Experimental investigation on a two-stage CO2 compressor with high back pressure

2011 ◽  
Vol 226 (7) ◽  
pp. 1811-1820
Author(s):  
Zhaogang Qi ◽  
Jun Yang ◽  
Jiangping Chen ◽  
Haifeng Zhang ◽  
Li Zhang
Keyword(s):  
Compression Ratio ◽  
Piston Compressor ◽  
Back Pressure ◽  
Volumetric Efficiency ◽  
Mean Deviation ◽  
Two Stage ◽  
Second Stage ◽  
Two Samples ◽  
Rolling Piston ◽  
Discharge Pressure

In this article, two samples of two-stage rolling piston CO2 compressors with and without intercooler are developed and experimentally studied. These CO2 compressors are high back-pressure compressors, which mean the pressure inside compressor shell is the discharge pressure of the second stage. A test rig was designed to measure the performance and efficiency of this compressor. The test results show that the suction vapor temperature at the second stage inlet pipe has few influences on the performance and efficiency of the first compressor sample with intercooler. The volumetric efficiency linearly decreases with the increase of compression ratio of the suction and discharge pressure, and the volumetric efficiency can maintain in a relative constant range during a wide compression ratio changes in this high back-pressure design. There exists an optimum compression ratio for each suction pressure at the first stage, where the compressor isentropic efficiency is maximum. A generalized volumetric efficiency correlation for two-stage CO2 rolling piston compressor as a function of compression ratio is proposed and it can describe 100% of the test data within ±5.0% with a mean deviation of 1.7%. This would be helpful as a guide for designing such type compressor.

Experimental study on a two-stage rolling piston CO2 compressor based on p–V indicator diagrams

2011 ◽  
Vol 226 (4) ◽  
pp. 995-1003 ◽  
Author(s):  
J Yang ◽  
Z Qi ◽  
J Chen ◽  
Z Chen
Keyword(s):  
Experimental Study ◽  
Operating Conditions ◽  
Test Rig ◽  
Two Stage ◽  
Second Stage ◽  
Compressor Inlet ◽  
Compressor Performance ◽  
Overall Efficiency ◽  
Rolling Piston ◽  
Discharge Pressure

In this article, a new two-stage rolling piston CO2 compressor was developed. A test rig was designed to measure the performance of this compressor. Based on the measured p–V indicator diagram, the distributions of indicated power and compressor performance under various operating conditions have been analysed in detail. It is shown that the discharge passage loss of the first stage and the suction passage loss of the second stage are much higher than other losses for the tested compressor. The overall efficiency of the tested compressor decreases by 1.2 per cent with the decrease of the discharge pressure at the same suction conditions. It is also found that the superheating at the compressor inlet has very small (0.3 per cent) effect on the compressor performance.

Controlled ASSCI With Moderate Auto-Ignition for Engine Knock Suppression in a GDI Engine With High Compression Ratio

2014 ◽  
Author(s):  
Hui Liu ◽  
Zhi Wang ◽  
Jianxin Wang ◽  
Mengke Wang ◽  
Wanli Yang
Keyword(s):  
Heat Release ◽  
Compression Ratio ◽  
High Compression Ratio ◽  
Two Stage ◽  
Second Stage ◽  
High Compression ◽  
Auto Ignition ◽  
Crank Angle ◽  
Engine Knock ◽  
Gdi Engine

This paper presents an experimental study on controlled ASSCI (Assisted Spark Stratified Compression Ignition) for engine knock suppression in a GDI engine with high compression ratio. The direct injection is used for forming desired stoichiometric stratified mixture at WOT condition without turbo-charging. The engine is filled with 20% cooled external EGR and the ignition timing is maintained at MBT point. The combustion characteristics of the desired stoichiometric stratified mixture show two-stage heat release, where the first stage is caused by spark ignition and the second stage is due to moderate auto-ignition. Compared with engine knock, the second stage heat release of controlled ASSCI shows smooth pressure curve without pressure oscillation. This is due to the low energy density mixture around the cylinder wall caused by cooled external EGR. The stratified mixture could suppress knock. Fuel economy and combustion characteristics of the baseline and the controlled ASSCI combustion were compared. The baseline GDI engine reaches a maximum of 8.9 bar BMEP with BSFC of 291 g/(kWh), the controlled ASSCI combustion achieves a maximum of 8.3 bar BMEP with BSFC of 256 g/(kWh), improving the fuel economy over 12% while maintaining approximately the same power. CA50 (the crank angle of 50% heat release) of the controlled ASSCI is detected at 8.4° CA ATDC, which is 17.4° CA advanced than that of the baseline while the combustion duration of the controlled ASSCI is 52.84dG CA, 16.6° CA longer than that of the baseline caused by diluted mixture and two-stage heat release. The COV of the controlled ASSCI is 1.4%, 2.1% lower than that of the baseline. The peak pressure (Pmax) and the maximum pressure rise rate (PRRmax) of the controlled ASSCI are 59.7 bar and 2.2 bar/° CA, 22.9 bar and 1.5 bar/° CA higher than that of the baseline respectively. The crank angle of Pmax and PRRmax of the controlled ASSCI are 11° CA ATDC and −1° CA ATDC, 15.4° CA and 17.2° CA earlier than that of the baseline. The results show that controlled ASSCI with two-stage heat releases is a potential combustion strategy to suppress engine knock while achieving high efficiency of the high compression ratio gasoline engine.

Controlled SSCI With Moderate End-Gas Auto-Ignition for Fuel Economy Improvement and Knock Suppression

2015 ◽  
Vol 137 (10) ◽  
Author(s):  
Hui Liu ◽  
Zhi Wang ◽  
Jianxin Wang ◽  
Mengke Wang ◽  
Wanli Yang
Keyword(s):  
Heat Release ◽  
Compression Ratio ◽  
Fuel Economy ◽  
Direct Injection ◽  
High Compression Ratio ◽  
Two Stage ◽  
Second Stage ◽  
Auto Ignition ◽  
Engine Knock ◽  
Gdi Engine

Hybrid combustion mode including flame propagation induced by spark ignition (SI) and auto-ignition could be an effective method to improve fuel economy and suppress engine knock simultaneously. An experimental research on controlled spark-assisted stratified compression ignition (SSCI) for this purpose was conducted in a gasoline direct injection (GDI) engine with high compression ratio. At wide open throttle (WOT) and minimum spark advance for best torque (MBT) condition without turbocharging, direct injection was used to form desired stoichiometric stratified mixture while 20% cooled external exhaust gas recirculation (e-EGR) was sucked into the cylinder. The combustion characteristics of controlled SSCI show two-stage heat release, where the first stage is caused by SI and the second stage is due to moderate auto-ignition. Compared with engine knock, the second stage heat release of controlled SSCI shows smooth pressure curve without pressure oscillation. This is due to the low energy density mixture around the cylinder wall caused by cooled e-EGR. The stratified mixture could suppress knock. Fuel economy and combustion characteristics of the baseline and the controlled SSCI combustion were compared. The baseline GDI engine reaches a maximum of 8.9 bar brake mean effective pressure (BMEP) with brake specific fuel consumption (BSFC) of 291 g/(kWh), and the controlled SSCI combustion achieves a maximum of 8.3 bar BMEP with BSFC of 256 g/(kWh), improving the fuel economy over 12% while maintaining approximately the same power. The results show that controlled SSCI with two-stage heat releases is a potential combustion strategy to suppress engine knock while achieving high efficiency of the high compression ratio gasoline engine.

Experimental study on the entrainment performance and flow choking phenomenon of a two-stage multi-nozzle ejector

2020 ◽  
Vol 34 (14n16) ◽  
pp. 2040099
Author(s):  
Pei Chen
Keyword(s):  
Total Pressure ◽  
Vacuum Chamber ◽  
Experimental System ◽  
Back Pressure ◽  
Test Model ◽  
Two Stage ◽  
Primary Flow ◽  
Flow Choking ◽  
Second Stage ◽  
Flow Changes

A two-stage multi-nozzle ejector experimental system is established, and the pressure distribution on the wall and in the flow field of the test model is measured when the total pressure of the two-stage primary flow changes. Results show that when the total pressure of primary flow increases, vacuum chamber static pressure decreases to its lowest limit of 1 kPa, and then begins to rise. Flow choking mechanism of two stage ejector is clarified. If the total pressure of the first stage primary flow is low, the flow in the second stage ejector first reaches the choking state when the total pressure of the second stage primary flow increases, which causes the rise of first stage back pressure, and then the first stage ejector reaches the choking state. If the total pressure of the first stage primary flow is high, the increase of total pressure of the second stage primary flow reduces the back pressure of the first stage ejector and therefore the first stage ejector first reaches the choking state, and then the second stage reaches the choking state.

An Enhanced Two Stage MMSE Equalizer for Coded FBMC/OQAM Systems

2019 ◽  
Vol 10 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Mohammad Rizk Assaf ◽  
Abdel-Nasser Assimi
Keyword(s):  
Error Propagation ◽  
Channel Model ◽  
Error Correcting Codes ◽  
Two Stage ◽  
Probability Of Error ◽  
Second Stage ◽  
Different Types ◽  
Mmse Equalizer ◽  
And Performance ◽  
Ici Cancellation

In this article, the authors investigate the enhanced two stage MMSE (TS-MMSE) equalizer in bit-interleaved coded FBMC/OQAM system which gives a tradeoff between complexity and performance, since error correcting codes limits error propagation, so this allows the equalizer to remove not only ICI but also ISI in the second stage. The proposed equalizer has shown less design complexity compared to the other MMSE equalizers. The obtained results show that the probability of error is improved where SNR gain reaches 2 dB measured at BER compared with ICI cancellation for different types of modulation schemes and ITU Vehicular B channel model. Some simulation results are provided to illustrate the effectiveness of the proposed equalizer.

Personalised attraction recommendation for enhancing topic diversity and accuracy

2021 ◽  
pp. 016555152199980
Author(s):  
Yuanyuan Lin ◽  
Chao Huang ◽  
Wei Yao ◽  
Yifei Shao
Keyword(s):  
Real World ◽  
Information Overload ◽  
Two Stage ◽  
Misclassification Cost ◽  
Second Stage ◽  
Low Visibility ◽  
Recommendation Diversity ◽  
Optimisation Model ◽  
Definition Of ◽  
Improved Methods

Attraction recommendation plays an important role in tourism, such as solving information overload problems and recommending proper attractions to users. Currently, most recommendation methods are dedicated to improving the accuracy of recommendations. However, recommendation methods only focusing on accuracy tend to recommend popular items that are often purchased by users, which results in a lack of diversity and low visibility of non-popular items. Hence, many studies have suggested the importance of recommendation diversity and proposed improved methods, but there is room for improvement. First, the definition of diversity for different items requires consideration for domain characteristics. Second, the existing algorithms for improving diversity sacrifice the accuracy of recommendations. Therefore, the article utilises the topic ‘features of attractions’ to define the calculation method of recommendation diversity. We developed a two-stage optimisation model to enhance recommendation diversity while maintaining the accuracy of recommendations. In the first stage, an optimisation model considering topic diversity is proposed to increase recommendation diversity and generate candidate attractions. In the second stage, we propose a minimisation misclassification cost optimisation model to balance recommendation diversity and accuracy. To assess the performance of the proposed method, experiments are conducted with real-world travel data. The results indicate that the proposed two-stage optimisation model can significantly improve the diversity and accuracy of recommendations.

scholarly journals Two-stage multi-tasking transform framework for large-scale many-objective optimization problems

2021 ◽  
Author(s):  
Lu Chen ◽  
Handing Wang ◽  
Wenping Ma
Keyword(s):  
Large Scale ◽  
Original Problem ◽  
Optimization Problems ◽  
Reference Points ◽  
Optimization Strategy ◽  
Two Stage ◽  
Decision Space ◽  
Second Stage ◽  
Decision Variables ◽  
Objective Space

AbstractReal-world optimization applications in complex systems always contain multiple factors to be optimized, which can be formulated as multi-objective optimization problems. These problems have been solved by many evolutionary algorithms like MOEA/D, NSGA-III, and KnEA. However, when the numbers of decision variables and objectives increase, the computation costs of those mentioned algorithms will be unaffordable. To reduce such high computation cost on large-scale many-objective optimization problems, we proposed a two-stage framework. The first stage of the proposed algorithm combines with a multi-tasking optimization strategy and a bi-directional search strategy, where the original problem is reformulated as a multi-tasking optimization problem in the decision space to enhance the convergence. To improve the diversity, in the second stage, the proposed algorithm applies multi-tasking optimization to a number of sub-problems based on reference points in the objective space. In this paper, to show the effectiveness of the proposed algorithm, we test the algorithm on the DTLZ and LSMOP problems and compare it with existing algorithms, and it outperforms other compared algorithms in most cases and shows disadvantage on both convergence and diversity.

scholarly journals A Two-Stage Mono- and Multi-Objective Method for the Optimization of General UPS Parallel Manipulators

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 543
Author(s):  
Alejandra Ríos ◽  
Eusebio E. Hernández ◽  
S. Ivvan Valdez
Keyword(s):  
Genetic Algorithm ◽  
Performance Metrics ◽  
Tracking Error ◽  
Parallel Manipulators ◽  
Optimization Method ◽  
Statistical Hypothesis ◽  
Two Stage ◽  
Multi Objective ◽  
Second Stage ◽  
Conflicting Objectives

This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a mono-objective optimization in order to reach, with sufficient dexterity, a regular target workspace while minimizing the elements’ lengths. For this optimization problem, we compare three bio-inspired algorithms: the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), and the Boltzman Univariate Marginal Distribution Algorithm (BUMDA). The second stage looks for the most suitable gains of a Proportional Integral Derivative (PID) control via the minimization of two conflicting objectives: one based on energy consumption and the tracking error of a target trajectory. To this effect, we compare two multi-objective algorithms: the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) and Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The main contributions lie in the optimization model, the proposal of a two-stage optimization method, and the findings of the performance of different bio-inspired algorithms for each stage. Furthermore, we show optimized designs delivered by the proposed method and provide directions for the best-performing algorithms through performance metrics and statistical hypothesis tests.

scholarly journals Fast Two-Stage Computation of an Index Policy for Multi-Armed Bandits with Setup Delays

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 52
Author(s):  
José Niño-Mora
Keyword(s):  
Numerical Study ◽  
Arithmetic Operation ◽  
Bandit Problem ◽  
Index Policy ◽  
Two Stage ◽  
Second Stage ◽  
Whittle Index ◽  
Set Up ◽  
Computing Method ◽  
Special Case

We consider the multi-armed bandit problem with penalties for switching that include setup delays and costs, extending the former results of the author for the special case with no switching delays. A priority index for projects with setup delays that characterizes, in part, optimal policies was introduced by Asawa and Teneketzis in 1996, yet without giving a means of computing it. We present a fast two-stage index computing method, which computes the continuation index (which applies when the project has been set up) in a first stage and certain extra quantities with cubic (arithmetic-operation) complexity in the number of project states and then computes the switching index (which applies when the project is not set up), in a second stage, with quadratic complexity. The approach is based on new methodological advances on restless bandit indexation, which are introduced and deployed herein, being motivated by the limitations of previous results, exploiting the fact that the aforementioned index is the Whittle index of the project in its restless reformulation. A numerical study demonstrates substantial runtime speed-ups of the new two-stage index algorithm versus a general one-stage Whittle index algorithm. The study further gives evidence that, in a multi-project setting, the index policy is consistently nearly optimal.

Sign in / Sign up

Export Citation Format

Share Document