Allan Moreira Mulin Leal


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Moreira Mulin Leal

First Name

Allan

ORCID

0000-0003-4340-610X

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2016 - 201932020 - 202511
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Publications 1 - 10 of 14
  • On-demand machine learning as an effective and reliable strategy to speed up reactive transport simulations
    Item type: Other Conference Item
    Moreira Mulin Leal, Allan (2021)
  • GeoProp: A thermophysical property modelling framework for single and two-phase geothermal geofluids
    Item type: Journal Article
    Merbecks, Tristan Leonard; Moreira Mulin Leal, Allan; Bombarda, Paola; et al. (2025)
    Geothermics
    The techno-economic evaluation of geothermal resources requires knowledge of the geofluid's thermophysical properties. While the properties of pure water and some specific brines have been studied extensively, no universally applicable model currently exists. This can result in a considerable degree of uncertainty as to how different geothermal resources will perform in practice. Geofluid modelling has historically been focused on two research fields: 1) partitioning the geofluid into separate phases, and 2) the estimation of the phases’ thermophysical properties. Models for the two fields have commonly been developed separately. Recognising their potential synergy, we introduce GeoProp, a novel geofluid modelling framework, which addresses this application gap by coupling existing state-of-the-art fluid partitioning simulators, such as Reaktoro, with high-accuracy thermophysical fluid property computation engines, like CoolProp and ThermoFun. GeoProp has been validated against field experimental data as well as existing models for some incompressible binary fluids. We corroborate GeoProp's efficacy at modelling the thermophysical properties of geothermal geofluids via a case study on the heat content of different geofluids. Our results highlight the importance of accurately characterising the thermophysical properties of geofluids in order to quantify the resource potential and optimise the design of geothermal power plants.
  • Reaktoro - an open-source C++/Python framework for modeling chemically reactive systems
    Item type: Presentation
    Moreira Mulin Leal, Allan (2020)
  • Ultra-fast geochemical calculations in reactive transport modeling with on-demand learning algorithms
    Item type: Other Conference Item
    Moreira Mulin Leal, Allan; Kyas, Svetlana; Kulik, Dmitrii A.; et al. (2020)
    Computational Methods in Water Resources XXIII (CMWR 2020). Proceedings
    Reactive transport simulations are in general time-consuming due to costly geochemical equilibrium and/or kinetics calculations. These may account for over 99% of all computing costs when complex chemical systems are considered, because those computations are needed one or more times in each cell of high-resolution meshes, at every time step of the simulation. To reduce their computing cost by orders of magnitude, we present an on-demand learning strategy that enables geochemical calculations to be rapidly and accurately predicted using previously learned geochemical states. We use sensitivity derivatives combined with first-order Taylor estimations to achieve these fast computations. These derivatives enable a complete bypass of expensive operations such as evaluation of thermodynamic properties (e.g., species activities, fugacities, equations of state), solution of matrix equations in each Newton iteration, time integration of ordinary differential equations, and more. We present reactive transport simulations, considering realistic chemical systems and strong non-ideal thermodynamic behavior, in which geochemical calculations were speed up by a factor of 100 to 200 using this on-demand learning algorithm.
  • ThermoFun: A C++/Python library for computing standard thermodynamic properties of substances and reactions across wide ranges of temperatures and pressures
    Item type: Journal Article
    Miron, George Dan; Moreira Mulin Leal, Allan; Dmytrieva, Svitlana V.; et al. (2023)
    Journal of Open Source Software
    ThermoFun is an open source library that facilitates the calculation and retrieval of standard thermodynamic properties of chemical substances, compounds, and reactions among them at a range of temperatures and pressures. The library is developed in C++ for performance, but it also has a Python API for broader and more convenient usage. It employs a variety of thermodynamic models and equations of state for solid, aqueous, surface, gaseous, and molten substances, and their reactions with input properties and parameters from various thermodynamic datasets that are collected and curated in the in ThermoHub database. The library can be used as a standalone code for searching and tabulating thermodynamic properties or linked to other modeling codes that require standard thermodynamic data as input. It offers the flexibility to use different thermodynamic datasets, including custom datasets and datasets retrieved from the online ThermoHub database, and to choose the most suitable models for different classes of substances necessary in various modeling applications. It can serve as a common source of thermodynamic models for standard properties of substances and reactions that can be easily integrated and combined, significantly improving the modeling capabilities for diverse (geo)chemical systems and over wide ranges of conditions.
  • Computational methods for reactive transport modeling: A Gibbs energy minimization approach for multiphase equilibrium calculations
    Item type: Journal Article
    Moreira Mulin Leal, Allan; Kulik, Dmitrii A.; Kosakowski, Georg (2016)
    Advances in Water Resources
  • Chemical Equilibrium: Numerical Challenges for Efficient and Stable Calculations in Computationally Intensive Applications
    Item type: Other Conference Item
    Moreira Mulin Leal, Allan; Smith, Richard; Kulik, Alexander; et al. (2018)
  • Accelerating reactive transport simulations with on-demand machine learning algorithms
    Item type: Other Conference Item
    Moreira Mulin Leal, Allan (2020)
    Wissenschaftlich-technische Berichte / HZDR, Helmholtz-Zentrum Dresden-Rossendorf ~ International Workshop on How to Integrate Geochemistry at Affordable Costs into Reactive Transport for Large-Scale Systems: Abstract Book
  • Supercooling, Glass Formation, and Mineral Assemblages upon Freezing of Salty Ice Grains from Enceladus's Ocean
    Item type: Journal Article
    Klenner, Fabian; Fifer, Lucas M.; Journaux, Baptiste; et al. (2025)
    The Planetary Science Journal
    The analysis of micrometer-sized ice grains emitted into space by Saturn's moon Enceladus suggests that the moon's subsurface ocean may be habitable. However, the formation conditions of these ice grains are largely unknown. Upon cooling, ocean droplets may supercool and then form a crystalline or glassy state, or a mixture of both. To investigate the processes of supercooling and glass formation in Enceladus's ice grains, we performed differential scanning calorimetry experiments with Enceladus-relevant salt mixtures at cooling rates ranging from 5 K minute$^{-1}$ to ~1227 K minute$^{-1}$ and extrapolated our results to faster cooling rates. We modeled the freezing of these solutions and associated mineral assemblages using the thermodynamic chemistry packages PHREEQC and Reaktoro. Our results indicate supercooling of ~25-30 K upon freezing from Enceladus's saline ocean. Freshly formed ice grains should be predominantly crystalline but contain up to 5% glass. Fast cooling rates and high salt concentrations favor the formation of glasses, potentially enabling the preservation of organics and cells, if present. Salts in the grains crystallize in the following sequence: first phosphate, followed by carbonates, and then chlorides. We find that the recently detected phosphates in Enceladus's ice grains are likely Na₂HPO₄:12H₂O. The pH values appear to vary among individual ice grains, depending on the stage of the freezing process, and these values may slightly differ from the pH of the moon's bulk ocean. Our experiments and models are relevant to other icy worlds with salty water reservoirs in their subsurfaces, such as Jupiter's moon Europa or the dwarf planet Ceres.
Publications 1 - 10 of 14