Multidisciplinary Optimization Research Articles

Multidisciplinary design optimisation of lattice-based battery housing for electric vehicles

Batteries with high energy densities become essential with the increased uptake of electric vehicles. Battery housing, a protective casing encapsulating the battery, must fulfil competing engineering requirements of high stiffness and effective thermal management whilst being lightweight. In this study, a graded lattice design framework is developed based on topology optimisation to effectively tackle the multidisciplinary objectives associated with battery housing. It leverages the triply periodic minimal surfaces lattices, aiming for high mechanical stiffness and efficient heat dissipation considering heat conduction and convection. The effectiveness of the proposed framework was demonstrated through the battery housing design, showcasing its ability to address multidisciplinary objectives as evidenced by the analysis of the Pareto front. This study identifies the potential of lattices in lightweight applications incorporating multiphysics and offers an efficient lattice design framework readily extended to other engineering challenges.

A reliability-based multidisciplinary design parallel optimization method based on double-layer approximation model for nuclear fuel assembly bottom nozzle

The design of intricate systems such as the nuclear fuel assembly necessitates elevated levels of multi-disciplinary performance and reliability. In current reliability-based multidisciplinary design optimization methods, the decoupling strategy between optimization and reliability assessment involves sequential optimization and reliability assessment, with reliability serving as a constraint for optimization. This approach often suffers failure in locating the global optimal solution. In light of this issue, a reliability-based multidisciplinary design parallel optimization method based on double-layer approximation model is hereby proposed, achieving parallel separation and global efficient optimization of deterministic disciplinary performances and reliability, while performing efficient and accurate calculation on the multi-disciplinary reliability numerical solution. This method has been implemented for the multi-disciplinary uncertain optimization of the nuclear fuel assembly bottom nozzle. In comparison to conventional optimization methods, this approach demonstrates enhanced global optimization effectiveness.

Beyond conventional: An integrated aerostructural optimization approach for innovative tailplane configurations

This research paper presents a comprehensive study focused on optimizing innovative tailplane configurations for transport jet aircraft. This study aims to enhance the aerodynamics of the aircraft's rear end by introducing a novel tail arrangement. The ultimate goal is to reduce the size of the horizontal empennage, which will have a positive impact on aircraft fuel efficiency. To fulfill its objectives, this work develops a systematic approach, integrating advanced methodologies such as the Design of Experiments and Response Surface Models for both aerodynamics and structural disciplines. By levering response surfaces methodology, the aerostructural optimization has been performed towards a size reduction of the horizontal tail. Results indicate a potential 9% reduction in the tailplane reference area, which could result in enhanced aerodynamic performance and weight saving. This target would only be achievable if the innovative design includes a Leading Edge Extension device to maintain the stability and handling characteristics of a conventional reference aircraft. The impact of the innovative optimized tail arrangement developed in this study at the aircraft level resulted in a 1% reduction in block fuel for a mission range of approximately 3,400 nautical miles for a 180-seat capacity jet aircraft (similar to A320neo). Furthermore, from an industrial perspective, this paper also demonstrates how an automated workflow assists with CAD modeling, mesh creation, simulation execution, and surrogate models to accelerate complex multidisciplinary optimization processes, thereby reducing the time and costs associated with the development of a new aircraft configuration.

Multidisciplinary Design Optimization of Cooling Turbine Blade: An Integrated Approach with R/ICSM

This paper presents an efficient integrated multidisciplinary design optimization method for shaping a high-pressure cooling turbine blade in aero engines. This approach utilizes a novel regression/interpolation combination surrogate model (R/ICSM), facilitating comprehensive design optimization through collaborative coupling feature parameterization modeling and numerical simulation analysis across various disciplines. The optimized blade adjusts the load distribution on its surface, effectively eliminating flow separation at the tip and trailing edge. Notably, the optimized blade achieves a 0.69% increase in isentropic efficiency while satisfying aerodynamic, strength, and structural constraints. This highlights the effectiveness and progressiveness of the multidisciplinary design optimization method for a cooling turbine blade based on the R/ICSM in enhancing overall performance. It offers a novel and feasible approach for turbine blade design optimization and provides valuable insights for future research and applications.

Aerostructural Wing Optimization Using a Structural Surrogate in a Coupled Adjoint Formulation

As the number of disciplines included in the multidisciplinary design-optimization process continues to increase, it is envisioned that some of the disciplinary tools will take the form of surrogate models, whereas others remain physics-based, depending on the requirements and stage of the design process. To simulate this in the context of an aerostructural optimization of an aircraft wing, the work presented herein features a high-fidelity aerodynamic flow solver, while a surrogate is employed to model the wing structure. This approach includes the evaluation of the sensitivities of both the aerodynamic and structural disciplines, using a coupled-adjoint formulation to enable gradient-based optimization. An important aspect of the method is that the surrogate is trained only once, prior to the optimization, and held fixed throughout. The surrogate in effect parameterizes the structural design process, and outputs the weight and stiffness of an optimized structure, given inputs of geometry parameters and sizing loads. To minimize the number of surrogate inputs and enable the representation of the entire structural design space, parameterized loads are used to build the surrogate. The method is applied to the optimization of the NASA Common Research Model, illustrating the effectiveness of the new approach.

Multidisciplinary analysis and structural optimization for the aeroelastic sizing of a UAV wing using open-source code integration

PurposeThis paper aims to propose a structural sizing approach of an unmanned aerial vehicle (UAV) wing that takes into account the aeroelasticity effects through a fluid–structure interaction analysis.Design/methodology/approachThe sizing approach proposed in this study is an iterative process, each iteration of which consists of two sub-loops, a multidisciplinary analysis (MDA) loop followed by a structural optimization loop. The MDA loop seeks the aeroelastic equilibrium between aerodynamic forces and structural displacements using a fixed-point iteration scheme. Once the equilibrium is reached, the converged pressure loads are used for the structural optimization, which aims to find the structural thicknesses that minimize the wing weight under failure criteria. The two sub-loops are run sequentially in an iterative process until the mass is converged. The analysis models are implemented in open-source software, namely, PANUKL for aerodynamics and MYSTRAN for structures, while the whole process is automated with Python and integrated in the open-source optimization framework OpenMDAO.FindingsThe approach was applied to the design of the Predator MQ-1 wing. The results of the MDAs show the convergence of the wing deformations to the flight shape after few iterations. At the end of the aeroelastic sizing loop, the result is a structurally sized wing with minimal weight considering the aeroelasticity effects.Originality/valueThe approach proposed takes into account the wing aero-structural coupling effects while sizing its structure instead of a fixed load distribution. In addition, the approach is fully based on open-source codes, which are freely available for public use and can be fully reproducible.

A Scoping Review on Simulation-Based Design Optimization in Marine Engineering: Trends, Best Practices, and Gaps

AbstractThis scoping review assesses the current use of simulation-based design optimization (SBDO) in marine engineering, focusing on identifying research trends, methodologies, and application areas. Analyzing 277 studies from Scopus and Web of Science, the review finds that SBDO is predominantly applied to optimizing marine vessel hulls, including both surface and underwater types, and extends to key components like bows, sterns, propellers, and fins. It also covers marine structures and renewable energy systems. A notable trend is the preference for deterministic single-objective optimization methods, indicating potential growth areas in multi-objective and stochastic approaches. The review points out the necessity of integrating more comprehensive multidisciplinary optimization methods to address the complex challenges in marine environments. Despite the extensive application of SBDO in marine engineering, there remains a need for enhancing the methodologies’ efficiency and robustness. This review offers a critical overview of SBDO’s role in marine engineering and highlights opportunities for future research to advance the field.

Multidisciplinary design and optimization of journal bearing for high-power wind turbine speed increaser

With the increasing power of wind turbine generators (WTG), the failure rate of rolling bearings in wind turbines due to insufficient bearing capacity increases with the increase of bearing size. To overcome these challenges, this paper proposes a design optimization method for the rectangular groove elliptical sliding bearing (RGEB) of the WTG output shaft. This method can maximize the radial bearing capacity under the premise of ensuring that the oil film pressure is large, the end leakage and the temperature rise are small. The multidisciplinary design and modeling of RGEB are carried out according to the structure and working conditions of WTG. Based on computational fluid dynamics (CFD), the influence of the number of rectangular dynamic pressure grooves on the bearing performance is analyzed. The kriging model, BP neural network model, and SSA-BP model are constructed for each performance index of RGEB, to establish a high-precision combined surrogate model based on global error criterion. After establishing the optimization equation, the PSO and SQP combined optimization algorithm is used to optimize the optimal structural parameters. The results show that the bearing capacity of the optimized RGEB is 95.9% higher than that of the ordinary elliptical bearing (EB) without increasing the size and quality of the bearing. In addition, the combined surrogate model can effectively replace the expensive finite element model to deal with the WTG sliding-bearing optimization problem.

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

The design of a helicopter involves multiple disciplines and a large number of technical parameters with conflicting objectives, leading to the challenges of multidisciplinary coupling in design and optimization. In the context of the application of Model-Based Systems Engineering (MBSE) in complex product design, how to bridge the gap between MBSE and Multidisciplinary Design Analysis and Optimization (MDAO) to accelerate the early design process of helicopters remains an urgent problem to be addressed. The paper proposed an optimization framework that links MBSE and MDAO models for the design optimization problem of helicopters. On the MBSE side, the design optimization problem of helicopters was defined through the descriptive SysML model. On the MDAO side, the specific domain analysis model and optimization analysis workflow were established. The integration of design data was achieved through stereotype plugins and design components, bridging the gap between MBSE and MDAO, and providing accurate engineering data for system design verification. The paper provided an optimization case of a helicopter, with the optimal mission performance of the helicopter as the objective function. Through MDAO analysis, the design optimization of fuel consumption, take-off weight, and rotor dynamics parameters was completed, achieving an integrated process of system design and optimization.

Optimization-based design support for engineer-to-order product quotation

AbstractQuotation of engineer-to-order products provides substantial challenges in effectively managing engineering resources. This paper describes an approach that rationalizes this process by integrating multi-disciplinary design analysis and optimization with a new open-source library for managing engineering knowledge before and after optimization. The approach is applied and evaluated on mechanical rock excavation machines. Adapting the approach and considering the user feedback gathered can lead to an enhanced design space overview during quotation and thus more competitive product offerings.

High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft

High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft

HerzMobil Tirol PreOp - A Multidisciplinary Telemonitoring Project for Heart Failure Patients Prior to Cardiac Surgery.

Patients with heart failure are at risk of perioperative complications with elective cardiac surgery. Conception of a multidisciplinary telemedicine-assisted optimisation project for high-risk patients prior to elective cardiac surgery. Multidisciplinary concept design. A pilot-project for 30 patients was developed. Design of the first preoperative telemonitoring-assisted optimisation project for high-risk patients undergoing cardiac surgery.

Multidisciplinary Design Optimization of Reentry-Powered Hypersonic Vehicles Based on Surrogate Model

Multidisciplinary Design Optimization of Reentry-Powered Hypersonic Vehicles Based on Surrogate Model

Discrete and Continuous Adjoint-Based Aerostructural Wing Shape Optimization of a Business Jet

This article presents single- and multi-disciplinary shape optimizations of a generic business jet wing at two transonic cruise flow conditions. The studies performed are based on two high-fidelity gradient-based optimization tools, assisted by the adjoint method (following both discrete and continuous approaches). Single discipline and coupled multi-disciplinary sensitivity derivatives computed from the two tools are compared and verified against finite differences. The importance of not making the frozen turbulence assumption in adjoint-based optimization is demonstrated. Then, a number of optimization runs, ranging from a pure aerodynamic with a rigid structure to an aerostructural one exploring the trade-offs between the involved disciplines, are presented and discussed. The middle-ground scenario of optimizing the wing with aerodynamic criteria and, then, performing an aerostructural trimming is also investigated.

A Framework for Aircraft Conceptual Design and Multidisciplinary Optimization

In this research, the architecture and the functionalities of the LAMBDA (Laboratory of Aircraft Multidisciplinary Knowledge-Based Design and Analysis) framework for the design, analysis, and optimization of civil aircraft are presented. The framework is developed in MATLAB R2022a and comprises a modular architecture, which gives the potential for the use of different methods and fidelities for each discipline. The methods can be selected from a set of built-in methods or custom user-defined scripts. Disciplinary modules of the LAMBDA are Requirements, Weight, Sizing, Geometry, Aerodynamics, Engine, Performance, Cost, Emission, and Optimization. This framework has been used for different types of design and optimization problems. When it is applied for the design and optimization of a novel regional TBW (Truss-Braced Wing) aircraft, the operating cost has been reduced by 7.7% in the optimum configuration compared to the base configuration.

Surrogate-assisted differential evolution using manifold learning-based sampling for high- dimensional expensive constrained optimization problems

To address the challenges of high-dimensional constrained optimization problems with expensive simulation models, a Surrogate-Assisted Differential Evolution using Manifold Learning-based Sampling (SADE-MLS) is proposed. In SADE-MLS, differential evolution operators are executed to generate numerous high-dimensional candidate points. To alleviate the curse of dimensionality, a Manifold Learning-based Sampling (MLS) mechanism is developed to explore the high-dimensional design space effectively. In MLS, the intrinsic dimensionality of the candidate points is determined by a maximum likelihood estimator. Then, the candidate points are mapped into a low-dimensional space using the dimensionality reduction technique, which can avoid significant information loss during dimensionality reduction. Thus, Kriging surrogates are constructed in the low-dimensional space to predict the responses of the mapped candidate points. The candidate points with high constrained expected improvement values are selected for global exploration. Moreover, the local search process assisted by radial basis function and differential evolution is performed to exploit the design space efficiently. Several numerical benchmarks are tested to compare SADE-MLS with other algorithms. Finally, SADE-MLS is successfully applied to a solid rocket motor multidisciplinary optimization problem and a re-entry vehicle aerodynamic optimization problem, with the total impulse and lift to drag ratio being increased by 32.7% and 35.5%, respectively. The optimization results demonstrate the practicality and effectiveness of the proposed method in real engineering practices.

On the Multidisciplinary Design of a Hybrid Rocket Launcher with a Composite Overwrapped Pressure Vessel

A multidisciplinary design optimisation (MDO) study of a hybrid rocket launcher is presented, with a focus on quantifying the impact of using composite overwrapped pressure vessels (COPVs) as the oxidiser tank. The rocket hybrid propulsion system (RHPS) consists of a combination of solid fuel (paraffin) and liquid oxidiser (NOx). The oxidiser is conventionally stored in metallic vessels. Alternative design concepts involving composite-based pressure vessels are explored that could lead to significant improvements in the overall performance of the rocket. This design choice may potentially affect parameters such as total weight, thrust curve, and maximum altitude achieved. With this eventual impact in mind, structural considerations such as wall thickness for the COPV are integrated into an in-house MDO framework to conceptually optimise a hybrid rocket launcher.

A novel conceptual design approach for autonomous underwater helicopter based on multidisciplinary collaborative optimization

Autonomous underwater helicopters (AUHs) are complex electromechanical systems consisting of multiple interconnected sub-disciplines, posing a significant challenge for traditional sequential design strategies in managing their interactions. To address this challenge, a multidisciplinary collaborative optimization (MCO) strategy is proposed, integrating structural, hydrodynamic, and energy disciplines to enhance AUH cruising range. Additionally, a novel approximation model is introduced, combining the Logistic-Tent chaos sparrow search algorithm (LTC-SSA) with the backpropagation neural network (BPNN) algorithm. This method aims to replace costly computational fluid dynamics (CFD) and structural mechanics calculations, thus reducing AUH optimization costs. The laminate design of the composite pressure hull follows classic lamination theory (CLT) and the Tsai-Wu failure criterion. Results demonstrate that the multidisciplinary co-design strategy significantly reduces optimization time costs of AUH, from several months to several days. Furthermore, the proposed LTC-SSA-BPNN algorithm accurately evaluates sailing resistance and Tsai-Wu failure index, with maximum errors of 1.64% and 9.32% respectively. Additionally, the composite pressure shell achieves a 30.4% weight reduction and a 4.1% reduction in sailing resistance while maintaining structural stability. Moreover, the maximum cruising range increases by 34.4%. This strategy offers theoretical support for AUH conceptual design and promises performance enhancement in practical engineering applications.

Multidisciplinary optimization and motion control method of electromagnetic linear actuator for electro-hydrostatic system

Multidisciplinary optimization and motion control method of electromagnetic linear actuator for electro-hydrostatic system

A Road Map to the Structural Optimization of a Type-C Composite UAV

The present paper investigates the design process and the dimensioning of a tailless type-C composite sandwich unmanned aerial vehicle (UAV). The objective is to investigate an innovative aircraft configuration which exceeds the standard approach of ribs and spars and replaces them with a sandwich structure for future unmanned aerial systems. The necessity of carbon fiber-reinforced materials arose due to the weight constraint of a Class C UAV, i.e., the whole vehicle must be under 25 kg, which limits the mass of the structure to 9 kg. The structural design of composite structures differs from the one of traditional isotropic structures. The number of holes should be limited, as drilling down the composite aerostructure would conclude to the generation of delaminations. In addition, the joints between sections with different thicknesses could lead to stress concentrations and disbands. Therefore, the present report is crucial for the continuance of the present project as it has contributed both to the structural design and assessment of the UAV. This work focusses on the computation of loads, the process of structural sizing through a multi-disciplinary optimization approach, and the simulation-based structural proof. Particular attention is paid to the specifically developed semi-analytical method for predicting the aero-elastic load. Based on the detailed finite element model of the global structure, the applicability of the minimum number of bolts as a major structural joining variant is proven. The design process from single components to the assembly of the overall aircraft results in the realization of the demonstrator structure.