A Novel Integrated Photovoltaic System with a Three-Dimensional Pulsating Heat Pipe

Solar energy is a valuable renewable energy source,and photovoltaic(PV)systems are a practical approach to harnessing this energy.Nevertheless,low energy efficiency is considered a major setback of the system.Moreover,high cell temperature and reflection of solar irradiance from the panel are considered chief culprits in this regard.Employing pulsating heat pipes(PHPs)is an innovative and useful approach to improving solar panel performance.This study presents the results of the power performance of a PV panel attached to a newly designed spiral pulsating heat pipe,while graphene oxide nanofluid with three different concentrations was used as a working fluid to maximize the efficacy of the solar panel.The study proved that the cooling method delivered high efficiency by reducing the temperature,especially in the middle of the day.Using nanofluid graphene oxide at concentrations of 0.2,0.4,and 0.8 gr/lit as the working fluid can reduce the thermal resistance of PHPs by over 30%,24%,and 15%,respectively.This,in turn,enhances the system’s electrical power output by approximately 9%,7%,and 6%,respectively.

NUMERICAL ANALYSIS OF THREE-DIMENSIONAL FLUID FLOW AND HEAT TRANSFER IN TIG WELD POOL WITH FULL PENETRATION

A model is established to analyze three-dimensional fluid flow and heat transfer in TICweld pools with full penetration.It considers the deformation of the molten pool surfaceat the condition of full penetrated workpieees,takes the are pressure as the drivingforce of the pool surface deformation,and determines the surface configuration of weldpool based on the dynamic balance of arc pressure,pool gravity and surface tension atdeformed weld pool surface. The SIMPLER algorithm is used to calculate the fluid flowfield and temperature distribution in TIG weld pools of stainless steel workpieces.TIGwelding experiments are made to verify the validity of the model.It shows the calculatedresults by the model are in good agreement with experimental measurements. professor,Dept of Welding Engineering,Harbin Institute of Technology,Harbin 150006,China

Experimental Study on the Wavelengths of Two-Dimensional and Three-Dimensional Freak Waves

Freak waves are commonly characterized by strong-nonlinearity, and the wave steepness, which is calculated from the wavelength, is a measure of the degree of the wave nonlinearity. Moreover, the wavelength can describe the locally spatial characteristics of freak waves. Generally, the wavelengths of freak waves are estimated from the dispersion relations of Stokes waves. This paper concerns whether this approach enables a consistent estimate of the wavelength of freak waves. The two-(unidirectional, long-crested) and three-dimensional(multidirectional, shortcrested) freak waves are simulated experimentally through the dispersive and directional focusing of component waves, and the wavelengths obtained from the surface elevations measured by the wave gauge array are compared with the results from the linear, 3rd-order and 5th-order Stokes wave theories. The comparison results suggest that the 3rd-order theory estimates the wavelengths of freak waves with higher accuracy than the linear and 5th-order theories. Furthermore, the results allow insights into the dominant factors. It is particularly noteworthy that the accuracy is likely to depend on the wave period, and that the wavelengths of longer period freak waves are overestimated but the wavelengths are underestimated for shorter period ones. In order to decrease the deviation, a modified formulation is presented to predict the wavelengths of two-and three-dimensional freak waves more accurately than the 3rd-order dispersion relation, by regression analysis. The normalized differences between the predicted and experimental results are over 50% smaller for the modified model suggested in this study compared with the 3rd-order dispersion relation.

Numerical Simulation of Three-dimensional Heat and Mass Transfer in Spray Cooling of Converter Gas in a Venturi Scrubber

In order to predict the pressure drop, collection efficiency, velocity, temperature and mole fraction of vapor in an industrial venturi scrubber with water spraying for converter gas cooling, a three-dimensional model of heat and mass transfer with phase change is established. The gas flow and liquid droplets are treated as a continuous phase with a Eulerian approach and as a discrete phase with a Lagrangian approach, respectively. The coupled problem of heat, force, and mass transfers between gas flow and liquid droplets is solved by a commercial computational fluid dynamics（CFD） package, FLUENT. The numerical results show that the water injections have an important influence on the distributions of pressure, velocity, temperature, and mole fraction of vapor, especially for the spraying region in the throat. In the spraying region, the pressure drop is higher and the velocity is lower than in other regions due to the gas-droplet drag, while the temperature is lower because the droplet absorbs large amounts of heat from the high temperature gas and the mole fraction of vapor is higher due to the phase change of the liquid droplet. A number of cases with different Water-to-gas volume flow ratios and baffle openings were simulated. The dependence of pressure drop, velocity, temperature, mole fraction of vapor, and collection efficiency on both the water-to-gas volume flow ratio and baffle opening are analyzed. The good agreements between simulation results and experiment data of pressure drop, temperature, and collection efficiency validate the model. The model should facilitate optimization of the venturi scrubber design in order to give better performance with lower pressure drops and higher collection efficiency.

IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,etc.In terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic.It is challenging to identify a specific attack due to complex features and data imbalance issues.To address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced data.First,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,etc.Second,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic anchors.Third,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority attacks.Fourth,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network traffic.Finally,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep features.Detailed experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and NSL-KDD.An explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

Causal Analysis Between Rice Growth and Cadmium Accumulation and Transfer under Arbuscular Mycorrhizal Inoculation

Cadmium(Cd)contamination in rice has been a serious threat to human health.To investigate the effects of arbuscular mycorrhizal fungi(AMF)on the Cd translocation in rice,a controlled pot experiment was conducted.The results indicated that AMF significantly increased rice biomass,with an increase of up to 40.0%,particularly in root biomass by up to 68.4%.Notably,the number of prominent rice individuals also increased,and their plasticity was enhanced following AMF inoculation.AMF led to an increase in the net photosynthetic rate and antioxidant enzyme activity of rice.In the AMF treatment group,the Cd concentration in the rice roots was significantly higher(19.1%‒68.0%)compared with that in the control group.Conversely,the Cd concentration in the rice seeds was lower in the AMF treatment group,indicating that AMF facilitated the sequestration of Cd in rice roots and reduced Cd accumulation in the seeds.Path coefficients varied across different treatments,suggesting that AMF inoculation reduced the direct impact of soil Cd concentration on the total Cd accumulation in seeds.The translocation of Cd was consistently associated with simultaneous growth dilution and compensatory accumulation as a result of mycorrhizal effects.Our study quantitatively analyzed this process through path analysis and clarified the causal relationship between rice growth and Cd transfer under the influence of AMF.

Robust Information Hiding Based on Neural Style Transfer with Artificial Intelligence

This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission.The algorithm we designed aims to mitigate the impact of various noise attacks on the integrity of secret information during transmission.The method we propose involves encoding secret images into stylized encrypted images and applies adversarial transfer to both the style and content features of the original and embedded data.This process effectively enhances the concealment and imperceptibility of confidential information,thereby improving the security of such information during transmission and reducing security risks.Furthermore,we have designed a specialized attack layer to simulate real-world attacks and common noise scenarios encountered in practical environments.Through adversarial training,the algorithm is strengthened to enhance its resilience against attacks and overall robustness,ensuring better protection against potential threats.Experimental results demonstrate that our proposed algorithm successfully enhances the concealment and unknowability of secret information while maintaining embedding capacity.Additionally,it ensures the quality and fidelity of the stego image.The method we propose not only improves the security and robustness of information hiding technology but also holds practical application value in protecting sensitive data and ensuring the invisibility of confidential information.

Generation of mitochondrial replacement monkeys by female pronucleus transfer

Mutations in mitochondrial DNA(mtDNA)are maternally inherited and have the potential to cause severe disorders.Mitochondrial replacement therapies,including spindle,polar body,and pronuclear transfers,are promising strategies for preventing the hereditary transmission of mtDNA diseases.While pronuclear transfer has been used to generate mitochondrial replacement mouse models and human embryos,its application in non-human primates has not been previously reported.In this study,we successfully generated four healthy cynomolgus monkeys(Macaca fascicularis)via female pronuclear transfer.These individuals all survived for more than two years and exhibited minimal mtDNA carryover(3.8%–6.7%),as well as relatively stable mtDNA heteroplasmy dynamics during development.The successful establishment of this nonhuman primate model highlights the considerable potential of pronuclear transfer in reducing the risk of inherited mtDNA diseases and provides a valuable preclinical research model for advancing mitochondrial replacement therapies in humans.

Effects of projectile parameters on the momentum transfer and projectile melting during hypervelocity impact

The effects of projectile/target impedance matching and projectile shape on energy,momentum transfer and projectile melting during collisions are investigated by numerical simulation.By comparing the computation results with the experimental results,the correctness of the calculation and the statistical method of momentum transfer coefficient is verified.Different shapes of aluminum,copper and heavy tungsten alloy projectiles striking aluminum,basalt,and pumice target for impacts up to 10 km/s are simulated.The influence mechanism of the shape of the projectile and projectile/target density on the momentum transfer was obtained.With an increase in projectile density and length-diameter ratio,the energy transfer time between the projectile and targets is prolonged.The projectile decelerates slowly,resulting in a larger cratering depth.The energy consumed by the projectile in the excavation stage increased,resulting in lower mass-velocity of ejecta and momentum transfer coefficient.The numerical simulation results demonstrated that for different projectile/target combinations,the higher the wave impedance of the projectile,the higher the initial phase transition velocity and the smaller the mass of phase transition.The results can provide theoretical guidance for kinetic impactor design and material selection.

Coherent optical frequency transfer via 972-km fiber link

We demonstrate coherent optical frequency dissemination over a distance of 972 km by cascading two spans where the phase noise is passively compensated for.Instead of employing a phase discriminator and a phase locking loop in the conventional active phase control scheme,the passive phase noise cancellation is realized by feeding double-trip beat-note frequency to the driver of the acoustic optical modulator at the local site.This passive scheme exhibits fine robustness and reliability,making it suitable for long-distance and noisy fiber links.An optical regeneration station is used in the link for signal amplification and cascaded transmission.The phase noise cancellation and transfer instability of the 972-km link is investigated,and transfer instability of 1.1×10^(-19)at 10^(4)s is achieved.This work provides a promising method for realizing optical frequency distribution over thousands of kilometers by using fiber links.

Three-dimensional turbulent model of heat transfer and fluid flow in GTAW process

A two-equation K-ε turbulent fluid flow model is built to model the heat transfer and fluid flow in gas tungsten arc welding （GTAW） process of stainless steel S US310 and S US316. This model combines the buoyancy force, lorentz force and marangni force as the driving forces of thefluidflow in the weld pool. The material properties are functions of temperature in this model. The simulated results show that the molten metal flowing outward is mainly caused by the marangoni convection, which makes the weld pool become wider and shallower. The comparison of the weld pool shape of SUS310 and SUS316 shows that the slight differences of the value of thermal conductivity mainly attributes to the difference of the weld pool shape and the distinction of heat transport in laminar and turbulent model makes large diversity in the simulated results.

Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation

The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source domain.However,in engineering scenarios,achieving such high-quality label annotation is difficult and expensive.The incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled samples.To overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three parts.First,a residual network with dual classifiers is to learn features from cross-domain samples.Second,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source domain.With the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised learning.Third,the adaptation trajectories are designed for sample distributions across domains.This ensures that the target domain samples are only adapted with the pure-labeled samples.The LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related machines.The results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.

Filling Simulation of Three-dimension Braided Composite in Resin Transfer Molding

This paper measured permeability of three-dimension braided preform by radial technology. The results show that principal permeability tensor coincided with their braiding axial direction. The software of one dimensional flow filling mold was designed using Visual C++ language. Filling time is predicted and validated. The result showed that the filling time of the mold centerline agrees with the prediction value. The filling time of the mould edge is shorter than that of the prediction. An actual plate of 3D braided preform/ modified polyarylacetylene composite is produced according to prediction value and validation analysis.

The regulation of ferrocene-based catalysts on heat transfer in highpressure combustion of ammonium perchlorate/hydroxyl-terminated polybutadiene/aluminum composite propellants

The regulation of the burning rate pressure exponent for the ammonium perchlorate/hydroxylterminated polybutadiene/aluminum(AP/HTPB/Al)composite propellants under high pressures is a crucial step for its application in high-pressure solid rocket motors.In this work,the combustion characteristics of AP/HTPB/Al composite propellants containing ferrocene-based catalysts were investigated,including the burning rate,thermal behavior,the local heat transfer,and temperature profile in the range of 7-28 MPa.The results showed that the exponent breaks were still observed in the propellants after the addition of positive catalysts(Ce-Fc-MOF),the burning rate inhibitor((Ferrocenylmethyl)trimethylammonium bromide,Fc Br)and the mixture of Fc Br/catocene(GFP).However,the characteristic pressure has increased,and the exponent decreased from 1.14 to 0.66,0.55,and 0.48 when the addition of Ce-FcMOF,Fc Br and Fc Br/GFP in the propellants.In addition,the temperature in the first decomposition stage was increased by 7.50℃ and 11.40℃ for the AP/Fc Br mixture and the AP/Fc Br/GFP mixture,respectively,compared to the pure AP.On the other hand,the temperature in the second decomposition stage decreased by 48.30℃ and 81.70℃ for AP/Fc Br and AP/Fc Br/GFP mixtures,respectively.It was also found that Fc Br might generate ammonia to cover the AP surface.In this case,a reaction between the methyl in Fc Br and perchloric acid caused more ammonia to appear at the AP surface,resulting in the suppression of ammonia desorption.In addition,the coarse AP particles on the quenched surface were of a concave shape relative to the binder matrix under low and high pressures when the catalysts were added.In the process,the decline at the AP/HTPB interface was only exhibited in the propellant with the addition of Ce-Fc-MOF.The ratio of the gas-phase temperature gradient of the propellants containing catalysts was reduced significantly below and above the characteristic pressure,rather than 3.6 times of the difference in the blank propellant.Overall,the obtained results demonstrated that the pressure exponent could be effectively regulated and controlled by adjusting the propellant local heat and mass transfer under high and low pressures.

Exact analytical solution to three-dimensional phase change heat transfer problems in biological tissues subject to freezing

Analytically solving a three-dimensional （3-D） bioheat transfer problem with phase change during a freezing process is extremely difficult but theoretically important. The moving heat source model and the Green function method are introduced to deal with the cryopreservation process of in vitro biomaterials. Exact solutions for the 3-D temperature transients of tissues under various boundary conditions, such as totally convective cooling, totally fixed temperature cooling and a hybrid between them on tissue surfaces, are obtained. Furthermore, the cryosurgical process in living tissues subject to freezing by a single or multiple cryoprobes is also analytically solved. A closed-form analytical solution to the bioheat phase change process is derived by considering contributions from blood perfusion heat transfer, metabolic heat generation, and heat sink of a cryoprobe. The present method is expected to have significant value for analytically solving complex bioheat transfer problems with phase change.

Embryo Transfer Strategies for Women with Recurrent Implantation Failure During the Frozen-thawed Embryo Transfer Cycles:Sequential Embryo Transfer or Double-blastocyst Transfer?

Objective Both sequential embryo transfer(SeET)and double-blastocyst transfer(DBT)can serve as embryo transfer strategies for women with recurrent implantation failure(RIF).This study aims to compare the effects of SeET and DBT on pregnancy outcomes.Methods Totally,261 frozen-thawed embryo transfer cycles of 243 RIF women were included in this multicenter retrospective analysis.According to different embryo quality and transfer strategies,they were divided into four groups:group A,good-quality SeET(GQ-SeET,n=38 cycles);group B,poor-quality or mixed-quality SeET(PQ/MQ-SeET,n=31 cycles);group C,good-quality DBT(GQ-DBT,n=121 cycles);and group D,poor-quality or mixed-quality DBT(PQ/MQ-DBT,n=71 cycles).The main outcome,clinical pregnancy rate,was compared,and the generalized estimating equation(GEE)model was used to correct potential confounders that might impact pregnancy outcomes.Results GQ-DBT achieved a significantly higher clinical pregnancy rate(aOR 2.588,95%CI 1.267–5.284,P=0.009)and live birth rate(aOR 3.082,95%CI 1.482–6.412,P=0.003)than PQ/MQ-DBT.Similarly,the clinical pregnancy rate was significantly higher in GQ-SeET than in PQ/MQ-SeET(aOR 4.047,95%CI 1.218–13.450,P=0.023).The pregnancy outcomes of GQ-SeET were not significantly different from those of GQ-DBT,and the same results were found between PQ/MQ-SeET and PQ/MQ-DBT.Conclusion SeET relative to DBT did not seem to improve pregnancy outcomes for RIF patients if the embryo quality was comparable between the two groups.Better clinical pregnancy outcomes could be obtained by transferring good-quality embryos,no matter whether in SeET or DBT.Embryo quality plays a more important role in pregnancy outcomes for RIF patients.

Three-dimensional finite element analysis of process-induced residual stress in resin transfer molding process

A three-dimensional finite element analysis of process-induced residual stress in resin transfer molding (RTM) process is presented. The finite element method (FEM) was employed to solve the coupled equations involved in the transient heat transfer and the cure kinetics of the resin, and the distributions of internal temperature and cure degree of the composite at any instant time were obtained. The self-consistent field micro-mechanics model was used to predict the cure-dependent mechanical properties of the composites. Thermal expansion and cure shrinkage were included in the analysis. The thermo-elastic mechanical governing equations were solved using the incremental stress-strain relationship based FEM and the residual stress development was predicted. The present results were validated by the comparisons with the pertinent literature. The numerical example of a half cylinder was presented. The results show that it is necessary to carry out the three-dimensional analysis due to the complex distributions of temperatures, cure degrees and process-induced stress for thick parts, which can be predicted at any point within composite structures in the present analysis.

Selective and Adaptive Incremental Transfer Learning with Multiple Datasets for Machine Fault Diagnosis

The visions of Industry 4.0 and 5.0 have reinforced the industrial environment.They have also made artificial intelligence incorporated as a major facilitator.Diagnosing machine faults has become a solid foundation for automatically recognizing machine failure,and thus timely maintenance can ensure safe operations.Transfer learning is a promising solution that can enhance the machine fault diagnosis model by borrowing pre-trained knowledge from the source model and applying it to the target model,which typically involves two datasets.In response to the availability of multiple datasets,this paper proposes using selective and adaptive incremental transfer learning(SA-ITL),which fuses three algorithms,namely,the hybrid selective algorithm,the transferability enhancement algorithm,and the incremental transfer learning algorithm.It is a selective algorithm that enables selecting and ordering appropriate datasets for transfer learning and selecting useful knowledge to avoid negative transfer.The algorithm also adaptively adjusts the portion of training data to balance the learning rate and training time.The proposed algorithm is evaluated and analyzed using ten benchmark datasets.Compared with other algorithms from existing works,SA-ITL improves the accuracy of all datasets.Ablation studies present the accuracy enhancements of the SA-ITL,including the hybrid selective algorithm(1.22%-3.82%),transferability enhancement algorithm(1.91%-4.15%),and incremental transfer learning algorithm(0.605%-2.68%).These also show the benefits of enhancing the target model with heterogeneous image datasets that widen the range of domain selection between source and target domains.

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

Numerical Investigation of Heat and Mass Transfer in Nanofluid-Filled Porous Medium

In this work, we numerically study the laminar mixed convection of fluid flow in a vertical channel filled with porous media during the drying process. The porous medium, modeled as a vertical wall, consists of solid and nanofluid phase (Water-Al2O3 or Water-Cu), as well as a gas phase. The established model is developed based on Whitaker’s theory and resolved by our numerical code using Fortran. Results principally show the influence of various physical parameters, such as nanoparticle volume fraction, ambient temperature, and saturation on heat and mass transfer on the drying process. This study brings the effect of the presence of nanofluids in porous media. It contributes not only to our fundamental understanding of drying processes but also provides practical insights that can guide the development of more efficient and sustainable drying technologies. .