ECLIPSE: An Evolutionary Computation Library for Instrumentation Prototyping in Scientific Engineering

2026-01-08

arXiv.org

AI Summary

This work addresses the challenges of integrating evolutionary computation into scientific instrument design, which is hindered by highly constrained design spaces, vast search dimensions, and expensive physical simulations. To overcome these obstacles, the authors propose a modular evolutionary computation framework tailored for scientific engineering applications. The framework innovatively combines domain-aware geometric-parametric individual encoding, seamless integration with external simulators, and an evolution strategy specifically adapted to low-throughput evaluation environments. Its effectiveness and practicality are demonstrated through successful applications in space science, including the optimization of 3D antennas and aerodynamic shapes for very low Earth orbit spacecraft, where it significantly reduces drag in real-world, high-fidelity simulation scenarios.

Technology Category

• Search and Optimization: Evolutionary Computation
• Machine Learning: Evolutionary Learning
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Search and Retrieval-Augmented AI: Vertical and domain-specific search

Abstract

Designing scientific instrumentation often requires exploring large, highly constrained design spaces using computationally expensive physics simulations. These simulators pose substantial challenges for integrating evolutionary computation (EC) into scientific design workflows. Evolutionary computation typically requires numerous design evaluations, making the integration of slow, low-throughput simulators particularly challenging, as they are optimized for accuracy and ease of use rather than throughput. We present ECLIPSE, an evolutionary computation framework built to interface directly with complex, domain-specific simulation tools while supporting flexible geometric and parametric representations of scientific hardware. ECLIPSE provides a modular architecture consisting of (1) Individuals, which encode hardware designs using domain-aware, physically constrained representations; (2) Evaluators, which prepare simulation inputs, invoke external simulators, and translate the simulator's outputs into fitness measures; and (3) Evolvers, which implement EC algorithms suitable for high-cost, limited-throughput environments. We demonstrate the utility of ECLIPSE across several active space-science applications, including evolved 3D antennas and spacecraft geometries optimized for drag reduction in very low Earth orbit. We further discuss the practical challenges encountered when coupling EC with scientific simulation workflows, including interoperability constraints, parallelization limits, and extreme evaluation costs, and outline ongoing efforts to combat these challenges. ECLIPSE enables interdisciplinary teams of physicists, engineers, and EC researchers to collaboratively explore unconventional designs for scientific hardware while leveraging existing domain-specific simulation software.

Problem

• evolutionary computation
• scientific instrumentation
• computationally expensive simulation
• design space exploration
• high-constrained optimization

Innovation

• Evolutionary Computation
• Scientific Instrumentation
• Simulation Integration
• Constrained Design Optimization
• Modular Framework