A new method for assessing the application of deterministic or stochastic modelling approach in evacuation scenarios

2014 ◽  
Vol 65 ◽  
pp. 11-18 ◽  
Author(s):  
D. Alvear ◽  
O. Abreu ◽  
A. Cuesta ◽  
V. Alonso
Keyword(s):  
Stochastic Modelling ◽  
New Method ◽  
Modelling Approach

Stochastic modelling of flow sequences for improved prediction of fluvial flood hazards

2018 ◽  
Vol 488 (1) ◽  
pp. 205-219 ◽  
Author(s):  
Sandhya Patidar ◽  
Deonie Allen ◽  
Rick Haynes ◽  
Heather Haynes
Keyword(s):  
Flood Risk ◽  
Stochastic Modelling ◽  
Statistical Characteristics ◽  
Probability Density Distribution ◽  
Flood Hazards ◽  
Limited Information ◽  
Daily Streamflow ◽  
Flooding Events ◽  
Gp Model ◽  
Modelling Approach

AbstractThe availability of historical streamflow data of the desired length is often limited and, in these situations, the ability to synthetically generate statistically significant datasets becomes important. We previously developed a highly efficient stochastic modelling approach for the synthetic generation of daily streamflow sequences using the systematic combination of a hidden Markov model with the generalized Pareto distribution (the HMM-GP model). Daily streamflow sequences provide limited information on various significant small duration flooding events exceeding the peak over threshold values, but these are averaged out in the daily datasets. These small duration intense flooding events are often capable of causing significant damage and are important in conducting thorough flood risk management and flood risk assessment studies. This paper presents upgrades to our HMM-GP stochastic modelling approach and examines its efficiency in simulating streamflow at a temporal resolution of 15 minutes. The potential of the HMM-GP model in simulating a synthetic 15-minute streamflow series is investigated by comparing various statistical characteristics (e.g. percentiles, the probability density distribution and the autocorrelation function) of the observed streamflow records with 100 synthetically simulated streamflow time series. The proposed modelling schematics are robustly validated across case studies in four UK rivers (the Don, Nith, Dee and Tweed).

scholarly journals Predicting DNA damage foci and their experimental readout with 2D microscopy: a unified approach applied to photon and neutron exposures

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sofia Barbieri ◽  
Gabriele Babini ◽  
Jacopo Morini ◽  
Werner Friedland ◽  
Manuela Buonanno ◽  
...  
Keyword(s):  
Dna Damage ◽  
Stochastic Modelling ◽  
Data Interpretation ◽  
Dose Dependence ◽  
Biological Damage ◽  
Full Control ◽  
Damage Content ◽  
Experimental Findings ◽  
Correct Data ◽  
Modelling Approach

Abstract The consideration of how a given technique affects results of experimental measurements is a must to achieve correct data interpretation. This might be challenging when it comes to measurements on biological systems, where it is unrealistic to have full control (e.g. through a software replica) of all steps in the measurement chain. In this work we address how the effectiveness of different radiation qualities in inducing biological damage can be assessed measuring DNA damage foci yields, only provided that artefacts related to the scoring technique are adequately considered. To this aim, we developed a unified stochastic modelling approach that, starting from radiation tracks, predicts both the induction, spatial distribution and complexity of DNA damage, and the experimental readout of foci when immunocytochemistry coupled to 2D fluorescence microscopy is used. The approach is used to interpret γ-H2AX data for photon and neutron exposures. When foci are reconstructed in the whole cell nucleus, we obtain information on damage characteristics “behind” experimental observations, as the average damage content of a focus. We reproduce how the detection technique affects experimental findings, e.g. contributing to the saturation of foci yields scored at 30 minutes after exposure with increasing dose and to the lack of dose dependence for yields at 24 hours.

scholarly journals Stochastic modelling and feedback control of bistability in a turbulent bluff body wake

2016 ◽  
Vol 802 ◽  
pp. 726-749 ◽  
Author(s):  
R. D. Brackston ◽  
J. M. García de la Cruz ◽  
A. Wynn ◽  
G. Rigas ◽  
J. F. Morrison
Keyword(s):  
Reynolds Number ◽  
Feedback Control ◽  
Symmetry Breaking ◽  
Large Scale ◽  
Bluff Body ◽  
Three Dimensional ◽  
Power Saving ◽  
Stochastic Modelling ◽  
Bluff Body Wake ◽  
Modelling Approach

A specific feature of three-dimensional bluff body wakes, flow bistability, is a subject of particular recent interest. This feature consists of a random flipping of the wake between two asymmetric configurations and is believed to contribute to the pressure drag of many bluff bodies. In this study we apply the modelling approach recently suggested for axisymmetric bodies by Rigaset al.(J. Fluid Mech., vol. 778, 2015, R2) to the reflectional symmetry-breaking modes of a rectilinear bluff body wake. We demonstrate the validity of the model and its Reynolds number independence through time-resolved base pressure measurements of the natural wake. Further, oscillating flaps are used to investigate the dynamics and time scales of the instability associated with the flipping process, demonstrating that they are largely independent of Reynolds number. The modelling approach is then used to design a feedback controller that uses the flaps to suppress the symmetry-breaking modes. The controller is successful, leading to a suppression of the bistability of the wake, with concomitant reductions in both lateral and streamwise forces. Importantly, the controller is found to be efficient, the actuator requiring only 24 % of the aerodynamic power saving. The controller therefore provides a key demonstration of efficient feedback control used to reduce the drag of a high-Reynolds-number three-dimensional bluff body. Furthermore, the results suggest that suppression of large-scale structures is a fundamentally efficient approach for bluff body drag reduction.

Faulted geological contacts: constraining uncertainty of discontinuities orientation using triangulation and combinatorial algorithm

2020 ◽  
Author(s):  
Michał Michalak ◽  
Ryszard Kuzak ◽  
Paweł Gładki ◽  
Agnieszka Kulawik
Keyword(s):  
Limited Resource ◽  
New Method ◽  
Combinatorial Algorithm ◽  
Fault Surface ◽  
Dominant Orientation ◽  
Delaunay Triangles ◽  
Synthetic Models ◽  
Element Set ◽  
Modelling Approach ◽  
Genetic Trends

<p>Subsurface information is usually a limited resource in geological modelling. This is not the case, however, for the Kraków-Silesian Homocline in central Poland. It was subject to rapid exploitation of ore-bearing clays in the second half of the 20<sup>th </sup>century. Exhaustive geological documentation remained after this activity had ceased and it contains thousands of borehole records. A small part of this resource has recently been incorporated to propose a new method for determining the dominant orientation of a selected geological contact. This new method regarded Delaunay triangles as source of local orientations that were then analyzed on stereonets. The geological contacts in this region are inclined gently towards NE, but they are also faulted and indicate some stratigraphic noise which makes the extraction of dominant orientation a challenging task.</p><p>It is still unknown, however, to which extent the proposed modelling approach is capable of detecting faults and calculating their orientation. This is particularly important for the introduction of a new method for the recognition of faults based on investigating spatial distribution of orientation patterns. This expert-guided methodology assumes to relate orientation trends with genetic trends and investigate them on 2D maps.</p><p>In this research, we built synthetic models of faulted contacts to observe the behaviour of triangles intersecting the fault surface. To observe the variability of the orientation at larger scale, and perhaps to constrain it at the same time, we applied a combinatorial algorithm for creating all three-element subsets from an n-element set. The employment of this combinatorial approach allowed to achieve a better clustering effect around the expected orientation. The limitation of the proposed approach can be attributed to some unexpected and unintuitive orientations. Compared to previous studies these singularities seem to be geometrical and not numerical in nature.</p>

A STOCHASTIC MODELLING APPROACH TO ACTUATED CONTROLS

2006 ◽  
Vol 39 (12) ◽  
pp. 478-483
Author(s):  
Francesco Viti ◽  
Hao Liu ◽  
Henk J. van Zuylen
Keyword(s):  
Stochastic Modelling ◽  
Modelling Approach

scholarly journals Asset Allocation to Optimise Life Insurance Annuity Firm Economic Capital and Risk Adjusted Performance

2008 ◽  
Vol 3 (1-2) ◽  
pp. 187-214 ◽  
Author(s):  
Bruce T. Porteous ◽  
Pradip Tapadar
Keyword(s):  
Life Insurance ◽  
Asset Allocation ◽  
Financial Services ◽  
Stochastic Modelling ◽  
Economic Capital ◽  
Conventional Wisdom ◽  
Low Risk ◽  
Bond Type ◽  
The Impact ◽  
Modelling Approach

ABSTRACTThe impact that asset allocation has on the economic capital and the risk adjusted performance of financial services firms is considered in this article. A stochastic modelling approach is used in conjunction with a life insurance annuity firm illustrative example. It is shown that traditional solvency driven deterministic approaches to financial services firm asset allocation can yield sub optimal results in terms of minimising economic capital or maximising risk adjusted performance. Our results challenge the conventional wisdom that the assets backing life insurance annuities and financial services firm capital should be invested in low risk, bond type, assets. Implications for firms, customers, capital providers and regulators are discussed.

scholarly journals A Stochastic Modelling Approach to Forecast Real-time Ice Jam Flood Severity Along the Transborder (New Brunswick/Maine) Saint John River of North America

2021 ◽  
Author(s):  
Apurba Das ◽  
Sujata Budhathoki ◽  
Karl-Erich Lindenschmidt
Keyword(s):  
Land Surface ◽  
Human Life ◽  
Stochastic Modelling ◽  
Stochastic Approach ◽  
Monte Carlo Analysis ◽  
Flood Forecasting ◽  
River Ice ◽  
Ice Jam ◽  
Saint John ◽  
Modelling Approach

Abstract Ice jam floods (IJF) are a major concern for many riverine communities, government and non-government authorities and companies in the higher latitudes of the northern hemisphere. Ice jam related flooding can result in millions of dollars of property damages, loss of human life and adverse impacts on ecology. Ice jam flood forecasting is challenging as its formation mechanism is chaotic and depends on numerous unpredictable hydraulic and river ice factors. In this study, Modélisation environnementale communautaire – surface hydrology (MESH), a semi-distributed physically-based land-surface hydrological modelling system was used to acquire a 10-day flow forecast, an important boundary condition for any modelling of river ice-jam flood forecasting. A stochastic modelling approach was then applied to simulate hundreds of possible ice-jam scenarios using the hydrodynamic river ice model RIVICE within a Monte-Carlo Analysis (MOCA) framework for the Saint John River from Fort Kent to Grand Falls. First, a 10-day outlook was simulated to provide insight on the severity of ice jam flooding during spring breakup. Then, 3-day forecasts were modelled to provide longitudinal profiles of exceedance probabilities of ice jam flood staging along the river during the ice-cover breakup. Overall, results show that the stochastic approach performed well to estimate maximum probable ice-jam backwater level elevations for the spring 2021 breakup season.

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