NSL Sugars Interview Questions and Answers

Rebound Hammer Test is a non-destructive test to determine the compressive strength of concrete.

• Calibrate the rebound hammer before use

• Clean the surface of the concrete to be tested

• Hold the rebound hammer perpendicular to the surface and press the plunger to release the hammer

• Record the rebound value and repeat the test at least twice on each location

• Calculate the average rebound value and use a conversion chart to determine the compressive strength

• Ensure safety measures are ...read more

If cubes do not attain strength as per IS code, next procedures include identifying the cause, taking corrective measures, and retesting.

• Identify the cause of low strength, such as improper mixing, curing, or testing procedures.

• Take corrective measures, such as adjusting the mix proportions, improving curing conditions, or retesting with proper procedures.

• Retest the cubes to ensure they meet the required strength as per IS code.

• Document the entire process for future reference...read more

Heat of hydration can be measured using calorimetry.

• Calorimetry involves measuring the heat released or absorbed during a chemical reaction.

• The heat of hydration can be calculated by subtracting the heat released by the reaction of the anhydrous compound with water from the heat released by the reaction of the hydrated compound with water.

• For example, the heat of hydration of calcium chloride can be measured by reacting anhydrous calcium chloride with water and measuring the ...read more

Mineral admixtures are used in concrete to improve its properties.

• Mineral admixtures are added to concrete to enhance its strength, durability, and workability.

• They can also reduce the amount of cement needed in concrete mixtures.

• Examples of mineral admixtures include fly ash, silica fume, and ground granulated blast furnace slag.

• Fly ash is a byproduct of coal combustion and is commonly used as a mineral admixture in concrete.

• Silica fume is a byproduct of the production of si...read more

My research topic in M.tech was on the development of machine learning algorithms for predictive maintenance in industrial systems.

• Developed machine learning models to predict equipment failures in industrial systems

• Used data from sensors and other sources to train the models

• Implemented the models in real-world scenarios to demonstrate their effectiveness

• Explored different algorithms and techniques to improve the accuracy of the predictions