BIM-Based Simulator for Rebar Placement

Park, U-Yeol

doi:10.5345/jkibc.2012.12.1.098

Cited by 16 publications

(6 citation statements)

References 4 publications

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“…Alternatively, a rebar drawing is created by applying CWM algorithm. [3,6,55,84,[86][87][88][89]91,95,97,98,103,105,108,110,111,114,119,120] Quantity take-off Rebar CWM algorithm is connected to the QTO task and progress. [3,5,6,[85][86][87]90,91,98,103,107,108,111,113,115,116] Rebar production…”

Section: Drawing Workmentioning

confidence: 99%

See 1 more Smart Citation

Cutting Waste Minimization of Rebar for Sustainable Structural Work: A Systematic Literature Review

Kwon

Kim

2021

Sustainability

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Rebar, the core resource of reinforced concrete structures, generates more carbon dioxide per unit weight than any other construction resource. Therefore, reducing rebar cutting wastes greatly contributes to the reduction of greenhouse gas (GHG). Over the past decades, many studies have been conducted to minimize cutting wastes, and various optimization algorithms have been proposed. However, the reality is that about 3 to 5% of cutting wastes are still generated. In this paper, the trends in the research on cutting waste minimization (CWM) of rebar for sustainable work are reviewed in a systematic method with meta-analysis. So far, the literature related to cutting waste minimization or optimization of rebar published has been identified, screened, and selected for eligibility by Preferred Reporting Items for Systematic Reviews and Meta-Analyses, and the final 52 records have been included in quantitative and qualitative syntheses. Review by meta-analysis was conducted on selected literatures, and the results were discussed. The findings identified after reviewing the literature are: (1) many studies have performed optimization for the market length, making it difficult to realize near-zero cutting wastes; (2) to achieve near-zero cutting wastes, rebars must be matched to a specific length by partially adjusting the lap splice position (LSP); (3) CWM is not a one-dimensional problem but an n-dimensional cutting stock problem when considering several rebar combination conditions; and (4) CWM should be dealt with in terms of sustainable value chain management in terms of GHG contributions.

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Section: Drawing Workmentioning

confidence: 99%

“…[ 84,85,89,97,98,102,103,105,110,112,118,120] Unlike ordinary materials, quite many variables should be considered in the case of the exact QTO work of rebars. It is a complex task that should reflect the size of stock material, concrete cover, and lap splice length, as well as variables not shown in the drawing, such as bending margin.…”

Section: Drawing Workmentioning

confidence: 99%

Cutting Waste Minimization of Rebar for Sustainable Structural Work: A Systematic Literature Review

Kwon

Kim

2021

Sustainability

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“…Building Information Modeling has the capability to automate a quantity takeoff, which will reduce the time and costs required to estimate a project [5]. The system using Autodesk Revit API automatically generates rebar placement plans for a building structure and labels the placement sequence of each individual bar or set of bars with ascending numbers [6]. At present, most rebar BIM models are established according to the two-dimensional map.…”

Section: Introductionmentioning

confidence: 99%

Applying an A-Star Search Algorithm for Generating the Minimized Material Scheme for the Rebar Quantity Takeoff

Chang¹,

Shiu²,

Wu³

2019

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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Rebar engineering is a construction method for building structures that is critical to the earthquake resistance of the entire building. The construction process and quality of rebar have always been valued by the construction industry, and it is imperative to improve the quality of reinforcement construction to reduce injuries. In recent years, Building Information Modeling (BIM) technology has been widely applied in the stages of design, operation and maintenance, but less in the construction phase. For rebar works in the construction phase, a BIM model of rebar can facilitate the development of a solution because 3D visualization of the model makes it easier to understand the problem. However, to apply the rebar BIM model to practice, it is necessary to build a model with the rebar takeoff to meet the actual construction status. Thus, how to optimize the takeoff of rebar from the completed 3D model has practical research value. This study takes the on-site construction of rebar as an example. For the main component, a BIM model is built with Tekla software to produce practical rebar takeoff plans with an A-star algorithm based on legal norms and construction feasibility that can reduce the amount of excess rebar material. It also chooses the best rebar takeoff plan to build the rebar BIM model. As a result, the relevant personnel who use the rebar BIM model can correctly solve the actual problems with the BIM model.

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“…Various researchers in the past have tried to solve the problem of the clash detection and resolution for automated design of rebar with the aid of BIM technology, in the literature, Park [3] developed a BIMbased simulator to determine the sequence of rebar placement, and the clashes of rebar were identified by a developed application programming interface. Nevertheless, it focused on the simulation of the placement sequence and the spatial clash has to be solved manually.…”

Section: Introductionmentioning

confidence: 99%

Automated Clash Resolution of Rebar Design in RC Joints using Multi-Agent Reinforcement Learning and BIM

Liu¹,

Liu²,

Feng³

et al. 2019

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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The design of rebar in reinforced concrete (RC) structures is a mandatory stage in building construction projects. Due to the large number and complicated arrangement rules of rebar in each design code, it is impractical, labor-intensive and error-prone for designers to avoid all clashes (i.e., collisions and congestion) manually or partial automation by using computer software. Therefore, the building information modeling (BIM) technology has been employed in the present architecture, engineering, and construction (ACE) industry for clash free rebar design. However, it is worth noting that most of existing BIM based approaches are using optimization algorithms for moving components, which can only be applied for regular shaped RC structures. In particular, shapes of rebar are fixed which means the optimized path of rebar cannot bend to avoid the obstacle in current studies. Furthermore, most of the existing studies cannot meet design constraints after avoiding clash, lack automatic and intelligent identification and resolution of rebar clash for complex RC joints and frame structures. Therefore, we present a framework towards automatic rebar design in RC frame without clashes via multi-agent reinforcement learning (MARL) system with BIM. In particular, by treating each rebar as an intelligence reinforcement learning (RL) agent, we propose to model the rebar design problem as a path-planning problem of multi-agent system. Next, by employing FALCON (A fusion architecture for learning, cognition, and navigation) with immediate evaluative feedback as the reinforcement learning engine, we design particular form of state, action, and rewards for reinforcement MARL for automatic rebar design. In addition, the design of rewards and some strategies in MARL are presented for build-ability constraints. Comprehensive experiments on one-story RC building frame have been conducted to evaluate the efficacy of the proposed framework. The obtained results confirmed that the proposed framework with MARL is effective and efficient.

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BIM-Based Simulator for Rebar Placement

Cited by 16 publications

References 4 publications

Cutting Waste Minimization of Rebar for Sustainable Structural Work: A Systematic Literature Review

Cutting Waste Minimization of Rebar for Sustainable Structural Work: A Systematic Literature Review

Applying an A-Star Search Algorithm for Generating the Minimized Material Scheme for the Rebar Quantity Takeoff

Automated Clash Resolution of Rebar Design in RC Joints using Multi-Agent Reinforcement Learning and BIM

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