BFGoodrich Aerospace, Aircraft Sensors Division, achieves lowest drag ever on debris-guarded temperature sensor using computational fluid dynamics

Citation

(1998), "BFGoodrich Aerospace, Aircraft Sensors Division, achieves lowest drag ever on debris-guarded temperature sensor using computational fluid dynamics", Sensor Review, Vol. 18 No. 1. https://doi.org/10.1108/sr.1998.08718aaf.006

BFGoodrich Aerospace, Aircraft Sensors Division, achieves lowest drag ever on debris-guarded temperature sensor using computational fluid dynamics

BFGoodrich Aerospace, Aircraft Sensors Division, achieves lowest drag ever on debris-guarded temperature sensor using computational fluid dynamics

BFGoodrich Aerospace Aircraft Sensors Division engineers achieved their best-ever level of aerodynamic performance on a temperature sensor with a debris guard by using computational fluid dynamics (CFD) to optimise the design prior to prototyping. Meeting the conflicting needs of protecting the sensing element from debris and achieving the desired level of sensor accuracy and performance made this a very complex problem. CFD allowed engineers to evaluate the performance of 20 different design alternatives within the six-month lead time for the project. This made it possible to substantially reduce drag relative to current designs while meeting all accuracy and durability requirements. The traditional build-and-test method is so much more costly and time-consuming than CFD that it would have been impossible to evaluate anywhere near this number of alternatives using this approach.

The total temperature sensor is used on a military gas turbine aircraft engine. The complexity of the design problem was increased by the fact that the sensor is installed in the engine ductwork behind the turbofan and near other structures, which can disturb the flow approaching the sensor. The total temperature measurements provided by the sensor incorporate static temperature plus the kinetic energy in the airstream. This measurement can be used in conjunction with pressure measurements to calculate airspeed, and it is also used by test engineers and/or pilots in engine performance optimisation.

Cross-section of the sensor showing pressure fields. The flow can be seen moving from left to right with the darker area coming off the point showing lower pressure and the darker areas opposite each other on the sides showing higher pressure

The sensor consists of a platinum sensing element. Platinum has a linear resistance vs temperature curve and thus provides accurate thermal measurements. An aerodynamic housing surrounds the sensing element and a flow path directs air over the element. The sensor is designed to measure temperatures from ­60°F to 500°F. The original proposal specified a cylindrical cross-section for the strut used to support the sensor. Later it was decided to switch to a NACA airfoil configuration for the strut. One reason for this was to minimise drag and thus improve the efficiency of the engine. Another reason was to avoid vortex shedding and turbulence from the wake of the sensor going into the engine inlet.

In the past, the issue of defining the internal passages in the sensor would have been addressed by building and testing prototypes. This approach is time-consuming and expensive, thus limiting the number of different design iterations which could have been evaluated. Each prototype iteration takes several weeks and requires expensive manufacturing changes for each prototype design. More importantly, the information generated from each build-test iteration is very limited. Wind tunnel testing determines the overall effectiveness of the design in reducing drag but provides little insight into what design features are responsible for the problem.

For this reason, BFGoodrich Aircraft Sensors Division began using FLUENT CFD software from Fluent Inc., Lebanon, New Hampshire, about three years ago. Aircraft Sensors Division engineers began the analysis by building a physical model of the proposed strut, installing it in an engine, and testing it in a wind tunnel to determine pressure fields which were used as boundary conditions in the CFD analysis. Engineers created a 75,000-element CFD model of an earlier sensor without a debris guard which provided aerodynamic performance similar to what was desired on the new sensor. This was done in order to establish a baseline for the flow field and velocity contours which were required to provide desired sensor performance. A key advantage of CFD is that it provides detailed flow, velocity, and pressure information at every point within the domain of the problem. As a result, it generally provides a level of insight into the problem far beyond that which can be achieved using the conventional build and test approach.

The next step was producing a 75,000-element external model of the sensor installed in the engine in order to refine boundary conditions for the internal sensor model. Then engineers created a 75,000-element full-blown internal and external model of the sensor. A bit of creativity was used to simplify the model. Engineers ran a steady-state rather than a time dependent model for most simulations to reduce solution time. In the beginning, engineers ran the baseline model under both steady-state and time dependent conditions and came up with a percentage difference figure which was applied to the subsequent iterations. Engineers also incorporated particle tracking into some iterations in order to check the performance of the debris guard. The final simulation was evaluated under time-dependent conditions for maximum accuracy.

Measurement accuracy played a critical role in the design of the internal flow path. The two key factors are recovery error, which depicts the accuracy of the thermal measurement, and thermal response, which determines the speed at which temperature changes are detected. These two factors conflict with each other in that accuracy demands a slow flow over the sensor while immediate response requires a fast flow. The analysis results made it possible to estimate the response time and recovery error of each configuration by comparing the flow direction and speed to existing sensors whose performance was known.

The primary purpose of the analysis was positioning and shaping the configuration of the flow passage in the strut used to position the sensing element. Three or four different design variations were modelled at a time. The different design variations were evaluated to see how the flow, pressure, and velocity readings compared to the sensor whose drag matched the target drag level. Once the desired drag was achieved, engineers turned their attention to protecting the sensing element from dirt and debris. The analysis output clearly indicated the effectiveness of the different configurations of debris guards that were evaluated by showing how much area they blocked.

The results of the analysis were surprising. They helped to rule out some complexity in the design that turned out not to be needed. The first physical prototype met all aerodynamic design criteria and required only minor mechanical tweaking after wind tunnel testing. This was a major change from past practice when many prototype build and test iterations were required to meet specifications. Another difference in this project is that the CFD output provided the opportunity to try many more alternatives than normal and also a much better than usual understanding of how each alternative worked. This made it possible to optimise aerodynamic performance to a level that would otherwise not have been possible to achieve on this design. In the future, engineers plan to use these same type of performance sensitivity analysis studies based on potential dimensional variation and thus improve the robustness of the manufacturing process.

As a result of the success of this application, engineers are now using CFD not only to design individual products such as this one but also in shaping the technology used in entirely new product generations. Engineers have found that rather than replacing physical testing, CFD serves as a useful complement since pressure, temperature, and flow readings from testing can be directly correlated to the analysis. Derived measurements such as drag, error, and response time require a bit more creativity to obtain from analysis but excellent results have been achieved through correlations to models of earlier designs. Using CFD technology, BFGoodrich Aerospace Aircraft Sensors Division engineers expect to be able to significantly improve the aerodynamic performance of many of their current and future products.

For more information contact Fluent Europe, Holmwood House, Cortworth Road, Ecclesall, Sheffield S11 9LP, UK. Tel: +44 114 281 8888; Fax: +44 114 281 8818.