Displacement Of Object Research Articles

From PIV to LSPIV: Harnessing deep learning for environmental flow velocimetry

The inference of velocity fields from the displacement of objects and/or fields visible within a series of consecutive images over known time intervals has been explored extensively within experimental fluid dynamics. Real image sequences of environmental hydrodynamic flows, however, pose additional challenges for velocity field inference due to factors such as lighting inhomogeneity, particle density, camera orientation and stability. Here we investigate the performance of classical and deep learning based velocity estimation methods on three experimental datasets; a hydrodynamics laboratory dataset of different flow types and two open-source datasets of aerial river footage from field campaigns. The river datasets are accompanied by observational datasets of in-situ measurements. In particular, we investigate the generalisation of deep learning based methods from ideal training conditions to real images. We consider three deep learning approaches; recurrent all-pairs-field transforms (RAFT), a physics-informed approach and an unsupervised learning approach (UnLiteFlowNet-PIV). Results indicate that RAFT, which achieves state-of-the-art performance on particle image datasets, showed good generalisation to the laboratory dataset and field imagery. The physics-informed approach performed similarly to RAFT across the laboratory dataset whilst generalisation to drone-based data proved challenging. Across the laboratory dataset, UnLiteFlowNet-PIV showed good performance within wake regions but an underestimation of channel flows and freestream regions with limited vorticity, also suffering under poor seeding density. Limited fine-tuning of UnLiteFlowNet-PIV on laboratory data, however, led to improved performance in these regions, indicating the potential of the unsupervised learning approach for environmental flows where 2D ground truth data sources are unavailable for training.

Analysis of the optical performance of intraocular lenses using profilometric measurements.

The aim of this study was to develop a methodology, based on profilometer measurements to assess the optical behaviour of Intraocular Lenses (IOls). The "Modulation Transfer Function through-object" (MTF through-object) based on vergence object displacement was calculated for different pupil sizes and pseudophakic eyes. Tilt and decentration were also analysed in a realistic cornea eye model. For comparison between the different IOLs, an optical quality criterion based on a minimum value the MTF through-object and the recognition of simulated vision optotypes was introduced. Five IOLs were used in this study: Tecnis Eyhance, Mini Well, Tecnis Symfony, Tecnis Synergy and RayOne EMV. The technique was validated with previous methodologies. A general narrowing of the through-object MTF curve compared to the through-focus MTF curve was shown, resulting in greater distances between near and intermediate points and less depth of field around the far peak. The comparison between the IOLs showed that variations in corneal aberrations, pupil size and decentration caused relevant changes in IOL performance. A decrease of the SA produced a hypermetropic shift of the far focus between + 0.3 D and + 0.4 D. Most of IOLs worsen the optical quality as pupil size increased, even the MTF through-object shape changed. Decentration was an important factor in IOL implantation, causing a significant change in MTF through-object shape in most of IOLs. This study highlights the need to evaluate pre-operative patients for corneal aberrations and pupillary size to have the best optical success after cataract surgery in multifocal or extended depth of focus IOLs. What is known MTF(Modulation Transfer Function)through-focus curves (calculated in image space by moving the detector plane) can be obtained from optical bench assembly or from commercial devices. Recently, some studies proposed to characterize the lens surface design based on the profilometric measurements What is new A novel methodology based on profilometer measurements to assess the optical behaviour of Intraocular Lenses (IOls) was shown. The "Modulation Transfer Function through-object" based on vergence object displacement was introduced in order to analyse five premium IOLs. MTF through-object curve is more appropriate for studying clinical behaviour, as it provides further near and intermediate points distances and lower depth of focus around far peak compare to MTF through-focus curves. The optical behaviour of the five IOLs can vary considerably depending on the eye model and pupil size. The effect of tilt and decentration on the MTF through-object the IOLs was analysed.

СПОСІБ ОЦІНКИ ЗМІЩЕННЯ ОБ'ЄКТІВ ЗА АНАЛІЗОМ ЗОБРАЖЕНЬ З КРУГОВИМ ГРАДІЄНТОМ КОЛЬОРУ У ЗАДАЧІ ВИМІРЮВАННЯ В ТЕХНІЧНИХ СИСТЕМАХ

The current stage of human development can be characterized as an incredibly large amount of information in the digital industry. Observing this, we can safely say that the digital industry has completely replaced and automated life and activities. As noted above, today there is a growing trend towards the full penetration of intelligent information technologies into all spheres of human activity, often accompanied by the use of various digital technical devices. One of the recent stable trends is the widespread use of imaging devices even in everyday life. At the same time, there is a growing need to determine the presence or absence of displacement of objects of observation. These circumstances create opportunities for solving this problem by comparing successive images, which allows not only to qualitatively assess the presence of displacement, but also to measure its magnitude. This approach makes it possible to solve measurement problems in technical systems. The key issue that determines the potential accuracy in a measurement task is the most accurate measurement of the position of the object of observation against the background of others. In general, the observer deals with a gradient change in color under both natural and artificial lighting conditions, and the task of determining the position of the object of observation is actually to analyze images with a circular color gradient.

Design and Experimental Study of a Cleaning Device for Edible Sunflower Harvesting

Existing cleaning devices for edible sunflower have a low cleaning efficiency, high cleaning loss rate, and high impurity rate; therefore, a wind-sieve-type cleaning device for edible sunflower harvesting was designed. According to the characteristics of dislodged objects, a vibrating screen for the device was designed, and the dislodged edible sunflower objects in the device were used for a mechanical analysis of the force conditions to determine the displacement of the different edible sunflower objects dislodged by the action of airflow. Using FLUENT-DEM gas–solid coupling simulation technology, the velocity of the flow field, the velocity vector, and the trajectory of the dislodged objects inside the cleaning device were analyzed, and the law of motion applied to the airflow and the dislodged objects inside the device was clarified. According to the results of the coupled simulation analysis, the key factors affecting the operation of the cleaning device were wind speed, vibration frequency, and amplitude. Based on the key factors of wind speed, vibration frequency, and amplitude, an orthogonal rotary combination test was carried out with the loss rate and impurity rate of cleaned grains as the evaluation indexes, and the test parameters were optimized to obtain the optimal combination of operating parameters of the device, which were as follows: wind speed: 30 m·s−1; vibration frequency: 8.44 Hz; and amplitude: 41.35 mm. With this combination of parameters, the seed loss rate and impurity rate reached 3.47% and 6.17%, respectively. Based on the optimal combination of operating parameters, a validation test was performed, and the results of this test were compared with the results of the test bench using this combination of parameters. The results show that the relative errors of the loss rate and impurity rate between the bench test and the simulation test were 3.45% and 3.07%, respectively, which are less than 5%, proving the reliability of the simulation analysis and the reasonableness of the design of the test bench.

Monolithically Integrated Michelson Interferometer Using an InGaAs/InAlAs Quantum Cascade Laser at λ = 4 µm

In the present article, we propose a monolithically integrated Michelson interferometer using a λ = 4 µm InGaAs/InAlAs quantum cascade laser as the light source. By using simple fringe detection and a four-point interpolation on each fringe, we will be able to detect minimal object displacements of 500 nm—corresponding to 25% of half the laser emission wavelength. Such an interferometric photonic integrated circuit has interesting applications for precision computerized numerical controlled machines. Since the industrial standard of such machines currently consists of glass-based linear encoders with a resolution of 5 µm, our interferometer-based system will enable an improvement of at least one order of magnitude.

Visuo-motor updating in individuals with heightened autistic traits

Autism spectrum disorder (ASD) presents a range of challenges, including heightened sensory sensitivities. Here, we examine the idea that sensory overload in ASD may be linked to issues with efference copy mechanisms, which predict the sensory outcomes of self-generated actions, such as eye movements. Efference copies play a vital role in maintaining visual and motor stability. Disrupted efference copies hinder precise predictions, leading to increased reliance on actual feedback and potential distortions in perceptions across eye movements. In our first experiment, we tested how well healthy individuals with varying levels of autistic traits updated their mental map after making eye movements. We found that those with more autistic traits had difficulty using information from their eye movements to update the spatial representation of their mental map, resulting in significant errors in object localization. In the second experiment, we looked at how participants perceived an object displacement after making eye movements. Using a trans-saccadic spatial updating task, we found that those with higher autism scores exhibited a greater bias, indicating under-compensation of eye movements and a failure to maintain spatial stability during saccades. Overall, our study underscores efference copy’s vital role in visuo-motor stability, aligning with Bayesian theories of autism, potentially informing interventions for improved action–perception integration in autism.

Visuo-motor updating in individuals with heightened autistic traits.

Autism spectrum disorder (ASD) presents a range of challenges, including heightened sensory sensitivities. Here, we examine the idea that sensory overload in ASD may be linked to issues with efference copy mechanisms, which predict the sensory outcomes of self-generated actions, such as eye movements. Efference copies play a vital role in maintaining visual and motor stability. Disrupted efference copies hinder precise predictions, leading to increased reliance on actual feedback and potential distortions in perceptions across eye movements. In our first experiment, we tested how well healthy individuals with varying levels of autistic traits updated their mental map after making eye movements. We found that those with more autistic traits had difficulty using information from their eye movements to update the spatial representation of their mental map, resulting in significant errors in object localization. In the second experiment, we looked at how participants perceived an object displacement after making eye movements. Using a trans-saccadic spatial updating task, we found that those with higher autism scores exhibited a greater bias, indicating under-compensation of eye movements and a failure to maintain spatial stability during saccades. Overall, our study underscores efference copy's vital role in visuo-motor stability, aligning with Bayesian theories of autism, potentially informing interventions for improved action-perception integration in autism.

Video-microscopy-based automated trajectory determination

We present a method for tracking densely clustered, high-velocity, indistinguishable objects being spawned at a high rate and moving in a directed force field using only object centroids as inputs and no other image information. The algorithm places minimal restrictions on the velocities or accelerations of the objects being tracked and uses a methodology based on a scoring function and a backtracking refinement process. This combination leads to successful tracking of hundreds of particles in challenging environments even when the displacement of the individual objects at successive times approaches the separation between neighboring objects in any one frame. We note that these cases can be particularly difficult to handle by existing methods. The performance of the algorithm is methodically examined by comparison to simulated trajectories, which vary the temporal and spatial densities, velocities, and accelerations of the objects in motion, as well as the signal/noise ratio. Also, we demonstrate its capability by analyzing data from experiments with superparamagnetic microspheres moving in an inhomogeneous magnetic field in aqueous buffer at room temperature. Our method should be widely applicable since trajectory determination problems are ubiquitous in video microscopy applications in biology, materials science, physics, and engineering.

Displacement Estimation via 3D-Printed RFID Sensors for Structural Health Monitoring: Leveraging Machine Learning and Photoluminescence to Overcome Data Gaps.

Monitoring object displacement is critical for structural health monitoring (SHM). Radio frequency identification (RFID) sensors can be used for this purpose. Using more sensors enhances displacement estimation accuracy, especially when it is realized through the use of machine learning (ML) algorithms for predicting the direction of arrival of the associated signals. Our research shows that ML algorithms, in conjunction with adequate RFID passive sensor data, can precisely evaluate azimuth angles. However, increasing the number of sensors can lead to gaps in the data, which typical numerical methods such as interpolation and imputation may not fully resolve. To overcome this challenge, we propose enhancing the sensitivity of 3D-printed passive RFID sensor arrays using a novel photoluminescence-based RF signal enhancement technique. This can boost received RF signal levels by 2 dB to 8 dB, depending on the propagation mode (near-field or far-field). Hence, it effectively mitigates the issue of missing data without necessitating changes in transmit power levels or the number of sensors. This approach, which enables remote shaping of radiation patterns via light, can herald new prospects in the development of smart antennas for various applications apart from SHM, such as biomedicine and aerospace.

An Unsupervised Scientific Machine Learning Algorithm for Approximating Displacement of Object in Mass-Spring-Damper Systems

An Unsupervised Scientific Machine Learning Algorithm for Approximating Displacement of Object in Mass-Spring-Damper Systems

SURFACE DISPLACEMENT MONITORING OF SUBURBAN EXPRESSWAY UNDER CONSTRUCTION BASED ON SENTINEL-1 SBAS-INSAR ANALYSIS

Abstract. The Synthetic Aperture Radar Interferometry (InSAR) technique can quickly obtain millimeter-level surface deformation in urban areas with high coherence. However, expanding the application of time series InSAR in non-urban areas is an important research focus. An improved SBAS-InSAR analysis approach is applied in this study to present the surface displacement along two expressways under construction. Taking the Kejiao and Yicheng Highway in the Shenzhen Shanwei Special Cooperation Zone as examples, the deformation along the highways under construction and the surrounding ground objects is revealed. Moreover, the time series displacements and construction conditions are combined to explain the possible mechanisms behind the different displacements of various ground objects along the expressways. The results show that the climate, environment, and construction conditions of the cooperation zone had an impact on the deformation of various ground objects along the route. Compared to traditional PS-InSAR methods, the density and accuracy of coherence points are improved, which better overcomes the spatiotemporal incoherence effects in non-urban areas.

Palmitoyl transferase zDHHCs: novel targets in Alzheimer’s disease

AbstractBackgroundGrowing evidence points to altered metabolic signals as a risk factor for Alzheimer’s disease (AD). The high fatty acid levels and brain insulin resistance (BIR) found in AD brains may impinge on protein S‐palmitoylation, which is a post‐translational modification critically involved in the regulation of neuronal protein localization and synaptic function. Our previous findings highlighted the critical role of aberrant palmitoylation in BIR‐dependent memory impairment (Spinelli et al., 2017).MethodWe analyzed both the expression of palmitoyl‐transferase enzymes (zDHHCs) in mouse AD brains and S‐palmitoylation levels of key proteins in human AD brains. We also tested the effect of chronic intranasal injection of the palmitoylation inhibitor 2‐bromopalmitate (2BP) on a large cohort of male and female 3xTg‐AD mice, starting from 3 months of age, by performing cognitive (novel object recognition and object displacement tests), electrophysiological (LTP), immunohistochemical (Abeta deposition) and molecular analyses (Abeta measurement by ELISA). Finally, we investigated the effects of lentiviral particles‐mediated zDHHC7 or zDHHC21 silencing in the hippocampus of 3xTg‐AD.ResultWe found increased levels of zDHHC7 and zDHHC21 in the hippocampus of 3xTg‐AD mice and aberrant palmitoylation of key enzymes triggering beta amyloid aggregation in human AD brains. 2BP delayed the onset of memory deficits in both male and female 3xTg‐AD mice. More importantly, 2BP significantly enhanced cognitive performances in 6‐, 9‐ and 12‐month‐old animals. Accordingly, electrophysiological analyses on hippocampal brain slices from 2BP‐treated 3xTg‐AD mice revealed greater long‐term potentiation at CA3‐CA1 synapses. In addition, both 2BP‐treated male and female mice showed lower Abeta deposition in hippocampus and a significant extension of lifespan. Finally, genetic inhibition of palmitoyl transferase zDHHC7 reverted the aberrant palmitoylation of proteins involved in synaptic plasticity and APP metabolism, and counteracted the onset of neurodegeneration and cognitive deficits in 3xTg‐AD mice.ConclusionThis is the first preclinical study on the effect of 2BP treatment on AD‐related cognitive decline. Our data indicate that aberrant palmitoylation plays a critical role in the onset and progression of AD and unveil the potential druggable role of zDHHC enzymes in dementia‐related neurodegenerative disorders.

Estimation of the sensitivity of optical measurements using a holographic interferometer

Various interferometers used for high-precision spectroscopic measurements are considered, and the choice of a holographic interferometer based on the spatial-spectral method of holographic interferometry is justified, with the help of which the movements of the phase center of a coherent light flux in a wide dynamic range are measured in real time and measurement information is recorded digitally. On the basis of mathematical relations proposed by the authors in previous publications and based on the results of experimental studies, the sensitivity of a holographic interferometer to spatial displacements of phase centers (focus points) of light streams – point light sources forming a holographic interferogram is numerically estimated. The dependence of the level of the normalized intensity of the luminous flux in the central region of the holographic interferogram on the movement of the actual point light source along the normal to the plane of the Fourier hologram is established. Based on the results of mathematical modeling, it is shown that the sensitivity of the holographic interferometer to the movements of a real point light source along the normal to the plane of the Fourier hologram depends on the parameters of the optical scheme of the holographic interferometer when exposing the hologram and during measurements. At the same time, the sensitivity of the holographic interferometer to the indicated displacements of a real point light source can only be evaluated experimentally. It is proposed to increase the sensitivity of the holographic interferometer by using a thin collecting lens in its optical scheme. For the first time, a mathematical relation was obtained and investigated for the gain coefficient of the light flux phase with a spherical wavefront, which makes it possible to numerically estimate the increase in sensitivity of a holographic interferometer implementing the spatial-spectral method of holographic interferometry with known parameters of a thin collecting lens in an optical scheme. It is shown that the sensitivity of a holographic interferometer to the movements of an imaginary point light source along the normal to the plane of the Fourier hologram is 2.86 times greater than its sensitivity to the same movements of a real point light source. It is established that the sensitivity of a holographic interferometer with a volumetric Fourier hologram and a thin collecting lens in its design can be increased by at least an order of magnitude compared to the sensitivity of known optical interferometers. The results of assessing the sensitivity of a holographic interferometer implementing the spatial-spectral method of holographic interferometry to the movements of point sources of real and imaginary light fluxes, as well as the obtained ratio for the gain of the light flux phase gain by a thin collecting lens will be useful for high-precision measurements of linear and angular displacements of objects, as well as for the construction of photonic device designs. Based on the results of the study, an experimental sample of an acousto-electric converter was developed and manufactured on the basis of a holographic interferometer, which has high sensitivity in wide dynamic and frequency ranges and is intended for use in acoustic location of unmanned aerial vehicles.

Exendin-4 Prevents Memory Loss and Neuronal Death in Rats with Sporadic Alzheimer-Like Disease.

This study investigated the neuroprotective effects of exendin-4 (EXE-4), an analog of the glucagon-like peptide 1 receptor (GLP-1R) on memory and on the neuronal populations that constitute the hippocampus of rats submitted to a sporadic dementia of Alzheimer's type (SDAT). Male Wistar rats received streptozotocin (STZ icv, 3mg/kg diluted in aCFS, 5µl/ventricle) and were treated for 21days with EXE-4 (10µg/kg, ip; saline as the vehicle). Four groups were formed: vehicle, EXE-4, STZ, and STZ + EXE-4. The groups were submitted to Y-Maze (YM), object recognition (ORT), and object displacement tasks (ODT) to assess learning and memory. The brains were used for immunohistochemical and immunofluorescent techniques with antibodies to NeuN, cleaved caspase-3 (CC3), PCNA, doublecortin (DCX), synaptophysin (SYP), and insulin receptor (IR). STZ worsened spatial memory in the YMT, as well as short-term (STM) and long-term (LTM) memories in the ORT and ODT, respectively. EXE-4 protected against memory impairment in STZ animals. STZ reduced mature neuron density (NeuN) and increased cell apoptosis (CC3) in the DG, CA1, and CA3. EXE-4 protected against neuronal death in all regions. EXE-4 increased PCNA+ cells in all regions of the hippocampus, and STZ attenuated this effect. STZ reduced neurogenesis in DG per se as well as synaptogenesis induced by EXE-4. EXE-4 increased immunoreactivity to IR in the CA1. From these findings, EXE-4 showed a beneficial effect on hippocampal pyramidal and granular neurons in the SDAT showing anti-apoptotic properties and promoting cell proliferation. In parallel, EXE-4 preserved the memory of SDAT rats. EXE-4 appears to enhance synapses at CA3 and DG. In conclusion, these data indicate that agonists to GLP-1R have a beneficial effect on hippocampal neurons in AD.

Modeling the short wavelength infrared laser radiance reflection on the sea surface.

The sea surface is a complex dynamic structure dependent on atmospheric conditions, and for which physical and chemical properties change from water to foam. Its roughness determines how the surface reflects, absorbs, and emits radiance, and depends on multiple parameters such as wind speed and direction, and foam and turbulence induced from natural waves or from object displacement. In this paper, a model description is given for laser reflection on the sea surface in open water driven by the wind. The model allows calculation of the reflected laser radiance from the sea surface toward a receiver as a function of the incoming laser radiance with a known beam intensity profile. Each subarea of the sea surface seen by one pixel of the receiver is considered as an ensemble of facets, where each facet is defined by its x and y directional slopes. The wind speed and orientation determine the probability density function of the sea surface facet slope occurrence. In this paper, we have analytically expressed the reflected radiance on the sea surface as a function of the wind speed, receiver range, receiver heading, laser position, laser output aperture, and laser incoming radiance. Using the tolerance ellipse, the reflected radiance expression was approximated, and both direct and approximated results were compared. The richness in behavior of the reflected radiance and its dependence on the geometry of the problem were studied showing the impact of the receiver position, the laser position, heading, and beam divergence.

Thinking on your feet: Anticipatory foot placements in repeated bimanual object displacements

Effective handling of objects requires proper use of the hands. If the object handling is done while standing or walking, it also requires proper use of the feet. We asked how people position their feet to meet future and ongoing object-handling demands. In previous research on this topic, participants walked to a table and picked up an object for a single displacement from one place to another. These studies shed light on sensitivity to kinematics but, strictly speaking, may not have revealed anything about sensitivity to dynamics. In the present study, we asked participants to walk to a table to move an object back and forth over different distances and at different rates. Prior to walking to the table, participants had full knowledge of what the task would be. By using a rhythmic rather than discrete object placement task, we could analyze participants' sensitivity to dynamics as well as kinematics. Consistent with our expectation that participants would tune their foot separations to demands related to dynamics, we found that stance width was wider for long than for short object displacements and was more pronounced for high displacement rates than for low displacement rates. Also consistent with our expectations about planning, these effects were evident as soon as participants reached the table. Our results add to the limited research on coordinated action of the hands and feet in purposeful object manipulation.

Using the LSTM Neural Network and the UWB Positioning System to Predict the Position of Low and High Speed Moving Objects.

Automation of transportation will play a crucial role in the future when people driving vehicles will be replaced by autonomous systems. Currently, the positioning systems are not used alone but are combined in order to create cooperative positioning systems. The ultra-wideband (UWB) system is an excellent alternative to the global positioning system (GPS) in a limited area but has some drawbacks. Despite many advantages of various object positioning systems, none is free from the problem of object displacement during measurement (data acquisition), which affects positioning accuracy. In addition, temporarily missing data from the absolute positioning system can lead to dangerous situations. Moreover, data pre-processing is unavoidable and takes some time, affecting additionally the object's displacement in relation to its previous position and its starting point of the new positioning process. So, the prediction of the position of an object is necessary to minimize the time when the position is unknown or out of date, especially when the object is moving at high speed and the position update rate is low. This article proposes using the long short-term memory (LSTM) artificial neural network to predict objects' positions based on historical data from the UWB system and inertial navigation. The proposed solution creates a reliable positioning system that predicts 10 positions of low and high-speed moving objects with an error below 10 cm. Position prediction allows detection of possible collisions-the intersection of the trajectories of moving objects.

Signal processing and acoustic calibration method of millimeter-wave vibration sensor

Millimeter-wave sensors can be utilized as non-contact vibration sensors. Applications of millimeter-wave vibration sensors are the vital sensing of humans (heartbeat, respiration, body motion), factory machines, and vibration sensing of social infrastructures, such as buildings and bridges. Millimeter-wave vibration sensors can simultaneously detect the position and the waveforms of the vibration displacements of vibration objects. The primary signal processing of millimeter-wave sensors is two-dimensional fast Fourier transform (2D-FFT), detecting the arrival direction (DOA) and processing the micro-Doppler signals. The detectable areas of the millimeter-wave vibration sensors are defined using the parameters related to these three signal-processing blocks. Measured vibration waveforms by millimeter-wave vibration sensors include all components of the vibration displacements in the defined detectable area. Therefore, the waveform of the vibration displacement is influenced by the definition of the detectable area and the vibration form of the vibrating object. The measured values of millimeter-wave vibration sensors must be calibrated with attention to these influences. The vibration waveforms of vibrating objects are estimated by acoustic measuring methods, such as the laser Doppler vibrometer and the parallel-phase shifting interferometry. This paper describes calibration methods of millimeter-wave vibration sensors employing these two measuring methods.

Design and Frame Strength Evaluation of Salt Washing Unit Capacity 50 Kg/hour

The salt washing unit is part of the salt processing machine. This unit's function is to wash raw salt with brine. This unit has a motor, agitator blade, washing chamber, and frame. The frame structure strength of the salt washing unit needs to be evaluated to ensure safety. This research aims to design the salt washing unit and obtain simulation results of frame structure strength to ensure the safety of the salt washing unit. This research was carried out by simulation to look for stress, strain, and changes in the shape of objects (displacement). The frame strength simulation was carried out using Solidwork software. The salt washing unit with a 50 kg/hour capacity has been designed. It has a cylindrical shape with 990 mm in height and 680 mm in diameter. From the simulation results of strain, it can be concluded that the minimum point is 1.80 × 108 Mpa, and the maximum point is 1.63 × 105 Mpa. From the simulation results of displacement, it can be concluded that the minimum point is 0 mm and the maximum point is 2,296 mm. The maximum stress is 5.254×106 N/m2, and the minimum stress point is 1.803×106 N/m2.

EXAMINATION OF ANALYSIS METHOD FOR HYDRAULIC MODEL EXPERIMENT UTILIZING RGBD IMAGES AND DUALSPHYSICS

Reconstruction method of real objects into point cloud based on RGB images and Depth images (RGB-D Images) has been adopted in various fields. By utilizing such reconstruction method, it would be possible to efficiently measure the complex shape of objects, such as tetrapods, without directly contacting to them in the real experiment. However, the measurements of three-dimensional (3D) objects have rarely been used in hydrodynamic experiments. In the present study, the methodology was built to carry out hydraulic experiments and numerical simulations focusing on the displacement of complex objects. It was carried out by combining reconstructed 3D point cloud data acquired from Intel RealSense LiDAR Camera L515 (L515) and DualSPHysics. The result of displacement of the objects was investigated by numerical simulation and hydrodynamic experiments.