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Altair > Case Studies > Thermal Analysis of LED Lamps Using AcuSolve: A DSM Case Study
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Thermal Analysis of LED Lamps Using AcuSolve: A DSM Case Study

Technology Category
  • Sensors - Temperature Sensors
  • Sensors - Utility Meters
Applicable Industries
  • Life Sciences
  • Plastics
Applicable Functions
  • Procurement
  • Product Research & Development
Use Cases
  • Last Mile Delivery
  • Smart Lighting
Services
  • Hardware Design & Engineering Services
  • Testing & Certification
The Challenge
DSM Engineering Plastics, a global provider of high-performance plastics, faced a challenge in the LED lighting applications sector. The heat sinks used in these applications, primarily made of aluminum, were responsible for dissipating heat generated by LEDs to the environment. However, aluminum, despite being a good heat conductor, had limitations such as high costs related to machining die-cast parts, limited design freedom, recyclability issues, and weight. DSM sought to provide a plastic-based solution for heat sinks to overcome these issues. To find an optimal design for the heat sink made of polymer material and predict its thermal performance, DSM needed to model natural convection and radiation cooling, the mechanisms by which LED heat sinks dissipate heat to the environment. The challenge was to find a tool that could accurately simulate these processes and provide reliable results.
About The Customer
DSM – Bright Science. Brighter Living.™ Royal DSM is a global science-based company active in health, nutrition, and materials. By connecting its unique competences in Life Sciences and Materials Sciences, DSM drives economic prosperity, environmental progress, and social advances to create sustainable value for all stakeholders. DSM delivers innovative solutions that nourish, protect, and improve performance in global markets such as food and dietary supplements, personal care, feed, pharmaceuticals, medical devices, automotive, paints, electrical and electronics, life protection, alternative energy, and bio-based materials. DSM’s 23,500 employees deliver annual net sales of about 9 billion Euros. The company is listed on NYSE Euronext.
The Solution
DSM implemented AcuSolve, a product of Altair Engineering, in its development processes. AcuSolve is a general-purpose Computational Fluid Dynamics (CFD) based software capable of modeling a variety of heat and flow problems. DSM used AcuSolve to model natural convection and radiation cooling. To evaluate the cooling capacity of a polymer heat sink, AcuSolve was used alongside other valuable CAE tools. AcuSolve was able to model heat loss by natural convection, taking into account the heat loss to the air flow around the heat sink due to density differences of the air in proximity to the heat sink surface. It also accounted for air flow stagnation due to boundary layer effects, particularly when a heat sink was designed with too small fin-to-fin spacing. Furthermore, AcuSolve was able to model radiation heat loss, taking into account view factors for different parts of the heat sink using the hemicube algorithm. This allowed for the optimization of the heat sink design to maximize radiative heat loss to the environment.
Operational Impact
  • The implementation of AcuSolve allowed DSM to accurately predict the thermal performance of heat sinks used in LED lighting applications. The results were satisfactory and enabled DSM to shift its development efforts from real testing to virtual development methods. This led to fewer prototypes and shorter development cycles, resulting in reduced development costs. The use of AcuSolve also facilitated the design and optimization of the heat sink geometry for a given application with high accuracy. AcuSolve’s preprocessor, AcuConsole, enabled the use of templates in a manner such that generating meshes for new cases was fast and easy. This streamlined the development process, leading to less physical prototypes, reduced development costs, and better usage of DSM’s high-performance plastics at their customers.
Quantitative Benefit
  • Accurate prediction of the thermal performance of heat sinks
  • Optimization of the heat sink geometry for a given application
  • Good correlation with measured results

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