Obtaining precise and rapid crop height is essential to facilitate agricultural production services, field management, disaster monitoring, and yield assessment. With the capability to penetrate ...vegetation and record vertical structure information, Polarimetric Synthetic Aperture Radar (PolSAR) holds significant potential for application in vegetation height inversion. The Water Cloud Model (WCM) and its enhanced versions are extensively utilized for estimating crop heights from PolSAR data owing to their physical significance and simplicity. However, the method is not practical for stalk crops due to the neglect of double-bounce scattering considerations. Therefore, according to the growth characteristics of stalk crops, a three-component polarimetric coherent backscattering model considering crop target double-bounce scattering is established by simplifying the Random Volume over Ground (RVoG) coherent scattering model. The empirical coefficient is introduced to simplify the model into a semi-empirical for crop height inversion. The suitability of applying the RVoG-B three-component model for crop height inversion at the early stage in corn fields was assessed using Multi-temporal C-band PolSAR RADARSAT-2 data in three polarimetric channels. The results show that the HV channel exhibits superior potential in inverting the height of corn compared with the HH and the VV channels. The results of corn height inversion demonstrate that the RVoG-B three-component semi-empirical model performs effectively in estimating corn height, with its inversion accuracy having an RMSE ranging from 11.66cm to 24.51cm. This study demonstrates the potential application of the RVoG-B three-component semi-empirical model for inverting crop height at the early stage dominated by double-bounce scattering.
•5 new hybrid machine learning models applied to abutment scour depth prediction.•A standalone machine learning model and 2 empirical methods served as benchmarks.•4 different input scenarios are ...considered for the machine learning models.•Same input variable has a different effectiveness on different abutment shape.•The machine learning models substantially outperform empirical methods.
Complex vortex flow patterns around bridge piers, especially during floods, cause scour process that can result in the failure of foundations. Abutment scour is a complex three-dimensional phenomenon that is difficult to predict especially with traditional formulas obtained using empirical approaches such as regressions. This paper presents a test of a standalone Kstar model with five novel hybrid algorithm of bagging (BA-Kstar), dagging (DA-Kstar), random committee (RC-Kstar), random subspace (RS-Kstar), and weighted instance handler wrapper (WIHW-Kstar) to predict scour depth (ds) for clear water condition. The dataset consists of 99 scour depth data from flume experiments (Dey and Barbhuiya, 2005) using abutment shapes such as vertical, semicircular and 45° wing. Four dimensionless parameter of relative flow depth (h/l), excess abutment Froude number (Fe), relative sediment size (d50/l) and relative submergence (d50/h) were considered for the prediction of relative scour depth (ds/l). A portion of the dataset was used for the calibration (70%), and the remaining used for model validation. Pearson correlation coefficients helped deciding relevance of the input parameters combination and finally four different combinations of input parameters were used. The performance of the models was assessed visually and with quantitative metrics. Overall, the best input combination for vertical abutment shape is the combination of Fe, d50/l and h/l, while for semicircular and 45° wing the combination of the Fe and d50/l is the most effective input parameter combination. Our results show that incorporating Fe, d50/l and h/l lead to higher performance while involving d50/h reduced the models prediction power for vertical abutment shape and for semicircular and 45° wing involving h/l and d50/h lead to more error. The WIHW-Kstar provided the highest performance in scour depth prediction around vertical abutment shape while RC-Kstar model outperform of other models for scour depth prediction around semicircular and 45° wing.
In this study, accuracy and suitability of eleven models from three different categories for estimating daily solar radiation in Iran were evaluated. For this purpose, daily meteorological data of 23 ...stations in Iran which record solar radiation was used. The models consist of temperature-, sunshine-based and complex models. Furthermore, four new models, namely; P1, P2, P3 and P4 were developed in the present study. The models P1 and P2 estimate daily solar radiation based on daily range of temperature and, P3 and P4 models contribute more meteorological data. The models were evaluated based on, root mean squared error (RMSE), mean bias error (MBE), coefficient of determination (R2) and modeling efficiency (ME) criteria. The results indicated that despite almost all the studied models were able to estimate daily solar radiation with such a good accuracy, the sunshine user models (either single variable or complex) could perform better than the non-sunshine user models. Furthermore, the accuracy of the sunshine based models was improved when daily range of dry and wet bulb air temperature parameters were included in the models. In addition, P1 and P2 models were the most accurate temperature based models. In terms of complex models, the newly proposed models P3 and P4, and the existing model C4 were the top ranked models. In case of the single variable models also the sunshine based models N1 and N2 were the best performing models.
•Dissimilar square wake greatly improves the harvested mechanical power.•Similar wake at close spacing shows the best energy harvesting performance.•Electromagnetic coupling of the mechanical system ...is analytically simulated.•Dissimilar wakes at close spacing display comparable energy performance values.•Isolated oscillator has slightly higher energy preferences than dissimilar wakes.
In recent times, transverse Flow Induced Vibration (FIV) has emerged as a promising technique for energy harvesting from fluid motion. However, relatively low harnessed power and efficiency remain as major challenges. Although several studies on hydrokinetic energy harvesting of circular oscillators at the wake of similar cylinders are reported in the literature, their performance under the influence of an upstream body with dissimilar cross-section is still unexplored. In this study, the effects of sharp edge square and diamond wakes on the energy harvesting of downstream circular cylinders are investigated through combined experimental and analytical modelings. The effect of electromagnetic coupling on the performance of the system is examined by numerical solution of the coupled mechanical and electromagnetic equations. Semi-empirical models are employed to simulate the response of the circular oscillator at the optimum electromagnetic coupling coefficient. The results show that the dissimilar wake is capable of considerably increasing (around 200%) the mechanical power of the circular oscillator but, at the cost of lower efficiency at high flow rates. Multi Criteria Decision Making (MCDM) analysis is performed to identify the priority of the similar and dissimilar wakes in the energy harvesting improvement. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with subjective and Shanon’s entropy weight factors prove the overall advantages of the similar wake at close distances over the dissimilar upstream cylinder. The present study contributes to the appropriate implementation of the upstream interfering bodies as a method to increase the energy performance of the FIV harvesters.
Empirical models of supernova (SN) spectral energy distributions (SEDs) are widely used for SN survey simulations and photometric classifications. The existing library of SED models has excellent ...optical templates, but limited, poorly constrained coverage of ultraviolet (UV) and infrared (IR) wavelengths. However, both regimes are critical for the design and operation of future SN surveys, particularly at IR wavelengths that will be accessible with the James Webb Space Telescope and the Wide-Field Infrared Survey Telescope. We create a public repository of improved empirical SED templates using a sampling of Type Ia and core-collapse (CC) photometric light curves to extend the Type Ia parameterized SALT2 model and a set of SN Ib, SN Ic, and SN II SED templates into the UV and near-IR. We apply this new repository of extrapolated SN SED models to examine how future surveys can discriminate between CC and Type Ia SNe at UV and IR wavelengths, and present an open-source software package written in Python, SNSEDextend, that enables users to generate their own extrapolated SEDs.
Abstract
Ly
α
emission is widely used to detect and confirm high-redshift galaxies and characterize the evolution of the intergalactic medium (IGM). However, many galaxies do not display Ly
α
...emission in typical spectroscopic observations, and intrinsic Ly
α
emitters represent a potentially biased set of high-redshift galaxies. In this work, we analyze a set of 703 galaxies at 2 ≲
z
≲ 3 with both Ly
α
spectroscopy and measurements of other rest-frame ultraviolet and optical properties in order to develop an empirical model for Ly
α
emission from galaxies and understand how the probability of Ly
α
emission depends on other observables. We consider several empirical proxies for the efficiency of Ly
α
photon production, as well as the subsequent escape of these photons through their local interstellar medium. We find that the equivalent width of metal-line absorption and the O3 ratio of rest-frame optical nebular lines are advantageous empirical proxies for Ly
α
escape and production, respectively. We develop a new quantity,
, that combines these two properties into a single predictor of net Ly
α
emission, which we find describes ∼90% of the observed variance in Ly
α
equivalent width when accounting for our observational uncertainties. We also construct conditional probability distributions demonstrating that galaxy selection based on measurements of galaxy properties yield samples of galaxies with widely varying probabilities of net Ly
α
emission. The application of the empirical models and probability distributions described here may be used to infer the selection biases of current galaxy surveys and evaluate the significance of high-redshift Ly
α
(non)detections in studies of reionization and the IGM.
Microbially induced carbonate precipitation (MICP) stands as a potent technique for remediating soils contaminated with heavy metals. However, the lack of efficient methods to detect the efficacy of ...MICP necessitates the use of electrical resistivity as an indicator. Consequently, an empirical model was devised to assess the strength and lead curing rate of the remediated soil. Through resistivity tests and microscopic experiments, it became evident that water content and lead contamination concentration exerted an influence on the electrical resistivity of the soil. Remarkably, the MICP technology led to a significant increase in the electrical resistivity of the remediated soil. This phenomenon can be attributed to the immobilization of lead ions within the contaminated soil, which consequently alters the soil’s pore structure, thereby resulting in noticeable modifications in electrical resistivity. The empirical model further revealed a linear correlation between the strength of the remediated soil and its electrical resistivity. As the electrical resistivity increased from 1.09 to 8.71 Ω m, the strength of the soil improved from 175 to 1070 kPa. Additionally, a multifactor linear framework elucidated the interrelation between the lead curing rate and water content, primary lead contamination concentration, and electrical resistivity. The rate of lead solidification showed a positive correlation with water content but exhibited a negative correlation with both the initial concentration of heavy metal pollutants and the electrical resistivity. Notably, the highest rate of lead curing rate, reaching 90.89%, was observed at a water content of 16.1%, a pollutant concentration of 100 mg/kg, and an electrical resistivity of 1.54 Ω m. These findings firmly establish electrical resistivity as an effective means of evaluating the remediation effect of MICP, thereby providing a theoretical foundation for assessing the impact of MICP technology in the field.
•Review of the correlations and models for the effective thermal conductivity of metal foams.•The illustrated models are validated against the experimental data available in the literature.•For the ...models with empirical constants, a new calibration of the parameters is illustrated.•A revised/implemented version of some of the existing correlations is presented.•The analysis is valid for high porosity Al foams, with air and water as saturating media.
Open cell metal foams are good candidates for augmenting the thermal performance of heat sinks and compact heat exchangers, with the added benefits of lighter and more compact equipments. Under this perspective, an estimation of the effective thermal conductivity of the medium is fundamental in order to properly design a metal foam heat transfer device. In this paper, a review of the empirical correlations and the theoretical models published in the literature for the prediction of the effective thermal conductivity is presented. In order to test the goodness of the illustrated models, a validation has been performed with the experimental data available in the literature for aluminum foams, for both air and water as working fluids and porosity higher than 0.89. For the models involving empirical or fitting constants, these parameters have been calibrated against the available experimental values, thus to enhance the predicting capability of the models. In addition, the mathematical formulation of some of the existing correlations has been revised and some efficient alternatives are suggested.
Abstract
We present the current state of models for the
z
∼ 3 carbon monoxide (CO) line intensity signal targeted by the CO Mapping Array Project (COMAP) Pathfinder in the context of its early ...science results. Our fiducial model, relating dark matter halo properties to CO luminosities, informs parameter priors with empirical models of the galaxy–halo connection and previous CO (1–0) observations. The Pathfinder early science data spanning wavenumbers
k
= 0.051–0.62 Mpc
−1
represent the first direct 3D constraint on the clustering component of the CO (1–0) power spectrum. Our 95% upper limit on the redshift-space clustering amplitude
A
clust
≲ 70
μ
K
2
greatly improves on the indirect upper limit of 420
μ
K
2
reported from the CO Power Spectrum Survey (COPSS) measurement at
k
∼ 1 Mpc
−1
. The COMAP limit excludes a subset of models from previous literature and constrains interpretation of the COPSS results, demonstrating the complementary nature of COMAP and interferometric CO surveys. Using line bias expectations from our priors, we also constrain the squared mean line intensity–bias product,
Tb
2
≲ 50
μ
K
2
, and the cosmic molecular gas density,
ρ
H2
< 2.5 × 10
8
M
⊙
Mpc
−3
(95% upper limits). Based on early instrument performance and our current CO signal estimates, we forecast that the 5 yr Pathfinder campaign will detect the CO power spectrum with overall signal-to-noise ratio of 9–17. Between then and now, we also expect to detect the CO–galaxy cross-spectrum using overlapping galaxy survey data, enabling enhanced inferences of cosmic star formation and galaxy evolution history.
In Brazil, research related to the occurrence and prevention of debris flows is incipient when compared to the extent of the impacts caused by the phenomena. There is a need for further studies that ...consider susceptibility and hazard, especially in areas that are environmentally and socioeconomically vulnerable. This study aimed at assessing debris-flow hazard in the Rio das Pedras watershed, in Cubatão (State of São Paulo, Brazil), based on a set of different physiographic parameters (geomorphological, morphometric, geological) and in the application of empirical models. The hazard assessment was based on: (1) the evaluation of the history of events in the region; (2) the identification of the geomorphic controlling factors; (3) the estimation of the magnitude of a potential event; and (4) the identification of the elements at hazard. The results show that a debris-flow event in Rio das Pedras would more severely impact the Anchieta Highway (SP-150), the gas pipeline GASAN, the oil pipeline OSSP and the districts Pinhal do Miranda and Cota 95. These results highlight the relevance of geomorphological and geological parameters when estimating the extent of debris runoff, which is essential when defining the hazard in a debris-flow-prone watershed.
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