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Magnetic properties of gadolinium and/or dysprosium substituted Sm-Co nanocomposite ribbons

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Journal of Rare Earths 2024年第6期42卷 1093-1100,I0004页

作者： Akila Raja Shampa Aich Department of Metallurgical A Materials EngineeringIndian Institute of Technology(iit) Kharagpur721302India

The present study reported the influence of heavy rare-earth elements(Gd and/or Dy)on Sm-Co-based melt-spun *** and magnetic properties of Sm-Co-based(Sm_(1-x)RE_(x)Co_(5))ternary and quaternary systems were *** X-ray diffraction,Auger spectroscopy,scanning electron microscopy(SEM)and transmission electron microscopy(TEM)analyses reveal the presence of the 1:5H and 2:17R phases in the as-spun ribbons.A high-temperature magnetic measurement reports a Curie temperature(Tc)at~825 and~869 K in Sm0.6Gd0.4Co5(ribbon A)and Sm_(0.6)Gd_(0.3)Dy_(0.1)Co_(5)(ribbon B),respectively.A low-temperature magnetic measurement on Sm0.6Gd0.3Dy0.1Co5 ribbons exhibits a type-2 SR(spin reorientation)behaviour at~72 K,which arises due to the presence of the DyCo5 *** temperature magnetic measurements reveal that overall magnetic measurement(OMP)is about 24 and 29.9 for ribbons A and B,***,the comparative investigations profess that ribbon B shows better magnetic performance due to Dy addition with reduced grain *** observation indicates that the Gd and Dy substituted Sm-Co magnet can be a potential magnet for high-temperature applications.

关键词： Permanent magnets Melt-spinning Heavy rare-earth Curie temperature Rare earths

Circum-Indian Holocene sea-level database:A repository of distinct relative sea-level plots across the Indian Peninsula

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Journal of Palaeogeography 2024年第1期13卷 1-17页

作者： Shradha Menon Pankaj Khanna Santanu Banerjee REEFS Lab Department of Earth SciencesIIT GandhinagarPalajGandhinagarGujarat382355India Department of Earth Sciences IIT BombayPowaiMumbai400076India

The Indian Peninsula is one of the most well-studied regions for Holocene sea-level fluctuations in the world, however, standardized relative sea-level datasets are missing. This study provides an archive of sealevel indicators(n = 162, 20 locations) along the western and the eastern sides of the peninsula, that have been used to develop Relative Sea Level(RSL) plots. Each dated sea-level indicator is recalibrated for its elevation based on tidal and tectonic correction, as well as age with reservoir correction, and have been separated into six zones based on coastal geomorphology and number of datasets. The database spans throughout the Holocene and covers sea-level depth/elevations from-45 m to +5 m from mean sea-level(MSL). Approximately 90 % of the dataset range from 8 ka to the present day. The first transgression is highly variable and identified between 8.5-8 ka BP in Gujarat(Zone 1), ~ 5.5 ka BP in Maharashtra(Zone 2), between 8 and 7 ka BP in Tamil Nadu(Zone 4) and between 8 and 7.5 ka BP in the Bengal coasts(Zone 6). No transgression above present sea-level is observed along Andhra Pradesh(Zone 5)(no data for Kerala-Zone 3).Further, Zones 1, 2, 4 and 6 show a strong uplift component(tectonic), whereas Zone 5 exhibits subsidence during the Holocene(Zone 3-insufficient data). Based on these findings, and given the region's coastal topography and tidal components, Zones 6 and 1 will likely undergo the largest coastal inundation, followed by Zones 5, 4, 2, and 3. These insights are critical in planning future coastal inundation measures across the Indian Peninsula.

关键词： Indian ocean Terraces Relative sea level curve Holocene Arabian sea Bay of Bengal

Multi-head neural networks for simulating particle breakage dynamics

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Theoretical & Applied Mechanics Letters 2024年第2期14卷 130-141页

作者： Abhishek Gupta Barada Kanta Mishra School of Mechanical Sciences Indian Institute of Technology(IIT)GoaPonda 403401India School of Chemical and Materials Science Indian Institute of Technology(IIT)GoaPonda 403401India

The breakage of brittle particulate materials into smaller particles under compressive or impact loads can be modelled as an instantiation of the population balance integro-differential *** this paper,the emerging computational science paradigm of physics-informed neural networks is studied for the first time for solving both linear and nonlinear variants of the governing *** conventional methods,the proposed neural network provides rapid simulations of arbitrarily high resolution in particle size,predicting values on arbitrarily fine grids without the need for model *** network is assigned a simple multi-head architecture tailored to uphold monotonicity of the modelled cumulative distribution function over particle *** method is theoretically analyzed and validated against analytical results before being applied to real-world data of a batch grinding *** agreement between laboratory data and numerical simulation encourages the use of physics-informed neural nets for optimal planning and control of industrial comminution processes.

关键词： Particle breakage dynamics Population balance equation Physics-informed neural networks

An improved reverse time migration for subsurface imaging over complex geological structures:A numerical study

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Energy Geoscience

Energy Geoscience 2024年第2期5卷 290-297页

作者： Alok Kumar Routa Priya Ranjan Monahty Department of Applied Geophysics IIT(ISM)DhanbadJharkhandIndia

In seismic exploration,it is a critical task to image and interpret different seismic signatures over complex geology due to strong lateral velocity contrast,steep reflectors,overburden strata and dipping *** understand the behavior of these seismic signatures,nowadays Reverse Time Migration(RTM)technique is used extensively by the oil&gas *** the extrapolation phase of RTM,the source wavefield needs to be saved,which needs high storage memory and large computing *** two are the main obstacles of RTM for production *** order to overcome these disadvantages,in this study,a second-generation improved RTM technique is *** this improved form,a shift operator is introduced at the time of imaging condition of RTM algorithm which is performed automatically both in space and time *** effort is made to produce a better-quality image by minimizing the computational time as well as numerical *** proposed method is applied over various benchmark models and validated by implementing over one field data set from the Jaisalmer Basin,*** the analysis,it is observed that the method consumes a minimum of 45%less storage space and reduce the execution time by 20%,as compared to conventional *** proposed RTM is found to work efficiently in comparison to the conventional RTM both in terms of imaging quality and minimization of numerical artefacts for all the benchmark models as well as field data.

关键词： Imaging condition Reverse time migration(RTM) Seismic imaging Velocity-depth model Wave propagation

A Bayesian multi-model inference methodology for imprecise momentindependent global sensitivity analysis of rock structures

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第3期16卷 840-859页

作者： Akshay Kumar Gaurav Tiwari Department of Civil Engineering Indian Institute of Technology(IIT)KanpurKanpur208016India

Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(*** of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model *** paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GSA methodology(BMMI-GSA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input *** methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input *** estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo’s indices by employing a reweighting approach on candidate probabilistic *** proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of *** proposed methodology was superior to the conventional GSA(neglects all epistemic uncertainties)and Bayesian coupled GSA(B-GSA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of *** Borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection *** performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample *** accurate importance ranking of properties was only possible via samples of large ***,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.

关键词： Bayesian inference Multi-model inference Statistical uncertainty Global sensitivity analysis(GSA) Borgonovo’s indices Limited data

Analysis and Optimization of Operational and Pollutant Attributes of Diesel Engine with CNT-Infused Orange Peel Biodiesel-Diesel Blend Fuel

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Journal of Thermal Science 2024年第2期33卷 761-778页

作者： Ranjeet RAI R.R.SAHOO Mechanical Engineering Department GLA UniversityMathura281406India Mechanical Engineering Department IIT(BHU)Varanasi221005India

The current study is performed to find sustainable solutions for the future of transportation and environmental *** conventional methods and experimental design table(L16 Orthogonal Array)techniques have been employed to examine and optimize a diesel-powered engine's operational and pollutant *** L16 Orthogonal Array is obtained through Taguchi's experimental design approach using Minitab 16 *** experimental design incorporated three control variables,namely engine speed,fuel type,and engine load,each with four *** operational parameters,namely brake thermal efficiency(BTE)and brake specific fuel consumption(BSFC),as well as the emission characteristics,including hydrocarbon(HC),carbon monoxide(CO),nitrogen oxide(NO),and smoke emissions,were acquired using the L16 orthogonal array(OA) and subsequently *** utilization of methodologies such as signal-to-noise(S/N) ratio and grey analysis was employed to determine the optimal operational state of the engine to achieve maximum performance while minimizing *** engine's ideal state of operation,in terms of BTE and BSFC,was determined to be at 75% engine load,1000 r/min engine speed,and using 10^(-4)(in vol) carbon nanotube incorporated 20% orange peel biodiesel(OPB20CNT100) blended fuel(A3-B1-C4).The study indicated that engine load significantly influenced BTE and BSFC,with 84.05% and 87.79% contribution factors,*** 25% engine load,1000 r/min,and OPB20CNT100 fuel(A1-B1-C4) CO,smoke,NO,and HC emissions were the *** load affects emissions the *** BSFC increased 3.10% and NO emissions 1.77%.BTE,CO,smoke,and HC emissions decreased by 1.9%,12.29%,47.05%,and 47.22%,respectively,at optimal operating conditions concerning diesel *** study shows that Taguchi-Grey's experimental design optimizes diesel engine operational and pollutant *** outcomes revealed that orange peel biodiesel infused with CNT can replace diesel fuel in a

关键词： Taguchi-Grey method OPB20CNT100 transesterification S/N ratio GRG HC CO and NO

A machine learning approach for the prediction of pore pressure using well log data of Hikurangi Tuaheni Zone of IODP Expedition 372,New Zealand

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Energy Geoscience

Energy Geoscience 2024年第2期5卷 225-231页

作者： Goutami Das Saumen Maiti Machine Learning and Geocomputing Laboratory Department of Applied GeophysicsIIT(ISM)Dhanbad826004JharkhandIndia

Pore pressure(PP)information plays an important role in analysing the geomechanical properties of the reservoir and hydrocarbon field *** prediction is an essential requirement to ensure safe drilling operations and it is a fundamental input for well design,and mud weight estimation for wellbore ***,the pore pressure trend prediction in complex geological provinces is challenging particularly at oceanic slope setting,where sedimentation rate is relatively high and PP can be driven by various complex *** overcome these difficulties,an advanced machine learning(ML)tool is implemented in combination with empirical *** empirical method for PP prediction is comprised of data pre-processing and model establishment ***'s method and Porosity method have been used for PP calculation of the well U1517A located at Tuaheni Landslide Complex of Hikurangi Subduction zone of IODP expedition ***-ray,sonic travel time,bulk density and sonic derived porosity are extracted from well log data for the theoretical framework *** normal compaction trend(NCT)curve analysis is used to check the optimum fitting of the low permeable zone *** statistical analysis is done using the histogram analysis and Pearson correlation coefficient matrix with PP data series to identify potential input combinations for ML-based predictive model *** dataset is prepared and divided into two parts:Training and *** PP data and well log of borehole U1517A is pre-processed to scale in between[-1,+1]to fit into the input range of the non-linear activation/transfer function of the decision tree regression *** Decision Tree Regression(DTR)algorithm is built and compared to the model performance to predict the PP and identify the overpressure zone in Hikurangi Tuaheni Zone of IODP Expedition 372.

关键词： Well log Pore pressure Machine learning(ML) IODP Hikurangi Tuaheni Zone IODP Expedition 372

Fuzzy inference system using genetic algorithm and pattern search for predicting roof fall rate in underground coal mines

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International Journal of Coal Science & Technology 2024年第1期11卷 31-41页

作者： Ayush Sahu Satish Sinha Haider Banka Department of CSE IIT(ISM)DhanbadJharkhand826004India Department of Sustainability Adani universityAhmedabadGujrat382421India

One of the most dangerous safety hazard in underground coal mines is roof falls during retreat *** falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation *** a result,a reliable roof fall prediction model is essential to tackle such *** parameters that substantially impact roof falls are ill-defined and intangible,making this an uncertain and challenging research *** National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof *** acquired for 37 mines is limited due to several restrictions,which increased the likelihood of *** logic is a technique for coping with ambiguity,incompleteness,and ***,In this paper,the fuzzy inference method is presented,which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of *** performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error,Mean-Absolute-Error,and coefficient of determination(R_(2)).Based on these criteria,the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.

关键词： Underground coal mining Roof fall Fuzzy logic Genetic algorithm

A comprehensive review of 3D cancer models for drug screening and translational research

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Cancer Innovation 2024年第1期3卷 61-78页

作者： Karthikey Sharma Sreenath Dey Rounik Karmakar Aravind Kumar Rengan Department of Biomedical Engineering Indian Institute of Technology(IIT)HyderabadIndia

The 3D cancer models fill the discovery gap of 2D cancer models and play an important role in cancer *** addition to cancer cells,a range of other factors include the stroma,density and composition of extracellular matrix,cancer-associated immune cells(e.g.,cancer-associated fibroblasts cancer cell-stroma interactions and subsequent interactions,and a number of other factors(e.g.,tumor vasculature and tumor-like microenvironment in vivo)has been widely ignored in the 2D concept of *** this knowledge,the continued use of monolayer cell culture methods has led to the failure of a series of clinical *** review discusses the immense importance of tumor microenvironment(TME)recapitulation in cancer research,prioritizing the individual roles of TME elements in cancer *** TME provided by the 3D model fulfills the requirements of in vivo spatiotemporal arrangement,components,and is helpful in analyzing various different aspects of drug sensitivity in preclinical and clinical trials,some of which are discussed ***,it discusses models for the co-assembly of different TME elements in vitro and focuses on their synergistic function and responsiveness as ***,this review broadly describes of a handful of recently developed 3D models whose main focus is limited to drug development and their screening and/or the impact of this approach in preclinical and translational research.

关键词： 3D models cancer drug development translational research tumor microenvironment elements