Self-organized criticality (SOC) is a property of dynamical systems that have a critical point as an attractor. Their macroscopic behavior thus displays the spatial or temporal scale-invariance characteristic of the critical point of a phase transition, but without the need to tune control parameters to a precise value, because the system, effectively, tunes itself as it evolves towards criticality.
A crowd is as a group of people that have gathered for a common purpose or intent. Examples are a demonstration, a sports event, or a looting. A crowd may also simply be made up of many people going about their business in a busy area.
Peter V. Coveney is a British chemist who is Professor of Physical Chemistry, Honorary Professor of Computer Science, and the Director of the Centre for Computational Science (CCS) and Associate Director of the Advanced Research Computing Centre at University College London (UCL). He is also a Professor of Applied High Performance Computing at University of Amsterdam (UvA) and Professor Adjunct at the Yale School of Medicine, Yale University. He is a Fellow of the Royal Academy of Engineering and Member of Academia Europaea. Coveney is active in a broad area of interdisciplinary research including condensed matter physics and chemistry, materials science, as well as life and medical sciences in all of which high performance computing plays a major role. The citation about Coveney on his election as a FREng says: Coveney "has made outstanding contributions across a wide range of scientific and engineering fields, including physics, chemistry, chemical engineering, materials, computer science, high performance computing and biomedicine, much of it harnessing the power of supercomputing to conduct original research at unprecedented space and time scales. He has shown outstanding leadership across these fields, manifested through running multiple initiatives and multi-partner interdisciplinary grants, in the UK, Europe and the US. His achievements at national and international level in advocacy and enablement are exceptional".
A second-order cellular automaton is a type of reversible cellular automaton (CA) invented by Edward Fredkin where the state of a cell at time t depends not only on its neighborhood at time t − 1, but also on its state at time t − 2.
Statistical finance is the application of econophysics to financial markets. Instead of the normative roots of finance, it uses a positivist framework. It includes exemplars from statistical physics with an emphasis on emergent or collective properties of financial markets. Empirically observed stylized facts are the starting point for this approach to understanding financial markets.
Boris S. Kerner is a German physicist and civil engineer who created three phase traffic theory. The three phase traffic theory is the framework for the description of empirical vehicular traffic states in three traffic phases: (i) free traffic flow (F), (ii) synchronized traffic flow (S), and (iii) wide moving jam (J). The synchronized traffic flow and wide moving jam phases belong to congested traffic.
Microscopic traffic flow models are a class of scientific models of vehicular traffic dynamics.
Superstatistics is a branch of statistical mechanics or statistical physics devoted to the study of non-linear and non-equilibrium systems. It is characterized by using the superposition of multiple differing statistical models to achieve the desired non-linearity. In terms of ordinary statistical ideas, this is equivalent to compounding the distributions of random variables and it may be considered a simple case of a doubly stochastic model.
In computational fluid dynamics, the immersed boundary method originally referred to an approach developed by Charles Peskin in 1972 to simulate fluid-structure (fiber) interactions. Treating the coupling of the structure deformations and the fluid flow poses a number of challenging problems for numerical simulations. In the immersed boundary method the fluid is represented in an Eulerian coordinate system and the structure is represented in Lagrangian coordinates. For Newtonian fluids governed by the Navier–Stokes equations, the fluid equations are
Dirk Helbing is Professor of Computational Social Science at the Department of Humanities, Social and Political Sciences and affiliate of the Computer Science Department at ETH Zurich.
In transportation infrastructure, a bidirectional traffic system divides travellers into two streams of traffic that flow in opposite directions.
Classic epidemic models of disease transmission are described in Compartmental models in epidemiology. Here we discuss the behavior when such models are simulated on a lattice. Lattice models, which were first explored in the context of cellular automata, act as good first approximations of more complex spatial configurations, although they do not reflect the heterogeneity of space. Lattice-based epidemic models can also be implemented as fixed agent-based models.
A reversible cellular automaton is a cellular automaton in which every configuration has a unique predecessor. That is, it is a regular grid of cells, each containing a state drawn from a finite set of states, with a rule for updating all cells simultaneously based on the states of their neighbors, such that the previous state of any cell before an update can be determined uniquely from the updated states of all the cells. The time-reversed dynamics of a reversible cellular automaton can always be described by another cellular automaton rule, possibly on a much larger neighborhood.
Stochastic cellular automata or probabilistic cellular automata (PCA) or random cellular automata or locally interacting Markov chains are an important extension of cellular automaton. Cellular automata are a discrete-time dynamical system of interacting entities, whose state is discrete.
Physics of financial markets is a non-orthodox economics discipline that studies financial markets as physical systems. It seeks to understand the nature of financial processes and phenomena by employing the scientific method and avoiding beliefs, unverifiable assumptions and immeasurable notions, not uncommon to economic disciplines.
In chemical kinetics, the Aquilanti–Mundim deformed Arrhenius model is a generalization of the standard Arrhenius law.
Erica Kuligowski is an American social research scientist investigating human behavior during emergencies and the performance of evacuation models in disasters. She currently works at RMIT university in Melbourne (Australia). Kuligowski used to work the Engineering Lab of the National Institute of Standards and Technology conducting research on several fire disasters including the NIST Hurricane Maria Project.
The Kincade Fire was a wildfire that burned in Sonoma County, California in the United States. The fire started northeast of Geyserville in The Geysers on 9:24 p.m. on October 23, 2019, and subsequently burned 77,758 acres (31,468 ha) until the fire was fully contained on November 6, 2019. The fire threatened over 90,000 structures and caused widespread evacuations throughout Sonoma County, including the communities of Geyserville, Healdsburg, Windsor, and Santa Rosa. The majority of Sonoma County and parts of Lake County were under evacuation warnings and orders. Lake county only had one evacuation order and that was the town of Middletown. The fire was the largest of the 2019 California wildfire season, and also the largest wildfire recorded in Sonoma County at the time before being surpassed by the LNU Lightning Complex fires in 2020.
Ruggiero Lovreglio is an Italian academic based in Auckland, New Zealand. He is an associate professor at Massey University and a Rutherford Discovery Fellow for Royal Society Te Apārangi. His research is focused on large-scale and small-scale evacuation dynamics and safety training using emerging technologies, such as virtual reality and augmented reality.
Evacuation models are simulation tools designed to predict the movement and behaviour of individuals during an emergency evacuation. These models are today used to simulate evacuations for several disasters, such as building fires, wildfires, hurricanes, and tsunamis. Thes models have been under development since the late 1970s and they are now widely to assess the time required to evacuate buildings, cities or wider regions.
