Een korte Nederlandse uitleg over het concept 'Whole Systems Approach' op basis van het promotie onderzoek van Anu Manickam van het Lectoraat Duurzaam Coöperatief Ondernemen
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The Heating Ventilation and Air Conditioning (HVAC) sector is responsible for a large part of the total worldwide energy consumption, a significant part of which is caused by incorrect operation of controls and maintenance. HVAC systems are becoming increasingly complex, especially due to multi-commodity energy sources, and as a result, the chance of failures in systems and controls will increase. Therefore, systems that diagnose energy performance are of paramount importance. However, despite much research on Fault Detection and Diagnosis (FDD) methods for HVAC systems, they are rarely applied. One major reason is that proposed methods are different from the approaches taken by HVAC designers who employ process and instrumentation diagrams (P&IDs). This led to the following main research question: Which FDD architecture is suitable for HVAC systems in general to support the set up and implementation of FDD methods, including energy performance diagnosis? First, an energy performance FDD architecture based on information embedded in P&IDs was elaborated. The new FDD method, called the 4S3F method, combines systems theory with data analysis. In the 4S3F method, the detection and diagnosis phases are separated. The symptoms and faults are classified into 4 types of symptoms (deviations from balance equations, operating states (OS) and energy performance (EP), and additional information) and 3 types of faults (component, control and model faults). Second, the 4S3F method has been tested in four case studies. In the first case study, the symptom detection part was tested using historical Building Management System (BMS) data for a whole year: the combined heat and power plant of the THUAS (The Hague University of Applied Sciences) building in Delft, including an aquifer thermal energy storage (ATES) system, a heat pump, a gas boiler and hot and cold water hydronic systems. This case study showed that balance, EP and OS symptoms can be extracted from the P&ID and the presence of symptoms detected. In the second case study, a proof of principle of the fault diagnosis part of the 4S3F method was successfully performed on the same HVAC system extracting possible component and control faults from the P&ID. A Bayesian Network diagnostic, which mimics the way of diagnosis by HVAC engineers, was applied to identify the probability of all possible faults by interpreting the symptoms. The diagnostic Bayesian network (DBN) was set up in accordance with the P&ID, i.e., with the same structure. Energy savings from fault corrections were estimated to be up to 25% of the primary energy consumption, while the HVAC system was initially considered to have an excellent performance. In the third case study, a demand-driven ventilation system (DCV) was analysed. The analysis showed that the 4S3F method works also to identify faults on an air ventilation system.
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Designers have grown increasingly interested in social consequences of new technologies. As social impacts become increasingly important it might be fruitful to understand how social impacts develop and how a designer can anticipate these consequences. In health care practices, for instance, it is important to control unintended social impacts at forehand. Social impact is an outcome of the mediating effect of a technology with its social environment. Human behaviour in a social environment can be analysed from the perspective of a social ecological system. To anticipate social impacts simulations of social practices are needed. To simulate practices the persona approach has been adapted to a screenplay approach in which the elements of a social ecology are used to gain a rich description of a social environment. This has been applied for a 'Heart Managers' case. It was concluded that the screenplay approach can be used for a systematic simulation of future social impacts.
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Introduction: The health-promoting school (HPS) approach was developed by the World Health Organization to create health promotion changes in the whole school system. Implementing the approach can be challenging for schools because schools are dynamic organizations with each a unique context. Many countries worldwide have a health promotion system in place in which healthy school (HS) advisors support schools in the process of implementing the HPS approach. Even though these HS advisors can take on various roles to provide support in an adaptive and context-oriented manner, these roles have not yet been described. The current study aims to identify and describe the key roles of the HS advisor when supporting schools during the dynamic process of implementing the HPS approach. Methods: The study was part of a project in which a capacity-building module was developed for and with HS advisors in the Netherlands. In the current study, a co-creation process enabled by participatory research was used in which researchers, HS advisors, national representatives, and coordinators of the Dutch HS program participated. Co-creation processes took place between October 2020 and November 2021 and consisted of four phases: (1) a narrative review of the literature, (2) interviews, (3) focus groups, and (4) a final check. Results: Five roles were identified. The role of “navigator” as a more central one and four other roles: “linking pin,” “expert in the field,” “critical friend,” and “ambassador of the HPS approach.” The (final) description of the five roles was recognizable for the HS advisors that participated in the study, and they indicated that it provided a comprehensive overview of the work of an HS advisor in the Netherlands. Discussion: The roles can provide guidance to all Dutch HS advisors and the regional public health organizations that employ them on what is needed to provide sufficient and context-oriented support to schools. These roles can inspire and guide people from other countries to adapt the roles to their own national context.
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The methodology of biomimicry design thinking is based on and builds upon the overarching patterns that all life abides by. “Cultivating cooperative relationships” within an ecosystem is one such pattern we as humans can learn from to nurture our own mutualistic and symbiotic relationships. While form and process translations from biology to design have proven accessible by students learning biomimicry, the realm of translating biological functions in a systematic approach has proven to be more difficult. This study examines how higher education students can approach the gap that many companies in transition are struggling with today; that of thinking within the closed loops of their own ecosystem, to do good without damaging the system itself. Design students should be able to assess and advise on product design choices within such systems after graduation. We know when tackling a design challenge, teams have difficulties sifting through the mass of information they encounter, and many obstacles are encountered by students and their professional clients when trying to implement systems thinking into their design process. While biomimicry offers guidelines and methodology, there is insufficient research on complex, systems-level problem solving that systems thinking biomimicry requires. This study looks at factors found in course exercises, through student surveys and interviews that helped (novice) professionals initiate systems thinking methods as part of their strategy. The steps found in this research show characteristics from student responses and matching educational steps which enabled them to develop their own approach to challenges in a systems thinking manner. Experiences from the 2022 cohort of the semester “Design with Nature” within the Industrial Design Engineering program at The Hague University of Applied Sciences in the Netherlands have shown that the mixing and matching of connected biological design strategies to understand integrating functions and relationships within a human system is a promising first step. Stevens LL, Whitehead C, Singhal A. Cultivating Cooperative Relationships: Identifying Learning Gaps When Teaching Students Systems Thinking Biomimicry. Biomimetics. 2022; 7(4):184. https://doi.org/10.3390/biomimetics7040184
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Innovations are required in urban infrastructures due to the pressing needs for mitigating climate change and prevent resource depletion. In order to address the slow pace of innovation in urban systems, this paper analyses factors involved in attempts to introduce novel sanitary systems. Today new requirements are important: sanitary systems should have an optimal energy/climate performance, with recovery of resources, and with fewer emissions. Anaerobic digestion has been suggested as an alternative to current aerobic waste water treatment processes. This paper presents an overview of attempts to introduce novel anaerobic sanitation systems for domestic sanitation. The paper identifies main factors that contributed to a premature termination of such attempts. Especially smaller scale anaerobic sanitation systems will probably not be able to compete economically with traditional sewage treatment. However, anaerobic treatment has various advantages for mitigating climate change, removing persistent chemicals, and for the transition to a circular economy. The paper concludes that loss avoidance, both in the sewage system and in the waste water treatment plants, should play a key role in determining experiments that could lead to a transition in sanitation. http://dx.doi.org/10.13044/j.sdewes.d6.0214 LinkedIn: https://www.linkedin.com/in/karel-mulder-163aa96/
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Current methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not consistent with process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to very limited application of energy performance diagnosis in practice. In a previous paper, a generic reference architecture – hereafter referred to as the 4S3F (four symptoms and three faults) framework – was developed. Because it is closely related to the way HVAC experts diagnose problems in HVAC installations, 4S3F largely overcomes the problem of limited application. The present article addresses the fault diagnosis process using automated fault identification (AFI) based on symptoms detected with a diagnostic Bayesian network (DBN). It demonstrates that possible faults can be extracted from P&IDs at different levels and that P&IDs form the basis for setting up effective DBNs. The process was applied to real sensor data for a whole year. In a case study for a thermal energy plant, control faults were successfully isolated using balance, energy performance and operational state symptoms. Correction of the isolated faults led to annual primary energy savings of 25%. An analysis showed that the values of set probabilities in the DBN model are not outcome-sensitive. Link to the formal publication via its DOI https://doi.org/10.1016/j.enbuild.2020.110289
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In spite of renewed attention for practices in tourism studies, the analysis of practices is often isolated from theories of practice. This theoretical paper identifies the main strands of practice theory and their relevance and application to tourism research, and develops a new approach to applying practice theory in the study of tourism participation. We propose a conceptual model of tourism practices based on the work of Collins (2004), which emphasises the role of rituals in generating emotional responses. This integrated approach can focus on individuals interacting in groups, as well as explaining why people join and leave specific practices. Charting the shifting of individuals between practices could help to illuminate the dynamics and complexity of tourism systems.
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In this article a generic fault detection and diagnosis (FDD) method for demand controlled ventilation (DCV) systems is presented. By automated fault detection both indoor air quality (IAQ) and energy performance are strongly increased. This method is derived from a reference architecture based on a network with 3 generic types of faults (component, control and model faults) and 4 generic types of symptoms (balance, energy performance, operational state and additional symptoms). This 4S3F architecture, originally set up for energy performance diagnosis of thermal energy plants is applied on the control of IAQ by variable air volume (VAV) systems. The proposed method, using diagnosis Bayesian networks (DBNs), overcomes problems encountered in current FDD methods for VAV systems, problems which inhibits in practice their wide application. Unambiguous fault diagnosis stays difficult, most methods are very system specific, and finally, methods are implemented at a very late stage, while an implementation during the design of the HVAC system and its control is needed. The IAQ 4S3F method, which solves these problems, is demonstrated for a common VAV system with demand controlled ventilation in an office with the use of a whole year hourly historic Building Management System (BMS) data and showed it applicability successfully. Next to this, the influence of prior and conditional probabilities on the diagnosis is studied. Link to the formal publication via its DOI https://doi.org/10.1016/j.buildenv.2019.106632
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