• Energy Research

This study proposes a new inverse design method that utilizes a physics-informed neural network (PINN) to parameterize the geometric and operating inputs, enabling the identification of optimal heat sink designs by starting with the desired objectives and working backward. A specialized hybrid PINN is designed to accurately approximate the governing equations of the conjugate heat transfer processes. On this basis, a surrogate model derived from the hybrid PINN is constructed and integrated with multi-objective optimization and decision-making algorithms. The results of an example finned heat sink system are presented, showcasing the accelerated search for Pareto-optimal designs. The proposed method nearly halved the search time to approximately 113.9 h in comparison with the traditional methods. Moreover, three representative scenarios—high-performance design, equilibrium design, and low-cost design —were compared to visualize the real-time changes in the multiphysics field, facilitating improved physical inspection and understanding of the optimal designs.

Abstract This paper introduces a bi-level reduced-order models (ROMs) approach for quickly deciphering the optimal exergy fields in closed wet cooling towers (CWCTs) with consideration of weather variations. First, an efficient sampling method based on stochastic reduced-order model is performed for the approximation of the multivariate probability distributions by generating a finite set of samples. The uncertainty associated with input variables is propagated via multi-sample CFD simulations of the CWCT model for each of the samples. The results of the state and output variables stored in the CFD solutions are used to construct the data-driven and physics-based ROMs by combining principal component analysis and artificial neural network methods. The constructed data-driven ROM is embedded in a sampling-based stochastic optimization model that seeks the maximization of the expected exergy efficiency ratio. The physics-based ROM is used to visualize the optimal field profiles of the thermal-, mechanical-, and chemical-exergy fluxes. Finally, the results of a case study demonstrate that the main strengths of the proposed approach is to simultaneously obtain the optimal exergy efficiency ratios and the exergy field profiles of the CWCT system in a computationally efficient manner.

The multiple effect evaporator (MEE) system is a typical process for liquor concentration in the energy-intensive industries. Many approaches and commercial software have been widely used for MEE s...

Abstract In a refining complex, an absorption-stabilization process used in the production of end-use petro-products (i.e. stable gasoline and liquefied petroleum gas) is energy-intensive and costly. A new absorption-stabilization process with a two-stage condensation section is introduced in this work to further improve energy-use performance. In the new process, a condenser, a condensed oil tank, and a side-reboiler are integrated into the original process and then a heat integration scheme is performed. Compared with the existing process, the proposed process can reduce the cold utility and hot utility by 17.98% and 25.65%, respectively, as well as decrease the total annual operating costs of the heat exchanger network by 17.48%. Additionally, the process retrofit reduces the annual operating costs of cooling water and steam by about $346,617 at the expense of capital costs around $487,006, and the corresponding payback period is approximately 17 months.

Abstract In order to promote the sustainable development of sludge-to-energy industry and help the decision-makers/stakeholders to select the most sustainable technology for achieving the sludge-to-energy target, this study aims at using grey Decision Making Trial and Evaluation Laboratory (DEMATEL) to identify the critical barriers that hinder the sustainable development of sludge-to-energy industry in China and to investigate the cause-effect relationships among these barriers. Accordingly, some policy implications for promoting the sustainable development of sludge-to-energy industry in China were proposed. After the grey DEMATEL analysis, a grey Multi-Criteria Decision Making (MCDM) framework which allows multiple decision-makers/stakeholders to use linguistic terms to participate in the decision-making for prioritizing the alternative technologies for sludge-to-energy was developed, and the evaluation criterion system for sustainability assessment of sludge-to-energy technologies was determined based on the results of grey DEMATEL analysis. Three alternative technologies for sludge-to-electricity were studied by the proposed MCDM method, and the results show that the proposed grey MCDM method is feasible for group decision-making and sustainability assessment of the alternative technologies for sludge-to-energy.

Plasma gasification (PG) based tri-generation process for dimethyl ether (DME) and power generation has been developed to valorize the poultry litter with an objective of energy, exergy, emergy, economic, and environment (5E) sustainability. PG process has been optimized by the application of a radial basis function surrogate optimization algorithm. Comparative analysis of the base and the optimized process has been performed. The results reveal that the economic performance of the optimized process is better than base process with 6% additional DME generation. The energy efficiencies of the optimized process and the base process are 44% and 48%, respectively while there is no significant difference in the results of exergy analysis. Process thermal energy has been converted into electrical energy through steam turbine powered generator, and 1271 kW electricity can be produced through it. Emergy analysis indicates that the sustainability index of the process is 2.509, to some extent, which means that the process is sustainable. Finally, the economic analysis shows that the capital payback period of the optimized process (7.2 year at 70% process efficiency) is shorter while the base process is not feasible when the process efficiency is below 90%. Therefore, this PG tri-generation optimized process is a feasible solution for biomass waste valorization based on 5E analysis.

Abstract This article presents a three-dimensional CFD model to describe the counter-current air-water flow across the staggered tube bundles in a bench-scale closed wet cooling tower by combining VOF multiphase method and SST k-ω turbulence model. The proposed model can investigate the interfacial heat-mass transfer and complex interaction mechanisms among multiple tubes. Through adding the shear force term and water evaporation in the model, the circumferential distribution of the falling film and air humidity fields are obtained, and the effects of the spray density and the air velocity on the falling film flow mode, air humidity, and transfer process are studied. The results show that, the thinnest water film and maximum evaporation rate are obtained when the circumferential angle is 75° and the spray density is 0.048 kg m−1 s−1, respectively; the air Reynolds number has a greater influence on multiphase heat and mass transfers than that of the spray water Reynolds number.