Organic Photovoltaic Device Model is a 1D Schottky-Read-Hall based drift diffusion model specifically designed to model organic photovoltaic (OPV) devices. It can describe non-geminate recombination via two mechanisms: free-to-trap processes via an exponential tail of trap states, and free-to-free carrier processes. The model solves the drift diffusion equations for electrons and holes, Poisson's equation to calculate the potential distribution in position space, and the Schottky-Read-Hall capture escape equations for a discretized set of energy levels. The model has been used to generate a number of publications. It can simulate the following experiments often used to characterize OPV devices: JV curves (Light/Dark), Charge extraction data (Light/Dark), and Steady state recombination data (Light/Dark).
SIM.JS is a general-purpose Discrete Event Simulation library fully capable of running in a Web browser. It provides constructs for creating Entities which are the active actors in a system, and encapsulates the state and logic of a system's components. Entities contend for resources, which can be Facilities (supports FIFO, LIFO with preemption and Processor Sharing service disciplines), Buffers, and Stores. Entities communicate by waiting on Events or by sending Messages. Statistics recording and analysis is provided by Data Series Statistics, Time Series Statistics, and Population Statistics. A random number library generates seeded random variates from various distributions, including uniform, exponential, normal, gamma, Pareto, and others.
Sea Ice is software for modeling the microwave emissivity of sea ice. It includes two plane-parallel radiative transfer models: a Monte Carlo ray tracing simulation that models ridged ice, and thermodynamic models that can be used to generate input to the emissivity models in the form of temperature and salinity profiles. It is written in C++ and Interactive Data Language (IDL). It has been used to generate results for several papers on sea ice emissivity.
PyParticles is a particle simulation toolbox entirely written in Python. It simulates a particle-by-particle model with the most popular integrations methods, including Euler, Runge Kutta, and Midpoint. It represents the results on an OpenGL or Matplotlib plot, and offers an easy-to-use API.
ARS (Autonomous Robot Simulator) is a physically-accurate simulation suite for research and development of mobile manipulators and, in general, any multi-body system. It is modular, easy to learn and use, and can be a valuable tool in the process of robot design, in the development of control and reasoning algorithms, and in teaching and educational activities. It will encompass a wide range of tools spanning from kinematics and dynamics simulation to robot interfacing and control.