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Validation of the SINDA/FLUINT Thermal Analyzer Code Using Several Analytical Solutions

机译:使用几种分析解决方案验证SINDA / FLUINT热分析仪码

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The Systems Improved Numerical Differencing Analyzer and Fluid Integrator (SINDA/FLUINT) program is a thermal analyzer code which has frequently been used as a design and analysis tool, to determine the transient and steady-state response of various fluid flow and thermal networks. While this code has provided important information in the design and analysis of a variety of aerospace systems, the validation of the code has been limited to a few simple test cases, and did not examine the resistance-capacitance or fluid flow network solving capability of the code. For the current study, the predictions from several simple models were compared to their corresponding analytical solutions. The first comparison considered steady-state, one-dimensional heat conduction in a constant area fin with four different fin tip boundary conditions. The second portion of the study examined an infinitely long fin which rejects heat to the environment by a simultaneous convection and radiation process. The next segment of the study compared the predicted cooling of a cube with the results produced by the Heisler chart method. Two fluid flow situations were also considered. The first case examined the flow in a circular duct which connects two infinitely large pressure reservoirs. The second fluid flow case examined the filling of a tank which experiences both heat transfer and control volume work. The results of all these comparison studies showed that the code was able to predict temperatures within 0.5% of the analytical solutions.
机译:该系统改进了数值差分分析仪和流体积分器(SINDA / FLUINT)程序是经常被用作设计和分析工具的热分析仪代码,以确定各种流体流量和热网络的瞬态和稳态响应。虽然这段代码在各种航空航天系统的设计和分析中提供了重要信息,但代码的验证已被限制为几个简单的测试用例,并且没有检查电阻电容或流体流量网络求解能力代码。对于目前的研究,将几种简单模型的预测与其相应的分析解决方案进行了比较。第一个比较被认为是具有四个不同翅片尖端边界条件的恒定区域翅片中的稳态,一维导热。该研究的第二部分检查了一种无限的长翅片,通过同时对流和辐射过程拒绝对环境的热量。该研究的下一段与由Heisler图表方法产生的结果进行了预测的立方体冷却。还考虑了两个流体流动情况。第一种情况检查了连接两个无限大的压力储层的圆形管道中的流动。第二流体流动盒检查了经历传热和控制体积工作的罐的填充物。所有这些比较研究的结果表明,代码能够在分析解决方案的0.5%内预测温度。

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