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metadata
license: apache-2.0
datasets:
  - Taylor658/fluid_dynamics_test
base_model:
  - mistralai/Mistral-Large-Instruct-2411
language:
  - en

Electrohydrodynamics for Hall Effect Thrusters

Model Card

Model Overview

Model Name: mistral-7b-hall-thruster-fluid-dynamics
Model Type: Transformer-based language model
Languages: English
License: Apache License 2.0

This model is based on the Mistral-Large-Instruct-2411 foundation model and is being fine-tuned on the Taylor658/fluid_dynamics_test dataset. It is designed to assist with understanding electrohydrodynamics, plasma-fluid interactions, and related fluid dynamic phenomena in Hall Effect Thrusters (HETs).


Model Details

  • Developers: A Taylor
  • Model Architecture: Transformer-based with enhancements for code generation and multimodal processing
  • Parameters: 7 Billion
  • Native Function Calling: Supported
  • Multimodal Capabilities: Text-based domain discussions

Intended Use

  • Primary Applications:
    • Assist aerospace engineers and researchers in analyzing plasma and fluid flows in HET channels
    • Provide support for understanding electrohydrodynamics in propulsion systems
    • Facilitate research by offering computational assistance in modeling plasma-fluid interactions
  • Usage Scenarios:
    • Discussing the influence of magnetic fields on electron mobility
    • Explaining ionization dynamics in the thruster discharge channel
    • Interpreting simulation data and theoretical results for efficiency and plume characteristics

Training Data

  • Dataset Name: Taylor658/fluid_dynamics_test
  • Description: A dataset containing textual explanations, theoretical derivations, and computational concepts related to fluid dynamics and plasma interactions in Hall thrusters.
  • Data Modalities:
    • Text: Technical documentation, research summaries, and theoretical analyses
    • Code:

Training Procedure

The model will be fine tuned to enhance its capabilities in handling advanced fluid dynamics and plasma physics scenarios relevant to Hall Effect Thrusters. Key enhancements include:

  1. Domain-Specific Fine-Tuning: Adjusting the model's parameters using the Taylor658/fluid_dynamics_test dataset to improve performance in electrohydrodynamics.
  2. Validation and Testing: Ensuring the model’s outputs are accurate and reliable by comparing them against established literature and computational benchmarks.
  3. Iterative Refinement: Continuously refining responses based on domain expert feedback and real-world problem sets.

How to Use

  • Input Format:
    • Natural language queries or prompts about electrohydrodynamics, fluid flow, or plasma phenomena in Hall Effect Thrusters.
  • Examples:
    • "Explain how the Hall parameter affects electron mobility in a Hall Effect Thruster."
    • "What are the primary factors influencing ionization efficiency in the thruster channel?"

Limitations

  • Work in Progress: The model is currently being fine-tuned; performance may improve over time.
  • Domain Specificity: Optimized for Hall Effect Thruster fluid dynamics, may not generalize well outside this domain.
  • Computational Resources: Requires adequate computational power for optimal performance due to model size.

Ethical Considerations

  • Accuracy: Intended as a research and educational aid; not a substitute for expert judgment.

Acknowledgements

  • Mistral AI: For providing the Mistral-Large-Instruct-2411 foundation model.
  • Dataset Contributors: Taylor658
  • Open-Source Community: Gratitude for tools and libraries that supported the fine-tuning process.

License

  • Model License: Apache License 2.0
  • Dataset License: Apache License 2.0

Future Work

  • Next Version: May incorporate advanced magnetohydrodynamic modeling, improved handling of variable mass flow rates, and refined treatments of plasma-wall interactions.

Contact Information

  • Author: A Taylor
  • Email
  • Repository:

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