scholarly journals <i>HESS Opinions</i> "A random walk on water"

2009 ◽  
Vol 6 (5) ◽  
pp. 6611-6658 ◽  
Author(s):  
D. Koutsoyiannis
Keyword(s):  
Random Walk ◽  
Time Horizon ◽  
Initial Conditions ◽  
Intrinsic Property ◽  
Natural Phenomena ◽  
Stochastic Representation ◽  
Natural Processes ◽  
Stochastic Properties ◽  
High Uncertainty

Abstract. According to the traditional notion of randomness and uncertainty, natural phenomena are separated into two mutually exclusive components, random (or stochastic) and deterministic. Within this dichotomous logic, the deterministic part supposedly represents cause-effect relationships and, thus, is physics and science (the "good"), whereas randomness has little relationship with science and no relationship with understanding (the "evil"). We argue that such views should be reconsidered by admitting that uncertainty is an intrinsic property of nature, that causality implies dependence of natural processes in time, thus suggesting predictability, but even the tiniest uncertainty (e.g., in initial conditions) may result in unpredictability after a certain time horizon. On these premises it is possible to shape a consistent stochastic representation of natural processes, in which predictability (suggested by deterministic laws) and unpredictability (randomness) coexist and are not separable or additive components. Deciding which of the two dominates is simply a matter of specifying the time horizon of the prediction. Long horizons of prediction are inevitably associated with high uncertainty, whose quantification relies on understanding the long-term stochastic properties of the processes.

scholarly journals HESS Opinions "A random walk on water"

2010 ◽  
Vol 14 (3) ◽  
pp. 585-601 ◽  
Author(s):  
D. Koutsoyiannis
Keyword(s):  
Random Walk ◽  
Time Horizon ◽  
Initial Conditions ◽  
Intrinsic Property ◽  
Natural Phenomena ◽  
Stochastic Representation ◽  
Natural Processes ◽  
Stochastic Properties ◽  
High Uncertainty

Abstract. According to the traditional notion of randomness and uncertainty, natural phenomena are separated into two mutually exclusive components, random (or stochastic) and deterministic. Within this dichotomous logic, the deterministic part supposedly represents cause-effect relationships and, thus, is physics and science (the "good"), whereas randomness has little relationship with science and no relationship with understanding (the "evil"). Here I argue that such views should be reconsidered by admitting that uncertainty is an intrinsic property of nature, that causality implies dependence of natural processes in time, thus suggesting predictability, but even the tiniest uncertainty (e.g. in initial conditions) may result in unpredictability after a certain time horizon. On these premises it is possible to shape a consistent stochastic representation of natural processes, in which predictability (suggested by deterministic laws) and unpredictability (randomness) coexist and are not separable or additive components. Deciding which of the two dominates is simply a matter of specifying the time horizon and scale of the prediction. Long horizons of prediction are inevitably associated with high uncertainty, whose quantification relies on the long-term stochastic properties of the processes.

scholarly journals Aircraft Maintenance Check Scheduling Using Reinforcement Learning

Aerospace ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 113
Author(s):  
Pedro Andrade ◽  
Catarina Silva ◽  
Bernardete Ribeiro ◽  
Bruno F. Santos
Keyword(s):  
Reinforcement Learning ◽  
Time Horizon ◽  
Learning Algorithm ◽  
Initial Conditions ◽  
Q Learning ◽  
Scheduling Policy ◽  
Real Scenario ◽  
Maintenance Plan ◽  
Small Disturbances

This paper presents a Reinforcement Learning (RL) approach to optimize the long-term scheduling of maintenance for an aircraft fleet. The problem considers fleet status, maintenance capacity, and other maintenance constraints to schedule hangar checks for a specified time horizon. The checks are scheduled within an interval, and the goal is to, schedule them as close as possible to their due date. In doing so, the number of checks is reduced, and the fleet availability increases. A Deep Q-learning algorithm is used to optimize the scheduling policy. The model is validated in a real scenario using maintenance data from 45 aircraft. The maintenance plan that is generated with our approach is compared with a previous study, which presented a Dynamic Programming (DP) based approach and airline estimations for the same period. The results show a reduction in the number of checks scheduled, which indicates the potential of RL in solving this problem. The adaptability of RL is also tested by introducing small disturbances in the initial conditions. After training the model with these simulated scenarios, the results show the robustness of the RL approach and its ability to generate efficient maintenance plans in only a few seconds.

scholarly journals The geographical prerequisites for the identification and prevention of dangerous geomorphological processes in the mountain geosystems of the Alpine-Himalayan belt (on the example of the Major Caucasus of Azerbaijan)

2020 ◽  
Vol 29 (1) ◽  
pp. 176-187
Author(s):  
Stara A. Tarikhazer
Keyword(s):  
Large Scale ◽  
Natural Phenomena ◽  
Mountainous Areas ◽  
Economic Activities ◽  
Natural Processes ◽  
Himalayan Belt ◽  
Himalayan Orogenic Belt ◽  
Geomorphological Processes ◽  
The Stability

Destructive natural phenomena are a serious, sometimes unsolvable, regional and local environmental and socioeconomic problem. This paper presents the results of a comprehensive analysis of materials from long-term geomorphological studies in the mountainous areas on the example of the Major Caucasus of Azerbaijan. The dangerous geomorphological processes on the example of the Major Caucasus of Azerbaijan were investigated in detail using large-scale maps, satellite imagery and aerial photography. Geomorphological maps were drawn (map of mudflow hazard and map of landslide hazard in the Azerbaijani part of the Major Caucasus). The research determined the dangerous zones where landslides could cover 65–70% of the total area and outlined the zones and regularities of spread of various types of mudflow origination sites. The analysis of the manifestations of most active (with catastrophic consequences) destructive natural processes and the morphotectonic structure of the studied area showed that the their occurrence and maximum intensity was confined to the weakest plexuses of mountains – intersections of faults and fractures of various directions and orders. A technique for assessing the eco-geomorphological risk to prevent dangerous natural phenomena was offered. The technique is based on the detection of zones with intensive geomorphological processes, which are often not dangerous separately, but could have catastrophic consequences together. The results obtained during the assessment of the effect of natural and man-caused factors on the stability of montane ecosystems may be used to forecast dangerous natural phenomena and to research geodynamical dangerous geomorphological process not only in Azerbaijan, but also in other regions of the Alpine-Himalayan orogenic belt. The obtained results can be used to plan and perform economic activities, determine and minimize the hazards and risks of occurrence of dangerous natural phenomena, and forecast such phenomena in the future.

scholarly journals Novel Method to Analytically Obtain the Asymptotic Stable Equilibria States of Extended SIR-type Epidemiological Models

2021 ◽  
Author(s):  
Teddy Lazebnik ◽  
Svetlana Bunimovich-Mendrazitsky ◽  
Leonid Shaikhet
Keyword(s):  
Large Scale ◽  
Initial Conditions ◽  
Scale Model ◽  
Epidemiological Models ◽  
Stochastic Representation ◽  
Asymptotic Stable ◽  
Large Scale Model ◽  
Stable Equilibria ◽  
Novel Method

We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the SIR-type epidemiological model that we developed for viral diseases with long-term immunity memory pandemic. This is a large-scale model containing 15 nonlinear ODE equations, and classical methods have failed to analytically obtain its equilibria. The proposed method is used to conduct a comprehensive analysis by a stochastic representation of the dynamics of the model, followed by finding all asymptotic stable equilibrium states of the model for any values of parameters and initial conditions.

scholarly journals Novel Method to Analytically Obtain the Asymptotic Stable Equilibria States of Extended SIR-Type Epidemiological Models

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1120
Author(s):  
Teddy Lazebnik ◽  
Svetlana Bunimovich-Mendrazitsky ◽  
Leonid Shaikhet
Keyword(s):  
Large Scale ◽  
Initial Conditions ◽  
Scale Model ◽  
Epidemiological Models ◽  
Stochastic Representation ◽  
Asymptotic Stable ◽  
Large Scale Model ◽  
Stable Equilibria ◽  
Novel Method

We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the Susceptible-Infectious-Recovered (SIR)-type epidemiological model that we developed for viral diseases with long-term immunity memory. This is a large-scale model containing 15 nonlinear ordinary differential equations (ODEs), and classical methods have failed to analytically obtain its equilibria. The proposed method is used to conduct a comprehensive analysis by a stochastic representation of the dynamics of the model, followed by finding all asymptotic stable equilibrium states of the model for any values of parameters and initial conditions thanks to the symmetry of the population size over time.

(A review) Atlas of especially protected natural areas of Saint Petersburg / Ed. in chief V. N. Khramtsov, T. V. Kovaleva, N. Yu. Natsvaladze. St. Petersburg, 2013. 176 p.

2014 ◽  
pp. 124-129
Author(s):  
Z. V. Karamysheva
Keyword(s):  
Protected Areas ◽  
Large Scale ◽  
Natural Areas ◽  
Natural Protected Areas ◽  
Saint Petersburg ◽  
Natural Processes ◽  
Original Illustrations ◽  
Vegetation Maps ◽  
Protected Natural Areas

The review contains detailed description of the «Atlas of especially protected natural areas of Saint Petersburg» published in 2013. This publication presents the results of long-term studies of 12 natural protected areas made by a large research team in the years from 2002 to 2013 (see References). The Atlas contains a large number of the historical maps, new satellite images, the original illustrations, detailed texts on the nature of protected areas, summary tables of rare species of vascular plants, fungi and vertebrates recorded in these areas. Special attention is paid to the principles of thematic large-scale mapping. The landscape maps, the vegetation maps as well as the maps of natural processes in landscapes are included. Reviewed Atlas deserves the highest praise.

scholarly journals Should We Expect a Disastrous Fire Accident in an Urban Road Tunnel? Literature Data Review and a Case Study for Selected Tunnels in Poland

2021 ◽  
Vol 13 (11) ◽  
pp. 6172
Author(s):  
Krystian Szewczyński ◽  
Aleksander Król ◽  
Małgorzata Król
Keyword(s):  
Time Horizon ◽  
Road Traffic ◽  
Traffic Intensity ◽  
Road Tunnel ◽  
Urban Road ◽  
Road Tunnels ◽  
High Uncertainty ◽  
Fire Outbreak ◽  
Fire Accident

Urban road tunnels are a reasonable remedy for inconvenience due to congested road traffic. However, they bring specific threats, especially those related to the possibility of fire outbreak. This work is a case study for selected urban road tunnels. Considering tunnel specificity, road traffic intensity, and structure and based on the literature data for vehicle fire probability, the chances of a fire accident were estimated for selected tunnels in Poland. It was shown that low power tunnel fires could be expected in the 10–20-year time horizon. Although such threats cannot be disregarded, tunnel systems are designed to cope with them. The chances of a disastrous fire accident were estimated as well. Such events can occur when an HGV with flammable goods or a tanker are involved. Such accidents are fortunately very rare, but, on the other hand, that is the reason why the available data are scanty and burdened with high uncertainty. Therefore, a discussion on the reliability of the obtained results is also provided.

scholarly journals MATLAB Virtual Toolbox for Retrospective Rockfall Source Detection and Volume Estimation Using 3D Point Clouds: A Case Study of a Subalpine Molasse Cliff

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 75
Author(s):  
Dario Carrea ◽  
Antonio Abellan ◽  
Marc-Henri Derron ◽  
Neal Gauvin ◽  
Michel Jaboyedoff
Keyword(s):  
Point Cloud ◽  
Natural Hazard ◽  
Point Clouds ◽  
Volume Estimation ◽  
Natural Phenomena ◽  
Frequency Distributions ◽  
Erosion Rates ◽  
3D Point Clouds

The use of 3D point clouds to improve the understanding of natural phenomena is currently applied in natural hazard investigations, including the quantification of rockfall activity. However, 3D point cloud treatment is typically accomplished using nondedicated (and not optimal) software. To fill this gap, we present an open-source, specific rockfall package in an object-oriented toolbox developed in the MATLAB® environment. The proposed package offers a complete and semiautomatic 3D solution that spans from extraction to identification and volume estimations of rockfall sources using state-of-the-art methods and newly implemented algorithms. To illustrate the capabilities of this package, we acquired a series of high-quality point clouds in a pilot study area referred to as the La Cornalle cliff (West Switzerland), obtained robust volume estimations at different volumetric scales, and derived rockfall magnitude–frequency distributions, which assisted in the assessment of rockfall activity and long-term erosion rates. An outcome of the case study shows the influence of the volume computation on the magnitude–frequency distribution and ensuing erosion process interpretation.

scholarly journals Ensemble forecasting greatly expands the prediction horizon for ocean mesoscale variability

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Prasad G. Thoppil ◽  
Sergey Frolov ◽  
Clark D. Rowley ◽  
Carolyn A. Reynolds ◽  
Gregg A. Jacobs ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
Mesoscale Dynamics ◽  
Predictive Skill ◽  
Freshwater Transport ◽  
Prediction Horizon ◽  
Initial Location ◽  
Ocean Models ◽  
High Uncertainty

AbstractMesoscale eddies dominate energetics of the ocean, modify mass, heat and freshwater transport and primary production in the upper ocean. However, the forecast skill horizon for ocean mesoscales in current operational models is shorter than 10 days: eddy-resolving ocean models, with horizontal resolution finer than 10 km in mid-latitudes, represent mesoscale dynamics, but mesoscale initial conditions are hard to constrain with available observations. Here we analyze a suite of ocean model simulations at high (1/25°) and lower (1/12.5°) resolution and compare with an ensemble of lower-resolution simulations. We show that the ensemble forecast significantly extends the predictability of the ocean mesoscales to between 20 and 40 days. We find that the lack of predictive skill in data assimilative deterministic ocean models is due to high uncertainty in the initial location and forecast of mesoscale features. Ensemble simulations account for this uncertainty and filter-out unconstrained scales. We suggest that advancements in ensemble analysis and forecasting should complement the current focus on high-resolution modeling of the ocean.

scholarly journals Simulation of MASPn Experiments in MISTRA Test Facility with COCOSYS Code

2008 ◽  
Vol 2008 ◽  
pp. 1-7 ◽  
Author(s):  
Mantas Povilaitis ◽  
Egidijus Urbonavičius
Keyword(s):  
Boundary Conditions ◽  
Nuclear Power ◽  
Power Plants ◽  
Volume Fraction ◽  
Characteristic Length ◽  
Initial Conditions ◽  
Test Facility ◽  
Work Package ◽  
Acceptable Agreement

An issue of the stratified atmospheres in the containments of nuclear power plants is still unresolved; different experiments are performed in the test facilities like TOSQAN and MISTRA. MASPn experiments belong to the spray benchmark, initiated in the containment atmosphere mixing work package of the SARNET network. The benchmark consisted of MASP0, MASP1 and MASP2 experiments. Only the measured depressurisation rates during MASPn were available for the comparison with calculations. When the analysis was performed, the boundary conditions were not clearly defined therefore most of the attention was concentrated on MASP0 simulation in order to develop the nodalisation scheme and define the initial and boundary conditions. After achieving acceptable agreement with measured depressurisation rate, simulations of MASP1 and MASP2 experiments were performed to check the influence of sprays. The paper presents developed nodalisation scheme of MISTRA for the COCOSYS code and the results of analyses. In the performed analyses, several parameters were considered: initial conditions, loss coefficient of the junctions, initial gradients of temperature and steam volume fraction, and characteristic length of structures. Parametric analysis shows that in the simulation the heat losses through the external walls behind the lower condenser installed in the MISTRA facility determine the long-term depressurisation rate.

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