scholarly journals Detecting critical nodes in forest landscape networks to reduce wildfire spread

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258060
Author(s):  
Denys Yemshanov ◽  
Ning Liu ◽  
Daniel K. Thompson ◽  
Marc-André Parisien ◽  
Quinn E. Barber ◽  
...  
Keyword(s):  
Cost Effective ◽  
Problem Formulation ◽  
Fire Spread ◽  
Economic Damage ◽  
Optimization Approach ◽  
Prescribed Burn ◽  
Fuel Treatments ◽  
Forest Sites ◽  
Wildfire Spread ◽  
Park Area

Although wildfires are an important ecological process in forested regions worldwide, they can cause significant economic damage and frequently create widespread health impacts. We propose a network optimization approach to plan wildfire fuel treatments that minimize the risk of fire spread in forested landscapes under an upper bound for total treated area. We used simulation modeling to estimate the probability of fire spread between pairs of forest sites and formulated a modified Critical Node Detection (CND) model that uses these estimated probabilities to find a pattern of fuel reduction treatments that minimizes the likely spread of fires across a landscape. We also present a problem formulation that includes control of the size and spatial contiguity of fuel treatments. We demonstrate the approach with a case study in Kootenay National Park, British Columbia, Canada, where we investigated prescribed burn options for reducing the risk of wildfire spread in the park area. Our results provide new insights into cost-effective planning to mitigate wildfire risk in forest landscapes. The approach should be applicable to other ecosystems with frequent wildfires.

scholarly journals Toward Decentralised Sanitary Sewage Collection Systems: A Multiobjective Approach for Cost-Effective and Resilient Designs

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1886
Author(s):  
Arezoo Zahediasl ◽  
Amin E. Bakhshipour ◽  
Ulrich Dittmer ◽  
Ali Haghighi
Keyword(s):  
Treatment Plant ◽  
Drainage System ◽  
Cost Effective ◽  
Optimization Approach ◽  
Hydraulic Design ◽  
Multiobjective Approach ◽  
Layout Generation ◽  
Plant Allocation ◽  
Problem Solving Process

In recent years, the concept of a centralized drainage system that connect an entire city to one single treatment plant is increasingly being questioned in terms of the costs, reliability, and environmental impacts. This study introduces an optimization approach based on decentralization in order to develop a cost-effective and sustainable sewage collection system. For this purpose, a new algorithm based on the growing spanning tree algorithm is developed for decentralized layout generation and treatment plant allocation. The trade-off between construction and operation costs, resilience, and the degree of centralization is a multiobjective problem that consists of two subproblems: the layout of the networks and the hydraulic design. The innovative characteristics of the proposed framework are that layout and hydraulic designs are solved simultaneously, three objectives are optimized together, and the entire problem solving process is self-adaptive. The model is then applied to a real case study. The results show that finding an optimum degree of centralization could reduce not only the network’s costs by 17.3%, but could also increase its structural resilience significantly compared to fully centralized networks.

Prescribed Burning for Stand Conversion in Budworm-killed Balsam Fir: An Ontario Case History

1986 ◽  
Vol 62 (2) ◽  
pp. 96-100 ◽  
Author(s):  
D. J. McRae
Keyword(s):  
Fuel Consumption ◽  
Prescribed Burning ◽  
Choristoneura Fumiferana ◽  
Abies Balsamea ◽  
Spruce Budworm ◽  
Fire Spread ◽  
Fire Effects ◽  
Balsam Fir ◽  
Prescribed Burn ◽  
Stand Conversion

Recent spruce budworm (Choristoneura fumiferana [Clem.]) infestations have resulted in widespread areas of balsam fir (Abies balsamea [L.] Mill.) mortality in Ontario, and there is growing interest in reestablishing these areas quickly as productive forests. One technique being used is prescribed fire after a salvage and bulldozer tramping operation. A 445-ha prescribed burn was carried out under moderate fire danger conditions in northern Ontario. The site, which was covered by balsam fir fuel that had been killed by spruce budworm, was tramped to improve fire spread. Weather, fuel consumption, and fire effects are reported. The burn effectively reduced heavy surface fuel loadings and consequently planting on the site was easier. Key words: Prescribed burning, fire, spruce budworm. Choristoneura fumiferana, balsam fir, Abies balsamea, fuel consumption, site preparation, tramping, stand conversion.

Characterisation of the fuel and fire environment in southern Ontario’s tallgrass prairie

2015 ◽  
Vol 24 (8) ◽  
pp. 1118 ◽  
Author(s):  
Susan Kidnie ◽  
B. Mike Wotton
Keyword(s):  
Moisture Content ◽  
Tallgrass Prairie ◽  
Prescribed Burning ◽  
Fire Spread ◽  
Fuel Load ◽  
Prairie Restoration ◽  
Prescribed Burn ◽  
Spread Rate ◽  
Prescribed Burns ◽  
Tallgrass Prairie Restoration

Prescribed burning can be an integral part of tallgrass prairie restoration and management. Understanding fire behaviour in this fuel is critical to conducting safe and effective prescribed burns. Our goal was to quantify important physical characteristics of southern Ontario’s tallgrass fuel complex prior to and during prescribed burns and synthesise our findings into useful applications for the prescribed fire community. We found that the average fuel load in tallgrass communities was 0.70 kg m–2. Fuel loads varied from 0.38 to 0.96 kg m–2. Average heat of combustion did not vary by species and was 17 334 kJ kg–1. A moisture content model was developed for fully cured, matted field grass, which was found to successfully predict moisture content of the surface layers of cured tallgrass in spring. We observed 25 head fires in spring-season prescribed burns with spread rates ranging from 4 to 55 m min–1. Flame front residence time averaged 27 s, varying significantly with fuel load but not fire spread rate. A grassland spread rate model from Australia showed the closest agreement with observed spread rates. These results provide prescribed-burn practitioners in Ontario better information to plan and deliver successful burns.

Fine-Scale Fire Spread in Pine Straw

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 69
Author(s):  
Daryn Sagel ◽  
Kevin Speer ◽  
Scott Pokswinski ◽  
Bryan Quaife
Keyword(s):  
Fire Spread ◽  
Small Scale ◽  
Natural Setting ◽  
Fine Scale ◽  
Prescribed Burn ◽  
Fire Dynamics ◽  
Rate Of Spread ◽  
Scale Models ◽  
Fire Front ◽  
Visible Images

Most wildland and prescribed fire spread occurs through ground fuels, and the rate of spread (RoS) in such environments is often summarized with empirical models that assume uniform environmental conditions and produce a unique RoS. On the other hand, representing the effects of local, small-scale variations of fuel and wind experienced in the field is challenging and, for landscape-scale models, impractical. Moreover, the level of uncertainty associated with characterizing RoS and flame dynamics in the presence of turbulent flow demonstrates the need for further understanding of fire dynamics at small scales in realistic settings. This work describes adapted computer vision techniques used to form fine-scale measurements of the spatially and temporally varying RoS in a natural setting. These algorithms are applied to infrared and visible images of a small-scale prescribed burn of a quasi-homogeneous pine needle bed under stationary wind conditions. A large number of distinct fire front displacements are then used statistically to analyze the fire spread. We find that the fine-scale forward RoS is characterized by an exponential distribution, suggesting a model for fire spread as a random process at this scale.

scholarly journals A delayed differentiation multiproduct model with the outsourcing of common parts, overtime strategy for end products, and quality reassurance

2021 ◽  
pp. 143-158 ◽  
Author(s):  
Singa Wang Chiu ◽  
Victoria Chiu ◽  
Ming-Hon Hwang ◽  
Yuan-Shyi Peter Chiu
Keyword(s):  
Cost Effective ◽  
Sensitivity Analyses ◽  
Optimization Approach ◽  
Limited Capacity ◽  
Numerical Illustration ◽  
Delayed Differentiation ◽  
Modeling Analysis ◽  
End Products ◽  
Effective Decision ◽  
Effective Decision Making

Production planners today must simultaneously face with the time and quality demands of various goods externally and meet limited capacity internally. This study presents a two-stage delayed- differentiation multiproduct model that considers the outsourcing options for common parts, overtime strategy for end products, and quality reassurance to assist in making fabrication runtime decisions that are cost-effective. Stage one produces all necessary common intermediate components for end products. To reduce stage one’s utilization/uptime, this study adopts a partial outsourcing option. Stage two uses an overtime strategy to fabricate end products that further shorten the uptime. The production processes in both phases are assumed to be imperfect. This study employs the reworking/scrapping of random faulty items to reassure product quality. The researchers build a model to depict the proposed problem’s characteristics and used the mathematical modeling, analysis, and optimization approach to determine the best rotation cycle length that minimizes the system’s expenses. Further, in this study, the researchers provide sensitivity analyses and a numerical illustration, which validate the result’s applicability and exhibit its capability. This result contributes to practical multiproduct-fabrication by (1) deriving the optimal manufacturing policy for a delayed-differentiation multiproduct system with dual uptime reduction policies and quality reassurance; and (2) offering a decisional model that allows production planners to explore the collective/separate effect of a quality-ensured and dual uptime reduction strategy on a problem’s operating policy and crucial system performance indicators, which assists in cost-effective decision-making.

Design and Analysis of Automotive Bumper Covers in Transient Loading Conditions

2016 ◽  
Vol 715 ◽  
pp. 174-179 ◽  
Author(s):  
Chih Hsing Liu ◽  
Ying Chia Huang ◽  
Chen Hua Chiu ◽  
Yu Cheng Lai ◽  
Tzu Yang Pai
Keyword(s):  
Optimal Design ◽  
Numerical Model ◽  
Design Method ◽  
Experimental Tests ◽  
Cost Effective ◽  
Limited Range ◽  
Optimization Approach ◽  
Loading Conditions ◽  
Element Analysis ◽  
Design Guideline

This paper presents the analysis methods for design of automotive bumper covers. The bumper covers are plastic structures attached to the front and rear ends of an automobile and are expected to absorb energy in a minor collision. One requirement in design of the bumper covers is to minimize the bumper deflection within a limited range under specific loadings at specific locations based on the design guideline. To investigate the stiffness performance under various loading conditions, a numerical model based on the explicit dynamic finite element analysis (FEA) using the commercial FEA solver, LS-DYNA, is developed to analyze the design. The experimental tests are also carried out to verify the numerical model. The thickness of the bumper cover is a design variable which usually varies from 3 to 4 mm depending on locations. To improve the stiffness of the bumper, an optimal design for the bumper under a pre-defined loading condition is identified by using the topology optimization approach, which is an optimal design method to obtain the optimal layout of an initial design domain under specific boundary conditions. The outcome of this study provides an efficient and cost-effective method to predict and improve the design of automotive bumper covers.

scholarly journals Economic aspects of management and planning of waste processing system development

2019 ◽  
Vol 110 ◽  
pp. 02079
Author(s):  
Edvard Tshovrebov ◽  
Evgeniy Velichko ◽  
Ural Niyazgulov ◽  
Yuliya Sadchikova
Keyword(s):  
System Development ◽  
Processing System ◽  
Cost Effective ◽  
Environmental Safety ◽  
Economic Incentives ◽  
Economic Damage ◽  
Environmental Damage ◽  
Natural Ecosystems ◽  
Technological Infrastructure ◽  
Production And Consumption

Annually, increasing volumes of industrial and municipal waste generation and disposal, leading to increasing anthropogenic environmental and sanitary-epidemiological pressure on the environment and, as a consequence, significant environmental damage and associated economic damage to natural ecosystems, represent one of the main threats to environmental safety territories, life and health of the population. At the same time, numerous valuable components extracted from processed production and consumption wastes can be an important source of reserve for the development of industries and sectors of the economy, entrepreneurial activities in the use of secondary resources for production, services, works and energy. This factor dictates the need to search for new sound management, economic, organizational and technical approaches and solutions to lawmaking, planning and forecasting the cost-effective organization of the system of separate collection, processing, disposal, disposal of production and consumption waste, the development of an appropriate industrial, scientific and technological infrastructure, increasing the share of secondary material and energy resources extracted from waste, the development of instruments of state oh support and economic incentives for this activity.

scholarly journals Unsupervised Parameterization for Optimal Segmentation of Agricultural Parcels from Satellite Images in Different Agricultural Landscapes

2020 ◽  
Vol 12 (18) ◽  
pp. 3096
Author(s):  
Gideon Okpoti Tetteh ◽  
Alexander Gocht ◽  
Marcel Schwieder ◽  
Stefan Erasmi ◽  
Christopher Conrad
Keyword(s):  
Evaluation System ◽  
Reference Data ◽  
Cost Effective ◽  
Agricultural Landscapes ◽  
Bayesian Optimization ◽  
Absolute Difference ◽  
Optimization Approach ◽  
Lower Saxony ◽  
Optimal Segmentation ◽  
Unsupervised Methods

Image segmentation is a cost-effective way to obtain information about the sizes and structural composition of agricultural parcels in an area. To accurately obtain such information, the parameters of the segmentation algorithm ought to be optimized using supervised or unsupervised methods. The difficulty in obtaining reference data makes unsupervised methods indispensable. In this study, we evaluated an existing unsupervised evaluation metric that minimizes a global score (GS), which is computed by summing up the intra-segment uniformity and inter-segment dissimilarity within a segmentation output. We modified this metric and proposed a new metric that uses absolute difference to compute the GS. We compared this proposed metric with the existing metric in two optimization approaches based on the Multiresolution Segmentation (MRS) algorithm to optimally delineate agricultural parcels from Sentinel-2 images in Lower Saxony, Germany. The first approach searches for optimal scale while keeping shape and compactness constant, while the second approach uses Bayesian optimization to optimize the three main parameters of the MRS algorithm. Based on a reference data of agricultural parcels, the optimal segmentation result of each optimization approach was evaluated by calculating the quality rate, over-segmentation, and under-segmentation. For both approaches, our proposed metric outperformed the existing metric in different agricultural landscapes. The proposed metric identified optimal segmentations that were less under-segmented compared to the existing metric. A comparison of the optimal segmentation results obtained in this study to existing benchmark results generated via supervised optimization showed that the unsupervised Bayesian optimization approach based on our proposed metric can potentially be used as an alternative to supervised optimization, particularly in geographic regions where reference data is unavailable or an automated evaluation system is sought.

Corrigendum to: Prioritising fuels reduction for water supply protection

2020 ◽  
Vol 29 (11) ◽  
pp. 1054
Author(s):  
Benjamin M. Gannon ◽  
Yu Wei ◽  
Lee H. MacDonald ◽  
Stephanie K. Kampf ◽  
Kelly W. Jones ◽  
...  
Keyword(s):  
Water Supply ◽  
Risk Mitigation ◽  
Cost Savings ◽  
Cost Effective ◽  
Fuel Treatments ◽  
Water Supplies ◽  
Fuel Treatment ◽  
Fuels Reduction ◽  
Forest Fuels ◽  
Multiple Resources

Concerns over wildfire impacts to water supplies have motivated efforts to mitigate risk by reducing forest fuels. Methods to assess fuel treatment effects and prioritise their placement are needed to guide risk mitigation efforts. We present a fuel treatment optimisation model to minimise risk to multiple water supplies based on constraints for treatment feasibility and cost. Risk is quantified as the expected sediment impact costs to water supplies by combining measures of fire likelihood and behaviour, erosion, sediment transport and water supply vulnerability. We demonstrate the model's utility for prioritising fuel treatments in two large watersheds in Colorado, USA, that are critical for municipal water supply. Our results indicate that wildfire risk to water supplies can be substantially reduced by treating a small portion of the watersheds that have dense, fire-prone forests on steep slopes that drain to water supply infrastructure. Our results also show that the cost of fuel treatments outweighs the expected cost savings from reduced sediment inputs owing to the low probability of fuel treatments encountering wildfire and the high cost of thinning forests. This highlights the need to expand use of more cost-effective treatments, like prescribed fire, and to identify fuel treatment projects that benefit multiple resources.

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