Changes between Version 10 and Version 11 of palm4u

Timestamp:

Dec 15, 2017 9:58:55 AM (7 years ago)

Author:

maronga

Comment:

--

palm4u

@@ -53 +53 @@
 
 == Multi-agent system ==
-The conventional approach to assess biometeorological aspects in urban areas is an Eulerian approach, i.e., the area-wide evaluation of relevant parameters and indices, and subsequent mapping and zoning of these parameters. In this approach, socio-economic aspects of urban residents, such as resident characteristics like age, skin sensitivity, wealth, or population density and the typical behavior and movement patterns of these residents are usually neglected. In order to account for these additional parameters, a multi-agent system is implemented in PALM-4U that allows a new quality of biometeorological assessment studies. The multi-agent system is a Lagrangian approach in which groups (from hundreds to several thousands) of individual agents (i.e., residents) are released at selected locations of interest in the model domain (see e.g. Bruse, 2007; Chen and Ng, 2011; Gross, 2015, for further reading). Each agent can have individual characteristics (age, clothing, speed, starting points, targets, etc.) so that typical population groups can be statistically represented and released in the model. Each agent is able to move according to a path-finding algorithm that takes into account not only the agent’s characteristics, but also the atmospheric conditions in its surroundings, like sun/shaded area, searching for an optimal compromise between the fastest and most convenient path. The path-finding algorithm will be based on a path-load scheme where each accessible surface element is given a specific resistance. The resistance itself can be regarded as the sum of distance from the target area and additional resistances due to sloped terrain, forbidden areas, shaded and non-shaded sites, or the occupation of areas by other agents.
+The conventional approach to assess biometeorological aspects in urban areas is an Eulerian approach, i.e., the area-wide evaluation of relevant parameters and indices, and subsequent mapping and zoning of these parameters. In this approach, socio-economic aspects of urban residents, such as resident characteristics like age, skin sensitivity, wealth, or population density and the typical behavior and movement patterns of these residents are usually neglected. In order to account for these additional parameters, a multi-agent system is implemented in PALM-4U that allows a new quality of biometeorological assessment studies. The multi-agent system is a Lagrangian approach in which groups (from hundreds to several thousands) of individual agents (i.e., residents) are released at selected locations of interest in the model domain (see e.g. Bruse, 2007; Chen and Ng, 2011; Gross, 2015, for further reading). Each agent can have individual characteristics (age, clothing, speed, starting points, targets, etc.) so that typical population groups can be statistically represented and released in the model. Each agent is able to move according to a path-finding algorithm that takes into account not only the agent’s characteristics, but also the atmospheric conditions in its surroundings, like sun/shaded area, searching for an optimal compromise between the fastest and most convenient path. The path-finding algorithm will be based on a potential field scheme where the direction of movement is determined from the sum of forces acting upon the agent. The potential itself can be regarded as the result of a force towards the target area and additional forces due to sloped terrain, forbidden areas (buildings), shaded and non-shaded sites, or the occupation of areas by other agents.
 
-The multi-agent system is suited not only for evaluating biometeorological comfort indices and the relevance of the conventional Eulerian approach, but also for investigating escape routes in case of accidents, possibly associated with release of hazardous and toxic sub-
-
+The multi-agent system is suited not only for evaluating biometeorological comfort indices and the relevance of the conventional Eulerian approach, but also for investigating escape routes in case of accidents, possibly associated with release of hazardous and toxic substances.
 
 == Human biometeorology ==
+The evaluation of human thermal and wind comfort/stress as well the exposure to UV radiation is treated in both the classical Eulerian way, but also in the Lagrangian multi-agent system. Standard biometeorological thermal indices like Physiologically Equivalent Temperature (PET), Perceived Temperature (PT), and Universal Thermal Climate Index (UTCI) as well as wind comfort are calculated area-wide directly by the biometeorology module in PALM-4U and provided as output data. The module is based on the existing models RayMan (Matzarakis et al., 2010) and Sky-Helios (Matzarakis and Matuschek, 2011). Moreover, a Lagrangian version is implemented in that sense that the thermal and wind comfort are estimated for the agents released in the urban environment. However, as the established biometeorological indices are only defined for stationary meteorological state, adaptation and possibly re-definition of these indices are required as the agents movement no longer provides stationary atmospheric conditions. 
 
+The actinic module will primarily deal with the UV exposure of agents as they are moving through the model domain. This is realized by calculating the biologically weighted UV exposure after Seckmeyer et al. (2013), taking into account not only the complex human geometry, but also including various clothing conditions (which are assigned as attributes to the individual agents) as well as the shading of buildings. While this method provides the cumulated exposure of selected individuals, a more general approach are also used to derive area-wide maps (Eulerian approach), for which exposure rates are calculated based on idealized typical human geometry and clothing.
+
+The biometeorological module does not only allow to automatically obtain relevant parameters for stress/comfort. The calculated indices and parameters are also able to be incorporated into the path-finding algorithm of the multi-agent system. For example, excessive UV exposure in summer time might lead to a
+an force towards those surface areas that are shaded by buildings and vegetation and which thus are favorable. In this way, the agents can adjust their way through the urban area with improved comfort.
 
 == Graphical user interface ==