Search results

The purpose of this paper is to present the performance requirements for the all-electric high lift motors and the inductance calculation process for the fractional slot concentrated winding.

This paper presents the research work related to all-electric aircraft high lift motors and the inductance calculation process of fractional slot concentrated winding. Firstly, this paper introduces the performance requirements for the high lift motor and summarizes the general process for calculating the inductance in fractional slot motors. Secondly, the analytical model of winding armature total inductance is obtained by the winding function method. Thirdly, a straightforward calculation method is employed for determining the total slot leakage inductance. Finally, the accuracy of the inductance calculation and controllability of the motor are confirmed through finite element model and motor control strategies.

In the fractional slot concentrated winding, the armature total inductance is equal to the armature self-inductance plus the armature mutual inductance. The slot leakage inductance is divided into the slot leakage self-inductance and the slot leakage mutual inductance. This allows inductance to be obtained quickly without finite element model.

This paper provides the inductance results of analytical and finite element simulation; the control strategy is employed to verify the conformity of the design requirements and control performance under the rated conditions. The implementation of double verification assures the practicality and effectiveness of the high lift motor.

To improve the output torque density of the machine and to be better suited for automation applications, this paper aims to propose a double-permanent-magnet enhanced hybrid stepping machine (DPMEHSM) with tangential and radial magnetization.

First, the structure of DPMEHSM is introduced and its operation principle is analyzed by describing the variation in stator poles versus time. Second, based on the similar electrical load and amount of PM, the size equations of the DPMEHSM are designed and the main parameters are presented. Third, the electromagnetic performances including the PM flux linkage distribution, magnetic density distribution, air-gap field, back electromotive force (back-EMF), detent torque, holding torque and output torque of DPMEHSM and stator-PM hybrid stepping machine (SPMHSM) are analyzed based on the finite element method.

The results show that the DPMEHSM has superiority in back-EMF, holding torque and output torque.

This paper proposes a DPMEHSM with tangential and radial magnetization to improve the output torque density.

This study constructed an information search process model based on costs and benefits to reflect different information search processes under different decisions from a behavioural economics perspective.

This study used a deductive approach to conceptualise the costs, benefits, and uncertainties of the information search process. Subsequently, we constructed an information search process model based on the costs and benefits using graphical reasoning, loss aversion theory, bounded rationality theory, the satisficing theory of behavioural economics, and the uncertainty changes of information search process.

The model revealed four types of user behaviours in the information search process: (1) avoiding search at the initiation of the search process; (2) exiting in the middle of a search; (3) stopping at the point of satisficing; and (4) continuing the search until experiencing physical discomfort.

The model constructed in this study treats the information search as a process based on costs and benefits with uncertainty. This model integrates information search avoidance and stopping into an information search process model. The model identifies users’ bounded rationality by evaluating ideal and real situations. Moreover, the model explains relative and absolute information overloads and the area beyond the user’s bounded rationality. These findings could help improve users’ information literacy and optimise information systems.

This study aims to investigate the impact of indium (In) content on the thermal properties, microstructure and mechanical properties of Sn-3Ag-3Sb-xIn (x = 0, 1, 2, 3, 4, 5 Wt.%) solders to enhance the performance of tin-based solder under demanding conditions and to meet the urgent need for high-reliability microelectronic interconnection materials in emerging sectors such as automotive intelligent technology, 5G communication technology and high-performance computing.

In this study, Sn-3Ag-3Sb-xIn solder alloys were prepared. The thermal properties of the solder alloys were characterised by differential scanning calorimetry. Subsequently, optical microscopy, scanning electron microscopy, X-ray diffraction and an electron probe X-ray microanalyser were used to analyse the influence of the In content on the microstructure of the solder. The mechanical properties of solder alloys were determined through tensile testing.

As the In content increased, the melting temperature of the Sn-3Ag-3Sb-xIn solder decreased, accompanied by less nucleation undercooling and an expanded melting range. The incorporation of In led to an enhancement in the yield and tensile strengths of the Sn-3Ag-3Sb-xIn solder alloys, but with a concomitant decrease in plasticity. In comparison to commercial Sn-3.0Ag-0.5Cu solder alloys, the yield strength and tensile strength of the Sn-3Ag-3Sb-3In alloy increased by 8.64 and 21.69 MPa, respectively, while the elongation decreased by 11.48%.

Sn-3Ag-3Sb-3In solder alloy was the most appropriate and expected comprehensive properties. The enhancements will provide substantial assistance and precise data references for the interconnection requirements in high-strength interconnection fields, such as automotive intelligent technology, 5G communication technology and high-performance computing.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.

The reliability of solder joints is closely related to the growth of an intermetallic compound (IMC) layer between the lead-free solder and substrate interface. This paper aims to investigate the growth behavior of the interfacial IMC layer during isothermal aging at 125°C for Sn-3Ag-3Sb-xIn/Cu (x = 0, 1, 2, 3, 4, 5 Wt.%) solder joints with different In contents and commercial Sn-3Ag-0.5Cu/Cu solder joints.

In this paper, Sn-3Ag-3Sb-xIn/Cu (x = 0, 1, 2, 3, 4, 5 Wt.%) and commercial Sn-3Ag-0.5Cu/Cu solder were prepared for bonding Cu substrate. Then these samples were subjected to isothermal aging for 0, 2, 8, 14, 25 and 45 days. Scanning electron microscopy and transmission electron microscopy were used to analyze the soldering interface reaction and the difference in IMC growth behavior during the isothermal aging process.

When the concentration of In in the Sn-3Ag-3Sb-xIn/Cu solder joints exceeded 2 Wt.%, a substantial amount of InSb particles were produced. These particles acted as a diffusion barrier, impeding the growth of the IMC layer at the interface. The growth of the Cu₃Sn layer during the aging process was strongly correlated with the presence of In. The growth rate of the Cu₃Sn layer was significantly reduced when the In concentration exceeded 3 Wt.%.

The addition of In promotes the formation of InSb particles in Sn-3Ag-3Sb-xIn/Cu solder joints. These particles limit the growth of the total IMC layer, while a higher In content also slows the growth of the Cu₃Sn layer. This study is significant for designing alloy compositions for new high-reliability solders.

This study investigates the influence of nonfinancial 8-K disclosures released during the earnings announcement window on the abnormal trading activities of individual investors.

We employ regression analysis in this empirical study to examine the impact of nonfinancial 8-K filings on individual investors' abnormal trading activities.

Our results reveal that individual investors exhibit higher levels of abnormal trading activities when firms release nonfinancial 8-Ks during the (0,1) window of earnings announcements. This effect is observed for both buyer-initiated and seller-initiated transactions and is particularly pronounced for firms reporting an operating loss. Negative sentiment in 8-Ks significantly intensifies such effect. Additionally, we find that buy-sell consensus increases significantly with concurrent nonfinancial 8-Ks. This suggests that 8-Ks may reduce information noise, leading individuals to trade with greater conviction.

Our study examines the joint influence of nonfinancial 8-Ks and earnings announcements on individual investors' trading activities, thereby providing a novel perspective on the mechanisms through which 8-K filings affect individual investors' trading behaviors.

This paper investigates individual investors' responses to stock underpricing and how their trading decisions are affected by analysts' forecasts and recommendations.

This empirical study uses mutual fund fire sales as an exogenous source that causes stock underpricing and analysts' forecasts and recommendations as price-correcting information. The study further uses regression analysis to examine individual investors' responses to fire sales and how their responses vary with price-correcting information.

The authors first show that individual investors respond to mutual fund fire sales by significantly decreasing net buys, and this effect appears to be prolonged. Next, the authors find that the decrease of net buys diminishes following analysts' price-correcting earnings forecast revisions and stock recommendation changes. Hence, the authors suggest that individual investors are not “wise” enough to recognize flow-driven underpricing; however, this response is weakened by analysts' price-correcting information.

There is an ongoing debate in the literature about whether individual investors should be portrayed as unsophisticated traders or informed traders who can predict future returns. The authors study a unique information event and provide new evidence related to both perspectives. Overall, our evidence suggests that the “unsophisticated traders” perspective is predominant, whereas a better information environment significantly reduces individual investors' information disadvantage. This finding could be of interest to both academic researchers and regulators.

The purpose of this paper is to develop the model of telemetry data processing flow (TDPF) for TDPF development and the TDPF run-time infrastructure to improve the spacecraft health monitoring capability.

This research tries to develop the TDPF by flow-based programming (FBP) method and the component-based telemetry data processing software.

The result from the case study is positive, thus reflecting the appropriateness of the suggested method.

Application of the proposed TDPF model and the component-based telemetry data processing software may result in improved development efficiency and less development costs.

This paper provides an effective way to develop TDPF without recompiling the software. It greatly facilitates the TDPF development that hopefully will save the TDPF development cost.