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The purpose of this study is to propose an analytical model with consideration of the permeability of soft-magnetic materials, which can predict the magnetic field distribution more accurately and facilitate the initial design and parameter optimization of the machine.

This paper proposes an analytical model of stator yokeless radial flux dual rotor permanent magnet synchronous machine (SYRFDR-PMSM) with the consideration of magnetic saturation of soft-magnetic material. The analytical model of SYRFDR-PMSM is divided into seven regions along the radial direction according to the different excitation source and magnetic medium, and the iron permeability in each region is considered based on the Maxwell–Fourier method and Cauchy’s product theorem. The magnetic vector potential of each region is obtained by the Laplace’s or Poisson’s equation, and the magnetic field solution is determined using the boundary conditions of adjacent regions.

The inner and outer air-gap flux density, flux linkage, output torque, etc., of SYRFDR-PMSM are predicted by analytical model, resulting in good agreement with that of finite element model. Additionally, the SYRFDR-PMSM prototype is manufactured and the correctness of analytical model is further verified by experiments on no-load back electromotive force and current–torque curve. Reasonable design of the slot opening width and pole arc coefficient can improve the average output torque and reduce output torque ripple.

The analytical model proposed in this paper assumes that the permeability of soft-magnetic material is a fixed value. However, the actual iron’s permeability varies nonlinearly; thus, the prediction results of the analytical model will have some deviations from the actual machine.

The main contribution of this paper is to propose an accurate magnetic field analytical model of SYRFDR-PMSM. It takes into account the permeability of soft-magnetic material and slot opening, which can quickly and accurately predict the electromagnetic performance of SYRFDR-PMSM. It can provide assistance for the initial design and optimization of SYRFDR-PMSM.

This study aims to accurately calculate the magnetic field distribution, which is a prerequisite for pre-design and optimization of electromagnetic performance. Accurate calculation of magnetic field distribution is a prerequisite for pre-design and optimization.

This paper proposes an analytical model of permanent magnet machines with segmented Halbach array (SHA-PMMs) to predict the magnetic field distribution and electromagnetic performance. The field problem is divided into four subdomains, i.e. permanent magnet, air-gap, stator slot and slot opening. The Poisson’s equation or Laplace’s equation of magnetic vector potential for each subdomain is solved. The field’s solution is obtained by applying the boundary conditions. The electromagnetic performances, such as magnetic flux density, unbalanced magnetic force, cogging torque and electromagnetic torque, are analytically predicted. Then, the influence of design parameters on the torque is explored by using the analytical model.

The finite element analysis and prototype experiments verify the analytical model’s accuracy. Adjusting the design parameters, e.g. segments per pole and air-gap length, can effectively increase the electromagnetic torque and simultaneously reduce the torque ripple.

The main contribution of this paper is to develop an accurate magnetic field analytical model of the SHA-PMMs. It can precisely describe complex topology, e.g. arbitrary segmented Halbach array and semi-closed slots, etc., and can quickly predict the magnetic field distribution and electromagnetic performance simultaneously.

To apply the design concept of regional design, excavate the typical culture of Chongqing for the current design, and endows the cultural elements and symbols that have lasted for a long time with a new flavor of The Times, firstly, the design concept of regional design is introduced to present and analyze typical regional cultural elements of Chongqing. Then, the cultural appeal and social influence of the design of Chongqing rail transit are analyzed, and the main entry point of the design is summarized to provide theoretical reference and method guidance for the subsequent design. Finally, after completing the theoretical framework, typical case analysis and the reference of design techniques, the design procedure of rail vehicles with Chongqing regional culture is proposed, and the shape design, exterior design and the interior design are completed, which have certain guiding significance for the regional characteristics of rail transit construction in Chongqing.

Step length is a key factor for pedestrian dead reckoning (PDR), which affects positioning accuracy and reliability. Traditional methods are difficult to handle step length estimation of dynamic gait, which have larger error and are not adapted to real walking. This paper aims to propose a step length estimation method based on frequency domain feature analysis and gait recognition for PDR, which considers the effects of real-time gait.

The new step length estimation method transformed the acceleration of pedestrians from time domain to frequency domain, and gait characteristics of pedestrians were obtained and matched with different walking speeds.

Many experiments are conducted and compared with Weinberg and Kim models, and the results show that the average errors of the new method were improved by about 2 meters to 5 meters. It also shows that the proposed method has strong stability and device robustness and meets the accuracy requirements of positioning.

A sliding window strategy used in fast Fourier transform is proposed to implement frequency domain analysis of the acceleration, and a fast adaptive gait recognition mechanism is proposed to identify gait of pedestrians.

This study proposes an approach to solve the fundamental problem in using query-based methods (i.e. searching engines and patent retrieval tools) to screen patents of information and communication technology in construction (ICTC). The fundamental problem is that ICTC incorporates various techniques and thus cannot be simply represented by man-made queries. To investigate this concern, this study develops a binary classifier by utilizing deep learning and NLP techniques to automatically identify whether a patent is relevant to ICTC, thus accurately screening a corpus of ICTC patents.

This study employs NLP techniques to convert the textual data of patents into numerical vectors. Then, a supervised deep learning model is developed to learn the relations between the input vectors and outputs.

The validation results indicate that (1) the proposed approach has a better performance in screening ICTC patents than traditional machine learning methods; (2) besides the United States Patent and Trademark Office (USPTO) that provides structured and well-written patents, the approach could also accurately screen patents form Derwent Innovations Index (DIX), in which patents are written in different genres.

This study contributes a specific collection for ICTC patents, which is not provided by the patent offices.

The proposed approach contributes an alternative manner in gathering a corpus of patents for domains like ICTC that neither exists as a searchable classification in patent offices, nor is accurately represented by man-made queries.

A deep learning model with two layers of neurons is developed to learn the non-linear relations between the input features and outputs providing better performance than traditional machine learning models. This study uses advanced NLP techniques lemmatization and part-of-speech POS to process textual data of ICTC patents. This study contributes specific collection for ICTC patents which is not provided by the patent offices.

This paper aims to make clear the sensitive zone of subsea pipeline to stress corrosion cracking (SCC) under a disbonded coating.

The change of microenvironment under a disbonded coating in artificial seawater was analyzed by using a rectangular crevice cell. The SCC behavior of subsea pipeline was studied by slow strain rate tensile tests.

The microenvironment at the crevice bottom exhibits obvious acidification, Cl- aggregation and cathodic protection potential (CP) rise. Accordingly, the susceptibility of X70 steels to SCC is high due to the intensive anodic dissolution effect. At the opening, hydrogen atom can access into the steel and induce hydrogen embrittlement effect on account of the applied over-protected CP potential, resulting in a relatively high susceptibility to SCC. The corrosiveness of the microenvironment at crevice middle, however, is mild with proper CP potential; thus, the susceptibility of X70 steel to SCC here is lower than that obtained at the opening and the crevice bottom.

A rectangular crevice cell is built to survey the microenvironment evolution under a disbonded coating in situ. The sensitive zone of subsea pipeline to SCC under a disbonded coating is clarified.