To accurately simulate all phases of the cardiac cycle, computational models of hemodynamics in heart chambers need to include a sufficiently faithful model of cardiac valves. This can be achieved efficiently through resistive methods, and the resistive immersed implicit surface (RIIS) model in particular [Fedele et al., BMMB, 2017]. However, the conventional RIIS model is not suited to fluid-structure interaction (FSI) simulations, since it neglects the reaction forces by which valves are attached to the cardiac walls, leading to models that are not consistent with Newton's laws. In this paper, we propose an improvement to RIIS to overcome this limitation, by adding distributed forces acting on the structure to model the attachment of valves to the cardiac walls. The modification has a minimal computational overhead thanks to an explicit numerical discretization scheme. Numerical experiments in both idealized and realistic settings demonstrate the effectiveness of the proposed modification in ensuring the physical consistency of the model, thus allowing to apply RIIS and other resistive valve models in the context of FSI simulations.
Pressure-relief valves, often the critical last line of defence in process engineering, are known to be susceptible to valve chatter. Such behaviour has been shown to arise from a flutter instability, or Hopf bifurcation, associated with the fundamental, quarter-wave acoustic mode of their inlet piping. Here, a novel design concept is proposed and analyzed for eliminating this instability. The concept involves using an oversized valve with reduced lift and adopting a discharge characteristic that enhances the blow-down effect, so that the valve opens immediately to its upper lift limit upon reaching set pressure. The concept is demonstrated numerically using an updated version of a 1D fluid pipe dynamics mathematical model solved using a Lax-Wendroff method. Stability properties are analysed using dynamical systems theory, applied to an improved reduced-order modal model. It is shown how the valve settles to a stable so-called pseudo equilibrium, in contact with the upper stop, provided the coefficient of restitution of is not too large. Such stable operation is reached despite the equivalent regular valve being unstable to the quarter-wave Hopf bifurcation. Parameter studies using
Soft valves serve to modulate and rectify flows in complex vasculatures across the tree of life, e.g. in the heart of every human reading this. Here we consider a minimal physical model of the heart mitral valve modeled as a flexible conical shell capable of flow rectification via collapse and coaptation in an impinging (reverse) flow. Our experiments show that the complex elastohydrodynamics of closure features a noise-activated rectification mechanism. A minimal theoretical model allows us to rationalize our observations while illuminating a dynamical bifurcation driven by stochastic hydrodynamic forces. Our theory also suggests a way to trigger the coaptation of soft valves on demand, which we corroborate using experiments, suggesting a design principle for their efficient operation.
Echocardiography provides an important tool for clinicians to observe the function of the heart in real time, at low cost, and without harmful radiation. Automated localization and classification of heart valves enables automatic extraction of quantities associated with heart mechanical function and related blood flow measurements. We propose a machine learning pipeline that uses deep neural networks for separate classification and localization steps. As the first step in the pipeline, we apply view classification to echocardiograms with ten unique anatomic views of the heart. In the second step, we apply deep learning-based object detection to both localize and identify the valves. Image segmentation based object detection in echocardiography has been shown in many earlier studies but, to the best of our knowledge, this is the first study that predicts the bounding boxes around the valves along with classification from 2D ultrasound images with the help of deep neural networks. Our object detection experiments applied to the Apical views suggest that it is possible to localize and identify multiple valves precisely.
Advances in three-dimensional imaging provide the ability to construct and analyze finite element (FE) models to evaluate the biomechanical behavior and function of atrioventricular valves. However, while obtaining patient-specific valve geometry is now possible, non-invasive measurement of patient-specific leaflet material properties remains nearly impossible. Both valve geometry and tissue properties play a significant role in governing valve dynamics, leading to the central question of whether clinically relevant insights can be attained from FE analysis of atrioventricular valves without precise knowledge of tissue properties. As such we investigated 1) the influence of tissue extensibility and 2) the effects of constitutive model parameters and leaflet thickness on simulated valve function and mechanics. We compared metrics of valve function (e.g., leaflet coaptation and regurgitant orifice area) and mechanics (e.g., stress and strain) across one normal and three regurgitant mitral valve (MV) models with common mechanisms of regurgitation (annular dilation, leaflet prolapse, leaflet tethering) of both moderate and severe degree. We developed a novel fully-automated approach to
Electric throttle valves represent a challenge for control design, as their dynamics involve strong nonlinearities, characterized by an asymmetric hysteresis. Carrying experiments on multiple valves, a large variability in the characteristics of each valve and erratic steady-state behaviors can also be noticed, impairing classical model-based control strategies. Nevertheless, local data-driven linear models can be obtained and simple proportional-integral (PI) controllers, tuned individually for each valve with the appropriate data set, provide good tracking performance. As these controllers cannot be transposed from one valve to another, a robust strategy and an adaptive controller (using identification in closed-loop and controller re-design) may be necessary to propose a general method. This work aims at promoting control education on a simple yet challenging process, going from frequency analysis and linear design to an adaptive control method implemented with an online recursive algorithm.
Immersed nonlinear elements are prevalent in biological systems that require a preferential flow direction, such as the venous and the lymphatic system. We investigate here a certain class of models where the fluid is driven by peristaltic pumping and the nonlinear elements are ideal valves that completely suppress backflow. This highly nonlinear system produces discontinuous solutions that are difficult to study. We show that as the density of valves increases, the pressure and flow are well-approximated by a continuum of valves which can be analytically treated, and we demonstrate through numeric simulation that the approximation works well even for intermediate valve densities. We find that the induced flow is linear in the peristaltic amplitude for small peristaltic forces and, in the case of sinusoidal peristalsis, is independent of pumping direction. Despite the continuum approximation used, the physical valve density is accounted for by modifying the resistance of the fluid appropriately. The suppression of backflow causes a net benefit in adding valves when the valve density is low, but once the density is high enough, valves predominately suppress forward flow, suggesting
This work performs a numerical study of electron transport through the fundamental logic gate in valleytronics - a valley valve consisting of two or increasing number of valley filters. Various typical effects on the transport are investigated, such as those due to interface scattering, long- and short- range impurity scattering, edge roughness, strain, inter-filter spacing, or increasing number of valley filters. For illustration, we consider the class of specific valves built from graphene quantum wire valley filters in single layer or bilayer graphene, with the filters subject to separate control of in-plane, transverse electric fields. The nearest-neighbor tight-binding model of graphene is used to formulate the corresponding transport problem, and the algorithm of recursive Green's function method is applied to solve for the corresponding transmission coefficient. In the case of two-filter valves, the result explicitly demonstrates the existence of a pronounced on-off contrast in electron transmission between the two configurations of valves, namely, one with identical and the other with opposite valley polarities in the two constituent filters. The contrast is shown to be enh
There are more than 300,000 heart valves implanted annually worldwide with about 50% of them being mechanical valves. The heart valve replacement is often a common treatment for severe valvular disease. However, valves may dysfunction leading to adverse hemodynamic conditions. The current computational study investigated the flow around a bileaflet mechanical heart valve at different leaflet dysfunction levels of 0%, 50%, and 100%, and documented the relevant flow characteristics such as vortical structures and turbulent shear stresses. Studying the flow characteristics through these valves during their normal operation and dysfunction can lead to better understanding of their performance, possibly improved designs, and help identify conditions that may increase the potential risk of blood cell damage. Results suggested that maximum flow velocities increased with dysfunction from 2.05 to 4.49 ms-1 which were accompanied by growing eddies and velocity fluctuations. These fluctuations led to higher turbulent shear stresses from 90 to 800 N.m-2 as dysfunctionality increased. These stress values exceeded the thresholds corresponding to elevated risk of hemolysis and platelet activation
Magnetoelectric coupling has been a trending research topic in both organic and inorganic materials and hybrids. The concept of controlling magnetism using an electric field is particularly appealing in energy efficient applications. In this spirit, ferroelectricity has been introduced to organic spin valves to manipulate the magneto transport, where the spin transport through the ferromagnet/organic spacer interfaces (spinterface) are under intensive study. The ferroelectric materials in the organic spin valves provide a knob to vary the interfacial energy alignment and the interfacial crystal structures, both are critical for the spin transport. In this review, we first go over the basic concepts of spin transport in organic spin valves. Then we introduce the recent efforts of controlling magnetoresistance of organic spin valves using ferroelectricity, where the ferroelectric material is either inserted as an interfacial layer or used as a spacer material. The realization of the ferroelectric control of magneto transport in organic spin valve, advances our understanding in the spin transport through the ferromagnet/organic interface and suggests more functionality of organic spin
We report the design and implementation of multiple Tesla type micro valves in the target delivery system of a reaction microscope (ReMi) to study gas phase structural dynamics of complex polyatomic molecules, when no delivery system currently exists that can deliver dense enough molecular jets of neutral complex molecules without ionizing or exciting the target. We show, the Tesla valves provide an efficient unidirectional flow of the cis-stilbene molecules into the ReMi. We demonstrate using a bubbler with Tesla valves an order-of-magnitude increase in the detected stilbene molecular ion signal following the strong-field tunnel ionization (SFTI), compared to conventional bubbler without any Tesla valves. Our results for the first time, opens the door for studying large, complex neutral molecules in the gas-phase with low vapour pressures in future ultrafast studies.
Magnetization switching due to a current-pulse in symmetric and asymmetric spin valves is studied theoretically within the macrospin model. The switching process and the corresponding switching parameters are shown to depend significantly on the pulse duration and also on the interplay of the torques due to spin transfer and external magnetic field. This interplay leads to peculiar features in the corresponding phase diagram. These features in standard spin valves, where the spin transfer torque stabilizes one of the magnetic configurations (either parallel or antiparallel) and destabilizes the opposite one, differ from those in nonstandard (asymmetric) spin valves, where both collinear configurations are stable for one current orientation and unstable for the opposite one. Following this we propose a scheme of ultrafast current-induced switching in nonstandard spin valves, based on a sequence of two current pulses.
With the development of additive manufacturing, 3D printing technology has become more common nowadays. We designed and 3D printed a cost-effective liquid fluid pressure measurement device that can convert liquid pressure to air pressure. Air pressure was measured by a low-cost manometer in this study. The device can measure the pressure drop across artificial aortic heart valves at different flow rate conditions. The main objective of this study is to utilize 3D printing technology to measure pressure loss through artificial aortic heart valves. From the measured pressure drop, the energy loss of flow that occurs through the artificial aortic heart valves can be estimated. In the experiment, both mechanical and biological (bovine skin) aortic heart valves have been tested at several different flow rate conditions. By doing so, we were able to measure energy loss at different flow rates through the valves to test which type and size of the heart valve have the lowest energy loss during operation. Lower energy loss of the blood through the valve should have a lower burden to a patients heart. This study provides an example of a new application of additive manufacturing in liquid flu
The degradation mechanisms of multilayer graphene spin valves are investigated. The spin injection signals in graphene spin valves have been reported to be linearly dependent on the drain bias voltage, which indicates that the spin polarization of injected spins in graphene is robust against the bias voltage. We present that the disappearance of this robustness is due to two different degradation mechanisms of the spin valves. Our findings indicate that the disappearance of the robustness is due to degradation rather than an intrinsic characteristic of graphene. Thus, the robustness can be greatly enhanced if degradation can be prevented.
Bicuspid aortic valve is the most common congenital heart defect, affecting 1-2% of the global population. Patients with bicuspid valves frequently develop dilation and aneurysms of the ascending aorta. Both hemodynamic and genetic factors are believed to contribute to dilation, yet the precise mechanism underlying this progression remains under debate. Controlled comparisons of hemodynamics in patients with different forms of bicuspid valve disease are challenging because of confounding factors, and simulations offer the opportunity for direct and systematic comparisons. Using fluid-structure interaction simulations, we simulate flows through multiple aortic valve models in a patient-specific geometry. The aortic geometry is based on a healthy patient with no known aortic or valvular disease, which allows us to isolate the hemodynamic consequences of changes to the valve alone. Four fully-passive, elastic model valves are studied: a tricuspid valve and bicuspid valves with fusion of the left- and right-, right- and non-, and non- and left-coronary cusps. The resulting tricuspid flow is relatively uniform, with little secondary or reverse flow, and little to no pressure gradient ac
Objective: Endobronchial Valves are a minimally invasive treatment for emphysema. After bronchoscopic placement the valves reduce the flow of air into targeted areas of the lung, causing collapse, and allowing the remainder of the lung to function more effectively. Approach: X-ray Velocimetry is a novel method that uses X-ray images taken during a breath to track lung motion, producing 3D maps of local ventilation. Healthy sheep received a CT scan and underwent X-ray Velocimetry imaging before and after endobronchial valves were placed in the lung. Sheep were imaged again when the endobronchial valves were removed after 14 days. Main results: X-ray Velocimetry enabled visualisation and quantification of a reduction of airflow to the areas downstream of the endobronchial valves, both in areas where collapse was and was not visible in CT. Changes to ventilation were also clearly visible in the remainder of the lungs. Significance: This preclinical study has shown X-ray Velocimetry is capable of detecting changes to ventilation caused by endobronchial valve placement, paving the way towards use in patients.
Bicuspid valves with crescent-shaped leaflets are found in lymphatic vessels and veins, where their primary function is to prevent reflux and ensure unidirectional flow toward the heart. These valves are passive, and their functionality emerges spontaneously from a complex interplay between the properties of the valve leaflets and the flow patterns developing within the vessel sinus region surrounding the valve. The main function of the valves is to limit retrograde flow, or reflux, but the optimal valve structure has not been well-characterized. Here we investigate numerically how the length of the leaflets affects the valve efficiency in preventing reflux. The valves are subjected to backward flow, akin to that imposed by gravity. We report the flux through the valve orifice as a function of key parameters: valve length, leaflet length, and leaflet rigidity. We monitor the transition in the flow regime - from reflux to complete flow blockage - by varying only the leaflet length. The transition threshold is found to depend strongly on the valve shape and stiffness. We captured these control parameters numerically to evaluate the ability of the valve to close and prevent reflux. Th
Spin valves are essential components in spintronic memory devices, whose conductance is modulated by controlling spin-polarized electron tunneling through the alignment of the magnetization in ferromagnetic elements. Whereas conventional spin valves unavoidably require at least two ferromagnetic elements, here we demonstrate a van der Waals spin valve based on a tunnel junction that comprises only one such ferromagnetic layer. Our devices combine a Fe3GeTe2 electrode acting as spin injector together with a paramagnetic tunnel barrier, formed by a CrBr3 multilayer operated above its Curie temperature. We show that these devices exhibit a conductance modulation with values comparable to that of conventional spin valves. A quantitative analysis of the magnetoconductance that accounts for the field-induced magnetization of CrBr3, and that includes the effect of exchange interaction, confirms that the spin valve effect originates from the paramagnetic response of the barrier, in the absence of spontaneous magnetization in CrBr3.
Aortic valve (AV) biomechanics play a critical role in maintaining normal cardiac function. Pathological variations, particularly in bicuspid aortic valves, alter leaflet loading, increase strain, and accelerate disease progression. Accurate patient-specific characterization of valve geometry and deformation is therefore essential for predicting disease progression and guiding durable repair. Current imaging and computational methods often fail to capture rapid valve motion and complex patient-specific features, limiting precise biomechanical assessment. To address these limitations, we developed an image registration framework coupled with the finite element method (FEM) to improve AV tracking and biomechanical evaluation. The valve geometries derived from 4D echocardiography and CT were used to simulate AV closure and generate intermediate deformation states. These FEM-generated states facilitated leaflet tracking, while image registration corrected misalignment between simulations and imaging data. In 20 patients, FEM-augmented registration improved accuracy by 40% compared with direct registration. This improvement enabled more reliable strain estimation by measuring leaflet de
Superheated steam is widely employed in various energy systems, particularly in power plants, chemical industries, and other applications where high-temperature and high-pressure steam is essential for efficient energy conversion and process control. In these systems, regulation valves are crucial components that control the flow of steam, adjusting its pressure and temperature to ensure safe and efficient operation. Accurate understanding and prediction of temperature variations within regulation valves are essential for optimizing their performance and improving the overall system efficiency. This study investigates the temperature variations of superheated steam flowing through a regulation valve using computational fluid dynamics (CFD) simulations combined with Proper Orthogonal Decomposition (POD) techniques. The analysis begins with an examination of the internal flow field parameters, including temperature and pressure, to understand the overall fluid dynamics within the valve. POD is applied to reduce the dimensionality of the CFD results. Singular Value Decomposition (SVD) is employed to extract the dominant modes that capture the key flow structures responsible for heat t