A Detailed Overview of All New Features in EikoTwin Version 2026.1: Three Major Core Upgrades—Python Programmability, Batch Processing Automation, and Independent Marker Tracking
Release time:
2026-03-04 17:57
Source:
In early 2026, a leading enterprise in digital image correlation (DIC) technology EikoSim The annual Echo Day online seminar was held, with the company’s co‑founder… Florian Macher With the Technical Lead Renaud Gras Together, we have unveiled the full suite of new features in EikoTwin 2026.1. This article draws on the software’s introduction during the seminar and provides a comprehensive overview of the latest technological developments and industry practices in the DIC field.
01 — Company Vision Bridging the Gap Between Testing and Simulation
EikoSim’s Core Mission and Product Portfolio
EikoSim has long been focused on a core proposition: Enable physical test data to truly “communicate” with numerical simulation models. Through digital image correlation (DIC) technology, the company precisely aligns and quantitatively compares the full-field deformation data collected during experiments with finite element simulation results, helping engineers extract maximum value from every test.
Our goal is to ensure that we derive maximum value from testing, validate the reliability of simulation models, and enable customers to rely on proven simulations to make trustworthy engineering decisions even in scenarios where physical testing is not feasible.
— Florian Macher, Co‑Founder of EikoSim
At present, EikoSim’s product portfolio has formed a complete closed loop:
- EikoTwin DIC — Core Image Processing and Simulation Alignment Comparison Engine
- EikoTwin Digital Twin — Simulation Model Optimization and Parameter Identification Driven by Test Data
- EikoTwin Vision — Image Acquisition, Camera Control, and Multi-Sensor Synchronization
- EikoTwin Virtual — Predicting Complex Test Scenarios and Optimizing Camera Placement
02 — Release Version EikoTwin 2026.1: Three Major Core Upgrades
Python: Programmability, Batch Processing Automation, and Independent Tag Tracking
Python API — Ushering in the Era of Programmable DIC
The most anticipated new feature in version 2026.1 is the brand‑new Python API. Users can now directly communicate with EikoTwin’s database via the Python console, enabling:
- Create Custom Sensors and User Fields
- Read and manipulate grid, displacement field, and terrain field data.
- Execute custom post‑processing calculations and write the results back to the database, then visualize them directly in the 3D window.
- Export processing results in various formats, including CSV and ODB (Abaqus).
The Python API empowers us to develop entirely new post‑processing capabilities. Crack propagation monitoring and crack detection are already areas being discussed with customers, but you can imagine that nearly any type of custom analysis can be realized through it.
— Florian Macher, Co‑Founder of EikoSim
Batch Processing Mode — Fully Open
Batch Mode, which had previously been offered only as an add‑on feature, has now been officially integrated into the main version—all… EikoTwin DIC All customers can use it. Through JSON configuration files, users can define complete automated processing pipelines—including calibration, displacement calculation, strain analysis, and data export—while supporting batch processing for multiple projects and automated, overnight execution via the command line, laying the foundation for deeply integrating DIC into industrial automation workflows.
Marked Tracking Independent Workflow
The new version allows users to perform marker point tracking and displacement measurement directly, without having to run a full-field DIC analysis. Previously, marker tracking had to be tied to a DIC measurement region; now, marker points can operate as completely independent measurement objects, greatly simplifying the workflow in certain specific scenarios.
More new features
- Meshless DIC (Automated Meshing) — No need to import a simulation mesh; you can directly draw ROIs on the camera view and automatically generate a pixel grid.
- Added CAE format — LS-DYNA and MSC Nastran (a joint achievement with Hexagon)
- Interface Optimization — Numerous UI/UX detail improvements
03 — On-Site Demonstration Practical Demonstration of Four Core Features
Demonstrated on-site by Technical Director Renaud Gras
Demonstration 1: Independent Marker Tracking
Taking the toolbox motion with three landmark points as an example, we provide a complete demonstration of the new workflow: load stereo images → perform stereo calibration (including error assessment: re-projection error, epipolar error, and reconstruction error) → detect landmarks and perform 3D reconstruction → compute and visualize displacements. Throughout the entire process, there is no need to load simulation meshes; stereo time-series analysis is carried out solely using calibrated images.
Demo 2: Hands‑on Practice with the Python API
Building on the marker tracking project, a live demonstration was conducted showing how to use the Python console to: read displacement data from three markers → calculate the mean of the three markers at each time step → create a new sensor and write the data to the database → plot the mean curve in a chart. The demonstration further showcased the ability to manipulate grids and displacement fields, create user-defined fields, and visualize them in the 3D window.
Demonstration 3: Meshless DIC Analysis
Using the rigid body motion dataset from the DIC Challenge (organized by IDICS), we demonstrate a complete workflow—from ROI delineation to automatic mesh generation, 3D reconstruction, and displacement field computation—without the need for prior mesh import.
Demonstration Four: Batch Script
It showcases JSON batch processing templates released with each version, covering complete parameter configurations for calibration, displacement calculation, and export, and supporting the sequential execution of multiple projects.
04 — Ecological Expansion New Plugins, Hardware Products, and Digital Twin Updates
Moving from a software company to a provider of integrated software and hardware solutions.
Experimental Modal Analysis Plugin (Newly Released)
The brand‑new Experimental Modal Analysis plugin can automatically extract the frequencies and mode shapes of vibration modes from DIC time‑series data. Designed for vibration analysis applications, it allows users to obtain mode shapes and frequency components over regions of interest. Currently in its first release, EikoSim is offering several months of free licenses to users who are interested in testing it.
Hardware Product Line Expansion
- EikoTwin Vision Improvement — Major UI/UX optimizations, supporting quick calibration directly within the software; added support for National Instruments data acquisition cards (external sensor data acquisition + camera triggering).
- Speckle Roller — Suitable for preparing planar, small‑size speckle patterns on tensile specimens and other similar applications, available in multiple specifications.
- Large Speckle Template — A silicone/polymer film template of up to approximately 1 meter, used for speckle spraying of large components.
- Mobile Workbench — Integrated DIC experimental workstation, featuring integrated device storage, a rotatable display, and an NI data acquisition card.
EikoTwin Digital Twin Update
- Fine Boundary Condition Control — Supports node-to-node boundary condition mapping and through-thickness stretching.
- Improved Sensitivity Analysis — Integrate doctoral research findings to enhance the reliability of parameter identifiability assessments and improve analytical stability.
- Linux Support — Core computing engine for Linux, compatible with the SLURM job scheduling system, and capable of running on HPC clusters.
05 — Product Roadmap Future Development Directions for the Next Year
Next-Stage Development Priorities Introduced by Renaud Gras
- Measure the confidence region — Visualizing the confidence interval for measurement results based on stereo calibration errors
- Multi-Time-Base Sensor Management — Unified management of full-field measurements, point sensors, and simulation data with different sampling rates.
- Identification Strategies and Validation Tools — Continuously integrate cutting-edge academic research findings
- CAE Solver Compatibility Extension — Further enhance support for mainstream solvers such as ANSYS and LS-DYNA.
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