Technological Concepts and Mathematical Models in the Evolution of Modern Engineering Systems: Controlling - Managing - Organizing

ISBN-13: 9783764369408 / Angielski / Twarda / 2003 / 268 str.

Mario Lucertini; Ana Millan Gasca; Fernando Nicolo

Opis

M. LUCERTINI, A. MILLAN GASCA, AND F. NICOLO 1 Technology as Knowledge: The Case of Modern Engineering Systems In recent years scholars coming from the fields of history and philosophy of sci ence and technology have devoted much attention to the problem of "technology as knowledge" and to the emergence of an autonomous engineering science in the Industrial Agel. This interest echoes a growing awareness among engineers of the independence of their conceptual approach with respect to other forms of knowl edge, linked to the consolidation of autonomous academic engineering research in th the 20 century. A careful examination of the nature of technological knowledge appears particularly valuable in view of the pervasive presence of technology in contemporary life and culture, not only as a result of its impressive achievements, but through the less obvious influence of its concepts and viewpoints as well. The activity of engineers and technicians has been traditionally based on the practical ability to cope with specific situations and to attain the corresponding specific goal by means of the design and realization of an artifact or structure, on the basis of past experience handed down by tradition and applied by means of trial-and-error and rule-of-thumb procedures. But the existence of a theoreti cal background and of principles underpinning this activity can be traced back to classical antiquity."

Spis treści

I Mathematical Methods and Technological Thought: Historical Aspects.- 1 Mathematical Methods in Preindustrial Technology and Machines.- 1.1 Renaissance Architects-Engineers.- 1.2 Steps Towards Scientific Technology and Technical Mechanics.- 1.3 The Achievements of Leonardo da Vinci.- 1.4 Engineers of the 16th century.- 2 Organization and Mathematics: A Look into the Prehistory of Industrial Engineering Ana Millön Gasca.- 2.1 A New Branch of Engineering Science.- 2.2 Quantitative Studies and Labour and Production Organization: The Early Attempts between the 18th and 19th Centuries.- 2.3 Rationality and Mathematization.- 2.4 Measurement Mathematical and Techniques:The Birth of Industrial Engineering.- 2.5 A Fresh Start: The Birth of Operations Research.- 3 Technological Innovation and New Mathematics: van der Pol and the Birth of Nonlinear Dynamics.- 3.1 Radio Waves and Mathematical Modeling.- 3.2 From Radio to Limit Cycles.- 3.3 The Contribution of the Soviet School.- 3.4 The Heartbeat “Model”.- 3.5 Concluding Remarks.- Appendix: Two Unpublished Letters Written by Balthasar van der Pol to Vito Volterra.- 4 Trasferring Formal and Mathematical Tools from War Management to Political, Technological, and Social Intervention (1940-1960).- 4.1 Operational Research and Mathematicians’ Mobilization in World War II.- 4.2 Mathematical Tools for Managing Social and/or Complex Systems.- 4.3 An Emblematic Site for the Deployment of these Tools: The RAND Corporation.- 4.4 On a Few Characters of these New Scientific Modes.- 4.5 Three Short Remarks as Way of Conclusion.- II Technological Knowledge and Mathematical Models in the Analysis, Planning, and Control of Modern Engineering Systems.- 5 Technological Concepts and Mathematical Models in the Evolution of Control Engineering.- 5.1 Regulators and Servomechanism.- 5.2 Models in Control Engineering.- 5.3 Model Representations.- 5.4 Determination of Stability of a System.- 5.5 External Models: Impulse and Frequency Response.- 5.6 Stochastic and Sampled-Data Signals.- 5.7 State Space Models and Optimal Control.- 5.8 System Identification.- 5.9 Conclusion.- 6 Feedback: A Technique and a “Tool for Thought”.- 6.1 Basic Elements of a Feedback Control System.- 6.2 Feedback Models of Some Technological Systems: Were their Inventors Aware of Such a Structure?.- 6.3 Feedback Loops in Mathematics and Computer Science.- 6.4 The Role of Feedback in Explanatory Models.- 6.5 Concluding Remarks.- 7 Adequacy of Mathematical Models in Control Theory, Physics, and Environmental Science.- 7.1 Mathematical Models of Technological Processes.- 7.2 Mathematical Modeling of Environmental Processes: Fluctuations in the Level of the Caspian Sea.- 7.3 Mathematical Simulation in the Civil Engineering Design of the Leningrad Dam.- 7.4 Mathematical Simulation of Physical Processes.- 8 The Development of Systems Science: Concepts of Knowledge as Seen from the Western and Eastern Perspective.- 8.1 Historical Perspective: Hard versus Soft Systems Science.- 8.2 Information Civilization: Megatrends and Challenges.- 8.3 Diverse Concepts of Knowledge.- 8.4 The Importance and Typical Forms of Mathematical Models Expressing Knowledge.- 8.5 An Example: Computerized Decision Support Systems.- 9 Coping With Complexity in the Management of Organized Systems.- 9.1 Forms of Complexity.- 9.2 The Forms of Simplification.- 9.3 Decentralized Management of Complex Organizations.- 9.4 Open Systems.- Index of Names.- Authors.