scholarly journals Anomaly of Rotor Dynamics in Ultra-Light Helicopter – Robinson R22

2019 ◽  
Vol 26 (4) ◽  
pp. 235-239
Author(s):  
Agnieszka Sobieszek
Keyword(s):  
Weather Condition ◽  
Weather Conditions ◽  
Rotor Dynamics ◽  
High Availability ◽  
Loss Of Control ◽  
Main Rotor ◽  
Additional Training ◽  
Unusual Behaviour ◽  
Special Instruction

AbstractThe article presents the analysis of anomaly of rotor dynamics in ultra-light helicopter - Robinson R22. Robinson R22 is two-seat, two-blade main rotor and single-engine helicopter, well known as simple and common used aircraft because of low price and high availability. At the same time, large number of accidents and strictly defined rules (recommended piloting technique) and weather condition for safe flight show disadvantages of Robinson R22. The reason for considering this topic is the analysis of different flight properties and helicopter behaviour as well as easy entering into dangerous flight manoeuvre. In the article different flight properties and loss of control during the pull-up, manoeuvre or vertical gusts of wind and mast bumping accidents were analysed. Analysis shows that problem may be caused by construction of three-hinged rotor hub, designed and patented by F. Robinson. Article presents model of rotor hub and review of main rotor and rotor hub construction in light helicopters. Because of number of accidents, caused by the unusual behaviour of Robinson R22, restrictive pilotage rules were introduced: prohibition of flight in certain weather conditions, the necessity of attending additional training conducted by trained instructors. To reduce the probability of an accident a special instruction for specific Robinson R22 properties was created. Moreover, the statistics of accidents resulting from loss of control and review of legal changes caused by Robinson R22 accidents are presented.

scholarly journals An investigation of the effects of environmental and ecologic factors on cutaneous leishmaniasis in the old world: a systematic review study

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Abolfazl Mohammadbeigi ◽  
Salman Khazaei ◽  
Hamidreza Heidari ◽  
Azadeh Asgarian ◽  
Shahram Arsangjang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Environmental Factors ◽  
Land Cover ◽  
Cutaneous Leishmaniasis ◽  
Weather Condition ◽  
Weather Conditions ◽  
Eligibility Criteria ◽  
Screening Process ◽  
Old World ◽  
Review Study

AbstractObjectivesLeishmaniasis is a neglected and widespread parasitic disease that can lead to serious health problems. The current review study aimed to synthesize the relationship between ecologic and environmental factors (e.g., weather conditions, climatology, temperature and topology) and the incidence of cutaneous leishmaniasis (CL) in the Old World.ContentA systematic review was conducted based on English, and Persian articles published from 2015 to 2020 in PubMed/Medline, Science Direct, Web of Science and Google Scholar. Keywords used to search articles were leishmaniasis, environmental factors, weather condition, soil, temperature, land cover, ecologic* and topogr*. All articles were selected and assessed for eligibility according to the titles or abstracts. The quality screening process of articles was carried out by two independent authors. The selected articles were checked according to the inclusion and exclusion criteria.Summary and outlookA total of 827 relevant records in 2015–2020 were searched and after evaluating the articles, 23 articles met the eligibility criteria; finally, 14 full-text articles were included in the systematic review. Two different categories of ecologic/environmental factors (weather conditions, temperature, rainfall/precipitation and humidity) and land characteristics (land cover, slope, elevation and altitude, earthquake and cattle sheds) were the most important factors associated with CL incidence.ConclusionsTemperature and rainfall play an important role in the seasonal cycle of CL as many CL cases occurred in arid and semiarid areas in the Old World. Moreover, given the findings of this study regarding the effect of weather conditions on CL, it can be concluded that designing an early warning system is necessary to predict the incidence of CL based on different weather conditions.

scholarly journals It’s the Weather: Quantifying the Impact of Weather on Retail Sales

2021 ◽  
Author(s):  
Natalie Rose ◽  
Les Dolega
Keyword(s):  
Weather Condition ◽  
Weather Conditions ◽  
Influential Factor ◽  
Retail Sector ◽  
Retail Sales ◽  
Weather Impact ◽  
High Street ◽  
Sector Decision ◽  
The Impact ◽  
The Relationship

AbstractThe weather is considered as an influential factor on consumer purchasing behaviours and plays a significant role in many aspects of retail sector decision making. As a result, better understanding of the magnitude and nature of the influence of variable UK weather conditions can be beneficial to many retailers and other stakeholders. This study addresses the dearth of research in this area by quantifying the relationship between different weather conditions and trading outcomes. By employing comprehensive daily sales data for a major high street retailer with over 2000 stores across England and adopting a random forest methodology, the study quantifies the influence of various weather conditions on daily retail sales. Results indicate that weather impact is greatest in the summer and spring months and that wind is consistently found to be the most influential weather condition. The top five most weather-dependent categories cover a range of different product types, with health foods emerging as the most susceptible to the weather. Also, sales from out-of-town stores show a far more complex relationship with the weather than those from traditional high street stores with the regions London and the South East experiencing the greatest levels of influence. Various implications of these findings for retail stakeholders are discussed and the scope for further research outlined.

scholarly journals Terminal Airspace Capacity Evaluation Model under Weather Condition from Perspective of a Controller

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Lu Liu
Keyword(s):  
Network Flow ◽  
Topological Structure ◽  
Evaluation Model ◽  
Weather Condition ◽  
Weather Conditions ◽  
Severe Weather ◽  
Safe Operation ◽  
Weather Factor ◽  
Route Network ◽  
Capacity Evaluation

A route network lays in the terminal airspace. The route network can be divided into multiple subnetworks according to sectors. When severe weather conditions occur, a controller takes measures to obtain safe operation of flights, such as navigation guidance or changing the availability of routes. In such circumstances, the route structure of a subnetwork is changed, and the controller’s attention paid to each route is also changed as well as the unit workload on it. As the subnetwork is handled by one controller, capacities of routes in it are associated. We find the way to determine the “related capacity” of a route in the conditions that whether topological structure of the terminal route network is changed or not. The capacity of the terminal route network calculated by network flow theory represents the capacity of terminal airspace. According to the analysis results, the weather factor reduces capacity of terminal airspace directly by reducing the capacities of routes blocked. Indirectly, it diverts controller’s attention to change capacities of other routes in the subnetwork.

scholarly journals Weather Prediction using Advanced Machine Learning Techniques

2021 ◽  
Vol 2089 (1) ◽  
pp. 012059
Author(s):  
G. Hemalatha ◽  
K. Srinivasa Rao ◽  
D. Arun Kumar
Keyword(s):  
Linear Relationship ◽  
Weather Prediction ◽  
Weather Condition ◽  
Weather Conditions ◽  
Machine Learning Techniques ◽  
Weather Data ◽  
Learning Techniques ◽  
Proposed Model ◽  
Non Linear ◽  
The Relationship

Abstract Prediction of weather condition is important to take efficient decisions. In general, the relationship between the input weather parameters and the output weather condition is non linear and predicting the weather conditions in non linear relationship posses challenging task. The traditional methods of weather prediction sometimes deviate in predicting the weather conditions due to non linear relationship between the input features and output condition. Motivated with this factor, we propose a neural networks based model for weather prediction. The superiority of the proposed model is tested with the weather data collected from Indian metrological Department (IMD). The performance of model is tested with various metrics..

"Integrating weather in modelling earthmoving mining operation using distributed simulation with HLA standards"

2018 ◽  
Author(s):  
M. AL-Alawi ◽  
Y. Mohamed ◽  
A. Bouferguene
Keyword(s):  
Distributed Simulation ◽  
Weather Condition ◽  
Mining Operation ◽  
Weather Conditions ◽  
Weather Generator ◽  
Sand Mining ◽  
Oil Sand ◽  
Weather Effects ◽  
High Level

"Changes in weather conditions impact construction activities. The consideration of effects of changes in weather condition is important to better estimate the performance of construction resources. This paper demonstrates the integration of a weather generator to support modelling earthmoving operation using distribution simulation with high level architectural (HLA) standards. The modelled earthmoving operation is related to the oil sand mining. The weather effects on the breakdown and maintenance events of earthmoving resources (trucks and excavators) were analyzed under different weather testing scenarios and their results were reported accordingly."

scholarly journals Variable Parameters for a Single Exponential Model of Photovoltaic Modules in Crystalline-Silicon

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2138 ◽  
Author(s):  
Ali Murtaza ◽  
Umer Munir ◽  
Marcello Chiaberge ◽  
Paolo Di Leo ◽  
Filippo Spertino
Keyword(s):  
Crystalline Silicon ◽  
Weather Condition ◽  
Computation Time ◽  
Weather Conditions ◽  
Iterative Solution ◽  
Exponential Model ◽  
Standard Test ◽  
Photovoltaic Module ◽  
Proposed Model ◽  
Power Point

The correct approximation of parallel resistance (Rp) and series resistance (Rs) poses a major challenge for the single diode model of the photovoltaic module (PV). The bottleneck behind the limited accuracy of the model is the static estimation of resistive parameters. This means that Rp and Rs, once estimated, usually remain constant for the entire operating range of the same weather condition, as well as for other conditions. Another contributing factor is the availability of only standard test condition (STC) data in the manufacturer’s datasheet. This paper proposes a single-diode model with dynamic relations of Rp and Rs. The relations not only vary the resistive parameters for constant/distinct weather conditions but also provide a non-iterative solution. Initially, appropriate software is used to extract the data of current-voltage (I-V) curves from the manufacturer’s datasheet. By using these raw data and simple statistical concepts, the relations for Rp and Rs are designed. Finally, it is proved through root mean square error (RMSE) analysis that the proposed model holds a one-tenth advantage over numerous recently proposed models. Simultaneously, it is low complex, iteration-free (0 to voltage in maximum power point Vmpp range), and requires less computation time to trace the I-V curve.

scholarly journals Classification of Active Fires and Weather Conditions in the Lower Amur River Basin

2020 ◽  
Vol 12 (19) ◽  
pp. 3204
Author(s):  
Hiroshi Hayasaka ◽  
Galina V. Sokolova ◽  
Andrey Ostroukhov ◽  
Daisuke Naito
Keyword(s):  
River Basin ◽  
Boreal Forests ◽  
Weather Condition ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Amur River Basin ◽  
Fire Weather ◽  
Strong Wind ◽  
Amur River ◽  
Active Fire

Most wildland fires in boreal forests occur during summer, but major fires in the lower Amur River Basin of the southern Khabarovsk Krai (SKK) mainly occur in spring. To reduce active fires in the SKK, we carried out daily analysis of MODIS (Moderate Resolution Imaging Spectroradiometer) hotspot (HS) data and various weather charts. HS data of 17 years from 2003 were used to identify the average seasonal fire occurrence. Active fire-periods were extracted by considering the number of daily HSs and their continuity. Weather charts, temperature maps, and wind maps during the top 12 active fire-periods were examined to clarify each fire weather condition. Analysis results showed that there were four active fire-periods that occurred in April, May, July, and October. Weather charts during the top active fire-periods showed active fires in April and October occurred under strong wind conditions (these wind velocities were over 30 km h−1) related to low-pressure systems. The very active summer fire at the end of June 2012 occurred related to warm air mass advection promoted by large westerly meandering. We showed clear fire weather conditions in the SKK from March to October. If a proper fire weather forecast is developed based on our results, more efficient and timely firefighting can be carried out.

scholarly journals Bedforms in a tidally modulated ridge and runnel shoreface (Berck-Plage; North France): implications for the geological record

2018 ◽  
Vol 189 (1) ◽  
pp. 5 ◽  
Author(s):  
Romain Vaucher ◽  
Bernard Pittet ◽  
Sophie Passot ◽  
Philippe Grandjean ◽  
Thomas Humbert ◽  
...  
Keyword(s):  
Intertidal Zone ◽  
Spring Tide ◽  
Experimental Studies ◽  
Weather Condition ◽  
Weather Conditions ◽  
Field Investigation ◽  
Fair Weather ◽  
Coastal System ◽  
The North ◽  
Current Ripples

Tidally modulated shoreface (TMS) corresponds to peculiar costal environments. The general morphology and the expressed bedforms are provided by the interplay of both waves and tides. The recognition of TMS in the fossil record still remains a difficult task. The study of one mega-tidal modern TMS in the north of France (Berck-Plage) provides new key criteria to identify this kind of coastal system in the rock record. Field investigation and digital mapping were realized at lowest tide during spring tide under fair-weather condition. The intertidal zone is characterized by a succession of several sand banks shore parallel separated by topographic lows that are defined as ridges and runnels. Seven distinct dominant bedforms are recognized: 3D current ripples, 3D asymmetrical ripples, 2D symmetrical ripples, 2D small symmetrical dunes, 2D large symmetrical dunes, 3D symmetrical dunes and plane beds. The upper stage plane bedding mainly composed the ridges while the six other bedforms are commonly found within the runnels or on the flanks of the ridges. Comparison of the bedforms of Berck-Plage with previous experimental studies on bedforms genesis proves that the necessary flow parameters for generating these bedforms belong to an oscillatory flow except for the 3D current ripples, which are formed by a unidirectional flow. This study confirms the dominance of oscillatory structures through the intertidal zone in a mega-tidal context and show that wave processes are more powerful than tide processes for bedform generation although during fair weather conditions. Based on the timing of genesis, the description and the repeated pattern of distribution of bedforms between two ridges is highlighted thus helping to propose a theoretical facies sequence for an intertidal zone characterized by ridges and runnels applicable to ancient sedimentary successions.

scholarly journals Improved Synthesis of Global Irradiance with One-Minute Resolution for PV System Simulations

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Martin Hofmann ◽  
Stefan Riechelmann ◽  
Cristian Crisosto ◽  
Riyad Mubarak ◽  
Gunther Seckmeyer
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Transition Probability ◽  
Weather Condition ◽  
Weather Conditions ◽  
Pv System ◽  
High Resolution Data ◽  
Frequency Distributions ◽  
Global Irradiance ◽  
Mean Square Errors

High resolution global irradiance time series are needed for accurate simulations of photovoltaic (PV) systems, since the typical volatile PV power output induced by fast irradiance changes cannot be simulated properly with commonly available hourly averages of global irradiance. We present a two-step algorithm that is capable of synthesizing one-minute global irradiance time series based on hourly averaged datasets. The algorithm is initialized by deriving characteristic transition probability matrices (TPM) for different weather conditions (cloudless, broken clouds and overcast) from a large number of high resolution measurements. Once initialized, the algorithm is location-independent and capable of synthesizing one-minute values based on hourly averaged global irradiance of any desired location. The one-minute time series are derived by discrete-time Markov chains based on a TPM that matches the weather condition of the input dataset. One-minute time series generated with the presented algorithm are compared with measured high resolution data and show a better agreement compared to two existing synthesizing algorithms in terms of temporal variability and characteristic frequency distributions of global irradiance and clearness index values. A comparison based on measurements performed in Lindenberg, Germany, and Carpentras, France, shows a reduction of the frequency distribution root mean square errors of more than 60% compared to the two existing synthesizing algorithms.

scholarly journals A Two-Class Stochastic Network Equilibrium Model under Adverse Weather Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Chenming Jiang ◽  
Linjun Lu ◽  
Junliang He ◽  
Caimao Tan
Keyword(s):  
Travel Time ◽  
Equilibrium Model ◽  
Route Choice ◽  
Weather Condition ◽  
Weather Conditions ◽  
User Equilibrium ◽  
Network Equilibrium ◽  
Adverse Weather Conditions ◽  
Adverse Weather Condition ◽  
Adverse Weather

Adverse weather condition is one of the inducements that lead to supply uncertainty of an urban transportation system, while travelers’ multiple route choice criteria are the nonignorable reason resulting in demand uncertainty. This paper proposes a novel stochastic traffic network equilibrium model considering impacts of adverse weather conditions on roadway capacity and route choice criteria of two-class mixed roadway travellers on demand modes, in which the two-class route choice criteria root in travelers’ different network information levels (NILs). The actual route travel time (ARTT) and perceived route travel time (PRTT) are considered as the route choice criteria of travelers with perfect information (TPI) and travelers with bounded information (TBI) under adverse weather conditions, respectively. We then formulate the user equilibrium (UE) traffic assignment model in a variational inequality problem and propose a solution algorithm. Numerical examples including a small triangle network and the Sioux Falls network are presented to testify the validity of the model and to clarify the inner mechanism of the two-class UE model under adverse weather conditions. Managerial implications and applications are also proposed based on our findings to improve the operation efficiency of urban roadway network under adverse weather conditions.

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