Why Risk Models should be Parameterised

Risk models using fault and event trees can be extended with explicit factors, which are states of the system, its users or its environment that influence event probabilities. The factors act as parameters in the risk model, enabling the model to be re-used and also providing a new way to estimate the overall risk of a system with many instances of the risk. A risk model with parameters can also be clearer

Evolution in complex systems

What features characterise complex system dynamics? Power laws and scale invariance of fluctuations are often taken as the hallmarks of complexity, drawing on analogies with equilibrium critical phenomena[1-3]. Here we argue that slow, directed dynamics, during which the system's properties change significantly, is fundamental. The underlying dynamics is related to a slow, decelerating but spasmodic release of an intrinsic strain or tension. Time series of a number of appropriate observables can be analysed to confirm this effect. The strain arises from local frustration. As the strain is released through "quakes", some system variable undergoes record statistics with accompanying log-Poisson statistics for the quake event times[4]. We demonstrate these phenomena via two very different systems: a model of magnetic relaxation in type II superconductors and the Tangled Nature model of evolutionary ecology, and show how quantitative indications of ageing can be found.Comment: 8 pages, 5 figures all in one fil

Complex Systems: A Survey

A complex system is a system composed of many interacting parts, often called agents, which displays collective behavior that does not follow trivially from the behaviors of the individual parts. Examples include condensed matter systems, ecosystems, stock markets and economies, biological evolution, and indeed the whole of human society. Substantial progress has been made in the quantitative understanding of complex systems, particularly since the 1980s, using a combination of basic theory, much of it derived from physics, and computer simulation. The subject is a broad one, drawing on techniques and ideas from a wide range of areas. Here I give a survey of the main themes and methods of complex systems science and an annotated bibliography of resources, ranging from classic papers to recent books and reviews.Comment: 10 page

Modeling Complex Systems

Abstract Empirical observations suggest that linear dynamics are not an adequate representa- tion of ecological systems and that a realistic representation would require adoption of complex nonlinear dynamical systems with characteristics encountered in complex adaptive systems (CAS). Adequate modelling should include and combine, among others, strategic interactions among economic agents, nonconvexities induced by non-linear feedbacks, separate spatial and temporal scales and modeling of spatiotempo-ral dynamics, and allowance of alternative time scales. Ignoring these characteristics might obscure very important features that we observe in reality such as bifurcations and irreversibilities or hysteresis. As a consequence, the design of policies that do not take CAS characteristics into account might lead to erroneous results and undesirable states of managed economic-ecological systems.Complex adaptive systems, differential games, spatiotemporal dynamics, fast-slow variables.

Susceptibility analysis of complex systems

A study of electromagnetic coupling effects on systems containing distributed elements and lumped linear components is presented. The structure is decomposed into sections containing multiconductor transmission lines and interconnection blocks holding lumped elements. The external field is assumed to interfere with line sections, but mutual influences among different sections are neglected. Both the sections and the blocks are treated as multiport components and characterized by their scattering parameters. The analysis is based on a correspondence matrix that accounts for the topology of connections between sections and blocks. Closed-form solutions are derived in the Laplace domain, and the temporal evolution of voltages and currents at any of the system ports is obtained by a numerical inversion. This method makes it possible to predict the susceptibility of complex systems and to verify the intra-system compatibility (especially crosstalk). The relative influence of circuit components and of line layouts on the severity of interferences is evidenced by simulation result