Relevant bibliographies by topics / Multidisciplinary design analysis and optimization / Journal articles

To see the other types of publications on this topic, follow the link: Multidisciplinary design analysis and optimization.

Journal articles on the topic 'Multidisciplinary design analysis and optimization'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 June 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Multidisciplinary design analysis and optimization.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

Shin, Moon-Kyun, and Gyung-Jin Park. "Multidisciplinary design optimization based on independent subspaces." International Journal for Numerical Methods in Engineering 64, no. 5 (2005): 599–617. http://dx.doi.org/10.1002/nme.1380.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Chu, X. Z., L. Gao, W. D. Li, H. B. Qiu, and X. Y. Shao. "An Uncertainty Analysis Approach to Multidisciplinary Design Optimization." Concurrent Engineering 17, no. 2 (2009): 121–28. http://dx.doi.org/10.1177/1063293x09105327.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Vlahopoulos, N., and C. G. Hart. "A Multidisciplinary Design Optimization Approach to Relating Affordability and Performance in a Conceptual Submarine Design." Journal of Ship Production and Design 26, no. 04 (2010): 273–89. http://dx.doi.org/10.5957/jspd.2010.26.4.273.

Full text

Abstract:

A multidisciplinary design optimization (MDO) framework is used for a conceptual submarine design study. Four discipline-level performances—internal deck area, powering, maneuvering, and structural analysis—are optimized simultaneously. The four discipline-level optimizations are driven by a system level optimization that minimizes the manufacturing cost while at the same time coordinates the exchange of information and the interaction among the discipline-level optimizations. Thus, the interaction among individual optimizations is captured along with the impact of the physical characteristics of the design on the manufacturing cost. A geometric model for the internal deck area of a submarine is created, and resistance, structural design, and maneuvering models are adapted from theoretical information available in the literature. These models are employed as simulation drivers in the discipline-level optimizations. Commercial cost-estimating software is leveraged to create a sophisticated, automated affordability model for the fabrication of a submarine pressure hull at the system level. First, each one of the four discipline optimizations and also the cost-related top level optimization are performed independently. As expected, five different design configurations result, one from each analysis. These results represent the "best" solution from each individual discipline optimization, and they are used as reference for comparison with the MDO solution. The deck area, resistance, structural, maneuvering, and affordability models are then synthesized into a multidisciplinary optimization statement reflecting a conceptual submarine design problem. The results from this coordinated MDO capture the interaction among disciplines and demonstrate the value that the MDO system offers in consolidating the results to a single design that improves the discipline-level objective functions while at the same time produces the highest possible improvement at the system level.

APA, Harvard, Vancouver, ISO, and other styles

Xu, Huanwei, Wei Li, Liudong Xing, and Shun-Peng Zhu. "Multidisciplinary design optimization under correlated uncertainties." Concurrent Engineering 25, no. 3 (2017): 262–75. http://dx.doi.org/10.1177/1063293x17697456.

Full text

Abstract:

Uncertainty analysis is a hot research topic in multidisciplinary design optimization for complex mechanical systems. Existing multidisciplinary design optimization works typically assume that uncertainties are uncorrelated of each other. In real-world engineering systems, however, correlations do exist between different uncertainties. The multidisciplinary design optimization methods without considering correlations between uncertainties may cause inaccuracy and thus misleading optimization results. In this article, we make contributions by proposing a new multidisciplinary design optimization approach based on the ellipsoidal set theory to investigate the characteristics of correlated uncertainties and incorporate their effects in the multidisciplinary design optimization through an advanced collaborative optimization method, where the quantitative model of correlated uncertainties is transformed into constrains of subsystems. Both a mathematical example and a case study of an engineering system are provided to illustrate feasibility and validity of the proposed method.

APA, Harvard, Vancouver, ISO, and other styles

Kurdi, Mohammad. "A Structural Optimization Framework for Multidisciplinary Design." Journal of Optimization 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/345120.

Full text

Abstract:

This work describes the development of a structural optimization framework adept at accommodating diverse customer requirements. The purpose is to provide a framework accessible to the optimization research analyst. The framework integrates the method of moving asymptotes into the finite element analysis program (FEAP) by exploiting the direct interface capability in FEAP. Analytic sensitivities are incorporated to provide a robust and efficient optimization search. User macros are developed to interface the design algorithm and analytic sensitivity with the finite element analysis program. To test the optimization tool and sensitivity calculations, three sizing and one topology optimization problems are considered. In addition, flutter analysis of a heated panel is analyzed as an example of coupling to nonstructural discipline. In sizing optimization, the calculated semianalytic sensitivities match analytic and finite difference calculations. Differences between analytic designs and numerical ones are less than 2.0% and are attributed to discrete nature of finite elements. In the topology problem, quadratic elements are found robust at resolving checkerboard patterns.

APA, Harvard, Vancouver, ISO, and other styles

Mohammad Zadeh, Parviz, and Mohadeseh Sadat Shirazi. "Multidisciplinary design optimization architecture to concurrent design of satellite systems." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 10 (2016): 1898–916. http://dx.doi.org/10.1177/0954410016665412.

Full text

Abstract:

The design of space systems is a complex and multidisciplinary process with multiple conflicting objectives, large number of design variables, and constraints that limits application of the existing multidisciplinary design optimization architectures to this class of design problems. This paper presents an enhanced multidisciplinary design optimization architecture to concurrent holistic design optimization of a satellite system. The proposed multidisciplinary design optimization architecture extends concepts of multidiscipline feasible and bi-level integrated system synthesis into a unified architecture using metamodels. The proposed architecture was evaluated and compared with the existing multidisciplinary design optimization architectures that include all-at-once, bi-level integrated system synthesis, and multidisciplinary design optimization using a remote sensing small satellite in low earth orbit. The satellite design optimization problem deals with the minimization of the total mass of the satellite, involving disciplines of mission analysis, payload, structures, attitude determination and control, communication, command and data handling, power and thermal. The computational performance and accuracy of the proposed architecture were compared with multidisciplinary design optimization benchmark problems. Then the proposed architecture is successfully applied to the satellite system design problem. The results obtained show that metamodel-based bi-level integrated system synthesis-multidisciplinary design optimization architecture presented in this paper provides an effective way of solving large-scale design problems.

APA, Harvard, Vancouver, ISO, and other styles

Brevault, Loïc, Mathieu Balesdent, and Sébastien Defoort. "Preliminary study on launch vehicle design: Applications of multidisciplinary design optimization methodologies." Concurrent Engineering 26, no. 1 (2017): 93–103. http://dx.doi.org/10.1177/1063293x17737131.

Full text

Abstract:

The design of complex systems such as launch vehicles involves different fields of expertise that are interconnected. To perform multidisciplinary studies, concurrent engineering aims at providing a collaborative environment which often relies on data set exchange. In order to efficiently achieve system-level analyses (uncertainty propagation, sensitivity analysis, optimization, etc.), it is necessary to go beyond data set exchange which limits the capabilities of performance assessments. Multidisciplinary design optimization methodologies is a collection of engineering methodologies to optimize systems modelled as a set of coupled disciplinary analyses and is a key enabler to extend concurrent engineering capabilities. This article is focused on several examples of recent developments of multidisciplinary design optimization methodologies (e.g. multidisciplinary design optimization with transversal decomposition of the design process, multidisciplinary design optimization under uncertainty) with applications to launch vehicle design to illustrate the benefices of taking into account the coupling effects between the different physics all along the design process. These methods enable to manage the complexity of the involved physical phenomena and their interactions in order to generate innovative concepts such as reusable launch vehicles beyond existing solutions.

APA, Harvard, Vancouver, ISO, and other styles

Lee, Jae-Woo, Seok-Min Choi, Nguyen Nhu Van, Ji-Min Kim, and Yung-Hwan Byun. "Multidisciplinary UAV Design Optimization Implementing Multi-Fidelity Analysis Techniques." Journal of the Korean Society for Aeronautical & Space Sciences 40, no. 8 (2012): 695–702. http://dx.doi.org/10.5139/jksas.2012.40.8.695.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Lin, JiGuan G. "Analysis and Enhancement of Collaborative Optimization for Multidisciplinary Design." AIAA Journal 42, no. 2 (2004): 348–60. http://dx.doi.org/10.2514/1.9098.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Sun, Yicheng, and Howard Smith. "Low-boom low-drag optimization in a multidisciplinary design analysis optimization environment." Aerospace Science and Technology 94 (November 2019): 105387. http://dx.doi.org/10.1016/j.ast.2019.105387.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Peri, Daniele, and Emilio F. Campana. "Multidisciplinary Design Optimization of a Naval Surface Combatant." Journal of Ship Research 47, no. 01 (2003): 1–12. http://dx.doi.org/10.5957/jsr.2003.47.1.1.

Full text

Abstract:

Whereas shape optimal design has received considerable attention in many industrial contexts, the application of automatic optimization procedures to hydrodynamic ship design has not yet reached the same maturity. Nevertheless, numerical tools, combining together modern computational fluid dynamics and optimization methods, can aid in the ship design, enhancing the operational performances and reducing development and construction costs. This paper represents an attempt of applying a multidisciplinary design optimization (MDO) procedure to the enhancement of the performances of an existing ship. At the present stage the work involves modeling, development, and implementation of algorithms only for the hydrodynamic optimization. For a naval surface combatant, the David Taylor Model Basin (DTMB) model ship 5415, a three-objective functions optimization for a two-discipline design problem is devised and solved in the framework of the MDO approach. A simple decision maker is used to order the Pareto optimal solutions, and a gradient-based refinement is performed on the selected design.

APA, Harvard, Vancouver, ISO, and other styles

Sridharan, Ananth, and Bharath Govindarajan. "A MultiDisciplinary Optimization Approach for Sizing Vertical Lift Aircraft." Journal of the American Helicopter Society 67, no. 2 (2022): 1–15. http://dx.doi.org/10.4050/jahs.67.022004.

Full text

Abstract:

This paper presents an approach to reframe the sizing problem for vertical-lift unmanned aerial vehicles (UAVs) as an optimization problem and obtains a weight-optimal solution with up to two orders of magnitude of savings in wall clock time. Because sizing is performed with higher fidelity models and design variables from several disciplines, the Simultaneous Analysis aNd Design (SAND) approach from fixed-wing multidisciplinary optimization literature is adapted for the UAV sizing task. Governing equations and disciplinary design variables that are usually self-contained within disciplines (airframe tube sizes, trim variables, and trim equations) are migrated to the sizing optimizer and added as design variables and (in)equality constraints. For sizing consistency, the iterative weight convergence loop is replaced by a coupling variable and associated equality consistency constraint for the sizing optimizer. Cruise airspeed is also added as a design variable and driven by the sizing optimizer. The methodology is demonstrated for sizing a package delivery vehicle (a lift-augment quadrotor biplane tailsitter) with up to 39 design variables and 201 constraints. Gradient-based optimizations were initiated from different starting points; without blade shape design in sizing, all processes converged to the same minimum, indicating that the design space is convex for the chosen bounds, constraints, and objective function. Several optimization schemes were investigated by moving combinations of relevant disciplines (airframe sizing with finite element analysis, vehicle trim, and blade aerodynamic shape design) to the sizing optimizer. The biggest advantage of the SAND strategy is its scope for parallelization, and the inherent ability to drive the design away from regions where disciplinary analyses (e. g., trim) cannot find a solution, obviating the need for ad hoc penalty functions. Even in serial mode, the SAND optimization strategy yields results in the shortest wall clock time compared to all other approaches.

APA, Harvard, Vancouver, ISO, and other styles

Adami, Amirhossein, Mahdi Mortazavi, Mehran Nosratollahi, Mohammadreza Taheri, and Jalal Sajadi. "Multidisciplinary Design Optimization and Analysis of Hydrazine Monopropellant Propulsion System." International Journal of Aerospace Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/295636.

Full text

Abstract:

Monopropellant propulsion systems are widely used especially for low cost attitude control or orbit correction (orbit maintenance). To optimize the total propulsion system, subsystems should be optimized. Chemical decomposition, aerothermodynamics, and structure disciplines demand different optimum condition such as tank pressure, catalyst bed length and diameter, catalyst bed pressure, and nozzle geometry. Subsystem conflicts can be solved by multidisciplinary design optimization (MDO) technique with simultaneous optimization of all subsystems with respect to any criteria and limitations. In this paper, monopropellant propulsion system design algorithm is presented and the results of the proposed algorithm are validated. Then, multidisciplinary design optimization of hydrazine propulsion system is proposed. The goal of optimization can be selected as minimizing the total mass (including propellant), minimizing the propellant mass (maximizing the Isp), or minimizing the dry mass. Minimum total mass, minimum propellant mass, and minimum dry mass are derived using MDO technique. It is shown that minimum total mass, minimum dry mass, and minimum propellant mass take place in different conditions. The optimum parameters include bed-loading, inlet pressure, mass flow, nozzle geometry, catalyst bed length and diameter, propellant tank mass, specific impulse (Isp), and feeding mass which are derived using genetic algorithm (GA).

APA, Harvard, Vancouver, ISO, and other styles

Pilcher, Chris, Joon Chung, and Michael Ringshandl. "A multidisciplinary design optimization approach to preliminary wing design using multifidelity analysis." Canadian Aeronautics and Space Journal 58, no. 02 (2012): 95–104. http://dx.doi.org/10.5589/q12-008.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Mishra, Soumya Ranjan, and Kamran Behdinan. "MULTIDISCIPLINARY DESIGN ANALYSIS AND OPTIMIZATION FRAMEWORK FOR REGULATORY DRIVEN MEDICAL DEVICE DEVELOPMENT." Proceedings of the Design Society 3 (June 19, 2023): 2735–44. http://dx.doi.org/10.1017/pds.2023.274.

Full text

Abstract:

AbstractMultidisciplinary design optimization (MDO) is a technique used in the design of systems involving the integration of many disciplines. The architecture and formulation of MDO has an impact on the solution time and optimality of final designs. The process of developing medical devices requires the combination of medical and technical knowledge and abilities. Developing a medical device is done by a complicated collection of Product Development Processes that entail tremendous oversight to ensure conformity to regulatory requirements. Regulatory standards often provide stern “Go / No-Go” policies which may discretize the design variables further increasing the complexity of the optimization problem. This work proposes a novel design approach which utilizes systems engineering practices to undertake complex multidisciplinary design optimization while implementing regulatory guidelines for medical devices. The formulated model is then applied and examined in a case study towards the development of a piezoelectric respiratory sensor. It is observed that the novel framework would extensively improve the design space definition and process driven product development practices.

APA, Harvard, Vancouver, ISO, and other styles

Zhang, Qiang, Jihong Liu, and Xu Chen. "Multidisciplinary Reliability Design Optimization Modeling Based on SysML." Applied Sciences 14, no. 17 (2024): 7558. http://dx.doi.org/10.3390/app14177558.

Full text

Abstract:

Model-Based Systems Engineering (MBSE) supports the system-level design of complex products effectively. Currently, system design and optimization for complex products are two distinct processes that must be executed using different software or platforms, involving intricate data conversion processes. Applying multidisciplinary optimization to validate system optimization often necessitates remodeling the optimization objects, which is time-consuming, labor-intensive, and highly error-prone. A critical activity in systems engineering is identifying the optimal design solution for the entire system. Multidisciplinary Design Optimization (MDO) and reliability analysis are essential methods for achieving this. This paper proposes a SysML-based multidisciplinary reliability design optimization modeling method. First, by analyzing the definitions and mathematical models of multidisciplinary reliability design optimization, the SysML extension mechanism is employed to represent the optimization model based on SysML. Next, model transformation techniques are used to convert the SysML optimization model generated in the first stage into an XML description model readable by optimization solvers. Finally, the proposed method’s effectiveness is validated through an engineering case study of an in-vehicle environmental control integration system. The results demonstrate that this method fully utilizes SysML to express MDO problems, enhancing the efficiency of design optimization for complex systems. Engineers and system designers working on complex, multidisciplinary projects can particularly benefit from these advancements, as they simplify the integration of design and optimization processes, facilitating more reliable and efficient product development.

APA, Harvard, Vancouver, ISO, and other styles

Yifei, Tong, Ye Wei, Yang Zhen, Li Dongbo, and Li Xiangdong. "Research on Multidisciplinary Optimization Design of Bridge Crane." Mathematical Problems in Engineering 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/763545.

Full text

Abstract:

Bridge crane is one of the most widely used cranes in our country, which is indispensable equipment for material conveying in the modern production. In this paper, the framework of multidisciplinary optimization for bridge crane is proposed. The presented research on crane multidisciplinary design technology for energy saving includes three levels, respectively: metal structures level, transmission design level, and electrical system design level. The shape optimal mathematical model of the crane is established for shape optimization design of metal structure level as well as size optimal mathematical model and topology optimal mathematical model of crane for topology optimization design of metal structure level is established. Finally, system-level multidisciplinary energy-saving optimization design of bridge crane is further carried out with energy-saving transmission design results feedback to energy-saving optimization design of metal structure. The optimization results show that structural optimization design can reduce total mass of crane greatly by using the finite element analysis and multidisciplinary optimization technology premised on the design requirements of cranes such as stiffness and strength; thus, energy-saving design can be achieved.

APA, Harvard, Vancouver, ISO, and other styles

Martins, Joaquim R. R. A., and Graeme J. Kennedy. "Enabling large-scale multidisciplinary design optimization through adjoint sensitivity analysis." Structural and Multidisciplinary Optimization 64, no. 5 (2021): 2959–74. http://dx.doi.org/10.1007/s00158-021-03067-y.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Full text

APA, Harvard, Vancouver, ISO, and other styles

Gray, Justin, Kenneth T. Moore, Tristan A. Hearn, and Bret A. Naylor. "Standard Platform for Benchmarking Multidisciplinary Design Analysis and Optimization Architectures." AIAA Journal 51, no. 10 (2013): 2380–94. http://dx.doi.org/10.2514/1.j052160.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Huang, Hong-Zhong, Xiaoling Zhang, Wei Yuan, Debiao Meng, and Xudong Zhang. "Collaborative Reliability Analysis under the Environment of Multidisciplinary Design Optimization." Concurrent Engineering 19, no. 3 (2011): 245–54. http://dx.doi.org/10.1177/1063293x11420177.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Ma, Rong, Ke-ping Zhou, and Feng Gao. "Stability analysis of underground engineering based on multidisciplinary design optimization." Journal of Coal Science and Engineering (China) 14, no. 4 (2008): 608–12. http://dx.doi.org/10.1007/s12404-008-0422-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Wang, Lei, Chuang Xiong, Juxi Hu, Xiaojun Wang, and Zhiping Qiu. "Sequential multidisciplinary design optimization and reliability analysis under interval uncertainty." Aerospace Science and Technology 80 (September 2018): 508–19. http://dx.doi.org/10.1016/j.ast.2018.07.029.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Mastroddi, Franco, and Stefania Gemma. "Analysis of Pareto frontiers for multidisciplinary design optimization of aircraft." Aerospace Science and Technology 28, no. 1 (2013): 40–55. http://dx.doi.org/10.1016/j.ast.2012.10.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Xu, Huanwei, Wei Li, Mufeng Li, Cong Hu, Suichuan Zhang, and Xin Wang. "Multidisciplinary robust design optimization based on time-varying sensitivity analysis." Journal of Mechanical Science and Technology 32, no. 3 (2018): 1195–207. http://dx.doi.org/10.1007/s12206-018-0223-8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Hosseini, Saeed, Mohammad Ali Vaziry-Zanjany, and Hamid Reza Ovesy. "A Framework for Aircraft Conceptual Design and Multidisciplinary Optimization." Aerospace 11, no. 4 (2024): 273. http://dx.doi.org/10.3390/aerospace11040273.

Full text

Abstract:

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 (Laboratory of Aircraft Multidisciplinary Knowledge-Based Design and Analysis) 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.

APA, Harvard, Vancouver, ISO, and other styles

Deng, Jian, Guangming Zhou, and Yu Qiao. "Multidisciplinary design optimization of sandwich-structured radomes." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 1 (2018): 179–89. http://dx.doi.org/10.1177/0954406218757268.

Full text

Abstract:

A multidisciplinary design optimization framework is proposed for sandwich-structured radomes. Radomes ensure the functional operation of antenna systems in adverse environment catering for aerodynamic stresses and payload requirements. The existence of radomes can partially degrade the electromagnetic performance of antenna systems. The electromagnetic performance and mechanical responses are taken into account simultaneously in the optimization design. This is more time-saving and economical compared to the traditional separate considerations on these two aspects. Coupled with multi-island genetic algorithm, transmission coefficient and boresight error are identified as the objectives. Lateral deformation, material failure, and structural stability are included in mechanical analysis. Three-dimensional ray-tracing technique and physical optics based aperture integration method are employed to address interactions between the antenna and radome. Tsai–Wu and maximum stress criteria are used to predict material failure. Structural stability is analyzed using the linear perturbation of stiffness matrices. The applicability of the electromagnetic model is validated using examples of a hemispheric air and single-layered radome. A numerical experiment is conducted to investigate the utility and feasibility of the multidisciplinary design optimization model. Results show that the optimal section profile brings about considerable improvement in transmission coefficient and boresight error. Mechanical constrains are reasonably subjected to the preset limits. Hence, the proposed multidisciplinary design optimization model is an effective and feasible alternative in the environment of radome design.

APA, Harvard, Vancouver, ISO, and other styles

Lei, Li, and Zhang Jianrun. "Multidisciplinary Design Optimization of Distribution Cam Mechanism of Diesel Engine." Applied Mathematics & Information Sciences 7, no. 5 (2013): 1957–62. http://dx.doi.org/10.12785/amis/070534.

Full text

APA, Harvard, Vancouver, ISO, and other styles

MIELOSZYK, Jacek, Tomasz GOETZENDORF-GRABOWSKI, and Dawid MIESZALSKI. "RAPID GEOMETRY DEFINITION FOR MULTIDISCIPLINARY DESIGN AND ANALYSIS OF AN AIRCRAFT." Aviation 20, no. 2 (2016): 60–64. http://dx.doi.org/10.3846/16487788.2016.1195066.

Full text

Abstract:

Conceptual and preliminary design level of aircraft design is searching for an easy, flexible and efficient way of computational geometry definition. Accelerating the process of geometry definition is the basic step for acceleration of all computations. It also enables optimization, where changes of numerical model are made automatically according to the optimization algorithms. The geometry definition has to be robust, free from errors and stay feasible.

APA, Harvard, Vancouver, ISO, and other styles

Chai, Mengjiang, Yongliang Yuan, and Wenjuan Zhao. "An improved particle swarm optimization algorithm for dynamic analysis of chain drive based on multidisciplinary design optimization." Advances in Mechanical Engineering 11, no. 3 (2019): 168781401982961. http://dx.doi.org/10.1177/1687814019829611.

Full text

Abstract:

Chain drive is one of the most commonly used mechanical devices in the main equipment transmission system. In the past decade, scholars focused on basic performance research, but ignore its best performance. In this study, due to the large vibration of the chain drive in the transmission system, the vibration performance and optimization parameters are also considered as a new method to design the chain drive system to obtain the best performance of the chain drive system. This article proposes a new method and takes a chain drive design as a case based on the multidisciplinary design optimization. The system optimization objective and sub-systems are established by the multidisciplinary design optimization method. To obtain the best performance for the chain, the chain drive is executed by an improved particle swarm optimization algorithm. Dynamic characteristics of the chain drive system are simulated based on the multidisciplinary design optimization results. The impact force of the chain links, vibration displacement, and the vibration frequency are analyzed. The results show that the kinematics principle of the chain drive and the optimal parameter value are obtained based on the multidisciplinary design optimization method.

APA, Harvard, Vancouver, ISO, and other styles

Bi, Wei, Wenhua Chen, and Jun Pan. "Multidisciplinary Reliability Design Considering Hybrid Uncertainty Incorporating Deep Learning." Wireless Communications and Mobile Computing 2022 (November 18, 2022): 1–11. http://dx.doi.org/10.1155/2022/5846684.

Full text

Abstract:

Multidisciplinary reliability design optimization is considered an effective method for solving complex product design optimization problems under the influence of uncertainty factors; however, the high computational cost seriously affects its application in practice. As an important part of multidisciplinary reliability design optimization, multidisciplinary reliability analysis plays a direct leading role in its computational efficiency. At present, multidisciplinary reliability analysis under mixed uncertainty is still nested or sequential execution mode, which leads to the problem of poor disciplinary autonomy and inefficiency in the reliability analysis of complex products. To this end, a multidisciplinary reliability assessment method integrating deep neural networks and probabilistic computational models under mixed uncertainty is proposed for the problem of multidisciplinary reliability analysis under mixed uncertainty. The method considers the stochastic-interval-fuzzy uncertainty, decouples the nested multidisciplinary probability analysis, multidisciplinary likelihood analysis, and multidisciplinary interval analysis, uses deep neural networks to extract subdisciplinary high-dimensional features, and fuses them with probabilistic computational models. Moreover, the whole system is divided into several independent subsystems, then the collected reliability data are classified, and the fault data are attributed to each subsystem. Meanwhile, the environmental conditions of the system are considered, and the corresponding environmental factors are added as input neurons along with each subsystem. In this paper, the effectiveness of the proposed method is verified on numerical calculations and real inverter power failure data.

APA, Harvard, Vancouver, ISO, and other styles

Zhang, Jun, and Bing Zhang. "A Collaborative Approach for Multidisciplinary Systems Reliability Design and Optimization." Advanced Materials Research 694-697 (May 2013): 911–14. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.911.

Full text

Abstract:

In order to improve the efficiency and robustness of reliability-based multidisciplinary design optimization (RBMDO), a new collaborative strategy (named C-RBMDO) which integrates performance measure approach (PMA) and concurrent subspace optimization strategy (CSSO) is proposed. Both the mathematical model and optimization procedure are put forward. The traditional triple-level nested flowchart of RBMDO is decoupled with the sequential optimization and reliability assessment (SORA). The deterministic multidisciplinary design optimization and the multidisciplinary reliability analysis are executed by CSSO and PMA respectively. Finally, the proposed method is verified through the design example of gear transmission.

APA, Harvard, Vancouver, ISO, and other styles

Lam, Xuan-Binh. "Multidiscilinary design optimization for aircraft wing using response surface method, genetic algorithm, and simulated annealing." Journal of Science and Technology in Civil Engineering (STCE) - NUCE 14, no. 1 (2020): 28–41. http://dx.doi.org/10.31814/stce.nuce2020-14(1)-03.

Full text

Abstract:

Multidisciplinary Design Optimization (MDO) has received a considerable attention in aerospace industry. The article develops a novel framework for Multidisciplinary Design Optimization of aircraft wing. Practically, the study implements a high-fidelity fluid/structure analyses and accurate optimization codes to obtain the wing with best performance. The Computational Fluid Dynamics (CFD) grid is automatically generated using Gridgen (Pointwise) and Catia. The fluid flow analysis is carried out with Ansys Fluent. The Computational Structural Mechanics (CSM) mesh is automatically created by Patran Command Language. The structural analysis is done by Nastran. Aerodynamic pressure is transferred to finite element analysis model using Volume Spline Interpolation. In terms of optimization algorithms, Response Surface Method, Genetic Algorithm, and Simulated Annealing are utilized to get global optimum. The optimization objective functions are minimizing weight and maximizing lift/drag. The design variables are aspect ratio, tapper ratio, sweepback angle. The optimization results demonstrate successful and desiable construction of MDO framework. Keywords: Multidisciplinary Design Optimization; fluid/structure analyses; global optimum; Genetic Algorithm; Response Surface Method.

APA, Harvard, Vancouver, ISO, and other styles

Siddappaji, Kiran, and Mark G. Turner. "An Advanced Multifidelity Multidisciplinary Design Analysis Optimization Toolkit for General Turbomachinery." Processes 10, no. 9 (2022): 1845. http://dx.doi.org/10.3390/pr10091845.

Full text

Abstract:

The MDAO framework has become an essential part of almost all fields, apart from mechanical, transportation, and aerospace industries, for efficient energy conversion or otherwise. It enables rapid iterative interaction among several engineering disciplines at various fidelities using automation tools for design improvement. An advanced framework from low to high fidelity is developed for ducted and unducted turbomachinery blade designs. The parametric blade geometry tool is a key feature which converts low-fidelity results into 3D blade shapes and can readily be used in high-fidelity multidisciplinary simulations as part of an optimization cycle. The geometry generator and physics solvers are connected to DAKOTA, an open-source optimizer with parallel computation capability. The entire cycle is automated and new design iterations are generated with input parameter variations controlled by DAKOTA. Single- and multi-objective genetic algorithm and gradient method-based optimization cases are demonstrated for various applications. B-splines are used to define smooth perturbation of parametric variables chordwise and spanwise of the blade. The ability to create parametric 3D blade shapes quickly from low-fidelity analyses with advanced control is demonstrated to be unique and enables a rapid 3D design cycle. Non-intuitive designs are feasible in this framework and designers can really benefit from parametric geometry manipulation. Optimization at each fidelity is realized through automation. As part of the multidisciplinary analysis, 3D structural analysis is also performed using the unidirectional fluid–structure interaction for a few cases with imported pressure loads from the 3D RANS solution. Examples of axial turbofans, compressor rotors, turbines, radial compressors, propellers, wind and hydrokinetic turbines are demonstrated to prove generality.

APA, Harvard, Vancouver, ISO, and other styles

Meng, Debiao, Miao Liu, Shunqi Yang, Hua Zhang, and Ran Ding. "A fluid–structure analysis approach and its application in the uncertainty-based multidisciplinary design and optimization for blades." Advances in Mechanical Engineering 10, no. 6 (2018): 168781401878341. http://dx.doi.org/10.1177/1687814018783410.

Full text

Abstract:

In practical engineering, the choice of blade shape is crucial in the design process of turbine. It is because not only the structural stability but also the aerodynamic performance of turbine depends on the shape of blades. Generally, the design of blades is a typical multidisciplinary design optimization problem which includes many different disciplines. In this study, a fluid–structure coupling analysis approach is proposed to show the application of multidisciplinary design optimization in engineering. Furthermore, a strategy of uncertainty-based multidisciplinary design optimization using fluid–structure coupling analysis is proposed to enhance the reliability and safety of blades in turbine. The design of experiment technique is also introduced to construct response surface during uncertainty-based multidisciplinary design optimization using fluid–structure coupling analysis. The design solution shows that the adiabatic efficiency is increased and the equivalent stress is decreased, which means that better performance of the turbine can be obtained.

APA, Harvard, Vancouver, ISO, and other styles

Jafarsalehi, A., HR Fazeley, and M. Mirshams. "Spacecraft mission design optimization under uncertainty." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 230, no. 16 (2016): 2872–87. http://dx.doi.org/10.1177/0954406215603416.

Full text

Abstract:

The design of space systems is a complex and multidisciplinary process. In this study, two deterministic and nondeterministic approaches are applied to the system design optimization of a spacecraft which is actually a small satellite in low Earth orbit with remote sensing mission. These approaches were then evaluated and compared. Different disciplines such as mission analysis, payload, electrical power supply, mass model, and launch manifest were properly combined for further use. Furthermore, genetic algorithm and sequential quadratic programming were employed as the system-level and local-level optimizers. The main optimization objective of this study is to minimize the resolution of the satellite imaging payload while there are several constraints. A probabilistic analysis was performed to compare the results of the deterministic and nondeterministic approaches. Analysis of the results showed that the deterministic approaches may lead to an unreliable design (because of leaving little or no room for uncertainties), while using the reliability-based multidisciplinary design optimization architecture, all probabilistic constraints were satisfied.

APA, Harvard, Vancouver, ISO, and other styles

Choi, Jung-Sun, and Gyung-Jin Park. "Multidisciplinary design optimization of the flapping wing system for forward flight." International Journal of Micro Air Vehicles 9, no. 2 (2017): 93–110. http://dx.doi.org/10.1177/1756829317691990.

Full text

Abstract:

The success of a flapping wing air vehicle flight is strongly related to the flapping motion and wing structure. Various disciplines should be considered for analysis and design of the flapping wing system. A design process for a flapping wing system is defined by using multidisciplinary design optimization. Unsteady aeroelastic analysis is employed as the system analysis. From the results of the aeroelastic analysis, the deformation of the wing is transmitted to the fluid discipline and the dynamic pressure is conveyed to the structural discipline. In the fluid discipline, a kinematic optimization problem is solved to maximize the time-averaged thrust coefficient and the propulsive efficiency simultaneously. In the structural discipline, nonlinear dynamic topology optimization is performed to find the distribution of reinforcement by using the equivalent static loads method for nonlinear static response structural optimization. The defined design process is applied to a flapping wing air vehicle model and the flapping wing air vehicle model is fabricated based on the optimization results.

APA, Harvard, Vancouver, ISO, and other styles

Zhang, Zhuo, Fei Yu, Bo Xu, Shipeng Du, and Qiuying Wang. "The Analysis and Optimization Design of Thermal-Electrical Coupling System with Consideration of Numerical Noises." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 6906–15. http://dx.doi.org/10.1166/jctn.2016.5646.

Full text

Abstract:

The optimization function for designing is usually not smooth or discontinuous due to numerical noises, which makes the multidisciplinary decoupling and optimization design more difficult. An global multidisciplinary optimization approach with consideration of numerical noises is proposed in this paper. First, the decoupling problem is transferred into optimization in line with the idea of Simultaneous Analysis and Design (SAND). Kriging models are introduced as surrogate models in order to filter the numerical noises, then the location of new samples is determined with the method of Maximum Likelihood Estimation (MLE), in order to reduce repetitive times of decoupling analysis. Second, the multidisciplinary optimization model of coupling systems is set up using the penalty function method. Finally, the proposed model and method is verified through a typical thermalelectrical coupling example.

APA, Harvard, Vancouver, ISO, and other styles

Talya, Shashishekara S., J. N. Rajadas, and A. Chattopadhyay. "Multidisciplinary design optimization of film-cooled gas turbine blades." Mathematical Problems in Engineering 5, no. 2 (1999): 97–119. http://dx.doi.org/10.1155/s1024123x99001015.

Full text

Abstract:

Design optimization of a gas turbine blade geometry for effective film cooling toreduce the blade temperature has been done using a multiobjective optimization formulation. Three optimization formulations have been used. In the first, the average blade temperature is chosen as the objective function to be minimized. An upper bound constraint has been imposed on the maximum blade temperature. In the second, the maximum blade temperature is chosen as the objective function to be minimized with an upper bound constraint on the average blade temperature. In the third formulation, the blade average and maximum temperatures are chosen as objective functions. Shape optimization is performed using geometric parameters associated with film cooling and blade external shape. A quasi-three-dimensional Navier–Stokes solver for turbomachinery flows is used to solve for the flow field external to the blade with appropriate modifications to incorporate the effect of film cooling. The heat transfer analysis for temperature distribution within the blade is performed by solving the heat diffusion equation using the finite element method. The multiobjective Kreisselmeier–Steinhauser function approach has been used in conjunction with an approximate analysis technique for optimization. The results obtained using both formulations are compared with reference geometry. All three formulations yield significant reductions in blade temperature with the multiobjective formulation yielding largest reduction in blade temperature.

APA, Harvard, Vancouver, ISO, and other styles

Armellin, Roberto, and Michèle Lavagna. "Multidisciplinary Optimization of Aerocapture Maneuvers." Journal of Artificial Evolution and Applications 2008 (April 7, 2008): 1–13. http://dx.doi.org/10.1155/2008/248798.

Full text

Abstract:

A multidisciplinary-multiobjective optimization of aerocapture maneuvers is presented. The proposed approach allows a detailed analysis of the coupling among vehicle's shape, trajectory control, and thermal protection system design. A set of simplified models are developed to address this analysis and a multiobjective particle swarm optimizer is adopted to obtain the set of Pareto optimal solutions. In order to deal with an unconstrained multiobjective optimization, a two-point boundary value problem is formulated to implicitly satisfy the constraints on the atmospheric exit conditions. The trajectories of the most promising solutions are further optimized in a more refined dynamical system by solving an optimal control problem using a direct multiple shooting transcription method. Furthermore, a more complete vehicle control is considered. All the simulations presented consider an aerocapture at Mars with a polar orbit of 200 km of altitude as target orbit.

APA, Harvard, Vancouver, ISO, and other styles

Besnard, Eric, Adeline Schmitz, Hamid Hefazi, and Rahul Shinde. "Constructive Neural Networks and Their Application to Ship Multidisciplinary Design Optimization." Journal of Ship Research 51, no. 04 (2007): 297–312. http://dx.doi.org/10.5957/jsr.2007.51.4.297.

Full text

Abstract:

This paper presents a neural network-based response surface method for reducing the cost of computer-intensive optimizations for applications in ship design. In the approach, complex or costly analyses are replaced by a neural network, which is used to instantaneously estimate the value of the function(s) of interest. The cost of the optimization is shifted to the generation of (smaller) data sets used for training the network. The focus of the paper is on the use and analysis of constructive networks, as opposed to networks of fixed size, for treating problems with a large number of variables, say around 30. The advantages offered by constructive networks are emphasized, leading to the selection and discussion of the cascade correlation algorithm. This topology allows for efficient neural network determination when dealing with function representation over large design spaces without requiring prior experience from the user. During training, the network grows until the error on a small set (validation set), different from that used in the training itself (training set), starts increasing. The method is validated for a mathematical function for dimensions ranging from 5 to 30, and the importance of analyzing the error on a set other than the training set is emphasized. The approach is then applied to the automated computational fluid dynamics-based shape optimization of a fast ship configuration known as the twin H-body. The classical approach yields a design improvement of 26%, whereas the neural network-based method allows reaching a 34% improvement at one fifth of the cost of the former. Based on the analysis of the results, areas for future improvements and research are outlined. The results demonstrate the potential of the method in saving valuable development cycle time and increasing the performance of future ship designs.

APA, Harvard, Vancouver, ISO, and other styles

Wang, Li, Boris Diskin, Robert T. Biedron, Eric J. Nielsen, and Olivier A. Bauchau. "High-Fidelity Multidisciplinary Sensitivity Analysis and Design Optimization for Rotorcraft Applications." AIAA Journal 57, no. 8 (2019): 3117–31. http://dx.doi.org/10.2514/1.j056587.

Full text

APA, Harvard, Vancouver, ISO, and other styles

York, Martin A., Berk Öztürk, Edward Burnell, and Warren W. Hoburg. "Efficient Aircraft Multidisciplinary Design Optimization and Sensitivity Analysis via Signomial Programming." AIAA Journal 56, no. 11 (2018): 4546–61. http://dx.doi.org/10.2514/1.j057020.

Full text

APA, Harvard, Vancouver, ISO, and other styles

KIM, Sangho, Jungkeun PARK, Jeong-Oog LEE, and Jae-Woo LEE. "A Systematic Approach for Quantitative Analysis of Multidisciplinary Design Optimization Framework." TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES 52, no. 178 (2010): 246–54. http://dx.doi.org/10.2322/tjsass.52.246.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Gray, Justin S., John T. Hwang, Joaquim R. R. A. Martins, Kenneth T. Moore, and Bret A. Naylor. "OpenMDAO: an open-source framework for multidisciplinary design, analysis, and optimization." Structural and Multidisciplinary Optimization 59, no. 4 (2019): 1075–104. http://dx.doi.org/10.1007/s00158-019-02211-z.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Tappeta, R. V., and J. E. Renaud. "Multiobjective Collaborative Optimization." Journal of Mechanical Design 119, no. 3 (1997): 403–11. http://dx.doi.org/10.1115/1.2826362.

Full text

Abstract:

This investigation focuses on the development of modifications to the Collaborative Optimization (CO) approach to multidisciplinary systems design, that will provide solution capabilities for multiobjective problems. The primary goal of this paper is to provide a comprehensive overview and development of mathematically rigorous optimization strategies for Multiobjective Collaborative Optimization (MOCO). Collaborative Optimization strategies provide design optimization capabilities to discipline designers within a multidisciplinary design environment. To date these CO strategies have primarily been applied to system design problems which have a single objective function. Recent investigations involving multidisciplinary design simulators have reported success in applying CO to multiobjective system design problems. In this research three Multiobjective Collaborative Optimization (MOCO) strategies are developed, reviewed and implemented in a comparative study. The goal of this effort is to provide an in depth comparison of different MOCO strategies available to system designers. Each of the three strategies makes use of parameter sensitivities within multilevel solution strategies. In implementation studies, each of the three MOCO strategies is effective in solving a multiobjective multidisciplinary systems design problem. Results indicate that these MOCO strategies require an accurate estimation of parameter sensitivities for successful implementation. In each of the three MOCO strategies these parameter sensitivities are obtained using post-optimality analysis techniques.

APA, Harvard, Vancouver, ISO, and other styles

Yang, Fan, Ming Liu, Lei Li, Hu Ren, and Jianbo Wu. "Evidence-Based Multidisciplinary Design Optimization with the Active Global Kriging Model." Complexity 2019 (November 15, 2019): 1–13. http://dx.doi.org/10.1155/2019/8390865.

Full text

Abstract:

This article presents an approach that combines the active global Kriging method and multidisciplinary strategy to investigate the problem of evidence-based multidisciplinary design optimization. The global Kriging model is constructed by introducing a so-called learning function and using actively selected samples in the entire optimization space. With the Kriging model, the plausibility, Pl, of failure is obtained with evidence theory. The multidisciplinary feasible and collaborative optimization strategies of multidisciplinary design optimization are combined with the evidence-based reliability analysis. Numerical examples are provided to illustrate the efficiency and accuracy of the proposed method. The numerical results show that the proposed algorithm is effective and valuable, which is valuable in engineering application.

APA, Harvard, Vancouver, ISO, and other styles

Zhang, Yi Shang, Bin Zhao, Yong Shou Liu, and Zhu Feng Yue. "Reliability-Based Multidisciplinary Design Optimization for Centrifugal Compressor Using the Fourth Moment Method." Advanced Materials Research 156-157 (October 2010): 575–81. http://dx.doi.org/10.4028/www.scientific.net/amr.156-157.575.

Full text

Abstract:

A reliability-based multidisciplinary design optimization (RBMDO) frame work for Centrifugal compressor was presented. Multidisciplinary feasible method was used to decouple the multidisciplinary analysis and the fourth moment method for reliability analysis was recommended systematically. Based on the approximation, the RBMDO framework was finished. The case study shows that optimization efforts could improve obviously the performance of centrifugal compressor under the requirements of reliability. This framework could make the design reach the best performance with a good reliability. It indicates that the proposed optimization method is available and feasible for the engineering application.

APA, Harvard, Vancouver, ISO, and other styles

Yu, Rong Gang, Jun Zhang, and Bing Zhang. "A PMA-Based Collaborative Strategy for Reliability Design and Optimization of Multidisciplinary Systems." Advanced Materials Research 418-420 (December 2011): 411–14. http://dx.doi.org/10.4028/www.scientific.net/amr.418-420.411.

Full text

Abstract:

To tackle the computing efficiency and robustness problems caused by the reliability index approach (RIA) in reliability-based multidisciplinary design optimization (RBMDO), a new performance measure approach-based method for RBMDO is proposed. Meanwhile, the traditional triple-level nested flowchart of RBMDO is decoupled through the main idea of sequential optimization and reliability assessment (SORA). Both deterministic multidisciplinary design optimization and the multidisciplinary reliability analysis are executed by collaborative optimization (CO). Finally, the proposed method is verified through the design example of gear transmission.

APA, Harvard, Vancouver, ISO, and other styles

Lu, Yun Tong, Chun Jie Wang, Ang Li, and Han Wang. "Multidisciplinary Design Optimization of a Lunar Lander’s Soft-Landing Gear." Applied Mechanics and Materials 42 (November 2010): 118–21. http://dx.doi.org/10.4028/www.scientific.net/amm.42.118.

Full text

Abstract:

The rapid development of Multidisciplinary Design Optimization (MDO) approach can simultaneously guarantee the cut of cost on design and optimal performance of spacecraft. Based on the theory of Collaborative Optimization approach (CO) of MDO, present paper proposes the method of CO by integrating Pro/E(3D modeling), Patran/Nastran(FEM analysis) and ADAMS(multi-body dynamic analysis) with the Isight software. In the analysis of the soft-landing gear of Lunar Lander, this method can optimize the mass of the landing gear and meanwhile ensures the reliability of structure statics, structure dynamics and multi-body dynamics. Thus the feasibility, applied value and guideline significance of this method in spacecraft structural design are proven.

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!