11,297 research outputs found
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution
Plateau-reduced Differentiable Path Tracing
Current differentiable renderers provide light transport gradients with
respect to arbitrary scene parameters. However, the mere existence of these
gradients does not guarantee useful update steps in an optimization. Instead,
inverse rendering might not converge due to inherent plateaus, i.e., regions of
zero gradient, in the objective function. We propose to alleviate this by
convolving the high-dimensional rendering function that maps scene parameters
to images with an additional kernel that blurs the parameter space. We describe
two Monte Carlo estimators to compute plateau-free gradients efficiently, i.e.,
with low variance, and show that these translate into net-gains in optimization
error and runtime performance. Our approach is a straightforward extension to
both black-box and differentiable renderers and enables optimization of
problems with intricate light transport, such as caustics or global
illumination, that existing differentiable renderers do not converge on.Comment: Accepted to CVPR 2023. Project page and interactive demos at
https://mfischer-ucl.github.io/prdpt
Deep Learning for Scene Flow Estimation on Point Clouds: A Survey and Prospective Trends
Aiming at obtaining structural information and 3D motion of dynamic scenes, scene flow estimation has been an interest of research in computer vision and computer graphics for a long time. It is also a fundamental task for various applications such as autonomous driving. Compared to previous methods that utilize image representations, many recent researches build upon the power of deep analysis and focus on point clouds representation to conduct 3D flow estimation. This paper comprehensively reviews the pioneering literature in scene flow estimation based on point clouds. Meanwhile, it delves into detail in learning paradigms and presents insightful comparisons between the state-of-the-art methods using deep learning for scene flow estimation. Furthermore, this paper investigates various higher-level scene understanding tasks, including object tracking, motion segmentation, etc. and concludes with an overview of foreseeable research trends for scene flow estimation
Kirchhoff-Love shell representation and analysis using triangle configuration B-splines
This paper presents the application of triangle configuration B-splines
(TCB-splines) for representing and analyzing the Kirchhoff-Love shell in the
context of isogeometric analysis (IGA). The Kirchhoff-Love shell formulation
requires global -continuous basis functions. The nonuniform rational
B-spline (NURBS)-based IGA has been extensively used for developing
Kirchhoff-Love shell elements. However, shells with complex geometries
inevitably need multiple patches and trimming techniques, where stitching
patches with high continuity is a challenge. On the other hand, due to their
unstructured nature, TCB-splines can accommodate general polygonal domains,
have local refinement, and are flexible to model complex geometries with
continuity, which naturally fit into the Kirchhoff-Love shell formulation with
complex geometries. Therefore, we propose to use TCB-splines as basis functions
for geometric representation and solution approximation. We apply our method to
both linear and nonlinear benchmark shell problems, where the accuracy and
robustness are validated. The applicability of the proposed approach to shell
analysis is further exemplified by performing geometrically nonlinear
Kirchhoff-Love shell simulations of a pipe junction and a front bumper
represented by a single patch of TCB-splines
A Finite Element-Inspired Hypergraph Neural Network: Application to Fluid Dynamics Simulations
An emerging trend in deep learning research focuses on the applications of
graph neural networks (GNNs) for mesh-based continuum mechanics simulations.
Most of these learning frameworks operate on graphs wherein each edge connects
two nodes. Inspired by the data connectivity in the finite element method, we
present a method to construct a hypergraph by connecting the nodes by elements
rather than edges. A hypergraph message-passing network is defined on such a
node-element hypergraph that mimics the calculation process of local stiffness
matrices. We term this method a finite element-inspired hypergraph neural
network, in short FEIH()-GNN. We further equip the proposed network with
rotation equivariance, and explore its capability for modeling unsteady fluid
flow systems. The effectiveness of the network is demonstrated on two common
benchmark problems, namely the fluid flow around a circular cylinder and
airfoil configurations. Stabilized and accurate temporal roll-out predictions
can be obtained using the -GNN framework within the interpolation
Reynolds number range. The network is also able to extrapolate moderately
towards higher Reynolds number domain out of the training range
FiabilitĂ© de lâunderfill et estimation de la durĂ©e de vie dâassemblages microĂ©lectroniques
Abstract : In order to protect the interconnections in flip-chip packages, an underfill material layer
is used to fill the volumes and provide mechanical support between the silicon chip and
the substrate. Due to the chip corner geometry and the mismatch of coefficient of thermal
expansion (CTE), the underfill suffers from a stress concentration at the chip corners when
the temperature is lower than the curing temperature. This stress concentration leads
to subsequent mechanical failures in flip-chip packages, such as chip-underfill interfacial
delamination and underfill cracking. Local stresses and strains are the most important
parameters for understanding the mechanism of underfill failures. As a result, the industry
currently relies on the finite element method (FEM) to calculate the stress components, but
the FEM may not be accurate enough compared to the actual stresses in underfill. FEM
simulations require a careful consideration of important geometrical details and material
properties. This thesis proposes a modeling approach that can accurately estimate the underfill delamination
areas and crack trajectories, with the following three objectives. The first
objective was to develop an experimental technique capable of measuring underfill deformations
around the chip corner region. This technique combined confocal microscopy and
the digital image correlation (DIC) method to enable tri-dimensional strain measurements
at different temperatures, and was named the confocal-DIC technique. This techique was
first validated by a theoretical analysis on thermal strains. In a test component similar
to a flip-chip package, the strain distribution obtained by the FEM model was in good
agreement with the results measured by the confocal-DIC technique, with relative errors
less than 20% at chip corners. Then, the second objective was to measure the strain near
a crack in underfills. Artificial cracks with lengths of 160 ÎŒm and 640 ÎŒm were fabricated
from the chip corner along the 45° diagonal direction. The confocal-DIC-measured
maximum hoop strains and first principal strains were located at the crack front area for
both the 160 ÎŒm and 640 ÎŒm cracks. A crack model was developed using the extended
finite element method (XFEM), and the strain distribution in the simulation had the same
trend as the experimental results. The distribution of hoop strains were in good agreement
with the measured values, when the model element size was smaller than 22 ÎŒm to
capture the strong strain gradient near the crack tip. The third objective was to propose
a modeling approach for underfill delamination and cracking with the effects of manufacturing
variables. A deep thermal cycling test was performed on 13 test cells to obtain the
reference chip-underfill delamination areas and crack profiles. An artificial neural network
(ANN) was trained to relate the effects of manufacturing variables and the number of
cycles to first delamination of each cell. The predicted numbers of cycles for all 6 cells in
the test dataset were located in the intervals of experimental observations. The growth
of delamination was carried out on FEM by evaluating the strain energy amplitude at
the interface elements between the chip and underfill. For 5 out of 6 cells in validation,
the delamination growth model was consistent with the experimental observations. The
cracks in bulk underfill were modelled by XFEM without predefined paths. The directions of edge cracks were in good agreement with the experimental observations, with an error
of less than 2.5°. This approach met the goal of the thesis of estimating the underfill
initial delamination, areas of delamination and crack paths in actual industrial flip-chip
assemblies.Afin de protĂ©ger les interconnexions dans les assemblages, une couche de matĂ©riau dâunderfill est utilisĂ©e pour remplir le volume et fournir un support mĂ©canique entre la puce de silicium et le substrat. En raison de la gĂ©omĂ©trie du coin de puce et de lâĂ©cart du coefficient de dilatation thermique (CTE), lâunderfill souffre dâune concentration de contraintes dans les coins lorsque la tempĂ©rature est infĂ©rieure Ă la tempĂ©rature de cuisson. Cette concentration de contraintes conduit Ă des dĂ©faillances mĂ©caniques dans les encapsulations de flip-chip, telles que la dĂ©lamination interfaciale puce-underfill et la fissuration dâunderfill. Les contraintes et dĂ©formations locales sont les paramĂštres les plus importants pour comprendre le mĂ©canisme des ruptures de lâunderfill. En consĂ©quent, lâindustrie utilise actuellement la mĂ©thode des Ă©lĂ©ments finis (EF) pour calculer les composantes de la contrainte, qui ne sont pas assez prĂ©cises par rapport aux contraintes actuelles dans lâunderfill. Ces simulations nĂ©cessitent un examen minutieux de dĂ©tails gĂ©omĂ©triques importants et des propriĂ©tĂ©s des matĂ©riaux. Cette thĂšse vise Ă proposer une approche de modĂ©lisation permettant dâestimer avec prĂ©cision les zones de dĂ©lamination et les trajectoires des fissures dans lâunderfill, avec les trois objectifs suivants. Le premier objectif est de mettre au point une technique expĂ©rimentale capable de mesurer la dĂ©formation de lâunderfill dans la rĂ©gion du coin de puce. Cette technique, combine la microscopie confocale et la mĂ©thode de corrĂ©lation des images numĂ©riques (DIC) pour permettre des mesures tridimensionnelles des dĂ©formations Ă diffĂ©rentes tempĂ©ratures, et a Ă©tĂ© nommĂ©e le technique confocale-DIC. Cette technique a dâabord Ă©tĂ© validĂ©e par une analyse thĂ©orique en dĂ©formation thermique. Dans un Ă©chantillon similaire Ă un flip-chip, la distribution de la dĂ©formation obtenues par le modĂšle EF Ă©tait en bon accord avec les rĂ©sultats de la technique confocal-DIC, avec des erreurs relatives infĂ©rieures Ă 20% au coin de puce. Ensuite, le second objectif est de mesurer la dĂ©formation autour dâune fissure dans lâunderfill. Des fissures artificielles dâune longueuer de 160 ÎŒm et 640 ÎŒm ont Ă©tĂ© fabriquĂ©es dans lâunderfill vers la direction diagonale de 45°. Les dĂ©formations circonfĂ©rentielles maximales et principale maximale Ă©taient situĂ©es aux pointes des fissures correspondantes. Un modĂšle de fissure a Ă©tĂ© dĂ©veloppĂ© en utilisant la mĂ©thode des Ă©lĂ©ments finis Ă©tendue (XFEM), et la distribution des contraintes dans la simuation a montrĂ© la mĂȘme tendance que les rĂ©sultats expĂ©rimentaux. La distribution des dĂ©formations circonfĂ©rentielles maximales Ă©tait en bon accord avec les valeurs mesurĂ©es lorsque la taille des Ă©lĂ©ments Ă©tait plus petite que 22 ÎŒm, assez petit pour capturer le grand gradient de dĂ©formation prĂšs de la pointe de fissure. Le troisiĂšme objectif Ă©tait dâapporter une approche de modĂ©lisation de la dĂ©lamination et de la fissuration de lâunderfill avec les effets des variables de fabrication. Un test de cyclage thermique a dâabord Ă©tĂ© effectuĂ© sur 13 cellules pour obtenir les zones dĂ©laminĂ©es entre la puce et lâunderfill, et les profils de fissures dans lâunderfill, comme rĂ©fĂ©rence. Un rĂ©seau neuronal artificiel (ANN) a Ă©tĂ© formĂ© pour Ă©tablir une liaison entre les effets des variables de fabrication et le nombre de cycles Ă la dĂ©lamination pour chaque cellule. Les nombres de cycles prĂ©dits pour les 6 cellules de lâensemble de test Ă©taient situĂ©s dans les intervalles dâobservations expĂ©rimentaux. La croissance de la dĂ©lamination a Ă©tĂ© rĂ©alisĂ©e par lâEF en Ă©valuant lâĂ©nergie de la dĂ©formation au niveau des Ă©lĂ©ments interfaciaux entre la puce et lâunderfill. Pour 5 des 6 cellules de la validation, le modĂšle de croissance du dĂ©laminage Ă©tait conforme aux observations expĂ©rimentales. Les fissures dans lâunderfill ont Ă©tĂ© modĂ©lisĂ©es par XFEM sans chemins prĂ©dĂ©finis. Les directions des fissures de bord Ă©taient en bon accord avec les observations expĂ©rimentales, avec une erreur infĂ©rieure Ă 2,5°. Cette approche a rĂ©pondu Ă la problĂ©matique qui consiste Ă estimer lâinitiation des dĂ©lamination, les zones de dĂ©lamination et les trajectoires de fissures dans lâunderfill pour des flip-chips industriels
Structure and adsorption properties of gas-ionic liquid interfaces
Supported ionic liquids are a diverse class of materials that have been considered
as a promising approach to design new surface properties within solids for gas
adsorption and separation applications. In these materials, the surface morphology and
composition of a porous solid are modified by depositing ionic liquid. The resulting
materials exhibit a unique combination of structural and gas adsorption properties
arising from both components, the support, and the liquid. Naturally, theoretical and
experimental studies devoted to understanding the underlying principles of exhibited
interfacial properties have been an intense area of research. However, a complete
understanding of the interplay between interfacial gas-liquid and liquid-solid
interactions as well as molecular details of these processes remains elusive.
The proposed problem is challenging and in this thesis, it is approached from
two different perspectives applying computational and experimental techniques. In
particular, molecular dynamics simulations are used to model gas adsorption in films
of ionic liquids on a molecular level. A detailed description of the modeled systems is
possible if the interfacial and bulk properties of ionic liquid films are separated. In this
study, we use a unique method that recognizes the interfacial and bulk structures of
ionic liquids and distinguishes gas adsorption from gas solubility. By combining
classical nitrogen sorption experiments with a mean-field theory, we study how liquid-solid interactions influence the adsorption of ionic liquids on the surface of the porous
support.
The developed approach was applied to a range of ionic liquids that feature
different interaction behavior with gas and porous support. Using molecular
simulations with interfacial analysis, it was discovered that gas adsorption capacity
can be directly related to gas solubility data, allowing the development of a predictive
model for the gas adsorption performance of ionic liquid films. Furthermore, it was
found that this CO2 adsorption on the surface of ionic liquid films is determined by the
specific arrangement of cations and anions on the surface. A particularly important
result is that, for the first time, a quantitative relation between these structural and
adsorption properties of different ionic liquid films has been established. This link
between two types of properties determines design principles for supported ionic
liquids.
However, the proposed predictive model and design principles rely on the
assumption that the ionic liquid is uniformly distributed on the surface of the porous
support. To test how ionic liquids behave under confinement, nitrogen physisorption
experiments were conducted for microâ and mesopore analysis of supported ionic
liquid materials. In conjunction with mean-field density functional theory applied to
the lattice gas and pore models, we revealed different scenarios for the pore-filling
mechanism depending on the strength of the liquid-solid interactions.
In this thesis, a combination of computational and experimental studies provides
a framework for the characterization of complex interfacial gas-liquid and liquid-solid
processes. It is shown that interfacial analysis is a powerful tool for studying
molecular-level interactions between different phases. Finally, nitrogen sorption
experiments were effectively used to obtain information on the structure of supported
ionic liquids
Rational maps with smooth degenerate Herman rings
We prove the existence of rational maps having smooth degenerate Herman
rings. This answers a question of Eremenko affirmatively. The proof is based on
the construction of smooth Siegel disks by Avila, Buff and Ch\'{e}ritat as well
as the classical Siegel-to-Herman quasiconformal surgery. A crucial ingredient
in the proof is the surgery's continuity, which relies on the control of the
loss of the area of quadratic filled-in Julia sets by Buff and Ch\'{e}ritat.
As a by-product, we prove the existence of rational maps having a nowhere
dense Julia set of positive area for which these maps have no irrationally
indifferent periodic points, no Herman rings, and are not renormalizable.Comment: 29 pages, 3 figure
Elasto-plastic deformations within a material point framework on modern GPU architectures
Plastic strain localization is an important process on Earth. It strongly influ- ences the mechanical behaviour of natural processes, such as fault mechanics, earthquakes or orogeny. At a smaller scale, a landslide is a fantastic example of elasto-plastic deformations. Such behaviour spans from pre-failure mech- anisms to post-failure propagation of the unstable material. To fully resolve the landslide mechanics, the selected numerical methods should be able to efficiently address a wide range of deformation magnitudes.
Accurate and performant numerical modelling requires important compu- tational resources. Mesh-free numerical methods such as the material point method (MPM) or the smoothed-particle hydrodynamics (SPH) are particu- larly computationally expensive, when compared with mesh-based methods, such as the finite element method (FEM) or the finite difference method (FDM). Still, mesh-free methods are particularly well-suited to numerical problems involving large elasto-plastic deformations. But, the computational efficiency of these methods should be first improved in order to tackle complex three-dimensional problems, i.e., landslides.
As such, this research work attempts to alleviate the computational cost of the material point method by using the most recent graphics processing unit (GPU) architectures available. GPUs are many-core processors originally designed to refresh screen pixels (e.g., for computer games) independently. This allows GPUs to delivers a massive parallelism when compared to central processing units (CPUs).
To do so, this research work first investigates code prototyping in a high- level language, e.g., MATLAB. This allows to implement vectorized algorithms and benchmark numerical results of two-dimensional analysis with analytical solutions and/or experimental results in an affordable amount of time. After- wards, low-level language such as CUDA C is used to efficiently implement a GPU-based solver, i.e., ep2-3De v1.0, can resolve three-dimensional prob- lems in a decent amount of time. This part takes advantages of the massive parallelism of modern GPU architectures. In addition, a first attempt of GPU parallel computing, i.e., multi-GPU codes, is performed to increase even more the performance and to address the on-chip memory limitation. Finally, this GPU-based solver is used to investigate three-dimensional granular collapses and is compared with experimental evidences obtained in the laboratory.
This research work demonstrates that the material point method is well suited to resolve small to large elasto-plastic deformations. Moreover, the computational efficiency of the method can be dramatically increased using modern GPU architectures. These allow fast, performant and accurate three- dimensional modelling of landslides, provided that the on-chip memory limi- tation is alleviated with an appropriate parallel strategy
- âŠ