Experimental Investigation Of Heat Transfer Enhancement In Industrial Waste Heat Recovery Units

Abstract

Industrial processes reject a substantial fraction of consumed energy as low- and medium-grade waste heat, and 
recovering this thermal resource is central to improving plant-level energy efficiency and reducing greenhouse
gas intensity. This empirical study analyzes performance data collected from a set of industrial waste heat 
recovery (WHR) installations comprising shell-and-tube heat exchangers, plate heat exchangers, heat-pipe 
recuperators, organic Rankine cycle (ORC) units, thermoelectric generators (TEGs), and absorption chillers, in 
order to quantify how design and operating variables govern thermal effectiveness, recovered energy, exergy 
efficiency, pressure-driven pumping losses, and financial payback. Field and test-rig measurements across 
varying mass flow rates, inlet temperatures, and fluid velocities were tabulated and statistically analyzed, and the 
resulting relationships were benchmarked against previously published findings [1]. The results show that 
thermal effectiveness declines predictably with increasing flow rate due to reduced residence time, recovered heat 
scales near-linearly with inlet temperature difference, and optimized heat-exchanger geometries raise exergy 
efficiency by six to nine percentage points relative to baseline designs. Pumping power was found to increase 
disproportionately with fluid velocity beyond 2.5 m/s, identifying a practical optimum operating window, while 
the economic analysis indicated payback periods between 4.4 and 5.2 years for representative retrofit scenarios. 
These findings directly support the study's central premise that systematic thermal optimization of WHR systems 
yields measurable, reproducible gains in both energy recovery and economic return, and they extend the empirical 
basis reported in earlier waste-heat-recovery literature [2]. The conclusions offer quantitative guidance for 
engineers selecting and tuning WHR technologies for specific industrial waste-stream conditions, and they 
reinforce the paper's overarching contribution: a data-grounded optimization framework that bridges thermal
engineering theory and practical industrial decision-making for sustainable energy recovery [3].