Population ageing has become a domain of international discussions and research throughout the spectrum of disciplines including housing, urban planning, and real estate. Older people are encouraged to continue living in their homes in their familiar environment, and this is referred to as “ageing-in-place”. Enabling one to age-in-place requires new housing arrangements that facilitate and enable older adults to live comfortably into old age, preferably with others. Innovative examples are provided from a Dutch social housing association, illustrating a new approach to environmental design that focuses more on building new communities in conjunction with the building itself, as opposed to the occupational therapeutic approaches and environmental support. Transformation projects, referred to as “Second Youth Experiments”, are conducted using the Røring method, which is based on the principles of co-creation. De Benring in Voorst, The Netherlands, is provided as a case study of an innovative transformation project. This project shows how social and technological innovations can be integrated in the retrofitting of existing real estate for older people. It leads to a flexible use of the real estate, which makes the building system- and customer preference proof. Original article at: https://doi.org/10.3390/buildings8070089 © 2018 by the authors. Licensee MDPI.
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In the housing market enormous challenges exist for the retrofitting of existing housing in combination with the ambition to realize new environmentally friendly and affordable dwellings. Bio-based building materials offer the possibility to use renewable resources in building and construction. The efficient use of bio-based building materials is desirable due to several potential advantages related to environmental and economic aspects e.g. CO2 fixation and additional value. The potential biodegradability of biomaterials however demands also in-novative solutions to avoid e.g. the use of environmental harmful substances. It is essential to use balanced technological solutions, which consider aspects like service life or technical per-formance as well as environmental aspects. Circular economy and biodiversity also play an im-portant role in these concepts and potential production chains. Other questions arise considering the interaction with other large biomass users e.g. food production. What will be the impact if we use more bio-based building materials with regard to biodiversity and resource availability? Does this create opportunities or risks for the increasing use of bio-based building materials or does intelligent use of biomass in building materials offer the possibility to apply still unused (bio) resources and use them as a carbon sink? Potential routes of intelligent usage of biomass as well as potential risks and disadvantages are highlighted and discussed in relation to resource efficiency and decoupling concept(s).
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Buildings need to be carefully operated and maintained for optimum health, comfort, energy performance, and utility costs. The increasing use of Machine Learning combined with Big Data in the building services sector has shown the potential to bring energy efficiency and cost-effectiveness. Therefore, upskilling and reskilling the current workforce is required to realize new possibilities. In addition, sharing and preserving knowledge are also required for the sustainable growth of professionals and companies. This formed the basis for the Dutch Research Council funded TransAct project. To increase access to education on the job, online learning is experiencing phenomenal growth. A study was conducted with two focus groups - professionals of a building service company and university researchers - to understand the existing challenges and the ways to improve knowledge sharing and upskilling through learning on the job. This study introduced an Enterprise Social Network platform that connects members and may facilitate knowledge sharing. As a community forum, Yammer from office 365 was used. For hosting project files, a SharePoint page was created. For online courses, the company’s online learning site was utilized. The log data from the online tools were analysed, semi-structured interviews and webinars were conducted and feedback was collected with google forms. Incentive models like social recognition and innovative project results were used to motivate the professionals for online activities. This paper distinguishes the impacts of initiatives on the behaviour of university researchers vs company employees.
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The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
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Assessment of the seismic vulnerability of the building stock in the earthquake-prone Marmara region of Turkey is of growing importance since such information is needed for reliable estimation of the losses that possible future earthquakes are likely to induce. The outcome of such loss assessment exercises can be used in planning of urban/regional-scale earthquake protection strategies; this is a priority in Turkey, particularly following the destructive earthquakes of 1999. Considering the size of the building inventory, Istanbul and its surrounding area is a case for which it is not easy to determine the structural properties and characteristics of the building stock. In this paper, geometrical, functional and material properties of the building stock in the northern Marmara Region, particularly around Istanbul, have been investigated and evaluated for use in loss estimation models and other types of statistic- or probability-based studies. In order to do that, the existing reinforced concrete (RC) stock has been classified as 'compliant' or 'non-compliant' buildings, dual (frame-wall) or frame structures and emergent or embedded-beam systems. In addition to the statistical parameters such as mean values, standard deviations, etc., probability density functions and their goodness-of-fit have also been investigated for all types of parameters. Functionalities such as purpose of use and floor area properties have been defined. Concrete properties of existing and recently constructed buildings and also characteristics of 220 and 420 MPa types of steel have been documented. Finally, the financial effects of retrofitting operations and damage repair have been investigated. © 2007 Elsevier Ltd. All rights reserved.
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This paper investigates the limits and efficacies of the Fiber Reinforced Polymer (FRP) material for strengthening mid-rise RC buildings against seismic actions. Turkey, the region of the highest seismic risk in Europe, is chosen as the case-study country, the building stock of which consists in its vast majority of mid-rise RC residential and/or commercial buildings. Strengthening with traditional methods is usually applied in most projects, as ordinary construction materials and no specialized workmanship are required. However, in cases of tight time constraints, architectural limitations, durability issues or higher demand for ductile performance, FRP material is often opted for since the most recent Turkish Earthquake Code allows engineers to employ this advanced-technology product to overcome issues of inadequate ductility or shear capacity of existing RC buildings. The paper compares strengthening of a characteristically typical mid-rise Turkish RC building by two methods, i.e., traditional column jacketing and FRP strengthening, evaluating their effectiveness with respect to the requirements of the Turkish Earthquake Code. The effect of FRP confinement is explicitly taken into account in the numerical model, unlike the common procedure followed according to which the demand on un-strengthened members is established and then mere section analyses are employed to meet the additional demands.
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B4B is a multi-year, multi-stakeholder project focused on developing methods to harness big data from smart meters, building management systems and the Internet of Things devices, to reduce energy consumption, increase comfort, respond flexibly to user behaviour and local energy supply and demand, and save on installation maintenance costs. This will be done through the development of faster and more efficient Machine Learning and Artificial Intelligence models and algorithms. The project is geared to existing utility buildings such as commercial and institutional buildings.
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The design of healthcare facilities is a complex and dynamic process, which involves many stakeholders each with their own set of needs. In the context of healthcare facilities, this complexity exists at the intersection of technology and society because the very design of these buildings forces us to consider the technology–human interface directly in terms of living-space, ethics and social priorities. In order to grasp this complexity, current healthcare design models need mechanisms to help prioritize the needs of the stakeholders. Assistance in this process can be derived by incorporating elements of technology philosophy into existing design models. In this article, we develop and examine the Inclusive and Integrated Health Facilities Design model (In2Health Design model) and its foundations. This model brings together three existing approaches: (i) the International Classification of Functioning, Disability and Health, (ii) the Model of Integrated Building Design, and (iii) the ontology by Dooyeweerd. The model can be used to analyze the needs of the various stakeholders, in relationship to the required performances of a building as delivered by various building systems. The applicability of the In2Health Design model is illustrated by two case studies concerning (i) the evaluation of the indoor environment for older people with dementia and (ii) the design process of the redevelopment of an existing hospital for psychiatric patients.
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One of the most complex and urgent challenges in the energy transition is the large‐scale refurbishment of the existing housing stock in the built environment. In order to comply with the goals of the Paris convention, the aim is to live “energy‐neutral,’’ that is, a dwelling should produce as much sustainable energy as it consumes on a yearly basis. This means that millions of existing houses need to undergo a radical energy retrofit. In the next 30 years, all dwellings should be upgraded to nearly zero‐energy buildings, which is a challenge to accomplish for a reasonable price. Across the EU, many projects have developed successful approaches to the improvement of building technologies and processes, as well a better involvement of citizens. It is important to compare and contrast such approaches and disseminate lessons learned.In practice, it is crucial to raise the level of participation of inhabitants in neighborhood renovation activities. Therefore,the central question of this issue is: How can we increase the involvement of tenants and homeowners into this radicalenergy renovation?
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The urgency for developing a circular economy is growing, and more and more companies and organisations are concerned with the importance of adapting their business to fit a changing economy. However, many analyses on the circular economy are still rather abstract and there is a lack of understanding about what circularity would mean for specific industries. This insufficient insight especially seems to be apparent in the building and construction sector. Besides, the building and construction sector is responsible for a major part of energy use and emissions. To tackle the issue of insufficient insight into the business consequences of circular developments, further research is necessary. Therefore, we propose to collaborate on a research project that aims to provide a more detailed level of analysis. The goal is to identify drivers and barriers to make better use of materials in the building and construction sector. This further research would benefit from an international collaboration between universities of applied sciences and industry from different European countries. An additional benefit of the applied orientation would be the relevance for professional education programmes. The article is published in the proceedings of the conference : http://dx.doi.org/10.4995/CARPE2019.2019.10582 Publisher Editorial Universitat Politècnica de València, 2019 www.lalibreria.upv.es / Ref.: 6523_01_01_01 Creative Commons Atribution-NonCommercial-NonDetivates-4.0 Int.
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