C.H.A.T. - Evaluation of Testing

C.H.A.T.

Completed Prototype Testing Introduction

As of 2/23/25, we completed 20 testing trials of the Completed Prototype Test detailed on the "Testing Plan" page. We compiled the averages of all the tests into a single dataset, which we have shown below. For an easy direct comparison, we ran an identical testing cycle with an aluminum tube with no solution applied to it. The results are included in the table shown below. To see individual data of all 20 tests, please see the spreadsheet linked below, and use the tabs at the bottom to navigate to different tests.

Completed Prototype Testing Data

Completed Prototype Testing Reflection

Data Implications

Our data over the course of 20 trials showcases a significant change in temperature from the fish tank heaters with and without the solution applied to the aluminum tube. You can see a drop of roughly 15 degrees Celsius when you average the trials. Meanwhile, you can see the heat is well dispersed throughout the CubeSat as the internal and external temperatures are consistent throughout the course of our testing. The MLI blankets and silver teflon are also shown to be in effect as the radiation from the silver teflon is clearly working as the heat picked up from the sensor is significantly increasing over time, while the MLI stays steady around room temperature throughout the experiment. Our power test shows that over the course of our 20 trials, approximately 11 watts were dissipated over the course of a hour. This is a significant increase from the original 5 watts dissipated from fish tank heaters on a base aluminum tube, showing that our solution is allowing for the fish tank heaters to stay cool and produce more heat.

Potential Improvements

We plan to do a side by side comparison between testing a plain aluminum tube and our CubeSat with our solution to see the differences. We also want to further analyze the amperage consumed throughout our test by the fish tank heaters to see power cycles. This can lead to more analysis as to when the heaters are running so we can see when they tend to overheat, for how long, and more important data to improve our solution.

Full Testing data

Physical Testing Data

Completed Prototype Testing Procedure Analysis

Accuracy

Our testing was conducted with the highest degree of precision aligned with the "Completed Prototype Testing Procedure" detailed on the "Testing Plan" page. The largest sabotaging factors stem from the testing environment, like the ability to seal the insulated bag, the accuracy of the degree of contact with the sensors and CubeSat, and potential software bugs while recording the temperatures.

Repeatability

The testing procedure is repeatable multiple times as none of the equipment used in the testing is compromised or sabotaged with repeated trials. Repeating the test will have no negative effect on the integrity of the data that is collected as a result of it.

Silver Teflon Testing Introduction

As of 1/15/25, we completed 3 testing trials of the Silver Teflon Test detailed on the "Testing Plan" page. This data, along with its analysis and interpretation, is shown below. As this testing took place well before the prototype was completed, we went over ways to improve our design as a result of data evaluation, as well as the many reasons why our testing occurs the way that it does.

Silver Teflon Testing Data

Silver Teflon Testing Procedure Analysis

Accuracy

Our testing was conducted with the highest degree of precision aligned with the "Silver Teflon Testing Procedure" detailed on the "Testing Plan" page. The largest sabotaging factors stem from the testing environment and software. This includes room temperature, the temperature at which the Silver Teflon was stored, imperfections along the surface of the Teflon tape, and temperature recording errors from the software.

Repeatability

Silver Teflon Testing Reflection

Data Implications

By determining the heat buildup of the Silver Teflon versus the heaters, we were able to gauge the overall emissivity of the Silver Teflon. As shown in the graph, the Silver Teflon manages to keep its temperatures very close to those of the Fishtank Heater, thus proving that it is a good conductor of heat and able to emit a large portion of the heat generated by internal components.

MLI Blanket Testing Introduction

As of 1/9/25, we completed 3 testing trials of the MLI Blanket Test detailed on the "Testing Plan" page. This data, along with the analysis and interpretation of it, is shown below. As this testing took place well before the prototype was completed, we went over ways to improve our design as a result of data evaluation, as well as the many reasons why our testing occurs the way that it does.

MLI Blanket Testing Data

MLI Blanket Testing Procedure Analysis

Accuracy

Our testing was conducted with the highest degree of precision aligned with the "MLI Blanket Testing Procedure" detailed on the "Testing Plan" page. The largest sabotaging factors stem from the testing environment and software. This includes room temperature, the temperature at which the blankets were stored, and temperature recording errors from the software.

Repeatability

MLI Blanket Testing Reflection

Data Implications

By determining the heat buildup of the MLI blanket versus the heaters, we were able to gauge the overall resistivity to the heat of the MLI blankets. We can evaluate the blanket's thermal performance, determine its effectiveness in limiting heat transfer, and identify whether it meets the required specifications. This information is crucial for refining and certifying the validity of our design and ensures that the CubeSat maintains optimal internal temperatures in space.

Potential Improvements

Since we know that the MLI Blankets effectively dissipate incoming heat, a potential way to improve our design would be to add more layers to the blanket. However, with this improvement, we must keep in mind the design criteria and continue to align our dimensions with the respective dimensions of the CubeSat deployer.

Conclusion

Why is a design solution to a technical problem an iterative process?

A design solution to a technical problem is an iterative process because it involves continuously testing, evaluating, and improving ideas to address the problem. Each iteration helps identify flaws or areas for improvement, allowing us to refine the solution until it meets the desired goals and performs as we intended it to.

What is the purpose of evaluating test results?

The purpose of evaluating our test results is to determine whether our solution works and meets the design criteria. It helps identify strengths and weaknesses that guide us in refining our solution to make it more effective.

Expert Evaluation

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