bluuebunny/crossref_metadata_2025 huggingface dataset:
Stable homotopy groups of spheres
Authors: Isaksen Daniel C. , Wang Guozhen , Xu Zhouli
Published: September 2020

Significance

The geometric objects of interest in algebraic topology can be constructed by fitting together spheres of varying dimensions. The homotopy groups of spheres describe the ways in which spheres can be attached to each other. From the viewpoint of algebraic topology, detailed knowledge of these groups would lead to a classification of geometric objects. We summarize the state of previous knowledge of the stable homotopy groups of spheres through dimension 61 and provide information in dimensions 62 through 90. It is a highly counterintuitive fact that some high-dimensional spheres can be viewed in more than one way from the perspective of differentiability. We enumerate these differentiable structures through dimension 90, except for dimension 4.
Decoding the mystery of American pain reveals a warning for the future
Authors: Case Anne , Deaton Angus , Stone Arthur A.
Published: September 2020

Significance

The elderly in the United States report less pain than those in midlife—suggesting, perhaps, that once people move into old age, their morbidity will fall. Unfortunately, assessing pain by age at one point in time masks the fact that each successive birth cohort reports more pain at any given age than the cohorts that came before it. We cannot use the experience of the elderly today to project pain prevalence of the elderly tomorrow. Today’s elderly have experienced less pain throughout their lives than those in midlife today, who will be tomorrow’s elderly. If these patterns continue, pain prevalence will continue to increase for all adults; tomorrow’s elderly will be sicker than today’s elderly, with serious implications for healthcare.
Genes and environments, development and time
Authors: Boyce W. Thomas , Sokolowski Marla B. , Robinson Gene E.
Published: September 2020

A now substantial body of science implicates a dynamic interplay between genetic and environmental variation in the development of individual differences in behavior and health. Such outcomes are affected by molecular, often epigenetic, processes involving gene–environment (G–E) interplay that can influence gene expression. Early environments with exposures to poverty, chronic adversities, and acutely stressful events have been linked to maladaptive development and compromised health and behavior. Genetic differences can impart either enhanced or blunted susceptibility to the effects of such pathogenic environments. However, largely missing from present discourse regarding G–E interplay is the role of time, a “third factor” guiding the emergence of complex developmental endpoints across different scales of time. Trajectories of development increasingly appear best accounted for by a complex, dynamic interchange among the highly linked elements of genes, contexts, and time at multiple scales, including neurobiological (minutes to milliseconds), genomic (hours to minutes), developmental (years and months), and evolutionary (centuries and millennia) time. This special issue of PNAS thus explores time and timing among G–E transactions: The importance of timing and timescales in plasticity and critical periods of brain development; epigenetics and the molecular underpinnings of biologically embedded experience; the encoding of experience across time and biological levels of organization; and gene-regulatory networks in behavior and development and their linkages to neuronal networks. Taken together, the collection of papers offers perspectives on how G–E interplay operates contingently within and against a backdrop of time and timescales.
Assessing L2 learners’ pragmatic ability in problem-solving situations at English-medium university
Authors: Ikeda Naoki
Published: September 2020

This paper discusses the oral pragmatic ability of current and prospective university students (international students) in an
English-speaking country by examining how they are differentiated in the assessed levels of this target ability. A total of 67 students, all
of whom were second language (L2) speakers of English, completed a set of oral discourse production tasks simulating interpersonal settings
encountered at university. Their task performances were analyzed qualitatively and quantitatively. The results show a substantial gap
between the highest performing university students and the prospective students in terms of their measured pragmatic ability. However, some
university students scored quite poorly and were actually outperformed by a certain number of prospective students who were preparing to
satisfy the English language requirements for university admission. These findings suggest that being a university student is not
necessarily an indicator of having sufficiently developed pragmatic ability to participate in interpersonal settings in an academic
environment. The findings shed light on the importance of providing students learning and assessment opportunities for pragmatics so they
can gain greater awareness of their own developing pragmatic ability in an English-medium university.
Conserved actin machinery drives microtubule-independent motility and phagocytosis in Naegleria
Authors: Velle Katrina B. , Fritz-Laylin Lillian K.
Published: September 2020

Much of our understanding of actin-driven phenotypes in eukaryotes has come from the “yeast-to-human” opisthokont lineage and the related amoebozoa. Outside of these groups lies the genus Naegleria, which shared a common ancestor with humans >1 billion years ago and includes the “brain-eating amoeba.” Unlike nearly all other known eukaryotic cells, Naegleria amoebae lack interphase microtubules; this suggests that actin alone drives phenotypes like cell crawling and phagocytosis. Naegleria therefore represents a powerful system to probe actin-driven functions in the absence of microtubules, yet surprisingly little is known about its actin cytoskeleton. Using genomic analysis, microscopy, and molecular perturbations, we show that Naegleria encodes conserved actin nucleators and builds Arp2/3–dependent lamellar protrusions. These protrusions correlate with the capacity to migrate and eat bacteria. Because human cells also use Arp2/3–dependent lamellar protrusions for motility and phagocytosis, this work supports an evolutionarily ancient origin for these processes and establishes Naegleria as a natural model system for studying microtubule-independent cytoskeletal phenotypes.
Mutations make gut antibodies promiscuous
Authors: Grasset Emilie K. , Cerutti Andrea
Published: September 2020

In this issue, Kabbert et al. (https://doi.org/10.1084/jem.20200275) show that intestinal antibodies from healthy subjects or patients with Crohn’s disease cross-target diverse but distinct communities of the gut microbiota through a mechanism involving somatic hypermutation but not germline-encoded polyreactivity.
Structural stability of CuAl2O4 under pressure
Authors: Agzamova P A , Belik A A , Streltsov S V
Published: September 2020

Structural properties of CuAl2O4, which was recently argued to show unusual suppression of the Jahn–Teller distortions by the spin–orbit coupling, are investigated under pressures up to 6 GPa. Analysis of x-ray powder diffraction experiments shows that CuAl2O4 gets unstable and decomposes onto CuO and Al2O3 at pressures ∼6 GPa and temperature ∼1000 K. This finding is complemented by the density-functional theory + U + spin–orbit coupling calculations, which demonstrate that this instability is partially driven by a (relatively) large compressibility of strongly Jahn–Teller distorted CuO.
Improved SDA-ss algorithm for nonsymmetric algebraic Riccati equations
Authors: Wu Runsheng , Tang Bo
Published: September 2020

It is well known that nonsymmetric algebraic Riccati equation can be efficiently solved by using the structure-preserving doubling algorithm (SDA) with the shift-and-shrink transformation and the corresponding doubling algorithm is called the SDA-ss. In this paper, we propose an improved SDA-ss algorithm. Preliminary numerical experiments show that the algorithm is efficient to derive the minimal nonnegative solution of nonsymmetric algebraic Riccati equation with M-matrix.
The host-market valuation effect of foreign company cross-listings — the case of the Hong Kong market
Authors: Ma Mengmeng , Yi Ronghua , Yu Ying , Yao Xiaoyang
Published: September 2020

This paper studies the valuation effect of time-varying and the difference between different markets of overseas companies cross-listing on the host market. Using the data of the Hong Kong market from 1991 to 2018, we adopt the event study method and multiple regression model to analyse the short- and long-term valuation effect, respectively. Furthermore, two-stage least squares (2SLS) regression are utilized to address the endogeneity. We find that the valuation of foreign company listings on the host market change with the duration and have a significant short-term positive spillover effect. However, the long-term spillover effect is related to the company’s home market. This study provides new insights into foreign cross-listing company valuation, offering a few implications for the establishment of a Chinese International Board.
Automatic detection process of solar active region based on SDO/AIA digital image
Authors: Sukarsih I , Hermawanti A , Respitawulan  , Priyatikanto R , Kurniati E
Published: September 2020

The aim of this study is to do automatic detection of the sunspot on the solar disc using MATLAB. The digital images from the satellite SDO (Solar Dynamic Observatory)/AIA (Atmospheric Imaging Assembly) with 512 x 512 pixels jpg image were being processed through several steps: segmentation threshold to separate the object from its background and obtain the area and coordinate points (centroids) of the sunspots. Then, the sunspot coordinates gained from the automatic detection are compared with the coordinates released by NASA at solarmonitor.org. The error calculation using RMSE gives 30.824022 “to 1120.2831” for horizontal position and 46.509763 “to 266.74988” for vertical position. The errors are still considered significant since Lembaga Penerbangan dan Antariksa Nasional (LAPAN, Indonesian National Institute of Aeronautics and Space) specify the error tolerance value of 20” maximum. The main factor for the difference is the spatial characteristics of the EUV images used for automatic detection are different with the characteristics of the photosphere image used by solarmonitor.org as the catalogue reference of the sunspots.
Student mathematical anxiety: investigation on problem based learning
Authors: Jatisunda M G , Kania N , Suciawati V , Nahdi D S
Published: September 2020

Problem-based learning is an alternative for students to exercise problem-solving ability. During the mathematics learning process, students also experience mathematics anxiety which prevents them to perform well. This study aims to explore the students’ mathematics anxiety in the problem-based learning process. Based on previous studies, problem-based learning was designed to reduce mathematics anxiety. This research is qualitative research with a phenomenology approach. The phenomenological research was examined based on the experience of the participants attending the mathematics classes with problem-based learning. In this study, we chose the subjects by considering the results of mathematics anxiety tests and students’ physical characteristics that indicate the occurrence of mathematical anxiety. The results found that students with high and moderate mathematics anxiety showed physical characteristics of mathematical anxiety observed during the problem-based learning process. After conducting in-depth interviews with the subjects, it was found that they had difficulty with the mathematics problems given. Finally, we concluded that the selection of mathematical problems given with the hope that it will reduce mathematical anxiety turns out to cause mathematical anxiety. It then affected their work that has not succeeded in solving the mathematics problems.
Pre-service mathematics teachers’ experiences of teaching practice in function composition
Authors: Kania N , Nurhikmayati I , Suciawati V
Published: September 2020

Generally, teaching practice is carried out as a conceptual decision in achieving the vision and mission of tertiary institutions and each faculty in an effort to produce qualified teacher candidates who are ready to deal directly with the community or school. The research aims to description performance students’ math education at Majalengka University in teaching practice. The approach used was a qualitative case study in students’ math education at Universitas Majalengka. Data sources sourced from the students’ math education who establish teaching practice at school partner academic year 2018/2019, teacher and student school partner. The results show that observation provides a lot of information that is very useful for prospective teachers to develop their competencies. Next, participated in teaching practice does not get many a chance to practicing and they shall not find special guidance from tutor teachers. Participated in teaching practice would be able to execute study practice independent learning. Furthermore, experiences within were making plans for the implementation of a lesson (RPP) has got a good deal. Participated in teaching practice had a wealth of experience in their activities to get extra on the school. The achievement of competence would be good enough. Participated in teaching practice is still following a lecture once at the campus. Lastly, participated in teaching practice need to improve its ability in using the learning methods and the media learning to promote disorder too.
Flexibility in solving open-ended mathematics problems based on students’ thinking styles
Authors: Isyrofinnisak F , Kusmayadi T A , Fitriana L
Published: September 2020

Flexibility is one of the abilities needed to solve mathematical problems using a variety of different perspectives. One factor that affects flexibility is students’ thinking styles. Students’ thinking styles are classified into 4 types, namely Concrete Sequential (CS), Abstract Sequence (AS), Concrete Random (CR), and Abstract Random (AR). These four thinking styles have an important role in increasing students’ understanding of the learning process. The aim of this research is to see the extent of students ‘mathematical flexibility abilities in solving open problems based on students’ thinking styles. This research uses descriptive research with a qualitative approach. The subjects in this study were 4 students. The research began by giving students a thinking style questionnaire which was then continued by giving open test questions and interviews. The validity of data measured using the triangulation method. The results of this study indicate that CS students, AS students, and CR students, have not been able to achieve indicators of flexibility, whereas AR students can achieve indicators of flexibility in solving open problems.
Metacognition skills and higher order thinking skills (HOTS) in mathematics
Authors: Albab U , Budiyono  , Indriati D
Published: September 2020

Based on the results of interviews with teachers and observations of mathematics students of class VIII at the school where the research is, the difficulty of students in learning material related to high-level thinking problems (HOTS) when receiving or understanding concepts given by the teacher. This study aims to find out how the influence of metacognition skills to the ability of Higher Order Thinking Skills (HOTS) MTs N 1 Kudus students and bias can be used as a trigger to increase Higher Order Thinking Skills (HOTS) skills. Hypothesis testing uses simple linear regresi. The results of this study indicate that: 1) there is a positive and significant correlation to the Higher Order Thinking Skills (HOTS) skills of 60.8%: 2) there is a positive and significant correlation to the Higher Order Thinking Skills (HOTS) skills based on indicators of metacognition skills (awareness = 43.8%, regulation = 65.5%, and evaluation = 57.8%).
Exploring students’ critical thinking skills in a geometry lesson
Authors: Hidayat D , Rosnawati R
Published: September 2020

The ability of critical thinking in mathematics is an important ability that should be mastered by students. The goal of this research is to describe students’ critical thinking in a geometry lesson. This research is a survey study in which the data are taken by the documentation. Students’ answers used in this data based on critical thinking questions in which 17 students’ in 8th grade on one of the junior high schools in Yogyakarta are involved in this research. Students’ critical thinking instruments consist of 6 questions which have three aspects, namely analyzing, evaluating, and concluding in which each is with a picture and without the picture. The result of this research shows that analyzing aspect with picture questions has a better result compare to the question without picture. Similarly, in evaluating and concluding aspects, the data show that students’ answers are better with the picture rather than the question without the picture. Furthermore, from the results of the sample students’ exploration answers, it is expected that learning in future geometry can facilitate students’ critical thinking skills then, the learning of geometry is better presented by using the pictures.
Classification of genetic expression in prostate cancer using support vector machine method
Authors: Komarudin S A , Anggraeni D , Riski A , Hadi A F
Published: September 2020

Prostate cancer has long been a concern of expert’s human genetics in health research. However, an explanation of the main causes of prostate cancer cannot be obtained metabolically-biologic, except the most common one of which is heredity. Explanation of the risk of contracting prostate cancer is sought through genetic explanation of prostate cancer cells and healthy prostate cells from DNA sequencing in the form of micro arrays data or in the form of Gleason values. Cancer cell genetic data is high dimensional where the number of variables observed were far more than the individual observed. It’s make ordinary multivariate classification techniques fail to handle this data because of the singularity matrix. In addition, the observations number of cancer patients are small since they are rarely found. With these two facts, then in this paper we will use a machine learning approach to study the classification, namely SVM. SVM will be compared with the Naive Bayes Classifier and Discriminant Analysis method to determine the accurate division in distinguishing prostate cancer cells from healthy prostate cells. The sample data used consisted of 102 people with 2135 genetic variables which were then divided into training data and testing data. Based on the results of the study, the classification by the SVM method has an accuracy value of 96% with a precision error in the tumor class of 7%. The Naive Bayes classification has a precision error of 23.5% with a classification accuracy of 84%. While the Discriminant Analysis method produces an accuracy of 92% with a precision error of 13.33%.
Geogebra in integral areas to improve mathematical representation ability
Authors: Septian A , Darhim  , Prabawanto S
Published: September 2020

Integral Calculus is material that must be understood by students as a basis for teaching in school. The ability of mathematical representation of an integral area is felt to be less comprehensively mastered. It is indicated by the large number of students having difficulty in making graphic visual displays. Several researchers make some approaches through technology-based media, including GeoGebra. The purpose of this study is to find out better improvement between the mathematical representation abilities of students who use GeoGebra in Integral Areas with conventional learning in terms of overall and prerequisite abilities. In this research, the sample is fourth semester students of the Mathematics Education Study Program at Universitas Suryakancana. The design of this study uses a nonequivalent control group design with purposive sampling technique. As a result, the improvement of Students’ mathematical representation ability who use GeoGebra in integral area is better than students who use conventional learning and mathematical representation ability with the category of high and low prerequisite abilities using Geogebra in Integral Areas is better than those carrying out conventional learning in the category of high and low prerequisite abilities.
Does gender affect the mathematics creativity of junior high school students?
Authors: Permatasari S D A , Budiyono  , Pratiwi H
Published: September 2020

Mathematics learning in the 21st century is a learning that emphasizes the importance of development in 4 aspects (4C), one of them is creativity. Mathematical creativity is students’ skill to solve a problem with several strategies to reach different answers in certain tasks which are useful in developing mathematical reasoning. Relating to this context, nowadays, the issues of gender in education have been concern, that education must treat male and female students as equal. This research used one-way ANOVA to analyze the differences between the mathematical creativity between male and female students in junior high school. The research method used was quantitative descriptive. The sample of this research was 56 students of SMP Batik Surakarta who were taken by random sampling method. The results found that male and female students did not have differences in the ability of mathematical creativity. The insignificant difference can only be seen from their average scores. Female students are superior to male in the indicators of fluency, flexibility, and elaboration, but not in the indicator of originality.
Non-empirical Induction in mathematics conjecturing in the new knowledge construction
Authors: Supratman  , Rustina Ratna , Heryani Yeni
Published: September 2020

This study aims to describe students’ conjecturing ability in accordance with and without the use of empirical mathematical induction methods in solving problems and building new knowledge. Data were obtained from 57 students in grade 8 by using the conjecturing process and unstructured interviews. The result showed that the conjectured process using empirical induction was longer than without its usage in solving problems and building new knowledge. However, the use of empirical induction, leads to no accommodation of problems, strategies and relationships, compared to when it is not used as shown by the Piaget’s theory.
TORIQ: Android-based mobile learning for vector lessons
Authors: Pratama R A , Larasati D , Khotimah H
Published: September 2020

This research aims to produce an Android-based learning media using Adobe Flash CS6 Professional named TORIQ—Vector Intelligence Quiz. The product was developed by attention to aspects of validity, practicality, and effectiveness in X-grade students’ mathematics learning of Airlangga Health Vocational School of Balikpapan. The implementation used the design of MDLC model development which consists of concept, design, material collecting, assembly, testing, and distribution. The results were obtained from media testing consisting of Alpha 1 test, Alpha 2 test, Beta test in small group, and Beta test in large group. The results concluded that the Android-based TORIQ learning media that have been developed are included in the category of highly valid with a percentage of 86.928%, very practical with an average percentage of 85.208%; and effective with a percentage of completeness of 93.333%. Thus, as a whole, the TORIQ learning media developed can be an alternative media in learning activities, especially on vector material.
Mathematical literacy in pre-service elementary school teacher: A case study
Authors: Yustitia V , Amin S M , Abadi
Published: September 2020

A prospective teacher to possess the ability of mathematical literacy in order to formulate, to apply, and to interpret mathematics in various contexts, including abilities to do mathematical reasoning and use mathematical concepts. The purpose of this research is to describe the mathematical abilities of the prospective elementary school teachers to solve mathematical literacy problems. We involved prospective teachers in the Elementary School Teacher Education Department as the research participants. This research is a qualitative research. Data collected by interview and test. The result of this study suggested that the ability of prospective teachers to solve basic mathematical literacy problems for levels 1 and level 2 were good, level 3 was enough, but for level 4 or above were still low. This was caused by the low ability of mathematical literacy. Pre-service teachers were rarely accustomed to solving literacy questions and they were less used to deal with the connection process in solving mathematical problems.
Mathematical Representation Ability and Self -Efficacy
Authors: Hanifah  , Waluya S.B. , Rochmad  , Wardono
Published: September 2020

In mathematics, there are several abilities should be belong to students. One of the abilities should be belong to students is the ability of the mathematical representation. Mathematical representation ability makes it easy for students to solve mathematical problems, because students are required to make their mathematical models, by making mathematical models students will be easier to solve mathematical problems. This basic mathematical ability can be mastered well by students if students have affective abilities, one of them is self-efficacy. In this study, qualitative research methods are used. Descriptive research is chosen the type of literature study. Data collection method with literature study. This article examines the ability of the representation and self-efficacy in mathematics learning, which includes indicators of what needs to be developed in the ability of the mathematical representation, and indicators contained self-efficacy in mathematics learning. The brief description is based on an analysis of the representation abilities and self-efficacy in mathematics learning.
Ensemble-support vector machine-random undersampling: Simulation study of multiclass classification for handling high dimensional and imbalanced data
Authors: Rahmi Nur Silviyah
Published: September 2020

Microarray technology measures on a large and parallel scale to express tens of thousands of genes. It has widely applied to predict gene function, new subtypes of specific tumors and cancer classification. However, microarray data are known has feature characteristics such as high dimension, small sample, high noise, and imbalanced class distribution. Support Vector Machine (SVM) has been widely used and shows the success in major applications to improve classification performance. To overcome the high dimension, we applied the Ensemble-SVM method. This method classifies features use clustering hierarchy and each group will be classified. While the condition of imbalance data becomes a problem in classification because the classifier will tend to predict the majority class compared to the minority class. Therefore, a Random Undersampling or EnSVM-RUS method is used to balance the size of the majority class into the minority class. We uses threefold cross-validation with a feature selection method that is Fast Correlation Based Filter (FCBF). The multiclass method used is SVM One Against One (OAO). While the evaluation criteria of performance classification based on the value of accuracy, F-score and G-mean and running time. We performs a simulation study with various scenario level of ratio imbalance (IR) that is ratio 1, 5, and 8 to know the performance of the proposed method. While the application on real data using Microarray DNA data with IR 4.22, 15.00 and 23.17 The results showed that EnSVM-RUS-OAO method with 2 clusters had higher performance than the EnSVM-OAO and EnSVM-OAO methods. Increasing the ratio imbalance doesn’t affect the advantage of the EnSVM-RUS-OAO method when compared to EnSVM-OAO and EnSVM-OAO methods. While on the use of the kernel, RBF kernel and polynomials produce higher performance and shorter computation time than linear kernels.
Simulation of Traffic T-Junction at Cibiru-Cileunyi Lane Using SimEvents MATLAB
Authors: Harahap E , Darmawan D , Badruzzaman F H
Published: September 2020

The Cibiru-Cileunyi line (JCC) or also called as Cinunuk road located in Bandung Regency, West Java, Indonesia, is one of the most densely lane vehicles because it is the only non-toll road that connects various cities in the western and northern regions to cities in the southern and eastern regions of Java West. In addition, the activities of the city and regency of Bandung and also the local community have added to the traffic jam at JCC. JCC traffic has been complained about by many people who pass to go to school, work or other activities. Congestion occurs every day, especially at rush hour, i.e. in the morning at 6 AM to 8 AM and the afternoon at 4:00 PM to 7:00 PM. However, outside of these hours, high traffic jams are also always occur. JCC travel time can reach more than 1 hour in congested conditions, while at normal situation the travel time to cross at JCC is an average of 10 minutes. One of the causes of congestion is the high traffic in and out of vehicles at several T-junction locations at JCC, where almost every T-junction at JCC raises a very long vehicle queue. In this article a simulation is proposed to represent the JCC traffic situation. The simulation is created using the SimEvents MATLAB. In this simulation, some traffic engineering is applied, such as by manage the crossings in and out of vehicles at several T-intersections in the JCC to reduce congestion.
Mathematical reasoning in problem-solving in three dimensions
Authors: Arifanti D R
Published: September 2020

This research is a qualitative study, where the purpose of this study is to describe the form of student reasoning in solving three-dimensional problems. To establish a research class, namely students of class XI-IPA who have studied Geometry material, especially Dimension Three, then conducts an analyzed test to determine the subject to be selected in the study. The number of research subjects to be selected are 3 people (high-ability subjects (ST), medium-capable subjects (SS), and low-ability subjects (SR). The research process followed the stages: Reasoning students in solving three dimensional problems with the indicators are: 1) Understanding the Problem; 2) Devising a Plan; 3) Carrying Out the Plan; 4) Looking Back.
The Science of Making Torque from Wind 2020 (TORQUE 2020)
Authors: Watson Simon J
Published: September 2020

Wind power is starting to make a significant contribution to the decarbonisation of our energy systems throughout the world, though much remains to be done. Although, wind turbine technology is seen as commercially viable and, in many cases, now, subsidy-free, there are still a number of basic grand challenges in wind energy that the scientific and industrial community must address [1]. These include: providing a better understanding of atmospheric flows and how they interact with windfarms; an improved understanding of the aerodynamic, structural and hydrodynamic behaviour of wind turbines; and how to integrate ever greater volumes of wind energy into our electrical grids.

Europe has become very much a centre for the scientific and industrial expertise to address these challenges. To provide a focus for academic research in wind energy, the European Academy of Wind Energy (EAWE) was founded. The Academy has become arguably the world’s leading association of academic institutes active in wind energy. Amongst its many activities, EAWE founded a conference where leading researchers from around the world could present their work related to wind turbine technology. The conference was called The Science of Making Torque from Wind (or TORQUE, for short) and its inaugural edition was held in Delft in 2004. The conference has gone from strength to strength and is probably the largest scientific conference devoted to wind energy in the world. History came full circle and the eighth edition, TORQUE 2020 was due to be held in Delft again in the spring of 2020. Unfortunately, the COVID-19 pandemic meant that the hosting of a physical conference was no longer possible, so the host, the TU Delft Wind Energy Institute at the Delft University of Technology moved the conference fully online.

Following the call for three-page abstracts, more than 500 submissions were made and, after a two-stage per review process by over 150 reviewers, nearly 320 full papers were accepted for publication in the proceedings. The online conference consists of three plenary session, 28 parallel oral sessions and five poster sessions. Due to the online nature of the conference, oral presentations are to be kept short (eight minutes each) and plenary keynotes are restricted to 15 minutes to allow plenty of time for discussion. All poster presenters are allowed a recorded one-minute pitch which can be accessed during the online poster sessions.
Non quadratic smooth model of fatigue for optimal fatigue-oriented individual pitch control
Authors: Collet D , Alamir M , Domenico D Di , Sabiron G
Published: September 2020

Operation and maintenance cost of wind turbine is intimately related to fatigue damage. However, considering fatigue directly in an optimization needs to be carefully done because its faithful model does not fit standard forms. Recent results have shown that the fatigue damage of a signal estimated using fatigue theory is non-linearly related to its corresponding variance. Therefore, this relationship is used to design a convex cost function approximating fatigue. In this paper, the sensitivity of open-loop optimizations using this fatigue-oriented non-quadratic cost function to the time horizon considered is studied, in terms of both fatigue and computational cost. Moreover, in order to alleviate the undesirable effects of the computational cost, an efficient fixed-point iteration-based way to optimize this fatigue-oriented cost function is presented. Results show that the fatigue-oriented cost function allows to obtain sensitive fatigue reduction compared to optimizations using a family of classical quadratic cost functions, especially for long optimization horizons. It is eventually, shown that the prediction horizon length required for the non-quadratic criterion to be efficient in an MPC makes its use prohibitive in such framework. However, prospects of reaping the benefits of the fatigue-oriented optimization using imitation learning are given.
Prediction and Validation of Fatigue loads using Artificial Intelligence on Real World Measurement Data
Authors: Venu Anish , Lüdde Mike , Omole John
Published: September 2020

Monitoring the fatigue loads acting on the crucial structural components of a turbine plays a vital role in lifetime assessment, operational maintenance, load and power optimization of the wind farm. Generic physical models used in recent times are not highly reliable and does ascertain true decision-making situations. To determine the realistic fatigue loads acting on the turbine components requires expensive instrumentation with strain gauges. This work describes using an artificial intelligent model on real measurement data to make cost-effective estimation of fatigue loads acting on the wind turbines. The model is validated with real measurement data gathered from two onshore and one offshore commercial wind turbines.
Individual Blade Pitch Control for Extended Fatigue Lifetime of Multi-Megawatt Wind Turbines
Authors: Hoghooghi H. , Chokani N. , Abhari R. S.
Published: September 2020

A novel experimental study on the use of individual pitch control to extend the fatigue life of wind turbines is conducted. The experiment is accomplished using a sub-scale model of a multi-megawatt turbine in both upwind and downwind configurations in a water towing tank. It is shown that individual pitch control based on a sinusoidal pitching scheme that is locked to the phase of the rotor rotation can mitigate unsteady loads caused by the velocity variation that is induced by the effect of rotor tilt and therefore extends the fatigue lifetime of blades. A positive pitching amplitude in the case of upwind configuration and a negative pitching amplitude in the case of downwind configuration eliminate the cumulative damage fractions due to the velocity variation.
Numerical Validation of Wind Plant Control Strategies
Authors: Gomez-Iradi Sugoi , Astrain David , Aparicio María , Fernández Lorena , Chávez Roberto
Published: September 2020

Research work carried out with the support of the CL-Windcon EU project where flow control strategies (flow redirection or yaw misalignment, and flow induction control or de-rating) are validated. These strategies were divided in optimizing a wind farm (WF) in terms of wind farm Annual Energy Production (AEP), and in optimizing the wind farm to reduce the worst Damage Equivalent Load (DEL) in blade root flap-wise moment that sees a wind turbine (WT) while keeping the WF AEP as high as possible. Two numerical methods were employed. A modified FLORIS that takes into account the DEL was used in the optimization process and the simulations, the baselines and the optimized configurations, were replicated with a higher fidelity method, SOWFA, to verify the lower fidelity tool results prior to implementation in a real system. From the studied cases, it has been found that the wake steering approaches maximized the total power by 6 to 15%, and the flow induction strategies, despite having a poor performance increasing of the overall power productions, showed their validity for reducing the flap-wise moment DEL of the WT blade. Numerically, SOWFA and FLORIS simulations showed significant discrepancies in partial wake conditions, which suggested a need of a new tuning of the FLORIS parameters for partial wake conditions. Finally, mention that now, thanks to EU CL-Windcon project there are publicly available experimental data, wind tunnel data, and SOWFA data that could be used for validation purpose.
Investigation on a Shallow Water Annular Tuned Liquid Damper for Suppressing Vibration of Wind Tower
Authors: Zhang Youlin , Li Huaxiang , Xu Yiqing
Published: September 2020

Although the annular tuned liquid damper (ATLD) filling with shallow water is helpful in mitigating the vibration response of wind tower, it’s challenging in predicting the interface force between the ATLD and its supporting system and evaluating the damping contribution of the ATLD to the dynamic response of tower. In this study, we developed an approach to investigate the damping performance of the ATLD base on the cooperation between the smoothed particle hydrodynamics method (SPH) and the equivalent tuned mass damper model (TMD). Herein the SPH method is employed to numerically investigate the non-linear behaviour of sloshing waves in the damper and calculate the interface force, while the TMD method is used to express the TLD properties. Based on this approach, a series of numerical simulations of liquid sloshing in a shallow water ATLD with different excitation periods are carried out. The equivalent damping ratios of ATLD are calculated to quantitatively analyse the suppression effect of ATLD on the vibration response of a wind tower.
Optimal strain gauge configurations for the estimation of mechanical loads in the main shaft of HAWT
Authors: Iriarte X. , Aginaga J. , Lerga F.J. , Gainza G. , Ros J. , Bacaicoa J.
Published: September 2020

In Structural Health Monitoring of wind turbines, measuring the mechanical loads is a key issue. The customary techniques for this task use a full-bridge strain gauge configuration to measure each of the six load components exerted on the shaft. However, using only six strain gauges should be sufficient to estimate the six load components if a one-to-one correspondence was achieved. In this paper a different approach to mechanical loads estimation is presented where, measuring the strain of individual gauges in quarter-bridge configurations, it is possible to estimate all the load components from a single set of gauges. The configurations are optimally determined making use of the D-optimality criterion, which maximises the observability of the estimated components. The approach also provides configurations where the apparent strain related to temperature variations is automatically compensated. Results show several optimal configurations for different measuring conditions and shows that six strain gauges are enough to estimate all the load components. The new approach also opens the possibility to obtain configurations with more strain gauges as well as configurations that have to meet other requirements.
Adaptation of Engineering Wake Models using Gaussian Process Regression and High-Fidelity Simulation Data
Authors: Andersson Leif Erik , Doekemeijer Bart , Hoek Daan van der , Wingerden Jan-Willem van , Imsland Lars
Published: September 2020

This article investigates the optimization of yaw control inputs of a nine-turbine wind farm. The wind farm is simulated using the high-fidelity simulator SOWFA. The optimization is performed with a modifier adaptation scheme based on Gaussian processes. Modifier adaptation corrects for the mismatch between plant and model and helps to converge to the actual plan optimum. In the case study the modifier adaptation approach is compared with the Bayesian optimization approach. Moreover, the use of two different covariance functions in the Gaussian process regression is discussed. Practical recommendations concerning the data preparation and application of the approach are given. It is shown that both the modifier adaptation and the Bayesian optimization approach can improve the power production with overall smaller yaw misalignments in comparison to the Gaussian wake model.
Investigating parallel multi-step vibration processing pipelines for planetary stage fault detection in wind turbine drivetrains
Authors: Koukoura Sofia , Peeters Cédric , Helsen Jan , Carroll James
Published: September 2020

This paper proposes a signal processing approach for wind turbine gearbox vibration signals based on employing multiple analysis pipelines. These so-called pipelines consist of combinations of various advanced signal processing methods that have been proven to be effective in literature when applied to wind turbine vibration signals. The performance of the pipelines is examined on vibration data containing different wind turbine gearbox faults in the planetary stages. Condition indicators are extracted from every pipeline to evaluate the fault detection capability for such incipient failures. The results indicate that the multipronged approach with the different pipelines increases the reliability of successfully detecting incipient planetary stage gearbox faults. The type, location, and severity of the fault influences the choice for the appropriate processing method combination. It is therefore often insufficient to only utilize a single processing pipeline for vibration analysis of wind turbine gearbox faults. Besides investigating the performance of the different processing techniques, the main outcome and recommendation of this paper is thus to employ a diversified analysis methodology which is not limited to a sole method combination, to improve the early detection rate of planetary stage gearbox faults.
Applicability of machine learning approaches for structural damage detection of offshore wind jacket structures based on low resolution data
Authors: Cevasco D , Tautz-Weinert J , Kolios A J , Smolka U
Published: September 2020

Structural damage in offshore wind jacket support structures are relatively unlikely due to the precautions taken in design but it could imply dramatic consequences if undetected. This work explores the possibilities of damage detection when using low resolution data, which are available with lower costs compared to dedicated high-resolution structural health monitoring. Machine learning approaches showed to be generally feasible for detecting a structural damage based on SCADA data collected in a simulation environment. Focus is here given to investigate model uncertainties, to assess the applicability of machine learning approaches for reality. Two jacket models are utilised representing the as-designed and the as-installed system, respectively. Extensive semi-coupled simulations representing different operating load cases are conducted to generate a database of low-resolution signals serving the machine learning training and testing. The analysis shows the challenges of classification approaches, i.e. supervised learning aiming to separate healthy and damage status, in coping with the uncertainty in system dynamics. Contrarily, an unsupervised novelty detection approach shows promising results when trained with data from both, the as-designed and the as-installed system. The findings highlight the importance of investigating model uncertainties and careful selection of training data.
Tensile rotary power transmission model development for airborne wind energy systems
Authors: Tulloch O , Amiri A Kazemi , Yue H , Feuchtwang J , Read R
Published: September 2020

Rotary airborne wind energy (AWE) systems are a family of AWE devices that utilise networked kites to form rotors. One such device is the Daisy Kite developed by Windswept and Interesting. The Daisy Kite uses a novel tensile rotary power transmission (TRPT) to transfer power generated at the flying rotor down to the ground. Two dynamic models have been developed and compared; one with simple spring-disc representation, and one with multi-spring representation that can take account of more degrees of freedom. Simulation results show that the angular velocity responses of the two TRPT models are more closely correlated in higher wind speeds when the system shows stiffer torsional behaviour. Another interesting point is the observation of two equilibrium states, when the spring-disc TRPT model is coupled with NREL’s AeroDyn. Given the computational efficiency of the simpler model and the high correlation of the results between the two models, the simple model can be used for more demanding simulations.
Immersed boundary methods and their applicability in wind energy
Authors: Krishnan Navaneetha , Viré Axelle , Schmehl Roland , van Bussel Gerard
Published: September 2020

Airborne wind energy systems often use kites made of thin membranes to save material costs and increase mobility. However, this design choice increases the complexity of the aeroelastic behaviour of the system and demands high-fidelity tools. On the aerodynamic side of the multi-physics problem, it is quite challenging to create a high quality body conforming grid due to the complexity of the geometry and the degree of deformation it undergoes. Immersed boundary methods (IBMs) are quite popular in fluid-structure interaction (FSI) problems that involve arbitrarily deforming bodies with complex geometries and are more tolerant to deformations compared to mesh deforming methods like ALE. This paper will look at some of the popular IBMs, outline criteria to evaluate their applicability, and discuss the limitations they have in fulfilling those in problems involving thin membranes.