Early-Stage Massing Decisions in School Buildings: Interactive Effects on Energy and Thermal Comfort Performance

Abstract

Early-stage architectural decisions strongly condition long-term energy demand and thermal comfort; however, their combined effects are often evaluated in isolation. This study investigates the interactive influence of mass configuration, orientation and the window-to-wall ratio (WWR) on the energy and thermal comfort performance of school buildings in Erbil, Iraq. Five representative school mass typologies were assessed using a structured two-phase simulation framework based on an Interactive Architectural Approach (IAA). The results reveal that mass configuration functions as a conditioning variable, governing not only absolute energy demand but also responsiveness to design variation. Articulated typologies showed amplified increases in cooling demand, overheating, and mean radiant temperature under a higher WWR, whereas compact forms exhibited comparatively stable behavior. Importantly, orientations minimizing energy demand did not consistently correspond to those minimizing thermal discomfort, revealing typology-dependent divergence between performance objectives. By quantifying interaction-based sensitivity rather than isolated parameter effects, the study advances IAA as a structured early-stage assessment framework for school design.

1. Introduction

The building sector remains one of the largest global consumers of energy and emitters of greenhouse gases, accounting for approximately 30–44% of total primary energy consumption and 30–40% of global CO₂ emissions worldwide [1]. Within buildings, the dominant share of energy demand is associated with heating, cooling, and lighting, all of which are strongly influenced by decisions made at the early design stage [2]. Unlike mechanical or façade systems that can be retrofitted or upgraded during a building’s lifecycle, geometric decisions related to massing, form, and spatial configuration are largely irreversible once established, exerting a long-term influence on energy demand and indoor environmental conditions [3,4].

Among early design variables, building mass configuration, orientation, and envelope geometry are consistently identified as primary geometric determinants of building performance [5,6]. Rather than acting independently, these parameters collectively interact to determine the building’s overall behavior by defining the solar exposure, façade area, thermal exchange and internal spatial organization. Given their active role in shaping operational energy performance and occupant comfort over time, understanding their combined effect and performance trade-offs is essential for informed early-stage design decisions.

Educational buildings, and school buildings in particular, represent a particularly critical context for investigating these relationships. Schools are characterized by long and predictable operating hours, high internal gains, and strict thermal comfort requirements that directly influence student well-being and learning performance [7,8]. In many regions, energy expenditure in public schools constitutes one of the largest operational costs after staffing, making performance optimization both an environmental and economic priority [9]. Furthermore, the standardized layouts, repetitive spatial modules, and consistent occupancy schedules typical of school buildings further make them especially suitable for the parametric modeling and systematic evaluation of early-stage design strategies [10,11].

1.1. Morphological Structure in Sustainable Building Design

Recent sustainability studies have shifted from technology-centered approaches toward recognizing spatial configuration as a structural determinant of environmental performance. Rather than framing sustainability solely through material efficiency or mechanical systems, contemporary studies emphasize how the compactness, aggregating patterns and geometric exposure fundamentally shape thermal exchange and resource demand [12]. At the building scale, mass configuration governs the surface-to-volume ratio, façade exposure and internal relationships, thereby influencing heating, cooling and ventilation behavior. While this morphology-driven perspective acknowledges geometry as a sustainability and performance driver, building-scale studies often evaluate geometric parameters parametrically without explicitly examining how predefined mass typologies condition sensitivity to orientation and envelope transparency. This distinction becomes particularly relevant when assessing early-stage design decisions, where typological form is typically established before detailed façade refinement.

1.2. Thermal Comfort and Performance in Educational Buildings

Thermal comfort, commonly defined as the condition of satisfaction with the thermal environment, is a critical performance criterion in educational buildings, influenced by both physical factors, such as air temperature, humidity, air velocity and radiant heat, and personal variables including an individual’s activity level and clothing [13]. In school buildings, overheating is particularly critical due to high occupancy and substantial internal gains from students, equipment and lighting, which can rapidly elevate indoor temperatures beyond acceptable comfort limits. Elevated classroom temperatures have been associated with reduced concentration, lower academic performance and increased occupant dissatisfaction [14]. Importantly, minimizing energy demand does not automatically ensure acceptable indoor conditions, and due to the role of early-stage geometric decisions in shaping solar exposure and thermal response and simultaneously affecting both energy demand and overheating risks, evaluating these performance domains together is therefore essential to identify potential trade-offs in school building design.

1.3. Literature Review

1.3.1. Massing Typology and Energy Performance

A substantial body of the literature has demonstrated that building mass configuration plays a significant role in shaping energy demand. Compact forms typically exhibit reduced thermal exchange due to lower surface-to volume (S/V) ratios, particularly in heating-dominated climates [15]. Meanwhile, in contrast, elongated, articulated, and courtyard-based configurations increase façade exposure, which can intensify both heat gains and losses depending on climatic context [16]. Studies focusing on school buildings report that mass configuration influences not only annual energy use but also the distribution of heating and cooling loads, confirming geometry as a first-order design variable in educational building performance [17].

1.3.2. Orientation Effects on Energy Use Intensity

Building orientation has been widely investigated as a determinant of solar exposure, cooling demand, and daylight availability. Simulation-based studies indicate that orientation can lead to measurable differences in energy use intensity (EUI), particularly in warm and cooling-dominated climates [18]. For elongated or directional building forms, orientation strongly influences solar gains and associated cooling loads [14]. However, several studies also report that orientation sensitivity diminishes as building compactness increases, suggesting that orientation effects are closely linked to mass configuration rather than acting as an independent parameter [19].

1.3.3. Window-to-Wall Ratio and Envelope Sensitivity

Envelope transparency, commonly expressed through the window-to-wall ratio (WWR), has been extensively examined in relation to energy demand and thermal comfort. A higher WWR increases cooling demand and elevates overheating risk due to greater solar heat gains, while reductions in heating demand are often comparatively limited [20,21]. Although lower WWR values can reduce total energy use, their impact on thermal comfort is more nuanced and strongly dependent on orientation, shading strategies, and massing configuration [21]. These findings highlight the WWR as a highly sensitive early-stage design parameter whose performance implications cannot be evaluated independently of geometric context [22].

1.4. Research Gap and Study Contribution

Existing research has established clear directional relationships between geometric design parameters and building performance outcomes; compact forms are generally associated with lower energy demand, a higher WWR tends to increase cooling loads and orientation impacts performance by influencing solar gains [23]. However, most studies evaluate these parameters independently or through broad optimization frameworks that do not explicitly investigate the role of mass configuration as an interactive mediator within structured early-stage assessment frameworks [24,25,26]. In particular, the Interactive Architectural Approach (IAA) has been introduced as a framework emphasizing the integration of multiple architectural parameters in design [27]. However, its operationalization for quantitative building performance evaluation, specifically incorporating mass configuration as a conditioning parameter influencing sensitivity to orientation and envelope transparency, has not been systematically developed [28,29].

This study advances the IAA framework by explicitly operationalizing mass configuration as an interactive architectural parameter within a structured performance assessment workflow. Rather than implementing full combinatorial simulations, a staged interaction sequential logic was adopted to reflect early-stage architectural decision logic and enable the isolation of typology-conditioned response behavior while maintaining methodological clarity. By integrating mass configuration within an IAA-informed evaluation framework, this study adopts an approach that reflects the practical sequencing of early-stage architectural decision-making, where orientation is typically established prior to detailed façade configuration, and contributes a typology-aware perspective that clarifies how early-stage geometric decisions condition both energy demand and thermal comfort response.

1.5. Aims and Objectives

To address the identified gap, this study aims to evaluate school mass configuration, when incorporated within an IAA, and mediate the combined influence of orientation and the WWR on energy and thermal comfort performance under the climatic conditions of Erbil city. The specific objectives are to:

• Compare energy use intensity (EUI) and thermal comfort performance across multiple school mass typologies at the early design stage.
• Identify typology-specific best- and worst-performing orientations for each mass configuration under a fixed baseline envelope condition.
• Quantify the sensitivity of energy demand and thermal comfort to changes in the window-to-wall ratio (20%, 40%, and 60%) under controlled orientation scenarios.
• Assess energy–comfort trade-offs resulting from combined variations in massing, orientation, and envelope transparency.

By systematically integrating these geometric parameters within an IAA-informed framework, the study seeks to provide performance-based insights that support informed early-stage decision-making in school building design.

2. Materials and Methods

2.1. Study Location and Climatic Context

The study is conducted for Erbil, Kurdistan Region, Iraq, which is characterized by a hot semi-arid climate (Koppen–Geiger classification: BSh) [30]. The region experiences prolonged high-temperature summers and is predominantly cooling-dominated. These climatic conditions make solar exposure, mass configuration and envelope-related design decisions particularly influential in determining the cooling demand and building overheating risk. Detailed weather data and simulation boundary conditions are described in Section 2.5.

2.2. Interactive Architectural Assessment Framework

The study employs a structured, performance-based assessment framework to evaluate the interaction between mass configuration, orientation and the WWR in shaping energy demand and thermal comfort at the conceptual design stage. Within the IAA framework, architectural performance is treated as the outcome of interactions among multiple design parameters rather than isolated optimization, where modification of one variable may alter the response of others [27]. In recent applications, the IAA has been used as a structured way to organize complex design variables into a coherent workflow that supports systematic comparison among cases [31]. Within this context, the study adopts a performance-based research-by-design approach, where architectural configurations are systematically explored through simulation to evaluate their impact on energy and thermal comfort outcomes; this enables structured evaluation of interaction-based performance at the early design stage.

In this study, the IAA is operationalized specifically for early-stage performance-based design by treating mass configuration, orientation and the WWR as interacting architectural parameters. The methodological novelty is the explicit positioning of massing configuration as an interactive parameter within an IAA-informed workflow, enabling its role as a conditioning variable that modulates sensitivity to orientation and envelope transparency to be explicitly quantified.

Following an IAA-consistent logic of staged exploration and testing, the study is organized into two sequential phases. Firstly, a baseline condition of WWR = 40% is used to identify typology-specific best- and worst-performing orientations for Erbil city’s climate; this staged approach reflects early-stage architectural sequencing, where orientation decisions typically precede detailed façade refinement and avoids exhaustive combinatorial complexity while preserving analytical clarity. The second phase employs a targeted sensitivity of varied WWR (20%, 40%, 60%) only for each case’s best and worst orientations, allowing the interactions between envelope openness and orientation to be evaluated through the lens of each massing configuration. The selected WWR range represents low-, moderate- and high-transparency conditions; 40% was adopted as a representative mid-range baseline, while 20% and 60% were introduced to capture lower- and upper-bound sensitivity responses. The two-phase structure supports the controlled identification of interaction and avoids interpreting WWR impacts without reference to typology- and orientation-specific behavior.

For ensured comparability and to isolate interaction effects, all simulations are conducted under consistent boundary conditions, including functional program assumptions, internal loads, occupancy schedules, HVAC system configurations and envelope thermal properties. Performance outcomes are reported using normalized indicators, such as annual energy use intensity (kWh/m²·yr), heating and cooling energy demand, alongside annual thermal comfort metrics. The operational structure of the IAA framework adopted in this study is illustrated in Figure 1, presenting the staged interaction logic that was adopted in this study.

2.3. Massing Archetype Selection and Geometric Characterization

Five school buildings were selected and abstracted into simplified geometric archetypes to capture a range of distinct massing typologies that are commonly observed in contemporary educational buildings design. The selected cases include a multi-block dispersed arrangement (International School of Choueifat—ISC), a moderately articulated H-shaped configuration (International School of Fakhir Mergasore—ISFM), an elongated linear bar with articulated wings (Kurdistan High School—KHS), a hybrid courtyard massing (Mamoun Al-Dabbagh High School—MDHS) and a pavilion-based clustered configuration (International Maarif Schools of Erbil—IMSE). Together, these typologies were chosen to capture a variant range of compactness degree, articulation and spatial aggregation, allowing for a systematic investigation of geometric effects on energy and thermal comfort performance. Case selection was based on geometric differentiation and was guided by the following criteria: representation of distinct school massing typologies, consistency in building function and use, diversity in geometric compactness, which is expressed through the S/V ratio, and suitability for early-stage simulation-based assessment. All selected buildings serve comparable educational programs and differ primarily in massing configuration, gross floor area, number of floors, and geometric compactness. Gross floor area ranges from approximately 2790 m² to 32,471 m², while S/V ratios vary between 0.87 and 1.35, capturing both compact and highly articulated forms.

This range of geometric characteristics enables the systematic investigation of how massing configuration and compactness influence energy demand and thermal comfort performance within an integrated early-stage assessment framework. An overview of the selected case studies is presented in

Table 1. Overview of selected school case studies and key dimensional parameters.

Typology ID	Morphological Description	(S/V) Ratio	Gross Floor Area (m2)	Number of Floors	Mass Configuration Diagram
Typology A (ISC)	Dispersed multi-block	0.88	32,470.98	2–3
Typology B (ISFM)	H-shape articulated	0.98	12,683.39	3
Typology C (KHS)	Linear articulated bar	1.35	2790.43	2
Typology D (MDHS)	Courtyard mass	1.12	3568.44	2–3
Typology E (IMSE)	Clustered pavilion	0.87	23,351.60	2

.

2.4. Simulation Workflow and Modeling Approach

2.4.1. Geometric Model Development

Simplified three-dimensional models of selected typologies were developed to represent the overall mass configuration of each typology. The modeling process retained primary volumetric characteristics, including footprint geometry, building height, number of floors and spatial aggregation patterns, while standardizing secondary facade elements across all cases to maintain comparability. This controlled abstraction ensures that performance differences primarily reflect mass configuration and geometric compactness rather than uncontrolled architectural variation. All models were generated using Rhinoceros 3D and subsequently translated into dynamic building energy simulation models using the Honeybee and Ladybug tools interfacing with the EnergyPlus simulation engine (U.S. Department of Energy, USA).

2.4.2. Orientation and WWR Parametric Strategy

To ensure consistent and comparative assessment, all models were simulated under identical baseline scenarios. A baseline WWR of 40% was applied uniformly to each typology to evaluate orientation-dependent performance behavior. Each typology was rotated in 90° increments (0°, 90°, 180° and 270°) to assess directional sensitivity under the climatic conditions of Erbil. Based on the resulting annual energy use intensity (EUI), typology-specific best- and worst-performing orientations were identified for consecutive analysis.

Following orientation screening, a targeted sensitivity analysis was conducted. For each typology, WWR values were varied to 20%, 40% and 60% under the previously identified best- and worst-performing orientations, while all other simulation parameters remained constant. The selected WWR range represents low, moderate and high envelope transparency conditions; previous assessment of school buildings in Erbil reported a WWR ranging between 14.9 and 46.6% [32]. Accordingly, 40% was adopted as a representative mid-range baseline condition, while 20% and 60% were introduced to examine lower- and upper-bound sensitivity responses within a controlled interaction framework.

The stepwise structure of the workflow enables the controlled identification of interaction effects by isolating orientation screening from envelope sensitivity analysis, thereby supporting the interpretation of typology-conditioned performance behavior. An overview of the simulation workflow is illustrated in Figure 2.

2.5. Boundary Conditions and Fixed Assumptions

To ensure comparability across all case studies and simulation scenarios, a consistent set of simulation settings was applied throughout the analysis (see Appendix A); all models were simulated using the same climatic data, construction assemblies, operational assumptions, and performance indicators. To clarify the simulation structure and ensure transparency, Figure 3 summarizes the fixed and variable parameters implemented within the modeling environment.

2.5.1. Climate Data and Weather File

All simulations were conducted using the same typical meteorological year (TMY) weather file corresponding to Erbil city, Kurdistan Region, Iraq. The standardized TMY dataset was used consistently across all cases to ensure that performance variations are attributable to mass configuration, orientation and the WWR rather than climatic fluctuations. Climatic conditions indicate a predominantly cooling-dominated context, providing relevant climatic background for interpreting the energy and overheating performance outcomes.

2.5.2. Building Construction and Envelope Properties

A consistent set of construction materials and envelope thermal properties was applied to all case studies. External walls, roofs, floors, and glazing assemblies were defined based on typical construction practices observed in school buildings in Erbil. Material definitions were implemented within the Honeybee interface in Grasshopper. Thermal transmittance (U-value) was computed through EnergyPlus based on the defined material layers, their thicknesses and thermal conductivities. The calculation procedure follows the steady-state thermal-resistant summation method consistent with ISO 6946 [33].

Table 2. Envelope construction material and corresponding U-values used in simulation.

Building Element	Construction Type	U-Value (W/m2·K)
External wall	Exterior mass wall	0.39
Internal wall	Masonry partition	0.52
Roof	Insulated built-up roof	0.35
Ground floor	Insulated ground-contact slab	0.5
Windows	Single glazing (SHGC = 0.31)	5.8

summarizes the construction assemblies and corresponding U-values adopted in the study.

2.5.3. Internal Loads and Occupancy

All case studies were assigned to the same functional program corresponding to a secondary school building, based on the DOE reference building definitions implemented in Honeybee/EnergyPlus. Classroom occupancy density was defined as 0.377 persons/m² (≈2.65 m² person), with weekday occupancy primarily between 08:00 and 16:00, reduced to zero occupancy during evenings, weekends and holidays. Lighting and equipment loads were applied according to the DOE secondary school definitions (e.g., corridor lighting power density = 4.41 W/m²), and identical schedules were used across all typologies. This standardized operational framework ensures that performance differences are attributable to geometric envelope variations rather than internal load assumptions.

2.5.4. HVAC System and Control Strategy

All simulations employed the EnergyPlus Ideal Loads Air System through Honeybee (Ladybug Tools 1.8.0) interfacing with EnergyPlus (version 23.2.0), representing a technology-neutral HVAC configuration; heating and cooling capacities were auto sized, with supply air temperature limits of 50 °C heating and 13 °C cooling, and outdoor ventilation defined according to the DOE 2019 Secondary school template. Thermostat setpoints were maintained at 20 °C for heating and 24 °C for cooling during occupied periods. The ideal loads representation was adopted to ensure a consistent and technology-neutral baseline across all typologies, allowing performance differences to be attributed to geometric values rather than mechanical system selection. Accordingly, reported energy values represent zone-level thermal demand under controlled assumptions rather than technology-specific HVAC energy consumption.

2.5.5. Simulation Period and Temporal Resolution

Annual simulations were conducted over a full calendar year for all scenarios. This temporal scope enables the assessment of both seasonal performance variations and aggregated annual performance, capturing winter heating demand, summer cooling demand, and intermediate seasonal conditions relevant to energy use and thermal comfort performance.

2.6. Performance Indicators and Thermal Comfort Assessment

Building performance was evaluated using a set of energy and thermal comfort indicators derived from annual dynamic simulations. The indicators were selected to capture not only absolute performance levels but also the sensitivity of energy demand and thermal comfort to variations in each of mass configuration, orientation and the WWR.

A comparative assessment at the early design stage was conducted, with all indicators derived from annual dynamic simulations and applied consistently across all case studies and parametric scenarios. The combination of aggregated energy metrics with complementary thermal comfort indicators enables the evaluation framework to identify interaction-driven trade-offs that are central to the integrated assessment approach adopted in this study.

2.6.1. Energy Performance Indicators

Energy performance was primarily assessed using annual energy use intensity (EUI), expressed in kWh/m²·yr, enabling comparison across buildings with differing sizes and geometries. Under the ideal loads system assumption, EUI represents the zone-level thermal energy demand required to maintain heating and cooling setpoints, rather than delivered energy consumption from specific HVAC technologies. To support the interpretation of seasonal performance, heating and cooling energy intensities were also extracted and reported separately. This distinction allows clearer interpretation of how massing configuration, orientation, and the WWR influence heating and cooling-dominated responses under the same climatic conditions.

2.6.2. Thermal Comfort Model and Baseline Definition

Thermal comfort performance was evaluated using an annual indicator derived from occupied hours. Overheating hours (%) were defined as the proportion of occupied time during which the zone operative temperature exceeded a fixed threshold of 26 °C. Total discomfort hours (%) was calculated as the percentage of occupied hours during which the zone operative temperature fell below the heating setpoint (20 °C) or exceeded the cooling setpoint (24 °C). Cooling degree hours above 26 °C (CDH26) were calculated to quantify the cumulative severity of temperature exceedance, accounting for both duration and magnitude. Operative temperature was used as a primary comfort variable, integrating both air temperature and mean radiant temperature (MRT). In addition to temperature-based indicators, relative humidity (RH%) was extracted to characterize indoor moisture conditions, recognizing its influence on perceived comfort in cooling-dominated climates. MRT and RH were evaluated as complementary parameters to provide a more comprehensive assessment of indoor thermal conditions under the adopted HVAC control assumptions.

2.6.3. Indicator Interpretation and Design Relevance

The selected indicators were chosen to support the interaction-based evaluation of early-stage design decisions rather than isolated performance optimization. Combining energy metrics with complementary thermal comfort indicators enables the identification of mass-conditioned performance sensitivity and trade-offs across different configuration scenarios. The indicators are interpreted comparatively, emphasizing relative geometric performance differences under consistent operational assumptions.

3. Results

3.1. Baseline Results (WWR 40%)

Baseline simulations were performed using a fixed WWR of 40% to assess the influence of orientation on both energy performance and thermal comfort across the selected school massing typologies. For each case study, annual heating demand, cooling demand, total energy use intensity (EUI), and aggregated thermal comfort indicators were evaluated for all orientations. The results are summarized in

Table 3. Annual heating demand, cooling demand, and total energy use intensity (EUI) for selected case studies under baseline WWR and orientation scenarios.

Scenarios	Heating Demand [kWh/m2]	Cooling Demand [kWh/m2]	Total Energy Intensity (kWh/m2·yr)
ISC
Base	79.297	204.215	283.512
N	79.279	204.168	283.447
E	79.571	206.064	285.635
W	79.586	206.089	285.675
S	79.302	204.124	283.425
ISFM
Base	53.957	143.452	197.409
N	53.265	142.41	195.675
E	53.733	143.73	197.464
W	53.707	143.832	197.539
S	53.794	141.983	195.777
KHS
Base	76.616	208.853	285.47
N	76.318	206.21	282.528
E	76.506	208.525	285.032
W	76.526	208.029	284.555
S	76.254	206.401	282.655
MDHS
Base	84.088	201.835	285.923
N	84.488	201.64	286.128
E	83.905	201.756	285.661
W	84.948	201.495	286.443
S	84.411	201.689	286.1
IMSE
Base	74.272	171.006	245.278
N	74.377	171.393	245.77
E	74.103	170.447	244.549
W	74.159	170.307	244.466
S	74.374	171.295	245.669

and illustrated in Figure 4. The results are presented comparatively across typologies to highlight interaction-based performance differences under consistent simulation conditions.

3.1.1. Energy Performance

Orientation-dependent variations in total annual EUI were observed across all school massing typologies under the baseline condition (WWR = 40%). However, in all cases, the magnitude of variation remained relatively limited, indicating that orientation influenced energy performance primarily through incremental adjustments rather than fundamental changes in overall demand. Table 3 summarizes the annual heating, cooling and total energy demand for all massing typologies, while Figure 4 presents the corresponding total EUI values of each case.

Across all typologies, cooling energy demand constituted the dominant component accounting for approximately 70–75% of total EUI and exhibited greater sensitivity to orientation than heating demand. In contrast, heating energy demand showed comparatively minor variation across orientations for all cases, with differences generally below 1.0 kWh/m²·yr.

For the multi-block dispersed typology (ISC), total EUI values ranged from 283.43 kWh/m²·yr (south-facing) to 285.68 kWh/m²·yr (west-facing), corresponding to an absolute variation of 2.25 kWh/m²·yr. Orientation-related differences were driven primarily by changes in cooling energy intensity, while heating demand remained nearly constant.

The articulated H-shaped typology (ISFM) exhibited total EUI values between 195.68 kWh/m²·yr (north-facing) and 197.54 kWh/m²·yr (west-facing), resulting in a variation of 1.86 kWh/m²·yr. Like ISC, cooling demand accounted for the most observed orientation sensitivity.

For the elongated linear typology (KHS), total EUI ranged from 282.53 kWh/m²·yr (north-facing) to 285.47 kWh/m²·yr (base orientation), representing the largest orientation-driven variation among all cases (2.94 kWh/m²·yr). Cooling energy intensity varied by more than 2.5 kWh/m²·yr, whereas heating energy differences remained below 0.4 kWh/m²·yr. This increased sensitivity can be attributed to the elongated geometry and the relatively high S/V ratio of the typology, which expose a larger portion of the façade to solar radiation. As a result, changes in orientation significantly alter solar gains and consequently produce more pronounced variations in cooling demand with more compact building forms.

The courtyard-based typology (MDHS) demonstrated very limited responsiveness to orientation, with total EUI confined to a narrow range of 285.66–286.44 kWh/m²·yr, corresponding to an absolute variation of 0.78 kWh/m²·yr. In this case, the east-facing orientation yielded the lowest total energy demand, while the west-facing orientation produced the highest. The courtyard configuration distributes façade exposure around the internal courtyard, which tends to moderate directional solar gains and reduce orientation sensitivity.

Similarly, the clustered pavilion typology (IMSE) showed low orientation sensitivity, with total EUI values ranging from 244.47 kWh/m²·yr (west-facing) to 245.77 kWh/m²·yr (north-facing), resulting in a variation of 1.30 kWh/m²·yr.

Overall, the reported results indicate that while orientation consistently influences total energy demand, its impact is secondary to mass configuration under fixed envelope conditions. Typologies with higher geometric articulation or larger façade areas exhibited greater orientation sensitivity, whereas compact or courtyard-based forms demonstrated more stable energy performance across orientations. Based on the baseline energy analysis, the best- and worst-performing orientations for each massing typology, defined by the minimum and maximum total EUI, were identified and retained for the subsequent WWR sensitivity analysis presented in Section 3.2.

3.1.2. Thermal Comfort Performance

Thermal comfort performance under baseline conditions was evaluated using the annual overheating percentage, cooling degree hours above 26 °C (CDH26), and total discomfort hours. The results for all cases and orientations are summarized in

Table 4. Summary of thermal comfort performance metrics for all case studies and orientations under baseline conditions (WWR = 40%).

Scenarios	Overheating Hours (>26 °C) [h]	Overheating (%)	CDH26 (°C·h)	Discomfort (%)
ISC
Base	1929	22.02%	4803.13	51.3%
N	1927	22.0%	4797.19	51.27%
E	1961	22.39%	4970.27	51.82%
W	1962	22.4%	4971.49	51.8%
S	1928	22.01%	4801.58	51.24%
ISFM
Base	1760	20.09%	3882.79	48.98%
N	1741	19.87%	3796.41	48.09%
E	1770	20.21%	3904.68	48.84%
W	1764	20.14%	3917.03	48.80%
S	1732	19.77%	3787.1	48.71%
KHS
Base	2174	24.82%	6989.02	55.08%
N	2131	24.33%	6674.05	54.69%
E	2170	24.77%	6957.18	55.01%
W	2186	24.95%	6964.78	55.24%
S	2131	24.33%	6579.18	54.65%
MDHS
Base	2307	26.34%	9290.35	59.50%
N	2295	26.20%	9196.82	59.68%
E	2298	26.23%	9303.64	59.34%
W	2261	25.81%	8967.44	59.43%
S	2277	25.99%	9140.22	59.28%
IMSE
Base	2123	24.24%	7314.76	56.77%
N	2117	24.17%	7314.49	56.80%
E	2117	24.17%	7284.3	56.68%
W	2110	24.09%	7249.05	56.75%
S	2123	24.24%	7308.52	56.85%

, while Figure 5 and Figure 6 illustrate the variation in overheating percentages and CDH26 across all studied massing typologies.

Across all case studies, orientation-related variations in thermal comfort indicators were generally smaller than those observed for energy performance, with absolute differences in overheating percentage generally below 0.7 percentage points within each massing typology. This indicates that orientation influences the intensity of thermal discomfort rather than substantially altering the overall frequency of overheating events.

For ISC, overheating percentages ranged from 22.01% (south) to 22.40% (west), corresponding to a variation of 0.39 percentage points, while CDH26 values varied between 4797 and 4971 °C·h. Similarly, ISFM exhibited the lowest overall heating among all cases, with overheating percentages between 19.77% (south) and 20.21% (east) and CDH26 values spanning between 3787 and 3917 °C·h.

KHS and MDHS showed substantially higher overheating severity, where KHS overheating percentages ranged from 24.33% (north/south) to 24.95% (west), while CDH26 values varied by more than 300 °C·h. (6579–6965 °C·h.), indicating increased sensitivity in overheating intensity. MDHS recorded the highest overheating severity overall, with CDH26 values ranging from 8967 to 9304 °C·h, while orientation-driven differences in overheating percentage remained within 0.53 percentage points.

In contrast, IMSE demonstrated highly stable thermal comfort performance across all orientations, with overheating percentages confined to a narrow range of 24.09–24.24% and CDH26 values varying by less than 70 °C·h., reflecting limited orientation sensitivity for this compact clustered configuration.

Complementary comfort indicators further support these observations. MRT values showed limited orientation sensitivity but varied slightly between typologies; compact configurations such as IMSE and ISFM recorded MRT values between approximately 23.1 and 23.5 °C, whereas the more articulated forms KHS and MDHS exhibited slightly higher values ranging between 23.3 and 24.1 °C, reflecting increased façade exposure and solar-driven radiant heat exchange. In contrast, RH remained largely stable across all cases and orientations, ranging between approximately 38.5% and 41.5%, with variation within each typology generally below 1% point, indicating limited sensitivity to orientation under the applied conditions.

Overall, the baseline thermal comfort results indicate that mass configuration governs the magnitude of overheating and discomfort, while orientation exerts a secondary but consistent influence, primarily affecting overheating intensity rather than the overall occurrence.

Figure 5 and Figure 6 present the variation in overheating, discomfort, and CDH26 across orientation scenarios for all typologies under the baseline WWR condition (40%). Orientation produced relatively small changes in overheating and discomfort percentages, generally below one percentage point within each case. However, differences between typologies were more evident, with the articulated KHS and courtyard-based MDHS configurations exhibiting higher overheating levels, while ISFM showed the lowest values. The CDH26 comparison further highlights orientation sensitivity relative to the baseline scenario, indicating that certain orientations increase or reduce the severity of overheating, particularly in the more articulated mass configurations.

3.2. Window-to-Wall Ratio Sensitivity Analysis

Following the baseline orientation assessment, a WWR sensitivity analysis was conducted for each case study using the previously identified best- and worst-performing orientations. WWR values of 20%, 40%, and 60% were evaluated to examine the combined effects of glazing proportion and orientation on energy demand and thermal comfort performance. The resulting heating and cooling energy intensities, as well as total EUI for each typology under both the best- and worst-performing orientations, are summarized in Figure 7.

3.2.1. Energy Performance Sensitivity

Figure 7 illustrates the variation in heating demand, cooling demand, and total energy use intensity (EUI) across the evaluated WWR scenarios (20%, 40%, and 60%) for both the best- and worst-performing orientations of each typology. Across all cases, increasing the WWR consistently resulted in a higher cooling energy demand, while heating demand exhibited only minor reductions. Consequently, total EUI increased progressively as the glazing proportion increased.

For ISC and ISFM, total EUI increased progressively as the WWR was raised from 20% to 60%, with absolute increases of approximately 10–15 kWh/m²·yr, depending on orientation. In both cases, the increase in cooling demand clearly outweighed the modest reduction in heating demand, leading to a net rise in total energy use. The effect was more pronounced under the worst-performing orientation, indicating an interaction between glazing proportion and orientation.

KHS and MDHS exhibited the strongest sensitivity to WWR changes compared to the other cases. In these more articulated configurations, increasing the WWR from 20% to 60% resulted in total EUI increases exceeding 20 kWh/m²·yr, particularly under the worst-performing orientations. Cooling demand accounted for most of this increase, highlighting the amplified impact of glazing proportion in cooling-dominated energy demand in less compact mass configurations.

In contrast, IMSE demonstrated a more moderate response to WWR variations. Total EUI increases associated with raising the WWR from 20% to 60% ranged from approximately 9.4 to 10.3 kWh/m²·yr, reflecting a buffering effect associated with its compact clustered configuration.

Overall, the WWR sensitivity analysis indicates that increasing envelope transparency consistently increases total energy demand, with the magnitude of impact strongly mediated by massing configuration and orientation. Articulated and courtyard-based typologies (KHS and MDHS) exhibit substantially higher sensitivity to WWR changes, whereas more compact configurations (ISFM and IMSE) demonstrate greater robustness under varying WWR ratios.

3.2.2. Thermal Comfort Sensitivity

Thermal comfort indicators exhibited a clear and consistent sensitivity to changes in the WWR across all case studies. For both the best- and worst-performing orientations, increasing the WWR from 20% to 60% resulted in higher overheating percentages and total discomfort, confirming that increased envelope transparency exacerbates thermal discomfort under the studied climatic conditions.

For ISFM, increasing the WWR led to overheating increases of 2.43 percentage points for the best-performing orientation (18.89% to 21.32%) and 2.33 percentage points for the worst-performing orientation (19.06% to 21.39%). The corresponding discomfort percentages increased by 1.04 and 1.06 percentage points respectively, indicating a moderate but consistent degradation in thermal comfort with higher glazing ratios.

ISC exhibited similar trends, with overheating percentages increasing by 2.93 percentage points for the best orientation (20.74% to 23.40) and 2.99 percentage points for the worst orientation (20.74% to 23.73%) as the WWR increased from 20% to 60%, while the discomfort percentages increased by approximately 1.11–1.04 percentage points over the same range.

On the other hand, KHS and MDHS showed the strongest sensitivity to WWR variation in terms of thermal comfort. In the case of KHS, the overheating percentages increased by 4.54 percentage points under the best-performing orientation (21.96% to 26.50%) and 4.77 percentage points under the worst-performing (22.36% to 27.13%), while the corresponding discomfort increases ranged from 1.75 to 2.31 percentage points.

Similarly, MDHS exhibited substantial overheating increases of 3.79 percentage points under the best orientation (24.54% to 28.33%) and 3.29 percentage points under the worst (24.11% to 27.40%), with discomfort percentages increasing by 1.69 and 1.37 percentage points respectively.

In contrast, IMSE demonstrated comparatively lower sensitivity to changes in the WWR, where increasing the values from 20% to 60% resulted in overheating increases of 2.10 percentage points for both the best and worst orientations (23.09% to 25.15% and 22.99% to 25.09%). The discomfort percentages increased by 0.69 percentage points, indicating a more buffered response associated with the compact clustered configuration.

Figure 8 illustrates the combined variation in overheating and total discomfort percentages across WWR levels (20%, 40%, and 60%) for each massing typology under the identified best- and worst-performing orientations. Across all cases, increasing the WWR systematically elevates both overheating and total discomfort, with articulated configurations (KHS and MDHS) exhibiting the strongest sensitivity, while compact typologies (ISFM and IMSE) demonstrate comparatively moderated responses.

In addition to overheating and discomfort, MRT increased consistently with a higher WWR across all typologies, with the largest rise observed in KHS and MDHS, where MRT increased by approximately 0.8–0.9 °C between 20% and 60% WWR. Compact configurations (IMSE and ISFM) showed smaller increases, generally below 0.5 °C. In contrast, indoor relative humidity exhibited only minor reductions as the WWR increased, with variations typically remaining below 0.7 percentage points across all cases and orientations. This indicates that glazing-driven comfort deterioration is primarily associated with elevated radiant temperature rather than significant changes in indoor humidity levels. Figure 9 presents the variation in annual MRT and RH% across WWR levels under the identified best- and worst-performing orientations.

3.2.3. Summary of WWR Effects

Overall, the WWR sensitivity analysis demonstrates that increasing the envelope transparency systematically increases both energy demand and thermal discomfort across all case studies. While lower WWR values generally improve energy and comfort performance, the magnitude of this effect varies depending on mass configuration and orientation. The results confirm that the WWR is a critical early-stage design parameter, increasing cooling-dominant demand and temperature-based discomfort; it is also associated with a higher MRT, while showing a comparatively limited impact on indoor RH. Its interaction with massing layout and orientation should therefore be carefully evaluated in an integrated manner. The combined energy and comfort implications of WWR variation are further examined through a comparative trade-off analysis in Section 3.3.

3.3. Energy and Thermal Comfort Trade-Offs

The combined evaluation of energy performance and thermal comfort across orientations and WWR scenarios revealed differentiated responses rather than uniform improvement across performance domains. While several configurations achieved a lower total EUI, corresponding improvements in thermal comfort metrics were not always proportional. Across all case studies, lower WWR values consistently resulted in a reduced total EUI, primarily driven by reductions in cooling energy demand. Thermal comfort indicators generally improved under lower WWR conditions; however, the magnitude of improvement in overheating and total discomfort hours was often smaller than the corresponding reduction in energy demand. This indicates that gains in energy efficiency do not scale linearly with improvements in indoor comfort conditions.

Conversely, increasing WWR values led to systematic increases in cooling demand, total EUI, overheating percentage, CHD26, and total discomfort hours across all cases. These changes were accompanied by consistent rises in MRT, indicating increased radiant heat exposure under higher glazing ratios, while RH remained comparatively stable. The strongest trade-offs were observed in the more articulated configurations, where increased glazing intensified solar-driven gains under less favorable orientations. It was noted that orientation further moderates the relationship between energy and comfort performance. In several cases, the orientation associated with the lowest total EUI did not consistently correspond to the lowest overheating or discomfort levels, indicating that energy-optimal orientations do not necessarily yield optimal thermal comfort outcomes.

Overall, these results demonstrate that improvements in energy performance and thermal comfort do not occur simultaneously across all scenarios. This highlights the importance of evaluating both energy demand and multiple comfort indicators concurrently during early-stage design, rather than relying on single-metric optimization strategies.

Figure 10 maps out the total EUI against overheating percentages for all typologies under the best and worst orientations across WWR levels. Increasing the WWR consistently shifts performance toward higher energy demand and overheating; however, typologies (KHS and MDHS) exhibit substantially greater sensitivity than compact forms (ISFM and IMSE). It also demonstrates how the lowest EUI scenarios do not always correspond to the lowest overheating levels, confirming a typology-dependent performance decoupling.

4. Discussion

This study investigated how building mass configuration interacts with orientation and the WWR to influence energy demand and thermal comfort during the early design stage of school buildings. Rather than evaluating these parameters in isolation, the analysis adopted an IAA perspective, allowing their combined and interactive effects to be examined systematically. The results demonstrate that early-stage performance is not governed by individual geometric variables alone, but by how these variables interact within specific mass configurations.

4.1. Massing Typology as a Mediator of Energy and Comfort Performance

The results indicate that mass configuration plays a primary role in shaping both absolute performance levels and performance sensitivity. Compact and clustered typologies (e.g., IMSE and ISFM) consistently exhibited a lower overall EUI and more stable thermal comfort indicators across all tested orientations and WWR scenarios. Their reduced sensitivity to geometric variation can be attributed to lower S/V ratios, which limit façade exposure and moderate solar heat gains.

In contrast, more articulated, elongated, and courtyard-based typologies (e.g., KHS and MDHS) demonstrated higher overall cooling demand and elevated overheating levels and larger increases in MRT as the WWR increased. These configurations expose a larger façade area to solar radiation, amplifying both sensible and radiant heat exchange. While indoor RH remained comparatively stable across scenarios, the rise in MRT confirms that discomfort sensitivity in these forms is primarily driven by radiant temperature effects rather than moisture variations. Importantly, these findings indicate that mass typology does not merely influence performance magnitude but also governs how strongly buildings respond to changes in other early-stage design parameters.

4.2. Orientation Effects Conditioned by Massing Configuration

Orientation sensitivity was found to vary substantially across massing configurations. Elongated and articulated forms exhibited clearer differentiation between the best- and worst-performing orientations, particularly in cooling demand, overheating severity and MRT values. In these cases, orientations with reduced solar exposure generally resulted in a lower total EUI and marginally improved thermal comfort outcomes.

On the other hand, compact configurations displayed limited orientation-driven variation in both energy and comfort metrics. For these configurations, performance indicators remained relatively stable across all orientations, suggesting that geometric compactness mitigates the influence of solar exposure. These findings confirm that orientation impacts cannot be evaluated independently from mass configuration. From an early-stage design perspective, orientation optimization is more critical for articulated forms, while its relative impact diminishes as geometric compactness increases.

4.3. Window-to-Wall Ratio Effects and Performance Divergence

The WWR sensitivity analysis revealed consistent but differentiated responses in energy and thermal comfort performance in all cases. Increasing the WWR led to systematic increases in cooling demand and total EUI, overheating percentage and MRT across all cases, while RH exhibited only minor variation, confirming that glazing-driven comfort deterioration under the studied climate is primarily associated with elevated radiant and operative temperature conditions.

However, reductions in the WWR did not consistently yield proportional improvements in overheating and discomfort metrics. This reveals a partial decoupling between energy efficiency and thermal comfort performance at the early design stage. While lower WWR values are effective for reducing cooling-dominated energy demand, their benefits for thermal comfort are more moderate and strongly conditioned by massing configuration and orientation. These results highlight the limitations of single-metric optimization strategies and underscore the need to evaluate envelope transparency using multiple performance indicators.

4.4. Implications for Integrated Architectural Assessment and Previous Research

The general influence of compactness, orientation and glazing proportion on the building performance has been widely reported in previous studies. However, the contribution of this work lies in the structured operationalization of the IAA concept as a staged, interaction-focused assessment method. Rather than evaluating geometric parameters independently or through exhaustive combinations, the framework treats mass configuration as a conditioning variable that shapes the sensitivity of orientation and the WWR.

The results demonstrate that typology not only affects absolute performance levels but also governs responsiveness to design variation. Articulated forms showed amplified sensitivity in cooling demand, overheating and MRT, while compact configurations in comparison exhibited stable behavior. Moreover, reductions in energy demand did not consistently correspond to proportional improvements in thermal comfort, indicating divergence between energy- and comfort-optimal scenarios depending on mass configuration. By quantifying typology-specific sensitivity within a controlled workflow, the study extends beyond confirming known trends and provides structure insight into how early geometric decisions condition performance responsiveness during the conceptual design stage.

4.5. Study Limitations and Future Research Directions

This study adopts an Ideal Loads Air System to isolate geometry-driven thermal demand. While this ensures consistent comparison across typologies, it does not reflect the operational behavior or efficiency of real HVAC systems; therefore, reported energy values represent relative demand rather than actual consumption.

Envelope properties, including glazing SHGC and insulation levels, were intentionally fixed to focus on geometric effects. Alternative envelope specifications may reduce solar gains and moderate orientation and WWR sensitivity. Future research should examine how envelope performance interacts with mass configuration to better reflect practical design scenarios.

Finally, the analysis is limited to a single climatic context and annual indicators. Extending the framework to additional climatic zones, seasonal assessments, and more detailed operational models would strengthen the applicability of the findings to real-world school design.

5. Conclusions

This study applied an IAA approach to examine how building mass configuration, orientation and the WWR interact to influence energy demand and thermal comfort during the early design stage of school buildings. Using a controlled simulation framework, the results demonstrate that mass configuration functions as a conditioning variable, influencing not only absolute energy and thermal comfort but also the magnitude of responsiveness to orientation and glazing variation.

Compact configurations exhibited comparatively stable performance across scenarios, whereas articulated and courtyard-based forms showed amplified sensitivity in cooling demand and overheating. While increasing the WWR systematically elevated cooling demand and overheating, reductions in energy use did not consistently correspond to proportional improvements in thermal comfort, indicating typology-dependent divergence between energy-efficient and comfort-optimal configurations.

The principal contribution of this study lies in structuring these geometric variables within an interaction-based IAA workflow and quantifying typology-specific performance sensitivity. By demonstrating that mass configuration conditions both performance magnitude and alignment between energy and comfort outcomes, the study provides geometry-aware guidance for early-stage design beyond isolated parameter optimization. It should be noted that the reported energy values represent relative thermal demand under ideal loads assumptions rather than actual operational energy consumption and should therefore be interpreted comparatively across design scenarios.