The design and construction of high-performance buildings have emerged as a preferred solution for reducing energy consumption and greenhouse gas emissions. However, sometimes there is a considerable gap between the design performance and the actual performance of the buildings. Post Occupancy Evaluations (POE) provide tools to quantify the performance relative to the occupant's health, well-being, and comfort. POE is getting widely accepted to obtain feedback for various parameters such as water, energy, indoor environmental quality, and occupant comfort. Key Performance Indicators (KPIs) can be derived based on the obtained feedback to determine the performance gaps. POE has evolved to be a robust scientific methodology; however, traditional methods of conducting POE have been proven time-consuming, inconsistent, and inefficient. This research aims to conceptualize the next generation of post occupancy evaluations that leverages cutting-edge technologies such as Building Information Modeling (BIM), Internet of Things based sensors (IoT), Geographic Information Systems (GIS), and digital twins. The key contributions of this research are presented in a series of manuscripts. In the first paper, the gaps in the existing POE were determined by conducting a thorough literature review. The observed gaps were classified in data collection, analysis, and visualization categories. Broader POE definition, spot measurements of parameters, and 2D plans and charts for visualization made the existing POE procedure time-consuming. Using digital twins that combine the geometric and parametric data from BIM models and built-environment data from GIS and sensor measurements were recommended as potential solutions to address the observed gaps. The second paper explored the application of BIM-IoT-GIS integration to conduct POE. Use case scenarios were developed to derive system requirements to host the BIM-IoT-GIS-integrated POE. Four sequential tests were conducted to integrate a BIM model from Revit and sensors' data from Excel with ArcGIS pro that contained the surrounding environment data. Based on lessons learned from the tests, an optimized workflow was recommended that can be used across a variety of projects. The third paper used the BIM-IoT-GIS-integration concept to create a holistic proof of concept for digital-twin-enabled POE. The proof of concept was validated by conducting a digital-twin-based POE on the STTC building on the Red River College campus in Winnipeg. The indoor thermal comfort was visualized within the STTC digital twin developed in ArcGIS Pro. The preliminary energy consumption analysis concluded that the STTC buildings' average energy savings were approximately 70,000 KWH/year. The potential users for digital-twin-enabled POE were presented with a comparison of iv existing POE and digital-twin-based POE over a survey and a focus group discussion. Based on opinion-based feedback, the conclusion can be made that digital twins improve the overall efficiency of POE. The fourth paper recommended the digital-twin-enabled POE procedure for UVic's engineering expansion project. It established the semantics for POE, followed by a digital twin execution plan that can be used for developing a digital twin during each phase (from planning to operations) of the project. Furthermore, the benefits of the digital-twin-enabled POE procedure were demonstrated by comparison with the existing POE procedure relative to the project phases. This study concluded that conducting the POE on the UVic ECS expansion project will enable the researchers to determine the effectiveness of sustainable features by comparing the performance of existing and proposed facilities. In conclusion, BIM-IoT-GIS-integrated digital twins address the limitations of data collection, analysis, and visualization. These digital twins will enable multi-objective analysis and spatial-temporal visualization and provide deeper insights into the way these high-performance buildings function. / Graduate / 2023-05-24

Inom byggbranschen är förseningar i byggprojekts leveranser vanligt förekommande och utgör ett utmanande problem. För att övervinna detta problem krävs en utvecklad och noggranna tidsplaner som följs av alla berörda parter. I dagsläget använder sig byggindustrin huvudsakligen av aktivitetsbaserade tidsplaner, som representeras av Critical Path Method (CPM) och dess Gantt-schema. Trots att en annan tidsplaneringsmetod, baserad på lokalitet, visar lovande potential för att effektivt hantera förseningar i leveranser, har den inte fått samma uppmärksamhet. Line of Balance (LOB) är en metod inom location-based scheduling (LBS), där platsen behandlas som en dimension i produktionsprocessen och den har visat sig vara effektivare alternativ än Gantt-schema. I stället för att endast fokusera på aktiviteter fördelar LOB-metoden aktiviteter på lokaliteter där de ska genomföras, vilket underlättar för alla parter att följa en tydlig plan och övervaka arbeten på ett enklare sätt. BIM-verktyg har visat sig vara effektiva för att förbättra och effektivisera LOB-tidsplaner genom att tillhandahålla specialiserade verktyg som underlättar skapandet av sådana tidsplaner. CPM-metoden utgör grunden för många programvaror som används för att skapa LOB-tidsplaner såsom programmet Vico Office. Dessutom kan användning av BIM-verktyg möjliggör tillämpning av Lean-tänkande som bidrar till att förbättra arbetsflöden och öka kvalitet. Detta arbete undersöker hur tidsplaner påverkas vid övergången från aktivitetsbaserade- till lokalitetsbaserade tidsplaner, med hjälp av BIM-verktyget Vico Office. Vidare undersöks hur tillämpningen av Lean-principer såsom ”Visual Management” och ”Reduced Batch Size” påverkar lokalitetsbaserade tidsplaner. Gantt-schemat som analyserades i detta arbete är specifikt för byggföretaget NCC och omfattar utförandet av Hus A, Hus B och en förskola. Dock var endast detaljerad information om aktiviteterna som ingår i Hus A tillgängliga. För att konvertera Gantt-schemat till en lokalitetsbaserad tidsplan användes aktiviteternas varaktighet och lokaliteter från Gantt-schemat. För aktiviteter som saknade lokaliteter användes logiskt tänkande och erfarenhet för att fördela dem i lämpliga lokaliteter. Dessutom användes byggritningar som tillhandahölls av Karlstads kommunen för att tillämpa Lean-principen ”Reduced Batch Size”. LOB-diagrammet som genereras av Vico:s Schedule Planner är i enlighet med Lean-principen ”Visual Management”. Det har visat en förbättrad förmåga att upptäcka tomma områden, kollisioner och diskontinuerliga aktiviteter jämfört med Gantt-scheman. Dessutom användes Lean-principen ”Reduced Batch Size” för att minska väntetiderna mellan arbetsgrupper. Trots att byggprojektets ledtid överskreds med två veckor, resulterade konverteringen i en lokalitetsbaserad tidsplan som främjade ett kontinuerligt arbetsflöde, en effektivare arbetsrytm och en förbättrad uppföljning av byggprocessen. / In the construction industry, delays in project deliveries are a common occurrence. In order to overcome this problem, a developed and accurate schedule is required which is followed by all parties concerned. Currently, traditional activity-based Gantt charts are primarily used. However, another scheduling method based on location shows promising potential for effectively managing delivery delays but has not received the same attention. Line of Balance (LOB) is a method within location-based scheduling (LBS), where the location is treated as a dimension in the production process, and it has proven to be a more efficient alternative than the Gantt chart. BIM tools, such as Vico Office, have proven effective in improving and streamlining LOB schedules by providing specialized tools that facilitate the creation of such schedules. Additionally, the use of BIM tools can facilitate the application of Lean thinking, which helps improve workflows. This study investigates how schedules are affected by the transition from activity-based to location-based schedules using the BIM tool Vico Office. Furthermore, it examines how the application of Lean principles such as “Visual Management” and “Reduced Batch Size” affect location-based schedules. The Gantt chart analysed in this study belongs to the construction company NCC and contains detailed information on the activities in House A. The LOB diagram generated by Vico's Schedule Planner aligns with the Lean principle of “Visual Management”. It has demonstrated an improved ability to detect empty areas, collisions, and discontinuous activities compared to Gantt charts. Additionally, the Lean principle of “Reduced Batch Size” was utilized to minimize waiting times between work groups. Despite the project exceeding the allotted time by two weeks, the conversion resulted in a location-based schedule that promoted continuous workflow, enhanced efficiency, and improved monitoring of the construction process.

<p>  </p> <p>This research is motivated by the potential of autonomous mobile robots (AMRs) in enhancing safety, productivity, and efficiency in the construction industry. The dynamic and complex nature of construction sites presents significant challenges to AMRs, particularly in localization and mapping – a process where AMRs determine their own position in the environment while creating a map of the surrounding area. These capabilities are crucial for autonomous navigation and task execution but are inadequately addressed by existing solutions, which primarily rely on visual Simultaneous Localization and Mapping (SLAM) methods. These methods are often ineffective in construction sites due to their underlying assumption of a static environment, leading to unreliable outcomes. Therefore, there is a pressing need to enhance the applicability of AMRs in construction by addressing the limitations of current localization and mapping methods in addressing the dynamic nature of construction sites, thereby empowering AMRs to function more effectively and fully realize their potential in the construction industry.</p> <p>The overarching goal of this research is to fulfill this critical need by developing a novel visual SLAM framework that is capable of not only detecting and segmenting diverse dynamic objects in construction environments but also effectively interpreting the semantic structure of the environment. Furthermore, it can efficiently integrate these functionalities into a unified system to provide an improved SLAM solution for dynamic, complex, and unstructured environments. The rationale is that such a SLAM system could effectively address the dynamic nature of construction sites, thereby significantly improving the efficiency and accuracy of robot localization and mapping in the construction working environment. </p> <p>Towards this goal, three specific objectives have been formulated. The first objective is to develop a novel methodology for comprehensive dynamic object segmentation that can support visual SLAM within highly variable construction environments. This novel method integrates class-agnostic objectness masks and motion cues into video object segmentation, thereby significantly improving the identification and segmentation of dynamic objects within construction sites. These dynamic objects present a significant challenge to the reliable operation of AMRs and, by accurately identifying and segmenting them, the accuracy and reliability of SLAM-based localization is expected to greatly improve. The key to this innovative approach involves a four-stage method for dynamic object segmentation, including objectness mask generation, motion saliency estimation, fusion of objectness masks and motion saliency, and bi-directional propagation of the fused mask. Experimental results show that the proposed method achieves a highest of 6.4% improvement for dynamic object segmentation than state-of-the-art methods, as well as lowest localization errors when integrated into visual SLAM system over public dataset. </p> <p>The second objective focuses on developing a flexible, cost-effective method for semantic segmentation of construction images of structural elements. This method harnesses the power of image-level labels and Building Information Modeling (BIM) object data to replace the traditional and often labor-intensive pixel-level annotations. The hypothesis for this objective is that by fusing image-level labels with BIM-derived object information, a segmentation that is competitive with pixel-level annotations while drastically reducing the associated cost and labor intensity can be achieved. The research method involves initializing object location, extracting object information, and incorporating location priors. Extensive experiments indicate the proposed method with simple image-level labels achieves competitive results with the full pixel-level supervisions, but completely remove the need for laborious and expensive pixel-level annotations when adapting networks to unseen environments. </p> <p>The third objective aims to create an efficient integration of dynamic object segmentation and semantic interpretation within a unified visual SLAM framework. It is proposed that a more efficient dynamic object segmentation with adaptively selected frames combined with the leveraging of a semantic floorplan from an as-built BIM would speed up the removal of dynamic objects and enhance localization while reducing the frequency of scene segmentation. The technical approach to achieving this objective is through two major modifications to the classic visual SLAM system: adaptive dynamic object segmentation, and semantic-based feature reliability update. Upon the accomplishment of this objective, an efficient framework is developed that seamlessly integrates dynamic object segmentation and semantic interpretation into a visual SLAM framework. Experiments demonstrate the proposed framework achieves competitive performance over the testing scenarios, with processing time almost halved than the counterpart dynamic SLAM algorithms.</p> <p>In conclusion, this research contributes significantly to the adoption of AMRs in construction by tailoring a visual SLAM framework specifically for dynamic construction sites. Through the integration of dynamic object segmentation and semantic interpretation, it enhances localization accuracy, mapping efficiency, and overall SLAM performance. With broader implications of visual SLAM algorithms such as site inspection in dangerous zones, progress monitoring, and material transportation, the study promises to advance AMR capabilities, marking a significant step towards a new era in construction automation.</p>

Den ökande komplexiteten i byggprojekt ger upphov till behovet av ett effektivt sätt att designa, hantera och underhålla strukturer. Byggnadsinformationsmodellering (BIM) underlättar dessa processer genom att tillhandahålla en digital representation av fysiska strukturer. Tekla Structures (TS) har blivit en populär programvara för byggnadsinformationsmodellering inom konstruktionsdesign. I konstruktionsingenjörskap spelar kopplingar en viktig roll i att förena olika byggnadsobjekt. Trots det återstår utmaningen att effektivt och noggrant designa kopplingar i TS på grund av det breda spektrumet av tillgängliga kopplingstyper. Befintliga lösningar för rekommendation av anslutningar förlitar sig ofta på fördefinierade regler, vilket begränsar deras tillämplighet och kräver tidskrävande installation. Nylig forskning har undersökt maskininlärningsmetoder för rekommendation av anslutningar, men de lider av skalbarhetsproblem eller hög beräkningskostnad. Denna avhandling behandlar problemet med rekommendation av anslutningstyp i Tekla Structures som en klassificeringsuppgift, genom att dra nytta av de olika representationerna av BIM-objekt, inklusive 2D-bilder och attribut. Avhandlingen förbättrar befintliga metoder för enskilda datakällor genom att jämföra XGBoost med random forest för attribut, samtidigt som den förbättrar den tidigare CNN-modellen för bildklassificering. Dessutom undersöker detta projekt potentialen att kombinera bilder och attributdata för klassificering av anslutningstyper, genom att använda två multimodala strategier för datafusion: sen fusion och intermediär fusion. Resultaten visar att XGBoost med metadata från attributdatamängden ger bästa prestanda, med en maximal noggrannhet på 0.9283, och de experimentella multimodala datametoderna kan inte ytterligare optimera klassificeringsresultaten. Noggrannheten för attributbaserade metoder förbättras med upp till 0.6%. Förbättringen i CNN-modellen kan öka klassificeringsnoggrannheten med upp till 5%. Genom att jämföra olika datakällor och tillvägagångssätt syftar denna avhandling till att ge en praktisk rekommendation för anslutningsdesign och därigenom lägga grunden för bättre anslutningsdesignprocesser inom byggprojekt. / The increasing complexity of construction projects gives rise to the need for an efficient way of designing, managing, and maintaining structures. Building Information Modeling (BIM) facilitates these processes by providing a digital representation of physical structures. Tekla Structures (TS) has emerged as a popular building information modeling software for structural design. In structural engineering, connections play an important role in joining various building objects. However, the efficient and accurate design of connections in TS remains a challenge due to the wide range of available connection types. Existing solutions for connection recommendation often rely on predefined rules, limiting their applicability and requiring time-consuming setup. Recent research has explored machine learning approaches for connection recommendation, but they suffer from scalability issues or high computational costs. This thesis addresses the connection type recommendation problem in TS as a classification task, leveraging the diverse representations of the BIM objects, including 2D images and attributes. This thesis improves existing approaches for single modality data, comparing XGBoost with random forest for attributes, while enhancing the previous CNN model for image classification. Furthermore, this thesis investigates the potential of combining images and attribute data for connection type classification, using two multimodal data fusion strategies: late fusion and intermediate fusion. The results show that XGBoost with metadata of the attribute dataset yields the best performance, with a maximum accuracy of 0.9283, and the experimented multimodal data fusion methods are unable to further optimise the classification results. The accuracy of attribute-based methods is improved by up to 0.6%. The improvement in CNN model can enhance the classification accuracy by up to 5%. By comparing various data sources and approaches, this thesis aims to provide a practical connection recommendation design, thereby laying a foundation for better connection design processes in construction projects.

<div> <div> <p>Building Information Modeling (BIM) serves as an important media in supporting automation in the architecture, engineering, and construction (AEC) domain. However, with its fast development by different software companies in different applications, data exchange became labor-intensive, costly, and error-prone, which is known as the problem of interoperability. Industry foundation classes (IFC) are widely accepted to be the future of BIM in solving the challenge of BIM interoperability. However, there are practical limitations of the IFC standards, e.g., IFC’s flexibility creates space for misuses of IFC entities. This incorrect semantic information of an object can cause severe problems to downstream uses. To address this problem, the author proposed to use the concept of invariant signatures, which are a new set of features that capture the essence of an AEC object. Based on invariant signatures, the author proposed a rule-based method and a machine learning method for BIM-based AEC object classification, which can be used to detect potential misuses automatically. Detailed categories for beams were tested to have error-free performance. The best performing algorithm developed by the methods achieved 99.6% precision and 99.6% recall in the general building object classification. To promote automation and further improve the interoperability of BIM tasks, the author adopted invariant signature-based object classification in quantity takeoff (QTO), structural analysis, and model validation for automated building code compliance checking (ACC). Automation in such BIM tasks was enabled with high accuracy.</p><p><br></p><p><br></p> </div> </div>

Reducing and managing the environmental impacts of building structures has become a priority of building stakeholders and within the architecture, engineering and construction (AEC) community; although, conflicting approaches and methods to combat the issues are present. For example, green building standards are widespread throughout the world; however each one has its own characteristics and consequently its own specific requirements. While all have proven to be effective rating systems and have similar requirements, the distinguishing characteristic that separates them is their treatment of performance and prescriptive metrics. The feature they all severely lack or currently limit is the inclusion of strict engineering evaluation through energy simulations; hence, the reason why they fail to offer procedural steps to meet performance metrics. How can design professionals design energy efficient buildings with such constraints? Fortunately, advances in technology have allowed design professionals access to content found in Building Information Modeling (BIM). However, extracting pertinent information for specific use in energy analysis is problematic because BIM software currently available is filled with interoperability issues when placed in external software for energy analysis and energy analysis software itself is created with many assumptions that affect the tabulated energy results. This research investigates current building rating systems, determines how current professionals meet energy requirements, and prove that it is possible to create an add-on feature to Autodesk Revit that will allow design professionals to extract the needed information to meet energy goals with actual prescribed methods of mechanical systems selection and evaluation.

В настоящее время активно развиваются средства автоматизированного проектирования (САПР), что не может не сказываться на эффективности и разнообразии реализации строительных процессов. Среди широкой гаммы представленных вариаций САПР особое место сейчас занимает продвижение интеллектуального, а точнее информационного проектирования. BIM (с английского Building Information Modeling), а именно информационное моделирование зданий обладает рядом неоспоримых преимуществ по сравнению с устоявшейся системой CAD (с английского Computer-Аided Design). Также BIM-технологии обладают внушительной функциональностью, так как их применение целесообразно не только на стадии проектирования, но и на стадиях строительства и эксплуатации зданий и сооружений. Цель научно-исследовательской работы заключается в разработке программного модуля (плагина) для программного обеспечения Revit 2019, плагин автоматизирует один из процессов строительного проектирования, а именно процесс отделки помещений. Реализовать автоматизацию можно только на основе информации из BIM-модели. / Currently, computer-aided design (CAD) tools are actively developing, which cannot but affect the efficiency and variety of implementation of construction processes. Among the wide range of CAD variations presented, a special place is now occupied by the promotion of intelligent, or rather informational design. BIM (from English Building Information Modeling), namely building information modeling, has a number of undeniable advantages over the established CAD system (from English Computer-Aided Design). Also, BIM technologies have impressive functionality, since their use is advisable not only at the design stage, but also at the stages of construction and operation of buildings and structures. The purpose of the research work is to develop a software module (plug-in) for the Revit 2019 software, the plug-in automates one of the building design processes, namely the interior decoration process. Automation can only be implemented based on information from the BIM model.

В данной работе поднимается решение проблемы проектной компании, заключающейся в трудоемкой и некачественной проверке Revit-моделей, с использованием технологии информационного моделирования. Данное исследование разработано с целью нахождения оптимального способа валидации информационной модели и практического применения результатов. Методом автоматизации валидации выступила разработка Dynamo-скриптов и плагина, выполняющих проверку информационной модели на несколько пунктов BIM-стандарта Компании. Результатом работы является серия Dynamo-скриптов и плагин для Revit, позволяющие сократить трудозатраты BIM-специалистов компании при проверке BIM-моделей на соответствие внутреннему BIM-стандарту, а также снизить влияние человеческого фактора на осуществление процесса валидации. / This paper raises the solution to the problem of the design company, which consists in time-consuming and low-quality verification of Revit models using information modeling technology. This study is designed to find the best way to validate the information model and practical application of the results. The validation automation method was the development of Dynamo scripts and an app that checks the information model for several points of the Company's BIM standard. The result of the work is a series of Dynamo scripts and a app for Revit, which reduce the labor costs of the company's BIM specialists when checking BIM models for compliance with the internal BIM standard, as well as reduce the impact of the human factor on the validation process.

В данной диссертации был проведен анализ программных комплексов на рынке. В процессе работы проводились мероприятия по сбору и формализации требований к программному продукту, проектирование продукта, созданы дизайн макеты, на основе которых был реализован конкретный прикладной сервис. Разработанный сервис выполняет задачи расчета инсоляции и коэффициента естественной освещенности и соответствует современным требованиям по части проектирование пользовательского интерфейса. / In this dissertation, an analysis of software systems on the market was carried out. In the process of work, activities were carried out to collect and formalize the requirements for a software product, product design, design layouts were created, on the basis of which a specific application service was implemented. The developed service performs the tasks of calculating insolation and daylight factor and meets modern requirements in terms of user interface design.

В исследовании рассматриваются подходы к разработке BIM-стандартов в России и заграницей. Описываются основные проблемы при моделировании и проектировании архитектурной части проектов; подход к разработке стандарта работы архитектурного отдела в Revit на примере отдельной проектной компании. / The study examines approaches to the development of BIM standards in Russia and abroad. The main problems in modeling and designing the architectural part of projects are described; approach to the development of a standard for the work of the architectural department in Revit on the example of a separate design company.