Two-dimensional Method Research Articles

MPFEM investigation on densification and mechanical structures during ferrous powder compaction

Metal powder compaction is a crucial process in powder metallurgy, significantly affecting the final properties of compacts. However, the quantitative characteristics of multi-scale mechanical structures and the microscopic densification behavior, taking into account the influence of friction conditions, remain unclear. This study utilises a two-dimensional multi-particle finite element method to analyse the ferrous powder compaction. The evolution of powder densification, powder deformation and multi-scale mechanical behaviour under different friction coefficient conditions are analyzed quantitatively and qualitatively. Results reveal that powder densification occurs in distinct stages, with lower friction coefficients promoting greater powder densification, as observed from relative density and coordination number. Additionally, as the axial strain increases, plastic strain gradually rises whilst roundness decreases. Higher friction coefficients are associated with higher equivalent plastic strain but lower powder roundness. The Von Mises stress exhibits different stages of increase with the increment of axial strain. Powders with lower friction coefficients exhibit lower levels of Von Mises stress. As axial strain increases, the number, length, strength and direction coefficient of force chains undergo different evolution processes. Force chains exhibit longer length, fewer numbers, lower strength and lower direction coefficients at lower friction coefficients.

A Novel Hydrogel Sponge for Three-Dimensional Cell Culture

Background/Objectives: Three-dimensional (3D) cell culture technologies allow us to overcome the constraints of two-dimensional methods in different fields like biochemistry and cell biology and in pharmaceutical in vitro tests. In this study, a novel 3D hydrogel sponge scaffold, composed of a crosslinked polyacrylic acid forming a porous matrix, has been developed and characterized. Methods: The scaffold was obtained via an innovative procedure involving thermal treatment followed by a salt-leaching step on a matrix-containing polymer along with a gas-forming agent. Based on experimental design for mixtures, a series of formulations were prepared to study the effect of the three components (polyacrylic acid, NaHCO3 and NaCl) on the scaffold mechanical properties, density, swelling behavior and morphological changes. Physical appearance, surface morphology, porosity, molecular diffusion, transparency, biocompatibility and cytocompatibility were also evaluated. Results: The hydrogel scaffolds obtained show high porosity and good optical transparency and mechanical resistance. The scaffolds were successfully employed to culture several cell lines for more than 20 days. Conclusions: The developed scaffolds could be an important tool, as such or with a specific coating, to obtain a more predictive cellular response to evaluate drugs in preclinical studies or for testing chemical compounds, biocides and cosmetics, thus reducing animal testing.

Unraveling Magnet Structural Defects in Permanent Magnet Synchronous Machines—Harmonic Diagnosis and Performance Signatures

Rare-earth-based permanent magnets (PMs) have a vital role in numerous sustainable energy systems, such as electrical machines (EMs). However, their production can greatly harm the environment and their supply chain monopoly presents economic threats. Alternative materials are emerging, but the use of rare-earth PMs remains dominant due to their exceptional performance. Damage to magnet structure can cause loss of performance and efficiency, and propagation of cracks in PMs can result in breaking. In this context, prolonging the service life of PMs and ensuring that they remain damage-free and suitable for re-use is important both for sustainability reasons and cost management. This paper presents a new harmonic content diagnosis and motor performance analysis caused by various magnet structure defects or faults, such as cracked or broken magnets. The proposed method is used for modeling the successive physical failure of the magnet structure in the form of crack formation, crack growth, and magnet breakage. A surface-mounted permanent magnet synchronous motor (PMSM) is studied using simulation in Ansys Maxwell software (Version 2023), and different cracks and PM faults are modeled using the two-dimensional finite element method (FEM). The frequency domain simulation results demonstrate the influence of magnet cracks and their propagation on EM performance measures, such as stator current, distribution of magnetic flux density, back EMF, flux linkage, losses, and efficiency. The results show strong potential for application in health monitoring systems, which could be used to reduce the occurrence of in-service failures, thus reducing the usage of rare-earth magnet materials as well as cost.

Research into the Influence Mechanisms of Visual-Comfort and Landscape Indicators of Urban Green Spaces

Urban green spaces play a crucial role in providing social services and enhancing residents’ mental health. It is essential for sustainable urban planning to explore the relationship between urban green spaces and human perceptions, particularly their visual comfort. However, most current research has analyzed green spaces using two-dimensional indicators (remote sensing), which often overlook human visual perceptions. This study combined two-dimensional and three-dimensional methods to evaluate urban green spaces. Additionally, the study employed machine learning to quantify residents’ visual comfort in green-space environments and explored the relationship between green spaces and human visual perceptions. The results indicated that Kitakyushu exhibited a moderate FCV and an extremely low Green View Index (GVI). Yahatanishi-ku was characterized as having the highest visual comfort. Tobata-ku demonstrated the lowest visual comfort. Natural, GVI, openness, enclosure, vegetation diversity, landscape diversity, and NDBI were positively correlated with visual comfort. FCV and ENVI were negatively correlated with visual comfort. Vegetation diversity had the most impact on improving visual comfort. By integrating remote sensing and street-view data, this study introduces a methodology to ensure a more holistic assessment of green spaces. Urban planners could use it to better identify areas with insufficient green space or areas that require improvement in terms of green-space quality. Meanwhile, it could be helpful in providing valuable input for formulating more effective green-space policies and improving overall urban environmental quality. The study provides a scientific foundation for urban planners to improve the planning and construction of healthy and sustainable cities.

Significant feature suppression and cross-feature fusion networks for fine-grained visual classification

The technique of extracting different distinguishing features by locating different part regions to achieve fine-grained visual classification (FGVC) has made significant improvements. Utilizing attention mechanisms for feature extraction has become one of the mainstream methods in computer vision, but these methods have certain limitations. They typically focus on the most discriminative regions and directly combine the features of these parts, neglecting other less prominent yet still discriminative regions. Additionally, these methods may not fully explore the intrinsic connections between higher-order and lower-order features to optimize model classification performance. By considering the potential relationships between different higher-order feature representations in the object image, we can enable the integrated higher-order features to contribute more significantly to the model’s classification decision-making capabilities. To this end, we propose a saliency feature suppression and cross-feature fusion network model (SFSCF-Net) to explore the interaction learning between different higher-order feature representations. These include (1) an object-level image generator (OIG): the intersection of the output feature maps of the last two convolutional blocks of the backbone network is used as an object mask and mapped to the original image for cropping to obtain an object-level image, which can effectively reduce the interference caused by complex backgrounds. (2) A saliency feature suppression module (SFSM): the most distinguishing part of the object image is obtained by a feature extractor, and the part is masked by a two-dimensional suppression method, which improves the accuracy of feature suppression. (3) A cross-feature fusion method (CFM) based on inter-layer interaction: the output feature maps of different network layers are interactively integrated to obtain high-dimensional features, and then the high-dimensional features are channel compressed to obtain the inter-layer interaction feature representation, which enriches the output feature semantic information. The proposed SFSCF-Net can be trained end-to-end and achieves state-of-the-art or competitive results on four FGVC benchmark datasets.

Separation and Characterization of Wenjin Tongluo San Essential Oil with a Comprehensive Chromatographic Separation

The essential oil components of traditional Chinese medicine in-hospital preparation were complex, and one-dimensional chromatographic separation was difficult to completely separate them due to the limited peak capacity. This study was carried out to establish a comprehensive two-dimensional chromatographic separation and analysis method based on countercurrent chromatography (CCC) and gas chromatography (GC). In this paper, we focused on the separation of the essential oil of the traditional Chinese medicine in-hospital preparation Wenjing Tongluo San by CCC × GC, and explored the orthogonality between the two chromatographic techniques to provide the new technical support for the screening of the active ingredients. A solvent system composed of n-hexane-ethyl acetate-methanol-water (9.5:0.5:8.5:1.5, v/v) was chosen for the first-dimensional CCC separation. All the fractions collected from CCC were transferred to GC for plotting two-dimensional contours map. The calculated capacity of the two-dimensional separation system exceeded 3000, which was 8 times more than that of the one-dimensional separation system. High orthogonality (r = 0.42) and spatial coverage factor (70.42%) were obtained. Meanwhile, all the fractions were identified by GC-MS. Our research provided a new methodology for separating essential oils in traditional Chinese medicine as well as an approach for evaluating the quality of traditional Chinese medicinal in-hospital preparation based on two-dimensional chromatographic fingerprints.

Flow features induced by a rod-shaped microswimmer and its swimming efficiency: a two-dimensional numerical study

Abstract The swimming performance of rod-shaped microswimmers in a channel was numerically investigated using the two-dimensional lattice Boltzmann method (LBM). We considered variable-length squirmer rods—assembled from circular squirmer models with self-propulsion mechanisms—and analyzed the effects of the Reynolds number (Re), the aspect ratio (e), the squirmer-type factor (b), and the blockage ratio (κ) on swimming efficiency (η) and power expenditure (P). The results show no significant difference in power expenditure between pushers (microswimmers propelled from the tail) and pullers (microswimmers propelled from the head) at low Reynolds numbers adopted in this study. However, the swimming efficiency of pushers surpasses that of pullers. Moreover, as the degree of channel blockage increases (i.e., κ increases), the squirmer rod consumes more energy while swimming, and its swimming efficiency also increases, clearly reflected when e ≤ 3. Notably, squirmer rods with a larger aspect ratio e and a b value approaching 0 can achieve high swimming efficiency with lower power expenditure. The advantages of self-propelled microswimmers are manifested when e ＞ 4 and b = ±1, where the squirmer rod consumes less energy than a passive rod driven by an external field. These findings underscore the potential for designing more efficient microswimmers by carefully considering the interactions between the microswimmer geometry, propulsion mechanism, and fluid dynamic environment.

Turbulence characteristics of non-spherical isolated particles with different flatness on a rough bed surface

The transport of non-spherical particles on bed is significantly influenced by flow dynamics and particle shape. To study the impact of changes in the flatness of isolated bed particles on the surrounding flow characteristics, we prefabricated three isovolumetric particles with varying levels of flatness and analyzed the flow field around them using two-dimensional particle image velocimetry measurement methods. The results show that the presence of the particles significantly alters the turbulence parameters of the surrounding flow. Specifically, the influence extends up to 1D upstream of the particles, 0.5D above the particle tops, and throughout most of the downstream region, where D represents the equivalent particle diameter. The particles cause a reduction in Reynolds stress and turbulent kinetic energy in the near-bed upstream region, with a more pronounced effect observed for particles with lower flatness. Increased particle flatness is associated with a smaller difference in the longitudinal time-averaged velocity between upstream and downstream regions. In the wake region, particle flatness shows a negative correlation with Reynolds stress, longitudinal turbulence intensity, and turbulent kinetic energy, with this effect being more pronounced closer to the particles. Quadrant analysis indicates that ejection (Q2) and sweep (Q4) quadrant events remain dominant in the presence of particles, while particle flatness positively correlates with the frequency of outward (Q1) and inward (Q3) events in the wake region and negatively correlates with the frequency of Q2 and Q4 events. This study enhances our understanding of particle-fluid interactions, particularly the response relationship between non-spherical particles and turbulent mechanisms.

Research on sedimentation characteristics of squirmer in a power-law fluid.

Sedimentation characteristics of a squirmer in a power-law fluid within a vertical channel are studied numerically using the two-dimensional lattice Boltzmann method. The effects of swimming type (- 5 ≤ β ≤ 5), self-propelling strength (0.5 ≤ α ≤ 1.1), power-law indexes (0.5 ≤ n ≤ 1.5), and the density ratio of the squirmer to the fluid (γ = 1.01, 1.5 and 2.3) on the sedimentation of the squirmer are analyzed. Four settlement patterns are identified: steady falling in the center, downward along the wall, oscillating with large amplitude and oscillating around the centerline. The squirmer in the channel exhibits more fluctuations in shear-thinning (n < 1) and Newtonian (n = 1) fluids compared to shear-thickening fluids (n > 1). Additionally, a puller (β > 0) settles faster than a pusher (β < 0) in shear-thinning and Newtonian fluids. Puller generates flow towards their head and away from their tail, exhibiting small amplitude oscillations. Pushers exhibit higher amplitude oscillations throughout the channel, creating flow towards their tail and away from their head. At lower γ, the fluctuation of the squirmer is less pronounced compared to higher γ.

Validation of an Enhanced Drinking Water Temperature Model during Distribution

Drinking water temperatures are expected to increase in the Netherlands due to climate change and the installation of district heating networks as part of the energy transition. To determine effective measures to prevent undesirable temperature increases in drinking water, a model was developed. This model describes the temperature in the drinking water distribution network as a result of the transfer of heat from the climate and above and underground heat sources through the soil. The model consists of two coupled applications. The extended soil temperature model (STM+) describes the soil temperatures using a two-dimensional finite element method that includes a drinking water pipe and two hot water pipes coupled with a micrometeorology model. The extended water temperature model (WTM+) describes the drinking water temperature as a function of the surrounding soil temperature (the boundary temperature resulting from the STM+), the thermal sphere of influence where the drinking water temperature influences the soil temperature, and the hydraulics in the drinking water network. Both models are validated with field measurements. This study describes the WTM+. Previous models did not consider the cooling effect of the drinking water on the surrounding soil, which led to an overestimation of the boundary temperature and how quickly the drinking water temperature reaches this boundary temperature. The field measurements show the improved accuracy of the WTM+ when considering one to two times the radius of the drinking water pipe as the thermal sphere of influence around the pipe.

A study of the effects of housing tongue design on radial turbine performance

The nozzleless volute housings can generate non-uniform flow distributions to the downstream radial turbine rotors, which not only affects turbine aerodynamic performance but also poses a threat to the fatigue life of the rotors. It is believed that the housing tongue is the main factor in generating this non-uniformity. Tongue design is based on experience and the geometric parameters of tongue, such as the distance between the tongue and rotor, the thickness of the tongue, and tongue shape are to be specified in the design. A few studies on housing tongue can be found in the literature, but in these investigations of the influences of tongue geometric parameters, factors such as mass flow rate and volute A/R distribution were not kept constant, thus introducing additional factors and reducing the persuasiveness of the results. Therefore, three new housings with different tongue-rotor distances are designed with a two-dimensional method for comparative CFD studies. The results indicate that when the mass flow of the turbines is kept, the distance between the tongue and the rotor has little impact on the turbine efficiency (about 0.1%), while the blade excitation forces from the housing increase with the decrease of the distance by more than 50%. Two further new housings are then created by modifying the housing inlet pipe to minimize tongue thickness, one of the housings is more practical with a short and thin tongue. CFD results indicate 0.2%∼0.4% improvement of turbine efficiency and reduction of housing excitation forces by more than 50% using these two thin tongue housings.

Maximizing torque per volume index for SHESM based on two-dimensional method and meta-heuristic optimization algorithms

In this paper, a permanent magnet synchronous machine (PMSM) with an auxiliary winding (AW) on the rotor is analyzed by two-dimensional approach. This PMSM with AW (AWPMSM) can be used in many applications such as propulsion system, aircraft and traction because it includes rotor flux control capability. First, the magnetic field in different parts of AWPMSM is calculated based on Maxwell equations. Then, as a consequence of the magnetic field, the torque components, including cogging, reluctance, electromagnetic and instantaneous torque are computed. Next, torque-speed characteristic has been investigated. This AWPMSM can be located in the flux weakening mode in two ways, first one is to attenuate the rotor field by changing the direction of the AW field and the other one is to adjust the armature current angle, both of them have been investigated. After that, the overload capability and temperature effects have been analyzed. Finally, using the meta-heuristic algorithms such as genetic algorithm, particle swarm optimization, differential evolution and teaching learn base optimization the dimensions of AWPMSM and the initial angle of the rotor are determined in such a way that the torque-to-volume ratio is maximized. The influences of the type of armature winding and the magnetization patterns have also been investigated. The results obtained by the two-dimensional method have been confirmed numerically.

Therapeutic effect of three-dimensional hanging drop cultured human umbilical cord mesenchymal stem cells on osteoarthritis in rabbits

BackgroundMesenchymal stem cells (MSCs) have shown a positive effect on Osteoarthritis (OA), but the efficacy is still not significant in clinical. Conventional two-dimensional (2D) monolayer culture method is prone to cause MSCs undergoing replication senescence, which may affect the functions of MSCs. Three-dimensional (3D) culture strategy can sustain cell proliferative capacity and multi-differentiation potential. This study aimed to investigate the therapeutic potential of human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) cultured by 3D hanging drop method on OA.MethodshUC-MSCs were isolated from umbilical cord and cultured by 3D hanging drop method for 48 h. Scanning electron microscopy (SEM) was used to observe gross morphology 2D and 3D hUC-MSCs. Transcriptome comparison of gene expression differences between 2D and 3D hUC-MSCs. GO enrichment analysis, KEGG pathway enrichment analysis and GSEA enrichment analysis were used to analyze the impact of 3D hanging drop culture on the biological functions of hUC-MSCs. Female New Zealand rabbits (n = 12) were divided into 4 groups: Normal group, Model group, 2D hUC-MSCs treatment group and 3D hUC-MSCs treatment group. After 8 weeks, the gross and histological appearance of the cartilage was evaluated by safranin O-fast green staining and Mankin scoring system. The expression of type I collagen and type II collagen was detected by immunohistochemistry. The levels of IL-6, IL-7, TNFα, TGFβ1 and IL-10 in the knee joint fluid were tested by ELISA.Results3D hanging drop culture changed cell morphology but did not affect phenotype. The MSCs transcriptome profiles showed that 3D hanging drop culture method enhanced cell-cell contact, improved cell responsiveness to external stimuli and immunomodulatory function. The animal experiment results showed that hUC-MSCs could promote cartilage regeneration compared with Model group. 3D hUC-MSCs treatment group had a higher histological score and significantly increased type II collagen secretion. In addition, 3D hUC-MSCs treatment group increased the expression of anti-inflammatory factors TGFβ1 and IL-10.ConclusionThe above experimental results illustrated that 3D hanging drop culture method could enhance the therapeutic effect of hUC-MSCs, and showed a good clinical application prospect in the treatment of OA.

Comparison of two-dimensional Grummons’ analysis and three-dimensional asymmetry index measurement in diagnosis of dentocraniofacial asymmetry

Background Dentocraniofacial asymmetry is a common condition that affects many individuals. Accurate diagnosis of this condition is essential for effective treatment planning. Aim This study aimed to compare the diagnosis of dentocraniofacial asymmetry using two-dimensional and three-dimensional methods. Methods A cross-sectional, observational study was conducted at the Orthodontic Specialist Clinic of the Dental Hospital Faculty of Dentistry, University of Indonesia from March to April 2023. The study included 15 patients who had not undergone orthodontic treatment and were diagnosed with dentocraniofacial asymmetry. The study compared the results of diagnosing asymmetry in 15 different facial features, including the anterior nasal spine, upper and lower first incisors, pterygomaxillary fissure, orbita, menton, porion, upper and lower first molars, coronoid process, gonion, zygoma, latero nasale, and jugulare. Results The study found that there was no significant difference in the diagnosis of dentocraniofacial symmetry between the two- and three-dimensional methods across all 15 parameters measured. The researchers used Fisher's Exact Test to compare the proportion between dependent variables and found that the p-value was greater than 0.05, indicating that there was no significant difference in the diagnosis of dentocraniofacial symmetry between the two methods. The study also used Kappa Cohen analysis to measure the strength of agreement between the diagnosis of dentocraniofacial symmetry of the two-dimensional and three-dimensional methods on each parameter. Conclusion The findings of this study suggest that both two-dimensional and three-dimensional methods are equally effective in diagnosing dentocraniofacial asymmetry. This information may be useful for orthodontists in deciding which method to use when diagnosing dentocraniofacial asymmetry.

Probing inhomogeneous cuprate superconductivity by terahertz Josephson echo spectroscopy

AbstractInhomogeneities crucially influence the properties of quantum materials, yet methods that can measure them remain limited and can access only a fraction of relevant observables. For example, local probes such as scanning tunnelling microscopy have documented that the electronic properties of cuprate superconductors are inhomogeneous over nanometre length scales. However, complementary techniques that can resolve higher-order correlations are needed to elucidate the nature of these inhomogeneities. Furthermore, local tunnelling probes are often effective only far below the critical temperature. Here we develop a two-dimensional terahertz spectroscopy method to measure Josephson plasmon echoes from an interlayer superconducting tunnelling resonance in a near-optimally doped cuprate. The technique allows us to study the multidimensional optical response of the interlayer Josephson coupling in the material and disentangle intrinsic lifetime broadening from extrinsic inhomogeneous broadening for interlayer superconducting tunnelling. We find that inhomogeneous broadening persists up to a substantial fraction of the critical temperature, above which this is overcome by the thermally increased lifetime broadening.

Application of Single Cell Type-Derived Spheroids Generated by Using a Hanging Drop Culture Technique in Various In Vitro Disease Models: A Narrow Review.

Cell culture methods are indispensable strategies for studies in biological sciences and for drug discovery and testing. Most cell cultures have been developed using two-dimensional (2D) culture methods, but three-dimensional (3D) culture techniques enable the establishment of in vitro models that replicate various pathogenic conditions and they provide valuable insights into the pathophysiology of various diseases as well as more precise results in tests for drug efficacy. However, one difficulty in the use of 3D cultures is selection of the appropriate 3D cell culture technique for the study purpose among the various techniques ranging from the simplest single cell type-derived spheroid culture to the more sophisticated organoid cultures. In the simplest single cell type-derived spheroid cultures, there are also various scaffold-assisted methods such as hydrogel-assisted cultures, biofilm-assisted cultures, particle-assisted cultures, and magnet particle-assisted cultures, as well as non-assisted methods, such as static suspension cultures, floating cultures, and hanging drop cultures. Since each method can be differently influenced by various factors such as gravity force, buoyant force, centrifugal force, and magnetic force, in addition to non-physiological scaffolds, each method has its own advantages and disadvantages, and the methods have different suitable applications. We have been focusing on the use of a hanging drop culture method for modeling various non-cancerous and cancerous diseases because this technique is affected only by gravity force and buoyant force and is thus the simplest method among the various single cell type-derived spheroid culture methods. We have found that the biological natures of spheroids generated even by the simplest method of hanging drop cultures are completely different from those of 2D cultured cells. In this review, we focus on the biological aspects of single cell type-derived spheroid culture and its applications in in vitro models for various diseases.

High repetition-rate laser-induced breakdown spectroscopy combined with two-dimensional correlation method for analysis of sea-salt aerosols

Laser-induced breakdown spectroscopy (LIBS) offers a tantalizing glimpse into real-time, on-the-spot aerosol analysis. Yet, the reliance on traditional lasers, with their limitations in energy and frequency, hampers optimal sample handling, dissociation, and excitation. To address those challenges, we propose a novel tactic: utilize a high repetition-rate (rep.-rate) laser with low pulse energy in combination with the two-dimensional correlation (2D-corr.) technique for sea-salt aerosols analyses. By examining the emission patterns from both the laser pulse train and individual pulses, we recognize distinctive analyte-specific rep.-rate responses, which allowed spectral reconstruction of analytes, avoiding background interferences. This discovery enabled the rep.-rate modulation for a 2D-corr. spectroscopy workflow. Consequently, we successfully differentiated between particle-related and air-species-related spectral components, obviating expensive spectrometers or intensified image detectors. For instance, the Na I at 589 nm stemming from aerosols exhibited an entirely different correlation contribution compared to O I at 777 nm, resulting in reconstructed clean aerosol-spectra without spectral peaks originated from air species. This 2D-corr. aerosol LIBS approach shows promising analytical potential streamlining aerosol particle analysis.

Research on the Depth Image Reconstruction Algorithm Using the Two-Dimensional Kaniadakis Entropy Threshold.

The photon-counting light laser detection and ranging (LiDAR), especially the Geiger mode avalanche photon diode (Gm-APD) LiDAR, can obtain three-dimensional images of the scene, with the characteristics of single-photon sensitivity, but the background noise limits the imaging quality of the laser radar. In order to solve this problem, a depth image estimation method based on a two-dimensional (2D) Kaniadakis entropy thresholding method is proposed which transforms a weak signal extraction problem into a denoising problem for point cloud data. The characteristics of signal peak aggregation in the data and the spatio-temporal correlation features between target image elements in the point cloud-intensity data are exploited. Through adequate simulations and outdoor target-imaging experiments under different signal-to-background ratios (SBRs), the effectiveness of the method under low signal-to-background ratio conditions is demonstrated. When the SBR is 0.025, the proposed method reaches a target recovery rate of 91.7%, which is better than the existing typical methods, such as the Peak-picking method, Cross-Correlation method, and the sparse Poisson intensity reconstruction algorithm (SPIRAL), which achieve a target recovery rate of 15.7%, 7.0%, and 18.4%, respectively. Additionally, comparing with the SPIRAL, the reconstruction recovery ratio is improved by 73.3%. The proposed method greatly improves the integrity of the target under high-background-noise environments and finally provides a basis for feature extraction and target recognition.

Design and analysis of a single-stage supersonic turbine with partial admission

Supersonic impulse turbines are commonly used to harvest waste heat from systems based on organic Rankine cycles, automotive applications, and gas-generator liquid rocket engines. This research aims to design and analyze a single-stage supersonic turbine with a rated power of approximately 440 KW. We present a comprehensive preliminary design roadmap followed by design parameters optimization. The preliminary sizing is carried out using one-dimensional flow analysis, while the blade geometrical design is performed using the two-dimensional method of characteristics. The turbine performance is then analyzed through numerical simulations on three-dimensional models. Comprehensive parametric analyses are conducted to examine the turbine performance sensitivity to changes in partial admission (PA), mean radius, and turbine blade height using three-dimensional sliding mesh techniques (SMT). The current analysis simulates the full turbine to capture PA effects, rather than focusing on a single periodic sector as is common in turbomachinery simulation practices. Different PA scenarios are investigated, emphasizing a single rotor passage over a complete rotor cycle in a partially admitted turbine, and examining its charging and discharging mechanisms. Flow tracking over such a blade shows that the turbine rotor exhibits compressor-like behavior over most of the unadmitted zone, contributing to efficiency drops and severe transients.

A novel framework of the lattice Boltzmann model for multilayer shallow water systems

This study proposes a novel framework of the lattice Boltzmann model for multilayer shallow water equations, considering the mass and momentum exchanges between layers (LABMSWE+). Compared with the original LABMSWE model consisting of N two-dimensional lattice Boltzmann method for shallow water equation (LABSWE) models, the new model includes 1+N LABSWE models. The singular LABSWE model with unit relaxation time is introduced to update the total water depth, and thus, the layer water depths can be obtained explicitly through the fixed layer ratios. The N-layer LABSWE models with the multiple-relaxation-time operator evolve the layer velocities. These two modules are coupled by the total water depth and depth-averaged velocities. The constructed model avoids the freely variable layer thicknesses, which is considered as the main source of the instability. In addition, the mass exchanges enable this model to simulate vertical circulation flows, which are beyond the application of the LABMSWE model. Several numerical tests are then conducted to validate the proposed model. The results show that it exactly satisfies the C-property. In addition, the central difference scheme is more stable and accurate than the upwind and nonequilibrium schemes in the computing of the mass exchanges. The numerical results have an excellent agreement with analytical solutions and reference data, while some unstable and nonphysical results are obtained by the original LABMSWE model. Moreover, the computational time is about 40%–60% of that for the MIKE3, a finite volume solver for the three-dimensional shallow water equations by the Danish Hydraulic Institute.