The reliability of water supply system is a critical factor in the development and the ongoing capability to succeed in life and people's health. Determining of its, with high certainty, for performance of water supply system is developed to ensure the sustainability of system. Reliability (Re) plays a great role in evaluation of system sustainability. The probability approaches have been used to evaluate the reliability problems of systems. The probability approach is failed to address the problems of reliability evaluation that comes by subjectivity, human inputs and lack of history data. This research proposed two models; I) traditional model: fuzzy reliability measure suggested by Duckstein and Shresthaand then developed by El-Baroudy; and II) developed model: fuzzy reliability-vulnerability model. The two models implemented and evaluation of water supply system by using two hypothetical systems (G and H). System (G) consists of a single pump and System (H) consists of a two parallel pumps. Triangular and trapezoidal membership functions (MFs) are used to investigate of the reliability measure to the form of the membership function. The results agree with expectations that the reliability of parallel component system {ReH (0.53)} is higher than the reliability of single component system {ReG (0.47)}. Moreover, the result by using fuzzy set reduces the effect of subjectively in process of decision-making (DM). The fuzzy reliability vulnerability is able to handle different fuzzy representations and different operation environment of system
Estimation of the reliability for repairable system after maintenance actions is usually based on mathematical models, which can be classified as parametric and non-parametric models where the parametric model is required a prior specified life time distribution while Non-parametric model is that relaxes of the assumption of the life time distribution. Nonparametric life time models are including proportional hazard model and proportional odd model. In this paper we develop repairable reliability model concentrate on generalized repairable model that indicate the mixture of proportional hazard model and proportional odd model. A proportional hazard-proportional odds (PH-PO) model for the purpose of to improve the repairable reliability to obtain accurate estimates of reliability for repairable industrial boiler system at normal operating conditions depending on transformation parameter for reliability prediction for repairable system that represent Beji industrial boiler in power plant. The results show the odd model better than hazard model for repairable system after preventive maintenance depends on time to repair where transformation parameter (c) equal 0.0525094 it is closer to odds model than hazard model. In addition, reliability industrial boiler in case without temperature effect is better than reliability with temperature effect by using exponential model where we note that the reliability at 500 it is worse state where degrade more than (400,450) .
One way of obtaining information about reliability of units is to accelerate their life by testing at higher levels of stress (such as increasing elevated temperatures or voltages). Predicting the lifetime of a unit at normal operating conditions based on data collected at accelerated conditions is a common objective of these tests. Different models of accelerated life testing are used for such extrapolations. Two statistical based models are widely used: parametric models which require a prior specified lifetime distribution, and nonparametric models that relax of the assumption of the life time distribution. The proportional odds model is a nonparametric model in accelerated life testing based on the odds function and show that it gives a more accurate reliability estimates than proportional hazard model. This paper will concentrate on the models of proportional odds nonparametric accelerated life test for reliability prediction.
The detection of faults in electronic circuits is crucial to ensure the proper performance and reliability of electronic applications that utilize these devices. This work discovers, for the first time, that a direct tester board for fault diagnosis can be used not only for the intended measurement of current and voltage but also for studying the potential development of these magnitudes in inaccessible locations, as it detects register transfer level signals through oscilloscopes with low acquisition speeds. The experimental analysis carried out combines the use of commercial software with spatial distribution tracking and the exploitation of the sizes of network links in their computer graphical representation. The proper detection of malfunctions in electronic systems is crucial for enhancing their performance and reliability. We intend to explore the troubleshooting of analog electronic systems, for which we use wide-band direct tester boards. To evaluate its performance in routine practice, we perform experimentation using two different analog circuits designed. They consist of conventional operational amplifiers and element modeling based on equivalent resistance-capacitance networks. Given the procedure followed, commercial programs were used. Special mention should be made of the conclusion matrix, which is interesting when selecting suitable diagnostic parameters. The effectiveness of direct measurement based on integrated probes in the two projects, which allowed for fault insertion, was also confirmed. The results and discussions were enriched by the summarized experimental test report. The work concludes with a reflection on the relationship between this work and the existing state of the art, as well as the new challenges posed by international researchers.
The direct sequence (DS) spread spectrum communication technique is widely regarded as one of the most effective methods of mitigating the effects of a repeating jammer in military communications systems. The proposed system coupled DS with multiple frequency shift keying (DS/MFSK). It is comprised of a transmitter and a receiver. Non-coherent demodulation is examined, as are the spreading sequences in question. The effect of AWGN and Rayleigh fading channels on the proposed approach's bit error rate (BER) is examined. The investigation demonstrates that even with an 8 dB signal-to-noise ratio, superior outcomes can be achieved; this study's suggested endeavor is to create a novel transceiver system built on the DS/MFSK modular architecture. MFSK modulation prevents multiple-access interference, while DS is typically employed to boost system efficiency across erratic fading. Test results show that reliability on the AWGN channel decreases a little while reliability is greatly enhanced by Rayleigh fading. Moreover, notable improvements in bandwidth efficiency are achieved.
Indeed, there are many hydrology variables influence on the operating of dam and reservoir system. Thus, modelling of dam operation is a complicated issue due to the nonlinearity of such hydrological parameters. Hence, the identification of a modern model with a high capacity to cope with the operation of the dam is extremely important. The current research introduced good an optimization algorithm, namely Genetic Algorithm (GA) to find best operation rules. The main aim of the suggested algorithm is to minimize the difference between irrigation demand and water release value. The developed algorithm was applied to find operation rules for Timah Tasoh Dam, Malaysia. This research used significant evaluation indexes to examine the algorithms' performance. The results indicated that the GA method achieved low Vulnerability, high Resilience and Reliability. It has been demonstrated that the GA method will be a promising tool in dealing with the problem of dam operation.
In the current article, an experimental investigation has been implemented of flow and heat transfer characteristics in a parabolic trough solar collector (PTSC) using both nano-fluids and artificial neural networks modeling. Water was used as a standard working fluid in order to compare with two different types of nano-fluid namely, nano-CuO /H2O and nano-TiO2/ H2O, both with a volume concentration of 0.02. The performance of the PTSC system was eval-uated using three main indicators: outlet water temperature, useful energy and thermal efficiency under the influence of mass flowrate ranging from 30 to 80 Lt/hr. In parallel, an artificial neural network (ANN) has been proposed to predict the thermal efficiency of PTSC depending on the experimental re-sults. An Artificial Neural Network (ANN) model consists of four inputs, one output parameter and two hidden layers, two neural network models (4-2-2-1) and (4-9-9-1) were built. The experimental results show that CuO/ H2O and TiO2/H2O have higher thermal performance than water. Overall, it was veri-fied that the maximum increase in thermal efficiency of TiO2/H2O and CuO/H2O compared to water was 7.12% and 19.2%, respectively. On the oth-er hand, the results of the model 4-9-9-1 of ANN provide a higher reliability and accuracy for predicting the Thermal efficiency than the model 4-2-2-1. The results revealed that the agreement in the thermal efficiency between the ANN analysis and the experimental results about of 91% and RMSE 3.951 for 4-9-9-1 and 86% and RMSE 5.278 for 4-2-21.
These systems show great promise by converting waste heat from photovoltaic modules into additional electrical power. The study analyzes the performance and efficiency of the hybrid PV-TEG systems under varying conditions, such as different solar concentration ratios, cooling methods, and materials. While these innovations promise to improve system efficiency, the review also identifies several challenges, including increased thermal resistance, higher system costs, and the minimal temperature difference across the TEG, which significantly limits its performance. This limitation, where the temperature differential is often too small to be effectively harnessed, reduces the TEG's overall efficiency and hinders the integrated system's potential gains. The review underscores the need for urgent and extensive research to develop optimized design configurations, durable mathematical models, and further experimental validation to ensure the practical viability of these systems under diverse environmental conditions. Despite these challenges, the potential of PV-TEG systems to revolutionize solar energy technologies is undeniable.PV-TEG performance is intricately linked to environmental conditions: higher solar radiation boosts efficiency, but increased ambient temperatures reduce it. TEGs often hinder PV cooling, yielding minimal efficiency gains. Non-uniform heat and low-temperature differences across TEGs further decrease performance. While hybrids can improve power conversion, high costs limit feasibility. However, with strategies such as enhancing solar concentration, using effective cooling methods like water or nanofluids, and advanced materials like phase change materials, the efficiency and reliability of these systems can be significantly improved
This research focuses on studying the speed flow density relationships which are considered the fundamental traffic flow relationships. The objective of the present study is to predict statistical models represent these relationships depending on a field survey data collected from Al-Thirthar road in Falluja city.Data were collected by using video-recording technique. The required data were abstracted, analyzed, grouped, and processed using computer programs developed for this purpose. Standard statistical analysis techniques were used to examine and analyze the observed data.FWASIM simulation traffic software program was used to verify the predicted traffic stream models, while the obtained results were presented in this research. To test the validity and reliability of the model, the output results of the predicated model were compared with the output data obtained from FWASIM model using similar input data and segment geometry. The comparison leads to consider that the developed regression model may be used to evaluate the performance of urban streets in Falluja city.
Matrix converters (MCs) have attracted significant interest and found extensive applications across multiple industries owing to their desirable characteristics. These include the capability to produce sinusoidal currents at both input and output, substantial size reduction, and enhanced reliability by minimizing significant passive components. This paper explores the potential of MC technology as a viable alternative to conventional AC-DC-AC converters in industrial applications. It discusses recent advancements in MC structural configurations, modulation/control algorithms, and multiphase structures and control systems. The paper offers an in-depth review of modern industrial uses of MC technology. It also delves into different methods for managing induction motors, particularly the DTC (Direct Torque Control) approach. The study explores the intricacies of DTC and its relationship with SVM. The primary research objective is to examine the performance of an IM when operated with an SVPWM inverter, focusing on harmonic analysis of voltages and currents. Various PWM methods regulate the voltage and frequency supplied to the IM. Sinusoidal Pulse Width Modulation (SPWM) and SVPWM are the two most commonly used 3-phase Voltage Source Inverter strategies. The growing adoption of SVPWM is driven by its ability to reduce harmonic content in voltage and enhance the fundamental output voltage of the IM. Consequently, this study models a DTC-SVM theory-driven IM using MATLAB/SIMULINK to control the speed of induction motors. The following values were calculated for the system: Quality factor=2.236, Damping ratio=4.45, and the cut-off frequency (fc=355.88H).
Serial Concatenation Convolutional Codes (SCCCs) encoder is built using a serial concatenation of two Recursive Systematic Convolutional (RSC) encoders, separated by an interleaver. These two RSC encoders depending on the trellis termination criteria are software implemented and the performance of each one of them is analyzed under different conditions and circumstances. The output data from the encoder are multiplied by an amplitude matrix (AM) at the transmitter side and the Inverse of Amplitude Matrix (IAM) at the receiver side. The reliability estimation, log-likelihood algebra, and soft channel outputs for Soft Output Viterbi Algorithm (SOVA) are examined. Then the modified Viterbi metric that incorporates a-priori information used for SOVA decoding is derived. A low memory implementation of the SOVA decoder is presented. The iterative SOVA for SCCCs is described with illustrative examples. The behavior of the SCCCs encoder-decoder scheme is tested under different circumstances with AM and without AM at the AWGN and Rayleigh fading channels with unlike frame sizes (FS) and constraint length (K). The results show that the performance of system with AM outperforms the other conventional system that worked without AM.