Influence of Building Envelope Modeling Parameters on Energy Simulation Results

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. The article only examines a single variable, yet actual building energy consumption is influenced by the interaction of multiple parameters. Simplified analysis may lead to underestimating or overestimating the true impact of certain parameters, particularly in complex building systems. It is recommended to supplement with sensitivity analysis among multiple parameters.
2. The baseline model lacks a validation process and verification using experimental or measured data. It is suggested to incorporate a validation step.
3. The overall logical consistency is insufficient. The introduction and methodology sections only discuss the building envelope (exterior walls, windows, etc.) but fail to explain why thermal capacitance is introduced. It is recommended to add theoretical groundwork in the preceding text as a foundation.
4. The charts and graphs are incomplete, and key conclusions are not effectively communicated through visualization, reducing readability. It is recommended to use more intuitive visuals to illustrate how each parameter impacts building energy consumption.
5. The charts and graphs are incomplete, and key conclusions are not effectively communicated through visualization, reducing readability. It is recommended to use more intuitive visuals to illustrate how each parameter impacts building energy consumption.

Comments on the Quality of English Language

Comments on English Language Quality The manuscript showcases a commendable command of academic English, demonstrating both technical proficiency and a solid grasp of linguistic conventions. The use of domain-specific terminology, such as "building envelope," and "sensitivity analysis," is accurate and consistent, reflecting a deep understanding of the field. Sentence structures are generally sound, with clear subject-verb agreements and appropriate verb tenses maintained throughout.

Author Response

1. Comment 1: The article only examines a single variable, yet actual building energy consumption is influenced by the interaction of multiple parameters. Simplified analysis may lead to underestimating or overestimating the true impact of certain parameters, particularly in complex building systems. It is recommended to supplement with sensitivity analysis among multiple parameters.
1. Response 1: We fully agree that the interaction of multiple parameters can significantly influence building energy consumption, especially in complex systems. In this study, we deliberately focused on analyzing individual parameters to thoroughly examine their specific impacts on simulation results, which was the primary objective of the research. This approach allowed us to isolate and quantify the effects of parameters such as glazing g-value, envelope U-value, and interior thermal capacitance. We recognize the importance of analyzing the interactions of multiple parameters, and we plan to conduct comprehensive sensitivity analyses incorporating combinations of parameters in future research to further enhance the understanding of their interdependencies.
2. Comment 2: The baseline model lacks a validation process and verification using experimental or measured data. It is suggested to incorporate a validation step.
1. Response 2: We completely understand the importance of validating models using experimental or measured data to ensure the reliability of results. In this study, we intentionally used theoretical building models to focus on the relative impact of input parameter variations under controlled conditions, which enabled a detailed analysis without additional variables associated with real-world data. Model validation based on experimental data is undoubtedly a critical step, and we plan to include such validation using actual energy consumption data in future studies to further substantiate our findings.
3. Comment 3: The overall logical consistency is insufficient. The introduction and methodology sections only discuss the building envelope (exterior walls, windows, etc.) but fail to explain why thermal capacitance is introduced. It is recommended to add theoretical groundwork in the preceding text as a foundation.
1. Response 3: We carefully reviewed the Results and Discussion section and ensured that all claims and conclusions are supported by the simulation results. The correlations and insights are now explicitly tied to data shown in Tables 9–20 and Figures 4–7.
4. Comment 4: The charts and graphs are incomplete, and key conclusions are not effectively communicated through visualization, reducing readability. It is recommended to use more intuitive visuals to illustrate how each parameter impacts building energy consumption.
1. Response 4: We tried to ensure that all simulation IDs are referenced explicitly. While not all parameters are visualized due to space limitations, we have ensured that the most influential and discussed parameters (e.g., g-value, window-to-floor ratio, BSF) are graphically represented.
5. Comment 5: The charts and graphs are incomplete, and key conclusions are not effectively communicated through visualization, reducing readability. It is recommended to use more intuitive visuals to illustrate how each parameter impacts building energy consumption.
1. Response 5: The whole paper has been significantly modified to increase readability and logical consistency.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

General comment

The manuscript addresses a relevant topic in the field of building energy simulation, focusing on how variations in envelope modelling parameters affect simulation results. However, despite the potential value of this research, the current version of the paper lacks clarity in structure, suffers from significant methodological ambiguities, and omits key literature and theoretical framing. A major revision is strongly recommended.

 

Specific comments

1. The title should clarify that the analysis is focused on new buildings. This is a crucial distinction in energy modelling and should also be clearly stressed throughout the text.
2. The abstract is overly focused on findings and lacks essential elements such as the research gap, the significance of the study, and its broader implications. A complete rewrite is advised.
3. The section “0. How to use this template” (lines 34–40) has not been removed. This should be corrected.
4. Introduction:
   1. The narrative lacks coherence. The logic connecting general context and the specific objectives of this study should be reinforced.
   2. Transitions are sharp, particularly between lines 123–124 and 139–140.
   3. Several norms (e.g., EPBD, EN standards) are mentioned but not cited properly in the references (this applies also in other sections of the manuscript).
   4. The long paragraph from lines 57–72 is unreferenced and should be split and supported by literature. For black-box and grey-box I suggest “Y. Li, Z. O’Neill, L. Zhang, J. Chen, P. Im, J. DeGraw, Grey-box modeling and application for building energy simulations - A critical review, Renewable and Sustainable Energy Reviews 146 (2021). https://doi.org/10.1016/j.rser.2021.111174”
   5. The review of simulation methods should include comparisons between quasi-steady state and dynamic approaches, their computational effort, temporal resolution, and data needs (e.g., hourly weather files, internal load schedules, occupancy). I suggest a work which compares several software capabilities “Crawley DB, Hand JW, Kummert M, Griffith BT. Contrasting the capabilities of building energy performance simulation programs. Building and Environment 2008;43:661–73. https://doi.org/10.1016/j.buildenv.2006.10.027” and other works on the topics:
      • Pacheco R, Ordóñez J, Martínez G. Energy efficient design of building: A review. Renewable and Sustainable Energy Reviews 2012;16:3559–73. https://doi.org/10.1016/j.rser.2012.03.045
      • Ferrero A, Lenta E, Monetti V, Fabrizio E, Filippi M, To G. How to apply building energy performance simulation at the various design stages: a recipes approach. 14th IBPSA Conference 2015:2286–93
      • Zakula T, Bagaric M, Ferdelji N, Milovanovic B, Mudrinic S, Ritosa K. Comparison of dynamic simulations and the ISO 52016 standard for the assessment of building energy performance. Applied Energy 2019;254:113553. https://doi.org/10.1016/j.apenergy.2019.113553
   6. The paragraph from line 79 to 111 is very long and not well organised, please consider rewriting.
   7. Greater emphasis should be placed on the role of occupancy in simulations (lines 117-123). Suggested references:
      • Rugani R, Picco M., Salvadori G, Fantozzi F, Marengo M. A numerical analysis of occupancy profile databases impact on dynamic energy simulation of buildings. Energy and Buildings 2024;310;114114. https://doi.org/10.1016/j.enbuild.2024.114114
      • Oldewurtel F, Sturzenegger D, Morari M. Importance of occupancy information for building climate control. Applied Energy 2013;101:521–32. https://doi.org/10.1016/j.apenergy.2012.06.014
   8. Climate change scenarios are briefly touched upon (lines 133–134) but could be enhanced with recent studies, e.g., “Viganò, G.S.M.; Rugani, R.; Marengo, M.; Picco, M. Assessing the Impact of Climate Change on Building Energy Performance: A Future-Oriented Analysis on the UK. Architecture 2024, 4, 1201–1224. https://doi.org/10.3390/ architecture4040062”
5. Methodology:
   1. The distinction between envelope energy needs and consumptions is not always clear. Clarify whether systems were simulated, assumed ideal, or we are just talking about envelope needs.
   2. The weather file source is not clearly documented. Graphical representations of temperature and solar radiation distributions should be included. Also, please indicate the climate classification (e.g., Köppen-Geiger) of the study site.
   3. Acronyms such as BSF must be defined the first time they appear in the main text.
   4. Inputs (lines 202–205) and boundary conditions should be aligned with relevant EN/ISO standards and cited explicitly.
   5. Please add details about the use that was given to the building, whether residential or office, and the schedules used, occupancy, and so on.
   6. Tables 2–4 would benefit from schematic illustrations of the wall, floor, and roof constructions.
   7. Paragraphs at lines 217–218 are unclear and disconnected. Clarify table references and simulation IDs.
   8. References to how EN or ISO standards treat modelling at external or internal reference lines should also be added to paragraphs 220-225.
   9. Line 238, Table 5 is named in the text after the table itself, it must be named before finding it in the text.
   10. Subchapter 2.3. The role of thermal mass is underexplored. Clarify the assumptions made and expand on its importance in dynamic simulation. Also, what do the U-value of the exterior walls refer to? I mean, what type of insulation was used? how does the thermal capacity of the structures vary?
6. Results and Discussions:
   1. The “Results and discussion” section lacks sufficient critical discussions. For instance:
      • Why do heating needs reach 50–60 kWh/m² even for new buildings? Can this be linked to climate data or assumptions?
      • Why are cooling demands really low in absolute terms, yet their sensitivity (percentage differences) matches that of heating?
      • The results concerning glazing, as also mentioned in the conclusions, risk being somewhat misinterpreted. One would indeed expect a change in the solar heat gain coefficient (g-value) from 0.62 to 0.22 to have a significantly greater impact than a 0.1 W/m²K variation in the glazing U-value. However, this does not imply that in all cases the g-value will always have a greater influence than the U-value. It is therefore difficult to draw general conclusions based solely on this case study.
      • Connected to the previous, avoid generalisations based on a single case study; some conclusions should be more cautiously worded.

1. 1. Typo at lines 291–292: “Therefore” is repeated.
   2. Figures 4–7 are hard to read due to colour choices. Red for cooling and blue for heating can be misleading. Moreover, I suggest including brief textual descriptions next to simulation IDs in figures for easier interpretation.

7. Limitations Section:
   1. A dedicated paragraph discussing the limitations of the study is strongly recommended, especially regarding generalisability, weather files, assumed inputs, and so on.
8. Conclusions:
   1. The conclusion section is too long and descriptive. Consider reducing it to focus on key findings and implications.

Author Response

General comment

The manuscript addresses a relevant topic in the field of building energy simulation, focusing on how variations in envelope modelling parameters affect simulation results. However, despite the potential value of this research, the current version of the paper lacks clarity in structure, suffers from significant methodological ambiguities, and omits key literature and theoretical framing. A major revision is strongly recommended.

 

Specific comments

1. Comment: The title should clarify that the analysis is focused on new buildings. This is a crucial distinction in energy modelling and should also be clearly stressed throughout the text.
   Response: As clarified in the revised manuscript, the baseline models are theoretical buildings designed to reflect common residential construction practices in Slovenia prior to NZEB regulations.
   We clarified in Section 2.1 that the selected baseline buildings represent typical multi-family residential buildings constructed in Slovenia over the last three decades. Additional references were provided to support this characterization [28,29].
   
   
2. Comment: The abstract is overly focused on findings and lacks essential elements such as the research gap, the significance of the study, and its broader implications. A complete rewrite is advised.
   Response: The abstract was revised to include the research context, aim, and significance of the study, in addition to the key results. We hope the new version better communicates the relevance and contribution of the paper
3. Comment: The section “0. How to use this template” (lines 34–40) has not been removed. This should be corrected.
   Rsponse: Removed
4. Comment: Introduction:
   Response: Thank you for these constructive suggestions. The introduction was completely restructured. We included the recommended references and improved the narrative flow, transitions, and clarity. The role of occupancy and the impact of climate change on energy performance were also mentioned, although they are not focus subject of this research.
1. Comment: The narrative lacks coherence. The logic connecting general context and the specific objectives of this study should be reinforced.
   Response: New Introduction section has improved logical flow and narrative coherence.
2. Comment: Transitions are sharp, particularly between lines 123–124 and 139–140.
   Response: Smoother transitions ensured in new introduction
3. Comment: Several norms (e.g., EPBD, EN standards) are mentioned but not cited properly in the references (this applies also in other sections of the manuscript).
   Response: Proper citation of EPBD and referenced standards included
4. Comment: The long paragraph from lines 57–72 is unreferenced and should be split and supported by literature. For black-box and grey-box I suggest “Y. Li, Z. O’Neill, L. Zhang, J. Chen, P. Im, J. DeGraw, Grey-box modeling and application for building energy simulations - A critical review, Renewable and Sustainable Energy Reviews 146 (2021). https://doi.org/10.1016/j.rser.2021.111174”
   Response: The long unreferenced paragraph (lines 57–72) is now split and supported with citations, including the suggested Li et al. (2021).
5. Comment: The review of simulation methods should include comparisons between quasi-steady state and dynamic approaches, their computational effort, temporal resolution, and data needs (e.g., hourly weather files, internal load schedules, occupancy). I suggest a work which compares several software capabilities “Crawley DB, Hand JW, Kummert M, Griffith BT. Contrasting the capabilities of building energy performance simulation programs. Building and Environment 2008;43:661–73. https://doi.org/10.1016/j.buildenv.2006.10.027” and other works on the topics:
• Pacheco R, Ordóñez J, Martínez G. Energy efficient design of building: A review. Renewable and Sustainable Energy Reviews 2012;16:3559–73. https://doi.org/10.1016/j.rser.2012.03.045
• Ferrero A, Lenta E, Monetti V, Fabrizio E, Filippi M, To G. How to apply building energy performance simulation at the various design stages: a recipes approach. 14th IBPSA Conference 2015:2286–93
• Zakula T, Bagaric M, Ferdelji N, Milovanovic B, Mudrinic S, Ritosa K. Comparison of dynamic simulations and the ISO 52016 standard for the assessment of building energy performance. Applied Energy 2019;254:113553. https://doi.org/10.1016/j.apenergy.2019.113553

Response: Comparison of quasi-steady-state and dynamic simulation approaches, including data requirements, temporal resolution, and cited Crawley et al. (2008), Ferrero et al. (2015), and others.

1. Comment: The paragraph from line 79 to 111 is very long and not well organised, please consider rewriting.
   Response: Rewritten
2. Comment: Greater emphasis should be placed on the role of occupancy in simulations (lines 117-123). Suggested references:
• Rugani R, Picco M., Salvadori G, Fantozzi F, Marengo M. A numerical analysis of occupancy profile databases impact on dynamic energy simulation of buildings. Energy and Buildings 2024;310;114114. https://doi.org/10.1016/j.enbuild.2024.114114
• Oldewurtel F, Sturzenegger D, Morari M. Importance of occupancy information for building climate control. Applied Energy 2013;101:521–32. https://doi.org/10.1016/j.apenergy.2012.06.014

Response: Expanded discussion of occupancy using Rugani et al. (2024) and Oldewurtel et al. (2013).

1. Comment: Climate change scenarios are briefly touched upon (lines 133–134) but could be enhanced with recent studies, e.g., “Viganò, G.S.M.; Rugani, R.; Marengo, M.; Picco, M. Assessing the Impact of Climate Change on Building Energy Performance: A Future-Oriented Analysis on the UK. Architecture 2024, 4, 1201–1224. https://doi.org/10.3390/ architecture4040062”
   Response: Climate change consideration now includes Viganò et al. (2024).
1. Comment: Methodology:
   Response: Thank you. We revised Section 2 to clarify distinctions between modeled energy needs and actual consumption. All key acronyms such as BSF are now defined at first use. We included references to EN ISO 52016-1 and clarified assumptions about internal gains, infiltration, and setpoints. However, due to space and formatting constraints, schematic illustrations of the construction layers in Tables 2–4 were not included, though textual descriptions are provided.
1. Comment: The distinction between envelope energy needs and consumptions is not always clear. Clarify whether systems were simulated, assumed ideal, or we are just talking about envelope needs.
   Response: Systems were assumed ideal, with unlimited power. The focus of the research is on envelope input parameters only, not on other energy flows related to occupancy, internal gains, or HVAC systems.
   In the paper it istated that we are modeling  qH,nd and qC,nd, (needs), not the actual consumption.
2. Comment: The weather file source is not clearly documented. Graphical representations of temperature and solar radiation distributions should be included. Also, please indicate the climate classification (e.g., Köppen-Geiger) of the study site.
   Response: Weather file, which represents a Typical Meteorological Year (TMY) for Ljubljana, Slovenia, compiled by the Slovenian Environmental Agency using the adapted Sandia method. The local climate is classified as Cfb (temperate oceanic climate) according to the Köppen–Geiger classification.
3. Comment: Acronyms such as BSF must be defined the first time they appear in the main text.
   Response: Included Building Shape Factor with BSF. Also provided in the Abbreviations table
4. Comment: Inputs (lines 202–205) and boundary conditions should be aligned with relevant EN/ISO standards and cited explicitly.
   Response: The boundary conditions are aligned with the Slovenian Rulebook on Efficient Use of Energy in Buildings [27], and heating/cooling setpoints are set to 20°C for heating and 26°C for cooling, consistent with EN ISO 7730 [28]
5. Comment: Please add details about the use that was given to the building, whether residential or office, and the schedules used, occupancy, and so on.
   Response: Only impact of the envelope parameters is investigated on theoretical residential buildins. But sincec the envelope inputs only are investigated (not the internal gains), the occupancy type and patterns are not of relevance for this research. Hopefully this has been clearly communicated in the paper now.
6. Comment: Tables 2–4 would benefit from schematic illustrations of the wall, floor, and roof constructions.
   Response: Thank you for the suggestion regarding schematic illustrations of the wall, roof, and floor constructions. While we agree that visual diagrams can be helpful in some contexts, in this case we believe that the tabular data provided in Tables 2–4 is sufficiently detailed to fully describe the construction assemblies, including layer thicknesses, material properties (density, conductivity, specific heat), and total U-values. These tables enable reproducibility of the model and allow readers to interpret or recreate the assemblies with precision. To maintain clarity and focus in the manuscript, and in light of space limitations, we have opted not to include additional schematics. However, we remain open to including such illustrations in supplementary material if the editorial board considers it necessary.
7. Comment: Paragraphs at lines 217–218 are unclear and disconnected. Clarify table references and simulation IDs.
   Response: The whole section has been rewritten. Simulation IDs and Tables correlation should be clear now.
8. Comment: References to how EN or ISO standards treat modelling at external or internal reference lines should also be added to paragraphs 220-225.
   Response: Now incuded in Section 2.2 Variation of referent dimensions for modeled floor area: According to EN ISO 52016-1:2017 and accompanying guidance documents (e.g., EN ISO 13790 and EN ISO 52000-1), the calculation of floor area and building geometry should be consistent with national definitions, which may adopt internal, external, or mid-wall references. These differences in geometric reference can significantly influence modeled air volumes and envelope surface areas, and consequently affect calculated infiltration and thermal loads. In this study, we explicitly test the sensitivity of energy demand to this geometric assumption by comparing all three reference cases.
9. Comment: Line 238, Table 5 is named in the text after the table itself, it must be named before finding it in the text.
   Response: Updated
10. Comment: Subchapter 2.3. The role of thermal mass is underexplored. Clarify the assumptions made and expand on its importance in dynamic simulation. Also, what do the U-value of the exterior walls refer to? I mean, what type of insulation was used? how does the thermal capacity of the structures vary?
    Response: We agree that thermal mass plays a significant role in dynamic simulation, particularly in relation to peak load shifting and the dampening of temperature fluctuations. In our baseline models, the thermal mass is defined by the thermophysical properties of the building envelope materials (e.g., concrete, mortar, brick), which are detailed in Tables 2–4. These materials provide a consistent and relatively high thermal capacity across all three building models. The U-value of the external walls (0.176 W/m²K) corresponds to a multilayer assembly that includes mineral wool insulation (λ = 0.144 W/m·K, 20 cm thick) as the primary insulating layer.
    To isolate the impact of added internal thermal mass, we introduced variations by modeling wooden furniture occupying 1% and 2% of the internal volume, with assumed material properties (density and specific heat) as noted in Section 2.5. While the structural thermal mass was held constant across simulations, these furniture mass variations allowed us to assess the impact of internal capacitance on cooling performance in particular. We have clarified these assumptions and expanded the discussion of thermal mass and its dynamic effects in the revised manuscript.
2. Comment: Results and Discussions:
   Response: Thank you for your thoughtful remarks. We expanded the Discussion section to address differences in absolute vs. relative energy needs for heating and cooling. We also added clarifications to avoid overgeneralization regarding the relative influence of glazing parameters. Additional commentary was provided to explain the counterintuitive sensitivity results.
1. Comment: The “Results and discussion” section lacks sufficient critical discussions. For instance:
• Comment: Why do heating needs reach 50–60 kWh/m² even for new buildings? Can this be linked to climate data or assumptions?
  Response: Thank you for your question. The heating demand values in the range of 50–60 kWh/m² are the result of several modeling assumptions. Notably, internal heat gains from occupancy, lighting, and appliances were intentionally omitted to isolate the effects of envelope-related parameters, which naturally increases the simulated heating load.
  Additionally, the simulated climate corresponds to Ljubljana, which has a relatively cold heating season. In this regional context, the observed values are not considered excessive. For comparison, national regulations in nearby countries, such as Serbia, define Energy Grade C for new residential buildings as requiring <100 kWh/m² for heating. Buildings achieving <50 kWh/m² (Grade B or better) remain relatively rare in practice.
  We have added a short clarification on this to avoid potential misinterpretation.
• Comment: Why are cooling demands really low in absolute terms, yet their sensitivity (percentage differences) matches that of heating?
  Response: Thank you for this important observation. The relatively low absolute cooling demands observed in our simulations result from a combination of factors, including the regional climate conditions (Ljubljana), building orientation, and the relatively modest glazing areas. While the absolute values remain low, the sensitivity to certain input parameters—particularly those affecting solar gains—remains high due to the limited baseline demand, which amplifies relative variation.
  We acknowledge that a deeper exploration of the underlying thermophysical mechanisms contributing to these patterns would add value. However, the primary objective of this study was to conduct a structured sensitivity analysis rather than a comprehensive explanation of model behavior. Further investigations into these mechanisms, possibly including parametric studies with varied climates and fenestration scenarios, are planned as part of future work.
• Comment: The results concerning glazing, as also mentioned in the conclusions, risk being somewhat misinterpreted. One would indeed expect a change in the solar heat gain coefficient (g-value) from 0.62 to 0.22 to have a significantly greater impact than a 0.1 W/m²K variation in the glazing U-value. However, this does not imply that in all cases the g-value will always have a greater influence than the U-value. It is therefore difficult to draw general conclusions based solely on this case study.
  Response: Conclusions chapter updated to stress out study limitations and avoid unncessary generalizations.
• Comment: Connected to the previous, avoid generalisations based on a single case study; some conclusions should be more cautiously worded.
  Response: This part has been rewritten.

1. Comment: Typo at lines 291–292: “Therefore” is repeated.
   Response: This part has been rewritten.
2. Comment: Figures 4–7 are hard to read due to colour choices. Red for cooling and blue for heating can be misleading. Moreover, I suggest including brief textual descriptions next to simulation IDs in figures for easier interpretation.
   Response: Colours have been updated

1. Comment: Limitations Section:
1. Comment: A dedicated paragraph discussing the limitations of the study is strongly recommended, especially regarding generalisability, weather files, assumed inputs, and so on.
   Response: Thank you for the suggestion. We have tried to address this by rewriting previous sections, including Introductio, Results, and Conclusions.
2. Comment: Conclusions:
1. Comment: The conclusion section is too long and descriptive. Consider reducing it to focus on key findings and implications.
   Response: Thank you. We shortened and refocused the Conclusions section to highlight key findings and practical implications, reducing descriptive repetition.
   
   

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have conducted extensive work on analyzing the influence of various parameters on the TRNSYS simulation results. While the research is somewhat meaningful and useful, the current presentation lacks novelty. Therefore, major revisions are required before the paper can be considered for acceptance. Below are the detailed comments:

1. Line 69: The sentence "This group... widely used" requires further elaboration. The authors should provide more details on black-box and grey-box models, including their limitations, so that readers can better understand why detailed simulation models are still the most widely used.

2. Line 79: This paragraph begins with a discussion of two main categories of BES software. However, the subsequent literature review rarely references or expands on this categorization. 

3. Line 94: The phrase "the use of convective but operational temperature for monitoring..." is somewhat unclear. 

4. The references throughout the manuscript are outdated. The authors should cite more recent studies to strengthen the paper and ensure it reflects the current state of research.

5. The introduction contains too many paragraphs, which affects the overall readability. The authors should consolidate and organize the introduction for better flow and coherence.

6. The novelty of the paper is not clearly articulated. The influence of different parameters on building simulation results is a well-studied area. The authors need to clarify and highlight what specifically sets their research apart from prior studies.

7. Line 140: The statement, "...occupancy patterns most often is not the part of building energy performance optimization process," is made, but the authors do not analyze the influence of occupancy patterns in their study. This discrepancy should be addressed.

8. The formal tone of the manuscript needs improvement. For example, the phrasing in Line 369 is too informal.

9. A figure should be added at the end of Section 3 to allow readers to visualize which parameters most significantly influence the simulation results. A heatmap or similar graphical representation would help.

Author Response

1. Comment: Line 69: The sentence "This group... widely used" requires further elaboration. The authors should provide more details on black-box and grey-box models, including their limitations, so that readers can better understand why detailed simulation models are still the most widely used.
   Response: We have expanded the relevant paragraph in the Introduction to include a brief explanation of black-box and grey-box models, along with their respective limitations. While these approaches offer benefits such as faster calibration, their reduced transparency and limited generalizability in design scenarios reinforce the continued preference for physics-based models in building simulation.
2. Comment: Line 79: This paragraph begins with a discussion of two main categories of BES software. However, the subsequent literature review rarely references or expands on this categorization. 
   Response: Thank you. We agree that the initial classification into two categories of BES tools (quasi-steady-state and dynamic) should be consistently reflected throughout the literature review. The revised Introduction now integrates this structure more clearly into the discussion of simulation tools and associated studies
3. Comment: Line 94: The phrase "the use of convective but operational temperature for monitoring..." is somewhat unclear. 
   Response: Thank you for pointing this out. The sentence has been revised for clarity. We replaced the ambiguous phrasing with “operational temperature, accounting for both convective and radiative components,” in accordance with EN ISO 7730 terminology.
4. Comment: The references throughout the manuscript are outdated. The authors should cite more recent studies to strengthen the paper and ensure it reflects the current state of research.
   Response: We appreciate this valuable comment. Several recent references have been added throughout the Introduction and Methodology sections to reflect current research trends and to strengthen the contextual background of our study. These include works published between 2019 and 2024, covering sensitivity analysis, simulation validation, occupancy modeling, and climate impacts.
   The reference list was partially reduced and modified. We consider older used references to be still relevant.
5. Comment: The introduction contains too many paragraphs, which affects the overall readability. The authors should consolidate and organize the introduction for better flow and coherence.
   Response: Thank you for this stylistic observation. We carefully revised the Introduction and consolidated several paragraphs to improve flow and readability, while maintaining thematic clarity.
6. Comment: The novelty of the paper is not clearly articulated. The influence of different parameters on building simulation results is a well-studied area. The authors need to clarify and highlight what specifically sets their research apart from prior studies.
   Response: We now explicitly clarify the novelty of our study in the revised Introduction and Conclusions. While sensitivity analyses of simulation parameters are not new per se, our work is unique in comparing how these sensitivities vary across buildings with different shape factors (BSF), using a consistent simulation framework. This allows us to identify when certain parameters (e.g., glazing properties) become more or less influential depending on geometry.
7. Comment: Line 140: The statement, "...occupancy patterns most often is not the part of building energy performance optimization process," is made, but the authors do not analyze the influence of occupancy patterns in their study. This discrepancy should be addressed.
   Response: We have revised the statement to clarify that while occupancy is a known influential parameter, it is not the focus of this study. Our simulations omit internal gains in order to isolate the effects of envelope-related variables.
8. Comment: The formal tone of the manuscript needs improvement. For example, the phrasing in Line 369 is too informal.
   Response: Thank you for the suggestion. The sentence in question was reworded to ensure a more formal tone in line with academic writing standards.
9. Comment: A figure should be added at the end of Section 3 to allow readers to visualize which parameters most significantly influence the simulation results. A heatmap or similar graphical representation would help.
   Response: Thank you for this thoughtful idea. While we agree that a graphical summary (e.g., heatmap) could enhance interpretation, we have chosen to maintain the current set of figures for consistency and space considerations. However, we expanded the textual discussion of sensitivity results at the end of Section 3 to help guide the reader through the key findings.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The paper is relatively well written and addresses an important topic. I suggest that the authors should elaborate more on their contributions. It's unclear what gaps have been identified in the literature and how this study has filled those gaps. A careful proofreading would improve the quality of the paper. E.g., section 0 should be removed. 

 

P9,ln.306-7: please avoid one sentence paragraph.

 

There's a place where design was written as sign.

It's surprising to see discussions of the practical implications of the study in section 2 material and methods. 

Author Response

Thank you for your comments. Per another reviewer's request, the paper has been significantly modified. Your comments have been included as well.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

1.This paper mainly adopts conventional methods in the field of building energy, namely TRNSYS simulation and sensitivity analysis. No new theoretical framework or algorithm improvement has been proposed.

2.Some chart numbers are duplicated. For example, Table 16 actually contains data for Building II, but the title is mislabeled as Building III, which may confuse readers.

3.The symbols in the formulas are not unified, and the writing is non - standard. For instance, "U - value" is written as "u - value" in the chart (Table 10) while it is written as "U - value" in the main text, which violates the norms of academic writing.

4.In the references, the comparison of simulation tools and parameter sensitivity has been explored. This paper has not significantly surpassed the existing achievements.

5.After revising the paper, only major revisions for improving readability and logical consistency are mentioned. There is no specific elaboration on the improvement of chart visualization, thus failing to truly respond to and address this comment.

6.The authors understand the importance of validation, have explained the reasons for using theoretical models, and stated that they will use actual energy consumption data for validation in the future. However, merely stating future plans without making substantial validation improvements to the current model cannot truly meet the need for model validation in this study.

Author Response

Comment 1: This paper mainly adopts conventional methods in the field of building energy, namely TRNSYS simulation and sensitivity analysis. No new theoretical framework or algorithm improvement has been proposed.

Response 1: No action needed

Comment 2: Some chart numbers are duplicated. For example, Table 16 actually contains data for Building II, but the title is mislabeled as Building III, which may confuse readers.

Response 2: Updated

Comment 3: The symbols in the formulas are not unified, and the writing is non - standard. For instance, "U - value" is written as "u - value" in the chart (Table 10) while it is written as "U - value" in the main text, which violates the norms of academic writing.

Response 3: Table 10 does not contain “U-value” or “u-value”. I was not able to identify “u-value” (lowercase) anywhere in the text. The “U-value” is consistently used throughout the paper.

Comment 4: In the references, the comparison of simulation tools and parameter sensitivity has been explored. This paper has not significantly surpassed the existing achievements

Response 4: No action needed.

Comment 5: After revising the paper, only major revisions for improving readability and logical consistency are mentioned. There is no specific elaboration on the improvement of chart visualization, thus failing to truly respond to and address this comment.

Response 5: We appreciate the reviewer’s continued attention to the clarity of the figures. In this revision, we updated the color scheme to use blue for cooling and red/orange for heating, which we believe enhances visual intuitiveness and was also recommended by another reviewer. While we considered alternative visualization approaches, we concluded that the current format best balances clarity, comparability across cases, and consistency with the manuscript structure. We would, however, be happy to implement additional improvements based on more specific suggestions regarding figure format or layout.

Comment 6: The authors understand the importance of validation, have explained the reasons for using theoretical models, and stated that they will use actual energy consumption data for validation in the future. However, merely stating future plans without making substantial validation improvements to the current model cannot truly meet the need for model validation in this study.

Response 6: We appreciate the reviewer’s emphasis on the importance of model validation. We fully agree that validation is essential in simulation studies where the objective is to make accurate predictions of real-world performance. However, we respectfully clarify that the aim of this study is not predictive modeling of a specific building, but rather to perform a sensitivity analysis of fundamental modeling assumptions (e.g., envelope properties, floor area geometry, infiltration rates) within a controlled, theoretical framework.
The use of theoretical models was a deliberate methodological choice that enables us to isolate the impact of key parameters without confounding factors present in real buildings (such as uncertain occupancy schedules or unmonitored control strategies). This is a widely accepted approach in parametric sensitivity studies (e.g., Calleja Rodriguez et al. 2019; Coakley et al. 2014) and allows for broader applicability of the findings. Importantly, we used TRNSYS 18, a mature and extensively validated simulation platform, whose thermal zone and HVAC modeling capabilities have been benchmarked against empirical data in numerous prior studies (e.g., Nageler et al. 2018; Dermentzis et al. 2021).
Furthermore, if we do not approach the matter systematically by varying individual parameters, certain parameters can compensate for each other in full-scale simulations. Even when comparing results with measurements published in scientific articles, we do not have always a clear understanding of which parameters have the strongest impact or how the authors defined the boundary conditions. Our article addresses precisely this issue — identifying the key factors that influence the results of thermal simulations. Various software packages, including TRNSYS, require numerous inputs, with varying levels of detail. At the same time, the literature lacks detailed descriptions of how the parameters analyzed in this article affect simulation outcomes.
We agree that empirical validation would enhance the study’s robustness. To this end, we have stated our intention to extend this work to real buildings in future phases, once sufficient monitoring data become available. We have also clarified this limitation more explicitly in the manuscript’s conclusion.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for your thorough revision of the manuscript and for addressing most of the concerns raised during the first round of review. The revised version demonstrates a significant improvement.

However, a few minor issues remain, mainly related to formatting and overlooked corrections.

 

Abstract revision

Although the response letter states that the abstract was revised, the current version appears to be unchanged from the initial submission. Please ensure that the updated abstract is correctly included in the manuscript.

 

Typographical and formatting issues

Several typographical issues persist in the manuscript:

• Line 41: a punctuation anomaly is present (period followed by comma).
• Line 44: awkward use of colons; the sentence structure needs review.
• Line 121: the phrase “Simulation is” appears to be a remnant from a previous draft.
• Line 298: the sentence begins with “Often when theDuring cooling periods”, which seems to be a copy-paste artifact.
• Paragraph from lines 296–304 contains similar inconsistencies and should be carefully proofread.
• In various places, newly inserted words appear to have been added without appropriate spacing from existing text.
• In Table 2, the unit “W/mkmK” appears twice, which is likely a typo and should be corrected.
• Tables 3 and 4, and possibly others, are left-aligned. For consistency with the journal format, consider right-aligning.

These are minor but important details that can be addressed with a careful proofreading and formatting pass.

 

Figures and data interpretation

The simulation ID labels in the figures remain difficult to interpret. I suggest again adding brief descriptions next to or below each code to improve result readability for the reader.

Author Response

Several typographical issues persist in the manuscript:

Comment 1: Line 41: a punctuation anomaly is present (period followed by comma).

Response 1: We thank the reviewer for this observation. However, we were unable to locate the punctuation issue noted on line 41, as the line 41 rads “sector’s energy demand. In households, this share rises further, with 70% of final energy used”. Also, we reviewed the punctuation throughout the paper, including instances of “e.g.,” and “i.e.,” and found that these follow standard formatting rules for abbreviations in academic English. If there is a specific example that remains unclear, we would be happy to revise it further.

Comment 2: Line 44: awkward use of colons; the sentence structure needs review.

Response 2: Thank you for the suggestion. The line 44: reads “climate change.” The first use of colon in the text is line 160, then 165, 176… The awkward use was possibly in the line 405, as part of the sentence “For the configurations investigated, the glazing solar heat-gain coefficient (g-value) exerts the largest relative impact: lowering g from 0.62 to 0.22 increased q_H,nd by ≈ 20–25% and reduced q_C,nd by ≈ 95%. However, this ranking of sensitivity applies only to the studied façades, window-to-floor ratios, and climate. In other climates or building designs, changes in glazing U-value or wall insulation may dominate.” This has been corrected.

Comment 3: Line 121: the phrase “Simulation is” appears to be a remnant from a previous draft.

Response 3: The only place in the original manuscript we have uploaded, where wording “simulation is” was used is line 65, as part of the sentence: “Dynamic simulation is particularly beneficial when modeling the impact of design decisions on HVAC sizing, control strategies, and thermal comfort. Ferrero et al. [5], Pacheco et al. [6], and Zakula et al. [7] provide useful overviews of how different simulation programs and methods can be applied at various stages of building design.”
We appreciate the reviewer’s attention to detail. It appears that some typographical or formatting inconsistencies may have been introduced during the automatic conversion of the Word document to PDF by the submission system. We kindly invite the reviewer to refer to the original Word version uploaded by the authors, which reflects the intended formatting and has been carefully proofread for punctuation and grammar.

Comment 4: Line 298: the sentence begins with “Often when theDuring cooling periods”, which seems to be a copy-paste artifact.

Response 4: Upon reviewing the paper, we were not able to identify “Often when theDuring cooling periods”. It appears like there might be some systematic issue with how the uploaded text is presented to the reviewer”. The only place in text where “During cooling periods” appears is Section 3, second paragraph, line 298.
We appreciate the reviewer’s attention to detail. It appears that some typographical or formatting inconsistencies may have been introduced during the automatic conversion of the Word document to PDF by the submission system. We kindly invite the reviewer to refer to the original Word version uploaded by the authors, which reflects the intended formatting and has been carefully proofread for punctuation and grammar.

Comment 5: Paragraph from lines 296–304 contains similar inconsistencies and should be carefully proofread.

Response 5: That paragraph reads: “A notable finding was the increased cooling energy demand when improving thermal insulation of envelope elements, a counterintuitive outcome driven by solar gains. During cooling periods, solar heat gains often dominate when outdoor temperatures fall below the 26 °C setpoint, causing heat flux from indoors to outdoors. Enhanced insulation reduces this passive cooling effect, retaining more heat indoors and increasing mechanical cooling needs (EN ISO 14683, 2007). This underscores the complex interplay of envelope properties in dynamic simulations, necessitating careful parameter specification to optimize energy performance [3].”
We were not able to identify any issues with punctuation or grammar in that paragraph. However we have revised the paragraph slightly for clarity, and now it reads:
“A notable finding was the increase in cooling energy demand resulting from improved thermal insulation of envelope elements—a counterintuitive outcome driven by solar gains. During cooling periods, solar heat gains often dominate, particularly when outdoor temperatures fall below the 26 °C setpoint, leading to a reversal of heat flux from indoors to outdoors. Enhanced insulation reduces this passive cooling effect, trapping more heat indoors and thereby increasing mechanical cooling needs (EN ISO 14683, 2007). This underscores the complex interplay of envelope properties in dynamic simulations, emphasizing the need for careful parameter specification to optimize energy performance [3].”

What is improved:

"increase in" is smoother than "increased ... when improving" (avoids stacking verbs).

Dash (—) improves the structure over the original comma in the first sentence.

Slight rephrasing for clarity: “leading to a reversal of heat flux” rather than “causing heat flux from…”

"trapping more heat" is more descriptive than "retaining more heat"

Replaced “necessitating careful…” with “emphasizing the need for…”, which is more natural and readable.

Comment 6: In various places, newly inserted words appear to have been added without appropriate spacing from existing text.

Response 6: Once again, we are afraid this might be a systematic issue with how the uploaded paper is presented to the reviewer, as we were not able to identify any such occurrences. There are no obvious spacing errors (e.g., missing space between words) in the current version of the manuscript. Reviewer 2 may have been referring to a previous draft, or possibly misinterpreted tight line breaks or hyphenation artifacts from the PDF rendering (the authors only uploaded the word document).
We appreciate the reviewer’s attention to detail. It appears that some typographical or formatting inconsistencies may have been introduced during the automatic conversion of the Word document to PDF by the submission system. We kindly invite the reviewer to refer to the original Word version uploaded by the authors, which reflects the intended formatting and has been carefully proofread for punctuation and grammar.

Comment 7: In Table 2, the unit “W/mkmK” appears twice, which is likely a typo and should be corrected.

Response 7: Once again, like the above. In the version that we have uploaded, or that we can download from the system, there is only (W/mK) in the Conductivity column.
We appreciate the reviewer’s attention to detail. It appears that some typographical or formatting inconsistencies may have been introduced during the automatic conversion of the Word document to PDF by the submission system. We kindly invite the reviewer to refer to the original Word version uploaded by the authors, which reflects the intended formatting and has been carefully proofread for punctuation and grammar.

Comment 8: Tables 3 and 4, and possibly others, are left-aligned. For consistency with the journal format, consider right-aligning.

Response 8: We appreciate the reviewer’s observation regarding table alignment. In the original submission, we followed the MDPI template instructions and applied the predefined MDPI_4.2_table_body style, which automatically aligns tables, and table content. Our intention was to avoid custom formatting that might conflict with the journal’s final layout process. However, in response to the reviewer’s comment, we have now manually adjusted the alignment of Tables 3 and 4 (and others where applicable) to improve consistency and readability.

Comment 9: These are minor but important details that can be addressed with a careful proofreading and formatting pass.

Response 9: We appreciate the reviewer’s attention to detail. It appears that some typographical or formatting inconsistencies may have been introduced during the automatic conversion of the Word document to PDF by the submission system. We kindly invite the reviewer to refer to the original Word version uploaded by the authors, which reflects the intended formatting and has been carefully proofread for punctuation and grammar.

Comment 9: The simulation ID labels in the figures remain difficult to interpret. I suggest again adding brief descriptions next to or below each code to improve result readability for the reader.

Response 9: We have tried to address these issues in section 3 and hopefully have improved readability.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have well responded to the reviewer's comments. The manuscript now can be accepted.

Author Response

Comment 1: The authors have well responded to the reviewer's comments. The manuscript now can be accepted.

Response 1: Thank you for your kind comments, guidance, and support. 

Round 3

Reviewer 1 Report

Comments and Suggestions for Authors

In Table 2, the unit of "Density (kg/m3)" is incorrectly expressed and should be changed to "kg/m³"

Comments on the Quality of English Language

Some sentences are too verbose and it is recommended to simplify them to improve readability.

Author Response

Comment 1: In Table 2, the unit of "Density (kg/m3)" is incorrectly expressed and should be changed to "kg/m³"
Response 1: Thank you for your comment. This has been updated.