The Power of Computational Medicine

Improving patient outcomes is the ultimate goal of biomedical research and development. Medicine has evolved substantially over the past few decades, with countless life-saving discoveries and inventions coming about from experimental methods. However, experimental research techniques have their limitations. In vivo procedures can be invasive, expensive, and in the worst case scenario, adversely affect the patient. In vitro experiments eliminate potential harm to patients, but it’s difficult to adequately recapitulate biological environments in the lab. Because of this, in vitro results often don’t translate to patients.

Simulation is a complementary approach to in vivo and in vitro techniques. In silico studies are non-invasive and assume no risk to the patient. In addition, the relevant physiological environment can be incorporated into the simulation, enabling virtual in situ research. Combining simulation and experiment in the biomedical field is becoming increasingly common, and the results are promising. Simulation can aid in the design and evaluation of medical devices, increase our understanding of physiological processes and disease progression, and ultimately enhance patient outcomes.

CONVERGE is an advanced computational fluid dynamics (CFD) solver that offers a number of advantages for biomedical simulation, including simple case setup, a library of relevant physical models, and built-in post-processing and data analysis capabilities. Moreover, the Convergent Science Development and Applications teams are always available to work with you to ensure our software meets your specific needs.

Simulate Complex Physical Geometries

In biomedical CFD, the geometry for the simulation is often a complex biological structure obtained from a patient scan. Since each patient’s anatomy is unique, each geometry will be unique as well. CFD simulations require a computational mesh, which divides the domain into discrete cells in which the physics are solved. For many CFD solvers, you must manually create this mesh—a time-consuming and tedious process, especially for intricate biological geometries. CONVERGE removes the need to manually create a mesh through its autonomous meshing. At runtime, CONVERGE rapidly generates a high-quality mesh that preserves the complex topological features of the physical structure. For moving geometries, CONVERGE regenerates the mesh at each time-step to seamlessly accommodate the motion and capture the resulting flow features.

Obtain Results Quickly

Time is often a critical factor in the biomedical field. While CFD is impractical for emergency medicine, if you’re designing a potentially life-saving heart valve or investigating treatment options for aortic coarctation, you still want results as quickly as you can get them. At the same time, you don’t want to compromise on accuracy, since errors could have detrimental consequences. Adaptive Mesh Refinement (AMR) in CONVERGE can help you strike the right balance between speed and accuracy. AMR automatically adjusts the mesh throughout the simulation, adding cells when and where you need them to capture the important physics. This feature ensures that your simulation is as efficient as possible, while retaining a high level of accuracy. 

Capture the Interaction Between Fluids and Solids

Countless physiological processes involve solid structures moving or deforming in response to fluid flow. Accurately representing these phenomena is key for a realistic biomedical simulation. CONVERGE includes an array of modeling approaches to simulate the various kinds of fluid-structure interactions (FSI) that occur in the body. 

Rigid Objects

Mechanical devices such as blood pumps and artificial heart valves often contain rigid components that move according to imposed fluid forces and applied body forces. CONVERGE’s rigid-body FSI solves for the displacement of the object, and the movement of the object through the computational mesh is easily accommodated by our cut-cell grid generation. The FSI stability challenge of matched fluid and solid densities (e.g., in the case of a leaflet heart valve) is handled by an implicit coupling method.

Deformable Structures

For non-rigid solids that deform in response to fluid flow (e.g., artery walls), CONVERGE offers several options. You can prescribe the motion of the deforming solid using either an analytical function or a motion profile obtained from medical imaging. If you’re interested in predicting the deformation based on the applied fluid forces, CONVERGE couples with the Abaqus FEA solver for advanced 3D FSI deformation studies. These approaches are useful for gaining insight into cardiovascular dynamics, bladder voiding, and peristaltic and membrane pumps, among many other applications.

Predict Shear Stresses

Wall shear stress (WSS) has been shown to play a significant role in a variety of diseases, including preeclampsia, acquired von Willebrand syndrome, aneurysm rupture, and atherosclerosis. CFD can predict WSS with high fidelity, including for turbulent biological flows such as those associated with severe aortic stenosis. CONVERGE contains a wide selection of turbulence models, including Reynolds-Averaged Navier-Stokes and large eddy simulation. These options span the spectrum of speed and accuracy, so you can select the appropriate model to meet your needs.

Include Relevant Liquid and Gas Species

CONVERGE provides significant flexibility with the materials you can incorporate in your simulation, including relevant Newtonian and non-Newtonian biological fluids. In addition, CONVERGE’s Eulerian multi-phase modeling capabilities allow you to include as many liquid and gas species in your simulation as desired. You can take advantage of this feature to study a variety of scenarios, such as CO2 injection during surgery, cavitation in blood pumps, and condensation in continuous positive airway pressure (CPAP) machines. 

Apply Physiological Boundary Conditions

Blood vessel CFD simulations capture only a small portion of the larger circulatory system. To ensure physiological relevance, you need to account for the transient flowfield downstream of the vessel segment included in your simulation domain. CONVERGE features the Windkessel model to account for the compliance of downstream arteries. The Windkessel model is an electric circuit analogue that mimics the expansion/contraction and the resistance effect of main arteries during the systolic and diastolic processes. Employing this model allows you to get medically useful results from your CFD simulations.

Model Aerosolized Droplets

The COVID-19 pandemic sparked considerable interest in modeling aerosolized droplets. CONVERGE’s Lagrangian modeling is a computationally efficient method for simulating parcels. You can apply these models to study problems such as cough jets, the impact of masks and face shields, the spread of virus-laden droplets in a room, the efficacy of ventilation systems, and the flow of droplets through the nose during inhalation/exhalation, sneezing, or from nasal sprays.


University of Cambridge
La Heij, L., Gkantonas, S., and Mastorakos, E., “Personalized Displacement Ventilation as an Energy-Efficient Solution for Airborne Disease Transmission Control in Offices,” Frontiers in Mechanical Engineering, 9, 2023. DOI: 10.3389/fmech.2023.1148276

University of Wisconsin-Madison
Rutkowski, D.R., Roldán-Alzate, A., and Johnson, K.M., “Enhancement of Cerebrovascular 4D Flow MRI Velocity Fields Using Machine Learning and Computational Fluid Dynamics Simulation Data,” Scientific Reports, 11, 2021. DOI: 10.1038/s41598-021-89636-z

University of Wisconsin-Madison
Pewowaruk, R., Rutkowski, D., Hernando, D., Kumapayi, B.B., Bushman, W., and Roldán-Alzate, A., “A Pilot Study of Bladder Voiding With Real-Time MRI and Computational Fluid Dynamics,” PLOS ONE, 2020. DOI: 10.1371/journal.pone.0238404

University of Wisconsin-Madison
Pewowaruk, R., Lamers, L., and Roldán-Alzate, A., “Accelerated Estimation of Pulmonary Artery Stenosis Pressure Gradients With Distributed Lumped Parameter Modeling vs. 3D CFD With Instantaneous Adaptive Mesh Refinement: Experimental Validation in Swine,” Annals of Biomedical Engineering, 49, 2365–2376, 2021. DOI: 10.1007/s10439-021-02780-5

University of Wisconsin-Madison; Northwestern University Feinberg School of Medicine; Northwestern University; Ann & Robert H. Lurie Children’s Hospital of Chicago
Shahid, L., Rice, J., Berhane, H., Rigsby, C., Robinson, J., Griffin, L., Markl, M., and Roldán-Alzate, A., “Enhanced 4D Flow MRI-Based CFD With Adaptive Mesh Refinement for Flow Dynamics Assessment in Coarctation of the Aorta,” Annals of Biomedical Engineering, 50, 1001–1016, 2022. DOI: 10.1007/s10439-022-02980-7

Texas Tech University; The University of Tennessee, Knoxville; Huazhong University of Science and Technology
Ge, H., Zhao, P., Parameswaran, S., Feng, Y., and Cui, X., “Large-Eddy Simulation of a Two-Phase Cough Jet,” ILASS-Americas 32nd Annual Conference on Liquid Atomization and Spray Systems, Madison, WI, United States, May 22–25, 2022.

Texas Tech University; The University of Tennessee, Knoxville; Huazhong University of Science and Technology
Ge, H., Zhao, P., Parameswaran, S., Feng, Y., and Cui, X., “Large-Eddy Simulation of Face Shield Effects on an Emitter During a Cough Process,” ILASS-Americas 32nd Annual Conference on Liquid Atomization and Spray Systems, Madison, WI, United States, May 22–25, 2022.

Oslo Metropolitan University
Sundsdal, O.M., “CFD Analysis of Human Respiratory Events in Indoor Environments,” M.S. thesis, Oslo Metropolitan University, Oslo, Norway, 2022.

Texas Tech University; The University of Tennessee, Knoxville; Kyungpook National University; Huazhong University of Science and Technology
Ge, H., Zhao, P., Choi, S., Deng, T., Feng, Y., and Cui, X., “Effects of Face Shield on an Emitter During a Cough Process: A Large-Eddy Simulation Study,” Science of the Total Environment, 831, 2022. DOI: 10.1016/j.scitotenv.2022.154856

University of Cambridge
Trivedi, S., Gkantonas, S., Mesquita, L.C.C., Iavarone, S., de Oliveira, P.M., and Mastorakos, E., “Estimates of the Stochasticity of Droplet Dispersion by a Cough,” Physics of Fluids, 33(11), 2021. DOI: 10.1063/5.0070528

The Pennsylvania State University
Jhun, C.-S., Newswanger, R., Cysyk, J.P., Ponnaluri, S., Good, B., Manning, K.B., and Rosenberg, G., “Dynamics of Blood Flows in Aortic Stenosis: Mild, Moderate, and Severe,” ASAIO Journal, 67(6), 666-674, 2021. DOI: 10.1097/MAT.0000000000001296

University of Minnesota
Narayanan, S.R. and Yang, S., “Airborne Transmission of Virus-Laden Aerosols Inside a Music Classroom: Effects of Portable Purifiers and Aerosol Injection Rates, “Physics of Fluids, 33, 2021. DOI: 10.1063/5.0042474

Huazhong University of Science and Technology; Texas Tech University; Shanghai Jiao Tong University
Cui, X., Ge, H., Wu, W., Feng, Y., and Wang, J., “LES Study of the Respiratory Airflow Field in a Whole-Lung Airway Model Considering Steady Respiration,” Journal of the Brazilian Society of Mechanical Sciences and Engineering, 43, 2021. DOI: 10.1007/s40430-021-02871-3

Huazhong University of Science and Technology; Shanghai Jiao Tong University; Texas Tech University
Cui, X., Wu, W., and Ge, H., “Investigation of Airflow Field in the Upper Airway Under Unsteady Respiration Pattern Using Large Eddy Simulation Method,” Respiratory Physiology & Neurobiology, 279, 2020. DOI: 10.1016/j.resp.2020.103468

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