TAILIEUCHUNG - Ebook Materials selection in mechanical design (2nd edition): Part 2
(BQ) Part 2 book "Materials selection in mechanical design" has contents: Data sources, Case studies - use of data sources, materials, aesthetics and industrial design; forces for change. | Data sources Introduction and synopsis The engineer, in selecting a material for a developing design, needs data for its properties. Engineers are often conservative in their choice, reluctant to consider material with which they are unfamiliar. One reason is this: that data for the old, well-tried materials are reliable, familiar, easily found; data for newer, more exciting, materials may not exist or, if they do, may not inspire confidence. Yet innovation is often made possible by new materials. So it is important to know where to find material data and how far it can be trusted. This chapter gives information about data sources. Chapter 14, which follows, describes case studies which illustrate data retrieval. As a design progresses from concept to detail, the data needs evolve in two ways (Figure ). At the start the need is for low-precision data for all materials and processes, structured to facilitate screening. At the end the need is for accurate data for one or a few of them, but with the richness of detail which assists with the difficult aspects of the selection: corrosion, wear, cost estimation and the like. The data sources which help with the first are inappropriate for the second. The chapter surveys data sources from the perspective of the designer seeking information at each stage of the design process. Long-establisihed materials are well documented; less-common materials may be less so, posing problems of checking and, sometimes, of estimation. The chapter proper ends with a discussion of how this can be done. So much for the text. Half the chapter is contained in the Appendix, Section 13A. It is a catalogue of data sources, with brief commentary. It is intended for reference. When you really need data, this is the section you want. Data needs for design Data breadth versus data precision Data needs evolve as a design develops (Figure ). In the conceptual stage, the designer requires approximate data for the widest possible .
đang nạp các trang xem trước
