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In this study, methods for automatically controlling load transportation by a swivel crane with high speed and suppressed swing motion of suspended load at the target position are proposed. First, highly versatile trajectories for each of swivel and straight transport of load are proposed on the basis of a linearized and simplified analytical model and the optimal control theory. The proposed method has the versatility that it can be applied even with different swivel radii and swivel angles. The effectiveness and limitations of the proposed methods are shown with computer simulations and experiments with a laboratory model. Next, we propose a new method that expands the proposed method and uses the measurement data of the swing information of the load. It is shown that by using this method, even if the load swings at the start of transport, it is possible to suppress the swing of the load at the target point of transport.

Many mechanical systems such as vehicles, robots and space structures are comprised of a lot of interconnected components. The motion of the components is constrained because of mechanical joints or specified motion trajectories. Multibody dynamics is one of effective methods to analyze nonlinear dynamic behavior for such systems. On the other hand, it is quite difficult to obtain all parameters required for numerical simulation by only direct measurement in complex mechanical systems. Therefore, parameter estimation and identification techniques are crucial for simulation in practical problems. This study aims to develop a parameter estimation technique based on the adjoint method which can be applied to mathematical models used in the multibody dynamics, namely, differential algebraic equations. In addition, a feature extraction technique based on the proper orthogonal decomposition is incorporated into the parameter estimation method in order to evaluate effect of model uncertainties on an accuracy of the parameter estimation, because the joint components often involve model uncertainties due to inherent physical characteristics such as friction, contact and so on. The validity of the present method is discussed by numerical experiments using the rigid multibody systems.

Vibration is one of the significant problems in crane operation. In the rotary crane, the boom is a flexible structure. The vibration in this crane is occurred at the boom and the hoisted load. This research proposed a control strategy for designing the optimal trajectory of the rotary crane with a flexible boom, which can suppress the vibration in the mechanism. In the proposed approach, the simplified dynamics model of the flexible rotary crane was introduced for designing the control trajectory. The boom’s flexibility was modeled with mass-spring systems. The constant-velocity access control method and the point-to-point access control method were used to design the vibrationless trajectory. To estimate the efficiency of the proposed model, the numerical simulation and experiment on the laboratory-scale flexible crane were conducted to measure the motion of the boom tip and hoisted load. The results were compared with those from the vibration control model that did not include the boom’s flexibility. The simulation and experiment results illustrated that the proposed control model with the flexibility of boom was able to suppress the vibration of both boom and hoisted load. Furthermore, the proposed model showed a better vibration suppression than the model that neglected the boom’s flexibility when the crane was driven at high acceleration.

Simulating the brain-body-environment trinity in closed loop is an attractive proposal to investigate how perception, motor activity and interactions with the environment shape brain activity, and vice versa. The relevance of this embodied approach, however, hinges entirely on the modeled complexity of the various simulated phenomena. In this article, we introduce a software framework that is capable of simulating large-scale, biologically realistic networks of spiking neurons embodied in a biomechanically accurate musculoskeletal system that interacts with a physically realistic virtual environment. We deploy this framework on the high performance computing resources of the EBRAINS research infrastructure and we investigate the scaling performance by distributing computation across an increasing number of interconnected compute nodes. Our architecture is based on requested compute nodes as well as persistent virtual machines; this provides a high-performance simulation environment that is accessible to multi-domain users without expert knowledge, with a view to enable users to instantiate and control simulations at custom scale via a web-based graphical user interface. Our simulation environment, entirely open source, is based on the Neurorobotics Platform developed in the context of the Human Brain Project, and the NEST simulator. We characterize the capabilities of our parallelized architecture for large-scale embodied brain simulations through two benchmark experiments, by investigating the effects of scaling compute resources on performance defined in terms of experiment runtime, brain instantiation and simulation time. The first benchmark is based on a large-scale balanced network, while the second one is a multi-region embodied brain simulation consisting of more than a million neurons and a billion synapses. Both benchmarks clearly show how scaling compute resources improves the aforementioned performance metrics in a near-linear fashion. The second benchmark in particular is indicative of both the potential and limitations of a highly distributed simulation in terms of a trade-off between computation speed and resource cost. Our simulation architecture is being prepared to be accessible for everyone as an EBRAINS service, thereby offering a community-wide tool with a unique workflow that should provide momentum to the investigation of closed-loop embodiment within the computational neuroscience community.

Computer simulation of the human brain at an individual neuron resolution is an ultimate goal of computational neuroscience. The Japanese flagship supercomputer, K, provides unprecedented computational capability toward this goal. The cerebellum contains 80% of the neurons in the whole brain. Therefore, computer simulation of the human-scale cerebellum will be a challenge for modern supercomputers. In this study, we built a human-scale spiking network model of the cerebellum, composed of 68 billion spiking neurons, on the K computer. As a benchmark, we performed a computer simulation of a cerebellum-dependent eye movement task known as the optokinetic response. We succeeded in reproducing plausible neuronal activity patterns that are observed experimentally in animals. The model was built on dedicated neural network simulation software called MONET (Millefeuille-like Organization NEural neTwork), which calculates layered sheet types of neural networks with parallelization by tile partitioning. To examine the scalability of the MONET simulator, we repeatedly performed simulations while changing the number of compute nodes from 1,024 to 82,944 and measured the computational time. We observed a good weak-scaling property for our cerebellar network model. Using all 82,944 nodes, we succeeded in simulating a human-scale cerebellum for the first time, although the simulation was 578 times slower than the wall clock time. These results suggest that the K computer is already capable of creating a simulation of a human-scale cerebellar model with the aid of the MONET simulator.

One of the grand challenges for computational neuroscience and high-performance computing is computer simulation of a human-scale whole brain model with spiking neurons and synaptic plasticity using supercomputers. To achieve such a simulation, the target network model must be partitioned onto a number of computational nodes, and the sub-network models are executed in parallel while communicating spike information across different nodes. However, it remains unclear how the target network model should be partitioned for efficient computing on next generation of supercomputers. Specifically, reducing the communication of spike information across compute nodes is essential, because of the relatively slower network performance than processor and memory. From the viewpoint of biological features, the cerebral cortex and cerebellum contain 99% of neurons and synapses and form layered sheet structures. Therefore, an efficient method to split the network should exploit the layered sheet structures. In this study, we indicate that a tile partitioning method leads to efficient communication. To demonstrate it, a simulation software called MONET (Millefeuille-like Organization NEural neTwork simulator) that partitions a network model as described above was developed. The MONET simulator was implemented on the Japanese flagship supercomputer K, which is composed of 82,944 computational nodes. We examined a performance of calculation, communication and memory consumption in the tile partitioning method for a cortical model with realistic anatomical and physiological parameters. The result showed that the tile partitioning method drastically reduced communication data amount by replacing network communication with DRAM access and sharing the communication data with neighboring neurons. We confirmed the scalability and efficiency of the tile partitioning method on up to 63,504 compute nodes of the K computer for the cortical model. In the companion paper by Yamaura et al., the performance for a cerebellar model was examined. These results suggest that the tile partitioning method will have advantage for a human-scale whole-brain simulation on exascale computers.

In this paper, we analyze the behavior of the chain by the analytical method of the multibody dynamics. For this system, there are two problems in the conventional method. One is the description of rotation for the rigid body. It leads to high nonlinearity and singularity caused by rotation. The other is the calculation efficiency due to the degree of freedom increases. In this research, in order to solve these problems, we introduces ”Rotation update equation”, which uses an incremental rotation for describing rotation matrix. This method doesn’t use the rotation angle in the equation, therefore the problems are mentioned improved. It can also reduce the calculation time, too. Moreover, this study introduces the normalization of the equation of rotation with the time step. It enables us to reduce the times of iteration procedure. This research compares the calculation results by the proroposed method with the results obtained from the experiment using the ball chain. Furthermore, we compare the experimental result and the analysis result by constructing an experimental equipment. From the above, we verified the validity of the proposed method.

This research studied an influence of the inertia of the hoisting rope on the dynamics of a mobile crane system. Two dynamics models of the mobile crane were formulated with the inertia included rope model and the massless rope model, and their dynamics response were compared. The floating frame of reference formulation was used in formulating the model of the deformable components. In the simulations, we variated the length of the rope and the mass of the hoisted load then applied the slewing motion to the boom for 10 seconds and let the system underwent free vibration for another 10 seconds while the boom angle was fixed. The deformation of the rope and the comparison of the hoisted load motion between two models were considered. The results illustrated that the rope model with included inertia was able to illustrated its bending during the crane operation and this deformation increased with the length of rope. It appeared that the deformation of the boom tip had influences on the deformation of the rope. In the motion of the hoisted load, the time - history data illustrated that the inertia included rope model had slightly higher frequency than the massless rope model during the free motion, and the trajectory also showed the slightly larger sway. In addition, the total calculation time of the inertia included rope model was around 13 times longer. The difference in the motion of the hoisted load from both models increased with the length of rope but decreased when the mass of load increased. In conclusion, the model with included inertia of rope showed different response to the massless rope model at long rope and light load condition, and this difference was decreased at short rope and heavy load condition.

The purpose of this study was to investigate vibrations suppression control methods of image transfer belt system which is widely applied in image formation procedure of printers and copy machines. The study focused on vibrations caused by loading torque of printing mediums when they were delivered into the machinery. The system was modelled as a four-rollers-belt with a stepper motor based on exist apparatus. Equations of motion and vibration of the four-rollers-belt system were established. Two types of description about the vibrations in the image forming part of belt, stretching displacement and absolute displacement were defined and selected as main inhibited quantities. Impacts on the two quantities by several parameters of the system, including Young's modulus of belt, rotational stiffness of motor coupling were studied. Additional flywheels and dynamic absorbers were used to improve the system performance, and an evaluation function was defined to estimate the effects. The results indicated that the two devices reduced the two displacements, and the outcomes varied as different attached locations and moment of inertia. It confirmed that by adding a flywheel with large inertia on burden roller, or a dynamic vibration absorber on drive roller could achieve better suppression results.

The cerebellum plays a fundamental, but as yet poorly understood, role in the control of locomotion. Recently, mice with gene mutations or knockouts have been used to investigate various aspects of cerebellar function with regard to locomotion. Although many of the mutant mice exhibit severe gait ataxia, kinematic analyses of limb movements have been performed in only a few cases. Here, we investigated locomotion in ho15J mice that have a mutation of the δ2 glutamate receptor. The cerebellum of ho15J mice shows a severe reduction in the number of parallel fiber-Purkinje synapses compared with wild-type mice. Analysis of hindlimb kinematics during treadmill locomotion showed abnormal hindlimb movements characterized by excessive toe elevation during the swing phase, and by severe hyperflexion of the ankles in ho15J mice. The great trochanter heights in ho15J mice were lower than in wild-type mice throughout the step cycle. However, there were no significant differences in various temporal parameters between ho15J and wild-type mice. We suggest that dysfunction of the cerebellar neuronal circuits underlies the observed characteristic kinematic abnormality of hindlimb movements during locomotion of ho15J mice.

Disc brake squeal refers to the high-frequency noise caused by self-excited vibration induced by the friction force between discs and pads. It has received considerable attention over decades, as customers have come to increasingly demand less noise, vibration and harshness of vehicles. The vibration of the disc, which is considered to be one of the main sources triggering squeal, is classified as either inplane (IP) or out-of-plane (OP). Substantial effort has been made to investigate and mitigate the squeal induced by the OP vibration of the disc. Meanwhile, there is still no effective remedy for the squeal related to the disc IP vibration, despite numerous investigations have been made to suppress it. Consequently, this paper focuses on the disc IP vibration related squeal. A squeal experiment which is developed for measuring and recording squeal signals is introduced. The squeal signals include acoustic signals of squeal and acceleration signals of main components in a disc brake system. Furthermore, natural frequencies of the main brake components are confirmed using experimental modal analysis. General time-frequency-energy characteristics of the squeal signals are first presented by using results of basic Fourier transform-based signal processing methods. Subsequently, more detailed frequency and energy features of those non-stationary and nonlinear squeal signals are illustrated based on decomposition results of the ensemble empirical mode decomposition and the Hilbert transform. The resultant figures indicate that the recorded high-frequency squeal is mainly caused by the disc IP circumference vibration. Furthermore, it is inferred that the lower frequency component (with higher energy), which becomes the predominant component of the squeal phenomenon, is induced by the higher frequency component (with lower energy generated) firstly. [ABSTRACT FROM AUTHOR]

Abstract A hydrodynamic bearing is widely used for hard disk drives, and it is better than a ball bearing in terms of vibration suppression, noise reduction and shock resistance. However, its cost to performance ratio should be further improved. In this study we analyzed the stability of a disk-spindle assembly supported by a hydrodynamic plain journal bearing and a pivot bearing at the bottom of the shaft. As a result, we found that a half-frequency whirl of a vertical spindle caused by the plain journal bearing becomes stable if the gyro factor of the rotor is larger than 0.5. We examined the effects of the bearing design parameters on the stability of the disk-spindle assembly, including the flexibility of the shaft. We also compared the stability of a disk-spindle assembly supported by two plain journal bearings and found that the vertical spindle is always unstable. Thus, the bottom end of the shaft should be supported as a fulcrum. [ABSTRACT FROM AUTHOR]

The autofluorescence of mitochondrial flavoprotein is very useful for functional brain imaging because the fluorescence intensity of flavoprotein changes as per neural activities. In this study, we developed an implantable imaging device for green fluorescence imaging and detected fluorescence changes of flavoprotein associated with visual stimulation using the device. We examined the device performance using anesthetized mice. We set the device on the visual cortex and measured fluorescence changes of flavoprotein in response to visual stimulation. A full-field sinusoidal grating with a vertical orientation was used for applying to activate the visual cortex. We successfully observed visually evoked fluorescence changes in the mouse visual cortex using our implantable device. This result suggests that we can observe the fluorescence changes of flavoprotein associated with visual stimulation in a freely moving mouse by using this technology. [ABSTRACT FROM AUTHOR]