Air Density Research Articles

Water-Glass-Assisted Foaming in Foamed Glass Production

The energy efficiency of buildings can be greatly improved by decreasing the energy embodied in installed materials. In this contribution, we investigated the possibility of foaming waste bottle glass in the air atmosphere with the addition of water glass, which would reduce the energy used in the production of foamed glass boards. The results show that with the increased addition of water glass, the crystallinity and the thermal conductivity decrease, however, the remaining crystal content prevents the formation of closed-porous foams. The added water glass only partly protects the carbon from premature oxidation, and the foaming mechanism in the air is different than in the argon atmosphere. The lowest obtained foam density in the air atmosphere is 123 kg m−3, while the lowest thermal conductivity is 53 mW m−1 K−1, with an open porosity of 50% for the sample obtained in the air, containing 12 wt% of water glass, 2 wt% of B2O3, 2 wt% AlPO4 and 2 wt% K3PO4.

50 years of Geldart classification

The Geldart classification reported in 1973 is widely acknowledged as one of the seminal papers on fluidization. Today, it remains the most used classification for particle fluidization. This is a simple comparison of the differential between particle and air densities versus Sauter-mean diameter, which successfully demarcates all particles into four distinctly different fluidization behaviors. To commemorate the 50th anniversary of this classification, an overview of the fluidization characteristics of the four Geldart groups is presented along with other such classifications, providing perspectives on why the Geldart classification is so universal. Some of the precautions that need to be considered when using this classification are also highlighted. This study is a tribute to the Geldart classification and is expected to be valuable as a summary of the advancements in the understanding of the Geldart groups to date.

Density and magnetic field strength dependence of radio pulses induced by energetic air showers

We have studied the effect of changing the density and magnetic field strength in the coherent pulses that are emitted as energetic showers develop in the atmosphere. For this purpose we have developed an extension of ZHS, a program to calculate coherent radio pulses from electromagnetic showers in homogeneous media, to account for the Lorentz force due to a magnetic field. This makes it possible to perform quite realistic simulations of radio pulses from air showers in a medium similar to the atmosphere but without variations of density with altitude. The effects of independently changing the density, the refractive index and the magnetic field strength are studied in the frequency domain for observers in the Cherenkov direction at far distances from the shower. This approach is particularly enlightening providing an explanation of the spectral behavior of the induced electric field in terms of shower development parameters. More importantly, it clearly displays the complex scaling properties of the pulses as density and magnetic field strength are varied. The usually assumed linear behavior of electric field amplitude with magnetic field strength is shown to hold up to a given magnetic field strength at which the extra time delays due to the deflection in the magnetic field break it. Scaling properties of the pulses are obtained as the density of air decreases relative to sea level. A remarkably accurate scaling law is obtained that relates the spectra of pulses obtained when reducing the density and increasing the magnetic field.

Numerical Simulation of Atomization Characteristics of Perfluorohexanone under Low-Pressure Environment

Since perfluorohexanone can play a role in cooling and extinguishing the heat loss of lithium batteries, it is urgent to study the atomization characteristics of perfluorohexanone in different ambient pressures (49 kPa, 75 kPa, 101 kPa) to ensure the flight safety of all-electric aircraft in the future and the storage and use the safety of lithium-ion battery in high plateau areas. The process of the primary and secondary breakup was studied by using the VOF-DPM model, and the influence of different environmental pressures on the development of atomization and its atomization characteristics was analyzed. The results showed that the primary breakup of the perfluorohexanone liquid sheet was caused by Kelvin Helmholtz/Rayleigh-Taylor (KH-RT), while the secondary breakup was mainly caused by RT instability. Under different environmental pressures, the Sauter Mean Diameter of (D32) along the spray axis decreases sharply at first and then increases slowly. As the air density decreases with the decrease of air pressure, D32 gradually increases, resulting in the decrease of atomization mass. Moreover, when the atomization drops from 101 kPa to 49 kPa, D32 of droplets increases by 38% to 51%, which is conducive to providing evidence for the effectiveness of perfluorohexanone in fire extinguishing under low-pressure conditions.

Deep Neural Network for Visual Localization of Autonomous Car in ITS Campus Environment

Intelligent Car (I-Car) ITS is an autonomous car prototype where one of the main localization methods is obtained through reading GPS data. However the accuracy of GPS readings is influenced by the availability of the information from GPS satellites, in which it often depends on the conditions of the place at that time, such as weather or atmospheric conditions, signal blockage, and density of a land. In this paper we propose the solution to overcome the unavailability of GPS localization information based on the omnidirectional camera visual data through environmental recognition around the ITS campus using Deep Neural Network. The process of recognition is to take GPS coordinate data to be used as an output reference point when the omnidirectional camera takes images of the surrounding environment. Visual localization trials were carried out in the ITS environment with a total of 200 GPS coordinates, where each GPS coordinate represents one class so that there are 200 classes for classification. Each coordinate/class has 96 training images. This condition is achieved for a vehicle speed of 20 km/h, with an image acquisition speed of 30 fps from the omnidirectional camera. By using AlexNet architecture, the result of visual localization accuracy is 49-54%. The test results were obtained by using a learning rate parameter of 0.00001, data augmentation, and the Drop Out technique to prevent overfitting and improve accuracy stability.

Primary Spontaneous Pneumothorax In Healthy Tall and Thin Male Secondary to Smoking: A Case Report and Literature Review

Background: Primary Spontaneous Pneumothorax (PSP) refers to the collapse of a lung without any underlying disease and is commonly observed in tall, thin young men, with smoking as an under-recognized risk factor. The management of PSP can vary significantly across different health centers. This case report highlights a young man with a pneumothorax without an underlying illness but has a smoking habit who initially gets treatment with an insertion of a chest tube.Case: This study focused on a 19-year-old man complaining of sudden right chest pain. The patient was a smoker for the past four years, and the examination showed hypersonic and vesicular loss on the right side. The laboratory tests revealed normal limits, and the sputum indicated the absence of tuberculosis. Chest X-ray showed an avascular radiolucent area in the right lung, and a Chest CT scan confirmed the presence of a hypodense area of air density in the right hemithorax. Right PSP was diagnosed and managed using a chest tube drainage on admission. After four days of treatment, he exhibited improvement and was discharged. A recurrence of pneumothorax was not discovered in the subsequent six-month follow-up period.Conclusion: Despite being a rare disorder, PSP should be considered during the physical examination of patients. It is also important to reassess the risk factors that can contribute to the onset of pneumothorax. The clinicians should be able to identify PSP and emphasize tall, thin, and young men at greater risk of pneumothorax in a pulmonary emergency.

Strategies of diaspore dispersal investment in Compositae: the case of the Andean highlands.

Understanding diaspore morphology and how much a species invests on dispersal appendages is key for improving our knowledge of dispersal in fragmented habitats. We investigate diaspore morphological traits in high-Andean Compositae and their main abiotic and biotic drivers and test whether they play a role in species distribution patterns across the naturally fragmented high-Andean grasslands. We collected diaspore trait data for 125 Compositae species across 47 tropical high-Andean summits, focusing on achene length and pappus-to-achene length ratio, with the latter as a proxy of dispersal investment. We analysed the role of abiotic (temperature, elevation and latitude) and biotic factors (phylogenetic signal and differences between tribes) on diaspore traits and whether they are related to distribution patterns across the Andes, using phylogenomics, distribution modelling and community ecology analyses. Seventy-five percent of the studied species show small achenes (length <3.3 mm) and 67% have high dispersal investment (pappus length at least two times the achene length). Dispersal investment increases with elevation, possibly to compensate for lower air density, and achene length increases towards the equator, where non-seasonal climate prevails. Diaspore traits show significant phylogenetic signal, and higher dispersal investment is observed in Gnaphalieae, Astereae and Senecioneae, which together represent 72% of our species. High-Andean-restricted species found across the tropical Andes have, on average, the pappus four times longer than the achene, a significantly higher dispersal investment than species present only in the northern Andes or only in the central Andes. Small achenes and high diaspore dispersal investment dominate among high-Andean Compositae, traits typical of mostly three tribes of African origin; but traits are also correlated with the environmental gradients within the high-Andean grasslands. Our results also suggest that diaspore dispersal investment is likely to shape species distribution patterns in naturally fragmented habitats.

Measuring the speed of sound with a pan flute and a smartphone: a half-melodic and totally-didactic experiment

Teaching wave-physics and related phenomena with musical instruments results in a very pleasant and didactic approach for undergraduate students. Music allows teaching concepts such as frequency, amplitude, harmonics, resonance, and so on. In addition, one may use some instruments to calculate other quantities such as the air density or the speed of sound in the air. In this work, we use a conventional bamboo-made panflute and a smartphone to obtain the speed of sound in the air. The method is simple. It consists of making the pipes sound and measuring the frequency of the fundamental harmonic. The frequency is approximately proportional to the inverse of the pipe length and this dependence allows us to obtain the speed of sound quite accurately from the slope of the curve. We compare it with the theoretical value and analyse three possible causes of discrepancy such as the end correction, the air composition, or the straightness of the tubes. The proposed experiment can be carried out completely by the students since it does not involve any danger. In addition, it could be appropriate for undergraduate students or even school students.

Numerical Exploration of Transverse Sonic Jet In Hypersonic Cross-flow

At high altitudes, due to low air density, the control response of highly agile and manoeuvrable aerospace vehicles through conventional aerodynamic surfaces is rather slow and inadequate. The control demand of such vehicles can be met very effectively with high-pressure side jets positioned at different locations of the vehicle. Additionally, as none of the components of passive jet control intrudes in the flow path in a passive state, no additional drag is incurred. CFD methods are increasingly being used to characterize jet-controlled aerospace vehicles. Before using in the design exercise, CFD methods need to be validated against reliable experimental results to find its range of applications and error band. In this work, a recent experimental study of transverse sonic injection into Mach 5 hypersonic stream is numerically explored by solving three-dimensional Reynolds Averaged Navier Stokes (RANS) equations using a commercial CFD solver. The computed surface pressures show a reasonable match with experimental results for different momentum ratios of jet and free stream flows. The predictive capabilities of different turbulence models were assessed. The spreading and penetration characteristics of the injectant are analysed from the computed data. The computed penetration and spreading of the injectant depicts nearly linear dependence with the momentum ratio.

INFORMATION SYSTEM FOR MAKING PC WIRE HEADS WITH PNEUMATIC SYSTEMS IN HEADING MACHINE

Pc wire or Prestressed concrete wire is iron thread with a round cross section and has indentations on its surface. Pc wire is widely used in the construction of buildings or buildings, railway sleepers and piles. This paper discusses the process of making pc wire heads and pneumatic systems that function as driving hammer dies in making pc wire. The aim of the research is to know the work process of making pc wire head (screw iron), calculating the pneumatic system for making pc wire head (screw iron). The data needed in the preparation of this report was obtained by collecting data, namely field studies which are direct data collection. data obtained through direct observation in the field accompanied by a field supervisor then Literature Study where literature study is data collection through literature books, journals, making pc wire heads by cutting pc wire with a diameter of 7.1 mm along 152 mm using a cutting grinder and then clamping it in a vise so that the screw iron does not shift when getting pressure from the die, the die will press the pc wire so that it is formed with a circular diameter of 13 mm and 7 mm thick. From the calculation of the density of dry air, the result is = 87.08 Pa, the result of the hydrostatic calculation is 609.78 Pa, and from the calculation of the Double Acting Cylinder, the result is 254.34 N.

Mars orbit injection via aerocapture and low-thrust nonlinear orbit control

This research proposes a new strategy for Mars orbit injection, based on aerocapture and low-thrust nonlinear orbit control. The range of periapse altitudes that allow aerocapture is identified as a function of the hyperbolic excess velocity at Mars arrival, with reference to a large variety of atmospheric density profiles and different ballistic coefficients. This analysis proves that a safe periares altitudinal range leading to aerocapture in all atmospheric conditions does not exist. Three different correction maneuvers, aimed at avoiding both impact and escape, are identified. After the atmospheric arc, the spacecraft orbit exhibits large dispersions in terms of orbit elements. Therefore, the identification of an effective autonomous guidance strategy, capable of driving the spacecraft toward the desired operational orbit, is mandatory. To do this, low-thrust nonlinear orbit control is proposed as an effective option. A feedback law for the low-thrust direction and magnitude, with saturation of the thrust magnitude, is defined, and is proven to enjoy global stability properties. As a result, the spacecraft travels toward the operational orbit of interest, i.e. either (a) an areostationary orbit, (b) a quasi-synchronous inclined orbit, or (c) a low-altitude, sunsynchronous orbit. Monte Carlo simulations, with stochastic density profiles and uncertain initial conditions, point out that the strategy at hand is successful and allows reducing the overall propellant budget in comparison to direct orbit injection based on chemical propulsion. Moreover, the overall time of flight typically ranges from 45 to 140 days, and therefore it is much shorter than that required with the use of aerobraking. As a last advantage, low-thrust nonlinear orbit control allows achievement of a variety of operational orbits, with great accuracy.

ЭФФЕКТИВНОЕ ИСПОЛЬЗОВАНИЕ АЛЬТЕРНАТИВНОЙ ЭНЕРГИИ ДЛЯ ОСНАЩЕНИЯ ВОЙСКОВЫХ ЧАСТЕЙ И ОТДАЛЕННЫХ НАСЕЛЕННЫХ ПУНКТОВ

The energy that is obtained from nature: from wind, sun, water, etc., is by far the cheapest type of resource and environmentally friendly. As the wind map shows, Kazakhstan’s wind potential provides a direction to promote the use of renewable energy sources as an important means to solve the problems of electricity shortage. The scientific article was published as part of the implementation of the scientific project of grant funding for 2022...2024 IRN № АР148039/0222 «Scientific and technical substantiation of the parameters and development of a wind power plant for the electric power supply of the objects of the Armed Forces, other troops and military formations of the Republic of Kazakhstan» (the study is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan). The article is devoted to the study and use of wind turbines with different parameters depending on climatic conditions, such as wind speed, air density, air pressure, air temperature, etc. The result of the research will be widely used in the design and manufacture of wind turbines in remote settlements and military units.

A Monte Carlo simulation method for probabilistic evaluation of annual energy production of wind farm considering wind flow model and wake effect

The wind energy utilization has attracted worldwide attention. The wind farm is the most important place to convert wind energy into electric energy. The accurate estimation of annual energy production and its uncertainty involves the wind resource assessment and investment risk management for the wind farm. In order to reasonably analyze the uncertainty, a Monte Carlo simulation method is proposed to obtain the annual energy production and its uncertainty for the wind farm. The method proposed in this paper not only includes the uncertainties associated with Weibull distribution parameters, measure-correlation-prediction method, power law exponent, air density and power curve in previous studies, but also incorporates the wind flow model uncertainty and wake effect. Specifically, the method proposed in this paper extrapolates the wind speed from the meteorological mast to each wind turbine in the wind farm based on the uncertainty of the wind flow model. At the same time, the wind speed reduction on the downstream wind turbines due to the wake effect will be considered, which leads to the annual energy production and uncertainty of the whole wind farm. Also, the effectiveness of the proposed method is verified based on the numerical example. The results show that the average annual energy productions of different wind turbines in the wind farm with flat terrain are close, but there are some slight differences among turbines due to the wake effect with the maximum loss of 3.5%. It is also observed that the simulated uncertainty of annual energy production of concerned wind farm is 9.0%, which is larger than 7.48% by square root of the sum of the squares method where correlations among variables are not considered.

Basal melt rates and ocean circulation under the Ryder Glacier ice tongue and their response to climate warming: a high-resolution modelling study

Abstract. The oceanic forcing of basal melt under floating ice shelves in Greenland and Antarctica is one of the major sources of uncertainty in climate ice sheet modelling. We use a high-resolution, nonhydrostatic configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) to investigate basal melt rates and melt-driven circulation in the Sherard Osborn Fjord under the floating tongue of Ryder Glacier, northwestern Greenland. The control model configuration, based on the first-ever observational survey by Ryder 2019 Expedition, yielded melt rates consistent with independent satellite estimates. A protocol of model sensitivity experiments quantified the response to oceanic thermal forcing due to warming Atlantic Water and to the buoyancy input from the subglacial discharge of surface fresh water. We found that the average basal melt rates show a nonlinear response to oceanic forcing in the lower range of ocean temperatures, while the response becomes indistinguishable from linear for higher ocean temperatures, which unifies the results from previous modelling studies of other marine-terminating glaciers. The melt rate response to subglacial discharge is sublinear, consistent with other studies. The melt rates and circulation below the ice tongue exhibit a spatial pattern that is determined by the ambient density stratification.

Emphysematous pyelonephritis and sepsis in a diabetic female patient caused by extended-spectrum beta-lactamase-producing Escherichia coli – case report

Emphysematous pyelonephritis (EPN) is a rare, severe, spontaneous gas-forming infection of renal parenchyma and its surrounding areas. EPN was detected in diabetic patients. A 49-year-old female with type I diabetes mellitus presented with severe thrombocytopenia, acute kidney injury (AKI) and was in need of haemodialysis treatment. She had impaired liver function tests, with active urine sediment, indicating severe upper urinary tract infection with suspected sepsis. The contrast enhanced CT scan of the abdomen showed multiple areas of air density in renal parenchyma and perirenal regions, suggestive of left-side EPN. The blood and urine cultures reported growth of extended-spectrum beta-lactamase (ESBL) producing Escherichia coli. The final diagnosis of emphysematous pyelonephritis complicated with severe sepsis and AKI was established. The patient was managed conservatively with wide-spectrum antibiotics, fluid resuscitation, consistent blood sugar control, and haemodialysis treatment. Percutaneous drainage techniques (PCD) and nephrectomy were postponed because of the initial clinical response to the antibiotics treatment. However, the patient experienced sudden clinical deterioration and died only a few hours after the established diagnosis. An autopsy was not performed upon the patient’s family’s request. EPN should be highly suspected in poorly controlled diabetic patients with urinary tract infection and should be promptly recognized and aggressively treated. The patients with multiple risk factors had high mortality, even with timely diagnosis and combined (conservative and surgical) treatment.

Improvment of combined solar chimney power plant with gas power plant

Recently, several researches have been done to improve the perfomance of solar chimney power plants (SCPP) and increase their low output power during hours when the solar radiation is limited. In this study, by combining a SCPP and a gas power plant, the output power is increased and the power output of the combined power plant can be gained at all hours of the day and night. Pipes are buried under the ground and the outlet hot gas from gas power plant flows through the buried pipes instead of being released into the atmosphere through the stacks. Flowing of hot gas through the buried pipes at the soil under the canopy increases the temperature of soil which is exposed to the solar radiation. Increasing of the soil temperature leads to the growth in the value of air temperature under the canopy. The air density reduces as the air temperature increases which leads to the increase of air velocity and output power. By applying the buried pipes, the output power is not zero during the hours when there is no radiation flux. The results for air temperature, heat loss and output power are studied in detail and it is shown that the use of buried pipes in which hot gas flows leads to the increase of the output power of SCPP by 554%, 208% and 125% at the radiation flux of 200 W/m2, 500 W/m2 and 800 W/m2, respectively.

Exergy and environmental analysis of a novel turbine inlet air cooling technique for power augmentation in a CCPP based on waste energy

Combined cycle power plant (CCPP) play a crucial role in providing electricity worldwide. Therefore, researchers and industrialists always focus on developing and improving its performance. One of the factors that affect the performance of CCPPs is weather conditions. As weather conditions change, the air density of the environment changes, which ultimately affects the production power of the gas turbine (GT) and consequently the CCPP. To mitigate the effects of weather on CCPPs' performance, power augmentation methods are developed. In the present research, a novel technique is proposed to reduce the air temperature entering the GT by recovering waste heat from the exhaust gas. The heat content of the exhaust gas is used as the heat source of an ejector refrigeration cycle (ERC), and the produced cooling capacity is used to cool down the air entering the GT. Exergy and environmental analyses are performed to investigate the proposed method's effect on exergy efficiency, environmental factors, and sustainability index. The results indicate that by the proposed method the power production of the CCPP is increased 6.26%.

Power-Weighted Prediction of Photovoltaic Power Generation in the Context of Structural Equation Modeling

With the popularization of solar energy development and utilization, photovoltaic power generation is widely used in countries around the world and is increasingly becoming an important part of new energy generation. However, it cannot be ignored that changes in solar radiation and meteorological conditions can cause volatility and intermittency in power generation, which, in turn, affects the stability and security of the power grid. Therefore, many studies aim to solve this problem by constructing accurate power prediction models for PV plants. However, most studies focus on adjusting the photovoltaic power station prediction model structure and parameters to achieve a high prediction accuracy. Few studies have examined how the various parameters affect the output of photovoltaic power plants, as well as how significantly and effectively these elements influence the forecast accuracy. In this study, we evaluate the correlations between solar irradiance intensity (GHI), atmospheric density (ρ), cloudiness (CC), wind speed (WS), relative humidity (RH), and ambient temperature (T) and a photovoltaic power station using a Pearson correlation analysis and remove the factors that have little correlation. The direct and indirect effects of the five factors other than wind speed (CC) on the photovoltaic power station are then estimated based on structural equation modeling; the indirect effects are generated by the interaction between the variables and ultimately have an impact on the power of the photovoltaic power station. Particle swarm optimization-based support vector regression (PSO-SVR) and variable weights utilizing the Mahalanobis distance were used to estimate the power of the photovoltaic power station over a short period of time, based on the contribution of the various solar radiation and climatic elements. Experiments were conducted on the basis of the measured data from a distributed photovoltaic power station in Changzhou, Jiangsu province, China. The results demonstrate that the short-term power of a photovoltaic power station is significantly influenced by the global horizontal irradiance (GHI), ambient temperature (T), and atmospheric density (ρ). Furthermore, the results also demonstrate how calculating the relative importance of the various contributing factors can help to improve the accuracy when estimating how powerful a photovoltaic power station will be. The multiple weighted regression model described in this study is demonstrated to be superior to the standard multiple regression model (PSO-SVR). The multiple weighted regression model resulted in a 7.2% increase in R2, a 10.7% decrease in the sum of squared error (SSE), a 2.2% decrease in the root mean square error (RMSE), and a 2.06% decrease in the continuous ranked probability score (CRPS).

Proposed Modification to Increase Main Swept Back Wing Efficiency for Aircraft Aermacchi Siai S211

A winglet is devices attached at the wing tips, used to improve aircraft wing efficiency by reduction influence wing tips vortices and induct drag, increasing lift force at the wing tips and effective aspect ratio without adding greatly to the structural stress and weight in the wing structure. This paper is presented three-dimensional numerical analysis to proposed modification swept back wing by adding Raked winglets devices at the main wing tips belong the two seat trainer aircraft type Aermacchi Siai S211 by using Fluent ANSYS 13 software. CFD numerical analysis process was performed at the same flight boundary conditions indifferent wing angle of attacks with constant air flow velocity V∞ =50 (m/sec), ambient pressure Po=101325 (Pa), ambient temperature To=288.14 (K), and at air density ρo=1.225 (kg\m3) to both proposed wing model and the main aircraft wing model. The results are shown an improvement in aerodynamic parameters including increment lift coefficient to (0.22%-5.95%), reduction drag coefficient to (0.34% - 3.60%), increment wing load efficiency ratio to (2.62% - 7.30%), reduction induct drag coefficient CDi to (7.65% - 13.11%) compared with the main aircraft wing model and achieved an improvement in aircraft flight maneuver abilities and stability controls especially during descent, approach, landing and takeoff with lower speed with shortage runway.

Multi-modal multi-step wind power forecasting based on stacking deep learning model

Wind power is becoming a clean and effective energy source for electric power generation. However, the abnormity, multi-modal, and uncertainty represented in wind power data are commonly undesired. Thus, accurate wind power forecasting is a significant method for keeping the power system operations steady. To solve these issues, a multi-modal multi-step wind power forecasting model is presented. To obtain this, the density-based spatial clustering of applications with noise (DBSCAN) is improved by the k-dimensional tree (kd-tree) for detecting abnormal data. Then, the low-rank matrix fusion method fuses the wind speed, wind direction, and air density modalities for obtaining a unified representation. To further increase model accuracy, we propose a stacking deep learning model (SDLM) for overcoming the uncertainty phenomenon, which contains the bidirectional gated recurrent unit (BGRU) and leaky echo state network (LESN). The final forecasting results are acquired by a meta-learning operator. To validate the accuracy and stability of the presented approach, the inland and offshore wind farm datasets are used for forecasting. The contrastive results demonstrate that the presented model outperforms satisfactory performance in multi-step wind power prediction.