Relevant bibliographies by topics / Multidisciplinary Design Optimisation

Academic literature on the topic 'Multidisciplinary Design Optimisation'

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Published: 14 March 2023

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Journal articles on the topic "Multidisciplinary Design Optimisation"

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Tovar, Andres, Nelson Arzola de la Peña, and Alexander Gómez Cassab. "Multidisciplinary design optimisation techniques." Ingeniería e Investigación 27, no. 1 (January 1, 2007): 84–92. http://dx.doi.org/10.15446/ing.investig.v27n1.14785.

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Design optimisation of a multidisciplinary project in engineering involves the decomposition of a system into disciplines and the subsequent association of their contributions. This work was aimed at presenting the most common decomposition and association techniques currently used in multidisciplinary design optimisation (MDO). Amongst the decomposition techniques this work includes hierarchical and non-hierarchical approaches as well as the most popular numerical procedures. The association techniques include: one-level methods (e.g. all-at-once optimisation and simultaneous analysis and design), multilevel methods (e.g. concurrent subspace optimisation and collaborative optimisation) and robust design. This work also incorporates an illustrative numerical example.
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Lee, Dong Seop, J. Periaux, L. F. Gonzalez, K. Srinivas, and E. Onate. "Robust multidisciplinary UAS design optimisation." Structural and Multidisciplinary Optimization 45, no. 3 (September 9, 2011): 433–50. http://dx.doi.org/10.1007/s00158-011-0705-0.

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Lee, Kyu-Yeul, Myung-Il Roh, and Seonho Cho. "Multidisciplinary design optimisation of mechanical systems using collaborative optimisation approach." International Journal of Vehicle Design 25, no. 4 (2001): 353. http://dx.doi.org/10.1504/ijvd.2001.005207.

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Mariens, J., A. Elham, and M. J. L. van Tooren. "Influence of weight modelling on the outcome of wing design using multidisciplinary design optimisation techniques." Aeronautical Journal 117, no. 1195 (September 2013): 871–95. http://dx.doi.org/10.1017/s0001924000008563.

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Abstract Weight estimation methods are categorised in different classes based on their level of fidelity. The lower class methods are based on statistical data, while higher class methods use physics based calculations. Statistical weight estimation methods are usually utilised in early design stages when the knowledge of designers about the new aircraft is limited. Higher class methods are applied in later design steps when the design is mature enough. Lower class methods are sometimes preferred in later design stages, even though the designers have enough knowledge about the design to use higher class methods. In high level multidisciplinary design optimisation (MDO) fidelity is often sacrificed to obtain models with shorter computation times. There is always a compromise required to select the proper weight estimation method for an MDO project. An investigation has been performed to study the effect of using different weight estimation methods, with low and medium levels of fidelity, on the results of a wing design using multidisciplinary design optimisation techniques. An MDO problem was formulated to design the wing planform of a typical turboprop and a turbofan passenger aircraft. The aircraft maximum take-off weight was selected as the objective function. A quasi-three-dimensional aerodynamic solver was developed to calculate the wing aerodynamic characteristics. Five various statistical methods and a quasi-analytical method are used to estimate the wing structural weight. These methods are compared to each other by analysing their accuracy and sensitivity to different design variables. The results of the optimisations showed that the optimum wing shape is affected by the method used to estimate the wing weight. Using different weight estimation methods also strongly affects the optimisation convergence history and computational time.
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Bäckryd, R. D., A. B. Ryberg, and L. Nilsson. "Multidisciplinary design optimisation methods for automotive structures." INTERNATIONAL JOURNAL OF AUTOMOTIVE AND MECHANICAL ENGINEERING 14, no. 1 (March 30, 2017): 4050–67. http://dx.doi.org/10.15282/ijame.14.1.2017.17.0327.

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Giassi, A., F. Bennis, and J. J. Maisonneuve. "Multidisciplinary design optimisation and robust design approaches applied to concurrent design." Structural and Multidisciplinary Optimization 28, no. 5 (August 4, 2004): 356–71. http://dx.doi.org/10.1007/s00158-004-0417-9.

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Van Nguyen, N., J. W. Lee, Y. D. Lee, and H. U. Park. "A multidisciplinary robust optimisation framework for UAV conceptual design." Aeronautical Journal 118, no. 1200 (February 2014): 123–42. http://dx.doi.org/10.1017/s0001924000009027.

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Abstract This paper describes a multidisciplinary robust optimisation framework for UAV conceptual design. An in-house configuration designer system is implemented to generate the full sets of configuration data for a well-developed advanced UAV analysis tool. A fully integrated configuration designer along with the UAV analysis tool ensures that full sets of configuration data are provided simultaneously while the UAV configuration changes during optimisation. The computational strategy for probabilistic analysis is proposed by implementing a central difference method and fitting distribution for a reduced number of Monte Carlo Simulation sampling points. The minimisation of a new robust design objective function helps to enhance the reliability while other UAV performance criteria are satisfied. In addition, the fully integrated process and a probabilistic analysis strategy method demonstrate a reduction in the probability of failure under noise factors without any noticeable increase in design turnaround time. The proposed robust optimisation framework for UAV conceptual design case study yields a more trustworthy prediction of the optimal configuration and is preferable to the traditional deterministic design approach. The high fidelity analysis ANSYS Fluent 13 is performed to demonstrate the accuracy of proposed framework on baseline, deterministic and RDO configuration.
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He, Jim, Shari Hannapel, David Singer, and Nickolas Vlahopoulos. "Multidisciplinary Design Optimisation of a Ship Hull Using Metamodels." Ship Technology Research 58, no. 3 (September 2011): 156–66. http://dx.doi.org/10.1179/str.2011.58.3.004.

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Campana, Emilio Fortunato, Giovanni Fasano, and Daniele Peri. "Penalty function approaches for ship multidisciplinary design optimisation (MDO)." European J. of Industrial Engineering 6, no. 6 (2012): 765. http://dx.doi.org/10.1504/ejie.2012.051076.

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Harris, J. C., and S. V. Fenwick. "The application of Pareto methods to multidisciplinary design optimisation." Aeronautical Journal 105, no. 1048 (June 2001): 329–34. http://dx.doi.org/10.1017/s0001924000012215.

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Abstract Multidisciplinary design optimisation (MDO) provides a framework for the timely exchange of data necessary to support the highly integrated tasks typical of aerospace design. This will help reduce the duration of the design cycle and improve efficiency of the final product. Well implemented MDO capabilities will play an increasingly important role in DERA's activities to support the definition of future system requirements and the assessment of new equipment. The framework in which an MDO approach is realised must be flexible and accommodate the diverse range of individual discipline-based tools that contribute to the overall process. This paper describes DERA's activity within the EC Framework IV ‘FRONTIER’ project to investigate the use of modern graphical user interface (GUI) methods and genetic algorithms (GAs) for the combined aerodynamic and structural design of a modern combat aircraft. The application of the techniques to identify a Pareto frontier in high level design objective space that represents the boundary beyond which improvements cannot be made without sacrificing one or other aspect of overall aircraft performance is described. The scope of the methods as an aid during the definition of system requirements and for the evaluation of trade-offs during the concept assessment stage of a project is discussed.
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Dissertations / Theses on the topic "Multidisciplinary Design Optimisation"

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Yin, Xuefei. "Application of multidisciplinary design optimisation to engine calibration optimisation." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5630.

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Automotive engines are becoming increasingly technically complex and associated legal emissions standards more restrictive, making the task of identifying optimum actuator settings to use significantly more difficult. Given these challenges, this research aims to develop a process for engine calibration optimisation by exploiting advanced mathematical methods. Validation of this work is based upon a case study describing a steady-state Diesel engine calibration problem. The calibration optimisation problem seeks an optimal combination of actuator settings that minimises fuel consumption, while simultaneously meeting or exceeding the legal emissions constraints over a specified drive cycle. As another engineering target, the engine control maps are required as smooth as possible. The Multidisciplinary Design Optimisation (MDO) Frameworks have been studied to develop the optimisation process for the steady state Diesel engine calibration optimisation problem. Two MDO strategies are proposed for formulating and addressing this optimisation problem, which are All At Once (AAO), Collaborative Optimisation. An innovative MDO formulation has been developed based on the Collaborative Optimisation application for Diesel engine calibration. Form the MDO implementations, the fuel consumption have been significantly improved, while keep the emission at same level compare with the bench mark solution provided by sponsoring company. More importantly, this research has shown the ability of MDO methodologies that manage and organize the Diesel engine calibration optimisation problem more effectively.
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Smith, David D. "Multidisciplinary design optimisation of morphing nonplanar wing systems." Thesis, University of Bristol, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.681343.

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Studies are undertaken using Multidisciplinary Design Optimisation (MDO) on the incorporation of an outboard morphing wing system, with two partitions that are variable in twist and dihedral angle, onto an existing conventionally designed commercial passenger jet. For this intent, an optimisation suite is created, incorporating a high end, low fidelity aero-structural control analysis together with a full engine model and integrated operational performance algorithm. Initial studies, focusing on the single objective of specific air range improvement for a number of flight phases, reveal increases of approximately 6.5-7.5% over the base line aircraft with wing fences across each case. Studies analyse the effects of the wing system on additional operational performance metrics, such as take-off, initial climb, approach-climb and landing performance parameters, in order to ascertain a truly holistic representation of the benefits of morphing wings. Further effort is expended to couple the effects of each phase within a multiobjective framework. Refined studies are performed, incorporating multiobjective optimisation methods and a critical phase, aero-structural wing sizing tool into the MDO suite. Results maintain strong improvements in cruise performance throughout the entire flight envelope and across multiple stage lengths. High fidelity computational and experimental analysis is performed upon a similarly modelled conventional aircraft wing. Results are generated with the intention of drawing meaningful comparisons with trends in aerodynamic and structural efficiency observed in the multidisciplinmy optimisation studies. Computational results are obtained with the DLR-Tau computational fluid dynamics code and experimental testing is performed in the University of Bristol 7' x 5' low speed wind tulmel. Outer twist variation of ±3 ° and dihedral angles from planar up to 90° are tested for a range of incidence angles. Results demonstrate varying levels of agreement between each form of analysis method and offer insight into the aerodynamic and structural trade-off required to select an optimal configuration. The work in this thesis numerically and experimentally outlines and provides justification for the feasible performance gains through the utilisation of morphing wing technology.
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Dababneh, Odeh. "Multidisciplinary design optimisation for aircraft wing mass estimation." Thesis, Cranfield University, 2016. http://dspace.lib.cranfield.ac.uk/handle/1826/10172.

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The implementation of key technologies in the initial stages of the aircraft wing design process has always represented a substantial challenge for aircraft designers. The lack of reliable and accessible wing mass prediction methods ¬which allow assessment of the relative benefits of new technologies for reducing structural wing weight - is of significant importance. This necessitates the development of new and generally applicable wing mass estimation methods. This thesis aims to create a new framework for estimating the mass of metallic and composite transport aircraft wings via finite element multidisciplinary analysis, and design optimisation techniques. To this end, the multidisciplinary static strength and stiffness, dynamic aeroelastic stability, and manufacturing constraints are simultaneously addressed within an optimisation environment through a gradient-based search algorithm. A practical optimisation procedure is presented as part of the sizing optimisation process, with enhanced features in solving large-scale nonlinear structural optimisation problems, incorporating an effective initial design variable value generation scheme based on the concept of the fully stressed design. The applicability and accuracy of the proposed approaches is accomplished by conducting a number of case studies in which the wingbox structure of the public domain NASA wing - commonly referred to as the Common Research Model (CRM) - is optimised to produce a minimum mass design. The results of a case study examining minimisation of the mass of the CRM wingbox structures designed using four different models of increasing structural fidelity prove that the multidisciplinary design optimisation framework can successfully calculate the mass of realistic real-world aircraft wing designs. This provides an insight into the competence of certain wingbox models in predicting the mass of the metallic and composite primary wing structures to an acceptable level of accuracy, and in demonstrating the relative merits of the wingbox structural complexity models under consideration and the computational resources necessary to achieving the required degree of accuracy ... [cont.].
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Pant, Sanjay. "Multidisciplinary and multiobjective design optimisation of coronary stents." Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/349008/.

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Coronary stents are tubular type scaffolds that are deployed, using an inflatable balloon on a catheter, most commonly to recover the lumen size of narrowed (diseased) arterial segments. Even though numerous stent designs, of varying geometrical and material complexity, are used in clinical practice today, the adverse biological responses post-stenting are not completely eliminated. In-stent restenosis (IR), reduction in lumen size due to neointima formation within 12 months of procedure, and stent thrombosis (ST), formation of a blood clot inside a stented vessel, are the two most common adverse responses to stents. Such adverse responses are multifactorial and their causes are not completely understood. However, the geometric design of a stent, which is a common differentiating factor between the numerous commercially available stents, is known to be a key factor influencing adverse responses. In light of the above, this thesis exploits stent geometry parameterisation in both constrained and multiobjective optimisation. Gaussian process surrogate modelling is used to cost effectively (a) understand the influence of stent geometry parameters on metrics indicating adverse response, and (b) obtain families of stent designs which are potentially more resistant to such responses. Various computational models are developed to evaluate the efficacy of a stent in terms of the factors influencing the adverse responses. In particular, two finite element analysis (FEA) models and two computational fluid dynamics (CFD) models are developed. The FEA models are used to simulate the balloon-expansion of stents in a representative coronary artery and bending of stents on application of bending moments. On the other hand, the CFD models simulate haemodynamic flow in the stented artery and the associated drug-release into the tissue. The expansion FEA models are validated against manufacturer provided pressure-diameter relationship and the flexibility FEA models are validated against the numerical studies found in literature. The numerical models are then used to extract metrics which are related to the adverse responses. Six metrics are formulated: (i) acute recoil, which measures the radial strength of the stent; (ii) volume average stress, which measures potential arterial injury caused by the stenting procedure; (iii) haemodynamic low and reverse index, which measures the haemodynamic alteration relevant to IR; (iv) volume average drug, which measures the amount of anti-proliferative drug delivered into the tissue; (v) drug deviation, which measures the uniformity of drug-distribution in the tissue; and (vi) flexibility metric, which measures the deliverability of the stent. These metrics are then used to compare the performance of different geometric stent designs. Two parameterisation techniques – one for a generic ring and link topology of stents, and one for the commercial CYPHER (Cordis corporation, Johnson & Johnson company) – are proposed to study the effect of geometrical variation in stent design on the formulated metrics of efficacy. These techniques are then combined with surrogate modelling to perform stent design optimisation studies and study the effect of stent geometry on the evaluation metrics. Finally, three paradigms to choose optimal stent designs from a set of non-dominated solutions, in terms of the evaluation metrics, are proposed, and optimal designs under such paradigms are identified. The last part of this thesis concerns surrogate assisted optimisation, and is not specific to the problem of stent design. Here, the use of analytically available gradient information in widely used Kriging predictors is explored. A search algorithm to locate all stationary points of a Krig, using a combination of an iterative sequence of the Krig derivative and a low-discrepancy sequence is proposed.
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Kianifar, Mohammed R. "Application of multidisciplinary design optimisation frameworks for engine mapping and calibration." Thesis, University of Bradford, 2014. http://hdl.handle.net/10454/14843.

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With ever-increasing numbers of engine actuators to calibrate within increasingly stringent emissions legislation, the engine mapping and calibration task of identifying optimal actuator settings is much more difficult. The aim of this research is to evaluate the feasibility and effectiveness of the Multidisciplinary Design Optimisation (MDO) frameworks to optimise the multi-attribute steady state engine calibration optimisation problems. Accordingly, this research is concentrated on two aspects of the steady state engine calibration optimisation: 1) development of a sequential Design of Experiment (DoE) strategy to enhance the steady state engine mapping process, and 2) application of different MDO architectures to optimally calibrate the complex engine applications. The validation of this research is based on two case studies, the mapping and calibration optimisation of a JLR AJ133 Jaguar GDI engine; and calibration optimisation of an EU6 Jaguar passenger car diesel engine. These case studies illustrated that: -The proposed sequential DoE strategy offers a coherent framework for the engine mapping process including Screening, Model Building, and Model Validation sequences. Applying the DoE strategy for the GDI engine case study, the number of required engine test points was reduced by 30 – 50 %. - The MDO optimisation frameworks offer an effective approach for the steady state engine calibration, delivering a considerable fuel economy benefits. For instance, the MDO/ATC calibration solution reduced the fuel consumption over NEDC drive cycle for the GDI engine case study (i.e. with single injection strategy) by 7.11%, and for the diesel engine case study by 2.5%, compared to the benchmark solutions.
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Kingsley, Thomas Charles. "Multidisciplinary design and optimisation of liquid containers for sloshing and impact." Diss., Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-01242006-100142.

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Ollar, Jonathan. "A multidisciplinary design optimisation framework for structural problems with disparate variable dependence." Thesis, Queen Mary, University of London, 2017. http://qmro.qmul.ac.uk/xmlui/handle/123456789/24715.

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Multidisciplinary design optimisation incorporates several disciplines in one integrated optimisation problem. The benefi t of considering all requirements at once rather than in individual optimisations is that synergies between disciplines can be exploited to fi nd superior designs to what would otherwise be possible. The main obstacle for the use of multidisciplinary design optimisation in an industrial setting is the related computational cost which may become prohibitively large. This work is focused on the development of a multidisciplinary design optimisation framework that extends the existing trust-region based optimisation method known as the mid-range approximation method. The main novel contribution is an approach to solving multidisciplinary design optimisation problems using metamodels built in sub-spaces of the design variable space. Each metamodel is built in the sub-space relevant to the corresponding discipline while the optimisation problem is solved in the full design variable space. Since the metamodels are built in a space of reduced dimensionality, the computational budget for building them can be reduced without compromising their quality. Furthermore, a method for efficiently building kriging metamodels is proposed. This is done by means of a two-step hyper parameter tuning strategy. The fi rst step is a line search where the set of tuning parameters is treated as a single variable. The solution of the fi rst step is used in the second step, a gradient based hyper parameter optimisation where partial derivatives are obtained using the adjoint method. The framework is demonstrated on two examples, a multidisciplinary design optimisation of a thin-walled beam section subject to static and impact requirements, and a multidisciplinary design optimisation of an aircraft wing subject to static and bird strike requirements. In both cases the developed technique demonstrates a reduced computational effort compared to what would typically be achieved by existing methods.
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Whellens, Matthew W. "Multidisciplinary optimisation of aero-engines using genetic algorithms and preliminary design tools." Thesis, Cranfield University, 2003. http://dspace.lib.cranfield.ac.uk/handle/1826/10510.

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This study investigates a novel methodology for the preliminary design of aeroengines. This involves the modelling of the disciplines that affect the engine's requirements and constraints, their implementation in software format and their coupling into a single unit. Subsequently, this unit is interfaced with an optimiser software. The resulting multidisciplinary optimisation (MDO) tool allows the automation of the traditional, human-based preliminary design process. The investigation of the above-mentioned novel methodology is carried out through the development of a "pilot" MDO tool and its subsequent utilisation in three case studies, characterised by different optimisation scenarios. The selection of each case study is motivated by current research questions, such as aviation's contribution to climate change or the attractiveness of specific novel propulsion concepts. The outcome of the pilot MDO study is considered successful and has been well received by several academic and industrial aero-engine organisations. The choice of the disciplines and of their modelling fidelity allowed a realistic representation of the main disciplinary interactions and tradeoffs that characterise the important phase of preliminary design. The computational effort involved in the solution of the optimisation studies was found to be acceptable, and no major reprogramming was required when different optimisation scenarios were considered. The case studies were investigated with an ease and comprehensiveness that would not have been achievable through a human-based parametric analysis. The positive experience with the pilot MDO tool suggests that an automated methodology for the preliminary design of aero-engines is feasible, applicable and valuable. Its adoption can provide substantial advantages over the traditional human-based approach, such as a reduction in human effort, costs and risk. From this perspective, the pilot study constitutes a first step towards the development of a full-scale MDO tooL usable by aero-engine manufacturers. In the near future, issues like climate change could drive significant modifications in airframe and engine design. A preliminary design MDO tool is therefore timely, and has the potential of making a significant contribution.
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Thauvin, Jérôme. "Exploring the design space for a hybrid-electric regional aircraft with multidisciplinary design optimisation methods." Phd thesis, Toulouse, INPT, 2018. http://oatao.univ-toulouse.fr/23607/1/Thauvin_jerome.pdf.

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Envisioned in the next 15 to 30 years in the aviation industry, hybrid-electric propulsion offers theopportunity to integrate new technology bricks providing additional degrees of freedom to improveoverall aircraft performance, limit the use of non-renewable fossil resources and reduce the aircraftenvironmental footprint. Today, hybrid-electric technology has mainly been applied to groundbased transports, cars, buses and trains, but also ships. The feasibility in the air industry has to beestablished and the improvement in aircraft performance has still to be demonstrated. This thesisaims to evaluate the energy savings enabled by electric power in the case of a 70-seat regionalaircraft. First, energy saving opportunities are identified from the analysis of the propulsion andaerodynamic efficiencies of a conventional twin turboprop aircraft. The potential benefits comingfrom the variation of the size of prime movers and the new power managements with the use ofbatteries are studied. Also, possible aerodynamic improvements enabled by new propellerintegrations are considered. For each topic, simplified analyses provide estimated potential ofenergy saving. These results are then used to select four electrified propulsion systems that arestudied in more detail in the thesis: a parallel-hybrid, a turboelectric with distributed propulsion, apartial-turboelectric with high-lift propellers and an all-electric. Evaluating the selected hybrid-electric aircraft is even more challenging that the sizing of the different components, the energymanagement strategies and the mission profiles one can imagine are many and varied. Inaddition, the overall aircraft design process and the evaluation tools need to be adaptedaccordingly. The Airbus in-house Multidisciplinary Design Optimisation platform named XMDO,which includes most of the required modifications, is eventually selected and further developedduring the thesis. For examples, new parametric component models (blown wing, electrical motor,gas turbine, propeller, etc…) are created, a generic formulation for solving the propulsion systemequilibrium is implemented, and simulation models for take-off and landing are improved. In orderto evaluate the energy efficiency of the hybrid-electric aircraft, a reference aircraft equipped with aconventional propulsion system is first optimised with XMDO. Different optimisation algorithms aretested, and the consistency of the new design method is checked. Then, all the hybrid-electricconfigurations are optimised under the same aircraft design requirements as the reference. Forthe electrical components, two levels of technology are defined regarding the service entry date ofthe aircraft. The optimisation results for the turboelectric and the partial-turboelectric are used tobetter understand the potential aerodynamic improvements identified in the first part of the thesis.Optimisations for the parallel-hybrid, including different battery recharge scenarios, highlight thebest energy management strategies when batteries are used as secondary energy sources. All theresults are finally compared to the reference in terms of fuel and energy efficiencies, for the twoelectrical technology levels. The last part of the thesis focuses on the all-electric aircraft, and aimsat identifying the minimum specific energy required for batteries as a function of the aircraft designrange. A trade study is also carried-out in accordance with the service entry date for the otherelectrical components
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Lapuh, Rok. "Mesh Morphing Technique used with Open-Source CFD Toolbox in Multidisciplinary Design Optimisation." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-348873.

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Nowadays, the product design process relies on computer simulations more than ever. Compared to the experimental tests, they allow substantially more designs to be evaluated. Moreover, computer simulations allow a search for the optimum. That is why a fast and efficient transition from one design iteration to the next is necessary.  For design evaluation in the aerospace industry, Computational Fluid Dynamics tools are used, where finite volume meshes are computationally expensive to create. Instead of recreating them for each product design during an optimisation process, it is much faster to morphone design into the next one. Here an algorithm for mesh morphing based on radial basis functions is presented. Its implementation is evaluated for mesh quality and performance. Mesh morphing of NURBS surfaces, a continuous representation of a given model geometry, together with discrete meshes is proposed next. Lastly, the implementation of the morphing algorithm is linked with a fluid flow solverand an optimisation suite. All three programs are used together to optimise a product coming from the aerospace industry.
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Books on the topic "Multidisciplinary Design Optimisation"

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Advances in collaborative civil aeronautical multidisciplinary design optimization. Reston, Va: American Institute of Aeronautics and Astronautics, 2010.

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Yu-Wang, Chen, Chen Min-Rong, Chen Peng (Optimizaton specialist), and Zeng Guo-Qiang, eds. Extremal optimization: Fundamentals, algorithms, and applications. Boca Raton: Taylor & Francis, CRC Press, 2015.

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1950-, Adeli Hojjat, ed. Advances in design optimizaton [sic]. London: Chapman & Hall, 1994.

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Computerized management of multiple small projects. New York: M. Dekker, 1992.

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Multidisciplinary Design & Optimisation. The Royal Aeronautical Society, 1998.

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Chen, Peng, Yongzai Lü, Yu-Wang Chen, Min-Rong Chen, and Guo-Qiang Zeng. Extremal Optimization. Taylor & Francis Group, 2020.

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Pack, Lonnie. Australian Guidebook for Structural Engineers. Taylor & Francis Group, 2017.

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Australian Guidebook for Structural Engineers. Taylor & Francis Group, 2017.

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Pack, Lonnie. Australian Guidebook for Structural Engineers. Taylor & Francis Group, 2017.

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Pack, Lonnie. Australian Guidebook for Structural Engineers. Taylor & Francis Group, 2017.

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Book chapters on the topic "Multidisciplinary Design Optimisation"

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Periaux, Jacques, Felipe Gonzalez, and Dong Seop Chris Lee. "Multidisciplinary Design Optimisation and Robust Design in Aerospace Systems." In Intelligent Systems, Control and Automation: Science and Engineering, 53–68. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9520-3_5.

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Vassiliadis, Panos, and Spiros Skiadopoulos. "Modelling and Optimisation Issues for Multidimensional Databases." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 482–97. Cham: Springer International Publishing, 2000. http://dx.doi.org/10.1007/3-540-45140-4_32.

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Barth, T., G. Schneider, M. Stettner, M. Grauer, H. Hoernlein, and E. Kereku. "Multidisciplinary Design Optimisation of an Aircraft Wing by Applying a Hybrid Optimisation Strategy." In Optimization in Industry, 289–301. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0675-3_24.

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Barnewitz, Holger. "Flexible Wing Optimisation Based on Shapes and Structures." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 287–305. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04093-1_20.

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Dupont, Cédric, Andrea Tromba, and Sophie Missonnier. "Multidisciplinary System Optimisation on the Design of Cost Effective Space Launch Vehicle." In Advances in Structural and Multidisciplinary Optimization, 3–16. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67988-4_1.

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Amigo, R. C. R., R. W. Hewson, and E. C. N. Silva. "Design of Adsorbed Natural Gas Tanks with Metal Inclusions by Topology Optimisation." In Advances in Structural and Multidisciplinary Optimization, 1757–64. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67988-4_132.

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Lee, D. S., L. F. Gonzalez, J. Périaux, and K. Srinivas. "Evolutionary Optimisation Methods with Uncertainty for Modern Multidisciplinary Design in Aeronautical Engineering." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 271–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-70805-6_21.

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Elsayed, Khairy, and Chris Lacor. "Analysis and Optimisation of Cyclone Separators Geometry Using RANS and LES Methodologies." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 65–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43489-5_8.

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González, L. F., E. J. Whitney, K. Srinivas, K. C. Wong, and J. Périaux. "Multidisciplinary Aircraft Conceptual Design Optimisation Using a Hierarchical Asynchronous Parallel Evolutionary Algorithm (HAPEA)." In Adaptive Computing in Design and Manufacture VI, 273–84. London: Springer London, 2004. http://dx.doi.org/10.1007/978-0-85729-338-1_23.

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Dunn, S. A. "Genetic Algorithm Optimisation of Mathematical Models — An Aircraft Structural Dynamics Case Study." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design (NNFM), 197–210. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-44873-0_15.

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Conference papers on the topic "Multidisciplinary Design Optimisation"

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Nystrom, Mattias. "Multidisciplinary optimisation with application to exhaust system design." In 8th Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-4749.

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Wahler, Nicolas F., Daigo Maruyama, and Ali Elham. "Credibility-Based Multidisciplinary Design Optimisation of Electric Aircraft." In AIAA SCITECH 2023 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2023. http://dx.doi.org/10.2514/6.2023-1847.

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Hall, James, T. Rendall, and Christian B. Allen. "Fuel Tank Geometry Optimisation For Mechanical Damping." In 10th AIAA Multidisciplinary Design Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-1339.

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Macquart, Terence. "Future research in multi-step composite optimisation." In 2016 International Conference Multidisciplinary Engineering Design Optimization (MEDO). IEEE, 2016. http://dx.doi.org/10.1109/medo.2016.7746552.

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Ugail, Hassan, Malcolm Bloor, and Michael Wilson. "Implementing automatic design optimisation in an interactive environment." In 8th Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-4858.

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Wuilbercq, Romain, Fabrizio Pescetelli, Alessandro Mogavero, Edmondo Minisci, and Richard E. Brown. "Robust Multidisciplinary Design and Optimisation of a Reusable Launch Vehicle." In 19th AIAA International Space Planes and Hypersonic Systems and Technologies Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-2363.

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Ghisu, Tiziano, Geoffrey Parks, Jerome Jarrett, and P. Clarkson. "Robust Design Optimisation of Gas Turbine Compression Systems." In 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-5828.

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Toomer, C., M. Topliss, and D. Hills. "Aerodynamic optimisation using analytic descriptions of the design space." In 6th Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1996. http://dx.doi.org/10.2514/6.1996-4141.

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Bell, Theo A., Jerome P. Jarrett, and P. John Clarkson. "Exploring Multidisciplinary Trade-Offs in Turbomachinery Design." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-90926.

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Abstract:
The complexity of the modern aeroengine has led to a fragmented, modular, and evolutionary design process which, due to the lack of methods for generating understanding about the design space, results in a potentially holistically suboptimal design. Technological maturity, environmental pressures and changing business models are among the challenges facing the industry today; thus, the need to understand and exploit the trade-offs between the economics of production, maintenance, and operating costs and understand their effects during the design process is increasingly important. The first steps toward increased design space exploration and understanding can be achieved by integrating multidisciplinary engine design tools. By coupling engine design tools via SignPosting, a design process management and optimisation technique with a hierarchical database to manage multiple fidelity data and confidences, we have developed an integrated engine design model (IED) with which “better” designs and multidisciplinary trade-offs can be explored and visualized. As aeroengine aerodynamics mature and business models change, the benefit of focusing on other performance variables increases and the definition of what constitutes “better” changes. Accordingly, we have used the IED to minimize the weight of an intermediate pressure compressor and uncooled turbine spool while maintaining aerodynamic performance. By taking three different approaches to the optimisation and using weight objectives of different resolutions (complete spool weight, turbine and compressor weight, and both blade and disc weights for the turbine and compressor separately), the implications of a more traditional approach, which uses the turbine and compressor weights, can be visualized. We also present an analysis of how multidisciplinary non-linearities are exploited to reduce spool weight.
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Kelly, Liam M., Andy Keane, Andras Sobester, and David Toal. "Topology Optimisation: Increasing the Speed and Reliability of Design." In 15th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-2593.

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