{"product_id":"the-second-order-adjoint-sensitivity-analysis-methodology-advances-in-applied-mathematics","title":"The Second-Order Adjoint Sensitivity Analysis Methodology (Advances in Applied Mathematics)","description":"\u003ch3\u003e\u003cstrong\u003eBook Details\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: CRC Press\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u003c\/strong\u003e: Dan Gabriel Cacuci\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eLanguage\u003c\/strong\u003e: English\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eISBN\u003c\/strong\u003e: 9781498726481\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003ePages\u003c\/strong\u003e: 306\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eCover\u003c\/strong\u003e: Hardcover\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDimensions\u003c\/strong\u003e: 9.4 x 6.3 x 0.9 inches\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003chr\u003e\n\u003ch3\u003e\u003cstrong\u003eAbout the Book\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp\u003e\u003cem\u003eThe Second-Order Adjoint Sensitivity Analysis Methodology\u003c\/em\u003e offers a comprehensive generalization of the First-Order Theory, building on the author’s previous works published by CRC Press. This breakthrough methodology holds numerous applications in sensitivity and uncertainty analysis, optimization, data assimilation, model calibration, and reducing uncertainties in model predictions.\u003c\/p\u003e\n\u003cp\u003eThe book provides an in-depth treatment of the second-order adjoint sensitivity analysis, with numerous illustrative examples to help readers grasp the complexity of the subject. It is aimed at a wide range of audiences, from graduate students to advanced researchers, and is designed to serve as a primary reference in high-order sensitivity and uncertainty analysis.\u003c\/p\u003e\n\u003cp\u003eKey Highlights:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eComprehensive Coverage\u003c\/strong\u003e: Applicable to a wide range of fields, particularly those involving numerical modeling, optimization, and the quantification of sensitivities in direct and inverse problems under uncertainty.\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003ePractical Applications\u003c\/strong\u003e: This book helps readers apply the methodology to real-world problems in their own fields, with illustrative examples that clarify complex concepts.\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eAdvanced Reference\u003c\/strong\u003e: Serves as a critical resource for anyone working with uncertainty quantification and sensitivity analysis in scientific and engineering disciplines.\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eDan Gabriel Cacuci, a highly esteemed academic and researcher, has dedicated his career to advancing the field of sensitivity analysis. He is a professor at the University of South Carolina, holding the South Carolina SmartState Endowed Chair, and is the Director of the Center for Nuclear Science and Energy. His extensive academic background and numerous awards make this work a crucial resource for researchers in applied physics, mechanical engineering, and nuclear engineering.\u003c\/p\u003e","brand":"CRC Press","offers":[{"title":"Default Title","offer_id":49948628091184,"sku":"Sarat_9781498726481","price":10643.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0690\/9968\/4144\/files\/crc-press-book-default-title-the-second-order-adjoint-sensitivity-analysis-methodology-advances-in-applied-mathematics-41313748615472.jpg?v=1775949641","url":"https:\/\/www.retailmaharaj.com\/products\/the-second-order-adjoint-sensitivity-analysis-methodology-advances-in-applied-mathematics","provider":"Retail Maharaj","version":"1.0","type":"link"}