arXiv subjects

Yichao Liu

Publications and source records attributed to Yichao Liu.

At least 37 records · Page 2Linked to original sources

arXiv2025

Broadband source-surrounded cloak for on-chip antenna radiation pattern protection

As the frequency range of electromagnetic wave communication continues to expand and the integration of integrated circuits increases, electromagnetic waves emitted by on-chip antennas are prone to scattering from electronic components, which limits further improvements in integration and the protection of radiation patterns. Cloaks can be used to reduce electromagnetic scattering; however, they cannot achieve both broadband and omnidirectional effectiveness simultaneously. Moreover, their operating modes are typically designed for scenarios where the source is located outside the cloak, making it difficult to address this problem. In this work, we propose a dispersionless air-impedance-matched metamaterial over the 2-8 GHz bandwidth that achieves an adjustable effective refractive index ranging from 1.1 to 1.5, with transmittance maintained above 93%. Based on this metamaterial, we introduce a broadband source-surrounded cloak that can guide electromagnetic waves from a broadband source surrounded by the cloak in any propagation direction to bypass obstacles and reproduce the original wavefronts outside the cloak. Thereby protecting the radiation pattern from distortion due to scattering caused by obstacles. Our work demonstrates significant potential for enhancing the integration density of integrated circuits and improving the operational stability of communication systems.

physics.optics↗

arXiv2024

DIG-FACE: De-biased Learning for Generalized Facial Expression Category Discovery

We introduce a novel task, Generalized Facial Expression Category Discovery (G-FACE), that discovers new, unseen facial expressions while recognizing known categories effectively. Even though there are generalized category discovery methods for natural images, they show compromised performance on G-FACE. We identified two biases that affect the learning: implicit bias, coming from an underlying distributional gap between new categories in unlabeled data and known categories in labeled data, and explicit bias, coming from shifted preference on explicit visual facial change characteristics from known expressions to unknown expressions. By addressing the challenges caused by both biases, we propose a Debiased G-FACE method, namely DIG-FACE, that facilitates the debiasing of both implicit and explicit biases. In the implicit debiasing process of DIG-FACE, we devise a novel learning strategy that aims at estimating and minimizing the upper bound of implicit bias. In the explicit debiasing process, we optimize the model's ability to handle nuanced visual facial expression data by introducing a hierarchical category-discrimination refinement strategy: sample-level, triplet-level, and distribution-level optimizations. Extensive experiments demonstrate that our DIG-FACE significantly enhances recognition accuracy for both known and new categories, setting a first-of-its-kind standard for the task.

cs.CV↗

arXiv2024

Ultra-broadband acoustic absorber based on periodic acoustic rigid-metaporous composite array

To address the increasingly serious issue of noise pollution, we propose an ultra-broadband and wide-angle acoustic absorber based on a periodic acoustic rigid-metaporous composite array. Numerical simulation results verify the broadband good acoustic absorption performance of the proposed absorber, which can achieve an average absorption coefficient of approximately 90.9% within the frequency band from 500 to 4000 Hz with incident angles ranging from -75 to +75 degrees, thus compensating for the shortcomings of traditional acoustic absorbers that are not as effective at low frequencies. This work will provide a new approach for ultra-broadband and wide-angle acoustic wave absorption and noise suppression.

cs.CE↗

arXiv2024

Broadband planar electromagnetic hyper-lens with uniform magnification in air

A planar hyper-lens, capable of creating sub-wavelength imaging for broadband electromagnetic wave, is designed based on electromagnetic null medium. Subsequently, a scheme for the implementation of the proposed hyper-lens is given by using well-designed flexural metal plates, which function as the reduced electromagnetic null medium for TM-polarized microwaves. Both simulated and measured results verify that the hyper-lens designed with flexural metal plates can achieve super-resolution imaging for microwave at operating wavelength (λ0=3cm) with a resolution of 0.25λ0 and a uniform magnification of about 5. Moreover, the designed hyper-lens ensures that both the object and image surfaces are planes, and simultaneously provides a uniform magnification for objects in different positions. Additionally, the proposed hyper-lens offers a broadband super-resolution imaging capabilities, achieving good super-resolution imaging effects for microwave frequencies ranging from 8.5 to 11 GHz. The proposed hyper-lens may find applications in high precision imaging, detection, and sensing.

physics.app-ph↗

arXiv2024

Experimental demonstration of a thermal-EM concentrator for enhancing EM signals and converging heat fluxes simultaneously

Simultaneously concentrating EM waves and heat fluxes to the same target region within an on-chip system carries substantial academic research importance and practical application value. Nevertheless, existing researches are primarily aimed at the design and experimentation of concentrators for individual EM waves or temperature fields. In this work, a thermal-EM concentrator, capable of simultaneously concentrating EM waves and heat fluxes, is designed using transformation optics/thermodynamics and fabricated with engineered EM-thermal metamaterials. The concentrating effects of the proposed thermal-EM concentrator on the thermal fluxes and EM waves are verified through numerical simulations and experimental measurements, respectively, which are in good agreement with each other. Both numerically simulated and experimentally measured results demonstrate the concentrating capability of the proposed thermal-EM concentrator, which can concentrate broadband TM-polarized EM waves ranging from 8-12 GHz and heat/cold flows to the same target region within an on-chip operating environment. The thermal-EM concentrator exhibits a thermal focusing efficiency close to 100% and more than three times enhancement of the magnetic field at the designed center frequency of 10 GHz. The proposed thermal-EM concentrator can be utilized for efficient cooling for the specified component and simultaneously enhancing the EM antenna's radiation/reception efficiency within an on-chip system.

physics.gen-ph↗

arXiv2024

Tunable uniform field enhancement in a subwavelength air pillar by photonic doping in epsilon-near-zero medium

In this study, a novel electric field compressor is proposed by doping a metal-air-metal pillar in epsilon-near-zero medium within a metallic waveguide, which effectively enhances the background electric fields in a sub-wavelength air pillar with high uniformity. The field enhancement factor can be analytically determined through theoretical derivations from Maxwell's equations, reaching its maximum value by appropriately selecting the size of the air pillar. Furthermore, the proposed compressor can achieve a tunable electric field enhancement effect within the deep sub-wavelength air pillar by adjusting the height of the air pillar through movement of two metal pillars inserted into the waveguide. Both theoretical analysis and numerical simulations are employed to validate the performance of the electric field compressor, which exhibits a wide range of tunable field enhancement effect (i.e., continuously adjustable enhancement factor between 20 and 800) with uniformity below 1.5 within the deep sub-wavelength air pillar (wherein the air volume is smaller than la0/10 * la0/10 * la0/16). Finally, a practical model is proposed for the realization of the electric field compressor in the microwave range, where specially placed metal pillars and wires are incorporated into a rectangular metallic waveguide structure. The field enhancement and tunable effects of this practical model have been verified through simulations.

physics.app-ph↗

arXiv2023

On-chip omnidirectional electromagnetic-thermal cloak

Simultaneously guiding electromagnetic waves and heat flow at any incidence angle to smoothly bypass some electromagnetic/thermal sensitive elements is a key factor to ensure efficient communication and thermal protection for an on-chip system. In this study, an omnidirectional on-chip electromagnetic-thermal cloak is proposed. Firstly, a holey metallic plate with periodic array of subwavelength apertures is designed by optical surface transformation to realize an omnidirectional electromagnetic cloaking module for on-chip electromagnetic signal. Secondly, a two-layer ring-shaped engineered thermal structure is designed by solving Laplace equation to realize an omnidirectional thermal cloaking module for in-chip heat flow. Finally, these two cloaking modules are combined elaborately to achieve cloaking effect for both the electromagnetic waves and thermal fields simultaneously from any detecting direction, thus protecting the build-in electromagnetic/thermal sensitive elements without disturbing the external electromagnetic/thermal signal. The proposed electromagnetic-thermal cloak may have potential advantage in dealing with omnidirectional electromagnetic compatibility/shielding and multi-directional thermal management/dissipation of an on-chip system.

physics.app-ph↗

arXiv2023

Exploring Large Language Models for Human Mobility Prediction under Public Events

Public events, such as concerts and sports games, can be major attractors for large crowds, leading to irregular surges in travel demand. Accurate human mobility prediction for public events is thus crucial for event planning as well as traffic or crowd management. While rich textual descriptions about public events are commonly available from online sources, it is challenging to encode such information in statistical or machine learning models. Existing methods are generally limited in incorporating textual information, handling data sparsity, or providing rationales for their predictions. To address these challenges, we introduce a framework for human mobility prediction under public events (LLM-MPE) based on Large Language Models (LLMs), leveraging their unprecedented ability to process textual data, learn from minimal examples, and generate human-readable explanations. Specifically, LLM-MPE first transforms raw, unstructured event descriptions from online sources into a standardized format, and then segments historical mobility data into regular and event-related components. A prompting strategy is designed to direct LLMs in making and rationalizing demand predictions considering historical mobility and event features. A case study is conducted for Barclays Center in New York City, based on publicly available event information and taxi trip data. Results show that LLM-MPE surpasses traditional models, particularly on event days, with textual data significantly enhancing its accuracy. Furthermore, LLM-MPE offers interpretable insights into its predictions. Despite the great potential of LLMs, we also identify key challenges including misinformation and high costs that remain barriers to their broader adoption in large-scale human mobility analysis.

cs.AI↗

arXiv2023

Simultaneously realizing thermal and electromagnetic cloaking by multi-physical null medium

Simultaneously manipulating multiple physical fields plays an important role in the increasingly complex integrated systems, aerospace equipment, biochemical productions, etc. For on-chip systems with high integration level (e.g., electronic/photonic chips and radio-frequency/microwave circuits), where both electromagnetic information/energy transporting and heat dissipation/recovery need to be considered, the precise and efficient control of the propagation of electromagnetic waves and heat fluxes simultaneously is particularly important. In this study, we propose a graphical designing method based on thermal-electromagnetic null medium to simultaneously control the propagation of electromagnetic waves and thermal fields according to the pre-designed paths. A thermal-electromagnetic cloak, which can create a cloaking effect on both electromagnetic waves and thermal fields simultaneously, is designed by thermal-electromagnetic surface transformation and verified by both numerical simulations and experimental measurements. The thermal-electromagnetic surface transformation proposed in this study provides a new methodology for simultaneous controlling on electromagnetic and temperature fields, which can be used to realize a series of novel thermal-electromagnetic devices such as thermal-electromagnetic shifter, splitter, bender, multiplexer and mode converter. The designed thermal-electromagnetic cloak opens up new ways to create a concealed region where any object within it does not create any disturbance to the external electromagnetic waves and temperature fields simultaneously, which may have significant applications in improving thermal-electromagnetic compatibility problem, protecting of thermal-electromagnetic sensitive components, and improving efficiency of energy usage for complex on-chip systems.

physics.app-ph↗

arXiv2022

Active thermal metasurfaces for remote heating/cooling by mimicking negative thermal conductivity

Remote temperature control can be obtained by a long-focus thermal lens that can focus heat fluxes into a spot far away from the back surface of the lens and create a virtual thermal source/sink in the background material, around which the temperature field distribution can be remotely controlled by changing the parameters of the thermal lens. However, due to the lack of negative thermal conductivity, the existing thermal lenses have extremely short focal lengths and cannot be used to remotely control the temperature field around the virtual thermal source/sink. In this study, we theoretically propose a general approach to equivalently realize negative thermal conductivity by elaborately distributed active thermal metasurface (ATMS), then use the proposed ATMS to implement a novel thermal lens with long focal length designed by transformation thermodynamics, and experimentally verify the performance of the designed long-focus thermal lens with measured focal length f=19.8mm for remote heating/cooling. The proposed method expands the scope of the thermal conductivity and open up new ways to realize unprecedented thermal effects with effective negative thermal conductivity, such as "thermal surface plasmon polaritons", thermal superlens, thermal tunneling effect, and thermal invisible gateway.

physics.gen-ph↗

arXiv2022

An Economic Model Predictive Control Approach for Load Mitigation on Multiple Tower Locations of Wind Turbines

The current trend in the evolution of wind turbines is to increase their rotor size in order to capture more power. This leads to taller, slender and more flexible towers, which thus experience higher dynamical loads due to the turbine rotation and environmental factors. It is hence compelling to deploy advanced control methods that can dynamically counteract such loads, especially at tower positions that are more prone to develop cracks or corrosion damages. Still, to the best of the authors' knowledge, little to no attention has been paid in the literature to load mitigation at multiple tower locations. Furthermore, there is a need for control schemes that can balance load reduction with optimization of power production. In this paper, we develop an Economic Model Predictive Control (eMPC) framework to address such needs. First, we develop a linear modal model to account for the tower flexural dynamics. Then we incorporate it into an eMPC framework, where the dynamics of the turbine rotation are expressed in energy terms. This allows us to obtain a convex formulation, that is computationally attractive. Our control law is designed to avoid the 'turn-pike' behavior and guarantee recursive feasibility. We demonstrate the performance of the proposed controller on a 5MW reference WT model: the results illustrate that the proposed controller is able to reduce the tower loads at multiple locations, without significant effects to the generated power.

eess.SY↗

arXiv2021

Global Attention Mechanism: Retain Information to Enhance Channel-Spatial Interactions

A variety of attention mechanisms have been studied to improve the performance of various computer vision tasks. However, the prior methods overlooked the significance of retaining the information on both channel and spatial aspects to enhance the cross-dimension interactions. Therefore, we propose a global attention mechanism that boosts the performance of deep neural networks by reducing information reduction and magnifying the global interactive representations. We introduce 3D-permutation with multilayer-perceptron for channel attention alongside a convolutional spatial attention submodule. The evaluation of the proposed mechanism for the image classification task on CIFAR-100 and ImageNet-1K indicates that our method stably outperforms several recent attention mechanisms with both ResNet and lightweight MobileNet.

cs.CV↗

arXiv2021

NAM: Normalization-based Attention Module

Recognizing less salient features is the key for model compression. However, it has not been investigated in the revolutionary attention mechanisms. In this work, we propose a novel normalization-based attention module (NAM), which suppresses less salient weights. It applies a weight sparsity penalty to the attention modules, thus, making them more computational efficient while retaining similar performance. A comparison with three other attention mechanisms on both Resnet and Mobilenet indicates that our method results in higher accuracy. Code for this paper can be publicly accessed at https://github.com/Christian-lyc/NAM.

cs.CV↗

arXiv2021

The Proportional Integral Notch and Coleman Blade Effective Wind Speed Estimators and Their Similarities

The estimation of the rotor effective wind speed is used in modern wind turbines to provide advanced power and load control capabilities. However, with the ever increasing rotor sizes, the wind field over the rotor surface shows a higher degree of spatial variation. A single effective wind speed estimation therefore limits the attainable levels of load mitigation, and the estimation of the Blade Effective Wind Speed (BEWS) might present opportunities for improved load control. This letter introduces two novel BEWS estimator approaches: A Proportional Integral Notch (PIN) estimator based on individual blade load measurements, and a Coleman estimator targeting the estimation in the non-rotating frame. Given the seeming disparities between these two estimators, the objective of this letter is to analyze the similarities between the approaches. It is shown that the PIN estimator, which is equivalent to the diagonal form of the Coleman estimator, is a simple but effective method to estimate the BEWS. The Coleman estimator, which takes the coupling effects between individual blades into account, shows a more well behaved transient response than the PIN estimator.

eess.SY↗

arXiv2021

The Immersion and Invariance Wind Speed Estimator Revisited and New Results

The Immersion and Invariance (I&I) wind speed estimator is a powerful and widely-used technique to estimate the rotor effective wind speed on horizontal axis wind turbines. Anyway, its global convergence proof is rather cumbersome, which hinders the extension of the method and proof to time-delayed and/or uncertain systems. In this letter, we illustrate that the circle criterion can be used as an alternative method to prove the global convergence of the I\&I estimator. This also opens up the inclusion of time-delays and uncertainties. First, we demonstrate that the I&I wind speed estimator is equivalent to a torque balance estimator with a proportional correction term. As the nonlinearity in the estimator is sector bounded, the well-known circle criterion is applied to the estimator to guarantee its global convergence for time-delayed systems. By looking at the theoretical framework from this new perspective, this letter further proposes the addition of an integrator to the correction term to improve the estimator performance. Case studies show that the proposed estimator with an additional integral correction term is effective at wind speed estimation. Furthermore, its global convergence can be guaranteed by the circle criterion for time-delayed systems.

eess.SY↗

arXiv2021

Periodic Load Rejection for Floating Offshore Wind Turbines via Constrained Subspace Predictive Repetitive Control

Individual Pitch Control (IPC) is an effective control strategy to mitigate the blade loads on large-scale wind turbines. Since IPC usually requires high pitch actuation, the safety constraints of the pitch actuator should be taken into account when designing the controller. This paper introduces a constrained Subspace Predictive Repetitive Control (SPRC) approach, which considers the limitation of blade pitch angle and pitch rate. To fulfill this goal, a model predictive control scheme is implemented in the fully data-driven SPRC approach to incorporate the physical limitations of the pitch actuator in the control problem formulation. An optimal control law subjected to constraints is then formulated so that future constraint violations are anticipated and prevented. Case studies show that the developed constrained SPRC reduces the pitch activities necessary to mitigate the blade loads when experiencing wind turbulence and abrupt wind gusts. More importantly, the approach allows the wind farm operator to design conservative bounds for the pitch actuator constraints that satisfies safety limitations, design specifications and physical restrictions. This will help to alleviate the cyclic fatigue loads on the actuators, increase the structural reliability and extend the lifespan of the pitch control system.

eess.SY↗

arXiv2021

Blade Effective Wind Speed Estimation: A Subspace Predictive Repetitive Estimator Approach

Modern wind turbine control algorithms typically utilize rotor effective wind speed measured from an anemometer on the turbine's nacelle. Unfortunately, the measured wind speed from such a single measurement point does not give a good representation of the effective wind speed over the blades, as it does not take the varying wind condition within the entire rotor area into account. As such, Blade Effective Wind Speed (BEWS) estimation can be seen as a more accurate alternative. This paper introduces a novel Subspace Predictive Repetitive Estimator (SPRE) approach to estimate the BEWS using blade load measurements. In detail, the azimuth-dependent cone coefficient is firstly formulated to describe the mapping between the out-of-plane blade root bending moment and the wind speed over blades. Then, the SPRE scheme, which is inspired by Subspace Predictive Repetitive Control (SPRC), is proposed to estimate the BEWS. Case studies exhibit the proposed method's effectiveness at predicting BEWS and identifying wind shear in varying wind speed conditions. Moreover, this novel technique enables complicated wind inflow conditions, where a rotor is impinged and overlapped by wake shed from an upstream turbine, to be estimated.

eess.SY↗

arXiv2020

Fault-Tolerant Individual Pitch Control of Floating Offshore Wind Turbines via Subspace Predictive Repetitive Control

Individual Pitch Control (IPC) is an effective and widely-used strategy to mitigate blade loads in wind turbines. However, conventional IPC fails to cope with blade and actuator faults, and this situation may lead to an emergency shutdown and increased maintenance costs. In this paper, a Fault-Tolerant Individual Pitch Control (FTIPC) scheme is developed to accommodate these faults in Floating Offshore Wind Turbines (FOWTs), based on a Subspace Predictive Repetitive Control (SPRC) approach. To fulfill this goal, an online subspace identification paradigm is implemented to derive a linear approximation of the FOWT system dynamics. Then, a repetitive control law is formulated to attain load mitigation under operational conditions, both in healthy and faulty conditions. Since the excitation noise used for the online subspace identification may interfere with the nominal power generation of the wind turbine, a novel excitation technique is developed to restrict excitation at specific frequencies. Results show that significant load reductions are achieved by FTIPC, while effectively accommodating blade and actuator faults and while restricting the energy of the persistently exciting control action.

eess.SY↗