Building Services Engineering Research & Technology

This article presents an overview of the concept of a hypothetical three-dimensional elevator system in extra-large buildings. The term three dimensional is used in this context in order to contrast the system with current conventional one-dimensional elevator systems that move bi-directionally in a dedicated vertical shaft; or two-dimensional elevator system that moves in a plane (e.g. in x-horizontal direction and z-vertical direction). The hypothetical three-dimensional elevator system presented in this article assumes that the elevator car can travel in all three directions (but obviously not at the same time). The proposed system comprises a vertical main shaft that allows elevator cars to travel to the required floor, and then to travel in two dimensions in a horizontal plane at the level of the required floor along a network of horizontal shafts in both x- and y- directions. Each elevator car is dispatched to one floor only in each round trip. This is more efficient as it removes the need to visit more than one floor in each journey, but relies heavily on the use of destination group control systems (in order to allow the allocation of the passengers destined to the same floor to the same elevator car). The article presents the general overview of the suggested system using sketches and then derives equations for calculating the round trip time for the elevator car. The Monte Carlo Simulation method is then used to verify the correctness of the derived equations.

Practical application : This manuscript provides a high level overview of the possible arrangement of a three-dimensional elevator traffic systems in a very large building. It can be used by architects to explore the possibility of employing a three-dimensional elevator system in a large building and checking its feasibility.

For achieving a balance between the operational safety and efficiency of a variable speed direct expansion air conditioning system, a new capacity controller that can not only simultaneously control indoor air temperature and humidity, but also select an optimized degree of superheat setting to properly balance the operational safety and efficiency has been developed, by adding a control module to a previously developed capacity controller. The core of the control module was an artificial neural network based model representing the known relationship between the inherent operational characteristics and operational stability of a variable speed direct expansion air conditioning system. Using the control module developed, the degree of superheat setting could be varied in accordance with the variation in operating conditions for ensuring a safe and an efficient operation. The performance of the new capacity controller was experimentally tested using an experimental variable speed direct expansion air conditioning system. Controllability test results showed that the system hunting was mitigated when a larger degree of superheat setting was selected by the developed control module and an improvement in COP at about 3.4% was achieved when a smaller one was selected when using the new capacity controller for simultaneously controlling indoor air temperature and humidity.

Practical application : This paper reports a new capacity for a VS DX A/C system, which can not only control indoor air temperature and humidity through varying compressor and supply fan speeds, but also select an optimized DS setting for ensuring both a safe and efficient system operation. The controllability test results showed that the new capacity controller could be applied to DX A/C systems for indoor thermal control with a higher operational safety and energy efficiency.

The empirical investigation and development of a new Drainage Research Group drain-line carry test solid (DRG) for use in building drainage, waste and ventilation system research is described. The ‘shelf life’ of the National Bureau of Standards test solid used historically (NBS solid) was short and variability in results was large, making it problematic for use in extended investigative work. Further investigations revealed that the materials used in its construction were porous and osmosis would be a contributing factor to the variability observed, as would biofilm growth, causing changes in the coefficients of kinetic and static friction. This research is timely in view of the changing (i.e. generally reducing) volume and energy of contemporary discharges through water conservation initiatives such as WaterWise. Modern materials and analytical techniques present an opportunity to update the NBS solid and develop a modern alternative for research. The results from laboratory testing of the DRG solid compare favourably to the results from the NBS solid. The current mathematical description of the behaviour of a test solid used in a computer-based simulation model (DRAINET) is expanded and updated to include the new findings, creating the potential for extensive follow-on uptake of these results and use by other researchers and potentially use as a standard.

Practical application : The research described articulates with other work in this field related to water conservation strategies; specifically, the investigation of potential unintended consequences through failure to maintain effective drain line carry and self-cleansing velocities. The results are suitable for use by researchers generally and by mathematical modellers in particular.

This paper focuses on the energy management problem applied to residential sector. The studied optimization problem is defined as the optimal management of production and consumption activities in buildings. A scheduling problem is identified to adjust the energy consumption to both the energy cost and the users’ comfort. The optimization procedure of energy management is based on available predictions (weather forecast, users habit, etc.). These predictions are not entirely known data of the optimization problem because of uncertainties. Parametric uncertainties are introduced in the home energy management problem in order to provide robust energy allocation. To improve the taking into account of uncertainties of prediction and the energy management problems, a Sensibility and Uncertainties Analysis method based on the procedure Branch & Bound and the multi-parametric linear programming is proposed. After a description of general principles and main steps, this algorithm is applied to various energy flow management problems in a smart platform.

Practical application : The problem of energy management in buildings is described as the optimization problem which is defined to adjust the energy consumption of buildings in order to reach equilibrium between production and consumption on the grid. This home energy management problem has been modeled with a lot of parameters that are uncertain data. This is generally the case in modeling. This is particularly true in the energy management problem because of the high sensitivity of the decision (the energy allocation) to the data. The proposed approach permits to analyze the sensitivity of the solutions according to uncertain parameters. Then the impact of an uncertainty can be analyzed. Each family of solutions can be used to quantify locally the stability of a robust solution over the uncertainties.

The paper presents a method for reducing the order of the thermal dynamics model of a building or room, obtained by application of a lumped parameter method. The reduced model has the same dynamic characteristics as the primary model, while additionally it is an observable one. The described model order reduction method involves the identification and aggregation of non-distinguishable state variables. The paper presents a sample calculation confirming the validity of the deliberations. The proposed reduction method of state variables can be used with other dynamic systems provided that the assumptions concerning the structures of the system matrices are fulfilled.

Practical application : The use of simplified but accurate mathematical models of the dynamics of heat in buildings enables the efficient design of high-performance control systems, e.g. the stabilisation of air temperature in the building. Simplified mathematical models also require less computing power and can be implemented in embedded control systems. This gives the ability to design, for example, distributed systems of predictive control, which requires mathematical models of controlled processes.

A hybrid system with a radiant heating system and a mechanical ventilation system, which is regarded as an advanced heating, ventilation and air-conditioning (HVAC) system, has been applied in many modern buildings worldwide. To date, almost no studies focused on comparative analysis of the indoor air distribution and the thermal environment for all combinations of radiant heating systems with mechanical ventilation systems. Therefore, in this article, the indoor air distribution and the thermal environment were comparatively analyzed in a room with floor heating (FH) or ceiling heating (CH) and mixing ventilation (MV) or displacement ventilation (DV) when the supply air temperature ranged from 15.0℃ to 19.0℃. The results showed that the temperature effectiveness values were 1.05–1.16 and 0.95–1.02 for MV + FH and MV + CH, respectively, and they were 0.78–0.91 and 0.51–0.67 for DV + FH and DV + CH, respectively. The Predicted Mean Vote values were from 0.24 to 0.45 and from 0.11 to 0.43 for MV + FH and MV + CH, respectively, and from 0.01 to 0.23 and from −0.41 to 0.10 for DV + FH and DV + CH, respectively. Hence, MV + FH had the largest temperature effectiveness and Predicted Mean Vote, and DV + CH had the smallest values. In addition, the vertical air temperature differences for MV + FH and MV + CH were all within the comfort zone according to ISO 7730, but exceeded the comfort zone for DV + FH and DV + CH when the supply air temperature was less than 17℃ and 19℃, respectively. The air distribution effectiveness values for MV + FH and MV + CH were close to the recommended value for MV in the ASHRAE Standard 62.1, and those for DV + FH and DV + CH were slightly less than the recommended value for displacement ventilation. The results in this article are relevant and useful in the process of selection and design of a hybrid system with a radiant heating system and a mechanical ventilation system in practice.

Practical application: The supply air temperature is one of key parameters for the design and operation of a hybrid system with a radiant heating system and a mechanical ventilation system. The results in this article may contribute to the design and operation of a hybrid system when taking in account the indoor air quality and thermal comfort.

The massive urbanization process registered since 1950s and projected to continue for the coming decades is posing a crucial issue for the management of existing cities and the planning of future ones. Smart cities are often envisioned as ideal urban environments where the different dimensions of a city, such as economy, education, energy, environment, finance, etc., are managed in an effective and proactive way. Nevertheless, in order to reach this remarkable and challenging objective, analysis tools are required to create scenarios that are able to inform policy makers’ decisions. Focusing on energy, this paper proposes an analysis method, based on exergy, to support smart city planning. It may help the decision makers to assess the energy-smartness of different scenarios, and to address urban energy policies. Possibilities and limitations of the analysis method are discussed via the application to the cities of London, Milan, and Lisbon that committed to become smart cities.

Practical application: The paper summarizes a study on the possibilities and limitations of adopting an assessment technique, based on exergy, in order to evaluate the energy-smartness of policies in existing and future smart cities. As highlighted in the paper, building’s energy uses have a huge share of many cities’ energy breakdown. Thus, professionals in the building industry will be interested in the paper not only because it refers to smart cities, but because the built environment plays a pivotal role in them. Professionals may also refer to this study to perform a similar analysis in other urban environments to support decision makers.

Massive amounts of building operational data are collected and stored in modern buildings, which provide rich information for in-depth investigation and assessment of actual building operational performance. However, the current utilization of big building operational data is far from being effective due to the gaps between building engineering and advanced big data analytics. Data mining is a promising technology for extracting previously unknown yet potentially useful insights from big data. This paper aims to explore the potential application of advanced data mining techniques for effective utilization of big building operational data. A case study of mining the operational data of an educational building for performance improvement is presented. Decision tree, clustering analysis, and association rule mining are adopted to analyze the operational data. The results show that useful knowledge can be extracted for identifying typical building operation patterns, detecting operation deficiencies, and spotting energy conservation opportunities.

Practical application: The current utilization of big building operational data in the building industry is rather limited due to the lack in experience of using advanced big data analytics. This study presents a data mining-based method for analyzing massive building operational data. The case study results validate the efficiency and effectiveness of the method proposed. It can help building professionals to discover valuable insights into building operation patterns and thereby developing strategies for improving building energy efficiency. The method can be fully realized using the open-source software R, which provides great flexibilities in its integration with building automation systems.