Current symptom detection methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not standardised and not consistent with HVAC process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to a very limited application of energy performance diagnosis systems in practice. This paper proposes detection methods to overcome these issues, based on the 4S3F (four types of symptom and three types of faults) framework. A set of generic symptoms divided into three categories (balance, energy performance and operational state symptoms) is discussed and related performance indicators are developed, using efficiencies, seasonal performance factors, capacities, and control and design-based operational indicators. The symptom detection method was applied successfully to the HVAC system of the building of The Hague University of Applied Sciences. Detection results on an annual, monthly and daily basis are discussed and compared. Link to the formail publication via its DOI https://doi.org/10.1016/j.autcon.2020.103344
Gepubliceerd in Mikroniek, nr. 6 2018 In manufacturing environments where collaborative robots are employed, conventional computer vision algorithms have trouble in the robust localisation and detection of products due to changing illumination conditions and shadows caused by a human sharing the workspace with the robotic system. In order to enhance the robustness of vision applications, machine learning with neural networks is explored. The performance of machine-learning algorithms versus conventional computer vision algorithms is studied by observing a generic user scenario for the manufacturing process: the assembly of a product by localisation, identification and manipulation of building blocks.
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The design and realization of a healthy indoor environment is a challenge that is investigated from different perspectives at the unit Building Physics and Systems (BPS; Faculty of Architecture, Building and Planning) of Eindhoven University of Technology. Performance requirements (for instance, with respect to air quality, thermal comfort and lighting) and performance based assessment methods are the point-of-departure, focusing at computational techniques supporting the design process. Different specific application fields such as dwellings, offices, schools, but also, operating theatres, churches, musea and multifunctional stadiums, underline the applied approach that is part of the research within the unit. In the design of healthy environments, the performance based design assessment is crucial in arriving at innovative design solutions and optimized indoor and outdoor environments. In this assessment computational support tools and experimental verification play an important role. However, assessing the right indicators in an objective way, applying the correct tools and correct application of these tools is not yet well established. Alongside, developments are still ongoing. The work performed in the unit by the different researchers relates to the research questions that can be derived from this notice. The paper gives an introduction to the Unit BPS and presents a brief overview of recent and ongoing research. An extensive list of references is provided for further reading and supports the conclusion that healthy environments can and should be addressed from a wide angle.
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In the past, textile material was used to add value to buildings in various applications, as well as improving building performance in terms or in terms of building and acoustics properties, and increasing the esthetic value.Textiles are light in weight, easy to shape, strong, insulating, moisture-regulating and can be provided with extra functions. Particularly in areas with an earthquake risk, as well as cases with a temporary demand for flexible shelters, textiles and primary use.
The energy transition is a highly complex technical and societal challenge, coping with e.g. existing ownership situations, intrusive retrofit measures, slow decision-making processes and uneven value distribution. Large scale retrofitting activities insulating multiple buildings at once is urgently needed to reach the climate targets but the decision-making of retrofitting in buildings with shared ownership is challenging. Each owner is accountable for his own energy bill (and footprint), giving a limited action scope. This has led to a fragmented response to the energy retrofitting challenge with negligible levels of building energy efficiency improvements conducted by multiple actors. Aggregating the energy design process on a building level would allow more systemic decisions to happen and offer the access to alternative types of funding for owners. “Collect Your Retrofits” intends to design a generic and collective retrofit approach in the challenging context of monumental areas. As there are no standardised approaches to conduct historical building energy retrofits, solutions are tailor-made, making the process expensive and unattractive for owners. The project will develop this approach under real conditions of two communities: a self-organised “woongroep” and a “VvE” in the historic centre of Amsterdam. Retrofit designs will be identified based on energy performance, carbon emissions, comfort and costs so that a prioritisation strategy can be drawn. Instead of each owner investing into their own energy retrofitting, the neighbourhood will invest into the most impactful measures and ensure that the generated economic value is retained locally in order to make further sustainable investments and thus accelerating the transition of the area to a CO2-neutral environment.
The Northern Netherlands (NN) finds itself at the junction of all the big transitions. Digitalisation is essential to follow through with these. Considering this, our region has the potential to make sizeable progress if it can successfully roll out widespread digitalisation. As a hardcore transition economy, the NN may even join the European frontrunners and act as an example for other regions. It is from this challenge that the NN will start with the European Digital Innovation Hub (EDIH NN). We have chosen to specialise in the area of Autonomous Systems, which includes multiple digital technologies that are relevant for the four transitions in the NN: (1) Smart Agro, (2) Smart Manufacturing, (3) Life Science and Health and (4) Utilities, Built Environment and Mobility. In the first three-year EDIH NN wants to support more than 750 companies and lay the foundation for long-term support of all companies. The following building blocks for EDIH NN are: • A Brokerage network that will identify issues regarding digitalisation and relay these to Solution Providers (high TRL) and knowledge providers (low TRL). • A Test Before Invest network (test and demo facilities) comprising 20+ organisations that will invest in Autonomous Systems within their domain, and collaborate towards becoming a European testing ground. • A Smart Factory Accelerator to strengthen the digital maturity of companies. • An Empowerment programme to strengthen companies in the areas of DEP Technologies: Cyber Security and Artificial Intelligence. • An approach based on High Performance Computing to make digitalisation more accessible. • The Smart Makers Academy: A programme aimed at matching supply and demand around digital skills, based on individual learning outcomes. • A Funding Readiness programme to help companies that need to invest for their digitalisation strategy, in finding funding opportunities. • A network to stimulate supply and demand around Autonomous Systems
