The book is structured to simplify complex engineering concepts into a summarized form. It is primarily intended to support students who have already completed foundational courses in thermodynamics and fluid mechanics. Key features include:
| | Description | |--------|-----------------| | FR‑1 | PDF Rendering – Use PDF.js to display the original PDF at native resolution, with optional “night mode”. | | FR‑2 | Search Engine – Index the PDF text and embedded LaTeX/MathML via ElasticSearch (or MeiliSearch ) with custom analyzers for symbols. | | FR‑3 | Equation Extraction – Run pdf2image + Mathpix OCR on each page to capture LaTeX strings; store them in a relational table linked to page numbers. | | FR‑4 | AI Summarizer – Call OpenAI GPT‑4o (or a locally hosted LLaMA 2 70B) with a prompt: “Summarize the following 2‑page excerpt from Fluid Machinery in ≤ 5 bullet points.” | | FR‑5 | Quiz Generator – Prompt‑template to LLM: “Create 5 multiple‑choice questions on the key concepts of Chapter X with one correct answer and a short explanation.” | | FR‑6 | Annotation Layer – Store user notes, highlights, and free‑hand drawings in a PostgreSQL table keyed by user_id , pdf_id , page_number . Use Fabric.js for drawing. | | FR‑7 | 3‑D Visualiser – Convert vector figures (SVG/AI) to glTF using svg2gltf ; render with three.js . Provide explode‑view controls. | | FR‑8 | Export Service – Assemble selected content (notes, summary, quiz) into a PDF via WeasyPrint or pdfkit ; also offer Markdown/Word export. | | FR‑9 | Authentication & Permissions – OAuth2 (Google/Institution) + role‑based access (private vs. public annotations). | | FR‑10 | Responsive UI – All features must work on desktop (≥1024 px) and tablets; mobile view hides heavy 3‑D visualisation. | Fluid Machinery By Jose Francisco Pdf
While physical copies were published by entities like , digital previews and lesson summaries are often available on academic sharing platforms: The book is structured to simplify complex engineering
@app.post("/summary") def summary(pages: dict = Body(...)): text = pages["text"] prompt = f"Summarize the following text from *Fluid Machinery* in ≤ 5 bullet points.\n\nText:\ntext" return "summary": call_llm(prompt) | | FR‑2 | Search Engine – Index
The guidebook is structured into seven distinct lessons that bridge fundamental fluid mechanics with the operational mechanics of specific machines: Fluid Machinery IM#3 | PDF - Scribd