Understanding Room Detection

Enscape Impact automatically detects and analyzes room data from your project’s geometry to provide energy performance insights. Here’s how the room detection process works and how you can ensure more accurate results:

1. What is Room Detection?

Room detection in Enscape Impact identifies enclosed spaces (rooms) from the geometry visible in your CAD model. It creates simplified room shells (essentially boxes) for each detected room and runs energy performance analysis based on that model. Different project views can yield different results because the analysis is performed on the visible geometry in the selected view.

2. Room Detection Limitations

Not all spaces in your project will be detected as rooms. For example, small spaces below 35 cm in any dimension (height, width, or depth) are ignored and merged with neighboring rooms. Additionally, shading elements are not detected as part of the analysis.

3. Voxel Accuracy and its Effect on Analysis

Enscape Impact uses voxels—3D “pixels”—to fill detected rooms and perform analysis. Each voxel is 35 cm in size. While this ensures efficient processing, it introduces a margin of error (up to 35 cm). This means that rooms might be slightly simplified, and the analysis may not reflect every small detail.

4. Improving Room Detection Accuracy

To improve the accuracy of your analysis:

• Ground Modeling: Ensure that floors and ground planes are modeled correctly.
• Simplify Geometry: Hide unnecessary objects like furniture, decorative elements, or assets that do not affect the analysis (Enscape assets are filtered by the algorithm, but hiding them can improve the performance).
• Transparent Materials: Ensure windows have transparent materials since the algorithm detects windows based on material transparency.Improving Room Detection Accuracy
  To improve the accuracy of your analysis:
• Clean Geometry: Check that there are no large openings (>35-70 cm) in your rooms that might prevent them from being detected as enclosed spaces.

You can also analyze different buildings separately to improve performance, as each building will be treated independently in the analysis.

5. What is Considered a Room?

A room is any enclosed space that is fully surrounded by geometry. Rooms must have dimensions greater than 35 cm in height, width, and depth to be considered. Large openings (over 35-70 cm) in a room will prevent it from being detected as enclosed.

6. Room Detection and Simulation Errors

Room detection is triggered every time Enscape Impact runs an analysis. It is triggered if you make changes to the geometry in your CAD model or if you change the project settings in Enscape Impact. Simulation errors can occur if the geometry is too complex, incomplete, or if there are large gaps between room boundaries. If you suspect there is an issue with room detection, such as missing rooms or inaccurate results, check if the geometry fits the room definition criteria. If you notice any issues, review your geometry and/or send us the logs so we can assist you with analyzing the issues.

7. Detecting Windows and Roofs

• Roofs: Roofs are automatically detected based on the upper boundaries of rooms with no geometry above them.
• Windows: The algorithm identifies windows based on their transparency. Transparent materials will be detected as windows.

8. Tips for Faster and More Accurate Analysis

• Use Separate Views: Set up different views in your CAD software for different buildings. Analyzing them individually improves performance and accuracy.
• Hide Non-Essential Elements: Hide elements that don’t affect energy performance, such as decorative objects or Enscape assets, to reduce calculation time.

Data inputs effect on analysis

Location

If the project has a location set, Enscape Impact will use this location as default. Longitude, latitude and elevation are taken into consideration. Users can change the location in the Settings tab at any time. The selected location assigns the relevant Climate zone automatically and an appropriate weather file (more about the weather files: https://www.iesve.com/support/weatherfiles). The climate zones are defined using the ASHRAE Standard 169-2009. IES follows the standard utilizing the following climate zones. Similar zoning maps are defined for the whole world, so your project can have any location.

Building types

Building types in Enscape Impact are based on ASHRAE building types. The selected building type defines the relevant operational schedules, internal loads and space conditions assigned to the model.
The first version of Enscape Impact offers the following building types:

• Single family
• Multiple family
• Office
• School or University
• Hospital
• Dining

As only one type can be selected, select the main building type. This may change in future versions of Enscape Impact. Additional building types will also be included.
In case the model includes several independent buildings with different main building types, they can be analyzed one by one using different views with the rest of the model being hidden and the building type changed according to the main building function.
Analyzing parts of one building independently based on function (example first floor is dining, second floor is office) is not advisable as the building envelope will have different performance and you will receive inaccurate results.

Building and renovation years

The Building age ranges are defined based on the available ASHRAE Standards editions. The following are used:

The appropriate standard is applied based on the building type and standard revisions, as the standard is applicable to buildings built after its issue date. ASHRAE 90.1 applies to all buildings except low-rise residential buildings. ASHRAE 90.2 applies only to low-rise residential buildings.

Default Datasets

Based on the inputs described above, default datasets developed by IES are assigned. The model is layered up with thermal properties and systems information suitable for the location, age, and building type. This includes relevant building fabric details, operational schedules, internal space conditions, typical internal loads, heating, ventilation, and air conditioning system types. IES derives the datasets to configure the buildings from the following ASHRAE Standards & User Manuals:

• Energy Standard for Buildings Except Low-Rise Residential Buildings, Versions: ASHRAE 90.1:2019, ASHRAE 90.1:2016, ASHRAE 90.1:2013, ASHRAE 90.1:2010, ASHRAE 90.1:2007, ASHRAE 90.1:2004
• Energy Standard for Buildings Low-Rise Residential Buildings, ASHRAE 90.2:2018
• Ventilation for Acceptable Indoor Air Quality, ASHRAE 62.1:2016
• Climatic Data for Building Design Standards, ASHRAE Standard 169-2013

Default Datasets content

The beta version of Enscape Impact uses these data sets to calculate building performance:

Heating System

• Heating Operation Profile
• Heating Setpoint
• Heating Plant Profile
• Heating Plant Radiant Fraction

Cooling System

• Cooling Operation Profile
• Cooling Setpoint
• Cooling Plant Profile
• Cooling Plant Radiant Fraction

Auxiliary Ventilation System

Domestic Hot Water System

• Hot Water Consumption
• Hot Water Consumption Pattern

Lighting

• Lighting Type
• Sensible Gain
• Variation Profile

Occupancy

• Occupancy Density
• Sensible Gain
• Latent Gain
• Variation Profile

Other Loads

• Load Type
• Sensible Gain
• Latent Gain
• Variation Profile

Infiltration

• Max Flow
• Variation Profile

In upcoming Enscape Impact versions there will be advanced options to change the default datasets.

Model calculations

Based on all inputs for the energy model, calculations are performed with IES’s APACHE engine. Widely regarded as the best whole-building energy simulation engine in the world, the powerful APACHE engine is used in this integration. The engine benefits from the dynamic thermal simulation with a time step output, that sits at the heart of any simulation that considers the energy efficiency or sustainability of a building from an energy or carbon usage viewpoint. Fully adherent with international standards APACHE helps designers worldwide effectively decarbonize their buildings. APACHE engine considers a complete virtual representation of the real building using first-principles models of heat transfer processes and are driven by recorded or future prediction weather data. Calculations consider the exact location of solar penetration and the associated solar gain throughout the building, and pressure network calculations assess both natural ventilation and forced air movement. Calculating size and select air- and waterside HVAC systems, APACHE provides a complete understanding of energy and carbon usage prediction for both the building and its equipment.

* More information on the used methodologies can be found here.

Benchmarking data

Benchmarking data is added so calculation results can be presented in a more user friendly way. Benchmarks for each building type have been generated based on the CBECS & RECS databases for North America as defined and shared by the U.S. Energy Information Administration (EIA), relevant for the building type and its location.
Benchmarking source for the United Kingdom and Republic of Ireland based buildings has been derived by IES to provide location specific benchmark assessment.
IES utilized the following databases:

• DECC measured data 2017
• CIBSE magazine measured data case studies 2017
• UK Public Authority published measured data 2017

IES created quartile ranges for the benchmarking. Quartiles are cut points that divide the range of a probability distribution into continuous intervals with four equal probabilities (as in one-fourth) of the
spectrum, as shown in the picture.

Benchmarking quartiles are climate reactive and aligning ASHRAE building types with CBECS & RECS databases for North America, and DECC, CIBSE and UK Public Authority data for United Kingdom and Ireland. The mapping of building types for each set is specified below:

• Single family – RECS Single Families Detached
• Multiple family – RECS Multi Family Large
• Office – CBECS Office
• School or University – CBECS Education
• Hospital – CBECS Inpatient Healthcare
• Dining – CBECS Food Service

Enscape Impact does not gather data from user projects for benchmarking.

Results

The accuracy of the results is based on how closely the default datasets match the actual design (see 1.4). Below are the key insights provided by Enscape Impact:

1. Peak Loads

Definition: Peak load refers to the energy consumption of the building during the most severe weather conditions, whether extreme heat or cold. This load is used to determine the size and capacity required for the HVAC systems.

• What’s Included: Peak load calculations consist of the highest demand for heating or cooling throughout the year. It does not include energy consumption for electricity, hot water, or internal gains like lighting and appliances.
• How Calculated: Peak loads are determined based on weather conditions from the selected location’s weather file and standards specified by ASHRAE. Only extreme or “design conditions” are considered, so it doesn’t simulate the entire year.
• Purpose: Peak loads help establish the size of systems like HVAC to ensure that they can meet the building’s maximum energy demands.
• Exclusions: The peak loads do not include internal gains, solar gains, electricity, or hot water energy.

2. Carbon Emissions

Definition: Carbon emissions represent the total annual carbon output from building operations. This includes emissions from gas, oil, and electricity used to operate the building.

• What’s Included: The sum of emissions generated from the building’s operational needs, specifically heating, cooling, lighting, and electricity.
• How Calculated: Based on the energy end-use data, the results reflect the annual emissions caused by operational energy demand. This includes emissions from fossil fuel sources and electricity, depending on the energy source mix.

3. Energy Use Intensity (EUI)

Definition: EUI is a measure of the building’s total energy consumption per year divided by its floor area, representing its overall energy efficiency.

• What’s Included: EUI includes all forms of energy used during the building’s operation (gas, oil, electricity).
• How Calculated: The total energy consumed for heating, cooling, lighting, and other operational needs is divided by the building’s total floor area. This is then expressed as energy per square meter or square foot.

4. Energy End Use

Definition: Energy end use breaks down the total energy consumption by category, helping users understand how much energy is used for cooling, heating, hot water, lighting, and other electricity needs.

• What’s Included: Energy distribution is shown between key categories, including heating, cooling, hot water, lighting, and other electrical demands.
• How Calculated: The energy end use results are derived based on default datasets and the selected building and weather conditions, allowing users to see how energy is allocated among different systems.

Peak loads

Reducing the peak load of a building during the early design stage can significantly enhance its energy efficiency, reduce operational costs, and improve occupant comfort. The lower the value, the better. Here are some strategies and design considerations to help achieve this in early design stages:

Optimize Building Orientation and Layout

• Orientation: Orient the building to maximize natural daylight and reduce solar heat gain, especially in hot climates. South-facing windows (in the Northern Hemisphere) can provide beneficial winter solar gain.
• Zoning: Design internal spaces to create thermal zones based on their usage patterns, allowing for more efficient heating and cooling control.

Enhance Daylighting and Shading

• Daylighting: Use skylights, light shelves, and clerestory windows to enhance natural light distribution, reducing the need for artificial lighting.
• Shading Devices: Incorporate external shading devices (e.g., overhangs, louvers) and internal shading (e.g., blinds, curtains) to control solar heat gain and glare.

Renewable Energy Integration (not included in this version of Enscape Impact)

• Solar Panels: Incorporate solar photovoltaic (PV) panels to generate on-site renewable energy, reducing dependency on external power sources.
• Solar Thermal: Use solar thermal systems for water heating to reduce the load on conventional water heaters.

Landscaping and Site Design

• Vegetation: Use landscaping to provide natural shading and windbreaks, which can reduce heating and cooling loads.
• Green Roofs: Install green roofs to provide additional insulation and reduce the urban heat island effect.

Carbon emissions

Reducing operational carbon emissions is a key goal in sustainable building design, and one of the most effective ways to achieve this is by targeting areas where energy consumption is highest.

Reducing Carbon Emissions through Peak Load and Energy End Use Improvements:

• Peak Loads: Reducing the building’s peak heating and cooling loads can significantly cut down the overall energy consumption during periods of maximum demand. By minimizing these peaks, the systems in place, like HVAC, can operate more efficiently, leading to lower carbon emissions.
  • See the Peak Loads section to explore ways to manage heating and cooling requirements during extreme weather conditions.
• Energy End Use: Understanding the breakdown of energy usage (heating, cooling, lighting, hot water, etc.) enables targeted efficiency measures, helping reduce energy demand in specific areas. Lowering overall energy consumption directly correlates with a reduction in carbon emissions.
  • Refer to the Energy End Use section to discover how analyzing energy distribution can help you identify areas for improvement.

By reducing both peak loads and energy end use, designers can take strategic actions to lower the building’s operational carbon emissions, leading to a more sustainable and efficient design.

Energy Use Intensity

The Energy Use Intensity (EUI) is benchmarked against data from similar buildings in terms of building type, size, age, and climate zone (see Benchmarking data). The EUI measures the total energy consumption per square meter or foot of building space, and the result is displayed on a color-coded dial for easy interpretation.

Red Dial: The building’s EUI is among the 71-100% of the benchmarked buildings, indicating a high energy use compared to similar buildings.

Yellow Dial: The building’s EUI is among the 31-70% of the benchmarked buildings, reflecting average energy use.

Green Dial: The building’s EUI is among the 0-30% of the benchmarked buildings, showcasing high energy efficiency.

Strategies to Improve EUI:

1. Optimize Building Orientation and Massing

• Orientation: Position the building to maximize natural daylight and passive solar heating, while minimizing excessive solar gain to reduce cooling demands.
• Shape and Massing: Design compact building shapes to minimize the surface area exposed to external temperature variations, helping to reduce heat transfer.

2. Improve Daylighting Efficiency

• Daylighting: Incorporate large windows, skylights, and light wells to maximize natural light penetration, thereby reducing the need for artificial lighting and lowering overall energy consumption.

Improving the EUI during the early design stages can significantly enhance a building’s energy performance, reduce operational costs, and increase sustainability.

Energy end use

The Energy End Use breakdown helps users understand how energy is distributed among various systems such as cooling, heating, hot water, lighting, and electricity annually. Knowing the breakdown early in the design stage offers valuable insights, allowing you to target specific areas for improvement and optimize overall energy performance.

By analyzing the energy end-use data, users can identify which systems are the major energy consumers and prioritize efficiency measures where they will have the most impact. For example, if cooling is a significant energy user, you might consider adjusting the building’s orientation, shape, or glazing to reduce the cooling demand.

Benefits:

• Identify Major Energy Consumers: Determine which systems consume the most energy, helping you focus on efficiency improvements for HVAC, lighting, or other energy-intensive systems.
• Targeted Design Adjustments: For example, lowering cooling energy requirements can be achieved by rethinking building orientation, window placement, and glazing to minimize heat gain.

This information helps you optimize the design to reduce energy use, increase sustainability, and potentially lower operational costs.

False color visualizations

The False Color Visualization feature allows users to visually analyze the performance of each room in terms of peak loads, heating, cooling, and solar gains. Performance is calculated individually for every room, and the rooms with the lowest and highest values form the scale. This means that rooms with very close performance values can still appear dramatically different in color (e.g., blue vs. red), as they set the boundaries for the color range. It’s important to check the scale values for precise interpretation.

This feature helps designers easily spot rooms that may require design improvements by highlighting performance disparities across the building. By identifying problematic rooms, users can implement targeted measures to improve the building’s overall performance.

Examples of solar gains:

• Which rooms receive the most solar gains? These rooms might benefit from less glazing or the addition of shading elements to prevent overheating.
• Which rooms receive the least solar gains? These may need more glazing or other design changes to ensure they meet lighting and energy needs effectively.

The False Color Visualization tool is a quick and intuitive way to analyze and optimize the building’s design for better performance.