ESTIMATION OF DAILY ENERGY GAIN OF SOLAR TRACKING SURFACES BASED ON GEOGRAPHIC POSITION

2021 ◽  
Vol 7 (1) ◽  
pp. 01-14
Author(s):  
Higor Miguel ◽  
Leticia Colombi Gomes ◽  
Cesar Turczyn Campos ◽  
Pablo Rodrigues Muniz
Keyword(s):  
Climatic Factors ◽  
Computational Cost ◽  
Iterative Algorithms ◽  
Relative Energy ◽  
Energy Gain ◽  
The Arctic ◽  
Atmospheric Conditions ◽  
Solar Systems ◽  
Geographic Position ◽  
Solar Tracking

The performance of solar systems depends on the effective incident solar energy on the capture surface. This factor is dependent on the geographic position, the orientation of the surface, atmospheric conditions, and other geo-climatic factors. Solar trackers, typically uni- and biaxial, are used to optimize the capture of solar radiation via movement of the plane of incidence of these devices. A reliable estimation of the energy gain of these trackers with respect to a fixed surface facilitates more accurate analyses of the feasibility, operation, and maintenance of solar ventures. In this work, a method for estimating the relative energy gain of uni- and biaxial solar trackers is developed. This approach applies to locations between the Arctic Circle and the Antarctic Circle, using geographic coordinates and the altitude of the location of interest, providing daily results throughout the year. Unlike empirical results or case studies, the proposed method applies to any location and has a low error. It can be implemented using iterative algorithms with a low computational cost and can be easily utilized by researchers and technicians in the field.

Working conditions and occupational pathology of coal miners in the Arctic

2019 ◽  
pp. 452-457 ◽  
Author(s):  
S. A. Gorbanev ◽  
S. A. Syurin ◽  
N. M. Frolova
Keyword(s):  
Coal Mining ◽  
Working Conditions ◽  
Occupational Diseases ◽  
Climatic Factors ◽  
Coal Mines ◽  
The Arctic ◽  
Morbidity Rate ◽  
Coal Miners ◽  
Increased Risk ◽  
The Impact

Introduction. Due to the impact of adverse working conditions and climate, workers in coal-mining enterprises in the Arctic are at increased risk of occupational diseases (OD).The aim of the study was to study the working conditions, causes, structure and prevalence of occupational diseases in miners of coal mines in the Arctic.Materials and methods. Th e data of social and hygienic monitoring “Working conditions and occupational morbidity” of the population of Vorkuta and Chukotka Autonomous District in 2007–2017 are studied.Results. It was established that in 2007–2017 years, 2,296 ODs were diagnosed for the first time in 1851 coal mines, mainly in the drifters, clearing face miners, repairmen and machinists of mining excavating machines. Most often, the ODs occurred when exposed to the severity of labor, fibrogenic aerosols and hand-arm vibration. The development of professional pathology in 98% of cases was due to design flaws of machines and mechanisms, as well as imperfections of workplaces and technological processes. Diseases of the musculoskeletal system (36.2%), respiratory organs (28.9%) and nervous system (22.5%) prevailed in the structure of professional pathology of miners of coal mines. Among the three most common nosological forms of OD were radiculopathy (32.1%), chronic bronchitis (27.7%) and mono-polyneuropathy (15.4%). In 2017, coal miners in the Arctic had a professional morbidity rate of 2.82 times higher than the national rates for coal mining.Conclusions. To preserve the health of miners of coal mining enterprises, technical measures to improve working conditions and medical interventions aimed at increasing the body’s resistance to the effects of harmful production and climatic factors are necessary.

scholarly journals Aerosol distribution around Svalbard during intense easterly winds

2010 ◽  
Vol 10 (4) ◽  
pp. 1473-1490 ◽  
Author(s):  
A. Dörnbrack ◽  
I. S. Stachlewska ◽  
C. Ritter ◽  
R. Neuber
Keyword(s):  
Sea Salt ◽  
Airborne Lidar ◽  
The Arctic ◽  
Aerosol Layer ◽  
Atmospheric Conditions ◽  
Sea Salt Aerosols ◽  
Aerosol Distribution ◽  
Weather Situation ◽  
Low Level Jet ◽  
Aerosol Plume

Abstract. This paper reports on backscatter and depolarization measurements by an airborne lidar in the Arctic during the ASTAR 2004 campaign. A unique weather situation facilitated the observation of the aerosol concentration under strongly forced atmospheric conditions. The vigorous easterly winds distorted the flow past Svalbard in such a way that mesoscale features were visible in the remote-sensing observations: The formation of a well-mixed aerosol layer inside the Adventdalen and the subsequent thinning of the aerosol plume were observed over the Isfjorden. Additionally, mobilization of sea salt aerosols due to a coastal low-level jet at the northern tip of Svalbard resulted in a sloped boundary layer toward north. Mesoscale numerical modelling was applied to identify the sources of the aerosol particles and to explain the observed patterns.

scholarly journals How Predictable Are the Arctic and North Atlantic Oscillations? Exploring the Variability and Predictability of the Northern Hemisphere

2018 ◽  
Vol 31 (3) ◽  
pp. 997-1014 ◽  
Author(s):  
Daniela I. V. Domeisen ◽  
Gualtiero Badin ◽  
Inga M. Koszalka
Keyword(s):  
Time Scales ◽  
Northern Hemisphere ◽  
North Atlantic ◽  
Prediction Models ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Atmospheric Conditions ◽  
Short Term ◽  
The North ◽  
The North Atlantic Oscillation

ABSTRACT The North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) describe the dominant part of the variability in the Northern Hemisphere extratropical troposphere. Because of the strong connection of these patterns with surface climate, recent years have shown an increased interest and an increasing skill in forecasting them. However, it is unclear what the intrinsic limits of short-term predictability for the NAO and AO patterns are. This study compares the variability and predictability of both patterns, using a range of data and index computation methods for the daily NAO and AO indices. Small deviations from Gaussianity are found along with characteristic decorrelation time scales of around one week. In the analysis of the Lyapunov spectrum it is found that predictability is not significantly different between the AO and NAO or between reanalysis products. Differences exist, however, between the indices based on EOF analysis, which exhibit predictability time scales around 12–16 days, and the station-based indices, exhibiting a longer predictability of 18–20 days. Both of these time scales indicate predictability beyond that currently obtained in ensemble prediction models for short-term predictability. Additional longer-term predictability for these patterns may be gained through local feedbacks and remote forcing mechanisms for particular atmospheric conditions.

Atmospheric conditions of thunderstorms in the European part of the Arctic derived from sounding and reanalysis data

2015 ◽  
Vol 154 ◽  
pp. 60-72 ◽  
Author(s):  
Bartosz Czernecki ◽  
Mateusz Taszarek ◽  
Leszek Kolendowicz ◽  
Katarzyna Szyga-Pluta
Keyword(s):  
Reanalysis Data ◽  
European Part ◽  
The Arctic ◽  
Atmospheric Conditions

The Spatial and Temporal Probability of Dust Storm Activity in Chryse, One of the Tentative Landing Areas of Tianwen-1 Mission

2020 ◽  
Author(s):  
Bo Li ◽  
Jiang Zhang ◽  
Zongyu Yue ◽  
Peiwen Yao ◽  
Chenfan Li ◽  
...  
Keyword(s):  
Dust Storm ◽  
Dust Storms ◽  
The Arctic ◽  
Atmospheric Conditions ◽  
Polar Ice ◽  
Storm Activity ◽  
Mars Atmosphere ◽  
Ice Cap ◽  
Activity Frequency ◽  
Temporal And Spatial

Abstract Dust storms, observed in all seasons, are among the most momentous Mars atmosphere activities. The Entry-Descent-Landing (EDL) activity of a Martian landing mission is influenced by local atmospheric conditions, especially the dust storm activity probability. It is of great significance to know well the dust storm situation that China's first Mars mission (Tianwen-1) may encounter in EDL season in the Chryse area, one of the tentative landing areas. Firstly, based on four Martian years’ Mars Orbiter Camera (MOC) Mars Daily Global Maps (MDGMs), 1172 dust storms were identified within Chryse’s 1600 km radius ring with their shape parameters extracted, including center, range and area. Secondly, the daily mean dust storm probability was calculated binned by 1° of solar longitude in the Chryse area during EDL season. Dust storm activity frequency was closely interrelated with the seasonal ebb and flow of the arctic polar ice cap, consequently, most of dust storms occurring in either the cap’s grow or the recession. The dust storm activity in the Chryse area mainly came from the northern polar cap region, Acidalia and Chryse, with some contribution from the southern hemisphere (Argyre and Bosprous) northward. Thirdly, we divided the Chryse area into many square grids of 0.5° and computed the average occurrence probability of dust storm in each grid during EDL season. The dust storm activity probability in space was also in-homogeneous, low in the west and south but high in the east and north, which was mainly affected by three factors: topography, the origin and the path of dust storm sequence. Based on Empirical orthogonal function (EOF) analysis, of the storms in the Chryse area we’ve discovered, 40.5% are cap-edge storms in the northern hemisphere and 17.5% are textured dust storms. Finally, according to the temporal and spatial probability of dust storm activity in the Chryse area during EDL season, we held that the preferred landing time of the Tianwen-1 mission in 2021 was in Ls=18°-65° and three preferred landing areas were selected with low dust storm probability.

scholarly journals Determination of a melt-onset date for Arctic sea-ice regions using passive-microwave data

1997 ◽  
Vol 25 ◽  
pp. 382-387 ◽  
Author(s):  
Mark R. Anderson
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Passive Microwave ◽  
The Arctic ◽  
Horizontal Channel ◽  
Onset Date ◽  
Atmospheric Conditions ◽  
Brightness Temperatures

Although the formation and melt of sea ice are primarily functions of the annual radiation cycle, atmospheric sensible-heat forcing does serve to delay or advance the timing of such events. Additionally, if atmospheric conditions in the Arctic were to vary due to climate change it may have significant influence on ice conditions. Therefore, this paper investigates a methodology to determine melt-onset dale distribution, both spatially and temporally, in the Arctic Ocean and surrounding sea-ice covered regions.Melt determination is made by a threshold technique using the spectral signatures of the horizontal brightness temperatures (19 GHz horizontal channel minus the 37 GHz horizontal channel) obtained from the Special Sensor Microwave Imager (SSM/I) passive-microwave sensor. Passive-microwave observations are used to identify melt because of the large increase in emissivity that occurs when liquid water is present. Emissivity variations are observed in the brightness temperatures due to the different scattering, absorption and penetration depths of the snowpack from the available satellite channels during melt. Monitoring the variations in the brightness temperatures allows the determination of melt-onset dates.Analysis of daily brightness temperature data allows spatial variations in the date of the snow inch onset for sea ice to be detected. Since the data are gridded on a daily basis, a climatology of daily melt-onset dates can be produced for the Arctic region. From this climatology, progression of melt can be obtained and compared inter-annually.

PATTERNS OF DIVERSITY IN THE CANADIAN INSECT FAUNA

1993 ◽  
Vol 125 (S165) ◽  
pp. 51-74 ◽  
Author(s):  
H.V. Danks
Keyword(s):  
Species Richness ◽  
Climatic Factors ◽  
Interspecific Interactions ◽  
The Arctic ◽  
Large Area ◽  
The West ◽  
Insect Fauna ◽  
Climatic Trend ◽  
The North ◽  
Historical Factors

AbstractThe diversity of the Canadian insect fauna decreases and its composition (at all taxonomic levels) changes as climates become progressively more harsh toward the north. This climatic trend dominates patterns of diversity, but many other factors interact to produce the observed patterns. In the arctic, species richness is greatest in the west. Farther south, overall species richness is greatest in the west (especially British Columbia), associated with coastal and cordilleran habitats, and to a somewhat smaller degree in the southeast (especially Ontario), associated with deciduous forests and particularly with transitional forests which occupy a large area of southeastern Canada. However, certain taxa are better represented in the west or in the east, depending on present-day habitats and on historical factors. These conclusions, based chiefly on a sample of taxa of different types, are possible only because basic systematic work has been carried out to distinguish and map the species. Preliminary data on numerical patterns, such as the numbers of species relative to different potential resources such as host plants in different zones, tend to suggest that the occurrence of species in the north may depend so heavily on climatic factors that potential resources are not fully exploited and the effects of interspecific interactions on diversity are reduced.

Improved numerical solvers for coupled chemistry-climate model simulations

2020 ◽  
Author(s):  
Emre Esenturk
Keyword(s):  
Atmospheric Chemistry ◽  
Climate Model ◽  
Numerical Solutions ◽  
Iterative Algorithms ◽  
Box Model ◽  
Stiff Systems ◽  
Atmospheric Conditions ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
The Uk

<p>A key and expensive part of coupled atmospheric chemistry-climate model simulations is the integration of gas phase chemistry, which involves dozens of species and hundreds of reactions. These species and reactions form a highly-coupled network of Differential Equations (DEs). There exists orders of magnitude variability in the lifetimes of the different species present in the atmosphere and so solving these DEs to obtain robust numerical solutions poses a “stiff problem”. With newer models having more species and increased complexity it is now becoming increasingly important to have chemistry solving schemes that reduce time but maintain accuracy.</p><p>A sound way to handle stiff systems is by using implicit DE solvers but the computational costs for such solvers are high due to internal iterative algorithms (e.g., Newton-Raphson (NR) methods). Here we propose an approach for implicit DE solvers that improves their convergence speed and robustness with relatively small modification in the code. We achieve this by using Quasi-Newton (QN) methods. We test our approach with numerical experiments on the UK Chemistry and Aerosol (UKCA) model, part of the UK Met Office Unified Model suite, run in both an idealized box-model environment and under realistic 3D atmospheric conditions. The box model tests reveal that the proposed method reduces the time spent in the solver routines significantly, with each QN call costing 27% of a call to the full NR routine. A series of experiments over a range of chemical environments was conducted with the box-model to find the optimal iteration steps to call the QN routine which result in the greatest reduction in the total number of NR iterations whilst minimising the chance of causing instabilities and maintaining solver accuracy. The 3D simulations show that our method for the chemistry solver, speeds up the chemistry routines by around 13%, resulting in a net improvement in overall run-time of the full model by approximately 3% with negligible loss in the accuracy (relative error of order 10<sup>-7</sup>) . The QN method also improves the robustness of the solver by significantly reducing (40% ) the number of grid cells which fail to converge hence avoiding unnecessary timestep adjustments. </p>

A Hybrid Approach for Automatic Aorta Segmentation in Abdominal 3D CT Scan Images

2021 ◽  
Vol 11 (3) ◽  
pp. 712-719
Author(s):  
Iftikhar Ahmad ◽  
Sami ur Rehman ◽  
Imran Ullah Khan ◽  
Arfa Ali ◽  
Hussain Rahman ◽  
...  
Keyword(s):  
Medical Imaging ◽  
Ct Scan ◽  
Hybrid Approach ◽  
Computational Cost ◽  
Iterative Algorithms ◽  
Fast Algorithms ◽  
Human Anatomy ◽  
3D Ct Scan ◽  
Segmentation Accuracy ◽  
Segmentation Algorithms

Due to rapid advancement in medical imaging, human anatomy is now observable in finer details bringing new dimensions to diagnosis and treatment. One such area which benefitted from advancement in medical imaging is aorta segmentation. Aorta segmentation is achieved by using anatomical features (shape and position of aorta) using specialized segmentation algorithms. These segmentation algorithms are broadly classified into two categories. The first type comprises of fast algorithms which exploits spatial and intensity properties of images. The second type are iterative algorithms which use optimization of a cost function to track aorta boundaries. Fast algorithms offer lower computation cost, whereas iterative algorithms offer better segmentation accuracy. Therefore, there is a tradeoff between segmentation accuracy and computational cost. In this work, a hybrid approach for aorta segmentation in 3D Computed Tomography (CT) scan images is proposed. The proposed approach produces high segmentation accuracy of intensity based (fast) approaches at reduced computational cost. The proposed technique is evaluated using real world 3D abdominal CT scan images. The proposed approach can either be used as a fast-standalone segmentation procedure, or as a pre-segmentation procedure for iterative and more accurate approaches.

scholarly journals Nonrigid Image Registration in Digital Subtraction Angiography Using Multilevel B-Spline

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Mansour Nejati ◽  
Saeid Sadri ◽  
Rassoul Amirfattahi
Keyword(s):  
Image Registration ◽  
Coronary Angiography ◽  
Digital Subtraction Angiography ◽  
Computational Cost ◽  
Iterative Algorithms ◽  
Motion Artifact ◽  
Data Sets ◽  
Digital Subtraction ◽  
Nonrigid Image Registration ◽  
B Spline

We address the problem of motion artifact reduction in digital subtraction angiography (DSA) using image registration techniques. Most of registration algorithms proposed for application in DSA, have been designed for peripheral and cerebral angiography images in which we mainly deal with global rigid motions. These algorithms did not yield good results when applied to coronary angiography images because of complex nonrigid motions that exist in this type of angiography images. Multiresolution and iterative algorithms are proposed to cope with this problem, but these algorithms are associated with high computational cost which makes them not acceptable for real-time clinical applications. In this paper we propose a nonrigid image registration algorithm for coronary angiography images that is significantly faster than multiresolution and iterative blocking methods and outperforms competing algorithms evaluated on the same data sets. This algorithm is based on a sparse set of matched feature point pairs and the elastic registration is performed by means of multilevel B-spline image warping. Experimental results with several clinical data sets demonstrate the effectiveness of our approach.

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