Browsing by Author "Bandara, RMPS"

Now showing 1 - 4 of 4

item: Thesis-Abstract
Modelling of combustion in a single-burner biogas fired cooking stove
(3/29/2011) Bandara, RMPS; Weerasinghe, R
A variety of stoves are used for household cooking in Sri Lanka. Fuel-wood, Liquefied Petroleum Gas (LPG), Electricity, Kerosene oil, Biogas etc. are the common cooking fuels used. Combustion process in a cooking stove is a complicated phenomenon. It is very difficult to predict the distributions of temperature, flow properties and combustion product concentrations of the cooking stove. It is emphasized that a detailed understanding of the combustion process taking place in a cooking stove is essential for the development of better stove designs. Computational modeling is an efficient tool that could be used successfully in describing the combustion in cooking stoves. Modeling of combustion in a cooking stove that uses a gaseous fuel is comparatively easier than that uses a solid fuel, mainly due to the complexity of the combustion process that the solid fuel undergoes. On this basis present work is involved in the modeling of combustion taking place in a biogas fired cooking stove using SOFIE, a Computational Fluid Dynamics (CFD) code extensively used for fire modeling. The combustion flow field of the stove has been modeled using the k-e turbulence model for turbulence and one-step reaction fast chemistry represents combustion chemistry. Simulations arc conducted for the biogas cooking flame alone and also for the single-burner biogas fired stove with a square- shaped cooking pan. Temperature, density and combustion product concentration predictions have been made using simulations. The predicted temperatures are compared with the experimental measurements. The results generated could be used as a basis for further research in combustion in cooking stoves in order to develop better designs.
item: Conference-Full-text
Optimization methodologies for building performance modeling and optimization
(2013) Bandara, RMPS; Attalage, RA
Buildings account for approximately 40% of the global energy consumption and 36% of total carbon dioxide emissions. At present, high emphasis is given on the reduction of energy consumption and carbon footprint by optimizing the performance and resource utilization of buildings to achieve sustainable development. Building performance is analyzed in terms of energy performance, indoor environment for human comfort & health, environmental degradation and economic aspects. As for the energy performance analysis, this can be best modeled and optimized by a whole building energy simulation tool coupled with an appropriate optimization algorithm. Building performance optimization problems are inherently multivariate and multi-criteria. Optimization methodologies with different characteristics that are broadly classified as Adaptive, Non-adaptive and Pareto Algorithms can be applied in this regard. The paper discusses the applicability of the aforementioned optimization methodologies in building performance optimization for achieving realistic results.
item: Conference-Full-text
Optimization methodologies for building performance modelling and optimization
(The Engineering Research Unit, University of Moratuwa, 2013-02) Bandara, RMPS; AttaIage, RA; Rodrigo, R
dioxide emfssions. At presen'high emphasis is given on the reduction of energy consumption and carbon footprint by optimizing the performance and resource utilization of buildings to ach,eve sus,a,noble development. Building performance is analyzed in terms of energy performance, indoor environment for human comfort & health, environmental degradation and economic aspects. As for the energy performance analysis, this can be best modeled and optimized by a whole building energy simulation tool coupled with an appropriate optimization algorithm. Building performance optimization problems are inherenty multivariate and multi-criteria. Optimization methodologies with different characteristics that are broadly classified as Adaptive, Non-adaptive and Pareto Algorithms can be applied in this regard. The paper discusses the applicability of the aforementioned optimization methodologies in building performance optimization for achieving realistic results.
item: Thesis-Full-text
Optimizing energy performance and indoor environmental quality of buildings using energy simulation, generic optimization and computational fluid dynamics
Bandara, RMPS; Attalage, RA
A building is a complex system with multiple interacting physical processes taking place simultaneously. Various aspects influence the performance of buildings and the building envelope is one of the major contributors in this regard. Building orientation, Aspect ratio, Window to wall ratio, Location and types of fenestration, Envelope materials and their characteristics etc. can have a major impact on the energy consumption and life cycle cost of buildings. However, the best combination of the said envelope elements for optimizing the performance of buildings is difficult to determine and is not known. Whole building simulation tools are often used in making building performance predictions. Building energy simulation is generally used on a scenario-by-scenario basis, with the designer generating a solution and subsequently having the computer evaluating it. This is however, a slow and a tedious process and only a few cases are evaluated in a large range of scenarios, possibly leading to sub-optimal envelope designs. By coupling a generic optimization tool with a whole building energy simulation tool, it is possible to optimize the performance of buildings by determining the best combination of envelope elements, subject to predefined constraints. First part of the thesis explains optimization of energy performance and life cycle cost of buildings through this methodology. Secondly, drawbacks of whole building simulation tools that lead to issues in energy performance predictions of buildings are discussed in detail. The issues have been addressed by coupling the whole building simulation tool with a computational fluid dynamics tool on a complementary data exchange platform. It is observed that with this approach more reliable building performance predictions can be made. Final section of the thesis discusses on optimizing indoor environmental quality using computational fluid dynamics with respect to identified mechanical ventilation configurations. Model predictions have been validated using a detailed experimental design where computational model predictions closely agree with the actual measurements.