New parametric computational test case for automated design and analysis of an axial blood pump

Commentary: Improving ventricular assist device design. Much achieved with further innovation on the horizon.

Thousands of children are born each year with significant cardiac defects that result in the development of heart disease and ultimately premature congestive heart failure (CHF). In addition, hundreds of children are exposed to viruses and bacteria that attack the heart muscle, causing myocarditis or cardiomyopathy that leads to CHF. The current treatment paradigm involves pharmacologic agents to mitigate symptoms and slow the progression to failure. Most severe cases require heart transplantation or the use of short or long-term mechanical circulatory support (MCS) systems, such as ventricular assist devices (VADs). Due to the shortage of donor hearts, waiting periods, and the difficulty of finding a donor heart, the implementation of MCS devices is on the rise as an alternative treatment strategy for pediatric patients with CHF. VADs specifically for children, continue to lag behind those developed for adults. In addition, there is no heart pump with the design innovation to support the dysfunctional states of heart failure and the range of the anatomic and physiological heterogeneity in pediatric patients from one stage of development to another. To address this unmet clinical need, I am developing two dual-configured mechanical VADs that only have two moving parts and the versatility to provide full or partial cardiovascular support to either the right or left ventricle of pediatric patients. These devices will not only support pediatric patients (body surface area [greater than or equal to] 0.7 m²), but they will also support their growth and development. he two VADs were designed to deliver flows of 1 - 5 L/min and pressure rises of 50 - 120 mmHg at 2,000 - 15,000 RPM. Both VADs underwent 2 design phases in order for the overall pump housing to be small enough to fit within the thoracic cavity of children. Having the VADs be completely implantable within the thoracic cavity eliminates the need for percutaneous driveline that protrudes from the abdomen. The research was focused on advancing the development of 4 centrifugal blood pumps and 3 axial blood pumps, which are incorporated in the VADs being developed, also referred to as the Parallel Concept and Series Concept Pediatric VADs. The generation 1 centrifugal pumps that were incorporated for both the Parallel and Series Concept VADs were designed using the Taguchi Optimization Method to produce 80 to 120 mmHg in the 3 to 5 LPM range. The diameter of both of the centrifugal impellers were 35.6 mm. Both Gen 1 centrifugal pumps were evaluated computationally and experimentally. The design of generation 1 axial pump was iteratively improved to maintain an overall length less than 50 mm while generating 50 to 80 mmHg. Generation 1 axial and centrifugal pumps were able to satisfy physiological pressure requirements while maintaining the blood damage index to less than 2%. The axial and centrifugal pumps were experimentally evaluated using a water-glycerin mixture in order to verify pressure generation predictions. The Gen 1 axial and centrifugal pumps experimentally outperformed computational predictions. Both of the centrifugal pumps experimentally outperformed computational predictions by 10-15%. The generation 1 pumps were decreased in size by 30 to 40% in order to establish the generation 2 axial and centrifugal pumps for both the Parallel and Series Concept VADs. The Gen 2 centrifugal pumps for both the Series and Parallel Concept VADs had an overall diameter of 30 mm. The impeller diameter for the Series Concept pump was 24 mm and the impeller diameter for the Parallel Concept was 22 mm. The axial pump length for both concepts was less than 35mm. Generation 2 pumps were able to satisfy the physiological pressure requirements at their new scaled size while maintaining the blood damage index to less than 2%. The experimental results for the Series Concept axial and centrifugal pumps demonstrated that the designs outperform computational predictions. The research performed for both the Series and Parallel Concept VADs demonstrates significant progress in the design of 2 Pediatric VADs. The Gen 2 impeller and the volute combination for both concepts is already less than 30 mm in diameter which satisfies the design requirement for the VADs to be implanted within the thoracic cavity of pediatric patients. These innovative pump design will support a wide range of patient ages and dysfunctional states of heart failure.

The success of left ventricular assist device (LVAD) therapy is hampered by complications such as thrombosis and bleeding. Understanding blood flow interactions between the heart and the LVAD might help optimize treatment and decrease complication rates. We hypothesized that LVADs modify shear stresses and blood transit in the left ventricle (LV) by changing flow patterns and that these changes can be characterized using 2D echo color Doppler velocimetry (echo-CDV). We used echo-CDV and custom postprocessing methods to map blood flow inside the LV in patients with ongoing LVAD support (Heartmate II, N = 7). We compared it to healthy controls (N = 20) and patients with dilated cardiomyopathy (DCM, N = 20). We also analyzed intraventricular flow changes during LVAD ramp tests (baseline ± 400 rpm). LVAD support reversed the increase in blood stasis associated with DCM, but it did not reduce intraventricular shear exposure. Within the narrow range studied, the ventricular flow was mostly insensitive to changes in pump speed. Patients with significant aortic insufficiency showed abnormalities in blood stasis and shear indices. Overall, this study suggests that noninvasive flow imaging could potentially be used in combination with standard clinical methods for adjusting LVAD settings to optimize flow transport and minimize stasis on an individual basis.

A case is made that introducing CAD-based geometry prematurely in the aircraft design process actually hinders multidisciplinary design. Consequently, a design process which allows a designer to quickly build and analyze aerospace configurations without CAD or computational meshing specialists is proposed. This allows higher fidelity analyses to be applied at conceptual design and decreases the turnaround time for trade studies and optimizations. The basic premise of conceptual geometry modeling is presented and discussed. Key features and capabilities which are essential for a successful geometry modeler are identified. Desktop Aeronautics' conceptual geometry modeler, RAGE, is described, with emphasis on recent progress and advances in the tool. A preliminary graphical-user-interface is presented along with an application programming interface. Extensibility of the RAGE modeler is discussed along with the importance of this feature. The applicability of RAGE to simple trade studies is demonstrated in an example problem. The precision of the RAGE modeler is also demonstrated on a complex aircraft design. Future plans for the geometry modeler are also discussed. I. Background In the conceptual phase of aircraft design, there is often a wide range of geometric configurations that the designer wishes to consider, analyze, and assess. A designer’s intuition and creativity are crucial to a successful conceptual design, yet are easily inhibited by the modeling and analysis process itself, particularly if high-fidelity analysis is warranted. If the time between inception and assessment of a candidate design is relatively long, a designer may be forced to limit the number of concepts considered. New data revealed in a design iteration may suggest or require significant changes to the geometry configuration. Since the majority of considered design configurations will eventually be discarded, an ideal conceptual design process should involve a highly efficient and easy to use geometry modeler. Significant changes should be allowed without tedious re-work of the geometry model. Exporting the model for analysis should require little effort and have the capability to be automated. Therefore, any modeling application used in this process should be flexible and not restrict the designer’s choice of user interface, analysis method, and design optimization environment. Most current design processes in the aerospace industry rely heavily on computer-aided-design (CAD) applications. As a general design tool, CAD is a powerful geometry modeler capable of precisely representing practically any shape. Unfortunately, this generality is realized at the cost of requiring specialized training to efficiently and effectively use the software. Also, a CAD model is often not easily modified, especially if significant re-work of the geometry is necessary. This can lead to the premature freeze of an aircraft design due to employing excessively high-fidelity geometry modeling too early in the design process. Parametric CAD modeling could address this issue, but creating a well-designed parametric CAD model is difficult. Not only does it require an extremely skilled operator, but also the designer must have some insight into what parameterization may ultimately be desired. Modifying a parametric CAD model is often more difficult than modifying a conventional CAD model. Significant changes, such as adding or removing cross-sections, may invalidate the parameterization in some cases. In most organizations, CAD modeling (whether it be parametric or conventional) is often assigned to a dedicated CAD specialist. Since the conceptual designer is usually not a CAD specialist, the latter must communicate his design intent to the former, often using sketches, dimensions, and word of mouth. When the CAD specialist interprets the sketches, any part or detail not precisely defined usually requires judgment and artistic license. This interpretation may result in loss of design intent and indeterminate iteration between the CAD specialist and designer to obtain a satisfactory result. Because this process is iterative, CAD operators often must recreate similar geometry

Left Ventricular Assist Devices and Renal Ramifications.

Parametric modeling is a critical technique in engineering design that enables the rapid generation and evaluation of candidate designs. To create parametric models, engineers need to be familiar with various Computer-Aided Design (CAD) software or have a strong grasp of at least one CAD scripting library. Modern multi-modal large language models (MLLMs) present an opportunity to automate parametric modeling, as they have shown the ability to write and execute code and also to analyze outputs such as images for further refinement. Based on these multidimensional capabilities, we propose Mechanical Engineering Design Agents (MEDA), an autonomous multi-agent framework that leverages AI agents to emulate human-like division of labor to create parametric CAD models. Our framework employs a combination of zero-shot and one-shot learning for the constituent agents, striking a balance between efficiency and accuracy. We evaluate our autonomous multi-agent framework using a dataset of 200 CAD prompts. MEDA achieves a success rate of 99% in script execution. Furthermore, we observe a minimal median point cloud distance of 0.0555 between generated and ground truth CAD models, a 56% reduction compared to prior work. Our findings demonstrate that through division of labor and effective collaboration, Artificial Intelligence (AI)-powered agents can autonomously generate more accurate CAD models relying primarily on their pre-trained knowledge. This paper highlights the significant potential of employing collaborative and dynamic multi-modal AI agents for design automation while also underscoring the current limitations of MLLMs in parametric CAD modeling. Code and data are available at : https://github.com/AnK-Accelerated-Komputing/MEDA

Hypoxemia after an axial flow pump Jarvik-2000 implantation: Catheter induced

A Realization Method for Transforming a Topology Optimization Design into Additive Manufacturing Structures

Topologically robust CAD model generation for structural optimisation

Structural analysis, based on the finite element method, and structural optimization, can help surgery planning or decrease the probability of fixator failure during bone healing. Structural optimization implies the creation of many finite element model instances, usually built using a computer-aided design (CAD) model of the bone-fixator assembly. The three most important features of such CAD models are: parameterization, robustness and bidirectional associativity with finite elements (FE) models. Their significance increases with the increase in the complexity of the modeled fixator. The aim of this study was to define an automated procedure for the configuration and placement of fixators used in the treatment of long bone fractures. Automated and robust positioning of the selfdynamisable internal fixator on the femur was achieved and sensitivity analysis of fixator stress on the change of major design parameters was performed. The application of the proposed methodology is considered to be beneficial in the preparation of CAD models for automated structural optimization procedures used in long bone fixation.

Artificial assist devices offer a promising treatment option for patients with congestive heart failure, especially when the patient is not eligible for heart transplantation. In order to develop a left ventricular assist device an interdisciplinary research, involving engineering and medical research teams, is conducted. The left ventricular assist device investigated in this study is the MicroMed DeBakey VAD [1], an axial blood pump that provides flow from the left ventricle to the aorta. The geometry of this baseline design is generated via parametric modeling. An optimization surface around the baseline design is formed by using the design of experiments method. Accordingly, eighty parameter sets and the corresponding CAD models are created. Flow through these pumps is simulated at the operation point. Flow data are evaluated to predict the pump performance, blood damage and bearing friction. An axial pump, closer to the optimum, is found that provides 8635 Pa pressure increase at a flow rate of 6 l/min and a rotational speed of 10000 rpm. Pressure head of the selected pump is 18% higher and blood damage is 4% less than the baseline design.

Integration of CAD (Computer Aided Design), CAPP (Computer Aided Process Planning) and Process Modeling activities plays a vital role in enabling concurrent product and process design. Typically each of these functions is performed in its own dedicated software environment. The integration will require interfacing several disconnected processes and software components built in different languages, and platforms. This paper presents an integration methodology, validated using a case study, in which a steering housing was analyzed and its process planning and design tasks were integrated using several software tools. The first integration task was to generate a feature based CAD model (in Unigraphics) and map these design features to a set of manufacturing features. Feature based design was performed using the Horizontal Modeling™ approach developed at Delphi. Features developed using this approach were then mapped to manufacturing features using APPS, a software tool developed at Delphi Dynamics and Propulsion Innovation Center. This task involved interrogation of the geometric CAD model to generate geometric and tolerance information and represent them in a format suitable for feature-based process planning. The second task of integration is generation of feasible “production-intent” process plans. This task is performed using APPS and IMPlanner process planner, a knowledge based software tool developed at Ohio University. The third and final task of integration is automated generation of in-process CAD models. This task involved the integration of Delphi process design techniques to generate CAD models (in Unigraphics) to represent the component at each stage of the manufacturing process. Evaluation of these steps through the case study has identified the strengths and weaknesses of the proposed integration methodology, which is reported in this paper.

The issue of improving quality, costs and delays indicators in design and manufacturing is more relevant than ever in the industry. After lean manufacturing, well known in production process, the lean engineering approach is being implemented today in the field of design, taking the name of lean product development. The management of knowledge and know-how (existing, new or to be acquired) is the heart of lean engineering. In our suggested methodology this is implemented through a new generation of tools called Knowledge Configuration Management (KCM) and Knowledge Extraction Assistant (KEA). KCM tools are lean engineering components that provide analytical approach to knowledge management and knowledge-based engineering. These tools require a highly integrated approach that involves, for example, predefined geometrical parametric 3D models, such as CAD templates. But this approach cannot be deployed in all engineering sites. We propose to complete this KCM approach introducing a semantic network approach, coupling with Feature Identity Card (FIC). FIC contains a set of metadata and information existing in the Product Data Management (PDM), connected with information extracted from 3D CAD (Computer Aided Design) models. It allows contextualizing information and ensures semantic connections, in order to manipulate the right parameters with mathematical algorithms. Those algorithms will search candidate relationships between design parameters extracted from CAD models. Our suggested approach aims at extracting knowledge in cases where design never came out of Knowledge Based Engineering (KBE) applications. In those situations, it seems important to complete classical knowledge management approach, and to find out the implicit knowledge embedded in 3D CAD models. This is achieved through a global approach, focusing on the product’s 3D definitions. We suggest introducing the latter approach by a suite of digital KEA tools (interfaced with KCM tools). Extracting knowledge from projects information stored in the Product Data Management does this. More precisely, the methodology is based on a commercial 3D similarity search tools for CAD models and on mathematical algorithms that search relationships between extracted design parameters. The goal is to submit new rules to the process and design experts. Implementing this methodology, a deeper knowledge of the product and its associated process can be acquired. This ensures a more productive and efficient design process.

<title>ABSTRACT</title> <p>The objective of this effort is to create parametric Computer-Aided Design (CAD) accommodation models for crew and dismount workstations with specific tasks. The CAD accommodation models are statistical models that have been created utilizing data from the Seated Soldier Study and follow-on studies. The final products are parametric CAD models that provide geometric boundaries indicating the required space and adjustments needed for the equipped Soldiers’ helmet, eyes, torso, knees, boots, controls, and seat travel. Clearances between the Soldier and surrounding interior surfaces and direct field of view have been added per MIL-STD-1472H. The CAD models can be applied early in the vehicle design process to ensure accommodation requirements are met and help explore possible design tradeoffs when conflicts with other design parameters exist. The CAD models are available to government and industry partners and via the GVSC public website once they have undergone Verification.</p> <p><bold>Citation:</bold> F. Huston II, G. Zielinski, M. Reed, PhD, “Creation of CAD Accommodation Models for Military Ground Vehicle Design,” In <italic>Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium</italic> (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022.</p>

The failing Fontan physiology may benefit from ventricular assist device (VAD) mechanical circulatory support, although a subpulmonary VAD placed at the Fontan connection has never successfully supported the Fontan circulation long term. The HeartWare CircuLite continuous flow VAD was examined for Fontan circulatory support in an in vitro mock circulation. The VAD was tested in three different scenarios: VAD in parallel, baffle restricted VAD in parallel, and VAD in series. Successful support was defined as simultaneous decrease in inferior vena cava (IVC) pressure of 5 mm Hg or more and an increase in cardiac output (CO) to 4.25 L/min or greater. The VAD in parallel scenario resulted in a CO decrease to 3.46 L/min and 2.22 mm Hg decrease in IVC pressure. The baffle restricted VAD in parallel scenario resulted in a CO increase to 3.9 L/min increase in CO and 20.5 mm Hg decrease in IVC pressure (at 90% restriction). The VAD in series scenario resulted in a CO of 1.75 L/min and 5.9 mm Hg decrease in IVC pressure. We successfully modeled chronic failing Fontan physiology using patient-specific hemodynamic and anatomic data. Although unsuccessful in supporting Fontan patients as defined here, the HeartWare CircuLite VAD demonstrates the possibility to reduce Fontan pressure and increase CO with a VAD in the Fontan connection. This study provides insight into pump performance and design issues when attempting to support Fontan circulation. Refinements in VAD design with specific parameters to help support this patient population is the subject of our future work.