System Parameters Research Articles

Centralized exhaust system simulation and parameter optimization

With the increase in high-rise buildings in cities, public flue exhaust systems have a direct impact on residential air quality and the living environment. Although existing studies have analyzed the problems in public flue exhaust systems through computational fluid dynamics (CFD) numerical simulations and experimental tests, these studies often lack an in-depth exploration of the specific impacts of individual components in the system. To solve this problem, this study not only thoroughly analyzes the key components in the public flue system, such as branch pipes, check valves, and tee pipes, but also develops a parametric public flue simulation system software based on C# and verifies the accuracy of the simulation through experiments. The study first determines the key parameters affecting the comprehensive resistance coefficient of the branch pipe, check valve, tee pipe, and other components through CFD simulation and experimental testing. Subsequently, a visualization program is developed using the C# language, which can quickly simulate and visualize the flow changes in the flue according to different building parameters such as the number of floors, height of floors, and size of the flue. The results confirm that the program can efficiently predict the flow distribution under different design options, providing a practical tool for the optimal design and performance evaluation of public flues, which is important for improving the air quality of the living environment.

Secure IRS-assisted Energy Scavenging NOMA Impaired by Realistic Factors

Intelligent reflective surface (IRS)-assisted energy scavenging (ES) non-orthogonal multiple access (NOMA) with jamming (sIEnoma) is promising for high spectral efficiency, energy efficiency, information security, and communication reliability. Nonetheless, practical imperfections, such as channel state information imperfection (CSIi), hardware imperfection (HWi), fading severity, and nonlinear energy scavenging (nlES) impact scavenged energy, information security, and communication reliability of sIEnoma. Accordingly, this paper proposes performance analysis for sIEnoma under these imperfections to quickly assess its potentials without time-consuming simulations. Results show that imperfections (HWi, CSIi, fading severity, nlES) and specifications (IRS, NOMA) significantly impact performance of sIEnoma. Nevertheless, proper adoption of power splitting factor, desired data rate, HWi level, and time switching coefficient can hinder complete outage in sIEnoma. Additionally, optimal metrics are achieved by configuring system parameters properly. Moreover, the proposed sIEnoma outperforms its baseline (IRS-assisted ES orthogonal multiple access with jamming).

Explicit formulas for the asymptotic variance of a linearized model of a Gaussian disturbance driven power system with a uniform damping-inertia ratio

Serious fluctuations caused by disturbances may lead to instability of power systems. With the disturbance modeled by a Brownian motion process, the fluctuations are often described by the asymptotic variance at the invariant probability distribution of an associated Gaussian stochastic process. Here, we derive the explicit formula of the variance matrix for the system with a uniform damping-inertia ratio at all the nodes, which enables us to analyze the influences of the system parameters on the fluctuations and investigate the fluctuation propagation in the network. With application to systems with complete graphs and star graphs, it is found that the variance of the frequency at the disturbed node is significantly bigger than those at all the other nodes. It is also shown that adding new nodes may prevent the propagation of fluctuations from the disturbed node to all the others. Finally, it is proven theoretically that larger line capacities accelerate the propagation of the frequency fluctuation and larger inertia of synchronous machines help suppress the fluctuations of the phase differences, however, these acceleration and suppression are quite limited.

Application of Artificial Intelligence Technology in Optimizing Control Parameters of Traffic Signal Group Systems

Application of Artificial Intelligence Technology in Optimizing Control Parameters of Traffic Signal Group Systems

USE OF IIoT TECHNOLOGIES IN ENGINE MONITORING AND CONTROL SYSTEMS

Determining the operating parameters of engine systems is very important to ensure its long-term reliability. Modern power plants use a large number of modern electronic components (sensors, controllers, etc.). All systems generate a huge volume of data that must be tracked, processed and analyzed, which in turn creates calls to gateways and servers. However, the current state of development of microcontrollers and their power allow the use of fog computing, which can lead to more efficient use of both the power plant and data transmission systems. Also, the use of modern microcontrollers and fog computing allows modernizing old power plants with minimal effort and creating new information nodes for monitoring the state of nodes and engine systems and easily combining them with systems already existing on the engine. The selection of a microcontroller and justification of its type for the modernization of the fuel system of a diesel engine are considered. Rapid processes occur in the high-pressure fuel system of diesel engines, which can be determined by changes in fuel pressure. For detailed measurement of processes in the fuel system, measurements should be made with a frequency of at least 24 kHz, i.e.: if the crankshaft rotation frequency is 4000 min-1, then 24,000 measurements should be made every second (when registering data after 1 degree of crankshaft rotation). Another indicator that imposes its requirements is the bit rate of the analog-to-digital converter (ADC), which depends on the range of recorded values. For example, an ADC with a resolution of 8 bits is capable of outputting 256 discrete values (0…255). That is, the higher the bit rate, the more sensitive the converter is to signal changes, and 8 bits may not be enough. Thus, even a small number of sensors can generate a huge amount of data. Transmitting large amounts of data is irrational and can lead to data loss and "clogging" of transmission channels, which challenges the computational performance of the microprocessor.

Utilizing fractional derivatives and sensitivity analysis in a random framework: a model-based approach to the investigation of random dynamics of malware spread

In this study, an ordinary-deterministic equation system modeling the spread dynamics of malware under mutation is analyzed with fractional derivatives and random variables. The original model is transformed into a system of fractional-random differential equations (FRDEs) using Caputo fractional derivatives. Normally distributed random variables are defined for the parameters of the original system that are related to the mutations and infections of the nodes in the network. The resulting system of FRDEs is simulated using the predictor-corrector method based fde12 algorithm and the forward fractional Euler method (ffEm) for various values of the model components such as the standard deviations, orders of derivation, and repetition numbers. Additionally, the sensitivity analysis of the original model is investigated in relation to the random nature of the components and the basic reproduction number (R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$R_{0}$\\end{document}) to underline the correspondence of random dynamics and sensitivity indices. Both the normalized forward sensitivity indices (NFSI) and the standard deviation of R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$R_{0}$\\end{document} with random components give matching results for analyzing the changes in the spread rate. Theoretical results are backed by the simulation outputs on the numerical characteristics of the fractional-random model for the expected number of infections and mutations, expected timing of the removal of mutations from the network, and measurement of the variability in the results such as the coefficients of variation. Comparison of the results from the original model and the fractional-random model shows that the fractional-random analysis provides a more generalized perspective while facilitating a versatile investigation with ease and can be used on different models as well.

Utilizing Photometry from Multiple Sources to Mitigate Stellar Variability in Precise Radial Velocities: A Case Study of Kepler-21

We present a new analysis of Kepler-21, the brightest (V = 8.5) Kepler system with a known transiting exoplanet, Kepler-21 b. Kepler-21 b is a radius valley planet (R = 1.6 ± 0.2R ⊕) with an Earth-like composition (8.38 ± 1.62 g cm–3), though its mass and radius fall in the regime of possible “water worlds.” We utilize new Keck/High-Resolution Echelle Spectrometer and WIYN/NEID radial velocity (RV) data in conjunction with Kepler and Transiting Exoplanet Survey Satellite (TESS) photometry to perform a detailed study of activity mitigation between photometry and RVs. We additionally refine the system parameters, and we utilize Gaia astrometry to place constraints on a long-term RV trend. Our activity analysis affirms the quality of Kepler photometry for removing correlated noise from RVs, despite its temporal distance, though we reveal some cases where TESS may be superior. Using refined orbital parameters and updated composition curves, we rule out a water world scenario for Kepler-21 b, and we identify a long-period super-Jupiter planetary candidate, Kepler-21 (c).

Influence of thermal bath on Pancharatnam-Berry phase in an accelerated frame

A uniformly accelerated atom captures Pancharatnam-Berry phase in its quantum state and the phase factor depends on the vacuum fluctuation of the background quantum fields. We observe that the thermal nature of the fields further affects the induced phase. Interestingly the induced phase captures the exchange symmetry between the Unruh and real thermal baths. This observation further supports the claim that the Unruh thermal bath mimics a real thermal bath. Moreover for certain values of system parameters and at high temperature, the phase is enhanced compared to zero temperature situation. However the required temperature to observe the phase experimentally is so high that the detection of Unruh effect through this is not possible within the current technology.

View Factors Approach for Bifacial Photovoltaic Array Modeling: Bifacial Gain Sensitivity Analysis

Abstract Bifacial modules, highly valued in the global photovoltaic market since they are able to receive sunlight from both sides, generating up to 10-30% additional energy. They are integrated into various sectors, including building and notably Agrivoltaics. In this work, a coupled optical-thermal-electrical model was developed in MATLAB to simulate the energy performance and bifacial gain for a ground raised bifacial system. The model allows optimization as a function of PV system and bifacial module characteristics. A fixed, south-facing bifacial PV arrays composed of three rows assumed to be installed in Agadir, Morocco. The optical model is based on an analytical determination of view factors using the cross-string rule. These enable evaluation of irradiances received by both sides of modules, which are subsequently used to evaluate the energy yield of the system. Model validation was carried out based on various statistical error tests by comparing the results with simulation results generated by various softwares. The comparison shows a height accuracy, notably with 3DbifacialVF (R2 1, RMSE 0.03W/m2 and R2 0.96, RMSE 12.4 W/m2) for front and rear side irradiance respectively. The DC energy generated by the system differs by less than 1% compared to PVsyst results. Sensitivity analysis revealed that all system parameters, particularly ground albedo, positively affect the bifacial gain. The bifacial gain increased from 10.6% to 20.1% as the ground albedo increased from 0.25 to 0.5.

The process optimization and exergy efficiency analysis for biogas to renewable hydrogen by chemical looping technology

The study on biogas-Chemical Looping Hydrogen Production (biogas-CLHP) highlights its potential to produce high-purity hydrogen with recycling waste bioenergy. It delves into the gas-solid reaction characteristics and optimizes crucial process parameters for the fixed-bed CLHP system. Movement rate equations for the reaction fronts of Fe2O3-Fe3O4 (Rf1), Fe3O4-FeO (Rf2), and FeO-Fe (Rf3) are formulated, aiding in clarifying CO breakthrough curves. The identified convergence temperatures (Tm) under CO and H2 atmospheres are 916 °C and 907 °C, respectively. Rf1 and Rf2 converged above Tm, which leads to the disappearance of the Fe3O4 region in oxygen carrier (OC) beds. A theoretical model for calculating the reduction solid conversion (Xaver) is established, accurately characterizing Xaver under varying reaction times, H2/CO ratios, and temperatures. By using the Particle Swarm Optimization (PSO) algorithm and thermodynamic analysis, the study determines the optimal length-radius ratio (L/r), reduction temperature (T), and H2/CO ratio (α) for the OC bed as 12.5, 916 °C, and 0.72, respectively, at which a maximum conversion ratio of 43.55 % is achieved. Based on optimal parameters, the results of Aspen simulation reveal energy and exergy efficiencies of 74.9 % and 70.8 %. Generally, this research comprehensively outlines the process dynamics, optimizes key parameters, and evaluates exergy efficiency of the biogas-CLHP system.

Time-dependent uniform upper semicontinuity of pullback attractors for non-autonomous delay dynamical systems: Theoretical results and applications

In this paper we provide general results on the uniform upper semicontinuity of pullback attractors with respect to the time parameter for non-autonomous delay dynamical systems. Namely, we establish a criteria in terms of the multi-index convergence of solutions for the delay system to the non-delay one, locally pointwise convergence and local controllability of pullback attractors. As an application, we prove the upper semicontinuity of pullback attractors for a non-autonomous delay reaction-diffusion equation to the corresponding nondelay one over any bounded time interval as the delay parameter tends to zero.

System Structural Error Analysis in Binocular Vision Measurement Systems

A binocular stereo vision measurement system is widely used in fields such as industrial inspection and marine engineering due to its high accuracy, low cost, and ease of deployment. An unreasonable structural design can lead to difficulties in image matching and inaccuracies in depth computation during subsequent processing, thereby limiting the system’s performance and applicability. This paper establishes a systemic error analysis model to enable the validation of changes in structural parameters on the performance of the binocular vision measurement. Specifically, the impact of structural parameters such as baseline distance and object distance on measurement error is analyzed. Extensive experiments reveal that when the ratio of baseline length to object distance is between 1 and 1.5, and the angle between the baseline and the optical axis is between 30 and 40 degrees, the system measurement error is minimized. The experimental conclusions provide guidance for subsequent measurement system research and parameter design.

The impact of isoflurane anesthesia on brain metabolism in mice: An MRI and electroencephalography study.

Isoflurane is one of the most widely used anesthetic agents in rodent imaging studies. However, the impact of isoflurane on brain metabolism has not been fully characterized to date, primarily due to a scarcity of noninvasive technologies to quantitatively measure the brain's metabolic rate in vivo. In this study, using noncontrast MRI techniques, we dynamically measured cerebral metabolic rate of oxygen (CMRO2) under varying doses of isoflurane anesthesia in mice. Concurrently, systemic parameters of heart and respiration rates were recorded alongside CMRO2. Additionally, electroencephalogram (EEG) recording was used to identify changes in neuronal activities under the same anesthetic regimen employed in the MRI experiments. We found suppression of the CMRO2 by isoflurane in a dose-dependent manner, concomitant with a diminished high-frequency EEG activity. The degree of metabolic suppression by isoflurane was strongly correlated with the respiration rate, which offers a potential approach to calibrate CMRO2 measurements. Furthermore, the metabolic level associated with neural responses of the somatosensory and motor cortices in mice was estimated as 308.2μmol/100 g/min. These findings may facilitate the integration of metabolic parameters into future studies involving animal disease models and anesthesia usage.

Enhanced Model Predictive Control Using State Variable Feedback for Steady-State Error Cancellation.

The rapid dynamic responses of predictive control algorithms are widely acknowledged. However, achieving accurate steady-state reference tracking hinges not just on a precise mathematical model of the system but also on its parameters. This document presents a predictive control scheme augmented with integral state feedback tailored to a photovoltaic (PV) application. In scenarios with uncertain system parameters, steady-state errors can particularly impact reactive power regulation, where the absence of an integral term in the loop exacerbates this issue. The robustness and sensitivity of both predictive control and the proposed enhanced predictive controller are thoroughly examined. Simulation and experimental results are included to validate the effectiveness of this approach.

Intrinsically safe DAB converter for reliable power supply in harsh environment via extended phase shift pulse train control

AbstractIn this article, an extended‐phase‐shift‐based pulse train control (EPS‐PT) for an intrinsically safe dual active bridge (DAB) converter is proposed to satisfy the safe and reliable power supply in harsh environments such as gas stations, chemical plants, and mining tunnels in complex power systems. A discrete pulse switching control method is introduced, and the input voltage and output current are sampled to calculate the primary target phase shift angle of the DAB converter, followed by the inner phase shift angle, while the secondary phase shift angle is rapidly adjusted by the voltage feedback. In order to meet the requirements of effective control and safe power supply in harsh environments, the system parameters are designed by comprehensively considering the control performance and intrinsically safe requirements. The simulation and experimental results demonstrate that the proposed DAB converter exhibits rapid dynamic response and intrinsic operation safety.

Association of body composition and systemic inflammation for patients with locally advanced cervical cancer following concurrent chemoradiotherapy

Systemic inflammation and body composition are associated with survival outcomes of cancer patients. This study aimed to examine the combined prognostic value of systemic inflammatory markers and body composition parameters in patients with locally advanced cervical cancer (LACC). Patients who underwent concurrent chemoradiotherapy (CCRT) for LACC at a tertiary referral teaching hospital between January 2010 and January 2018 were enrolled. A predictive model was established based on systemic immune-inflammation index (SII) and computer tomography-derived visceral fat-to-muscle ratio (vFMR). Overall survival (OS) and progression-free survival (PFS) were assessed using the Kaplan-Meier method and Cox regression models. The model performance was assessed using discrimination, calibration, and clinical usefulness. In total, 212 patients were enrolled. The SII and vFMR were closely related, and both independently predicted survival (P < 0.05). A predictive model was established based on the above biomarkers and included three subgroups: high-risk [both high SII (>828) and high vFMR (>1.1)], middle-risk (either high SII or high vFMR), and low-risk (neither high SII nor high vFMR). The 3-year OS (PFS) rates for low-, middle-, and high-risk patients were 90.5% (86.0%), 73.9% (58.4%), and 46.8% (36.1%), respectively (P < 0.05). This model demonstrated satisfactory predictive accuracy (area under the curve values for predicting 3-year OS and PFS were 0.704 and 0.718, respectively), good fit (Hosmer-Lemeshow tests: P > 0.05), and clinical usefulness. Systemic inflammatory markers combined with body composition parameters could independently predict the prognosis of patients with LACC, highlighting the utilization of commonly collected indicators in decision-making processes. The SII and vFMR, as well as their composite indices, were promising prognostic factors in patients with LACC who received definitive CCRT. Future studies are needed to explore novel therapies to improve the outcomes in high-risk patients.

A Novel Single-Stage Boost Single-Phase Inverter and Its Composite Control Strategy to Suppress Low-Frequency Input Ripples

Low-frequency pulsating ripples exist on the input side of a single-phase inverter, which bring some adverse effects and harm to the inverter and photovoltaic power generation system. In order to suppress the low-frequency pulsating ripple and reduce the filter circuit parameters, a novel single-stage boost single-phase inverter is proposed, which can suppress low-frequency ripple. And a three-closed-loop compound control strategy that can suppress input low-frequency ripples under the limitation of an energy storage inductor current and buffer capacitor voltage is proposed. The circuit topology, control strategy, key circuit parameters design, system modeling, and simulation of the inverters are deeply analyzed and studied. Simulation and experimental results show that the inverter has a good ability to suppress input low-frequency ripples.

AEEFCSR: an adaptive ensemble empirical feed-forward cascade stochastic resonance system for weak signal detection

Abstract A novel adaptive ensemble empirical feed-forward cascade stochastic resonance (AEEFCSR) method is proposed in this study for the challenges of detecting target signals from intense background noise. At first, we create an unsaturated piecewise self-adaptive variable-stable potential function to overcome the limitations of traditional potential functions. Subsequently, based on the foundation of a feed-forward cascaded stochastic resonance method, a novel weighted function and system architecture is created, which effectively addresses the issue of low-frequency noise enrichment through ensemble empirical mode decomposition. Lastly, inspired by the spider wasp algorithm and nutcracker optimization algorithm, the spider wasp nutcracker optimization algorithm is proposed to optimize the system parameters and overcome the problem of relying on manual experience. In this paper, to evaluate its performance, the output signal-to-noise ratio (SNR), spectral sub-peak difference, and time-domain recovery capability are used as evaluation metrics. The AEEFCSR method is demonstrated through theoretical analysis. To further illustrate the performance of the AEEFCSR method, Validate the adoption of multiple engineering datasets. The results show that compared with the compared algorithms, the output SNR of the AEEFCSR method is at least 6.2801 dB higher, the spectral subpeak difference is more than 0.25 higher, and the time-domain recovery effect is more excellent. In summary, the AEEFCSR method has great potential for weak signal detection in complex environments.

Restoring Adiabatic State Transfer in Time-Modulated Non-Hermitian Systems.

Non-Hermitian systems have attracted much interest in recent decades, driven partly by the existence of exotic spectral singularities, known as exceptional points (EPs), where the dimensionality of the system evolution operator is reduced. Among various intriguing applications, the discovery of EPs has suggested the potential for implementing a symmetric mode switch, when encircling them in a system parameter space. However, subsequent theoretical and experimental works have revealed that dynamical encirclement of EPs invariably results in asymmetric mode conversion; namely, the mode switching depends only on the winding direction but not on the initial state. This chirality arises from the failure of adiabaticity due to the complex spectrum of non-Hermitian systems. Although the chirality revealed has undoubtedly made a significant impact in the field, a realization of the originally sought symmetric adiabatic passage in non-Hermitian systems with EPs has since been elusive. In this work, we bridge this gap and theoretically demonstrate that adiabaticity, and therefore a symmetric state transfer, is achievable when dynamically winding around an EP. This becomes feasible by specifically choosing a trajectory in the system parameter space along which the corresponding evolution operator attains a real spectrum. Our findings, thus, offer a promise for advancing various wave manipulation protocols in both quantum and classical domains.

Investigation on the unsteady aerodynamic performance of the Drela AG 08 and Boeing B29 airfoils subjected to heaving motion

This article aims to investigate the unsteady flow characteristics of Drela AG08 and Boeing B29 airfoils when subjected to heaving motion. The influence of heave amplitude, heave frequency in terms of instantaneous force coefficients of the airfoil is investigated at Re = 5 × 104. Furthermore, the flow field investigations were carried out to analyze the Leading Edge Vortex (LEV) formation and its convection airfoil’s suction side. From the findings, a variation in the oscillation amplitude of force coefficients was observed and a non-sinusoidal behavior was also noticed. Additionally, a remarkable change in the instantaneous force coefficients (both qualitatively and quantitatively) is also observed with respect to the slight change in aforementioned parameters. A transition in the wake pattern from drag inducing to thrust producing is observed under certain conditions. It is observed that the flow separates at the leading edge by forming LEV on both airfoil’s suction side and pressure side. It is also noticed that whenever the flow departs the trailing edge, these vortices convect downstream of the airfoil and form alternating pattern of coherent vortices. With the increase in number of cycles, these vortices interfere with the previously shed vortices and affects the airfoil’s aerodynamic characteristics. From the investigations, it is observed that, by controlling the system parameters, the adverse effects of the LEV can be minimized.