3 ׀ RESULTS AND DISCUSSION
Prior to solving the CDU network synthesis problem, the reliability of the HINT software was first investigated by solving the Example problem of Colberg and Morari whose stream and cost data was presented in presented in Table 2. The goal was to predict the area target of the HEN in that study. A comparison was then made between their results and the results obtained in the present study which showed similar area targets thus confirming the reliability of HINT software. The grid diagram of the heat exchanger network, and the composite curve as generated in the HINT for the problem adapted from Coldberg and Morari is presented in Figures 3 and 4 respectively. A total number of 6 exchangers and area target of 298.227 m2 were obtained in this study. The area target obtained in this study is within 1% of the one obtained in simple area targeting of Colberg and Morrari . This suggests that the HINT software employed in this study is an effective package for pinch analysis. It gives operating and capital cost of 31,000 $/yr and 34,215.5$/yr respectively. This amounts to total cost of 65,215.5$/year. The NLP of Colberg and Morari could not target for the operating cost and the total cost.
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Figure 3 Composite curve of Example problem showing total heating and cooling targets of 620 and 230 kW respectively.
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Figure 4 Optimum ΔTmin of 8.84 K at area target of 301.88 m2 obtained from HINT
Results were compared with that of Colberg and Morari as shown in Table 3. Colberg and Morari obtained with their NLP, a total area target of 259.7 m2 as the starting point solution using MINOS 5.0 software with a spaghetti structure. With no restriction in stream matching, the NLP yielded an area target of 258.8 m2; but the authors’ simple area targeting method based on composite curves predicted a target of 295.6 m2. They also observed that the optimal ΔTmin of 4.2 K was less than the ΔTmin (10 K) specified for utility targeting in that case study. A comparison of results revealed that the simple area targeting method of Colberg and Morari overestimated the area target by 14.22% while the matching used in the present study overestimated the target by 15.23%, which is just about 1% different from the NLP solution of Colberg and Morari. However given the closeness of the areas between this study and that of Colberg and Morari, the HINT software is therefore considered a reliable tool that can be used in the study of pinch technology.
Table 3 Results comparison