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Bearing fault diagnosis is an important research field for rotating machinery health monitoring. Recently, many intelligent fault diagnosis methods driven by big data, such as transfer learning, have been studied. However, there are two shortcomings for the prior transfer learning method in industry application. First, it is necessary to design a complex loss function to enhance the similarity between the two domains further. Second, previous studies required big data both in source and target task, without considering the lack of sufficient training samples. Inspired by relevant research work, this article proposes a local joint distribution discrepancy to increase similar features. A sub-domain adaptive transfer learning is designed to detect bearing faults based on the residual network. Two kinds of transfer experiments are designed to verify the method effectiveness. After that, the impact of small training samples and noise on the results is explored. The proposed method reaches high accuracy. [ABSTRACT FROM AUTHOR]

• An experimental dataset of flow boiling heat transfer in mini channels with pin fins was built. • A transfer learning framework was proposed to predict the heat transfer coefficient. • The effects of different factors on heat transfer coefficient prediction accuracy was identified. Flow boiling in mini channels with micro pin fins is a promising heat sink technique to achieve high-efficient aircraft thermal management. The accurate prediction of its heat transfer coefficient is critical for the practical design of two-phase heat exchanger based on mini channels with micro pin fins. Previous investigation shows that heat transfer coefficient prediction accuracy of the machine learning method is generally better than that of conventional empirical correlations. However, the machine learning method cannot guarantee its prediction accuracy among different data domains. To extend the application region of the conventional machine learning method, a transfer learning framework was proposed in present study. First of all, an experimental system was built to acquire test data from different sample domains (i.e., the diamond pin fins with different geometries). Then a conventional machine learning model was developed based on the deep learning method. Furthermore, the developed deep learning model was adjusted with transfer learning process, and the performance of these two kinds of models (i.e., conventional machine learning model and transfer learning model) was comprehensively evaluated. Results showed that the conventional machine learning model had a good prediction accuracy with an overall deviation of 4.11 % but was only confined in the same data domain as training data. Differently, the transfer learning model with 70 % data set from the new domain can achieve appropriate prediction in the new domains with deviation of 4.28 %. The results of this paper demonstrated that the conventional machine learning model can extend into different domains with reasonable prediction accuracy through transfer learning frameworks. It will benefit the practical design of high-efficiency heat exchangers for aircraft thermal management. [ABSTRACT FROM AUTHOR]

This paper evaluates the potential usage of graphene/crosslinked polyethylene (graphene/XLPE) as the insulating material for high voltage direct current (HVDC) cables. Thermal, mechanical and electrical properties of blends with/without graphene were evaluated by differential scanning calorimetry (DSC), tensile strength, DC conductivity, space charge measurements and water tree aging test. The results indicate that 0.007–0.008% weight amount of graphene can improve the mechanical and electrical insulation properties of XLPE blends, namely higher tensile/yield strength, improved space charge distribution, and shorter/fewer water tree branches. The improvements mainly attribute to the high stiffness of graphene, deep traps introduced by the interaction zones of graphene and XLPE, and the blockage effect of graphene within XLPE. For thermal performance of XLPE blends, graphene nano-fillers have but limited improvement. The crystallinity of the blends barely changes with the addition of graphene. However, the crosslinking degree increases as the additive-like amounts of graphene doped. The above findings provide a guide for tailoring lightweight XLPE materials with excellent mechanical and electrical performances by doping them with a small amount of graphene. [ABSTRACT FROM AUTHOR]

To improve the reliability of power systems, online cable condition monitoring must be implemented to replace traditional regular power outage maintenance. Existing online monitoring methods have certain limitations. In this article, a novel method based on low-frequency signal injection is proposed to monitor power cable insulation conditions online. For this method, a low-frequency signal is injected into the power system via the potential transformer (PT) open delta configuration. The cable conductor voltage and leakage current are detected. The interpolating windowed fast Fourier transform (FFT) algorithm is applied to calculate the dielectric loss angle. Then, the cable tangent delta ($\tan \delta $) can be deduced, and the cable condition can be assessed. A distribution network system is built based on the power system computer-aided design (PSCAD) software. The frequency and amplitude of the injected signal are simulated and discussed. An online monitoring platform is established in the laboratory. Thermal-aged cable samples and water tree-aged cable samples are prepared and measured. The experimental results confirm that the proposed method can effectively assess power cable insulation. [ABSTRACT FROM AUTHOR]

This paper presents a novel oscillation wave test system (OWTS) to detect the partial discharge (PD) of mounting defects in power cable insulation. In the proposed system, a charging capacitor is added to the circuit topology based on the traditional OWTS. The charging capacitor is charged to the desired voltage by a high-voltage DC power source. After the charging process, the test cable sample is charged by the capacitor. The resonant circuit is formed by the charging capacitor, the test cable, and the resonant reactor to create an oscillating decay voltage. With this novel method, no space charge is injected into the cable insulation. The effect of the charging capacitance on the charging efficiency is calculated with the Multisim software. This paper describes the working principle and the assembly of a laboratory prototype for the PD detection of a 500 m cable circuit. The test results show the feasibility of the novel OWTS method. [ABSTRACT FROM AUTHOR]

The onsite partial discharge (PD) detection of cable insulation is of great importance for power system maintenance. To preserve more basic features of denoised PD signal, in this paper, a PD denoising by a new class of affine projection algorithm (APA) is proposed based on the high-order error power (HOEP) criterion. We propose a new affine projection least mean absolute third algorithm (APLMATA), which exploits the HOEP criterion ($p=3$) and can achieve reliable performance under Gaussian interference. We further develop a modified APLMATA (MAPLMATA) to reduce the misadjustment with moderate computational burden. Analytical models are derived for MAPLMATA for Gaussian signals. To enhance the stability of the algorithm in generalized Gaussian noise scenarios, an affine project least mean $p$ th power algorithm (APLMPA) that includes the $p$ th power dependence on the error is presented. In particular, we apply the proposed APA-based algorithms to suppress the noise from PD signal in power cables. Simulation and experimental results demonstrate the effectiveness of the proposed algorithms for system identification and PD denoising. [ABSTRACT FROM AUTHOR]

In this paper, a numerical model of high-temperature proton exchange membrane fuel cell (HT-PEMFC) was developed, in which the thermal and electrical properties were treated as temperature dependent. Based on the numerical simulation, the needed training data was acquired and used for the development of data-driven model via the artificial neural network (ANN) algorithm. The developed data-driven model was then used to predict the performance of HT-PEMFC. The simulation results indicated that the deviation of ANN prediction was less than 2.48% compared with numerical simulation. The effects of various influential factors, such as the geometry size of the gas flow channel, the thickness of the membrane and the operating temperature, could be predicted easily by using the ANN model. The ANN model prediction results showed that the more compact fuel cell and the higher operating temperature improved the performance of HT-PEMFC. The proposed ANN model and the parameters study will contribute to the further design and operation of HT-PEMFC. • A numerical model of HT-PEMFC was developed with temperature dependent property. • An ANN based data-driven model was built for HT-PEMFC performance prediction. • The deviation between the ANN model and numerical model was less than 2.48%. • The effects on the geometry and the operating temperature were evaluated by ANN model. • The compact design and high operating temperature improved the HT-PEMFC performance. [ABSTRACT FROM AUTHOR]

Highlights • A CCHP system primed by Maisotsenko combustion turbine cycle was proposed. • Performance comparison with that based on conventional gas turbine cycle was made. • Dynamic system simulations were conducted using the TRNSYS platform. • Different climate regions were considered with the results compared. • The loading profiles affected the relative performances of the two CCHP systems. Abstract Buildings are the significant primary energy consumption and pollutant emission contributors in a modern city. Distributed multi-generation systems such as combined cooling, heating and power (CCHP) systems are considered an alternative to fulfil the energy saving requirements in the building sectors. In this study, a CCHP system primed with Maisotsenko combustion turbine cycle (MCTC) was considered with its performance compared with that primed with a simple gas turbine with recuperator (SGTR). With dynamic models of the CCHP systems constructed using TRNSYS, a design optimisation was conducted using genetic algorithm to determine the system component size and number based on the best year-round cost saving. A study case which consisted of building complexes in a district scale was used for investigation under two climatic conditions. The simulation results showed that the relative performances of both CCHP systems depended on the load profiles which differed from the situations when both prime movers were used solely for power generation. In a heating-dominated application, the performance of the MCTC-primed CCHP system was better than the SGTR-primed one only during the summer period and that the year-round performance was inferior to the latter one. Last but not the least, a parameter study was conducted which showed the benefit reduction of CCHP system with the decreasing of public grid price and increasing fuel gas price. [ABSTRACT FROM AUTHOR]

This work addresses an alternative and green route for glycerol upgrading recently highlighted as a potentially critical aspect of the economic and environmental viability of future biodiesel-based bio-refineries. For the first time we report the microwave-assisted hydrothermal process, examining the effects of the temperature (150–250 °C), pressure (50–120 bar), reaction time (0–2 h) and catalyst mass (5–15 wt%; Ni–Co/Al–Mg) during the upgrading of a 30 wt% glycerol solution. The global glycerol conversion and the carbon converted to gas and liquids varied by 5–54%, 0–21% and 3–42%, respectively. Increasing the temperature, reaction time and/or catalyst amount increased glycerol decomposition due to the positive kinetic effects that these variables have on the process. The pressure exerted two counteracting effects: a positive kinetic effect and a thermodynamic inhibitory influence; this latter being accounted for by the lower dielectric loss factor of water at high pressures. The liquid phase was made up of monohydric (10–62 wt%) and polyhydric (0–46 wt%) alcohols, carboxylic acids (0–9 wt%) and C3-ketones (0–80 wt%). Monohydric alcohols and C3-ketones were the most abundant compounds in the liquid when short reaction times and/or low catalyst amounts were used. An increase in these operating variables increased the concentration of polyhydric alcohols and decreased the amount of C3-ketones. The production of C3-ketones (72 wt%) could be maximised using a medium temperature (210 °C) and low pressure (50 bar) and catalyst mass (5 wt%) for a long reaction time (2 h). Around 40% of the glycerol can be purely converted to monohydric (79 wt%) and polyhydric (21 wt%) alcohols by employing a temperature of 250 °C, a pressure of 83 bar and a catalyst mass of 10 wt% for 2 h. [ABSTRACT FROM AUTHOR]

This paper investigated the performance of a regenerative heat and mass exchanger (RHMX) for indirect evaporative cooling. A numerical model for RHMX was developed and validated with experimental data from the literature. Then, a data-driven model based on artificial neural network (ANN) algorithm was presented which was derived from the simulation results generated from the numerical model. The comparison between ANN prediction and experiment data showed good prediction accuracy. The average prediction error between the predicted and tested data was around 4% based on the air temperature change across the dry channel. With the data-driven model, parametric analyses were made to investigate the performance of the RHMX under different operating conditions. Finally, a design optimisation of the extraction air ratio was conducted under different ambient conditions. It was found that the optimal extraction air ratio decreased with the ambient temperature and/or relative humidity which ranged from 0.3 to 0.36. [ABSTRACT FROM AUTHOR]

• Up-to-data dew-point evaporative cooling techniques were comprehensively reviewed. • The recent applications in demand-side and supply-side were summarized. • Research limitations in temperature region and film distribution were discussed. • Future research directions with the use of renewable energy were highlighted. Dew-point evaporative cooling (DPEC) is a high-efficiency heat and mass transfer technique and has been widely used in various industries. The suitable and efficient application of this technology is helpful for energy conservation and can bring great benefits for the fulfillment of carbon–neutral development. In this paper, a comprehensive review of DPEC techniques was conducted through the introduction of its current applications and limitations. First, the theories behind DPEC together with the existing modelling methods and experimental tests were presented after a brief introduction of its research significance. Then, recent advances of DPEC techniques from both demand-side and supply-side applications were described in detail, such as Heating Ventilation Air Conditioning system, gas turbine and other special designs. The research gap between actual carbon–neutral applications and current techniques and potential future research directions were also discussed and finally, some conclusive remarks were outlined. This review concludes the current main characteristics of DPEC techniques and indicates the possible further investigation directions. The inadequate investigation in high temperature region or un-even distribution water film together with future renewable energy combination are highlighted, which is expected to guide the future development of dew-point evaporative coolers and serve the carbon–neutral strategies. [ABSTRACT FROM AUTHOR]

The adoptions of mini-channel and nanofluid are potential technologies to improve the heat transfer capability. The present study experimentally investigated the flow and thermal performance of EG/water based ZnO nanofluid inside a mini-channel with serrated fins with an equivalent diameter of 1.59 mm. EG/water mixture with a mass fraction of 40%/60% served as the base fluid. Nanofluids with a volumetric concentration of 0.75 vol% and 1.5 vol% were prepared. The thermophysical properties of viscosity, density and thermal conductivity were measured. It reveals that although the adding of nanoparticles is able to improve the thermal conductivity by 4.2% on average, the viscosity also enlarges remarkably by up to 18.9%. The measured density and thermal conductivity can be predicted accurately by existing formulations. As all correlations underestimate the viscosity, a new one is proposed for the fabricated nanofluid with a small Mean Absolute Relative Deviation (MARD) of 0.1%. The Nusselt number can be averagely improved by 10.6% and 13.2% for the 0.75 vol% and 1.5 vol% nanofluid with a corresponding sacrifice of friction factor augmentation of 31.2% and 47.3% respectively due to the significant augmentation of viscosity, which results in a relatively small heat transfer coefficient enhancement ratio of 0.92–1.09 under the same pumping power. In addition, the heat transfer enhancement shows a nonlinear increment with the concentration and a higher relative enhancement is found at a lower concentration. This indirectly indicates that the heat transfer does not always increase with the concentration. Even though some published correlations present acceptable predictions for the tested flow and thermal performance of EG/water based ZnO nanofluid, the newly developed Backpropagation Artificial Neural Networks (BP-ANNs) show even better prediction accuracies for Nusselt number and friction factor with the MARDs of 0.39% and 0.35% respectively. Our study is expected to give valuable data sources and inspiration for future investigation on hydrodynamic and thermal behavior of nanofluids. • Flow and heat transfer behavior of ZnO-EG/water nanofluid were studied. • Thermal properties of nanofluid were measured and compared with correlations. • A new correlation for viscosity was proposed for ZnO-EG/water nanofluid. • Empirical Nusselt number correlations were evaluated by measured data. • Novel BP-ANNs were proposed to predict Nusselt number and friction. [ABSTRACT FROM AUTHOR]

• The flow and thermal performance of ZnO/water nanofluid were investigated. • Impacts of channel size, concentration and Reynolds number were identified. • A novel GA-optimized BP-ANN was proposed for Nusselt number prediction. • CFD studies with single-phase, mixture and various turbulence models were conducted. The thermal and flow characteristics of ZnO/water nanofluid in two multiport mini-channels were experimentally and numerically studied. Nanofluids with volumetric concentrations of 0.75 and 1.5% were used. Experimentally, the influences of concentration, Reynolds number (100–3750) and channel size (1.22 and 1.42 mm) on performance were identified. A novel Genetic Algorithm-optimized Backpropagation-Artificial Neural Network (GA-optimized BP-ANN) was proposed for Nusselt number prediction. Numerically, the performance using single-phase and mixture model with different turbulence models were evaluated. Results reveal that the nanofluids show better heat transfer performance and higher pressure drop than that of water. Additionally, the improvement is more obvious in laminar/turbulent transition region at a higher concentration. A better heat transfer performance is observed in a smaller channel after laminar flow region. For thermal performance factor, enhancement only appears at higher Reynolds numbers after flow transition. The most remarkable enhancements are nearly 1.3 and 1.48 for the two channels at the Reynolds numbers of 1600 and 1430, respectively. The developed GA-optimized BP-ANN shows an extremely high prediction accuracy with a Mean Absolute Relative Deviation (MARD) of 2.70%. Numerically, the single-phase model combined with the Lam-Bremhorst model exhibits better simulation results for nanofluid in mini-channel with a MARD of 9.0% than the mixture model. [ABSTRACT FROM AUTHOR]

An integrated method combining one-dimensional design and automatic three-dimensional optimization is proposed for SCO2 radial inflow turbines with low specific speed. The optimization of the nozzle and impeller are performed simultaneously. Four optimization algorithms, namely, grey wolf optimizer, elephant herding optimization, genetic algorithm, and simulated annealing algorithm, are integrated with computational fluid dynamics simulation and finite element analysis to improve the turbine efficiency. Two constraints (mass flow variation and maximum stress) are imposed in the optimization process. The results indicate that the grey wolf optimizer is the optimal algorithm. The total-to-static efficiency of the optimal turbine is 89.56 %, which is increased by 3.25 %. Moreover, splitter blades are also investigated and optimized. The maximum total-to-static efficiency of 90.16 % can be obtained by reasonably arranging splitter blades. The proposed method is versatile, nimble, and easy to implement. It can improve the design efficiency and provide a geometric reference for low specific speed SCO2 turbines. [ABSTRACT FROM AUTHOR]

• Both flow boiling and condensation in mini channels with segregated fins were investigated; • Machine learning based performance prediction models were developed; • The influential factors of different dimensionless parameters were analyzed. Two phase flow boiling and condensation heat transfer in mini channels are promising technologies in handling the challenges of modern thermal management in various fields. In this paper, experimental systems were developed to generate data for flow boiling and condensation of refrigerant R134a in two mini channels with serrated fins under various working conditions. Based on these data, machine learning based Artificial Neural Network (ANN) models were trained to predict the heat transfer performance for both flow boiling and condensation. The proposed ANN models predict the heat transfer coefficient satisfactorily with a Mean Absolute Relative Deviation (MARD) of 11.41% and 6.06% for boiling and condensation respectively compared with experimental data. The test results also indicate that using the most important parameters rather than all available parameters is able to formulate a reasonable ANN model. It also reveals that the developed ANN model can be transferred in a different dataset from the same domains but shows an unacceptable performance for different domains. The proposed ANN model can illuminate future study on two phase flow and be used in practical heat exchanger design, which will benefit the advanced thermal management system. [ABSTRACT FROM AUTHOR]

The aircraft ice protection system that can guarantee flight safety consumes a part of the energy of the aircraft, which is necessary to be optimized. A study for the mechanism of the heat load reduction in the thermal anti-icing system under the evaporative mode was presented. Based on the relationship between the anti-icing heat load and the heating power distribution, an optimization method involved in the genetic algorithm was adopted to optimize the anti-icing heat load and obtain the optimal heating power distribution. An experiment carried out in an icing wind tunnel was conducted to validate the optimized results. The mechanism of the anti-icing heat load reduction was revealed by analyzing the influences of the key factors, such as the heating range, the surface temperature and the convective heat transfer coefficient. The results show that the reduction in the anti-icing heat load is actually the decrease in the convective heat load. In the evaporative mode, decreasing the heating range outside the water droplet impinging limit can reduce the convective heat load. Evaporating the runback water in the high-temperature region can lead to the less convective heat load. For the airfoil, the heating power distribution that has an opposite trend with the convective heat transfer coefficient can reduce the convective heat load. Thus, the optimal heating power distribution has such a trend that is low at the leading edge, high at the water droplet impinging limit and zero at the end of the protected area. [ABSTRACT FROM AUTHOR]

The aircraft ice protection system that can guarantee flight safety consumes a part of the energy of the aircraft, which is necessary to be optimized. A study for the mechanism of the heat load reduction in the thermal anti-icing system under the evaporative mode was presented. Based on the relationship between the anti-icing heat load and the heating power distribution, an optimization method involved in the genetic algorithm was adopted to optimize the anti-icing heat load and obtain the optimal heating power distribution. An experiment carried out in an icing wind tunnel was conducted to validate the optimized results. The mechanism of the anti-icing heat load reduction was revealed by analyzing the influences of the key factors, such as the heating range, the surface temperature and the convective heat transfer coefficient. The results show that the reduction in the anti-icing heat load is actually the decrease in the convective heat load. In the evaporative mode, decreasing the heating range outside the water droplet impinging limit can reduce the convective heat load. Evaporating the runback water in the high-temperature region can lead to the less convective heat load. For the airfoil, the heating power distribution that has an opposite trend with the convective heat transfer coefficient can reduce the convective heat load. Thus, the optimal heating power distribution has such a trend that is low at the leading edge, high at the water droplet impinging limit and zero at the end of the protected area. [ABSTRACT FROM AUTHOR]

The non-receptor protein tyrosine phosphatase (PTP) SHP2, encoded by PTPN11 , plays an essential role in RAS-mitogen-activated protein kinase (MAPK) signaling during normal development. It has been perplexing as to why both enzymatically activating and inactivating mutations in PTPN11 result in human developmental disorders with overlapping clinical manifestations. Here, we uncover a common liquid-liquid phase separation (LLPS) behavior shared by these disease-associated SHP2 mutants. SHP2 LLPS is mediated by the conserved well-folded PTP domain through multivalent electrostatic interactions and regulated by an intrinsic autoinhibitory mechanism through conformational changes. SHP2 allosteric inhibitors can attenuate LLPS of SHP2 mutants, which boosts SHP2 PTP activity. Moreover, disease-associated SHP2 mutants can recruit and activate wild-type (WT) SHP2 in LLPS to promote MAPK activation. These results not only suggest that LLPS serves as a gain-of-function mechanism involved in the pathogenesis of SHP2-associated human diseases but also provide evidence that PTP may be regulated by LLPS that can be therapeutically targeted. • Disease-associated mutations endow SHP2 liquid-liquid phase separation capability • SHP2 LLPS is driven by electrostatic interactions mediated by PTP domain • SHP2 allosteric inhibitors block SHP2 LLPS by locking SHP2 in closed conformation • Mutant SHP2 can recruit and activate WT SHP2 in LLPS to promote MAPK activation Disease-associated mutants of a critical phosphatase in the RAS-MAPK pathway undergo phase separation through a dominant gain-of-function mechanism, explaining how both enzymatically activating and inactivating mutations dysregulate the pathway and can be therapeutically targeted. [ABSTRACT FROM AUTHOR]

Isocitrate dehydrogenase 1 (IDH1), which catalyzes the conversion of isocitrate to α-ketoglutarate, is one of key enzymes in the tricarboxylic acid cycle (TCA). Hotspot mutation at Arg132 in IDH1 that alters the function of IDH1 by further converting the α-ketoglutarate(α-KG) to 2-hydroxyglutarate (2-HG) have been identified in a variety of cancers. Because the IDH1 mutations occur in a significant portion of gliomas and glioblastomas, it is important that IDH1 inhibitors have to be brain penetrant to treat IDH1-mutant brain tumors. Here we report the efforts to design and synthesize a novel serial of mutant IDH1 inhibitors with improved activity and the blood-brain barrier (BBB) penetration. We show that compound 5 exhibits good brain exposure and potent 2-HG inhibition in a HT1080-derived mouse xenograft model, which makes it a potential preclinical candidate to treat IDH1-mutant brain tumors. Image 1 • A series of 24 new mutant IDH1 inhibitors have been synthesized and tested. • Compound 5 exhibits excellent inhibitory activity both in the enzyme and in cells. • Compound 5 is demonstrated good pharmacodynamics and pharmacokinetics properties. • Compound 5 exhibits higher exposure than AG-120 in the brain and tumor. • Compound 5 is effective in inhibiting 2-HG in HT1080 xenograft tumor samples. [ABSTRACT FROM AUTHOR]

• The merit of humidified gas turbine cycle was investigated. • Two air saturator designs were considered for performance comparison. • Detailed heat and mass transfer analysis were employed for the air saturators. • Parametric studies were conducted under different operating conditions. • The Maisotsenko combustion turbine cycle offered higher energy efficiency. The urge for more energy-efficient power plant systems to relieve the energy crisis triggers the design for more advanced power cycles. The humidified gas turbine cycle is considered one of the potential choices, and the air saturator performance is critical to the energy merit of such kind of system. To understand more, the performances of humidified gas turbine cycles with two types of air saturator designs were compared in this study. Type 1 air saturator was a hybrid design which combined an indirect evaporative cooler with a Maisotsenko cycle while Type 2 was a conventional indirect evaporative cooler. Detailed heat and mass transfer analysis was taken into account in the air saturator modelling. Through system simulations, it was found that all the humidified gas turbine cycle systems offered higher system efficiencies than a simple gas turbine system with recuperator. Besides, parametric studies were conducted which highlighted the effects of system inlet air temperature, turbine inlet temperature, water injection rate, and part-load ratio on the performances of the different humidified gas turbine cycle designs. The employment of Type 1 air saturator offered 9.34% and 23.55% enhancement in the system efficiencies as compared to those using Type 2 air saturator under the design and 50% part-load ratio conditions respectively. This reinforced the benefit of applying Maisotsenko cycle to the air saturator design of humidified gas turbine cycle for the enhancement of system efficiency. [ABSTRACT FROM AUTHOR]

• Design optimization and two-stage control strategy of the CCHP system were conducted. • CCHP system performance was investigated in two different climatic regions. • The performance of different control strategies was compared. Combined cooling, heating and power (CCHP) is a promising energy supply technology to improve the overall energy utilization efficiency. It provides an opportunity to achieve low or zero carbon energy supply with tactful control strategies. In this study, the two-stage model predictive control (MPC) strategy with combined rolling optimization and real-time adjustment is demonstrated to be highly effective for CCHP system application. In most previous studies, the MPC strategy was performed under a given design configuration, which was not optimally constructed. In real practice, the system configuration, the installed equipment capacity, and the control strategy altogether affect the CCHP system performance. Both the system design optimization and the two-stage MPC strategy were conducted in our numerical analysis through a hypothetical case study. Our simulation results illustrated that the equipment selection affects the running cost of the CCHP system, and the desirable solution is well linked to the building load profile. The effect of forecasting error on the two-stage MPC was also investigated. The results showed that although the two-stage MPC strategy is able to give better performance than the traditional strategies in most cases, poor performance may still exist when the load forecasting error is more than 8.8%. [ABSTRACT FROM AUTHOR]

• The dimensionless factors of Maisotsenko cycle heat and mass exchanger were detected. • A dew-point effectiveness correlation was developed. • The mean absolute deviations of the proposed correlation were less than 6.75%. • The influence of dimensionless parameters was discussed. The Maisotsenko cycle heat and mass exchanger (HMX) has been proven to be a high-efficiency facility, which can be regarded as heat recovery to improve the efficiency of energy supply system or directly applied as an evaporative cooler. Many experimental tests and numerical simulations have been conducted to verify its performance and help to serve energy supply system simulation. However, it is impossible to conduct an experimental test over a wide range of working conditions and employing the numerical model for system simulation is also inconvenient. Therefore, the modelling of empirical correlations for the practical application of HMX becomes necessary. This paper conducts a detailed theoretical analysis of heat and mass transfer in HMX, and the influential dimensionless parameters on dew-point effectiveness were identified. A dew-point effectiveness correlation for HMX was proposed based on the detected parameters. The results indicated that the mean absolute deviations of the proposed correlation were 2.35% and 6.75% when compared with numerical simulation and experimental data respectively. The newly proposed correlation could be used directly to evaluate the performance of HMX or further benefit the system simulation when the HMX is used as heat recovery component. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) detection plays a vital role in on-line condition monitoring of electrical apparatus in the power systems. However, the noise of PD measurements significantly degrades the performance of detection algorithms. In this paper, we focus on developing an adaptive filtering technique for the PD denoising problem. Heretofore, there are just a few literature reviews addressing the PD denoising based on such a method. The proposed recursive continuous S-shaped (RCSS) algorithm integrates the advantages of recursive strategy and continuous S-shaped function into adaptive noise cancellation (ANC) system, yielding enhanced filtering performance. The proposed algorithm can tackle PD noises in both Gaussian and impulsive scenarios, which is easy to implement in practical applications. The convergence behavior is also analyzed. Extensive simulation and experimental results confirm that the proposed algorithm can address polluted PD pulses, even in excessively noisy conditions, resulting in smaller mean square error (MSE) as compared to other state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

In this paper, the inhibitory effect of preinjected rejuvenation liquid on trees in cross-linked polyethylene (XLPE) cables was investigated. Experimental samples were prepared by inserting needles into XLPE samples, and many equally-spaced holes existed in the outer semiconductive layer. All cable samples were divided into two groups. One sample group was treated with rejuvenation liquid, while the other group was the control group. A tree accelerated aging system was used to obtain trees in the XLPE cable samples. During the aging experiment, an impulse voltage was applied to the samples repeatedly. The micromorphologies of the two groups were observed. Based on the micromorphologies, two parameters were determined: the initiation rate of electrical trees and the average length of trees. Furthermore, the electric field distribution was simulated to analyze the initiation of electrical trees. The results indicate that an electrical tree is much harder to initiate in the pretreated XLPE cables than in the untreated cables. This phenomenon is likely attributed to the dielectrophoretic forces in the pretreated cables. Moreover, rejuvenation liquid deposited in XLPE causes a substantial reduction in the Maxwell stress of molecular chains. Rejuvenation liquid inhibits electrical tree initiation and water tree growth to a great extent. [ABSTRACT FROM AUTHOR]

This study investigates the microstructural changes of water trees in different stages of propagation. It is proposed that microstructural changes within a tree influence its macroscopic propagation. Five groups of XLPE cable samples with pinhole defects were subjected to an accelerated water tree aging experiment for different aging times. The morphologies and sizes of water trees in different aging periods were observed by optical and scanning electron microscopes. The microscopic observations show that the propagation rates of water trees can change during different aging stages. In the initial stage, the propagation rate of water trees can reach 0.46 μm/hour. However, in the stagnation stage, the propagation rate decreases considerably to as low as 0.01 μm/hour. In the late stage, water trees with irregular shapes can form, and the propagation rate of the longest water tree branches can rise to 0.33 μm/hour. In addition, the shape of the microvoids within the water trees can change. In the later period of the stagnation stage, microvoids with irregular shapes (not round shape) can form by the connection between microvoids with different sizes. The simulation results of the electric field indicate that the microstructural change within the water trees is the fundamental reason for the changes of the propagation rates. In different propagation stages, the changes in the density, the sizes, and the shape of the microvoids can lead to the changes of water distribution and electric field distribution in water tree regions, which further results in different propagation rates. [ABSTRACT FROM AUTHOR]

Flow boiling in micro pin fin arrays is an effective way to solve the heat dissipation problem. However, studies on the flow boiling performance of pin fin arrays with different structural parameters are still insufficient, especially for the application of long channels for practical evaporators in aircraft environmental control systems. In this paper, the flow boiling performance of R134a was experimentally investigated in a 300 mm long mini channel with micro pin fin arrays. The mass fluxes, heat fluxes, inlet saturation pressures and vapor qualities were in ranges of 200 -500 kg/(m2s), 15–30 kW/m2, 500–700 kPa and 0.05–0.90, respectively. The local heat transfer coefficient and pressure drop of staggered diamond pin fin arrays with different channel widths of 1.0, 1.2 and 1.4 mm were comprehensively studied. Subsequently, the performance analysis of the above channels was carried out. Results indicate that the nucleate boiling and convective boiling together govern the two-phase flow boiling heat transfer in the pin fin array. In particular, the increase in channel width delays the transition to convective boiling dominated flow. The local heat transfer coefficient increases with mass flux. However, in the high vapor quality region, the flow disturbance caused by a large mass flux may suppress the heat transfer, as high-speed gas destroys the continuous thin liquid film on the walls. Furthermore, the influence of saturation pressure on the heat transfer coefficient is reversed with the increase in vapor quality. Additionally, the performance analysis indicated better performance of the pin fin array at low vapor quality regions and small mass flux. Significantly, the best performance was obtained in pin fin array with a channel width of 1.4 mm, due to a drastic increase in two-phase pressure drop compared to heat transfer. Finally, a new correlation with the consideration of pin fin array structure parameters was proposed with an overall mean absolute deviation of 16.2%. This new correlation is proved to have an obvious accuracy improvement in predicting the flow boiling local heat transfer coefficient of R134a in a mini channel with pin fin arrays. The present work can provide critical information for the design optimization of a mini channel two-phase heat exchanger with pin fin arrays. [ABSTRACT FROM AUTHOR]

The actual operation of turbomachinery is inevitably affected by multi-source uncertainties. Such uncertainties are detrimental to the performance and reliability of energy systems. Based on graph learning methods, this work aims to provide a convenient and effective approach for aerodynamic robust optimization of turbomachinery. A radial inflow turbine is taken as the research target and Dual Graph Neural Network (DGNN) regression model is constructed for flow field prediction and performance discrimination. By comparing the accuracy and time consumption, the advantages of DGNN over classical surrogate models and computational fluid dynamics (CFD) are clarified. The proposed model is integrated into uncertainty quantification and aerodynamic robust optimization. The effect of multi-source uncertainties on performance is quantified. The stochastic response of flow fields is also obtained conveniently through DGNN. Robust optimization is performed for power and efficiency, respectively. The power robust optimization improves the power by 1.52% and reduces the standard deviation of power by 15.45%. The efficiency robust optimization achieves an efficiency improvement of 1.76% (increment) and an efficiency standard deviation reduction of 36.82%. The proposed approach is an efficient and competitive choice for uncertainty quantification and robust optimization. The present work contributes to constructing the digital twin of turbomachinery systems. • A new complete approach for aerodynamic robust optimization. • A graph deep learning model is contained for flow fields and performance prediction. • Our model performs better than classical surrogate models. • The effect of multi-source uncertainties is quantified. • The proposed approach can effectively solve aerodynamic robust optimization problems. [ABSTRACT FROM AUTHOR]

The improvements in signal-to-noise ratio (SNR) are indispensable to obtain the desired output signal of partial discharge (PD) under square wave pulsewidth modulation (PWM) voltage. In this article, the effect of complex PWM voltage parameters (rise time, fall time, frequency, duty cycle) on the SNR of PD tests is investigated. The results revealed that the sensor's high-frequency gain should be increased to improve the SNR under faster switching. PD impulses are more likely to be submerged in the residual interference under high-frequency voltage. The SNR can be improved by only detecting the PD at the rising front because the PD signal overlaps with commutation noise at the falling front of short duty cycle voltage, such as 0.03% duty cycle. The above results can reference the PWM parameters and improve the SNR in PD tests for rotating machines controlled by power electronics. [ABSTRACT FROM AUTHOR]

SHP1 is a non-receptor protein tyrosine phosphatase that is widely expressed in hematopoietic cells such as white blood cells, neutrophils, and immune cells. SHP1 can regulate the occurrence and differentiation of immune cells and plays an important role as a tumor suppressor. Previous studies have suggested that SHP2, the homologous protein of phosphatase SHP1, can undergo liquid–liquid phase separation (LLPS). Therefore, in this study, we investigated if SHP1 is also capable of LLPS. To the best of our knowledge, our study is the first to reveal that SHP1 has the ability to undergo LLPS. In addition, we identified an important residue, SHP1-R360E, that can completely inhibit the LLPS ability of SHP1, but this mutation has no remarkable effect on SHP1's enzymatic activity. This allows us to explore the phosphatase activity and phase separation ability of SHP1 separately, providing a basis for future exploration of the phase separation mechanism of phosphatases. • SHP1 can undergo liquid–liquid phase separation(LLPS). • The PTP domain is responsible for SHP1 LLPS. • The SHP1 mutant, K358E/R360E, can perturb LLPS and catalytic ability. • SHP1-R360E can abolish the LLPS ability of SHP1 without affecting SHP1's enzymatic activity. [ABSTRACT FROM AUTHOR]

Carbonate tidal delta system used to be put much less attention on unlike the counterparts in siliciclastic systems, and its unique architecture influences the reservoir heterogeneity and corresponding development strategy significantly. This study aims to recognize and characterize the carbonate tidal delta system of Mishrif Formation in Southeast Iraq. Based on detailed observation of cores from 5 wells and integrated analysis on well-loggings and 3D seismic, five lithofacies associations were recognized: (1) subtidal mudstone to wackestone (LF-1); (2) back-margin massive wackestone to packstone (LF-2); (3) high-energy bioclastic grainstone (LF-3); (4) swamp carbonaceous mudstone interbedded with bioclastic wackestone (LF-4); and (5) incision brown mudstone to wackestone with chert nodular (LF-5). A detailed description of the recognized lithofacies and facies association of the system is given in this work, together with an interpretation of the corresponding depositional setting. The architecture of the reservoir bodies has been reconstructed in detail and placed within a high-frequency sequence-stratigraphic framework. The studied interval belongs to the highstand system tract (HST) of a single composite sequence and comprises two shallowing-upward high-frequency sequences. The internal architecture of the tidal delta system is the result of complex tidal-dominated hydrodynamics. Facies and diagenetic partitioning with each high-frequency sequences are primary controls on pore types and reservoir properties. Original lithofacies texture and subsequent meteoric dissolution resulted in regional barriers and high permeable streaks that created a complex internal architecture of reservoir bodies. The shape of reservoir bodies generally follows those of the lithofacies, but with the addition of intercalated thin flow barriers. • The flood tidal delta system develops different types of lithofacies. • The architecture of the system is analyzed within high-frequency sequence framework. • The stratigraphic architecture and diagenetic alternation complicate the reservoir heterogeneity. • Compartmentalization of the reservoir is caused by the presence of barriers and the tidal channel. [ABSTRACT FROM AUTHOR]

• Local condensation heat transfer in smooth channels and pin fin array is presented. • The effect of operating parameters on the heat transfer characteristics was analyzed. • Sensitivity analysis is performed of heat transfer to identify the critical parameters. • Condensation heat transfer increases with heat flux in the range of vapor quality above 0.4. In this paper, an experimental study of flow condensation was carried out of R134a in a multiport mini channel and a mini channel with pin fin array. The former comprised 20 parallel rectangular channels with an equivalent diameter of 0.64 mm. The latter is a narrow rectangular mini channel containing 10 rows of diamond pin fins with a staggered configuration, and height and longitudinal/transverse pitch of 0.5 mm and 2 mm respectively. To acquire the local value of heat flux and heat transfer coefficient, air jet impingement cooling devices were adopted to condense the vapor of refrigerants. The effects of vapor quality, mass flux, heat flux, and saturation pressure on flow condensation heat transfer coefficient were investigated with the operating conditions: vapor quality from 1 to 0, mass flux from 160 to 450 kg/(m2s), heat flux from 10.0 to 39.8 kW/m2, and saturation pressure from 600 to 1500 kPa. The experimental results indicated that the pin fin array significantly improves the condensation heat transfer coefficient up to nearly 186 % compared to the multiport mini channel in the high vapor quality region. For both channels, the local heat transfer coefficient increases with an increase in vapor quality, mass flux, and heat flux whereas decreases with increase in saturation pressure. The influence of heat flux and mass flux on heat transfer coefficient was more pronounced in the high vapor quality region than in the low vapor quality region. A sensitivity analysis was performed at different vapor quality levels. The most influential parameters in the smooth channel and the pin fin array are saturation pressure and mass flux, respectively. The relative contribution of heat flux is more obvious in the high vapor quality region. Some of the existing correlations have good prediction performance for the smooth channel experimental data in this paper, and the corresponding MAD is within 20 %. However, their deviations are much greater for the applications of pin fin array. [ABSTRACT FROM AUTHOR]

The main insulation of converter transformers consists of transformer oil and oil-impregnated pressboard. Under operating conditions, the valve-side winding of the converter transformer is subject to DC voltage components. Therefore, studies on the characteristics of oil-impregnated pressboard conductivity are necessary. In this paper, the temperature, moisture and electric field dependency of pressboard conductivity are investigated based on a specially designed three-electrode experimental chamber, which allows for a variation in temperature ranging from 25 °C to 120 °C and an electric field strength ranging from 0 to 30 kV/mm. The experimental results show that, within the experimental conditions, the conductivity of oil-impregnated pressboard increases exponentially with increasing moisture and temperature. High moisture and temperature will increase both the carrier concentration and carrier mobility, which explains the exponential correspondence. Furthermore, the electric field dependency of the conductivity is more obvious for wet pressboard than for dry pressboard. Protons in the wet pressboard are more easily accelerated by the electric field than the impurity ions in the oil of the dry pressboard, which leads to an obvious electric field dependency of the wet pressboard conductivity. [ABSTRACT FROM AUTHOR]

To understand abnormal water tree shapes under mechanical stresses, this paper reveals the mechanism of mechanical orientation for the effect of water tree propagation behaviors. A heated metal needle was used to produce pinhole defects in two groups of XLPE bar samples (group A and group B) to simulate the mechanical orientation of the XLPE material. The samples in group A were subjected to orientation analysis by an infrared spectrum (IR) method, and the samples in group B were subjected to an accelerated water tree aging experiment. According to the results of IR analysis, the XLPE material around the pinholes was oriented after the insertion of the heated metal needle. The microscopic observation results show that there are abnormal water tree shapes in the samples in group B. The abnormal water tree shapes are very similar to the morphology of the stress strips observed in the samples in group A. Based on the mechanical orientation theory, after the mechanical orientation, the XLPE material becomes anisotropic, and some performances of the material will change in the direction of orientation and in the transverse direction. As a result, in the direction of orientation, water tree propagation is promoted, whereas water tree propagation is inhibited in the direction perpendicular to orientation. Mechanical orientation is the main reason for the abnormal water tree shapes. A similar phenomenon is also verified in bent cable samples. The types, directions, and intensities of mechanical stresses determine the behaviors of mechanical orientation in cables, which can further influence the behaviors of water trees. [ABSTRACT FROM AUTHOR]

Pantograph–catenary (PC) arc has become an obstacle for the further development of high-speed railway. Understanding on the underlying physical mechanisms of PC arc dynamics is still far away from satisfactory; therefore, researches from both experimental and numerical aspects are urgently required. This paper focused on the dynamic characteristics of PC arc during the pantograph lowering process by numerical simulation method. A PC arc model was established based on the classical magnetohydrodynamics theory, with the temporal evolution of PC arc dynamics considered. The dynamic mesh technique was utilized to take care of the departure process between the pantograph and the catenary. Detailed behaviors of arc plasmas during the pantograph lowering process were presented by the temperature distribution and flow filed. Two interesting vortexes located below the catenary were found. The vortexes rotated in the opposite direction, resulting from the special gas flow motion during the pantograph movement. Furthermore, the gas flow brought about a thermal pinch effect on arc column, which had a significant influence on the next behaviors of arc plasmas. Besides, the effects of input current on the arc characteristics were studied. [ABSTRACT FROM AUTHOR]

Phenomena of the pantograph arcing have become a challenge for the further development of high-speed electrified railway system. Despite of the large attention that has been paid to the radiated electromagnetic interference, materials ablation as well as the power-quality decline resulted from pantograph arcing, the specific dynamics of pantograph arcing with a high time resolution are still in absence. In this paper, the pantograph arcing phenomena in a laboratory simulation system were experimentally studied by high-speed photography. Synchronized electrical voltage and current waveforms were obtained to acquire a more comprehensive understanding on the underlying physics. The overall dynamics of the pantograph arcing from ignition to extinguishment were recorded. Three stages of the electric-contact process, from approaching arc, mechanical contact to the drawn arc, were well distinguished. A much intensified drawn arc was observed than the approaching arc. Typical lasting time of the drawn arcing is found $\sim 4$ times larger than the approaching arcing for our test setup. Maximum diameter of 3.3 mm was reached at around the current-peak moment. An interesting stable arc voltage of \sim 23$ V was found during the drawn arcing. Intense material splash above the carbon strip was observed during the arcing process. The transient resistance during a typical arcing period was also analyzed, and a minimum value of \sim 100~\text{m}\Omega was determined. [ABSTRACT FROM PUBLISHER]

Polyimide nano-composite film (Kapton 100CR) is a special type of engineering plastic film, which is widely used in turn insulation of form-wound inverter-fed motor. Partial discharge (PD) caused by high-frequency surge impulse is one of the key factors leading to premature failure of turn insulation of inverter-fed motors. Aging experiments on turn insulation samples under repetitive bipolar square impulse voltage were carried out in this study. Experimental results show that, in the presence of PD, the damage to the structure of the polyimide nano-composite film under impulse voltage is concentrated on the surface layer of the sample. Moreover, the results indicate that with the increase of aging time, the discharge phase distribution becomes broader. Therefore, the appearance of the discharge at higher phase would be the reflection that the insulation of the sample reaches its terminal stage. Surface microscopic images taken by the scanning electron microscope (SEM) show that, because of PD erosion, the polymer matrix was carbonized and volatilized, the residual nano-fillers remained on the surface and formed a screen layer to resist further damages caused by PDs. It is a symbol that faults expand rapidly when the floccules and voids appear on the surface layer, which indicates the insulation could be breakdown soon. [ABSTRACT FROM AUTHOR]

In order to investigate the effects of inorganic nanofillers on the electrical properties of polyimide (PI), PI/Al2O3 nanocomposites films were prepared via the in-situ polymerization. The hybrids films were characterized by scanning electron microscope (SEM) and Fourier transform infrared spectroscopy (FTIR). The dielectric behaviors of pure PI and PI/Al2O3 samples were studied as a function of the measured frequencies and temperatures. Meanwhile, the breakdown strength of pure PI and PI/Al2O3samples measured at 25 and 230 °C was analyzed. The corona-resistant lifetime of samples under bipolar continuous square impulse voltage (BCSIV) was performed. With the wt% content of Al2O3 nanoparticles increasing, the real (ε') and imaginary (ε") of relative permittivity present an increasing tendency, while electrical breakdown strength declines obviously. The Al2O3 nanofillers improved the corona-resistant property of PI and the corona-resistant lifetime of PI/Al2O3 sample with 25 wt% (weight percent) of nano-Al2O3 particles is over 23 times longer than that of the pure PI film. Besides, the temperature is an important factor which would significantly influence the electrical properties of pure PI and PI/Al2O3 samples. The elevated temperature would reduce the breakdown voltage and corona-resistant property [ABSTRACT FROM AUTHOR]

High-speed airflow, which is generated around trains running at a high speed, causes uneven pollutant distribution on insulator surfaces and changes their insulation properties. In this paper, a method has been proposed to calculate the residual pollutant resistance on polluted insulator. Based on the analysis of flashover model, the influence of pollution distribution along and around insulator was discussed. Analysis result showed that flashover voltage would increase when the pollutant distribution on insulator decreased compared to conditions with uniformly distributed pollutant, and vice versa. It implied that there should be a maximum pollutant accumulation value above and below the insulator shed. In this situation, the flashover voltage will be the lowest. Model analysis showed that the flashover voltage would increase with the length of the insulated plate and vice versa. The theoretical analysis was in good agreement with experimental result, which implied that this method might be able to provide reference for insulator shed design. [ABSTRACT FROM AUTHOR]

Tumor metastasis accounts for the majority of cancer-related deaths; it is therefore important to develop preclinical models that faithfully recapitulate disease progression. Here, we generated paired organoids derived from primary tumors and matched liver metastases in the same colorectal cancer (CRC) patients. Despite the fact that paired organoids exhibit comparable gene expression and cell morphology, organoids from metastatic lesions demonstrate more aggressive phenotypes, tumorigenesis, and metastatic capacity than those from primary lesions. Transcriptional analyses of the paired organoids reveal signature genes and pathways altered during the progression of CRC, including SOX2. Further study shows that inducible knockdown of SOX2 attenuated invasion, proliferation, and liver metastasis outgrowth. Taken together, we use patient-derived paired primary and metastatic cancer organoids to model CRC metastasis and illustrate that SOX2 is associated with CRC progression and may serve as a potential prognostic biomarker and therapeutic target of CRC. [ABSTRACT FROM AUTHOR]

Locating the partial discharge (PD) source is one of the most effective means to locate local defects in power cable lines. The sampling rate and the frequency-dependent characteristic of phase velocity have an obvious influence on localization accuracy based on the times of arrival (TOA) evaluation algorithm. In this paper, we present a cross-correlation algorithm based on propagation distance to locate the PD source in cable lines. First, we introduce the basic principle of the cross-correlation function of propagation distance. Then we verify the proposed method through a computer simulation model and investigate the influences of propagation distance, sampling rate, and noise on localization accuracy. Finally, we perform PD location experiments on two 250 m 10 kV XLPE power cables using the oscillation wave test system. The simulation and experiment results indicate that compared with traditional TOA evaluation methods, the proposed method has superior locating precision. [ABSTRACT FROM AUTHOR]