Computer Simulation Experiments Research Articles

Real-Time Wind Field Estimation and Pitot Tube Calibration Using an Extended Kalman Filter

The airspeed is an important feedback signal for flight control, and its measurement accuracy is related to the safety of aircraft, especially for hybrid vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAV) in the transition phase. However, offline calibration of the pitot tube cannot fully simulate the situation in real cases, and this is why online calibration after installation is necessary. In addition, the environmental wind field creates a high risk for the conversion flight of a hybrid UAV, thus real-time wind field measurement of the flight field has great significance for the flight path planning of the conversion process. In this article, an innovative method for online calibration of pitot tube and wind field estimation is proposed. After establishing the extended Kalman filter (EKF) for estimation, an analysis method is proposed to analyze the observability of EKF under different flight strategies. Then, the hovering flight is selected as the experimental flight trajectory. The laboratory computer simulation and flight experiment results validate the theory and prove that the proposed method could re-calibrate the scale factor of the pitot tube and estimate the wind field.

Airborne Ground Penetrating Radar, Field Test

Deployment of a ground penetrating radar (GPR) on a flying machine allows one to substantially extend the application area of this geophysical method and to simplify carrying out large surveys of dangerous and hard-to-reach terrain, where usual ground-based methods are hardly applied. There is a necessity to promote investigations in this direction by modifying hardware characteristics and developing specific proceeding algorithms. For this purpose, we upgraded commercial ground-based subsurface sounding hardware and performed corresponding computer simulation and real experiments. Finally, the first experimental flights were done with the constructed GPR prototype mounted on a helicopter. Using our experience in the development of ground-based GPR and the results of numerical simulations, an appropriate configuration of antennas and their placing on the flying machine were chosen. Computer modeling allowed us to select an optimal resistive loading of transmitter and receiver dipoles; calculate radiation patterns on fixed frequencies; analyze the efficiency of different conductor diameters in antenna circuit; calculate cross-coupling of transmitting and receiving antennas with the helicopter. Preliminary laboratory experiments to check the efficiency of the designed system were performed on an urban building site, using a tower crane with the horizontal jib to operate the measuring system in the air above the ground area to be sounded. Both signals from the surface and subsurface objects were recorded. To interpret the results, numerical modeling was carried out. A two-dimensional model of our experiment was simulated, it matches well the experimental data. Laboratory experiments provided an opportunity to estimate the level of spurious reflections from the external objects, which helps to recognize weak signals from subsurface objects in GPR surveys under live conditions.

A smart path planner for wheeled mobile robots using adaptive particle swarm optimization

Finding the shortest path to the destination is a vital need for autonomous mobile robots. In this article, a smart adaptive particle swarm optimization (APSO) algorithm is proposed for robot path planning. It allows the robot to reach the target point with the shortest possible path and to avoid the obstacles safely in uncertain environments. A new objective function is derived with distance function and a path smoothening parameter is integrated to avoid sharp turns. The results of the proposed method rely on computer simulation and real robot experimentation in different environments. It is proved that they are in good agreement. A comparative study between the proposed algorithm and various other algorithms is also presented. The results showed that the proposed smart algorithm is capable of successfully avoiding various types of obstacles including the local minima situation.

Hydrogen–helium chemical and nuclear galaxy collision: Hydrodynamic simulations on AVX-512 supercomputers

A computational hydrodynamic model of interacting galaxies is presented. The interstellar medium (ISM) is described by a model of gravitational multicomponent single-velocity hydrodynamics. A model based on first moments of the collisionless Boltzmann equation is used to describe the stellar component and dark matter. Subgrid processes of star formation and supernovae feedback, as well as cooling and heating functions are added to the hydrodynamic model. The computational model includes chemical and nuclear reactions of the basic forms of hydrogen and helium before the formation of the helium hydride ion. The hydrodynamic equations have a suitable form for solving by a unified computational method based on the “Harten – Lax – van Leer” (HLL) method. The equations and the numerical method are written in vector form to use advanced vector extensions AVX-512 to speed up the calculations. A parallel implementation of the model and some computational simulation experiments on the chemical dynamics of interacting galaxies are presented.

Quantitative phase microscopy imaging based on fractional spiral phase plate

Quantitative phase imaging (QPI), which combines phase imaging with optical microscopy technology, provides a marker-free, fast, non-destructive, and high-resolution imaging method for observing transparent biological samples. It is widely used in life science, biomedicine, etc. As an emerging QPI technology, spiral phase contrast microscopy (SPCM) uses a spiral phase filter to achieve edge enhancement of amplitude or phase objects. Using the multi-step phase-shifting technology, a complex sample can be measured quantitatively, which has the advantages of high stability, high sensitivity and high precision. However, the SPCM requires at least three-step phase-shifted spiral phase filtered images to achieve the quantitative reconstruction of the amplitude and phase of a sample, and the image acquisition process and the reconstruction process are relatively complicated, which require high stability of system, and the SPCM has low temporal resolution. In order to further improve the performance of SPCM and increase the system stability, sensitivity and temporal resolution, in this paper a quantitative phase imaging method and system based on a fractional spiral phase plate is proposed. Through a sample intensity image filtered by a fractional spiral phase plate, the modified Gerchberg-Saxton iterative phase retrieval algorithm is used to quantitatively reconstruct the phase of a pure phase sample, which simplifies the experimental process and phase reconstruction steps of spiral phase contrast microsocopy. In the computer simulation experiments, the phase imaging process and the reconstruction process of spiral phase plates based on different topological charges are studied, the feasibility of which is analyzed. Finally, through imaging and phase reconstruction of the phase grating and biological cell sample, it is verified that the phase contrast microscopy method based on the fractional spiral phase plate can effectively improve the contrast of spiral phase contrast microscopy and can obtain a quantitative reconstruciton of a weak phase object. The phase information of a sample has significance in research and application for developing the spiral phase contrast microscopy.

Improved Particle Swarm Optimization Algorithm Based on Dynamic Change Speed Attenuation Factor and Inertia Weight Factor

Compared with other optimization algorithms, the particle swarm optimization algorithm (pso) has the advantages of fast convergence, simple calculation, and fewer parameters to be adjusted. Therefore, it has been greatly developed in the past period of time. In order to further accelerate convergence, in recent years, more efficient and convenient particle swarm optimization algorithms such as LDWPSO, NLPSO, and DPSO have been proposed.However, these algorithms have many problems such as large amount of calculation, lack of precision, and easy to fall into local optimum.Therefore, the algorithm still needs to be improved. In order to obtain an efficient global search ability early in the algorithm iteration and better local optimization performance in the later stage of the algorithm iteration, this paper proposes a special expression form of dynamic change speed attenuation factor and inertia weight factor, and in the algorithm some random parameters are added to the iterative formula and applied to the algorithm iteration formula to improve the optimization speed and optimization effect of the algorithm.Finally, the effectiveness and correctness of the algorithm are also demonstrated by computer simulation experiments.

Iterative learning control of an inverse novel ball screw transmission system

Iterative Learning Control is a branch of intelligent control which combines artificial intelligence and control theory. This objective of this study aims at reducing the cyclic error of an inverse ball screw transmission system by using iterative learning control approach. Firstly, kinematic and dynamic analyses are conducted by using the vectorial loop closure and Lagrange equations, respectively. Then, system identification is performed followed by controller design. Moreover, controller parameters are optimized to minimize the error. Finally, the feasibility and the effectiveness of the proposed approach are verified by computer simulation and prototype experiment. The experimental results showed that the reducing percentage of the square error sum of the output speed is 90.64% by using PID control only. If ILC is applied additionally, the error is further reduced to 94.21%. Therefore, the proposed approach is not only feasible and but also effective.

Time Delay Estimation Method Used Median Filter in Low Signal to Noise Ratio Pulse Environment

In practice, the collected signal often contains impulsive noise. The classical time delay estimation algorithm based on the second-order statistics of Gaussian distribution will degrade or even be unreliable, so that it cannot be used. Although the fractional low-order signal processing method can be better adapted to signal processing in the impulse noise environment, the determination of the order p value of the fractional low-order moment depends on the prior knowledge or estimation of the characteristic index α value of the pulse, and when the pulse is stronger or the signal-to-noise ratio is low, the performance cannot meet the requirements well. The paper adopted the method of median filter preprocessing. First, the abnormal points (pulse points) are removed in the noise and return the noise to the Gaussian model distribution; next, use the time delay estimation algorithm under the second-order statistics to avoid the estimate of p-value. Computer simulation experiments show that the method proposed in this paper has better estimation performance in low snr pulse environment.

Research Method for Management of Thermoplastics Production Improvement in Rubber Industry with the Use of 3D Simulation Modeling

Abstract The paper concerns research and improvement of production processes in one of the European companies in the rubber industry The company did not allow the name or country to be given. . The main goal is to improve the production process of the thermo-plastics obtained from polymer materials on the company's production line. Improvement is defined as a reduction of the setup time of a key machine in the tested production process. The research method includes the analysis of the literature, observation of the studied process, and the accomplished computer simulation experiments. The proposed activities relate to the reinforcement of the key part of the machine, the change of the machine setup method, and the preliminary staff assignment to the specific tasks. The results of the simulation experiments confirm the implementation of the proposed improvements. The theoretical contribution to the research field development is the proposal of the simulation modeling methodology to improve production processes of continuous materials. Practical conclusions lead to recommendations for the implementation of improvements in the enterprise, with direct application of the proposed actions.

Highway Concrete Guardrail Lifting Scheme and Safety Performance Verification

In order to achieve the old fence of reuse, improve the safety performance of guardrail, barrier structure does not meet the requirements, make full use of the old concrete guardrail on the basis of heightening, through computer simulation experiment were analyzed, and optimization design, through the real car collision test, make the concrete guardrail after heightening structure satisfies the requirement of the safety performance of current specification. The results show that the protective performance of the two guardrail schemes meets the requirements of the current guardrail evaluation standards through the computer simulation experiment. Through the optimized design of scheme 1, the actual car crash test proves that the enhanced structure of Minhua TYPE II concrete guardrail can meet the requirements of safety performance evaluation. The research results provide an important basis for the transformation of the guardrail and the revision of the current design of expressway in China.

Multi-Axis Support-Free Printing of Freeform Parts with Lattice Infill Structures

In additive manufacturing, infill structures are commonly used to reduce the weight and cost of a solid part. Currently, most infill structure generation methods are based on the conventional 2.5-axis printing configuration, which, although able to satisfy the self-supporting condition on the infills, suffer from the well-known stair-case effect on the finished surface and the need of extensive support for overhang features. In this paper, based on the emerging continuous multi-axis printing configuration, we present a new lattice infill structure generation algorithm, which is able to achieve the self-supporting condition for both the infills and the boundary surface of the part. The algorithm critically relies on the use of three mutually orthogonal geodesic distance fields that are embedded in the tetrahedral mesh of the solid model. The intersection between the iso-geodesic distance surfaces of these three geodesic distance fields naturally forms the desired lattice of infill structure, while the density of the infills can be conveniently controlled by adjusting the iso-values. The lattice infill pattern in each curved slicing layer is trimmed to conform to an Eulerian graph so to generate a continuous printing path, which can effectively reduce the retractions of the nozzle during the printing process. In addition, to cater to the collision-free requirement and to improve the printing efficiency, we also propose a printing sequence optimization algorithm for determining a collision-free order of printing of the connected lattice infills, which seeks to reduce the air-move length of the nozzle. Ample experiments in both computer simulation and physical printing are performed, and the results give a preliminary confirmation of the advantages of our methodology.

A Microwave Three-Dimensional Imaging Method Based on Optimal Wave Spectrum Reconstruction

Limited by the Shannon–Nyquist sampling law, the number of antenna elements and echo signal data of the traditional microwave three-dimensional (3D) imaging system are extremely high. Compressed sensing imaging methods based on sparse representation of target scene can reduce the data sampling rate, but the dictionary matrix of these methods takes a lot of memory, and the imaging has poor quality for continuously distributed targets. For the above problems, a microwave 3D imaging method based on optimal wave spectrum reconstruction and optimization with target reflectance gradient is proposed in this paper. Based on the analysis of the spatial distribution characteristics of the target echo in the frequency domain, this method constructs an orthogonal projection reconstruction model for the wavefront to realize the optimal reconstruction of the target wave spectrum. Then, the inverse Fourier transform of the optimal target wave spectrum is optimized according to the law of the target reflectance gradient distribution. The proposed method has the advantages of less memory space and less computation time. What is more, the method has a better imaging quality for the continuously distributed target. The computer simulation experiment and microwave anechoic chamber measurement experiment verify the effectiveness of the proposed method.

Walls composed of different materials: a brief review on thermal comfort

The present work is dedicated to identifying the central researches related to the influence of the different materials that make up the walls in the performance of thermal comfort. At first, the keywords “Wall materials” and “Thermal comfort” were used in the search for scientific articles through a systematic review in the Scopus and Web of Science databases, restricted to the areas of Architecture and Urbanism, Social Sciences, Arts and Humanities. 85 scientific articles were identified, of which 44 were included in the research, the excluded did not have adherence, because they were out of the subject or in duplicate. In order to organize the data and discuss the subjects, four contexts were identified: building evaluation (39%), computer simulation (39%), prototype construction (15%) and laboratory experiment evaluation (7%). Among the materials, hemp and straw bales stood out by demonstrating the ability to cushion temperature variations in both winter and summer, and are therefore good thermal regulators. The melting temperature of the Phase-Change Material (PCM) of 25 ° C optimized the installation in all locations. The ceramic brick wall had a worse performance, from 1.25 to 1.45W / (m.K) in relation to the traditional mud walls at 1.1 to 1.2W / (m.K) and the earth block construction technique stabilized with cement at 1.05 to 1.25W / (m.K). The application of materials provided for wall construction is one of the best alternatives to achieve the condition of internal thermal comfort of buildings.

Inhibition of Acetylcholinesterase by Wood Creosote and Simple Phenolic Compounds.

Anisakiasis is common in countries where raw or incompletely cooked marine fish are consumed. Currently, effective therapeutic methods to treat anisakiasis are unavailable. A recent study found that wood creosote inactivates the movement of Anisakis species. Essential oil of Origanum compactum containing carvacrol and thymol, which are similar to the constituents of wood creosote, was reported to inactivate Anisakis by inhibiting its acetylcholinesterase. We examined whether wood creosote can also inhibit acetylcholinesterase. We examined the effect of components of wood creosote using the same experimental method. A computer simulation experiment (molecular docking) was also performed. Here, we demonstrate that wood creosote inactivated acetylcholinesterase in a dose-dependent manner with an IC50 of 0.25 mg/mL. Components of wood creosote were also tested individually: 5-methylguaiacol, p-cresol, guaiacol, o-cresol, 2,4-dimethylphenol, m-cresol, phenol and 4-methylguaiacol inactivated the enzyme with an IC50 of 14.0, 5.6, 17.0, 6.3, 3.9, 10.0, 15.2 and 27.2 mM, respectively. The mechanism of acetylcholinesterase inactivation was analyzed using a computer-based molecular docking simulation, which employed a three-dimensional structure of acetylcholinesterase and above phenolic compounds as docking ligands. The simulation indicated that the phenolic compounds bind to the active site of the enzyme, thereby competitively blocking entry of the substrate acetylcholine. These findings suggest that the mechanism for the inactivation of Anisakis movement by wood creosote is due to inhibition of acetylcholinesterase needed for motor neuron activity.

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning.

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning-based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 103 particles with mean process times scaling as N 0.5 Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

Path Planning for Excavator Arm: Fuzzy Logic Control Approach

This paper proposes an algorithm to design the path for automated excavator arm. The path designing is divided into two phases. Firstly, the fuzzy logic technique is used to determine the change of the path to adapt with the variation of the material after each digging period. Secondly, the B-spline algorithm is used to build the optimal trajectory. By this, the excavator can maximize the dug weight although the shape of the material is variation. The effectiveness of the algorithm is verified through computer simulation and real-time experiment. The simulation and experimental results show that the generated optimal path keeps the dug weight around the expected value regardless of the change of the environment.

Tempo-spatially modulated imaging spectropolarimetry based on polarization modulation array

In this paper, we propose an instrument concept based on a polarization modulation array for the simultaneous measurement of the irradiance, spectrum, and polarization states of the target of interest. Using a group of retarders and polarizers oriented in specific directions, the full set of Stokes parameters can be determined directly without internal moving parts or extensive calculations. The polarization array consists of two retarders and four linear polarizers located at the incident aperture, so that the incident light is divided into four separate modulation channels. To measure the modulated spectra, we include an interference spectrometer based on the Savart polariscope principle in the system and retrieve the polarization spectra by Fourier transform. We apply a tempo-spatially modulation mode in the scheme to extract the multi-dimensional data of each point in the field of view. The system's performance, especially the capability for Stokes spectra measurement, is verified through both computer simulation and laboratory experiments. Possible sources of error are also analyzed.

Теоретико-вероятностный подход к моделированию респиратора на химически связанном кислороде

At present, the main prospects for improving the insulating means of respiratory protection are related to the chemical method of oxygen reservation. The arguments in favor of this choice are the high density of oxygen packaging and its self-regulating supply, depending on the physical activity of the person. Usually, the working process in devices on chemically bound oxygen is modeled using mathematical physics methods that solve the so-called sorption dynamics problem. As a result, under given boundary and initial conditions, the concentration of CO2 molecules in the regenerative cartridge turns out to be a deterministic function of time and coordinates. However, the coordinate of the elementary act of sorption is essentially a random variable. The law of its distribution evolves as the absorbing resource of the regenerative cartridge is consumed. Taking into account the above, a probability-theoretic approach to modeling the working process of an insulating breathing apparatus based on chemically bound oxygen was developed. The approach is based on the description by probability theory methods of the random coordinate of the elementary act of chemosorption of a CO2 molecule by potassium peroxide granules and the random lifetime of this molecule in the regenerative cartridge of the respiratory apparatus. The evolution of the initial and central statistical moments of these values is established. The symmetry of their probability density with respect to the permutation of dimensionless arguments is shown, which are the time and distance from the entrance to the regenerative cartridge to the considered layer of chemisorbent. The presence of symmetry increases the speed of numerical experiments by one or two orders of magnitude. Gaussian asymptotics of the process at long times and corrections to it by inverse degrees of dispersion due to asymmetries and excesses of different orders are revealed. This further increases the speed of numerical experiments in computer simulation of the working process of an insulating respirator on chemically bound oxygen.

Influence of Student Depression on the Spread of Public Opinion in University

In this study, we examined the impact of college students’ mental health on their social behavior. A social network was identified based on the behavior of college students sharing a meal. We analyzed the impact of depression on the structure of this network and found that students without obvious depressive symptoms, based on the test data of the SCL-90 Assessment Scale, were better at socializing than students with obvious depressive symptoms. We proposed a public opinion spreading model on social networks and formulated a heterogeneous mean-field theory to describe it. Further, using computer simulation experiments, we studied the impact of students’ mental health on the process of information propagation in college. The results of the experiments showed that students without obvious depressive symptoms were more likely to receive information than students with obvious depressive symptoms. Based on the results of our study, college psychological consultants can actively identify students who may be at risk of mental illness and give them attention and guidance.

Some Models for Subjectively Estimating Representative Values of Multiple Data: Comparison with New Indexes and Traditional Indexes through Computer Simulation and Psychological Experiment

Some Models for Subjectively Estimating Representative Values of Multiple Data: Comparison with New Indexes and Traditional Indexes through Computer Simulation and Psychological Experiment