Browsing by Author "Turrin, Michela"

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Citation - WoS: 37
Citation - Scopus: 52
Acoustic absorbers by additive manufacturing
(PERGAMON-ELSEVIER SCIENCE LTD, 2014) Foteini Setaki; Martin Tenpierik; Michela Turrin; Arjan van Timmeren; Turrin, Michela; van Timmeren, Arjan; Tenpierik, Martin; Setaki, Foteini
Acoustic design has a large impact on comfort in the built environment, and reduction of noise by means of sound absorption plays a crucial role in acoustic design. Depending on the peculiarities of functions and spaces acoustic design requires a variety of customized solutions. However current sound absorbers have limitations in being tailored to the specific acoustic requirements of a space, these limitations mostly regard geometry and materials and are related mainly to design and fabrication limitations. In order to investigate solutions for highly customized sound absorbers this research focuses on absorbers based on the passive destructive interference principle (PDI). This choice is due to the close relationship between geometry and acoustic performance which is peculiar of PDI absorbers. When focusing on customized geometry fabrication techniques become crucial for the project feasibility. In this paper this aspect is addressed with reference to additive manufacturing which allows for the fabrication of unique pieces even in case of complex and freeform geometries. Focusing on these aspects this paper presents the preliminary results of research at TU Delft. The first phase of this research focused on laboratory tests measuring the sound absorption coefficient of samples fabricated with additive manufacturing. This allowed understanding the acoustics underlying the performance behaviour. In the second phase the acoustic rules have been formulated into guidelines relating geometric factors to acoustic performance, and in parametric relations between performance and geometric design parameters. Finally a case study has been developed. (C) 2013 Elsevier Ltd. All rights reserved.
Engineering Performance Simulations in Architectural Design Conception Atrium in Shenyang: a case study on thermal mass
(Education and research in Computer Aided Architectural Design in Europe, 2013) Michela Turrin; Ioannis Chatzikonstantinou; Martin J. Tenpierik; I. Sevil Sariyildiz; Turrin, Michela; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Tenpierik, Martin; R. Stouffs , S. Sariyildiz
The paper tackles the integration of engineering performance simulations in the conceptual phase of architectural design with specific focus on parametric design processes. A general framework is exemplified in which the use of performance simulations and the learning process of the designer are discussed in relation to the parameterization process. A specific case study is presented more in details regarding the design of an atrium for the reuse of an existing building in Shenyang-China. Performance simulations concerning the thermal comfort in the atrium are presented and discussed in relation to the general framework. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 9
Citation - Scopus: 16
Impacts of problem scale and sampling strategy on surrogate model accuracy: An application of surrogate-based optimization in building design
(Institute of Electrical and Electronics Engineers Inc., 2016) Ding Yang; Yimin Sun; Danilo Di Stefano; Michela Turrin; I. Sevil Sariyildiz; di Stefano, Danilo; Turrin, Michela; Sariyildiz, Sevil; Sun, Yimin; Yang, Ding
Surrogate-based Optimization is a useful approach when the objective function is computationally expensive to evaluate compared to Simulation-based Optimization. In the surrogate-based method analytically tractable 'surrogate models' (also known as 'Response Surface Models - RSMs' or 'metamodels') are constructed and validated for each optimization objective and constraint at relatively low computational cost. They are useful for replacing the time-consuming simulations during the optimization, quickly locating the area where the optimum is expected to be for further search, and gaining insight into the global behavior of the system. Nevertheless there are still concerns about the surrogate model accuracy and the number of simulations necessary to get a reasonably accurate surrogate model. This paper aims to unveil: 1) the possible impacts of problem scale and sampling strategy on the surrogate model accuracy, and 2) the potential of Surrogatebased Optimization in finding high quality solutions for building envelope design optimization problems. For this purpose a series of multi-objective optimization test cases that mainly consider daylight and energy performance were conducted within the same time frame. Then the results were compared in pair based on which discussions were made. Finally the corresponding conclusions were obtained after the comparative study. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 38
Citation - Scopus: 52
Multi-zone optimisation of high-rise buildings using artificial intelligence for sustainable metropolises. Part 1: Background methodology setup and machine learning results
(Elsevier Ltd, 2021) Berk Ekici; Tugce Kazanasmaz; Michela Turrin; M. Fatih Tasgetiren; I. Sevil Sariyildiz; Ekici, Berk; Turrin, Michela; Tasgetiren, M. Fatih; Sariyildiz, I. Sevil; Kazanasmaz, Z. Tugce
Designing high-rise buildings is one of the complex tasks of architecture because it involves interdisciplinary performance aspects in the conceptual phase. The necessity for sustainable high-rise buildings has increased owing to the demand for metropolises based on population growth and urbanisation trends. Although artificial intelligence (AI) techniques support swift decision-making when addressing multiple performance aspects related to sustainable buildings previous studies only examined single floors because modelling and optimising the entire building requires extensive computational time. However different floor levels require various design decisions because of the performance variances between the ground and sky levels of high-rises in dense urban districts. This paper presents a multi-zone optimisation (MUZO) methodology to support decision-making for an entire high-rise building considering multiple floor levels and performance aspects. The proposed methodology includes parametric modelling and simulations of high-rise buildings as well as machine learning and optimisation as AI methods. The specific setup focuses on the quad-grid and diagrid shading devices using two daylight metrics of LEED: spatial daylight autonomy and annual sunlight exposure. The parametric model generated samples to develop surrogate models using an artificial neural network. The results of 40 surrogate models indicated that the machine learning part of the MUZO methodology can report very high prediction accuracies for 31 models and high accuracies for six quad-grid and three diagrid models. The findings indicate that the MUZO can be an important part of designing high-rises in metropolises while predicting multiple performance aspects related to sustainable buildings during the conceptual design phase. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 28
Citation - Scopus: 35
Multi-zone optimisation of high-rise buildings using artificial intelligence for sustainable metropolises. Part 2: Optimisation problems algorithms results and method validation
(Elsevier Ltd, 2021) Berk Ekici; Tugce Kazanasmaz; Michela Turrin; M. Fatih Tasgetiren; I. Sevil Sariyildiz; Ekici, Berk; Turrin, Michela; Tasgetiren, M. Fatih; Sariyildiz, I. Sevil; Kazanasmaz, Z. Tugce
High-rise building optimisation is becoming increasingly relevant owing to global population growth and urbanisation trends. Previous studies have demonstrated the potential of high-rise optimisation but have been focused on the use of the parameters of single floors for the entire design, thus the differences related to the impact of the dense surroundings are not taken into consideration. Part 1 of this study presents a multi-zone optimisation (MUZO) methodology and surrogate models (SMs) which provide a swift and accurate prediction for the entire building design, hence the SMs can be used for optimisation processes. Owing to the high number of parameters involved in the design process the optimisation task remains challenging. This paper presents how MUZO can cope with an enormous number of parameters to optimise the entire design of high-rise buildings using three algorithms with an adaptive penalty function. Two design scenarios are considered for quad-grid and diagrid shading devices glazing type and building-shape parameters using the setup and the SMs developed in part 1. The optimisation part of the MUZO methodology reported satisfactory results for spatial daylight autonomy and annual sunlight exposure by meeting the Leadership in Energy and Environmental Design standards in 19 of 20 optimisation problems. To validate the impact of the methodology optimised designs were compared with 8748 and 5832 typical quad-grid and diagrid scenarios respectively using the same design parameters for all floor levels. The findings indicate that the MUZO methodology provides significant improvements in the optimisation of high-rise buildings in dense urban areas. © 2021 Elsevier B.V. All rights reserved.
pCOLAD: online sharing of parameters for collaborative architectural design
(Education and research in Computer Aided Architectural Design in Europe, 2014) Hans J.C. Hubers; Michela Turrin; Irem Erbas; Ioannis Chatzikonstantinou; Turrin, Michela; Erbas, Irem; Chatzikonstantinou, Ioannis; Hubers, Hans J. C.; E.M. Thompson
Simultaneous interdisciplinary architectural design from the very start of a project faces challenges in properly sharing information across disciplines. This research developed a method and related digital tool to improve collaborative design and aimed at making selected information to be shared faster and more transparently. The method consists of developing alternative parametric solutions for different parts of the design in such a way that crucial parameters form a link between these parts. The digital tool has been developed for Grasshopper and permits synchronic (real-time over the Internet) and a-synchronic sharing of these parameters. The design alternatives are evaluated with specific criteria pros and cons in an Internet Forum and discussed via a video-conferencing tool. Decisions are then taken in a collaborative manner through voting. The paper describes the method based on a case study. © 2024 Elsevier B.V. All rights reserved.
Citation - Scopus: 2
Performance-based parameterization strategies
(2013) Michela Turrin; Rudi Stouffs; I. Sevil Sariyildiz; Turrin, Michela; Sariyildiz, Sevil; Stouffs, Rudi
In this paper alternative approaches to structure the parametric geometry in relation to information on various performances are described and exemplified. They relate to different levels of knowledge that concern the performances considered in the process and which are available to the designer while the parametric model is being set. Atheoretic framework embeds the different approaches for which the use of parametric modelling is structured in three phases: strategy-definition, model-building, and solution-assessment. The phases and their interrelations are discussed. Finally four case studies are presented focusing on the relation between the knowledge available in strategy-definition and the exploration occurring in solution-assessment. © 2013 The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) Hong Kong and Center for Advanced Studies in Architecture (CASA) Department of Architecture-NUS Singapore. © 2014 Elsevier B.V. All rights reserved.
Citation - WoS: 1
PERFORMANCE-BASED PARAMETERIZATION STRATEGIES A theoretic framework and case studies
(CAADRIA-ASSOC COMPUTER-AIDED ARCHITECTURAL DESIGN RESEARCH ASIA, 2013) Michela Turrin; Rudi Stouffs; Sevil Sariyildiz; Turrin, Michela; Sariyildiz, Sevil; Stouffs, Rudi; R Stouffs; P Janssen; S Roudavski; B Tuncer
In this paper alternative approaches to structure the parametric geometry in relation to information on various performances are described and exemplified. They relate to different levels of knowledge that concern the performances considered in the process and which are available to the designer while the parametric model is being set. Atheoretic framework embeds the different approaches for which the use of parametric modelling is structured in three phases: strategy-definition, model-building, and solution-assessment. The phases and their interrelations are discussed. Finally four case studies are presented focusing on the relation between the knowledge available in strategy-definition and the exploration occurring in solution-assessment.
Citation - WoS: 99
Citation - Scopus: 115
Performative computational architecture using swarm and evolutionary optimisation: A review
(Elsevier Ltd, 2019) Berk Ekici; Cemre Cubukcuoglu; Michela Turrin; I. Sevil Sariyildiz; Ekici, Berk; Turrin, Michela; Sariyildiz, I. Sevil; Cubukcuoglu, Cemre
This study presents a systematic review and summary of performative computational architecture using swarm and evolutionary optimisation. The taxonomy for one hundred types of studies is presented herein that includes different sub-categories of performative computational architecture such as sustainability cost functionality and structure. Specifically energy daylight solar radiation environmental impact thermal comfort life-cycle cost initial and global costs energy use cost space allocation logistics structural assessment and holistic design approaches are investigated by considering their corresponding performance aspects. The main findings including optimisation and all the types of parameters are presented by focussing on different aspects of buildings. In addition usage of form-finding parameters of all reviewed studies and the distributions for each performance objectives are also presented. Moreover usage of swarm and evolutionary optimisation algorithms in reviewed studies is summarised. Trends in publications published years problem scales and building functions are examined. Finally future prospects are highlighted by focussing on different aspects of performative computational architecture in accordance to the evidence collected based on the review process. © 2018 Elsevier B.V. All rights reserved.
Citation - Scopus: 14
Sports building envelope optimization using Multi-objective Multidisciplinary Design Optimization (M-MDO) techniques
(Institute of Electrical and Electronics Engineers Inc., 2015) Ding Yang; Michela Turrin; I. Sevil Sariyildiz; Yimin Sun; Turrin, Michela; Sariyildiz, Sevil; Sun, Yimin; Yang, Ding
Sports building envelopes are complex systems involving multiple architectural and engineering performance requirements that are sometimes in conflict with each other. Typically daylight usage and energy efficiency as two primary concerns in building envelope design are of those conflicting aspects. To improve overall performance (including daylight and energy performance) by changing the geometries of the envelope windows and shading elements as well as the selection of construction materials Multi-objective Optimization (MOO) is a natural choice. Based on the generated Pareto front trade-off decisions between competing performance objectives can be made. However as the number of design variables from different disciplines increases the huge design space and the specialization of disciplines make the optimization process less efficient. Therefore two possible Multidisciplinary Design Optimization (MDO) frameworks namely Individual Disciplinary Feasible (i.e. IDF a single-level MDO framework) and Collaborative Optimization (i.e. CO a bi-level MDO framework) are investigated to combine with MOO. Resorting to the capability of MDO in decomposition and coordination between different disciplines parallel disciplinary simulations and/or bi-level optimizations can be realized which compresses design cycle time and achieves better overall performance. Through the combination of MOO and MDO Multi-objective Multidisciplinary Design Optimization (M-MDO or multi-objective MDO) problems are expected to be solved more effectively and efficiently. The whole process of the proposed method consists of three phases (i.e. preprocessing solution and post-processing phases) in which variable screening multi-objective MDO solving and Pareto front comparison are performed respectively. An ongoing real project located in China is used as a case study to test the proposed method. For now the research work is in the preprocessing phase. Preliminary observations and results are obtained and future research is discussed. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 6
Sports Building Envelope Optimization Using Multi-objective Multidisciplinary Design Optimization (M-MDO) Techniques Case of Indoor Sports Building Project in China
(IEEE, 2015) Ding Yang; Michela Turrin; Sevil Sariyildiz; Yimin Sun; Turrin, Michela; Sariyildiz, Sevil; Sun, Yimin; Yang, Ding
Sports building envelopes are complex systems involving multiple architectural and engineering performance requirements that are sometimes in conflict with each other. Typically daylight usage and energy efficiency as two primary concerns in building envelope design are of those conflicting aspects. To improve overall performance (including daylight and energy performance) by changing the geometries of the envelope windows and shading elements as well as the selection of construction materials Multi-objective Optimization (MOO) is a natural choice. Based on the generated Pareto front trade-off decisions between competing performance objectives can be made. However as the number of design variables from different disciplines increases the huge design space and the specialization of disciplines make the optimization process less efficient. Therefore two possible Multidisciplinary Design Optimization (MDO) frameworks namely Individual Disciplinary Feasible (i.e. IDF a single-level MDO framework) and Collaborative Optimization (i.e. CO a bi-level MDO framework) are investigated to combine with MOO. Resorting to the capability of MDO in decomposition and coordination between different disciplines parallel disciplinary simulations and/or bi-level optimizations can be realized which compresses design cycle time and achieves better overall performance. Through the combination of MOO and MDO Multi-objective Multidisciplinary Design Optimization (M-MDO or multi-objective MDO) problems are expected to be solved more effectively and efficiently. The whole process of the proposed method consists of three phases (i.e. preprocessing solution and post-processing phases) in which variable screening multi-objective MDO solving and Pareto front comparison are performed respectively. An ongoing real project located in China is used as a case study to test the proposed method. For now the research work is in the preprocessing phase. Preliminary observations and results are obtained and future research is discussed.
Citation - WoS: 1
Citation - Scopus: 1
The Human Factor - Introducing Game Mechanics to Computerized Home Automation Systems User experience as a method for reducing consumption in domestic buildings
(ECAADE-EDUCATION & RESEARCH COMPUTER AIDED ARCHITECTURAL DESIGN EUROPE, 2013) Itai Cohen; Michela Turrin; Florian Heinzelmann; Ivo Welzner; Turrin, Michela; Cohen, Itai; Welzner, Ivo; Heinzelmann, Florian; R Stouffs; S Sariyildiz
A method of integration of game mechanics and game dynamics into a user interface for a home automation system as means of reducing the inhabitant's environmental footprint is described and detailed up to the point of proof of concept. In detail the paper describes the game framework and the method in which the competitive game could be balanced between different dwellings to ensure a fair game. A unique and intuitive method of control via smartphone is described that aims at making the interaction with the device and game more intrusive and friendly. This method is prototyped and tested to the stage of proof of concept.