RESEARCH ON THE FLUID-INDUCED EXCITATION CHARACTERISTICS OF THE CENTRIFUGAL PUMP CONSIDERING THE COMPOUND WHIRL EFFECT

In order to study the correlation mechanism between the flow characteristics and the fluid-induced force under the compound whirl motion in the centrifugal pump, the RNG k-ε model is selected in this paper to simulate a low specific speed centrifugal pump with impeller eccentricity based on the N-S equation. The changes of fluid-induced force with impeller eccentricity and the unsteady flow characteristics of the internal flow field of centrifugal pump under different flow conditions and rotation speeds are investigated, and the relationship between the fluid-induced force of the impeller and the internal flow field characteristics is discussed. The results show that the trend of fluid-induced force and the pressure coefficient is similar. When the rotation speed changes and when the flow is similar, the pressure coefficient under different rotation speeds almost coincides. With the increase of impeller speed and impeller eccentricity, the dynamic and static interferences between the impeller and the volute tongue are more significant, the uneven distribution of the pressure around the impeller makes the internal flow of centrifugal pump more disordered and increases the fluid-induced force near the volute tongue. The research results can provide important reference value for accurately grasping the internal flow excitation principle of the centrifugal pump

Scientometric research and critical analysis of battery state-of-charge estimation

With the advent of lithium-ion batteries (LIBs) and electric vehicle (EV) technology, the research on the battery State-of-Charge (SoC) estimation has begun to rise and develop rapidly. In order to objectively understand the current research status and development trends in the field of battery SoC estimation, this work uses an advanced search method to analyse the literature in the field of battery SoC estimation from 2004 to 2020 in the Web of Science (WoS) database. We employed bibliometrics analysis methods to make statistics on the publication year, the number of publications, discipline distribution, journal distribution, research institutions, application fields, test methods, analysis theories, and influencing factors in the field of battery SoC estimation. With using the Citespace software, a total of 2946 relevant research literature in the field of battery SoC estimation are analyzed. The research results show that the publication of relevant research documents keeps increasing from 2004 to 2020 in the field of battery SoC estimation. The research topics focus on battery model, management system, LIB, and EV. The research contents mainly involve Kalman filtering, wavelet neural network, impedance, and model predictive control. The main research approaches include model simulation, charging and discharging data recording, algorithm improvement, and environmental test. The research direction is shown to be more and more closely related to computer science and even artificial intelligence (AI). Intelligence, visualization, and multi-method collaboration are the future research trends of battery SoC estimation

Stochastic Model Generation of Porous Rocks and Study on 2D Pore Morphology Influencing Rock Strength and Stiffness

With the increasing usage of porous rocks in engineering construction, their well-performed properties (e.g., permeability and heat insulation) have attracted increasing attention from researchers in engineering geology. In nature, the vesicles in porous rocks always exhibit irregularity in morphology. This article proposes a workflow combining photogrammetry and Fourier transform to accurately acquire, characterize, and regenerate the natural pore morphology of porous rocks, including four steps: 1) initially, several 3D digital models of volcanic porous rock surfaces are reconstructed through a photogrammetry system, and the hollow pores in the surface are split into assemblies; 2) then, the 3D pore assembly is projected to a 2D reference plane with each pore being recognized and extracted; 3) the contours of a single pore are processed based on discrete Fourier transform (DFT), and a series of Fourier descriptors (mainly consist of D2, D3, and D8) are then statistically analyzed; 4) an inverse discrete Fourier transform (IDFT) is then conducted to quantitatively reconstruct the pores. Based on the earlier processes, the pores are distributed in a numerical model (rock failure and process analysis code, RFPA2D), and uniaxial compression simulations are performed to further investigate the influences of porosity and pore morphology on rock strength and stiffness. Herein, we introduce significant Fourier descriptors (i.e., D2, D3, and D8) as representations of three levels of pore morphology. Thus, 12 groups of numerical simulations considering the impact of porosity, pore orientation, D2, D3, and D8 are conducted. Results show that the porosity exerts a first-order control on the mechanical properties of rocks, while the effect of pore orientation is related to D2. All of them closely match those typically observed in previous studies. Furthermore, these simulations also highlight the influence of detailed pore morphology, such as convex hulls and subtle zigzags characterized by D3 and D8, respectively, on the rock failure process, marking that a more complicated morphology (e.g., with more convex hulls) may result in a reduction in rock strength and Young’s modulus. The proposed study provides a novel perspective on natural pore morphology together with its influence on rock strength and stiffness

Auto-diagnosis of time-of-flight for ultrasonic signal based on defect peaks tracking model

With the popularization of humans working in tandem with robots and artificial intelligence (AI) by Industry 5.0, ultrasonic non-destructive testing (NDT)) technology has been increasingly used in quality inspections in the industry. As a crucial part of handling ultrasonic testing results–signal processing, the current approach focuses on professional training to perform signal discrimination but automatic and intelligent signal optimization and estimation lack systematic research. Though the automated and intelligent framework for ultrasonic echo signal processing has already exhibited essential research significance for diagnosing defect locations, the real-time applicability of the algorithm for the time-of-flight (ToF) estimation is rarely considered, which is a very important indicator for intelligent detection. This paper conducts a systematic comparison among different ToF algorithms for the first time and presents the auto-diagnosis of the ToF approach based on the Defect Peaks Tracking Model (DPTM). The proposed DPTM is used for ultrasonic echo signal processing and recognition for the first time. The DPTM using the Hilbert transform was verified to locate the defect with the size of 2–10 mm, in which the wavelet denoising method was adopted. With the designed mechanical fixture through 3D printing technology on the pipeline to inspect defects, the difficulty of collecting sufficient data could be conquered. The maximum auto-diagnosis error could be reduced to 0.25% and 1.25% for steel plate and pipeline under constant pressure, respectively, which were much smaller than those with the DPTM adopting the cross-correlation. The real-time auto-diagnosis identification feature of DPTM has the potential to be combined with AI in future work, such as machine learning and deep learning, to achieve more intelligent approaches for industrial health inspection

Cold tolerance identification of nine Rosa L. materials and expression patterns of genes related to cold tolerance in Rosa hybrida

Members of the Rosa genus have a high ornamental value, but their cultivation area is limited by their sensitivity to cold temperatures. The aim of this study was to evaluate the cold tolerance of a range of Rosa materials, and then determine which genes were related to cold tolerance. Nine Rosa materials were subjected to a cold treatment. To identify genes related to cold tolerance, R. hybrida was treated at −15°C for 10 min, and leaves collected before and after this treatment were collected for RNA-Seq analyses. The transcript profiles of four DEGs (POD17, NDUFA9, PMA1, and b-Amy1) in R. hybrida were determined by qRT-PCR at 0 h, 1 h, 2 h, and 3 h at −15°C. Nine Rosa materials were subjected to a cold treatment, and the most cold-tolerant materials were identified as those that showed the lowest levels of electrolyte leakage and the best recovery after 30 d of growth. The most cold-tolerant materials were Rosa hybrida, Rosa rugosa ‘Pingyin 12’, and Rosa rugosa. In total, 204 significantly differentially expressed genes (DEGs) were identified, of which 88 were significantly up-regulated and 116 were significantly down-regulated under cold conditions. Gene Ontology classification and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that the DEGs were enriched in 57 pathways, especially starch and sucrose metabolism, phenylpropane biosynthesis, MAPK signaling, fructose and mannose metabolism, and oxidative phosphorylation. By transcriptional analysis, PMA1, which was related to H+ ATPase activity, was continuously up-regulated, but the transcript levels of POD17, NDUFA9, and β-Amy1 fluctuated during the freezing treatment. This research uncovered scarce cold-resistant materials and layed the foundation for further research on the cold tolerance mechanism of Rosa plants and the breeding of cold-tolerant varieties

Miniature intravascular photoacoustic endoscopy with coaxial excitation and detection

Recent research pointed out that the degree of inflammation in the adventitia could correlate with the severity of atherosclerotic plaques. Intravascular photoacoustic endoscopy can provide the information of arterial morphology and plaque composition, and even detecting the inflammation. However, most reported work used a non-coaxial configuration for the photoacoustic catheter design, which formed a limited light-sound overlap area for imaging so as to miss the adventitia information. Here we developed a novel 0.9 mm-diameter intravascular photoacoustic catheter with coaxial excitation and detection to resolve the aforementioned issue. A miniature hollow ultrasound transducer with a 0.18 mm-diameter orifice in the center was successfully fabricated. To show the significance and merits of our design, phantom and ex vivo imaging experiments were conducted on both coaxial and non-coaxial catheters for comparison. The results demonstrated that the coaxial catheter exhibited much better photoacoustic/ultrasound imaging performance from the intima to the adventitia

Anion Dependent Self-Assembly of Polynuclear Cd-Ln Schiff Base Nanoclusters: NIR Luminescent Sensing of Nitro Explosives

Two types of polynuclear Cd-Ln complexes [CdLnL(NO3)Cl2(DMF)2] [Ln = La (1) and Nd (2)] and [Ln2CdL2(NO3)2(DMF)2](OH)2 [Ln = La (3) and Nd (4)] were constructed using a new Schiff base ligand which has a long backbone with two phenyl groups. The Schiff base ligands show a “twist” configuration in 1–4. The crystal structures show that the molecular dimensions of 3 and 4 are about 6 × 10 × 15 Å. The Cd-Nd complexes 2 and 4 exhibit the typical NIR luminescence of Nd3+. Interestingly, 4 shows the luminescent sensing of nitro explosives and exhibits a high sensitivity to 2-nitrophenol at the ppm level

Prognostic value and immune-infiltration pattern of FOXD3-AS1 in patients with glioma

Gliomas are difficult-to-treat brain tumors due to their aggressive nature, rapid proliferation, and high invasiveness (Zhang et al., J Cell Biochem, 2019, 120 (9), 15106–15118; Ge et al., Int J Biochem Cell Biol, 2021, 139, 106054). FOXD3-AS1 has been identified as an emerging potential target for tumor prediction and treatment in many studies (Qin et al., Front Oncol, 2021, 11, 688027). However, the utility of FOXD3-AS1 has not been reported in glioma patients (Li et al., Cancer Manag Res, 2021, 13, 9037–9048). The differential profiles of FOXD3-AS1 in TCGA–GBMLGG database were analyzed across clinical subgroups. The analysis of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) revealed that a high level of FOXD3-AS1 was associated with a poor prognosis and survival outcome. Based on the Cox regression analysis, FOXD3-AS1 was found to be a high-risk factor for glioma that affects prognosis outcomes independently. More importantly, because oxidative stress is closely linked to glioma prognosis, we focused on the potential mechanisms of six oxidative stress co-expressed genes with FOXD3-AS1. In addition, the predictive value of FOXD3-AS1 was determined for each clinical subgroup status. The ROC curve results showed that FOXD3-AS1 had a good predictive performance. A stratified clinicopathological subgroup analysis revealed that high expression of FOXD3-AS1 is associated with a poor prognosis. This also indicates a link between FOXD3-AS1 and tumorigenesis and prognosis, which has potential application value. Furthermore, the immune cell infiltration of FOXD3-AS1 and the signal marker correlation suggested that immune cell infiltration differed significantly between immune cell subsets. To the best of our knowledge, this is the first report to investigate FOXD3-AS1 in glioma and how it may modulate GBM and LGG immune microenvironments. Furthermore, FOXD3-AS1 was detected in tumor and paraneoplastic tissues using RT–qPCR. Transwell analysis verified the migration and invasion of the FOXD3-AS1 knockout group in vitro to a certain extent. In conclusion, FOXD3-AS1 can be used as a prognostic indicator for GBM and LGG, and it is closely related to immune infiltration and response to oxidative stress, which may contribute to the advancement of glioma immunotherapy research