a new era in machine learning

Engineering

PI probaligence gmbh

Boost your Simulation with STOCHOS

STOCHOS in CAE

Machine Learning has become an important tool in the realm of computer simulation, particularly in applications involving Finite Element Method (FEM). ML techniques are employed to enhance the efficiency, accuracy, and optimization of simulations across various domains.
The integration of STOCHOS in computer simulation marks a significant leap forward in predictive modeling and analysis. This synergy empowers engineers and researchers to tackle increasingly complex problems, optimize designs, and explore innovative solutions in a more efficient and data-driven manner across various industries.

STOCHOS

Adaptive model improvement

New samples are suggested according to the uncertainty of the model

STOCHOS models can learn continuously as new data becomes available. Rather than training the model once and keeping it static, it is updated regularly to capture evolving patterns and trends.

The adaptive model improvement is especially valuable in real-world applications where the environment is dynamic, and the data landscape evolves over time. It allows ML models to remain effective and relevant in scenarios where static models might become outdated or less accurate.

Bayesian Optimization

Optimizer PI-BO

Our proprietary Bayesian optimizer PI-BO is a probabilistic model-based optimization technique used to optimize complex, expensive, and noisy objective functions. It’s particularly useful when the evaluation of the objective function is time-consuming or resource-intensive.

Bayesian optimization is particularly effective in scenarios where the objective function is expensive to evaluate, and the goal is to minimize the number of evaluations needed to find the optimum. And furthermore it can also be utilized to generate a digital twin in the most efficient way.

.

Multi Fidelity

Multi-fidelity is the utilization of models with varying levels of accuracy and computational expense. STOCHOS© only deploys high-fidelity features, that is more accurate, and computationally expensive modelling in those areas where the model uncertainty is high. By then automatically combining the information from areas with different fidelity levels into a single model, we can achieve the same  accuracy as in a fully high fidelity model in only a fraction of time. In combination with our integrated noise detection this allows real data modelling of highly complex problems even on GPU or CPU with astonishing accuracy.

Sensitivity Analysis

Always get immediate sensitivity analysis for your models to understand the weight of different parameters

STOCHOS brings a new level of transparency to machine learning by combining probabilistic modeling with automatic sensitivity analysis. It helps you understand not just what your model predicts, but why. With built-in tools for both global and local parameter sensitivity, you can easily explore how different inputs influence your results. This makes it easier to identify key drivers, assess model robustness, and support more informed decision-making—all without additional coding or complex setup.

Global Sensitivity

Local Sensitivity

Probabilistic Intelligence in Simulation

The Impact of STOCHOS on Computer-Aided Engineering (CAE)

In the dynamic field of engineering, the infusion of Machine Learning into Computer-Aided Engineering is reshaping traditional approaches to problem-solving. CAE, known for simulating complex physical systems, has found a powerful ally in ML, bringing adaptability and efficiency to the forefront.

By learning from extensive datasets, our algorithms discern intricate patterns and relationships, particularly beneficial in scenarios where traditional models struggle with nonlinearity or numerous variables.

Reducing computational burdens is another advantage of STOCHOS by approximating complex simulations, accelerating design iterations and enabling real-time decision-making in dynamic scenarios.

From optimizing designs to predicting structural integrity, the synergy between ML and CAE empowers engineers to push boundaries and innovate in previously impractical ways.

Partnership with ANSYS

Since 2022 our AI/ML algorithms are used by Ansys OptiSLang

To Ansys

Part of CADFEM Group

Since Nov 2023 we are a part of the CADFEM Group

To CADFEM Group

High Fidelity Digital Twins using AI

Simulation of complex composite structures together with DLR and SGL

To the project

A New Era in Machine Learning

PI Probaligence

Address

Social Networks

Links List

PI Probaligence GmbH

(c) 2023 All Rights Reserved