The flow approach to swept volume

In this thesis, a method for representing swept volume based on the sweep differential equation and sweep vector field flow is developed. This method can be used to determine the boundary representation of a swept volume generated by any polygonal object undergoing a general smooth 2-D sweep. For any given sweep and object, a. set of candidate boundary points is computed using a selection criterion based on vector field behavior. The set of candidate boundary points is then trimmed in order to obtain the true boundary of the swept volume. This trimming procedure is based on some simple topological principles and it utilizes the concept of extended sweep. This method is more general and efficient than existing approaches (e. g. it can readily deal with the cases in which the swept volume area. has holes ) and can easily be extended to 3-D sweeps; the 3-D extension is discussed but only briefly. Several examples are given to illustrate the implementation of the prototype software for 2-D sweeps which has been developed in conjunction with this research

Actively controlling the topological transition of dispersion based on electrically controllable metamaterials

Topological transition of the iso-frequency contour (IFC) from a closed ellipsoid to an open hyperboloid, will provide unique capabilities for controlling the propagation of light. However, the ability to actively tune these effects remains elusive and the related experimental observations are highly desirable. Here, tunable electric IFC in periodic structure which is composed of graphene/dielectric multilayers is investigated by tuning the chemical potential of graphene layer. Specially, we present the actively controlled transportation in two kinds of anisotropic zero-index media containing PEC/PMC impurities. At last, by adding variable capacitance diodes into two-dimensional transmission-line system, we present the experimental demonstration of the actively controlled magnetic topological transition of dispersion based on electrically controllable metamaterials. With the increase of voltage, we measure the different emission patterns from a point source inside the structure and observe the phase-transition process of IFCs. The realization of actively tuned topological transition will opens up a new avenue in the dynamical control of metamaterials.Comment: 21 pages,8 figure

Investigation of the Spatial Variability of Steel Weight Loss and Corrosion Cracking: A Novel X-ray Technique

The performance of corrosion-affected RC members depends strongly on localized damages of reinforcement. Therefore, modeling the spatial variability of steel corrosion is very important for the assessment of the remaining service life of corroded structures or time for maintenance. To study the changes of spatial variability of steel weight loss over time, a continuous monitoring is necessary. In this paper, a novel procedure of X-ray technique application in monitoring the spatial growth of a corroded bar in a RC specimen is demonstrated along with the digital image processing of X-ray images to estimate the steel weight loss. The relationship of steel weight loss and corrosion cracking is studied at different stages of corrosion. The validity of the estimation method of steel weight loss is also presented. In this study, a novel procedure of X-ray technique application in monitoring the spatial growth of corroded bars in RC specimens is demonstrated along with the digital image processing of X-ray images to estimate the steel weight loss. A single RC beam (80 mm × 140 mm × 1460 mm) reinforced with a longitudinal rebar and stirrups were fabricated for the investigation. The steel corrosion was accelerated via an electrochemical test. The relationship of steel weight loss and corrosion cracking was studied at different stages of corrosion. The validity of the method was also discussed. The outcome of spatial variability of steel weight loss might be used to validate analytical models for estimating non-uniform steel corrosion or incorporated with inspected corrosion levels of in-situ structures for the input data in a predicting model to estimate the long-term structural performance of corroded RC structures

AudioFormer: Audio Transformer learns audio feature representations from discrete acoustic codes

We propose a method named AudioFormer,which learns audio feature representations through the acquisition of discrete acoustic codes and subsequently fine-tunes them for audio classification tasks. Initially,we introduce a novel perspective by considering the audio classification task as a form of natural language understanding (NLU). Leveraging an existing neural audio codec model,we generate discrete acoustic codes and utilize them to train a masked language model (MLM),thereby obtaining audio feature representations. Furthermore,we pioneer the integration of a Multi-Positive sample Contrastive (MPC) learning approach. This method enables the learning of joint representations among multiple discrete acoustic codes within the same audio input. In our experiments,we treat discrete acoustic codes as textual data and train a masked language model using a cloze-like methodology,ultimately deriving high-quality audio representations. Notably,the MPC learning technique effectively captures collaborative representations among distinct positive samples. Our research outcomes demonstrate that AudioFormer attains significantly improved performance compared to prevailing monomodal audio classification models across multiple datasets,and even outperforms audio-visual multimodal classification models on select datasets. Specifically,our approach achieves remarkable results on datasets including AudioSet (2M,20K),and FSD50K,with performance scores of 53.9,45.1,and 65.6,respectively. We have openly shared both the code and models: https://github.com/LZH-0225/AudioFormer.git.Comment: 9 pages, 4 figure