scholarly journals Erratum: “Data-Driven Predesign Tool for Small-Scale Centrifugal Compressor in Refrigeration” [ASME J. Eng. Gas Turbines Power, 140(12), p. 121011; DOI: 10.1115/1.4040845]

2019 ◽  
Vol 141 (10) ◽  
Author(s):  
Violette Mounier ◽  
Cyril Picard ◽  
Jürg Schiffmann
Author(s):  
Mounier Violette ◽  
Picard Cyril ◽  
Schiffmann Jürg

Domestic scale heat pumps and air conditioners are mainly driven by volumetric compressors. Yet the use of reduced scale centrifugal compressors is reconsidered due to their high efficiency and power density. The design procedure of centrifugal compressors starts with predesign tools based on the Cordier line. However, the optimality of the obtained predesign, which is the starting point of a complex and iterative process, is not guaranteed, especially for small-scale compressors operating with refrigerants. This paper proposes a data-driven predesign tool tailored for small-scale centrifugal compressors used in refrigeration applications. The predesign model is generated using an experimentally validated one-dimensional (1D) code which evaluates the compressor performance as a function of its detailed geometry and operating conditions. Using a symbolic regression tool, a reduced order model that predicts the performance of a given compressor geometry has been built. The proposed predesign model offers an alternative to the existing tools by providing a higher level of detail and flexibility. Particularly, the model includes the effect of the pressure ratio, the blade height ratio, and the shroud to tip radius ratio. The analysis of the centrifugal compressor losses allows identifying the underlying phenomena that shape the new isentropic efficiency contours. Compared to the validated 1D code, the new predesign model yields deviations below 4% on the isentropic efficiency, while running 1500 times faster. The new predesign model is, therefore, of significant interest when the compressor is part of an integrated system design process.


Author(s):  
Violette Mounier ◽  
Cyril Picard ◽  
Jürg Schiffmann

Domestic scale heat pumps and air conditioners are mainly driven by volumetric compressors. Yet the use of reduced scale centrifugal compressors is reconsidered due to their high efficiency and power density. Recent work has demonstrated the technical feasibility of a 20 mm centrifugal compressor on gas lubricated bearings operated with R134a by achieving isentropic efficiencies in excess of 75%. The design procedure of such centrifugal compressor starts by using pre-design tools based on the Cordier line. However, the optimality of the obtained pre-design, which is the starting point of a complex and iterative process, is not guaranteed, especially when small-scale compressors operating with organic fluids are targeted. This paper proposes an updated data-driven pre-design tool tailored for small-scale centrifugal compressors used in refrigeration applications. The pre-design model is generated using an experimentally validated 1D code which evaluates the compressor performance as a function of its detailed geometry and operating conditions. Using a symbolic regression tool, a reduced order model that predicts the performance of a given compressor geometry has been built. The proposed pre-design model offers an alternative to the tools available in literature by providing a higher level of detail and flexibility. Particularly, the model includes the effect of the pressure ratio PR and additional geometrical features such as blade height ratio b4 and the shroud to tip radius ratio r2s for addressing the inlet and exhaust areas. The analysis of the centrifugal compressor losses allows identifying the underlying phenomena that shape the new isentropic efficiency contours. As a consequence, for a specific operating condition, a compressor can have different geometries that yield the same efficiency. Low Ns compressors with high b4 are limited by blade loading and recirculation losses and operate closer to the surge limit. Compressors with low b4 and high Ns are exposed to high tip clearance and skin friction losses. Finally, the design space is limited at high Ns due to choke at the compressor inlet, while high incidence losses occur at low Ns at a constant r2s. Since incidence losses relate to the impeller inlet area, increasing r2s enables to achieve higher Ns, while decreasing r2s enables to explore lower Ns conditions. Compared to the 1D model the new pre-design model yields deviations below 4% on the isentropic efficiency, while running 1500 times faster. The new pre-design model is therefore of significant interest when the compressor is part of an integrated system design process.


2021 ◽  
pp. 5-16
Author(s):  
Yu.М. Temis ◽  
A.V. Solovjeva ◽  
Yu.N. Zhurenkov ◽  
A.N. Startsev ◽  
M.Yu. Temis ◽  
...  

2021 ◽  
Author(s):  
Senthil Krishnababu ◽  
Omar Valero ◽  
Roger Wells

Abstract Data driven technologies are revolutionising the engineering sector by providing new ways of performing day to day tasks through the life cycle of a product as it progresses through manufacture, to build, qualification test, field operation and maintenance. Significant increase in data transfer speeds combined with cost effective data storage, and ever-increasing computational power provide the building blocks that enable companies to adopt data driven technologies such as data analytics, IOT and machine learning. Improved business operational efficiency and more responsive customer support provide the incentives for business investment. Digital twins, that leverages these technologies in their various forms to converge physics and data driven models, are therefore being widely adopted. A high-fidelity multi-physics digital twin, HFDT, that digitally replicates a gas turbine as it is built based on part and build data using advanced component and assembly models is introduced. The HFDT, among other benefits enables data driven assessments to be carried out during manufacture and assembly for each turbine allowing these processes to be optimised and the impact of variability or process change to be readily evaluated. On delivery of the turbine and its associated HFDT to the service support team the HFDT supports the evaluation of in-service performance deteriorations, the impact of field interventions and repair and the changes in operating characteristics resulting from overhaul and turbine upgrade. Thus, creating a cradle to grave physics and data driven twin of the gas turbine asset. In this paper, one branch of HFDT using a power turbine module is firstly presented. This involves simultaneous modelling of gas path and solid using high fidelity CFD and FEA which converts the cold geometry to hot running conditions to assess the impact of various manufacturing and build variabilities. It is shown this process can be executed within reasonable time frames enabling creation of HFDT for each turbine during manufacture and assembly and for this to be transferred to the service team for deployment during field operations. Following this, it is shown how data driven technologies are used in conjunction with the HFDT to improve predictions of engine performance from early build information. The example shown, shows how a higher degree of confidence is achieved through the development of an artificial neural network of the compressor tip gap feature and its effect on overall compressor efficiency.


Author(s):  
Matti Malkamäki ◽  
Ahti Jaatinen-Värri ◽  
Antti Uusitalo ◽  
Aki Grönman ◽  
Juha Honkatukia ◽  
...  

Decentralized electricity and heat production is a rising trend in small-scale industry. There is a tendency towards more distributed power generation. The decentralized power generation is also pushed forward by the policymakers. Reciprocating engines and gas turbines have an essential role in the global decentralized energy markets and improvements in their electrical efficiency have a substantial impact from the environmental and economic viewpoints. This paper introduces an intercooled and recuperated three stage, three-shaft gas turbine concept in 850 kW electric output range. The gas turbine is optimized for a realistic combination of the turbomachinery efficiencies, the turbine inlet temperature, the compressor specific speeds, the recuperation rate and the pressure ratio. The new gas turbine design is a natural development of the earlier two-spool gas turbine construction and it competes with the efficiencies achieved both with similar size reciprocating engines and large industrial gas turbines used in heat and power generation all over the world and manufactured in large production series. This paper presents a small-scale gas turbine process, which has a simulated electrical efficiency of 48% as well as thermal efficiency of 51% and can compete with reciprocating engines in terms of electrical efficiency at nominal and partial load conditions.


Author(s):  
N. Courtois ◽  
F. Ebacher ◽  
P. K. Dubois ◽  
N. Kochrad ◽  
C. Landry ◽  
...  

The use of ceramics in gas turbines potentially allows for very high cycle efficiency and power density, by increasing operating temperatures. This is especially relevant for sub-megawatt gas turbines, where the integration of complex blade cooling greatly affects machine capital cost. However, ceramics are brittle and prone to fragile, catastrophic failure, making their current use limited to static and low-stress parts. Using the inside-out ceramic turbine (ICT) configuration solves this issue by converting the centrifugal blade loading to compressive stress, by using an external high-strength carbon-polymer composite rim. This paper presents a superalloy cooling system designed to protect the composite rim and allow it to withstand operating temperatures up to 1600 K. The cooling system was designed using one-dimensional (1D) models, developed to predict flow conditions as well as the temperatures of its critical components. These models were subsequently supported with computational fluid dynamics and used to conduct a power scalability study on a single stage ICT. Results suggest that the ICT configuration should achieve a turbine inlet temperature (TIT) of 1600 K with a composite rim cooling-to-main mass flow rate ratio under 5.2% for power levels above 350 kW. A proof of concept was performed by experimental validation of a small-scale 15 kW prototype, using a commercially available bismaleimide-carbon (BMI-carbon) composite rim and Inconel® 718 nickel-based alloy. The combination of numerical and experimental results show that the ICT can operate at a TIT of 1100 K without damage to the composite rim.


Author(s):  
M. Pinelli ◽  
A. Mazzi ◽  
G. Russo

In this paper, a methodology for the optimization of a single off-shore gas compression station is developed. The station is composed of three gas turbines, each one driving a centrifugal compressor. The study concerns the feasibility of the most suitable arrangement to face the depletion of wells and the consequent reduction of the head top pressure. Once the arrangement is chosen, an optimization procedure is developed and carried out. The procedure, which is aimed at obtaining either high production rates or good station efficiency, is based on knowledge of the centrifugal compressor characteristics and on the availability of gas turbine thermodynamic cycle program, the latter allowing the definition of the machine actual operating state.


2021 ◽  
Author(s):  
Victoria SA. Momyer ◽  
Samantha Dixon ◽  
Q. John Liu ◽  
Brian Wee ◽  
Tiffany Y. Chen ◽  
...  

Given the ongoing transmission and emergence of SARS-Cov-2 variants globally, it is critical to have a timely assessment on individuals' immune responses as well as population immunity. Important questions such as the durability of COVID-19 immunity or the efficacy of vaccines require large datasets to generate meaningful insights. However, due to the complexity and relatively high-cost of many immunity assays and the needs for blood-drawing specialists, these assays were mostly limited to small-scale clinical studies. Our work demonstrated the potential of a non-invasive, inexpensive and data-driven solution for large-scale immunity surveillance and for predictive modeling of vaccine efficacy. Combining a proprietary saliva processing method and an ultra-sensitive digital detection technology, we were able to rapidly gather information regarding personalized immune response following infection or vaccination, monitor temporal evolution, and optimize predictive models for variant protection.


Author(s):  
Fabrizio Reale ◽  
Vincenzo Iannotta ◽  
Raffaele Tuccillo

The primary need of reducing pollutant and greenhouse gas emissions has led to new energy scenarios. The interest of research community is mainly focused on the development of energy systems based on renewable resources and energy storage systems and smart energy grids. In the latter case small scale energy systems can become of interest as nodes of distributed energy systems. In this context micro gas turbines (MGT) can play a key role thanks to their flexibility and a strategy to increase their overall efficiency is to integrate gas turbines with a bottoming cycle. In this paper the authors analyze the possibility to integrate a MGT with a super critical CO2 Brayton cycle turbine (sCO2 GT) as a bottoming cycle (BC). A 0D thermodynamic analysis is used to highlight opportunities and critical aspects also by a comparison with another integrated energy system in which the waste heat recovery (WHR) is obtained by the adoption of an organic Rankine cycle (ORC). While ORC is widely used in case of middle and low temperature of the heat source, s-CO2 BC is a new method in this field of application. One of the aim of the analysis is to verify if this choice can be comparable with ORC for this operative range, with a medium-low value of exhaust gases and very small power values. The studied MGT is a Turbec T100P.


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