Search results

The purpose of this paper is to propose a new method for mathematical modeling of the buck dc‐dc converter in discontinuous conduction mode (DCM). By using the presented modeling method, the analysis of the transient and the steady states of the buck dc‐dc converter can be performed.

The proposed method is based on the two Laplace and Z transforms. In the proposed method, at first, the equations of the inductor current and the capacitor voltage are obtained as the power switch is on and off. Then by using the Laplace and Z transforms, the obtained equations are solved and the relations of the inductor current and the output voltage are obtained. In the proposed method, the Laplace transform is used for determining of the general relations of the inductor current and the output voltage. Also the Z‐transform is used as a tool for determining the initial values of the inductor current and the output voltage.

The transient and the steady state response of the dc‐dc converter is analyzed by the proposed method. By using the Z‐transform, the transient response of the converter and the effect of the elements of the converter on the time constant of the transient response are investigated. In addition, the effect of the elements of the converter and the load resistance on the electrical parameters of the converter such as the output voltage ripple and the inductor current ripple are investigated.

The proposed method in this paper is a suitable method for mathematical modeling of dc‐dc converters. The acernote of this method is that it can be used in both transient and steady state response, analysis of the dc‐dc converters. By using the final value theorem of the Z‐transform, the steady state response of the converter is investigated. Also by using this transform, the time constants of the transient response of the converter are determined. Finally, the results of the theoretical analysis are compared with the results of simulation in PSCAD/EMTDC and also the experimental results to prove the validity of the presented subjects.

The main purpose of this study resides essentially in the development of a new tool to quantify the biomass in the bioreactor operating under steady state conditions.

Modeling is the most relevant tool for understanding the functioning of some complex processes such as biological wastewater treatment. A steady state model equation of activated sludge model 1 (ASM1) was developed, especially for autotrophic biomass (XBA) and for oxygen uptake rate (OUR). Furthermore, a respirometric measurement, under steady state and endogenous conditions, was used as a new tool for quantifying the viable biomass concentration in the bioreactor.

The developed steady state equations simplified the sensitivity analysis and allowed the autotrophic biomass (XBA) quantification. Indeed, the XBA concentration was approximately 212 mg COD/L and 454 mgCOD/L for SRT, equal to 20 and 40 d, respectively. Under the steady state condition, monitoring of endogenous OUR permitted biomass quantification in the bioreactor. Comparing XBA obtained by the steady state equation and respirometric tool indicated a percentage deviation of about 3 to 13%. Modeling bioreactor using GPS-X showed an excellent agreement between simulation and experimental measurements concerning the XBA evolution.

These results confirmed the importance of respirometric measurements as a simple and available tool for quantifying biomass.

Modeling electric machines is one of the powerful approaches for analyzing their performance. A dynamic model and a steady-state model are introduced for each electric machine. Permanent magnet induction machine (PMIM) is a dual-rotor electric machine, which has various advantages such as high-power factor and low magnetizing current. Studying PMIM and its modeling might be valuable. The purpose of this paper is to introduce a simple and accurate method for dynamic and steady-state modeling of PMIM.

In this paper, arbitrary dqo reference frame is used to model PMIM. First, three-phase dynamic equations of stator and rotors are introduced. Then, they are transferred to an arbitrary reference frame. The voltage and magnetic flux equations aligned at dqo axes are obtained. These equations give the dynamic model. To investigate the results, PMIM simulation is performed according to obtained dynamic equations. Simulation results verify the analytic calculations.

In this paper, dynamic equations of PMIM are obtained. These equations are used to determine dynamic equivalent circuits of PMIM. Steady-state equations and one phase equivalent circuit of the PMIM using phasor relations are also extracted.

PMIM equations along dqo axes and their dynamic and steady-state equivalent circuits are determined. These equations and the equivalent circuits can be transformed to different reference frames and analyzed easily.

The paper seeks to investigate the effect of the rotor‐phase sequence connection on the steady‐state stability of the brushless cascaded doubly‐fed machine (BCDFM). The stability analysis is carried out considering the eigenvalue method.

The BCDFM includes a two wound‐rotor induction machines: a power machine cascaded to a control one. The BCDFM modeling is firstly treated considering a Park reference frame linked to the rotating field of the power machine, and for both rotor‐phase sequence connections. Then, a state representation related to small perturbations is established following the linearisation of the BCDFM model around a steady‐state operating point. This allows the investigation of the BCDFM steady‐state stability and efficiency.

It has been found that the electrical variables of the control machine power supply greatly affect the BCDFM steady‐state stability and efficiency.

The work should be extended considering a validation of the established results through experimental tests.

The small perturbation model of the BCDFM has been introduced for the first time which is the key of the machine steady‐state stability analysis and efficiency investigation.

While steady-state analysis is useful, it does not consider the inherent transient characteristics of repairable systems' behavior, especially in systems that have relatively short life spans, or when their transient behavior is of special concern such as the motivating example used in this paper, military systems. Therefore, a maintenance policy that considers both transient and steady-state availability and aims to achieve the best trade-off between high steady-state availability and rapid stabilization is essential.

This paper studies the transient behavior of system availability under the Kijima Type II virtual age model. While such systems achieve steady-state availability, and it has been proved that deploying preventive maintenance (PM) can significantly improve its steady-state availability, this improvement often comes at the price of longer and increased fluctuating transient behavior, which affects overall system performance. The authors present a methodology that identifies the optimal PM policy that achieves the best trade-off between high steady-state availability and rapid stabilization based on cost-availability analysis.

When the proposed simulation-based optimization and cost analysis methodology is applied to the motivating example, it produces an optimal PM policy that achieves an availability–variability balance between transient and steady-state system behaviors. The optimal PM policy produces a notably lower availability coefficient of variation (by 11.5%), while at the same time suffering a negligible limiting availability loss of only 0.3%. The new optimal PM policy also provides cost savings of about 5% in total maintenance cost. The performed sensitivity analysis shows that the system's optimal maintenance cost is sensitive to the repair time, the shape parameter of the Weibull distribution and the downtime cost, but is robust with respect to changes in the remaining parameters.

Most of the current maintenance models emphasize the steady-state behavior of availability and neglect its transient behavior. For some systems, using steady-state availability as the sole metric for performance is not adequate, especially in systems that have relatively short life spans or when their transient behavior affects the overall performance. However, little work has been done on the transient analysis of such systems. In this paper, the authors aim to fill this gap by emphasizing such systems and applications where transient behavior is of critical importance to efficiently optimize system performance. The authors use military systems as a motivating example.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming and powder metallurgy are briefly discussed. The range of applications of finite elements on the subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for the last five years, and more than 1100 references are listed.

The purpose of this paper is to propose a state dependent stochastic Markov model for availability analysis of process plant instead of traditional time dependent model.

The traditional concepts of system performance measurement and reliability (namely, binary; two-state concepts) are observed to be inadequate to characterize performance of complex system components. Availability analysis considering an intermediate state, such as a degraded state, provides a better alternative mechanism for system performance mapping. The availability model provides a better assessment of failure and repair characteristics for equipment in the sub-system and its overall performance. In addition to availability analysis, this paper also discusses the preventive maintenance (PM) program to achieve target availability. In this model, the degraded state is considered as a PM state. Using Markov analysis the optimum maintenance interval is determined.

Markov process provides an easier way to measure the performance of the process facility. This study also revealed that the maintenance interval has a major influence in the availability of a process facility as well as in maintaining target availability. The developed model is also applicable to the varying target availability as well as having the capability to handle even the reconfigured process systems.

Considering the degraded state as an operative state, a higher availability of the plant is predicted. The consideration of the degraded state of the system makes the availability estimation more realistic and acceptable. Availability quantification, target availability allocation and a PM model are exemplified in a sub-system of an liquefied natural gas facility.

The unique features of the present study are; Markov modeling approach integrating availability and PM; optimum PM interval determination of stochastically degrading components based on target availability; consideration of three-state systems; and consideration of increasing failure rates.

Volumetric air receivers experience high thermal stress as a consequence of the intense radiation flux they are exposed to when used for heat and/or power generation. This study aims to propose a proper design that is required for the absorber and its holder to ensure efficient heat transfer between the fluid and solid phases and to avoid system failure due to thermal stress.

The design and modeling processes are applied to both the absorber and its holder. A multi-channel explicit geometry design and a discrete model is applied to the absorber to investigate the conjugate heat transfer and thermo-mechanical stress levels present in the steady-state condition. The discrete model is used to calibrate the initial state of the continuum model that is then used to investigate the transient operating states representing cloud-passing events.

The steady-state results constitute promising findings for operating the system at the desired airflow temperature of 700°C. In addition, we identified regions with high temperatures and high-stress values. Furthermore, the transient state model is capable of capturing the heat transfer and fluid dynamics phenomena, allowing the boundaries to be checked under normal operating conditions.

Thermal stress analysis of the absorber and the steady/transient-state thermal analysis of the absorber/holder were conducted. Steady-state heat transfer in the explicit model was used to calibrate the initial steady-state of the continuum model.

The advent of the new retail era witnessed the consumers’ demand shift from on the traditional product quality to on the full supply chain service quality, and product service and service manufacturing is gradually taking shape. The purpose of this paper is to propose whether there is a “quality bridge” in the dynamic evolution process of retail service supply chain (RSSC) and discuss the system role, steady-state characteristics and dynamic evolution mechanism of service quality in this dynamic evolution process.

This paper proposes the dissipation system structure of the RSSC under the steady-state quality constraint, constructs a Markov chain model (MCM) for the evolution of the service quality of RSSC, and tests the objective existence of the steady-state distribution of the service quality by taking Chinese HJ retail enterprises as samples.

The research value of this study is summarized as follows. The research finds that the evolution of service quality of RSSC is a dynamic and non-linear growth process, which has significant characteristics of complex adaptability and steady-state convergence. The study finds that the quality evolution process of the RSSC is a steady-state convergence process, and there is a steady-state distribution of quality in its co-evolution, in which different process input levels have a significant positive impact on the stable level of quality state. The study finds that the steady state of quality plays a crucial role in the collaborative evolution of the RSSC, that is, when the service quality reaches a certain steady state distribution, the operating efficiency and profit level of the whole chain will show an “explosive” growth trend.

Quality bridge, an original concept in this paper, represents the role of quality steady-state in the operation of RSSC. Based on Markov chain and system simulation tools, this paper verifies the existence of steady-state service quality and its positive effect on the co-evolution and sustainable development of RSSC. When the service quality reaches a certain steady distribution, the operating efficiency and income level of the whole chain will show n trend of explosive growth.