• Journal of KIBIM
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• v.14 no.2
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• pp.13-24
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• 2024

This research suggests a novel visualization approach utilizing Generative AI to render photorealistic architectural alternatives images in the early design phase. Photorealistic rendering intuitively describes alternatives and facilitates clear communication between stakeholders. Nevertheless, the conventional rendering process, utilizing 3D modelling and rendering engines, demands sophisticate model and processing time. In this context, the paper suggests a rendering approach employing the text-to-image method aimed at generating a broader range of intuitive and relevant reference images. Additionally, it employs an Text-to-Image method focused on producing a diverse array of alternatives reflecting architects' styles when visualizing the exteriors of residential buildings from the mass model images. To achieve this, fine-tuning for architects' styles was conducted using the Low-Rank Adaptation (LoRA) method. This approach, supported by fine-tuned models, allows not only single style-applied alternatives, but also the fusion of two or more styles to generate new alternatives. Using the proposed approach, we generated more than 15,000 meaningful images, with each image taking only about 5 seconds to produce. This demonstrates that the Generative AI-based visualization approach significantly reduces the labour and time required in conventional visualization processes, holding significant potential for transforming abstract ideas into tangible images, even in the early stages of design.

• Journal of KIBIM
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• v.14 no.2
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• pp.25-34
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• 2024

This study proposes a new methodology to increase the flexibility and efficiency of the design data evaluation system by combining Building Information Modeling (BIM) technology in the architectural industry, OpenAI's interactive artificial intelligence, and ChatGPT. BIM technology plays an important role in digitally modeling and managing architectural information. Since architectural information is included, research and development are underway to review and evaluate BIM data according to conditions through program development. However, in the process of reviewing BIM design data, if the review criteria or evaluation criteria according to design change occur frequently, it is necessary to update the program anew. In order for designers or reviewers to apply the changed criteria, requesting a program developer will delay time. This problem was studied by using ChatGPT to modify and update the design data evaluation program code in real time. In this study, it is aimed to improve the changing standards and accuracy by enabling programming non-professionals to change the design regulations and calculation standards of the BIM evaluation program system using ChatGPT. In this study, in the BIM-based design certification automation evaluation program, a program in which the automation evaluation method is being studied based on the design certification evaluation manual was first used. In the design certification automation evaluation program, the programming non-majors checked the automation evaluation code by linking ChatGPT, and the changed calculation criteria were created and modified interactively. As a result of the evaluation, the change in the calculation standard was explained to ChatGPT and the applied result was confirmed.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.321-327
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• 2023

The current rapid development of artificial intelligence technology has involved all aspects of the production field. The development of various algorithms and programs has pushed artificial intelligence to a new peak. Due to its complexity and diversity in the field of architectural design, the positive impact of artificial intelligence technology on architectural design is discussed from the perspective of conceptual design. For museums, which are one of the increasingly popular public facilities, the introduction of artificial intelligence technology has provided certain help in assisting the conceptual design of the museum. This article analyzes the theoretical and practical support of artificial intelligence technology in improving conceptual design, analyzing the architectural appearance, structural layout, materials, etc., to increase the feasibility and practicality of assisting conceptual design. It has certain reference significance for building a modern, advanced, international and interactive modern museum.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.203-208
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• 2023

The implementation of artificial intelligence (AI) design for tall building structures is an essential solution for addressing critical challenges in the current structural design industry. Generative AI technology is a crucial technical aid because it can acquire knowledge of design principles from multiple sources, such as architectural and structural design data, empirical knowledge, and mechanical principles. This paper presents a set of AI design techniques for building structures based on two types of generative AI: generative adversarial networks and graph neural networks. Specifically, these techniques effectively master the design of vertical and horizontal component layouts as well as the cross-sectional size of components in reinforced concrete shear walls and frame structures of tall buildings. Consequently, these approaches enable the development of high-quality and high-efficiency AI designs for building structures.

• Architectural research
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• v.26 no.1
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• pp.1-12
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• 2024

This study introduces a deep reinforcement learning (DRL)-based methodology for optimizing apartment space arrangements, addressing the limitations of human capability in evaluating all potential spatial configurations. Leveraging computational power, the methodology facilitates the autonomous exploration and evaluation of innovative layout options, considering architectural principles, legal standards, and client re-quirements. Through comprehensive simulation tests across various apartment types, the research demonstrates the DRL approach's effec-tiveness in generating efficient spatial arrangements that align with current design trends and meet predefined performance objectives. The comparative analysis of AI-generated layouts with those designed by professionals validates the methodology's applicability and potential in enhancing architectural design practices by offering novel, optimized spatial configuration solutions.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 1995.10a
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• pp.85-93
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• 1995

Recently, the development of Artificial Intelligence(AI) and Expert System has caused some interest in the possibility of developing an intelligent CAD system. However, these development and possibility are in an extremenly early stage for Architectural design. In this study, the design process of Residence being recognized as a Constraints-satisfied model, a part of these constraints used in the Architectural design of Residence are being systematized and sorted by the design process. Those regulations and planning items to be considered in the basic planning stage are being systematized as a knowledge base system. The possibility of this knowledge-based system as an effective design tool is studied and an integrated form of Architectural design system is proposed.

• Steel and Composite Structures
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• v.43 no.4
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• pp.501-509
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• 2022

Cracks are common defects in concrete structures. Thus far, crack inspection has been manually performed using the contact inspection method. This manpower-dependent method inevitably increases the cost and work hours. Various non-contact studies have been conducted to overcome such difficulties. However, previous studies have focused on developing a methodology for non-contact inspection or local quantitative detection of crack width or length on concrete surfaces. However, crack depth can affect the safety of concrete structures. In particular, although macrocrack depth is structurally fatal, it is difficult to find it with the existing method. Therefore, an experimental investigation based on non-contact infrared thermography and multivariate machine learning was performed in this study to estimate the hidden macrocrack depth. To consider practical applications for inspection, an experiment was conducted that considered the simulated piloting of an unmanned aerial vehicle equipped with infrared thermography equipment. The crack depths (10-60 mm) were comparatively evaluated using linear regression, gradient boosting, and random forest (AI regression methods).

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1249-1249
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• 2022

The facade, an exterior material of a building, is one of the crucial factors that determine its morphological identity and its functional levels, such as energy performance, earthquake and fire resistance. However, regardless of the type of exterior materials, huge property and human casualties are continuing due to frequent exterior materials dropout accidents. The quality of the building envelope depends on the detailed design and is closely related to the back frames that support the exterior material. Detailed design means the creation of a shop drawing, which is the stage of developing the basic design to a level where construction is possible by specifying the exact necessary details. However, due to chronic problems in the construction industry, such as reducing working hours and the lack of design personnel, detailed design is not being appropriately implemented. Considering these characteristics, it is necessary to develop the detailed design process of exterior materials and works based on the domain-expert knowledge of the construction industry using artificial intelligence (AI). Therefore, this study aims to establish a detailed design automation algorithm for AI-based condition-responsive exterior wall panels and their back frames. The scope of the study is limited to "detailed design" performed based on the working drawings during the exterior work process and "stone panels" among exterior materials. First, working-level data on stone works is collected to analyze the existing detailed design process. After that, design parameters are derived by analyzing factors that affect the design of the building's exterior wall and back frames, such as structure, floor height, wind load, lift limit, and transportation elements. The relational expression between the derived parameters is derived, and it is algorithmized to implement a rule-based AI design. These algorithms can be applied to detailed designs based on 3D BIM to automatically calculate quantity and unit price. The next goal is to derive the iterative elements that occur in the process and implement a robotic process automation (RPA)-based system to link the entire "Detailed design-Quality calculation-Order process." This study is significant because it expands the design automation research, which has been rather limited to basic and implemented design, to the detailed design area at the beginning of the construction execution and increases the productivity by using AI. In addition, it can help fundamentally improve the working environment of the construction industry through the development of direct and applicable technologies to practice.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.6
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• pp.303-310
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• 2023

The equivalent static load for non-structural elements has a limitation in that the sloshing effect and the interaction between the fluid and the water tank cannot be considered. In this study, the equations to evaluate the impulse and convective components in the design codes and previous research were compared with the shaking table test results of a rectangular water tank with flexible wall panels. The conclusions of this study can be summarized as follows: (1) It was observed that the natural periods of the impulsive component according to ACI 350.3 were longer than system identification results. Thus, ACI 350.3 may underestimate the earthquake load in the case of water tanks with flexible walls. (2) In the case of water tanks with flexible walls, the side walls deform due to bending of the front and back walls. When such three-dimensional fluid-structure interaction was included, the natural period of the impulsive component became similar to the experimental results. (3) When a detailed finite element (FE) model of the water tank was unavailable, the assumption S_ai = S_DS could be used, resulting in a reasonably conservative design earthquake load.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.708-712
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• 2006

The objective of this study was to analyze the effects on management performance of architectural design offices, created by requirements of ISO 9001 Quality Management System, including design quality improvement, introduction of management tools to improve architectural office internal management environment, international standardization and open market impacts. This study conducted a questionnaire survey of architectural design offices in Seoul which holding ISO 9001 Quality System Certification. Following analysis using SPSS10, the result of this study is as follow; (1) The requirements of a quality management system influenced performance of resource management, production realization and customer satisfaction. The measurement analysis and improvements show the effect on design group member satisfaction. Also, production realization, resource management and manager responsibility have an effect on improving quality, and measurement analysis and improvement have an effect on economic performance. (2) The requirements of the Quality Management System were shown to influence the group members satisfaction most, but showed a low influence on economic success. (4) The design group member's opinion about the ISO Quality Management System was very positive and had the effect of improving motivation. The system and the result after acquisition was proven to be very positive in architectural design offices.