Patent Publication Number: US-2022221149-A1

Title: Automatic air-flow settings in combustion systems and associated methods

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to, and benefits from U.S. Provisional Application Ser. No. 62/864,997, filed Jun. 21, 2019. This application is also related to each of: U.S. Provisional Application Ser. No. 62/864,954, filed Jun. 21, 2019; U.S. Provisional Application Ser. No. 62/864,967, filed Jun. 21, 2019; U.S. Provisional Application Ser. No. 62/864,992, filed Jun. 21, 2019; U.S. Provisional Application Ser. No. 62/865,007, filed Jun. 21, 2019; U.S. Provisional Application Ser. No. 62/865,021, filed Jun. 21, 2019; and U.S. Provisional Application Ser. No. 62/865,031, filed Jun. 21, 2019. The entire contents of each of the aforementioned applications are incorporated herein as if fully set forth. 
    
    
     BACKGROUND 
     Process heaters have multiple burners (sometimes up to 200+ burners per furnace) and each one has its own manual air register (also referred to as a damper) that can be used to throttle the airflow to a component of the heater (such as a burner). Some burner designs have multiple air register control handles. Many times, the air register handles are designed differently per burner technology. 
     Some applications require various air register setting per burner within the firebox based on the elevation at which the burner is installed or the fired heat release of each burner. 
     The “ideal air register setting” on each burner is historically very difficult to determine. Historically the system operator, by evaluating the excess O2 measured in the furnace, and manually adjusts the burner air registers to reduce the excess O 2  in the heater box. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
       The foregoing and other features and advantages of the disclosure will be apparent from the more particular description of the embodiments, as illustrated in the accompanying drawings, in which like reference characters refer to the same parts throughout the different figures. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the disclosure. 
         FIG. 1  depicts an example system of a process heater with automatic air register setting determination, in embodiments. 
         FIG. 2  depicts a typical draft profile throughout a heater (e.g., the heater of  FIG. 1 ). 
         FIG. 3  depicts a plurality of example process tube types. 
         FIG. 4  depicts a diagram showing air temperature and humidity effects on sensed excess O 2  levels. 
         FIG. 5  depicts a schematic of air and fuel mixture in a pre-mix burner, in embodiments. 
         FIG. 6  depicts a schematic of air and fuel mixture in a diffusion burner, in embodiments. 
         FIG. 7  depicts an example cutaway diagram of a burner, which is an example of the burner of  FIG. 1 . 
         FIG. 8  depicts an example air register handle and indicator plate  804  that is manually controlled. 
         FIG. 9  depicts example burner tips with different shapes and sizes. 
         FIG. 10  depicts example burner tips with the same shape, but different drill hole configurations. 
         FIG. 11  depicts a block diagram of the heater controller of  FIG. 1  in further detail, in embodiments. 
         FIG. 12  depicts an example air analyzer (e.g., the air analyzer of  FIG. 11 ), including an air-flow optimizer, in embodiments. 
         FIG. 13  depicts an example diagram indicating physical geometry of a COOLstar® burner indicating pressure losses throughout the burner, in an embodiment. 
         FIG. 14  depicts a heater with six rows of burners and six fired control zones. 
         FIG. 15  shows results from a fired-systems model showing how the air distributes to each of the plurality of burners of  FIG. 14  as a function of the duct design with the burner air registers full open, for example. 
         FIG. 16  depicts an example air ductwork having four air supply zones each coupled to a single air input. 
         FIG. 17  shows a CFD model of a forced (or balanced) draft system including a single airside pressure sensor. 
         FIG. 18  depicts a comparison of optimized (recommended) air register settings after optimization using the air-flow optimizer compared to the manually adjusted air-register settings, in an example. 
         FIG. 19  depicts a comparison of optimized (recommended) air register settings after optimization using the air-flow optimizer compared to the manually adjusted air-register settings, in an example. 
         FIG. 20  depicts visual impact on optimized burner air register settings after implementation of the airflow optimizer, in an embodiment. 
         FIG. 21  depicts additional benefits that are achieved after implementation of the airflow optimizer, in an embodiment. 
         FIGS. 22-23  depict the stoichiometric ratio (air/fuel ratio) of before and after, respectively, implementation of the airflow optimizer, in an embodiment. 
         FIG. 24  depicts a method for generating optimized air-flow settings in a combustion system, in embodiments. 
         FIG. 25  shows an example graph illustrating weather changes (such as seasonal changes) that impact the excess oxygen readings as compared to the designed/tuned conditions. 
         FIG. 26  depicts a method for generating optimized air-flow settings that achieve a desired combustion system control range over a period of time, in an embodiment. 
         FIG. 27  depicts an example of clogged fins on process tubes. 
     
    
    
     DETAILED DESCRIPTION OF THE EMBODIMENTS 
       FIG. 1  depicts an example system  100  of a process heater with intelligent monitoring system, in embodiments. The system  100  includes a heater  102  that is heated by one or more burners  104  located in the housing  103  thereof. Heater  102  can have any number of burners  104  therein, each operating under different operating conditions (as discussed in further detail below). Moreover, although  FIG. 1  shows a burner located on the floor of the heater  102 , one or more burners may also be located on the walls and/or ceiling of the heater  102  without departing from the scope hereof (indeed, heaters in the industry often have over 100 burners). Further, the heater  102  may have different configurations, for example a box heater, a cylindrical heater, a cabin heater, and other shapes, sizes, etc. as known in the art. 
     Burner  104  provides heat necessary to perform chemical reactions or heat up process fluid in one or more process tubes  106  (not all of which are labeled in  FIG. 1 . Any number of process tubes  106  may be located within the heater  102 , and in any configuration (e.g., horizontal, vertical, curved, off-set, slanted, or any configuration thereof). Burner  104  is configured to combust a fuel source  108  with an oxidizer such as air input  110  to convert the chemical energy in the fuel into thermal energy  112  (e.g., a flame). This thermal energy  112  then radiates to the process tubes  106  and is transferred through the process tubes  106  into a material therein that is being processed. Accordingly, the heater  102  typically has a radiant section  113 , a convection section  114 , and a stack  116 . Heat transfer from the thermal energy  112  to the process tubes  106  primarily occurs in the radiant section  113  and the convection section  114 . 
     Airflow into the heater  102  (through the burner  104 ) typically occurs in one of four ways natural, induced, forced, and balanced. 
     A natural induced airflow draft occurs via a difference in density of the flue gas inside the heater  102  caused by the combustion. There are no fans associated in a natural induced system. However, the stack  116  includes a stack damper  118  and the burner includes a burner air register  120  that are adjustable to change the amount of naturally induced airflow draft within the heater  102 . 
     An induced airflow draft system includes a stack fan (or blower)  122  located in the stack (or connected to the stack)  116 . In other or additional embodiments, other motive forces than a fan are be used to create the induced draft, such as steam injection to educts flue gas flow through the heater. The stack fan  122  operates to pull air through the burner air register  120  creating the induced-draft airflow within the heater  102 . The stack fan  122  operating parameters (such as the stack fan  122  speed and the stack damper  118  settings) and the burner air register  120  impact the draft airflow. The stack damper  118  may be a component of the stack fan  122 , or separate therefrom. 
     A forced-draft system includes an air input forced fan  124  that forces air input  110  into the heater  102  via the burner  104 . The forced fan  124  operating parameters (such as the forced fan  124  speed and the burner air register  120  settings) and the stack damper  118  impact the draft airflow. The burner air register  120  may be a component of the forced fan  124 , but is commonly separate therefrom and a component of the burner  104 . 
     A balanced-draft system includes both the air input forced fan  124  and the stack fan  122 . Each fan  122 ,  124  operate in concert, along with the burner air register  120  and stack damper  118  to control the airflow and draft throughout the heater  102 . 
     Draft throughout the heater  102  varies depending on the location within the heater  102 .  FIG. 2  depicts a typical draft profile  200  throughout a heater (e.g., heater  102 ). Line  202  depicts a desired draft that is consistent with the design of the heater and components therein. Line  204  depicts a high draft situation where pressure in the heater is more negative than desired (and thus further negative compared to atmospheric pressure outside of the heater). Line  206  depicts a low draft situation where pressure in the heater is more positive than desired (and thus closer to or greater than atmospheric pressure outside of the heater). As shown, by line  202 , heaters are often designed to have a − 0 . 1  pressure at the arch of the heater. 
     Draft throughout the heater  102  is also be impacted based on the geometry of the heater and components thereon. For example, draft is strongly a function of heater  102  height. The taller the heater  102 , the more negative the draft will be at the floor of the heater  102  to maintain the same draft level at the top of the heater  102  (normally − 0 . 1  in H 2 O). The components greatly impact the draft. For example,  FIG. 3  depicts a plurality of process tube types. The convection section process tubes  106  may or may not have heat sink fins thereon to manage the heat transfer from the thermal energy  112  to the process tube  106 . These convection section fins may plug or corrode overtime-varying the required draft within a heater as compared to the designed draft for the same heater with the same components. As the convection section flue gas channel open area begins to decrease, a greater pressure differential is required to pull the same quantity of flue gas through the convection section. 
     Referring to  FIG. 1 , pressure (indicating draft) within the heater  102  is measured at a variety of locations in the heater respectively via one of a plurality of pressure sensors. Floor pressure sensor  126 ( 1 ) measures the pressure at the floor of the heater  102 . Arch pressure sensor  126 ( 2 ) measures the pressure at the arch of the heater  102  where the radiant section  113  transitions to the convection section  114 . Convection pressure sensor  127  measures the pressure of the convection section  114 . Stack pressure sensor  129 , if included, measures the pressure of the stack  116 . 
     The pressure sensors  126 ,  127 ,  129  may include a manometer, or a Magnehelic draft gauge, where the pressure readings are manually entered into process controller  128  (or a handheld computer and then transferred wirelessly or via wired connection from the handheld computer to the process controller  128 ) including a sensor database  130  therein storing data from various components associated with the heater  102 . The pressure sensors  126 ,  127 ,  129  may also include electronic pressure sensors and/or draft transmitters that transmit the sensed pressure to the process controller  128  via a wired or wireless connection  133 . The wireless or wired connection  133  may be any communication protocol, including WiFi, cellular, CAN bus, etc. 
     The process controller  128  is a distributed control system (DCS) (or plant control system (PLC) used to control various systems throughout the system  100 , including fuel-side control (e.g., control of components associated with getting fuel source  108  into the heater  102  for combustion therein), air-side control (e.g., control of components associated with getting air source  110  into the heater  102 ), internal combustion-process control (e.g., components associated with managing production of the thermal energy  112 , such as draft within the heater  102 ), and post-combustion control (e.g., components associated with managing the emissions after production of the thermal energy  112  through the stack  116 ). The process controller  128  typically includes many control loops, in which autonomous controllers are distributed throughout the system  100  (associated with individual or multiple components thereof), and including a central operator supervisory control. 
     Operating conditions within the heater  102  (such as draft, and the stoichiometry associated with creating the thermal energy  112 ) are further impacted via atmospheric conditions, such as wind, wind direction, humidity, ambient air temperature, sea level, etc.  FIG. 4  depicts a diagram  400  showing air temperature and humidity effects on sensed excess O 2  levels. The changes in operating conditions are often controlled by monitoring and manipulating the draft conditions within the heater  102 . The stack dampers  118  are commonly digitally controlled, and therefore often controllable from the operating room of the system  100 , via the process controller  128 . However, many systems do not include burner air registers  120  that are digitally controlled. Because of this, system operators often control draft within the heater  102  using just an electronic stack damper (e.g., stack damper  118 ) thereby avoiding timely and costly manual operation of each burner air register (e.g., burner air register  120 ) associated with each individual burner (e.g., burner  104 ). This cost grows depending on the number of burners located in each heater—each heater may have over 100 burners therein. 
     In addition to the draft as discussed above, burner geometry plays a critical role in managing the thermal energy  112  produced in the heater  102 . Each burner  104  is configured to mix the fuel source  108  with the air source  110  to cause combustion and thereby create the thermal energy  112 . Common burner types include pre-mix burners and diffusion burners.  FIG. 5  depicts a schematic  500  of air and fuel mixture in a pre-mix burner, in embodiments. In a pre-mix burner, kinetic energy of the fuel gas  502  draws some primary air  504  needed for combustion into the burner. The fuel and air mix to create an air/fuel mixture  504  having a specific air-to-fuel ratio prior to igniting to create the thermal energy  112 .  FIG. 6  depicts a schematic  600  of air and fuel mixture in a diffusion burner, in embodiments. In a diffusion burner, air  604  for combustion is drawn (by induced- or natural-draft) or pushed (by forced-, or balanced-draft) into the heater before mixing with the fuel  602 . The mixture burns at the burner gas tip  606 . 
       FIG. 7  depicts an example cutaway diagram of a burner  700 , which is an example of the burner  104  of  FIG. 1 . Burner  700  is an example of a diffusion burner. Burner  700  is shown located mounted in a heater at the heater floor  702 . Proximate the burner  700  in the heater floor  702  is a manometer  704 , which is an example of the pressure sensors  126 ,  127 ,  129  discussed above. The manometer  704  may be another type of pressure sensor without departing from the scope hereof. Burner  700  is shown for a natural or induced-draft heater system, and includes a muffler  706  and a burner air register  708 . Ambient air flows through the muffler  706  from outside the heater system. In a forced or balanced-draft system, the muffler  706  may not be included and instead be replaced with an intake ducting from the forced fan (e.g., forced fan  124  in  FIG. 1 ). The burner air register  708  is an example of the burner air register  120  discussed above with respect to  FIG. 1 , and may be manipulated via an air register handle  710  to one of a plurality of settings defining how open or closed the air register  708  is. As discussed above, the air register handle  710  is typically manually controlled (although sometimes is fitted with an actuator, or provided with mechanical linkage and an actuator so a single actuator manipulates a plurality of burners).  FIG. 8  depicts an example air register handle  802  and indicator plate  804  that is manually controlled. The input air then travels through the burner plenum  712  towards the burner output  714  where it is mixed with input fuel and ignited to combust and produce thermal energy (e.g., thermal energy  112  of  FIG. 1 ). 
     The fuel travels through a fuel line  716 , and is output at a burner tip  718 . The fuel may be disbursed on a deflector  720 . The burner tip  718  and deflector  720  may be configured with a variety of shapes, sizes, fuel injection holes, etc. to achieve the desired combustion results (e.g., flame shaping, emissions tuning, etc.).  FIG. 9  depicts example burner tips with different shapes and sizes.  FIG. 10  depicts example burner tips with the same shape, but different drill hole configurations. Furthermore, one or more tiles  722  may be included at the burner output  714  to achieve a desired flame shape or other characteristic. 
     Referring to  FIG. 1 , control of the system  100  occurs both manually and digitally. As discussed above, various components, such as burner air register  120  are commonly manually controlled. However, the system  100  also includes a variety of sensors throughout the heater  102 , the fuel-side input, and the air-side input used to monitor and control the system using the process controller  128 . 
     At the stack  116 , an oxygen sensor  132 , a carbon monoxide sensor  134 , and NO x  sensor  136  can be utilized to monitor the condition of the exhaust and emissions leaving the heater  102  via the stack  116 . Each of the oxygen sensor  132 , carbon monoxide sensor  134 , and NO x  sensor  136  may be separate sensors, or part of a single gas-analysis system. The oxygen sensor  132 , carbon monoxide sensor  134 , and NO x  sensor  136  are each operatively coupled to the process controller  128  via a wired or wireless communication link. These sensors indicate the state of combustion in the heater  102  in substantially real-time. Data captured by these sensors is transmitted to the process controller  128  and stored in the sensor database  130 . By monitoring the combustion process represented by at least one of the oxygen sensor  132 , carbon monoxide sensor  134 , and NO x  sensor  136 , the system operator may adjust the process and combustion to stabilize the heater  102 , improve efficiency, and/or reduce emissions. In some examples, other sensors, not shown, can be included to monitor other emissions (e.g., combustibles, methane, sulfur dioxide, particulates, carbon dioxide, etc.) on a real-time basis to comply with environmental regulations and/or add constraints to the operation of the process system. Further, although the oxygen sensor  132 , carbon monoxide sensor  134 , and NO x  sensor  136  are shown in the stack  116 , there may be additional oxygen sensor(s), carbon monoxide sensor(s), and NO x  sensor(s) located elsewhere in the heater  102 , such as at one or more of the convection section  114 , radiant section  113 , and/or arch of the heater  102 . The above discussed sensors in the stack section may include a flue gas analyzer (not shown) prior to transmission to the process controller  128  that extract, or otherwise test, a sample of the emitted gas within the stack  116  (or other section of the heater) and perform an analysis on the sample to determine the associated oxygen, carbon monoxide, or NO x  levels in the sample (or other analyzed gas). Other types of sensors include tunable laser diode absorption spectroscopy (TDLAS) systems that determine the chemical composition of the gas based on laser spectroscopy. 
     Flue gas temperature may also be monitored by the process controller  128 . To monitor the flue gas temperatures, the heater  102  may include one or more of a stack temperature sensor  138 , a convection sensor temperature sensor  140 , and a radiant temperature sensor  142  that are operatively coupled to the process controller  128 . Data from the temperature sensors  138 ,  140 ,  142  are transmitted to the process controller  128  and stored in the sensor database  130 . Further, each section may have a plurality of temperature sensors—in the example of  FIG. 1 , there are three radiant section temperature sensors  142 ( 1 )-( 3 ). The above discussed temperature sensors may include a thermocouple, suction pyrometer, and/or laser spectroscopy analysis systems that determine the temperature associated with the given temperature sensor. 
     The process controller  128  may further monitor air-side measurements and control airflow into the burner  104  and heater  102 . Air-side measurement devices include an air temperature sensor  144 , an air-humidity sensor  146 , a pre-burner air register air pressure sensor  148 , and a post-burner air register air pressure sensor  150 . In embodiments, the post-burner air pressure is determined based on monitoring excess oxygen readings in the heater  102 . The air-side measurement devices are coupled within or to the air-side ductwork  151  to measure characteristics of the air flowing into the burner  104  and heater  102 . The air-temperature sensor  144  may be configured to sense ambient air temperatures, particularly for natural and induced-draft systems. The air-temperature sensor  144  may also be configured to detect air temperature just prior to entering the burner  104  such that any pre-heated air from an air-preheat system is taken into consideration by the process controller  128 . The air-temperature sensor  144  may be a thermocouple, suction pyrometer, or any other temperature measuring device known in the art. The air humidity sensor  146  may be a component of the air temperature sensor, or may be separate therefrom, and is configured to sense the humidity in the air entering the burner  104 . The air temperature sensor  144  and air humidity sensor  146  may be located upstream or downstream from the burner air register  120  without departing from the scope hereof. The pre-burner air register air pressure sensor  148  is configured to determine the air pressure before the burner air register  120 . The post-burner air register air pressure sensor  150  is configured to determine the air pressure after the burner air register  120 . The post-burner air register air pressure sensor  150  may not be a sensor measuring the furnace draft at the burner elevation, or other elevation and then calculated to determine the furnace draft at the burner elevation. Comparisons between the post-burner air register air pressure sensor  150  and the pre-burner air register air pressure sensor  148  may be made by the process controller to determine the pressure drop across the burner  104 , particularly in a forced-draft or balanced-draft system. Air-side and temperature measurements discussed herein may further be measured using one or more TDLAS devices  147  located within the heater  102  (at any of the radiant section  113 , convection section  114 , and/or stack  116 ). 
     Burner  104  operational parameters may further be monitored using a flame scanner  149 . Flame scanners  149  operate to analyze frequency oscillations in ultraviolet and/or infrared wavelengths of one or both of the main burner flame or the burner pilot light. 
       FIG. 1  also shows an air handling damper  152  that is located prior to the burner air register  120 . The air-handling damper  152  includes any damper that impacts air-flow into the heater  102 , such as a duct damper, variable speed fan, fixed-speed fan with air throttling damper, etc.) In certain system configurations, a single air input (including a given fan  124 ) supplies air to a plurality of burners, or a plurality of zones within a given heater. There may be any number of fans (e.g., forced fan  124 ), temperature sensors (e.g., air temperature sensor  144 ), air humidity sensors (e.g., air humidity sensor  146 ), air pressure sensors (e.g., pre-burner air register air pressure sensor  148 ) for a given configuration. Further, any of these air-side sensors maybe located upstream or downstream from the air handling damper  152  without departing form the scope hereof. 
     The process controller  128  may further monitor fuel-side measurements and control fuel flow into the burner  104 . Fuel-side measurement devices include one or more of flow sensor  154 , fuel temperature sensor  156 , and fuel-pressure sensor  158 . The fuel-side measurement devices are coupled within or to the fuel supply line(s)  160  to measure characteristics of the fuel flowing into the burner  104 . The flow sensor  154  may be configured to sense flow of the fuel through the fuel supply line  160 . The fuel-temperature sensor  156  detects fuel temperature in the fuel supply line  160 , and includes known temperature sensors such as a thermocouple. The fuel-pressure sensor  158  detects fuel-pressure in the fuel supply line  160 . 
     The fuel line(s)  160  may have a plurality of fuel control valves  162  located thereon. These fuel control valves  162  operate to control the flow of fuel through the supply lines  160 . The fuel control valves  162  are typically digitally controlled via control signals generated by the process controller  128 .  FIG. 1  shows a first fuel control valve  162 ( 1 ) and a second fuel control valve  162 ( 2 ). The first fuel control valve  162 ( 1 ) controls fuel being supplied to all burners located in the heater  102 . The second fuel control valve  162 ( 2 ) controls fuel being supplied to each individual burner  104  (or a grouping of burners in each heater zone). There may be more or fewer fuel control valves  162  without departing from the scope hereof. Further, as shown, there may be a grouping of fuel-side measurement devices between individual components on the fuel supply line  160 . For example, a first flow sensor  154 ( 1 ), first fuel temperature sensor  156 ( 1 ), and first fuel-pressure sensor  158 ( 1 ) are located on the fuel supply line  160  between the fuel source  108  and the first fuel control valve  162 ( 1 ). A second flow sensor  154 ( 2 ), second fuel temperature sensor  156 ( 2 ), and second fuel-pressure sensor  158 ( 2 ) are located on the fuel supply line  160  between the first fuel control valve  162 ( 1 ) and the second fuel control valve  162 ( 2 ). Additionally, a third flow sensor  154 ( 3 ), third fuel temperature sensor  156 ( 3 ), and third fuel-pressure sensor  158 ( 3 ) are located on the fuel supply line  160  between the second fuel control valve  162 ( 2 ) and the burner  104 . The third fuel temperature sensor  156 ( 3 ), and third fuel-pressure sensor  158 ( 3 ) may be configured to determine flow, temperature, and pressure respectively of an air/fuel mixture for pre-mix burners discussed above with respect to  FIG. 5 . 
     The process controller  128  may also measure process-side temperatures associated with the processes occurring within the process tubes  106 . For example, system  100  may further include one or more tube temperature sensors  168 , such as a thermocouple, that monitor the temperature of the process tubes  106 . The temperature sensor  168  may also be implemented using optical scanning technologies, such as an IR camera, and/or one of the TDLAS devices  147 . Furthermore, the process controller  128  may also receive sensed outlet temperature of the fluid within the process tubes  106  from process outlet temperature sensor (not shown), such as a thermocouple. The process controller  128  may then use these sensed temperatures (from the tube temperature sensors  168  and/or the outlet temperature sensor) to control firing rate of the burners  104  to increase or decrease the generated thermal energy  112  to achieve a desired process temperature. 
       FIG. 11  depicts a block diagram of the process controller  128  of  FIG. 1  in further detail, in embodiments. The process controller  128  includes a processor  1102  communicatively coupled with memory  1104 . The processor  1102  may include a single processing device or a plurality of processing devices operating in concert. The memory  1104  may include transitory and or non-transitory memory that is volatile and/or non-volatile. 
     The process controller  128  may further include communication circuitry  1106  and a display  1108 . The communication circuitry  1106  includes wired or wireless communication protocols known in the art configured to receive and transmit data from and to components of the system  100 . The display  1108  may be co-located with the process controller  128 , or may be remote therefrom and displays data about the operating conditions of the heater  102  as discussed in further detail below. 
     Memory  1104  stores the sensor database  130  discussed above, which includes any one or more of fuel data  1110 , air data  1118 , heater data  1126 , emissions data  1140 , process-side data  1170 , and any combination thereof. In embodiments, the sensor database  130  includes fuel data  1110 . The fuel data  1110  includes fuel flow  1112 , fuel temperature  1114 , and fuel-pressure  1116  readings throughout the system  100  regarding the fuel being supplied to the burner  104 . For example, the fuel flow data  1112  includes sensed readings from any one or more of the flow sensor(s)  154  in system  100  transmitted to the process controller  128 . The fuel temperature data  1114  includes sensed readings from any one or more of the fuel temperature sensor(s)  156  in system  100  transmitted to the process controller  128 . The fuel-pressure data  1116  includes sensed readings from any one or more of the fuel-pressure sensor(s)  158  in system  100  transmitted to the process controller  128 . In embodiments, the fuel data  1110  may further include fuel composition information that is either sensed via a sensor located at the fuel source  108  or that is determined based on an inferred fuel composition such as that discussed in U.S. Provisional Patent Application No. 62/864,954, filed Jun. 21, 2019 and which is incorporated by reference herein as if fully set forth. The fuel data  1110  may also include data regarding other fuel-side sensors not necessarily shown in  FIG. 1 , but known in the art. 
     In embodiments, the sensor database  130  includes air data  1118  regarding the air being supplied to the burner  104  and heater  102 . The air data  1118  includes air temperature data  1120 , air humidity data  1122 , and air pressure data  1124 . The air temperature data  1120  includes sensed readings from any one or more of the air temperature sensor(s)  144  in system  100  transmitted to the process controller  128 . The air humidity data  1122  includes sensed readings from any one or more of the air humidity sensor(s)  146  in system  100 , and/or data from local weather servers, transmitted to the process controller  128 . The air pressure data  1124  includes sensed readings from any one or more of the pre-burner air register air pressure sensor  148 , and a post-burner air register air pressure sensor  150  (or any other air pressure sensor) in system  100  transmitted to the process controller  128 . The air data  1118  may also include data regarding other air-side sensors not necessarily shown in  FIG. 1 , but known in the art. 
     In embodiments, the sensor database  130  includes heater data  1126 . The heater data  1126  includes radiant-section temperature data  1128 , convection-section temperature data  1130 , stack-section temperature data  1132 , radiant-section pressure data  1134 , convection-section pressure data  1136 , and stack-section pressure data  1138 . The radiant-section temperature data  1128  includes sensed readings from the radiant temperature sensor(s)  142  of system  100  that are transmitted to the process controller  128 . The convection-section temperature data  1130  includes sensed readings from the convection temperature sensor(s)  140  of system  100  that are transmitted to the process controller  128 . The stack-section temperature data  1132  includes sensed readings from the stack temperature sensor(s)  138  of system  100  that are transmitted to the process controller  128 . The radiant-section pressure data  1134  includes sensed readings from the radiant pressure sensor(s)  126  of system  100  that are transmitted to the process controller  128 . The convection-section pressure data  1136  includes sensed readings from the convection pressure sensor(s)  127  of system  100  that are transmitted to the process controller  128 . The stack-section pressure data  1136  includes sensed readings from the stack pressure sensor(s)  129  of system  100  that are transmitted to the process controller  128 . The heater data  1126  may also include data regarding other heater sensors not necessarily shown in  FIG. 1 , but known in the art. 
     In embodiments, the sensor database  130  further includes emissions data  1140 . The emissions data  1140  includes O 2  reading(s)  1142 , CO reading(s)  1144 , and NO x  reading(s)  1146 . The O 2  reading(s)  1142  include sensed readings from the oxygen sensor  132  transmitted to the process controller  128 . The CO reading(s)  1144  include sensed readings from the carbon monoxide sensor  134  transmitted to the process controller  128 . The NO x  reading(s)  1146  include sensed readings from the NO x  sensor  136  transmitted to the process controller  128 . The emissions data  1140  may also include data regarding other emissions sensors not necessarily shown in  FIG. 1 , but known in the art. 
     In embodiments, the sensor database  130  includes process-side data  1170  regarding the conditions of the process tubes  106  and the process occurring. The process-side data  1170  includes process tube temperature  1172 , and the outlet fluid temperature  1174 . The process tube temperature  1172  may include data captured by the process tube temperature sensor  168 , discussed above. The outlet fluid temperature  1174  may include data captured by an outlet fluid sensor (not shown), such as a thermocouple. The process-side data  1170  may also include data regarding other process-side sensors not necessarily shown in  FIG. 1 , but known in the art. 
     Data within the sensor database  130  is indexed according to the sensor providing said readings. Accordingly, data within the sensor database  130  may be used to provide real-time operating conditions of the system  100 . 
     The memory  1104 , in embodiments, further includes one or more of a fuel analyzer  1148 , an air analyzer  1150 , a draft analyzer  1152 , an emissions analyzer  1154 , a process-side analyzer  1176 , and any combination thereof. Each of the fuel analyzer  1148 , air analyzer  1150 , draft analyzer  1152 , emissions analyzer  1154 , and process-side analyzer  1176  comprise machine readable instructions that when executed by the processor  1102  operate to perform the functionality associated with each respective analyzer discussed herein. Each of the fuel analyzer  1148 , air analyzer  1150 , draft analyzer  1152 , emissions analyzer  1154 , and process-side analyzer  1176  may be executed in serial or parallel to one another. 
     The fuel analyzer  1148  operates to compare the fuel data  1110  against one or more fuel alarm thresholds  1156 . One common fuel alarm threshold  1156  includes fuel-pressure threshold that sets a safe operation under normal operating condition without causing nuisance shutdowns of the system  100  due to improperly functioning burner  104  caused by excess or low fuel-pressure. The fuel alarm thresholds  1156  are typically set during design of the system  100 . The fuel analyzer  1148  may analyze other data within the sensor database  130  not included in the fuel data  1110 , such as any one or more of air data  1118 , heater data  1126 , emissions data  1140 , process-side data  1170 , and any combination thereof to ensure there is appropriate air to fuel ratio within the heater to achieve the stoichiometric conditions for appropriate generation of the thermal energy  112 . 
     The air analyzer  1150  operates to compare the air data  1118  against one or more air alarm thresholds  1158 . One common air alarm threshold  1158  includes fan operating threshold that sets a safe operation condition of the forced fan  124  and/or stack fan  122  under normal operating condition without causing nuisance shutdowns of the system  100  due to improper draft within the heater  102  caused by excess or low air pressure throughout the system  100 . The air alarm thresholds  1158  are typically set during design of the system  100 . The air analyzer  1150  may analyze other data within the sensor database  130  not included in the air data  1118 , such as any one or more of fuel data  1110 , heater data  1126 , emissions data  1140 , process-side data  1170 , and any combination thereof to ensure there is appropriate air to fuel ratio within the heater to achieve the stoichiometric conditions for appropriate generation of the thermal energy  112 . 
     The draft analyzer  1152  operates to compare the heater data  1126  against one or more draft alarm thresholds  1160 . One common draft alarm threshold  1160  includes heater pressure threshold that sets safe operation conditions of the heater  102  under normal operating condition without causing nuisance shutdowns or dangerous conditions of the system  100  due to positive pressure within the heater  102  (such as at the arch of the heater  102 ). The draft alarm thresholds  1160  are typically set during design of the system  100 . The draft analyzer  1152  may analyze other data within the sensor database  130  not included in the heater data  1126 , such as any one or more of fuel data  1110 , air data  1118 , emissions data  1140 , process-side data  1170 , and any combination thereof to ensure there is appropriate operating conditions within the heater  102  to achieve the stoichiometric conditions for appropriate generation of the thermal energy  112 . 
     The emissions analyzer  1154  operates to compare the emissions data  1140  against one or more emission alarm thresholds  1162 . One emissions alarm threshold  1162  include a minimum and maximum excess oxygen level that sets safe operation conditions of the heater  102  under normal operating condition without causing nuisance shutdowns or dangerous conditions of the system  100  due to too little or too much oxygen within the heater  102  during creation of the thermal energy  112 . Other emission alarm thresholds  1162  include pollution limits set by environmental guidelines associated with the location in which system  100  is installed. The emission alarm thresholds  1162  are typically set during design of the system  100 . The emissions analyzer  1154  may analyze other data within the sensor database  130  not included in the emissions data  1140 , such as any one or more of fuel data  1110 , air data  1118 , heater data  1126 , process-side data  1170 , and any combination thereof to ensure there is appropriate operating conditions within the heater  102  to achieve the stoichiometric conditions for appropriate generation of the thermal energy  112 . 
     The process-side analyzer  1176  operates to compare the process-side data  1170  against one or more process thresholds  1178 . One common process threshold  1178  includes a desired outlet temperature to achieve efficient process conversion in the process tubes  106 . Another example process threshold  1178  includes a maximum temperature threshold of the process tube  106  at which the process tube  106  is unlikely to fail. The process-side analyzer  1176  may analyze other data within the sensor database  130  not included in the process-side data  1170 , such as any one or more of fuel data  1110 , air-data  1118 , heater data  1126 , emissions data  1140 , and any combination thereof to ensure there is appropriate air to fuel ratio within the heater to achieve the stoichiometric conditions for appropriate generation of the thermal energy  112 . 
     The fuel analyzer  1148 , the air analyzer  1150 , the draft analyzer  1152 , the emissions analyzer  1154 , and the process-side analyzer  1176  operate to create one or more of control signals  1164 , alarms  1166 , and displayed operating conditions  1168 . The control signals  1164  include signals transmitted from the process controller  128  to one or more components of the system  100 , such as the dampers  118 , air registers  120  (if electrically controlled), fans  122 ,  124 , and valves  162 . The alarms  1166  include audible, tactile, and visual alarms that are generated in response to tripping of one or more of the fuel alarm threshold  1156 , air alarm threshold  1158 , draft alarm threshold  1160 , and emission alarm threshold  1162 . The displayed operating conditions  1168  include information that is displayed on the display  1108  regarding the data within the sensor database  130  and the operating conditions analyzed by one or more of the fuel analyzer  1148 , air analyzer  1150 , draft analyzer  1152 , emissions analyzer  1154 , and process-side analyzer  1176 . 
     Referring to  FIG. 1 , one or more of the fuel analyzer  1148 , the air analyzer  1150 , the draft analyzer  1152 , the emissions analyzer  1154  and the process-side analyzer  1176  may be entirely or partially implemented on an external server  164 . The external server  164  may receive some or all of the data within the sensor database  130  and implement specific algorithms within each of the fuel analyzer  1148 , the air analyzer  1150 , the draft analyzer  1152 , the emissions analyzer  1154  and the process-side analyzer  1176 . In response, the external server  164  may transmit one or more of the control signals  1164 , the alarms  1166 , and/or the displayed operating conditions  1168  back to the process controller  128 . 
     Automatic Air Register/Damper Setting Control 
     The present disclosure acknowledges that, because of the manual nature required to achieve excess oxygen within the heater (e.g., as sensed by the oxygen sensor  132 ) by manually altering each burner air register (e.g., air register  120 ), the furnace is often left in a high oxygen state, or a low oxygen state with a more negative draft than desirable (e.g., stronger pull of air into the heater) to move the excess oxygen control to the stack damper  118  that can be controlled remotely from the operating room (e.g., via the process controller  128 ). Such common operating process results in inefficiencies in operating the process heater because the airflow throughout the burners and heater are not operating under optimal conditions—even if the target excess oxygen levels are reached. The present disclosure resolves this problem by iteratively solving a fired-systems model of the system using known geometry of the heater, burner, air inlet ductwork, and other features of the system to optimize the air register and/or damper settings throughout the system. 
       FIG. 12  depicts an example air analyzer (e.g., air analyzer  1150  of  FIG. 11 ), including an air-flow optimizer  1202 , in embodiments. Airflow optimizer  1202  includes computer readable instructions that when executed by a processor (e.g., processor  1102 ), operate to generate one or more of optimized burner air register settings  1206 , optimized stack damper settings  1208 , and optimized air handling settings  1210 , and any combination thereof. 
     The airflow optimizer  1202 , in an embodiment, operates to iteratively solve a fired-systems model  1204  of the system (e.g., system  100 ) to identify optimized burner air register settings  1206  to achieve the target excess oxygen level  1214 . The fired-systems model  1204  may be for an entire combustion system (e.g., from the air-input and the fuel-input through the exit of the stack), or may be for one or more specific components within a given combustion system (such as one or more of a burner model, an air ductwork model, a model of draft within the heater, a model of heat transfer surrounding process tubes, etc.). The fired-systems model  1204  model may be based on any one or more of combustion chemistry, combustion kinetics, air and fuel fluid dynamics, heat transfer, process side modeling, computational fluid dynamics modeling, and other various types of combustion modeling. The fired-systems model  1204  may account for various system constraints and operational characteristics. For example, by iteratively solving the fired-systems model  1204 , the airflow optimizer  1202  analyzes, based on a known fuel information  1212 , target heat release  1214  per heater zone, ambient air information  1216 , and available airflow  1218  at each burner, what burner air register setting  1206  is appropriate to obtain a target excess oxygen level  1220 . 
     The fuel information  1212  includes the fuel data  1110  discussed above and identifies the fuel flow  1112 , fuel temperature  1114 , and fuel pressure  1116  capable of being supplied to each burner  104 . The fuel information  1212  may further identify the fuel composition such that the fired-systems model  1204  may determine the heat release provided by each burner according to each potential burner air register setting. 
     The target heat release  1214  is input into the system  100  (e.g., at the process controller  128 ) by a system operator, or determined by the process controller  128  based on the necessary heat supplied by each burner  104 , or plurality of burners  104  in a burner zone within the heater to obtain the necessary thermal energy  112  to properly perform the chemical process on the material within the process tubes  106  or to heat up the fluid in the process tubes  106 . The target heat release  1214  may include a plurality of target heat releases  1214  each representing a given zone within the heater  102 . 
     The target excess oxygen level  1220  is input into the system  100  (e.g., at the process controller  128 ) by a system operator, or determined by the process controller  128  based on the necessary heat supplied by each burner  104 , or plurality of burners  104  in a burner zone within the heater to obtain the necessary thermal energy  112  to properly perform the chemical process on the material within the process tubes  106  or to heat up the fluid in the process tubes  106 . The target excess oxygen level  1220  may include a plurality of target excess oxygen levels  1220  defined for each of a plurality of zones within the heater  102 . The target excess oxygen level  1220  for each zone may be above, below, or equal to a target global oxygen level of the overall system such that the cumulative excess oxygen provided by each zone equals the target global excess oxygen level. In other words, the summation of the total fuel/zone and the summation of the total air/zone must not be greater than the summation of global total fuel and the summation of total global air input into the system that achieves a desired global excess oxygen level after combustion of the fuel and air to create the thermal energy. 
     The ambient air information  1216  includes the air data  1118  including the air temperature  1120 , air humidity  1122 , and air pressure  1124  that is either sensed by sensors proximate or at the heater  102 , or obtained from a third-party weather server. 
     The available airflow  1218  at each burner  104  includes the amount of air capable of being provided into the heater  102  by each burner  104  for each burner air register setting (e.g., each setting the air register handle  802  defining the controllable range shown on indicator plate  804  in  FIG. 8 ). In certain embodiments, the available airflow  1218  is known based on information about the burner. In certain embodiments, the available airflow  1218  is determined by the airflow optimizer  1202  by analyzing the pressure differential across each burner  104 . Referring back to  FIG. 1 , in many systems, only a single air pressure sensor (e.g., air pressure sensor  148  is located within the airflow ductwork (e.g., ductwork  151 ), and the air-pressure sensor  150  is not included in the system. Thus, the airflow optimizer  1202  may receive this ductwork air pressure sensor data  1222  (e.g., from the air pressure sensor  148 ) and the in-heater pressure data  1224  (e.g., including one or more of the radiant-section pressure data  1134 , convection-section pressure data  1136 , and stack-section pressure data  1138  respectively based on the pressure sensors  126 ,  127 , and  129 ). The airflow optimizer  1202  may then calculate the available airflow  1218  based on the pressure differential across each burner  102  as determined from the ductwork air pressure sensor data  1222  and the in-heater pressure data  1224 . The available airflow  1218  may be further based on sensed airflow, as opposed to calculating the pressure differential across the burner, such as airflow sensed by an anemometer located within the ductwork  151 . 
     The in-heater pressure data  1224  defines the draft within the heater  102 . The more negative the draft, the more air that will be pulled through the burners  104 —as discussed above, conventionally heaters are often controlled to more negative draft than desirable to transfer control to the stack damper  118  and/or stack fan  122 , which are controllable from the process controller  128 . In a natural and induced draft system, the air pressure defined by the ductwork air pressure sensor data  1222  is the same as the ambient air pressure because there is nothing pushing air into the ductwork  151  (e.g., the forced fan  124 ). In a forced and balanced draft system, the air pressure defined by the ductwork air pressure sensor data  1222  may be influenced based on the fan settings of the forced fan  124 . 
     In certain embodiments, the in-heater pressure data  1224  for at the location of a given burner may be interpolated from data sensed by a pressure sensor at a physical location away from the given burner. For example, in certain systems, the pressure within the heater  102  is sensed at the heater arch. Pressure at other levels within the heater  102 , separated from the location of the sensed pressure, may then be determined based on fluid dynamics calculations. 
     In certain embodiments, the ductwork air pressure sensor data  1222  for a given burner may be interpolated from data sensed by a pressure sensor at a physical location within the ductwork  151  away from the burner, or interpolated from information such as a forced fan setting of the forced fan  124 . 
     Accordingly, in certain embodiments, the fired-systems model(s)  1204  is further based on one or more of the heater housing geometry  1226 , process tube geometry  1228 , burner geometry  1230 , and air supply ductwork geometry  1232 , or any combination thereof. 
     The geometry (such as the shape and height) of the heater housing  1226  plays an important role in defining how the draft within the heater will travel through the heater. This affects how the air will be input and output from the system through convection influenced by the draft. 
     The process tube geometry  1228  includes the orientation of the process tubes (e.g., tubes  106 ), as well as size, shape, etc. such as shown in  FIG. 3 , above. As discussed above, the characteristics of the process tubes may influence the draft in the heater and thus influence the air-flow throughout the system  100  and available airflow from each burner  104  therein. 
     The geometry of the burner  1230  includes the number, location, and physical geometry of the burners, the burner zones within the heater, as well as burner settings for each burner, such as the controllable range of the burner air registers (e.g., burner air register  120 ) such as the controllable range shown on indicator plate  804  in  FIG. 8 .  FIG. 13  depicts an example diagram indicating physical geometry of a COOLstar® burner indicating pressure losses throughout the burner, in an embodiment. The physical geometry of the burner  1230  may impact the airflow capable of being supplied into the heater  102  based on the path that the air must flow through the burner.  FIG. 14  depicts a heater with six rows of burners and twelve fired control zones. In  FIG. 14 , each half row of burners ( 10  burner clusters) may be controlled to independent heat release rates (e.g., by altering the fuel flow rate via manipulation of a fuel supply valve to satisfy the process temperature demands below each cluster of burners, such as fuel supply valve  162  of  FIG. 1 , and correspondingly altering the air-flow rate by utilizing a more closed air register handle setting) to satisfy the air flow rate demand of each cluster of burners. 
     The geometry of the air ductwork  1232  includes the geometry of the airflow ductwork (e.g., ductwork  151 ) throughout the system  100 . This includes any air handling damper (e.g., air handling register  152 ), the air-flow zones, and the geometry of each of the above.  FIG. 15  shows results from a fired-systems model  1500  showing how the air distributes to each of the plurality of burners of  FIG. 14  as a function of the duct design with the burner air registers full open, for example. If the burner is not firing the exact same percentage of expected airflow distribution percentage, each burner will not be firing at equal stoichiometry. Since the fired percentage varies frequently to adjust based on process outlet temperatures for tubes near each cluster of burners, the air must be modulated as well. In many systems, it is not modulated properly because the insights of air fuel ratio per burner are not available and adding additional hardware (such as airflow measurement devices) to each individual burner is expensive and requires excessive and undesirable maintenance to upkeep said airflow measurement devices.  FIG. 16  depicts an example air ductwork having four air supply zones  1602 ( 1 )-( 4 ) each coupled to a single air input  1604 . Depending on the configuration of the system, in certain embodiment, each zone  1602  may have a distinct pressure. Solving of the fired-systems model  1204  using the geometry of the air ductwork  1232  provides significant insight into the airflow of the system and allows the air-flow optimizer  1202  to understand actual air-flow potential for each burner of the system. 
     In embodiments, the fired-systems model  1204  is solved based on further information of the system  100 , such as one or more of a current or future stack damper setting  1234 , a current or future stack fan setting  1236  (if included in system  100 , such as in induced- or balanced-draft systems), a current or future forced fan setting  1238  (if included in system  100 , such as in forced- or balanced-draft systems). 
     The current stack damper setting  1234  includes information about the stack damper (e.g., stack damper  118 ), as well as control ranges associated therewith, such that the optimized burner air register settings  1206  are not generated in a manner that is improper in view of the current hardware and controllability associated with the stack damper. 
     The current stack fan setting  1236  includes information about the stack fan (e.g., stack fan  122 ), as well as control ranges associated therewith, such that the optimized burner air register settings  1206  are not generated in a manner that is improper in view of the current hardware and controllability associated with the stack fan. 
     The current forced fan setting  1238  includes information about the forced fan (e.g., forced fan  124 ), as well as control ranges associated therewith, such that the optimized burner air register settings  1206  are not generated in a manner that is improper in view of the current hardware and controllability associated with the forced fan. 
     By iteratively solving the fired-systems model  1204 , the airflow optimizer  1202  changes variables in the fired-systems model  1204  for each iteration and determines if the overall excess oxygen level expected to be generated by all burners meets the target excess oxygen level  1220  while still obtaining the target heat release  1214  for each given burner, or zone including a plurality of burners. 
     Airflow optimization by the airflow analyzer  1150  may be triggered for a variety of reasons. For example, any one or more of weather changes above a predefined threshold (e.g., humidity changes, temperature changes, pressure changes, etc.), input fuel composition changes, process-side material changes, and other changes that otherwise impact operation and efficiency of the combustion system may trigger airflow optimization. In certain embodiments, the fired-systems model  1204  is iteratively solved, but the optimized settings  1206 ,  120 - 8 , and/or  1210  are not output unless the adjustment will provide a cost benefit to the operator above a predefined threshold. 
     As another example, when the measured excess oxygen sensed by the O2 sensor  132  starts to divert from a prediction, one or more TDLAS measurements (from the TDLAS device(s)  147 ) within the heater can be leveraged to identify the specific areas/regions within the heater that are most likely the cause of the deviation. Using the fired-systems model  1204  for that identified area, TDLAS, historical data, and AI, the air-flow analyzer  1150  can indicate which burners/zones within the heaters require maintenance. Further, if the fired-systems model  1204  verifies appropriate settings of the airflow to the burners  104 , then another potential issue can be flagged, such as tramp air, and analyzed for (such as discussed in U.S. Provisional No. 62/864,967, filed Jun. 21, 2019 and which is incorporated by reference as if set forth in its entirety). 
     In embodiments, the fired-systems model  1204  is generated by manually testing the differential pressure of the burners at each burner air register setting for given draft levels. In further or alternative embodiments, the fired-systems model  1204  is generated based on physics-based modeling of the combustion system or specific components thereof (such as the heater  102 , or the burner  104 ). Embodiments utilizing a physics-based modeling provide the advantage that, because the physics modeling requires minimal computational power, optimized air register settings  1206 , stack damper settings  1208 , and optimized air handling settings  1210  may be generated quickly. This allows the operator of the system  100  to compensate for unexpected or abnormal weather variations, changes in fuel compensation, changes in hardware of the system  100 , etc.—all of which greatly impact the operational conditions inside the heater  102 . In further or alternative embodiments, the fired-systems model  1204  is based further on computational fluid dynamics (CFD) modeling of the system  100 .  FIG. 17  shows a CFD model of a forced (or balanced) draft system including a single airside pressure sensor  1702 . The system shown in  FIG. 17  includes twelve rows of ten burners. The burners located towards the middle of each row receive significantly less airflow due to the configuration of the ductwork. Advantageously, utilizing CFD in the model  1204  allows the model to be fine-tuned thereby providing more accurate information and thus more accurate optimized air register settings  1206 , stack damper settings  1208 , and optimized air handling settings  1210 . 
     In further or alternative embodiments, the fired-systems model  1204  is solved based on further real-time sensed data  1240  of the system  100 . Over time, due to the harsh conditions of the environment in the process heater  102 , the pre-stored information about the geometry of the system and components therein changes due to build up on the components. For example, burner tips can develop coke therein that blocks the drilled holes. Accordingly, the real-time sensed data  1240  may include information captured and stored in the sensor database  130 , discussed above. The real-time sensed data  1240  additionally allows the output optimized air register settings  1206  to be verified in real-time. For example, after verification that the heater has been configured according to the optimized burner air register settings  1206  (or other optimized settings discussed herein), the airflow optimizer  1202  may compare real-time sensed data  1240  against the solved physics-based fired-systems model  1204  to verify that the desired output is obtained. 
     In embodiments, the airflow optimizer  1202  generates the optimized settings (e.g., optimized burner air register settings  1206 , optimized stack damper settings  1208 , and optimized air handling damper settings  1210 ) based on further historical data  1242 . The historical data  1242  may include historically sensed data from the system  100 , and/or may include historical data regarding similar systems that are recorded at an external server (e.g., external server  164 ). 
     In some embodiments, the historical data  1242  represents an artificial intelligence data, such as a neural network, that the airflow optimizer  1202  may infer any unknown geometry of the system  100 , unknown setting of the system  100 , or discrepancy in a solved fired-systems model than expected result. This provides the airflow optimizer  1202  to infer characteristics of the system  100  that are unknown due to inaccurately installed hardware, corroded hardware, or other deviations from known plan that are required to solve the fired-systems model  1204 . As an example of where artificial intelligence and/or machine learning provides an impact, in some instances, the error associated between the solved physics-based model and the testing data is still significant. In these cases, a combined approach of physics based calculations and paired with data science will enable a hybrid model to be developed that leverages the “easy to calculate” physics based properties, but leaves the “hard to quantify” information to the ML algorithm. For example, when there is a burner with a combustion section within the burner itself. The combustion process creates a positive pressure section within a part of the burner that would otherwise be negative. Because the pressure associated and generated from the combustion process would be very difficult to represent with physics-based modeling approaches, parts of the burner may be modeled with physics based models combined with other parts that have been “learned” based on test data sets. The test data sets may come from physical testing or sometimes CFD can be used to generate data sets for reduced order ML models. 
     Accordingly, the fired-systems model  1204  may be based on any one or more of manually testing of the heater system, physics-based modeling of the heater system, CFD modeling of the heater system, real-time sensed data of the heater system, historical data of the system or other systems, and any combination thereof. 
     In embodiments herein, the fired-systems model  1204  (or any predicted data, expected data, estimated data, or other outputs from a fired-system model discussed herein) is calculated using, for example, physics-based modeling of the heater system based on sensed data (e.g., the real-time sensed data and/or historical data of the system), and artificial intelligence gleaned data. In such embodiments, the systems and methods herein may accommodate error ranges to provide a confidence region around the output of the fired-systems model  1204  (or any predicted data, expected data, estimated data, or other outputs from a fired-system model discussed herein). The sensors used to capture sensed data (e.g., the real-time sensed data and/or historical data of the system) may not be entirely accurate resulting in a sensor-based calculation uncertainty value. The sensor-based calculation uncertainty value is typically a fixed percentage that can change based on a calculated value (e.g., sensors are X % efficient when measuring temperatures across a first range, and Y % efficient across a second range). Similarly, the artificial intelligence engine may have an AI uncertainty that varies based on given inputs to the artificial intelligence engine. The AI engine, for example, models historical combined data distributions and analyzes statistical deviations of the current distribution on a scale of 0 to 100%. The confidence region allows a given prediction by the physics-based calculations and/or the AI-based engine to accommodate variances in the associated data. This then prevents false identifications of conditions within the process heater  102  in the system. 
     In embodiments, including a forced draft fan (e.g., forced draft fan  124 ), the airflow optimizer  1202  iterates under one or more constraints  1244 . For example, the constraint may require the optimization algorithm to leave at least one burner in the entire network with a “full open” burner air register setting. This constraint ensures the achieved solution minimizes the overall system pressure demand which is beneficial as it reduces the energy consumed by the forced draft fan. 
     In embodiments, additional or alternative air-side settings may be optimized using the airflow optimizer  1202 . For example, the fired-systems model  1204  may be iteratively solved to additionally or alternatively generate one or both of optimized stack damper settings  1208 , and optimized air handling register settings  1210 . The optimized stack damper settings  1208  include electronic control settings that may automatically control the stack damper (e.g., the stack damper  118  of  FIG. 1 ), as well as manual recommendations for controlling the stack damper. The optimized air-handling register settings  1210  include electronic control settings that may automatically control the air handling damper (e.g., the air handling register  152  of  FIG. 1 ), as well as manual recommendations for controlling the air handling damper. 
       FIG. 18  depicts a comparison of optimized (recommended) air register settings after optimization using the air-flow optimizer  1202  compared to the manually adjusted air-register settings, in an example. The system in  FIG. 18  included a multi zone firebox consisting of 21 burners.  FIG. 18  shows a screenshot of the displayed (e.g., displayed on display  1108 ) of optimized burner air register settings per burner. In the system shown in  FIG. 18 , the indicator position on each burner was configurable between 0 and 9 with adjustments available in increments of 0.5, with 0 being closed and 9 being full open. 
     Multi-Zonal Optimization 
       FIG. 19  depicts a comparison of optimized (recommended) air register settings after optimization using the air-flow optimizer  1202  compared to the manually adjusted air-register settings, in an example. In the  FIG. 19 , there are over 168 burners that must be adjusted to achieve the correct airflow per burner to make a single O 2  sensor (e.g., oxygen sensor  132 ) achieve the correct cumulative value. Without direct and real-time feedback on a per burner basis, this is nearly impossible.  FIG. 19  also illustrates that the optimized burner settings  1206  need not be for each individual burner, but may be grouped according to zone, row, column or any other desired grouping without departing from the scope hereof. 
     In the system shown in  FIG. 19 , there are six burner zones ( 1906 ( 1 )- 1906 ( 6 )). During analysis of the fired-systems model  1204  associated with the system shown in  FIG. 19 , each zone  1906  may be indicated with a specific heat release (e.g., target heat release  1214 ) for that zone. Each row within the “recommended air register settings” indicates a different height within the heater, and thus the draft at each row is different. Accordingly, the iteratively solved fired-systems model  1204  accounts for the airflow at each burner, within each zone  1906 , and at each height within the heater (to compensate for the varying draft at the given heights). Furthermore, as discussed above, the target heat release for each zone may be different. In the example shown in  FIG. 19 , the target heat release (e.g., target excess oxygen level  1214 ) for the floor zone  1906 ( 5 ) is significantly greater than the target heat release for the zone  1906 ( 6 ). In embodiments, the biased air/fuel ratio per burner zone could be intentional to target reduced emissions levels or improved heat flux at the process tubes. In embodiments, the target excess oxygen level (e.g., target excess oxygen level  1220 ) for the floor zone  1906 ( 5 ) may be greater than the global target excess oxygen level of all zones, while the target excess oxygen levels of the zones  1906 ( 1 )-( 4 ), and  1906 ( 6 ) may be equivalent or below the global target excess oxygen level because the excess air input from the burners in the floor zone  1906 ( 5 ) will travel upward within the heater (due to draft in the heater) and be consumed during combustion associated with the zones  1906 ( 1 )-( 4 ), and  1906 ( 6 ). 
       FIG. 20  depicts visual impact on optimized burner air register settings after implementation of the airflow optimizer  1220 , in an embodiment. The left image in  FIG. 20  indicates improperly configured burner air registers. The flame (e.g., thermal energy  112 ) is travelling up the wall of the heater. In contrast, the right image in  FIG. 20  shows the burner flames after optimized burner air register settings. The thermal energy in the right image is consistent throughout the burner, indicating proper damper settings. 
       FIG. 21  depicts additional benefits that are achieved after implementation of the airflow optimizer  1202 , in an embodiment.  FIG. 21  shows example reduction in heat release per fuel feed rate by adjusting between historical improper burner air register adjustments and proper air register adjustments using airflow optimizer  1220  with better flame quality (such as the flame quality shown in the right image of  FIG. 20 ). When knowledge of the fuel air ratio per burner is also available, emissions (such as CO and NO x ) are also be reduced systematically, and further yet, burner safety trip settings can be modified such as described in U.S. Provisional Application Ser. No. 62/865,007, filed Jun. 21, 2019 and which is incorporated herein in its entirety as if fully set forth. 
       FIGS. 22-23  depict the stoichiometric ratio (air/fuel ratio) of before and after, respectively, implementation of the airflow optimizer  1220 , in an embodiment. The graphs in  FIGS. 22-23  show stoichiometric ratio levels for six burner rows, and the ratio for each half burner row. The ideal stoichiometric ratio for each row is 1.1. As seen, the outer rows are being supplied too little air in  FIG. 22 , at a stoichiometric ratio of approximately 0.85, and the inner rows are being supplied too much air at a stoichiometric ratio of approximately 1.25-1.275. Thus, the stoichiometric ratio during the manual (prior art) method of controlling burner air registers was inefficient. However, after implementation of the airflow optimizer  1220 , nearly all burners were operating with a balanced air to fuel ratio at or near the desired stoichiometric ratio of 1.1. 
       FIG. 24  depicts a method  2400  for generating optimized air-flow settings in a combustion system, in embodiments. Method  2400  is implemented in the system  100  shown and discussed above in  FIGS. 1-23 , and in particular using the air-flow optimizer  1202  discussed above. 
     In block  2402 , the method  2400  generates a fired-systems model. In one example of block  2402 , the fired-systems model  1204  is generated. In embodiments of block  2402 , the fired-systems model may be generated may by manually testing the differential pressure of the burners at each burner air register setting for given draft levels. In further or alternative embodiments, the fired-systems model is generated based on physics-based modeling of the heater. In further or alternative embodiments, the fired-systems model  1204  is based further on computational fluid dynamics (CFD) modeling of the system  100 . In further or alternative embodiments, the fired-systems model is generated based on real-time sensed data (e.g., real-time sensed data  1240 ) of the system. Accordingly, the fired-systems model  1204  may be based on any one or more of manually testing of the heater system, physics-based modeling of the heater system, CFD modeling of the heater system, real-time sensed data of the heater system, historical data of the system or other systems, and any combination thereof. 
     In embodiments of method  2400  including block  2404 , the method  2400  tunes the fired-systems model. In an example of block  2404 , the fired-systems model  1204  is tuned based on one or more of real-time sensed data  1240 , CFD modeling, historical data  1242 , or any combination thereof. 
     In block  2406 , the method  2400  obtains fuel information, a target heat release, ambient air information, and available airflow at each burner within a process heater. In one example of block  2406 , the air analyzer  1150  receives the fuel information  1212 , target heat release  1214 , ambient air information  1216 , and available draft at each burner  1218 . In embodiments of block  2406 , the received fuel information, a target heat release, ambient air information, and available airflow at each burner within a process heater may be for a single zone, or may be received based on multiple zones within the process heater. 
     In block  2408 , the method  2400  solves the generated fired-systems model with a set of variables to achieve a target excess oxygen level. In one example of block  2408 , the air-flow optimizer  1202  solves the fired-systems model  1204  with a set of variables defined at least in part by air register settings (and/or stack damper settings, and/or air handling settings) to determine if the set of variables results in a target excess oxygen level  1220 . In embodiments including multiple zones of burners, the set of variables may include differing target excess oxygen levels for each zone within the heater  102 , each of the differing target excess oxygen levels being above, equal, or below a global target excess oxygen level, but accumulating to equal the global target excess oxygen level. 
     In block  2410 , the method  2400  determines if the variables used in block  2408  solve the fired-systems model. If yes, method  2400  proceeds to block  2412 , else method  2400  proceeds to block  2414 . In block  2412 , the method  2400  determines if the variables used in block  2408  meets a constraint associated with the fired-systems model. If yes, method  2400  proceeds to block  2416 , else method  2400  proceeds to block  2414 . In one example of block  2412 , the air-flow optimizer  1202  determines if constraints  1244  are met. 
     In block  2414 , the method  2400  changes one or more variables in the fired-systems model and then repeats blocks  2408 - 2414  iteratively until the fired-systems model is solved to the target excess oxygen level and all constraints are met. Then the method proceeds with block  2416 . 
     If the method  2400  has generated optimized burner air register settings, in block  2416 , the method  2400  outputs the optimized burner air register settings equivalent to the variables used to solve the fired-systems model to the target excess oxygen level while meeting all constraints during the iteration of steps  2408 - 2414 . In one embodiment of block  2416 , the air-flow optimizer  1202  outputs the optimized burner air register settings  1206 . 
     If the method  2400  has additionally or alternatively generated optimized stack damper settings, in block  2418 , the method  2400  outputs the optimized stack damper settings equivalent to the variables used to solve the fired-systems model to the target excess oxygen level while meeting all constraints during the iteration of steps  2408 - 2414 . In one embodiment of block  2418 , the air-flow optimizer  1202  outputs the optimized stack damper settings  1208 . 
     If the method  2400  has additionally or alternatively generated optimized air handling settings, in block  2420 , the method  2400  outputs the optimized air handling settings equivalent to the variables used to solve the fired-systems model to the target excess oxygen level while meeting all constraints during the iteration of steps  2408 - 2414 . In one embodiment of block  2418 , the air-flow optimizer  1202  outputs the optimized air handling settings  1210 . 
     In block  2422 , the method  2400  operates the heater according to the optimized settings generated in one or more of the above blocks  2416 - 2420 . 
     Stack Damper Optimized Settings 
     As discussed above, in certain embodiments, the airflow optimizer  1202  additionally or alternatively generates optimized stack damper settings  1208 . These settings advantageously optimize the draft within the system and allows efficient and consistent airflow through the burners. However, the optimized stack damper settings  1208  may provide an additional advantage—allowing the operator to set a desired draft level within the heater  102  that allows for only certain number of burner air register handle changes over a given future time period. 
     Each burner  104  is installed in the heater as a system, and operators must modulate stack dampers, in combination with burner air registers, to get the ideal amount of draft within the furnace and the correct excess oxygen. In forced draft or induced draft systems, the operators or burner operating system must modulate the induced draft and forced draft fans. 
     Normally, operators are instructed to operate their furnace as approximately 0.1 in H 2 O of negative pressure at the furnace arch and use the burner air register to tune the amount of air entering into the system, as shown in  FIG. 2 . While the heater  102  is designed for specific conditions, the heater draft is significantly impacted by the ambient air conditions.  FIG. 25  shows an example graph illustrating weather changes (such as seasonal changes) that impact the excess oxygen readings as compared to the designed/tuned conditions. 
     Because of the necessity for frequent draft adjustments, the stack dampers are commonly fitted with an actuator. The actuator enables the operator to adjust the draft of the heater remotely, from the operating control room, such as via the process controller  128 . In contrast, the burner air registers are not often fitted with actuators and as such must be manually changed. This manual operation of the burner air register handles is time consuming, particularly on heaters having upwards of 200 burners. Because of this, draft and excess air movements (that should be adjusted by the burner air register) are often handled by the stack damper (e.g., stack damper  118 ), by increasing or decreasing the draft within the firebox via stack damper. To account for swings in ambient conditions and varying firing rate required, the operator commonly chooses to set the arch (bridge wall) draft a larger draft (0.5 in H 2 O WC (water column) negative pressure is not uncommon). This decision made for convenience has some negative impacts in that the draft selected negatively impacts the efficiency of the heater (and requires additional cost). These negative impacts are not visible to the operator, and as a result, while the operator meets the desire of limiting the number of operator manual air register tuning rounds to the burner air register handles, the operator may be incurring significant costs by keeping the draft at an undesired level. 
     To provide more efficient control of the stack damper  118  (and/or stack fan  122 , and/or forced fan  124 ), while maintaining the operator&#39;s desire to limit the number of operator manual air register tuning rounds to the burner air register control handles and meeting desired cost and equipment efficiency for operating the system. 
     Accordingly, in embodiments the airflow optimizer  1202  additionally or alternatively generates optimized stack damper settings  1208  and/or air handling settings  1210 , the fired-systems model  1204  may be solved further based on desired number of operator manual air register tuning rounds  1246  to change the burner air register settings, and operational cost  1248  of achieving differing draft levels. 
     For example, if an operator never wants to go adjust burner air registers throughout the year, the solved fired-systems model  1204  will output the draft (most likely a relatively high number) that will be capable of operation throughout the year with no burner air register adjustments, and the associated optimized stack damper settings  1208  and/or air handling settings  1210  to achieve that draft. If the operator is willing to go adjust burner air registers four times per year (one for each seasonal change), then the solved fired-systems model  1204  will output the draft that will still allow the burners to achieve their controllable region. 
     Being having a fired-systems model that represents the draft through every section of the heater enables multi-variable optimization relative to the air and draft adjustments within the heater. It allows the operator to minimize draft (which will reduce the amount of tramp air, and reduce the energy consumption from the ID fan if present), maximize controllability throughout operating swings, and decide up-front the number of operator manual air register tuning rounds to the heater that are tolerable for burner air register adjustments while knowing the associated cost that said decisions make. 
       FIG. 26  depicts a method  2600  for generating optimized air-flow settings that achieve a desired combustion system control range over a period of time, in an embodiment. Method  2600  is implemented, for example, in the air-flow analyzer  1202  discussed above with reference to system  100  of  FIGS. 1-25 . Method  2600  may be implemented in alternative to method  2400 , or in addition thereto. 
     Method  2600  begins with steps  2402  and  2404  discussed above with respect to method  2400 . 
     In block  2602 , the method  2600  obtains a of desired number of operator manual air register tuning rounds to change the burner air register settings. In one example of block  2602 , the air analyzer  1150  receives the desired number of operator manual air register tuning rounds  1246  to change the burner air register settings via interaction with the operator through process controller  128 . Block  2602  may be a component of block  2406  of method  2400 . 
     In block  2604 , the method  2600  solves the generated fired-systems model with a set of variables to achieve a necessary draft range within the heater that can withstand weather variations over a given period of time while maintaining the number of desired operator manual air register tuning rounds to change the burner air register settings. In one example of block  2604 , the air-flow optimizer  1202  solves the fired-systems model  1204  with a set of variables defined at least in part by air register settings (and/or stack damper settings, and/or air handling settings) to determine a necessary draft range within the heater that can withstand predicted weather variations over a future period of time (e.g., one year, half a year, multiple seasons, etc.) while maintaining the number of desired operator manual air register tuning rounds to change the burner air register settings. Block  2604  may be a component of block  2408 . 
     In block  2606 , the method  2600  determines if the variables used in block  2606  solve the fired-systems model with a realistic and/or achievable draft. If yes, method  2600  proceeds to block  2608 , else method  2600  proceeds to block  2610 . In block  2608 , the method  2600  determines if the variables used in block  2608  meets a constraint associated with the fired-systems model. If yes, method  2600  proceeds to block  2612 , else method  2600  proceeds to block  2610 . In one example of block  2608 , the air-flow optimizer  1202  determines if constraints  1244  are met, wherein the constraints  1244  include an operational cost  1248 . Accordingly, if a realistic draft is achievable while only changing the burner air registers according to a desired number of times over a given period (e.g., one year, half a year, etc.), but the predicted operational cost for achieving that realistic draft is too high (e.g., above a threshold defined by the operational cost  1248 ), the variables may be altered again to determine if changing the selected stack damper and/or air-handling settings used to solve the fired-systems model will lower the operational cost. Blocks  2606  and  2608  may be components of blocks  2410  and  2412 , respectively. 
     In block  2610 , the method  2600  changes one or more variables in the fired-systems model and then repeats blocks  2604 - 2610  iteratively until the fired-systems model is solved to achieve a realistic/achievable draft and all constraints are met. Then the method proceeds with block  2612 . Block  2610  may be a component of block  2414 . 
     If the method  2600  has generated optimized burner air register settings, in block  2612 , the method  2600  outputs the optimized burner air register settings equivalent to the variables used to solve the fired-systems model to the generate an achievable draft level while meeting all constraints during the iteration of steps  2604 - 2610 . In one embodiment of block  2612 , the air-flow optimizer  1202  outputs the optimized burner air register settings  1206 . Block  2612  may be a component of block  2416 . 
     If the method  2600  has additionally or alternatively generated optimized stack damper settings, in block  2614 , the method  2600  outputs the optimized stack damper settings equivalent to the variables used to solve the fired-systems model to the generate an achievable draft level while meeting all constraints during the iteration of steps  2604 - 2610 . In one embodiment of block  2614 , the air-flow optimizer  1202  outputs the optimized stack damper settings  1208 . Block  2614  may be a component of block  2418 . 
     If the method  2600  has additionally or alternatively generated optimized air handling settings, in block  2616 , the method  2600  outputs the optimized air handling settings equivalent to the variables used to solve the fired-systems model to the generate an achievable draft level while meeting all constraints during the iteration of steps  2604 - 2610 . In one embodiment of block  2616 , the air-flow optimizer  1202  outputs the optimized air handling settings  1210 . Block  2616  may be a component of block  2420 . 
     In block  2618 , the method  2600  operates the heater according to the optimized settings generated in one or more of the above blocks  2612 - 2616 . Block  2618  may be a component of block  2422 . 
     Anomaly Detection based on Optimized Settings 
     Once the air-flow optimizer  1202  generates the optimized burner air register settings  1206 , optimized stack damper settings  1208 , and optimized air handling settings  1210 , and any combination thereof, the expected draft, stack damper setting, burner air register settings, induced draft fan or forced draft fan settings (if included), can be compared to what is sensed, and used as an anomaly detection for when there could be a faulty hardware condition that would cause the hydraulic system to respond differently than the calculation. Anomaly detection may also occur without the optimized settings, but instead using manually recorded data regarding the register settings, damper settings, and other air handling settings. 
     As discussed above, the air-flow optimizer  1202  may further analyze real-time sensed data  1240 . If this real-time sensed data  1240  begins to deviate from expected values, based on the generated and implemented optimized burner air register settings  1206 , optimized stack damper settings  1208 , and optimized air handling settings  1210 , and combination thereof, then the air-flow optimizer  1202  may generate an alert  1250 . The alert  1250  may be an audible, visual, or tactile indication on the process controller  128 , or another device such as a mobile device of a heater operator. The alert  1250  may also include a remediation action that automatically controls the heater  102 , and components associated therewith, to compensate for the deviation of sensed values from expected values. 
     One example of how the sensed values could deviate from the expected values is, if a process tube  106  developed a leak, the leak would add volume/mass into the heater  102  and change the heater/system level hydraulics of the draft (or the readings in the emissions data  1140 ). As such, the alert  1250  will indicate incorrect emission levels in the heater, and/or identify the location of the leak and recommend maintenance thereon. If the leak causes unsafe conditions, the alert  1250  may include a remediation action that shuts down the system for safety concerns. 
     Another example of how the sensed values could deviate from the expected values is, if the process tubes  106  include fins, such as discussed above with respect to  FIG. 3 , the fins may become clogged due to the harsh conditions in the heater  102 .  FIG. 27  depicts an example of clogged fins on process tubes. These clogged fins will greatly impact the draft through the heater  102 , and thus the sensed data will not be consistent with the expected data. As such, the alert  1250  will indicate incorrect draft in the heater, and/or identify the location of the draft discrepancy and recommend maintenance thereon. If the clogged fins cause unsafe conditions, the alert  1250  may include a remediation action that shuts down the system for safety concerns. 
     As discussed above, any predicted data, expected data, estimated data, or other outputs from a fired-system models discussed herein may be calculated using, for example, physics-based modeling of the heater system based on sensed data (e.g., the real-time sensed data and/or historical data of the system), and artificial intelligence gleaned data. In such embodiments, the systems and methods herein may accommodate error ranges to provide a confidence region around the output of the predicted data, expected data, estimated data, or other outputs from a fired-system model. The sensors used to capture sensed data (e.g., the real-time sensed data and/or historical data of the system) may not be entirely accurate resulting in a sensor-based calculation uncertainty value. The sensor-based calculation uncertainty value is typically a fixed percentage that can change based on a calculated value (e.g., sensors are X % efficient when measuring temperatures across a first range, and Y % efficient across a second range). Similarly, the artificial intelligence engine may have an AI uncertainty that varies based on given inputs to the artificial intelligence engine. The AI engine, for example, models historical combined data distributions and analyzes statistical deviations of the current distribution on a scale of 0 to 100%. The confidence region allows a given prediction by the physics-based calculations and/or the AI-based engine to accommodate variances in the associated data. This confidence region prevents false identifications of conditions within the process heater  102  in the system when the sensed values deviate within a certain range about a predicted value, the range being defined by the confidence region. 
       FIGS. 28-33  depict graphs indicating heater operation over time when the fins of process tubes become clogged due to harsh conditions in the heater, in an embodiment.  FIG. 34  depicts data table represented by the graphs of  FIGS. 28-33 . Conventionally, an operator is unaware of the clogging of process tube fins that results in an improper draft within the heater (e.g., heater  102 ). As previously illustrated, convection fouling is a build-up of debris on the tubes and extended surfaces in the convection. This causes an increase in thermal resistance reducing the heat transferred to the process and increased flue gas side pressure drop. Convection fouling causes a decrease in efficiency. Conventionally, the operator does not have enough insight into the heater operation to be fully aware of what is causing this decrease in efficiency. The operator is unable to visually see the fin clogging unless the operator is continuously viewing through a viewport of the heater  102 , which is unrealistic. Because of this, the heater is typically controlled to fire at a higher rate forcing more duty to be absorbed in the radiant section. The overall absorbed duty/coil outlet temperature must be maintained to allow for proper process of the material in the process tubes. Increased thermal resistance can be seen as a decrease in coil crossover temperature (if available), increase in firing rates, increase in bridgewall temperature, and an increase in stack temperature. Along with increased thermal resistance, this fouling forces the flue gas across a decreasing cross-sectional area along its flow path. This throttling effect increases the flue gas side pressure drop across the convection. This can be seen with an increase in open percentage of the stack damper to compensate and maintain the draft pressure at the bridgewall. 
     The air-flow optimizer  1202 , described above, utilizes the fired-systems model  1204 , real-time sensed data  1240 , and historical data  1242  to calculate expected values of the heater  102  at any given time. Comparison of these expected values to the real-time sensed data  1240  allows the air-flow optimizer  1202  to automatically detect and diagnose anomalies in the air flow, such as convection fouling (e.g., clogging of the fins/heat sinks of process tubes  106 ). In  FIGS. 28-34  (where  FIG. 34  is a table of the data in  FIGS. 28-33 ), it is seen that during time slot  1  (start of run, “SOR”), the heater  102  is operating as expected, where the modeled convection section dP matches the convection section dP sensed. However, as time passes, the modeled convection section dP begins to deviate from the measured convection section dP. At a certain point, the delta between the measured and modeled convection section dP may become greater than a predetermined threshold, at which the air-flow optimizer  1202  may generate the alert  1250  indicating cleaning of the process tubes  102  is necessary. 
     The air-flow optimizer  1202  provides insight that operators conventionally previously did not have. Operators were typically unaware of what the convection section dP should be. Instead, operators had to manually visually inspect process tubes  106  to determine if the process tubes  106  were clogged. In contrast, the present system and methods are capable of flagging an anomaly when the heater&#39;s efficiency is lower than what it historically was (e.g., via monitoring the varying heater efficiency over time as shown in  FIGS. 28-34 ) for the current process conditions (absorbed duty, inlet temperature, outlet temperature, etc.) and raise some questions. The present system is able to determine that the problem is not internal fouling (coking) occurring in the radiant tubes because the process pressure drop and tube metal temperatures are within the expected range. The present system is able to determine that the problem is convection fouling because, for the current firing rate there is an increase in bridgewall temperature, stack temperature, and the stack damper is more open than expected as indicated by the fired-systems model  1204 . 
     When combined with generation of the optimized settings as discussed above, the present systems and methods are able to invalidate potential anomalies, such as improper air register settings, as causing the discrepancy in expected versus measured values. 
     The above discussed anomaly detection may occur in either methods  2400  or  2600  during operation of the heater in blocks  2422  and  2618 , respectively. Furthermore, the above discussed anomaly detection may be performed by other “analyzers” described herein, such as the fuel analyzer  1148 , the draft analyzer  1152 , the emissions analyzer  1154 , and the process-side analyzer  1176 . Each of these analyzers may operate to detect different anomalies, as well. 
     Cloud Computing Embodiments: 
     In embodiments, a portion or all of the airflow analyzer  1150  may be implemented remotely from the process controller  128 , such as in the network-based “cloud”, where the airflow analyzer  1150  and the process controller  128  is a portion of an edge computing scheme. For example, geometry information in the air analyzer  1150 , and airflow optimizer  1202  may be stored at the external server  164 , such that after the fired-systems model  1204  is solved to generate the optimized burner air register settings  1206  (and/or optimized stack damper settings  1208 , and/or optimized air handling damper settings  1210 ). These generated settings are then transmitted from the external server  164  to the process controller  128  for display on the display  1108  or automatic control of the hardware associated with each optimized setting. The data necessary for analysis by the airflow analyzer  1150  may be gathered at the process controller  128  (such as at the system DCS or PLC (plant control system) and transmitted to the external server  164  for analysis by the airflow analyzer  1150   0 . Alternatively, or additionally, one or more of the devices capturing the current operating parameters  1402  may be an embedded device having data transmission capability that transfers its respective data directly to the external server  164  for analysis by the airflow analyzer  1150 . 
     System Component Validation: 
     Continued understanding on the modeling side (either via the the airflow analyzer  1150 , or other physics-based modeling, or analytics discussed herein or in any of the provisional applications incorporated by reference as discussed above) allows for the process controller  128  to monitor and validate the measurement devices that populate the data within the sensor database  130 . Because the modeling provides optimized control settings, the analyzers discussed herein are able to compare the measured data to the expected data generated via calculations. If the measured data varies with respect to the calculated data, the system is able to troubleshoot the particular reason for that discrepancy. 
     For example, a variation in a fuel-side calculation may indicate that the calculated heat release based on pressure with clean burner tips is higher than a given fuel mass flow measurement. In such situation, the fuel analyzer  1148  may implement the following troubleshooting: (i) identify that one or more of the burners are out of service, (ii) determine if one or more of the fuel valves are full-open (even though they are supposed to be at a specific setting), (iii) determine if the burner tips have additional fouling that is visually identifiable, (iv) determine if the burner tips have a different orifice diameter than expected, and (v) determine if the pressure transmitter or flow meter providing the measurements are in need of calibration. 
     As another example, a variation in a fuel-side calculation may indicate that the calculated heat release based on pressure with clean burner tips is lower than a given mass flow measurement. In such situation, the fuel analyzer  1148  may implement the following troubleshooting: (i) confirm quantity of out-of-service burners, (ii) verify that the out-of-service burners are truly out of service, (iii) determine if there are gas leaks within the combustion system (visually observed by small “candle flames” until the tip is plugged), (iv) determine if flame patterns match conditions indicating missing burner tips or burner tips that have ports that are eroded, (v) confirm burner tip orifice diameter, (vi) determine improper line loss calculations, (vii) determine if the pressure transmitter or flow meter providing the measurements are in need of calibration. 
     As another example, a variation in an air-side calculation may indicate that the calculated oxygen is higher than a measured oxygen level. In such situation, the air-side analyzer  1150  (or the emissions analyzer  1154 ) may implement the following troubleshooting process: (i) confirm the number of burners out-of-service, (ii) confirm that the air register settings are accurate within the model, (iii) analyze the burners for blocked air passages, such as blocked air inlets, refractory fallen into burner throats, wall burner air-tip fouling, loos burner insulation, flashback or combustion back pressure within the burner, (iv) determine potential leaks within the process tubes (and shut down if so), (v) verify ambient air conditions, (vi) check wind speeds, (vii) calibrate air-side measurement devices such as the air-pressure and O2 analyzer. 
     As another example, a variation in an air-side calculation may indicate that the calculated oxygen is lower than a measured oxygen level. In such situation, the air-side analyzer  1150  (or the emissions analyzer  1154 ) may implement the following troubleshooting process: (i) confirm the number of burners out-of-service, (ii) confirm that the air register settings are accurate within the model, (iii) analyze for tramp-air entering the system (such as via sight ports, lighting ports, gas tip riser mounting plates, etc.), (iv) determine potential leaks within the process tubes (and shut down if so), (v) verify ambient air conditions, (vi) check wind speeds, (vii) analyze for additional gas leakage into the system, (viii) calibrate air-side measurement devices such as the air-pressure and O2 analyzer. 
     Definitions 
     The disclosure herein may reference “physics-based models” and transforming, interpolating, or otherwise calculating certain data from other data inputs. Those of ordinary skill in the art should understand what physics-based models incorporate, and the calculations necessary to implement said transforming, interpolating, or otherwise calculating for a given situation. However, the present disclosure incorporates by reference chapter 9 of the “John Zink Hamworthy Combustion Handbook”, which is incorporated by reference in its entirety (Baukal, Charles E. The John Zink Hamworthy Combustion Handbook. Fundamentals. 2nd ed., vol. 1 of 3, CRC Press, 2013) for further disclosure related to understanding of fluid dynamics physics-based modeling and other calculations. It should be appreciated, however, that “physics-based models” and transforming, interpolating, or otherwise calculating certain data from other data inputs is not limited to just those fluid dynamics calculations listed in chapter 9 of the John Zink Hamworthy Combustion Handbook. 
     Changes may be made in the above methods and systems without departing from the scope hereof. It should thus be noted that the matter contained in the above description or shown in the accompanying drawings should be interpreted as illustrative and not in a limiting sense. The following claims are intended to cover all generic and specific features described herein, as well as all statements of the scope of the present method and system, which, as a matter of language, might be said to fall therebetween. 
     Any of the functionality described herein may be combined, in any combination, with the functionality described in the applications incorporated by reference as discussed above. Such combinations include using given outputs from the various described “analyzers” to identify further insights into the control of the described combustion systems, as will be appreciated by those of ordinary skill in the art. Examples of combinations are produced below: 
     (A1) In a first aspect, a combustion system includes: a heater having a heater housing; an air source coupled to the process heater via air ductwork; a plurality of burners configured to combust a fuel source with the air source to produce thermal energy, each burner including a burner air register configurable to one of a plurality of burner air register settings to control input of the air source into the burner; an oxygen sensor configured to generate a sensed oxygen level inside the heater; a processor; and a memory operatively coupled to the processor. The memory stores an air-side analyzer comprising computer readable instructions that when executed by the processor operate to: iteratively solve a fired-systems model of the process heater based on fuel information, a target heat release of the plurality of burners, ambient air information, and available airflow at each of the plurality of burners to identify optimized burner air register settings to achieve a target global excess oxygen level to be sensed by the oxygen sensor, and, output the optimized burner air register settings to a heater controller of the process heater. 
     (A2) In an embodiment of (A1), the plurality of burners are separated into burner zones within the heater housing. 
     (A3) In an embodiment of (A2), each burner zone having a respective target heat release; the computer readable instructions that operate to iteratively solve the fired-systems model further operating to: solve the fired-systems model according to each respective target heat release of each burner zone. 
     (A4) In an embodiment of any of (A1)-(A3), each burner zone having a respective target excess oxygen level; the computer readable instructions that operate to iteratively solve the fired-systems model further operating to: solve the fired-systems model to achieve each respective target excess oxygen level of each burner zone. 
     (A5) In an embodiment of any of (A1)-(A4) each respective target excess oxygen level of each burner zone being above, below, or equal to a target global oxygen level, and the cumulative excess oxygen equaling the target global excess oxygen level. 
     (A6) In an embodiment of any of (A1)-(A5), the ambient air information being sensed by sensors proximate the heater housing or obtained from a third-party weather server. 
     (A7) In an embodiment of any of (A1)-(A6), the available airflow at each burner being known based on information about each respective burner. 
     (A8) In an embodiment of any of (A1)-(A7), the available airflow at each burner being determined by the air-flow analyzer based on the pressure differential across each burner. 
     (A9) In an embodiment of (A8), the pressure differential being determined based on ductwork air pressure sensor data and in-heater pressure data. 
     (A10) In an embodiment of any of (A9), the in-heater pressure data defining draft within the heater. 
     (A11) In an embodiment of any of (A9)-(A10), the in-heater pressure data being interpolated for each of the plurality of burners from pressure sensor data from a pressure sensor located at a known location from each of the plurality of burners. 
     (A12) In an embodiment of any of (A1)-(A11), the fired-systems model being generated based on manual testing data of the heater. 
     (A13) In an embodiment of any of (A1)-(A11), the fired-systems model being defined by physics-based models of air-flow within the heater housing. 
     (A14) In an embodiment of any of (A1)-(A13), the fired-systems model being defined by computational fluid dynamics (CFD) of the heater. 
     (A15) In an embodiment of any of (A1)-(A14), the fired-systems model being tuned based on real-time sensed data from within the heater, computational fluid dynamics data of the heater, historical data of the heater and/or other heaters similar to the heater, or any combination thereof. 
     (A16) In an embodiment of any of (A1)-(A15), the computer readable instructions that operate to iteratively solve the fired-systems model further operating to: identify optimized stack damper settings and/or optimized air-flow handling settings to achieve a target global excess oxygen level to be sensed by the oxygen sensor. 
     (A17) In an embodiment of any of (A1)-(A16), the computer readable instructions that iteratively solve the fired-systems model operating to: solve the fired-systems model based on one or more constraints. 
     (A18) In an embodiment of any of (A17), the one or more constraints requiring the optimized burner air register settings to include at least one burner air register at full-open setting. 
     (A19) In an embodiment of any of (A1)-(A18), the computer readable instructions that when executed by the processor further operate to: iteratively solve the fired-systems model based on a desired number of burner air register changes over a future period of time to identify optimized stack damper settings and/or optimized air-handling settings to define a necessary draft range within the heater that can withstand weather variations over the future period of time. 
     (A20) In an embodiment of any of (A19), the computer readable instructions that when executed by the processor further operate to: identify the optimized stack damper settings and/or optimized air-handling settings that define the necessary draft range and maintain predicted operational cost below a predefined operational cost threshold. 
     (A21) In an embodiment of any of (A1)-(A20), the computer readable instructions that when executed by the processor further operate to: receive sensed data from within the heater after implementation of the optimized burner air register settings, the optimized stack damper settings, the optimized air-flow handling settings, or any combination thereof; and output an alert when the sensed data varies from expected data. 
     (A22) In an embodiment of any of (A21), the alert including an audible, visual, or tactile indication on the heater controller. 
     (A23) In an embodiment of any of (A21)-(A22), the alert including a remediation action that shuts down the heater. 
     (A24) In an embodiment of any of (A1)-(A23), the air-side analyzer being located remotely from the heater controller; the output the optimized burner air register settings to a heater controller of the process heater including transmitting the optimized burner air register settings to the heater controller. 
     (B1) In a second aspect, a method for automatic air-register settings in a combustion system includes: iteratively solving a fired-systems model of a process heater, of the combustion system, based on fuel information, a target heat release of a plurality of burners in the process heater, ambient air information, and available airflow at each of the plurality of burners to identify optimized burner air register settings to achieve a target global excess oxygen level to be sensed by an oxygen sensor that senses oxygen level inside the process heater; and, output the optimized burner air register settings to a heater controller of the process heater. 
     (B2) In an embodiment of (B1), the plurality of burners being separated into burner zones within the heater housing. 
     (B3) In an embodiment of any of (B1)-(B2), each burner zone having a respective target heat release; the iteratively solving the fired-systems model including solving the fired-systems model according to each respective target heat release of each burner zone. 
     (B4) In an embodiment of any of (B1)-(B3), each burner zone having a respective target excess oxygen level; the iteratively solving the fired-systems model including solving the fired-systems model according to each respective target excess oxygen level of each burner zone. 
     (B5) In an embodiment of any of (B4), each respective target excess oxygen level of each burner zone being above, below, or equal to a target global oxygen level, and the cumulative excess oxygen equaling the target global excess oxygen level. 
     (B6) In an embodiment of any of (B1)-(B5), further comprising receiving the ambient air information from sensors proximate the heater housing or obtaining the ambient air information from a third-party weather server. 
     (B7) In an embodiment of any of (B1)-(B6), the available airflow at each burner being known based on information about each respective burner. 
     (B8) In an embodiment of any of (B1)-(B7), further comprising determining the available airflow at each burner based on the pressure differential across each burner. 
     (B9) In an embodiment of any of (B8), further comprising determining the pressure differential based on ductwork air pressure sensor data and in-heater pressure data. 
     (B10) In an embodiment of any of (B9), the in-heater pressure data defining draft within the heater. 
     (B11) In an embodiment of any of (B9)-(B10), further comprising interpolating the in-heater pressure data for each of the plurality of burners from pressure sensor data from a pressure sensor located at a known location from each of the plurality of burners 
     (B12) In an embodiment of any of (B1)-(B11), the fired-systems model being generated based on manual testing data of the heater. 
     (B13) In an embodiment of any of (B1)-(B12), the fired-systems model being defined by physics-based models of air-flow within the heater housing. 
     (B14) In an embodiment of any of (B1)-(B13), the fired-systems model being defined by computational fluid dynamics (CFD) of the heater. 
     (B15) In an embodiment of any of (B1)-(B14), the fired-systems model being tuned based on real-time sensed data from within the heater, computational fluid dynamics data of the heater, historical data of the heater and/or other heaters similar to the heater, or any combination thereof. 
     (B16) In an embodiment of any of (B1)-(B15), further comprising identifying optimized stack damper settings and/or optimized air-flow handling settings to achieve a target global excess oxygen level to be sensed by the oxygen sensor 
     (B17) In an embodiment of any of (B1)-(B16), further comprising solving the fired-systems model based on one or more constraints. 
     (B18) In an embodiment of any of (B17), the one or more constraints requiring the optimized burner air register settings to include at least one burner air register at full-open setting. 
     (B19) In an embodiment of any of (B1)-(B18), further comprising: iteratively solving the fired-systems model based on a desired number of burner air register changes over a future period of time to identify optimized stack damper settings and/or optimized air-handling settings to define a necessary draft range within the heater that can withstand weather variations over the future period of time. 
     (B20) In an embodiment of any of (B1)-(B19), further comprising: identifying the optimized stack damper settings and/or optimized air-handling settings that define the necessary draft range and maintain predicted operational cost below a predefined operational cost threshold. 
     (B21) In an embodiment of any of (B1)-(B20), further comprising: receiving sensed data from within the heater after implementation of the optimized burner air register settings, the optimized stack damper settings, the optimized air-flow handling settings, or any combination thereof; and outputting an alert when the sensed data varies from expected data. 
     (B22) In an embodiment of any of (B21), the alert including an audible, visual, or tactile indication on the heater controller. 
     (B23) In an embodiment of any of (B21)-(B22), the alert including a remediation action that shuts down the heater.