Thermal Performance Analysis of Building Envelope Components in a Multi-Story Building Using Numerical Simulation

The use of thermal insulation materials throughout prehistoric times and before the Industrial Revolution demonstrates humanity's constant quest to adapt to its surroundings, particularly extreme temperatures. Early humans used natural materials such as straw, clay, and wool to protect their shelters from heat and cold. With urban development, energy consumption in the building sector has increased significantly, accounting for about one-third of global energy use, while HVAC systems represent a major portion of this demand [1-5]. Advanced numerical tools such as ANSYS Fluent based on Computational Fluid Dynamics (CFD) are widely applied to analyze heat transfer mechanisms, including conduction, convection, and radiation, while considering environmental effects such as solar radiation and wind conditions [6-9]. Thermal simulation of multi-story buildings helps evaluate temperature distribution, airflow behavior, and floor-by-floor heat loads. Accurate envelope properties, especially the U-value, are essential for reliable energy prediction and improving building efficiency. These approaches support the design of sustainable, smart, and energy-efficient buildings [9-16].

This paper aims to use ANSYS Fluent software to create an accurate numerical model for estimating heat loads in multi-story buildings. To improve the efficiency of heating and cooling systems, the project studies heat distribution and airflow on each floor. Furthermore, the project seeks to provide precise data to help design smart, energy-efficient structures while ensuring thermal comfort for building occupants. The results will focus on identifying heat loads and optimizing heat distribution to support the design of highly efficient air conditioning systems, with the goal of reducing overall energy consumption.

5.1 Results of the first model

In Figure 5, the first model, the third wall layer was a 20 cm thick solid block with a thermal conductivity of approximately 1.4 W/m·K. The temperature on its inner surface, after the outer surface was exposed to 35 ℃, was approximately 29 ℃. The temperature differences between the layers were minimal due to poor insulation, with the temperature distribution recorded as approximately 35, 32, 30, and 29 ℃ across the four layers.

In the second model, the third layer was replaced with Thermo stone, which has a low thermal conductivity (0.35 W/m·K). Under the same conditions, the outer surface remained at 35 ℃, but the temperature after the third layer dropped significantly to 24 ℃. The temperature distribution recorded was 35, 31, 27, and 24 ℃, demonstrating an improvement in insulation of approximately 25% compared to the first model. The third model, using lightweight silicate brick with a thermal conductivity coefficient of 0.22 W/m·K, exhibited the highest thermal performance, with the internal temperature dropping to only 21 ℃. The results demonstrate that the third design achieved a heat transfer rate exceeding 35% compared to the other designs. The use of materials with relatively low thermal conductivity and lightweight properties contributed to improved thermal insulation and reduced heat transfer. The thermal distribution diagrams show that the average temperature ranged between approximately 28 and 30 ℃, indicating that the thermal insulation properties reduce and improve temperature regulation within the wall, leading to improved overall building thermal performance. This is one of the most important benefits of using materials with good thermal insulation to maintain thermal balance within a building. The average temperature is approximately 27 ℃, which is slightly lower than the average due to higher peak values near the outer surface. The mode represents the most frequent temperature within the range (25–27 ℃), indicating moderate heat diffusion within the wall.

The temperature range reaches approximately 15 ℃ between the highest value at the outer surface and the lowest value at the inner layers, confirming the poor resistance to heat transfer. The standard deviation is relatively high (≈5 ℃), reflecting significant dispersion in the temperature values. The skewness coefficient is positive, indicating a tendency for the data towards higher values due to heat leakage from the outside. Finally, the correlation coefficient shows a strong positive relationship between a high material conductivity and increased heat diffusion within the wall.

38-5.png

Figure 5. Numerical results of temperature distribution in all wall systems

38-6.png

Figure 6. The heat flux results at all walls

In Table 3 and Figure 6, the following is shown: In the first model, which uses solid blocks in the third layer, the maximum heat flux reached 113.92 W/m² and the minimum value was 9.0564 W/m², indicating high heat transfer through the wall due to poor insulation and the high thermal conductivity of the solid blocks. The heat flux distribution was slightly gradual due to the lower resistance to heat transfer.

In the second model, after replacing the third layer with Thermostone, the maximum heat flux decreased to 11.751 W/m² and the minimum value reached 0.9851 W/m², demonstrating a significant improvement in resistance to heat transfer and a reduction in total heat-transfer rate of over 85% compared to the first model. The third model, which used lightweight silicate brick in the third layer, recorded a maximum heat flux of 14.567 W/m² and a minimum of 1.2242 W/m². The results showed that Thermostone exhibited the best thermal insulation properties among the studied models, thanks to its low thermal conductivity and minimal heat flow. Lightweight silicate blocks ranked second, demonstrating good results, while conventional solid blocks showed the weakest performance.

Statistical analysis confirmed that the first model exhibited the greatest thermal fluctuations and poor durability, while Thermostone demonstrated the least variability and high stability in its thermal characteristics. Furthermore, the low conductivity of the material resulted in reduced heat transfer and increased thermal insulation efficiency.

5.2 Results of the second model

The results obtained from Figure 7, show the heat distribution through the three wall types. The first type exhibited distinct cooling zones, suggesting that its large size is the primary reason for its poor thermal conductivity. The second type showed average performance due to its unique porous properties, which enhance insulation and thus increase thermal insulation. The third type exhibited the most uniform heat distribution, indicating an ideal balance between thermal insulation and heat transfer. All three designs reach a similar maximum temperature of approximately 322.3 ℃, assuming they are subjected to the same thermal stress. The differences in color distribution are attributed to the varying thermal properties of each material. It was observed that the second model, after the first, exhibits very uniform heat transfer, while the first model shows outstanding supportive internal thermal memory, and the second model falls between the two models together.

38-7.png

Figure 7. Numerical temperature distribution results across all wall configurations

Figure 8 shows a comparison of the total heat that radiates of three obstruction samples under loyal warm sampling environments: a compact block, a Thermostone block, and a thin silicate block. The divergent heat transfer patterns indicate dissimilarities in their heat generation rate and insulation adeptness. The compact block exhibits the best peak heat that radiates at 114.74 W/m², displaying better heat permeability and lower padding adeptness on account of its extreme mass and good heat generation rate. The color lines current toward yellow and a combination of red and yellow, displaying meaningful heat dissipation through the obstruction. The Thermostone block registers a much lower peak heat that radiates of 11.708 W/m², emphasize allure superior padding. The rotating green and sad colors display that heat transfer is restricted apiece block's teased construction, which holds air bubbles that decrease the thermal generated power. The thin silicate block exhibits a peak heat that radiates of 14.502 W/m² above Thermostone but much inferior to the compact bulk, including an equalized thermal accomplishment accompanying good covering and even warm disposal. The color disposal displays smooth heat transfer from the outside related to adequate adeptness in lowering heat deficit. The color slope allocation discloses that the heat way in dependable blocks is direct and rapid, while in Thermostone it is slow and opposing, and in Silicate Block it exhibits moderate and equalized transfer. In addition, Figure 8 indicates that warm permittivity is obviously decreased in lightweight fabrics on account of lower bulk and generated power.

38-8.png

Figure 8. Wall heat flux results

5.3 Results of the third model

Figure 9 shows the heat allocation through a three-hide obstruction: an outer 3 mm dense mirror plate, understood by a 14 mm dense compressed air sheath. “The glazing cavity was represented as a sealed air gap of 14 mm thickness, assuming no pressurization; hence, the term compressed air layer is not applicable in this model”, and before a central 3 mm dense glass plate. Itemized heat dispersion through the divider: The external face of the glass (3 mm slice) shows the capital hotness in Figure 9, about 322 K, signifying exposure to an abundant heat beginning (cosmic, change of possession, radiation). Inside the jar itself, the hotness drops kind of to about 316–319 K due to the heat generation rate. As the condensed air coating begins (14 mm dense), the hotness remarkably decreases to about 311–313 K. his reduction is greater than that observed in the bottle because air has a low thermal conductivity. Inside this tier, a pale azure-green slope indicates a continuous hotness decline from 311 K to nearly 305–308 K. This domain shows the most solid warm drop, indicating air's insulating possessions that slow heat transfer. Forthcoming the end of the air coating and near trade the central glass, the hotness drops to nearly 300–302 K, signifying that a meaningful portion of the warmth has self-indulgent through the middle tier. As the central cup pane (4 mm) starts to move, the slope shifts repeated to a dark sky hue, and the heat persists to belittle through the jug, arriving the lowest profit written in Figure 9, at 297 K on the central side. The hotness decrease inside the inner mirror is less distinct distinguished to the air tier, consistent accompanying mirror being a greater leader than air but lower than metals. The total difference between the highest level of performance or physical object (322 K) and the hostile point (297 K) is approximately 25 K, indicating the effectiveness of the jug-air-jar composite wall in restricting heat transfer, specifically on account of the compacted air layer.

38-9.png

Figure 9. Numerical temperature field results of all wall models

Figure 10 decorates the total heat flow allocation across an obstruction composed of the following three coatings: a 4 mm dense external glass covering, followed by a 16 mm dense shortened air layer, and therefore a 4 mm dense central jug shell. Figure 9 shows that the maximum heat flow, nearly 1283.3 W/m², is reduced on the exposed jug surface. This indicates an extreme level of joint outside heat exchange. As the heat transfer happens inside the outer jug, the alteration evenly decreases to between 1141 and 1000 W/m², reflecting the restricted heat generation rate of the mirror. Upon reaching the concentrated air tier, an important and evident drop in flux happens, accompanying principles dropping to betwixt 859 and 434 W/m². This region performs ignorant, vulgar, and green, professing that the air acts as an effective insulator, considerably restricting heat transfer distinguished to the jar. It is also apparent that the preeminent supporter decrease influx is reduced precisely in this place coating on account of the very depressed thermal generated power of the air. Towards completely of the air coating, the flow drops to even lower levels, arriving at an inferior 300 W/m², reflecting a solid deficit of heat strength before arriving at the inner jar. Inside the central jar, the decrease continues, although less distinct, as far as the heat flow reaches allure lowest advantage noticed in the drawing: 10.8 W/m² clever. This suggests that most of the heat has been thwarted and prevented from escaping inwards. The diagram clearly shows that the distribution of heat flow through the wall is not linear. It decreases sharply within the air layer due to its high insulation, while the transitions are much smoother within the glass layer. This distribution confirms that the composite wall (glass-air-glass) is highly efficient in reducing heat transfer, with the compressed air layer playing the most significant role in reducing the intensity of heat flux entering the building.

38-10.png

Figure 10. Results of heat flux for all walls

5.4 Results of the fourth model

Figure 11 illustrates that, both in a steady state and under a thermal load, the convective surface's maximum temperature reached 322.3 K, then progressively dropped to 297 K at the opposite end, resulting in a 25.3 K temperature differential throughout the 448 mm roof thickness. Starting at about 322.3 K, the first layer (50 mm reflective ceramic tiles) is the most convective. The heat resistance of the 40 mm cement mortar in the second layer causes the temperature to drop to roughly 319.5 K. At the waterproofing layer (8 mm SBS), the temperature drops to about 316.7 K. Because the thermal insulation layer (80 mm XPS) has a lower thermal conductivity, a more noticeable reduction in temperature is seen there, where it falls to about 311–308 K. The temperature then rises to about 305 K in the 50 mm sloping cement layer. Because of the increased thickness and heat conduction through the reinforced concrete slab (200 mm), it progressively drops to about 300 K. Lastly, the temperature at the inner surface of the internal plaster layer (20 mm) drops to a minimum of about 297 K.

38-11.png

Figure 11. Numerical simulation results of temperature distribution across the roof structure using ANSYS

38-22.png

Figure 12. Comprehensive thermal analysis of heat flux in all wall models

In addition to confirming that the thermal insulation layer (XPS) experiences the largest temperature drop, this even and gradual distribution shows that heat transfer through the layers is nearly one-dimensional and that it is effective in minimizing heat transfer and preserving temperature stability in the interior space following thermal loading.

From Figure 12, a peak of 9.2565 W/m² was observed in the total heat flux values at the outermost surface that was immediately exposed to the convection after the convection was applied to the building's roof and the temperature had stabilized. This flux steadily dropped across the layers, settling at the deepest surface with a minimum of 5.53 × 10⁻⁶ W/m². This suggests that the 448 mm roof thickness has a consistent gradient in heat transfer. The heat flow in the external tiers, consisting of 50 mm porcelain slabs and 40 mm cement thick, remained approximately extreme, related to direct trade with the heat source. A step-by-step decrease in flow was noticed as it went through the 8 mm thick airtight tier. Ultimate significant decline happened in the 80 mm dense XPS waterproofing covering, place the force of the flow decreased remarkably on account of the material's lower heat generation rate. The reduction then proceeds through the reinforced concrete slab (200 mm) and the cement screed layer (50 mm) before reaching its lowest value at the inside plaster layer (20 mm). These findings show that the XPS thermal insulation layer is the most important factor in lowering heat flux and preserving stable thermal conditions inside the building, and that the roof is very effective at limiting heat transfer to the interior once it reaches a stable state.

Table 5 uses consistent terminology where heat flux is given as heat-flux density (W/m²), total heat transfer is reported in kW, and thermal resistance in m²·K/W. At 113.92 W/m² and a total flux of 41.097 kW, the Halan Stone had the highest flux density in Model-1. In Model-2, the concrete block recorded 114.74 W/m² and a greater total flux of 151.686 kW because of its enormous area (1322.02 m²).

With a total flux of 462.95 kW and the maximum heat flux density of 1283.3 W/m², Model-3 demonstrated exceptionally strong heat transfer through the glass. The Model-4 building's roof, on the other hand, had the lowest heat flux density of 9.2565 W/m² and a total flux of 7.788 kW while having an area of 841.39 m², indicating the effectiveness of the roof insulation system.

Table 5. The heat flux results for all walls

The statistical indicators (Mean, Standard Deviation, Mode, Skewness, And Correlation Coefficient) were calculated based on the nodal results extracted from ANSYS. A total of 65408 nodal points and 8911 elements were used for each model. The variables considered were temperature and heat flux distributions across the wall domain.

The average temperature of lightweight silicate bricks was ≈30 ℃ with a standard deviation of ≈5 ℃, and they achieved a reduction in internal temperature of more than 35%. The correlation coefficient between conductivity and temperature rise was R ≈ 0.85.