Plant Test Data Research Articles

Modeling of moving bed CO2 capture process using amine solid adsorbent and its validation using pilot plant test data

A modeling study is presented for a pilot plant of a moving bed adsorption process for carbon dioxide (CO2) capture using an amine solid sorbent. The pilot plant consists of four towers—adsorption, desorption, and two drying towers. The plant has a capacity of approximately 5 ton-CO2/day, which is the largest scale in the world as a moving bed for CO2 capture using an amine-loaded solid sorbent. Using this plant, 11 operating conditions were implemented and tested. The isotherm in the model were established from lab-scale measurements. For the 11 conditions, the model successfully captured the influences of operating conditions, such as the circulation flow rate of solid sorbent, amount of solid sorbent, temperature and humidity of the feed gas, and amount of steam introduced in the desorption step. Furthermore, the temperature of the solid sorbent and composition of the outlet gases was found to be in agreement with the model.

Techno-economic evaluation of post-combustion carbon capture based on chemical absorption for the thermal cracking furnace in ethylene manufacturing

As the core unit of an ethylene production plant, thermal cracking furnace generates a large amount of CO2 emissions. To reduce the CO2 emissions, post-combustion carbon capture based on chemical absorption using monoethanolamine (MEA) solvent is used to capture CO2 from the thermal cracking furnace. The computational fluid dynamics (CFD) method was used to simulate the operation of a 60kt/a thermal cracking furnace to obtain the flow rate and composition of the flue gas. A carbon capture plant model was developed using Aspen Plus® and validated using the pilot plant test data from Technology Centre Mongstad (TCM) in Norway. Scale-up of the capture plant model was carried out to match the flue gas flow rate of the thermal cracking furnace. Two integration cases of the carbon capture plant and the industrial thermal cracking unit were carried out. The results show that the excess heat of the gasoline fractionator can be used to provide heat for the carbon capture plant without affecting ethylene production. The economic evaluation was conducted based on the two case studies. Results show that the cost of CO2 capture can be reduced from $80.03/tonne (without heat integration) to $70.41/tonne with heat integration. When considering the impact of carbon credits on capture costs, the cost will be further reduced to $50.41/tonne.

DMC controller design for an integrated Allam cycle and air separation plant

Advanced process control is developed for a novel oxy-fuel Allam cycle power plant integrated with an Air Separation Unit (ASU) with no greenhouse gas and NOx emissions. The Dynamic Matrix Control (DMC) controller was developed with AspenTech's DMC Technology Version 11 engineering software. The DMC controller improves nitrogen purity, carbon dioxide purity and flowrate, and power output by an average of 4%. Also, the DMC controller is able to handle disturbances in the range of 12.5% for feed flow changes and 10% for feed composition changes. Substantial enhancement was observed in upgrading carbon dioxide purity from 97% Enhanced Oil Recovery (EOR) grade to 99.9% food/medical grade. Therefore, this advanced control strategy is superior to regulatory PID controllers and the developed DMC controller can be used as a seed model in the actual plant control by combining with the actual plant test data in the calibrate mode.

Sensitivity Analysis of an Excitation System in Order to Simplify and Validate Dynamic Model Utilizing Plant Test Data

Electrical system dynamic modeling of associated components such as generators, turbines and other drivers, excitation systems, governors, and rotating loads requires countless engineering man-hours to determine the models' necessary parameters. Therefore, any reduction or simplification of the component dynamic models that can be performed, while assuring statistically equivalent analyses results, will reduce man-hours and modeling process duration. This paper addresses generator excitation system models, which include complex Laplace transfer functions typically provided in IEEE Std 421.5-2005, along with their simplification and parameter reduction by utilizing a novel sensitivity analysis method; the method yields a simplified IEEE model. It further addresses the process for digitizing hard copy trace recorder plots of power plant field test data. This paper then addresses the tuning process for obtaining optimized exciter model parameters. Finally, the original and simplified exciter models are used to perform system dynamic analysis on a stand-alone 6.9-kV microgrid with five large sequentially started induction motors powered from a 7-MW diesel generator with an IEEE type AC5A excitation system. The results of the two dynamic analyses validate the entire process by comparison with the sequential motor start test results.

A pilot reactor study to determine operational factors of the commercial hydrodesulphurization (HDS) catalyst to produce ultra-low sulphur diesel (ULSD)

A pilot plant test was carried out using a catalyst from the refinery hydrotreater unit to process blend feed of 70vol% Light Gas Oil – LGO & 30vol% hydrotreated Gas Oil – HDT GO to produce 8ppm ultra-low sulphur diesel (ULSD) product. The impact of changes in process conditions have been studied for catalyst deactivation rate and hydrogen consumption. Test results shown that refinery unit can process such blend feed to reach 8ppm sulphur product by an increase of the reactor bed temperature. However due to higher aromatic content in the blend feed as compare to reference feed LGO, moderate increase in hydrogen consumption was also observed. Catalyst performance was evaluated at 55/42/32bar hydrogen partial pressure (PPH2) to determine catalyst deactivation rate and hydrogen consumption, targeting ULSD product. A decrease of PPH2 from 52bar (which is current operating condition) to 32bar resulted in reduction of H2 consumption but also shows decrease of catalyst cycle length due to higher deactivation rate. Pilot plant test shows that by contriving computational methods and analysis techniques for hydrogen balance & catalyst deactivation rate from the pilot plant test data, it becomes possible to predict catalyst performance in commercial unit.

A new small-scale test to determine flotation performance – Part 1: Overall performance

The majority of flotation models incorporate a parameter that describes the propensity of particles or classes of particles to be recovered through true flotation. This is typically captured in the flotation rate constant or “floatability”, and results from complex interactions between particles, solid/liquid/air interfaces and operational variables.Historically, there have been two distinct approaches in determining flotation rate parameters for industrial circuits. Fundamental approaches have focused on mechanisms for quantifying particle–bubble interactions and how these relate to kinetics. The more applied approach, which uses floatability components (grouping of particles that have the same flotation behaviour in terms of rate of recovery), relies on the availability of plant and batch test data, as well as specialised equipment measurements, to back-calculate floatability components or rate parameters, and their distribution in the feed. Since the parameters are derived from experimental data they are only applicable under the specific operating and feed conditions from which they are derived.A third method is emerging which applies mineralogical data to determine the flotation response of individual particles. This is done typically through a Cassie-type approach if the rates of the liberated components are known, or by developing a database of information which relates the flotation response of classes of particles to key mineralogical features.In this paper, a new small-scale test is presented, to compliment current laboratory batch test methods for separability characterisation. Data are presented to demonstrate the comparability of the overall separation achieved in the small-scale test to batch flotation and full scale plant measurements. The small-scale test is shown to be sufficiently sensitive to particle surface attributes, and based on the results presented in this paper, is a good candidate for further development to potentially determining flotation rate parameters. Work in this area is ongoing and will be reported in a subsequent article.

Simulation and Analysis of a Tubular Fixed‐Bed Fischer‐Tropsch Synthesis Reactor with Co‐Based Catalyst

AbstractA two‐dimensional pseudohomogeneous reactor model is proposed to simulate the performance of fixed‐bed Fischer‐Tropsch synthesis (FTS) reactors by lumped thought. A CO consumption kinetics equation and a carbon chain growth probability model were incorporated into the reactor model. The model equations discretized by a two‐dimensional orthogonal collocation method were solved by the Broyden method. Concentration and temperature profiles were obtained. The validity of the reactor model against the pilot plant test data was investigated. Satisfactory agreements between model prediction values and experiment results were obtained. Further simulations were carried out to investigate the effect of operating conditions on the reaction behavior of the fixed‐bed FTS reactor.

Detection of Unmeasured Disturbances in Model Predictive Control (MPC) Plant Test Data

The fidelity of MPC models can be significantly compromised if the effect of unmeasured disturbances is contained in the data set used to identify the process models. This paper addresses an asymptotical detection method (ADM) based on the normalized primary residual and the χ2 statistic. An iteratively procedure, based on ADM, is proposed for removing data containing the effect of unmeasured disturbances until all the data passes the ADM χ2 test. A detailed simulation of a refining FCC unit is used to evaluate the performance of the proposed method for identifying unmeasured disturbances. A series of random walk unmeasured disturbances with varying amplitudes was applied during a simulated testing period. The proposed algorithm was applied to iteratively identify and remove the corrupted data. After the corrupted data were removed, the identified MPC models showed significant improvement. The sensitivity of the ADM to measurement noise is also evaluated.

OECD/DOE/CEA VVER-1000 coolant transient (V1000CT) benchmark – A consistent approach for assessing coupled codes for RIA analysis

The rod ejection accident (REA) and the main steam line break (MSLB) are two of the most important design basis accidents (DBA) for VVER-1000 exhibiting significant localized space-time effects. A consistent approach for assessing coupled three-dimensional (3-D) neutron kinetics/thermal-hydraulics codes for reactivity insertion accidents (RIA) is to first validate the codes using the available plant test (measured) data and after that to perform cross code comparative analysis for REA and MSLB scenarios. The coupled 3-D neutron kinetics/thermal-hydraulics benchmark presented in this paper is based on data from the Unit #6 of the Bulgarian Kozloduy Nuclear Power Plant (KNPP) and it is entitled the VVER-1000 coolant transient (V1000CT) benchmark. Two real plant transients are selected for simulation in the benchmark: main coolant pump start-up (Phase 1) and coolant mixing tests (Phase 2). In addition to these transients extreme scenarios were defined for better testing 3-D neutronics/thermal-hydraulics coupling: rod ejection simulation with control rod being ejected in the core sector cooled by the switched on MCP (Phase 1) and MSLB transient (Phase 2). The paper presents an overview of the Phase 1 (V1000CT-1) benchmark activities and describes the approach used for assessing the coupled neutron kinetics/thermal-hydraulics codes. Selected comparative analysis of currently submitted participants' results is presented with emphasis on the observed modeling issues and deviations from the measured data.

A Computational Model of a Combined Cycle Power Generation Unit

A computational model of a combined cycle power generation unit is developed and applied to one operated by a local utility company. The objective is to predict the performance of this unit by carrying out energy and exergy analyses of its components. The model is based on thermodynamic, heat transfer, and psychrometric principles, and includes an inlet air conditioning (fogging) system for the gas turbine cycle. To evaluate the model, simulation results are compared with available plant test data at rated load with and without the inlet fogging system in operation.

Industrial plant for Xenon extraction from tail streams of air fractionating plants

A schematic diagram of the plant for getting nitrogen-xenon mixture from “dirty” oxygen of air-fractionating plant (AFP) is shown and described. Industrial plant test data are presented in the form of relationship of the adsorber operation time with the temperature of the “dirty” oxygen at the inlet and of the duration of the application stage with the xenon concentration at the inlet.

Formation and elimination of polychlorinated dibenzo- p -dioxins and polychlorinated dibenzofurans from municipal solid waste incinerators

The emissions of polychlorinated dibenzo- p -dioxins and polychlorinated dibenzofurans (PCDD/Fs) from incineration processes has become a major subject of considerable public and scientific concern in light of the evidence of their extreme toxicity. Efficient control of PCDD/F emissions from municipal solid waste (MSW) incineration plants requires fundamental knowledge of the pathways by which they are formed in these plants. Analytical tests conducted on several MSW incinerator residues confirmed that PCDD/Fs form in the heat recovery unit of the incinerator plant and are removed from the flue gas in the fabric filter. A mathematical model for predicting PCDD/F emissions from MSW incinerator plants was developed based on governing equations for their formation through the de novo synthesis mechanism in the post-combustion zone and their removal by the fabric filter. The PCDD/F concentrations and removal efficiencies computed using the mathematical model were also found to correspond remarkably well with plant test data.

Seasonal Variation in Nutrient Status of Australian Waxflowers

Seasonal fluctuations in the concentrations of 12 nutrients were assessed over 3 years for Chamelaucium uncinatum cultivars Alba and Purple Pride and for Chamelaucium hybrid (C. floriferum × C. uncinatum) known locally as Walpole wax. The plantings were located in the Mount Lofty Ranges, Lower South East and Lower Murray regions of South Australia. Tips of stems, 25–40 mm long, were collected on a monthly basis. The nutrient data were used to identify the most suitable time for tissue analysis; to determine the magnitude of the differences in nutrient composition between cultivars; and to determine the correlations between nutrients. The effect of the sampling error was also determined. The seasonal decrease in concentrations of nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), and sulfur (S) corresponded with vegetative flushing (growth dilution effect). Concentrations of the variably mobile nutrients copper (Cu) and zinc (Zn) were unstable, particularly during autumn–winter. Concentrations of phloem immobile nutrients calcium (Ca), boron (B), and manganese (Mn) decreased early in the season, were lowest when vegetative flushing peaked (summer), and tended to increase in autumn and winter. For preferred sampling times, seasonal trends showed that concentrations of N, P, Ca, Mg, sodium (Na), chloride (Cl), B, Zn, and Mn were fairly stable over the period January–March. Similarly, concentrations of K, S, and Cu were relatively stable during the period July–September when vegetative growth was minimal. The error associated with our sampling procedure was within acceptable limits (coefficients of variation <10%) for N, P, K, Ca, Mg, Na, Cl, S, B, and Mn. For the cultivar Alba, the seasonal trends for all nutrients were similar even though they were grown at different sites. Nitrogen and Mg concentrations in stem tips of the cultivar Alba were consistently higher than those in stem tips of the cultivar Purple Pride. In contrast, concentrations of K, Na, Cl, and Mn were lower. For these nutrients, different interpretation standards may be required for these cultivars. Significant (P < 0.05) correlations were found between many nutrients. For example, K concentrations were positively correlated with Cl, S, Cu, and Zn and negatively correlated with Ca and Mg concentrations. These significant relationships may indicate synergistic and antagonistic interactions between nutrients, which need to be considered when interpreting plant test data.

Two‐step procedure for data‐based modeling for inferential control applications

AbstractA two‐step procedure for building an inferential control model, which uses both historical operation data and plant test data, is proposed. Motivation for using the two types of data is given, and a systematic way to combine them in the model‐identification step is proposed. Some potential problems associated with the procedure in practice and their solutions are discussed. The efficacy of the procedure is demonstrated in a case study involving a multicomponent distillation column simulated in HYSYS.

Statistical and causal model‐based approaches to fault detection and isolation

AbstractBoth fundamental and practical differences between two common approaches to fault detection and isolation are examined. One approach is based on causal state‐variable or parity‐relation models developed from theory or identified from plant test data. The faults are then detected and isolated using structured or directional residuals from these models. The multivariate statistical process control approaches are based on noncausal models built from historical process data using multivariate latent variable methods such as PCA and PLS. The faults are then detected by referencing future data against these covariance models, and isolation is attempted through examining contributions to the breakdown of the covariance structure. There are major differences between these approaches arising mainly from the different types of models and data utilized to build them. Each of them has clear, but complementary, strengths and weaknesses. These are discussed using simulated data from a CSTR process.

Relationships Between Statistical and Causal Model Based Approaches to Fault Detection and Isolation

Abstract This paper examines both the fundamental and the practical differences between two common approaches to fault detection and isolation. One approach is based on causal state variable or parity relation models developed from theory or identified from plant test data. The faults are then detected and isolated using structured or directional residuals from these models. The multivariate statistical process control approaches are based on non-causal models built from historical process data using multivariate latent variable methods such as PCA and PLS. The faults are then detected by referencing future data against these covariance models, and isolation is attempted through examining contributions to the breakdown of the covariance structure. There are major differences between these approaches arising mainly from the different types of models and data utilized to build them. Each of them has clear, but complementary strengths and weaknesses. These are discussed in some detail and illustrated using simulated data from a CSTR process.

Study of the behavior of thermal shield support system for the French plants

Degradation/failure of thermal shield support system in PWRs has been observed in the US as well as in foreign plants. In almost all cases, remedial actions were put in place at very high economic cost to the utilities only after the failures had occurred. This paper presents the results of a comprehensive study to predict the long-term behavior of a thermal shield support system due to flow-induced vibratory loads and thermal transients. Excellent agreement from the system finite model between the measured plant test data on the barrel/thermal shield beam and shell mode frequencies and the flexure strains confirms the basic structural behavior and physics of the flow induced vibrations. Loads and stresses on the support bolts and the flexures were determined to predict the fatigue life of the components.

Seismic individual plant examination of external events of US nuclear power plants: insights and implications

As part of the implementation of the severe accident policy, nuclear power plants in the US are conducting the individual plant examination of external events (IPEEE). Seismic events are treated in these IPEEEs by either a seismic probabilistic risk assessment (PRA) or a seismic margin assessment. The major elements of a seismic PRA are the seismic hazard analysis, seismic fragility evaluation of structures and equipment and systems analysis using event tree and fault tree analysis techniques to develop accident sequences and calculate their frequencies of occurrence. The seismic margin assessment is a deterministic evaluation of the seismic margin of the plant beyond the design basis earthquake. A review level earthquake is selected and some of the components that are on the success paths are screened out as exceeding the review level earthquake; the remaining ones are evaluated for their seismic capacity using information from the original plant design criteria, test data and plant walkdown. The IPEEEs of over 100 operating nuclear power plants are nearing completion. This paper summarizes the lessons learned in conducting the IPEEEs and their applicability to nuclear power plants outside of the United States.

Torsional system parameter identification of turbine-generator sets

Accurate low order linear models that represent the torsional motion of turbine-generator sets are needed for determining shaft torsional responses resulting from subsynchronous resonance conditions, electric system faults and planned/unplanned switching actions in the electric network. This paper outlines the theoretical background and the methodology used for identification of linear state-space models of turbine-generator systems. These analytic mass-spring-damper models are lumped-parameter approximations, which in reality represent a continuous nonlinear system. For transient torque studies these models are adequate representations of the torsional dynamics of interest. Reduced analytic models of any particular turbine-generator unit, however, usually do not match precisely the behavior of the real machine. The paper describes an optimization method that can give a more precise representation of a particular turbine-generator based on actual plant tests and an assumed model of that unit. The parameter identification process is illustrated using plant test data from a 618 MVA turbine-generator unit.

Assessment of the nitrogen and potassium status of irrigated Brussels sprouts (Brassica oleracea L. var. gemmifera) by plant analysis

Four field experiments were carried out during 1992-93 (sites 1 and 2) and 1993-94 (sites 3 and 4) to assess the effects of nitrogen (N), at rates up to 600 kgha, and potassium (K), at rates up to 300 kgha, on total N, nitrate-N and K concentrations in petioles of the youngest fully expanded leaves (P-YFEL) of Brussels sprouts (Brassica oleracea var. gemmifera). The experiments were located in commercial plantings in the Mt Lofty Ranges, South Australia. Plant samples were collected at 2-4-week intervals from 4 to 28 weeks after the plants were transplanted. Temporal or seasonal variation, and the effects on concentrations of total N, nitrate-N and K of sampling leaves next in age (YFEL-1 to YFEL+2) to the index leaf, were also studied. Total N concentration in P-YFEL was more sensitive to variations in N supply than nitrate-N at all sites. Total N and nitrate-N concentrations in petioles also varied with the age of the leaf sampled. Total N concentrations in petioles of leaves sampled 4-16 weeks after transplanting decreased with increasing leaf age. In contrast, nitrate-N concentrations in petioles sampled 4-8 weeks after transplanting increased with leaf age. Potassium concentrations in petioles did not vary consistently between leaves of different age. From 4 to 6 weeks after transplanting, relationships between total N or nitrate-N concentrations in P-YFEL and relative total yield were not significant (P&gt;0.05), therefore, critical concentrations could not be determined. Linear and quadratic models were used to study the relationships between total N and nitrate-N concentration in P-YFEL and relative total yield during 8-28 weeks after transplanting. Total N concentrations accounted for a greater amount of variation in relative total yield at 10, 12, 14, 16, 18, 20, 24 and 28 weeks after transplanting compared with nitrate-N. Coefficients of determination (r2) were in the range 0.52-0.93. Relationships between nitrate-N concentration in P-YFEL and relative total yield were only significant 8, 10, 14 and 16 weeks after transplanting and 9 values were in the range 0.49-0.82. Critical concentrations for total N decreased from 3.13-3.44% at 10 weeks to 1.22-1.38% at 28 weeks after transplanting. This decrease highlights the importance of carefully defining sampling time to ensure correct interpretation of plant test data. Potassium concentrations also decreased between 4 and 28 weeks after transplanting. Critical concentrations were not determined for K, because the crops at all sites did not respond significantly (P&gt;0.05) to applied K. Based on sensitivity (as indicated by the range in tissue concentrations in response to variations in N supply) and on the correlations between total N and nitrate-N concentrations and relative total yield, we concluded that total N was better than nitrate-N as an indicator of plant N status and yield response of Brussels sprouts. We suggested that growers sample P-YFEL several times during the growing season, starting 10 weeks after transplanting. Plant analysis can be used to monitor N status and to detect N deficiencies which may arise during the growing season of Brussels sprouts which may be up to 9 months duration. Growers can adjust their fertiliser N program to ensure deficiencies are quickly corrected.