Engine Test Research Articles

A novel method of computation for anchorage length based on the propagation characteristics of anchor excitation stress wave

ABSTRACT Detecting the anchoring length is an integral part of the quality inspection of the bolt anchoring, which is crucial to the safety of the roadway support. This paper studies the influence of the anchoring length on the propagation characteristics of the exciting stress wave of the bolt. The research finds that the change in the anchoring length affects the attenuation rate and frequency distribution of the stress wave signal amplitude. Under the same test conditions, the anchoring length negatively correlates with the consolidation wave velocity. The VMD analysis and processing method decomposes the original detection signal once or the characteristic mode function twice. The bottom reflection time is obtained from the bottom reflection signal identified according to the decomposed mode function. Based on the propagation characteristics of the exciting stress wave in the anchor rod, a method of calculating the anchoring length using the bottom reflection time is proposed. Experimental verification of anchoring models for different anchoring lengths is carried out. The calculated results are consistent with the actual anchoring length; the longer the length, the smaller the relative error. The error rate meets the accuracy requirements of on-site engineering tests and guarantees safe production.

Experimental study on the cerium oxide nanoparticles doped in diesel fuel improving the cold start performance of diesel engines at high-altitude and low-temperature environments

CeO2 nanoparticles are effective fuel additives that enhance fuel spray, atomization, and combustion characteristics due to their high catalytic activity and excellent thermal properties. When added to fuel, CeO2 nanoparticles significantly improve in-cylinder combustion, and engine performance, and reduce pollutant emissions under normal engine operating conditions. Diesel engines encounter persistent challenges during cold starts at low temperatures and high altitudes. However, there is limited research on the effects of CeO2 nanoparticles on ignition and combustion at low temperatures and cold start performance. This study aims to evaluate the impact of CeO2 nanoparticles doping in diesel fuel on the cold start performance of diesel engines in high-altitude and low-temperature environments. Diesel fuel doped with CeO2 nanoparticles at various concentrations was prepared using magnetic stirring and ultrasonication. The cold start performance of the test engine was assessed in an environmental chamber. This work investigated and evaluated the improvements of CeO2 nanoparticles on cold start performance from three perspectives: general low-temperature conditions, high-altitude environments, and extreme low-temperature scenarios with diethyl ether premixing. Experimental results indicate that incorporating CeO2 nanoparticles expanded the critical temperature required for a successful cold start from 0 °C to −5 °C. At high altitudes, the addition of CeO2 nanoparticles effectively increased the proportion of efficient combustion, evidenced by single peak and parent peak patterns during cold starts. CeO2 nanoparticles facilitated the transition from low-temperature to high-temperature reactions, promoting fuel ignition during the first injection cycle and reducing speed fluctuations during cold starts with diethyl ether premixing at −40 °C. Furthermore, adding CeO2 nanoparticles prevented detonation and rapid pressure surges during cold starts. Overall, doping diesel fuel with CeO2 nanoparticles proves to be an effective method for enhancing cold start performance in diesel engines. This study offers a novel approach for improving diesel engine cold start performance in high-altitude and low-temperature conditions.

Evaluation of localized mechanical properties of modified N50 welded joints at cryogenic temperature through a digital image correlation technique

The modified N50 austenitic stainless steel has been determined to be applied as the superconducting magnet supporting material of the Chinese Fusion Engineering Test Reactor (CFETR), especially the jacket material of the CICCs of both the TF coils and the CS coils and the case material of the TF coils, which inevitably requires welding connection. The welding process generally results in welding defects as well as degradation of cryogenic mechanical properties of metallurgical inhomogeneous zones. However, limited research has been reported to demonstrate the distinct localized performance of these zones at cryogenic temperature. The present paper presents an approach to characterize localized mechanical properties of the modified N50 welds at both room temperature (300 K) and cryogenic temperature (6 K). We identified the welding zone (WZ) through metallographic analysis and then the boundaries of the heat-affected zone (HAZ) were recognized by hardness measurements at room temperature. Finally, the localized optical digital image correlation (DIC) technique was used to obtain the localized yield strength Rp0.2 and percentage extension e of the WZ, the HAZ, and the base metal (BM) at both room and cryogenic temperature, of which the observed trend is verified through comparison with that of hardness measurements at room temperature. The technique proposed provides the localized measurement of cryogenic tensile properties of weld metals and also presents experimental data on different zones of the modified N50 welded joints as a jacket material for the next-generation fusion reactors.

Performance of anhydrous ethanol and gasoline blends on a SI engine: Decoupling evaporation enthalpy and knock resistance

Blending bioethanol with gasoline is recognized as a rapid solution for mitigating nonrenewable carbon dioxide emissions. This approach proves particularly meaningful in markets where the production of this biofuel aligns with sustainable practices. Understanding the alterations in the combustion process holds significance within these markets, contributing to informed decision-making and fostering environmentally conscious practices. In this context, it is widely known that highly ethanol blended fuels can provide benefits regarding suppression of knocking combustion in spark ignited engines if the quality of the base-fuel is not deteriorated to maintain octane ratings. However, the results of engine knocking investigations can be affected by two effects simultaneously. Firstly, ethanol has a beneficial effect on knock suppression due to its high enthalpy of evaporation compared to gasoline, which results in inner mixture cooling especially with direct injection. Secondly, ethanol can have beneficial effects on knock suppression by its decreased self-ignition tendency. This paper provides the set-up and results of an adapted engine testing procedure to diminish the effects of evaporation enthalpy during the knocking investigations of different highly ethanol blended fuels. The presented testing procedure at a single-cylinder research engine includes three technical steps: (1) the engine is equipped with a port fuel injection in stoichiometric operation for all tested fuels; (2) the engine is operated with constant speed of 1500 rpm and constant spark timing of 33° firing top dead center; (3) the engine is operated with fuel individual settings for the intake manifold gas pressure and intake manifold gas temperature. These parameters are adjusted to test all fuels with similar in-cylinder conditions at spark timing. The differing heating values of the fuels obviously result in differing engine loads. However, the presented testing procedure is aimed to achieve comparable in-cylinder conditions at spark timing without the effect of evaporation enthalpy. The novelty of the study lies in its adapted engine testing procedure that mitigates the cross-effects of fuel properties and operational conditions to isolate the true influences on knock occurrence. The paper provides a comprehensive description of the theoretical backgrounds, experimental set-up and post-processing procedures and also shows the results of the first measurement campaign.

Rapid aerodynamic characterization of surface heat exchangers for turbofan aeroengines through optical techniques and additive manufacturing

Surface heat exchangers that use the bypass flow as heat sink are becoming a widely used solution to alleviate the high thermal load of modern aeroengines. Experimental characterization of such heat exchangers in full-scale engine tests is extremely expensive and time-consuming, so carrying out experiments in scaled wind tunnels that can replicate their very challenging flow conditions is highly desirable. However, intrusive instrumentation can affect the actual aerodynamics of the component due to the reduced size of the section and the typical high air velocities of turbofan engines. For this reason, a methodology to characterize a surface heat exchanger designed to work in the turbofan bypass using optical techniques is presented in this work. Additionally, the possibility of replicating the experimental conditions using additively manufactured models of exchangers would allow rapid preliminary characterization of these components. In this investigation, different non-intrusive techniques such as PIV, LDA, Schlieren, or LDV have been applied to determine the heat exchanger aerodynamic performance and vibration response, and a detailed characterization of the flow field has been carried out. Data have been cross-validated using different measurement techniques. A 3D-printed model has also been built to compare with the aluminum heat exchanger, showing almost an identical behavior in terms of velocity distribution downstream of the heat exchanger and pressure drop induced by its fins, as well as corrected frequencies, confirming thus the suitability of additive manufacturing for the aerodynamic characterization of these devices in preliminary stages.

Effects of industrial hydrogen-rich gases on the performance of the spark ignition engine under various combustion modes

Hydrogen is emerging as a promising alternative to traditional fossil fuels for the transportation. Additionally, the hydrogen-rich gases (HRG) can produce on a large scale during the process of chemical production. In this study, the influences of HRG on the performance behaviors of the spark ignition (SI) engine are comprehensively analyzed under various combustion modes and operating conditions. The experimental results indicate that with increasing the lambda, the torque of the test engine can maintain the target value under equivalent ratio and lean combustion modes, while it sharply decreases under ultra-lean combustion. When the value of the lambda is 1.5, the brake thermal efficiency (BTE) and brake specific hydrogen consumption (BSHC) of the HRG SI engine respectively reach up to 33.6% and 89.1 g/kW.h, yielding superior fuel economy. The NOx emissions of the HRG SI engine firstly increase and then decrease with increasing lambda, reaching the peak value at the lambda of 1.1. In addition, the NOx, CO, and HC emissions of the HRG SI engine greatly reduce when the lambda is approximately 1.5. Consequently, using HRG partially substitute the traditional fossil gasoline in the SI engine can benefit to achieve energy conservation and emissions reduction in transportation section.

A Study on the Effects of Preheating Thevetia Peruviana Biodiesel on the Performance of CI Engine

Biodiesel is becoming increasingly popular as a substitute fuel for compression ignition (CI) engines because of its comparable characteristics to those of diesel and its little environmental impact. The development of diesel engines that run on biodiesel and reduce emissions of pollutants, while also improving thermal efficiency, are key concerns in engine design. The most crucial prerequisites for achieving these are precise and quick air-fuel mixing. However, biodiesel's viscosity is considered a drawback for its application as a substitute fuel for IC engines. Heating can greatly lower the viscosity, which can eliminate the problems caused by excessive viscosity during injection. Hence in this effort, preheated Thevetia Peruviana biodiesel (Methyl Ester) is utilized. The present research aims to examine how preheating biodiesel affects the operation of a direct injection (DI) diesel engine. Engine tests were done on a stationary, single-cylinder, constant speed, naturally aspirated, water-cooled CI engine with a preheated 20% blend of Thevetia Peruviana biodiesel (PH-TPME20 with a conventional jerk type injection system. Engine performance of preheated TPME20 was compared with the unheated 20% blend of TPME and diesel. Preheating reduced the viscosity of the oil, which resulted in a noticeable improvement in engine performance. A considerable drop in emission levels from the engine exhaust gas was noted. The preheating improved combustion characteristics i.e. it lowered the delay period and resulted in quicker release of heat because of improved fuel-air mixing, fuel vaporization, and atomization.

Benchmark Analysis of a Prismatic Type-high Temperature Gas-cooled Reactor with the ENDF/B-VII.0, ENDF/B-VII.1 and ENDF/B-VIII.0 Nuclear Data Libraries

In this work we performed a benchmark analysis of the High Temperature Engineering Test Reactor (HTTR) fully-loaded start-up critical core with a 30-bundle loading configuration using the Monte Carlo code Serpent 2 with the recently released nuclear data libraries ENDF/B-VII.0, ENDF/B-VII.1 and ENDF/B-VIII.0. The purpose of the work is to reveal the impacts of using different ENDF nuclear data libraries on neutronics calculations of a prismatic high temperature gas-cooled reactor (HTGR). The benchmark results obtained with Serpent 2 were compared against the available experimental values and those attained by different computer codes (MCNP5 and SCALE) using the nuclear data library ENDF/B-VII.0. The comparative results showed good agreement between Serpent 2, the experimental values, MCNP5 and SCALE. The results also exhibited a notable difference between using ENDF/B-VII.0, ENDF/B-VII.1 and ENDF/B-VIII.0 in predicting the neutronics parameters of the HTTR that suggests further investigation in future work.

Material Design and Performance Study of a Porous Sound-Absorbing Sound Barrier

A new type of porous sound-absorbing sound barrier was developed with quartz sand and self-developed polysiloxane resin. The forming process of the material was studied. The test specimens of the porous sound-absorbing sound barrier were prepared with different mesh numbers of quartz sand and different proportions of resin, and the void properties, compressive strength, durability, and acoustic performance were investigated. Based on the mix design results, it is suggested that 20-mesh quartz sand and a 10:1 mass ratio of quartz sand are used to prepare the porous sound-absorbing sound barrier. The durability study showed that the porous sound-absorbing sound-barrier material had good salt and alkali resistance, poor acid resistance, good water stability, and freeze–thaw stability. The laboratory acoustic test and practical engineering application results showed that the porous sound-absorbing sound barrier had excellent acoustic performance and good noise-reduction effects.

Thermodynamic investigation and 4Es analysis of a VCR diesel engine using emulsified diesel with catalytic co-pyrolysis fuel derived from waste LDPE and Pongamia pinnata seeds

Global challenges for massive plastic waste disposal and regular decrement of conventional resources, converting plastic and biomass seeds waste into transportation-grade fuels through co-pyrolysis offer a better option for providing a promising solution. This investigation signifies a thermodynamic power cycle model, and 4Es (Energy, Exergy, Environmental, Economic) analysis of a direct injection unmodified diesel engine powered with various blends of test fuels derived from thermo-catalytic co-pyrolysis of low-density polyethylene (LDPE) wastes and Pongamia pinnata seeds at 500 °C with calcium oxide as catalyst, mixed with diesel. The fuel mixtures of pure diesel and pyrolytic test fuels are utilized for diesel engine testing with varying compression ratio. The synergistic effects of major parameters such as full engine load, varying compression ratios (16:1, 17:1, 18:1, and 19:1), and fuel blends (10, 20, 30, and 40 %) are considered for engine run. The Brake thermal energy was found to increase for the 20 % blend at 6.6 % (40 % load) in comparison to pure diesel. Also, the Brake specific fuel consumption was the least for the same blend, 0.31 kg/kWh at 18:1 CR. The smoke was also found to have lowered by 22 % for the 20 % blend in comparison to pure diesel. At a compression ratio of 18:1, the NOx formation also decreased by approximately 1.4 % in comparison to the pure diesel for almost all considered fuel blends. The fuel efficiency was observed to increase for the 20 % blend compared to pure diesel by 20 %. The cost and exergy destruction analysis also confirmed the D80PB20 to have the least and maximum values respectively for both parameters. The energy, exergy, emission, and economic (4Es) analysis confirmed the suitability of blended fuels for achieving improved engine performance and emissions. In addition, the economic and fuel sustainability analysis foster the techno-economic feasibility of the test fuels as compared to conventional diesel fuel.

A denoising algorithm based on ARIMA and competitive K-SVD for the diagnosis of rolling bearing faults

Rolling bearings are extensively employed in industrial production as essential support components for rotating machinery. However, under conditions of high load and harsh operation, bearings are highly susceptible to failure. The weak vibration signals associated with these failures may be obscured by complex harmonic interference and strong noise, posing challenges for the accurate diagnosis of rolling bearing failures. In this paper, an autoregressive integrated moving average and competitive K-singular value decomposition (ARIMA-CK-SVD) algorithm is proposed to realize effective extraction of faulty pulse signals in a strong interference environment. First, the ARIMA model is used to preprocess the original signal to eliminate the interference of harmonic components. Second, a method is proposed for the adaptive selection of parameters in the ARIMA model, with consideration given to the characteristics of K-SVD. Subsequently, a competitive mechanism is introduced during the dictionary update phase of the algorithm to adjust the pattern of atomic updates and eliminate noise atoms. Finally, the effectiveness of the ARIMA-CK-SVD has been validated through simulation experiments and engineering tests.

Sparse regularized graph pooling network optimal sensor placement method for diesel engine vibration fault perception system

Vibration sensor network optimization increases monitoring effectiveness and reduces sensor quantity and transmission burden. However, the traditional model-driven methods depend on precise finite element models, challenging for complex machinery. This paper presents a data-driven approach using the Sparse Regularized Graph Pooling Network (SRGPN), which conceptualizes sensor networks as graphs and uses graph pooling to identify optimal sensor combinations. A sparsity regularization term related to the number of sensors is included in the loss function, aiming for the minimal yet effective sensor combination. Additionally, a monitoring capability metric suited for diesel engines with multi-source impulse signals is proposed, reflecting the sensors’ monitoring capacity. Validated through simulations and tests on a diesel engine test bench, the results show that SRGPN optimally places sensors near excitation sources, balancing sensor count and monitoring needs. This approach shows potential for optimizing sensor placements in condition monitoring.

Surrogate model-based cognitive digital twin for smart remote maintenance of fusion reactor: modeling and implementation

Abstract A remote maintenance robot system (RMRS) plays a critical role in safeguarding the fusion energy experimental device’s security and stability. State-of-the-art intelligent technology such as cognitive digital twins (CDT) is widely considered capable of improving complex equipment’s performance and reducing management burden using a visualized system. However, the CDT virtual space cannot mirror the RMRS which is a kind of flexible multi-body system in real-time and with high fidelity. Therefore, we propose a cognitive digital twin (CDT) modeling method based on a surrogate model for the RMRS. Firstly, model-based system engineering (MBSE) is leveraged to build a structural modular architecture, which can decrease the modeling complexity of CDT and increase the modeling efficiency. Then, the surrogate models are self-learning within the CDT physical space, which reconstructs the RMRS’s real-time dynamic performances and endows CDT with cognitive capabilities. Finally, after integrating the CDT system, a smart decision-making plan that compensates for the operation error is generated for RMRS’s accurate control. We take a China Fusion Engineering Test Reactor (CFETR) multi-purpose overload robot (CMOR) as an example to demonstrate the implementation process. According to the results, CDT can achieve real-time (230 ms time delay) high-fidelity (5 mm control error) monitoring and accurate control, and CMOR conducts smart maintenance based on the simulation results. This method improves the efficiency of RM and provides solutions for high-duty cycle time of CFETR, it can also be applied to other tokamak fusion energy devices.

Multi-objective Optimization of Diesel Engine Operating Parameters Under Highway Drive Conditions

Abstract Experimental and optimization work is carried out to study the effects of fuel injection pressure, boost pressure, pilot injection timing, pilot injection quantity and main injection timing as input parameters. A four-cylinder, automotive model direct injection diesel engine, incorporated with a variable-geometry turbocharger, was chosen for the experiment. Engine test runs are conducted at a driving condition of 80.3 Nm torque and an engine speed of 1750 rpm, respectively, corresponding to highway driving conditions, using 10 % of exhaust gases recirculated. The Response Surface Methodology is employed to design experiments and analyze the experimental data to optimize engine parameters, considering the mentioned parameters as input parameters. A multi-objective response approach is adopted to optimize engine-operating parameters to obtain desired performance and engine-out emissions. Confirmatory tests are conducted at design conditions to validate the results predicted by the model. It is observed that for the chosen engine configuration, the optimum performance and emission characteristics could be obtained with 120 kPa boost pressure, 61.1 MPa fuel injection pressure, and 11.5 % of total fuel amount as pilot injection and remaining as main injection quantity at 332° and 359° crank angle, respectively. Overall. fairly better engine performance was observed with the use of selected ranges. It is noted that with the procedures adopted, improved engine performance and a significant reduction in harmful emissions are obtained without using major add-ons. The investigation revealed excellent potential for a diesel engine to be an effective prime mover.

Effects of dual-spark ignition system with two different piston bowl shapes on combustion and efficiency in a single-cylinder engine

In this study, a dual-spark ignition system was systemically evaluated in a single-cylinder engine. Since the test engine was originally based on the diesel engine, two sparks were located symmetrically on the left and right, with the diesel injector in the middle of the engine head. At first, the effect of dual-spark ignition on the combustion process was compared with the single-spark (only right used) condition under 1600 rpm/gIMEP 0.7 MPa. Also, varying excessive air ratios were evaluated for the two conditions. The second experiment changed the piston bowl shape from (a Mexican) hat to a flat (bathtub-shaped) for the dual-spark ignition system under five representative operating conditions. Also, the maximum load was verified under a knocking frequency of 30%. The results emphasized that dual-spark ignition showed superb CoV of net indicated mean effective pressure (nIMEP) as 2.71% under excessive air ratio 1.55 condition, while it was higher than 5% with single-spark ignition. In addition, the net indicated thermal efficiency was 37.33%. Also, when flat bowl-shaped piston was used with dual-spark ignition system, the maximum load with avoidance of severe knocking could be increased from nIMEP 1.07 to 1.44 MPa due to enhancing flame propagation speed.

Processing the Narrative: Innovative Graph Models and Queries for Textual Content Knowledge Extraction

The internet contains vast amounts of text-based information across various domains, such as commercial documents, medical records, scientific research, engineering tests, and events affecting urban and natural environments. Extracting knowledge from these texts requires a deep understanding of natural language nuances and accurately representing content while preserving essential information. This process enables effective knowledge extraction, inference, and discovery. This paper proposes a critical study of state-of-the-art contributions exploring the complexities and emerging trends in representing, querying, and analysing content extracted from textual data. This study’s hypothesis states that graph-based representations can be particularly effective when annotated with sophisticated querying and analytics techniques. This hypothesis is discussed through the lenses of contributions in linguistics, natural language processing, graph theory, databases, and artificial intelligence.

The K2 and TESS Synergy. III. Search and Rescue of the Lost Ephemeris for K2's First Planet

K2-2 b/HIP 116454 b, the first exoplanet discovery by K2 during its Two-Wheeled Concept Engineering Test, is a sub-Neptune (2.5 ± 0.1 R ⊕, 9.7 ± 1.2 M ⊕) orbiting a relatively bright (K S = 8.03) K-dwarf star on a 9.1 day period. Unfortunately, due to a spurious follow-up transit detection and ephemeris degradation, the transit ephemeris for this planet was lost. In this work, we recover and refine the transit ephemeris for K2-2 b, showing a ∼40σ discrepancy from the discovery results. To accurately measure the transit ephemeris and update the parameters of the system, we jointly fit space-based photometric observations from NASA’s K2, Transiting Exoplanet Survey Satellite, and Spitzer missions with new photometric observations from the ground, as well as radial velocities from HARPS-N that are corrected for stellar activity using a new modeling technique. Ephemerides becoming lost or significantly degraded, as is the case for most transiting planets, highlights the importance of systematically updating transit ephemerides with upcoming large efforts expected to characterize hundreds of exoplanet atmospheres. K2-2 b sits at the high-mass peak of the known radius valley for sub-Neptunes, and is now well-suited for transmission spectroscopy with current and future facilities. Our updated transit ephemeris will ensure no more than a 13 minute uncertainty through 2030.

Studies on fuels and engine attributes powered by bio-diesel and bio-oil derived from stone apple seed (Aegle marmelos) for bioenergy

Biofuel is an alternative fuel for diesel engines which is necessary to reduce exhaust emissions and helps to balance the depletion of fossil fuels. This study details the synthesis of bio-diesel and bio-oil from stone apple seeds ( Aegle marmelos) through transesterification, direct oxygenate additive, and pyrolysis processes. The diesel engine is powered by the resulting stone apple methyl ester bio-diesel/diesel and bio-oil/diesel mixtures. In a test engine rig, the effectiveness and emission uniqueness of test fuel mixes were examined at various engine loads (EL = 3 kg–12 kg) and compression ratios (CR = 16–17.5) while maintaining a steady speed of 1500 r/min. Furthermore, engine performance and emissions for bio-diesel and bio-oil are measured and compared. The oxides of nitrogen (NOx) emission by bio-diesel and bio-oil opus were higher than neat diesel (FD). Also, carbon monoxide (CO) and hydrocarbon (HC) emissions were measured to be lower. The improvements of BTE by 4.87% and decrement of CO by 18.8%, HC by 13.26% were observed with the trans-esterified bio-diesel/diesel opus compared to diesel at a higher CR and rated load conditions. The engine analysis responses revealed that the FBD blend showed enhanced performance and lower emissions except NOx compared to diesel fuel. Hence, trans-esterified bio-diesel is a greater diesel alternative than FBDE and FBO.

Thermal performance of counterflow wet cooling tower filled with inclined folding wave packing: An experimental and numerical investigation

Improve the heat transfer performance of cooling tower packing in the field of energy saving and environmental protection is of great significance, this study proposes a kind of inclined folding wave packing, using experimental research and numerical calculations combined method to study the heat and mass transfer characteristics of inclined folding wave packing, the results show that: inlet wind speed rises, the cooling tower approximation reduced from 4.38 °C to 2.78 °C; when the gas to water mass ratio increases from 0.322 to 1.019, the cooling number from 1.115 to 1.754; when the gas to water mass ratio of 0.54, the height of the packing from 0.915 m to 1.830 m, the cooling number from 1.15 to 1.64, the height of the packing to enhance the channel of the gas-liquid heat transfer effect. Compared with the traditional ramp packing, the cooling efficiency of the developed inclined folded wave packing is improved by 15.32 %. Combined with the actual engineering test found that the packing height can be increased to reduce gas to water mass ratio and air volume requirements, up to 28 % of the air volume can be saved. The motor output power of 1.830 m high inclined folding wave packing in actual operation is 0.268 kW, compared with 0.915 m high inclined folding wave packing, the difference in energy consumption is 0.246 kW. Inclined folding wave packing can not only improve the overall performance of the cooling tower, but also significantly reduce energy consumption, which can guide the engineering practice.

Heavy fuel preparation effects on the operation of a spark ignition unmanned aerial vehicle engine

PurposeThis paper aims to conduct an experimental and theoretical investigation into fuel pre-delivery effects for a heavy fuel crankcase scavenged spark ignition two-stroke cycle engine for unmanned aerial vehicle application.Design/methodology/approachOne-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline and fuels.FindingsThe experimental research has shown performance improvements using fuel preheating via use of auxiliary transfer port fuel injection. Computational simulation has allowed comparisons with auxiliary transfer port injection and direct in-cylinder injection to be made.Practical implicationsWhile some heavy fuel engines are now available for unmanned aerial vehicles the best solution to meet the military equipment single fuel policy remains an area of evolving research. The findings within this study show possibilities for fuel pre-treatment.Originality/valueOne-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline fuels.