Constant Parameters Research Articles

Kinematic Parameter Identification and Error Compensation of Industrial Robots Based on Unscented Kalman Filter with Adaptive Process Noise Covariance

Kinematic calibration plays a pivotal role in enhancing the absolute positioning accuracy of industrial robots, with parameter identification and error compensation constituting its core components. While the conventional parameter identification method, based on linearization, has shown promise, it suffers from the loss of high-order system information. To address this issue, we propose an unscented Kalman filter (UKF) with adaptive process noise covariance for robot kinematic parameter identification. The kinematic model of a typical 6-degree-of-freedom industrial robot is established. The UKF is introduced to identify the unknown constant parameters within this model. To mitigate the reliance of the UKF on the process noise covariance, an adaptive process noise covariance strategy is proposed to adjust and correct this covariance. The effectiveness of the proposed algorithm is then demonstrated through identification and error compensation experiments for the industrial robot. Results indicate its superior stability and accuracy across various initial conditions. Compared to the conventional UKF algorithm, the proposed approach enhances the robot’s accuracy stability by 25% under differing initial conditions. Moreover, compared to alternative methods such as the extended Kalman algorithm, particle swarm optimization algorithm, and grey wolf algorithm, the proposed approach yields average improvements of 4.13%, 26.47%, and 41.59%, respectively.

Valorization of Sour Cherry Kernels: Extraction of Polyphenols Using Natural Deep Eutectic Solvents (NADESs).

The objective of this research was to optimize the natural deep eutectic solvent (NADES) extraction process from sour cherry kernels (Prunus cerasus L.). For polyphenol isolation, conventional solid-liquid extraction was employed using different concentrations of ethanol (0, 10, 20, 30, 40, 50, 60, 70, 80, 90, and 96%), as well as the innovative NADES extraction technique. In the initial phase of the research, a screening of 10 different NADESs was conducted, while extraction was carried out under constant parameters (50 °C, 1:20 w/w, 60 min). NADES 4, composed of lactic acid and glucose in a molar ratio of 5:1, exhibited the highest efficiency in the polyphenol isolation. In the subsequent phase of the research, response surface methodology (RSM) was utilized to optimize the extraction process. Three independent variables, namely temperature, extraction time, and solid-liquid (S/L) ratio, were examined at three different levels. The extracted samples were analyzed for total phenol (TP) and antioxidant activity using the DPPH, ABTS, and FRAP assays. ANOVA and descriptive statistics (R2 and CV) were performed to fit the applied model. According to RSM, the optimal extraction conditions were determined as follows: temperature of 70 °C, extraction time of 161 min, and S/L ratio of 1:25 w/w.

A Novel Approach to Image Retrieval for Vision-Based Positioning Utilizing Graph Topology

Abstract. This research introduces a novel approach to improve vision-based positioning in the absence of GNSS signals. Specifically, we address the challenge posed by obstacles that alter image information or features, making retrieving the query image from the database difficult. While the Bag of Visual Words (BoVW) is a widely used image retrieval technique, it has a limitation in representing each image with a single histogram vector or vocabulary of visual words, i.e., the emergence of obstacles can introduce new features to the query image, resulting in different visual words. Our study overcomes this limitation by clustering the features of each image using the k-means method and generating a graph for each class. Each node or key point in the graph obtains additional information from its direct neighbors using functions employed in graph neural networks, functioning as a feedforward network with constant parameters. This process generates new embedding nodes, and eventually, global pooling is applied to produce one vector for each graph, representing each image with graph vectors based on objects or feature classes. As a result, each image is represented with graph vectors based on objects or feature classes. In the presence of obstacles covering one or more graphs, there is sufficient information from the query image to retrieve the most relevant image from the database. Our approach was applied to indoor positioning applications, with the database collected in Bolz Hall at The Ohio State University. Traditional BoVW techniques struggle to properly retrieve most query images from the database due to obstacles like humans or recently deployed objects that alter image features. In contrast, our approach has shown progress in image retrieval by representing each image with multiple graph vectors, depending on the number of objects in the image. This helps prevent or mitigate changes in image features caused by obstacles covering or adding features to the image, as demonstrated in the results.

Accelerating universe with wet dark fluid in modified theory of gravity

In the present work we have focused on the investigation of LRS Bianchi type –I metric within the framework of f(R) theory of gravity filled with wet dark fluid as the candidate of dark energy. The solution of the metric is an accelerating universe, derived by assuming the negative constant deceleration parameter and utilizing a power law relation. Additionally, we have visually analyzed the metric's dynamical and geometrical properties through graphical representations.

Flexible NH3 gas sensors based on ZnO nanostructures deposited on kevlar substrates via hydrothermal method

Owing to their flexibility and high thermal resistance, para-aramid based Kevlar™ fabric substrates are an ideal candidate for obtaining flexible gas sensors for new-generation wearable technologies. The morphology of the surface of the substrate where the target gas comes into contact directly affects the important features of the sensor such as detection limit, selectivity, and response. In this context, a feasible technique is introduced to enhance the efficiency of flexible gas sensors utilizing ZnO/Kevlar™, entailing the modification of ZnO morphology. ZnO based gas sensing layers were deposited on Kevlar™ fabric substrates by a two-stage method. Initially, seed layer was produced on Kevlar™ fabric using the ultrasonic bath method, with five different seed layer processing times ranging from 1 min to 20 min. In the nucleation, all nanostructured layers were deposited by hydrothermal method with constant parameters and under the same conditions. As the seeding time was increased, nanorods (1D) formed on the surface became flakes (2D), leading to considerable improvement in NH3 gas sensing properties. The sensor with a 5-min seeding time showed a sensitivity of 49 % at an optimal operating temperature of 190 °C, while the sensor produced in 20 min showed the best response performance with 169 % at 130 °C for 50 ppm NH3 gas. The increase in seeding time not only reduced the operating temperature of the gas sensor through the conversion from 1D nanostructure to 2D, but also significantly increased the sensor response. Under constant hydrothermal conditions and solution concentration, the density per unit area increases. However, after 10 min of seeding, the length of nanorods shortens and turn into a rod-flake hybrid morphology. A superior sensor performance was demonstrated for the samples examined. The obtained results also showed that flexible Kevlar™ fabric could be a feasible and interesting substrate for nanostructured ZnO-based NH3 gas sensors.

Acoustic black hole: the Sagnac effect, the geodesics and the bounding values of the parameters

Sagnac interference experiment is theoretically analyzed in the curved spacetime of the Rotating Acoustic Black hole metric. The Zero and the infinite Sagnac delay has been analyzed. The geodesic motion in the metric is discussed very briefly to derive the formula for the Sagnac delay. For the first time, the values of the two constant parameters related to the metric of the acoustic black hole have been found to be restricted within certain limit by the use of the formula for the Sagnac delay. The equation for finding the sonic horizon has also been deduced.

Computational analysis of the bioconvective flow of Williamson–Sutterby fluid with microorganisms and activation energy subject to Cattaneo–Christov double-diffusion effects

This research aims to develop a mathematical model and outline the implications of the free convection flow within a non-Newtonian Williamson–Sutterby type nonfluid through a stretching surface placed horizontally with magnetic dipole effect. The present attempt establishes the influence of multiple factors, including double diffusion, and heat flux. Utilizing the Cattaneo–Christov heat mass flux model approximations, to shape the thermal and concentration balance equations, incorporating various generalized transport laws. Furthermore, the transportation mechanism incorporates Arrhenius activation energy and binary chemical reactions. The impact of bioconvection resulting from self-propelled microorganisms is incorporated into the fluidic model. A nonlinear set of partial differential equations (PDEs) are appropriately formulated, employing boundary layer approximations theory, to comprehensively describe the convective flow. The PDEs are converted to ordinary differential equations via similarity transformation, and then computationally computed via a well-structured RKF45 technique with a shooting algorithm. To validate the results, a comparison is made with published findings in limiting cases. It is observed that the velocity profiles exhibit an escalation in tandem with ascending values of the electric parameter and mixed convection. Conversely, the velocity diminishes with the augmentation of the magnetic factor, ferrohydrodynamic interaction parameter, porosity parameter, and Sutterby fluid parameter. Temperature profiles elevate in response to escalating values of the Eckert number, radiation parameter, and Brownian motion parameter while diminishing with the augmentation of the thermal relaxation constant, Prandtl number, and Sutterby fluid parameter. The concentration distribution exhibits an augmentation with the increasing magnitude of the thermophoresis parameter and activation energy while experiencing a reduction with the improvement in the behavior of Schmidt number and Brownian parameter. The ongoing investigation encompasses a wide spectrum of applications within the field of applied sciences, placing particular emphasis on thermal oil recovery, geothermal reservoirs, chemical engineering, and the cooling processes pertinent to nuclear reactors.

Velocity and Temperature Dependence of Steady‐State Friction of Natural Gouge Controlled by Competing Healing Mechanisms

AbstractThe empirical rate‐ and state‐dependent friction law is widely used to explain the frictional resistance of rocks. However, the constitutive parameters vary with temperature and sliding velocity, preventing extrapolation of laboratory results to natural conditions. Here, we explain the frictional properties of natural gouge from the San Andreas Fault, Alpine Fault, and the Nankai Trough from room temperature to ∼300°C for a wide range of slip‐rates with constant constitutive parameters by invoking the competition between two healing mechanisms with different thermodynamic properties. A transition from velocity‐strengthening to velocity‐weakening at steady‐state can be attained either by decreasing the slip‐rate or by increasing temperature. Our study provides a framework to understand the physics underlying the slip‐rate and state dependence of friction and the dependence of frictional properties on ambient physical conditions.

Tribological behavior evaluation of poly-ether-ether-ketone (PEEK) in dry journal bearing on shaft wear test

This paper investigated the tribological behavior of pure PEEK playing as a dry journal bearing, sliding against stainless steel, under real-life operating conditions in a wear test lasting 2 h. Four conditions were carried out with different magnitudes of normal load and sliding speed, while keeping a constant PV parameter. Sample topography assessments were performed with scanning electron microscopy and white light interferometry techniques. In addition, PEEK samples were also evaluated by Fourier Transformed Infrared Spectroscopy and thermal analyses by Differential Scanning Calorimetry. The coefficient of friction (COF) changed throughout the wear test and exhibited a running-in period followed by a transition, with an increase of COF, and then a tendency to reach a steady-state. Moreover, the COF behavior obtained suggests that there was an influence of the wear test parameters, mainly right after the running-in period — and the COF averages for the steady-state period were statistically equal. Stainless steel samples showed mild wear, while PEEK samples had a drastic alteration of their topography imposed by the wear test — including an increase in its degree of crystallinity. Nonetheless, the PEEK journal bearing samples did not fail from wear and their mass losses were small. Polymeric wear particles were generated and were found weakly adhered to both the body and the counter body. PEEK exhibited a lumpy transfer process — nonetheless, SEM images evaluation was useful to verify that these particles were eventually merged during sliding, and kneaded in the convex-concave contact, which provided them a film-like appearance. Furthermore, adhesive and abrasive wear mechanisms were identified, which were shown to be related to the journal bearing on shaft wear test arrangement.

Fractal analysis of dimensionless permeability and Kozeny–Carman constant of spherical granular porous media with randomly distributed tree-like branching networks

The seepage of porous media has garnered significant interest due to its ubiquitous presence in nature, but most of the research is based on the model of a single dendritic branching network. In this study, we derive a fractal model of the dimensionless permeability and the Kozeny–Carman (KC) constant of porous media consisting of spherical particles and randomly distributed tree-like branching networks based on fractal theory. In addition, three different types of corrugated pipes are considered. Then, the relationships between the KC constant, dimensionless permeability, and other structural parameters were discussed in detail. It is worth noting that the KC constant of the porous media composed of three types of pipes decreases sharply first and then increases with the increase in the internal diameter ratio, while the dimensionless permeability has the opposite trend and conforms to the physical law. In addition, empirical constants are not included in the analytical formulas of the present model, and the physical mechanism of fluid flow in spherical granular porous media with randomly distributed tree-like branching networks is clearly revealed.

Effect of adaptive control of cooling rate on microstructure and mechanical properties of laser additively manufactured Inconel 718 thin walls

Ni-alloy Inconel 718 (IN718) is finding ever-increasing applications in various industries like aviation and aerospace. IN718 is a precipitation-strengthened alloy which derives its strength mainly from the intermetallic phases, γ” (Ni3Nb) along with the γ’ (Ni3(Al, Ti)) phase which can be precipitated using standard heat treatment schedules. However, the consummation of Nb in Laves phase formation during solidification tends to deteriorate the strength of the material. During laser additive manufacturing (LAM) by directed energy deposition (DED), the cooling rate variation along the build direction causes variations in the microstructure, properties and Laves phase distribution. The study aims to minimize the heterogeneities along the build direction by monitoring and controlling the cooling rate during DED of IN718. The feedback control system involves the use of two pyrometers in tandem with a leading pyrometer measuring the molten pool temperature and a trailing pyrometer measuring the temperature at a distance behind the molten pool. Two sets of thin walls of 120 layers were fabricated with one set being of constant process parameters without feedback control and the other set being of adaptive-controlled process parameters. The adaptive control was aimed at maintaining the cooling rates above a desired limit by changing the process parameters, namely the laser scan speed and the powder feed rate. The Laves phase morphology, which affects the strength of the deposited part deleteriously was finer and more discrete in the adaptive-controlled walls which led to their easier dissolution during heat treatment. This in turn helped in the precipitation of more amount of strengthening phases during heat treatment which led to better mechanical properties. The characterizations of the two sets of walls reflected the superior part quality of the adaptive-controlled wall in terms of homogeneity of microstructure, enhanced microhardness and tensile strength, thereby validating the importance of adaptive control of cooling rate in ensuring better quality in LAM parts.

Lie group analysis of bingham plastic flow over a straining surface in the presence of magnetohydrodynamic effects and slip conditions

This paper investigates the two-dimensional flow of a Bingham plastic over a straining surface subjected to an externally applied magnetic field and surface slips. The study aims to understand the behavior of such flows and their response to external factors, which has applications in various industrial processes involving complex fluid dynamics. Through Lie group analysis, a new set of similarity transformations are derived to reduce the number of variables in the governing partial differential equations, facilitating a more tractable analysis. These transformations enable the conversion of the partial differential equations into a self-similar system of ordinary differential equations. A high-order, three-stage Lobatto IIIa formula along with appropriate boundary conditions is applied to solve this system. The solutions obtained for various physical parameters lead to several key deductions. It is found that under constant physical parameter values, the velocity layer thickness of the plastic flow is lower compared to the thermal layer thickness, indicating the dominance of the plastic flow behavior. Additionally, an increase in the magnetic field results in a reduction in the thickness of the plastic boundary layer, highlighting the significant influence of magnetic fields on the flow characteristics. These findings provide valuable insights into the control and optimization of processes involving Bingham plastic flows, particularly in the presence of magnetic fields and surface slips.

Design exploration of the status detection system for car-mounted catenary tension compensation device

The tension compensation device is a critical component for maintaining constant parameters of the contact wire, such as tension, catenary height, and sag, in the overhead contact system. Its operational status directly affects the normal operation of the entire contact wire system. This paper provides a comprehensive review of existing tension compensation device state detection techniques and analyzes their shortcomings. By comparing with existing methods for monitoring cable tension, a vehicle-mounted contact wire tension compensation device state detection system based on the three-point bending method is proposed. This system can simultaneously monitor the operational status of the device at the line side and anchor section, issuing real-time warnings in case of abnormal device states and possessing significant application value. This study provides a reliable tool for railway operators to monitor the devices status and take timely maintenance and adjustment measures to ensure the normal operation of the contact wire system

Forecasting the UK top 1% income share in a shifting world

AbstractUK top income shares have varied hugely over the past two centuries, ranging from more than 30% to less than 7% of pre‐tax national income allocated to the top 1 percentile. We build a congruent dynamic linear regression model of the top 1% income share allowing for economic, political and social factors. Saturation estimation is used to model outliers and trend breaks, proxying underlying structural changes driving income inequality in the UK. We use the model to forecast the top 1% income share over the last 15 years, and compare to a range of forecast devices. Despite a well‐specified constant parameter model conditioning on significant explanatory variables, the best performing forecasts are obtained from a random walk and a smoothed random walk. These results are explained by the presence of shifts in the income share over the forecast period, resulting in forecasts from equilibrium correction models converging to the wrong equilibrium. Our best prediction for 2026 based on the most recent data from 2021 (a 5‐year ahead projection) is that the pre‐tax top 1% income share will remain at the most recent realized value of 12.7%, but there is a large degree of uncertainty, with a 95% confidence band ranging from 10% to 15.7%.

A new car-following model with incorporation of Markkula's framework of sensorimotor control in sustained motion tasks

This study develops a car-following model called the “Markkula Intelligent Driver Model (MIDM)” based on Markkula's Framework of Sensorimotor Control. The MIDM predicts the start time of driver's reaction based on the evidence accumulation within Markkula's framework unlike the existing car-following models that use a constant reaction time parameter. The MIDM also accurately represents the actual shape and duration of acceleration maneuvers. Fifty drivers’ car-following behavior was observed in 2 different scenarios using a driving simulator – reaction to a decelerating lead vehicle and reaction to a stopped lead vehicle. Trajectory data from the NGSIM project were also used for the evaluation. Compared to the Gipps Model, the Wiedemann Model and the IDM, the MIDM realistically reproduced trajectories of speed, acceleration, jerk and spacing for both simulator and NGSIM data. The MIDM can also incorporate the effects of lead vehicle brake lights for more accurate estimation of the driver reaction time.

A simple model of the soil freezing characteristic curve for saline soils with two freezing stages

Soil freezing characteristic curve (SFCC) describes the relationship between unfrozen water and subzero temperature, which is of significance for the simulation of heat, water, salt migration in cold regions. There are two phase transition stages in some saline soils, which is often explained by the phase equilibrium of bulk solution. However, the second phase transition and chemical characteristic of solute are ignored in the current coupling numerical models for freezing-thawing soils. The newest SFCC methods considering abovementioned two items are not applicable to numerical models due to complex calculation or irregularly changeable parameters. To solve those problems, a simple model was proposed in this paper. Firstly, the complete phase diagram of pore solution at icing stage was speculated from published experimental SFCCs of saline soils. Then, the temperatures of saline soils at freezing and eutectic points were quantitative expressed with phase diagram of bulk solution and SFCC of nonsaline soil, and the criteria determining whether single icing stage or icing-eutectic stage occurs in saline soils was proposed. A synthetic index was used to describe the effects of soil matrix and initial solute concentration on the exponent. Only three constant parameters were introduced to reflect the soil matrix effect on phase transition points of pore solution and the influence of chemical characteristic of solute on pore water freezing process. Finally, the model was validated by the experimental data of saline soils and showed good results and ease of use compared to a widely used theorical model for saline soil with single freezing stage and other two models both considering two phase transitions. The work provides a deeper view of freezing process in saline soils and promote the improvement of numerical simulation effect for heat, water and salt migration in seasonal freezing-thawing areas.

Improving the optical and dielectric characteristics of PVA/PVP/PEG/ZnWO4/CdS blends

This work aims to create novel nanocomposite blended polymers by incorporating (1−x)ZnWO4-xCdS into poly (vinyl alcohol) (PVA)/polyvinyl pyrrolidone (PVP)/polyethylene glycol (PEG) blend to employ these nanocomposites in various optoelectronic applications. This study focused on investigating the structural, optical and electrical features of PVA/PVP/PEG/(1−x)ZnMn2O4-xCdS blends. The x-ray diffraction and scanning electron microscope techniques were used to explore the structure and morphology of the formed samples. The structure and percentages of ZnWO4 and CdS in different fillers were performed using Rietveld method. The doped blends exhibited significant absorption of UVA and UVB types. The greatest amounts of absorption were observed when the filler contained 25 % CdS. The direct and indirect optical band gaps of the doped blend became 5.02 and (1.88, 2.37) eV as the amount of CdS became 25 % in the filler sample. The refractive index, optical dielectric constant, optical conductivity, and nonlinear optical parameters are affected by the amount of CdS in the fillers. The fluorescence spectra for the blends affected by the excitation wavelength and amount of CdS in the filler. The maximum energy density of the doped blend was reached when the amount of CdS in the filler reached 25 %. The purities of emitted color in the undoped blend are 83 % and 74 % under excitation wavelengths of 317 nm and 380 nm. The purity of the blend experienced a slight change when loaded with filler samples. As the ZnWO4 doping of the PVA/PVP/PEG blended polymer rose, its electrical dielectric constant and ac conductivity first enhanced and then irregularly declined as the filler's CdS content rose. Incorporating (1−x)ZnWO4-xCdS into the nanocomposite enhanced their optical and electrical properties, making them a potential material for flexible optoelectronic and energy storage uses.

Fault-Tolerant Phototaxis of a Modular System Inspired by Gonium pectorale Using Phase-Based Control

In this study, we proposed a model for modular robots in which autonomous decentralized modules adaptively organize their behavior. The phototaxis of Gonium pectorale, a species of volvocine algae, was modeled as a modular system, and a fault-tolerant modular control method of phototaxis was proposed for it. The proposed method was based on the rotation phase of the colony and adaptively adjusted an internal response-related parameter to enhance the fault tolerance of the system. Compared to a constant parameter approach, the simulation results demonstrated a significant improvement in the phototaxis time for positive and negative phototaxis during module failures. This method contributes to achieving autonomous, decentralized, and purposeful mediation of the modules necessary for controlling modular robots.

A gradient-based calibration method for the Heston model

The Heston model is a well-known two-dimensional financial model. Because the Heston model contains implicit parameters that cannot be determined directly from real market data, calibrating the parameters to real market data is challenging. In addition, some of the parameters in the model are non-linear, which makes it difficult to find the global minimum of the optimization problem within the calibration. In this paper, we present a first step towards a novel space mapping approach for parameter calibration of the Heston model. Since the space mapping approach requires an optimization algorithm, we focus on deriving a gradient descent algorithm. To this end, we determine the formal adjoint of the Heston PDE, which is then used to update the Heston parameters. Since the methods are similar, we consider a variation of constant and time-dependent parameter sets. Numerical results show that our calibration of the Heston PDE works well for the various challenges in the calibration process and meets the requirements for later incorporation into the space mapping approach. Since the model and the algorithm are well known, this work is formulated as a proof of concept.

Simulation of fretting wear in steel wires under variable coefficient of friction and variable wear coefficient

In this paper, the fretting wear behaviour of steel wires working in coal mining technology is studied numerically. In past studies, the fretting process of steel wires was carried out numerically considering that the coefficient of friction (COF) and wear coefficient (WC) are constant parameters. However, it has been noticed experimentally that COF increases up to a certain number of fretting cycles and then becomes constant, i.e. a steady-state stage, depending on the loading conditions. This increase in COF during the fretting process is also known as the running-up stage. The fretting wear model is modified to evaluate the influence of the varying coefficient of friction (VCOF), which is associated with the variable wear coefficient (VWC), so the influence of VWC is also considered. The subroutine UMESHMOTION used to implement the wear law is also modified to study the effect of VCOF and VWC. Therefore, in this study, the numerical results of a three-dimensional finite element (FE) model are compared, with analytical results of contact area and contact stresses, and with experimental results of peak wear depth. After validating the FE model, the wear scar, the increasing wear depth, wear volume, and the decreasing contact stress with increasing fretting cycles are determined numerically considering VCOF and VWC using cycle jump approach. The energy dissipation effect of frictional force and fretting amplitude is also studied for varying interaction properties of fretting wear models. The numerical simulations are performed by considering both elastic and plastic material properties to analyse the influence of varying interaction properties on fretting wear models at the running-up stage. The results indicate that the VWC model exhibits comparable impacts on both the elastic and plastic models. The results also show that the VWC fretting wear model leads to higher wear scar, wear volume, and wear depth values at the running-up stage as well as at the steady state stage, which are close to the experimental data.