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Design and Implementation of High Performance Current Steering DACs using On-Chip Enhancement Technique
No full textThe future generation (6G) machine type communication (MTC) enabled IoT devices gain massive attention in recent years. The wireless IoT devices utilize the emerging low power wide area networks (LPWAN) technologies. These technologies are extremely energy and cost efficient and suitable for providing long range connectivity. Most of these IoT devices are used in smart city, smart village, air quality measurement, ecological surveillance, smart industrial and agricultural applications etc. These demanding applications require uninterrupted communication between devices. For the simultaneous transmission and reception of the signals, these high end devices explicitly use complex transceiver units. To interface with the real analog signals, the transceiver unit utilizes the system-on-chip (SoC) digital to analog converter (DAC), which is the vital component for the signal processing. In this context, the IoT devices require a low-to-medium resolution (i.e., 6 to-12-bit) high performance DAC with a sampling frequency below 1 GHz for direct conversion and transmission of data. Current steering DAC (CS-DAC) is one of the most promising DAC architecture to meet these requirements. The intrinsic advantages like fast switching and low output node driver make CS-DAC structures more suitable for high speed and wide band transmitters. The effectiveness of these CS-DACs are determined on the basis of static and dynamic performance parameters. The spurious free dynamic range (SFDR) is one of such important performance metric, which is used to measure the linearity of the CS-DACs. Although, the CS-DACs suffer from performance degradation at high frequencies due to process and technology mismatches and other non-idealities. All of these effects make it very challenging to design a high performance CS-DAC. In this work, the major CS-DAC non-ideal error sources like amplitude mismatch and code dependent load variation (CDLV) effects are analyzed and to address these effects, three enhancement techniques are proposed. To mitigate the amplitude mismatch errors, novel dynamic element matching (DEM) techniques like pair wise swap enabled DEM (PSER-DEM) and fully random rotation based DEM (FRR-DEM) are proposed. Additionally, an on-chip partial self-healing technique is implemented to improve the linearity of the CS-DAC by reducing the amplitude mismatch effect. A code independent output impedance compensation (CIIC) technique is proposed to reduce the CDLV effect. To verify these techniques, three 10-bit CS-DACs are designed using 180 nm CMOS process technology followed by rigorous mismatch based simulations at 500 MHz sampling frequency. Further, a 6-bit CS-DAC is implemented in 180 nm CMOS process and tested to validate the proposed PSER-DEM technique. More than 6 dB improvement in SFDR is observed from the measurement results for PSER-DEM enabled DAC. Similarly, on chip partial self healing method shows 3.5 LSB improvement in INL value from the mismatch based simulation. The partial self-healing assisted PSER-DEM technique is presented to design a robust hybrid CS-DAC to enhance both static and dynamic performances to achieve better FOM values. A comparative assessment of the proposed methods are performed, which exhibit better performances with improved Figure-of-Merit (FOM), compared to the state-of-the-art CS-DAC architectures
Investigation Of Delayed Emission From Singlet And Triplet States In Pure Organic Molecules: Design, Synthesis, Photophysical and Electroluminescent Applications
No full textThe current thesis addresses the molecular design, synthesis, and photophysical analyses of a novel class of pure organic thermally activated delayed fluorescence emitters for use in solution-processed organic light-emitting diodes (OLEDs). In addition, the research focuses on the design, synthesis, and photophysical analysis of a novel class of pure organic room-temperature phosphorescent materials. In chapter 1, a general overview of the development of the new generation and several molecular design strategies, fundamental principles used to achieve high efficiency in TADF OLEDs and pure organic RTP materials, a literature review of recent trends, and a brief summary of the objectives of this thesis are presented. In this chapter, the basic purpose and significance of the planned work of the thesis are summarized. In chapter 2, two TADF emitters are synthesized utilizing new design strategy of twisted interlocked acceptor core integrated with carbazole (KCCz) and tert. butyl-carbazole (KCTBC) as donors. Twisting of acceptor core by two methyl groups resulted in complete separation of HOMO and LUMO along with cyanide group facilitate in generating low-lying triplet exited states as suggested by theoretical simulation. These emitters showed deep blue emission with good quantum yield in film as well as good thermal stability. According to the electrochemical investigation, both of the emitters exhibit distinct oxidation and reduction behaviors which are in good agreement with theoretical values (by DFT). To assess these emitters in electroluminescence application, non-doped/doped OLED devices were fabricated. A doped device based on KCCz showed EQEmax of 3.9% and CIE coordinates of (0.16, 0.13). However, doped device based on KCTBC showed EQEmax of 9.0% along with low Efficiency roll-off with long operational device half lifetime of 72 minutes at initial brightness of 1,000 cd m-2, and CIE coordinates of (0.17, 0.13). In addition, with 12.5 wt% of 4CzFCN as assistant dopant/co-host to enhanced the performance of the KCTBC based device with an EQEmax of 13.9% and CIE coordinates of (0.18, 0.13). Further, a high-efficiency warm white OLED adopting the TADF hybrid approach is realized with EQEmax of 9.0 %. In chapter 3, to tune the color in towards red end of spectrum, one benzene ring was inserted between acceptor (KC) and donors, carbazole/diphenyl amine. This design further tuned the spectra from deep-blue to red shifted, blue region because of enhancement of -conjugation. The cyclic voltammetry demonstrates the redox behavior of the emitters. The 7.5 wt% KCPhCz doped device (in CBP) exhibited a PEmax of 22.7 lm/W, CEmax of 32.5 cd/A, EQEmax of 10.8%, and Lmax of 4,850 cd/m2 with CIE color coordinates of (018, 0.19). The 7.5 wt% KCPhDPA doped device (in CBP) exhibited a PEmax of 39.2 lm/W, CEmax of 49.8 cd/A, EQEmax of 15.3%, and Lmax of 15,530 cd/m2. In chapter 4, two new TADF emitters are designed utilizing the strategy of very strong donors, Phenoxazine and Phenothiazine integrated with the interlocked acceptor core KC. The two new TADF emitters based on the donors, Phenoxazine (KCPOZ) and Phenothiazine (KCPTZ) emitted in yellow region. Unsymmetrical and twisted molecular structure aided twisted intramolecular charge transfer in
film. Narrow ΔEST in both the emitters enabled efficient triplet exciton population and RISC to manufacture high-efficiency devices. The 7.5 wt% KCPTZ doped device exhibited a PEmax of 51.54 lm/W, CEmax of 65.6 cd/A, EQEmax of 21.9%, and Lmax of 11,640 cd/m2. A doped (5% in CBP) OLED device based on KCPOZ showed the best performance among both. The 5.0 wt% KCPOZ doped device exhibited a PEmax of 85.6 lm/W, CEmax of 95.2 cd/A, EQEmax of 31.5%, and Lmax of 18,240 cd/m2. Both emitters were also employed as sensitizers for TBRb, an orange TADF emitter, to improve orange device performance. EQEmax increased from 5% to 20% and 18.0% when KCPOZ and KCPTZ concentrations climbed from 0% to 10%. At 100 cd/m2, the KCPOZ device had an estimated half lifetime of 19,844 hours while the KCPTZ device had a lifetime of 10,550 hours. This work demonstrates using unconventional ways to design molecular core structures integrated with appropriate donors to enable high efficiency in the OLED device with a longer lifetime. In chapter 5, two new TADF emitters with the strategy of methoxy substituted double-twisted pyridine-cyano core as weak acceptor unit integrated strong donor by integrating double-twisted pyridine-cyano core as acceptor unit with phenoxazine (PyCN-POZ) and dimethyl acridine (PyCN-DMARC) were designed. PL spectra in solution as well as in neat film suggested emission of PyCN-DMARC in yellow region while that of PyCN-POZ in red region. Cyclic voltammetry analysis has been carried out to know the low and high lying HOMO-LUMO energy levels for the optimization of devices. Both the emitters showed very narrow EST by DFT calculations which suggests these two emitters can be very potential for 3rd generation OLEDs. In chapter 6, two positional isomers (benzaldehyde-alkyl spacer-carbazole) namely, pC4CZ and mC4CZ was designed and synthesized. It is found that these positional isomers with alkyl spacer shows different phosphorescence properties at room temperature in terms of lifetime and Quantum efficiency. Both shows RTP behavior in crystal form with lifetime of 384 and 79 ms and phosphorescence quantum yield of 3.8% and 0.3% respectively. Combined with crystals investigations, rate constant calculations and theoretical studies, it was found that greater phosphorescence lifetime of pC4CZ was due to their strong intermolecular electronic interactions which leads to its reduced krP and knrP by means of stabilized emissive states in dimers. Whereas smaller phosphorescence lifetime of mC4CZ crystals was owing to its weak intermolecular electronic interactions which caused higher krP and knrP. Further, it has been shown that pC4CZ can be very good candidate for anticounterfeiting applications. In chapter 7, the replacement of the carbonyl group with cyanide was executed to get RTP. These positional isomers with alkyl spacer show different phosphorescence properties at room temperature. Rigorous molecular packing investigation of their single crystal tells their diverse RTP behavior by means of the different types of interactions they make in the crystalline state. Also, theoretical investigations of their monomeric as well as different dimeric forms confirms stabilized emissive states in OCNCZ leads to its longer lifetime by efficient kisc. Further, it has been shown that, owing to its longer afterglow, OCNCZ can be potential candidate for Data security/Anticounterfeiting applications. Chapter 8 contains the work's summary and conclusion. The present dissertation focuses on the design, synthesis, and photophysical studies of a novel/new class of D-A pure organic TADF and RTP emitters, with the goal of studying TADF emitters in solution-processed OLED. This chapter provides a summary of the present investigation's observations and conclusions
Graphitic Carbon Nitride (g-C3N4) Based Hybrid Nanomaterials for Energy and Environmental Applications
No full textThe rapid increase in global population and industrial developments are major sources of calamities like shortage of energy and alarming increase in environmental pollution. To tackle these issues, visible-light-driven photocatalysis is considered as an emerging green tool that could efficiently degrade organic and inorganic pollutants into sustainable products and generate H2 energy by splitting water. Therefore, in this doctoral work, an effort has been made to explore the fabrication of different g-C3N4-based advanced photocatalytic materials that can be used for environmental pollution abatement and energy production. In the first objective g-C3N4/metal-free heterojunction nanocomposites i.e, nitrogen-doped reduced graphene oxide covalently coupled with graphitic carbon nitride/sulfur-doped graphitic carbon nitride heterojunction nanocatalysts (4NrGO/g–g PSCN) was fabricated successfully and was found to exhibit extraordinary performance for photoreduction and degradation of 4-Nitrophenol, In our second objective we have tried to develop g-C3N4/metal oxide heterojunction systems namely Ag nanoparticles functionalized Sg-C3N4/Bi2O3 2D nanohybrid (Sg-C3N4/Bi2O3/Ag), and g-C3N4/α-Fe2O3 heterojunction fabricated from g-C3N4/MIL-53(Fe), that were found to exhibit excellent visible-light photocatalytic performance towards Rhodamine B (RhB) dye and Tetracycline hydrochloride (TCH) degradation, and degradation of Bromoxynil, As(III) oxidation, and H2 evolution reactions respectively. Finally, in our last objective we have successfully developed g-C3N4/MOF system, i.e., graphitic carbon nitride (g-CN) nano-Island coupled Ni-MOF (Ni-ML) that exhibits enhanced photocatalytic activity towards N2 fixation and Cr (VI) reaction reactions. The mechanism of all the studied photocatalytic process were thoroughly investigated based on the outcomes of the various physiochemical characterizations, elemental trapping experimental results, and band structures of the developed catalyst. Furthermore, for the view of practical applications stability of all the developed catalysts were exhaustively investigated through multiple recycling experiments. In conclusion, we assume that this thesis work interprets a superlative opportunity to develop proficient g-C3N4-based photocatalyst for energy and environmental remediation
Implementation Strategies for Industry 4.0 Enabling Technologies in Indian Manufacturing Industries
No full textIn recent years, competition among the Indian Manufacturing Industries (IMIs) has increased enormously in the global market. The current uncertainty in the market context is characterised and governed by the customised requirements of the customers. Thus, the manufacturing system in the industries should be capable of adapting the parameters like flexibility in scalability, variety, agility, system responsiveness, inter-connectivity, automatic data exchange with communication among the manufacturing systems, transparency and human-machine interaction, which are the main components and principles of Industry 4.0 (I4.0). Thus, adopting I4.0 is vital in corroborating its long-term survival in the global marketplace. However, very few research work considerations contribute to the issues induced by adopting I4.0 in manufacturing industries. Initially, 13 Industrial System Requirements (ISRs) of IMIs along with 18 barriers faced by these industries during implementing I4.0 enabling technologies in existing systems were identified through literature review and industry experts’ feedback. This work aims to minimise the gap between the existing ISRs, and the challenges faced during implementing I4.0 technologies in existing Industries. The identified ISRs and barriers were evaluated and analysed based on the data set collected from a questionnaire-based survey. Fuzzy multi-criteria analysis is conducted to identify the most weighted ISRs and barriers, and ranked them concerning their importance. The most dominant ISR is found to be ‘Transparency through real-time data monitoring and exchange’ while the most dominant implementing barrier obtained is ‘Employee inflexibility to learn and adapt’. This work offers the researchers, practitioners and industrialists an opportunity to formulate and solve multi-criteria decision-making problems through numerous case studies to prioritise the ISRs and barriers for analysis. Next, the inter-item correlation between the ISRs and barriers were investigated. These correlation values produced from the analysis show how the implementation barriers affect each system’s needs. The collected values of the degree of correlation between each ISR and each barrier have been used to narrow down the gap between existing ISRs and barriers. The maximum positive degree of correlation is found between ISR ‘Increasing system responsiveness’ and the barrier ‘Lack of quick reconfiguration of systems’. It guides industrial specialists, decision-makers, solution providers and researchers in narrowing down the search space to focus on the highest degree of correlated factors. These correlations can create multiple frameworks, conceptual models, maturity models, readiness models and strategical approaches for Indian firms to efficiently implement I4.0 technology. Based on these findings along with a team of eight experts taken from an Indian industry, a Conceptual Framework-based Architecture (CFA) was designed, developed and validated in three phases as per their existing production environment, current technologies, ISRs and barriers faced during the process of upgradation. The proposed CFA allows industrial strategists, decision-makers, policymakers, and researchers to use it as an architectural reference tool for integrating I4.0 enabling technologies, and configuring them as per diverse theoretical, practical, managerial and social implications in the Indian manufacturing sector. In the next phase of the work, subsequent visit to the same Indian industry was conducted. This enabled to identifying significant 52 CFA elements that are currently required to implement in the existing industry with the help of a systematic literature review. These IEF elements were validated as per the readiness level to adopt them in considered industry with the help of a series of brainstorming sessions and interviews with industry experts. Consequently, all identified CFA elements were sorted and merged with their input, resulting in a novel set of 35 CFA elements for this industry. These elements are categorised into six distinct groups based on their functionality for adopting strategy and efficient decision analysis. These 35 CFA elements were analysed based on extent of their readiness to be adopted in the existing industry with the help of industry experts. The degree of significance and readiness to adopt these elements in the existing industry as per the priorities were evaluated through fuzzy-AHP multi-criteria decision analysis. This prioritisation of the sub-categorised framework elements helps in initiating the strategies for implementation process in this manufacturing plant. The most significant CFA element is found to be ‘Decision Making and Management Skills’. For the long-term sustainable implementation of CFA elements, a customised sustainable framework of these elements was designed. The causal relations among these elements were investigated through the fuzzy-DEMATEL method. The diagraphs of the causal relations from each group of the sustainable framework were mapped and interpreted to determine the influencing factors as well as the factors that get influenced. ‘Central Database Server’ is determined to be the most significant sustainable framework element, while the maximum number of casual relationships is obtained from the categorised group, ‘Skill upgradation of the workforce’. This approach has a higher benefit in diverse sectors since it helps decision-makers to visualise and identify issues graphically, hence facilitating a better grasp of causal relationship, which are often complicated and hard to perceive in real-life industrial environment. This study allows industrial strategists, decision-makers, policymakers and researchers to use the approach, framework and findings as a reference tool for integrating I4.0 enabling technologies in existing IMIs and configuring them based on their individual requirements. It also proposes hypothesis of implementations and diverse theoretical, practical, managerial and social implications to address the growing demand of I4.0 technologies in the Indian manufacturing sector
Estimation and Classification Problems under Equality Restrictions on Parameters
No full textThis thesis deals with the problem of estimation and classification for the parametric stochastic model under the equality restriction on the model parameters. A parametric classification problem is a supervised learning problem in machine learning. The key characteristic of parametric classification problems is that they assume that the input data comes from a specific distribution and that the relationship between the input features and the output classes can be captured using a fixed set of parameters. In this thesis, our primary focus is to estimate the unknown model parameters and study the corresponding classification procedures for the different parametric models. In Chapter 1, we briefly introduce the general problem of classification and estimation of unknown parameters. We provide a comprehensive literature review on classification and estimating the unknown model parameters under equality restriction. In Chapter 2, we discuss some fundamental notations, terminology, and results for the estimation and classification problem that helps to frame the rest of the chapters. In Chapter 3, we revisit the problems of estimation and classification for k(_ 2) normal populations with common mean and ordered variances. In the literature, authors have proposed classification rules based on the Graybill-Deal estimator or its improved version of a common mean under ordered variances. Still, the maximum likelihood estimator (MLE), whose closed-form expression does not exist, is not used for classification purposes. We have proposed the plug-in type restricted version of MLEs of model parameters and utilize these estimators to construct plug-in type classification rules. More importantly, a simulation study has been carried out to numerically compare the performances for all the classification rules, including the existing ones. It has been observed that the classification rules, which are based on the MLE and its restricted version, perform quite satisfactorily (if not the best) compared to other rules. This study is extended to several normal populations with a common mean and ordered variances. To show the practical implication of the proposed methodology, we have considered real-life datasets and obtained the rules’ accuracy. Chapter 4 studies the estimation and classification problem for two inverse Gaussian populations under the equality restriction on model parameters. We have considered the two different situations when the mean parameter is common and the other when the scale like (dispersion ) parameter is common. Under the common mean setup, we proposed restricted-type MLEs and some plug-in type estimators for a common mean parameter. We proposed several plug-in type classification rules using these estimators under order-restricted scale-like parameters. In the sequel, we numerically compared the risk values of all the estimators, which shows that one of the proposed plug-in types restricted MLE outperforms others, including the Graybil-Deal type estimator of the common mean. Our computational results reveal that the proposed classification rules outperform existing rules regarding the probability of correct classification. A similar study has been done for the case when the dispersion parameter is common and mean parameters are different. We proposed the Bayes estimator for the model parameters using the Markov chain Monte Carlo (MCMC) method, which is missing in the literature. The classification rule based on Bayes estimators outperforms the existing rules in terms of the expected probability of correct classification. Chapter 5 considers the estimation and classification problem for two logistic populations under equality restriction on the location or scale parameters. The existence and uniqueness of MLEs of the common location and scale parameters are proved. Further, We constructed several plug-in type classification rules based on the MLEs and the Bayes estimators of model parameters. Moreover, the oracle property for the rules based on the MLEs is established. More importantly, an in-depth simulation study is carried out to compare the performance of proposed model estimators and the corresponding classification rules. Similarly, we considered the estimation and classification problems for two logistic populations with common scales and different mean parameters. In Chapter 6, we studied the classification procedure when the training samples are type-II censored from two exponential populations with a common location and different scale parameters. We have also considered the case when prior information about ordering scale parameters exists. We have developed the classification procedure to classify a censored observation into one of the two exponential populations. Using the original and improved estimators of the common location parameters, we have proposed several classification rules and compared their performances numerically. In Chapter 7, we have generalised these results for the case when the training samples are progressive type-II censored. In this regard, we obtain several estimators of the common location and derive a sufficient condition for improving these estimators, considering with and without order restriction on scale parameters. Further, we have constructed several classification rules to classify a group of progressive type-II censored samples into one of the exponential populations. In both cases, real-life datasets are used to demonstrate the estimation and classification methodologies. Chapter 8 concludes our findings and discusses some of our future research problems
Simulation of CO2 Separation from Flue Gas by Cryogenic Process
No full textSeparating carbon dioxide (CO2) from flue gas is challenging due to the energy penalty. Developing a cryogenic or low-temperature CO2 separation method helps overcome the energy penalty associated with CO2 separation. This study aims to develop an energy process to treat coal-fired power plants’ flue gas. In this research work, as a first step, a preliminary comparative study is carried out between the theoretically modified Linde and external cooling processes for the separation of CO2 by liquefaction. The study results reveal that CO2 separation by the external cooling process is better than the modified Linde process. A separation unit, heat exchanger, and compressor are essential components for CO2 separation by external cooling. Generally, three separation methods, namely gas-liquid separation, flash separation, and column distillation are used in industrial applications. So, as a second step, a sensitivity analysis is carried out for these three methods using Aspen Plus. This is to determine an appropriate method for separating CO2 from a gas stream containing N2 and CO2. The study results reveal that the "RadFrac" column distillation model is a rigorous model for simulating all types of multistage vapor-liquid fractionation operations. The column distillation model provides a better model for CO2 separation compared to the other two methods. As a third step, a sensitivity analysis of the heat exchanger is conducted using the Aspen Exchanger Design and Rating for the N2-CO2 mixture. The study results reveal that the heat transfer coefficient increases with an increase in CO2 concentration in the hot fluid. The pressure drop decreases with an increase in CO2 concentration in the hot fluid. A fourth step is a sensitivity analysis of a compressor using Aspen Plus for an N2-CO2 mixture at various CO2 concentrations (10–90%). Compressor load decreases with an increase in CO2 concentration in the feed gas. As a fifth step, a cryogenic column distillation separation process is developed to separate CO2 from N2-CO2 mixtures. The findings show that the energy penalty is low for highly concentrated CO2 feed gas in this process. Coal-fired power plants emit 13-15% CO2 and other pollutants. As a result, the developed cryogenic column distillation separation process consumes more amount of energy. The membrane-cryogenic column distillation separation method overcomes this difficulty. Therefore, as a sixth step, membrane modeling for hollow fiber membranes is performed, and an in-house computer program is developed using MATLAB software. The effects of the number of tubes, length of the tube, feed pressure, and permeate pressure on purity and recovery are studied. The membrane model is optimized using multi-objective JAYA algorithm. The objective function for optimization is obtained from the Response Surface Method (RSM) in Design Expert software. The study results reveal that hybrid processes have lower energy penalties than stand-alone conventional processes. As a seventh step, the hybrid process's energy savings are further improved by utilizing waste heat available in the hybrid process's compression train. For this purpose, the organic Rankine cycle (ORC) is coupled to the hybrid separation system (membrane-cryogenic CO2 capture). This arrangement improves separation system efficiency. The energy, exergy, economic, and environmental analyses (4E) of the hybrid separation process are carried out. The energy penalty of the membrane-cryogenic distillation CO2 separation process with ORC is 1.33 MJ/kg of CO2. The exergy loss of the membrane-cryogenic distillation CO2 separation process with ORC is 9.05 kW for capturing 19.9 kg/hr CO2 from the flue gas's 106.28 kg/hr flow rate. The specific capital and operating cost of the membrane-cryogenic distillation CO2 separation process with ORC is 91.94 million / kg of CO2, respectively. The indirect CO2 emissions of the membrane-cryogenic distillation CO2 separation process with ORC is 5.24 kg/h
Efficient Message Dissemination in Hybrid Vehicular Ad hoc NETworks (VANETs)
No full textThe success of safety and non-safety-related applications in VANETs largely depends on effective dissemination of data among vehicles. Therefore, a suitable MAC protocol is required explicitly for VANETs which can deliver timely and reliably these sort of messages over a wireless collaborative environment. However, channel allocation remains as a challenging problem in VANETs, in fact, in any broadcast networks. The channel allocation among the vehicles in hybrid VANETs is normally done by a RSU. • In this research, an RSU controlled prioritized channel allocation strategy is proposed named as RCAPChA to minimize waiting time of the most deserving vehicle wanting to disseminate a message in the network. As the first contribution of the thesis, the proposed algorithm RCAPChA uses an MCDM tool named as AHP for prioritizing the vehicles. RCAPChA enables the RSU to compute the priority values for all the vehicles requesting for channels, and ranks them accordingly. The priority calculation is executed involving three criteria including severity of the message, vehicle speed, and channel occupancy time to compare our proposed scheme with the existing ones. The simulation results show that RCAPChA defeats the existing schemes regarding delay, PSR, PDR and Throughput at the expense of more energy in saturated data traffic condition. • VANETs can be a great help for WBAN users travelling in a vehicle for prompt and reliable transfer of alert messages to the caregivers. This research aims to minimize the delay of alert message dissemination and maximize the PDR and throughput of the network by applying priority scheduling of message transmission requests involving WBANs and hybrid VANETs. The proposed mechanism named as TRP which is the second contribution of the thesis, involves Prioritization of the sensors, Collection of physiological data from sensors, Detection of abnormality and alert message generation, Priority Scheduling by the RSU of the message transmission requests using MCDM tools named as FAHP and TOPSIS and finally delivers the alert message to its proper destination. The simulation analysis demonstrates that the outcomes of TRP are superior to those of the standard scheme. • MCDM approaches have been developed to support a wider range of application areas The AHP developed by Saaty, is capable of prior weight calculation of individual criteria using CPM and rank computation of alternatives as well. Another MCDM technique, termed TOPSIS, is a ranking technique that requires inputs of the weights of the criteria. As the third contribution of the thesis, this portion of research aims to analyze the impact on ranks of various alternatives for different CPMs using AHP-AHP method as well as AHP-TOPSIS method. For both the cases weights of criteria have been calculated using AHP prior to rank computation. In addition to that, this work deals with performance evaluation of VANETs for priority based channel allocation in terms of Request Service Rate and Average Waiting Time for various CPMs. It is observed that AHP-TOPSIS performs better in terms of Request Service Rate with the increasing number of alternatives. • The success of VANETs largely depends on effective data dissemination among vehicles. As the safety information intended for vehicles must be sent over the network in real time, the vehicles in the network must use a broadcast method for communication which can lead to broadcast storm problem which in turn leads to improper utilization of network resources. As a significant fourth contribution of the thesis, to mitigate the broadcast storm problem, an efficient relay vehicle selection mechanism named as ReUse is proposed for selecting the promising relay vehicle(s) in the network for broadcasting. The relay vehicle(s) is(are) chosen depending on a number of factors including mobility, link quality, buffer size, and number of neighbors using HSA and two MCDM tools named as FAHP and EDAS. ReUSe beats existing relay vehicle selection schemes in terms of reachability, redundancy rate, collision rate, delay, PDR, PSR, and throughput, according to simulation results. • In a dense vehicular network, high message generation rate demanding more transmissions could further increases the effects of the broadcast storm problem. In this context, message aggregation schemes could offer a great relief. As a strong fifth contribution of the thesis, a cluster based RSU enabled message aggregation protocol (CluRMA) is proposed which applies two levels of message aggregation — local aggregation at the cluster heads and global aggregation at the RSU. Before message aggregation process is performed, we make use of cosine distance for similarity checking between the messages for eliminating the duplicates. Then the syntactic aggregation is accomplished by employing message compression techniques — Adaptive Huffman Compression technique for safety messages, and Arithmetic Coding Technique for non-safety messages. The competence of CluRMA has been rigorously analysed and compared with the existing ones regarding several metrics including delay, PDR, collision rate, redundancy rate and overload
Dolochar Derived Zeolites: Optimal Synthesis and Adsorptive Removal of Water Pollutants
No full textWater contamination by different sources is a major environmental issue because of adverse ecological impacts and detrimental health conditions. Adsorption is a highly favoured method due to its versatility and high efficacy in wastewater. Hence, the present work aims to develop low-cost, highly effective adsorbent-dolochar derived nanoporous zeolite to purify contaminated water. Highly versatile an efficient zeolites (X, modified X, and Y) have been synthesized from low-cost material, dolochar. Dolochar is a byproduct generated from the sponge iron industry during the direct reduction of iron. Doochar consists of silica, alumina, and other trace elements, thus it can be used for the zeolite synthesis through alkali activation. The zeolites were synthesized using conventional hydrothermal treatment and non-conventional, ultrasound-assisted hydrothermal treatment. The synthesized zeolites were subsequently used for the wastewater treatment, in removing heavy metals, dyes, and pharmaceuticals. The batch study for conventional adsorption and sono-assisted adsorption were performed, adsorption isotherms, kinetics, and thermodymanics were investigated and the maximum adsorption capacity of the zeolites were evaluated. The synthesized zeolites were characterized using different characterization techniques such as FESEM, TEM, XRD, FTIR, BET, TG-DTA, Raman spectroscopy, and Zeta potential. The zeolite synthesis and the adsorption of pollutants were optimized using Design of Experiments, particularly RSM-BBD. The synthesis parameters such as NaOH/Dolochar ratio, crystallization temperature, and crystallization time were optimized using RSM-BBD to maximize the crystallinity of the synthesized zeolite X (ZX). The optimum conditions obtained include NaOH/Dolochar ratio 1.375, crystallization temperature of 100℃ and crystallization time of 11 h. ZX had a crystallinity of 87.23%, and average crystallite size of 0.79μm. ZX had a pore size of 3.316 nm, specific surface area of 583.117 m2/g, micropore area of 567.226 m2/g, and pore volume of 0.311 cc/g, and ZX was stable at high temperatures up to 800℃. ZX was used for the batch adsorption study of Cd(II) and Pb(II). The optimum parameters for Cd(II) and Pb(II) adsorption includes 6.5 pH, concentration of 50mg/l, adsorbent dosage of 0.25 g/l and 80 min. The maximum adsorption capacity was 714.825 and 738.017 mg/g respectively, following Freundlich isotherm and pseudo-second order kinetics. The ZX was used for the ciprofloxacin (CIP) removal and resulted in 37.786% removal, as zeolite has lesser affinity towards the anionic pollutants. Hence, the surface ZX was modified using Fe(III) to enhance the CIP removal. FeZX was synthesized from ZX using ion-exchange method by varying the Fe(III) concentration from 0.05-0.25M. As observed from SEM and XRD, the iron incorporation didn’t alter the morphology or the crystallinity of the parent material. The CIP removal was maximized using RSM-BBD, the pH, time, initial concentration, and adsorbent dosage were chosen as the input parameters. A removal of 97.974% was obtained at 8.06 pH, time of 59.422 min, concentration of 17.117 mg/l, and adsorbent dosage of 0.478 g/l. Freundlich isotherm and pseudo-second kinetics best fits the experimental data. The nano zeolite X (NaX) was synthesized using ultrasound-assisted hydrothermal method. This technique yields smaller crystals with better efficiency and reduces the time. The synthesized NaX had a cubic octahedral crystals with 88.948% crystallinity. The pore size, pore volume, specific surface area, and micropore area were 3.072nm, 0.354 cc/g, 617.079 m2/g, and 604.782 m2/g. NaX was employed for the sono-assisted removal of dyes such as Rhodamine B (RB), Bismarck brown (BB), and Malchite green (MG). A maximum removal of RB, BB,and MG was 98.841%, 98.543%, and 97.912% respectively, achieved under 8 pH, time of 20 min, adsorbent dosage of 0.35 g/l and initial concentration of 15 mg/l. The Freundlich isotherm and pseudo-second order kinetics well suited the experimental data. Nano zeolite Y (NaY) was hydrothermally synthesized for the sono sorption of sulfamethoxazole (SMX). NaY exhibited 87.178% crystallinity, with cubic octahedral crystals, having pore size of 2.834 nm, pore volume of 0.208 cc/g, specific surface area of 543.661 m2/g, and micropore area of 528.117 m2/g. The SMX removal was maximized using RSM- BBD, the input parameters were pH, sonication time, initial SMX concentration, and adsorbent dosage. A removal of 98.417% was achieved under optimum conditions of 6.123 pH, 56.729 min of sonication time, 11.977 mg/l of SMX concentration, and 0.466 g/l of adsorbent dosage. The Langmuir isotherm and pseudo-second order kinetics were the best fit, with maximum adsorption capacity of 90.909 mg/g. The relevance of the results highlights the importance of using this dolochar-derived nanoporous zeolite as an adsorbent to effectively treat wastewater containing heavy metals, dyes, and pharmaceuticals. Therefore, the concurrent utilization of hazardous solid waste like dolochar to produce value-added materials, for the application in wastewater treatment processes, brings us closer to achieving environmental sustainability
Experimental Studies on Machinability of Inconel 718 and 825 Superalloys under Application of Different Coolant Media and Cutting Inserts
No full textINCONEL refers to a particular family of nickel-chromium-iron based superalloys (trademarked by the Special Metals Corporation). Inconel alloys possess excellent oxidation-corrosion resistance appropriate for service under aggressive operating conditions subjected to intense pressure and heat. Inconel 718 and 825 both belong to the category of Ni-Cr-Fe based superalloys with small amount of Mo, Ti and Al. The addition of Ti and Al imparts high strength and hardness to these alloys. The major constitutional difference between these two superalloys is the presence of Nb (within Inconel 718) and Cu (within Inconel 825). The addition of Nb within Inconel 718 imparts age-hardenability; increases strength and fatigue resistance due to formation of the stable intermetallic compound (Ni3Nb) within base matrix-microstructure. Mo and Cu added within Inconel 825 provide outstanding resistance towards corrosive environments. Inconel 718 is extensively used for applications in jet engine and gas turbine operations whilst the major application of Inconel 825 is found in chemical processing industries. Superalloys are often experienced as ‘difficult-to-cut’ through conventional machining routes. Dry machining of superalloys with uncoated cemented carbide tool is not encouraged due to enormous cutting heat generation which causes significant plastic deformation of the tool point. Owing to high toughness of carbide, thermally softened tool point (altered tool geometry) requires higher cutting force, causes rapid tool wear and finally degraded machined surface quality. Research endeavors are being put to determine an efficient method towards improving machinability of Inconel. Application of coolants, harder tool materials (harder than carbides); depositing coating material(s) over tool substrate and usage of coated tools, precise tuning of cutting parameters and appropriate combination of the above may ensure satisfactory machining yield with acceptable balance amongst productivity, part quality and economy. In the present dissertation, the machinability of two nickel-based superalloys such as Inconel 718 and 825 are analyzed through a few case experimental studies. Owing to the fact that Inconel 825 possesses higher degree of chemical reactivity (towards tool substrate/ binder/ coating materials) than Inconel 718; machining experiments on Inconel 825 work alloy are planned under application of Nanofluid Minimum Quantity Lubrication (NFMQL) environment. On the other hand, the machinability of Inconel 718 is studied under dry condition as well as conventional MQL (sunflower oil-based) with application of single/ multi-layered coated carbide tools (in comparison to that of uncoated counterparts). The entire dissertation is divided into four modular clusters. In the first module, longitudinal finish turning operations are carried out on Inconel 825 under (distilled water + nano-Al2O3 powder)-based NFMQL using a PVD multi-layered (TiN-TiCN-TiN) coated cermet insert. In the second module, performances of two nanofluids are compared during turning of Inconel 825 workpiece using uncoated WC-Co tool. Nanofluids are prepared by dispersing nano-Al2O3 powder and Multi-Walled Carbon Nanotubes (MWCNTs) separately, within biodegradable sunflower oil (as base fluid). In the third module, conventional MQL (sunflower oil-based) machining of Inconel 718 is attempted under application of uncoated/ coated WC-Co tools. Performances of MT CVD multi-layered TiCN-Al2O3-TiOCN coated and MT CVD double-layered TiCN-Al2O3 coated carbide tools are compared to that of uncoated WC-Co counterpart. The fourth module focuses on use of a coated tool (tool with deposited advanced coating material) during dry machining of Inconel 718. Instead of an uncoated WC-Co tool, a HSN2 (2nd generation TiAlxN supernitride; TiAlN doped with Si) coated WC-Co tool is used. The WC-Co tool substrate is coated with PVD HSN2 layer through DC magnetron sputtering technique. In HSN2 coating, the blend of titanium and silicon nitride provides high hardness to the deposited coating layer, refractoriness and resistance towards thermal oxidation. The silicon content develops a strong resistive barrier to thermal diffusion which restricts oxidative and diffusive wear at elevated cutting temperatures. In the present dissertation, machinability of Inconel 718 and 825 are studied in perspectives of magnitude of cutting force components (offset mean value), approximate tool-tip temperature, tool flank wear (width) and quantitative estimates of chip’s micro-morphology (segmentation spacing and frequency, equivalent chip thickness, segment shear angle, segmentation ratio, segment included angle, microhardness, etc.). In addition to detailed tool wear morphology, effects of cutting velocity on influencing machinability of the said work alloys are investigated therein. In relation to machinability of Inconel 825, the severity of machining induced vibrations (absolute value of the maximum amplitude of acceleration) is experienced relatively less during (nano-Al2O3 powder + distilled water) nanofluid assisted machining than dry machining condition. It is also experienced that (MWCNTs + sunflower oil) nanofluid outperforms (nano-Al2O3 powder + sunflower oil) nanofluid due to possession of higher thermal conductivity (imparting better cooling action) and nano-structured cylindrical morphology (ensuring better lubrication effect) of dispersed Carbon Nanotubes (CNTs) causing improved thermo-physical and tribological properties of the resultant nanofluid. While exercising ease of machining of Inconel 718, it is experienced that under sunflower oil-based MQL environment, TiCN-Al2O3-TiOCN multi-layered coated carbide tools may be a better choice than TiCN-Al2O3 double-layered coated carbide tool for operation up tov = 80 m/min. When cutting velocity exceedsv = 80 m/min, TiCN-Al2O3 double-layered coated carbide tool outperforms due to dominance of thermal properties of coating layers thus subsiding frictional effects at tool-work and tool-chip interfacial regions. Dry machining of Inconel 718 with application of HSN2 coated carbide tool is suggested in comparison with usage of uncoated WC-Co counterpart. Application of HSN2 coated carbide tool causes lower cutting force, feed force and thrust force; lower progression width of tool flank wear, better morphology at chip’s underside surface and lower microhardness of chips when compared to that obtained using uncoated tool
Flow and Conjugate Heat Transfer Characteristics of Real-scale IRS (Infrared suppression) Device
No full textAn infrared suppression (IRS) device has complicated thermo-fluid characteristics because they involve complex flow features. The entrainment of surrounding cold air and subsequent mixing with the hot turbine exhaust gas in cargo/naval ships occurs in the device. The thermo-fluid behavior of three types of IRS systems has been elucidated here. The shapes of the funnels used in the IRS system are conical, louvered cylindrical, and louvered conical. Numerical simulations are performed for the real-scale IRS unit by solving the equations of mass, momentum, energy, and radiation in the computational domain surrounding the IRS system. Three types of funnel shapes are considered for the present study: conical, louvered cylindrical, and louvered conical. The study elucidates the influence of the Reynolds number (6.1 × 105 to 3.18 × 106), nozzle overlapping (zero, negative, and positive), inclination angle, funnel-overlapping (zero, negative, and positive), and guide vanes on the air intake and system outlet temperature. It is found that the maximum air intake and minimum outlet temperature for the conical funnel can be achieved with five funnels. Therefore, the authors choose five funnels for analyzing louvered cylindrical and louvered conical funnel situations. The mass intake and device outlet temperature are also affected by funnel-overlapping and nozzle-overlapping. The maximum air intake and minimum outlet temperature are obtained by zero funnel-overlapping and zero nozzle-overlapping conditions. The mass intake increases when diathermic funnels are used in place of the adiabatic funnels with surface radiation for all situations. The impact of funnel wall inclination and the type of guide vanes are also discussed. Using nonlinear regression analysis of the data, empirical relationships for mass intake and outlet temperature ratio are established. Calculation of the lock-on range of the ship with or without the IRS device is also carried out for louvered cylindrical and louvered conical funnels. The present research also takes into account the entropy generation analysis of an infrared suppression (IRS) system. The effect of different boundary conditions for funnel walls (i.e., adiabatic, diathermic with or without radiation) on entropy generation is discussed. Furthermore, entropy generation due to heat transfer has a prominent contribution to total entropy generation. This entropy production study also helps us suggest a configuration of the IRS device with minimum entropy production and how this configuration relates to mass entrainment and device outlet temperature. The entropy generation is lowest for diathermic funnel walls compared to other boundary conditions for the funnel