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An idealized model is used to examine the tropospheric response to sudden stratospheric warmings (SSWs), by imposing transient stratospheric momentum torques tailored to mimic the wave-forcing impulse associated with spontaneously occurring SSWs. Such an approach enables us to examine both the ∼2–3-week forcing stage of an SSW during which there is anomalous stratospheric wave-activity convergence, as well as the recovery stage during which the wave forcing abates and the stratosphere radiatively recovers over 2–3 months. It is argued that applying a torque is better suited than a heating perturbation for examining the response to SSWs, due to the meridional circulation that is induced to maintain thermal-wind balance (i.e., the “Eliassen adjustment”); an easterly torque yields downwelling at high latitudes and equatorward flow below, similar to the wave-induced circulation that occurs during spontaneously occurring SSWs, whereas a heating perturbation yields qualitatively opposite behavior and thus cannot capture the initial SSW evolution. During the forcing stage, the meridional circulation in response to an impulse comparable to the model’s internal variability is able to penetrate down to the surface and drive easterly-wind anomalies via Coriolis torques acting on the anomalous equatorward flow. During the recovery stage, after which the tropospheric flow has already responded, the meridional circulation associated with the stratosphere’s radiative recovery appears to provide the persistent stratospheric forcing that drives the high-latitude easterly anomalies, whereas planetary waves are found to play a smaller role. This is then augmented by synoptic-wave feedbacks that drive and amplify the annular-mode response.

The Antarctic Slope Current (ASC) plays a central role in redistributing water masses, sea ice, and tracer properties around the Antarctic margins, and in mediating cross-slope exchanges. While the ASC has historically been understood as a wind-driven circulation, recent studies have highlighted important momentum transfers due to mesoscale eddies and tidal flows. Furthermore, momentum input due to wind stress is transferred through sea ice to the ASC during most of the year, yet previous studies have typically considered the circulations of the ocean and sea ice independently. Thus, it remains unclear how the momentum input from the winds is mediated by sea ice, tidal forcing, and transient eddies in the ocean, and how the resulting momentum transfers serve to structure the ASC. In this study the dynamics of the coupled ocean–sea ice–ASC circulation are investigated using high-resolution process-oriented simulations and interpreted with the aid of a reduced-order model. In almost all simulations considered here, sea ice redistributes almost 100% of the wind stress away from the continental slope, resulting in approximately identical sea ice and ocean surface flows in the core of the ASC in a fully spun-up equilibrium state. This ice–ocean coupling results from suppression of vertical momentum transfer by mesoscale eddies over the continental slope, which allows the sea ice to accelerate the ocean surface flow until the speeds coincide. Tidal acceleration of the along-slope flow exaggerates this effect and may even result in ocean-to-ice momentum transfer. The implications of these findings for along- and across-slope transport of water masses and sea ice around Antarctica are discussed.

An implementation of the actuator line method (ALM) is applied to a hovering helicopter rotor. This method, which is widely used for wind turbine simulations, replaces the rotor blades by momentum ...

Floating offshore wind turbines may experience large surge motions, which can cause blade–vortex interaction if they are similar to or faster than the local wind speed. Previous research hypothesized that this blade–vortex interaction phenomenon represented a turbulent wake state or even a vortex ring state, rendering the actuator disc momentum theory and the blade element momentum theory invalid. This hypothesis is challenged, and we show that the actuator disc momentum theory is valid and accurate in predicting the induction at the actuator in surge, even for large and fast motions. To accomplish this, we develop a dynamic inflow model that simulates the vorticity–velocity system and the effect of motion. The model's predictions are compared to other authors' results, a semi-free-wake vortex ring model, other dynamic inflow models, and CFD simulations of an actuator disc in surge. The results show that surge motion and rotor–wake interaction do not result in a turbulent wake or vortex ring state and that the application of actuator disc momentum theory and blade element momentum theory is valid and accurate when applied correctly in an inertial reference frame. In all cases, the results show excellent agreement with the higher-fidelity simulations. The proposed dynamic inflow model includes a modified Glauert correction for highly loaded streamtubes and is accurate and simple enough to be easily implemented in most blade element momentum models.

Momentum technique has recently emerged as an effective strategy in accelerating convergence of gradient descent (GD) methods and exhibits improved performance in deep learning as well as regularized learning. Typical momentum examples include Nesterov's accelerated gradient (NAG) and heavy-ball (HB) methods. However, so far, almost all the acceleration analyses are only limited to NAG, and a few investigations about the acceleration of HB are reported. In this article, we address the convergence about the last iterate of HB in nonsmooth optimizations with constraints, which we name individual convergence. This question is significant in machine learning, where the constraints are required to impose on the learning structure and the individual output is needed to effectively guarantee this structure while keeping an optimal rate of convergence. Specifically, we prove that HB achieves an individual convergence rate of O(1/√t) , where t is the number of iterations. This indicates that both of the two momentum methods can accelerate the individual convergence of basic GD to be optimal. Even for the convergence of averaged iterates, our result avoids the disadvantages of the previous work in restricting the optimization problem to be unconstrained as well as limiting the performed number of iterations to be predefined. The novelty of convergence analysis presented in this article provides a clear understanding of how the HB momentum can accelerate the individual convergence and reveals more insights about the similarities and differences in getting the averaging and individual convergence rates. The derived optimal individual convergence is extended to regularized and stochastic settings, in which an individual solution can be produced by the projection-based operation. In contrast to the averaged output, the sparsity can be reduced remarkably without sacrificing the theoretical optimal rates. Several real experiments demonstrate the performance of HB momentum strategy.

A three-dimensional nonhydrostatic coastal model SUNTANS is used to study hyperpycnal plumes on sloping continental shelves with idealized domain setup. The study aims to examine the nonhydrostatic effect of the plunging hyperpycnal plume and the associated flow structures on different shelf slopes. The unstructured triangular grid in SUNTANS allows for local refinement of the grid size for regions in which the flow varies abruptly, while retaining low-cost computation using the coarse grid resolution for regions in which the flow is more uniform. These nonhydrostatic simulations reveal detailed three-dimensional flow structures in both transient and steady states. Via comparison with the hydrostatic simulation, we show that the nonhydrostatic effect is particularly important before plunging, when the plume is subject to significant changes in both the along-shore and vertical directions. After plunging, where the plume becomes an undercurrent that is more spatially uniform, little difference is found between the hydrostatic and nonhydrostatic simulations in the present gentle- and mild-slope cases. A grid-dependence study shows that the nonhydrostatic effect can be seen only when the grid resolution is sufficiently fine that the calculation is not overly diffusive. A depth-integrated momentum budget analysis is then conducted to show that the flow convergence due to plunging is an important factor in the three-dimensional flow structures. Moreover, it shows that the nonhydrostatic effect becomes more important as the slope increases, and in the steep-slope case, neglect of transport of the vertical momentum during plunging in the hydrostatic case further leads to an erroneous prediction for the undercurrent.

Factor momentum has formed the basis of factor timing strategies. We propose an alternative approach for timing factor portfolio returns by exploiting the information from their portfolio characteristics. Different combinations of dimension reduction techniques are employed to independently reduce the number of predictors and portfolios to predict. Characteristic-based models outperform factor momentum in terms of exact predictability as well as investment performance.

In distributed training, increasing batch size can improve parallelism, but it can also bring many difficulties to the training process and cause training errors. In this work, we investigate the occurrence of training errors in theory and train ResNet-50 on CIFAR-10 by using Stochastic Gradient Descent (SGD) and Adaptive moment estimation (Adam) while keeping the total batch size in the parameter server constant and lowering the batch size on each Graphics Processing Unit (GPU). A new method that considers momentum to eliminate training errors in distributed training is proposed. We define a Momentum-like Factor (MF) to represent the influence of former gradients on parameter updates in each iteration. Then, we modify the MF values and conduct experiments to explore how different MF values influence the training performance based on SGD, Adam, and Nesterov accelerated gradient. Experimental results reveal that increasing MFs is a reliable method for reducing training errors in distributed training. The analysis of convergent conditions in distributed training with consideration of a large batch size and multiple GPUs is presented in this paper.

The classical maximum intensity theory of Emanuel suggests that the maximum azimuthal wind of tropical cyclones (TCs) depends linearly on the ratio of surface enthalpy and momentum exchange coefficients (Ck and Cd). In this study a series of sensitivity experiments are conducted using the three-dimensional Cloud Model 1 (CM1), by fixing the ratio of Ck/Cd but varying the specific values of Ck and Cd simultaneously. Results show significant variations of simulated maximum intensities by varying Ck and Cd, even if their ratio is fixed. Overall the maximum intensity increases steadily with increasing Ck and Cd when their value is smaller than 1.00×10-3, and then this increase trend slows down with further increasing the coefficients. Two previous theoretical frameworks, one based on gradient-wind balance and the other one incorporating the unbalanced terms, are applied to calculate the maximum potential intensity (PI). The calculated value of the former one shows little variation with varying the specific values of Ck and Cd, while the latter one shows larger value with increasing both Ck and Cd. A further examination suggests that the unbalanced effect have played a key role in contributing to the increasing intensity with increasing Ck and Cd.

The Eulerian multifluid mathematical model is developed to describe the marine atmospheric boundary layer laden with sea spray under the high-wind condition of a hurricane. The model considers spray and air as separate continuous interacting turbulent media and employs the multifluid E–ϵ closure. Each phase is described by its own set of coupled conservation equations and characterized by its own velocity. Such an approach enables us to accurately quantify the interaction between spray and air and pinpoint the effect of spray on the vertical momentum transport much more precisely than could be done with traditional mixture-type approaches. The model consistently quantifies the effect of spray inertia and the suppression of air turbulence due to two different mechanisms: the turbulence attenuation, which results from the inability of spray droplets to fully follow turbulent fluctuations, and the vertical transport of spray against the gravity by turbulent eddies. The results of numerical and asymptotic analyses show that the turbulence suppression by spray overpowers its inertia several meters above wave crests, resulting in a noticeable wind acceleration and the corresponding reduction of the drag coefficient from the reference values for a spray-free atmosphere. This occurs at much lower than predicted previously spray volume fraction values of ∼10−5. The falloff of the drag coefficient from its reference values is more strongly pronounced at higher altitudes. The drag coefficient reaches its maximum at spray volume fraction values of ∼10−4, which is several times smaller than predicted by mixture-type models.

Aerodynamic roughness length ( z 0 m ) is a key parameter in the characterization of land surface turbulent heat fluxes and widely used in many surface and climate-related process models. The global products of time series of z 0 m at finer spatio-temporal resolution, however, have never been publicly available. Here we presented a practical method for global estimates of 500 m daily z 0 m with a combination of machine learning techniques, wind profile equation, observations from 273 sites and MODIS remote sensing data. Results showed that the random forest (RF) model outperformed the deep neural network (DNN) and convolutional neural network (CNN) models, and it could well reproduce the magnitude and temporal variability of daily z 0 m at almost all sites for all land cover types. In the validation of the RF-estimated daily z 0 m with the in-situ observations, the root mean square error (RMSE) varied between 0.02 m and 0.09 m, the mean absolute error (MAE) varied between 0.01 m and 0.05 m and the coefficient of determination ( R 2 ) was 1 for medium-to-high canopy shrublands, savannas and forests; for short-canopy croplands, grasslands and wetlands, the RMSE and MAE were 0.02 m and 0.01 m, respectively, and the R 2 varied between 0.94 and 1. Compared to the Climate Forecast System Version 2 (CFSv2, 0.3°/monthly) and ECMWF Reanalysis v5 (ERA5, 0.25°/monthly) products in 2019, the RF-estimated z 0 m was found to have the similar global spatial pattern but significantly larger temporal variability, and it also showed a higher and lower global mean of z 0 m over forests and non-forests, respectively. The RF-estimated z 0 m displayed a higher temporal variability but a similar global spatial pattern of this variability compared to the CFSv2, whereas the ERA5 z 0 m product exhibited almost no temporal variability except for grasslands and croplands. This study is beneficial for improving the simulation of the momentum, water and energy transfer between land and atmosphere and helping boost the development of high-resolution land surface models and Earth system models.

The paper describes a modified non-contact Hall sensor based centrifugal and momentum force type flow transducer with simple design, low cost and rugged construction. In this transducer two identical permanent magnets are fixed on the two ends of the common balance lever on which sensing U-tube and dummy U-tube are placed at equal distances from the pivot. The movement of lever ends with variation of flow rate, changes the magnet positions with respect to the two identical Hall sensors fixed at two locations just below the magnets. Thus the outputs of the Hall sensors supplied from a stabilized DC source vary with the variation of flow rate. The difference between these outputs is a DC voltage signal non-linearly related with flow rate.

Momentum stochastic gradient descent (MSGD) algorithm has been widely applied to many nonconvex optimization problems in machine learning (e.g., training deep neural networks, variational Bayesian inference, etc.). Despite its empirical success, there is still a lack of theoretical understanding of convergence properties of MSGD. To fill this gap, we propose to analyze the algorithmic behavior of MSGD by diffusion approximations for nonconvex optimization problems with strict saddle points and isolated local optima. Our study shows that the momentum helps escape from saddle points but hurts the convergence within the neighborhood of optima (if without the step size annealing or momentum annealing). Our theoretical discovery partially corroborates the empirical success of MSGD in training deep neural networks.

An accurate assessment of the hydro-environmental impacts of tidal range energy schemes, where the performance of the scheme has an impact on the marine environment and ecology, is crucial in optimising the design and development of such schemes. A proposal for a new coastally-attached impoundment, namely West Somerset Lagoon, has been investigated in this research and the numerical model TELEMAC-2D has been refined to model theimpacts of this scheme on the Bristol Channel and Severn Estuary. Domain decomposition was applied and full momentum conservation between the subdomains was included in the model by implementing momentum source terms at the turbine locations. The results have confirmed the importance of including full momentum conservation in modelling the effects of turbo-machinery in tidal lagoons. It was found that the operation of the scheme decreased the high water level slightly in the Bristol Channel and Severn Estuary, while there was a decrease in the low intertidal areas. The maximum velocity and bed shear stress were predicted to increase in the inner Bristol Channel, while they decreased noticeably across most of the interior of the lagoon, away from the turbine wakes. Furthermore, the operation of the lagoon significantly improved the water renewal in the region.

During the periods of sudden transition to online education, the opportunity to make applications that might attract students' attention to the course has decreased even more. Although this deficiency was tried to be eliminated with videos and simulations, it was not possible to ensure active participation of students in some cases. In this study, the Algodoo program, which can increase the efficiency of the teaching environment by ensuring active participation of students in online lessons and the applications that can be done about Impulse and momentum are explained in detail. A total of 6 different applications were carried out, 1 related to the subject of impulse, 1 related to the momentum, 2 related to the relationship between impulse and momentum change, and 2 related to momentum conservation. At the same time, while developing these applications, the adjustments made on the simulation and the reasons are explained in detail. In this way, both the introduction of the program and the sample application suggestion were presented. The values obtained as a result of the applications were calculated and compared both theoretically and on simulation in different ways. As a result, it has been observed that the values have internal consistency with each other and are also compatible with theoretical calculations. Algodoo program, which allows many interactive applications and can be downloaded for free, is a program that can be used both in lecturing and evaluation processes in physics lessons while online education process., Comment: 7 pages, published article

This paper examines if there are value and momentum effects in the New Zealand housing market across different regions. It is found that the short-term momentum effect exists with the winner regions in the past year outperforming the loser regions in the following year by 2.06%, mainly from capital gains, after adjusting for the market risk. The house returns exhibit long-term reversal with the winner regions in the last six years underperforming the loser regions in each of the next eight years due to lower capital gains. A value effect is present with regions with high rent-price ratios outperforming those with low rent-price ratios in each of the next seven years due to persistent higher rental yields. However, both the reversal effect and value effect can be explained by the market risk.

An adaptive clamping method (SGD-MS) based on the radius of curvature is designed to alleviate the local optimal oscillation problem in deep neural network, which combines the radius of curvature of the objective function and the gradient descent of the optimizer. The radius of curvature is considered as the threshold to separate the momentum term or the future gradient moving average term adaptively. In addition, on this basis, we propose an accelerated version (SGD-MA), which further improves the convergence speed by using the method of aggregated momentum. Experimental results on several datasets show that the proposed methods effectively alleviate the local optimal oscillation problem and greatly improve the convergence speed and accuracy. A novel parameter updating algorithm is also provided in this paper for deep neural network.

In the current state-of-the-art, high-loss flow in the endwall significantly influences compressor performance. Therefore, the control of endwall corner separation in compressor blade rows is important to consider. Based on the previous research of the Blended Blade and EndWall (BBEW) technique, which can significantly reduce corner separation, in combination with a non-axisymmetric endwall, the full-BBEW technique is proposed in this study to further reduce the separation in endwall region. The principle of the unchanged axial passage area is considered to derive the geometric method for this technique. Three models are further classified based on different geometric characteristics of this technique: the BBEW model, Inclining-Only EndWall (IOEW) model, and full-BBEW model. The most effective design of each model is then found by performing several optimizations at the design point and related numerical investigations over the entire operational conditions. Compared with the prototype, the total pressure loss coefficient decreases by 7%–9% in the optimized full-BBEW at the design point. Moreover, the aerodynamic blockage coefficient over the entire operational range decreases more than the other models, which shows its positive effect for diffusion. This approach has a larger decrease at negative incidence angles where the intersection of the boundary layer plays an important role in corner separation. The analysis shows that the blended blade profile enlarges the dihedral angle and creates a span-wise pressure gradient to move low momentum fluid towards the mainstream. Furthermore, the inclining hub geometry accelerates the accumulated flow in the corner downstream by increasing the pressure gradient. Overall, though losses in the mainstream grow, especially for large incidences, the full-BBEW technique effectively reduces the separation in corners.

We study a simple system of charges and currents, consisting of two electric dipoles that are driven by exponentially growing currents running between the ends of each dipole. The exponential time dependence allows the electric and magnetic fields to be calculated exactly. The forces between the dipoles must be evaluated carefully when the exponential growth is slow and are shown to not be equal and opposite. The imbalance is accounted for by the rate of change of momentum in the electromagnetic field, so that the total momentum is conserved even though Newton's third law fails. Implications for momentum conservation for “semistatic” slowly varying currents, for which the Biot–Savart law is applicable, are discussed.

There is great potential for carbon emission reduction in energy-enriched areas. It is important to master the spatiotemporal characteristics and driving factors of carbon emissions to achieve the goal of carbon emission reduction. Previous studies on carbon emissions mainly focused on the numerical changes in regional carbon emissions. There have been few studies on spatiotemporal characteristics, making it difficult to formulate carbon emission reduction strategies according to local conditions. This study is based on the carbon emission calculation method proposed by the Intergovernmental Panel on Climate Change (IPCC), taking the method of exploratory spatial data analysis (ESDA), standard deviation ellipse (SDE) analysis and the geographically weighted regression model (GWR) to analyse the spatiotemporal evolution characteristics and determinants and dividing regional types of carbon emissions. The results show that aggregate carbon emissions and other carbon emission indicators presented an upward trend from 2000 to 2016, and the growth momentum of carbon emissions was difficult to curb in the short term. The carbon emissions of the study area are relatively concentrated in spatial; the direction of carbon emissions presented a trend of “northeast–southwest”, and the main axis and centre of carbon emissions tend to move northward over time. There are six regional types of carbon emissions in the study area. The low total amount–low intensity–low pressure type (L-L-L) became the dominant regional type of carbon emissions. The results of the GWR model showed that the degree of influence of explanatory variables on carbon emissions in descending order is urbanization rate > industrial structure > population > population density > per capita GDP.

Riblets inspired by shark skin exhibit a great air drag reduction potential in many industries, such as the aircraft, energy, and transportation industries. Many studies have reported that blade riblets attain the highest air drag reduction ability, with a current limit of ∼11%. Here, we propose multilayer hierarchical riblets (MLHRs) to further improve the air drag reduction ability. MLHRs were fabricated via a three-layer hybrid mask lithography method, and the air drag reduction ability was studied in a closed air channel. The experimental results indicated that the maximum air drag reduction achieved with MLHRs in the closed channel was 16.67%, which represents a 52% higher reduction than the highest previously reported. Conceptual models were proposed to explain the experiments from a microscopic perspective. MLHRs enhanced the stability of lifting and pinning vortices, while vortices gradually decelerated further, reducing the momentum exchange occurring near the wall. This verified that MLHRs overcome the current air drag reduction limit of riblets. The conceptual models lay a foundation to further improve the air drag reduction ability of riblets.

Strong, regional sea level trends, mainly related to basin–wide wind stress anomalies, have been observed in the western tropical Pacific over the last three decades. Analyses of regional sea level in the densely populated regions of the neighbouring Australasian Mediterranean Sea (AMS) are hindered by its complex topography and respective studies are sparse. We used a series of global, eddy permitting ocean models, including a high–resolution configuration that resolves the AMS with horizontal resolution, forced by a comprehensive atmospheric forcing product over 1958–2016, to characterize the patterns and magnitude of decadal sea level variability in the AMS. The nature of this variability is elucidated further by sensitivity experiments with interannual variability restricted to either the momentum or buoyancy fluxes, building on an experiment employing a repeated-year forcing without interannual variability in all forcing components. Our results suggest that decadal fluctuations of ENSO account for over 80 % of the variability in all deep basins of the region, except for the central South China Sea (SCS). PDO–related changes are most pronounced in the shallow Arafura and Timor seas and in the central SCS. On average, buoyancy fluxes account for less than 10 % of decadal SSH variability, although this ratio is highly variable over time and can reach values of up to 50 %. In particular, our results suggest that buoyancy flux forcing amplifies the dominant wind stress driven anomalies related to ENSO cycles. Intrinsic variability is mostly negligible except in the SCS, where it accounts for 25 % of the total decadal SSH variability.

This paper studies the effects of “psychological momentum” on strategic behavior in single- and double-elimination tournaments. We show that in presence of both positive and negative momentum a single-elimination tournament elicits a higher total effort than that of a double-elimination tournament if and only if the positive momentum is insignificant and the negative momentum is significant. Regardless of momentum effects, a single-elimination tournament elicits a higher average effort per match than a double-elimination tournament does.

Temperature and salinity data, obtained by two snapshot surveys during 19–20 May 2019 and 12–25 September 2019 across the East China Sea (ECS) shelf, revealed that the Kuroshio intrusion to the north of 28°N comprised the Nearshore Kuroshio Branch Current (NKBC) and the Offshore Kuroshio Branch Current (OKBC) at the bottom of the ECS during spring 2019, and that the NKBC was weak during autumn 2019. The Regional Ocean Model System was used to reproduce the distribution of water masses and the current structure over the continental shelf of the ECS during 2019. Analyses of the momentum balances indicated that the cross-shore range and the intensity of the NKBC were determined by the combination of the geostrophic flow and bottom Ekman current. In comparison with that in May 2019, a weakened shoreward bottom Ekman current and an increased offshoreward geostrophic flow caused the disappearance of cross-shore range of the NKBC in September 2019. Meanwhile, a diminished northeastward alongshore geostrophic flow in September 2019 also weakened the intensity of the NKBC. Sensitivity experiments indicated that a strong southwestward wind can push the western (eastern) boundary of the NKBC further offshoreward (shoreward) by increasing (decreasing) the offshore geostrophic flow (bottom Ekman current). A weak Taiwan Warm Current (TWC) can move the eastern boundary of the NKBC shoreward by decreasing the onshore bottom Ekman current. A weak Kuroshio Current (KC) can move the eastern boundary of the NKBC shoreward by increasing the offshoreward geostrophic flow. Furthermore, a strong (weak) southwestward wind, weak (strong) TWC, and strong (weak) KC can diminish (enhance) the intensity of the NKBC. Of the three factors, the wind plays the major role in influencing the NKBC.

In this study, two fractional-based stochastic gradient (FSG) algorithms for time-delayed auto-regressive exogenous (ARX) models are proposed. By combining momentum and adaptive methods, a momentum-based FSG and an adaptive-based FSG algorithms are developed. These two FSG algorithms have faster convergence rates when compared with the stochastic gradient algorithm. The mechanism of the convergence is proved in theory. Furthermore, two simulated examples are presented to illustrate the efficiency of the new proposed algorithms.

Hadley circulation (HC) is a planetary-scale overturning circulation in the tropics that transports momentum, heat, and moisture poleward. In this study, we evaluate the strength and extent of the HC in the historical and future climate simulations of the Korean Meteorological Administration (KMA) Advanced Community Earth system model (K-ACE), which was recently developed by the National Institute of Meteorological Sciences of Korea. Compared with a reanalysis product, the overall structure of the HC is reasonably reproduced by the K-ACE. At the same time, it is also found that the Northern Hemisphere HC in the K-ACE is shifted southward by a few degrees, while the strength of the Southern Hemisphere (SH) HC is under-represented by approximately 20%. These biases in the strength and extent of the HC can be explained by biases in the eddy momentum flux and precipitation in the tropics. In the future climate simulations under the Shared Socioeconomic Pathway 5-Representative Concentration Pathway 8.5 scenario, the HCs in the K-ACE show a weakening and widening trend in both hemispheres, which is consistent with the projections of many Coupled Model Intercomparison Project Phase 6 models. A notable feature of the K-ACE is the widening of the SH HC, which takes place at a rate that is about double the multi-model mean. Climate models that share the component models with the K-ACE, such as UKESM, HadGEM3-GC31-LL, and ACCESS-CM2/ESM1, also show enhanced poleward expansion of the HC in the SH. This strong expansion is shown to be dominated by the expansion of the regional HC over the Pacific.

In molten phase metallurgical processes, mixing via gas injection has a vital role in obtaining a homogeneous product. The efficiency of mixing depends on operational variables such as gas flow rate and slag height as well as physical properties of the molten phases. A numerical simulation is conducted to study the above parameters in the flow behavior of a bottom-blown bath. The molten metal and the slag are modeled by water and oil, respectively. The numerical results, particularly the mixing time, are validated against experimental data. The results show that mixing time increases as the slag height increases and decreases as the density of the slag material increases. The mixing time decreases with an increase in the density of the primary phase; however, it increases as the surface tension between air and water increases. A case with properties close to a real molten metal is also modeled. The performance of the system is influenced by the momentum rather than the dissipative forces. Thus, the effect of the density of the molten phase on the mixing process is more pronounced compared to the effect of the surface tension between the air and the molten phase.

Hardware that can be manufactured from free and open source descriptions has gained a lot of momentum. This article gives a general introduction, focusing on electronics and integrated circuits, corresponding open ecosystems and organizations, and highlights benefits and challenges.

In this paper, a novel PAT system was analyzed and evaluated for utilization at very low specific speeds. Thus, a regenerative pump was employed due to the simplicity, compact size, stable features, low manufacturing costs, and very low specific speed. A theoretical analysis was developed based on the momentum exchange theory to predict the performance characteristics of the regenerative pump in reverse operation. Also, a 3D numerical simulation was implemented to study the performance of the pump in reverse mode. The numerical simulations were validated with experimental data of the pump. Results revealed that except for very low flow rates the presented model provides an acceptable prediction of the PAT performance. Results showed that at BEP, efficiency has decreased by about 20%. The head ratio and discharge ratio was obtained a bout 3.5 and 3.6, respectively. According to the results of entropy generation method, the impeller blades showed the most potential for energy losses. It was concluded that regenerative pump could be easily run as a low specific speed hydraulic turbine or a pressure reducing valve due to the cheapness, reliability and availability.

Background: Efficacy and safety of inebilizumab for treatment of neuromyelitis optica spectrum disorder in adults seropositive for aquaporin-4 (AQP4)–immunoglobulin (Ig) G were demonstrated in the 28-week randomized controlled period of the N-MOmentum study. Objective: To assess efficacy and safety of long-term inebilizumab treatment. Methods: Post hoc analysis was performed in 75 AQP4–IgG–seropositive participants receiving inebilizumab for ⩾4 years in the randomized controlled period and open-label extension of the N-MOmentum study. Results: Eighteen attacks occurred in 13 participants during inebilizumab treatment (annualized attack rate, 0.052 attacks/person-year). Twelve attacks occurred during the first year of treatment, and two each occurred in years 2–4. Disability scores remained stable throughout ⩾4 years of treatment. Inebilizumab was well tolerated, with two (2.7%) serious treatment-emergent adverse events related to inebilizumab and no deaths. Immunoglobulin G levels decreased over time; however, correlation between severe infections and low IgG levels could not be determined because of their small numbers. Conclusion: These results from the N-MOmentum study continue to support use of inebilizumab for treatment of neuromyelitis optica spectrum disorder. Furthermore, the findings suggest that efficacy of inebilizumab may be enhanced after the first year of treatment, warranting additional long-term investigation.

This study evaluated the effects of the adding of flow momentum using artificial external source on the controlling of oblique shock wave of a supersonic flow in a three dimensional duct with low-aspect-ratio (based on experimental data) through a numerical investigation by employing an OpenFoam extended solver. The oblique shock occurred due to a 20° compression ramp which placed on the top of the low-aspect-ratio duct. The flow characteristics were consistent with the published data, suggesting that the numerical methodology successfully resolved the interaction between the shock-waves and flow boundary-layer. To investigate the effect of momentum adding, based on literature, three different cases with various forces exerted on the upper and lower walls of the duct were considered. The results showed that momentum adding led to a decrement in the separation region and shock strength. Moreover, adding the momentum sources on the lower wall of the duct suppressed the lambda shock that happened by the collision of separated and incident shocks and Mach stem. However, by applying the momentum source on the upper wall (upstream of the compression ramp) had more effects on the interaction between shock wave and boundary layer, as compared to the lower wall. Therefore, based on the obtained results, to achieve the best performance of momentum source, it must apply at the critical point with the greatest effect on discontinuities in the flow structure.

A companion paper by Lund et al. employed a compressible model to describe the evolution of mountain waves arising due to increasing flow with time over the southern Andes, their breaking, secondary gravity waves and acoustic waves arising from these dynamics, and their local responses. This paper describes the mountain wave, secondary gravity wave, and acoustic wave vertical fluxes of horizontal momentum, and the local and large-scale three-dimensional responses to gravity breaking and wave–mean-flow interactions accompanying this event. Mountain wave and secondary gravity wave momentum fluxes and deposition vary strongly in space and time due to variable large-scale winds and spatially localized mountain wave and secondary gravity wave responses. Mountain wave instabilities accompanying breaking induce strong, local, largely zonal forcing. Secondary gravity waves arising from mountain wave breaking also interact strongly with large-scale winds at altitudes above ~80 km. Together, these mountain wave and secondary gravity wave interactions reveal systematic gravity wave–mean-flow interactions having implications for both mean and tidal forcing and feedbacks. Acoustic waves likewise achieve large momentum fluxes, but typically imply significant responses only at much higher altitudes.

This study is based on a three-dimensional hydrodynamic model of the global climate including a atmospheric general circulation model, a model of the ocean in the geostrophic approximation with a frictional term in the equations of horizontal momentum with the actual configuration of depths and continents, and a model of the evolution of sea ice. Computations of forecasting the climate until 2100 with the use of scenarios of a growth in CO2 are presented. A significant decrease in meridional water flow in the Atlantic in the case of the stringent scenario is established.

Post-harvest handling of candlenut requires special attention to get the best quality whole kernel and high selling price. The cracking of candlenut traditionally and mechanically using a ripple mill equipment produces a low whole kernel yield. This research aims to find the best handling method of candlenut to obtain the maximum whole kernel yield. The heating pre-treatments using hot air were used to heat up the candlenuts under different temperature variations (80, 90, 100 °C) and heating durations (3, 4, 5 h). The hot air was generated by a heat gun with a flow rate of 500 L/min. After drying, the candlenut was soaked in the water with a temperature of 5 °C for 20 min. The process of cracking candlenut was carried out by two methods: method-1 by dropping candlenuts from several altitudes, i.e., 1, 2, 3, 4, 5 m above the concrete surface and method-2 by dropping a load of 100 g to the candlenut from several altitudes (0.2, 0.4, 0.6 and 0.8 m). The results showed that the optimum pre-treatment that produces the highest whole kernel yield (91.67%) was heating with a temperature of 90 °C for 3 h and by dropping candlenut from an altitude of 5 m (method-1). The momentum needed to break the candlenut shell without damaging the kernel are 0.096 kg.m/s with momentum velocity of 9.905 m/s. This optimal momentum data can be further used for the development of centrifugal-type candlenut cracking equipment.

The literature survey revealed that limited prior investigations exist on the two-phase refrigerant distribution for a horizontal header/horizontal mini-channel tube configuration, which is of importance in many heat exchange circumstances including the cooling of an electric vehicle battery. In this study, we investigated R-1234yf distribution into two mini-channel tubes from a header. Especially, the focus was concentrated on the effect of inlet and outlet configuration on the flow distribution. The tests were conducted for the mass flux from 49 to 147 kg/m2s and the inlet quality from 0.2 to 0.8. The effect of the inclination of the heat exchanger was also investigated. The flow distribution was mainly governed by the balance of the relating forces – momentum, centrifugal and gravitational. Thus, poor distribution was obtained at a tilted case, where the momentum and centrifugal forces were assisting. The flow distribution was also highly dependent on the inlet configuration. On the other hand, the effect of outlet configuration was of secondary importance. The parallel inlet induced a significant mal-distribution compared with the normal inlet, especially in the channel away from the inlet, where an early dry out in the channel was observed. A flow distribution correlation was developed, which predicted the data within ± 30%.

Accurate prediction of shear stress distribution along the boundary in an open channel is the key to solving numerous critical engineering problems such as flood control, sediment transport, riverbank protection, and others. Similarly, the estimation of flow discharge in flood conditions is also challenging for engineers and scientists. The flow structure in compound channels becomes complicated due to the transfer of momentum between the deep main channel and the adjoining floodplains, which affects the distribution of shear force and flow rate across the width. Percentage sharing of shear force at floodplain (%Sfp) is dependent on the non-dimensional parameters like width ratio of the channel $$(\alpha )$$ , relative depth $$(\beta )$$ , sinuosity $$(s)$$ , longitudinal channel bed slope $$(S_{{\text{o}}} ),$$ meander belt width ratio $$(\omega )$$ , and differential roughness $$(\gamma )$$ . In this paper, various artificial intelligence approaches such as multivariate adaptive regression spline (MARS), group method of data handling Neural Network (GMDH-NN), and gene-expression programming (GEP) are adopted to construct model equations for determining %Sfp for meandering compound channels with relative roughness. The influence of each parameter used in the model for predicting the %Sfp is also analyzed through sensitivity analysis. Statistical indices are employed to assess the performance of these models. Validation of the developed %Sfp model is performed for the experimental observations by conventional analytical models; to verify their effectiveness. Results indicate that the proposed GMDH-NN model predicted the %Sfp satisfactorily with the coefficient of determination (R2) of 0.98 and 0.97 and mean absolute percentage error (MAPE) of 0.05% and 0.04% for training and testing dataset, respectively as compared to GEP and MARS. The developed model is also validated with various sinuous channels having sinuosity 1.343, 1.91 and 2.06.

Based on observations over an alpine glacier, we investigate the turbulent flux dissimilarity between momentum and sensible heat transfer in a stably stratified katabatic flow. The flux correlation coefficient RF is employed as a measure of variable levels of the flux similarity, which are found to be modulated by the anisotropy of turbulence. In the katabatic wind regime over this glacier, heat is transported more efficiently than momentum. Based on quadrant analysis, the sweep–ejection differences in the flux fraction constitute turbulence characteristics in terms of the velocity aspect ratio, which unravel dissimilar transport of momentum and heat. Moreover, an innovative method is established for connecting quadrant analysis and cospectral analysis, whereby the hyperbolic quadrant hole size is coupled to the frequency underlying the fast Fourier transform. In extending applications of octant analysis, we introduce a hypothetical octant hole, whose size is solicited as a proxy for the amplitude scale of fluctuating fluxes. The contributions to $${R}_{F}$$ can then be quantified for eddy structures that are associated with different amplitude scales. The katabatic flow structures identified from octant analysis differ in their behaviour so helping illuminate the outcome of flux dissimilarity. Exhibited as a statistical behaviour regardless of amplitude scale, along-wind rapid motions of heated air parcels can modify fractional contributions to the heat flux instead of the momentum flux, with reductions in $${R}_{F}$$ related to decreasing heat-flux fractions. Besides, along-wind slow motions of cooled air parcels cannot modify the flux fractions for both momentum and heat. Thus, the flux dissimilarity due to low-speed low-temperature eddies cannot be explicable in terms of the flux fractions alone. These findings are an incipient step towards physical understanding of the turbulent flux dissimilarity for a stably stratified katabatic flow.

Momentum strategies have historically delivered large alphas, yet they also displayed significant time-variation that is not very well understood. I document that expected momentum profits vary negatively with the formation period return difference between past winners and losers, which I term the momentum gap. A one standard deviation increase in the momentum gap predicts a 1.29% decrease in the monthly momentum return after controlling for existing predictors. I find consistent results across 21 international stock markets. Following the simple real-time strategy of investing in momentum only when the momentum gap is below the 80th percentile generates monthly returns of 1.28%. ∗Cox School of Business, Southern Methodist University. This paper is based on my dissertation at Yale University. I would especially like to thank Nick Barberis, Will Goetzmann, Andrew Metrick, and Jake Thomas. I would also like to thank Sriya Anbil, Sandro Andrade, Brad Barber, Michael Brandt, Hui Chen, James Choi, Lauren Cohen, Kent Daniel, Assaf Eisdorfer, Harrison Hong, Sean Hundtofte, Stacey Jacobsen, Eric Kelley, Peter Kelly, Alok Kumar, Mattia Landoni, Charles Lee, Stefan Lewellen, Jim Linck, David McLean, Alan Moreira, Tyler Muir, Marina Niessner, Terry Odean, Mark Ready, Scott Richardson, Geert Rouwenhorst, Ravi Sastry, Clemens Sialm, Rick Sias, Sorin Sorescu, Matt Spiegel, Johan Sulaeman, Paul Tetlock, Sheridan Titman, Rex Thompson, Kumar Venkataraman, Jeff Wurgler, Lei Xie, Hongjun Yan, Frank Zhang, Harold Zhang, Guofu Zhou, as well as seminar participants at the WFA Meetings, the Lone Star Finance Conference, Southern Methodist University, Texas A&M University, the University of Arizona, the University of Connecticut, the University of Miami, the University of Wisconsin, Washington University at St. Louis, Yale University, Algert Global, Cubist Systematic Strategies, Menta Capital, Nipun Capital, QMS Capital Management, and Sensato Investors. I gratefully acknowledge financial support of the Whitebox Advisors Doctoral Fellowship.

In the present study, the turbulent flows in a T-junction are investigated by using large eddy simulations at two different flow pattern conditions of wall and impinging jets. Their momentum ratios...

This work aims to predict moderate, intense, and super geomagnetic storms during the two recent solar cycles 23 and 24 encompassing the period 1996–2018 using an artificial neural network (ANN). Optimization of the neural network includes a choice of activation function, training function, learning function, hidden layers, hidden neurons, learning rate, and momentum constant. The results obtained by the present study show the ability of the ANN model to produce an accurate estimate of the probability appearance of moderate and intense storms of about 88.9%.

The California Undercurrent (CUC) transport, with significant variability ranging from weeks to decades, has consequences for both the climate and biogeochemistry of the California Current system. This study evaluates the governors of the CUC transport and its temporal variability from a momentum perspective, using a mesoscale-resolving regional model. From a 16-yr mean perspective, the along-isobath pressure gradient acts to accelerate the CUC, whereas eddy advection retards it. The topographic form stress, which is part of the volume integrated along-isobath pressure gradient, not only acts in the direction of the time-mean CUC, but also greatly modulates the temporal variability of the CUC transport. This temporal variability is also correlated with the eddy momentum advection. The eddy stress plays a role in transferring both the equatorward wind stress and poleward CUC momentum downward. A theory is formulated to show that, in addition to the conventional vertical redistribution of momentum, the eddy stress can also redistribute momentum horizontally in the area where the correlation between the pressure anomaly and isopycnal fluctuations has large spatial variability.

A nonmagnetized collisional plasma parameter estimator from two frequency signal interrogation attenuation is developed. The plasma parameters that are estimated are the plasma frequency, electron neutral momentum collision frequency, and the plasma thickness. The plasma frequency and electron neutral momentum collision frequency are considered uniform across the plasma thickness. The relative permittivity is defined, and the complex index of refraction is developed. Using this definition and applying the plasma frequency, electron neutral momentum collision frequency, the radial propagation frequency, and plasma thickness, an attenuation is determined for known cases. The development of the estimator is discussed. The estimator uses a performance index where the minimum difference between the plasma frequencies and electron neutral momentum collision frequencies is determined for the two signal interrogation frequencies under the constraint of the same plasma thickness. The estimator was developed in three stages which include iterative, sequential, and adaptive. The setups of the iterative, sequential, and adaptive approaches are discussed. The impact of the interrogation frequency and the estimator setup is investigated. The estimator in the three development stages is compared with known cases and the plasma parameter estimator performance is quantified.

International audience; Aerodynamic loads of wind turbine blades are often predicted by manufacturers using the Blade Element Momentum (BEM) theory, for which many corrections have been proposed in the literature. The physical impacts of such corrections on field measurements have seldom been assessed because of the relative unavailability of dedicated measurements. Based on the unique full scale database of the DANAERO project, available through the IEA (International Energy Agency) Task 29, this work incrementally applies on aerodynamic field measurement, improvements of the BEM theory: atmospheric boundary layer vertical velocity gradient, neighbouring wake, yaw misalignment, wind inflow location, tower shadow effect, cone angles modelling, blade aeroelastic deformation and dynamic wake. This is performed using the iBEM method (inverse Blade Element Momentum), which back-calculates the aerodynamic coefficients (lift - CL and drag - CD) using aerodynamic loads from field tests.