MIMIC: A Historical Overview of a Pioneering Simulation Language
MIMIC, a highly influential computer simulation language developed in 1964, holds a significant place in the history of scientific computing. Designed by H. E. Petersen, F. J. Sansom, and L. M. Warshawsky of the Systems Engineering Group at the Air Force Materiel Command at Wright-Patterson Air Force Base (WPAFB) in Dayton, Ohio, MIMIC was born out of a need to enhance the modeling and simulation capabilities available to researchers in various scientific fields. In particular, MIMIC aimed to improve the simulation of dynamic systems in continuous time, and its development represented a substantial leap forward from its predecessor, MIDAS (Modified Integration Digital Analog Simulator). This article delves into the essential features of MIMIC, its historical context, and its significance in the evolution of simulation languages.
Historical Context and Development
The mid-20th century saw significant advancements in computational technology, particularly in the realm of scientific simulation. During this period, the ability to model complex dynamic systems was becoming increasingly important, as engineers, scientists, and researchers sought to better understand phenomena ranging from electrical circuits to biological systems. Prior to MIMIC, tools like MIDAS had been used to simulate analog systems, but they lacked the sophistication needed for large-scale and more complex models.
MIMIC was developed as a response to these limitations. Building on the foundation laid by MIDAS, it introduced more advanced capabilities in terms of both the types of systems that could be simulated and the ease with which these simulations could be conducted. MIMIC was specifically designed as an expression-oriented continuous block simulation language, capable of solving ordinary differential equations (ODEs) that are common in various scientific disciplines, including physics, chemistry, biology, engineering, economics, and even social sciences.
The development of MIMIC was undertaken by a team of researchers at WPAFB, who were part of the Air Force Materiel Command. Their goal was to create a more robust and flexible simulation environment, one that could handle larger and more intricate models than previously possible. Written entirely in FORTRAN (with the exception of a single routine written in COMPASS), MIMIC was executed on Control Data supercomputers, marking a significant leap in computational power for simulation tasks.
Core Features and Functionality
MIMIC was a language built around solving differential equations and simulating dynamic systems through numerical methods. Its primary computational tool was a variable step-size numerical integrator that employed the fourth-order Runge-Kutta method. This method allowed MIMIC to solve the differential equations that defined the behavior of systems over time, with greater precision and efficiency than its predecessors.
One of MIMIC’s most notable features was its ability to integrate blocks of FORTRAN-like algebra into its simulations. This allowed users to create complex models that included both dynamic system simulations and more traditional algebraic computations. For example, the simulation of an electrical circuit could easily be augmented with algebraic equations governing the behavior of the components, allowing for a more comprehensive analysis of the system’s overall behavior.
MIMIC also supported the inclusion of a range of specialized functions for simulating electrical circuit elements. This was particularly important in the context of military and aerospace applications, where complex electrical systems needed to be modeled accurately. Beyond electrical engineering, MIMIC found applications in fields as diverse as biological modeling, economics, and the social sciences, making it a versatile tool for researchers in many disciplines.
Another significant aspect of MIMIC was its compilation process. Unlike interpreted languages, MIMIC’s simulation programs were compiled before being executed. This compiled approach allowed for faster execution and greater efficiency in handling large-scale models. The simulation process in MIMIC was carried out in six distinct passes:
- MIMIN (Input): This pass reads the user’s simulation program and data into the system.
- MIMCO (Compiler): The compiler translates the user’s program into an in-core array of instructions, preparing it for execution.
- MIMSO (Sort): This pass sorts the instructions array based on the dependencies between variables, ensuring that computations are carried out in the correct order.
- MIMAS (Assembler): The assembler converts the sorted instructions into machine-oriented code.
- MIMEX (Execute): This pass executes the simulation by numerically integrating the model’s differential equations.
- MIMOUT (Output): Finally, the output pass generates a list or diagram of the results from the simulation.
This multi-pass process was key to MIMIC’s ability to handle large, complex simulations, ensuring both accuracy and efficiency.
Influence and Legacy
Although MIMIC was primarily developed for military applications, its influence extended far beyond the confines of the Air Force. The ability to solve ordinary differential equations and model nonlinear dynamic systems in a flexible, efficient manner made MIMIC highly useful in a wide array of scientific fields. Its development marked a significant step in the evolution of simulation languages and contributed to the advancement of computational modeling in numerous disciplines.
The use of MIMIC in solving complex scientific problems also helped lay the groundwork for future developments in the field of simulation. As computational power continued to increase, the techniques pioneered by MIMIC were refined and incorporated into newer simulation languages and software packages. In particular, the use of variable step-size numerical integration methods, such as the fourth-order Runge-Kutta method employed by MIMIC, became a standard technique in the simulation of dynamic systems.
MIMIC also influenced the development of other simulation environments and languages. Its design principles were reflected in later tools that sought to make simulation more accessible and powerful. The integration of algebraic equations with dynamic system models, the compilation process for improved performance, and the focus on nonlinear dynamic analysis were all ideas that would find their way into future simulation languages and software packages.
Despite its historical significance, MIMIC eventually fell out of use as newer, more advanced simulation tools emerged. However, the language’s impact on the field of scientific computing remains undeniable. It represented a significant step forward in the development of simulation technologies, providing researchers with the tools they needed to tackle increasingly complex and dynamic systems.
Conclusion
MIMIC stands as a testament to the ingenuity and foresight of the researchers at Wright-Patterson Air Force Base who developed it in the early 1960s. In a period when the computational capabilities were still in their infancy, MIMIC offered a powerful and flexible environment for simulating complex systems across a wide range of scientific disciplines. Its ability to handle nonlinear dynamics, integrate algebraic equations, and execute large-scale simulations made it a groundbreaking tool that paved the way for many of the simulation technologies that followed. Today, while MIMIC may be considered a historical artifact, its influence continues to resonate in the development of modern simulation software.
The legacy of MIMIC is a reminder of the important role that simulation languages and tools play in scientific discovery. As researchers continue to explore increasingly complex systems, the principles of simulation and numerical modeling first developed in MIMIC will remain essential to advancing our understanding of the world around us.