Dr. Anshul Yadav

 

Brief Details:

Dr Anshul Yadav is currently Scientist in Membrane Science and Separation Technology division, CSIR-Central Salt and Marine Chemicals Research Institute, Bhavnagar. He received B.Tech.-M.Tech. dual degree in Mechanical Engineering from Indian Institute of Technology Kanpur in 2017 and Ph.D. in Engineering Sciences from Academy of Scientific and Innovative Research, New Delhi in 2022. He works in the area of water treatment specializing in membrane-based treatment techniques. He received best PhD thesis award from AcSIR, International Sol-Gel Society and Indian Membrane Society. He is recipient of ISEES Young Scientist Award in 2023 for his contributions in water treatment processes. He has received several research grants from Council of Scientific and Industrial research, Bureau of Indian Standards, to name a few.

Research : Membrane distillation process for high saline water and wastewater treatment

Industrial and population growth, accompanied by environmental pollution, has led to an unprecedented freshwater crisis, which has attracted the serious attention of membrane technocrats. The conventional waste(water) treatment methods, such as reverse osmosis and multi-effect distillation are rendered limited due to certain limitations such as improper reject disposal and high energy consumption. Membrane distillation (MD), a synergistic process with advantages of the membrane and thermal separation process, has many applications in desalination and industrial wastewater treatment. In this work, the potential of various flat-sheet mixed matrix membranes for saline water and wastewater (tannery, textile and pharmaceutical industries) treatment was attempted. The work delves into the fabrication of membranes, investigating the incorporation of inorganic fillers and the fine-tuning of hydrophobicity to enhance MD performance. This work also presents a novel concept of MD membranes with self-cleaning properties, offering the potential for significant cost and energy savings. A major breakthrough achieved in this work is the successful integration of MD with crystallization for salt recovery from subsoil brine and tannery industry wastewater, a vital step toward achieving zero liquid discharge. This work also utilizes computational fluid dynamics modelling to gain valuable insights into the MD process, providing a robust foundation for process optimization before resource-intensive experimental trials. The study demonstrates the scalability and effectiveness of synthesized membranes in this integrated approach. Overall, this work comprehensively explores and offers innovative solutions to address high saline and wastewater treatment challenges, positioning membrane technology as a vital component of sustainable water treatment processes.

Teaching: Numerical Methods in Heat, Mass, and Momentum Transfer 

Numerical methods can help achieve sufficiently accurate approximate solutions for complex equations faster and more accurately. To simulate fluid flow, heat transfer, and other related physical phenomena, it is necessary to describe the associated physics in mathematical terms. Nearly all the physical phenomena of interest to us are governed by conservation principles and are expressed in terms of partial differential equations expressing these principles. We will derive a typical conservation equation and examine its mathematical properties. The conservation equations governing the transport of momentum, heat and other specific quantities will be represented through a common form embodied in the general scalar transport equation. We will examine numerical methods for solving governing equations and identify the main components of the solution methods. Discretization is required to obtain an appropriate solution to a mathematical problem. Several popular methods are available for the discretization of an equation, such as the finite difference method, finite elements method and finite volume method. These methods will be briefly introduced. One of the challenges in dynamics problems is to select a solution method and implement an appropriate meshing method to expedite the simulation. Meshing discretizes a complex object into well-defined cells where the governing equation can be assigned so that the solver can easily simulate physical behaviour. The accuracy of the model depends on the type of element chosen for simulation. Hence, common mesh types are also discussed. At last, ways of characterizing numerical methods in terms of accuracy, consistency, stability and convergence will be examined.