In its truest essence, MDO means optimizing a design, within a set design space, across multiple disciplines by computer. For those unfamiliar with it, a good example from the automotive industry is a body-in-white (BIW). Many disciplines are involved in the design of a car body, each with their own objectives and requirements. For example, a stylist might suggest a certain shape that looks good but is aerodynamically inefficient. Or the crash safety team could propose a certain material that helps to achieve a 5 star crash rating more easily but might be poor from an NVH perspective. And so on….so the key in MDO is not necessarily optimizing the performance of a particular discipline but rather trading and balancing the competing requirements of individual disciplines to optimize the overall system and find the best compromise.
In MDO, we can distinguish single-objective (e.g. minimize weight) and multi-objective optimization (e.g. minimize weight and maximize strength). In case of multi-objective optimization, the key is finding the designs that comprise the pareto frontier. This is where MDO frameworks come into play. If the optimization problem is small enough, i.e. one discipline, one objective and only a handful of independent design variables, an experienced engineer may be able to ‘manually’ optimize the design. Most real world applications however are more complex, thus necessitating smart algorithms to explore the design space and quickly narrow down to the region of interest, and ultimately finding the (set of) optimal design(s).
An example of a single-objective and multi-objective optimization is shown below.
Designing a modern electric motor for an electrified automobile requires striking the perfect balance between cost, weight, and performance. From a modeling and simulation standpoint, predicting the overall performance of the motor requires multiple multi-disciplinary analyses, including electromagnetic, thermal, and stress analyses.
Watch this video as presented by Mr. Jürgen Bruns from Volkswagen AG, at the 8th BEFORE REALITY Conference.
Northrop Grumman Corporation applied Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) to the development of Phased Array Antenna Models to Improve Design Time and Quality
Watch this video presentation by Mr. Jean-Christophe Carniel from Groupe PSA, at the 8th BEFORE REALITY Conference.
“Siloed or simulation tool-specific SPDM is simply not scalable with the increasing demands for more and more simulation as part of the overall design process,” contends Pawel Chadzynski, senior director, product marketing at Aras. “When simulation data is in multiple spreadsheets owned by individual experts, you can’t scale up the volume of simulation needed for the complexity of products. You just can’t do it with existing infrastructure.”
Phoenix Integration Case Study: Submarine Hull Design Optimization.
The objective of this book is to provide prudent, actionable, vendor independent, information and best-practices on how to approach an SDM project and achieve a first successful SDM deployment as well as identifying pitfalls to avoid based on facts and data from 20 years of SDM project experiences.
In an effort to expedite the development of innovative, sustainable engines, drive enterprise-wide collaboration, and support environmental sustainability initiatives, Cummins is leveraging Ansys Minerva, powered by Aras. Learn more! #digitaltransforamationplatform #SPDM
It is clear that democratization of MDO and company wide collaboration can only happen with a friendly to use modern commercial server-based framework that integrates any existing tool, manages the simulation and process data, and offers flexibility regarding distributed execution.
Mathematically, a sensitivity is a partial derivative of some measure of the performance of a product, such as the aerodynamic drag or the stress at a point, with respect to a parameter representing a physical property of the product or its environment. In this context sensitivity analysis provides a measure of the effect of small perturbations, local to the initial design. Read more in this NAFEMS pamphlet.
As the complexity of design solutions increases it becomes difficult to define the"worst case scenario” and identify the appropriate reserve margin for any given situation. This results in situations where designs are over- or under-designed. The use of UQ techniques addresses these issues directly. Read more in this NAFEMS pamphlet.
Read this article on the benefits of server-based MDO compared to desktop solutions, with some lessons learned from the AFRL EXPEDITE program!
This paper presents the roadmap for the development of the new wingtip for the EMBRAER 175 aircraft, and how MultiDisciplinary Optimization (MDO) was applied on its definition and design.
Research conducted in parallel with the Air Force Research Laboratory’s (AFRL’s) Expanded Multidisciplinary Design Optimization (MDO) for Effectiveness Based Design Technologies (EXPEDITE) program is presented. Special consideration is given to detailing the design, components, and execution of a modern aircraft conceptual MDO process within the ESTECO modeFRONTIER® and VOLTA® software products.
Multidisciplinary Optimization in Aerospace: Enable Real Change
Higher complexity doesn't imply higher cost
ADAS (Advanced Driving Assistance Systems ) and AD (Autonomous Driving) systems are the next big frontier for automotive companies. The challenge lays in finding the right balance between minimizing the number of accidents and casualties while maximizing the comfort of traveling in complex conditions.
ESTECO President, Carlo Poloni shares some ingredients that have proven to be essential for effective decision making in the digital world.
What good is a revolution if it doesn’t result in useful change? See how companies are achieving measurable improvements in time savings, simulation data…
The CAASE Conference in Cleveland, June 5-7, will feature a wealth of presentations on the challenges and ROI of real-world democratization efforts at a number of companies in the US and elsewhere.