The thesis describes a study of the effects of weather on construction projects using a simulation model. The model uses project data supplied in the form of a network and historical weather data records to evaluate the effects of the weather elements—temperature, rainfall, windchill and windspeed—on the progress of construction work, using threshold limits specified for weather-sensitive activities. The overall effects of weather are measured by the losses in project production time. Thus by simulating a project over a long period of weather it is possible to obtain results which reasonably reflect the effects of weather on the project.

Introducing new technologies or innovative processes can enhance construction efficiency and enable organisations to achieve objectives of lowering costs, continuous improvement and competitive advantage. New ideas have to show significant benefits before they are accepted. Despite of the differences between the construction and manufacturing industries, opportunities are still available to leam from manufacturing approaches to innovation. A fundamental challenge facing construction innovation is the way that construction organisations plan and control the implementation of innovation where many projects do not fulfil their time and cost objectives. Management should not only improve techniques for planning and scheduling but also allow managers to assess and simulate the anticipated performance resulting from innovation. According to this assessment, managers would be more able and perhaps more ready to accept new processes/products or iterate the implementation process until a satisfactory level of performance has been achieved. Intangible benefits offered by advanced construction technologies are hard to quantify using traditional economic analysis techniques. This could result in the rejection of a potentially profitable idea. Benefits to be gained from improvements in operational efficiency are measured by cost and time-savings and increasing productivity. These benefits, in addition to intangible benefits, need to be measured and quantified. Simulating the implementation process of innovation has not been addressed, although many models have been developed to describe the innovation process in construction which considered implementation as a sequential process incorporating iterations.

The primary objective of this thesis is to show the significant role which statistics and probability theory can play in the design of various aspects of a building (i. e. the lifts, the structure, the water supply, the thermal environment, the fire protection etc.). It is shown that the operational performance of the majority of these building subsystems is dependent upon one or more factors which are probabilistic in nature, and consequently should not be considered deterministically as is commonly the practice in present design codes. These so called probabilistic approaches to design allow the performance of any design solution to be quantified as the frequency, or probability of inadequacy. The second objective of this thesis is to consider the use of two rational design procedures to aid the designer in choosing the desired probabilities of inadequacy or failure for each subsystem of the building. The first method, which was developed during the course of this research project, balances the operational performance of all the various subsystems of the building using the criterion that the frequency of inadequacy of each subsystem should be inversely proportional to the consequences of inadequacy. This design criterion produces a building which has a satisfactory overall performance from the users view point. The second rational method considered in this thesis is the use of classical cost benefit techniques to determine the optimal economic level of performance for each of the probabilistic subsystems. This design method requires that capital and running costs must be considered in addition to the expected losses should inadequacy of the subsystem occur.

The main areas of study covered by this thesis are: 1. Analysis of the past performance of the market for new housebuilding, and projections of future activity, over the period 1977 to 1986, for the number and type of duelling completions. 2. Analysis of the usage of materials in new housebuilding and the factors which might promote or inhibit the substitution of materials. 3. Identification of areas in new housebuilding where further substitution might occur over the period 1977 to 1986. 4. Future demand for housebuilding materials based on the forecasts of completions and the usage of materials. New duelling completions over the next ten years are estimated to be at an annual average rate of 305,000, +/- 15,000, with maximum demand occurring during the two year period 1981/82. Activity between the private and public sectors will depend on the Government of the day. A Conservative administration will probably support the private sector and a Labour administration can be expected to lean more towards the public sector. Duelling types and sizes are not expected to show any marked change but there will probably be a tendency towards smaller units. The usage of materials in various duelling types has been identified and has been measured by the amount required for each 100 square metres of floor area constructed. Substitution of materials has been found to be determined by their initial costs. The cheaper the material the more likely it is to lead the market. The technical performance of a material and its cost in use are not considered to be the main factors which control substitution. Further substitution and innovation of materials will most likely take place through changes in the Building Regulations. Particularly important in this aspect are the regulations which control the thermal insulation of duellings. It is anticipated that before 1986 these regulations will be more stringent and this should give materials manufacturers the opportunity to innovate with new materials. Throughout the period 1977 to 1986 it is not thought that manufacturers of materials, for new housebuilding, will experience any difficulties in supplying the demand of the market. The only problem which might occur is if overall activity continues to decline and the capacity of the materials industries decreases to a point where it cannot quickly rise to meet an upsurge in demand. Should this happen, it is not expected that the difficulties will take very long to overcome.

Building regulatory control of Domestic extensions in contrast to volume house building and commercial projects manifests a propensity to consume more economic resources than that generated from fee income. In personal Building Control practice cost and efficiency savings were achieved through linear programming, economies of scale and new technologies but the problem remained. More efficient and alternative mechanisms for alleviating this quandary were required, and academic inquiry provided an opportunity. The current literature was reviewed and thereafter continually revisited. A kaleidoscopic research model involving different epistemologies and methodologies but combining microscopic and periscopic views was regarded as a pragmatic means to synergise the relationship between academic inquiry and industry. A preliminary practice based case study was conducted followed by interviews and archival retrieval at various Building Control units. The investigation was a heuristic trial and error research tool and sufficiently robust to form the foundation for the main research based on region-wide case studies, building surveys, interviews, and archive documentation. The empirical evidence established resource use overruns were found in all districts researched and up to half of domestic extension activity failed to cover fee income. The presumption of regulators and regulatees was that overruns were caused by the poor practices of inadequate Builders. Analysis of the data contradicted this sentiment and revealed the major cause was Designers’ mistakes and to a lesser extent unexpected externalities, Building Control procedures, and Home Owners’ revisions. Solutions are proposed and evaluated to overcome the challenges presented by these complications and remedy these causal incidents. Ways are explored and assessed that have practical application for Building Control bodies in achieving regulatory conformity within fee income for domestic extensions and be practically functioned. The research was limited to a single English region; to establish if the phenomenon is found nationally will require further inquiry.

The aim of this work was to investigate the aerodynamic performance of sports stadiums located in the built environment and conduct a design optimisation study to improve the wind comfort conditions for both players and spectators. A 1:300 scale semi-open stadium model was assessed with combined Atmospheric Boundary Layer (ABL) wind tunnel experimentation and Computational Fluid Dynamics (CFD) techniques against pressure and velocity distribution patterns in both interior and exterior areas of the stadium bowl. The validation of the numeric analysis was performed with the experimental results of pressure coefficients. The aerodynamic performance analysis compared two impinging wind angles (0o and 90o) and two building envelope porosities, defined by the existence of an elevated and non-elevated roof configuration. The results indicated that the wind direction caused small differentiations on the developed wind distribution patterns, with the wind angle of 90o generating smaller negative pressures in both interior and exterior stadium surfaces. Further analysis of the air velocity distribution results indicated that the provision of a horizontal ventilation opening between the roof and the upper spectator tiers substantially improves the airflow distribution for the benefit of spectators, but induces up to 25 % higher velocities at the centre of the pitch level. Parametric studies were performed to evaluate the impact of the roof geometry changes on the developed wind comfort conditions for the players and the spectators. By employing coupled CFD-Response Surface Methodology (RSM) techniques, it was found that the wind speeds and the flow homogeneity at the stadium bowl are more susceptible to firstly the roof height and secondly the roof radius. Finally, the generated response surfaces formed the basis for the conduction of a multi-objective optimisation study, which revealed that a drastic reduction of the roof height and the roof radius by 96.9 % and 50 % respectively may reduce the wind speeds and the flow heterogeneity up to 37 % and 49.6 % in the occupied areas.

Outdoor air quality in the UK is widely governed by existing regulations. This is in contrast to the quality of air indoors which is managed by prescribing ventilation rates recommended by stakeholders from the building industry. This ventilation approach stems from the 1930s, when Yaglou first raised the importance of minimum building ventilation rates to remove body odour from rooms. The minimum ventilation rates approach may deliver acceptable indoor air quality (IAQ) for standard sized rooms, however, when considering large spaces this approach is insufficient.

The decision to use Off-Site Manufacturing (OSM) as a construction strategy in the house building industry is often made using ‘gut-feel’ or poor information and at the wrong time and for the wrong reasons. Research has shown that the correct use of OSM in house building has the potential to address some of the key challenges facing the UK house building industry, such as the increase in supply of new homes, skills shortage gap, the need to reduce CO2 emissions and environmental impacts, reduce overall project duration, minimise overall project costs, and reduce defects in new housing. However, with poor decision making surrounding the use of OSM, this potential remains untapped.

One of the principle causes for deviations between predicted and simulated performance of buildings relates to the stochastic nature of their occupants: their presence, activities whilst present, activity dependent behaviours and the consequent implications for their perceived comfort. A growing research community is active in the development and validation of stochastic models addressing these issues; and considerable progress has been made. Specifically models in the areas of presence, activities while present, shading devices, window openings and lighting usage. One key outstanding challenge relates to the integration of these prototype models with building simulation in a coherent and generalizable way; meaning that emerging models can be integrated with a range of building simulation software. This thesis describes our proof of concept platform that integrates stochastic occupancy models within a multi agent simulation platform, which communicates directly with building simulation software. The tool is called Nottingham Multi-Agent Stochastic Simulation (No-MASS). No-MASS is tested with a building performance simulation solver to demonstrate the effectiveness of the integrated stochastic models on a residential building and a non-residential building. To account for diversity between occupants No-MASS makes use of archetypical behaviours within the stochastic models of windows, shades and activities. Thus providing designers with means to evaluate the performance of their designs in response to the range of expected behaviours and to evaluate the robustness of their design solutions; which is not possible using current simplistic deterministic representations. A methodology for including rule based models is built into No-MASS, this allows for testing what-if scenarios with building performance simulation and provides a pragmatic basis for the modelling of the behaviours for which there is insufficient data to develop stochastic models. A Belief-Desire-Intention model is used to develop a set of goals and plans that an agent must follow to influence the environment based on their beliefs about current environmental conditions. Recommendations for the future development of stochastic models are presented based on the sensitivity analysis of the plans. A social interactions framework is developed within No-MASS to resolve conflicts between competing agents. This framework resolves situations where each agent may have different desires, for example one may wish to have a window open and another closed based on the outputs of the stochastic models. A votes casting system determines the agent choice, the most votes becomes the action acted on. No-MASS employs agent machine learning techniques that allow them to learn how to respond to the processes taking place within a building and agents can choose a strategy without the need for context specific rules. Employing these complementary techniques to support the comprehensive simulation of occupants presence and behaviour, integrated within a single platform that can readily interface with a range of building (and urban) energy simulation programs is the key contribution to knowledge from this thesis. Nevertheless, there is significant scope to extend this work to further reduce the performance gap between simulated and real world buildings.

This thesis presents the development of a new, stochastic bottom-up model for predicting household appliance energy demand, named the Household Appliance Usage (HAU) model. Three sub models are developed which have different functions and are based on different supporting datasets. Firstly, 2013-2014 English Housing Survey (EHS), a UK Government national representative household sample of around 17,000 homes, is chosen to provide a platform to generate the electricity demand profiles. Secondly, an appliance ownership model is developed where the nationally representative household sample is populated with electrical appliances using the appliance saturation levels derived from 2011 UK Government s Energy Follow-Up Survey (EFUS) of 3000 homes. Thirdly, an occupant behaviour model is developed where appliance behaviour metrics are simulated using monitored data from the UK Government s 2011 Household Electricity Survey (HES) of 225 homes, and electricity demand profiles are generated using the results of the appliance behaviour model. A new approach to bottom-up occupant behaviour modelling for predicting the use of household electrical appliances in domestic buildings is presented. Stochastic model predictions are made for individual households and appliances which can be used as inputs for the dynamic thermal simulation of 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 in the HES sample. The analysis shows that occupant behaviour varies substantially between households, across appliance types and over time. This new modelling approach uses probability and cumulative distribution functions to capture daily variations and is based on individual households and appliances. It is shown to have advantages for modelling the variations in appliance occupant behaviours. Two minutely household appliance electricity demand profiles are generated using the appliance behaviour metrics and power demand during usage. The comparison of simulation results and measured values show that the HAU model daily power demand predictions closely match the measured data (up to 8% difference during peak time). iii The final HAU (Household Appliance Usage) model, which generates aggregate electricity demand profiles of 13,276 households that were randomly populated with appliances for 16 appliance types, is scaled up to national level using the weighting factors calculated by the 2013-2014 EHS study. The HAU model is then applied to demand shifting of individual appliance in the households to evaluate the extent that electricity demand could be shaped by time shifting. The findings provide insights about the amount of residential load that is available for shifting and a discussion is presented on the future potential of household electricity demand response. The implications of findings for policy, industry and research are discussed. The thesis discusses the design of future monitoring studies (including monitoring strategies and sample sizes) and the design of future research studies (including statistical analysis, probabilistic modelling and validation approaches) in order to further improve our understanding of and ability to predict the behaviours of occupants and their use of household appliances within buildings.