Biblio

Inertial Confinement Fusion(ICF) uses the inertia of the substance itself to confine the nest-temperature thermonuclear fuel plasma to achieve thermonuclear fusion and obtain fusion energy. In the design of the local-volume ignition target capsule, the ignition zone and the main combustion zone are separated by heavy medium. The ignition zone is located in the center of the system (the part of the fusion combustion). The mass is small and can be compressed to high density and the overall temperature is raised to the ignition state (local-volume ignition). The temperature increase and density increase of the local volume ignition are relatively decoupled in time. The multi-step enhanced shock wave heats the fuel temperature drop, after which the collision effect accelerates the metal shell layer by layer, and uses the inertia of high-Z metal shell with a larger residual mass to achieve effective compression of the fuel areal after the driving source ends for a long time. Local volume ignition has the advantages of no need to reshape the radiation driving pulse, resistance to the influence of hot electrons, less demanding compression symmetry, and large combustion gain.

The MagNIF team at LLNL is developing a pulsed power platform to enable magnetized inertial confinement fusion and high energy density experiments at the National Ignition Facility. A pulsed solenoidal driver capable of premagnetizing fusion fuel to 40T is predicted to increase performance of indirect drive implosions. We have written a specialized Python code suite to support the delivery of a practical design optimized for target magnetization and risk mitigation. The code simulates pulsed power in parameterized system designs and converges to high-performance candidates compliant with evolving engineering constraints, such as scale, mass, diagnostic access, mechanical displacement, thermal energy deposition, facility standards, and component-specific failure modes. The physics resolution and associated computational costs of our code are intermediate between those of 0D circuit codes and 3D magnetohydrodynamic codes, to be predictive and support fast, parallel simulations in parameter space. Development of a reduced-order, physics-based target model is driven by high-resolution simulations in ALE3D (an institutional multiphysics code) and multi-diagnostic data from a commissioned pulser platform. Results indicate system performance is sensitive to transient target response, which should include magnetohydrodynamic expansion, resistive heating, nonlinear magnetic diffusion, and phase change. Design optimization results for a conceptual NIF platform are reported.

A new pulse power system is being developed with the goal of generating up to 40T seed magnetic fields for increasing the fusion yield of indirect drive inertial confinement fusion (ICF) experiments on the National Ignition Facility. This pulser is located outside of the target chamber and delivers a current pulse to the target through a coaxial cable bundle and custom flex-circuit strip-lines integrated into a cryogenic target positioner. At the target, the current passes through a multi-turn solenoid wrapped around the outside of a hohlraum and is insulated with Kapton coating. A 11.33 uF capacitor, charged up to 40 kV and switched by spark-gap, drives up to 40 kA of current before the coil disassembles. A custom Python design optimization code was written to maximize peak magnetic field strength while balancing competing pulser, load and facility constraints. Additionally, using an institutional multi-physics code, ALE3D, simulations that include coil dynamics such as temperature dependent resistance, coil forces and motion, and magnetic diffusion were conducted for detailed analysis of target coils. First experiments are reported as well as comparisons with current modelling efforts.

The transportation system is becoming tremendously important in today's human activities and the number of urban vehicles grows rapidly. The vehicle theft also has become a shared concern for all vehicle owners. However, the present anti-theft system which maybe high reliable, lack of proper mechanism for preventing theft before it happens. This work proposes the internet of things based smart vehicle security staring system; efficient security provided to the vehicle owners relies on securing car ignition system by using a developed android application running on smart phone connected to the designed system installed in vehicle. With this system it is non- viable to access the vehicle's functional system in case the ignition key has been stolen or lost. It gives the drivers the ability to stay connected with their vehicle. Whenever the ignition key is stolen or lost, it is impossible to start the vehicle as the ignition system is still locked on the vehicle start and only the authorized person will be able to start the vehicle at convenient time with the combination of ignition key and smart phone application. This study proposes to design the system that uses node MCU, Bluetooth low energy (BLE), transistors, power relays and android smartphone in system testing. In addition, it is cost effective and once installed in the vehicle there is no more cost of maintenance.

Automobiles provide comfort and mobility to owners. While they make life more meaningful they also pose challenges and risks in their safety and security mechanisms. Some modern automobiles are equipped with anti-theft systems and enhanced safety measures to safeguard its drivers. But at times, these mechanisms for safety and secured operation of automobiles are insufficient due to various mechanisms used by intruders and car thieves to defeat them. Drunk drivers cause accidents on our roads and thus the need to safeguard the driver when he is intoxicated and render the car to be incapable of being driven. These issues merit an integrated approach to safety and security of automobiles. In the light of these challenges, an integrated microcontroller-based hardware and software system for safety and security of automobiles to be fixed into existing vehicle architecture, was designed, developed and deployed. The system submodules are: (1) Two-step ignition for automobiles, namely: (a) biometric ignition and (b) alcohol detection with engine control, (2) Global Positioning System (GPS) based vehicle tracking and (3) Multisensor-based fire detection using neuro-fuzzy logic. All submodules of the system were implemented using one microcontroller, the Arduino Mega 2560, as the central control unit. The microcontroller was programmed using C++11. The developed system performed quite well with the tests performed on it. Given the right conditions, the alcohol detection subsystem operated with a 92% efficiency. The biometric ignition subsystem operated with about 80% efficiency. The fire detection subsystem operated with a 95% efficiency in locations registered with the neuro-fuzzy system. The vehicle tracking subsystem operated with an efficiency of 90%.