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Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algor

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Computers, Materials & Continua 2024年第4期79卷 1727-1755页

作者： Parth khandelwal Harshit Indranil Manna Metallurgical&Materials Engineering Department Indian Institute of TechnologyKharagpurWest Bengal721302India Computer Science&Engineering Department Indian Institute of TechnologyKharagpurWest Bengal721302India Vice Chancellor Office Birla Institute of Technology(BIT)MesraRanchiJharkhand835215India

Metallic alloys for a given application are usually designed to achieve the desired properties by devising experimentsbased on experience, thermodynamic and kinetic principles, and various modeling and simulation ***, the influence of process parameters and material properties is often non-linear and non-colligative. Inrecent years, machine learning (ML) has emerged as a promising tool to dealwith the complex interrelation betweencomposition, properties, and process parameters to facilitate accelerated discovery and development of new alloysand functionalities. In this study, we adopt an ML-based approach, coupled with genetic algorithm (GA) principles,to design novel copper alloys for achieving seemingly contradictory targets of high strength and high electricalconductivity. Initially, we establish a correlation between the alloy composition (binary to multi-component) andthe target properties, namely, electrical conductivity and mechanical strength. Catboost, an ML model coupledwith GA, was used for this task. The accuracy of the model was above 93.5%. Next, for obtaining the optimizedcompositions the outputs fromthe initial model were refined by combining the concepts of data augmentation andPareto front. Finally, the ultimate objective of predicting the target composition that would deliver the desired rangeof properties was achieved by developing an advancedMLmodel through data segregation and data *** examine the reliability of this model, results were rigorously compared and verified using several independentdata reported in the literature. This comparison substantiates that the results predicted by our model regarding thevariation of conductivity and evolution ofmicrostructure and mechanical properties with composition are in goodagreement with the reports published in the literature.

关键词： Machine learning genetic algorithm solid-solution precipitation strengthening pareto front data augmentation

Prediction of rock fragmentation in a fiery seam of an open-pit coal mine in India

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第8期16卷 2879-2893页

作者： Mukul Sharma Bhanwar Singh Choudhary Autar K.Raina Manoj khandelwal Saurav Rukhiyar Department of Mining Engineering Indian Institute of Technology(ISM)Dhanbad826004India CSIR-Central Institute of Mining and Fuel Research Nagpur Research Center(Mining Technology)Nagpur440006India Institute of Innovation Science and SustainabilityFederation University AustraliaBallaratVIC3350Australia

Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading *** condition,known as hot-hole blasting,is dangerous due to the increased possibility of premature explosions in loaded ***,it is crucial to load the blastholes with an appropriate amount of explosives within a short period to avoid premature detonation caused by high temperatures of ***,it will help achieve the desired fragment *** study tried to ascertain the most influencial variables of mean fragment size and their optimum values adopted for blasting in a fiery *** on blast design,rock mass,and fragmentation of 100 blasts in fiery seams of a coal mine were collected and used to develop mean fragmentation prediction models using soft computational *** coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute error(MAE),mean square error(MSE),variance account for(VAF)and coefficient of efficiency in percentage(CE)were calculated to validate the *** indicates that the random forest algorithm(RFA)outperforms the artificial neural network(ANN),response surface method(RSM),and decision tree(DT).The values of R^(2),RMSE,MAE,MSE,VAF,and CE for RFA are 0.94,0.034,0.027,0.001,93.58,and 93.01,*** parametric sensitivity analyses(MPSAs)of the input variables showed that the Schmidt hammer rebound number and spacing-to-burden ratio are the most influencial variables for the blast fragment *** analysis was finally used to define the best blast design variables to achieve optimum fragment size from *** optimum factor values for RFA of S/B,ld/B and ls/ld are 1.03,1.85 and 0.7,respectively.

关键词： Fiery seam Rock fragmentation Response Surface Method(RSM) Artificial Neural Network(ANN) Random Forest Algorithm(RFA) Multiple Parametric Sensitivity Analysis (MPSA)

Time and Space Efficient Multi-Model Convolution Vision Transformer for Tomato Disease Detection from Leaf Images with Varied Backgrounds

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Computers, Materials & Continua 2024年第4期79卷 117-142页

作者： Ankita Gangwar Vijaypal Singh Dhaka Geeta Rani Shrey khandelwal Ester Zumpano Eugenio Vocaturo Department of Computer and Communication Engineering Manipal University JaipurJaipurIndia Department of IoT and Intelligent Systems Manipal University JaipurJaipurIndia Department of Computer Engineering ModellingElectronics and Systems(DIMES)University of CalabriaRende(Cosenza)Italy National Research Council Institute of Nanotechnology(NANOTEC)Rende(Cosenza)Italy

A consumption of 46.9 million tons of processed tomatoes was reported in 2022 which is merely 20%of the total *** increase of 3.3%in consumption is predicted from 2024 to *** are also rich in iron,potassium,antioxidant lycopene,vitamins A,C and K which are important for preventing cancer,and maintaining blood pressure and glucose ***,tomatoes are globally important due to their widespread usage and nutritional *** face the high demand for tomatoes,it is mandatory to investigate the causes of crop loss and minimize *** are one of the major causes that adversely affect crop yield and degrade the quality of the tomato *** leads to financial losses and affects the livelihood of ***,automatic disease detection at any stage of the tomato plant is a critical *** learning models introduced in the literature show promising results,but the models are difficult to implement on handheld devices such as mobile phones due to high computational costs and a large number of ***,most of the models proposed so far work efficiently for images with plain backgrounds where a clear demarcation exists between the background and leaf ***,the existing techniques lack in recognizing multiple diseases on the same *** address these concerns,we introduce a customized deep learning-based convolution vision transformer *** achieves an accuracy of 93.51%for classifying tomato leaf images with plain as well as complex backgrounds into 13 *** requires a space storage of merely 5.8 MB which is 98.93%,98.33%,and 92.64%less than stateof-the-art visual geometry group,vision transformers,and convolution vision transformermodels,*** training time of 44 min is 51.12%,74.12%,and 57.7%lower than the above-mentioned ***,it can be deployed on(Internet of Things)IoT-enabled devices,drones,or mobile devices to assist farmers in the real-time monitoring of tomato *** p

关键词： Tomato disease transformer deep learning mobile devices

Applications of Soft Computing Methods in Backbreak Assessment in Surface Mines: A Comprehensive Review

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2207-2238页

作者： Mojtaba Yari Manoj khandelwal Payam Abbasi Evangelos I.Koutras Danial Jahed Armaghani Panagiotis G.Asteris Department of Mining Engineering Faculty of EngineeringMalayer UniversityMalayer***Iran Institute of Innovation Science and SustainabilityFederation University AustraliaBallaratVIC 3350Australia Marane Olia Ornamental Stone Mine Sanandaj***Iran Computational Mechanics Laboratory School of Pedagogical and Technological EducationAthens15122Greece School of Civil and Environmental Engineering University of Technology SydneySydneyNSW 2007Australia

Geo-engineering problems are known for their complexity and high uncertainty levels,requiring precise defini-tions,past experiences,logical reasoning,mathematical analysis,and practical insight to address them *** Computing(SC)methods have gained popularity in engineering disciplines such as mining and civil engineering due to computer hardware and machine learning *** traditional hard computing approaches,SC models use soft values and fuzzy sets to navigate uncertain *** study focuses on the application of SC methods to predict backbreak,a common issue in blasting operations within mining and civil ***,which refers to the unintended fracturing of rock beyond the desired blast perimeter,can significantly impact project timelines and *** study aims to explore how SC methods can be effectively employed to anticipate and mitigate the undesirable consequences of blasting operations,specifically focusing on backbreak *** research explores the complexities of backbreak prediction and highlights the potential benefits of utilizing SC methods to address this challenging issue in geo-engineering projects.

关键词： Backbreak blasting soft computing methods prediction theory-guided machine learning

Evaluating the Efficacy of Cervical Tactile Ultrasound Technique as a Predictive Tool for Spontaneous Preterm Birth

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Open Journal of Obstetrics and Gynecology 2024年第5期14卷 832-846页

作者： Vladimir Egorov Todd Rosen Jennifer Hill Meena khandelwal Victors Kurtenoks Brendan Francy Noune Sarvazyan Advanced Tactile Imaging Inc. Ewing New Jersey USA Department of Obstetrics Gynecology and Reproductive Sciences Rutgers Robert Wood Johnson Medical School New Brunswick New Jersey USA Department of Maternal-Fetal Medicine Cooper Medical School of Rowan University Camden New Jersey USA

Background: Premature cervical softening and shortening may be considered an early mechanical failure that predispose to preterm birth. Purpose: This study aims to explore the applicability of an innovative cervical tactile ultrasound approach for predicting spontaneous preterm birth (sPTB). Materials and Methods: Eligible participants were women with low-risk singleton pregnancies in their second trimester, enrolled in this prospective observational study. A Cervix Monitor (CM) device was designed with a vaginal probe comprising four tactile sensors and a single ultrasound transducer operating at 5 MHz. The probe enabled the application of controllable pressure to the external cervical surface, facilitating the acquisition of stress-strain data from both anterior and posterior cervical sectors. Gestational age at delivery was recorded and compared against cervical elasticity. Results: CM examination data were analyzed for 127 women at 240/7 - 286/7 gestational weeks. sPTB was observed in 6.3% of the cases. The preterm group exhibited a lower average cervical stress-to-strain ratio (elasticity) of 0.70 ± 0.26 kPa/mm compared to the term group’s 1.63 ± 0.65 kPa/mm with a p-value of 1.1 × 10−4. Diagnostic accuracy for predicting spontaneous preterm birth based solely on cervical elasticity data was found to be 95.0% (95% CI, 88.5 - 100.0). Conclusion: These findings suggest that measuring cervical elasticity with the designed tactile ultrasound probe has the potential to predict spontaneous preterm birth in a cost-effective manner.

关键词： Cervical Elasticity Spontaneous Preterm Birth Tactile Ultrasound Probe

High-frequency supercapacitors with phosphorus-doped Ketjen black

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Journal of Energy Chemistry 2023年第7期82卷 464-474,I0010页

作者： Qing Jin Mahima khandelwal Woong Kim Department of Materials Science and Engineering Korea UniversitySeoul 02841Republic of Korea

Compact supercapacitors(SCs)have attracted attention for their great potential to replace bulky aluminum electrolytic capacitors(AECs)in alternating current(AC)line filtering ***,the fabrication of a high-frequency SC is reported using Ketjen black(KB)nanoparticles doped with phosphorus(P)to achieve a high areal capacitance of up to 2.26 mF cm^(-2)along with a high-rate capability,with a phase angle of-80.2°at 120 *** high performance of the phosphorus-doped KB(designated PKB)SC with a 6 M KOH aqueous electrolyte is associated with its increased surface wettability and additional capacitive sites provided by the *** functional theory(DFT)calculations further indicate that the P-doping enhances the interactions between the electrolyte ions and the carbon surface,thus leading to an improved electrochemical *** results suggest that the P-doped carbonbased SC could be highly favored in replacing conventional AECs in various high-frequency electronic devices.

关键词： Phosphorus doping Frequency response Wettability Supercapacitor AC line filtering DFT calculation

Removal and recovery of toxic nanosized Cerium Oxide using eco-friendly Iron Oxide Nanoparticles

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Frontiers of Environmental Science & Engineering 2020年第1期14卷 175-184页

作者： Kanha Gupta Nitin khandelwal Gopala Krishna Darbha Department of Chemical Sciences USER KolkataMohanpurWest BengalPincode 741246India Environmental Nanoscience Laboratory Department of Earth SciencesUSER KolkataMohanpurWest BengalPincode 741246India Center for Climate&Environmental Studies USER KolkataMohanpurWest BengalPincode 741246India

Increasing applications of metal oxide nanoparticles and their release in the natural environment is a serious concern due to their toxic ***,it is essential to have eco-friendly solutions for the remediation of toxic metal oxides in an aqueous *** the present study,eco-friendly Iron Oxide Nanoparticles(IONPs)are synthesized using solvothermal technique and successfully characterized using scanning and transmission electron microscopy(SEM and TEM respectively)and powder X-Ray diffraction(PXRD).These IONPs were further utilized for the remediation of toxic metal oxide nanoparticle,i.e.,*** experiments were also performed in complex aqueous solutions and real water samples to check its applicability in the natural *** study was performed to show *** show that these 200 nm-sized spherical IONPs,as revealed by SEM and TEM analysis,were magnetite(Fe3O4)and contained short-range crystallinity as confirmed from XRD *** experiments show that the composite follows the pseudosecond-order kinetic *** k>0.99 for Langmuir sorption isotherm suggests chemisorption as probable removal mechanism with monolayer sorption of Ce02 NPs on *** than 80%recovery of adsorbed Ce02 NPs through ultrasonication and magnetic separation of reaction precipitate confirms reusability of *** removal%of Ce02 in various synthetic and real water samples was>90%signifying that IONPs are candidate adsorbent for the removal and recovery of toxic metal oxide nanoparticles from contaminated environmental water samples.

关键词： Adsorption toxic metal oxide remediation eco-friendly IONP Iron oxide CeO2 removal

Proposing a novel comprehensive evaluation model for the coal burst liability in underground coal mines considering uncertainty factors

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International Journal of Mining Science and Technology 2021年第5期31卷 799-812页

作者： Jian Zhou Chao Chen Mingzheng Wang Manoj khandelwal School of Resources and Safety Engineering Central South UniversityChangsha 410083China Bharti School of Engineering Laurentian UniversitySudburyOntarioCanada School of Engineering Information Technology and Physical SciencesFederation University AustraliaBallaratAustralia

Coal burst is a severe hazard that can result in fatalities and damage of facilities in underground coal *** address this issue,a robust unascertained combination model is proposed to study the coal burst hazard based on an updated *** assessment indexes are used in the model,which are the dynamic failure duration(DT),elastic energy index(WET),impact energy index(KE)and uniaxial compressive strength(RC).Four membership functions,including linear(L),parabolic(P),S and Weibull(W)functions,are proposed to measure the uncertainty level of individual *** corresponding weights are determined through information entropy(EN),analysis hierarchy process(AHP)and synthetic weights(CW).Simultaneously,the classification criteria,including unascertained cluster(UC)and credible identification principle(CIP),are *** combination algorithm,consisting of P function,CW and CIP(P-CW-CIP),is selected as the optimal classification model in function of theory analysis and to train the ***,the established ensemble model is further validated through test samples with 100%*** results reveal that the hybrid model has a great potential in the coal burst hazard evaluation in underground coal mines.

关键词： Coal burst liability(CBL) Unascertained measurement(UM) Analysis hierarchy process Information entropy Synthetic weights Comprehensive evaluation

Recent Developments in Integrated Solar Combined Cycle Power Plants

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Journal of Thermal Science 2020年第2期29卷 298-322页

作者： khandelwal Neelam SHARMA Meeta SINGH Onkar SHUKLA Anoop Kumar Mechanical Engineering Department Amity University Uttar PradeshNoida(U.P.)201313India Mechanical Engineering Department Harcourt Butler Technical UniversityKanpur(U.P.)208002India

Global concern for depleting fossil fuel reserves have been compelling for evolving power generation options using renewable energy sources. The solar energy happens to be a potential source for running the power plants among renewable energy sources. Integrated Solar Combined Cycle(ISCC) power plants have gained popularity among the thermal power plants. Traditional ISCC power plants use Direct Steam Generation(DSG) approach. However, with the DSG method, the ISCC plant’s overall thermal efficiency does not increase significantly due to variations in the availability of solar energy. Thermal Energy Storage(TES) systems when integrated into the solar cycle can address such issues related to energy efficiency, process flexibility, reducing intermittency during non-solar hours. This review work focuses and discusses the developments in various components of the ISCC system including its major cycles and related parameters. The main focus is on CSP technologies, Heat Transfer Fluid(HTF), and Phase Change Material(PCM) used for thermal energy storage. Further, study includes heat enhancement methods with HTF and latent heat storage system. This study will be beneficial to the power plant professionals intending to modify the solar-based Combined Cycle Power Plant(CCPP) and to retrofit the existing Natural Gas Combined Cycle(NGCC) plant with the advanced solar cycle.

关键词： CSP(Concentrated Solar Power) HTF(Heat Transfer Fluid) ISCC(Integrated Solar Combined Cycle) TES(Thermal Energy Storage) PCM(Phase Change Material)