Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation

Mg alloys possess an inherent plastic anisotropy owing to the selective activation of deformation mechanisms depending on the loading condition.This characteristic results in a diverse range of flow curves that vary with a deformation condition.This study proposes a novel approach for accurately predicting an anisotropic deformation behavior of wrought Mg alloys using machine learning(ML)with data augmentation.The developed model combines four key strategies from data science:learning the entire flow curves,generative adversarial networks(GAN),algorithm-driven hyperparameter tuning,and gated recurrent unit(GRU)architecture.The proposed model,namely GAN-aided GRU,was extensively evaluated for various predictive scenarios,such as interpolation,extrapolation,and a limited dataset size.The model exhibited significant predictability and improved generalizability for estimating the anisotropic compressive behavior of ZK60 Mg alloys under 11 annealing conditions and for three loading directions.The GAN-aided GRU results were superior to those of previous ML models and constitutive equations.The superior performance was attributed to hyperparameter optimization,GAN-based data augmentation,and the inherent predictivity of the GRU for extrapolation.As a first attempt to employ ML techniques other than artificial neural networks,this study proposes a novel perspective on predicting the anisotropic deformation behaviors of wrought Mg alloys.

New possibility for PET plastic recycling by a tailored hydrolytic enzyme

Plastic waste puts a huge burden on the ecosystem due to the current lack of mature recycling technology.Poly(ethylene terephthalate)(PET)is one of the most produced plastics in the world.Enzymatic decomposition holds the promise of recovering monomers from PET plastic,and the monomers can be used to regenerate new PET products.However,there are still limitations in the activity and thermal stability of the existing PET hydrolases.The recent study by Lu et al.introduced a novel PET hydrolase via machine learning-aided engineering.The obtained PET hydrolase showed excellent activity and thermal stability in the hydrolysis of PET and is capable of directly degrading large amounts of postconsumer PET products.This approach provides an effective method for recycling PET waste and is expected to improve the current state of plastic pollution worldwide.

IMPROVE THE KINETIC PERFORMANCE OF THE PUMP CONTROLLED CLAMPING UNIT IN PLASTIC INJECTION MOLDING MACHINE WITH ADAPTIVE CONTROL STRATEGY

The kinetic characteristics of the clamping unit of plastic injection molding machine that is controlled by close loop with newly developed double speed variable pump unit are investigated. Considering the wide variation of the cylinder equivalent mass caused by the transmission ratio of clamping unit and the severe instantaneous impact force acted on the cylinder during the mold closing and opening process, an adaptive control principle of parameter and structure is proposed to improve its kinetic performance. The adaptive correlation between the acceleration feedback gain and the variable mass is derived. The pressure differential feedback is introduced to improve the dynamic performance in the case of small inertia and heavy impact load. The adaptation of sum pressure to load is used to reduce the energy loss of the system. The research results are verified by the simulation and experiment, The investigation method and the conclusions are also suitable for the differential cylinder system controlled by the traditional servo pump unit.

Machine Learning Models of Plastic Flow Based on Representation Theory

We use machine learning(ML)to infer stress and plastic flow rules using data from representative polycrystalline simulations.In particular,we use so-called deep(multilayer)neural networks(NN)to represent the two response functions.The ML process does not choose appropriate inputs or outputs,rather it is trained on selected inputs and output.Likewise,its discrimination of features is crucially connected to the chosen inputoutput map.Hence,we draw upon classical constitutive modeling to select inputs and enforce well-accepted symmetries and other properties.In the context of the results of numerous simulations,we discuss the design,stability and accuracy of constitutive NNs trained on typical experimental data.With these developments,we enable rapid model building in real-time with experiments,and guide data collection and feature discovery.

Quantitative structure-plasticity relationship in metallic glass:A machine learning study

The lack of the long-range order in the atomic structure challenges the identification of the structural defects,akin to dislocations in crystals,which are responsible for predicting plastic events and mechanical failure in metallic glasses(MGs).Although vast structural indicators have been proposed to identify the structural defects,quantitatively gauging the correlations between these proposed indicators based on the undeformed configuration and the plasticity of MGs upon external loads is still lacking.Here,we systematically analyze the ability of these indicators to predict plastic events in a representative MG model using machine learning method.Moreover,we evaluate the influences of coarse graining method and medium-range order on the predictive power.We demonstrate that indicators relevant to the low-frequency vibrational modes reveal the intrinsic structural characteristics of plastic rearrangements.Our work makes an important step towards quantitative assessments of given indicators,and thereby an effective identification of the structural defects in MGs.

Life Can’t Be Any Easier than This—Introduction of the Portable and Disposable V.A.C. Machines

The application of controlled levels of negative pressure on to a wound has been shown to accelerate evacuation of dead cells, debris and fluid which eventually encourages wound healing in a verity of surgical wounds. Vacuum Assisted Closure (V.A.C.) therapy—KCI Medical Limited, the terminology by which this is widely known, became popular, especially among the plastic surgery professionals in America and soon gained recognition worldwide. It is now widely used in the UK to manage and assist healing in a wide variety of wounds. Although KCI’s V.A.C. machines were the only ones on the market for a number of years, several wound management companies have now brought out their own machines and these are now known collectively as topical negative pressure therapy (TNPT). Traditional TNPT is often considered a relatively costly procedure. It is often used in patients with large wounds to facilitate dressing management and promote rapid cleaning and granulation. This may also allow them to be discharged to the community when they would otherwise remain inpatients, thereby saving bed days. Capital purchase of the machines is expensive and hospitals often rent or lease them on a short or long term basis. This can lead to difficulties in arranging the finances for discharge to the community. Subsequent dressing changes (recommended every 48 - 72 hrs) also incur high costs and involvement of the trained medical or nursing staff. As we all know;“Need is the mother of invention”. The disposable TNPT machine (V.A.C. ViaTM KCI Medical Ltd) has been introduced to help to solve these problems. It is a single use machine, inclusive of a dressing and canister and available off the shelf. It is very cost effective, easy to use and is used for small to moderate sized wounds. Senior author is using this machine which excellent results and illustrated the use of this machine with pictures in this paper.

Soil moisture content as a predictor of soil disturbance caused by wheeled forest harvesting machines on soils of the Western Carpathians

Limiting surface soil disturbance caused by forest harvesting machines is an important task and is influenced by the selection of efficient and reliable predictors of such disturbance. Our objective was to determine whether soil moisture content affects soil load bearing capacity and the formation of ruts. Measurements were conducted in six forest stands where various machines operated. We measured the formation of ruts along skid trails in connection with varying soil moisture content. Soil moisture content was determined through the gravimetric sampling method. Our results showed that severe（rut depth16–25 cm） to very severe disturbance（rut depth [26 cm）occurred in forest stands where the instantaneous soil moisture exceeded its plasticity limits defined through Atterberg limits. Atterberg limits of soil plasticity ranged from 26 to 32 % in individual stands. Regression and correlation analysis confirmed a moderately strong relationship（R = 0.52; p ／ 0.05） between soil moisture content and average rut depth. This confirmed that soil moisture is a suitable and effective predictor of soil disturbance.

Versatile Plastic Bottles Blowing Machine

The versatile plastic bottle blowing machine, developed and produced by the Anhui Tongda Science and Technology Development Corp. under the Sino-foreign joint venture Guobao Group, has been exported to Britain, Iceland, Paraguay, Thailand, Pakistan, Bangladesh and the Commonwealth of Independent States. At an

New Model Die Set for PET Plastic Jet-Moulding Machine

At the China International Food Packing Machinery Exhibition, the new model die set for PET plastic jet-mouldingmachine developed by the Zhejiang Province Taizhou Municipality Huangyan Sanyou Plastics Factory attracted the attention of numerous domestic and foreign clients. They rushed to the stand in great numbers for consultation and talks on ordering. According to the evaluation of the experts concerned, the die set is the most advanced one nationwide for PET plastic jet-moulding machinery.

Analysis and correction of the machining errors of small plastic helical gears by ball-end milling

Many small-size precise plastic helical involutes gears are used in electrical appliances to transmit rotary movements con- tinuously and smoothly. Ball-end milling is an effective method for trial manufacture or small batch production of this type of gear, but the precision of the gear is usually low. In this research, the main sources of the errors of the gear, machining errors of the tooth profile and trace of the gear obtained were analyzed. The correction amounts for these errors are then determined by using a CNC gear tester. They are used to generate a new 3D-CAD model for gear machining with better nrecision.

Computer aided design of free-machinability prehardened mold steel for plastic

In order to improve the machinability but not to impair other properties of the prehardened mold steel for plastic, the composition was designed by application of Thermo-Calc software package to regulate the type of non-metallic inclusion formed in the steel. The regulated non-metallic inclusion type was also observed by SEM and EDX. Then the machinability assessment of the steel with designed composition under different conditions was studied by the measurement of tool wear amount and cutting force. The results show that the composition of free cutting elements adding to mold steel for plastic can be optimized to obtain proper type of non-metallic inclusion in the aid of Thermo-Calc, compared with the large volume fraction of soft inclusion which is needed for promoting ductile fracture at low cutting speeds, the proper type of inclusion at high cutting speeds is glassy oxide inclusion. All those can be obtained in the present work.

塑性磨料气射流仿真与试验研究

塑性磨料气射流加工(PAJM)是一种先进的减材加工技术,是采用热固性塑性磨料代替传统硬磨料而发展的新型技术,该技术可有效去除表面涂层,且不损伤基材。基材无损主要是通过控制塑性磨料对基材的冲蚀应力,使得塑性磨料的冲蚀应力小于基材纤维的极限强度或纤维与树脂的结合强度。本研究采用有限元仿真和试验相结合的方法,对颗粒速度进行理论分析、计算流体动力学仿真模拟和试验研究,研究不同气体压力下的颗粒速度,计算结果与试验数据吻合较好。结果表明,随着磨料颗粒离开喷嘴,在距离喷嘴出口6.2 dN内(dN为喷嘴内径),颗粒速度增加;相反,距离喷嘴出口6.2 dN外,颗粒速度逐渐减小。当磨料粒径由20~30目变为40~50目时,最大颗粒速度由164.365 m/s增加到228.402 m/s。随着磨料粒径的减小,颗粒速度增加,且发散角增加。相比而言,数值模型能更好的预测塑性磨料的颗粒速度和分布。该研究突出了控制颗粒粒径和支座距离对射流场颗粒速度和发散角的影响。为控制颗粒对基材的冲蚀应力,避免基材损伤提供理论参考。

基于机器学习和遗传算法的非局部晶体塑性模型参数识别

非局部晶体塑性模型考虑了由非均匀变形引起的位错在空间上的重排,使得其本构模型变得复杂,可调节参数众多,因此采用常规的“试错法”难以准确确定这些参数.虽然遗传算法能够稳健地全局优化解决参数确定问题,但对于非局部晶体塑性模型,其计算成本相对较高.为解决这一问题,提出了一种耦合机器学习模型的遗传算法,以有效降低计算成本.针对含有冷却孔的镍基高温合金的拉伸响应问题,以单拉应力-应变曲线为目标,基于屈服应力和最终应力建立评价公式,使得优化结果与实验尽可能接近.在这一方法中,机器学习模型能够通过非局部晶体塑性模型的参数来预测相应的应力值,从而替代了遗传算法中原本需要的有限元计算过程.为了分析本构模型参数对单拉力学响应的影响,研究采用SHAP框架,并通过有限元结果进行验证.结果表明,通过该方法可以有效获取非局部晶体塑性模型参数,使得参数计算得到的应力-应变响应与实验结果吻合较好.此外, SHAP框架能够提供本构模型参数的重要程度分析,以及对屈服应力和最终应力的影响.

铜对4Cr16Mo塑料模具钢切削性能的影响

将4Cr16MoCu、4Cr16Mo和SDP136钢在1030℃保温4 h,冷却至室温后回火两次,第一次为540℃×4 h,4Cr16MoCu钢的第二次回火工艺为590℃×3 h,4Cr16Mo和SDP136钢为565℃×3 h,使其硬度达到35~36 HRC。采用扫描电子显微镜检测钢的显微组织,采用数控车床进行切削性能试验。分别采用SY-3F型应变式三维测力传感器、红外测温仪、TR200粗糙度测量仪和超景深显微镜测定切削力、刀尖温度、工件粗糙度和磨损刀具的形貌。结果表明:在相同的切削条件下,铜的添加能延长刀具的使用寿命;切削4Cr16MoCu钢的刀具温度比切削4Cr16Mo钢的刀具温度低50℃,切削试验的前、中期4Cr16Mo钢的切削力比4Cr16MoCu钢大43~94 N,但后期4Cr16MoCu钢的切削力上升至839 N,比SDP136钢大211 N。

残膜机械化回收技术专利信息分析

地膜覆盖技术在农业生产中得到广泛应用,但随着覆膜年限和面积不断增加,残留地膜给环境带来严重污染。目前,机械回收是治理残膜污染的有效技术手段。对现有残膜机械化回收技术专利信息进行归纳总结,从申请时间、申请地区、专利权人类型和技术特征等方面阐述残膜机械化回收技术发展趋势。从机械化角度分析残膜回收技术专利失效的主要原因,对不同申请主体的专利失效现象进行剖析,更好地理解专利失效背后的原因。结合现有专利技术热点和发展趋势,提出促进残膜机械化回收技术的发展建议。

超声塑化微注射成型技术研究现状及展望

简述了超声塑化中界面摩擦生热、黏弹性生热和空化效应3种生热机理及其研究现状,从超声塑化微注射成型(UPMIM)工艺参数的影响效果和成品性能的影响因素两个角度分析概括了UPMIM工艺的研究现状。介绍了现有UPMIM装置的结构及加工步骤,概括了UPMIM在精密药物输送装置、智能定制植入物和微流控设备等领域的应用研究现状,指出了UPMIM技术大规模工业化生产应用所具有的技术优势和面临的诸多技术挑战,对UPMIM未来的主要研究方向与应用领域进行了总结与展望。

辊板式铝塑泡罩包装机的开发

目的铝塑泡罩包装机分为DPA系列(辊辊型)、DPP(B)系列(平板或板板型)、DPH(T)系列(辊板型)3种类型,针对过去的泡罩包装机存在着一些如封合后会弯曲、影响美观以及效率低下等问题,需要加大力度对泡罩包装机进行设计开发,使其达到国际先进水平。方法DPH(T)系列辊板式铝塑泡罩包装机在辊辊式和平板式铝塑泡罩包装机的技术基础上优化并组合,DPH(T)系列辊板式铝塑泡罩包装机采用平板式吹塑成型(也叫正压成型)和辊式封合技术;新研发的DPH辊板型铝塑泡罩包装机采用摆线运动规律来改善凸轮的动力特性。结果DPH(T)系列铝塑泡罩包装机生产效率高、运行平稳、结构合理、操作简单、性能可靠、消除了刚性和柔性冲击;DPH(T)系列铝塑泡罩包装机广泛用于药品、食品等的包装。结论DPH(T)系列铝塑泡罩包装机综合性能得到了改善和提高,并且有些机型目前已经达到了国际先进水平。

刀具类型及工艺方法对纤维增强复合材料制孔加工质量影响的研究进展

概括总结了刀具类型及工艺方法对纤维增强复合材料(FRC)制孔加工质量影响的最新研究进展。首先介绍了FRC的分类、特性及其在航空航天领域中的应用,以及传统麻花钻制孔刀具及工艺存在的加工缺陷及问题;其次,概述了FRC制孔的分层缺陷形成及评价;再次,从制孔刀具类型及工艺方法两方面,分别概述了FRC制孔加工质量的研究进展,并总结了改善制孔加工质量的新刀具、新工艺和新方法;最后,分析总结了刀具类型及工艺方法对FRC制孔加工质量效果的影响,同时对未来发展趋势和未来工作研究可能方向进行了展望。

变论域模糊PID在吹膜机收卷张力中的应用

在吹膜机生产加工过程中,吹膜机张力的精准控制和稳定性是影响薄膜质量的关键因素,传统PLC控制的吹膜机张力控制系统是一个非线性、强耦合和抗干扰能力低的控制系统,结合吹膜机设备结构功能特点,搭建薄膜收卷张力控制系统模型,采用变论域模糊PID控制方式实现对吹膜机张力精准的提高。变论域模糊PID控制主要是通过伸缩因子来实时调整模糊论域变化进而实现动态调节PID参数,通过MATLAB仿真对比分析可知,变论域模糊PID在收卷张力控制效果方面优于模糊PID和传统PID控制方式,且吹膜机张力控制系统无超调,上升时间短,抗干扰能力强。实验表明,变论域模糊PID控制策略对非线性时变的薄膜张力控制效果改变显著。

塑料挤出复合机分配器流道仿真优化

针对塑料挤出复合机的分配器流道容易出现塑料熔体滞留时间较长、烧焦等问题,对塑料挤出复合机的分配器流道进行仿真优化。采用质量连续性方程、动量控制方程、四面体网格划分、Carreau模型、仿工况模拟VOF模型、单相流模拟仿真等方法,建立几何模型、数学模型、材料本构模型、内流道网格划分模型等分配器流动仿真模型,对分配器内流道2种塑料熔体的流动过程进行仿工况模拟仿真分析;掌握2种塑料熔体在分配器内流动过程中的速度分布、压力分布等情况,并对分配器原始结构进行压力分布、流线分布、速度矢量分布、出口处流场分析等单相流模拟分析,得到造成熔体滞留的3个主要区域。针对横向扩展段边角处、三股熔体交汇处、靠近出口处等3个主要区域,提出横向扩展段边角处增加导流装置、调整熔体交汇处控制刀具偏角、去掉出口处小台阶等分配器流道结构优化方案,通过对比优化前后结构的压力分布、流线分布、速度矢量分布等单相流仿真结果,发现优化结构明显好于原始结构,分配器流道的压力分布更加均匀,能大大减少这3个区域的熔体滞留,从而能够有效提高挤出塑料复合薄膜成品的质量。