Modeling the Influence of Engine Dynamics on Its Indicator Diagram

This article presents a proposal to describe the pressure changes in the combustion chamber of an engine as a function of the angle of rotation of the crankshaft, taking into account changes in rotational speed resulting from acceleration. The aim of the proposed model is to determine variable piston forces in simulation studies of torsional vibrations of a crankshaft with a vibration damper during the acceleration process. Its essence is the use of a Fourier series as a continuous function to describe pressure changes in one cycle of work. Such a solution is required due to the variable integration step during the simulation. It was proposed to determine the series coefficients on the basis of a Fourier transform of the averaged waveform of a discreet open indicator diagram, calculated for the registration of successive cycles. Recording of the indicative pressure waveforms and shaft angle sensor signals was carried out during tests on the chassis dynamometer. An analysis of the influence of the adopted number of series coefficients on the representation of signal energy was carried out. The model can also take into account the phenomenon of work cycle uniqueness by introducing random changes in the coefficients with magnitudes set on the basis of determined standard deviations for each coefficient of the series. An indispensable supplement to the model is a description of changes in the engine rotational speed, used as a control signal for the PID controller in the simulation of the load performed by the dynamometer. The accuracy of determining the instantaneous rotational speed was analyzed on the basis of signals from the crankshaft position angle sensor and the piston top dead center (TDC) sensor. Limitations resulting from the parameters of digital signal recording were defined.

Stability Analysis and Optimization of Semi-Explicit Predictor–Corrector Methods

The increasing complexity of advanced devices and systems increases the scale of mathematical models used in computer simulations. Multiparametric analysis and study on long-term time intervals of large-scale systems are computationally expensive. Therefore, efficient numerical methods are required to reduce time costs. Recently, semi-explicit and semi-implicit Adams–Bashforth–Moulton methods have been proposed, showing great computational efficiency in low-dimensional systems simulation. In this study, we examine the numerical stability of these methods by plotting stability regions. We explicitly show that semi-explicit methods possess higher numerical stability than the conventional predictor–corrector algorithms. The second contribution of the reported research is a novel algorithm to generate an optimized finite-difference scheme of semi-explicit and semi-implicit Adams–Bashforth–Moulton methods without redundant computation of predicted values that are not used for correction. The experimental part of the study includes the numerical simulation of the three-body problem and a network of coupled oscillators with a fixed and variable integration step and finely confirms the theoretical findings.

BCH Two-step Auxiliary Variable Integration with MplusAutomation

This R tutorial automates the BCH two-step axiliary variable procedure (Bolk, Croon, Hagenaars, 2004) using the MplusAutomation package (Hallquist & Wiley, 2018) to estimate models and extract relevant parameters. To learn more about auxiliary variable integration methods and why multi-step methods are necessary for producing un-biased estimates see Asparouhov & Muthén (2014). The name of this mehtod, BCH, stands for Bolck, Croon, & Hagenaars, the authors who developed this method (Bolk, Croon, Hagenaars, 2004). This tutorial utilizes the public-use data repository named the Longitudinal Survey of American Youth (LSAY; Miller et al., 1992). The applied example used in this tutorial is based off the example presented in the seminal chapter on mixture modeling by Katherine Masyn (2013). This tutorial contains the 9 math indicators from this original study as well as two auxiliary variables.

3-Step ML Auxiliary Variable Integration Using MplusAutomation

This R tutorial automates the 3-step ML axiliary variable procedure using the MplusAutomation package (Hallquist & Wiley, 2018) to estimate models and extract relevant parameters. To learn more about auxiliary variable integration methods and why multi-step methods are necessary for producing un-biased estimates see Asparouhov & Muthén (2014). The motivation for writing this tutorial is that conducting the 3-step manually is highly error prone as it requires pulling logit values estimated in the step-1 model and adding them in the model statement of the step-2 model (i.e., lots of copying & pasting). In contrast, this approach is fully replicable and provides clear documentation which translates to more reliable research.

Study of Fractional Analytic Functions and Local Fractional Calculus

In this present paper, the role of fractional analytic function in local fractional calculus is studied. Some important properties and theorems in local fractional calculus are discussed, such as product rule, quotient rule, chain rule, fundamental theorem of local fractional calculus, change of variable, integration by parts and so on. In addition, we propose several examples and formulas of local fractional calculus.

The influence of auger wear on the parameters of the dehydration process of solid waste in the garbage truck

The article is dedicated to the study of the influence of auger wear on the parameters of the dehydration process of municipal solid waste in the garbage truck. An improved mathematical model of the drive operation of dehydration of solid waste in the garbage truck is proposed, which takes into account the wear of the auger and allowed to numerically determine the dynamics of the drive during start-up. It was also established that increasing wear of the auger, the pressure of the working fluid at the inlet of the hydraulic motor rises, and the angular velocity and speed of the auger is significantly reduced. The research of this mathematical model was carried out using the numerical Runge-Kutta-Felberg method of the 4th order with a variable integration step. By means of the method of regression analysis, the power dependencies of the change of nominal values ​​of pressures at the inlet of the hydraulic motor, angular velocity and speed of rotation of the auger from the value of its wear are determined. The last-mentioned dependence defines the detuning from the optimal speed of the auger during its wear and is used to determine the energy consumption of dehydration of solid waste, taking into account the wear of the auger. It is established that the wear of the auger by 1000 mm leads to an increase in the energy consumption of dehydration of solid waste by 11.6%, and, therefore, also leads to an increase of the cost of the process of their dehydration in the garbage truck. It was also established the expediency of further research to determine the appropriate material of the auger and the ways to increase its wear resistance.

Pervasive Suicidal Integrases in Deep-Sea Archaea

Mobile genetic elements (MGEs) often encode integrases which catalyze the site-specific insertion of their genetic information into the host genome and the reverse reaction of excision. Hyperthermophilic archaea harbor integrases belonging to the SSV-family which carry the MGE recombination site within their open reading frame. Upon integration into the host genome, SSV integrases disrupt their own gene into two inactive pseudogenes and are termed suicidal for this reason. The evolutionary maintenance of suicidal integrases, concurring with the high prevalence and multiples recruitments of these recombinases by archaeal MGEs, is highly paradoxical. To elucidate this phenomenon, we analyzed the wide phylogenomic distribution of a prominent class of suicidal integrases which revealed a highly variable integration site specificity. Our results highlighted the remarkable hybrid nature of these enzymes encoded from the assembly of inactive pseudogenes of different origins. The characterization of the biological properties of one of these integrases, IntpT26-2 showed that this enzyme was active over a wide range of temperatures up to 99 °C and displayed a less-stringent site specificity requirement than comparable integrases. These observations concurred in explaining the pervasiveness of these suicidal integrases in the most hyperthermophilic organisms. The biochemical and phylogenomic data presented here revealed a target site switching system operating on highly thermostable integrases and suggested a new model for split gene reconstitution. By generating fast-evolving pseudogenes at high frequency, suicidal integrases constitute a powerful model to approach the molecular mechanisms involved in the generation of active genes variants by the recombination of proto-genes.

Experimental Biointegration of a Titanium Implant in Delayed Mandibular Reconstruction

Background: Mandibular reconstruction, after extensive resection of the mandible for the treatment of oral cancer, is a well-known procedure, however, relatively little is known about bone integration into the titanium implant after reconstruction with a temporary plastic implant. The main goal of this experimental study was to study the process of osseous integration into the titanium implant in an in vivo experiment following prior mandibular reconstruction with a temporary plastic implant. Materials and Methods: Four ewes initially underwent a partial one-sided resection of the mandible, with the formation of an approximately 3 × 1 cm defect. All of the subjects received reconstruction with an implantation of a plastic plate (3 cm). The plastic plate was removed and replaced by a titanium implant at 1, 3, 6, and 12 months, accordingly. Both plastic and titanium implants were made via 3D-printing technology and personalized modeling. A total of 6 months after titanium implantation, a histological evaluation of biointegration was performed. Results: All surgeries were uncomplicated. The integration of osseous tissue into the titanium implant was seen in all cases. Histologically, each case showed variable integration of dense fibrotic tissue with fibroblasts and non-mature bone tissue with a definitive layer of bone matrix with many osteoblasts on the periphery. The prior implantation of the plastic plate did not interfere with bone integration into the titanium implant. Conclusion: Preliminary results demonstrated that a temporary plastic implant for mandibular reconstruction does not interfere with the consequent osseous biointegration of a permanent titanium implant. This shows that temporary reconstruction is a safe solution when delayed mandibular reconstruction is required due to disease severity.