CFD

Here is a representative list of the type of domains and physics which we have handled through various projects.

• Internal and external aerodynamics with RANS-based turbulence models

• Conjugate heat transfer

• Combustion and radiation modeling

• Discrete-phase flows

• Multi-phase flows

• Subsonic, transonic and supersonic flows

Mathematical modeling and design

We can help you develop mathematical models for your systems. Systems can be broken down into modules and modules can be modeled using different approaches. Our team has an in-depth understanding of non-linear systems and complex phenomena can be accurately represented using reduced-order models, artificial neural networks, surrogate statistical models, and even as data fields by performing a large number of experiments and/or numerical simulations.

Models thus developed can be further validated and fine-tuned by subsequent numerical analysis. Such models can and have been used for designing process controllers.

Engine health management (EHM)

We have rich experience in the field of EHM for one of the leading aircraft engine manufacturers

• Sensor placement for data acquisition (measure key parameters like pressure, temperature, flow rate, vibration levels at regular intervals during flight)

• Worked on all stages of EHM: sensing and measurement, data acquisition, data transfer, data analysis and action management

• Experience with Aircraft Condition Monitoring System (ACMS)

• Trend prediction and anomaly detection using rules-based and machine learning algorithms

audio signal processing

We have a rich background in audio signal processing using time and frequency domain processing. We have experience with DSP algorithms like multi-band filtering, dynamic range compression, signal de-noising, signal smoothing and feedback suppression. We have performed audio signal processing in Matlab (R&D and proof-of-concept), Python (non-real-time processing) and C++ (real-time processing). We have also integrated DSP algorithms into smartphone apps using native libraries (C++, for Android as well as iOS) to perform real-time processing and modification of audio signals.

machine learning

We have a good understanding and experience of fundamentals of machine learning. Our team has used various techniques and algorithms from TensorFlow, Scikit Learn and Keras libraries to develop proof-of-concept applications in anomaly detection (prediction of part break-down using acoustic signal analysis) and computer vision (visual quality control during manufacturing).

We are currently investigating the possibility of using ANNs to predict flow parameters for internal flows, based on boundary conditions.

aerodynamics

We have carried out multiple projects for numerical simulation of internal and external aerodynamic flows. Our team has worked with automotive sports teams for drag prediction of race vehicles, where proven CFD methodologies were needed to repeatedly and accurately match wind-tunnel predictions. We have carried out projects for mixed (internal/external) aerodynamic analysis of supersonic RAMJET vehicles with complex physics and flow-shock interactions. We have successfully helped multiple clients improve the design of their power generation equipment for improved flow mixing, reduced pressure losses and more efficient heat transfer.

flight mechanics

Our team of experts have profound understanding of the fundamental principles of flight mechanics. We have worked on academic and industrial projects for fixed and rotary wing aircraft platforms. AKN has published two textbooks and multiple papers in this field and his paper on panic-button algorithm was widely hailed as one of the seminal publications in the year 2005.

combustion and heat transfer

Our team has a profound understanding of the principles of combustion, radiation and conjugate heat transfer. We have worked in academic and industrial research projects to accurately model and predict fluid flow and heat transfer properties of reacting and burning fluids. We can help you write models (UDFs in Ansys Fluent) to mimic the complex Physics of your flow problems and use CFD Simulations to better understand and design the behavior of your equipment.

computational geometry

Our team has multiple commercial-grade projects under its belt in the field of computational geometry (geometric modeling, mesh generation and associated algorithms). We have helped organizations develop custom algorithms for mesh generation based on their problems, which allowed the algorithms to be fine-tuned to provide optimal performance. We have contributed to architecture design, data structure and algorithm implementation as well as helped many of our clients add features to their mesh generation and CAD software.