A Novel Multiple DBC-staked units Package to Parallel More Chips for SiC Power Module

Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.

J-shaped association between dietary thiamine intake and the risk of cognitive decline in cognitively healthy,older Chinese individuals

Background The prospective association of dietary thiamine intake with the risk of cognitive decline among the general older adults remains uncertain.Aims To investigate the association between dietary thiamine intake and cognitive decline in cognitively healthy,older Chinese individuals.Methods The study included a total of 3106 participants capable of completing repeated cognitive function tests.Dietary nutrient intake information was collected through 3-day dietary recalls and using a 3-day food-weighed method to assess cooking oil and condiment consumption.Cognitive decline was defined as the 5-year decline rate in global or composite cognitive scores based on a subset of items from the Telephone Interview for Cognitive Status-modified.Results The median follow-up duration was 5.9 years.There was a J-shaped relationship between dietary thiamine intake and the 5-year decline rate in global and composite cognitive scores,with an inflection point of 0.68 mg/day(95%confidence interval(Cl):0.56 to 0.80)and a minimal risk at 0.60-1.00 mg/day of dietary thiamine intake.Before the inflection point,thiamine intake was not significantly associated with cognitive decline.Beyond the inflection point,each unit increase in thiamine intake(mg/day)was associated with a significant decrease of 4.24(95%Cl:2.22 to 6.27)points in the global score and 0.49(95%Cl:0.23 to 0.76)standard units in the composite score within 5 years.A stronger positive association between thiamine intake and cognitive decline was observed in those with hypertension,obesity and those who were non-smokers(all p<0.05).Conclusions This study revealed a J-shaped association between dietary thiamine intake and cognitive decline in cognitively healthy,older Chinese individuals,with an inflection point at 0.68 mg/day and a minimal risk at 0.60-1.00 mg/day of dietary thiamine intake.

The interaction between a shaped charge jet and a single moving plate

Reactive armour is a very efficient add-on armour against shaped charge threats.Explosive reactive armour consists of one or several plates that are accelerated by an explosive.Similar but less violent acceleration of plates can also be achieved in a completely inert reactive armour.To be efficient against elongated jets,the motion of the plates needs to be inclined against the jet such that a sliding contact between the jet and the plates is established.This sliding contact causes a deflection and thinning of the jet.Under certain circumstances,the contact will become unstable,leading to severe disturbances on the jet.These disturbances will drastically reduce the jet penetration performance and it is therefore of interest to study the conditions that leads to an unstable contact.Previous studies on the interaction between shaped charge jets and flyer plates have shown that it is mainly the forward moving plate in an explosive reactive armour that is effective in disturbing the jet.This is usually attributed to the higher plate-to-jet mass flux ratio involved in the collision of the forward moving plate compared to the backward moving plate.For slow moving plates,as occurs in inert reactive armour,the difference in mass flux for the forward and backward moving plate is much lesser,and it is therefore of interest to study if other factors than the mass flux influences on the protection capability.In this work,experiments have been performed where a plate is accelerated along its length,interacting with a shaped charge jet that is fired at an oblique angle to the plate’s normal,either against or along the plate’s velocity.The arrangement corresponds to a jet interacting with a flyer plate from a reactive armour,with the exception that the collision velocity is the same for both types of obliquities in these experiments.The experiments show that disturbances on the jet are different in the two cases even though the collision velocities are the same.Numerical simulations of the interaction support the observation.The difference is attributed to the character of the contact pressure in the interaction region.For a backward moving plate,the maximum contact pressure is obtained at the beginning of the interaction zone and the contact pressure is therefore higher upstream than downstream of the jet while the opposite is true for a forward moving plate.A negative interface pressure gradient with respect to the jet motion results in a more stable flow than a positive,which means that the jet-plate contact is more stable for a backward moving plate than for a forward moving plate.A forward moving plate is thus more effective in disturbing the jet than a backward moving plate,not only because of the higher jet to plate mass flux ratio but also because of the character of the contact with the jet.

Analysis of the Effect of Temperature and Relative Humidity on the Reliability of a Photovoltaic Module

Photovoltaic energy occupies a significant place in the renewable energy market, with photovoltaic (PV) modules playing a vital role in converting solar energy into electricity. However, their effectiveness is likely to be affected by variations in environmental conditions, including temperature and relative humidity. The study examines the impact of these major climatic factors on the reliability of PV modules, aiming to provide crucial information for optimizing and managing these systems under varying conditions. Inspired by Weibull’s law to model the lifespan of components, we proposed a mathematical model integrating a correction factor linked to temperature and relative humidity. Using this approach, simulations in Matlab Simulink reveal that increasing temperature and relative humidity have an adverse impact on the reliability and lifespan of PV modules, with a more pronounced impact on temperature. The results highlight the importance of considering these environmental parameters in the management and optimization of photovoltaic systems to ensure their long-term efficiency.

A High Resolution Convolutional Neural Network with Squeeze and Excitation Module for Automatic Modulation Classification

Automatic modulation classification(AMC) technology is one of the cutting-edge technologies in cognitive radio communications. AMC based on deep learning has recently attracted much attention due to its superior performances in classification accuracy and robustness. In this paper, we propose a novel, high resolution and multi-scale feature fusion convolutional neural network model with a squeeze-excitation block, referred to as HRSENet,to classify different kinds of modulation signals.The proposed model establishes a parallel computing mechanism of multi-resolution feature maps through the multi-layer convolution operation, which effectively reduces the information loss caused by downsampling convolution. Moreover, through dense skipconnecting at the same resolution and up-sampling or down-sampling connection at different resolutions, the low resolution representation of the deep feature maps and the high resolution representation of the shallow feature maps are simultaneously extracted and fully integrated, which is benificial to mine signal multilevel features. Finally, the feature squeeze and excitation module embedded in the decoder is used to adjust the response weights between channels, further improving classification accuracy of proposed model.The proposed HRSENet significantly outperforms existing methods in terms of classification accuracy on the public dataset “Over the Air” in signal-to-noise(SNR) ranging from-2dB to 20dB. The classification accuracy in the proposed model achieves 85.36% and97.30% at 4dB and 10dB, respectively, with the improvement by 9.71% and 5.82% compared to LWNet.Furthermore, the model also has a moderate computation complexity compared with several state-of-the-art methods.

A review on the cooling of energy conversion and storage systems using thermoelectric modules

Exploitation of sustainable energy sources requires the use of unique conversion and storage systems,such as solar panels,batteries,fuel cells,and electronic equipment.Thermal load management of these energy conversion and storage systems is one of their challenges and concerns.In this article,the thermal management of these systems using thermoelectric modules is reviewed.The results show that by choosing the right option to remove heat from the hot side of the thermoelectric modules,it will be a suitable local cooling,and the thermoelectric modules increase the power and lifespan of the system by reducing the spot temperature.Thermoelectric modules were effective in reducing panel temperature.They increase the time to reach a temperature above 50℃ in batteries by 3 to 4 times.Also,in their integration with fuel cells,they increase the power density of the fuel cell.

Review of Thermal Design of SiC Power Module for Motor Drive in Electrical Vehicle Application

In the current vehicle electric propulsion systems,the thermal design of power modules heavily relies on empirical knowledge,making it challenging to effectively optimize irregularly arranged Pinfin structures,thereby limiting their performance.This paper aims to review the underlying mechanisms of how irregularly arranged Pinfins influence the thermal characteristics of power modules and introduce collaborative thermal design with DC bus capacitor and motor.Literature considers chip size,placement,coolant flow direction with the goal of reducing thermal resistance of power modules,minimizing chip junction temperature differentials,and optimizing Pinfin layouts.In the first step,algorithms should efficiently generating numerous unique irregular Pinfin layouts to enhance optimization quality.The second step is to efficiently evaluate Pinfin layouts.Simulation accuracy and speed should be ensured to improve computational efficiency.Finally,to improve overall heat dissipation effectiveness,papers establish models for capacitors,motors,to aid collaborative Pinfin optimization.These research outcomes will provide essential support for future developments in high power density motor drive for vehicles.

Machine learning optimization strategy of shaped charge liner structure based on jet penetration efficiency

Shaped charge liner(SCL)has been extensively applied in oil recovery and defense industries.Achieving superior penetration capability through optimizing SCL structures presents a substantial challenge due to intricate rate-dependent processes involving detonation-driven liner collapse,high-speed jet stretching,and penetration.This study introduces an innovative optimization strategy for SCL structures that employs jet penetration efficiency as the primary objective function.The strategy combines experimentally validated finite element method with machine learning(FEM-ML).We propose a novel jet penetration efficiency index derived from enhanced cutoff velocity and shape characteristics of the jet via machine learning.This index effectively evaluates the jet penetration performance.Furthermore,a multi-model fusion based on a machine learning optimization method,called XGBOOST-MFO,is put forward to optimize SCL structure over a large input space.The strategy's feasibility is demonstrated through the optimization of copper SCL implemented via the FEM-ML strategy.Finally,this strategy is extended to optimize the structure of the recently emerging CrMnFeCoNi high-entropy alloy conical liners and hemispherical copper liners.Therefore,the strategy can provide helpful guidance for the engineering design of SCL.

Engineering vascularized organotypic tissues via module assembly

Adequate vascularization is a critical determinant for the successful construction and clinical implementation of complex organotypic tissue models. Currently, low cell and vessel density and insufficient vascular maturation make vascularized organotypic tissue construction difficult,greatly limiting its use in tissue engineering and regenerative medicine. To address these limitations, recent studies have adopted pre-vascularized microtissue assembly for the rapid generation of functional tissue analogs with dense vascular networks and high cell density. In this article, we summarize the development of module assembly-based vascularized organotypic tissue construction and its application in tissue repair and regeneration, organ-scale tissue biomanufacturing, as well as advanced tissue modeling.

A Hybrid Integrated and Low-Cost Multi-Chip Broadband Doherty Power Amplifier Module for 5G Massive MIMO Application

In this paper,a hybrid integrated broadband Doherty power amplifier(DPA)based on a multi-chip module(MCM),whose active devices are fabricated using the gallium nitride(GaN)process and whose passive circuits are fabricated using the gallium arsenide(GaAs)integrated passive device(IPD)process,is proposed for 5G massive multiple-input multiple-output(MIMO)application.An inverted DPA structure with a low-Q output network is proposed to achieve better bandwidth performance,and a single-driver architecture is adopted for a chip with high gain and small area.The proposed DPA has a bandwidth of 4.4-5.0 GHz that can achieve a saturation of more than 45.0 dBm.The gain compression from 37 dBm to saturation power is less than 4 dB,and the average power-added efficiency(PAE)is 36.3%with an 8.5 dB peak-to-average power ratio(PAPR)in 4.5-5.0 GHz.The measured adjacent channel power ratio(ACPR)is better than50 dBc after digital predistortion(DPD),exhibiting satisfactory linearity.

Research on the LA-UMamba Model for Asymmetric Modules with Added Auxiliary Information

Deep learning techniques are revolutionizing the developmentof medical image segmentation.With the advancement of Transformer models,especially ViT and Swin-Transformer,which enhances the remote-dependent modeling capability of the model through the self-attention mechanism,better segmentation performance can be achieve.Moreover,the high computational cost of Transformer has motivated researchers to explore more efficient models,such as the Mamba model based on state-space modeling(SSM),and for the field of medical segmentation,reducing the number of model parameters is also necessary.In this study,a novel asymmetric model called LA-UMamba was proposed,which integrates visual Mamba module to efficiently capture complex visual features and remote dependencies.The classical design of U-Net was adopted in the upsampling phase to help reduce the number of references and recover more details.To mitigate the information loss problem,an auxiliary U-Net downsampling layer was designed to focus on sizing without extracting features,thus enhancing the protection of input information while maintaining the efficiency of the model.The experiments were conducted on the ACDC MRI cardiac segmentation dataset,and the results showed that the proposed LA-UMamba achieves proved performance compared to the baseline model in several evaluation metrics,such as IoU,Accuracy,Precision,HD and ASD,which improved that the model is successful in optimizing the detail processing and reducing the complexity of the model,providing a new perspective for further optimization of medical image segmentation techniques.

Efficient and Stable Inverted Perovskite Solar Modules Enabled by Solid-Liquid Two-Step Film Formation

A considerable efficiency gap exists between large-area perovskite solar modules and small-area perovskite solar cells.The control of forming uniform and large-area film and perovskite crystallization is still the main obstacle restricting the efficiency of PSMs.In this work,we adopted a solid-liquid two-step film formation technique,which involved the evaporation of a lead iodide film and blade coating of an organic ammonium halide solution to prepare perovskite films.This method possesses the advantages of integrating vapor deposition and solution methods,which could apply to substrates with different roughness and avoid using toxic solvents to achieve a more uniform,large-area perovskite film.Furthermore,modification of the NiO_(x)/perovskite buried interface and introduction of Urea additives were utilized to reduce interface recombination and regulate perovskite crystallization.As a result,a large-area perovskite film possessing larger grains,fewer pinholes,and reduced defects could be achieved.The inverted PSM with an active area of 61.56 cm^(2)(10×10 cm^(2)substrate)achieved a champion power conversion efficiency of 20.56%and significantly improved stability.This method suggests an innovative approach to resolving the uniformity issue associated with large-area film fabrication.

Selection of shaped charges parameters for producing aluminum particles with velocities in the range of 2.5-16 km/s

Testing rocket and space technology objects in ground conditions for resistance to the impact of meteoroids and fragments of space debris can be carried out using shaped charges. To substantiate the design parameters of shaped charges that ensure the formation of aluminum particles in a wide velocity range(from 2.5 to 16 km/s), numerical modeling of the formation process was carried out within the framework of a two-dimensional axisymmetric problem of continuum mechanics using three different computing codes to increase the reliability of the results. The calculations consider shaped charges with a diameter of 20-100 mm with aluminum liners of various shapes. It is shown that the formation of particles with velocities close to the lower limit of the considered range is ensured by gently sloping segmental liners of degressive thickness. To form higher-velocity particles with velocities over 5 km/s, it is proposed to use combined liners, the jet-forming part of which has the shape of a hemisphere of constant thickness or the shape of a semi-ellipsoid or semi-superellipsoid of rotation of degressive thickness.

Arc additive manufacturing of gradient hot forging die with shaped waterways

Under the working environment of high temperature and strong load impact,hot forging die is prone to failure which reduces the service life of die.Using arc additive manufacturing in the die cavity,a gradient material hot forging die with high precision,superior per-formance,and conformal cooling channels is developed.This improves the toughness of the die cavity and reduces the working temperature,thereby forming an isothermal field,which is an effective method to enhance the lifespan of the hot forging die.Three kinds of gradient flux-cored wires are designed for the surface of 5CrNiMo steel,and the microstructure and mechanical properties between gradient interfaces were studied.Based on the spatial curved structure of shaped waterways in the hot forging die cavity,a study was conducted on the strategy of partitioned forming for the manufacturing of the die with shaped waterways.In order to avoid interference with the arc gun,the hot for-ging die is divided into four regions,namely the transition region,upper,middle,and lower region,based on a combination of cavity depth and internal U-shaped and quadrilateral structures.The results show that the developed flux-cored wires have good moldability with straight sides of deposited metal under different process parameters and flat surface without cracks,pores and other defects.Under the same working conditions,the life of hot forging die formed by the gradient materials is more than multiple times that of the single material hot forging die,and the temperature gradient field of the shaped waterway die is 7℃/cm smaller than that of traditional straight waterway.

Analysis of thermal management and anti-mechanical abuse of multi-functional battery modules based on magneto-sensitive shear thickening fluid

Electric vehicles(EVs)have garnered significant attention as a vital driver of economic growth and environmental sustainability.Nevertheless,ensuring the safety of high-energy batteries is now a top priority that cannot be overlooked during large-scale applications.This paper proposes an innovative active protection and cooling integrated battery module using smart materials,magneto-sensitive shear thickening fluid(MSTF),which is specifically designed to address safety threats posed by lithium-ion batteries(LIBs)exposed to harsh mechanical and environmental conditions.The theoretical framework introduces a novel approach for harnessing the smoothed-particle hydrodynamics(SPH)methodology that incorporates the intricate interplay of non-Newtonian fluid behavior,capturing the fluid-structure coupling inherent to the MSTF.This approach is further advanced by adopting an enhanced Herschel-Bulkley(H-B)model to encapsulate the intricate rheology of the MSTF under the influence of the magnetorheological effect(MRE)and shear thickening(ST)behavior.Numerical simulation results show that in the case of cooling,the MSTF is an effective cooling medium for rapidly reducing the temperature.In terms of mechanical abuse,the MSTF solidifies through actively applying the magnetic field during mechanical compression and impact within the battery module,resulting in 66%and 61.7%reductions in the maximum stress within the battery jellyroll,and 31.1%and 23%reductions in the reaction force,respectively.This mechanism effectively lowers the risk of short-circuit failure.The groundbreaking concepts unveiled in this paper for active protection battery modules are anticipated to be a valuable technological breakthrough in the areas of EV safety and lightweight/integrated design.

Analysis for Effects of Temperature Rise of PV Modules upon Driving Distance of Vehicle Integrated Photovoltaic Electric Vehicles

The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO2 emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.

Study on Image Recognition Algorithm for Residual Snow and Ice on Photovoltaic Modules

The accumulation of snow and ice on PV modules can have a detrimental impact on power generation,leading to reduced efficiency for prolonged periods.Thus,it becomes imperative to develop an intelligent system capable of accurately assessing the extent of snow and ice coverage on PV modules.To address this issue,the article proposes an innovative ice and snow recognition algorithm that effectively segments the ice and snow areas within the collected images.Furthermore,the algorithm incorporates an analysis of the morphological characteristics of ice and snow coverage on PV modules,allowing for the establishment of a residual ice and snow recognition process.This process utilizes both the external ellipse method and the pixel statistical method to refine the identification process.The effectiveness of the proposed algorithm is validated through extensive testing with isolated and continuous snow area pictures.The results demonstrate the algorithm’s accuracy and reliability in identifying and quantifying residual snow and ice on PV modules.In conclusion,this research presents a valuable method for accurately detecting and quantifying snow and ice coverage on PV modules.This breakthrough is of utmost significance for PV power plants,as it enables predictions of power generation efficiency and facilitates efficient PV maintenance during the challenging winter conditions characterized by snow and ice.By proactively managing snow and ice coverage,PV power plants can optimize energy production and minimize downtime,ensuring a sustainable and reliable renewable energy supply.

Heat dissipation enhancement method for finned heat sink for AGV motor driver's IGBT module

With the widespread use of high-power and highly integrated insulated gate bipolar transistor(IGBT),their cooling methods have become challenging.This paper proposes a liquid cooling scheme for heavy-duty automated guided vehicle(AGV)motor driver in port environment,and improves heat dissipation by analyzing and optimizing the core component of finned heat sink.Firstly,the temperature distribution of the initial scheme is studied by using Fluent software,and the heat transfer characteristics of the finned heat sink are obtained through numerical analysis.Secondly,an orthogonal test is designed and combined with the response surface methodology to optimize the structural parameters of the finned heat sink,resulting in a 14.57%increase in the heat dissipation effect.Finally,the effectiveness of heat dissipation enhancement is verified.This work provides valuable insights into improving the heat dissipation of IGBT modules and heat sinks,and provides guidance for their future applications.

Unsupervised multi-modal image translation based on the squeeze-and-excitation mechanism and feature attention module

The unsupervised multi-modal image translation is an emerging domain of computer vision whose goal is to transform an image from the source domain into many diverse styles in the target domain.However,the multi-generator mechanism is employed among the advanced approaches available to model different domain mappings,which results in inefficient training of neural networks and pattern collapse,leading to inefficient generation of image diversity.To address this issue,this paper introduces a multi-modal unsupervised image translation framework that uses a generator to perform multi-modal image translation.Specifically,firstly,the domain code is introduced in this paper to explicitly control the different generation tasks.Secondly,this paper brings in the squeeze-and-excitation(SE)mechanism and feature attention(FA)module.Finally,the model integrates multiple optimization objectives to ensure efficient multi-modal translation.This paper performs qualitative and quantitative experiments on multiple non-paired benchmark image translation datasets while demonstrating the benefits of the proposed method over existing technologies.Overall,experimental results have shown that the proposed method is versatile and scalable.

The Origins of the Arc-Shaped Langshan Uplift and Linhe Trench

In the northern part of the Ordos Basin, there is a 325 km long arc-shaped Langshan uplift and a 15 km-deep Linhe Trench in front of Langshan, which are rare geological phenomena for which origins no one has explained. This article comprehensively analyzes the research achievements over the past 40 years of geology, geomorphology, seismic exploration, paleogeography, and oil and gas exploration in the Ordos Basin and Langshan. It recognizes that the northern part of the Ordos Basin experienced a meteorite impact in the Late Cretaceous period. The impact pushed the block northwest ward, subducting after colliding with igneous rocks in the north. This sudden event formed a clear arc-shaped mountain zone in the north and a wedge-shaped trench in front of the mountain. The chaotic layers, prolonged and continuous faults, and numerous thrust layers in the Langshan, a negative anomaly area in the center of the northern Ordos, abnormal orientation of crystalline basement structures in the north of Ordos, Moho uplift, and distribution of meteorite fragments in the northwest of Langshan, all of these geological phenomena support the occurrence of the meteorite impact event, forming the arc-shaped Langshan and the Trench.