An Approach to Urban Quarter Design Using Building Generative Design and Thermal Performance Optimization

AbstractBuildings thermal performance is influenced by the urban context, such as adjacent buildings shadows, block wind paths, or solar radiation reflection. For this reason, in this paper, an automated procedure is used to generate and optimize buildings’ thermal performance in a closed O-shape urban quarter with ten building blocks to determine the importance of including the surroundings in estimating the buildings’ thermal behavior. The overall shape of the urban quarter is pre-designed, being mainly residential, with several stores in the ground floor and limited to three levels. Each building will have four alternative designs created using a hybrid evolutionary strategy technique that generates building's floor plans according to practitioner's preferences and requirements. Then, a sequential variable optimization procedure coupled with dynamic simulation engine is used to explore the improvement potential of each solution by changing and adding several building elements. The final quarter design is determined by combining the best of all buildings’ solutions from thermal performance criteria.The results demonstrate the influence of urban context in the resulting building's thermal performance. Despite the building's shape is similar in the four solutions, these have significant thermal behavior difference due to their interior organization and position in the urban quarter. A comparison analysis is carried out between all building block designs. The buildings, which have exterior walls with openings facing south, have almost half degree-hours of thermal discomfort due to the combination of large openings and shading overhangs. It is also possible to conclude that generative tools, enhanced with optimization procedures, may help practitioners in designing more energy efficient buildings

Recent developments in the optimization of the bulk heterojunction morphology of polymer: Fullerene solar cells

Organic photovoltaic (OPV) devices, made with semiconducting polymers, have recently attained a power conversion efficiency (PCE) over 14% in single junction cells and over 17% in tandem cells. These high performances, together with the suitability of the technology to inexpensive large-scale manufacture, over lightweight and flexible plastic substrates using roll-to-roll (R2R) processing, place the technology amongst the most promising for future harvesting of solar energy. Although OPVs using non-fullerene acceptors have recently outperformed their fullerene-based counterparts, the research in the development of new fullerenes and in the improvement of the bulk-heterojunction (BHJ) morphology and device efficiency of polymer:fullerene solar cells remains very active. In this review article, the most relevant research works performed over the last 3 years, that is, since the year 2016 onwards, in the field of fullerene-based polymer solar cells based on the copolymers PTB7, PTB7-Th (also known as PBDTTT-EFT) and PffBT4T-2OD, are presented and discussed. This review is primarily focused on studies that involve the improvement of the BHJ morphology, efficiency and stability of small active area devices (typically 2), through the use of different processing strategies such as the use of different fullerene acceptors, different processing solvents and additives and different thermal treatments.HG thanks Fundação para a Ciência e a Tecnologia (FCT) for a PhD scholarship (SFRH/BD/103009/ 2014). FF thanks Fundação para a Ciência e a Tecnologia (FCT) for the financial support to QOPNA (FCT UID/QUI/00062/2013). GB and AM are thankful to POCI-01-0145-FEDER-006939 (Laboratory for Process Engineering, Environment, Biotechnology and Energy—UID/EQU/00511/2013) funded by the European Regional Development Fund (ERDF), through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) and by national funds, through FCT—Fundação para a Ciência e a Tecnologia and NORTE-01-0145-FEDER-000005—LEPABE-2-ECO-INNOVATION, supported by North Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 687008. HG and JCV acknowledge funding by National Funds through FCT—Portuguese Foundation for Science and Technology, Reference UID/CTM/50025/2013 and FEDER funds through the COMPETE 2020 Programme under the project number POCI-01-0145-FEDER-007688 (i3N).info:eu-repo/semantics/publishedVersio

Energy and exergy-based indicators

SUMMARY The current increase of the energy consumption of buildings requires new approaches to solve economic, environmental and regulatory issues. Exergy methods are thermodynamic tools searching for sources of inefficiencies in energy conversion systems that the current energy techniques may not identify. Desiccant cooling systems (DCS) are equipments applied to dehumidifying and cooling air streams, which may provide reductions of primary energy demand relatively to conventional air-conditioning units. In this study, a detailed thermodynamic analysis of open-cycle DCS is presented. It aims to assess the overall energy and exergy performance of the plant and identify its most inefficient sub-components, associated to higher sources of irreversibilities. The main limitations of the energy methods are highlighted, and the opportunities given by exergy approach for improving the system performance are properly identified. As case study, using a pre-calibrated TRNSYS model, the overall energy and exergy efficiency of the plant were found as 32.2% and 11.8%, respectively, for a summer week in Mediterranean climate. The exergy efficiency defect identified the boiler (69.0%) and the chiller (12.3%) as the most inefficient components of the plant, so their replacement by high efficient systems is the most rational approach for improving its performance. As alternative heating system to the boiler, a set of different technologies and integration of renewables were proposed and evaluated applying the indicators: primary energy ratio (PER) and exergy efficiency. The heating system fuelled by wood was found as having the best primary energy performance (PER = 109.6%), although the related exergy efficiency is only 11.4%. The highest exergy performance option corresponds to heat pump technology with coefficient of performance (COP) = 4, having a PER of 50.6% and exergy efficiency of 28.2%. Additionally, the parametric analyses conducted for different operating conditions indicate that the overall irreversibility rate increases moderately for larger cooling effects and more significant for higher dehumidification rates. Copyright © 2013 John Wiley & Sons, Ltd

Online survey for collective clustering of computer generated architectural floor plans

The aim of this study is to understand what are the collective actions of architecture practitioners when grouping floor plan designs. The understanding of how professionals and students solve this complex problem may help to develop specific programmes for the teaching of architecture. In addition, the findings of this study can help in the development of query mechanisms for database retrieval of floor plans and the implementation of clustering mechanisms to aggregate floor plans resulting from generative design methods. The study aims to capture how practitioners define similarity between floor plans from a pool of available designs. A hybrid evolutionary strategy is used, which takes into account the building's functional program to generate alternative floor plan designs. The first step of this methodology consisted in an online survey to gather information on how the respondents would perform a clustering task. Online surveys have been used in several applications and are a method of data collection that conveys several advantages. When properly developed and implemented, a survey portrays the characteristics of large groups of respondents on a specific topic and allows assessing its representation. Several types of surveys are available; e.g. questionnaire and interview formats, phone survey, and online surveys, which can be coupled with inference engines that act and direct the survey according to respondents' answers. In the present study, the survey was posed as an online exercise in which respondents had to perform a pre-defined task, which makes it similar to running an experiment in an online environment. The experiment aimed to understand the perception and criteria of the target population to perform the clustering task by comparing the results with the respondents' answers to a questionnaire presented at the end of the exercise