Connecting simulation to the digital thread is the next big step for engineering teams to unleash the full potential of simulation across the product life cycle. Connecting simulation to the digital thread is the next big step for engineering teams to unleash the full potential of simulation across the product life cycle. In this eBook, we demonstrate how the ESTECO VOLTA platform for Simulation and Process Data Management and Design Optimization enables organizations to take full control of the engineering design process, from simulation workflows to high-level business decisions.

As the Luna Rossa Prada Pirelli prototype was getting ready to sail the waters of Cagliari, Italy, we took a moment to interview Matteo Ledri, Head of CFD, and Andrea Vergombello, VPP and CFD Optimization of the Luna Rossa Prada Pirelli Team.

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”.

This webinar demonstrates how to introduce a modern design-simulate-optimize workflow in a product development cycle. The joint webinar is co-hosted by Aaron Magnin, Partner Success Manager at Onshape, Steve Lainé, Application Engineering Manager at SimScale and Gabriele Degrassi, Support Engineer at ESTECO. They present a design-simulate-optimize workflow relying on simulation tools built on the latest cloud computing technology, currently the only technical platform that can deliver on the promise of liberating engineers from legacy software constraints and hardware limitations. Agenda: Onshape/PTC - live demo SimScale - live demo ESTECO - live demo

Business Process Management (BPM) is about modeling, analyzing and improving business processes - coordinating the behavior of people, systems and information. In simulation-driven product design, BPM helps overcome silos by adopting a process-oriented approach, where interdependencies between tasks become clearer. The new VOLTA BPM modules expand the benefits of the existing Simulation Process and Data Management (SPDM) technology by bringing the sequencing and orchestration of both human and machine-operated tasks from a single workflow. In this white paper, you'll read about how companies can use BPM to: increase the visibility of the simulation process, align interaction between management, engineering and simulation departments, speed up product development.

Simulation process and data management (SPDM) software has become an essential design and analysis capability, especially for large organizations that might be running dozens of simulations at any time, and then needing to track, share and recall that data at the appropriate time in the design lifecycle. Specifically, the SPDM technology is critical to: Automate the execution of complex simulation and enable more engineers to perform routine analysis. Master simulation processes and data with version control, dependency management and traceability. Democratize the access to simulation data among users throughout the company. In this white paper, you'll read how the right SPDM tool helps digitalize product development processes and accelerate time-to-market by scaling up the use of simulation models across global organizations and teams, in the aerospace, automotive, manufacturing and other industries.

This webinar demonstrates the added value of integrating nTop platform with modeFRONTIER Multidisciplinary Design Optimization (MDO) software through nTopCL to act as an unbreakable generative geometry node. This opens up new and unique possibilities for advanced engineering design exploration. Gaurish Sharma of ESTECO and Evan Pilz of nTopology show how to set up, run, and evaluate the results of an automated Topology Optimization DoE to identify a truly optimal solution. Agenda: Automate DoE in modeFRONTIER and pass design parameters to nTop Platform Generate part geometry using topology optimization and automated post-processing Evaluate the results in ANSYS and select the best design using statistical methods

The America’s Cup isn’t just the first sailing competition in history, it’s also the first when it comes to innovation. Learn how American Magic engineers partnered with ESTECO to prepare for their next challenge. Using modeFRONTIER in different phases of the design process, they integrated geometry changes, performed hydrodynamic CFD simulations and explored different optimization strategies. ## New design challenges: monohulls that fly The America’s Cup is the oldest and most important trophy in sailing. What makes it unique is that the reigning champion gets to decide the rules for the next edition, like the date and the location. More importantly, it defines boat class and design rules. The 33rd America’s cup in 2010 pushed the boundaries of boat design by introducing new technologies, design concepts and materials. When BMW Oracle pitted its 34-meter trimaran and 55-meter high rigid wing against Alinghi in the first regatta, it won by 15 minutes, sailing at more than 18 knots in 8 knots of wind. The 36th America’s Cup builds on changes to previous edition class rules with a new boat concept: a monohull racing boat that doesn’t sacrifice the concept of flying boats. Two t-shaped side foils guarantee that the boat flies above the water. Engineers can’t rely on previous experience and now find themselves having to design a completely new boat. Moreover, competition rules allow teams to design only certain parts of the boat, like foil wings, sails, hulls and systems, while others must be designed by third parties. Whereas the foil wing structure and profile can be designed by teams, the arm structure is determined, designed, and built by a supplier company. American Magic is using ESTECO technology in each phase of the design process, from concept to the refinement of foils and sails. Specifically it uses modeFRONTIER. Its process automation, intelligent algorithms and advanced post-processing capabilities enable engineers to deliver optimized solutions faster. ## Complex simulation studies on foil and mainsail geometries The AC75 has two t-shaped side foils. The arm is attached to the hull with a moving joint which allows the crew to move the foils in and out of the water according to the sailing mode. On the other end of the arm is the foil itself. The foil has a main airfoil profile section coupled with moving flaps. Internally, enough space must be guaranteed for the systems to operate the flaps. Foil design is challenging because it involves the simulation of myriad geometries in different configurations and under multiple operating conditions - all of which determine boat performance. Foils need to create low drag but generate enough force to enable the boat to lift at the start and fly during the race. Righting moment is required to balance the heeling moment of the sails. At higher speeds, cavitation can cause significant loss in performance. Stability is fundamental, especially during maneuvers. In the first stage, hydrodynamic performance is computed using a low-fidelity solver that takes into account the different operating conditions - namely speed, sailing mode and position in the water. In the second stage, the full 3D geometry is designed and evaluated using CFD simulations. High-fidelity simulations can’t be used directly in the first stage of development due to lengthy computational times. The sail plan is composed of the mainsail and a jib or code zero, which are interchangeable. All dimensions are restricted by rules, so engineers can optimize the shape within specific limits. The mainsail is a twin skin sail that acts like an airfoil. By adjusting mast rotation, twist and boom position, the 3D geometry of the mainsail can be tuned for different wind speeds and sailing modes foils, the aerodynamic forces are tuned to generate lift, maintaining momentum and low drag. ## Getting foil and sail design just right American Magic engineers are using several simulation software for the foil and sail design which consists of three steps: geometry definition, force computation and boat speed estimation. The entire process is automated in modeFRONTIER. Multiple workflows handle input modifications, the execution of different tools and file and data exchange. Mares, developed by Airbus, handles the geometry generation of the airfoil and the flap, considering different combinations. Hydrodynamic forces generated by the foil, lift, drag and momentum, as well as cavitation speed are obtained through CFD simulations. The designers use a low fidelity 1D potential-based code in the initial phases to evaluate multiple configurations in a small amount of time. American Magic uses a RANS-based tool to perform high fidelity 3D simulations in the final refinement and optimization phase. Both Mares and the CFD tools are coupled with modeFRONTIER using Easydriver nodes. This enables them to couple their in-house tools using input and output files and customize execution scripts. Geometry consistency is guaranteed by constraints that filter out weird shapes and meet requirements for internal cabling and mechanisms as well as cavitation limits. The main goal of the optimization is to minimize drag for specific lift values. It isn’t enough to understand the efficacy of a foil shape. It’s important to understand how the boat behaves. An in-house Velocity Prediction Program (VPP) software estimates the overall boat performance at different wind speeds and sailing modes. The software uses forces generated by foils and sails to find the overall boat equilibrium and predict boat velocity. A nested modeFRONTIER workflow handles different operating conditions. These are sequentially run, using internal loops to compute the global performance of the design. Multiple operations are handled in parallel to make the most of computational resources. Once the forces are solved, these are passed on to the VPP calculation. Foil and sail design share most of the process and simulation tools but defining the geometry is more complex. The mainsail is divided into several sections where each section can have a different shape based on input values. On top of this, optimal adjustments for every shape need to be calculated. This results in large numbers of configurations which are run to find the best design. It’s fundamental to formulate constraints based on maneuverability, considering adjustments that are feasible for the crew - optimal solutions have no meaning if they are too complex to be performed during the race. Each design phase requires a different optimization strategy. In early stages, genetic algorithms guarantee robustness to find the global optimum in a large design domain. In the last phase, it’s important to cut optimization time - conventional techniques aren’t feasible. Therefore, multi-strategy algorithms are used in combination with advanced initialization techniques to speed up the whole optimization process. ## American Magic and ESTECO - partners in innovation The American Magic design team relied on ESTECO technology in the design and optimization of the boat. Paolo Motta, Performance Prediction Engineer says, “The AC75 is a complex racing boat with interacting subsystems. This makes the design process a challenging and time-consuming task. Using modeFRONTIER process automation, intelligent algorithms and decision making capabilities enables us to decrease foil optimization time from 3 weeks to 4 days. This gives us time to discuss and think about present challenges and develop new solutions”. According to Arthur Rozand, Performance Prediction Engineer, “The key benefit of using modeFRONTIER is to have a suite of tools in one place. In this way it’s easy to manage design and optimization from the exploratory phase to post-processing and decision making. Time is a constraint in development. With modeFRONTIER, we have the flexibility to tailor the strategy. For example, in the early stages of development, DOE strategies and the sensitivity analysis tool help us understand which design variables are the most important. In the final stage of development we use multi-strategy algorithms and advanced charts to select the best design.” “Our partnership with ESTECO is bringing in great results.” says Giorgio Provinciali, Velocity Prediction Program (VPP) Lead, “Working side-by-side with ESTECO engineers enables us to pool our respective expertise to get the most out of modeFRONTIER”.

This webinar presents the successful integration of aPriori cost data technology in the modeFRONTIER workflow in order to investigate a wide selection of manufacturing options quickly. Manufacturing cost is a critical component to finding the best possible design when completing engineering optimization. This webinar demonstrates how to leverage modeFRONTIER capabilities to coordinate a parametric optimization that includes all the performance requirements plus manufacturing cost with aPriori. Watch it now to learn how: Automate your costing activities in engineering workflows Find multiple design alternatives meeting performance and cost targets Select the best alternative from the set for moving forward Compare the old and new design to understand the overall savings Find the best cost decision throughout the design process

This seminar focus on how metamodelling techniques speed up the search for promising designs by replacing computationally expensive design evaluations or simulations. In 2018, ESTECO joined this NAFEMS Web Seminar talking about how metamodelling techniques provide a global model of some design response, which can then be optimized efficiently. As, in the context of digital transformation, simulation is expected to spread all over the product lifecycle, metamodelling techniques too will be requested to adapt to different types of data and to exploit different types of predictive capabilities.