Uncertainty quantification and model calibration / edited by Jan Peter Hessling.

Format:

Book

Author/Creator:

Jan Peter Hessling

Contributor:

Hessling, Jan Peter, editor.

Language:

English

Subjects (All):

Mathematical models.

Engineering mathematics.

Physical Description:

1 online resource (226 pages)

Place of Publication:

IntechOpen 2017

[Place of publication not identified] : IntechOpen, [2017]

Language Note:

English

Summary:

Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.

Notes:

Description based on print version record.

ISBN:

9789535147541

9535147544

9789535132806

9535132806