The Soralux Daylighting System: Passive Solar Illumination for Deep-Plan Building Spaces

2011
Projet étudiant

Résumé

Daylight is a valuable resource for both energy and human health. However, this resource is often underutilized in buildings due to the difficulty of controlling the changing qualities of daylight. Deep-plan building spaces pose an especially challenging problem because traditional sidelighting strategies are only effective for workplanes adjacent to the facade. Infrequently adjusted shading systems can also limit the availability of daylight. A number of advanced daylighting systems have been developed that attempt to address these challenges with varying priorities and success. This thesis proposes a new technology named the Soralux Daylighting System. The system is passive, requires no shading adjustments, even under direct sunlight, and works well with deep-plan spaces on the order of 8 to 15 m deep. The Soralux system presents itself as a double-glazing window unit, allowing it to be easily integrated into curtain wall facades typical of deep-plan offices in large cities. Computer simulations using the ray tracing programs Radiance and TracePro were conducted to estimate the annual performance of the system. Variables such as facade orientation, sky obstruction, and climate were evaluated for their effect on system performance. The system was found to increase light levels by a factor of 2 to 10 compared to an unshaded window at depths between 8 and 15 m from the facade. Two physical mockups of the Soralux system were fabricated for testing. The first mockup tested was a small proof-of-concept prototype, while the second was a full-scale mockup which was installed in a Tokyo office building. The physical mockups were used to evaluate visual comfort and appearance. A monitoring campaign was also conducted for the Tokyo mockup and the measured data were compared with a Radiance model of the building space to validate the accuracy of the simulation results. The average error between simulated and measured illuminance values was 16%. Based on these results, recommendations are provided identifying which scenarios are well-suited for the system. The Soralux Daylighting System is scheduled to be permanently installed into a Tokyo office building in 2012.

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https://infoscience.epfl.ch/record/168578?ln=fr

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2011
Projet étudiant

Résumé

Official source

https://infoscience.epfl.ch/record/168578?ln=fr

À propos de ce résultat

Concepts associés (15)

Concepts associés

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Publications associées (15)

Publications associées

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Development and application of a numerical simulation system to evaluate the impact of anthropogenic heat fluxes on urban boundary layer climate

Andrea Krpo

Increasing economic development, and growing population, generated during the last decades a very important growth of cities. Urban regions include nowadays more than half of the global population and, by 2030, this proportion is forecasted to increase to three quarters. A consequent more and more extensive use of natural resources, together with increasing anthropogenic activities such as emissions from traffic and factories, or heating from air-conditioning facilities, modify local climate in many different ways, leading to a progressive degradation of life quality in urban areas. Taking these facts into account, there is nowadays a real need for efficient urban planning guidelines and sustainability policies in order to improve life quality in urban areas. Different points should be considered including urban warming, air pollution, human health, economic, and cooling energy needs. The present work goes in this direction, aiming at developing a simulation system for the study of the complex interactions between buildings and the atmosphere. The system of equations describing atmospheric flows is highly non linear and it is common to employ numerical techniques in order to solve them. Moreover, the representation of urban canopy climate, and related air pollution problems, requiree taking the interaction between urban scale (tens of kilometers), and mesoscale (hundreds of kilometers) processes into account. At first, starting from previous studies, a mesoscale meteorological model has been developed as part of this work. Urban induced processes have been considered by implementing inside the model a detailed urban parameterization scheme developed in a previous work. The scheme is able to capture different urban processes, and reproduces the effects of cities in a more accurate way than traditional methods usually used in mesoscale models. However, the heat generated in buildings, and the way this heat is exchanged with the exterior, was not explicitly resolved. In particular, recent studies indicated that anthropogenic heat from air-conditioning facilities can play an important role and should be taken into account for more complete urban climate studies. To this purpose, a Building Energy Model (BEM) has been developed, and coupled to the Urban Canopy Parameterisation (UCP). This building model takes into account the diffusion of heat through walls, roofs, and floors, the natural ventilation, the generation of heat from occupants and equipments, and the consumption of energy through air conditioning systems. Comparisons with other programs indicate that BEM is able to accurately simulate the basic heat transfer phenomena, and to reproduce the heat fluxes exchanged between buildings and the atmosphere. In a second part of the work, the simulation system composed by the Mesoscale Model (MM), UCP, and BEM is tested with respect to one, and two-dimensional configurations. In particular, the impact of BEM on the meteorological variables is analyzed, as well as the efficiency of different urban warming countermeasures, and cooling energy demands control strategies. Two-dimensional results are then utilized as guidance for the application of MM-UCP-BEM over the realistic configuration including the city of Basel and the surrounding areas. At first, comparisons of urban and rural simulated temperatures with measures provided by the BUBBLE project (Basel Urban Boundary Layer Experiment), have shown that the model could reasonably well reproduce the variations in outdoor air temperature. In a second time, the simulations considered for the two-dimensional configuration are applied to the case of Basel. Numerical results confirm that anthropogenic fluxes from air-conditioning facilities can have a non negligent impact on the urban meteorology. Typically, they modify the outdoor temperature and increase the Urban Heat Island (UHI) phenomenon. In the last part of the study, the applicability of the model in performing urban warming countermeasures, and cooling energy demands control strategies, is evaluated. In this purpose in mind, a sensitivity analysis is carried out indicating that appropriate physical properties of built materials, efficient air-conditioning systems, and the application of simple energy saving policies, can lead to very important cooling energy savings. In general, the application of BEM inside the UCP allows computing the heat released into the atmosphere by air-conditioning facilities, as well as the corresponding feedbacks produced on the different meteorological variables. It also increases the capability of the urban parameterisation to provide more detailed studies of urban warming countermeasures, and cooling energy demands in real cities.

EPFL2009

Chargement

Recent advances in data processing and communication systems have led to a continuous increase in the amount of data communicated over today’s networks. These large volumes of data pose new challenges on the current networking infrastructure that only offers a best effort mechanism for data delivery. The emergence of new distributed network architectures, such as peer-to-peer networks and wireless mesh networks, and the need for efficient data delivery mechanisms have motivated researchers to reconsider the way that information is communicated and processed in the networks. This has given rise to a new research field called network coding. The network coding paradigm departs from the traditional routing principle where information is simply relayed by the network nodes towards the destination, and introduces some intelligence in the network through coding at the intermediate nodes. This in-network data processing has been proved to substantially improve the performance of data delivery systems in terms of throughput and error resilience in networks with high path diversity. Motivated by the promising results in the network coding research, we focus in this thesis on the design of network coding algorithms for simultaneous transmission of multiple data sources in overlay networks. We investigate several problems that arise in the context of inter-session network coding, namely (i) decoding delay minimization in inter-session network coding, (ii) distributed rate allocation for inter-session network coding and (iii) correlation-aware decoding of incomplete network coded data. We start by proposing a novel framework for data delivery from multiple sources to multiple clients in an overlay wireline network, where intermediate nodes employ randomized inter-session network coding. We consider networks with high resource diversity, which creates network coding opportunities with possibly large gains in terms of throughput, delay and error robustness. However, the coding operations in the intermediate nodes must be carefully designed in order to enable efficient data delivery. We look at the problem from the decoding delay perspective and design solutions that lead to a small decoding delay at clients through proper coding and rate allocation. We cast the optimization problem as a rate allocation problem, which seeks for the coding operations that minimize the average decoding delay in the client population. We demonstrate the validity of our algorithm through simulations in representative network topologies. The results show that an effective combination of intra- and inter-session network coding based on randomized linear coding permits to reach small decoding delays and to better exploit the available network resources even in challenging network settings. Next, we design a distributed rate allocation algorithm where the users decide locally how many intra- and inter-session network coded packets should be requested from the parent nodes in order to get minimal decoding delay. The capability to take coding decisions locally with only a partial knowledge of the network statistics is of crucial importance for applications where users are organized in dynamic overlay networks. We propose a receiver-driven communication protocol that operates in two rounds. First, the users request and obtain information regarding the network conditions and packet availability in their local neighborhood. Then, every user independently optimizes the rate allocation among different possible intra- and inter-session packet combinations to be requested from its parents. We also introduce the novel concept of equivalent flows, which permits to efficiently estimate the expected number of packets that are necessary for decoding and hence to simplify the rate allocation process. Experimental results indicate that our algorithm is capable of eliminating the bottlenecks and reducing the decoding delay of users with limited resources. We further investigate the application of the proposed distributed rate allocation algorithm to the transmission of video sequences and validate the performance of our system using the NS-3 simulator. The simulation results show that the proposed rate allocation algorithm is successful in improving the quality of the delivered video compared to intra-session network coding based solutions. Finally, we investigate the problem of decoding the source information from an incomplete set of network coded data with the help of source priors in a finite algebraic field. The inability to form a complete decoding system can be often caused by transmission losses or timing constraints imposed by the application. In this case, exact reconstruction of the source data by conventional algorithms such as Gaussian elimination is not feasible; however, partial recovery of the source data may still be possible, which can be useful in applications where approximate reconstruction is informative. We use the statistical characteristics of the source data in order to perform approximate decoding. We first analyze the performance of a hypothetical maximum a posteriori decoder, which recovers the source data from an incomplete set of network coded data given the joint statistics of the sources. We derive an upper bound on the probability of erroneous source sequence decoding as a function of the system parameters. We then propose a constructive solution to the approximate decoding problem and design an iterative decoding algorithm based on message passing, which jointly considers the network coding and the correlation constraints. We illustrate the performance of our decoding algorithm through extensive simulations on synthetic and real data sets. The results demonstrate that, even by using a simple correlation model expressed as a correlation noise between pairs of sources, the original source data can be partially decoded in practice from an incomplete set of network coded symbols. Overall, this thesis addresses several important issues related to the design of efficient data delivery methods with inter-session network coding. Our novel framework for decoding delay minimization can impact the development of practical inter-session network coding algorithms that are appropriate for applications with low delay requirements. Our rate allocation algorithms are able to exploit the high resource diversity of modern networking systems and represent an effective alternative in the development of distributed communication systems. Finally, our algorithm for data recovery from incomplete network coded data using correlation priors can contribute significantly to the improvement of the delivered data quality and provide new insights towards the design of joint source and network coding algorithms.

EPFL2013

Chargement

Measuring school contact networks using wireless sensor technology

Marcel Salathé

Interaction networks shaped by social processes constitute the substrate on which various phenomena of interest to human biology occur, for example, epidemics, diffusion of health information, and the exertion of social influence related to health. Understanding the structure of network formation is thus crucial to our understanding of how relational human interactions mediate key biosocial outcomes. Research in this area has been hampered by a lack of high-quality data on the formation and structure of contact networks. Using Wireless Sensor Network (WSN) technology, measured the temporal dynamics of close-proximity interaction networks during a typical school day in a high school in the San Francisco Bay Area. Participants wore small wireless sensors which send and receive radio signals to and from other sensors nearby. This technology allowed us to collect dynamic contact network data with unparalleled precision. At a 94% coverage, we collected 762,868 CPIs at a maximal distance of 3 meters among 788 individuals. The data revealed a high density network with typical small world properties and a relatively homogenous distribution of both interaction time and interaction partners among subjects. Computer simulations of the spread of an influenza-like disease on the weighted contact graph are in good agreement with absentee data during the most recent influenza season. Analysis of targeted immunization strategies suggested that contact network data are required to design strategies that are significantly more effective than random immunization. Immunization strategies based on contact network data were most effective at high vaccination coverage

Wiley2011

Chargement

EPFL2013

Development and application of a numerical simulation system to evaluate the impact of anthropogenic heat fluxes on urban boundary layer climate

Andrea Krpo

EPFL2009