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UEI Symposium

Date: 19 November 10:30-17:00 (walk-in from 10:00, followed by networking drinks from 17:00) Location: The Old Library, Raam 180, 2611 WP Delft Register Here Submit Research Paper The Netherlands aims to increase energy renovations in existing buildings to 200,000 per year. For the past four years, the "Integrated Approaches for Energy Renovations in Existing Buildings" (IEBB) consortium has worked to develop innovative and scalable solutions to achieve this goal. On November 19, Urban Energy Institute will host its annual symposium which will also serve as the closing event for the IEBB program. The event will showcase IEBB’s most promising results and lessons learned. Professionals from industry, government and academia will gather to exchange ideas on how these results can be further put into practice. This event is organized by TU Delft and TNO in collaboration with TKI Urban Energy, TKI Bouw en Techniek and RVO. For more information about the IEBB consortium and outcomes, please visit the IEBB Website and TU Delft IEBB Research . Program 10:00 – 10:30 Walk-in, Registration & Coffee 10:30 – 10:40 Welcome Remarks by Moderator, Geert Maarse Speaker Moderator Geert Maarse 10:40 – 11:00 Opening Keynote: “Transitions” by Laure Itard, Professor of Building Energy Epidemiology, TU Delft (EN) Speaker The energy transition in buildings entails many different transitions. Drawing on insights from IEBB and broader developments in science, technology and society, Laure Itard will discuss next steps towards broad sustainability in the built environment. TU Delft Laure Itard 11:00 – 11:30 Opening Panel Discussion: Reflecting on IEBB Collaboration (NL) Speakers Hogeschool Utrecht Mieke Oostra TNO Huub Keizers RVO Marion Bakker TU Delft Henk Visscher 11:30 – 12:00 PhD Panel: Tangible Results for Industry (EN) Speakers Priva Paula van den Brom TU Delft Prateek Wahi TU Delft Evert van Beek 12:00 – 13:00 Networking Lunch 13:00 – 14:30 Parallel Sessions: Round 1 Track 1: Bundling Renovation Measures (NL) Accelerating the energy transition in the built environment requires a different way of thinking about renovation “products” and more efficient, standardized ways to produce and install them. This section presents a cross-section of the various technological developments, tools and methods have been developed within IEBB for this purpose. Reimarkt Mathijs Vallinga TNO Piet Jacobs Cyclomedia Niels van den Kieboom Track 2: Collaboration Models for Energy Renovations (EN) Speeding up renovations of buildings owned by multiple owners requires a different way of doing business. This workshop will focus on the IEBB project WNR (Woonlasten-neutraal Renoveren – Living Cost Neutral Renovation) and its follow-up, the LIFE project CondoReno . The session offers insights into new business models and collaboration structures that help homeowners to jointly pursue a whole renovation trajectory. WNR Walter van Steenis TU Delft Ragy Elgendy Verbouwstromen Olivier Lauteslager TKI Urban Energy Guus Mulder TU Delft Erwin Mlecnik Track 3: Site Visit to Green Village (EN) Explore The Green Village , TU Delft’s inhabited, low-regulation field lab where sustainable innovations for the built environment are being tested. During the tour you'll discover pioneering solutions for climate adaptation, energy transition, and sustainable construction. The tour is led by Arnoud van der Zee, program manager Energy Transition. The tour takes place outdoors, so come prepared for the weather. The Green Village Arnoud van der Zee 14:30 – 14:45 Break 14:45 – 16:00 Parallel Sessions: Round 2 Track 4: How to Get People on Board: Behavioral Insights into Renovation Decisions, Processes, and Use (EN) TU Delft Stella Boess TU Delft Gerdien de Vries TUE Ioulia Ossokina TUE Tije van Casteren TU Delft Queena Qian Track 5: Preparing Homes for District Heating (EN) What is needed to connect a home to a district heating network, what can be done to simplify and accelerate this, and what are possible alternatives? In this session, we take a look at developments both “in front of” and “behind” the meter with respect to district heating networks. TNO Andries van Wijhe TNO Martijn Clarijs TU Delft Prateek Wahi Track 6: Data-Driven Solutions for Scaling Up Renovations (EN) This breakout session shares IEBB research and results for data-driven approaches to enhance building performance, focusing on renovation strategies, energy assessments, and dynamic behavior modeling. TU Delft Laure Itard TUE Luyi Xu W/E Geurt Donze Priva Paula van den Brom TNO Sten de Wit TU Delft Prateek Wahi 16:00 – 16:30 Closing Panel Discussion: Lessons Learned and Recommendations from IEBB Experience (NL) Speakers KGG Marjolein van Splunder TKI Urban Energy Guus Mulder RVO Marion Bakker VRO David van der Woude 16:30 – 16:45 Closing Keynote by Maaike Zwart, Vice-Mayor Sustainability City of Delft (NL) Speaker Gemeente Delft Maaike Zwart 16:45 – 17:00 Final Reflections and Wrap-Up Speakers TNO Marco Bakker TU Delft Henk Visscher 17:00 – 18:00 Networking Reception Get a glimpse of the experience by watching the aftermovie from the UEI Symposium 2023, 'Future Horizons of the Energy Transition.'

Machine Learning & Data Science

Pro2Tech Research Cluster Machine Learning & Data Science In an era marked by the rapid advancement of technology and availability of data, the Pro2Tech Machine Learning and Data Science Research Cluster is bridging research efforts and industry to bring new technologies to practice. In our cluster, we have a clear vision for the future of machine learning and data science in industrial practice. To achieve this vision, we bring together researchers from key technical fields including computer science, chemical engineering, and control engineering. Our aim is to build consortia that cover the whole value chain from technology development over software companies to end-users. Artur Schweidtmann This facilities the quick takeoff of our developments and long-term maintenance. Ultimately, we aim to create win-win situations creating value for all partners and society. To set this up, our technology and business developers help us to identify suitable partners, collaboration modes, and co-funding opportunities. The cluster's research is divided into three primary areas of focus: Machine Learning for Process Operation: This area explores the application of machine learning techniques to enhance process engineering, including the use of soft sensors for monitoring and control. By leveraging data-driven models, the cluster aims to improve the efficiency, reliability, and sustainability of manufacturing and processing operations. Topics of interest include predictive maintenance, process optimization, and the integration of IoT technologies to create smart, adaptive systems. Machine Learning for Process Design and Development: This area aims to support the process design and development to optimize process efficiency, reduce time-to-market, and enhance the sustainability. Key endeavors include hybrid modeling, surrogate modeling, and (superstructure) optimization. Moreover, we develop generative AI methods for the design of novel (chemical) processes. Machine Learning for Product Engineering: In the realm of product engineering, the cluster seeks to revolutionize the design and development of new materials and chemicals through molecular machine learning. This innovative approach combines computational chemistry, biology, and machine learning to predict molecular properties and behaviors, accelerating the discovery and creation of novel materials and molecules for a wide range of applications. Areas of exploration include drug discovery, material science, and the development of environmentally friendly chemicals and materials. The Machine Learning and Data Science Research Cluster is committed to advancing fundamental research, as well as applying its findings to real-world applications. By working closely with industry partners and other academic disciplines, the cluster aims to not only push the boundaries of what is scientifically possible but also to deliver practical, impactful solutions that address the pressing needs of society. Key topics of interest for the cluster include: Advanced algorithms for machine learning and data analysis. Development and implementation of soft sensors in industrial settings. Computational methods for molecular property prediction and material design. Data-driven optimization of process engineering and product development. Integration of artificial intelligence with traditional engineering disciplines to create innovative solutions. The overarching goal of the Machine Learning and Data Science Research Cluster is to lead the way in the application of machine learning and data science in engineering. By fostering a collaborative environment that bridges the gap between theoretical research and practical application, the cluster aims to make significant contributions to the fields of process and product engineering, ultimately enhancing efficiency, sustainability, and innovation. Dr. A.M. Schweidtmann Process Systems Engineering +31 (0)15 2786678 (secr.) A.Schweidtmann@tudelft.nl

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TU Delft jointly wins XPRIZE Rainforest drone competition in Brazil

TU Delft jointly wins in the XPRIZE Rainforest competition in the Amazon, Brazil Imagine using rapid and autonomous robot technology for research into the green and humid lungs of our planet; our global rainforests. Drones that autonomously deploy eDNA samplers and canopy rafts uncover the rich biodiversity of these complex ecosystems while revealing the effects of human activity on nature and climate change. On November 15, 2024, after five years of intensive research and competition, the ETHBiodivX team, which included TU Delft Aerospace researchers Salua Hamaza and Georg Strunck, achieved an outstanding milestone: winning the XPRIZE Rainforest Bonus Prize for outstanding effort in co-developing inclusive technology for nature conservation. The goal: create automated technology and methods to gain near real-time insights about biodiversity – providing necessary data that can inform conservation action and policy, support sustainable bioeconomies, and empower Indigenous Peoples and local communities who are the primary protectors and knowledge holders of the planet’s tropical rainforests. The ETHBiodivX team, made of experts in Robotics, eDNA, and Data Insights, is tackling the massive challenge of automating and streamlining the way we monitor ecosystems. Leading the Robotics division, a collaboration between TU Delft’s Prof. Salua Hamaza, ETH Zurich’s Prof. Stefano Mintchev and Aarhus University’s Profs. Claus Melvad and Toke Thomas Høye, is developing cutting-edge robotic solutions to gather ecology and biology data autonomously. “We faced the immense challenge of deploying robots in the wild -- and not just any outdoor environment but one of the most demanding and uncharted: the wet rainforests. This required extraordinary efforts to ensure robustness and reliability, pushing the boundaries of what the hardware could achieve for autonomous data collection of images, sounds, and eDNA, in the Amazon” says prof. Hamaza. “Ultimately, this technology will be available to Indigenous communities as a tool to better understand the forest's ongoing changes in biodiversity, which provide essential resources as food and shelter to the locals.” . . . .

Students Amos Yusuf, Mick Dam & Bas Brouwer winners of Mekel Prize 2024

Master students Amos Yusuf, from the ME faculty (Mick Dam, from the EEMCS faculty and graduate Bas Brouwer have won the Mekel Prize 2024 for the best extra scientific activity at TU Delft: the development of an initiative that brings master students into the classroom teaching sciences to the younger generations. The prize was ceremonially awarded by prof Tim van den Hagen on 13 November after the Van Hasselt Lecture at the Prinsenhof, Delft. They received a statue of Professor Jan Mekel and 1.500,- to spend on their project. Insights into climate change are being openly doubted. Funding for important educational efforts and research are being withdrawn. Short clips – so called “reels” – on Youtube and TikTok threaten to simplify complex political and social problems. AI fakes befuddle what is true and what is not. The voices of science that contribute to those discussion with modesty, careful argument and scepticism, are drowned in noise. This poses a threat for universities like TU Delft, who strive to increase student numbers, who benefit from diverse student populations and aim to pass on their knowledge and scientific virtues to the next generation. It is, therefore, alarming that student enrolments to Bachelor and Master Programs at TU Delft have declined in the past year. Students in front of the class The project is aimed to make the sciences more appealing to the next generation. They have identified the problem that students tend miss out on the opportunity of entering a higher education trajectory in the Beta sciences – because they have a wrong picture of such education. In their mind, they depict it as boring and dry. In his pilot lecture at the Stanislas VMBO in Delft, Amos Yusuf has successfully challenged this image. He shared his enthusiasm for the field of robotics and presented himself as a positive role model to the pupils. And in return the excitement of the high school students is palpable in the videos and pictures from the day. The spark of science fills their eyes. Bas Brouwer Mick Dam are the founders of NUVO – the platform that facilitates the engagement of Master Students in high school education in Delft Their efforts offer TU Delft Master Students a valuable learning moment: By sharing insights from their fields with pupils at high school in an educational setting, our students can find identify their own misunderstandings of their subject, learn to speak in front of non-scientific audiences and peak into education as a work field they themselves might not have considered. An extraordinary commitment According to the Mekel jury, the project scored well on all the criteria (risk mitigation, inclusiveness, transparency and societal relevance). However, it was the extraordinary commitment of Amos who was fully immersed during his Master Project and the efforts of Brouwer and Dam that brought together teaching and research which is integral to academic culture that made the project stand out. About the Mekel Prize The Mekel Prize will be awarded to the most socially responsible research project or extra-scientific activity (e.g. founding of an NGO or organization, an initiative or realization of an event or other impactful project) by an employee or group of employees of TU Delft – projects that showcase in an outstanding fashion that they have been committed from the beginning to relevant moral and societal values and have been aware of and tried to mitigate as much as possible in innovative ways the risks involved in their research. The award recognizes such efforts and wants to encourage the responsible development of science and technology at TU Delft in the future. For furthermore information About the project: https://www.de-nuvo.nl/video-robotica-pilot/ About the Mekel Prize: https://www.tudelft.nl/en/tpm/our-faculty/departments/values-technology-and-innovation/sections/ethics-philosophy-of-technology/mekel-prize

New catheter technology promises safer and more efficient treatment of blood vessels

Each year, more than 200 million catheters are used worldwide to treat vascular diseases, including heart disease and artery stenosis. When navigating into blood vessels, friction between the catheter and the vessel wall can cause major complications. With a new innovative catheter technology, Mostafa Atalla and colleagues can change the friction from having grip to completely slippery with the flick of a switch. Their design improves the safety and efficiency of endovascular procedures. The findings have been published in IEEE. Catheter with variable friction The prototype of the new catheter features advanced friction control modules to precisely control the friction between the catheter and the vessel wall. The friction is modulated via ultrasonic vibrations, which overpressure the thin fluid layer. This innovative variable friction technology makes it possible to switch between low friction for smooth navigation through the vessel and high friction for optimal stability during the procedure. In a proof-of-concept, Atalla and his team show that the prototype significantly reduces friction, averaging 60% on rigid surfaces and 11% on soft surfaces. Experiments on animal aortic tissue confirm the promising results of this technology and its potential for medical applications. Fully assembled catheters The researchers tested the prototype during friction experiments on different tissue types. They are also investigating how the technology can be applied to other procedures, such as bowel interventions. More information Publicatie DOI : 10.1109/TMRB.2024.3464672 Toward Variable-Friction Catheters Using Ultrasonic Lubrication | IEEE Journals & Magazine | IEEE Xplore Mostafa Atalla: m.a.a.atalla@tudelft.nl Aimee Sakes: a.sakes@tudelft.nl Michaël Wiertlewski: m.wiertlewski@tudelft.nl Would you like to know more and/or attend a demonstration of the prototype please contact me: Fien Bosman, press officer Health TU Delft: f.j.bosman@tudelft.nl/ 0624953733