Integrated gas turbine system diagnostics: components and sensor faults quantification using artificial neural networks

The role of diagnostic systems in gas turbine operations has changed over the past years from a single support troubleshooting maintenance to a more proactive integrated diagnostic system. This has become so, because detecting and fixing fault(s) on one gas turbine sub-system can trigger false fault(s) indication, on other component(s) of the gas turbine system, due to interrelationships between data obtained to monitor not only the GT single component, but also the integrated components and sensors. Hence, there is need for integration of gas turbine system diagnostics. The purpose of this paper is to present artificial neural network diagnostic system (ANNDS) as an integrated gas turbine system diagnostic tool capable of quantifying gas turbine component and sensor fault. A model based approach which consists of an engine model, and an associated parameter estimation algorithm that predicts the difference between the real engine data and the estimated output data is described in this paper. The ANNDS system was trained to detect, isolate and assess component(s) and sensor fault(s) of a single spool industrial gas turbine GT-PG9171ER. The ANN model was construed with multi-layer feed-forward back propagation network for component fault(s) and auto associative network for sensor fault(s). The diagnostic methodology adopted was a nested network structure, trained to handle specific objective function of detecting, isolating or quantifying faults. The data used for training, and testing purposes were obtained from a non-linear aero-thermodynamic model using PYTHIA; a Cranfield University in-house software. The data set analyzed in this paper represent samples of clean and faulty gas turbine components caused by fouling (0.5% - 6% degradation) and sensor fault(s) due to bias (±1% - ±7%). The results show the capability of ANN to detect, isolate (classification) and quantify multiple faults if properly trained

Effect of working fluid on selection of gas turbine cycle configuration for Gen-IV nuclear power plant system

The cycle configuration of the energy conversion system in a nuclear power plant tends to have a governing effect on the overall performance and acquisition cost. Interestingly, one factor that could greatly affect the design choice of the cycle configuration which may not have been explored extensively in many literatures reviewed is the choice of the working fluid. This paper presents a technical analysis on the effect of working fluid on selection of the cycle arrangement for a Generation IV nuclear power plant. It provides insight on potential performance gains that justifies the benefit for an additional cost of a complex cycle, and how the working fluid can influence this choice. The study identifies candidate working fluid that may be suitable for simple, inter-cooled-recuperated, recuperated and other complex cycles. The results obtained shows that for fluid like carbon dioxide, its optimal performance is achieved above it critical points which will require pressurizing the system or operating at high pressure ratio, hence, it would be suitable for a re-compressed inter-cooled cycle configuration. Similar, for fluid like helium with low molecular weight and high gas properties, the simple cycle configuration seem more realistic for its highest cycle efficiency of 41% and turbomachinery design

Feasibility of a helium closed-cycle gas turbine for UAV propulsion

When selecting a design for an unmanned aerial vehicle, the choice of the propulsion system is vital in terms of mission requirements, sustainability, usability, noise, controllability, reliability and technology readiness level (TRL). This study analyses the various propulsion systems used in unmanned aerial vehicles (UAVs), paying particular focus on the closed-cycle propulsion systems. The study also investigates the feasibility of using helium closed-cycle gas turbines for UAV propulsion, highlighting the merits and demerits of helium closed-cycle gas turbines. Some of the advantages mentioned include high payload, low noise and high altitude mission ability; while the major drawbacks include a heat sink, nuclear hazard radiation and the shield weight. A preliminary assessment of the cycle showed that a pressure ratio of 4, turbine entry temperature (TET) of 800 °C and mass flow of 50 kg/s could be used to achieve a lightweight helium closed-cycle gas turbine design for UAV mission considering component design constraints

GT-ACYSS: gas turbine arekret-cycle simulation modelling for training and educational purposes

This paper presents the modelling approach of a multi-purpose simulation tool called GT-ACYSS; which can be utilized for simulation of steady-state and pseudo transient performance of closed-cycle gas turbine plants. The tool analyses the design point performance as a function of component design and performance map characteristics predicted based on multi-fluid map scaling technique. The off-design point is analyzed as a function of design point performance, plant control settings and a wide array of other off-design conditions. GT-ACYSS can be a useful educational tool since it allows the student to monitor gas path properties throughout the cycle without laborious calculations. It allows the user to have flexibility in selection of four different working fluids, and the ability to simulate various single-shaft closed-cycle configurations, as well as the ability to carry out preliminary component sizing of the plant. The modelling approach described in this paper has been verified with case studies and the trends shown appeared to be reasonable when compared with reference data in the open literature, hence, can be utilized to perform independent analyses of any referenced single-shaft closed-cycle gas turbine plants. The results of case studies presented herein demonstrated that the multi-fluid scaling method of components and the algorithm of the steady state analysis were in good agreement for predicting cycle performance parameters (such as efficiency, and output power) with mean deviations from referenced plant data ranging between 0.1% and 1% over wide array of operations

Economic optimization from fleets of aero-derivative gas turbines utilising flared associated gas

Associated gas is been wasted to flaring in some parts of the world. The use of these flared gases for both industrial and economic purposes would be very beneficial. This paper presents the development of a model for optimizing the economic return of fleets of gas turbines utilizing flared associated gas. The paper further analyzed the impact of gas turbine degradation on the optimized divestment times of the redundant engines and the economic use of associated gas. Hypothetical but realistic gas turbines were modeled using the Cranfield University performance simulation tool, TURBOMATCH. In furtherance with the investigation, the Techno-Economic and Environmental Risk Assessment (TERA) framework has been adopted for a broad and multi-dimensional optimization of the economic return from the fleets. The results were employed in three degradation scenarios (optimistic, medium, and pessimistic) within the TERA framework to generate economic models. Genetic Algorithm (GA) in MATLAB was used in carrying out optimization to maximize the economic benefit. The result showed that an increase of 1.0% and 1.6% in the energy and net present value (NPV) respectively of the optimized clean fleet as against the baseline were achieved. The economic performance of the fleets shows the optimized fleet (clean) having the highest NPV of $2.84b and the pessimistic degraded fleet having the least NPV of$2.39b. More results revealed that degradation reduced the NPV of the project by 4.0%, 9.1%, and 15.8% for the three different degradation scenarios. This paper has proposed a model that can be used for the profitable economic utilization of associated gas which would be useful to gas turbine operators and investor

Performance analyses and evaluation of CO2 and N2 as coolants in a recuperated Brayton gas turbine cycle for a Generation IV nuclear reactor power plant

As demands for clean and sustainable energy renew interests in nuclear power to meet future energy demands, Generation IV nuclear reactors are seen as having the potential to provide the improvements required for nuclear power generation. However, for their benefits to be fully realised, it is important to explore the performance of the reactors when coupled to different configurations of closed-cycle gas turbine power conversion systems. The configurations provide variation in performance due to different working fluids over a range of operating pressures and temperatures. The objective of this paper is to undertake analyses at the design and off-design conditions in combination with a recuperated closed-cycle gas turbine and comparing the influence of carbon dioxide and nitrogen as the working fluid in the cycle. The analysis is demonstrated using an in-house tool, which was developed by the authors. The results show that the choice of working fluid controls the range of cycle operating pressures, temperatures and overall performance of the power plant due to the thermodynamic and heat properties of the fluids. The performance results favored the nitrogen working fluid over CO2 due to the behavior CO2 below its critical conditions. The analyses intend to aid the development of cycles for Generation IV NPPs specifically Gas-cooled Fast Reactors (GFRs) and Very High-Temperature Reactors (VHTRs)

Performance simulation to understand the effects of multi-fluid scaling of gas turbine components for Generation IV nuclear power plants

A significant hurdle in the development of performance simulation tools to analyse and evaluate nuclear power plants (NPP) is finding data relating to component performance maps. As a result, Engineers often rely on an estimation approach using various scaling techniques. The purpose of this study is to determine the component characteristics of a closed-cycle gas turbine NPP using existing component maps with corresponding design data. The design data is applied for different working fluids using a multi-fluid scaling approach to adapt data from one component map into another. The multi-fluid scaling technique described herein was developed as an in-house computer simulation tool. This approach makes it easy to theoretically scale existing maps using similar or different working fluids without carrying out a full experimental test or repeating the whole design and development process. The results of selected case studies show a reasonable agreement with available data. The analyses intend to aid the development of cycles for Generation IV NPPs specifically Gas-cooled Fast Reactors (GFRs) and Very High-Temperature Reactors (VHTRs)

Thermodynamic performance and creep life assessment comparing hydrogen- and jet-fueled turbofan aero engine

There is renewed interest in hydrogen as an alternative fuel for aero engines, due to their perceived environmental and performance benefits compared to jet fuel. This paper presents a cycle, thermal performance, energy and creep life assessment of hydrogen compared with jet fuel, using a turbofan aero engine. The turbofan cycle performance was simulated using a code developed by the authors that allows hydrogen and jet fuel to be selected as fuel input. The exergy assessment uses both conservations of energy and mass and the second law of thermodynamics to understand the impact of the fuels on the exergy destruction, exergy efficiency, waste factor ratio, environmental effect factor and sustainability index for a turbofan aero engine. Finally, the study looks at a top-level creep life assessment on the high-pressure turbine hot section influenced by the fuel heating values. This study shows performance (64% reduced fuel flow rate, better SFC) and more extended blade life (15% increase) benefits using liquefied hydrogen fuel, which corresponds with other literary work on the benefits of LH2 over jet fuel. This paper also highlights some drawbacks of hydrogen fuel based on previous research work, and gives recommendations for future work, aimed at maturing the hydrogen fuel concept in aviation

APOE E4 is associated with impaired self-declared cognition but not disease risk or age of onset in Nigerians with Parkinson's disease

The relationship between APOE polymorphisms and Parkinson's disease (PD) in black Africans has not been previously investigated. We evaluated the association between APOE polymorphic variability and self-declared cognition in 1100 Nigerians with PD and 1097 age-matched healthy controls. Cognition in PD was assessed using the single item cognition question (item 1.1) of the MDS-UPDRS. APOE genotype and allele frequencies did not differ between PD and controls (p > 0.05). No allelic or genotypic association was observed between APOE and age at onset of PD. In PD, APOE ε4/ε4 conferred a two-fold risk of cognitive impairment compared to one or no ε4 (HR: 2.09 (95% CI: 1.13-3.89; p = 0.02)), while APOE ε2 was associated with modest protection against cognitive impairment (HR: 0.41 (95% CI 0.19-0.99, p = 0.02)). Of 773 PD with motor phenotype and APOE characterized, tremor-dominant (TD) phenotype predominated significantly in ε2 carriers (87/135, 64.4%) compared to 22.2% in persons with postural instability/gait difficulty (PIGD) (30/135) and 13.3% in indeterminate (ID) (18/135, 13.3%) (p = 0.037). Although the frequency of the TD phenotype was highest in homozygous ε2 carriers (85.7%), the distribution of motor phenotypes across the six genotypes did not differ significantly (p = 0.18). Altogether, our findings support previous studies in other ethnicities, implying a role for APOE ε4 and ε2 as risk and protective factors, respectively, for cognitive impairment in PD

A model for booster station matching of gas turbine and gas compressor power under different ambient conditions

Transporting natural gas across different locations require compressor stations to provide the pressure needed to keep the gas moving. This paper presents a model for matching the gas turbine and gas compressor power required under different environmental conditions to support the continuous gas transmission across other locations. The trans-Saharan gas pipeline (TSGP) project proposed to transport gas from Nigeria to Algeria has been used as a case study in this paper. The TSGP project is a Nigerian Government initiative to rejig its gas development and transportation infrastructure to meet its internal and external market demand. The numerical method used in this paper integrates the effect of the ambient temperature in the power matching of the gas turbine and gas compressors. There are 18 compressor stations across the TSGP network, and compressor station 2 is used as the reference point. The daily temperature fluctuation is segmented into hours of the day, emphasising considerable ambient temperature variation at 3:00 h, 9:00 h, 15:00 h. One benefit of the model against others in the open literature is accounting for changes in the ambient temperature along the pipeline network and gas compression stations. Accounting for changes in ambient temperature provides accuracy to near real-life operational experience for gas distribution via pipelines. The model also accounts for variations in turbine entry temperature (TET) to compensate for changes in the ambient conditions to meet the power requirements of the gas turbine and the gas compressor. The results show that for every 1% increase in ambient temperature, a 3.5% increase in power is required to drive the gas compressor and a 1% decrease in gas turbine output power. The effect of the 1% increase in ambient would require a 3.5% increase in TET to meet both the gas turbine and gas compressor requirement