Готові списки джерел за темами / Aerospace systems design

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Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Aerospace systems design"

1

Valenti, Michael. "Re-Engineering Aerospace Design." Mechanical Engineering 120, no. 01 (January 1, 1998): 70–72. http://dx.doi.org/10.1115/1.1998-jan-5.

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This article reviews that by integrating its CAD/CAM tools, Boeing’s Space Systems Unit hopes to enhance the quality of its products as it reduces both design- and manufacturing-cycle times. Sharper market competition led management to re-emphasize the practice and couple it with integrated CAD/CAM systems to provide a more supportive environment for concurrent engineering, thereby assuring the customer that cost, schedule, and quality goals would be met. This concept, called integrated product development (IPD), was launched in 1991. Boeing’s intention is to use the IPD strategy to reduce design-cycle time and manufacturing-cycle time as well as recurring costs. To support IPD, the Boeing designers developed electronic change control (ECC), an online system that enables engineers, technicians, manufacturers, and logisticians throughout the company to track and control engineering changes on a network of minicomputers, workstations, and desktops. Among the Unigraphics-based tools Boeing uses in IPD is the electronic development fixture (EDF), a three-dimensional digital model. EDF enables its users to electronically investigate fit, form, function, and interference detection.
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2

Sira-Ramirez, H., P. Lischinsky-Arenas, and O. Llanes-Santiago. "Dynamic compensator design in nonlinear aerospace systems." IEEE Transactions on Aerospace and Electronic Systems 29, no. 2 (April 1993): 364–79. http://dx.doi.org/10.1109/7.210075.

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3

Livne, Eli. "Special Issue: Multidisciplinary Design Optimization of Aerospace Systems." Journal of Aircraft 36, no. 1 (January 1999): 9–10. http://dx.doi.org/10.2514/2.2439.

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4

Monell, Donald W., and William M. Piland. "Aerospace systems design in NASA's collaborative engineering environment." Acta Astronautica 47, no. 2-9 (July 2000): 255–64. http://dx.doi.org/10.1016/s0094-5765(00)00065-5.

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5

Wang, Yi Wen, Ming Na Ding, Wen Juan Zheng, Zhen Chen, and Jing Shu Hu. "Design of Typical Aerospace Materials Database System." Materials Science Forum 800-801 (July 2014): 644–48. http://dx.doi.org/10.4028/www.scientific.net/msf.800-801.644.

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Due to the rapid development of aerospace industry, the amount of cutting data is increasing. Establishing cutting database for aerospace industry is necessary. Therefore, this article designs the typical aerospace material database system. According to project requirements analysis and the conceptual design, nine function blocks is set. They are data management, experiment management, optimization management, cutting tool design, cutting tool simulation, knowledge base, aerospace solutions, systems management, and help. And the article describes content and processes of every function block.
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6

Shi, Renhe, Teng Long, Nianhui Ye, Yufei Wu, Zhao Wei, and Zhenyu Liu. "Metamodel-based multidisciplinary design optimization methods for aerospace system." Astrodynamics 5, no. 3 (September 2021): 185–215. http://dx.doi.org/10.1007/s42064-021-0109-x.

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AbstractThe design of complex aerospace systems is a multidisciplinary design optimization (MDO) problem involving the interaction of multiple disciplines. However, because of the necessity of evaluating expensive black-box simulations, the enormous computational cost of solving MDO problems in aerospace systems has also become a problem in practice. To resolve this, metamodel-based design optimization techniques have been applied to MDO. With these methods, system models can be rapidly predicted using approximate metamodels to improve the optimization efficiency. This paper presents an overall survey of metamodel-based MDO for aerospace systems. From the perspective of aerospace system design, this paper introduces the fundamental methodology and technology of metamodel-based MDO, including aerospace system MDO problem formulation, metamodeling techniques, state-of-the-art metamodel-based multidisciplinary optimization strategies, and expensive black-box constraint-handling mechanisms. Moreover, various aerospace system examples are presented to illustrate the application of metamodel-based MDOs to practical engineering. The conclusions derived from this work are summarized in the final section of the paper. The survey results are expected to serve as guide and reference for designers involved in metamodel-based MDO in the field of aerospace engineering.
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7

Gil, Paulo J. S., Pedro M. B. Rosa, and Ivo M. L. Ferreira. "Modern approaches in the design of complex aerospace systems." Journal of Aerospace Engineering, Sciences and Applications 2, no. 1 (January 1, 2010): 15–26. http://dx.doi.org/10.7446/jaesa.0201.02.

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8

Bindolino, G., S. Ricci, and P. Mantegazza. "Integrated Servostructural Optimization in the Design of Aerospace Systems." Journal of Aircraft 36, no. 1 (January 1999): 167–75. http://dx.doi.org/10.2514/2.2423.

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9

Gupta, K. K. "An Integrated Systems Approach for Design of Aerospace Structures." International Journal of Space Structures 3, no. 2 (June 1988): 118–29. http://dx.doi.org/10.1177/026635118800300205.

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This paper is primarily concerned with the analysis and design of structural systems relating to aeronautical and aerospace engineering. Some numerical formulations are presented that deal with the synthesis of these systems integrating such disciplines as structures, unsteady aero-dynamics and control engineering. A general-purpose finite element computer program developed for associated large-scale computations is also described in some detail. Finally, results of relevant numerical analyses pertaining to some representative aircraft and spacecraft, obtained by utilizing the program, are presented that testify to the efficacy of the currently developed solution procedures.
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10

Saleh, Joseph H., Daniel E. Hastings, and Dava J. Newman. "Flexibility in system design and implications for aerospace systems." Acta Astronautica 53, no. 12 (December 2003): 927–44. http://dx.doi.org/10.1016/s0094-5765(02)00241-2.

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Дисертації з теми "Aerospace systems design"

1

Pfaender, Jens Holger. "Competitive Assessment of Aerospace Systems using System Dynamics." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14014.

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Aircraft design has recently experienced a trend away from performance centric design towards a more balanced approach with increased emphasis on engineering an economically successful system. This approach focuses on bringing forward a comprehensive economic and life-cycle cost analysis, which can be addressed by the introduction of a dynamic method allowing the analysis of the future attractiveness of such a concept in the presence of uncertainty. One way of addressing this is through the use of a competitive market model. However, existing market models do not focus on the dynamics of the market, which results in poor predictive capabilities. The method proposed here focuses on a top-down approach that integrates a competitive model based on work in the field of system dynamics into the aircraft design process. The primary contribution is the demonstration of the feasibility of such integration. This integration is achieved through the use of surrogate models, which enabled not only the practical integration of analysis techniques, but also reduced the computational requirements so that interactive exploration as envisioned is actually possible. An example demonstration of this integration is built on the competition in the 250 seat large commercial aircraft market. Two aircraft models were calibrated to existing performance and certification data and then integrated into the system dynamics market model, which was then calibrated with historical market data. This calibration showed a much improved predictive capability as compared to the conventional logit regression models. The resulting market model was then integrated into a prediction profiler environment with a time variant Monte-Carlo analysis resulting in a unique trade-off environment. This environment was shown to allow interactive trade-off between aircraft design decisions and economic considerations while allowing the exploration potential market success in the light of varying external market conditions and scenarios. Another use of the existing outputs of the Monte-Carlo analysis was then realized by visualizing the model variables on a multivariate scatter plot. This enables the designer to define strategic market and return on investment goals for a number of scenarios and then directly see which specific aircraft designs meet these goals.
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2

Fernandez, Martin Ismael. "Valuation of design adaptability in aerospace systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22584.

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Анотація:
Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2008.
Committee Chair: Dr. Mavris, Dimitri; Committee Member: Dr. Hollingsworth, Peter; Committee Member: Dr. McMichael, Jim; Committee Member: Dr. Saleh, Joseph; Committee Member: Dr. Schrage, Daniel.
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3

Waslander, Steven L. "Multi-agent systems design for aerospace applications /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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4

Borer, Nicholas Keith. "Decision Making Strategies for Probabilistic Aerospace Systems Design." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/10469.

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Modern aerospace systems design problems are often characterized by the necessity to identify and enable multiple tradeoffs. This can be accomplished by transformation of the design problem to a multiple objective optimization formulation. However, existing multiple criteria techniques can lead to unattractive solutions due to their basic assumptions; namely that of monotonically increasing utility and independent decision criteria. Further, it can be difficult to quantify the relative importance of each decision metric, and it is very difficult to view the pertinent tradeoffs for large-scale problems. This thesis presents a discussion and application of Multiple Criteria Decision Making (MCDM) to aerospace systems design and quantifies the complications associated with switching from single to multiple objectives. It then presents a procedure to tackle these problems by utilizing a two-part relative importance model for each criterion. This model contains a static and dynamic portion with respect to the current value of the decision metric. The static portion is selected based on an entropy analogy of each metric within the decision space to alleviate the problems associated with quantifying basic (monotonic) relative importance. This static value is further modified by examination of the interdependence of the decision metrics. The dynamic contribution uses a penalty function approach for any constraints and further reduces the importance of any metric approaching a user-specified threshold level. This reduces the impact of the assumption of monotonically increasing utility by constantly updating the relative importance of a given metric based on its current value. A method is also developed to determine a linearly independent subset of the original requirements, resulting in compact visualization techniques for large-scale problems.
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5

Wang, Jennifer Y. "Migration of aerospace technologies to adjacent markets." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/105302.

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Анотація:
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 51-56).
Shrinking government budgets due to economic woes has aerospace and defense contractors scrambling to sustain their business and minimize the effects of budget sequestration. Given the global economic climate and the level of federal debt, government budget spending is unlikely to recover in the near future to previous levels, where aerospace and defense contractors had enjoyed an abundance of million and billion dollar cost-reimbursable contracts. In current business conditions, company leadership has put a new focus on finding and developing business in adjacent markets, where core competencies can be utilized to generate alternative streams of revenue. In order to provide insight into potential adjacent markets for aerospace technologies and entry strategies that increase chances of success, this thesis analyzes cases of technologies originally developed for an aerospace application that were eventually adopted for use in another (non-aerospace) industry. Analysis of metrics and 35 cases compiled from NASA's Spinoff and Technology Databases reinforce several observations that have been generalized in other literature: 1) a wide variety of industries could be considered adjacent markets, 2) entering established industries may offer the highest technology adoption rate, 3) partnership with an existing firm or organization with knowledge of the adjacent market has played a key role in the successful adoption of the technology in the adjacent market, and 4) building-block technologies at the subsystem, component and base material level most often traversed market boundaries. However, a handful of cases prove that systems can traverse market boundaries in whole under certain conditions. Most importantly, the role of the aerospace industry as advanced analog lead users is a unique advantage that aerospace firms should leverage.
by Jennifer Y. Wang.
S.M. in Engineering and Management
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6

Hart, Peter Bartholomew. "A plm implementation for aerospace systems engineering-conceptual rotorcraft design." Thesis, Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28278.

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The thesis will discuss the Systems Engineering phase of an original Conceptual Design Engineering Methodology for Aerospace Engineering-Vehicle Synthesis. This iterative phase is shown to benefit from digitization of Integrated Product&Process Design (IPPD) activities, through the application of Product Lifecycle Management (PLM) technologies. Requirements analysis through the use of Quality Function Deployment (QFD) and 7 MaP tools is explored as an illustration. A "Requirements Data Manager" (RDM) is used to show the ability to reduce the time and cost to design for both new and legacy/derivative designs. Here the COTS tool Teamcenter Systems Engineering (TCSE) is used as the RDM. The utility of the new methodology is explored through consideration of a legacy RFP based vehicle design proposal and associated aerospace engineering. The 2001 American Helicopter Society (AHS) 18th Student Design Competition RFP is considered as a starting point for the Systems Engineering phase. A Conceptual Design Engineering activity was conducted in 2000/2001 by Graduate students (including the author) in Rotorcraft Engineering at the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology, Atlanta GA. This resulted in the "Kingfisher" vehicle design, an advanced search and rescue rotorcraft capable of performing the "Perfect Storm" mission, from the movie of the same name. The associated requirements, architectures, and work breakdown structure data sets for the Kingfisher are used to relate the capabilities of the proposed Integrated Digital Environment (IDE). The IDE is discussed as a repository for legacy knowledge capture, management, and design template creation. A primary thesis theme is to promote the automation of the up-front conceptual definition of complex systems, specifically aerospace vehicles, while anticipating downstream preliminary and full spectrum lifecycle design activities. The thesis forms a basis for additional discussions of PLM tool integration across the engineering, manufacturing, MRO and EOL lifecycle phases to support business management processes.
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7

Agte, Jeremy S. (Jeremy Sundermeyer). "Multistate analysis and design : case studies in aerospace design and long endurance systems." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68167.

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Анотація:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, September 2011.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
"September 2011." Cataloged from student submitted PDF version of thesis.
Includes bibliographical references (p. 221-230).
This research contributes to the field of aerospace engineering by proposing and demonstrating an integrated process for the early-stage, multistate design of aerospace systems. The process takes into early consideration the many partially degraded states that real-world systems experience throughout their operation. Despite advancing efforts aimed at maintaining operation in a state of optimum performance, most systems spend very substantial amounts of time operating in degraded or off-nominal states (e.g. Hubble space telescope, Mars Spirit rover, or aircraft flying under minimum-equipment-list restrictions). There exist relatively few methods and tools to address this at the beginning of the design process. At one end of the spectrum is design optimization, but this typically concentrates on the system in its nominal state of operation, only infrequently considering failure states through piecemeal application of constraints. There is reliability analysis, which focuses on component failure rates and the benefits of redundancy but does not consider how well or poorly the system performs with partial failures. Finally, there is controls theory, where control laws are optimized but the plant is typically assumed to be given a priori. The methodology described within this thesis coordinates elements from each of these three areas into an effective integrated framework. It allows the designer deeper insight into the complex problem of designing cost effective systems that must operate for long durations with little or expensive opportunity for repair or intervention. Specific contributions include: 1) the above methodology, which evaluates responses in system expected performance and availability to changes in static design variables (geometry) and component failure rates, accounting for control design variables (gains) where appropriate, 2) the demonstration of the cost and benefits associated with a multistate design approach as compared to reliability analysis and the nominal design approach, and 3) a multilayer extension of Markov analysis, for translating single sortie vehicle level metrics into measures of multistate campaign performance. The process is demonstrated through three application case studies. The first of these establishes the feasibility of the approach through the multistate analysis of performance for an existing twin-engine aircraft. This analysis was enabled through the development of a multidisciplinary simulation based design model for evaluation of multistate aircraft performance. A medium-altitude long endurance unmanned aerial vehicle is designed in the second case study, first from a single-sortie, ultra long endurance perspective and then from a multiple sortie, mission campaign perspective. Finally, the third case study demonstrates applicability of the approach to a lower level subsystem, that of the lubrication system for a geared turbofan engine. Several major findings result from these case studies, including that: 1) multistate performance output spaces have distinctly unique shapes and boundaries, depending on whether formed through variation of component failure rates, static design variables (geometry), or a multistate combination of both, 2) a region of multistate performance results from the combined variation of failure rates and static design variables that is unachievable through the independent variation of either one, 3) small changes in static design variables may be used to significantly improve system availability, and 4) the general multistate design problem is one of competing objectives between system availability, expected performance, nominal performance, and cost.
by Jeremy S. Agte.
Ph.D.
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8

Hollingsworth, Peter Michael. "Requirements Controlled Design: A Method for Discovery of Discontinuous System Boundaries in the Requirements Hyperspace." Diss., Available online, Georgia Institute of Technology, 2004:, 2004. http://etd.gatech.edu/theses/available/etd-04092004-151914/unrestricted/hollingsworth%5Fpeter%5Fm%5F200405%5Fphd.pdf.

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Анотація:
Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2004.
Nickol, Craig, Committee Member ; Goodman, Seymour, Committee Member ; Schrage, Daniel, Committee Member ; Craig, James, Committee Member ; Mavris, Dimitri, Committee Chair. Vita. Includes bibliographical references (leaves 272-283).
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9

Papageorgiou, George. "Robust control system design : H∞ loop sharing and aerospace applications." Thesis, University of Cambridge, 1998. https://www.repository.cam.ac.uk/handle/1810/272494.

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10

Daberkow, Debora Daniela. "A formulation of metamodel implementation processes for complex systems design." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/12478.

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Книги з теми "Aerospace systems design"

1

Kumar, S. Kishore, Indira Narayanaswamy, and V. Ramesh, eds. Design and Development of Aerospace Vehicles and Propulsion Systems. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9601-8.

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2

Albers, James A. NASA Ames Aerospace Systems Directorate research. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1991.

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3

Kodiyalam, S. Multidisciplinary aerospace systems optimization, computational aerosciences (CAS) project. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 2001.

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4

Engineers, Society of Automotive, ed. Aerospace environmental systems: Proceedings of the Sixteenth ICES conference. Warrendale, PA: Society of Automotive Engineers, 1986.

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5

Bement, Laurence J. A manual for pyrotechnic design, development and qualification. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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6

Mishkin, A. H. Space-based multifunctional end effector systems: Functional requirements and proposed designs. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1988.

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7

Voigt, Robert G. Requirements for multidisciplinary design of aerospace vehicles on high performance computers. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1989.

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8

Malone, J. B. The design of future airbreathing engine systems within an intelligent synthesis environment. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 1999.

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9

Malone, J. B. The design of future airbreathing engine systems within an intelligent synthesis environment. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 1999.

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10

Concurrent Design and Manufacture of Aerospace Transmission Systems (Conference) (1998 Derby (England)). Aerospace transmission systems: Concurrent design and manufacture : 20 May 1998, Rolls-Royce, Derby, UK. Bury St. Edmunds: Professional Engineering, 1998.

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Частини книг з теми "Aerospace systems design"

1

Perrotin, Maxime, Julien Delange, and Jérôme Hugues. "The Design of Aerospace Systems." In Distributed Systems, 191–227. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118601365.ch9.

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2

Bozzano, Marco, Harold Bruintjes, Alessandro Cimatti, Joost-Pieter Katoen, Thomas Noll, and Stefano Tonetta. "Formal Methods for Aerospace Systems." In Cyber-Physical System Design from an Architecture Analysis Viewpoint, 133–59. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4436-6_6.

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3

Vassev, Emil, and Mike Hinchey. "Fundamentals of Designing Complex Aerospace Software Systems." In Complex Systems Design & Management, 65–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25203-7_4.

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4

Minisci, Edmondo, and Massimiliano Vasile. "Multidisciplinary Design Optimization of Aerospace Transportation Systems." In Computational Intelligence in Aerospace Sciences, 491–528. Reston, VA: American Institute of Aeronautics and Astronautics, Inc., 2014. http://dx.doi.org/10.2514/5.9781624102714.0491.0528.

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5

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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6

Gery, Eran. "Realizing Digital Systems Engineering—Aerospace and Defence Use Case." In Complex Systems Design & Management, 385–400. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73539-5_29.

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7

Saadat, Mozafar. "Challenges in the Assembly of Large Aerospace Components." In Integrated Systems, Design and Technology 2010, 37–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17384-4_4.

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Martins, Joaquim R. R. A. "Chapter 19: Multidisciplinary Design Optimization of Aerospace Systems." In Advances and Trends in Optimization with Engineering Applications, 249–57. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2017. http://dx.doi.org/10.1137/1.9781611974683.ch19.

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Mavris, Dimitri N., and Olivia J. Pinon. "An Overview of Design Challenges and Methods in Aerospace Engineering." In Complex Systems Design & Management, 1–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25203-7_1.

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Ramalingam, Thirunavukkarasu, Joel Otto, and Benaroya Christophe. "Design Space Exploration for Aerospace IoT Products." In Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation, 707–21. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64849-7_62.

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Тези доповідей конференцій з теми "Aerospace systems design"

1

CHAMIS, C., and S. SINGHAL. "Computational simulation of concurrent engineering for aerospace propulsion systems." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-1144.

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2

Becz, Sandor, Alessandro Pinto, Lawrence Zeidner, Ritest Khire, Hayden Reeve, and Andrzej Banaszuk. "Design System for Managing Complexity in Aerospace Systems." In 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-9223.

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3

WOLF, DIETER. "Transys - A software system for preliminary design, analysis and evaluation of space transportation systems." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-1193.

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4

RYAN, ROBERT, and V. I. VERDERAIME. "Launch Vehicle Systems Design Analysis." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1993. http://dx.doi.org/10.2514/6.1993-1140.

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5

PETERSEN, T., and P. SUTCLIFFE. "Systems engineering as applied to the Boeing 777." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-1010.

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6

BACKES, PAUL, MARK LONG, and ROBERT STEELE. "Designing minimal space telerobotics systems for maximum performance." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-1015.

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7

BRIGGS, HUGH. "Integrated modeling and design of advanced optical systems." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-1249.

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8

Braun, Robert, Ilan Kroo, and Peter Gage. "Post-optimality analysis in aerospace vehicle design." In Aircraft Design, Systems, and Operations Meeting. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1993. http://dx.doi.org/10.2514/6.1993-3932.

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9

DECKER, D., L. INOUYE, and D. ROLANDELLI. "Design of hi-power unit components for space systems." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-1062.

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10

SCHROEDER, W., R. BROGDON, J. PETERS, and C. GLANCY. "Application of RDD-100 for Space Station systems engineering." In Aerospace Design Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-1257.

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Звіти організацій з теми "Aerospace systems design"

1

Burns, John A. A Computational Environment for Design of Aerospace Systems. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada379978.

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2

Teel, Andrew R. Hybrid Control Systems: Design and Analysis for Aerospace Applications. Fort Belvoir, VA: Defense Technical Information Center, February 2009. http://dx.doi.org/10.21236/ada495350.

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3

Burns, John A. Sensitivity and Adjoint Methods for Design of Aerospace Systems. Fort Belvoir, VA: Defense Technical Information Center, July 2002. http://dx.doi.org/10.21236/ada417179.

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4

Jameson, Anthony, and Juan J. Alonso. Computational Algorithms for High-Fidelity Multidisciplinary Design of Complex Aerospace Systems. Fort Belvoir, VA: Defense Technical Information Center, December 2003. http://dx.doi.org/10.21236/ada430007.

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5

Haddad, Wassim M. An Energy-Based Thermodynamic Stabilization Framework for Hybrid Control Design of Large-Scale Aerospace Systems. Fort Belvoir, VA: Defense Technical Information Center, February 2009. http://dx.doi.org/10.21236/ada500028.

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6

Roye, Thorsten. The Right Level of Automation for Industry 4.0. SAE International, May 2022. http://dx.doi.org/10.4271/epr2022013.

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Анотація:
In its entirety, automation is part of an integrated, multi-disciplinary product development process including the design, process, production, logistics, and systems approach—it depends on all these areas, but it also influences them as well. Automation in aerospace manufacturing is present throughout the entire supply chain, from elementary part manufacturing at suppliers up to final assembly, and a clear understanding of all the benefits (and drawbacks) of automation would help designers and engineers select the right designs for and levels of automation. The Right Level of Automation Within Industry 4.0 examines all impacts of automation that should be known by designers, manufacturers, and companies before investments in automation-related decisions are made—regardless of the which industry they work in. The process and the set of criteria discussed in this report will help decision makers select the right level of automation.
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