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This research aims to present a novel cooperative control architecture designed specifically for roads with variations in height and curvature. The primary objective is to enhance the longitudinal and lateral tracking accuracy of the vehicle.

In addressing the challenges posed by time-varying road information and vehicle dynamics parameters, a combination of model predictive control (MPC) and active disturbance rejection control (ADRC) is employed in this study. A coupled controller based on the authors’ model was developed by utilizing the capabilities of MPC and ADRC. Emphasis is placed on the ramifications of road undulations and changes in curvature concerning control effectiveness. Recognizing these factors as disturbances, measures are taken to offset their influences within the system. Load transfer due to variations in road parameters has been considered and integrated into the design of the authors’ synergistic architecture.

The framework's efficacy is validated through hardware-in-the-loop simulation. Experimental results show that the integrated controller is more robust than conventional MPC and PID controllers. Consequently, the integrated controller improves the vehicle's driving stability and safety.

The proposed coupled control strategy notably enhances vehicle stability and reduces slip concerns. A tailored model is introduced integrating a control strategy based on MPC and ADRC which takes into account vertical and longitudinal force variations and allowing it to effectively cope with complex scenarios and multifaceted constraints problems.

In the analysis of structures in a fire situation by simplified and analytical methods, one assumption is that the fire resistance time is greater than or equal to the required fire resistance time. Among the methodologies involving the fire resistance time, the most used is the tabular method, which associates fire resistance time values to structural elements based on minimum dimensions of the cross section. The tabular method is widely accepted by the technical-scientific community due to the fact that it is safe and practical. However, its main criticism is that it results in lower fire resistance times than advanced thermal and thermostructural analysis methods. The objective of this study was to evaluate the fire resistance time of reinforced concrete beams and compare it with the required fire resistance time recommended by the tabular method of NBR 15200 (ABNT, 2012).

The fire resistance time and required fire resistance time of reinforced concrete beams were evaluated using, respectively, numerical models developed based on the finite element method and the tabular method of NBR 15200 (ABNT, 2012). The influence of the following parameters was investigated: longitudinal reinforcement cover, characteristic compressive strength of concrete, beam height, longitudinal reinforcement area and arrangement of steel bars.

Among the evaluated parameters, the covering of the longitudinal reinforcement proved to be more relevant for the fire resistance time, justifying that the tabular method of NBR 15200 (ABNT, 2012) being strongly and directly influenced by this parameter. In turn, more resistant concretes, higher beams and higher steel grades have lower fire resistance time values. This is because beams in these conditions have greater resistance capacity at room temperature and, consequently, are subject to external stresses of greater magnitude. In some cases, the fire resistance time was even lower than the required fire resistance time prescribed by NBR 15200 (ABNT, 2012). Both the fire resistance time and the required fire resistance time were not influenced by the arrangement of the longitudinal reinforcements.

The present paper innovates by demonstrating the influence of other important design variables on the required fire resistance time of the NBR 15200 (ABNT, 2012). Among several conclusions, it was found that the load level to which the structural elements are subjected considerably affects their fire resistance time. For this reason, it was recommended that the methods for calculating the required fire resistance time consider the load level. In addition, the article quantifies the security degree of the tabular method and exposes some situations for which the tabular method proved to be unsafe. Moreover, in all the models analyzed, the relationship between the span and the vertical deflection associated with the failure of the beams in a fire situation was determined. With this, a span over average deflection relationship was presented in which beams in fire situations fail.

The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.

This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.

The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.

This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.

The existing technology acceptance models have not yet investigated functional and motivational factors impacting trust in and use of conversational artificial intelligence (AI) by integrating the feedback and sequential updating mechanisms. This study challenged the existing models and constructed an integrated longitudinal model. Using a territory-wide two-wave survey of a representative sample, this new model examined the effects of hedonic motivation, social motivation, perceived ease of use, and perceived usefulness on continued trust, intended use, and actual use of conversational AI.

An autoregressive cross-lagged model was adopted to test the structural associations of the seven repeatedly measured constructs.

The results revealed that trust in conversational AI positively affected continued actual use, hedonic motivation increased continued intended use, and social motivation and perceived ease of use enhanced continued trust in conversational AI. While the original technology acceptance model was unable to explain the continued acceptance of conversational AI, the findings showed positive feedback effects of actual use on continued intended use. Except for trust, the sequential updating effects of all the measured factors were significant.

This study intended to contribute to the technology acceptance and human–AI interaction paradigms by developing a longitudinal model of continued acceptance of conversational AI. This new model adds to the literature by considering the feedback and sequential updating mechanisms in understanding continued conversational AI acceptance.

The purpose of this paper is to obtain values that stabilize the lateral and longitudinal flight of the quadrotor for which the morphing amount and the best Proportional-Integral-Derivative (PID) coefficients are determined by using the simultaneous perturbation stochastic approximation (SPSA) optimization algorithm.

Quadrotor consists of body and arms; there are propellers at the ends of the arms to take off and rotors that rotate them. By reducing the angle between mechanism 1 and the rotors with the horizontal plane, the angle between mechanism 2 and the arms, the rotors rise and different configurations are obtained. Conventional multi-rotor aircraft has a fixed fuselage and does not need a tail rotor to change course as helicopters do. The translational and rotational movements are provided by the rotation of the rotors of the aircraft at different speeds by creating moments about the geometric center in 6-degree-of-freedom (DOF) space. These commands sent from the ground are provided by the flight control board in the aircraft. The longitudinal and lateral flight stability and properties of different configurations evaluated by dynamic analysis and simulations in 6 DOF spaces are investigated. An algorithm and PID controller are being developed using SPSA to achieve in-flight position and attitude control of an active deformable aircraft. The results are compared with the results of the literature review and the results of the previous article.

With SPSA, the best PID coefficients were obtained in case of morphing.

The effects of quadrotor arm height and hub angle changes affect flight stability. With the SPSA optimization method presented in this study, the attitude is quickly stabilized.

With the optimization method, the most suitable PID coefficients and angle values for the lateral and longitudinal flight stability of the quadrotor are obtained.

The transition rate and PID coefficients are determined by using the optimization method, which is advantageous in terms of cost and practicality.

With the proposed method, the aircraft can change shape to adapt to different environments, and the parameters required for more stable flight for each situation will be calculated, and this will be obtained more quickly and safely with the SPSA optimization method.

The objective of this study is to investigate the impact of longitudinal forces on extreme-long heavy-haul trains, providing new insights and methods for their design and operation, thereby enhancing safety, operational efficiency and track system design.

A longitudinal dynamics simulation model of the super long heavy haul train was established and verified by the braking test data of 30,000 t heavy-haul combination train on the long and steep down grade of Daqing Line. The simulation model was used to analyze the influence of factors on the longitudinal force of super long heavy haul train.

Under normal conditions, the formation length of extreme-long heavy-haul combined train has a small effect on the maximum longitudinal coupler force under full service braking and emergency braking on the straight line. The slope difference of the long and steep down grade has a great impact on the maximum longitudinal coupler force of the extreme-long heavy-haul trains. Under the condition that the longitudinal force does not exceed the safety limit of 2,250 kN under full service braking at the speed of 60 km/h the maximum allowable slope difference of long and steep down grade for 40,000 t super long heavy-haul combined trains is 13‰, and that of 100,000 t is only 5‰.

The results will provide important theoretical basis and practical guidance for further improving the transportation efficiency and safety of extreme-long heavy-haul trains.

This paper aims to present a novel dynamic reliability model that considers the interval mixed uncertainty for the air-breathing hypersonic flight vehicle (AHFV) to guarantee flight safety and structural reliability.

Initially, the force condition of the fuselage is analyzed based on the longitudinal elastic model of an AHFV. Subsequently, a new high-efficiency dynamic reliability model is presented to describe the failure probability evolution of the fuselage structure. For the random uncertainty problem with interval distribution parameters, the interval PHI2 method of time-dependent reliability is used to obtain the time-dependent reliability interval of the AHFV. Finally, the key variables that affect the failure probability accumulation are determined, which provide an important reference for ensuring structural reliability and improving the life span of AHFVs.

It is demonstrated that the proposed reliability model can obtain more accurate dynamic reliability results for the fuselage, and it is confirmed the key variables that affect the failure probability accumulation. The results also provide an important reference for the reliability analysis of hypersonic vehicles.

The novelty of this work comes from the first application of the PHI2 method (considering the interval mixed uncertainty) in the AHFV and the development of a new reliability model for the entire body of AHFVs. The proposed analysis scheme is implemented on the dynamic model of the AHFV, which provides a more accurate reference for improving the structural reliability and life span of AHFVs.

Accurately estimating the severity of derailment is a crucial step in quantifying train derailment consequences and, thereby, mitigating its impacts. The purpose of this paper is to propose a simplified approach aimed at addressing this research gap by developing a physics-informed 1-D model. The model is used to simulate train dynamics through a time-stepping algorithm, incorporating derailment data after the point of derailment.

In this study, a simplified approach is adopted that applies a 1-D kinematic analysis with data obtained from various derailments. These include the length and weight of the rail cars behind the point of derailment, the train braking effects, derailment blockage forces, the grade of the track and the train rolling and aerodynamic resistance. Since train braking/blockage effects and derailment blockage forces are not always available for historical or potential train derailment, it is also necessary to fit the historical data and find optimal parameters to estimate these two variables. Using these fitted parameters, a detailed comparison can be performed between the physics-informed 1-D model and previous statistical models to predict the derailment severity.

The results show that the proposed model outperforms the Truncated Geometric model (the latest statistical model used in prior research) in estimating derailment severity. The proposed model contributes to the understanding and prevention of train derailments and hazmat release consequences, offering improved accuracy for certain scenarios and train types

This paper presents a simplified physics-informed 1-D model, which could help understand the derailment mechanism and, thus, is expected to estimate train derailment severity more accurately for certain scenarios and train types compared with the latest statistical model. The performance of the braking response and the 1-D model is verified by comparing known ride-down profiles with estimated ones. This validation process ensures that both the braking response and the 1-D model accurately represent the expected behavior.

A paradigm shift toward a corporate model of higher educational settings has led to complex and excess work demands, yet the potential long-run ramifications of work overload are still under-examined. Building the arguments on the “spiral of resource loss” corollary of the conservation of resources (COR) theory, the authors have bridged this gap by testing how work overload spills over into career resilience via reduced harmonious passion. In addition, the authors compare how the employees having standardized workloads differ in their harmonious passion and career resilience from those having excessive (non-standardized) workloads.

Through a longitudinal natural field experiment of 402 faculty members [N = 198 in the standardized group (optimal load) and N = 204 in the non-standardized group (overload)] working in higher educational institutions of Pakistan, data were collected in three waves (each six months apart). The group comparison, trend analysis and longitudinal mediation analysis done through SPSS and MPlus affirmed the hypothesized associations.

The results have shown that work overload impacts career resilience through the mediating role of harmonious passion. The faculty members in the standardized workload had more passion and career resilience as compared to the non-standardized workload group. In addition, these impacts intensified overtime for the overloaded faculty members while faculty members with optimal workload sustained their passion and resilience for the teaching profession.

Taking the COR perspective, this study sheds light on how faculty members' work overloads reduce their capability to retain their passion and resilience for teaching from a longitudinal and experimental perspective.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.