Local Speed Research Articles

Turbulent Energy Transfer at Dipolarization Fronts

AbstractDipolarization fronts (DFs), ion‐scale magnetic transients characterized by dramatic enhancement of northward magnetic field, have been documented as crucial energy transfer regions in the magnetosphere. DF‐driven energy transfer has hitherto been studied mainly in the laminar regime. Energy transfer driven by turbulent processes, however, remains unclear. Here we perform a comprehensive investigation of turbulent energy transfer (TET) developed at DFs, via using high‐cadence data from Magnetospheric Multiscale mission. We find that: (a) TET is equally governed by energy loads and generators, different from laminar energy transfer which is typically dominated by energy loads; (b) ion and electron currents play comparable roles in driving TET; (c) TET is positively correlated with local magnetic field strength and ion speed; (d) TET shows asymmetric global distributions along the dawn‐dusk direction. These features implicate that TET is primarily related to electromagnetic turbulence at electron‐ion hybrid scales. These new results, uncovering unique characteristics of DF‐driven TET, can deeply advance our understanding of energy budgets in the magnetosphere.

Molecules with ALMA at Planet-forming Scales (MAPS): Complex Kinematics in the AS 209 Disk Induced by a Forming Planet and Disk Winds

We study the kinematics of the AS 209 disk using the J = 2–1 transitions of 12CO, 13CO, and C18O. We derive the radial, azimuthal, and vertical velocity of the gas, taking into account the lowered emission surface near the annular gap at ≃1.″7 (200 au) within which a candidate circumplanetary-disk-hosting planet has been reported previously. In 12CO and 13CO, we find a coherent upward flow arising from the gap. The upward gas flow is as fast as 150 m s−1 in the regions traced by 12CO emission, which corresponds to about 50% of the local sound speed or 6% of the local Keplerian speed. Such an upward gas flow is difficult to reconcile with an embedded planet alone. Instead, we propose that magnetically driven winds via ambipolar diffusion are triggered by the low gas density within the planet-carved gap, dominating the kinematics of the gap region. We estimate the ambipolar Elsässer number, Am, using the HCO+ column density as a proxy for ion density and find that Am is ∼0.1 at the radial location of the upward flow. This value is broadly consistent with the value at which numerical simulations find that ambipolar diffusion drives strong winds. We hypothesize that the activation of magnetically driven winds in a planet-carved gap can control the growth of the embedded planet. We provide a scaling relationship that describes the wind-regulated terminal mass: adopting parameters relevant to 100 au from a solar-mass star, we find that the wind-regulated terminal mass is about one Jupiter mass, which may help explain the dearth of directly imaged super-Jovian-mass planets.

Design of the particle swarm optimization simulated annealing MPPT control method based on motion shadow

Under the same environmental conditions, photovoltaic arrays at different operating voltages will significantly affect the size of solar power. To obtain as much power as possible, the maximum power point tracking (MPPT) control method has been invented. Previous studies focused on the tracking problem under local shadow conditions, but the dynamic shadow problem with rapid changes in local shadow was rarely discussed. To solve the tracking problem that the maximum power point has multi-peak and fast-changing characteristics under this condition, this paper proposes a simulated annealing MPPT control method based on particle swarm optimization, which compensates the disadvantages of the memoryless Markov chain in the optimization algorithm by adaptive asymmetric memory factor, thus improving the local search ability and convergence speed in the later stage. The control effect is verified by modeling and simulation in Simulink of MATLAB, and the adaptability of the heuristic control method is reflected by simulating the tracking mode under the moving shadow condition through the actual hardware deployment on the moving car.

Introduction of business continuity plan for small and medium-sized local construction companies and restoration activities in Japan in the event of natural disasters

In recent years, Japan has suffered significant damage due to natural disasters such as major earthquakes and flood Construction companies are expected to play an important role during natural disasters and respond quickly and restore infrastructure. The first author runs a small local construction company in Okayama, Japan. During a flood in 2011 at Okayama, the embankment restoring site turned extremely dangerous for workers. At this juncture, the first author, in the capacity of a company manager, identified the safety and administrative issues, and in 2013, the company began to implement BCP. When there was heavy flooding in Okayama in 2017, they supported the administration in recovery operations based on their BCP. The impact of BCP is to be acknowledged as the emergency operations were safer and timelier. BCP of the company has been continuously improved, and they were invited to join infrastructure recovery activities in the disaster area of Great East Japan Earthquake in 2019. The area is not the usual business region of the company, but 1,000 km away. There is a high requirement for human resources and equipment for emergency and recovery activities immediately after a disaster. Most of the construction companies are small and locally based in Japan, and several resources available at the construction site itself for initial recovery activities. It is desirable to prepare a plan so that the affected companies themselves can respond. The main tasks are the training of personnel to provide guidance and support for BCP, and the development of systems and laws that can actively support activities. By capturing accurate information on resources of local construction companies, their capability and response speed during an emergency can be improved. It is also necessary to create a system to receive support from other companies or organizations in case self-help is difficult or insufficient.

Electric Vehicle Routing Problem With Variable Vehicle Speed and Soft Time Windows for Perishable Product Delivery

This work studies perishable products’ distribution using electric commercial vehicles (ECVs). Extra energy is consumed for refrigeration to keep such products from deteriorating, which shortens the limited driving range of ECVs. Besides charging at public recharging stations, their travel speed can be adjusted to improve their driving range and decrease distribution cost. We propose an Electric Vehicle Routing problem with variable vehicle speed and soft time windows for perishable products (EVRP-VS). An energy consumption rate function of refrigerated ECVs during driving is introduced into the problem. The function considers refrigeration and has a nonlinear relationship with ECV speed and weight. As long as the carriage is not empty, the vehicle needs refrigeration during driving and during its stay at customers and stations. A mathematical programming model is developed for EVRP-VS, to minimize total distribution cost, including vehicle cost, power cost, refrigeration cost, and penalty cost due to delayed delivery. An adaptive hybrid ant colony optimization (AHACO) with a two-stage speed optimization strategy is proposed to solve EVRP-VS. In the first stage, local speed optimization is used to optimize the speed of each ant (ECV) in each transfer step. In the second one, global speed optimization further optimizes the speed for each fixed route constructed by ants. AHACO is applied to many problem instances. Experimental results show that it can effectively solve EVRP-VS in comparison with CPLEX and other meta-heuristics.

Trajectory Planning for Autonomous Valet Parking in Narrow Environments With Enhanced Hybrid A* Search and Nonlinear Optimization

This paper focuses on the problem of autonomous valet parking trajectory planning in complex environments. The task normally can be well described by an optimal control problem (OCP) for the rapid, accurate, and optimal trajectory generation. Appropriate initial guesses obtained by sampling or searching-based methods are important for the numerical optimization procedure. Still, in highly complex environments with narrow passages, it may incur high computational costs or fail to find the proper initial guess. To address this challenge, an enhanced hybrid A* (EHA) algorithm is proposed to address the issue. The EHA includes four steps. The first step is to quickly obtain the global coarse trajectory using a traditional A* search. The second step is constructing a series of driving corridors along the rough trajectory, then evaluating and extracting nodes from each wide or narrow passage based on the length of the box's side. The third step is to extract each passage's boundary points. The final step is connecting boundary points by hybrid A* and generating a feasible initial guess for OCP. To reduce safety risks, vehicles in particular areas (Fig. 1b) should travel as slowly as possible. The global and local speed restrictions are distinct, and local restrictions are only activated when the vehicle enters a particular area. This “if-else” structure makes the optimization problem difficult. A novel approximation formulation for these local state constraints is introduced to overcome this issue. The experimental results demonstrate that the proposed method for trajectory planning is effective and robust.

Refraction-Based Speed of Sound Estimation in Layered Media: an Angular Approach.

Speed of sound estimation in ultrasound imaging is a growing modality with several clinical applications such as hepatic steatosis stages quantification. A key challenge for clinically-relevant speed of sound estimation is to obtain repeatable values independent from superficial tissues and available in real-time. Recent works have demonstrated the feasibility to achieve quantitative estimations of the local speed of sound in layered media. However, such techniques require a high computational power and exhibit instabilities. We present a novel speed of sound estimation technique based on an angular approach of ultrasound imaging in which plane-waves are considered in transmit and in receive. This change of paradigm allows us to rely on refraction properties of plane-waves to infer local speed of sound values directly from the angular raw-data. The proposed method robustly estimates the local speed of sound with only few ultrasound emissions and with a low computational complexity which makes it compatible with real-time imaging. Simulations and in vitro experimental results show that the proposed method outperforms state-of-the-art approaches with biases and standard deviations lower than 10ms-1, 8 times less emissions and 1000 times lower computational time. Further in vivo experiments validate its performance for liver imaging.

Instability of Rotating-Cone Boundary Layer in Axial Inflow: Effect of Cone Angle

Boundary-layer instability on a rotating cone induces coherent spiral vortices that are linked to the onset of laminar–turbulent transition. This type of transition is relevant to several aerospace systems with rotating components, e.g., aeroengine nose cones. Because a variety of options exist for the nose-cone shapes, it is important to know how their shape affects the boundary-layer transition phenomena. This study investigates the effect of varying cone angle on the boundary-layer instability on rotating cones facing axial inflow. It is found that increasing cone angle has a stabilizing effect on the boundary layer over rotating cones in axial inflow. The parameter space of Reynolds number and local rotational speed ratio is experimentally explored to find the spiral vortex growth on rotating cones of half angle , 45°, and 50°. The previously addressed cases of and 30° are also revisited. Increasing half-cone angle is found to have a stabilizing effect on the boundary layer on the rotating cones with ; i.e., the spiral vortex growth is delayed to higher and . This effect diminishes when the half-cone angle increases from to 50°. The spiral vortex angle decreases with increasing rotational speed ratio for all the investigated cones, irrespective of the half-cone angle. However, the instability on the broader cones is found to induce shorter azimuthal wavelengths.

Weather image-based short-term dense wind speed forecast with a ConvLSTM-LSTM deep learning model

Short-term wind speed predication is of great significance for scholars (e.g., understanding wind profiles), practitioners (e.g., building energy management), regulators (e.g., urban microclimate regulation), and even the general public. Current wind speed forecasting methods either generate sparse predictions or occur high cost. This paper reports a novel, inexpensive framework to forecast urban local dense wind speed. The central tenet is a convolutional long short-term memory (ConvLSTM) and LSTM combinatorial deep learning model to learn the features of input historical weather image series coupled with spatial-temporal correlations. The model was trained and tested using Hong Kong datasets. The feasibility and effectiveness of the proposed model are verified and compared with parallel models under different criteria, including mean absolute error (MAE), root mean square error (RMSE) and R-squared (R2). The experimental results show that: (1) the proposed ConvLSTM-LSTM deep learning model can effectively forecast wind speed regardless of location; (2) the overall MAE, RMSE, and R2 value of the proposed model are improved by 14.84%, 15.04%, and 7.51%, respectively, compared to the ConvLSTM-full connected (ConvLSTM-FC) model, and by 22.12%, 22.80%, and 12.24%, respectively, compared to the convolutional neural network-LSTM (CNN-LSTM) model; and (3) compared with parallel models, the proposed model has better performance in predicting wind speed series with large amplitude variations and rapid frequency changes.

Thermodiffusively-unstable lean premixed hydrogen flames: Phenomenology, empirical modelling, and thermal leading points

Thermodiffusively-unstable lean premixed hydrogen flames are investigated using three-dimensional direct numerical simulation with finite-rate chemical kinetics. A large number of simulations have been performed to investigate the influence of reactant conditions (pressure, temperature, and equivalence ratio) on thermodiffusive response in freely-propagating and turbulent flames. Reactant conditions are characterised using an instability parameter ω2, which was recently shown to characterise freely-propagating flames well in 2D. Freely-propagating flame speeds and thicknesses are found to correlate with ω2 using the same functional form found in 2D (with larger model constants), and different correlations are required either side of the most-unstable surface in ω2-space. The freely-propagating values are demonstrated to be more appropriate for characterising turbulent flames than the corresponding 1D laminar flame values. Both turbulence and thermodiffusive instability bring about a similar flame response (increasing curvature, reaction rates and temperature), and so starting from strongly thermodiffusively-unstable conditions limits the potential turbulent response; an empirical model for local flame speed and thickness is provided incorporating this dependence. Joint probability density functions are used to correlate local consumption-based flame speed with curvature, strain-rate and stretch with single and independent Markstein numbers. A simple curvature-based model coupled with the empirical flame speed model is found to yield reasonable results. Principal curvatures are used to partition the flame surface into six classifications, allowing for conditional analysis in different parts of the flame surface. Fractional contributions show that the bulk of the fuel consumption occurs in flat regions and leading edges, shifting from the former to the latter with increasing instability and/or turbulence. Furthermore, the flat flame regions experience speeds in excess of the reference value despite the lack of focussing of fuel by preferential diffusion in these regions, contrary to the conventional expectations of thermodiffusive instability. We propose a thermal leading point interpretation of these phenomena: as expected, strong positive curvature in the leading points/edges result in diffusive focussing of fuel, increasing the reaction rates, resulting in superadiabatic temperatures; these high temperatures left behind the leading points/edges then support higher-than-expected reaction rates in regions where the flame surface is relatively-flat.

Gas kinetic principles in Navier-Stokes finite-volume solvers

We present a new approach for introducing more physics into the flux function of a finite-volume solver for compressible Navier-Stokes equations. This approach is conceived as an alternative solution to classical approximate Riemann solvers.The peculiarity of the solution we designed comes from the use of the gas distribution function, which is employed in the kinetic theory of gases; once computed from the Boltzmann equation with a simplified collision source term (BGK model), this distribution function is used, then, for the computation of the cell interface flux.Two solutions are investigated for computing the distribution function. In the first solution, this function is approximated as a first-order approximation of the BGK equation; in that case the resulting numerical flux smoothly evolves between a Godunov-like flux and a flux vector splitting: this first choice generates the simple gas kinetic scheme (SCG scheme). In the second solution, we use the kinetic meaning of the local sound speed at cell interfaces, to introduce macroscopic wave informations into the gas distribution function; this way, the resulting numerical flux is a convex combination between a HLLE-type flux and a modified flux-vector-splitting: this is what we call the acoustic gas kinetic scheme (ASCGE scheme). Both solutions are inserted into a space-time separation algorithm that is solved by a positive Runge-Kutta (SSPRK) method; in addition, a MUSCL procedure for generating a high-order positivity-preserving scheme, is selected.Viscous fluxes are computed by using kinetic informations coming from both sides of the cell face of the finite-volume method. Lastly, both schemes (SCG and ASCGE schemes) are investigated and analyzed over a variety of test-cases including inviscid/viscous and steady/unsteady problems.

Decision Support System for Selection of the Best Fuel for Households Using the Weighted Product (WP) Method

Fuel is one of the most critical needs for the community in carrying out various household activities dominated by fuel oil. Meanwhile, the availability of fuel is increasingly running low. Most people in the Botumoito area in Gorontalo province work in the agricultural sector with low local income. Availability of fuels such as kerosene and gas there is quite challenging because there is no source or supply of gas either directly from the gas field or terminal. The government needs to make the right policy on fuel selection according to the problems in the region. This research aims to design and build a decision support system for selecting the best fuel and implementing the Weighted Product (WP) method into the system. The method used in designing and manufacturing this system is the waterfall method. This research results in a decision support system that can help fuel ranking. The ranking results are based on the magnitude of the Vector (V) value obtained from testing ten alternative fuels. Bioethanol occupies the top priority with a vector value of 0.152. This research can help consultants, fuel experts, and local governments speed up their work in determining the best household fuel according to their respective regions.

The impact of spume droplets induced by the bag-breakup mechanism on tropical cyclone modeling

Spume, large-radius seawater droplets that are ejected from the ocean into the atmosphere, can exchange moisture and heat fluxes with the surrounding air. Under severe weather conditions, spume can substantially mediate air-sea fluxes through thermal effects and thus needs to be physically parameterized. While the impact made by spume on air-sea interactions has been considered in bulk turbulent air-sea algorithms, various hypotheses in current models have resulted in uncertainties remaining regarding the effect of spume on air-sea coupling. In this study, we extended a classic bulk turbulent air-sea algorithm with a “bag-breakup” physical scheme of spume generation parameterizations to include spume effects in a complicated numerical model. To investigate the impact of spume on air-sea coupling, we conducted numerical experiments in a simulation of Tropical Cyclone Narelle. We observed a significant improvement in the ability to model minimum central pressure and maximum sustained surface wind speed when including the bag-breakup spume scheme. In particular, the impact of the bag breakup–generated spume is observed in the intensity, structure, and size of the tropical cyclone system through the modulation of local wind speed (U10), wave height (Hs), and sea surface temperature.

Meteorological Driving Datasets for the U.S. Midwest and Great Lakes Region Incorporating Precipitation Gauge Undercatch Corrections

Abstract Precipitation (P) gauge undercatch (PUC) is an important source of error when using observed meteorological datasets for hydrologic modeling studies in regions with cold and windy winters. Preliminary simulations using the Variable Infiltration Capacity (VIC) hydrological model forced with different meteorological datasets showed significant underprediction of simulated streamflow throughout the domain. A new hybrid gridded meteorological dataset at 1/16° resolution based on observed station data was assembled over the U.S. Midwest and Great Lakes region from 1915 to 2021 at a daily time step. Correction of primary station data using existing techniques is generally difficult or infeasible in the United States due to missing station metadata and lack of local wind speed (WS) measurements. We developed and tested several different postprocessing adjustment techniques using regridded WS obtained from the NCEP–NCAR reanalysis. The most effective approach corrected rain or mixed P using WS alone, and P as snow using a regressed snow-to-P ratio from a group of wind-shielded reference stations (to account for different and generally unknown snow measurement techniques). The PUC-corrected gridded products were validated against high-quality shielded stations and corrected Global Historical Climatology Network stations with in situ WS, showing good overall agreement. Observed monthly streamflow at 40 river basins was also compared to hydrologic model simulations forced by datasets with and without PUC corrections. The best PUC-corrected dataset produced improvements in streamflow simulations in at least 80% of the streamflow locations for three validation metrics (r2, Nash–Sutcliff efficiency, bias in the mean), demonstrating its value for hydrometeorological studies in the greater Midwest region. Significance Statement Many applications in hydrology require in situ precipitation (P) measurements, which are known to have a systematic low bias due to the effects of wind, also known as precipitation undercatch (PUC). Addressing PUC is problematic in the United States due to limited access to detailed station metadata (SMD) and local wind speed (WS) measurements. In this paper we develop a set of procedures to create gridded precipitation datasets for the U.S. Midwest region that incorporate corrections for PUC without needing either (i) detailed SMD or (ii) local WS measurements. Among other tests, results in 40 test basins throughout the Midwest show substantial improvements in simulated streamflow in 32 out of 40 basins when PUC corrections are included in meteorological driving datasets.

Modelling of geospatial data through multi criteria analysis for cemetery land management

The suitability of the new cemetery site selection area is one of the management that needs to be emphasized for sustainable development. Lack of suitable land for burial is a major issue that often arises especially in big cities including Malaysia, even though guidelines have been specified. To overcome this problem, the systematic use of technology needs to be implemented. The aim of this study is to analyze the existing modeling method and the factors involved in obtaining a suitable area for a new cemetery site, which has to meet all the specified guidelines. Along with advancement, the uses of Geographic Information System (GIS) technology and the Analytical Hierarchy Process (AHP) in digital form can help speed up the accession to a suitable physical location. This method is expected to help the local authorities and speed up the process of choosing a suitable place for the cemetery. The application of the AHP technique supports the study results through variable weighting values (weightage) according to the suitability of the study area. Evaluation of the weighted value (weightage) is suggested to be done in areas outside of the study area to assess consistency and appropriateness in all places. Proposals related to the location of new cemeteries require a quantitative study of the ratio of racial composition in an area. As a conclusion, the study is able to find a new cemetery location that is suitable and meets the specified guidelines is very crucial. The criteria used depend on the religious followers in a particular area.

Neutrosophic MCDM Methodology for Evaluation Onshore Wind for Electricity Generation and Sustainability Ecological

The conviction in the necessity of renewable energy has been prompted by both the constantly increasing need for power production and the ecological issues of recent years. When it comes to generating power in a sustainable manner, wind is among the most essential renewable energy sources. This research attempts to present a structural technique for assessing the performance of operational onshore wind facilities with respect to the three dimensions of sustainability. The energy production, environmental effect, and practicability of onshore wind facilities are all dependent on accurate assessments. Wind resources, site accessibility, environmental impact, permitting and regulatory requirements, turbine technology, maintenance and operation, interconnection and transmission, and other criteria and factors are discussed in this research paper. Renewable energy, cost-effectiveness, dependability, and job creation are only a few of the advantages of onshore wind facilities that are mentioned. This study used the interval-valued neutrosophic set with the Weighted Sum Model (WSM) method to compute the weights of criteria and rank the alternatives. We got the wind speed and direction as the best criterion. The potential energy production of a wind plant is heavily dependent on the local wind speed and direction.

Wind Speed Forecast for Sudan Using the Two-Parameter Weibull Distribution: The Case of Khartoum City

In this quick study, we estimated the Weibull distribution’s parameters using wind data collected between March 2017 and January 2018 using a twelve-meter mast meteorological station on the grounds of the National Energy Research Center in Khartoum. In order to quantify these descriptors, we relied on analytical and stochastic methods, subsequently enabling specialists from researchers, engineers, decision-makers, and policymakers to apprehend the wind characteristics in the vicinity. Hence, the computed scale and shape parameters were provided, in which the Firefly algorithm (FA) resulted in the most accuracy in terms of the coefficient of determination, which equaled 0.999, which we considered logical due to the observed nonlinearity in the wind speed numbers. On the contrary, the energy pattern factor method had the worst prediction capability depending on several goodness-of-fit metrics. This concise work is unique because it is the first to use data from Sudan to forecast local wind speeds using artificial intelligence algorithms, particularly the FA technique, which is widely used in solar photovoltaic modeling. Additionally, since classic estimating approaches act differently spatially, evaluating their efficacy becomes innovative, which was accomplished here. On a similar note, a weighted-average wind speed was found to equal 4.98 m/s and the FA average wind speed was 3.73 m/s, while the rose diagram indicated that most winds with potential energy equivalent to 3 m/s or more blow from the north.

Comparative Analysis of Wind Farm Simulators for Wind Farm Control

This paper conducts a comparative analysis of three wind farm simulators, examining the influence of wake on the local wind speed and power output for downstream turbines using experimental data. The study features experiments in three distinct scenarios, evaluating differences among the simulators by calculating the local wind speed and power for each. Each simulator employs a unique wake model, which substantially affects the local wind speed experienced by downstream turbines. Furthermore, the experiment involves adjusting parameter values for each simulator to assess their respective impacts on wind farm performance. The findings of this research are expected to play an important role in investigations related to power optimization and wake effects in the wind farm control.

Pediatric Walking Speed Normal Reference Values in a Local Population.

This study's aim was to develop a local walking speed norm using the 10-m walk test (10MWT) for 5- to 17-year-old children and youth who are developing typically. Healthy child and adolescent participants were recruited from schools in one rural Alaska school district. The 10MWT was performed using a 2 repetitions per speed protocol. Outcome measures were average time for the normal and fast-speed trials, separated by age and gender. Average walking speed was established in this group of children and youth who are developing typically by age and gender. Local walking speed norms for 5- to 17-year-olds can be accurately obtained by examining students in a rural school district.

Zooming in on abnormal local and global processing biases after stroke: Frequency, lateralization, and associations with cognitive functions.

The 'attentional spotlight' can be adjusted depending on the task requirements, resulting in processing information at either the local or global level. Stroke can lead to local or global processing biases, or the inability to simultaneously attend both levels. In this study, we assessed the (1) prevalence of abnormal local and global biases following stroke, (2) differences between left- and right-sided brain damaged patients, and (3) relations between local and global interference, the ability to attend local and global levels simultaneously, and lateralized attention, search organization, search speed, visuo-construction, executive functioning, and verbal (working) memory. Stroke patients admitted for inpatient rehabilitation completed directed (N=192 total; N = 46 left-sided/N = 48 right-sided lesion) and divided (N = 258 total; N = 67 left-sided/N = 66 right-sided lesion) local-global processing tasks, as well as a conventional neuropsychological assessment. Processing biases and interference effects were separately computed for directed and divided tasks. On the local-global tasks, 7.8-10.9% of patients showed an abnormal local bias and 6.3-8.3% an abnormal global bias for directed attention, and 5.4-10.1% an abnormal local bias and 6.6-15.9% an abnormal global bias for divided attention. There was no significant difference between patients with left- and right-sided brain damage. There was a moderate positive relation between local interference and search speed, and a small positive relation between global interference and neglect. Abnormal local and global biases can occur after stroke and might relate to a range of cognitive functions. A specific bias might require a different approach in assessment, psycho-education, and treatment.