Computer Methods in Biomechanics and Biomedical Engineering

This study aimed to (1) develop an elasticity framework for the sprint force-velocity (F-V) relationship and (2) examine how maximal force (F_{0}), maximal velocity (v_{0}), and sprint distance modulate the four derived elasticity metrics, and (3) explore these elasticity metrics' interrelation. After modelling the F-V relationship differential equation, four elasticity metrics were defined as force elasticity (F_{e}), the elasticity of sprint time to F_{0}; velocity elasticity (v_{e}), the elasticity of sprint time to v_{0}; the force-velocity elasticity norm {(\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}=\sqrt{F_{e}^{2}+v_{e}^{2}}), capturing the combined sprint time sensitivity to proportional changes in F_{0} and v_{0}; and the force-velocity elasticity ratio {(\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=F_{e}{\div v}_{e}), indicating which variable dominates the sprint time response. Model simulations showed that F_{e} decreased with rising F_{0} and increased with rising v_{0}, while v_{e} showed the opposite pattern. With increasing sprint distance, F_{e} decreased and v_{e} increased. Given its negligible effect on sprint time, ignoring air resistance yields a conservation law (2F_{e}+v_{e}\equiv 1), indicating that a gain in one elasticity metric necessarily diminishes the other in a fixed proportion. This framework also identifies a valley distance (d_{valley}) at {\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=2, where {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}} is minimized (\sqrt{0.2}) and sprint time is least responsive to changes in F-V relationship variables. Empirical data confirmed that the two theoretical laws still hold approximately when air resistance is considered. By linking changes in F_{0} and v_{0} to sprint time across different distances, the elasticity framework provides a quantitative basis for estimating the theoretical sprint time response to documented changes in F-V relationship variables.

PurposeThis study aimed to investigate the role of neck muscle activity and neck damping characteristics in traumatic brain injury (TBI) mechanisms. MethodsWe used a previously validated head-neck finite element (FE) model that incorporates various components such as scalp, skull, cerebrospinal fluid, brain, muscles, ligaments, cervical vertebrae, and intervertebral discs. Impact scenarios included a Golf ball impact, NBDL linear acceleration, and Zhangs linear and rotational accelerations. Three muscle activation strategies (no-activation, low-to-medium, and high activation levels) and two neck damping levels by perturbing intervertebral disc properties (high: hyper-viscoelastic and low: hyper-elastic) strategies were examined. We employed Head Injury Criterion (HIC), Brain Injury Criterion (BrIC), and maximum principal strain (MPS) as TBI measures. ResultsIncreased neck muscle activation consistently reduced the values of all TBI measures in Golf ball impact (HIC: 4%-7%, BrIC: 11%-25%, and MPS (occipital): 27%-50%) and NBDL study (HIC: 64%-69%, BrIC: 3%-9%, and MPS (occipital): 6%-19%) simulations. In Zhangs study, TBI metric values decreased with the increased muscle activation from no-activation to low-to-medium (HIC: 74%-83%, BrIC: 27%-27%, and MPS (occipital): 60%-90%) and then drastically increased with further increases to the high activation level (HIC: 288%-507%, BrIC: 1%-25%, and MPS (occipital): 23%-305%). Neck damping changes from low to high decreased all values of TBI metrics, particularly in Zhangs study (up to 40% reductions). ConclusionOur results underscore the pivotal role of neck muscle activation and neck damping in TBI mitigation and holds promise to advance effective TBI prevention and protection strategies for diverse applications.

Muscle activation dynamics is usually described with a nonlinear differential equation, such that the activation occurs faster than deactivation. When a muscle excitation input switches rapidly between two values, this produces a "pumping" effect that raises the activation above the mean excitation input. This effect will favor rapid switching strategies when excitation is used in the optimization objective for human movement. The optimal strategy has infinitely fast switching, and is difficult to obtain with direct collocation methods. This problem can be eliminated by using activation, rather than excitation, in the optimization objective.

Our understanding of the process of formation of gyri (ridges) and sulci (furrows) in the cerebrum during development is moving beyond the role of neurons. Glial cells such as astrocytes, which are the most common cell type in the brain, are especially prominent under the gyri and have been shown to be essential for gyrification in ferrets. Their dysfunction has been linked to a host of neurodevelopmental diseases and disorders in humans, leading to abnormal folding patterns, hence, it is crucial to understand their role in the mechanics of folding. In this work, we propose two hypotheses of how astrocytes affect cortical folding. Our previous study demonstrated that astrocytes proliferate in the white matter (subcortex), and that inhibiting this process impairs gyrification. This leads to the pushing hypothesis, where astrocytes push up the cortex outwards, leading to formation of folds. On the other hand, ex vivo studies demonstrate areas of the cortex and subcortex that experience tension, due to the differential growth between materials in the brain tissue. This leads to the pulling hypothesis, where astrocytes experience tension from the surrounding tissue, leading to their proliferation, distribution of tensile stresses, and initiation of growth in those regions. Using the theory of finite growth, we implement these hypotheses via morphogenetic growth (pushing) and stress-driven (pulling) growth criteria. We find that morphological trends during development between the pushing and pulling effects are not dissimilar, with a comparable gyrification index. The stress distributions from both models also show common features, but the pulling effect shows tension in the subcortex, which matches trends observed in experiments. Therefore, it is more likely that the astrocytes affect gyrification by proliferating as a response to tensile cues and decrease the tension they experience, leading to deeper folds, rather than astrocytes independently proliferating under a gyri and then pushing the cortex up.

The control of shipborne disease outbreaks represents a vexing but entirely predictable challenge at the start of any pandemic. Passenger ships, with large numbers of people confined in close quarters, can serve as incubators of disease, seeding the pandemic across the globe as infected passengers return home. Short-term steps taken by local authorities can exacerbate this problem, creating humanitarian crises and worsening the scale of the outbreak. In this work, we have undertaken a model-based examination of the USS Theodore Roosevelt outbreak to understand the dynamics of COVID-19 spread aboard the aircraft carrier. We have used a series of counterfactual "what-if" analyses to better understand the options available to public health authorities in such situations. The models suggest that rapid mass evacuation and widespread surveillance testing can be effective in these settings. Our results lead to a set of generalizable recommendations for disease control that are broadly applicable to the current COVID-19 crisis as well as to future pandemics.

Acute subdural hematoma (ASDH) is a prevalent injury with high mortality and morbidity, often resulting from bridging vein (BV) disruption secondary to cortical relative motion. As a thin membrane enveloping the brain surface and anchoring BVs, the pia mater is hypothesized to play a critical mechanical role in cortical response and hence ASDH pathogenesis. Finite element (FE) head models are valuable tools to predict ASDH occurrence during impacts. However, the pia mater is often represented as an elastic material in existing FE head models, despite experimental evidence reporting its nonlinear mechanical behavior. In this study, both linear (Young's modulus of 11.5 MPa) and nonlinear (the stress-strain curve derived from pial tension tests) material models of the pia mater were implemented in one FE head model. The models were subjected to three experimental impact loadings, one of which was known to cause ASDH and two of which were not. Results demonstrated that, across all simulated impacts, the model with nonlinear pia mater properties predicted larger cortical displacements and BV responses than the linear model. For the impact with known ASDH occurrence, the predicted BV strain was 0.17 for the nonlinear model and 0.094 for the linear model, with only the former approaching the reported rupture strain range of the BV-superior sagittal sinus complex (0.29 {+/-} 0.13). These findings verified the mechanical importance of the pia mater in cortical responses and hence the prediction of ASDH, suggesting that conventional linear pia modeling might over-constrain cortical motion, leading to underestimation of BV strain and ASDH risk. The current study supported the adoption of experimentally derived nonlinear pia mater properties in FE head models to improve the reliability of ASDH prediction.

Cetaceans reduce the net cost of sustained swimming through intermittent locomotion, alternating active fluking with unpowered gliding. The energy balance of this strategy is central to understanding survival rates, population sustainability, and the effects of anthropogenic and environmental pressures. While active-phase energetics have been characterized extensively, the glide phase remains largely unexplored. Here we derive the optimal glide duration (Topt) and the maximum glide duration beyond which energy savings vanish (Tzero) for three odontocetes spanning a 20-fold range in body mass, using high-fidelity CAD models and wall-modeled large eddy simulations. We show analytically that speed retention at Topt and mass-specific peak energy savings are both fully determined by the active-to-passive drag ratio, propulsive efficiency, and swimming speed, independently of body morphometry and drag coefficient, and are therefore invariant across species at any given speed. These passive-phase optima extend the known size-independent active-phase invariants to the glide phase, towards a scale-independent energetic framework for burst-and-glide locomotion in small cetaceans.

The spring-loaded inverted pendulum (SLIP) model has effectively explained center of mass (CoM) and ground reaction force (GRF) dynamics during human gait despite its simplicity, describing both walking and running within the same mechanical principles. A recent study extended the explanatory capability of the SLIP model to joint dynamics by reproducing ankle joint dynamics during walking. However, during running, the model did not capture the empirical ankle torque profile, suggesting that such mechanical unification may not hold at the joint level. Because the previous model represented the body as a single point mass, it neglected leg inertia, which may become important during running as rapid motion generates substantial angular momentum. To address this limitation, we propose an extended two-mass model that separates the whole-body mass into the swing-leg and the remaining body mass, thereby explicitly incorporating swing-leg inertia into stance-leg joint dynamics. The swing leg is modeled using a linear spring and a torsional spring at the hip joint for its radial and rotational motion. Through inertial coupling, swing-leg dynamics influence the stance-leg ankle torque. Consequently, the proposed model reproduces the symmetric, single-peaked ankle torque profile observed experimentally while preserving the CoM and GRF of the previous model. These findings suggest that the discrepancy of the previous model during running may be explained by the omission of swing-leg inertia. By accounting for the gait-mode-dependent contribution of swing-leg inertia, the proposed model provides a unified mechanical framework for extending simple gait models from CoM-level behavior to joint dynamics.

The European New Car Assessment Programme (Euro NCAP), the Insurance Institute for Highway Safety (IIHS), and the U.S. National Highway Traffic Safety Administration (NHTSA) each publish safety ratings of new passenger vehicles based on crash test results and crash avoidance technology soon after they are introduced into the market. IIHS alone singles out vehicles for "Top Safety Pick". The Institute also periodically lists driver death rates of vehicles during their first few years of use, accompanied by assertions that larger, heavier passenger vehicles are safer. Median death rates by vehicle size in the Institutes data do not support the assertion. This study examines the association of vehicle weight to the risk of all deaths in fatal crashes where specific makes and models were involved, controlling statistically for the Institutes vehicle safety ratings as well as NHTSA ratings of full-frontal crash tests and rollover propensity, lane retention warnings, adaptive cruise control, and automatic braking. Increased weight is slightly related to a lower fatal risk in the 2014-2017 models but not the 2018-2019 models. Lane retention warnings and IIHSs higher ratings of crashworthiness are related to reduced death risk. Adaptive cruise control is not associated with fatal crash risk. Automatic emergency braking (AEB) technology rated "superior" is a criterion for an IIHS "Top Safety Pick" but it is correlated to higher fatal crash involvement of vehicles that have the technology as optional or standard equipment. IIHS tests of AEB systems are conducted only at low speeds. The statistical results are not definitive but suggest that a rating system based on modeling death risk prediction from more detailed data from various tests such as Euro NCAP tests of AEB systems could better inform consumer choice of vehicles.

The maize (Zea mays) stem is a biological structure that must both balance biotic and structural load bearing duties. These competing requirements are particularly relevant in the design of new bioenergy crops. With the right balance between structural and biological activities, it may be possible to design crops that are high-yielding and have digestible biomass. But increased stem digestibility is typically associated with a lower structural strength and higher propensity for lodging. This study investigates the hypothesis that geometric factors are much more influential in determining structural strength than tissue properties. To study these influences, both physical and in silico experiments were used. First, maize stems were tested in three-point bending. Specimen-specific finite element models were created based on x-ray computed tomography scans. Models were validated by comparison with in vitro data. As hypothesized, geometry was found to have a much stronger influence on structural stability than material properties. This information reinforces the notion that deficiencies in tissue strength could be offset by manipulation of stalk morphology, thus allowing the creation of stalks with are both resilient and digestible. HighlightThis study utilized physical and in silico experiments to confirm that geometric parameters are far more influential in determining stalk strength than mechanical tissue stiffnesses.

End-of-August updates for Covid-19 infection case predictions for 10 US States (NY, WA, GA, IL, MN, FL, OH, MI, CA, and NC) are compared to actual data. Several states that experienced significant summer surges gained control of accelerating infection spread during August. The US as a whole and the 10 States investigated continue to follow periods of linear infection growth that defines a boundary separating accelerated infection growth and infection decay. August 31 predictions (initiated July 27, 2020) for four States (NY, WA, MI and MN) are within 10% of actual data. Predictions for four other States (GA, IL, CA, and OH) agree between 10 and 20% of actual data. Predictions for two States (FL and NC) are greater than 20% different from actual data. Systematic differences between predictions and actual data are related to the impact of the June-July summer surge, and human behavior reactions (ie, increased face mask usage and distancing) to accelerated infection growth. Outdoor temperature effects and school re-opening effects are not apparent nor expected for August. Human behavior parameters (Social Distance Index, SDI, and disease transmission efficiency, G, parameters) are adjusted to mirror August data. Comparisons of actual versus predicted daily new infection cases display the complexity of SARS-CoV-2 transmission.

The corpus callosum is the largest white matter structure connecting the two cerebral hemispheres and is anatomically divided into three major subregions along the anteroposterior axis: the genu, midbody, and splenium. The splenium is frequently affected in traumatic head impacts, yet the biomechanical basis for this selective vulnerability remains poorly understood. Clinical studies have long hypothesized that the falx cerebri contributes to the splenial susceptibility because of its close anatomical relationship with the posterior corpus callosum, although direct verification is lacking. To address this, a high-resolution finite element head model with explicit representations of the genu, midbody, and splenium was employed. Two model variants, differing only in the presence or absence of an anatomically and mechanically detailed falx, were used to simulate ten head impacts covering a range of loading directions and severities. Peak strain, strain rate, and shear stress were quantified in each corpus callosum subregion and compared using linear mixed-effects models. The results showed that inclusion of the falx altered the regional distribution of mechanical responses within the corpus callosum. Across the simulated impacts, the splenium consistently exhibited greater strain, strain rate, and shear stress than the genu and midbody when the falx was present. In contrast, these preferentially larger splenial deformation were not consistently observed when the falx was absent. Statistical analyses demonstrated significant region-dependent effects of the falx, with falx-induced increases in strain, strain rate, and shear stress being significantly greater in the splenium than in the genu and midbody (p < 0.05). These findings verified the hypothesis that the falx selectively amplified mechanical loading within the splenium, thereby contributing to its heightened vulnerability to injury. This work provides a plausible biomechanical explanation for the frequent involvement of the splenium in brain trauma patients and highlights the heterogeneous influence of the falx on mechanical responses across corpus callosum subregions.

IntroductionCoronavirus Disease 2019 (COVID-19) infection has been characterized by rapid spread and unusually large case clusters. It is important to have an estimate of the current state of COVID-19 epidemic in the U.S. to help develop informed public health strategies. MethodsWe estimated the potential scale of the COVID-19 epidemic (as of 03/01/2020) in the U.S. from cases imported directly from Wuhan area. We used simulations based on transmission dynamics parameters estimated from previous studies and air traffic data from Wuhan to the U.S and deliberately built our model based on conservative assumptions. Detection and quarantine of individual COVID-19 cases in the U.S before 03/01/2020 were also taken into account. A SEIR model was used to simulate the growth of the number of infected individuals in Wuhan area and in the U.S. ResultsWith the most likely model, we estimated that there would be 9,484 infected cases (90%CI 2,054-24,241) as of 03/01/2020 if no successful intervention procedure had been taken to reduce the transmissibility in unidentified cases. Assuming current preventive procedures have reduced 25% of the transmissibility in unidentified cases, the number of infected cases would be 1,043 (90%CI 107-2,474). ConclusionOur research indicates that, as of 03/01/2020., it is likely that there are already thousands of individuals in the US infected with SARS-CoV-2. Our model is dynamic and is available to the research community to further evaluate as the situation becomes clearer.

We introduce an innovative method for the investigation of human gait, which is based on the visualisation of the vertical component of the movement of the centre of mass during walking or running, in the space of the coordinates position, velocity, and acceleration of the centre of mass. Collected data has been numerically approximated by the best fitting curve for a non-linear model. The resulting equation for the best fitting plane or curve in this space is a differential equation of second order. The model that we suggest is a Duffing equation with coefficients that depend on the height of a walker or runner and on the angular frequency of the oscillation. Statistics about the distribution of the Duffing stiffness depending on the speed is presented. 1 Author SummaryWe study the human gait modelled by the movement of the centre of mass of the test person. This is an example of a biological process which can be considered as a periodical dynamic system. Roughly, this movement behaves in a similar way to a vibrating mass suspended on a spring, but it is more complex. The vertical component of the movement during walking or running can be visualised as an oscillogram: a graph of the position as a function of time. We suggest a visualisation of the data in 3D space, where the coordinates describe position, velocity, and acceleration. Our new visualisation method allows us to model the movement of a persons centre of mass by a nonlinear differential equation. The resulting curve for an ideal spring-mass movement, without viscosity or external force, is an ellipse in the suggested 3D space. The shape of the data curve shows at which position an additional force was applied, or the movement slowed down. Some deviations are common for all test persons and others are different. In the future we plan to investigate the reasons for these deviations, such as different running techniques or the presence of injuries.

Concussion can result from various events in everyday life, including falls, sports collisions, and motor vehicle accidents, which could lead to the disruption of neuronal cell membranes and axonal stretching, leading to a neuro-metabolic cascade of molecular changes in the brain. There is currently no agreement on which computational method can assess such low-level injuries. This paper demonstrates for the first time that the Peak Virtual Power (PVP), based on the Clausius-Duhem inequality, assuming that the injury is represented by the irreversible work in a human body, could be a candidate to capture brain distortion related to concussion. The work is based on the evaluation of the PVP via reconstruction of three NFL helmet-to-helmet impacts by means of finite element analysis, using validated Biocore helmet models fitted with calibrated Hybrid III headforms against linear and angular acceleration impact corridors, which were defined as realistic impact conditions for each collision scenario. Once the exact impact parameters were defined, the Hybrid III headform was replaced with a validated THUMS 4.02 human head model in which the PVP was computed for each head at the corpus callosum and midbrain locations. The results indicate that mild and severe concussions could be prevented for lateral collisions and frontal impacts with PVP values lower than 0.928mW and 9.405mW, respectively, and no concussion would happen in the head vertical impact direction for a PVP value of less than 1.184mW. This innovative method proposes a new paradigm to improve helmet designs, assess sports injuries and improve peoples wellbeing. HighlightsO_LIPeak Virtual Power method can capture brain distortion related to concussion C_LIO_LIConcussion is extracted from corpus callosum and midbrain locations of THUMS4.02 C_LIO_LIPeak power in midbrain less than 1.184mW for a vertical impact leads to no concussion C_LIO_LIPeak power in midbrain more than 0.928mW for a lateral impact leads to concussion C_LIO_LIPeak power in midbrain more than 9.405mW for a front impact leads to concussion C_LI

Despite its ubiquity in natural flows, the effects of turbulence on fish locomotion and behavior remain poorly understood. The prevailing hypothesis is that these effects depend on the spatial and temporal scales of the turbulence relative to the fishs size and swimming speed. But in conventional facilities, turbulence usually increases with mean flow, which forces higher swimming speeds and can leave these relative scales unchanged. We therefore present a novel experimental facility that leverages a jet array to decouple the turbulence from the mean flow and systematically control its scales. This approach allows the ratio of turbulent to fish inertial scales to be varied over an order of magnitude, providing a controlled framework for quantifying fish-turbulence interactions. The facility also supports experiments probing strategies fish may use to cope with turbulence, including collective behaviors. Insights from this work have broader implications for ecological studies and engineering applications, including the design of effective fishways and bio-inspired underwater vehicles.

Understanding how muscles use energy is essential for elucidating the role of skeletal muscle in animal locomotion. Yet, experimental measures of in vivo muscle energetics are challenging to obtain, so physiologically-based muscle models are often used to estimate energy use. These predictions of individual muscle energy expenditure are not often compared to indirect whole body measures of energetic cost. Here, we examined and illustrated the capability of physiologically-based muscle models to predict in vivo measures of energy use. To improve model predictions and ensure a physiological basis for model parameters, we refined our model to include data from isolated muscle experiments. Simulations were performed to capture three different experimental protocols, which involved varying contraction frequency, duty cycle, and muscle fascicle length. Our results demonstrated that these models are able capture the general features of whole body energetics across contractile conditions, but tended to under predict the magnitude of energetic cost. Our analysis revealed that when predicting in vivo energetic rates across contractile conditions, the model was most sensitive to the force-velocity parameters and the data informing the energetic rates when predicting in vivo energetic rates across contractile conditions. This work highlights it is the mechanics of skeletal muscle contraction that govern muscle energy use.

Understanding the vertical ground reaction force (vGRF) profile offers important insight into how humans regulate mechanical work during walking. Although the characteristic double-hump vGRF pattern is well documented, the mechanical factors underlying asymmetry in peak amplitudes and midstance trough timing remain unclear. Using a simple powered walking model and an inverted pendulum simulation with constant hip torque, we examined how step-transition work--collision and push-off--shapes the vGRF trajectory. We further compared these predictions to empirical data spanning walking speeds from 0.8-1.4 m. s-1. The simple walking model predicted symmetric vGRF profiles across speeds because collision and push-off impulses were equal, resulting in passive single-support motion. In contrast, adding hip torque within the pendular model produced stance-phase asymmetries, shifting the vGRF trough earlier when torque added energy and later when torque dissipated energy. Empirical analysis revealed that collision and push-off impulses were generally unequal except at one speed, producing asymmetric vGRF peaks. At low speeds, push-off exceeded collision; at high speeds, the reverse occurred, consistent with a need for compensatory single-support positive work. These mechanical imbalances predicted systematic shifts in trough timing toward the dominant impulse. Therefore, we propose the Vertical GRF Trough Timing Index (vGRF-TTI), combined with collision and push-off peak amplitudes, as a clinically meaningful outcome capturing the balance of step-transition work. Earlier troughs with elevated collision peaks indicate impaired push-off or constrained gait conditions, whereas later troughs with larger push-off peaks reflect compensatory or enhanced propulsion. These metrics provide sensitive, mechanism-based indicators of gait efficiency and neuromotor control.

A popular way to model contact interactions in musculoskeletal simulations uses Hertz theory applied to contact spheres, with Hunt Crossley based dissipation. Suitable contact parameters for dynamic simulations will be highly dependent on the morphology, scale, materials, and movement in question. Inappropriate parameter choices can manifest in unpredictable ways during simulations, potentially resulting in misinterpretations or failed simulations. Here, I demonstrate that both the plane strain modulus and the dissipation parameters are not scale invariant. I derive equations to scale the contact parameters in dimensionless form, which allows accounting for differences in body size, number of legs, contact sphere radius, and number of spheres per foot. As a demonstration of this scaling approach, I scale the contact parameters of a 62 kg human to a 500 kg human, a mouse (0.02 kg), an emu (37.8 kg), a horse (545 kg), and a giraffe (1190 kg), and demonstrate that geometrically and dynamically similar contact behaviour is achieved in all cases. The scaling approach presented here can be used to scale parameters known to work for one model to a completely different model, which is particularly useful in studies that simulate the effects of allometric scaling. I also provide equations to estimate suitable contact parameters for a model directly, without using a different model as a starting point. The limitations of Hertz Hunt Crossley contact models in biomechanical simulations are discussed. Lastly, I derive dimensionless expressions and scaling guidelines for the smoothed contact force implementation "SmoothSphereHalfSpaceForce" in the popular biomechanical simulator OpenSim.

Thrombosis refers to the formation of a thrombus, or a blood clot, within the body, which can occur either partially or completely. It serves as a crucial indicator of the severity of a patients medical condition, with the location and characteristics of thrombosis dictating its clinical implications. Hence, accurate diagnosis and effective management of thrombosis are paramount. In our current investigation, we incorporate the porous attributes of a thrombus using the Theory of Porous Media. This involves dividing the aggregate into solid, liquid, and nutrient phases and utilising volume fractions to capture microstructural details. Fluid flow through the porous media is modelled using a modified Darcy-Brinkman type equation, with interaction terms within balance equations facilitating the modelling of the mass exchange and other phase interactions. The shorter time scales are neglected. We present a comprehensive framework of equations and assumptions governing the behaviour of a strongly coupled multiphasic porous medium problem. Additionally, we introduce scenarios involving type B Aortic Dissection and false lumen geometries, providing a detailed outline of the problem setup. Thereafter, we present the potential of the model for thrombi growth. The simulation results are compared with velocity plots aligning with Magnetic Resonance Imaging data for three distinct cases with varying entry and exit tear sizes. Consequently, our proposed model offers a promising and reasonable approach for numerically simulating thrombosis and gaining insights into the underlying growth mechanics.