Enhancing Aerodynamics With Artificial Intelligence: A Revolution in Engineering
Introduction: Artificial Intelligence In Engineering
Traditional engineering practices have inherent challenges that hinder efficiency and progress. Time-consuming processes, resource-intensive simulations, and limited real-time feedback are among the primary challenges engineers face on a day-to-day basis.
Reliance on large volumes of physical prototypes and extensive tests further restricts design exploration and prolongs development timelines.
Artificial intelligence (AI) has been transforming the field of aerodynamics, bringing a remarkable shift in engineering simulations.
It is a great enabler for engineers to delve into intricate details of aerodynamic phenomena, resulting in optimized performance parameters that were previously labor-intensive.
Through the utilization of computational advancements that AI has been unlocking, engineers can simulate cases of control of fluid flow dynamics, as shown in Figure 1.
This transformative impact has pushed the limits of what was previously believed achievable.
The final model design and evaluation process can be accelerated by using the right AI models, reducing the calculation time from 12 hours to only 20 ms.
Figure 1 – Comparison between the prediction from our software and CFD results.
This article delves into Navasto’s AI-driven solutions that address aerodynamic challenges, provide real-time feedback, and enhance performance and efficiency.
As a true innovator in aerodynamics, NAVASTO employs AI to overcome the limitations of conventional simulation workflows.
Integrating simulation into design allows engineers to optimize the performance of their product and resolve potential issues without the cost of wind tunnel testing.
Our solution offers real-time feedback and actionable insights, empowering engineers to optimize performance parameters and make informed decisions cost-effectively.
The instant feedback from the predictive models enables engineers to fine-tune and optimize designs for maximum efficiency and cost savings (eliminating the costs of wind tunnel testing).
Addressing Aerodynamic Challenges
Accelerating Product Development
In today’s fast-paced world, industries, particularly the automotive sector, face a growing demand for accelerated product development.
Companies like Tesla have set a high standard for rapid innovation, putting pressure on automotive engineers to speed up their design and development processes.
Taking on this challenge of AI technology, Navasto is committed to providing innovative AI solutions that enable customers to keep up with the industry’s pace.
Leveraging AI-powered tools and algorithms, NAVASTO empowers engineers in aerodynamics to streamline workflows, enhance collaboration, and expedite the entire product development lifecycle.
From concept ideation to virtual prototyping and validation, NAVASTO’s AI solutions offer real-time feedback and insights, facilitating informed decisions and faster optimization and improvement of designs.
The Rise of Electric Vehicles: The Importance of Aerodynamics
Amid the transition towards sustainable transportation, electric vehicles (EVs) have gained popularity, with aerodynamic performance severely impacting their range and efficiency.
Well-designed vehicle aerodynamic profiles can substantially reduce drag, with emissions regulations improve energy efficiency, and enhance EVs’ overall performance and driving range.
Industrial challengers such as Audi have been consistently pushing the limits of vehicle aerodynamic efficiency by applying innovative and intelligent engineering tools to vehicle parts.
NAVASTO genuinely understands the complexity of aerodynamic challenges in the context of electric vehicles.
Thanks to its AI-based intelligent simulation workflows, NAVASTO is at the forefront of driving innovation in the aerodynamics of EVs.
Their cutting-edge technologies empower engineers to optimize the aerodynamic performance of EVs, ensuring maximum efficiency and range.
With AI algorithms that analyze complex wind tunnel airflow patterns, NAVASTO paves the way for the streamlined engineering design and analysis of systems and materials that minimize drag and maximize energy utilization with thoroughly accelerated AI-assisted engineering, for example, as can be seen in Figure 2.
The Technology Behind the Transformation
NAVASTO’s Approach: AI Integration and Real-Time Feedback
Beneath the surface of NAVASTO lies a complex system driven by the intricacies of the NAVPACK API.
The integration and automation of AI models into engineering applications entails implementing automation through a series of data processing stages. This comprehensive automation workflow encompasses preprocessing, model training, hyperparameter tuning, and the eventual deployment of models for predictive purposes.
At the core of this process is the crucial step of data preprocessing. NAVPACK simplifies this essential stage through the accessibility of the Snaplib library. Snaplib is a robust toolkit designed for efficient data storage, manipulation, and visualization.
Its versatile modules cater to various aspects of data analysis and manipulation, all contributing to the seamless handling of input data in diverse formats and sizes. The snapshot data backend, rooted in the powerful VTK library, is seamlessly facilitated by Snaplib to ensure data management, optimal filtering, conversion, and mapping of data, aligning it with AI requirements.
The journey continues with model training, where NAVPACK’s versatility shines. Recognizing the diversity of engineering challenges, NAVPACK takes a flexible approach, ensuring users have the most suitable method at their disposal.
The comprehensive ML library embedded within NAVPACK offers a complete toolkit for training, optimizing, and evaluating a wide range of machine learning and deep learning models. Notable methods such as POD+I, Isomap+I for parameterized design spaces, GNN, CNN, and PCT for shape-based machine learning models are among the prominent options available.
Upon training, NAVPACK’s scope expands to making predictions, granting users real-time insights into new designs. The design space exploration is made interactive with supported frontend tools, while the predictions seamlessly integrate into customers’ post-processing workflows. Alternatively, NAVPACK facilitates programmatic optimization.
The integrated post-processing feature eliminates the need for cumbersome file I/O, allowing the direct extraction of relevant information. Moreover, NAVPACK’s adaptability extends to custom dashboards, catering to unique use case scenarios. This holistic technology blend transcends being a mere tool; it embodies the fluid fusion of AI and engineering, delivering adaptability and value.
Leveraging Blender: A Powerful Design Tool for Aerodynamics
Blender, an open-source 3D computer graphics software, stands as a robust tool for 3D modelers. Blender takes on a pivotal role in our methodology for conquering design challenges when merged with AI capabilities.
Figure A showcases Blender’s interface, hosting our AI-based aerodynamics simulator. The synergy between Blender’s rich 3D modeling and simulation tools and our embedded AI models amplifies its prowess. This convergence empowers advanced analysis and predictions.
A significant advantage emerges in the form of direct mesh interaction and real-time visualizations of predicted flow fields and drag coefficients. This immediate feedback loop becomes a wellspring of insights, allowing engineers to make informed decisions and iterate for performance optimization swiftly.
The navDesign plugin, available for ParaView® and Blender®, cements this connection. With support for Blender, engineers gain access to powerful geometry manipulation and rendering capabilities, seamlessly working with models trained using NAVPACK.
navDesign for Blender empowers engineers to refine geometry using Blender®’s full suite and instantly visualize physical outcomes for new shapes, including volume and surface fields.
It predicts scalar values, like aerodynamic coefficients, for the present geometry, and calculates node-wise sensitivities toward scalar values within seconds, aiding decision-making. Immediate insights into the reliability of predictions are attainable.
Engineers can even export the current interface geometry for further applications. This dynamic amalgamation of AI and Blender transforms the design process, accelerating decisions, and delivering enriched results.
Interrogating the Accuracy
Integrating AI models into Blender offers engineers a unique opportunity to interact with real-time AI predictions. This integration allows for quick loading of AI models and immediate feedback on crucial aerodynamic parameters, including drag coefficients and flow fields.
The ability to have data scientists receive real-time feedback empowers engineers to assess the impact of design modifications and make informed decisions based on predicted results.
This interactive process is invaluable in optimizing performance, as engineers can identify areas of high drag or turbulence and explore design iterations for maximum aerodynamic efficiency, while ensuring the accuracy of the models in use (Figure M).
Figure M. Calibration plot with uncertainties to assess the accuracy of our tool.
NAVASTO Is Shaping AI-Driven Engineering
Our journey began with a vision: augmenting engineering using AI. From AI Engineering in Berlin, we’ve grown into a team of 23 diverse experts. Our combined expertise in engineering, physics, computer science, and software development empowers us to create advanced AI solutions for aerodynamics.
Navpack, our flagship software, redefines AI-accelerated engineering. Developed over a decade with industry leaders, it seamlessly integrates AI for real-time insights, predictive modeling, and efficient optimization. Navpack empowers engineers, drives innovation, and accelerates industries.
AI has revolutionized engineering, offering real-time feedback, predictive modeling, and optimization. In aerodynamics, AI-driven solutions provide rapid simulations, accurate predictions, and proactive maintenance. AI-powered optimization fine-tunes performance and reduces environmental impact.
As technology advances, we embrace AI’s integration into workflows, offering real-time insights and efficient optimization of tasks. Staying at the forefront, we shape the industry, equipping engineers to overcome challenges.
Conclusion: Artificial Intelligence Is the Future of Aerodynamic Engineering
NAVASTO stands resolutely at the forefront of AI’s transformative potential in aerodynamics and engineering.
NAVASTO’s innovative solutions blend AI with engineering processes harmoniously, providing real-time insights and data-driven design choices.
Through our flagship software, Navpack, which embodies a decade of expertise, we’re driving AI-accelerated engineering and shaping the sector’s future.
Our commitment not only promises a bright future but fundamentally alters the way engineers approach and conquer complex challenges.