{"product_id":"computational-modeling-and-digital-twins-with-ai-9798295450389","title":"Computational Modeling and Digital Twins with AI","description":"\u003cp\u003e • Author(s): Ant\u003cbr\u003e • Publisher: Dr. Ant\u003cbr\u003e • Publisher Imprint: Dr. Ant\u003cbr\u003e • BISAC: Artificial Intelligence - Expert Systems\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eComputational Modeling and Digital Twins with AI\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Points: Computational Modeling and Digital Twins with AI\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eDefinition and Evolution of Digital Twins\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCore Characteristics of Digital Twins\u003c\/strong\u003e.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eValue Proposition and Industry Impact\u003c\/strong\u003e\u003cul\u003e\n\u003cli\u003eEnhanced monitoring, predictive maintenance, and performance optimization.\u003c\/li\u003e\n\u003cli\u003eAccelerated design cycles and improved decision-making.\u003c\/li\u003e\n\u003cli\u003eTangible cost savings, increased efficiency, and sustainability benefits across sectors like aerospace, automotive, manufacturing, energy, healthcare, construction, logistics, and agriculture.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel Fidelity and Abstraction\u003c\/strong\u003e\u003cul\u003e\n\u003cli\u003eFidelity refers to how accurately the digital twin mirrors its physical counterpart, across geometric, behavioral, state, contextual, and data dimensions.\u003c\/li\u003e\n\u003cli\u003eThe level of abstraction and granularity is purpose-driven, balancing detail with computational feasibility.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePhysics-Based and Data-Driven Modeling\u003c\/strong\u003e\u003cul\u003e\n\u003cli\u003ePhysics-based models use fundamental laws (e.g., conservation, constitutive relations) for deterministic, interpretable predictions.\u003c\/li\u003e\n\u003cli\u003eData-driven models leverage empirical data and machine learning to capture complex, real-world behaviors.\u003c\/li\u003e\n\u003cli\u003eHybrid modeling combines both approaches for greater accuracy and adaptability.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePhysics-Informed Machine Learning (PIML)\u003c\/strong\u003e\u003cul\u003e\u003cli\u003ePIML integrates physical laws into machine learning models, improving generalization, reducing data requirements, and ensuring physically plausible predictions.\u003c\/li\u003e\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eUsed for complex simulations in fluid dynamics, structural mechanics, and materials science. \u003c\/p\u003e","brand":"Dr. Ant","offers":[{"title":"Paperback","offer_id":46862055145623,"sku":"9798295450389","price":2422.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798295450389.webp?v=1769964566","url":"https:\/\/atlanticbooks.com\/products\/computational-modeling-and-digital-twins-with-ai-9798295450389","provider":"Atlantic Books","version":"1.0","type":"link"}