{"b2a7a7dfa98271586f9e8d6bf1b43224itft-puma":{"DOI":"10.1002/stab.70009","ISBN":"","ISSN":"0038-9145","URL":"https://onlinelibrary.wiley.com/doi/10.1002/stab.70009","abstract":"Angesichts des steigenden Energiebedarfs im Gebäudebetrieb gewinnt die Entwicklung adaptiver Fassadensysteme zunehmend an Bedeutung. Insbesondere solaraktive Gebäudehüllen bieten Potenzial, durch gezielte Steuerung von Sonneneinstrahlung, Belüftung und Tageslichtnutzung den Energieverbrauch zu senken und gleichzeitig den Nutzerkomfort zu erhöhen. Das Forschungsprojekt FlectoLine-Fassade verfolgt das Ziel, intelligente, materialbasierte adaptive Fassadenlösungen ohne klassische Antriebs- und Steuerungssysteme zu realisieren. Im Zentrum stehen dabei flexible Faltelemente, die auf bioinspirierten, nachgiebigen Mechanismen basieren und sich durch die elastische Verformbarkeit von FVK-Platten ohne Gelenke auszeichnen. Durch integrierte pneumatische Aktuatoren, präzise programmierte Materialsysteme und gezielte Differenzierung der Steifigkeiten kann eine kontrollierte Faltbewegung bis 90° erreicht werden. Neben einem Hybridmaterialsystem wurde eine thermoplastische Variante entwickelt, die einfacher zu fertigen und recycelbar ist. Umfangreiche Belastungstests belegen die Langlebigkeit beider Systeme. Ergänzend wurden flexible Photovoltaikzellen integriert, um Energie zu gewinnen. Ein digitaler Zwilling mit Sensorik und Wetterdaten steuert die Fassade in Echtzeit. Der Demonstrator mit 101 individuell verformbaren Elementen auf 83,5 m2 zeigt die technische Umsetzbarkeit und das energetische Potenzial adaptiver Fassadentechnologien der nächsten Generation.\r\n\r\nIn view of the increasing energy demand in building operations, the development of adaptive façade systems is gaining growing importance. In particular, solar-active building envelopes offer potential to reduce energy consumption through targeted control of solar radiation, ventilation, and daylight use, while simultaneously increasing user comfort. The research project FlectoLine Façade aims to realize intelligent, material-based adaptive façade solutions without conventional drive and control systems. At its core are flexible folding elements based on bio-inspired, compliant mechanisms characterized by elastic deformability of fibre-reinforced composite (FRC) panels without joints. Through integrated pneumatic actuators, precisely programmed material systems, and targeted differentiation of stiffness, a controlled folding movement of up to 90° can be achieved. In addition to a hybrid material system, a thermoplastic variant was developed that is easier to manufacture and recyclable. Extensive load tests demonstrate the durability of both systems. Furthermore, flexible photovoltaic cells were integrated to generate energy. A digital twin with sensors and weather data controls the façade in real time. The demonstrator with 101 individually deformable elements covering 83.5 m2 demonstrates the technical feasibility and the energetic potential of next-generation adaptive façade technologies.","annote":"","author":[{"family":"Körner","given":"Axel"},{"family":"Martin","given":"Edith Anahi Gonzalez San"},{"family":"Born","given":"Larissa"},{"family":"Ridder","given":"Matthias"},{"family":"Moser","given":"Stephan"},{"family":"Weitlaner","given":"Robert"},{"family":"Gresser","given":"Götz T."},{"family":"Knippers","given":"Jan"}],"citation-label":"Korner.2025","collection-editor":[],"collection-title":"","container-author":[],"container-title":"Stahlbau","documents":[],"edition":"","editor":[],"event-date":{"date-parts":[["2025","10"]],"literal":"2025"},"event-place":"","id":"b2a7a7dfa98271586f9e8d6bf1b43224itft-puma","interhash":"f15df303e6bf81a97566df307eddcfc2","intrahash":"b2a7a7dfa98271586f9e8d6bf1b43224","issue":"","issued":{"date-parts":[["2025","10"]],"literal":"2025"},"keyword":"biomimetic voltaic photo reinforced digital responsive digitaler Zwilling machine compliant actuation Bionik Kunststoff fibre Mechanismen Fassade Lernen learning pneumatische plastic twin adaptive faserverstärkter Photovoltaik maschinelles pneumatic nachgiebige façade Aktuatorik mechanisms","misc":{"language":"ger eng","file":"K{\\\"o}rner, Martin et al 2025 - FlectoLine:Attachments/K{\\\"o}rner, Martin et al 2025 - FlectoLine.pdf:application/pdf","issn":"0038-9145","doi":"10.1002/stab.70009"},"note":"","number":"","page":"","page-first":"","publisher":"","publisher-place":"","status":"","title":"FlectoLine: eine adaptive Fassade für nachhaltige Architektur\r\nFlectoLine: A responsive Façade for sustainable architecture","type":"article-journal","username":"itft-puma","version":"","volume":""},"48571bf42f9b3e1b94b541f568cd4f0fisw-bibliothek":{"DOI":"10.23919/ECC64448.2024.10591213","ISBN":"","ISSN":"","URL":"","abstract":"Rack-and-pinion drives are commonly used in large machine tools to provide linear motion of heavy loads over long travel distances. A key concern in this context is the achievable path accuracy, which is limited by assembly and manufacturing tolerances of the gearing components in conjunction with load-dependent deformation and the inherent backlash of the system. To address this issue, this paper presents a method for robust modeling of the individual and state-dependent transmission errors of a drive utilizing a two-stage machine learning approach. Based on this, the position control is extended to include an error compensation, which suppresses the modeled deviations in the mechanical system including the position-dependent backlash. The achievable increase in path accuracy as well as the robustness of the approach are evaluated and quantified by an experimental validation on a system with industry standard components.","annote":"","author":[{"family":"Steinle","given":"Lukas"},{"family":"Leipe","given":"Valentin"},{"family":"Lechler","given":"Armin"},{"family":"Veri","given":"Alexander"}],"citation-label":"10591213","collection-editor":[],"collection-title":"","container-author":[],"container-title":"2024 European Control Conference (ECC)","documents":[],"edition":"","editor":[],"event-date":{"date-parts":[["2024","06"]],"literal":"2024"},"event-place":"","id":"48571bf42f9b3e1b94b541f568cd4f0fisw-bibliothek","interhash":"fc115f1ff8efe474a50ffb3153d44a85","intrahash":"48571bf42f9b3e1b94b541f568cd4f0f","issue":"","issued":{"date-parts":[["2024","06"]],"literal":"2024"},"keyword":"tool feed error machine compensation learning isw drive","misc":{"doi":"10.23919/ECC64448.2024.10591213"},"note":"","number":"","number-of-pages":"6","page":"2441-2447","page-first":"2441","publisher":"","publisher-place":"","status":"","title":"Learning Compensation of the State-Dependent Transmission Errors in Rack-and-Pinion Drives","type":"paper-conference","username":"isw-bibliothek","version":"","volume":""},"dcbd7d1383b2d1fb49e78e5c2a25817aisw-bibliothek":{"DOI":"10.1016/j.cirp.2022.03.026","ISBN":"","ISSN":"","URL":"https://doi.org/10.1016%2Fj.cirp.2022.03.026","abstract":"","annote":"","author":[{"family":"Verl","given":"Alexander"},{"family":"Steinle","given":"Lukas"}],"citation-label":"Verl_2022","collection-editor":[{"family":"Technology","given":"CIRP Annals Manufacturing"}],"collection-title":"","container-author":[{"family":"Technology","given":"CIRP Annals Manufacturing"}],"container-title":"CIRP Annals","documents":[],"edition":"","editor":[{"family":"Technology","given":"CIRP Annals Manufacturing"}],"event-date":{"date-parts":[["2022"]],"literal":"2022"},"event-place":"","id":"dcbd7d1383b2d1fb49e78e5c2a25817aisw-bibliothek","interhash":"2089008983eb6ff2a8073a674a8ff704","intrahash":"dcbd7d1383b2d1fb49e78e5c2a25817a","issue":"1","issued":{"date-parts":[["2022"]],"literal":"2022"},"keyword":"tool Learning Compensation Feed drive Machine","misc":{"doi":"10.1016/j.cirp.2022.03.026"},"note":"","number":"1","number-of-pages":"3","page":"345--348","page-first":"345","publisher":"Elsevier BV","publisher-place":"","status":"","title":"Adaptive compensation of the transmission errors in rack-and-pinion drives","type":"article-journal","username":"isw-bibliothek","version":"","volume":"71"},"5ffc94d275983812893472d515d4aae8mariedavidova":{"DOI":"","ISBN":"","ISSN":"","URL":"http://papers.cumincad.org/cgi-bin/works/paper/caadria2020_069","abstract":"","annote":"","author":[{"family":"Davidová","given":"Marie"},{"family":"Zavoleas","given":"Yannis"}],"citation-label":"davidova2020postaanthropocene","collection-editor":[{"family":"Holzer","given":"Dominik"},{"family":"Nakapan","given":"Walaiporn"},{"family":"Globa","given":"Anastasia"},{"family":"Koh","given":"Immanuel"}],"collection-title":"","container-author":[{"family":"Holzer","given":"Dominik"},{"family":"Nakapan","given":"Walaiporn"},{"family":"Globa","given":"Anastasia"},{"family":"Koh","given":"Immanuel"}],"container-title":"CAADRIA 2020: Re:Anthropocene - Design in the Age of Humans","documents":[],"edition":"","editor":[{"family":"Holzer","given":"Dominik"},{"family":"Nakapan","given":"Walaiporn"},{"family":"Globa","given":"Anastasia"},{"family":"Koh","given":"Immanuel"}],"event-date":{"date-parts":[["2020"]],"literal":"2020"},"event-place":"","id":"5ffc94d275983812893472d515d4aae8mariedavidova","interhash":"ae995d7d9a6f9e6e1ec1bda740cf3cbe","intrahash":"5ffc94d275983812893472d515d4aae8","issue":"","issued":{"date-parts":[["2020"]],"literal":"2020"},"keyword":"systemic myown biodiversity approach learning architetural performance urban machine morre-than-human to post-Anthropocene","misc":{"ee":"http://dx.doi.org/10.1109/26.231913"},"note":"","number":"","number-of-pages":"9","page":"203-212","page-first":"203","publisher":"Association for Computer Aided Architectural Design in Asia","publisher-place":"","status":"","title":"Post-Anthropocene: The Design after the Human Centered Design Age","type":"paper-conference","username":"mariedavidova","version":"","volume":"2"},"58377687a8e0c39891119950dcc33afemariedavidova":{"DOI":"","ISBN":"","ISSN":"","URL":"http://architecturemps.com/wp-content/uploads/2018/12/AMPS-Proceedings-12-Critical-Practice-in-an-Age-of-Complexity-1.pdf","abstract":"The paper and its presentation is to discuss a family house Spiraling Slope (sophia) that is co-designed, inhabited, tested and developed prototype by the second and third author of this submission, the clients. The eco-systemically performing house, literally twisted as a helix into the sloping terrain, gaining its thermal energy, is also covered by extensive greenery to gain this property on its top. Algae, grown on the glass roof, is to moderate its atrium clime. Through its sloping disposition, the house employs natural ventilation for its airing. Though the first author is conducting research that this performance is operated by nature of material properties (Davidová 2016c), in the time of the house’s design stage, this research was not developed enough to meet the building practice. Therefore, the house’s eco-systemic performance that could not have been reached by biology is achieved through the technology of autonomous environment control (sysloop). Sysloop is a real-time knowledge processing software cowering physical computing, where the clients are the main developer, co-designing with all the other professions involved in the house design and construction, including its architects and systemic designer. Since the house’s design is based on natural performance, both its environmental, social, cultural and practical performance is operated through a computer based system AI that relates to BIG Data, the paper therefore presents one of the first attempts of fusion of abiotic and biotic agency with artificial intelligence in architectural practice. Testing such prototype by life co-living experience brings true insights into its design in time. This approach has been defined by Sevaldson as Time-Based Design at the start of this millennium (Sevaldson 2004; Sevaldson 2005). However, at that time the crucial leading design team member was not at the same time the subject of testing. This brings the Shön’s discussion on ‘reflective practitioner’ (Schön 1983) few steps further. It is not the case when her/his designing and lecturing is enriched by tacit knowledge of i.e. building practice experience, but furthermore, the co-designer’s experience is gained through living within the system s/he is co-designing and co-prototyping in real life and for real life. Therefore, through such case studies, as the approach fuses the life performance with its design and eco-systemic design and living processes, the first author defends to ratify a new design field, Systemic Approach to Architectural Performance that fights for the shift from Anthropocene.","annote":"","author":[{"family":"Davidová","given":"Marie"},{"family":"Pánek","given":"Karel"},{"family":"Pánková","given":"Michaela"}],"citation-label":"noauthororeditor","collection-editor":[{"family":"Bean","given":"Jonathan"},{"family":"Dickinson","given":"Susannah"},{"family":"Ida","given":"Aletheia"}],"collection-title":"","container-author":[{"family":"Bean","given":"Jonathan"},{"family":"Dickinson","given":"Susannah"},{"family":"Ida","given":"Aletheia"}],"container-title":"","documents":[],"edition":"","editor":[{"family":"Bean","given":"Jonathan"},{"family":"Dickinson","given":"Susannah"},{"family":"Ida","given":"Aletheia"}],"event-date":{"date-parts":[["2018"]],"literal":"2018"},"event-place":"","id":"58377687a8e0c39891119950dcc33afemariedavidova","interhash":"73ba92c7c47c76043132af8999a2071e","intrahash":"58377687a8e0c39891119950dcc33afe","issue":"","issued":{"date-parts":[["2018"]],"literal":"2018"},"keyword":"myown biodiversity machine codesign learning life ecosystem gigamapping performance","note":"","number":"","number-of-pages":"9","page":"133-142","page-first":"133","publisher":"University of Arizona","publisher-place":"","status":"","title":"Spiralling Slope as a Real Life Co-Design Laboratory","type":"chapter","username":"mariedavidova","version":"","volume":""},"44f62035c93a24f0d6329be720db5d6dmariedavidova":{"DOI":"","ISBN":"","ISSN":"","URL":"http://architecturemps.com/wp-content/uploads/2018/12/AMPS-Proceedings-12-Critical-Practice-in-an-Age-of-Complexity-1.pdf","abstract":"Unlike preceding “autonomous house systems” sysloop is cross-layered and highly scalable concept of “allopoietic system”, a system that is autonomous though dependent on the exchange across its environment (Dekkers 2015). This is performed through three types of co-design: • co-designing of trans-disciplinary co-authors; • co-designing of environment from which it is learning, users included; • co-designing of artificial intelligence and big data. At the scale of local environment, sysloop is focused mainly on interrelations of individual life space qualities, providing contextual autonomous behaviour across many aspects such as climate, light, sound, smell, safety, access control, etc. Due to such scope, the trans-disciplinary team of experts developing sysloop technology is evolving in time in reference to related fields. We specify key aspects of an alternative information system with ability to make decisions based on automated interpretation of meanings, instead of (conventional) symbol processing. We verify such information system in practice of environment automation, introducing technological support of overlapping values such as information hygiene, lifelong learning, aesthetics, overall comfort, etc. Such environments are integrated at “buildings” units scale in phenomenological terms and at “industrial” units scale focused on adaptive automation and reliability engineering, both processing micro-sensorial data and performing qualified decision making in real-time. These together with other big data available are integrated to support the “cities’” scale layer. This layer is to serve for informed city planning and emergency situations solutions, including automated, personalised assistance to individual citizens, etc. This multi-scaled system is feedback looping across its layers of scales and types of co-design and thus evolving by data and most importantly, its ever-changing relations. It gives to the term “smart buildings” its meaning across the scales towards sustainable development, performance and ecosystems. The authors, among all the team, built the first prototypical family and office building for real-world testing and further development. This “real life co-design laboratory” is elaborated at separate paper for this conference.","annote":"","author":[{"family":"Pánek","given":"Karel"},{"family":"Davidová","given":"Marie"}],"citation-label":"noauthororeditor","collection-editor":[{"family":"Bean","given":"Jonathan"},{"family":"Dickinson","given":"Susannah"},{"family":"Ida","given":"Aletheia"}],"collection-title":"","container-author":[{"family":"Bean","given":"Jonathan"},{"family":"Dickinson","given":"Susannah"},{"family":"Ida","given":"Aletheia"}],"container-title":"","documents":[],"edition":"","editor":[{"family":"Bean","given":"Jonathan"},{"family":"Dickinson","given":"Susannah"},{"family":"Ida","given":"Aletheia"}],"event-date":{"date-parts":[["2018"]],"literal":"2018"},"event-place":"","id":"44f62035c93a24f0d6329be720db5d6dmariedavidova","interhash":"662f443905d1502dd9ff1e6a844d1474","intrahash":"44f62035c93a24f0d6329be720db5d6d","issue":"","issued":{"date-parts":[["2018"]],"literal":"2018"},"keyword":"responsive myown systems machine codesign learning architecture intelligent","note":"","number":"","number-of-pages":"9","page":"132-141","page-first":"132","publisher":"University of Arizona","publisher-place":"","status":"","title":"sysloop","type":"chapter","username":"mariedavidova","version":"","volume":""},"f784ea9b6e4531d6f5d88103ed300f8cisw-bibliothek":{"DOI":"","ISBN":"978-3-662-53806-7","ISSN":"","URL":"","abstract":"Cyber physical systems (CPS) are changing the way machine tools function and operate. As the CAD-CAM-CNC tool chain gains intelligence the boundaries of the elements of the tool chain become blurred and new features, based on advancements in artificial intelligence can be integrated. The main task of the CAD-CAM-CNC chain is to generate the cutter trajectories for the manufacturing operation. Driven by sustainability and the need for capacity, the need arises to optimize the paths through this tool chain. In this paper a concept for path optimization with reinforcement learning is proposed, with focus on the reward function, specific to tool path optimization via the channel method.","annote":"","author":[{"family":"Dripke","given":"Caren"},{"family":"Höhr","given":"Sara"},{"family":"Csiszar","given":"Akos"},{"family":"Verl","given":"Alexander"}],"citation-label":"10.1007/978-3-662-53806-7_1","collection-editor":[{"family":"Beyerer","given":"Jürgen"},{"family":"Niggemann","given":"Oliver"},{"family":"Kühnert","given":"Christian"}],"collection-title":"","container-author":[{"family":"Beyerer","given":"Jürgen"},{"family":"Niggemann","given":"Oliver"},{"family":"Kühnert","given":"Christian"}],"container-title":"Machine Learning for Cyber Physical Systems","documents":[],"edition":"","editor":[{"family":"Beyerer","given":"Jürgen"},{"family":"Niggemann","given":"Oliver"},{"family":"Kühnert","given":"Christian"}],"event-date":{"date-parts":[["2017"]],"literal":"2017"},"event-place":"Berlin, Heidelberg","id":"f784ea9b6e4531d6f5d88103ed300f8cisw-bibliothek","interhash":"c73c7ba4b206589bfe506d040073c60d","intrahash":"f784ea9b6e4531d6f5d88103ed300f8c","issue":"","issued":{"date-parts":[["2017"]],"literal":"2017"},"keyword":"automation cnc machine learning","misc":{"isbn":"978-3-662-53806-7"},"note":"","number":"","number-of-pages":"7","page":"1--8","page-first":"1","publisher":"Springer Berlin Heidelberg","publisher-place":"Berlin, Heidelberg","status":"","title":"A Concept for the Application of Reinforcement Learning in the Optimization of CAM-Generated Tool Paths","type":"paper-conference","username":"isw-bibliothek","version":"","volume":""},"2e462c4831ee144a8e452f10fa7c21beisw-bibliothek":{"DOI":"10.1109/M2VIP.2017.8211457","ISBN":"","ISSN":"","URL":"","abstract":"","annote":"","author":[{"family":"Csiszar","given":"A."},{"family":"Eilers","given":"J."},{"family":"Verl","given":"A."}],"citation-label":"8211457","collection-editor":[],"collection-title":"","container-author":[],"container-title":"2017 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","documents":[],"edition":"","editor":[],"event-date":{"date-parts":[["2017","11"]],"literal":"2017"},"event-place":"","id":"2e462c4831ee144a8e452f10fa7c21beisw-bibliothek","interhash":"21c14e75583b366ad70399bf46602bde","intrahash":"2e462c4831ee144a8e452f10fa7c21be","issue":"","issued":{"date-parts":[["2017","11"]],"literal":"2017"},"keyword":"robotics, machine learning","misc":{"doi":"10.1109/M2VIP.2017.8211457"},"note":"","number":"","number-of-pages":"5","page":"1-6","page-first":"1","publisher":"","publisher-place":"","status":"","title":"On solving the inverse kinematics problem using neural networks","type":"paper-conference","username":"isw-bibliothek","version":"","volume":""},"015b4f7373b8f6d62bf3fd6818abd3d3isw-bibliothek":{"DOI":"","ISBN":"","ISSN":"","URL":"","abstract":"","annote":"","author":[{"family":"Csiszar","given":"Akos"},{"family":"Jaensch","given":"Florian"},{"family":"Kienzlen","given":"Annika"},{"family":"Scheifele","given":"Christian"}],"citation-label":"Csiszar.2017","collection-editor":[],"collection-title":"","container-author":[],"container-title":"SPS MAGAZIN","documents":[],"edition":"","editor":[],"event-date":{"date-parts":[["2017"]],"literal":"2017"},"event-place":"","id":"015b4f7373b8f6d62bf3fd6818abd3d3isw-bibliothek","interhash":"f74766ceec573e4a9d96d9773d3beb34","intrahash":"015b4f7373b8f6d62bf3fd6818abd3d3","issue":"12 2017","issued":{"date-parts":[["2017"]],"literal":"2017"},"keyword":"Learning grk2198 Steuerungstechnik Machine","note":"","number":"12 2017","number-of-pages":"2","page":"42--44","page-first":"42","publisher":"","publisher-place":"","status":"","title":"Machine Learning in Steuerungstechnik und Robotik","type":"article-journal","username":"isw-bibliothek","version":"","volume":"30"}}