Frontiers in Mechanical Engineering最新文献

{"title":"Editorial: New developments in vehicle thermal management","authors":"D. Di Battista, M. Di Bartolomeo, F. Fatigati","doi":"10.3389/fmech.2023.1255405","DOIUrl":"https://doi.org/10.3389/fmech.2023.1255405","url":null,"abstract":"","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"20 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85955172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical simulation of the effect of geometric parameters on silicone airway stent migration","authors":"Maryam Mazraehei Farahani, A. Bakhtiyari, Saed Beshkoofe, A. Kajbafzadeh, A. Kiani, A. Eskandari, M. Baniassadi, M. Baghani","doi":"10.3389/fmech.2023.1215895","DOIUrl":"https://doi.org/10.3389/fmech.2023.1215895","url":null,"abstract":"Recently, endotracheal stenting has become critical in treating respiratory diseases. Due to the COVID-19 pandemic in recent years, many patients had stenosis because of long-term intubation, and silicone stents can be used to treat tracheal stenosis in these patients. Standard airway stents are silicone tubes that provide immediate relief but are prone to migration. In this work, we design different silicone stents and analyze them in the trachea to evaluate silicone airway stents’ performance to overcome undesired migration. A finite-element model of the trachea was employed to evaluate anti-migration forces in each stent. The geometry of the trachea is brought from a computerized tomography scan of the chest of a 68-year-old healthy man. The results are shown based on the least migration of stents based on anti-migration forces. Also, the conditions of stent placement have been considered based on two different assumed friction factors, and the importance of choosing the type of silicone for stent construction has been analyzed. The results show that increasing the diameter of the stent reduces the displacement and migration of it in the trachea. Furthermore, the 23 mm stent with a 45° angle revealed the best implementation against compression under the impact of respiratory pressure differences.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"10 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87131696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of key parameters on performance of a pre-cooled core engine based on the closed helium cycle","authors":"Ma Tong-Ling, Jiang Xue-Feng, Liu Guo-dong, Liu Zhen-de, Gao Han, He Xue-gang, Du Peng-Cheng","doi":"10.3389/fmech.2023.1208468","DOIUrl":"https://doi.org/10.3389/fmech.2023.1208468","url":null,"abstract":"A pre-cooled combined engine based on a closed helium (He) cycle offers high specific thrust and high specific impulse. Therefore, evaluation of the performance of such an engine is crucial for engine applications and key technology research. This study employs an analytical approach to investigate the effects of key parameters on the performance of a pre-cooled core engine, assuming a perfect gas model. The findings revealed that the specific thrust and specific impulse of the pre-cooled core engine are related to the pressurized coefficient of the airflow passage and equivalence ratio (ER). An increase in the pressurized coefficient leads to an increase in both specific thrust and specific impulse. However, within a certain range, although the specific thrust is positively correlated with the ER, the specific impulse is greatly reduced. With specific component parameters and a fixed thermodynamic cycle, a minimum ER exists, which satisfies the cycle-matching requirement. Moreover, the value of the minimum ER is related to the closed-cycle efficiency. For a pre-cooled core engine with a simple closed He cycle, the minimum ER is approximately 2.5–3.5.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"10 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87778653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of the Rate of Injection of Diesel Solenoid Injectors Operated in the Multiple Injection Strategy: A Comparison of the Spray Momentum and Bosch Tube Methods","authors":"Bassam S. E. Aljohani, Moez Ben Houidi, Jian-ying Du, Aibolat Dyuisenakhmetov, B. Mohan, Abdullah S. AlRamadan, W. Roberts","doi":"10.3389/fmech.2022.889255","DOIUrl":"https://doi.org/10.3389/fmech.2022.889255","url":null,"abstract":"Multiple injection strategies can be used for controlling the heat release rate in an engine, particularly in compression ignition engines. This can mitigate the heat transfer losses and overcome the limitation related to the maximum pressure allowed for a particular engine. Controlling heat release with repetitive injections requires precise characterization of the fuel injection rates. In such a configuration, the injector used should be characterized for its hydraulic delay, rate of injection, and the effect of dwell timing with multiple injections. This study investigates the fuel injection behavior of a high-flow-rate solenoid injector operated with single and double injections. Two characterization methods, the momentum flux, and the Bosch tube are used and compared to investigate their suitability with the multiple injection strategies. Experiments with single injection are conducted by varying the Energizing Timing (ET) from 0.5 up to 2 ms. The tests with multiple injections (i.e., double injections) are conducted with a fixed ET of 0.5 ms, while the dwell times (δt) are varied from 0.1 up to 1 ms. All tests are performed at 500, 1000, 1500, and 2000 bar rail pressures. Depending on the injection pressure, the injector’s needle could not fully close with short dwell times and the injections are merged. The momentum flux method has faster ramp-up and decaying and more oscillations in the quasi-steady-state phase compared to the Bosch tube method. The effective duration of injection is overpredicted with the Bosch tube method. The momentum flux method is demonstrated to be more suitable for measuring the ROI of multiple injection strategies.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"320 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80220310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On Modeling of Spray G ECN Using ROI-Based Eulerian-Lagrangian Simulation","authors":"Akhil Ailaboina, K. Saha","doi":"10.3389/fmech.2022.880635","DOIUrl":"https://doi.org/10.3389/fmech.2022.880635","url":null,"abstract":"A numerical study has been carried out to understand the effects of Unsteady Reynolds Averaged Navier-Stokes (standard k ― ε and RNG k ― ε model) and large eddy simulations (LES) on a multi-hole gasoline direct injection (GDI) system. The fuel injector considered in this study is the Spray G nozzle from the Engine Combustion Network (ECN). A blob injection model, based on empirical rate of injection (ROI) profile, is considered in this study. The latest data on spray penetrations from Engine Combustion Network is used for model validation along with experimental findings on suction velocity and local droplet diameter. The spray breakup is simulated by using the KH-RT breakup length model. The turbulence model constant Cε1, is tuned to match with the experimental data of liquid and vapor penetrations in simulations while using the standard k-ε turbulence model. On the other hand, the Kelvin-Helmholtz breakup model time constant (B1) and Rayleigh Taylor breakup length constant (Cbl) are tuned for the RNG k ― ε turbulence model. From this work it is observed that by increasing the breakup length model constants (Cbl), the radial dispersion of the spray increases, and the extent of breakup is lowered. The set of optimized model parameters used with RNG k - ε is also used for LES modeling studies with different sub-grid models. The spray penetrations with standard k ― ε turbulence (Cε1=1.44) model are reported underpredicting, and the RNG k ― ε and LES sub-grid models predicted well with the latest and recommended data from ECN. In terms of gas axial velocity comparison, the standard k-ε(Cε1=1.44) simulation setup does not perform as well as the simulation setups using RNG k-ε and LES turbulence models (with breakup parameters: Cbl = 16 and B1 = 32). However, the standard k-ε(Cε1=1.44) simulation setup perform better than the simulation setups using RNG k-ε and LES turbulence models (with breakup parameters: Cbl = 16 and B1 = 32) when it comes to predicting local droplet diameter at 15 mm downstream of the injector tip. A parametric study is also performed considering the geometry of the stepped holes in the computational domain. The rate of injection based simulation is initiated at the end of the smaller hole. The case including the stepped holes led to over-prediction compared to the case with the usual computational domain (i.e., without the stepped holes), in terms of spray penetrations, but exhibited higher levels of fluctuations in the spray morphology. Finally, parametric studies were carried out to understand the relative importance of the individual spray sub-models (breakup, evaporation and collision) and the results are conclusive that for a spray simulation the breakup models are the dominant factors.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"2006 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89878056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent Classification of Tungsten Inert Gas Welding Defects: A Transfer Learning Approach","authors":"R. Aravind Sekhar, Deepak Kumar Sharma, Pritesh Shah","doi":"10.3389/fmech.2022.824038","DOIUrl":"https://doi.org/10.3389/fmech.2022.824038","url":null,"abstract":"Automated and intelligent classification of defects can improve productivity, quality, and safety of various welded components used in industries. This study presents a transfer learning approach for accurate classification of tungsten inert gas (TIG) welding defects while joining stainless steel parts. In this approach, eight pre-trained deep learning models (VGG16, VGG19, ResNet50, InceptionV3, InceptionResNetV2, Xception, MobileNetV2, and DenseNet169) were explored to classify welding images into two-class (good weld/bad weld) and multi-class (good weld/burn through/contamination/lack of fusion/lack of shielding gas/high travel speed) classifications. Moreover, four optimizers (SGD, Adam, Adagrad, and Rmsprop) were applied separately to each of the deep learning models to maximize prediction accuracies. All models were evaluated based on testing accuracy, precision, recall, F1 scores, training/validation losses, and accuracies over successive training epochs. Primary results show that the VGG19-SGD and DenseNet169-SGD architectures attained the best testing accuracies for two-class (99.69%) and multi-class (97.28%) defects classifications, respectively. For “burn through,” “contamination,” and “high travel speed” defects, most deep learning models ensured productivity over quality assurance of TIG welded joints. On the other hand, the weld quality was promoted over productivity during classification of “lack of fusion” and “lack of shielding gas” defects. Thus, transfer learning methodology can help boost productivity and quality of welded joints by accurate classification of good and bad welds.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"426 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77801302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and Predicting Heavy-Duty Vehicle Engine-Out and Tailpipe Nitrogen Oxide (NOx) Emissions Using Deep Learning","authors":"R. Pillai, V. Triantopoulos, A. Berahas, Matthew J. Brusstar, Ruonan Sun, Tim A. Nevius, A. Boehman","doi":"10.3389/fmech.2022.840310","DOIUrl":"https://doi.org/10.3389/fmech.2022.840310","url":null,"abstract":"As emissions regulations for transportation become stricter, it is increasingly important to develop accurate nitrogen oxide (NO x ) emissions models for heavy-duty vehicles. However, estimation of transient NO x emissions using physics-based models is challenging due to its highly dynamic nature, which arises from the complex interactions between power demand, engine operation, and exhaust aftertreatment efficiency. As an alternative to physics-based models, a multi-dimensional data-driven approach is proposed as a framework to estimate NO x emissions across an extensive set of representative engine and exhaust aftertreatment system operating conditions. This paper employs Deep Neural Networks (DNN) to develop two models, an engine-out NO x and a tailpipe NO x model, to predict heavy-duty vehicle NO x emissions. The DNN models were developed using variables that are available from On-board Diagnostics from two datasets, an engine dynamometer and a chassis dynamometer dataset. Results from trained DNN models using the engine dynamometer dataset showed that the proposed approach can predict NO x emissions with high accuracy, where R 2 scores are higher than 0.99 for both engine-out and tailpipe NO x models on cold/hot Federal Test Procedure (FTP) and Ramped Mode Cycle (RMC) data. Similarly, the engine-out and tailpipe NO x models using the chassis dynamometer dataset achieved R 2 scores of 0.97 and 0.93, respectively. All models developed in this study have a mean absolute error percentage of approximately 1% relative to maximum NO x in the datasets, which is comparable to that of physical NO x emissions measurement analyzers. The input feature importance studies conducted in this work indicate that high accuracy DNN models (R 2 = 0.92–0.95) could be developed by utilizing minimal significant engine and aftertreatment inputs. This study also demonstrates that DNN NO x emissions models can be very effective tools for fault detection in Selective Catalytic Reduction (SCR) systems.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83500263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain Shape Changes Associated With Cerebral Atrophy in Healthy Aging and Alzheimer’s Disease","authors":"Yana Blinkouskaya, J. Weickenmeier","doi":"10.3389/fmech.2021.705653","DOIUrl":"https://doi.org/10.3389/fmech.2021.705653","url":null,"abstract":"Both healthy and pathological brain aging are characterized by various degrees of cognitive decline that strongly correlate with morphological changes referred to as cerebral atrophy. These hallmark morphological changes include cortical thinning, white and gray matter volume loss, ventricular enlargement, and loss of gyrification all caused by a myriad of subcellular and cellular aging processes. While the biology of brain aging has been investigated extensively, the mechanics of brain aging remains vastly understudied. Here, we propose a multiphysics model that couples tissue atrophy and Alzheimer’s disease biomarker progression. We adopt the multiplicative split of the deformation gradient into a shrinking and an elastic part. We model atrophy as region-specific isotropic shrinking and differentiate between a constant, tissue-dependent atrophy rate in healthy aging, and an atrophy rate in Alzheimer’s disease that is proportional to the local biomarker concentration. Our finite element modeling approach delivers a computational framework to systematically study the spatiotemporal progression of cerebral atrophy and its regional effect on brain shape. We verify our results via comparison with cross-sectional medical imaging studies that reveal persistent age-related atrophy patterns. Our long-term goal is to develop a diagnostic tool able to differentiate between healthy and accelerated aging, typically observed in Alzheimer’s disease and related dementias, in order to allow for earlier and more effective interventions.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"60 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77898549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NO x Formation in MILD Combustion: Potential and Limitations of Existing Approaches in CFD","authors":"S. Iavarone, A. Parente","doi":"10.17863/CAM.51136","DOIUrl":"https://doi.org/10.17863/CAM.51136","url":null,"abstract":"Emissions of nitrogen oxides (NOx) from combustion systems remain a lingering environmental issue, being these species either greenhouse gases or acid rain precursors. Moderate or Intense Low-oxygen Dilution (MILD) combustion can reduce the emissions of nitrogen oxides thanks to its characteristic features (i.e., homogeneous reaction zones, reduced temperature peaks, diluted mixtures of reactants) that influence and change the main chemical pathways of NOx formation. A summary of the relevant routes of formation and destruction of nitrogen oxides in MILD combustion is presented in this review, along with the identification of the sources of uncertainty that prevent reaching an overall consensus in the literature about the dominant NOx chemical pathway in MILD regime. Computational Fluid Dynamics (CFD) approaches are essential tools for investigating the critical phenomena occurring in MILD combustion and the design of pollutant-free turbulent combustion systems. This paper provides an outline of the modeling approaches employed in CFD simulations of turbulent combustion systems to predict NOx emissions in MILD conditions. An assessment of the performances of selected models in estimating NOx formation in a lab-scale MILD combustion burner is then presented, followed by a discussion about relevant modeling issues, perspectives and opportunities for future research.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"42 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80798709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling Temperature Variations in MILD Combustion Using MuSt-FGM","authors":"M. U. Goktolga, P. D. Goey, J. V. Oijen","doi":"10.3389/FMECH.2020.00006","DOIUrl":"https://doi.org/10.3389/FMECH.2020.00006","url":null,"abstract":"The energy demand in the world is ever increasing, and for some applications combustion is still the only reliable source, and will remain as such in the foreseeable future. To be able to mitigate the environmental effects of combustion, we need to move to cleaner technologies. Moderate or intense low oxygen dilution (MILD) combustion is one of these technologies, which offer less harmful emissions, especially nitric oxide and nitrogen dioxide (NOx). It is achieved by the recirculation of the flue gases into the fresh reactants, reducing the oxygen content, and thereby causing the oxidation reactions to occur at a milder pace, as the acronym suggests. This results in a flameless combustion process and reduces the harmful emissions to negligible amounts. To assist in the design and development of combustors that work in the MILD regime, reliable and efficient models are required. In this study, modeling of the effects of temperature variation in the oxidizer of a MILD combustion case is tackled. The turbulent scales are fully resolved by performing direct numerical simulations (DNS), and chemistry is modeled using multistage flamelet generated manifolds (MuSt-FGM). In order to model the temperature variations, a passive scalar which is created by normalizing the initial temperature in the oxidizer is defined as a new control variable. During flamelet creation, it was observed that not all the compositions are autoigniting. Several approaches are proposed to solve this issue. The results from these cases are compared against the ones performed using detailed chemistry. With the best performing approach, the ignition delay is predicted fairly well, but the average heat release rate is over-predicted. Some possible causes of this mismatch are also given in the discussion.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":"32 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2020-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75550537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}