Advancements in satellite technologies are increasing the power density of electronics and payloads. When the power consumption increases within a limited volume, waste heat generation also increases and this necessitates a proper and efficient thermal management system. Mostly, micro and nanosatellites use passive thermal control methods because of the low cost, no additional power requirement, ease of implementation, and better thermal performance. Passive methods lack the ability to meet certain thermal requirements on larger and smaller satellite platforms. This work numerically studies the performance of some of the passive thermal control techniques such as thermal straps, surface coatings, multi-layer insulation (MLI), and radiators for a 6U small satellite configuration carrying a mid-wave infrared (MWIR) payload whose temperature needs to be cooled down to 100K. Infrared (IR) imagers require low temperature, and the level of cooling is entirely dependent on the infrared wavelengths. These instruments are used for various applications including Earth observations, defence, and imaging at IR wavelengths. To achieve these low temperatures on such instruments, a micro-cryocooler is considered in this study. Most of the higher heat dissipating elements in the satellite are mounted to a heat exchanger plate, which is thermally coupled to an external radiator using thermal straps and heat pipes. The effects of the radiator size, orbital inclinations, space environments, satellite attitude with respect to the sun, and surface coatings are discussed elaborately for a 6U satellite configuration.

Publication: applsci-12-02858.pdf

Source: Applied Sciences, 2022, 12(6), 2858

Author: Shanmugasundaram Selvadurai, Amal Chandran, David Valentini, and Bret Lamprecht

Year: 2022

Content Tags: mli, multi-layer insulation, surface elements, surface coating a mesh, radiator, phase change material, thermocouples, finite element, finite elements, convergence, material properties, properties, CCHP

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 application of the general purpose SINDA/FLUINT thermohydraulic analyzer to the modeling of vapor compression (VC) cycles such as those commonly used in automotive climate control and building HVAC systems. The software is able to simulate transient operation of vapor compression cycles, predicting pressures, coefficients of performance, and condenser/evaporator liquid positions in a closed two-phase system with a fixed fluid charge. The program can also be used to size components, to estimate the impact of tolerances and other variations, and to help estimate uncertainties given limited test data.

SINDA/FLUINT has a user base numbering in the thousands. It has several graphical user interfaces, preprocessors, and postprocessors; has strong links to CAD and structural tools; and has built-in optimization, data correlation, parametric analysis, reliability estimation, and robust design tools.

Nonetheless, widespread application to vapor compression cycles is comparatively recent (Ref 2), and is largely due to an increased demand for transient modeling of air conditioning systems. Toward this requirement, SINDA/FLUINT’s unique abilities to analyze transient two-phase phenomena have been recognized as being critical to achieving accurate performance predictions.

Publication: vc.pdf

Source: ICES

Author: Brent A. Cullimore

Year: 2000

Content Tags: condensers, evaporator, registers, evaporators, slip flow, orifices, valves, capillary tubes, parameterizing, parametric analysis, reliability engineering, robust design, model correlation, vapor compression, compressor, parametric, parameterize, solver, transient

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

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

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