scholarly journals What Is Your Actual Pump Flow Rate?

2017 ◽  
Author(s):  
Norman F. Perkins ◽  
Philip S. Stacy
Keyword(s):  
Power Plant ◽  
Performance Test ◽  
Performance Testing ◽  
Field Performance ◽  
Thermal Plant ◽  
Power Plant Equipment ◽  
Uncertainty Estimates ◽  
Pump Flow Rate ◽  
Aging Infrastructure ◽  
Simple Question

What appears to be a simple question is often quite difficult to answer depending on the quantity of flow; and size, type, and location of piping. Even the reason for asking the question can be varied and complex — ranging from environmental regulation, investment decisions, aging infrastructure improvement planning, and new equipment evaluation. Absolute field performance testing of power plant equipment yields valuable data that can be used in a variety of ways. National and International codes list several methods to measure water flow in a performance application and provide realistic uncertainty estimates. Codes and standards exist for equipment evaluation and contractual performance tests. These Codes, though, are sometimes viewed as costly or perceived to impose additional risk on suppliers. Herein, we will present how to obtain performance test data and how that data can be used. In many rehabilitation or regulation driven projects, an accurate representation of the state of the existing power plant is desired. Pump curves typically do not represent an accurate depiction of flow due to equipment degradation, changes in system components/geometry, and/or bio-fouling. While the testing may be considered costly, it can often be justified as part of a rehabilitation project. Absolute testing provides a lower uncertainty that can yield more definitive estimates of return on investment to justify projects that might be otherwise considered marginal. Case studies will be discussed that illustrate these points, including: • Flow measurement feasibility and site testing at a nuclear thermal plant • In-situ flow testing to calibrate existing ultrasonic flow meters at a biomass thermal plant • Condenser performance testing at a nuclear thermal plant Paper published with permission.

Evaluation of Asphalt Mixture Performance Using Cracking and Durability Tests at a Full-Scale Pavement Facility

2021 ◽  
pp. 036119812110218
Author(s):  
Amir Golalipour ◽  
Varun Veginati ◽  
David J. Mensching
Keyword(s):  
Performance Test ◽  
Asphalt Mixture ◽  
Performance Testing ◽  
Field Performance ◽  
Optimization Procedure ◽  
Cyclic Fatigue ◽  
Intermediate Temperature ◽  
Index Test ◽  
Reclaimed Asphalt ◽  
Indirect Tensile

In the asphalt materials community, the most critical research need is centered around a paradigm shift in mixture design from the volumetric process of the previous 20-plus years to an optimization procedure based on laboratory-measured mechanical properties that should lead to an increase in long-term pavement performance. This study is focused on advancing the state of understanding with respect to the value of intermediate temperature cracking tests, which may be included in a balanced mix design. The materials included are plant-mixed, laboratory-compacted specimens reheated from the 2013 Federal Highway Administration’s (FHWA’s) Accelerated Loading Facility (ALF) study on reclaimed asphalt pavement/reclaimed asphalt shingle (RAP/RAS) materials. Six commonly discussed intermediate temperature (cracking and durability) performance testing (i.e., Asphalt Mixture Performance Tester [AMPT] Cyclic Fatigue, Cantabro, Illinois Flexibility Index Test [I-FIT], Indirect Tensile Cracking [ITC, also known as IDEAL-CT], Indirect Tensile Nflex, and Texas Overlay Test) were selected for use in this study based on input from stakeholders. Test results were analyzed to compare differences between the cracking tests. In addition, statistical analyses were conducted to assess the separation among materials (lanes) for each performance test. Cyclic fatigue and IDEAL-CT tests showed the most promising results. The ranking from these two tests’ index parameters matched closely with ALF field performance. Furthermore, both showed reasonable variability of test data and they were successful in differentiating between different materials.

Performance Testing of Coal Fired Power Plants

2007 ◽  
Author(s):  
Shane E. Powers ◽  
William C. Wood
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Performance Test ◽  
Model Development ◽  
Performance Testing ◽  
The United States ◽  
Plant Performance ◽  
Cycle Performance ◽  
Test Program

With the renewed interest in the construction of coal-fired power plants in the United States, there has also been an increased interest in the methodology used to calculate/determine the overall performance of a coal fired power plant. This methodology is detailed in the ASME PTC 46 (1996) Code, which provides an excellent framework for determining the power output and heat rate of coal fired power plants. Unfortunately, the power industry has been slow to adopt this methodology, in part because of the lack of some details in the Code regarding the planning needed to design a performance test program for the determination of coal fired power plant performance. This paper will expand on the ASME PTC 46 (1996) Code by discussing key concepts that need to be addressed when planning an overall plant performance test of a coal fired power plant. The most difficult aspect of calculating coal fired power plant performance is integrating the calculation of boiler performance with the calculation of turbine cycle performance and other balance of plant aspects. If proper planning of the performance test is not performed, the integration of boiler and turbine data will result in a test result that does not accurately reflect the true performance of the overall plant. This planning must start very early in the development of the test program, and be implemented in all stages of the test program design. This paper will address the necessary planning of the test program, including: • Determination of Actual Plant Performance. • Selection of a Test Goal. • Development of the Basic Correction Algorithm. • Designing a Plant Model. • Development of Correction Curves. • Operation of the Power Plant during the Test. All nomenclature in this paper utilizes the ASME PTC 46 definitions for the calculation and correction of plant performance.

An improved model for predicting the efficiency of hydraulic propeller turbines

2005 ◽  
Vol 32 (5) ◽  
pp. 789-795 ◽  
Author(s):  
Jessica Manness ◽  
Jay Doering
Keyword(s):  
Performance Test ◽  
Performance Testing ◽  
Field Performance ◽  
Large Data ◽  
Hydraulic Turbine ◽  
Original Method ◽  
Large Network ◽  
Periodic Field ◽  
Data Set ◽  
Efficient Operation

Field performance testing of hydraulic turbines is undertaken to define the head-power-discharge relationship that identifies the peak operating point of the turbine. This relationship is essential for the efficient operation of a hydraulic turbine. Unfortunately, in some cases it is not feasible to field test turbines because of time, budgetary, or other constraints. Gordon (2001) proposed a method of predicting and (or) simulating the performance curve for several types of turbines. However, a limited data set was available for the development of his model for certain types of turbines. Moreover, his model did not include a precise method of developing performance curves for rerunnered turbines. Manitoba Hydro operates a large network of hydroelectric turbines, which are subject to periodic field performance testing. This provided a large data set with which to refine the model proposed by Gordon (2001). Furthermore, since these data include rerunnered units, this provides an opportunity to refine the effects of rerunnering. Analysis shows that the accuracy of the refined model is within 2% of the performance test results for an "old" turbine, while for a newer turbine or a rerunnered turbine the error is within 1%. For both an old turbine and a rerunnered turbine, this indicates an accuracy improvement of 3% over the original method proposed by Gordon (2001).Key words: hydraulic turbine, efficiency, simulation modeling

Consideration of Co-Variance in Power Plant Test Uncertainty Calculations

2007 ◽  
Author(s):  
Terrence B. Sullivan ◽  
Keith Kirkpatrick
Keyword(s):  
Power Plant ◽  
Thermal Performance ◽  
Performance Test ◽  
Performance Testing ◽  
Random Component ◽  
Plant Test ◽  
American Society ◽  
Test Uncertainty

One of the most important aspects of American Society of Mechanical Engineers (ASME) Performance Test Code (PTC) thermal performance testing is the proper determination of test uncertainty since the Uncertainty Analysis (UA) validates the quality of a test as well as demonstrates that the test meets code requirements. It can also carry a commercial relevance when test tolerances are linked to uncertainty figures. This paper introduces an approach to the calculation of the random component of uncertainty when covariance exists between certain primary measurements in thermal performance testing. It demonstrates how to identify parameters that are co-variant, provides a methodology for properly calculating the aggregated random uncertainty of co-variant measurements, and discusses the effect of co-variance on UA results.

scholarly journals Synthesis of ZSM-5 zeolites from biomass power plant ash for removal of ionic dyes from aqueous solution: equilibrium isotherm, kinetic and thermodynamic analysis

RSC Advances ◽  
2021 ◽  
Vol 11 (36) ◽  
pp. 22365-22375
Author(s):  
Guangbing Liang ◽  
Yanhong Li ◽  
Chun Yang ◽  
Xun Hu ◽  
Qingyin Li ◽  
...  
Keyword(s):  
Power Plant ◽  
Performance Testing ◽  
Value Added ◽  
Adsorption Performance ◽  
Original Intention ◽  
Power Plant Ash ◽  
Kinetic And Thermodynamic Analysis ◽  
Biomass Power Plant ◽  
First Time ◽  
Plant Ash

In this work, industrial biomass power plant ash was used to synthesize the ZSM-5 zeolites for the first time with the original intention to turn value-added material into wealth, and then committed to adsorption performance testing.

A Comparative Study of Genetic Algorithms and Gradient Methods for RM12 Turbofan Engine Diagnostics and Performance Estimation

2004 ◽  
Author(s):  
Tomas Gro¨nstedt ◽  
Markus Wallin
Keyword(s):  
Gas Turbine ◽  
Performance Test ◽  
Gradient Methods ◽  
Performance Testing ◽  
Performance Estimation ◽  
Data Sets ◽  
Data Set ◽  
Turbofan Engine ◽  
Local Optima ◽  
Bypass Ratio

Recent work on gas turbine diagnostics based on optimisation techniques advocates two different approaches: 1) Stochastic optimisation, including Genetic Algorithm techniques, for its robustness when optimising objective functions with many local optima and 2) Gradient based methods mainly for their computational efficiency. For smooth and single optimum functions, gradient methods are known to provide superior numerical performance. This paper addresses the key issue for method selection, i.e. whether multiple local optima may occur when the optimisation approach is applied to real engine testing. Two performance test data sets for the RM12 low bypass ratio turbofan engine, powering the Swedish Fighter Gripen, have been analysed. One set of data was recorded during performance testing of a highly degraded engine. This engine has been subjected to Accelerated Mission Testing (AMT) cycles corresponding to more than 4000 hours of run time. The other data set was recorded for a development engine with less than 200 hours of operation. The search for multiple optima was performed starting from more than 100 extreme points. Not a single case of multi-modality was encountered, i.e. one unique solution for each of the two data sets was consistently obtained. The RM12 engine cycle is typical for a modern fighter engine, implying that the obtained results can be transferred to, at least, most low bypass ratio turbofan engines. The paper goes on to describe the numerical difficulties that had to be resolved to obtain efficient and robust performance by the gradient solvers. Ill conditioning and noise may, as illustrated on a model problem, introduce local optima without a correspondence in the gas turbine physics. Numerical methods exploiting the special problem structure represented by a non-linear least squares formulation is given special attention. Finally, a mixed norm allowing for both robustness and numerical efficiency is suggested.

Early Warning of Power Plant Equipment Based on Massive Real-Time Data Mining Technology

2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Early Warning ◽  
Time Data ◽  
Mining Technology ◽  
Equipment Safety ◽  
State Evaluation ◽  
Power Plant Equipment ◽  
Real Time Data

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.

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