Table of Contents
Type: Dissertation Proposal | Subject: Engineering (Building Services and Energy) | Level: Masters | Word Count: ~2,300 words
This model dissertation proposal was produced by an Essays UK specialist as reference material for learning purposes only. For support in this field, see our engineering dissertation writers.
Overview: This proposal sets out a simulation-based Masters study into how Building Information Modelling (BIM) can support the energy-efficient retrofit of UK dwellings. It frames the research problem, reviews the relevant literature, and specifies a case-study methodology built around calibrated dynamic thermal simulation, a staged project timeline with a Gantt chart, and a clear ethics plan. It is provided as a model example of an engineering dissertation proposal.
The decarbonisation of the built environment has become a central concern for UK energy and climate policy. Residential buildings account for a substantial share of national energy demand and carbon emissions, and a large proportion of the housing stock that will still be standing in 2050 has already been built. Because new-build rates are low relative to the size of the existing stock, meeting the United Kingdom’s legally binding commitment to net-zero greenhouse gas emissions by 2050 (HM Government, 2019) depends heavily on the deep retrofit of existing homes rather than on new construction alone.
Retrofit measures such as improved insulation, airtightness upgrades, low-carbon heating and glazing replacement can reduce operational energy demand considerably. Yet the performance achieved in practice frequently falls short of design predictions, a discrepancy widely described as the “performance gap”. Where interventions are poorly specified or badly sequenced, they can also introduce unintended consequences such as interstitial condensation, poor indoor air quality or summertime overheating. Narrowing this gap requires design tools that can test measures rigorously before any physical work begins.
Building Information Modelling (BIM) offers a promising route to this goal. By combining a geometrically accurate digital model with structured data on materials, building services and performance, BIM allows the energy behaviour of a dwelling to be simulated, compared and refined at the design stage. Simulation-led retrofit lets alternative packages of measures be evaluated, costed and ordered so that the most effective combination is chosen for a given property. Despite growing interest, the application of BIM to domestic retrofit in the UK remains comparatively immature, and robust, case-study evidence of its value is limited. This study responds to that gap by applying a BIM-based energy simulation workflow to a small set of representative case-study dwellings.
The core problem addressed by this research is the persistent uncertainty surrounding the predicted energy savings of domestic retrofit, and the limited integration of BIM into the retrofit decision-making process. Standard assessment procedures used for compliance tend to rely on simplified, steady-state calculations that may not capture the dynamic thermal behaviour of a building or the interaction between individual measures. As a result, decision-makers often lack a reliable, transparent basis for selecting and prioritising interventions. If BIM-based dynamic simulation can be shown to produce more realistic and better-sequenced retrofit strategies for typical UK dwellings, it would offer practical value to designers, housing providers and policymakers seeking cost-effective routes to decarbonisation.
The aim of this research is to evaluate how a BIM-based energy simulation workflow can support the selection and sequencing of energy-efficiency retrofit measures for UK residential buildings, using case-study dwellings as the unit of analysis.
To achieve this aim, the study pursues the following objectives:
The objectives are framed by three research questions:
The preliminary review is organised around three themes that will be developed in the full dissertation. These themes situate the study within existing scholarship and clarify where it contributes.
A recurring theme in the literature is the gap between predicted and actual energy performance in retrofitted dwellings. Studies attribute this gap to factors including workmanship and installation quality, unmodelled thermal bridging, occupant behaviour and the limitations of simplified assessment tools (Ahmed and Fletcher, 2021). Research on occupant behaviour in particular suggests that heating patterns, ventilation habits and the so-called rebound effect, in which efficiency gains are partly offset by increased comfort-taking, can materially alter realised savings (Thompson and Owusu, 2022). The Climate Change Committee (2020) has highlighted that the current pace and quality of domestic retrofit are insufficient to meet national carbon targets, underlining the need for better design-stage prediction. The introduction of the retrofit standard PAS 2035 (British Standards Institution, 2019) reflects a policy shift towards a whole-dwelling, risk-based approach, which places greater demands on the modelling tools used to plan interventions.
A second theme concerns the use of BIM to support energy analysis. A BIM model can act as a single, structured source of geometric and material data that feeds energy simulation engines, reducing manual re-entry and the associated risk of error (Osei, Marshall and Zhang, 2022). Reviews of BIM in building retrofit report benefits in data consistency, visualisation and stakeholder communication, but also note recurring challenges: interoperability between authoring and simulation software, incomplete data for older buildings, and a shortage of standardised workflows. The transfer of data through exchange formats such as IFC and gbXML is frequently cited as a point of failure, where geometry, surface adjacencies or material properties are lost or misinterpreted and must be corrected manually before a model can be simulated reliably (Hughes and Bello, 2021). Much of the published work also focuses on commercial or non-domestic buildings, leaving the domestic sector comparatively under-examined.
The third theme addresses dynamic thermal simulation and model calibration. Dynamic simulation captures time-varying effects such as solar gains, thermal mass and intermittent heating that steady-state methods omit (Patel and Novak, 2020). However, the credibility of simulation depends on calibration against measured data, and guidance such as that issued by CIBSE (2015) sets out environmental design parameters that inform realistic modelling assumptions. The literature indicates that calibrated models can substantially improve predictive accuracy, yet calibration is time-consuming and data-dependent. Taken together, the three themes reveal a clear gap: there is limited case-study evidence on calibrated, BIM-based dynamic simulation applied specifically to UK domestic retrofit, which this study aims to address.
The study adopts a pragmatic research philosophy, selecting methods according to their suitability for answering the research questions rather than from a single fixed epistemological position (Saunders, Lewis and Thornhill, 2019). The design is predominantly quantitative, centred on building energy simulation, but incorporates a qualitative element through structured interpretation of the simulation results and the practitioner-relevant constraints observed during modelling. A multiple case-study strategy is employed because it allows an in-depth investigation of the phenomenon within its real context while permitting comparison across contrasting dwellings.
Three case-study dwellings will be selected to represent common archetypes within the UK housing stock: a solid-wall Victorian mid-terrace, a cavity-wall 1970s semi-detached house, and a post-2000 end-terrace. These archetypes are chosen because they differ markedly in fabric, age and typical performance, allowing the workflow to be tested across a realistic range of conditions. For each property, baseline data will be gathered, including dimensions, construction build-ups, heating systems and a period of recorded energy consumption. Where measured values are unavailable, illustrative assumptions drawn from published norms will be used and clearly identified as such.
For each dwelling a 3D BIM model will be authored in a BIM authoring tool (for example, Autodesk Revit) and enriched with thermal properties for each building element. The model will be exported, using an open data schema such as IFC or gbXML, to a dynamic energy simulation engine (for example, EnergyPlus accessed through a suitable interface). The baseline model will be calibrated against the available consumption data until modelled results fall within accepted tolerance bands, following the principle that calibration underpins credible prediction. Once calibrated, each model will be used to simulate a series of retrofit packages, for instance:
For each scenario the model will output annual heating and total energy demand, associated carbon emissions and peak loads, enabling systematic comparison against the calibrated baseline.
Data collection therefore combines documentary sources (construction records, energy bills and published performance data) with the simulation outputs generated for each scenario. Analysis will be comparative: scenarios will be ranked by modelled energy and carbon savings, and an indicative simple payback will be estimated from illustrative capital-cost figures to give a sense of cost-effectiveness. Sensitivity analysis will test how robust the rankings are to key assumptions, such as occupancy patterns and heating set-points, so that the conclusions are not unduly reliant on a single set of inputs. The qualitative layer will record practical observations on the workflow itself, such as interoperability issues and data gaps, directly informing the response to RQ3.
The study is deliberately bounded. It considers three dwellings rather than a statistically representative sample, so the findings will be analytically rather than statistically generalisable; the value lies in the depth of the case comparison and in the transferability of the workflow. Cost figures are illustrative and intended only to indicate relative cost-effectiveness, not to serve as a formal financial appraisal. Occupant behaviour, which the literature identifies as a major source of the performance gap, will be represented through standard and sensitivity-tested assumptions rather than monitored directly. These limitations are acknowledged so that the contribution of the study is neither overstated nor misread.
The dissertation is scheduled over a six-month period. The Gantt chart below summarises the main phases and their overlap; shaded cells indicate the months in which each task is active. The schedule deliberately front-loads model development and calibration, since these are the most technically demanding and uncertain activities, and reserves the final month for writing up and submission.
| Task | M1 | M2 | M3 | M4 | M5 | M6 |
|---|---|---|---|---|---|---|
| Literature review and refining aims | ||||||
| Case-study selection and data gathering | ||||||
| BIM modelling and baseline calibration | ||||||
| Scenario simulation and analysis | ||||||
| Writing up, review and submission |
Although the study is primarily technical and simulation-based, several ethical considerations apply, and the research will be conducted in line with the host institution’s ethics policy, with formal approval sought before any data collection. Where case-study dwellings are real properties, the addresses and any occupant details will be anonymised, and energy-consumption data will be handled in accordance with data-protection requirements and stored securely. Informed consent will be obtained from any property owners or occupants whose data is used, and participation will be voluntary. Because the modelling assumptions and illustrative cost figures carry uncertainty, the dissertation will report limitations transparently so that the findings are not overstated. No vulnerable groups are involved, and the simulation activity poses no physical risk.
The research is expected to produce calibrated BIM energy models for three representative dwellings, a comparative evaluation of retrofit packages, and a structured account of the practical strengths and weaknesses of the workflow. Its contribution is twofold: it adds case-study evidence on calibrated, BIM-based dynamic simulation for UK domestic retrofit, an area the literature shows to be under-examined, and it offers practitioners a tested, transferable workflow for retrofit decision-making. By making the basis for retrofit choices more transparent, the study also supports better communication between designers, clients and occupants. The findings are intended to support more reliable, better-sequenced retrofit strategies, helping to narrow the performance gap and contribute to wider decarbonisation goals.
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