Topology Design Research Articles

A proposition to teach engineering projects using Problem-based Learning (PBL) concepts

This article shows the design of a mechanical engineering project using problem-based learning concepts. The work shows the complexity of the teaching-learning process of a complex problem such as developing, simulating, and testing a prototype of a piezoresistive pressure sensor. This type of problem is typical in theoretical-practical classes involving different concepts learned during an undergraduate course. The cognitive structure may or may not be influenced by the presentation of ideas and methods for organizing the content and executing the desired project. Using a pressure sensor project made it possible to develop the concepts of learning models by applying the idea of project-based learning (PBL). The main results obtained were the product design topology, operating concepts of a sensor device, computer-aided design projects, analysis of simulation results and assembly, and mechanical prototyping concepts, involving different materials for machining and product encapsulation.

Taming Connectedness in Machine-Learning-Based Topology Optimization with Connectivity Graphs

Despite the remarkable advancements in machine learning (ML) techniques for topology optimization, the predicted solutions often overlook the necessary structural connectivity required to meet the load-carrying demands of the resulting designs. Consequently, these predicted solutions exhibit subpar structural performance because disconnected components are unable to bear loads effectively and significantly compromise the manufacturability of the designs.In this paper, we propose an approach to enhance the topological accuracy of ML-based topology optimization methods by employing a predicted dual connectivity graph. We show that the tangency graph of the Maximal Disjoint Ball Decomposition (MDBD), which accurately captures the topology of the optimal design, can be used in conjunction with a point transformer network to improve the connectivity of the design predicted by Generative Adversarial Networks and Convolutional Neural Networks. Our experiments show that the proposed method can significantly improve the connectivity of the final predicted structures. Specifically, in our experiments the error in the number of disconnected components was reduced by a factor of 4 or more without any loss of accuracy. We demonstrate the flexibility of our approach by presenting examples including various boundary conditions (both seen and unseen), domain resolutions, and initial design domains. Importantly, our method can seamlessly integrate with other existing deep learning-based optimization algorithms, utilize training datasets with models using any valid geometric representations, and naturally extend to three-dimensional applications.

Ultrabroadband (DC–80 GHz) RF MEMS DC/capacitive load shunt switch

AbstractThis study presents the design and fabrication of a novel direct current (DC)/capacitive radio frequency (RF) Micro‐Electro‐Mechanical Systems (MEMS) switch in the ultrabroadband range from DC to 80 GHz. This proposed RF MEMS switch consists of two arms, with one arm providing a DC loading state (), whereas the second arm provides a capacitive loading state () to the ground when pull‐in voltage is applied. Insertion loss less than 1.85 dB and return loss better than 10 dB are achieved in the OFF state () from DC to 80 GHz (no pull‐in voltage is applied). Due to the novel design topology, this switch can act as a DC‐only switch (0–17 GHz) that provides isolation better than 25 dB during the state. A capacitive‐only switch (48–80 GHz) provides isolation better than 17 dB. This proposed structure can act as either DC(S1) or a capacitive () switch (17–48 GHz) and provides isolation better than 10 dB in either state. This proposed switch finds its best application in reconfigurable circuits like phase shifters due to switching between DC and capacitive loading during the On state from 17 to 48 GHz. The proposed switch's measured pull‐in and lift‐off voltages are 3.5 and 2.85 V, respectively.

A topology optimization framework for 3D phononic crystals via the method of successive iteration of analysis and design

Topology optimization has become a useful tool for designing Phononic Crystals (PnCs) to achieve desired elastic wave propagation properties. However, topological design of three-dimensional (3D) PnCs remains a significant challenge due to extremely high computational cost required for the repeated solution of the nested double-loop problem of design optimization and eigenvalue analysis to determine the band structure during the optimization iteration process. This paper presents a more efficient topology optimization method based on the concept of successive iteration of analysis and design. The method employs a sequential approximation of the eigenpairs through an inverse iteration-like procedure to avoid solving the expensive eigenvalue problems in each design iteration. To further improve the efficiency of the design iteration, the eigenmodes of the intermediate PnCs designs are first computed on a relatively coarse finite element mesh. Then they are mapped onto the fine mesh and used as the initial trial eigenmodes in the eigenpair analysis and design sensitivity analysis. The high efficiency of the proposed method, as compared with conventional nested double-loop optimization approaches, is demonstrated by 3D numerical examples with over one million degrees of freedom. It is shown that this approach can achieve simultaneous convergence of the eigenvectors along with the design evolution of the unit cell, therefore substantially reduces the computational burden for high-resolution topological design of 3D PnCs.

From Linear to Nets: Multiconfiguration Polymer Structure Generation with PolyFlin.

Molecular modeling and simulations are essential tools in polymer science and engineering, enabling researchers to predict and understand the properties of macromolecules, including their structure, dynamics, thermodynamics, and overall material characteristics. However, one of the key challenges in polymer simulation and modeling lies in the initial topology design, as existing programs often lack the capability to generate all types of polymer forms. In this study, we present PolyFlin, a powerful Python module that addresses this limitation by allowing the generation of a wide range of polymer structures, from simple homopolymers to complex copolymers, including grafts, cyclic, star, dendrimers, and nets. PolyFlin offers a versatile and efficient tool for exploring and creating diverse polymer architectures, facilitating advancements in various fields that require precise polymer modeling and simulation.

Hybrid Cross-Linking to Construct Functional Elastomers.

ConspectusElastomers have been extensively used in diverse industrial sectors such as footwear, seals, tires, and cable jacketing and have attracted more and more attention in emerging fields such as regenerative medicine, soft robotics, and stretchable electronics. Global consumption of natural and synthetic elastomers amounted to nearly 27 million metric tons in 2020. In addition, to further enhance the common properties of elastomers, it is highly desired to endow elastomers with functionalities such as reprocessability, biomimetic mechanical properties, self-healing ability, bioactivity, and electrical conductivity, which will significantly broaden their applications. The covalent or noncovalent cross-linked structure is the essential factor for the elasticity of elastomers. Traditional elastomers usually comprise a single type of cross-linked molecular network, for which it is difficult to modulate the properties and introduce functionalities. Inspired by the simultaneous existence of multiple cross-linked structures in proteins, researchers have employed a hybrid cross-linking strategy to construct elastomers. Various noncovalent interactions (e.g., hydrogen bonds, metal-ligand coordination, ionic interactions, and chain folding) and dynamic covalent bonds (e.g., disulfide bonds, oxime-urethane bonds, and urea bonds) have been integrated in elastomers. Accordingly, the properties and functionalities of elastomers can be tuned by regulating the types, ratios, and distributions of cross-links. The hybrid cross-linking strategy provides a versatile and effective way to construct diverse functional elastomers for broad applications in various important fields.In this Account, we present our recent progress on functional elastomers constructed by a hybrid cross-linking strategy, including their design, preparation, properties, and diverse applications. First, we provide a brief introduction of the basic concept of functional elastomers and outline general strategies and mechanics for functional elastomers constructed by hybrid cross-linking. Then, we classify hybrid cross-linked elastomers by their design strategies, including multiple cross-linking, topological design, chemical coupling, and multiple networks. The relationships between the functionalities and hybrid cross-linked structures are summarized. At the same time, we also introduce diverse applications of these hybrid cross-linked elastomers in biomedicine, flexible electronics, soft robotics, 3D printing, and so on. Finally, we discuss our perspective on open challenges and future development trends of this rapidly evolving field. This Account highlighting the diverse hybrid cross-linked elastomers not only provides insights into strategies for elastomer functionalization but also provides new ideas for material design and inspires a variety of new applications.

Topological Design and Synthesis of High-Spin Aza-triangulenes without Jahn-Teller Distortions.

The atomic doping of open-shell nanographenes enables precise tuning of their electronic and magnetic states, which is crucial for their promising potential applications in optoelectronics and spintronics. Among this intriguing class of molecules, triangulenes stand out with their size-dependent electronic properties and spin states, which can also be influenced by the presence of dopant atoms and functional groups. However, the occurrence of Jahn-Teller distortions in such systems can have a crucial impact on their total spin and requires further theoretical and experimental investigation. In this study, we examine the nitrogen-doped aza-triangulene series via a combination of density functional theory and on-surface synthesis. We identify a general trend in the calculated spin states of aza-[n]triangulenes of various sizes, separating them into two symmetry classes, one of which features molecules that are predicted to undergo Jahn-Teller distortions that reduce their symmetry and thus their total spin. We link this behavior to the location of the central nitrogen atom relative to the two underlying carbon sublattices of the molecules. Consequently, our findings reveal that neutral centrally doped aza-triangulenes have one less radical than their undoped counterparts, irrespective of their predicted symmetry. We follow this by demonstrating the on-surface synthesis of π-extended aza-[5]triangulene, a large member of the higher symmetry class without Jahn-Teller distortions, via a simple one-step annealing process on Cu(111) and Au(111). Using scanning probe microscopy and spectroscopy combined with theoretical calculations, we prove that the molecule is positively charged on the Au(111) substrate, with a high-spin quintet state of S = 2, the same total spin as undoped neutral [5]triangulene. Our study uncovers the correlation between the dopant position and the radical nature of high-spin nanographenes, providing a strategy for the design and development of these nanographenes for various applications.

Multi-material isogeometric topology optimization in multiple NURBS patches

In design optimization of structures, design domains are often described by multiple non-uniform rational B-spline (NURBS) patches. To perform multi-material topological design in such design domains, an effective Nitsche-based multi-material isogeometric topology optimization (ITO) method is proposed in this paper. Specifically, the Nitsche's method is utilized to effectively couple the interfaces between adjacent NURBS patches. In order to preserve the coercivity of the bilinear form, the stabilization parameters are estimated locally according to the element size. Meanwhile, the discrete material optimization (DMO) approach is employed to describe the mixing of candidate materials. Analytical computation of sensitivities for coupled elements is developed as well. The effectiveness of the proposed method is demonstrated via several 2D and 3D numerical examples, where the design domains are constituted by conforming and non-conforming NURBS patches, respectively.

Design and Control of a Photovoltaic Distribution System Based on Modular Buck-Boost Converters

The main contribution of this research is the design of a series hybrid topology for a photovoltaic distribution system using Buck-Boost converter modules. This design incorporates a maximum power point tracking (MPPT) algorithm based on the perturb and observe method, linear PI controllers, and an energy management algorithm. The controllers' design is validated through simulation using PSIM and SISOTOOL/MATLAB. This work aims to achieve active power-sharing in the AC grid through a control loop implemented with a three-phase inverter. The validation of the topology and controller design demonstrates tracking and robustness in four test scenarios for the state variables in microgrids: constant and variable irradiance conditions, auxiliary storage device (ASD) protection and control loops, and power-sharing with the AC grid, while considering the DC system dynamics.

A topological gap waveguide based on unidirectional locking of pseudo-spins

Photonic topological insulators have been widely studied due to the robustness of energy transport via supported edge modes immune to structural disorder. In this work, a topological gap waveguide is constructed by introducing line defect into a topological photonic crystal structure and combining it with a gap waveguide structure, the design of which, therefore, combines the advantages of both topological and gap waveguides. Not only does it give high transmission efficiency but it also enables high robustness for energy transmission under structural defects and sharp bends. Our proposed topological waveguide design can be implemented with conventional semiconductor technology and integrated into optical circuits for communication systems.

High‐performance healable plastics: Focusing topological structure design based on constitutional dynamic chemistry

AbstractOver the past three decades, significant efforts have been dedicated to developing polymeric materials with exciting healable ability; however, stiff and healable plastics with high glass transition temperatures (Tg) have received relatively less attention compared to their soft counterparts such as gels and elastomers due to the inherent trade‐off between mechanical robustness and dynamics. High‐performance plastics are irreplaceable in the fields of engineering and industry, making it a challenging yet urgent task to confer them with desired healable properties whilst maintaining high mechanical strength. In this review, we first present recent advances in the field of high‐performance healable plastics based on constitutional dynamic chemistry, from the perspective of different topological structures including linear‐, branched‐ and network types. Meanwhile, we also elaborate on various toughening strategies for existing healable plastics, mainly centered around molecular to micrometer scale modifications. Moreover, we also provide a detailed exposition of previous reports on the autonomously room‐temperature self‐healing plastics, which represent a groundbreaking development in the realm of advanced healable plastics. Eventually, we emphasize diverse functionalized healable plastics to illustrate their potential for practical implementation, and propose an outlook on the future development of healable plastics.image

Structural and topological design of conformal bilayered scaffolds for bone tissue engineering

A fundamental outcome of bone tissue engineering is the regeneration of bone defects presenting large dimensions. A promising solution in biomedical practice is the implantation of biomimetic scaffolds, i.e. porous structures mimicking the natural shapes of healthy bone tissues, which are colonized by mesenchymal stem cells and that support the growth of the regenerating tissues, until the complete healing process is realized. This work presented a workflow for the geometrical modeling and the mechanical design of beam-based, bilayered, and conformal scaffolds, mimicking the human cortico-cancellous bone structure for filling a large dimension defect in the mandibular bone of an injured patient. An isotropic Voronoi topology built on a refined point set generated by a high-quality meshing algorithm was adopted for lattice generation, which led to an open-cell architecture characterized by full connectivity and uniform cell size. Such geometrical and structural features represent crucially important requirements for maximizing the osteointegration and the vascularization of the implanted scaffold. An irregular scaffold was modelled, including a cortical and a sponge layer. The beam radii of both layers were determined by matching the elastic properties of the corresponding bone tissues, thus minimizing the stress shielding effects. Interestingly, several scaffold properties deriving from the proposed procedure, such as the porosity and the pore size, were in good agreement with those reported in the literature.

Topological and functional vulnerability analysis and mitigation for single-source heating networks based on tree models

The performance of district heating networks (DHNs) to provide heat to users under different operation conditions depends largely on their topology. It is of great significance to analyze the topological and functional characteristics of DHNs and propose design and reconstruction guidelines for vulnerability reduction. This study proposes binary tree and generalized tree models of DHNs, from which their topological characteristics can be quickly identified, and the functional analysis can be facilitated. Then, we propose a topology design and reconstruction framework for DHNs based on vulnerability assessment. Various characteristics of the branched and looped structure are studied in their influence on system vulnerability, based on which several design criteria for single-source DHNs are deduced. Specifically, single-source branched DHNs shall be designed as symmetrical to avoid long pipelines bearing enormous heat loads. When transforming the branched DHNs into looped DHNs, priority should be given to adding cotrees between the intermediate nodes of high importance, and the diameters of looped pipes should be enlarged. Finally, a detailed case study on a real-world single-source DHN demonstrates the effectiveness of the proposed approaches and design criteria.

Single‐stage triple‐output Cuk power factor correction converter

SummaryTraditional multiple‐output AC‐DC power supply with power factor correction (PFC) function usually employs a two‐stage cascaded topology that is composed of prestage PFC converter and N independent poststage DC‐DC converters to achieve PFC and voltage or current regulation of N outputs. Hence, the conventional two‐stage cascaded multiple‐output AC‐DC power supply needs N + 1 magnetic components as power inductors or transformers and N + 1 controllers, which increases the cost and size of the multioutput converters. The conventional multiple‐string AC‐DC LED driving circuits usually employ a two‐stage topology to realize PFC and independent current regulation of each LED string. To address the issue of complexity, high cost, and large size of the two‐stage multistring LED driving circuit, a single‐stage triple‐output Cuk PFC converter is proposed by cascading boost converter and single‐inductor triple‐output buck converter with sharing main power switch in this paper. The topology operation principle, control strategy, design consideration, and operation characteristics of the proposed circuit are investigated in detail. With the switch sharing and inductor multiplexing technologies at the same time, the proposed converter utilizes only single‐stage converter to achieve PFC function, independent regulation of triple‐channel output current, and flicker‐free with low twice line frequency LED current ripple. The proposed converter is verified by a 50‐W experimental prototype of LED driver for triple string LEDs. The proposed converter only uses two power inductors and a set of controller to achieve greater than 0.945 PF, up to 90.5% efficiency, low LED current ripple, and independent current regulation for triple LED strings with different forward voltage, which may significantly reduce the cost and size of the traditional AC‐DC multistring LED driving circuit.

End‐to‐end generation of structural topology for complex architectural layouts with graph neural networks

AbstractCurrent automated structural topology design methods can only deal with limited design spaces or simplified architectural layouts for lack of data or a proper representation of structure topology. To address this, the abundant information of manually designed architectural and structural layouts should be exploited to guide the topology design. To achieve automatic generation of structural topologies according to real‐world architectural layouts, this research introduces StrucTopo‐generative adversarial network (GAN), an end‐to‐end generative model with node and edge generation stages based on proper graph representation. Nodes are generated using an image‐to‐image translation model, and edges are generated with a GAN‐based approach. The model is trained and tested on a dataset of 300 complex architectural and structural layouts. Measured against the manually designed topologies, the results indicate that the proposed model can generate reasonable structural topologies, with a recall of 97% and an intersection‐over‐union of 80% in node generation, with a precision of 92% and a recall of 91% in edge generation. Additionally, the joint generation shows a graph similarity of 72%. The proposed model is the first of its kind to consider complex architectural layout constraints in the generation of structural topology, marking a step forward in applying artificial intelligence to practical structural design.

Topological design factor optimization in the development of periodic‐type honeycomb lattice structure on the carbon fiber reinforced polyethylene terephthalate glycol composite

AbstractIn most of the automobile and aerospace materials, cellular structures are extensively used due to their lightweight and high energy absorption capabilities. Naturally available animal bones and plant stems are light in weight due to their natural cellular structures. This may inspire various researchers for integrating the various lattice structures such as beam, planar, triply periodic minimal surfaces, and voronoi structures on the various structural materials. The development of lattice structures using 3D printing technology has opened up major attention towards fabricating lightweight components without any complications. In this study, the detailed crashworthiness responses such as compressive strength was optimized in terms of varying the topology‐related factors on the carbon fiber reinforced polyethylene terephthalate glycol (CF/PETG) composite. The experimentation was conducted concerning variable topology factors such as shell thickness, unit cell type, wall thickness (WT), unit cell orientation (UCO), skewing angle, and unit cell size. The model was examined and optimized by means of the Taguchi optimization technique. The crashworthiness response was analyzed using the compression test and moreover, this experimental response is used for the optimization processes. From the observation, the topology factors which contributed more for the higher compressive strength will be UCO of 65.47% and WT of 15.20%. Results of the regression study show that the R square value with concern to the compressive strength will be 92.74%. The optimized design parametric condition for CF/PETG composite established a higher compressive strength of 41.179 MPa, From the overall results, it is clear that the variation in the topology factors has developed a huge and favorable impact on the mechanical characteristics of the lattice‐structured CF/PETG polymer composite.Highlights Hexagonal Lattice structure incorporation on the carbon fiber reinforced PETG composite. Design optimization on the compressive properties. Taguchi optimization is performed on design‐based lattice structures. Unit cell orientation has higher percentage contribution on compressive strength.

Incorporating buckling effect into the topology design of 2D continuum structures using isolines

Isolines Topology Design (ITD) is an iterative algorithm for use in the topological design of two-dimensional (2D) continuum structures using isolines. This paper presents an extension to this algorithm for topology design of 2D continuum structures under the influence of buckling. Topology design has been used to obtain the lightest structure that can support the loading conditions without failure, with optimal designs typically consisting of slender members. In many cases, instability (or buckling) of the slender compressive members may occur at load levels below those predicted using a stress-based failure criteria. Although topology optimization is often used in the conceptual phase of the design, the influence of buckling has a significant impact on the features and performance of the final structure. This article presents an alternative approach to incorporate the buckling effect into the ITD algorithm for the design of 2D continuum structures. The concept consists of transforming the buckling topology optimization problem into a conventional von Mises stress-based topology design problem at each iteration using the shape of the buckling mode of the structure obtained by the eigenvalue analysis. Three examples are presented to show the viability and effectiveness of the alternative approach implemented into the ITD algorithm. The effect of the displacement factor ratio value on the first critical load of a resulting designs was studied. The resulting designs presented are in good agreement with those from the literature. The main conclusion is that the alternative approach can maximize the first critical load of a design subject to final volume constraints if the associated stiffness loss can be assumed.

Study of Bipolar Inductively Isolated High-Voltage Pulse Source

To meet the application requirements of pulsed power technology in wastewater treatment and other aspects (for example, a scenario that requires a high-voltage pulse source that can output a pulse with a rising edge in the nanosecond range and a device that can stabilize the pulse under high-frequency conditions), this paper designed an inductively isolated bipolar high-voltage pulse source. It consists of three parts: the primary charging power supply, the isolated driver circuit, and the pulse-forming circuit. By using inductance instead of traditional resistance isolation, using the inductance for charging and isolation, the inductance can increase the charging voltage of the capacitor, so the circuit can achieve a higher voltage output. The dual-Marx generator parallel connection design of the pulsed power supply topology, using a primary charging power supply for positive and negative polarity charging, can simultaneously output the reverse polarity and size of high-voltage pulses to achieve a bipolar output, so the load has an effect on the pulse. The equipment was selected on the basis of the design of the isolated driver circuit, primary charging power supply circuit, and pulse-forming circuit for the corresponding simulation, and in the experiment to build a principle model, the tests showed that the pulse source output pulse amplitude range was 0~10 kV (the positive pulse voltage was 5 kV, and the negative pulse voltage was −5 kV), the pulse rising edge was approximately 200 ns, the pulse width was 1 μs, and the frequency range was 0~1 kHz for the pulse source frequency. The power supply was designed to be used in applications such as wastewater treatment.

Congestion control analysis of optical packet switch for optical data center applications

Abstract Optical data centers serve as the backbone of modern networking, facilitating seamless connectivity for users across the globe. The connection between users and the optical data centers is established through various network topologies, which play a critical role in determining the traffic characteristics. The design and implementation of these network topologies, along with the assortment of applications hosted on optical data centers, significantly influence the flow of data within the network. The advent of cloud computing has further revolutionized optical data center operations, leading to the coexistence of a wide range of applications on different optical data center switches. As a result, the traffic characteristics observed on each optical data center switch vary significantly. This diversity in traffic patterns necessitates a comprehensive understanding of how data arrival is managed and handled by the networking infrastructure. In this paper, we explore the concept of a random traffic model for data arrival on Top of Rack (ToR) switches, which represent a crucial component of optical data center networking. In the modeling, small world model is considered. The effect of buffering and packet priorities is observed on traffic shaping. Finally, to evaluate the effectiveness of the traffic shaping techniques, we measure the packet loss performance of ToR switches and found to be as low as 10−4 even at the higher loads. Blocking performance provides valuable insights into how effectively the optical data center network manages incoming data and avoids congestion or bottlenecks.

Mechanical predictive modeling of stereolithographic additive manufactured alumina microlattices

Alumina microlattices with stretch- and bending-dominated structures were manufactured to establish the intercorrelation between the quasi-static microlattice mechanical properties and the strut aspect ratio using the stereolithographic additive manufacturing method. In the present work, two kinds of novel mechanical prediction models were calibrated and validated through the experiment and simulation data, aiming to realize the topological optimization and effective design of the weight, strut size, and spatial geometrical structures of the microlattice according to the given load bearing and stiffness demands. First, the mathematical prediction models of the compression strength and Young’s modulus for the microlattices with different aspect ratios were developed based on the modified Gibson and Ashby’s law and Timoshenko beam theory. Then, the prediction models exhibited an excellent prediction achievement of the experiment and simulation results with the assistance of data fitting. Subsequently, the tensile and compressive damage models perfectly reappeared and tracked the actual fracture behaviors of the microlattice, demonstrating different collapse trends for the Simple cubic (SC) and Body-centered cubic (BCC) microlattices. Finally, the quasi-static mechanical properties of SC were far stronger than that of BCC under the same aspect ratio and from the experiment data, simulation results, and theory formulas. This work laid a solid foundation for the microlattice structure design in lightweight engineering.