Parametric Geometry Model Research Articles

Proof-of-principle of parametric stellarator neutronics modeling using Serpent2

This contribution presents neutron transport studies for the 5-period helical-axis advanced stellarator stellarator using the Serpent2 code. These studies utilize a parametric geometry model, enabling scans in neutronics modeling by varying the thickness of the reactor layers. For example, the tritium breeding ratio (TBR) can be determined by exploring various blanket material options and thicknesses to identify the threshold configuration that meets the TBR design criterion of 1.15. We found out that with the helium-cooled pebble ped candidate option, the TBR criterion is met with a breeding zone thickness of 26 cm, while with the dual-coolant lithium lead the threshold is exceeded at a thickness of 46 cm. Furthermore, the geometry includes non-planar field coils, allowing to study the fast neutron flux in these superconducting coils with a technological limit of 1×1091/cm2s . It is shown that the neutron fast flux is not constant at the coils, necessitating a neutron transport simulation to determine the distribution of the fast-flux at the coils. We show that the peak fast flux can be more than a factor of 2 higher than the average flux, and that the peak flux location rotates helically.

Enabling cross-morphological performance comparison: A case study in heat management design

Cross-morphological performance comparisons in mechanical engineering design may well resemble comparisons of apples and oranges. They are meaningful only if pertinent properties shared across compared morphologies (so-calledtertia comparationis) are identified, and equity with regard to these properties is established. This article demonstrates such an approach with the use of parametric geometry modeling, optimization, and additive manufacturing, enabling a thermal performance comparison of different heat sink morphologies, using both steady-state numerical simulation and experimental evaluation, by establishing equity across the compared heat sinks in terms of (thermal) mass. Limitations in additive manufacturing precision, as well as inconsistencies between numerical simulation and experimental evaluation results, were encountered in this case study. Likely resulting from the heat sinks’ thermal properties on the additive manufacturing process and the simulation environment’s disproportionate reliance on convection surface area, these limitations and inconsistencies will likely diminish as additive manufacturing and numerical simulation technologies improve. The cross-morphological comparison approach presented here is shown to be viable in principle and may inform decision-making in applied mechanical engineering design research and practice.

Reverse Engineering-Inspired Parametric 3D Geometry Model of Marine Propeller

Abstract In this study, an effective parametric 3D geometry model of a propeller was established with the aid of reverse engineering. The goal is to reduce the free parameters while automating the modelling of the propeller. The process of building the parametric model begins by generating an initial point cloud by defining the feature matrix associated with the propeller blade profile shape. Subsequently, the initial point cloud is deformed and refined by the deformation feature matrix and resampling. Finally, a 3D geometry model of the propeller is generated by surface reconstruction. The model can be built automatically by interactively modifying the feature matrices. Two numerical analyses illustrate the performance of the parametric 3D geometry model. Specifically, two propellers are constructed using the proposed model to estimate the shape error between the reconstructed propellers and the original offset of the propellers. These propellers are selected as research objects to determine the hydrodynamic performance error between the propeller constructed by the proposed model and a benchmark propeller. According to the results of the numerical study, the parametric 3D geometry model can precisely reconstruct the aforementioned geometry within a valid error range. The hydrodynamic error analysis demonstrates that the geometric inaccuracy from the reconstructed model has less impact on the propeller performance. This indicates that the model described in this study is generalised and robust. Moreover, some uncommon propeller CAD models were generated in batches using the parametric 3D geometry model.

Surrogate-assisted optimization for anti-ship missile body configuration considering high-velocity water touching

As a crucial weapon in the sea battle, anti-ship missiles generally employ a sea-skimming penetration strategy to reduce the probability of being detected by the target radar, which greatly increases the risk of touching water caused by sensor errors or random sea conditions. To alleviate the large impact load by high-velocity water touching, a novel anti-ship missile body configuration is proposed in this paper, which is inspired by the idea of hydroplaning. A parametric geometry model is first developed to modify the configuration of the anti-ship missile body. Subsequently, a structured arbitrary Lagrange-Eulerian based Fluid-Structure Interaction (FSI) model is established to analyze the kinematics parameters of the missile body during the hydroplaning process. A missile body configuration optimization problem is then formulated to minimize the impact load considering several constraints, e.g., horizontal velocity loss, pitch angle after touching water, and inside capacity for payload. Due to the time-consuming FSI simulation, a Kriging-assisted constrained differential evolution method is utilized to optimize the missile body configuration for reducing the impact load. During the optimization process, radial basis function and Kriging are combined with evolutionary operators to lead the search to the vicinity of the optimum rapidly. The result shows that the proposed missile body configuration can reduce the impact load by 18.8% compared with the ordinary configuration. Additionally, the optimized configuration can further yield a 17.4% impact load decrease subject to all the constraints and avoid structural damage by the high-velocity water touching, which demonstrates the effectiveness and practicability of the proposed anti-ship missile body configuration and corresponding optimization framework for reducing the impact load.

Variable-Speed Propeller Turbine for Small Hydropower Applications

Standard technical solutions are not cost-effective for many small hydropower sites. This study aims to demonstrate the workflow for the tailor-made variable-speed axial propeller turbine and provide proof of this concept. The turbine is designed to meet the site’s specific space limitations and operating range needs. The runner shape is adjusted to the variable-speed operation and defined hydraulic profile using a parametric geometry model and CFD-based optimization. The variable-speed propeller turbine shows excellent flow control while keeping the mechanical design simple. The tailor-made approach minimizes construction costs using existing structures and is highly suitable for mini-hydropower applications. The prototype—an atypical turbine designed for highly restricted space and installed on-site—serves as proof of the concept. The findings on the design of axial variable-speed turbines are presented.

RANS-Based Aeroacoustic Global Sensitivity Study and Optimization of UAV Propellers

Modeling of Unmanned Aerial Vehicles (UAV) propellers in a global, multidisciplinary aeroacoustic optimization was investigated. The modeling consists of three aspects: geometry, aerodynamics, and aeroacoustics. Firstly, a parametric geometry model was established using chord, twist, and sweep distributions along the radius, defined by splines to ensure smoothness. Additionally, airfoil parameters including maximum camber and its position, as well as the position of maximum thickness, were added. Secondly, a blade geometry-resolved aerodynamic model based on steady RANS was established. A two-equation SST turbulence model was used for compressible flow with periodic boundary conditions. Thirdly, an aeroacoustic model for far-field tonal noise calculation was defined, based on the Ffowcs Williams and Hawkings analogy and a RANS solution. A global sensitivity analysis was performed to establish the importance of individual design variables. Consequently, surrogate modeling-based optimization strategy was devised to efficiently establish Pareto front of propeller geometries in multi-objective aeroacoustic optimization.

A parametric geometry model of the aortic valve for subject-specific blood flow simulations using a resistive approach

Cardiac valves simulation is one of the most complex tasks in cardiovascular modeling. Fluid–structure interaction is not only highly computationally demanding but also requires knowledge of the mechanical properties of the tissue. Therefore, an alternative is to include valves as resistive flow obstacles, prescribing the geometry (and its possible changes) in a simple way, but, at the same time, with a geometry complex enough to reproduce both healthy and pathological configurations. In this work, we present a generalized parametric model of the aortic valve to obtain patient-specific geometries that can be included into blood flow simulations using a resistive immersed implicit surface (RIIS) approach. Numerical tests are presented for geometry generation and flow simulations in aortic stenosis patients whose parameters are extracted from ECG-gated CT images.

VALIDATION OF PARAMETRIC OPENDRIVE ROAD SPACE MODELS

Abstract. The standard OpenDRIVE is widely used for exchanging road space models in order to simulate the traffic of a city or individual driving situations. For modeling continuous road courses at lane level, OpenDRIVE utilizes its own parametric geometry model. However, violations of continuity requirements due to geometric leaps or kinks can cause the vehicle dynamics simulation to fail when testing vehicle components. But also defective lane predecessor and successor relations can result in an OpenDRIVE dataset not being usable as a reference map for vehicle navigation. Since these geometric, topological, and semantic constraints go beyond the rules encoded in the schema, this article presents a framework and a first implementation for validating OpenDRIVE datasets. As the lane widths are defined parametrically relative to the reference line of the respective road, lane connectivities at road transitions are evaluated using explicit geometries derived from the parametric geometry representations. Moreover, a derived CityGML representation enables a visual inspection of the parametric models to identify unexpected but visible defects. The implemented framework is applied to examine a total of 99 OpenDRIVE datasets, where significant lane gaps were detected in the explicit representation for about 20% of the datasets.

A parametric head geometry model accounting for variation among adolescent and young adult populations

Background and objectiveModeling the size and shape of human skull and scalp is essential for head injury assessment, design of helmets and head-borne equipment, and many other safety applications. Finite element (FE) head models are important tools to assess injury risks and design personal protective equipment. However, current FE head models are mainly developed based on the midsize male, failing to account for the significant morphological variation that exists in the skull and brain. The objective of this study was to develop a statistical head geometry model that accounts for size and shape variations among the adolescent and young adult population. MethodsTo represent subject-specific geometry using a homologous mesh, threshold-based segmentation of head CT scans of 101 subjects between 14 and 25 years of age was performed, followed by landmarking, mesh morphing, and projection. Skull and scalp statistical geometry models were then developed as functions of age, sex, stature, BMI, head length, head breadth, and tragion-to-top of head using generalized Procrustes analysis (GPA), principal component analysis (PCA) and multivariate regression analysis. ResultsThe statistical geometry models account for a high percentage of morphological variations in scalp geometry (R2=0.63), outer skull geometry (R2=0.66), inner skull geometry (R2=0.55), and skull thickness (error < 1 mm) ConclusionsSkull and scalp statistical geometry models accounts for size and shape variations among the adolescent and young adult population were developed as functions of subject covariates. These models may serve as the geometric basis to develop individualized head FE models for injury assessment and design of head-borne equipment.

Digital design and stability simulation for large underground powerhouse caverns with parametric model based on BIM-based framework

Large infrastructures involving underground engineering like the underground powerhouse caverns constitute multi-medium, complicated and interaction systems, which require geotechnical data management, parametric model construction, optimal design alternatives, and real-time safety assessment. However, even though the data needed for numerical analysis is recorded in the Building Information Modeling (BIM) parametric models, the transformation of geometric characteristics between BIM and numerical models is cumbersome. Therefore, an automatic numerical simulation analysis framework was proposed, which can not only convert 3D parametric structural geometry model by indirect method, but also realize automatic pre-treatment and analysis, such as mechanical properties definition, boundary conditions assignment and mesh generation. In this study, the digital model of underground powerhouse caverns accompanying with cavern support system could be constructed automatically via secondary development on CATIA software. Reorganized borehole logs at geological profiles accompanying with topographic-geologic map are also used to define the 3D subsoil model. Python codes are programmed for pre-treatment of numerical model to enhance the calculation efficiency and alleviate the manual interventions by linking differ-format data files. Furthermore, a case study of Suki Kinari underground powerhouse caverns was exemplified the advantages of this framework in terms of modeling and pre-treatment efficiency, and error-free geometric information translation. The proposed framework provides a fundamental process for automatic design-to-analysis, hence mitigates user intervention and error-free structural calculation for design-making.

Geometry scaling technique and application to aerodynamic redesign of multi-stage transonic axial-flow compressors

Geometry scaling technique, as one of the essential steps in aerodynamic redesign of multi-stage compressor, directly determines whether the new scaled geometry meets the required performance or not. It is also one of the effective measures in unsteady flow simulation of multi-stage compressor to reduce greatly the computational cost by scaling the computational domain from full-annulus passages to partial-annulus passages. The common critical issue arisen from both practices is the geometry dissimilarity in which some certain difference exists between the original and scaled geometries due to a diversity of redesign requirements or model simplifications. However, the extent of how the geometry dissimilarity influences the aerodynamic performance of multi-stage transonic compressor is unclear up to now. Particularly, how to keep the aerodynamic performance similarity in the case of geometry dissimilarity has not been explored yet. Here we propose a geometry scaling technique in which 3D parametric geometry modeling and 1D mean-line analysis are combined to define a series of key redesign criteria in order to keep as minor as possible variations in the aerodynamic performance of multi-stage compressor. The proposed technique is applied to redesign a 3.5 stage transonic axial-flow compressor with two geometry scaling strategies, i.e., adjustable blade/vane numbers and inlet guide vane (IGV)-rotor-stator axial spacing. The key aerodynamic parameters determined by the key redesign criteria are then quantified to verify the feasibility and accuracy of the proposed technique by computational fluid dynamics (CFD) simulations. The results show that by keeping the similarity of key redesign criteria, that is, blade solidity, stagger angle, inlet blade angle, outlet blade angle and thickness to chord distribution, the similarity of key aerodynamic parameters (incidence angle, deviation angle, loss coefficient and aerodynamic blockage) and thus of overall aerodynamic performance (mass flow rate, pressure ratio and efficiency) can be generally guaranteed. The variations of aerodynamic performance in the case of geometry dissimilarity with different blade/vane numbers and IGV-rotor-stator axial spacing are generally within 1%. Compared against the similarity of the other key aerodynamic parameters, a certain dissimilarity of aerodynamic blockage is observed, impacting slightly on the mass flow rate and thus stall margin. The present work is of effective assistance to improve the redesign methodology for multi-stage axial-flow compressors.

Design and Optimization of Lightweight and HSD Excavator Bucket with Uncertain Load

Excavators are used primarily to excavate below the natural surface of the ground on which the machine rests and load it into trucks or tractor. Due to severe working conditions, excavator parts are subjected to high loads. The excavator mechanism must work reliably under unpredictable working conditions. Thus, it is very much necessary for the designers to provide not only a equipment of maximum reliability but also of minimum weight and cost, keeping design. safe under all loading conditions weight and cost, keeping design safe under all loading conditions. It can be concluded that, force analysis and strength analysis is an important step in the design of excavator parts. This paper presents a methodology for lightweight and high-strength design of an excavator bucket under uncertain loading. Uncertain loads are obtained by using the Monte Carlo simulation based on the existing soil-bucket interaction model in which the soil parameters are variable. And the well-known 3-sigma methodology is used for the quantification of the uncertain loads. Excavator bucket modelling is finished by using ANSYS Parameter Design Language (APDL). A multi-objective optimization model aiming to decrease the maximum von Mises stress and to reduce the weight of the bucket is established on the foundations of the uncertain load and the parametric geometry model. The structural shape and topology of the bucket are then designed by using the mixed variable genetic algorithm to solve the established optimization problem. The results show that the presented method can be effectively and efficiently applied for the optimization design of the excavator bucket and that the optimized bucket signifies obvious decreases in the weight and the stress compared with the initial reference model. The proposed methodology for structure optimization design considering uncertain loads not only provides the technical means for the design and development of high-performance bucket but also lays a preliminary theoretical foundation for the optimization design integrated machine-environment interaction.

Parametric geometry model design of a wingsuit

PurposeThis paper aims to introduce a process chain spanning from scanned data to computer-aided engineering and further required simulations up to the subsequent production. This approach has the potential to reduce production costs and accelerate the procedure.Design/methodology/approachA parametric computer-aided design (CAD) model of the flyer wearing a wingsuit is created enabling easy changes in its posture and the wingsuit geometry. The objective is to track the influence of geometry changes in a timely manner for following simulation scenarios.FindingsAt the final stage, the two-dimensional (2D) pattern cuts were derived from the developed three-dimensional (3D) wingsuit, and the results were compared with the conventional ones used in the first stages of the wingsuit development.Originality/valueProposing a virtual development process chain is challenging; apart from the fact that the CAD construction of a wingsuit flyer – in itself posing a complicated task – is required at a very early stage of the procedure.

Parametric design and optimization of SWATH for reduced resistance based on evolutionary algorithm

This study develops a numerical simulation-based optimization procedure of Small Waterplane Area Twin Hull (SWATH) design. The procedure integrates the parametric geometry model, numerical analysis of total resistance, response surface methodology (RSM) model, and evolutionary optimization (EVOL) algorithm. The parametric hull form model is constructed based on general characteristic curves and several parameters to achieve model fully automated geometry variation quickly in the process. The resistance numerical simulation is performed and the results of resistance forces are taken as the optimization objective. The RSM model is built by stepwise selection method to accelerate the optimization process. The EVOL algorithm is applied to solve the optimization problem. A 32 m SWATH has been taken as an example to present the efficiency of the optimization. The optimization result shows that the optimized hull form has lower resistance than the original hull. The effect of the design parameters on the total resistance is discussed, which offers a few suggestions for the improvement of SWATH.

Low-boom low-drag optimization in a multidisciplinary design analysis optimization environment

This paper introduces a multidisciplinary design analysis and optimization environment called GENUS. The GENUS aircraft design environment's key features are that it is modular, expandable, flexible, independent, and sustainable. This paper discusses the application of this environment to the design of supersonic business jets (SSBJs). SSBJs are regarded as the pioneers of the next generation of supersonic airliners. Methodologies appropriate to SSBJs are developed in the GENUS environment. The Mach plane cross-sectional area is calculated based on the parametric geometry model. PANAIR is integrated to perform automated aerodynamic analysis. The drag coefficient is corrected by the Harris wave drag calculation and form factor method. The sonic boom intensity is predicted by the wave form parameter method, which is validated by PCBoom. The Cranfield E-5 SSBJ is chosen as a baseline configuration. Low-boom and low-drag optimization are carried out based on this configuration. Through the optimization, the sonic boom intensity is mitigated by 71.36% and the drag decreases by 20.65%.

Coupled simulation of thermally active building systems to support a digital twin

Based on 2050 Swiss and European Union targets, significant energy performance improvements will be required for new and renovated buildings. However, the construction industry has a poor record for delivering productivity and efficiency advancement. As proven in other industries, digital methods can shorten product development time and cost by reducing prototyping with the use of numerical simulation. Further, a digital twin is an extensive computational model of a product that is planned to improve over its lifecycle by leveraging operational data. This paper presents a coupled simulation for the thermal design of a heating and cooling system that is integrated with a lightweight roof structure. The concrete roof structure is shape optimised to provide a low embodied energy building element, which is thermally activated to supply space conditioning from a renewable geothermal source. This work is focused on the modelling methodology used by the energy domain to support the development of a digital twin for a multifunctional building element. High-resolution analysis is used to resolve building physics issues and to provide the initial system performance. A parametric geometry model is used to apply the hydronic pipework to a complex roof shape. With input from the previous two steps, a reduced resolution method is used to add the characteristics of the system to an industry standard whole building simulation model. This final step allows for the development of initial control strategies for the novel multifunctional element. The implications of the research findings are discussed in the context of possible alternations to the building design process due to the influence of digital fabrication.

Lightweight and high-strength optimization design for a fully parametric working attachment of a hydraulic excavator based on limiting theoretical digging capability model

This paper presents a methodology for the optimization design of a fully parametric working attachment of a hydraulic excavator with the weight reduction and maximum stress minimization as the design objectives. A novel 3D force output model named limiting theoretical digging capability model is proposed to completely and accurately calculate the maximum force and moment an excavator can apply in the preferred bucket force space. On the basis of this model, the joint forces acting on the working attachment are calculated. Further, the critical digging condition and design loads used for the structure optimization can be determined by using the stress-based evaluation method. A fully parametric geometry model of the working attachment is constructed to achieve automatic design optimization and reduce the remodeling time. The plate thickness parameters and some critical structure parameters are selected as the design variables for the optimization design problem, which aims at minimizing the maximum stress in the structure and reducing the weight of the working attachment. Mixed variable genetic algorithm is used to solve this optimization problem due to its design variables include both discrete and continuous parameters. A simulation and optimization framework is established to support load calculation and processing, stress analysis, and structure optimization. Finally, the capabilities of the proposed methodology and established framework are demonstrated by a practical design. The results show that both the weight and maximum stress of the working attachment have an obvious decrease. This work provides a pragmatic tool for efficient virtual design and automatic optimization for the working attachment of an excavator.

Lightweight and High‐Strength Design of an Excavator Bucket under Uncertain Loading

This paper presents a methodology for lightweight and high‐strength design of an excavator bucket under uncertain loading. Uncertain loads are obtained by using the Monte Carlo simulation based on the existing soil‐bucket interaction model in which the soil parameters are variable. And the well‐known 3‐sigma methodology is used for the quantification of the uncertain loads. Excavator bucket modelling is finished by using ANSYS Parameter Design Language (APDL). A multiobjective optimization model aiming to decrease the maximum von Mises stress and to reduce the weight of the bucket is established on the foundations of the uncertain load and the parametric geometry model. The structural shape and topology of the bucket are then designed by using the mixed variable genetic algorithm to solve the established optimization problem. The results show that the presented method can be effectively and efficiently applied for the optimization design of the excavator bucket and that the optimized bucket signifies obvious decreases in the weight and the stress compared with the initial reference model. The proposed methodology for structure optimization design considering uncertain loads not only provides the technical means for the design and development of high‐performance bucket but also lays a preliminary theoretical foundation for the optimization design integrated machine‐environment interaction.

A User-centric Approach to Optimize Visitor’s Experience in Exhibition Spaces Using Parametric Spatial Analysis

Being the main user of any architectural product, the user's role in the designing process should be significant, especially in complex spatial spaces such as hospitals, museums, offices, and public-use buildings. This gives the users meta- roles such as communicators, performers, and interpreters. User-Centered Design (UCD) tries to optimize the fit of the spaces with how users can, want to, and need to use in these spaces, rather than forcing the users to change their behavior to accommodate the architectural spaces or designing dysfunctional spaces. Such spaces were designed neglecting the human factor and only using building regulations. The visitor’s parameters, profiles, spatial experiences, and the architectural configuration are what can affect the experience in architectural spaces. This paper explores a different UCD (user-centered design) approach in the evaluation of the built environment which is the parametric spatial analysis approach. The approach studies the spatial pattern of human behavior of a random selection of users, so it could represent any potential users in the buildings. Aiming to intensively engage users in the design process, the approach uses parametric spatial design in analyzing the visitor's behavior and deducing some design patterns and configurations that focus on different ways of user's engagement. This approach compares the definition of users, their roles, and the type of space envisioned and produced as well. This paper describes an approach that attempts to bridge the gap between parametric geometry modeling and methods for measuring the spatial properties of this geometry. In exhibition spaces with their different spatiality, visitors tend to have some indicators which can be measured. Accordingly, designers create functional spaces that suit the different types of visitors using parametric components that study the collective human behavior (organizational behavior). These functional spaces are designed through observation, user surveys, and interviews to simplify the complexity of decisions regarding the design process and visitor’s parameters, and to embed them into an algorithm that can solve the complexity of the visitor’s parameters. Analyzing visitors’ behavior and the spatial morphology improves the visiting experience and provides better interpretations. The analysis makes the designers aware of visitors’ circulation, visiting styles, behavior, patterns, tendencies, and trends within a wide diversity of spaces. Moreover, this analysis can be combined into an evolutionary algorithm to help solve problems.

Pre-procedural fit-testing of TAVR valves using parametric modeling and 3D printing

BackgroundSuccessful transcatheter aortic valve replacement (TAVR) requires an understanding of how a prosthetic valve will interact with a patient's anatomy in advance of surgical deployment. To improve this understanding, we developed a benchtop workflow that allows for testing of physical interactions between prosthetic valves and patient-specific aortic root anatomy, including calcified leaflets, prior to actual prosthetic valve placement. MethodsThis was a retrospective study of 30 patients who underwent TAVR at a single high volume center. By design, the dataset contained 15 patients with a successful annular seal (defined by an absence of paravalvular leaks) and 15 patients with a sub-optimal seal (presence of paravalvular leaks) on post-procedure transthoracic echocardiogram (TTE). Patients received either a balloon-expandable (Edwards Sapien or Sapien XT, n = 15), or a self-expanding (Medtronic CoreValve or Core Evolut, n = 14, St. Jude Portico, n = 1) valve. Pre-procedural computed tomography (CT) angiograms, parametric geometry modeling, and multi-material 3D printing were utilized to create flexible aortic root physical models, including displaceable calcified valve leaflets. A 3D printed adjustable sizing device was then positioned in the aortic root models and sequentially opened to larger valve sizes, progressively flattening the calcified leaflets against the aortic wall. Optimal valve size and fit were determined by visual inspection and quantitative pressure mapping of interactions between the sizer and models. ResultsBenchtop-predicted “best fit” valve size showed a statistically significant correlation with gold standard CT measurements of the average annulus diameter (n = 30, p < 0.0001 Wilcoxon matched-pairs signed rank test). Adequateness of seal (presence or absence of paravalvular leak) was correctly predicted in 11/15 (73.3%) patients who received a balloon-expandable valve, and in 9/15 (60%) patients who received a self-expanding valve. Pressure testing provided a physical map of areas with an inadequate seal; these corresponded to areas of paravalvular leak documented by post-procedural transthoracic echocardiography. ConclusionWe present and demonstrate the potential of a workflow for determining optimal prosthetic valve size that accounts for aortic annular dimensions as well as the active displacement of calcified valve leaflets during prosthetic valve deployment. The workflow's open source framework offers a platform for providing predictive insights into the design and testing of future prosthetic valves.