Emissions such as Nox and CO resulting from the combustion of the diesel engines in the commercial vehicles leads to environmental degradation and ozone layer depletion. Alarming environment trend forces the government institutions to develop and enforce strict emission laws for the next generation transportation vehicles. Stricter emission laws mean higher operating pressure, temperature, reduced weight, tight packaging space, engine downsizing etc. Engine cooling systems are the critical components in the managing the engine cooling requirement of the commercial vehicle. Generally engine cooling system includes radiator, charge air cooler, engine oil cooler etc. Product development of thermal management system using the traditional design process takes more time, resource and money. To solve the complex design problem, numerical technique such as finite element analysis is performed upfront in the product development of the radiator to evaluate the structure behaviour under mechanical loading. In this paper, internal static pressure analysis of a radiator is presented to showcase the benefits of using the finite element technique earlier in the product design phase. Pressure cycle life at a critical joint of the radiator is calculated using strain-life approach. Finite element analysis aids in visualization of the hot spots in the design, comparing different design options with less turnaround time. Experimental testing and prototypes can be reduced. Risk of a product being failed is greatly minimized by performing the numerical simulation.

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Governmental agencies across the globe are constantly evolving with stringent emission laws to tackle the problem of CO2 and NOx/SOx emissions. New emission standards force the Truck OEM’s to redesign the engine. The paper is aimed to measure the header tube joint stress of the radiator subjected to random variations in geometry, shape and material properties. Linear analysis will not consider the uncertainty and randomness due to tolerance, process changes, part-part variation etc. Stochastic finite element analysis (FEA) is carried out to account the uncertainty in the system. The finite element model of radiator system is built and baseline linear simulation is performed to obtain the baseline deformation and baseline stress responses. Then the uncertainty and random variation due to the geometry, material and shape variable is defined by a normal distribution function. Random designs are generated by defining the upper and lower bound limit values for the input design variable. Random designs are populated using Monte-Carlo simulation technique. 250 random design points are created for each design variables. Then stochastic simulation is performed to evaluate the responses at random design points. Statistical and probabilistic tools are used to post process the simulation results. The paper showcases application of stochastic simulation method which aids in indentifying the robust design with minimum variations. This also enables engineers and designers to understand the relationship and significance between different design variables in designing energy efficient systems.