bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application and Prospect of Intelligent Manufacturing in Practice
Authors: Zhang Runyan , Yuan Yan , Chen Limin 
Published: June 2023

Abstract
Intelligent manufacturing is the core technology paradigm of the new round of scientific and technological revolution, and the main direction of strengthening the integration of digital and real technology and building a manufacturing power. This paper focuses on intelligent manufacturing. Take intelligent mechanical engineering, intelligent logistics, industrial robots and intelligent production workshops as examples. Exploring the phased achievements and applications of intelligent manufacturing technology. Research showed that the realization of intelligent manufacturing has adopted technologies such as the Internet of Things, big data, cloud computing, machine learning, intelligent sensing, interconnection and remote operation and maintenance, effectively solving many current engineering and scientific research problems. Indicating that the intelligent manufacturing industry supported by information technology and advanced digital technology has broad application prospects. It also provides reference for the application and high-quality development of intelligent manufacturing.
An Evaluation Method of Equipment Development Priority Combining Subjective and Objective
Authors: Guo Zhiming , Ye Jun , Wang Wei , Gao Liang , Qiao Hu 
Published: June 2023

Abstract
This article proposes a Subjective And Objective Evaluation (SAOE) method for equipment development priorities. By establishing the evaluation index system of equipment development priority evaluation, using fuzzy analytic hierarchy process to determine the subjective weights of each indicator in the indicator system, and then use the deviation maximization method to determine the objective weight of each indicator in the indicator system. Finally, based on least square method and relative entropy principle, combining subjective and objective weights to obtain the combined weight value of indicators, to obtain the equipment development priority. This method uses SAOE method to evaluate the priority of equipment development, which improves the scientific and reliability of the evaluation results, and is more practical, and provides a reliable basis for equipment development planning.
Improvement of measurement accuracy using Bayesian inference - Reduction of instrumentation effort in an axial compressor
Authors: Cruz Gonçalo G. , Ottavy Xavier , Fontaneto Fabrizio 
Published: June 2023

Abstract
As the next generation of turbomachinery components becomes more sensitive to instrumentation intrusiveness, a reduction of the number of measurement devices required for the evaluation of performance is a possible and cost-effective way to mitigate the arising of non-mastered experimental errors. A hybrid methodology that couples experimental techniques with modeling techniques through a Bayesian data-driven framework is employed to reduce the instrumentation effort. A numerical model is employed to provide an initial belief of the flow, which is then updated based on undersampled experimental observations by a Bayesian inference algorithm. The goal of the present work is to showcase the proposed hybrid methodology and demonstrate its partial application through Gaussian Process regression in reducing the instrumentation effort and testing time at the outlet of a low aspect ratio axial compressor stage representative of the last stage of a high-pressure compressor. Preliminary results show an accurate reconstruction of the mean flow field with a direct uncertainty quantification provided by the Bayesian approach.
Two-wavelength interferometry for measurement of transonic airflow in a compressor blade cascade
Authors: Psota P , Kredba J , Stašík M , Cubreli G , Lédl V , Šimurda D 
Published: June 2023

Abstract
This paper presents high-speed two wavelength interferometry for measuring fast phenomena, which allows to extend the dynamic range of measurement using two different wavelengths at the same time. The method was applied to measure transonic airflow through a blade cascade
Laser Doppler Anemometry technique to study the flow field in the nozzle and in the water jet of a Pelton turbine
Authors: Pisaturo Giuseppe Roberto , Nicolosi Francesco Fabio , Gusmerotti Daniele , Righetti Maurizio , Renzi Massimiliano 
Published: June 2023

Abstract
The constant availability of water from the mountain basins is crucial to feed the hydropower plants that currently represent the most important renewable energy source in many countries, like Italy. The long dry periods that are nowadays registered during the summer periods have imposed the managers of the hydropower plants to operate the machines at very low flow rates, close to the lowest allowed values. In this work we focus our attention on the fluid-dynamics of the water jet of a Pelton machine and of the corresponding nozzle, with particular attention to the low flow-rate ranges. The nozzle has been manufactured in PMMA to be able to study the internal fluid-dynamics using the Laser Doppler Anemometry (LDA) technique. The shape of the nozzle has been adapted to limit the laser beam distortion and an algorithm has been implemented to correct the position of the measurement volume and the evaluation of the velocity components. Moreover, a specific measurement layout has been proposed and implemented to be able to study the velocity of the water jet downstream the nozzle and to study the homogeneity of the flow velocity in the jet, which is a crucial characteristic to grant a proper operation of the Pelton runner. The specific set-up of the test bench and the LDA parameters are presented; the signal of the LDA receiver proved to be very consistent and reliable. Moreover, the results of the measurements have been used to validate CFD simulations and to extend the results of the analyses to other operating conditions of the Pelton nozzle
Time-of-flight estimation in acoustic pyrometry: sensitivity to pulse characteristics
Authors: Pettinari Matteo , Ferrari Lorenzo 
Published: June 2023

Abstract
Acoustic pyrometry is a non-intrusive measurement technique that may have several applications in turbomachinery. This methodology estimates the gas temperature by measuring the time of flight of an acoustic wave moving through a medium. It can be accomplished by placing a sound source (emitter) and a set of microphones (receivers) on opposite sides of a section. The emitter generates a sound pulse, and the receivers detect it. Since the emitter-receiver distances are known and fixed, the average temperatures of the paths traversed by the acoustic pulse can be computed by estimating the time-of-flight through deconvolution techniques. However, despite the straightforward principle, an acoustic wave suffers a variation of amplitude when propagating within a medium because of energy losses and ambient noise. Hence, time-of-flight estimation becomes a critical task, especially when considering high-frequency waves or short distances between sensors. It is then fundamental to select proper acoustic waves to maximise the cross-correlation between the signals of the emitter-receiver couples, thus improving the accuracy of the time-of-flight measurements and, consequently, the estimation of the spatial temperature distribution within a specific area. This study is a preliminary investigation, based on a modelling approach, to estimate the impact of different acoustic waves on the accuracy of the time-of-flight measurement. The results of this analysis will be useful to design and setup an acoustic pyrometry application.
Test Rig Design Considerations to Detect Volatile Organic Compounds in Aircraft Cabins
Authors: Nasoulis Christos P. , Mantziou Stavroula , Gkoutzamanis Vasilis G. , Kalfas Anestis I. 
Published: June 2023

Abstract
A numerical investigation for simulating the aircraft cabin as an environmental chamber is set to assist a test rig design assimilating passenger comfort, considering their exposure to high concentrations of Volatile Organic Compounds. Computational Fluid Dynamics is used to evaluate the flow inside the cabin for 800 sec of actual flow time, where the mixing and transport of chemical species are also evaluated. Measurements close to the passengers’ noses are used to create a Boruta feature selection-based dataset that trains four machine learning classifiers, namely, Support Vector Machine, Random Forest, Naive Bayes, and Logistic Regression, and compares their performance. Furthermore, the evaluation of molecular weight impact on residence time is explored, with an additional simulation including cabin filters. The model is proven to be insensitive to inlet air mass flow variation, indicating that the air-conditioning system mass flow has a minor impact on chemical species mass measurements. The Naive Bayes classifier shows the greatest performance with 96 % accuracy and is being selected to create a digital nose model. Moreover, when comparing simulation results between the models with and without cabin filters, results indicate that the residence time is independent of each compound’s molecular weight, with all showing equivalent residence time reduction. Finally, the observed cabin flow irregularities indicate that passengers may share different comfort experiences during the flight. This dictates the need to manufacture a full-scale test rig to quantify the impact of the flow asymmetry on the comfort of frequent travelers and aviation professionals.
Instrumentation improvements for NGV aerodynamic characterization at high Mach numbers
Authors: Puente A , Garcia-Valdecasas G 
Published: June 2023

Abstract
One of the most important new engine concepts is the Geared turbofan. In these engines a gear box allows the decoupling between fan and turbine rotational speeds. As a consequence, the separate aerodynamic optimization of both components becomes possible leading to an increase in engine bypass ratios, higher propulsive efficiency and lower specific fuel consumption. The multi-stage intermediate pressure turbine (IPT) is one of the key parts of the thermodynamic cycle in geared turbofan architectures. During the characterization of a LPT NGV row, it is important to have detailed pressure losses measurements as accurate as possible. Because of the aerodynamic differences with conventional low pressure turbines (LPT), this becomes mandatory when the NGV is designed for an IPT. The main error sources are related to circumferential anisotropy, to repeatability of US and DS measurements, to effects of instrumentation in 2D losses and to static pressure measurement in the probe environment.
A fluorescent PIV technique for turbomachinery flows
Authors: Okada M , Pinho J , Cernat B , Lavagnoli S 
Published: June 2023

Abstract
This paper presents the development and applications of a fluorescent Particle Image Velocimetry (PIV) technique as a countermeasure for undesired light reflections on surfaces of channel walls or obstacles. The employment of the fluorescent dye-doped tracer particle with a wavelength-specific optical filter enables a separation of the stokes-shifted particle light emission from reflections on the surfaces. Aiming at applying the technique to engine-like turbomachinery flows, the fluorescent tracer particles were made out of pyrromethene 567 and Di-Ethyl-Hexyl-Sebacat considering multiple aspects of characteristics. The developed particles were firstly tested in a low-speed wind tunnel with a metal turbine blade placed in the flow path and a laser sheet oriented to impinge the blade surface. With the installation of an adequate optical filter, the undesired light reflections were successfully removed, and reasonable vector calculations were enabled in proximity to the reflective blade surfaces. Secondly, the fluorescent PIV was performed on a high-pressure turbine stage hosted in a high-speed short-duration rotating turbine rig to demonstrate the feasibility of the technique in engine-representative turbomachinery flows.
Design of a small pressure chamber to evaluate probe calibrations at varying Reynolds numbers
Authors: Speck K , Schäffer C , Gümmer V 
Published: June 2023

Abstract
The Chair of Turbomachinery and Flight Propulsion (LTF) at the Technical University of Munich (TUM) operates a wind tunnel for probe calibration (Caljet). This paper describes the design and the validation process of a pressure chamber. The pressure chamber is used to calibrate probes for turbomachinery applications at comparable conditions to a 3.5-stages axial compressor test rig. This allows the study of Reynolds number and Mach number effects individually. The pressure chamber is designed as an additional component for the Caljet to enable probe calibration at higher mass flow densities and higher Reynolds numbers. Therefore, the original free stream jet is encased by this chamber, nevertheless the outlet of the calibration wind tunnel remains open to the environment. After a first pre-design study, numerical simulations are carried out to confirm expected flow conditions in the measurement area. Ansys Fluent is used for RANS simulations with air modeled as compressible gas. The numerical results are validated with experimental investigations that simultaneously provide a deeper understanding of the flow behavior. Therefore, a five-hole probe, a hot-wire probe, and a Fast Response Aerodynamic Probe are utilized. It is shown that the capability of the jet meets the expectations and can be used for the calibration of hot-wire probes at conditions comparable to a state-of-the-art 3.5-stages axial compressor.
Acoustic pyrometry for flow velocity estimation: preliminary analysis
Authors: Caposciutti G. , Ferrari L. 
Published: June 2023

Abstract
Acoustic pyrometry uses the variations of the speed of sound in a medium to determine its temperature. One of the assumptions at the base of this technique is that the flow velocity component in the direction of the acoustic path is negligible in comparison to the speed of sound. However, if the temperature of the medium is known, the acoustic pyrometry approach can be used to determine flow speed, as long as the flow is not perpendicular to the acoustic path. The combined approach of temperature and velocity determination is also known as acoustic tomography. This technique allows the determination of velocity and temperature maps in a flow region. Even though this is an interesting result, the mathematical approach to solve the velocity and temperature fields might be very complex and sensitive measurement set-up. In this study, a preliminary investigation is carried out to determine the flow velocity by starting from the time of flight of an acoustic signal moving along different acoustic paths in a constant temperature field. For this purpose, a simplified geometry is considered. The developed mathematical approach at the base of the methodology is presented in this study.
An alternative post-processing of transient liquid crystal experiments using the wall temperature gradient time response
Authors: Peteinaris A , Haftka O , Terzis Alexandros 
Published: June 2023

Abstract
An alternative method for the fast evaluation of transient liquid crystal experiments is presented in this study. The calibration of liquid crystals has been considered essential to obtain accurate heat transfer measurements. Nevertheless, liquid crystal aging, illumination, and ex situ calibration effects remain a difficult and might influence the heat transfer level. Proposed here is to bypass liquid crystal calibration by utilizing the evolution of the wall temperature gradients. This necessitates the use of the detection times of the maximum red and green intensities of narrow bandwidth liquid crystals, e.g., less than 1 K, whose temperature span is on the order of 0.3 K. The calculation of the heat transfer coefficients can be thus feasible by differentiating the wall temperature from the solution of the semi-infinite body approach with respect to time. This approach is examined over different experiments with varying geometries and liquid crystal detection times. The in-advance possession of the calibration curves of the liquid crystals allows for the method’s cross-evaluation. The results indicate that the proposed method is in sufficiently good agreement with the values obtained using the calibrated liquid crystal signals. In particular, the average heat transfer coefficient of a surface is within 8% from the traditional method which is sufficient for industrial applications and preliminary thermal designs.
Deep-Learning Based Identification of Inducer Cavitation Instability
Authors: Yoon Youngkuk , Lee Sanghyun , Song Seung Jin 
Published: June 2023

Abstract
A deep-learning based method is introduced to detect and identify the inducer cavitation instability. To identify alternate blade cavitation, which is a common cavitation instability occurs at two-bladed inducer, synthetic unsteady pressure data under equal length cavitation and alternate blade cavitation have been generated and used as training data sets. The neural network is trained to categorize the unknown unsteady pressure signal into with or without cavitation instability. In the present research, the network shows good performance in capturing the key features of the instability and robustness against random noise compared with the previous mode analysis technique
Blade pressure loading and torque measurement in a transonic linear cascade
Authors: Lepicovsky Jan , Šimurda David , Hála Jindřich , Šidlof Petr , Štěpán Martin 
Published: June 2023

Abstract
Experimental results of a transonic compressor blade pressure loadings and blade shaft torque measurements are presented in this paper. Data were acquired for the cascade middle blade being set to a number of incidence angle offsets to simulate phases of a blade flutter oscillatory motion. This paper should be viewed as a progress report on the ongoing larger research effort on blade flutter in transonic flow regimes.
Regionally differentiated promotion of electric vehicles in China considering environmental and human health impacts
Authors: Fang Yan Ru , Sun Xin , Zhang Silu , Liu Gang , Liu Xiaorui , Zhang Peng , Kang Yifei , Dai Hancheng 
Published: June 2023

Abstract
Private passenger vehicles, with its high emissions of CO2 and air pollutants, poses a severe threat to global climate and human health, particularly for a large developing country like China. Although both energy efficiency improvement of internal combustion engine vehicles (ICEVs) and the wide adoption of electric vehicles (EVs) could contribute to reducing emissions, how they should be jointly implemented in provinces with a heterogeneous context to maximize their net benefits remains insufficiently explored. Here, based on an integrated modeling framework associated with one factual (REF) and four counterfactual scenarios to explore the priority and best-ranked ordering of both EVs’ penetration and high energy-efficient ICEVs in 31 Chinese provinces to achieve the most environmental and human health benefits from 2011 to 2018. The results demonstrate that electrification of the passenger fleet, which is charged by a slightly cleaner power source relative to 2011, yields significant co-benefits of CO2 reduction and air quality improvement. Compared with REF, the fleet electrification scenario would lead to 3167 cases of avoided mortality and attain US$4.269 billion of health benefits in 2018, accounting for 0.03% of China’s gross domestic product. Nonetheless, highly efficient ICEVs are found to harbor decarbonization potential and health benefits in northern China. Based on these results, Sichuan, Hebei and seven other provinces in east China should promote EVs imminently; conversely, eight provinces with a high share of thermal power must continually advance their implementation of ICEVs in the near future. Such prioritization of EVs and ICEV development at the provincial level provides timely insights for devising tailored policies regarding passenger car transition and for maximizing climate and health benefits based on regional heterogeneity.
Towards interpreting machine learning models for predicting soil moisture droughts
Authors: Huang Feini , Zhang Yongkun , Zhang Ye , Nourani Vahid , Li Qingliang , Li Lu , Shangguan Wei 
Published: June 2023

Abstract
Determination of the dominant factors which affect soil moisture (SM) predictions for drought analysis is an essential step to assess the reliability of the prediction results. However, artificial intelligence (AI) based drought modelling only provides prediction results without the physical interpretation of the models. Here, we propose an explainable AI (XAI) framework to reveal the modelling of SM drought events. Random forest based site-specific SM prediction models were developed using the data from 30 sites, covering 8 vegetation types. The unity of multiply XAI tools was applied to interpret the site-models both globally (generally) and locally. Globally, the models were interpreted using two methods: permutation importance and accumulated local effect (ALE). On the other hand, for each drought event, the models were interpreted locally via Shapley additive explanations (SHAP), local interpretable model-agnostic explanation (LIME) and individual conditional expectation (ICE) methods. Globally, the dominant features for SM predictions were identified as soil temperature, atmospheric aridity, time variables and latent heat flux. But through local interpretations of the drought events, SM showed a greater reliance on soil temperature, atmospheric aridity and latent heat flux at grass sites, with higher correlation to the time-dependent parameters at the sites located in forests. The temporal variation of the feature which effects the drought events was also demonstrated. The interpretation could shed light on how predictions are made and could promote the application of AI techniques in drought prediction, which may be useful for irrigation and water resource management.
Improved stability and luminescent efficiency of AgInSe2 nanocrystals by shelling with ZnS
Authors: Thi Thu Huong Tran , Thi Hiep Nguyen , Loan Nguyen Thu , Van Long Le , Han HyukSu , Thi Thao Nguyen , Thi Dieu Thuy Ung , Liem Nguyen Quang 
Published: June 2023

Abstract
In this paper, AgInSe2 (AISe) core and AgInSe2/ZnS (AISe/ZnS) core/shell nanocrystals (NCs) were synthesised by a one-pot method in an organic solvent. Firstly, the synthesis of AIS core NCs with different sizes was performed by hot-injection of Se precursor into the Ag and In complexes at different temperatures from 100 °C to 180 °C for a reaction time of 20 min Then, the ZnS was grown on the surface of AISe NCs at 150 °C for 60 min to produce the AISe/ZnS core/shell structures. The as-synthesised AISe core and AISe/ZnS core/shell NCs were characterised by using x-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and optical spectroscopies (UV–vis absorption and photoluminescence (PL)). After shelling ZnS layer, AISe/ZnS core/shell NCs become more stable (12 months) in ambient air and emit strong luminescence with a high quantum yield (QY) of 40% in the range from 610 nm to 762 nm by varying the reaction temperature of AISe core synthesis from 100 °C to 180 °C. The observed increase of QY and blue-shift in photoluminescence spectra after coating ZnS on surface AISe core NCs are rationalised by the formation of the alloyed structure and passivation of surface states. With their outstanding luminescent properties, AISe core and AISe/ZnS core/shell NCs are very promising in designing emitters for solid-state lighting sources in the greenhouse and in-door farming and bio-related devices.