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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Investigating Resiliency of Transportation Network under Targeted and Potential Climate Change Disruptions

Ensuring robustness and resilience in intermodal transportation systems is essential for the continuity and reliability of global logistics. These systems are vulnerable to various disruptions, including natural disasters and technical failures. Despite significant research on freight transportation resilience, investigating the robustness of the system after targeted and climate-change-driven disruption remains a crucial challenge. Drawing on network science methodologies, this study models the interdependencies within the rail and water transport networks and simulates different disruption scenarios to evaluate system responses. Here, we use the data from the U.S. Department of Energy Volpe Center for network topology and tonnage projections. The proposed framework quantifies deliberate, stochastic, and climate-driven infrastructure failure, using higher resolution downscaled multiple Earth System Models’ simulations from Coupled Model Intercomparison Project Phase version 6. We show that the disruptions of a few nodes could have a larger impact on the total tonnage of freight transport than on network topology. For example, the removal of targeted 20 nodes can bring the total tonnage carrying capacity to 30% with about 75% of the rail freight network intact. This research advances the theoretical understanding of transportation resilience and provides practical applications for infrastructure managers and policymakers. By implementing these strategies, stakeholders and policymakers can better prepare for and respond to unexpected disruptions, ensuring sustained operational efficiency in transportation networks.

Climate Change Disruptions↗
DOE OSTI2026

Using Machine Learning to Understand Electric and Hybrid Vehicles Ownership in Burdened and Nonburdened Communities

Transitioning to electric and hybrid vehicles (EHVs) for all communities is a pivotal step toward sustainable transportation and environmental conservation. This paper aims to understand the adoption of EHVs, focusing on burdened communities (BCs) in the United States. The EHV ownership-based analysis combines two datasets—behavioral data from the Puget Sound Regional Travel Survey integrated with BCs (Justice40) data covering transportation insecurity, environmental burden, social vulnerability, health vulnerability, and climate and disaster risk burden. After creating this unique database, descriptive analysis and modeling are used to analyze the data and predict EHV ownership in the future. Specifically, we use a new method that combines particle swarm optimization (PSO) with a stacking model named PSO-Stacking, which incorporates heterogeneous base learners of machine learning and deep learning. PSO applies a customized objective function to select the optimal hyperparameters for heterogeneous learners within the stacking model, effectively addressing challenges such as multicollinearity, data imbalance, nonlinearity, and overfitting. The proposed solution covers more accurate results than standard benchmark models for EHV ownership in BCs and non-BCs. In addition, the results of the PSO-Stacking method are explained using the local interpretable model-agnostic explanations technique. Results show a negative correlation between the BCs indicators, that is, higher transportation insecurity associated with lower EHV ownership. Furthermore, BCs have higher future climate risk scores, diesel particulate matter levels, and PM2.5 in the air than non-BCs because of higher conventional vehicle ownership. These communities are at higher risk and can benefit from electrification, EV infrastructure, and EV policies to address environmental challenges.

Aslam, Zeeshan [ORNL]↗
DOE OSTI2025

An open-access simulated earthquake ground-motion database for an M7 Hayward Fault earthquake in the San Francisco Bay Region

Comprehensive understanding of earthquake ground motions, particularly in the near-fault region of large-magnitude events, is limited by gaps in strong-motion data. This challenge is prominent in areas with high seismic hazard but infrequent large earthquakes where data is sparse and difficult to interpret. These data limitations lead to uncertainties in the development of site-specific ground motions, which are crucial for engineering risk assessments. To address these challenges, physics-based regional-scale ground-motion simulations have been developed. With the emergence of exaflop-scale computing ecosystems, it is now possible to simulate regional earthquake processes at unprecedented fidelity and generate the large number of fault rupture realizations necessary to characterize both intra- and inter-event ground-motion variability. This article introduces a new database of simulated earthquake ground motions, created for applications in earthquake engineering, earthquake planning, and emergency response. The inaugural version of the database features simulated ground motions for a magnitude 7 Hayward Fault earthquake in the San Francisco Bay Region (SFBR), using the EarthQuake SIMulation (EQSIM) simulation framework and the Graves–Pitarka kinematic rupture model. The aim is to provide high-fidelity, spatially dense, three-component motions generated on the Department of Energy’s (DOE) newest generation of graphics processing unit (GPU)-accelerated supercomputers. These motions are being made openly available to the engineering, scientific, and disaster planning communities. In addition, this work develops protocols for the efficient dissemination of these large data sets and emphasizes community engagement to build confidence in their application. This article discusses the methodology behind the data, underlying software verification and validation, scalable data management, and a user interface for data access. The goal is to facilitate widespread use and elicit expert feedback to maximize the utility and exploitation of simulated motions. While the initial focus is on the San Francisco Region, simulations for additional regions will be added as the DOE program progresses.

Simulated ground-motion database↗
DOE OSTI2025

Risk of longer-term endocrine and metabolic conditions in the Deepwater Horizon Oil Spill Coast Guard cohort study – five years of follow-up

Abstract Introduction Long-term endocrine and metabolic health risks associated with oil spill cleanup exposures are largely unknown, despite the endocrine-disrupting potential of crude oil and oil dispersant constituents. We aimed to investigate risks of longer-term endocrine and metabolic conditions among U.S. Coast Guard (USCG) responders to the Deepwater Horizon (DWH) oil spill. Methods Our study population included all active duty DWH Oil Spill Coast Guard Cohort members ( N = 45,224). Self-reported spill exposures were ascertained from post-deployment surveys. Incident endocrine and metabolic outcomes were defined using International Classification of Diseases (9th Revision) diagnostic codes from military health encounter records up to 5.5 years post-DWH. Using Cox proportional hazards regression, we estimated adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) for various incident endocrine and metabolic diagnoses (2010–2015, and separately during 2010–2012 and 2013–2015). Results The mean baseline age was 30 years (~ 77% white, ~ 86% male). Compared to non-responders ( n = 39,260), spill responders ( n = 5,964) had elevated risks for simple and unspecified goiter (aHR = 2.09, 95% CI: 1.29–3.38) and disorders of lipid metabolism (aHR = 1.09, 95% CI: 1.00–1.18), including its subcategory other and unspecified hyperlipidemia (aHR = 1.10, 95% CI: 1.01–1.21). The dysmetabolic syndrome X risk was elevated only during 2010–2012 (aHR = 2.07, 95% CI: 1.22–3.51). Responders reporting ever ( n = 1,068) vs. never ( n = 2,424) crude oil inhalation exposure had elevated risks for disorders of lipid metabolism (aHR = 1.24, 95% CI: 1.00–1.53), including its subcategory pure hypercholesterolemia (aHR = 1.71, 95% CI: 1.08–2.72), the overweight, obesity and other hyperalimentation subcategory of unspecified obesity (aHR = 1.52, 95% CI: 1.09–2.13), and abnormal weight gain (aHR = 2.60, 95% CI: 1.04–6.55). Risk estimates for endocrine/metabolic conditions were generally stronger among responders reporting exposure to both crude oil and dispersants (vs. neither) than among responders reporting only oil exposure (vs. neither). Conclusion In this large cohort of active duty USCG responders to the DWH disaster, oil spill cleanup exposures were associated with elevated risks for longer-term endocrine and metabolic conditions.

Denic-Roberts, Hristina↗
DOE OSTI2022

A deformation-dependent coupled Lagrangian/semi-Lagrangian meshfree hydromechanical formulation for landslide modeling

Abstract The numerical modelling of natural disasters such as landslides presents several challenges for conventional mesh-based methods such as the finite element method (FEM) due to the presence of numerically challenging phenomena such as severe material deformation and fragmentation. In contrast, meshfree methods such as the reproducing kernel particle method (RKPM) possess unique features conducive to modelling extreme events such as the absence of a structured mesh and the ease of adaptive refinement, among others. While the semi-Lagrangian reproducing kernel (SL-RK) shape functions of RKPM defined in the current configuration have proven to be effective in extreme event modelling, the computational cost for the re-evaluation of the shape functions at every time step is costly. In this work, a deformation-dependent coupling of the Lagrangian reproducing kernel (L-RK) and SL-RK approximations is proposed for the solution of a hydro-mechanical formulation for effective simulations of landslides. The ramp function is constructed based on an equivalent plastic strain as a deformation-dependent transition from L-RK shape functions to SL-RK ones as the deformation progresses. The particular focus of the paper will be on modelling seepage-induced landslides with a mixed $$u$$ u – $$p$$ p formulation to couple the solid and fluid phases. Examples are presented to examine the effectiveness of this coupled Lagrangian/semi-Lagrangian reproducing kernel (L–SL RK) formulation and to highlight its performance in landslide modelling.

Baek, Jonghyuk↗
DOE OSTI2023

Providing Geospatial Intelligence through a Scalable Imagery Pipeline

This chapter describes ORNL’s (Oak Ridge National Laboratory’s) contributions to imagery preprocessing for geospatial intelligence research and development (R&D) in four sections. First, we discuss challenges involved in building an effective imagery preprocessing workflow and the world-class high-performance computing (HPC) resources at ORNL available to process petabytes of imagery data. Second, we highlight how we developed imagery preprocessing tools over three decades while paving the way for our current cutting-edge machine learning and computer vision algorithms that are impacting humanitarian and disaster response efforts. Third, we discuss how PIPE modules work together to turn raw images into analysis-ready datasets. Fourth, we look toward the future and discuss planned advancements to PIPE and computing trends that will affect geospatial intelligence R&D.

Reith, Andrew↗
DOE OSTI2023

Current UAS Capabilities for Geospatial Spectral Solutions

Unmanned aerial systems (UAS) are playing an increasingly pivotal role in advancing the remote collection of data. The various datasets collected by these cutting-edge systems provide near-real-time information and help inform end users on everything from disaster recovery efforts to monitoring atmospheric constituents. This chapter focuses on how the collection of imagery has progressed over time, including the pivotal role UAS play in building large-scale datasets driving data analysis. The authors report the findings of a 2018–2021 survey of the fields that use UAS, the UAS platforms most commonly used, and the sensor components users select to outfit their UAS. The chapter will also discuss the range of platforms currently available, with a specific focus on issues including battery life, data downlinks, data processing times, edge computing, and availability of new sensors. The authors will also discuss the future direction of UAS platforms as well as many of the problems associated with the high spatial and temporal resolution of modern geospatial datasets.

Cotten, David↗
DOE OSTI2024

Advancing stem cell technologies for conservation of wildlife biodiversity

ABSTRACT Wildlife biodiversity is essential for healthy, resilient and sustainable ecosystems. For biologists, this diversity also represents a treasure trove of genetic, molecular and developmental mechanisms that deepen our understanding of the origins and rules of life. However, the rapid decline in biodiversity reported recently foreshadows a potentially catastrophic collapse of many important ecosystems and the associated irreversible loss of many forms of life on our planet. Immediate action by conservationists of all stripes is required to avert this disaster. In this Spotlight, we draw together insights and proposals discussed at a recent workshop hosted by Revive & Restore, which gathered experts to discuss how stem cell technologies can support traditional conservation techniques and help protect animal biodiversity. We discuss reprogramming, in vitro gametogenesis, disease modelling and embryo modelling, and we highlight the prospects for leveraging stem cell technologies beyond mammalian species.

Developmental Biology↗
DOE OSTI2016

Using the sound of nuclear energy

The generation of sound by heat has been documented as an “acoustical curiosity” since a Buddhist monk reported the loud tone generated by a ceremonial rice-cooker in his diary, in 1568. Over the last four decades, significant progress has been made in understanding “thermoacoustic processes,” enabling the design of thermoacoustic engines and refrigerators. Motivated by the Fukushima nuclear reactor disaster, we have developed and tested a thermoacoustic engine that exploits the energy-rich conditions in the core of a nuclear reactor to provide core condition information to the operators without a need for external electrical power. The heat engine is self-powered and can wirelessly transmit the temperature and reactor power level by generation of a pure tone which can be detected outside the reactor. We report here the first use of a fission-powered thermoacoustic engine capable of serving as a performance and safety sensor in the core of a research reactor and present data from the hydrophones in the coolant (far from the core) and an accelerometer attached to a structure outside the reactor. These measurements confirmed that the frequency of the sound produced indicates the reactor’s coolant temperature and that the amplitude (above an onset threshold) is related to the reactor’s operating power level. Furthermore, these signals can be detected even in the presence of substantial background noise generated by the reactor’s fluid pumps.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Microbial cells can cooperate to resist high-level chronic ionizing radiation

Understanding chronic ionizing radiation (CIR) effects is of utmost importance to protecting human health and the environment. Diverse bacteria and fungi inhabiting extremely radioactive waste and disaster sites (e.g. Hanford, Chernobyl, Fukushima) represent new targets of CIR research. We show that many microorganisms can grow under intense gamma-CIR dose rates of 13–126 Gy/h, with fungi identified as a particularly CIR-resistant group of eukaryotes: among 145 phylogenetically diverse strains tested, 78 grew under 36 Gy/h. Importantly, we demonstrate that CIR resistance can depend on cell concentration and that certain resistant microbial cells protect their neighbors (not only conspecifics, but even radiosensitive species from a different phylum), from high-level CIR. We apply a mechanistically-motivated mathematical model of CIR effects, based on accumulation/removal kinetics of reactive oxygen species (ROS) and antioxidants, in bacteria (3 Escherichia coli strains and Deinococcus radiodurans) and in fungi (Candida parapsilosis, Kazachstania exigua, Pichia kudriavzevii, Rhodotorula lysinophila, Saccharomyces cerevisiae, and Trichosporon mucoides). We also show that correlations between responses to CIR and acute ionizing radiation (AIR) among studied microorganisms are weak. For example, in D. radiodurans, the best molecular correlate for CIR resistance is the antioxidant enzyme catalase, which is dispensable for AIR resistance; and numerous CIR-resistant fungi are not AIR-resistant. Our experimental findings and quantitative modeling thus demonstrate the importance of investigating CIR responses directly, rather than extrapolating from AIR. Protection of radiosensitive cell-types by radioresistant ones under high-level CIR is a potentially important new tool for bioremediation of radioactive sites and development of CIR-resistant microbiota as radioprotectors.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2014

Nuclear Arms Control, Nonproliferation, and Counterterrorism: Impacts on Public Health

Reducing the risks of nuclear war, limiting the spread of nuclear weapons and reducing global nuclear weapons stockpiles are key national and international security goals. They are pursued through a variety of international arms control, nonproliferation and counter-terrorism treaties and agreements. These legally binding and political commitments, together with the institutional infrastructure that supports them, work to establish global norms of behavior and have limited the spread of weapons of mass destruction. Beyond the primary security objectives, reducing the likelihood of the use of nuclear weapons, preventing environmental releases of radioactive material, increasing the availability of safe and secure nuclear technology for peaceful purposes, and providing scientific data relevant to predicting and managing the consequences of natural or human-caused disasters world-wide provide significant benefits to global public health.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2011

Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G} for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

A Human Factors Perspective on Alarm System Research and Development 2000 to 2010

By definition, alarms serve to notify human operators of out-of-parameter conditions that could threaten equipment, the environment, product quality and, of course, human life. Given the complexities of industrial systems, human machine interfaces, and the human operator, the understanding of how alarms and humans can best work together to prevent disaster is continually developing. This review examines advances in alarm research and development from 2000 to 2010 and includes the writings of trade professionals, engineering and human factors researchers, and standards organizations with the goal of documenting advances in alarms system design, research, and implementation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Developing an Operational Capabilities Index of the Emergency Services Sector

In order to enhance the resilience of the Nation and its ability to protect itself in the face of natural and human-caused hazards, the ability of the critical infrastructure (CI) system to withstand specific threats and return to normal operations after degradation must be determined. To fully analyze the resilience of a region and the CI that resides within it, both the actual resilience of the individual CI and the capability of the Emergency Services Sector (ESS) to protect against and respond to potential hazards need to be considered. Thus, a regional resilience approach requires the comprehensive consideration of all parts of the CI system as well as the characterization of emergency services. This characterization must generate reproducible results that can support decision making with regard to risk management, disaster response, business continuity, and community planning and management. To address these issues, Argonne National Laboratory, in collaboration with the U.S. Department of Homeland Security (DHS) Sector Specific Agency - Executive Management Office, developed a comprehensive methodology to create an Emergency Services Sector Capabilities Index (ESSCI). The ESSCI is a performance metric that ranges from 0 (low level of capabilities) to 100 (high). Because an emergency services program has a high ESSCI, however, does not mean that a specific event would not be able to affect a region or cause severe consequences. And because a program has a low ESSCI does not mean that a disruptive event would automatically lead to serious consequences in a region. Moreover, a score of 100 on the ESSCI is not the level of capability expected of emergency services programs; rather, it represents an optimal program that would rarely be observed. The ESSCI characterizes the state of preparedness of a jurisdiction in terms of emergency and risk management. Perhaps the index's primary benefit is that it can systematically capture, at a given point in time, the capabilities of a jurisdiction to protect itself from, mitigate, respond to, and recover from a potential incident. On the basis of this metric, an interactive tool - the ESSCI Dashboard - can identify scenarios for enhancement that can be implemented, and it can identify the repercussions of these scenarios on the jurisdiction. It can assess the capabilities of law enforcement, fire fighting, search and rescue, emergency medical services, hazardous materials response, dispatch/911, and emergency management services in a given jurisdiction and it can help guide those who need to prioritize what limited resources should be used to improve these capabilities. Furthermore, this tool can be used to compare the level of capabilities of various jurisdictions that have similar socioeconomic characteristics. It can thus help DHS define how it can support risk reduction and community preparedness at a national level. This tool aligns directly with Presidential Policy Directive 8 by giving a jurisdiction a metric of its ESS's capabilities and by promoting an interactive approach for defining options to improve preparedness and to effectively respond to a disruptive event. It can be used in combination with other CI performance metrics developed at Argonne National Laboratory, such as the vulnerability index and the resilience index for assessing regional resilience.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Our Next Two Steps for Fukushima Daiichi Muon Tomography

After the vast disasters caused by the great earthquake and tsunami in eastern Japan, we proposed applying our Muon Tomography (MT) technique to help and improve the emergency situation at Fukushima Daiichi using cosmic-ray muons. A reactor-tomography team was formed at LANL which was supported by the Laboratory as a response to a request by the former Japanese Prime Minister, Naoto Kan. Our goal is to help the Japanese people and support remediation of the reactors. At LANL, we have carried out a proof-of-principle technical demonstration and simulation studies that established the feasibility of MT to image a reactor core. This proposal covers the next two critical steps for Fukushima Daiichi Muon Imaging: (1) undertake case study mock-up experiments of Fukushima Daiichi, and (2) system optimization. We requested funding to the US and Japanese government to assess damage of reactors at Fukushima Daiichi. The two steps will bring our project to the 'ready-to-go' level.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Air Monitoring of Emissions from the Fukushima Daiichi Reactor

In response to the disasters in Japan on March 11, 2011, and the subsequent emissions from Fukushima-Daiichi, we monitored the air near Los Alamos using four air-monitoring systems: the standard AIRNET samplers, the standard rad-NESHAP samplers, the NEWNET system, and high-volume air samplers. Each of these systems has advantages and disadvantages. In combination, they provide a comprehensive set of measurements of airborne radionuclides near Los Alamos during the weeks following March 11. We report air-monitoring measurements of the fission products released from the Fukushima-Daiichi nuclear-power-plant accident in 2011. Clear gamma-spectrometry peaks were observed from Cs-134, Cs-136, Cs-137, I-131, I132, Te-132, and Te-129m. These data, together with measurements of other radionuclides, are adequate for an assessment and assure us that radionuclides from Fukushima Daiichi did not present a threat to human health at or near Los Alamos. The data demonstrate the capabilities of the Los Alamos air-monitoring systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Strategic Analysis of Complex Security Scenarios

Many advanced technical tools are available to prevent attacks on national infrastructure. Nevertheless, while traditional analyses of security problems have succeeded in producing good technical solutions, they have often ignored the human factor integral to these problems. Human attackers (who may be individuals or state-level attackers) expend substantial effort to breach security because they have the incentive for doing so. People involved in implementing security follow individual incentives, which need not align with global security concerns; consequently, desired security solutions are often implemented poorly, or not at all. This complex interplay between individual incentives and global (organizational and/or national) goals can be modeled and analyzed using game theoretic techniques. By analyzing not only what is possible, but also what is motivated, a holistic approach to security problems can be developed, informing policy and providing tools to policy makers. We study game theoretic models that unify several current incentive-based approaches to security, and develop simulation-based and mathematical optimization methods for analyzing such models that exploit the high-performance computing capabilities at Sandia. Our first model studies security in interdependent settings, offering a scalable local search heuristic to approximate optimal security decisions in general, and a linear programming approach, coupled with simulations of consequences, to optimally compute security in an important special case. Our second class of models addresses security patrolling problems when an adversary gets to observe the patrol location. We present a general framework, based on stochastic games, for computing optimal security policies in such settings, and present more scalable tools that apply in the important special cases. Our third contribution is a model of security that involves many defenders, but only models non-adaptive attackers (or natural disasters, inadvertent errors, etc). In this model, we demonstrate that the security decisions of many players result in global security configuration that is not very far from optimal, and is much more resilient to environment changes that an optimal solution. This positive effect dissipates, however, when the number of decision makers becomes too large.

Vorobeychik, Yevgeniy↗
DOE OSTI2012

WildFire Ignition Resistance Estimator (WildFIRE) Wizard Software Development Report

This report describes the development of a software tool, entitled “WildFire Ignition Resistance Estimator Wizard” (WildFIRE Wizard, Version 2.10). This software was developed within the Wildfire Ignition Resistant Home Design (WIRHD) program, sponsored by the U. S. Department of Homeland Security, Science and Technology Directorate, Infrastructure Protection & Disaster Management Division. WildFIRE Wizard is a tool that enables homeowners to take preventive actions that will reduce their home’s vulnerability to wildfire ignition sources (i.e., embers, radiant heat, and direct flame impingement) well in advance of a wildfire event. This report describes the development of the software, its operation, its technical basis and calculations, and steps taken to verify its performance.

97 MATHEMATICS AND COMPUTING↗