#sotascience

[sotascience]

OPTIMIZATION OF ENERGY ACCORDING TO TREE TYPE & LOCATION IN THE GARDEN

Detailed numerical calculations of building energy modeling can be made using the Radiance and EnergyPlus which are open-source softwares developed by respectively Lawrance Berkeley National Laboratory and Department of Energy (DOE). It is possible to evaluate heating & cooling loads, HVAC sizing, surface temperatures, shading effect, luminance, illuminance with using these solvers.

All these calculations are solved by iterative ways by defining the structural material information (thicknesses, thermal conductivity values, surface irradiation quantities, etc.), location information and annual climate data (for 8760 hours).

The balance between the comfort level of the building and the energy consumption is improved by performing these analyzes while still in the design phase. Considering that approximately 40% of the energy consumed in the world is caused by buildings, methods such as Computational Fluid Dynamics and Building Energy Simulation are gaining importance due to increase the energy and comfort performance of the design. By combining these two different methods, the design will reach a much better level in terms of energy savings with comfort. In early design step, small details of passive and active systems can provide significant gains.

This study focuses on how environmental factors can influence the energy consumption of building heating and cooling loads. First, it is aimed to analyze the location and type of a tree to be planted in the garden of the sample project house by the building energy simulation method. Coupling of two question with coalesencing genomes;

Where is the best location of tree in your garden to reduce energy consumption?

Which type of tree is the best schedule of drop leaves season to reduce energy consumption?

Cross-over optimization of two different analyzes will be possible with the answers to these two questions.

Secondly, in the case of the presence and absence of the tree on energy-efficient results, the wind distribution over a single tree was analyzed by CFD analysis.

The location of the sample house is located in Iznik district of Bursa. The annual climate data is taken from the nearest station to the working area and the correct input to the analysis as input is very important for the consistency of the results. Long-term climate data from Bursa Yenişehir Airport is 26 km beeline away from house.

The orbit of the sun in the year shows differences in each latitude. Therefore, the shadowing of the environmental factors on the sample house will be different at each latitude. In this case, it is necessary to take into account the different location optimizations separately. In the following image, it is possible to see how the sun’s path changes in different latitude / longitude.

In order to understand the proportional difference between presence and absence of the tree, the first analysis was realized without a tree. As a result, annual consumption of 83540 kWh was observed. This value is taken into consideration in the optimization analyzes.

As a result of the first analysis in which 828 different options were tried, the 6 best positions were selected close to each other. 1st-3rd-5th locations are the southwest of the garden, 2nd-4th locations are the southeast of the garden and the 6th location is the south of the garden.

The decrease in energy consumption is between 2.44% and 2.73% for these locations. In the first analysis, it was assumed that the tree did not shed its leaf for 8760 hours. Another aim of the preliminary analysis is to reduce the duration of the secondary analysis. If two analyzes were carried out together, 7452 different analyzes would be required for 9 different trees.

In this study, 9 tree species can be grown in Bursa season. As the sun follows different paths in each latitude, the deciduous seasons of the trees also vary in each climate. These trees can reach a certain volume of plane, willow, elm, hornbeam, mulberry, lime, poplar, pine and cypress. The average volume of an adult tree was accepted as 73.5 m3 (3.5m x 3.5m x 6m) and this volume was based on the analyzes. Before passing to the second analysis, the transparency ratios of the leaf-shedding algorithm for these tree types were made ready for hourly analysis in the form of code of 8760 lines.

After the prepared leaf-shedding algoritm according to the permeability values of the trees, the second analysis was started for 54 different options (6 best positions x 9 different trees). As a result of the analysis, the decrease in energy consumption is between 2.50% and 2.63% for wood types. After the sum of the gains in energy consumption provided by both analyzes, the value can reach 5.30%.

The optimization studies at the design stage will be an important tool in determining the performance of energy efficient buildings. After the construction, under favour of monitoring of building with different sensors can allow to continue optimization and machine learning can be enlight further designs. In spite of increasing urbanization, increasing the quality of human life and reducing the carbon footprint will be possible with this and similar data processing methods.

[sotascience]

HOW NEW BUILDINGS AFFECT THE DYNAMICS OF URBAN?

Cities are a compound that brings together the most important elements of modern life. While approximately 55% of the world’s population lives in cities, more than 70% of the countries’ Gross Domestic Product is provided by urban rather rural. Therefore, the increasing capaciousness and prominence of cities affect many living standards and the comfort of the citizens. In 2050, the ratio of the urban population living in the world to the whole population is expected to reach 68%, which will bring about an increase in energy consumption and pollution in the urban.

Increasing urbanization causes micro-climate change at the local scale, come into existence of heat islands between building blocks arise from the heated air waves by the effect of buildings. Air waves cannot be evacuated by prevailing wind. While heat islands affect the energy consumption of buildings by increasing the cooling loads. The risks for the inhabitants can be observed as air pollution, post-hot psychological depression and respiratory problems.

As a result of the analyzes carried out in regions with the same climatic conditions of Mecidiyekoy, Istanbul, average temperatures in July vary in rural areas and cities. While the average temperature in rural areas in Istanbul is 24,09 °C. 24.33 °C is observed in urban areas with local urbanization and 24.39 °C in urban areas with commercial and local urbanization. The difference of temperature causes window/wall ratio (WWR) of buildings, thermal capacities of the surfaces, number of vehicles and people.

While energy consumption and comfort parameters can be handled together with many certifications, investor and user requests during the construction design phase, studies on energy, comfort and psychological effects of new buildings to the city and the city remain secondary. However, the more important the energy efficiency and comfort of the new building, the more important it is to the existing buildings and their environment. While designing the new building, all parameters considered under the name of sustainability definition will change with a new building to be built next to it without considering its environment. Continuous movement and development in cities has left its name to “Gentrification” with sudden and penetrated changes made from time to time. The new designs that will be made by taking into consideration the effect it will have on the environment during the transformation will make significant contributions to the city’s climate, micro-climate, the invoices and comfort of the citizens.

The more important the energy efficiency and comfort of the occupants in the new buildings, the more important it is to the existing buildings. This requires an integrated approach to the settlement and impact of new buildings in the city. In this study, evaluation conditions at design stage,

Energy consumption and comfort of the new design,

The effect of the new design on the energy consumption and comfort of the surrounding buildings,

The effect of the new design on the random apartments

as well as multi-purpose optimizations. After the selection algorithm which will change the floor heights randomly without changing the square meter of three new buildings has been created in the Grasshopper interface. Parametric analyzes of 168 different combinations have been performed.

The most significant benefit of generative design and these algorithms will be to increase the energy and comfort performance of designs by rapidly evaluating and reproducing multi-purpose optimizations. In order to achive the optimum results of architectural spaces need to use restrictive, modifier and selector functions to determine generative features of spatials as sizes, usage types, energy usage, daylight levels and comfort parameters.

The selection algorithm created for this study can determine the number of blocks, minimum and maximum floor height, and redefine these variables each time with the goal of keeping the square constant. The algorithm is designed to optimize not only the number of blocks and floor heights, but also the distance between the blocks. When we cross the genetic algorithms, one of the machine learning tools, with the selection algorithm, it is possible to evaluate the performance criteria of thousands of design proposals and reach the optimum result.

With the integration of the energy model established with all algorithms and data interpretation and visualization tools, the impact of the new structures on itself and its environment can be made visible.

While 28000 analyzes will be required to calculate the potential energy consumption and daylight levels of the new and the surrounding buildings The evolution and complaint of the results constructed in genetic algorithms can be reduced to 2300 analyzes by statistical evaluations. The analyzes, which are expected to last for 1 month, can be performed in 3 days.

At the beginning of the subject, which can be described as evolutionary design tools, it is inevitable that optimization works in all areas, especially energy, will emerge as one of the most crucial agendas of the world. These analyzes showed that the energy consumption of the new building could be reduced by 3% only by changing the floor heights and indexed to the average value. When we think that 40% of the total energy consumed in the world is caused by buildings, it should be underlined that 3% can actually have a big impact.