Modelling of 3D concrete printing process: A perspective on material and structural simulations

Nguyen‐Van, Vuong; Li, Shuai; Liu, Junli; Nguyen, Kien; Tran, Phuong T.

doi:10.1016/j.addma.2022.103333

Cited by 30 publications

(20 citation statements)

References 118 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The emphasis is predominantly on unmanned aerial vehicles (UAVs) [26][27][28], where the main goal is to determine the most efficient flight trajectories from departure to arrival points, adhering to mission specifications and autonomous navigation limitations. This field of research also encompasses advancements in 3D-printing design [29,30] and extends to robotic applications in agriculture [31], clinical neurosurgery [32], and visual servoing technologies [33]. A shared aspect among these applications is the creation of three-dimensional models, consideration of real-world limitations, refinement of optimization models, and researchers' widespread adoption of heuristic algorithms to address these complex problems.…”

Section: In the Research On Three-dimensional Path Optimizationmentioning

confidence: 99%

Optimizing the Three-Dimensional Multi-Objective of Feeder Bus Routes Considering the Timetable

Gao,

Liu,

Jiang

et al. 2024

Mathematics

View full text Add to dashboard Cite

To optimize the evacuation process of rail transit passenger flows, the influence of the feeder bus network on bus demand is pivotal. This study first examines the transportation mode preferences of rail transit station passengers and addresses the feeder bus network’s optimization challenge within a three-dimensional framework, incorporating an elastic mechanism. Consequently, a strategic planning model is developed. Subsequently, a multi-objective optimization model is constructed to simultaneously increase passenger numbers and decrease both travel time costs and bus operational expenses. Due to the NP-hard nature of this optimization problem, we introduce an enhanced non-dominated sorting genetic algorithm, INSGA-II. This algorithm integrates innovative encoding and decoding rules, adaptive parameter adjustment strategies, and a combination of crowding distance and distribution entropy mechanisms alongside an external elite archive strategy to enhance population convergence and local search capabilities. The efficacy of the proposed model and algorithm is corroborated through simulations employing standard test functions and instances. The results demonstrate that the INSGA-II algorithm closely approximates the true Pareto front, attaining Pareto optimal solutions that are uniformly distributed. Additionally, an increase in the fleet size correlates with greater passenger volumes and higher operational costs, yet it substantially lowers the average travel cost per customer. An optimal fleet size of 11 vehicles is identified. Moreover, expanding feeder bus routes enhances passenger counts by 18.03%, raises operational costs by 32.33%, and cuts passenger travel time expenses by 21.23%. These findings necessitate revisions to the bus timetable. Therefore, for a bus network with elastic demand, it is essential to holistically optimize the actual passenger flow demand, fleet size, bus schedules, and departure frequencies.

show abstract

Section: In the Research On Three-dimensional Path Optimizationmentioning

confidence: 99%

Optimizing the Three-Dimensional Multi-Objective of Feeder Bus Routes Considering the Timetable

Gao,

Liu,

Jiang

et al. 2024

Mathematics

View full text Add to dashboard Cite

show abstract

“…An alternative approach to numerical simulation that does not come with a high computational cost is data-driven modeling (Nguyen- Van et al, 2023). Researchers used data-driven models to either predict the geometrical properties of the filament or to validate a numerical model using data-driven models.…”

Section: Data-driven Modelingmentioning

confidence: 99%

Developing a data-driven filament shape prediction model for 3D concrete printing

Alhussain,

Duarte,

Brown

2024

Front. Built Environ.

View full text Add to dashboard Cite

With the growing global need for housing and infrastructure, 3D concrete printing (3DCP) has emerged as an innovative construction method offering several potential benefits including design flexibility, speed, and sustainability. However, enhancing the reliability of 3DCP involves managing a variety of parameters that influence various aspects of the 3D printed structure. Process parameters like nozzle velocity, nozzle diameter, nozzle height, and material flow velocity have a major impact on the structural stability and filament shape. This project aimed to develop fast and accurate data-driven models for predicting and classifying filament shape based on process parameters. A print experiment systematically varied process parameters across 144 samples. The resulting filament geometry (width, height, contact width) was measured and classified by quality. Models were trained on this data to predict filament width, contact width, filament height, and classify filaments. These models can be utilized with any buildable material - a material with a high enough yield stress to bear the weight of upper layers without significant deformation. This condition does not restrict this study’s scope as it is a prerequisite for all 3DCP applications. The models’ robustness and generalizability were confirmed through validation on literature data across various printable materials and setups. These data-driven models can aid in optimizing parameters, generating variable width filaments, and printing non-planar layers. By linking print inputs to filament outputs, this comprehensive modeling approach advances 3DCP research for more reliable and versatile concrete printing.

show abstract

“…The digital twin allows the development of a real-time control system that combines physical space and cyberspace so that problems that occur during the printing process like fluctuations in material properties or pumping would be immediately identified and responded to without interrupting the process; this greatly improves its robustness [63]. The DT model can initiate the correct actions for the upcoming printing process based on real-time data sets and it is considered to be effective in improving the automation of 3DCP as well as machine learning techniques [64].…”

Section: Construction Phasementioning

confidence: 99%

Digital Twin Applications in 3D Concrete Printing

et al. 2023

View full text Add to dashboard Cite

The benefits of 3D concrete printing (3DCP) include reducing construction time and costs, providing design freedom, and being environmentally friendly. This technology is expected to be effective in addressing the global house shortage. This review highlights the main 3DCP applications and four critical challenges. It is proposed to combine 3D concrete printing with Digital Twin (DT) technology to meet the challenges the 3DCP faces and improve quality and sustainability. This paper provides a critical review of research into the application of DT technology in 3DCP, categorize the applications and directions proposed according to different lifecycles, and explore the possibility of incorporating them into existing 3DCP systems. A comprehensive roadmap was proposed to detail how DT can be used at different lifecycle stages to optimize and address the four main challenges of 3DCP, providing directions and ideas for further research.

show abstract

Modelling of 3D concrete printing process: A perspective on material and structural simulations

Cited by 30 publications

References 118 publications

Optimizing the Three-Dimensional Multi-Objective of Feeder Bus Routes Considering the Timetable

Optimizing the Three-Dimensional Multi-Objective of Feeder Bus Routes Considering the Timetable

Developing a data-driven filament shape prediction model for 3D concrete printing

Digital Twin Applications in 3D Concrete Printing

Contact Info

Product

Resources

About