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ESTECO VOLTA: the game-changer for SPDM & collaborative Design Optimization

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Success story
Faster than the wind: the optimization experience in the America's Cup Challenge
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”.
Success story
Handling the Complexity of Mechatronic System Design
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.
Engineering design, simulation, and optimization in the cloud
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
Success story
Perfecting the manufacture of pressurized gas vessels
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.
Accelerate aircraft design
This webinar demonstrates the added value of combining their technologies for a server-based optimization of an EXPEDITE (EXPanded MDO for Effectiveness Based DesIgn TEchnologies) derived preliminary aircraft design. Watch this webinar and learn more about: EXPEDITE-like modern aircraft conceptual design project** Coupling Pacelab APD preliminary aircraft design platform with modeFRONTIER** Aircraft Design with PACE Model-based technology and VOLTA web collaborative platform for MDO (live demo)** loghi.png
Success story
Honda enhances pedestrian protection with modeFRONTIER
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.
Master engineering complexity and speed up product development with ESTECO modeFRONTIER
With ESTECO modeFRONTIER, you can manage the logical steps of your engineering design process, perform design space exploration and search for the optimal solution efficiently and faster.
White paper
Breaking down organizational silos in simulation with business process management
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.
Take full control of the engineering design process with ESTECO VOLTA
With VOLTA, ESTECO Enterprise platform for Simulation Process and Data Management (SPDM) and design optimization, you can expect to scale up the usage of simulation models and design exploration and optimization techniques across teams and different organizations to deliver better products, faster.
White paper
How to Accelerate and Democratize Your Design Processes
Within the world of simulation, automation is a leading digital technology that’s proving its worth, accelerating and democratizing every step in the design process. Usability, though, is a key issue for many working with automated solutions. Regardless of their level of expertise, individuals are faced with complex algorithms and must identify the right optimization strategies to get the best result, while taking into account the available resources. In this white paper, you'll read how the ESTECO Autonomous Optimization technology can help: automate every sort of simulation process, free up time and human resources, democratize design space exploration and expedite decision-making processes.