RESOURCE LIBRARY

Jingyuan Yan, Ph.D in Department of Mechanical Engineering, used modeFRONTIER to develop his Ph.D research project focused on the design and optimization of the Direct Metal Deposition (DMD) process. DMD is a 3D printing process for metal, similar to welding, using powders instead of wire. It uses a continuous wave or pulsed laser to induce a melt pool on a substrate, and metallic powders are delivered into the pool via injection nozzles. The process is able to deposit different metal powders onto different locations of the powder substrate in order to manufacture multi-material parts according to user requirements at the microscale level. Despite the benefits of DMD, this process is not widely used in industry: the building powder waste, the need for reduction of energy usage and inaccurate material composition in the fabricated parts are still critical issues. The DMD system provided by Optomec was used to implement the research. During his research on DMD, Jingyuan worked on an injection nozzle designing first of all its geometry to maximize the process efficiency and investigate the relationship between the desired part’s composition and the process parameters. Jingyuan also wanted to improve the DMD process parameters considering their effect on efficiency when manufacturing multi-material parts. “In order to make the best use of powders and to minimize the laser energy consumption, we aimed at optimizing the process parameters. The bi-objective optimization problem was set up in modeFRONTIER workflow using the direct node to MATLAB. Eight design variables related to the process parameters (injection angles, velocities and nozzle diameters for the two materials as well as the laser power and the scanning speed) were set and automatically adjusted with modeFRONTIER to minimize the outputs results: powder waste and energy cost.". “The multi-objective genetic algorithm (MOGA-II)” continues Jingyuan, “turned out effective in driving the search process and identify the designs which met the constraints on the deposition of multiple materials. As we see in the scattered chart, the feasible designs show a trade-off relationship between the two objective functions. The Pareto front results, marked with green color, enable the users to rapidly select the configuration with lower powder waste.” “The calculation process took about three hours. Using modeFRONTIER, we saved about three days of calculation time compared to the traditional optimization method. In the future, the optimization method can be applied to analyze other combinations of materials used in DMD, with any powder feed rate ratio. The results will be validated with experimental tests and it will be possible to generate a database of optimal process parameters for any given condition to be reused for future DMD projects. In the long run, modeFRONTIER can help tailor the process parameters during the DMD manufacturing of functionally graded parts, in order to get an accurate material composition as desired.”

modeFRONTIER helps the astronaut-like researchers develop system models for sustainable living on Mars, in particular in terms of waste reduction and sustainable lifestyle. Hawaii Space Exploration Analog and Simulation (HISEAS) is a NASA-funded research project aimed to help determine the individual and team requirements for long term space exploration missions, including travel to Mars. HI-SEAS V is an 8-month Mars analog isolation mission that begun on January 19th, 2017. Two 8-month missions are scheduled starting in January 2017 and 2018. During the HI-SEAS Mission V, six researchers are studying human behavior on Mars by entering in a geodesic dome in the isolated environment of Mauna Loa volcano on the Hawaii Big Island, including 20-minutes delayed communication and partial self-sufficiency. The purpose of Campaign 3 is to directly address the IRP Team Risk: “Risk of Performance Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team”. Ansley Barnard is the Engineering Officer for Mission V. She is in charge of monitoring their life support systems and fixing things that break down. “On a space mission, the astronaut crew is very limited on what they can bring with them. Launch mass (fully fueled) is highly valuable, so every item you send on a rocket needs to be weight and size efficient, including food, water, research materials, and personal effects. When you are traveling far away, like a manned mission to Mars, you need more supplies and you have to burn more fuel to get everything there - this makes resource optimization even more challenging”. “Parametric modeling and optimization software tools like modeFRONTIER provide us with faster and more robust ways to optimize. It is possible to find trends that your human eyes might have missed, which can yield better solutions in less time. modeFRONTIER is an easy to learn tool with a lot of built-in capability and modular flexibility. It is possible to tailor the software to specific needs, and the modeFRONTIER support people have always been helpful when I feel stuck”. Moreover, our resources are limited and we have to use them wisely. If we run out of something before we are resupplied, we have to find a way to make do. Sustainable living is important to me on a personal level and is a big motivator for me to use an optimization approach in my engineering work. While in the habitat, I am hoping to learn more skills about efficient living, like using less water and power by making active choices in how I cook, shower or do laundry. These are real skills I can bring home with me. Just like in space, each of us can balance what we use with what resources are available if we have a curious and observant eye. Tools like modeFRONTIER can help us model systems, but changes are carried out through our actions. By building parametric models of our life support system, I hope to balance our resource needs and find ways for the crew to have energy and water available for all our research and personal uses. My goal is to make a tangible difference in how my crewmates live day-to-day in our mission and provide future HI-SEAS crews with updated engineering information on the habitat life support systems.

Toyota has virtualized a significant portion of its calibration and testing process, reducing dramatically the development time and man-hours dedicated to it. Mr. Goh [Project manager, TMC Laboratory Automation System, Toyota Technical Development Corp.] and Mr. Goto [Group Manager, Power Train Company, Engine Management System Development] talk about the benefits of using automated Design Exploration techniques to verify actuator responses and identify the best control values. “It’s easy to find the optimal control value for a single actuator but when looking to improve EGR, supercharging, VTT, direct injection, etc. With the number of actuators and consequently of the output variables and constraints, manually identifying the optimal control values would require a massive amount of time due to measurement tasks.”, says Mr. Goh. ## Methodology To test the engine, temperature and pressure sensors, torque and fuel consumption (gauge) meter and exhaust gas analyzer are installed and the control systems are implemented accordingly. The combined software iTEST and ORION – the automated control and measurement system for engine bench test implemented at Toyota – manages the controls equipment and collects the output from each instrument. These values are then validated by checking the reference maps. The complexity of the calibration procedure is streamlined by including modeFRONTIER in the process, directly integrated with ORION – that is used for automatic measurements. This replaces all the manual measurement tasks conducted at the engine test bench (laboratory) and relieves the team from the burden of the repeated iterations between the “design room” and the “laboratory”, where now measurement, modelling and accuracy evaluation can be automatically repeated. “To understand the output trend and find the optimal solution with experimental points, we used mFC to create a Design of Experiment, measure data, train and compare metamodels (RSMs). The next step of the process consists in determining the optimal Engine Control Units maps and finally test again on the real engine.” “mFC succeeds in reducing the difficulties experienced by calibration engineers when using tools for model-based calibration by providing a dedicated graphic interface to directly set parameters, lower and upper bounds. mFC automatically generates designs and RSMs, then iteratively evaluates the accuracy levels and stops the evaluations when the target model accuracy is reached.” Mr. Goh says. Since real engine test is influenced by the variability of control variables and by measurements error, sometimes the combination of temperature, pressure and torque cause the stop of the testing for safety reasons. ## Benefits By using a visual filter in mFC, this issue is easily identified and the DOE is automatically substituted with a more suitable dataset. “In any case, during the evaluation, it is easy to stop mFC and change the DOE. Given certain scenarios, with this technique we can reduce the number of evaluation by 50%” Mr Goh says. This method empowers the system engineering process by adding the capabilities of simulation and automation in the right side of the V-cycle, the experimental evaluation phase of the Verification and Validation model, where is hardly used. ESTECO modeFRONTIER technology has been widely used in the engine modeling phase, in combination with GT-SUITE. Mr. Goto says that by reciprocally using optimization result as continuous feedback between the design and testing phases, there is great potential for further accuracy improvement. “By performing optimization with real engine data, we can leverage the efficiency and accuracy gained during the testing back in model design. Thanks to the common use of both data and models, designer and calibration experts can work together and further improve our operations” concluded Mr. Goh, stressing collaboration among experts as a major benefit of this technology.

ESTECO and Enventive Engineering Inc. present the integration of modeFRONTIER, Enventive®, and Ansys Workbench to optimize the shape of an electrical connector. ​In this webinar Alexander Duggan ( Senior Application Engineer, ESTECO) and Kristin Dawson (Product Manager, Enventive Engineering, Inc.) demonstrate using Enventive® to analyze variation of the forces and friction between a pin and connector, coupled with using Ansys Workbench to determine the stress in the connector as it is deflected by the pin. By integrating Enventive® and Ansys Workbench, modeFRONTIER can optimize design parameters to ensure that the pin insertion force and contact reaction force fulfill design requirements while ensuring that the stress in the connector component does not exceed the yield strength of the material. Agenda: ANSYS Workbench for finite element analysis (FEA) Enventive's force and dimentional variation analysis modeFRONTIER integration with Enventive and ANSYS Workbench

​In this webinar Alberto Clarich (Technical Manager, ESTECO) presents the modeFRONTIER 2016 approach of dealing with uncertainties is based on Multi-Objective Robust Design Optimization (MORDO). This consists of investigating the noise factors in the neighborhood of a sample design with a given probability distribution. While tackling optimization within manufacturing process, engineers face uncertainty with regards to design variables and problem parameters from various sources. These uncertainties impact the optimization process both in terms of reliability and in terms of robustness. Using modeFRONTIER, this case applied a multi-objective optimization algorithm to optimize mean values while minimizing their variations. Highlights: Theory and real world applications about Robust Design and Polynomial Chaos Efficient methodologies for large number of uncertainties Robust Design Optimization and Reliability-based Optimization

​In this webinar Alberto Clarich (Technical Manager, ESTECO) and Giulio Cassio (Application Engineer, ESTECO) demonstrate how modeFRONTIER provides new advanced features for project complexity handling: a dedicated panel for workflow setting (Workflow Global Properties), the Design Space Node, the improved Subprocess Node and many more. Watch it and learn how: Automate the execution of complex chains of preprocessing and simulation tools with modeFRONTIER. Take advantage of the very flexible workflow and the wide range of direct integration nodes for the most popular simulation tools. Optimize your design choosing among of innovative algorithms to determine the set of best possible solutions combining the complex set of opposing objectives.

This webinar, cohosted by ESTECO and Ansys, demonstrates the benefits of using the new integration between Ansys HPC Parametric Pack and modeFRONTIER 2016 by presenting the results of two industrial application in the automotive field. Why watching this webinar? This webinar give insights on how to better leverage company's private cloud or HPC systems for faster simulation analysis. The case studies will show how to make the use of computational resources more efficient and save time with the joint use of the newly released modeFRONTER 2016 and ANSYS WB HPC Parametric Pack, that will make design optimization projects execute faster.​ ​​The first application was developed by BorgWarner Morse system and EnginSoft, dealing with the optimization of a tensioner arm. The second case study is aimed at improving the design of heat exchangers and part of an EU funded project, OptimHex.

​This webinar presents a smart combination of modeFRONTIER with the PowerFLOW Suite.​​ ESTECO and Exa integrate their software platform to serve the automatic creation of highly accurate RSM models purpose. The combination of the adaptive sampling of the new modeFRONTIER ASF algorithm and the Exa's high-performance simulation and visual flow analysis tools leads engineers to an enhanced understanding of trends seen in the generation of new design options. Watch this webinar to learn more about: A smart filling strategy of ASF perfectly to create automatically of highly accurate RSM models purpose. How CFD analysts and designers can fully exploit the advanced prediction capability of Exa's PowerFLOW and obtain high-fidelity simulation of real-world flow conditions without compromising geometric detail for a smaller number of significant and better performing designs.

In this webinar, Danilo Di Stefano (Product Manager at ESTECO) and Alberto Clarich (Technical Manager at ESTECO) demonstrate the newly added RSM Trainer Node, and how to combine it with the innovative Adaptive Space Filler (ASF) and other analytics tools in modeFRONTIER. RSM-based optimization is an excellent strategy to manage heavy simulation processes: by acting as surrogates of simulation models, RSMs let engineers fast-run the classic optimization process. Why watching this webinar? This webinar give insights on the advanced RSM capabilities included in modeFRONTIER Discover the new automation of RSM training and learn how to re-use the model both for the same workflow and other projects​​ Find out how the new Adaptive Space Filler combines state-of-the-art space filling strategies with the predictive ability of response surfaces. Get to know two real-world case studies leveraging modeFRONTIER RSM capabilities

​In this webinar ESTECO, TASS International and Jingwen Hu from the ​University of Michigan, as guest speaker, present the successful integration of their technologies to optimize a rear-seat restraint system considering a diverse population.​​​ Together they will present a project where the rear seat restraint systems was optimized for 6 to 12 year-old children, adults and infants through sled tests and computational simulations leveraging the integration within MADYMO and modeFRONTIER. Watch this webinar to learn more about: The integrated use of MADYMO and the optimization platform modeFRONTIER​ How modeFRONTIER and Madymo helped the University of Michigan Transportation Research Institute biosciences group simultaneously improving the rear seat occupant protection for all age groups.