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Home Stochastic Finite Element Modeling in Electronic Packaging - Hardcover
Stochastic Finite Element Modeling in Electronic Packaging
  • Books,
  • Electronic Materials,
  • Materials Science,
  • Mathematics,
  • Probability & Statistics,
  • Stochastic Processes,
  • Technology & Engineering,

Stochastic Finite Element Modeling in Electronic Packaging - Hardcover

Original price $171.74 - Original price $171.74
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$171.74
$171.74 - $171.74
Current price $171.74
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Availability: In Stock
SKU 9781394352944
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by Liu Chu (Author)

An expert integration of digital twin technology and advanced simulation methods for the design and optimization of electronic packaging systems

In Stochastic Finite Element Modeling in Electronic Packaging, distinguished researcher Liu Chu delivers an expert discussion of the latest advanced numerical methods and modeling techniques specific to electronic packaging. The book supplements its explanations with original MATLAB and ANSYS (APDL) code that can be applied immediately. It also includes robust examples that draw on a comprehensive description of the mechanics of electronic packaging modeling.

Chu explains the fundamentals of modeling logic and concepts in an accessible way that is ideal for beginners to the topic. She demonstrates practical guides and benchmarks that will assist readers in the testing, measurement, and modeling of their own materials.

Readers will also find:

  • A thorough introduction to a modeling approach that focuses on digital twins and big data applications, including Monte Carlo Sampling
  • Comprehensive explorations of benchmarks, testing, measurement, and modeling
  • Practical discussions of theoretical finite element models in electronic packaging
  • Complete treatments of the fundamentals of modeling logic and concepts

Perfect for undergraduate and graduate students in electrical engineering and computer science, Stochastic Finite Element Modeling in Electronic Packaging will also benefit practicing electronic design engineers and academic researchers with an interest in electronic packaging and materials science.

Back Jacket

An expert integration of digital twin technology and advanced simulation methods for the design and optimization of electronic packaging systems

In Stochastic Finite Element Modeling in Electronic Packaging, distinguished researcher Liu Chu delivers an expert discussion of the latest advanced numerical methods and modeling techniques specific to electronic packaging. The book supplements its explanations with original MATLAB and ANSYS (APDL) code that can be applied immediately. It also includes robust examples that draw on a comprehensive description of the mechanics of electronic packaging modeling.

Chu explains the fundamentals of modeling logic and concepts in an accessible way that is ideal for beginners to the topic. She demonstrates practical guides and benchmarks that will assist readers in the testing, measurement, and modeling of their own materials.

Readers will also find:

  • A thorough introduction to a modeling approach that focuses on digital twins and big data applications, including Monte Carlo Sampling
  • Comprehensive explorations of benchmarks, testing, measurement, and modeling
  • Practical discussions of theoretical finite element models in electronic packaging
  • Complete treatments of the fundamentals of modeling logic and concepts

Perfect for undergraduate and graduate students in electrical engineering and computer science, Stochastic Finite Element Modeling in Electronic Packaging will also benefit practicing electronic design engineers and academic researchers with an interest in electronic packaging and materials science.

Author Biography

Liu Chu, PhD, is an Associate Professor, School of Electronic and Information Engineering, Tongji University. Her research is primarily focused on uncertainty quantification in stochastic defects, numerical simulations for electronic packaging, and the development of advanced computational mechanics methods.

Number of Pages: 288
Dimensions: 0.69 x 9 x 6 IN
Publication Date: February 10, 2026

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