3D Design Research Articles

Three-Dimensional Multi-Morphology TPMS-Based Microchannel Design Method for Conformal Cooling in Injection Molding

Abstract Triply periodic minimal surface (TPMS) possesses diverse morphological characteristics, such as pore sizes, porosity, and structural types. Integrating TPMS-based microchannels into micro-cellular cooling structures is advantageous for designing and controlling fluid characteristics within mold cooling channels. However, it is still difficult to design multi-morphology TPMS-based cooling microchannels that conform to the external shapes of injection molds. This work proposes a 3D multi-morphology TPMS-based design method that transforms 3D constraints into a combination of 2D constraints. First, a beta growth algorithm based on closed-loop constraints is proposed to transition different morphologies smoothly on the plane. Subsequently, a transition optimization algorithm along the normal direction of the plane is introduced to smoothly transition multi-morphology TPMS-based microchannels in all directions. With this layered approach, multi-morphology microchannels can be obtained with first-order geometric continuity under complex shape constraints. Finally, several TPMS-based conformal cooling structures are designed for an automotive hood cover. The results of finite element simulations show that the cooling structures generated by the proposed method have a better cooling effect than the conformal channels. It can be concluded that multi-morphology TPMS-based structures perform better by contrast with conformal channels as the average temperature of the cooling surface decreases by 8.48 K, and the standard deviation of temperature distribution decreases by 24.65%.

Design and Analysis of a Liftfan for eVTOL Aircraft

Abstract Ducted liftfans provide greater hovering efficiency to eVTOL aircraft than open propellers of equal disk area. Liftfans are designed with minimised length to limit propulsor weight added and drag incurred during forward flight. Three challenges posed by the liftfan propulsor configuration are addressed in this paper. First, instead of a single-row propeller, liftfans require the design of a fully integrated stage. To maximise the hovering figure of merit, a non-dimensional measure of power consumption, the preliminary and 3D design variables of the rotor and splittered-diffuser stator rows are optimised simultaneously using 3D CFD. The resulting prototype liftfan design is validated through experimental testing. Second, despite efficiency improvements during hover, liftfans sustain additional inlet distortion and drag during forward flight due to their surrounding nacelles. A low-order model is developed to investigate the maximum range for different fan designs with varying diffuser area ratios and forward flight tilt angles. Design selections are validated using full annulus 3D CFD and experimental wind tunnel tests. Third, as the electric motors of liftfans are mounted within the hub, fan-driven active cooling is necessary to prevent overheating. The stagnation pressure losses incurred by cooling airflow must be minimised without impeding heat transfer. Low-order models are developed to predict motor heat transfer and loss and to guide the design of a mixed-flow cooling fan. Experimental testing and 3D CFD simulations confirm that the addition of forward sweep and adoption of a high blade count can reduce cooling fan losses.

Soft template-assisted design and synthesis of anisotropic 2D–3D CuInS2 with a controlled morphology and band gap: exploring photothermal interfacial water evaporation

Synthesizing I–III–VI2 ternary semiconductor chalcogenide nanostructures with precise control over their shape and bandgap is a major focus of current research.

PeerPub: A Device for Concurrent Operant Oral Self-Administration by Multiple Rats.

The social environment has long been recognized to play an important role in substance use, which is often modeled in rodents using operant conditioning. However, most operant chambers only accommodate one rodent at a time. We present PeerPub-a unique social operant chamber. PeerPub employs touch sensors to track the licking behavior on drinking spouts. When the number of licks meets a set reinforcement schedule, it dispenses a drop of solution with a fixed volume as a reward at the tip of the spout. A radio frequency identification (RFID) chip implanted in each rat's skull identifies it throughout the experiment. The system is managed by a Raspberry Pi computer. We evaluated PeerPub using Sprague Dawley rats in daily 1 h sessions, where supersac (a glucose and saccharin solution) was provided under a fixed-ratio five schedule. We discovered that male rats consumed more supersac in dual rat conditions compared with single rat conditions. These findings illustrate PeerPub's effectiveness in modeling the interaction between motivated behavior and social context. We expect devices like PeerPub will help highlight the role of social environments in substance use disorder phenotypes. All computer code, 3D design, and build instructions for PeerPub can be found at http://github.com/nijie321/PeerPub.

Design and Simulation of an Arduino-Based Password-Protected Door Locking System

In the contemporary world, where technology has advanced and with the incidents of thefts increasing, more traditional locking mechanisms such as a single lock and key are needed to offer better security. New reliable, intelligent, and smart door-locking mechanisms are necessary to improve the security and safety of residential or commercial properties. This paper aims to describe the design and implementation of an Arduino-based door lock system that includes an LCD for displaying the related information, a servo motor that controls the door's locking mechanism, and a keypad that will be used for user input. The suggested method is password protected since it asks the user for their password before accessing a door. When a user enters an erroneous password more than a predetermined number of times, the system also offers the option to reset the password and lock it out for a predetermined period. An additional feature of using the GSM module is to implement a function that notifies the owner of any unwanted access by sending a message to them when the door is locked after the number of erroneous passwords exceeds the set limit, thus alerting the owner of any unauthorized access. The suggested model's incorporation of these elements contributes to increased security. An online 3D design and simulation tool called Tinker cad is used to simulate the system initially. Thus, the suggested model of a password-enabled door-locking system improves security and offers a solution that is easily adjustable and user-friendly by integrating the hardware components and offering thorough simulation and testing through the software simulation using Tinkercad software.

Computational design of siRNA targeting <i>Homo sapiens</i> HER2 splice variant mRNA: A potential strategy for breast cancer intervention

This research focuses on an innovative approach utilizing in silico methods to design small interfering RNA (siRNA) targeting the HER2 splice variant mRNA in Homo sapiens. HER2 is known to be overexpressed in certain types of breast cancer, contributing to tumor progression and poor prognosis. By designing siRNA molecules that can specifically bind to and degrade HER2 mRNA, this study aims to reduce HER2 protein levels, thereby hindering the growth and spread of breast cancer cells. The in-silico design process involves identifying optimal siRNA sequences that maximize target specificity and minimize off-target effects, which is crucial for potential therapeutic applications. This approach represents a promising step towards personalized medicine in the treatment of breast cancer, offering a targeted strategy to combat this variant associated with aggressive disease. The methodology comprises the RNA computational tools used for the design, the selection criteria for siRNA candidates, and the potential implications of this research in a clinical setting. The resulting outcomes are 2D and 3D siRNA designs that could potentially silence HER2 mRNA through an in-silico approach. The leads were generated using a de novo modeling approach, with no existing template available in GenBank. Moreover, it is concluded that computational tools can generate sufficiently stable 2D and 3D RNA models that could be advanced for further molecular simulation studies. The benefit of this outcome is that it facilitates better preparation for wet laboratory experiments in siRNA assays, with future implementation in vivo and clinical trial settings.

Preserving conceptual design integrity: strategies for enhancing interoperability in architectural digital design workflows

AbstractThis research addresses the persistent challenges of data loss and inefficient workflow integration between 3D digital design tools (Rhinoceros) and Building Information Modelling (BIM) platforms (Revit) in the architecture, engineering, and construction (AEC) industries. The study investigates how design integrity can be preserved during the transition between these platforms, focusing on ensuring compatibility while maintaining the original design intent. The research aims to answer the question: How can design integrity be preserved when transitioning from 3D design tools to BIM platforms while ensuring seamless interoperability? Using an inductive bottom-up approach, empirical data were collected from 35 student projects over three years at The American University in Cairo. Observations were used to classify challenges encountered in transitioning from Rhinoceros to Revit, synthesising the results into evidence-based best practices. Surveys and statistical analyses were conducted on the participants’ (students’) responses to validate the findings from the analysis and observations of their digital workflow experiences. This study fills a gap in existing literature, which often overlooks the technical integration between 3D design tools and BIM platforms during the creative design phase. The research offers practical solutions for improving workflow integration, reducing data loss, and enhancing collaborative efficiency. The findings are expected to impact both professional practice and education, offering pathways to more efficient design transitions and equipping students with skills to navigate digital design challenges in future AEC projects.

Optimization and experimental validation of a mini wind turbine prototype with PMSG

Wind energy has emerged as a pivotal renewable energy source, offering a sustainable solution to the growing global energy demands and environmental challenges. This work presents the design, optimization, and experimental vali- dation of a mini horizontal-axis wind turbine equipped with a Permanent Magnet Synchronous Generator (PMSG). A comprehensive approach was adopted, beginning with a 3D design of the turbine’s structural components using Tinkercad software, followed by mathematical modeling and simulation of the PMSG using Python. The mathematical model incorporates advanced techniques, including the Park transformation and equations of electromagnetic and mechanical dynamics, to ensure accurate predictions of the generator’s performance. The turbine prototype was fabricated, and a custom-designed wattmeter utilizing Arduino technology was developed to facilitate performance characterization. Experimental tests were conducted under controlled conditions to evaluate the electrical output of the wind turbine. The results were compared with the theoretical simulations, revealing a satisfactory correlation. However, minor deviations were identified, attributed to losses and limitations in the prototype’s physical components. This study underscores the feasibility and effectiveness of employing small-scale wind turbines with PMSGs for sustainable energy applications. The insights derived from this work provide a foundation for further opti- mization in terms of design, material selection, and integration with energy storage systems. Future prospects include enhancing the magnetic flux density of the generator and exploring hybrid renewable systems for improved efficiency.

Applying Design Thinking to Teach Physics and Mathematics: A Case Study on Building a Parachute and Analyzing Its Properties

Eleven high school students participated in a one-week STEM summer camp focused on designing and building parachutes to deliver fragile objects safely. Using the Engineering Design Process (EDP) as a framework, students explored how canopy size affects performance. They applied physics concepts such as terminal velocity, forces, and acceleration, alongside mathematical skills like diagram interpretation. The program incorporated innovative technologies, including 3D design and printing tools and the BBC micro:bit microcontroller. Students followed the EDP steps—designing, building, testing, and refining prototypes—while also discussing the nature of science and distinguishing it from engineering practices. The camp successfully met its objectives: students enhanced their understanding of physics concepts, grasped key aspects of the nature of science, and demonstrated the ability to follow the EDP. They designed and built two parachutes, collected and analyzed data from test falls, and drew meaningful conclusions. This study highlights the potential of integrating engineering, physics, mathematics, and the nature of science into STEM education. The findings suggest that guided use of the EDP and modern technologies can improve students' scientific knowledge and problem-solving skills, fostering a deeper engagement with STEM concepts.

New dynamics performance for established dark solitons in polariton condensate

New diverse enormous soliton solutions to the Gross–Pitaevskii equation, which describes the dynamics of two dark solitons in a polarization condensate under non-resonant pumping, have been constructed for the first time by using two different schemes. The two schemes utilized are the generalized Kudryashov scheme and the (G’/G)-expansion scheme. Throughout these two suggested schemes we construct new diverse forms solutions that include dark, bright-shaped soliton solutions, combined bright-shaped, dark-shaped soliton solutions, hyperbolic function soliton solutions, singular-shaped soliton solutions and other rational soliton solutions. The two 2D and 3D figure designs have been configured using the Mathematica program. In addition, the Haar wavelet numerical scheme has been applied to construct the identical numerical behavior for all soliton solutions achieved by the two suggested schemes to show the existing similarity between the soliton solutions and numerical solutions.

Fixed Full-Arch Implant-Supported Restorations: Techniques Review and Proposal for Improvement.

Full-arch zirconia restorations on implants have gained popularity due to zirconia's strength and aesthetics, yet they are still associated with challenges like structural fractures, peri-implant complications, and design misfits. Advances in CAD/CAM and digital workflows offer potential improvements, but a technique that consistently addresses these issues in fixed, full-arch, implant-supported prostheses is needed. This novel technique integrates a facially and prosthetically driven treatment approach, which is divided into three phases: data acquisition, restoration design, and manufacturing/delivery. Digital tools, including intraoral scanning and photogrammetry, facilitate accurate implant positioning, while 3D design software enables functional and aesthetic validation before final milling. A dual software approach is used to reverse engineer a titanium bar from the final restoration design, ensuring a superior outcome to other protocols. The restoration incorporates a zirconia-titanium hybrid structure, optimizing strength, flexibility, and weight. The proposed workflow enhances restoration precision and predictability through a prosthetically driven treatment plan, by ensuring passivity and aligning with biological and mechanical principles to promote long-term stability. By starting with the proposed restoration design and reverse engineering the bar, while also allowing for flexibility in material and component choices, this technique accommodates both patient needs and financial considerations. This approach demonstrates potential for improving patient outcomes in full-arch implant restorations by minimizing complications associated with traditional methods. Further research is recommended to validate the technique's efficacy and broaden its clinical applications.

LLM4CAD: Multimodal Large Language Models for Three-Dimensional Computer-Aided Design Generation

Abstract The evolution of multimodal large language models (LLMs) capable of processing diverse input modalities (e.g., text and images) holds new prospects for their application in engineering design, such as the generation of 3D computer-aided design (CAD) models. However, little is known about the ability of multimodal LLMs to generate 3D design objects, and there is a lack of quantitative assessment. In this study, we develop an approach to enable LLMs to generate 3D CAD models (i.e., LLM4CAD) and perform experiments to evaluate their efficacy where GPT-4 and GPT-4V were employed as examples. To address the challenge of data scarcity for multimodal LLM studies, we created a data synthesis pipeline to generate CAD models, sketches, and image data of typical mechanical components (e.g., gears and springs) and collect their natural language descriptions with dimensional information using Amazon Mechanical Turk. We positioned the CAD program (programming script for CAD design) as a bridge, facilitating the conversion of LLMs’ textual output into tangible CAD design objects. We focus on two critical capabilities: the generation of syntactically correct CAD programs (Cap1) and the accuracy of the parsed 3D shapes (Cap2) quantified by intersection over union. The results show that both GPT-4 and GPT-4V demonstrate great potential in 3D CAD generation by just leveraging their zero-shot learning ability. Specifically, on average, GPT-4V outperforms when processing only text-based input, exceeding the results obtained using multimodal inputs, such as text with image, for Cap 1 and Cap 2. However, when examining category-specific results of mechanical components, the prominence of multimodal inputs is increasingly evident for more complex geometries (e.g., springs and gears) in both Cap 1 and Cap 2. The potential of multimodal LLMs to improve 3D CAD generation is clear, but their application must be carefully calibrated to the complexity of the target CAD models to be generated.

Artificial intelligence applications in smile design dentistry: A scoping review.

Artificial intelligence (AI) applications are growing in smile design and aesthetic procedures. The current expansion and performance of AI models in digital smile design applications have not yet been systematically documented and analyzed. The purpose of this review was to assess the performance of AI models in smile design, assess the criteria of points of reference using AI analysis, and assess different AI software performance. An electronic review was completed in five databases: MEDLINE/PubMed, EMBASE, World of Science, Cochrane, and Scopus. Studies that developed AI models for smile design were included. The search strategy included articles published until November 1, 2024. Two investigators independently evaluated the quality of the studies by applying the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Quasi-Experimental Studies and Textual Evidence: Expert Opinion Results. The search resulted in 2653 articles. A total of 2649 were excluded according to the exclusion criteria after reading the title, abstract, and/or full-text review. Four articles published between 2023 and 2024 were included in the present investigation. Two articles compared 2D and 3D points while one article compared the outcome of satisfaction between dentists and patients, and the last article emphasized the ethical components of using AI. The results of the studies reviewed in this paper suggest that AI-generated smile designs are not significantly different from manually created designs in terms of esthetic perception. 3D designs are more accurate than 2D designs and offer more advantages. More articles are needed in the field of AI and smile design.

Enhancing Assessment and Feedback in Game Design Programs

The integration of generative AI tools in game design education offers promising ways to streamline the grading, assessment, and feedback processes that are typically labor-intensive. In game design programs, faculty often deal with varied file formats, including 3D models, executable prototypes, videos, and complex game design documents. Traditional methods of assessment and feedback, primarily text-based, struggle to provide timely and actionable insights for students. Furthermore, only a small percentage of top students consistently review and apply feedback, leading to inefficiencies. This article explores how generative AI tools can augment these processes by automating aspects of grading, generating more personalized and meaningful feedback, and addressing the time-intensive nature of reviewing diverse file formats. Key strategies are discussed, including the use of rubrics tailored for AI-based assessment, automated prompts for narrative-driven assignments, and the application of AI in reviewing complex project builds. The objective is to create more time for faculty to engage in live mentoring and hands-on learning activities, which research shows to be more effective. Practical examples of various game design assignments, including build reviews and document evaluations, are provided to illustrate these new approaches. This shift promises to enhance student engagement and improve learning outcomes.

Advancements in Dental Bioreactor Design: A Comprehensive Approach for Application in Dentistry.

The protocol introduces a novel multi-chamber bioreactor tailored for ex-vivo cell culture in dentistry research, emulating the 3D dental environment to propel research in dental applications. Constructed primarily from a polymeric material with a sophisticated 3D design, the bioreactor securely holds teeth structures within sealed chambers, enabling controlled perfusion of culture medium crucial for cell growth through a singular entry and exit point. An integrated electronic system manages flow and pressure, ensuring precise control over environmental conditions. This technology facilitates cell cultivation under conditions closely resembling natural tooth microenvironments, offering opportunities for varied studies from understanding cellular behavior in dental contexts to targeted therapy development. The bioreactor's amalgamation of polymeric components, 3D design, and electronic controls enhances adaptability and accuracy, rendering it a valuable asset in dental research. The report comprehensively delineates the bioreactor's design, operations, and potential applications, showcasing its significant contributions to dental research and regenerative medicine. By amalgamating advanced technologies, this bioreactor emerges as a pivotal tool for investigating cellular processes within dental structures, paving the way for scientific exploration and therapeutic advancements.

Topology optimization for 3D fluid diode design considering wall-connected structures

This paper proposes a density-based topology optimization method for the three-dimensional design of fluid diodes considering wall-connected structures based on the fictitious physical modeling approach. The optimum design problem of fluid diodes is formulated as maximizing the energy dissipation in the reverse flow subject to the upper bound constraint of the energy dissipation in the forward flow. A fictitious physical model and a geometric constraint are constructed to detect and restrict the “floating” solid domains, which are not connected to the outer boundaries. The sensitivities of cost functions are derived and computed based on the continuous adjoint method. The finite volume method is employed to discretize the governing and adjoint equations to mitigate the huge computational costs of three-dimensional fluid analysis. Numerical investigations are presented to validate the fictitious physical model and the geometric constraint for excluding “floating” islands. Finally, topology optimization for fluid diodes with and without the geometric constraint is performed, and the result demonstrates that the proposed method is capable of generating fluid diodes with wall connectivity, while maintaining a good functional performance.

PROSTHESIS REPAIR OF ORAL IMPLANTS BASED ON ARTIFICIAL INTELLIGENC`E FINITE ELEMENT ANALYSIS

Dentists often suggest dental implants to replace missing teeth; nevertheless, mechanical issues can develop with these implants, which could lead to prosthesis replacement or repairs. When investigating implant systems' mechanical characteristics and stress distribution, finite element analysis (FEA) is a popular computational tool. In biomechanical investigations, this strategy is widely used. However, traditional FEA methods can be tedious and require expert expertise for accurate simulation and translation of results. To automate and simplify the process of mending oral implant prostheses, the article suggests a new framework called AI-FEA. The three primary parts that make up the suggested AI-FEA framework are 1. An AI-powered model creation module that utilizes data from medical imaging to autonomously construct 3D finite element designs that are unique to each patient. Utilizing deep learning approaches, this module segments and reconstructs three-dimensional geometries from computed tomography (CT) or cone-beam CT data using material properties and boundary conditions. 2. A FEA solver that runs simulations to test the way the implant system handles different loads. This component uses state-of-the-art numerical methods to model the implant and bone interface and determine stress distributions. 3. An AI-based decision support system that takes all that data and recommends the best way to fix the prosthesis. Combining FEA findings with patient-specific variables, this decision support system uses machine learning algorithms educated on an extensive dataset of implant failure instances and repair results to provide the optimal repair strategy. For patients experiencing issues with oral implants, the suggested AI-FEA framework might mean huge time and skill savings in prosthesis repair planning, leading to better, more individualized care.

A lattice-mechanical metamaterial with tunable two-step deformation, tunable stiffness, tunable energy absorption and programmable properties

Abstract Mechanical metamaterials have attracted much attention in recent years because of excellent properties. However, most mechanical metamaterials have only a relatively fixed and single deformation mode. Although some multi-step deformation metamaterials have been proposed, their rich static and dynamic mechanical properties have yet to be studied in depth. Therefore, a lattice-mechanical metamaterial is introduced in this study. Under vertical compression, different unit cells under the same architecture can achieve two or three steps of deformation, respectively. Metamaterials built from these unit cells can also achieve the same properties. These properties can exist in multiple directions and are not affected by the number of unit cells. In addition, this metamaterial not only has adjustable two-step deformation, adjustable stiffness, and adjustable energy absorption properties but it can also be spatially programmed by changing geometric parameters and tessellation. Finally, a 3D design version of the metamaterial is provided, and its conceptual application is briefly demonstrated. The developed metamaterial can achieve more static and dynamic mechanical properties while taking into account two-step deformation. This can provide richer content for the development of mechanical metamaterials and also provide new perspectives for the application of energy absorbers, aerospace, and industrial products.

Application of BIM in Modeling Concrete Retaining Walls

During the hydraulic design phase, challenges often arise, such as poor coordination between different disciplines and ineffective information transfer. These issues can lead to errors in the design process and unreasonable structural designs. As the complexity of engineering projects continues to increase, traditional 2D design methods can no longer meet current demands. As a result, Building Information Modeling (BIM) technology has been introduced, shifting the design approach to 3D modeling. This transition has significantly improved design accuracy and construction efficiency. To further optimize this process, a user interface interaction system based on C# language and the Revit API was developed. Through this system, we successfully implemented the 3D automatic modeling of retaining wall components and a reinforcement plugin. These tools have greatly saved time on repetitive tasks for designers, improving work efficiency. At the same time, they have advanced the informatization of hydraulic concrete structure construction, making the construction process more efficient, precise, and controllable. The 3D deepening design can accurately express the geometric characteristics of the structure, enhancing precision and accelerating the informatization development of hydraulic concrete structure construction.

Enhancing metal halide perovskite LED performance by minimizing ion migration through the design of a mixed 2D(RP+DJ)/3D active layer structure

Low dimensional perovskite has attracted much research attention in recent years due to its unique quantum well structure and enhanced stability. Although quasi-2D perovskites show great potential for light-emitting diodes due to their impressive performance, there are still challenges in achieving uniform n-phases and stable internal crystal structures in films. These inconsistencies can lead to reduced performance in LED devices. The fabrication of 2D/3D mixed structures has shown great potential for achieving efficient energy transfer from high band gap to low band gap and stable LEDs. In this work, the effect of 2D perovskite as an additive on the morphological, optical and optoelectronic properties of 3D MAPbBr3 perovskite was investigated. The 2D/3D mixed structure with 2D Ruddlesden-Popper (RP) phase and Dion-Jacobson (DJ) phase containing different concentrations of (OA)2PbBr4 and (BDA)PbBr4 perovskites was investigated. The effect of concentration on the crystal structure, quality and optical properties of perovskite films was also studied. Furthermore, we have mixed RP and DJ phases to preparing mixed phase 2D perovskite. The optimal concentrations of the three phases of 2D/3D mixed perovskite structures (x=20 %) were determined based on their PLQY and used as the active layer in the fabrication of LEDs. The mixture of 2D and 3D, led to a reduction in holes, defects and a subsequent increase in PLQY. The LEDs based on 2D(RP+DJ)/3D mixed perovskite, exhibited remarkable stability, with its luminance decreasing from 4639 cdm−2 to 3197 cdm−2 over a period of 15 days. This represents a 68 % retention of its initial brightness. The results show the significant reduction in hysteresis for the 2D/3D perovskite device with a mixed phase cation (RP+DJ). This indicates that the mixed cation approach is highly effective in suppressing ion migration within the perovskite layer.