Quick Navigation
Topics
Open Quantum Systems Decoherence
Entanglement Theory Quantum Correlations
Quantum Thermodynamics
Global linear-irreversible principle for optimization in finite-time thermodynamics
arXiv
Authors: Ramandeep S. Johal
Year
2017
Paper ID
7644
Status
Preprint
Abstract Read
~2 min
Abstract Words
196
Citations
N/A
Abstract
There is intense effort into understanding the universal properties of finite-time models of thermal machines---at optimal performance---such as efficiency at maximum power, coefficient of performance at maximum cooling power, and other such criteria. In this letter, a {\it global} principle consistent with linear irreversible thermodynamics is proposed for the whole cycle---without considering details of irreversibilities in the individual steps of the cycle. This helps to express the total duration of the cycle as τpropto {bar{Q}2}/{Δrm tot S}, where bar{Q} models the effective heat transferred through the machine during the cycle, and Δrm tot S is the total entropy generated. By taking bar{Q} in the form of simple algebraic means (such as arithmetic and geometric means) over the heats exchanged by the reservoirs, the present approach is able to predict various standard expressions for figures of merit at optimal performance, as well as the bounds respected by them. It simplifies the optimization procedure to a one-parameter optimization, and provides a fresh perspective on the issue of universality at optimal performance, for small difference in reservoir temperatures. As an illustration, we compare performance of a partially optimized four-step endoreversible cycle with the present approach.
Why This Paper Matters
- This paper contributes to the Quantum Thermodynamics research area in the Quantum Articles archive.
- It adds a 2017 reference point for readers tracking recent quantum research.
- There is intense effort into understanding the universal properties of finite-time models of thermal machines---at optimal performance---such as efficiency at maximum power...
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.