17911 results about "Fuel gas" patented technology

The present invention includes a spray drying disposable device for use in a spray drying system. The disposable has a spray drying head and a plasma drying chamber. The head has a spray dry nozzle assembly in fluid communication with the plasma source and the pressurized aerosol gas source. The pressurized gas flows in a vortex pattern that atomizes plasma droplets in the chamber. The head also includes a plenum has uniform air pressure of the drying gas. A baffle plate forms the floor of the plenum having drying gas jets that supply drying gas to the chamber. The atomized plasma droplets evaporate in the presence of the drying gas emitted from the jets to obtain dried plasma particles and humid air. A capture filter captures the dried plasma particles and allows the humid air to pass. The humid air passes through the gas outlet and the exhaust port.

The invention relates to the technical field of data processing, and discloses a fuel gas monitoring fault analysis method and system and a storage medium. The method comprises the following steps: acquiring multi-dimensional data through a sensor group, and transmitting the multi-dimensional data to a processing unit for pre-screening through an Internet of Things protocol; carrying out filtering, feature calculation and dimension reduction processing on the data to obtain a feature vector; establishing a fault database and generating a mapping relation; time sequence and space data are fused to calculate a fault judgment value; an early warning result is obtained by combining sensor state data evaluation; historical data is retrieved, similarity is calculated, and a disposal instruction is generated. According to the method, the accuracy of gas pipe network fault diagnosis is improved through fusion analysis of multi-source data, and early recognition and early warning of faults are achieved.

The invention belongs to the technical field of gas leakage monitoring, and particularly relates to a multi-sensor fused gas leakage sensing, identifying and alarming method, which comprises the following steps of: firstly, monitoring the state of a gas pipeline in real time through an integrated sensor, acquiring and preprocessing multi-dimensional data, secondly, analyzing sound wave and image data by utilizing a pre-trained abnormal sensing model, and finally, analyzing the abnormal sensing model. Thirdly, determining whether the gas pipeline is abnormal or not according to data such as temperature and pressure and abnormal monitoring scores, quickly positioning a leakage point through a multi-position node sensor and a time positioning algorithm once abnormal leakage is detected, and finally, judging whether the gas pipeline is abnormal or not according to the leakage position and an abnormal determination result. Through the gas leakage emergency strategy library and the alarm device, when a corresponding emergency processing scheme is rapidly generated, abnormal fixed-point alarm is rapidly carried out, and gas safety is ensured.

The invention relates to the technical field of gas pipeline safety assessment, in particular to a gas pipeline safety assessment early warning system and method based on data analysis. The method comprises the following steps: collecting gas pressure data of a gas pipeline at multiple points at the same time, carrying out time-space synchronization processing to obtain aligned gas pressure data so as to construct a continuous gas pressure field of the pipeline, based on the gas pressure field, identifying the pressure distribution difference of the pipeline, estimating the transient flow velocity of the gas, continuously recording the transient flow velocity of the gas, and deducing the change of the flow velocity. Judging the deformation condition of the inner wall of the pipeline in combination with air pressure field data, positioning a deformation area, reconstructing a pipeline frame, analyzing deformation response, identifying a deformation type, identifying a corrosion evolution trend, performing safety evaluation, judging the gas circulation degree and performing physical safety evaluation. According to the invention, dynamic monitoring of the gas pipeline is realized, a data-driven safety management mode is promoted, the early warning capability of potential risks is improved, and a more intelligent safety assessment and early warning mechanism is formed.

A method of operating a gas turbine engine comprising an engine core comprising a turbine, a compressor, a combustor arranged to combust a fuel, and a core shaft connecting the turbine to the compressor; a fan located upstream of the engine core; a gearbox that receives an input from the core shaft and outputs drive to the fan; an oil loop system arranged to supply oil to the gearbox; and a heat exchange system comprising an air-oil heat exchanger through which the oil flows, a fuel-oil heat exchanger through which the oil and the fuel flow; and a valve arranged to allow a proportion of the oil sent via at least one of the heat exchangers to be varied, is disclosed, the method comprising controlling the valve such that, under cruise conditions, an oil flow ratio of:rate⁢ of⁢ oil⁢ flow⁢ into⁢ air-oil⁢ heat⁢ exchangerrate⁢ of⁢ oil⁢ flow⁢ into⁢ fuel-oil⁢ heat⁢ exchangeris in the range from 0 to 0.59.

The invention discloses a multi-source data fusion vehicle-mounted gas leakage traceability detection system and method, and relates to the technical field of gas leakage traceability detection. According to the vehicle-mounted gas leakage traceability detection method based on multi-source data fusion, the diffusion coefficient is dynamically corrected by obtaining the gas concentration and environmental data in the vehicle running process in real time, and the leakage source position and the leakage rate are reversely calculated in combination with the self-adaptive particle swarm optimization algorithm; the method can dynamically correct the diffusion coefficient according to the gas concentration and environmental data obtained in real time when the vehicle runs, and accurately and reversely calculate the leakage source position and the leakage rate through the adaptive particle swarm optimization algorithm, and the traditional detection method generally depends on static parameters and preset models, lacks the ability to cope with the fast changing environment, and is difficult to detect. According to the method, the model is adjusted in real time through multi-dimensional environment data obtained in real time, such as information of wind speed, temperature and humidity, air pressure and the like, and it is ensured that the leakage source can still be rapidly and accurately positioned in a dynamic environment.

The invention relates to the technical field of intelligent inspection, in particular to a pipeline inspection abnormal hidden danger intelligent identification system based on an unmanned aerial vehicle. According to the invention, the three-dimensional grid construction is carried out on the data collected by the unmanned aerial vehicle in the inspection process, so that the space division of the inspection area is realized, and the detection of the gas pipeline has higher precision. In combination with hyperspectral data analysis, measurement of methane concentration can be accurately mapped to space grid points, interference of environmental factors is reduced, and preliminary recognition accuracy of a leakage area is improved. On the basis of local concentration gradient calculation, through a data smoothing and diffusion optimization method, the boundary of a leakage area is clearer, interference of environmental noise is eliminated, meanwhile, the concentration value is dynamically adjusted, and the adaptive capacity to the change trend of leakage points is enhanced. By means of the construction of the virtual diffusion field and in combination with the space occupation condition of terrain obstacles, the analysis of the gas flow path is more accurate, and the problem of misjudgment caused by terrain complexity is solved.

The invention provides an intelligent fuel gas accessory part safety monitoring method, an Internet of Things system and a medium, and relates to the field of fuel gas pipeline accessory facility monitoring. The method is executed by an intelligent gas accessory safety monitoring Internet of Things system, and comprises the following steps: determining a first abnormal value; determining a target acquisition parameter based on the first abnormal value; determining an acquisition instruction based on the target acquisition parameter; determining a second abnormal value; and determining a maintenance instruction and / or a parameter adjustment instruction based on the second abnormal value. The Internet of Things system comprises a government safety supervision management platform, a government safety supervision sensing network platform, a government safety supervision object platform, a gas company management platform, a gas company sensing network platform, a gas equipment object platform and a gas pipeline maintenance object platform. The method can be operated after a computer instruction stored in a computer readable storage medium is read. According to the method, real-time monitoring and intelligent management of the appurtenances can be realized, so that the detection result is more comprehensive and accurate.

The invention provides a one-key start-stop operation monitoring method and system for a gas-steam combined cycle unit, and relates to the technical field of equipment state monitoring, and the method comprises the steps: obtaining operation data, carrying out the data cleaning, noise reduction and standardization, and extracting the performance characteristics of the unit; constructing a component correlation model based on the spatial-temporal characteristics, and optimizing operation efficiency parameters; and performing fault diagnosis by using a multi-modal feature enhancement network, constructing a layered optimization control system, and performing control strategy optimization to obtain an optimal control strategy. According to the invention, intelligent monitoring, fault diagnosis and optimal control of the gas-steam combined cycle unit can be realized, the operation efficiency and reliability of the unit are improved, the fault risk is reduced, and the service life of equipment is prolonged.

A method for separating a raw feed gas stream utilizes a compressor, a chiller, a membrane drying stage, and a plurality of membrane separation stages. The raw feed gas stream may comprise biogas. In one example, the raw feed gas stream is supplied to the chiller where it is cooled to a target operating temperature to separate out condensed water. The gas stream is then supplied to a membrane drying stage to separate out water vapor. An off-gas from one of the membrane module stages may be recycled as a low pressure sweep gas on the low pressure side of the membrane drying stage to increase the driving force for water permeation within the membrane drying stage. The gas stream is then supplied to the plurality of membrane separation stages where it is upgraded into a high purity methane stream.

A multi-energy load forecasting method, a multi-energy load forecasting system, an electronic device, a program, and a storage medium are provided that realize accurate long-term forecasting of multi-energy loads in a target integrated energy system under conditions where no historical load data is available. [Solution] A multi-energy load forecasting method for an integrated energy system without historical data involves obtaining the meteorological characteristics of a target complex and the cooling, heating, electricity, and gas historical data of a source domain group complex, preprocessing the obtained data, performing cross-correlation and generalization ability analysis of the complex on the preprocessed cooling, heating, electricity, and gas historical data of the source domain group complex, determining appropriate source domain data, constructing a multi-energy load forecasting model, training the model based on the source domain data according to the Metas training policy, obtaining a trained forecasting model, and inputting the preprocessed meteorological characteristics of the target complex into the forecasting model to obtain a forecast result.

A method of operating a gas turbine engine having a combustor having a combustion chamber and a plurality of fuel spray nozzles configured to inject fuel into the combustion chamber. The fuel spray nozzles have a first subset of fuel spray nozzles and a second subset of fuel spray nozzles. The combustor is operable in a condition in which the first subset of fuel spray nozzles are supplied with more fuel than the second subset of fuel spray nozzles. A ratio of the number of fuel spray nozzles in the first subset of fuel spray nozzles to the number of fuel spray nozzles in the second subset of fuel spray nozzles is in the range of 1:2 to 1:5. The method includes providing a fuel to the plurality of fuel spray nozzles having a calorific value of at least 43.5 MJ / kg. A gas turbine engine can be for an aircraft.

The invention provides a multi-mode fusion gas station leakage-fire early warning method and system, and belongs to the field of gas system leakage and fire monitoring. The method comprises the following steps: firstly, acquiring infrared image data, pressure and gas concentration time sequence data of a gas station pipeline; secondly, the collected data are preprocessed; thirdly, an abnormal heat source image data set is manufactured, and a yov5 abnormal heat source monitoring model is constructed and trained and used for recognizing an abnormal heat source and calculating the fire symptom abnormal probability; and then, merging the fire symptom anomaly probability with a sensor data set, making a leakage-fire data set, and establishing a multi-mode gas station leakage-fire anomaly identification model for training and tuning. And finally, the trained multi-mode model is used for carrying out leakage-fire abnormity monitoring on the gas station, and corresponding early warning information is sent out according to an output result. According to the invention, gas leakage-fire joint abnormity discrimination can be realized, and the safety and early warning accuracy of the gas station are improved.

The invention discloses a gas user intelligent safety inspection system based on the Internet of Things. According to the invention, through a multi-stage intelligent decision-making mechanism, the active protection capability of gas safety management is significantly improved. A traditional alarm system depends on single sensor threshold triggering, is susceptible to environmental interference and lags in response, while the system can accurately distinguish scenes such as real leakage and cooking interference by fusing multi-dimensional data such as gas concentration, temperature and flame and combining a user behavior mode to dynamically evaluate a risk level. For example, when it is detected that the gas concentration is abnormal but not accompanied by sudden temperature rise or a flame signal, the system automatically lowers the alarm level and only pushes prompt information; and when high-risk leakage is confirmed, the valve is immediately closed in a linkage mode, exhaust equipment is started, synchronous early warning is conducted through multiple channels such as telephones, short messages and a community platform, and it is ensured that the user and rescue strength respond in the golden time.

The invention discloses a big data prediction model intelligent ammonia spraying control method and system suitable for kiln flue gas denitration. According to the ammonia spraying control method, historical and real-time data of multiple parameters such as the fuel gas flow of the glass kiln are collected firstly, the NOx amount is predicted through modeling of the LSTM-GRU hybrid neural network, the ammonia spraying amount is calculated through self-adaptive control, and the accuracy is ensured through two-stage correction. And the calculated ammonia spraying amount is transmitted to a production master control system to adjust an ammonia supply valve, and automatic alarm and manual control are switched in case of failure. The system comprises a data acquisition module, an intelligent prediction module, a self-adaptive control module and the like, and further comprises a dynamic catalytic reaction simulation test platform for optimization. According to the invention, intelligent automatic control of the big data model is realized, the ammonia spraying amount is accurately adjusted, the denitration efficiency and the ammonia utilization rate are improved, the operation cost is reduced, and the system reliability and stability are enhanced.

The invention discloses a gas mixing control device for an LPG (Liquefied Petroleum Gas) generator set, which relates to the technical field of generator set operation control, and comprises a gas engine for realizing accurate mixing proportion control under the matching of a proportion dynamic response component, predicting the optimal gas mixing proportion and flow demand under the current working condition, and controlling the gas engine to operate according to the optimal gas mixing proportion and flow demand. When the propane content in the LPG is increased, the model prediction controller properly reduces the gas inflow and increases the air amount, sufficient combustion is ensured, the mixing proportion and flow can be rapidly corrected, the combustion process is rapidly recovered to be stable, it is ensured that the gas engine stably operates under different loads, the whole device forms flow balance and stable operation, and the service life of the gas engine is prolonged. Under different gas sources and LPG component differences, effective components actually participating in combustion are accurately judged, so that the needed gas and air amount is accurately calculated, accurate mixing proportion control is achieved, and meanwhile accurate control over the mixed gas mixing process is achieved under the cooperation of an adjusting control assembly.

The invention relates to the technical field of fuel gas safety, and discloses an intelligent fuel gas safety valve and a method for intelligently opening and closing the safety valve, and the intelligent fuel gas safety valve comprises a sensor unit which is configured to be installed near a fuel gas pipeline or fuel gas equipment; the control unit is in communication connection with the sensor unit; the execution unit is in communication connection with the control unit; the communication unit is in communication connection with the control unit; and the standby power supply is used for providing emergency power for the intelligent gas safety valve when the main power supply fails or is powered off. The concentration, the pressure, the temperature and the flow of the fuel gas are monitored in real time through the sensor unit, the system can quickly send out an instruction for closing the valve when detecting abnormal conditions (such as gas leakage and too high or too low pressure), and accidents such as fire disasters or explosions caused by fuel gas leakage are effectively prevented. The system monitors a plurality of key parameters of the gas system through a plurality of sensors in a combined mode, and a multi-level safety guarantee mechanism is formed.

An aircraft gas turbine engine includes a combustor, with a combustion chamber and fuel spray nozzles to inject fuel into the chamber. The nozzles include first and second subsets. The first subset of nozzles is supplied with fuel at a greater rate than each of the second subset. A ratio of nozzles in the first subset to the second subset is 1:3 to 1:6. A lean cruise nvPM emissions index ratio isEIcruise⁡(lean),SAFEIcruise⁡(lean),FF,where EIcruise(lean),SAF isEImaxTO,SAF+EIclimb,SAF2and EIcruise(lean),FF isEImaxTO,FF+EIclimb,FF2.EImaxTO,SAF is nvPM emissions index operating at 100% available thrust and EIclimb,SAF is the nvPM emissions index operating at 85% available thrust if fuel includes sustainable aviation fuel. EImaxTO,FF is the nvPM emissions index operating at 100% available thrust and EIclimb,FF is the nvPM emissions index at 85% available thrust if fuel is a fossil-based hydrocarbon. The lean cruise nvPM emissions index ratio is less than 1.

A gas turbine engine for an aircraft is disclosed. The gas turbine engine comprises: a combustor, comprising a combustion chamber and a plurality of fuel spray nozzles configured to inject fuel into the combustion chamber, wherein the plurality of fuel spray nozzles comprises a first subset of fuel spray nozzles and a second subset of fuel spray nozzles, wherein the combustor is operable in a condition in which each of the fuel spray nozzles of the first subset of fuel spray nozzles is supplied with fuel at a greater fuel flow rate than each of the fuel spray nozzles of the second subset of fuel spray nozzles, wherein a ratio of the number of fuel spray nozzles in the first subset of fuel spray nozzles to the number of fuel spray nozzles in the second subset of fuel spray nozzles is in the range of 1:2 to 1:5. A thrust nvPM emissions index ratio is defined as:EImaxTO / FmaxTOEIidle / Fidlewhere: EIidle is the system loss corrected nvPM emissions index in mg / kg of the gas turbine engine if operating at around 7% available thrust for given operating conditions; EImaxTO is the system loss corrected nvPM emissions index in mg / kg of the gas turbine engine if operating at around 100% available thrust for the given operating conditions; FmaxTO is the thrust of the gas turbine engine at around 100% available thrust in kN for the given operating conditions; and Fidle is the thrust of the gas turbine engine at around 7% available thrust in kN for the given operating conditions. The thrust nvPM emissions index ratio is greater than 0.001. The gas turbine engine is configured to provide fuel comprising a sustainable aviation fuel (SAF) to the plurality of fuel spray nozzles. Also disclosed is a method of operating the gas turbine engine.

The invention relates to the technical field of urban public safety, in particular to an underground gas pipe network safety pre-warning system, which comprises an acquisition module, a monitoring module, a monitoring module and a control module, and is characterized in that the acquisition module is used for arranging sensing nodes at key positions of a gas pipeline body and a surrounding environment to form a distributed monitoring network; the method comprises the following steps: synchronously acquiring mechanical deformation, methane concentration and mechanical vibration data of a pipeline through a distributed monitoring network to obtain a multi-modal sensing data set; the fusion module is used for performing humidity and temperature interference correction on the methane concentration data in the multi-modal sensing data set to obtain corrected methane concentration data; and performing fusion processing on the mechanical deformation data, the mechanical vibration data and the corrected methane concentration data to obtain an initial pipeline safety state evaluation index. Through multi-source data fusion, environmental interference correction and spatial domain calibration, transmission and dynamic analysis are combined, and precise early warning and efficient linkage disposal of the safety state of the gas pipe network are achieved.

The invention relates to the technical field of energy, in particular to a dynamic self-adaptive control method and system for a gas-steam combined cycle unit, and the method comprises the steps: constructing a multi-modal model library comprising a plurality of operation modes; operating parameters and environment parameters of the unit are collected in real time, and multi-source data fusion and system state evaluation are carried out; carrying out multi-time scale prediction on the load demand, fuel characteristics and environmental parameters of the unit based on a deep learning model; dynamically selecting model precision according to a prediction result, and implementing a multi-mode collaborative optimization decision to generate a control instruction; and executing the control instruction and monitoring an execution effect, and carrying out adaptive adjustment on model parameters and strategies according to feedback. According to the method, the unit can maintain efficient and stable operation under the scenes of power grid peak regulation, rapid load fluctuation, complex environment change and the like, meanwhile, pollutant emission is reduced, and the service life of key equipment is prolonged.

Systems and methods for providing lubrication to a gas turbine engine are described. An example gas turbine engine includes a plurality of bearings disposed along an axial length of a rotatable shaft to provide rotational support between a static structure and at least one of a compressor and a turbine of the gas turbine engine. The gas turbine engine further includes a fuel system operable to deliver a mixture of fuel and lubricant sequentially to at least one of the plurality of bearings and the combustor so that during operation of the gas turbine engine, at least the lubricant within the mixture is in a liquid phase prior to being received by the at least one of the plurality of bearings, and in a vapor phase once the lubricant is delivered to the at least one of the plurality of bearings.

1. The name of the product of this design: Portable gas heater (single and double tank series). 2. Purpose of this design product: used for heating, especially suitable for outdoor use. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the key points of the design: 3D drawing of Design 1. 5. Designate Design 1 as the base design.

A gas turbine engine for an aircraft is disclosed. The gas turbine engine comprises: a combustor, comprising a combustion chamber and a plurality of fuel spray nozzles configured to inject fuel into the combustion chamber, wherein the plurality of fuel spray nozzles comprises a first subset of fuel spray nozzles and a second subset of fuel spray nozzles, wherein the combustor is operable in a condition in which each of the fuel spray nozzles of the first subset of fuel spray nozzles is supplied with fuel at a greater fuel flow rate than each of the fuel spray nozzles of the second subset of fuel spray nozzles, wherein a ratio of the number of fuel spray nozzles in the first subset of fuel spray nozzles to the number of fuel spray nozzles in the second subset of fuel spray nozzles is in the range of 1:3 to 1:6. A MTO nvPM emissions index ratio is defined as:EImaxTO,SAFEImaxTO,FFwhere: EImaxTO,SAF is the system loss corrected nvPM emissions index in mg / kg of the gas turbine engine when operating at around 100% available thrust for given operating conditions if a fuel provided to the plurality of fuel spray nozzles comprises a sustainable aviation fuel (SAF); and EImaxTO,FF is the system loss corrected nvPM emissions index in mg / kg of the gas turbine engine when operating at around 100% available thrust for the given operating conditions if a fuel provided to the plurality of fuel spray nozzles is a fossil-based hydrocarbon fuel. The MTO nvPM emissions index ratio of the gas turbine engine is less than 1. The gas turbine engine is configured to provide fuel comprising a SAF to the plurality of fuel spray nozzles. Also disclosed are methods of operating the gas turbine engine.

The invention relates to the technical field of intelligent control, in particular to a wall-hanging stove constant-temperature energy-saving control system based on enhanced autonomous learning and an SAC algorithm, and the system comprises a gas flow optimization module which collects heating operation data of a wall-hanging stove, classifies the heating operation data according to the change characteristics of a plurality of events, calculates the frequency of occurrence of each event, and outputs the frequency of occurrence of each event; and analyzing the change condition of the operation data according to the event occurrence frequency, and generating a gas flow data set. According to the method, the gas flow data is generated through real-time collection and multi-dimensional classification analysis of the operation data of the wall-hanging stove in combination with the event triggering characteristics, and accurate data support is provided for follow-up heat supply demand prediction and combustion control. And the opening degree of the combustion valve and the gas supply pressure are dynamically adjusted through the enhanced autonomous learning algorithm, dynamic adaptation of the gas flow and the heating requirement is achieved, and the gas utilization efficiency is remarkably improved. And dynamic division and adjustment of a heat exchange area are combined, so that the distribution characteristic of a heat flow path is optimized.

The invention discloses a community fuel gas system management method and system based on fuel gas safety, and relates to the technical field of fuel gas system management.The method comprises the following steps that basic data of an old community fuel gas system are collected, field inspection is conducted on fuel gas pipelines, valves and combustion appliances in a community, and current situation data are recorded; risk assessment is carried out based on the on-site inspection result and basic data of the gas system, and potential safety hazards and weak links are identified; and potential safety hazards and weak links are identified according to risk assessment. Sensors are installed on gas pipelines and key equipment, key data of pressure, flow and leakage detection are collected and processed in real time, early warning of different levels is triggered once abnormal data are monitored, a corresponding early warning mechanism is generated, and therefore the safety monitoring level of a gas system is improved, and the safety of the gas system is guaranteed. Potential safety hazards can be found and early warned in time, and accidents are effectively avoided.

A gas turbine engine for an aircraft. The gas turbine engine comprising: a combustor, comprising a combustion chamber and a plurality of fuel spray nozzles configured to inject fuel into the combustion chamber, wherein the plurality of fuel spray nozzles comprises a first subset of fuel spray nozzles and a second subset of fuel spray nozzles, wherein the combustor is operable in a condition in which each of the fuel spray nozzles of the first subset of fuel spray nozzles is supplied with fuel at a greater fuel flow rate than each of the fuel spray nozzles of the second subset of fuel spray nozzles, wherein a ratio of the number of fuel spray nozzles in the first subset of fuel spray nozzles to the number of fuel spray nozzles in the second subset of fuel spray nozzles is in the range of 1:2 to 1:5. An MTO nvPM emissions index ratio-modified fuel flow is defined as:EImaxTO,SAFEImaxTO,FF×Wf,maxTOwhere: EImaxTO,SAF is the system loss corrected nvPM emissions index in mg / kg of the gas turbine engine when operating at around 100% available thrust for given operating conditions if a fuel provided to the plurality of fuel spray nozzles comprises a sustainable aviation fuel (SAF); EImaxTO,FF is the system loss corrected nvPM emissions index in mg / kg of the gas turbine engine when operating at around 100% available thrust for the given operating conditions if a fuel provided to the plurality of fuel spray nozzles is a fossil-based hydrocarbon fuel; and Wf,maxTO is the mass flow rate of fuel provided to the plurality of fuel spray nozzles in kg / s when the gas turbine engine is operating at around 100% available thrust for the given operating conditions. The MTO nvPM emissions index ratio-modified fuel flow of the gas turbine engine in kg / s is less than 2. The gas turbine engine is configured to provide fuel comprising a SAF to the plurality of fuel spray nozzles. Also disclosed is a method of operating the gas turbine engine.

A gas turbine engine includes a combustor with a combustion chamber and fuel spray nozzles to inject fuel into the combustion chamber. The nozzles include a first and second subset. Each of the nozzles of the first subset is supplied with fuel at a greater rate than each of the second subset. A ratio of nozzles in the first subset to nozzles in the second subset from 1:3 to 1:6. A fuel-flow nvPM emissions index ratio isEIidle×Wf,idleRImaxTO×Wf,maxTO.EIidle and EImaxTO are the system loss corrected nvPM emissions index in mg / kg operating at around 7% and 100% available thrust for the given operating conditions, respectively. Wf,idle and Wf,maxTO are the rate of fuel flow to the fuel spray nozzles in kg / s at around 7% and 100% available thrust for the given operating conditions, respectively. The fuel-flow nvPM emissions index ratio of the gas turbine engine is less than 0.3.

A turbine engine for an aircraft including a combustor, a turbine, and a steam system. The combustor generates combustion gases. The turbine receives the combustion gases and is drivingly coupled to a shaft. The steam system includes a boiler, a superheater, and a steam turbine. The boiler receives water and is fluidly connected to the combustor to receive a first portion of the combustion gases from the combustor and to boil the water to generate steam. The superheater is located downstream of the combustor to receive a second portion of the combustion gases from the combustor and to heat the steam. The steam turbine is fluidly coupled to the superheater to receive the steam from the superheater and to rotate the steam turbine. The steam turbine is drivingly coupled to the shaft.

A gas turbine engine includes: a rich burn, quick quench, lean burn combustor having a number of fuel spray nozzles in the range 14-22 or a number of fuel spray nozzles per unit engine core size in the range 2 to 6. An nvPM emissions index ratio is defined as:EIidle×Wf,idleEImaxTO×Wf,maxTOwhere: EIidle and EImaxTO are respectively the nvPM emissions index in mg / kg of gas turbine engine if operating at around 7% or 100% available thrust for given operating conditions; Wf,idle and Wf,maxTO are respectively the rate of fuel flow to fuel spray nozzles in kg / s at around 7% or 100% available thrust for given operating conditions. The fuel-flow nvPM emissions index ratio is less than 0.08. The gas turbine engine is configured to provide fuel including sustainable aviation fuel to fuel spray nozzles. Also disclosed is a method of operating the gas turbine engine.