Prediction Of Attenuation Research Articles

Marsh restoration in front of seawalls is an economically justified nature-based solution for coastal protection

A marsh-fronted seawall is a hybrid nature-based coastal protection solution because it attenuates wave energy, reduces erosion, and provides ecosystem services. However, we still have a limited understanding of how to quantify the marsh wave attenuation benefits for economic analysis. Here, we incorporate a prediction of wave attenuation that accounts for species-specific morphology and structural stiffness into a 1-D wave model and validate it with field measurements. Our results show that the wave attenuation varies by a factor of two across different vegetation species. Further, we performed a benefit-cost analysis, in which the economic benefits represent the environmental services value and avoided seawall heightening cost that would otherwise be required to deliver the same overtopping rate without vegetation. We applied the model to a real-world, marsh-fronted seawall design at Juniper Cove, Massachusetts. Although the benefit of marsh-fronted seawalls is sensitive to discount rate, they have benefit-cost ratios greater than one, indicating that it is an economically justified nature-based solution. Further, we found that wave attenuation and benefit-cost ratio are more sensitive to water depth than wave height. Our study demonstrates the importance of considering the coastal protection of marshes and economic benefits in one framework.

Performance of advanced-deep learning algorithm for modeling and prediction of rain height over some selected locations in the tropics and sub-tropics zone for radio propagation applications

As demand for high-frequency broadband communication services keeps rising, rain-induced attenuation remains the predominant threat to radiowave propagation. Accurate prediction of attenuation requires continuous measurement and monitoring of rain-induced meteorological parameters, specifically rain rate and rain height, due to their spatio-temporal variations. Rain height is an upper dataset mostly computed from Zero- degree Isotherm Heights (ZDIH) measured by radar. This research proposes a novel approach for predicting rain height from earth surface data such as surface temperature, pressure, total cloud cover, dew point temperature, surface solar radiation, water vapor amount in the air, and humidity. This research investigates the relationship between meteorological surface data and rain height. Subsequently, six machine learning models were employed for predicting rain height using the ten years surface data as input variables. The models were applied to six sub-tropical (Polokwane, Pretoria. and Cape Town) and tropical (Sokoto, Akure, and Port Harcourt (PH)) stations in South Africa and Nigeria, respectively. Analysis of the results shows that the Gradient Boosting Algorithm (GBA) performed best with determination coefficients greater than 0.80 and RMSE less than 350 in all three stations in South Africa. However, all the models failed to produce good result for the Nigeria stations. The Random Forest model has the fairest performance metrics with r2 of 0.40, 0.46 and 0.46 in Sokoto, Akure and PH. respectively. GBA is recommended for predicting rain height in South Africa. The research outcome would assist radio engineers in improving the prediction of rain-induced attenuation and determining appropriate fade mitigation techniques.

Advances of the Holographic Technique to Test the Basic Properties of the Thin-Film Organics: Refractivity Change and Novel Mechanism of the Nonlinear Attenuation Prediction.

A large number of the thin-film organic structures (polyimides, 2-cyclooctylarnino-5-nitropyridine, N-(4-nitrophenyl)-(L)-prolinol, 2-(n-Prolinol)-5-nitropyridine) sensitized with the different types of the nano-objects (fullerenes, carbon nanotubes, quantum dots, shungites, reduced graphene oxides) are presented, which are studied using the holographic technique under the Raman-Nath diffraction conditions. Pulsed laser irradiation testing of these materials predicts a dramatic increase of the laser-induced refractive index, which is in several orders of the magnitude greater compared to pure materials. The estimated nonlinear refraction coefficients and the cubic nonlinearities for the materials studied are close to or larger than those known for volumetric inorganic crystals. The role of the intermolecular charge transfer complex formation is considered as the essential in the refractivity increase in nano-objects-doped organics. As a new idea, the shift of charge from the intramolecular donor fragment to the intermolecular acceptors can be proposed as the development of Janus particles. The energy losses via diffraction are considered as an additional mechanism to explain the nonlinear attenuation of the laser beam.

A methodology for appropriate withdrawal of tsunami warnings based on numerical simulations

This study performed large-scale numerical simulations for predicting the attenuation of tsunamis caused by the 2011 Tohoku, Japan, and 2010 Maule, Chile earthquakes, recorded at Japanese tide gauges. Tsunami amplitude waveforms were generated by computing the moving root-mean-square of the data for quantitative analyses. Sensitivity analysis showed that tsunami nonlinearity and computational grid intervals near the tide gauges significantly impact the prediction of tsunami attenuation. The predicted withdrawal times of tsunami warnings agreed with the observations; however, time discrepancies were observed for advisory withdrawals at several stations. Using the proposed method, we predicted the warning period of a great interplate earthquake in the Nankai Trough to be approximately one day. These findings can provide critical information for disaster prevention because the withdrawal of warnings is directly related to permission to enter coastal areas affected by the tsunami, whereas unnecessarily long warnings hinder rescue operations.

Research on the Calculation Method and Influence Law of High-speed Railway Line Sound Source Propagation Attenuation Caused by Building Sheltering

Abstract In recent years, China’s rail transit system, particularly the high-speed railway network, has experienced rapid development. However, the issue of noise pollution along these railways has become increasingly severe. The accurate prediction of sound levels at specific points near buildings is challenging due to complex factors such as differences in line height, distance, and angle relative to the building. To address this challenge and improve predictions of sound propagation attenuation caused by building shelter from high-speed railway line sources, this study derives an integral expression for diffraction attenuation based on Curze and Meakawa’s point source acoustic diffraction theory. Numerical calculations are conducted to investigate the sound propagation attenuation patterns under different position relationships between buildings and railway lines. Field tests are also carried out along a high-speed railway in China. The findings are as follows: (1) The calculated results show a difference of less than 0.5 dB compared to measured values, indicating that they accurately reflect sound attenuation caused by building shelter. (2) The angle between the building and the railway as well as the distance between the sound point and the edge of the building significantly influence building shelter attenuation; with angle being most prominent among them within a frequency band of 500~2000 Hz resulting in an attenuation range of 0.6~15 dB variation should be considered when predicting noise levels at sensitive points or designing vibration and noise reduction measures accordingly. (3) Different distances between buildings and railway lines result in additional effects on attenuations.

The influence of contrast media on calcium-based imaging of the spine in dual-layer CT

This study aimed to evaluate the impact of contrast media application on CT attenuation of the bone using a novel calcium-only imaging technique (VCa) from dual-layer spectral detector CT (DLCT), which enables CT-based bone mineral density measurement unimpeded by soft tissue components. For this, true non-contrast (TNC) and venous phase images (VP) of n = 97 patients were acquired. CT attenuation of the first lumbar vertebra (L1) was measured in TNC-VCa, VP-VCa, and in virtual non-contrast images (VNC). CT attenuation was significantly higher in VP-VCa than in TNC-VCa (p < 0.001), although regression analyses revealed a strong linear association between these measures (R2 = 0.84). A statistical model for the prediction of TNC-VCa CT attenuation was established (TNC-VCa[HU] = − 6.81 + 0.87 × VP-VCa[HU]-0.55 × body weight[kg]) and yielded good agreement between observed and predicted values. Furthermore, a L1 CT attenuation threshold of 293 HU in VP-VCa showed a sensitivity of 90% and a specificity of 96% for detecting osteoporosis. The application of contrast media leads to an overestimation of L1 CT attenuation in VCa. However, CT attenuation values from VP-VCa can be used within CT-based opportunistic osteoporosis screening eighter by applying a separate threshold of 293 HU or by converting measured data to TNC-VCa CT attenuation with the given regression equation.

Prediction method of long-term creep deformation of mobile phone resin lens module in a harsh temp environment

In recent years, the replacement cycle of digital products such as mobile phones in the market has significantly increased, and the accurate prediction of attenuation under long-term usage conditions of the lens module, storage, and other components has become important. The vast majority of mobile phone lens modules are processed from optical resins, and the degradation of their imaging performance is mainly caused by assembly deformation and long-term creep deformation after a high-temperature reliability test. Therefore, there is an urgent need for a reliable model to describe the long-term creep deformation of the mobile phone resin lens module in a harsh temperature environment. This study proposed a modified derivation method for the parameters of the Maxwell constitutive model to predict the long-term creep deformation of the mobile phone resin lens module in a high-temperature environment. The fitting accuracy of the modified generalized Maxwell model and the time-hardening model were compared through uniaxial compression creep experiments. Long-term creep simulations and experiments were conducted on the mobile phone resin lens module; the deformation law of each component of the mobile phone resin lens module was identified; and the creep deformation mechanism was elucidated. The result shows that the modified generalized Maxwell model has much higher accuracy than the time-hardening model in predicting the long-term creep deformation of different resin materials. When considering the influence of the creep phenomenon, the simulation result matches well with the experimental result, and the high-temperature creep mechanism of the mobile phone resin lens module was clarified. In addition, it was found that the maximum deformation of the lens occurred at the lens with the largest size, which was 2.1 µm, and the position with the largest surface deviation was at the edge of the lens. The prediction method proposed in this study can provide guidance and correction suggestions for the structural design of a mobile phone resin lens module and the rationality of optical design; thus, the imaging accuracy of lens modules will be guaranteed to the greatest extent possible.

Phase and group speeds of airborne surface waves over porous layers and periodically rough hard surfaces.

Sound fields above porous layers or rough acoustically hard boundaries may include airborne surface waves. The surface wave properties depend on the effective surface admittance. Analytical expressions for surface wave speeds are derived from models for the acoustical properties of rigid porous media. Surface wave effects on measurements of level difference spectra over porous asphalt are investigated and predictions of phase, group speeds, and vertical attenuation of the surface waves over externally reacting hard backed layers corresponding to a porous asphalt are compared. Predictions of surface wave characteristics above an identical vertical slit medium are compared with data obtained over arrays of parallel aluminum strips on an acoustically hard surface. Group speeds of surface waves over lattices, parallel regularly spaced strips, and snow obtained by numerical differentiation of the phase speed spectra corresponding to admittance spectra deduced from complex excess attenuation are found to compare well with those estimated from time domain data. An effective admittance, deduced from a boundary element method simulation of the excess attenuation spectrum over regularly spaced ribs so that the frequency of the peak corresponds with that in the measured spectrum, is used to estimate the group speed of the associated surface wave.

Seasonal variations in drag coefficient of salt marsh vegetation

Understanding the seasonal variations of vegetation drag coefficients is crucial for improving wave attenuation predictions and adapting to climate impacts. This study explores the seasonal changes in drag coefficients within salt marsh vegetation, using data from a year-long series of field measurements at the Chongming Dongtan Wetland. It uncovers the complex seasonal variations of drag coefficients. Results demonstrate that incorporating a nonlinear equation for characteristic flow velocity and effective vegetation length significantly improves the precision of drag coefficient predictions, ensuring a closer match with field observations. Furthermore, it introduces a refined drag coefficient formula that incorporates adjustments for vegetation stiffness and relative submergence, offering a more accurate representation of the seasonal variability in drag forces exerted by salt marsh vegetation. This enhanced formula is crucial for accurately assessing vegetation's role in wave attenuation, providing critical insights for the design and implementation of coastal defense and wetland conservation initiatives.

Research on prediction model of quantitative relationship of pressure attenuation of hydrogen fuel cell air compressor based on artificial neural network

Abstract This thesis considers the field of the pressure attenuation of hydrogen fuel cell air compressors as the main subject of its study. Traditional methods usually model the prediction of pressure attenuation based on a durability test or physical model, which is costly and time-consuming. Based on the method of artificial neural network (ANN), this paper establishes a prediction model of the quantitative relationship of outlet pressure attenuation of hydrogen fuel cell air compressors. A neural network is used to capture the nonlinear relationship of outlet pressure of air compressors, and the prediction results of the model are analyzed and explained to explore the attenuation process of outlet pressure of hydrogen fuel cell air compressors. The comparison between the actual test data and the predicted data through the endurance test of the air compressor shows that the prediction ability of the model is good, and the correlation of the regression analysis results of the prediction model is above 0.99, which can be used to predict the quantitative relationship of outlet pressure attenuation of hydrogen fuel cell air compressor.

Deep neural network-based prediction of tsunami wave attenuation by mangrove forests

The goal of this research is to develop a model employing deep neural networks (DNNs) to predict the effectiveness of mangrove forests in attenuating the impact of tsunami waves. The dataset for the DNN model is obtained by simulating tsunami wave attenuation using the Boussinesq model with a staggered grid approximation. The Boussinesq model for wave attenuation is validated using laboratory experiments exhibiting a mean absolute error (MAE) ranging from 0.003 to 0.01. We employ over 40,000 data points generated from the Boussinesq numerical simulations to train the DNN. Efforts are made to optimize hyperparameters and determine the neural network architecture to attain optimal performance during the training process. The prediction results of the DNN model exhibit a coefficient of determination (R2) of 0.99560, an MAE of 0.00118, a root mean squared error (RMSE) of 0.00151, and a mean absolute percentage error (MAPE) of 3 %. When comparing the DNN model with three alternative machine learning models— support vector regression (SVR), multiple linear regression (MLR), and extreme gradient boosting (XGBoost)— the performance of DNN is superior to that of SVR and MLR, but it is similar to XGBoost.•High-accuracy DNN models require hyperparameter optimization and neural network architecture selection.•The error of DNN models in predicting the attenuation of tsunami waves by mangrove forests is less than 3 %.•DNN can serve as an alternate predictive model to empirical formulas or classical numerical models.

A multi-faceted methodology for calibration of coastal vegetation drag coefficient

The accurate prediction of wave height attenuation due to vegetation is crucial for designing effective and efficient natural and nature-based solutions for flood mitigation, shoreline protection, and coastal ecosystem preservation. Central to these predictions is the estimation of the vegetation drag coefficient (Cd). The present study undertakes a comprehensive evaluation of three distinct methodologies for estimating the drag coefficient: traditional manual calibration, calibration using a novel application of state-of-the-art metaheuristic optimization algorithms, and the integration of an empirical bulk drag coefficient formula (Tanino and Nepf, 2008) into the XBeach non-hydrostatic wave model. These methodologies were tested using a series of existing laboratory experiments involving nearshore vegetation on a sloping beach. A key innovation of the study is the first application of metaheuristic optimization algorithms for calibrating the drag coefficient, which enables efficient automated searches to identify optimal values aligning with measurements. We found that the optimization algorithms rapidly converge to precise drag coefficients, enhancing accuracy and overcoming limitations in manual calibration which can be laborious and inconsistent. While the integrated empirical formula also demonstrates reasonable performance, the optimization approach exemplifies the potential of computational techniques to transform traditional practices of model calibration. Comparing these strategies provides a framework to determine effective methodology based on constraints in determining the vegetation drag coefficient.

Simulation of Rainfall Attenuation Prediction Models for the Optimization of High-Speed Links in Millimeter Bands (80GHz): Tropical Regions’ Case

We deal with the problem of attenuation of electromagnetic waves due to precipitation. Indeed, the millimeter wave frequency (30&amp;ndash;300 GHz) is a promising candidate for broadband wireless networks (4G and beyond), but atmospheric elements limit radio links to this frequency band. Precipitation is the important atmospheric element that causes the attenuation of a wave during its propagation and should therefore be estimated for the proper functioning of a link. It is with this in mind that our study focuses on the choice of an appropriate model for predicting the attenuation of a radio link after simulation of several models proposed in the literature in order to assess the impact of precipitation in the tropical region. The method used to achieve this objective consists firstly of analysing existing models and determining theoretical and actual unavailability using ITU-R methods and the Nomad monitoring tool; then secondly, we develop an application to evaluate the attenuation due to rain using the Da Silva, Mello and ITU-R models. The calculated attenuations were compared to experimental measurements, and Da Silva&amp;#39;s model was found to be the best fit. On a local level, these results have a significant impact on the planning and optimization of communications infrastructures, enabling better performance of networks using millimeter waves. At the national level, this contributes to improved telecommunications networks and more reliable connectivity. Globally, this research can aid the development of high-frequency wireless communications in tropical regions, thereby promoting large-scale technological and economic advancement.

Multi-dimensional investigation of ceiling jet temperature characteristics beneath curved ceiling produced by fire in the utility tunnel

To study the temperature profile beneath the curved ceiling from a multi-dimensional perspective, an experimental investigation was conducted in utility tunnels with two different sizes, and a series of models were established to predict a two-dimensional longitudinal temperature profile and transverse temperature attenuation in this study. The prediction models for the two-dimensional longitudinal temperature profile were developed by modeling the vertical temperature distribution, thermal boundary layer thickness, Gaussian thermal layer thickness and maximum longitudinal temperature attenuation. Through the experimental validation on two sizes, it is found that the proposed prediction model can express the longitudinal temperature profile from a two-dimensional view within the relative error range of 20%. Besides, the prediction model for transverse temperature attenuation was established by the definition of characteristic tilt angle, and the three detailed expressions of this model were proposed according to different types of ceiling jets after impingement. The proposed prediction model for transverse temperature attenuation was also validated, and the verification results showed that the relative error of the transverse temperature attenuation prediction model can be controlled within a 25%. The developed prediction models in this study can be applied in the fire protection engineering of utility tunnels.

Rain Attenuation Prediction at Different Time Percentages for Ku, K, and Ka Bands Satellite Communication Systems over Nigeria

This paper evaluates the influence of rainfall on propagated signal at different time exceedance percentages of an average year, over the climate zones of the country. Specifically, it demonstrates critical and non critical signal fade or signal outage time exceedance (0.001% to 1%) for Ku, K, and Ka-band systems in an average year. The study was carried out using meteorological data made available by the Nigerian Meteorological Agency (NiMet) over a period of 10 years (2009–2018). The four climate zones in the country were represented by five (5) locations; Maidugiri (warm desert climate), Sokoto (tropical dry climate), Port Harcourt (tropical monsoon climate), Abuja and Enugu (tropical savanna climate). The parameters were simulated into the International Telecommunications Union Recommended (ITU-R) models for rain attenuation over the tropics and results presented using MatLab and Origin Lab. Results of Ku band propagations showed that only locations in the tropical savanna and tropical monsoon climates experienced total signal outage for time percentage exceedance equal to or below 0.01% for both horizontal and vertical polarizations. At K band propagations, the five locations showed to have experienced signal outage at time exceedance equal to and below 0.01%, almost same was recorded for the Ka-band propagation. It was also observed that horizontal and vertical polarization of signal had slightly different rain attenuation values for the studied bands at the five locations, with horizontal polarization having higher values than vertical polarization.

The Path Reduction Factor for the Prediction of Rain Attenuation Affecting Short EHF Terrestrial Links

The Path Reduction Factor for the Prediction of Rain Attenuation Affecting Short EHF Terrestrial Links

On the wave attenuation properties of seagrass meadows

The wave attenuation properties of seagrass meadows were investigated in a flume facility using dynamically-scaled models of seagrass exposed to regular long crested waves. Experiments were conducted for 66 wave conditions and with four plant densities; waves were measured with eight resistance wave gauges. The data collected represent the most-comprehensive dataset of its kind. They reveal that the wave attenuation coefficient KD of a seagrass meadow reaches a uniform value after a distance of approximately 1.5–3 times the water depth from the meadow start and that both KD and the drag coefficient Cd depend significantly on the plant density. An improved model of KD based on the work of Lei and Nepf (2019) is proposed that takes into account the effects of the solid volume fraction of the plant model through a correction on Cd and that of plant density via an effective vegetation frontal area av−e. The effective vegetation frontal area is described as a power law of the roughness density λf. The model, which was validated with the data of KD obtained from the laboratory experiments described herein, displays an excellent agreement with data from the literature. It can predict KD accurately also for cases whereby the maximum wave orbital excursion is comparable with the blade length, despite this condition violates the model’s assumptions. This work provides a comprehensive dataset and a new model that can be used to improve the prediction of wave attenuation of seagrass meadows.

Laboratory experiments and theoretical study of pressure and fluid influences on acoustic response in tight rocks with pore microstructure

AbstractWave‐induced fluid flow is considered to be a major source of seismic attenuation and dispersion in porous rocks. From the physical description of partially saturated reservoirs, numerous analytical solutions based on upscaling homogenization theories have been employed to calculate equivalent frequency‐dependent poroelastic media. Nevertheless, dispersion and attenuation predictions are often not reasonably consistent with laboratory and field measurements in a broad frequency range, particularly due to influences of biphasic fluids and their distribution, presence of heterogeneities on various length scales, and pore microstructure. We investigate the role of pore microstructure on pressure and fluid saturation dependence of elastic velocities in tight sandstones. Previous work points out that differentiating the impacts of heterogeneities at various scales on dispersion within seismic exploration and sonic frequencies can be very difficult. In practice, this is because fluid‐related dispersion mechanisms are impossible to be independent. Thus, it is important for a theoretical and more quantitative analysis of the relative contribution of interrelated energy dissipation processes through a better understanding of combined influences due to the presence of microscopic and mesoscopic heterogeneities. Based on microscopic squirt flow and mesoscopic flow in a partially saturated medium, we develop a poroelastic model that allows evaluating the overall frequency‐dependent dispersion via considering a random distribution of fluid heterogeneities as well as the broadly distributed aspect ratio of compliant pores. Experimental validation of the model is accomplished via a comprehensive comparison of predictions with measurements of partially saturated velocities versus pressure and fluid for sandstones with specific pore microstructures.

Sand and Dust Storm Attenuation Prediction Using Visibility and Humidity Measurements

Sand and Dust Storm Attenuation Prediction Using Visibility and Humidity Measurements

Acoustic attenuation prediction and analysis of perforated hybrid mufflers with non-uniform flow based on frequency domain linearized Navier-Stokes equations

The three-dimensional frequency-domain linearized Navier-Stokes equations (LNSEs) with consideration of eddy viscosity are developed to evaluate the acoustic attenuation performance of perforated hybrid mufflers in the presence of non-uniform flow. The computations are performed in two steps: time averaged flow variables are acquired by using steady-state computational fluid dynamics (CFD) method and then mapped into the acoustic mesh, and the acoustic perturbation variables are obtained by solving frequency-domain LNSEs, where the sound-absorbing material is treated as an equivalent fluid with complex sound speed and density. The predictions of transmission losses of the two-pass perforated hybrid mufflers in the presence of non-uniform flow are in good consistencies with the measurements, which verifies the correctness of LNSEs. The effect of Mach numbers on acoustic attenuation performance of the mufflers with different filling densities and perforated components is investigated in detail. The transmission loss of the mufflers with various filling densities are increased by complex airflow in the lower frequency range. For the mufflers where not all components have been perforated, the flow lowers low-frequency resonance peak. The influence of complex airflow on acoustic attenuation performance of all configurations is weakened at higher frequencies.