Modeling and simulation of heat source trajectories through phase-change materials

TL;DR

This paper presents a novel modeling approach for controlling heat source trajectories through phase-change materials, with applications in space exploration and climate research, using energy minimization and split operator algorithms.

Contribution

It introduces an energy minimization framework and a coupled split operator algorithm for simulating probe trajectories in phase-change environments, improving control and modeling accuracy.

Findings

Demonstrates effective trajectory control via differential heating.

Provides a coupled operator algorithm implemented in Python and C++.

Shows dynamic response of probe velocity to heat flux changes.

Abstract

The modeling and simulation of heat source trajectories through phase-change materials is a relevant problem both for space exploration and for terrestrial climate research, among other fields. In space, the DLR and NASA are both interested in exploring beneath the surfaces of icy moons, primarily Enceladus and Europa, where conditions may alloy for extraterrestrial life. On Earth, unique sub-glacial aquatic ecosystems offer potential for geo-biological discoveries. Unfortunately, existing ice-drilling technology is dirty and cumbersome. Melting probes are a clean and compact alternative technology which use heaters to melt through the ice. A melting probe's trajectory can be controlled with differential heating. Successful trajectory control requires advancements not only in the modeling and simulation of the ambient dynamics, but also of the probe's coupled rigid body dynamics. Fundamentally, the rigid body dynamics can be modeled by the equations of motion; but this approach is prohibitively complex. This work proposes an approach which exploits that the motion of the probe is driven by contact with the evolving liquid-solid interface. From this perspective, an energy minimization problem is formulated. The general mathematical problem is formulated as two split operators, respectively for the rigid body dynamics and the ambient dynamics. These operators are coupled with feasibility constraints which ensure that the probe does not penetrate the solid. Concrete examples are shown both for the energy minimization problem and for the unsteady ambient dynamics. Finally, an algorithm is presented for the temporal coupling of the split operators, which is implemented using Python and C++. Example trajectories are shown, including the dynamic response of the probe velocity to a rapid change in the heat flux.