Abstract A novel approach is proposed to design an aircraft heat exchanger considering multiple working conditions to develop the conventional approach that designs for only one working condition. Calculation results show that the performance of the heat exchangers designed by this novel approach meets the requirement of pressure drop and heat transfer for all working conditions (flight height varies from 0 m to 12,000 m, and Mach number varies from 0 to 1.2). After working conditions discrete and heat exchanger design, the extreme working conditions of pressure drop and heat transfer rate are found not coincided, which have been all considered in design without artificially screening. Therefore, it is not necessary to find a ‘seeming extreme working condition’ before design for this approach. In the optimization design, a deeply optimized structure of heat exchanger is proposed by changing the values of the selected structural parameters to reduce by roughly 30% of the total weight in comparison to common design results. Moreover, the pressure drop and the heat transfer rate of the optimal result can be reasonably distributed at different working conditions. Actually in this novel approach, more other specific criteria required could be also added into the integrate criterion of optimization to control the result. In addition, two detailed optimization methods, sacrifice of secondary objective parameters and ‘the macro-to-micro design method’, have been proposed in optimization design for further optimal structure.

Abstract In order to solve the problem of overpressure release of oxygen supply network caused by the contradiction between continuous oxygen production by air separation unit (ASU) and intermitting oxygen consumption in converter steelmaking, a pressure balance strategy for pre-adjusting liquid-vapor ratio of ASU was proposed. Used Aspen Plus software, a full-compression model of an ASU in an iron and steel enterprise was established. Before stopping oxygen consumption in the converter steelmaking, method of pre-adjusting liquid-vapor ratio from the low-pressure distillation column to reduce the oxygen production of the air separation unit was calculated. This strategy consists of two steps. First step is pre-adjusting liquid-vapor ratio from the low-pressure distillation column to reduce the oxygen production of ASU, before stopping oxygen consumption in the converter steelmaking. The second step is the reduction of the supply oxygen production pipe network pressure, when stopping oxygen consumption in the converter steelmaking. The pre-adjusting oxygen production and the starting time are the key of the strategy. The energy consumption analysis of the strategy is carried out. The results show that the strategy reduces the pressure of the oxygen supply pipe network by 1.3% and reduces the large amount of oxygen release, while increase of the energy consumption of ASU is neglected.

Abstract High-fidelity computational thermal models (HFMs) of mechanical systems typically incorporate multi-disciplinary data sources to define boundary conditions, constraints, and dynamic system inputs. Oftentimes, HFMs are used during the planning, design, fabrication, testing, and operational phases of the mechanical systems, however, most of that data is processed during the modeling and test phases to discover and verify system responses. This approach can lead to much unused data and engineering effort that could otherwise provide useful information during the operational phases of the systems. One major bottleneck in using HFMs during the operational phase is data volume and computation time. Reduced-order models (ROMs), such as Gaussian processes, can consolidate data volume, data complexity, and time complexity needed for processing HFMs. The Borg multi-objective evolutionary algorithm (MOEA) presents a possible effective approach for processing ROM information in conjunction with real-time true process data to better understand the real-time state of a system. An investigation is being performed into the use of ROMs with the Borg MOEA to capitalize on engineering effort and simulation data that would otherwise be abandoned. This paper discusses the results of such a study in a steady-state conductive-radiative heat transfer system.

Abstract A water extraction device that takes water from air in dry area is proposed. This device is designed to meet domestic water demand in remote rural areas, where the climate is dry and fresh water is scarce. The device can be driven effectively by low-temperature waste heat and has the characteristics of large daily water production, low energy consumption per unit of water and high water quality. Because the moisture content of air in dry area is very low, the effect of direct condensation is limited. Solid adsorbent is able to adsorb water vapor from air at a low temperature and release water vapor at under high temperature, which can be used for water extracting from air. To improve its performance under dry circumstances, the key technical point of this device is to use solid adsorbent to collect water vapor from other air to raise its dew point temperature, and then use high temperature cold source to condense water vapor from it. In this paper, configurations of the solid adsorption are proposed, which can be driven with low regeneration temperature under the same humidity increasing amount. This device uses multi-stage desiccant wheels to realize humid increasing. Desiccant wheel can be driven with high temperature to take water vapor from dehumidification air and release water vapor to regeneration air. The multi-stage configuration is good for the reduction of regeneration temperature, making applications of low temperature waste heat form heat pumps possible. Then, influencing factors of water extracting rate are analyzed. The influencing of regeneration temperature, humid reduction amount of the humidified air and cooling and heating systems, etc., are analyzed. Last, air handling processes considering cold and heat sources are recommended to reduce energy consumption. The heat pump driven scenarios are discussed in particular. Through optimization, the water extracting rate can be increased and energy consumption per unit of water can be reduced. At present, this paper only studies air water extracting processes and thermal processes, and does not involve structure of the device, water purification and power consumption of fans, etc.

Abstract Metal matrix composites (MMCs) can be manufactured by infiltrating a melting matrix alloy into hard powders — such as silicon carbide and tungsten carbide — loaded in a graphite mold and quenched to achieve a specific quenching temperature profile for proper solidification. Water quench is a widely used quenching technique within the aluminum and steel industry. It is more common to apply numerical simulation to optimize process parameters and help improve product quality, which depends upon reliable boundary conditions (e.g., heat flux or heat transfer coefficient); however, heat transfer coefficient changes with surface temperature and water flow rate. Moreover, the heat transfer coefficient in the discussed manufacturing process was never quantified. A combined experimental and simulation method to investigate heat transfer coefficient of the external surface of the graphite mold associated with water quenching is proposed. Firstly, the heat flux from the graphite mold is measured, which varies with water flow rate, mold surface temperature, nozzle arrangement, and water flow pattern. Without modifying the hardware design, this study focuses on the effects of water flow rate and mold surface temperature on surface heat flux. Secondly, the temperature distribution within the mold is used to inversely determine the heat transfer coefficient by solving an inversed optimization problem.

A revolutionary cooling system is designed for a multi-fuel rotary engine (200 cc, 40 hp). The patented cooling system includes a water cooled array of engine housings, an innovative rotor and hydrodynamic bearings set cooled with a secondary oil cooling system. The oil conduits, however, are incorporated into water jackets, therefore the heat is further transferred to the water flow. Numerous fins and ribs are utilized as deflectors in water jackets thus controlling water flow to carry heat from the “hot” side of the engine housing to the “cold” side, which minimize temperature differential over the housing as well as reducing peak temperature. Numerical simulation indicated hot spots and uneven temperature distribution issues were controlled in the water jackets. Testing the optimized water jackets as part of the cooling system was also shown in successful in controlling temperature, hot spots and cavitation on the rotary engine with multi-fuels testing, such as kerosene, JP-5, JP-8, alcohol, gasoline, and E85. The potential of applying current water cooling system in other rotary engines is feasible.

Manifold-microchannel combinations used on heat transfer surfaces have shown the potential for superior heat transfer performance to pressure drop ratio when compared to chevron type corrugations for plate heat exchangers (PHE) [1–4]. However, compared with heat transfer enhancements such as intermating troughs and Chevron corrugations, manifold-microchannels (MM) have several times more variables that influence the heat transfer and pressure drop characteristics, including microchannel width, depth, passes, manifold depth, width, and manifold fin thickness. Previous work has reported on the effects of some of the variables, and provides some models for their effects on thermal and hydraulic performance. The current paper presents a genetic algorithm (GA)-based procedure to analyze the implicit effects of some of the manifold-microchannel variables, and compare the performance of manifold-microchannel plate heat exchangers to those using standard Chevron corrugations. The objective of the present work is to evaluate the performance of manifold-microchannel heat transfer enhancements and demonstrate the potential for using GA-based procedure to optimize the heat exchanger. This paper also presents the modifications of the standard GA algorithm when applied to the optimization of MM. The resulting GA procedure is particularly well suited to PHEs for several reasons, including the fact that it does not require continuous variables or functional dependence on the design variables. In addition, the computational effort required for the GA technique in our implementation scales linearly, with a scaling coefficient that is significantly less than one, making it economical to analyze PHEs with several variables with degrees of freedom (DOF) with respect to the fitness function. The results of optimizing a manifold-microchannel plate heat exchanger are presented, and the exchanger’s performance is compared to more conventional PHE of the same volume utilizing chevron corrugations. Finally, results from the empirical procedure presented in this paper for a manifold-microchannel are compared with experimental measurements in Andhare [5].

In dropwise condensation process, superhydrophobicity is usually achieved by introducing micro/nano-roughness to hydrophobic materials. The analysis of droplets growing and moving and the optimization of the surface structures entails a comprehensive knowledge of the contact line dissipation. However, it in many cases is neglected due to the insufficient understanding, particularly regarding its magnitude and characteristics. In this study, we report a study on the contact line dynamics of water droplets spreading on nano-structured Teflon surfaces. The Teflon surfaces are modeled on Gromacs 5.1.2 and based on the OPLSAA force field. The Teflon model is then validated by examining the glass transition temperature and thermal expansion coefficient. Patterned pillars are created by a confined layer method. The contact line dynamics of water on as-formed surfaces with different solid fraction is then analyzed using the molecular kinetic theory modified by incorporating both viscous damping and solid-liquid retarding. The unit displacement length of contact line is demonstrated to be a constant value of 0.605 nm on both flat and pillar-arrayed surfaces. The contact line friction coefficient is calculated to be on the same order of magnitude with the dynamic viscosity of water, and can be significantly decreased on superhydrophobic surfaces as a result of reduced liquid-solid contact, although contact line experiences stronger resistance on a single pillar.

Drag reduction in fluid flows using the concept of a super hydrophobic surface has recently gained attentions from several researchers. The hydrophobic surfaces developed are inspired by the non-wetting properties of a lotus leaf. They find several applications in areas like, self-cleaning surfaces, mixing in laminar flows and others. In this paper, computational studies were done for isothermal pure water along with the focus in the surface optimization. Different possible geometries are investigated with the use of commercial computational fluid dynamics code. Parametric study on the geometrical variations of the surface is the main discussion of the current paper, as well as their effects on the wetting. Some of the geometrical variations are the square, rectangular, and isosceles triangular groove surfaces. The drag reduction was found to increase by increasing the roughness spacing and decreasing the roughness height irrespective of the type of the surface geometry.

Heat transfer is a naturally occurring phenomenon which can be greatly enhanced by introducing longitudinal vortex generators (VGs). As the longitudinal vortices can potentially enhance heat transfer with small pressure loss penalty, VGs are widely used to enhance the heat transfer of flat-plate type heat exchangers. However, there are few researches which deal with its thermal optimization. Three dimensional numerical simulations are performed to study the effect of angle of attack and attach angle (angle between VG and wall) of vortex generator on the fluid flow and heat transfer characteristics of a flat-plate channel. The flow is assumed as steady state, incompressible and laminar within the range of studied Reynolds numbers ( Re = 380, 760, 1140). In the present work, the average and local Nusselt number and pressure drop are investigated for Rectangular vortex generator (RVG) with varying angle of attack and attach angle. The numerical results indicate that the heat transfer and pressure drop increases with increasing the angle of attack to a certain range and then decreases with increasing angle of attack. Moreover, the attach angle also plays an importance role; a 90° attach angle is not necessary for enhancing the heat transfer. Usually, heat transfer enhancement is achieved at the expense of pressure drop penalty. To find the optimal position of vortex generator to obtain maximum heat transfer and minimum pressure drop, the data obtained from numerical simulations are used to train a BRANN (Bayesian-regularized artificial neural network). This in turn is used to drive multi-objective genetic algorithm (MOGA) to find the optimal parameters of VGs in the form of Pareto front. The optimal values of these parameters are finally presented.

Constructal principles are used to investigate the optimization of material utilization in a metal matrix heat sink that maximizes the total heat transfer rate through the base of heat sink. This approach utilizes a two-dimensional geometry to examine spatial heat flow and optimal material distribution in a metal matrix in the plane perpendicular to the coolant flow direction. The matrix is composed of multiple layers of conductive tees built up from the smallest constituent, the unit T-cell. The unit cell consists of a conductive tee-shaped geometry with the two rectangular void regions each making up half of a cooling channel. The horizontal boundaries must match the temperature and heat flux at the boundaries of the neighboring unit cells as this is a conjugate conduction/convection problem. The geometry of the unit cell is characterized by aspect ratios of channel width to height, overall cell width to height, and channel height to cell height. The matrix structure is assembled by stacking unit cells into multiple layers where the number of cells in each layer is an integer multiple of the cells contained in the lower layer. The solution is obtained for optimal T-cell geometric parameters under a set of predetermined constraints including overall volume, solid fill fraction, and number of layers. When a large number of stacked unit cells are considered, the results describe the ideal spatial distribution of porosity and pore sizes for two dimensional functionally graded metal-matrix heat sink. These results will lead to a better understanding of the role played by the porosity distribution in a metal-matrix heat sink and may be applied to the analysis, optimization, and design of more effective heat sinks.

Thermal energy storage units based on phase change materials (PCMs) need a fine design of highly conductive fins to improve the average heat transfer rate. In this paper, we seek the optimal distribution of a highly conductive material embedded in a PCM through a density-based topology optimization method. The phase change problem is solved through an enthalpy-porosity model, which accounts for natural convection in the fluid. Results show fundamental differences in the optimized layout between the solidification and the melting case. Fins optimized for solidification show a quasi-periodic pattern along the angular direction. On the other hand, fins optimized for melting elongate mostly in the bottom part of the unit leaving only two short baffles at the top. In both cases, the optimized structures show non-intuitive details which could not be obtained neglecting fluid flow. These additional features reduce the solidification and melting time by 11 % and 27 % respectively compared to a structure optimized for diffusion.

Carbon monoxide (CO) boilers play an important role in the petroleum refining industry, completing the combustion of CO in the flue gas generated by the regeneration of fluidized cracking catalyst. The heat released by the CO combustion is used to generate steam for use in the refinery. The flue gas flow path can have a significant effect on the thermal efficiency and operation safety of the boiler. In this paper, a CO boiler which had been experiencing low thermal efficiency and high operation risks was studied. A three-dimensional (3D) computational fluid dynamics (CFD) model was developed with detailed description on the combustion process, flow characteristics and heat transfer. The results obtained from the model have good agreement with the plant measurement data. The heat transfer between the tubes and the combustion flue gas was optimized by adding a checker wall.

Heat and water recovery using Transport Membrane Condenser (TMC) based heat exchangers is a promising technology in power generation industry. In this type of innovative heat exchangers the tube walls are made of a nano-porous material and have a high membrane selectivity which is able to extract condensate water from the flue gas in the presence of the other non-condensable gases such as CO 2 , O 2 and N 2 . Considering the fact that for industrial applications, a matrix of TMC heat exchangers with several TMC modulus in the cross section or along the flow direction is necessary. Numerical simulation of multi-stage TMC heat exchanger units is of a great importance in terms of design, performance evaluation and optimization. In this work, performance of a two-stage TMC heat exchanger unit has been studied numerically using a multi-species transport model. In order to investigate the performance of the two-stage TMC heat exchanger unit, parametric study on the effect of transversal and longitudinal pitches in terms of heat transfer, pressure drop and condensation rate inside the heat exchangers have been carried out. The results indicate that the heat transfer and condensation rates both increase by reducing TMC tube pitches in the second stage and increasing the number of TMC tube pitches in the first stage of the units.

Nanofluids are a class of fluids with nanoparticles suspended in a base fluid. The aim for using nanofluids is often to improve the thermophysical properties of the base fluid so as to enhance the energy transfer efficiency. As the technology develops; the size of devices and systems needs to get smaller to fulfill the engineering requirements and/or to be leading among competitors. The use of nanofluids in heat transfer applications seems to be a viable solution to current heat transfer problems, albeit with certain limitations. As an enhancing factor for the thermal conductivity of the base fluid, nanofluids are considered to be use in cooling system applications. For these applications, the base fluid, the refrigerant, exists as a two-phase liquid-vapor mixture in parts of the refrigeration cycle. To analyze, design and optimize the cycle in such applications, the thermophysical properties of the refrigerant based nanofluids for two-phase flow of refrigerant are needed. There are different models present in the literature derived for the thermophysical properties of nanofluids. However, a majority of the existing models for nanofluid thermophysical properties have been proposed for water- and other liquids-based nanofluids, through theoretical, numerical and experimental research. Therefore, the existing models for determination of the nanofluid thermophysical properties are not applicable for refrigerant based nanofluid applications when the results are compared. Thus, in this work, a new model is derived for the thermal conductivity and viscosity of refrigerant based nanofluids, using existing data from both heat transfer and thermophysical property measurement experiments. The effect of the nanoparticles on heat transfer in two phase flow of the refrigerant is considered by applying the two phase heat transfer correlations in the literature to experimental data. As a result, the thermophysical properties of the known states are determined through known heat transfer performance. Even though the model is developed from the analysis of flow in an evaporator and flow in a single tube with evaporating refrigerant, it is aimed to cover the flows in both evaporator and condenser sections in a vapor compression refrigeration cycle to provide the necessary models for thermophysical properties in heat transfer devices which will allow the design of both cycle and evaporator or condenser in terms of sizing and rating problems by performing heat transfer analysis and/or optimization. The model can also be improved by considering the effects of slip mechanisms that lead to slip velocity between the nanoparticle and base fluid.

Two time-dependent mathematical and numerical models with different levels of complexity and fidelity were developed to investigate the melting of a phase change material (PCM) configured as a number of aluminum-encased, PCM-filled slabs with embedded micro-channel aluminum tubes, and with parallel air-flow passages interposed between the slabs. Melting was first analyzed with the COMSOL Multiphysics ® finite-element model (FEM) in a 2-D domain representing a full-size slab. The melting process is simulated via the apparent heat capacity method. The model captures the effect of natural convection in the PCM melt as well as the conjugate heat transfer through the aluminum tubes. A fast-executing quasi 2-D reduced-order model (ROM) was developed for repetitive design optimization studies. The ROM relies on a time-dependent 1-D closed-form solution of the heat conduction equation in a melting PCM, coupled with variations of the air temperature and heat transfer coefficient. Consequently, the FEM results were employed to develop corrections to the ROM. The corrected ROM was then utilized to study the melting process in a multi-slab thermal storage device that is designed to freeze the PCM at night and release 500 W-h of cooling over a span of ∼10 h during the day.

Patterned thin film structures can offer spectrally selective radiative properties that benefit many engineering applications including photovoltaic energy conversion at extremely efficient scales. Inverse design of such structures can be expressed as an interesting optimization problem with a specific regime of complexity; namely moderate number of optimization parameters but highly time-consuming forward problem. For problems like this, a search technique that can somehow learn and parameterize the multi-dimensional behavior of the objective function based on past search points can be extremely useful in guiding the global search algorithm and expediting the solution for such complexity regimes. Based on this idea, we have developed a novel search algorithm for optimizing absorption coefficient of visible light in a multi-layered silicon-based nano-scale thin film solar cell. The proposed optimization algorithm uses a machine-learning predictive tool called regression-tree in an intermediary step to learn (i.e. regress) the objective function based on a previous generation of random search points. The fitted model is then used as a guide to resample from a new generation of candidate solutions with a significantly higher average gain. This process can be repeated multiple times and better solutions are obtained with high likelihood at each stage. Through numerical experiments we demonstrate how in only one resampling stage, the propose technique dominates the state-of-the-art global search algorithms such as gradient based techniques or MCMC methods in the considered nano-design problem.

Two time-dependent mathematical and numerical models with different levels of complexity and fidelity were developed to investigate the freezing of a PCM configured as a slab with an embedded serpentine microchannel evaporator of a vapor compression refrigeration system. The time-dependent PCM freezing process was first analyzed using finite-element modeling (FEM) of a representative 2-D domain. This model incorporates 2-D conduction and natural convection within the molten PCM. The FEM revealed that natural convection is negligible and that the freezing front advances in essentially 1-D fashion. However, the long execution time of FEM makes it unsuitable for repetitive design optimization of thermal storage devices. Consequently, a fast-executing quasi 2-D reduced-order model (ROM) was developed. The ROM is then utilized to study the freezing process in a multi-slab thermal storage device that is designed to store ∼500 W-h of “cooling” during ∼8 h of freezing operation at night, to be subsequently released for local cooling of room air during the day. The results show that (1) freezing rate is strongly affected by the frozen PCM thermal conductivity; (2) freezing almost ceases once the refrigerant is fully evaporated; (3) refrigerant exit quality drops precipitously toward the end of the freezing cycle.

In the Compressed Air Energy Storage (CAES) approach, air is compressed to high pressure, stored, and expanded to output work when needed. The temperature of air tends to rise during compression, and the rise in the air internal energy is wasted during the later storage period as the compressed air cools back to ambient temperature. The present study focuses on designing an interrupted-plate heat exchanger used in a liquid-piston compression chamber for CAES. The exchanger features layers of thin plates stacked in an interrupted pattern. Twenty-seven exchangers featuring different combinations of shape parameters are analyzed. The exchangers are modeled as porous media. As such, for each exchanger shape, a Representative Elementary Volume (REV), which represents a unit cell of the exchanger, is developed. The flow through the REV is simulated with periodic velocity and thermal boundary conditions, using the commercial CFD software ANSYS FLUENT. Simulations of the REVs for the various exchangers characterize the various shape parameter effects on values of pressure drop and heat transfer coefficient between solid surfaces and fluid. For an experimental validation of the numerical solution, two different exchanger models made by rapid prototyping, are tested for pressure drop and heat transfer. Good agreement is found between numerical and experimental results. Nusselt number vs. Reynolds number relations are developed on the basis of pore size and on hydraulic diameter. To analyze performance of exchangers with different shapes, a simplified zero-dimensional thermodynamic model for the compression chamber with the inserted heat exchange elements is developed. This model, valuable for system optimization and control simulations, is a set of ordinary differential equations. They are solved numerically for each exchanger insert shape to determine the geometries of best compression efficiency.

Heat exchangers using in-tube condensation have great significance in the refrigeration, automotive and process industries. Effective heat exchangers have been rapidly developed due to the demand for more compact systems, higher energy efficiency, lower material costs and other economic incentives. Enhanced surfaces, displaced enhancement devices, swirl-flow devices and surface tension devices improve the heat transfer coefficients in these heat exchangers. This study is a critical review on the determination of the condensation heat transfer coefficient of pure refrigerants flowing in vertical and horizontal tubes. The authors’ previous publications on this issue, including the experimental, theoretical and numerical analyses are summarized here. The lengths of the vertical and horizontal test sections varied between 0.5 m and 4 m countercurrent flow double-tube heat exchangers with refrigerant flowing in the inner tube and cooling water flowing in the annulus. The measured data are compared to theoretical and numerical predictions based on the solution of the artificial intelligence methods and CFD analyses for the condensation process in the smooth and enhanced tubes. The theoretical solutions are related to the design of double tube heat exchangers in refrigeration, air conditioning and heat pump applications. Detailed information on the in-tube condensation studies of heat transfer coefficient in the literature is given. A genetic algorithm (GA), various artificial neural network models (ANN) such as multilayer perceptron (MLP), radial basis networks (RBFN), generalized regression neural network (GRNN), and adaptive neuro-fuzzy inference system (ANFIS), and various optimization techniques such as unconstrained nonlinear minimization algorithm-Nelder-Mead method (NM), non-linear least squares error method (NLS), and Ansys CFD program are used in the numerical solutions. It is shown that the convective heat transfer coefficient of laminar and turbulent condensing film flows can be predicted by means of theoretical and numerical analyses reasonably well if there is a sufficient amount of reliable experimental data. Regression analysis gave convincing correlations, and the most suitable coefficients of the proposed correlations are depicted as compatible with the large number of experimental data by means of the computational numerical methods.