bluuebunny/crossref_metadata_2025_split huggingface dataset:
Are students having trouble solving problems polyhedron?
Authors: Arifah A N , Retnawati H 
Published: September 2020

AbstractThe ability to solve problems is not only needed in school learning, but also to solve problems in daily life. One of the problems that cannot be separated from daily life is related to space objects such as tables, cabinets, bottles, balls, houses, and others. Mathematics is a lesson’s school that addresses these problems, especially regarding (to) polyhedrons. The purpose of this study is to describe the difficulties of students in solving problems related to polyhedrons. The difficulties are classified based on Newman’s Error Procedure (NEP). The research method used is a case study. The respondents of this study were middle school students of class IX (ninth grade of middle school). Data collection is done through tests and interviews. Validity is measured based on the Aiken index with a score of 0.82 which mean it is very valid. The difficulties are analyzed descriptively by observing the students’ errors in answering test questions. The results showed that about 8% of students had difficulty in reading error, 13% of students had difficulty in comprehension error, 21% of students had difficulty in transformation error, 49% of students had difficulty process skills error, and 71% of students had difficulty in encode error. It is known several factors that cause these errors so that some solutions can be obtained by the teacher to overcome these errors.
Analysis of metacognition ability in solving environmental mathematics problems
Authors: Mumu Jeinne , Tanujaya Benidiktus 
Published: September 2020

Abstract
This study aims to analyse the metacognition abilities of students in solving environmental mathematical problems. The method used is the descriptive qualitative method. The research instruments used were ability tests, questionnaires, and interview guidelines. The subjects included 18 students of Mathematics Education. The students were chosen randomly from the group of students’ interests in algebra. The results showed that there were three groups of students based on metacognition abilities, aware, reflective, and strategic learner. The first group is aware learner who are knows about some of the kinds of thinking they do. The second group is strategic learner, who are knows the strategies to help them learning something. The last group is reflective learner who are able to reflect upon their thinking in progress, ponder their strategies and revise them. These results prove that environmental education can be integrated in mathematics through the use of environmental mathematics problems. Integrating environmental education and mathematics can improve students’ metacognitive abilities as well as increase students’ awareness of environmental problems.
Students’ cognitive style in mathematical thinking process
Authors: Izzatin M , Waluyo S B , Rochmad  , Wardono  
Published: September 2020

Abstract
The process of mathematical thinking in learning mathematics is very important. One internal factor that affects it is cognitive style. The purpose of this study is to describe how each student’s cognitive style performs mathematical thinking processes. The types of cognitive styles studied are field dependent (FD) and field independent (FI). This research is a literature study by examining journals related to cognitive style and students’ mathematical thinking abilities. The results of journals review show that students with FI cognitive style analyze and orient analytically to process information and are able to process information using mathematical notation and their own language, and are able to model problems using image visualization. Students with FD cognitive styles adopt a global orientation to understand and process information. In solving mathematical problems, students with FI cognitive style were better than students with FD cognitive style.
Enhancing students’ self-efficacy through metacognitive strategies in learning mathematics
Authors: Amal M F , Mahmudi Ali 
Published: September 2020

Abstract
Student activities in the learning process in the classroom have not yet determined the effectiveness in thinking and learning. Students and teachers must learn in the right collaboration, one of which applies a learning strategy. Metacognitive strategies are learning strategies that support students in improving their cognitive abilities. The cognitive development of students is very important because it is often used with children’s intelligence and children’s intelligence is always directly proportional to self-efficacy. In addition to cognitive, affective domains are also important to stimulate students’ minds to improve their academic abilities. The question is that students’ self-efficacy, self-efficacy depends on the individual’s confidence in his ability to complete the task. In this paper, the authors argue that metacognitive strategies can be applied in mathematics learning to improve students’ self-efficacy in two ways. First, the orientation of the two variables are similar, although not completely as metacognitive activities are able to train students’ thinking processes and their relevance with self-efficacy ie students who have a high sense of self-efficacy will affect their cognitive processes, for example students who are taught using metacognitive strategies will have a positive impact on metacognition and self-efficacy abilities. Second, learning with metacognitive strategies based on strengthening self-efficacy students will obtain high academic achievements in several cognitive aspects, such as reasoning and communication skills, problem solving skill.
Unconstrained optimization based fractional order derivative for data classification
Authors: Hapsari Dian Puspita , Utoyo Imam , Purnami Santi Wulan 
Published: September 2020

AbstractData classification has several problems one of which is a large amount of data that will reduce computing time. The Fractional gradient descent method is an unconstrained optimization algorithm to train classifiers with support vector machines that have convex problems. Compared to the classic integer-order model, a model built with fractional calculus has a significant advantage to accelerate computing time. In this research it is to conduct a qualitative literature review in order to investigate the current state of these new optimization method fractional derivatives can be implemented in the classifier algorithm.
Statistics literacy: what, why and how?
Authors: Hidayati N A , Waluya S B , Rochmad  , Wardono  
Published: September 2020

Abstract
21st Century learning directs human resources to become literate societies, where human resources can obtain information, organize, facilitate, communicate in various contexts. Statistical literacy and mathematical literacy are among the developed literacy. Statistics Literacy and mathematical literacy might be like literacy about the same discipline, but is that the case? What exactly is statistical literacy? How is the mindset designed to be built in statistical literacy? How to calculate the statistical literacy of a person? Why has it become an important competency for society today? This paper will try to explain it.
Pressure based active load control of a blade in dynamic stall conditions
Authors: Barrio J. Fernández , Mertens C. , Ragni D. , Schiacchitano A. , Oudheusden B. van 
Published: September 2020

Abstract
A proportionate controller is investigated experimentally for unsteady load alleviation purposes on a 2D wing model with a trailing-edge flap. The controller acts on the velocity of the flaps, and pressure sensors are used to detect the unsteady loads, which are generated by actuating the wing model in a sinusoidal motion. Two different regimes are considered: attached flow and dynamic stall. The influence of actuation frequency and controller time lag is also studied. A reduction of 87.5% in the standard deviation of the lift is obtained for a frequency of 0.2Hz and time lag in the control system of 12ms for attached flow conditions. The reduction of the standard deviation of the lift deteriorates for increased frequency and time lag. The proposed controller is also able to reduce the loads during dynamic stall, although the reduction is smaller, close to 40%, and can negatively affect the aerodynamic damping of the model. The flap actuation is also shown to delay the onset of dynamic stall, by increasing the static stall angle with respect to the case without flap deflection.
Response sensitivity of a semisubmersible floating offshore wind turbine to different wind spectral models
Authors: Putri R M , Obhrai C , Jakobsen J B 
Published: September 2020

Abstract
Previous research on the OC3 spar floating offshore wind turbine (FOWT) has shown the sensitivity of the yaw and side-side modes’ load and motion responses to different atmospheric conditions. Using the same baseline turbine of the OC3 spar wind turbine for a semisubmersible floater (OC4), this study investigates the load and motion responses of such offshore wind turbine for neutral and unstable atmospheric conditions. The effect of different levels of wind spatial coherence associated with two different wind spectral models for neutral conditions (Kaimal and Mann) are studied for the same turbulence intensity levels. An increase of 18% in the tower torsional moment fatigue damage equivalent load (DEL) is observed for the wind inflow with the weakest coherence (Mann spectral model), compared to the DELs under turbulent wind inflow with the highest coherence (Kaimal spectral model). Unstable atmospheric conditions are also simulated based on the Pointed-Blunt spectral model derived from FINO1 wind measurement. The yaw mode of the semisubmersible wind turbine is found to be the response component most affected by the variation in atmospheric stability conditions. A 28% higher fatigue DEL for the tower torsional moment is observed for very unstable atmosphere than the DELs under neutral atmospheric conditions.
A Novel Frequency Regulation Control Method for Deloaded Wind Turbines
Authors: Karimpour Mostafa , Schmid Robert , Tan Ying 
Published: September 2020

Abstract
The recent proliferation of converter-based power generating systems used within renewable energy sources has increased the need to consider how renewable energy sources, including wind turbines, may participate in ancillary services to ensure the security of the power grid. In this paper, we discuss a modern control methodology known as exact output regulation (EOR) and investigate its application to the problem of wind turbine provision of grid frequency support services. The EOR method assumes that both wind preview information from LIDAR measurements and the power demand curve from the grid are available in the design of the turbine control law. Our simulation study will compare the performance of EOR with a baseline controller, for the tracking of a time-varying power demand curve. Our work focuses on region 3 wind signals, however it has the capability to extend to other wind speed region. The simulations will employ the FAST simulator for a 5MW wind turbine, with wind signals generated by TurbSim. The simulations show that the LIDAR-enhanced EOR method has the potential to substantially improve power demand tracking performance, relative to a baseline controller.
Multi-Sectional Lift Actuation for Wind Turbine Load Alleviation
Authors: Liu Chang , Gupta Abhineet , Rotea Mario 
Published: September 2020

Abstract
The development of large rotors can be limited by the ability to manage dynamic loads. Active Flow Control (AFC) actuators have been proposed to reduce these dynamic loads. This paper aims to study and quantify the advantages of using multiple AFC actuators compared to using a single AFC actuator for each blade. For this study, AFC actuators are idealized and modeled as instantaneous changes to the local lift coefficient at the corresponding blade sections. We refer to this idealized actuators as sectional lift actuators (SLA). A comparison between a single SLA and two SLAs per blade is made using feedforward and feedback control. Blade loads in above-rated wind conditions are used for the comparative analysis, which is conducted using the DTU-10MW reference turbine model.
Revisiting disturbance accommodating control for wind turbines
Authors: Sinner Michael , Pao Lucy Y. 
Published: September 2020

Abstract
Disturbance accommodating control has received considerable interest in the wind turbine research community for its ability to explicitly account for disturbances in the incoming wind field. Early work was based around estimating the disturbance from feedback information, while more recent research into disturbance accommodating control (as well as other feedforward control laws) has considered disturbance measurements produced by lidar. This work compares the two methods (estimating and measuring the disturbance) while keeping all other aspects of the controller the same. By doing so, we shed light on the performance improvements that can be attained using preview disturbance measurements of the wind.
Dynamic Flow Modelling for Model-Predictive Wind Farm Control
Authors: van den Broek Maarten J. , Wingerden Jan-Willem van 
Published: September 2020

Abstract
We aim to improve wind farm control for power output by building on the results from WFSim for the development of a dynamic wind farm model. This model will be part of a closed-loop, economic model-predictive control approach for wind farms. It is constructed from first principles using open-source tools to be suitable for adjoint-based optimisation of turbine yaw angles.
In a steady-state inflow configuration with two turbines, the new control model matches power expectations from high fidelity simulations in SOWFA to within 15 %. Under time-varying wind directions, it shows time delays in wake direction as inflow changes propagate through the farm with the wind speed, although the dynamics still differ from the SOWFA reference. The model runs flow simulations for a wind farm with a 3 x 3 array of turbines at a real-time order of magnitude on a regular laptop computer.
The new control model shows dynamic flow behaviour as wake changes propagate through the wind farm. Some further adjustments are necessary to accurately model three-dimensional flow in two dimensions. With more validation of the wake dynamics, it will be suitable for application in a new closed-loop wind farm controller.
Expert Elicitation on Wind Farm Control
Authors: van Wingerden J. W. , Fleming P. A. , Göçmen T. , Eguinoa I. , Doekemeijer B. M. , Dykes K. , Lawson M. , Simley E. , King J. , Astrain D. , Iribas M. , Bottasso C. L. , Meyers J. , Raach S. , Kölle K. , Giebel G. 
Published: September 2020

Abstract
Wind farm control is an active and growing field of research in which the control actions of individual turbines in a farm are coordinated, accounting for inter-turbine aerodynamic interaction, to improve the overall performance of the wind farm and to reduce costs. The primary objectives of wind farm control include increasing power production, reducing turbine loads, and providing electricity grid support services. Additional objectives include improving reliability or reducing external impacts to the environment and communities. In 2019, a European research project (FarmConners) was started with the main goal of providing an overview of the state-of-the-art in wind farm control, identifying consensus of research findings, data sets, and best practices, providing a summary of the main research challenges, and establishing a roadmap on how to address these challenges. Complementary to the FarmConners project, an IEA Wind Topical Expert Meeting (TEM) and two rounds of surveys among experts were performed. From these events we can clearly identify an interest in more public validation campaigns. Additionally, a deeper understanding of the mechanical loads and the uncertainties concerning the effectiveness of wind farm control are considered two major research gaps.
Increasing wind farm efficiency by yaw control: beyond ideal studies towards a realistic assessment
Authors: Ciri U , Rotea M A , Leonardi S 
Published: September 2020

Abstract
Recent studies have demonstrated promising results for yaw control to mitigate wake interactions and optimize wind farm efficiency. These studies have been carried out for a single ‘ideal’ operating condition, typically assuming a fixed wind direction and speed. In a real scenario, the wind speed and direction change continuously over time, including cases in which yaw control does not provide any improvement. Thus, results from idealized studies cannot be generalized to estimate annual energy production (AEP) improvements in real scenarios with sufficient accuracy. In this paper, we provide a method to estimate the impact of yaw control on annual energy production, based on high-fidelity simulations. The stochastic procedure leverages high-fidelity numerical simulations to obtain a surrogate model with generalized Polynomial Chaos (gPC). For a single wind direction improvements of the order ∼ 10% are obtained; which is typical of an ideal estimate. On the other hand, the AEP gain is about 3% for the entire wind farm under realistic variable wind directions. The magnitude of the AEP gain is site-dependent. The proposed methodology provides an accurate tool useful for evaluating the value proposition of yaw control for wake steering.
Does the use of load-reducing IPC on a wake-steering turbine affect wake behavior?
Authors: Wang C , Campagnolo F , Bottasso C L 
Published: September 2020

Abstract
This paper aims at quantifying and explaining the effects of Individual Pitch Control (IPC) on the wake of a wake-steering wind turbine. As the machine is intentionally misaligned with respect to the wind, IPC can be used to mitigate the resulting extra loading. However, while IPC reduces loads, it also affects the wake, which influences the power of downstream turbines. The question is therefore whether the IPC activity has any other appreciable effect at the wind farm level, in addition to its original turbine-level load reduction goal. In this work, experiments and CFD simulations of scaled wind turbines in a boundary layer wind tunnel are considered. The CFD model is first validated with measurements, and then used to show subtle changes in the wake, power and loads caused by IPC. It is observed that IPC does indeed have some non-negligible effects, and that these effects differ for positive and negative yawing.
Determining Remaining Lifetime of Wind Turbine Gearbox Using a Health Status Indicator Signal
Authors: Lázaro Roberto , Yürüșen Nurseda Y. , Melero Julio J. 
Published: September 2020

Abstract
Wind turbine component’s failure prognosis allows wind farm owners to apply predictive maintenance techniques to their fleets. This permits optimal scheduling of the maintenance actions considering the best time to stop the turbines and perform those actions. Determining the health status of a turbine’s component typically requires verifying a wide number of variables that should be monitored simultaneously. The scope of this study is the investigation and the selection of an effective combination of variables and smoothing and forecasting methodologies for obtaining a wind turbine gearbox health status indicator, in order to interpret clearly the remaining lifetime of the gearbox. The proposed methodology is based on Gaussian Mixture Copula Model (GMCM) models combined with the smoothing treatment and the forecasting model to define the health index of the wind turbine gearbox. Then, the resulting index is tested using various warning and critical thresholds. These thresholds should be chosen adequately in order to indicate appropriate inspection visit and preventive maintenance intervention date. Then, the best combination found, for the studied cases, was 50% and 70% for warning and critical respectively. This combination ensures that the developed procedure is capable of providing long enough time window for maintenance decision making.
Model predictive control of wind turbine fatigue via online rainflow-counting on stress history and prediction
Authors: Loew S , Obradovic D , Bottasso C L 
Published: September 2020

Abstract
The standard fatigue estimation procedure is implemented in Model Predictive Control via externalization of the Rainflow algorithm from the optimization problem. Additionally, stress history is considered in a consistent manner by employing a so-called stress residue. The formulation is implemented in the state-of-the-art MPC framework acados and tested in closed-loop with the 5MW onshore turbine in OpenFAST. Simulation results indicate that the new formulation outperforms conventional PID- and MPC-controllers over the entire wind regime, and that the consideration of stress history is highly beneficial.
Vertical wake deflection for offshore floating wind turbines by differential ballast control
Authors: Nanos Emmanouil M , Letizia Stefano , Clemente Daniel J Barreiro , Wang Chengyu , Rotea Mario , Iungo Valerio I , Bottasso Carlo L 
Published: September 2020

Abstract
This paper discusses the idea of vertical wake deflection for offshore wind turbines using active ballast control. First, the concept of active ballast control for changing the attitude of an offshore wind energy semi-submersible platform is presented and briefly explored. Next, the influence of vertical wake deflection on the wake behavior and power production of a cluster of two wind turbines is studied through wind tunnel experiments and LES simulations. Results show that vertical deflection changes substantially the wake characteristics and affects the inflow at a downstream wind turbine in terms of available kinetic energy and turbulence intensity. For the most favorable case considered here, the cluster power was increased by approximately 8%.
Feedforward control for wave disturbance rejection on floating offshore wind turbines
Authors: Al M. , Fontanella A. , van der Hoek D. , Liu Y. , Belloli M. , van Wingerden J. W. 
Published: September 2020

Abstract
Floating offshore wind turbines allow wind energy to be harvested in deep waters. However, additional dynamics and structural loads may result when the floating platform is being excited by wind and waves. In this work, the conventional wind turbine controller is complemented with a novel linear feedforward controller based on wave measurements. The objective of the feedforward controller is to attenuate rotor speed variations caused by wave forcing. To design this controller, a linear model is developed that describes the system response to incident waves. The performance of the feedback-feedforward controller is assessed by a high-fidelity numerical tool using the DTU 10MW turbine and the INNWIND.EU TripleSpar platform as references. Simulations in the presence of irregular waves and turbulent wind show that the feedforward controller effectively compensates the wave-induced rotor oscillations. The novel controller is able to reduce the rotor speed variance by 26%. As a result, the remaining rotor speed variance is only 4% higher compared to operation in still water.