Suchergebnis: Katalogdaten im Frühjahrssemester 2022
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| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 103-0448-01L | Transformation of Urban Landscapes Nur für Master-Studierende, ansonsten ist eine Spezialbewilligung des Dozierenden notwendig. | W | 3 KP | 2G | J. Van Wezemael, A. Gonzalez Martinez | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The lecture course addresses the transformation of urban landscapes towards sustainable inward development. The course reconnects two largely separated complexity approaches in «spatial planning» and «urban sciences» as a basic framework to look at a number of spatial systems considering economic, political, and cultural factors. Focus lies on participation and interaction of students in groups. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | - Understand cities as complex adaptive systems - Understand planning in a complex context and planning competitions as decision-making - Seeing cities through big data and understand (Urban) Governance as self-organization - Learn Design-Thinking methods for solving problems of inward development - Practice presentation skills - Practice argumentation and reflection skills by writing critiques - Practice writing skills in a small project - Practice teamwork | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Starting point and red thread of the lecture course is the transformation of urban landscapes as we can see for example across the Swiss Mittelland - but in fact also globally. The lecture course presents a theoretical foundation to see cities as complex systems. On this basis it addresses practical questions as well as the complex interplay of economic, political or spatial systems. While cities and their planning were always complex the new era of globalization exposed and brought to the fore this complexity. It created a situation that the complexity of cities can no longer be ignored. The reason behind this is the networking of hitherto rather isolated places and systems across scales on the basis of Information and Communication Technologies. «Parts» of the world still look pretty much the same but we have networked them and made them strongly interdependent. This networking fuels processes of self-organization. In this view regions emerge from a multitude of relational networks of varying geographical reach and they display intrinsic timescales at which problems develop. In such a context, an increasing number of planning problems remain unaffected by either «command-and-control» approaches or instruments of spatial development that are one-sidedly infrastructure- or land-use orientated. In fact, they urge for novel, more open and more bottom-up assembling modes of governance and a «smart» focus on how space is actually used. Thus, in order to be effective, spatial planning and governance must be reconceptualised based on a complexity understanding of cities and regions, considering self-organizing and participatory approaches and the increasingly available wealth of data. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | A reader with original papers will be provided via the ILIAS system. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Only for masters students, otherwise a special permit of the lecturer is necessary. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-3900-00L | Big Data for Engineers This course is not intended for Computer Science and Data Science MSc students! | W | 6 KP | 2V + 2U + 1A | G. Fourny | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course is part of the series of database lectures offered to all ETH departments, together with Information Systems for Engineers. It introduces the most recent advances in the database field: how do we scale storage and querying to Petabytes of data, with trillions of records? How do we deal with heterogeneous data sets? How do we deal with alternate data shapes like trees and graphs? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | This lesson is complementary with Information Systems for Engineers as they cover different time periods of database history and practices -- you can even take both lectures at the same time. The key challenge of the information society is to turn data into information, information into knowledge, knowledge into value. This has become increasingly complex. Data comes in larger volumes, diverse shapes, from different sources. Data is more heterogeneous and less structured than forty years ago. Nevertheless, it still needs to be processed fast, with support for complex operations. This combination of requirements, together with the technologies that have emerged in order to address them, is typically referred to as "Big Data." This revolution has led to a completely new way to do business, e.g., develop new products and business models, but also to do science -- which is sometimes referred to as data-driven science or the "fourth paradigm". Unfortunately, the quantity of data produced and available -- now in the Zettabyte range (that's 21 zeros) per year -- keeps growing faster than our ability to process it. Hence, new architectures and approaches for processing it were and are still needed. Harnessing them must involve a deep understanding of data not only in the large, but also in the small. The field of databases evolves at a fast pace. In order to be prepared, to the extent possible, to the (r)evolutions that will take place in the next few decades, the emphasis of the lecture will be on the paradigms and core design ideas, while today's technologies will serve as supporting illustrations thereof. After visiting this lecture, you should have gained an overview and understanding of the Big Data landscape, which is the basis on which one can make informed decisions, i.e., pick and orchestrate the relevant technologies together for addressing each business use case efficiently and consistently. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This course gives an overview of database technologies and of the most important database design principles that lay the foundations of the Big Data universe. It targets specifically students with a scientific or Engineering, but not Computer Science, background. We take the monolithic, one-machine relational stack from the 1970s, smash it down and rebuild it on top of large clusters: starting with distributed storage, and all the way up to syntax, models, validation, processing, indexing, and querying. A broad range of aspects is covered with a focus on how they fit all together in the big picture of the Big Data ecosystem. No data is harmed during this course, however, please be psychologically prepared that our data may not always be in normal form. - physical storage: distributed file systems (HDFS), object storage(S3), key-value stores - logical storage: document stores (MongoDB), column stores (HBase) - data formats and syntaxes (XML, JSON, RDF, CSV, YAML, protocol buffers, Avro) - data shapes and models (tables, trees) - type systems and schemas: atomic types, structured types (arrays, maps), set-based type systems (?, *, +) - an overview of functional, declarative programming languages across data shapes (SQL, JSONiq) - the most important query paradigms (selection, projection, joining, grouping, ordering, windowing) - paradigms for parallel processing, two-stage (MapReduce) and DAG-based (Spark) - resource management (YARN) - what a data center is made of and why it matters (racks, nodes, ...) - underlying architectures (internal machinery of HDFS, HBase, Spark) - optimization techniques (functional and declarative paradigms, query plans, rewrites, indexing) - applications. Large scale analytics and machine learning are outside of the scope of this course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Papers from scientific conferences and journals. References will be given as part of the course material during the semester. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | This course is not intended for Computer Science and Data Science students. Computer Science and Data Science students interested in Big Data MUST attend the Master's level Big Data lecture, offered in Fall. Requirements: programming knowledge (Java, C++, Python, PHP, ...) as well as basic knowledge on databases (SQL). If you have already built your own website with a backend SQL database, this is perfect. Attendance is especially recommended to those who attended Information Systems for Engineers last Fall, which introduced the "good old databases of the 1970s" (SQL, tables and cubes). However, this is not a strict requirement, and it is also possible to take the lectures in reverse order. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 101-0526-00L | Introduction to Visual Machine Perception for Architecture, Construction and Facility Management | W | 3 KP | 2G | I. Armeni | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course is an introduction to Visual Machine Perception technology, and specifically Computer Vision and Machine Learning, for Architecture, Construction, and Facility Management (ACFM). It will explore fundamentals in these Artificial Intelligence (AI) technologies in a tight reference to three applications in ACFM, namely architectural design, construction renovation, and facility management. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | By the end of the course students will develop computational thinking related to visual machine perception applications for the ACFM domain. Specifically, they will: -Gain a fundamental understanding of how this technology works and the impact it can have in the ACFM industry by being exposed to example applications. -Be able to identify limitations, pitfalls, and bottlenecks in these applications. -Critically think on solutions for the above issues. -Acquire hands-on experience in creatively thinking and designing an application given a base system. -Use this course as a “stepping-stone” or entry-point to Machine Learning-intensive courses offered in D-BAUG and D-ARCH. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The past few years a lot of discussion has been sparked on AI in the Architecture, Construction, and Facility Management (ACFM) industry. Despite advancements in this interdisciplinary field, we still have not answered fundamental questions about adopting and adapting AI technology for ACFM. In order to achieve this, we need to be equipped with rudimentary knowledge of how this technology works and what are essential points to consider when applying AI to this specific domain. In addition, the availability of sensors that collect visual data in commodity hardware (e.g., mobile phone and tablet), is creating an even bigger pressure in identifying ways that new technology can be leveraged to increase efficiency and decrease risk in this trillion-dollar industry. However, cautious and well-thought steps need to be taken in the right direction, in order for such technologies to thrive in an industry that showcases inertia in technological adoption. The course will unfold as two parallel storylines that intersect in multiple places: 1) The first storyline will introduce fundamentals in computer vision and machine learning technology, as building blocks that one should consider when developing related applications. These blocks will be discussed with respect to latest developments (e.g., deep neural networks), pointing out their impact in the final solution. 2) The second storyline consists of 3 ACFM processes, namely architectural design, construction renovation, and facility management. These processes will serve as application examples of the technological storyline. In the points of connection students will see the importance of taking into account the application requirements when designing an AI system, as well as their impact on the building blocks. Guest speakers from both the AI and ACFM domains will complement the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | The course does not require any background in AI, Computer Science, coding, or the ACFM domain. It is designed for students of any background and knowledge on these topics. Despite being an introductory class, it will still engage advanced students in the aforementioned topics. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 051-0912-22L | Seminarwoche Frühjahrssemester 2022  Belegung möglich und erforderlich vom 7.-11. Februar 2022. Weitere Infos s. Kursbeschrieb. | W | 2 KP | 3A | Dozent/innen | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Mit verschiedenen Lehrinhalten, obligatorisch für Studierende aller Semester. Programme werden jeweils am ersten Semestertag publiziert. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Die Studierenden werden in die Lage versetzt, eng umschriebene Sachfragen in kleinen Unterrichtsgruppen und in direktem Kontakt mit den Dozierenden an spezifischen Orten zu diskutieren. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Mit verschiedenen Lehrinhalten, obligatorisch für Studierende aller Semester. Programme werden jeweils am ersten Semestertag publiziert. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Einschreibefenster offen vom 7.-11.2.2022. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 363-1065-00L | Design Thinking: Human-Centred Solutions to Real World Challenges Information and application: http://sparklabs.ch/ | W | 5 KP | 5G | A. Cabello Llamas, S. Brusoni, L. Cabello | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The goal is to engage in multidisciplinary collaboration to tackle real world problems. Following a design thinking approach, students work in teams to solve a two design challenges. The 1st is virtual and builds upon digital content into customer discovery, problem definition, ideation and prototyping. The 2nd is in collaboration with an external project partner and goes deeper into application. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | During the course, students will learn about different design thinking methods and tools. This will enable them to: - Generate deep insights through the systematic observation and interaction of key stakeholders (empathy). - Engage in collaborative ideation with a multidisciplinary team. - Rapidly prototype and iteratively test ideas and concepts by using various materials and techniques. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The purpose of this course is to equip the students with methods and tools to tackle a broad range of problems. Following a Design Thinking approach, the students will learn how to observe and interact with key stakeholders in order to develop an in-depth understanding of what is truly important and emotionally meaningful to the people at the center of a problem. Based on these insights, the students ideate on possible solutions and immediately validated them through quick iterations of prototyping and testing using different tools and materials. Design Thinking is a deeply human process that taps into the creative abilities we all have, but that get often overlooked by more conventional problem solving practices. It relies on our ability to be intuitive, to recognize patterns, to construct ideas that are emotionally meaningful as well as functional, and to express ourselves through means beyond words or symbols. Design Thinking provides an integrated way by incorporating tools, processes and techniques from design, engineering, the humanities and social sciences to identify, define and address diverse challenges. This integration leads to a highly productive collaboration between different disciplines. For more information visit: http://sparklabs.ch/ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Open mind, ability to manage uncertainty and to work with students from various background. Class attendance and active participation is crucial as much of the learning occurs through the work in teams during class hours. Therefore, attendance is obligatory for every session. Please also note that the group work outside class is an essential element of this course, so that students must expect an above-average workload. Please note that the class is designed for full-time MSc students. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 063-0640-22L | Advanced Computational Design ITA Pool information event on the offered courses: 9.2.22, 10-11 am, ONLINE https://ethz.zoom.us/j/61932735301 | W | 3 KP | 3G | B. Dillenburger | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | In this course we will discuss how strategies of Artificial Intelligence such as Machine Learning or Evolutionary Strategies can be used in the design process. Principal concepts of computational geometry for architecture will be connected with methods to automatically generate, evaluate and search for design solutions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Students will understand programming basics, and will learn how to control geometry using code. They will learn to translate a design concept into an algorithmic approach - or vice versa - and will obtain an awareness of potentials and limitations of AI in the design phase. Students will deepen their knowledge in customizing existing CAD software such as Rhino using scripting. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | In this course we will discuss how concepts of Artificial Intelligence can be used in the design process. In tutorials and exercises, we will explore the use strategies such as Machine Learning or Evolutionary Strategies to turn the computer from a drawing instrument into an active partner in design, extending both the imagination and the intuition of the designer. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Successful completion of the course "Structural Design VI" (063-0606-00L), "Design III" (052-0541/43/45) or "Das Digitale in der Architektur" (063-0610-00L) are recommended ITA Pool information event on the offered courses: 9.2.22, 10-11h, ONLINE https://ethz.zoom.us/j/61932735301 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 063-0610-22L | The Digital in Architecture ITA Pool information event on the offered courses: 9.2.22, 10-11 h, ONLINE https://ethz.zoom.us/j/61932735301 | W | 2 KP | 1V + 2U | F. Gramazio, M. Kohler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | In lecture series coupled with a series of taught exercises, the course establishes a conceptual framework of digital fabrication in architecture. The exercises focus on simple yet powerful methods of digital, computational and algorithmic design. Two seminar sessions open a debate on the digital as a driving force of a future building and architecture culture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Students develop an understanding of the digital and its concepts in architecture and of current developments in the field of digital fabrication. Students learn about design strategies based on digital methods and are able to relate these to their own design approach and its wider context at the Department of Architecture. In the exercises, they learn to use Rhino 5 / Grasshopper and write their first code in Python. The aim is to equip students with the necessary intellectual and technical skills that allow them to independently deepen their engagement with the digital in the chosen design studios. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The course consists of a lecture series coupled with a series of taught exercises. Departing from the work of Gramazio Kohler Research, the lectures establish a conceptual framework of the digital in architecture with special regard to digital fabrication. The exercises focus on simple yet powerful methods of digital, computational and algorithmic design. Two seminar sessions are dedicated to an open debate on the digital as a driving force of a future building and architecture culture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | ITA Pool information event on the offered courses: 9.2.22, 10-11h, ONLINE https://ethz.zoom.us/j/61932735301 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 052-0568-22L | Raumakustik | W | 2 KP | 2G | K. Eggenschwiler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Einfluss von Form und Material auf die Sprach- und Musik-Hörsamkeit in Räumen. Besonderen Anforderungen an akustisch sensible Räume wie Schulzimmer, Musikzimmer, Theater, Konzertsäle, Opernhäuser und Kirchen (historischen und neue Bauten). Moderne Berechnungs- und Beurteilungsverfahren. Einführung in die Beschallungstechnik für Sprache. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Die Studierenden sollen in die Lage versetzt werden, den Stellenwert der Raumakustik zu erkennen und einfache Räume selbständig akustisch projektieren zu können. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Zu Beginn wird versucht, die Aufmerksamkeit auf die akustische Dimension des Raumes zu lenken, ohne die anderen Wahrnehmungsbereiche auszuschliessen. Dann wird der Einfluss von Form und Material auf die Sprach- und Musik-Hörsamkeit in Räumen an Beispielen und mit Hilfe der spezifischen Werkzeuge der technischen Akustik untersucht. Es werden die besonderen Anforderungen akustisch sensibler Räume wie Schulzimmer, Musikzimmer, Theater, Konzertsäle, Opernhäuser und Kirchen theoretisch und an historischen sowie neuen Bauten diskutiert. Moderne Berechnungs und Beurteilungsverfahren werden dargestellt und es wird eine kleine Einführung in die Beschallungstechnik für Sprache gegeben. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Ein Skript ist zu Beginn der Vorlesung erhältlich. Präsentationen und zusätzliche Dokumente werden auf der Lernplattform abgelegt | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 052-0638-22L | Building Integrated Photovoltaics (BIPV) - Workshop Only for BSc students from 5th/6th semester and MSc students. There are few places left (10.6.22) This course is offered the last time in FS22! | W | 2 KP | 3G | A. Schlüter | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The weeklong workshop will focus on building integrated photovolatics (BiPV). Students will be introduced to theory, methods and tools to support them in developing demonstrator objects in teams in ITA's Robotic Fabrication Lab (RFL). The week program also includes an industry site visit and final presentations. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | On successful completion of the course, students will be able to: 1) explain the principles of BIPV and the relevant aspects of designing with solar materials (e.g. principles of the photovoltaic effect and solar glass properties); 2) assess the effects of the position of the sun, solar irradiance and design choices on PV system performance with basic calculations and tools; 3) fabricate PV demonstrator objects and demonstrate various PV designs 4) explain secondary functions of BIPV and how this relates to conventional construction; and 5) explain environmental benefits and market drivers of BIPV. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Program Overview M / Session 1 / Welcome & Introduction M / Session 2 / Input Lecture on Theory & Methods M / Session 3 / Input Lecture on Tools M / Session 4 / Demonstrator Object Group Work Tu / Sessions 1-2 / Industry Site Visit Tu / Session 3-4 / Demonstrator Object Group Work W / Sessions 1 / Feedback Session W / Session 2-4 / Demonstrator Object Group Work Th / Sessions 1 / Feedback Session Th / Session 2-4 / Demonstrator Object Group Work F / Sessions 1-2 / Exhibit Installation F / Session 3-4 / Presentation & Feedback Sessions with External Reviewers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | 1) Energy & Climate Systems 1&2, Building Systems 1&2 or equivalent coursework is prerequisite; 2) 1 week workshop: September 12-16, 2022! 3) Application open until July 1, 2022! Apply with CV, concise motivation letter and your current Transcript of Records to: illias.hischier@arch.ethz.ch. 4) Material costs are included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 363-1164-00L | Topics in Energy and Climate Policy Participation is limited to 20 students. A mandatory prerequisite is to attend the Energy Economics and Policy course offered by MTEC in FS 2022. | W | 1.5 KP | 1V | M. Filippini, S. Srinivasan | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The seminar offers students the possibility to deepen their knowledge on energy and climate policy issues by presenting and discussing some scientific papers that analyse the economic aspects of energy and climate policy instruments. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | After taking this course, students will be able to: • Engage in, participate and learn from discussion on the design, implementation and effectiveness of energy and climate policy instruments. • Read, present and discuss scientific papers that analyse issues in energy and climate policy critically. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | During the course of Energy Economics and Policy, which is a prerequisite for this course, the students will be learning the basic principles and ideas in a frontal instruction-oriented style. This course is additionally offered to those interested students who want to further deepen their knowledge of topics in energy economics and policy. This block seminar will take place on a Friday afternoon and Saturday as a retreat, and it will adopt a more participatory approach where students will actively present and discuss some topics in energy and climate policy. This block course will take place at the end of the spring semester. We will be discussing papers dealing with the following topics: Participation in the course will be limited to 20 students. • Economics of market-oriented policy measures such as taxes and subsidies • Economics of non-market-oriented policy instruments such as standards, regulations, information policies, nudges, etc. • Application of energy and climate policy instruments with a focus on developing countries including topics related to mobility, electrification, and pollution. The students will receive a proposal of a series of scientific papers at the beginning of the semester, during an introductory meeting, from which to choose one to present to the participants of the seminar. The presentation can be individual or in groups, depending on the number of participants. The student assessment will be based on their presentation as well as on their discussion of the other papers that are presented. Participation in the course will be limited to 20 students, and a mandatory prerequisite is to attend the Energy Economics and Policy course offered by MTEC in FS2022. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 101-0531-00L | Digitalization for Circular Construction (D4C^2) All students who register go onto a waiting list and 25 of them will be selected by the lecturer | W | 4 KP | 9P | C. De Wolf | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Students will learn about digital innovations for circular construction (e.g. reuse of materials) through hands-on learning: they will be accompanied on demolition sites to recover and reclaim building materials, they will learn how to use computational tools to design structures with an available stock of materials, and they will use digital fabrication techniques to build a dome on campus. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The project has several goals: •Teach students about the challenges of reuse in the built environment and how to overcome them in order to transition the construction sector from a linear to a circular economy – this can only be done through the proposed industry collaboration and hands-on, on-site learning. •Show students how to design and built from A to Z: many engineering and architecture students end up acquiring amazing design skills, but have never been on a demolition site to disassemble the structure themselves – this course will offer this experience to them. •Demonstrate how we can bring together two worlds that are often too distinct: low-impact construction and digital innovation – this course will explore which digital tools already used in other sectors could be beneficial for reuse and low-carbon construction. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This is a workshop-based course on circular construction on-site. During the first workshop, students will use photogrammetry from drone imagery and LiDAR scanning to capture data on building materials; Scan-to-BIM techniques for geometric reconstruction based on point-clouds; and computer-vision techniques for identifying material geometries, types, and conditions in order to make an inventory of available materials. During the second workshop, my industry partners (e.g., Baubüro in situ, Materiuum, Rotor) and I will work with the students on the disassembly of the building in a non-destructive way. During the third workshop, students will learn to use computational design tools to structurally optimize their structure’s shape with the available stock of materials. Finally, during the fourth workshop, students will build a dome structure with the reclaimed materials on the ETH campus. This class will enable students to explore all digital tools available (assessment, disassembly, design, and reassembly) for circular construction on a real-world case study. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Workshop-based course & hands-on learning. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Sustainability – Circular Economy in the Digital Age special issue Çetin, S., De Wolf, C., Bocken, N. “Circular Digital Built Environment: An Emerging Framework.” 13, 6348, DOI: 10.3390/su13116348 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Interest in Digitalisation and Construction. MIBS students: 3rd semester on higher are eligible to apply. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 252-0840-02L | Anwendungsnahes Programmieren mit Python | W | 2 KP | 2G | L. E. Fässler, M. Dahinden | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Diese Lehrveranstaltung vermittelt wichtige Basiskonzepte zur Bearbeitung interdisziplinärer Programmierprojekte mit Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Die Studierenden können... - selbstständig Aufgabenstellungen als Programm codieren, Programme testen und Fehler beheben. - bestehenden Programmcode verstehen, hinterfragen und verbessern. - mit der Komplexität realer Daten umgehen. - Daten in einer geeigneten Datenstruktur speichern. - Modelle aus den Naturwissenschaften als Simulation umzusetzen. - Zufallsexperimente durchführen und die Resultate interpretieren. - Standard-Algorithmen erklären und anwenden. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | In der Vorlesung werden folgende Basis-Konzepte behandelt: 1. Variablen und Datentypen 2. Kontrollstrukturen und Logik 3. Sequentielle Datentypen, Such- und Sortieralgorithmen, Simulationen 4. Funktionen, Module und Animationen 5. Matrizen, Zufallsexperimente und Zelluläre Automaten. 6. Klassen und Objekte Im praktischen Teil der Lehrveranstaltung werden selbstständig kleine Programmierprojekte mit naturwissenschaftlichem Kontext bearbeitet. Als Vorbereitung werden elektronische Tutorials bereitgestellt. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | L. Fässler, M. Dahinden, D. Komm, and D. Sichau: Einführung in die Programmierung mit Python und Matlab. Begleitunterlagen zum Onlinekurs und zur Vorlesung, 2016. ISBN: 978-3741250842. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Für diese Lehrveranstaltung werden keine Vorkenntnisse vorausgesetzt. Sie basiert auf anwendungsorientiertem Lernen. Den grössten Teil der Arbeit verbringen die Studierenden damit, Programmierprojekte mit naturwissenschaftlichen Daten zu bearbeiten und die Resultate mit Assistierenden zu diskutieren. Für die Aneignung der Programmier-Grundlagen stehen elektronische Tutorials zur Verfügung. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 151-0928-00L | CO2 Capture and Storage and the Industry of Carbon-Based Resources | W | 4 KP | 3G | M. Mazzotti, A. Bardow, V. Becattini, P. Eckle, N. Gruber, M. Repmann, T. Schmidt, D. Sutter | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course introduces the fundamentals of carbon capture, utilization, and storage and related interdependencies between technosphere, ecosphere, and sociosphere. Topics covered: origin, production, processing, and resource economics of carbon-based resources; climate change in science & policies; CC(U)S systems in power & industrial plants; CO2 transport & storage. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The lecture aims to introduce carbon dioxide capture, utilization, and storage (CCUS) systems, the technical solutions developed so far, and current research questions. This is done in the context of the origin, production, processing, and economics of carbon-based resources and of climate change issues. After this course, students are familiar with relevant technical and non-technical issues related to the use of carbon resources, climate change, and CCUS as a mitigation measure. The class will be structured in 2 hours of lecture and one hour of exercises/discussion. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The transition to a net-zero society is associated with major challenges in all sectors, including energy, transportation, and industry. In the IPCC Special Report on Global Warming of 1.5 °C, rapid emission reduction and negative emission technologies are crucial to limiting global warming to below 1.5 °C. Therefore, this course illuminates carbon capture, utilization, and storage as a potential set of technologies for emission mitigation and for generating negative emissions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Lecture slides and supplementary documents will be available online. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | IPCC Special Report on Global Warming of 1.5°C, 2018. http://www.ipcc.ch/report/sr15/ IPCC AR5 Climate Change 2014: Synthesis Report, 2014. www.ipcc.ch/report/ar5/syr/ IPCC Special Report on Carbon dioxide Capture and Storage, 2005. www.ipcc.ch/activity/srccs/index.htm The Global Status of CCS: 2014. Published by the Global CCS Institute, Nov 2014. http://www.globalccsinstitute.com/publications/global-status-ccs-2014 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | External lecturers from the industry and other institutes will contribute with specialized lectures according to the schedule distributed at the beginning of the semester. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 052-0640-22L | Climate Responsive Architecture with Hive Online course offer. ITA Pool information event on the offered courses: 9.2.22, 10-11h, ONLINE https://ethz.zoom.us/j/61932735301 | W | 1 KP | 2G | A. Schlüter | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This Online course provides an introduction to climate-responsive design using the Hive tool and how to apply it in early building design stages. Hive allows architecture and building science students to understand the relation between architectural design, climate, comfort and energy. Hive is a plugin for the 3D modeling environment Rhino and its visual programming interface Grasshopper. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | • Recall general principles of climate responsive design and examples of it. • Utilize 3D building geometries to conduct simplified energy demand and supply simulations. • Observe relevant physical principles and interactions between climate, energy and geometry. • Implement passive and active concepts for Climate Responsive Design. • Apply Hive for building design analysis and integrate it into own designs or in design courses. • Identify and harness synergies and trade-offs between climate, energy and architectural design aspects. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The course can be frequented individually, or as a prerequisite for other courses such as the master course Climate and Energy Systems 3 or architectural design studios. Modules: 1. Course overview. 2. Introduction to climate responsive design. 3. Introduction to Rhino, Grasshopper and HIVE. 4. Early solar analyses. 5. Passive Solar Design (E.g. Fixed and movable shading). 6. Active Solar Design (E.g. Using Photovoltaics). 7. Real- world Applications and Examples. This is a blended-learning self-paced ONLINE COURSE that can be started at any time. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | A working Rhino 6 or 7 license is necessary. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 701-1252-00L | Climate Change Uncertainty and Risk: From Probabilistic Forecasts to Economics of Climate Adaptation Number of participants limited to 50. | W | 3 KP | 2V + 1U | D. N. Bresch, R. Knutti | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course introduces the concepts of predictability, probability, uncertainty and probabilistic risk modelling and their application to climate modeling and the economics of climate adaptation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Students will acquire knowledge in uncertainty and risk quantification (probabilistic modelling) and an understanding of the economics of climate adaptation. They will become able to construct their own uncertainty and risk assessment models (in Python), hence basic understanding of scientific programming forms a prerequisite of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The first part of the course covers methods to quantify uncertainty in detecting and attributing human influence on climate change and to generate probabilistic climate change projections on global to regional scales. Model evaluation, calibration and structural error are discussed. In the second part, quantification of risks associated with local climate impacts and the economics of different baskets of climate adaptation options are assessed – leading to informed decisions to optimally allocate resources. Such pre-emptive risk management allows evaluating a mix of prevention, preparation, response, recovery, and (financial) risk transfer actions, resulting in an optimal balance of public and private contributions to risk management, aiming at a more resilient society. The course provides an introduction to the following themes: 1) basics of probabilistic modelling and quantification of uncertainty from global climate change to local impacts of extreme events 2) methods to optimize and constrain model parameters using observations 3) risk management from identification (perception) and understanding (assessment, modelling) to actions (prevention, preparation, response, recovery, risk transfer) 4) basics of economic evaluation, economic decision making in the presence of climate risks and pre-emptive risk management to optimally allocate resources | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Powerpoint slides will be made available. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Many papers for in-depth study will be referred to during the lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Hands-on experience with probabilistic climate models and risk models will be acquired in the tutorials; hence good understanding of scientific programming forms a prerequisite of the course, in Python (teaching language, object oriented) or similar. Basic understanding of the climate system, e.g. as covered in the course 'Klimasysteme' is required. Examination: graded tutorials during the semester (benotete Semesterleistung) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0649-00L | International Development Engineering | W | 1 KP | 2V | I. Günther, K. Shea, E. Tilley | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | In this seminar, students will learn from researchers around the globe about technological interventions designed to improve human and economic development within complex, low-resource setting. Students will also get familiar with frameworks from social sciences and engineering, helping them to understand, and evaluate the discussed technologies and to put them into a broader context. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | • Students will get familiar with frameworks from social sciences and engineering needed for innovation in a complex, low-resource setting. • Students will learn about concrete examples of technological interventions designed to improve sustainable development and critically reflect on them. • Students get a broad understanding of some of the most important issues and discussions related to global sustainable development. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | In the introductory class, students will learn about challenges related to global sustainable developments and how they have developed over time. Students will then get exposed to frameworks from social sciences and engineering disciplines, which will help them analyze technologies designed for low-resource settings. In the remaining sessions thought leaders from the field of development engineering will present a wide range of innovations from sectors such as health, water and sanitation, education and governance that will then get discussed with students. Since many of this thought leaders will come from around the globe at least 50% of sessions will be online. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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