{"product_id":"scientific-machine-learning-with-engineering-applications","title":"Scientific Machine Learning with Engineering Applications","description":"\u003cdiv id=\"bookDescription_feature_div\" class=\"celwidget\" data-feature-name=\"bookDescription\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"bookDescription\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-asin=\"0993745598\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"7y9w7h-rgk3d4-2xixgp-6jetc1\" data-cel-widget=\"bookDescription_feature_div\"\u003e\n\u003cdiv data-a-expander-name=\"book_description_expander\" data-a-expander-collapsed-height=\"280\" class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\"\u003e\n\u003cdiv aria-expanded=\"false\" class=\"a-expander-content a-expander-partial-collapse-content\"\u003e\n\u003cdiv data-cel-widget=\"bookDescription_feature_div\" data-csa-c-id=\"gxtlx9-xq8p2r-kr731a-lnhwca\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-asin=\"1032660937\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-content-id=\"bookDescription\" data-csa-c-type=\"widget\" data-feature-name=\"bookDescription\" class=\"celwidget\" id=\"bookDescription_feature_div\"\u003e\n\u003cdiv class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\" data-a-expander-collapsed-height=\"280\" data-a-expander-name=\"book_description_expander\"\u003e\n\u003cdiv class=\"a-expander-content a-expander-partial-collapse-content\" data-expanded=\"false\"\u003e\n\u003cul\u003e\u003c\/ul\u003e\n\u003cdiv id=\"bookDescription_feature_div\" class=\"celwidget\" data-feature-name=\"bookDescription\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"bookDescription\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-asin=\"3030051196\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"ebcfnd-phb9rj-wa05hj-5sqrnc\" data-cel-widget=\"bookDescription_feature_div\"\u003e\n\u003cdiv data-a-expander-name=\"book_description_expander\" data-a-expander-collapsed-height=\"280\" class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\"\u003e\n\u003cdiv data-expanded=\"false\" class=\"a-expander-content a-expander-partial-collapse-content\"\u003e\n\u003cspan\u003e\u003c!--StartFragment --\u003e\u003c\/span\u003e\n\u003cp\u003eThis book equips readers with a rigorous and practical framework for solving complex engineering problems directly from governing equations using modern machine learning techniques. It bridges established principles from mechanics, numerical analysis, and scientific computing with emerging physics-based learning approaches, enabling reliable modeling, simulation, optimization, and inverse analysis beyond purely data-driven methods. A distinctive feature is its critical comparison of machine learning-based solvers with classical techniques such as the finite element method, isogeometric analysis, and meshfree methods, highlighting strengths, limitations, and domains of applicability. The scope ranges from foundational concepts to advanced engineering applications, supported by worked examples, reproducible code, and extensive references. The book is intended for graduate students, researchers, and practitioners in engineering, applied mathematics, and computational sciences who seek a principled entry point and a state-of-the-art reference for physics-based machine learning in modeling and simulation.\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable of contents (7 chapters)\u003c\/strong\u003e\u003cbr\u003eFront Matter\u003cbr\u003ePages i-xi\u003cbr\u003eIntroduction\u003cbr\u003ePages 1-5\u003cbr\u003eMachine Learning Concepts\u003cbr\u003ePages 7-52\u003cbr\u003ePartial Differential Equations in Engineering\u003cbr\u003ePages 53-103\u003cbr\u003eMachine Learning Based Solutions of PDEs\u003cbr\u003ePages 105-160\u003cbr\u003eSurrogate Models Based on Machine Learning\u003cbr\u003ePages 161-191\u003cbr\u003eNeural Operators\u003cbr\u003ePages 193-224\u003cbr\u003eConclusions and Future Directions\u003cbr\u003ePages 225-232\u003cbr\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"celwidget aplus-module module-12 aplus-standard\" data-cel-widget=\"aplus-module-12\" data-csa-c-id=\"e48qwb-36wm3s-vb6e8j-pnxs9b\"\u003e\n\u003cdiv class=\"aplus-module-wrapper apm-spacing apm-floatnone apm-fixed-width\"\u003e\n\u003cdiv class=\"apm-sidemodule aplus-module-content\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-base\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cb\u003eBOOKREAD™ 5-STEP SATISFACTION GUARANTEE\u003c\/b\u003e\u003c\/strong\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003e1. No Risk, 30-Day Money-Back Guarantee. \u003cbr\u003e2. instant download. No surprises or hidden fees.\u003cbr\u003e3. Safe Payments via Credit\/Debit Card or PayPal® \u003cbr\u003e4. McAfee™ and SSL secured shopping cart.\u003cbr\u003e5. lifetime customer support.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e","brand":"My Store","offers":[{"title":"PDF","offer_id":57446857048395,"sku":null,"price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1031\/1204\/8971\/files\/61ma1yKZgUL._SL1246.jpg?v=1779834525","url":"https:\/\/bookread.io\/products\/scientific-machine-learning-with-engineering-applications","provider":"bookread","version":"1.0","type":"link"}