Approximation-assisted Optimization Research Articles

Multi-objective optimization of an offset strip fin heat exchanger for waste heat recovery in electric vehicles

To increase short driving range of electric vehicle, it is important to reduce power consumption of heat pump system. In this study, an offset strip fin heat exchanger with perpendicular flow is investigated to improve the performance of an electric vehicle heat pump using waste heat. The correlations of the Colburn and friction factor are developed using the experimental data. The simulation results are compared to the experimental results and are validated within temperature and pressure errors of 1.51% and 1.55%, respectively. A multi-objective optimization is performed to maximize the thermal–hydraulic performance of the offset strip fin heat exchanger with six independent design variables via the approximation-assisted optimization technique. The five optimal designs exhibit a 3.7% increase in the heat transfer rate and a 42.1% decrease in the pressure drop for the main simulation condition. Sensitivity analysis and parametric studies are conducted to analyze the effects of each design variable. The results reveal that the fin wrinkle angle, fin height, fin length, and fin spacing had a significant impact on the thermal–hydraulic performance of the offset strip fin heat exchanger.

Multi-scale and multi-physics analysis, design optimization, and experimental validation of heat exchangers utilizing high performance, non-round tubes

Air-to-refrigerant heat exchangers (HXs) are fundamental components in HVAC&R systems, and considerable research has been dedicated designing continually smaller, lighter, and more efficient HX designs. In recent years, researchers have leveraged advancements in Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and optimization algorithms to consider primary tube shape and topology optimization to design highly compact, high performance HXs for a multitude of applications.In this research, we present a computationally efficient, comprehensive, multi-scale, and multi-physics analysis and optimization method for air-to-refrigerant HXs featuring automated CFD and FEA simulations and approximation-assisted optimization. This methodology was utilized to design HXs with shape-optimized, non-round tubes which outperform current state-of-the-art tube-fin HXs without compromising structural integrity. The optimal HXs were shown to deliver similar thermal performance to the baseline HXs while also achieving more than 20% reductions in airside pressure drop and core envelope volume and more than 30% reduction in internal volume.Comprehensive experimental validation of the optimization methodology was conducted through the testing of two prototypes in a standardized wind tunnel facility under multiple operating conditions. For prototype #1 under dry evaporator conditions, the predicted heat load agreed within ± 10% of measured values and the predicted airside pressure drop agreed within ± 30%, while for dehumidifying conditions, the predicted sensible and latent heat loads agreed within ± 10% and ± 20% of the measured values, respectively. For prototype #2, the predicted condenser heat load agreed within ± 3.0% of measured values, and the predicted airside pressure drop agreed within ± 27%. The acceptable agreement between simulation and experimental results for the present application highlights the flexibility of the novel optimization methodology to design next generation HXs with improved performance and reduced volume, weight, and environmental impact.

Numerical investigation and design optimization of a novel polymer heat exchanger with ogive sinusoidal wavy tube

In this paper, a novel polymer bare-tube heat exchanger (BTHX) with an ogive tube shape and a sinusoidal wavy channel is proposed and investigated for the liquid-to-gas application. The thermal-hydraulic performance of the proposed polymer BTHX is calculated using a validated computational fluid dynamics (CFD) simulation model, and the performance is optimized by setting nine independent design variables. A selective-series CFD method with an approximation-assisted optimization technique is developed for the multi-objective optimization to reduce the computational time. As a result, the thermal-hydraulic performance of the optimized novel polymer BTHX shows 91.5% and 134.9% of that of the target aluminum louvered-fin micro-channel heat exchanger (MCHX), respectively. This is mainly due to the improved air-side heat transfer coefficient of the proposed polymer BTHX by 70.2% compared to the target aluminum MCHX. Compared to the recent teardrop-shaped polymer BTHX, the thermal-hydraulic performance of the proposed BTHX is significantly improved. Regarding the polymer thermal conductivity, it is found that the thermal performance degradation can be minimized with at least 8.0 W·m−1·K−1 of the thermal conductivity. The flow field of the proposed polymer BTHX is also discussed and shows that the unique structure of the sinusoidal wavy tube can reduce the air-side pressure drop and promote the mixing of the air flow, thereby improving the air-side convective heat transfer.

Development and design optimization of novel polymer heat exchanger using the multi-objective genetic algorithm

Recently, there has been great attention to find new materials of a heat exchanger to replace aluminum which has been typically used for a long time as a basic material of heat exchangers. In this context, polymeric materials are considered as candidates due to their characteristics of lightweight and excellent corrosion resistance. Despite substantial benefits of polymeric materials, there is a critical issue as used for the heat exchanger, which is the low heat transfer performance due to their extremely low thermal conductivity. In this study, to overcome this limitation, a novel polymer heat exchanger is proposed with the new heat flow design. The finless teardrop-shaped tube bundle polymer heat exchanger is newly designed and its thermal-hydraulic performances are investigated with experiments and simulations. Then, the geometries of the novel polymer heat exchanger are optimized to maximize the thermal and hydraulic performance by using the online approximation-assisted optimization technique.

Optimization of two-phase R600a ejector geometries using a non-equilibrium CFD model

A vapor compression cycle, which is typically utilized for the heat pump, air conditioning and refrigeration systems, has inherent thermodynamic losses associated with expansion and compression processes. To minimize these losses and improve the energy efficiency of the vapor compression cycle, an ejector can be applied. However, due to the occurrence of complex physics i.e., non-equilibrium flashing compressible flow in the nozzle with possible shock interactions, it has not been feasible to model or optimize the design of a two-phase ejector. In this study, a homogeneous, non-equilibrium, two-phase flow computational fluid dynamics (CFD) model in a commercial code is used with an in-house empirical correlation for the mass transfer coefficient and real gas properties to perform a geometric optimization of a two-phase ejector. The model is first validated with experimental data of an ejector with R600a as the working fluid. After that, the design parameters of the ejector are optimized using multi-objective genetic algorithm (MOGA) based online approximation-assisted optimization (OAAO) approaches to find the maximum performance.

Chevron plate heat exchanger optimization using efficient approximation-assisted multi-objective optimization techniques

This article presents a comparison between different multi-objective optimization approaches that can be used to efficiently optimize the design of different thermal systems and components. Plate heat exchanger optimization is taken as case study to compare the different optimization techniques. The plate heat exchanger flow channel geometry is optimized to maximize the thermal-hydraulic performance of the heat exchanger. The thermal-hydrodynamic characteristics of single phase turbulent flow in chevron-type plate heat exchangers with sinusoidal-shaped corrugations have been analyzed using a commercially available computational fluid dynamics tool. The computational domain consists of a corrugation channel, and the simulations adopted the shear-stress transport κ-ω model as the turbulence model. The analysis of even a single design is computationally expensive, and hence, approximation techniques are used to speed up the optimization process. Exhaustive search, offline approximation-assisted optimization, and online approximation-assisted optimization are compared to optimize plate heat exchanger design. For both approximation techniques (offline and online), design optimization is performed using the multi-objective genetic algorithm based on metamodels that are built to represent the entire design space. In offline approximation, globally accurate metamodels are built, which requires adding samples in the entire design space. However in online approximation-assisted optimization, samples are added just to improve metamodel performance in the expected optimum region. Approximated optimum designs are verified using computationally expensive actual computational fluid dynamics simulations. Finally, a comparison between exhaustive search and offline/online approximation-assisted optimization is presented with guidelines to apply both approaches in the area of heat exchanger design optimization. The methods presented in this article are generic and can be applied to optimize different types of heat exchangers, electronic cooling devices, and other thermal system components.

Numerical simulation and optimization of single-phase turbulent flow in chevron-type plate heat exchanger with sinusoidal corrugations

The thermal-hydrodynamic characteristics of a single-phase turbulent flow in chevron-type plate heat exchangers with sinusoidal-shaped corrugations have been numerically investigated in this article. The computational domain contains a corrugation channel, and the simulations adopted the shear-stress transport κ-ω model as the turbulence model. The numerical simulation results in terms of Nusselt number and friction factor were compared with limited experimental data and existing correlations in order to verify the accuracy of the numerical model. The validation was performed using single-phase water as the working fluid. A bi-objective optimization was carried out using an approximation-assisted optimization technique, which provided considerable computational savings to ensure the feasibility of optimization. The corrugation depth, corrugation angle, corrugation pitch, and fluid inlet velocity were identified as design variables, and 200 samples were selected using the maximum entropy design method to build the metamodel for obtaining the heat transfer coefficient as well as the pressure drop per unit length. A multi-objective genetic algorithm was utilized as the optimizer. The optimization results were presented in the form of Pareto solution set, which clearly showed its dominance over the entire design space and the tradeoff between the two optimization objectives: maximizing heat transfer coefficient and minimizing drop per unit length. Also, the Pareto optimal designs were validated against the values directly obtained from numerical simulations. The approximation-assisted optimization shows that all optimal designs have largest enlargement factor values inside the design space, and the optimal corrugation angle increases with the increase of maximum heat transfer coefficient.

Approximation-Assisted Optimization for Novel Compact Heat Exchanger Designs

This paper describes a systematic approach for the use of an approximation-assisted optimization technique in the design of a novel heat exchanger (HX) with a high degree of model fidelity and a low computational cost. Design optimization is performed using multiobjective optimization, and high model fidelity is achieved by using a multiscale HX simulation tool. An approximation technique was used to provide computational savings in order to ensure computational feasibility. This technique was applied to different HX design problems. It was observed that for a 1 kW (3412 Btu/h) heating coil with pressure drop constraints of 100 Pa (0.4 in. water) on the air side and 1000 Pa (0.15 psi) on the water side there is a potential for a more than 61% reduction in the HX volume and an 84% reduction in the HX material when the proposed geometry is compared with the current state-of-the-art technology. The proposed approximation approach produced significant computational savings. The approximation-assisted optimization platform shows great potential for examining new and existing designs and providing a greater understanding of design limitations.