Correction: Williams et al. Kinetics and Kinematics of Working Trials Dogs: The Impact of Long Jump Length on Peak Vertical Landing Force and Joint Angulation. Animals 2021, 11, 2804

The authors wish to make the following correction to this paper [...]

Investigation Of Hydraulic Flow Characteristics On Drop Structures

Drop structures are required if the slope of the ground level is steeper than the maximum allowable gradient channel. Drop structures become bigger as height increases. Its hydraulic capability may be reduced due to variations of jets falling on the stilling basin floor due to discharge changing. Drop structures should not be used if the change in energy level exceeds 1.50 m. The free-falling overflow on drop structures will hit the stilling basin and move downstream. As a result of overflows and turbulence in the pool below the nappe, some energy is dissipated at the front. The rest of the energy will be reduced downstream. The objectives of this study are to investigate the hydraulics flow behavior in straight and sloping drop structures and to investigate hydraulics flow behavior in a single and serial vertical drop (stepped drop). The hydraulic model results of single and stepped drop structures are compared to obtain flow behavior and energy dissipation information. The comparisons are specific to the flow parameters, including flow depth at the drop structures toe, flow depth after the jump, and hydraulic jump length.

Kinetics and Kinematics of Working Trials Dogs: The Impact of Long Jump Length on Peak Vertical Landing Force and Joint Angulation

Working trials is a competitive canine discipline based on work undertaken by military and police dogs. A 9 ft long jump is a key component of the discipline. Research into landing forces and joint angulation in other canine disciplines has highlighted the potential for the occurrence of soft tissue injuries, predominantly in the front limbs. There is a paucity of work into the impact of spread/long jumps on joint angulation and peak vertical force (PVF) on landing, and limited research on working trials dogs generally. This study aimed to determine whether altering the length of the long jump impacted PVF and apparent joint angulation upon landing. 21 dogs regularly competing in working trials cleared the long jump at three lengths: 9 ft (full length), 8 ft, and 7 ft. The impact of altered long jump length on the PVF, apparent shoulder and carpus angulation, and duration of landing, were analysed using general linear mixed models. There was no significant relationship between the length of the long jump and PVF or joint angulation on landing (p > 0.05). Greatest joint compression was observed on landing after clearing 9 ft. Individual variability in landing joint angulation, PVF and force distribution of the left and right front limbs on landing was observed across all three experimental lengths. We recommend further research is undertaken to examine individual variability and the effect of training and experience in working trials participants, to provide evidence-based recommendations for training people and competing dogs in this discipline.

Uncertainty analyses regarding evaluating effective parameters on the hydraulic jump characteristics of different shape channels

The hydraulic jump phenomenon is a beneficial tool in open channels for dissipating the extra energy of the flow. The sequent depth ratio and hydraulic jump length critically contribute to designing hydraulic structures. In this research, the capability of Support Vector Machine (SVM) and Gaussian Process Regression (GPR) as kernel-based approaches was evaluated to estimate the features of submerged and free hydraulic jumps in channels with rough elements and various shapes, followed by comparing the findings of GPR and SVM models and the semi-empirical equations. The results represented the effect of the geometry (i.e., steps and roughness elements) of the applied appurtenances on hydraulic jump features in channels with appurtenances. Moreover, the findings confirmed the significance of the upstream Froude number in the sequent depth ratio estimating in submerged and free hydraulic jumps. In addition, the immersion was the highest contributing variable regarding the submerged jump length on sloped smooth bed and horizontal channels. Based on the comparisons among kernel-based approaches and the semi-empirical equations, kernel-based models showed better performance than these equations. Finally, an uncertainty analysis was conducted to assess the dependability of the best applied model. The results revealed that the GRP model possesses an acceptable level of uncertainty in the modeling process.

Existence of a linear flows particle tracking model with a stochastic waiting time depending on the Gaussian jump length

This paper discusses the existence of the tracking model to detect a linear flows particle with a stochastic waiting time depending on the Gaussian jump length. This model is useful to measure the impurity quantification such as Radionuclides and Toxic Chemicals (particle) within the interaction medium (fluid) with minimum time and maximum probability. The particle flows linearly toward the origin (either from the left or the right). The flow line contains a nano programmed sensor (or nano UV detector). This sensor starts the tracking process for the particle (target) from the origin (filtration point) with speed equals one. We obtain the expected value of the tracking time until the sensor return to the origin with the target. Some competitive analysis depends on the uncertain values of the traveled distances which are derived to get necessary conditions for the sensor’s optimal distances. The numerical results demonstrate the efficiency of this model.

A Novel Analytical Method for Evaluating the Characteristics of Hydraulic Jump at a Positive Step

We present a new method to evaluate the hydraulic jump characteristics in a horizontal rectangular channel with a positive step. We considered the flow curvature effect and the free surface’s small rise at the A-type hydraulic jump’s end. First, we present a novel method to give jump length estimation based on the similarity of the jump and the turbulent wall-jet, considering the pressure gradient. Then, considering the jump as a curvilinear flow and using a one-dimensional momentum equation, we present an accurate expression for the conjugate flow depth regarding the initial Froude number and step height. Finally, we compute the jump’s energy dissipation rate. Compared to the theoretical models for conjugate flow depth in a hydraulic jump, the proposed equation in this study fit the experimental data better, even for high steps and large initial Froude numbers. However, for low Froude numbers (F1 < 5), the equation was less accurate in estimating the jump length. Regarding the jump’s energy dissipation rate, the results agreed well with the experimental data from previous investigations. However, it is noted that the increased energy dissipation rate dwindled in larger Froude numbers.

Predicting submerged hydraulic jump characteristics using machine learning methods

Hydraulic jump typically occurs downstream of hydraulic structures by converting the supercritical to subcritical flow regimes. If the tail-water depth is greater than the secondary depth of the hydraulic jump, the jump will be submerged (SHJ). In these conditions, the momentum equations will not have an analytical solution and a new solution is required. In this study, after dimensional analysis, an experimental study was conducted in a rectangular flume with a length of 9 m, a width of 0.5 m and a depth of 0.45 m in a wide range of Froude numbers (Fr = 3.5 to 11.5) and submergence ratios (Sr = 0.1 to 4). The data were then normalized and divided into two parts of training and testing. A new technique, DGMDH, was used to predict the submerged hydraulic jump characteristics. The results were then compared with the GMDH model. The results showed that DGMDH model estimated the relative submergence depth, jump length, and relative energy loss with accuracy of R2 = 0.9944 and MAPE = 0.038, R2 = 0.9779 and MAPE = 0.0387, and R2 = 0.9932 and MAPE = 0.0192, respectively. While the accuracy of GMDH model for relative submergence depth, jump length, and relative energy loss was respectively R2 = 0.9923 and MAPE = 0.043, R2 = 0.9671 and MAPE = 0.0527, and R2 = 0.9932 and MAPE = 0.0192. Due to superiority of the DGMDH model over the GMDH model, it is recommended to use this model to estimate the submerged hydraulic jump characteristics. Highlight The results showed that DGMDH model have more accurate results than the GMDH model in predicting the relative submergence depth, jump length, and relative energy loss.

Development of a modified cross-over hop test to reduce measurement errors in return-to-competition testing

Context Hop tests play an important role in the rehabilitation process after injuries. A comparison of the jumping distances of both extremities allows for an evaluation of the injured limb. In the conventional cross-over hop test for distance, the jump width (medial vs. lateral) that the athlete has to cross during the jump is not standardised and therefore highly variable. This affects the absolute jump length in each jump series. Hypothesis Modifying the test may reduce the jump length variance between test series of an athlete as well as the test-dependent variations in the cross-over hop for distance. Methods N = 47 athletes from the German and French national Judo youth teams were included in the study (age: 15.3 years ± 13–17). A modified version of the cross-over hop for distance was developed with a cross-over width of 50 cm and a fixed landing zone of 10 cm. The jump lengths of the conventional test and the modified test were documented. The change in jump length variations of the two sexes were compared. Results The mean value of the coefficient of variation decreased significantly from 4.09 % to 2.83 % (p < 0.01) due to the test modification. This resulted in an absolute improvement in accuracy of 1.26 % and a relative improvement of 30.8 %. A comparison of the limb symmetry index between the conventional and the modified cross-over hop for distance revealed no significant differences. Conclusion The modified cross-over hop for distance showed a significantly lower variation in jump lengths compared with the conventional cross-over hop for distance. As a result, more accurate statements can be made regarding the patient’s return-to-competition progress.

Experimental study and modeling of hydraulic jump for a suddenly expanding stilling basin using different hybrid algorithms

Hydraulic jump is a highly important phenomenon for dissipation of energy. This event, which involves flow regime change, can occur in many different types of stilling basins. In this study, hydraulic jump characteristics such as relative jump length and sequent depth ratio occurring in a suddenly expanding stilling basin were estimated using hybrid Extreme Learning Machine (ELM). To hybridize ELM, Imperialist Competitive Algorithm (ICA), Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) metaheuristic algorithms were implemented. In addition, six different models were established to determine effective dimensionless (relative) input variables. A new dataset was constructed by adding the data obtained from the experimental study in the present research to the data obtained from the literature. The performance of each model was evaluated using k-fold cross validation. Results showed that ICA hybridization slightly outperformed FA and PSO methods. Considering relative input parameters, Froude number (Fr), expansion ratio (B) and relative sill height (S), and effective input combinations were Fr – B– S and Fr – B for the prediction of the sequent depth ratio (Y) and relative hydraulic jump length (Lj/h1), respectively.

Velocity Distribution and Attenuation Characteristic in Hydraulic Jumps on Rough Beds

This study was conducted to investigate the velocity distribution and attenuation in free jumps on rough beds. Based on the length scale of jump length Lj, the velocity distribution of the free jump on a rough bed can be divided into four parts by three typical sections where are in the position of x=0.4Lj, x=0.8Lj, and x=1.2Lj. It seems that the velocity distribution near section x=0.4Lj is the most uneven. The velocity attenuation rate in the bottom half of the water is larger than that in the top half of the water. The attenuation of the maximum velocity um is mainly done from x=0 to x=0.8Lj. The results show the mixed triangular corrugated floor increases the resistance of hydraulic jump development and is very efficient in energy dissipation.