Fault detection through discrete wavelet transform in overhead power transmission lines

Transmission lines are a very important and vulnerable part of the power system. Power supply to the consumers depends on the fault-free status of transmission lines. If the normal working condition of the power system is disturbed due to faults, the persisting fault of long duration results in financial and economic losses. The fault analysis has an important association with the selection of protective devices and reliability assessment of high-voltage transmission lines. It is imperative to devise a suitable feature extraction tool for accurate fault detection and classification in transmission lines. Several feature extraction techniques have been used in the past but due to their limitations, that is, for use in stationary signals, limited space in localizing nonstationary signals, and less robustness in case of variations in normal operation conditions. Not suitable for real-time applications and large calculation time and memory requirements. This research presents a discrete wavelet transform (DWT)-based novel fault detection technique at different parameters, that is, fault inception and fault resistance with proper selection of mother wavelet. In this study, the feasibility of DWT using MATLAB software has been investigated. It has been concluded from the simulated data that wavelet transform together with an effective classification algorithm can be implemented as an effective tool for real-time monitoring and accurate fault detection and classification in the transmission lines.© 2023 The Authors. Energy Science & Engineering published by Society of Chemical Industry and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Formation Evaluation of Lower Goru Sands of Khipro Block, Lower Indus Basin, Pakistan

Formation evaluation is widely used in exploration and production in order to minimize the risk, uncertainty, and understanding of the detailed characteristics of potential reservoir rocks. This study is aimed to evaluate the Petrophysical characteristics of upper and lower basal sands of the Cretaceous lower Goru Formation in Niamat-01 and Siraj-01 wells and to focus on hydrocarbon exploration potential. These wells have been drilled in the Khipro block, lower Indus basin, which is the least explored for the reservoir quality evaluation. Present study characterized the lower Goru sands of the Khipro block. It is interpreted that the thickness of upper and lower Basal sands are 13m and 10m, respectively in Naimat Basal 01, whereas 9m and 17m, respectively, are reported in SirajSouth-01. The average effective porosity is 11% in upper Basal sands while 26% is interpreted for lower Basal sand in Naimat Basal-01. An average porosity of 11% is found for upper Basal sands in Siraj South-01 and 11% for lower Basal sand. Water saturation (Sw) calculated for upper and lower Basal sands are 22% and 19%, respectively. The hydrocarbon saturation (Sh) of 78% is interpreted for upper Basal sands and 81% hydrocarbon saturation reported for lower Basal sands in Naimat basal-01. However, 36% and 45% Sw have been recognized for upper and lower Basal sands, respectively. Whereas hydrocarbon saturations of 64% and 55% are reported for the upper and lower basal sands, respectively, in SirajSouth-01. Crossover effects in front of targeted formations confirmed the presence of hydrocarbons in the zone of interest. Lower sands of the lower Goru Formation in the Khipro block are favorable for hydrocarbon production and have potential for future hydrocarbon exploration activities

Emerging Technologies for Connected and Smart Vehicles

[EN] The ten articles in this special section focus on new and emerging technologies for connected and smart vehicles. Due to the rapid growth of connected vehicles, many research constraints need to be addressed, e.g., reliability and latency, practical MAC and routing protocols, performance and adaptability to the changes in the environment (node density and oscillation in network topology), and validation of protocols under the umbrella of coherent assumptions using simulation methodologies. In this Feature Topic, we present 10 papers proposing very interesting solutions and architectures for futuristic and smarter connected vehiclesAhmed, SH.; Ben-Othman, J.; Lloret, J.; Khokhar, A.; Beyah, R.; Sánchez, A.; Guibene, W. (2018). Emerging Technologies for Connected and Smart Vehicles. IEEE Communications Magazine. 56(10):20-21. https://doi.org/10.1109/MCOM.2018.84931122021561

Heat transfer augmentation through engine oil-based hybrid nanofluid inside a trapezoid cavity

Heat transfer occurs as a result of density differences caused by temperature changes. It has several industrial applications. To improve performance, one must investigate the heat transfer behaviour of the working fluid. Hence, the purpose of this work is to report a heat transfer analysis of a partially heated trapezoid cavity filled with a hybrid nanofluid. The temperature conditions of the cavity are such that the bottom boundary is partially heated, inclined side boundaries are kept at a lower temperature, and the upper boundary is kept adiabatic. A trapezoidal shape heated obstacle is considered in the cavity’s centre. The heat transfer and flow take place inside the cavity due to density variation. The mechanism is regulated by mass, momentum, and energy conservation, as well as related boundary constraints. The solutions are determined by the use of a numerical technique known as the Finite Element Method after the governing equations are transformed into non-dimensional form, which brings up physical parameters affecting the heat transfer and flow. The initial study is performed for three types of nanofluids with silver and magnesium oxide nanoparticles inside water 2, kerosene , and engine oil . The study revealed that the engine oil-based hybrid nanofluid produced an increased heat transfer rate. Simulation is performed using engine-based hybrid nanofluid with the range of physical parameters, such as Rayleigh number (105≤≤107), Hartmann number (0≤≤100) and nanoparticles volume fraction (0≤≤0.2). It is found that the heat transfer rate is enhanced by increasing the fraction of nanoparticles in the base fluid. Moreover, imposition of magnetic field has reverse impact on the fluid movement

Suspended silicon integrated platform for the long-wavelength mid-infrared band

The atmospheric-transmission window and the fingerprint region of many substances overlaps with the long-wave infrared band. This has enabled the emergence of a new path for photonic integrated circuits, which could exploit the potential applications of this wavelength range, including chemical and bio sensing. In this work we review our latest advances in the suspended silicon platform with subwavelength grating lateral cladding at 7.7-µm wavelength. Suspended waveguides only require one lithographic etch step and can be specifically designed to maximize sensitivity when used as sensors. Waveguides with propagation loss of 3.1±0.3 dB/cm are demonstrated, as well as bends with less than 0.1 dB/bend. Suspended waveguides based on shifted Bragg grating lateral cladding are also reported, with propagation loss of 5.1±0.6 dB/cm. These results prepare the ground for the development of a platform capable of covering the entire mid-infrared band. Keywords: suspended silicon, mid-infrared, long-wave infrared, subwavelength grating, Bragg.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Mitigation of Power Losses and Enhancement in Voltage Profile by Optimal Placement of Capacitor Banks With Particle Swarm Optimization in Radial Distribution Networks

The prime purpose of placing a capaci- tor bank in a power system is to provide reactive power, reduce power losses, and enhances voltage profile. The main challenge is to determine the optimum capacitor position and size that reduces both system power losses and the overall cost of the sys- tem with rigid constraints. For this purpose, different optimization techniques are used, for example Particle Swarm Optimization (PSO) which converges the com- plex non-linear problem in a systematic and method- ological way to find the best optimal solution. In this paper, the standard IEEE 33-bus and 69-bus systems are used to find the optimum location and size of the capacitors bank. These power networks are simu- lated in Siemens PSS®E software. For the optimum solution of capacitor banks, the PSO algorithm is used. The PSO fitness function is modelled in such a way which contains the high average bus voltage, the small size of capacitor banks, and low power losses. The fitness function used is a weighted type to reduce the computation time and multi-objective function complexity

Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer

BACKGROUND: The purpose of this study was to build radiogenomics models from texture signatures derived from computed tomography (CT) and 18F-FDG PET-CT (FDG PET-CT) images of non-small cell lung cancer (NSCLC) with and without epidermal growth factor receptor (EGFR) mutations. METHODS: Fifty patients diagnosed with NSCLC between 2011 and 2015 and with known EGFR mutation status were retrospectively identified. Texture features extracted from pretreatment CT and FDG PET-CT images by manual contouring of the primary tumor were used to develop multivariate logistic regression (LR) models to predict EGFR mutations in exon 19 and exon 20. RESULTS: An LR model evaluating FDG PET-texture features was able to differentiate EGFR mutant from wild type with an area under the curve (AUC), sensitivity, specificity, and accuracy of 0.87, 0.76, 0.66, and 0.71, respectively. The model derived from CT texture features had an AUC, sensitivity, specificity, and accuracy of 0.83, 0.84, 0.73, and 0.78, respectively. FDG PET-texture features that could discriminate between mutations in EGFR exon 19 and 21 demonstrated AUC, sensitivity, specificity, and accuracy of 0.86, 0.84, 0.73, and 0.78, respectively. Based on CT texture features, the AUC, sensitivity, specificity, and accuracy were 0.75, 0.81, 0.69, and 0.75, respectively. CONCLUSION: Non-small cell lung cancer texture analysis using FGD-PET and CT images can identify tumors with mutations in EGFR. Imaging signatures could be valuable for pretreatment assessment and prognosis in precision therapy

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020