Dariusz Alterman

The Significance of Temperature Based Approach Over the Energy Based Approaches in the Buildings Thermal Assessment

Abstract The design of low energy buildings requires accurate thermal simulation software to assess the heating and cooling loads. Such designs should sustain thermal comfort for occupants and promote less energy usage over the life time of any building. One of the house energy rating used in Australia is AccuRate, star rating tool to assess and compare the thermal performance of various buildings where the heating and cooling loads are calculated based on fixed operational temperatures between 20 °C to 25 °C to sustain thermal comfort for the occupants. However, these fixed settings for the time and temperatures considerably increase the heating and cooling loads. On the other hand the adaptive thermal model applies a broader range of weather conditions, interacts with the occupants and promotes low energy solutions to maintain thermal comfort. This can be achieved by natural ventilation (opening window/doors), suitable clothes, shading and low energy heating/cooling solutions for the occupied spaces (rooms). These activities will save significant amount of operating energy what can to be taken into account to predict energy consumption for a building. Most of the buildings thermal assessment tools depend on energy-based approaches to predict the thermal performance of any building e.g. AccuRate in Australia. This approach encourages the use of energy to maintain thermal comfort. This paper describes the advantages of a temperature-based approach to assess the building’s thermal performance (using an adaptive thermal comfort model) over energy based approach (AccuRate Software used in Australia). The temperature-based approach was validated and compared with the energy-based approach using four full scale housing test modules located in Newcastle, Australia (Cavity Brick (CB), Insulated Cavity Brick (InsCB), Insulated Brick Veneer (InsBV) and Insulated Reverse Brick Veneer (InsRBV)) subjected to a range of seasonal conditions in a moderate climate. The time required for heating and/or cooling using the adaptive thermal comfort approach and AccuRate predictions were estimated. Significant savings (of about 50 %) in energy consumption in minimising the time required for heating and cooling were achieved by using the adaptive thermal comfort model.

A statistical study on the combined effects of wall thermal mass and thermal resistance on internal air temperatures

Statistical analyses are important for real-world validation of theoretical model predictions. In this article, a statistical analysis of real data shows empirically how thermal resistance, thermal mass, building design, season and external air temperature collectively affect indoor air temperature. A simple, four-point, diurnal, temperature-by-time profile is used to summarise daily thermal performance and is used as the response variable for the analysis of performance. The findings from the statistical analysis imply that, at least for moderate climates, the best performing construction/design will be one in which insulation and thermal mass arrangements can be dynamically altered to suit weather and season.

An Analysis of the Bonding Energy through Pull-Out Tests for Aerated Concrete with Various Steel Strip Geometries

The relationship between various steel strip geometries and the bonding energy through pull-out tests of aerated concrete specimens is investigated. Prismatic concrete samples containing embedded steel strips with and without holes of differing sizes and quantities were analysed. Improvements of the bonding energy through pull-out tests by 70% are possible by increasing the number of holes on a steel strip from one to four while maintaining a constant surface area. The energy increased even up to 130% for strips containing holes compared to strips without. In addition, the tests have been carried out with a novel easy to assemble set-up containing a freely adjustable ball-joint and a plate with embedded bolts to avoid eccentricity during pull-out tests.

Prediction of Tension Softening Curve in Concrete Using Artificial Neural Networks

Knowledge of the tension softening process of concrete is essential to understand fracture mechanism, further to analyze fracture behaviour, and further to evaluate properties of concrete. For the last eight years, many different tests on uniaxial tension with elimination of secondary flexure were performed in Tohoku Institute of Technology. The paper is dedicated to predict tension softening curve of concrete by using artificial neural networks (ANNs) based on experimental data of five different mixtures of concrete (including High Performance Concrete). It is an advantage to predict a proper tension softening curve without performing uniaxial tension tests. Several artificial neural networks with different architectures (with various hidden neurons and layers) were studied using software - Statistica Neural Network. In order to evaluate the prediction accuracy, tension softening curve and other fracture parameters were predicted for each mix from the other four mixes and compared with the omitted data of the relevant mix. High accuracy was obtained in the all predicted tension softening curves and the fracture parameters were also well predicted.

An Impregnation Technique for Crack Identification Following Uniaxial Tension Tests

This paper is dedicated to an impregnation technique for crack identification of uniaxial tensile behaviour of concrete samples. A method for crack identification in concrete after uniaxial tension tests was adopted for the observation of differences between various experiments which were conducted with and without the elimination of secondary flexure. During the procedure an epoxy resin containing fluorescent dye was infused into concrete samples by vacuum to expose cracks and defects. After impregnation the samples were sawed from the prism and pictures taken under ultraviolet light.

Size Effect of Concrete in Uniaxial Tension

In order to investigate the size effect of concrete, four sizes of rectangular prisms were tested in uniaxial tension. The cross sections of the prisms were 50x100mm, 100x100mm, 200x100mm and 400x100mm. The concrete was an ordinary one with the compressive strength of 34 MPa and the maximum aggregate size of 20mm. Notches were applied on four side faces and secondary flexure was completely eliminated during the test in order to obtain the exact nominal tensile strength. The size effect was analyzed by four factors, namely tensile strength, fracture energy, critical crack opening displacement and tension softening curves. Clear size dependence was observed in critical crack opening displacement and initial convexity of tension softening curves, and a slight size dependence was observed in tensile strength. On the other hand, size effect was unclear in fracture energy and other part of tension softening curves because of their scatters.

Adaptation the Use of CFD Modelling for Building Thermal Simulation

This paper demonstrate the possibility of using CFD simulation alone to determine the internal air temperature of buildings for long periods (one year), without the assistance of any additional software, with fast computing times and an acceptable degree of accuracy for the simulation results. An experiment on CFD simulations were carried out to examine the accuracy of CFD simulation to predict building internal air temperature for a complete house in Perth, Australia. Real data recorded inside a house were compared with CFD modeling results to find the precision of the CFD simulation after CFD adaptation process applied in this research. This study is an attempt to use CFD alone to calculate the buildings internal air temperatures for extended periods (months, years). Using CFD simulations with extended periods have some problems, for example; lengthy computing times, discrepancies in peak temperature time and the internal air temperatures inside the model keep rising with time. Performing CFD analysis after applying the measures to adapt the use of CFD modeling resulted in faster computing times, with 1% of the computing time compared to that for a 1 minute time step, and with 90% of the results lying within 3°C of the real (observed) data. The overall results from CFD simulations with an average accuracy of 92% compared with the real data recorded inside the house.