Effect of spheroidized microstructure on the impact toughness and electrochemical performance of a high-carbon steel

The influence of cementite spheroidization on the impact toughness and electrochemical properties of a high-carbon steel has been thoroughly investigated in this study. Heavy warm rolling, followed by 2 h of annealing, has resulted in near-complete spheroidization, leading to a microstructure consisting of nano-cementite globules dispersed in the ultrafine-grained ferritic matrix. The Charpy impact test exhibited superior impact toughness with increased spheroidization. It is validated by the presence of abundant dimples in the fractographs of spheroidized specimens, in contrast to the as-received one that experienced a brittle failure due to its lamellar pearlitic structure. Potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) carried out in a 3.5% NaCl solution revealed that the corrosion resistance of the alloy gets improved with the increase in the degree of spheroidization. This is attributed to the lower susceptibility of the spheroidized specimen to microgalvanic corrosion owing to the minimum area of contact between nano-spheroidized cementite and ferrite, as elucidated with the help of EIS results aided by equivalent electrical circuit model.     

Synthesis of AlPO4 Molecular Sieves with AFI and AEL Structures by Dry-Gel Conversion Method and Catalytic Application of Their SAPO Counterparts on Isopropylation of Biphenyl

AlPO₄-5 and AlPO₄-11 were synthesized by dry-gel conversion (DGC) method. Steam-assisted conversion (SAC) and vapor-phase transport (VPT) techniques were applied for this purpose. The synthesis was successful in presence of a certain minimum amount of external bulk water, without which the crystallization failed. Crystallization by VPT method was slower than corresponding SAC and HTS method. SAPO analogs of the samples, SAPO-5 and SAPO-11 were also synthesized by DGC method. Samples made by DGC methods had higher yield than the conventional hydrothermal synthesis (HTS); otherwise the samples showed similar characteristics as that made by HTS. XRD, SEM and N₂-adsorption results showed high crystallinity and purity of the samples made by DGC, and ²⁷Al MAS NMR spectra indicated the tetrahedral framework nature of Al. SAPO-5 and SAPO-11 were tested for their catalytic activity in isopropylation of biphenyl, and in terms of conversion and selectivity, SAPO-5 was found to be suitable for this application.     

Optimizing spatiotemporal sensors placement for nutrient monitoring: a stochastic optimization framework

Nutrient monitoring is very important for the area of food–energy–water nexus. The sensor network for nutrient monitoring requires dynamic sensing where the positions of the sensors change with time. In this work, we have proposed a methodology to optimize a dynamic sensor network which can address the spatiotemporal aspect of nutrient movement in a watershed. This is a first paper in the series where an algorithmic and methodological framework for spatiotemporal sensor placement problem is proposed. Dynamic sensing is widely used in wireless sensors, and the current approaches to solving this problem are data intensive. This is the first time we are introducing a stochastic optimization approach to dynamic sensing which is efficient. This framework is based on a novel stochastic optimization algorithm called Better Optimization of Nonlinear Uncertain Systems (BONUS). A small case study of the dynamic sensor placement problem is presented to illustrate the approach. In the second paper of this series, we will present a detailed case study of nutrient monitoring in a watershed.     

Geomorphology Based Semi-Distributed Approach for Modelling Rainfall-Runoff Process

This study presents a geomorphology based semi-distributed methodology for prediction of runoff of a catchment. In this proposed methodology, the catchment area is divided into a number of sub-catchments using the Thiessen polygon method. The rainfall records of particular rain-gauge station are considered as uniformly distributed over the entire sub-watershed. Four different weighting factors are proposed to obtain the sub-catchment’s contribution towards runoff. The weighting factors are calculated based on the geomorphological parameters of the catchment. The geomorphological parameters of the sub-watersheds are obtained from SRTM digital elevation data. The weighted contributions from all the sub-watersheds at current and previous time steps and the previous time step discharge are used to develop an Artificial Neural Network (ANN) for predicting the discharge at the basin outlet. A lump model considering average rainfall of the catchment is also developed using ANN for evaluating the performance of the proposed distributed model. For the lump model, average rainfall is calculated using Thiessen polygon method. The historic rainfall and runoff data recorded at the Dikrong basin, a sub-catchment of the river Brahmaputra is used to evaluate the efficiency of the developed methodology. The evaluation results show that the presented model is superior to the lump model and has the potential for field application. A comparative study is also carried out to obtain the most influential combination of geomorphological parameters in predicting the catchment’s runoff.     

Optimal design of unit hydrographs using probability distribution and genetic algorithms

A nonlinear optimization model is developed to transmute a unit hydrograph into a probability distribution function (PDF). The objective function is to minimize the sum of the square of the deviation between predicted and actual direct runoff hydrograph of a watershed. The predicted runoff hydrograph is estimated by using a PDF. In a unit hydrograph, the depth of rainfall excess must be unity and the ordinates must be positive. Incorporation of a PDF ensures that the depth of rainfall excess for the unit hydrograph is unity, and the ordinates are also positive. Unit hydrograph ordinates are in terms of intensity of rainfall excess on a discharge per unit catchment area basis, the unit area thus representing the unit rainfall excess. The proposed method does not have any constraint. The nonlinear optimization formulation is solved using binary-coded genetic algorithms. The number of variables to be estimated by optimization is the same as the number of probability distribution parameters; gamma and log-normal probability distributions are used. The existing nonlinear programming model for obtaining optimal unit hydrograph has also been solved using genetic algorithms, where the constrained nonlinear optimization problem is converted to an unconstrained problem using penalty parameter approach. The results obtained are compared with those obtained by the earlier LP model and are fairly similar.     

SLDG: a metamodel for Simulink/Stateflow models and its applications

Simulink and Stateflow (SL/SF) models are being widely used to design and develop embedded systems. Often the SL/SF models of embedded controllers turn out to be large and consist of many subsystems and hierarchies. When such a system is maintained, it becomes difficult to manually analyse the model to identify the impacted elements due to the existence of several explicit and implicit dependencies among the model elements. To automate the analysis of an SL/SF model, we propose a metamodel to capture various types of dependencies existing across the basic blocks. We have named this metamodel Simulink dependency graph (SLDG). We investigate the use of SLDG in change impact visualization and regression test selection. We have developed a prototype tool by implementing our approach for the aforementioned applications.     

印度东部钛磁铁矿的氧化行为和相分析

钛磁铁矿是一种复杂的共生矿石,含有钛铁矿、磁铁矿、铁铝尖晶石和镁铁铝尖晶石等矿物。对从印度东部采集到的钛磁铁矿石进行XRD、WDXRF、SEM和M？ssbauer谱分析。在氧气气氛下,通过TG-DTA分析对矿石的氧化行为进行研究。随后,在氧气和空气气氛下,将样品在不同温度下（873-1473 K）保温不同时间,进行等温氧化实验。观察到在较低的温度下钛铁矿相转变为赤铁矿、氧化钛,而在较高的温度下转变为钛酸亚铁相。将氧化后的矿样与焦炭混合压制成圆柱形球团,在1473 K下进行直接还原,成功地实现了将磁铁矿铁转变为氧化铁和二氧化钛的相变。     

Development of an Innovative Bituminized Jute Paving Fabric (BJPF) Along with its Commercial Field Trials for Potential Application in the Field of Geotechnical Construction with an Eye Towards Global Concern

In the last quarter of the twentieth century, a new class of materials, Geosynthetics, emerged prospectively leading significant innovation in the design of geotechnical and geoenvironmental systems. Geotextiles have proven to be among the most versatile and techno-economically viable ground modification materials playing a significant role in modern pavement design and maintenance techniques. With the growing environmental concern across the globe, technologists, researchers have inclined towards the natural geotextile where Jute Geotextile (JGT) is one of the potential candidates. But, JGT has been restricted mainly as underlay in road construction. Hence, there is an urgent need to design and develop a precise innovative fabric as overlay on existing pavements and other emerging civil works to stay technically and economically competitive in the global market. Such a fabric will not only prove techno-economically viable but will also reduce the carbon foot-print generation to a large extent. This paper delineates the development of Grey Jute Paving Fabric (GJPF) followed by its bituminization with suitable type and grade of bitumen to develop Bituminized Jute Paving Fabric (BJPF). The BJPF will enhance the life of the overlay thereby reducing the cost of maintenance as well as serving as a partial substitute of bitumen mastic.