Topological Configurations Research Articles

Structural design and motion characteristics analysis of dual-mode active swing arm tracked robot

Focusing on the demand for complex terrain traversal capability of mobile robots, this paper presents a mobile and creep dual-mode tracked robot configuration with capability of autonomous extrication, in response to solving the problem of tracked robots trapped due to insufficient obstacle-crossing capability. Based on the geometrical characteristics of parallelogram and its dynamic computation on the ground, a topological configuration of mobile tracked mechanism with the ability of creep is studied. An integrated structural design method of mobile chassis that integrates the swing arm and the tracked mechanism is proposed and a dual-mode active swing arm tracked robot structural model is established. The mobile and creep characteristics of the dual-mode active swing arm tracked robot are revealed through comparative simulations in multiple working conditions; Through the prototype tests in such typical working conditions as climbing, turning and obstacle-crossing, the feasibility of creep for the robot is verified and it is proved that the obstacle-crossing ability can be effectively improved. The research results provide theoretical support for improving the adaptability and possibility of mobile robots in complex terrain.

Method for Locating Secondary Circuit Faults in Substations Based on Graph Neural Networks

To improve the accuracy and portability of fault location in secondary circuits of smart substations, a fault location method for secondary circuits based on graph neural networks is proposed. First, a fault analysis of the secondary circuits in smart substations is conducted, and a graph database model of the secondary circuits is constructed, revealing the connection relationships between the secondary devices. Then, the fault location problem in secondary circuits is defined as a graph classification problem, and a fault graph generation model is proposed based on a representation method for fault information in secondary circuits. Finally, a fault location model for secondary circuits based on graph neural networks is constructed, and a performance optimization method based on binary cross-entropy is proposed to achieve accurate fault location in substation secondary circuits. Using the secondary circuits of a 220 kV smart substation as a reference, different case studies of secondary circuit faults are generated by altering the network topology, connection relationships, and network configurations through the fault graph generation model. Experiments comparing the proposed location method with other models show that this method has higher location accuracy and robustness.

Yield surface of multi-directional gradient lattices with octet architectures

In this paper, a theoretical method is developed to delineate the effective elastic properties and yield surface of the gradient cellular structure. Additionally, a technique is presented for the construction of multi-directional gradient lattices, and two novel tri-directional gradient lattices (TD-GLs) by assembling octet unit cells with side lengths following specified gradient topological parameters serve as an illustrative example. Their effective elastic properties and yield surfaces are systematically investigated with the aid of theoretical, experimental, and finite element methods. It is found that the effective elastic modulus of the proposed TD-GLs exceeds by 48.80% as compared to that of conventional uniform octet lattices. Moreover, the normalized yield surfaces are proposed to emphasize the predominant role of structural topological features by eliminating the influence of the relative density on the yield behavior of TD-GLs, and this method that also can be extrapolated to other tension-dominated lattices. Subsequently, a theoretical model is developed to establish closed-form yield functions for characterizing the yield behavior of TD-GLs. The predicted yield surfaces from the proposed theoretical model demonstrate good agreement with the simulated results. Finally, the proposed TD-GLs demonstrate outstanding yield performance in various directions deviating from their orthogonal principal axes or planes, compared to lattices with uni- or dual-directional gradient topological configurations. In summary, the proposed multi-directional gradient lattices in this study exhibit the exceptional stiffness and outstanding yield performance in various directions, offering valuable insights for the structural design and engineering applications of lattice structures.

Abnormal intrinsic brain functional network dynamics in patients with retinal detachment based on graph theory and machine learning

Backgroundand purpose: The investigation of functional plasticity and remodeling of the brain in patients with retinal detachment (RD) has gained increasing attention and validation. However, the precise alterations in the topological configuration of dynamic functional networks are still not fully understood. This study aimed to investigate the topological structure of dynamic brain functional networks in RD patients. MethodsWe recruited 32 patients with RD and 33 healthy controls (HCs) to participate in resting-state fMRI. Employing the sliding time window analysis and K-means clustering method, we sought to identify dynamic functional connectivity (dFC) variability patterns in both groups. The investigation into the topological structure of whole-brain functional networks utilized a graph theoretical approach. Furthermore, we employed machine learning analysis, selecting altered topological properties as classification features to distinguish RD patients from HCs. ResultsAll participants exhibited four distinct states of dynamic functional connectivity. Compared to the healthy control (HC) group, patients with RD experienced a significant reduction in the number of transitions among these four states. Additionally, the dynamic topological properties of RD patients demonstrated notable changes in both global and node-specific characteristics, with these changes correlating with clinical parameters. The support vector machine (SVM) model used for classification achieved an accuracy of 0.938, an area under the curve (AUC) of 0.988, and both sensitivity and specificity of 0.937. ConclusionThe alterations in the topological properties of the brain in RD patients may indicate the integration function and information exchange efficiency of the whole brain network were reduced. In addition, the topological properties hold considerable promise for distinguishing between RD and HCs.

Multi-scale topology optimization of periodic structures with orthotropic multiple materials using the element-free Galerkin method

ABSTRACT A multi-scale topology optimization model is proposed for orthotropic multi-material periodic structures using the element-free Galerkin method. The macro multi-material distribution is optimized with the alternating active-phase algorithm, and the effective elastic tensor of multi-type microstructures is determined by energy-based homogenization. The feasibility of the model is verified and the effects of the quantities of material types and design subdomains, the Poisson's ratio factor and the multi-material off-angle on topological configuration and compliance are studied. The results indicate that the quantity of material types affects the mechanical properties of the periodic structure, and different microstructure configurations can be obtained under different numbers of design subdomains. The increase in the Poisson's ratio factor and decrease in the off-angle can enhance the effective elastic properties of the microstructure and reduce the compliance. Reasonable values of the Poisson's ratio factor and multi-material off-angle are suggested to be 2–4 and 0–45°.

An enhanced proportional topology optimization method with new density filtering weight function for the minimum compliance problem

This article proposes an enhanced proportional topology optimization (EPTO) method to solve the structural topology optimization problem of minimizing compliance under material volume constraints. In the proposed method, a new filtering weight function based on the improved Heaviside threshold function is adopted to filter element density during the optimization process. The optimization process of the EPTO method consists of an inner loop and an outer loop. In the inner loop, density distribution is modified in combination with a new filtering weight function. By locally averaging the weighted element compliance, an improved density distribution function in the inner loop is put forward to make the topology configuration of the optimized structure more reasonable. In addition, the projection method is used to reduce the number of intermediate density elements, thereby obtaining optimization results with clear boundaries. In the outer loop, a new termination criterion is adopted, which terminates the optimization process by determining that the relative error of the objective function in several consecutive iterations is less than the specified value. The effectiveness and efficiency of the proposed method are demonstrated through several numerical examples involving two-dimensional (2D) and three-dimensional (3D) topology optimization problems. The results of numerical examples show that the proposed method can not only accelerate the convergence of optimization iterations, but also obtain optimized structures with smaller objective function values and better topology configurations. HIGHLIGHTS A new density filtering weight function is proposed based on an improved Heaviside threshold function. An improved inner loop density distribution formula is proposed by combining a new filtering weight function. Using projection based methods to suppress the appearance of intermediate density elements. Verify the effectiveness of the proposed algorithm by comparing the optimization results with existing algorithms such as top88 and PTO.

Structural topology optimization for plastic-limit behavior of I-beams, considering various beam-column connections

This work proposes topology optimization for steel I-beams, including consideration of bolted beam-column connections with geometric and material nonlinear analysis. The aim is to assess and compare the topological configurations influenced by different connections, examining their stress distribution and rotational stiffness to illustrate the potential of structural optimization. The bi-directional evolutionary structural optimization (BESO) approach is implemented. Furthermore, several bolted steel beam-column configurations were validated based on experimental tests. Subsequently, a series of finite element models were developed, contributing to a comprehensive understanding of the plastic-limit behavior of I-beams under different loading conditions. The proposed method could potentially use a lesser quantity of material while maintaining the same level of structural performance. The results indicate that the implementation of structural topology optimization on I-beams while considering various beam-column connections, yields structural performance similar to that of solid web configurations, achieved through material reduction.

N18 ring: A building block for constructing 1D and 2D polymeric nitrogen frameworks

Exploring the fundamental building block is essential for constructing functional materials with extended topological configurations. In the polymeric nitrogen system, no fundamental building blocks have been reported so far. Here, we successfully synthesize the buckled 1-dimensional (1D) band-shaped and 2-dimensional (2D) layered polymeric nitrogen frameworks with N18 ring as a fundamental building block for the first time. Furthermore, the dimensions of the polymeric nitrogen frameworks can be regulated by pressure conditions. Bader charge analyses indicate that the charge transfer from the La atom to the low-order bonded nitrogen atom plays a crucial role in stabilizing these two low-dimensional polymeric frameworks. Both LaN16 and LaN8 are promising high-energy-density materials (HEDMs). This study reveals that the N18 ring can serve as a fundamental building block, analogous to thesix-membered ring in carbon-based materials, enabling the construction of novel polymeric nitrogen materials with extended frameworks.

An inherent fault current blocking modular series multilevel converter using half-bridge sub-modules for grid integration

This paper proposes an inherent fault current blocking modular series multilevel converter (MSMC) using half-bridge (HB) sub-modules (SMs) for grid integration. The proposed converter uses passive filters to decouple the AC and DC side. Compared to conventional three-phase modular multilevel converters (MMCs) that use half-bridge sub-modules (HBSMs), the new MSMC design significantly reduces the number of switching devices required. Furthermore, one of the features of the proposed MSMC is its inherent ability to limit fault currents, which is achieved through its unique topological configuration whereas the conventional HB-MMC is susceptible to DC and AC faults. Despite these advancements, the new MSMC design retains all the desirable characteristics of conventional HB-MMCs, ensuring compatibility and ease of adoption. The paper thoroughly examines the operation of the MSMC under both steady-state and fault conditions. It also discusses the equivalent voltage decoupling circuit, energy balancing which is essential for the proper functioning of the converter. Additionally, the pre-charging process of the sub-module capacitors, a critical step for ensuring the safe start-up of the converter, is discussed in detail. Furthermore, Extended topologies can be derived from proposed topology for different applications.

Edge-on anchored discotic liquid crystals in spherical shells: A computational study of the phases and defects.

The self-assembly of liquid crystal droplets and shells represents a captivating frontier in soft matter physics, promising precision engineering of functional materials. In this study, we delve into the phase behavior and investigate defect formation patterns in spherical shell-confined discotic liquid crystals (DLCs) through NpT Monte Carlo simulations. These shells are created by confining DLCs between two spherical surfaces, promoting the same anchoring. In this study, we focus on the case when both surfaces promote edge-on (planar) anchoring. Our study confirms a general result which states that, when a liquid crystal is under strong confinement, the nature of the isotropic-nematic transition changes from first order into continuous. Furthermore, as expected, topological defects at the spherical surface arise due to the topological constraints on the director field. Notably, our investigation reveals a unique topological defect configuration, characterized by the formation of four disclination lines that bridge the inner and external surfaces. Additionally, we observe a mixed ±1/2 wedge-twist disclination line that forms an arch that terminates at the outer surface. This arch decreases its length with decreasing temperature to eventually disappear.

An integrated optimization method for the damper placements, shape and size of truss structures

This work extends the application of the approximation concept in dynamic topology optimization for truss structures. The corresponding problem contains both continuous and discrete variables, encompassing damper placements, truss shape and cross-sectional area. First, the utilization of a branched multipoint approximation (BMA) function establishes sequential approximation problems that also involve such mixed variables, marking its innovative application in dynamic optimization. Then, a modified genetic algorithm (GA) is used to optimize discrete variables. To enhance convergence stationarity, the concept of ‘adjacent individuals’ is proposed to control the degree of difference in topology configuration between initial population members and the current optimal. Additionally, adjustments to the sequence-based crossover process ensure compliance with damper quantity constraints. Examples demonstrate that the introduction of adjacent individuals is beneficial to convergence stationarity, and the shape change of the truss increases the mode damping ratio by more than 20%. The created optimization platform can also tackle other mixed variables optimization problems.

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li7La3Zr2O12-LiCoO2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li7La3Zr2O12-LiCoO2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. Our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

Tonic and burst-like locus coeruleus stimulation distinctly shift network activity across the cortical hierarchy

Noradrenaline (NA) release from the locus coeruleus (LC) changes activity and connectivity in neuronal networks across the brain, modulating multiple behavioral states. NA release is mediated by both tonic and burst-like LC activity. However, it is unknown whether the functional changes in target areas depend on these firing patterns. Using optogenetics, photometry, electrophysiology and functional magnetic resonance imaging in mice, we show that tonic and burst-like LC firing patterns elicit brain responses that hinge on their distinct NA release dynamics. During moderate tonic LC activation, NA release engages regions associated with associative processing, while burst-like stimulation biases the brain toward sensory processing. These activation patterns locally couple with increased astrocytic and inhibitory activity and change the brain’s topological configuration in line with the hierarchical organization of the cerebral cortex. Together, these findings reveal how the LC–NA system achieves a nuanced regulation of global circuit operations.

Cognitive Navigation for Intelligent Mobile Robots: A Learning-Based Approach with Topological Memory Configuration

Cognitive Navigation for Intelligent Mobile Robots: A Learning-Based Approach with Topological Memory Configuration

Numerical investigation of aerodynamic characteristics in tandem cascades with various curving strategies

Tandem configurations with curved blades can improve the flow field in compressor cascades. This study conducts a numerical investigation into the impact of various curving strategies on the losses and flow structures within tandem cascades. Curving strategies of three distinct configurations (curving both blades, solely the rear blade, and solely the front blade) along with three curved angles (5°, 10°, and 15°) are compared. Four primary vortex structures are causing losses in the tandem cascades. Loss weight coefficients, derived from each vortex, are adopted to quantify the proportion of losses. All curving strategies mitigate the accumulation of low-energy fluid near the endwalls, weakening the passage vortex. Various curving strategies have different effects on losses of the endwall spanwise vortex and trailing edge shedding vortices. The influence of curved angles on the three configurations indicates that curving both blades at 5° and curving the front blade at 5° or 10° can mitigate losses. An increasing loss is observed when the rear blade curves at any angle alone. Curving both blades or only the front blade mitigates the corner separation while the curved rear blade exacerbates it. The novelty of this study lies in applying topology analysis to establish correlations between losses, vortices, and topological configurations. This approach is a pivotal research methodology for elucidating the underlying mechanisms of loss generation and vortex dynamics within curved tandem cascades.

Toroidal phase topologies within paraxial laser beams

Control of topologies in structured light fields with multi-degrees of freedom integrates fundamental optical physics and topological invariance. Beyond the simple phase vortex, three-dimensional (3D) topological singularities and related nonsingular textures have recently gained significant interest. Here, we experimentally demonstrate the creation of a family of toroidal phase topologies within paraxial laser beams. By employing single two-dimensional (2D) phase control, we generate propagating 3D topological textures, effectively embodying the topological configuration of a four-dimensional (4D) parameter space. The resulting light fields exhibit amplitude isosurfaces of toroidal vortices and hopfionic phase textures, both controlled by topological charges. The ability to prepare scalar phase textures of light offers new insights into the high-dimensional control of complex structured textures and may find significant applications in light-matter interactions, optical manipulation, and optical information encoding.

Topology optimization design for voltage enhancement in variable structure double-layer flexible thermoelectric devices

Flexible thermoelectric devices possess the capability to generate electricity by harnessing temperature differences, rendering them highly promising for applications in wearable devices and powering the Internet of Things. This paper introduces a topology optimization design approach for double-layer thin-film flexible thermoelectric devices with the aim of enhancing the device's output voltage and improving the efficiency of green energy utilization. The design process took into consideration the coupled effects of mechanical, electrical, and thermal aspects. It not only optimized the force transmission paths of the variable structure device but also accounted for heat dissipation and circuit topology configuration. The study employed a field function model to concurrently optimize the structure of both the substrate and thermoelectric materials in an integrated design, with the primary objective being the maximization of output voltage. The efficacy of this methodology was confirmed through a series of numerical simulations and experiments conducted under various load and operational conditions. The optimized flexible thermoelectric devices exhibited an output voltage increase of more than threefold when compared to flat devices.

Thermodynamic topology of phantom AdS black holes in massive gravity

In this work, we explore the thermodynamic topology of phantom AdS black holes in the context of massive gravity. To this end, we evaluate these black holes in two distinct ensembles: the canonical and grand canonical ensembles (GCE). We begin by examining the topological charge linked to the critical point and confirming the existence of a conventional critical point (CP1) in the canonical ensemble (CE), this critical point has a topological charge of −1 and acts as a point of phase annihilation, this situation can only be considered within the context of the classical Einstein–Maxwell (CEM) theory (η=1), while no critical point is identified in the GCE. Furthermore, we consider black holes as a topological defect within the thermodynamic space. To gain an understanding of the local and global topological configuration of this defect, we will analyze its winding numbers, and observe that the total topological charge in the CE consistently remains at 1. When the system experiences a pressure below the critical threshold, it gives rise to the occurrence of annihilation and generation points. The value of electric potential determines whether the total topological charge in the GCE is zero or one. As a result, we detect a point of generation point or absence of generation/annihilation point. Based on our analysis, it can be inferred that ensembles significantly impact the topological class of phantom AdS black holes in massive gravity.

Effects of route guidance strategies on traffic emissions in urban traffic networks

Urban traffic emissions have significant environmental and health implications. Diverging from traditional research that primarily aims to improve traffic flow and efficiency, this study specifically focuses on the environmental impact on traffic emissions, conducting a comprehensive analysis within the Manhattan urban network through four route guidance strategies. The performance of these strategies is examined across various vehicle densities, and their impact on four traffic pollutant emissions (Carbon-dioxide, Nitrogen Oxides, Volatile Organic Compounds and Particulate Matter) is assessed. Moreover, our innovative approach analyzes emissions from the perspectives of both travel distance and trip frequency, placing special emphasis on trip frequency to provide practical insights with high real-world applicability. The results highlight the potential and limitation of the Congestion Coefficient Strategy. Under equal travel demands, the Congestion Coefficient Strategy showed promise in reducing carbon emissions. However, at lower vehicle densities, it led to a significant increase in emissions. This revelation pointed to the need for modifications to the strategy when applied in scenarios with lower traffic density. Recognizing this limitation, we introduced a modified strategy that achieved remarkable reductions in emissions across diverse vehicle densities, effectively overcoming the challenges posed by the original Congestion Coefficient Strategy. These findings offer valuable insights for policymakers and transportation planners in selecting optimal route guidance strategies to reduce pollutant emissions. Future studies will explore the efficacy of these strategies in road networks characterized by different topological configurations.

Refinement of Global Coronal and Interplanetary Magnetic Field Extrapolations Constrained by Remote-sensing and In Situ Observations at the Solar Minimum

Solar magnetic fields are closely related to various physical phenomena on the Sun, which can be extrapolated with different models from photospheric magnetograms. However, the open flux problem (OFP), the underestimation of the magnetic field derived from the extrapolated model, is still unsolved. To minimize the impact of the OFP, we propose three evaluation parameters to quantitatively evaluate magnetic field models and determine the optimal free parameters in the models by constraining the coronal magnetic fields and the interplanetary magnetic fields (IMFs) with real observations. Although the OFP still exists, we find that magnetic field lines traced from the coronal models effectively capture the intricate topological configurations observed in the corona, including streamers and plumes. The OFP is lessened by using the Helioseismic and Magnetic Imager synoptic map instead of the Global Oscillation Network Group daily synoptic maps, and the potential field source surface + potential field current sheet (PFSS+PFCS) model instead of the current sheet source surface (CSSS) model. For Carrington Rotation 2231 at the solar minimum, we suggest that the optimal parameters for the PFSS+PFCS model are R ss = 2.2–2.5 R ☉ and R scs = 10.5–14.0 R ☉, as well as for the CSSS model, are R cs = 2.0–2.4 R ☉, R ss = 11.0–14.7 R ☉, and a = 1.0 R ☉. Despite the IMFs at 1 au being consistent with the measurements by artificially increasing the polar magnetic fields, the IMFs near the Sun are still underestimated. The OFP might be advanced by improving the accuracy of both the weak magnetic fields and polar magnetic fields, especially considering magnetic activities arising from interplanetary physical processes.