Digital Twinning with STKO

STKO is part of a perfectly integrated solution to digital twinning. Scroll down the page to learn more about our system and how STKO can help you monitor your structure.

The Advantages of STKO

Using STKO for the creation and maintenance of your digital twin has a lot of benefits. To learn more about STKO and MonStr, click the button below and explore the ASDEA Hardware Website.

ASDEA Hardware

Harness OpenSees

The software used to process and analyze the FEM model digital twin of your structure is a crucial factor in the development of a digitial twin. STKO uses OpenSees solvers to analyze the models, and supports advanced micro-modeling techniques capable of representing the minute specifications of the structure.

Predict and Plan

Using STKO, the model in its current conditions can be tested under a variety of scenarios, including earthquake simulations, which can help predict suitability of disaster response plans, or aid in the creation of optimized plans.

What-if Analyses

The FEM model can be used to predict and plan maintenance interventions and even run simulations on the effectiveness of different repair scenarios, saving time and money.

A Winning Combo

A digital twin is only as useful as the software processing and analyzing the data. When you choose ASDEA for your digital twinning needs, you get the analytic capabilities of STKO.

The System

Monstr Sensor nodes are placed on the structure in locations determined using OSP (optimal sensor placement). They are fitted with a variety of sensors designed for use in structural health monitoring scenarios. Data is collected, stored, and analyzed. Round-the-clock monitoring generates massive amounts of data and irregularities that contaminate the data set. Our system cleans the data of noise using specially developed AI algorithms. The Digital FEM twin model is continuously updated to reflect the data and detect structural anomalies, giving a holistic view of the health of the structure. The data is processed using the OpenSees solvers in STKO, and the database and results can be interacted with using the dedicated Python interface.