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Discover how Luna Rossa Prada Pirelli team can predict design performance for sailing yachts thanks to ESTECO modeFRONTIER simulation process automation. Luna Rossa Prada Pirelli is all set to challenge for the Louis Vuitton 37th America’s Cup. Once again on an AC75 foiling monohull and representing the yacht club Circolo della Vela Sicilia for the third time. With the help of ESTECO simulation process automation and design optimization technology, the team has tested solutions and materials for their sailing yachts, built and developed in-house at the Cagliari base on Sardinia’s southern coast, Italy. The AC75 Class has also been chosen to compete in the 37th America’s cup. It’s a high-performance monohull intended to spearhead the development of sailing through innovative technology, ensure the class is relevant to the sport of sailing and provide competitive racing in light and stronger wind conditions. The class rule defines the limits of the design space. Some parts, like the foil arm and foil cant system, are the same for every team. The AC37 Protocol also focuses on cost reduction, including limitations on the number of components: Teams are only permitted to build one new AC75 Limitations on the quantity of foils and componentry that can be built for the AC75’s Introduction of the multipurpose One Design AC40 class which teams will be able to partially convert and use for testing, component development and Match Race training Possibility to use test boat (LEQ12) with max LOA 12m Furthermore the towing tank or wind tunnel tests are prohibited. As a result, numerical simulation is a crucial and integral part of the design process at the Luna Rossa Prada Pirelli team. They analyze and optimize ideas before even seeing them applied to the yacht. The 38-member unit forms the largest design team and is divided into five units: naval architecture, structural engineering, mechanical engineering, computer engineering, and aero-and hydrodynamic engineering. Among them, there is a group of designers who use modeFRONTIER to improve the design performance of AC75 yacht components: • Matteo Ledri, Head of CFD • Simone Bartesaghi, CFD Specialist • Martin Jacoby, CFD Specialist • Andrea Vergombello, Head of VPP • Andrea Zugna, Performance & Mechatronics In addition to designing hulls, sails, and custom components, the team analyzes data from simulators and computers connected to the boat during sea training. Through synchronized collaboration with the Sailing team and the Shore team, they work daily on studying and designing solutions to enhance the boat’s performance. Foiling boats can be explained by comparing them to aircraft in case anyone has never seen one. These similarities can be useful to understand why simulation technology used in designing and testing foiling boats can draw upon decades of development in the aerospace industry. If you compare the AC75 boat to a glider, it is possible to identify the fuselage with the hull, the wing with the main wing foil, the winglet with the wing tip, and the rudder with elevator. The main difference in the case of the AC75 is that only one foil maintains the boat out of the water, so the roll balance is achieved by considering the upward force of the foil, the weight of the boat, and the roll component of the force of the sail, which is continuously adjusted to keep the boat upright. Continuing the fly analogy, regarding controls, the pitch of the boat is controlled by the rake of the rudder blade, which changes the angle of attack of the rudder elevator. Ground clearance is maintained by controlling the flap angle of the foils. The most precious commodity in an America’s Cup campaign is time, despite having a three/four year timeframe to design the yacht. This is why, when it comes to selecting tools for simulation, the design team prefers relying on proven and reliable commercial solutions. modeFRONTIER is one of those. The software offers flexibility, usability and straightforward methods for design exploration and optimization, making it possible to accomplish various automated tasks in a short amount of time. The optimization-driven design process begins with defining an objective function and constraints, followed by parameterizing the design, running an optimization algorithm, and validating the optimized solutions. ### 4.1 Hull shape optimization For the hull shape, a preliminary investigation related to raw geometric parameters linked to the AC75 rules was done to try to cover the entire design space, even with out of the box shapes generated by using input parameters from a Design of Experiments (DOE) table. Good candidates coming from a preliminary geometry optimization (rulewise) were tested via CFD hydro simulations and then the obtained data were integrated in modeFRONTIER to properly analyze the trends and compare the different solutions. By using the same approach, combining DOE exploration and direct optimization, the design space was refined in the optimum area extracted from preliminary design loops and updated at every step of the design itself. ### 4.2 Optimization of the foil section modeFRONTIER has been used extensively to perfect the design of the foil section by setting up a multi-objective optimization with genetic algorithms. The direct optimization allowed us to explore millions of possible shapes and select a family of best candidates to test and deep compare on the virtual AC75 complete model. The main goal was to minimize drag for a given lift with constraints like structural properties (stress and stiffness), cavitation, systems. Also, the process involved a parametrization based on B-Splines curves and parametric models to account for control system volume and some 3D effects. ### 4.3 Design space exploration of the wing The design space of the wing was explored exhaustively using modeFRONTIER in two main areas: bulb and twist distribution. This optimization task was very complex due to lots of constraints and objectives to be fulfilled. Regarding the bulb optimization, the requirement of a given volume to carry the required weight, the space to fit the flap system and a shape that has minimum as possible drag in all conditions. These are the constraints and objectives for the bulb optimization. The geometry generation was done with Rhino/Grasshopper and automated in modeFRONTIER to execute a DOE. Then, the geometry was sent to an HPC cluster to run a CFD analysis. In this context, modeFRONTIER enabled our team to efficiently perform this task and reduce the time to produce the optimized geometry. The purpose of Twist optimization was to find the optimum distribution of Angle of Attack of the hydrofoil section along the span of the foil. This distribution of twist angle impacts several aspects of the foil performance and behavior. You could think about the structural part, where the center of lift spanwise will impact on the stress at the root of the wing, therefore asking for higher modulus which might lead to thicker sections. Seeking performance is the main objective where the aim is to fit the 2D section at a range of AoA where the efficiency is maximized, and from a 3D hydro point of view there is performance loss due to the eddies created by the lift produced. This with an optimal twist distribution can be minimized, always monitoring how the cavitation area gets modified with the twist changes. In that complex scenario modeFRONTIER fitting capabilities enabled us to find a virtual optimum with great confidence. The twist optimization problem had big non-linearities related to the laminar-turbulent transition and with the correct settings we were able to optimize with Response Surface models (RSM) techniques and validate the optimum with excellent results. ### 4.4 RSM modeling for wave model fitting: hydro and aero Lots of challenges require CFD computations that are very costly in terms of computational power, however with the correct study of the problem, a good fitting of the CFD response can be done and then being used to reduce the need of simulations to be run. The choice of the RSM settings is of major importance, not only should be checked with validation points but also with engineer’s criteria. Later the fitting can be used to “anchor” low fidelity models that can expand the scenarios studied. Anchoring means that the expected difference between the high fidelity and the low fidelity model is studied and fitted and when that is known, it can be used to correct the low fidelity model in other parts of the design space, where a specific high fidelity simulation has not been run. Here the cases of study are the wave-resistance model of the AC75, where the URANS have been conducted at “center” sailing conditions. And, with the creation of an analytical wave model it was possible to expand the results to a very big amount of conditions that a wave scenario can have, think about wave height, wave period, angle, flight height. modeFRONTIER was used to bring up the quality of the low-fidelity model and enable us to study a broader space. modeFRONTIER has become an indispensable tool in developing the new AC75 class boat, providing the design team with the necessary optimization techniques to excel in various fields such as hull and foil design. Simone Bartesaghi, CFD Specialist, Luna Rossa Prada Pirelli says, “modeFRONTIER has helped us to improve and speed up our design process, allowing us to explore all the design space and finding unusual, out of the box shapes that we may not have considered otherwise. Based on our results from modeFRONTIER, we could quickly and effectively obtain 2D section design and optimization for foils and rudders, and even adapt them for different zones along the span of a foil or rudder. Finally, the software enabled us to create models for complex scenarios like waves interaction and aerodynamics forces for direct optimization".

Learn how ESTECO modeFRONTIER helped Delft University of Technology to perform multi-objective aircraft design optimization to compare future aviation fuels. Pieter-Jan Proesmans, PhD Candidate in the Flight Performance & Propulsion group at Delft University of Technology, used modeFRONTIER to perform multi-objective aircraft design optimization to compare future aviation fuels. ## Challenge This research has been undertaken in the framework of the GLOWOPT project sponsored by the EU’s Clean Sky 2 program, and under the supervision of Dr.Ir. Roelof Vos, associate professor at Delft University of Technology. The objective is the development and validation of Climate Functions for Aircraft Design (CFAD) with respect to minimizing global warming and their application to the Multidisciplinary Design Optimization (MDO) of next-generation aircraft for relevant market segments. To reach this goal, novel fuels, such as liquid hydrogen (LH2) and sustainable aviation fuel (SAF) can provide more sustainable solutions. However, the climate objective conflicts with the typical design objective of minimal operating costs. While these two fuels can offer a significant reduction in climate impact, they are also more expensive and have consequences for the aircraft design (in the case of cryogenic LH2 tanks). ## Solution The modeFRONTIER Multidisciplinary Design Optimization (MDO) framework was selected to investigate the climate impact reduction and operating costs for hydrogen and SAF fuel in regional, medium-range and long-range aircraft categories. The cost-optimal, kerosene-powered aircraft served as the reference case for all multidisciplinary aircraft design optimizations. The MDO process was set-up in a modeFRONTIER workflow. Its Python interface made it possible to orchestrate in-house tools for aerodynamics, propulsion, mission analysis, mass estimation and climate impact. Next, the optimization strategy was executed. The pilOPT algorithm evaluated thousands of configurations by changing airframe, turbofan engine and mission design variables to obtain the cost versus climate trade-off for all fuel types in the three aircraft categories. ## Benefits “The easy-to-use parallel coordinates and scatter matrix charts were very helpful in gaining conceptual insights. One of the key finding was that the SAF-powered aircraft are preferred over the cost-optimal hydrogen aircraft for the regional and medium-range categories. With modeFRONTIER, we could perform the multi-objective optimization and post-processing in a much faster and user-friendly way compared to when we had to rely on programming libraries. In the future, we will investigate how to combine the aircraft optimization with a network allocation routine to update not only aircraft design variables, but also top-level aircraft requirements” said Pieter-Jan Proesmans, PhD Candidate in the Flight Performance & Propulsion group at Delft University of Technology.

Learn how ESTECO world-class engineering software helped Hyundai Motor Group R&D optimize the vehicle architecture trade-offs. In the wider context of Hyundai Motor Group R&D efforts aimed at integrating engineering design, Computer Aided Engineering (CAE) and testing for vehicle development, ESTECO world-class engineering support proved itself a trustworthy partner in optimizing the vehicle architecture trade-offs. In particular, ESTECO modeFRONTIER software solution was utilized in the conceptual design phase for the next generation of Genesis luxury sedan. ## Challenge Hyundai’s architecture-driven structure conveys vehicle concept planning which takes numerous factors into account from the initial stage of development, including vehicle performance, parts sharing, standardization and even up to procurement, production and suppliers. Currently, their research engineers need to find a proven simulation-driven design technology for upcoming Electric Vehicle (EV) architecture development. To test this methodology, they took as baseline a Genesis G80 luxury midsize sedan looking at rapidly investigating and identifying the global optimum design region , focusing on mechanical package, system selection, and attribute modeling. The analysis involved components such as suspensions, fuel economy, battery, and architecture costs. Solution By employing modeFRONTIER, they could perform Trade Space Analysis (TSA) in order to identify a set of system parameters, attributes, and characteristics to satisfy the required vehicle performance during the conceptual product development phase. In practice, starting from an automated multidisciplinary modeFRONTIER workflow, they ran 3000 Design of Experiments (DOE) to rapidly evaluate all the possible vehicle configurations. For this purpose it was mandatory to build fast evaluation simulation models such as Matlab (Octave) for suspensions, Excel for batteries, RSM for the performance and so on, to get the results in a few hours. Then, they applied advanced post-processing techniques such as Clustering and Multi-Criteria Decision Making (MCDM) to group similar designs and rank all reasonable alternatives on the basis of given preferences. ## Benefits “We realized that modeFRONTIER software is the ideal solution for vehicle trade-off-analysis and optimization. After generating 3000 different vehicle configurations, we could cluster and then rank all reasonable design alternatives on the basis of user-defined preferences. This significantly accelerated our internal decision making process among all stakeholders involved in the project. We look forward to applying the same methodology for our next EV architecture development projects by also considering ESTECO VOLTA SPDM platform to foster collaboration across departments” - said James (KR) Yoon - Senior Research Engineer, Virtual MBSE & HPC AI Research, Hyundai Motor Company.

Bouygues Construction develops innovation to support companies with new construction methods and materials, while considering future usages. The main requirements for a new construction include objective measures, flexibility, industrialization, collaboration and sustainability. Moreover, customers also ask for innovative and evolving buildings. Bouygues keeps developing innovative processes together with a collaborative Multidisciplinary Design Optimization (MDO) platform, which allows the various actors involved in the project to make quicker decisions and have a crystal clear overview of the possible solutions. Cover image: courtesy of Bouygues Construction | Morpheus Hotel | credit photo Virgile Simon Bertrand (2018) Challenge A building is a prototype that is manufactured once. It’s not a functional project like a car or an airplane, where a design process can be profitable thanks to the sales volumes involved. On top of this, a building is created on site with local resources and labour, as well as environmental challenges that need to be taken into account. Engineers have to mix different disciplines such as cost engineering, methods, structure (reinforce concrete, steel, timber etc.), and building life cycle. Bouygues Construction had to take into consideration a variety of disciplines and variables to optimize building performances and propose the most adapted design to its client. ## Solution Bouygues has automated the design process of a building floor with modeFRONTIER, considering 26 input parameters such as geometry, solutions, usage specifications, structural dimensions, unit prices, and unit times of construction. The outputs were the costs, construction pace, carbon footprint. Within the VOLTA collaborative platform, engineers succeeded in implementing different construction designs and provided the most profitable and the most sustainable solutions to the building team. This was possible thanks to the seamless integration of the simulation tools currently deployed at Bouygues. This was performed in as little as two days with one engineer. “The good software is the one the designer knows and masters - explained Sylvain Géry, Senior Structural Engineer at Bouygues Construction - ESTECO Technology can easily integrate with any simulation solver. This helps when a project involves different countries and enterprises who are used to working with different tools”. Benefits Thanks to the ESTECO Technologies for process automation, design optimization and simulation data management, Bouygues fastened the simulation process and reduced the overall design project time. Engineers built multidisciplinary processes and effectively coordinated all the phases involved. They could also assess the final design performance while considering costs and carbon footprint. Moreover, the collaboration between experts from different areas and the traceability of the simulation model evolution simplified the management of the project. In the building industry there are many construction options available. “Thanks to MDO, - Géry said - we could objectively quantify the benefits of the various construction types and identify the most appropriate combination of material usage, material technology and construction workers costs.”

The ESTECO optimization technology as a way to skip any prototype phase for a hybrid-electric aircraft propeller Pipistrel, an aviation & aerospace company based in Slovenia, relied on ESTECO Technologies to design the propeller for a highly efficient, hybrid-electric aircraft. The work was part of the EU-funded project MAHEPA (Modular Approach to Hybrid Electric Propulsion Architecture), that had the aim of advancing two variants of a low emission, serial hybrid-electric propulsion architecture to TRL (Technology Readiness Level) 6. The modeFRONTIER process automation and optimization software allowed automation in the simulation process and identification of innovative and optimized designs in a limited time. Challenge Engineers at Pipistrel had the challenge to design a propeller, driven by hybrid-electric propulsion system taking into account the different conditions the aircraft meets during the four flight phases: takeoff, climb, cruise and descent. Considering speed, power and thrust requirements changing during the flight, the objective was to maximize takeoff thrust and recuperation power during descent and minimize power during climb and cruise phase. The optimization involved three stages: the preliminary propeller optimization, the airfoil optimization, and the final propeller optimization. ## Solution For this multi-phase optimization project, Rok Lapuh and David Eržen, aero-dynamics engineers at Pipistrel, used modeFRONTIER coupled with CHARM (Comprehensive Hierarchical Aeromechanics Rotorcraft Model) and XFOIL, an interactive program for the design and analysis of subsonic isolated airfoils. Benefiting from the ESTECO process automation technology, Pipistrel could automate the simulation workflows, simultaneously evaluate thousands of designs and identify innovative optimized results. This process was conducted in a fully autonomous way leaving Pipistrel’s engineers the task to select the most appropriate design. With the first propeller optimization, Pipistrel optimized the chord and twist distribution to get the maximum thrust and minimum power for a given set of airfoils. The results were then used as requirements for the airfoil optimization. The design team used modeFRONTIER to design the airfoil under specific geometry constraints (thickness, cur- vature or leading-edge radius), while increasing the lift and reducing the drag. They started a Design of Experiments phase and then used the HYBRID genetic algorithm to successfully run the airfoil optimization and get the Pareto front with the optimal designs. At last, they used the optimum airfoil for the final propeller optimization. With the ESTECO optimization algorithms, engineers at Pipistrel could evaluate almost five thousand designs in a limited time and increase the thrust by 30% during takeoff. ## Benefits Before using modeFRONTIER, Pipistrel went through a manual process to simulate multiple designs and choose the preferred one. With the introduction of ESTECO Technology, Pipistrel engineers not only were able to automate this process, but could evaluate options not considered otherwise. “modeFRONTIER optimization technology gave me the opportunity to think outside of the box - said Rok Lapuh, Aerodynamics Engineer at Pipistrel - We could find a design that is completely different from what we’re used to, but that may work even better”. They also dramatically reduced the go-to-market time as they moved from simulation directly to the production. “We trust the results we get with modeFRONTIER so much that we don’t expect we’ll require a prototype - said David Eržen, Aerodynamics Engineer at Pipistrel - We go straight into production”.

The 34th edition of the America’s Cup was a breakthrough event in the world of sailing, with traditional mono hulls giving way to the AC72 class foiling catamarans equipped with foils and wing sails. Since then, sailing and engineering teams have been dealing with a new set of challenges ranging from boat handling, tactics and, it goes without saying, the design of these new vessels and their subsystems. ## New America’s Cup regulations: a design challenge From a design point of view, naval architects and engineers have been forced to rethink their way of working and open up to other design processes and methods, like in motor racing, which has already gone through a similar shift, where regulations tend to trigger a series of small incremental changes rather than radical one-off developments. Moreover, the change from yacht to flying catamaran has revolutionized sailing philosophy, leading to constant changes in speed and boat response to conditions. This means that catamaran performance needs to be maximized by taking into consideration a whole new set of predictions and external factors. When the Luna Rossa Challenge Team started developing the concept for the catamarans in view of their campaign of the 35th America’s Cup, it opted to implement design process integration and automation routines. The limitations imposed by America’s Cup regulations served to highlight the need for simulations and multi-domain analysis - tools that proved crucial to developing and improving the new AC62 class boats. ## The sailing modes and the need for optimization The new race regulations have brought about a multifaceted design process which requires taking into account different “sailing modes” and their respective physics in parallel. Even though the impact of the hull on overall performance at high wind speeds is practically negligible, its impact becomes significant at low-to-medium sailing speeds. Whereas in displacement sailing mode, the hull is fully immersed and more than 80% of the lift is due to the buoyancy of the hull, in skimming sailing mode, wind intensity makes the boat to start flying, resulting in a reduced effect of the buoyancy to 20% of the lift force. In foiling mode, at high wind speeds, the hull is completely out of the water and the catamaran sails on foils, reaching 30 knots upwind and 50 knots downwind. Analysts therefore need to consider both hydrodynamic and aerodynamic drag when switching from one mode to another, meaning that the higher the number of different configurations in terms of hull, foils and wings considered as design alternatives, the higher the probability of enhancing the performance of each mode. Moreover, given that regulations prevent the actual sailing of 62-foot catamarans until around five months before the competition, most of the important early design decisions are necessarily based on data taken from simulations. The highly sophisticated design skills needed and the different disciplines involved in the design make performance prediction harder, leading to the conclusion that the use, coupling and automation of simulation tools in the design process are indispensable. Add to that the sheer number of variables, constraints and objectives involved and it becomes obvious that a trial and error approach is unfeasible. These considerations led the Luna Rossa Challenge Team to adopt modeFRONTIER as its automation and numerical optimization tool of choice, ensuring an integrated design approach from the earliest stages of the catamaran design process. ## The Design Program Hull shape optimization As mentioned earlier, the hull is still a crucial element in the design of the boat. In the first stage of the design process the team decided to focus on the hydrodynamic analysis, considering the displacement and skimming modes. It is in pre-start phase when the hull shape affects performance the most as the boat accelerates from an almost static condition to reach peak speed and in some of the maneuvering conditions where the wind is not strong enough to make the boat fly. To optimize the hull shape taking into account the two sailing conditions, the team developed a hull shape generator to simulate the response for each variation and calculate the drag considering exclusively the shape. Michele Stroligo, CFD Analyst at Luna Rossa Challenge, set up the logic flow with modeFRONTIER to drive the design investigation and optimization of the hull shape. He first prepared VBA macros in Excel to generate the set of control points and splines. These were then transferred to Maxsurf to create the surfaces and return a geometry file as output. CFD simulations were then computed with STAR CCM+, analyzing a single hull 3D geometry with a time-dependent simulation where the boat was free to sink, moving from the hydrostatic to the dynamic equilibrium. “The automatic process was developed using modeFRONTIER, taking advantage of the Excel direct integration node, and two scripting nodes piloting the Maxsurf routine and the execution of CFD simulations on a remote cluster. This set up enabled us to use up to 400 cores for each design, significantly reducing the computational time from 10 hours to about 40 minutes” says Stroligo. The results from the first design step showed a reduction of drag of the order of 2% in displacement mode and of 18% in skimming mode. A single-objective process was used in the preliminary phase, where the cost function was weighted on each of the two computed conditions making this solution a compromise between the two scenarios. In the second step, the use of a multi-objective approach gave the advantage of making the solution independent from the user defined weight, imposed previously. The geometries generated during this second optimization study ensured better results for the combined displacement and skimming conditions. Moving forward, the team wanted to make sure that even during dynamic acceleration and take-off, the new candidates would bring about the same improvements when compared to the reference hull shape. With this in mind, the team performed a series of acceleration tests using a mathematical model that simulated wing and sail loads and the related force that pulled the boat in order to determine the time needed to switch from skimming to foiling mode. An appended hull configuration was used (hull, daggerboard, rudder and elevator) for these simulations. The angles and extensions of the appendages were the same for both cases. The comparison between a baseline hull and an optimized hull is shown in the chart below. As highlighted in the image above, the optimized hull (right) confirmed its superiority also during accelerations and take-offs, enabling the catamaran to begin the foiling phase about 5 seconds earlier, giving an advantage in terms of speed, distance traveled and agility. ### Foil optimization The other major task of the design program at Luna Rossa Challenge was to maximize performance during in foiling mode. The use of daggerboards - or foils - enables boats to lift both hulls out of the water and “fly” in medium and high wind intensity. From a physical perspective, foils must ensure a sufficient upward lift force - approximately equal to the weight of the boat - as well as a high horizontal force to counteract the side force generated by the wing sail and jib. At the same time, the drag and roll moment had to be minimized. To be complete, the analysis also needed to take into account constraints coming from rule specifications, structural behavior, cavitation limitations and stability criteria. “At Luna Rossa Challenge, we managed to setup a workflow that helped us explore a very wide range of foil shapes in an attempt to identify the optimum shape for given targets (drag, heeling moment, VMG…) and subject to a number of constraints (rule compliance, structural, cavitation, stability….). In this way, the exploration became fully automatic, resulting in significant time savings” says Giorgio Provinciali, Velocity Prediction Program (VPP) Leader, in charge of the foil design. The optimization workflow for the foil was built by integrating a Rhino 3D/Grasshopper model to generate the parametric 3D geometry; a CFD code (Panel code / Ranse) then evaluated the hydrodynamic performance. The geometry generation was driven by a script defining – among others - the following parameters: A spine curve defining the front view of the foil The leading edge shape Chord values along the span Airfoil thickness values along the span Airfoil camber values along the span Airfoil twist values along the span Airfoil sections basic shapes along the span The file was read and run by a Grasshopper script within Rhino 3D and the updated .igs geometry file was then transferred to the CFD code selected for the simulation - either the in-house panel code (DasBoot) or Ranse (StarCCM+). When the panel code was used, leeway and rake capable of achieving a target lift and side force were sought for different speed values. Whereas with the Ranse code, the simulated values for leeway and rake were interpolated to find the target lift and side force at given values of speed. The optimization objectives were drag and roll moment minimization at different speeds determined by the upwind and downwind sailing configuration for a given wind condition. These conditions were estimated by weighting each wind condition with the expected wind distribution at the competition venue. All inputs, geometrical variables, constraints and objectives were defined in the modeFRONTIER workflow. To successfully handle the highly constrained physical problem and efficiently explore the design space, the team opted for a combination of the ESTECO proprietary HYBRID and the NSGA II genetic algorithms. By taking advantage of the internal and automatic RSM computation of HYBRID, execution time was reduced even further. Despite the pervasive constraints, the algorithm was able to find feasible and efficient solutions and identify the Pareto front, balancing the optimal solutions for the two objective functions. “The post-processing tools available in modeFRONTIER gave us a good grasp of the most important parameters impacting the objectives and their correlation. Even more so, these advanced tools clearly highlighted the design trends, putting us in the right direction for more detailed investigation. ### Benefits and conclusions The America’s Cup regatta showcases the best sailing and engineering teams in the world who push design and vessel performance to the limits in their aim to win the coveted competition. Relying on design and simulation tools has become unavoidable; however, choosing the technology that serves as a true enabler of a designer’s ingenuity is still an invaluable source of advantage against other teams. As highlighted in the case studies, modeFRONTIER gave Luna Rossa specialists four key advantages: the automation of the design processes, the seamless integration of the software chain, the effective exploration capabilities of its proprietary algorithms and – boosting the efficiency of the whole simulation process - the flexible handling of distributed computing resources. By integrating and automating the multiple tools, engineering team was able to let the complex, multi-disciplinary simulation workflows run autonomously and simultaneously consider several physical aspects while having more time to focus on design analysis, post-processing of results and in-depth decision making. The intelligent design space exploration and optimization capabilities of the algorithms combined with the efficiency of using a distributed computation set-up helped reduce the development time and quickly delivered prototypes to be tested by the sailing team. By running parallel simulations on a network of computers using the modeFRONTIER Grid Tool, designers found better solutions with a reduced number of iterations made by the robust algorithms. Further steps of the design program at Luna Rossa aim to include the other disciplines (structures and aerodynamics) as well as other modeling approaches (VPP simulation, race modeling program, wing sail optimization, and boat handling) in the process. Provinciali concludes that “working on the Velocity Prediction Program (VPP) and race modeling within the foil design optimization workflow would allow us to optimize boat performance by also considering the race track and the wind conditions expected at the AC venue.” Stroligo points out that “sensible reduction of parallel simulation execution in this perspective gives us the option to add robustness in the design optimization process of the hull shape taking into account the variability of sea conditions as well as focus our attention on maneuver and handling requirements”.

ABB Group, a global leader in power and automation technologies, covers almost every segment of the power generation and industrial process control market with its products and systems. With $1.4 billion in annual investments, the 8,500 engineers and scientists at ABB Research & Development are committed to meeting the automation industry’s ever-increasing demand for reducing energy consumption and improving reliability and performance. The design projects illustrated here highlight how ABB Group leverages optimization-based development to handle the complexity that electronic and software components entail. Looking at system interdependencies from the earliest concept phase is crucial for an effective strategy that aims at maximizing product performance, meeting reliability demands and easing the environmental impact of their products. ## Optimization-Based Development of Ultra High Performance Twin Robot Xbar Press Tending Robot System The industry challenge Industrial robots are sophisticated systems incorporating hardware and – increasingly – software components. Subsystem design (gearboxes, motors, sensors and brakes) and the interactions between elements such as machine interfaces, safety integrations, field buses, PCBAs, power supplies and drive modules must be carefully planned to assure the best possible performance. Over the years, cost pressures have made robots a commodity in terms of physical specifications. Among the many design challenges, the need for lighter components has resulted in reduced stiffness, making the control problem more complex. Furthermore, many third-party interfaces require integration and products that must comply to software, electrical and mechanical quality standards. ABB experience In the case of the Twin Robot Xbar Press Tending Robot System, one of ABB’s flagship robots, engineers considered 18 design variables (representing the gear torque, motor torque and motor speed) and managed objectives and constraints in modeFRONTIER, achieving a 12% energy saving, solely by varying the software components. “We optimized this robot ‘manually’ for 30 years and it is one of the most used. With modeFRONTIER we were able to identify a new design – requiring no implementation costs – bringing 12% of energy savings without compromising performance by changing only the software configuration. Obviously, this is something that can’t be done by hand – you need an optimization software to do it.” says Dr. Wappling, Global R&D Manager at ABB. ### Benefits “The ability to manage mechatronics is becoming increasingly important as simulation encompasses more and more systems and not just components: the impact of the mechanics, electronics and software all need to be accounted for.” continues Wappling. ESTECO technology keeps pace with evolving R&D needs and provides designers with a flexible environment that handles each delicate step of complex system analysis and enhancement. As seen in the example of the robot, inserting virtual control models in the simulation framework enables designers to apply the optimization approach, calibrate the software and identify zero-cost solutions. ## Multiobjective Optimization of a Medium Voltage Recloser The challenge Medium voltage reclosers now represent an important grid protection device that connects different grid sources, increase the network/grid reliability and make the implementation of self-healing and auto reconfiguration schemes for overhead lines possible. With a high level of renewable energy penetration, medium voltage networks are becoming bidirectional. Therefore, the associated switching devices must ensure the protection of newer types of power systems as well as new types of loads. The optimal design of medium voltage reclosers is therefore important in order to enable excellent switching capabilities. The switching capabilities of medium voltage recloser can be influenced by various parameters such as actuation energy responsible for opening and closing the device. Therefore, to maximize the lifetime of the recloser, it is essential to establish an optimized control especially related to the actuation energy. The goal of the multi-objective optimization is to identify an optimal actuation energy control strategy for the closing and opening operations. The solution ABB R&D Teams built a two-step optimization framework that incorporates the energy efficiency constraints by working initially on the electromagnetic actuator and directly optimizing the Finite Elements Model (FEM). The numerical simulation step was then completed with physical calibration via a Hardware-in-the-Loop (HIL) optimization process, ensuring that the whole system reaches the desired performance. During the first iterations, modeFRONTIER helped improve the FEM model by identifying the best configuration possible for the electromagnetic system, while satisfying the constraint imposed by the design boundary conditions. The parameterized FEM model created with COMSOL Multiphysics was connected to Matlab LiveLink so as to pilot all design changes automatically and control both models in sequence, leveraging the direct integration node for Matlab in modeFRONTIER. In the second step, the R&D Teams opted for the in-depth analysis of the system where modeFRONTIER was coupled both with the simulation model and with the hardware to further enhance the switching properties. The HIL framework enabled an investigation environment for the whole recloser system. Thanks to this approach, optimization can be applied to the control scheme implemented with CompactRIO/LabVIEW: after running one full closing-opening operation, data is transferred to Matlab for post processing and reinserted in the loop for the next runs. Since reducing overtravel and backtravel is extremely important for the product lifetime, with modeFRONTIER piloting the HIL system (1,500 runs with a DOE featuring selected parameters from the first optimization step), R&D Scientists pinpointed a new control scheme that enables significant extension of the product lifetime. “The identified control scheme enables up to 50% reduction of the overtravel and backtravel, enabling a remarkable improvement in terms of lifetime”, says Octavian Craciun Senior Scientist at ABB.

Funded by the European Union, the GASVESSEL project aims to prove the techno-economic feasibility of a new transport concept for compressed natural gas (CNG). ESTECO, in partnership with other industrial organizations from the energy, Oil&Gas and naval engineering fields, has developed an innovative solution to manufacture pressure vessels that are considerably lighter than the current state-of-the-art alternatives. These super-light pressure vessels enable new ship designs that have much higher payloads and dramatically lower transportation costs per volume of gas. ## Challenge Traditional pressure vessels normally used to transport liquified gas by ship cannot be used to transport CNG. This is because the relevant thickness of the ship walls required to maintain the operating pressure of 300 bar would add significant weight to the vessels, reducing their loading capacity. In fact, one of the main challenges addressed by the project is to produce lightweight pressure vessels for the transport of CNG using filament winding, which is a popular method suitable for manufacturing axisymmetric structures that are light and stiff. It involves the use of several layers of fiber-reinforced composite materials wrapped around a thin internal metal liner. ## Solution During the design phase, the material and geometrical parameters of the vessel (mainly related to the number and winding angle of the layers, the percentage of composite fibers and the liner’s mechanical properties) were considered for optimization to reduce the weight and costs while honoring the structural constraints. The winding process was physically modelled with CADWIND software to evaluate the distribution of composite layer thickness at each point of the vessel. The filament winding simulation model and the stress analysis of the vessel were then integrated in a modeFRONTIER workflow to evaluate the different solutions and choose the best designs. The optimization task, which aimed to maximize the uniformity of distribution of the winding layers and minimize their number while respecting the structural constraints of the vessel, was conducted using pilOPT, ESTECO proprietary autonomous algorithm. ## Benefits modeFRONTIER process automation and optimization capabilities enabled the engineers involved in the project to automatically evaluate thousands of gas vessel designs in just a few days, as opposed to losing weeks by doing it manually. The Bubble Chart allowed them to visualize and identify the best candidate designs among those with the lower weight and manufacturing costs. As a result, the first gas vessel prototypes, which weighed up to 70% less than the vessels not reinforced with filament winding, could be manufactured and have already been successfully tested.

Using modeFRONTIER to minimize crash deformation of an aluminum hood Honda Automobile R&D Center strives to fulfil their social responsibilities as an automaker with respect to environmental conservation, safety and quality assurance. Among these challenges, engineers at Honda employed modeFRONTIER software solution to find the optimal vehicle aluminum hood configuration in order to reduce pedestrian head injuries caused by car collisions. ## Challenge Japanese traffic accident statistics show that more than a thousand of fatalities occur every year mainly due to head injuries. The European New Car Assessment Program (Euro NCAP) is widely used to evaluate pedestrian head protection with impacts against vehicles. In addition, car manufacturers are required to reduce vehicle weight to meet CO2 emissions standard. As a result, they have increased the use of aluminum hood which guarantees 40% of weight reduction compared with steel. However, this normally demands a longer crash deformation for pedestrian protection because the energy absorption characteristics is lower than steel (low inertia and stiffness). Accordingly, aluminum requires increased clearances under the hood together with further restrictions in terms of layout structure. Combining pedestrian protection and weight reduction became a key challenge in the car industry. Engineers at Honda, focused on building an aluminum hood capable of reducing crash deformation and achieving five-star Euro NCAP for head protection. ## Solution Starting from a conventional aluminum hood with many large holes, the panel has been filled and impressed with truncated cones to increase mass and stiffness. An optimization process was created in modeFRONTIER workflow to perfect the inner embossed aluminum hood for 9 head impact points defined by Euro-NCAP. modeFRONTIER allowed to refine 15 design parameters (mainly related to mass and stiffness) to minimize the impact deformation, and automate the interaction between different simulation solvers. CATIA was used to modify the shape, while ANSA solver generated the mesh for head impact simulation performed by LS-DYNA solver. The results were then processed in LS-PrePost to evaluate Head Injury Criterion (HIC) and deformation. Benefits “modeFRONTIER enabled us to save computational time when optimizing design variables for each head impact point. Design of Experiments (DOE) analysis led to identify the impact point (No. 6) which did not meet the HIC requirements. The Multi-Objective Simulated Annealing (MOSA) algorithm was used to optimize the worst impact point. This allowed to find the best designs after few evaluations. The overall optimization process allowed to reduce 6% of the crash deformation compared to the conventional aluminum hood and satisfy HIC target values” said Osamu Ito, Assistant Chief Engineer, Technology Research Division, Honda R&D Co. Ltd.

modeFRONTIER enabled Michael Bambula of the University of Florida to run the workflow, integrate third-party software, automate the design exploration process and perform post-process analysis. The winner, Michael Bambula of the University of Florida, presented a top-notch design project, in which he achieved significant performance improvements (64.2 hp @16500 rpm) while developing a complete model for a Moto3 bike and realistic simulations that also considered the specifics of the race track. Organized in partnership with Aprilia Racing and Gamma Technologies, the competition was open to teams of undergraduate and graduate engineering students. The challenge was to improve the design of a 4 stroke single cylinder engine through multidisciplinary optimization (using modeFRONTIER) and 1-D simulation of the engine system with GT-SUITE. The competition award included an internship opportunity at the APRILIA Racing team, which counts several World Championship Awards. The goal of the project was to maximize engine power. Due to the constrained engine architecture, an optimization of the Intake/Exhaust system was performed. Gamma Technologies supplied a set of simulation tools (GT-Suite) to develop the 1-D model of the high-performance engine. Various aspects of the base engine architecture were constrained such as Bore, Stroke, Con Rod Length, Engine Speed, Max Valve Diameters, Max Valve Lift, Max Throttle Diameter, Max Compression Ratio, Non-variable Cam Timing, and Naturally Aspirated. Considering these constraints, the optimization of the cylinder filling (Wave Dynamics) was seen as the logical design direction. modeFRONTIER workflow was used to automate the design exploration process and integrate Excel and GT-Suite for computing lifts value intake and exhaust valve lift profiles and simulating the engine power output. During the development of the 1-D Engine Model there were inherently many unknowns, therefore Michael made assumptions supported by rigorous research. The design variables related to the intake/ exhaust system were automatically found by modeFRONTIER to optimize the output results: sum of engine power across engine speeds speeds from lowest to highest respectively (11500 rpm to 17500 rpm). “modeFRONTIER ran 1000 different designs that varied the input parameters. The Hybrid Algorithm did an amazing job at finding the optimum solutions based on the objective of maximizing the engine power” said Michael Bambula, University of Florida Racing Team. “The analysis went beyond just determining the most powerful engine”, continued Bambula, “in fact the final objective, aimed at determining whether a certain design is sufficient for motorsports, was to compare it to lap times. This is why it was decided that the final group of optimum results from modeFRONTIER would be simulated in OptimumLap software considering, among other assumptions, a Moto3 motorcycle model traversing the Phillip Island Grand Prix Circuit in Australia”.