Abstract
<div class="section abstract"><div class="htmlview paragraph">A major concern for a high-power density, heavy-duty engine is the durability of its components, which are subjected to high thermal loads from combustion. The thermal loads from combustion are unsteady and exhibit strong spatial gradients. Experimental techniques to characterize these thermal loads at high load conditions on a moving component such as the piston are challenging and expensive due to mechanical limitations. High performance computing has improved the capability of numerical techniques to predict these thermal loads with considerable accuracy. High-fidelity simulation techniques such as three-dimensional computational fluid dynamics and finite element thermal analysis were coupled offline and iterated by exchanging boundary conditions to predict the crank angle-resolved convective heat flux and surface temperature distribution on the piston of a heavy-duty diesel engine. A Bayesian calibration method was used to arrive at heat transfer coefficients for some of the impactful piston cooling surfaces.</div><div class="htmlview paragraph">This work provides insights about the potential use of injection parameters to manage piston thermal loads and maximize thermal efficiency at high load conditions. The influence of key injection parameters such as injection timing (start of injection) and pressure on the transient heat flux and surface temperature distribution on the piston surface were analyzed using the above-mentioned numerical technique. The results show that later injection timings result in lower piston surface temperatures, but also lower efficiencies. A reduced injection pressure at the earliest combustion phasing reduced the piston surface temperature with a slight drop in thermal efficiency. Significant spatial variations of heat flux and surface temperature were observed and quantified for the changes in injection parameters.</div></div>
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