A Value Function Approach to Information Operations MOE\u27s: A Preliminary Study

A value focused thinking approach is applied to information operations. A preliminary value hierarchy for information operations is constructed by extracting the values of senior military leadership from existing doctrine. To identify these key values for information operations, applicable existing doctrine was reviewed and summarized. Additionally, hierarchical representations of the values represented within each reviewed doctrine are developed. A value hierarchy requires that supporting objectives be mutually exclusive and collectively exhaustive. Within this analysis, these requirements are enforced, in part, by developed definitions which serve as tests to maintain mutual exclusivity. An exhaustive set of supporting values is also guaranteed by identifying a spanning set of values that directly support the overall objective of information operations. This preliminary value hierarchy serves as the basis for continuing research. The implications for this research include the construction of a prescriptive model in which the effectiveness of current and future systems can be assessed on a common scale. Further, the effectiveness of developing technologies can be assessed and the value of these technologies determined with respect to the values of senior military leadership. With this, the value of holes in our suite of information warfare systems can also be assessed in terms of their effectiveness in fulfilling the values of military leadership

How Should Life Support Be Modeled and Simulated?

Why do most space life support research groups build and investigate large models for systems simulation? The need for them seems accepted, but are we asking the right questions and solving the real problems? The modeling results leave many questions unanswered. How then should space life support be modeled and simulated? Life support system research and development uses modeling and simulation to study dynamic behavior as part of systems engineering and analysis. It is used to size material flows and buffers and plan contingent operations. A DoD sponsored study used the systems engineering approach to define a set of best practices for modeling and simulation. These best practices describe a systems engineering process of developing and validating requirements, defining and analyzing the model concept, and designing and testing the model. Other general principles for modeling and simulation are presented. Some specific additional advice includes performing a static analysis before developing a dynamic simulation, applying the mass and energy conservation laws, modeling on the appropriate system level, using simplified subsystem representations, designing the model to solve a specific problem, and testing the model on several different problems. Modeling and simulation is necessary in life support design but many problems are outside its scope

Space Station communications and tracking systems modeling and RF link simulation

In this final report, the effort spent on Space Station Communications and Tracking System Modeling and RF Link Simulation is described in detail. The effort is mainly divided into three parts: frequency division multiple access (FDMA) system simulation modeling and software implementation; a study on design and evaluation of a functional computerized RF link simulation/analysis system for Space Station; and a study on design and evaluation of simulation system architecture. This report documents the results of these studies. In addition, a separate User's Manual on Space Communications Simulation System (SCSS) (Version 1) documents the software developed for the Space Station FDMA communications system simulation. The final report, SCSS user's manual, and the software located in the NASA JSC system analysis division's VAX 750 computer together serve as the deliverables from LinCom for this project effort

The role of learning on industrial simulation design and analysis

The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools, a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments

Modeling of power electronic systems with EMTP

In view of the potential impact of power electronics on power systems, there is need for a computer modeling/analysis tool to perform simulation studies on power systems with power electronic components as well as to educate engineering students about such systems. The modeling of the major power electronic components of the NASA Space Station Freedom Electric Power System is described along with ElectroMagnetic Transients Program (EMTP) and it is demonstrated that EMTP can serve as a very useful tool for teaching, design, analysis, and research in the area of power systems with power electronic components. EMTP modeling of power electronic circuits is described and simulation results are presented