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Congenital pyriform sinus fistula (CPSF) is a very rare branchial apparatus malformation. Traditional open surgery for fistulectomy might fail to excise the lesion completely, leading to continual recurrence. Herein, we report our experience of endoscopic coblation technique for treatment of CPSF in children. To observe the clinical efficacy of endoscopic coblation treatment of CPSF in children, especially for those in acute infection stage. Retrospective case series with 54 patients (including 20 cases in acute infection stage and 34 cases in non infection stage) who were diagnosed with CPSF between October 2017 to November 2019, all patients were treated with endoscopic coblation to close the piriform fossa fistula, neck abscess incision and drainage performed simultaneously for acute infection stage cases. Data collected including age of diagnosis, presenting symptoms, diagnostic methods, prior and subsequent treatments, length of hospitalization, and recurrence were analyzed. Of the 20 cases in acute infection stage, there were 3 children with transient vocal cord paresis all of which resolved with 1 month. Four children of the 34 cases in non infection stage appeared reddish swelling of the neck on the 4th, 5th, 6th, and 7th days after coblation and then underwent abscess incision and drainage. All cases experienced no recurrence, vocal cord paralysis, pharyngeal fistula and massive hemorrhage after their first endoscopic coblation of the sinus tract in the follow up of 3 to 28 months. Endoscopic coblation is an effective and safe approach for children with CPSF, neck abscess incision and drainage could be performed simultaneously in acute infection stage. We advocate using this minimally invasive technique as first line of treatment for CPSF.

Partially-premixed compression-ignition (PPCI) is an advanced combustion mode that simultaneously reduces particulate and NOx emissions. Fuels with properties intermediate to that of gasoline and diesel are preferred for PPCI. This paper is a follow-on to a recent work published in Fuel from the authors’ research group on the topic of PPCI combustion with ULG75 (75 vol% gasoline/25 vol% diesel). That paper reported the opportunity of using ULG75 and hot external exhaust-gas-recirculation (EGR) for solving the low-load combustion-stability issue caused by the low reactivity of ULG75. That paper also concluded that ‘It was not possible to obtain stable ULG75 PPCI combustion without using low fuel injection pressure’. Additionally, from the point of ULG75’s volatility and viscosity, it does not require as high injection pressure as diesel. This paper assesses the spray characteristics (spray morphology, penetration length, cone angle and droplet size) of ULG75 at low injection pressures (Pinj = 35/75 MPa). In this work, high-speed macroscopic imaging (0.25 million fps) was carried out at backpressure (BP) of 0.1/4.0 MPa, and ambient temperature (Ta) of 25/125 °C. In addition, ultra-high speed microscopic imaging (1 million fps) was carried out at BP = 4 MPa and Ta = 25 °C. The same tests were conducted for diesel, and the results were used for comparisons. Under preheated ambient condition (Ta = 125 °C), ULG75 showed a noticeable improvement in the spray quality as compared to the non-evaporative condition (Ta = 25 °C), indicated by a shorter spray penetration length, larger spray cone angle and spray area. However, no such changes were observed for diesel spray upon increasing Ta from 25 °C to 125 °C. Both Pinj and BP strongly affected the spray penetration length evolution. However, they showed limited impacts on spray cone angle and spray area. In addition to the experimental study, empirical estimations were conducted to predict the spray penetration length, air entrainment and spray droplet size. The calculations predicted smaller SMD for ULG75 than diesel at all conditions and also indicated ambient temperature as a key factor affecting the spray quality, especially at low injection pressures.

In this paper, n-hexane flashing jets discharged from a single-hole gasoline direct injector (GDI) were studied numerically with the adoption of diffuse Eulerian framework and the homogeneous relaxation model (HRM). The fuel temperature ranged from 30 to 130 °C, and the ambient pressure varied from 20 to 101 kPa. The results showed that considerable vaporization started at the counter bore and a liquid core existed near the nozzle exit. Due to drastic vaporization, the pressure within the liquid core increased so the two-phase flow became under-expanded. Violent expansion then occurred and a low-pressure region was formed, which is believed as the origin of the spray collapse under flashing conditions for multi-hole GDI injectors. At high superheat levels, shock wave structures similar to those in highly under-expanded gaseous jets were identified. However, the transonic position located at some distances from the nozzle rather than at the throttle. Besides, vapor fraction played the dominant role in the onset of expansion, while the expansion was ended by the pressure difference between the two sides of the Mach disk.

CrxNiyTi0.05La0.01 (x: y = 1:1, 2:1, 1:2) laser cladded -plasma nitrided composite modified layers were prepared on the surface of N80 steel. The effect of Cr and Ni content on the microstructure, wear resistance and corrosion resistance of the composite modified layer was investigated. The experimental results showed that Cr1Ni1Ti0.05La0.01 and Cr1Ni2Ti0.05La0.01 laser cladded layers are mainly composed of columnar crystals with FCC structure perpendicular to the surface, and Cr2Ni1Ti0.05La0.01 laser cladded layer is composed of equiaxed BCC and FCC crystals. The nitrided layers of the three samples are mainly composed of CrN phase, and the nitrided layer of Cr2Ni1Ti0.05La0.01-cladded sample has the highest content of CrN and the best homogeneity and compactness, but the thickness of its nitrided layer is the smallest and the speed of nitriding is the slowest. Compared with N80 substrate, the hardness of the three cladded layers is improved, which enhances the strength support of the nitrided layer and improves the hardness gradient of cross-section. Among them, the strengthening effect of the Cr2Ni1Ti0.05La0.01-cladded layer is the best. The wear resistance and corrosion resistance of the three composite modified layers are improved compared with the conventional nitrided layer on N80 steel, and the nitrided layer of Cr2Ni1Ti0.05La0.01-cladded sample is the best, and its friction coefficient and wear loss are only about 30% and 35% of the nitrided layer on N80, its corrosion current densities in 3.5% NaCl solution and in 0.5 mol/L H2SO4 solution are reduced about 6 times and 3 orders of magnitude, respectively.

In this paper, the valence electron structure and the bond energy of covalent bonds of α-Fe and e-Fe2N, e-Fe3N and γ′-Fe4N were calculated by means of the empirical electron theory (EET). It was put forward that the valence electron structure parameter related to hardness is the covalent electron density, the valence electron structure parameters related to plasticity are the lattice electron density and the symmetry factor of the atomic bonding strength, the valence electron structure parameters related to corrosion resistance are the atomic total bonding energy and lattice electron density, and the valence electron structure parameter related to stability is the average atomic total bonding energy. The hardening and corrosion resistance mechanism of ion-based nitriding layer was discussed and the influence of three Fe-N compounds on the hardness, brittleness, corrosion resistance and stability were compared and analyzed from the perspective of electron structure. The calculation results show that the three Fe-N compounds, which have larger covalent electron density and average atomic total bonding energy and smaller lattice electron density than α-Fe, can improve the hardness and corrosion resistance of the iron-based surface. Among the three compounds, e-Fe2N has the greatest hardness, corrosion resistance and stability, and the least brittleness. Therefore, during the nitriding process, efforts shall be made to prompt the formation of e-Fe2N as much as possible.

This study was performed to investigate the feasibility of using a three-dimensional (3D) finite element model for laryngomalacia severity assessment. We analyzed laryngeal computed tomography images of seven children with laryngomalacia using Mimics software. The gray threshold of different tissues was distinguishable, and a 3D visualization model and finite element model were constructed. The laryngeal structure parameters were defined. The peak von Mises stress (PVMS) value was obtained through laryngeal mechanical analysis. The PVMS values of the laryngeal soft tissue and cartilage scaffolds were independently correlated with disease severity. After stress loading the model, the relationship between laryngomalacia severity and the PVMS value was apparent. However, the PVMS value of laryngeal soft tissue was not correlated with laryngomalacia severity. This study established the efficacy of a finite element model to illustrate the morphological features of the laryngeal cavity in infants with laryngomalacia. However, further study is required before widespread application of 3D finite element modeling of laryngomalacia. PVMS values of the laryngeal cartilage scaffold might be useful for assessment of laryngomalacia severity. These findings support the notion that structural abnormalities of the laryngeal cartilage may manifest as quantifiable changes in stress variants of the supraglottic larynx.

The work presented in this paper is a progression to previous research which developed an overcurrent-tolerant prediction model. This paper presents some of the modelling and development techniques used for the previous research, but more emphasis is placed on the requirements of the case study; whereby an aeroplane pushback tug is converted into a series Hybrid Electric Vehicle (HEV). An iterative design process enabled the traction motor, transmission, generator and battery pack parameters to be tailored for this vehicle’s unique duty cycle. A MATLAB/Simulink model was developed to simulate the existing internal combustion engine powertrain as well as the series HEV equivalent for comparative analysis and validation purposes. The HEV design was validated by comparing the simulation results to recorded real-world data collected from the existing vehicle (torque, speeds etc.). The HEV simulations provided greater fuel savings and reduced emissions over the daily duty cycle in comparison to the existing vehicle.

This paper reports the design optimization for a dual clutch transmission (DCT) of a multi-mode axle-split hybrid electric vehicle (HEV). The purpose of optimization is to minimize the equivalent fuel consumption of automobile power demand. The variables that need to be optimized are gear ratio and Shifting threshold value. The optimization is based on a co-simulation platform, in which, the HEV is modelled in LSM Amesim and the control/optimization algorithms are programmed in MATLAB/ Simulink. In this study, the Hybrid Particle Swarm Optimization (HPSO) algorithm is used to solve the optimization problem, which has better global and local search capability comparing with conventional PSO algorithm. The simulation results show that the optimized transmission parameters can guarantee the power demand and have a good fuel economy.

Flame kernel evolution and shock wave propagation in ethanol/air mixtures with laser ignition in a constant-volume chamber was investigated by means of high-speed Schlieren photography. At initial pressure of 0.1 MPa and temperature of 333 K, ignition was performed using a pulsed laser at the second harmonic wavelength with six different laser energies from 75 to 200 mJ, for the equivalence ratios ranging from 0.8 to 1.4. A cross-shaped plasma spot is captured ∼3.0 µs after the laser triggering, whereas the shape of the flame kernel is initially circular and then transforms to an ellipsoid structure. Following the contraction of the plasma, the flame kernel growth rate is initially very different in the four directions and then approaches a steady flame speed. The contraction of the plasma zone is accompanied by a rapid shock wave propagation where, the wave propagation speed is found to be negligibly influenced by the variations in either laser energy or mixture equivalence ratio. Under the test conditions in this study for ethanol/air mixtures, the initial shock wave speed is ∼480 m/s which decays to ∼380 m/s after 20 µs. The shock wave front propagates with a time dependency of about t0.6 when t

In order to mitigate spray collapse and fully utilize the advantage of flash boiling injection in gasoline direct injection (GDI) engines, it is important to understand the flashing jet behavior and its relationship with spray collapse. In this study, n-hexane sprays discharged from a modified single-hole injector and the original five-hole injector were studied. The tests were carried out in a constant volume vessel with injection temperatures from 30 to 130 °C and ambient pressures (Pamb) from 20 to 101 kPa. By analyzing the relationship between the jet width and different parameters including superheat level, nucleation rate, and chemical potential of phase change (Δμ), strong correlation was found between the jet width and Δμ·Pamb−0.5, indicating the radial expansion of flashing jets was determined by chemical potential of phase change and ambient resistance. Beyond 20d0, the correlation was gradually weakened along the axis, as flash boiling process was finished. Besides, it was found that the extent of single-jet radial expansion was positively related to that of multi-jet spray collapse in the transitional collapse region. Therefore, to mitigate spray collapse, it is necessary to restrict the radial jet expansion, and generating external flashing jets is proposed as a practical approach to realize it.

Background: Microsatellite Instability (MSI) is a prognostic and predictive biomarker which can guide treatments including immunotherapy for patients with gastrointestinal cancer. Universal MSI testing would benefit to patients to receive a better therapy, but many patients remain untested. To deliver broadly accessible MSI testing, deep learning models have demonstrated their feasibility for MSI prediction using H&E-stained whole-slide images (WSIs). However, to be deployed into clinical routine care, prediction models should be validated in datasets from multicenter and multiethnic groups. In addition, these models should provide uncertainty of prediction to help clinicians to make informed decisions. Method: We develop a MSI prediction model using WSIs based on Deep Gaussian process (DGP), a Bayesian model being able to model the uncertainty in prediction. We implement a DGP model in the transfer learning, where a WPI is decomposed into multiple non-overlap image patches which are converted to feature vectors by a pretrained convolutional neural network (CNN). Then, the DGP model makes a prediction for an image by averaging score function values at all the feature vectors in the image in weakly supervised learning (WSL). To test our method, we collected H&E stained colorectal/stomach cancer slides (n=1,619) from multi-institutions and multiethnic groups, including TCGA Colorectal (CRC; n=351) and Stomach Adenocarcinoma (STAD; n=174) and six datasets from tertiary hospitals in Korea (i.e., Yonsei-1 (n=174), Yonsei-1-remade (n=146), Yonsei-2 (n=95), St. Mary-1 (n=48), St. Mary-2 (n=50), and Yonsei-CLASSIC trial (n=581)). We also compare our method to multiple deep learning methods, including Densenet, Resnet, Shufflenet, Googlenet, Squeezenet and two WSL models, MIL (Campanell et al., 2019) and CLAM (Lu et al., 2021). Result: In each cancer type, we train each model using TCGA dataset as discovery cohort and tested on the rest of datasets as validation cohort. We use the area under of roc curve (AUC) for the evaluation metric. For the CRC cohorts, our DGP method achieves overall best performance with 0.81 (Yonsei-1), 0.82 (Yonsei-1-remade), 0.89 (Yonsei-2), 0.85 (St. Mary-1) 0.75 (St. Mary-2) AUCs compared to the state-of-the art methods. For the STAD cohorts, our method also achieves overall best performance with 0.74 AUC (Yonsei-classic). In addition, incorporating the uncertainty in prediction measured by our method improves the model’s performance to predict MSI. Specifically, removing cases with prediction results with high uncertainty, which could lead false positive prediction, significantly improves MSI prediction performance. Taken together, these results demonstrate the robustness and generalisability of the DGP model for MSI prediction across multicenter and multiethnic datasets. Citation Format: Sunho Park, Hongming Xu, Sung Hak Lee, Jeonghyun Kang, Tae Hyun Hwang. Deep Gaussian process with uncertainty estimation Improves microsatellite instability prediction based on whole slide image: A retrospective multicenter and multiethnic cohort study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5012.

Histological distribution and density of tumor infiltrating lymphocytes (TILs) are known to be informative to cancer patients’ outcome. However, due to the heterogeneity and huge size of digitized pathology slides, it has been a challenging problem to quantify TILs-related features in whole slide images (WSI). This study aimed to explore the impact of spatial distribution of TILs quantified by deep learning (DL) approaches based on digitalized WSI stained with hematoxylin and eosin in patients with colorectal cancer (CRC). The cancer and TILs regions are first separately identified by deep learning models in the WSI. The TILs densities at tumor invasive margins are then quantified by image analysis algorithms and used for prognosis of progression-free survival (PFS) in CRC patients. The prognostic impact of spatial distributions of TILs in CRC patients was explored in the Yonsei cohort (n=180) and validated in the TCGA cohort (n=268). Two experienced pathologists manually measured TILs at the most invasive margin as 0-3 by the Klintrup-Mäkinen (KM) grading method and compared to DL approaches. On multivariate analysis, TILs densities within 200µm of the invasive margin (f_im200) was remained as the most significant prognostic factor for PFS (HR 0.004 [95% CI, 0.0001-0.1502], p=.002) in the Yonsei cohort. On multivariate analysis using the TCGA dataset, f_im200 retained prognostic significance for PFS (HR 0.031, [95% CI 0.001-0.645], p=.024). Inter-observer agreement of manual KM grading was insignificant in both cohorts. The survival analysis by pathologists’ manual KM grading showed statistically significant different PFS from the TCGA cohort, but not the Yonsei cohort. In summary, automated quantification of TILs at the invasive margin showed a prognostic utility to predict PFS, and could provide reproducible TILs density measurement in CRC patients. Citation Format: Hongming Xu, Yoon Jin Cha, Jean Clemenceau, Jinhwan Choi, Sung Hak Lee, Jeonghyun Kang, Tae Hyun Hwang. Spatial analysis of tumor infiltrating lymphocytes in histological images using deep learning predicts progression-free survival in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 642.

Background: The tumor microenvironment is a biological environment comprising of heterogeneous cellular components, such as tumor, immune, and stromal cells. Stromal cells in the tumor microenvironment have been shown that they play an important role in cancer development, but how they are linked to patient prognosis, chemotherapy response, and immunotherapy resistance is not fully investigated yet. The present study sought to investigate the stroma composition in the tumor microenvironment by using spatial analysis and deep learning. Method: We analyzed stroma composition in Whole Slide Images (WSIs) of hematoxylin and eosin-stained formalin-fixed paraffin-embedded (FFPE) sections from 4 patient cohorts: St. Mary (37 patients), Yonsei-1 (622 patients), Yonsei-2 (66 patients), and TCGA-STAD (359 patients). St. Mary was collected from St. Mary Hospital, Seoul, Republic of Korea. Yonsei-1 and Yonsei-2 were collected from Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea. Each WSI was tessellated into 256x256 um at 40X magnification and normalized using Macenko and Reinhard normalization methods to reduce the color variability of the stained tissue images. Two deep learning models (ResNet and U-Net) were used to create prediction models using Kather’s tumor dataset and a crowdsourcing stroma dataset. Models were trained over 100 epochs, using the Adam optimizer, 1e-4 learning rate, a binary loss function, and L2 regularization. Trained models were used to predict WSIs including tumor, stroma, tumor-infiltrating lymphocytes (TILs), Microsatellite instability. Spatial analysis was conducted by using Getis-Ord-Gi*, a local statistic that identifies a statistically significant hot-spot region by providing relatedness with its neighbors. Tumor hot-spot regions were computed based on z-scores in the predicted WSIs and used for understanding the spatial variation of cancer cells, recognizing statistically significant regions and their spatial relatedness. Results: In Yonsei-1, stroma composition was significantly higher in the chemotherapy high-risk group (p-value 2.9e-09). The proportion of stroma composition is significantly different with the risk groups (p-value 0.074). In TCGA-STAD, the proportion of stroma composition is significantly different with ACTA2 and Microsatellite instability (p-value 0.028). In St. Mary, Yonsei-1, and Yonsei-2, stroma composition was significantly higher in the immunotherapy treatment non-response group (p-value 0.001). Conclusion:These findings suggest that stroma composition in the tumor microenvironment is strongly associated with patient prognosis, chemotherapy response, and immunotherapy resistance on stomach cancer. Citation Format: Sanghoon Lee, Isaiah Pressman, Hongming Xu, Tae Hyun Hwang. Spatial image analysis on stroma composition linking to patient prognosis, chemotherapy response, and immunotherapy resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5044.

This paper is to investigate the characteristics of trans-critical propane spray compared with the flash boiling spray ejected from a multi-hole injector in a constant volume chamber by using the Schlieren and backlit imaging methods. The fuel temperature ( T f ) is set from 30 °C to 120 °C, injection pressure ( p f ) from 60 bar to 120 bar and ambient pressure ( p a ) from 0.2 bar to 10 bar. The results show that the trans-critical spray has longer vapor penetration and shorter liquid penetration than the flash boiling spray, but those two sprays have similar curve liquid boundaries near the nozzle. Several discernable collapsed shock structures near the nozzle are observed at T f = 120 °C, p f =120 bar, p a = 1 bar, but they disappear when p f drops to 60 bar for the transition path may not enter the two-phase region, and the liquid phase hardly occurs. The Mach disk distance of trans-critical spray in this study is larger than that of the under-expanded ideal gas jet because of the collapse phenomenon. At T f = 120 °C, p f = 120 bar, the liquid length decreases when p a increases from 0.2 bar to 2.5 bar and increases when p a continues to rise.

Understanding spray behaviors is key for the successful employment of high injection pressure systems and biofuels such as 2-methylfuran (MF) and ethanol (ETH) in modern direct-injection gasoline engines. In this present work, the MF spray characteristics in the near-field (up to 1.6 mm) and far-field (up to 48 mm) were experimentally investigated under ultra-high injection pressure of 30, 40 and 50 MPa compared to those of ETH and isooctane (ISO). The effects of injection pressure and fuel properties on the spray morphology, tip penetration and cone angle development have been analyzed. The results showed that MF had a unique spray tip structure with a bubble attached to a mushroom tip at 30 and 40 MPa. The formation of this mushroom tip and bubble was closely related and strongly influenced by the Weber number. Among the three fuels tested, MF presented the lowest spray tip velocity at both near-field and far-field due to its large density. Compared to ETH, MF and ISO always had wider macro cone angles due to their lower viscosity.

This study presents a new hybrid and electric vehicle (HEV/EV) traction motor sizing strategy, an overcurrent-tolerant prediction model is used to estimate the dynamic and thermal characteristics of a motor operating in the overcurrent region. This can be used to determine if a prospective traction motor and powertrain configuration is able to fulfil the HEV/EVs target dynamic objectives. Since the prediction model only requires minimal motor torque-speed characteristics, it can be a useful tool during the early development stages of an HEV/EV when the detailed motor parameters used in analytical models cannot be obtained. Allowing the motor to operate in the overcurrent region could downsize the traction motor used in the final HEV/EV design to one that is smaller, easier to package and likely to run in a higher efficiency region. A case study is explored where this sizing strategy is used to convert an aeroplane pushback vehicle into a series HEV and tasked with following a rigorous duty cycle. The feasibility of two HEV configurations is then analysed further. The final HEV design reduces the fuel consumption and engine emissions by up to 52% from the original internal combustion engine powered vehicle.

This study researches an improved scheme of membership function optimisation (MFO) for fuzzy air–fuel ratio (AFR) control of gasoline direct injection (GDI) engines based on correspondence analysis (CA). This proportional–integral-like fuzzy knowledge-based controller (FKBC) optimised by the proposed scheme can further optimise AFR control performance while maximising conversion efficiency of the three-way catalyst to eliminate the exhaust emissions in real time. Different from the conventional experience-based membership function (MF) design method for an FKBC, the proposed MFO scheme uses CA approach and can visualise the relationship between engine step gain scenarios and designed MF patterns to precisely determine its scalar parameters for AFR regulation of GDI engines. Within this context: (i) specialised MFs for self-adaptive AFR control system of a GDI engine are designed with weight distribution; (ii) based on designed scalar parameters, the CA model with taxonomic dimensions is built for acquiring a customised MF to counter transient scenario changes more effectively; (iii) the engine controller with the proposed scheme is real time validated in a production V6 GDI engine, and its advantage in terms of engine transient control performance is further demonstrated by comparing with a benchmark controller designed based on experience.

This paper proposes a new concept of PI-like fuzzy knowledge–based controller with self-tuning capability, high robustness and rapid development capability to regulate air/fuel ratio for gasoline d...

For modern engines, the number of adjustable variables is increasing considerably. With an increase in the number of degrees of freedom and the consequent increase in the complexity of the calibration process, traditional design of experiments–based engine calibration methods are reaching their limits. As a result, an automated engine calibration approach is desired. In this paper, a model-based computational intelligence multi-objective optimization approach for gasoline direct injection engine calibration is developed, which can optimize the engine’s indicated specific fuel consumption, indicated specific particulate matter by mass, and indicated specific particulate matter by number simultaneously, by intelligently adjusting the engine actuators’ settings through Strength Pareto Evolutionary Algorithm 2. A mean-value model of gasoline direct injection engine is developed in the author’s earlier work and used to predict the performance of indicated specific fuel consumption, indicated specific particulate matter by mass, and indicated specific particulate matter by number with given value of intake valves opening timing, exhaust valves closing timing, spark timing, injection timing, and rail pressure. Then a co-simulation platform is established for the introduced intelligence engine calibration approach in the given engine operating condition. The co-simulation study and experimental validation results suggest that the developed intelligence calibration approach can find the optimal gasoline direct injection engine actuators’ settings with acceptable accuracy in much less time, compared to the traditional approach.

In this research, n-hexane jets discharged from a single-hole gasoline direct injector (GDI) were studied in a constant volume vessel. The injection temperature ranged from 20 °C to 100 °C, and the ambient pressure varied from 4 kPa to 101 kPa. The jets were in the external flashing regime over all the superheated conditions with the maximum Rp of 60.23. At the ambient pressures lower than 10 kPa, a liquid core can be observed inside the sprays, surrounded by the mist composed of fine droplets. With the increase in the injection temperature, the length of the liquid core decreased and the mist area became wider. By correlating the nucleation rate with the spray width, it was found that the intensity of bubble blast was positively related to the nucleation rate when the nucleation rates were relatively low. However, as the nucleation rate reached a critical point, the thermal energy for vaporization became the rate-controlling factor. Furthermore, realizing external flashing was proposed as a potential way to mitigate the collapse of multi-jet flashing GDI sprays because it could suppress the severe jet overlap near the nozzle exit, which was believed as one of the necessary conditions for the spray collapse.

The current optical and thermal experimental tests were mainly focused on obtaining a comprehensive understanding of the effects of gasoline direct injector fouling on mass flow rates, spray characteristics, engine emissions and engine performance. A robust injector fouling cycle was employed to produce coked injectors in a multi-cylinder thermal engine. Deposit build-up in the coked injectors and fouling cycle repeatability was first examined by measurements of fuel flow rate. Macroscopic spray characteristics of the clean and the coked injectors were carried out using high-speed imaging and Planar Laser Induced Fluorescence (PLIF) of sprays foot-print. Fuel droplets size and velocity were characterised with a two-dimensional Phase Doppler Particle Analyser (PDPA). It was observed that the deposit build-up inside injector nozzles and on injector tips reduced the plume cone angle while increased plume penetration length, plume separation angles, mean droplet velocity and size for the coked injector. Impact of injector fouling was further investigated by PLIF measurements of in-cylinder charge inhomogeneity and repeatability in mixture preparation. The coked injectors showed higher degree of inhomogeneity and poorer repeatability in mixture preparation. These were in agreement with combustion analysis results where the coked injectors showed lower load and lower combustion stability compared with the clean injector under same operating conditions. Significantly higher unburned hydrocarbon emissions and particulate number concentration were also observed for the coked injectors. This work was carried out to obtain a broad picture of injector cooking effects in GDI engines.

Spray and droplet characteristics of a coked injector were compared to those of a clean injector at the atmospheric conditions and investigated using high-speed imaging and a Phase Doppler Particle Analyzer (PDPA). Scanning Electron Microscope (SEM) and X-ray 3D microtomography images were analysed to understand the physical characteristics of injector nozzle deposits. Furthermore, Energy Dispersive X-Ray Spectroscopy (EDS) was utilized to obtain the elemental composition of the deposit. A single cylinder optical gasoline direct injection (GDI) engine was used to compare diffusion flames for each injector. In this study, the location and topography of the deposits demonstrated that they extensively formed in the external holes of the injector, and reduced in size and quantity through the internal holes. Elemental analysis of the deposits exhibited that carbon (C) and oxygen (O) were the predominant elemental components through both the internal and external holes of the injector. The coked injector exhibited higher penetration lengths, smaller plume angles, larger spray cone angles, higher mean droplet velocity and larger droplet size as compared to the clean injector. Images of the optical engine indicated strong diffusion flames around the coked injector tip. In-cylinder pressure measurements indicated that the coked injector produced lower in-cylinder pressures, implying lower combustion stability compared with the clean injector. This work was carried out to obtain a comprehensive study of injector coking effects on spray behaviour and engine performance.

This article proposes an intelligent transient calibration method for the air-path controller of a light-duty diesel engine. This method is developed based on the chaos-enhanced accelerated particle swarm optimization algorithm. The target is to reduce the engine’s fuel consumption during transient scenarios by optimizing the controller parameters. The advanced dual-loop exhaust gas recirculation system is first introduced. Then, it formulates the transient calibration process as a multiple-objective optimization problem with constraints. Different from steady state calibration, the proposed method designs a new cost-function to evaluate the controller’s transient performance. The intelligent transient calibration module is programmed in MATLAB code. Interface between the calibration module and a physical engine plant is established via ETAS INCA. The optimization result of the proposal method is discussed by comparing it with the result of existing calibration methods. The engine performance with the calibrated controller is evaluated based on engine tests.

Airborne particles and vapours, like many other environmental samples including water, soils and sediments, contain complex mixtures of hydrocarbons, often deriving from crude oil either before or after fractionation into fuels, lubricants and feedstocks. Comprehensive 2D gas chromatography time-of-flight mass spectrometry (GC × GC-ToF-MS), offers a very powerful technique that separates and identifies many compounds in complicated hydrocarbon mixtures. However, quantification and identification of individual constituents at high ionization energies would require hundreds of expensive (when available) standards for calibration. Although the precise chemical structure of hydrocarbons does matter for their environmental impact and fate, strong similarities can be expected for compounds having very similar chemical structures and carbon numbers. There is, therefore, a clear benefit in an analytical technique which is specific enough to separate different classes of compounds and to distinguish homologous series while avoiding the need to handle each isomer individually. Varying EI (electron impact) ionization mass spectrometry significantly enhances the identification of individual isomers and homologous compound groups, which we refer to as “isomer sets”. Advances are reported in mapping and quantifying isomer sets of hydrocarbons (≥ C12) in diesel fuel, lubricating oil and diesel exhaust emissions. By using this analysis we report mass closures of ca. 90 and 75 % for diesel fuel and lubricating oil, and identify 85 and 75 % of the total ion current for gas- and particulate-phase diesel exhaust emissions.

A number of major studies have demonstrated that the SVOC (Semi-volatile organic compounds) within engine emissions derive predominantly from unburned fuel and lubricants, and are a major contributor to primary atmospheric aerosol containing thousands of organic compounds. The GC × GC-ToF-MS (2 dimensional Gas Chromatography – Time of Flight – Mass Spectrometry) comprehensive analytical technique was utilized in this study, to resolve the complex mixtures and characterize the SVOC content in eight different commercial lubricants, including 5 W30 synthetic and semi-synthetic, mineral and base oil. In order to quantify the aliphatic isomers, which comprise the largest component of the lubricants, a TIC-M.Q./Mass (Total ion current ratio to the molar quantity/mass) method has been developed. The TIC intensity was observed to be proportional to the molar quantity of n-alkanes for carbon number C25. Additionally, the TIC intensity of the alkyl-cyclohexanes under the identical retention indices were found to have an equivalent response to those of the n-alkanes, showing that the quantitative calibrations derived for the n-alkane series could be applied to estimate the concentrations of isomeric aliphatic compounds with similar molecular weight. Furthermore, a mesh method was introduced to group the alkane species (n-alkanes, branched alkanes and cyclic alkanes etc.), combining with the use of a soft EI (electron impact) ionization (14 eV) to retain the distinct identity of the isomers with less fragmentation, which allowed the TIC-M.Q./Mass methodology to integrate all the constitutional isomers present in the lubricating oil samples. By utilizing this methodology, compositions from different samples were comprehensively compared, leading to the following conclusions: 1) the synthetic and semi-synthetic oils contained a larger abundance of HMW (high molecular weight) aliphatic compounds (carbon number C24–C29), while those in the LMW (low molecular weight range, carbon number C18–C25) were predominant in the mineral and base oil; 2) cycloalkanes were predominant in the synthetic and semi-synthetic oils; whereas the branched alkanes were more prominent in the mineral and base oils; 3) for lubricants used for a short period, a slight increase of LMW compounds was observed, while the HMW compounds underwent a decrease, whereas, there was an overall mass reduction for all the aliphatic compounds detected in the oil samples used for six-months.

AlxCoCrFeNiTi1-x (x = 1.0, 0.8, 0.5 in molar ratio) high entropy alloys (abbreviated as Al-1.0, Al-0.8, Al-0.5 in the paper) were fabricated by repeated arc-melting and casting under vacuum. the effects of Al being replaced partially by Ti on the microstructure, mechanical properties and corrosion resistance in the solutions of 3.5 wt% NaCl, 0.5 mol/L NaOH and 0.5 mol/L H2SO4 were studied. The microstructure analysis showed that the Al-1.0 is mainly composed of single-phase BCC solid solution, while the Al-0.8 and the Al-0.5 consist of BCC and FCC biphasic solid solutions. With the increase of Ti atomic content, the elemental segregation intensifies, the FCC phase increases, and the BCC phase decreases. The results of hardness test and compressive test showed that all of the three alloys have good comprehensive mechanical properties, especially the Al-0.8. In the NaCl and NaOH solutions, the Al-1.0 and the Al-0.5 have similar corrosion resistance, but the Al-1.0 is a better choice out of economic consideration. In the H2SO4 solution, the Al-0.5 has the best corrosion resistance, followed by the A1-1.0 and the Al-0.8. A small amount of Ti addition in AlxCoCrFeNiTi1-x cannot offset the negative effects of the biphasic structure and the intense elemental segregation on the corrosion resistance and the corrosion resistance can be improved obviously Only when the atomic percentage of Ti exceeds that of Al.

Gasoline direct injection (GDI) engines are currently the dominant powertrains for passenger cars. With the implementation of increasingly stringent fuel consumption and emission regulations worldwide, GDI engines are facing challenges owing to high particulate matter emissions and a tendency to knock, leading to a change in the research and design (R&D) issues compared with those in the twentieth century. This paper reviews the progress in research regarding GDI engine technologies over the past 20 years, focusing on combustion system configurations, and also highlights common issues in GDI R&D, including pre-ignition and deto-knock, soot formation and PM emissions, injector deposits and gasoline compression ignition (GCI). First, an overview of recent developments in the field as driven by regulations is provided, following which progress in injection and combustion systems is examined. Third, the review addresses the occurrence and mechanism of deto-knock and considers means of suppressing this phenomenon. The fourth section discusses soot formation mechanisms and particulate matter emission characteristics of GDI engines and describes the application of gasoline particulate filter (GPF) after-treatment. The subsequent section summarizes studies regarding injector deposit formation, as well as pioneering research into GCI combustion modes. Finally, a summary and future prospects for GDI engine technologies are provided.

Objective Lymphatic malformations (LMs) are rare and benign diseases. This article aimed to present a series of surgically treated giant cervicofacial LMs in children. Methods A retrospective analysis of giant cervicofacial LMs (tumor diameter greater than 10 cm) in children over the past 8 years was performed in our department. Results The 10 patients included 4 males and 6 females. Macrocystic lesion presented in 4 patients, mixed cystic lesion presented in 4 patients, and microcystic lesion presented in 2 patients. All the patients underwent surgical resection combined with bleomycin sclerotherapy. Despite the wide range of lesions, most patients (7/10, 70%) received only a single treatment, 3 patients had a recurrent lesion. Seven patients experienced complete or almost complete resolution of the disease with an average follow-up time of 26.4 months. Conclusions Surgical resection is the preferred method for the treatment of giant LMs, combination of bleomycin sclerotherapy can reduce the recurrence rate. The curative effect of macrocystic disease is relatively enhanced compared with microcystic and mixed cystic diseases.

Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission and will dominate road transportation in the future. Energy management, which optimizes the onboard energy usage, is a critical functionality of electric vehicles. It is usually developed following the model-based routine, which is conventionally costly and time-consuming and is hard to meet the increasing market competition in the digital era. To reduce the development workload for the energy management controller, this paper studies an innovative transfer learning routine. A new transferable representation control model is proposed by incorporating two promising artificial intelligence technologies, adaptive neural fuzzy inference system and Gaussian process regression, where the former applies k-fold cross valudation to build a neural fuzzy system for real-time implementation of offline optimization result, and the later connects the neural fuzzy system with a ‘deeper’ architecture to transfer the offline optimization knowledge learnt at source domain to new target domains. By introducing a concept of control utility that evaluates vehicle energy efficiency with a penalty on usage of battery energy, experimental evaluations based on the hardware-in-the-loop testing platform are conducted. Competitive real-time control ultility values (as much as 90% of offline benchmarking results) can be achieved by the proposed control method. They are over 27% higher than that achieved by the neural-network-based model.

The present study is geared towards the investigation of the impact of fuel temperature, ambient pressure, and fuel properties on the spray characteristics of a 6-hole gasoline direct injector. High speed imaging is employed to verify the spray structural variation of various fuels including iso-octane, gasoline, methanol, and ethanol over wide range of operating conditions in an optical vessel. These structural parameters were correlated to the ratio of the ambient to saturation pressure ratio (Pa/Ps) that represents the superheated degree. At a constant pressure of 150 bar the fuel was injected, and the fuel temperature ranged between 25 and 120 °C, whilst the ambient pressure ranged from 0.1 to 1 bar. The results indicated that for all the fuels, the spray width was reduced, and the adjacent plumes collapsed into single bulk as the (Pa/Ps) decreased. Furthermore, at very low (Pa/Ps = 0.065), the spray getting longer, and for iso-octane the fuel spray shrinkage toward the injector centreline and shaped like a Fish with sharpen spray tip. The spray cone angle for ethanol, methanol, and gasoline was reduced when the Pa/Ps ratio was decreased from 1 to 0.16 with the exception that at Pa/Ps = 0.54 for ethanol the cone angle was increased and then decreased with the reduction of Pa/Ps. Then a massive increase in the cone angle was noticed by reducing the Pa/Ps ratio reduced from 0.16 to 0.065. For iso-octane, the behaviour is chaotic and not follow any specific trend with the reduction of Pa/Ps. Furthermore, the appearance of interstitial streams in the gaps between the original spray streams was noticed at Pa/Ps ratio ≤ 0.28. Phase Doppler data showed for the Pa/Ps ratios of 0.85, 0.54, and 0.28, that the interstellar streams consistently had a lower mean droplets velocity and a very narrow head stage compared to that of spray main streams. Moreover, reducing the Pa/Ps ratios of 0.85, 0.28, resulted in a significant reduction in Sauter mean diameter with approximately 49.5%.

Flash boiling injection can significantly promote spray atomization owing to rapid bubble growth and explosion. Nevertheless, the effects of component proportions on spray expansion of multi-component fuels still need more quantitative studies. In this work, a typical non-ideal binary solution (aqueous ethanol solution) was utilized as the injection fluid. The effects of ethanol proportion at varying injection temperatures and ambient pressures were tested in a constant volume vessel. Both increasing injection temperature and decreasing ambient pressure intensified the flashing instant expansion for all tested fluids. Instant expansion of pure water spray can be intensified by adding ethanol but adding ethanol into the aqueous ethanol solution induced an opposite behavior. Such phenomenon was caused by the combined effect of differences in heat capacity and proportions of evaporation components. Hence, superheat level was no longer a suitable index for evaluating the instant expansion between sprays with different component proportions. A new index ΔQ′ was proposed to quantify the expansion extent of binary solutions. A strong correlation was found between expansion extent and ΔQ′∙Pamb−0.75 over a wide condition range, indicating the superheated energy available for the first-vaporizable part of the solution is an important factor controlling the extent of instant expansion for binary solution spray.

Bioenergy attracts more attention owing to the reduction of both air pollution and greenhouse gas emissions in a whole life cycle compared to fossil fuels. As a third-generation biofuel, Microalgae Oil (MAO) can utilise carbon dioxide and light energy at an increased photosynthetic efficiency compared to energy crops for biomass. Due to the wide variety of MAO and their blends with diesel in different ratios, characterization of these biofuels’ engine performance is difficult to be standardized, e.g., in-cylinder pressure. This paper proposes a novel approach of geometric neuro-fuzzy transfer learning (GNFTL) for in-cylinder pressure modelling of a diesel engine fuelled with MAO. Inspired by computational geometry, this approach only utilizes limited experimental data obtained by geometric screening to learn a high-precise transfer model of the in-cylinder pressure with different MAO blending ratios. Followed by the process of MAO extraction and test cell description, the proposed approach of GNFTL is presented which comprises geometric transfer domain segmentation and neuro-fuzzy transfer learning. By a comprehensive study, the results demonstrate that the proposed approach can achieve a competitive prediction accuracy whilst significantly reducing experimental efforts on used biofuel by 47.8% and operation time by 41.5%, compared to the conventional manual design of experiment.

Atomization of fuel sprays is a key factor in the control of combustion quality in direct-injection engines. In the present work, the near-field spray patterns of 2-methylfuran (MF), ethanol (ETH) and isooctane (ISO) under non-flash boiling and flash boiling conditions were investigated using an ultra-highspeed imaging technique. Fuel was injected from a single-hole solenoid injector into an optically accessible constant volume chamber at the injection pressure of 40 MPa. Various conditions were tested, ranging from non-flash boiling conditions (ambient) to flare-flash boiling conditions with fuel temperatures of 20 °C and 80 °C and different back pressures. High-speed imaging was performed using a long-distance microscope coupled with an ultra-highspeed camera (1 million fps). Results showed that under flash boiling conditions, near-nozzle spray patterns changed significantly and clear radial expansion was observed due to bubble formation and explosion. Among the three fuels, MF showed the most intense flash boiling behavior due to it having the highest vapor pressure. The effects of different non-dimensional numbers were also considered and it was found that saturation ratio and cavitation number were the two main governing factors for the near-nozzle spray behaviors. During the end of the injection process, the low effective pressure led to poorly atomized spray with a compact liquid column and large ligaments; this could result in poor air/fuel mixing and thus higher HC and particle emissions. Significant improvements were observed at Rs = 0.2 where flash boiling greatly promoted the spray atomization, even with low fuel velocity.

In 2017, the Chinese government issued a strategic policy of nationwide use of bioethanol as a gasoline-blending component by 2020 for the consideration of reducing smog and greenhouse gas (GHG) emissions. It is highly relevant to estimate the benefits of well-to-wheel (WTW) GHG emission savings using future engine technologies. However, literature about the WTW GHG emissions for ethanol blends did not cover the engine efficiency gains in engines with future technologies. In a previous publication from the authors’ group, an empirical model was developed to predict the anti-knock property and engine thermal efficiency gains of ethanol blends in spark-ignition (SI) engines. This paper is a follow-up study, looking at not only the potential engine thermal efficiency gains but also WTW GHG emissions in future engine technologies. More specifically, a case study of adding bioethanol to two representative E10 fuels (main- and premium-octane-grade fuels) from China was conducted. It is assumed that future engin...

Background Branchial anomalies (BAs) account for 20% of all congenital masses in children. We sought to review the incidence of involvement of individual anomalies, diagnostic methods, surgical treatment, and complications of BAs in children. In addition, we also classified our study and analyzed a congenital lower neck cutaneous fistula near the sternoclavicular joint that was thought to be the skin-side remnant of the fourth BAs. Methods We conducted a retrospective analysis of 105 children who were referred to our hospital from June 2009 to December 2016 for the treatment of BAs. Results In this series, there were 51 males and 54 females. The age at the time of operation varied from 19 days to 13 years, and the mean age was 4.5 years. A total of 33 (31.4%) cases presented with first BAs, 13 (12.4%) presented with second BAs, and 59 (56.2%) presented with third and fourth BAs, including 6 cases of congenital lower neck cutaneous fistula. Fistulectomy under general anesthesia was performed on all of them. For postoperative complications, 2 cases had temporary facial paralysis, 1 case had permanent facial paralysis, 4 cases had temporary recurrent laryngeal nerve injury. Recurrence occurred in 2 patients with first BAs after medium follow-up time of 3.6 years (6 months–8 years). Conclusions BAs are common congenital head and neck lesions in children, and there are four distinct types (first, second, third and fourth anomalies). The incidence of third and fourth BAs in Asia maybe higher when compared with literature reports, second BAs seem rare in this population, but more research is needed to confirm this perspective. Diagnosis is not difficult with a proper knowledge of the anatomy of the BAs. The surgical procedures should be tailored depending on the various types, and complete excision of the fistula is the key to prevent recurrence.

Microscopic and macroscopic impingement characteristics of a single jet were investigated under various flash boiling conditions. The influences of split injection strategy and the related interaction between split injections were studied. The fuel concentration distribution during the impingement process was also quantified. It was found that non-flash boiling condition lead to large secondary droplets and ligaments, resulting in a large amount of liquid fuel deposited on the impact surface. The boosted flash boiling could effectively reduce the sizes of primary droplets and secondary droplets and the resultant deposited fuel. The employment of split injection strategy could further decrease the deposited fuel. The second split injection built up the fuel film more quickly than the first injection due to the existence of the built fuel film by the first injection, however, increasing flash boiling strength decreased the building-up rate by improving dispersion and evaporation. In addition, the concentration of the deposited fuel on the surface could effectively be reduced by enhanced flash boiling and the lifetime of dense fuel was shortened by increasing dwell interval between split injections.

The main objective of this study is to investigate the effect of ambient pressure ( P amb ) on the morphology of multi-jet flash boiling sprays and to promote the understanding on the collapse mechanism. With the high-speed imaging technique, the n-hexane spray process in a constant volume vessel was captured under the ambient pressures from 2 kPa to 101.3 kPa and the fuel temperatures ( T fuel ) from 20 °C to 120 °C. The spray width within the axial distances of 20 nozzle diameters ( do ) could be increased by increasing T fuel and/or decreasing P amb . Beyond 20 do , the change in spray width against superheated degree ( ΔT SD ) was fairly sensitive to P amb . It decreased with the increase in ΔT SD at P amb larger than 50 kPa, and increased with ΔT SD at P amb less than 50 kPa. Based on the new understanding that the collapse in multi-jet flash-boiling sprays was induced by vapor condensation at the nozzle exit and the resultant local pressure drop (i.e. generation of low-pressure zone), the sensitivity of spray width on P amb could be well explained as follows: relatively larger P amb (>50 kPa for the used injector) would be conducive to the vapor coagulation and cause stronger vapor condensation (i.e. larger pressure drop) while the vapor dispersion may become dominant at lower P amb (

Chassis dynamometer experiments were conducted to investigate the effect of vehicle speed and usage of ethanol-blended gasoline (E10) on formation and evolution of gasoline vehicular secondary organic aerosol (SOA) using a Gothenburg Potential Aerosol Mass (Go: PAM) reactor. The SOA forms rapidly, and its concentration exceeds that of primary organic aerosol (POA) at an equivalent photochemical age (EPA) of ~1 day. The particle effective densities grow from 0.62 ± 0.02 g cm−3 to 1.43 ± 0.07 g cm−3 with increased hydroxyl radical (OH) exposure. The maximum SOA production under idling conditions (4259–7394 mg kg-fuel−1) is ~20 times greater than under cruising conditions. There was no statistical difference between SOA formation from pure gasoline and its formation from E10. The slopes in Van Krevelen diagram indicate that the formation pathways of bulk SOA includes the addition of both alcohol/peroxide functional groups and carboxylic acid formation from fragmentation. A closure estimation of SOA based on bottom-up and top-down methods shows that only 16%–38% of the measured SOA can be explained by the oxidation of measured volatile organic compounds (VOCs), suggesting the existence of missing precursors, e.g. unmeasured VOCs and probably semivolatile or intermediate volatile organic compounds (S/IVOCs). Our results suggest that applying parameters obtained from unified driving cycles to model SOA concentrations may lead to large discrepancies between modeled and ambient vehicular SOA. No reduction in vehicular `SOA production is realized by replacing normal gasoline with E10.

Traffic-related volatile organic compounds (VOCs) emissions are regarded as the primary anthropogenic source of ambient VOCs in urban areas and precursors to ozone formation. Given the extensive use of gasoline-ethanol mixtures on light-duty vehicles, it is essential to discuss its effects on the atmospheric environment, especially the VOCs emissions and ozone forming potential (OFP) values of one typical formulation called the “match-blend.” In this paper, VOCs emission factors, VOCs distributions, specific reactivity (SR) values, and OFP values of a China-6 commercial gasoline and four E10 match-blend fuels used on seven China-6 vehicles were studied. Thirteen carbonyls detected by high-performance liquid chromatography along with seven VOCs detected by gas chromatography-mass spectrometry were considered in the calculation of OFP and SR. Besides, the effects of test temperatures are discussed. Results show that ethanol increases VOCs emissions, OFP, and SR values at cold-start/room temperature, but behaves oppositely at cold-start/low temperature. Increases in heavy aromatics always lead to higher VOCs emissions and OFP values.

For a multi-component hydrocarbon mixture under supercritical conditions, especially for fuels injected into compression ignition engines, the mechanism for the transition of the dominant mixing mode from evaporation to diffusion is not well established. In this paper, evaporation processes of a six-component hydrocarbon fuel (13.16 mol% toluene, 13.81 mol% n-decane, 22.30 mol% n-dodecane, 24.60 mol% n-tetradecane, 14.66 mol% n-hexadecane and 11.47 mol% n-octadecane) droplet in nitrogen environments were studied using molecular dynamics (MD) simulations, in comparison with those of three-component and single-component fuel droplets. The ambient pressure ranged from 2 MPa to 16 MPa and the ambient temperature ranged from 750 K to 1350 K. Results indicated that the transition characteristics of the mixed fuel were not the linearly weighted average of the physical properties of individual components in the mixture based on their mole fractions. The reason why there is a limitation on the maximum transition temperature when diffusion dominates the fuel-ambient gas mixing process under high pressures has been discussed. The average resultant force on a fuel atom of an individual component increases with increasing pressure or decreasing temperature at the supercritical temperature, and diffusion will gradually dominate the mixing process of the fuel. The clustering behavior of fuels under supercritical conditions has also been discussed.