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Density is an important indicator for evaluating diesel fuel quality that directly affects the injection timing and injection rule of the engine, and also has a significant impact on the spray broken particle size, the spray penetration distance, the spray cone angle, and so forth, which in turn affects the combustion process and pollutant emission of the compression-ignition engine. Therefore, it is important to accurately predict the diesel fuel mixture density in industrial and compression-ignition engines. However, the mathematical models for predicting the density of diesel fuel mixture with changed temperature are relatively lacking and less accurate, especially for ternary diesel fuel mixtures with different physicochemical properties. This paper proposes a mathematical model including binary and ternary diesel mixtures under changed fuel volume fraction and temperature, and published data were used for verification. The data verification results show that: for the density prediction of binary diesel fuel mixtures at constant temperature, the average relative deviation (ARD) is 0.0245%, the RMS error (RMSE) is 0.000344, and the correlation coefficient (R) is 0.9993. For the density prediction of binary diesel fuel mixtures at changed temperature, the ARD is 0.0609%, the RMSE is 0.000695, and R is 0.9980. For the density prediction of ternary diesel fuel mixtures at constant temperature, the ARD is lower than 0.0571%, the RMSE is lower than 0.000610, and R is higher than 0.9861. For the density prediction of ternary diesel fuel mixtures at changed temperature, the ARD is 0.0484%, the RMSE is 0.000513, and R is 0.9996. The diesel mixed fuel density prediction model proposed in this paper has good accuracy and calculation convenience, and provides important reference value for measuring or designing the density of diesel mixed fuel in the field of compression-ignition engines. [ABSTRACT FROM AUTHOR]

In the realm of prognosticating the remaining useful life (RUL) of pivotal components, such as aircraft engines, a prevalent challenge persists where the available historical life data often proves insufficient. This insufficiency engenders obstacles such as impediments in performance degradation feature extraction, inadequacies in capturing temporal relationships comprehensively, and diminished predictive accuracy. To address this issue, a 1D CNN-GRU prediction model for few-shot conditions is proposed in this paper. In pursuit of more comprehensive data feature extraction and enhanced RUL prognostication precision, the Convolutional Neural Network (CNN) is selected for its capacity to discern high-dimensional features amid the intricate dynamics of the data. Concurrently, the Gated Recurrent Unit (GRU) network is leveraged for its robust capability in extracting temporal features inherent within the data. We combine the two to construct a CNN-GRU hybrid network. Moreover, the integration of data distribution alongside correlation and monotonicity indices is employed to winnow the input of multi-sensor monitoring parameters into the CNN-GRU network. Finally, the engine RULs are predicted by the trained model. In this paper, experiments are conducted on a sub-dataset of the National Aeronautics and Space Administration (NASA) C-MAPSS multi-constraint dataset to validate the effectiveness of the method. Experimental results have demonstrated that this method has high accuracy in RUL prediction tasks, which can powerfully demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

This article presents the authors' considerations regarding the possibilities of developing fuel equipment for modern compression ignition engines used in special and non-road vehicles. The paper discusses the process of fuel combustion and atomization in the chamber of a piston combustion engine. The paper then presents the concept of modifying the atomizer of a modern fuel injector for operation using hydrogen-containing fuels of plant origin. The authors present a review of tests performed using an engine dynamometer on a modern engine with a Common Rail system running on biofuel. The CI engine operated with standard and modified fuel injectors. During the tests, the external ecological characteristics of the engine were analyzed as a function of rotational speed; the values of injection doses at individual rotational speeds and their effects on the characteristics were read from the current parameters, and the pressure and temperature in the engine's combustion chamber were measured. The research results show that implementing the changes proposed by the authors of this work is a good direction for the development of compression ignition engines. [ABSTRACT FROM AUTHOR]

AbstractThe unique mission of the helicopter compared to the fixed-wing aircraft introduces challenges to the aerodynamic stability of the turboshaft engine. Thus, the assessment of the availability of stability margin for special operating conditions in the envelope of this equipment is required to guarantee flight safety. In this paper, a rapid nonlinear complete engine method is developed to investigate the effect of helicopter ground-effect operation and high-altitude hovering on aerodynamic stability by considering factors including inlet distortion and component matching. Research indicated that the most dangerous point of stability margin in a unique section of the flight envelope is high altitude hovering, with about a 16.7% reduction in available stability margin compared to standard ground test conditions. This paper also investigates the effects of typical helicopter ground effects on a turboshaft engine and shows that the stability margin will be reduced by a maximum of 1.43% in hovering if the influence of ground effects in the flight envelope is not considered in the design. [ABSTRACT FROM AUTHOR]

This paper introduces a feedforward control method for physical systems that can be described with linear parameter-varying (LPV) models. The proposed feedforward controller structure is consequently derived from a generic LPV representation and is shown to be identifiable directly from noisy measurement data. The identified structure is advantageous for feedforward control, as using a simple least squares algorithm allows to parameterise basis functions representing the required input trajectory to follow a given output trajectory. Also, with the proposed regularisation, the input trajectory remains bounded even when the physical system exhibits non-minimum phase behaviour. Additionally, the proposed controller structure does not possess states but only considers the inputs and outputs signals and their derivatives, leading to a unique physical interpretation of each controller's parameter. Multiple feedforward controllers identified at various operating points can therefore be directly merged to create a parameter-varying controller. A nonlinear and locally non-minimum phase system is considered in this study, i.e. an engine air path, to evaluate the performances of the proposed feedforward strategy. The controller parameters are first identified from noisy measurement data, and then the proposed feedforward controller is implemented with a feedback controller to track the exhaust pressure and $ \mathrm {NO}_{\mathrm {x}} $ NO x concentration. Using a detailed physical simulation of the engine air path, the proposed feedforward strategy showed encouraging output tracking performances compared to state-of-the-art control methods. The presented feedforward method is shown to be straightforward to identify and calibrate while guaranteeing a contained computational complexity and being applicable to many physical systems thanks to its modularity. [ABSTRACT FROM AUTHOR]

In an internal combustion engine, interactions of fuel droplets and heated walls can significantly affect the combustion process and engine performance. The formation and characteristics of secondary droplets from drop-wall interactions are functions of various factors such as fuel properties, impact velocity, ambient conditions, and wall temperature. Understanding the impact behavior is important to optimize the distribution of the fuel-air mixture for efficient and clean combustion and to develop a comprehensive spray-wall interaction model. In this study, three-dimensional smoothed particle hydrodynamics (SPH) simulations are performed to investigate the interactions of fuel droplets with a heated wall at atmospheric and elevated pressures over a range of Weber numbers (We). The SPH model is validated using available experimental data. Secondary atomization is characterized by using size distributions for different fuels. The resulting droplets vary in size, where secondary droplets are mostly below 7 µm in diameter. Following these cases, this paper qualitatively describes the impact process and proposes empirical correlation relating the mean secondary droplet size to ambient pressure in the film-boiling regime. Postimpingement vaporization characteristics are also analyzed and compared for fuels with drastically different vapor pressures. [ABSTRACT FROM AUTHOR]

This paper presents a numerical investigation of the effect of wing integration on the aerodynamic behavior of a typical large civil aero-engine exhaust system at wind-milling flow conditions. The work is based on the dual stream jet propulsion (DSJP) test rig, as will be tested within the transonic wind tunnel (TWT) located at the aircraft research association (ARA) in the UK. The DSJP rig was designed to measure the impact of the installed pressure field due to the effect of the wing on the aerodynamic performance of separate-jet exhausts. The rig is equipped with the dual separate flow reference nozzle (DSFRN), installed under a swept wing. Computational fluid dynamic simulations were carried out for representative ranges of fan and core nozzle pressure ratios (CNPR) for "engine-out" wind-milling scenarios at end of runway (EOR) takeoff, diversion, and cruise conditions. Analyses were done for both isolated and installed configurations to quantify the impact of the installed pressure field on the fan and core nozzle discharge coefficients. The impact of fan and core nozzle pressure ratios, as well as freestream Mach number and high-lift surfaces on the installed suppression effect, was also evaluated. It is shown that the installed pressure field can reduce the fan nozzle discharge coefficient by up to 16%, relative to the isolated configuration for EOR wind-milling conditions. The results were used to inform the design and setup of the experimental activity which is planned for 2023. [ABSTRACT FROM AUTHOR]

This paper provides a framework based on machine learning approach in I4.0 environment to predict the remaining useful life of an aviation engine. For illustration purpose, an industrial case study is presented which applies machine learning algorithms to analyze the data collected using the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) simulation which includes run-to-degradation data for a turbofan engine. The results obtained from the study validate the proposed framework to identify prominent features and perform sequential analysis on unstructured data for predicting the remaining useful life of an aviation engine. Six machine learning models are applied to the dataset containing four subsets: FD001, FD002, FD003 and FD004 in C-MAPSS dataset each working on different degradation conditions for turbofan engine. For FD001, random forest had the lowest RMSE (11.59), and for FD002, FD003 and FD004, the lowest RMSE was given by LGBM classifier (12.78, 7.95 and 11.04), respectively. From the findings, it is observed that LGBM performs better with higher AUC 89% and lowest RMSE. The proposed framework can be applied to a wide range of failure prediction applications. Regardless of the underlying physics, ML-based data-driven methodologies can be used to analyze a wide range of systems. [ABSTRACT FROM AUTHOR]

The prototype O system seamlessly integrates Web searching and browsing on touch-enabled tablets using two-handed gesture interaction, much like handling and marking content on a piece of paper. The system also leverages contextual information to infer user intent and significantly improve search results over traditional keyword-based approaches, enabling users to go beyond websites' "walled garden"' and more fully explore information objects. [ABSTRACT FROM PUBLISHER]

Engine as the core component of mechanical equipment, its operating state directly affects whether the equipment can operate normally. Predicting the engine remaining useful life (RUL) can monitor the health of the engine in real time and formulate a timely and reasonable maintenance plan. Aiming at the engine monitoring data with various and long time span, we propose a direct prediction method of engine RUL based on particle swarm optimization (PSO) optimized multi-layer Long Short-Term Memory (LSTM) in this paper. Firstly, the monitoring data that can well reflect the engine degradation trend is screened out, and the samples are constructed through a sliding time window. Then, a multi-layer LSTM model is constructed to mine the deep-seated features of the samples for predicting the engine RUL. Finally, the hyperparameters of the multi-layer LSTM model are optimized automatically by the PSO algorithm to optimize the performance of the model. The effectiveness of this method is verified by NASA data set. RMSE, MAE and the scoring function are used as evaluation indexes. RMSE and score of the prediction results are 12.35 and 284.1, respectively. It has higher prediction accuracy compared with traditional deep learning and machine learning methods. [ABSTRACT FROM AUTHOR]

Data-driven fault diagnosis method is widely used in the field of engine health management, which uses engine sensor data as input and engine faulty components as output for component-level fault diagnosis of the engine. The application premise of the general data-driven fault diagnosis method is that all data come from the same working conditions, that is, they belong to the same distribution. However, this assumption is not valid in the actual engine fault diagnosis, because the engine state will change with the increase of running time. In the meantime, collecting engine data is usually expensive, time-consuming, and laborious. To solve these problems, extreme learning machine (ELM)-based two transfer learning methods for fault diagnosis of turboshaft engines are proposed in this paper. One is joint solving ELM (JSELM), which regards the information of the target domain and source domain as similar and different parts, respectively, and knowledge is extracted from them at the same time. The other is model transfer-based ELM (MTELM), which uses the idea of pretraining. First, a general ELM classifier is trained with the source domain data and then fine-tuned with the target domain data. Both methods have a good real-time performance as the traditional ELM. When there are a few data in the target domain, they achieve much better classification accuracy than traditional ELM. Finally, experiments are carried out with turboshaft engine simulation data. The results show that both methods are effective, especially MTELM, which has better classification accuracy. [ABSTRACT FROM AUTHOR]

Pulse Detonation Engine has been a point of interest in the propulsion industry for some time and the interest has been rising due to its better output and results. But any system can perform its task efficiently based on the efficiency of its control system. In this paper we have presented a comparative study between multiple control systems- one based on Bluetooth technology, the other based on infrared sensor technology and one based on wired electrical system. For the wireless system, the signal received from either of the media is passed to the various sensors and systems connected through an Arduino board that further controls the solenoid valves and ignition system. Primarily, a control system circuit is developed using Arduino board and different sensors to connect the fuel supply and ignition system. In the next stage, Bluetooth sensors are connected using an android app and then an infrared sensor based system is integrated with the Arduino to control the engine and the performance of the two systems are compared. Whereas for wired system, every sub system is controlled through optical wires including the solenoid valves, the injection system and the sensors. [ABSTRACT FROM AUTHOR]

Turboshaft engines are different from each other due to manufacturing and installation tolerances. Hence, it is difficult to draw out the physical model from the average component maps and design points to represent the performance of the individual engine. The available test-bed data is usually less than the number of correction coefficients to update the maps, and it is the underdetermined state optimization issue. In this paper, we propose a novel reduced-order optimization, namely PSO-EKF algorithm, combined with prior state estimation for non-linear model correction of the turboshaft engine. This method combines the advantages of PSO and extended Kalman filter (EKF). PSO-EKF method converts partial parameters optimized by PSO into parameters directly solved by EKF. The order of optimization space is reduced. Using the correction coefficient function, a stability improvement strategy is designed to ensure the stability of the optimization process. Compared with the GA and PSO algorithms, experimental verification shows that the method has a faster convergence speed and smaller model error than the general PSO. After the performance map is updated by this method, the error of outputs of the individual model is within 1.4 %. [ABSTRACT FROM AUTHOR]

New generations of spark-ignition engines include exhaust gas recirculation (EGR) to improve the engine efficiency. Depending on the design of the EGR routing, some differences in the total amount of recirculated gases that reach each cylinder can be induced. This affects the air-to-fuel ratio on each cylinder due to the combination of the different temperature and composition of the gases at the intake valve closure. As a consequence, significant deviations in the combustion process and the subsequent composition upstream the three-way catalyst can be reached. This paper explores these effects on catalyst performance and tailpipe emissions, individualizing the behavior for each regulated species. The study was performed in a four-cylinder naturally aspirated engine with Atkinson cycle and a close-coupled three-way catalyst. The most significant deterioration in conversion efficiency appeared for the nitrogen oxides, directly linked to the EGR dispersion level. In the case of carbon monoxide (CO) emissions, no significant impact was observed except at high average EGR rates, where one or more of the cylinders exceeded the EGR tolerance for that speed and load. Based on these results, a strategy where the fuel injector command is adapted to correct the air-to-fuel ratio deviations induced by the EGR was developed and implemented. [ABSTRACT FROM AUTHOR]

With escalating environmental standards and the pursuit of energy efficiency, Gasoline Direct Injection (GDI) technology has become crucial for enhancing engine performance and reducing emissions. As a vital component of the engine, the design of the piston ring significantly influences the thermodynamic performance of the engine. This paper systematically studies the thermodynamic impact of piston ring gaps in GDI engines. Initially, through the analysis of heat transfer and piston strength associated with piston ring gaps, the effects on engine thermal efficiency and structural stability are explored. Subsequently, by integrating three different thermal analysis boundary conditions and mechanical load conditions, we assess how these variables affect the piston's thermal state and engine performance. Existing studies, often relying on simplified models or empirical formulas, tend to overlook the complex thermodynamic and mechanical interactions under actual operating conditions, resulting in inadequate predictive accuracy. This research introduces more complex boundary condition simulations, aiming to provide a more precise method for predicting piston performance, thus offering theoretical support and practical guidance for the optimization of GDI engine design. This study not only fills the research gap regarding piston ring gaps but also provides new perspectives and data support for engine design and optimization, contributing to the advancement of efficient, low-emission engine technologies. [ABSTRACT FROM AUTHOR]

This paper presents a Linear Joule Engine Generator (LJEG) powered by ammonia and hydrogen co-combustion to tackle decarbonisation in the electrification of transport propulsion systems. A dynamic model of the LJEG, which integrates mechanics, thermodynamics, and electromagnetics sub-models, as well as detailed combustion chemistry analysis for emissions, is presented. The dynamic model is integrated and validated, and the LJEG performance is optimised for improved performance and reduced emissions. At optimal conditions, the engine could generate 1.96 kWe at a thermal efficiency of 34.3% and an electrical efficiency of 91%. It is found that the electromagnetic force of the linear alternator and heat addition from the external combustor and engine valve timing have the most significant influences on performance, whereas the piston stroke has a lesser impact. The impacts of hydrogen ratio, oxygen concentration, inlet pressure, and equivalence ratio of ammonia-air on nitric oxide (NO) formation and reduction are revealed using a detailed chemical kinetic analysis. Results indicated that rich combustion and elevated pressure are beneficial for NO reduction. The rate of production analysis indicates that the equivalence ratio significantly changes the relative contribution among the critical NO formation and reduction reaction pathways. [ABSTRACT FROM AUTHOR]

Wind propulsion systems (WPS) for commercial ships can be a key ingredient to achieving the IMO green targets. Most WPS installations will operate in conjunction with propellers and marine engines in a hybrid mode, which will affect their performance. The present paper presents the development of a generic, fast, and easy tool to predict the propeller and engine performance variation, along with the cost, as a function of the wind power installed in two operation conditions: fixed ship speed and constant shaft speed. Specific focus is directed toward showing generic trends and trade-offs that inform economic decision-making. To this end, a key feature of the presented work is the ability to assess the cost–benefit of both controllable pitch propellers and fixed pitch propellers (CPPs and FPPs). This provides advice on when, in terms of WPS installation size, it is worthwhile to install which kind of propeller. CPPs are found to be more suitable for newly built wind-powered ships (>70% wind power), while a conventional FPP is satisfactory for wind-assisted ships (<70% wind power) and retrofitted installations. The results for a 91,373 GT bulk carrier showed that a WPS unloads the propeller and the engine, which leads to an increase in the propulsive efficiency and a detrimental rise of the engine specific fuel oil consumption. However, propeller gains are found to be greater than engine losses, which result in extra savings. Thus, not only does a WPS save fuel and corresponding pollutant emissions, but it also increases the entire propulsive efficiency. [ABSTRACT FROM AUTHOR]

The increasing significance of data analytics in modern information analysis is underpinned by vast amounts of user data. However, it is only feasible to amass sufficient data for various tasks in specific data-gathering contexts that either have limited security information or are associated with older applications. There are numerous scenarios where a domain is too new, too specialized, too secure, or data are too sparsely available to adequately support data analytics endeavors. In such cases, synthetic data generation becomes necessary to facilitate further analysis. To address this challenge, we have developed an Algorithm-based Data Generation (ADG) Engine that enables data generation without the need for initial data, relying instead on user behavior patterns, including both normal and abnormal behavior. The ADG Engine uses a structured database system to keep track of users across different types of activity. It then uses all of this information to make the generated data as real as possible. Our efforts are particularly focused on data analytics, achieved by generating abnormalities within the data and allowing users to customize the generation of normal and abnormal data ratios. In situations where obtaining additional data through conventional means would be impractical or impossible, especially in the case of specific characteristics like anomaly percentages, algorithmically generated datasets provide a viable alternative. In this paper, we introduce the ADG Engine, which can create coherent datasets for multiple users engaged in different activities and across various platforms, entirely from scratch. The ADG Engine incorporates normal and abnormal ratios within each data platform through the application of core algorithms for time-based and numeric-based anomaly generation. The resulting abnormal percentage is compared against the expected values and ranges from 0.13 to 0.17 abnormal data instances in each column. Along with the normal/abnormal ratio, the results strongly suggest that the ADG Engine has successfully completed its primary task. [ABSTRACT FROM AUTHOR]

Efficient safeguarding of the security of interconnected devices, which are often resource-constrained, can be achieved through collective remote attestation schemes. However, in existing schemes, the attestation keys are independent of the device configuration, leading to increased requirements for the trusted computing base. This paper introduces a symmetrical aggregate trust attestation that is compatible with devices adhering to the device identifier composition engine framework. The proposed scheme simplifies the trusted computing base requirements by generating an attestation key that is derived from the device configuration. Moreover, the scheme employs distributed aggregate message authentication codes to reduce both the communication volume within the device network and the size of the attestation report, thereby enhancing the aggregation efficiency. In addition, the scheme incorporates interactive authentication to accurately identify compromised devices. [ABSTRACT FROM AUTHOR]

This paper presents the exploration and optimization of a hybridized opposed piston (OP) engine. In this work, the exhaust crankshaft lead (ECL) is introduced as a controllable parameter in the hybridized OP engine enabled by eliminating the conventional geartrain linking the two crankshafts of an OP engine. This allows for variation in the effective compression and expansion ratio of the engine, along with scavenging performance. This novel control actuator as well as the adjustable speed and load setpoint in a series hybrid OP engine powertrain architecture necessitates an intensive calibration effort to realize any possible efficiency improvements. However, the OP engine within this series hybrid powertrain does not need to operate in highly transient conditions, but rather its operating point is fixed or slowly varying. This property permits the use of online calibration techniques. After manually sweeping speed and ECL values at two power setpoints, the use of an extremum-seeking type intercycle optimization algorithm to optimize the operating setpoint is validated, showing that near optimal speed and ECL setpoints can be selected despite the relatively flat operating map of the OP engine. [ABSTRACT FROM AUTHOR]

This paper discusses the selection of an interior permanent magnet synchronous machine and converter for a 100V-200V DC, 100-400 Hz, 150-175 Nm, 30kW-100kW, 1550-4100 rpm electrical vehicle engine alternator. The electrical vehicle engine application requirements are outlined including the engine coupling configuration. Then the characteristics of different machines and their converters are compared through a competitive trade-off study framed by the alternator requirements; direct-drive induction, variable-reluctance, surface permanent magnet synchronous machine, and interior permanent magnet synchronous machine are all considered. The results of the study indicate that the interior permanent magnet synchronous machine is a potentially superior candidate, and so this machine is selected for further investigation. The preliminary findings are described, and the paper concludes with a discussion of current work addressing analytic design. [ABSTRACT FROM AUTHOR]

Engine blades work at high temperature, high pressure and high speed for a long time. Foreign bodies enter during the working process, and inevitably damage occurs. For the repair of damaged surface at the edge of curved and twisted blades, this paper adopts the allocation criterion based on the intact section line of intact blade in the adjacent undamaged area and the intact part of the blade section line in the damaged area to obtain the point cloud feature of the blade section line at the damaged edge and realize the regeneration and reconstruction of damaged surface. At the same time, the iterative closest point (ICP) registration algorithm is used to overcome the shortcoming of searching the nearest point set for a long time. The closest point pair search method based on auxiliary circular neighborhood is proposed to reduce the registration time cost. Finally, the smoothness of the damaged surface is analyzed to verify the feasibility of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

Conventional emulated damping, in which velocity feedback is employed in combination with motor current control to emulate damping, is used in a number of mechatronic applications. As known in the field, although such damping should be strictly passive, several implementation factors render this emulation nonpassive and subject to instability, especially with increasing damping ratios. This paper describes an alternative implementation of emulated damping that employs passive motor control, which does not draw energy from a battery or any other power source. The method is specifically described in the context of a brushless direct-current (BLDC) motor; an unique controller architecture is used along with a particular MOSFET switching scheme which employs only a subset of the standard BLDC motor driver and does not require electronic commutation. This paper employs analytical and experimental means to compare damping control with the described passive motor approach, relative to using a conventional BLDC motor control approach. Stability considerations for each scheme are discussed. Benchtop testing demonstrates the advantage of the passive control scheme in terms of providing smooth behavior, enhancing control robustness, preventing energy leaks, and providing accurate behavior. The special cases of unilateral and asymmetric behaviors (i.e., different damping command for each direction of rotation) are also considered. [ABSTRACT FROM AUTHOR]

Architecture-Driven Modernization (ADM) is a special kind of reengineering that employs models along the process. The main ADM metamodel is the Knowledge Discovery Metamodel (KDM), which is a platform-independent metamodel able to represent several views of a system. Although a lot of research is currently focused on the reverse engineering phase of ADM, little has been devoted to the forward engineering one, mainly on the generation of Platform-Specific Models (PSMs) from KDM. The forward engineering phase is essential because it belongs to the end of the horseshoe model, completing the reengineering process. Besides, the lack of research and the absence of tooling support in this phase hinder the industrial adoption of ADM. Therefore, in this paper, we present a process for creating Transformation Engines (TEs) capable of transforming KDM instances in a chosen PSM. We highlight two main contributions in this work. The first is a process that software engineers can follow for building TEs capable of generating PSM instances (e.g., Java model, Python model, etc.) from KDM instances. Having that on their hands, modernization engineers can then use generators for generating language-specific source code from the PSM. The second is delivering a specific TE called RUTE-K2J, which is able to generate Java models from KDM models. The transformation rules of RUTE-K2J have been tested considering sets of common code structures that normally appear when modernizing systems. The test cases have shown that in this version of RUTE the transformation rules are able to correctly generate 92% of the source code submitted to the transformation. [ABSTRACT FROM AUTHOR]

Historical cars are an important part of the cultural heritage of the last 150 years. Their preservation in technical museums raises the question of how to preserve their primary functionality, namely their mobility. This implies being able to reactivate and to maintain their thermal engines, which are the source of their motion. However, the diversity and complexity of these engines generally require the presence of highly qualified personnel as well as detailed condition reports to assist the conservators. This study proposes to use acoustic emission techniques to facilitate these conservation procedures by objectifying the evaluation of the state of the engines and by providing systematic quantitative indicators for their health monitoring. To illustrate the implementation and the potentialities of this approach, different tests have been carried out at the National Automobile Museum of Mulhouse, on a Renault Type AG1. A dedicated experimental setup and the associated measurement protocol are presented in this paper. The derived results show the ability of this method to detect specific types of engine malfunctions, both during bench test and in situ measurement conditions. A critical discussion is finally proposed to highlight the feasibility and the possibilities of such laboratory techniques in the context of conservation assistance. [ABSTRACT FROM AUTHOR]

A lumped-parameter dynamic performance model for a single-spool turbojet engine is presented in this paper. This model can handle pre and poststall transients under forward and reverse-flow conditions. The inter-component volume technique is employed instead of the standard matching technique to be able to handle high-frequency transients and reverse-flow conditions. Inspired by Greitzer's lumped-parameter surge model, momentum (duct) and volume elements are placed within the flow path to handle surge dynamics. Compressor and turbine maps are extended to low-flow and reverse-flow regions using a combination of the guidelines presented by Kurzke, the cubic axisymmetric characteristics of Moore and Greitzer, and a quadratic function guess for in-stall characteristics. Combustor efficiency, stability limits, and delay are taken from the literature. Poststall behavior of the model is validated using the data available in the literature for a Rolls-Royce Viper engine. A good match is observed with a correct prediction of poststall behaviors, which transition from surge after locked stall to multiple surge cycles around 80% speed and multiple surge cycles to surge after flameout around 95% speed. The effects of different modeling choices and modeling parameters on the obtained results are discussed. The produced model can be calibrated for a specific engine with surge tests, and it can be used for hard-to-test scenarios like surge after shaft breakage. Different surge/stall-causing events, such as fuel spiking, in-bleeding, and shaft breakage, are simulated to see the capabilities of the model. [ABSTRACT FROM AUTHOR]

As a key component of high‐performance switches and routers, the packet forwarding engine (PFE) is mainly responsible for selecting the appropriate output port for tens of thousands of packets within an extremely short time frame. However, the performance of PFE is determined by the selected group membership algorithm. This paper puts forth a hybrid strategy–caching scalar‐pair and vectors routing and forwarding (CSVRF), consisting of virtual output port bitmap caching (VOPBC) and fractional‐N SVRF to address major multicast forwarding issues such as scalability by using content addressable memory. In CSVRF, a virtual output port bitmap cache is introduced, which includes the most popular combinations of output port bitmap and divides the big scalar‐pair into N sub‐groups to achieve parallel compute and the reusability of less bit‐length prime. The results demonstrate that the memory space and the forwarding latency are effectively reduced compared with previous work. In space efficiency, it only required 10% memory space compared with the original SVRF/fractional‐N SVRF, decreased 10% memory usage compared with pure VOPBC and nearly improved 1 to 4 orders of magnitude of packet processing time compared with the original SVRF and the fractional‐N SVRF respectively. [ABSTRACT FROM AUTHOR]

Most hydraulic excavators use passive power control to adjust the engine speed according to the load torque to achieve power matching, which has very limited effectiveness in energy saving. In this paper, an active power optimization control of speed closed-loop engine is proposed to improve its tracking performance for the dynamic energy-saving operating points. The inertia movement of the engine during variable speed control is analyzed to determine the kinetic energy requirements for different start and end operating points. An RBF-based neural network controller is designed based on power optimization to actively compensate the strong hysteresis of the engine speed relative to the optimal torque. The simulation and the experimental results show that the proposed control method has a much faster response for the energy-saving operating points, which reduces the energy consumption by 9.28% and 5.56% without adding any energy storage devices to the hydraulic excavator. [ABSTRACT FROM AUTHOR]

Changing the mass flow rate of powder propellant with high precision and large range is essential and challenging for adjusting thrust of the powder engine. In this paper, the regulation characteristics of the powder flow rate are investigated by adjusting two gases, namely driving gas and regulating gas. Firstly, the effect of driving gas on powder flow are analyzed, which provides the large ranged flow regulation with the adjustment rate of 2.39 and high precision with resolution ratio of 0.8 g/s. The powder flow rate is successfully predicted based on the Bernoulli equation, not only with an less deviation of 4.73%, but also more conducive to development of the lightweight system. Second, the introduction of regulating gas provides a new method for powder flow regulation. The powder flow rate can achieve a regulation rate of 1.36 with a small amount of regulating gas. The linear relationship between powder flow rate and regulating gas fraction is established to enable its prediction. Finally, the regulation logic is proposed, based on which the flow rate can be increased or decreased by adjusting the quantities of these two gases flexibly. This study can provide a reference for the thrust regulation of powder engines. • Regulation of powder flow in powder propellant supply system was realized. • Predictive model of the driving gas in powder flow regulation was constructed. • A new method of powder flow regulation by changing regulating gas was proposed. [ABSTRACT FROM AUTHOR]

In the problem of gliding flight, i.e., aircraft longitudinal movement with its engines switched off, the aircraft was traditionally assumed to be an absolutely rigid body, the Earth was not rotating and had a plane surface, and the atmosphere was quiet. Further, the attack angle and the air density were assumed constant. The aim of this paper is to discuss the applicability limits of these assumptions. [ABSTRACT FROM AUTHOR]

The article describes the impact of hydrogen-containing vegetable fuels consumption with modern injection apparatus. The fuel in question is B100 rapeseed oil ethyl ester. The process of atomizing fuel in the engine at high temperature and in a high pressure chamber plays an important role in the combustion processes in the CI engine. The elements responsible for supplying fuel to the engine's combustion chamber are the injectors and the injection pump. The paper presents the construction and operation of modern injection pumps and fuel injectors, the methods of their diagnosis are discussed, the important role of precision, and the course of their wear phenomenon are indicated. The paper discusses the impact of hydrogen-containing "green" vegetable fuels on the durability and reliability of injection pumps and fuel injectors used in Common Rail systems. In addition, the tests on the operating parameters of the fuel injector and pump operating on conventional fuel and hydrogen-containing "green" biofuel were carried out. [ABSTRACT FROM AUTHOR]

Diesel engines play a very significant role in the automotive industry, but the total emissions of diesel engines are more than 1.8 times that of petrol engines. It is therefore important for diesel engines to control emissions. Theoretically, the Miller cycle can be used to achieve NOx reductions by changing the effective compression ratio, while it has become increasingly popular in recent years with the increasing maturity of current turbocharging technology. Based on Ricardo WAVE software, this paper analyses the NOx emissions and engine performance of diesel engines by modelling and simulating their operation under different loads with two types of Miller cycles (EIVC and LIVC) at different degrees. Simulation of engines operating under different loads allows a more comprehensive study of the effects of the Miller cycle on the engine, and a specific analysis in the context of the actual engine operating environment. The result is that both versions of the Miller cycle are most effective in reducing NOx emissions at 10% load, showing a maximum reduction of 21% for EIVC and 37% for LIVC. However, as the Miller cycle decreases engine power, the paper further investigates the application of turbocharger systems in the EIVC Miller cycle, with results showing a 32% increase in brake power at 10% load and −25% EIVC Miller cycle degree. Both ethanol-fueled diesel-cycle and Miller cycle engines were also analyzed, and a reduction in NOx emissions was observed, as well as hydrogen engine performance and NOx emissions. [ABSTRACT FROM AUTHOR]

Significant efforts are under way to develop innovative ignition systems for spark-ignition engines used in transportation. Within this context, passive pre-chamber technology has emerged as a promising alternative for passenger cars. However, several uncertainties remain regarding the operation of this concept at low engine loads and speeds, as well as the impact of specific design features on combustion stability. Previous investigations have indicated that the tangential angle of the pre-chamber holes can play a vital role in stabilizing the combustion process. Nonetheless, the underlying thermo-physical phenomena responsible for these results have not yet been thoroughly studied. To address these knowledge gaps, this paper presents a numerical study using a computational fluid dynamics model that has been validated with experimental results. An alternative modeling methodology was developed to conduct multi-cycle large-eddy simulations and investigate two different pre-chamber configurations, one with tangential holes and the other with radial holes. The results revealed an intriguing correlation between the combustion stability and the spatial distribution of the flame inside the pre-chamber. The cycle-to-cycle dispersion of pre-chamber flow variables was significantly higher when using radial holes compared to tangential holes, potentially explaining the unstable behavior of the former design. Additionally, the undesirable flow-field of the radial-hole pre-chamber caused the flame to evolve asymmetrically, resulting in substantial variations in the ejected jets. This asymmetry can significantly affect the morphology of the main chamber ignition in each cycle. [ABSTRACT FROM AUTHOR]

As multi/many-core processors are widely deployed in high-performance computing systems, efficient intra-node communication becomes more important. Intra-node communication involves data copy operations to move messages from source to destination buffer. Researchers have tried to reduce the overhead of this copy operation, but the copy operation performed by CPU still wastes the CPU resources and even hinders overlapping between computation and communication. The copy engine is a hardware component that can move data between intra-node buffers without intervention of CPU. Thus, we can offload the copy operation performed by CPU onto the copy engine. In this paper, we aim at exploiting copy engines for MPI blocking collective communication, such as broadcast and gather operations. MPI is a messaging-based parallel programming model and provides point-to-point, collective, and one-sided communications. Research has been conducted to utilize the copy engine for MPI, but the support for collective communication has not yet been studied. We propose the asynchronism in blocking collective communication and the CE-CPU hybrid approach to utilize both copy engine and CPU for intra-node collective communication. The measurement results show that the proposed approach can reduce the overall execution time of a microbenchmark and a synthetic application that perform collective communication and computation up to 72% and 57%, respectively. [ABSTRACT FROM AUTHOR]

This paper presents the results of experimental tests with a spark-ignition engine powered using ammonia and DME (dimethyl ether). The tests were carried out on a CFR (cooperative fuel research) engine with a compression ratio of 10 and a rotational speed of 600 rpm. DME was used as a fuel to facilitate the initiation and then accelerate the combustion in the SI (spark-ignition) engine. It turned out that only about 10% of the energy share of DME ensures the correct combustion process. DME has a positive effect on the combustion stages, reduces the ignition delay time, and shortens the combustion duration. Thanks to this, for 18% of the energy share of NH3, the highest engine efficiency (29.8%), the highest value of the average indicated pressure IMEP (712 kPa), and the minimum value of specific energy consumption (12.1 MJ/kWh) were obtained. Even the smallest DME content ensured the high repeatability of IMEP, below the permissible limit of 5%. [ABSTRACT FROM AUTHOR]

Free-piston engine linear generators (FPELGs) are an innovative linear power device that exhibits the distinctive dynamics of pistons and performance of free-piston engines. Furthermore, the single-cylinder/single-piston FPELG structure type has more advantages than other FPELG structure types, including a straightforward structure and ease of control. However, when coupled with various rebound devices, the operational characteristics and piston and engine performance of single-cylinder/single-piston FPELGs are quite different. Therefore, this paper aims to quantitatively compare the dynamics of the piston and engine performance of single-cylinder/single-piston FPELGs coupled with various types of rebound device. The results indicate that when the equivalent stiffness of the gas spring is greater than that of the mechanical spring, the operating frequency of the piston of the FPELG coupled with a gas spring will be higher than that when coupled with a mechanical spring. During the compression stroke, the piston velocity of a FPELG coupled with a mechanical spring changes linearly, while the piston velocity of a FPELG coupled with a gas spring changes nonlinearly. FPELGs coupled with gas springs have shorter compression and expansion durations compared to those coupled with mechanical springs. In addition, the indicated powers of FPELGs coupled with ideal gas springs and mechanical springs are 1.5 kW and 1.3 kW, respectively. However, due to leakage, the thermal efficiency of a FPELG coupled with an actual gas spring is reduced by approximately 2.5% compared with the FPELG coupled with the ideal gas spring. Furthermore, the operation frequency of the piston is positively correlated with the stiffness of the mechanical spring. In addition, as the stiffness of the mechanical spring increases, the combustion process of the engine becomes close to an isovolumetric process. The changes in piston dynamics and engine performance when increasing the initial gas pressure of the gas spring are similar to those when increasing the stiffness of the mechanical spring. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the causes of damage and fragmentation to the high-pressure turbine (HTP) disc of the RD-33 engine mounted in the MIG-29 aircraft. The authors have carried out an analysis of the changes to the structure of the disc material, both in the areas containing cracks and in the undamaged areas. The impact of structural changes on the alterations in the analysed strength properties along the disc radius was assessed. Material tests were correlated with the analysis of the recorded engine parameters, indicating potential causes of the HPT disc fragmentation. [ABSTRACT FROM AUTHOR]