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Show CRSim A F R C 2 0 1 5 Continuous Online Monitoring of Fireside Tube Skin Temperature in a Depropanizer Reboiler P. Smithuv, J. Thornockv, S. Smithv, M. Hradiskyv, D. Smithw, P. Emettw, K. Dainesx, B. Harrisx, uCRSim Inc, vThe University of Utah, wAPCO Inc, xHollyFrontier Corp ABSTRACT Continuous monitoring of the fireside skin temperature of process tubes is a difficult but desired objective for the safe and efficient operation of many process heaters and boilers. A new measurement technology has been developed for providing local skin temperatures in such furnaces. With this paper we present the development of this technology on a refinery process heater serving as a reboiler for the bottoms of a depropanizer tower. The cylindrical, vertical type furnace is operated by a refinery in North Salt Lake, Utah. It is fired from four floor-fired, staged fuel gas burners with individual gas pilots. There are 40 radiant tubes which are arranged vertically around the wall of the furnace. The technology for online monitoring of the maximum fireside skin temperatures takes advantage of the existing continuous measurements of the process side fluid temperature at the inlet and outlet of each coil in the heater. High performance computing simulations were performed to map out the operational space of the furnace. Surrogate models were constructed for the local skin temperatures as a function of operating parameters. Thus the skin temperature is correlated through the non-linear detailed model of the combustion process to the continuous measurements of the outlet process temperature of each of the coils. This model is calibrated and updated through continuous feedback through remote monitoring of the furnace operating conditions. The first phase of deployment of this technology was to develop the instrument model and demonstrate proof-of-concept. This phase is presented in this paper. The final three stages, yet to be completed, are to validate the instrument model then deploy it, first offline, then online for continuous tube skin temperature monitoring. summer 2015 1 INTRODUCTION Most modern instruments use indirect measurement. For example when a thermocouple is used in a suction pyrometer to measure the temperature of combustion gases it requires the construction of a somewhat elaborate model of the the environment in which the measurement is being made in order to convert the measured voltage to the temperature output. This model involves an understanding of the Seebeck, Thomson and Peltier effects to relate the temperature to the voltage or electromotive force. It also requires models of the radiative losses from the thermocouple bead to the various layers of the suction pyrometer. Conductive/convective heat transfer models are incorporated to relate the bead temperature to the gas temperature. In the end, the voltage that is the direct measure is converted through the model to the indirect measure of temperature. In this paper we refer to this type of indirect model as the instrument model. Instrument models require validation and calibration. The validation process quantifies the degree of uncertainty of the output of the instrument model (i.e. gas temperature) to the uncertainty in the instrument model input (i.e. the measured voltage). The calibration process reduces the uncertainty in model parameters based on independently acquired information (including uncertainty) about the instrument model output (i.e. gas temperature). The instrument model is then run in near real time, coupled with modern data acquisition systems to continuously produce indirect output measurements. In this example the instrument model reads voltages from the thermocouple and produces continuous near real-time indirect measurement of the gas temperature. High performance computing and Bayesian analytics combine to provide an opportunity to efficiently use much more sophisticated instrument models than have ever been used before to produce indirect measurements of ever more difficult quantities of interest. In this paper we describe a project to produce an indirect measurement of fireside skin temperature of process tubes in process heaters and boilers. Tracking local tube skin temperatures for all tubes across all tube lengths is a difficult but desired objective for the safe and efficient operation of many process heaters and boilers. We present the development of this technology on a refinery process heater serving as a reboiler for the bottoms of a depropanizer tower. 2 THE REBOILER This fuel gas fired furnace acts as a reboiler on the bottom of the depropanizer tower. The furnace adds 25.6 MMBTU/hr to the bottom of this tower. It is designed for about 65 wt. % evaporation (91,750 lb/hr liquid, 176,000 lb/hr vapor) of charge passing through it at design conditions with an efficiency of 85%. The design maximum pressure is 500 psig at 450oF temperature. The reboiler furnace normally operates at 285 psig at 355oF at the inlet and 270 psig at 424-440oF at the outlet. This is a cylindrical, vertical type furnace and is fired from four John Zink PSFG-16RM staged fuel gas burners with individual gas pilots. The burners are mounted in the floor of the furnace. There are 120 tubes in the depropanizer reboiler heater. There are 64 finned and 16 bare or shield, horizontal tubes in the convection section. The shield tubes are located below the finned tubes to give a more even distribution of heat to the product and shield the finned tubes in the convection section. The 40 radiant tubes are 24'-0" long except the radiant inlet tubes which are 27'-6" long and the radiant outlet tubes which are 26'-6" long. The radiant tubes are arranged vertically around the wall of the furnace. The reboiler heater has four identical coil passes; north pass, north center pass, south center pass, and south pass. Each pass is equipped with transmitters to show the individual coil flows. Each coil pass has 16 3 finned convection tubes, 4 shield tubes, and 10 tubes in the radiant section. All the tubes are 4.5" O.D. A-106 Gr. B stainless steel material. All the return bends are welded. The flow enters each coil pass on the top row of the convection section and flows down through the convection sections, out the cross over and into the top of each radiant section. Flow enters each radiant coil pass, flows through the 10 tubes, and out the top of the radiant section and returns to the depropanizer tower. The radiant section north coil pass and north center coil pass outlets are on the north side of the furnace. The radiant section south center coil pass and south coil pass outlets are on the south side of the furnace. The furnace is 10'-5" diameter and 35'-0" tall, excluding the stack. The stack is 4'-0" diameter and 82'-0" tall and rests upon a transition section and rectangular convection section on top of the cylindrical part of the furnace. A damper is provided in the furnace stack and is manually operable from ground level. Smothering steam lines are provided for the firebox. The combustion air to the furnace is controlled by a damper system in the wind box on the bottom of the furnace. A flue gas sample connection is provided in the stack below the damper for running flue gas analysis (for pollution control and efficiency). 4 T H E D E V E L O P M E N T S T R AT E G Y This instrument development has been conducted with several collaborators. CRSim Inc. has developed the intellectual property. The high performance computer simulations have been developed by the authors at The University of Utah. The large eddy simulation software (ARCHES) is an open source distribution from the Institute for Clean and Secure Energy. HollyFrontier Corp. owns and operates the refinery and the reboiler technical support and data have been provided by HollyFrontier Corp. Apco Inc. has collaborated on the process data acquisition, control and online implementation of the instrument. The development strategy for the overall project has followed the following work plan: • Phase 1) Develop the instrument model for the reboiler; thus, producing a proof-ofconcept for the tube skin temperature measurement. • Phase 2) Produce static skin temperature measurement for HollyFrontier refinery base-case conditions. This constitutes the validation of the instrument model. • Phase 3) Develop map of operating conditions; thus, producing offline dynamic tube skin temperature measurement. • Phase 4) Deploy the online dynamic measurement at the refinery as part of the control system. The project was initiated this calendar year. This paper presents phase 1, the development of the instrument model. It is anticipated that phase 2-4 will be completed before year end. 5 THE INSTRUMENT MODEL Consistency Analysis Generate Sim Data Generate Surrogate Model Process Inputs (xi +/- ux) Process Measurement Data (ym +/- uy) (xo,s +/- ux) (Bayesian Analytics w/ Monte Carlo) CRSim ym 7! yi out (xo,s ) The instrument model is shown in a block-flow diagram above. SimMapp™ SimMapp™ measured process variable w/ error bars (yi +/- uy) 7! Tskin (l) The purpose of the instrument is to take the measurement of the exit process temperature from each of the four process coils (y , the measured output); and,skin through temperature the validated continuous measurement of tube and calibrated instrument model obtain a corresponding indirect measurement of the m measurement w/simulation local tube skin temperature on all four process & coilsuncertainty (y , the indirect outputquantification measurement). i using input, operating and scenario Theprocess process measurement data and process inputs (xo,s, processparameters operating and scenario parameters, xi, process input parameters) shown in this block diagram have been provided by HollyFrontier as indicated in the diagram. From all process input variables (xi) a dynamic, large-eddy simulation of the reboiler is performed across the span of all operating and scenarios parameters (xo,s). The figure below shows one temporal realization of this simulation space. Through this instrument model ym is mapped to yi. 6 The simulation space is then interpolated through a proprietary surrogate model for the high performance computer simulations. This surrogate model is what is used for the online instrument model. Its speed, efficiency and accuracy are quantified during the validation process. This surrogate model is used in the inverse process through Bayesian analytics to produce the resulting mapping of the measured process outlet fluid to local tube skin temperature. It is called a SimMapp. 7 The SimMapp calibration is performed with the measured outlet temperature using the most uncertain of the process scenario parameters as the calibration parameter. In this way, the calibration is performed continuously with each measurement (each realization of the SimMapp). In this application, the most uncertain parameter was the fouling on the exterior and interior of the tubes that results in a large uncertainty in the thermal resistance across the tubes. The uncertainty in this thermal resistance is reduced by continuously calibrating the outlet temperature from the instrument model with the measured outlet process fluid temperature (ym). One temporal realization of the measurement of the local coil skin temperature as a function of run length for each of the four coils in the reboiler is shown in the following figure. This constitutes one temporal realization of the SimMapp measurement: ! 8 In this realization of the instrument model there is a wind directed at the reboiler such that there is a temperature gradient on the exterior shell of the reboiler. The effect on the tubes is to produce an asymmetry that creates a range of temperatures for the four sets of tubes as shown in the figure. The process fluid and coil loops start at the top of the reboiler, take five passes and end at the top. The higher skin temperatures are near the bottom of the five passes of each coil but are somewhat cooler as the process fluid approach the bottom of the reboiler. The very highest temperatures arise in the bend at the bottom of the furnace. The coolest temperatures are near the top of each pass. In this temporal realization the hottest skin temperature is near 1000oF at the bottom turn of the 2nd pass, at about 80 ft from the inlet, of the southwest coil. The asymmetry in the heat flux created by the external weather conditions produces a lower skin temperature for the other coils. The process fluid temperatures as a function of run length is also obtained for each coil and for this proof-of-concept realization these temperatures are shown in the following figure: ! 9 The four coil process fluid outlet temperatures are those measured and dynamically recorded in the refinery data acquisition system. These measurements are used for the dynamic calibration of the instrument model. The inlet temperature for each coil is also dynamically measured and recorded at the refinery. This inlet temperature is one of the many process scenario parameters need for the instrument model. The variation of process fluid temperature along the run length of each coil is computed as part of the instrument model. The resulting vapor liquid split for the process fluid is required for the instrument model. We calculate it with a local flash calculation. The resulting mass fraction of vapor in each coil is shown here: ! 10 CONCLUSIONS High performance computing and Bayesian analytics combine to provide an opportunity to efficiently use much more sophisticated instrument models than have ever been used before to produce indirect measurements of ever more difficult quantities of interest. We have used these methods to produce an indirect measurement of fireside skin temperature of process tubes in process heaters and boilers. Tracking local tube skin temperatures for all tubes across all tube lengths is a difficult but desired objective for the safe and efficient operation of many process heaters and boilers. Deployment of this technology is under way for a refinery process heater serving as a reboiler for the bottoms of a depropanizer tower. The instrument model has been developed and a proof-ofconcept application has been completed. The validation and online deployment involves some changes in plant operation and monitoring and is currently underway. 11 |