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1

Thomas, Nathan. "Systems engineering: Program empowerment for 21st century aerospace projects." IEEE Aerospace and Electronic Systems Magazine 29, no. 12 (2014): 18–26. http://dx.doi.org/10.1109/maes.2014.130171.

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2

Zalewski, Janusz. "Aerospace software engineering." Control Engineering Practice 3, no. 9 (1995): 1349–50. http://dx.doi.org/10.1016/0967-0661(95)90053-5.

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3

Chahl, Javaan. "Unmanned Aerial Systems Platform Research Prognosis." Applied Mechanics and Materials 225 (November 2012): 555–60. http://dx.doi.org/10.4028/www.scientific.net/amm.225.555.

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Much of aerospace academia is anticipating a boom in Unmanned Aerial Vehicle (UAV) funding and research opportunities. The expectation is built on the premise that UAVs will revolutionize aerospace, which is likely based on current trends. There is also an anticipation of an increasing number of new platforms and research investment, which is likely but must be analyzed carefully to determine where the opportunities might lie. This paper draws on the state of industry and a systems engineering approach. We explore what aspects of UAVs really are the results of aerospace science advances and what aspects will be rather more mundane works of engineering.
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4

Sun, Fuyu, Hua Wang, and Jianping Zhou. "Research and development techniques for early-warning satellite systems using concurrent engineering." Concurrent Engineering 26, no. 3 (2018): 215–30. http://dx.doi.org/10.1177/1063293x18768668.

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An early-warning satellite system is a complex project that requires the participation of many aerospace academies and scientific institutions. In terms of software programming, this study proposes a new simulation integrated management platform for the analysis of parallel and distributed systems. The platform facilitates the design and testing of both applications and architectures. To improve the efficiency of project development, new early-warning satellite systems are designed based on the simulation integrated management platform. In terms of project management, this study applies concurrent engineering theory to aerospace engineering and presents a method of collaborative project management. Finally, through a series of experiments, this study validates the simulation integrated management platform, models, and project management method. Furthermore, the causes of deviation and prevention methods are explained in detail. The proposed simulation platform, models, and project management method provide a foundation for further validations of autonomous technology in space attack–defense architecture research.
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5

Oliva, Roger, Erik Blasch, and Ron Ogan. "Applying Aerospace Technologies to Current Issues Using Systems Engineering: 3rd AESS chapter summit." IEEE Aerospace and Electronic Systems Magazine 28, no. 2 (2013): 34–41. http://dx.doi.org/10.1109/maes.2013.6477867.

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6

Sanya, I. O., and E. M. Shehab. "An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry." International Journal of Production Research 52, no. 20 (2014): 6192–215. http://dx.doi.org/10.1080/00207543.2014.919422.

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7

Balthazar, José M., Paulo Batista Gonçalves, Stefan Kaczmarczyk, André Fenili, Marcos Silveira, and Ignacio Herrera Navarro. "Editorial Dynamics and Control of Aerospace and Vertical Transportation Systems." Applied Mechanics and Materials 706 (December 2014): 1–5. http://dx.doi.org/10.4028/www.scientific.net/amm.706.1.

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This Special Issue presents a selection of papers initially presented at the 11th International Conference on Vibration Problems (ICOVP-2013), held from 9 to 12 September 2013 in Lisbon, Portugal. The main topics of this Special Issue are linear and, mainly, nonlinear dynamics, chaos and control of systems and structures and their applications in different field of science and engineering. According to the goal of the Special Issue, the selected contributions are divided into three major parts: “Vibration Problems in Vertical Transportation Systems”, “Nonlinear Dynamics, Chaos and Control of Elastic Structures” and “New Strategies and Challenges for Aerospace and Ocean Structures Dynamics and Control”.
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8

Nitoi, Dan, Florin Samer, Constantin Gheorghe Opran, and Constantin Petriceanu. "Finite Element Modelling of Thermal Behaviour of Solar Cells." Materials Science Forum 957 (June 2019): 493–502. http://dx.doi.org/10.4028/www.scientific.net/msf.957.493.

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Engineering Science Based on Modelling and Simulation (M & S) is defined as the discipline that provides the scientific and mathematical basis for simulation of engineering systems. These systems range from microelectronic devices to automobiles, aircraft, and even oilfield and city infrastructure. In a word, M & S combines knowledge and techniques in the fields of traditional engineering - electrical, mechanical, civil, chemical, aerospace, nuclear, biomedical and materials science - with the knowledge and techniques of fields such as computer science, mathematics and physics, and social sciences. One of the problems that arise during solar cell operation is that of heating them because of permanent solar radiation. Since the layers of which they are made are very small and thick it is almost impossible to experimentally determine the temperature in each layer. In this sense, the finite element method comes and provides a very good prediction and gives results impossible to obtain by other methods. This article models and then simulates the thermal composition of two types of solar cells, one of them having an additional layer of silicon carbide that aims to lower the temperature in the lower layer, where the electronic components stick to degradable materials under the influence of heat.
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9

Baird, J. A. "How Can Systems Engineers Do Systems Engineering?" IEEE Aerospace and Electronic Systems Magazine 12, no. 9 (1997): 42. http://dx.doi.org/10.1109/maes.1997.618018.

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10

Xiao, Bing, Hamid Reza Karimi, Xiang Yu, and Qingbin Gao. "IEEE Access Special Section: Recent Advances in Fault Diagnosis and Fault-Tolerant Control of Aerospace Engineering Systems." IEEE Access 8 (2020): 61157–60. http://dx.doi.org/10.1109/access.2020.2980433.

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11

Wang, Gan, Ricardo Valerdi, Garry J. Roedler, Aaron Ankrum, and John E. Gaffney. "Harmonising software engineering and systems engineering cost estimation." International Journal of Computer Integrated Manufacturing 25, no. 4-5 (2012): 432–43. http://dx.doi.org/10.1080/0951192x.2010.542182.

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12

Smales, H. "Friction Materials—Black Art or Science?" Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 209, no. 3 (1995): 151–57. http://dx.doi.org/10.1243/pime_proc_1995_209_200_02.

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This address highlights some of the experiences of the Chairman in his career at Mintex Don Limited, a member of the BBA Group of companies, concerning the development and installation engineering of friction materials. Work on specific component design to overcome problems in both transmissions and brake systems is described; an outline is given of how testing has developed over the past 40 years; and the influence of regulations on testing is described, as well as how the change from asbestos-based to asbestos-free friction materials was achieved. Modern analysis techniques, electronic instrumentation and computational methods have increasingly assisted in this work and it is shown that friction materials have ceased to be developed by ‘black art’ and are now a well understood science.
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13

Garrison, T. P., M. Ince, J. Pizzicaroli, and P. A. Swan. "Systems Engineering Trades for the IRIDIUM Constellation." Journal of Spacecraft and Rockets 34, no. 5 (1997): 675–80. http://dx.doi.org/10.2514/2.3267.

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14

Augustine, N. R. "The engineering of systems engineers." IEEE Aerospace and Electronic Systems Magazine 15, no. 10 (2000): 3–8. http://dx.doi.org/10.1109/maes.2000.879390.

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15

Ruggieri, Marina. "Systems engineering in South Africa." IEEE Aerospace and Electronic Systems Magazine 25, no. 7 (2010): 37–39. http://dx.doi.org/10.1109/maes.2010.5546293.

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16

White, B. E. "Complex adaptive systems engineering (CASE)." IEEE Aerospace and Electronic Systems Magazine 25, no. 12 (2010): 16–22. http://dx.doi.org/10.1109/maes.2010.5638784.

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17

Tennyson, R. C., T. Coroy, G. Duck, et al. "Fibre optic sensors in civil engineering structures." Canadian Journal of Civil Engineering 27, no. 5 (2000): 880–89. http://dx.doi.org/10.1139/l00-010.

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This paper presents an overview of the development and application of ISIS fibre optic sensor (FOS) technology by the University of Toronto Institute for Aerospace Studies and Department of Electrical and Computer Engineering. The primary focus of this technology has involved the use of fibre Bragg gratings (FBGs) to measure strain and temperature in concrete structures and fibre reinforced plastic (FRP) overwraps applied to concrete structures. A brief review of existing fibre optic sensor configurations and the advantages of using FOS compared to other strain sensors is first presented. Subsequently, the development of new sensor concepts such as a long gauge of arbitrary length, a distributed gauge for measuring local strain gradients, and multiple FBGs on a single fibre optic cable are discussed, with examples of their application to civil engineering structures. In addition, the specialized instruments under development that are essential for obtaining strain information from these sensors are also described. Finally, the issue of wireless remote monitoring of FOS systems is addressed.Key words: fibre optic sensors, Bragg gratings, civil engineering structures, instrumentation.
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18

Reising, Dal Vernon C. "Book review of Cognitive Systems Engineering." International Journal of Aviation Psychology 9, no. 3 (1999): 291–302. http://dx.doi.org/10.1207/s15327108ijap0903_6.

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19

Madni, Azad M. "Producing the Best for Aerospace and Defense: Systems Architecting and Engineering Program at the University of Southern California." Astropolitics 9, no. 2-3 (2011): 165–72. http://dx.doi.org/10.1080/14777622.2011.625921.

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20

McQuay, W. K. "Distributed collaborative environments for systems engineering." IEEE Aerospace and Electronic Systems Magazine 20, no. 8 (2005): 7–12. http://dx.doi.org/10.1109/maes.2005.1499287.

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21

Head, Steve, and Bill Virostko. "Systems engineering execution and knowledge management." IEEE Aerospace and Electronic Systems Magazine 24, no. 10 (2009): 4–9. http://dx.doi.org/10.1109/maes.2009.5317774.

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22

Jansma, P. A. "Making a case for systems engineering." IEEE Aerospace and Electronic Systems Magazine 25, no. 4 (2010): 4–17. http://dx.doi.org/10.1109/maes.2010.5467651.

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23

Smith, M. J., K. E. Jacobson, and J. P. Afman. "Towards certification of computational fluid dynamics as numerical experiments for rotorcraft applications." Aeronautical Journal 122, no. 1247 (2017): 104–30. http://dx.doi.org/10.1017/aer.2017.118.

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ABSTRACTVirtual Engineering (VE), also known as Model-Based Systems Engineering (MBSE), is necessary in both current operational engineering qualifications and to help reduce the costs of future vertical lift design and analysis. As computational power continues to provide increasing capability to the rotorcraft engineering community to perform simulations in both real time and off line, it is imperative that the community develop verification and validation protocols and processes to certify these methods so that they can be reliably used to help reduce engineering cost and schedule. Computational Fluid Dynamics (CFD) has become a major Computational Science and Engineering (CSE) tool in the fixed wing and vertical lift communities, but it has not been developed to the point where it is accepted as a replacement for testing in certification of new or existing systems or vehicles. Since the rise of modern CFD in the 1980s, the promise of CFD’s capabilities has been met or exceeded, but its role in certification arguably remains less prominent than projected. The ability to implement transformative technologies further drives the need for CFD in design. To meet CFD’s role in certification, several goals must be met to provide a true “numerical experiment” from which accuracies (error estimates), sensitivities, and consistent application results can be extracted. This paper discusses the progress and direction towards developing CFD strategies for certification.
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24

Oman, H. ""Spacecraft Systems Engineering" Second Edition [Book Review]." IEEE Aerospace and Electronic Systems Magazine 11, no. 4 (1996): 39. http://dx.doi.org/10.1109/maes.1996.490223.

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25

BARAKAT, O., J. P. BOURRIÈRES, and F. LHOTE. "A hierarchical knowledge engineering of production systems." International Journal of Computer Integrated Manufacturing 6, no. 6 (1993): 350–56. http://dx.doi.org/10.1080/09511929308944586.

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26

O’GRADY, PETER J., YEONGHO KIM, and ROBERT E. YOUNG. "A hierarchical approach to concurrent engineering systems." International Journal of Computer Integrated Manufacturing 7, no. 3 (1994): 152–62. http://dx.doi.org/10.1080/09511929408944605.

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27

Morris, Huong, Simon Lee, Eric Shan, and Sai Zeng. "Information Integration Framework For Product Life-Cycle Management of Diverse Data." Journal of Computing and Information Science in Engineering 4, no. 4 (2004): 352–58. http://dx.doi.org/10.1115/1.1818684.

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Automobile, aerospace, and other industrial manufacturers have evolved over the years to use a multitude of computer-aided design (CAD) and product data management (PDM) systems and have long depended on single-vendor solutions to support their enterprise-wide engineering activities. Increased product complexity, distributed authoring environments, and the need for tighter team integration with partners and suppliers have created challenges and new opportunities for information technology (IT) vendors to be able to integrate systems from multiple independent software vendors (ISVs) to form a coherent Enterprise PDM system. This paper will describe, in detail, a case study and solution of an IBM Research project called Hedwig. Hedwig investigates creating robust solutions for Product Life-Cycle Management (PLM). We focus on several research issues, including information federation, data mapping, synchronization, and web services connections. We describe a working system that allows access to several heterogeneous PDM systems that are used in the automotive and aerospace industries.
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28

Young, Peter. "Data-Based Mechanistic Modeling of Engineering Systems." Journal of Vibration and Control 4, no. 1 (1998): 5–28. http://dx.doi.org/10.1177/107754639800400102.

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29

Burnham, S. "Systems Engineering: A Practical Approach for Junior Engineers." IEEE Aerospace and Electronic Systems Magazine 21, no. 6 (2006): 3–8. http://dx.doi.org/10.1109/maes.2006.1662002.

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30

Dempster, William F. "Biosphere II: Engineering of Manned, Closed Ecological Systems." Journal of Aerospace Engineering 4, no. 1 (1991): 23–30. http://dx.doi.org/10.1061/(asce)0893-1321(1991)4:1(23).

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31

Marin, Băleanu, and Vlase. "Symmetry in Applied Continuous Mechanics." Symmetry 11, no. 10 (2019): 1286. http://dx.doi.org/10.3390/sym11101286.

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Engineering practice requires the use of structures containing identical components or parts, which are useful from several points of view: less information is needed to describe the system, design is made quicker and easier, components are made faster than a complex assembly, and finally the time to achieve the structure and the cost of manufacturing decreases. Additionally, the subsequent maintenance of the system becomes easier and cheaper. This Special Issue is dedicated to this kind of mechanical structure, describing the properties and methods of analysis of these structures. Discrete or continuous structures in static and dynamic cases are considered. Theoretical models, mathematical methods, and numerical analysis of the systems, such as the finite element method and experimental methods, are expected to be used in the research. Such applications can be used in most engineering fields including machine building, automotive, aerospace, and civil engineering.
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32

Fischer, Philipp Martin, Meenakshi Deshmukh, Volker Maiwald, Dominik Quantius, Antonio Martelo Gomez, and Andreas Gerndt. "Conceptual data model: A foundation for successful concurrent engineering." Concurrent Engineering 26, no. 1 (2017): 55–76. http://dx.doi.org/10.1177/1063293x17734592.

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Today, phase A studies of future space systems are often conducted in special design facilities such as the Concurrent Engineering Facility at the German Aerospace Center (DLR). Within these facilities, the studies are performed following a defined process making use of a data model for information exchange. Quite often it remains unclear what exactly such a data model is and how it is implemented and applied. Nowadays, such a data model is usually a software using a formal specification describing its capabilities within a so-called meta-model. This meta-model, often referred as conceptual data model, is finally used and instantiated as system model during these concurrent engineering studies. Such software also provides a user interface for instantiating and sharing the system model within the design team and it provides capabilities to analyze the system model on the fly. This is possible due to the semantics of the underlying conceptual data model creating a common language used to exchange and process design information. This article explains the implementation of the data model at DLR and shows information how it is applied in the concurrent engineering process of the Concurrent Engineering Facility. It highlights important aspects concerning the modeling capabilities during a study and discusses how they can be implemented into a corresponding conceptual data model. Accordingly, the article presents important aspects such as rights management and data consistency and the implications of them to the software’s underlying technology. A special use case of the data model is depicted and shows the flexibility of the implementation proven by a study of a multi-module space station.
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Schilling, K. "Design of pico-satellites for education in systems engineering." IEEE Aerospace and Electronic Systems Magazine 21, no. 7 (2006): S_9—S_14. http://dx.doi.org/10.1109/maes.2006.1684269.

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34

Letfullin, Renat R., Thomas F. George, and Asror Kh Ramazanov. "Multifunctional Cosmic-Ray Shielding of Spacecraft with Elements of Systems Engineering Design." Journal of Spacecraft and Rockets 56, no. 5 (2019): 1312–21. http://dx.doi.org/10.2514/1.a34440.

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35

Tittmann, B. "Advanced Processing of Composites." MRS Bulletin 13, no. 4 (1988): 21–27. http://dx.doi.org/10.1557/s0883769400065854.

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The preservation of U.S. aeronautical leadership is an economic and military necessity, but it is by no means assured. The rise of Airbus, Ariane, and Embraer has been lightning fast; tomorrow could see the development of Japan's FSC or Israel's Lavi. Our competitors are well organized and often enjoy the support of their governments. Our capabilities are no longer unique; thus our future work is clearly defined for us.The key to continued U.S. preeminence in aerospace is to be found in the further research, development, and application of a group of revolutionary technologies in the areas of propulsion, numerical and symbolic computation, laminar flow modeling, and advanced materials and structures. Exploitation of the emerging technologies in these areas by industry, government, and universities will significantly impact the performance and cost of future aerospace vehicles and systems. Materials science and engineering, particularly the discipline of nondestructive evaluation, will play a major role in making such continued aerospace leadership a reality.From the use of plastic and glass radomes in the first jet engine demonstrators to the composite parts of today's most advanced aircraft, the need to ensure reliable materials has always been critical. Advanced materials and structural concepts offer the opportunity for significant airframe improvements on all types of aircraft. Indeed tomorrow's aerospace structures, such as the National Aerospace Plane, the Space Station, as well as the ATF and SDI-related items will employ a myriad of exotic materials that must be extremely reliable and highly producible.
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36

Whitmore, Stephen A., and Spencer N. Chandler. "Engineering Model for Self-Pressurizing Saturated-N2O-Propellant Feed Systems." Journal of Propulsion and Power 26, no. 4 (2010): 706–14. http://dx.doi.org/10.2514/1.47131.

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37

Cooper, P. A. "Using Software - Assisted Systems Engineering on Large Satellite Development Contracts." IEEE Aerospace and Electronic Systems Magazine 21, no. 5 (2006): 7–11. http://dx.doi.org/10.1109/maes.2006.1635167.

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38

Jamshidi, M. "System of systems engineering - New challenges for the 21st century." IEEE Aerospace and Electronic Systems Magazine 23, no. 5 (2008): 4–19. http://dx.doi.org/10.1109/maes.2008.4523909.

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39

Jaluria, Yogesh. "Thermal Processing of Materials: From Basic Research to Engineering." Journal of Heat Transfer 125, no. 6 (2003): 957–79. http://dx.doi.org/10.1115/1.1621889.

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This paper reviews the active and growing field of thermal processing of materials, with a particular emphasis on the linking of basic research with engineering aspects. In order to meet the challenges posed by new applications arising in electronics, telecommunications, aerospace, transportation, and other areas, extensive work has been done on the development of new materials and processing techniques in recent years. Among the materials that have seen intense interest and research activity over the last two decades are semiconductor and optical materials, composites, ceramics, biomaterials, advanced polymers, and specialized alloys. New processing techniques have been developed to improve product quality, reduce cost, and control material properties. However, it is necessary to couple research efforts directed at the fundamental mechanisms that govern materials processing with engineering issues that arise in the process, such as system design and optimization, process feasibility, and selection of operating conditions to achieve desired product characteristics. Many traditional and emerging materials processing applications involve thermal transport, which plays a critical role in the determination of the quality and characteristics of the final product and in the operation, control, and design of the system. This review is directed at the heat and mass transfer phenomena underlying a wide variety of materials processing operations, such as optical fiber manufacture, casting, thin film manufacture, and polymer processing, and at the engineering aspects that arise in actual practical systems. The review outlines the basic and applied considerations in thermal materials processing, available solution techniques, and the effect of the transport on the process, the product and the system. The complexities that are inherent in materials processing, such as large material property changes, complicated and multiple regions, combined heat and mass transfer mechanisms, and complex boundary conditions, are discussed. The governing equations for typical processes, along with important parameters, common simplifications and specialized methods employed to study these processes are outlined. The field of thermal materials processing is quite extensive and only a few important techniques employed for materials processing are considered in detail. The effect of heat and mass transfer on the final product, the nature of the basic problems involved, solution strategies, and engineering issues involved in the area are brought out. The current status and future trends are discussed, along with critical research needs in the area. The coupling between the research on the basic aspects of materials processing and the engineering concerns in practical processes and systems is discussed in detail.
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40

Besco, Robert O., and Ken Funk. "Conceptual Design Guidelines to Rediscover Systems Engineering for Automated Flight Decks." International Journal of Aviation Psychology 9, no. 2 (1999): 189–98. http://dx.doi.org/10.1207/s15327108ijap0902_7.

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41

Prösser, Malte, Philip Moore, Xi Chen, Chi-Biu Wong, and Ulrich Schmidt. "A new approach towards systems integration within the mechatronic engineering design process of manufacturing systems." International Journal of Computer Integrated Manufacturing 26, no. 8 (2013): 806–15. http://dx.doi.org/10.1080/0951192x.2013.785026.

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42

Ogunsakin, Rotimi, Cesar A. Marin, and Nikolay Mehandjiev. "Towards engineering manufacturing systems for mass personalisation: a stigmergic approach." International Journal of Computer Integrated Manufacturing 34, no. 4 (2021): 341–69. http://dx.doi.org/10.1080/0951192x.2020.1858508.

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43

Pransky, Joanne. "The Pransky interview: Dr Hod Lipson, Professor at Columbia University; Robotics, AI, Digital Design and Manufacturing Innovator and Entrepreneur." Industrial Robot: the international journal of robotics research and application 46, no. 5 (2019): 568–72. http://dx.doi.org/10.1108/ir-06-2019-0127.

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Purpose This paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD and innovator regarding his personal journey and the commercialization and challenges of bringing a technological invention to market. This paper aims to discuss these issues. Design/methodology/approach The interviewee is Dr Hod Lipson, James and Sally Scapa Professor of Innovation of Mechanical Engineering and Data Science at Columbia University. Lipson’s bio-inspired research led him to co-found four companies. In this interview, Dr Lipson shares some of his personal and business experiences of working in academia and industry. Findings Dr Lipson received his BSc in Mechanical Engineering from the Technion Israel Institute of Technology in 1989. He worked as a software developer and also served for the next five years as a Lieutenant Commander for the Israeli Navy. He then co-founded his first company, Tri-logical Technologies (an Israeli company) in 1994 before pursuing a PhD, which was awarded to him from the Technion Israel Institute of Technology in Mechanical Engineering in the fall of 1998. From 1998 to 2001, he did his postdoc research at Brandeis University, Computer Science Department, while also lecturing at MIT. Dr Lipson served as Professor of Mechanical & Aerospace Engineering and Computing & Information Science at Cornell University for 14 years and joined Columbia University as a Professor in Mechanical Engineering in 2015. From 2013 to 2015, he also served as Editor-in-Chief for the journal 3D Printing and Additive Manufacturing (3DP), published by Mary Ann Liebert Inc. Originality/value Dr Lipson’s broad spectrum and multi-decades of research has focused on self-aware and self-replicating robots. Dr Lipson directs the Creative Machines Lab which pioneers new ways for novel autonomous systems to design and make other machines, based on biological concepts. In total, his lab has graduated over 50 graduate students and over 20 PhD and Postdocs. Some of these students joined Lipson, in cofounding startups, while others went on to found their own companies. Lipson has coauthored over 300 publications that received over 20,000 citations. He has also coauthored the award-winning book Fabricated: The New World of 3D Printing and the book Driverless: Intelligent Cars and the Road Ahead. Forbes magazine named him one of the “World's Most Powerful Data Scientists”. His TED Talk on self-aware machines is one of the most viewed presentations on AI and robotics.
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Dasari, Siva Krishna, Abbas Cheddad, and Petter Andersson. "Predictive modelling to support sensitivity analysis for robust design in aerospace engineering." Structural and Multidisciplinary Optimization 61, no. 5 (2020): 2177–92. http://dx.doi.org/10.1007/s00158-019-02467-5.

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AbstractThe design of aircraft engines involves computationally expensive engineering simulations. One way to solve this problem is the use of response surface models to approximate the high-fidelity time-consuming simulations while reducing computational time. For a robust design, sensitivity analysis based on these models allows for the efficient study of uncertain variables’ effect on system performance. The aim of this study is to support sensitivity analysis for a robust design in aerospace engineering. For this, an approach is presented in which random forests (RF) and multivariate adaptive regression splines (MARS) are explored to handle linear and non-linear response types for response surface modelling. Quantitative experiments are conducted to evaluate the predictive performance of these methods with Turbine Rear Structure (a component of aircraft) case study datasets for response surface modelling. Furthermore, to test these models’ applicability to perform sensitivity analysis, experiments are conducted using mathematical test problems (linear and non-linear functions) and their results are presented. From the experimental investigations, it appears that RF fits better on non-linear functions compared with MARS, whereas MARS fits well on linear functions.
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45

Dougan, MJ, JL Celeiro, and A. Rubio. "Engineering systems to meet the challenge of zero-defect parts." Metal Powder Report 64, no. 10 (2009): 29–33. http://dx.doi.org/10.1016/s0026-0657(10)70025-4.

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46

Koch, Wolfgang. "Towards cognitive tools: Systems engineering aspects for public safety and security." IEEE Aerospace and Electronic Systems Magazine 29, no. 9 (2014): 14–26. http://dx.doi.org/10.1109/maes.2014.130213.

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47

Bilgen, Onur, Lauren M. Butt, Steven R. Day, et al. "A novel unmanned aircraft with solid-state control surfaces: Analysis and flight demonstration." Journal of Intelligent Material Systems and Structures 24, no. 2 (2012): 147–67. http://dx.doi.org/10.1177/1045389x12459592.

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This article presents a completely servo-less, piezoelectric controlled, wind tunnel and flight tested, remotely piloted aircraft that has been developed by the 2010 Virginia Tech Wing Morphing Design Team (a senior design project between the Departments of Mechanical Engineering and Aerospace and Ocean Engineering). A type of piezocomposite actuator, the Macro-Fiber Composite, is used for changing the camber of all control surfaces on the aircraft. The aircraft is analyzed theoretically for its aerodynamic characteristics to aid the design of the piezoelectric control surfaces. A vortex lattice analysis complemented the database of aerodynamic derivatives used to analyze control response. Steady-state roll rates were measured in a wind tunnel and were compared to a similar aircraft with servomotor actuated control surfaces. The theoretical analysis and wind tunnel testing demonstrated the stability and control authority of the concept, culminating in the first flight of the completely Macro-Fiber Composite controlled aircraft on 29 April 2010. An electric motor-driven propulsion system is used to generate thrust, and all systems are powered with a single lithium polymer battery. This vehicle became the first completely Macro-Fiber Composite controlled, flight tested aircraft. It is also known to be the first fully solid-state piezoelectric material controlled, nontethered, flight tested fixed-wing aircraft.
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48

Cardinale, Michael. "Free Space Optical Systems Engineering: Design and Analysis (Stotts, L.B.) [Book Review]." IEEE Aerospace and Electronic Systems Magazine 34, no. 5 (2019): 86–87. http://dx.doi.org/10.1109/maes.2019.2914984.

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49

Celis, Raúl de, Pablo Solano, and Luis Cadarso. "Applying Neural Networks in Aerial Vehicle Guidance to Simplify Navigation Systems." Algorithms 13, no. 12 (2020): 333. http://dx.doi.org/10.3390/a13120333.

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The Guidance, Navigation and Control (GNC) of air and space vehicles has been one of the spearheads of research in the aerospace field in recent times. Using Global Navigation Satellite Systems (GNSS) and inertial navigation systems, accuracy may be detached from range. However, these sensor-based GNC systems may cause significant errors in determining attitude and position. These effects can be ameliorated using additional sensors, independent of cumulative errors. The quadrant photodetector semiactive laser is a good candidate for such a purpose. However, GNC systems’ development and construction costs are high. Reducing costs, while maintaining safety and accuracy standards, is key for development in aerospace engineering. Advanced algorithms for getting such standards while eliminating sensors are cornerstone. The development and application of machine learning techniques to GNC poses an innovative path for reducing complexity and costs. Here, a new nonlinear hybridization algorithm, which is based on neural networks, to estimate the gravity vector is presented. Using a neural network means that once it is trained, the physical-mathematical foundations of flight are not relevant; it is the network that returns dynamics to be fed to the GNC algorithm. The gravity vector, which can be accurately predicted, is used to determine vehicle attitude without calling for gyroscopes. Nonlinear simulations based on real flight dynamics are used to train the neural networks. Then, the approach is tested and simulated together with a GNC system. Monte Carlo analysis is conducted to determine performance when uncertainty arises. Simulation results prove that the performance of the presented approach is robust and precise in a six-degree-of-freedom simulation environment.
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50

Segreto, Tiziana, Alessandra Caggiano, and Doriana M. D'Addona. "Assessment of laser-based reverse engineering systems for tangible cultural heritage conservation." International Journal of Computer Integrated Manufacturing 26, no. 9 (2013): 857–65. http://dx.doi.org/10.1080/0951192x.2013.799781.

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