File size: 8,899 Bytes
8305fd4 ae75a67 0a63c8c 8305fd4 aba3252 1d6869b 8305fd4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 | ---
license: other
license_name: other
license_link: LICENSE
viewer: false
task_categories:
- summarization
- text-generation
language:
- en
tags:
- physics
- electromagnetism
- simulation
- finite-difference
- conductive-media
- signal-processing
- computational-physics
- time-series
- tabular-data
- engineering
- education
- reproducible-research
- physics
- electromagnetism
- finite-difference
- simulation
- conductive-media
- time-series
- computational-physics
- reproducible-research
---
# Telegraphing Without Wires (1884) — Finite-Difference Simulator and Synthetic Dataset Reconstruction
Original manuscript: [Telegraphing Without Wires - An Experiment](https://ieeexplore.ieee.org/document/5570293)
Video: [Reconstructing an 1884 Telegraph Experiment with Modern Simulation](https://www.youtube.com/watch?v=ZmkGXuwWpN0)
**Developed by:** DBbun LLC
**Version:** v1.1
**Data Formats:** CSV · JSON · NPZ · PNG
---
## Who Should Use This Dataset
This dataset is intended for:
- **Students** studying electromagnetism, signal processing, or numerical simulation
- **Engineers** exploring signal transmission in conductive media
- **Data scientists** working with physics-generated structured data
- **Researchers** interested in executable reconstructions of historical experiments
- **Educators** integrating computational laboratories into coursework
It provides a reproducible computational environment for studying signal transmission through conductive media, bridging physical modeling, circuit abstraction, and time-domain system behavior.
---
## Abstract
This dataset provides a computational reconstruction of S. J. M. Bear's 1884 experiment *"Telegraphing Without Wires,"* originally presented before the American Institute of Electrical Engineers. The project transforms a pre-digital manuscript — written decades before computers and numerical modeling — into a fully reproducible finite-difference simulation framework. By solving the variable-conductivity Laplace equation, it enables quantitative analysis of electric potential fields, current density distributions, and receiver behavior in conductive media.
The dataset includes multi-scenario simulations with spatially varying conductivity (uniform media, freshwater–brine interfaces, insulating obstacles, conductive paths, and localized plumes). Receiver behavior is modeled using a Thevenin-equivalent formulation with relay resistance and threshold dynamics. Time-domain simulations capture keying signals, electrode polarization effects, and relay actuation.
Beyond historical reconstruction, this resource serves as an educational and research platform:
- **For students:** a hands-on bridge between electromagnetic theory, partial differential equations, numerical methods, and signal processing.
- **For engineers:** a sandbox for studying signal transmission in conductive environments (e.g., underwater communication, geophysical sensing, bioelectric systems).
- **For data scientists:** structured, multi-modal datasets suitable for statistical modeling, inverse problems, parameter estimation, surrogate modeling, and machine learning experiments on physics-generated data.
All outputs are provided in CSV, JSON, and compressed NumPy formats to support reproducibility and downstream analysis. The included Python source code regenerates all scenarios.
---
## Dataset Structure
Each experiment generates:
| File | Description |
|------|-------------|
| `*_fields.npz` | Spatial field arrays (potential, electric field, current density) |
| `*_timeseries.csv` | Time-domain signal and relay behavior |
| `*_summary.json` | Per-experiment scalar results and circuit parameters |
| `figs/` | Figures directory |
Global outputs:
| File | Description |
|------|-------------|
| `experiment_summary_v1p1.csv` | Aggregated scalar results across all experiments |
| `experiment_summary_v1p1.json` | JSON equivalent of the above |
| `sweep_sigma_v1p1.csv` | Conductivity sweep results |
| `sweep_sigma_v1p1.json` | JSON equivalent of the sweep |
| `manifest_v1p1.json` | File inventory and checksums |
| `run_meta_v1p1.json` | Run metadata (version, timestamp, grid parameters) |
---
## NPZ File Specification (`*_fields.npz`)
### Material Map
| Array | Type | Description |
|-------|------|-------------|
| `sigma` | 2D float | Spatial conductivity map of the tub. Higher values indicate more conductive regions; lower values indicate less conductive or insulating regions. |
---
### Base 1-Volt Sending Condition
| Array | Type | Description |
|-------|------|-------------|
| `V_tub_1V` | 2D float | Potential distribution when 1 volt is applied across the sending electrodes. |
| `Ex_1V` | 2D float | Horizontal component of the electric field under the 1-volt sending condition. |
| `Ey_1V` | 2D float | Vertical component of the electric field under the 1-volt sending condition. |
| `Emag_1V` | 2D float | Magnitude of the electric field at each spatial location. |
| `Jx_1V` | 2D float | Horizontal component of current density. |
| `Jy_1V` | 2D float | Vertical component of current density. |
| `Jmag_1V` | 2D float | Magnitude of current density. |
---
### Delivered Voltage Fields
| Array | Type | Description |
|-------|------|-------------|
| `V_delivered_no_pol` | 2D float | Potential distribution accounting for battery internal resistance and contact resistance, without polarization. |
| `V_delivered_pol` | 2D float | Potential distribution including steady-state electrode polarization effects. |
---
### Receiver-Port Solution
| Array | Type | Description |
|-------|------|-------------|
| `V_port_1V` | 2D float | Potential distribution when 1 volt is applied directly across the receiver electrodes. Used to estimate the receiver's effective resistance. |
---
### Electrode Masks
Binary arrays (0 or 1):
| Array | Description |
|-------|-------------|
| `tx_plus` | Positive sending electrode region |
| `tx_minus` | Negative sending electrode region |
| `rx1` | First receiver electrode |
| `rx2` | Second receiver electrode |
---
## Time-Series CSV Specification (`*_timeseries.csv`)
| Column | Description |
|--------|-------------|
| `t` | Simulation time in seconds |
| `key` | Telegraph key state (1 = pressed, 0 = released) |
| `Vpol` | Electrode polarization voltage |
| `Vtub` | Voltage delivered across the tub |
| `Isource` | Current supplied by the battery |
| `Vth` | Effective voltage at the receiver |
| `Irelay` | Current flowing through the relay |
| `relay_state` | Relay state (1 = closed, 0 = open) |
---
## Per-Experiment Summary JSON Fields (`*_summary.json`)
| Field | Description |
|-------|-------------|
| `name` | Experiment identifier |
| `sigma_map_name` | Conductivity scenario used |
| `battery_voltage` | Battery voltage |
| `battery_internal_resistance_ohm` | Internal battery resistance |
| `electrode_contact_resistance_ohm` | Electrode contact resistance |
| `relay_resistance_ohm` | Relay resistance |
| `relay_pull_in_current` | Current required to activate relay |
| `relay_release_current` | Current below which relay releases |
| `Vth_per_1V` | Receiver voltage scaling factor |
| `Rth_ohm_like` | Effective resistance at receiver port |
| `delivered_tub_voltage_no_pol` | Tub voltage without polarization |
| `delivered_tub_voltage_with_pol` | Tub voltage with polarization |
| `Irelay_no_pol` | Relay current without polarization |
| `Irelay_with_pol` | Relay current with polarization |
| `relay_click_no_pol` | Relay activation without polarization (bool) |
| `relay_click_with_pol` | Relay activation with polarization (bool) |
| `tub_resistance_ohm_like` | Effective tub resistance |
| `source_current_no_pol` | Battery current without polarization |
| `source_current_with_pol` | Battery current with polarization |
---
## Conductivity Sweep Dataset (`sweep_sigma_v1p1.csv`)
| Column | Description |
|--------|-------------|
| `sigma` | Uniform conductivity value |
| `R_tub` | Effective tub resistance |
| `Vth_per_1V` | Receiver scaling factor |
| `Rth` | Effective receiver resistance |
| `Vtub_no_pol` | Delivered voltage without polarization |
| `Irelay_no_pol` | Relay current without polarization |
| `click_no_pol` | Relay activation without polarization (0/1) |
| `Vtub_pol` | Delivered voltage with polarization |
| `Irelay_pol` | Relay current with polarization |
| `click_pol` | Relay activation with polarization (0/1) |
---
## Reproducibility
Run:
```bash
python Bear-1884-Code-v1.1.py
```
Outputs are generated under:
```
output/
output/figs/
```
**Dependencies:**
- `numpy`
- `scipy`
- `matplotlib`
---
## Contribution
Developed by **DBbun LLC**, this project demonstrates how a historical scientific experiment can be transformed into a structured, reproducible computational laboratory suitable for education, engineering analysis, and data-driven research. |