Analysis of the hygrothermal functional properties of stabilised rammed earth materials

Suitable experimental methodologies for determining the hygrothermal properties of stabilised rammed earth (SRE) materials have been presented along with comparative experimental data for three different SRE mix designs with parametric analysis of the influence of these variables on material function. Higher bulk porosity corresponds to reduced volumetric heat capacity (C), but increased sorptivity (S) and vapour permeance (W). Since bulk porosity and void size distribution (VSD) are interdependent variables, it follows that for constant particle size distribution (PSD) and compaction energy an increase in porosity results in an increase in the mean pore radius, for a material. This explains why the magnitude of liquid/vapour transfer (S and W) terms are inversely related to the hygroscopic moisture capacity, ξ since the capillary potential, Ψ will increase when the mean pore diameter decreases. The implications are that the hygrothermal properties of SRE materials can be designed and predicted by manipulating particle size distribution and compaction energy

Humidity buffering using stabilised rammed earth materials

The humidity buffering potential of stabilised rammed earth materials is investigated based on the moisture buffer value concept. The moisture buffer value is (a) measured experimentally, (b) calculated from an analytical solution of the mass transfer and (c) simulated using a numerical solution of the combined heat and mass transfer. The numerical solution to the equations is described, as well as the modelling tool termed ‘CHAMP’ (coupled heat and mass transport in porous media). The results show that stabilised rammed earth can be a ‘good’ moisture buffering material under the Nordtest classification scheme. They also show that the moisture buffer value of stabilised rammed earth materials could be optimised or maximised by controlling the grading and mineralogy of the sub-soil and the manufacturing techniques. Sensitivity analysis of the moisture buffer value to the moisture transfer resistance at the surface is explored through numerical simulation and the need to control the experimental measurement carefully is explored

Early-stage design decision-making for Community Energy Schemes

A model and an assessment framework have been developed to support the transition of residential districts from passive energy consumers to active prosumers linked within Community Energy Systems (CES). Three hypothetic districts form the case studies on which an assumed scenario was applied and examined for the financial, environmental and energy efficiency outcomes it achieves. The case studies consider houses of different types and thermal efficiencies. The results show a promising level of detail, enough to enhance decisionmaking during the early concept design of projects. The model and assessment framework can evaluate a range of applications including the transformation of old districts into CESs, the expansion of recently built CESs to include adjacent districts with older and usually less efficient dwellings and the designing of CESs for new housing developments

Hygrothermal assessment of two solid-brick walls under varying internal and external parameter settings

Hygrothermal simulation incorporates transient heat and moisture transport in 1D and 2D wall assemblies. There is a need to understand how hygrothermal analysis can play a role in buildings designed to be moisture resilient. This paper investigates the hygrothermal effects on two different wall structures using different distributions of input parameters and two different weather scenarios. Results show that the differences in weather and distribution of the parameters have a limited effect on the sensitivity of parameters, but have a large impact on the uncertainty of the outcomes. A normal distribution of parameter means and an accurate weather scenario will improve the accuracy of the simulation, but might not be necessary if only the sensitivity of the parameters is of concern

How do householders interact with their heating controls?

This paper presents measurements of householders’ manual interaction with their heating controls. The results demonstrate the importance of measuring heating use behaviour directly rather than relying on thermostat and timer settings or inferring heating use from internal temperature measurements. This is the first time, to the author’s knowledge, that manual heating interactions have been recorded. Heating controls will only save energy if used effectively, yet currently, little is known about how they are used. This paper describes an in-depth study of twelve UK residential properties that had new heating controls installed. Heating system interactions with these controls, energy consumption and room temperatures were monitored for ten months from July 2014 to April 2015 inclusive, covering autumn and spring shoulder months and the winter heating season. These measured data were supported by a series of qualitative interviews with the households. The paper reports details of the householders’ heating system use, separating the occupants’ manual interactions with the controls from their pre-programmed heating schedules. The findings show that the participants had many manual interactions with their heating systems, even during scheduled heating periods; changing heating durations and demand temperatures. The results also identify that manual interactions with heating controls occur more frequently during the winter season than in the shoulder months. The results have important implications relating to assumptions of set-point temperatures and schedule characteristics previously based only on self-reported use or measured internal temperature profiles

Estimation of building heat transfer coefficients from in-use data: Impacts of unmonitored energy flows

PurposeThe purpose of this paper is to identify the impact of traditionally unmonitored energy sources and sinks on assessment of the as-built thermal performance of occupied homes. The analysis aims to demonstrate the potential scale of uncertainties introduced in a heat balance estimation of the heat transfer coefficient (HTC) when using in-use monitored data. Design/methodology/approach Energy flows for two UK homes – one a 1930s dwelling with high heat loss, the second a higher-performing 2014-built home – are predicted using the UK Government’s standard assessment procedure (SAP) and visualised using Sankey diagrams. Selected modelled energy flows are used as inputs in a quasi-steady state heat balance to calculate in-use HTCs as if from measured data sets gathered in occupied homes. The estimated in-use HTCs are compared against SAP-calculated values to illustrate the impact of including or omitting various heat sources and sinks. Findings The results demonstrate that for dwellings with low heat loss, the increased proportion of heating demand met by unmetered internal and solar gains informs a greater sensitivity of a heat balance estimation of the HTC to their omission. While simple quasi-steady state heat balance methods may be appropriate for dwellings with very high heat loss, alternative approaches are likely to be required for those with lower heat loss. Originality/value A need to understand the impacts of unmetered heat flows on the accuracy with which a building’s thermal performance may be inferred from in-use monitored data is identified: this paper illustrates the scale of these impacts for two homes at opposite ends of the energy performance scale.</div

Occupant behaviour modelling in domestic buildings: the case of household electrical appliances

This paper presents a new approach to bottom-up stochastic occupant behaviour modelling for predicting the use of household electrical appliances in domestic buildings. Three metrics relating to appliance occupant behaviours are defined: the number of switch-on events per day, the switch-on times, and the duration of each appliance usage. The metrics were calculated for 1,076 appliances in 225 households from the UK Government’s Household Electricity Survey carried out in 2010-2011. The analysis shows that occupant behaviour varies substantially between households, across appliance types and over time. The new modelling approach improves on previous approaches by using a three step process where the three appliance occupant behaviour metrics are simulated respectively using stochastic processes to capture daily variations in appliance occupant behaviour. It uses probability and cumulative density functions based on individual households and appliances which are shown to have advantages for modelling the variations in appliance occupant behaviours

The expanding house : extensions to domestic buildings and their impact on energy consumption

The energy impact of extensions, defined as the percentage increase in total household energy consumption caused by an extension, has been investigated and quantified. This has been achieved through a two-step process. Firstly, a set of typical extension sizes and prevalence was defined through a survey using publicly available aerial imagery and GIS mapping software. Secondly the energy impact of these extensions was predicted through the application of a reduced data Standard Assessment Procedure. A catalogue of extension types has been created and statistically significant relationships between extension prevalence and tenure, household income and building archetype have been proven. The energy impact of extensions has been estimated to be 16% on average across all building and extension types; which would account for 3.8% of England’s domestic energy demand if the results of this study were scaled nationally

Seasonal variation in household electricity demand: A comparison of monitored and synthetic daily load profiles

Abstract This paper examines seasonal variation in household electricity demand through analysis of two sets of half-hourly electricity demand data: a monitored dataset gathered from 58 English households between July and December 2011; and a synthetic dataset generated using a time-of-use-based load modelling tool. Analysis of variance (ANOVA) tests were used to identify statistically significant between-months differences in four metrics describing the shape of household-level daily load profiles: mean electrical load; peak load; load factor; and timing of peak load. For the monitored dataset, all four metrics exhibited significant monthly variation. With the exception of peak load time, significant between-months differences were also present for all metrics calculated for the synthetic dataset. However, monthly variability was generally under-represented in the synthetic data, and the predicted between-months differences in load factors and peak load timing were inconsistent with those exhibited by the monitored data. The study demonstrates that the shapes of household daily electrical load profiles can vary significantly between months, and that limited treatment of seasonal variation in load modelling can lead to inaccurate predictions of its effects

Overheating in dwellings: a matched pair of test houses with synthetic occupants

Summertime overheating is increasingly prevalent in both new and existing UK dwellings. High internal temperatures can be dangerous to vulnerable occupants, disrupt sleep and cause thermal discomfort. The mitigation or exacerbation of overheating through simple occupant interventions like window opening and blind use needs better understanding if homes are to be comfortable and safe in summer without the use of air conditioning. This paper describes the adaptation of two adjoining, semi-detached houses to create a matched pair of test houses for full-scale, side-by-side overheating experiments under real weather conditions. Synthetic occupancy was installed to allow dynamic remote control of actuated windows, motorised curtains, automated internal doors and internal heat gains. The houses were instrumented with calibrated sensors to measure the internal and external environment. The results of the experiments conducted in summer 2017 will be presented in a future paper. These instrumented, matched pair homes can be used to accurately quantify the effects on energy demand, internal temperatures and air quality of occupant behaviours and different heating, cooling and ventilation technologies