Bryon C. Applequist, Zachary L. Motz, Anastasia Kyvelidou
<b>Background:</b> Linear methods of analysis of variability are concerned with the magnitude of variability and often consider deviations from a central mean as errors. The utilization of nonlinear tools to examine variability allows for the exploration and measurement of the patterns of variability displayed by the system. This methodology explores the deterministic properties of biological signals, in this case, gait, or how previous iterations within the gait cycle influence subsequent and future iterations. The nonlinear analysis of gait variability of the joint angle time series has not been investigated in developing children. <b>Methods</b>: We collected 3 min of treadmill walking data for 28 children between the ages of 2 and 10 years old and analyzed their joint angle time series using nonlinear methods of analysis (sample entropy, largest Lyapunov exponent, and recurrence quantification analysis). <b>Results</b>: Our results indicate that the nonlinear variability of children’s gait increases as children age. Interestingly, this contrasts with the findings from our previous work that showed a decrease in linear variability as children age. The combination of a decrease in linear variability, or a refined and improved stability of gait, as well as an increase in nonlinear variability, or an increase in the sophistication and quality of movement patterns, suggest an overall maturation of the neuromuscular system. <b>Conclusions</b>: Our study indicate that there is a refining of gait with age and motor maturation. This refining speaks to the overall multifaceted organization of systems that defines the maturation of gait.
Mechanics of engineering. Applied mechanics, Descriptive and experimental mechanics
Mohammed Irfan Khan, Anil Patel, Shubham Soni
et al.
The aim of this study is to determine the ideal stress distribution for a multi-Leaf Spring assembly using finite element analysis. Furthermore, the topology enhanced model, based on associate load is included in this research work. This work is carried out by considering two different techniques involving design for manufacturing (DFM) after the attainment of results from topology optimization. The vehicle's overall load is bear by the main leaf spring and graduated leaves are used to support the main leaf thus the prospective techniques intend to create holes across the graduated leaves and cut a custom slot along the graduated leaves of the spring assembly. The disclosure manifest that it is feasible to lessen the leaf spring assembly weight in order to create a lightweight, structurally sound design and reduce energy consumption that can be employed to heavy-duty commercial electric vehicles. The suggested techniques promisingly anticipate that a significant proportion of weight deduction of about 3.4 percent with holes and 17.34 percent with slots can be attained in multi-leaf spring assembly.
Юрій Петраков, Олександр Охріменко, О. Пасічник
et al.
Among various machining processes, turning accounts for the largest volume of chip removal worldwide, so much attention is paid to predicting stability and preventing chatter, with a special emphasis on machining systems. The use of CNC machines expands the possibilities for controlling the cutting process in accordance with the Stability Lobes Diagram (SLD), which allows not only to ensure the required quality and the reduce of vibrations, but also to select the cutting mode that ensures maximum productivity. Designing a SLD involves building a mathematical model of the machining system, which is associated with determining its dynamic characteristics. A dynamic model of the machining system of a lathe has been developed as a composition of the main units using the receptance coupling method, which made it possible to calculate the rigidity of the entire system, reduced to the tip of the cutter, as a function of the longitudinal coordinate when machining a workpiece installed in a chuck and in a chuck and rear center. The cutting process model represents the components of the cutting forces acting along the coordinate axes, which allows it to be integrated into the structure of the machining system. A method for experimental modal analysis of the machining system of a lathe using a hammer, accelerometer and a storage two-channel oscilloscope has been developed. Software for determining the frequency response function using a digital file of the experimental impulse response function has been created.
The current study highlights the importance of accurate temperature prediction in Iraq, a country facing economic challenges due to its hot, arid climate and increasing climate change effects. Conventional forecasting methods, such as statistical and shallow machine learning models, struggle to address the complex time-dependent characteristics of meteorological data. The present study proposes to improve the temperature forecasting of the three large cities in Iraq, i.e., Dohuk, Erbil, and Mosul, using the deep learning models that can learn both short- and seasonal weather trends. A meteorological dataset of 24 years (2000-2024) was created with five major characteristics, namely, temperature, wind speed, relative humidity, total precipitation, and surface pressure. The models to be used in the deep learning model were three, namely (Long Short-term memory (LSTM), Gated Recurrent Unit (GRU), and Artificial Neural Network (ANN). The metrics of performance were Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Squared Error (MSE), and R². The LSTM model performed the best in all the cities with RMSE values of 2.544, 2.366, and 2.323 and R² scores of 0.941, 0.948, and 0.952 in Dohuk, Erbil, and Mosul, respectively. The study confirms that LSTM is the most effective in modeling complex temporal dependencies in climatic time series, making it a significant contribution to understanding deep learning's application in weather forecasting in the Middle East. It suggests integrating AI-driven technology into the national meteorological system for climate-resistant decision-making in agricultural, water resource management, and urban development sectors.
Engineering machinery, tools, and implements, Mechanics of engineering. Applied mechanics
Structural damage monitoring is inevitable for the structures to perform during their intended service life adroitly. In the present review, literature related to techniques for diagnosing vibration-intensive damages have been evaluated in order to determine the material characteristics, such as stiffness and damping. Also, extensive review has been presented in the for damage detection in composite materials. The review encompasses the literature published in last 42 years, i.e., 1982 to 2024. The literature review is classified into sections as damage detection workflow, composite materials, damage detection techniques, and advanced damage detection techniques. The usage of strain energy, mode-shapes, waveform dimension, wavelet transform and updating finite element models in detection of damage are also discussed. Further, an overview of concepts, techniques, and advancement in vibration-induced damage detection are presented. The limitations of each technique are explained. An insight on advanced techniques and tools from genetic algorithm and artificial neural network regarding their employability to detect the damage is provided. This work portrays the damage detection methodologies.
Andrew Craig-Jones, Daniel R. Greene, Haley L. Gilbert
et al.
The purpose of this study was to compare average rate of oxygen consumption (VO<sub>2</sub>), slow component of oxygen consumption (VO<sub>2</sub> drift), heart rate (HR) and rating of perceived exertion (RPE) while wearing compression pants vs. a control garment during long-distance running. Methods: Nine injury-free and recreationally active participants (32 ± 11 years) were recruited for this study. Participants ran in full-leg compression pants (COMP) and a loose-fitting control garment (CON). Participants ran in each condition for 40 min at a preferred submaximal speed. The rate of oxygen consumption (VO<sub>2</sub>) was measured continuously via a metabolic cart throughout each condition. Both HR and RPE were recorded every 5 min during each condition. Oxygen consumption was averaged across the entirety of the steady state during the 40 min conditions for analysis. Additionally, the average from the first five minutes of the steady state was subtracted from the average of the last five minutes to assess VO<sub>2</sub>. A paired t-test was used to assess for differences for both variables. Both HR and RPE were each compared between conditions using 2 (garment) × 8 (time) repeated measure ANOVAs (α = 0.05). Results: There were no differences between VO<sub>2</sub> or VO<sub>2</sub> drift while running with full-leg compression pants vs. the control garment (<i>p</i> > 0.05). Neither RPE nor HR were influenced by the garments (<i>p</i> > 0.05) or time (<i>p</i> > 0.05) during each condition. Conclusion: Wearing compression pants did not result in reduced VO<sub>2</sub>, VO<sub>2</sub> drift, HR or RPE during a long-distance run. Although measured performance variables were not aided using compression pants, there were no negative effects to the use of compression pants.
Mechanics of engineering. Applied mechanics, Descriptive and experimental mechanics
Krzysztof Adamczuk, Daniel Dębowski, Szymon Wojciechowski
et al.
The aim of this study was to determine the impact of additions of tungsten carbide and silicon carbide microparticles to the lubricant used in the burnishing process on the tribological properties of friction pairs. The cylinders made of AISI 1045 steel constituted a workpiece. Burnishing was made with a lubricant the SN150 base oil with addition of tungsten carbide and silicon carbide microparticles. The tested materials were burnished with forces of 1000 N and 1500 N. Before and after the burnishing process, the surface roughness and hardness of the tested materials were measured. The study also presents the results of tribological properties of friction pairs with the tested structural materials. It was found that the addition of tungsten carbide microparticles to the base oil in the burnishing process can result in improved surface quality and reduced surface roughness. The results also confirmed the effect of addition of tungsten carbide and silicon carbide to the lubricant used in the burnishing process on tribological properties.
The influence of fluid phase on soil instabilities is investigated using the modified Cam-clay model within a two-phase description. Spurious mesh dependence of finite element results is prevented by a gradient enhancement of the model. The results of numerical tests for one-phase and two-phase model are compared. The influence of permeability on the stabilizing role of the fluid phase is assessed.
Computer engineering. Computer hardware, Mechanics of engineering. Applied mechanics
PDMS (polydimethylsiloxane) is an important soft biocompatible material, which has various applications such as an implantable neural interface, a microfluidic chip, a wearable brain–computer interface, etc. However, the selective removal of the PDMS encapsulation layer is still a big challenge due to its chemical inertness and soft mechanical properties. Here, we use an excimer laser as a cold micro-machining tool for the precise removal of the PDMS encapsulation layer which can expose the electrode sites in an implantable neural interface. This study investigated and optimized the effect of excimer laser cutting parameters on the electrochemical impedance of a neural electrode by using orthogonal experiment design. Electrochemical impedance at the representative frequencies is discussed, which helps to construct the equivalent circuit model. Furthermore, the parameters of the equivalent circuit model are fitted, which reveals details about the electrochemical property of neural electrode using PDMS as an encapsulation layer. Our experimental findings suggest the promising application of excimer lasers in the micro-machining of implantable neural interface.
This study conducted several tensile tests to determine the effect of 20-30 nm silicon dioxide nanopowder on the mechanical properties of composite material polyester/carbon fiber. Samples were prepared at weight fractions of carbon fibers (i.e. 25, 40, and 55%), with different weights of silica nanoparticles (i.e. 0.16, 0.2, and 0.24%). The experimental results showed that the mechanical properties improved at various ratios as a result of increasing the weight fraction of the carbon fibers and the ratio of the silicon dioxide nanopowder in the composition of the composite samples. The maximum increase by 33.49% resulting from increasing the weight fraction from 25% to 40% at 0.16% silicon dioxide nanopowder. The maximum effect of increasing the weight of the silicon dioxide nanopowder from 0.2 to 0.24 resulted from increasing the stress by 33.53% at weight fraction of 25%. The SEM images of the structure showed the distribution of nanoparticles and crack growth in the region neighboring the fracture after the tensile test at different weight fractions of carbon fibers and nano-silica particles. The improvement in the mechanical properties of this low-cost composite material when using nanomaterials has potential for use in multiple applications, including boat hulls.
Mechanical engineering and machinery, Mechanics of engineering. Applied mechanics
A new analytical solution is presented for functionally graded (FG) beams to investigate the bending behaviour under the hygro-thermo-mechanical loading using a new fifth order shear and normal deformation theory (FOSNDT). The material properties of the FG beam are varied along the thickness direction according to the power law index. In the present theory, a polynomial shape function is expanded up to fifth-order in terms of thickness coordinate to consider the effects of transverse shear and normal deformations. The present theory is free from the shear correction factor. Using the Navier’s solution technique the closed-form solution is obtained for simply supported FG beams. All the results are presented in non-dimensional form and validated it by developing the classical beam theory (CBT), first order shear deformation theory (FSDT by Mindlin) and third order shear deformation theory (TSDT by Reddy) considering the hygro-thermo-mechanical loading effects which is mostly missing in the literature. It is noticed that the presented FOSNDT is very simple and accurate to predict the bending behaviour of FG beams under linear and non-linear hygro-thermo-mechanical loadings.
Contemporary multiplicative plasticity models are now generally accepted as “proper material models” for modelling plastic behaviour of deformable bodies within the framework of finite-strain elastoplasticity. The models are based on the assumptions that the intermediate configuration of the body is stress-free or locally unstressed, for which no plastic deformation exists that meets the conditions of compatibility. The assumption; however, has never really been questioned nor justified, but was rather taken as an axiom and therefore considered to be generally true. In this study, we take a critical look at the assumption from both, physical and mathematical points of view, in order to investigate whether contemporary multiplicative plasticity models are indeed continuum based and if there are alternatives to them.
The present investigation draws scholars' attention to the effect of exponential variable viscosity modeled by Vogel and variable permeability on stagnation point flow of Carreau Nanofluid over an electromagnetic plate through a porous medium. Brownian motion and thermophoretic diffusion mechanism are taken into consideration. An efficient fourth-order RK method along with shooting technique are implemented to obtain the required solution of the non-dimensional modeled equations. The contribution of the present study is that augmented electromagnetic field strength due to the suitable arrangement of the plate and that of porosity parameter yield an accelerated motion while that of viscosity parameter produces retarded motion of shear-thickening fluid, contrary to shear-thinning fluid. At the same time, it discusses the inclusion of porous matrix which controls the thermal as well as concentration boundary layers, while enhanced Brownian motion exhibits diametrically opposite trend for them in response to shear-thickening fluid.
Peculiar features of the knowledge economy are investigated. The author’s own view on the content of such categories as 'capital' and 'human capital' is given, the role of the latter in the knowledge economy is specified.
Architecrure of expert system for technological setting up and trouble shooting for the units and systems of grain combine harvester is offered. Structure and composition of data bases of different sub-systems are considered.Used models for representation of knowledge are described.
Digital filtering is one of the main fundamental aspect of digital signal processing (DSP). Finite Impulse Response (FIR) digital filter design involves multi parameter optimization, on which the existing optimization algorithm may does not work efficiently. Particle Swarm Optimization (PSO) algorithm is a bio-inspired optimization algorithm which has been empirically demonstrated to perform well on many optimization problems. It is widely used to find the global optimum solution in a complex search space.
This paper presents the design of linear phase low pass FIR filter using particle swarm optimization (PSO) algorithm and discuss the influence of changing the PSO algorithm parameters such as the inertia weight (w), cognitive (c1) and social (c2) on the FIR filter design problem. Also the linear phase low pass FIR filter has been designed using the conventional genetic algorithm (GA) and a comparison has been made.
The simulation results show that PSO algorithm is better than the conventional GA with more rapidly convergence speed and better performance of the designed filter.
The FIR filter design using PSO algorithm is simulated using MATLAB programming language version 7.
Engineering machinery, tools, and implements, Mechanics of engineering. Applied mechanics
Saljnikov Aleksandar, Gojak Milan, Trifunović Miroslav
et al.
This paper deals with thermal radiation properties of ash deposits on a pulverized coal boiler of an electric power plant. Normal emittance spectra in the 2.5-25 μm interval, and total normal emittance, were measured on 2 kinds of ash layers of a mm magnitude order thickness, at 560→1460→560 K in heating and cooling. The emittance increases with ash radiation wavelength and temperature. Ash powder is sintered and fused above 1200 K. The emittance of the sintered layer is above that of the unsintered layer. The authors propose, and explain by example, correlating the experimentally obtained emittance spectra of ash deposits with a continuous curve, the formula of which defines the dependence of the emittance on wavelength and temperature, i.e. ε = ε (λ,T). Use of this formula, with parameter values determined by the proposed methodology, may greatly simplify the practical application of the experimentally determined emittances in the thermal design of existing and new steam boiler furnaces.
Engineering (General). Civil engineering (General), Mechanics of engineering. Applied mechanics