RESOURCE LIBRARY

This webinar presents how modeFRONTIER robust and reliability-based optimization capabilities can be applied to avoid opting for designs that perform well on paper, but under-perform in real life. Danilo Di Stefano (Product Manager) and Alberto Clarich (Technical Manager) introduce the Quality Engineering module available in modeFRONTIER. They present how robust and reliability-based optimization can be applied to leave out designs that perform well on paper, but under-perform in real life. Quality Engineering allows to perform a robust analysis in those cases where the variable is affected by a non-probabilistic deviation, or noise. Agenda: ROBUST DESIGN & RELIABILITY - Manage uncertainties with ESTECO technology QUALITY ENGINEERING - A new Robust Design method available in modeFRONTIER modeFRONTIER PLANNER - A modular interface to set-up design exploration, optimization and robust design campaigns easier

This webinar demonstrates the benefits of a server-based Multidisciplinary Design Optimization (MDO) approach and Simulation and Process Data Management (SPDM). With a server-based approach, large MDO workflows can be easily managed and collaboration can be stimulated through a modern web interface which is accessible anytime, anywhere. On the execution side, a server-based approach offers many advantages related to distributed execution enabling hybrid compute infrastructures. SPDM is an important aspect of server-based MDO since it manages the ownership, version control and permissions of all the data and models needed to build and execute complex workflows. With SPDM, MDO becomes a team effort instead of an ‘expert-only’ exercise. Workflows can be quickly upgraded or rolled back to a known state, simplifying the debugging and editing process.

This webinar explains how to create a response surface or mathematical model that can be used to predict the results of a new set of experiments, without having to execute those experiments. This technique is especially useful for computationally expensive simulations such as 3D FEA or CFD, where runtimes of hours or even days can be reduced to seconds. Watch this webinar and learn more about the importance of response surface modeling in simulation based design, the various algorithms and strategies of implementation.

This webinar showcases how to perform Parametric Optimization in modeFRONTIER. Parametric optimization is a computer algorithm driven automated process that modifies the problem parameters to find the optimum, or Pareto set of optimums, within a predefined design space, taking objectives and constraints into account. This iterative method allows simulation based design processes to be driven to achieve predefined targets, or to minimize or maximize certain performance characteristics. Watch this webinar and learn more about the importance of parametric optimization, the different algorithms used, strategies and some representative industrial cases.

This webinar hosted by ESTECO and TXT company PACE, demonstrates the added value of combining their technologies for a server-based optimization of an EXPEDITE (EXPanded MDO for Effectiveness Based DesIgn TEchnologies) derived preliminary aircraft design. Taking an EXPEDITE-like modern aircraft conceptual design as a baseline, the webinar showcases the advantages of creating a smart, reconfigurable aircraft model with PACE's preliminary aircraft design platform Pacelab APD and integrating it in modeFRONTIER parametric optimization to identify the optimum solutions, based on constraints and performance requirements. Watch this webinar and learn more about how to implement this methodology in an international context, consisting of distributed teams and the extended enterprise.

This webinar explores the possibilities of the use of modeFRONTIER and DEP MeshWorks to accelerate the design process in the biomedical field. Medical devices community needs to adopt faster go-to-market strategies to go from conceptual design to market deployment. Virtual engineering and virtual testing become one of the key factors that enable this speed of development. Engineering simulation enables design, development, and analysis of these complex medical devices with great accuracy. Mathematical techniques such as numerical optimization and machine learning further enhance the design process by allowing the identification of robust and optimal solutions in a short time. ESTECO North America and Detroit Engineered Products (DEP), specialized in model parameterization, explain the value of optimization and response surface modeling in simulation-based medical device development.

The role of innovation in the automotive industry has emerged as a key factor, with companies shifting their revenues from well-established models to new ones. This white paper illustrates how Ford Motor Company achieved streamlined, multi-user design process management by expanding its Multidisciplinary Design Optimization (MDO) approach at enterprise level with the ESTECO technology. Specifically, the deployment of the ESTECO platform for Simulation Process and Data Management (SPDM) made it possible for Ford engineers to: process and generate large quantities of designs very quickly, assure the immediate impact of results on vehicle design from the earliest design stages, provide a wealth of data from which several useful design alternatives could be explored.

Whether you need to start understanding your engineering problem or you work under strict timelines, you can embrace our AI-based Autonomous Optimization approach and focus on the improvement you want to reach without any setting required.

Using modeFRONTIER coupled with Rocky DEM to design a better deflector while saving up to 130 hours of computational time The Arvedi Group turned to the University of Trieste to find a solution to the uneven material distribution inside the hopper of the blast furnace in Trieste, Italy. The Mechanical Engineering Department investigated the problem and used modeFRONTIER to optimize the design of a new deflector ensuring a better distribution of the materials. Exploiting the ESTECO integration and process automation technology they coupled modeFRONTIER with Rocky DEM software to accelerate the simulation process of the material distribution. Using the proprietary algorithms available in modeFRONTIER, they were also able to find the optimal design for a new deflector. ## Challenge The project concerned the charging process of coke coal and iron ore inside the hopper. The different materials formed piles and pitches, leading to a lower performance of the plant. The uneven material distribution inside the hopper caused variations in the temperature profile, gas flow, and gas composition. To solve this problem modeFRONTIER was coupled with Rocky DEM to get a better understanding of materials behavior and optimize the design of the deflector. The integration with modeFRONTIER also allowed to meet the time constraints, reducing the computational time for each simulation. ## Solution This project was developed in two phases. The first phase concerned the calibration of Rocky DEM parameters and the simulation of hopper charge. The second phase consisted in optimizing the geometry of a new deflector for the charging process.For the calibration process, they used the parameters of Discrete Element Method as inputs in modeFRONTIER, such as particle- particle static friction and rolling resistance. The repose angle of simulated material was used as output. For the device optimization, a sensitivity analysis with Uniform Latin Hypercube allowed to run 90 designs and identify the most important design variables. Engineers then optimized three different geometries, taking these geometrical variables as inputs. The outputs were based on the material distribution, calculated by virtually splitting the hopper into 12 sectors and performing statistical analysis on the particles found in each. These values were used to define the two objectives and the constraints of the optimization. They used the ESTECO proprietary pilOPT algorithm to run the three optimization studies. Thanks to the autonomous mode they could evaluate more than 1000 designs in just a few weeks, without having to set any parameters and with remarkable benefits in terms of time. Benefits Thanks to a user-friendly graphical user interface, modeFRONTIER helped automate the simulation process. Without modeFRONTIER, engineers would have had to manually change the geometry of the deflector for every simulation, with significant waste of time. With modeFRONTIER they were able to save up to 130 hours of computational time. Finally, by automating the process, design engineers could launch the optimization and avoid the painstaking process of manually combining the output from multiple applications.

Perfect your design by choosing among a complete set of intelligent algorithms. With the modeFRONTIER Planner modular environment you can create your DOE, RSM-based and optimization studies in an assisted way and focus on your engineering goal.