The transportation of lithium batteries is heavily regulated. UN 3480, lithium-ion batteries (batteries not packed with or contained within equipment) are forbidden on passenger aircraft and cannot exceed 30% state of charge (SoC) when transported on cargo aircraft.

In March 2024, two packages containing lithium-ion cells (UN3480) started to smolder while being loaded into a unit load device (ULD) at the Hong Kong International Airport. An investigation determined that numerous cells within both packages showed significant signs of charring. Other packages from this shipping account had arrived at its destination airport in Ontario, California.

A team of hazardous materials aviation safety inspectors from the Federal Aviation Administration (FAA)’s Office of Hazardous Materials Safety (AXH) inspected the packages on-site in California. Subsequently, AXH contacted the FAA’s Fire Safety Branch to aid in further analysis. Twelve batteries were sent to the Fire Safety Branch at the William J. Hughes Technical Center, where testing was performed to determine the as-delivered SoC. Findings determined that the average SoC of the twelve lithium-ion batteries was 49.2%.

The fire growth rate of interior linings, furnishings, and construction materials is measured in full-scale fire tests such as the ASTM E84 Steiner Tunnel, the ISO 9705 room fire, and a passenger aircraft cabin as the flame spread rate, time-to-flashover, or time to incapacitation, respectively. The results are used to indicate the level of passive fire protection afforded by the combustible material or product in the test. These large-scale tests require many square meters of product, are very expensive to conduct, and can exhibit poor repeatability- making them unsuitable for product development, quality control, or product surveillance. For this reason, smaller ( 0.01 m2) samples are tested in bench-scale fire calorimeters under controlled conditions, and these one-dimensional burning histories are correlated with the results of the two- and three-dimensional burning histories in full-scale fire tests by a variety of empirical and semi-empirical fire propagation indices, as well as analytic and computer models that are particular to the full-scale fire test.

A more general approach described here equates the coupled fire growth processes of surface flame spread and in-depth burning to the generation of combustion heat in response to the radiant energy from a fire calorimeter that is above the critical value for ignition and burning. This measurement in a cone calorimeter under standard conditions (ASTM E1354) is used to compute the fire growth potential of the combustible solid, (m2/MJ), which is realized as a hazard when the heat of combustion, Hc (MJ/m2), is sufficient to grow the fire. Consequently, the dimensionless fire hazard of a material or product is obtained directly from a single cone calorimeter measurement as  =Hc. The physical basis for  and  as well as their method of evaluation in a cone calorimeter are described. Experimental data show that the development of full-scalecompartment fires and free standing product fires correlates with  as the sole explanatory variable.

Electrical odors and smoke incidents in aviation have become a pressing concern, with over half of the detector activations resulting in false alarms, leading to uncertainties for flight crews. The escalating costs of diversions and growing awareness of associated health risks underscore the need for more reliable detection and discrimination from false alarms. This study harnesses advanced multi-sensor array technologies, intelligent algorithms, and Metal Oxide Sensors (MOS) sensors equipped with AI capabilities to detect and analyze signatures from candidate internal contaminant sources located in the cockpit. Printed circuit boards from avionics, aviation cables of different insulation, and external contaminant sources were put to failure testing to analyze the early fire signatures. These signatures were subsequently assessed using clustering algorithms and multivariate analysis to pinpoint distinct markers. Comprehensive gas analysis and light obscuration measurements further characterized the environment. Experiments were executed at both the University of Maryland and the Federal Aviation Administration (FAA) Technical Center, replicating diverse conditions, including an altitude simulation of 8000 ft. The focus was on the capability to distinguish between samples during the smoldering phase, leveraging a multivariate approach and gas analysis. The study also incorporated Aspirating Smoke Detection (ASD) to characterize the responses during large-scale testing. The findings pave the way for identifying and integrating innovative technologies, achieving accurate detection of early-stage signatures from internal contaminants during potential aircraft smoke events.