Physics AI, Machine Learning, & Uncertainty Quantification for Engineering
SmartUQ provides advanced Machine Learning and Uncertainty Quantification tools that help our customers save time, decrease costs, improve quality, increase reliability, and reduce risk.
Trusted by Industry Leaders
- 50–75% faster design loops
- 30–60% test cost reduction
- Removes 10–20% over-design
SmartUQ Delivers Best-in-Class Capabilities
Our tools are optimized for engineering data sets from simulation, testing, manufacturing, and digital twins. SmartUQ goes beyond checking accuracy to quantify the disagreement and uncertainty in results and predictions. Because data is never perfect and models always have errors, knowing how far off they are from reality is critical when making engineering decisions.
Surrogate Modeling
High-accuracy, machine learning based emulators, including advanced flexible Gaussian process models, accelerate computationally heavy simulations across multi-dimensional, continuous, discrete, and varying geometry datasets.
Physics AI
Physics-based simulations are used to train advanced Gaussian process-based surrogate models to accurately predict a wide variety of results. This means fewer computationally heavy simulations runs or expensive tests relative to both direct analysis or deep learning based methods.
Data Sampling & Subsampling
Intelligent space-filling and uniform subsampling algorithms compress massive simulation and test datasets, preserving critical feature distributions and parameter sensitivities while slashing computational overhead.
Design of Experiments
Novel space-filling DOEs and adaptive sampling methods maximize coverage and target critical boundaries with minimal simulation or test runs.
Statistical Calibration
Advanced Bayesian calibration systematically tunes model parameters against physical test data, accounting for measurement noise and discrepancy.
Model Validation
Assess the agreement between simulations and physical data to establish model credibility. SmartUQ streamlines verification, validation, and uncertainty quantification (VVUQ) by aligning with standards and compliance directives from ASME V&V, FDA, DoD, and NASA etc.
Uncertainty Quantification
Comprehensive global sensitivity analysis, aleatory/epistemic uncertainty propagation, and reliability-based optimization ensure robust, risk-informed decisions.
Inverse Analysis
Infer unobservable input parameters, material properties, and operational boundary conditions by mapping backward from observed physical test responses and sensor measurements to rapidly resolve simulation discrepancies.
Bayesian Optimization
Optimization algorithms couple with SmartUQ's automated learning and advanced Gaussian process models to make optimization faster, instantly repeatable, and easily extensible to other analysis.
Run on Local Hardware
SmartUQ's advanced sampling, Bayesian methods, and modeling algorithms are efficient enough to run entirely on local hardware. This means everything can be done on existing workstations and no data leaves your system. For bigger problems, the tools can be deployed across Linux or Windows clusters.
Enhance Your Existing Processes
Modern engineering teams need SmartUQ to cut development time, curb cost, and protect product integrity—before small issues become million-dollar problems.
Simulation Acceleration & Accuracy 50–75% faster design loops
What SmartUQ does
- Advanced DOEs & Bayesian Optimization reduce runs
- Surrogate models yield instant predictions
- Statistical calibration aligns models to reality
Value delivered
- 50–75% faster design loops
- Confident design decisions early
Problems avoided
- Missed launch dates
- Costly re-work due to poor correlation
Testing Efficiency 30–60% test cost reduction
What SmartUQ does
- Minimizes test matrices without losing coverage
- Links test data to simulation for reusability
Value delivered
- 30–60% test cost reduction
- Fewer prototypes & less scrap
Problems avoided
- Bloated test budgets
- Late-cycle failures
Optimization Under Uncertainty Removes 10–20% over-design
What SmartUQ does
- Sensitivity analysis identifies critical drivers
- Reliability-based optimization reduces weight, cost, energy
Value delivered
- Removes 10–20% over-design
- Extends product life-cycle margin
Problems avoided
- Warranty claims
- Excess material & BOM cost
Digital Twins & Predictive Analytics Live health monitoring
What SmartUQ does
- Builds fast, calibrated virtual sensors
- Powers real-time twins for CBM+, prognostics, What-Ifs
Value delivered
- Live health monitoring
- Downtime avoidance
Problems avoided
- Unplanned outages
- Reactive maintenance culture
“SmartUQ has the best prediction accuracy among all tools I have ever used.”
“SmartUQ's adaptive design can significantly reduce the number of required simulations [a 72% reduction] and lead to much higher model accuracy [96% reduction in reference prediction error]”
“Our Uncertainty Quantification discipline now uses SmartUQ as its central tool and with it we have helped save millions of dollars and thousands of hours of work.”
Discover How SmartUQ Drives Innovative Solutions
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Who are We?
SmartUQ offers Industry-Scale Uncertainty Quantification
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Predictive Analytics
SmartUQ: Predictive Analytics for Engineering and Physical Sciences
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What is Uncertainty Quantification?
Manage your risk with SmartUQ
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Why Uncertainty Quantification?
Gain the competitive edge with your analytics
Upcoming Events
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When Simulation and Reality Disagree: Statistical Methods Explain Why
Japan/Korea Time: Thursday, November 19 11:00 AM – 12:00 PM (JST/KST)
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When Simulation and Reality Disagree: Statistical Methods Explain Why (30 Minutes)
North America: Thursday, November 19 9:00 AM - 9:30 AM CST
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When Simulation and Reality Disagree: Statistical Methods Explain Why (60 Minutes)
North America: Thursday, November 19 1:00 PM - 2:00 PM CST