Search Results (19)

High-flow aeroengine transient tests involve strong coupling and external disturbances, which pose significant challenges for intake environment simulation systems (IESSs). This study proposes a compound control scheme that combines fixed-time active disturbance rejection with static decoupling methods. The scheme integrates a fixed-time sliding-mode controller (FT-SMC) and a super-twisting fixed-time extended-state observer (ST-FT-ESO). A decoupling transformation separates pressure and temperature dynamics into two independent loops. The observer estimates system states and total disturbances, including residual coupling, while the controller ensures fixed-time convergence. The method is deployed on a real-time programmable logic controller (PLC) and validated through hardware-in-the-loop (HIL) simulations under representative high-flow scenarios. Compared to conventional linear active disturbance rejection decoupling control (LADRDC), the proposed scheme reduces the absolute integral error (AIE) in pressure and temperature tracking by 71.9% and 77.9%, respectively, and reduces the mean-squared error (MSE) by 46.0% and 41.3%. The settling time improves from over 5 s to under 2 s. These results demonstrate improved tracking accuracy, faster convergence, and enhanced robustness against disturbances. Full article

Altitude Test Facility (ATF) compressor systems are widely used in aero-engine tests. These systems achieve the control of gas pressure and transport through complex operation processes. With advancements in the aviation industry, there is a growing demand for higher performance, greater safety, and more energy efficiency in digital ATF systems. Hybrid modeling is a technology that combines many methods and can meet these requirements. The Modular Dynamic System Greitzer (MDSG) compressor model, including mechanistic and data-driven modeling approaches, is combined with a neural network to obtain a BPNN-MDSG hybrid modeling method for the digital turbine system. The digital simulation is linked with the physical sensors of the ATF system to realize real-time simulation and monitoring. The steady and dynamic conditions of the actual system are simulated in virtual space. Compared with the actual results, the average error of steady mass flow is less than 3%, and the error of pressure is less than 1%. The average error of dynamic mass flow is less than 5%, and the error of pressure is less than 3%. The simulation and characteristic predictions are carried out in BPNN-MDSG virtual space. The anti-surge characteristics of the ATF system under start-up conditions are obtained. The full-condition anti-surge operation map of the system is obtained, which provides guidance for the actual operation of the ATF system. Full article

Altitude test facilities for aero-engines employ multi-chamber, multi-valve intake systems that require effective decoupling and strong disturbance rejection during transient tests. This paper proposes a coordinated active disturbance rejection control (ADRC) scheme based on external penalty functions. The chamber pressure safety limit is formulated as an inequality-constrained optimization problem, and an exponential penalty together with a gradient based algorithm is designed for dynamic constraint relaxation, with guaranteed global convergence. A coordination term is then integrated into a distributed ADRC framework to yield a multi-valve coordinated ADRC controller, whose asymptotic stability is established via Lyapunov theory. Hardware-in-the-loop simulations using MATLAB/Simulink and a PLC demonstrate that, under ±3 kPa pressure constraints, the maximum engine inlet pressure error is 1.782 kPa (77.1% lower than PID control), and under an 80 kg/s² flow-rate disturbance, valve oscillations decrease from ±27% to ±5%. These results confirm the superior disturbance rejection and decoupling performance of the proposed method. Full article

This paper investigates the heat distribution on the movable vertical arm of the CZ-12 launch vehicle within the rocket plume impact field in the three-horizontal test launch mode. A model for the different flight altitudes of rocket plume impact on the different angles of the vertical arm was established based on the three-dimensional Navier–Stokes equations and a realizable $k-\epsilon$ turbulence model. The numerical results were compared with experimental data and schlieren images from literature to verify the effectiveness and accuracy of the established numerical model. The results show that when the flight altitude of the rocket is between 30 m and 40 m, the worst heat environment occurs on the front and bottom of the vertical arm. Before reaching a flight altitude of 30 m, a smaller rotation angle of the vertical arm leads to higher maximum temperatures at these two regions. After reaching a flight altitude of 40 m, a larger rotation angle of the vertical arm results in higher maximum temperatures. The top of the lower frame structure is not directly affected by the rocket plume before reaching a flight altitude of 30 m. After reaching a flight altitude of 40 m, a smaller rotation angle of the vertical arm results in higher heat loads on the frame. The results of this study can provide a basis for designing targeted thermal protection for vertical arms. They also contribute a new idea for reducing the thermal load on the vertical arm, which is to rotate the vertical arm to the appropriate angle according to the rocket takeoff altitude. Meanwhile, these research findings will supply a relative reference for researchers who are concerned about other facilities in the surrounding area. Full article

In recent years, thanks to the great diffusion of drone technology and the development of miniaturized sensors that can be connected to drones, in order to increase the sustainability of landfills and oil and gas facilities, interest in finding methane leaks and quantifying the relative flow has grown significantly. This operation requires the methane background concentration to be subtracted from the calculations. Therefore, in order to proceed with a right estimate of CH₄ flows emitted, the possibility of correctly measuring or estimating the background level becomes crucial. The present work intends to illustrate the effects of different variables on the background-noise measurement in a drone-based system that uses a tunable diode laser absorption spectrometer (TDLAS). The methodology used is that of field testing; the data acquisition campaign consisted of the execution of 80 flights during which different flight variables (drone speed, flight altitude) were tested; the flights were repeated in different weather and climate conditions both during the same day and in different periods of the year. Different surfaces, similar to those found in landfill or natural gas sites, were also tested. In some of the field trials, a controlled methane release test was performed in order to verify how much the quantification of the methane flow can vary depending on the background level used. The results of the different field trials highlighted the best conditions under which to measure methane emissions with a TDLAS sensor in order to minimize the number of outliers: flight altitude not exceeding 15 m above ground level; the drone speed appears to have less impact on the results, however, it is optimal between 1 and 2 ms⁻¹; a very sunny day produces much higher methane background levels than a cloudy one. The type of surface also significantly affects the measurement of background noise. Finally, tests conducted with a controlled methane release highlighted that different levels of background have a significant impact on the estimation of the methane flux emitted. Full article

As an indispensable part of the engine manufacturer supply chain, the eco-efficiency of altitude test facility (ATF) operations must improve. Automation is a key enabler in this context since it not only increases precision and reproducibility but also allows for reducing the test time and energy consumption. A suitable controller and reliable validation are crucial to ensure the stability and appropriate response of the control system. Both aspects necessitate a thorough understanding of the control plant, expressed in a numerical model. These models have to be suitable for control system design and validation while covering asymmetric flow phenomena that occur in the pipe system and detailing the nonlinear system dynamics to a high degree of accuracy. One-dimensional network models, state-space models, highly resolving numerical models, and data-driven models are relevant applications for this task. We compare the results of state-of-the-art one-dimensional network models which mainly imply symmetric flow conditions with those of three-dimensional Reynolds-averaged-Navier–Stokes (RANS) simulations which cover asymmetric flow phenomena. The findings show that the assumptions of idealized, axis-symmetric flow in the one-dimensional flow elements do not hold true for the complex flows in an altitude test facility. In a second step, we have compared the results of one-dimensional simulations with in-service measurements taken during ATF test campaigns. Deviations were observed, which become explainable based on the insights gained from the comparison with the RANS simulation. The findings reveal that the one-dimensional simulation-based approach is insufficient to adequately reflect the plant and subsequently for validation due to the observed asymmetric flow phenomena. To overcome this limitation, the application of an empirical first-order transfer function using system identification methods is proposed. Its applicability is successfully demonstrated for the exhaust gas section of the ATF. Subsequently, essential criteria for the design of a suitable control concept for the outlet condition are derived. Full article

The Hellenic Naval Academy (HNA) reports the latest results from a medium-range, near-maritime, free-space laser-communications-testing facility, between the lighthouse of Psitalia Island and the academy’s laboratory building. The FSO link is established within the premises of Piraeus port, with a path length of 2958 m and an average altitude of 35 m, mainly above water. Recently, the facility was upgraded through the addition of a BLS450 scintillometer, which is co-located with the MRV TS5000/155 FSO system and a WS-2000 weather station. This paper presents the preliminary optical turbulence measurements, collected from 24 to 31 of May 2022, alongside the macroscopic meteorological parameters. Four machine-learning algorithms (random forest (RF), gradient boosting regressor (GBR), single layer (ANN), and deep neural network (DNN)) were utilized for refractive-index-structural-parameter regression modeling. Additionally, another DNN was used to classify the strength level of the optical turbulence, as either strong or weak. The results showed very good prediction accuracy for all the models. Specifically, the ANN algorithm resulted in an R-squared of 0.896 and a mean square error (MSE) of 0.0834; the RF algorithm also gave a highly acceptable R-squared of 0.865 and a root mean square error (RMSE) of 0.241. The Gradient Boosting Regressor (GBR) resulted in an R-squared of 0.851 and a RMSE of 0.252 and, finally, the DNN algorithm resulted in an R-squared of 0.79 and a RMSE of 0.088. The DNN-turbulence-strength-classification model exhibited a very acceptable classification performance, given the highly variability of our target value ($C_n^2$), since we observed a predictive accuracy of 87% with the model. Full article

Cutaneous leishmaniasis (CL) is a zoonotic infection caused by obligate intracellular protozoa of the genus Leishmania. This study aimed to investigate CL in Khyber Pakhtunkhwa, Pakistan and to estimate the risk of epidemics. Clinico-epidemiological data of 3188 CL patients were collected from health facilities in 2021. Risk factors were analyzed using the chi-square test. ArcGIS V.10.7.1 was applied for spatial analysis. The association between CL occurrence and climatic variables was examined by Bayesian geostatistical analysis. The clinical data revealed males or individuals younger than 20 years old were more affected. Most patients presented with a single lesion, and the face was the most attacked body part. CL was prevalent in the southern region in winter. A proportional symbol map, a choropleth map, and a digital elevation model map were built to show the distribution of CL. Focal transmission was predicted by inverse distance weighting interpolation. Cluster and outlier analysis identified clusters in Bannu, Dir Lower, and Mardan, and hotspot analysis suggested Bannu as a high-risk foci. Bayesian geostatistical analysis indicated that increasing precipitation and temperature as well as low altitudes were associated with CL infection. The study has provided important information for public health sectors to develop intervention strategies for future CL epidemics. Full article

Moderate altitude (1000–2000 m above sea level) residence is emerging as a protective factor from the mortality of various causes, including of cardiovascular diseases. Conversely, mortality from certain respiratory diseases is higher at these altitudes than in lowlands. These divergent outcomes could indicate either beneficial or detrimental effects of altitude on the mortality of COVID-19 that primarily infects the respiratory tract but results in multi-organ damage. Previous epidemiological data indeed suggest divergent outcomes of moderate to high altitude residence in various countries. Confounding factors, such as variations in the access to clinical facilities or selection biases of investigated populations, may contribute to the equivocation of these observations. We interrogated a dataset of the complete population of an Alpine country in the center of Europe with relatively similar testing and clinical support conditions across altitude-levels of residence (up to around 2000 m) to assess altitude-dependent mortality from COVID-19 throughout 2020. While a reduced all-cause mortality was confirmed for people living higher than 1000 m, no differences in the mortality from COVID-19 between the lowest and the highest altitude regions were observed for the overall population and the population older than 60 years as well. Conversely, COVID-19 mortality seems to have been reduced in the very old (>85 years) women at moderate altitudes. Full article

Background: Malaria is a global burden in terms of morbidity and mortality. In the Democratic Republic of Congo, malaria prevalence is increasing due to strong climatic variations. Reductions in malaria morbidity and mortality, the fight against climate change, good health and well-being constitute key development aims as set by the United Nations Sustainable Development Goals (SDGs). This study aims to predict malaria morbidity to 2036 in relation to climate variations between 2001 and 2019, which may serve as a basis to develop an early warning system that integrates monitoring of rainfall and temperature trends and early detection of anomalies in weather patterns. Methods: Meteorological data were collected at the Mettelsat and the database of the Epidemiological Surveillance Directorate including all malaria cases registered in the surveillance system based on positive blood test results, either by microscopy or by a rapid diagnostic test for malaria, was used to estimate malaria morbidity and mortality by province of the DRC from 2001 to 2019. Malaria prevalence and mortality rates by year and province using direct standardization and mean annual percentage change were calculated using DRC mid-year populations. Time series combining several predictive models were used to forecast malaria epidemic episodes to 2036. Finally, the impact of climatic factors on malaria morbidity was modeled using multivariate time series analysis. Results: The geographical distribution of malaria prevalence from 2001 and 2019 shows strong disparities between provinces with the highest of 7700 cases per 100,000 people at risk for South Kivu. In the northwest, malaria prevalence ranges from 4980 to 7700 cases per 100,000 people at risk. Malaria has been most deadly in Sankuru with a case-fatality rate of 0.526%, followed by Kasai (0.430%), Kwango (0.415%), Bas-Uélé, (0.366%) and Kwilu (0.346%), respectively. However, the stochastic trend model predicts an average annual increase of 6024.07 malaria cases per facility with exponential growth in epidemic waves over the next 200 months of the study. This represents an increase of 99.2%. There was overwhelming evidence of associations between geographic location (western, central and northeastern region of the country), total evaporation under shelter, maximum daily temperature at two meters altitude and malaria morbidity (p < 0.0001). Conclusions: The stochastic trends in our time series observed in this study suggest an exponential increase in epidemic waves over the next 200 months of the study. The increase in new malaria cases is statistically related to population density, average number of rainy days, average wind speed, and unstable and intermediate epidemiological facies. Therefore, the results of this research should provide relevant information for the Congolese government to respond to malaria in real time by setting up a warning system integrating the monitoring of rainfall and temperature trends and early detection of anomalies in weather patterns. Full article

To solve the modeling problem of altitude ground test facility (AGTF) exhaust systems, which is caused by nonlinearity along the gas path and the difficulty of ejection factor calculation, a multi-cavity iterative modeling method is presented. The components of exhaust systems, such as the exhaust diffuser and cooler, are built with a series of volumes. It overcomes the disadvantage that traditional lumped-parameter models have, whereby they cannot calculate the dynamic parameters along the gas path. The exhaust system model is built with an iterative method based on multi-cavity components, and simulations are carried out under experimental conditions. The simulation results show that the maximum error of pressure is 2 kPa in the steady state and less than 6 kPa in the transient process compared with experimental data. Closed-loop simulations are also carried out to further verify the accuracy and effectiveness of the multi-cavity iterative exhaust system modeling method. Full article

Background: Anaemia is a condition characterised by a decrease in the concentration of haemoglobin (Hb) in the blood. Anaemia suffers under five years children about 47.4% and 67.6% worldwide and developing countries including Ethiopia, respectively. The aim of this study was to assess the prevalence rate and the associated socio-economic, geographic and demographic factors of anaemia status of under five years children in Ethiopia. Methods: The data for this study were obtained from the 2011 Ethiopia National Malaria Indicator Survey (EMIS 2011). A sample of 4356 under five years age children was obtained from three regional states of Ethiopia. Based on haemoglobin level, child anaemia status was ordered and takes an ordinal value as no anaemia, mild anaemia, moderate anaemia and severe anaemia, respectively. Ordinal logistic regression model, specifically the proportional odds model was used by considering with and without survey design features. Results: Of the 4356 complete cases, 2190 (50.28%) were male and 1966 (49.72%) were female children under five years old. The children overall mean (SD) age was 2.68 (1.21) years. It was observed that both the mean ages and their variabilities in the regions are approximately equal to the overall mean and variability. It was also observed that in Amhara, Oromiya and SNNP regions 72.28%, 67.99% and 73.63% of the children, respectively had no anaemia; 15.93%, 13.47% and 13.56% of the children, respectively had mild anaemia; 10.99%, 15.61% and 11.33% of the children, respectively had moderate anaemia; and only 0.81%, 2.93% and 1.49% had severe anaemia, respectively. The prevalence of severe child anaemia status was higher in Oromiya region compared to Amhara and SNNP regions, respectively. Our result indicates that age, use of mosquito net, malaria RDT outcome, type of toilet facility, household wealth index, region and median altitude were significantly related to child anaemia status. However, it was observed that some covariates were model dependent, for example household wealth index and type of toilet facility were not significant when considering survey features. Conclusions: Anaemia burden remains high particularly in developing countries. Controlling the burden of anaemia necessitates the formulation of integrated interventions which prioritise the highest risk groups including children under five years. The statistical model used in this paper identified individual, household and cluster level risk factors of child anaemia. The identified risk factors for example not having improved toilet facility in the dwelling where a child lived as well as poorest household wealth index suggest the policymakers should target to focus more on children from poor community. Further, the strong association between malaria infection and anaemia suggests that malaria preventative methods such as vector control methods namely, long-lasting insecticidal nets (LLINs) and indoor residual spraying of households with insecticides and including case diagnostic testing and treatment may be the most effective ways to reduce infections associated with anaemia. Such collective assessment approach may lead to more effective public health strategies and could have important policy implications for health promotion and for the reduction of health disparities. Full article

There is an obvious tendency towards increasing the information content of surveys of hard-to-reach objects at high altitudes through the use of remote-controlled robot crawlers. This can be explained by the reasonable desire of industrial objects owners to maintain their property: pipelines, containers, metal structures in operating technical condition, which contributes to reducing accident risks and increasing the economic efficiency of operation (optimization of repair planning, etc.) This paper presents the concept of a robotic device equipped with LIDAR and EMAT which can move over pipes from a diameter of 100 mm by using a special type of magnetic wheel. The robot uses convolutional neural networks to detect structural elements and classify their defects. The article contains information about tests held on a specially developed test rig. The results showed that the device could increase the information level of survey and reduce the labour intensity. In this work, we consider a prototype of the device which has not started mass operation at industrial facilities yet. Full article

The use of drones is very extended for multiple applications. Some of them impose attitude and navigation requirements that need appropriate measurements. Pixhawk is an open-source autopilot used on board drones that includes a magnetometer as part of its inertial measurement unit. A testing facility based on a Helmholtz cage is used to evaluate the metrological features of different magnetometer units. The first test induces a magnetic field rotation around six different Pixhawk magnetometers, simulating changes in attitude and course for a drone. The data show a standard deviation higher than 250 mG, in comparison with the standard deviation of 30 mG in the standard gaussmeter model HMR2300. The second test is focused on the stability of the magnetometer, where the Helmholtz cage simulates a certain flight altitude and course. Values obtained from Pixhawk magnetometers range between 25 mG and 116 mG for the highest peak-to-peak magnetic field amplitude, while the standard gaussmeter range is only between 1.3 mG to 5.4 mG. Considering these results, it is possible to determine the limitations of the Pixhawk autopilot magnetometer, both in terms of manufacturing tolerances and measuring stability. Therefore, users should be very careful when using this type of autopilot in professional applications that require precision and safety. Full article

The Flight Environment Simulation System (FESS) at Altitude Ground Test Facilities (AGTF) is used to test aircraft engines. The FESS model is the basis of research and verification of advanced control algorithms. To further improve the steady and dynamic accuracy of the FESS model, a modeling method based on quasi-one-dimensional flow is proposed. Firstly, based on the unified inlet/outlet boundary specifications, the component models of test equipment, such as the quasi-one-dimensional flow model of pipe, the regulating valve model considering the heat transfer process, the multi-inlet and multi-outlet volume model reflecting the mixing characteristics of air flow, and the air source model and engine model, were established. Secondly, according to the real structure and working mechanism of the FESS, the above component models were used to build the numerical simulation model of the FESS. The simulation results showed that the relative deviation of mass flow and pressure were less than 4.4% and 0.9%, respectively, which verifies the correctness of the modeling method. In addition, the PI controller was designed for the FESS, and the simulation results show that the model is able to support controller development and verification. Full article