Abstract
The present article describes how to support a development project by heat and fluid simulation in all project stages in the example of the development of an electric wheel hub drive unit. The project starts at a low know-how level in the planning stage, which is then enhanced continually by simulation. A detailed and adapted simulation model will then be available with the finished product. The process chain - simple calculation, design, testing, detailed model, design, testing, is repeatedly carried out during the project. Finally, a design proposal for the cooling system of a city bus is shown.

Publication: Heatsimulation During the Development of a Bus E-Drive, Altvater and Boch, 2003.pdf

Source: Verein Deutscher Ingenieure (VDI) Berichte

Author: Dipl.-Ing. (FH) R. Altvater, Dipl-Ing. (FH) P. Boch, ZF Friedrichshafen AG, Friedrichshafen

Year: 2003

Content Tags:

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:

Publication: NewOsummary.pdf

Source: ASME

Author: Brent A. Cullimore

Year: 2001

Content Tags: model calibration, CFD, parametric, design optimization, design synthesis, Phenomena

The major influence on the reliability of electronics is temperature, yet thermal/fluid modeling is plagued with uncertainties and unknowns. Nonetheless, if appropriate values of these unknown parameters are available for any specific electronics package, then its temperature response can be accurately predicted using modern thermal/fluid analysis tools.

Traditionally, uncertainties are dealt with by a combination of testing, safety factors or margins, and worst-case design scenarios. Analyses are performed iteratively in a repetitive “point design evaluation” mode. Computer-based design simulation tools have emphasized increasing detail and fidelity to physical phenomena, seemingly ignoring the fact that the inputs to these simulations are highly uncertain.

This paper describes both current and future methods of dealing with uncertainties in thermal engineering. It introduces advanced tools and alternative methodologies that can automate not only the quantification of reliability, but can also help synthesize designs on the basis of reliability. It advocates using rapid gains in computer speed not to increase the degree of detail in a model, but to help the engineer find a robust design by automating high-level design tasks.

Publication: IPACK2001-15516.pdf

Source: InterPack

Author: Brent A. Cullimore

Year: 2001

Content Tags: parameterize, parametric, contact conductance, design synthesis, Phenomena, robust design, design optimization, design variables, reliability engineering

Nonlinear Programming Applied to Calibrating Thermal and Fluid Models to Test Data (Semi-Therm 2002)

Publication: calibrating.pdf

Source: Semi-Therm

Author: Jane Baumann, Brent Cullimore

Year: 2002

Content Tags: model calibration, model correlation, condenser, condensers, validation, design optimization, parametric

This paper describes readily available techniques for automating the search for worst-case (e.g., “hot case”, “cold case”) design scenarios using only modest computational resources. These methods not only streamline a repetitive yet crucial task, they usually produce better results.

The problems with prior approaches are summarized, then the improvements are demonstrated via a simplified example that is analyzed using various approaches. Finally, areas for further automation are outlined, including attacking the entire design problem at a higher-level.

Publication: WorstCase-ICES.pdf

Source: ICES

Author: B. Cullimore

Year: 2003

Content Tags: parametric, model correlation, design optimization, convergence

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

Active cooling technologies such as heat pipes, loop heat pipes (LHPs), thermosyphons, loop thermosyphons (LTSs), and pumped single- or two-phase coolant loops require specialized modeling treatment. However, these 1D ducted systems are largely overlooked in 3D thermal modeling tools. The increasing popularity of CFD and FEM models and generation of analysis data from 3D CAD data are strong trends in the thermal analysis community, but most software answering such demands has not provided linear modeling elements appropriate for the simulation of heat pipes and coolant loops.

This paper describes techniques whereby CAD line-drawing methods can be used to quickly generate 1D fluid models of heat pipes and coolant loops within a 3D thermal model. These arcs and lines can be attached intimately or via linear contact or saddle resistances to plates and other surfaces, whether those surfaces are modeled using thermal finite difference methods (FDM), or finite element methods (FEM), or combinations of both. The fluid lines can also be manifolded and customized as needed to represent complex heat exchangers and plumbing arrangements. Furthermore, the assumption of 1D flow can be combined with 2D/3D models of walls, including advanced methods of extruding a complex 2D cross-section along a curved or mitered centerline.

To demonstrate these concepts, several distinct examples are developed and discussed.

Publication: FloCAD3-ICES.pdf

Source: ICES

Author: B. Cullimore, D. A. Johnson

Year: 2003

Content Tags: finite difference, heat pipe, Loop Heat Pipe, finite element, structural mesh, duct, noncondensible gas, condenser, wall

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

Thermal analysis is typically performed using a point design approach, where a single model is analyzed one analysis case at a time. Changes to the system design are analyzed by updating the thermal radiation and conduction models by hand, which can become a bottleneck when attempting to adopt a concurrent engineering approach. This paper presents the parametric modeling features that have been added to Thermal DesktopTM to support concurrent engineering. The thermal model may now be characterized by a set of design variables that are easily modified to reflect system level design changes. Geometric features, optical and material properties, and orbital elements may all be specified using user-defined variables and expressions. Furthermore, these variables may be automatically modified by Thermal Desktop’s optimization capabilities in order to satisfy user-defined design goals, or for correlating thermal models to test data. By sharing the set of design variables among analysis models spanning multiple disciplines, further integrated analysis and design may be accomplished. The framework into which Thermal Desktop is embedded in order to support an integrated Thermal/Structural/Optical design, analysis, and optimization system is also presented.

Publication: 00ICES-266.pdf

Source: ICES

Author: Timothy D. Panczak, Brent A. Cullimore

Year: 2000

Content Tags: concurrent engineering, parametric, parameterize, register, registers, dynamic mode, dynamic SINDA, symbol manager, expression editor, expressions, design optimization, orbital heating, model correlation, solver, optical properties, heat pipes, symbol, variables, case set manager, properties, structural

Historically, thermal/fluid modeling began as a means of validating and sometimes correcting passively cooled designs that had been proposed by nonspecialists in heat transfer and fluid flow. As dissipation fluxes have risen, and as air cooling reaches the limits of its usefulness, involvement of thermal engineers is required earlier in the design process. Thermal engineers are now commonly responsible for sizing and selecting active cooling components such as fans and heat sinks, and increasingly single and two-phase coolant loops.

Meanwhile, heat transfer and fluid flow design analysis software has matured, growing both in ease of use and in phenomenological modeling prowess. Unfortunately, most software retains a focus on point-design simulations and needs to do a better job of helping thermal engineers not only evaluate designs, but also investigate alternatives and even automate the search for optimal designs.

This paper shows how readily available nonlinear programming (NLP) techniques can be successfully applied to automating design synthesis activities, allowing the thermal engineer to approach the problem from a higher level of automation. This paper briefly introduces NLP concepts, and then demonstrates their application both to a simplified fin (extended surface) as well as a more realistic case: a finned heat sink.

Publication: Optimizing.pdf

Source: ITherm

Author: Brent A. Cullimore

Year: 2002

Content Tags: design optimization, parametric, design synthesis, design variables, variables, sink temperature