3D Parts Research Articles

The Use and Development of Artificial Intelligence in Architectural Design Processes

Artificial intelligence is widely used as an interactive technology in various professional disciplines. The widespread use of these technologies, which we benefit from in most areas of our lives, in the education sector will provide important developments in the field of education. The main purpose of this study is based on analysing the existing studies in which the use of artificial intelligence helps in architectural design processes. In the study, identification, screening, eligibility, inclusion and data analysis processes were carried out in three search engines such as Web of Science, ScienceDirect and ULAKBIM. While reporting the research, ‘Systematic Literature Review’ and ‘Preferred Reporting Items for Meta-Analysis’ protocols were followed and a total of 35 relevant articles were identified. In the research, three popular Artificial Intelligence applications used in architectural design processes were identified as Generative Adversarial Networks (GAN), Machine Learning and Data Mining. In addition, Systematic Literature Review (SLR) outputs show that most researchers are supported by artificial intelligence applications in architectural design processes. As a result of the research, it was determined that artificial intelligence is widely used in architectural design processes, however, it has positive effects in 3D and animation parts.

PhysFiT: Physical-aware 3D Shape Understanding for Finishing Incomplete Assembly

Understanding the part composition and structure of 3D shapes is crucial for a wide range of 3D applications, including 3D part assembly and 3D assembly completion. Compared to 3D part assembly, 3D assembly completion is more complicated which involves repairing broken or incomplete furniture that miss several parts with a toolkit. The primary challenge persists in how to reveal the potential part relations to infer the absent parts from multiple indistinguishable candidates with similar geometries, and complete for well-connected, structurally stable and aesthetically pleasing assemblies. This task necessitates not only specialized knowledge of part composition but, more importantly, an awareness of physical constraints, i.e. , connectivity, stability, and symmetry. Neglecting these constraints often results in assemblies that, although visually plausible, are impractical. To address this challenge, we propose PhysFiT, a physical-aware 3D shape understanding framework. This framework is built upon attention-based part relation modeling and incorporates connection modeling, simulation-free stability optimization and symmetric transformation consistency. We evaluate its efficacy on 3D part assembly and 3D assembly completion, a novel assembly task presented in this work. Extensive experiments demonstrate the effectiveness of PhysFiT in constructing geometrically sound and physically compliant assemblies.

Generalized SmartScan: An Intelligent LPBF Scan Sequence Optimization Approach for Reduced Residual Stress and Distortion in 3D Part Geometries

Abstract Laser powder bed fusion (LPBF) is an additive manufacturing technique that is gaining popularity for producing metallic parts in various industries. However, parts produced by LPBF are prone to residual stress, deformation, cracks and other quality defects due to uneven temperature distribution during the LPBF process. To address this issue, in prior work, the authors have proposed SmartScan, a method for determining laser scan sequence in LPBF using an intelligent (i.e., model-based and optimization-driven) approach, rather than using heuristics, and applied it to simple 2D geometries. This paper presents a generalized SmartScan methodology that is applicable to arbitrary 3D geometries. This is achieved by: (1) expanding the thermal model and optimization approach used in SmartScan to multiple layers; (2) enabling SmartScan to process shapes with arbitrary contours and infill patterns within each layer; (3) providing the optimization in SmartScan with a balance of exploration and exploitation to make it less myopic; and (4) improving SmartScan’s computational efficiency via model order reduction using singular value decomposition. Sample 3D test artifacts are simulated and printed using SmartScan in comparison with common heuristic scan sequences. Reductions of up to 92% in temperature inhomogeneity, 86% in residual stress, 24% in maximum deformation and 50% in geometric inaccuracy were observed using SmartScan. An approach for using SmartScan for printing complex 3D parts in practice, by integrating it as a plug-in to a commercial slicing software, was also demonstrated experimentally, along with its benefits in significantly improving printed part quality.

Towards Photocrosslinkable Lyotropic Blends of Organosolv Lignin and Hydroxypropyl Cellulose for 3D Printing by Direct Ink Writing.

Polymer blends containing up to 70% organosolv lignin content and lyotropic cellulose derivatives have been established as "lignin inks" for direct ink writing of fully biobased 3D parts. However, a fast-crosslinking mechanism is needed to improve throughput and design space. In this paper, UV-photocrosslinkable organosolv lignin/hydroxypropyl cellulose inks are formulated through doping with common photocrosslinkers. The most potent photocrosslinkers for neat hydroxypropyl cellulose, lignin and their blends are determined through a series of DOEs. Hydroxypropyl cellulose is significantly more amenable to photocrosslinking than organosolv lignin. The optimal photocrosslinkable ink formulations are printable and exhibit up to 70% gel content, although thermal post-curing remains essential. Chemical, thermal, and mechanical investigations of the photocrosslinked 3D parts evidence efficient crosslinking of HPC through its hydroxyl groups, while lignin appears internally plasticized and/or degraded during inefficient photocrosslinking. Despite this, photocrosslinkable inks exhibit improved tensile properties, shape flexibility, and fidelity. The heterogeneous crosslinking and residual creep highlight the need to further activate lignin for homogeneous photocrosslinking in order to fully exploit the potential of lignin inks in DIW.

Finite Element Analysis of Leaf Spring Fabricated Via Fused Deposition Modeling (FDM)

An introduction to fused deposition modeling, or 3D printing technology, will be given in this chapter. The basic idea of additive manufacturing and its underlying scientific theory will be presented at the outset of this chapter as a novel and emerging industrial technology. The parameters used to predict the melt deposition of polymers and their basic interactions with the structural component qualities will also be covered in this chapter. The chapter will provide a brief description of the quality features of FDM products concerning the process parameters. The additive manufacturing process will involve layering material to produce three-dimensional (3D) parts using a class of manufacturing technologies known as additive manufacturing (AM). This substance will include composite, metal, polymer, or concrete materials. A manufacturing process will need to have the following three main elements to be designated as an AM technique: making visual 3D models with computers and computer-aided design (CAD), utilizing a variety of CAD tools such as AutoCAD, SolidWorks, CATIA, and others. Some of these programs will be either closed- source or open-source. For additive manufacturing to be successful, an engineer or artist working with several computers will need to be proficient in using multiple operating systems. With these CAD tools and user experiences, it will be possible to produce a variety of complex 3D product models. The amount of material a 3D printer will take and the time it will require will be important factors influencing the additive manufacturing process.

Research and application of 3D spatial safety electronic fence technology based on beidou high-precision positioning in substation construction projects

Abstract In recent years, the Beidou Navigation Satellite System (BDS) has developed rapidly, achieving global coverage and being widely used in various fields. The high-precision positioning capability of the Beidou system provides strong technical support for a variety of application scenarios, especially in fields requiring high-accuracy location information, such as safety monitoring in substation engineering. Substations are critical components of the power system, and their operational safety is vital for the stable operation of the entire grid. However, due to the complexity of the equipment and harsh working environments in substation engineering, utilizing Beidou’s high-precision positioning capabilities can significantly enhance the safety management level of substation construction projects and reduce the occurrence of accidents. This paper primarily explores and investigates high-precision positioning-based three-dimensional (3D) spatial safety electronic fence technology for substation construction projects. The process begins with using laser radar to capture 3D scene information and extract key parts of the point cloud model. Comprehensive positioning sensors, integrating the Beidou Navigation Satellite System (BDS) and inertial navigation, are then installed on crane booms to achieve real-time monitoring of the boom’s posture. Finally, a software platform is established to calculate the real-time 3D spatial distance between the crane boom and surrounding sensitive facilities, ensuring the safety of large-scale construction machinery. Field test results validate the effectiveness of the proposed method.

Powder coarsening mechanisms of Ti-6Al-4 V with multiple build cycles in laser powder bed fusion

Laser powder bed fusion (LPBF) is an additive manufacturing process which can produce complex 3D parts from digital models. The performance of parts fabricated by LPBF is largely dependent on the characteristics of the powder feedstock, in particular, the particle size distribution. The coarsening of powder particles may limit the potential for reusing powder in further builds, as consistency in powder quality is crucial for ensuring consistent parts performance when using reused powder, especially in aerospace applications. However, there is a lack of systematic understanding regarding the causes and nature of powder coarsening in LPBF. In this work, the characteristics of powder samples from different locations in the build chamber during LPBF were studied to understand the particle size evolution and determine the origin of coarsening, which has not been previously reported. Meanwhile, powder coarsening was found to have a detrimental effect on the relative density and surface quality of as-built parts, highlighting the importance of exploring the mechanisms of powder coarsening and finding ways to control it in LPBF. The relationship between powder in key locations in the build chamber and its effect on powder coarsening has been established. Layer thickness is identified as a critical factor in causing powder coarsening due to the fine powder size characteristic in the powder bed. Spatter, in its various forms, plays a direct or indirect role in powder coarsening. Sintered powders resulting from spatter and the laser scanning borders of as-built parts were observed to contribute to the powder coarsening. Therefore, three main mechanisms (layer thickness, spatter, sintered powder) associated with the powder coarsening are therefore proposed. This work provides insight and potential solutions to control powder coarsening and maintain consistent parts performance.

Solar thermal cooking device for domestic cooking applications: Bridging sustainable development goals and innovation

Fossil fuels are vital in the cooking field rather than the automotive sector. Hence, solar cooking has been popularized in recent years due to the rising cost of cooking gas. However, implementing successful renewable energy for cooking in urban area is still challenging for industries. Hence, a solar thermic cooking device with a compact size suited for domestic cooking in urban area is proposed. Thus, the solar cooking device will be developed as a fully functional prototype with necessary supporting modules, depending on the heat transfer fluid (HTF) flow and heat transfer rate between fluids. The main objective is to represent various computational fluid dynamics (CFD) and thermal analysis results on different optimistic designs for a solar thermoelectric cooking device's heat exchanger and storage unit. The 3D part model of the modules has been developed using SOLIDWORKS 2019 software. CFD has also been carried out using the same workspace with an additional package called flow simulation to analyze the flow properties of heat transfer fluid at different rates when circulated in other modules.Moreover, the thermal behavior of the HTF concerning the heat transition between module surfaces is simulated using SOLIDWORKS flow simulation to evaluate the heat storage capacity and rate of heat transfer. The theoretical formulations for the modules are derived through thermodynamic equations concerning the materials and fluid involved in the unit. The thermal and CFD analysis is carried out for different optimistic 3D models based on thermal sustainability, and the results are compared with theoretical analysis, which is discussed in this paper.

Optical manipulation of ultrashort laser pulses for applications in challenging environments

Over the last few years, high throughput ultrashort-pulse laser sources have become increasingly affordable. This facilitated the emergence of many applications that require sub-micron precision material modification. Processes have been demonstrated in applications including micro-structuring semiconductor chips, manufacturing complex 3D parts or inscribing optical materials for data storage. Furthermore, recent progress in techniques for the optical manipulation of ultrashort laser pulses opened up new avenues in applications for challenging environments such as those involving high energy physics or particle beam radiotherapy. These applications require high-resolution 3D structures to be produced in radiation tolerant materials, to make particle sensors with the required sensitivity and resolution. For such processes, accurate spatial and temporal structuring and manipulating of optical parameters such as polarization, wavefront and intensity of laser beams, is essential. This paper presents recent results in advanced optical manipulation including the induction of helical or longitudinal fields at the focus. The resulting laser material coupling interactions are characterized and their suitability for making particle sensors from radiation hard materials considered.

Enhancing 3D Printing Copper-PLA Composite Fabrication via Fused Deposition Modeling through Statistical Process Parameter Study.

The rapid advancement of additive manufacturing (AM) technologies has provided new avenues for creating three-dimensional (3D) parts with intricate geometries. Fused Deposition Modeling (FDM) is a prominent technology in this domain, involving the layer-by-layer fabrication of objects by extruding a filament comprising a blend of polymer and metal powder. This study focuses on the FDM process using a filament of Copper-Polylactic Acid (Cu-PLA) composite, which capitalizes on the advantageous properties of copper (high electrical and thermal conductivity, corrosion resistance) combined with the easily processable thermoplastic PLA material. The research delves into the impact of FDM process parameters, specifically, infill percentage (IP), infill pattern (P), and layer thickness (LT) on the maximum failure load (N), percentage of elongation at break, and weight of Cu-PLA composite filament-based parts. The study employs the response surface method (RSM) with Design-Expert V11 software. The selected parameters include infill percentage at five levels (10, 20, 30, 40, and 50%), fill patterns at five levels (Grid, Triangle, Tri-Hexagonal, Cubic-Subdivision, and Lines), and layer thickness at five levels (0.1, 0.2, 0.3, 0.4, and 0.5 mm). Also, the optimal factor values were obtained. The findings highlight that layer thickness and infill percentage significantly influence the weight of the samples, with an observed increase as these parameters are raised. Additionally, an increase in layer thickness and infill percentage corresponds to a higher maximum failure load in the specimens. The peak maximum failure load (230 N) is achieved at a 0.5 mm layer thickness and Tri-Hexagonal pattern. As the infill percentage changes from 10% to 50%, the percentage of elongation at break decreases. The maximum percentage of elongation at break is attained with a 20% infill percentage, 0.2 mm layer thickness, and 0.5 Cubic-Subdivision pattern. Using a multi-objective response optimization, the layer thickness of 0.152 mm, an infill percentage of 32.909%, and a Grid infill pattern was found to be the best configuration.

Exploring the impact of epoxy coated 3D-Printed polymers on surface roughness and mechanical behavior: An experimental and numerical study

The present study used polymers such as PLA and ABS filaments for the 3D printing parts with varying layer thicknesses. The mechanical properties and surface finish of the as-printed and epoxy resin-coated samples were investigated. Noteworthy findings indicate that when the PLA material is printed at a layer thickness of 0.06 mm followed by no coating one can achieve superior tensile strength of approximately 39 MPa as compared to 20 MPa of ABS material. The ultimate tensile strength of the coated materials averaged approximately 15 MPa for both PLA and ABS. The surface roughness of PLA material printed with a 0.06 mm layer thickness showed a 95.13 % reduction after coating. Despite ABS samples being harder than PLA material, the layer thickness emerged as the most influential factor in enhancing the hardness. The dominance of lower layer thickness over other conditions is particularly evident in the modulus of elasticity. In addition to the experimental investigation, a non-linear structural analysis of the uniaxial tensile behaviour of the coated and uncoated 3D prints was also carried out. The fracture modes and deformation behaviours in numerical modelling and experimental results across various parametric conditions were found to be in good agreement. Specifically, the numerical results at lower loading conditions for a layer thickness of 0.06 mm PLA and ABS samples, in the uncoated conditions, mirrored the experimental outcomes.

Application of Numerical Modeling and Finite Element Analysis in Fused Filament Fabrication: A Review.

Additive manufacturing (AM) is not necessarily a new process but an advanced method for manufacturing complex three-dimensional (3D) parts. Among the several advantages of AM are the affordable cost, capability of building objects with complex structures for small-batch production, and raw material versatility. There are several sub-categories of AM, among which is fused filament fabrication (FFF), also commonly known as fused deposition modeling (FDM). FFF has been one of the most widely used additive manufacturing techniques due to its cost-efficiency, simplicity, and widespread availability. The FFF process is mainly used to create 3D parts made of thermoplastic polymers, and complex physical phenomena such as melt flow, heat transfer, solidification, crystallization, etc. are involved in the FFF process. Different techniques have been developed and employed to analyze these phenomena, including experimental, analytical, numerical, and finite element analysis (FEA). This study specifically aims to provide a comprehensive review of the developed numerical models and simulation tools used to analyze melt flow behavior, heat transfer, crystallization and solidification kinetics, structural analysis, and the material characterization of polymeric components in the FFF process. The strengths and weaknesses of these numerical models are discussed, simplifications and assumptions are highlighted, and an outlook on future work in the numerical modeling and FE simulation of FFF is provided.

A Multi-Objective Optimization Design for Enhancing Space Utilization and Minimizing Cutting Time in Nuclear Facility Component Decommissioning

According to the International Atomic Energy Agency’s requirements for the minimization of radioactive waste, nuclear facility components need to be cut into smaller blocks and packaged in waste containers during decommissioning. Therefore, it is important to increase the space utilization (SU) of the cut blocks in the containers while reducing the cutting time (CT). In engineering practice, increasing SU often leads to longer CTs, which poses a great challenge to improve the efficiency of the nuclear decommissioning process. To overcome this challenge and to determine the optimal operational parameters, this paper introduces a multi-objective optimization design method for cutting and packaging nuclear facility components. The goal is to increase SU while concurrently reducing CTs, ultimately minimizing the waste and reducing the decommissioning cost. First, we project the intricate three-dimensional (3D) irregular parts packing problem onto a two-dimensional plane to simplify the complexity inherent in 3D parts packing and to formulate a packing optimization model. Second, we employ the Morris method to perform global sensitivity analysis on critical parameters, including cutting angle, height, component radius, and plate thickness parameters, throughout the cutting process of nuclear facility components. This analysis produces global sensitivity indicators for each parameter, facilitating a precise assessment of the sensitivity values associated with different operational parameters. Finally, we formulate a multi-objective design optimization model for cutting and packing nuclear facility components that yields a series of alternative operating parameter solutions upon solving it. This methodology offers a resolution for the selection of optimal operational parameters in the decommissioning process of nuclear facility components, thereby attaining optimal outcomes in waste disposal and furnishing guidance for subsequent decommissioning activities.

A multi-modal and multi-stage fusion enhancement network for segmentation based on OCT and OCTA images

The accurate segmentation of retinal vessels (RV) and Foveal Avascular Zone (FAZ) is crucial for the retina health assessment. However, fusing OCT and OCTA images while projecting these 3D data for segmentation is a challenge. In this paper, we propose an Adaptive Projection and Multi-stage Fusion Enhancement Network for the segmentation of RV and FAZ, which consists of 3D projection, fusion enhancement, and 2D segmentation parts. We design a kernel adaptive unidirectional convolution to improve projection efficiency and a volume fusion module to capture semantic and spatial information accurately. Then we construct a Multi-stage Complementary Fusion Module and a Multi-modal Difference Fusion Module to enhance features by complementarity and differences in features. At last, we employ three U-Nets with a Feature Interaction Module for segmentation. Experiments show that our method achieves state-of-the-art performance with DICE, BACC, and JAC of 0.8996, 0.8181, 0.9421, 0.9395, 0.8923, and 0.9717 for RV and FAZ.

Sustainable optimization of micro-milling machining parameters considering reliability assessment

Micro-milling is a crucial machining technology used for complex and precise 3D parts and plays a crucial role in modern manufacturing. In this work, to comprehensively evaluate the safety, economic feasibility, and environmental friendliness of the micro-milling processing process, a sustainable optimization framework including reliability assessment is designed. Firstly, modeling and experimental measurements are conducted on sustainability evaluation standards such as tool life, machining process, machining surface quality, material removal rate, machining cost, and carbon emissions. Subsequently, the influence of physical information such as observation/measurement data and processing errors is analyzed, and a Bayesian update method is proposed and integrated with neural networks to precisely inversion the probability distribution of parameters within the optimization cycle under conditions of uncertainty. Finally, combined with the overall sustainability indicators, the multi-objective optimization process is refined through penalty functions and weighting methods, aiming to achieve the best balance between processing performance and sustainability. The simulation and experimental results have verified the superiority of the developed framework, and the present method provides valuable guidance for sustainable micromanufacturing.

High-performance PEEK composite materials research on 3D printing for neutron and photon radiation shielding

With the rapid advancement of nuclear energy technology, addressing technical challenges in the field of radiation shielding, particularly achieving lightweight and efficient shielding against neutron and multiple radiation types, remains a formidable task. To address the aforementioned issues, this study investigates the 3D printing performance of polyether ether ketone (PEEK) composite materials for shielding against both neutron and photon multibeam radiation. High-content 3D printing filament is developed, with simultaneous shielding capabilities against neutron and photon radiation. This research successfully accomplishes the high-density 3D printing of PEEK shielding composites with increased concentrations of boron carbide(B4C), tungsten(W), and both materials. The experimental results indicate that 3D printed specimens of B4C/W/PEEK, a neutron and photon shielding composite material, exhibit excellent mechanical properties. Importantly, the radiation shielding composite 3D function parts achieves effective shielding against muitibeam radiation and weight reduction compared to traditional radiation shielding materials.

Rapid volcanic ash entombment reveals the 3D anatomy of Cambrian trilobites.

Knowledge of Cambrian animal anatomy is limited by preservational processes that result in compaction, size bias, and incompleteness. We documented pristine three-dimensional (3D) anatomy of trilobites fossilized through rapid ash burial from a pyroclastic flow entering a shallow marine environment. Cambrian ellipsocephaloid trilobites from Morocco are articulated and undistorted, revealing exquisite details of the appendages and digestive system. Previously unknown anatomy includes a soft-tissue labrum attached to the hypostome, a slit-like mouth, and distinctive cephalic feeding appendages. Our findings resolve controversy over whether the trilobite hypostome is the labrum or incorporates it and establish crown-group euarthropod homologies in trilobites. This occurrence of moldic fossils with 3D soft parts highlights volcanic ash deposits in marine settings as an underexplored source for exceptionally preserved organisms.

Optimizing heterogeneous elastic material distributions on 3D models

Optimizing heterogeneous elastic material distribution on a 3D part to achieve desired deformation behavior is an important task in computer-aided design and additive manufacturing. This paper presents a solution to this problem, which involves interactive design, automatic deformation generation, and optimization of spatial distribution of heterogeneous elastic materials. Our method improves previous techniques in three aspects. First, we incorporates a geometric deformation-based interactive design into FEM-based optimization, which makes the solution less dependent of initial guesses of Young’s modulus values and it more likely to produce the target design even with sparse user input of displacements and forces at a limited set of mesh vertices. Second, we formulate the problem as an L2- or L0-optimization problem. The L2 formulation outputs smoothly varying heterogeneous material distribution that accommodates multiple functions within a single part. The L0 formulation achieves the computation of sparse material distribution in one step, which is beneficial for additive manufacturing with multi-material printers. Third, we utilize the adjoint method to derive formulae for efficiently computing the gradient of the objective functions, making it possible to quickly solve the optimization problem in the full-dimensional space of materials, which was previously infeasible. The experiments demonstrate the robustness and efficiency of our approach.

3D simulations of a neon burning convective shell in a massive star

ABSTRACT The treatment of convection remains a major weakness in the modelling of stellar evolution with one-dimensional (1D) codes. The ever-increasing computing power makes now possible to simulate in three-dimensional (3D) part of a star for a fraction of its life, allowing us to study the full complexity of convective zones with hydrodynamics codes. Here, we performed state-of-the-art hydrodynamics simulations of turbulence in a neon-burning convective zone, during the late stage of the life of a massive star. We produced a set of simulations varying the resolution of the computing domain (from 1283 to 10243 cells) and the efficiency of the nuclear reactions (by boosting the energy generation rate from nominal to a factor of 1000). We analysed our results by the mean of Fourier transform of the velocity field, and mean-field decomposition of the various transport equations. Our results are in line with previous studies, showing that the behaviour of the bulk of the convective zone is already well captured at a relatively low resolution (2563), while the details of the convective boundaries require higher resolutions. The different boosting factors used show how various quantities (velocity, buoyancy, abundances, and abundance variances) depend on the energy generation rate. We found that for low boosting factors, convective zones are well mixed, validating the approach usually used in 1D stellar evolution codes. However, when nuclear burning and turbulent transport occur on the same time-scale, a more sophisticated treatment would be needed. This is typically the case when shell mergers occur.

Conformal Low‐Temperature Molecular Layer Deposited Coatings as Interface Modifications to Support Ceramic Protective Films on Macroscopic Flexible Devices

Flexible devices often need a protective coating when operating in harmful environments, ranging from mild ambient conditions to a biologically active environment of the human body. The flexibility poses a problem for traditional encapsulation solutions, as those make the device bulky and limit functionality by applying an external casing. Alternatively, fully conformal encapsulation of a device of arbitrary shape can be realized with thin‐film encapsulation (TFE) without altering device dimensions. Yet, TFE is susceptible to fail under mechanical stresses, especially when a hard ceramic coating is applied on a polymer. Reliability of TFE can be enhanced by altering the elasticity of the hard and brittle thin films, by adding softer layers in between sample and barrier. Herein, molecular layer deposited (MLD) metal‐linked trioxysilylheptanoate (M‐TOSH) films are studied for coating of large devices to conformally and uniformly tune the interface between polymer and atomic‐layer‐deposited protective film. The results show that M‐TOSH process scales to large chambers; parameter optimization leads to superior film quality and lowers elastic modulus. Conformality, tested with home‐built macroscopic test device, finds the process suitable for 3D parts. Final testing reveals that ten cycles of MLD interlayer double the crack‐onset‐strain from 0.26% to 0.51%.