Steady-state Case Research Articles

Dynamics of water pollution concentration with uniform and exponential increment of pollutants

The study focuses on the one dimensional Advection-Dispersion Equation (ADE) to study the dynamics of concentration of water pollution when the pollutants at the source is increasing uniformly and exponentially. Analytical solutions are obtained by using Laplace transform and numerical solutions are by Finite Difference Method (FDM). The steady state case is studied. The dynamics of pollution concentration along the length of river channel are studied through two dimensional plots by varying the rate of added pollutants, cross sectional area of river and water flow velocity. The pollution concentration decreases along the length of river (downstream) for each analysis. The analytical and numerical solutions are shown in three dimensional plots. The analytical and numerical solutions are compared with the help of relative error. The relative errors calculated for uniform and exponential increment of pollutants at the source are compared while studying the dynamics of the concentration. The environmental and chemical engineering may substantially benefit from such studies.

Actuator fault diagnosis and severity identification of turbofan engines for steady-state and dynamic conditions

Actuator faults can be critical in turbofan engines as they can lead to stall, surge, loss of thrust and failure of speed control. Thus, fault diagnosis of gas turbine actuators has attracted considerable attention, from both academia and industry. However, the extensive literature that exists on this topic does not address identifying the severity of actuator faults and focuses mainly on actuator fault detection and isolation. In addition, previous studies of actuator fault identification have not dealt with multiple concurrent faults in real time, especially when these are accompanied by sudden failures under dynamic conditions. This study develops component-level models for fault identification in four typical actuators used in high-bypass ratio turbofan engines under both dynamic and steady-state conditions and these are then integrated with the engine performance model developed by the authors. The research results reported here present a novel method of quantifying actuator faults using dynamic effect compensation. The maximum error for each actuator is less than 0.06% and 0.07%, with average computational time of less than 0.0058 s and 0.0086 s for steady-state and transient cases, respectively. These results confirm that the proposed method can accurately and efficiently identify concurrent actuator fault for an engine operating under either transient or steady-state conditions, even in the case of a sudden malfunction. The research results demonstrate the potential benefit to emergency response capabilities by introducing this method of monitoring the health of aero engines.

Optimizing the Design of Container House Walls Using Argon and Recycled Plastic Materials

Interest in the use of container houses has been increasing in recent years because of their resistance to earthquakes and fires. The incorporation of recyclable materials into these houses will simultaneously reduce energy use and greenhouse gas emission rates. In this context, the thermal performance of an external multi-layer wall of a container house mostly made of recyclable materials is studied and compared to that of a normal wall. The current study proposes a completely new structure, where there are air gaps and plastic layers between the steel sheets to enhance thermal insulation. In these gaps, different gases including argon are tested to reduce the heat loss. Calculations are carried out for a steady-state case in the winter season using the student version of ANSYS 2023 R2 Academic software, and the heat loss is calculated for different materials and different thicknesses of the wall layers. Afterward, based on a life-cycle cost analysis, the optimum air gap materials, optimum thickness of plastic and air gap, and energy savings are determined for a period of 20 years. We found that the optimum number of plastic layers to minimize the heating load is 21, but this reduces to 11 when considering economic factors. Furthermore, if a reflective layer covers the plastic layer, the optimum is just one layer. For an insulation thickness of 2 cm, the maximum total life-cycle savings are 335.14 and 350.52 USD, respectively, and the minimum ones are 16.06 and 31.44 USD, respectively, for multi-layer walls with and without reflective layers compared to conventional walls.

Charge Transport Characteristics in Doped Organic Semiconductors Using Hall Effect

Numerical computations through the finite element method (FEM) are used to determine the impact of doping on carrier concentration and recombination between charges in time for organic semiconductor diodes having low mobility. The Hall effect is used to determine the effects of doping on the performance and reliability of organic semiconductor devices by accurately modeling these processes. In this work, the number density of charge carriers and Hall voltages are computed for n-type doped semiconductors with two different recombination processes, such as non-Langevin and Langevin-type. The findings reveal that in the Langevin system with β′=1, the number density of charge carriers is almost five and four times lower compared with the non-Langevin system with β′=0.01 for increasing dopant concentrations of Npd = 1 and 3, respectively. The Langevin system also had lower Hall voltages than the steady-state and non-Langevin systems for different magnetic fields with dopants, and the non-Langevin system had nearly identical Hall voltages as the steady-state case. The outcome of the current work provides insights into charge transportation mechanisms in low-mobility doped organic semiconductors with Hall effect measurements to improve device efficiency.

Wind-induced vibration energy harvesters under base excitation: Analytical and numerical analysis

In this paper, analytical analysis of a wind-induced vibration energy harvester used for the bacterial disinfection of water is mainly considered. The complexification-averaging (CA) method is utilized to analytically calculate the results of the harvester, the model equations of the harvester satisfied are reduced into a set of complex variable equations. The relationship between the displacement amplitude and voltage amplitude is derived under the steady-state case. The amplitudes and phases of both the displacement and voltage are obtained. The analytical solutions of the harvester are then verified by direct numerical simulation. The response mechanism under different parameters is discussed. The frequency island and multi-valued phenomena are found. Meanwhile, it is found that a higher wind speed corresponds to a larger displacement amplitude and voltage. In addition, the RMS voltage and average power are studied. Both have the same variation rules under different excitation amplitudes. Under the same coupling coefficient, load resistance and piezoelectric patch capacitance, the lower the frequency, the easier it is to obtain the larger voltage output. However, the load resistance has the opposite effect on both of them. Finally, to obtain maximum output in a wider frequency region, the optimization and choice of the parameters is studied, and the critical boundary can be identified.

Design of reduced-order observer based steady state optimal linear-quadratic feedback controllers

In this paper we formulate and solve a problem encountered in engineering applications when a linear-quadratic (LQ) optimal feedback controller uses state estimates obtained via a reduced-order observer. Due to the use of state estimates instead of the actual state variables, the optimal quadratic performance is degraded in a pretty complex manner. In the paper, we show how to find the exact formula for the optimal performance degradation (optimal performance loss) in linear time invariant systems for the steady state case (infinite horizon optimization problem). The optimal performance loss is obtained in terms of solution of a reduced-order algebraic Lyapunov equation whose dimension is equal to the dimension of the reduced-order observer. The quantities that impact the performance criterion loss are identified. Practical examples (an inverted pendulum on a cart and an aircraft) show that the optimal performance loss can be very significant in some applications, and even very high in the presented linear-quadratic optimal control of an inverted pendulum problem. We have shown, using the derived formula, how the optimal performance loss can be considerably reduced by properly choosing the reduced-order observer initial conditions via the least square method.

Modified exponentially weighted moving average control chart for monitoring process dispersion

The exponentially weighted moving average ( EWMA ) charts are widely used memory-type charts for monitoring small to moderate shifts in process parameters. However, the performance of the EWMA chart has been improved over time due to various modifications and enhancements. This paper proposes two modified EWMA ( M ‐ EWMA ) charts to monitor process dispersion. The upper-sided modified EWMA chart is denoted by M ‐ EWMA U , while a lower-sided modified EWMA chart is symbolized as the M ‐ EWMA L chart. Monte Carlo simulations determine the proposed schemes’ run length (RL) properties in zero- and steady-state scenarios. The proposed upper- and lower-sided M ‐ EWMA charts are compared to the upper- and lower-sided CH ‐ EWMA and SJ-EWMA charts. The comparisons reveal that the proposed M-EWMA charts have better detection ability than the upper- and lower-sided CH-EWMA, and SJ-EWMA charts, respectively. Finally, a real-life application is provided to illustrate the implementation of the upper-sided M-EWMA and CH-EWMA charts practically in both zero-state and steady-state cases.

Insulin resistance and glucose homeostasis in Egyptian children with sickle cell anemia

Background A single gene mutation produces sickle cell anemia (SCA), an autosomal recessive illness. The body can keep the glycemic state in normal range via various mechanisms depending mainly on pancreatic hormones. Aim Evaluation of glucose homeostasis and insulin resistance in a group of Egyptian sickle cell children. Patients and methods This cross-sectional comparative study was carried out on 80 participants aged from 5 to 16 years old of both sexes, 40 patients with sickle cell hemoglobinopathies and in a steady state (case group), and 40 healthy individuals as control (control group). Fasting blood glucose, fasting serum insulin, glycosylated hemoglobin were measured in all participants, and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) was calculated. Serum fructosamine (SF) was measured in the cases group. Results Glucose homeostasis was kept normal in most patients with only 10% of them showed abnormal glycemia. HOMA–IR was significantly different between the two groups with 15% of patients had pathological HOMA-IR. The study found a strong positive correlation (r=0.479, <0.001) between the HOMA-IR and the frequency of vaso-occlusive crisis per year before participants were recruited and between SF and fasting blood glucose (r=0.772, <0.001). On comparing glycosylated hemoglobin between both groups there was no statistically significant difference between both groups (P value = 0.874) Conclusions and recommendations Normal glucose homeostasis was proved in the majority of patients. Insulin resistance was detected in a limited number of sickle cell anemia patients. Follow-up of glucose homeostasis is indicated in sickle cell cases.

The exponentiated exponentially weighted moving average control chart

Memory-type control charts are widely used for monitoring small to moderate shifts in the process parameter(s). In the present article, we present an exponentiated exponentially weighted moving average (Exp-EWMA) control chart that weights the past observations of a process using an exponentiated function. We evaluated the run-length characteristics of the Exp-EWMA chart via Monte Carlo simulations. A comparison study versus the CUSUM, EWMA and extended EWMA (EEWMA) charts under similar in-control (IC) run-length properties demonstrates that the Exp-EWMA chart is more effective for detecting small and, under certain circumstances, moderate shifts for both the zero-state and steady-state cases. Moreover, the Exp-EWMA chart has better zero-state out-of-control (OOC) performance than an EWMA chart with smoothing parameter equal to the limit to the infinity of the exponentiated function, while the two charts perform similarly for the steady-state case. Finally, it is shown that the Exp-EWMA chart is more IC robust than its competitors under several non-normal distributions. Two examples are provided to explain the implementation of the proposed chart

Computation of mRNA Number Distributions in Interactive Pathway Stochastic Gene Transcription Model

Gene expression is a stochastic process characterized by fluctuations in the amount of mRNA in individual cells of an isogenic cell population. The fluctuation can be characterized by the mRNA number distribution Pm (t) , which denotes the probability of producing m copies of mRNA molecules in one cell at time t. For a given stochastic gene transcription model, how to solve the corresponding Pm (t) exact expression has been a hot research topic in this field. In the existing work, most of the results are solved for Pm (t) in the steady state case or in a specific parameter region, which affects us to fully understand the kinetic effects of different stochastic gene regulation patterns on the distribution of mRNA quantities. In this thesis, we explore the computation of Pm (t) for the cross-talk pathway model and give its exact expression under arbitrary system parameter conditions. The interactive signaling pathway model is successfully applied to elaborate stochastic transcription data of inducible genes in response to environmental changes. This work provides a kinetic theoretical basis for us to further investigate the interactive signaling pathway regulatory mechanism of gene transcription.

Response Time of Queueing Mechanisms

We study response time, a key performance characteristic of queueing mechanisms. The studied model incorporates both active and passive queue management, arbitrary service time distribution, as well as a complex model of arrivals. Therefore, the obtained formulas can be used to calculate the response time of many real queueing mechanisms with different features, by parameterizing adequately the general model considered here. The paper consists of two parts. In the first, mathematical part, we derive the distribution function for the response time, its density, and the mean value. This is done by constructing two systems of integral equations, for the distribution function and the mean value, respectively, and solving these systems with transform techniques. All the characteristics are derived both in the time-dependent and steady-state cases. In the second part, we present numerical values of the response time for a few system parameterizations and point out several of its properties, some rather counterintuitive.

Shear-Relative Asymmetric Kinematic Characteristics of Intensifying Hurricanes as Observed by Airborne Doppler Radar

Abstract While recent observational studies of intensifying (IN) versus steady-state (SS) hurricanes have noted several differences in their axisymmetric and asymmetric structures, there remain gaps in the characterization of these differences in a fully three-dimensional framework. To address these limitations, this study investigates differences in the shear-relative asymmetric structure between IN and SS hurricanes using airborne Doppler radar data from a dataset covering an extended period of time. Statistics from individual cases show that IN cases are characterized by peak wavenumber-1 ascent concentrated in the upshear-left (USL) quadrant at ∼12-km height, consistent with previous studies. Moderate updrafts (2–6 m s−1) occur more frequently in the downshear eyewall for IN cases than for SS cases, likely leading to a higher frequency of moderate to strong updrafts USL above 9-km height. Composites of IN cases show that low-level outflow from the eye region associated with maximum wavenumber-1 vorticity inside the radius of maximum wind (RMW) in the downshear-left quadrant converges with low-level inflow outside the RMW, forming a stronger local secondary circulation in the downshear eyewall than SS cases. The vigorous eyewall convection of IN cases produces a net vertical mass flux increasing with height up to ∼5 km and then is almost constant up to 10 km, whereas the net vertical mass flux of SS cases decreases with height above 4 km. Strong USL upper-level ascent provides greater potential for the vertical development of the hurricane vortex, which is argued to be favorable for continued intensification in shear environments.

On the performance and comparison of various memory-type control charts

Several versions of the exponentially weighted moving average (EWMA) control chart, such as the generally weighted moving average (GWMA), the double, triple, and quadruple EWMA (DEWMA, TEWMA, and QEWMA), and the homogeneously weighted moving average (HWMA) charts, have been developed to enhance its detection ability, especially for small and moderate shifts. These charts have been criticized as it is considered that an appropriately designed EWMA chart provides as good or better zero-state and steady-state average run-length (ARL) performance. In this article, we perform a careful comparison study of the above control charts under similar in-control (IC) run-length properties. We show that the “new” memory-type control charts have better out-of-control (OOC) run-length characteristics, especially for small to moderate shifts in the process mean for both the zero-state and steady-state cases, except for the HWMA chart where its steady-state OOC performance is very poor. We also present a comparison study based on the worst-case ARL measure. Finally, the extensions of the EWMA chart have better IC robustness ability than the EWMA and HWMA charts.

Parametric investigation and optimization of phase change material-based thermal energy storage integrated desiccant coated energy exchanger through physics informed neural networks oriented deep learning approach

To improve the energy exchange abilities, and to enhance indoor air quality, a desiccant-coated energy exchanger (DCEE) is a capable substitute compared to conventional energy exchangers such as fixed beds and desiccant wheels. Thus, accurately predicting the DCEE's physical characteristics is crucial for enhancing the system's performance. Therefore, in the current study, a novel data-driven modeling methodology utilizing physics-informed neural networks (PINNs) is developed to predict the exit parameters of DCEE, like the outlet temperature of cooling water, the outlet temperature of the air, and the outlet-specific humidity of the air. The performance characteristics of DCEE are evaluated using PINN by considering different input parameters. The performance parameters selected for the DCEE performance assessment are dehumidification capacity, thermal coefficient of performance, and heat recovery efficiency. The coated desiccant material chosen for the present study is silica gel. Good agreement is obtained between the PINN and experimental results for both the steady-state and transient cases, proving the PINN method's capability in solving multiple physics-based partial differential equations (PDEs) on a single domain with a maximum discrepancy of ±7.8 %. The developed model is used to obtain the optimal inlet conditions for a given operating condition. Adsorption kinetics of the coated desiccant silica gel revealed that the maximum water uptake capability for the given operating range is 0.345 g.g−1. A case study has been carried out by integrating an industrial waste heat-driven DCEE with a thermal energy storage module (TES) to analyze the energy storage ability during regeneration. A parametric study has been conducted to examine the transfer characteristics of the TES module. Further, the effectiveness of the TES module for five different phase change materials (PCMs) has been assessed. Finally, the seasonal energy efficacy ratio (SEER) of five different PCMs was investigated for 365 days to evaluate year-round performance. The effectiveness of thermal energy storage is maximum for Palmitic acid and minimum for Climsel C48, with corresponding values of 0.73 and 0.37. SEER is the largest for Palmitic acid and lowest for Climsel C48. The values of SEER for Palmitic acid during the summer and winter seasons are 5.489 and 3.31, whereas the values of SEER for Climsel C48 during the summer and winter seasons are 5 and 2.89, respectively.

Nonreciprocal Heat Circulation Metadevices.

Thermal nonreciprocity typically stems from nonlinearity or spatiotemporal variation of parameters. However, constrained by the inherent temperature-dependent properties and the law of mass conservation, previous works have been compelled to treat dynamic and steady-state cases separately. Here, by establishing a unified thermal scattering theory, the creation of a convection-based thermal metadevice which supports both dynamic and steady-state nonreciprocal heat circulation is reported. The nontrivial dependence between the nonreciprocal resonance peaks and the dynamic parameters is observed and the unique nonreciprocal mechanism of multiple scattering is revealed at steady state. This mechanism enables thermal nonreciprocity in the initially quasi-symmetric scattering matrix of the three-port metadevice and has been experimentally validated with a significant isolation ratio of heat fluxes. The findings establish a framework for thermal nonreciprocity that can be smoothly modulated for dynamic and steady-state heat signals, it may also offer insight into other heat-transfer-related problems or even other fields such as acoustics and mechanics.

Dynamical analysis for the motion of a 2DOF spring pendulum on a Lissajous curve

This study examines the motion of a spring pendulum with two degrees-of-freedom (DOF) in a plane as a vibrating system, in which its pivot point is constrained to move along a Lissajous curve. In light of the system’s coordinates, the governing equations of motion (EOM) are obtained utilizing the equations of Lagrange’s. The novelty of this work is to use the approach of multiple scales (AMS), as a traditional method, to obtain novel approximate solutions (AS) of the EOM with a higher degree of approximation. These solutions have been compared with the numerical ones that have been obtained using the fourth-order Runge–Kutta algorithm (4RKA) to reveal the accuracy of the analytic solutions. According to the requirements of solvability, the emergent resonance cases are grouped and the modulation equations (ME) are established. Therefore, the solutions at the steady-state case are confirmed. The stability/instability regions are inspected using Routh–Hurwitz criteria (RHC), and examined in accordance with the steady-state solutions. The achieved outcomes, resonance responses, and stability areas are demonstrated and graphically displayed, to evaluate the positive effects of different values of the physical parameters on the behavior of the examined system. Investigating zones of stability/instability reveals that the system’s behavior is stable for a significant portion of its parameters. A better knowledge of the vibrational movements that are closely related to resonance is crucial in many engineering applications because it enables the avoidance of on-going exposure to potentially harmful occurrences.

Effects of Inversion Layer on The Atmospheric Pollutant Dispersion from A High Chimney

An inversion layer is a layer in the lower atmosphere at a certain height through which there is no transport of pollutants. It plays as a significant factor in the formation of air pollutants where they are trapped. In this paper, a mathematical model describing an atmospheric pollutant dispersion from a high chimney in the presence of an inversion layer is constructed. The aim of the model is to predict the concentration of pollutants at ground level. The advection-diffusion equation governs the concentration of a pollutant released into the air. An analytical solution procedure via the integral transforms is presented for the steady-state case. Solutions are entirely determined by two parameters, i.e., the source strength emanating from the chimney and the height of the inversion layer. The pollutant concentration on the ground level with some multiple source formations will be explored, and also for various values of inversion layer height. Results show that the lower the inversion layer, the higher the pollutant concentration on the ground level is.

Impact of Temperature Variation on Calcium Profiling in a Neuronal Cell Due to Cancer: A Steady-State Case

Impact of Temperature Variation on Calcium Profiling in a Neuronal Cell Due to Cancer: A Steady-State Case

In-cylinder air mass flow estimation of gasoline engines based on map self-learning

Accurate in-cylinder air mass flow estimation is important for reducing emissions and improving the fuel efficiency of gasoline engines. Especially, the air-fuel ratio (AFR) control for gasoline engines is directly affected by the air mass flow estimation, which is used in feedforward control. At present, the transient air intake estimation for an engine is much more complex than the steady-state case. In practice, the working conditions of gasoline engines are always changeable to adapt to different traffic conditions, so it is important to improve the air intake estimation under the transient conditions. In order to improve the accuracy of intake air estimation, an appropriate filtering method is designed to eliminate the periodic fluctuations of the signals. And an estimation method based on the map self-learning algorithm is proposed, which considers the full working state of the engine, especially the transient conditions. The convergence of the proposed algorithm is guaranteed theoretically, and the method is designed to realize real-time identification and recursively correct of the volumetric efficiency value. The parameters of the observer are designed and adjusted through experiments to verify the effectiveness of the algorithm. With the continuous recursion of the algorithm, the accuracy of the air intake estimation will be improved and the error will be reduced. At last, the proposed strategy is analyzed and verified by a large number of experiments on the engine test bench to show its promising potentials.

Clinical implication of changes in serum cations and anions on clinical severity in sickle cell disease: A case–control study in a tertiary center

Objectives: Vaso-occlusive crisis in sickle cell disease (SCD) is related to disproportionate serum ions distribution. The objective was to evaluate the influence of changes in serum cations and anions on clinical severity in SCD patients. Materials and Methods: The case–control study included 26 SCD cases and 27 apparently healthy control individuals. The cases were further grouped as crisis state and steady state cases. Each participant was assigned a disease severity score. All study participants were evaluated for serum electrolytes, osmolality, calcium, magnesium, phosphorus, total protein, and albumin. Statistical Analysis: IBMSPSS version 26 was used for the statistical analysis. Results: The mean serum sodium (135.65 mmol/L), chloride (99.88 mmol/L), calcium (2.28 mmol/L), magnesium (0.76 mmol/L), osmolality (285.19 mOsm/kg), and albumin (0.59 mmol/L) were grossly reduced in cases than the control group. The SCD crisis group recorded low serum sodium (p ¼ 0.01), calcium (p ¼ 0.011), total cations (p ¼ 0.023), anions (p ¼ 0.008), and cation–anion ratio (p ¼ 0.041). Of all the cations, serum calcium correlated inversely with disease severity score (r ¼ –0.367, p ¼ 0.033), whereas serum albumin among the serum anions influenced severity the most (r ¼ –0.338, p ¼ 0.046). The cutoff values for serum calcium and albumin were, respectively, 2.41 and 0.63 mmol/L, with a sensitivity of 83.3 and 88.9%. A calculated ratio of serum sodium–albumin revealed a positive relationship with the severity score (r ¼ 0.328, p ¼ 0.05) with a sensitivity of 94.4% for a cutoff value of 208.45. Conclusion: Low serum sodium, calcium, albumin, and raised sodium–albumin ratio were linked to the crisis state, and routine estimation of these parameters will help in the early assessment of the clinical severity and initiate appropriate fluid management.