Publications

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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.

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

Optimization, Data Correlation, and Parametric Analysis Features in SINDA/FLUINT Version 4.0

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

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:

Beyond Point Design Evaluation

Publication: NewOsummary.pdf

Source: ASME

Author: Brent A. Cullimore

Year: 2001

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

Dealing with Uncertainties and Variations in Thermal Design

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)

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

Automated Determination of Worst-case Design Scenarios

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

Parametric Thermal Analysis and Optimization Using Thermal Desktop

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

Nonlinear Programming Applied to Thermal and Fluid Design Optimization

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

Highlights in thermal engineering at Carlo Gavazzi Space

Publication: 17th_EWTES_MOLINA_FREQUENCYDOMAIN.pdf

Source: 17th Workshop on Thermal and ECLS Software-ESTEC

Author: Marco Molina, Christian Vettore

Year: 2003

Content Tags: third-party software, radks, heating rates

A CAD-based Tool for FDM and FEM Radiation and Conduction Modeling

Thermal engineering has long been left out of the concurrent engineering environment dominated by CAD (computer aided design) and FEM (finite element method) software.  Current tools attempt to force the thermal design process into an environment primarily created to support structural analysis, which results in inappropriate thermal models. As a result, many thermal engineers either build models “by hand” or use geometric user interfaces that are separate from and have little useful connection, if any, to CAD and FEM systems.

This paper describes the development of a new thermal design environment called the Thermal Desktop. This system, while fully integrated into a neutral, low-cost CAD system, and which utilizes both FEM and FD methods, does not compromise the needs of the thermal engineer. Rather, the features needed for concurrent thermal analysis are specifically addressed by combining traditional parametric surface-based radiation and FD based conduction modeling with CAD and FEM methods. The use of flexible and familiar temperature solvers such as SINDA/FLUINT is retained.

Publication: ices-98es-51.pdf

Source: ASME

Author: Tim Panczak, Steve Ring, Mark Welch

Year: 1997

Content Tags: finite element, finite difference, concurrent engineering, heater, heatpipe, heat pipe, radiation analysis groups, optical properties, Phenomena, refraction, scaffolding, CAD geometry, layers, expression editor, solver, mesh, mesher, structural mesh, ray tracing, boundary conditions, thermal stress, radiator, conductance, batteries, orbital heating, mli, multi-layer insulation, radks, articulation, articulating