Simplification and Improvement of the Efficiency of Testing Thermophysical Properties of Facade Composite Materials

The choice of highly efficient materials for the opaque parts of the building facades is the most effective factor in increasing its thermal protection. A decrease in the coefficient of U-value of opaque parts of a building directly affects the consumption of both thermal energy and the energy demand for cooling. Two-component or multi-component composite materials today occupy a large place in modern construction. This article analyzes the methodology for testing the thermophysical properties of these materials, reveals a new approach to determine to it, taking into account the links between the thermal conductivity and the thermal diffusivity of materials. The article analyzes the relationship between buildings and the surfaces of the outer envelope and the dependence of the energy efficiency index of the building.

Thermal Performance of LSF Wall Systems with Vacuum Insulation Panels

Lightweight Steel Frames (LSF) in building construction are becoming more popular due to their fast, clean, and flexible constructability. Typical LSF wall panels are made of cold-formed and thin-walled steel lipped channel studs with plasterboard linings. Due to the high thermal conductivity of steel, these LSF components must be well engineered and covered against unintended thermal bridges. Therefore, it is essential to investigate the heat transfer of the LSF wall of different configurations and reduce heat loss through walls by lowering the thermal transmittance, which would ultimately minimise the energy consumption in buildings. The effect of novel thermal insulation material, Vacuum Insulation Panels (VIP), their position on the LSF wall configuration, and Oriented Strand Board (OSB) and plasterboard’s effect on the thermal transmittance of LSF walls were investigated through numerical analysis. A total of 56 wall configurations and 112 finite element models were analysed and compared with the minimum U-value requirements of UK building regulations. Numerical model results exhibited that using plasterboards instead of OSB has no considerable effect on the U-value of the LSF walls. However, 77% (4 times) of U-value reduction was exhibited by introducing the 20 mm VIP. Moreover, the position of the VIP to the U-value of LSF was negligible. Based on the results, optimum LSF wall configurations were proposed by highlighting the construction methods. Additionally, this study, through literature, seeks to identify other areas in which additional research can be conducted to achieve the desired thermal efficiency of buildings using LSF wall systems.

Thermal Performance Assessment of a Wall Made of Lightweight Concrete Blocks with Recycled Brick and Ground Polystyrene

Hollow concrete masonry blocks made of low strength self-compacting concrete with recycled crushed brick and ground polystyrene as an aggregate (RBC-EP blocks), and their expected structural role as masonry infill in steel frames, has been confirmed in previous research studies, thus the extensive investigation of thermal properties is presented in this paper to fully approve their potential application in practice. The Heat Flow and Temperature Based Method was used to conduct in-situ measurements of the wall thermal transmittance (U-value). The experimental U-values of the wall without insulation varied from 1.363 to 1.782 W/m2·K, and the theoretical value was calculated to be 2.01 W/m2·K. Thermal conductivity of the material used for making RBC-EP blocks was measured in a laboratory by using a heat flow meter instrument. To better understand the thermal performance characteristics of a wall constructed from RBC-EP blocks, a comparison with standard materials currently used and found on the market was performed. Walls constructed from RBC-EP blocks show an improvement of building technology and environmentally based enhancement of concrete blocks, since they use recycled materials. They can replace standard lightweight concrete blocks due to their desired mechanical properties, as well as the better thermal performance properties compared to commonly used materials for building walls.

In-situ measurements of the U-value of a ventilated wall assembly

The walls in a building envelope have the largest contact area with the exterior environment, and, therefore, a considerable portion of the thermal energy can be lost through the walls compared to the other parts of the building envelope. For energy-saving purposes, the thermal transmittance of walls is typically limited by building energy performance standards at the national level. However, the presence of a ventilated air-space behind the external cladding, which has variable hydro-dynamic behavior, can differently affect the total thermal transmittance of the entire structure. This paper aims to provide an experimental analysis of the total U-value of a ventilated wall assembly measured in a building prototype following the average and dynamic methods defined by ISO 9869-1. Differences between the calculated theoretical U-value and the measured U-value are compared. The contribution of the thermal resistance of the ventilated air-space in the total thermal transmittance of the wall assembly is also analyzed. The results show that the air movement and the enthalpy change in the ventilated cavity can affect the thermal performance of the wall structure to a certain extent.

Characterising the effects of wind-driven rain on the thermophysical performance of cavity walls by means of a Bayesian framework

Cavity wall is one of the most common construction types in temperate maritime climates, including the UK. However, water penetration may lead to damp within the structure, freeze-thaw damage at the outer surface and a reduction in thermal resistance. The magnitude of wetting effects on the energy performance of cavity walls is still unclear, with potentially significant implications for climate-change-mitigation strategies. This paper investigates the thermophysical performance of uninsulated and insulated cavity walls and its degradation as the element is wettened. Experiments were performed in a hygrothermal laboratory where two cavity-wall specimens (one of which coated with external waterproofing treatment) were tested under a high wind-driven rain exposure. Changes in the thermophysical performance between dry and wet conditions were evaluated through U-value testing and Bayesian inference. Substantial U-value increase was observed for wet uninsulated specimens (compared to dry conditions); conversely, closer U-value ranges were obtained when insulated with EPS grey beads. Moreover, latent-heat effects through the external masonry leaf of the untreated specimen were predicted by the Bayesian framework. Results suggest a negligible efficacy of waterproofing surface treatments as strategies for the reduction of heat transfer within the element, and possible effects of these agents on the evaporative and drying process.

Thermal transmittance prediction based on the application of artificial neural networks on heat flux method results

Deep energy renovation of building stock came more into focus in the European Union due to energy efficiency related directives. Many buildings that must undergo deep energy renovation are old and may lack design/renovation documentation, or possible degradation of materials might have occurred in building elements over time. Thermal transmittance (i.e. U-value) is one of the most important parameters for determining the transmission heat losses through building envelope elements. It depends on the thickness and thermal properties of all the materials that form a building element. In-situ U-value can be determined by ISO 9869-1 standard (Heat Flux Method - HFM). Still, measurement duration is one of the reasons why HFM is not widely used in field testing before the renovation design process commences. This paper analyzes the possibility of reducing the measurement time by conducting parallel measurements with one heat-flux sensor. This parallelization could be achieved by applying a specific class of the Artificial Neural Network (ANN) on HFM results to predict unknown heat flux based on collected interior and exterior air temperatures. After the satisfying prediction is achieved, HFM sensor can be relocated to another measuring location. Paper shows a comparison of four ANN cases applied to HFM results for a measurement held on one multi-layer wall – multilayer perceptron with three neurons in one hidden layer, long short-term memory with 100 units, gated recurrent unit with 100 units and combination of 50 long short-term memory units and 50 gated recurrent units. The analysis gave promising results in term of predicting the heat flux rate based on the two input temperatures. Additional analysis on another wall showed possible limitations of the method that serves as a direction for further research on this topic.

A case study on the impact of fixed input parameter values in the modelling of indoor overheating

Global efforts to reduce greenhouse gas emissions from buildings while also improving their environmental resilience have intensified. These efforts are often supported by building stock models which can inform policymakers on the impact of policies on energy consumption, greenhouse gas emissions and the indoor environment. The input values of such models are commonly informed by reference tables, which can result in inaccurate specification and incomplete representation of the distribution of possible values. In this modelling case study of a semi-detached dwelling archetype, the influence of using a reference U-value (2.1 W/(m2K)) for solid walls in England on heat-related mortality rate is compared to a probabilistic specification based on empirical evidence (median = 1.7W/(m2K)). Using the theoretical reference U-value generally resulted in a lower indoor overheating risk compared to the use of the empirically derived U-values pre-retrofit, but a larger increase in heat-related mortality rate following internal wall insulation (1.20%) than the use of the empirical median (0.94%, 95 % Confidence Interval = 0.87–0.99 %). This highlights the potentially significant implications of using fixed reference values. Future work will employ this probabilistic framework on multiple influential parameters.

Strategyproof Randomized Social Choice for Restricted Sets of Utility Functions

When aggregating preferences of multiple agents, strategyproofness is a fundamental requirement. For randomized voting rules, so-called social decision schemes (SDSs), strategyproofness is usually formalized with the help of utility functions. A classic result shown by Gibbard in 1977 characterizes the set of SDSs that are strategyproof with respect to all utility functions and shows that these SDSs are either indecisive or unfair. For finding more insights into the trade-off between strategyproofness and decisiveness, we propose the notion of U-strategyproofness which requires that only voters with a utility function in the set U cannot manipulate. In particular, we show that if the utility functions in U value the best alternative much more than other alternatives, there are U-strategyproof SDSs that choose an alternative with probability 1 whenever all but k voters rank it first. We also prove for rank-based SDSs that this large gap in the utilities is required to be strategyproof and that the gap must increase in k. On the negative side, we show that U-strategyproofness is incompatible with Condorcet-consistency if U satisfies minimal symmetry conditions and there are at least four alternatives. For three alternatives, the Condorcet rule can be characterized based on U-strategyproofness for the set U containing all equi-distant utility functions.