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      Mechanical Characterization Using Digital Image Correlation: Advanced Fibrous Composite Laminates

      2 in stock

      Firm sale: non returnable item
      SKU 9783030840396 Categories ,
      In this book, a precise treatment of the experimental characterization of advanced composite materials using Digital Image Correlation (DIC) is presented. The text explains test methods, testing setup with 2D- and stereo-DIC, specimen preparation and patterning, testing analysis and data reduction s...

      £74.99

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      Description

      Product ID:9783030840396
      Product Form:Hardback
      Country of Manufacture:GB
      Title:Mechanical Characterization Using Digital Image Correlation
      Subtitle:Advanced Fibrous Composite Laminates
      Authors:Author: Matthias Merzkirch
      Page Count:295
      Subjects:Ceramic and glass technology, Ceramics & glass technology, Materials science, Testing of materials, Civil engineering, surveying and building, Computer vision, Materials science, Testing of materials, Civil engineering, surveying & building, Computer vision
      Description:In this book, a precise treatment of the experimental characterization of advanced composite materials using Digital Image Correlation (DIC) is presented. The text explains test methods, testing setup with 2D- and stereo-DIC, specimen preparation and patterning, testing analysis and data reduction schemes to determine and to compare mechanical properties, such as modulus, strength and fracture toughness of advanced composite materials. Sensitivity and uncertainty studies on the DIC calculated data and mechanical properties for a detailed engineering-based understanding are covered instead of idealized theories and sugarcoated results. The book provides students, instructors, researchers and engineers in industrial or government institutions, and practitioners working in the field of experimental/applied structural mechanics of materials a myriad of color figures from DIC measurements for better explanation, datasets of material properties serving as  input parametersfor analytical modelling, raw data and computer codes for data reduction, illustrative graphs for teaching purposes, practice exercises with solutions provided online and extensive references to the literature at the end of each stand-alone chapter.
      Imprint Name:Springer Nature Switzerland AG
      Publisher Name:Springer Nature Switzerland AG
      Country of Publication:GB
      Publishing Date:2021-12-15

      Additional information

      Weight686 g
      Dimensions160 × 242 × 23 mm