Value Of Time Delay Research Articles

Analysis of the possibility of solid-phase ignition of coal fuel

The article presents the results of theoretical and experimental studies of the ignition process of coal fuel particles in a pelletized state during high-temperature radiation-convective heating in an oxidizing environment. A new, different from the known, “two-temperature” mathematical model of the ignition process of a cylindrical coal pellet under intense heating conditions is presented. During the modeling, a detailed kinetic scheme of the reaction of gaseous products of thermal decomposition of coal with atmospheric oxygen was considered. The mathematical model was tested through a comparative analysis of the theoretical and experimental values of the ignition delay times of coal pellet fuel with experimental data. A wide range of heating conditions that could potentially lead to solid-phase ignition were analyzed. The research results showed that even under conditions of high oxygen content in the original coal, solid-phase ignition of coal pellets does not occur during intense heating. Based on the results of numerical modeling, it was established that the ignition process occurs in the gas phase. The oxygen released during the thermal decomposition of coal is not enough for stable gas-phase or heterogeneous ignition of pyrolysis products in the intrapore space of the fuel pellet. Based on the results of the numerical modeling, it was established that the oxygen released during the thermal decomposition of coal is significantly deficient in the intrapore space. The O2 concentration is not enough for a significant (in terms of heat flow) thermochemical intrapore reaction with gaseous and solid products of thermal decomposition.

Thickness measurement of polychlorotrifluoroethylene coating over metallic seal using terahertz time-domain spectroscopy

ABSTRACT Polychlorotrifluoroethylene is used as a coating material over metallic seals in low-temperature applications to arrest fluid leakage from the impeller side in turbopumps. Typically, polychlorotrifluoroethylene coating is applied on V-type seals, with a thickness ranging from 80 to 130 μm by spraying an emulsion over the substrate followed by heat treatment. An attempt has been made to measure the polychlorotrifluoroethylene coating thickness over V-type seals using terahertz time-domain spectroscopy in reflection geometry, a noncontact, non-invasive NDT method. When the terahertz pulse from a transmitter photo-conductive antenna is incident on the V-type seal, it penetrates through the polychlorotrifluoroethylene coating. It gets reflected from the coating/base coat interface. Here, the reflected echoes from the air-to-polychlorotrifluoroethylene coating interface and polychlorotrifluoroethylene coating to the basecoat interface get overlapped in the time domain as the polychlorotrifluoroethylene coating layer is very thin. The sparse deconvolution technique separates the individual reflected signals and obtains the time delay signals from various interfaces. From the estimation of time delay values, the thickness of the coating has been computed using the refractive index value extracted using terahertz time-domain spectroscopy in transmission mode before the reflection measurements. The obtained thickness values are in close agreement with the coating thickness measured using optical microscopy.

Dynamic analysis of a fractional-order delayed SIQR epidemic model for COVID-19 pandemic

In this paper, we build a fractional-order delayed SIQR epidemic model for COVID-19 pandemic. By leveraging the linearization method and the Laplace transform, the characteristic equation of the linearized system corresponding to the model is derived. The relationship between time delay and the stability of the positive equilibrium point is then explored through the examination of the roots of the characteristic equation and the cross-sectional conditions. Furthermore, a formula for calculating the critical value of time delay for the Hopf bifurcation is derived. Finally, suitable system parameters are chosen for numerical simulation to validate the soundness of the theoretical analysis.

Improved variable step adaptive filtering algorithm and its application in time delay estimation for continuous wave dual-sensor pulse signals

Continuous wave mud pulse transmission is crucial for wireless logging, but surface pump noise disrupts upstream mud pulses, hindering downhole information extraction. At a theoretical level, the dual-sensor differential denoising approach is an excellent technology for suppressing pump noise, but precisely identifying the time delay, which has a considerable impact on the denoising effect, remains a challenge. This paper provides an improved variable step-size adaptive time delay estimation method TVSS-LMSTDE to address this issue. Iteration time regulates the change in step size. The preset adjustment principle states that modifying parameters ζ and γ controls the learning features of step size. A series of stable and erratic dual-sensor continuous wave mud pulse signals interfered by various noise intensities are created in the simulation, and the performance of three different variable step-size technologies—error-oriented, nonlinear relationship, and iterative time regulation—in terms of convergence speed, estimation stability, and calculation amount are compared and analyzed. The results show that the iterative time regulation technique produces a minimal mean square error in time delay estimate, with generally steady estimation and excellent accuracy. When applied to hydraulic cycle tests, the technique accurately gets the time delay value of dual-sensor signals, giving critical support for the successful recovery of mud pulse data severely disrupted by pump noise.

AF automatic classification based on different time-delay values of the recurrence plot.

Recurrence plot (RP) has been widely used to transform 1D ECG waveforms into 2D images and explore the recurrence patterns of the electrical signals generated by the cardiac system. However, selecting the critical parameter time-delay τ for creating an RP has not been well-reported. In this work, we investigated the influence of different τ values on the RP-based AF prediction. And the results illustrated that the best classification performance could be achieved at τ=1 with full characters of the dynamic system.Clinical Relevance-This work established the AF classification system based on recurrence features and found the optimal parameters of the recurrence plot improving the ECG-based classification performance.

Fractional and MDD analysis of piezo-photo-thermo-elastic waves in semiconductor medium

This manuscript examines the effects of memory-dependent and fractional-order derivatives on a novel generalized piezo-thermo-elastic semiconductor model. The medium is homogenous and orthotropic, subjected to photo-thermal excitation. The governing equations include fractional-order parameters, relaxation time, time delay, and kernel function tailored to specific problem requirements. Normal mode method use to solve the equations, yielding analytical expressions. Graphical representations show physical field distribution across various fractional-order parameters, kernel functions, time delay, and frequency values. This study has the potential to advance precise model development and future simulations.

Adaptive leak signal extraction based on EMD-CC for water pipeline leak location

When using acoustic methods for water pipeline leak localization, noise will significantly affect the accuracy of localization, especially for the case that the noise intensity far exceeds the signal intensity, the traditional noise reduction methods will be ineffective. Therefore, an empirical mode decomposition and cross-correlation (EMD-CC) method for leak localization is proposed, which can adaptively extract effective leak signals from low signal-to-noise ratio (SNR) detection signals, and then can significantly improve the accuracy of localization. In this paper, the principle and steps of the algorithm are elaborated, and the effectiveness is verified in simulations and experiments. In the simulations, the SNR of the reconstructed signal −15 dB is dramatically increased to −6 dB. Compared with conventional noise reduction methods, the time-delay value estimation of EMD-CC is more accurate, more reliable, and more noise resistant. In full-size experiments, the accuracy of localization after processing is significantly improved.

Influence of a magnetic field on a nonlocal thermoelastic porous solid with memory-dependent derivative

AbstractA novel model of a nonlocal magneto-thermoelastic porous solid in the context of the three-phase-lag model with a memory-dependent derivative is introduced. The effect of a magnetic field on a nonlocal thermoelastic porous medium in the context of a three-phase-lag model with memory-dependent derivatives was studied. The normal mode analysis is used to solve the problem of an isothermal boundary to obtain the exact expressions of physical fields. The numerical results are represented to estimate the effects of the magnetic field, time delay, and the nonlocal parameter on the behavior of all of the field variables such as temperature, displacement, and stresses. Comparisons are given for the results in the absence and presence of the magnetic field as well as the locality. Comparisons are also given for the results for different values of time delay. To the best of the author’s knowledge, this model is reported for the first time. Some particular cases are also deduced from the present investigation.

Time Series Analysis on Flame Length of Micron Coal Dust Explosion with Ignition Delay Time

To discuss Pm variation law with t in large scale coal dust explosion equipment, shock wave pipe is used and a 60 m linear explosion test system is built. P m of dust explosion is measured by flame collection system. ARIMA (p,q,d) time series analysis model of t and P m is built, differential methods are used to eliminate upward trend of the maximum flame length data. By calculating the autocorrelation, the partial correlation coefficient, and the value of AIC and SBC, autoregression and moving average orders are got. Model parameters are estimated by least squares method. 20 groups of flame length prediction show that: ARIMA model have high precision, prediction value of optimum ignition delay time is consistent with measured value, which realizes reasonable analysis on fluctuation characteristics of P m. This model can reasonably predict the up and down fluctuations of the local flame length data, reflecting the superiority of the model, which is not achievable by general prediction models. The results of this study can greatly reduce the number of coal dust explosion tests, save material costs and provide a new idea for studying the relationship between ignition delay time and coal dust explosion flame length.

Analisi dell'ereditabilità delle proprietà contrattili: osservazioni su gemelli monozigoti campioni nazionali di atletica giovanile

Heritability estimates for various traits were previously obtained in large-scale twin studies as well as in genomic analyses, which have been used more frequently recently. The potential for heritability in studies of twin athletes has never been observed for tensiomyography (TMG)-derived contractile properties. Accordingly, the aim of this study was to investigate the hereditary capabilities (HC) of lower-limb contractile properties using a twin case study design performed on a pair of monozygotic (MZ) track and field youth champions from Croatia. The results showed high HC values for contraction time, time delay, and contraction velocity, which measure the absolute (Tc, Td) and relative (Vc) velocity of the lower limb muscles. Very high HC values of the listed contractile properties indicate a strong influence of heritability on selected, mainly velocity-related properties, whereas Td-variable related to the peripheral nervous system is the most affected. Second, the muscle morphology of vastus lateralis, vastus medialis, and rectus femoris also appears to be subject to a strong heritable influence. In conclusion, the HC estimates presented, together with the heritability coefficients, can be used as guidelines for talent identification processes, especially when combined with TMG, a suitable non-invasive alternative for estimating lower-limb contractile properties in adolescent athletes.

Ignition processes and characteristics of charring conductive polymers with a cavity geometry in precombustion chamber for applications in micro/nano satellite hybrid rocket motors

The arc ignition system based on charring polymers has advantages of simple structure, low ignition power consumption and multiple ignitions, which bringing it broadly application prospect in hybrid propulsion system of micro/nano satellite. However, charring polymers alone need a relatively high input voltage to achieve pyrolysis and ignition, which increases the burden and cost of the power system of micro/nano satellite in practical application. Adding conductive substance into charring polymers can effectively decrease the conducting voltage which can realize low voltage and low power consumption repeated ignition of arc ignition system. In this paper, a charring conductive polymer ignition grain with a cavity geometry in precombustion chamber, which is composed of PLA and multiwall carbon nanotubes (MWCNT) was proposed. The detailed ignition processes were analyzed and two different ignition mechanisms in the cavity of charring conductive polymers were revealed. The ignition characteristics of charring conductive polymers were also investigated at different input voltages, ignition grain structures, ignition locations and injection schemes in a visual ignition combustor. The results demonstrated that the ignition delay and external energy required for ignition were inversely correlated with the voltages applied to ignition grain. Moreover, the incremental depth of cavity shortened the ignition delay and external energy required for ignition while accelerated the propagation of flame. As the depth of cavity increased from 2 to 6 mm (at 50 V), the time of flame propagating out of ignition grain changed from 235.6 to 108 ms, and values of mean ignition delay time and mean external energy required for ignition decreased from 462.8 to 320 ms and 16.2 to 10.75 J, respectively. The rear side of the cavity was the ideal ignition position which had a shorter ignition delay and a faster flame propagation speed in comparison to other ignition positions. Compared to direct injection scheme, swirling injection provided a more favorable flow field environment in the cavity, which was beneficial to ignition and initial flame propagation, but the ignition position needed to be away from the outlet of swirling injector. At last, the repeated ignition characteristic of charring conductive polymers was also investigated. The ignition delay time and external energy required for ignition decreased with repeated ignition times but the variation was decreasing gradually.

Modal Transformation based Fault Location in Radial Distribution Network

This paper introduces the technique of fault distance estimation based on modal transformation and signal processing. The recorded faulted phase currents are applied to the Karrenbauer model transformation and these model component currents are decomposed into detail coefficients by the use of Daubechies wavelet, db6. The fault recorder installed at the terminal of the feeder records different time delays between the modal components. In order to find fault distance, the time delay values and modal components velocity are used in traveling wave theory. This paper compares two different conditions: the first condition does not use a modal transformation and the second condition uses a modal transformation. When using modal transformation conditions, three different coefficient levels (detail coefficient level 1 (D1); the combination of detail coefficient level 1+2 (D1+2) and the combination of detail coefficient level 1+2+3 (D1+2+3) ) are used to estimate the fault distance. Different fault types with different fault locations are created in MATLAB simulation.

Hopf Bifurcation in a Modified Leslie-Gower Two Preys One Predator Model and Holling Type II Functional Response with Harvesting and Time-Delay

In this paper, a modified Leslie-Gower two preys one predator model and Holling type II functional response with harvesting and time-delay were discussed. Model analysis is carried out by determining fixed points, then analyzing the stability of the fixed points and discussing the existence of the Hopf bifurcation. In some conditions that occur in nature indicate the occurrence of hunting of prey and predator species by humans. Therefore, this model is modified by adding the assumption that prey and predators are being harvested. Another modification given to the model is the use of time delays.The delay time term is for taking into account the case that the members of the predator species need time from birth to predation for being active predators. The first case is a model without time delay, it is obtained that 3 fixed points are unstable and 7 fixed points are stable. One of them is the interior fixed point tested with the Routh-Hurwitz criteria. The second case is a model with a delay time, the critical delay value is obained. Hopf bifurcation occurs when the delay time value is equal to the critical delay value and also fulfills the transversality condition. Observations on the model simulation are carried out by varying the value of the delay time. When the Hopf bifurcation occurs, the graph on the solution plane shows a constant oscillatory movement. If the value of the delay time given is less than the critical value of the delay, the controlled system solution goes to a balanced state. Then when the delay time value is greater than the critical delay value, the system solution continues to fluctuate causing an unstable system condition.

Shear-wave splitting perspectives from the intense aftershock sequence of Damasi – Tyrnavos

The area of Damasi-Tyrnavos (Thessaloniki, Central Greece), in the vicinity of Larissa, was characterized by low seismic activity during the last decades. Two strong earthquakes of Mw = 6.3 and Mw = 6.0 The area of Damasi – Tyrnavos (Thessaly, Central Greece), in the vicinity of Larissa, was characterized occurred in early March 2021, followed by an intense aftershock sequence, related to WNW-ESE to NW-SE oriented faulting. This sequence was recorded by a dense local seismological network that provided a rich dataset and a unique opportunity to investigate upper crust shear-wave splitting for the first time in the study area. A fully automated technique, employing the eigenvalues method and cluster analysis, was implemented to measure the fast shear-wave polarization direction and the time-delay between the two split-shear-waves. This procedure yielded 655 results of adequate quality grade at 9 stations, after analyzing 1602 events and applying strict selection criteria, including the shear-wave window. The measured directions revealed a complex upper crust anisotropic regime. WNW-ESE to NW-SE, in accordance both with the APE model, being parallel to the local 𝜎 Hmax direction, and the strike of the fault planes. On the other hand, stations at the central part exhibit NNW-SSE and NNE-SSW anisotropy directions. An interesting feature is that the two northern stations are characterized by larger normalized time-delay values, possibly related to the migration of seismicity to the north during the initial stage of the seismic sequence.

An improved method of global dynamics: Analyzing the COVID-19 model with time delays and exposed infection.

Considering the transmission characteristics of the coronavirus disease 2019 (COVID-19), there are certain time delays in the transition from susceptible individuals to exposed individuals after contact with exposed, symptomatically infected, and asymptomatically infected individuals. A COVID-19 model with time delays and exposed infection is developed and then the global dynamics of this model is investigated by an improved method; moreover, the numerical simulations are carried out. It is shown that the COVID-19-free equilibrium T0 is globally asymptotically stable (GAS) if and only if the control reproduction number Rc≤1, while T0 is unstable and the COVID-19 equilibrium T∗ is GAS if and only if Rc>1. The numerical results reveal that strengthening quarantine measures is helpful to control the COVID-19 epidemic in India. Furthermore, when Rc<1, the numbers of symptomatically infected, asymptomatically infected, and quarantined individuals eventually tend to the zero equilibrium state, and with the increase in the time delay, the three kinds of variables change faster and their peaks become larger; when Rc>1, the three kinds of variables eventually tend to the positive equilibrium state, which are oscillatory and the amplitudes of the oscillation enlarge as the value of time delay increases. The numerical results show that when Rc<1, the smaller the value of time delay, the smaller the final epidemic size. In short, the longer it takes time for susceptible individuals to transform exposed individuals, the harder COVID-19 will be controlled.

COMMERCIAL VOLTAGE INDICATOR AS A GAMMA RADIATION DETECTOR.

The paper analyses the possibility of commercial neon indicator lamp at low pressure application as a gamma radiation detector. The diode is most often used as an indicator in electrical switchers. The analysis was performed on the basis of experimental electrical breakdown time delay data as a function of relaxation time, applied voltage and gamma ray air kerma rate. It has been shown that the indicator can be used as a detector for relaxation time greater than 70ms. During this time period, a complete recombination/de-excitation of the particles formed during previous breakdown and subsequent self-sustaining discharge, which can further initiate next breakdown, takes place. It was also shown that gamma radiation leads to a significant reduction in electrical breakdown time delay for applied voltages close to indicator breakdown voltage. Based on the behavior of the dependence of the mean value of the electrical breakdown time delay on the gamma ray air kerma rate, it was shown that the indicator can be used very efficiently as a detector up to air kerma rate of $\textsf{2.3}\cdot \textsf{10}^{-\textsf{5}}$Gy/h, when the electrical breakdown time delay is measured for applied voltage 10% higher than the breakdown voltage.

Optimal Timing of Targeted Temperature Management for Post-Cardiac Arrest Syndrome: Is Sooner Better?

Targeted temperature management (TTM) is often considered to improve post-cardiac arrest patients' outcomes. However, the optimal timing to initiate cooling remained uncertain. This retrospective analysis enrolled all non-traumatic post-cardiac arrest adult patients with either out-of-hospital cardiac arrest (OHCA) or in-hospital cardiac arrest (IHCA) who received TTM from July 2015 to July 2021 at our hospital. The values of time delay before TTM and time to target temperature were divided into three periods according to optimal cut-off values identified using receiver operating characteristic curve analysis. A total of 177 patients were enrolled. A shorter time delay before TTM (pre-induction time) was associated with a lower survival chance at 28 days (32.00% vs. 54.00%, p = 0.0279). Patients with a longer cooling induction time (>440 minis) had better neurological outcomes (1.58% vs. 1.05%; p = 0.001) and survival at 28 days (58.06% vs. 29.25%; p = 0.006). After COX regression analysis, the influence of pre-induction time on survival became insignificant, but patients who cooled slowest still had a better chance of survival at 28 days. In conclusion, a shorter delay before TTM was not associated with better clinical outcomes. However, patients who took longer to reach the target temperature had better hospital survival and neurological outcomes than those who were cooled more rapidly. A further prospective study was warranted to evaluate the appropriate time window of TTM.

Vaccination games and imitation dynamics with memory

In this paper, we model dynamics of pediatric vaccination as an imitation game, in which the rate of switching of vaccination strategies is proportional to perceived payoff gain that consists of the difference between perceived risk of infection and perceived risk of vaccine side effects. To account for the fact that vaccine side effects may affect people's perceptions of vaccine safety for some period of time, we use a delay distribution to represent how memory of past side effects influences current perception of risk. We find disease-free, pure vaccinator, and endemic equilibria and obtain conditions for their stability in terms of system parameters and characteristics of a delay distribution. Numerical bifurcation analysis illustrates how stability of the endemic steady state varies with the imitation rate and the mean time delay, and this shows that it is not just the mean duration of memory of past side effects, but also the actual distribution that determines whether disease will be maintained in the population at some steady level, or if sustained periodic oscillations around this steady state will be observed. Numerical simulations illustrate a comparison of the dynamics for different mean delays and different distributions, and they show that even when periodic solutions are observed, there are differences in their amplitude and period for different distributions. We also investigate the effect of constant public health information campaigns on vaccination dynamics. The analysis suggests that the introduction of such campaigns acts as a stabilizing factor for endemic equilibrium, allowing it to remain stable for larger values of mean time delays.

Atmosphere air temperature forecasting using the honey badger optimization algorithm: on the warmest and coldest areas of the world

Precisely forecasting air temperature as a significant meteorological parameter has a critical role in environment quality management. Hence, this study employs a hybrid intelligent model for accurately monthly temperature forecasting for one to three times ahead in the hottest and coldest regions of the world. The hybrid model contains the artificial neural network (ANN) hybridized with the powerful hetaeristic Honey Badger Algorithm (HBA-ANN). The average mutual information (AMI) technique is employed to find the optimal time delay values for the temperature variable for different time horizons. Finally, the performance of the developed hybrid model is compared with the classical ANN and the Gene Expression Programming (GEP) using some statistical criteria, and the Taylor and scatter diagrams. Results indicated that in each time horizon, the HBA-ANN model with the lowest distance from observation points based on Taylor diagram, high values for NSE and R2, and low values for RMSE, MAE, and RSR outperformed the ANN and GEP models in both training and testing phases. Hence, using the Honey Badger Algorithm could increase the accuracy of the model. This model's precise performance supports the case for it to be employed to forecast other environmental parameters.

A new method for solving the mobile payment scheduling problem using harris hawks optimization algorithm during the COVID-19 pandemic

The Coronavirus Disease 2019 (COVID-19) epidemic is causing once-in-a-century upheavals in global civilization. Payment systems have advanced lately, from simple cash or credit card transactions to various forms of mobile payment systems. This transformation is occurred due to COVID 19 and shifts in the economy, the growth of social networks, technical advancements on the Internet, and the increased usage of mobile devices. Throughout COVID19, this article offers a unique approach to the payment scheduling issue, which seeks out a timetable that enhances the project's stakeholders' benefit. Both the sponsor and the contractor in a project want to have a strong payment plan on their own. To create an equal schedule between the sponsor and the development team, the timing of payments and the completion periods of project activities are decided concurrently. The Harris hawks optimization method is designed to tackle the problem because of its high NP-hardness. Harris hawks optimization is a novel meta-heuristic nature-inspired optimizer inspired by how Harris hawks hunt food in nature. By comparing the suggested Harris hawks optimization optimizer to existing nature-inspired methods, the efficacy of the suggested Harris hawks optimization optimizer is determined. The Harris hawks optimization algorithm appears to be highly promising based on the statistical findings and comparisons. The MATLAB simulator's simulation findings confirm the algorithm's superiority over earlier efforts regarding energy, cost, delay time, and net value.