Conducting a thermal tooling survey on three complex tools of different materials - C105

 

Conducting a thermal tooling survey on three complex tools of different materials
Case study
Infrared image compared with a standard camera of an aluminum tool after heating.
Document Type	Case study
Document Identifier	105
Themes	Thermal management
Tags	Convective heating Heat transfer System control Tooling Thermal properties Tooling parameters
Objective functions	Cost Maintain Rate Maintain Quality Increase
MSTE workflow	Development
Prerequisites	Convection Effect of tooling in a thermal management system Ensuring tooling choice meets part quality metrics Specific heat capacity Thermal conductivity Thermal diffusivity Troubleshooting tooling to achieve part quality

Summary

As part of a Canadian Composites Manufacturing Research and Development consortium (CCMRD) project, the Composite Research Network (CRN) along with Convergent Manufacturing Technologies performed a thermal tooling survey on three different tools. The goal of the project was to study the effect of tooling material, tooling geometry, and autoclave airflow on the overall thermal response of the tools. Currently this case study only touches on the former two effects, with the effect of autoclave airflow to come soon.

Through this project, researchers were able to demonstrate the applicability and generality of fundamental principles, such as thermal mass and thermal diffusivity, to describe the thermal response of complex tools. Moreover, they were able to replicate these results using simulation software.

Challenge

Tools, and especially large tools, play a significant role in controlling the thermal response of the part. Understanding of how a tool will heat up, where the hot and cold spots will be, and what the temperature gradients may look like are features one may not consider when designing or selecting tooling. However, such information plays a huge role during manufacturing when the part is sitting on the tool. Demonstrating how fundamental principles and simulation software can be used to to provide an understanding of such phenomena was paramount to this project.

Prerequisites

Recommended documents to review before, or in parallel with this document:

• Effect of tooling in a thermal management system
• Thermal diffusivity
• Specific heat capacity
• Thermal conductivity
• Convection

To learn more about tooling choice on the part quality metrics from a development and troubleshooting perspective, click on the following links:

• Ensuring tooling choice meets part quality metrics
• Troubleshooting tooling to achieve part quality

Approach

Three c-shaped tools were placed in an autoclave and run through a thermal cycle to investigate their respective temperature distributions upon heating. Each tool had the same geometry but was constructed of a different material; invar, carbon-fibre reinforced polymer (CFRP) composite, and aluminum. Images of each of the tools and their thermal properties are shown below.

Tools used with their respective material properties

The temperature and pressure cycles that the tools were subject to, along with the airflow patterns are provided below. Thermocouples (TCs) were placed along the tools in order to measure their temperature at various locations. To get a visual depiction of the temperature distribution, the autoclave door was opened immediately after each test and a FLIR t620 infrared (IR) camera was used to take a thermal image of the tools. Each tool was covered with a vacuum bag painted with a flat and non-reflective black paint to increase accuracy of the IR measurements. An emissivity of 0.97 was assumed for each tool.

Experimental conditions.

Processing conditions	Settings
Temperature cycle	5°C/min to 100°C (ramp only) 5°C/min to 100°C, hold for 30 mins (ramp + 30 min hold) 5°C/min to 100°C, hold for 60 mins (ramp + 60 min hold)
Pressure cycle	Vacuum pressure only (101 kPa) Vacuum pressure (101 kPa) and 85 psi external pressure (586 kPa)
Airflow pattern	Unmodified airflow Modified airflow by adding aluminum sheets

Thermal simulations of the tools for the ramp only experiments were performed using Abaqus 6.14 implicit solver, taking only the processing conditions, material properties, and geometrical features of the tools into account. DC3D4 heat transfer elements were used with the air temperature and heat transfer coefficients (HTCs) determined from the experiments. The goal here was to show that simulation software can accurately predict the thermal response of complex tooling. The material properties used for the model are included in the table below:

Material properties for simulations.

	Density (kg/m3)	Specific heat capacity (J/kgK)	Through-thickness thermal conductivity (W/mK)	Thermal diffusivity (m2/s)
Invar	8000	515	11.0	2.67 x 10-6
Composite	1580	870	0.7	0.5 x 10-6
Aluminum	2710	896	167	68.9 x 10-6

Note that in the case study presented here, currently the modified airflow and pressurized results are not shown. These aspects of the case study are coming soon.

Outcomes

The experimental results from the thermocouple data and IR camera are provided in the images below. Three major points to note from the ramp only test are that the composite tool reached the highest temperature (78°C) with the largest thermal gradient across its facesheet (27°C). The invar tool on the other hand displayed the coldest maximum and minimum temperature at 59°C and 40°C respectively. Meanwhile, the aluminum tool presented the lowest thermal gradient of the three tools with a temperature spread of only 13°C over its facesheet.

Thermocouple data from ramp only test.

These results confirm the expected behaviour of these tools based on their material properties. The composite tool has the lowest thermal mass and therefore requires the least energy to raise its temperature. As a result, it achieves the highest temperature of the three tools. In contrast, the invar tool has the highest thermal mass and therefore requires the most energy to raise its temperature. This, therefore, results in it having the lowest temperature of the three tools. With regards to temperature distribution, the composite tool's low thermal conductivity gives it the lowest thermal diffusivity of the three tools. Therefore, heat does not flow as easy through the composite tool, resulting in the large spread in temperature seen in this tool. The aluminum tool on the other hand has a similar specific heat capacity to the composite tool, a thermal mass that is about 3x higher, but a thermal conductivity that is 240x larger. This gives it a significantly higher thermal diffusivity as compared with the composite and the highest thermal diffusivity of the three tools. Hence, why it displays the most uniform temperature distribution.

IR results from ramp only and ramp + 30 min hold tests.

With the added 30 minute hold, the additional time allows for the thermal response of the tools to be much more similar. However, commonalities with the pure ramp test are still seen between the three tools. The composite tool is still the hottest (although only slightly), the invar tool is still the coldest, and the aluminum tool still has the lowest thermal gradient (though again only slightly). The only change is that the invar tool now displays the greatest thermal gradient, rather than the composite. This has to do with the difference in thermal mass between the two tools. Although the thermal diffusivity of the invar may be higher, its high thermal mass means that the tool requires additional time for it to heat up. Therefore, its thermal response is relatively stable. For the composite, however, while heat may distribute relatively poorly through the tool, it does not take as much energy to raise its temperature at any given point. This also means that it is more responsive to the environmental conditions. Therefore, the tool heats up relatively quickly, allowing the initially "cold" areas to catch up with the already warm areas.

While not shown here, with an added 60 minute hold following the ramp, all the tools achieve more or less the same temperature distribution.

A comparison between the experimental and simulation results of the ramp only experiments are shown in the image below. The simulation results show a good agreement with the experimental results. This validates the use of fundamental principles to predict the thermal response of complex tools. The effect of the geometrical complexities on the thermal response of the tools is captured in both the experiments and simulations. Note that in order to provide a good contrast on the simulation images the temperature scale was plotted between 25°C and 85°C. The previous IR images had the scale between 20°C and 100°C, hence why the colour distribution seems slightly different in these images.

Comparison between experimental and simulation results for ramp only test.

For each tool, the warmest zones are near the back, on the facesheet. This is a result of the airflow distribution in the autoclave, with the highest impinging airflow occuring at the back of the tool, thus raising the local heat transfer coefficient (HTC) over this zone. Similarly, the tooling substructure is the coldest due to a lack of airflow (low HTC) in these regions. It is common for the underside of tools to have a lower HTC as a result of poor airflow. Moreover, cavities (such as that seen on the right hand side of the tool) also limit airflow and thus have a reduced HTC. That said, while the cavity may have less airflow than the topside of the tool, without this cavity there would be no airflow through that region. This is the difference between an open and closed substructure. Therefore, while the cavity reduces airflow compared to the open facesheet, it increases airflow compared to a closed substructure and thus helps the HTC in that region. Furthermore, the open substructure reduced the thermal mass of the tool, allowing that region to respond quicker to thermal conditions than it otherwise would if it were a solid block.

To learn more about the effect of open and closed substructures on the thermal response of the tool and part, or to learn more about the effect of the HTC, click on the following links.

• Tooling configuration and part/tool thermal response
• HTC effect on part thermal response

Related pages

Page type	Links
Introduction to Composites Articles
Foundational Knowledge Articles
Foundational Knowledge Method Documents
Foundational Knowledge Worked Examples
Systems Knowledge Articles	Effect of tooling in a RSDM system - A277
Systems Knowledge Method Documents
Systems Knowledge Worked Examples
Systems Catalogue Articles
Systems Catalogue Objects – Material
Systems Catalogue Objects – Shape
Systems Catalogue Objects – Tooling and consumables
Systems Catalogue Objects – Equipment
Practice Documents	Developing production scale tooling - P129 Ensuring tooling choice meets part quality metrics - P128 Transitioning tooling styles between different thermal transformation equipment - P139 Troubleshooting tooling to achieve part quality - P142 Troubleshooting when changing production tooling material - P130
Case Studies	Conducting a thermal tooling survey on three complex tools of different materials - C105 Developing for Future Production Scale Up - C113 Use of Right Sized Simulation to Aid Decision Making in Thermoplastic Composite Manufacturing Systems - C114
Perspectives Articles

References

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A quantitative measure of how a material will respond to transient thermal conditions. It is defined as the ratio of thermal conductivity to the volumetric heat capacity of the material (density times the specific heat capacity).

Materials with large thermal diffusivity have a high thermal conductivity relative to their capacity to store energy (heat capacity) and will rapidly distribute the thermal energy throughout its volume and rapidly change temperature to reach the new equilibrium temperature.

Materials with small thermal diffusivity have a low thermal conductivity relative to their capacity to store energy (heat capacity) and will have a sluggish temperature response to a change in thermal conditions (large temperature lag). This is because it takes more energy per unit volume to change the temperature, and the low thermal conductivity means it takes longer to distribute the thermal energy throughout its volume.

Engineered materials (designed to have specific properties) made from two or more constituent materials with different physical or chemical properties. The constituents remain separate and distinct on a macroscopic level within the finished structure.