Progress of Cryomodule System in 2017

ADS Injector-II linear accelerator is mainly composed of ECR ion source,LEBT,RFQ,MEBT,a superconducting accelerating segment and HEBT.The superconducting accelerating segment is composed of two HWR010 cavity cryomodules,a taper cavity cryomodule and a spoke cavity cryomodule(CM1+CM2+CM3+CM4),which has accelerated the proton beam to 25 MeV in Jun.2017.

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.

Design and Experimental Investigation for Subsea Control Module Test System

As a core part of subsea production systems,subsea control modules(SCMs)are costly,difficult,and expensive to install and inconvenient to use in underwater maintenance.Therefore,performance and function tests must be carried out before launching SCMs.This study developed a testing device and an SCM test by investigating SCMs and their underwater.The testing device includes four parts:a hydraulic station,an SCM test stand,a signal generating device,and an electronic test unit.First,the basic indices of the testing device were determined from the performance and working parameters of the SCM.Second,the design scheme of the testing device for the SCM was tentatively proposed,and each testing device was designed.Finally,a practical measurement of the SCM,in combination with the hydraulic station,SCM test stand,signal generator,electronic unit,and highpressure water tank,was carried out according to the test requirements.The measurement mainly involved equipment inspection before testing and an experimental test for the SCM.The validity and feasibility of the testing device and method were simultaneously verified through an association test.

Thermal-Hydraulic System Study of the Helium Cooled Pebble Bed (HCPB) Test Blanket Module (TBM) for ITER Using System Code RELAP5

The HCPB concept has been a European DEMO reference concept for nearly one decade. Detailed thermal-hydraulic study on the control behavior of the whole system is one of the important parts of this development. The thermal-hydraulic effect of the TBM-combined cooling circuit during a cyclic operation in ITER has been studied using the system code RELAP5. The RELAP5 is based on an one-dimensional, transient two-fluid model for the flow of a two-phase steam-water mixture that can contain noncondensable components like Helium. The RELAP5models are modified to take the cyclic operation of the circulator, heat, exchanger, bypass, valves etc in to account. A sequence of operational phases is investigated, starting from the cold state through the heating phase that brings the system to a stand-by condition, followed by typical power cycles applied in ITER. The results show that the implemented control mechanisms keep the inlet temperature to the TBM and the total mass flow rate at the required values through all phases.

Digital image stabilization system based on inertial measurement module

In order to stabilize the video module to build digital image stabilization image sequence, a method of using inertial measurement system is proposed. Through applying real-time attitude in- formation of the camera that obtained by high-precision attitude sensor to estimate the image motion vector and then to compensate for image, the purpose of stabilizing the image sequence can be a- chieved. Experiments demonstrate that this method has a high image stabilization precision, and the up to 16 frame/s video output rate completely meets the real-time requirements.

Functional-type Single-input-rule-modules Connected Neural Fuzzy System for Wind Speed Prediction

Wind is one kind of clean and free renewable energy sources. Wind speed plays a pivotal role in the wind power output. However, due to the random and unstable nature of the wind, accurate prediction of wind speed is a particularly challenging task. This paper presents a novel neural fuzzy method for the hourly wind speed prediction. Firstly, a neural structure is proposed for the functional-type single-input-rule-modules(FSIRMs) connected fuzzy inference system(FIS) to combine the merits of both the FSIRMs connected FIS and the neural network. Then, in order to achieve both the smallest training errors and the smallest parameters, a least square method based parameter learning algorithm is presented for the proposed FSIRMs connected neural fuzzy system(FSIRMNFS). Further,the proposed FSIRMNFS and its parameter learning algorithm are applied to the hourly wind speed prediction. Experiments and comparisons are also made to show the effectiveness and advantages of the proposed approach. Experimental results verified that our study has presented an effective approach for the hourly wind speed prediction. The proposed approach can also be used for the prediction of wind direction, wind power and some other prediction applications in the research field of renewable energy.

Design of Protograph LDPC-Coded MIMO-VLC Systems with Generalized Spatial Modulation

This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC systems.Moreover, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.

Systemic modulation of skeletal mineralization by magnesium implant promoting fracture healing: Radiological exploration enhanced with PCA-based machine learning in a rat femoral model

The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo trials.However,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based implants.Thus,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment modalities.The primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat model.In addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical applications.Compared to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D evaluation.The bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMC)in humerus.In the surgical femur,the Mg group presented higher TMD,but lower TV and BMC in the distal metaphyseal region,as well as reduced BMC at the osteotomy site.Principal component analysis(PCA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D scoring.The study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.

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.

Simulation Research on Performance of a Novel Heating and Cooling System with Thermoelectric Module

This work proposes a novel heating and cooling system,with incorporated thermoelectric module,that can achieve energy balance using a self-water supply heat exchange subsystem.The thermoelectric effect is used to achieve controlled and adjustable heating of the circulating water.Simulations were conducted to study the thermal performance of the system while it simultaneously produces hot and cold water,with different working conditions for the hot-and cold-side water outlets.The results show that the water temperature at the hot side outlet increases from 32℃to 75℃when the power increases from 4.5 to 50 W.Additionally,the use of thermoelectric modules to heat water and recover waste heat is 22%more efficient than ordinary electric water heating systems.

100-112 Gbit/s complete ETDM systems based on monolithically integrated transmitter and receiver modules

Traditional intensity modulated two-level electrical time-division multiplexing （ETDM） transmission systems working at 100 -112 Gbit/s were investigated. The complete ETDM systems based on monolithically integrated transmitter and receiver modules were demonstrated with biterror-rate （BER） performance of 10-s at 107 Gbit/s, and near error-free standard forward error correction （FEC） threshold （2 × 10 -3） at 112 Gbit/s. The experiment results showed that directly modulated high-speed ETDM transmission systems with the symbol rates at 100 Gbaud and beyond were promising candidate for cost-effective 100 GbE applications and might be a preform of the next generation of Terabit/s Ethernet.

Research of the Wireless Management System for Solar Street Lamp Based on NanoLOC AVR Module

In order to improve the service life of solar street lamp, it is necessary to manage the lamp＇s battery in the form of on-line detection via wireless communanication. A wireless managonent systean for solar street lamp based on nanoLOC AVR nttlule is researched in this paper, the system can real-timely detect the solar street lamp＇s battery voltage, corrent, tonperature, internal resistance, residual capacity and so on. And the collected data is transmitted to computer＇ s management via wireless connnunication to achieve recording, storage, analysis and processing for various parameters.

RECURSIVENESS OF ZERO STRUCTURES FOR SYSTEM MATRICES OF INTERCONNECTED LINEAR SYSTEMS VIA MODULE THEORETIC TOOLS

The importance of the zeros of multwariable linear systems is well-knoiun in terms of measure obstructions to the controllability and the. observability. In this paper, a recursive decarnposi Am oj interconnected systems is outlined by taking into account the sequential structure of the connnections. The paper extends the, coordinate, module-theoretic studies from the elementary algebraic systems theory to include the case oj such linear interconnected systems which need not to be controllable or observable. Also, the properties of controllability and observability, the decoupling zeros and the signal Making issues are characterized.

Intelligent Automation Module-Based Gear Edge Grinding System

As industry progresses toward intelligent production and development,on-site workers that perform repetitive tasks will be replaced by intelligent machines.Currently,automation applications still have the following problems:(1)on-site personnel are required to line up the workpieces before a robot arm can pick it up;(2)the trajectory generated by offline programming software must be adjusted by on-site personnel in accordance with the processing results;and(3)because of workpiece positioning errors and tool wear,achieving acceptable processing results is difficult.This study developed intelligent application modules that solve the aforementioned automation application problems.These modules predict processing quality,generate trajectory,enable robot arms to load and unload randomly positioned workpieces,and automatically calibrate the system.An automatic gear edge grinding system was developed by integrating each module;the system increases the processing efficiency and solves the current problem of manual grinding being required after gear processing.

Information System Construction and Function Module Design Based on Reverse Logistics

Reverse logistics are playing more and more important role with the development of competition and the social responsibility of enterprises.It could be divided into commission acceptance,recycling and returned goods handling.Reverse logistics information system consists of the database establishment,network structure and logic structure design.The collection,storage,processing,transmission and output functions of the reverse logistics information system were discussed in the thesis.Eventually,it established seven modules for the reverse logistics information system including the system management module,oriented module,returning goods processing module,reverse transportation management module,information sharing module,statistical analysis module and cost control module.

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.

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.

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.

Exercise-induced adaptation of neurons in the vertebrate locomotor system

Vertebrate neurons are highly dynamic cells that undergo several alterations in their functioning and physiologies in adaptation to various external stimuli.In particular,how these neurons respond to physical exercise has long been an area of active research.Studies of the vertebrate locomotor system’s adaptability suggest multiple mechanisms are involved in the regulation of neuronal activity and properties during exercise.In this brief review,we highlight recent results and insights from the field with a focus on the following mechanisms:(a)alterations in neuronal excitability during acute exercise;(b)alterations in neuronal excitability after chronic exercise;(c)exercise-induced changes in neuronal membrane properties via modulation of ion channel activity;(d)exercise-enhanced dendritic plasticity;and(e)exercise-induced alterations in neuronal gene expression and protein synthesis.Our hope is to update the community with a cellular and molecular understanding of the recent mechanisms underlying the adaptability of the vertebrate locomotor system in response to both acute and chronic physical exercise.

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.