Feature Extraction of Oscillating Flow with Vapor Condensation of Moist Air in a Sonic Nozzle

The sonic nozzle is commonly used in flow measurement. However, the non-equilibrium condensation phenomenon of moist air in the nozzle has a negative effect on the measuring accuracy. To investigate this complex phenomenon, the experiments on the oscillating condensation flow of moist air were conducted by an adjustable humidification apparatus with different relative humidity (0-100%), temperature (30-50° C) and carrier gas pressure (1-6 bar), where the micro size pressure measuring system was designed by Bergh-Tijdeman (B-T) Model. The accurate mathematical model of nonequilibrium condensation was also built and validated by the experimental data of time-averaged pressure distribution. Then, the frequency and intensity of pressure fluctuation of oscillating flow at a wide range of operation condition were obtained combining experimental data and physical simulation model. Importantly, a new semi-empirical relation of dimensionless frequency deduced from dimensionless analysis was identified accurately by experimental data. Finally, the signal nonstationarity was also observed by using the continuous wavelet transform (CWT). The instantaneous frequency saltation and the energy attenuation of pressure signals were observed in the condensation flow

Polydispersed droplet spectrum and exergy analysis in wet steam flows using method of moments

In steam turbine flow, the complex droplet spectrum caused by nonequilibrium condensation is necessary to be modeled accurately to predict the droplet behavior and estimate the exergy destruction and erosion rate. This study built and validated a polydispersed model with Quadrature method of moments (QMOM), consisting of transition SST model, the moments and entropy generation. A spline-based algorithm was used to reconstruct the shape of the probability density function (PDF) of radius. It’s proved that the polydispersed model has a better prediction result for Sauter radius compare with monodispersed model. Then, the distributions of moments and droplet spectra in the nozzle with effects of asymmetric lambda shock and evaporation were investigated. The shape of droplet spectrum is closer to gamma distribution in nucleation zone and log-normal distribution in growth zone when outflow is supersonic. In the turbine, because the oblique shock induces complex evaporation and secondary condensation, the reconstructed shape is closer to gamma distribution. Finally, the obtained maximum exergy destruction is 25.293 kJ/kg. The rate of exergy destruction increases from 1.04% to 4.45%. The range of Baumann factor is 0.574–1.312. Besides, the erosion rate in polydispersed model is only 58.4–64.3% of monodispersed model. The polydispersed model used in this study can predict the droplet spectrum and energy loss of the turbine systems more accurately

Prediction of dehydration performance of supersonic separator based on a multi-fluid model with heterogeneous condensation

Supersonic separation is a novel technology. A multi-fluid slip model for swirling flow with homogenous/heterogenous condensation and evaporation processes in the supersonic separator was built to estimate the separation efficiency. This model solves the governing equations of compressible turbulent gas phase and dispersed homogenous/heterogenous liquid phase considering droplet coalescence and interphase force. Its prediction accuracy for condensation and swirling flows was validated. Then, the flow field, slip velocity and droplet trajectory inside the separators with different swirl strengths were investigated. The maximum values of radial slip velocity are 29.2 and 8.26 m/s for inlet foreign droplet radius of 1.0 and 0.4 micron. It means the larger foreign droplet has a better condensation rate. However, the residence time of larger foreign droplet in core flow is shorten. Thus, the inlet radius of foreign droplet has to be moderate for best separation efficiency. Finally, the dehydration performances of separator were evaluated. The optimal radius of inlet foreign droplet to maximize the dehumidification and efficiency was found. For the separator with swirl strength of 22%, the optimal radius is 0.85 micron at inlet pressure of 250 kPa, where the maximum dew point depression is 42.41 °C and the water removal rate is 87.82%

Synthesis and Operability Strategies for Computer-Aided Process Intensification

Today's chemical process industry is faced with pressing challenges to sustain the increasingly competitive global market with rising concerns on energy, water, food, and environment. Process intensification (PI) offers the potential to address these challenges by realizing step changes in process economics, energy efficiency, and environmental impacts through the development of novel process schemes and equipment. However, early PI breakthroughs mostly relied on Edisonian efforts while lack of theoretic development driving for systematic innovation. Meanwhile, PI technologies bring new challenges such as task-integrated design, new operating conditions, vulnerability to disturbance, etc. Thus, advanced computational and systems-based methods are essential means to support the analysis and optimization of PI systems at the early design stage. In this thesis, we aim to address two key open questions for computer-aided PI: (i) how to systematically generate innovative and intensified process systems? and (ii) how to ensure that the derived intensified designs are operable under varying operating conditions? To answer the first question, we propose a PI synthesis strategy based on the Generalized Modular Representation Framework. A superstructure representation is developed to model chemical processes leveraging modular phenomenological building blocks (i.e., pure heat exchange module, mass/heat exchange module). Novel process structures can be systematically identified to enhance process performance without pre-postulation of equipment design. The proposed approach is further integrated with model-based operability strategies towards a holistic framework for the synthesis of operable process intensification systems. The following operability aspects are investigated with design optimization: (i) multiperiod process synthesis with flexibility considerations to generate design solution with guaranteed feasibility under uncertainty, (ii) inherently safer design by integrating risk analysis metrics as process constraints, and (iii) simultaneous design and control to deliver optimal design with optimal control actions. The applicability and versatility of the framework are demonstrated with a number of real-world applications to deliver intensified operable process systems, e.g. reactive separation, extractive separation with novel materials, dividing wall columns

Droplet impact on the super-hydrophobic surface with micro-pillar arrays fabricated by hybrid laser ablation and silanization process

A super-hydrophobic aluminum alloy surface with decorated pillar arrays was obtained by the hybrid laser ablation and further silanization process. The as-prepared surface showed a high apparent contact angle of 158.2 ± 2.0° and low sliding angle of 3 ± 1°. Surface morphologies and surface chemistry were explored to account for the generation process of super-hydrophobicity. The main aim of this current work is to investigate the maximum spreading factor of water droplets impacting on the pillar-patterned super-hydrophobic surface based on the energy conservation concept. Although many previous studies have investigated the droplet impacting behavior on flat solid surfaces, the empirical models were proposed based on few parameters of the Reynolds number (Re), Weber number (We) as well as the Ohnesorge number (Oh), causing the limitation for the super-hydrophobic surfaces due to the ignorance of geometrical parameters of the pillars and viscous energy dissipation for liquid flow within the pillar arrays. In this paper, the maximum spreading factor was deduced from the perspective of energy balance, and the predicated results were in good consistent with our experimental data with a mean error of 4.99% and standard deviation of 0.10

Comparative Study on Drying Characteristics and Quality of Apple Cubes Dried in Two Different Microwave Dryers

A rotary plate microwave dryer (RMD) and a newly-developed microwave convection coupled dryer (MCD) were used to dry apple cubes. The effects of microwave output power on drying, heating characteristics and quality attributes including scorching rate, color parameters, rehydration ratio, shrinkage, hardness, and sensory scores of the apple cubes were investigated and compared. The results showed that the microwave power required to complete drying in RMD was only 1/6 of that in MCD at the same microwave power density. Total drying time was 120, 60 and 30 min at 70, 210 and 350 W in RMD, respectively, while 160, 90, 80 and 60 min at 400; 800; 1,200; and 1,600 W in MCD, respectively. Compared with the products dried using hot air, the apple cubes dried in both dryers at the low microwave power had better rehydration capacity, less shrinkage and lower hardness as well as a* and b* value of color. Application of microwave power of over 800 W in MCD and over 210 W in RMD caused the increase in scorching rate as well as decreased the L* value and the sensory quality of the apple cubes. Microwave drying in MCD with temperature control improved the quality of the dried product. The microwave drying conditions suitable for the apple cubes were 400 W in MCD and 1,600 W in MCD with temperature control followed by 70 W in RMD; the products obtained under these three condition variants had superior or comparable quality to the products obtained upon conventional hot air-drying

A New Method for Bare Permafrost Extraction on the Tibetan Plateau by Integrating Machine Learning and Multi-Source Information

Bare permafrost refers to permafrost with almost no vegetation on the surface, which is an essential part of the ecosystem of the Tibetan Plateau. An accurate extraction of the boundaries of bare permafrost is vital for studying how it is being impacted by climate change. The accuracy of permafrost and bare land distribution maps is inadequate, and the spatial and temporal resolution is low. This is due to the challenges associated with obtaining significant amounts of data in high-altitude and alpine regions and the limitations of current mapping techniques in effectively integrating multiple factors. This study introduces a novel approach to extracting information about the distribution of bare permafrost. The approach introduced here involves amalgamating a sample extraction method, the fusion of multi-source remote sensing information, and a hierarchical classification strategy. Initially, the available multi-source permafrost data, expert knowledge, and refinement rules for training samples are integrated to produce extensive and consistent permafrost training samples. Using the random forest method, these samples are then utilized to create features and classify permafrost. Subsequently, a methodology utilizing a hierarchical classification approach in conjunction with machine learning techniques is implemented to identify an appropriate threshold for fractional vegetation cover, thereby facilitating the extraction of bare land. The bare permafrost boundary is ultimately derived through layer overlay analysis. The permafrost classification exhibits an overall accuracy of 90.79% and a Kappa coefficient of 0.806. The overall accuracies of the two stratified extractions in bare land were 97.47% and 96.99%, with Kappa coefficients of 0.954 and 0.911. The proposed approach exhibits superiority over the extant bare land and permafrost distribution maps. It is well-suited for retrieving vast bare permafrost regions and is valuable for acquiring bare permafrost distribution data across a vast expanse. It offers technical assistance in acquiring extended-term data on the distribution of exposed permafrost on the Tibetan Plateau. Furthermore, it facilitates the elucidation of the impact of climate change on exposed permafrost

Graphene-Based Nanocomposites for Neural Tissue Engineering

Graphene has made significant contributions to neural tissue engineering due to its electrical conductivity, biocompatibility, mechanical strength, and high surface area. However, it demonstrates a lack of biological and chemical cues. Also, it may cause potential damage to the host body, limiting its achievement of efficient construction of neural tissues. Recently, there has been an increasing number of studies showing that combining graphene with other materials to form nano-composites can provide exceptional platforms for both stimulating neural stem cell adhesion, proliferation, differentiation and neural regeneration. This suggests that graphene nanocomposites are greatly beneficial in neural regenerative medicine. In this mini review, we will discuss the application of graphene nanocomposites in neural tissue engineering and their limitations, through their effect on neural stem cell differentiation and constructs for neural regeneration

Intelligent augmented keyword search on spatial entities in real-life internet of vehicles

Internet of Vehicles (IoV) has attracted wide attention from both academia and industry. Due to the popularity of the geographical devices deployed on the vehicles, a tremendous amount of spatial entities which include spatial information, unstructured information and structured information, are generated every second. This development calls for intelligent augmented spatial keyword queries (ASKQ), which intelligently takes into account the locations, unstructured information (in the form of keyword sets), structured information (in the form of boolean expressions) of 182MinzuAvespatial entities. In this paper, we take the first step to address the issue of processing ASKQ in real traffic networks of IoV environments (ASKQIV) and focus on Top-k ASKQIV queries. To support network distance pruning, keyword pruning, and boolean expression pruning intelligently and simultaneously, a novel hybrid index structure called ASKTI is proposed. Note in the real-life traffic networks of IoV environments, travel cost is not only decided by the network distance, but also decided by some additional travel factors. By considering these additional factors, a combined factor Cftc of each road (edge) in the traffic network of IoV environments is calculated, and weighted network distance is calculated and adopted. Based on ASKTI, an efficient algorithm for Top-k ASKQIV query processing is proposed. Our method can also be extended to handle boolean range ASKQIV Queries and ranking ASKQIV Queries. Finally, simulation experiments on one real traffic network of IoV environments and two synthetic spatial entity sets are conducted. The results show that our ASKTI based method is superior to its competitors.University of Derb