Physics-Based Deep Learning for Flow Problems

It is the tradition for the fluid community to study fluid dynamics problems via numerical simulations such as finite-element, finite-difference and finite-volume methods. These approaches use various mesh techniques to discretize a complicated geometry and eventually convert governing equations into finite-dimensional algebraic systems. To date, many attempts have been made by exploiting machine learning to solve flow problems. However, conventional data-driven machine learning algorithms require heavy inputs of large labeled data, which is computationally expensive for complex and multi-physics problems. In this paper, we proposed a data-free, physics-driven deep learning approach to solve various low-speed flow problems and demonstrated its robustness in generating reliable solutions. Instead of feeding neural networks large labeled data, we exploited the known physical laws and incorporated this physics into a neural network to relax the strict requirement of big data and improve prediction accuracy. The employed physics-informed neural networks (PINNs) provide a feasible and cheap alternative to approximate the solution of differential equations with specified initial and boundary conditions. Approximate solutions of physical equations can be obtained via the minimization of the customized objective function, which consists of residuals satisfying differential operators, the initial/boundary conditions as well as the mean-squared errors between predictions and target values. This new approach is data efficient and can greatly lower the computational cost for large and complex geometries. The capacity and generality of the proposed method have been assessed by solving various flow and transport problems, including the flow past cylinder, linear Poisson, heat conduction and the Taylor–Green vortex problem.</jats:p

The preparation and application of mesoporous materials for energy storage

Designing new energy storage system is necessary for renewable energy development. With the large surface area and appropriate pore structure for good electrolyte wetting and rapid ionic motion, electric double layer capacitors (EDLC), as an ultracapacitor, have the potential to meet this challenge. As the constructing materials for EDLC, the prepration of ordered mesoporous materials, including silica-based mesoporous materials, carbon nitride, ordered mesoporous carbons as well as metal oxides, are summarized. Further researches on pore size control and morphology control of mesoporous materials have also been reviewed. These mesoporous materials, with high surface area, narrow distribution of pore size, good corrosion resistance, high stability, and tunable pore structure and easy surface modification, are widely used as electrocatalyst support and electrode in EDLC. The large surface area and small pore diameter can improve the specific capacitance. The tunable pore structure and surface functionalization are beneficial for capacitance improvement

Experimental study of cold inflow effect on a small natural draft dry cooling tower

The heat rejection rate of natural draft dry cooling tower, as well as the operating performance of a power plant, can be affected by numerous ambient factors. The cold inflow is an unfavourable air turbulence at the top of the cooling tower and has a significant negative effect on the performance of natural draft cooling towers. In the present research, results are given for a 20 m high natural draft dry cooling tower experimental system tested at different ambient conditions. Several events of cold air incursion into the top of the cooling tower are identified and the detailed experimental data are presented. The experimental data show that this effect could seriously impair the thermal performance of the cooling tower. The water outlet temperature of the cooling tower has increased by as much as to 3 °C in these tests because of the cold inflow effect. The mechanism and the solution are discussed based on the experimental data. The findings in this paper can lay an important foundation for future small natural draft cooling tower design and operation

The achievement, significance and future prospect of China's renewable energy initiative

China's high-speed economic growth and ambitious urbanization depend heavily on the massive consumption of fossil fuel. However, the over-dependence on the depleting fossil fuels causes severe environmental problems, making China the largest energy consumer and the biggest CO emitter in the world. Faced with significant challenges in terms of managing its environment and moving forward with the concept of sustainable economic development, the Chinese government plans to move away from fossil fuels and rely on renewables such as hydropower, wind power, solar power, biomass power and nuclear power. In this paper, the current status of China's renewable energy deployment and the ongoing development projects are summarized and discussed. Most recent developments of major renewable energy sources are clearly reviewed. Additionally, the renewable energy development policies including laws and regulations, economic encouragement, technical research and development are also summarized. This study showcases China's achievements in exploiting its abundant domestic renewable energy sources to meet the future energy demand and reducing carbon emissions. To move toward a low carbon society, technological progress and policy improvements are needed for improving grid access (wind), securing nuclear fuel supplies and managing safety protocols (nuclear), integrating supply chains to achieve indigenous manufacture of technologies across supply chains (solar). Beyond that, a preliminary prediction of the development of China's future renewable energy developments, and proposes targeted countermeasures and suggestions are proposed. The proposal involves developing smart-grid system, investing on renewable energy research, improving the feed-in tariff system and clarifying the subsidy system

Python code supporting 'Physics-informed Deep Learning for Simultaneous Surrogate Modelling and PDE-constrained Optimization'

Python code; single fileRoyal Society (grant number NIF\R1\192317) Marie Sklodowska-Curie grant agreement No 76626

Cavitation in diesel fuel injector nozzles and its influence on atomization and spray

In combustors, high-pressure fuel injector nozzles are employed for liquid atomization and spray generation. The internal flow within nozzles, especially cavitation, plays an important role in promoting the breakup of liquid jets. The formation mechanism and evolvement of cavitation are reviewed and described. Different cavitation regimes were characterized experimentally and the positive effect of cavitation on liquid atomization was confirmed. Different empirical formulas correlating the discharge coefficient with fluid-dynamical parameters are summarized. The applicability, advantages, and disadvantages of two popular computational models for flow modeling, i.e., the interface tracking model and the homogeneous equilibrium model, are reviewed. The effects of cavitation on the generated spray are discussed

A review on the performance evaluation of natural draft dry cooling towers and possible improvements via inlet air spray cooling

Concentrating solar power (CSP) plants make use of the renewable and inexhaustible solar energy to produce electricity. Limited by the scarce water resources, CSP plants built in arid areas choose Natural Draft Dry Cooling Tower (NDDCT) to remove waste heat. However, NDDCT suffers from low efficiency in hot summer days. To resolve this problem, inlet air spray-cooling is introduced to improve the performance of NDDCT. In the first part of this paper, the research progress focused on both the theoretical and experimental studies on NDDCT are summarized. Then, in the second part, the spray cooling system consisting of various kinds of spray nozzles are described. Various nozzles produce different spray patterns such as flat-fan, hollow cone, full cone and solid jet. These spray patterns are characterized by flow rate, pressure, mean droplet size and droplet size distribution. Furthermore, the mathematical models correlating the cooling tower performance with the droplet evaporation process are used to predict the spray cooling performance and are summarized here. Finally, predictive results are presented to evaluate the performance of the pre-cooling system. The results illustrate that the inlet air pre-cooling would improve the efficiency of NDDCT and thus reduce power generation loss under high-ambient air temperature conditions. More research should be conducted to develop a practical NDDCT-based spray cooling system for industrial applications

Numerical and experimental study on the spray characteristics of full-cone pressure swirl atomizers

Numerical and experimental studies have been performed to investigate the macroscopic spray structure and spray characteristics of sprays generated by a full-cone pressure swirl atomizer. The simulation employs Eulerian-Lagrangian scheme to account for the multiphase flow and the linearized instability sheet atomization model to predict film formation, sheet breakup and atomization. Reynolds-Averaged Navier–Stokes (RANS) equations are solved for turbulent gas flow. The model predictions show great consistency with the experimental measurements of the spatial variation of the droplet size and velocity obtained from Phase Doppler Particle Analyser (PDPA). The robustness of this model makes it useful to predict the structures and characteristics of co-flow sprays produced by pressure-swirl atomizers. This particular spray is quite important in spray cooling application but is not extensively studied. The study reveals that the entrainment effect and intense central-region atomization cause small droplets to concentrate on the spray axis and large droplets to dominate in the peripheral region of the spray. This finding is consistent with the observation that turbulence kinetic energy of air is maximum near the nozzle exit, where atomization is intense and momentum exchange is strong, and gradually decreases in both radial and axial directions. Moreover, the drops inside the full cone are relatively small, and evaporate more easily than their large counterparts in the peripheral region, hence removing substantial sensible heat from surrounding air and creating low-temperature region in the central of the spray

Investigations on the influence of nozzle arrangement on the pre-cooling effect for the natural draft dry cooling tower

Natural draft dry cooling tower (NDDCT), with little water usage, is a primary choice for power plants in dried regions. However, the increased ambient temperature during summer days decreases the cooling performance of NDDCT. Inlet air pre-cooling is used to alleviate the tower deterioration by making use of water evaporation to remove excess heat from inlet air. To achieve the maximal cooling effect, the injection heights, radial distances and injection directions of employed nozzle LNN1.5 were studied based on the CFD results. The study shows that lower nozzle placement can cool the central part of the radiator While the higher one cools the middle part. Additionally, the increasing extended length can boost the evaporation process of generated spray. Moreover, the upward and co-flow injections have poorer performance than the downward and counter-flow injections. Furthermore, an introduction of wall cover changes the flow field and drives the pre-cooled air flow through the edge of radiator. Since the wall cover reduces the blockage caused by the near-wall vortex the resultant low-temperature region move outwardly. (C) 2017 Elsevier Ltd. All rights reserved