Thermal simulation outputs: exploring the concept of patterns in design decision-making

Figures & data

Figure 1. Elements of an outline pattern.

Table 1. Generic questions related to design aims in using BPS (from Bleil de Souza and Tucker 2014).

Index	Questions related to aims	Type of question	Analysis process
Exploring a specific design strategy
E1	How does this building perform?	Performance query	Descriptive
E2	How do these buildings perform in relation to each other?	Performance query	Comparison of two or more models
E3	What is the effect on performance when a single parameter is changed?	Performance query	Comparison with previous model
E4	What is the effect on performance when several parameters are changed simultaneously?	Performance query	Comparison with previous model
Understanding specific performance results
U1	What is causing the performance of this building?	Advice	Elimination parametric
U2	How sensitive is this building to design parameter X?	Advice	Sensitivity test
U3a	How sensitive is this building to user defined parameters X, Y, Z, … n ?	Advice	Sensitivity test
U3b	How sensitive is this building to automatically pre-defined parameters X, Y, Z, … n ?	Advice	Sensitivity test
Meeting a target
T1	How does this building perform in relation to target(s)?	Performance query	Comparison with target
T2	What is causing the performance of this building not to meet the target(s)?	Advice	Elimination parametric
T3a	How sensitive is this building to user defined parameters X, Y, Z, … n in relation to target(s)?	Advice	Sensitivity test
T3b	How sensitive is this building to automatically pre-defined parameters X, Y, Z, … n in relation to target(s)?	Advice	Sensitivity test
T4a	What are optimum values of user defined parameters X, Y, Z, … n to meet target(s)?	Advice	Optimisation
T4b	What are optimum values of automatically defined parameters X, Y, Z, … n to meet target(s)?	Advice	Optimisation
Assessing a specific product
AP1	How does this building perform with this product?	Performance query	Descriptive
AP2	What is causing the performance of this building with this product?	Advice	Elimination parametric
AP3	How sensitive is this building to parameters X, Y, Z, … n of the specific product?	Advice	Sensitivity test
AP4	What are optimum values of parameters X, Y, Z, … n of the specific product?	Advice	Optimization
Optimizing
O1a	What are optimum values of user defined parameters X, Y, Z, … n for best performance?	Advice	Optimization
O1b	What are optimum values of automatically defined parameters X, Y, Z, … I for best performance?	Advice	Optimization

Figure 2. Information required in an outline pattern.

Figure 3. Computer model (Integrated Environmental Solutions) of Ellingham School designed by ECD Architects, London.

Table 2. Examples of patterns.

	Goal/question	Model settings	Simulation/analysis/ post-processing	Outputs (overview)	Interaction with outputs
1	Will the building meet BB101 overheating targets in 2020, 2050, 2080? What would the energy use be?^a	1. Base case: As per drawings/ specifications. Settings follow recommendations.^b	Descriptive analysis.	Text: BB101 PASS or FAIL.	Zoom: Location and time (produces Bar chart: Heat and cool energy).^e
		1a. Free-running.	Weather files:^c	Table of BB101 figures.	Bar chart: Heat and cool energy
		1b. With heat/cool system.	2020/H/90/DSY	Bar chart: Annual heat and cool energy.^d
			2020/H/50/DSY
			2050/H/90/DSY
			2050/H/50/DSY
			2080/H/90/DSY
			2080/H/50/DSY
2	Will the fixed shading as designed be sufficient until 2050, or should it be made adjustable or extendable?^f	1. Base case.	Comparative analysis.	Text: BB101 PASS or FAIL.	Zoom: Location and time (produces Bar chart: Heat and cool energy)
		2. No shading.	Weather files:	Table of BB101 figures.	Bar chart: Heat and cool energy^e
		3.100% efficient shading.^g	2050/H/90/DSY	Bar chart: Annual heat and cool energy.
		Each model simulated with:	2050/H/50/DSY
		3 * ventilation values (1, 3, 5 ac/h).
		2 * internal gains values (low and standard).

^a BB101 specifies the recommended overheating limits for UK schools.

^b All settings for ventilation, internal gains, etc. follow appropriate recommendations (e.g. from the Chartered Institute of Building Services Engineers). Simulations include free-running and for heating & cooling loads.

^c Probabilistic weather files are represented as ‘year/emissions scenario/percentile/file type’.

^d The outputs shown are thought to be the minimum required for answering the question.

^e Zoom into user selected time range and location (e.g. classroom).

^f The second part of this question is addressed by reframing it as ‘does the building need any shading at all?’

^g The ‘100% efficient shading’ model gives a result that indicates whether any shading solution will work. The range of values for ventilation and internal gains represent different scenarios.

Figure 4. User facing pattern template.

Figure 5. Draft template (user facing) of a pattern for testing room temperatures and comfort levels.

Figure 6. Draft template (developer facing) of a pattern for testing reduction of overheating through shading.

Table 3. Proposed hierarchy of patterns.

Level	Type/purpose	Modelling details/notes
High-level, planning related	Site analysis, guidance on climatic strategies, passive and low-energy strategies and renewable energy systems potential	Simple models (from a library) could be used to test concepts (e.g. heavy – lightweight, insulation levels, glazing for solar gains) and explore site and overarching design strategy
Mid-level, building related	Exploring building form, glazing ratios, insulation of building elements, preliminary calculations on renewable energy systems integration and site specific ‘rules-of-thumb’	Models (user generated) tend to have many defaults ascribed
Low-level, detailed modelling	Effect on performance of building parameters, plant efficiencies and effect of occupants	User-detailed model is constructed to carry out detailed building performance experiments

Table 4. Outline of pattern selection procedure

Step	Description
1	Identify question(s) by selecting and modifying from a list (as in Table 1) or drop down menus, or through use of a natural language user interface (see e.g. Androutsopoulos, Ritchie, and Thanisch 1995)
2	Information retrieval method recovers/constructs/modifies appropriate patterns
3	User selects required pattern
4	Pattern produces any required input dialogue
5	Pattern runs simulations and produces outputs, options for interaction with results and links to appropriate further patterns

Table 5. Problems identified in interviews.

Problems of communication: Communication problems occurred in relation to consultants, clients, planners and others and include:

Delays in getting feedback from consultants on building performance

Being unable through lack of knowledge and information to be able to discuss the recommendations of the consultant in terms of implications on the design (as opposed to simply having to accept them)

Feedback from consultants does not include information on how to change the design to improve it or why it is unsatisfactory (i.e. relative effect of parameters on performance)

Dissatisfaction with ‘separation’ of consultant from design process and development and the effects of this on the final design

Dissatisfaction with simplified methods used by consultants that result (in the opinion of the designers) in a ‘sub-optimal’ design

Problems of effectively displaying information to clients on relationships between design decisions, performance and cost

Use of one tool in the practice (e.g. daylighting assessment) but not the others required for the project (e.g. thermal)

Being unable to effectively share knowledge (e.g. on performance benchmarks for specific building typologies)

Problems accessing performance information: These types of problem typically occur at early design stages and include:

A need for sensitivity testing of building elements that designers are interested in manipulating

The need to guarantee to planners at an early stage a performance level, without understanding fully the implications that this will have on the design and strategy

Lack of procedures for testing proposed strategies throughout the design process

Problems involving costs: Costs were related to the building and its operation, and time spent on design-related work

Increased performance modelling costs at early design stages

Difficulties in relating capital, in-use and life cycle costs

Table 6. Initial responses to patterns concept from building designers.

Communication and design management

Patterns could

facilitate informed conversations with engineers and consultants

allow designers to check on the results and recommendations of consultants and be able to query their advice

provide more information and insight into the results: information on which design parameters could be changed and by how much to improve performance

facilitate demonstration to clients of the advantages of a proposal

deliver reports in a user preferred format

assist in the timing of decision-making

hold benchmarks for energy, lighting and local benchmarks related to building control

hold ‘internal benchmarks’ (i.e. benchmarks chosen by the practice)

support ‘integrated design’ (i.e. integrating all aspects of design into the building)

Performance-related information

Patterns could

provide identification of potential performance problems with respect to building regulations at the start of a project

provide instant feedback on the effect of design actions

facilitate early exploration of design strategies

facilitate understanding of cause and effect (i.e. a building parameter's effect on performance)

be of use in developing modular or prototype rooms or buildings

facilitate life cycle costing and performance studies

Suggestions for related patterns

integrate lighting and thermal studies and show the results in a consistent ‘client-friendly’ format

test for overheating risks

sensitivity tests on specified parameters to identify alternative designs

determine window sizing

exploring ratio of opaque/glazed areas for office buildings

exploring effect of shading on daylighting and overheating/space heating energy within a context of costs

explore relationships between ventilation, CO2 levels and overheating in schools

refurbishment modelling (in the context of uncertainty of existing building element compositions)

rights to light modelling

Bleil de Souza, C., and S. Tucker. 2014. “Thermal Simulation Software Outputs: A Framework to Produce Meaningful Information for Design Decision Making.” Journal of Building Performance Simulation. http://dx.doi.org/10.1080/19401493.2013.872191

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Androutsopoulos, I., G. D. Ritchie, and P. Thanisch. 1995. “Natural Language Interfaces to Databases – An Introduction.” Natural Language Engineering 1 (1): 29–81. doi: 10.1017/S135132490000005X

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