Large-scale Pressure Research Articles

Modelling the Effects of Forest use Change on Brownification of Finnish Rivers under Atmospheric Pressure.

Browning of surface waters due to increased terrestrial loading of dissolved organic matter (DOM) is observed across the Northern Hemisphere. The effects influence several ecosystem services from freshwater productivity to water purification. Brownification is often explained by changes in large-scale anthropogenic pressures and ecosystem functioning (acidification, climate change, and land cover changes). This study examined the effect of forest use changes on water browning in Finland, considering the effects of global pressures. Our goal was to find the ecosystems and geographic areas that are most sensitive to environmental pressures that increase the loading of DOM. We were also looking for land use strategies that decrease browning. We combined mathematical watershed modelling to scenarios of climate change, atmospheric deposition, and forest use change. Changes included scenarios of forest harvest and protection on forest, that were derived from European Union's regulation. The study area covered 20 watersheds from south to north of Finland. In northern Finland brownification continue. In southern Finland global influence (atmospheric deposition, climate change) seem to weaken, giving more space for local forest use change having an influence on brownification. Forest use change was more influential in river basins dominated by organic soils than in mineral soils. Extending forest protection decreased brownification especially in areas where the influence of atmospheric pressure is decreasing. When forest protection is planned to provide a carbon storage and sequestration potential and to favor biodiversity, it has favorable effect on surface water quality as well.

The Kunming-Montreal Global Biodiversity Framework needs headline indicators that can actually monitor forest integrity

Abstract Intact native forests under negligible large-scale human pressures (i.e. high-integrity forests) are critical for biodiversity conservation. However, high-integrity forests are declining worldwide due to deforestation and forest degradation. Recognizing the importance of high-integrity ecosystems (including forests), the Kunming-Montreal Global Biodiversity Framework (GBF) has directly included the maintenance and restoration of ecosystem integrity, in addition to ecosystem extent, in its goals and targets. Yet, the headline indicators identified to help nations monitor forest ecosystems and their integrity can currently track changes only in (1) forest cover or extent, and (2) the risk of ecosystem collapse using the IUCN Red List of Ecosystems (RLE). These headline indicators are unlikely to facilitate the monitoring of forest integrity for two reasons. First, focusing on forest cover not only misses the impacts of anthropogenic degradation on forests but can also fail to detect the effect of positive management actions in enhancing forest integrity. Second, the risk of ecosystem collapse as measured by the ordinal RLE index (from Least Concern to Critically Endangered) makes it unlikely that changes to the continuum of forest integrity over space and time would be reported by nations. Importantly, forest ecosystems in many biodiverse African and Asian nations remain unassessed with the RLE. As such, many nations will likely resort to monitoring forest cover alone and therefore inadequately report progress against forest integrity goals and targets. We concur that monitoring changes in forest cover and the risk of ecosystem collapse are indeed vital aspects of conservation monitoring. Yet, they are insufficient for the specific purpose of tracking progress against crucial ecosystem integrity components of the GBF’s goals. We discuss the pitfalls of merely monitoring forest cover, a likely outcome with the current headline indicators. Augmenting forest cover monitoring with indicators that capture change in absolute area along the continuum of forest integrity would help monitor progress toward achieving area-based targets related to both integrity and extent of global forests.

Generation of Large-Scale Plasma Jet with Excitation of Bipolar Nanosecond Pulse Voltage in Single-Spiral Electrode Configuration

In this study, a single-outer-spiral electrode with inductance of 20 μH is employed to couple the energy input of a bipolar nanosecond pulse for the purpose of generating a large-scale atmospheric pressure plasma jet. When the spiral electrode is wrapped around a plasma jet tube with a length of 35 cm, the electrical field can be optimized, resulting in a stable laminar flow field, and a plasma jet with a length and diameter larger than 14 cm and 1.2 cm can be generated. A comparative study of the bipolar and unipolar pulse excitation voltages is also conducted, showing that the maximum lengths of the plasma jet excited by a bipolar pulse voltage, positive pulse voltage, and negative are 14 cm, 10 cm, and 7 cm, respectively. The temporal and spatially resolved spectra of the plasma jets excited by both bipolar and unipolar pulses are investigated, respectively, and the main physiochemical processes of the active species and the plasma dynamics’ evolution are discussed.

Robust future projections of global spatial distribution of major tropical cyclones and sea level pressure gradients

Despite the profound societal impacts of intense tropical cyclones (TCs), prediction of future changes in their regional occurrence remains challenging owing to climate model limitations and to the infrequent occurrence of such TCs. Here we reveal projected changes in the frequency of major TC occurrence (i.e., maximum sustained wind speed: ≥ 50 m s−1) on the regional scale. Two independent high-resolution climate models projected similar changes in major TC occurrence. Their spatial patterns highlight an increase in the Central Pacific and a reduction in occurrence in the Southern Hemisphere—likely attributable to anthropogenic climate change. Furthermore, this study suggests that major TCs can modify large-scale sea-level pressure fields, potentially leading to the abrupt onset of strong wind speeds even when the storm centers are thousands of kilometers away. This study highlights the amplified risk of storm-related hazards, specifically in the Central Pacific, even when major TCs are far from the populated regions.

A planar plume array emanating from an atmospheric pressure argon plasma jet employing floating electrodes

Large-scale plasma plumes downstream of plasma jets are in urgent need from a practical viewpoint. In this Letter, an argon plasma jet with floating electrodes is proposed to produce a large-scale planar plume array. Results indicate that with increasing peak voltage (Vp), the planar plume array elongates gradually and scales up in the lateral direction to an optimal value of 90.0 mm. There is only one discharge pulse per voltage half cycle, whose intensity and duration increase with increasing Vp. Moreover, there is a time lag between the initiations of individual plumes. Fast photography reveals that the planar plume array originates from the repeated process of some micro-discharge filaments stretching along the argon stream. By optical emission spectroscopy, the spatial distribution of plasma parameters is obtained, such as electron density, electron temperature, and gas temperature. At last, the planar plume array is employed to test the surface modification of polyethylene terephthalate, for which a uniform modification has been realized with a scan velocity of 1.0 cm/min. These results are of great significance for the development of large-scale atmospheric pressure plasma sources.

Aerodynamic characteristics of the retro propulsion landing burn of vertically landing launchers

In the frame of the European funded H2020 project RETALT (retro propulsion-assisted landing technologies), the unsteady aerodynamics of vertically descending and landing launchers have been investigated. In this paper, experimental data of the landing burn tested in the Vertical Free-Jet Facility Cologne at DLR in Cologne are presented. The landing burn was simulated with a cold gas jet of pressurized air opposing the wind tunnel free stream. Tests with several jet conditions were compared to results without active jet. Proper orthogonal decomposition of schlieren recordings and spectral analyses of their time histories are performed and are compared to frequencies in pressure measurements. Dominant frequencies were found, which are strongest at Mach 0.8. Especially, a Strouhal number of 0.2 was found to be most dominant. The intensity of the dominant frequencies can be lowered if the engine is active. The normalized root mean square pressure fluctuations are between 0.1 and 0.3 during the landing maneuver. Additionally, the steady flow features scale well with the ambient pressure ratio and the momentum flux ratio. The unsteady flow field dynamics of the subsonic retro propulsion flow field can likely be linked to large-scale turbulent structures in the supersonic jet, triggering large-scale pressure fluctuations and altering the overall flow field.

The multi-scale coupled model: a new framework capturing wind farm–atmosphere interaction and global blockage effects

Abstract. The growth in the number and size of wind energy projects in the last decade has revealed structural limitations in the current approach adopted by the wind industry to assess potential wind farm sites. These limitations are the result of neglecting the mutual interaction of large wind farms and the thermally stratified atmospheric boundary layer. While currently available analytical models are sufficiently accurate to conduct site assessments for isolated rotors or small wind turbine clusters, the wind farm's interaction with the atmosphere cannot be neglected for large-size arrays. Specifically, the wind farm displaces the boundary layer vertically, triggering atmospheric gravity waves that induce large-scale horizontal pressure gradients. These perturbations in pressure alter the velocity field at the turbine locations, ultimately affecting global wind farm power production. The implication of such dynamics can also produce an extended blockage region upstream of the first turbines and a favorable pressure gradient inside the wind farm. In this paper, we present the multi-scale coupled (MSC) model, a novel approach that allows the simultaneous prediction of micro-scale effects occurring at the wind turbine scale, such as individual wake interactions and rotor induction, and meso-scale phenomena occurring at the wind farm scale and larger, such as atmospheric gravity waves. This is achieved by evaluating wake models on a spatially heterogeneous background velocity field obtained from a reduced-order meso-scale model. Verification of the MSC model is performed against two large-eddy simulations (LESs) with similar average inflow velocity profiles and a different capping inversion strength, so that two distinct interfacial gravity wave regimes are produced, i.e. subcritical and supercritical. Interfacial waves can produce high blockage in the first case, as they are allowed to propagate upstream. On the other hand, in the supercritical regime their propagation speed is less than their advection velocity, and upstream blockage is only operated by internal waves. The MSC model not only proves to successfully capture both local induction and global blockage effects in the two analyzed regimes, but also captures the interaction between the wind farm and gravity waves, underestimating wind farm power by about only 2 % compared with the LES results. Conversely, wake models alone cannot distinguish between differences in thermal stratification, even if combined with a local induction model. Specifically, they are affected by a first-row overprediction bias that leads to an overestimation of the wind farm power by 13 % to 20 % for the modeled regimes.

Understanding the drivers of near-surface winds in Adélie Land, East Antarctica

Abstract. Near-surface winds play a crucial role in the climate of Antarctica, but accurately quantifying and understanding their drivers is complex. They result from the contribution of two distinct families of drivers: the large-scale pressure gradient and surface-induced pressure gradients known as katabatic and thermal wind. The extrapolation of vertical potential temperature above the boundary layer down to the surface enables us to separate and quantify the contribution of these different pressure gradients in the momentum budget equations. Using this method applied to outputs of the regional atmospheric model MAR at a 3-hourly resolution, we find that the seasonal and spatial variability in near-surface winds in Adélie Land is dominated by surface processes. On the other hand, high-frequency temporal variability (3-hourly) is mainly controlled by large-scale variability everywhere in Antarctica, except on the coast. In coastal regions, although the katabatic acceleration surpasses all other accelerations in magnitude, none of the katabatic or large-scale accelerations can be identified as the single primary driver of near-surface wind variability. The angle between the large-scale acceleration and the surface slope is a key factor in explaining strong wind speed events: the highest-wind-speed events happen when the katabatic and large-scale forcing are aligned, although each acceleration, when acting alone, can also cause strong wind speed. This study underlines the complexity of the drivers of Antarctic surface winds and the value of the momentum budget decomposition to identify drivers at different spatial and temporal scales.

Hybrid triboelectric-piezoelectric nanogenerator for long-term load monitoring in total knee replacements

A self-powered and durable pressure sensor for large-scale pressure detection on the knee implant would be highly advantageous for designing long-lasting and reliable knee implants as well as obtaining information about knee function after the operation. The purpose of this study is to develop a robust energy harvester that can convert wide ranges of pressure to electricity to power a load sensor inside the knee implant. To efficiently convert loads to electricity, we design a cuboid-array-structured tribo-pizoelectric nanogenerator (TPENG) in vertical contact mode inside a knee implant package. The proposed TPENG is fabricated with aluminum and cuboid-patterned silicone rubber layers. Using the cuboid-patterned silicone rubber as a dielectric and aluminum as electrodes improves performance compared with previously reported self-powered sensors. The combination of 10 wt% dopamine-modified BaTiO3 piezoelectric nanoparticles in the silicone rubber enhanced electrical stability and mechanical durability of the silicone rubber. To examine the output, the package-harvester assemblies are loaded into an MTS machine under different periodic loading. Under different cyclic loading, frequencies, and resistance loads, the harvester’s output performance is also theoretically studied and experimentally verified. The proposed cuboid-array-structured TPENG integrated into the knee implant package can generate approximately 15 μ W of apparent power under dynamic compressive loading of 2200 N magnitude. In addition, as a result of the TPENG’s materials being effectively optimized, it possesses remarkable mechanical durability and signal stability, functioning after more than 30 000 cycles under 2200 N load and producing about 300 V peak to peak. We have also presented a mathematical model and numerical results that closely capture experimental results. We have reported how the TPENG charge density varies with force. This study represents a significant advancement in a better understanding of harvesting mechanical energy for instrumented knee implants to detect a load imbalance or abnormal gait patterns.

Artificial tactile system for pressure monitoring in extracorporeal circulation processes

Current intraoperative pressure monitoring methods still face significant limitations in perception and feedback, struggling to strike a balance between precision and wearable flexibility. Inspired by biological skin, we propose a biomimetic tactile sensing system for pressure monitoring during extracorporeal circulation, comprising flexible pressure sensors and artificial synaptic transistors. Aimed at addressing the aforementioned issues, our system employs a pyramid-shaped elastic design for flexible pressure sensors, utilizing biocompatible materials polydimethylsiloxane and multi-walled carbon nanotubes as the strain-sensitive layer. This configuration boasts ultra-high sensitivity and resolution (115 kPa−1), accurately detecting subtle pressure changes, such as blood circulation wall pressures. With artificial synaptic transistors as the information processing core, our system successfully simulates crucial neural processing functions, including excitatory post-synaptic currents and double-pulse facilitation, while providing alerts for abnormal blood pressure signals. This system facilitates real-time data processing at the device edge, reducing power consumption, improving efficiency, and better addressing the demands of large-scale physiological pressure data processing. It presents a significant reference for future developments in biomedical electronics and bionics.

Setting Up a Large-Eddy Simulation to Focus on the Atmospheric Surface Layer

Large-eddy simulations (LES) above forests and cities typically constrain the simulation domain to the first 10–20% of the Atmospheric Boundary Layer (ABL), aiming to represent the finer details of the roughness elements and sublayer. These simulations are also commonly driven by a constant pressure gradient term in the streamwise direction and zero stress at the top, resulting in an unrealistic fast decay of the total stress profile. In this study, we investigate five LES setups, including pressure and/or top-shear driven flows with and without the Coriolis force, with the aim of identifying which option best represents turbulence profiles in the atmospheric surface layer (ASL). We show that flows driven solely by pressure not only result in a fast-decaying stress profile, but also in lower velocity variances and higher velocity skewnesses. Top-shear driven flows, on the other hand, better replicate ASL statistics. Overall, we recommend, and provide setup guidance for, simulation designs that include both a large scale pressure forcing and a non-zero stress and scalar flux at the top of the domain, and that also represent the Coriolis force. Such setups retain all the forces used in typical full ABL cases and result in the best match of the profiles of various statistical moments.

Formation and evolution of vortex breakdown consequent to post design flow increase in a Francis turbine

Draft tube flow instability encountered under off-design operating conditions in hydraulic turbines significantly limits their operational flexibility. The instability arises consequent to a higher than threshold swirl content in the runner outflow and leads to vortex breakdown phenomenon in the draft tube cone. At high load condition, the phenomenon presents as an enlarged vortex core counter-rotating with respect to the runner. The flow situation is known to compromise the turbine efficiency besides the generation of unwanted effects such as power swings and large-scale pressure fluctuations. The present paper is the first to encapsulate a thorough numerical investigation on the formation and evolution of the enlarged vortex core alongside the consequent effects. A transient operating sequence between best efficiency and high load operating points in a model Francis turbine is simulated. Turbulence closure has been attained using the shear stress transport-scale adaptive simulations turbulence model. Dynamic meshing based on a Laplacian smoothing scheme has been used to account for mesh deformation arising from guide vane motion during load change. The pressure and velocity fields have been determined and analyzed to elucidate the physics of vortex breakdown, the phenomenon underlying the formation of the enlarged vortex core. Furthermore, pressure fluctuations at salient points in the domain have been analyzed using Fourier and short-time Fourier transforms. Finally, the enlarged vortex core formed in the draft tube has been visualized through the λ2 criterion. The core takes the shape of a cork-screw like compactly wound spiral structure extending up to the draft tube elbow.

Potentialities of the combined use of underwater fluorescence imagery and photogrammetry for the detection of fine-scale changes in marine bioconstructors

Marine communities are facing both natural disturbances and anthropogenic stressors. Bioconstructor species are endangered by multiple large-scale and local pressures and the early identification of impacts and damages is a primary goal for preserving coral reefs. Taking advantage of the recent development in underwater photogrammetry, the use of photogrammetry and fluorimetry was coupled to design, test and validate in laboratory a multi-sensor measuring system that could be potentially exploited in open water by SCUBA divers for assessing the health status of corals and detecting relevant biometric parameters with high accuracy and resolution. The approach was tested with fragments of the endemic coral Cladocora caespitosa, the sole zooxanthellate scleractinian reef-builder in the Mediterranean. The most significant results contributing to the scientific advancement of knowledge were: 1) the development of a cost-effective, flexible and easy-to-use approach based on emerging technologies; 2) the achievement of a sub-centimetric resolution for measuring relevant biometric parameters (polyp counting, colony surface areas and volumes); 3) set up of a reliable and repeatable strategy for multi-temporal analyses capable of quantifying changes in coral morphology with sub-centimeter accuracy; 4) detect changes in coral health status at a fine scale and under natural lighting through autofluorescence analysis. The novelty of the present research lies in the coupling of emerging techniques that could be applied to a wide range of 3D morphometrics, different habitats and species, thus paving the way to innovative opportunities in ecological research and more effective results than traditional in-situ measurements. Moreover, the possibility to easily modify the developed system to be installed on an underwater remotely operated vehicle further highlights the possible concrete impact of the research for ecological monitoring and protection purposes.

New distribution records of the endemic pitcher plant, Nepenthes khasiana Hook. f. and identification of threats in Meghalaya, India

Aim: The present study entails new distribution records along with the identification of threats to the pitcher plant, Nepenthes khasiana Hook. f. in Meghalaya, India. Methodology: A trail survey was employed to find the distribution of pitcher plants in different locations of the Garo, Khasi, and Jaintia hills of Meghalaya between 2018 and 2022. Results: The present study reported some new distribution records in the Garo, Jaintia, and Khasi Hills of Meghalaya mostly in private lands which are scatteredly distributed. They are adversely threatened due to large-scale jhum cultivation, mining, traffic, road construction, human pressure, and tourism as depicted in the present study. Besides, the pitcher plants have been wiped out from many areas of Meghalaya which was earlier reported. Interpretation: The present work documented the distribution of pitcher plants in some new areas of the Garo, Khasi, and Jaintia Hills of Meghalaya. The population of the pitcher plant is sharply declining in Meghalaya due to various threat factors. Hence, the conservation of pitcher plant need urgent attention. Therefore, an action plan is required to safeguard the pitcher plant in these habitats. Besides public awareness, stakeholder participation is the paramount need of the hour to protect and preserve the plants. Further, new areas also need to be explored for the distribution of pitcher plants in other areas of the state including intensive studies in Garo, Khasi and Jaintia Hills. Key words: Carnivorous plants, Endemic, Meghalaya, Nepenthes khasiana, Pitcher plant

Mechanisms of Low-Level Jet Formation in the U.S. Mid-Atlantic Offshore

Abstract Low-level jets (LLJs), in which the wind speed attains a local maximum at low altitudes, have been found to occur in the U.S. mid-Atlantic offshore, a region of active wind energy deployment as of 2023. In contrast to widely studied regions such as the U.S. southern Great Plains and the California coastline, the mechanisms that underlie LLJs in the U.S. mid-Atlantic are poorly understood. This work analyzes floating lidar data from buoys deployed in the New York Bight to understand the characteristics and causes of coastal LLJs in the region. Application of the Hilbert–Huang transform, a frequency analysis technique, to LLJ case studies reveals that mid-Atlantic jets frequently occur during times of adjustment in synoptic-scale motions, such as large-scale temperature and pressure gradients or frontal passages, and that they do not coincide with motions at the native inertial oscillation frequency. Subsequent analysis with theoretical models of inertial oscillation and thermal winds further reveals that these jets can form in the stationary geostrophic wind profile from horizontal temperature gradients alone—in contrast to canonical LLJs, which arise from low-level inertial motions. Here, inertial oscillation can further modulate the intensity and altitude of the wind speed maximum. Statistical evidence indicates that these oscillations arise from stable stratification and the associated frictional decoupling due to warmer air flowing over a cold sea surface during the springtime land–sea breeze. These results improve our conceptual understanding of mid-Atlantic jets and may be used to better predict low-level wind speed maxima. Significance Statement The purpose of this work is to identify and characterize the atmospheric mechanisms that result in an occasional low-level maximum in the wind speed off the U.S. mid-Atlantic coastline. Our findings show that these low-level jets form due to horizontal temperature gradients arising from fronts and synoptic systems, as well as from the land–sea breeze that forces warmer air over the cold ocean surface. This work aids predictability of such jets, improves our understanding of this coastal environment, and has implications for future deployment of offshore wind energy in this region.

THE EFFECTS OF SHAPE AND LIQUID PROPERTIES ON PRESSURE SWIRL ATOMIZER IN-NOZZLE FLOW

The internal flow in pressure swirl atomizers is numerically predicted by performing large eddy simulations and using a volume of fluid approach. The output of the numerical model is validated by comparing it with three databases of experimental measurements obtained on large-scale pressure swirl atomizers available in the open literature. A simplified analytical model previously developed by the authors, which relates the swirl intensity to the thickness of the fluid exiting the nozzle, is used to analyze the flow behavior in three pressure swirl atomizers, with large differences in the injector geometry, the operating conditions, and the fluid thermophysical properties. This simple relationship is found to hold for the three pressure swirl atomizers, with small changes of the parameter that accounts for energy losses, while data obtained with relatively small variations of the injector geometry are found to collapse on the same curve. The effects of operating conditions and fluid thermophysical properties on this relation are found to be irrelevant.

A Primal-Dual Box-Constrained QP Pressure Poisson Solver With Topology-Aware Geometry-Inspired Aggregation AMG.

We propose a new barrier-based box-constrained convex QP solver based on a primal-dual interior point method to efficiently solve large-scale pressure Poisson problems with non-negative pressure constraints, which commonly arise in liquid animation. The performance of prior active-set-based approaches is limited by the need to repeatedly update the active set. Our solver eliminates this issue by entirely avoiding the use of an active set, which in turn makes the inner problems of our Newton iteration process fully unconstrained. For efficiency, exploiting the solution uniqueness of convex QPs and the fact that the pressure constraints are simple box constraints, we aggressively update solution candidates without performing any step selection procedure (such as line search) and instead directly clamp candidates back to the bounds wherever constraint violations occur. Additionally, to accelerate the inner linear solves, we present a topology-aware geometry-inspired aggregation algebraic multigrid preconditioner and describe in detail several key performance optimizations that we incorporate. We demonstrate the efficacy of our solver in various practical scenarios and show that it often surpasses various alternatives in terms of speed and memory usage.

MXene/PPy@PDMS sponge-based flexible pressure sensor for human posture recognition with the assistance of a convolutional neural network in deep learning

The combination of flexible sensors and deep learning has attracted much attention as an efficient method for the recognition of human postures. In this paper, an in situ polymerized MXene/polypyrrole (PPy) composite is dip-coated on a polydimethylsiloxane (PDMS) sponge to fabricate an MXene/PPy@PDMS (MPP) piezoresistive sensor. The sponge sensor achieves ultrahigh sensitivity (6.8925 kPa−1) at 0–15 kPa, a short response/recovery time (100/110 ms), excellent stability (5000 cycles) and wash resistance. The synergistic effect of PPy and MXene improves the performance of the composite materials and facilitates the transfer of electrons, making the MPP sponge at least five times more sensitive than sponges based on each of the individual single materials. The large-area conductive network allows the MPP sensor to maintain excellent electrical performance over a large-scale pressure range. The MPP sensor can detect a variety of human body activity signals, such as radial artery pulse and different joint movements. The detection and analysis of human motion data, which is assisted by convolutional neural network (CNN) deep learning algorithms, enable the recognition and judgment of 16 types of human postures. The MXene/PPy flexible pressure sensor based on a PDMS sponge has broad application prospects in human motion detection, intelligent sensing and wearable devices.

Non-iterative reconstruction of time-domain sound pressure and rapid prediction of large-scale sound field based on IG-DRBEM and POD-RBF

In this paper, a novel non-iterative reconstruction method of time-domain sound pressure and rapid prediction scheme of large-scale sound field are proposed respectively based on the isogeometric dual reciprocity boundary element method (IG-DRBEM) and proper orthogonal decomposition - radial basis functions (POD-RBF). By establishing the non-iterative inversion theory in the meaning of least squares, infinite domain acoustic holography is achieved with a small number of measured sound pressure information. Furthermore, the POD-RBF network is adopted to predict large-scale sound pressure. The presented work further expands the scope of application of IG-DRBEM, and gives full play to its advantage of not having to calculate the coefficient matrix repeatedly when analyzing the sound field at different moments. Moreover, in order to satisfy the integral regularization conditions, a suitable convergence condition about variation coefficients is investigated. Numerical results show that the proposed method has high accuracy and good stability even when the sound pressure of complex airship model is predicted with large-scale freedom.

Integration of large-scale pressure swing adsorption units in local hospitals in Morocco: Design, simulation and performance evaluation

To enhance the availability and accessibility of medical oxygen in local hospitals in Morocco, a solid approach has been conducted for upscaling PSA unit. This comprehensive research involves the design, simulation, and performance evaluation of the PSA unit to confirm the functioning and efficiency of the system. The design phase meticulously considers hospital oxygen requirements, utilizing data from multiple local hospitals. Objectives include using PSA technology to produce high-purity oxygen, providing autonomy for 30–35 patients at 5 L/min. Although, the hospital needs 650 L/min of medical oxygen in order to supply all the patients. The study reveals promising results for oxygen concentration which reaches a maximum of 96 % of oxygen under 29 mol/min of flowrate which give an equivalent to 660 L/min volumetric flow rate that can supply the needs of local hospitals within a short time. These findings will enable hospitals decision makers to consider large PSA over cryogenic separation unit that has been known with major drawbacks in delivery and pose logistical and environmental problems and to ensure a steady and reliable supply of medical oxygen, ultimately contributing to improved healthcare services and patient care.