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Finnish ‘sand battery’ can store energy for months

Finnish researchers have presented the world's first sand battery. The battery can store solar and wind energy for months. Is this the solution to balancing the power grid?

Thesis Duration Arrangement

Effective from academic year 2018-2019 for all students of all cohorts: The nominal duration of the MSc Thesis Project is 21 full-time weeks. The maximum duration of a MSc Thesis Project is 25 weeks. When a student does not pass the first green-light meeting within 17 weeks after the kick-off date, the graduation committee may motivate to extend the graduation process of the student with a maximum time period of 3 months (13 weeks). The motivation for extension of the master thesis project has to be indicated on the green-light form. When a student does not pass the second green-light meeting, he/she has to start with a new graduation topic and new graduation committee.

Projects

Projects Data-driven assessment & optimization of life-cycle inspection and maintenance decisions under uncertainty This PhD research focuses on the development of computational frameworks that incorporate time-varying risk & reliability concepts in optimal design, monitoring, and maintenance of structural systems. This includes data-driven assessment and optimization enabled by probabilistic inference, structural reliability, and reinforcement learning methods. Learning to disentangle dependencies in multi-component structural systems for scalable decisions in high-dimensional spaces This PhD research approaches built environment decisions from a system-level perspective, aiming at disentangling the inherent high-dimensional correlations and dependencies that exist in data and models of engineering networks. It provides insights in questions related to the value of information, joint model updating, and coordination of autonomous agents acting on distributed components through Bayesian networks and decentralized reinforcement learning. Deep Visual Similarity Learning for Architectural Drawings Architects communicate their designs through various visual abstractions of the physical space; including orthographic drawings, photos, and 3D models. Semantic similarity learning for architectural drawings is a PhD project of Casper van Engelenburg that started in October 2021, focusing on understanding visual patterns in floorplan image data. He develops deep contrastive learning frameworks that enables us to learn low-dimensional, task-agnostic representations of architectural drawings. This research line builds a foundation for large quantitative analysis of archival and linked visual data. Beyond Appearance in Architectural Visual Data At the confluence of computer vision, data science, and architecture, a building is a high-dimensional data instance, predominantly represented in visual computer models encoding both aesthetic and performance indexes. Fatemeh Mostafavi started her PhD in June 2022 and focuses on performance-driven abstraction and generation of design models using computer vision. She is developing deep learning models that are able to make sense of a building plan with respect to sustainability, daylight, and comfort.

masterkickoff

Reduced environmental pressure by nanocoating pesticides

Recently, a TU Delft team led by prof. Ruud van Ommen developed an approach for more gradual release of pharmaceutics by applying nanocoatings; they now propose to use this also to reduce the amounts of required pesticides.

Lead

AiDAPT AI for a sustainable and resilient built environment Empowering decision-making processes of architects and engineers through AI, across different scales and life-cycle design phases of the built environment, is a key lever for the necessary sustainability transitions in the age of data and digitalization. At AiDAPT, computer vision, data science, and decision optimization methods come together through the development of deep learning, reinforcement learning, and uncertainty quantification frameworks that help us analyze and synthesize decisions for architectural and structural systems. This entails operation and reasoning in the complex spaces created by the confluence of diverse imagery data, noisy sensory measurements, virtual structural simulators, and uncertain numerical models. Application themes of interest range from automatic recognition of architectural drawings in large databases and generative design recommendations (initial design phase) to predictive intervention planning for life extension, structural risk mitigation, and multi-agent optimization of built systems (life-cycle optimization phase). Bridging fundamental and applied AI, AiDAPT aims at creating new scientific paradigms towards a more reliable and sustainable built environment. The AiDAPT Lab is part of the TU Delft AI Labs programme.

BBC Future: the epic attempts to power planes with hydrogen

“During the Cold War, both the US and USSR researched liquid hydrogen as a way to fuel aircraft. Could this cleaner fuel finally be around the corner?” BBC Future journalist Mark Piesing investigates this question in an informative longread published on 21 March 2022 on BBC Future.

Code & Datasets

Code & Datasets Codes (educational) Computer vision in intercative architecture Street view image collection form Google map Datasets AmsterTime dataset 2022 Ot & Sien dataset 2021

Call - DIAM Fast Track PhD Scholarship 2022 and Peter Paul Peterich PhD Fast-Track Grant

Are you an excellent student in the Master programme of the Delft Institute of Applied Mathematics (DIAM) with the ambition to extend your Master project into a PhD research project? Apply now for a DIAM Fast-Track PhD Scholarship or a Peter Paul Peterich PhD Fast-Track Grant! We offer: · after successfully completing your Master, you enroll into a 3-year fast track PhD position funded by DIAM. We ask: · You are on track completing, or have completed, your Master in Applied Mathematics at the TU Delft nominally and with cum laude distinction You write a PhD research plan (max. 1500 words) and a statement detailing the connection between your master project and the PhD project (max. 500 words). Your send your application, which also includes the names of the prospective promotor(s) and daily supervisor, a motivation letter, and a copy of your Master grade lists, to J.M.A.M.vanNeerven@tudelft.nl . The deadline is September 1, 2022 . The prospective promotor submits a letter of recommendation by the same date. A selection committee, appointed by the DIAM Management Team, will select the winning proposal by October 1, 2022.

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Finnish ‘sand battery’ can store energy for months

Finnish researchers have presented the world's first sand battery. The battery can store solar and wind energy for months. Is this the solution to balancing the power grid?

Thesis Duration Arrangement

Effective from academic year 2018-2019 for all students of all cohorts: The nominal duration of the MSc Thesis Project is 21 full-time weeks. The maximum duration of a MSc Thesis Project is 25 weeks. When a student does not pass the first green-light meeting within 17 weeks after the kick-off date, the graduation committee may motivate to extend the graduation process of the student with a maximum time period of 3 months (13 weeks). The motivation for extension of the master thesis project has to be indicated on the green-light form. When a student does not pass the second green-light meeting, he/she has to start with a new graduation topic and new graduation committee.

Projects

Projects Data-driven assessment & optimization of life-cycle inspection and maintenance decisions under uncertainty This PhD research focuses on the development of computational frameworks that incorporate time-varying risk & reliability concepts in optimal design, monitoring, and maintenance of structural systems. This includes data-driven assessment and optimization enabled by probabilistic inference, structural reliability, and reinforcement learning methods. Learning to disentangle dependencies in multi-component structural systems for scalable decisions in high-dimensional spaces This PhD research approaches built environment decisions from a system-level perspective, aiming at disentangling the inherent high-dimensional correlations and dependencies that exist in data and models of engineering networks. It provides insights in questions related to the value of information, joint model updating, and coordination of autonomous agents acting on distributed components through Bayesian networks and decentralized reinforcement learning. Deep Visual Similarity Learning for Architectural Drawings Architects communicate their designs through various visual abstractions of the physical space; including orthographic drawings, photos, and 3D models. Semantic similarity learning for architectural drawings is a PhD project of Casper van Engelenburg that started in October 2021, focusing on understanding visual patterns in floorplan image data. He develops deep contrastive learning frameworks that enables us to learn low-dimensional, task-agnostic representations of architectural drawings. This research line builds a foundation for large quantitative analysis of archival and linked visual data. Beyond Appearance in Architectural Visual Data At the confluence of computer vision, data science, and architecture, a building is a high-dimensional data instance, predominantly represented in visual computer models encoding both aesthetic and performance indexes. Fatemeh Mostafavi started her PhD in June 2022 and focuses on performance-driven abstraction and generation of design models using computer vision. She is developing deep learning models that are able to make sense of a building plan with respect to sustainability, daylight, and comfort.

masterkickoff

Reduced environmental pressure by nanocoating pesticides

Recently, a TU Delft team led by prof. Ruud van Ommen developed an approach for more gradual release of pharmaceutics by applying nanocoatings; they now propose to use this also to reduce the amounts of required pesticides.

Lead

AiDAPT AI for a sustainable and resilient built environment Empowering decision-making processes of architects and engineers through AI, across different scales and life-cycle design phases of the built environment, is a key lever for the necessary sustainability transitions in the age of data and digitalization. At AiDAPT, computer vision, data science, and decision optimization methods come together through the development of deep learning, reinforcement learning, and uncertainty quantification frameworks that help us analyze and synthesize decisions for architectural and structural systems. This entails operation and reasoning in the complex spaces created by the confluence of diverse imagery data, noisy sensory measurements, virtual structural simulators, and uncertain numerical models. Application themes of interest range from automatic recognition of architectural drawings in large databases and generative design recommendations (initial design phase) to predictive intervention planning for life extension, structural risk mitigation, and multi-agent optimization of built systems (life-cycle optimization phase). Bridging fundamental and applied AI, AiDAPT aims at creating new scientific paradigms towards a more reliable and sustainable built environment. The AiDAPT Lab is part of the TU Delft AI Labs programme.

BBC Future: the epic attempts to power planes with hydrogen

“During the Cold War, both the US and USSR researched liquid hydrogen as a way to fuel aircraft. Could this cleaner fuel finally be around the corner?” BBC Future journalist Mark Piesing investigates this question in an informative longread published on 21 March 2022 on BBC Future.

Code & Datasets

Code & Datasets Codes (educational) Computer vision in intercative architecture Street view image collection form Google map Datasets AmsterTime dataset 2022 Ot & Sien dataset 2021

Call - DIAM Fast Track PhD Scholarship 2022 and Peter Paul Peterich PhD Fast-Track Grant

Are you an excellent student in the Master programme of the Delft Institute of Applied Mathematics (DIAM) with the ambition to extend your Master project into a PhD research project? Apply now for a DIAM Fast-Track PhD Scholarship or a Peter Paul Peterich PhD Fast-Track Grant! We offer: · after successfully completing your Master, you enroll into a 3-year fast track PhD position funded by DIAM. We ask: · You are on track completing, or have completed, your Master in Applied Mathematics at the TU Delft nominally and with cum laude distinction You write a PhD research plan (max. 1500 words) and a statement detailing the connection between your master project and the PhD project (max. 500 words). Your send your application, which also includes the names of the prospective promotor(s) and daily supervisor, a motivation letter, and a copy of your Master grade lists, to J.M.A.M.vanNeerven@tudelft.nl . The deadline is September 1, 2022 . The prospective promotor submits a letter of recommendation by the same date. A selection committee, appointed by the DIAM Management Team, will select the winning proposal by October 1, 2022.
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Moving the Closet

You simply cannot miss it, it is big and magenta: the Pink Closet . On 12 November 2024 the Pink Closet will head to the Main Hall of the TU Delft Library for the first time! The Pink Closet will take its place at the Nook, where it will feature as part of the Studium Generale programme on loneliness. More information on events that coincide with and incorporate the Pink Closet at TU Delft Library will soon be available on the website of Studium Generale .

Green ammonia remains a challenge, but researchers make significant progress

The production of ammonia, essential for fertiliser production, is responsible for almost 1.5% of global carbon emissions. This needs to be greener, which is why researchers have been looking for sustainable alternatives for years.

"Measuring brain activity through the skull with ultrasound opens new doors"

PhD Candidate Rick Waasdorp is looking for ways to correct the distortion caused by the skull when using Ultrasound technology. ‘’My goal is to develop an adaptive method for skull corrections that automatically measures the skull of new patients.’’

NWO funding for flexible power demand in electrically driven industry

NWO is funding two projects to explore ways to make the power demand of industry more flexible, allowing it to better align with future energy supplies. One of these projects, “DEFLAME,” is led by Machteld van den Broek from TU Delft.

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

The ENHANCE Diversity Seed Fund

Are you a student at TU Delft or another ENHANCE university with a passion for promoting diversity and inclusion? The ENHANCE Diversity Seed Fund is your chance to turn that passion into action. ENHANCE provides funding to support innovative, student-led projects that address key challenges related to inclusion and diversity within our academic communities. Key Details: Funding Available: Up to 1500 Euros per project in the 1st round! Eligibility: Students from ENHANCE member universities. Staff can also join student-led initiatives. Application Deadline: 8 January 2025. More information: Join the online Information Event on the 26 November 2024 16:00-17:00 CET on Zoom . More information: enhanceuniversity.eu/diversity/diversityseedfund/

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