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Joaquim R R A Martins - One of the best experts on this subject based on the ideXlab platform.

  • enabling large scale Multidisciplinary Design Optimization through adjoint sensitivity analysis
    Structural and Multidisciplinary Optimization, 2021
    Co-Authors: Joaquim R R A Martins, Graeme J Kennedy
    Abstract:

    This paper is written to honor Raphael T. Haftka’s seminal contributions to Multidisciplinary Design Optimization. We focus on those contributions that directly impacted our research, namely: the adjoint method for computing derivatives, wing aerostructural Design Optimization, and architectures for Multidisciplinary Design Optimization. For each of these topics, we describe Haftka’s contributions, how they impacted our research, and examples of what they enabled us to do. The overarching theme of the contributions and developments described in this paper is the efficient computation of derivatives, which, together with gradient-based optimizers, enables the Optimization with respect to large numbers of Design variables, even when using costly high-fidelity models.

  • Multidisciplinary Design Optimization Framework with Coupled Derivative Computation for Hybrid Aircraft
    Journal of Aircraft, 2020
    Co-Authors: Alessandro Sgueglia, Joaquim R R A Martins, Peter Schmollgruber, Nathalie Bartoli, Emmanuel Bénard, Joseph Morlier, John Jasa, John T. Hwang, Justin S. Gray
    Abstract:

    Hybrid-electric aircraft are a potential way to reduce the environmental footprint of aviation. Research aimed at this subject has been pursued over the last decade; nevertheless, at this stage, a full overall aircraft Design procedure is still an open issue. This work proposes to enrich the procedure for the conceptual Design of hybrid aircraft found in literature through the definition of a Multidisciplinary Design Optimization (MDO) framework aimed at handling Design problems for such kinds of aircraft. The MDO technique has been chosen because the hybrid aircraft Design problem shows more interaction between disciplines than a conventional configuration, and the classical approach based on Multidisciplinary Design analysis may neglect relevant features. The procedure has been tested on the case study of a single-aisle aircraft featuring hybrid propulsion with distributed electric ducted fans. The analysis considers three configurations (with 16, 32, and 48 electric motors) compared with a conventional baseline at the same 2035 technological horizon. To demonstrate the framework’s capability, these configurations are optimized with respect to fuel and energy consumption. It is shown that the hybrid-electric concept consumes less fuel/energy when it flies on short range due to the partial mission electrification. When one increases the Design range, penalties in weight introduced by hybrid propulsion overcome the advantages of electrified mission segment: the range for which hybrid aircraft have the same performance of the reference conventional aircraft is named the “breakdown range.” Starting from this range, the concept is no longer advantageous compared to conventional aircraft. Furthermore, a tradeoff between aerodynamic and propulsive efficiency is detected, and the optimal configuration is the one that balances these two effects. Finally, multiobjective Optimization is performed to establish a tradeoff between airframe weight and energy consumption.

  • Multidisciplinary Design Optimization of large wind turbines technical economic and Design challenges
    Energy Conversion and Management, 2016
    Co-Authors: Tamar Ashuri, M B Zaaijer, Joaquim R R A Martins, Jie Zhang
    Abstract:

    Wind energy has experienced a continuous cost reduction in the last decades. A popular cost reduction technique is to increase the rated power of the wind turbine by making it larger. However, it is not clear whether further upscaling of the existing wind turbines beyond the 5–7MW range is technically feasible and economically attractive. To address this question, this study uses 5, 10, and 20MW wind turbines that are developed using Multidisciplinary Design Optimization as upscaling data points. These wind turbines are upwind, 3-bladed, pitch-regulated, variable-speed machines with a tubular tower. Based on the Design data and properties of these wind turbines, scaling trends such as loading, mass, and cost are developed. These trends are used to study the technical and economical aspects of upscaling and its impact on the Design and cost. The results of this research show the technical feasibility of the existing wind turbines up to 20 MW, but the Design of such an upscaled machine is cost prohibitive. Mass increase of the rotor is identified as a main Design challenge to overcome. The results of this research support the development of alternative lightweight materials and Design concepts such as a two-bladed downwind Design for upscaling to remain a cost effective solution for future wind turbines.

  • Multidisciplinary Design Optimization of offshore wind turbines for minimum levelized cost of energy
    Renewable Energy, 2014
    Co-Authors: Tamar Ashuri, M B Zaaijer, G J W Van Bussel, Joaquim R R A Martins, G A M Van Kuik
    Abstract:

    This paper presents a method for Multidisciplinary Design Optimization of offshore wind turbines at system level. The formulation and implementation that enable the integrated aerodynamic and structural Design of the rotor and tower simultaneously are detailed. The objective function to be minimized is the levelized cost of energy. The model includes various Design constraints: stresses, deflections, modal frequencies and fatigue limits along different stations of the blade and tower. The rotor Design variables are: chord and twist distribution, blade length, rated rotational speed and structural thicknesses along the span. The tower Design variables are: tower thickness and diameter distribution, as well as the tower height. For the other wind turbine components, a representative mass model is used to include their dynamic interactions in the system. To calculate the system costs, representative cost models of a wind turbine located in an offshore wind farm are used. To show the potential of the method and to verify its usefulness, the 5 MW NREL wind turbine is used as a case study. The result of the Design Optimization process shows 2.3% decrease in the levelized cost of energy for a representative Dutch site, while satisfying all the Design constraints.

  • Multidisciplinary Design Optimization of offshore wind turbines for minimum levelized cost of energy
    Renewable Energy, 2014
    Co-Authors: Tamar Ashuri, M B Zaaijer, Joaquim R R A Martins, G J W Van Bussel, G A M Van Kuik
    Abstract:

    This paper presents a method for Multidisciplinary Design Optimization of offshore wind turbines at system level. The formulation and implementation that enable the integrated aerodynamic and structural Design of the rotor and tower simultaneously are detailed. The objective function to be minimized is the levelized cost of energy. The model includes various Design constraints: stresses, deflections, modal frequencies and fatigue limits along different stations of the blade and tower. The rotor Design variables are: chord and twist distribution, blade length, rated rotational speed and structural thicknesses along the span. The tower Design variables are: tower thickness and diameter distribution, as well as the tower height. For the other wind turbine components, a representative mass model is used to include their dynamic interactions in the system. To calculate the system costs, representative cost models of a wind turbine located in an offshore wind farm are used. To show the potential of the method and to verify its usefulness, the 5 MW NREL wind turbine is used as a case study. The result of the Design Optimization process shows 2.3% decrease in the levelized cost of energy for a representative Dutch site, while satisfying all the Design constraints.

Jie Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Surrogate based Multidisciplinary Design Optimization of lithium-ion battery thermal management system in electric vehicles
    Structural and Multidisciplinary Optimization, 2017
    Co-Authors: Xiaobang Wang, Xueguan Song, Mao Li, Jie Zhang
    Abstract:

    A battery thermal management system (BTMS) is a complex system that uses various heat removal and temperature control strategies to keep battery packs at optimal thermal conditions, thereby improving the lifetime and safety of lithium-ion battery packs in electric vehicles (EVs). However, an optimal Design of BTMS is still challenging, due to its large number of sub-systems and/or disciplines involved. To address this challenge, an air-based BTMS is hierarchically decoupled into four sub-systems and/or sub-disciplines in this paper, including the battery thermodynamics, fluid dynamics, structure, and lifetime model. A high-fidelity computational fluid dynamics (CFD) model is first developed to analyze the effects of key Design variables (i.e., heat flux, mass flow rate, and passage spacing size) on the performance of BTMS. Aiming to perform the Multidisciplinary Design Optimization (MDO) of BTMS based on the high-fidelity CFD model, surrogate models are developed using an automatic model selection method, the Concurrent Surrogate Model Selection (COSMOS). The surrogate models represent the BTMS performance metrics (i.e., the pressure difference between air inlet and outlet, the maximum temperature difference among battery cells, and the average temperature of the battery pack) as functions of key Design parameters. The objectives are to maximize the battery lifetime and to minimize the battery volume, the fan’s power, and the temperature difference among different cells. The MDO results show that the lifetime of the battery module is significantly improved by reducing the temperature difference and battery volume.

  • Multidisciplinary Design Optimization of tunnel boring machine considering both structure and control parameters under complex geological conditions
    Structural and Multidisciplinary Optimization, 2016
    Co-Authors: Xiaobang Wang, Lintao Wang, Jie Zhang, Xueguan Song
    Abstract:

    A Tunnel Boring Machine (TBM) is an extremely large and complex engineering machine that usually works under a complicated geological environment to excavate tunnel underground. Considering the large number of sub-systems that usually belong to different disciplines, it is a challenging task to define, model, and optimize the whole TBM from the perspective of system engineering. Also, due to the complex mechanism and geological environment, the flexibility and efficiency of existing TBM excavation strategies are generally limited. To address these challenges, a Multidisciplinary modeling is presented so that corresponding analytical or empirical models of each sub-system are formulated, and a Multidisciplinary Design Optimization (MDO) method is applied to the TBM system Optimization. Four excavation strategies are studied and compared, including: (i) two existing excavation strategies, and (ii) two new proposed excavation strategies by making control and/or structure parameters adaptive to geological conditions. Two case studies with these four excavation strategies are presented to illustrate the effectiveness and benefits of Designing TBM using MDO methodologies. Wherein, Case I aims to minimize the construction period taking into account the restriction of sub-systems, and Case II simultaneously minimizes construction period, cost, and energy consumption. Since the resulting MDO formulation is straightforward to be solved as a single problem, the All-At-Once (AAO) method is utilized in this paper. The Optimization results obtained by modeling the problem as MDO show that the excavation strategy with adaptive control and structure parameters can significantly reduce the total construction time, with lower cost and energy consumption.

  • Multidisciplinary Design Optimization of large wind turbines technical economic and Design challenges
    Energy Conversion and Management, 2016
    Co-Authors: Tamar Ashuri, M B Zaaijer, Joaquim R R A Martins, Jie Zhang
    Abstract:

    Wind energy has experienced a continuous cost reduction in the last decades. A popular cost reduction technique is to increase the rated power of the wind turbine by making it larger. However, it is not clear whether further upscaling of the existing wind turbines beyond the 5–7MW range is technically feasible and economically attractive. To address this question, this study uses 5, 10, and 20MW wind turbines that are developed using Multidisciplinary Design Optimization as upscaling data points. These wind turbines are upwind, 3-bladed, pitch-regulated, variable-speed machines with a tubular tower. Based on the Design data and properties of these wind turbines, scaling trends such as loading, mass, and cost are developed. These trends are used to study the technical and economical aspects of upscaling and its impact on the Design and cost. The results of this research show the technical feasibility of the existing wind turbines up to 20 MW, but the Design of such an upscaled machine is cost prohibitive. Mass increase of the rotor is identified as a main Design challenge to overcome. The results of this research support the development of alternative lightweight materials and Design concepts such as a two-bladed downwind Design for upscaling to remain a cost effective solution for future wind turbines.

Tamar Ashuri - One of the best experts on this subject based on the ideXlab platform.

  • Multidisciplinary Design Optimization of large wind turbines technical economic and Design challenges
    Energy Conversion and Management, 2016
    Co-Authors: Tamar Ashuri, M B Zaaijer, Joaquim R R A Martins, Jie Zhang
    Abstract:

    Wind energy has experienced a continuous cost reduction in the last decades. A popular cost reduction technique is to increase the rated power of the wind turbine by making it larger. However, it is not clear whether further upscaling of the existing wind turbines beyond the 5–7MW range is technically feasible and economically attractive. To address this question, this study uses 5, 10, and 20MW wind turbines that are developed using Multidisciplinary Design Optimization as upscaling data points. These wind turbines are upwind, 3-bladed, pitch-regulated, variable-speed machines with a tubular tower. Based on the Design data and properties of these wind turbines, scaling trends such as loading, mass, and cost are developed. These trends are used to study the technical and economical aspects of upscaling and its impact on the Design and cost. The results of this research show the technical feasibility of the existing wind turbines up to 20 MW, but the Design of such an upscaled machine is cost prohibitive. Mass increase of the rotor is identified as a main Design challenge to overcome. The results of this research support the development of alternative lightweight materials and Design concepts such as a two-bladed downwind Design for upscaling to remain a cost effective solution for future wind turbines.

  • Multidisciplinary Design Optimization of offshore wind turbines for minimum levelized cost of energy
    Renewable Energy, 2014
    Co-Authors: Tamar Ashuri, M B Zaaijer, G J W Van Bussel, Joaquim R R A Martins, G A M Van Kuik
    Abstract:

    This paper presents a method for Multidisciplinary Design Optimization of offshore wind turbines at system level. The formulation and implementation that enable the integrated aerodynamic and structural Design of the rotor and tower simultaneously are detailed. The objective function to be minimized is the levelized cost of energy. The model includes various Design constraints: stresses, deflections, modal frequencies and fatigue limits along different stations of the blade and tower. The rotor Design variables are: chord and twist distribution, blade length, rated rotational speed and structural thicknesses along the span. The tower Design variables are: tower thickness and diameter distribution, as well as the tower height. For the other wind turbine components, a representative mass model is used to include their dynamic interactions in the system. To calculate the system costs, representative cost models of a wind turbine located in an offshore wind farm are used. To show the potential of the method and to verify its usefulness, the 5 MW NREL wind turbine is used as a case study. The result of the Design Optimization process shows 2.3% decrease in the levelized cost of energy for a representative Dutch site, while satisfying all the Design constraints.

  • Multidisciplinary Design Optimization of offshore wind turbines for minimum levelized cost of energy
    Renewable Energy, 2014
    Co-Authors: Tamar Ashuri, M B Zaaijer, Joaquim R R A Martins, G J W Van Bussel, G A M Van Kuik
    Abstract:

    This paper presents a method for Multidisciplinary Design Optimization of offshore wind turbines at system level. The formulation and implementation that enable the integrated aerodynamic and structural Design of the rotor and tower simultaneously are detailed. The objective function to be minimized is the levelized cost of energy. The model includes various Design constraints: stresses, deflections, modal frequencies and fatigue limits along different stations of the blade and tower. The rotor Design variables are: chord and twist distribution, blade length, rated rotational speed and structural thicknesses along the span. The tower Design variables are: tower thickness and diameter distribution, as well as the tower height. For the other wind turbine components, a representative mass model is used to include their dynamic interactions in the system. To calculate the system costs, representative cost models of a wind turbine located in an offshore wind farm are used. To show the potential of the method and to verify its usefulness, the 5 MW NREL wind turbine is used as a case study. The result of the Design Optimization process shows 2.3% decrease in the levelized cost of energy for a representative Dutch site, while satisfying all the Design constraints.

Jafar Roshanian - One of the best experts on this subject based on the ideXlab platform.

  • Multidisciplinary Design Optimization of space transportation control system using genetic algorithm
    Proceedings of the Institution of Mechanical Engineers Part G: Journal of Aerospace Engineering, 2014
    Co-Authors: Jafar Roshanian, Masoud Ebrahimi, Ehsan Taheri, Ali A Bataleblu
    Abstract:

    In this study, due to the innate trans-atmospheric nature of flight of the space transportation system, assessment of the control discipline interaction with aerodynamic, weights and sizing, external fin-stabilizers configuration, and trajectory disciplines in an Multidisciplinary Design Optimization-based platform has been addressed. Parameters considered for the control sub-system Optimization are external stabilizing fins geometrical characteristics and attitude control vernier motors thrust value. Specifically, this article addresses Optimization of fin–body combinations with geometric constraints for minimizing control moment required by vernier motors as well as total possible control sub-system weight satisfying Design constraints. Results show that using external stabilizer fins is not economical from energetic stand point for space transportation system, but is necessary for control subsystems when there are deflection constraints for vernier motors.

  • latin hypercube sampling applied to reliability based Multidisciplinary Design Optimization of a launch vehicle
    Aerospace Science and Technology, 2013
    Co-Authors: Jafar Roshanian, Masoud Ebrahimi
    Abstract:

    Abstract In this paper, Reliability-Based Multidisciplinary Design Optimization (RBMDO) of a two-stage solid propellant expendable launch vehicle (LV) is investigated. Propulsion, weight, aerodynamics (geometry) and trajectory (performance) disciplines are used in an appropriate combination. Throw weight minimization is chosen as objective function. Design variables for system level Optimization are selected from propulsion, geometry and trajectory disciplines. Mission constraints contain the final velocity, the height above ground, and flight path angle. The constraints that appear during the flight are also considered. Assuming a normal distribution for the uncertain variables, Latin Hypercube Sampling (LHS) method selects the sample values for simulation runs which are eventually utilized for calculating probability density function of constraints and their reliability at each Design point. Sequential Quadratic Programming (SQP) technique is used to achieve the optimal solution. Although the launch vehicle throw weight is increased negligibly in comparison with deterministic Optimization, results show that the reliability-based method satisfied desired reliability of the constraints.

  • Multidisciplinary Design Optimization of a small solid propellant launch vehicle using system sensitivity analysis
    Structural and Multidisciplinary Optimization, 2009
    Co-Authors: Jahangir Jodei, Masoud Ebrahimi, Jafar Roshanian
    Abstract:

    Multidisciplinary Design Optimization approaches have significant effects on aerospace vehicle Design methodology. In Designing next generation of space launch systems, MDO processes will face new and greater challenges. This study develops a system sensitivity analysis method to optimize Multidisciplinary Design of a two-stage small solid propellant launch vehicle. Suitable Design variables, technological, and functional constraints are considered. Appropriate combinations of disciplines such as propulsion, weight, geometry, and trajectory simulation are used. A generalized sensitivity equation is developed and solved. These results are basis for Optimization. Comparison of the developed approach with gradient Optimization methods reveals that developed approach requires less computation time.

Abdelhamid Chriette - One of the best experts on this subject based on the ideXlab platform.

  • A survey of Multidisciplinary Design Optimization methods in launch vehicle Design
    Structural and Multidisciplinary Optimization, 2012
    Co-Authors: Mathieu Balesdent, Nicolas Bérend, Philippe Dépincé, Abdelhamid Chriette
    Abstract:

    Optimal Design of launch vehicles is a complex problem which requires the use of specific techniques called Multidisciplinary Design Optimization (MDO) methods. MDO methodologies are applied in various domains and are an interesting strategy to solve such an Optimization problem. This paper surveys the different MDO methods and their applications to launch vehicle Design. The paper is focused on the analysis of the launch vehicle Design problem and brings out the advantages and the drawbacks of the main MDO methods in this specific problem. Some characteristics such as the robustness, the calculation costs, the flexibility, the convergence speed or the implementation difficulty are considered in order to determine the methods which are the most appropriate in the launch vehicle Design framework. From this analysis, several ways of improvement of the MDO methods are proposed to take into account the specificities of the launch vehicle Design problem in order to improve the efficiency of the Optimization process.