[HTML][HTML] Overview on artificial intelligence in design of Organic Rankine Cycle
Converting thermal energy into mechanical work by means of Organic Rankine Cycle is a
validated technology to exploit low-grade waste heat. The typical design process of Organic …
validated technology to exploit low-grade waste heat. The typical design process of Organic …
Data-driven methods for estimating the effective thermal conductivity of nanofluids: A comprehensive review
There is a growing body of work in the field of nanofluids and several investigations have
been conducted on their thermal conductivities. While the experimental works require …
been conducted on their thermal conductivities. While the experimental works require …
Working fluid design and performance optimization for the heat pump-organic Rankine cycle Carnot battery system based on the group contribution method
H Qiao, X Yu, B Yang - Energy Conversion and Management, 2023 - Elsevier
Among various energy storage technologies, the heat pump-organic Rankine cycle (HP-
ORC) Carnot battery technology exists comparably long-life cycles, geographical …
ORC) Carnot battery technology exists comparably long-life cycles, geographical …
Machine learning prediction of ORC performance based on properties of working fluid
Y Peng, X Lin, J Liu, W Su, N Zhou - Applied Thermal Engineering, 2021 - Elsevier
In order to develop machine learning methods for performance prediction of basic ORC
(BORC) and regenerative ORC (RORC), thermodynamic properties of working fluids are …
(BORC) and regenerative ORC (RORC), thermodynamic properties of working fluids are …
Prediction of critical properties and boiling point of fluorine/chlorine-containing refrigerants
In this work, molecular groups were used as the descriptor of molecular structures,
combining with multi-layer perceptron algorithm to establish the prediction models of boiling …
combining with multi-layer perceptron algorithm to establish the prediction models of boiling …
Simultaneous working fluids design and cycle optimization for Organic Rankine cycle using group contribution model
Abstract The performance of Organic Rankine Cycle (ORC) is significantly influenced by the
used working fluid and the operating condition. Consequently, this paper presents a …
used working fluid and the operating condition. Consequently, this paper presents a …
Development of an efficient cross-scale model for working fluid selection of Rankine-based Carnot battery based on group contribution method
H Qiao, B Yang, X Yu - Renewable Energy, 2025 - Elsevier
Rankine-based Carnot battery is promising system with outstanding performances in
addressing the challenges of local consumption of renewable energy generation and …
addressing the challenges of local consumption of renewable energy generation and …
Optimization of geothermal energy aided absorption refrigeration system—GAARS: A novel ANN-based approach
The aim of this study is to optimize the geothermal energy aided absorption refrigeration
system using NH 3–H 2 O as the working fluid. A total of 3660 different designs, with different …
system using NH 3–H 2 O as the working fluid. A total of 3660 different designs, with different …
Using machine learning algorithms to predict the pressure drop during evaporation of R407C
The calculation of the pressure drop for two-phase flow in evaporation and condensation
processes is required by a variety of design practices. In recent years, many correlations …
processes is required by a variety of design practices. In recent years, many correlations …
How to evaluate the performance of sub-critical Organic Rankine Cycle from key properties of working fluids by group contribution methods?
An artificial neural network (ANN) model is developed to predict the ORC performance from
key properties of working fluids, including critical temperature, critical pressure, acentric …
key properties of working fluids, including critical temperature, critical pressure, acentric …