Proposal Of Simplified Way of Applying Wind Load on Circular Cross-Section

Wind action on circular cross section was described in many publications. It finds an application for flue gas ducts, pipelines, silo or chimneys. This study concentrate on elements with diameter greater than 1m. There are well recognized analytical solutions of static calculation with uses Fourier-series for wind distribution. Although during last 10 years numerical methods of solving problems get more popular, especially among young engineers. For surface structures ability of analytical finding internal forces disappears, and Finish Element Method substitutes analytical calculation. Modelling of wind load in FEM programs cause several problems. Using wind load distribution proposed in Eurocode 1-4, or from laboratory test, it is usually necessary to divide circular cross-section into 32 up to 72 rectangular elements. Applying load in that way is the most accurate method to imitate wind load in FE model. From the other hand that take much time, and requires preparing data about distribution before modelling. Applying wind on complicated model, with many independent parts of piping, for at least 2 load cases cause faults and slows down work. This paper shows and compares a few proposal wind load models for numerical calculation. Those models were built to obtain accurate internal forces in compare to Eurocode procedure. Proposed models offers simplification of Geometry in numerical model, and saves of time. It also helps to make FE mesh become independent from structural nodes, lines or divisions. This paper concern on one case of one Reynolds number, with refers to 2m wide cylinder, wind velocity of 22m/s and surface roughness of steel plate – 0,05 mm. This paper compares different wind load distributions, in terms of required number of division of model, time consuming, precision of results. Author selected one proposal load distribution, with give equivalent internal forces as wind load distribution obtained from Wind Flow simulation (for example CFD method). Proposed model is useful for structural engineers and statics in offer stage of project. With some safety factor it can be also used as wind load as case for detailing cylindrical structures.

Intrusion Detecting System Based on Temporal Convolutional Network for In-Vehicle CAN Networks

In recent years, deep learning theories, such as Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN), have been applied as effective methods for intrusion detection in the vehicle CAN network. However, the existing RNNs realize detection by establishing independent models for each CAN ID, which are unable to learn the potential characteristics of different IDs well, and have relatively complicated model structure and high calculation time cost. CNNs can achieve rapid detection by learning the characteristics of normal and attack CAN ID sequences and exhibit good performance, but the current methods do not locate abnormal points in the sequence. To solve the above problems, this paper proposes an in-vehicle CAN network intrusion detection model based on Temporal Convolutional Network, which is called Temporal Convolutional Network-Based Intrusion Detection System (TCNIDS). In TCNIDS, the CAN ID is serialized into a natural language sequence and a word vector is constructed for each CAN ID through the word embedding coding method to reduce the data dimension. At the same time, TCNIDS uses the parameterized Relu method to improve the temporal convolutional network, which can better learn the potential features of the normal sequence. The TCNIDS model has a simple structure and realizes the point anomaly detection at the message level by predicting the future sequence of normal CAN data and setting the probability strategy. The experimental results show that the overall detection rate, false alarm rate, and accuracy rate of TCNIDS under fuzzy attack, spoofing attack, and DoS attack are higher than those of the traditional temporal convolutional network intrusion detection model.

Stock Market Prediction using Machine Learning

Stock market is one of the most complicated and sophisticated ways to do business. Small ownerships, brokerage corporations, banking sectors, all depend on this very body to make revenue and divide risks; a very complicated model. However, this paper proposes to use machine learning algorithms to predict the future stock price for exchange by using pre-existing algorithms to help make this unpredictable format of business a little more predictable. The use of machine learning which makes predictions based on the values of current stock market indices by training on their previous values. Machine learning itself employs different models to make prediction easier and authentic. The data has to be cleansed before it can be used for predictions. This paper focuses on categorizing various methods used for predictive analytics in different domains to date, their shortcomings.

A systematic identification approach for biaxial piezoelectric stage with coupled Duhem-type hysteresis

Purpose The problem of parameter identification for biaxial piezoelectric stages is still a challenging task because of the existing hysteresis, dynamics and cross-axis coupling. This study aims to find an accurate and systematic approach to tackle this problem. Design/methodology/approach First, a dual-input and dual-output (DIDO) model with Duhem-type hysteresis is proposed to depict the dynamic behavior of the biaxial piezoelectric stage. Then, a systematic identification approach based on a modified differential evolution (DE) algorithm is proposed to identify the unknown parameters of the Duhem-type DIDO model for a biaxial piezostage. The randomness and parallelism of the modified DE algorithm guarantee its high efficiency. Findings The experimental results show that the characteristics of the biaxial piezoelectric stage can be identified with adequate accuracy based on the input–output data, and the peak-valley errors account for 2.8% of the full range in the X direction and 1.5% in the Y direction. The attained results validated the correctness and effectiveness of the presented identification method. Originality/value The classical DE algorithm has many adjustment parameters, which increases the inconvenience and difficulty of using in practice. The parameter identification of Duhem-type DIDO piezoelectric model is rarely studied in detail and its successful application based on DE algorithm on a biaxial piezostage is hitherto unexplored. To close this gap, this work proposed a modified DE-based systematic identification approach. It not only can identify this complicated model with more parameters, but also has little tuning parameters and thus is easy to use.

Improved Method for Approximating the Hazard Rate for Convolution Poisson Random Variables

In this study, we investigate the performance of the saddlepoint approximation of the probability mass function and the cumulative distribution function for the weighted sum of independent Poisson random variables. The goal is to approximate the hazard rate function for this complicated model. The better performance of this method is shown by numerical simulations and comparison with a performance of other approximation methods.

Characterisation of Atlantic meridional overturning hysteresis using Langevin dynamics

Hysteresis diagrams of the Atlantic meridional overturning circulation (AMOC) under freshwater forcing from climate models of intermediate complexity are fitted to a simple model based on the Langevin equation. A total of six parameters are sufficient to quantitatively describe the collapses seen in these simulations. Reversing the freshwater forcing results in asymmetric behaviour that is less well captured and appears to require a more complicated model. The Langevin model allows for comparison between models that display an AMOC collapse. Differences between the climate models studied here are mainly due to the strength of the stable AMOC and the strength of the response to a freshwater forcing.

Reconstructing Ita at Schaffhausen

The Nellenburg family looms large in the historical memory of Schaffhausen. Count Eberhard (ca. 1015-1078/1079) and his wife Ita (d. ca. 1105) had transformed the small city with their patronage, most notably through the foundation of the monastery of Allerheiligen; their children held prominent military and ecclesiastical positions across the Lake Constance region. Together with their son Burkhard, his wife Hedwig, and a cousin known as Irmentrud, Eberhard and Ita were buried prominently in Allerheiligen; their collective funerary monument is one of the earliest and most ambitious of its type that is known from the twelfth century. The monument, however, has only survived in pieces: twentieth-century excavations uncovered two effigies for men and a small fragment of a head from a woman’s effigy, usually identified as Ita. The male figures, largely intact, have received ample scholarly attention from art historians, but the presence of women in the family grave has been overlooked thanks to the near-total loss of their monuments. A recent reconstruction sought to ameliorate this situation by adding a body to complete the fragmentary female head, using the contemporaneous Quedlinburg effigies as a model. The resulting modern monument is beautifully executed and visually gratifying, but like all facsimiles it complicates our view of the original. This article questions the relationship of the fragmentary head and its reception in relation to Ita, whose historical position has been privileged at the expense of her daughter-in-law Hedwig and cousin Irmentrud; it also highlights contextual differences that make the imperial canoness effigies of Quedlinburg a complicated model for reimagining the Schaffhausen women. The goal is not to dismiss the reconstruction but rather to probe the underlying assumptions that continue to impact how medieval bodies, and women’s bodies in particular, are projected into the modern world.

Multi-physics simulation of an insect with flapping wings

In this paper, the unsteady aerodynamic of an insect’s forward flight has been carried out with a novel approach. In order to fully utilize the available powerful solvers, an innovative intermediary MATLAB code has been written for the high-fidelity time-resolved multi-physics problems involving fluid flow and multi-body simulations. For simulating the insect’s flight, the FLUENT solver has been utilized to determine aerodynamic forces and moments of the wings and main body while ADAMS software has been employed to calculate translational and angular velocities. Overset grid technology accompanied with dynamic mesh method have been implemented for the movement of the insect. The code is responsible for the synchronization of the solvers at the end of each time step as well as the integration of the solutions. Three different simulations are done for two different insects’ geometries. For the first and second simulations, a simplified geometry of an insect is selected, due to the ease of manufacturing and testing. At first, all rotational and translational degrees of freedom are considered to be free. The motion path history shows the instability due to an inappropriate location of the center of gravity. Hence, in the second case, it is assumed that the insect’s main body is limited to the vertical motion. In the final simulation, a complicated model of a bee with exact geometry and wings kinematics extracts from the experimental data with the free translational degrees of freedom. According to the results, combining multiple software in which they can interact with each other at each time step, is the most accurate way for doing precise multi-physics simulations.

Collapse of the Atlantic Meridional Overturning described by Langevin dynamics

Using a machine learning technique, collapse trajectories of the Atlantic Meridional Overturning Circulation from climate models of intermediate complexity are fitted to a simple model based on the Langevin equation. A total of six parameters are sufficient to quantitatively describe the collapses seen in these simulations under a freshwater forcing. Reversing the freshwater forcing results in asymmetric behaviour that is less well captured and would require a more complicated model.

How affinity of the ELT-2 GATA factor binding to cis-acting regulatory sites controls Caenorhabditis elegans intestinal gene transcription

ABSTRACTWe define a quantitative relationship between the affinity with which the intestine-specific GATA factor ELT-2 binds to cis-acting regulatory motifs and the resulting transcription of asp-1, a target gene representative of genes involved in Caenorhabditis elegans intestine differentiation. By establishing an experimental system that allows unknown parameters (e.g. the influence of chromatin) to effectively cancel out, we show that levels of asp-1 transcripts increase monotonically with increasing binding affinity of ELT-2 to variant promoter TGATAA sites. The shape of the response curve reveals that the product of the unbound ELT-2 concentration in vivo [i.e. (ELT-2free) or ELT-2 ‘activity’] and the largest ELT-XXTGATAAXX association constant (Kmax) lies between five and ten. We suggest that this (unitless) product [Kmax×(ELT-2free) or the equivalent product for any other transcription factor] provides an important quantitative descriptor of transcription-factor/regulatory-motif interaction in development, evolution and genetic disease. A more complicated model than simple binding affinity is necessary to explain the fact that ELT-2 appears to discriminate in vivo against equal-affinity binding sites that contain AGATAA instead of TGATAA.