Node Geometry Research Articles

ОПТИМІЗАЦІЯ КОНСТРУКЦІЇ ТА РЕЖИМУ РОБОТИ СУШИЛЬНОЇ КАМЕРИ НА ОСНОВІ ЇЇ 3D МОДЕЛІ

This paper focuses on the analysis and optimization of the drying chamber design using SolidWorks Simulation software. One of the main problems that arises in the design of drying chambers is the need to ensure optimal conditions for efficient drying of materials. In this regard, this study determines the optimal design parameters of the drying chamber and its operating mode to ensure uniform temperature distribution in the stack. The methodology includes creating a 3D model of the drying chamber and its main components in SolidWorks, generating a difference mesh, conducting a thermal study in SolidWorks Simulation, and applying Design Study to optimize the design parameters of the drying chamber and its operating modes. The simulation results include the output of the heat flow in the stack and temperature measurements at various points, which allows us to assess the temperature differences and the impact of optimization parameters on them. Temperature measurements at different points were performed using the Prob tool, which takes into account the exact geometry and location of nodes on the tetrahedral elements of the difference grid of the 3D model of the drying chamber used for the calculations. In general, the study consists of applying an integrated approach to the design of drying chambers using SolidWorks and automating the optimization process through the SolidWorks API, for which software has been created. The software also allows users to enter input data for the 3D model design and thermal study parameters for their transfer to SolidWorks. In addition, the software provides the ability to perform calculations directly in SolidWorks Simulation but in the background, so that the results obtained will be displayed in a special program window in a fully automated mode. It is also worth noting that performing calculations without visualizing this process significantly reduces the time to obtain results that can be used to improve the technological processes of drying various materials in drying chambers.

Parametric Automated Design and Virtual Simulation of Building Machine Using BIM

With the continuous development of the construction technology of the main structure of high-rise buildings, traditional construction techniques have been widely used in high-rise building projects. However, these technologies have problems such as low safety, low intelligence, and poor integrity. In order to solve these challenges, the Third Engineering Bureau of China Construction independently developed a new type of construction technology—a high-rise building integrated work construction platform (referred to as a building machine). Building machines has been gradually applied to high-rise building projects due to its intelligence, integration, safety, and other advantages. However, with the increase in the number of high-rise building projects, the traditional way of designing building machine layout programs is inefficient and the design program is complicated to change. To solve these problems, this paper proposes a building machine parametric design and layout and virtual simulation method. This method uses Blender open-source software to model the building machine parametrically and quickly using its visual programming tool Geometry Nodes (GN) and simulates the building machine in the virtual scene through the Unity3D platform. The results show that, compared with the traditional design mode, the method proposed in this paper can quickly complete the scheme design in the design phase of the building machine and display it through the 3D model, which has a better visualization effect, improves the design efficiency, and reduces the design cost, and the Unity simulation platform can also provide the construction personnel with pre-shift education and simulation of the operation of the building machine. This method provides a theoretical basis and guidance for the digital construction of the building machine.

Multifractality of Complex Networks Is Also Due to Geometry: A Geometric Sandbox Algorithm.

Over the past three decades, describing the reality surrounding us using the language of complex networks has become very useful and therefore popular. One of the most important features, especially of real networks, is their complexity, which often manifests itself in a fractal or even multifractal structure. As a generalization of fractal analysis, the multifractal analysis of complex networks is a useful tool for identifying and quantitatively describing the spatial hierarchy of both theoretical and numerical fractal patterns. Nowadays, there are many methods of multifractal analysis. However, all these methods take into account only the fact of connection between nodes (and eventually the weight of edges) and do not take into account the real positions (coordinates) of nodes in space. However, intuition suggests that the geometry of network nodes' position should have a significant impact on the true fractal structure. Many networks identified in nature (e.g., air connection networks, energy networks, social networks, mountain ridge networks, networks of neurones in the brain, and street networks) have their own often unique and characteristic geometry, which is not taken into account in the identification process of multifractality in commonly used methods. In this paper, we propose a multifractal network analysis method that takes into account both connections between nodes and the location coordinates of nodes (network geometry). We show the results for different geometrical variants of the same network and reveal that this method, contrary to the commonly used method, is sensitive to changes in network geometry. We also carry out tests for synthetic as well as real-world networks.

A Data-Driven Factor Graph Model for Anchor-Based Positioning.

This work presents a data-driven factor graph (FG) model designed to perform anchor-based positioning. The system makes use of the FG to compute the target position, given the distance measurements to the anchor node that know its own position.The aim was to design a hybrid structure (that involves data and modeling approaches) to address positioning models from a Bayesian point of view, customizing them for each technology and scenario. The weighted geometric dilution of precision (WGDOP) metric, which measures the effect on the positioning solution of distance error to the corresponding anchor node and network geometry of the anchor nodes, was taken into account. The presented algorithms were tested with simulated data and also with real-life data collected from IEEE 802.15.4-compliant sensor network nodes with a physical layer based on ultra-wide band (UWB) technology, in scenarios with one target node, three and four anchor nodes, and a time-of-arrival-based range technique. The results showed that the presented algorithm based on the FG technique provided better positioning results than the least squares-based algorithms and even UWB-based commercial systems in various scenarios, with different setups in terms of geometries and propagation conditions.

Understanding Photocatalytic Activity Dependence on Node Topology in Ti-Based Metal–Organic Frameworks

Despite the drive to develop more efficient Ti-based metal–organic framework (MOF) photocatalysts, MIL-125-NH2 is still the benchmark, and only a few design principles have been offered to improve photocatalytic performance. Linker functionalization in Ti MOFs has been shown to enable photocatalysis under visible light by closing the electronic band gap, significantly improving charge carrier lifetimes. Limited by known Ti-based MOFs, the role of node nuclearity and topology on photocatalytic activity remains unclear. Here, we report a new MOF, ICGM-1, a 3D-connected framework featuring 1D Ti–O rods. Photocatalytic hydrogen evolution reveals a significant difference in activity, which we attribute solely to node geometry. Using time-resolved spectroscopy and DFT calculations, we ascribe these differences to subtle electronic and geometric properties, paving the way for the development of Ti-MOF photocatalysts.

Sensitivity of the electrical response of a node of Ranvier model to alterations of the myelin sheath geometry.

Nodes of Ranvier play critical roles in the generation and transmission of action potentials. Alterations in node properties during pathology and/or development are known to affect the speed and quality of electrical transmission. From a modelling standpoint, nodes of Ranvier are often described by systems of ordinary differential equations neglecting or greatly simplifying their geometric structure. These approaches fail to accurately describe how fine scale alteration in the node geometry or in myelin thickness in the paranode region will impact action potential generation and transmission. Here, we rely on a finite element approximation to describe the three dimensional geometry of a node of Ranvier. With this, we are able to investigate how sensitive is the electrical response to alterations in the myelin sheath and paranode geometry. We could in particular investigate irregular loss of myelin, which might be more physiologically relevant than the uniform loss often described through simpler modelling approaches.

Toward Reliable UAV-Enabled Positioning in Mountainous Environments: System Design and Preliminary Results

Reliable positioning services are extremely important for users in mountainous environments. However, in such environments, the service reliability of conventional wireless positioning technologies is often disappointing due to frequent non-line-of-sight (NLoS) propagation and poor geometry of available anchor nodes. Hence, we propose a unmanned aerial vehicle (UAV)-enabled positioning system that utilizes UAV’s mobility to overcome the above challenges. In this article, we first analyze and model the major causes of service failures in the proposed system. In particular, a geometry-based NLoS probability model is established based on the digital elevation models (DEMs) of realistic terrain for reliability analysis. Subsequently, we propose a reliability-prediction method and derive the corresponding metric to evaluate the system’s ability to provide reliable positioning services. Moreover, we also develop a voting-based method for the further enhancement of service reliability. Monte Carlo simulations show that in mountainous environments, the proposed reliability-prediction method could achieve a prediction accuracy that is at least 36.8 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> higher than that of the existing technique. In addition, in the experiments conducted in two typical valley scenarios, the proposed reliability-enhancement method improves the service reliability of the proposed system by 23 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and 29 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> , respectively. These numerical results demonstrate the strong potential of the proposed system and methods for reliable positioning.

A case study of a real-time internet of things system for site-specific potato crop management in El-Salhia Area-Egypt

The site-specific management is the technology that considers the natural variability within the same field of factors related to crop growth to improve its management practices such that the agricultural treatments are varied for field's small production zones saving resources and environment, and improving crop quality and size. Since site-specific decisions are not far from the Fourth Industrial Revolution and the concept of processes automation, this work addresses improving the process of spatial variability analysis and thus supporting management decisions by developing a system—entitled EGYPADS—based on the Internet of Things and its enabling technologies. EGYPADS automates data collection, zones delineation according to their land suitability evaluation, and maps generation. The paper addresses a case study of potato crop in a specific area in Egypt, El-Salhia, in which eighty-five sites were chosen as main dataset for the modeling process during different stages of crop growth. Three management zones were recognized of the selected field based on the differentiation in their land suitability characteristics, representing about 5%, 65%, and 30% of the total area, respectively. The structure, screens, and services of EGYPADS are described in this paper. EGYPADS offered services include: management zones delineation using absolute and virtual coordinates, Land Suitability Assessment (LSA), data entry from field in real-time as well as from excel sheets, saving maps in suitable format for variable rate application, real-time and historical data processing, centralized management, and flexible formulation of events and related actions. The implementation of EGYPADS was verified. The system dynamically produces non-contiguous isobands, each representing a specific range of parameter values, and can be properly exported for use by other programs or smart machinery. It was proven that EGYPADS supports more than one land with different geometry, area, location, and number of nodes. EGYPADS was compared with the traditional LSA method, and was found to produce similar management zones.

Malicious anchor node extraction using geodesic search for survivable underwater wireless sensor network

Localization in underwater wireless sensor network (UWSN) faces an imminent threat when the triangulating anchor node starts to malfunction. Traditional geometric approaches are insufficient to cope with the survivability of UWSN topology. To address these issues, this paper presents a symplectic geometry for identification of the malicious anchor node. Consequently, a geodesic search algorithm (GSA) based Target localization is proposed which reduces the positioning error by exploiting the phase-space constancy of the underwater acoustic sensor network topology to effectively triangulate the target node despite its mobility. First, a malicious anchor node model is presented. The node movement is expressed in the form of “ripple region”. GSA is then proposed which effectively frees the node metastasis from anchor node geometry, thereby making the underwater system more survivable and resilient. Simulation results evaluate the survivability of the geodesic formalism in terms of the reduced penalty incurred by node movement, as well as the reduced impact of anchor node malfunction. An improvement of 13.46% and 9.26% reveals the utility of the geodesic technique in aquamarine sensor deployments, which would be beneficial in underwater resource exploration and defense planning.

Charge sensing properties of monolithic CMOS pixel sensors fabricated in a 65 nm technology

In this work the initial performance studies of the first small monolithic pixel sensors dedicated to charged particle detection, called CE-65, fabricated in the 65nm TowerJazz Panasonic Semiconductor Company are presented. The tested prototypes comprise matrices of 64×32 square analogue-output pixels with a pitch of 15μm. Different pixel types explore several sensing node geometries and amplification schemes, which allows for various biasing voltage of the detection layer and hence depletion conditions and electric field shaping. Laboratory tests conducted with a 55Fe source demonstrated that the CE-65 sensors reach equivalent noise charge in the 15 to 25e− range and excellent charge collection efficiencies. Charge sharing is substantial for standard diodes, but can be largely suppressed by modifying their design. Depletion of the thin sensitive layer saturates at a reverse diode bias of about 5 V.

3D CFD study of hydrodynamics and mass transfer phenomena for spiral wound membrane submerged-type feed spacer with different node geometries and sizes

Modification of the spacer geometry is a promising approach to increase the efficiency of reverse osmosis (RO) spiral wound membrane modules. Column nodes and spherical nodes are considered in this three-dimensional computational fluid dynamic (CFD) study to evaluate the hydrodynamic and mass transfer performance of submerged spacers with different node geometries and sizes. Small-scale CFD analysis results reveal that the column node has better mass transfer performance than the spherical node geometry because column nodes divert more flow to the filaments, leading to higher local velocity at the region between the filament and wall. Furthermore, when the dimensionless node diameter ratio of the column nodes increases from 0.3 to 1.2, Sherwood number and wall shear increase by 25% and 8% respectively at the expense of higher global friction factor (44%). A sea water RO full-scale analysis revealed that column node spacers yield higher average flux than spherical nodes and conventional spacers at high feed inlet velocity (> 0.1 m/s), because the mixing effects by the spacer that improve mass transfer are more prominent.

Exploiting perturbed and coalescent anchor node geometry with semidefinite relaxation for sensor network localization

Localization in wireless sensor networks (WSNs) suffer from performance issues whenever the anchor nodes (which are aware of their location) are subjected to motion from their usual position. Moreover, accurate localization demands more anchor nodes which is a scarce resource and needs to be used judiciously. In the current work, we propose a novel framework that addresses these two prime concerns by harnessing the inter relationship of anchor node geometry. For an unknown source node surrounded by anchor nodes, the anchors lying on the inner boundary of the deployment geometry may be carrying closely related information about source node, leading to redundancy and inefficient utilization. By anticipating the level of correlation between these anchors, localization can be made more frugal. Rigorous mathematical analysis is carried out to derive lower bounds on estimated locations. Based on fisher information from two proposed models, a convex estimation objective function is formulated using semidefinite programming (SDP) approach to validate the theoretical proceedings. Based on the findings, the proposed method is able to successfully extract useful information about the unknown source node location with limited number of anchor nodes, hence achieving superior localization.

Automated Design Workflow for Structural Nodes of Space Frame Structures

Large-scale structures are often built using space frames or trusses. These can become complex if the geometry of the space frame structure is customizable and if they do not contain any recurring components. Consequently, the design effort required, and the production cost of these unique components become large. Further, designing and creating these structures is challenging for novice designers as these processes require large design know-how. This challenge can be addressed with a knowledge-based engineering (KBE) approach. Design processes for specific, repeating tasks are analyzed and broken down into individual steps, which can be automated as a rule-based design procedure.This work introduces an automated design workflow that follows a KBE approach. The workflow automates the design process for irregular space frame structures. The workflow takes a mesh geometry of the space-frame structure as an input, and decomposes the mesh to nodes, bars, and panels. The workflow then generates and exports the fabrication data that are required for production: STL files for the three-dimensional node geometries that are additively manufactured with multi jet fusion, cutting lines for the planar panels that are produced with a laser-cuter, and length values that are used to cut straight bars. The work describes in detail the rules applied for the automation of the design process. This automated design workflow enables novice designers to create space frame structures with reduced design effort. The workflow is applied on a horse sculpture to demonstrate the manufacturability of the parts and the assembly of the space frame structure.

Smart Structures in Architectural Projects: Towards an interactive design framework combining multiscalar structural optimisation and custom-optimized structural nodes for generative design

Interactive mass customisation is changing practice in the architecture, engineering, and construction (AEC) industry. Future workflows in software systems could address human-in-the-loop technology to augment human creative capacities. Early design stages require quick and well-informed decisions in response to data available from building information modelling technology. Architectural de-sign has been transformed by the in-troduction of design software but until recently the actual design has continued to be performed by the architect. That has begun to change with the exploration of interactive design frame works. Optimizing structures on multiple scales effects both, the overall structure in dependence of the architectural geometry and the local expression of 3D printed structural nodes. The reported research explored an algo-rithm to close geometric gaps in generative design of structural components. This foam-like algorithm allowed the artist and architect to design New Structuralism style using a combination of different optimisation routines. As a result, the SPUME algorithm was investigated to inte-grate several geometric parts in an organic shape for design of custom-optimized structural nodes. As part of the case study, a pavilion with a tessellated structure and 3D printed custom-optimized structural nodes was designed by an artist and an architect to showcase the application potential of the conceptualized framework. Finally, a prototype for connecting brackets and BESO optimized shape of the structural nodes was produced to combine all aspects of the local node geometry in the tectonic representation.

Semi-automated braiding of complex, spatially branched FRP-structures

In building industries, branched load-bearing structures are used for defined load transfer and load distribution. While fiber-reinforced plastics are established as concrete formwork for straight segments, node geometries are less available. This is caused by the complex manufacturing process of spatially branched, three-dimensional textile preforms. There are only few productive textile processes for the manufacture that are attractive to industry, the most common is braiding. However, setting up the process, including programming the mandrel path through the braiding machine and adjusting the fiber placement, is very time consuming, making the process unattractive despite high productivity. This paper presents a new digitalized process workflow for the fabrication which simplifies the process preparation and thus could establish the braiding process for rapid fabrication of spatially branched, three-dimensional geometries. The digitalized workflow is validated by manufacturing a 4-arm node structure consisting of a concrete-filled CFRP in a scale relevant to the building industry.

A Model Reduction Method for Bladed Disks With Large Geometric Mistuning Using a Partially Reduced Intermediate System Model

Abstract Reduced order models (ROMs) are widely used to enable efficient simulation of mistuned bladed disks. ROMs based on projecting the system dynamics into a subspace spanned by the modes of the tuned structure work well for small amounts of mistuning. When presented with large mistuning, including changes of geometry and number of finite element mesh nodes, advanced methods such as the pristine-rogue-interface modal expansion (PRIME) are necessary. PRIME builds a reduced model from two full cyclic symmetric analyses, one for the nominal and one for the modified type of sector. In this paper, a new reduced order model suitable for large mistuning with arbitrary mesh modifications is presented. It achieves higher accuracy than PRIME, while saving approximately 25% computational effort during the reduction process, when using the same number of cyclic modes. The new method gains its efficiency by recognizing that large modifications from damage or repair are unlikely to be exactly the same for multiple blades. It works by building a partially reduced intermediate model: All nominal sectors are reduced using cyclic modes of the tuned structure. The single modified sector is kept as the full model. For this reason, the new reduction method is called partially reduced intermediate system model (PRISM) method. The accuracy of the PRISM method is demonstrated on an axial compressor blisk and an academic blisk geometry.

SINR-Based Analysis of IEEE 802.11p/bd Broadcast VANETs for Safety Services

The safety-critical applications of vehicular ad hoc networks (VANETs) require high reliability and low transmission latency. IEEE 802.11p and IEEE 802.11bd are two standards proposed for such vehicular communication systems. In this paper, we propose an effective SINR-based model to conduct the QoS analysis of IEEE 802.11p/bd driven VANETs for safety applications. First, a semi-Markov process (SMP) model with a D/G/1/1 queue is tailored and modified for characterizing channel access behavior of IEEE 802.11 broadcast networks with deterministic message generation rate. Then, a novel approach is developed to derive the distribution of signal-to-interference-to-noise ratio (SINR) on each receiver in the VANET, given general channel fading/shadowing models as well as general node geometry distributions. Consequently, various QoS metrics in Physical/MAC/Application layer of VANETs are defined and evaluated. Compared with the existed analytic SINR-based models for broadcast VANETs, the proposed models are more general, more accurate, and are faster to solve. Finally, a new mechanism is shown to map the performance in physical layer into the QoS quantification in higher layer so that the QoS prediction of IEEE 80211bd driven VANETs is enabled. Furthermore, comparison between 802.11p and 802.11bd is conducted regarding how the stringent QoS requirements of selected safety applications in both human driving VANETs and autonomous driving VANETs are met by the two communication systems. Constructive conclusions are given on the suitability of IEEE 802.11bd for VANET critical safety services and the directions of future development.

Influence of Pore Structure and Metal-Node Geometry on the Polymerization of Ethylene over Cr-Based Metal-Organic Frameworks.

Metal–organic frameworks (MOFs) have received increasing interest as solid single‐site catalysts, owing to their tunable pore architecture and metal node geometry. The ability to exploit these modulators makes them prominent candidates for producing polyethylene (PE) materials with narrow dispersity index (Ð) values. Here a study is presented in which the ethylene polymerization properties, with Et2AlCl as activator, of three renowned Cr‐based MOFs, MIL‐101(Cr)‐NDC (NDC=2,6‐dicarboxynapthalene), MIL‐53(Cr) and HKUST‐1(Cr), are systematically investigated. Ethylene polymerization reactions revealed varying catalytic activities, with MIL‐101(Cr)‐NDC and MIL‐53(Cr) being significantly more active than HKUST‐1(Cr). Analysis of the PE products revealed large Ð values, demonstrating that polymerization occurs over a multitude of active Cr centers rather than a singular type of Cr site. Spectroscopic experiments, in the form of powder X‐ray diffraction (pXRD), UV/Vis‐NIR diffuse reflectance spectroscopy (DRS) and CO probe molecule Fourier transform infrared (FTIR) spectroscopy corroborated these findings, indicating that indeed for each MOF unique active sites are generated, however without alteration of the original oxidation state. Furthermore, the pXRD experiments indicated that one major prerequisite for catalytic activity was the degree of MOF activation by the Et2AlCl co‐catalyst, with the more active materials portraying a larger degree of activation.

Passive Geometry Calibration for Microphone Arrays Based on Distributed Damped Newton Optimization

Geometry calibration is an inherent challenge in distributed acoustic sensor networks. To mitigate this problem, a passive geometry calibration approach based on distributed damped Newton optimization is proposed. Specifically, a geometric cost function incorporating direction of arrivals (DoAs) and time difference of arrivals (TDoAs) is first formulated, and then its identifiability conditions are given. Next, to achieve a distributed geometry calibration, the cost function is split into multiple local cost functions that are assigned to every node. After that, a distributed damped Newton optimization is presented to retrieve the geometry of microphone nodes and synchronize the internal delay between each two neighboring nodes. Finally, computational complexity and transmission bandwidth requirements are further analyzed. Compared with the existing approaches, the proposed method estimates the geometry structure of microphone networks in a distributed manner. Moreover, it requires a small number of acoustic sources. Experimental results show the validity of the proposed method.

Image-Based Geometrical Characterization of Nodes in Additively Manufactured Lattice Structures.

Additive manufacturing (AM) enables the fabrication of lattice structures with optimal mechanical, fluid, and thermal properties. However, during the AM fabrication process, defects are produced in the strut and node elements, which comprise the lattice structure. This leads to discrepancies between the AM fabricated lattice and its idealized computer-aided design (CAD) model, negatively affecting the ability to predict the mechanical behavior of the fabricated lattice via numerical models. Current research is focused on quantification of geometric uncertainties in the strut elements of the lattice; as-manufactured node geometries remain relatively unexplored on an individual scale, despite their criticality to the mechanical response of the structure. Understanding the geometrical properties of as-manufactured nodes relative to CAD idealizations can be used to improve lattice designs and numerical models. In this research, X-ray microcomputed tomography (μCT) is used to analyze and quantify the as-manufactured nodal geometry, found in face-centered cubic and face-centered cubic with axial struts lattices fabricated via selective laser melting. A custom tool is developed that enables auto-isolation and classification of nodal joints from μCT-derived cross-sectional slices. Geometrical properties are extracted from the isolated nodal cross sections and compared with their idealized CAD model counterpart. Quantification of geometrical defects provides insight into how nodes within an AM lattice structure differ from each other and their idealized design. Overall, this research is an initial step toward developing accurate and efficient numerical models, as well as better node design for AM.