Investigation on Applicability and Limitation of Cosine Similarity-Based Structural Condition Monitoring for Gageocho Offshore Structure

The key to coping with global warming is reconstructing energy governance from carbon-based to sustainable resources. Offshore energy sources, such as offshore wind turbines, are promising alternatives. However, the abnormal climate is a potential threat to the safety of offshore structures because construction guidelines cannot embrace climate outliers. A cosine similarity-based maintenance strategy may be a possible solution for managing and mitigating these risks. However, a study reporting its application to an actual field structure has not yet been reported. Thus, as an initial study, this study investigated whether the technique is applicable or whether it has limitations in the real field using an actual example, the Gageocho Ocean Research Station. Consequently, it was found that damage can only be detected correctly if the damage states are very similar to the comparison target database. Therefore, the high accuracy of natural frequencies, including environmental effects, should be ensured. Specifically, damage scenarios must be carefully designed, and an alternative is to devise more efficient techniques that can compensate for the present procedure.

Application of Meshless local Petrov-Galerkin approach for steady state groundwater flow modeling

The complicated behavior of groundwater system in an arid aquifer is generally studied by solving the governing equations using either analytical or numerical methods. In this regard, analytical methods are just for some aquifers with regular boundaries. Numerical methods used for this aim are finite difference (FDM) and finite element methods (FEM) which are engaged for some simple aquifers. Using them in the complex cases with irregular boundaries has some shortcomings, depended on meshes. In this study, meshless local Petrov-Galerkin (MLPG) method based on the moving kriging (MK) approximation function is used to simulate groundwater flow in steady state over three aquifers, two standard and a real field aquifer. Moving kriging function known as new function which reduces the uncertain parameter. For the first aquifer, a simple rectangular aquifer, MLPG-MK indicates good agreement with analytical solutions. In the second one, aquifer conditions get more complicated. However, MLPG-MK reveals results more accurate than FDM. RMSE for MLPG-MK and FDM is 0.066 and 0.322 m respectively. In the third aquifer, Birjand unconfined aquifer located in Iran is investigated. In this aquifer, there are 190 extraction wells. The geometry of the aquifer is irregular as well. With this challenging issues, MLPG-MK again shows satisfactory accuracy. As the RMSE for MLPG-MK and FDM are 0.483 m and 0.566 m. therefore, planning for this aquifer based on the MLPG-MK is closer to reality.

Relating Ndesign to Field Compaction: A Case Study in Minnesota

High field density helps in increasing the durability of asphalt pavements. In a current research effort, the University of Minnesota and the Minnesota Department of Transportation (MnDOT) have been working on designing asphalt mixtures with higher field densities. One critical issue is the determination of the Ndesign values for these mixtures. The physical meaning of Ndesign is discussed first. Instead of the traditional approach, in which Ndesign represents a measure of rutting resistance, Ndesign is interpreted as an indication of the compactability of mixtures. The field density data from some recent Minnesota pavement projects are analyzed. A clear negative correlation between Ndesign and field density level is identified, which confirms the significant effect of Ndesign on the compactability and consequently on the field density of mixtures. To achieve consistency between the laboratory and field compaction, it is proposed that Ndesign should be determined to reflect the real field compaction effort. A parameter called the equivalent number of gyrations to field compaction effort (Nequ) is proposed to quantify the field compaction effort, and the Nequ values for some recent Minnesota pavement projects are calculated. The results indicate that the field compaction effort for the current Minnesota projects evaluated corresponds to about 30 gyrations of gyratory compaction. The computed Nequ is then used as the Ndesign for a Superpave 5 mixture placed in a paving project, for which field density data and laboratory performance test results are obtained. The data analysis shows that both the field density and pavement performance of the Superpave 5 mixture are significantly improved compared with the traditional mixtures. The results indicate that Nequ provides a reasonable estimation of field compaction effort, and that Nequ can be used as the Ndesign for achieving higher field densities.

Securing SCADA Energy Management System under DDos Attacks Using Token Verification Approach

The advanced connection requirements of industrial automation and control systems have sparked a new revolution in the Industrial Internet of Things (IIoT), and the Supervisory Control and Data Acquisition (SCADA) network has evolved into an open and highly interconnected network. In addition, the equipment of industrial electronic devices has experienced complete systemic integration by connecting with the SCADA network, and due to the control and monitoring advantages of SCADA, the interconnectivity and working efficiency among systems have been tremendously improved. However, it is inevitable that the SCADA system cannot be separated from the public network, which indicates that there are concerns over cyber-attacks and cyber-threats, as well as information security breaches, in the SCADA network system. According to this context, this paper proposes a module based on the token authentication service to deter attackers from performing distributed denial-of-service (DDoS) attacks. Moreover, a simulated experiment has been conducted in an energy management system in the actual field, and the experimental results have suggested that the security defense architecture proposed by this paper can effectively improve security and is compatible with real field systems.

High-fidelity aeroelastic analyses of wind turbines in complex terrain: FSI and aerodynamic modelling

This paper shows high-fidelity Fluid Structure Interaction (FSI) studies applied on the research wind turbine of the WINSENT project. In this project, two research wind turbines are going to be erected in the South of Germany in the WindForS complex terrain test field. The FSI is obtained by coupling the CFD URANS/DES code FLOWer and the multiphysics FEM solver Kratos, in which both beam and shell structural elements can be chosen to model the turbine. The two codes are coupled in both an explicit and an implicit way. The different modelling approaches strongly differ with respect to computational resources and therefore the advantages of their higher accuracy must be correlated with the respective additional computational costs. The presented FSI coupling method has been applied firstly to a single blade model of the turbine under standard uniform inflow conditions. It could be concluded that for such a small turbine, in uniform conditions a beam model is sufficient to correctly build the blade deformations. Afterwards, the aerodynamic complexity has been increased considering the full turbine with turbulent inflow conditions generated from real field data, in both a flat and complex terrains. It is shown that in these cases a higher structural fidelity is necessary. The effects of aeroelasticity are then shown on the phase-averaged blade loads, showing that using the same inflow turbulence, a flat terrain is mostly influenced by the shear, while the complex terrain is mostly affected by low velocity structures generated by the forest. Finally, the impact of aeroelasticity and turbulence on the Damage Equivalent Loading (DEL) is discussed, showing that flexibility is reducing the DEL in case of turbulent inflow, acting as a damper breaking larger cycles into smaller ones.

Investigating the Implementation of Classroom Assessment by Novice English Teachers

Classroom assessment plays an important role in the success of English language teaching and learning in the classroom. Besides, implementing classroom assessment can be challenging for teachers since it needs a comprehensive process as well as adequate knowledge related to the subject matter. Some previous studies have proven that Indonesian novice teachers of English faced various challenges related to the real field of teaching that assessment is one of the challenges. Regarding the challenges of the assessment, this research is aimed at investigating the implementation of classroom assessment in assessing students’ English skills including its challenges and opportunities faced by novice English teachers. This research employed an open-ended questionnaire involving four female novice English teachers who have less than three years of teaching experience when this research is conducted. The results show that most of the novice English teachers implemented achievement tests that are often summative and used various tasks for assessing their students’ English skills. However, some of the novice English teachers could not answer the questions related to their practices of the assessment principles. Furthermore, the novice English teachers experienced challenges in implementing the classroom assessment such as when implementing peer-assessment, creating a valid grade in the assessment process, and not having enough time for the test preparation. Lastly, one of the novice English teachers involved in this research experienced the opportunities related to the implementation of classroom assessment as assessment not only can reflect the students’ learning progress, but also can know the weakness of the teaching.

A ROBUST DEEP LEARNING APPROACH TO ENHANCE THE ACCURACY OF POMEGRANATE FRUIT DISEASE DETECTION UNDER REAL FIELD CONDITION

Pomegranate fruits are infected by various diseases and pests, which negatively affect food security, productivity, and quality. Recent advancements in deep learning with Convolutional Neural Networks (CNNs) have significantly improved the accuracy of fruit disease detection and classification. The main objective of this investigation is to find the most suitable deep-learning architecture to enhance fruit disease detection and classification accuracy. The current study proposed an efficient deep learning-based approach to detect the most prominent diseases of pomegranate such as bacterial blight, anthracnose, fruit spot, wilt, and fruit borer. For experimentation, a total of 1493 stagewise diseases development images of fruits and leaves are captured via a camera of an interval of 25 days for a total of six months duration. Additionally, extensive data augmentation was performed to increase the dataset, data diversity and to achieve a more robust model for disease detection. For this, the performance of three CNN-based architectures i.e., ResNet50, ResNet18, and Inception-V3 on a real field environment dataset was measured. Experimental results revealed that the proposed CNN-based ResNet50 architecture has effectively detected and classified five different types of diseases whose symptoms are not well defined and with the capability to deal with complex backgrounds. The optimized ResNet50 model achieved 97.92 % test accuracy over ResNet18 (87.5 %) and Inception-V3 (78.75 %) on learning rate 0.001. The multiclass cross-entropy loss function is applied for determining the error rate. To deal with CNN ‘Black Box’ problem Grad-CAM model can be used in the future. The proposed method will help the agricultural industry in detecting the most prominent diseases of pomegranate, which are likely to cause a decrease in productivity, thereby avoiding economic loss.

A New Model for Real-Time Prediction of Wellbore Stability Considering Elastic and Strength Anisotropy of Bedding Formation

Severe wellbore stability issues were reported while drilling in laminated formation with weak planes such as beddings. To accurately determine the safe mud weight according to the changing environment is of primary importance for safety control of drilling. Considering both the elastic and strength anisotropy of bedding formation, a novel theoretical model is established and the stress and failure around wellbores are analyzed. The accuracy and applicability of the theoretical model is verified by in situ field data. For the purpose of fulfilling real-time prediction, the method flowchart of programming is also provided. The results show that the model built can be conveniently used to predict the stress distribution, failure area, and collapse and fracture pressure while drilling, and rather good predictions can be made compared to real field data. In addition, the inhomogeneity of in situ stress and elastic parameters affect the upper limit of the safe mud weight window (SMWW) greater than the lower limit. Negative SMWW may appear with the direction change of the wellbore or weak plane, especially when the azimuths of them change. As to the magnitude of SMWW, the anisotropic effects of Young’s modulus are greater than the Poisson’s ratio. The method established in this paper can greatly help with the precise prediction of wellbore stability as drilling proceeds in bedding formation.

The effect of gravity drainage mechanism on oil recovery by reservoir simulation; a case study in an Iranian highly fractured reservoir

A comprehensive reservoir simulation study was performed on an oil field that had a wide fracture network and could be considered a typical example of highly fractured reservoirs in Iran. This field is located in southwest of Iran in Zagros sedimentary basin among several neighborhood fields with relatively considerable fractured networks. In this reservoir, the pressure drops below the saturation pressure and causes the formation of a secondary gas cap. This can help to better assess the gravity drainage phenomenon. We decided to investigate and track the effect of gravity drainage mechanism on the recovery factor of oil production in this field. In this study, after/before the implementation of gas injection scenarios with different discharges, the contribution of gravity drainage mechanism to the recovery factor was found more than 50%. Considering that a relatively large number of studies have been conducted on this field simultaneously with the growth of information from different aspects and this study is the last and most comprehensive study and also the results are extracted from real field data using existing reservoir simulators, it is of special importance and can be used by researchers.

Плюригармонические определимые функции в некоторых $o$-минимальных расширениях вещественного поля

In this paper, we first try to solve the following problem: If a pluriharmonic function $f$ is definable in an arbitrary o-minimal expansion of the structure of the real field $\overline{\mathbb{R}}:=(\mathbb{R},+,-,.,0,1,<)$, does this function be locally the real part of a holomorphic function which is definable in the same expansion? In Proposition 2.1 below, we prove that this problem has a positive answer if the Weierstrass division theorem holds true for the system of the rings of real analytic definable germs at the origin of $\mathbb{R}^n$. We obtain the same answer for an o-minimal expansion of the real field which is pfaffian closed (Proposition 2.6) for the harmonic functions. In the last section, we are going to show that the Weierstrass division theorem does not hold true for the rings of germs of real analytic functions at $0\in\mathbb{R}^n$ which are definable in the o-minimal structure $(\overline{\mathbb{R}}, x^{\alpha_1},\ldots,x^{\alpha_p})$, here $\alpha_1,\ldots,\alpha_p$ are irrational real numbers.