Efficient Solution of Emissivity for the Area Blackbody Based on the Multiple Reflection Method
Jian Xing, Dingyu Liu, Shuanglong Cui
Frontiers in Physics · 2022
doi:10.3389/fphy.2022.832225 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
At present, the Monte Carlo method is the only method to evaluate the area blackbody emissivity, so it needs to be compared and verified with other calculation methods. In particular, the efficiency of Monte Carlo is low when the micro-cavity structure of the area blackbody is more complex for higher emissivity. An efficient algorithm for calculating emissivity of the area blackbody based on the multiple reflection method was put forward in this article. A multiple reflected light path that radiated into the inner micro-cavity structure of the area blackbody was simulated. The ratio of the outgoing light intensity to the incident light intensity was obtained by setting a threshold of the outgoing light intensity, and then the area blackbody emissivity was calculated. The simulation results showed that, compared with the Monte Carlo method, the results of the emissivity calculation were similar, and calculation efficiency was increased more than 100 times under the same micro-cavity structure. A practical area blackbody was made based on the simulation results from the proposed multiple reflection method, and the emissivity measurement experiments were carried out and compared to the cavity blackbody at the same temperature. The results showed that the emissivity was near one and stable for the NIR (Near Infrared) spectrum range when the temperature was higher than 280°C. Thus, the feasibility of the multiple reflection method for calculating the area blackbody emissivity was verified. The multiple reflection method proposed in this article provided one more design path for developing area blackbodies with more complex micro-cavity structures.
Abstract licence: CC BY
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.