Application of neural networks to predict the elevated temperature flow behavior of a low alloy steel

In order to study the workability and establish the optimum hot forming processing parameters for 42CrMo steel, the compressive deformation behavior of 42CrMo steel was investigated at the temperatures from 850 °C to 1150 °C and strain rates from 0.01 s⁻¹ to 50 s⁻¹ on Gleeble-1500 thermo-simulation machine. Based on these experimental results, an artificial neural network (ANN) model is developed to predict the constitutive flow behaviors of 42CrMo steel during hot deformation. The inputs of the neural network are deformation temperature, log strain rate and strain whereas flow stress is the output. A three layer feed forward network with 12 neurons in a single hidden layer and back propagation (BP) learning algorithm has been employed. The effect of deformation temperature, strain rate and strain on the flow behavior of 42CrMo steel has been investigated by comparing the experimental and predicted results using the developed ANN model. A very good correlation between experimental and predicted result has been obtained, and the predicted results are consistent with what is expected from fundamental theory of hot compression deformation, which indicates that the excellent capability of the developed ANN model to predict the flow stress level, the strain hardening and flow softening stages is well evidenced.     

闭孔泡沫铝压缩性能研究

闭孔泡沫铝作为一种新型多孔金属材料,被应用于各个领域,但其压缩力学性能受到孔隙率、孔洞结构参数、相对密度及材料基本力学性能等的影响,因此针对某闭孔泡沫铝企业研究出的一款新型产品,在确定其相关参数后进行10组试样的压缩力学试验,确定其应力-应变曲线,分析各段曲线意义和产生机理,并针对其特有的压缩力学性能,研究在外力作用下...     

Preparation of polybenzoxazine foam and its transformation to carbon foam

An organic foam derived from a new type of phenolic resin, namely polybenzoxazine, was successfully prepared with a noncomplex and economical foaming method by using azodicarbonamide (AZD) as a foaming agent. The influence of foam density on the physical and mechanical properties of the foams was studied. All resulting polybenzoxazine foams and carbon foams exhibit a tailorable uniform microstructure. Polybenzoxazine foams showed a density in the range of 273–407 kg/m³, and a compressive strength and a compressive modulus in the range of 5.2–12.4 MPa and 268–681 MPa, respectively. The foam density not only affects the physical and mechanical properties, but also affects the deformation response of the foam. In addition, the polybenzoxazine foam was further transformed into carbon foam by carbonization at 800 °C under an inert atmosphere, and its properties were examined.     

高温处理后闭孔泡沫铝压缩性能及变形机理

目的 探究温度和孔隙率对闭孔泡沫铝材料压缩力学性能和变形机理的影响。方法 将孔隙率为84.3%～87.3%的泡沫铝试件在温度25～700 ℃内进行加热处理,对处理后的试样开展准静态压缩实验。结果 在准静态压缩条件下,闭孔泡沫铝材料在不同温度加热处理后的压缩应力–应变曲线均经历了3个阶段:弹性阶段、塑性平台阶段和密实阶段。孔隙率从87.3%减小到84.3%时,其弹性模量增大了44.4 MPa,屈服强度增大了0.39 MPa,平台应力增大了0.94 MPa。孔隙率为84.3%的泡沫铝,在25 ℃时,其弹性模量为141.4 MPa、屈服强度为4.25 MPa、平台应力为4.75 MPa;当加热温度为500 ℃时,弹性模量减小到了128.0 MPa、屈服强度减小到了4.22 MPa、平台应力减小到了4.51 MPa。结论 泡沫铝的弹性模量、抗压屈服强度和平台应力均随孔隙率的增加而减小;加热温度低于500 ℃以下时,泡沫铝材料力学性能变化很小,但屈服强度和弹性模量均小幅度降低;在压缩载荷下,泡沫铝的变形破坏模式呈现出先从试件铝基体较薄弱部分产生孔壁塑性变形、孔洞坍塌,并逐渐出现断裂压缩带,直至泡沫铝孔洞完全坍塌密实。     

Closed-cell Al alloy composite foams: Production and characterization

Foamy Al alloy SiCp composites of different densities ranging from 0.4 to 0.7 g/cm³ were manufactured by melt-foaming process, which consisted of direct CaCO₃ addition into the molten A356 aluminum bath. Mechanical properties and morphological observations indicated that the three-stage deformation mechanism of typical cellular foams is dominant in the produced A356 aluminum foams. Middle-stage stress plateau shrinkage plus compressive strength and bending stress enhancements were observed in denser foams. With the same Al/SiCp ratio, energy absorption ability and plastic collapse strength of the closed-cell foams were increased with the foam density. Doubling cell-face bending effects resulted in larger compressive than bending strengths in the closed-cell foams; while stiffness lowering was due to the cell-face stretching conditions.     

Predicting of mechanical properties of Fe–Mn–(Al, Si) TRIP/TWIP steels using neural network modeling

In this work, an artificial neural network (ANN) model was established in order to predict the mechanical properties of transformation induced plasticity/twinning induced plasticity (TRIP/TWIP) steels. The model developed in this study was consider the contents of Mn (15–30 wt%), Si (2–4 wt%) and Al (2–4 wt%) as inputs, while, the total elongation, yield strength and tensile strength are presented as outputs. The optimal ANN architecture and training algorithm were determined. Comparing the predicted values by ANN with the experimental data indicates that trained neural network model provides accurate results.     

Artificial neural network modeling to predict the high temperature flow behavior of an AZ81 magnesium alloy

In the present work, the capability of artificial neural network (ANN) has been evaluated to describe and to predict the high temperature flow behavior of a cast AZ81 magnesium alloy. Toward this end, a set of isothermal hot compression tests were carried out in temperature range of 250–400 °C and strain rates of 0.0001, 0.001 and 0.01 s⁻¹ up to a true strain of 0.6. The flow stress was primarily predicted by the hyperbolic laws in an Arrhenius-type of constitutive equation considering the effects of strain, strain rate and temperature. Then, a feed-forward back propagation artificial neural network with single hidden layer was established to investigate the flow behavior of the material. The neural network has been trained with an in-house database obtained from hot compression tests. The performance of the proposed models has been evaluated using a wide variety of statistical indices. The comparative assessment of the results indicates that the trained ANN model is more efficient and accurate in predicting the hot compressive behavior of cast AZ81 magnesium alloy than the constitutive equations.     

Prediction of mechanical properties of a warm compacted molybdenum prealloy using artificial neural network and adaptive neuro-fuzzy models

Predictive models using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were successfully developed to predict yield strength and ultimate tensile strength of warm compacted 0.85 wt.% molybdenum prealloy samples. To construct these models, 48 different experimental data were gathered from the literature. A portion of the data set was randomly chosen to train both ANN with back propagation (BP) learning algorithm and ANFIS model with Gaussian membership function and the rest was implemented to verify the performance of the trained network against the unseen data. The generalization capability of the networks was also evaluated by applying new input data within the domain covered by the training pattern. To compare the obtained results, coefficient of determination (R²), root mean squared error (RMSE) and average absolute error (AAE) indexes were chosen and calculated for both of the models. The results showed that artificial neural network and adaptive neuro-fuzzy system were both potentially strong for prediction of the mechanical properties of warm compacted 0.85 wt.% molybdenum prealloy; however, the proposed ANFIS showed better performance than the ANN model. Also, the ANFIS model was subjected to a sensitivity analysis to find the significant inputs affecting mechanical properties of the samples.     

FE modeling of the compressive behavior of porous copper-matrix nanocomposites

Compressive mechanical test and numerical simulation via finite element modeling have been employed on closed-cell copper-matrix nanocomposite foams reinforced by alumina particles. The FE analysis' purpose was to model the foam deformation behavior under compressive loading and to investigate the correlation between material characteristics and the compressive mechanical behavior. Exploring this, several foam samples with different conditions were manufactured and compression test was carried out on the samples. Scanning electron microscopy and image analysis have been performed on the foam samples to obtain the required data for the numerical simulation. The stress–strain curves exhibited plateau stress between 18 and 112.5 MPa and energy absorption in the range of 20.03–51.20 MJ/m³ for the foams with different relative densities. The foams exhibited enhanced mechanical properties to an optimum value, as a consequence of increasing the reinforcing nanoparticles, through both experimental tests and numerical simulation data. Also, the validated model of copper-matrix nanocomposite foams has been used to probe stress distribution in the foams. In addition, the results obtained by numerical simulation via ABAQUS CAE finite element modeling provided support for experimental test results. This confirmed that FEM is a favorable technique for predicting mechanical properties of nanocomposite copper foams.     

Preparation, characterization and applications of novel iminodiacetic polyurethane foam (IDA-PUF) for determination and removal of some alkali metal ions from water

The new type of ion chelating resin (IDA-PUF) has iminodiacetic group that was prepared from polyurethane foam (PUF) by the reaction between primary amine of PUF and monochloro-acetic acid. The IDA-PUF was characterized using infrared spectra, elemental and thermal analysis. The exchange properties and chromatographic behaviour of the new chelating resin were investigated for removal of some alkali metal ions (lithium, sodium and potassium) using batch and column processes. The maximum distribution coefficient (K_D) of trace alkali metal ions was in the pH range of 8–10. The kinetics of sorption of the alkali metal ions was found to be fast with average values of half-life of sorption (t_1/2) of 4.93 min. The values of ΔG, ΔS and ΔH were −3.86 kJ mol⁻¹, 57.73 J mol⁻¹ K⁻¹ and 14.41 kJ mol⁻¹, respectively, which reflects the spontaneous and endothermic nature of ion exchanger process. The average sorption capacity of IDA-PUF is 4.8 mmol/g for alkali metal ions, enrichment factors ≈40 and the recovery 95–100% were also achieved with average value of RSD% = 1.67. The proposed method has been successfully applied to preconcentrate, determinate and remove the alkali metal ions from different samples of water.     

闭孔泡沫铝的力学性能和吸能能力

在闭孔泡沫铝准静态压缩试验的基础上,研究了其力学性能、吸能能力。结果表明,闭孔泡沫铝单轴压缩应力-应变曲线呈现线弹性变形、塑性平台阶段、致密化阶段3个阶段;闭孔泡沫铝的压缩强度、吸能能力随着孔隙率的增大而减小,采用Gibson-Ashby模型分析闭孔泡沫铝的压缩屈服强度,吻合良好。并在此基础上,提出可供工程使用的多孔泡沫金属吸能能力公式,为其工程应用提供理论支持。     

Effect of strain rate and density on dynamic behaviour of syntactic foam

The final objective of this study is to improve the mechanical behaviour of composite sandwich structures under dynamic loading (impact or crash). Cellular materials are often used as core in sandwich structures and their behaviour has a significant influence on the response of the sandwich under impact. Syntactic foams are widely used in many impact-absorbing applications and can be employed as sandwich core. To optimize their mechanical performance requires the characterisation of the foam behaviour at high strain rates and identification of the underlying mechanisms.Mechanical tests were conducted on syntactic foams under quasi-static and high strain rate compression loading. The material behaviour has been determined as a function of two parameters, density and strain rate. These tests were complemented by experiments on a new device installed on a flywheel. This device was designed in order to achieve compression tests on foam at intermediate strain rates. With these test machines, the dynamic compressive behaviour has been evaluated in the strain rate range up [6.7 · 10⁻⁴ s⁻¹, 100 s⁻¹].Impact tests were conducted on syntactic foam plates with varying volume fractions of microspheres and impact conditions. A Design of Experiment tool was employed to identify the influence of the three parameters (microsphere volume fraction, projectile mass and height of fall) on the energy response. Microtomography was employed to visualize in 3D the deformation of the structure of hollow spheres to obtain a better understanding of the micromechanisms involved in energy absorption.     

开孔与闭孔泡沫铝的压缩力学行为

研究了开孔与闭孔两种胞孔结构不同、制备工艺不同的泡沫铝在准静态压缩载荷下的压缩响应曲线.结果表明:开孔与闭孔泡沫铝压缩应力-应变曲线均具有多孔泡沫材料明显的三阶段特征,即线弹性段、塑性屈服平台段及致密段;相对密度对泡沫材料的力学性能(如杨氏模量、屈服强度)有很大影响;在准静态下,开孔泡沫铝表现出明显的应变率效应,而闭孔泡沫不如开孔敏感;泡沫铝材料表现为弱的各向异性;胞孔结构影响两种泡沫材料的压缩响应曲线.     

Long term water uptake of a low density polyvinyl chloride foam and its effect on the foam microstructure and mechanical properties

The water uptake, evolution of the cell morphology and basic mechanical properties of a 48 kg/m³ commercial polyvinyl chloride (PVC) foam immersed in distilled water and seawater for up to 12 months is investigated. The samples of PVC foam immersed in distilled water showed a faster water absorption rate and water uptake than the samples immersed in seawater. For both conditions, the tensile and compressive properties of the foam evidence a plasticization effect with a small reduction in the elastic modulus (∼10%) and an increase in the ultimate tensile strain (∼19%) for 12 months of immersion. The detailed micrographic analysis conducted provides conspicuous evidence that for both conditions the cells at the surface of the foam are severely damaged after a few days of immersion, but such cell damage is superficial and does not cause severe irreversible damage to the internal cellular microstructure of the foam.     

Coupling extraction–flotation with surfactant and electrochemical degradation for the treatment of PAH contaminated hazardous wastes

The performance of a two-stage process combining extraction of polycyclic aromatic hydrocarbons (PAHs) with an amphoteric surfactant (CAS) followed by electro-oxidation of PAH-foam concentrate was studied for the decontamination of aluminum industry wastes (AIW) and polluted soils. The PAH suspensions extracted from AIW and soils were treated in a 2 L-parallelepipedic electrolytic cell containing Ti/RuO₂ anodes and stainless steel cathodes. Current densities varying from 4.6 to 18.5 mA cm⁻² have been tested with and without addition of a supporting electrolyte (6.25 to 50 kg Na₂SO₄ t⁻¹ of dry waste). The best performance for PAH degradation was obtained while the electrolytic cell was operated during 90 min at a current density of 9.2 mA cm⁻², with a total solids concentration of 2.0%, and in presence 12.5 kg Na₂SO₄ t⁻¹. The application of the process on AIW (initial PAH content: 3424 mg kg⁻¹) allowed extracting 42% of PAH, whereas 50% of PAH was electrochemically degraded in the resulting foam suspensions. By comparison, 44% to 60% of PAH was extracted from polluted soils (initial PAH content: 1758 to 4160 mg kg⁻¹) and 21% to 55% of PAH was oxidized in the foam suspensions. The electrochemical treatment cost (including only electrolyte and energy consumption) recorded in the best experimental conditions varied from 99 to 188 USD $ t⁻¹ of soils or AIW treated.     

粉煤灰聚氨酯复合泡沫静动态力学特性实验研究

以大尺寸粉煤灰漂珠为主要组分,以硬质聚氨酯泡沫为黏结剂制备了一种具有多尺度胞孔形态的复合泡沫,对其准静态压缩和动态冲击下的力学性能和变形机制进行研究。结果表明:①该复合泡沫应力应变曲线具有典型的线弹性、塑性平台和致密化三个特征阶段且具有相对稳定的平台应力;在密度0.45~0.6 g/cm^3,复合泡沫平台应力(6.5~18 MPa)和到压实应变处吸收的能量(3.42~8.9 MJ/m 3)随密度增大而提高,且平台应力与相对密度之间满足幂函数关系;②采用铝蜂窝为增强相可使同密度下复合泡沫抗压强度和平台应力分别提升约20%~45%和10%~25%,准静态下复合泡沫主要发生剪切失效,增强泡沫的主要失效形式则转变为轴向压缩失效。③在0.001~1500 s^-1应变率范围内,复合泡沫抗压强度有明显的应变率效应但平台应力并未随应变率的增大而提高。增强复合泡沫的强度和平台应力均呈现出明显的应变率效应,采用铝蜂窝不仅能提高复合泡沫力学性能,还能够改善其力学行为,使材料具有更优异的动力学特性;研究为工业固废粉煤灰的综合利用提供新思路。     

相对密度对泡沫铝力学性能和能量吸收性能的影响

对不同相对密度的两种胞孔结构--开孔和闭孔泡沫铝进行了单轴压缩试验,研究了相对密度对泡沫铝力学性能和能量吸收性能的影响.结果表明:随着相对密度的增大,泡沫铝的屈服强度与流动应力也相应增加,通过对本实验结果进行拟合,得出泡沫铝的屈服强度与相对密度的关系式.泡沫铝材料吸收的能量随着应变量的增大而增加,在相同应变量下,高密度开孔泡沫铝的吸收能比低密度闭孔材料多.吸能效率反映材料本身的一种属性,高的理想吸能效率表明泡沫铝是一种优良的吸能材料.     

The toucan beak: Structure and mechanical response

The structure and mechanical response of a Toco toucan (Ramphastos toco) beak were established. The beak was found to be a sandwich composite with an exterior of keratin scales (50 μm diameter and 1 μm thickness) and a core composed of fibrous network of closed-cells made of collagen. The tensile strength of the external shell is about 50 MPa. Micro- and nanoindentation hardness measurements corroborate these values. The keratin shell exhibits a strain-rate sensitive response with a transition from slippage of the scales due to release of the organic glue, at a low strain rate (5 × 10^− 5 s^− 1) to fracture of the scales at a higher strain rate (1.5 × 10^− 3 s^− 1). The closed-cell foam consists of fibers having a Young's modulus (measured by nanoindentation) of 12.7 GPa. This is twice as high as the keratin shells, which have E = 6.7 GPa. This is attributed to their higher calcium content. The compressive collapse of the foam was modeled by the Gibson–Ashby constitutive equations.There is a synergistic effect between foam and shell evidenced by a finite-element analysis. The foam stabilizes the deformation of the keratin shell by providing an internal support which increases its buckling load under compressive loading.     

NH3 in-tube condensation heat transfer and pressure drop in a smooth tube

This paper presents an overview of the issues and new results for in-tube condensation of ammonia in horizontal round tubes. A new empirical correlation is presented based on measured NH₃ in-tube condensation heat transfer and pressure drop by Komandiwirya et al. [Komandiwirya, H.B., Hrnjak, P.S., Newell, T.A., 2005. An experimental investigation of pressure drop and heat transfer in an in-tube condensation system of ammonia with and without miscible oil in smooth and enhanced tubes. ACRC CR-54, University of Illinois at Urbana-Champaign] in an 8.1 mm aluminum tube at a saturation temperature of 35 °C, and for a mass flux range of 20–270 kg m⁻² s⁻¹. Most correlations overpredict these measured NH₃ heat transfer coefficients, up to 300%. The reasons are attributed to difference in thermophysical properties of ammonia compared to other refrigerants used in generation and validation of the correlations. Based on the conventional correlations, thermophysical properties of ammonia, and measured heat transfer coefficients, a new correlation was developed which can predict most of the measured values within ±20%. Measured NH₃ pressure drop is shown and discussed. Two separated flow models are shown to predict the pressure drop relatively well at pressure drop higher than 1 kPa m⁻¹, while a homogeneous model yields acceptable values at pressure drop less than 1 kPa m⁻¹. The pressure drop mechanism and prediction accuracy are explained though the use of flow patterns.