arXiv subjects

Yichao Zhu

Publications and source records attributed to Yichao Zhu.

17 recordsLinked to original sources

arXiv2026

RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation

Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due to the significant hardware heterogeneity across bimanual robotic platforms. To bridge this gap, we introduce RoboCOIN, a large-scale multi-embodiment bimanual manipulation dataset comprising over 180,000 demonstrations collected from 15 distinct robotic platforms. Spanning 16 diverse environments-including residential, commercial, and industrial settings-the dataset features 421 bimanual tasks systematically categorized by 39 bimanual collaboration actions and 432 objects. A key innovation of our work is the hierarchical capability pyramid, which provides granular annotations ranging from trajectory-level concepts to segment-level subtasks and frame-level kinematics. Furthermore, we present CoRobot, an efficient data processing pipeline powered by the Robot Trajectory Markup Language (RTML), designed to facilitate quality assessment, automated annotation, and unified multi-embodiment and data management. Extensive experiments demonstrate the effectiveness of RoboCOIN in enhancing the performance of various bimanual manipulation models across a wide spectrum of robotic embodiments. The entire dataset and codebase are fully open-sourced, providing a valuable resource for advancing research in bimanual and multi-embodiment manipulation.

cs.RO↗

arXiv2026

"Do I Trust the AI?" Towards Trustworthy AI-Assisted Diagnosis: Understanding User Perception in LLM-Supported Reasoning

Large language models (LLMs) have shown considerable potential in supporting medical diagnosis. However, their effective integration into clinical workflows is hindered by physicians' difficulties in perceiving and trusting LLM capabilities, which often results in miscalibrated trust. Existing model evaluations primarily emphasize standardized benchmarks and predefined tasks, offering limited insights into clinical reasoning practices. Moreover, research on human-AI collaboration has rarely examined physicians' perceptions of LLMs' clinical reasoning capability. In this work, we investigate how physicians perceive LLMs' capabilities in the clinical reasoning process. We designed clinical cases, collected the corresponding analyses, and obtained evaluations from physicians (N=37) to quantitatively represent their perceived LLM diagnostic capabilities. By comparing the perceived evaluations with benchmark performance, our study highlights the aspects of clinical reasoning that physicians value and underscores the limitations of benchmark-based evaluation. We further discuss the implications of opportunities for enhancing trustworthy collaboration between physicians and LLMs in LLM-supported clinical reasoning.

cs.HC↗

arXiv2025

Asymptotic Formulation of the Role of Shear Loads on Multi-Layered Thin Shells and Classification of Their Deformation Modes

Shell structures are generally modeled based on kinematic hypotheses, where some of the parameters are preferentially evaluated in a phenomenological manner. In this article, asymptotic analysis against the underlying three-dimensional equation system is considered so as to provide a rational framework for modeling and interpreting the deformation behavior of multi-layered thin shells (MTSs). Capable of accurately predicting both overall stiffness and detailed stress distribution, the proposed shell theory shows its distinguishing features at least in the following aspects. Firstly, it naturally introduces a rule for classifying the deformation modes of MTSs based on the magnitude of the maximum dimensionless principal curvature. Secondly, for each class, the hierarchy in the order of the involved field quantities is examined, and it is shown that when the product of the maximum principal curvature and the characteristic shell size reaches the magnitude of unity or larger, the resulting shell theory cannot be treated by natural extension of plate theories. Lastly, it is demonstrated that, for moderate shear forces and comparable material properties, a leading-order multi-layered shell theory derived from asymptotic analysis should suffice to output satisfactory predictions over the shell stiffness, as well as its internal stress distribution. Numerical examples of the deformation and strength analysis for MTSs are also presented to show the reliability of the leading-order model.

cond-mat.mtrl-sci↗

arXiv2023

FaST-GShare: Enabling Efficient Spatio-Temporal GPU Sharing in Serverless Computing for Deep Learning Inference

Serverless computing (FaaS) has been extensively utilized for deep learning (DL) inference due to the ease of deployment and pay-per-use benefits. However, existing FaaS platforms utilize GPUs in a coarse manner for DL inferences, without taking into account spatio-temporal resource multiplexing and isolation, which results in severe GPU under-utilization, high usage expenses, and SLO (Service Level Objectives) violation. There is an imperative need to enable an efficient and SLO-aware GPU-sharing mechanism in serverless computing to facilitate cost-effective DL inferences. In this paper, we propose \textbf{FaST-GShare}, an efficient \textit{\textbf{Fa}aS-oriented \textbf{S}patio-\textbf{T}emporal \textbf{G}PU \textbf{Sharing}} architecture for deep learning inferences. In the architecture, we introduce the FaST-Manager to limit and isolate spatio-temporal resources for GPU multiplexing. In order to realize function performance, the automatic and flexible FaST-Profiler is proposed to profile function throughput under various resource allocations. Based on the profiling data and the isolation mechanism, we introduce the FaST-Scheduler with heuristic auto-scaling and efficient resource allocation to guarantee function SLOs. Meanwhile, FaST-Scheduler schedules function with efficient GPU node selection to maximize GPU usage. Furthermore, model sharing is exploited to mitigate memory contention. Our prototype implementation on the OpenFaaS platform and experiments on MLPerf-based benchmark prove that FaST-GShare can ensure resource isolation and function SLOs. Compared to the time sharing mechanism, FaST-GShare can improve throughput by 3.15x, GPU utilization by 1.34x, and SM (Streaming Multiprocessor) occupancy by 3.13x on average.

cs.DC↗

arXiv2021

Stiffness minimisation of graded microstructural configurations using asymptotic analysis and machine learning

The article is aimed to address a mutually boosting use of asymptotic analysis and machine learning, for fast stiffness design of configurations infilled with smoothly-varying graded microstructures. The discussion is conducted in the context of an improved asymptotic-homogenisation topology optimisation (AHTO plus) framework. It is demonstrated that on one hand, machine learning can be employed to represent the key but implicit inter-relationships revealed from asymptotic analysis, and the evaluations of the homogenised quantities, as well as the sensitivities of the design variables, become quite efficient. On the other hand, the use of asymptotic analysis identifies a computational routine for data acquisition, thus the training data here are inexhaustible in theory. Key issues regarding integration of the two methods, such as ensuring the positive definiteness of the homogenised elasticity tensor represented with neural networks, are also discussed. The accuracies and the efficiencies of the present scheme are numerically demonstrated. For two-dimensional optimisation, it takes the present algorithm roughly 300 seconds on a standard desktop computer, and this qualifies the present scheme as one of the most efficient algorithms used for the compliance optimisation of configurations infilled with complex microstructures.

math.NA↗

arXiv2021

Optimisation of spatially varying orthotropic porous structures based on conformal mapping

In this article, a compliance minimisation scheme for designing spatially varying orthotropic porous structures is proposed. With the utilisation of conformal mapping, the porous structures here can be generated by two controlling field variables, the (logarithm of) the local scaling factor and the rotational angle of the matrix cell, and they are interrelated through the Cauchy-Riemann equations. Thus the design variables are simply reduced to the logarithm values of the local scaling factor on selected boundary points. Other attractive features shown by the present method are summarised as follows. Firstly, with the condition of total differential automatically met by the two controlling field variables, the integrability problem which necessitates post-processing treatments in many other similar methods can be resolved naturally. Secondly, according to the maximum principle for harmonic functions, the minimum feature size can be explicitly monitored during optimisation. Thirdly, the rotational symmetry possessed by the matrix cell can be fully exploited in the context of conformal mapping, and the computational cost for solving the cell problems for the homogenised elasticity tensor is maximally abased. In particular, when the design domain takes a rectangle shape, analytical expressions for the controlling fields are available. The homogenised results are shown, both theoretically and numerically, to converge to the corresponding fine-scale results, and the effectiveness of the proposed work is further demonstrated with more numerical examples.

math.NA↗

arXiv2020

Surrogate representation of sink strengths and the long-term role of crystalline interfaces in the development of irradiation-induced bubbles

The present article addresses an early-stage attempt on replacing the analyticity-based sink strength terms in rate equations by surrogate models of machine learning representation. Here we emphasise, in the context of multiscale modelling, a combinative use of machine learning with scale analysis, through which a set of fine-resolution problems of partial differential equations describing the (quasi-steady) short-range individual sink behaviour can be asymptotically sorted out from the mean-field kinetics. Hence the training of machine learning is restrictively oriented, that is, to express the local and already identified, but analytically unavailable nonlinear functional relationships between the sink strengths and other local continuum field quantities. With the trained models, one is enabled to quantitatively investigate the biased effect shown by a void/bubble being a point defect sink, and the results are compared with existing ones over well-studied scenarios. Moreover, the faster diffusive mechanisms on crystalline interfaces are distinguishingly modelled by locally planar rate equations, and their linkages with rate equations for bulk diffusion are formulated through derivative jumps of point defect concentrations across the interfaces. Thus the distinctive role of crystalline interfaces as partial sinks and quick diffusive channels can be investigated. Methodologicalwise, the present treatment is also applicable for studying more complicated situation of long-term sink behaviour observed in irradiated materials.

cond-mat.mtrl-sci↗

arXiv2020

Generation of smoothly-varying infill configurations from a continuous menu of cell patterns and the asymptotic analysis of its mechanical behaviour

We here introduce a novel scheme for generating smoothly-varying infill graded microstructural (IGM) configurations from a given menu of generating cells. The scheme was originally proposed for essentially improving the variety of describable configurations in a modified asymptotic homogenisation-based topology optimisation framework [1] for fast IGM design. But the proposed scheme, after modification, also demonstrates its unique values in two aspects of applications. First, it provides a fairly simple way of generating an IGM configuration continuously patching any given cell configurations. Second, it tenders a straightforward mean for decorating microstructures on a given manifold. We will further show that the form of topology description function given here effectively offers a platform for unifying most existing approaches for IGM generation. Fuelled by asymptotic analysis of the mechanical behaviour of the resulting IGM configurations, a topology optimisation scheme for compliance minimisation is introduced. We will finally show that, the use of the present scheme helps reduce the compliance value of an optimised structure by nearly a half, if compared with that from the original framework [1].

cs.CE↗

arXiv2019

On speeding up an asymptotic-analysis-based homogenisation scheme for designing gradient porous structured materials using a zoning strategy

Gradient porous structured materials possess significant potential of being applied in many engineering fields. To accelerate the design process of infill graded microstructures, a novel asymptotic homogenisation topology optimisation method was proposed by Zhu et al.(2019), aiming for 1) significantly enriching the pool of representable graded microstructures; 2) deriving an homogenised formulation for stress analysis in consistency with fine-scale results. But the work is severely confined from being widely applied, mainly due to the following two reasons. Firstly, to circumvent the macroscopically pointwise computation for solving various microscopic cell problems, linearisation had to be adopted for its numerical implementation, and this significantly reduces the design freedom. Secondly, lacking of sensitive analysis, genetic algorithm was chosen for optimisation, inevitably decreasing the computational efficiency. To address these bottleneck challenging issues, a zoning scheme empowered by computational parallelism is introduced, and the sensitivity analysis associated with the new asymptotic framework is conducted. Through comparisons with fine-scale simulation results, the proposed algorithm is shown to be an effective tool for evaluating the mechanical behaviour of graded microstructures. As an optimisation tool, the mapping function takes a concise and explicit form. But its parameterisation still needs further investigation, so as to improve the solution optimality of the present approach, especially in comparison with another recently proposed method by Groen et al (2018). The high computational efficiency shown by the proposed scheme is also demonstrated with optimisation results for three-dimensional graded microstructures, which are not frequently discussed in literature, possibly because of the high computational cost generated.

cs.CE↗

arXiv2019

Optimal design of shell-graded-infill structures by a hybrid MMC-MMV approach

In the present work, a hybrid MMC-MMV approach is developed for designing additive manufacturing-oriented shell-graded-infill structures. The key idea is to describe the geometry of a shell-graded-infill structure explicitly using some geometry parameters. To this end, a set of morphable voids is adopted to describe the boundary of the coating shell, while a set of morphable components combing with a coordinate perturbation technique are introduced to represent the graded infill distribution. Under such treatment, both the crisp boundary of the coating shell and the graded infill can be optimized simultaneously, with a small number of design variables. Numerical examples demonstrate the effectiveness of the proposed approach.

cs.CE↗

arXiv2018

An efficient Moving Morphable Component (MMC)-based approach for multi-resolution topology optimization

In the present work, a highly efficient Moving Morphable Component (MMC) based approach for multi-resolution topology optimization is proposed. In this approach, high-resolution optimization results can be obtained with much less number of degrees of freedoms (DOFs) and design variables since the finite element analysis model and the design optimization model are totally decoupled in the MMC-based problem formulation. This is achieved by introducing super-elements for structural response analysis and adopting a domain decomposition strategy to preserve the topology complexity of optimized structures. Both two-and three-dimensional numerical results demonstrate that substantial computational efforts can be saved with use of the proposed approach.

cs.CE↗

arXiv2018

The Role of Grain Boundaries under Long-Time Radiation

Materials containing a high proportion of grain boundaries offer significant potential for the development of radiation-resistent structural materials. However, a proper understanding of the connection between the radiation-induced microstructural behaviour of grain boundary and its impact at long natural time scales is still missing. In this letter, point defect absorption at interfaces is summarised by a jump Robin-type condition at a coarse-grained level, wherein the role of interface microstructure is effectively taken into account. Then a concise formula linking the sink strength of a polycrystalline aggregate with its grain size is introduced, and is well compared with experimental observation. Based on the derived model, a coarse-grained formulation incorporating the coupled evolution of grain boundaries and point defects is proposed, so as to underpin the study of long-time morphological evolution of grains induced by irradiation. Our simulation results suggest that the presence of point defect sources within a grain further accelerates its shrinking process, and radiation tends to trigger the extension of twin boundary sections.

cond-mat.mtrl-sci↗

arXiv2018

A continuum model for distributions of dislocations incorporating short-range interactions

Dislocations are the main carriers of the permanent deformation of crystals. For simulations of engineering applications, continuum models where material microstructures are represented by continuous density distributions of dislocations are preferred. It is challenging to capture in the continuum model the short-range dislocation interactions, which vanish after the standard averaging procedure from discrete dislocation models. In this study, we consider systems of parallel straight dislocation walls and develop continuum descriptions for the short-range interactions of dislocations by using asymptotic analysis. The obtained continuum short-range interaction formulas are incorporated in the continuum model for dislocation dynamics based on a pair of dislocation density potential functions that represent continuous distributions of dislocations. This derived continuum model is able to describe the anisotropic dislocation interaction and motion. Mathematically, these short-range interaction terms ensure strong stability property of the continuum model that is possessed by the discrete dislocation dynamics model. The derived continuum model is validated by comparisons with the discrete dislocation dynamical simulation results.

cond-mat.mtrl-sci↗

arXiv2017

A magnification-based multi-asperity (MBMA) model of rough contact where the Greenwood-Williamson and Persson theories meet

Contact analysis without adhesion is still a challenging problem, mainly owing to the multiscale and self-fractal characteristics of rough surfaces. Up to now, theories for analyzing contact behavior of rough surfaces in literature can be generally categorized into two groups: the asperity-based Hertz contact models initiated by Greenwood and Williamson (G-W model), which is shown more accurate under small indentation distance, and the magnification-based pressure diffusion theory initiated by Persson, which is shown to work well under full contact conditions. The aim of this paper is to propose a theoretical model that can effectively formulate the contact status of rough surfaces during the entire compression process. This is achieved by integrating the idea of magnification, or evolving resolution into an asperity representation of rough surfaces, and a magnification-based multi-asperity model is thus established. In the derived model, the originally complex contact problem is decomposed into a family of sub-problems each defined on a morphologically simpler contact islands. Benefiting from the explicit results given by Greenwood and Williamson, the proposed method is relatively easy for numerical implementation. Compared to other G-W type models, the proposed method has especially shown its strength in the computation of the contact area. Moreover, the G-W and Persson models are found well connected by the proposed method. For its validation, the proposed model is well compared with existing numerical, theoretical and experimental results. In particular, the proposed model has shown its excellency through comparison with representative theoretical, numerical and experimental data compiled in the contact challenge test by Mueser et al.

physics.app-ph↗

arXiv2016

Continuum dynamics of the formation, migration and dissociation of self-locked dislocation structures on parallel slip planes

In continuum models of dislocations, proper formulations of short-range elastic interactions of dislocations are crucial for capturing various types of dislocation patterns formed in crystalline materials. In this article, the continuum dynamics of straight dislocations distributed on two parallel slip planes is modelled through upscaling the underlying discrete dislocation dynamics. Two continuum velocity field quantities are introduced to facilitate the discrete-to-continuum transition. The first one is the local migration velocity of dislocation ensembles which is found fully independent of the short-range dislocation correlations. The second one is the decoupling velocity of dislocation pairs controlled by a threshold stress value, which is proposed to be the effective flow stress for single slip systems. Compared to the almost ubiquitously adopted Taylor relationship, the derived flow stress formula exhibits two features that are more consistent with the underlying discrete dislocation dynamics: i) the flow stress increases with the in-plane component of the dislocation density only up to a certain value, hence the derived formula admits a minimum inter-dislocation distance within slip planes; ii) the flow stress smoothly transits to zero when all dislocations become geometrically necessary dislocations. A regime under which inhomogeneities in dislocation density grow is identified, and is further validated through comparison with discrete dislocation dynamical simulation results. Based on the findings in this article and in our previous works, a general strategy for incorporating short-range dislocation correlations in continuum models of dislocations is proposed.

cond-mat.mtrl-sci↗

arXiv2016

Homogenisation of a Row of Dislocation Dipoles from Discrete Dislocation Dynamics

Conventional discrete-to-continuum approaches have seen their limitation in describing the collective behaviour of the multi-polar configurations of dislocations, which are widely observed in crystalline materials. The reason is that dislocation dipoles, which play an important role in determining the mechanical properties of crystals, often get smeared out when traditional homogenisation methods are applied. To address such difficulties, the collective behaviour of a row of dislocation dipoles is studied by using matched asymptotic techniques. The discrete-to-continuum transition is facilitated by introducing two field variables respectively describing the dislocation pair density potential and the dislocation pair width. It is found that the dislocation pair width evolves much faster than the pair density. Such hierarchy in evolution time scales enables us to describe the dislocation dynamics at the coarse-grained level by an evolution equation for the slowly varying variable (the pair density) coupled with an equilibrium equation for the fast varying variable (the pair width). The time-scale separation method adopted here paves a way for properly incorporating dipole-like (zero net Burgers vector but non-vanishing) dislocation structures, known as the statistically stored dislocations (SSDs) into macroscopic models of crystal plasticity in three dimensions. Moreover, the natural transition between different equilibrium patterns found here may also shed light on understanding the emergence of the persistent slip bands (PSBs) in fatigue metals induced by cyclic loads.

cond-mat.mtrl-sci↗

arXiv2015

A continuum model for dislocation dynamics in three dimensions using the dislocation density potential functions and its application in understanding the micro-pillar size effect

In this paper, we present a dislocation-density-based three-dimensional continuum model, where the dislocation substructures are represented by pairs of dislocation density potential functions (DDPFs), denoted by $ϕ$ and $ψ$. The slip plane distribution is characterized by the contour surfaces of $ψ$, while the distribution of dislocation curves on each slip plane is identified by the contour curves of $ϕ$ which represents the plastic slip on the slip plane. By using DDPFs, we can explicitly write down an evolution equation system, which is shown consistent with the underlying discrete dislocation dynamics. The system includes i) A constitutive stress rule, which describes how the total stress field is determined in the presence of dislocation networks and applied loads; ii) A plastic flow rule, which describes how dislocation ensembles evolve. The proposed continuum model is validated through comparisons with discrete dislocation dynamics simulation results and experimental data. As an application of the proposed model, the "smaller-being-stronger" size effect observed in single-crystal micro-pillars is studied. A scaling law for the pillar flow stress $σ_{\text{flow}}$ against its (non-dimensionalized) size $D$ is derived to be $σ_{\text{flow}}\sim\log(D)/D$.

cond-mat.mtrl-sci↗