meschini references

Author: RemDelaporteMathurin

paper.bib

@@ -68,3 +68,41 @@ @misc{jinja
 	note = {original-date: 2010-10-17T13:41:17Z},
 	keywords = {jinja, jinja2, pallets, python, template-engine, templates},
 }
+
+
+@article{meschini_modeling_2023,
+	title = {Modeling and analysis of the tritium fuel cycle for {ARC}- and {STEP}-class {D}-{T} fusion power plants},
+	volume = {63},
+	copyright = {All rights reserved},
+	issn = {0029-5515},
+	url = {https://dx.doi.org/10.1088/1741-4326/acf3fc},
+	doi = {10.1088/1741-4326/acf3fc},
+	abstract = {The limited tritium resources available for the first fusion power plants (FPPs) make fuel self-sufficiency and tritium inventory minimization leading issues in FPP design. This work builds on the model proposed by Abdou et al (2020 Nucl. Fusion 61 013001), which analyzed the fuel cycle (FC) of a DEMOnstration nuclear FPP-class FPP with a time-dependent system-level model. Here, we use a modified version of their model to analyze the FC of an Affordable, Robust, Compact (ARC)-class tokamak and two versions of a Spherical Tokamak for Energy Production (STEP)-class tokamak. The ARC-class tokamak breeds tritium in a 2LiF + BeF2 liquid immersion blanket, while the STEP-class tokamak breeds tritium utilizing either a liquid-lithium blanket design or an encapsulated breeding blanket. A time-dependent system-level model is developed in Matlab Simulink® to simulate the evolution of tritium flows and tritium inventories in the FC. The main goals of this work are to assess tritium self-sufficiency of the ARC- and STEP-class designs and to determine quantitative design requirements that can be used to analyze the adequacy of a proposed FC system. These design requirements are aimed at achieving a low tritium inventory doubling time () and a low start-up inventory () while keeping the required tritium breeding ratio (TBR) as low as possible. We also consider how improvements in FC technology and POs affect TBR and . The model results show that TBR for ARC- and STEP-class FPPs should be achievable if the tritium burn efficiency (TBE) reaches 0.5\%–1\% (TBR1.2). This assumes significant, but attainable, improvements over current abilities. However, the model results indicate that an FPP must achieve ambitious performance targets, including FPP availability 70\%, tritium processing time 4 h, and the implementation of direct internal recycling (DIR). If future research yields major improvements to achievable TBE, it may be possible to achieve tritium self-sufficiency while operating at lower availability and without implementing DIR.},
+	language = {en},
+	number = {12},
+	urldate = {2023-12-22},
+	journal = {Nuclear Fusion},
+	author = {Meschini, Samuele and Ferry, Sara E. and Delaporte-Mathurin, Rémi and Whyte, Dennis G.},
+	month = sep,
+	year = {2023},
+	note = {Publisher: IOP Publishing},
+	pages = {126005},
+}
+
+
+@article{meschini_impact_2025,
+	title = {Impact of trapping on tritium self-sufficiency and tritium inventories in fusion power plant fuel cycles},
+	volume = {65},
+	issn = {0029-5515},
+	url = {https://dx.doi.org/10.1088/1741-4326/adacfa},
+	doi = {10.1088/1741-4326/adacfa},
+	abstract = {The dynamic analysis of fusion power plant (FPP) fuel cycles highlights the challenge of achieving tritium self-sufficiency in future FPPs. While state-of-the-art fuel cycle models offer valuable insights into the necessary design parameters for attaining tritium self-sufficiency, none of these models currently consider the impact of tritium trapping within fuel cycle components. However, detailed analysis of individual components reveals that substantial amounts of tritium can be trapped within the first wall, divertors, and breeding blanket systems, suggesting that tritium trapping may significantly influence the FPP ability to achieve self-sufficiency. The compounded effects of additional tritium traps generated by irradiation effects and component replacements further exacerbate this challenge. The novelty of this work is the integration of an explicit, physics-based model for tritium trapping, evolution of damage-induced traps, and component replacements into a dynamic, system-level model of a fuel cycle. The results show an increase of a factor of tritium inventory in the first wall and vacuum vessel of an ARC-class FPP when accounting for the aforementioned phenomena. This, coupled with the replacement of components subject to significant tritium trapping, slows down fuel cycle dynamics, resulting in an extended tritium doubling time (50\% increase), higher start-up inventory (30\% increase), and higher required tritium breeding ratio (2\%–5\%) compared to a scenario without tritium trapping.},
+	language = {en},
+	number = {3},
+	urldate = {2025-08-13},
+	journal = {Nuclear Fusion},
+	author = {Meschini, Samuele and Delaporte-Mathurin, Rémi and Tynan, George R. and Ferry, Sara E.},
+	month = feb,
+	year = {2025},
+	pages = {036010},
+}

paper.md

@@ -38,7 +38,7 @@ In addition to mirroring nearly all of `PathSim`'s capabilities, `PathView` uses
 
 # Statement of need
 
-`PathSim` is a powerful and flexible simulation framework for modelling complex systems. However, building large-scale or intricate models solely through Python scripting can be cumbersome and error-prone, particularly for new users or for projects that benefit from visual inspection of system layout.
+`PathSim` is a powerful and flexible simulation framework for modelling complex systems. However, building large-scale or intricate models solely through Python scripting can be cumbersome and error-prone, particularly for new users or for projects that benefit from visual inspection of system layout. This is for example the case for nuclear fusion fuel cycle applications [@meschini_modeling_2023; @meschini_impact_2025].
 Many established simulation platforms, such as MathWorks Simulink [@simulink] or Aspen Plus [@aspen], provide graphical user interfaces to enhance usability, model comprehension, and collaboration. Until now, such a visual modelling environment was missing for `PathSim`.
 `PathView` fills this gap by providing a modern, interactive, and extensible GUI, reducing the barrier to entry for new users and improving productivity for experienced modellers.