3D Layout Research Articles

Enhanced Design Automation for Hydraulic Manifolds Produced Using Additive Manufacturing

Complex, highly functional components such as hydraulic manifolds can be produced using metal additive manufacturing (AM). The design process is a major challenge in the development of AM components that exploit this potential. Since traditional CAD systems are not made to efficiently create highly complex designs, new approaches to the design process are required. Design Automation (DA) and Knowledge-Based Engineering (KBE) are approaches that can be used to create designs and implement design changes faster and improve functionality. For the application of fluid components, KBE design workflows were developed which enable the automated generation of AM manifolds.However, these workflows have some limitations that need to be improved to provide a flexible design tool that enables users to automatically create geometries that meet all requirements. This paper shows how the workflows have been improved by introducing two new features. First, the object-oriented input format presents a new approach to how the information of a hydraulic circuit diagram can be processed to start the workflows. This is done through a component library that contains a selection of flow components providing all information and geometries of one component, a 3D layout assembly to orient the relevant components in space, and a connectivity matrix that defines the connection through flow channels for the manifold. Second, the bending radius constraint allows users to define a radius that the centerline of a flow channel should not undergo along the whole path. The new features are presented in detail in this paper. Further, the advantages are shown and compared to the previously published workflows in a case study. This work lays the foundation for future work that has the aim to fully automate the design process by only taking a hydraulic circuit diagram as an input and providing all required manufacturing files as an output.

Stripe Sensitive Convolution for Omnidirectional Image Dehazing.

The haze in a scenario may affect the 360 photo/video quality and the immersive 360 ° virtual reality (VR) experience. The recent single image dehazing methods, to date, have been only focused on plane images. In this work, we propose a novel neural network pipeline for single omnidirectional image dehazing. To create the pipeline, we build the first hazy omnidirectional image dataset, which contains both synthetic and real-world samples. Then, we propose a new stripe sensitive convolution (SSConv) to handle the distortion problems due to the equirectangular projections. The SSConv calibrates distortion in two steps: 1) extracting features using different rectangular filters and, 2) learning to select the optimal features by a weighting of the feature stripes (a series of rows in the feature maps). Subsequently, using SSConv, we design an end-to-end network that jointly learns haze removal and depth estimation from a single omnidirectional image. The estimated depth map is leveraged as the intermediate representation and provides global context and geometric information to the dehazing module. Extensive experiments on challenging synthetic and real-world omnidirectional image datasets demonstrate the effectiveness of SSConv, and our network attains superior dehazing performance. The experiments on practical applications also demonstrate that our method can significantly improve the 3-D object detection and 3-D layout performances for hazy omnidirectional images.

New Materials for Memory Applications by Atomic Layer Deposition

The architectures of integrated logic and memory devices have shifted from 2D to 3D layouts, enabling a continued scaling of device densities. Atomic layer deposition (ALD) allows the conformal deposition of thin films with sub-nm thickness control on high aspect ratio 3D structures. ALD has become the technique of choice for the synthesis of an increasing number of materials in advanced logic and memory devices. In the first part of this presentation, we briefly review some of the key ALD processes which enable the fabrication of state-of-the-art 3D-NAND and 2D-DRAM. Next, we present the ALD of emerging ferroelectric HfZrO developed at ASM in industrial scale ALD reactors. HfO2 has been established as the preferred gate oxide material for logic devices for almost two decades. The recent discovery of ferroelectricity in HfO2 has opened new applications for HfO2-based materials as active memory elements in DRAM and 3D-NAND. We show that ALD La:HfZrO can achieve high polarization field (2Pr > 60 uC/cm2) and high endurance (> 107 cycle) by applying interface engineering schemes and optimizing deposition processes and film composition (i.e. Hf/Zr ratio, dopant concentration).

Undirected graph representing strategy for general room layout estimation

Room layout estimation aims to predict the spatial structure of a room from a single image. Most existing methods relying on 2D cues are suitable for cuboid rooms, but non-cuboid rooms. 3D layout estimation methods can reconstruct 3D models of general rooms, but they are trained with depth information on high collection costs, consume large computation resources, and run slowly. This paper considers an undirected graph representation method of the general room layouts, which includes cuboid and non-cuboid rooms consisting of a single ceiling, a single floor, and multiple walls. To this end, we first predict the positions of the layout vertices and then use the network automatically learn the connection relationship between the vertices. The final layout is obtained through a simple layout inference post-processing algorithm. The experimental results both on cuboid and non-cuboid datasets validate the effectiveness and efficiency of our method. The code is available at https://github.com/Hui-Yao/2D-graph-layout-estimation.

Analysis of the fusion development of traditional culture concept and interior art design based on 3D scene analysis

Abstract In this paper, by collecting a large number of 3D scenes with traditional cultural styles, after pre-processing, the style analysis task of 3D scenes is realized through two stages of model style element discovery and scene style pattern mining. In the style pattern mining stage, the maximum frequent pattern mining algorithm is used to get the style pattern of the final scene, and the part is visualized. To reduce the user’s selection time, a 3D interior layout recommendation system based on style rule mining is designed using collaborative filtering. Based on the previous work on scene style pattern mining, the style association rules are further mined, and the user is provided with candidate layouts and furniture dynamically and in real-time by introducing user interaction. Comparing the text-improved recommendation algorithm with the traditional recommendation algorithm, the accuracy rate of the traditional algorithm starts to saturate to 65% after TopN>20, while the algorithm in this paper is higher than 80%. In the analysis of traditional cultural contexts of interior art, in terms of the aesthetic acquisition, the highest proportion of aesthetic association is 63.7%. In terms of emotional expression, the proportion of symbolization of emotion is 73.1%. In terms of object comparison, the highest proportion of plurality and flexibility of combinations was 57.5%. Therefore, this paper provides good research ideas for how to better integrate traditional culture into interior design.

Ferroelectric polarization reversals in C2N/α-In2Se3 van der Waals heterostructures: a conversion from the traditional type-II to S-scheme.

Introduction: Ferroelectric substances, characterized by inherent spontaneous polarization, can boost photocatalytic efficiency by facilitating the separation of photogenerated carriers. However, conventional photocatalysts with perovskite-class ferroelectricity are generally constrained by their 3D arrangement, leading to less accessible active sites for catalysis and a smaller specific surface area compared to a 2D layout. Methods: In my research, I developed a 2D ferroelectric heterostructure consisting of C2N/α-In2Se3. I performed first-principle calculations on the 2D C2N/α-In2Se3 heterostructure, specifically varying the out-of-plane ferroelectric polarization directions. I primarily focused on C2N/α-In2Se3 (I) and C2N/α-In2Se3 (II) heterostructures. Results: My findings revealed that reversing the ferroelectric polarization of the 2D α-In2Se3 layer in the heterostructures led to a transition from the conventional type-II [C2N/α-In2Se3 (I)] to an S-scheme [C2N/α-In2Se3 (II)]. The S-scheme heterostructure [C2N/α-In2Se3 (II)] demonstrated a high optical absorption rate of 17% in visible light, marking it as a promising photocatalytic material. Discussion: This research underscores the significance of ferroelectric polarization in facilitating charge transfer within heterogeneous structures. It provides a theoretical perspective for developing enhanced S-scheme photocatalysts, highlighting the potential of 2D ferroelectric heterostructures in photocatalytic applications.

Development of a Low-Cost Lightweight Advanced K-Band Horn Antenna With Charge-Programmed Deposition 3-D Printing

We present the first development of a lightweight, monolithic, circularly polarized (CP) K-band horn antenna developed using a novel charge-programmed deposition (CPD) manufacturing process. The horn has a polymer body with metalized interior surface. The CPD process creates complex geometries with programmed charged surfaces via three-dimensional (3D) printing and allows the deposition of metallics anywhere within the 3D layout. Intricate internal structures of the horn, such as the meandered waveguide transition and the septum polarizer, were successfully constructed. Measured patterns of the horn demonstrated great agreement with simulations, with an axial ratio below 2.5 dB in the range of 17.5 - 20.5 GHz. The total weight of the horn is only 11 g, marking a significant weight reduction of around 80% compared to traditionally fabricated horns of similar size and operating frequency. The low-cost and lightweight horn antennas enabled by this process can significantly benefit mass- and cost-sensitive applications such as small satellite and CubeSat missions.

M-StruGAN: An Automatic 2D-Plan Generation System under Mixed Structural Constraints for Homestays

Existing methods for generating 2D plans based on intelligent systems usually require human-defined rules, and their operations are complex. GANs can solve these problems through independent research and learning. However, they only have generative design research based on a single constraint condition, and whether they can generate a qualified design scheme under many constraints is still unclear. Therefore, this paper develops the M-StruGAN generative model based on the structural design framework of a GAN. Its application research is extended to the 2D-plan layout generation of homestay based on the constraints of hybrid structures, and the feasibility of the method is comprehensively verified through three aspects: image synthesis quality assessment, scheme rationality assessment, and scheme design quality assessment. Experimental results show that the quality of the drawings generated by M-StruGAN is qualified, designers have a high degree of acceptance of the design results of M-StruGAN, and M-StruGAN completed the learning of the critical points of the 2D layout. Finally, through the human–computer interaction application of M-StruGAN, it can be found that compared with traditional design methods, M-StruGAN based on pix2pixHD has high-definition image quality, higher design efficiency, lower design cost, and more stable design quality.

GeoGraphViz: Geographically constrained 3D force‐directed graph for knowledge graph visualization

AbstractKnowledge graphs are a key technique for linking and integrating cross‐domain data, concepts, tools, and knowledge to enable data‐driven analytics. As much of the world's data have become massive in size, visualizing graph entities and their interrelationships intuitively and interactively has become a crucial task for ingesting and better utilizing graph content to support semantic reasoning, discovering hidden knowledge discovering, and better scientific understanding of geophysical and social phenomena. Despite the fact that many such phenomena (e.g., disasters) have clear spatial footprints and geographic properties, their location information is considered only as a textual label in existing graph visualization tools, limiting their capability to reveal the geospatial distribution patterns of the graph nodes. In addition, most graph visualization techniques rely on 2D graph visualization, which constrains the dimensions of information that can be presented and lacks support for graph structure examination from multiple angles. To tackle the above challenges, we developed a novel 3D map‐based graph visualization algorithm to enable interactive exploration of graph content and patterns in a spatially explicit manner. The algorithm extends a 3D force directed graph by integrating a web map, an additional geolocational force, and a force balancing variable that allows for the dynamic adjustment of the 3D graph structure and layout. This mechanism helps create a balanced graph view between the semantic forces among the graph nodes and the attractive force from a geolocation to a graph node. Our solution offers a new perspective in visualizing and understanding spatial entities and events in a knowledge graph.

Why 2D layout in 3D images matters: evidence from visual search and eyetracking.

Precise perception of three-dimensional (3D) images is crucial for a rewarding experience when using novel displays. However, the capability of the human visual system to perceive binocular disparities varies across the visual field meaning that depth perception might be affected by the two-dimensional (2D) layout of items on the screen. Nevertheless, potential difficulties in perceiving 3D images during free viewing have received only a little attention so far, limiting opportunities to enhance visual effectiveness of information presentation. The aim of this study was to elucidate how the 2D layout of items in 3D images impacts visual search and distribution of maintaining attention based on the analysis of the viewer's gaze. Participants were searching for a target which was projected one plane closer to the viewer compared to distractors on a multi-plane display. The 2D layout of items was manipulated by changing the item distance from the center of the display plane from 2° to 8°. As a result, the targets were identified correctly when the items were displayed close to the center of the display plane, however, the number of errors grew with an increase in distance. Moreover, correct responses were given more often when subjects paid more attention to targets compared to other items on the screen. However, a more balanced distribution of attention over time across all items was characteristic of the incorrectly completed trials. Thus, our results suggest that items should be displayed close to each other in a 2D layout to facilitate precise perception of 3D images and considering distribution of attention maintenance based on eye-tracking might be useful in the objective assessment of user experience for novel displays.

3D Shape‐Morphing Display Enabled by Electrothermally Responsive, Stiffness‐Tunable Liquid Metal Platform with Stretchable Electroluminescent Device

Abstract3D displays are of great interest as next‐generation displays by providing intensified realism of 3D visual information and haptic perception. However, challenges lie in implementing 3D displays due to the limitation of conventional display manufacturing technologies that restrict the dimensional scaling of their forms beyond the 2D layout. Furthermore, on account of the inherent static mechanical properties of constituent materials, the current display form factors can hardly achieve robust and complex 3D structures, thereby hindering their diversity in morphologies and applications. Herein, a versatile shape‐morphing display is presented that can reconfigure its shape into various complex 3D structures through electrothermal operation and firmly maintain its morphed states without power consumption. To achieve this, a shape‐morphing platform, which is composed of a low melting point alloy (LMPA)‐graphene nanoplatelets (GNPs)‐elastomer composite, is integrated with a stretchable electroluminescent (EL) device. The LMPA in the composite, the key material for variable stiffness, imparts shape memory property and forms conductive pathways with GNPs enabling rapid electrothermal actuation. The stretchable EL device provides reliable illumination in 3D shape implementations. Experimental studies and proof‐of‐concept demonstrations show the potential of the shape‐morphing display, opening new opportunities for 3D art displays, transformative wearable electronics, and visio‐tactile automotive interfaces.

Highly Efficient Traffic Planning for Autonomous Vehicles to Cross Intersections Without a Stop

Waiting in a long queue at traffic lights not only wastes valuable time but also pollutes the environment. With the advances in autonomous vehicles and 5G networks, the previous jamming scenarios at intersections may be turned into non-stop weaving traffic flows. Toward this vision, we propose a highly efficient traffic planning system, namely DASHX, which enables connected autonomous vehicles to cross multi-way intersections without a stop. Specifically, DASHX has a comprehensive model to represent intersections and vehicle status. It can constantly process large volumes of vehicle information, resolve scheduling conflicts, and generate optimal travel plans for all vehicles coming toward the intersection in real time. Unlike existing works that are limited to certain types of intersections and lack considerations of practicability, DASHX is universal for any type of 3D intersection and yields the near-maximum throughput while still ensuring riding comfort. To better evaluate the effectiveness of traffic scheduling systems in real-world scenarios, we developed a sophisticated open source 3D traffic simulation platform (DASHX-SIM) that can handle complicated 3D road layouts and simulate vehicles’ networking and decision-making processes. We have conducted extensive experiments, and the experimental results demonstrate the practicality, effectiveness, and efficiency of the DASHX system and the simulator.

Mathematical Model and Simulation for Improving Brake, Bump and Roll Steers in Light Commercial Vehicle (LCV)

Due to recent infrastructural developments and emerging competitive automotive market in India, there is seen a huge shift in customer demand and vehicle drivability pattern for small commercial vehicles. Various factors contributing to driver’s fatigue include driver negligence, inappropriate driving habits and vehicle inherent design error due to which a driver is forced to make frequent steering wheel corrections so as to make the vehicle run in a straight line. Thus, optimization of steering, suspension and front axle geometry becomes important for improving the overall vehicle drivability and reducing the driver fatigue. Mentioned herewith are the major kinematic characteristics in a vehicle which plays vital role for ensuring vehicle improved drivability – Brake steer, Bump steer, Roll steer and Ackerman Geometry. As on today, the above analysis for deriving optimized linkages hard points for steering, suspension and front axle system are done in customized Multi body dynamics software’s like ADAMS/Trucksim. Although the derived hard points in such MBD software’s are precise yet there are several drawbacks in such approach like increase in overall project time plan, mainly due to the vehicle packaging issues for the proposed hard points and also these software customized license and AMC are quite high which increases the overall operating cost of a project. In this paper, an approach has been developed so as to derive these linkages hard points through mathematical calculation and kinematic simulation model in product design Catia platform itself. This helps the designer to derive the optimized hard points of linkages for “n” number of design iterations at the concept stage itself. Thus, this design methodology saves not only on the project design cost but also it reduces the overall product design lifecycle and gives the respective designer to choose the optimum hard point based upon the vehicle packaging feasibility Brake steer, Bump steer, Roll steer, Catia 2D layout, Camber, TCD, Ackermann error.
 

Vulnerable underground entrance understanding for visual surveillance systems

Protecting critical infrastructure through visual surveillance is of vital importance, especially in underground entrance environments where large chunks of sloping glass ceilings are particularly susceptible to various types of terrorist activity. However, owing to the diversity of underground entrance environments, understanding them remains a challenge. Traditional 3D layout and object pose estimation that are evaluated on 3D point clouds or RGB-D data are energy-consuming and difficult to account for semantic information in environments. In this study, we present a methodology to understand underground entrance environments, and to recover their 3D reconstruction from a monocular camera. Clusters of sloping angle projections are extracted. Through their corresponding vanishing points (VPs), surfaces of sloping structures are estimated. Relative geometric constraints of different planes are built to bridge the gap between 2D sloping surfaces and 3D reconstruction without precise depth or point clouds. An underground entrance scene is approximated by Manhattan and sloping non-Manhattan structures in 3D reconstruction. The approach requires no prior training, and it requires neither the camera being calibrated nor the camera internal parameters being constant. Compared to the ground truth, the percentage of incorrectly understood pixels were measured and the results demonstrated that the method can successfully understand underground entrance scenes, meeting the requirements in safety monitoring for critical infrastructures from a resource-constrained surveillance camera.

Nonlinear Dielectric Nanoresonators and Metasurfaces: Toward Efficient Generation of Entangled Photons

AbstractAmong the most prominent effects resulting from nonlinear light–matter interaction is the generation of correlated and entangled photons through various processes, notably via spontaneous parametric down‐conversion or spontaneous four‐wave mixing. Such nonlinear optical processes benefit from the concentration of electromagnetic fields in small volumes. Dielectric nanoresonators and their 2D layouts—metasurfaces—provide efficient ways to control light in subwavelength volumes enabling the enhancement of nonlinear light–matter interaction and the generation of entangled photons. Nanoresonators and metasurfaces offer a radical miniaturization of quantum light sources allowing better scalability, which opens a pathway toward arrangements of photon sources in complex subwavelength configurations for advanced photon state control. In this work, the recent progress in this emergent area of research is reviewed.

3D layout estimation of general rooms based on ordinal semantic segmentation

AbstractRoom layout estimation aims to predict the location and range of layout planes of interior spaces. Previous works treat each layout plane as an independent individual without considering the ordinal relation between walls, resulting the loss of the wall planes and the lack of integrity. This paper proposes a novel two‐branch neural networks model to estimate 3D layouts of cuboid and non‐cuboid room types. The model embeds the ordinal relation between layout planes into the layout segmentation branch through an proposed ordinal classification loss function, and outputs both pixel‐level layout segmentation maps and layout plane parameter maps. Then, the instance‐level plane parameters of each layout plane are determined by using an instance‐aware pooling layer. Finally, the sharpness of layout edges of the 2D layout semantic segmentation map is optimized by using an improved depth map intersection algorithm. Furthermore, we annotate a large‐scale 3D room layout estimation dataset, InteriorNet‐Layout, to obtain a steady model. Experiments on synthesized real‐world datasets show that the proposed method achieves faster calculation while maintaining high accuracy. Code is available at https://github.com/Hui‐Yao/3D‐ordinal‐layout‐estimation.

Performance enhancement in thermally activated delayed fluorescence emitters by multi-fold layout

A series of thermally activated delayed fluorescence (TADF) materials, namely o-Ac2BBP, o-Px2BBP, D-BP-DMAC and D-BP-PXZ, were designed with double acridine (DMAC) or phenoxazine (PXZ) donors and double carbonyl acceptors. Phenylene and biphenylene were selected as the central bridges for these emitters, and each benzene ring on the central bridge was substituted at ortho-sites. The biphenylene bridge based D-BP-DMAC and D-BP-PXZ show 3D dimensional non-planar conformations and multi-fold layout, which result in multiple intramolecular interactions including C–H⋯O hydrogen bonds and C–H···π interactions and finally strongly stabilized and rigidified the whole molecular structures by locking the molecular geometry. As a result, the nonradiative transition rates (knr) were effectively suppressed by 5 times in comparison with the corresponding phenylene bridged analogues, and the photoluminescence quantum yields were increased to over 95%. The green and yellow OLEDs with D-BP-DMAC and D-BP-PXZ as doped emitters exhibited the maximum external quantum efficiencies (EQE) of 24.3% and 17.3%, which are almost double of the corresponding values (13.1% and 9.3%) of the phenylene bridged analogues o-Ac2BBP and o-Px2BBP. These results indicate that to increase molecular rigidity by multi-fold-layout is an effective design strategy to enhance the performance of TADF materials and OLEDs.

Towards characterizing of Enterocytozoon hepatopenaei (EHP) spore wall proteins with feature identification and analogy modeling

Enterocytozoon hepatopenaei (EHP) is a parasite that mostly affects shrimp; it is linked to spore-forming and obligatory intracellular microsporidia and causes growth retardation and body length fluctuation, which results in financial consequences for the shrimp industry in Asian nations. However, the introduction of technologies to detect EHP has been complicated by the absence of a thorough knowledge of the properties of spore wall proteins (SWPs) linked to host infection. Thus, characterization, feature identification, 3D modeling of protein sequence, prediction of transmembrane regions, motif analysis, as well as model validation of SWPs can help improve drug delivery in the future. Conservation analysis was performed using ClustalW. InterPro, MEMEsuite, and TMHMM Server v2.0 were used to perform motif analysis, family domain prognosis, and transmembrane region analysis, respectively. Finally, the Alphafold2 server was used for analogy modeling and 3D layout. Different model validation servers were used to validate the protein structural model. Physicochemical features for SWPs were analyzed and found molecular weight around 16.701 KDa-38.314 KDa, theoretical pI 5.25–9.05, instability index 32.04–48.89, aliphatic index 76.49–99.84, grand average of hydropathicity (GRAVY) – 0.059 to −0.892. Each SWP was discovered to be hydrophilic. There was no significant region detected in the conserved region analysis. Both a lower and higher E value were found by the motif analysis. For most of the proteins, there were no transmembrane regions. Finally, analogous 3D models for each protein were created and verified using various bioinformatics tools and software. This investigation could aid in the further research of diseases and the development of drug delivery systems.

3D layout of the Spidergon-Donut on-chip interconnection network

3D layout of the Spidergon-Donut on-chip interconnection network

Layout planning and analysis of a Flexible Manufacturing System based on 3D Simulation and Virtual Reality

The high competition in the global market where the agile product launch and variable demand of goods by customers persuaded manufacturing companies to adopt Flexible Manufacturing System (FMS) and many companies have already implemented FMS solutions. On the other hand, manufacturing digitalization such as digital twin development, Industrial Virtual Reality (IVR), virtual modeling and 3D simulation of manufacturing systems offer new possibilities for effective facility layout planning, quick and easy modification and validation of production processes, analysis, and optimize the workflow and activities conducted on a factory floor. These new technological developments in digitalization have changed the thinking of manufacturing companies and they are eager to use digitalization solutions in their factory operations. However, there is a lack of harmonized methods and procedures to implement virtual modeling, 3D simulation, and IVR for layout planning and analysis of FMS. This paper proposed an approach for performance analysis of a FMS that is based on the 3D layout creation and simulation in a virtual environment, monitoring of key performance indicators via a digital dashboard, and immersive visualization through virtual reality. The relevance and feasibility of the proposed performance analysis approach are demonstrated by a case study.