Abstract
The Low-Carbon Innovation Building (LCIB) Digital Twin is a physics-based thermodynamic simulation embedded directly on this website at /LCIB_DIGITAL_TWIN/. It models the energy performance of a building in real time, enabling users to adjust parameters — occupancy schedules, HVAC setpoints, insulation R-values, window-to-wall ratios, and external climate conditions — and immediately observe their impact on indoor temperature profiles, energy demand curves, and CO₂ footprint estimates.
The underlying physics is rooted in conservation of energy and mass balance: the model solves transient heat transfer equations governing conduction through walls and roofing assemblies, convective exchange with indoor air, and radiative gains from solar irradiance. HVAC loads are computed from enthalpy balance across cooling/heating coils, with fan power modelled as a function of air-exchange rate and duct pressure drop. Carbon accounting ties electricity consumption to grid emission factors, producing a real-time CO₂ intensity metric.
This work connects to Prof. Afzal's broader research programme in digital twins and physics-informed neural networks. Where traditional building energy simulation tools (EnergyPlus, TRNSYS) require desktop installation and lengthy batch runs, the LCIB Digital Twin runs at interactive frame rates in a standard web browser — no plugins, no downloads. Users can toggle between parametric sweeps and single-point analyses, making it a practical sandbox for early-stage design exploration.
The interactive tool is available on this website. Navigate to the LCIB Digital Twin section to launch the simulator. Adjust sliders for occupancy count, thermostat setpoints, roof tinting levels, and insulation thickness. The dashboard updates in real time, displaying room temperature trajectories, ventilation rates, oxygen and CO₂ concentrations, and cumulative energy consumption.
Digital twins are rapidly becoming essential infrastructure for low-carbon building design. By coupling physics-based models with real-time data streams, they enable continuous performance monitoring, predictive maintenance scheduling, and what-if scenario analysis — capabilities that static simulation tools cannot provide. For architects evaluating passive design strategies, sustainability engineers benchmarking LEED or GRIHA compliance, and facility managers optimising operational energy budgets, the LCIB Digital Twin demonstrates how computational modelling translates directly into actionable design intelligence.
Key Findings
- Real-time thermodynamic solver runs at interactive frame rates in a standard web browser with no plugins required.
- Users can adjust occupancy, HVAC setpoints, insulation values, and solar shading to see immediate impact on energy demand and CO₂ footprint.
- The model solves transient heat transfer equations for conduction, convection, and radiative gains with HVAC enthalpy balance.
Interactive Digital Twin Sandbox — Low-Carbon Innovation Building (LCIB)
Below is the live, browser-based thermodynamic digital twin simulator (the same interactive engine as on the home page). Adjust outdoor temperatures, sunroof tinting, occupancy loads, and AC setpoints to evaluate real-time thermal comfort, HVAC energy demand, and CO₂ footprint.
Methodological Approach
The simulation solves conservation of energy and mass balance equations for temperature, CO₂, and O₂ levels within a multi-zone building control volume, using real-time inputs for external climate, occupancy, and HVAC setpoints. Physics includes wall conduction, convective air exchange, solar radiative gains, and HVAC enthalpy balance.
Implications for Hydraulic Practice
Allows architects, sustainability engineers, and building managers to evaluate insulation properties, ventilation rates, and control strategies to minimise carbon footprint and maintain thermal comfort — directly in the browser, without specialised software.
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