scholarly journals Analysis of Air Pressure Distributions with Wavelets

2016 ◽  
Vol 26 (2) ◽  
Author(s):  
Andreas Baierl
Keyword(s):  
Time Series ◽  
Historical Data ◽  
Air Pressure ◽  
Dependence Structure ◽  
Pressure Data ◽  
Pressure Distributions ◽  
Time Period ◽  
Alternative Approach ◽  
Simulation Purpose ◽  
Parametric Approximation

The article constitutes an alternative approach to transform air pressure distributions for downscaling climate parameters. The objectives include a low-parametric approximation of original pressure surfaces and, in the following, the analysis of the dependence structure of temporal successive distributions for simulation purpose. Wavelets are applied to carry outthe transformation of the distributions. Based on these results, time series analysis is used for the further investigations.The underlying air pressure data covers the relevant region for the central Europeanweather. Daily historical data is available for the time period between 1946 and 1994.

German Bight Storminess over the Last Century

2020 ◽  
Author(s):  
Daniel Krieger ◽  
Oliver Krueger ◽  
Frauke Feser ◽  
Ralf Weisse ◽  
Birger Tinz ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
German Bight ◽  
Geostrophic Wind ◽  
Air Pressure ◽  
Offshore Wind ◽  
Pressure Data ◽  
Storm Activity ◽  
Wind Speeds ◽  
North East

<p>Assessing past storm activity provides valuable knowledge for economic and ecological sectors, such as the renewable energy sector, insurances, or health and safety. However, long time series of wind speed measurements are often not available as they are usually hampered by inhomogeneities due to changes in the surroundings of a measurement site, station relocations, and changes in the instrumentation. On the contrary, air pressure measurements provide mostly homogeneous time series as the air pressure is usually unaffected by such factors.</p><p>Therefore, we perform statistical analyses on historical pressure data measured at several locations within the German Bight (southeastern North Sea) between 1897 and 2018. We calculate geostrophic wind speeds from triplets of mean sea level pressure observations that form triangles over the German Bight. We then investigate the evolution of German Bight storminess from 1897 to 2018 through analyzing upper quantiles of geostrophic wind speeds, which act as a proxy for past storm activity. The derivation of storm activity is achieved by enhancing the established triangle proxy method via combining and merging storminess time series from numerous partially overlapping triangles in an ensemble-like manner. The utilized approach allows for the construction of robust, long-term and subdaily German Bight storminess time series. Further, the method provides insights into the underlying uncertainty of the time series.</p><p>The results show that storm activity over the German Bight is subject to multidecadal variability. The latest decades are characterized by an increase in activity from the 1960s to the 1990s, followed by a decline lasting into the 2000s and below-average activity up until present. The results are backed through a comparison with reanalysis products from four datasets, which provide high-resolution wind and pressure data starting in 1979 and offshore wind speed measurements taken from the FINO-WIND project. This study also finds that German Bight storminess positively correlates with storminess in the North-East Atlantic in general. In certain years, however, notably different levels of storm activity in the two regions can be found, which likely result from shifted large-scale circulation patterns.</p>

THE USE OF HISTORICAL DATA IN ACCOUNTING RESEARCH: THE CASE OF THE AMERICAN SUGAR REFINING COMPANY

1997 ◽  
Vol 24 (2) ◽  
pp. 1-24 ◽  
Author(s):  
Robert Bricker ◽  
Kevin Brown
Keyword(s):  
Capital Market ◽  
Historical Data ◽  
Abnormal Returns ◽  
Deep Understanding ◽  
Historical Record ◽  
Historical Period ◽  
Financial Condition ◽  
A Value ◽  
Time Period ◽  
And Performance

In 1908, the American Sugar Refining Company (ASR) reversed its long-held policy of secrecy as to its financial condition and performance. Prior work, applying contemporary capital market methods to ASR security price data of that period, has suggested a value to ASR shareholders of this policy reversal. This paper examines the historical record of that time and presents additional evidence on this matter, particularly in terms of identifying potentially confounding events occurring during the period under study. The results of this analysis suggest a difficulty in attributing observed abnormal returns to ASR's secrecy policy reversal on the basis of the results obtained from applying capital markets methods. This analysis is useful for scholars interested in applying modern capital market methods to historical data. It highlights the significance of the possible effects of contemporaneous historical events, focuses attention on the importance of a deep understanding of the historical period studied, and suggests a value in combining historical and empirical-markets methods to gain a richer understanding of the events and conditions in the time period under study.

scholarly journals A Hybrid Energy System Workflow for Energy Portfolio Optimization

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4392
Author(s):  
Jia Zhou ◽  
Hany Abdel-Khalik ◽  
Paul Talbot ◽  
Cristian Rabiti
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Electricity Market ◽  
Process Model ◽  
Net Present Value ◽  
Historical Data ◽  
Energy System ◽  
Initial Guess ◽  
Reduced Order ◽  
The Impact

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

Effects of different wind directions on ventilation of surrounding areas of two generic building configurations in Hong Kong

2021 ◽  
pp. 1420326X2110160
Author(s):  
Kai Yip Lee ◽  
Cheuk Ming Mak
Keyword(s):  
Wind Velocity ◽  
Natural Ventilation ◽  
Urban Environments ◽  
Air Pressure ◽  
Pressure Distributions ◽  
Air Intake ◽  
Dynamics Simulations ◽  
Surrounding Areas ◽  
Effective Use ◽  
Velocity Zone

This study investigated effects of incident wind angles on wind velocity distributions in wakes of two generic building configurations, namely, ‘T’- and ‘+’-shaped, and the air pressure distributions along their leeward walls by using computational fluid dynamics simulations. Results show that when the wind approaches laterally (90°) (vs. when the wind is direct (0°)), the downwind length and maximum bilateral width of the low-wind velocity zone in the wake of ‘T’-shaped building decrease by 11.5% and 37.9%, respectively. When the incident wind is oblique (45°) (vs. when it is direct), the length and width of this low-wind velocity zone in the wake of ‘+’-shaped building decrease by 15.0% and 30.9%, respectively. Furthermore, results show that the air pressure on the leeward walls of the ‘T’- and ‘+’-shaped buildings gradually decreases along with the building height. The resulting low-wind conditions on upper floors of buildings reduce the fresh air intake of their leeward units utilizing natural ventilation. It is particularly apparent in the case of direct approaching wind. Thus, the appropriate selection of building configurations and their orientations allows for the most effective use of wind to enhance ventilation in indoor and urban environments.

scholarly journals Complexity traits and synchrony of cryptocurrencies price dynamics

2021 ◽  
Author(s):  
Davide Provenzano ◽  
Rodolfo Baggio
Keyword(s):  
Time Series ◽  
Complex Network ◽  
Complex Structures ◽  
Slope Parameter ◽  
Exponential Distributions ◽  
Horizontal Visibility ◽  
Time Period ◽  
Before And After ◽  
Visibility Algorithm ◽  
Similar Complex

AbstractIn this study, we characterized the dynamics and analyzed the degree of synchronization of the time series of daily closing prices and volumes in US$ of three cryptocurrencies, Bitcoin, Ethereum, and Litecoin, over the period September 1,2015–March 31, 2020. Time series were first mapped into a complex network by the horizontal visibility algorithm in order to revel the structure of their temporal characters and dynamics. Then, the synchrony of the time series was investigated to determine the possibility that the cryptocurrencies under study co-bubble simultaneously. Findings reveal similar complex structures for the three virtual currencies in terms of number and internal composition of communities. To the aim of our analysis, such result proves that price and volume dynamics of the cryptocurrencies were characterized by cyclical patterns of similar wavelength and amplitude over the time period considered. Yet, the value of the slope parameter associated with the exponential distributions fitted to the data suggests a higher stability and predictability for Bitcoin and Litecoin than for Ethereum. The study of synchrony between the time series investigated displayed a different degree of synchronization between the three cryptocurrencies before and after a collapse event. These results could be of interest for investors who might prefer to switch from one cryptocurrency to another to exploit the potential opportunities of profit generated by the dynamics of price and volumes in the market of virtual currencies.

scholarly journals LO22: Improving the pain experience for children with limb injury: a city-wide quality improvement collaborative

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S14-S14
Author(s):  
J. Thull-Freedman ◽  
T. Williamson ◽  
E. Pols ◽  
A. McFetridge ◽  
S. Libbey ◽  
...  
Keyword(s):  
Time Series ◽  
Quality Improvement ◽  
Time Series Analysis ◽  
Median Time ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Process Measures ◽  
Limb Injury ◽  
Time Period ◽  
Limb Injuries

Introduction: Undertreated pain is known to cause short and long-term harm in children. Limb injuries are a common painful condition in emergency department (ED) patients, accounting for 12% of ED visits by children. Our city has one pediatric ED in a freestanding children’s hospital and 3 general ED’s that treat both adults and children. 68% of pediatric limb injuries in our city are treated in the pediatric ED and 32% are treated in a general ED. A quality improvement (QI) initiative was developed at the children’s hospital ED in April 2015 focusing on “Commitment to Comfort.” After achieving aims at the childrens hospital, a QI collaborative was formed among the pediatric ED and the 3 general ED’s to 1) improve the proportion of children citywide receiving analgesia for limb injuries from 27% to 40% and 2) reduce the median time to analgesia from 37 minutes to 15 minutes, during the time period of April-September, 2016. Methods: Data were obtained from computerized order entry records for children 0-17.99 years visiting any participating ED with a chief complaint of limb injury. Project teams from each site met monthly to discuss aims, develop key driver diagrams, plan tests of change, and share learnings. Implementation strategies were based on the Model for Improvement with PDSA cycles. Patient and family consultation was obtained. Process measures included the proportion of children treated with analgesic medication and time to analgesia; balancing measures were duration of triage and length of stay for limb injury and all patients. Site-specific run charts were used to detect special cause variation. Data from all sites were combined at study end to measure city-wide impact using 2 and interrupted time series analysis. Results: During the 3.5-year time period studied (April 1, 2014-September 30, 2017), there were 45,567 visits to the participating ED’s by children 0-17.99 years with limb injury. All visits were included in analysis. Special cause was detected in run charts of all process measures. Interrupted time series analysis comparing the year prior to implementation at the childrens hospital in April 2015 to the year following completion of implementation at the 3 general hospitals in October 2016 demonstrated that the proportion of patients with limb injury receiving analgesia increased from 27% to 40% (p<0.01), and the median time from arrival to analgesia decreased from 37 to 11 minutes (p<0.01). Balancing measure analysis is in progress. Conclusion: This multisite initiative emphasizing “Commitment to Comfort” was successful in improving pain outcomes for all children with limb injuries seen in city-wide ED’s, and was sustained for one year following implementation. A QI collaborative can be an effective method for spreading improvement. The project team is now spreading the Commitment to Comfort initiative to over 30 rural and regional EDs throughout the province through establishment of a provincial QI collaborative.

Surface Pressure Distribution on a Blade of a 10 m Diameter HAWT (Field Measurements versus Wind Tunnel Measurements)

2005 ◽  
Vol 127 (2) ◽  
pp. 185-191 ◽  
Author(s):  
T. Maeda ◽  
E. Ismaili ◽  
H. Kawabuchi ◽  
Y. Kamada
Keyword(s):  
Wind Tunnel ◽  
Surface Pressure ◽  
Field Measurements ◽  
Reynolds Numbers ◽  
Blade Surface ◽  
Pressure Data ◽  
Surface Pressure Distribution ◽  
Pressure Distributions ◽  
Wind Tunnel Data ◽  
Local Angle

This paper exploits blade surface pressure data acquired by testing a three-bladed upwind turbine operating in the field. Data were collected for a rotor blade at spanwise 0.7R with the rotor disc at zero yaw. Then, for the same blade, surface pressure data were acquired by testing in a wind tunnel. Analyses compared aerodynamic forces and surface pressure distributions under field conditions against analogous baseline data acquired from the wind tunnel data. The results show that aerodynamic performance of the section 70%, for local angle of attack below static stall, is similar for free stream and wind tunnel conditions and resemblances those commonly observed on two-dimensional aerofoils near stall. For post-stall flow, it is presumed that the exhibited differences are attributes of the differences on the Reynolds numbers at which the experiments were conducted.

scholarly journals Time Series Modeling on Monthly Data of Tourist Arrivals in Nepal: An Alternative Approach

2017 ◽  
Vol 1 ◽  
pp. 41-54 ◽  
Author(s):  
Amrit Subedi
Keyword(s):  
Time Series ◽  
Autoregressive Model ◽  
Time Series Data ◽  
Polynomial Function ◽  
Seasonal Fluctuation ◽  
Ar Model ◽  
Series Data ◽  
Monthly Data ◽  
Annual Trend ◽  
Alternative Approach

Background: There are various approaches of modeling on time series data. Most of the studies conducted regarding time series data are based on annual trend whereas very few concerned with data having monthly fluctuation. The data of tourist arrivals is an example of time series data with monthly fluctuation which reveals that there is higher number of tourist arrivals in some months/seasons whereas others have less number. Starting from January, it makes a complete cycle in every 12 months with 3 bends indicating that it can be captured by biquadratic function.Objective: To provide an alternative approach of modeling i.e. combination of Autoregressive model with polynomial (biquadratic) function on time series data with monthly/seasonal fluctuation and compare its adequacy with widely used cyclic autoregressive model i.e. AR (12).Materials and Methods: This study is based on monthly data of tourist arrivals in Nepal. Firstly, usual time series model AR (12) has been adopted and an alternative approach of modeling has been attempted combining AR and biquadratic function. The first part of the model i.e. AR represents annual trend whereas biquadratic part does for monthly fluctuation.Results: The fitted cyclic autoregressive model on monthly data of tourist arrivals is Est. Ym = 3614.33 + 0.9509Ym-12, (R2=0.80); Est. Ym indicates predicted tourist arrivals for mth month and Ym-12 indicates observed tourist arrivals in (m-12)th month and the combined model of AR and biquadratic function is Est. Yt(m) = -46464.6 + 1.000Yt-1 + 52911.56m - 17177m2 + 2043.95m3 - 79.43m4, (R2=0.78); Est. Yt(m) indicates predicted tourist arrivals for mth month of tth year and Yt-1 indicates average tourist arrivals in (t-1)th year. The AR model combined with polynomial function reveals normal and homoscedastic residuals more accurately compared to first one.Conclusion: The use of polynomial function combined with autoregressive model can be useful for time series data having seasonal fluctuation. It can be an alternative approach for picking up a good model for such type of data. Nepalese Journal of Statistics, 2017,  Vol. 1, 41-54

Latex Carpet Compound Rheology

2008 ◽  
Vol 18 (6) ◽  
pp. 64250-1-64250-9
Author(s):  
Nick Triantafillopoulos ◽  
Bruce Schreiner ◽  
James Vaughn ◽  
Douglas Bousfield
Keyword(s):  
Shear Rate ◽  
Fluid Dynamic ◽  
Pressure Distributions ◽  
Time Period ◽  
Three Phase ◽  
Transient Viscosity ◽  
Short Time ◽  
Rate Development ◽  
Solid System ◽  
Foam Rheology

Abstract This is a study of three-phase foam rheology to qualify penetration in to backing webs during frothed carpet compounds applications. Transient viscosity as a function of shear rate under a short time period is proposed to characterize flow of these compounds in response to a rapidly changing shear field during their application. We developed a fluid dynamic model that predicts the shear and pressure distributions in the compound during its processing in a metering nip based on process parameters and rheological results. We tested frothed compound formulations that are empirically known to be “penetrating” and “non-penetrating” based on the choice of soap (frothing surfactant). Formulated at the same froth density, penetrating to carpet backing compounds had large froth bubbles, relatively low transient shear viscosity and showed increasing foam breakdown due to shear when compared to non-penetrating compounds. Such frothed compounds readily collapse under shear and have relatively low dynamic stability, so the transition from a three-phased (air/aqueous/solid) to a two-phased (water/solid) system occurs much easier and faster during application. The model predicts the shear rate development and a small difference in the pressure distributions in the applicator nip between these formulations, but reduction in drainage for the non-penetrating formulation.

Sign in / Sign up

Export Citation Format

Share Document