Study of residual stresses and distortions from the Ti6Al4V based thinwalled geometries built using LPBF process

The current paper focuses on the prediction of residual stresses and distortions in the Laser Powder Bed Fusion(LPBF)built Ti6Al4V thin-walled geometries using Ansys Additive Print(AAP)software which employs a layer-by-layer accumulation of inherent strain to calculate the deformations.Isotropic and anisotropic strain scaling factors were calibrated initially within the APP software for the Ti6Al4V based single cantilever beam geometry.Subsequently,the numerical simulations were performed in APP software and computed the residual stresses and distortions for the varied process parameters including laser power,scan speed and hatch distance while maintaining the layer thickness constant for all the design iterations.The numerical predictions were compared;they were found to match reasonably well with the XRD measurements within the calibrated regime.

A novel design approach of charge plasma tunnel FET for radio frequency applications

In this paper, the impact of extra electron source(EES) and dual metal gate engineering on conventional charge plasma TFET(CP-TFET) have been done for improving DC and analog/RF parameters. CP-TFET structure is upgraded to double source CP-TFET(DS-CP-TFET) by placing an EES below the source/channel junction for enhancing the device performance in terms of driving current and RF figures of merit(FOMs). But, in spite of these pros, the approach is having cons of higher leakage current similar to MOSFET and negative conductance(inherent nature of TFET). Both the issues have been resolved in the double source dual gate CP-TFET(DS-DG-CP-TFET) by gate workfunction engineering and drain underlapping respectively. Additionally,for getting the optimum performance of DS-DG-CP-TFET, the device sensitivity has been investigated in terms of position of EES,length of drain electrode and workfunction of gate electrode 1(GE1).

粉末冶金Al-5.6Zn-2Mg合金在热压缩过程中加工硬化特性及本构模型的比较

在300~5000℃、应变速率为0.1~0.0001 s−1的条件下,在万能试验机上对Al-5.6Zn-2Mg铝合金进行热压缩试验,以确定动态再结晶开始时的加工硬化速率曲线σ_(c)(ε_(c))l以及关键特征σ_(c)(ε_(c))l、σ_(p)(ε_(p))和σ_(ss)与Z系数之间的相关性。使用了四个本构模型,Arrhenius模型、改进的Johnson-Cook模型(MJC)、改进的Zerilli-Armstrong模型(MZA)和开发的人工神经网络(ANN)。结果表明,ANN型模型和Arrhenius模型的相对误差的绝对平均值最低,分别为0.486%和3.36%,MZA型模型和MJC型模型的相对误差的绝对平均值较高,分别为8.84%和3.93%。由于Arrhenius模型能够处理各种因素之间的非线性关系,因此它被认为是最合适的预测模型,但在材料性质未知或实验数据有限的情况下,MJC模型可能是一种更简单的替代方法。MZA模型不适合估计热压缩时的流变应力。此外,训练最好的神经网络模型的预测性能最好,相对误差的绝对平均值为0.486%,R值为0.99。

Effect of fusion welding processes on tensile properties of armor grade, high thickness, non-heat treatable aluminium alloy joints

AA5059 is one of the high strength armor grade aluminium alloy that finds its applications in the military vehicles due to the higher resistance against the armor piercing (AP) threats. This study aimed at finding the best suitable process among the fusion welding processes such as gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) by evaluating the tensile properties of AA5059 aluminium alloy joints. The fracture path was identified by mapping the low hardness distribution profile (LHDP) across the weld cross section under tensile loading. Optical and scanning electron microscopies were used to characterize the microstructural features of the welded joints at various zones. It is evident from the results that GTAW joints showed superior tensile properties compared to GMAW joints and this is primarily owing to the presence of finer grains in the weld metal zone (WMZ) and narrow heat-affected zone (HAZ). The lower heat input associated with the GTAW process effectively reduced the size of the WMZ and HAZ compared to GMAW process. Lower heat input of GTAW process results in faster cooling rate which hinders the grain growth and reduces the evaporation of magnesium in weld metal compared to GMAW joints. The fracture surface of GTAW joint consists of more dimples than GMAW joints which is an indication that the GTAW joint possess improved ductility than GMAW joint.

SEIHCRD Model for COVID-19 Spread Scenarios,Disease Predictions and Estimates the Basic Reproduction Number,Case Fatality Rate,Hospital,and ICU Beds Requirement

We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and results.We have studiedCOVID-19 cases of six countries,where the impact of this disease in the highest are Brazil,India,Italy,Spain,the United Kingdom,and the United States.After estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic evolution.Themodel calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category scenario.Themodel calculates two types of Case fatality rate one is CFR daily,and the other is total CFR.The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection.The SEIHCRD model outperforms the classic ARXmodel and the ARIMA model.RMSE,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target diagrams.The result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.

A New Design Approach for Nearly Linear Phase Stable IIR Filter using Fractional Derivative

In this paper,a new design method for digital infinite impulse response(IIR)filters with nearly linear-phase response is presented using fractional derivative constraints(FDCs).In the proposed method,design problem of an IIR frlter is constructed as the minimization of phase error between the desired and designed phase response of an allpass filter(APF)such that the designed lowpass filter(LPF)or highpass frlter(HPF)yields less passband(ep),and stopband errors(es)with optimal stopband attenuation(As).In order to have accurate passband(pb)response,FDCs are imposed on appropriate reference frequency,where the optimality of these FDCs are ensured by using a new greedy based sorting mechanism.The simulated results reflect the efficiency of the proposed method in term of improved passband response along with better transition width.However,small reduction in^is observed within the allowable limit,when compared to noin-fractional design approach,but the designed filter remains immune to wordlength(WL)effect.

Study of Non-Pharmacological Interventions on COVID-19 Spread

COVID-19 disease has emerged as one of the life threatening threat to the society.A novel beta coronavirus causes it.It began as unidentified pneumonia of unknown etiology in Wuhan City,Hubei province in China emerged in December 2019.No vaccine has been produced till now.Mathematical models are used to study the impact of different measures used to decrease pandemic.Mathematical models have been designed to estimate the numbers of spreaders in different scenarios in the present manuscript.In the present manuscript,three different mathematical models have been proposed with different scenarios,such as screening,quarantine,andNPIs,to estimate the number of virus spreaders.The analysis shows that the numbers of COVID-19 patients will be more without screening the peoples coming from other countries.Since every people suffering fromCOVID-19 disease are spreaders.The screening and quarantine with NPIs have been implemented to study their impact on the spreaders.It has been found that NPI measures can reduce the number of spreaders.The NPI measures reduce the spread function’s growth and provide decision makers more time to prepare with in dealing with the disease.

ZnO/CeO_(2)/carbon xerogel composites with direct Z-scheme heterojunctions:Enhancing photocatalytic remediation of 4-chlorophenol under visible light

This paper aims to create visible light driven ternary photocatalysts using zinc oxide(ZnO),cerium(IV)oxide(CeO_(2)),and carbon xerogel(CX) as constituent materials.The use of CeO_(2) is based on the creation of direct-Z-scheme heterojunctions with the ZnO and the consequent diminishing of charge recombination,whereas the carbon xerogel inclusion is predicted to minimize bandgap energy,decrease electro n-hole reco mbination,and boost specific surface area.Furthermo re,the choice of the black-wattle tannin as a carbonaceous precursor was targeted at the development of an environmentally friendly and affordable composite.The existence of the hexagonal phase of zinc oxide and cubic structure of the cerium(IV) oxide in the ternary material was confirmed by X-ray diffractometry and X-ray photoelectron spectroscopy,with the latter also suggesting chemical bonding between the ZnO and the CX due to the creation of zinc oxycarbide complexes.The inclusion of the carbon xerogel provokes a significant modification in the morphology of the ternary material,resulting in an increased surface area and smaller particle aggregates.The CX/ZnO-CeO_(2) ternary composite obtains the highest photocatalytic efficiency among all the materials studied,degrading 100% of 4-chlorophenol under simulated sunlight and 68% under visible radiation,after 5 h.The increased photocatalytic activity can be attributed to the formation of direct Z-scheme heterojunctions between the semiconductors,higher visible light response,and higher specific surface area,as evidenced by the results obtained by active radical scavenging,chronoamperometry,diffuse reflectance spectroscopy,and N_(2) adsorption-desorption isotherms.

深冷异步轧制制备高力学性能CrCoNi中熵合金

为了获得具有更好强塑性平衡的CrCoNi中熵合金,采用冷轧、异步轧制、深冷轧制和深冷异步轧制4种工艺对中熵合金CrCoNi进行加工,并对合金进行不同温度的退火处理。研究结果表明:深冷异步轧制的合金获得超过1.6 GPa的高强度,当经过1073 K的退火处理后,在具有接近60%的伸长率的同时,仍然保留接近1 GPa的强度。采用深冷异步轧制和退火后,得到较室温异步轧制更为明显的异质特征,这使材料具有更高的强度与更好的塑性。

A Context Sensitive Multilevel Thresholding Using Swarm Based Algorithms

In this paper, a comprehensive energy function is used to formulate the three most popular objective functions:Kapur's, Otsu and Tsalli's functions for performing effective multilevel color image thresholding. These new energy based objective criterions are further combined with the proficient search capability of swarm based algorithms to improve the efficiency and robustness. The proposed multilevel thresholding approach accurately determines the optimal threshold values by using generated energy curve, and acutely distinguishes different objects within the multi-channel complex images. The performance evaluation indices and experiments on different test images illustrate that Kapur's entropy aided with differential evolution and bacterial foraging optimization algorithm generates the most accurate and visually pleasing segmented images.

Experimental Evaluation of Certain Pursuit and Evasion Schemes for Wheeled Mobile Robots

Pursuit-evasion games involving mobile robots provide an excellent platform to analyze the performance of pursuit and evasion strategies. Pursuit-evasion has received considerable attention from researchers in the past few decades due to its application to a broad spectrum of problems that arise in various domains such as defense research, robotics, computer games, drug delivery, cell biology, etc. Several methods have been introduced in the literature to compute the winning chances of a single pursuer or single evader in a two-player game. Over the past few decades, proportional navigation guidance (PNG) based methods have proved to be quite effective for the purpose of pursuit especially for missile navigation and target tracking. However, a performance comparison of these pursuer-centric strategies against recent evader-centric schemes has not been found in the literature, for wheeled mobile robot applications. With a view to understanding the performance of each of the evasion strategies against various pursuit strategies and vice versa, four different proportional navigation-based pursuit schemes have been evaluated against five evader-centric schemes and vice-versa for non-holonomic wheeled mobile robots. The pursuer′s strategies include three well-known schemes namely, augmented ideal proportional navigation guidance (AIPNG), modified AIPNG, angular acceleration guidance (AAG), and a recently introduced pursuer-centric scheme called anticipated trajectory-based proportional navigation guidance (ATPNG). Evader-centric schemes are classic evasion, random motion, optical-flow based evasion, Apollonius circle based evasion and another recently introduced evasion strategy called anticipated velocity based evasion. The performance of each of the pursuit methods was evaluated against five different evasion methods through hardware implementation. The performance was analyzed in terms of time of interception and the distance traveled by players. The working environment was obstacle-free and the maximum velocity of the pursuer was taken to be greater than that of the evader to conclude the game in finite time. It is concluded that ATPNG performs better than other PNG-based schemes, and the anticipated velocity based evasion scheme performs better than the other evasion schemes.

Ni_(3)B modified BiVO_(4) photoanodes for enhanced photoelectrochemical water splitting:The key role of Ni_(3)B on reducing the water oxidation barrier

Bismuth vanadate(BiVO_(4),BVO)as a promising photoelectrode has been received great attention for photoelectrochemical(PEC)water splitting.However,the slow oxidation kinetics on the surface of BiVO_(4)limited the PEC water splitting efficiency.Herein,nickel boride(Ni_(3)B,NB)nanoparticles,generally used in electrocatalytic field material,were modified on the surface of BiVO_(4)photoelectrode as an efficient cocatalyst to accelerate the oxygen evolution reaction.The as-prepared BVO-NB-5P photoelectrode exhibits a remarkable photocurrent density of 1.47 mA·cm^(−2)at 1.23 V versus the reversible hydrogen electrode(RHE)under air mass(AM)1.5 G illumination,which is about 2.8 times higher than the bare BiVO_(4)photoelectrode,and its water splitting rate is 11.3 times higher than bare BiVO_(4).The PEC studies reveal that the spin coated Ni_(3)B crystal cocatalyst could effectively reduce the water oxidation barrier,and improve the surface charge injection efficiency to 94%,which could boost the photogenerated holes reaction to enhance the PEC performance of BiVO_(4)photoelectrode.

Active Learning Query Strategies for Classification,Regression,and Clustering:A Survey

Generally,data is available abundantly in unlabeled form,and its annotation requires some cost.The labeling,as well as learning cost,can be minimized by learning with the minimum labeled data instances.Active learning(AL),learns from a few labeled data instances with the additional facility of querying the labels of instances from an expert annotator or oracle.The active learner uses an instance selection strategy for selecting those critical query instances,which reduce the generalization error as fast as possible.This process results in a refined training dataset,which helps in minimizing the overall cost.The key to the success of AL is query strategies that select the candidate query instances and help the learner in learning a valid hypothesis.This survey reviews AL query strategies for classification,regression,and clustering under the pool-based AL scenario.The query strategies under classification are further divided into:informative-based,representative-based,informative-and representative-based,and others.Also,more advanced query strategies based on reinforcement learning and deep learning,along with query strategies under the realistic environment setting,are presented.After a rigorous mathematical analysis of AL strategies,this work presents a comparative analysis of these strategies.Finally,implementation guide,applications,and challenges of AL are discussed.

High Order Stable Infinite Impulse Response Filter Design Using Cuckoo Search Algorithm

In this paper, an efficient technique for optimal design of digital infinite impulse response （IIR） filter with minimum passband error （ep）, minimum stopband error （es）, high stopband attenuation （As）, and also free from limit cycle effect is proposed using cuckoo search （CS） algorithm. In the proposed method, error function, which is multi-model and non-differentiable in the heuristic surface, is constructed as the mean squared difference between the designed and desired response in frequency domain, and is optimized using CS algorithm. Computational efficiency of the proposed technique for exploration in search space is examined, and during exploration, stability of filter is maintained by considering lattice representation of the denominator polynomials, which requires less computational complexity as well as it improves the exploration ability in search space for designing higher filter taps. A comparative study of the proposed method with other algorithms is made, and the obtained results show that 90% reduction in errors is achieved using the proposed method. However, computational complexity in term of CPU time is increased as compared to other existing algorithms.

Route Towards Road Freight Electrification in India:Examining Battery Electric Truck Powertrain and Energy Consumption

Medium-duty/heavy-duty trucks(MD/HDTs)are yet to be included in India’s electric mobility plans.With the improvement of electric vehicle(EV)technologies,there is a growing interest in battery-electric trucks(BETs)from original equipment manufacturers(OEMs).The time is opportune to consider electrification as a future direction for road freight in India.Accordingly,this article presents the results of an energy consumption simulation study of a BET under Indian conditions.This study specifically considered an MDBET over a domestic drive cycle.These energy consumption figures can facilitate future studies that analyze the technical and practical feasibility of BETs in the country.In addition,the article provides the requisite groundwork for BET modeling for a simulation study by reviewing available EV powertrain systems and components.Appropriate powertrain considerations are thereby obtained for a typical medium-duty/heavy-duty battery-electric truck(MD/HDBET)in the Indian context.

Convective heat transfer of nanofluids with correlations

To investigate the convective heat transfer of nanofluids, experiments were performed using silver-water nanofluids under laminar, transition and turbulent flow regimes in a horizontal 4.3 mm inner-diameter tube-in-tube counter-current heat transfer test section. The volume concentration of the nanoparticles varied from 0.3% to 0.9% in steps of 0.3%, and the effects of thermo-physical properties, inlet temperature, volume concentration, and mass flow rate on heat transfer coefficient were investigated. Experiments showed that the suspended nanoparticles remarkably increased the convective heat transfer coefficient, by as much as 28.7% and 69.3% for 0.3% and 0.9% of silver content, respectively. Based on the experimental results a correlation was developed to predict the Nusselt number of the silver-water nanofluid, with ＋10% agreement between experiments and prediction.

An Advanced Analysis System for Identifying Alcoholic Brain State Through EEG Signals

This paper addresses an advanced analysis system for the identification of alcoholic brain states from electroencephalogram(EEG) data in an automatic way. This study introduces an optimum allocation based sampling(OAS) scheme to discover the most favourable representative data points from every single time-window of each EEG signal considering the minimal variability of the observations. Combining all representative samples of each time-window in a set, some statistical features are extracted from every set of each class. The Mann-Whitney U test is used to assess whether each of the features is significant between the two classes(e.g., alcoholic and control). In order to evaluate the effectiveness of the OAS-based features, four well-known machine learning methods(decision table,support vector machine(SVM), k-nearest neighbor(k-NN) and logistic regression) are considered for identification of alcoholic brain state. The experimental results on the UCI KDD(i.e., UCI knowledge discovery in databases) database demonstrate that the OAS based decision table algorithm yields the highest accuracy of 99.58% with a low false alarm rate 0.40%, which is an improvement of up to9.58% over the existing algorithms. A proposed analysis system can be used to detect alcoholism and also to determine the level of alcoholism-related changes in EEG signals.

A New Stable Algorithm to Compute Hankel Transform Using Chebyshev Wavelets

A new stable numerical method,based on Chebyshev wavelets for numerical evaluation of Hankel transform,is proposed in this paper.The Chebyshev wavelets are used as a basis to expand a part of the integrand,r f(r),appearing in the Hankel transform integral.This transforms the Hankel transform integral into a Fourier-Bessel series.By truncating the series,an efficient and stable algorithm is obtained for the numerical evaluations of the Hankel transforms of order ν>−1.The method is quite accurate and stable,as illustrated by given numerical examples with varying degree of random noise terms εθ_(i) added to the data function f(r),where θ_(i) is a uniform random variable with values in[−1,1].Finally,an application of the proposed method is given for solving the heat equation in an infinite cylinder with a radiation condition.