flow conditions representative of key AF-associated defects. Results demonstrate that both AF and ageing negatively affect flow circulation. The main consequence of concomitant occurrence is enhancement of endothelial cell activation potential (ECAP) throughout the vascular domain, mainly at aortic arch and descending thoracic aorta, which is consistent with some clinical observations. The outcome of the current study suggests that AF exacerbates the vascular defects occurred due to the ageing, which increases the possibility of cardiovascular diseases per se.

A computational simulation platform for designing real-time monitoring systems with application to COVID-19.

With the aim of contributing to the fight against the coronavirus disease 2019 (COVID-19), numerous strategies have been proposed. While developing an effective vaccine can take months up to years, detection of infected patients seems like one of the best ideas for controlling the situation. The role of biosensors in containing highly pathogenic viruses, saving lives and economy is evident. A new competitive numerical platform specifically for designing microfluidic-integrated biosensors is developed and presented in this work. Properties of the biosensor, sample, buffer fluid and even the microfluidic channel can be modified in this model. This feature provides the scientific community with the ability to design a specific biosensor for requested point-of-care (POC) applications. First, the validation of the presented numerical platform against experimental data and then results and discussion, highlighting the important role of the design parameters on the performance of the biosensor is presented. For the latter, the baseline case has been set on the previous studies on the biosensors suitable for SARS-CoV, which has the highest similarity to the 2019 nCoV. Subsequently, the effects of concentration of the targeted molecules in the sample, installation position and properties of the biosensor on its performance were investigated in 11 case studies. The presented numerical framework provides an insight into understanding of the virus reaction in the design process of the biosensor and enhances our preparation for any future outbreaks. Furthermore, the integration of biosensors with different devices for accelerating the process of defeating the pandemic is proposed.

Numerical framework for simulating bio-species transport in microfluidic channels with application to antibody biosensors.

Diagnosis is a fundamental stage in health care and medical treatment. Microfluidic biosensors and lab-on-a-chip devices are amongst the few practical tools for achieving this goal. A new computational code, specifically for designing microfluidic-integrated biosensors is developed, the details of which is presented in this work. This new approach is developed using control-volume based finite-element (CVFEM) method and solves bio-recognition chemical reactions and full Navier-Stokes equations. The results of the proposed platform are validated against the experimental data for a microfluidic based biosensor, where excellent agreement is achieved. The properties of the biosensor, sample, buffer fluid and even the microfluidic channel can easily be modified in this platform. This feature provides the scientific community with the ability to design a specific biosensor for requested point-of-care applications.•A new approach is developed using control-volume based finite-element (CVFEM) method for investigating flow inside a microfluidic-integrated biosensor. It is also used to study the influence of surface functionalization on binding cycle.•The proposed model solves bio-recognition chemical reactions as well as full Navier-Stokes and energy equations. Experimental-based or personalized equations of the chemical reactions and flow behaviour are adoptable to this code.•The developed model is Fortran-based and has the potential to be used in both industry and academia for biosensing technology.

Investigation of Overlapped Twisted Tapes Inserted in a Double-Pipe Heat Exchanger Using Two-Phase Nanofluid.

This study investigated the laminar convective heat transfer and fluid flow of Al2O3 nanofluid in a counter flow double-pipe heat exchanger equipped with overlapped twisted tape inserts in both inner and outer tubes. Two models of the same (co-swirling twisted tapes) and opposite (counter-swirling twisted tapes) angular directions for the stationary twisted tapes were considered. The computational fluid dynamic simulations were conducted through varying the design parameters, including the angular direction of twisted tape inserts, nanofluid volume concentration, and Reynolds number. It was found that inserting the overlapped twisted tapes in the heat exchanger significantly increases the thermal performance as well as the friction factor compared with the plain heat exchanger. The results indicate that models of co-swirling twisted tapes and counter-swirling twisted tapes increase the average Nusselt number by almost 35.2-66.2% and 42.1-68.7% over the Reynolds number ranging 250-1000, respectively. To assess the interplay between heat transfer enhancement and pressure loss penalty, the dimensionless number of performance evaluation criterion was calculated for all the captured configurations. Ultimately, the highest value of performance evaluation criterion is equal to 1.40 and 1.26 at inner and outer tubes at the Reynolds number of 1000 and the volume fraction of 3% in the case of counter-swirling twisted tapes model.

A Patient-Specific CFD Pipeline Using Doppler Echocardiography for Application in Coarctation of the Aorta in a Limited Resource Clinical Context.

Congenital heart disease (CHD) is the most common birth defect globally and coarctation of the aorta (CoA) is one of the commoner CHD conditions, affecting around 1/1800 live births. CoA is considered a CHD of critical severity. Unfortunately, the prognosis for a child born in a low and lower-middle income country (LLMICs) with CoA is far worse than in a high-income country. Reduced diagnostic and interventional capacities of specialists in these regions lead to delayed diagnosis and treatment, which in turn lead to more cases presenting at an advanced stage. Computational fluid dynamics (CFD) is an important tool in this context since it can provide additional diagnostic data in the form of hemodynamic parameters. It also provides an in silico framework, both to test potential procedures and to assess the risk of further complications arising post-repair. Although this concept is already in practice in high income countries, the clinical infrastructure in LLMICs can be sparse, and access to advanced imaging modalities such as phase contrast magnetic resonance imaging (PC-MRI) is limited, if not impossible. In this study, a pipeline was developed in conjunction with clinicians at the Red Cross War Memorial Children's Hospital, Cape Town and was applied to perform a patient-specific CFD study of CoA. The pipeline uses data acquired from CT angiography and Doppler transthoracic echocardiography (both much more clinically available than MRI in LLMICs), while segmentation is conducted via SimVascular and simulation is realized using OpenFOAM. The reduction in cost through use of open-source software and the use of broadly available imaging modalities makes the methodology clinically feasible and repeatable within resource-constrained environments. The project identifies the key role of Doppler echocardiography, despite its disadvantages, as an intrinsic component of the pipeline if it is to be used routinely in LLMICs.

Numerical Study of Atrial Fibrillation Effects on Flow Distribution in Aortic Circulation.

Atrial fibrillation (AF) is the most common type of arrhythmia, which undermines cardiac function. Atrial fibrillation is a multi-facet malady and it may occur as a result of other diseases or it may trigger other problems. One of the main complications of AF is stroke due to the possibility of clot formation inside the atrium. However, the possibility of stroke occurrence due to the AF and the location from which an embolus dispatches are subject of debate. Another hypothesis about the embolus formation during AF is thrombus formation in aorta and carotid arteries, embolus detachment and its movement. To investigate the possibility of the latter postulation, the current work suggests a parametric study to quantify the sensitivity of aortic flow to four common AF traits including lack of atrial kick, atrial remodelling, left ventricle systolic dysfunction, and high frequency fibrillation. The simulation was carried out by coupling several in-house codes and ANSYS-CFX module. The results reveal that AF traits lower flow rate at left ventricular outflow tract, which in general lowers blood perfusion to systemic, cerebral and coronary circulations. Consequently, it leads to endothelial cell activation potential (ECAP) increase and variation of flow structure that both suggest predisposed areas to atherogenesis and thrombus formation in different regions in ascending aorta, aortic arch and descending thoracic aorta.

Desiccation crisis of saline lakes: A new decision-support framework for building resilience to climate change.

River flow reductions as a result of agricultural withdrawals and climate change are rapidly desiccating endorheic lakes, increasing their salinity and affecting the bio-diversity and human wellbeing in the surrounding areas. Here we present a new framework to guide eco-hydrological restoration of saline lakes and build their resilience to climate change by optimizing agricultural land use and related water withdrawals. The framework involves four steps: 1. selection of global circulation models for the basin under study; 2. establishment of a hydrological balance over the lake's area to estimate the amount of water required for its restoration; 3. water allocation modeling to determine the water available for restoration and allocation of the remaining water across different users in the lake's basin; and 4. basin-scale optimization of land use and cropping patterns subject to water availability. We illustrated the general applicability of the framework through the case of the second largest (by volume) hyper-saline lake globally, Lake Urmia, which lost 96% of its volume in only 20 years, primarily as a result of upstream water withdrawals. Through the application of the framework, we estimated the amount of water needed to restore the lake, either fully or partially, and proposed a sustainable land-use strategy, while protect farmers' income in the basin. Considering future climate change projections under two representative concentration pathways (RCP) 4.5 and 8.5, we found that an average annual surface inflow of 3,648 Mm3 (∼70% increase in RCP 4.5) and 3,692 Mm3 (∼73% increase in RCP 8.5) would be required to restore the lake by 2050, respectively. This would require the respective conversion of 95,600 ha and 133,687 ha of irrigated land to rain-fed cropland or grassland across the basin by 2050. The proposed framework can be used for building resilience to climate change and mitigating human-induced threats to other declining saline lakes.

Impact of Using Conventional Inlet/Outlet Boundary Conditions on Haemodynamic Metrics in a Subject-Specific Rabbit Aorta.

Computational fluid dynamics is a tool capable of accurately measuring metrics currently used to predict the behaviour of cardiovascular diseases. This study quantifies the impact various commonly used inlet and outlet boundary conditions have on various shear rate-based haemodynamic metrics currently used for predicting the localisation of cardiovascular diseases. Simulations are conducted on an accurately represented rabbit aorta configuration and comparison has been made against available in vivo data. The boundary conditions studied include two different inlet profiles, three outlet boundary conditions, and steady-state versus pulsatile flow cases. Large variations were found in the results, particularly when using different outlet boundary conditions, and the discrepancies were evaluated both quantitatively and qualitatively. The results clearly highlight the importance of the type of boundary condition used when simulating complex cardiovascular models. By restricting the attention to the flow within the aorta and the intercostal branches, the results suggest that prescribing transient simulation and fully developed flow at the inlet are not required. Furthermore, assuming the widely accepted low wall shear stress theory of Caro, it was found that Murray's law-based outlet boundary condition returns the most physiologically accurate results when compared to in vivo data.

Optimisation of a Novel Spiral-Inducing Bypass Graft Using Computational Fluid Dynamics.

Graft failure is currently a major concern for medical practitioners in treating Peripheral Vascular Disease (PVD) and Coronary Artery Disease (CAD). It is now widely accepted that unfavourable haemodynamic conditions play an essential role in the formation and development of intimal hyperplasia, which is the main cause of graft failure. This paper uses Computational Fluid Dynamics (CFD) to conduct a parametric study to enhance the design and performance of a novel prosthetic graft, which utilises internal ridge(s) to induce spiral flow. This design is primarily based on the identification of the blood flow as spiral in the whole arterial system and is believed to improve the graft longevity and patency rates at distal graft anastomoses. Four different design parameters were assessed in this work and the trailing edge orientation of the ridge was identified as the most important parameter to induce physiological swirling flow, while the height of the ridge also significantly contributed to the enhanced performance of this type of graft. Building on these conclusions, an enhanced configuration of spiral graft is proposed and compared against conventional and spiral grafts to reaffirm its potential benefits.

Numerical Assessment of Novel Helical/Spiral Grafts with Improved Hemodynamics for Distal Graft Anastomoses.

In the present work, numerical simulations were conducted for a typical end-to-side distal graft anastomosis to assess the effects of inducing secondary flow, which is believed to remove unfavourable flow environment. Simulations were carried out for four models, generated based on two main features of 'out-of-plane helicity' and 'spiral ridge' in the grafts as well as their combination. Following a qualitative comparison against in vitro data, various mean flow and hemodynamic parameters were compared and the results showed that helicity is significantly more effective in inducing swirling flow in comparison to a spiral ridge, while their combination could be even more effective. In addition, the induced swirling flow was generally found to be increasing the wall shear stress and reducing the flow stagnation and particle residence time within the anastomotic region and the host artery, which may be beneficial to the graft longevity and patency rates. Finally, a parametric study on the spiral ridge geometrical features was conducted, which showed that the ridge height and the number of spiral ridges have significant effects on inducing swirling flow, and revealed the potential of improving the efficiency of such designs.