Multidisciplinary design optimization (MDO) is concerned with solving design problems involving coupled numerical models of complex engineering systems. While various MDO software frameworks exist, none of them take full advantage of state-of-the-art algorithms to solve coupled models efficiently. Furthermore, there is a need to facilitate the computation of the derivatives of these coupled models for use with gradient-based optimization algorithms to enable design with respect to large numbers of variables. In this paper, we present the theory and architecture of OpenMDAO, an open-source MDO framework that uses Newton-type algorithms to solve coupled systems and exploits problem structure through new hierarchical strategies to achieve high computational efficiency. OpenMDAO also provides a framework for computing coupled derivatives efficiently and in a way that exploits problem sparsity. We demonstrate the framework’s efficiency by benchmarking scalable test problems. We also summarize a number of OpenMDAO applications previously reported in the literature, which include trajectory optimization, wing design, and structural topology optimization, demonstrating that the framework is effective in both coupling existing models and developing new multidisciplinary models from the ground up. Given the potential of the OpenMDAO framework, we expect the number of users and developers to continue growing, enabling even more diverse applications in engineering analysis and design.

/pdf/openmdao-an-open-source-framework-for-multidisciplinary-53cf53elz5.pdf

OpenMDAO: an open-source framework for multidisciplinary design, analysis, and optimization

Biosurfactants are natural compounds with surface activity and emulsifying properties produced by several types of microorganisms and have been considered an interesting alternative to synthetic surfactants. Glycolipids are promising biosurfactants, due to low toxicity, biodegradability, and chemical stability in different conditions and also because they have many biological activities, allowing wide applications in different fields. In this review, we addressed general information about families of glycolipids, rhamnolipids, sophorolipids, mannosylerythritol lipids, and trehalose lipids, describing their chemical and surface characteristics, recent studies using alternative substrates, and new strategies to improve of production, beyond their specificities. We focus in providing recent developments and trends in biotechnological process and medical and industrial applications.

Current status in biotechnological production and applications of glycolipid biosurfactants

This paper describes the GEMS software developed as part of the IRT Saint Exupery MDA-MDO project 1 for supporting Multidisciplinary Design Optimization (MDO) capabilities. GEMS is a Python library for programing MDO simulation processes, built on top of NumPy 2 , SciPy 3 and Matplotlib 4. GEMS aims at pushing forward the limits of automation in simulation process development , with a particular focus on : i) the automatic programming of MDO processes; ii) distributed and multi-level MDO formulations (or MDO architectures); iii) the integration and development of state-of-the-art algorithms for optimization, design of experiments, surrogate models and coupled analyses; iv) the automation of MDO result analysis; v) the deployment of MDO processes in heterogeneous and distributed industrial simulation environments.

/pdf/gems-a-python-library-for-automation-of-multidisciplinary-4ygrfiaher.pdf

GEMS: A Python Library for Automation of Multidisciplinary Design Optimization Process Generation

A new system is presented that enables the visualization of large multidisciplinary design optimization (MDO) problems and their solution strategy. It was developed within the scope of the European project AGILE. In AGILE, collaborative MDO is performed in large, heterogeneous teams of experts by solving MDO problems using a collection of design and analysis tools. This paper focuses on the visualizations required to support the formulation phase of an MDO project. The Knowledge and graph-based AGILE Design for Multidisciplinary Optimization System (KADMOS), an open-source MDO support system developed by Delft University of Technology, uses graph-based analysis to formulate an MDO problem and its solution strategy, based on the disciplinary analyses available in a repository. The results of KADMOS are stored in the standardized format CMDOWS (Common MDO Workflow Schema), which comprises the entire information on an MDO system. Although, based on Extensible Markup Language, the readability of the CMDOWS file is quite poor also for MDO experts, especially for large MDO systems involving thousands of variables. Providing visualization capabilities to thoroughly inspect the outcome of the different MDO formulation steps becomes a key factor to enable the specification of large MDO systems in a heterogeneous team. Therefore, VISTOMS (VISualization TOol for MDO Systems), a dynamic visualization package, was developed by RWTH Aachen University to enable the visualization and inspection of the different MDO system specification steps, thereby removing one of the main hurdles for using MDO as a development process. The developed visualization capabilities are demonstrated by means of an aerostructural wing design optimization project.

/pdf/graph-based-algorithms-and-data-driven-documents-for-4clfch9oc8.pdf

Graph-based algorithms and data-driven documents for formulation and visualization of large MDO systems

https://repository.tudelft.nl/islandora/object/uuid%3Ae49ec021-f461-4663-8240-d865328179af/datastream/OBJ/download

Formulation and integration of MDAO systems for collaborative design : A graph-based methodological approach

The MDA–MDO project of IRT Saint-Exupery aims at performing an aircraft engine pylon MDO. A bi-level formulation is enabling the reuse of the disciplinary optimisation software for aerodynamic, str...

Aerodynamic optimisation of a parametrised engine pylon on a mission path using the adjoint method

Error-Based Adaptive Coupling Process Between Multipoint High-Fidelity Aerodynamics and Mission Performance for Shape Optimization in the MDA-MDO Project

Industrial Application of an Advanced Bi-level MDO Formulation to Aircraft Engine Pylon Optimization

An overall summary of the Institute of Technology IRT Saint Exupery MDA-MDO project (Multi-Disciplinary Analysis - Multidisciplinary Design Optimization) is presented The aim of the project is to develop efficient capabilities (methods, tools and a software platform) to enable industrial deployment of MDO methods in industry At IRT Saint Exupery, industrial and academic partners collaborate in a single place to the development of MDO methodologies; the advantage provided by this mixed organization is to directly benefit from both advanced methods at the cutting edge of research and deep knowledge of industrial needs and constraints This paper presents the three main goals of the project: the elaboration of innovative MDO methodologies and formulations (also referred to as architectures in the literature 1) adapted to the resolution of industrial aircraft optimization design problems, the development of a MDO platform featuring scalable MDO capabilities for transfer to industry and the achievement of a simulation-based optimization of an aircraft engine pylon with industrial Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) tools

/pdf/towards-the-industrialization-of-new-mdo-methodologies-and-1nlo9okn4c.pdf

Towards the Industrialization of New MDO Methodologies and Tools for Aircraft Design

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