Abstract: Conventionally, root cause analysis and process documentation in process industries has been manually performed resulting in time consuming effort, cost, and human resources. Moreover, in the event of failure, looking at such document and searching for possible root causes is practically impossible in the interest of time and cost associated. Systems and methods of the present disclosure systematically curate knowledge of industrial process(es) from various sources and generate process ontology via meta model(s). Root cause graph (RCG) is created wherein the RCG corresponds to process and root cause and failure modes in the process. The RCG is then transformed to machine instructions which are executed for root cause analysis in real time. The created graphs/knowledge also help in identifying conflicting knowledge or redundant knowledge. Present disclosure enables root cause analysis as soon as a failure occurs or as the systems show or indicate a tendency towards failure.

Abstract: Machine Learning approaches in literature for determining optimal solver-preconditioner-smoother for solving matrix equations in computer modelling of any systems are directly dependent on matrix property calculation as an intermediate step. However, in CFD domain, this matrix system is generated from simulation input parameters. Also, part of simulation parameter's relation with the matrix equations can be derived from the theory. Embodiments of the present disclosure provide a method and system for prediction of fastest solver combination for solution of matrix equations during CFD simulations. The system trains a Machine Learning (ML) model using a set of relevant input parameters, based on domain knowledge of a CFD problem of interest, as a plurality of input features. The ML model is a multi-class classification model for the prediction of solver combination taking the CFD simulation parameters as an input.

Abstract: Simulation of dynamic physical systems is done using iterative solvers. However, this iterative process is a time consuming and compute intensive process and, for a given set of simulation parameters, the solution does not always converge to a physically meaningful solution, resulting in huge waste of man hours and computation resource. Embodiments herein provide a method and system for stabilizing a diverged numerical simulation and accelerating a converged numerical simulation by changing one or more control parameters. An automatic monitoring mechanism of residue history (to interpret convergence or divergence) and a subsequent control logic to auto-tune the under-relaxation factor would help in stabilizing a diverging simulation and reaching faster convergence by accelerating converging simulation.

Abstract: This disclosure relates generally to system and method for optimization of industrial processes, for example a tundish process. Typically geometries for industrial processes are simulated in a numerical analysis model such as a CFD. In order to simulate a physical phenomenon (such as tundish process) numerically, the domain thereof is discretized in order to convert the differential equations to be solved in the domain into linear equations. The accuracy of a CFD solution is dependent on a mesh of the domain, which in turn depends on a geometry thereof. For setting up an optimization task, the disclosed method provides first a CFD friendly base geometry, so that a faulty geometry can be detected before forming the complete geometry.

Abstract: This disclosure relates generally to system and method for optimization of industrial processes, for example a tundish process. Typically geometries for industrial processes are simulated in a numerical analysis model such as a CFD. In order to simulate a physical phenomenon (such as tundish process) numerically, the domain thereof is discretized in order to convert the differential equations to be solved in the domain into linear equations. The accuracy of a CFD solution is dependent on a mesh of the domain, which in turn depends on a geometry thereof. For setting up an optimization task, the disclosed method provides first a CFD friendly base geometry, so that a faulty geometry can be detected before forming the complete geometry.

Abstract: This disclosure relates generally to conditioned spaces, and more particularly to a system and method for thermo-fluid management in the conditioned space. In one embodiment, the method includes retrieving geometry and operational information of the conditioned space from a conditioned space data. A 3D geometry of the conditioned space is automatically generated in a format suitable for a mesh generation model for numerical analysis by parsing the conditioned space data. A mesh is created within the 3D geometry using the mesh generation model. A simulation data is generated based at least on an operational data of the plurality of components. The simulation data is applied on the mesh to simulate a thermo-fluid model of the conditioned space.

Abstract: The present disclosure relates to a process for the purification of water. The process includes leading water laden with microorganisms and arsenic through an arsenic adsorption media followed by treating the resultant arsenic deficient water with a disinfectant releasing system to obtain water deficient of arsenic and viable microorganisms. The present disclosure also provides an apparatus for the purification of water using the afore-stated process.

Abstract: This disclosure relates generally to conditioned spaces, and more particularly to a system and method for thermo-fluid management in the conditioned space. In one embodiment, the method includes retrieving geometry and operational information of the conditioned space from a conditioned space data. A 3D geometry of the conditioned space is automatically generated in a format suitable for a mesh generation model for numerical analysis by parsing the conditioned space data. A mesh is created within the 3D geometry using the mesh generation model. A simulation data is generated based at least on an operational data of the plurality of components. The simulation data is applied on the mesh to simulate a thermo-fluid model of the conditioned space.

Abstract: The present disclosure relates to a process for the purification of water. The process includes leading water laden with microorganisms and arsenic through an arsenic adsorption media followed by treating the resultant arsenic deficient water with a disinfectant releasing system to obtain water deficient of arsenic and viable microorganisms. The present disclosure also provides an apparatus for the purification of water using the afore-stated process.