Composable Twins¶
This outline is signed before any prose is generated. Text up here is the preamble: it belongs to no heading, is never handed to a generator, and exists for whoever opens the file next. Audience: practising engineers who have built one twin and are now asked for five.
- author: Prasad Talasila
Front matter¶
Preface¶
Why this book exists and who it is for. You write this page yourself.
Part I: Foundations¶
What a twin is, and is not¶
Establish the vocabulary the rest of the book leans on, and settle the twin/shadow distinction early -- later chapters assume it. Must not drift into architecture; that is Part II's job.
The model half¶
What the model must reproduce, and the fidelity question stated but not
answered. The answer is ch-fidelity.
The data half¶
Synchronisation, sampling and staleness, as vocabulary only.
What a twin costs¶
The honest chapter. Build cost, maintenance cost, and the cost of a twin
nobody trusts. Leans on ch-what's vocabulary and nothing else.
What you pay to build one¶
What you pay to keep one¶
Part II: Building one¶
Choosing fidelity¶
Answers the question sec-model raised. This is the book's technical
core and the chapter most likely to need two passes.
Fidelity against a decision¶
The chapter's central claim: fidelity is chosen against the decision the twin supports, never maximised in the abstract.
When more fidelity makes things worse¶
The deadline argument. A more faithful model that misses its update window is worse than a coarse one that does not.
Keeping it in step¶
Staleness, dropped links, and what an operator should see when the twin
is behind. Cross-references sec-data for the vocabulary it does not
re-introduce.
Staleness, and how to show it¶
When the link drops¶
Part III: Living with one¶
Trust and what earns it¶
Why an operator ignores a twin that has been wrong once, and what the
literature says about rebuilding that. Leans on ch-cost's "cost of a
twin nobody trusts" and pays it off.
Where this goes next¶
Short. Open problems, with the validation gap named as the largest. No new vocabulary.