Inertial Parameters Research Articles

Comprehensive CFD Analysis of Base Pressure Control Using Quarter Ribs in Sudden Expansion Duct at Sonic Mach Numbers

This study aims to assess the effect of rib size, shape, and location in a suddenly expanded flow at sonic Mach number. Flow from a converging nozzle is exhausted into a larger area of duct diameter of 18 mm. The geometric parameters considered are the area ratio, duct length, rib radius, and inertia parameters, which are considered the level of expansion at critical Mach number. In the present study, duct lengths were from 1D to 6D, rib radii considered were 1 mm to 3 mm, and rib locations were 0.5D, 1D, 1.5D, 2D, and 3D. Results show that when the ribs are placed near the reattachment point with a 3 mm radius, they are efficient and capable of reducing the suction in the recirculation zone and the base pressure, which was lower than the ambient pressure in the absence of ribs, is assorted larger than the back pressure. If the requirement is to equate the pressure at the base to ambient pressure, then a 2 mm radius is the right choice. Furthermore, the 1 mm rib cannot reduce the suction in the base region, and base pressure remains sub-atmospheric for the entire range of rib locations, as well as the NPRs of the present study. When the orientation of the ribs is changed, and the flow interacts with the flat surface instead of the curved surface, there is a marginal change in the flow pattern, and there is no significant change in the base pressure values.

A novel inertial parameter identification method for the ship-mounted Stewart platform based on a wave compensation platform

To meet the requirement of time-varying inertial parameter identification of control algorithms for shipborne Stewart wave compensation platforms, this study proposes an innovative inertial parameter identification method based on a non-inertial system. Unlike traditional Stewart identification methods with a fixed frame, the proposed method does not require designing excitation trajectories to consider the condition number of the observation matrix. Namely, the proposed method requires only performing two-dimensional dynamic parameter collection for parameter identification in a six-dimensional non-inertial motion. In addition, a coupling error dimension reduction method is developed to improve the identification accuracy under the condition of coupling motion. Finally, experiments are conducted to verify the effectiveness of the proposed identification method. The experimental results show that under the coupling motion conditions, the coupling errors of the corrected singularity points are reduced by 7.9–28.1% compared to before correction, and the axial force average error correction is below 5.32%.

A vertical take-off and landing (VTOL) unmanned aircraft vehicle trajectory control model with air-launched missiles

Purpose In today’s technology, the significance of unmanned aerial vehicles is steadily increasing. Many unmanned aerial vehicles design, especially those used for military purposes, have achieved autonomy from human operators. Undoubtedly, one of the most crucial features of these aircraft is their vertical take-off and landing (VTOL) capability. Inspired by quadrotor methodology, this paper aims to conduct, a modeling of an aircraft with VTOL capabilities. Design/methodology/approach The impact of releasing air-launched missiles, considered as the useful payload carried during the flight of the aircraft, has been taken into account in this modeling. The release of air-launched missiles disrupts both the symmetric structure of the system and alters the mass and inertia parameters. Simulations were conducted to investigate scenarios involving the simultaneous release of all air-launched missiles and their release at different times. Findings The investigation focused on determining how quickly an aircraft, aiming to consecutively hit targets, can return to its desired trajectory. The time interval between the consecutive releases of two air-launched missiles has been identified. Originality/value It is crucial for a VTOL-capable aircraft to possess a unique modeling structure to examine its capability of releasing air-launched missiles in various scenarios. This entails understanding not only the aircraft’s VTOL functionality but also its ability to effectively release missiles in different operational conditions.

MHD flow of chemically reacting Casson fluid through a moving plate in non-Darcian porous medium with second-order slip velocity

The MHD flow of optically thick, incompressible, chemically reacting Casson fluid through a moving vertical plate exposed in a non-Darcian porous medium with second-order slip velocity is studied in this work. The plate is under a constant suction velocity. A consistently strong magnetic field is anticipated to be applied normally to the plate. This study includes the effects of Joule heating, viscous dissipation, Soret number and heat source. The MATLAB-bvp4c method is employed for solving the associated governing equations. The flow velocity rises with the growth of porosity parameter, solutal Grashof number, thermal Grashof number and Soret number but it decreases with the inertia parameter, chemical reaction parameter and magnetic parameter. The effect of Soret number raises the skin friction.

Effects of new nonlinear curvature models and non-local elasticity on buckling investigation of FG tapered nano-beams locating on elastic foundations

New nonlinear curvature models are proposed to show their effects on the compressive critical buckling load on functionally graded (FG) tapered nano-beams locating on elastic foundations in the presence of non-local elasticity. Fourth and fifth orders finite difference methods (bvp4c and bvp5c) are applied on the governing differential equation which is a highly non-linear, due to curvature and has variable coefficients, due to properties. Dimensional analyses have been applied on the governing system together with the problem conditions to produce their dimensionless forms. For different considered parameters, the critical buckling load is computed using the eigenvalue theorem. The effects of nonlinear curvature, variable Young modulus, variable moment inertia and foundation parameters are studied and displayed in tables and figures. The stability and convergence of the present solution are tested using more than one strategy as: comparison with available results, comparison between bvp4c and bvp5c with different mesh intervals and tolerances of truncation errors. These comparisons show that, the new curvature model affects the critical buckling with different ratios depending on variability of properties and foundation parameters. The new results show that the nonlinear curvature model reduces the critical buckling load in comparison with the classical linear model, which, leads to decreasing in factor of safety in design of structures. The new results show that the design of structures will be influenced with the new reduction of the compressive critical buckling load, since it may affect the factor of safety in design of structures. The new results can lead, generally, to more reduction of critical buckling load for large or small input parameters and it will affect other critical values such that frequencies. The introduced Tables and Figures of the present problem with comparisons of previously exact, analytical and numerical works establish the higher accuracy and stability of current findings using bvp4c or bvp5c with preferable of the later. This study is related to some practical applications such as aeronautical and structural engineering.

Voltage stability control strategy for DC microgrid based on adaptive virtual DC motor

The large-scale integration of distributed energy sources and power electronic devices results in the DC microgrid exhibiting significant low inertia and weak damping characteristics. This, in turn, leads to inevitable fluctuations in the DC bus voltage, which endanger the stable operation of the DC system. Energy storage devices can provide equivalent inertia. To enhance the inertia and response speed of the DC bus interface converter, this paper proposes a power allocation parameter adaptive virtual DC motor control strategy based on a hybrid energy storage unit. The strategy introduces power allocation control to regulate the energy storage converter on the basis of virtual inertia parameter adaptive control, thereby enabling the energy storage converter to simulate the inertia and damping characteristics of a DC generator. The small-signal stability of the system is analyzed by establishing a small-signal model of the photovoltaic energy storage system and utilizing the impedance ratio criterion. Finally, the proposed control strategy is validated through simulation. The results demonstrate that the strategy effectively mitigates the fluctuations in bus voltage under varying photovoltaic power and sudden load changes, ensures the power distribution in the hybrid energy storage system, and enhances the dynamic response of the system.

Sensorless Human–Robot Interaction: Real‐Time Estimation of Co‐Grasped Object Mass and Human Wrench for Compliant Interaction

Human–robot physical interaction in shared object manipulation can fully leverage the strengths of both humans and collaborative robots, achieving better interaction outcomes. However, in typical physical interactions, the inertia parameters of the object are either assumed to be known or ignored, simplifying the interaction to be directly between the human and the collaborative robot. This simplification can lead to inaccuracies in the robot's understanding of human intent due to deviations in object dynamics. This article presents a method that eliminates the need for a force sensor on the human side during human–robot collaboration. Using an extended Kalman filter, the method estimates object parameters online and applies a disturbance observer to determine human force. This approach reduces human effort and improves tracking performance compared to traditional methods. It also avoids the hassle of installing and removing sensors in complex scenarios. By estimating object mass and human force in real time, the robot can adjust its behavior to ensure safer and smoother interactions. Furthermore, the system can handle various objects without requiring specific programming for each case.

From lab to field: validity and reliability of inertial measurement unit-derived gait parameters during a standardised run

ABSTRACT The aim was to assess concurrent validity and test–retest reliability of spatiotemporal gait parameters from a thoracic-placed inertial measurement unit (IMU) in lab- (Phase One) and field-based (Phase Two) conditions. Spatiotemporal gait parameters were compared (target speeds 3, 5 and 7.5 m·s−1) between a 100 Hz IMU and an optical measurement system (OptoJump Next, 1000 hz) in 14 trained individuals (Phase One). Additionally, 29 English Premier League football players performed weekly 3 × 60 m runs (5 m·s−1; observations = 1227; Phase Two). Mixed effects modelling assessed the effect of speed on agreement between systems (Phase One) and test–retest reliability (Phase Two). IMU step time showed strong agreement (<0.3%) regardless of individual or running speed. Direction of mean biases up to 40 ms for contact and flight time depended on the running speed and individual. Step time, length and frequency were most reliable (coefficient of variation = 1.3-1.4%) but confounded by running speed. Step time, length and frequency derived from a thoracic-placed IMU can be used confidently. Contact time could be used if bias is corrected for each individual. To optimise test–retest reliability, a minimum running distance of 40 m is needed to ensure 10 constant-speed steps is gathered.

Dynamics Parameter Identification of Articulated Robot

Dynamics parameter identification in the establishment of a multiple degree-of-freedom (DOF) robot’s dynamics model poses significant challenges. This study employs a non-symbolic numerical method to establish a dynamics model based on the Newton–Euler formula and then derives a proper dynamics model through decoupling. Initially, a minimum inertial parameter set is acquired by using QR decomposition, with the inclusion of a friction model in the robot dynamics model. Subsequently, the least squares method is employed to solve for the minimum inertial parameters, forming the basis for a comprehensive robot dynamics parameter identification system. Then, after the optimization of the genetic algorithm, the Fourier series trajectory function is used to derive the trajectory function for parameter identification. Validation of the robot’s dynamics parameter identification is performed through simulation and experimentation on a 6-DOF robot, leading to a precise identification value of the robot’s inertial parameters. Furthermore, two methods are employed to verify the inertia parameters, with analysis of experimental errors demonstrating the effectiveness of the robot dynamics parameter identification method. Overall, the effectiveness of the entire calibration system is verified by experiments, which can provide valuable insights for practical engineering applications, and a complete and effective robot dynamics parameter identification scheme for a 6-DOF robot is established and improved.

Multi-visual-inertial system: Analysis, calibration, and estimation

In this paper, we study state estimation of multi-visual-inertial systems (MVIS) and develop sensor fusion algorithms to optimally fuse an arbitrary number of asynchronous inertial measurement units (IMUs) or gyroscopes and global and/or rolling shutter cameras. We are especially interested in the full calibration of the associated visual-inertial sensors, including the IMU/camera intrinsics and the IMU-IMU/camera spatiotemporal extrinsics as well as the image readout time of rolling-shutter cameras (if used). To this end, we develop a new analytic combined IMU integration with inertial intrinsics—termed ACI3—to pre-integrate IMU measurements, which is leveraged to fuse auxiliary IMUs and/or gyroscopes alongside a base IMU. We model the multi-inertial measurements to include all the necessary inertial intrinsic and IMU-IMU spatiotemporal extrinsic parameters, while leveraging IMU-IMU rigid-body constraints to eliminate the necessity of auxiliary inertial poses and thus reducing computational complexity. By performing observability analysis of MVIS, we prove that the standard four unobservable directions remain—no matter how many inertial sensors are used, and also identify, for the first time, degenerate motions for IMU-IMU spatiotemporal extrinsics and auxiliary inertial intrinsics. In addition to extensive simulations that validate our analysis and algorithms, we have built our own MVIS sensor rig and collected over 25 real-world datasets to experimentally verify the proposed calibration against the state-of-the-art calibration method Kalibr. We show that the proposed MVIS calibration is able to achieve competing accuracy with improved convergence and repeatability, which is open sourced to better benefit the community.

System identification and force estimation of robotic manipulator using semirecursive multibody formulation

AbstractForce estimation in multibody dynamics relies heavily on knowing the system model with a high level of accuracy. However, in complex mechatronic systems, such as robots or mobile machinery, the values of model parameters may be only roughly estimated based on design information, such as CAD data. The errors in model parameters consequently have a direct effect on force estimation accuracy because the estimator compensates the erroneous inertia, friction, and applied forces by changing the value of estimated external force. The objective of this study is to present the workflow of system identification and state/force estimation of an open-loop multibody structure. The system identification utilizes a linear regression identification method used in robotics adapted to the multibody framework. The semirecursive multibody formulation, in particular, is studied as a formulation for both system identification and force estimation. The multibody state/force estimator is constructed using extended Kalman filter. The specific aim of this paper is to demonstrate the utilization of these per se known modeling, identification, and estimation tools to address their current lack of integration as a complete toolchain in virtual sensing of multibody systems. The methodology of the study is tested with both artificial and experimental data of Stäubli TX40 robotic manipulator. In the experimental analysis, an openly available benchmark data set was used. Artificial data were created by running an inverse dynamics analysis with inertia and friction parameters taken from literature. The results show that the multibody inertia and friction parameters can be accurately identified and the identified model can be used to produce decent estimates of external forces. The proposed multibody system identification method itself opens new opportunities in tuning the multibody models used in product development. Moreover, effective use of system identification together with state estimation helps to build more accurate estimators. When the system model is accurately identified, the capability of state estimator to observe unknown inputs, such as external forces, is significantly enhanced.

Insight into the magnetohydrodynamic flow of CNT-based nanofluid through a horizontal porous channel: Nanoparticle passive control

This work aims to investigate the CNT-based nanofluid flow in a rotating horizontal channel. The fluid is considered to be thermally radiative, and Hall effect is expected to be dominant in the fluid flow. The Darcy-Forchheimer model is used to describe the flow of a porous material. The usual approach of transformation converts the nonlinear partial differential equations (PDEs) into a reduced set of ordinary differential equations (ODEs). To solve the created model, the MATLAB bvp4c procedure is used. The effects on temperature, speed and volume percentage of nanotubes of the key flow parameters are clearly indicated by the graphs. Energy strength, and surface drag force are also calculated and summarized. The result shows that both primary and secondary fluid velocities with MWCNTs are decreased with the inertia parameter. In addition, a rise in thermophoresis occurrences leads to an increased temperature of nanofluids, whereas an increase of Brownian diffusion parameter leads to lower nanofluid temperature.

An analytical approach for power system frequency stability evaluation

AbstractRecent years have seen high penetration of renewable energies, which have significantly reduced the inertia of bulk power systems. As a result, the frequency behaviour of power systems is becoming more complex. To resolve this technical challenge, there is a particularly strong interest in developing analytical solutions for frequency dynamics studies. This study first describes a second‐order frequency dynamics model for power systems with renewable energies. A non‐linear perturbation approach is suggested to drive the analytical solution of the model. It is shown that, under many circumstances, frequency dynamics can be effectively approximated using a linear model. Subsequently, the article describes a fourth‐order linear frequency dynamics model that takes into account governor‐turbines. A polynomial eigenvalue method is proposed to identify the dominant and non‐dominant modes of the solution of the four‐order model. It is demonstrated that the dominant mode has a decisive impact on frequency behaviour, while the non‐dominant modes influence the relative frequency oscillations only. Finally, the study derives the analytical expressions of the standard frequency performance metrics and examines the impact of damping and inertia parameters. The introduced results are verified using two test systems, demonstrating the accuracy and effectiveness of the suggested method.

Microscopic derivation of the generalized collective Hamiltonian

The nucleus in the center-of-mass frame is described by 3A−3 independent coordinates, including three Euler angles and three variables ρ,β,andγ to describe orientation, size, and shape of the nuclear inertia ellipsoid as well as 3A−9 generalized Euler angles to describe internal motion of the nucleons. Based on the idea that the incompressible nucleus has constant density, we suggest a definition of the deformation parameter β. It allows us to derive the Hamiltonian, which describes large-amplitude collective motions. At β≪1 it reduces to a sum of the Bohr Hamiltonian and the Hamiltonian of monopole ρ vibrations. As a result of straightforward calculations we obtain explicit expressions for all the inertial parameters as functions of the variables ρ,β,andγ. Published by the American Physical Society 2024

Analysis of Darcy–Forchheimer flow of magnetized hybrid nanofluid (MoS 2+ZnO/E) with non-linear heat source and quartic autocatalytic chemical reaction

In this article, an effort is made to analyze the 3 − D flow of hybrid nanofluid over a rotating stretching sheet. The hybrid nanofluid contains engine oil as a base fluid amalgamated with nano-particles Mo S 2 and ZnO . The flow is assumed to pass through a Darcy–Forchheimer medium subjected to the influence of an inclined magnetic field. In addition, heat radiation, Joule heating, viscous dissipation, nonlinear heat source, and quartic autocatalytic chemical reaction are applied to discourse heat and mass transfer features. The PDEs representing the physical problem are converted to ODEs with the introduction of similarity transformations. The solution of the problem is determined numerically by using MATLAB built-in bvp4c method. The proposed mathematical model’s validation is ascertained by comparing it with an earlier study in limiting case. In this regard, an excellent consensus is accomplished. The current investigation reveals that the flow along axial direction gets retarded by enhancing the values of rotational parameter, inertial parameter, and magnetic parameter, whereas the flow along radial direction gets accelerated. The increasing value of angle of inclination admirably resists the motion of nanofluid and hybrid nanofluid. The concentration profile gets decreased under the increasing influence of inclination angle and Schmidt number while it enhances for homogeneous reaction parameter. The enhancing values of rotational parameter, solid volume fraction and temperature, and exponential dependent heat generation parameters enhance the value of Nusselt number.

Parameter identification of an open-frame underwater vehicle based on numerical simulation and quantum particle swarm optimization

Accurate parameter identification of underwater vehicles is of great significance for their controller design and fault diagnosis. Some studies adopt numerical simulation methods to obtain the model parameters of underwater vehicles, but usually only conduct decoupled single-degree-of-freedom steady-state numerical simulations to identify resistance parameters. In this paper, the velocity response is solved by applying a force (or torque) to the underwater vehicle based on the overset grid and Dynamic Fluid-Body Interaction model of STAR-CCM+, solving for the velocity response of an underwater vehicle in all directions in response to propulsive force (or moment) inputs. Based on the data from numerical simulations, a parameter identification method using quantum particle swarm optimization is proposed to simultaneously identify inertia and resistance parameters. By comparing the forward velocity response curves obtained from pool experiments, the identified vehicle model’s mean square error of forward velocity is less than 0.20%, which is superior to the steady-state simulation method and particle swarm optimization and genetic algorithm approaches.

Blind parameter identification of implicit differential equations using the collocation discretization and homotopy optimization methods

In this paper, our objectives are to estimate the moments of inertia and reconstruct the inputs of a two-link pendulum that models a human arm. A blind parameter identification routine to determine the inertia properties of human limbs without input data based on a combination of collocation discretization and homotopy optimization is suggested. Without the input data, inertia parameters are structurally unidentifiable. Complementary equations in terms of the ratio of inertia parameters in the cost function and the rate of change of the inputs in the constraints are introduced to make the problem structurally identifiable. Numerous simulations are performed to validate our approach. Experiments to record human upper arm and forearm oscillatory movements were also performed, and moment of inertia terms were evaluated. The significance of the proposed method is that the method can be used to evaluate the moments of inertia of human body segments only from the experimental kinematic data. The advantages of the method are: numerical integration of dynamic and sensitivity equations is avoided and the record of the inputs to the system is not needed.

Effects of tennis racket swingweight on forehand speed and accuracy in youth players

ABSTRACT Few studies have analysed the effects of the racket inertial parameters on hitting performance in young tennis players. The research aims to study the relationship between the swingweight of the racket and speed and accuracy variables, in young tennis players. Twenty-six players (13.1 ± 2.94 years) performed a forehand hitting test with three rackets of different swingweight (low, medium, and high). Ball speed and hitting accuracy were calculated using a radar, Zepp2 sensor and photogrammetry. Significant differences were found in the ball speed measured by the Zepp2, with the racket with a low swingweight producing a higher speed (p < 0.05; Mean ± SD; 108 ± 43 vs. 102 ± 47 vs. 101 ± 49 km/h, for the racket with a low, medium, and high swingweight). In accuracy, there were significant differences in the absolute longitudinal error, being the racket of the low swingweight the most accurate (182 ± 49 cm vs. 215 ± 88 vs. 208 ± 72 cm; p < 0.05). Also, the low swingweight racket showed higher errors in the net. It is concluded that the lower swingweight racket generates the highest speed values while the error pattern is different between the different swingweights.

Heat transfer in a reversible esterification process of hydromagnetic Casson fluid with Arrhenius activation energy

Engineering technology is rapidly changing, and activation and binary chemical reactions have many uses in the fields of chemical engineering, processing food, and mobility and Geothermal reservoir, etc. Energy activation stimulates reactants with the least energy whenever a chemical transition occurs. The thermophysical features of viscoelastic fluids are based on internal energy change, which has been discussed for years. With this significance the current proposal focuses on the heat transfer process in reversible esterification reactions. The reversible chemical reaction and the activation energy with hydromagnetic movement of Casson fluid are considered. A complex multivariate partial differential equation set can be reduced to ordinary differential equations using appropriate variables. A numerical method is utilized to determine the solutions. In order to examine the outcomes of the concentration boundary layer utilizing the R-K-based shooting technique, the study primarily considers the reversible esterification process, which involves an ethanol-based reversible chemical reaction. Also, the bvp4c solver was employed to validate the results and appraise the precision of the R-K methodology. The temperature field, the momentum field, and the volumetric concentration of the esterification process are analysed in relation to a variety of numerical values. Graphical analysis considers the pertinent physical ramifications for temperature, velocity, and concentration contours. Explications that furnish a comprehension of the values accompany the tabular depictions of the heat transfer rate, local Sherwood number and skin friction. Reversible and irreversible flows differ considerably in the assessment of Sherwood number, local Nusselt number and rate of shear stress, when the inertial parameter, temperature difference parameter and activation energy are measured.

An innovative inertial parameters identification method for non-cooperative space targets based on electrostatic interaction

Inertial characteristics of non-cooperative targets are crucial for space capture and subsequent on-orbit servicing. Previous methods for identifying inertial parameters involve proximity operations, which are associated with the risk of collision with non-cooperative targets. This paper introduces a long-range, contactless method for identifying the inertial parameters of a non-cooperative target during the pre-capture phase. Specifically, electrostatic interaction is used as an external excitation to alter the target’s motion. A force estimation algorithm that uses measurements from visual and potential sensors is proposed to estimate the electrostatic interaction and eliminate the need for force sensors. Furthermore, a recursive estimation–identification framework is presented to concurrently estimate the coupled motion state, weak electrostatic interaction, and inertial parameters of the target. The simulation results show that the proposed method extends the identification distance to 170 times that of the previous method while maintaining high identification precision for all parameters.