SINDA/FLUINT (Ref 1-7) is the NASA-standard heat transfer and fluid flow analyzer for thermal control systems. Because of its general formulation, it is also used in other aerospace specialties such as environmental control (ECLSS) and liquid propulsion, and in terrestrial industries such as electronics packaging, refrigeration, power generation, and transportation industries.

SINDA/FLUINT is used to design and simulate thermal/fluid systems that can be represented in networks corresponding to finite difference, finite element, and/or lumped parameter equations. In addition to conduction, convection, and radiation heat transfer, the program can model steady or unsteady single- and two-phase flow networks.

C&R’s SinapsPlus® is a complete graphical user interface (preand postprocessor) and interactive model debugging environment for SINDA/FLUINT (Ref 8, 9). SinapsPlus also supports the C language in addition to the traditional choice of Fortran for concurrently executed user logic.

This paper describes revolutionary advances in SINDA/FLUINT, the NASA-standard heat transfer and fluid flow analyzer, changing it from a traditional point-design simulator into a tool that can help shape preliminary designs, rapidly perform parametrics and sensitivity studies, and even correlate modeling uncertainties using available test data.

Innovations include the incorporation of a complete spreadsheet-like module that allows users to centralize and automate model changes, even while thermal/fluid solutions are in progress. This feature reduces training time by eliminating many archaic options, and encourages the performance of parametrics and other what-if analyses that help engineers develop an intuitive understanding of their designs and how they are modeled.

The more revolutionary enhancement, though, is the complete integration of a nonlinear programming module that enables users to perform formal design optimization tasks such as weight minimization or performance maximization. The user can select any number of design variables and may apply any number of arbitrarily complex constraints to the optimization. This capability also can be used to find the best fit to available test data, automating a laborious but important task: the correlation of modeling uncertainties such as optical properties, contact conductances, as-built insulation performance, natural convection coefficients, etc.

Finally, this paper presents an overview of related developments that, coupled with the optimization capabilities, further enhance the power of the whole package.

Publication: sfpaper.pdf

Source: IECEC

Author: Brent A. Cullimore

Year: 1998

Content Tags: design optimization, model correlation, parameterize, parametric, two-phase flow, two-phase, optical properties, submodels, registers, expression editor, user logic, concurrent engineering, concurrent design, dynamic mode, dynamic SINDA, specific heat, solver, constraint, slip flow, Phenomena, capillary systems, mixtures, working fluids, nonequilibrium, vapor compression, uncertainty, uncertainty analysis

This paper describes revolutionary advances in SINDA/FLUINT, the NASA-standard heat transfer and fluid flow analyzer, changing it from a traditional point-design simulator into a tool that can help shape preliminary designs, rapidly perform parametrics and sensitivity studies, and even correlate modeling uncertainties using available test data.

Innovations include the incorporation of a complete spreadsheet-like module that allows users to centralize and automate model changes, even while thermal/fluid solutions are in progress. This feature reduces training time by eliminating many archaic options, and encourages the performance of parametrics and other what-if analyses that help engineers develop an intuitive understanding of their designs and how they are modeled.

The more revolutionary enhancement, though, is the complete integration of a nonlinear programming module that enables users to perform formal design optimization tasks such as weight minimization or performance maximization. The user can select any number of design variables and may apply any number of arbitrarily complex constraints to the optimization. This capability also can be used to find the best fit to available test data, automating a laborious but important task: the correlation of modeling uncertainties such as optical properties, contact conductances, as-built insulation performance, natural convection coefficients, etc.

Finally, this paper presents an overview of related developments that, coupled with the optimization capabilities, further enhance the power of the whole package.

Publication: sf981574.pdf

Source: ICES 1998

Author: Brent A. Cullimore

Year: 1998

Content Tags: design optimization, model correlation, parameterize, parametric, two-phase flow, two-phase, optical properties, submodels, registers, expression editor, user logic, concurrent engineering, concurrent design, dynamic mode, dynamic SINDA, specific heat, solver, constraint, slip flow, Phenomena, capillary systems, mixtures, working fluids, nonequilibrium, vapor compression, uncertainty, uncertainty analysis

Optimization and Automated Data Correlation in the NASA Standard Thermal/Fluid System Analyzer

SINDA/FLUINT (Ref 1-7) is the NASA-standard heat transfer and fluid flow analyzer for thermal control systems. Because of its general formulation, it is also used in other aerospace specialties such as environmental control (ECLSS) and liquid propulsion, and in terrestrial industries such as electronics packaging, refrigeration, power generation, and transportation industries. SINDA/FLUINT is used to design and simulate thermal/fluid systems that can be represented in networks corresponding to finite difference, finite element, and/or lumped parameter equations. In addition to conduction, convection, and radiation heat transfer, the program can model steady or unsteady single- and two-phase flow networks. CRTech's SinapsPlus® is a complete graphical user interface (preand postprocessor) and interactive model debugging environment for SINDA/FLUINT (Ref 8, 9). SinapsPlus also supports the C language in addition to the traditional choice of Fortran for concurrently executed user logic. This paper describes revolutionary advances in SINDA/FLUINT, the NASA-standard heat transfer and fluid flow analyzer, changing it from a traditional point-design simulator into a tool that can help shape preliminary designs, rapidly perform parametrics and sensitivity studies, and even correlate modeling uncertainties using available test data. Innovations include the incorporation of a complete spreadsheet-like module that allows users to centralize and automate model changes, even while thermal/fluid solutions are in progress. This feature reduces training time by eliminating many archaic options, and encourages the performance of parametrics and other what-if analyses that help engineers develop an intuitive understanding of their designs and how they are modeled. The more revolutionary enhancement, though, is the complete integration of a nonlinear programming module that enables users to perform formal design optimization tasks such as weight minimization or performance maximization. The user can select any number of design variables and may apply any number of arbitrarily complex constraints to the optimization. This capability also can be used to find the best fit to available test data, automating a laborious but important task: the correlation of modeling uncertainties such as optical properties, contact conductances, as-built insulation performance, natural convection coefficients, etc. Finally, this paper presents an overview of related developments that, coupled with the optimization capabilities, further enhance the power of the whole package.

Publication: sfpaper.pdf

Source: IECEC 1998

Author: Brent A. Cullimore

Year: 1998

Content Tags:

Recent years have witnessed more improvement to the SINDA/FLUINT thermohydraulic analyzer than at any other time in its long history. These improvements have included not only expansions in analytic power, but also the additions of high-level modules that offer revolutions in thermal/ fluid engineering itself.

One such high-level module, “Reliability Engineering,” is described in this paper. Reliability Engineering means considering tolerances in design parameters, uncertainties in environments, uncertainties in application (e.g. usage scenarios), and variations in manufacturing as the stochastic phenomena that they are. Using this approach, the probability that a design will achieve its required performance (i.e., the reliability) is calculated, providing an assessment of risk or confidence in the design, and quantifying the amount of over- or under-design present.

The design to be evaluated for reliability will likely have been produced using traditional methods. Possibly, the design was generated using the Solver optimizer, another high-level module available in SINDA/FLUINT. Using design optimization, the user quantifies the goals that make one design better than another (mass, efficiency, etc.), and specifies the thresholds or requirements which render a given design viable or useless (exceeding a performance limit, etc.). SINDA/FLUINT then automatically searches for an optimal design.

Robust Design means factoring reliability into the development of the design itself: designing for a target reliability and thereby avoiding either costly over-design or dangerous under-design in the first place. Such an approach eliminates a deterministic stack-up of tolerances, worst-case scenarios, safety factors, and margins that have been the traditional approaches for treating uncertainties.

In any real system or product, heat transfer and fluid flow play a limited role: there are many other aspects to a successful design than the realm of thermal/fluids that is encompassed by SINDA/FLUINT. Therefore, this paper concludes with brief descriptions of methods for performing interdisciplinary design tasks.

Publication: releng1.pdf

Source: CRTech White Paper

Author: Brent A. Cullimore

Year: 2000

Content Tags: design optimization, reliability engineering, robust design, constraints, boundary conditions, concurrent design, concurrent engineering, batteries, flow control, orifices, radiator, registers, two-phase flow, solver, model correlation, dynamic SINDA, dynamic mode, variables, Monte Carlo, material properties, third-party software, uncertainty analysis, uncertainty

This paper describes the need for dynamic (transient) simulation of automotive air conditioning systems, the reasons why such simulations are challenging, and the applicability of a general purpose off-the-shelf thermohydraulic analyzer to answer such challenges.

An overview of modeling methods for the basic components are presented, along with relevant approximations and their effect on speed and accuracy of the results.

Publication: vtms2001.pdf

Source: VTMS

Author: Brent A. Cullimore, Terry J. Hendricks

Year: 2001

Content Tags: compressor, evaporator, evaporators, condensers, slip flow, working fluids, registers, vapor compression, throttle, capillary tube, choked

Modeling lessons learned form Ford, Visteon, GM, Delpi, Danfoss, etc.

Publication: VCimaps.pps

Source: ITherm

Author: Brent Cullimore

Year: 2002

Content Tags: vapor compression, compressor, two-phase heat transfer, evaporator, condenser, parametric, slip flow, finite difference

The National Renewable Energy Laboratory (NREL) and U.S. Department of Energy (DOE) are interested in developing more efficient vehicle air conditioning (A/C) systems to reduce fuel consumption in advanced vehicle designs. Vehicle A/C systems utilizing electrically-driven compressors are one possible system design approach to increasing A/C system performance over various drive cycle conditions. NREL’s transient A/C system model was used to perform multivariable design optimization of electrically-driven compressor A/C systems, in which five to seven system design variables were simultaneously optimized to maximize A/C system performance. Design optimization results demonstrate that significant improvements in system COP are possible, particularly system COP > 3, in a properly optimized system design with dynamically-controlled operation. System optimization analyses investigated dynamic A/C system design strategies employing dual-compressor-speeds in electrically-driven systems to evaluate their effects on system performance. A system optimization methodology was developed which can systematically quantify impacts on A/C system design and performance resulting from varying degrees of design influence being given to widely different design objectives. The technique is based upon formulating optimization objective functions from linear combinations of critical design performance parameters that characterize independent design goals. It was demonstrated here by giving varying degrees of design influence to maximizing system COP and maximizing evaporator cooling capacity over SC03 and US06 drive cycles.

Publication: C599-061.pdf

Source: NREL

Author: T. Hendricks

Year: 2003

Content Tags: design optimization, compressor, condenser, evaporator, expansion, system-level modeling, design variables

This paper describes a vehicle-level simulation model for climate control and powertrain cooling developed and currently utilized at GM. The tool was developed in response to GM's need to speed vehicle development for HVAC and powertrain cooling to meet world-class program execution timing (18 to 24 month vehicle development cycles). At the same time the simulation tool had to complement GM's strategy to move additional engineering responsibility to its HVAC suppliers. This simulation tool called "e-Thermal" was quickly developed and currently is in widespread (global) use across GM. This paper describes GM's objectives and requirements for developing e-Thermal. The structure of the tool and the capabilities of the simulation tool modules (refrigeration, front end airflow, passenger compartment, engine, transmission, Interior air handling …) is introduced. Model data requirements and GM's strategy for acquiring component data are also described. The paper includes an example of a typical application of the tool with sample output from the simulation and some comparison to actual test data from a vehicle under the same test scenario.

Publication: 2004-01-1510.pdf

Source: SAE Technical Paper Series

Author: Todd M. Tumas, Balaji Maniam, Milind Mahajan, Gaurav Anand, Nagendra Jain

Year: 2004

Content Tags: Components, heat exchangers, system-level modeling, third-party software, refrigeration cycles, model correlation

e-Thermal is a vehicle level thermal analysis tool developed by General Motors to simulate the transient performance of the entire vehicle HVAC and Powertrain cooling system. It is currently in widespread (global) use across GM. This paper discusses the details of the airconditioning module of e-Thermal. Most of the literature available on transient modeling of the air conditioning systems is based on finite difference approach that require large simulation times. This has been overcome by appropriately modeling the components using Sinda/Fluint. The basic components of automotive air conditioning system, evaporator, condenser, compressor and expansion valve, are parametrically modeled in Sinda/Fluint. For each component, physical characteristics and performance data is collected in form of component data standards. This performance data is used to curve fit parameters that then reproduce the component performance. These components are then integrated together to form various A/C system configurations including orifice tube systems, txv systems and dual evaporator systems. The A/C subsystem uses airflow rates, temperatures, humidity’s and compressor speed as inputs. The outputs include overall system energy balance, system COP, refrigerant flow rates and system pressures. The A/C simulation runs about three times faster to three times slower than real time. The modeling technique used is also capable of tracking the effect of system charge on the overall system performance. A database of automotive air conditioning components accompanies the simulation tool. This database is then integrated in e-Thermal to provide the component data for modeling. Validation results for component level models are demonstrated. They form the basis of system level models. System level validation is also demonstrated. The simulation times vary from 3 times faster than real time to 5 times slower than real time depending on the nature of the simulation.

Publication: 2004-01-1509.pdf

Source: SAE Technical Paper Series

Author: Gaurav Anand, Milind Mahajan, Nagendra Jain, Balaji Maniam, Todd M. Tumas

Year: 2004

Content Tags: parametric, two-phase flow, two-phase, Components, heat exchangers, compressor, condenser, evaporator, expansion, system-level modeling, third-party software, refrigeration cycles, model correlation

Publication: aerospace2005heatpipes.pps

Source: Aerospace Thermal Control Workshop

Author: Brent Cullimore, Jane Baumann

Year: 2005

Content Tags: LHP, Loop Heat Pipe, radiation analysis groups, concurrent engineering, heat pipe, system-level modeling, noncondensable gas, VCHP, CCHP, wall, two-phase heat transfer, two-phase flow, condenser, condensers, evaporator, evaporators