Reliability Requirements Research Articles

DG Compensation Using Optimal Distribution in Microgrids with High DG Penetration

This study developed a model to compensate for both active and passive power in an electric microgrid with an optimal power flow to allow a detailed analysis of its power flow, which encourages the integration of renewable energy sources (RESs). Mixture integer linear programming (MILP) is proposed, with distributed generation (DG) integrated into the existing bars. It is developed in the GAMS tool to minimize operating costs in the microgrid as an objective function, to guarantee reliability, and quality in the microgrid. The algorithm calculates an optimal solution that meets all requirements for reliability and quality in the microgrid. Finally, a comparison of data between the two systems without and with DG was performed, showing an improvement in voltage profiles, reduced active power losses in the lines, a better power factor (PF), and improved angular behavior; that also adheres to the restrictions set forth at a minimum operating cost. A nine-bar model has been used to model the problem by IEEE standards.

Dual-directional SCR device with dual-gate controlled mechanism for ESD protection in photoelectric chip

The dual-directional silicon-controlled rectifier (DDSCR) is an electrostatic discharge (ESD) protection device. It can provide positive and negative ESD surge paths and has excellent robustness. However, industry-level sensors operating in strong electromagnetic interference environments impose higher reliability requirements on photoelectric chips. This paper proposed a novel DDSCR with a dual-gate controlled mechanism. By incorporating the gate diode triggering and the gate field modulation mechanism into the traditional DDSCR, and further utilizing additional parasitic bipolar junction transistors (BJTs) for diversion, the proposed device exhibits significantly improved ESD characteristics. Measurement results indicate that, compared to DDSCR, the proposed device exhibits a 27.5% reduction in trigger voltage (Vt1 ), a 96.1% improvement in holding voltage (Vh ), and achieves an equivalent human body model protection level of 11.45 kV, demonstrating exceptional design area efficiency. The experimental findings validate the effectiveness of the proposed device in 5 V photoelectric chip applications.

Prediction of JTE breakdown performance in SiC PiN diode radiation detectors using TCAD augmented machine learning

The design of Junction Termination Extension (JTE) is an important step for meeting the reliability requirement of SiC PiN diode radiation detectors. For early evaluation, Technology Computer Aided Design (TCAD) software is often used to simulate the electronic property of detectors with different JTE parameters. But it is time consuming, which need 1 h or even longer for one case. Here, a TCAD augmented Machine Learning (ML) method based on the fully connected Neural Network (NN) algorithm is proposed to predict the breakdown performance quickly with different parameters of Spatial Modulation (SM) JTE. Utilized ∼5000 datum generated by TCAD simulation, the ML model could be established and achieve good prediction of breakdown voltage and location within a few seconds. As a semi-supervised learning model, its prediction accuracy of breakdown location is higher than 89.4 % and the determination coefficient R2 of breakdown voltage could be up to 0.97 compared with TCAD simulations. Moreover, this model could give the relationship curve of breakdown voltages and doping concentration, which is useful to choose an ideal structure with a wide implantation dose window. Based on this ML prediction model, the design cycle of SiC PiN diode radiation detectors could be reduced significantly.

Enhanced Network Reliability Following Emergency (E911) Calls

Purpose: In this research, the purpose is to explore E911 call reliability requirements, study real-world issues related to telecommunication networks transitioning from LTE to 5G (NR) and WCDMA, and present network optimization solutions. The primary objective is to ensure the continuous supply of emergency services and improve the dependability of Enhanced 911 (E911) calls.
 Methodology: The research methodology involves an examination of the transition from LTE to 5G (NR) and WCDMA in telecommunication networks. The study delves into government-mandated E911 call reliability requirements and conducts a detailed analysis of two real-world issues affecting tight connectivity for E911 calls. Additionally, the research proposes network optimization solutions to address these challenges and enhance the overall reliability of emergency services.
 Findings: The findings of this research reveal insights into government-mandated E911 call reliability requirements and identify two practical issues affecting the continuity of emergency services during the transition from LTE to 5G (NR) and WCDMA.
 Unique contributor to theory, policy and practice: The study presents network optimization solutions aimed at overcoming these challenges, with the ultimate goal of improving the dependability of E911 calls and enhancing public safety.

Remarkable improved strength and ductility in brittle eutectic high-entropy alloy via a novel spheroidization and recrystallization strategy

Eutectic high-entropy alloys (EHEAs), as a classification of high-entropy alloys (HEAs), have received worldwide interest due to superior fluidity and attractive properties. However, other than the FCC + B2 EHEA system, most other reported EHEA systems show inherent brittleness during tensile loading at room temperature, which limits their advanced engineering application. In this work, a novel spheroidization + recrystallization (SR) strategy for synergistic strengthening and plasticizing of the brittle CoCrFeNi2(V6B3Si)0.149 was proposed. The superior combination of strength and ductility was achieved by tailoring spherical M3B2 + recrystallized FCC duplex phases. Based on this strategy, the yield strength and elongation were improved from 565 ± 15 MPa and 2.3 % ± 0.3 % to 841 ± 24 – 1278 ± 20 MPa and 14.7 % ± 0.5 % – 22.5 % ± 1.2 %, with an increase of 48 %–126 % and 539 %–878 %, respectively. The synergistic increment in the strength and ductility of SR-FCC+M3B2 EHEAs exceeds all reported further strengthened FCC + B2 EHEAs. Meanwhile, such simple thermo-mechanical processing is suitable for large-scale industrial production. The high strength results from the back stress provided by the dual heterogeneity of FCC grain sizes and soft FCC/hard M3B2. The good ductility is attributed to the dislocation movement path released by spheroidized M3B2 and a more uniform stress distribution caused by the recrystallized FCC. This work provides a new strategy for synergistic strengthening and plasticizing of the brittle EHEAs to meet industrial reliability requirements.

Reliability-based design optimization of river-sea-going ship based on agent model technology

The common ship structural optimization design is a deterministic method without considering uncertain factors, whereas the Reliability-Based Design Optimization (RBDO) can compensate for this deficiency. The RBDO of ship structure is a multi-parameter, high-dimensional, and high-nonlinear optimization solver. There exists a difficulty in guaranteeing accuracy and efficiency due to massive computation. In this study, the high-precision agent model for the limit state of ship hold structure is established based on agent model technology, including BP neural network, Radial Basis Function neural network, and Support Vector Machine combined with SMOTE oversampling algorithm. Furthermore, the reliability computation program is developed using Monte Carlo Simulation Method. A river-sea-going ship is considered the research object. The definition of rules, structural direct calculation result, and reliability requirement within all life cycles are considered boundary conditions. The RBDO system is constructed by the simulated annealing algorithm to investigate the lightweight structure. The established system can improve the efficiency and accuracy of the RBDO, which is significant for the ship's structural optimization design.

Enhanced Network Reliability Following Emergency (E911) Calls

Purpose: In this research, the purpose is to explore E911 call reliability requirements, study real-world issues related to telecommunication networks transitioning from LTE to 5G (NR) and WCDMA, and present network optimization solutions. The primary objective is to ensure the continuous supply of emergency services and improve the dependability of Enhanced 911 (E911) calls.
 Methodology: The research methodology involves an examination of the transition from LTE to 5G (NR) and WCDMA in telecommunication networks. The study delves into government-mandated E911 call reliability requirements and conducts a detailed analysis of two real-world issues affecting tight connectivity for E911 calls. Additionally, the research proposes network optimization solutions to address these challenges and enhance the overall reliability of emergency services.
 Findings: The findings of this research reveal insights into government-mandated E911 call reliability requirements and identify two practical issues affecting the continuity of emergency services during the transition from LTE to 5G (NR) and WCDMA.
 Unique contributor to theory, policy and practice: The study presents network optimization solutions aimed at overcoming these challenges, with the ultimate goal of improving the dependability of E911 calls and enhancing public safety.

Performance characterization of a new, low-cost multi-GNSS instrument for the cryosphere

Abstract We developed a multi-frequency, multi-Global Navigation Satellite System (GNSS) positioning instrument optimized for autonomous applications in the cryosphere. At lower power requirements and a fraction of the cost and weight compared to commercially available options, this instrument simplifies field usage and associated logistics. In this paper, we assess several baseline aspects of performance in a polar environment relative to geodetic receivers commonly used for glaciological applications. Evaluations of precision and relative accuracy of positioning show millimeter to centimeter-level (‘geodetic-grade’) quality of this instrument, making it a competitive alternative for GNSS glaciological and geophysical applications such as monitoring surface elevation change and ice flow. An array of these instruments, tested in the field on the Greenland Ice Sheet, also demonstrated robustness throughout the polar winter and met power and reliability requirements.

A Method for Calculating of the Efficiency of Communication Systems with Multiple Modulation Types and Multi-Stage Composite Coding

Analytical relations and a methodology for calculating the performance indicators of communication and multimedia broadcasting systems using multi-position modulation types (QAM-M, FM-M, FM-M, CHMS-M, AM-M, OFM-M) and multi-stage coding based on non-systematic convolutional codes and non-binary block Reed-Solomon codes are proposed. The relations obtained are common for studies of noise immunity, corrective capacity, energy and information efficiency of systems, depending on the requirements for reception reliability, modulation format, type of codes used and their parameters. The calculation of the characteristics of systems with cascade composite coding is carried out in a closed form and does not require the use of complex computer simulation procedures.

Development of Four-Tier Instrument at First Intermediate Level Chemistry Concepts

Chemical concepts are tiered from simple to complex. If misconceptions occur in simple concepts, they can cause misconceptions in complex concepts. The four-tier instrument is a tool for detecting misconceptions. This research aims to develop and describe the validity and reliability of a four-tier instrument on junior secondary-level chemistry concepts. This development research consists of 6 procedures: (1) concept mapping, (2) testing, (3) defining unscientific concepts, (4) developing four-tier instrument prototypes, (5) validating four-tier instrument prototypes, and (6) finalization of four-tier instruments. The developed four-tier instrument consists of 27 questions that measure chemistry concepts at the junior intermediate level. The instrument received an expert validation score of 92.81% with very valid criteria. The test results on 30 samples showed a reliability value based on a Cronbach alpha score of 0.713 with good criteria. The four-tier instrument on lower secondary level chemistry concepts meets the validity and reliability requirements so that it can be used to diagnose misconceptions on lower secondary level chemistry concepts.

Local Indigenous: Internalization of Siri And Kareso Tamatappuk on Teacher Performance

This research aims to determine: 1) Internalization of siri’ on teacher performance. 2) Internalization of kareso tamatappuk on teacher performance. 3) Internalization of siri ’ and kareso tamatappuk on teacher performance. This research was conducted with a quantitative approach, with a population of 52 for research sampling. The data collection technique used a questionnaire with a Likert scale, each of which has been tested and meets the requirements of validity and reliability. The data analysis techniques used were simple linear regression and multiple linear regression. The research results show that: 1) Siri’s internalization influences teacher performance. Based on simple linear regression analysis with a coefficient value of 0.247, the results of the t test with a calculated t value is 2.637 > ttable value of 2.010, a significance value of 0.001 <0.05, and an r squared value of 37.1%. 2) Internalization of kareso tamatappuk has an effect on teacher performance at SMA Negeri 19 Gowa Regency. Based on simple linear regression analysis with a coefficient value of 0.412, the t test results with a tcount value of 2.801 > t table value of 2.010, a significance value of 0.003 <0.05, and an r squared value of 39.4 %. 3) Internalization of Siri’ and kareso tamatappuk influences teacher performance, with the amount of influence exerted is around 45.1 %.
 Keywords: Siri’ internalization, Kareso Tamatappuk, teacher performance

Service Quality an Antecedent of Customer Satisfaction

The study is conducted on customers of banks in Pakistan to find out whether service quality is an antecedent of customer satisfaction. The study also provides the comparative analysis of four alternative extended versions of service quality models namely SERVQUAL, Weighted SERVQUAL, SERVPERF, and Weighted SERVPERF. The quantitative analysis has been conducted and to form the sample for the study, self-administered questionnaires have been distributed and responded to by 500 customers of Pakistani commercial banks. The data was analyzed on four alternative service quality models concerning customers’ opinions regarding service quality expectations, perceptions, and importance, and their impact on customer satisfaction and further efficacy of these alternative models have been compared. The comparative analysis of four alternative service quality models has been carried out by applying construct validity, reliability, uni-dimensionality, and model fit indices on service quality variables revealing that all four service quality models fulfilled the requirement of validity, reliability, and goodness of fit as well as the models significantly and positively impact the customer satisfaction, however, the superiority and higher effectiveness of the Weighted SERVPERF model over the other three service quality models have been established. The mean-based ranking of four alternative service quality models has been attempted and further analysis of banks' high and low-performing variables from a customer perspective was performed. In the Weighted SERVPERF model, the tangible, reliability, and responsiveness variables were established as high-performing, whereas empathy and assurance variables were established as low-performing variables. The bank management should enhance customer satisfaction by improving service quality with a more focused approach as provided in this study.

Reliability risk analysis and control strategy of COTS devices in aviation equipment

With the rapid advancement of aviation equipment, the adoption of commercial off-the-shelf (COTS) devices in aviation equipment has witnessed a substantial rise. As these devices are not specifically designed for aviation equipment with high safety and reliability requirements, their widespread use may give rise to numerous challenges and issues. Therefore, conducting reliability risk analysis and control of COTS devices is crucial for ensuring the performance and reliability of aviation equipment. This paper examines the fundamental conditions and current issues regarding the test and evaluation work of COTS products in U.S. military aviation equipment. Furthermore, it conducts a thorough analysis of the reliability risks associated with COTS devices in aviation equipment. Subsequently, a strategy and procedure for managing reliability risks related to COTS devices in aviation equipment is proposed. The results of the application case analysis demonstrate the effectiveness of the proposed method in identifying and capturing the key factors associated with the reliability risk of COTS devices. This subsequently guides the assessment and control of reliability risks associated with COTS devices in aviation equipment.

Energy-Efficient Functional Safety Design Methodology Using ASIL Decomposition for Automotive Cyber-Physical Systems

Automotive cyber-physical systems (ACPS) are typical cyber-physical systems because of the joint interaction between the cyber part and physical part. Functional safety requirement (including response time and reliability requirements) for an ACPS function must be assured for safe driving. Auto industry is cost-sensitive, power-sensitive, and environment-friendly. Energy consumption affects the development efficiency of the ACPS and the living environment of people. This paper solves the problem of optimizing the energy consumption for an ACPS function while assuring its functional safety requirement (i.e., energy-efficient functional safety for ACPS). However, implementing minimum response time, maximum reliability, and minimum energy consumption is a conflicting problem. Consequently, solving the problem is a challenge. In this paper, we propose a three-stage design process toward energy-efficient functional safety for ACPS. The topic problem is divided into three sub-problems, namely, response time requirement verification (first stage), functional safety requirement verification (second stage), and functional safety-critical energy consumption optimization (third stage). The proposed energy-efficient functional safety design methodology is implemented by using automotive safety integrity level decomposition, which is defined in the ACPS functional safety standard ISO 26262. Experiments with real-life and synthetic ACPS functions reveal the advantages of the proposed design methodology toward energy-efficient functional safety for ACPS compared with state-of-the-art algorithms.

РАЗВИТИЕ КРИТЕРИЕВ ОЦЕНКИ ЭФФЕКТИВНОСТИ СИСТЕМ ВНУТРЕННЕГО КОНТРОЛЯ В СОВРЕМЕННЫХ УСЛОВИЯХ

The relevance of the study is due to the need to improve the effectiveness of internal control systems in a rapidly changing external environment and increasing requirements for transparency and reliability of the organization’s activities. The authors of the article emphasize the importance of the problems of determining the criteria for the effectiveness of internal control, which have become the object of research by many domestic and foreign scientists, due to the need to improve this tool for managing economic activity. The article examines the approaches of various authors to the definition of criteria for evaluating the effectiveness of internal control systems. Based on the analysis, interpretations of the content of the most frequently used criteria for evaluating the effectiveness of the internal control system (effectiveness, efficiency, cost-effectiveness, expediency, timeliness) are formulated. The author conducts a study of criteria defined by leading international professional organizations (COSO, the Basel Committee on Banking Supervision, the Institute of Internal Auditors, the Association of Audit and Control of Information Systems). According to the author, the criteria for the effectiveness of the internal control system should not only reflect the current state of the internal control system, but also serve as a basis for its further development and improvement. As a result of the study, a systematization of the criteria for the effectiveness of the internal control system was proposed, which includes five groups involving an assessment of the level of organization of the internal control system; the level of human resources involved in the internal control system; the level of information, technical, technological and financial support for the internal control system; the state of the environment of the internal control system; the level of quality of internal control measures control within the framework of the internal control system. The proposed systematization of the criteria for the effectiveness of the internal control system allows for a deeper understanding of the essence and content of internal control and can become an effective management tool and contribute to the achievement of the tasks set. The systematization proposed by the author of the study can serve as a basis for the development and improvement of internal control systems in organizations. The results of the study can be useful for managers and specialists in the field of risk management, audit and control, as well as for anyone interested in improving the efficiency of organizations.

Data-Driven Robust Adaptive Control With Deep Learning for Wastewater Treatment Process

Due to high complexity and time-variant operation, as well as increasingly requirements for water quality, stability and reliability, wastewater treatment process (WWTP) is regarded as an adaptive control problem. In this study, a data-driven adaptive control with deep learning (DRAC-DL) is developed to improve the operational performance of WWTP. First, a feedback controller is designed to construct the closed-loop control scheme. Second, an adaptive deep belief network (ADBN), based on the data-driven self-incremental learning strategy, is proposed to approximate the ideal control law. Third, the stability of DRAC-DL scheme is analyzed in detail. The main advantage of DRAC-DL lies in its improved robustness and efficiency, which benefit from Lyapunov-based closed-loop strategy and efficient ADBN controller. Finally, the feasibility and applicability of DRAC-DL are verified by two parts: 1) Simulation on nonlinear system; and 2) Application to WWTP on the benchmark simulation model No.1 (BSM1). The experimental results show the applicability and effectiveness, among which DRAC-DL reduces the output fluctuation (Var) by no less than 82% and realizes the better stability and robustness.

Probabilistic Electricity Price Forecast With Optimal Prediction Interval

The uncertainty of electricity prices poses a challenge to all market participants as their decisions highly depend on the accuracy of price forecasts. Prediction intervals become an efficient method to quantify the uncertainties that reside in electricity price forecasts. In this paper, we propose a probabilistic electricity price forecast with optimal prediction interval method that considers both reliability and sharpness requirements. Taking reliability and sharpness into account, we ensure the prediction interval has a narrow width without sacrificing reliability. In the proposed method, the quantile regression is utilized to estimate the upper and lower bounds of the prediction intervals to avoid electricity price distribution assumption. In addition, the extreme learning machine (ELM) method is embedded in the forecast method to capture the nonlinear relationship within price data, and its tuning parameters are optimized using the augmented Lagrangian relaxation method in this paper. The effectiveness of the proposed probabilistic forecast method is demonstrated using data from various electricity markets.

EDFA with power pump laser in WDM Network design of 10GBPS transmission

Wavelength Division Multiplexing (WDM) that enabled optical networks are currently widely used in current telecommunications infrastructures and are anticipated to play a significant role in next-generation networks and the future Internet, supporting a wide range of services with a wide range of bandwidth, latency, reliability, and other feature requirements. In WDM networks, the input power of an optical transmitter is crucial; as a result, this results in a good output signal at the receiver side. The purpose of this paper is to design a WDM Optical Network in terms of length and pump power. The system is simulated using Opti-System software to achieve bit error rate (BER), quality factor, and output power of EDFA through optimized fiber length and pump power. In this analysis, the BER value, Q-factor and output of the system have been evaluated between 1550 and 1552nm with 0 dBm input signal power. EDFA length of 5km, power pump value of 500mv and 980nm frequency was set as reference in this study. This system was analysed using Opti-System simulation software at 10 Gigabits per second (10GBPS) transmission system. Result have shown that, min BER value shows a very significant increase at a 9-meter length and the Q-factor was rapidly decrease. The min BER value was in range 10-11 and 10-19 and Q-factor range 6.5 to 9.1 for 200mW to 8000mW power pump.

Recent Progress in Wearable Triboelectric Nanogenerator for Advanced Health Monitoring and Rehabilitation

Triboelectric nanogenerators (TENGs) have become a vital technology in physical health monitoring and rehabilitation applications, enabling continuous, personalized, and convenient monitoring, facilitating early detection and prevention, and offering valuable data‐driven insights. On‐body wearable triboelectric sensors enable real‐time tracking of vital health parameters, promoting accurate and personalized healthcare interventions. In addition to being self‐powered, these sensors facilitate early detection and prevention by capturing early warning signs of potential health issues, leading to timely interventions. Furthermore, they play a vital role in rehabilitation monitoring and feedback, helping to assess progress during the recovery process. This continuous monitoring, along with artificial intelligence, provides data‐driven insights into patterns, trends, and correlations, facilitating evidence‐based healthcare decision‐making. In this review, we provide an overview of the recent wearable TENG developments for healthcare applications. We discuss how TENGs work and explore a wide range of self‐powered health monitoring and rehabilitation applications. We then summarize recent advancements in healthcare applications, material selection, and unique features to help design highly efficient, accurate, and practical bioapplicable technology. Further, we discuss the challenges and prospects of the TENGs technology for healthcare applications, including miniaturization, moisture resistance, device maintenance, data reliability, and high outpower requirements.

Development of quality control methods for measurements and testing concrete structures

The development of building materials, structures, calculation and design methods, technologies leads to a significant lag in quality control methods, in particular, concrete. Modern control methods cannot guarantee the level of reliability of buildings and structures under construction. The standards for designing and controlling the compressive strength class of concrete, which are controlled according to various schemes, cannot meet the requirements for reliability during construction and operation. Goal. Give recommendations on the use of various concrete classes to ensure the required level of reliability and reliability of critical structures. Methods and materials. Standard concrete samples of classes B 30,50,100 in the form of 150 mm cubes were used as materials. Methods for estimating random variables for the load-bearing capacity and the load effect on the structure are used. Results. Different classes of concrete in terms of compressive strength provide different safety margins. With an increase in the concrete class, the safety factor increases, which ensures more efficient use of high-strength concretes in construction practice in terms of reliability. The probability of failure increases as the concrete class increases, which is due to different safety factors as the class increases. Practical significance. The development of control methods contributes to the level of development of engineering and technology of design and construction. The conducted research will improve the accuracy and quality of measurements and tests in the control of building materials and structures, even when using destructive methods.