[railML3.2] Cant Deficiency Class for RS and/or TT [message #2890] |
Sun, 30 January 2022 13:46 |
Joerg von Lingen
Messages: 149 Registered: May 2011
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Senior Member |
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Dear all,
for use case ITMS there is the request to have "Cant Deficiency Class" in
rollingstock data. There is reference given to UNISIG Specification SUBSET-026-06.
When looking into chapter 6.5.1.5.34 NC_DIFF it becomes clear the resulting
Static Speed Profile (SSP) is what's needed. The definition of values for
NC_DIFF is the typical mixture of physical values and other conditions. Most of
the values for NC_DIFF are related to a specific value of cant deficiency in mm.
However, there are three values in-between referring to the brake position.
Question: Shall we model in railML the brake position and cant deficiency
separately or as a resulting integer like in UNISIG?
P.S: Be reminded that RS can only take (maximal) values of a train. But TT may
define deviating values/settings according to the needs of the specific run.
--
Best regards,
Joerg v. Lingen - Rollingstock Coordinator
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Re: [railML3.2] Cant Deficiency Class for RS and/or TT [message #2939 is a reply to message #2894] |
Mon, 07 March 2022 19:20 |
Milan Wölke
Messages: 146 Registered: April 2007
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Senior Member |
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Hi guys,
Im really not sure this is the right place to discuss this. From my point of view this is a topic that affects IS, RS and TT each. Therefore my understanding would be, that this should be discussed in the "Common" part of the forum. Actually I even found that there actually already is some modelling regarding CantDeficiency done there. So I guess we should take that over there and find out what requirements led to the currently modelled representation.
In general, I would follow Dirks view here, however I am unsure as to if this is what was modelled, nor do I know if it already was published or if it still just is a draft for the upcoming 3.2.
Best regards, Milan
Milan Wölke – Timetable scheme coordinator
railML.org (Registry of Associations: VR 5750)
Altplauen 19h; 01187 Dresden; Germany www.railML.org
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