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Smith, Jonathan

Publications and source records attributed to Smith, Jonathan.

10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Trains of electron micro-bunches in plasma wake-field acceleration

Plasma-based charged particle accelerators have been intensively investigated in the past three decades due to their capability to open up new horizons in accelerator science and particle physics yielding electric field accelerating gradient more than three orders of magnitudes higher than in conventional devices. At the current stage the most advanced and reliable mechanism for accelerating electrons is based on the propagation of an intense laser pulse or a relativistic electron beam in a low density gaseous target. In this paper we concentrate on the electron beam-driven plasma wake-field acceleration and demonstrate using 3D PiC simulations that a train of electron micro-bunches with ~10 fs period can be generated behind the driving beam propagating in a density down-ramp. We will discuss the conditions and properties of the micro-bunches generated aiming at understanding and study of multi-bunch mechanism of injection. It is show that the periodicity and duration of micro-bunches can be controlled by adjusting the plasma density gradient and driving beam charge.

Physics↗
NASA NTRS2016

MONTE's Client-Based Trajectory Propagation Architecture

The Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) is JPL's (Jet Propulsion Laboratory's) signature astrodynamic computing platform. It supports all phases of space mission development, from early stage mission design and analysis through flight navigation services. MONTE employs a client-based trajectory propagation architecture where accelerations are calculated in the main MONTE library and the integrator exists on the periphery as a client. This paper outlines this approach to a trajectory propagation system and provides a concrete set of examples showing its utility.

Smith, Jonathan↗
NASA NTRS2016

MONTE Python for Deep Space Navigation

The Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) is the Jet Propulsion Laboratory’s (JPL) signature astrodynamic computing platform. It was built to support JPL’s deep space exploration program, and has been used to fly robotic spacecraft to Mars, Jupiter, Saturn, Ceres, and many solar system small bodies. At its core, MONTE consists of low-level astrodynamic libraries that are written in C++ and presented to the end user as an importable Python language module. These libraries form the basis on which Python-language applications are built for specific astrodynamic applications, such as trajectory design and optimization, orbit determination, flight path control, and more. The first half of this paper gives context to the MONTE project by outlining its history, the field of deep space navigation and where MONTE fits into the current Python landscape. The second half gives an overview of the main MONTE libraries and provides a narrative example of how it can be used for astrodynamic analysis.

aerospace↗
NASA NTRS2016

MONTE: the Next Generation of Mission Design and Navigation Software

The Mission Analysis, Operations and Navigation Toolkit Environment (MONTE) is an astrodynamic toolkit produced by the Mission Design and Navigation Software Group at the Jet Propulsion Laboratory. It provides a single integrated environment for all phases of deep space and Earth orbiting missions. Capabilities include: trajectory optimization and analysis, operational orbit determination, flight path control, and 2D/3D visualization. MONTE is presented to the user as an importable Python language module. This allows a simple but powerful user interface via CLUI or script. In addition, the Python interface allows MONTE to be used seamlessly with other canonical scientific programming tools such as SciPy, NumPy, and Matplotlib. MONTE is the prime operational orbit determination software for all JPL navigated missions.

Optimization↗