Frequency Curves Research Articles

Analysis of Extreme Rainfall Characteristics in 2022 and Projection of Extreme Rainfall Based on Climate Change Scenarios

In this study, we analyzed the characteristics of the heavy rainfall events that occurred in Seoul in 2022 and compared them with the projections of the representative concentration pathway (RCP). The analysis results indicated that climate change is ongoing. In this era of climate crisis, based on the shared socioeconomic pathway (SSP) data, we projected the 20-year frequency rainfall for South Korea at intervals of 1 day/24 h. Our results indicate that the maximum rainfall (with a 24 h duration) will increase by ~18% in the second half of the 21st century, compared to the current maximum rainfall. Finally, we projected the intensity–duration–frequency (IDF) curve for the infrastructure design of Seoul. According to the projected IDF curve, across all durations, the rainfall intensity was the strongest in the early 21st century, indicating that at present, we are in the midst of a climate crisis. Thus, it is important to develop and implement effective urban and river flood management measures to mitigate the current effects of climate change. Notably, our study can serve as a reference for future studies on climate change and help policymakers and decision-makers develop relevant policies and mitigation strategies related to the effects of climate change.

Vibration suppression of pipe conveying fluid using a nonlinear absorber in longitudinal direction

The article outlines the design of a nonlinear absorber that features cubic stiffness. The absorber was created for a pipe conveying fluid and was based on the internal resonance mechanism. To create the nonlinear absorber, a sliding mass oscillator was attached along to the pipe conveying fluid. Nonlinear equations were derived using Hamilton's principle. The flowing fluid was considered both as a constant value and a fluctuating term. To investigate the nonlinear behavior of the coupled pipe-absorber system, the direct multiple scales method was used. By selecting appropriate values of mass and stiffness for the absorber, the natural frequency of the absorber was tuned in three cases: 1–1, 2–1, and 3–1 internal resonance ratios between the natural frequency of the absorber and the first natural frequency of the pipe. The goal of the mechanism was to transfer energy from the pipe to the absorber, and the design was successful in achieving this. A saturation phenomenon was detected in the force modulation response at the three-to-one internal resonance. The results showed a reduction in amplitudes in both frequency and force response curves under the external primary resonance and pulsating flowing fluid in the supercritical regime. The nonlinear absorber has a good performance in a wide range of flow velocity and excitation. The accuracy of the results was verified using Galerkin and Finite difference methods.

The natural frequency estimation for a system composed of a beam and a spring-mass system

This study presents an approximate method for determining the natural frequency of a system composed of a beam and a two-degree-of-freedom spring-mass system. The expression for estimating the natural frequency is derived following the standard procedures of the forced vibration analysis of a beam. The results obtained using the current method are in good agreement with those obtained through the dynamic stiffness method, especially when the spring stiffness is large. The innovativeness of the current method is that it reveals the relevance between the natural frequency of the system, the natural frequency of the beam, and the mode shape data at the positions where the spring-mass system is attached to the beam. The method is potentially useful in the dynamic wheel-track interaction analysis because the train wheel is normally simplified as a spring-mass system with high spring stiffness. It may also be applied to natural frequency-based damage detection where an auxiliary spring-mass system is used. When the spring-mass system roves on the beam, the curve of natural frequency versus spring-mass system location would be relevant to the mode shape square which is sensitive to local damage.

Estimating IDF curves under changing climate conditions for different climate regions

Abstract Although climate models can highlight potential shifts in intensity–duration–frequency (IDF) curves, their limited geographical and temporal resolutions limit their direct use in predicting sub-daily heavy precipitation. To use global or regional model outputs to predict urban short-term precipitation, approaches that give the requisite level of spatial and temporal downscaling are required, and these processes remain one of the difficulties that have demanded intensive effort in recent years. Although no novel methods are given in this work, there are few studies in the literature that investigate the impact of climate change on the analysis and design of infrastructure-related engineering structures. Therefore, the purpose of this research is to determine the potential changes in IDF curves because of climate change. The equidistance quantile matching method was used to turn future rainfall forecast data from global climate models (HadGEM2-ES, MPI-ESM-MR, and GFDL-ESM2M) corresponding to RCP4.5 and RCP8.5 scenarios into standard duration rainfall data, and new IDF curves were generated. These IDF curves corresponded very well with those generated from observed data (R2 ≈ 1). The HadGEM2-ES model predicts up to a 25% rise in rainfall intensity, whereas the other two models expect up to a 50% drop.

Variation of Ionospheric Shortwave Absorption of the Extraordinary Wave

AbstractIn this study, associating with the A‐H formulation, we have developed a comprehensive ionospheric absorption model by incorporating the latest version of geomagnetic model, the atmospheric and ionospheric model as the background. Based on the absorption model, the ionospheric stratification theory is utilized to explore the trend of the total absorption for extraordinary (X) wave with frequency and elevation angle. We found that the factor of local time has a greater impact on the trend of total absorption variation than other factors—solar activity, season, and latitude, attributing to the variation of electron collision frequency. During the two different local times (daytime and night), the trends of the total absorption have distinct differences. In the daytime, it is worth noting that the reflection heights and the peaks of the absorption coefficient both mainly occur in Layers D and E. Therefore, the non‐deviative absorption dominates the variation of the total absorption. On the other hand, the occurrence of Pedersen ray results in inflexion points arising in the curves of absorption versus frequency or elevation angle. Another interesting phenomenon is the dominant role of deviative absorption at night. At night, the reflection heights mainly occur in Layer F, and the absorption coefficient of Layer F begins to exceed the peak levels of Layers D and E when the frequency or elevation angle is larger than certain values. Hence, the total absorption will grow as a result of the increase in deviative absorption with the increase in reflection height and absorption coefficient.

Extreme Rainfall Analysis for Development of Rainfall Intensity Duration Frequency Curves for Semiarid Region of Andhra Pradesh in India

Extreme Rainfall Analysis for Development of Rainfall Intensity Duration Frequency Curves for Semiarid Region of Andhra Pradesh in India

Derivation of the Rainfall Intensity- Duration- Frequency Curve for Erbil city, Using SCS II Method

Derivation of the Rainfall Intensity- Duration- Frequency Curve for Erbil city, Using SCS II Method

Three point mutations in AaCYP51 combined with induced overexpression of AaCYP51 conferred low-level resistance to mefentrifluconazole in Alternaria alternata

Tomato early blight is a significant disease that causes substantial losses to tomato yield and quality. Mefentrifluconazole, an isopropanol-azole subgroup of triazole fungicides, has been registered in China for controlling various plant diseases, including tomato early blight, grape anthracnose, and apple brown spot. However, limited information is available on the mefentrifluconazole resistance risk and mechanism in plant pathogens. The sensitivity to mefentrifluconazole of 122 isolates of Alternaria alternata, one of the causal agents of tomato early blight, collected from different provinces in China, was evaluated. The results showed a unimodal curve for the sensitivity frequency, with an average EC50 of 0.306 μg/mL. Through fungicide adaption, six resistant mutants (N4, N5, T4, T5, NG1, and NG10) were obtained from three parental isolates, with a mutation frequency of 3.28 × 10−4 and resistance factors ranging between 19 and 147. The survival fitness of the resistant mutants, except for NG1, was significantly lower than that of their parental isolates. Positive cross-resistance was observed between mefentrifluconazole and difenoconazole or fenbuconazole, whereas no cross-resistance was found with three non-DMI fungicides. Furthermore, three distinct point mutations were detected in the AaCYP51 protein of the resistant mutants: I300S in T4 and T5; A303T in N4, NG1, and NG10; and A303V in N5. Compared to the parental isolates, the AaCYP51 gene was overexpressed in all six resistant mutants when treated with mefentrifluconazole. In summary, the resistance risk of A. alternata to mefentrifluconazole was low, and point mutations and overexpression of the AaCYP51 gene were identified as contributing factors to mefentrifluconazole resistance in A. alternata.

Identification of the Sediment Movement Mechanism via Grain Size and Shape: A Case Study of a Beach in Eastern Hainan Island in South China

This paper used dynamic image analysis (DIA) to analyze the grain size and shape data of beach surface sediments in Bao’ding Bay, eastern Hainan Island, China, and explored the effects of sediment transport modes and beach morphology on the grain size–shape trend curves. This paper adopted a method of combining grain size cumulative frequency curves and grain size–shape trend curves to identify three sediment transport modes: suspension, saltation, and traction, and analyzed the characteristics of the grain size–shape trend curves under different beach morphologies (reflective, intermediate, and dissipative). This paper found that the grain size–shape trend curves can effectively indicate the sediment transport modes and improve the accuracy of subpopulation division; the grain size–shape trend curves showed different distribution characteristics in the cross-shore and longshore directions, which are closely related to the beach’s morphology and sediment transport direction. This paper provides a new method and idea for studying beach sediment transport and sedimentary environment using sediment grain size and shape data.

Interpretation and characterization of rate of penetration intelligent prediction model

Accurate prediction of the rate of penetration (ROP) is significant for drilling optimization. While the intelligent ROP prediction model based on fully connected neural networks (FNN) outperforms traditional ROP equations and machine learning algorithms, its lack of interpretability undermines its credibility. This study proposes a novel interpretation and characterization method for the FNN ROP prediction model using the Rectified Linear Unit (ReLU) activation function. By leveraging the derivative of the ReLU function, the FNN function calculation process is transformed into vector operations. The FNN model is linearly characterized through further simplification, enabling its interpretation and analysis. The proposed method is applied in ROP prediction scenarios using drilling data from three vertical wells in the Tarim Oilfield. The results demonstrate that the FNN ROP prediction model with ReLU as the activation function performs exceptionally well. The relative activation frequency curve of hidden layer neurons aids in analyzing the overfitting of the FNN ROP model and determining drilling data similarity. In the well sections with similar drilling data, averaging the weight parameters enables linear characterization of the FNN ROP prediction model, leading to the establishment of a corresponding linear representation equation. Furthermore, the quantitative analysis of each feature's influence on ROP facilitates the proposal of drilling parameter optimization schemes for the current well section. The established linear characterization equation exhibits high precision, strong stability, and adaptability through the application and validation across multiple well sections.

Automatic high depth-resolvability inspection of TBC debonding defects using nonlinear frequency modulation photothermal radar

In this article, a novel nonlinear frequency modulation (NLFM) photothermal radar whose instantaneous frequency curve is a concave quadratic function is proposed and further combines K-means clustering image segmentation algorithm to achieve automatic high depth-resolvability inspection of debonding defects in thermal barrier coating (TBC) structure. Firstly, a 3-dimensional (3D) photothermal finite element (FE) model of TBC structure is established, where the extrapolated Beer-Lambert model is introduced to describe the spatially volumetric heat source within the ceramic coating. Afterwards, the superior depth resolvability of the proposed NLFM photothermal radar is demonstrated compared to conventional waveforms using the established FE model. Meanwhile, its depth resolvability dependence on the thickness and thermal diffusivity of the ceramic coating is also investigated. Finally, the photothermal experiments of the TBC structure containing artificial debonding defects are conducted, and the influence of the coating thickness and metal substrate on the non-destructive testing (NDT) detection of TBC structure by NLFM photothermal radar combining K-means clustering is also experimentally studied. The results reveal that NLFM photothermal radar combining K-means clustering can achieve automatic high depth-resolvability inspection of debonding defects in TBC structure and the coating thickness and metal substrate have also a great influence on the photothermal NDT of the debonding defects of TBC structure.

Assessing the spatial pattern of public primary schools in Moro Local Government Area of Kwara State, Nigeria

Education is one of the most significant investments a nation can make in its citizens that can address poverty and inequality in the nearest future. This study sought to assess the spatial pattern of public primary schools in Moro Local Government Area (LGA) of Kwara State, Nigeria. The purpose of the study was to look at the geographic distribution and the level of inequality of the public primary schools in the study area. The number, names and addresses of public primary schools were obtained from the unit of the planning, research and statistics department of Moro Local Government Education Authority (MGLEA) while the data on the geographic location of the public primary schools were gotten via GPS device (Mreno 120, Garmin). Descriptive statistics such as frequency, percentages and Lorenz curve were used to assess the distribution of public primary schools in the study area. These data were also analyzed using Nearest Neighbour Analysis (NNA) to derive the spatial pattern of public primary schools in the area. Findings revealed that there are one hundred and fifty six (156) public primary schools in Moro LGA. Findings further revealed that Malete had the highest percentage of public primary schools with 10.3%, followed by Megida with 9.6% while Ajanaku and Pakunma had the least public primary schools, with 1.9% and 2.6%, respectively. The NNA result of the spatial pattern of public primary schools produced a clustered pattern at 0.01% significance level with the Nearest Neighbour Ratio (NNR) of 0.86 and a Z-Score of -3.39. The paper consequently recommends that Moro LGC should liaise with the Kwara state government and other relevant stakeholders in order to ensure that the allocation of primary schools is distributed equitably throughout the LGA for easy accessibility.

A Multi-Domain Joint Novel Method for ISAR Imaging of Multi-Ship Targets

As a key object on the ocean, regulating civilian and military ship targets more effectively is a very important part of maintaining maritime security. One of the ways to obtain high-resolution images of ship targets is the inverse synthetic aperture radar (ISAR) imaging technique. However, in the actual ISAR imaging process, ship targets in a formation often lead to complicated motion conditions. Due to the close distance between the ship targets, the rough imaging results of the targets cannot be completely separated in the image domain, and the small differences in motion parameters lead to overlapping phenomena in the Doppler history. Therefore, for situations in which ship formation targets with little difference in motion parameters are included in the same radar beam, this paper proposes a multi-domain joint ISAR separation imaging method for multi-ship targets. First, the method performs echo separation using the Hough transform (HT) with the minimum entropy autofocus method in the image domain. Secondly, the time–frequency curve is extracted in the time–frequency domain using the short-time Fourier transform (STFT) for time–frequency analysis, which solves the problem of the ship formation targets being aliased on both echo and Doppler history after range compression and achieves the purpose of separating the echo signals of the sub-ship targets with high accuracy. Eventually, better-focused images of each target are obtained via further motion compensation and precise imaging. Finally, the effectiveness of the proposed method is verified using a simulation and measured data.

Acoustic Characteristics Analysis of Double-Layer Liquid-Filled Pipes Based on Acoustic–Solid Coupling Theory

Based on the theory of acoustic–solid coupling, the phase velocity-thickness product of a double-layer liquid-filled pipeline is analyzed, and the dispersion relationship between angular frequency and wavenumber–thickness product is analyzed, providing a theoretical basis for ultrasonic guided wave detection. The wave number analytical expression of the double-layer liquid-filled pipeline is constructed, and the dispersion relationship of the double-layer liquid-filled pipeline under different frequency–thickness products and wavenumber–thickness products is calculated through parameter scanning. The dispersion curves of the double-layer liquid-filled pipeline are numerically analyzed in the domains of pressure acoustics, solid mechanics, and acoustic–solid coupling. The numerically simulated dispersion curves show high consistency with the analytically calculated dispersion curves. The analysis of the phase velocity frequency–thickness product indicates that the axial mode dispersion curves of the pipe wall decrease with the increase in frequency–thickness product in the coupling domain, and then tend to be flat and intersect with the radial mode dispersion curves in the coupling domain; these intersection points cannot be used for ultrasonic guided wave detection. The T(0,1) mode dispersion curve in the coupling domain of the pressure acoustics domain remains smooth from low frequency to high frequency. It is found that the dispersion curves of the phase velocity frequency–thickness product, angular frequency wavenumber–thickness product, and the acoustic pressure distribution map of the double-layer liquid-filled pipeline based on acoustic–solid coupling can provide theoretical support for ultrasonic guided wave detection of pipelines.

To what extent does river routing matter in hydrological modeling?

Abstract. Spatially distributed hydrology and land surface models are typically applied in combination with river routing schemes that convert instantaneous runoff into streamflow. Nevertheless, the development of such schemes has been somehow disconnected from hydrologic model calibration research, although both seek to achieve more realistic streamflow simulations. In this paper, we seek to bridge this gap to understand the extent to which the configuration of routing schemes affects hydrologic model parameter searches in water resources applications. To this end, we configure the Variable Infiltration Capacity (VIC) model coupled with the mizuRoute routing model in the Cautín River basin (2770 km2), Chile. We use the Latin hypercube sampling (LHS) method to generate 3500 different model parameters sets, for which basin-averaged runoff estimates are obtained directly (no routing or instantaneous runoff case) and are subsequently compared against outputs from four routing schemes (unit hydrograph, Lagrangian kinematic wave, Muskingum–Cunge, and diffusive wave) applied with five different routing time steps (1, 2, 3, 4, and 6 h). The results show that incorporating routing schemes may alter streamflow simulations at sub-daily, daily, and even monthly timescales. The maximum Kling–Gupta efficiency (KGE) obtained for daily streamflow increases from 0.64 (instantaneous runoff) to 0.81 (for the best routing scheme), and such improvements do not depend on the routing time step. Moreover, the optimal parameter sets may differ depending on the routing scheme configuration, affecting the baseflow contribution to total runoff. Including routing models decreases streamflow values in flood frequency curves and may alter the probabilistic distribution of the medium- and low-flow segments of the flow duration curve considerably (compared to the case without routing). More generally, the results presented here highlight the potential impacts of river routing implementations on water resources applications that involve hydrologic models and, in particular, parameter calibration.

Research on rainfall prediction based on RBF neural network model and stormwater inundation risk in scenic areas: A case study of the Yesanpo Scenic Area, Baoding, China

Research on stormwater inundation risk and rainwater management in scenic areas has a lot to do with rainfall during the flood season. When the measured rainfall data is limited, an artificial network model with nonlinear mapping capability can be applied to predict rainfall data during the flood season, which increases the sample size of rainfall data and improves the accuracy of research results. Based on a radial basis function (RBF)neural network model, this paper takes the Yesanpo Scenic Area in Baoding City, Hebei Province as an example to estimate the monthly maximum rainfall data during the flood season (July–September) of 2022, 2023, and 2024 in the study area. On this basis, the Pearson III frequency curve is used to calculate the design rainfall corresponding to the rainfall frequency of 20%, 5%, and 2%. With the help of SCS-CN model and ArcGIS spatial analysis tools, the stormwater inundation areas are simulated in the study area, which are divided into three risk levels: high, medium, and low, providing a reference for the stormwater management in the Yesanpo Scenic Area.

Grain size characteristics of surface sediment in the Jilantai Salt Lake Protection System after long‐term wind‐sand activities

AbstractIn order to explore the influence of vegetation on homogeneity of surface particle size distribution (PSD) and heterogeneity of soil structure, observations, theory, and multifractal results were synthesized to highlight the evolution of the soil particle composition in the Jilantai Salt Lake Protection System (Jilantai system) after long‐term wind‐sand activities and its soil structure characteristics. From flowing sand dune to saline‐alkali wasteland areas, the mean grain size and surface particle sorting degree gradually increased and decreased, respectively, whereas the shape of the particle frequency curve gradually changed from extremely positive deviation to negative deviation, and the peak shape of the curve gradually changed from narrow to wide. Furthermore, the inhomogeneity of the soil particle composition gradually decreased, whereas the range of the soil PSD gradually increased, and the soil increasingly became fine‐grained. Therefore, the contents of clay and silt in shelterbelt soil increased by 16% and 18.36%, respectively, over 1986 levels. Additionally, clay and silt play a vital role in determining soil particle parameters such as standard deviation (SD), skewness (SKI), and monofractal (D), while vegetation factors are the main controlling factors of clay and silt. In conclusion, the Jilantai system could increase heterogeneity and homogeneity and decrease the concentration of soil PSD by changing the sedimentary environment, while this affect depends largely on the fractional vegetation cover, vegetation height, and light penetrating porosity. Moreover, the multifractal and particle parameters could describe the soil structure characteristics and sedimentary process, respectively, after long‐term wind‐sand activities.

Detection and time–frequency analysis of multiple plant-wide oscillations using adaptive multivariate intrinsic chirp component decomposition

Analyzing plant-wide oscillations is a challenging task owing to the presence of noise, nonstationarity, and multiple modes in a process control system. Multivariate intrinsic chirp component decomposition (MICCD) is a novel powerful tool for multivariate signal processing. Nevertheless, MICCD requires users to provide component number in advance, which restricts its adaptability. This study proposes an adaptive MICCD (AMICCD) that can adaptively determine the component number by utilizing the permutation entropy of instantaneous frequency. An AMICCD-based time–frequency analysis framework is presented to detect and characterize the multiple plant-wide oscillations. Compared to the latest methods, such as multivariate empirical mode decomposition and multivariate intrinsic time-scale decomposition, the proposed method can process not only single/multiple plant-wide oscillations, but also time-invariant/time-varying plant-wide oscillations. In particular, the proposed method can directly provide the time–frequency curves of multiple plant-wide oscillations, which have not been achieved by the state-of-the-art techniques. Finally, the effectiveness and advantages of the proposed approach are demonstrated on a wide variety of simulations and industrial cases.

Drought intensity–duration–frequency curves based on deficit in precipitation and streamflow for water resources management

Abstract. Drought estimates in terms of physically measurable variables such as precipitation deficit or streamflow deficit are key knowledge for an effective water management. How these deficits vary with the drought event severity indicated by commonly used standardized indices is often unclear. Drought severity calculated from the drought index does not necessarily correspond to the same amount of deficit in precipitation or streamflow at different regions, and it is different for each month in the same region. We investigate drought to remove this disadvantage of the index-based drought intensity–duration–frequency (IDF) curves and develop IDF curves in terms of the associated deficit. In order to study the variation of deficits, we use the link between precipitation and streamflow and the associated indices, the Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSI). More specifically, the analysis relies on frequency analysis combined with the total probability theorem applied to the critical drought severity. The critical drought has varying durations, and it is extracted from dry periods. IDF curves in terms of precipitation and streamflow deficits for the most severe drought of each drought duration in each year are then subject to comparison of statistical characteristics of droughts for different return periods. Precipitation and streamflow data from two catchments, the Seyhan River (Türkiye) and the Kocher River (Germany), provide examples for two climatically and hydrologically different cases. A comparison of the two cases allows a similar method to be tested in different hydrological conditions. We found that precipitation and streamflow deficits vary systematically, reflecting seasonality and the magnitude of precipitation and streamflow characteristics of the catchments. Deficits change from one month to another at a given station. Higher precipitation deficits were observed in winter months compared to summer months. Additionally, we assessed observed past major droughts experienced in both catchments on the IDF curves, which show that the major droughts have return periods at the order of 100 years at short durations. This coincides with the observation in the catchments and shows the applicability of the IDF curves. The IDF curves can be considered a tool for using in a range of specific activities of agriculture, ecology, industry, energy and water supply, etc. This is particularly important to end users and decision-makers to act against the drought quickly and precisely in a more physically understandable manner.

Majorana noise model and its influence on the power spectrum

Majorana quantum computation offers a potential approach to securely manipulating and storing quantum data in a topological manner that may effectively resist the decoherence induced by local noise. However, actual Majorana qubit setups are susceptible to noise. In this study, from a quantum dynamics perspective, we develop a noise model for Majorana qubits that accounts for quasi-particle poisoning and Majorana overlapping with fluctuation. Furthermore, we focus on Majorana parity readout methodologies, specifically those leveraging an ancillary quantum dot, and carry out an in-depth exploration of continuous measurement techniques founded on the quantum jump model of a quantum point contact. Utilizing these methodologies, we proceed to analyze the influence of noise on the afore-mentioned noise model, employing numerical computation to evaluate the power spectrum and frequency curve. In the culmination of our study, we put forward a strategy to benchmark the presence and detailed properties of noise in Majorana qubits.