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Here, we present the results of turbulent flow structures and their influence on aeolian sand transport over gobi surfaces based on quadrant analysis. The results show that the classified turbulent structures over gobi accounted for 43%–44% of the time frequency and contributed ∼97% to the Reynolds stress, yet the contribution rates to sand transport rate ranged from 45% to 52%. Sweeps (Quadrant 4) and ejections (Q2) were the two most frequent events and accounted for 70% of the total frequency for the classified turbulent structures. Sweeps made a major contribution of 51%–57% to sand transport rate over gobi. Outward interactions (Q1) were relatively rare, but they individually entrained as much sand as sweeps of comparable magnitude and duration. The turbulent structures over gobi show similar behaviors comparable to those of water flows over gravel riverbeds or rough seabeds yet different from those of air flow over flat sand surfaces. Plain Language Summary Turbulence is the driving factor for aeolian sand transport. Turbulence behavior over gobi, a major type of rough land surface in Asia, and its influence on sand transport are poorly understood. Quadrant analysis has been widely used to evaluate boundary layer turbulence based on the streamwise (u′) and vertical (w′) fluctuating wind speed components from the mean. Four distinct quadrants can be defined, that is, outward interactions (Q1) (u′ > 0, w′ > 0), ejections (Q2) (u′ < 0, w′ > 0), inward interactions (Q3) (u′ < 0, w′ < 0), and sweeps (Q4) (u′ > 0, w′ < 0). The quadrant analysis shows that sweeps and ejections were the two most frequent turbulent structures over gobi, accounting for a total frequency of 70%. Sweeps made the largest contribution to sand transport rate over gobi. In contrast, outward interactions were individually as effective as sweeps, and they contributed less to sand transport rate than sweeps only because they were less common. The presence of gravel on the gobi surface affects the surrounding flow field and makes the turbulent structures different from those over flat sand surfaces, highlighted by the more frequent occurrence of ejections and sweeps, whereas they show similar characteristics to those over gravel riverbeds or rough seabeds. Key Points Turbulent flow structures over a gobi surface and their impact on sand transport rate were examined Sweeps made the largest contribution to sand transport rate over gobi, while outward interactions were individually as effective as sweeps The behavior of turbulent flow over gobi surfaces shows similar turbulence characteristics to water flows over rough riverbeds or seabeds

The exchange of momentum, heat and trace gases between atmosphere and surface is mainly controlled by turbulent fluxes. Turbulent mixing is usually parametrized using Monin–Obukhov similarity theory (MOST), which was derived for steady turbulence over homogeneous and flat surfaces, but is nevertheless routinely applied to unsteady turbulence over non-homogeneous surfaces. We study four years of eddy-covariance measurements at a highly heterogeneous alpine valley site in Finse, Norway, to gain insights into the validity of MOST, the turbulent transport mechanisms and the contributing coherent structures. The site exhibits a bimodal topography-following flux footprint, with the two dominant wind sectors characterized by organized and strongly negative momentum flux, but different anisotropy and contributions of submeso-scale motions, leading to a failure of eddy-diffusivity closures and different transfer efficiencies for different scalars. The quadrant analysis of the momentum flux reveals that under stable conditions sweeps transport more momentum than the more frequently occurring ejections, while the opposite is observed under unstable stratification. From quadrant analysis, we derive the ratio of the amount of disorganized to organized structures, that we refer to as organization ratio (OR). We find an invertible relation between transfer efficiency and corresponding organization ratio with an algebraic sigmoid function. The organization ratio further explains the scatter around scaling functions used in MOST and thus indicates that coherent structures modify MOST. Our results highlight the critical role of coherent structures in turbulent transport in heterogeneous tundra environments and may help to find new parametrizations for numerical weather prediction or climate models.

Integrated quadrant analysis is a novel technique to identify and to characterize the trajectory and strength of turbulent coherent structures in the atmospheric surface layer. By integrating the three-dimensional velocity field characterized by traditional quadrant analysis with respect to time, the trajectory history of individual coherent structures can be preserved with Eulerian turbulence measurements. We develop a method to identify the ejection phase of coherent structures based on turbulence kinetic energy (TKE). Identifying coherent structures within a time series using TKE performs better than identifying them with the streamwise and vertical velocity components because some coherent structures are dominated by the cross-stream velocity component as they pass the sensor. By combining this identification method with the integrated quadrant analysis, one can animate or plot the trajectory of individual coherent structures from high-frequency velocity measurements. This procedure links a coherent ejection with the subsequent sweep and quiescent period in time to visualize and quantify the strength and the duration of a coherent structure. We develop and verify the method of integrated quadrant analysis with data from two field studies: the Eclipse Boundary Layer Experiment (EBLE) in Corvallis, Oregon in August 2017 (grass field) and the Vertical Cherry Array Experiment (VACE) in Linden, California in November 2019 (cherry orchard). The combined TKE identification method and integrated quadrant analysis are promising additions to conditional sampling techniques and coherent structure characterization because the identify coherent structures and couple the sweep and ejection components in space. In an orchard (VACE), integrated quadrant analysis verifies each coherent structure is dominated by a sweep. Conversely, above the roughness sublayer (EBLE), each coherent structure is dominated by an ejection.

The noise radiated from ships can be used for their identification and classification using passive sonar systems. Several techniques have been proposed for military ship classification based on acoustic signatures, which can be acquired through controlled experiments performed in an acoustic lane. The cost for such data acquisition is a significant issue since the ship and crew have to be dislocated from the fleet. In addition, the experiments have to be repeated for different operational conditions, taking a considerable amount of time. Even with this massive effort, the scarce amount of data produced by these controlled experiments may limit further detailed analyses. In this paper, deep learning models are used for full exploitation of such acquired data, envisaging passive sonar signal classification. A drawback of such models is the large number of parameters, which requires extensive data volumes for parameter tuning along the training phase. Thus, generative adversarial networks (GANs) are used to synthesize data so that a larger data volume can be produced for training convolutional neural networks (CNNs), which are used for the classification task. Different GAN design approaches were evaluated and both maximum probability and class-expert strategies were exploited for signal classification. Special attention was paid to how the expert knowledge might give a handle on analyzing the performance of the various deep learning models through tests that mirrored actual deployment. An accuracy as high as 99.0±0.4% was achieved using experimental data, which improves upon previous machine learning designs in the field.

Climate change is expected to result in increased occurrences of extreme weather events such as heat waves and cold spells. Urban planning responses are crucial for improving the capacity of cities and communities to deal with significant temperature variations across seasons. This study aims to investigate the relationship between urban temperature fluctuations and urban morphology throughout the four seasons. Through quadrant and statistical analyses, built-environment factors are identified that moderate or exacerbate seasonal land surface temperatures (LSTs). The focus is on Seoul, South Korea, as a case study, and seasonal LST values are calculated at both the grid (100 m × 100 m) and street block levels, incorporating factors such as vegetation density, land use patterns, albedo, two- and three-dimensional building forms, and gravity indices for large forests and water bodies. The quadrant analysis reveals a spatial segregation between areas demonstrating high LST adaptability (cooler summers and warmer winters) and those displaying LST vulnerability (hotter summers and colder winters), with significant differences in vegetation and building forms. Spatial regression analyses demonstrate that higher vegetation density and proximity to water bodies play key roles in moderating LSTs, leading to cooler summers and warmer winters. Building characteristics have a constant impact on LSTs across all seasons: horizontal expansion increases the LST, while vertical expansion reduces the LST. These findings are consistent for both grid- and block-level analyses. This study emphasizes the flexible role of the natural environment in moderating temperatures.

PurposeThis paper proposes an approach for prioritizing Risk Mitigation (RMTG) approaches in perishable food Supply Chains (SCs).Design/methodology/approachAn integrative approach has been proposed, based on the risk typology and Supply Chain RMTG (SCRMTG) approaches literature review, integrating trending Failure Modes and Effects Analysis (FMEA), Quality Function Deployment (QFD) and Quadrant Analysis (QA). Risks are prioritized using Trending FMEA. SCRMTG approaches are prioritized by considering the prioritized risks using QFD and also based on their strategic importance and ease of Benchmarking via QA. The proposed approach has been examined in a dairy-manufacturing company.FindingsFindings indicated supplying the imported machine parts, old machines and delayed new product introduction, respectively, as the most prominent supply, process and demand risks and multiple sourcing, upgraded machinery, hiring skilled staff and training, collaboration with downstream partners as the highly prioritized SCRMTG approaches based on the strategic importance and ease of benchmarking.Research limitations/implicationsThe results of this study increase the awareness of SC managers and provide the company with a framework of risk management and the insights to manage SCRs in the dairy industry more effectively and efficiently.Originality/valueWhile the literature review indicates that only a few studies have been focused on prioritizing SCRMTG approaches concerning each type of SCRs, SCRMTG approaches are prioritized based on the SCRs type. Other innovations include QFD development based on the FMEA and SCRMTG approaches, considering the probability of risk occurrence, severity-impact cost and risk recovery duration in trending FMEA instead of the three risk factors in traditional FMEA.

Accurate representation of heat fluxes is crucial for understanding land–atmosphere interactions and improving atmospheric simulations. However, a common issue arises with flux imbalance, where the measured turbulent heat flux tends to be underestimated due to the nonlocal effects of atmospheric secondary circulations. This study evaluated four flux imbalance prediction models by analyzing data from large eddy simulations performed over heterogeneous land surfaces. For that, a checkerboard pattern of soil moisture was used to define the lower boundary conditions for the atmosphere, across heterogeneity scales ranging from 50 m to 2.4 km. The results show that the selected models can effectively predict flux imbalance when provided with proper semi-empirical factors. The presence of two distinct secondary circulations, thermally-induced mesoscale circulation and turbulent organized structures, account for the nonlinear effect of the heterogeneity scale on the flux imbalance, but it does not affect the performance of the selected models. This study suggests that the flux imbalance prediction models are useful for improving e.g. eddy-covariance measurements. Additionally, a quadrant analysis showed an increasing difference between ejections and sweeps with height, which explains the decrease and increase of the turbulent heat flux and flux imbalance, respectively, and underscores the importance of accounting for vertical variations in turbulent fluxes to represent atmospheric processes accurately.

Bridge pier is a common feature in hydraulic structure. Its impact to the river usually occurs in group form rather than single pier, so this challenging piers-group influence towards river hydraulics and turbulence needs to be explored. In this paper, the measurements were conducted using an Acoustic doppler velocimeter (ADV) to study velocities in three dimensions (longitudinal, transversal, and vertical). Based on the experimental data, we have observed reversed depth-averaged velocity vector after each pier in the group of three-pier. The analysis has been conducted on the contribution of each bursting event to Reynolds shear stress (RSS) generation, in order to identify the critical events and turbulence structures around the piers. In the upstream near-wake flow in the bed-wall layer, strong sweep and ejection events have been observed; while at downstream, sweeps were more dominant. The pattern of burst changed in the outer layer of flow, where ejections were more dominant. Furthermore, the contribution fractional ratio to RSS variation at hole size H = 0 indicates that sweeps and ejections were significantly generated at the near wake-flow in upstream.

A comprehensive investigation is undertaken to discern the structure of momentum flux, turbulent kinetic energy, and scalar fluxes like heat, CO2, and H2O in the atmospheric surface layer (ASL) at the Thumba Equatorial Rocket Launching Station—a coastal station on the west coast of southern peninsular India. The vertical transport, transfer efficiency, and dissimilarity between flux transport are studied as a function of stability using data collected over 1 year. The transfer efficiency for heat fluxes and momentum exhibits a strong dependence on stability (ζ). However, the transfer efficiency of passive scalars CO2 and H2O displays no apparent dependence on ζ. The correlation between fluxes and squared coherence estimates is evaluated to study the dissimilarity between flux transport. The correlation is strongest among momentum and heat fluxes and between CO2 and H2O fluxes and shows a dependence on the prevailing stability conditions. However, the influence of stability is not evident for the various other combinations. The momentum and heat flux transport is dissimilar for unstable conditions, and it becomes similar during the transition from unstable to near-neutral conditions. The quadrant analysis is employed to study the contribution of different fluid motions to the aforementioned turbulent fluxes. Except for CO2 and H2O fluxes, where all the quadrants have an equal contribution, ejections and sweeps are the dominating contributors for momentum and heat fluxes. The stability conditions greatly determine the ejection-sweep balance for heat flux, while some changes in duration and impact fraction are also detectable for momentum flux. Furthermore, contour maps of joint-probability function (JPDF) of vertical velocity fluctuations (w′) with streamwise velocity fluctuation (u′), temperature fluctuation (T′), and scalar fluctuations, respectively, are also presented. The dominance of the ejection and sweep cycles for turbulent fluxes provide evidence for the presence and importance of coherent structures in ASL.

Large-eddy simulation (LES) is used to investigate the effects of building-height variability on turbulent flows over an actual urban area, the city of Kyoto, which is reproduced using a 2-m resolution digital surface dataset. Comparison of the morphological characteristics of Kyoto with those of European, North American, and other Japanese cities indicates a similarity to European cities but with more variable building heights. The performance of the LES model is validated and found to be consistent with turbulence observations obtained from a meteorological tower and from Doppler lidar. We conducted the following two numerical experiments: a control experiment using Kyoto buildings, and a sensitivity experiment in which all the building heights are set to the average height over the computational region hall. The difference of Reynolds stress at height z=2.5hall between the control and sensitivity experiments is found to increase with the increase in the plan-area index (λp) for λp>0.32. Thus, values of λp≈0.3 can be regarded as a threshold for distinguishing the effects of building-height variability. The quadrant analysis reveals that sweeps contribute to the increase in the Reynolds stress in the control experiment at a height z=2.5hall. The exuberance in the control experiment at height z=0.5hall is found to decrease with increase in the building-height variability. Although the extreme momentum flux at height z=2.5hall in the control experiment appears around buildings, it contributes little to the total Reynolds stress and is not associated with coherent motions.