Multidisciplinary Optimization Framework Research Articles

Blended-Wing-Body Regional Aircraft Optimization with High-Fidelity Aerodynamics and Critical Design Requirements

Conventional tube-and-wing and proposed blended-wing-body airliners must satisfy several design requirements, but the latter configuration is tightly integrated and sensitive to these requirements. In this work, blended-wing-body regional aircraft are investigated using a gradient-based mixed-fidelity multidisciplinary optimization framework centered on a Reynolds-averaged Navier–Stokes solver. In addition to sizing and cruise trim, design requirements considered include one-engine-inoperative directional trim, takeoff rotation ability, takeoff field length, initial climb performance, low-speed trim and static margin, and top-of-climb rate of climb. Results show how optimal design features vary and performance is overpredicted if critical design requirements are excluded and how key elements of geometric freedom help realize the potential of the configuration. A 4.8% block fuel burn benefit is enabled by pivot-piston variable-length landing gear even with low-mounted engines and high design freedom. The off-design constraints penalize block fuel burn by 3.2% if variable-length landing gear is considered, but this value reaches 7.6% if lower geometric freedom that inhibits tight cabin contouring and the formation of a novel forebody ridge is removed. Leading-edge carving is found to be optimal. The high design freedom and high-fidelity aerodynamics model help efficiently satisfy the design requirements, resulting in a cruise lift-to-drag ratio of 21.7 at 36,000 ft and Mach 0.78.

Collaborative optimization of a composite pressure cylindrical shell based on dynamic penalty functions

This article reports the design and optimization of pressure cylindrical shells comprising carbon/epoxy and glass/epoxy composite materials. It presents a method for analyzing the pressure cylindrical shells of composite materials, analyzes the strength and buckling of composite pressure cylindrical shells with different rib numbers, and investigates the influence of thickness and ply angles ([±θ]10 and [903(±θ)2903]) on the critical buckling and strength-failure stresses. An approximate model of composite pressure cylindrical shells and collaborative optimization based on dynamic penalty functions are combined into a multidisciplinary optimization framework of composite pressure cylindrical shells. The optimization aims to maximize the critical buckling stress while minimizing the buoyancy coefficient. At a buoyancy coefficient similar to that of the initial scheme, the critical buckling stresses of the carbon/epoxy and glass/epoxy cylindrical shells increased by 21.85% and 9.5%, respectively, verifying the effectiveness of the collaborative optimization framework based on dynamic penalty functions.

A sensitivity-based estimation method for investigating control co-design relevance

Abstract. Control co-design is a promising approach for wind turbine design due to the importance of the controller in power production, stability, load alleviation, and the resulting coupled effects on the sizing of the turbine components. However, the high computational effort required to solve optimization problems with added control design variables is a major obstacle to quantifying the benefit of this approach. In this work, we propose a methodology to identify if a design problem can benefit from control co-design. The estimation method, based on post-optimum sensitivity analysis, quantifies how the optimal objective value varies with a change in control tuning. The performance of the method is evaluated on a tower design optimization problem, where fatigue load constraints are a major driver, and using a linear quadratic regulator targeting fatigue load alleviation. We use the gradient-based multi-disciplinary optimization framework Cp-max. Fatigue damage is evaluated with time-domain simulations corresponding to the certification standards. The estimation method applied to the optimal tower mass and optimal cost of energy show good agreement with the results of the control co-design optimization while using only a fraction of the computational effort. Our results additionally show that there may be little benefit to using control co-design in the presence of an active frequency constraint. However, for a soft–soft tower configuration where the resonance can be avoided with active control, using control co-design results in a taller tower with reduced mass.

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.

Enhancing gust load alleviation performance in an optimized composite wing using passive wingtip devices: Folding and Twist approaches

This paper introduces an innovative numerical method for the design and optimization of high-aspect-ratio composite wings equipped with passive control systems, specifically, Folding WingTip (FWT) and Twist WingTip (TWT) devices. The aim is to enhance Gust Load Alleviation (GLA) performance in the baseline wing. Recent numerical studies have indicated that the inclusion of spring devices and wingtip modifications can offer additional benefits in alleviating gust loads during flight. The baseline wing is designed using a comprehensive multi-disciplinary optimization framework, taking into account aerostructural constraints and exploiting the anisotropic properties of composite materials. The proposed methodology integrates Finite Element (FE) software, an in-house Reduced Order Model (ROM) framework for nonlinear aeroelastic analyses, and Particle Swarm Optimization (PSO). This method, implemented in the Nonlinear Aeroelastic Simulation Software (NAS2) package, facilitated the streamlined design of composite wings with optimized aeroelastic and structural performance. The paper is divided into two main parts. Part 1 introduces a Multidisciplinary Design Optimization (MDO) approach for high-aspect-ratio composite wings, leading to the development of a baseline wing model. Part 2 evaluates the effectiveness of the FWT and TWT devices in alleviating gust loads on the baseline wing, with a focus on the Root Bending Moment (RBM) as a critical criterion for comparison. In wingtip modeling, geometrical nonlinearity is incorporated, and elastic trim is adjusted in each iteration to accommodate shape changes under load and aerodynamic panel movement is synchronized with structural adjustments.

A Multidisciplinary Optimization Framework for Ecodesign of Reusable Microsatellite Launchers

The commercial space launch sector is currently undergoing a significant shift, with increasing competition and demand for launch services, as well as growing concerns about the environmental impact of rocket launches. To address these challenges, within the New Space Portugal project scope, a multidisciplinary framework for designing and optimizing new launch vehicles is proposed. Creating a more resilient and responsible space industry can be achieved by combining technological innovation and environmental sustainability, as emphasized by the framework. The main scope of the framework was to couple all the disciplines relevant to the space vehicle design in a modular way. Significant emphasis was placed on the infusion of ecodesign principles, including Life Cycle Assessment (LCA) considerations. Optimization techniques were employed to enhance the design and help designers conduct trade-off studies. In general, this multidisciplinary framework aims to provide a comprehensive approach to designing next-generation launch vehicles that meet the demands of a rapidly changing market while also minimizing their environmental impact. A methodology that leverages the strengths of both genetic and gradient-based algorithms is employed for optimizations with the objectives of maximizing the apogee altitude and minimizing the Global Warming Potential (GWP). Despite only being tested at the moment for sounding rockets, the framework has demonstrated promising results. It has illuminated the potential of this approach, leading to the identification of three optimal designs: one for maximizing the apogee, another for minimizing GWP, and a compromise design that strikes a balance between the two objectives. The outcomes yielded a maximum apogee of 6.41 km, a minimum GWP of 9.06 kg CO2eq, and a balanced compromise design featuring an apogee of 5.75 km and a GWP of 25.64 kg CO2eq.

Multidisciplinary optimization of high aspect ratio composite wings with geometrical nonlinearity and aeroelastic tailoring

This study presents a systematic numerical approach for the design and optimization of high aspect ratio composite wings subjected to aerodynamic loads. The primary objective is to develop a multi-objective, multi-disciplinary optimization framework that considers aerostructural constraints, such as subsonic aeroelasticity and geometrical nonlinearity. The incorporation of anisotropic properties of composite materials is emphasized to construct lightweight aerospace structures. Aeroelastic tailoring, a technique leveraging these properties, is employed in the optimization process. The proposed methodology integrates three analysis tools, Finite Element software for structural behavior simulation, an in-house Reduced Order Model (ROM) framework for nonlinear aeroelastic analyses with tailoring capabilities, and Particle Swarm Optimization (PSO) as a population-based stochastic optimization method. This integration enables the development of a powerful numerical approach, implemented in the Nonlinear Aeroelastic Simulation Software (NAS2) package, for designing composite wings with optimized aeroelastic and structural performance. The proposed methodology has broad applicability in aerospace engineering, encompassing aircraft and unmanned aerial vehicles, offering significant potential to enhance their design and overall performance.

Digital Twin Data-Driven Multi-Disciplinary and Multi-Objective Optimization Framework for Automatic Design of Negative Stiffness Honeycomb

Digital Twin Data-Driven Multi-Disciplinary and Multi-Objective Optimization Framework for Automatic Design of Negative Stiffness Honeycomb

Robust multidisciplinary analysis and optimization for conceptual design of flexible aircraft under dynamic aeroelastic constraints

We present a computational framework for robust multidisciplinary design and optimization of flexible aircraft, suited for the conceptual design exploration phase. Constraints are representative of some dynamic aeroelastic effects, including flutter and gust-induced structural stresses. Uncertainties on wing structural parameters are considered, and reliability-based optimization under dynamic aeroelastic constraints is addressed by a Bayesian approach. This work details the implementation aspects, covering disciplinary software tools and the overall aircraft design suite, the optimization algorithm and the approach to propagate uncertainty efficiently. Results are thoroughly discussed for a reference aircraft, which is optimized in the study with respect to a few wing parameters including aspect ratio. The proposed approach is compared to a conventional design methodology assuming a rigid airframe. We show that when applied to slender and flexible wings, the latter can produce dangerous non-conservative results, as its predictions are too optimistic both with respect to efficiency and to aeroelastic safety.

Research on MDO of Ship Propulsion Shafting Dynamics Considering the Coupling Effect of a Propeller-Shafting-Hull System

Abstract Dynamic designs for ship propulsion shafting can be categorised as complex multi-disciplinary coupling systems. The traditional single disciplinary optimisation design method has become a bottleneck, restricting the further improvement of shafting design. In this paper, taking a complex propulsion shafting as the object, a dynamic analysis model of the propeller-shafting-hull system was established. In order to analyse the coupling effect of propeller hydrodynamics on shafting dynamics, the propeller’s hydrodynamic force in the wake flow field was calculated as the input for shafting alignment and vibration analysis. On this basis, the discipline decomposition and analysis of the subdisciplines in design of shafting dynamics were carried out. The coupling relationships between design variables in the subdisciplines were studied and the Multi-disciplinary Design Optimisation (MDO) framework of shafting dynamics was established. Finally, taking the hollowness of the shaft segments and the vertical displacement of bearings as design variables, combined with the optimal algorithm, the MDO of shafting dynamics, considering the coupling effect of the propeller-shafting-hull system, was realised. The results presented in this paper can provide a beneficial reference for improving the design quality of ship shafting.

Multidisciplinary concurrent optimization framework for multi-phase building design process

AbstractModern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. This paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.

A framework for the bi-level optimization of a generic transport aircraft fuselage using aeroelastic loads

The aeroelastic loads and design processes at the German Aerospace Center, Institute of Aeroelasticity in the framework of multi-disciplinary optimization are constantly evolving. New developments have been made in the in-house model generation tool ModGen, which allow us to create detailed fuselage models for preliminary design. As a part of the subsequent developments to integrate the fuselage structure in our aeroelastic design process, a new framework for optimizing the fuselage structure has been developed. The process is based on a bi-level optimization approach which follows a global–local optimization methodology to simplify a large optimization problem. A sub-structuring procedure is used to define stiffened panels as independent structures for local optimization. The panels are sized with stress and buckling constraints with consideration of several aeroelastic load cases. Furthermore, in this paper, we present a physical sub-structure grouping process which enables reduced number of panel optimizations and saves considerable computational effort with little compromise in the solution accuracy.

Investigations on the Potentials of Novel Technologies for Aircraft Fuel Burn Reduction through Aerostructural Optimisation

A physics-based optimisation framework is developed to investigate the potential advantages of novel technologies on the energy efficiency of a midrange passenger aircraft. In particular, the coupled-adjoint aerostructural analysis and optimisation tool FEMWET is modified to study the effects of active flow control at different load cases for conventional and unconventional wing configurations. This multidisciplinary design optimisation (MDO) framework presents the opportunity to optimise the wing considering static aeroelastic effect and, by its gradient-based method, save substantial computational time compared to high-fidelity tools, keeping a satisfying level of accuracy. Two different configurations are analysed: a forward- and backward-swept wing aircraft, developed inside the Cluster of Excellence SE2A (Sustainable and Energy-Efficient Aviation). The forward-swept configuration is sensitive to the aeroelastic stability effect, and the backward configuration is influenced by the aileron constraint. They may lead to a weight increment. Sensitivity studies show the possible role of key parameters on the optimisation results. The highest fuel weight reduction achievable for the two configurations is 5.6% for the forward-swept wing and 9.8% for the backward configuration. Finally, both optimised wings show higher flexibility.

Sensitivity analysis of a Ground-Gen Airborne Wind Energy System design

The architecture of a new multidisciplinary design and optimization framework for rigid wing Airborne Wind Energy Systems, named T-GliDe, is introduced and a Ground-Gen AWES is analyzed to illustrate the features of the design approach. T-GliDe features an optimization module and an uncertainty quantification module, allowing for a number of algorithm-based design techniques. T-GliDe performs an AWES design optimizing market-based objective functions, while satisfying constraints related to fight stability. The fight dynamics is modelled with analytical aerodynamic theories, allowing for fast and consistent design evaluations, without the use of time simulation codes and thus of active control. In this work, a reduced optimization problem is run to find optimal working-set points of a Ground-Gen AWES with respect to power production. The reel-out factor and the pitch angle as function of wind speed are considered as design variables and output trends are shown. A variance based sensitivity analysis is then run to investigate how the rigid body eigenvalues are influenced by a set of independent variables. Among the chosen independent variables, a sub-set of variables which bear an impact on the dynamics is identified and they will be considered in future design and optimization activities as design variables.

Parametrisation Scheme for Multidisciplinary Design Analysis and Optimisation of a Floating Offshore Wind Turbine Substructure – OC3 5MW Case Study

The development of novel energy technologies is considered imperative in the provision of solutions to meet an increasing global demand for clean energy. Floating Offshore Wind Turbine (FOWT) is one of the emerging technologies to exploit the vast wind resources available in deeper waters. To lower the levelized cost of energy (LCOE) or optimise the performance response associated with a FOWT system, a detailed understanding of the different disciplines (Aero-Hydro-Servo-Elastic) within the system and the relationship between the FOWT system and the dynamics of the marine environment is required. This requires an efficient Multidisciplinary Design, Analysis and Optimisation (MDAO) framework for FOWT systems to reduce the capital cost and increase dynamic performance. A key component of any MDAO framework is the shape parameterisation scheme, as it enables the modelling of a large array of platform designs with different geometric shapes using limited number of parameters. This work focuses on the B-Spline parameterisation modelling technique of OC3 spar-buoy and the use pattern search optimization algorithm to select the optimal design variants. The parametrisation technique is implemented in an analysis framework, where a B-spline library from Sesam GeniE is used to model each design representation, and a potential flow frequency domain analysis solver (HydroD/Wadam) is used for the hydrodynamic analysis. Validation of the selected designs within the design space is conducted with a benchmark NREL5MW spar-buoy hydrodynamic response results in literature with the hydrodynamic response of the frequency domain modelling approach using Sesam GeniE and HydroD/Wadam. This analysis process shows a high accuracy in response results between the OC3 spar-buoy in literature and the OC3 spar-buoy model design using B-Spline parametrization technique. Key performance metrics like the cost of materials and root mean square (RMS) of the nacelle acceleration also show improvement with the design variants compared to estimation from OC3 design in literature.

A Flexible, Multi-fidelity Levelised Cost of Energy Model for Floating Offshore Wind Turbines Multidisciplinary Design, Analysis and Optimisation Approaches

As the UK takes a step towards a greener, cleaner future aiming to be net zero by 2050, continuous development of the power network is required. A clear solution is offshore wind, having already proved its feasibility and success in nearshore sites. However, a large majority of near shore sites in the UK are already being utilised. The next step is to move into deeper waters and utilise the stronger, more consistent wind resources. A solution could be floating offshore wind which is still in its infancy, with only a few operational floating wind farms installed. Building upon the multidisciplinary design, analysis, and optimisation framework (MDAO) for floating offshore wind turbines (FOWT) being developed at the University of Strathclyde, called FEDORA, the aim of this work is to refine the LCoE model adopted by FEDORA, and applying it to perform the optimisation of the floating offshore OC3 SPAR. There is limited data on cost, therefore Hywind Scotland Pilot Park will be used as a basis for the LCoE model, allowing the results to be validated. This model is not restricted to SPARs, as it establishes a general methodology to calculate the life cycle cost of floating offshore wind farms. Utilising the improved cost model this work finds four optimised SPAR structures for four different maximum angles of inclination which can be experienced in the wind turbines operation. The improved cost model has a much higher accuracy, highlighting the initial cost model underestimates the cost of the SPAR structure by around half.

Conceptual design of a long-range autonomous underwater vehicle based on multidisciplinary optimization framework

The endurance of a deep-sea AUV is closely related to its sailing resistance, the amount of carrying batteries and equipment load, which involves interactions among multiple disciplines. In this paper, in order to develop the conceptual design of a long-range AUV in the early stage, a multidisciplinary optimization design framework is presented for decision-makers to explore the given design space, which takes into account the coupling between the disciplines of hull form, structural design and energy use. A Self-adaptive Surrogate Ensemble (SASE) method is proposed to replace the expensive process of hydrodynamic analysis, a recommended approach by the China Classification Society (CCS) specification is applied to carry out the design of metallic pressure hulls, and the classical lamination theory and Tsai–Wu criteria are adopted in the design of composite pressure hulls. Finally, the evaluation model of AUV endurance is created from the perspective of energy capacity and consumption. The conceptual design of a 200 kg-class AUV is executed to maximize the endurance based on the proposed multidisciplinary optimization design framework. The results show that the most important factors that affect AUV endurance are the velocity and diameter, and the optimum velocity of the AUV increases with the load power. The Sea-Whale 2000 AUV was developed based on the optimal result and the excellent endurance performance in the sea trial validated the effectiveness of the proposed design method in the preliminary design process.

Multidisciplinary design optimisation of a fully electric regional aircraft wing with active flow control technology

AbstractThe German research Cluster of Excellence SE2A (Sustainable and Energy Efficient Aviation) is investigating different technologies to be implemented in the following decades, to achieve more efficient air transportation. This paper studies the Hybrid Laminar Flow Control (HLFC) using boundary layer suction for drag reduction, combined with other technologies for load and structural weight reduction and a novel full-electric propulsion system. A multidisciplinary design optimisation framework is presented, enabling physics-based analysis and optimisation of a fully electric aircraft wing equipped with HLFC technologies and load alleviation, and new structures and materials. The main focus is on simulation and optimisation of the boundary layer suction and its influence on wing design and optimisation. A quasi three-dimensional aerodynamic analysis is used for drag estimation of the wing. The tool executes the aerofoil analysis using XFOILSUC, which provides accurate drag estimation through boundary layer suction. The optimisation is based on a genetic algorithm for maximum take-off weight (MTOW) minimisation. The optimisation results show that the active flow control applied on the optimised geometry results in more than 45% reduction in aircraft drag coefficient, compared to the same geometry without HLFC technology. The power absorbed for the HLFC suction system implies a battery mass variation lower than 2%, considering the designed range as top-level requirement (TLR).

Multidisciplinary design and optimization of expendable launch vehicle for microsatellite missions

PurposeThe capability to predict and evaluate various configurations’ performance during the conceptual design phase using multidisciplinary design analysis and optimization can significantly increase the preliminary design process’s efficiency and reduce design and development costs. This research paper aims to perform multidisciplinary design and optimization for an expendable microsatellite launch vehicle (MSLV) comprising three solid-propellant stages, capable of delivering micro-payloads in the low earth orbit. The methodology’s primary purpose is to increase the conceptual and preliminary design process’s efficiency by reducing both the design and development costs.Design/methodology/approachMultidiscipline feasible architecture is applied for the multidisciplinary design and optimization of an expendable MSLV at the conceptual level to accommodate interdisciplinary interactions during the optimization process. The multidisciplinary design and optimization framework developed and implemented in this research effort encompasses coupled analysis disciplines of vehicle geometry, mass calculations, aerodynamics, propulsion and trajectory. Nineteen design variables were selected to optimize expendable MSLV to launch a 100 kg satellite at an altitude of 600 km in the low earth orbit. Modern heuristic optimization methods such as genetic algorithm (GA), particle swarm optimization (PSO) and SA are applied and compared to obtain the optimal configurations. The initial population is created by passing the upper and lower bounds of design variables to the optimizer. The optimizer then searches for the best possible combination of design variables to obtain the objective function while satisfying the constraints.FindingsAll of the applied heuristic methods were able to optimize the design problem. Optimized design variables from these methods lie within the lower and upper bounds. This research successfully achieves the desired altitude and final injection velocity while satisfying all the constraints. In this research effort, multiple runs of heuristic algorithms reduce the fundamental stochastic error.Research limitations/implicationsThe use of multiple heuristics optimization methods such as GA, PSO and SA in the conceptual design phase owing to the exclusivity of their search approach provides a unique opportunity for exploration of the feasible design space and helps in obtaining alternative configurations capable of meeting the mission objectives, which is not possible when using any of the single optimization algorithm.Practical implicationsThe optimized configurations can be further used as baseline configurations in the microsatellite launch missions’ conceptual and preliminary design phases.Originality/valueSatellite launch vehicle design and optimization is a complex multidisciplinary problem, and it is dealt with effectively in the multidisciplinary design and optimization domain. It integrates several interlinked disciplines and gives the optimum result that satisfies these disciplines’ requirements. This research effort provides the multidisciplinary design and optimization-based simulation framework to predict and evaluate various expendable satellite launch vehicle configurations’ performance. This framework significantly increases the conceptual and preliminary design process’s efficiency by reducing design and development costs.

Multi-disciplinary framework for propeller blade design

Improved propeller designs are necessary to ensure an eco-friendly and resource-saving operation. The shape optimization of propellers involves different disciplines, which include the aerodynamics and the structural characteristics of the propeller. The requirements of the individual disciplines for the propeller design are contradictory and compromises must be made. To deal with this complex optimization task, a modular multi-disciplinary optimization framework is developed. The framework is based on a Python control script, which invokes the individual analysis modules. Within the framework, a blade element momentum theory approach for the aerodynamic analysis and a finite element method for the structural analysis are used. This allows for an efficient calculation of various designs. In a first step, a pure aerodynamic optimization is conducted. In a second step, structural constraints in form of the permissible material stress and the propeller blade tip deflection are considered. The results are compared to a design method, which calculates the blade shape for minimal induced losses.