Design, experimental investigation and multi-objective optimization of a small-scale radial compressor for heat pump applications

Small scale turbomachines in domestic heat pumps reach high efficiency and provide oil-free solutions which improve heat-exchanger performance and offer major advantages in the design of advanced thermodynamic cycles. An appropriate turbocompressor for domestic air based heat pumps requires the ability to operate on a wide range of inlet pressure, pressure ratios and mass flows, confronting the designer with the necessity to compromise between range and efficiency. Further the design of small-scale direct driven turbomachines is a complex and interdisciplinary task. Textbook design procedures propose to split such systems into subcomponents and to design and optimize each element individually. This common procedure, however, tends to neglect the interactions between the different components leading to suboptimal solutions. The authors propose an approach based on the integrated philosophy for designing and optimizing gas bearing supported, direct driven turbocompressors for applications with challenging requirements with regards to operation range and efficiency. Using previously validated reduced order models for the different components an integrated model of the compressor is implemented and the optimum system found via multi-objective optimization. It is shown that compared to standard design procedure the integrated approach yields an increase of the seasonal compressor efficiency of more than 12 points. Further a design optimization based sensitivity analysis allows to investigate the influence of design constraints determined prior to optimization such as impeller surface roughness, rotor material and impeller force. A relaxation of these constrains yields additional room for improvement. Reduced impeller force improves efficiency due to a smaller thrust bearing mainly, whereas a lighter rotor material improves rotordynamic performance. A hydraulically smoother impeller surface improves the overall efficiency considerably by reducing aerodynamic losses. A combination of the relaxation of the 3 design constraints yields an additional improvement of 6 points compared to the original optimization process. The integrated design and optimization procedure implemented in the case of a complex design problem thus clearly shows its advantages compared to traditional design methods by allowing a truly exhaustive search for optimum solutions throughout the complete design space. It can be used for both design optimization and for design analysis.

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Experimental investigation and multi-objective optimization of fracture properties of asphalt mixtures containing nano-calcium carbonate

Construction and Building Materials ◽

10.1016/j.conbuildmat.2021.122876 ◽

2021 ◽

Vol 285 ◽

pp. 122876 ◽

Cited By ~ 1

Author(s):

Ahmad Ghasemzadeh Mahani ◽

Payam Bazoobandi ◽

Seyed Mohsen Hosseinian ◽

Hassan Ziari

Keyword(s):

Experimental Investigation ◽

Calcium Carbonate ◽

Asphalt Mixtures ◽

Multi Objective Optimization ◽

Fracture Properties ◽

Multi Objective

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Design methodology and multi-objective optimization of small-scale power-water production based on integration of Stirling engine and multi-effect evaporation desalination system

Desalination ◽

10.1016/j.desal.2021.115542 ◽

2022 ◽

Vol 526 ◽

pp. 115542

Author(s):

Bahram Mahjoob Karambasti ◽

Maryam Ghodrat ◽

Ghadir Ghorbani ◽

Ali Lalbakhsh ◽

Masud Behnia

Keyword(s):

Design Methodology ◽

Stirling Engine ◽

Small Scale ◽

Water Production ◽

Multi Objective Optimization ◽

Multi Objective

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Statistical and experimental investigation using a novel multi-objective optimization algorithm on a novel titanium hybrid composite developed by lens process

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406220959101 ◽

2020 ◽

pp. 095440622095910

Author(s):

Soutrik Bose ◽

Titas Nandi

Keyword(s):

Experimental Investigation ◽

Optimization Algorithm ◽

Grey Relational Analysis ◽

Hybrid Composite ◽

Confirmatory Test ◽

Multi Objective Optimization ◽

Multi Objective ◽

Relational Analysis ◽

Grey Relational ◽

Wedm Process

The machining of titanium based hybrid composite by conventional method is very complicated because of its enhanced strength-to-weight ratio, resistance to corrosion, abrasion and fatigue and this hybrid composite is extensively necessary for automobile, aerospace, sports, spacecrafts, marine and bio-medical industries. In this paper, an investigation is presented based on a novel optimization algorithm named as desirable grey relational analysis (DGRA) where desirability function is coupled with grey relational analysis for multi-objective optimization (MOO). A novel titanium hybrid composite is developed by laser engineered net shaping (LENS) process. Experimental investigation is carried on wire electro-discharge machining (WEDM) process varying power, time off and peak current as the most important input process parameters. Fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) is proposed along with fuzzy analytical hierarchy process (FAHP) for criteria weights for the comparison of the experimental and the predicted results. Statistical investigation on response surface methodology (RSM) is carried on the Box-Behnken design (BBD) model using 3 factors and 3 levels design of experiments (DOE) on output responses like material removal rate (MRR), surface roughness (SR), kerf width (KW) and over cut (OC) to obtain satisfactory outcomes and then authenticated by confirmatory test. Analysis of variance (ANOVA) is used for significance of the models. Optimal condition and solution is attained by method of desirability to accomplish the best output response. This optimized result is further enhanced by 3.09%, 2.05% and 1.02% when compared with desirability to FTOPSIS, FTOPSIS to DGRA, and desirability to DGRA.

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