A review on experimental research using scale models for buildings: Application and methodologies

A complete review on scale model testing for buildings, considering a wide range of methodologies and new manufacturing techniques, in areas such as statics and dynamics, acoustics, lighting, aerodynamics and thermodynamics for energy efficiency is presented. On the one hand, scale model testing for buildings require different considerations and techniques and are usually focused on one specific physical field contributing to the information scattering. On the other hand, they are sometimes too general, theoretical or unpractical. Although commercial computer simulations are first option among professionals, they necessarily simplify complex phenomena and ignore, among other aspects, size effects and latest findings in fractals. The potential of complementary experiments using new manufactured scale models for buildings is raising, however, it is still missing a practical overview through different physical fields specifically for buildings with these considerations. This review gives a wide perspective and unified scope on uses and possibilities of scale model testing for buildings, from the traditional configurations of Leon Battiste Alberti to new possibilities applying complex physics and new techniques of 3D-modelling

Development of robust building energy demand-side control strategy under uncertainty

The potential of carbon emission regulations applied to an individual building will encourage building owners to purchase utility-provided green power or to employ onsite renewable energy generation. As both cases are based on intermittent renewable energy sources, demand side control is a fundamental precondition for maximizing the effectiveness of using renewable energy sources. Such control leads to a reduction in peak demand and/or in energy demand variability, therefore, such reduction in the demand profile eventually enhances the efficiency of an erratic supply of renewable energy. The combined operation of active thermal energy storage and passive building thermal mass has shown substantial improvement in demand-side control performance when compared to current state-of-the-art demand-side control measures. Specifically, "model-based" optimal control for this operation has the potential to significantly increase performance and bring economic advantages. However, due to the uncertainty in certain operating conditions in the field its control effectiveness could be diminished and/or seriously damaged, which results in poor performance. This dissertation pursues improvements of current demand-side controls under uncertainty by proposing a robust supervisory demand-side control strategy that is designed to be immune from uncertainty and perform consistently under uncertain conditions. Uniqueness and superiority of the proposed robust demand-side controls are found as below: a. It is developed based on fundamental studies about uncertainty and a systematic approach to uncertainty analysis. b. It reduces variability of performance under varied conditions, and thus avoids the worst case scenario. c. It is reactive in cases of critical "discrepancies" observed caused by the unpredictable uncertainty that typically scenario uncertainty imposes, and thus it increases control efficiency. This is obtainable by means of i) multi-source composition of weather forecasts including both historical archive and online sources and ii) adaptive Multiple model-based controls (MMC) to mitigate detrimental impacts of varying scenario uncertainties. The proposed robust demand-side control strategy verifies its outstanding demand-side control performance in varied and non-indigenous conditions compared to the existing control strategies including deterministic optimal controls. This result reemphasizes importance of the demand-side control for a building in the global carbon economy. It also demonstrates a capability of risk management of the proposed robust demand-side controls in highly uncertain situations, which eventually attains the maximum benefit in both theoretical and practical perspectives.Ph.D.Committee Chair: Augenbroe, Gofried; Committee Member: Brown, Jason; Committee Member: Jeter, Sheldon; Committee Member: Paredis,Christiaan; Committee Member: Sastry, Chellur

Development, modelling and analysis of Vacuum Assisted Multipoint Moulding for manufacturing fibre-reinforced plastic composites

Full version: Access restricted permanently due to 3rd party copyright restrictions. Restriction set on 12.11.2019 by SE, Doctoral CollegeMultipoint tooling is a mould making technology that enables the rapid reconfiguration of a mould to create individual components. It replaces the commonly used, elaborately designed, and costly manufactured solid die, with an array of individually adjustable pins. These pins can be set to represent a large variety of freeform surfaces. An elastic interpolation layer (IPL) is used to smoothen the pin array and forms the actual tooling surface. This technology is well established in sheet metal forming and other areas of manufacturing. However, only little research has been conducted in the area of fibre-reinforced plastic composites. In this thesis, a novel multipoint tooling technology is introduced, that is specifically designed for fibre-reinforced plastic (FRP) manufacturing. Different to existing solutions, this Vacuum Assisted Multipoint Moulding (VAMM) is capable of creating concave and convex geometries on a single sided mould. This enables the use of established FRP manufacturing processes without further adaptation. Two iterations of this technology are developed: A manually adjusted small-scale test bench is used to validate the VAMM concept and conduct experiments on, and a fully automated full scale manufacturing prototype then is used to demonstrate the feasibility of the technology for an industrial application. The elasticity of the IPL introduces two system immanent dimensional defects: the overall shape deviates due to the deformation of the IPL and the punctual support of the interpolation layer leads to a golf-ball-like surface effect. A process model was created to predict behaviour of the VAMM tool and the interpolation layer, and estimate the expected part quality. An iterative shape control algorithm was implemented, to improve the dimensional accuracy of the manufacturing process, by readjusting individual pins in the tool. On this model, a sensitivity analysis was conducted to quantify the influence of the process and pin array parameters on the dimpling of the tool surface. The most important parameters were identified and used in a Metamodel of Optimal Prognosis (MOP). This MOP enables the rapid estimation of the system behaviour. It was used to optimise the VAMM process and the interpolation layer in order to maximise the geometric part quality. With this method two IPL designs, one with a single, and one with two separate layers of silicone rubber, were evaluated. It turned out that the dual layer configuration can handle a 24 % higher process pressure, while using a 9 % thinner interpolation layer, to produce parts similar to the single layer configuration.Huber Kunststoff und Technik GmbHSGL Carbon SEPutzin Maschinenbau Gmb

On the Adaptation of Building Controls to the Envelope and the Occupants

The sun is the biggest known source of energy in our solar system. We feel its strength when it gets hot during the the day and we notice its absence during the night when we feel cold. So as to be less dependent on the sun as an energy source, we implemented additional heating and cooling sources to maintain the temperature within a comfortable range. The downside to this is that the majority of energy consumed within the housing sector is used up on the heating and cooling alone. To profit from the vast energy source of the sun we propose a user-adaptive and building-adaptive blind control for residential buildings, that is implemented in prefabricated modules for facade renovation. User-adaptive means that it is the occupant who is responsible for the temperature control within the home. Building-adaptive, in this context, means that the temperature control is established automatically without any user input. Through the evaluation of occupant queries we have shown that a general measure for thermal comfort is not possible for all occupants. Consequently, there is a need for a personalized measure of thermal comfort. In order to create this the occupant enters votes via the interface; from this we deduced statistically the probability of comfort relative to the indoor temperature. According to the profile the control sets its target temperature. The profile steadily adapts the user's preferences and through this we can also capture seasonal changes in comfort temperature. This guarantees that at each point in time the control system knows the desired temperature and is taking action to achieve it. The adaption to the building is achieved with the fitting of a simple thermal building model with data collected by the sensors of the control system. We showed that the monitored data sufficiently fits the model. With the help of the simple model we evaluated different control strategies and optimized them according to the thermal profile. For our performance tests we conducted computer simulations as well as a 6-month field study. For the simulations, a specific test bed was suggested that would assess the saving potential, which can then be compared to the performance of the tested control. Results showed that the suggested control system is capitalizing on most of the achievable energy savings and thermal comfort. A 6-month field study in the LESO-PB building was carried out to test the impact on energy demand as well as comfort under real conditions. It appeared that the automatically controlled office needed only approximately 50% of the average heating energy that was used in the manually controlled offices. Furthermore, the probability of thermal comfort was, on average, 10% higher in the automatically controlled offices when compared to those that were controlled manually