arXiv subjects

Stefano Campagnola

Publications and source records attributed to Stefano Campagnola.

4 recordsLinked to original sources

arXiv2026

Three-dimensional Lagrangian ecosystems: carbon dynamics and potential for artificial fertilization

Transient supplies of nutrients to the surface ocean, both natural and artificial, stimulate blooms of phytoplankton and the formation of organic matter, driving air-sea gradients and uptake of CO$_2$. However, quantifying the associated carbon budget remains challenging, as it requires tracking the coupled biophysical evolution of water masses while they are transported, stretched and diluted. Here, we present an idealized three-dimensional model that describes biomass production and carbon dynamics within a Lagrangian patch in the ocean. The framework reproduces observed biogeochemical patterns from an artificial fertilization experiment and provides integrated metrics for the local carbon budget. Utilizing large ensembles of simulations, we examine the sensitivity of patch-scale primary production and carbon uptake to biochemical and physical factors. Our results show that patch dilution can enhance the ecosystem response, and how carbon uptake is sensitive to initial injected area, horizontal divergence and vertical diffusivity. In the context of renewed interest in ocean fertilization strategies for climate mitigation, our approach can thus provide quantitative tools to assess their efficacy and potential.

physics.ao-ph↗

arXiv2022

Tube Stochastic Optimal Control for Nonlinear Constrained Trajectory Optimization Problems

Recent low-thrust space missions have highlighted the importance of designing trajectories that are robust against uncertainties. In its complete form, this process is formulated as a nonlinear constrained stochastic optimal control problem. This problem is among the most complex in control theory, and no practically applicable method to low-thrust trajectory optimization problems has been proposed to date. This paper presents a new algorithm to solve stochastic optimal control problems with nonlinear systems and constraints. The proposed algorithm uses the unscented transform to convert a stochastic optimal control problem into a deterministic problem, which is then solved by trajectory optimization methods such as differential dynamic programming. Two numerical examples, one of which applies the proposed method to low-thrust trajectory design, illustrate that it automatically introduces margins that improve robustness. Finally, Monte Carlo simulations are used to evaluate the robustness and optimality of the solution.

math.OC↗

arXiv2016

GTOC8: Results and Methods of ESA Advanced Concepts Team and JAXA-ISAS

We consider the interplanetary trajectory design problem posed by the 8th edition of the Global Trajectory Optimization Competition and present the end-to-end strategy developed by the team ACT-ISAS (a collaboration between the European Space Agency's Advanced Concepts Team and JAXA's Institute of Space and Astronautical Science). The resulting interplanetary trajectory won 1st place in the competition, achieving a final mission value of $J=146.33$ [Mkm]. Several new algorithms were developed in this context but have an interest that go beyond the particular problem considered, thus, they are discussed in some detail. These include the Moon-targeting technique, allowing one to target a Moon encounter from a low Earth orbit; the 1-$k$ and 2-$k$ fly-by targeting techniques, enabling one to design resonant fly-bys while ensuring a targeted future formation plane% is acquired at some point after the manoeuvre ; the distributed low-thrust targeting technique, admitting one to control the spacecraft formation plane at 1,000,000 [km]; and the low-thrust optimization technique, permitting one to enforce the formation plane's orientations as path constraints.

physics.space-ph↗

arXiv2011

Design of Low-Thrust Gravity Assist Trajectories to Europa

This paper presents the design of a mission to Europa using solar electric propulsion as main source of thrust. A direct transcription method based on Finite Elements in Time was used for the design and optimisation of the entire low-thrust gravity assist transfer from the Earth to Europa. Prior to that, a global search algorithm was used to generate a set of suitable first guess solutions for the transfer to Jupiter, and for the capture in the Jovian system. In particular, a fast deterministic search algorithm was developed to find the most promising set of swing-bys to reach Jupiter A second fast search algorithm was developed to find the best sequence of swing-bys of the Jovian moons. After introducing the global search algorithms and the direct transcription through Finite Elements in Time, the paper presents a number of first guess Solutions and a fully optimised transfer from the Earth to Europa.

math.OC↗