Extrapolation of Creep Rupture Data Using Parametric Numerical Isothermal Datum (P-NID) Method for Inconel 617

2020 ◽  
Author(s):  
Mohammad Shafinul Haque
Keyword(s):  
Model Calibration ◽  
Power Plants ◽  
Prediction Models ◽  
Creep Rupture ◽  
Operating Conditions ◽  
Parametric Models ◽  
Mathematical Form ◽  
Rupture Data ◽  
Inconel 617 ◽  
Calibration Approach

Abstract The development of advanced power plants requires alloys to operate at elevated temperature and pressure for an extended period of time. It is critical to consider creep during the design process to avoid catastrophic failure. Creep rupture data are often not available for desired operating conditions. Accurate extrapolation of creep life is necessary. One of the earliest and most widely used life prediction model is the classic Larson-Miller Parametric (LM) model. Over time numerous time-temperature parametric (TTP) models have been proposed such as Manson-Haferd, Orr-Sherby-Dorn, Manson-Succop, Graham-Walles, Goldhoff-Sherby parametric models. Non-TTP models such as the Wilshire equation is available. The prediction models vary in mathematical form, and number of material constants but shares a common calibration approach. Each model is calibrated against data for every available isotherm. A recently proposed model calibration approach is the parametric numerical isothermal datum (P-NID) method that can be applied to an existing model for improved long-term extrapolation. The P-NID approach is different than the traditional approach as the data are transferred to a datum temperature followed by model calibration against the transferred data at the datum temperature. The calibrated model is then transferred back to the original temperatures. In this study, the P-NID method is applied to the LM model to perform extrapolation for Inconel 617 alloy. Creep rupture data for five isotherms ranging from 800 to 1000°C and stress levels from 9MPa to 170 MPa are used. A detail step by step procedure is provided for the application of the P-NID method to calibrate the LM model (LM-NID). The extrapolation performance of the classic LM and LM-NID models are compared. Normalized Mean Squared Error (NMSE) is used to analyze prediction accuracy. It is observed that the LM-NID model provides a realistic inflection free prediction compared to the LM model. A 10% data-cull from the lowest stress data is performed to assess the reliability of extrapolation. Based on the comparison a recommendation is provided.

Could biomass-fueled boilers be operated at higher steam temperatures? Part 3: Initial analysis of costs and benefits

TAPPI Journal ◽  
2014 ◽  
Vol 13 (8) ◽  
pp. 65-78 ◽  
Author(s):  
W.B.A. (SANDY) SHARP ◽  
W.J. JIM FREDERICK ◽  
JAMES R. KEISER ◽  
DOUGLAS L. SINGBEIL
Keyword(s):  
Flue Gas ◽  
Power Plants ◽  
Superheated Steam ◽  
Black Liquor ◽  
Simulation Software ◽  
Operating Conditions ◽  
Costs And Benefits ◽  
Steam Generation ◽  
Fireside Corrosion ◽  
Corrosion Resistant

The efficiencies of biomass-fueled power plants are much lower than those of coal-fueled plants because they restrict their exit steam temperatures to inhibit fireside corrosion of superheater tubes. However, restricting the temperature of a given mass of steam produced by a biomass boiler decreases the amount of power that can be generated from this steam in the turbine generator. This paper examines the relationship between the temperature of superheated steam produced by a boiler and the quantity of power that it can generate. The thermodynamic basis for this relationship is presented, and the value of the additional power that could be generated by operating with higher superheated steam temperatures is estimated. Calculations are presented for five plants that produce both steam and power. Two are powered by black liquor recovery boilers and three by wood-fired boilers. Steam generation parameters for these plants were supplied by industrial partners. Calculations using thermodynamics-based plant simulation software show that the value of the increased power that could be generated in these units by increasing superheated steam temperatures 100°C above current operating conditions ranges between US$2,410,000 and US$11,180,000 per year. The costs and benefits of achieving higher superheated steam conditions in an individual boiler depend on local plant conditions and the price of power. However, the magnitude of the increased power that can be generated by increasing superheated steam temperatures is so great that it appears to justify the cost of corrosion-mitigation methods such as installing corrosion-resistant materials costing far more than current superheater alloys; redesigning biomassfueled boilers to remove the superheater from the flue gas path; or adding chemicals to remove corrosive constituents from the flue gas. The most economic pathways to higher steam temperatures will very likely involve combinations of these methods. Particularly attractive approaches include installing more corrosion-resistant alloys in the hottest superheater locations, and relocating the superheater from the flue gas path to an externally-fired location or to the loop seal of a circulating fluidized bed boiler.

"Recent Patents on the Triboelectrostatic Separation of Fly Ash"

2019 ◽  
Vol 13 ◽  
Author(s):  
Haisheng Li ◽  
Wenping Wang ◽  
Yinghua Chen ◽  
Xinxi Zhang ◽  
Chaoyong Li
Keyword(s):  
Fly Ash ◽  
Power Plants ◽  
High Efficiency ◽  
Separation Efficiency ◽  
High Reliability ◽  
Operating Conditions ◽  
Security Requirements ◽  
Unburned Carbon ◽  
Efficient Operation ◽  
Triboelectrostatic Separation

Background: The fly ash produced by coal-fired power plants is an industrial waste. The environmental pollution problems caused by fly ash have been widely of public environmental concern. As a waste of recoverable resources, it can be used in the field of building materials, agricultural fertilizers, environmental materials, new materials, etc. Unburned carbon content in fly ash has an influence on the performance of resource reuse products. Therefore, it is the key to remove unburned carbon from fly ash. As a physical method, triboelectrostatic separation technology has been widely used because of obvious advantages, such as high-efficiency, simple process, high reliability, without water resources consumption and secondary pollution. Objective: The related patents of fly ash triboelectrostatic separation had been reviewed. The structural characteristics and working principle of these patents are analyzed in detail. The results can provide some meaningful references for the improvement of separation efficiency and optimal design. Methods: Based on the comparative analysis for the latest patents related to fly ash triboelectrostatic separation, the future development is presented. Results: The patents focused on the charging efficiency and separation efficiency. Studies show that remarkable improvements have been achieved for the fly ash triboelectrostatic separation. Some patents have been used in industrial production. Conclusion: According to the current technology status, the researches related to process optimization and anti-interference ability will be beneficial to overcome the influence of operating conditions and complex environment, and meet system security requirements. The intelligent control can not only ensure the process continuity and stability, but also realize the efficient operation and management automatically. Meanwhile, the researchers should pay more attention to the resource utilization of fly ash processed by triboelectrostatic separation.

Local Calibration of Pavement Mechanistic-Empirical Faulting Reliability using Pavement Management Data

2021 ◽  
pp. 036119812110013
Author(s):  
Lucio Salles de Salles ◽  
Lev Khazanovich
Keyword(s):  
Model Calibration ◽  
Prediction Models ◽  
Plain Concrete ◽  
Performance Model ◽  
Pavement Management ◽  
Pavement Design ◽  
Reliability Model ◽  
Transverse Joint ◽  
Design Characteristics ◽  
And Performance

The Pavement ME transverse joint faulting model incorporates mechanistic theories that predict development of joint faulting in jointed plain concrete pavements (JPCP). The model is calibrated using the Long-Term Pavement Performance database. However, the Mechanistic-Empirical Pavement Design Guide (MEPDG) encourages transportation agencies, such as state departments of transportation, to perform local calibrations of the faulting model included in Pavement ME. Model calibration is a complicated and effort-intensive process that requires high-quality pavement design and performance data. Pavement management data—which is collected regularly and in large amounts—may present higher variability than is desired for faulting performance model calibration. The MEPDG performance prediction models predict pavement distresses with 50% reliability. JPCP are usually designed for high levels of faulting reliability to reduce likelihood of excessive faulting. For design, improving the faulting reliability model is as important as improving the faulting prediction model. This paper proposes a calibration of the Pavement ME reliability model using pavement management system (PMS) data. It illustrates the proposed approach using PMS data from Pennsylvania Department of Transportation. Results show an increase in accuracy for faulting predictions using the new reliability model with various design characteristics. Moreover, the new reliability model allows design of JPCP considering higher levels of traffic because of the less conservative predictions.

scholarly journals Selection of Heat Pump Capacity Used at Thermal Power Plants under Electricity Market Operating Conditions

Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 226
Author(s):  
Milana Treshcheva ◽  
Irina Anikina ◽  
Vitaly Sergeev ◽  
Sergey Skulkin ◽  
Dmitry Treshchev
Keyword(s):  
Electric Power ◽  
Heat Pump ◽  
Heat Load ◽  
Power Plants ◽  
Thermal Power ◽  
Heat Pumps ◽  
Operating Conditions ◽  
Energy Resources ◽  
Thermal Power Plants ◽  
Maximum Heat

The percentage of heat pumps used in thermal power plants (TPPs) in the fuel and energy balance is extremely low in in most countries. One of the reasons for this is the lack of a systematic approach to selecting and justifying the circuit solutions and equipment capacity. This article aims to develop a new method of calculating the maximum capacity of heat pumps. The method proposed in the article has elements of marginal analysis. It takes into account the limitation of heat pump capacity by break-even operation at electric power market (compensation of fuel expenses, connected with electric power production). In this case, the heat pump’s maximum allowable capacity depends on the electric capacity of TPP, electricity consumption for own needs, specific consumption of conditional fuel for electricity production, a ratio of prices for energy resources, and a conversion factor of heat pump. For TPP based on combined cycle gas turbine (CCGT) CCGT-450 with prices at the Russian energy resources markets at the level of 2019, when operating with the maximum heat load, the allowable heat pump capacity will be about 50 MW, and when operating with the minimum heat load—about 200 MW.

Beyond Deep Learning: An Econometric Example

2020 ◽  
Vol 28 (Supp01) ◽  
pp. 31-38 ◽  
Author(s):  
Ruofan Liao ◽  
Paravee Maneejuk ◽  
Songsak Sriboonchitta
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Prediction Models ◽  
Original Data ◽  
Parametric Model ◽  
Parametric Models ◽  
The Past ◽  
Currency Exchange ◽  
Currency Exchange Rate ◽  
Linear And Nonlinear

In the past, in many areas, the best prediction models were linear and nonlinear parametric models. In the last decade, in many application areas, deep learning has shown to lead to more accurate predictions than the parametric models. Deep learning-based predictions are reasonably accurate, but not perfect. How can we achieve better accuracy? To achieve this objective, we propose to combine neural networks with parametric model: namely, to train neural networks not on the original data, but on the differences between the actual data and the predictions of the parametric model. On the example of predicting currency exchange rate, we show that this idea indeed leads to more accurate predictions.

Designing CO2 Transmission Pipelines Without Crack Arrestors

2010 ◽  
Author(s):  
Graeme G. King ◽  
Satish Kumar
Keyword(s):  
Wall Thickness ◽  
Carbon Capture ◽  
Power Plants ◽  
Oil And Gas ◽  
Cost Optimization ◽  
Operating Conditions ◽  
Operating Pressure ◽  
Design Work ◽  
Industrial Facilities ◽  
Pipeline Network

Masdar is developing several carbon capture projects from power plants, smelters, steel works, industrial facilities and oil and gas processing plants in Abu Dhabi in a phased series of projects. Captured CO2 will be transported in a new national CO2 pipeline network with a nominal capacity of 20×106 T/y to oil reservoirs where it will be injected for reservoir management and sequestration. Design of the pipeline network considered three primary factors in the selection of wall thickness and toughness, (a) steady and transient operating conditions, (b) prevention of longitudinal ductile fractures and (c) optimization of total project owning and operating costs. The paper explains how the three factors affect wall thickness and toughness. It sets out code requirements that must be satisfied when choosing wall thickness and gives details of how to calculate toughness to prevent propagation of long ductile fracture in CO2 pipelines. It then uses cost optimization to resolve contention between the different requirements and arrive at a safe and economical pipeline design. The design work selected a design pressure of 24.5 MPa, well above the critical point for CO2 and much higher than is normally seen in conventional oil and gas pipelines. Despite its high operating pressure, the proposed network will be one of the safest pipeline systems in the world today.

Inlet Air Cooling Applied to Combined Cycle Power Plants: Influence of Site Climate and Thermal Storage Systems

2008 ◽  
Vol 130 (2) ◽  
Author(s):  
Nicola Palestra ◽  
Giovanna Barigozzi ◽  
Antonio Perdichizzi
Keyword(s):  
Power Output ◽  
Parametric Analysis ◽  
Power Plants ◽  
Cooling System ◽  
Thermal Storage ◽  
Combined Cycle ◽  
Operating Conditions ◽  
Air Cooling ◽  
Ambient Conditions ◽  
Cooling Systems

The paper presents the results of an investigation on inlet air cooling systems based on cool thermal storage, applied to combined cycle power plants. Such systems provide a significant increase of electric energy production in the peak hours; the charge of the cool thermal storage is performed instead during the night time. The inlet air cooling system also allows the plant to reduce power output dependence on ambient conditions. A 127MW combined cycle power plant operating in the Italian scenario is the object of this investigation. Two different technologies for cool thermal storage have been considered: ice harvester and stratified chilled water. To evaluate the performance of the combined cycle under different operating conditions, inlet cooling systems have been simulated with an in-house developed computational code. An economical analysis has been then performed. Different plant location sites have been considered, with the purpose to weigh up the influence of climatic conditions. Finally, a parametric analysis has been carried out in order to investigate how a variation of the thermal storage size affects the combined cycle performances and the investment profitability. It was found that both cool thermal storage technologies considered perform similarly in terms of gross extra production of energy. Despite this, the ice harvester shows higher parasitic load due to chillers consumptions. Warmer climates of the plant site resulted in a greater increase in the amount of operational hours than power output augmentation; investment profitability is different as well. Results of parametric analysis showed how important the size of inlet cooling storage may be for economical results.

CORRECTION OF PREDICTION MODEL OUTPUT–APPLICATION TO GENERAL CORROSION MODEL

2021 ◽  
Vol 156 (A4) ◽  
Author(s):  
N Hifi ◽  
N Barltrop
Keyword(s):  
Prediction Model ◽  
Reliability Analysis ◽  
Model Calibration ◽  
Structural Reliability ◽  
Prediction Models ◽  
General Corrosion ◽  
Model Output ◽  
Reliability Models ◽  
Corrosion Model ◽  
Recorded Data

This paper applies a newly developed methodology to calibrate the corrosion model within a structural reliability analysis. The methodology combines data from experience (measurements and expert judgment) and prediction models to adjust the structural reliability models. Two corrosion models published in the literature have been used to demonstrate the technique used for the model calibration. One model is used as a prediction for a future degradation and a second one to represent the inspection recorded data. The results of the calibration process are presented and discussed.

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