Spread Parameter Research Articles

Impact of Zinc Application on Growth, Yield, and Quality of African Marigold in Semi-Arid Conditions

Marigold is a widely cultivated, hardy flower crop known for its adaptability. Among the various intercultural practices in marigold cultivation, foliar application of zinc plays a critical role in enhancing yield and quality, however, standardization of this practice is necessary to optimize commercial production. Hence, the investigation aimed to standardize foliar zinc application for improving productivity in African marigold (Pusa Narangi Gainda) at Rajasthan Agricultural Research Institute, Jaipur, during 2020-21, and 2021-22. Two concentrations of zinc sulphate (ZnSO₄), Z1 (0.2%), and Z2 (0.5%), were applied at 35 and 65 days after transplanting (DAT) in a factorial randomized block design with three replications. Results indicated that Z1 (ZnSO₄ 0.2%) was most effective in increasing plant height, and promoting early bud initiation, and flower opening, while Z2 (ZnSO₄ 0.5%) significantly enhanced plant spread, primary branching, leaf dimensions, plant biomass, root-to-shoot ratio, flower diameter, and yield parameters such as flower mass and number. Z2 also improved quality traits like chlorophyll and xanthophyll content. Statistical analysis revealed significant differences among treatments, suggesting that the application of ZnSO₄ at 0.5% may be recommended for optimizing growth, yield, and quality in commercial marigold cultivation, thereby enhancing productivity and profitability.

Effect of Powder Spreading Parameters on Laser Absorption Behavior and Processability of High‐Strength Aluminum Alloy Fabricated by Laser Powder Bed Fusion

Laser powder bed fusion (LPBF) of rare‐earth‐modified high‐strength aluminum alloys presents a novel approach for manufacturing complex components with enhanced structural performance, particularly in aerospace applications. This study fabricates Al–Mg–Sc–Zr specimens using various powder spreading parameters to explore their impact on laser processability. The investigation reveals that varying the powder layer thickness from 30 to 70 μm yields the smallest irradiation diameter of 135 μm at an optimal thickness of 50 μm, attributable to effective multiple reflections, high laser absorption rates, and stability. With an optimal laser power of 400 W, a scanning speed of 600 mm s−1, and a hatching spacing of 60 μm, the sample produced at 50 μm layer thickness achieves a relative density of 99.23%, a top surface roughness of 15.42 μm, and a refined grain size of 1.67 μm. Following aging at 325 °C for 4 h, this sample exhibits a tensile strength of 518 MPa and an elongation of 15.6%. The findings establish a theoretical basis for controlling the morphology and properties of high‐strength aluminum alloys in laser additive manufacturing.

Fuzzy Logic-Based Feedwater Controller for the Super Fast Reactor

Abstract Super fast reactor is a Generation IV reactor with water coolant at supercritical pressure. It has advantages of having high efficiency of about 44%, more economical and excellent safety features. Its last core design which adopted one heating in one coolant cycle, however, results a large density change along the fuel channels. It leads to a sensitive steam temperature change against a change of power which might mismatch with the flow change. The sensitivity should be reduced to maintain the structure integrity of the reactor components. A feedwater controller which based on fuzzy logic was used to reduce the sensitivity. Method of fuzzy-based control is applied. Two signals of the temperature and the power changes were taken as the inputs of the fuzzy controller, and change of the feedwater coolant flow was taken as the control output. Fuzzifications used triangular member functions with Tsukamoto fuzzy model for inferencing process. Two control parameters of member function spread and signal values which lead to fuzzy degree of 1 were optimized so that the criteria of outlet coolant temperature and the stability were fulfilled. Test results of the control system showed that the deviation of the water temperature at outlet side could be kept within the criteria when mismatch change of power and water flow happened. The temperature deviation could be supressed by using the fuzzy-based control.

Estimating the parameters of epidemic spread on two-layer random graphs: a classical and a neural network approach

In this paper, we propose and analyse various methods for estimating the infection parameter τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au $$\\end{document} in an SIR (susceptible-infected-recovered) epidemic spread model simulated on two-layer random graphs with a preferential attachment component. The statistics that can be used for the estimates is the number of susceptible and infected vertices. Our classical approach is based on the maximum likelihood method, while the machine learning approach uses a graph neural network (GNN). The underlying graph has a layer consisting of disjoint cliques (representing e.g. households) and a random second layer with a preferential attachment structure. Our simulation study reveals that the estimation is poorer at the beginning of the epidemic, for larger preferential attachment parameter of the graph, and for larger τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au $$\\end{document}. As for the neural networks, we find that dense networks offer better training datasets. Moreover, GNN perfomance is measured better using the l2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_2$$\\end{document} loss function rather than cross-entropy.

Effect of blade geometry on the powder spreading process in additive manufacturing

In powder-bed-based additive manufacturing, the quality of the powder bed is closely related to the geometry of the blade used during the powder spreading process. In this study, the spreading process with the vertical blade, inclined blade, and round blade with different radii was performed by discrete element method to investigate the effects of blade geometry on powder spreading. The results show that at the same spreading parameters, the round blade caused the highest density than inclined blade and vertical blade. Increasing the round blade radius can improve the packing density of the powder bed, but it has little effect on the uniformity. The increase in packing density is related to the transitional smoothness of the blade surface at the entrance of the powder bed. The smoother the shape transition of the blade surface at the powder bed entrance, the powders enter the powder bed more gently, so more powders enter the powder bed, resulting in higher packing density. The results may provide suggestions for improving the laser melting process.

Droplet impinging on sparse micropillar-arrayed non-wetting surfaces

Wettability of droplets and droplet impinging on sparse micropillar-arrayed polydimethylsiloxane (PDMS) surfaces were experimentally investigated. For droplets wetting on these surfaces, the contact line density model combining stability factor and droplet sagging depth was developed to predict whether the droplets were in the Wenzel or Cassie–Baxter wetting state. It was found that droplets on the sparser micropillar-arrayed PDMS surfaces were in the Wenzel wetting state, indicating that a complete rebound cannot happen for droplets impinging on these surfaces. For the case of droplets impinging on sparse micropillar-arrayed PDMS surfaces, it was found that there existed a range of impact velocity for bouncing droplets on the micropatterned surfaces with a solid fraction of 0.022. To predict the upper limit of impact velocity for bouncing droplets, a theoretical model considering the immersion depth of liquid into the micropillar structure was established to make the prediction, and the lower limit of impact velocity for bouncing droplets can be obtained by balancing kinetic energy with energy barrier due to contact angle hysteresis. In addition, the droplet maximum spreading parameter was fitted and found to follow the scale law of We1/4.

Investigation of Effects of Spreading Parameters on Powder Bed Quality in Additive Manufacturing

Powder bed-based additive manufacturing processes such as laser powder bed fusion, binder jetting, and electron beam melting are commonly utilized in various critical areas such as medical, aviation, and energy. Common to all these operations, the powders are first spread onto the built platform in a layer-by-layer fashion and selectively fused or bound with a suitable method. The quality of the process depends on several process parameters, including how the powders are spread onto the built platform. Powder spreading is an important step in these operations and can affect various process outputs. In this study, the powder spreading is numerically investigated using the discrete element method to determine the effects of the layer thickness, rotation, and transition velocities selected as parameters with a powder spreader roller. The relationship between powder spreading parameters and powder volume packing fraction was investigated using the 'Hertz-Mindlin and Johnson-Kendall-Robert’s (JKR) contact model considering the interactions between particle-particle and particle-built plate, has been added to the numerical model. A Design of Experiment combined with analysis of variance (ANOVA) was utilized to gain a broader understanding on the relationship between process parameters and green density and dynamic angle of repose.

Characteristics of concurrent flame spread over convex charring materials

In real forest fire scenarios, there are a large number of convex and concave terrains at the junction of flat land and slopes. In this paper, a typical charring material, kraft paper, is selected as the experimental sample, and the variation law of key characteristic parameters of flame spread over convex solid surface are investigated. The experimental results show that all the flame spread processes have obvious deceleration behaviors, and the influence mechanism of flame tangent angle on the flame spread deceleration of convex surfaces is revealed. The characteristic length of the pyrolysis zone shows a tendency of increasing and then decreasing with time. The variation curves of radiant heat flux present two peaks. Combining with the characteristic length, the reason for the occurrence of two peaks is explained. The exponential relationship between the instantaneous mass loss rate and the characteristic length of the pyrolysis zone is obtained. Based on the range of power exponents, the heat transfer controlling mechanism in the pyrolysis zone is classified into three categories for all the working conditions. Moreover, a piecewise power-law relationship between the dimensionless maximum flame height and the dimensionless heat release rate is established. The results of this study will fill the research gap of flame spread of solid materials with curved surfaces, and will be of great academic value for the improvement and development of theories on building and forest fire safety.

A Systematic Approach to Map and Evaluate the Wildfire Behavior at a Territorial Scale in the Northwestern Iberian Peninsula

In the current context of extreme wildfires, understanding fire behavior at a territorial level has proven crucial for territory planning. This type of analysis is usually conducted by analyzing past wildfire statistics. In this study, we forego the past information related to wildfires and analyze, instead, the behavior of the entire territory in the face of wildfires. This allows for the distribution of ignition points to be systematized and for typical and atypical weather scenarios to be considered. This analysis relies on the use of wildfire simulation software. Ignition points used for the simulations were distributed using a systematic 1 × 1 km grid throughout the whole study area. Wildfires were simulated for each ignition point using eight different weather scenarios representing both typical and atypical weather conditions. The fire behavior on the territory was analyzed using rate of spread and intensity parameters for each simulated wildfire. It was observed that this territory is extremely prone to large wildfires both in typical and atypical weather conditions and that there is a tendency for extreme behaviors to develop. Some features were identified as prevention issues that ought to be addressed. This study develops a strategy to evaluate, in a systematic manner, the response of the territory to the threat of wildfires.

Double-Swing Spring Origami Triboelectric Nanogenerators for Self-Powered Ocean Monitoring

Coastal areas often experience high population density and intense human activity owing to the considerable value of the ocean. Therefore, devices for monitoring marine disasters are crucial for ensuring the safety of human life. Herein, we develop hemispherical spring origami (SO) triboelectric nanogenerators (TENGs) (HSO-TENGs) for self-powered ocean wave monitoring. Optimization is performed using two approaches. First, swing machine experiments are conducted to investigate the monitoring performance of the HSO-TENGs regarding wave height and period with satisfactory accuracy. To increase power generation and monitoring accuracy, the internal inertia and centroid of gravity of the HSO-TENGs are optimized with respect to the structural parameters (i.e., magnet weight, hammer height, and external swing arm length). Second, numerical simulations are performed using the smoothed-particle hydrodynamics (SPH) method to determine the most suitable fixed condition for the HSO-TENGs for sensing wave changes. Subsequently, wave tank experiments are conducted on the HSO-TENGs to determine their ability to sense wave height, period, frequency, and direction. Tests related to supplying other sensors are also conducted. Eventually, the ability of the HSO-TENGs to monitor wave direction and spreading parameters is investigated in a numerical SPH circular wave tank. The results prove that the optimized HSO-TENGs can achieve powering and sensing through the same device.

Exploration of improved, roller-based spreading strategies for cohesive powders in additive manufacturing via coupled DEM-FEM simulations

Spreading of fine (D50 ≤20μm) powders into thin layers, such as required by layer-wise additive manufacturing (AM) processes, typically requires a mechanism such as a roller that provides adequate shear and compression to overcome the cohesive forces between particles. We explore improved, roller-based spreading strategies for highly cohesive powders using an integrated discrete element-finite element (DEM-FEM) framework. We find that optimal roller-based spreading, quantified by maximum packing density and uniformity of layer thickness, relies on a combination of surface friction of the roller and roller kinematics, e.g., counter-rotation or angular oscillation, that impart sufficient kinetic energy to break cohesive bonds between powder particles. However, excess rotation speed (or shear stress) can impart excessive kinetic energy to the powder causing ejection of particles and a non-uniform layer, suggesting the existence of a process window of optimal spreading parameters. Interestingly, the identified optimal parameters for both investigated roller kinematics, i.e., angular velocity for counter-rotation as well as angular frequency and amplitude for rotational oscillation, result in a very similar range of roller surface velocities, suggesting roller surface velocity as the critical kinematic parameter. When these conditions are chosen appropriately, layers with packing fractions beyond 50% are predicted for layer thicknesses as small as ∼2 times D90 of the exemplary cohesive powder, and the layer quality is robust with respect to substrate adhesion over a 10-fold range. The latter is an important consideration given the spatially varying substrate conditions in AM due to the combination of fused/bound and bare powder regions. As compared to counter-rotation, the proposed rotational oscillation kinematics are particularly attractive because they can overcome practical issues with mechanical runout of roller mechanisms (which limit their precision).

Design of Software Reliability Prediction using Radial Basis Function Networks with Nonlinear Analysis and Topological Considerations

This study presents a thorough methodology for predicting software reliability by employing Radial Basis Function Networks (RBFNs). By using machine learning methodologies such as Radial Basis Function Networks (RBFNs), software development teams are enabled to make well-informed decisions, optimize resource allocation, and proactively mitigate potential dependability concerns. Consequently, this results in improved software quality and heightened customer happiness. This methodology involves multiple stages, starting with data collection and preprocessing. We assemble a comprehensive dataset comprising historical software performance metrics, defect reports, and relevant development process information. After data cleansing and feature engineering, we split the dataset into training, validation, and testing subsets. The core of this approach lies in the construction and training of RBFNs. These neural networks consist of an input layer, a hidden layer with radial basis functions, and an output layer. The architecture parameters, particularly the number of hidden neurons and the spread parameter of the radial basis functions, are optimized through a systematic hyperparameter tuning process using the validation dataset. Upon achieving an optimal model configuration, we rigorously evaluate the RBFN predictive capabilities using the testing dataset.

A Study on Powder Spreading Quality in Powder Bed Fusion Processes Using Discrete Element Method Simulation

Powder deposition is a very important aspect of PBF-based additive manufacturing processes. Discrete Element Method (DEM) is commonly utilized by researchers to examine the physically complex aspects of powder-spreading methods. This work focuses on vibration-assisted doctor blade powder recoating. The aim of this work is to use experiment-verified DEM simulations in combination with Taguchi Design of Experiments (DoE) to identify optimum spreading parameters based on robust layer quality criteria. The verification of the used powder model is performed via angle of repose and angle of avalanche simulation–experiment cross-checking. Then, four criteria, namely layer thickness deviation, surface coverage ratio, surface root-mean-square roughness and true packing density, are defined. It has been proven that the doctor blade’s translational speed plays the most important role in defining the quality of the deposited layer. The true packing density was found to be unaffected by the spreading parameters. The vertical vibration of the doctor blade recoater was found to have a beneficial effect on the quality of the deposited layer. Ultimately, a weighted mean quality criteria analysis is mapped out. Skewness and kurtosis were proven to function as effective indicators of layer quality, showing a linear relation to the weighted means of the defined quality criteria. The specific weights that optimize this linearity were identified.

Planar dose calculation of electron therapy

Purpose. The aim of this study is to determine the planar dose distribution of irregularly-shaped electron beams at their maximum dose depth (z max) using the modied lateral build-up ratio (LBR) and curve-fitting methods. Methods. Circular and irregular cutouts were created using Cerrobend alloy for a 14 × 14 cm2 applicator. Percentage depth dose (PDD) at the standard source-surface-distance (SSD = 100 cm) and point dose at different SSD were measured for each cutout. Orthogonal profiles of the cutouts were measured at z max. Data were collected for 6, 9, 12, and 15 MeV electron beam energies on a VERSA HDTM LINAC using the IBA Blue Phantom2 3D water phantom system. The planar dose distributions of the cutouts were also measured at z max in solid water using EDR2 films. Results. The measured PDD curves were normalized to a normalization depth (d 0) of 1 mm. The lateral-buildup-ratio (LBR), lateral spread parameter (σ R (z)), and effective SSD (SSD eff ) for each cutout were calculated using the PDD of the open applicator as the reference field. The modified LBR method was then employed to calculate the planar dose distribution of the irregular cutouts within the field at least 5 mm from the edge. A simple curve-fitting model was developed based on the profile shapes of the circular cutouts around the field edge. This model was used to calculate the planar dose distribution of the irregular cutouts in the region from 3 mm outside to 5 mm inside the field edge. Finally, the calculated planar dose distribution was compared with the film measurement. Conclusions. The planar dose distribution of electron therapy for irregular cutouts at z max was calculated using the improved LBR method and a simple curve-fitting model. The calculated profiles were within 3% of the measured values. The gamma passing rate with a 3%/3 mm and 10% dose threshold was more than 96%.

Atomic wetting of oil droplets into hexagons and stripes

HypothesisPrevious studies showed that liquid droplets can be spherical caps or polygonal shapes on patterned surfaces. We hypothesize that these phenomena can be narrowed down to nanoscale and affecting liquid molecular wetting. We anticipate observing preferential wetting on the underlying substrate with atomic crystalline lattice. ExperimentsThis study explores the wetting behavior of oil nanodroplets deposited on highly ordered pyrolytic graphite (HOPG) with atomic force microscope (AFM). Oil droplets were scanned with hydrophobic and hydrophilic AFM tips in water in peak force mode AFM, carefully controlling the scanning force. Simple modeling was carried out using Surface Evolver to simulate how oil droplets wet on HOPG with molecular lattice. FindingsThe results showed two distinct wetting behaviors: the hexagonal nanodroplets and stripe nanometric films. In both cases, the droplets appear to wet preferentially along preferred orientations which reflect the atomic periodicity of the underlying substrate. This preferential wetting occurs because the atomic roughness is significant at the length scale of the nanodroplets, while the eventual outcome of the wetting (i.e. whether the droplet settles to a finite contact angle, or wets completely into a nanometric film) is dependent on the spreading parameter of the droplet-substrate system, independent of scanning direction.

Wave attenuation by three-dimensional circular floating sea ice: Regular and irregular waves

The evolution of ice conditions and wave patterns in polar water areas is complex, and studying the hydrodynamic response between sea ice and waves is crucial. In this study, the hydrodynamic response of sea ice in infinitely deep water is investigated by a sea ice scattering model based on linear potential flow and thin plate approximation theory. Building upon regular wave and sea ice scattering models, an irregular wave model was established and analyzed. This paper discusses the factors that influence sea ice resonance in a three-dimensional scattering model. It categorizes resonance phenomena into strong and weak based on mass and elasticity coefficients and provides a predictive function for identifying strong resonance points. Additionally, the study examines sea ice attenuation from an energy perspective. Research on sea ice in irregular waves indicates a negative correlation between the directional spreading parameter and wave attenuation. An increase in directional spreading parameter weakens the inhibitory effect on the high-frequency part of the waves. Increasing sea ice thickness enhances wave attenuation, exerting an inhibitory effect on waves in the high-frequency region.

Slump-flow channel test for evaluating the relations between spreading and rheological parameters of sediment mixtures

Understanding debris flow phenomena and modeling them effectively requires accurate estimation of their rheological parameters. This study introduces a simple approach defined as the “slump-flow channel test”, which employs a horizontal rectangular channel to evaluate these parameters. The results of slump-flow channel tests indicate that the spreading parameters (spread length, angle of reach, and time to final spread) of sediment mixtures are strongly influenced by their sediment fractions and rheological properties. An empirical analysis of the temporal evolution of the spread length and spread velocity was carried out employing both experimental and simulation results. The numerical simulation of the slump-flow channel tests was performed using the Flow-3D software. Both experimental and simulation results demonstrate that the spreading and the rheological parameters of sediment mixtures exhibit strong correlations and this implies that the rheological parameters of sediment mixtures can be evaluated indirectly using a simple slump-flow channel test.

Wave-induced residual response and liquefaction of a nonhomogeneous layered seabed

Numerical studies were conducted on the wave-induced residual liquefaction of a silt–coarse sand layered seabed. Fully dynamic soil equations and residual seabed response equations were incorporated into the development of a numerical model. The numerical results were compared with theoretical solutions and experimental data from previous studies. Relatively good agreement was found in this comparison, validating the reliability of the proposed numerical model. The present model was applied to systematically investigate the wave-induced residual response with a silt–coarse sand layered seabed. The effects of coverage thickness, permeability, Young’s modulus in the upper silt layer on the residual response of the seabed were carefully examined. Numerical simulations indicate that the potential liquefaction is prone to occur with low permeability of the upper silt layer and shallower water depth, and the effect of coverage thickness of the silt layer on pore pressure and liquefaction potential is determined by shear stress ratio (χ) and effective normalized spreading parameter (Se) which represent the “generation power” and “dissipation potential” for residual pore pressure. The performance of the pore pressure and liquefaction in the layered seabed is the result of a trade-off between two non-dimensional parameters.

Flexible Bayesian inference on partially observed epidemics.

Individual-based models of contagious processes are useful for predicting epidemic trajectories and informing intervention strategies. In such models, the incorporation of contact network information can capture the non-randomness and heterogeneity of realistic contact dynamics. In this article, we consider Bayesian inference on the spreading parameters of an SIR contagion on a known, static network, where information regarding individual disease status is known only from a series of tests (positive or negative disease status). When the contagion model is complex or information such as infection and removal times is missing, the posterior distribution can be difficult to sample from. Previous work has considered the use of Approximate Bayesian Computation (ABC), which allows for simulation-based Bayesian inference on complex models. However, ABC methods usually require the user to select reasonable summary statistics. Here, we consider an inference scheme based on the Mixture Density Network compressed ABC, which minimizes the expected posterior entropy in order to learn informative summary statistics. This allows us to conduct Bayesian inference on the parameters of a partially observed contagious process while also circumventing the need for manual summary statistic selection. This methodology can be extended to incorporate additional simulation complexities, including behavioural change after positive tests or false test results.

Utility of PSMA PET/CT for imaging ductal carcinoma of the prostate.

49 Background: Ductal carcinoma (DC) is the second most commonly encountered histologic variant of prostate cancer. Previous studies have described its molecular features and aggressive behavior, but few have explored the performance of PSMA PET/CT in the initial staging and follow-up of DC. Methods: To address this gap, we performed a single-institution retrospective analysis using the Mayo Clinic PSMA PET database. All patients receiving a PSMA PET/CT scan in the interval of January 1, 2021, to December 31, 2022, were eligible for inclusion. Cases were filtered and categorized by histology at the time of diagnosis to select for pure DAC and mixed ductal variants. Trained research personnel annotated disease- and treatment-related variables. A board-certified radiologist performed tumor burden segmentation with calculations of SUV max, total lesion SUV mean and volume, and total lesion uptake, and ascribed a miPSMA expression score. Results: We queried 1792 patients from our PSMA PET/CT registry and identified 32 (1.8%) patients with a pathologically confirmed DC, including 8 (25%) patients with pure ductal and 25 (75%) patients with mixed histology. The indication for PSMA PET/CT was biochemical progression or restaging for 29 (91%) patients and initial staging for 3 (9%) patients. The median (IQR) time from prostate cancer diagnosis to PSMA PET scan was 41.6 (11.5-64.7) months, during this time 50% (n= 16) of patients developed CRPC. At the time of the PSMA PET/CT scan, the median age was 70 years, the median (IQR) PSA was 0.5 ng/mL (0.2-2.6). The distribution of metastatic spread and quantitative imaging parameters from PSMA PET are shown in the Table. Conclusions: Despite low PSA at the time of imaging, PSMA PET/CT frequently detected high volume osseous and/or visceral metastases in patients with DC. However, it is noteworthy that more than 50% of patients with DC had a low miPSMA score (0-1). Additional studies are needed to better understand the performance of novel imaging modalities when evaluating variant prostate cancers. [Table: see text]