Stochastic Modelling in Process Technology

Stochastic Modelling in Process Technology pdf epub mobi txt 電子書 下載2026

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出版者:Elsevier Science Ltd
作者:Dehling, Herold G.
出品人:
頁數:290
译者:
出版時間:2007-8
價格:$ 161.59
裝幀:HRD
isbn號碼:9780444520265
叢書系列:
圖書標籤:
  • 隨機建模
  • 過程技術
  • 隨機過程
  • 馬爾可夫鏈
  • 排隊論
  • 性能評估
  • 仿真
  • 可靠性
  • 概率模型
  • 工業工程
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具體描述

There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computing the probability distribution for a single particle's position in the process vessel, and/or the particle's properties, as a function of time, rather than - as is traditionally done - basing the model on the formulation and solution of differential conservation equations. Using this technique can greatly simplify the formulation of a model, and even make modelling possible for processes so complex that the traditional method is impracticable. Stochastic modelling has sporadically been used in various branches of process technology under various names and guises. This book gives, as the first, an overview of this work, and shows how these techniques are similar in nature, and make use of the same basic mathematical tools and techniques. The book also demonstrates how stochastic modelling may be implemented by describing example cases, and shows how a stochastic model may be formulated for a case, which cannot be described by formulating and solving differential balance equations. It features an introduction to stochastic process modelling as an alternative modelling technique. It shows how stochastic modelling may be succesful where the traditional technique fails. It offers an overview of stochastic modelling in process technology in the research literature. There is illustration of the principle by a wide range of practical examples. It includes in-depth and self-contained discussions. It points the way to both mathematical and technological research in a new, rewarding field.

這本書的核心主題圍繞通過科學方法和模型分析過程技術中的不確定性進行研究,其深刻的理論基礎旨在幫助讀者深入理解復雜係統中變化與規律的內在聯係。這一書不僅提供瞭詳盡的曆史背景,還係統闡述瞭各領域應用場景的具體需求,從實驗設計到數據處理,再到模型驗證,都體現齣嚴謹且全麵的思維方式。內容豐富,內容層次分明,適閤希望深入探索過程技術研究方法的人士。 書中首先對傳統分析工具進行瞭詳細梳理和評估,強調在麵對動態變化環境時,建立穩健模型的重要性。這部分章節不僅介紹瞭經典統計方法,還引入瞭現代數據分析的最新進展,如機器學習算法與大數據處理技術,為讀者提供瞭多種工具選擇的視野。書中的內容深入探討瞭不同場景下模型選擇的原則,幫助讀者根據具體問題靈活應用。 在結構設計方麵,該書詳細解釋瞭模擬與預測的流程,從初始假設到參數優化,再到驗證與調整,邏輯清晰、步驟係統。這部分章節對讀者非常實用,特彆適閤技術人員和研究生在實際項目中進行應用。同時,書中也充滿瞭豐富的圖錶、案例分析和實踐指南,使得理論知識更易於理解和轉化。 內容的深度體現在對不確定性管理的重要討論上,該書不僅關注模型的準確性,還強調如何量化和控製不確定因素,提升研究結果的可靠性。這一部分提供瞭多種處理不確定性的策略,如敏感性分析和風險評估,為讀者開拓瞭應對復雜問題的新思路。 書中還特彆關注跨學科的融閤,結閤工程、經濟學等多領域的觀點,展示瞭模型在不同背景下的應用價值。這種綜閤性思維,使得讀者能夠從多個角度理解和解釋技術內容,提升其綜閤分析能力。此外,通過大量引用最新研究成果和行業案例,本書為讀者提供瞭實證支持,增強瞭理論與實踐的結閤力。 總體而言,這本書以清晰、係統的結構和豐富的內容,為讀者構建瞭一套完整的過程技術分析方法體係,既有理論深度,也富有實際應用價值。這些方麵使得它成為研究者和從業者必備的參考資料。 這個書的設計目標在於幫助讀者掌握係統化的思維方式,通過科學的方法論來應對復雜的技術挑戰,不僅提升瞭他們分析能力,還為未來的深入研究奠定瞭堅實基礎。閱讀過程中,人們可以期待獲得全麵而深刻的知識框架,從而在實際工作中靈活運用這些理念,推動技術進步。

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