Air Path Research Articles

Performance degradation modeling of civil aviation engines based on component characteristic map optimization

In order to provide a theoretical basis for the degradation of the air path performance of civil aviation engines at the unit level, the CFM56-3 engine was used as the research object. First, on the basis of using the characteristic map scaling method to obtain the component characteristic equation, the selection process of the scaling reference point of the fan general characteristic map was optimized, and a surface fitting method of the characteristic map was proposed to construct an engine component-level benchmark performance model that meets specific speed conditions under steady-state conditions. Then, by introducing the fault factor to generate the fault coefficient matrix, the deviation of the engine monitoring parameters as the component efficiency decreases was calculated, and compared with the fingerprint map data of the GE training manual, it was verified that the engine steady-state performance model that integrates the fan characteristic map scaling reference point optimization and the characteristic map surface fitting method has good accuracy and use in the analysis of air path performance degradation.

Surface roughness effects in a transonic axial flow compressor operating at near-stall conditions

Surface roughness is a major contributor to performance degradation in gas turbine engines. The fan and the compressor, as the first components in the engine's air path, are especially vulnerable to the effects of surface roughness. Debris ingestion, accumulation of grime, dust, or insect remnants, typically at low atmospheric conditions, over several cycles of operation are some major causes of surface roughness over the blade surfaces. The flow in compressor rotors is inherently highly complex. From the perspective of the component designers, it is, thus, important to study the effect of surface roughness on the performance and flow physics, especially at near-stall conditions. In this study, we examine the effect of surface roughness on flow physics such as shock-boundary layer interactions, tip and hub flow separations, the formation and changes in the critical points, and tip leakage vortices among other phenomena. Steady and unsteady Reynolds Averaged Navier Stokes calculations are conducted at near-stall conditions for smooth and rough National Aeronautics and Space Administration rotor 67 blades. Surface streamlines, Q-criterion, and entropy contours aid in analyzing the flow physics qualitatively and quantitatively. It is observed that from the onset of stall, to fully stalled conditions, the blockage varies from 21.7% to 59.6% from 90% span to the tip in the smooth case, and from 40.5% to 75.2% in the rough case. This significant blockage, caused by vortex breakdown and chaotic flow structures, leads to the onset of full rotor stall.

Characterizing hydrogen-diesel dual-fuel performance and emissions in a commercial heavy-duty diesel truck

This study investigates hydrogen (H2) as a supplementary fuel in heavy-duty diesel engines using pre-manifold injection. A H2-diesel dual-fuel (H2DF) system was implemented on a commercial class-8 heavy-duty diesel truck without modifying the original diesel injection system and engine control unit (ECU). Tests were conducted on a chassis dynamometer at engine speeds between 1000 and 1400 rpm with driver-demanded torques from 10 to 75%. The hydrogen energy fraction (HEF) was strategically controlled in the range between 10 and 30%. Overall, CO2 reduction (comparable to the HEF level) was achieved with similar brake-specific energy consumption (BSEC) at all loads and speeds. To maintain the same shaft torque, the driver-demanded torque was reduced in H2DF operation, which resulted in a lower boost pressure. At higher loads, engine-out BSNOx slightly decreased, while BSCO and black carbon (BC) increased significantly due to lower oxygen concentration resulting from the lower boost pressure. At lower loads, engine-out BSCO and BSBC decreased moderately, while NO2/NO ratio increased substantially in H2DF operation. Deliberate air path and diesel injection control are expected to enable higher HEF and GHG reductions.

Assessing the performance of three experimental methods to investigate air path inside wall assemblies

Air leakages in buildings’ envelopes can lead to an over-consumption of energy and to additional issues such as moisture damage and poor indoor environment. The leakage air flow rate is usually assessed at the building scale using a pressurization test and leakage locations are commonly detected by infrared thermography or smoke. However, little is known about the air paths within wall assemblies, despite the need for detailed experimental data to validate numerical models for the coupled heat, moisture and pollutants transfers. One of the reasons is the difficulty to find adapted and robust experimental methods.In this paper, three experimental laboratory approaches are tested on simple light-wall assembly configurations: the implementation of three-dimensional grids of thermocouples and relative humidity sensors within the wall, and the use of a micro-particle tracer. The results are compared with each other as well as with numerical simulations.It was found that thermocouple grid has limited intrusiveness, good accuracy and response time but results are subject to flow fluctuations. Moreover, heat capacity and conductive transfer within materials complicate the correlation between heat and air transfers. Humidity sensors grid avoids the latter issue but is intrusive, overestimating air dispersion. The micro-particle tracer has the advantage of being non-intrusive and less impacted by flow fluctuations but its ability to track the air flow is strongly linked with the insulation filtration properties and the flow velocity. Overall this method seems to provide the best results but it is also the most complex and time-consuming one.

Partitioned model predictive control of LiU-Diesel engine air path based on recursive least squares

Partitioned model predictive control of LiU-Diesel engine air path based on recursive least squares

Integrated 1D Simulation of Aftertreatment System and Chemistry-Based Multizone RCCI Combustion for Optimal Performance with Methane Oxidation Catalyst

This paper presents a comprehensive investigation into the design of a methane oxidation catalyst aftertreatment system specifically tailored for the Wärtsilä W31DF natural gas engine which has been converted to a reactivity-controlled compression ignition NG/Diesel engine. A GT-Power model was coupled with a predictive physical base chemical kinetic multizone model (MZM) as a combustion object. In this MZM simulation, a set of 54 species and 269 reactions as chemical kinetic mechanism were used for modelling combustion and emissions. Aftertreatment simulations were conducted using a 1D air-path model in the same GT-Power model, integrated with a chemical kinetic model featuring 15 catalytic reactions, based on activation energy and species concentrations from combustion outputs. The latter offered detailed exhaust composition and exhaust thermodynamic data under specific operating conditions, effectively capturing the intricate interactions between the investigated aftertreatment system, combustion, and exhaust composition. Special emphasis was placed on the formation of intermediate hydrocarbons such as C2H4 and C2H6, despite their concentrations being lower than that of CH4. The analysis of catalytic conversion focused on key species, including H2O, CO2, CO, CH4, C2H4, and C2H6, examining their interactions. After consideration of thermal management and pressure drop, a practical choice of a 400 mm long catalyst with a density of 10 cells per cm2 was selected. Investigations of this catalyst’s specification revealed complete CO conversion and a minimum of 89% hydrocarbon conversion efficiency. Integrating the exhaust aftertreatment system into the air path resulted in a reduction in engine-indicated efficiency by up to 2.65% but did not affect in-cylinder combustion.

Adaptive integral sliding mode fault‐tolerant control for diesel engine air path system via disturbance observer

AbstractThis paper proposes a fault‐tolerant control strategy for the air path system of a turbocharged diesel engine, considering the simultaneous presence of matched and mismatched external disturbances, additive and loss of effectiveness fault modes in the EGR and VGT subsystems. Firstly, a disturbance observer based on theory is designed for estimating additive faults and external disturbances, and the upper bound of observation error is obtained. Based on the observation information, an integral sliding mode surface is designed, and the effectiveness of the sliding mode surface is analyzed. For the loss of effectiveness faults in the actuators, a novel adaptive update sliding mode controller is designed. The proposed control algorithm can get the fault information of the system and achieve fault‐tolerant control of through controller reconstruction. Ultimately, the effectiveness of the proposed method is validated through simulations and comparative analysis.

The Effect of Turbulence on Generation of High-Intensity Light Channels during Femtosecond Laser Pulse Propagation along a 100-Meter Air Path

The Effect of Turbulence on Generation of High-Intensity Light Channels during Femtosecond Laser Pulse Propagation along a 100-Meter Air Path

Структура и элементная база приёмо-передающего модуля для организации подводной оптической беспроводной системы передачи данных

In the paper, the results of theoretical study of a wireless optical data transmission channel, as well as experimental study of its characteristics, taking into account different configurations of the optical component base of receiving and transmitting modules, were presented. The model of the wireless underwater optical communication channel with pulse-position modulation (4 bits per symbol) of digital data traffic with 100 Mbps is proposed. The model showed that to organize a communication channel on a 10 m path, the use of an array of light-emitting diodes (LEDs) is requires (the amount is up to 20 LEDs). For this case, a sufficiently large route budget will be provided, even with additional factor that reduce the efficiency of light propagation in seawater. The LEDs were chosen to organize the data transmission channel, since they have a wide radiation pattern and allow the implementation of a relatively simple driver circuit. The required optical radiation power is realized with the use of an array of LEDs. Schematic diagrams of the LEDs driver and power supply for the receiving and transmitting modules have been designed. A measuring layout with optical transmitter and receiver blocks has been implemented. The test signal is a regular sequence of pulses with a duty cycle of 2, and a frequency of 1 MHz. In the receiving module, the signal from the output of the pin photodiode is amplified using a wideband operational amplifier. Sets of 3 pin photodiodes and 10 LEDs were selected and tests were carried out to determine options for optical components that provide the best time characteristics of the output electrical signal in terms of delay time, rising and falling edges of pulses in a wireless optical airborne communication channel. Also, measurements were done on an air path with a length of 0.25-3 m using one or two LEDs as part of the transmitting module. It has been experimentally confirmed that the organization of a communication channel with a length of up to 10 m requires about 15-20 light-emitting diodes. Further study involves the designing and testing of a driver for the LEDs array and a prototype transceiver module.

CFD simulation and optimization of an industrial cement gas–solid air classifier

An air classifier is one of the main and effective devices in cement industry. In this study, a three-dimensional, steady and two-phase (solid-gas) computational fluid dynamics (CFD) simulation was performed to optimize the performance of this device in the Kerman Momtazan cement plant, Iran. After the validation of CFD results, the air flow field and air path lines between fixed blades were checked carefully and the non-uniformity in velocity distribution and the formation of vortex flows between the blades close to particle inlets were observed. The study tried to improve the device efficiency by changing the method of entering particles into the device, resulting in a reduction in air classifier electrical energy consumption (from 41 to 35 (kW h)/t) and an increase in production rate (from 203 to 214 t/h). Additionally, the study investigated the effects of other modifiable operating conditions like rotary cage rotation speed, pressure difference, and inlet air temperature on the particle size distribution and classifier efficiency. The results showed that increasing the cage rotation speed decreased the product rate and the product particles mean diameter while increasing pressure difference or increasing temperature increased the product rate and the product particles mean diameter. It was concluded that these modifiable operating conditions can significantly affect the performance of the air classifier in the cement industry.

A method to quantify the advantages of a variable valve train for CI engines

Today’s CI engines are subject to strict regulations of pollutant emissions and ambitious fuel consumption targets. Therefore, the interaction between the engine and the exhaust aftertreatment system (ATS) has become increasingly important. Numerous studies have shown that a variable valve train (VVT) improves the interaction between engine and ATS. However, most of these studies either quantify the advantage on a specific engine or only present complex CFD models, such that the results are not easily transferable to different engines. Thus, engine manufacturers cannot directly use these results to assess the advantage of various VVT strategies for their engines. In this paper, we propose a cycle-discrete cylinder model based on first principles which allows to simulate various VVT strategies. In contrast to present methods based on CFD, the proposed cylinder model can be realized with the equations presented. Furthermore, the model is identified with measurement data of an engine without a VVT. A separate engine, which is retrofitted with a fully VVT, is used to validate the proposed modeling approach. Using the identified model in combination with a mean-value model of the air path, we are able to simulate the effects of early intake valve closing, early exhaust valve opening, and cylinder deactivation for a complete CI engine that has no VVT installed. The model is then used to highlight the advantage of a VVT for two scenarios at part-load operation. At cold start, where the temperature of the ATS must be increased quickly, variable valve timing achieves higher enthalpy flows to the ATS while also lowering engine-out NOx emissions when compared to a standard engine strategy. If the ATS is at the operating temperature, cylinder deactivation achieves significantly higher enthalpy flows which prevents the ATS from cooling down. In addition, cylinder deactivation also lowers fuel consumption and engine-out NOx emissions.

Power saving in a central air conditioning system by using multiple PCMs integrated with fresh air path

Decreasing the fresh air temperature before entering the air conditioning (AC) system will have a significant influence on reducing domestic power usage. To obtain a low fresh air temperature, the current work highlights a numerical investigation of an air-phase change materials (PCM) heat exchanger (H.EX.) with AC systems using ANSYS software. The heat exchanger was divided into several cells filled with multiple PCMs (RT-22, RT-24, RT-26). Throughout the day, the outside air passes through the system to decrease its temperature. Also, the PCMs are discharged by the low ambient temperature during the night. A numerical model was established and validated with experimental results from the literature and got a good match. The influences of multiple types of PCMs, outlet air temperature from the system, and the reduction in the cooling coil power were investigated. The outcomes concluded that multiple PCMs have a significant impact in decreasing the fresh air temperature before entering the AC system, compared to a single PCM. The fresh air temperature decreased from 45, 42, and 39 °C to roughly the values of 33, 32, and 31 °C, respectively, by using the air-PCM H.EX. The cooling power decreased by 11.76, and 11.17 % at the fresh air temperature of 45, and 39 °C, respectively, compared to the system without air-PCM H.EX. The proposed design is suggested to integrate with the AC systems.

Design of a high counting efficiency sensor for 1.0 cubic feet per minute laser particle counter.

Based on the theory of Mie scattering, an optical sensor for a 1.0 cubic feet per minute laser particle counter is developed in this paper. First, an illumination optical path relying on aspherical lens and cylindrical lens for laser shaping was designed, and a narrow optical spot with the illumination in the vertical direction of the photosensitive area approximately distributed as a flat top was obtained. Second, the scattering light path was designed by using the theory of Mie scattering and geometric optics method. Then, the structure of the sampling air path was designed with reference to the principle of Laval nozzle, and the particle flow trajectory was verified by simulation using the fluid dynamics software Ansys Fluent. Finally, the performance of the optical sensor was measured with polystyrene latex (PSL) particles, and the results showed that the counting efficiency of the 0.3μm particle size channel met the requirement of 50% ± 20% and the 0.5μm particle size channel met the requirement of 100% ± 10%, which complied with the ISO 21501-4 standard.

Systematic hyperparameter selection in Machine Learning-based engine control to minimize calibration effort

For automotive powertrain control systems, the calibration effort is exploding due to growing system complexity and increasingly strict legal requirements for greenhouse gas and real-world pollutant emissions. These powertrain systems are characterized by their highly dynamic operation, so transient performance is key. Currently applied control methods require tuning of an increasing number of look-up tables and of parameters in the applied models. Especially for transient control this state-of-the-art calibration process is unsystematic and requires a large development effort. Also, embedding models in a controller can set challenging requirements to production control hardware. In this work, we assess the potential of Machine Learning to dramatically reduce the calibration effort in transient air path control development. This is not only done for the existing benchmark controller, but also for a new preview controller. In order to efficiently realize preview, a strategy is proposed where the existing reference signal is shifted in time. These reference signals are then modeled as a function of engine torque demand using a Long Short-Term Memory (LSTM) neural network, which can capture the dynamic input–output relationship. A multi-objective optimization problem is defined to systematically select hyperparameters that optimize the trade-off between model accuracy, system performance, calibration effort and computational requirements. This problem is solved using an exhaustive search approach. The control system performance is validated over a transient driving cycle. For the LSTM-based controllers, the proposed calibration approach achieves a significant reduction of 71% in the control calibration effort compared to the benchmark process. The expert effort and turbocharger experiments used in calibrating transient compensation maps in physics-based feedforward controller are replaced by little simulation time and parametrization effort in ML-based controller, which requires significantly less expert effort and system knowledge compared to benchmark process. The best trade-off between multi-objective cost terms is achieved with one layer and 32 cells LSTM neural network for both non-preview and preview control. For non-preview control, a comparable control system performance is achieved with the LSTM-based controller, while 5% reduction in cumulative NOx emissions and similar fuel consumption is achieved with preview controller.

Optimizing Cutting Sequences and Paths for Common-Edge Nested Parts

Different from the normal nesting algorithm, common-edge nesting reduces the spacing between parts, improves the utilization rate of the sheet, and shortens the processing time. Although common-edge nested parts may be useful in theory, they are not practical for large-scale production due to their cutting limitations. Existing research either did not consider all common cutting constraints or used graph theory methods for global common cutting path planning. However, due to cutting thermal effects and sheet deformation, it is difficult to use global common cutting path planning in actual processing. Therefore, this paper proposes a cutting sequence optimization algorithm for common-edge nested parts that consider all cutting constraints and proposes an algorithm for generating and optimizing common cutting paths. Experiments show that the common cutting path optimization algorithm proposed in this paper can reduce about 70% of the air path compared with commercial software. Furthermore, comparison by optical microscopy shows that the quality of the actual machined part is not inferior to that of the part machined according to the cut path generated by the commercial software.

Numerical study on soundproof photovoltaic–thermal air path design based on ISO 9806 experimental validation

Numerical study on soundproof photovoltaic–thermal air path design based on ISO 9806 experimental validation

Dynamic model-based feature extraction for fault detection and diagnosis of a supermarket refrigeration system†

With the increasing concerns over climate change and carbon emissions, fault detection and diagnostics (FDD) of low–global warming potential (GWP) refrigerant supermarket refrigeration systems has gained great attention from academic and industrial sectors. Various FDD approaches have been developed to detect, identify, and diagnose faults to save energy, improve food quality, and protect the environment. To mitigate the difficulty of collecting high-quality steady-state operational data in field operations faced by most model-based FDD methods, this study developed dynamic models of a low–GWP refrigerant (CO2) supermarket refrigeration system. The model accuracy was validated using manufacturer data and experimental data. Simulations were conducted to predict the system dynamic response under two common operational faults—evaporator air path blockage fault and the display case door open fault—to identify fault patterns and define key dynamic behavior indexes for supporting FDD algorithm development.

A Modular Approach for Diesel Engine Air Path Control Based on Nonlinear MPC

This article presents a systematic approach to realize highly dynamic control strategies for the air path of diesel engines. It is based on grey-box models of individual air path components, designed to be applied in nonlinear model predictive control (NMPC). Specifically, they are suited for algorithmic differentiation and gradient-based optimization. This modular approach allows to derive models for a variety of complex air path systems and can be identified with a low amount of measurement data. An NMPC structure, which is based on these models, enables the tracking of arbitrary air path reference signals and allows the introduction of further control objectives for overactuated systems. We demonstrate our approach’s general applicability and effectiveness on two different laboratory engines using rapid control prototyping hardware. For a turbocharged light-duty diesel engine with dual-loop exhaust gas recirculation (EGR), we apply the proposed control structure to track intake manifold gas conditions while simultaneously minimizing engine pumping losses. Experimental results show an excellent tracking performance and reduced pumping losses compared to other control strategies. For a turbocharged heavy-duty engine with high-pressure EGR, we experimentally demonstrate a superior tracking performance to that obtained with a reference controller. Due to the modular and systematic approach, the algorithm design is straightforward, and the experimental calibration effort is low.

Numerical Evaluation of Fuel Consumption and Transient Emissions of Different Hybrid Topologies for Two-Wheeler Application

<div>In Asian countries, small two-wheelers form a major share of the automobile segment and contribute significantly to carbon dioxide (CO<sub>2</sub>) emissions. Hybrid drives, though not widely applied in two-wheelers, can reduce fuel consumption and CO<sub>2</sub> emissions. In this work three hybrid topologies, viz., P2 (electric motor placed between engine and transmission), P3 (electric motor placed between transmission and final drive), and power-split concepts (with planetary gear-train) have been modeled in Simulink, and their fuel consumption and emissions under the World Motorcycle Test Cycle (WMTC) have been evaluated. A physics-based model for the Continuously Variable Transmission (CVT) was used which is capable of predicting its transient characteristics. A map-based fuel consumption model and a Neural Network (NN)-based transient emission model were used for the engine. The NN-based transient emission model avoids the need to model the air path and fuel path in transient conditions, which is time consuming. The fueling characteristics of the Engine Control Unit (ECU) in transients need not be known if an NN model is built and tuned with sufficient experimental data. Several transient experiments were performed with speed-load profiles similar to the WMTC for tuning the NN emission models. Simulation results show that the P2 hybrid, P3 hybrid, and power-split drives have fuel economy benefits of about 27%, 37%, and 49%, respectively, compared to the conventional powertrain. However, nitrogen oxides (NOx) emissions are much higher for the hybrid powertrains due to the operation of the engine at higher load ranges for efficiency but are still within the prevailing BS6 Indian emission limits. A significant portion of the wheel energy input can be recovered through efficient regenerative braking in the WMTC. This will be even more significant under peak traffic city driving conditions. The belt losses in the CVT significantly reduce the potential benefits of the hybrid powertrain, and hence, an efficient transmission to replace it will be beneficial.</div>

Potentials of Air Path Variabilities for Future Commercial Vehicle Gas Engines to Increase Efficiency and Reduce Emissions

Potentials of Air Path Variabilities for Future Commercial Vehicle Gas Engines to Increase Efficiency and Reduce Emissions