The future of data-driven predictions is here!
In this article, we will cover the potential of AI and machine learning for engineering. To do this, we will show how SimScale and NAVASTO collaborate to bring a fully integrated, cloud-native AI-based physics prediction platform to engineers and physicists working worldwide!
Watch our webinar “AI-Based Physics Predictions in Your Web-Browser” now
A Fundamental Paradigm Shift in Engineering Design
AI and machine learning are already used extensively to enhance how engineers design products. The traditional design cycle, where simulation typically occurs towards the end of the product development process, is undergoing a profound transformation.
The collaborative effort between SimScale and NAVASTO is paving the way for the first cloud-native AI-based physics prediction platform, providing instant simulation results for engineers.
Over the past few months, both teams have been working hard at enhancing SimScale’s AI capabilities and enabling engineers all over the world to use this technology.
SimScale highlights that AI is robust but requires prepared data and training. It’s not the primary choice for standard PDE simulations, but it’s useful when organizations have a limited design space.
SimScale integrated AI prediction capabilities right alongside their trusted PDE solver. This means that for a given problem, you can choose between AI prediction and the traditional PDE solver, depending on what best suits your needs.
This collaboration will make AI capabilities accessible to engineers of all levels.
🔗 For more on AI Accelerated Engineering, check out this podcast.
In the past, such powerful simulations were confined to massive servers within large organizations. Now, it’s democratized, making it available to a broader audience.
Herein, we’ll explore real-world use cases, and explain the technology’s history and evolution, and its impact on the future of engineering.
Read on to discover how you can utilize the power and knowledge of AI in your engineering endeavors!
The Need for AI in Engineering
The need for AI in engineering stems from the continuously evolving challenges faced by today’s engineering organizations.
These include:
- Optimization Needs: Engineers constantly seek to reduce manufacturing costs, energy consumption, material usage, and environmental impact. AI can help identify optimal solutions in a complex and broad design space.
- Generative Design: The emergence of tools capable of generating thousands of design models quickly necessitates an engineering solution for evaluating and optimizing these model designs effectively.
- Diverse Design Criteria: Engineering criteria have expanded to include factors like thermal management, vibrations, environmental and light exposure, electromagnetics, and more. Sometimes, there are multiple design objectives and standards that need to be met that cannot be easily managed using traditional methods.
- Digital Twins: The development of digital replicas of real-world products for real-time monitoring, optimization, and anomaly detection is now a reality, demanding specialized tools. AI can help learn from old products and incorporate learnings and mistakes in new product designs.
- Time to market: In today’s competitive landscape, engineering organizations are under increasing pressure to accelerate the time it takes to bring new products to market. This urgency arises from the dynamic interplay of evolving technology, stringent regulations, and new market entrants. AI plays a pivotal role by enabling real-time simulation iterations, empowering engineers to swiftly refine their product designs and meet the demands of this fast-paced industry.
To address these challenges efficiently at every stage of the design process, from generative design to monitoring and operation, AI is a solution that finds more traction in the engineering industry.
Implementing AI at NAVASTO
NAVASTO’s role in this collaboration is to provide AI solutions that accelerate engineering processes.
The critical components of NAVASTO’s AI solutions include:
- Data Collection: Gathering input data, which in theory can be obtained from various sources, including existing project data and legacy information.
- Machine Learning Models: Training machine learning models using different methods, such as Graph Neural Networks (GNN), Point Cloud Transformers (PCT), Convolutional Neural Networks (CNN), or Reduced Order Models (ROM), depending on the use case.
- Prediction Capabilities: Enabling engineers to use AI models for predicting scalar performance values, flow fields, and sensitivities.
- Real-time Feedback: Providing instant, real-time feedback for rapid decision-making and design iterations.
- Confidence and Uncertainty Estimator: A tool to validate predictions, ensuring trustworthiness for decision-making.
NAVASTO’s AI solutions have diverse applications, from optimizing sailing designs to simulating crash scenarios, transferring heat in heatsinks, and predicting drag coefficients on car designs.
The real benefit of these solutions is the ability to iterate and test numerous design variations without running extensive, time-consuming simulations.
SimScale’ AI Preview
SimScale’s AI Preview is an exciting feature that provides engineers instant feedback during the simulation setup.
Users can manipulate geometry, apply loads, and make design changes while receiving immediate AI-based predictions for various simulation results. This enables engineers to explore different scenarios and optimize designs efficiently.
For example, engineers can test how changes in load conditions impact stress distribution or other performance metrics. The AI Preview enhances the design process by offering real-time insights into the effects of design changes within seconds.
Assessing the Accuracy of AI Predictions
Validating their accuracy is essential to ensure the reliability of AI predictions.
SimScale makes it easy to compare AI-generated results with traditional simulation results.
By running simulations with the same inputs and comparing the two sets of correct predicted results, engineers can confirm that the AI predictions they correct align closely with the established simulation data. Thus, engineers will learn how to interpret and trust uncertainty and confidence indicators accurately.
The Road Ahead: AI Solvers & Self-Managed Models
The collaboration between SimScale and NAVASTO is constantly evolving.
The next phase involves the introduction of complete AI solvers, where engineers can choose to run simulations using AI-powered solvers that are equivalent in behavior to traditional PDE solvers.
This enhancement will provide API support and facilitate integration with third-party tools, extending the reach of AI-accelerated simulations. Furthermore, SimScale is working towards enabling users to create and manage their own AI models.
This will enable them to leverage their existing data or generate new datasets, train their machine-learning models, and deploy them for private or public use. These self-managed AI models will also provide a digital thread to track model versions and performance improvements over space and time.
AI-based physics predictions in your web browser are set to reshape the landscape of engineering design. The collaboration between SimScale and NAVASTO offers engineers a powerful platform to accelerate their design processes, improve accuracy, and streamline decision-making.
If you’re eager to explore the possibilities for your projects, don’t hesitate to contact us. Join our early access program and share your data with us.
Get in Touch With the NAVASTO Team
We’ll be happy to work together to create AI and machine learning models tailored to your team and unique needs, making them available for you to use as soon as possible!
Your case could be the next success story.
About SimScale & NAVASTO
SimScale is a cloud-native simulation platform that simplifies access to engineering simulations. It’s an all-in-one platform, offering a unified user interface for various physics simulations, real-time collaboration, and scalability.
With SimScale, users can seamlessly transition from running a single simulation to thousands in parallel, all while remaining cost-effective.
Founded in 2014, NAVASTO is pioneering and spearheading the adaptation of artificial intelligence in engineering processes to speed up development cycles drastically.
Today, NAVASTO comprises a team of experts from various fields, all united by a love of problem-solving. The company’s software products are built on a foundation of real-world engineering experience and are designed to address the problems faced by engineers and managers in the industry.
NAVASTO aims to accelerate engineering processes, enabling engineers from various disciplines and departments to make real-time decisions without time-consuming iterative methods.