Success Syndrome teaches us -‘How NOT to Design’ “… (The design mistake) It was repeated 3000 years ago, 300 years ago, just 30 years ago and will likely to be repeated even today.” “…Possibly the greatest tragedy underlying design errors & the resultant failures is that many of them do…

2002… Prof. Anthony Brennan looked awestruck standing in front of the rows of submarines and ships docked at the Pearl Harbour. He was carefully examining the submerged portions which were fouled heavily by algae. The barnacles — in the Capt. Haddock’s language, “Billions of Blue Blistering Barnacles” — were spread…

Designs Contradictions in Naval Architecture Almost every designer comes across “design contractions”, meaning two different impacts with and without the chosen design concepts. For example, the inward opening of the door caused the death of the Apollo-1 crew unable to open the door in a fire accident that developed high…

The valuation of a startup is tricky & challenging. The value of a startup at the moment of the investment is called as Pre-Money — the starting point of a startup on the path of success. Let me brief the major 5 approaches to value a startup. Here we go. …

Activation Functions An activation function in a neural network defines how the weighted sum of the input is transformed into an output from a node or nodes in a layer of the network. Why do we use Activation Function (AF)? The neuron in NN performs linear computation. But, our data…

When the Pope Sixtus V directed it to be re-erected in the colonnaded square before the Basilica of St. Peter, in 1586, the 83 feet tall obelisk stood on a spot 50 feet from the left outside wall of today’s St. Peter’s Basilica. It was originally erected at Julian Forum…

Physics based Machine Learning is growing fast by merging both the machine learning & the numerical methods techniques. However PBML is outperformed by traditional approaches in case of well-posed forward problems. The well-posed problems are well defined boundary & initial conditions. A system of partial differential equations is well-posed if it…

Let the ML learn physics Multi-physics simulations have been traditionally using numerical methods to solve Partial Differential Equations (PDE). Most of the time real-life physical problems give many surprises with noisy boundary conditions & missing data. We need to manage the data to strike a balance somewhere. PDEs can't incorporate…

Physics Based Machine Learning… Tremendous progress has been made in numerical methods with partial differential equations (PDE) to solve multi-physics problems in the past 50 years. …