FIELDMIND LABCOMPUTATIONAL R&DRU

PUBLIC EVIDENCE DOSSIER

P1Propulsion2025

Numerical proof-of-concept

P1: Propulsion Autopilot in a Driven–Dissipative Field

A self-tuning controller coordinates frequency, phase, and PWM duty in a lossy wave/jet chamber model to maximise phase locking and useful through-flow.

Read the dossierOpen publication record OPEN INTERACTIVE INSTRUMENT

Normalized educational approximation; not a reproduction of the published experiment.

P1
EVIDENCE MODE
Numerical study
SCOPE
CLAIM-BOUNDED
Publication
Public publication · DOI
01QUESTION

Research question

Can a closed-loop controller find and retain a robust operating basin while detecting drift and recovering from degraded states?

02MODEL

MODEL SCOPE

Public model description

A normalized driven–dissipative wave/jet chamber model is coupled to a controller that updates frequency, phase, and PWM duty from phase-locking and through-flow observables.

03EXPERIMENT

PROTOCOL

Declared evidence chain

Nine stages progress from power-balance baselines and basin scans to closed-loop tuning, validation tails, CUSUM drift detection, warm-start recovery, rollback, and panic safeguards.

Series: P1.1–P1.9 · ω/φ/d control · drift · recovery · safety

  • P1.1–P1.9
  • ω/φ/d control
  • drift
  • recovery
  • safety

The labels below preserve the public protocol identity. They are an index to the publication, not a substitute for its full methods or an open reproducibility bundle.

04RESULT

EVIDENCE

Results inside the model

9Control stages
ω / φ / dTuned control axes
CUSUMDrift diagnostic

INTERACTIVE MODEL LENS

Lock-and-flow control lens

A driven–dissipative chamber view of basin scanning, closed-loop ω/φ/d control, validation tails, drift detection, and rollback.

NORMALIZED EXPLANATORY VIEW
Active stateClosed-loop lock

Frequency, phase, and duty coordinate inside the accepted model basin.

Geometry, intensity, timing, and motion in this lens are normalized explanatory encodings. They are not experimental measurements. Published aggregates remain in the evidence signals and source figure.
  1. The report maps candidate locking/through-flow basins before enabling control.
  2. Validation tails and rollback constrain acceptance of online parameter updates.
  3. CUSUM and the statebook provide model-level drift detection and recovery in the resilient mode.
05CLAIM BOUNDARY

BOUNDARY

CLAIM BOUNDARY

  1. 01
    Declared numerical protocol

    P1.1–P1.9 · ω/φ/d control · drift · recovery · safety

  2. 02
    Supported model-level finding

    The report maps candidate locking/through-flow basins before enabling control.

  3. Claim boundary
  4. 03
    Requires a separate validation chain

    This is a controller study in a normalized driven–dissipative field. It does not establish net thrust, propulsive efficiency, a working engine, or compliance with conservation and full fluid/plasma physics in hardware.

Numerical evidence is not physical validation. Transfer to a material, device, organism, environment, or operational service requires a separate validation chain whenever such a transfer is relevant.

06PUBLICATION

Publication record

Author
Nikita Teslia
Programme
Propulsion
Claim type
Numerical proof-of-concept
Year
2025
Dossier review
Series
P1.1–P1.9 · ω/φ/d control · drift · recovery · safety
License
CC BY-NC-ND 4.0
DOI
10.5281/zenodo.17340108

Citation

Teslia, N. (2025). P1: Propulsion Autopilot in a Driven–Dissipative Field. Zenodo. https://doi.org/10.5281/zenodo.17340108Open publication record

The DOI is the canonical external record. The site condenses the public publication and does not replace it.

PROGRAMME TOPOLOGY

Research lineage

Lineage records publication sequence and explicit revision or supersession links. It does not assert empirical causation or an otherwise unverified cross-branch dependence.

Predecessors

No predecessor is asserted in the current research graph.

P1Propulsion
Successors

No published successor is encoded in the current research graph.

FIELDSTABLE