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Article

Application of BIM-Driven BEM Methodologies for Enhancing Energy Efficiency in Retrofitting Projects in Morocco: A Socio-Technical Perspective

by
Rim Afa
1,*,
Issam Sobhy
1,2 and
Abderrahim Brakez
1
1
Laboratory of Processes for Sustainable Energy & Environment—ProcEDE, Physics Department, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech 40000, Morocco
2
National Architecture School of Marrakech (ENAM), Marrakesh 40000, Morocco
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(3), 429; https://doi.org/10.3390/buildings15030429
Submission received: 23 November 2024 / Revised: 8 January 2025 / Accepted: 13 January 2025 / Published: 29 January 2025
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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Abstract

:
Conducting accurate and quick energy analyses for retrofitting purposes became crucial for Architecture, Engineering, Construction, and Operations (AECO) markets worldwide. This paper investigates the possibility of determining and implementing an architect-friendly BIM-based energy analysis for Morocco’s Energy Efficiency Retrofitting (EER). For this matter, a socio-technical approach is adopted. The technical part of the study assesses two Building Information Modeling (BIM) tools (ArchiCAD v26 and Revit v23) regarding their Building Energy Modeling (BEM) capabilities for EER. Their evaluation uses a confirmed case of EER located in Marrakech as a baseline to compare the two tools. The social part investigates the AECO market of Marrakech, where the baseline is located, to anticipate the strengths and limits that might influence the implementation of the BIM-based BEM for an EER workflow in architecture studios. The technical part underlines the significant potential of the chosen BIM tools: ArchiCAD is more flexible, customizable, and accurate regarding energy analysis results, while Revit allows for the strong integration of regulations within its process. The social investigation showcases the studied market’s potential for adopting BIM and BEM for EER but highlights the issue of persisting 2D Computer-Aided Design (CAD) workflows. The same social investigation also suggests that combining BIM tools (ArchiCAD and Revit) in the same workflow might benefit the studied market more because of AECO professionals’ diverse needs. These findings constitute a first base for the national implementation of a BIM-based BEM for EER. They also hold the potential to be used in emerging economies with similar AECO markets.

1. Introduction

As a process that takes into consideration both embodied and operating energy [1], energy efficiency retrofitting (EER) for existing buildings is the most efficient way to improve their energy performance by lowering their consumption and adopting renewable energy [2,3,4]. A combination of active and passive methods on the physical and operational levels of the building achieves a critical change in energy consumption and occupants’ behaviors [5,6]. The process shows a significant energy load reduction that can range from 30% to even 72% [2,7,8]. This possibility can be valid for existing structures even if they have very old or weak insulation systems [6,9]. For this matter, retrofitting existing buildings is crucial in developing countries’ strategies for energy and environmental purposes [2,10].
Nonetheless, EER faces many challenges, such as the complexity and uniqueness of existing aging buildings and poor knowledge regarding the financial outcome of retrofitting [11]. Also, the persistence of the linear and sequential approach to the building process in various developing countries [12,13,14] has a critical role in challenging the implementation of EER strategies. Since these markets must regulate energy use, Architecture, Engineering, Construction, and Operations (AECO) professionals, especially architects, are expected to integrate energy performance and consumption evaluations during their projects [15]. Increasing interest in EER requires architects to have an extensive knowledge of energy efficiency, theoretically and practically.
When Building Performance Simulation (BPS) tools started being more architect-friendly during the 1980s and the 1990s [16], they reached more than 400 in number [11]. The difficulty resided in each one of these numerous tools requiring a particular process, know-how, and experience [17]. These requirements make these tools complex and time-consuming for architects, who must integrate Building Energy Modeling (BEM) into their work and collaborate with engineers on the energy aspect [17,18].
TRNSYS exemplifies the complexities of the traditional standalone BPS tools. It is ideal for conducting detailed analyses, such as heating and cooling loads or solar control, yet it operates on a complex energy analysis flowchart (see Figure 6 in ref. [19]). The tool’s intricacy is due to its reliance on creating systems from individual black box elements from its standard library [20] and adding new components from scratch [21].
Tackling the complexity of standalone BPS tools requires adopting better ways to incorporate energy analyses within the process of a project. Building Information Modeling (BIM) presents an efficient building lifecycle that can help an architect-friendly integration of energy analyses within a project (see Figure 1 in ref. [22]). Comparing the TRNSYS flowchart with BIM building lifecycle phases illustrates (see Table 1) the different take on energy integration in a project. This comparison is valid for both new and retrofitting projects, as retrofitting comes as a decision in the operation and maintenance phase and requires a new building lifecycle.
Additionally, regarding the efficiency and clarity of the BIM building lifecycle, BIM authoring tools included internal functionalities and services to conduct energy analyses within their interface. Software packages like ArchiCAD and Revit aim to eliminate inappropriate human intervention that could compromise the reliability of results [23,24]. Maile et al.’s BIM-based BEM workflow [25] exemplifies the ideal semi-automated building energy simulation approach. Numerous studies have investigated BIM-based BEM capabilities of commercial authoring tools [26], underscoring the need for a single tool to build the digital model and run energy analyses.
Establishing an architect-friendly BIM-based BEM workflow for EER does not only face technical challenges. A significant part of its efficiency and success relies on the social component. Various discussions related to implementing Information and Communication Technologies (ICT) in the AECO industries of developing countries cite the human element and its expertise [27]. The social aspect of BIM is one of the critical approaches to consider when implementing it in an AECO market [28]. A particular study by Maskil-Leitan and Reychav [29] underscores the pivotal role of the social component in the successful integration of BEM in BIM. Considering the social impact of the various AECO professionals regarding work culture, interests, and knowledge ensures the efficiency of EER’s BIM-based BEM workflow.
By adopting a socio-technical approach, considered by Abbasnead et al. [28] as a successful ICT implementation method in an AECO market, this study investigates the possibility of establishing an architect-friendly BIM-based BEM workflow for EER in Morocco as an example of an emerging economy. An assessment of BIM tools regarding BEM capabilities for EER is conducted and linked to the results of an exploratory survey about AECO professionals’ software tool use. This approach aims to understand the likelihood of the workflow being implemented and used.
The region of Marrakech in Morocco serves as the case study for investigating this research question. This choice relies on the city’s critical situation regarding energy consumption, climate change aggravation, and important existing housing stock. Marrakech was also chosen as it is already a subject of a successful case of EER of a low-rise residential building, thus providing a reliable baseline for the technical part of this study [30,31,32,33,34,35,36,37]. It is also important to note that Morocco still does not have a BIM implementation strategy and regulations related to EER [38,39,40,41,42]. The official BPS tool implemented in Morocco, Binayate, has already been tested regarding its potential for EER and interoperability with BIM tools [22]. This assessment showed Binayate as not applicable to an EER process; thus, there is a need for a more reliable BIM-based BEM workflow.
The present study is organized into five parts (see Figure 1). The first part introduces the study and defines the research question. The second part establishes a literature review of the research question and highlights the research gap. The method (third part) presents the baseline used to assess the chosen BIM tools and how the social investigation was conducted. The fourth part presents and discusses the outcomes of the technical assessment and the social surveys. Finally, the fifth part serves as a conclusion, underlining the need for more insight into the significance of the results for the research question and future development.

2. Literature Review

As expressed by the research question in the previous part, the present study includes a technical and a social component. The technical aspect of the study requires a clear understanding of existing research on BIM-based BEM for EER regarding the used tools, potentialities, and challenges. On the other hand, the social part aims to uncover the scale of integrating the human component within BIM and BEM for EER-based studies.

2.1. Technical Component

Three keyword categories were chosen to collect relevant references in the existing literature for the review of BIM-based BEM for EER. These categories refer to the three components that compose the problem statement. The first category focused on energy and included terms such as “BEM”, “Energy Simulation”, and “Energy Analysis.” The second category referred to the software part (e.g., “BIM”, “Software”, “Simulation tool”, and “Analysis tool”). The last category focused more on the terminology related to the hardware part of the project, which included words like “Retrofitting”, “Renovation”, “Refurbishment”, and “Building.” The Boolean “OR” and “AND” operators linked each category’s keywords to determine the search strings used. Selected references include peer-reviewed papers published in journals or conference proceedings and Doctorate/Master/Bachelor theses that focused solely on the BEM aspect of a BIM software tool. All references were collected from known databases, Google Scholar, and journals’ websites with related scopes.
A first general review established the dominance of two primary BIM authoring tools: ArchiCAD and Revit. Therefore, a second round prioritized studies on ArchiCAD and EcoDesigner, as well as energy analyses using Revit for EER. Comparative studies between the two authoring tools were kept only when they were focused on energy-related aspects. Overviews about various software tools and reviews were selected only if they were energy-related and included a BIM tool (Autodesk energy-related services such as Green Building Studio (GBS) and Insight were also included). The final selection also comprises studies detailing the BEM and energy analysis process within these software tools, even if they were not focused on retrofitting or low-rise single-family residential buildings.
The criteria discussed above narrowed the number of references to 68, covering a period from 2010 to 2023 (see Figure 2). As shown in Figure 3, Revit is the primary BIM tool used in research studies, with 42% of the selected references, compared to 20% for ArchiCAD. Figure 3 also establishes four categories within the selected references according to their focus and nature: overviews, comparative studies, studies using ArchiCAD, and studies using Revit.

2.1.1. ArchiCAD-Centered References

The main observation about the references focusing on ArchiCAD is the contrast between the small number of papers and the abundance of theses. It is essential to highlight that the selected theses are not exhaustive yet surpass the number of peer-reviewed papers on the authoring tool. Nonetheless, despite their scarcity, the few selected papers provided an exciting and clear insight into the capabilities of ArchiCAD in terms of energy analysis and retrofitting [26,43,44]. Since the selected theses are either for the bachelor’s or master’s degree, they only offer a global insight into the general process of using ArchiCAD and EcoDesigner (BIM-based BEM workflow). The exception is Gholami’s doctoral thesis [45], which focuses on energy efficiency retrofitting for residential buildings, thus offering a deep dive into the topic.

2.1.2. Revit-Centered References

Almost all studies reviewed for this category that conducted energy simulations use Revit solely for BEM but export the energy model to another Autodesk product, such as GBS for energy analysis [46,47,48,49], or Insight 360 for energy performance [50,51,52]. None of these studies addressed the internal energy analysis functionalities critically provided by Revit. It is understood from the selected references that the general approach of BIM-based BEM in Revit means using the authoring tool for energy modeling and conducting energy or building performance analyses using another Autodesk tool. Following the same approach adopted by ArchiCAD-centered references, a part of the studies focused on assessing the capabilities of Revit (and b consequence, an additional Autodesk web-based service) in terms of energy analysis, but many other references were reviewed for the overview they offer on the BEM process.

2.1.3. Comparative Studies

From Figure 3, this category represents only 19% of the selected references. A scarcity is observed in studies that compared the two authoring tools regarding their embedded BEM capabilities. Among the observed tendencies are general descriptive studies [53,54] and studies comparing the authoring tools in terms of their compliance with national third-party energy tools [55,56]. Other studies used interoperability formats (gbXML and IFC) as a means to compare the authoring tools [57,58] or focused on comparing specific functionalities such as R-value calculators, the final parameters interpretation and energy performance results [56], or building schedules and occupancy profiles [23].

2.1.4. Overviews of Various BIM and BEM Software Tools

This category was not expected to offer a detailed insight into the BIM-based BEM process through specific case studies. Nevertheless, it effectively contextualized the capabilities of the two authoring tools on a more comprehensive macro level. While ArchiCAD’s BEM capabilities were reviewed through EcoDesigner, the issue was with Revit, as it is almost never compared with other tools in terms of BEM. Other Autodesk tools, such as GBS or Insight, are the usual choices, with a frequent inclusion of Ecotect (discontinued in 2015). In terms of their nature, these studies are either in-depth literature reviews [17,59], broad studies discussing the issue of BIM and energy [11], overviews focusing on interoperability [60,61], or studies comparing a specific selection of software tools [16,48].
Since all these categories include Revit or ArchiCAD, an analysis was conducted to determine the frequency of inclusion of each one of these authoring tools. It considered the references centered on each authoring tool, comparative studies, and an overview or review that compared Revit, ArchiCAD, or both with other tools. Figure 3 showcases the frequent use of Revit in terms of the literature, which aligns with the percentage representing Revit-centered studies among the overall selection of references for this literature review. However, in light of the observation about the approach to the BIM-based BEM in Revit, Figure 3 also highlights the actual Autodesk tools used for energy analysis. Revit internal energy analysis functionalities represent only 12% of selected studies, even less than Ecotect, an obsolete tool since 2015. This percentage includes mainly the studies that used data generated in Revit to illustrate some aspects of energy analysis findings. Nonetheless, as the same chart suggests, GBS and Insight are the sole tools used to exemplify energy analysis.
An additional analyis is centered around the references presenting case studies subjected to a semi-automated simulation within Revit or ArchiCAD. The distribution of these references according to the geographical location of the studied case studies is represented on a map (see Figure 4). By frequency, the principal case studies are located in the Middle East and South Asia, with India as the most frequent location (eight case studies from 38). Concerning the nature of these case studies, residential use was dominant (see Figure 3) with 66%, with the other 34% representing mainly public buildings and a few commercial case studies. Nonetheless, this only sometimes suggests that all residential case studies are of a small scale, as they represent 54% of the total case studies. Various residential case studies represented mid-size and large buildings, while all non-residential buildings exceeded the small scale.

2.2. Social Component

Despite the technical component being the main focus of the literature review, it is crucial to understand the BIM-based BEM through a non-technical lens. Literature on the social aspect of BIM-based BEM indicates the adoption of two major scales: broad studies and exploratory investigations focusing on AECO professionals of a specific region. Concerning broad studies, various authors discussed BIM in developing countries, social issues related to its implementation, and strategies that can allow its successful integration within the fragile AECO markets [27,28,29,62,63,64]. Exploratory investigations in specific regions complement the findings of the broad studies, bringing more understanding. Attia et al. [65] studied the criteria determining the “architect-friendliness” of 10 BPS tools in the USA according to various profiles of AECO professionals. Sistani and Rezaei [66] surveyed AECO professionals to better understand BIM implementation and use. Focusing on the “architect-friendliness” of energy analysis tools, Weytjens and Verbeeck [15] chose Flanders to survey architects’ preferences and use of BPS tools.

2.3. Research Gap

On the technical level, the literature review highlights the scarcity of studies centering on comparing BIM tools in terms of BEM for EER without relying on third-party tools via IFC or gbXML files, particularly for Revit. Regarding the social aspect, and despite broad studies discussing BIM in developing countries, a lack of studies focusing on these specific AECO markets can be observed. Almost all studies surveying architects and professionals in a particular region are located in developed countries. These two aspects constitute the research gap this paper wants to address. The findings of this literature review strengthen the choice of Marrakech in Morocco for the social part of this study and address the lack of comparative studies on BIM-based BEM by choosing to assess the BEM capabilities of ArchiCAD and Revit for EER.

3. Method

Concerning the technical part of this study, ArchiCAD and Revit will be compared regarding their BIM-based BEM capabilities for EER. To do so, the living laboratory Dar Nassim [33,67], exemplifying a successful EER in Marrakech, was chosen as a baseline. Its retrofitting process was based on a TRNSYS energy analysis, serving as a basis for making adequate EER decisions. Heating and cooling loads were lowered by 19% and 42%, respectively, after retrofitting, thus confirming the reliability of TRNSYS analyses. The living laboratory Dar Nassim provides necessary data for as-is building modeling and BEM. Pre-retrofitting characteristics of the baseline were chosen to compare the two chosen BIM authoring tools (see Figure 5 and Table 2). Two as-is models based on these characteristics were elaborated in ArchiCAD 26 and Revit 23 (see Figure 6).

3.1. ArchiCAD Analysis

The simulation used the standard built-in EcoDesigner of ArchiCAD 26, as the paid version was discontinued [68]. The model is divided into various thermal blocks. Each one integrates relevant architectural zones and inherits all their characteristics regarding structural elements and openings. Various adjustments are made to finalize the energy model, mainly the general U-Value, solar absorptance, and infiltration of all structural elements and openings. The infiltration value was set to 0 for all structural elements and openings. U-value and solar absorptance were modified manually, as the values calculated from ArchiCAD materials and those of the baseline model were slightly different.
An operational profile with a residential occupancy type was created, with a daily schedule indicating no human activity and a ranging internal temperature between 18 °C and 26 °C (see Figure 7). This profile was assigned to all thermal blocks, including a wall-mounted gas boiler for heating and Window AC units for cooling as building systems.
A Typical Meteorological Years (TMY) climate data file was uploaded and then matched with the exact location of the building. ArchiCAD generates a climate analysis that includes air temperature, relative humidity, solar radiation, and wind speed. Annual air temperature data indicate 46 °C as the highest temperature and 3 °C as the lowest, which verifies the accuracy of the climate analysis. Details about horizontal shading (see Figure 8) and wind protection (see Figure 9) were added. A solar analysis of all openings containing a glazing percentage was rerun to consider new adjustments.

3.2. Revit Analysis

For Revit, spaces were created and characterized by their construction and space types. This study’s analytical construction elements were left in their “default form”. A space type named “Nassim” was created and assigned to all spaces, where each value was set to 0 to match the scenario of an unoccupied dwelling. Created spaces were assigned to adequate Heating, Ventilation and Air Conditioning (HVAC) zones matching the baseline model (see Figure 5), which were completed with additional inputs (see Table 3). Calculated U-values were not similar to those of the baseline model. The structural elements and openings’ parameters were adjusted to reach the targeted values. Since Revit does not offer the possibility to upload a weather file, the location of the living laboratory Dar Nassim was added, and the nearest weather station was chosen for energy analysis (see Figure 10).

3.3. Social Study

Two surveys were conducted to assess the Marrakech AECO market regarding its potentialities and challenges for adopting BIM-based BEM workflows for EER. The first survey targeted architecture and civil engineering students to assess future AECO professionals’ use of BIM and BEM tools. Architecture students targeted by the survey were from the 3rd to the 6th year. As civil engineering is a master degree specialization, civil engineering studentswere from the 4th and 5th year. A total of 165 students were surveyed, with 53% being from the architecture curriculum and 47% in the masters of civil engineering. The survey tackled broader aspects about the BIM, BEM, and EER, but results regarding used software tools were the only outcome included in the present study.
The second survey targeted architecture studios. Rather than interviewing studio owners and managers, this study chose to conduct the survey from the perspective of their interns. As 4th-year architecture students have a mandatory and graded internship, seventy-five students were interviewed regarding their experience. Students provided details about the studio of their internship in terms of their general workflow, used software tools, relationships with the civil engineering firms, and their likelihood to integrate new technologies or approaches suggested by the interninto their workflow. This approach aimed to get an honest third-party point of view about the studio, thus choosing students interning in an architecture studio for the first time instead of directly interviewing its manager. Studios outside the region of Marrakech or in different climate zones were excluded, keeping 38 studios.

4. Results and Discussion

Following the steps described in the method, two sections underline and comment on this study’s results. The first section focuses on the BIM tools analyses, while the second concentrates on the social investigation.

4.1. BIM Tools Analyses

The comparison between Revit and ArchiCAD can be compiled into three categories. The first category concerns modeling capabilities and includes as-is building modeling and the integration of thermal properties within the model’s components. The second category assesses energy-related parameters (building systems and climate/location) and energy modeling. The third category focuses more on the analyses results. It showcases the nature and readability of the output and the heating and cooling loads. These aspects were chosen as they significantly affect the results of semi-automated energy simulations for EER.

4.1.1. Modeling Flexibility and Challenges

  • As-is building modeling:
Both software tools present many challenges in accurately modeling the as-is model due to the complexity of existing buildings and unregulated changes. Various countries have inherited a housing stock built before establishing adequate construction regulations, with peculiar characteristics clashing with the modeling logic of authoring tools. Creating many construction elements and materials from scratch was necessary for this study.
ArchiCAD offers broad flexibility in modeling and customizing these construction elements in terms of materials, graphic representation, and structural role. Revit can allow customization, but not by creating elements or materials from scratch. It is only possible by duplicating a similar existing type in a family.
For openings in existing buildings, they are often subject to various Do-it-Yourself (DIY) changes by users. These changes cause them to be outside the standard models and complicate their as-is 3D modeling. As Revit heavily relies on ASHRAE 140 [69,70], customizing openings within a 3D model is challenging. The “family” approach of the tool goes against the intuitive process of BIM modeling. ArchiCAD allows the same flexibility discussed herein for openings. Existing models can be customized (e.g., materials, glazing/opaque ratio), or new openings can be modeled and easily added to its library.
  • Thermal properties:
ArchiCAD and Revit included U-value calculators that take needed data from the materials’ properties to minimize manual input. Both provide extensive materials libraries that provide necessary thermal properties. Except for a few materials (e.g., air space), all other materials have characteristics that vary from the baseline. However, the characteristics of ArchiCAD building materials are the closest to those used in the living laboratory Dar Nassim.
While ArchiCAD allows creating new material from scratch, Revit offers only the possibility to duplicate an existing material, thus inheriting a set of parameters that the user might not need (see Figure 11). In addition to many other inaccuracies highlighted by the existing literature with U-value calculators of Revit and ArchiCAD [16,56,71], the approach to customization is the major difference between the two tools. While Revit has many limitations on the matter, ArchiCAD allows it, thus using only relevant parameters for each material. For better accuracy, there is also the possibility to override the calculated U-value.

4.1.2. Energy Settings and Modeling

  • Climate and location:
Revit provides the user with available weather stations online [72] with two types of climate data: TMY weather stations (starting with 59###) and stations from Autodesk’s climate server based on the years 2004 and 2006 [72]. ArchiCAD downloads climate data from the Strusoft Climate Server based on data from the NOAA-CIRES Climate Diagnostics Center [73]. Nonetheless, it also allows climate data to be uploaded in various file formats. In many EER cases, this possibility provides more accuracy than relying on weather stations.
ArchiCAD provides an automatic analysis within the same window once a climate file is uploaded to verify the accuracy of climate data before running energy analyses. Revit 2023 does not offer the same possibility, as the user can access climate data only through GBS.
  • Building systems:
ArchiCAD also allows customization for building systems. They are either chosen from the default list or created from scratch. Revit does not consider building systems an independent component added or avoided in an HVAC zone. Chosen building systems are rather integrated into “scenarios” that ASHRAE requires according to the nature of a building and its occupancy.
  • Energy modeling:
Each authoring tool has various clashes and inconsistencies that affect the reliability of the energy model. Level 0 of a project seems to have an important effect on thermal zone recognition in the energy model. Other details, like the position and direction of openings and columns pillars, also affect the energy model.
The walls present the biggest challenge for BEM, especially when they have hybrid thicknesses and materials composition, as the BIM tool does not intuitively understand them. They cause the omission of some spaces and elements from the energy model, which requires time to palliate the issue. Many studies highlighted visually or explicitly the same issue [45,50,52]. Nonetheless, these difficulties highlighted the capabilities of the two tools regarding BEM updating. ArchiCAD is quick and straightforward while updating thermal blocks and energy models. Revit, however, takes more time to update an energy model and requires constant deleting and reloading with each change.

4.1.3. Analysis Results and Accuracy

  • Output:
Within ArchiCAD, the energy evaluation is straightforward, generating results within seconds (less than a minute). It generates a customizable and downloadable (as PDF) report containing analyses and information. Key values are given at the top of the report, allowing architects and clients to understand them easily. EcoDesigner also exports the results as an .xlsx file, providing more details for each thermal zone and targeting the more knowledgeable.
Revit is more complex, as its output is split with GBS and Insight 360. Revit provides detailed reports on annual simulations and zone load summaries, but it takes considerable time to generate them. These reports are complex and challenging in terms of exploitation. Another type of energy analysis is elaborated in the cloud, but it takes much time, depending on the size and complexity of the building. The results are only visible in GBS and Insight 360, both web-based services. Insight 360 provides the value of energy consumption by Energy Use Intensity (EUI), the overall cost, and the level of compliance with ASHRAE 90.1 [70] (irrelevant for the case of low-rise residential buildings, which is the focus of this study) and Architecture 2030. GBS provides details on energy consumption and weather analysis.
  • Heating and cooling loads:
The values of heating and cooling loads calculated by ArchiCAD and Revit were compared with the TRNSYS results [31] to determine the reliability of their energy analysis (see Table 4).
However, comparing Revit thoroughly with TRNSYS and ArchiCAD was impossible, as Insight 360 only provides the EUI. To the authors’ best knowledge, no other report and analysis in Revit and GBS provided the net heating and cooling loads or the total number of hours used for their calculations. This issue might be related to the version of Revit used for this study (23), which is associated with many bugs and limitations among users.
ArchiCAD provides the needed values in its report. It highlights a slender overestimation of the net heating and cooling energy. Nonetheless, it remains within an acceptable range since the gap with the TRNSYS results does not reach the acceptable 5% threshold. The deviation of the ArchiCAD results from the baseline might be related to the climate data, as the EcoDesigner climate analysis shows a slight difference regarding the baseline climate values. Other factors might also lead to this deviation, such as the thermodynamic algorithms on which ArchiCAD simulations are based.
Despite Revit and ArchiCAD asserting their compliance with ASHRAE 140 [23,70], a variation is observed between their total net energy. The plethora of parameters that cannot be customized within Revit explains the different results. This difference might also be related to each engine’s calculation method and mathematical and thermodynamic algorithms.

4.1.4. Overall Technical Assessment

Regarding ArchiCAD and Revit energy analysis capabilities, the significant difference between the two authoring tools remains their overall paradigm and approach to architectural design and construction in general. Revit appears to be based on “guiding” users and creating various restrictions that will orient or dictate how they should conduct the different phases of a given project. This approach was experienced in this study, as any parameter that might be misleading or prone to error becomes limited to a specific set of choices the user cannot transgress. This restrictive approach holds many benefits, especially concerning respecting regulations. However, these restrictions tremendously limit data customization regarding as-is models and various thermal inputs, which will always issue an inaccurate energy analysis. ArchiCAD adopts a more holistic approach and allows for adapting and modifying relevant parameters. This is crucial for EER, as existing buildings do not necessarily conform to regulations and undergo unregulated modifications. Yet, vigilance should be taken with the possibility of customization, as it might lead to data manipulation or misleading and inaccurate results. Table 5 summarizes all comparative elements discussed above, revealing the duality between Revit restrictiveness and ArchiCAD customizability. The same table reinforces the difficulty of using TRNSYS by architects, as it lacks 3D and energy modeling flexibility.

4.2. Social Investigation

4.2.1. Pedagogical Insights

Regarding the survey targeting architecture and civil engineering students, the results help determine the major used software tools in each educational field, as shown in Figure 12. A total of 39 software tools were surveyed in students’ answers, but Figure 12 displays only 15 and excludes tools used by less than 10 students. The 15 software tools represent various categories, ranging from tools specifically used by architects (e.g., Lumion, Photoshop) to those used mainly by civil engineers (e.g., Covadis, Robot). Results show the presence of Binayate (both Prescriptive and Performantielle), suggesting a rise of consciousness about the importance of including energy analysis tools in higher education. A notable difference was observed in terms of the BIM authoring tools used. ArchiCAD seems to be the most used BIM tool, while Revit is less used compared to tools such as Sketchup, which is not properly BIM. AutoCAD is the software tool used by the maximum number of students. This result does not translate into AutoCAD being the most used tool, as students specify all software tools they use and master. Being a 2D CAD, the presence of AutoCAD shows the persistence of traditional approaches regarding architecture and civil engineering pedagogical curriculums. However, although this has only been answered by architecture students, the presence of Rhinoceros + Grasshopper among the 15 tools indicates a promising effort to update pedagogical programs to include the latest approaches to architecture and engineering.

4.2.2. Industry Practices

Figure 13 stresses the dominance of architecture studios established in Marrakech compared to nearby cities where few studios have the capacity and enough professional activities to accept interns. Studios with 15 years of experience or less are more open to accepting interns, as they make up 66% of the total surveyed studios. This finding indicates openness in their work culture and flexibility in workflows. The dominance of studios with less than five years of experience reinforces this hypothesis (see Figure 13). The human capacity of studios can influence the likelihood of adopting a BIM-based BEM for EER. The average for the surveyed studios is 4.42 people per studio, a value that suggests implementing a BIM-based workflow for EER in its workflow is possible. The number of tools each studio uses also influences this possibility (see Figure 13), with 2.5 as the average number of tools used per studio. However, it depends on the nature of the tool used.
Figure 14 illustrates this point, showing the dominance of ArchiCAD as the leading BIM tool used. This finding aligns with the two tools chosen for the technical part of this study from the literature. It suggests the possibility of implementing the ArchiCAD-based workflow, which already holds promising results in terms of energy analysis results accuracy and its customizable and flexible capabilities. However, the persistence of studios not using any BIM tool is apparent, backed up by the fact that 52.6% of studios still use AutoCAD. In many cases, a workflow can integrate both AutoCAD and a BIM tool, but using this later makes the difference. Figure 14 indicates that only two studios use the BIM tool in alliance with the BIM approach (collaborative work, integrating data within the 3D model, and scheduling). For 63.3%, the BIM tool serves as a 3D CAD. The issue remains with the 30% of studios still using the BIM tool in a 2D CAD approach, perpetuating ineffective workflows in the AECO market. However, studios with 15 years of experience or less still hold significant potential, as they integrate both the two studios adopting a relatively BIM-based approach of the used tool, plus 80% of total studios that use the BIM tool as 3D CAD. It is easier for a 3D CAD to shift towards a BIM approach than a 2D CAD.

4.3. Summary and Implications

The combination of technical and social results shows interesting findings regarding the possibility of shaping a BIM-based BEM workflow for EER for the Marrakech AECO market’s characteristics. The presence of ArchiCAD and Revit in students’ answers reinforces the relevance and the crucial importance of the technical evaluation conducted for this study. Despite this promising observation, there is a severe limitation to better exploiting both BIM tools (Figure 14). While Revit is underused in architecture studios, ArchiCAD is misused and never exploited to its full potential. The findings suggest that the persistence of the 2D CAD approach to architectural design is the main challenge limiting the proper use of BIM tools. Revit is avoided, as AutoCAD can quickly achieve 2D CAD needs. On the other hand, ArchiCAD is used by many studios as a 2D CAD tool, since they seem to prefer the 2D approach to architectural design but continue using ArchiCAD in their workflow.
These challenges might not be opposing for a BIM-based BEM workflow for EER. They can lead to interesting possibilities regarding the versatility of the chosen workflow for EER. As students’ answers showcase the popularity of ArchiCAD and many Autodesk products (e.g., 3Ds Max, Robot), they call for a hybrid approach to an efficient BIM-based BEM workflow for EER. It is especially needed, considering the primary use of Robot by civil engineers in their job line. Simultaneously, the promising flexibility of an ArchiCAD BIM-based BEM over Revit and its compliance with architects’ need reinforces the relevance of a hybrid approach to combine the best features of both authoring tools.

5. Conclusions

This paper examines the opportunities and barriers associated with the implementation of a Building Information Modeling (BIM)-based Building Energy Modeling (BEM) workflow for Energy Efficiency Retrofits (EERs) in Marrakech. This investigation adopted a socio-technical approach, focusing on the capabilities and limits of the software tool and the human component.
This research’s technical and social findings include an evaluation of ArchiCAD and Revit in terms of their BEM functionalities for EER, alongside surveys that investigated the Architecture, Engineering, Construction, and Operations (AECO) market in Marrakech. The results highlight several critical insights:
  • ArchiCAD and Revit have different potential for EER due to the differences in their general paradigm and approach to architecture and design.
  • ArchiCAD is more accurate and flexible, while Revit has a strong integration of regulations requirements in its internal workflow.
  • The emerging architecture and civil engineering professionals present a substantial potential for the AECO market of Marrakech, as their education provides the necessary tools to apprehend BIM-based BEM workflows for EER.
  • The persistence of the 2D CAD approach to architecture and design in the existing AECO market might present many challenges for implementing a BIM-based BEM workflow for EER.
The interplay between the identified opportunities and challenges, as revealed by the technical and social analyses, is essential for EER in selecting an effective BIM-based BEM workflow.
  • Combining its positive technical results with its wide use by architects, as the surveys suggested, ArchiCAD constitutes a practical choice for a BIM-based BEM workflow for EER.
  • The persistence of AutoCAD usage (2D CAD) as an Autodesk product could be transformed from an issue to an asset for a Revit-based workflow.
  • A hybrid approach might as well be relevant, combining both ArchiCAD- and Revit-based workflows and using interoperability file formats.
Although Marrakech is taken as a case study for this research, results indicate its potential to generalize its findings.
  • National level: The findings of this study hold potential benefits for other regions within Morocco, attributable to the commonalities observed in AECO markets and the parallels in architectural and engineering educational programs.
  • International scale: This study might be beneficial as a first basis for a focused investigation. Since the current paper presents regular issues related to emerging economies, it is relevant to the general discussion about implementing BIM, BEM, and EER in these industries across the globe.
Regardless, this study represents only a first exploration of the topic. Despite the significant results, further studies are needed on the technical and social components and their combination, as suggested by the following:
  • BIM and BEM modeling: Sensitivity studies around each crucial parameter in a BIM-based BEM will bring more understanding of the potential of BIM authoring tools for EER.
  • Workflows: Further research should also be done on a hybrid approach of BIM-based BEM for EER, integrating both ArchiCAD and Revit.
  • AECO market analyses: As the conducted surveys were only exploratory, their role was to indicate the significant trends of the studied AECO market. Their findings can be the basis for further detailed and generalized research, such as applying the Implementation Process Theory, as suggested by Olugboyega and Windapo [62].
  • Pedagogical analyses: Further research is also crucial in the pedagogical aspect, especially regarding in-service training to improve AECO professionals’ knowledge of BIM, BEM, and EER.

Author Contributions

Conceptualization, R.A.; Methodology, R.A., I.S. and A.B.; Software, R.A. and I.S.; Validation, R.A. and A.B.; Investigation, R.A. and I.S.; Resources, R.A.; Data curation, R.A.; Writing—original draft, R.A.; Writing—review & editing, R.A., I.S. and A.B.; Visualization, R.A.; Supervision, I.S. and A.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Structure of the paper.
Figure 1. Structure of the paper.
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Figure 2. Yearly distribution of selected references for the literature review.
Figure 2. Yearly distribution of selected references for the literature review.
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Figure 3. Distribution of selected references for the literature review according to their content.
Figure 3. Distribution of selected references for the literature review according to their content.
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Figure 4. Location of projects used in selected references involving case studies.
Figure 4. Location of projects used in selected references involving case studies.
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Figure 5. Geometric data of the living laboratory Dar Nassim. (a) Ground floor. (b) First floor. (c) Terrace. (d) Section.
Figure 5. Geometric data of the living laboratory Dar Nassim. (a) Ground floor. (b) First floor. (c) Terrace. (d) Section.
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Figure 6. BIM representation of the baseline model. (a) Existing building before retrofitting. (b) ArchiCAD as-is model. (c) Revit as-is model.
Figure 6. BIM representation of the baseline model. (a) Existing building before retrofitting. (b) ArchiCAD as-is model. (c) Revit as-is model.
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Figure 7. Adopted operation profile.
Figure 7. Adopted operation profile.
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Figure 8. Horizontal shading input.
Figure 8. Horizontal shading input.
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Figure 9. Wind protection input.
Figure 9. Wind protection input.
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Figure 10. Chosen weather station for the analysis on Revit.
Figure 10. Chosen weather station for the analysis on Revit.
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Figure 11. Materials properties in Revit.
Figure 11. Materials properties in Revit.
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Figure 12. Software tools use by students.
Figure 12. Software tools use by students.
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Figure 13. Surveyed architecture studios’ characteristics.
Figure 13. Surveyed architecture studios’ characteristics.
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Figure 14. Use of BIM tools trends by architecture studios.
Figure 14. Use of BIM tools trends by architecture studios.
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Table 1. TRNSYS complexities by BIM building life cycle phases.
Table 1. TRNSYS complexities by BIM building life cycle phases.
BIM Building Life Cycle PhaseTRNSYS Approach
Programming
  • Requires various data sets in multiple file formats, which is prone to errors regarding their exactness.
  • Does not support conceptual or detailed design hence the obligation to use other software tools for the matter (e.g., AutoCAD, Sketchup).
Conceptual Design
Detailed Design
Analysis
  • Takes considerable time to elaborate energy simulations.
  • Requires particular know-how to identify needs for each energy simulation.
  • Needs manual input for all data (e.g., materials characteristics, weather data).
  • Demands the use of additional components for certain steps of an energy simulation (e.g., TRNbuild, TRNSYS3d, TRNFlow).
  • Requires particular knowledge to understand the output (e.g., graphs, tables) and use it to make retrofitting decisions.
  • Does not support the possibility of elaborating final design documentation, hence the obligation to do it from scratch and manually in third-party software tools (e.g., 3D models, 2D details, building documents).
  • Lacks minimal interoperability with other Computer-Aided Design (CAD) tools (e.g., adding data from a TRNSYS output to a 3D model in third-party software tools).
Documentation
Fabrication
  • Does not support elaborating documents related to fabrication and scheduling, thus requiring additional third-party software tools (e.g., Microsoft Project, Microsoft Excel), which increases time consumption and the risk of errors.
Construction 4D/5D
Construction
Logistics
Operation and Maintenance
  • Demands repeating all the steps above with new data sets to perform needed simulations for maintenance/operation decisions.
  • Does not keep a building’s energy-related history in one compact “file project”.
Table 2. Structural elements thermal characteristics of the living laboratory Dar Nassim.
Table 2. Structural elements thermal characteristics of the living laboratory Dar Nassim.
CompositionThickness (cm)Heat Transfer Coefficient (W/m2·K)Solar Absorptance
East-West wallsMortar1.50.720.8
Red brick10
Air gap5
Red brick10
Mortar1.5
South-Nord wallsMortar1.51.10.7
Concrete Masonry Unit (CMU)20
Mortar1.5
Interior wallsMortar1.52.740.6
Concrete Masonry Unit (CMU)10
Mortar1.5
Ground floor high slab Plaster coating12.440.6
Hollow roofing brick16
Reinforced concrete4
Concrete screed7
Tiling1
Ground floor low slab (in contact with soil)Pebbles501.860.6
Reinforced concrete7
Concrete screed7
Tiling1
First floor high slabPlaster coating12.240.6
Hollow roofing brick16
Reinforced concrete4
Concrete screed10
Tiling2
Staircase slabPlaster coating12.950.85
Reinforced concrete12
Concrete screed7
Tiling2
Table 3. Chosen inputs for energy settings in Revit.
Table 3. Chosen inputs for energy settings in Revit.
Input Parameters Value
HVAC Zones Creation
Service typeSplit system(s) with mechanical ventilation
Cooling set point26 °C
Heating set point18 °C
Openings Parameters: Windows and Doors
Visual light transmittance0.76
Solar heat gain coefficient0.7
Heat transfer coefficient (U)5.75 W/(m2·K)
Analytic constructionSingle glazing SC = 0.6
Energy Settings
Building serviceSplit System(s) with Mechanical Ventilation
Building infiltration classNone
Building typeSingle Family
HVAC systemResidential 14 SEER/8.3 HSPF split packaged heat pump
Table 4. Heating and cooling loads of the compared software tools.
Table 4. Heating and cooling loads of the compared software tools.
ArchiCAD (Version 26) Revit
(Version 23)		TRNSYS (Version 18) Gap (%) Between TRNSYS and
ArchiCAD		Gap (%) Between TRNSYS and Revit
Net Heating energy (kWh/m2/yr)28.26Not
calculated		27.00 [31]4.6-
Net Cooling
Energy (kWh/m2/yr)		67.08Not
calculated		64.00 [31]4.8-
Total Net energy (kWh/m2/yr)95.3497.5091.00 [31]4.77.4
Table 5. Summarized comparison between TRNSYS and the analyzed BIM authoring tools.
Table 5. Summarized comparison between TRNSYS and the analyzed BIM authoring tools.
TRNSYS
(Version 18)		ArchiCAD
(Version 26)		Revit
(Version 23)
3D Modeling flexibility✗✓✓
3D Construction elements customization ✗✓✗
U-value customization✓✓✗
Materials properties customization✓✓✗
Climate analysis accuracy✓✓✓
Climate data customization✓✓✗
Building systems customization✓✓✗
Energy modeling fluidity✗✓✓
Energy models updating✗✓✗
Output readability✗✓✗
Heating and cooling load accuracy✓✓✗
Compliance with a specific regulation✗✗✓
✓—Available. ✗—Not Available.
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Afa, R.; Sobhy, I.; Brakez, A. Application of BIM-Driven BEM Methodologies for Enhancing Energy Efficiency in Retrofitting Projects in Morocco: A Socio-Technical Perspective. Buildings 2025, 15, 429. https://doi.org/10.3390/buildings15030429

AMA Style

Afa R, Sobhy I, Brakez A. Application of BIM-Driven BEM Methodologies for Enhancing Energy Efficiency in Retrofitting Projects in Morocco: A Socio-Technical Perspective. Buildings. 2025; 15(3):429. https://doi.org/10.3390/buildings15030429

Chicago/Turabian Style

Afa, Rim, Issam Sobhy, and Abderrahim Brakez. 2025. "Application of BIM-Driven BEM Methodologies for Enhancing Energy Efficiency in Retrofitting Projects in Morocco: A Socio-Technical Perspective" Buildings 15, no. 3: 429. https://doi.org/10.3390/buildings15030429

APA Style

Afa, R., Sobhy, I., & Brakez, A. (2025). Application of BIM-Driven BEM Methodologies for Enhancing Energy Efficiency in Retrofitting Projects in Morocco: A Socio-Technical Perspective. Buildings, 15(3), 429. https://doi.org/10.3390/buildings15030429

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