Lawson criterion for ignition exceeded in an inertial fusion experiment

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion

Automatic incident detection and classification at intersections

Collisions at intersections are common and their consequences are often severe. This paper addresses the need for information on accident causation; a knowledge that can be used to obtain more effective countermeasures. A novel method that can be applied to data recorded in a groundbased observation system or similar is proposedfor classifying vehicle interactions into a set ofpredefined traffic scenarios. The classification isbased on possible combinations of trajectories of two interacting vehicles that have passed through an intersection. Additionally, the authors present an incident detection algorithm that uses the classified vehicle interactions. This algorithm constitutes the core of a video-based automatic incident detection at intersections (AIDI) system. The performance of the AIDI system was successfullyverified both in a driving simulator and in real traffic conditions

Automatic incident detection and classification at intersections

Collisions at intersections are common and their consequences are often severe. This paper addresses the need for information on accident causation; a knowledge that can be used to obtain more effective countermeasures. A novel method that can be applied to data recorded in a groundbased observation system or similar is proposedfor classifying vehicle interactions into a set ofpredefined traffic scenarios. The classification isbased on possible combinations of trajectories of two interacting vehicles that have passed through an intersection. Additionally, the authors present an incident detection algorithm that uses the classified vehicle interactions. This algorithm constitutes the core of a video-based automatic incident detection at intersections (AIDI) system. The performance of the AIDI system was successfullyverified both in a driving simulator and in real traffic conditions