SINDA code was developed a long time ago, and there are various
SINDA-like codes available. SINDA/FLUINT is, however, the most featured
and complete thermal/hydraulic network solver available. More person-years
have been invested in its development than in any other SINDA-like
code, and it shows.
to other codes? You should!
Here's a few
items to consider. The following is not a complete list of the
features in SINDA/FLUINT. Rather, it is a list of SINDA/FLUINT's
features that cannot be matched by any other thermal network analyzer.
first introduced the concept of an integral spreadsheet almost a
decade ago, and this has proven to be very popular and powerful.
The integral spreadsheet feature was further advanced in Version
4.1 to include conditional operators and access to processor variables.
These expansions have tremendously increased the ease of use of
the code, rendering many common uses of logic blocks archaic. The
built-in spreadsheet ...
makes models easier to read, easier
to inherit (more self-documenting), and easier to change and maintain
enables sweeping changes while the model
is running, facilitating parametric and sensitivity analyses on-the-fly.
allows model building to precede final
dimensions and properties on fast turn-around projects.
Enables multiple designs and design
cases to be stored within a single model
permits complicated interrelationships
to be defined between inputs, and even between inputs and outputs
is so popular and powerful that competitors are trying to mimic
its features. Still, none can match the following features in SINDA/FLUINT,
which distinguish truly integral spreadsheet-like functionality,
from a hastily added patchwork:
The ability to use user-defined variables
("registers") almost anywhere within the model, including
array data, fluid data, property data, initial conditions, temperature-
and time-dependent options, etc. etc. In fact, about the only
thing that can't be algebraically defined is the name of a node.
The ability to make indirect references
to other registers and variables. For example, registers can be
defined in terms of each other (e.g., OuterDia = InnerDia - 2*WallThck).
Indirect references are resolved iteratively in true spreadsheet
fashion, even while the processor is executing.
The ability to refer to "processor"
(response or output) variables such as "T22" within
expressions, including those used to define registers and any
The ability to use built-in functions,
constants, conditional (IF/THEN/ELSE) operators, etc.
The ability to use indirect references
to make expressions reusable, and to eliminate rework or errors
when node names changes. For example, the capacitance of a node
can be defined in terms of its own temperature "T#this",
such that the expression remains valid (or can be copied and pasted
to other nodes) even if the node ID changes.
common and expensive. In large scale projects, each discipline (thermal,
structural, power, etc.) communicates worst-case requirements to
other disciplines leading to designs that are heavier and more costly
than they need to be, and in some cases does not even result in
a safer or more reliable design. Only
when meeting an extreme stack-up of margins and uncertainties becomes
impossible does a renegotiation of adequate margin begin, and such
renegotiations are seldom based on any mathematical rigor or true
knowledge of the underlying risk.
As an alternative
to stacking up worst-case margins, uncertainties, the engineer can
combine these factors statistically to yield information about the
degree of confidence ("reliability") in a particular point design.
with the Solver, the user can synthesize a
design that meets reliability requirements up front, intelligently
balancing cost against risk
Using our Reliability
Engineering model, the engineer can
not just a single performance prediction but also a distribution
of performance predictions with associated probabilities of occurrence.
tolerances in design parameters, uncertainties in environments,
uncertainties in application, and variations in manufacturing
as the stochastic phenomena that they are
the probability that a design will achieve its required performance
(i.e., the reliability)
an assessment of risk or confidence in the design
the amount of over- or under-design present in a given system
variables as "uncertain" and allow them to vary over
a prescribed range based on their probability distribution
arbitrary, normal distributions
wide range of statistical analysis routines
Carlo, descriptive, and gradient
information on the Reliability Engineering module built into SINDA/FLUINT
please review the following white paper:
think "optimization" means manually tweaking a design
until it seems better. SINDA/FLUINT features fully automated design
optimization and goal seeking, with little or no user programming
required. Using a built-in nonlinear programming module, the user
lists an arbitrary number of design
parameters to be adjusted
provides a figure of merit to distinguish
what is "better or worse" about a design or correlation
Examples: weight (minimize), efficiency
(maximize), error between test and predictions (minimize)
defines arbitrarily complicated criteria
that separate a useful design from a useless one, based on design
parameters, design performance, etc.
Examples: keep nodes within temperature
limits, don't accept a pressure drop too high ...
supplies an evaluation procedure, which
may invoke any SINDA/FLUINT analysis routine or method available
in any combination
Example: a simple steady state,
a series of transient events ...
SINDA/FLUINT then autonomously seeks
and reports the best design, or the values of uncertainties that
best match available test data.
may also be used to invert the normal input/output sequence for
almost any parameter. For example, instead of providing a conductivity
and getting back a temperature, the user can provide a temperature
and get back a conductivity.
is like programming a series of old SINDA runs to perform some design
or analysis task automatically. In addition to reducing
engineering labor, this "Solver" module transcends the
prior usage of SINDA as a steady or transient analyzer of point-designs.
This module provides higher order functionality that lets the thermal
engineer contribute to preliminary designs rather than always playing
goes by many names: "calibration," "model adjustment,"
and even "solving the reverse problem." It is a critical,
labor-intensive, and until recently procedurally ill-defined task.
SINDA/FLUINT offers completely automated data correlation tools
that avoid guessed adjustments, iterative runs, and subjective comparisons
such as visual plot matching. The user has complete control over:
the uncertainties to vary, and within
the number and type of comparisons to
the frequency of comparisons, from a
single steady state, to multiple steady states, to several comparisons
within multiple transient runs, etc.
the order in which uncertainties are
resolved (if all uncertainties are not solved simultaneously)
the mathematical basis for making a
comparison (perhaps least squares, or minimized maximum error,
Auxiliary routines are available
for handling the large amounts of data typically required for these
comparisons. These routines help prepare data, make comparisons,
and report the results of the comparisons.
Nodes and conductors
are the backbone network elements to almost all SINDA-like thermal
analyzers. However, this doesn't mean that all analyzers provide
the same modeling tools to the users.
'85", the precursor to SINDA/FLUINT, introduced the concept
of submodels almost 15 years ago. This powerful feature allows:
multiple models to be easily combined
into a single model without concern for node number collisions,
differences in solution techniques or control parameters or logic,
higher-level solution schemes that can
treat each submodel semi-independently, for increased speed and
dynamic model manipulations, such as
switching in and out components, changing boundary conditions
and environments or materials, etc.
SINDA/FLUINT offers multiple steady-state
and transient solution methods not just routines.We are continuously improving these methods, and that includes
obsolescing less efficient methods to avoid confusion and to facilitate
training. For example, at least four completely different acceleration
schemes are available in the two steady-state routines. An addition
each submodel can be solved with a different method based upon different
criteria. This allow complete customization of the solution. Packaging
multiple solution options within a few routines not only makes SINDA/FLUINT
easier to learn by avoiding a matrix of complex control options
(some of which only work in some routines or which change meaning
in different routines), it allows the user to adjust a model dynamically.
features true thermodynamic/thermohydraulic fluid networks, not
just traditional SINDA nodes and conductors masquerading as "pipes"
and "pressure nodes," and barely able to solve single-phase
steady incompressible piping networks. The fluid analysis features
in SINDA/FLUINT ("FLUINT") are designed to solve
the unique problems exhibited by real, complex thermal/fluid systems
involving full conservation of mass (including species mass), momentum,
and energy in multiple phases.
systems increasingly use fluid systems (pumped loops, heat pipes
or capillary loops, thermosyphons, air circulators, vapor compression
cycles) to meet design objectives. But because SINDA/FLUINT offers
the most powerful general-purpose hydraulics code available anywhere
in any industry, it is the tool of choice not only for thermal
engineers but for specialists in cryogenic systems, climate control
systems, refrigeration, oil and gas delivery and storage systems,
fuel and exhaust systems, and many more. In fact, many SINDA/FLUINT
users use the fluid modeling features exclusively, not needing the
traditional SINDA heat transfer networks. But they're there if those
users ever change their minds.
The fluid modeling
capabilities in SINDA/FLUINT include:
arbitrary 1D networks, including thermal
stratification in 2D and 3D control volumes
conjugate heat transfer
steady or transient, from quasi-steady
(e.g., thermally-dominated) transients to full hydrodynamic transients
such as waterhammer
fluid independence: user-defined fluid
properties of arbitrary complexity
single- or two-phase flows
incompressible or compressible working
pure substances or mixtures of gases,
liquids, or both
pumps, valves, ducts, etc.
custom control systems and fluid components
The two-phase analysis capabilities in
SINDA/FLUINT are extensive, featuring
boiling, flashing, condensation, cavitation,
homogeneous or slip flow
complete mechanistic flow regime mapping
equilibrium or nonequilibrium phases
capillary models (wicks, vapor barriers,
liquid acquisition/control/separators, etc., including many modeling
tools such as evaporator-pumps for capillary pumped loops and
loop heat pipes - CPLs, LHPs)
mixtures of condensible/volatile substances
and oils and/or gases
CRTech has offered a complete GUI for SINDA/FLUINT: Sinaps®.
Sinapseliminates the need to work with ASCII inputs
and ASCII outputs, allowing visual manipulation and control of the
entire SINDA/FLUINT model (fluid, thermal, or both).
While it provides
very complete preprocessing and postprocessing options, Sinaps
is more than a GUI. It allows the user to pass models as documentation
to unlicensed users. These models can be used to review networks,
or to generate new results, or even as stand-alone tools.
like SINDA/FLUINT, is nongeometric: it is a sketchpad-like circuit
design tool for thermal and/or fluid circuits. When the user needs
to work with geometric entities in the construction or postprocessing
of a model, then CRTech also offers geometry-based GUIs such as
RadCAD® and the Thermal
No other supplier
of thermal network analysis software also provides a complete thermal
radiation package, much less a CAD-compatible tool that is faster
and friendlier than any alternative. RadCAD®,
a modern thermal radiation pre- and post-processor to SINDA/FLUINT,
is the first CAD-based and FEM-compatible tool of its kind. It features
fast new algorithms, and powerful model building and maintenance
concepts such as property aliases, analysis groups, and articulators.
is not a finite difference code, it is an equation solver. It can
solve lumped parameter, finite difference, and finite element equations
all at the same time, and with equal ease.]
designers can no longer afford to be spectators to the concurrent
engineering revolution, and they no longer need be shoe-horned into
a structural code in order to participate in a design team.
Desktop can be thought of as a geometric GUI to SINDA/FLUINT, but
it is more than that: it is the first tool designed specifically
for thermal engineers that operates in a CAD environment and that
is fully compatible with FEM methods, without sacrificing good thermal
modeling practices. Thermal Desktop allows thermal engineers to
work directly with CAD designers and structural engineers on their
project, without having to be trained in their methods nor being
forced to learn and use tools that are inappropriate for thermal
For an explanation
of why RadCAD and the Thermal Desktop represent truly revolutionary
advances in concurrent thermal engineering, follow
Often we are
asked why SINDA/FLUINT has only one steady state and two transient
routines, while other codes have many more. This is an ILLUSION!
SINDA/FLUINT features many methods and variations built
into our routines, while other codes just offer different routines.
We believe that too many routines just adds confusion to the user,
by forcing the user to decide which routine is appropriate for each
of their models. It is like having 24 clocks and not knowing what
time it is, and having to look at all 24 before you know which ones
you can trust with EACH problem you try. We instead develop our
routines to work for EVERY model. SINDA/FLUINT gives the user the
default methods which normally work fine, and THEN the user can
play around with different options if you wish. In fact, the methods
themselves can be varied submodel by submodel, which cannot be done
in any other code. In other words, SINDA/FLUINT is easier to use
and STILL more flexible.
WITHIN our "one" steady state routine, the user can choose
PER SUBMODEL to have matrix methods or iterative methds, to have
Aitkin's acceleration or overrelaxation/damping or several types
of automatic overrelaxation etc. etc. So in fact, if you have only
two submodels, the user could create "solution routines"
that do not exist in other codes that offer no submodels. In other
codes, the user must pick ONE method and ONE set of criteria and
apply them to the WHOLE model blindly. So in fact, our code offers
almost an infinite number of methods or routines.
people combining models. If one used matrix method and one used
an iterative method, they are easily combined in SINDA/FLUINT: each
submodel can continue to use its own methods. But in other codes,
one method must "win" and an another must "lose",
and logic, control constants, etc. will all have to be revised to
try to get the "loser" to work in the new routine. This
is IN ADDITION to all the work needed to renumber the nodes, combine
two transient routines the use can choose iterative or matrix methods,
variable calls to temperature-dependent logic routines, different
accuracy levels, etc etc all PER SUBMODEL.
is also handled very easily in SINDA/FLUINT as an option that can
be easily turned on or off (even while the code is executing!) with
no changes to the model or to any logic.