By Dr Surya Kalidindi – CTO, Multiscale Technologies | Papers & Citations.
Introduction
Engineering and scientific computing have long relied on forward solvers to simulate physical processes. These solvers predict an outcome given a set of input conditions, making them essential for designing materials, optimizing manufacturing processes, and testing system performance. However, forward solvers face significant limitations when applied to inverse problems—situations where engineers need to determine the optimal inputs to achieve a desired outcome.
Traditional inverse problem-solving methods often lead to unsatisfactory results, computational inefficiencies, and local optima traps, limiting their real-world applicability. At Multiscale Technologies, we have developed a first-to-market AI-driven Inverse Solver that fundamentally transforms the way engineering teams approach complex optimization challenges. Our platform, powered by Bayesian inference and generative AI, is designed to work backward from target performance goals, providing engineers with the most efficient path to achieve their desired outcomes.
With Multiscale, The Desired Outcome Drives Optimized Inputs, we take an Inverse first approach.
The Limitations of Forward Solvers in Inverse Problems
1. Inverse Problems Are Ill-Posed
Unlike forward problems, where well-defined input conditions produce predictable results, inverse problems are inherently ill-posed. This means:
- Multiple input solutions may lead to the same outcome, making direct inference difficult.
- Small variations in inputs can lead to highly nonlinear and unstable results.
- Traditional optimization techniques often fail when applied to real-world engineering challenges.
2. High Computational Costs and Local Optima
Forward solvers require iterative adjustments of input parameters to approximate the desired outcome, leading to:
- Massive computational overhead due to repeated simulations.
- Since most current approaches are gradient based, they are prone to getting stuck in local optima, where minor improvements are made, but the global best solution is never found.
- Inefficiencies in real-world design cycles, requiring extensive human intervention.
3. Lack of Real-World Feedback Integration
Traditional solvers do not integrate live physical testing data dynamically. This results in:
- Simulations that fail to adapt to real-world conditions.
- Static models that do not update based on evolving physical constraints.
- Significant delays in R&D due to reliance on disconnected physical and digital workflows.
Multiscale’s Inverse Solver: A Paradigm Shift in Engineering Optimization
1. AI-Powered Bayesian Inference for Inverse Solutions
Multiscale Technologies introduces a revolutionary Bayesian-driven Inverse Solver that tackles these limitations by:
- Working backward from the desired outcome, systematically identifying the optimal input conditions.
- Leveraging probabilistic modeling to implement active learning and/or smart design of experiments strategies.
- Using generative AI to explore efficiently high-dimensional topologically complex design spaces.
2. Dynamic Model Updates with Real-World Testing Data
Unlike traditional solvers, Multiscale is the only digital twin platform that dynamically updates simulation models with results from real physical testing. This capability is crucial for industries where precision matters, such as:
- Automotive: Enhancing full-body crash testing accuracy.
- Aerospace & Defense: Optimizing high-performance alloy compositions.
- Manufacturing: Reducing waste and increasing material consistency.
- Battery Technology: Accelerating battery design by optimizing material compositions and processes to improve energy density, charging speed, and cycle life
3. Dramatically improve Trial-and-Error Through AI-Driven Process Optimization
Multiscale’s inverse solver eliminates the inefficiencies of trial-and-error by:
- Objectively determining the next set of best process parameters to try in achieving the desired material or structural properties.
- Reducing R&D time by accelerating the discovery of optimal solutions.
- Increasing engineering team productivity by automating the extraction of actionable insights through versioned data pipelines.
Real-World Application Examples of Multiscale’s Inverse Solver
Automotive: Full-Body Crash Testing Optimization
- Dynamically refines crash simulation models using real-world crash test data, ensuring accuracy in impact analysis.
- Reduces development cycles and costs for vehicle safety testing.
Aerospace & Advanced Materials
- Determines optimal heat treatment and material compositions for high-strength, lightweight components.
- Enables manufacturers to design materials with unprecedented thermal and mechanical properties.
Manufacturing & Process Optimization
- Reduces material waste and energy consumption by optimizing process parameters based on AI-driven insights.
- Enhances digital twins by incorporating live production data, ensuring unmatched accuracy in predictive maintenance and quality control.
Battery Design & Development
- AI-driven material discovery expedites the identification of novel battery materials with superior energy density, charging speed, and cycle life.
- Optimizes battery cell manufacturing processes to improve durability and efficiency.
Immediately Elevate Your Internal AI Engineering Team
- AI engineers are overwhelmed with a constant influx of requests, often stretched across a field so vast that delivering on complex challenges becomes a struggle.
- The Multiscale Platform was designed by world-leading AI experts to tackle the most advanced computational problems. By leveraging this built-in expertise, your internal AI team gains instant access to cutting-edge capabilities, supercharging their ability to solve complex challenges faster and more effectively.
These examples represent just a fraction of the transformative applications enabled by our AI-powered Inverse Solver and Optimization Platform. If you’re leading the charge in driving your company’s next breakthrough, Multiscale’s first-to-market solution will help you achieve it faster—keeping you ahead of the competition and accelerating innovation like never before.
Conclusion: The Future of Engineering is Inverse-Driven
Multiscale Technologies is pioneering the next evolution of engineering optimization. By shifting from traditional forward solvers to AI-powered inverse problem-solving, we enable engineering teams to:
- Design faster, smarter, and with greater precision.
- Eliminate inefficiencies in material and process optimization.
- Achieve breakthrough innovations in every industry.
If you’re a Chief Engineer, R&D Leader, Innovation Director or AI/ML Strategist we invite you to explore how Multiscale’s AI-driven Inverse Solver can transform your workflow. Let’s discuss how we can help you achieve higher efficiency, lower costs, increased productivity, faster root cause analysis and superior engineering outcomes.
How To Unlock the Power of AI-Driven Inverse Solving
The Multiscale Platform is a flexible, enterprise-grade software solution that can be deployed on-premises, in your cloud, or hosted by us—ensuring seamless integration with your existing infrastructure. With security embedded at every level, you can trust that your data and workflows remain protected while achieving breakthrough innovation. Multiscale also includes access to advanced AI Engineers help to support you achieving your goals along with a customer success team to white-glove the experience for you.
If you’re tackling a complex engineering challenge and want to explore how AI-driven Inverse Solving can deliver faster, more precise solutions, let’s connect.
Schedule a no strings consultation with Matt Foster at matt@multiscale.tech or call +1 650.515.5739. Also there is a summary overview here if you would like to review first.
At Multiscale Technologies, we are a value-first company, and it would be our pleasure to prove out our capabilities and help you drive the next leap forward for you and your organization.
Engineering the Future, Powered by AI, Built by Multiscale
The First AI Powered Inverse Solver and Optimization Platform