Insights from developing a multidisciplinary design and analysis environment

Wang, Chengen

doi:10.1016/j.compind.2014.02.015

Cited by 9 publications

(6 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown in Fig. 17, the design collaboration system is mainly composed of project management and workflow management [194]. The former is the core competency that configures engineering sources in accord with each product development project, and supports collaboration among team members.…”

Section: Integrated Human-machine Interface For Designing Turbine Engmentioning

confidence: 99%

See 1 more Smart Citation

Automating design with intelligent human–machine integration

et al. 2015

View full text Add to dashboard Cite

Section: Integrated Human-machine Interface For Designing Turbine Engmentioning

confidence: 99%

“…Unstructured data can be transformed into structured data through meshing and mapping to reduce computation time and cost [194]. As shown in the upper part of Fig.…”

Section: Integrated Human-machine Interface For Designing Turbine Engmentioning

confidence: 99%

Automating design with intelligent human–machine integration

et al. 2015

View full text Add to dashboard Cite

“…From system perspective, multidisciplinary design and analysis requires to integrate, coordinate, and control disciplinary software tools, data sources, and other engineering resources as holistic solutions. System integration aims to overcome engineering inefficiency, incongruence and inconsistency off information caused by automation islands and synergize system components for system-level optimizations [35].…”

Section: ) Disciplinary Technologies For Data Utilizationmentioning

confidence: 99%

The State of the Art of Information Integration in Space Applications

Yung

et al. 2022

IEEE Access

View full text Add to dashboard Cite

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and classified; (2) existing works in space system development are analyzed in terms of their contributions to space economy, divisions, activities, and missions; (3) enabling space information technologies are explored at aspects of sensing, communication, networking, data analysis, and system integration; (4) the importance of first-time right (FTR) for implementation of a space system is emphasized, the limitations of digital twin (DT-I) as technological enablers are discussed, and a concept digital-triad (DT-II) is introduced as an information platform to overcome these limitations with a list of fundamental design principles; (5) the research challenges and opportunities are discussed to promote SII and advance space informatics in future.INDEX TERMS Information integration (II), space informatics, digital triad (DT-II), internet of digital-triad things (IoDTT), first-time right (FTR), space information integration (SII). FIGURE 2. Technical drivers of II applications.

show abstract

“…The success of such an aircraft design can provide opportunities to consider the welfare and comfort of passengers in its design phase and lead to a decrease in fuel consumption. To achieve this aim, faster and more efficient approaches to design optimization of lightweight but strong aircraft have been well studied by many researchers [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic Approaches to Solve a Complex Aircraft Performance Optimization Problem

2019

View full text Add to dashboard Cite

The increasing demands for travelling comfort and reduction of carbon dioxide emissions have been considered substantially in the stage of conceptual aircraft design. However, the design of a modern aircraft is a multidisciplinary process, which requires the coordination of information from several specific disciplines, such as structures, aerodynamics, control, etc. To address this problem with adequate accuracy, the multidisciplinary analysis and optimization (MAO) method is usually applied as a systematic and robust approach to solve such complex design issues arising from industries. Since MAO method is tedious and computationally expensive, genetic programming (GP)-based metamodeling techniques incorporating MAO are proposed as an effective approach to minimize the wing stiffness of a large aircraft subject to aerodynamic, aeroelastic and stability constraints in the conceptual design phase. Based on the linear small-disturbance theory, the state-space equation is employed for stability analysis. In the process of multidisciplinary analysis, aeroelastic response simulations are performed using Nastran. To construct metamodels representing the responses of the interests with high accuracy as well as less computational burden, optimal Latin hypercube design of experiments (DoE) is applied to determine the optimized distribution of sampling points. Following that, parametric optimization is carried out on metamodels to obtain the optimal wing geometry shape, elastic axis positions and stiffness distribution, and then the solution is verified by finite element simulations. Finally, the superiority of the GP-based metamodel technique over genetic algorithm is demonstrated by multidisciplinary design optimization of a representative beam-frame wing structure in terms of accuracy and efficiency. The results also show that GP metamodel-based strategy for solving MAO problems can provide valuable insights to tailoring parameters for the effective design of a large aircraft in the conceptual phase.

show abstract

Insights from developing a multidisciplinary design and analysis environment

Cited by 9 publications

References 32 publications

Automating design with intelligent human–machine integration

Automating design with intelligent human–machine integration

The State of the Art of Information Integration in Space Applications

Metaheuristic Approaches to Solve a Complex Aircraft Performance Optimization Problem

Contact Info

Product

Resources

About