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An innovative and simplified method of electroless pure‑nickel coating was plated on graphene nanoplatelets (GNPs). The nickel-coated graphene nanoplatelets (NiGNPs) were uniformly dispersed in Inconel 625 (IN625) powder with the ratio of 1:9 by ball milling. Then laser cladding was used to fabricate the NiGNPs reinforced IN625 composite coatings. The survivability of NiGNPs, morphology of precipitated phase, microhardness through transverse section and wear resistance at room and elevated temperatures were studied. The results indicated that the NiGNPs were successfully incorporated into IN625 coatings by laser cladding. Part of them were deduced to be damaged or dissolved into molten pool, which benefited the formation of NbC, but most of them could be observed as exposed GNPs and well-distributed welded GNPs. Compared to laser cladded IN625 coating, the composite coating showed higher hardness at bottom region of cladded coating and smaller size of HAZ due to the improvement of thermal conductivity by additional NiGNPs. Furthermore, comparative wear test demonstrated that friction coefficient (COF) and wear rate were decreased at both room and elevated temperatures. Combined with wrinkled, tiled and rolled GNPs observed on the worn surface, it was revealed that the wear properties were efficiently benefited from superior lubrication between interlayers of GNPs.

This paper deals with a first passage mean-variance problem for semi-Markov decision processes in Borel spaces. The goal is to minimize the variance of a total discounted reward up to the system's first entry to some target set, where the optimization is over a class of policies with a prescribed expected first passage reward. The reward rates are assumed to be possibly unbounded, while the discount factor may vary with states of the system and controls. We first develop some suitable conditions for the existence of first passage mean-variance optimal policies and provide a policy improvement algorithm for computing an optimal policy. Then, two examples are included to illustrate our results. At last, we show how the results here are reduced to the cases of discrete-time Markov decision processes and continuous-time Markov decision processes.

In this paper, we deal with two-person zero-sum stochastic games for discrete-time Markov processes. The optimality criterion to be studied is the discounted payoff criterion during a first passage time to some target set, where the discount factor is state-dependent. The state and action spaces are all Borel spaces, and the payoff functions are allowed to be unbounded. Under the suitable conditions, we first establish the optimality equation. Then, using dynamic programming techniques, we obtain the existence of the value of the game and a pair of optimal stationary policies. Moreover, we present the exponential convergence of the value iteration and a ‘martingale characterization’ of a pair of optimal policies. Finally, we illustrate the applications of our main results with an inventory system.

A novel microsensor has been designed for the measurement of thermal conductivity of fluids based on the three omega (3ω) method. First, we theoretically analyzed the heat conduction using the 3ω method to demonstrate the mechanism of the microsensor to measure the thermal conductivity of a fluid. For the main structure of the microsensor, a heater was supported by the thin dielectric layers. In order to obtain the optimal parameters, we used the finite element method to simulate the working condition of the microsensor. In the simulation model, the effects of the thicknesses of the heater and dielectric layers on the thermal conductivity λ of the fluid were analyzed. The simulation results confirmed the validity and accuracy of conventional analytical calculations. Based on the simulation and theoretical calculation, a microsensor was optimally designed and fabricated to measure the thermal conductivity of fluids. Experimental data are consistent with those reported in the literature and demonstrate that the proposed sensor is effective for measuring thermal conductivity of fluids, including conductive ones.

In this paper we focus on the finite-horizon optimality for denumerable continuous-time Markov decision processes, in which the transition and reward/cost rates are allowed to be unbounded, and the optimality is over the class of all randomized history-dependent policies. Under mild reasonable conditions, we first establish the existence of a solution to the finite-horizon optimality equation by designing a technique of approximations from the bounded transition rates to unbounded ones. Then we prove the existence of ε (≥ 0)-optimal Markov policies and verify that the value function is the unique solution to the optimality equation by establishing the analog of the Itô-Dynkin formula. Finally, we provide an example in which the transition rates and the value function are all unbounded and, thus, obtain solutions to some of the unsolved problems by Yushkevich (1978).

Generally, the 3ω method for the measurement of fluid thermal properties is based on an approximate solution to heat conduction model assuming vanishing heater-thickness, no dielectric layer and infinite heater-length. In this study, a novel three-dimensional model and partial differential equations of the dimensionless heating conduction in frequency domain were established, which took into account the finite thicknesses of the heater and dielectric layer as well as a finite heater length to investigate thermal conductivity and diffusivity of fluid. Through the numerical studies, it was found that we could reduce the ratio of thickness to width of heater or the thickness and thermal conductivity of the dielectric layer to minimize discrepancy between the numerical results and the approximate solutions. Additionally, the edge effects of a finite heater length can be ignored at low measurement frequencies and high ratio of length to width of the heater.