About

Michael Gollner is a Professor in the Department of Fire Protection Engineering at the University of Maryland, with a background in Mechanical Engineering from the University of California, San Diego, where he earned his B.S., M.S., and Ph.D. His doctoral thesis focused on studies of upward flame spread. Gollner's research interests include wildland and wildland-urban interface fires, fire dynamics, buoyancy-driven fluid dynamics, environmental sustainability, and combustion. He has contributed to the understanding of fire phenomena such as blue whirls and fire tornadoes, and has been involved in studies on fire spread, suppression, and safety. He has held various leadership roles, including serving on the Board of Directors of the International Association of Wildland Fire, the Research Advisory Board of the NFPA Fire Protection Research Foundation, and the NFPA Technical Committee on Wildland and Rural Fire Protection. Gollner is an active member of multiple editorial boards and has received numerous honors, including the Fire Protection Research Foundation Medal, the Proulx Early Career Award, and the NSF CAREER Award. His work has been recognized for its impact on fire science, wildfire modeling, and fire safety engineering, and he is known for his research on phenomena such as fire whirls and the spread of wildfires into communities.

Research topics

• Artificial Intelligence
• Computer Science
• Engineering
• Organic chemistry
• Biology
• Physics
• Geology
• Aerospace engineering
• Botany
• Materials science
• Meteorology
• Ecology
• Biological system
• Biochemical engineering
• Environmental science
• Chemistry
• Chemical engineering
• Geography
• Atmospheric sciences
• Composite material
• Geotechnical engineering

Selected publications

• Opposed flame spread limit over PMMA rods in normal and micro gravity

  Fire Safety Journal · 2026-03-18

  article
  PublisherDOI

• Using data categorization and augmentation strategies to improve machine learning frameworks for flame spread over electrical wires

  Journal of Loss Prevention in the Process Industries · 2026-05-01

  article
  PublisherDOI

• Wind-Driven Building-to-Building Fire Spread: Experimental Results and Probabilistic Modeling

  Fire Technology · 2026-01-28 · 4 citations

  articleOpen access

  This study presents a comprehensive experimental and probabilistic analysis of wind-driven building-to-building fire spread, focusing on the interplay between exposure intensity, duration, and material response. Twenty-three full-scale tests were conducted under varied wind speeds, separation distances, and material configurations to capture a spectrum of damage levels and move beyond the conventional binary outcomes of most fire experiments. As fire intensity builds, the target structure experiences increasing heat exposure, while collapse of the source structure during the growth phase disrupts flame dynamics and causes abrupt intensity drops. This deviation from the classic growth, steady, and decay pattern weakens the correlation between observed damage and traditional metrics such as peak heat flux or long-duration heat load. To address this, damage classifications from cosmetic to destroyed were mapped to statistical distributions of energy fluence accumulated over a characteristic intermediate timescale, better reflecting material response under realistic fire conditions. The resulting probabilistic framework supports risk-informed decisions aligned with the acceptable level of risk. At a separation of 10 ft (3 m), the tested building materials showed minimal likelihood of survival when exposed to fires from large, fully loaded sheds. By about 20 ft (6 m), the fire exposure decreases to a level where resilient building components have a fighting chance, and survival probabilities improve substantially at 30 ft (9 m). This framework provides a statistical view based on a physics-based interpretation of ignition thresholds to quantify intermediate damage and assess vulnerability under variable fire exposures, supporting fire-resilient community design and mitigation.

  PublisherDOI

• Sensitivity of ELMFIRE to real-world input datasets for WUI fire modeling

  Fire Safety Journal · 2026-02-09

  articleOpen accessSenior authorCorresponding

  Wildland–urban interface (WUI) fires pose significant threats to communities, and computational models are critical for their mitigation. These models depend strongly on input data, yet the impact of real-world input variability on operational models remains unquantified. To address this gap, we integrated an urban fire spread model into ELMFIRE and simulated three California WUI fires (Tubbs, Thomas, and Camp) to assess sensitivity to commonly used inputs, including wind, fuel moisture content (FMC), structures, and roadways. Real-world wind data varied by up to 40%, resulted in differences of over 50% in simulation accuracy, while downscaling had minor effects ( < 20%). FMC was equally influential, with multi-stage processing increasing uncertainty and reducing the accuracy of burned area (40%) and structure damage (70%). Simplified structure representations minimally affected burned area ( < 15%) but reduced structure damage accuracy ( > 40%), while misrepresented road firebreaks could significantly reduce accuracy (60%). Overall, wind and FMC effects are dominant; wind direction and speed control directionality and extent, while FMC governs vegetation ignitability. Some inputs can offset inaccuracies through compensation effects, while others (e.g., wind direction) have unique, non-compensable effects. Despite limitations such as variability in structure properties, this study provides practical guidance for selecting input data toward standardized operational WUI fire modeling. • Real-world wind data differences can reach up to 40% and cause simulation discrepancies over 50%. • Downscaling wind data had minor effects, altering results by less than 20%. • Multi-stage FMC processing increased uncertainty, reducing accuracy by up to 70%. • Misrepresenting types of road considered as firebreak could lower accuracy by up to 60%. • Some variables like wind direction capture key fire behavior; others can have compensation effects.

  PublisherDOI

• Lab Experiments of Wind-Driven Flame Spread Over a Gap at the Missoula Fire Sciences Laboratory (2020-2024)

  California Digital Library · 2026-01-01

  datasetOpen accessSenior author

  The following dataset contains thermocouple (TC), heat flux gauge (HFG), infrared (IR), and GoPro Video data for wind-driven flame spread experiments through 4-6cm deep longleaf pine needle fuel beds over a fuel discontinuity (gap). The purpose of this experiment is to characterize the impact of wind speed, moisture content, and fuel break size on fire behavior.These experiments were conducted in the low-speed wind tunnel at the U.S. Forest Service Missoula Fire Sciences Laborary in Missoula, MT using 0.5 m/s and 1 m/s wind speeds. For the main body of experiments, fuel bed size (4.9 x 1.8 m) was kept constant (called â full bed testsâ ), while the ambient wind speed, fuel moisture, and fuel break size were varied. Fuel moisture was binned into â dryâ tests, less than 9% fuel moisture content, while â wetâ tests has greater than 9% moisture content. Fuel break size was varied such that for each moisture content and wind speed testing condition, there were cases where the flame crossed the gap, and cases where it extinguished.In addition to the full bed tests, patch fuel tests were conducted to see the impact of changing the bed with and length on flame spread over the gap. Fuel bed widths of 1.2 m (4.9 m, 2.4 m, 1.2 m, and 0.6 m lengths) and 0.6 m (4.9 m, 2.4 m, and 1.2 m lengths) were tested. For these tests, wind speed, moisture content, and gap size were varied in addition to bed length and width.A related, larger-scale experiment was conducted the Insurance Institute for Business &amp; Home Safety (IBHS) in Richburg, SC. The data for the larger scale is archived under the title â Lab Experiments of Wind-Driven Flame Spread Over a Gap at the Insurance Institute for Business &amp; Home Safety (IBHS) (2021-2022)â .

  OA PDFDOI

• Occupationally Relevant Wildfire Smoke Inhalation Impairs Nitric Oxide Signaling and Promotes Progressive Aortic Stiffening in Hypercholesterolemic Mice

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-20

  article

  ABSTRACT Background Wildland firefighters experience repeated occupational exposure to wildfire smoke at high particulate matter (PM) concentrations, leading to elevated cardiovascular disease risk and hypertension prevalence. However, the pathophysiological processes linking cumulative smoke inhalation to vascular damage and blood pressure elevation remain poorly characterized. To evaluate these effects under controlled exposure conditions, we used a preclinical exposure model calibrated to match the cumulative PM burden deposited in wildland firefighter airways over 7-14 years of service. Male apolipoprotein E knockout (Apoe −/− ) mice underwent whole-body inhalation of Douglas fir smoke or filtered air for 2 hours/day, 5 days/week, for 8 or 16 weeks at target PM concentrations of 40 mg/m 3 . Results Prolonged smoke exposure induced sustained elevation of circulating tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6), coupled with diffused nuclear factor kappa B (NF-κB) activation throughout the aortic wall. Smoke inhalation disrupted endothelial adherens junctions, upregulated intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), and promoted monocyte recruitment to aortic tissues, concurrent with enhanced monocyte chemoattractant protein-1 (MCP-1) expression. Oxidative stress was evidenced by increased nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunit 2 (NOX2) expression, elevated superoxide levels, and endothelial nitric oxide synthase (eNOS) uncoupling in the aorta, leading to lipid peroxidation and accompanied by intimal apoptosis. These inflammatory and oxidative perturbations occurred alongside a pro-fibrotic phenotypic shift characterized by transforming growth factor beta 1 (TGF-β1) upregulation, myofibroblast differentiation, and progressive collagen accumulation in medial and adventitial compartments of the aortic wall. Functionally, smoke exposure progressively impaired aortic cyclic distensibility through combined wall thickening and circumferential tissue stiffening, while severely attenuating endothelium-dependent and nitric oxide (NO)-mediated vasodilation. These functional and structural shifts culminated in elevated systolic and diastolic blood pressures. While endothelial dysfunction reached maximal impairment by 8 weeks, aortic stiffening continued to worsen through 16 weeks of exposure, demonstrating differential temporal progression of vascular damage. Conclusions These findings demonstrate that occupationally relevant wildfire smoke exposure produces convergent inflammatory, oxidative, and profibrotic vascular remodeling with progressive loss of arterial compliance and impaired endothelium-dependent vasodilation, underscoring potential vascular targets for cardiovascular health surveillance and risk mitigation in wildland firefighters.

  PublisherDOI

• Impact of fuel moisture on chaparral emissions under flaming and smoldering conditions

  Fire Safety Journal · 2026-03-04

  articleSenior authorCorresponding
  PublisherDOI

• Simulations of firebrand-driven fire spread in landscape-scale Wildland-Urban-Interface (WUI) and urban conflagration models

  Fire Safety Journal · 2026-03-07 · 1 citations

  articleOpen access

  This study presents an application of a recently developed firebrand model to the case of fire spread in WUI and urban communities using a landscape-scale formulation. The study considers a benchmark configuration corresponding to an array of identical, equally-spaced, square structures; the array is characterized by two length scales: the structure size (SS) and structure separation distance (SSD). Simulations are performed both in one-dimension using MATLAB and in two-dimension using an established landscape-scale fire spread simulator called ELMFIRE. The firebrand model features descriptions of generation, transport and ignition: these were recently introduced for wildland fire applications and are here adapted to the case of WUI/urban fires. Simulations provide an evaluation of the critical conditions that lead to structure-to-structure fire spread, in terms of SSD, wind velocity and firebrand generation rates. The study also includes an evaluation of the model sensitivity to changes in spatial resolution. The model is found to be sensitive to changes in spatial resolution and requires a resolution of less than SS and SSD for grid convergence. These results can be explained by the dominant role of SS and SSD in the WUI/urban fire problem: both length scales need to be captured by the computational grid. • A framework to model firebrand-driven conflagrations in urban areas is presented. • The firebrand model is integrated into a landscape-scale fire spread simulator. • The model features descriptions of firebrand generation, transport and ignition. • The model sensitivity to changes in spatial resolution is evaluated. • It is found that grid convergence requires a spatial resolution of less than 10-m.

  PublisherDOI

• Quantifying Fire Performance and Minimum Char Thickness of Pre-charred Wood: Effect of Density and Moisture Content

  Proceedings of the Combustion Institute · 2025-01-01 · 2 citations

  articleSenior author
  PublisherDOI

• From incident to insight: Fire risk in modern data centers

  Journal of Loss Prevention in the Process Industries · 2025-12-17 · 2 citations

  articleOpen access

  Modern data centers are becoming increasingly vital infrastructure, yet several recent high-profile fire incidents have exposed persistent vulnerabilities. As artificial intelligence (AI) technologies continue to advance, these risks will only intensify. Contributing causes of such fires include electrical faults, battery failures, cooling system malfunctions, and human error. This perspective paper synthesizes key information from recently reported incidents and discusses practical fire safety strategies for both prevention (i.e., AI-driven fault detection and fire-safe battery storage) and suppression (i.e., clean agents and liquid nitrogen system). Emerging technologies are highlighted as potential fire safety enhancements, and their development and implementation in modern data centers are recommended. Two relevant methods for fire risk assessment are explored, specifically non-scenario-based consideration of common fire causes and scenario-based examination of recent incidents. These assessment methods should be utilized while considering engineering design practices, operational feasibility, and regulatory alignment to enhance resilience and promote adoption in modern data centers. This work intends to offer a perspective on data center fire risk assessment by examining past incidents, presenting insights into current knowledge gaps, and proposing future research and stakeholder efforts for the improvement of data center fire safety. • Fire incident risk across modern data centers is increasing rapidly. • Contributing causes of these fires are analyzed based on representative case studies. • Practical fire safety strategies for both prevention and suppression are discussed. • Emerging technologies are highlighted as potential enhancements to fire safety.

  PublisherDOI

Recent grants

• CAREER: Understanding the Mechanisms of Wildland Fire Spread

  NSF · $549k · 2016–2020

• CAREER: Understanding the Mechanisms of Wildland Fire Spread

  NSF · $170k · 2020–2022

Frequent coauthors

• Mark A. Finney

  Rocky Mountain Research Station

  21 shared

• Sriram Bharath Hariharan

  17 shared

• Elaine S. Oran

  16 shared

• Raquel S.P. Hakes

  University of Maryland, College Park

  16 shared

• Florian Linseis

  15 shared

• Jarosław Kita

  University of Bayreuth

  15 shared

• Ralf Moos

  University of Bayreuth

  14 shared

• Xingyu Ren

  Huangshan University

  13 shared

Education

• Ph.D., Mechanical and Aerospace Engineering

  University of California, San Diego

  2012