Uncertainty Quantification and Machine Learning for the Automotive, Off-Road, and Heavy Equipment Vehicle Industries
As the automotive, off-road, and heavy-equipment markets undergo rapid transition, engineers must innovate faster, with fewer resources, and greater confidence in their results. Traditional design, simulation, and testing methodsâwhile effective under specific conditionsâstruggle to keep pace with growing complexity in suspension systems, crashworthiness, thermal-fluid interactions, and structural dynamics. Without enhanced tools, teams face:
- Excessive runtimes that limit design-space exploration and delay programs;
- Oversimplified models that erode confidence in performance predictions;
- Brute-force optimization approaches that are slow, resource-intensive, and often incomplete;
- Difficulty modeling complex behaviors like transient sloshing, multi-body dynamics, or thermal cycling;
- Inability to incorporate uncertainty, tolerance variability, and real-world operating conditions;
- Missed innovation opportunities due to lack of fast, predictive workflows.
SmartUQ Solutions
SmartUQ is a next-generation UQ and ML platform built to address these challenges head-on. By combining cutting-edge Design of Experiments (DOE), statistical emulation, and machine-learning techniques, SmartUQ empowers OEMs and suppliers to rapidly explore design spaces, trace uncertainty through vehicle systems, and achieve probabilistic performance estimatesâall while slashing computational costs.
- Efficient DOE & Sampling: Employ advanced DOE methods to map inputâoutput relationships with fewer simulations, enabling rapid insights even for long-running CFD and FEA studies.
- Accurate Surrogate Modeling: Build high-fidelity emulators (âstatistical prediction modelsâ) that require only a few hundred simulations for problems with 10â20 inputs. Leverage multifidelity modeling to combine low- and high-fidelity data.
- Analytics Workflows for Complex Data: Handle spatially and time-varying outputs (e.g., temperature histories, pressure fields) and mix continuous and categorical variables across operating modes.
- Uncertainty Quantification & Variability Management: Trace material, manufacturing, and operational variability through system-level models to obtain probabilistic performance estimates and robust design margins.
- Statistical Calibration & Model Validation: Ground simulations in physical test and field dataâaddressing both parameter and model-form uncertaintyâto improve agreement with engine tests, wind-tunnel results, and fielded-unit records.
- Digital-Twin Integration: Fuse design simulations, prototype tests, manufacturing records, and in-service data to create âauthoritative truthâ sources that drive continuous model update and system-level digital twins.
Key Benefits for Engineering Teams
- 1. Faster Exploration, Fewer Runs Achieve target surrogate-model accuracy with minimal data, freeing engineers to iterate designs rapidly.
- 2. Broadened Applicability Apply surrogate modeling and UQ to specialized domainsâcrash, suspension dynamics, lubrication, thermal managementâwhere traditional methods falter.
- 3. Smarter Optimization Replace brute-force search with accurate emulators, improving convergence, reliability, and time to solution for simulation-driven design.
- 4. Greater Confidence through Calibration Use SmartUQâs unique statistical calibration to reconcile simulations and experimentsâeven when models contain simplifying assumptions.
- 5. End-to-End Insight Integrate multi-source and multi-fidelity data across the product lifecycle for continuous improvement, component-failure analysis, and digital-twin construction.
Summary
With a complete suite of DOE, data-sampling, emulation, UQ, and calibration tools, SmartUQ transforms how automotive, off-road, and heavy-equipment teams develop and validate vehicle systems. Explore our white papers and webinars w to learn how SmartUQ can accelerate your simulations, reduce costs, and unlock new innovation frontiers.
