scholarly journals RandomFront 2.3: a physical parameterisation of fire spotting for operational fire spread models – implementation in WRF-SFIRE and response analysis with LSFire+

2019 ◽  
Vol 12 (1) ◽  
pp. 69-87 ◽  
Author(s):  
Andrea Trucchia ◽  
Vera Egorova ◽  
Anton Butenko ◽  
Inderpreet Kaur ◽  
Gianni Pagnini
Keyword(s):  
Large Scale ◽  
Fire Spread ◽  
Response Analysis ◽  
Test Case ◽  
Physical Processes ◽  
Time Step ◽  
Propagation Models ◽  
Processing Scheme ◽  
Firebrand Transport ◽  
The Many

Abstract. Fire spotting is often responsible for dangerous flare-ups in wildfires and causes secondary ignitions isolated from the primary fire zone, which lead to perilous situations. The main aim of the present research is to provide a versatile probabilistic model for fire spotting that is suitable for implementation as a post-processing scheme at each time step in any of the existing operational large-scale wildfire propagation models, without calling for any major changes in the original framework. In particular, a complete physical parameterisation of fire spotting is presented and the corresponding updated model RandomFront 2.3 is implemented in a coupled fire–atmosphere model: WRF-SFIRE. A test case is simulated and discussed. Moreover, the results from different simulations with a simple model based on the level set method, namely LSFire+, highlight the response of the parameterisation to varying fire intensities, wind conditions and different firebrand radii. The contribution of the firebrands to increasing the fire perimeter varies according to different concurrent conditions, and the simulations show results in agreement with the physical processes. Among the many rigorous approaches available in the literature to model firebrand transport and distribution, the approach presented here proves to be simple yet versatile for application to operational large-scale fire spread models.

scholarly journals Physical parametrisation of fire-spotting for operational fire spread models: response analysis with a model based on the Level Set Method

2018 ◽  
Author(s):  
Inderpreet Kaur ◽  
Anton Butenko ◽  
Gianni Pagnini
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Discrete Event ◽  
Fire Spread ◽  
Response Analysis ◽  
System Specification ◽  
Time Step ◽  
Processing Scheme ◽  
Model Based ◽  
The Many

Abstract. Fire-spotting is often responsible for a dangerous flare up in the wildfire and causes secondary ignitions isolated from the primary fire zone leading to perilous situations. In this paper a complete physical parametrisation of fire-spotting is presented within a formulation aimed to include random processes into operational fire spread models. This formulation can be implemented into existing operational models as a post-processing scheme at each time step, without calling for any major changes in the original framework. In particular, the efficacy of this formulation has already been shown for wildfire simulators based on an Eulerian moving interface method, namely the Level Set Method (LSM) that forms the baseline of the operational software WRF-SFIRE, and for wildfire simulators based on a Lagrangian front tracking technique, namely the Discrete Event System Specification (DEVS) that forms the baseline of the operational software FOREFIRE. The simple and computationally less expensive parametrisation includes the important parameters necessary for describing the landing behavior of the firebrands. The results from different simulations with a simple model based on the LSM highlight the response of the parametrisation to varying fire intensities, wind conditions and different firebrand radii. The contribution of the firebrands towards increasing the fire perimeter varies according to different concurrent conditions and the simulation results prove to be in agreement with the physical processes. Among the many rigorous approaches available in literature to model the firebrand transport and distribution, the approach presented here proves to be simple yet versatile for application to operational fire spread models.

Integration of Ecological and Engineering Aspects in Planning Large Scale Tidal Power Development in the Bay of Fundy, Canada

1984 ◽  
Vol 16 (1-2) ◽  
pp. 281-295 ◽  
Author(s):  
Donald C Gordon
Keyword(s):  
Large Scale ◽  
Feasibility Studies ◽  
Bay Of Fundy ◽  
Final Decision ◽  
Power Development ◽  
Tidal Power ◽  
History Of ◽  
Scientists And Engineers ◽  
The Many ◽  
University Scientists

Large-scale tidal power development in the Bay of Fundy has been given serious consideration for over 60 years. There has been a long history of productive interaction between environmental scientists and engineers durinn the many feasibility studies undertaken. Up until recently, tidal power proposals were dropped on economic grounds. However, large-scale development in the upper reaches of the Bay of Fundy now appears to be economically viable and a pre-commitment design program is highly likely in the near future. A large number of basic scientific research studies have been and are being conducted by government and university scientists. Likely environmental impacts have been examined by scientists and engineers together in a preliminary fashion on several occasions. A full environmental assessment will be conducted before a final decision is made and the results will definately influence the outcome.

scholarly journals A Novel Unsupervised Classification Method for Sandy Land Using Fully Polarimetric SAR Data

2021 ◽  
Vol 13 (3) ◽  
pp. 355
Author(s):  
Weixian Tan ◽  
Borong Sun ◽  
Chenyu Xiao ◽  
Pingping Huang ◽  
Wei Xu ◽  
...  
Keyword(s):  
Spectral Clustering ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Feature Vector ◽  
Unsupervised Classification ◽  
Classification Method ◽  
Sandy Land ◽  
Classification Methods ◽  
The Many ◽  
Representative Points

Classification based on polarimetric synthetic aperture radar (PolSAR) images is an emerging technology, and recent years have seen the introduction of various classification methods that have been proven to be effective to identify typical features of many terrain types. Among the many regions of the study, the Hunshandake Sandy Land in Inner Mongolia, China stands out for its vast area of sandy land, variety of ground objects, and intricate structure, with more irregular characteristics than conventional land cover. Accounting for the particular surface features of the Hunshandake Sandy Land, an unsupervised classification method based on new decomposition and large-scale spectral clustering with superpixels (ND-LSC) is proposed in this study. Firstly, the polarization scattering parameters are extracted through a new decomposition, rather than other decomposition approaches, which gives rise to more accurate feature vector estimate. Secondly, a large-scale spectral clustering is applied as appropriate to meet the massive land and complex terrain. More specifically, this involves a beginning sub-step of superpixels generation via the Adaptive Simple Linear Iterative Clustering (ASLIC) algorithm when the feature vector combined with the spatial coordinate information are employed as input, and subsequently a sub-step of representative points selection as well as bipartite graph formation, followed by the spectral clustering algorithm to complete the classification task. Finally, testing and analysis are conducted on the RADARSAT-2 fully PolSAR dataset acquired over the Hunshandake Sandy Land in 2016. Both qualitative and quantitative experiments compared with several classification methods are conducted to show that proposed method can significantly improve performance on classification.

scholarly journals Grounding semantic transparency in context

Morphology ◽  
2021 ◽  
Author(s):  
Rossella Varvara ◽  
Gabriella Lapesa ◽  
Sebastian Padó
Keyword(s):  
Large Scale ◽  
Point Of View ◽  
Distributional Semantics ◽  
Semantic Transparency ◽  
Inclusion Measure ◽  
The Difference ◽  
Semantic Point ◽  
The Many ◽  
The Relationship

AbstractWe present the results of a large-scale corpus-based comparison of two German event nominalization patterns: deverbal nouns in -ung (e.g., die Evaluierung, ‘the evaluation’) and nominal infinitives (e.g., das Evaluieren, ‘the evaluating’). Among the many available event nominalization patterns for German, we selected these two because they are both highly productive and challenging from the semantic point of view. Both patterns are known to keep a tight relation with the event denoted by the base verb, but with different nuances. Our study targets a better understanding of the differences in their semantic import.The key notion of our comparison is that of semantic transparency, and we propose a usage-based characterization of the relationship between derived nominals and their bases. Using methods from distributional semantics, we bring to bear two concrete measures of transparency which highlight different nuances: the first one, cosine, detects nominalizations which are semantically similar to their bases; the second one, distributional inclusion, detects nominalizations which are used in a subset of the contexts of the base verb. We find that only the inclusion measure helps in characterizing the difference between the two types of nominalizations, in relation with the traditionally considered variable of relative frequency (Hay, 2001). Finally, the distributional analysis allows us to frame our comparison in the broader coordinates of the inflection vs. derivation cline.

scholarly journals A large-scale 2005–2012 flood map record derived from ENVISAT-ASAR data: United Kingdom as a test case

2021 ◽  
Vol 256 ◽  
pp. 112338
Author(s):  
Jie Zhao ◽  
Ramona Pelich ◽  
Renaud Hostache ◽  
Patrick Matgen ◽  
Wolfgang Wagner ◽  
...  
Keyword(s):  
United Kingdom ◽  
Large Scale ◽  
Test Case ◽  
Envisat Asar

scholarly journals Opportunistic Large Array Propagation Models: A Comprehensive Survey

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4206
Author(s):  
Farhan Nawaz ◽  
Hemant Kumar ◽  
Syed Ali Hassan ◽  
Haejoon Jung
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Performance Metrics ◽  
Experimental Studies ◽  
Cooperative Transmission ◽  
Analytical Models ◽  
Future Research ◽  
Large Array ◽  
Propagation Models ◽  
Comprehensive Survey

Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

scholarly journals A new noise detected in the ocean

2007 ◽  
Vol 87 (5) ◽  
pp. 1255-1256 ◽  
Author(s):  
Angel Guerra ◽  
Xavier Martinell ◽  
Angel F. González ◽  
Michael Vecchione ◽  
Joaquin Gracia ◽  
...  
Keyword(s):  
Ambient Noise ◽  
Sound Production ◽  
Biological Activities ◽  
Physical Processes ◽  
Defensive Strategy ◽  
Reflection And Refraction ◽  
Turbulent Pressure ◽  
In The Wild ◽  
The Many ◽  
Many Sources

Many observers have noted that the sea is full of loud sounds, both ongoing and episodic. Among the many sources of natural ambient noise are wave action, physical processes such as undersea earthquakes, and biological activities of shrimps, fish, dolphins and whales. Despite interest by acoustics experts, sound production by cephalopods has been reported only twice, both involving squid. The ‘faint poppings’ produced were thought to result from fluttering of the thin external lips of the squid's funnel while water is being expelled through it. Otherwise, no information is available on cephalopod sounds. Here we present a noise produced by a stressed common octopus. The event was filmed and recorded in the wild. The hypothesis we offer to explain how this sound was produced is cavitation, which has been documented in several biological systems. In our case, the water expelled through the funnel may have created a jet with a velocity so high that the turbulent pressure dropped locally below the vapour pressure of the water. Seawater contains gas microbubbles, which will grow in size when they are entrained in the region of low pressure. Subsequently, the bubbles collapse violently when pressure rises again. The sound produced by the octopus is like a gunshot, and distinct lights observed at the same time contradict the existence of a simple pressure wave and point to the possible presence of gas-bubbles, which would change the light intensity by reflection and refraction of the sunlight. This behaviour seems to be a defensive strategy to escape from vibration-sensitive predators.

Toolkit for Epidemiologic Response to an Acute Chemical Release

2016 ◽  
Vol 10 (4) ◽  
pp. 631-632 ◽  
Author(s):  
Mary Anne Duncan ◽  
Maureen F. Orr
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Technical Assistance ◽  
Local Health ◽  
Toxic Substances ◽  
Public Health Action ◽  
Public Health Agencies ◽  
Chemical Release ◽  
State And Local ◽  
The Many

AbstractWhen a large chemical incident occurs and people are injured, public health agencies need to be able to provide guidance and respond to questions from the public, the media, and public officials. Because of this urgent need for information to support appropriate public health action, the Agency for Toxic Substances and Disease Registry (ATSDR) of the US Department of Health and Human Services has developed the Assessment of Chemical Exposures (ACE) Toolkit. The ACE Toolkit, available on the ATSDR website, offers materials including surveys, consent forms, databases, and training materials that state and local health personnel can use to rapidly conduct an epidemiologic investigation after a large-scale acute chemical release. All materials are readily adaptable to the many different chemical incident scenarios that may occur and the data needs of the responding agency. An expert ACE team is available to provide technical assistance on site or remotely. (Disaster Med Public Health Preparedness. 2016;10:631–632)

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