Velocity Slope Research Articles

A contribution to rainfall simulator design – a concept of moving storm automation

Abstract. We developed an advanced-design programmable rainfall simulator (RS) to simulate a moving storm rainfall condition. The RS consists of an automated nozzle control system coupled with a pressure regulator mechanism for an operating range of 50 to 180 kPa at a drop height of 2000 mm above the soil flume surface. Additionally, a programmable mobile application was developed to regulate all RS valves. Near natural rainfall conditions were simulated at varying spatial and temporal resolutions in a controlled environment. A soil flume of 2500 mm × 1400 mm × 500 mm was fabricated to conduct different hydrological experiments. The flume was designed to record overland, subsurface, and baseflows simultaneously. This study focused on a detailed analysis of moving storms and their impact on hydrograph characteristics. Experimental results showed a considerable difference in terms of time to peak (tp), peak discharge (Qp), and hydrograph recession for two different storm movement directions (upstream and downstream). Two multiple regression models indicate a statistically significant relationship between the dependent variable (tp or Qp) and the independent variables (i.e. storm movement direction, storm velocity, and bed slope gradient) at a 5 % level of significance. Further, the impact of these moving storm phenomena reduces with the increase in the storm movement velocity.

ANALYSIS OF OVERESTIMATION IN HISTORICAL ICE FLOW VELOCITY MAPS IN WESTERN PACIFIC OCEAN SECTOR, ANTARCTICA

Abstract. High accuracy reconstruction of historical ice flow velocity fields is crucial in mass balance research of the Antarctic Ice Sheet by utilizing the input-output approach. A historical flow velocity of the Western Pacific Ocean sector region of East Antarctica from 1963 to 1989 was mapped and then corrected for its velocity overestimation. In this study, we analyzed the spatial distribution of the corrected values, and further assessed the relationship between the corrected values and related factors including timespan of image pairs, ice flow velocity, the spatial acceleration of ice flow velocity, and surface slope. The results indicate that the corrected ice flow velocity points are mostly dispersed between a buffer 25 km upstream and a buffer 25 km downstream the grounding line, with the largest mean value emerging in the region between the grounding line and its 25 km downstream. The corrected values exhibit linear correlation with three conditions: 1) when the ice flow velocity range is 0 – 1586 m/y, 2) spatial acceleration is 0 – 69 (m/y)/km, and 3) the slope is 0 – 1.95 degrees and the R2 is higher than 0.7. However, the correlation between timespan and corrected values is not obvious. The corrected values for the floating region have a greater linear correlation with all three factors than the inland region. Ice flow velocity, spatial acceleration, and surface slope all have an influence on the distribution of the corrected values of the reconstructed historical ice flow velocity maps, and may further affect the assessment of the mass balance of the Antarctic Ice Sheet.

The Warm Neptune GJ 3470b Has a Polar Orbit

The warm Neptune GJ 3470b transits a nearby (d = 29 pc) bright slowly rotating M1.5-dwarf star. Using spectroscopic observations during two transits with the newly commissioned NEID spectrometer on the WIYN 3.5 m Telescope at Kitt Peak Observatory, we model the classical Rossiter–McLaughlin effect, yielding a sky-projected obliquity of and a . Leveraging information about the rotation period and size of the host star, our analysis yields a true obliquity of , revealing that GJ 3470b is on a polar orbit. Using radial velocities from HIRES, HARPS, and the Habitable-zone Planet Finder, we show that the data are compatible with a long-term radial velocity (RV) slope of over a baseline of 12.9 yr. If the RV slope is due to acceleration from another companion in the system, we show that such a companion is capable of explaining the polar and mildly eccentric orbit of GJ 3470b using two different secular excitation models. The existence of an outer companion can be further constrained with additional RV observations, Gaia astrometry, and future high-contrast imaging observations. Lastly, we show that tidal heating from GJ 3470b’s mild eccentricity has most likely inflated the radius of GJ 3470b by a factor of ∼1.5–1.7, which could help account for its evaporating atmosphere.

Thermal cooling performance of convective non-Newtonian nanofluid flowing with variant power-index across moving extending surface

This communication focuses on assessing the effectiveness of nanoparticles, and a power-law variation fluid on a moving stretching surface is analyzed. Newtonian fluids for different nanomaterials are considered due to its industrial demand. The partial differential equations describing the flow are transformed to ordinary differential equations by employing local similarity transformations and then solved numerically by an effective numerical approach, namely, the local nonsimilarity method (LNS). The numerical solution is computed for different parameters by using the computational software MATLAB. Different types of nanoparticles are considered, and the impact of those nanoparticles as well as the impact of different pertaining parameters on velocity, temperature, missing velocity slope, and missing temperature slope are presented graphically. Comparisons are made with the available results in the open literature. Our investigation conveys a better impact on {text{Ag}} nanoparticles due to their higher thermal conductivity. Furthermore, an increase in the free stream velocity, missing temperature slope and velocity slope is enhanced, but after a point of separation, the missing temperature slope decays.

Level of Agreement, Reliability, and Minimal Detectable Change of the MusclelabTM Laser Speed Device on Force-Velocity-Power Sprint Profiles in Division II Collegiate Athletes.

This study examined the level of agreement (Pearson product-moment correlation [rP]), within- and between-day reliability (intraclass correlation coefficient [ICC]), and minimal detectable change of the MusclelabTM Laser Speed (MLS) device on sprint time and force–velocity–power profiles in Division II Collegiate athletes. Twenty-two athletes (soccer = 17, basketball = 2, volleyball = 3; 20.1 ± 1.5 y; 1.71 ± 0.11 m; 70.7 ± 12.5 kg) performed three 30-m (m) sprints on two separate occasions (seven days apart). Six time splits (5, 10, 15, 20, 25, and 30 m), horizontal force (HZT F0; N∙kg−1), peak velocity (VMAX; m∙s−1), horizontal power (HZT P0; W∙kg−1), and force–velocity slope (SFV; N·s·m−1·kg−1) were measured. Sprint data for the MLS were compared to the previously validated MySprint (MySp) app to assess for level of agreement. The MLS reported good to excellent reliability for within- and between-day trials (ICC = 0.69–0.98, ICC = 0.77–0.98, respectively). Despite a low level of agreement with HZT F0 (rP = 0.44), the MLS had moderate to excellent agreement across nine variables (rp = 0.68–0.98). Bland–Altman plots displayed significant proportional bias for VMAX (mean difference = 0.31 m∙s−1, MLS < MySp). Overall, the MLS is in agreement with the MySp app and is a reliable device for assessing sprint times, VMAX, HZT P0, and SFV. Proportional bias should be considered for VMAX when comparing the MLS to the MySp app.

Potent antiplatelet aggregation, anticoagulant and antioxidant activity of aerial Canna x generalis L.H Bailey & E.Z Bailey and its phytoconstituents

This study evaluated for the first time the inhibitory effect on human platelet aggregation, blood coagulation, and the antioxidant activity of Canna x generalis fractions and its phytoconstituents. The antiplatelet effect was evaluated using the turbidimetric method to determine the percentage inhibition (%I), the area under aggregation curve (AUC) and the aggregation velocity (slope). Prothrombin time (PT), activated partial thromboplastin time (APTT) and thrombin time (TT) were measured to assess the inhibitory effect on blood coagulation. ABTS and DPPH assays were performed for evaluation of the antioxidant effect. Compounds structures were determined by NMR and MS spectroscopic methods. The ethyl acetate fraction exhibited the most potent antiplatelet (%I, 98.2 ± 1.7% at 4 mg/mL), anticoagulation (mean APTT, 42.97 s) and antioxidant activity (IC50, 58 ± 0.1 and 12.5 ± 2.0 μg/mL for DPPH and ABTS, respectively). Thirteen compounds were found for the first time from aerial CG: 16α-hydro‑ent-kauran-3β-ol-7,19-dioic acid, named cannagelic acid (a new ent‑kaurane diterpenoid) (1), 16α-hydro‑ent-kauran-17,19-dioic acid (2), ent‑kauran-15-en-17,19-dioic acid (3), 3-methoxybenzaldehyde (4), 2-methoxynaphtalene (5), 4-ketopinoresinol (6), p-coumaric acid (7), indole-3-carboxylic acid (8), procatechuic aldehyde (9), astragalin (10), isoquercitrin (11), corchoionol C (12) and rutin (13). Compounds 7, 9–11, 13 possess good antiplatelet, anticoagulant and antioxidant activity. This study demonstrated that compound 1 did not show any tested effects. Compounds 4 and 5 had a very weak antiplatelet effect. Compound 8 expressed the highest capacity to inhibit platelet aggregation for both ADP and collagen (%I = 70.2 ± 1.8 and 79.2 ± 1.4 at 0.4 mg/mL, respectively), followed by compound 6. Moreover, these two compounds at 0.4 mg/mL could prolong APTT compared to the negative control (p < 0.05). Compound 12 had weak antiplatelet activity, but its antioxidant effect was better than other tested compounds. In conclusion, CG would be a good natural resource of bioactive molecules or dietary supplements to prevent and/or treat cardiovascular and free radicals-associated diseases.

Objective measurement of HINTS (Head Impulse, Nystagmus, Test of Skew) in peripheral vestibulopathy

To evaluate how often the positive sign of HINTS (Head-Impulse, Gaze Evoked Nystagmus, Test of Skew) appears in patients with acute peripheral vestibular lesion, HINTS findings were quantitatively measured and analyzed in patients with peripheral vestibulopathy accompanying spontaneous nystagmus. HINTS was evaluated in 14 vertigo patients with spontaneous nystagmus. Horizontal vestibulo-ocular reflex (VOR) gain was measured using the video head impulse test (vHIT). To evaluate gaze-evoked nystagmus (GEN), slow-phase velocities at different points of lateral gaze were measured and plotted, then the slope and its inverse value, the neural integrator time constant, were calculated. Skew deviation was tested using anaglyph filters to simulate the alternate cover test, and the degree and latency of vertical eyeball deviation were measured. The ABCD2 score was calculated to evaluate the risk of stroke. Among 13 patients of peripheral vestibulopathy, 7 showed positive signs in HINTS (normal vHIT: 5, direction-changing GEN: 0, skew deviation: 3). One patient with a cerebellopontine angle tumor presented with both a peripheral and central pattern and showed positive HINTS findings (presence of direction-changing GEN). The mean VOR gain of patients with abnormal vHIT was 0.58±0.29 and 1.10±0.11 in the affected and contralateral side, respectively, while those in patients with normal vHIT were 1.04±0.21 and 1.13±0.12, respectively. The neural integrator time constant calculated from the mean slope of horizontal slow-phase velocity according to horizontal eye position was 42.9 s. The mean vertical eyeball deviation of patients with positive skew was 2.14±1.18° while uncovering the eye on the affected side, and -1.97±1.59° while uncovering the eye on the unaffected side. The median ABCD2 score of 14 patients was 2 (range, 1-3). HINTS findings were objectively measured in vertigo patients with spontaneous nystagmus. Although positive findings of HINTS have been recognized as a central sign, 54% (7/13) of cases with peripheral vestibulopathy showed positive HINTS signs. HINTS results should be interpreted carefully considering that a substantial proportion of peripheral vestibulopathy shows a positive HINTS sign.

Neural Network-Based Prediction of Vehicle Fuel Consumption Based on Driving Cycle Data

This paper deals with fuel consumption prediction based on vehicle velocity, acceleration, and road slope time series inputs. Several data-driven models are considered for this purpose, including linear regression models and neural network-based ones. The emphasis is on accounting for the road slope impact when forming the model inputs, in order to improve the prediction accuracy. A particular focus is devoted to conversion of length-varying driving cycles into fixed dimension inputs suitable for neural networks. The proposed prediction algorithms are parameterized and tested based on GPS- and CAN-based tracking data recorded on a number of city buses during their regular operation. The test results demonstrate that a proposed neural network-based approach provides a favorable prediction accuracy and reasonable execution speed, thus making it suitable for various applications such as vehicle routing optimization, synthetic driving cycle validation, transport planning and similar.

Comparison Between Numerical Flow3d Software and Laboratory Data, For Sediment Incipient Motion.

In this paper, the laboratory data were compared with computational fluid dynamics (CFD) Flow3D for predicting the beginning of sediment incipient motion in rigid boundary channel for two types of sands, irrigation, and sewer types, in rectangular flume (0.5*0.5)m cross-section. Tests were made for soil samples with different diameters, specific weights. The testing was performed in slopes ranging from 0.001-0.003 for irrigation types and 0.0025-0.025 for sewer types depending on the original parameter. The Flow-3D software has simulated the laboratory work using scouring models MPM and Nielsen. the relation between sediment incipient motion velocity, particle size, and channel bed slope was predicted. The results were relatively more than laboratory data for the MPM model, while grating convergence for Nielsen model, especially for small diameter sediment. Also, the laboratory results are more close to the results of Flow3D using the Nielsen model when the value of bed slope of the channel is greater, and vice versa when the slope decreases.

Improving the Minimum Design Velocity of Sewage Pipes

The minimum design velocity for sewage pipes is set based on the planned quantity; however, deriving a reasonable design with only a single standard is limited. Thus, it is necessary to review whether consistent standards, such as the current minimum flow velocity, can efficiently transport the particles flowing in pipes. Improving the design that can determine the minimum design velocity rate and slope according to the concentration, specific gravity, particle size, and characteristics of the pipe material of the sediment flowing into the sewer system is necessary. In this study, the minimum design velocity for each particle size was examined based on the results of the simulation of fluid-solid multiphase flow required for the review process of hydraulic properties inside the pipe. The minimum design velocity standards for domestic and international sewage systems were investigated and compared, and a minimum design flow rate prediction equation was proposed considering the sedimentation. The equation includes the relationship between the particle size and pipe diameter and can be easily estimated.

Mean flow structure and velocity–bed shear stress maxima phase difference in smooth wall, transitionally turbulent oscillatory boundary layers: direct numerical simulations

Direct numerical simulations of oscillatory boundary-layer flows in the transitional regime were performed to explain discrepancies in the literature regarding the phase difference${\rm \Delta} \phi$between the bed-shear stress and free-stream velocity maxima. Recent experimental observations in smooth bed oscillatory boundary-layer (OBL) flows, showed a significant change in the widely used${\rm \Delta} \phi$diagram (Mieret al.,J. Fluid Mech., vol. 922, 2021, A29). However, the limitations of the point-wise measurement technique did not allow us to associate this finding with the turbulent kinetic energy budget and to detect the approach to a ‘near-equilibrium’ condition, defined in a narrow sense herein. Direct numerical simulation results suggest that a phase lag occurs as the result of a delayed and incomplete transition of OBL flows to a stage that mimics the fully turbulent regime. Data from the literature were also used to support the presence of the phase lag and propose a new${\rm \Delta} \phi$diagram. Simulations performed for${\textit {Re}}_{\delta }=671$confirmed the sensitivity in the development of self-sustained turbulence on the background disturbances ($\textit{Re}_{\delta}=U_{o}\delta/\nu$, where$\delta=[2\nu/\omega]^{1/2}$is the Stokes' length,$U_{o}$is the maximum free stream velocity of the oscillation,$\nu$is the kinematic viscosity and$\omega=2{\rm \pi}/T$is the angular velocity based on the period of the oscillationT). Variations of the mean velocity slope and intersect values for oscillatory flows are also explained in terms of the proximity to near-equilibrium conditions. Relaminarization and transition effects can significantly delay the development of OBL flows, resulting in an incomplete transition. The shape and defect factors are examined as diagnostic parameters for conditions that allow the formation of a logarithmic profile with the universal von Kármán constant and intersect. These findings are of relevance for environmental fluid mechanics and coastal morphodynamics/engineering applications.

Slow Motion Analysis of Repetitive Tapping (SMART) Test: Measuring Bradykinesia in Recently Diagnosed Parkinson's Disease and Idiopathic Anosmia.

Bradykinesia is the defining motor feature of Parkinson's disease (PD). There are limitations to its assessment using standard clinical rating scales, especially in the early stages of PD when a floor effect may be observed. To develop a quantitative method to track repetitive tapping movements and to compare people in the early stages of PD, healthy controls, and individuals with idiopathic anosmia. This was a cross-sectional study of 99 participants (early-stage PD = 26, controls = 64, idiopathic anosmia = 9). For each participant, repetitive finger tapping was recorded over 20 seconds using a smartphone at 240 frames per second. From each video, amplitude between fingers, frequency (number of taps per second), and velocity (distance travelled per second) was extracted. Clinical assessment was based on the motor section of the MDS-UPDRS. People in the early stage of PD performed the task with slower velocity (p < 0.001) and with greater frequency slope than controls (p = 0.003). The combination of reduced velocity and greater frequency slope obtained the best accuracy to separate early-stage PD from controls based on metric thresholds alone (AUC = 0.88). Individuals with anosmia exhibited slower velocity (p = 0.001) and smaller amplitude (p < 0.001) compared with controls. We present a simple, proof-of-concept method to detect early motor dysfunction in PD. Mean tap velocity appeared to be the best parameter to differentiate patients with PD from controls. Patients with anosmia also showed detectable differences in motor performance compared with controls which may suggest that some were in the prodromal phase of PD.

Multi-parameter predictive shift schedule of automatic mechanical transmission for electric bus

Shift schedule is crucial in improving the dynamic and economic performance of electric vehicles (EVs) equipped with automatic mechanical transmission (AMT). As the driver, vehicle, and road constitute a closed-loop inseparable system, identifying the states of both vehicle and road is fundamental to realizing optimal shift schedule. However, the existing shift strategies neglect the coupling relationship of multiple parameters to the shift strategy. To minimize this gap, this paper presents a novel multi-parameter shift schedule based on model predictive control. Firstly, cubature Kalman filters (CKF) algorithm is employed to accurately estimate vehicle quality and road slope, which could improve the energy economy of EVs. Secondly, an artificial neural network (ANN) is adopted to forecast the compound future short horizon driving conditions, which contains the perdition information of vehicle velocity and road slope. Meanwhile, the AMT predictive shift schedule based on the above estimated and forecast information is constructed, which used dynamic programming to optimize in the rolling horizon. Simulation study results indicate that the ANN-based predictive approach shows better performance on accuracy and robustness than that of Markov chain, and the electricity consumption over China typical urban driving cycle (CTUDC) is further reduced by 6.79% than that of multi-parameter rule-based shift schedule.

Spectra of Temperature Fluctuations in the Solar Wind

Turbulent cascade transferring the free energy contained within the large scale fluctuations of the magnetic field, velocity and density into the smaller ones is probably one of the most important mechanisms responsible for heating of the solar corona and solar wind, thus the turbulent behavior of these quantities is intensively studied. The temperature is also highly fluctuating quantity but its variations are studied only rarely. There are probably two reasons, first the temperature is tensor and, second, an experimental determination of temperature variations requires knowledge of the full velocity distribution with an appropriate time resolution but such measurements are scarce. To overcome this problem, the Bright Monitor of the Solar Wind (BMSW) on board Spektr-R used the Maxwellian approximation and provided the thermal velocity with a 32 ms resolution, investigating factors influencing the temperature power spectral density shape. We discuss the question whether the temperature spectra determined from Faraday cups are real or apparent and analyze mutual relations of power spectral densities of parameters like the density, parallel and perpendicular components of the velocity and magnetic field fluctuations. Finally, we compare their spectral slopes with the slopes of the thermal velocity in both inertial and kinetic ranges and their evolution in course of solar wind expansion.

Constructing representative driving cycle for heavy duty vehicle based on Markov chain method considering road slope

Electrification of heavy duty vehicles (HDVs) is critical to realization of the target of carbon neutralization in the future. For most HDVs, the influence of road slope on vehicle power usually cannot be ignored due to significant road slope variation during long driving mileages. In order to design the powertrain system for electrified HDVs effectively, it is necessary to construct representative driving cycles with road slope information. There are two difficulties for this task. (1) Road slope measuring devices are usually costly. A cheaper yet effective method for measuring road slope needs to be developed. (2) A 3D (three dimension) Markov chain method is usually utilized for constructing cycles with velocity and road slope. This method is complex and time consuming, and needs to be improved. In this paper, a 2D (two dimension) Markov chain method for addressing these issues is proposed. A road slope observation is designed based on normal GPS (Global Positioning System) signals and a high order Butterworth filter. The effectiveness of the method is validated. Driving velocity and road slope are collected and observed for the area between Beijing and Zhangjiakou in northern China. Representative cycles with road slope are constructed using a 2D Markov chain method and a matching algorithm based on average speed. With the introduced technology, three representative driving cycles with road slope for urban, suburban and highway routes are designed. Statistic results on vehicle power show that, the representative driving cycles are effective with relative errors less than 4% compared to the real driving conditions. These driving cycles will be utilized in designing electric HDVs, such as hydrogen fuel cell vehicles in the future.

Abstract P508: Hyperglycemia Exacerbated Sars-cov-2 Spike Protein-induced Electrophysiological Dysfunctions In Hipsc-derived Cardiomyocytes

Background: Cardiac arrhythmias, heart failure, and myocarditis are common symptoms associated with coronavirus 2 (SARS-CoV-2) infection. The cytopathic effect of SARS-CoV-2 is initiated by spike protein (S-protein) binding to the ACE2 receptor. However, cellular mechanisms of SARS-CoV-2 causing cardiac complications, particularly in a subset of the population such as diabetic patients, remain unclear. Aims: To determine electrophysiological cytopathic effects of SARS-CoV-2 S-protein in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Methods and Results: CMs were differentiated from WTC-11, then re-plated on 48-well microelectrode array (MEA) plates and cultured under normal or hyperglycemic conditions (Glucose 5 mM (NG), and Glucose 20 mM (HG)) for three days. These HiPSC-CMs were treated with recombinant S-protein with or without insulin supplementation. Cardiac modules in AxIS MEA program were used to acquire and analyze electric and contractile functions. Beat period and field potential duration were significantly prolonged, while conductance velocity and spike slope were accelerated in HG without insulin compared to that in HG with insulin (p&lt;0.05). S-protein-induced perturbations in local extracellular action potential (LEAP) matrices (e.g., LPD30, 50, 90) and Contractility matrices in HG were mitigated by insulin treatment. Higher concentration S-protein induced perturbations in normal hiPSC-CMs (NG+insulin). One day after S-protein treatment, CM functions appeared comparable to the pretreatment state, although changes in some electro-contractile matrices persisted. Conclusion: These results demonstrate SARS-CoV-2 viral structural protein can induce acute electrophysiological dysfunctions in hiPSC-CMs, which is influenced by glucose level. This establishes a new model for dissecting the mechanism of cardiac complications in viral infection.

Analytical solution of nonlinear differential equations two oscillators mechanism using Akbari–Ganji method

In the last decade, many potent analytical methods have been utilized to find the approximate solution of nonlinear differential equations. Some of these methods are energy balance method (EBM), homotopy perturbation method (HPM), variational iteration method (VIM), amplitude frequency formulation (AFF), and max–min approach (MMA). Besides the methods mentioned above, the Akbari–Ganji method (AGM) is a highly efficient analytical method to solve a wide range of nonlinear equations, including heat transfer, mass transfer, and vibration problems. In this study, it was constructed the approximate analytic solution for movement of two mechanical oscillators by employing the AGM. In the derived analytical method, both oscillator motion equations and the sensitivity analysis of the frequency were included. The AGM was validated through comparison against Runge–Kutta fourth-order numerical method and an excellent agreement was achieved. Based on the results, the highest sensitivity of the oscillation frequency is related to the mass. As [Formula: see text] and [Formula: see text] increase, the slope of the system velocity and acceleration will increase.

Determination of the escape velocity of the Milky Way using a halo sample selected based on proper motion

Context. The Gaia mission has provided the largest catalogue ever of sources with tangential velocity information. However, it is difficult to use this catalogue for dynamical studies because most of the stars lack line-of-sight velocity measurements. Recently, we presented a selection of ∼107 halo stars with accurate distances that were selected based on their photometry and proper motions. Aims. Using this sample, we model the tail of the velocity distribution in the stellar halo locally and as a function of distance. Our goal is to measure the escape velocity, and based on this, to constrain the mass of our Galaxy. Methods. We fitted the tail of the velocity distribution with a power-law distribution, a commonly used approach that has long been established. For the first time, we used tangential velocities that were accurately measured for an unprecedented number of halo stars to estimate the escape velocity. Results. In the solar neighbourhood, we obtain a very precise estimate of the escape velocity, which is 497−8+8 km s−1. This estimate is most likely biased low, our best guess is by 10%. As a result, the true escape velocity is most likely closer to 550 km s−1. The escape velocity directly constrains the total mass of the Milky Way. To find the best-fitting halo mass and concentration parameter, we adjusted the dark (spherical Navarro-Frenk-White) halo of a realistic Milky Way potential while keeping the circular velocity at the solar radius fixed at vc(R⊙) = 232.8 km s−1. The resulting halo parameters are M200+10% = 1.11−0.07+0.08 · 1012 M⊙, and the concentration parameter is c+10% = 11.8−0.3+0.3, where we use the explicit notation to indicate that they are corrected for the 10% bias. The slope of the escape velocity with galactocentric distance is as expected in the inner Galaxy based on Milky Way models. Curiously, we find a disagreement beyond the solar radius where the estimated escape velocity is higher than at the solar radius. This result is likely an effect of a change in the shape of the velocity distribution and could be related to the presence of velocity clumps. A tentative analysis of the escape velocity as a function of (R, z) shows that the slope is shallower than expected for a spherical halo when standard values are used for the characteristic parameters describing the galactic disc.

Study on Energy Consumption Characteristics of Sewage Pipe under Different Conditions

It can optimize the design of sewage pipe network system and select the design conditions of pipe network to obtain the best hydraulic characteristics and the most economical design plan by studying the hydraulic characteristics of sewage pipe network under different conditions. In this paper, k-s turbulence model is used to calculate the change of energy consumption characteristics in sewage pipe network under different working conditions. The results show that the pipe diameter is too small and the pressure on the pipe wall increases, which is not conducive to flood discharge. If the inlet velocity is too small, the negative slope of the pipe would lead to the reduction of the overall flow rate, which is easy to cause siltation of the sewage pipe network. Proper pipe diameter, inlet velocity and reasonable slope can help the pipe drain water. Increasing the diameter of the main pipe can improve the stability of the fluid, which is more conducive to sewage discharge.

Synthesis and Feature Selection-Supported Validation of Multidimensional Driving Cycles

This paper presents the synthesis and validation of multidimensional driving cycles represented by vehicle velocity, vehicle acceleration, and road slope profiles. For this purpose, a rich set of city bus driving cycles has been recorded. First, a Markov chain model is established based on velocity, acceleration, road slope and road slope time derivative states. Next, a large set of synthetic driving cycles is generated by using a corresponding 8D transition probability matrix, which is implemented in a sparse form based on a dictionary of keys to improve computational efficiency and reduce memory requirements. In support of synthetic driving cycles validation, a number of time- and frequency-domain statistical features are considered, including unique cross-correlation velocity–acceleration–road slope indicators. To predict fuel consumption related to synthetic driving cycles, an accurate neural network model is introduced which uses a fixed 3D histogram of counted discrete velocity, acceleration, and road slope inputs. The significance of each nominated statistical feature and its impact on fuel consumption is revealed by means of linear regression modelling and least absolute shrinkage and selection operator (LASSO) feature selection method. A model having only several most significant features as inputs and fuel consumption as output is proposed to be used for unambiguous single-criterion validation of synthetic driving cycles with respect to recorded ones. Finally, the proposed validation approach is verified against a widely used method relying on minimization of statistical feature deviations with respect to true values. The results point out that, by applying the proposed synthesis and validation method, it is possible to extract most representative synthetic driving cycles in a straightforward and computationally efficient way. The main anticipated applications include various simulation-based analyses that require representative synthetic driving cycles and/or accurate vehicle energy consumption predictions.