Dynamics and Control of Distillation using Aspen

This thesis interprets about the dynamics and control study of distillation columns using Aspen. As all of us are aware, that distillation is one of the most important separation processes in the Chemical Engineering. In the present thesis, simulation studies of the distillation column are presented. Steady state simulations are being performed using Aspen Plus followed by Aspen Dynamic simulation, licensed software of Aspen Tech. In the steady state simulation we have tried to see the effect of changing the flow rate of the extracting solvent etc., which gives criterion about the optimum flow rate in the distillation column. The basic controllers are used for controlling sump level, reflux level and molar feed flow rate. Further two important strategies used for controlling the purity of distillate are: (1) controlling the tray temperature where the maximum change of temperature is observed due to reboiler heat change (2) composition controller. Tyreus ¡VLuyben method is used to tune the proportional integrator controller (PI) for temperature and composition control. The location of temperature controlled tray is obtained by steady state gain value. The design value of integral time constant, I ƒä of temperature control and composition control configurations are found as 2.54 min. and 68.54 min. respectively. Hence, response of temperature controller is faster than the composition controller, but on account of less purity. Thus results encourage to use cascade controller

A Critical Study on Missile and Missile Guidance

As a result of advancements in armament technology, traditional conceptions of battle are going through a profound transformation. The use of technology as a force multiplier is extremely prevalent in modern combat. In the modern battlefield, autonomous weapons are absolutely necessary. In this day and age, the presence of missiles is almost always indicative of a country\u27s level of military power. The employment of guided weapons is an unavoidable need in the arsenals of modern militaries. The study will primarily concentrate on several types of weapons, ranging in range from extremely short to medium, long, and automated. This study analyses a wide variety of missiles and classifies them according to the criteria that distinguish them, including the type of missile, its target, its range, how it is launched, and whether or not it has an autopilot guiding system (APG)

A novel coronavirus (SARS-CoV-2): current status and challenges

In December, 2019 a new public health crisis threatened the world with the emergence of new zoonotic virus, the 2019 novel coronavirus. SARS-Cov-2 or severe acute respiratory syndrome coronavirus-2 belongs to the family of coronaviruses named for the crown-like spikes on its surfaces. SARS-CoV-2 causes COVID-19 (Coronavirus Disease-2019), a contagious viral infection that attacks primarily throat and lungs causing pneumonia-like symptoms. It is speculated that SARS-CoV-2 seem to have come from a bat, but the intermediate reservoir is still unknown. This review will address SARS-CoV-2 structure, clinical features, SARS-CoV-2 genome and its different variant, diagnosis, and treatment and also gives a bird's eye view on the epidemiology and pathology based on current evidence. DOI: http://dx.doi.org/10.5281/zenodo.656139

THRUST GENERATION BY ION PROPULSION TECHNOLOGY

Electric propulsion system proven to be a suitable and efficient alternative for conventional propulsion systems .Ion thrusters is one of the electric propulsion systems. It has very high specific impulse generation (Isp) and consumes very low amount of fuel. Ion thrusters can easily compete with chemical rockets propulsion, even if the thrust produce is very low compares to chemical propulsion. Ion propulsion system can be used for various space missions like orbit station keeping for geostationary satellite, orbit and altitude controlling, multi-goal missions. Ion thrusters are more compatible for deep space missions as they are tested for endurance test where as chemical proportion is highly unsuitable for deep space mission

μ\mu2mech: a Software Package Combining Microstructure Modeling and Mechanical Property Prediction

We have developed a graphical user interface (GUI) based package $\mu$2mech to perform phase-field simulation for predicting microstructure evolution. The package can take inputs from ab initio calculations and CALPHAD (Calculation of Phase Diagrams) tools for quantitative microstructure prediction. The package also provides a seamless connection to transfer output from the mesoscale phase field method to the microscale finite element analysis for mechanical property prediction. Such a multiscale simulation package can facilitate microstructure-property correlation, one of the cornerstones in accelerated materials development within the integrated computational materials engineering (ICME) framework

Predicting prognosis in large cohort of decompensated cirrhosis of liver (DCLD)- a machine learning (ML) approach

Background and aims: Onset of decompensation in cirrhosis is associated with poor outcome. The current clinico-biochemical tools have limited accuracy in predicting outcomes reliably. Identifying the predictors with precision model on the big data using artificial intelligence may improve predictability. We aimed to develop a machine learning (ML) based prognostic model for predicting 90 day survival in patients of cirrhosis presenting with decompensation. Method: We analysed electronic medical records retrospectively of hospitalised cirrhosis patients at the ILBS, with a complete 90-day follow-up. Clinical data, laboratory parameters and organ involvement were serially noted. AI-modelling was done after appropriate mining, feature engineering, splitted randomly into train and testsets (20:80). The class imbalance problem was handled by random over-sampling technique, to make balanced 50:50 ratios. After 10- fold cross validation, 3 repetitions and grid search for optimal hyper parameters, the XGB-CV model was chosen. AUC was the primary selection criteria and confusion matrix was used to compare AUCs between AI-models and existing indices; CTP and MELD-score. Results: Total of 6326 patients [mean age 48.2 ± 11.5 years, 84% male, Mean CTP 10.4 ± 2.2 and MELD Na-30.4 ± 11.9, alcohol 49.4%] were included. Ninety day mortality was 29.2%. Acute insult was identified in 80% cases; of which extra-hepatic 49%, hepatic 46% and unknown 5% cases respectively. The XGB-CV model had the best accuracy for prediction of 90 days event in the train set 0.90 (0.90–0.93), validation set 0.80 (0.79–0.81) and for overall dataset 0.80 (0.79– 0.81). The AUC of the XGB-CV model was better than CTP and MELD Na-score by 16% and 15% respectively. The prediction model considered 43 variables; 18 of which predicted the outcome, and 10 maximum contributors are shown in concordance classifier. The most contributors to poor outcome included, index presentation as HE, diagnosis of AD/ACLF/ESLD, PT-INR, serum creatinine, total bilirubin, acute insult etiology, prior decompensation, acute hepatic or extrahepatic insult, leukocyte count and present duration of illness. In the Decision Tree Model, the presence of HE, PT-INR and syndromic diagnosis of AD or ACLF/ESLD was able to stratify the patients into low (22%), intermediate (23–46%) and high risk (\u3e75%) of mortality at 90 days. Conclusion: The AI based current model developed using a large data base of CLD patients presenting with decompensation immensely adds to the current indices of liver disease severity and can stratify patients at admission. Simple ML algorithms using HE and INR besides syndromic presentation, could help treatment decisions and prognostication

New high precision study on the decay width of the Hoyle state in C-12

Precise estimation of the rare direct 3α decay of the Hoyle state of 12C has been made to unveil its unusual α-cluster configurations ranging from linear 3α chain structure to diffuse Bose gas as well as Bose Einstein condensate. The present new high precision, nearly zero background experimental study with Hoyle events has converged on the upper limit for direct decay at ∼0.019% with 95% confidence limit, which is more than a factor of 2 lower than the limit obtained in the previous studies.Two of the authors (S.B. and A.R.) acknowledge the financial support received as Raja Ramanna Fellowship from the Department of Atomic Energy, Government of India