KAILA

The Flight Simulator for broadcast engineers.

_{UHF television transmitter training simulator · technical reference · public preview}

Technical brief (HTML) · Vision · Brand notes · Figures

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1. General data

Item	Value
System type	Dual-mode UHF TV transmitter plant training simulator
Product name	Kaila
Presentation client	Unreal Engine 5.8
Simulation authority	Python (local process)
Modes	Analog (NTSC/PAL-class) · Digital (8VSB / ATSC-class)
IPC	Schema-versioned control / telemetry bus (local)
GPU role	Optional acceleration (PIC beam, coverage, spectacle kernels)
Accuracy class	Training-plausible · not lab metrology · not on-air control
Author	David Lombardo (coldbricks)
Public status	Coming soon — this repository is the public technical surface
License	MIT

WARNING. Training digital twin only. Do not connect to operational transmitter plant control. Do not treat meters, coverage, or station stubs as certified measurements.

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2. System description

Kaila is an end-to-end training system for UHF television transmitter facilities. The operator enters a facility representation, occupies the control position, and exercises plant procedures under a live physics model.

The system is split for correctness:

Layer	Responsibility
Unreal Engine 5.8	World, console, HUD, instruments presentation, operator presence
Python	RF chains, amplifier models, instruments math, scenarios, GPU kernels
Control bus	Controls downstream · telemetry upstream · versioned schema
Data	Station / site YAML stubs · DEM terrain · training scenarios

RF math is not reimplemented in Blueprints. The presentation client consumes authority state.

Unreal (presentation)
        │  controls / telemetry
        ▼
Python (physics authority)
        │
        ├── analog chain
        ├── digital chain
        ├── amplifier models (tube-class / solid-state stubs)
        ├── instruments (meters, spectrum, constellation)
        └── GPU kernels (PIC, coverage, spectacle) [optional]

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3. Operating modes

Mode	Plant behavior (training model)
Analog	Baseband → RF chain · tube-class amplifier discipline · filament / HV / drive procedure space
Digital	8VSB / ATSC-class chain · solid-state PA stubs · MER / constellation instrumentation
Site set	Multi-tower mountain farm + supporting sites (public-data parameterization)
Terrain	DEM-driven ridgeline coverage and multipath visualization

Station parameters are training stubs derived from public filings. Operational use requires verification against primary sources and facility documentation.

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4. Figures

Figure 11 — Helderberg night ridge (animated)

_{Fig. 11 — Helderberg escarpment at night · staggered obstruction beacons · city glow on the horizon}

Figure 12 — Tower farm beacons (animated)

_{Fig. 12 — Night tower farm close-in · red L-864-class flash bloom · light shafts}

Figure 1 — System overview (animated)

_{Fig. 1 — Plant spectacle chain: beam · multipath · coverage · instruments · site}

Figure 2 — PIC beam cutaway (animated)

_{Fig. 2 — Electron-beam PIC cutaway (live bunching path)}

Figure 3 — Instrument panel (animated)

_{Fig. 3 — Operator instruments: spectrum, meters, digital quality glass}

Figure 4 — Mission control (animated)

_{Fig. 4 — Aggregate plant / coverage dashboard}

Figure 5 — Live bunching (animated)

_{Fig. 5 — Live electron bunching cutaway (GPU PIC path)}

Figure 6 — Particle stream (animated)

_{Fig. 6 — Particle-stream beam spectacle}

Figure 7 — Coverage map (animated)

_{Fig. 7 — Terrain coverage visualization}

Figure 8 — Tower site (animated)

_{Fig. 8 — Mountain tower farm site presentation}

Figure 9 — Control room (animated)

_{Fig. 9 — Control room / console environment}

Figure 10 — Multipath field (animated)

_{Fig. 10 — Multipath ray field over terrain}

Source stills and alternate encodings: assets/.

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5. Operator sequence (target public build)

Step	Action	Expected training outcome
1	Boot plant (analog or digital path)	Stable authority process + client telemetry
2	Apply startup procedure	Safe warm-up / chain enable discipline
3	Adjust drive / tune / load parameters	Meter and spectrum response
4	Observe VSWR / reflection behavior	Fault recognition under load scenarios
5	Switch or compare modes	Analog ↔ digital plant literacy
6	Run scenario pack	Repeatable drills (startup, ice/VSWR, arc recovery, multi-tower balance)

Scenario definitions ship as data files in the private tree; public packaging is pending.

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6. Architecture constraints

Constraint	Rule
Authority	Python owns plant state
Presentation	Unreal renders; does not invent RF math
Schema	Versioned controls and telemetry
Hardware link	Local training only — no on-air plant interface
Accuracy language	Training-plausible; not certified

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7. Release status

Track	State
Physics core	Implemented (private)
UE 5.8 client	Implemented (private)
GPU PIC / spectacle path	Implemented (private; hardware-dependent)
This public repository	Coming-soon surface (manual, figures, brand)
Public source / demo build	Not yet published

Star and watch coldbricks/kaila for release signals.

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8. Honesty bar

Claim	Status
Training twin	Yes
Lab-certified metrology	No
On-air / remote transmitter control	No
Public-data station stubs	Yes (verify before operational use)
Facility-exact twin of a specific rack	No

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9. Legal

Copyright © 2026 David Lombardo (coldbricks) and contributors.
License: MIT.

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Kaila — The Flight Simulator for broadcast engineers.
_{Created by David Lombardo · Coming soon.}