arXiv subjects

Qiang Zou

Publications and source records attributed to Qiang Zou.

At least 55 records · Page 3Linked to original sources

arXiv2022

Towards computing complete parameter ranges in parametric modeling

In parametric design, the geometric model is edited by changing relevant parameters in the parametric model, which is commonly done sequentially on multiple parameters. Without guidance on allowable parameter ranges that can guarantee the solvability of the geometric constraint system, the user could assign improper parameter values to the model's parameters, which would further lead to a failure in model updating. However, current commercial CAD systems provide little support for the proper parameter assignments. Although the existing methods can compute allowable ranges for individual parameters, they face difficulties in handling multi-parameter situations. In particular, these methods could miss some feasible parameter values and provide incomplete allowable parameter ranges. To solve this problem, an automatic approach is proposed in this paper to compute complete parameter ranges in multi-parameter editing. In the approach, a set of variable parameters are first selected to be sequentially edited by the user; before each editing operation, the one-dimensional ranges of the variable parameters are presented as guidance. To compute the one-dimensional ranges, each variable parameter is expressed as an equality-constrained function, and its one-dimensional allowable range is obtained by calculating the function range. To effectively obtain the function range which can hardly be calculated in a normal way, the function range problem is converted into a constrained optimization problem, and is then solved by Lagrange multiplier method and the Niching particle swarm optimization algorithm (the NichePSO). The effectiveness and efficiency of the proposed approach is verified by several experimental results.

cs.GR↗

arXiv2022

Variational design for a structural family of CAD models

Variational design is a well-recognized CAD technique due to the increased design efficiency. It often presents as a parametric family of CAD models. Although effective, this way of working cannot handle design requirements that go beyond parametric changes. Such design requirements are not uncommon today due to the increasing popularity of product customization. In particular, there is often a need for designing a new model out of an existing structural family of models, which share a structural pattern but have individually varied detail features. To facilitate such design requirements, a new method is presented in this paper. The idea is to express the underlying structural pattern in terms of a submodel composed of the maximum common design features of the family, and then to build a single master model by attaching to the submodel all detail design features in the family. This master model is a representative model for the family and contains all the features. By removing unwanted detail features and adding new features, the master model can be easily adapted into a new design, while keeping aligned with the family, structurally. Effectiveness of this method has been validated by a series of case studies and comparisons of increasing complexity.

stat.ME↗

arXiv2021

Competitive and Cooperative electronic states in Ba(Fe$_{1-x}$T$_x$)$_2$As$_2$ with T=Co, Ni, Cr

The electronic structure inhomogeneities in Co, Ni, and Cr doped BaFe2As2 122 single crystals are compared using scanning tunneling microscopy/spectroscopy (STM/S) at the nanoscale within three bulk property regions in the phase diagram: a pure superconducting (SC) dome region (Co-122), a coexisting SC and antiferromagnetic (AFM) region (Ni-122), and a non-SC region (Cr-122). Machine learning is utilized to categorize the various nanometer scale inhomogeneous electronic states, described here as in-gap, L-shape and S-shape states immersed into the SC matrix for Ni-and Co-doped 122, and L-shape and S-shape states into the metallic matrix for Cr-doped 122. Although the relative percentages of in-gap, L-shape and S-shape states vary in the three samples, the total volume fraction of the three electronic states is quite similar. This is coincident with the number of electrons (Ni0.04 and Co0.08) and holes (Cr0.04) doped into the 122 compound. By combining the volume fractions of the three states, the local density of states (LDOS), magnetic field dependent behavior and global properties in these three samples, the in-gap state is confirmed as a magnetic impurity state from the Co or Ni dopants. In addition, the L-shape state is identified as a spin density wave (SDW) which competes with the SC phase, and the S-shape state is found to be another form of magnetic order which constructively cooperates with the SC phase, rather than competing with it. The comparison of the vortex structures indicates that the inhomogeneous electronic states serve as pinning centers for stabilizing the vortex lattice.

cond-mat.supr-con↗

arXiv2021

Revealing the chemical bonding in adatoms arrays via machine learning of 3D scanning tunneling spectroscopy data

The adatom arrays on surfaces offer an ideal playground to explore the mechanisms of chemical bonding via changes in the local electronic tunneling spectra. While this information is readily available in hyperspectral scanning tunneling spectroscopy data, its analysis has been considerably impeded by a lack of suitable analytical tools. Here we develop a machine learning based workflow combining supervised feature identification in the spatial domain and un-supervised clustering in the energy domain to reveal the details of structure-dependent changes of the electronic structure in adatom arrays on the Co3Sn2S2 cleaved surface. This approach, in combination with first-principles calculations, provides insight for using artificial neural networks to detect adatoms and classifies each based on their local neighborhood comprised of other adatoms. These structurally classified adatoms are further spectrally deconvolved. The unexpected inhomogeneity of electronic structures among adatoms in similar configurations is unveiled using this method, suggesting there is not a single atomic species of adatoms, but rather multiple types of adatoms on the Co3Sn2S2 surface. This is further supported by a slight contrast difference in the images (or slight size variation) of the topography of the adatoms.

cond-mat.mtrl-sci↗

arXiv2021

Memory-Efficient Modeling and Slicing of Large-Scale Adaptive Lattice Structures

Lattice structures have been widely used in various applications of additive manufacturing due to its superior physical properties. If modeled by triangular meshes, a lattice structure with huge number of struts would consume massive memory. This hinders the use of lattice structures in large-scale applications (e.g., to design the interior structure of a solid with spatially graded material properties). To solve this issue, we propose a memory-efficient method for the modeling and slicing of adaptive lattice structures. A lattice structure is represented by a weighted graph where the edge weights store the struts' radii. When slicing the structure, its solid model is locally evaluated through convolution surfaces and in a streaming manner. As such, only limited memory is needed to generate the toolpaths of fabrication. Also, the use of convolution surfaces leads to natural blending at intersections of struts, which can avoid the stress concentration at these regions. We also present a computational framework for optimizing supporting structures and adapting lattice structures with prescribed density distributions. The presented methods have been validated by a series of case studies with large number (up to 100M) of struts to demonstrate its applicability to large-scale lattice structures.

cs.CG↗

arXiv2020

Bayesian learning of adatom interactions from atomically-resolved imaging data

Atomic structures and adatom geometries of surfaces encode information about the thermodynamics and kinetics of the processes that lead to their formation, and which can be captured by a generative physical model. Here we develop a workflow based on a machine learning-based analysis of scanning tunneling microscopy images to reconstruct the atomic and adatom positions, and a Bayesian optimization procedure to minimize statistical distance between the chosen physical models and experimental observations. We optimize the parameters of a 2- and 3-parameter Ising model describing surface ordering and use the derived generative model to make predictions across the parameter space. For concentration dependence, we compare the predicted morphologies at different adatom concentrations with the dissimilar regions on the sample surfaces that serendipitously had different adatom concentrations. The proposed workflow is universal and can be used to reconstruct the thermodynamic models and associated uncertainties from the experimental observations of materials microstructures. The code used in the manuscript is available at https://github.com/saimani5/Adatom_interactions.

cond-mat.mtrl-sci↗

arXiv2020

Length-optimal tool path planning for freeform surfaces with preferred feed directions

This paper presents a new method to generate tool paths for machining freeform surfaces represented either as parametric surfaces or as triangular meshes. This method allows for the optimal tradeoff between the preferred feed direction field and the constant scallop height, and yields a minimized overall path length. The optimality is achieved by formulating tool path planning as a Poisson problem that minimizes a simple, quadratic energy. This Poisson formulation considers all tool paths at once, without resorting to any heuristic sampling or initial tool path choosing as in existing methods, and is thus a globally optimal solution. Finding the optimal tool paths amounts to solving a well-conditioned sparse linear system, which is computationally convenient and efficient. Tool paths are represented with an implicit scheme that can completely avoid the challenging topological issues of path singularities and self-intersections seen in previous methods. The presented method has been validated with a series of examples and comparisons.

cs.GR↗

arXiv2020

Robust and efficient tool path generation for poor-quality triangular mesh surface machining

This paper presents a new method to generate iso-scallop tool paths for triangular mesh surfaces. With the popularity of 3D scanning techniques, scanning-derived mesh surfaces have seen a significant increase in their application to machining. Quite often, such mesh surfaces exhibit defects such as noises, which differentiate them from the good-quality mesh surfaces previous research work focuses on. To generate tool paths for such poor-quality mesh surfaces, the primary challenge lies in robustness against the defects. In this work, a robust tool path generation method is proposed for poor-quality mesh surfaces. In addition to robustness, the method is quite efficient, providing the benefit of faster iterations and improved integration between scanning and machining. The fundamental principle of the method is to convert the tool path generation problem to the heat diffusion problem that has robust and efficient algorithms available. The effectiveness of the method will be demonstrated by a series of case studies and comparisons.

cs.GR↗

arXiv2020

A robust direct modeling method for quadric B-rep models based on geometry-topology inconsistency tracking

Boundary representation (B-rep) model editing plays an essential role in computer-aided design and motivates the very recent direct modeling paradigm, which features intuitive push-pull manipulation of the model geometry. In mechanical design, a substantial part of B-rep models being used are quadric models (composed of linear and quadric surfaces). However, push-pulling such models is not trivial due to the possible smooth face-face connections in the models. The major issue is that, during push-pull moves, it is often desirable to preserve these connections for functional, manufacturing, or aesthetic reasons, but this could cause complex inconsistencies between the geometry and topology in the model and lead to robustness issues in updating the model. The challenge lies in effectiveness towards detecting the instants when geometry-topology inconsistencies occur during push-pull moves. This paper proposes a novel reverse detection method to solve the challenge and then, based on it, presents a robust method for push-pull direct modeling while preserving smooth connections. Case studies and comparisons have been conducted to demonstrate the effectiveness of the method.

cs.CG↗

arXiv2019

Local Superconductivity in Vanadium Iron Arsenide

We investigate the chemical substitution of group 5 into BaFe2As2 (122) iron arsenide, in the effort to understand why Fe-site hole doping of this compound (e.g., using group 5 or 6) does not yield bulk superconductivity. We find an increase in c-lattice parameter of the BaFe2As2 with the substitution of V, Nb, or Ta; the reduction in c predicts the lack of bulk superconductivity [1] that is confirmed here through transport and magnetization results. However, our spectroscopy measurements find a coexistence of antiferromagnetic and local superconducting nanoscale regions in V-122, observed for the first time in a transition-metal hole-doped iron arsenide. In BaFe2As2, there is a complex connection between local parameters such as composition and lattice strain, average lattice details, and the emergence of bulk quantum states such as superconductivity and magnetism. [1] L. M. N. Konzen, and A. S. Sefat, J. Phys.: Condens. Matter 29 (2017), 083001.

cond-mat.supr-con↗

arXiv2019

On Limitations of the Witness Configuration Method for Geometric Constraint Solving in CAD Modeling

This paper presents discussions on the limitations of the witness configuration method. These limitations have rarely been reported in previous studies. The witness configuration method is a very recent approach for geometric constraint solving, which is of critical importance for modern computer-aided design systems. The witness configuration method may be the most promising method to solve satisfactorily the challenges of geometric constraint solving. This method, in the current form, is however found to be limited for the three essential tasks in the geometric constraint solving domain. Examples are given to validate this work's statements on these limitations.

cs.CG↗

arXiv2019

A decision-support method for information inconsistency resolution in direct modeling of CAD models

Direct modeling is a very recent CAD paradigm that can provide unprecedented modeling flexibility. It, however, lacks the parametric capability, which is indispensable to modern CAD systems. For direct modeling to have this capability, an additional associativity information layer in the form of geometric constraint systems needs to be incorporated into direct modeling. This is no trivial matter due to the possible inconsistencies between the associativity information and geometry information in a model after direct edits. The major issue of resolving such inconsistencies is that there often exist many resolution options. The challenge lies in avoiding invalid resolution options and prioritizing valid ones. This paper presents an effective method to support the user in making decisions among the resolution options. In particular, the method can provide automatic information inconsistency reasoning, avoid invalid resolution options completely, and guide the choice among valid resolution options. Case studies and comparisons have been conducted to demonstrate the effectiveness of the method.

cs.CG↗

arXiv2019

An Air-Stable and Atomically Thin Graphene/Gallium Superconducting Heterostructure

Two-dimensional layered and atomically thin elemental superconductors may be key ingredients in next-generation quantum technologies, if they can be stabilized and integrated into heterostructured devices under ambient conditions. However, atomically thin elemental superconductors are largely unexplored outside ultra-high vacuum due to rapid oxidation, and even 2D layered superconductors require complex encapsulation strategies to maintain material quality. Here we demonstrate environmentally stable, single-crystal, few-atom-thick superconducting gallium, 2D-Ga, produced by confinement heteroepitaxy (CHet) at the interface of epitaxial graphene (EG) and silicon carbide (SiC). 2D-Ga becomes superconducting at 4 K; this elevation over bulk alpha-Ga (Tc~1 K) is primarily attributed to an increased density of states at the Fermi level as the incipient Ga-Ga dimerization seen in alpha-Ga is suppressed by epitaxy to SiC. We also demonstrate the importance of controlling SiC surface morphology (i.e. step height) and defect-engineering in graphene layers prior to intercalation to achieve large-area uniform 2D-Ga layers with isotropic transport properties. This work demonstrates that unique 2D forms of 3D materials can be stabilized at the EG/SiC interface, which represents a scalable route towards air-stable crystalline 2D superconductors as a potential foundation for next-generation quantum technologies.

cond-mat.supr-con↗

arXiv2019

Lattice Disorder Effect on Magnetic Ordering of Iron Arsenides

This study investigates the changes of magnetic ordering temperature via nano- and mesoscale structural features in an iron arsenide. Although magnetic ground states in quantum materials can be theoretically predicted from known crystal structures and chemical compositions, the ordering temperature is harder to pinpoint due to such local lattice variations. In this work we find surprisingly that a locally disordered material can exhibit a significantly larger Neel temperature (TN) than an ordered material of precisely the same chemical stoichiometry. Here, a EuFe2As2 crystal, which is a 122 parent of iron arsenide superconductors, is found through synthesis to have ordering below TN = 195 K (for the disordered crystal) or TN = 175 K (for the ordered crystal). In the higher TN crystals, there are shorter planar Fe-Fe bonds [2.7692(2) A vs. 2.7745(3) A], a randomized in-plane defect structure, and diffuse scattering along the [00L] crystallographic direction that manifests as a rather broad specific heat peak. For the lower TN crystals, the a-lattice parameter is larger and the in-plane microscopic structure shows defect ordering along the antiphase boundaries, giving a larger TN and a higher superconducting temperature (Tc) upon the application of pressure. First principles calculations find a strong interaction between c-axis strain and interlayer magnetic coupling, but little impact of planar strain on the magnetic order. Neutron single-crystal diffraction shows that the low-temperature magnetic phase transition due to localized Eu moments is not lattice or disorder sensitive, unlike the higher-temperature Fe sublattice ordering. This study demonstrates a higher magnetic ordering point arising from local disorder in 122.

cond-mat.supr-con↗

arXiv2019

Variational B-rep Model Analysis for Direct Modeling using Geometric Perturbation

The very recent CAD paradigm of direct modeling gives rise to the need of processing 3D geometric constraint systems defined on boundary representation (B-rep) models. The major issue of processing such variational B-rep models (in the STEP format) is that free motions of a well-constrained model involve more than just rigid-body motions. The fundamental difficulty lies in having a systematic description of what pattern these free motions follow. This paper proposes a geometric perturbation method to study these free motions. This method is a generalization of the witness method, allowing it to directly deal with variational B-rep models represented with the standard STEP scheme. This generalization is essentially achieved by using a direct, geometric representation of the free motions, and then expressing the free motions in terms of composites of several basis motions. To demonstrate the effectiveness of the proposed method, a series of comparisons and case studies are presented.

cs.CG↗

arXiv2018

Iso-level tool path planning for free-form surfaces

The aim of tool path planning is to maximize the efficiency against some given precision criteria. In practice, scallop height should be kept constant to avoid unnecessary cutting, while the tool path should be smooth enough to maintain a high feed rate. However, iso-scallop and smoothness often conflict with each other. Existing methods smooth iso-scallop paths one-by-one, which make the final tool path far from being globally optimal. This paper proposes a new framework for tool path optimization. It views a family of iso-level curves of a scalar function defined over the surface as tool path so that desired tool path can be generated by finding the function that minimizes certain energy functional and different objectives can be considered simultaneously. We use the framework to plan globally optimal tool path with respect to iso-scallop and smoothness. The energy functionals for planning iso-scallop, smoothness, and optimal tool path are respectively derived, and the path topology is studied too. Experimental results are given to show the effectiveness of the proposed methods.

cs.GR↗

arXiv2018

Iso-parametric tool path planning for point clouds

The computational consuming and non-robust reconstruction from point clouds to either meshes or spline surfaces motivates the direct tool path planning for point clouds. In this paper, a novel approach for planning iso-parametric tool path from a point cloud is presented. The planning depends on the parameterization of point clouds. Accordingly, a conformal map is employed to build the parameterization which leads to a significant simplification of computing tool path parameters and boundary conformed paths. Then, Tool path is generated through linear interpolation with the forward and side step computed against specified chord deviation and scallop height, respectively. Experimental results are given to illustrate effectiveness of the proposed methods.

cs.GR↗

arXiv2018

Push-pull direct modeling of solid CAD models

Direct modeling is a very recent CAD modeling paradigm featuring direct, intuitive push-pull interactions with the geometry of the model to much increase model editing flexibility. The major issue for push-pull direct modeling is the possible inconsistency between the altered geometry of the model and its unchanged topology. The challenge of resolving the geometry-topology inconsistency lies in ensuring that the resulting model remains as a valid solid model and that the model shape follows a continuous change pattern. Although push-pull direct modeling has been implemented in several CAD software packages, robustness towards generating valid modeling results and continuous shape changes still remains an open issue. This paper proposes a systematic method to handle the resolution of any possible inconsistent situation. The method formulates the continuous shape change requirement as successive Boolean operations on the model volume, thereby guaranteeing valid solid models and continuous shape changes. Further, this formulation allows for an easy implementation of push-pull direct modeling using existing CAD research and engineering results. In order to show the effectiveness of the proposed method, a software prototype is developed and the modeling results are compared with those of five leading CAD software packages.

cs.CG↗