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Digital shadow–driven optimization of membrane reactors for high-efficiency blue hydrogen production
Get PDFThe growing demand for low-carbon energy has intensified interest in hydrogen, especially via methanol steam reforming (MSR) for on-site production. However, optimizing MSR reactors—particularly those using membrane and fluidized-bed technologies—is complex due to nonlinear interactions among key parameters like temperature, pressure, gas hourly space velocity (GHSV), and feed ratio. Traditional mechanistic models, while informative, are often too computationally intensive for real-time applications. To address this, the study proposes a digital shadow framework that integrates computational fluid dynamics (CFD) with machine learning (ML) to enable fast, scalable optimization of MSR systems. CFD simulations were used to model transport and reaction phenomena in four reactor types: PBR, FBR, and their membrane-equipped versions (PBMR and FBMR). The CFD simulation results were validated against experimental data from the literature, and their outputs under varied conditions provided datasets for training various ML regressors (MLP, RFR, SVR, GBR, XGB, and KNN). The goal of this study was to evaluate and compare different reactor configurations, to identify the optimal configuration for efficient hydrogen production via MSR. The ML models served as surrogates for rapid performance prediction. Among them, KNN outperformed others, achieving R2 ∼ 1 and MSE ∼0.002 for FBMR, and was selected for optimization using Bayesian methods. Under optimized conditions, FBMR yielded the best performance with ∼98.4 % methanol conversion and ∼96.2 % hydrogen yield due to superior mixing and hydrogen removal. PBMR followed with ∼91.7 % conversion and nearly 100 % hydrogen selectivity. FBR (∼88 %) outperformed PBR (∼79 %), highlighting fluidization's benefits. Sensitivity analysis revealed that feed ratio and pressure most influenced FBMR performance, while GHSV and stoichiometry were more critical in PBR and FBR. Overall, the study confirms the advantages of silica-MRs, particularly FBMR, for high-efficiency hydrogen production. The digital shadow provides a robust, accurate tool for optimizing reactor design and operations in clean hydrogen technologies
Recipes for Baking Bread: Stories from Holodomor
No full textThis paper explores the potential of creative practice to tell stories from Holodomor, Ukraine 1932–33 using graphic design and film. The results of the study are five animated documentaries: Recipes for Baking Bread, released in September 2021. I take reference from visual art and film, situating Mykola Bondarenko’s 1992–93 linocuts Ukraina 1933: Kulinara knyha (Ukraine 1933: A Cookbook) within Nicolas Bourriaud’s theories on “relational art”. Practices to describe “human interactions and its social context.”[1] I include a comparative analysis of three works by Jane Cheadle, Jordan Baseman and Theodore Ushev. The study questions the suitability of film and graphic design to tell stories, raise awareness, develop new creative practices and provide new research in the field. Following an introduction and background I separate my analysis into three parts: maps, poetry and Recipes for Baking Bread. The work includes in-depth analysis of letters as testimony from an engineer working in Ukraine during Holodomor, Jerry Berman. I explore the work of Gareth Jones, a Welsh journalist who reported from Holodomor from the perspective of his great nephew, an interview with Philip Colley. The project makes use of five interviews. The interviewees are: Jaroslaw Prytulak, Professor Serhii Ploky, Philip Colley, Dr Daria Mattingly, and Fr. Volodymyr Sampara with letters by Jerry Berman courtesy of Alison Marshall. I include evidence of new research available to scholars in public archives and online and a campaign for awareness of the Holodomor for general audiences. I conclude with a summary of impact.
1. Nicolas Bourriaud, Relational Aesthetics, trans. Simon Pleasance & Fronza Woods (Dijon-Quetigny: Les presses du réel, 2002), p. 14
Public procurement in Russia: state patronage, corruption, and tax evasion in the construction industry
No full textThis study examines public procurement in Russia’s construction sector, highlighting its deep entrenchment in corruption and state patronage. Based on 50 interviews with 27 business and state officials, we find that authorities enable corruption and tax evasion for self-enrichment and power consolidation. Contrary to claims that digitalisation curbs corruption in public procurement, we argue that state patronage sustains a cycle of illegal practices. A weak judiciary reinforces corruption, increasing state intervention, eroding public trust, and lowering tax compliance. As a result, corruption remains socially accepted, making meaningful reform unlikely
Technological readiness during different stages of the pandemic: A qualitative comparative analysis approach
No full textThe COVID-19 pandemic has triggered a significant transformation, requiring society to adapt to the ‘new normal’ and shifting how individuals and organizations operate. This study seeks to analyze the changes in technological readiness among the workforce during the COVID-19 pandemic and to explore the impact of key factors on individuals' readiness to embrace digital technologies. We investigate how organizations' technological readiness is influenced by employees' characteristics, including adaptation to change, attitude toward change, collaboration with others, coping with stress, and decisiveness. A Two-Step Fuzzy-Set Qualitative Comparative Analysis (fsQCA) was adopted in this study to disentangle the causal complexity under Technological readiness and study its interplay with possible relevant individual characteristics during and after the pandemic. Our study highlighted significant insights comparing 2020 and 2022, notably the importance of collaboration as a necessary condition for technological readiness later in the pandemic. Other individual characteristics significantly lead to high technological readiness in both years. We also suggested future studies that would help strengthen our current study
Presentazione del volume Discrezionalità legislativa e sindacato della Corte costituzionale M. Ruotolo (a cura di) Dipartimento di Giurisprudenza Università degli Studi di Napoli Federico II 5 marzo 2026, ore 9.30 Aula Biblioteca Guarino
No full textAir-source ammonia heat pump for district heating: a field modeling approach with focus on frosting-defrosting cycles
No full textFrost formation on air-source evaporators in cold and humid climates significantly increases energy consumption due to airflow obstruction and thermal insulation.
While this issue is well recognized, effective control strategies for multi-evaporator fields remain underexplored. This paper presents a novel evaporator model that
combines experimental validation under transient frosting conditions with a new algorithm for solving frost accumulation and defrosting process across an entire
evaporator field coupled to the heat pump cycle.
The model is applied to simulate a large-scale ammonia heat pump serving a Danish district heating network over an annual period. Results show that neglecting
frosting in design analyses can lead to strongly overestimated performance, with total costs increasing by up to 70 % once frost and defrosting cycles are considered.
The study also identifies an optimal field configuration of 80 evaporators with a fin pitch of 9 mm and an airflow velocity of 3.5 m/s, and shows that defrosting 20 %
of the field simultaneously is more effective than defrosting 10 %. Overall, the outcomes emphasize the critical importance of accounting for frost and defrosting
cycles in thermo-economic optimization, showing that the optimal design depends on local climatic conditions and should be supported by dedicated modelling tools
Hybridity of mainly asexually propagating duckweeds in genus Lemna – dead end or breakthrough?
No full textThe cosmopolitan, mainly vegetatively propagating, organ-reduced monocotyledonous aquatic duckweeds are the smallest and fastest growing angiosperms, distributed world-wide and flower rarely in nature. Recently, we reported intra- and interspecific hybrids and ploidy variants in the genus Lemna. Thus, contrary to the expectation, sexual propagation may occasionally occur within and between Lemna species. Our main goal was to uncover whether the ecologically successful hybrids are evolutionary dead ends or initiate further speciation and novel sexual recombination. We investigated flower development, pollen viability, seed set, and seed germination in hybrids and their parental species and characterized genome size and genetic markers in the progenies. Intraspecific crosses yielded fertile progeny, but all diploid and triploid interspecific hybrids were male sterile. Only an established allotetraploid hybrid reproduced sexually, while colchicine-induced allotetraploids from allodiploids did not regain sexual competence so far. We concluded that only established allotetraploid hybrids represent an evolutionary breakthrough in duckweeds. Our results regarding sexual traits within the duckweed genus Lemna and the sexual competence of diverse hybrids pave the way for further investigation in this understudied field, provide fundamental data regarding the evolutionary potential of duckweed hybrids and are important for future breeding efforts on this emerging crop
LIDAR-Based Relative Navigation and 3D Target Reconstruction for Close Proximity Operations With Unknown Target
No full textThis paper presents a LIDAR-based relative navigation architecture designed to deal with uncooperative and unknown targets. It foresees two sequential functional blocks. The former aims at reconstructing a geometric model of the target by recursively registering consecutive point clouds collected over a certain time frame. In this block, a correction step is applied at a frequency lower than the LIDAR update rate in order to bound to odometry-related drift in the estimated relative trajectory. The resulting reconstructed model is then used within the latter block which implements model-based registration algorithms to accurately estimate the target pose. The performance of the proposed architecture is assessed in a numerical simulation environment which realistically reproduces both the relative orbital dynamics and the measurement process of a spaceborne LIDAR system and assuming ENVISAT as target. Results of the reconstruction phase show a Chamfer distance of few square centimeters between the reference geometry and the reconstructed model. In the relative navigation phase dm-level and degree-level accuracy is achieved in the pose estimated with the reconstructed model