Forumavia.ru - QNH и QFE, что лучше-то?

Двигатеелист 21

15.01.2007 23:46

Yeger:
ikar:
Аэрофлот320:
Roy Brown:

Касаемо QNH, QNE, QFE, QBB из той же оперы (т.е. таблицы), ИКАО и РПП совместимости

(теория и практика):

Должна присутствовать теория Каналов ввода-вывода (IOC) информации для РПП через
Создание Совместного КАНАЛА ВВОДА-ВЫВОДА ВСЕМИРНОЙ МЕТЕОРОЛОГИЧЕСКОЙ ОРГАНИЗАЦИИ
WMO-IOC, то есть IOC activities in the field of Integrated Coastal Area Management (ICAM)
Обзор создания ИКАО инициатив представлен в документе канала ввода-вывода EC-XXXI/13 и
располагаем в IOC/IYO Узле web http://ioc.unesco.org/iyo.

These documents were revised on the basis of the results of consultation with the
scientific
community as represented by the International Scientific Advisory Board (ISAB) and the
International Scientific Organizing Committee (ISOC) and the comments received from
National Commissions and Permanent Delegations, Academies of Science and National
Research Councils, IGOs, organizations of the United Nations system and NGOs concerned
with science. The final version of these two documents, prepared in early April 1999, are
presented in Part II of document 156 EX/8 for discussion under item 3.3.1

При этом необходимо обязательно учесть местный РЕГИОНАЛЬНЫЙ ОПЫТ 9-летних наблюдений:

The year 1998 was a turning point for IOC activities in the field of Integrated Coastal
Area Management (ICAM). Following the recommendations of the IOC Assembly, the revised
ICAM programme will be developed on the basis of the five following core components:
interdisciplinary approaches; marine scientific and technological information system;
methodology development; monitoring systems; and training, education and mutual
assistance (TEMA). The programme is progressively expanding and complementing other
related IOC programmes such as Integrated Global Observing Strategy (IGOS) , OSNLR,
OSLR and GIPME. In line with the conclusions
of the ACC Sub-Committee on Oceans and Coastal Areas (ACC SOCA) at its seventh session
(Monaco, 8-12 February 1999), initiatives have been taken to strengthen interagency
cooperation in the implementation of ICAM with UNEP acting as the lead agency.

Also, at the fifth International Conference of
Hydrology (Geneva, 8-12 February 1999), jointly organized by UNESCO and WMO, the two
agencies reviewed the results achieved since the United Nations Conference on Environment
and Development (UNCED).(Откуда ИМХО и пошли рекомендации в обьективных постановках для
региональных правил ИКАО на полеты по QNH, QNE, QFE )

А ВОТ ТОТ КУСОК, КОТОРЫЙ ЗАТРОНУЛ Roy Brown:

Уважаемые коллеги!
Нужна помощь. Вопрос для меня новый. Суть проблемы такова - подготовили новую редакцию РПП,

а я НАЧАЛ (пока невостребованную) переводную КНИГУ по РПП для ИКАО для этой постановки (как наиболее
важной вводной функциональности БП, можно разрабатывать так:

QNH, QNE, QFE , - shown in

> NH - нотикал хайт, FE - филд элэвэйшн.
> Так есть ли официальная версия?
Интересно, не разу не слышал, а во многих пособиях выделенны так называемые "Q-группы",
куда входят ещё и QDM, QDR, QTE, QUJ (unused joker) и т.д.

ПоЭтому, опять же с позиции Q-(unused joker*a), хочу отметить- задолбетесь
приспосабливать ИКАО позиции в .PDF бухгалтерию, потому как "или РЕВЕРСА" никогда не удовлетворят
эти РПП...он всегда будет прав, а вот инспектирующие "закрученные" пункты РПП - неизвестно.

Нужен более обьективный подход:

Many problems represent some localised interaction in a psuedo-infite space. In other
words any radiation shed from the interaction should propagate away without ever
being reflected back into the region of interest. In such cases boundaries must be
sufficiently far away from the important area of the field to have no effect on the
result, and when periodic boundary conditions are used (these are in fact enforced with
xmds) damping must be applied near the boundaries so as to absorb any such radiation.
The lattice used in each transverse dimension must be sufficiently fine to be able to
exhibit the details, yet not so fine as to cause memory problems - or cause the solution
to take forever to compute. Further still, field details that are significantly smaller
than those present at initialisation may evolve during the simulation, and the evolution
of such detail will ultimately be affected by the finesse of the transverse lattice.
Therefore simply reducing the time step alone is not a complete guarantee of accuracy.
The results must be inspected to ensure that the transverse lattice was fine enough to
contain the detail. If unsure then re-run the simulation with a finer lattice, as the
evolution may be attempting to generate singularities.

Usually, meaningful results only come from stochastic integration by averaging moments
of the fields over large numbers of paths. This leads to a second form of error for
stochastic equations due to the standard error in the mean. This is known as the
sampling error, and scales as the inverse square root of the number of paths taken.

Development and Program Structure:

It only takes a few items of information to define a numerical simulation, yet the list
of instructions necessary to get a computer to calculate the solution is vast in
comparison. Going from the former to the later is non-trivial. It can be done in a
single step (as far as the user is concerned) with high level programming languages,
but most computer programmers know from experience that the numerical solution can be
calculated more efficiently by writing comparatively more code in a low level script,
than less code in a high level script. This is because the programmer knows the purpose
of the program, and can optimise it accordingly as the list of instructions is expanded.
On the other hand a compiler can only perform optimisations that it knows are guaranteed
to work regardless of the purpose of the program.

By restricting the scope of programs to those with a known range of purposes, one is able
to write a compiler that generates more efficient output code. In other words the possible
input code is constrained to a very small set of instructions which, even though they may
be complex, have a well defined expansion into a simpler instruction set. Further, it is
not necessary to define the expansion down to the level of assembly code - one only needs
to define the expansion to a point where it no longer relies critically on the compiler's
optimisation ability. This is how **XSIL** works: transform from specialised input script to
efficient C code, and then let an ordinary compiler do the rest.

In choosing the high level syntax we have attempted to employ some degree of foresight:
the future is likely to see more interconnection of computer networks around the world,
and information is already taking a standardised form for transfer. Until now this has
primarily been HTML (Hyper Text Mark-up Language), but now there is increasing interest
in an ``extensible'' mark-up language of which HTML is only a subset. This is known as
XML (eXtensible Mark-up Language)A . Also, a standard for data interchange has been
developed at CaltechA which is a subset of XML: XSIL or eXtensible Scientific
Interchange Language, and this has been chosen as the format for field data input/output.

Using XML for the input script has another significant advantage: the format for the
simulation data takes on a tree-like structure which can be extended and made as complex
as is necessary. This is the extensible property of XML. Appropriately named element tags
are used to mark-up the essential data, and may be nested accordingly to group the information.
The result is a logical human-readable script with data represented in a manner preserving
both synthetic and sequential relationships.

XSIL has undergone a few development iterations for the purpose of refinement and extension.
There have been two particularly difficult aspects. The first was in defining an
appropriate equation syntax. This syntax had to be in C code style since xmds merely
transplants these equations into the output C code (which it then compiles), and yet it
had to be capable of representing equations of the form shown in EquationA 4.1. Further,
it was desired that the C code form of such an equation must be the same regardless of the
type of integration algorithm chosen. This difficulty was compounded by the desire to
include split-operator algorithms, which process the linear and nonlinear terms entirely
separately. The result that we have achieved here is quite elegant, though there are a
few caveats with regard to writing the equations.

The second area of difficulty was enabling the user to define exactly what they wanted as
output. The simplest solution would have been to save the raw field data to file as the
simulation progressed, and the user left to process it afterward in their own preferred
plotting and calculation package. However, with stochastic problems the user usually
wishes to calculate the average of some property or moment of the field over many
different trajectories or integration runs. Therefore it was necessary to enable to
user to define such moments so that they may be calculated and averaged before the output
data is written to file.

The source code for XSIL is written in object oriented C, otherwise known as C++. The main
routine is very simple, and its procedure is as shown on the left side in FigureA 3.1. The
right side is performed by the simulation data class.

A non-validating XML parser processes the input file and populates a node tree based on the
Document Object Model A . This parser was written by the author, but there is little
need to describe it in detail here. This node tree is then passed to a simulation class
object which extracts its own relevant data, and in turn creates child objects to process
the relevant sub-trees. The class structure of XSIL is shown in Figure A 3.2

Once the input file has been processed, a ``dry run'' of the main sequence tree is
called in order to evaluate the total number of samples requested for each output moment
group. Finally the output code is generated. This is accomplished with a ``tree walking''
technique. To begin with the simulation object writes any include statements that
are necessary. Then it writes any define statements particular to itself, and then calls
each of its child objects to do the same. This process is continued down the tree until
every object in the tree has written its define statements. Starting again at the
simulation element, the process is repeated to write the global variables, the routine
prototypes, and finally the routines themselves. This tree walking is performed by the
Element class with the virtual functions, aptly titled, writeDefines(), writeGlobals(),
writePrototypes(), and writeRoutines(). These routines are then overridden in the derived
classes to write the code specific to each class.

As mentioned in the previous section, one of the primary areas of difficulty was
developing a C-code style syntax which would allow a large range of complex PDEs to be
encoded, and in a manner that remains independent of the exact integrate algorithm chosen.
This was implemented using a two step process. To begin with, the user is required to
write equations with any differential operators replaced by an operator[component]
representation. For example, the
* QNH, QNE, QFE , - shown in IKAO documents (pp.826-839):

Ну и далее по текту НАШЕЙ новой теоретической редакции для ИКАО и РПП....

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QNH и QFE, что лучше-то?

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