Browsing by Author "Noureldin, Mohamed"

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  • Algorithmic design and parametric analytics for BIM-driven standardization and automation of prefabricated element drawing creation
    (2024-08-19) Matikainen, Onni
     Insinööritieteiden korkeakoulu | Master's thesis
    The design process of a concrete element involves numerous stages and approximately 3rd of the design time is dedicated to creating structural drawings. The aim of this thesis is to investigate the possibilities of automating and accelerating the drawing creation process within Tekla Structures. WSP assigned this problem to be investigated using Grasshopper-Tekla Drawing Link, a Grasshopper tool kit created by Grzegorz Olszewski. This tool kit allows Grasshopper to automate repetitive manual labor involved in a drawing creation process in Tekla Structures. The main objective of this thesis is to develop an automation tool for creating structural drawings of prefabricated elements using algorithmic design. A secondary objective is to standardize the design process before drawing creation to ensure the correct circumstances for the tool. The first part of this thesis examines the current research on the topic. Numerous studies have explored these possibilities, however, a significant gap remains in current practices. In the scope of precast element drawings, an important factor is specifically the creation of section views depending on the embedded elements and unique characteristics of the structure, and automating this process has not been discussed. The case study, the second part of the thesis, investigates the functionality of the created tool on five different concrete columns. The results are compared by creating similar drawings with an alternative automation tool for drawing creation within Tekla Structures. A tool to create structural drawings automatically was successfully developed. Using the tool, there were no significant mistakes to be remade, all the needed characteristics were dimensioned and the drawings were clear to read which were the the main demands for the developed tool. In addition, the developed standardized methods ensured the correct circumstances for the tool to work as it should.
  • Efficiency optimization in Finnish electrical substation design: Leveraging coding integration and Tekla automation
    (2024-08-12) Polloshka, Gent
     Insinööritieteiden korkeakoulu | Master's thesis
    The urgency to adapt to climate change and the shift towards renewable energy generation have significantly increased the demand for efficient electrical substation designs in Finland. As a result, experts predict a substantial increase in the construction of new similar substations in the coming years. This thesis investigates the inefficiencies in the current design practices of Finnish electrical substations, with a focus on enhancing design efficiency through technological advancements. Through an examination of case studies, work-hour analysis, and interviews with industry experts, the research highlights significant inefficiencies. Modelling and Tekla drawings consume 70% of the project time, emphasizing the critical need for optimization to improve efficiency. To address these challenges, the thesis proposes innovative strategies such as # C coding integration and automation of Tekla tools for modelling and drawing processes. It also provides a collection of structural types essential for electrical substation design. Results demonstrate that when used properly, these strategies and the contributions made in this thesis can improve time efficiency by 10%.
  • Estimation of Prediction Intervals for Performance Assessment of Building Using Machine Learning
    (2024-07) Shabbir, Khurram; Umair, Muhammad; Sim, Sung Han; Ali, Usman; Noureldin, Mohamed
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This study utilizes artificial neural networks (ANN) to estimate prediction intervals (PI) for seismic performance assessment of buildings subjected to long-term ground motion. To address the uncertainty quantification in structural health monitoring (SHM), the quality-driven lower upper bound estimation (QD-LUBE) has been opted for global probabilistic assessment of damage at local and global levels, unlike traditional methods. A distribution-free machine learning model has been adopted for enhanced reliability in quantifying uncertainty and ensuring robustness in post-earthquake probabilistic assessments and early warning systems. The distribution-free machine learning model is capable of quantifying uncertainty with high accuracy as compared to previous methods such as the bootstrap method, etc. This research demonstrates the efficacy of the QD-LUBE method in complex seismic risk assessment scenarios, thereby contributing significant enhancement in building resilience and disaster management strategies. This study also validates the findings through fragility curve analysis, offering comprehensive insights into structural damage assessment and mitigation strategies.
  • Explainable artificial intelligence framework for FRP composites design
    (2024-08-01) Yossef, Mostafa; Noureldin, Mohamed; Al Kabbani, Aghyad
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Fiber-reinforced polymer (FRP) materials are integral to various industries, from automotive and aerospace to infrastructure and construction. While FRP composite design guidelines have been established, the process of obtaining the desired strength of an FRP composite demands considerable time and resources. Despite recent advancements in Machine Learning (ML) models which are commonly used as predictive models, the inherent 'black box' nature of those models poses challenges in understanding the relationship between input design parameters and output strength of the composite. Moreover, these models do not provide tools to facilitate the designing process of the composite. The current study introduces an explainable Artificial Intelligence (XAI) framework that will provide understanding for the input–output relationships of the model through SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs). In addition, the framework provides for the first time a designing approach for adjusting the important design parameters to obtain the desired composite strength by the designer through utilizing an explainability technique called Counterfactual (CF). The framework is evaluated through the design of a 14-ply composite, successfully identifying critical design parameters, and specifying necessary adjustments to meet strength requirements.
  • Review of Mechanical Characteristics of Voided Biaxial Reinforced Concrete
    (2024-04-25) Tran, Minh
     Insinööritieteiden korkeakoulu | Bachelor's thesis
    Voided biaxial reinforced concrete slab, a.k.a. voided slab (VS), is an innovative approach to reducing the weight of slabs and optimizing the volume of concrete used, while not compromising the structural strength. This thesis aims to study the properties of VS, with a strong focus on the mechanical response of slabs to loads. To that end, this work conducted a literature review to explore experimental and computational works done on VS, in which 32 papers as well as materials from selected manufacturers were surveyed. Additionally, 4 reinforced concrete slabs were modelled and were placed under uniform load to qualitatively demonstrate the difference between solid slabs (SS) and VS. The literature review found that compared to SS with the same thickness, VS has fK >= 80% flexural stiffness and fS ~ 60% punching shear strength. With mitigation strategies to improve punching shear strength, VS has fU ~ 90% ultimate load capacity of SS, otherwise fU ~ fS. Strengths and crack patterns of VC can be predicted with construction codes, when removed material is considered. VS can be 10% to 30% lighter, and has higher strength per weight compared to SS. Fire resistance and seismic resistance of VS are comparable to SS. Finally, VS can result in a small reduction in construction cost, a minor increase in construction time and complexity, and a significant reduction in environmental impact indicators. The conducted simulations found that VS can distribute and transfer load more efficiently, and that VS are stronger than SS with the same volume of concrete. In conclusion, voided biaxial reinforced concrete slab technology can offer comparable structural properties to traditional solid concrete slabs, reduce the weight of building, improve the efficiency of concrete material usage, reduce construction cost, and contribute to sustainability in construction.
  • Seismic behavior of semi-rigid beam-to-column connections
    (2023-05-10) Wirén, Alex
     Insinööritieteiden korkeakoulu | Bachelor's thesis