02255nas a2200241   4500008004100000022001400041245005300055210005300108260006900161300001200230490000800242520148400250653002201734653003301756653002101789100002401810700001701834700001901851700001801870700001601888700002201904856008701926       2012                        eng d  a1385-894700aModeling of liquid propellant combustion chamber0 aModeling of liquid propellant combustion chamber  aPO BOX 564, 1001 LAUSANNE, SWITZERLANDbELSEVIER SCIENCE SAcOCT  a151-1660 v2073 a<p>Liquid propellants are fuels which do not require external supply of oxygen for combustion. These fuels are widely used for propulsion applications in oxygen rare environments (underwater, space). We had previously presented a model for solid propellant decomposition in a combustion chamber. In this study we extend the model for the case of combined solid and liquid propellant combustion. Sub-models relating to solid propellant combustion and outlet flow-rate in the present study are borrowed from the previous study. The combustion chamber is assumed to be a `well-mixed reactor'. A model is developed to characterize the liquid propellant spray assuming the spray is a collection of individually burning droplets. A single droplet decomposition model was developed and used along-with the spray model to solve for the liquid propellant burning rate. Appropriate numerical methods and computer programs were developed to solve the model equations. The model predictions were compared with the experimental data obtained in earlier studies. Appropriate methodology for calibrating the model parameters was developed and its usefulness was demonstrated by comparing the simulated pressure profiles with the experimental pressure profiles. The presented model and results will be useful for selecting appropriate liquid propellants for propulsion systems and for the development of a system level model of propulsion systems. (C) 2012 Elsevier B.V. All rights reserved.</p>10aLiquid propellant10aSingle droplet decomposition10aSpray combustion1 aPandit, Ajinkya, V.1 aKumar, Ashok1 aRao, Srinivasa1 aKedarnath, C.1 aSrihari, R.1 aRanade, Vivek, V.  uhttps://library.ncl.res.in/content/modeling-liquid-propellant-combustion-chamber-002910nas a2200157   4500008004100000022001400041245010800055210006900163260007100232300001600303490000700319520224800326100002402574700002202598856013202620       2015                        eng d  a0888-588500aModeling hysteresis during crystallization and dissolution: application to a paracetamol-ethanol system0 aModeling hysteresis during crystallization and dissolution appli  a1155 16TH ST, NW, WASHINGTON, DC 20036 USAbAMER CHEMICAL SOCcOCT  a10364-103820 v543 a<p>Crystallization and dissolution processes are of great scientific and commercial interest. Significant efforts have been made in the past to develop mathematical models to describe these processes. In this work, observed hysteresis in particle counts during the crystallization and dissolution processes was used to develop and to test the mathematical models of crystallization and dissolution. Crystallization and dissolution experiments were performed with a system of paracetamol and ethanol. An undersaturated solution was first cooled at a particular rate causing crystallization and crystal growth. The solution was then reheated at the same rate to completely dissolve the generated particles. The particle counts and particle size distribution were measured online using a focus beam reflectance measurement (FBRM) probe. A hysteresis was observed in particle counts with respect to the solution temperature. It was also observed that this hysteresis was affected by the applied heating/cooling rates (0.3, 0.5, and 0.7 K/min) for of the solution. A systematic modeling framework based on the population balance equation (PBE) is developed for quantitatively capturing this hysteresis and the influence of cooling/heating rate on the hysteresis curve. A two-level approach was developed to simulate hysteresis: (a) PBE was solved using computationally efficient method of moments for the crystallization stage. This step was used to efficiently estimate values of parameters appearing in the model equations. (b) PBEs describing crystallization and dissolution were then solved using high resolution finite volume (HRFV) scheme coupled with the moving pivot method. The simulated hysteresis curve showed good agreement with the experimental data. Though simulated results over predicted the average particle (by,similar to 131%), the models were successful in qualitatively explaining the counterintuitive trends observed as the average particle size was tracked with time. The framework was thus shown to be a reliable and robust framework to model crystallization and dissolution processes. The developed approach, models, and results will be useful for simulating industrially relevant crystallization dissolution processes.</p>1 aPandit, Ajinkya, V.1 aRanade, Vivek, V.  uhttps://library.ncl.res.in/content/modeling-hysteresis-during-crystallization-and-dissolution-application-paracetamol-ethanol-001564nas a2200145   4500008004100000245006000041210006000101260000800161300001400169490000700183520109000190100002401280700002201304856009201326       2016                        eng d00aChord length distribution to particle size distribution0 aChord length distribution to particle size distribution  cDEC  a4215-42280 v623 aA simple model is presented to extract the particle size distribution (PSD) from the chord length distribution measured using a focused beam reflectance measurement probe. The model can be implemented using simple spread sheeting tools and does not require the description of additional parameters as opposed to previous models. The model was validated for two systems consisting of spherical ceramic beads by comparing model predicted PSD against the PSD obtained through image analysis (IA). Then, the model was evaluated by considering various systems consisting of irregularly shaped particles (sand/zinc dust/plasma alumina). Model predictions accurately predicted the mean but over-predicted the variance of the PSD in comparison with the PSD obtained from IA. However, overall, a reasonable agreement was observed. Finally, the model was shown to be accurate in predicting PSD in comparison with the measured PSD for systems of practical relevance such as for paracetamol and p-aminophenol crystals. (c) 2016 American Institute of Chemical Engineers AIChE J, 62: 4215-4228, 20161 aPandit, Ajinkya, V.1 aRanade, Vivek, V.  uhttps://library.ncl.res.in/content/chord-length-distribution-particle-size-distribution02393nas a2200241   4500008004100000022001400041245005900055210005700114260000800171300001200179490000700191520169000198653000801888653001801896653002401914653001801938653001101956100002301967700002401990700002602014700002202040856008902062       2019                        eng d  a0008-403400aFlow, mixing, and heat transfer in fluidic oscillators0 aFlow mixing and heat transfer in fluidic oscillators  cFEB  a542-5590 v973 a<p>There is an increasing emphasis on process intensification and development of compact, intensified reactors and separators in recent years. Significant efforts are being made to develop such intensified reactors and separators without any moving parts. Some of the recent research studies have proven that a liquid-liquid extractor based on the Coanda effect and feedback oscillations exhibit excellent mixing and liquid-liquid contacting. These fluidic oscillators can potentially be used for a variety of other multiphase reactions and systems demanding enhanced mixing and heat and mass transfer. In this work, we have computationally investigated flow, mixing, and heat transfer in fluidic oscillators based on the Coanda effect. Available information on flow and mixing in fluidic oscillators was critically reviewed and key gaps in the available knowledge with respect to the design and optimization of fluidic oscillators were identified. Computational flow models were developed to characterize key flow features like unsteady flows, secondary vortices, and internal recirculation over a range of Reynolds number (Re = 90-1538) for three different oscillator designs. Systematic numerical studies were carried out to quantify different flow regimes, oscillations, and the influence of key geometric parameters on flow, mixing, and heat transfer. Simulated results were critically analyzed and are presented in the form of dimensionless numbers. The approach and results presented in this work will provide useful insights and a systematic basis for extending the applications of the Coanda-based feedback oscillatory devices for a wide range of engineering applications.</p>10aCFD10aCoanda effect10afluidic oscillators10aheat transfer10amixing1 aKhalde, Chirag, M.1 aPandit, Ajinkya, V.1 aSangwai, Jitendra, S.1 aRanade, Vivek, V.  uhttps://library.ncl.res.in/content/flow-mixing-and-heat-transfer-fluidic-oscillators