scholarly journals Wildland surface fire spread modelling, 1990 - 2007. 1: Physical and quasi-physical models

2009 ◽  
Vol 18 (4) ◽  
pp. 349 ◽  
Author(s):  
Andrew L. Sullivan
Keyword(s):  
Physical Nature ◽  
Simulation Models ◽  
Fire Spread ◽  
Physical Models ◽  
Current Paper ◽  
Present Series ◽  
Wildland Fires ◽  
Computational Power ◽  
Surface Fire ◽  
Starting Point

In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across the landscape. The present series of articles endeavours to comprehensively survey and précis all types of surface fire spread models developed during the period 1990–2007, providing a useful starting point for those readers interested in recent modelling activities. The current paper surveys models of a physical or quasi-physical nature. These models are based on the fundamental chemistry and physics, or physics alone, of combustion and fire spread. Other papers in the series review models of an empirical or quasi-empirical nature, and mathematical analogues and simulation models. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but in much less detail.

scholarly journals Wildland surface fire spread modelling, 1990 - 2007. 2: Empirical and quasi-empirical models

2009 ◽  
Vol 18 (4) ◽  
pp. 369 ◽  
Author(s):  
Andrew L. Sullivan
Keyword(s):  
Statistical Analysis ◽  
Wind Speed ◽  
Physical Nature ◽  
Simulation Models ◽  
Fire Spread ◽  
Empirical Models ◽  
Fuel Moisture ◽  
Computational Power ◽  
Surface Fire ◽  
Fuel Moisture Content

In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across landscape. The present series of articles endeavours to comprehensively survey and précis all types of surface fire spread models developed during the period 1990–2007. The current paper surveys models of an empirical or quasi-empirical nature. These models are based on the statistical analysis of experimentally obtained data with or without some physical framework for the basis of the relations. Other papers in the series review models of a physical or quasi-physical nature, and mathematical analogues and simulation models. The main relations of empirical models are those of wind speed and fuel moisture content with rate of forward spread. The focus of the discussion is on the treatment of the wind speed and fuel moisture functions by the models.

scholarly journals Wildland surface fire spread modelling, 1990 - 2007. 3: Simulation and mathematical analogue models

2009 ◽  
Vol 18 (4) ◽  
pp. 387 ◽  
Author(s):  
Andrew L. Sullivan
Keyword(s):  
Physical Nature ◽  
Simulation Models ◽  
Mathematical Concept ◽  
Fire Spread ◽  
Two Dimensions ◽  
Computational Power ◽  
Surface Fire ◽  
One Dimensional ◽  
Analogue Models ◽  
Physical Representation

In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across landscape. The present series of articles endeavours to comprehensively survey and précis all types of surface fire spread models developed during the period 1990–2007. The present paper surveys models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one-dimensional models to two dimensions and then simulate the propagation of a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical concept (rather than a physical representation of fire spread) that coincidentally represents the spread of fire. Other papers in the series survey models of a physical or quasi-physical nature, and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.

RATES OF SURFACE FIRE SPREAD IN A YOUNG CALABRIAN PINE (Pinus brutia Ten.) PLANTATION

2012 ◽  
Vol 11 (8) ◽  
pp. 1475-1480 ◽  
Author(s):  
Omer Kucuk ◽  
Ertugrul Bilgili ◽  
Serkan Bulut ◽  
Paulo M. Fernandes
Keyword(s):  
Fire Spread ◽  
Surface Fire ◽  
Pinus Brutia ◽  
Calabrian Pine

scholarly journals Guidelines to Calibrate a Multi-Residential Building Simulation Model Addressing Overheating Evaluation and Residents’ Influence

Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 242
Author(s):  
Christoph Schünemann ◽  
David Schiela ◽  
Regine Ortlepp
Keyword(s):  
Simulation Model ◽  
Time Window ◽  
Residential Building ◽  
Simulation Models ◽  
Building Simulation ◽  
Night Time ◽  
Building Performance Simulation ◽  
Starting Point ◽  
3D Simulation Model ◽  
Building Physics

Can building performance simulation reproduce measured summertime indoor conditions of a multi-residential building in good conformity? This question is answered by calibrating simulated to monitored room temperatures of several rooms of a multi-residential building for an entire summer in two process steps. First, we did a calibration for several days without the residents being present to validate the building physics of the 3D simulation model. Second, the simulations were calibrated for the entire summer period, including the residents’ impact on evolving room temperature and overheating. As a result, a high degree of conformity between simulation and measurement could be achieved for all monitored rooms. The credibility of our results was secured by a detailed sensitivity analysis under varying meteorological conditions, shading situations, and window ventilation or room use in the simulation model. For top floor dwellings, a high overheating intensity was evoked by a combination of insufficient use of night-time window ventilation and non-heat-adapted residential behavior in combination with high solar gains and low heat storage capacities. Finally, the overall findings were merged into a process guideline to describe how a step-by-step calibration of residential building simulation models can be done. This guideline is intended to be a starting point for future discussions about the validity of the simplified boundary conditions which are often used in present-day standard overheating assessment.

The simulation of surface fire spread based on Rothermel model in windthrow area of Changbai Mountain (Jilin, China)

2018 ◽  
Author(s):  
Hang Yin ◽  
Hui Jin ◽  
Ying Zhao ◽  
Yuguang Fan ◽  
Liwu Qin ◽  
...  
Keyword(s):  
Fire Spread ◽  
Changbai Mountain ◽  
Surface Fire

scholarly journals ABWiSE v1.0: Toward and Agent-Based Approach to Simulating Wildfire Spread

2021 ◽  
Author(s):  
Jeffrey Katan ◽  
Liliana Perez
Keyword(s):  
Human Life ◽  
Simulation Models ◽  
Empirical Models ◽  
Physical Models ◽  
Fire Behaviour ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Fire Front ◽  
Wildfire Simulation ◽  
Behaviour Simulation

Abstract. Wildfires are a complex phenomenon emerging from interactions between air, heat, and vegetation, and while they are an important component of many ecosystems’ dynamics, they pose great danger to those ecosystems, and human life and property. Wildfire simulation models are an important research tool that help further our understanding of fire behaviour and can allow experimentation without recourse to live fires. Current fire simulation models fit into two general categories: empirical models and physical models. We present a new modelling approach that uses agent-based modelling to combine the complexity found in physical models with the ease of computation of empirical models. Our model represents the fire front as a set of moving agents that respond to, and interact with, vegetation, wind, and terrain. We calibrate the model using two simulated fires and one real fire, and validate the model against another real fire and the interim behaviour of the real calibration fire. Our model successfully replicates these fires, with a Figure of Merit on par with simulations by the Prometheus simulation model. Our model is a stepping-stone in using agent-based modelling for fire behaviour simulation, as we demonstrate the ability of agent-based modelling to replicate fire behaviour through emergence alone.

scholarly journals A Novel Framework for Anomaly Detection for Satellite Momentum Wheel Based on Optimized SVM and Huffman-Multi-Scale Entropy

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1062
Author(s):  
Yuqing Li ◽  
Mingjia Lei ◽  
Pengpeng Liu ◽  
Rixin Wang ◽  
Minqiang Xu
Keyword(s):  
Anomaly Detection ◽  
Detection Rate ◽  
Recognition Accuracy ◽  
Simulation Models ◽  
Physical Models ◽  
Telemetry Data ◽  
Data Types ◽  
Multi Scale ◽  
Svm Model ◽  
The Time Domain

The health status of the momentum wheel is vital for a satellite. Recently, research on anomaly detection for satellites has become more and more extensive. Previous research mostly required simulation models for key components. However, the physical models are difficult to construct, and the simulation data does not match the telemetry data in engineering applications. To overcome the above problem, this paper proposes a new anomaly detection framework based on real telemetry data. First, the time-domain and frequency-domain features of the preprocessed telemetry signal are calculated, and the effective features are selected through evaluation. Second, a new Huffman-multi-scale entropy (HMSE) system is proposed, which can effectively improve the discrimination between different data types. Third, this paper adopts a multi-class SVM model based on the directed acyclic graph (DAG) principle and proposes an improved adaptive particle swarm optimization (APSO) method to train the SVM model. The proposed method is applied to anomaly detection for satellite momentum wheel voltage telemetry data. The recognition accuracy and detection rate of the method proposed in this paper can reach 99.60% and 99.87%. Compared with other methods, the proposed method can effectively improve the recognition accuracy and detection rate, and it can also effectively reduce the false alarm rate and the missed alarm rate.

Mantras of wildland fire behaviour modelling: facts or fallacies?

2017 ◽  
Vol 26 (11) ◽  
pp. 973 ◽  
Author(s):  
Miguel G. Cruz ◽  
Martin E. Alexander ◽  
Andrew L. Sullivan
Keyword(s):  
Wildland Fire ◽  
Original Data ◽  
Fire Spread ◽  
Empirical Models ◽  
Physical Models ◽  
Fire Behaviour ◽  
Fire Science ◽  
Current State ◽  
Valid Data ◽  
Insight Into

Generalised statements about the state of fire science are often used to provide a simplified context for new work. This paper explores the validity of five frequently repeated statements regarding empirical and physical models for predicting wildland fire behaviour. For empirical models, these include statements that they: (1) work well over the range of their original data; and (2) are not appropriate for and should not be applied to conditions outside the range of the original data. For physical models, common statements include that they: (3) provide insight into the mechanisms that drive wildland fire spread and other aspects of fire behaviour; (4) give a better understanding of how fuel treatments modify fire behaviour; and (5) can be used to derive simplified models to predict fire behaviour operationally. The first statement was judged to be true only under certain conditions, whereas the second was shown not to be necessarily correct if valid data and appropriate modelling forms are used. Statements three through five, although theoretically valid, were considered not to be true given the current state of knowledge regarding fundamental wildland fire processes.

Re-inventing model-based decision support with Australian dryland farmers. 1. Changing intervention concepts during 17 years of action research

2009 ◽  
Vol 60 (11) ◽  
pp. 1017 ◽  
Author(s):  
R. L. McCown ◽  
P. S. Carberry ◽  
Z. Hochman ◽  
N. P. Dalgliesh ◽  
M. A. Foale
Keyword(s):  
Decision Support ◽  
Systems Thinking ◽  
Management Practice ◽  
Simulation Models ◽  
Third Party ◽  
Support Intervention ◽  
Decision Support Intervention ◽  
Systems Research ◽  
Local Soil ◽  
Starting Point

The idea that simulation models of agricultural production can serve as tools for farmers remains a compelling idea even after 3 decades of mostly disappointing development efforts. This paper is the first in a series that reports on 17 years of systems research that used models differently from the Decision Support System idea that has dominated the field. The starting point of FARMSCAPE (Farmers’, Advisers’, Researchers’, Monitoring, Simulation, Communication And Performance Evaluation) was finding whether farmers could value simulation when conditions for appreciation were improved by (a) specifying the simulator for individual paddocks in question and (b) delivering customised simulation to decision makers as a supporting service rather than software as a decision support product. The first aim of the program has been to learn how to effectively intervene in farm management practice using complex, abstract models of croplands, specified with local soil, climate, and management data. The second aim has been to learn how a resulting service that farmers value can be delivered cost effectively by a third party. This first paper deals with an aspect of the first aim, i.e. valued decision support intervention. In the terms used by Checkland (1981), the activities that served this systems practice aim were guided by ‘what we thought we were doing’ in intervening in farmers’ practice, i.e. our systems thinking. This first paper concerns FARMSCAPE systems thinking and how it evolved over 17 years as we learned successively through discovery of a new concept or representation in the literature to overcome limitations of the then-current conceptual framework. Subsequent papers deal with customising scientific monitoring and simulation for farmers, communication as engagement in situations of practice, understanding decision support intervention as facilitation of personal knowledge construction, and piloting commercial delivery of a simulation-based service to farmers and their advisers.

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