Numerical investigation of an innovative furnace concept for industrial coil coating lines

In this work, the engineering performance of an innovative furnace concept developed for continuous drying and curing of paint-coated metal sheets (coil coating process) is investigated through advanced modeling and numerical simulation techniques. Unlike the traditional and wide-spread coil coating furnaces – which operate according to the so-called convective air-drying technology –, the present furnace concept relies on infrared radiative heating to drive solvent evaporation and curing reactions. Radiative heat is provided by the operation of radiant porous burners which are fed with evaporated solvents. The current furnace concept consists of two main chambers (the radiant burner section and the curing oven section) with different gas compositions (atmospheres) that are separated by a semi-transparent window. The window allows energy transfer and prevents gas mixing between the two sections. To utilize the solvent-loaded atmosphere available in the curing oven section as fuel – and to prevent the development of explosive conditions therein –, a novel inertization concept shielding the curing oven section from the external environment is considered. The current furnace concept aims at improving process intensification and promoting energy efficiency. For the current furnace concept, numerical simulation results support a suitable and competitive performance for drying the applied coatings in comparison with the traditional approach. Simultaneously, a safe operation is predicted, without (i) solvent leakage from the furnace and (ii) oxygen entrainment from the surrounding ambient into the furnace. These conditions are satisfied demonstrating a safe operation and a complete evaporation of solvents from applied liquid film coatings

Numerical investigation of an innovative furnace concept for industrial coil coating lines

This research was funded by the European Community's Framework Programme for Research and Innovation Horizon 2020 under grant agreement no. 768692 (ECCO). Publisher Copyright: © 2023 The Author(s)In this work, the engineering performance of an innovative furnace concept developed for continuous drying and curing of paint-coated metal sheets (coil coating process) is investigated through advanced modeling and numerical simulation techniques. Unlike the traditional and wide-spread coil coating furnaces – which operate according to the so-called convective air-drying technology –, the present furnace concept relies on infrared radiative heating to drive solvent evaporation and curing reactions. Radiative heat is provided by the operation of radiant porous burners which are fed with evaporated solvents. The current furnace concept consists of two main chambers (the radiant burner section and the curing oven section) with different gas compositions (atmospheres) that are separated by a semi-transparent window. The window allows energy transfer and prevents gas mixing between the two sections. To utilize the solvent-loaded atmosphere available in the curing oven section as fuel – and to prevent the development of explosive conditions therein –, a novel inertization concept shielding the curing oven section from the external environment is considered. The current furnace concept aims at improving process intensification and promoting energy efficiency. For the current furnace concept, numerical simulation results support a suitable and competitive performance for drying the applied coatings in comparison with the traditional approach. Simultaneously, a safe operation is predicted, without (i) solvent leakage from the furnace and (ii) oxygen entrainment from the surrounding ambient into the furnace. These conditions are satisfied demonstrating a safe operation and a complete evaporation of solvents from applied liquid film coatings.publishersversionpublishe

Evolving and evaluating the OMERACT fellows program: insights and implications from OMERACT 2023 fellows

Objective: To describe the evolution of the OMERACT Fellows Program (OM FP) and to evaluate the innovative changes implemented in the 2023 program. Methods: The OM FP, the first of its kind in global rheumatology, was developed in 2000 to mentor early career researchers in methods and processes for reaching evidence-driven consensus for outcome measures in clinical studies. The OM FP has evolved through continuing iterations of face to face and online feedback. Key new features delivered in 2023 included e-learning modules, virtual introductory pre-meetings, increased networking with Patient Research Partners (PRPs), learning opportunities to give and receive personal feedback, ongoing performance feedback during the meeting from Fellow peers, PRPs, senior OMERACTers (members of the OMERACT community) and Emerging Leader mentors, involvement in pitching promotions, two-minute Lightning Talks in a plenary session and an embedded poster tour. An online survey was distributed after the meeting to evaluate the program. Results: OM FP has included 208 fellows from 16 countries across 4 continents covering 47 different aspects of rheumatology outcomes since its inception. Over 50 % have remained engaged with OMERACT work. In 2023, 18 Fellows attended and 15 (83 %) completed the post-meeting survey. A dedicated OM FP was deemed important by all respondents, and 93 % would attend the meeting in future. The PRP/Fellow Connection Carousel and Lightning Talks were rated exceptional by 93 %. Key components to improve included clarification of expectations, overall workload, the Emerging Leaders Mentoring Program, and the content and duration of daily summary sessions. Conclusion: The innovations in the 2023 OM FP were well received by the majority of participants and supports early career rheumatology researchers to develop collaborations, skills and expertise in outcome measurement. Implementation of feedback from Fellows will enhance the program for future meetings, continuing to facilitate learning and succession planning within OMERACT

On the continuous Weber and k-median problems

We give the first exact algorithmic study of facility location problems having a continuum of demand points. In particular, we consider versions of the ''continuous k-means (Weber) problem'' where the goal is to select one or more center points that minimize average distance to a set of points in a demand region. In such problems, the average is computed as an integral over the relevant region, versus the usual discrete sum of distances. The resulting facility location problems are inherently geometric, requiring analysis techniques of computational geometry. We provide polynomial-time algorithms for various versions of the L1 1-mean (Weber) problem. We also consider the multiple-center version of the L1 k-means problem, which we prove is NP-hard for large k