Flow Discharge Research Articles

Eco-friendly dredging methods of changing fluvial landforms for enhancing hydraulic habitat quality and river corridor continuum

Hydraulic habitat connectivity, including the longitudinal continuum respect and lateral flood pulse, is critical for fish survival and organism dispersal. Inappropriate and excessive dredging for prevent flooding may harm river ecosystems. The main objective of this study is to evaluate whether eco-friendly dredging presented by changing local river landforms incorporating the concept of nature-based solutions could grow fish habitat quality for improving river continuity and achieving flood control effects. By combining various mathematical models and empirical formulas and verifying them with the data obtained through field surveys, we explore the interconnections of hydrology, river morphology, and the habitat dynamics of four endemic fishes in an alluvial river. The relationship between habitat structure, flood risk, and river topography, flow discharge was presented as the reference for developing the proper river dredging approaches. The results reveal that the primary habitat defects were lack of high-quality habitat, unsatisfied habitat diversity, deficiency in refugia, and disconnectivity. Longitudinal disconnectivity was induced due to shallow water depth, while lateral disconnectivity is primarily caused by fast flow velocity, suggesting different and specific dredging methods were instructed. We recommend that the corresponding eco-friendly dredging schemes for longitudinal and lateral suitable habitat linkages increase fish habitat quality and river corridor continuity. The win-win strategy for enhancing the connection between suitable habitats sustains a more beneficial aquatic corridor and simultaneously achieves alluvial flood disaster risk reduction.

Experimental study of simple flumes with converging triangular walls

For water management, the accurate measurement of discharge in irrigation channels is essential. Static flow measuring devices such as weirs and flumes play a significant role in discharge measurement in open channels. Flumes are one of the most commonly used devices for flow measurement. Many researchers have focused on application of simple flumes in irrigation networks. This investigation aims to study the flow discharge through a simple flume with converging triangular walls under free-flow conditions. The flume is constructed by placing two right-angled triangular plates on either side of a rectangular open channel. The channel cross section is rectangular while height of the converging walls reaches to zero at the end of the flume opening. The proposed flume is inexpensive, its operation is simple, its installation is easy and does not require high maintenance (maintenance free). The present study is designed to determine the effect of different variables on flow discharge of this kind of flumes. For this, an experimental program was conducted under upstream subcritical flow regime and under free outflow conditions to formulate the flow discharge of the flume. Flume discharge relationship was deduced using dimensional analysis method and then calibrated using the experimental data collected in this study (318 runs). The proposed discharge equation has an average absolute relative error of 1.66 %, and for 96.5 % of the measured discharge values, the relative errors are within ±5 %. To reliably estimate the flume discharge, free-flow and submerged-flow conditions should be distinguished. For this, suitable equation with an average absolute relative error less than 3.44 % was presented to estimate the submergence threshold. This flume is suitable for the rectangular channel for accurate measurement of free flow at any location on field. This particular device has considerable advantages over the other devices, as it can be quickly installed and removed for use in irrigation channels. The findings and results of this study will be of interest for practical applications.

How to consider groundwater flow systems in the Earth's Critical Zone? – Demonstration in the Central Pannonian Basin, Hungary

Study regionCentral Pannonian Basin, Hungary. Study focusCritical Zone (CZ) Science generally focuses on the soil and weathered bedrock in a few or tens of meters depth, thus influence of deeper groundwater on the CZ is understudied. Here we aim to introduce a hydrogeological methodology that can separate normal and abnormal pressure regimes and determine the groundwater flow pattern to characterize the connection of different groundwater flow systems to the CZ. Basin-scale evaluation of about 5500 measured hydraulic data were carried out by p(z) and h(z) profiles, tomographic maps and hydraulic cross sections. New hydrological insights for the RegionThree flow domains were separated and characterized. Namely, i) the uppermost topography-driven flow systems, which penetrate only a few hundred meters, ii) a deep overpressured regime below 1600–2100 m depth, which drives fluids upward; and iii) a newly identified transition zone between the former two, which gains its energy from overpressure dissipation and contains non-renewable water resources. Topography-driven flow systems and discharge areas of the transition zone, where its upwelling saline water contributes to surface salinization, are parts of the CZ. Discharge areas of the transition zone cover about 50% of the Great Hungarian Plain. The overpressured system can only influence the CZ through the transition zone. The approach and methodology can be used in any terrestrial sedimentary basin where a deep overpressured regime exists.

Staged SWAT calibration with bias-corrected precipitation product for enhancing flow data continuity in tributaries of the Mekong River

Accurate and continuous flow data are crucial for effective water management in large river basins worldwide. However, these catchments often face challenges regarding data continuity in the mainstream and their tributaries. This study proposes a methodological framework for enhancing flow data continuity that uses a staged calibration scheme of Soil and Water Assessment Tool (SWAT) modeling with an appropriate satellite precipitation product (SPP) for each watershed. This framework is successfully applied in the Mun-Chi River Basin, the largest tributary of the Lower Mekong River, over a 20-year period at 34 stations. The staged calibration involves partitioning the catchment into smaller sub-catchments, guided by the flow monitoring stations and flow discontinuity structures such as dams. The sequential calibration from upstream to downstream partitions the overall model calibration challenge into smaller problems and contributes to a more efficient and accurate calibration and validation. Alternative SPPs were considered to overcome monitoring gaps. Their bias was corrected using quantile mapping, and their performance was evaluated with flow simulations using the SWAT model. The assessment indicates that the CMORPH-CRT product, with a spatial resolution of 0.25°, demonstrates good suitability for hydrological modeling of the Mun-Chi River Basin. The proposed methodological framework provides a continuous time series of flow discharge at multiple stations within the watershed, offering valuable insights for sustainable water resource management strategies in river systems under changing climate and land use conditions, and supporting future studies on environmental issues.

Design and Analysis of a Base Bleed Unit for the Drag Reduction of a High-Power Rocket Operating at Transonic Speeds

In the present study, a passive flow device is considered for drag reduction purposes through implementation in a transonic high-power rocket. The high-power rocket serves as a reference platform that, apart from the operating conditions, enforces several constraints in terms of available volume and placement locations. A step-by-step methodology is suggested, where the unit is initially broken down into an inlet and an outlet component. The flow field is investigated by means of computational modeling (CFD), where the Reynolds-averaged Navier–Stokes equations are solved coupled with turbulence models that vary depending on the design phase and the individual component. In the first design phase, the best alternative configuration is selected for each component by comparing mass flow rates and discharge coefficients. In the second design phase, each component is analyzed in greater detail based on the first phase results. Indicatively, the protruding inlet diffuser-type channel is converted into a protruding inlet nozzle-type channel to avoid choked flow phenomena, and a nozzle geometry is selected as the outlet amongst the other considered scenarios. The two components are eventually integrated into a common base bleed unit and a final assessment is made. The computational results are used to predict the performance and trajectory of the rocket through a well-established trajectory software. The overall methodology is validated against full-scale test flight data. The results show that the base bleed unit developed in the framework of this study yields a drag reduction of approximately 15% at transonic speeds without impacting the rocket mass and stability.

Estimating sediment transport capacity on sloping farmland on the Loess Plateau considering soil particle size characteristics

The sediment transport capacity (Tc) is essential for understanding soil erosion and creating soil erosion prediction models. Although many Tc equations exist, they are not universally applicable to sloping farmland on the Loess Plateau. To tailor Tc equations for this region, Tc for four soils (Shenmu Inceptisol (SMI), Shenmu Entisol (SME), Ansai Inceptisol (AS), and Yongshou Alfisol (YS)) from sloping farmland on the Loess Plateau was determined through flume tests with slopes ranging from 15.84 % to 38.39 % and flow discharges of 0.05 to 0.11 m2 min−1. Additionally, appropriate particle size characteristics were selected to distinguish the soil types. The results revealed that the Tc of SME exceeded that of YS, followed by SMI and AS in descending order. The Tc of the four individual soils increased exponentially with flow discharge (Q) and slope (S). Tc for individual soils could be satisfactorily predicted using power functions of mean velocity, shear stress (τ), stream power (ω), or effective stream power (R2: 0.661–0.950, MAE: 0.020–0.110, RMSE: 0.023–0.151), with ω being identified as an optimal hydraulic parameter for simulating Tc. In contrast, the unit stream power was a poor predictor of Tc for individual soils (R2: 0.403–0.700, MAE: 0.035–0.123, RMSE: 0.040–0.161). The median particle size (D50), sorting coefficient, and kurtosis (Kg) exhibited highly significant positive correlations with Tc (P < 0.01). Finally, a quadratic power equation for Q, S, D50, and Kg, along with two ternary power equations for ω (or τ), D50, and Kg were newly constructed, all with satisfactory accuracies (R2: 0.808–0.826, MAE: 0.061–0.063, RMSE: 0.086–0.090). The inclusion of σ and Kg rectified the inaccuracies in predicting Tc for all four soils using Q and S equations or ω (or τ). The results of this study offer valuable insights into the construction of the Tc equations.

Fluvial bedload transport modelling: advanced ensemble tree-based models or optimized deep learning algorithms?

The potential of advanced tree-based models and optimized deep learning algorithms to predict fluvial bedload transport was explored, identifying the most flexible and accurate algorithm, and the optimum set of readily available and reliable inputs. Using 926 datasets for 20 rivers, the performance of three groups of models was tested: (1) standalone tree-based models Alternating Model Tree (AMT) and Dual Perturb and Combine Tree (DPCT); (2) ensemble tree-based models Iterative Absolute Error Regression (IAER), ensembled with AMT and DPCT; and (3) optimized deep learning models Long Short-Term Memory (LSTM) and Recurrent Neural Network (RNN) ensembled with Grey Wolf Optimizer. Comparison of the predictive performance of the models with that of commonly used empirical equations and sensitivity analysis of the driving variables revealed that: (i) the coarse grain-size percentile D 90 was the most effective variable in bedload transport prediction (where D x is the xth percentile of the bed surface grain size distribution), followed by D 84, D 50, flow discharge, D 16, and channel slope and width; (ii) all tree-based models and optimized deep learning algorithms displayed ‘very good’ or ‘good’ performance, outperforming empirical equations; and (iii) all algorithms performed best when all input parameters were used. Thus, a range of different input variable combinations must be considered in the optimization of these models. Overall, ensemble algorithms provided more accurate predictions of bedload transport than their standalone counterpart. In particular, the ensemble tree-based model IAER-AMT performed most strongly, displaying great potential to produce robust predictions of bedload transport in coarse-grained rivers based on a few readily available flow and channel variables.

Flow resistance of emergent rigid vegetation in steady flow

Abstract Enhanced understanding of flow resistance in open channels with emergent vegetation is essential for flood management and river ecosystem restoration. The presence of vegetation can significantly alter bed resistance, leading to a challenge in accurately predicting flow discharge, water levels, sediment transport, and bed deformation. Previous studies on vegetated flows have focused on vegetation resistance, on which the impact of vegetation has been ignored or poorly estimated. This study proposes a new analytical model, built upon the momentum conservation law, to predict flow resistance to vegetated zones in a plain bed without bed forms, explicitly quantifying bed resistance and vegetation resistance in a corollary manner. The proposed model is benchmarked against five typical sets of laboratory experiments. It is demonstrated that the present model using a modified logarithmic velocity distribution performs best, whereas that assuming a uniform velocity profile considerably overestimates the vegetation resistance and neglects the effect of vegetation on bed resistance. The ratio of bed resistance to the total resistance is shown to range between 5% and 40%, and it decreases with increasing vegetation density and decreases with water depth. Therefore, bed resistance cannot be ignored when modelling shallow water flow with sparsely distributed vegetation. It is also revealed that vegetation arrangements significantly affect flow resistance, and therefore a model incorporating the effect of vegetation arrangement performs better. Overall, the present model facilitates a viable and promising tool for quantifying flow resistance in emergent vegetated channels.

Experimental Study of the Reaction of OH Radicals with Carbonyl Sulfide between 365 and 960 K: Kinetics and Products

Reaction OH + OCS ® products (1) has been studied in a discharge–flow reactor combined with modulated molecular beam mass spectrometry. The reaction rate constant has been determined under pseudo-first-order conditions through monitoring OH decays in a high excess of OCS: k1 = (2.35 ± 0.25) × 10−12 exp(−(2144 ± 56)/T) cm3 molecule−1 s−1 at T = 365–960 K (the uncertainties represent precision at the 2σ level, the total 2σ relative uncertainty including statistical and systematic errors on the rate constant being 20% at all temperatures). The rate constant of reaction (1) was found to be similar at a total helium pressure of 1, 2, and 8 torr at around 500 K. The SH radical was identified as the primary product of the reaction, and its yield was determined to be about 100% at T = 500 and 750 K. The kinetic and mechanistic data from the present study are compared to previous experimental and theoretical work.

Physics-informed neural networks for solving flow problems modeled by the 2D Shallow Water Equations without labeled data

This paper investigates the application of physics-informed neural networks (PINNs) to solve free-surface flow problems governed by the 2D shallow water equations (SWEs). Two types of PINNs are developed and analyzed: a physics-informed fully connected neural network (PIFCN) and a physics-informed convolutional neural network (PICN). The PINNs eliminate the need for labeled data for training by employing the SWEs, initial and boundary conditions as components of the loss function to be minimized. Results from a set of idealized and real-world tests showed that the prediction accuracy and computation time (i.e., training time) of both PINNs may be less affected by the resolution of the domain discretization when compared against solutions by a Finite Volume (FV) model. Overall, the PICN shows a better trade-off between computational speed and accuracy than the PIFCN. Also, our results for the idealized problems indicated that PINNs can provide more than 5 times higher prediction accuracy than the FV model, while the FV simulation with coarse resolution (e.g., 10 m) can provide sub-centimeter accurate (RMSE) solutions at least one order of magnitude faster than the PINNs. Results from a river flood simulation showed that PINNs delivered better speed-accuracy trade-off than the FV model in terms of predicting the water depth, while FV models outperformed the PINNs for predictions of total flow discharge.

Sustainable energy storage solutions for coal-fired power plants: A comparative study on the integration of liquid air energy storage and hydrogen energy storage systems

With the majority of the world's energy demand still reliant on fossil fuels, particularly coal, mitigating the substantial carbon dioxide (CO2) emissions from coal-fired power plants is imperative for achieving a net-zero carbon future. Energy storage technologies offer a viable solution to provide better flexibility against load fluctuations and reduce the carbon footprint of coal-fired power plants by minimizing exergy losses, thereby achieving better energy efficiency. This work focuses on developing two such energy storage technologies: Liquid Air Energy Storage (LAES) and Hydrogen Energy Storage (HES), and their integration strategies with a sub-critical coal-fired power plant. The performance of the integrated systems is analyzed based on key parameters like energy storage capacity, net unit power output during charging and discharging, round-trip efficiencies, and net unit efficiencies at different operating load conditions of the plant. Our results show that during the charging cycles, by increasing the air flow rate in LAES and the hydrogen production rate in HES, the net unit efficiency of the integrated plant decreases by 3–10% at different load conditions, while the energy-based round-trip efficiency increases with increasing liquid air and hydrogen flow rates during the discharge cycles. For the HES system, utilization of the produced hydrogen in the fuel cells gives 40–50% better roundtrip efficiencies than co-firing hydrogen in the boiler at full and minimum load and it increases with increasing hydrogen flow rates. While HES has shown a better overall net unit efficiency (41.5%, in fuel cell scenario) of the integrated unit than the LAES system (40%) for the base case operation, LAES shows superior round-trip efficiencies when operated at higher liquid air discharge flow rates (>80 kg/s). The results provide insights into the system modeling of LAES and HES integrated with a sub-critical coal power plant, contributing to the advancement of sustainable energy storage solutions.

The riverbank vegetation for mitigating the adverse effects of sediment dredging

AbstractSediment dredging has been an ever‐growing issue, especially in developing nations with high demand for concrete filler material. River systems are adversely affected by sediment mining, resulting in decreased stability of the riverbed and riverbanks. Nature‐based solutions for riverbank erosion have been a research topic that has led to the proposal of vegetation on the riverbanks. However, little is known about the extent of riverbank vegetation required to negate the devastating effects of sediment mining because dense vegetation severely affects the flow structure and becomes a waste trap. This experimental study uses sparsely dense, flexible, and bladed vegetation to study the annulment effects of vegetation against the existing mining pit. Near‐bed turbulence and sediment transport have increased in the test section in the presence of a mining pit. The increase in near‐bed streamwise and transverse Reynolds shear stresses helped us understand the increased sediment movement in streamwise and lateral directions. The morphology of the test section showed increased riverbed erosion at the beginning of the test segment. The entire cross‐section was levelled at the end of the test section, and aggradation was downstream of the test segment. In contrast, in the vegetated riverbank case, the initial profile of the bank was almost unchanged for the same discharge of flow and upstream sand pit. The sparse vegetation overperformed the intended negation effects. This study establishes that sparse vegetation would perform better in maintaining the channel morphology, which otherwise in dense vegetation would have faced a high erosion rate in the main channel while giving the same protection to the riverbanks.

Field physical model tests on the mechanism of river blocking by debris flow in the middle reaches of the Dadu River, Southwest China.

Debris flow is a typical natural disaster in the middle reaches of the Dadu River, Southwest China. Field physical model tests were conducted to reveal the mechanism of river blocking by debris flow in the middle reaches of the Dadu River. The dynamic processes of riHver blocking by debris flows were revealed, and based on which three typical river-blocking modes of debris flow are observed, i.e. thrust-type river blocking, mixed-flow-type river blocking and progressive river blocking. The test results showed that the material composition of debris flows plays an important role in the river-blocking mode, only the tests that adopted the mixed soil and gravel exhibited the thrust-type river blocking mode. The material composition has a controlling effect on the thrust-type river-blocking model. Mixed-flow-type river-blocking mode appears most often in the tests with an intersection angle of 60°, because the small intersection angle is conducive to the mixing of the debris flow and the water in the main channel. The debris flows composed of sand tend to block the river with mixed-flow-type river-blocking mode, accounting for 50% of the occurrences in the model tests. The high flow rate and discharge in the main channel and the low flow rate and discharge in the branch channel are the key factors controlling the progressive river-blocking mode. The test results in this study can support the debris flow disaster prevention and mitigation in this area.

Optimal operation of the dam reservoir in real time based on generalized structure of group method of data handling and optimization technique

The historical data on water intake into the reservoir is collected and used within the framework of a deterministic optimization method to determine the best operating parameters for the dam. The principles that have been used to extract the best values of the flow release from the dam may no longer be accurate in the coming years when the inflow to dams will be changing, and the results will differ greatly from what was predicted. This represents this method’s main drawback. The objective of this study is to provide a framework that can be used to guarantee that the dam is running as efficiently as possible in real time. Because of the way this structure is created, if the dam’s inflows change in the future, the optimization process does not need to be repeated. In this case, deep learning techniques may be used to restore the ideal values of the dam’s outflow in the shortest amount of time. This is achieved by accounting for the environment’s changing conditions. The water evaluation and planning system simulator model and the MOPSO multi-objective algorithm are combined in this study to derive the reservoir’s optimal flow release parameters. The most effective flow discharge will be made feasible as a result. The generalized structure of the group method of data handling (GSGMDH), which is predicated on the results of the MOPSO algorithm, is then used to build a new model. This model determines the downstream needs and ideal release values from the reservoir in real time by accounting for specific reservoir water budget factors, such as inflows and storage changes in the reservoir. Next, a comparison is drawn between this model’s performance and other machine learning techniques, such as ORELM and SAELM, among others. The results indicate that, when compared to the ORELM and SAELM models, the GSGMDH model performs best in the test stage when the RMSE, NRMSE, NASH, and R evaluation indices are taken into account. These indices have values of 1.08, 0.088, 0.969, and 0.972, in that order. It is therefore offered as the best model for figuring out the largest dam rule curve pattern in real time. The structure developed in this study can quickly provide the best operating rules in accordance with the new inflows to the dam by using the GSGMDH model. This is done in a way that makes it possible to manage the system optimally in real time.

Application of One-Dimensional Hydrodynamic Coupling Model in Complex River Channels: Taking the Yongding River as an Example

River conditions are complex and affected by human activities. Various hydraulic structures change the longitudinal slope and cross-sectional shape of the riverbed, which has a significant impact on the simulation of water-head evolution. With continuous population growth, the hydrological characteristics of the Yongding River Basin have undergone significant changes. Too little or too much water discharge may be insufficient to meet downstream ecological needs or lead to the wastage of water resources, respectively. It is necessary to consider whether the total flow in each key section can achieve the expected value under different discharge flows. Therefore, a reliable computer model is needed to simulate the evolution of the water head and changes in the water level and flow under different flow rates to achieve efficient water resource allocation. A one-dimensional hydrodynamic coupling model based on the Saint-Venant equations was established for the Yongding River Basin. Different coupling methods were employed to calibrate the coupling model parameters, using centralised water replenishment data for the autumn of 2022, and the simulation results were verified using centralised water replenishment data for the spring of 2023. The maximum error of the water-head arrival time between different river sections was 4 h, and the maximum error of the water-head arrival time from the Guanting Reservoir to each key cross-section was 6 h. The maximum flow error was less than 5 m3/s, and the changing trend of the flow over time was consistent with the measured data. The model effectively solved the problem of low accuracy of the water level and flow calculation results when using the traditional one-dimensional hydrodynamic model to simulate the flow movement of complex river channels in the Yongding River. The output results of the model include the time when the water head arrives at the key section, the change process of the water level and flow of each section, the change process of the water storage of lakes and gravel pits, and the change process of the total flow and water surface area of the key section. This paper reports data that support the development of an ecological water compensation scheme for the Yongding River.

Plasma emission spectroscopy and optical properties of reactive-sputtered silicon oxynitride films

Silicon oxynitride (SiO x N y ) thin films were synthesized via reactive direct current magnetron sputtering under different reactive gas mass flow ratios (O2:N2) and discharge powers. The process was monitored by optical emission spectroscopy (OES), while spectroscopic ellipsometry was used to characterize the optical properties of the thin films and deposition rates. In this work, the plasma generated under different deposition parameters is analyzed by monitoring the emission lines of different species (Si I, Ar I, O2, and N2) and these results are then correlated with the corresponding target poisoning process and the optical properties of the grown thin films. According to the spectral analysis, the emission lines proved to be sensitive to the synthesis process as it was possible to differentiate deposition variations when other parameters remained unchanged. Furthermore, similar plasma conditions determined via the emission of different species were found to produce consistent thin film optical properties and vice versa. OES showed to be an effective method of monitoring and controlling the deposition of SiO x N y thin films with specific compositions.

Numerical estimation of discharge coefficient for non-circular bottom intake racks

Current research presents a comprehensive numerical study on the performance of riverbed intake systems equipped with non-circular cross section racks. Three types of bottom racks, such as rhombus bars, rounded-edge rectangle bars, and circular bars, were numerically modeled using Flow3D software with different geometric and hydraulic parameter, all in super critical approaching flow in clear water condition. Subsequently, changes in diverted discharge ratio (DDR) of bottom racks and factors affecting its intensity and manner of changes, were studied using model results. The study reveals that the RNG k-ε turbulence model accurately represents the flow field around the bottom racks. The results indicated that the DDR changes are directly related to rack length changes but is inversely related to the rack slope and upstream flow discharge. Also, rhombus bars outperform circular and rounded bars, with 23.34% and 35.92% higher flow diversion, respectively, attributed to the formation of more negative pressures between bars. The main focus of the present study was on accurate and complete estimation of the diverted discharge coefficient (Cd) for racks with different bar shapes—especially non-circular bars using the results of the constructed numerical model. Proposed relations for the diverted discharge coefficient (DDC), especially for non-circular bars, were rigorously validated and showed high accuracy in predicting DDC under diverse hydraulic and geometric conditions.

Study of the Hydrological Mode of the Volga-Akhtuba Canal Depending on the Hydrograph of the Volzhskaya HPP Operation

The flow rates and water flow rates in the Volga-Akhtuba Canal, which is of critical importance in the watering of Akhtuba river and Volga-Akhtuba bottom land territory, have been determined in various hydrologic phases. Relationships between discharge flows through the Volgograd hydroelectric unit and flows through the Volga-Akhtuba Canal have been established. Graphs of the relationship between the water level in the lower canal pound and water flows through the Volgograd hydroelectric unit in various years are constructed. Recommendations are given for additional watering of the Volga-Akhtuba bottom land.

Clinical validation of grass pollen exposure chamber in patients with allergic rhinitis triggered by timothy grass.

The fluctuation in concentrations of airborne allergens frequently presents a challenge to assessing the efficacy of allergen immunotherapy (AIT) in 'field' studies. Allergen exposure chambers (AECs) are specialized medical installations developed to expose individuals to allergens at defined and consistent concentrations under a controlled environment. The aim of the study was to validate the provocation test with timothy grass pollen as well as to assess its safety in the AEC in patients with allergic rhinitis. In the ALLEC® AEC, varying concentrations of timothy grass pollen were dispersed. Allergic symptoms were measured by total nasal symptom score (TNSS), acoustic rhinometry, peak nasal inspiratory flow (PNIF) and nasal discharge volume. Lung function, assessed through peak expiratory flow rate (PEFR) and forced expiratory volume in the first second (FEV1), was used to evaluate safety. The consistency of the test was proved by the stability of environmental conditions, including temperature, humidity and CO2 levels, as well as constant concentrations of grass pollen at predetermined levels ranging from 1000 to 10,000 particles per cubic meter (p/m3). Allergic individuals developed symptoms at concentrations of 3000 p/m3 and above, across all measured endpoints. Lung function was not affected throughout all the challenges. The reproducibility of symptoms was confirmed throughout the tests. The concentration of 8000 p/m3 together with a challenge duration of 120 min was found to be optimal. The study demonstrates that the ALLEC® grass pollen exposure chamber provides a reliable and safe method for inducing repeatable symptoms in patients with allergic rhinitis. This approach can be effectively applied for allergy diagnostics and clinical endpoint determination during AIT.

Numerical modelling of flow field at shaft spillways with the marguerite-shaped inlets

By decreasing the entrained air flow discharge and improving the hydraulic characteristics of vertical shaft spillways, Marguerite-shaped inlets (MSIs) can mitigate the effects of swirling flow surrounding their inlet. The hydraulic and hydrodynamic characteristics of flow around MSIs under orifice flow regime were numerically investigated, applying different geometrical parameters. This inlet configuration can decrease the strength of swirling flow and increase the flow discharge through the shaft. The finite-volume method and the re-normalisation group k–ε turbulence model were employed to solve the governing equations of motion in a cylindrical coordinate system and a two-phase air–water flow on the water free-surface. Increasing the height and length of the blades of the MSIs was found to increase the area of the barriers against swirling flow, weaken the swirling flow strength, engender a more uniform flow and lower the water free-surface level. Extremely long or high blades, however, resulted in an intense collision of the flow with the spillway and increased the water free-surface level and the swirling flow strength at the MSI.