Aircraft Accident Prevention Technology | STAR – Safety Technology for Aviation and Disaster-Relief Program | Aeronautical Technology Directorate
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Japan Aerospace Exploration Agency

Aircraft Accident Prevention Technology


March 24, 2017
JAXA begins demonstration tests on snow and ice monitoring sensors

Demonstration tests on snow and ice monitoring sensors, which JAXA has led the way in researching and developing, have begun at Kitami Institute of Technology (Kitami, Hokkaido) in December 2016. ...[more]

It is forecasted that air transport demand will double during the next 20 years. This increase in air transport creates the possibility of more aircraft accidents. Primary factors of aircraft accidents include special weather and human error. It is extremely important to implement measures for addressing such factors.

In terms of special weather, Japan faces one of the world's most severe environments for aircraft in the winter season. In addition to slippery conditions caused by snow, relatively large aircraft are operated on short runways. As a result, operation of aircraft is greatly affected by snow and ice on runways. The adherence of snow and ice to the airframe also has a significant impact on operation, particularly takeoff and landing. Furthermore, thunder is extremely strong during winter and the airframe will suffer more serious damage when struck by lightning. Generally speaking, it is difficult to predict snow and lightning. Although aircraft are designed to maintain a certain level of safety even when such weather occurs, the fact remains that operation efficiency is decreased in order to heighten safety. Moreover, when unforeseen weather conditions occur, there is the possibility of accidents and malfunctions.

In terms of human error, it is not sufficient to only implement measures for human error which can be foreseen in advance. Therefore, it is necessary to take measures by predicting potential errors.

In order to efficiently maintain airframe safety against the risks of special weather and human error, JAXA is conducting research and development for aircraft accident prevention technology. Specific developments are protection technology for weather disturbances, which detects and predicts the condition of the airframe, runway, and weather (airframe anti-icing technology, technology for ice contaminated runways, advance weather prediction technology, anti-lightning technology, engine technology for resistance to special weather), and Operational Procedure Safety Analysis Monitoring System (OPSAMS), technology which predicts and protects against threats by forecasting potential human error.

WEATHER-Eye (WEATHER-Endurance Aircraft Technology to Hold, Evade and Recover by Eye) technology

Operation image (protection technology for weather disturbances)

Airframe anti-icing technology

Flight performance declines when ice adheres (icing) to the airframe, particularly the wings. In some cases, icing can lead to a major accident. If it becomes possible to monitor the icing of wings, then the pilot can assess the icing condition of wings. Deicing and other measures can then be taken prior to takeoff. JAXA is also working to develop a special coating that prevents icing as much as possible.

Image of anti-ice coating

Technology for contaminated runways with snow and/or ice

Real-time monitoring of snow and ice conditions on runways makes it possible to make a swift decision regarding the safe takeoff or landing of the aircraft. Runways were only equipped with a sensor to determine whether or not snow has accumulated on the runway so far. This sensor facilitated the decision of whether or not to remove snow from the runway. However, in order to support operation, there is the need for detailed information on snow and ice accumulation. In response, through an industry-government-academia partnership, JAXA is working to develop an embedded runway sensor which measures the type and depth (resolution: 10 mm) of snow and ice.

Image of runway sensor placement

Advance weather prediction technology

Advance recognition of weather conditions which may cause icing or lightning strike makes it possible for the aircraft to avoid the threat of unexpected weather during operation. In addition to contributing to aircraft safety, this also reduces airframe repairs to fix damages caused by lightning strikes. Overall, this leads to an increase in operating efficiency. Accordingly, JAXA has started working to develop technology for the advance detection of weather conditions.

Image of system using advance weather prediction technology

Anti-lightning technology

It is difficult to prevent all lightning from striking aircraft. Therefore, it is extremely important to minimize the damage caused to airframes by lightning strikes. In response, through an industry-government-academia partnership, JAXA is working to develop technology that minimizes damage caused by lightning strikes through the use of special structures and materials. Moreover, JAXA has also started work for technology which detects lightning damage.

Engine technology for resistance to special weather

If volcanic ash enters a jet engine, there is the possibility of damage to the fan or turbine due to erosion (friction and damage caused by the intake of fine particles). Furthermore, the ice accretion may lead to a decrease or in the worst case loss of thrust. In response, JAXA has started work to develop technology for improving resistance to erosion and icing.

Electronic Monitoring Technology for Human Behavior

Operation image
(Monitors pilot behavior and conditions surrounding the aircraft, detects errors and threats, and gives appropriate advice to the pilot)

Operational Procedure Safety Analysis Monitoring System (OPSAMS)

Accidents caused by human error consist of a major cause and several background causes. Therefore, it is necessary to extract unsafe elements from daily operation data which does not lead to an accident. In response, JAXA has started work to develop technology for extracting unsafe elements (pilot error and other elements which affect safety) from operation data.

System image of OPSAMS