This paper presents a procedure for minimizing the cost of a shell-and-tube heat exchanger based on genetic algorithms (GA). The global cost includes the operating cost (pumping power) and the initial cost expressed in terms of annuities. Eleven design variables associated with shell-and-tube heat exchanger geometries are considered: tube pitch, tube layout patterns, number of tube passes, baffle spacing at the centre, baffle spacing at the inlet and outlet, baffle cut, tube-to-baffle diametrical clearance, shell-to-baffle diametrical clearance, tube bundle outer diameter, shell diameter, and tube outer diameter. Evaluations of the heat exchangers performances are based on an adapted version of the Bell–Delaware method. Pressure drops constraints are included in the procedure. Reliability and maintenance due to fouling are taken into account by restraining the coefficient of increase of surface into a given interval. Two case studies are presented. Results show that the procedure can properly and rapidly identify the optimal design for a specified heat transfer process. Copyright © 2006 John Wiley & Sons, Ltd.

Novel intelligent systems to assist energy transition and improve sustainability can be deployed at different scales, ranging from a house to an entire region. University campuses are an interesting intermediate size (big enough to matter and small enough to be tractable) for research, development, test and training on the integration of smartness at all levels, which has led to the emergence of the concept of “smart campus” over the last few years. This review article proposes an extensive analysis of the scientific literature on smart campuses from the last decade (2010-2020). The 182 selected publications are distributed into seven categories of smartness: smart building, smart environment, smart mobility, smart living, smart people, smart governance and smart data. The main open questions and challenges regarding smart campuses are presented at the end of the review and deal with sustainability and energy transition, acceptability and ethics, learning models, open data policies and interoperability. The present work was carried out within the framework of the Energy Network of the Regional Leaders Summit (RLS-Energy) as part of its multilateral research efforts on smart regions.

This paper presents a model for estimating the total cost of shell-and-tube heat exchangers (HEs) with condensation in tubes or in the shell, as well as a designing strategy for minimizing this cost. The optimization process is based on a genetic algorithm. The global cost includes the energy cost (i.e. pumping power) and the initial purchase cost of the exchanger. The choice of the best exchanger is based on its annualized total cost. Eleven design variables are optimized. Ten are associated with the HE geometry: tube pitch, tube layout patterns, baffle spacing at the center, baffle spacing at the inlet and outlet, baffle cut, tube-to-baffle diametrical clearance, shell-to-baffle diametrical clearance, tube bundle outer diameter, shell diameter, and tube outer diameter. The last design variable indicates whether the condensing fluid should flow in the tubes or in the shell. Two case studies are presented and the results obtained show that the procedure can rapidly identify the best design for a given heat transfer process between two fluids, one of which is condensing. Copyright © 2008 John Wiley & Sons, Ltd.

A model is developed to simulate a cross-flow heat exchanger, including fins, in the wall of which thermoelectric generators are sandwiched. Such a system could be used for waste heat recovery. The model is used to optimize the device based on several objective functions: total volume, total number of thermoelectric modules, power output, and pumping power. The design variables are the local distribution of modules and of current, the shape of the fins, and the division of the heat exchanger in sub-channels. Pareto fronts are achieved with a multi-objective genetic algorithm, and are presented here. The results show that the number of sub-channels in the heat exchanger has a larger impact on the overall performance than the fin geometry for this particular problem. Also, the net power output is mostly correlated to the number of thermoelectric modules, and less to the heat exchanger volume. Various relations between the different competing objectives are shown and analyzed. Copyright © 2011 John Wiley & Sons, Ltd.

In this paper, we demonstrate that asymmetry in fluid distribution tree networks emerges from power requirement minimization, under global volume constraint. We have discovered several levels of asymmetry in optimal trees: different pipe lengths at the same level of branching, different mass flow rates at junctions or bifurcations, and different main branches to build the optimal dendrite. The emergence of asymmetry in optimal tree networks (man-made or natural) is a result of the optimization: it is not an assumption or a modeling feature. The constructal method that we used to discover asymmetry is predictive, and this distinguishes it from descriptive methods such as fractal geometry.