Fluctuation Characteristics Research Articles

Three-Year Analysis of the Rectal Cancer Care Trajectory after the COVID-19 Pandemic.

The global pandemic period from 2020 to 2022 caused important alterations in oncology care. This study aimed to describe the trends and variations in patient characteristics, comorbidities, and treatment approaches during this time in Romania. We conducted a retrospective database search to identify patients with rectal cancer who underwent surgical intervention between 2020 and 2022 and the year 2019, which served as a pre-pandemic period control. This study included 164 patients, with a yearly increase of approximately 10% in surgical interventions noted from 2020 (1709 interventions) to 2022 (2118 interventions), but an overall 34.4% decrease compared with the pre-pandemic period. Notable shifts were observed in the type of surgeries performed, with laparoscopic procedures doubling from 2020 (25%) to 2022 (47.5%), confirming the decrease in emergency presentations during the last year of the COVID-19 pandemic and a recovery to normality with planned, elective interventions. Elective interventions increased significantly in 2022 (79.7%) compared with the previous years (p = 0.043), with a concurrent rise in neoadjuvant therapy uptake in 2022 (35.6%). However, significant alterations in the TNM staging, from 12.5% stage IV cases in 2020 to 25.4% in 2022 (p = 0.039), indicated an increased diagnosis of advanced stages of rectal cancer as the years progressed. There was a significant difference in albumin levels over the years (p = 0.019) and in the American Society of Anesthesiology (ASA) scores (from 6.2% ASA stage IV in 2020 to 16.9% in 2022), denoting an increase in case complexity (p = 0.043). This study reveals a trend of increasing surgical interventions and the prevalence of more advanced stages of rectal cancer during the pandemic years. Despite the subtle fluctuations in various patient characteristics and treatment approaches, notable shifts were documented in the severity at diagnosis and surgery types, pointing toward more advanced disease presentations and changes in surgical strategies over the period studied. Nevertheless, the trends in ICU admission rates and mortality did not alter significantly during the pandemic period.

Flow boiling heat transfer and pressure fluctuation characteristics in a divergent channel with inclined downward-facing heater

The core catcher cooling system is used in nuclear power plant to mitigate the core meltdown accident through flow boiling heat transfer. In order to better understand the flow boiling characteristics in the system, experimental research was conducted on an inclined channel. The flow channel is oriented 15° with a divergent downward-heating surface. The two-phase flow behavior and pressure fluctuations were capture by a high-speed camera and pressure transducer. The inlet mass flux and subcooling effects on flow boiling characteristics were deeply investigated. The inlet mass flux and subcooling conditions are within 100–400 kg/m2s and 1–30 K, respectively. The results showed that the boiling curves shift to the higher wall superheat with the increase of mass flux, and the effect of subcooling is weak. The bubble dynamic images by the high-speed camera showed that the bubbles continue to grow and coalesce during the sliding process along the wall. Large bubble blankets are formed periodically upon the boiling surface beyond a heat flux threshold, and they would undergo a rapid condensation process after departing the heating area, which leads to the liquid reversal and accompanied by strong pressure fluctuations. Further, beyond a certain subcooling and heat flux, two-phase flow instability phenomenon appears, which is characterized by complete condensation of bubble blanket accompanied by pressure shocks, meanwhile, the heat transfer coefficient decreases and the wall superheat increases sharply. The bubble blanket frequency could be obtained by the Fast Fourier Transform analysis of pressure, which is positively correlated with the heat flux and is negatively correlated with the mass flux and subcooling. Furthermore, a dimensionless correlation of reduction factor (RF) was proposed, which directly related the bubble blanket characteristics to the thermal–hydraulic parameters.

STATISTICAL ANALYSIS BY WAVELET LEADERS REVEALS DIFFERENCES IN MULTI-FRACTAL CHARACTERISTICS OF STOCK PRICE AND RETURN SERIES IN TURKISH HIGH FREQUENCY DATA

The price and return time series are two distinct features of any financial asset. Hence, examining the evolution of multiscale characteristics of price and returns sequential data in time domain would be helpful in gaining a better understanding of the dynamical evolution mechanism of the financial asset as a complex system. In fact, this is important to understand their respective dynamics and to design their appropriate predictive models. The main purpose of the current work is to investigate the multiscale fractals of price and return high frequency data in Turkish stock market. In this regard, the wavelet leaders computational method is applied to each high frequency data to reveal its multi-fractal behavior. In particular, the method is applied to a large set of Turkish stocks and statistical results are performed to check for (i) presence of multi-fractals in price and return series and (ii) differences between prices and returns in terms of multi-fractals. Our statistical results show strong evidence that high frequency price and return data exhibit multi-fractal dynamics. In addition, they show evidence of distinct fractal characteristics on different scales between price and return series. Furthermore, our statistical results show evidence of differences in local fluctuation characteristics of price and return time series. Therefore, differences in local characteristics are useful to build specific predictive models for each type of data for better modeling and prediction to generate profits. Besides, we found evidence that both long-range correlations and fat-tail distributions contribute to the multifractality in Turkish stocks. This finding can be attributed to the major role played by international investors in increasing the volatility of Turkish stocks.

Exponential sinusoidal modelling and parameterizing studies for the air temperature waves during underground tunnel ventilation

Air precooling or preheating in underground tunnels is beneficial for reducing air conditioning energy consumption and has been widely used in underground spaces such as hydropower stations and utility tunnels. The fluctuation of the ambient temperature has a significant effect on the precooling and preheating performance of underground tunnels. To explore the fluctuation characteristics of the air temperature in an underground tunnel, field testing was conducted at a hydropower station and an exponential sinusoidal model based on the one-dimensional heat transfer differential equation was established. Comparative analysis has shown that the established model can effectively describe the field air temperature fluctuations in the tunnel. The research results reveal that the air temperature wave propagates along the underground tunnel with a period of 24 h, and the amplitude and average temperature continuously decay from 4.57 °C to 24.87 °C at the tunnel inlet to 0.51 °C and 22.95 °C at the tunnel outlet, respectively, with a delay time of approximately 3 h. Furthermore, the wavelength of the air temperature wave propagating along the underground traffic tunnel is approximately 7912 m, which is longer than the tunnel's actual length of 1000 m. Comparative analysis has verified that the exponential sinusoidal model established in this study has reliable predictive performance, which is beneficial for designing the ventilation and air conditioning system of underground spaces and the utilization strategy of surrounding rock natural energy.

Spatial-temporal tendencies of the ice regime of the Dnipro Cascade reservoirs

Formulation of the problem. Knowledge about the formation, destruction and trends of the ice regime of rivers and reservoirs is very important for hydropower, shipping, fisheries, etc. There are almost no studies that evaluated the trends, homogeneity and stationarity of the ice regime of the Dnipro Cascade reservoirs. At the same time, such research is relevant especially in the conditions of a changing climate. The objective of this paper is evaluation of spatio-temporal trends of a observation series for the ice regime of the Dnipro Cascade reservoirs based on a complex approach using statistical and graphical methods. Methods. The research used statistical methods, namely the Pearson method for establishing of the trend equation in the time series and the correlation coefficient between variables, and the Mann-Kendell statistical non-parametric test for assessing the statistical significance of the trend. Among the graphic methods, the mass curve and residual mass curve were used to assess the homogeneity and stationarity of observation series, respectively, as well as combined chronological graphs for spatial analysis, determination of synchronous and in-phase (or on the contrary) long-term cyclic fluctuations of the ice regime characteristics at various water gauges. The research was carried out based on the observation data for dates of ice appearance, ice freeze-up, ice break-up (i.e., melt onset), ice disappearance for 35 water gauges. Results. According to the Mann-Kendall statistical test, contradictory results were obtained regarding the stationarity of the observation series of the ice regime of the Dnipro Cascade reservoirs. At the same time, according to graphic analysis, such series turned out to be quasi-homogeneous and quasi-stationary, since they have unfinished phases of increase and decrease of long-term cyclical fluctuations. In turn, the cyclic fluctuations are characterized by synchronous and in-phase, which indicates the same temporal and spatial tendencies of the ice regime of six reservoirs. The dates of the appearance of main phases of the ice regime of the Dnipro Cascade reservoirs are characterized by significant variability. Scientific novelty and practical significance. For the first time, modern knowledge about the ice regime characteristics of the Dnipro Cascade reservoirs were obtained based on the simultaneous application of statistical and graphical methods. In addition, the research results can be used for further research, namely any statistical processing (determination of probabilistic characteristics, search for prognostic dependencies, generalizations, etc.).

Research on the Influencing Factors of Chinese Gasoline Price Fluctuation During the COVID-19 Epidemic

Gasoline is an important energy source in China, and the stability of its price lays the foundation for the countrys transportation and industrial development. Therefore, fluctuations in gasoline prices are directly related to the normal operation of the countrys transportation system and industrial production. Since 2020, during the COVID-19 outbreak, Chinas gasoline prices have experienced huge abnormal fluctuations, which have affected the national economy. The purpose of this article is to study what factors have affected gasoline price fluctuations in China during the COVID-19 pandemic and how to solve the problem of excessive fluctuations. This article analyzes the fluctuation characteristics of gasoline prices in China from 2019 to 2023 and lists four factors that affected gasoline price fluctuations through qualitative research. For unexpected fluctuations like this, this article proposes two feasible suggestions, including formulating a stronger environmental protection policy and strengthening international cooperation based on oil exports to stabilize the price of gasoline.

Fluctuation characteristics induced by energetic coherent structures in air-core vortex: The most complex vortex in the tidal power station intake system

The air-core vortex is the most complex vortex in the intake system of tidal power stations. Nearly all power plants prohibit the operation of units with air-core vortices, as these vortices not only contain air but also induce significant inflow fluctuations that can potentially lead to significant damage to the units. The current understanding of the fluctuation characteristics and mechanisms induced by energetic coherent structures in the air-core vortex flow is very limited. To address this, the coupled level-set and volume-of-fluid large-eddy simulations are conducted to investigate the energetic coherent structures that cause power output fluctuations. Two critical frequencies have been identified in the energy spectra of the velocity field: the air-core vortex meandering frequency and the shear vortex shedding frequency. The level and trend of the spectrum density at low frequencies are determined by the large-scale energy structure represented by the air-core vortex. The shear vortices are initially formed from a shear separation layer that eventually evolves into streamwise vortices downstream. When the air-core vortex enters the pipe, it breaks up and merges with the near-wall coherent structures. The enhanced velocity and pressure fluctuations, induced by air-core vortices and coherence structures, are analyzed using the turbulent kinetic energy transport equation, revealing that the production term dominates the development of turbulent kinetic energy. Moreover, the diffusion term is responsible for transferring energy through the evolution of turbulent structures. The energy loss induced by fluctuations is investigated using the entropy production method. We find that the direct dissipation of entropy production is mainly induced by air-core vortices, while the side-wall coherent structures in the pipe contribute to the turbulent dissipation.

A variable-time day-ahead scheduling strategy considering spectrum analysis

To build a new type of power system, the proportion of renewable energy sources with wind and solar energy as the main body has increased into the power grid. Due to the strong randomness and volatility of renewable energy as a power source, thermal power units need to fluctuate frequently to respond to system power requirements. To ensure the smooth operation of the thermal power units, a variable period day scheduling strategy considering spectrum analysis is proposed. Firstly, different dispatching periods are divided according to the characteristics of system net load fluctuation, secondly, to minimize the total cost, the joint dispatching model of wind power, solar energy, thermal power, and energy storage is established to form a day-ahead dispatching plan with variable time period. Finally, an example shows that this strategy can increase the smooth operation of thermal power units and improve the utilization rate of pumped storage units.

Operational Characteristics Assessment of a Wind–Solar–Hydro Hybrid Power System with Regulating Hydropower

Renewable energy generation technology, as an alternative to traditional coal-fired power generation, is receiving increasing attention. However, the intermittent characteristics of wind and solar energy pose certain challenges to the stable operation of power grids. This requires a better understanding of the operational characteristics of renewable energy to improve the comprehensive efficiency. To achieve this, firstly, four indicators (i.e., average fluctuation magnitude, Richards–Baker flashiness, average climbing rate, and change in the time-averaged value) within a single-evaluation-indicator framework are proposed to quantitatively evaluate the fluctuation characteristics of wind, solar, and hydropower and a wind–solar–hydro hybrid power system. Secondly, a comprehensive evaluation indicator is developed by scientifically assigning and recombining the four indicators using entropy weight theory. Furthermore, the comprehensive evaluation index is applied to the wind–solar–hydro hybrid power system to determine the operational characteristics of subsystems and a complementary system at different time scales. Finally, the load tracking coefficient and coupling degree are used to quantify the complementarity degree of the hybrid power system. It is found that the fluctuation degree of the hybrid power system is smaller than that of the individual power system. Meanwhile, both fluctuation and complementary characteristics are strengthened with the increase in time scale. The proposed methods and results shift the volatility from an abstract concept to concrete representation, providing a new perspective and reference for evaluating the operational characteristics of the hybrid power system to achieve power system planning and scheduling.

Analyzing the performance of single-cutter cutting rock under bottom-hole pressure conditions

Addressing the ambiguity surrounding the process of crack initiation and propagation in rock subjected to confining pressure and hydrostatic pressure, this study integrates laboratory experiments with numerical simulations. First, an analysis is conducted on the cutting force, rock fragmentation energy consumption, rock chip size, and distribution of cutting stress in rocks simultaneously exposed to confining pressure and hydrostatic pressure. Subsequently, an internal crack propagation analysis model for rock is established using the finite discrete element method, and the accuracy of this model is verified through experimentation. The process and characteristics of internal crack propagation during the cutting process are analyzed. Lastly, the variation characteristics of cutting forces under different cutting parameter conditions are compared. The findings indicate that, under identical cutting conditions, confining pressure reduces the degree of granite rock fragmentation, increases the presence of powdery rock debris, and mitigates force fluctuation characteristics, leading to an approximate 17% increase in energy consumption of rock breaking. The presence of confining pressure promotes the generation of micro-cracks within the rock, but restricts the expansion of primary cracks. Notably, shear cracks ahead of the cutting cutter and tensile cracks beneath the cutting path are conspicuously diminished, thereby augmenting the difficulty of rock failure. The elevation of confining pressure and cutting depth emerges as the principal factors contributing to elevated cutting forces, with cutting forces exhibiting exponential growth with increasing confining pressure. At a hydrostatic pressure of 9 MPa, cutting forces escalate by 50 %. Moreover, substantial cutting depth induces discontinuity in the rock failure mechanism. Stress during cutting predominantly concentrates in the vicinity of the PDC cutter front and beneath the cutting trajectory, extending along the advancement direction of the PDC cutter and below the cutting path. These results offer valuable insights for optimizing drilling parameters under confining pressure conditions.

Prediction of Water Level in Lakes by RNN-Based Deep Learning Algorithms to Preserve Sustainability in Changing Climate and Relationship to Microcystin

In recent years, intensive water use combined with global climate change has increased fluctuations in freshwater lake levels, hydrological characteristics, water quality, and water ecosystem balance. To provide a sustainable management plan in the long term, deep learning models (DL) can provide fast and reliable predictions of lake water levels (LWLs) in challenging future scenarios. In this study, artificial neural networks (ANNs) and four recurrent neural network (RNN) algorithms were investigated to predict LWLs that were applied in time series such as one day, five days, ten days, twenty days, one month, two months, and four months ahead. The results show that the performance of the Long Short-Term Memory (LSTM) model with a prediction of 60 days is in the very good range and outperforms the benchmark, the Naïve Method, by 78% and the ANN at the significance level (p < 0.05) with an RMSE = 0.1762 compared to other DL algorithms. The RNN-based DL algorithms show better prediction performance, specifically, for long time horizons, 57.98% for 45 days, 78.55% for 60 days, and 58% for 120 days, and it is better to use a prediction period of at least 20 days with an 18.45% performance increase to take advantage of the gated RNN algorithms for predicting future water levels. Additionally, microcystin concentration was tightly correlated with temperature and was most elevated between 15 and 20 m water depths during the summer months. Evidence on LWL forecasting and microcystin concentrations in the context of climate change could help develop a sustainable water management plan and long-term policy for drinking water lakes.

Charging/discharging performance and corrosion behavior of a novel latent heat thermal energy storage device with different fin plate materials

The use of low-grade industrial waste heat for building heating could facilitate the decarbonization of heat sector, which accounts for a large share of energy consumption worldwide. However, the uncontrollable fluctuation characteristics of heat source and mismatch between energy supply and demand greatly limit its large-scale application. Notably, latent heat thermal energy storage (LHTES) technology, showing remarkable advantages in terms of energy storage density, heat storage temperature (nearly constant), technology maturity and cost, could effectively solve the above problem. Hence, this work specially focused on LHTES device that utilized fin plate for improving performance of heat harvesting and reuse. Furthermore, charging/discharging performance and corrosion behavior of a novel device with different fin plate materials (brass, aluminum and stainless steel) were investigated. Results showed that temperature difference between plate surface and melting point above 10 °C effectively shortened charging time more than 45.7 %. A higher thermal conductivity of fin material contributed to a better thermal performance. Aluminum and stainless steel preferred to be used as fin plate materials of targeted hydrated salt owing to their low corrosion rate of 0.016 and 0.002 mg/(cm2·yr), respectively. This work was expected to provide a guidance on designing a LHTES device applied in building heating.

A novel hybrid grey system forecasting model based on seasonal fluctuation characteristics for electricity consumption in primary industry

As a critical economic index, the annual electricity consumption plays an essential role in reflecting the domestic economic environment. For the sustainable development of the electricity power industry, an accurate electricity consumption forecasting model can not only guide the power generation work in advance but also help to determine the regulation law of electricity economic development. To accurately describe the seasonal fluctuation characteristics of electricity consumption in China's primary industry, Fourier modified grey forecasting model based on seasonal fluctuation characteristics and initial condition optimization (FDSGM(1,1,x(β),γ)) was put forward. Based on the empirical data of seasonal electricity consumption in China's primary industry, comparing with SGM(1,1), RSGM(1,1) and DSGM(1,1), the minimum mean absolute percentage errors (MAPEs) in the training set was reduced to 0.2 %, while that in the testing set was also reduced to 6.02 %, which was significantly better than those of the previous three forecasting models and was also markedly better than the prediction accuracy of reference [15]. The results indicated that FDSGM(1,1,x(β),γ) could identify seasonal fluctuations and variations and was a reliable seasonal forecasting tool that could be used to ensure sustainable development of electricity markets.

Multifractal Analysis of Chinese Industry and Stock Markets Fluctuation Under the COVID-19 Pandemic

Researchers and authorities have become increasingly interested in how the COVID-19 pandemic has profoundly impacted the real economy and financial markets around the world since its outbreak in late 2019. Applying the methods of multifractal analysis, this paper investigates the fluctuation characteristics and market risks of Chinese industry and stock markets under the COVID-19 pandemic, and reveals the whole dynamics of industry and stock markets from the perspective of system theory. The empirical results show that the multifractal strength of the industry market has significantly increased during the pandemic with elevated systematic risk, while the situation is different for the stock market. Specifically, the Hurst surfaces generated using the multiscale technique intuitively visualize the dynamical behaviors of the systematic fluctuation of the Chinese industry and stock markets at various scales under the COVID-19 pandemic. Furthermore, it is found that the sources of multifractality of the two types of markets include long-range correlation and fat-tailed distribution, with the contribution of fat-tailed distribution being greater. The chi-square test is promoted in this paper to measure the contribution of the internal components of the multivariate system to the multifractality sources of the whole system, revealing that the real estate industry has a greater impact on the multifractality of the whole industry system, while the Shanghai Composite Index has a stronger influence on the whole stock system.

Unsteady Cavitation Analysis of the Centrifugal Pump Based on Entropy Production and Pressure Fluctuation

A numerical method using combined detached-eddy simulation (DES) and a cavitation model considering the rotation effect is used for unsteady cavitation flow field of the centrifugal pump. A closed-type pump test system was established to obtain the pump performance and pressure pulsation characteristics under different flow rates and cavitation condition, which provide boundary conditions and verification of calculations. Based on the calculation results of the unsteady flow field of the centrifugal pump cavitation, the entropy generation analysis of the flow field and an analysis of the pressure fluctuation characteristics were carried out. Then, we tried to reveal the relationship between cavitation and the deterioration of the centrifugal pump performance and the generation of the unstable operation excitation force. The internal energy loss is mainly concentrated in the impeller, volute, and pump cavity area, which accounts for more than 85% of the total entropy generation. The characteristic frequency of a Strouhal number of about 0.333 appears at the volute tongue due to the cavitation flow spread downstream.

Experimental study of airflow thermal fluctuation properties induced by liquid metal pouring based on schlieren and proper orthogonal decomposition

Understanding the thermal fluctuation characteristics of the induced airflow during liquid metal pouring processes aids in effective control of emissions from metallurgical plants. This study used schlieren and proper orthogonal decomposition (POD) to analyze the thermal fluctuation characteristics of induced airflow during continuous and discontinuous liquid column flow, within the range of Grashof numbers from 2.64 × 105–3.19 × 105, and liquid column discharge rates ranging from 2500 to 3000 mL/min. The results show that the induced airflow exhibited weak turbulence in both continuous liquid column flow (CLCF) and discontinuous liquid column flow (DLCF). Higher Grashof numbers predominantly elevate the induced airflow thermal fluctuation in CLCF, whereas increased liquid column flow rates primarily enhance the induced airflow thermal fluctuation in DLCF. The primary spatial fluctuation region of induced airflow is within a dimensionless distance (X/r') of 1 at the front side of the pouring cup; the dimensionless horizontal thermal fluctuation diameter (d') of the induced airflow around the liquid column is approximately 2.5. The fluctuation frequency of the induced airflow was mainly within the range of 0–5 Hz. The main frequency during the CLCF was greater than 1 Hz; during the DLCF it was less than 1 Hz. Additionally, the root-mean-square values of the schlieren image grayscale demonstrated the potential advantage of identifying regions with pronounced turbulence characteristics. In summary, identifying the primary location and frequency of the induced airflow with different pouring processes is beneficial for developing novel smoke-control technologies, and the experimental methods and induced airflow details are good references for further studies.

Research on fluctuation characteristics of AC interference parameters and corrosion behavior of buried gas pipelines

With the large-scale construction of high-speed railways in China, pipelines are subject to increasingly severe alternating current (AC) interference. It's been found through detection that the AC interference parameters of pipelines near high-speed railways fluctuate greatly. Based on the field test data, this paper statistically analyses the fluctuation law of parameters on the pipeline. On this basis, an indoor simulation experiment was configured to explore the effect of AC current density and cathodic protection potential on dynamic AC corrosion. The results showed that for the same level of cathodic protection, a higher AC current density indicates a higher dynamic AC corrosion rate. When the AC current density increases to 100 A/m2 or higher, the corrosion rate tends to decrease first and then increase with the negative shift of cathodic protection potential. The corrosion risk assessment diagram under dynamic AC interference was drawn through the experiment of field buried coupon experiment and the laboratory simulation experiment. In addition, the mechanism of AC corrosion is discussed to provide a reference for assessing the corrosion risk under dynamic AC interference.

Near-field pressure and wake velocity coherence of a circular cylinder

Aerodynamic noise and unsteady loads resulting from the vortex shedding of a circular cylinder pose significant challenges in engineering applications. Understanding these challenges is closely related to pressure fluctuations on the cylinder surface. This experimental study conducted simultaneous measurements of surface pressure and velocity fluctuations within the subcritical Reynolds number range (14.7×103≤Re≤30×103) to investigate the influence of vortex shedding on near-field pressure. The experiments utilized a highly instrumented cylinder with mini-pressure transducers. The results revealed that surface pressure fluctuations exhibit maximum energy content near the cylinder's shoulders at the fundamental vortex shedding frequency (f0), aligning with pronounced lift fluctuations. The analysis of pressure–velocity coherence indicated that the most energetic flow structures resulting from vortex shedding significantly contribute to generating surface pressure fluctuations at the f0-peak frequency, extending over a considerable distance from the near- to far-wake regions. Additionally, the pressure fluctuations responsible for drag fluctuations are predominantly imposed at the base of the cylinder, primarily at the second harmonic (2f0), arising from flow structures shed at the end of the vortex formation region. Wavelet analysis provided insights into the temporal characteristics of surface pressure fluctuations, revealing amplitude modulation over time with multiple repetitive patches around the f0-peak frequency and close to the cylinder's shoulders, where the highest energy level predominates due to vortex shedding.

Flow Fluctuation during Flow Boiling of Binary Mixtures in High Aspect Ratio Microchannel

Flow boiling performance is affected by several factors, such as channel characteristics and working fluid types. It is found that there is still limited study that discusses the use of binary mixtures combined with high aspect ratio microchannels. The aim of this study is to investigate the flow fluctuation during flow boiling of binary mixtures in rectangular microchannels. Here, a 6 mm width and 0.3 mm depth rectangular channel was utilised, and it represents a hydraulic diameter of 571 μm and an aspect ratio of 20. In the present works, a mass flux of 10 kg m-2 s-1 was used, and the heat flux ranged from 15.2 and 21.0 kW m-2. The image processing technique was applied to track the bubble tail movement. In addition, the thermal camera was utilised to gather the wall temperature distribution of the channel. The preliminary results show that the use of binary mixtures influences the vapour fraction in the channel and the flow fluctuation characteristics. Some differences are observed in terms of wall temperature characteristics. However, the rapid increase of wall temperature is found in the outlet region for high flux cases under all liquid types which suggests the dominance of dry out event.

Visualization of pressure fluctuation characteristics of weapon bay on unmanned aerial vehicle using delayed detached eddy simulation

In the present study CFD simulation with delayed detached eddy simulation (DDES) are performed to investigate pressure fluctuation environment on an open cavity and weapon bay of UAV. The main purpose of this study is to explore the aerodynamic noise level of complex cavities with slant ceiling and irregular length–depth ratio. First, two cases on an open cavity at Ma 0.85 are analyzed to determine the slant ceiling influence, which shows that the sound pressure levels increase by 1 dB due to the transverse flow effect. Then, a typical weapon bay on unmanned aerial vehicle is simulated to investigate the aerodynamic noise environment. The overall sound pressure level in the weapon bay is up to 157 dB, and when the Mach number turns from 0.6 to 0.8, the amplitude of all modes increases about 16–23 dB. The main focuses of this investigation are to discuss the mechanism of noise generation in a slant ceiling cavity and determine the pressure fluctuation characteristic of a typical weapon bay on unmanned aerial vehicle.Graphical abstract