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This paper aims to derive a reduced-order model for the heat transfer across the interface between a millimetric thermocapillary liquid bridge from silicone oil and the surrounding ambient gas.

Numerical solutions for the two-fluid model are computed covering a wide parametric space, making a total of 2,800 numerical flow simulations. Based on the computed data, a reduced single-fluid model for the liquid phase is devised, in which the heat transfer between the liquid and the gas is modeled by Newton’s heat transfer law, albeit with a space-dependent Biot function Bi(z), instead of a constant Biot number Bi.

An explicit robust fit of Bi(z) is obtained covering the whole range of parameters considered. The single-fluid model together with the Biot function derived yields very accurate results at much lesser computational cost than the corresponding two-phase fully-coupled simulation required for the two-fluid model.

Using this novel Biot function approach instead of a constant Biot number, the critical Reynolds number can be predicted much more accurately within single-phase linear stability solvers.

The Biot function for thermocapillary liquid bridges is derived from the full multiphase problem by a robust multi-stage fit procedure. The derived Biot function reproduces very well the theoretical boundary layer scalings.

The characteristic of static is quite important especially for the manipulator with force feedback. This paper aims to improve the traditional static model by considering the limitations such as lacking of versatility and ignoring gravity of links. For this purpose, a new asymmetric mass distribution method on the analysis of universal “force-sensing” model has been put forward to overcome the limitations.

Through the forces and torques analysis of every link and the moving platform, the static model of 3-RUU manipulator is acquired. Then, based on the physical meaning analysis of every part in the static model of 3-RUU manipulator, a new asymmetric mass distribution method on the analysis of universal “force-sensing” model can be obtained.

The correctness of the static model of 3-RUU manipulator is verified by simulation results based on Pro/Engineer software and Adams software. Furthermore, experiment results based on a manipulator similar to the Omega.3 manipulator indicate that the universal “force-sensing” model can be applicable to the above manipulator.

A new asymmetric mass distribution method on the analysis of universal static mathematical model has been put forward. Based on physical meaning of the above method, the “force-sensing” model can be established quickly and it owns versatility, which can be applicable to the 3-RUU manipulator, the Omega.3 parallel manipulator and other similar manipulators with force feedback. In addition, it can improve the accuracy of the “force-sensing” model to a great extent.

High-speed Indium Phosphide (InP) HBTs have been widely used to design high-speed analog, digital and mixed-signal integrated circuits. The purpose of this study is to propose a new parameter extraction procedure for determining an improved T-topology small-signal equivalent circuit of InP heterojunction bipolar transistors (HBTs).

The alternating current crowding effect is considered through adding the intrinsic base capacitance in the small-signal equivalent circuit. All of the circuit parameters are extracted directly without using any approximation.

The extraction technique is more easily understood and clearer than other extraction methods, as the equations are derived from the S-parameters by peeling peripheral elements from small-signal models to get reduced ones and extracting each equivalent-circuit parameter using each equation.

To validate the presented parameter extraction technology, an n-p-n emitter-up InP HBT was analyzed adopting the method. Excellent agreement between measured and modeled S-parameters is obtained up to 40 GHz.

Even though multi-rotor aircrafts are becoming more and more prevalent in the fields of aerial photography, agricultural spraying, disaster searching and rescuing, how to achieve higher reliability and robustness of an aircraft still poses a big challenge. It is not a rare case that a multi-rotor aircraft is severely damaged or crushed when an actuator or sensor is malfunctioned. This paper aims at the resilience of an aircraft when a rotor is malfunctioned.

The reliability of a multi-rotor aircraft can be measured in terms of stability, robustness, resilience and fault tolerance. All of these four aspects are taken into consideration to improve overall reliability of aircrafts. When a rotor malfunction occurs, the control algorithm is cable of adjusting the operation conditions of the rest of rotors to achieve system stability.

In this paper, the authors first present a research topic on the development of a resilient multi-robot aircraft. A multi-rotor aircraft usually possesses more actuated motions than the required degrees of freedom.

The authors proposed to equip the multi-rotor aircraft with malfunction detecting sensors, and they developed the self-repairing algorithm to re-stabilize the aircraft when a malfunction of a rotor occurs. The design concept and methods were implemented on an eight-rotor aircraft, and the performance of the proposed instrumentation and self-repairing algorithm have been verified and validated.

The purpose of this paper is to illustrate the importance of redesigning, reusing, remanufacturing, recovering, recycling and reducing (6R) to sustainable manufacturing and discuss the general procedure to reconfigure robots. Two critical challenges in adopting industrial robots in small and medium-sized enterprise (SMEs) are flexibility and cost, as the number of tasks of the same type can be limited because of the size of an SME. The challenges can be alleviated by 6R. The 6R processes allow a robot to adopt new tasks, increase its utilization rate and reduce unit costs of products.

There is no shortcut to implement sustainable manufacturing. All of the manufacturing resources in a system should be planned optimally to reduce waste and maximize the utilization rates of resources. In this paper, modularization and reconfiguration are emphasized to implement 6R processes in sustainable manufacturing; robots are especially taken into consideration as core functional modules in the system. Modular architecture makes it feasible to integrate robots with low-cost customized modules for various tasks for the high utilization rates. A case study is provided to show the feasibility.

Finding the ways to reuse manufacturing resources could bring significant competitiveness to an SME, in the sense that sophisticated machines and tools, such as robots, can be highly utilized even in a manufacturing environment with low or medium product volumes. The concepts of modularization and 6R processes can be synergized to achieve this goal.

The authors propose the strategy to enhance the utilization rates of core manufacturing resources using modular architecture and 6R practice. The axiomatic design theory can be applied as the theoretical fundamental to guide the 6R processes; however, a universal solution in the implementation is not available. The solutions have to be tailored to specific SMEs, and the solutions should vary with respect to time.

To operate a sustainable manufacturing system, a continuous design effort is required to reconfigure existing resources and enhance their capabilities to fulfill new tasks in the dynamic environment.

The authors focus on the importance of sustainable manufacturing to modern society, and they achieve this goal by reusing robots as system components in different applications.

Sustainable manufacturing has attracted a great deal of attention, although the operable guidance for system implementation is scarce. The presented work has thrown some light in this research area. The 6R concept has been introduced in a modular system to maximize the utilizations of critical manufacturing resources. It is particularly advantageous for SMEs to adopt sophisticated robots cost-effectively.

The study aims to investigate the mediating impact of supplier quality integration on the operational performance of the pharmaceutical supply chain (PSCs) by comparing mature and evolving PSCs.

The study adopted a quantitative method where data were gathered through a survey instrument to identify the differentiators of dynamic capabilities and establish the extent of quality integration in PSCs. Thus, 310 questionnaires were collected from mature and evolving PSCs, where the PROCESS technique was used to analyse the data.

The results demonstrate the significant paths that enable companies to create, extend and modify the resources to develop their dynamic capabilities. The results reveal significant differences in internal and supplier quality implementation and their impact on operational performance between mature and evolving PSCs.

To the best of our knowledge, this is the first study to examine dynamic capabilities aspects of the pharmaceutical supply chain quality integration in mature and evolving PSCs, which extends the body of knowledge and makes a practical contribution.

Based on the context of the Internet of Things (IoT), the territorial public emergency supplies will be networked, platform-based management, unified emergency dispatch. The problem of supplies dispatching in the “last kilometer” of emergency is solved, and the supplies needed in the disaster area are promptly delivered to the hands of the victims so that they can quickly be rescued after the disaster and to save valuable time for rapid rescue, which can greatly decrease casualties and property losses. This paper aims to discuss these issues.

By analyzing the shortage of existing emergency supplies dispatching research and taking all factors such as disaster area demand, social reserve, road conditions, mode of transport, loading limit, disaster area satisfaction rate and road capacity into consideration under the background of IoT, a variety of the territorial emergency supplies dispatching model with more rescue points, more affected areas are constructed. The objective function of the model is to aim in finding the shortest rescue time, giving the solution algorithm, and finally simulating the simulation case.

Based on the context of the IoT, the territorial public emergency supplies will be networked, platform-based management, unified emergency dispatch. Considering factors such as road conditions, modes of transport and road capacity, the authors construct a number of emergency rescue plans, multiple disaster scenarios and various emergency supplies dispatching models. The authors simulate the situation through simulation cases with the shortest time being the ultimate goal. The problem of supplies dispatching in the “last kilometer” of emergency is solved, and the supplies needed in the disaster area are promptly delivered to the hands of the victims so that they can quickly be rescued after the disaster and to save valuable time for rapid rescue, which can greatly decrease casualties and property losses.

This paper provides little research on the dispatch of emergency supplies. The problems of direct dispatch from the rescue point to the affected area and dispatch of supplies without relying on the arrival of emergency supplies at the rear are addressed. Therefore, this study does not focus on the arrival of emergency supplies at the rear but on direct dispatching issues during territorial public emergency supplies from the rescue point to the disaster point.

This study aims to investigate the morphology and physicochemical properties of BiOBr/Polyvinylidene fluoride (PVDF) composite membranes and the differences in the properties of BiOBr/PVDF composite membranes made by adding different precursor ratios during the casting process.

In this paper, sodium bromide and Bi(NO3)3 were used as precursors for the preparation of BiOBr photocatalysts, and PVDF membranes were modified by using the phase conversion method in conjunction with the in situ deposition method to produce BiOBr/PVDF hydrophilic composite membranes with both membrane separation and photocatalytic capabilities.

The characterization results confirmed that the composites were successfully and homogeneously co-mingled in the PVDF membranes. The related performance of the composite membrane was tested, and it was found that the composite membrane with the optimal precursor incorporation ratio had good photocatalytic efficiency and antipollution ability; the removal efficiencies of methyl orange, rhodamine B and methylene blue were 80.43%, 85.02% and 86.94%, respectively, in 2.5 h. The photocatalytic efficiency of composite membranes with different precursor ratios increased and then decreased with the increase of the precursor addition ratio.

The composite membrane is prepared by phase conversion method with in situ deposition method, and the BiOBr material has unique advantages for the degradation of organic dyes. The comprehensive experimental data can be known that the composite membrane prepared in this paper has high degradation efficiency and good durability for organic dyes.

This paper aims to propose a dynamic parameter identification method based on sensitivity analysis for the 5-degree of freedom (DOF) hybrid robots, to solve the problems of too many identification parameters, complex model, difficult convergence of optimization algorithms and easy-to-fall into a locally optimal solution, and improve the efficiency and accuracy of dynamic parameter identification.

First, the dynamic parameter identification model of the 5-DOF hybrid robot was established based on the principle of virtual work. Then, the sensitivity of the parameters to be identified is analyzed by Sobol’s sensitivity method and verified by simulation. Finally, an identification strategy based on sensitivity analysis was designed, experiments were carried out on the real robot and the results were verified.

Compared with the traditional full-parameter identification method, the dynamic parameter identification method based on sensitivity analysis proposed in this paper converges faster when optimized using the genetic algorithm, and the identified dynamic model has higher prediction accuracy for joint drive forces and torques than the full-parameter identification models.

This work analyzes the sensitivity of the parameters to be identified in the dynamic parameter identification model for the first time. Then a parameter identification method is proposed based on the results of the sensitivity analysis, which can effectively reduce the parameters to be identified, simplify the identification model, accelerate the convergence of the optimization algorithm and improve the prediction accuracy of the identified model for the joint driving forces and torques.

This chapter explored health and safety considerations in stealth construction, emphasising the integration of advanced technologies and innovative practices. It commences with a general introduction, followed by a historical overview of safety practices in the construction industry, highlighting the evolution of a safety culture. The chapter examined various health and safety management techniques, including policy formulation, safety training programs, and job safety analysis. Additionally, it discussed current trends such as wearable technology, IoT, VR/AR, and predictive analytics. The unique requirements of stealth construction are addressed, focusing on building cross-section design, visibility, application of radio frequency emission and countermeasures. Finally, it presents a comprehensive approach to achieving stealth construction, emphasising environmental protection, safety, speed, economy, and aesthetics, and provides practical examples to illustrate these concepts.