Attenuation Data Research Articles

Effective range of auditory frightening devices based on hearing capabilities and antipredator responses of nuisance blackbirds

AbstractA variety of acoustic strategies have been implemented to disperse wildlife from areas of human‐wildlife conflict. Propane cannons are a popular tool; however, their efficacy based on avian behavior has yet to be fully explored. We collected sound attenuation data for a propane cannon, compared to a rifle and shotgun, with reference to hearing capabilities in birds. We evaluated the behavioral responses of red‐winged blackbirds (Agelaius phoeniceus, RWBL) and brown‐headed cowbirds (Molothrus ater, BHCO) to detonations of a cannon. We placed birds in individual enclosures, void of visual stimuli, at 15–495 m from a cannon and evaluated responses (i.e., relaxed, vigilant, startled) to cannon blasts using 2 approaches: 1) incremental, where individual birds were exposed to a series of detonations at decreasing distances and 2) random assignment, where individual birds were randomly assigned distances and exposed to 2 series of 4 cannon blasts. We found behavioral responses of birds significantly decreased at greater distances (χ2(1) = 127, P < 0.001), regardless of species (χ2(1) = 0.74, P = 0.389), when incrementally approached. The probability of startling (i.e., flinch, wing flap, feather compression, or flight) was greater than vigilance (i.e., increased head turning, sudden head‐up, or neck extension) within 64 m for BHCO and 136 m for RWBL. We found a significant effect of distance (χ2(1) = 97.8, P < 0.001), between species (χ2(1) = 19.6, P < 0.001), and blast number (χ2(3) = 17.6, P < 0.001) when birds were randomly assigned a distance from the cannon. With the first cannon blast, the probability of startling was greater than vigilance or relaxed within 334 m for BHCO and 153 m for RWBL. With subsequent blasts the probability of startling was greater than vigilance and relaxed within 204–221 m of the cannon for BHCO, but startling was never greater than vigilance for RWBL. We note that the estimated range of the cannon is conservative given birds are contained with limited flight ability. Nevertheless, information on effective range and avian responses to repeated blasts informs managers on the potential interstimulus timing and distribution of propane cannons to protect resources from birds.

X-ray spectrum estimation from the transmission method using the radioluminescence of an Al2O3:C crystal

The X-ray spectrum of X-ray tube is crucial for radiation dose calculations. Due to the high photon flux, it is difficult to directly measure the primary spectrum of X-ray tube. Transmission measurement is one of indirect method used to determine the primary spectrum of X-ray tube. Although the method is experimentally simple, X-ray spectrum estimation from transmission method is a seriously ill-conditioned problem. In this paper, a new transmission measurement instrument with an the Al2O3:C crystal detector is proposed. Real-time dose rate attenuation data from transmission method are collected by using the radioluminescence(RL) of the Al2O3:C crystal. The expectation-maximization (EM) method is applied for X-ray spectrum estimation from transmission method. The method is demonstrated on typical simulated spectra of 80,100,120,140 and 160 kV from X-ray tubes. The X-ray spectra are simulated with the Monte Carlo code Geant4. The EM method is successfully applied to seriously ill-conditioned and under determined estimation problems. The results showed that the X-ray spectrum estimation method is a robust technique for estimating the primary spectrum of X-ray tube, and that the new instrument for transmission measurements can be used to accurately estimate X-ray spectrum.

A cryogenic forced oscillation apparatus to measure anelasticity of ice.

We have developed a new cryogenic uni-axial forced oscillation apparatus to measure the anelastic behavior of ice by adapting the design of a previous high-precision apparatus for use in low-temperature (<0 °C) conditions. With this new apparatus, Young's modulus and attenuation can be measured over a broad frequency range from 10-4 to 10Hz. We have performed calibration tests with standard materials (steel spring, stainless steel, and acrylic samples) under various conditions to assess the apparatus properties and correct the effects on the obtained raw data. Young's modulus and attenuation for an acrylic sample after all of the data corrections show good agreement with previously published values, demonstrating the validity of the data corrections and reliability of the obtained data. We further obtained a preliminary dataset of Young's modulus and attenuation for an ice polycrystalline sample under small median stress and small stress amplitude. The anelastic response was not strain amplitude-dependent, that is, the response is linear. Moreover, the attenuation data are consistent with the data measured for other polycrystalline materials under similarly small stress conditions in terms of the Maxwell frequency scaling, which is known as a scaling law applicable to linear anelasticity induced by the diffusionally accommodated grain boundary sliding mechanism. Although there is still room for improving the control of testing conditions, we show that the new forced oscillation apparatus is capable of systematic studies on the anelastic properties of ice, the subject of future studies.

Optimization of contrast and dose in x-ray phase-contrast tomography with a Talbot-Lau interferometer

X-ray phase-contrast imaging has become a valuable tool for biomedical research due to its improved contrast abilities over regular attenuation-based imaging. The recently emerged Talbot-Lau interferometer can provide quantitative attenuation, phase-contrast and dark-field image data, even with low-brilliance x-ray tube sources. Thus, it has become a valid option for clinical environments. In this study, we analyze the effects of x-ray tube voltage and total number of images on the contrast-to-noise ratio (CNR) and dose-weighted CNR (CNRD) calculated from tomographic transmission and phase-contrast data of a phantom sample. Constant counting statistics regardless of the voltage was ensured by adjusting the image exposure time for each voltage setting. The results indicate that the x-ray tube voltage has a clear effect on both image contrast and noise. This effect is amplified in the case of phase-contrast images, which is explained by the polychromatic x-ray spectrum and the dependence of interferometer visibility on the spectrum. CNRD is additionally affected by the total imaging time. While submerging the sample into a water container effectively reduces image artefacts and improves the CNR, the additional attenuation of the water must be compensated with a longer exposure time. This reduces dose efficiency. Both the CNR and CNRD are higher in the phase-contrast images compared to transmission images. For transmission images, and phase-contrast images without the water container, CNRD can be increased by using higher tube voltages (in combination with a lower exposure time). For phase-contrast images with the water container, CNRD is increased with lower tube voltages. In general, the CNRD does not strongly depend on the number of tomographic angles or phase steps used.

Inversion of shear wave slowness and attenuation from dipole acoustic logging data based on an equivalent tool theory

The presence of a sonic logging tool affects the propagation characteristics of dipole-flexural waves in a fluid-filled borehole. As a result, the tool effect should be considered during the processing and inversion of the dipole-flexural waves for the acoustic properties of a shear wave (S wave). We show that the presence of the tool not only changes the slowness dispersion of the flexural wave but also results in a shift of its frequency-dependent attenuation toward lower frequencies. The equivalent tool theory (ETT) can realistically model the effect of an acoustic tool on guided wave propagation. With the ETT framework, we develop a unified workflow for estimating the S-wave slowness and attenuation from dipole array acoustic waveforms. The workflow is an extension of the model-based dispersive processing of dipole logging data. Our workflow involves two inversion procedures. By matching the actual dispersion data with the theoretical dispersion predicted by the ETT, we can invert the S-wave slowness and tool parameters. With the estimated S-wave slowness and other borehole parameters, we further calculate the partition coefficients of flexural waves using the ETT. Based on the concept of energy partitioning, we formulate a linear optimization problem and invert for the S-wave attenuation from the frequency-dependent dipole attenuation. We use synthetic and field data to demonstrate the effectiveness and applicability of the developed method. The results show that it is important to incorporate the tool effect when processing dipole acoustic logging data for S-wave slowness and attenuation, especially in a fast formation.

Characterization of selected additive manufacturing materials for synchrotron monochromatic imaging and broad-beam radiotherapy at the Australian synchrotron-imaging and medical beamline

Objective. This study aims to characterize radiological properties of selected additive manufacturing (AM) materials utilizing both material extrusion and vat photopolymerization technologies. Monochromatic synchrotron x-ray images and synchrotron treatment beam dosimetry were acquired at the hutch 3B and 2B of the Australian Synchrotron-Imaging and Medical Beamline. Approach. Eight energies from 30 keV up to 65 keV were used to acquire the attenuation coefficients of the AM materials. Comparison of theoretical, and experimental attenuation data of AM materials and standard solid water for MV linac was performed. Broad-beam dosimetry experiment through attenuated dose measurement and a Geant4 Monte Carlo simulation were done for the studied materials to investigate its attenuation properties specific for a 4 tesla wiggler field with varying synchrotron radiation beam qualities. Main results. Polylactic acid (PLA) plus matches attenuation coefficients of both soft tissue and brain tissue, while acrylonitrile butadiene styrene, Acrylonitrile styrene acrylate, and Draft resin have close equivalence to adipose tissue. Lastly, PLA, co-polyester plus, thermoplastic polyurethane, and White resins are promising substitute materials for breast tissue. For broad-beam experiment and simulation, many of the studied materials were able to simulate RMI457 Solid Water and bolus within ±10% for the three synchrotron beam qualities. These results are useful in fabricating phantoms for synchrotron and other related medical radiation applications such as orthovoltage treatments. Significance and conclusion. These 3D printing materials were studied as potential substitutes for selected tissues such as breast tissue, adipose tissue, soft-tissue, and brain tissue useful in fabricating 3D printed phantoms for synchrotron imaging, therapy, and orthovoltage applications. Fabricating customizable heterogeneous anthropomorphic phantoms (e.g. breast, head, thorax) and pre-clinical animal phantoms (e.g. rodents, canine) for synchrotron imaging and radiotherapy using AM can be done based on the results of this study.

Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation

AbstractPrecipitation estimation models are typically sourced by rain gauges, weather radars and satellite observations. A relatively new technique of precipitation estimation relies on the network of Commercial Microwave Links (CMLs) employed for cellular communication networks: the rain‐inducted attenuation in the links enables the precipitation estimation. In the paper, it is analysed to what extent the precipitation derived from CML attenuation data is useful in estimation of the precipitation field with the high temporal and spatial resolution required in nowcasting models. Two methods of determination of precipitation along CMLs from attenuation of signal with several frequencies were proposed. Then, in order to generate precipitation field, three approaches for assigning appropriate precipitation values to a specific point or set of pixels along the link are developed and tested. The CML‐based estimates are compared with point observations from manual rain gauges and multi‐source precipitation fields using daily and half‐hourly accumulations. It was found that the CML‐based precipitation fields are much worse than radar‐derived estimates. At the same time, they had slightly poorer reliability than spatially interpolated telemetric rain gauge data and significantly higher reliability than satellite estimates. Furthermore, the impact of link characteristics, such as length and frequency, on the reliability of CML‐based precipitation estimates is analysed.

Updates on the Applications of Spectral Computed Tomography for Musculoskeletal Imaging.

Spectral CT represents a novel imaging approach that can noninvasively visualize, quantify, and characterize many musculoskeletal pathologies. This modality has revolutionized the field of radiology by capturing CT attenuation data across multiple energy levels and offering superior tissue characterization while potentially minimizing radiation exposure compared to traditional enhanced CT scans. Despite MRI being the preferred imaging method for many musculoskeletal conditions, it is not viable for some patients. Moreover, this technique is time-consuming, costly, and has limited availability in many healthcare settings. Thus, spectral CT has a considerable role in improving the diagnosis, characterization, and treatment of gout, inflammatory arthropathies, degenerative disc disease, osteoporosis, occult fractures, malignancies, ligamentous injuries, and other bone-marrow pathologies. This comprehensive review will delve into the diverse capabilities of dual-energy CT, a subset of spectral CT, in addressing these musculoskeletal conditions and explore potential future avenues for its integration into clinical practice.

Quantifying the influence of clay-bound water on wave dispersion and attenuation signatures of shale: An experimental study

Understanding the elastic and attenuation signatures of shales is of considerable interest for unconventional reservoir characterization and sealing capacity evaluation for CO2 sequestration and nuclear waste disposal. We have conducted laboratory measurements on seven shale samples at seismic frequencies (2–100 Hz) to study the effects of clay-bound water (CBW) on their wave dispersion and attenuation signatures. With nuclear magnetic resonance and a helium porosimeter, the volume of CBW in the shale samples is quantified. The forced-oscillation measurement reveals that Young’s modulus exhibits a continuous dispersion trend from 2 to 100 Hz. The extensional attenuation ([Formula: see text]) shows a weak frequency and pressure dependence on effective pressure ranging from 5 to 35 MPa. The magnitude of extensional attenuation shows a positive correlation with CBW, with an [Formula: see text] value of 0.89. It is found that 4% of CBW in the rock frame causes approximately a 5% modulus increase from 2 to 100 Hz. We adopt a constant [Formula: see text] model for assigning frequency-dependent bulk and shear moduli to the CBW in the rock-physics modeling, which can fit the experimental data of modulus dispersion and attenuation well, indicating that the bulk and shear moduli of CBW in shales might behave viscoelastically.

Monte Carlo calculated photon interaction coefficients for several body tissues.

Absorption of energy in body tissues because of radiation interactions may induce harmful outcomes such as cancer and hereditary effects due to a variety of damages in the integrity and activity of the cells. This study presents Monte Carlo calculated $\boldsymbol{\mu} /\boldsymbol{\rho}$, ${\boldsymbol{\mu}}_{\boldsymbol{en}}/\boldsymbol{\rho}$ and ${\boldsymbol{\mu}}_{\boldsymbol{tr}}/\boldsymbol{\rho}$ values of some common tissues and organs found in the human body (namely, adipose tissue, blood, bone-cortical, brain-grey/white matter, breast tissue, eye lens, lung tissue, muscle-skeletal, ovary, soft tissue and testes) as well as water for comparison purposes. The simulation model involves a monoenergetic point source producing a pencil beam where, depending on the parameter under study, particle flux, energy flux or absorbed dose from photon interactions are scored in the range of 10keV to 20MeV energy. The simulations were performed using the Monte Carlo package MCNP6.1 and provided $\boldsymbol{\mu} /\boldsymbol{\rho}$, ${\boldsymbol{\mu}}_{\boldsymbol{en}}/\boldsymbol{\rho}$ and ${\boldsymbol{\mu}}_{\boldsymbol{tr}}/\boldsymbol{\rho}$ values. The data produced in this study were compared with theoretical photon attenuation data from the XMUDAT database and demonstrated good agreement. The results, which are based on a simple model geometry and pure elemental compositions, indicate that this approach can be applied to evaluate $\boldsymbol{\mu} /\boldsymbol{\rho}$, ${\boldsymbol{\mu}}_{\boldsymbol{en}}/\boldsymbol{\rho}$ and ${\boldsymbol{\mu}}_{\boldsymbol{tr}}/\boldsymbol{\rho}$ in a broad energy range for any element, compound or mixture.

Novel techniques for in situ estimation of shear-wave velocity and damping ratio through MASW testing part II: a Monte Carlo algorithm for the joint inversion of phase velocity and phase attenuation

SUMMARY This paper deals with in situ characterization of the small-strain shear-wave velocity VS and damping ratio DS from an advanced interpretation of Multi-channel Analysis of Surface Waves (MASW) surveys. A new approach based on extracting Rayleigh wave data using the CFDBFa method has been discussed in the companion paper. This paper focuses on mapping the experimental Rayleigh wave phase velocity and attenuation into profiles of VS and DS versus depth, which is achieved through a joint inversion procedure. The joint inversion of phase velocity and attenuation data utilizes a newly developed Monte Carlo global search algorithm, which implements a smart sampling procedure. This scheme exploits the scaling properties of the solution of the Rayleigh eigenvalue problem to modify the trial earth models and improve the matching with the experimental data. Thus, a reliable result can be achieved with a limited number of trial ground models. The proposed algorithm is applied to the inversion of synthetic data and of experimental data collected at the Garner Valley Downhole Array site, as described in the companion paper. In general, inverted soil models exhibit well-defined VS profiles, whereas DS profiles are affected by larger uncertainties. Greater uncertainty in the inverted DS profiles is a direct result of higher variability in the experimental attenuation data, the limited wavelength range at which reliable values of attenuation parameters can be retrieved, and the sensitivity of attenuation data to both DS and VS. Nonetheless, the resulting inverted earth models agree well with alternative in situ estimates and geological data. The results stress the feasibility of retrieving both stiffness and attenuation parameters from active-source MASW testing and the effectiveness of extracting in situ damping ratio estimates from surface wave data.

Novel techniques for in situ estimation of shear-wave velocity and damping ratio through MASW testing – I: a beamforming procedure for extracting Rayleigh-wave phase velocity and phase attenuation

SUMMARY A robust, in situ estimate of shear-wave velocity VS and the small-strain damping ratio DS (or equivalently, the quality factor QS) is crucial for the design of buildings and geotechnical systems subjected to vibrations or earthquake ground shaking. A promising technique for simultaneously obtaining both VS and DS relies on the Multichannel Analysis of Surface Waves (MASW) method. MASW can be used to extract the Rayleigh wave phase velocity and phase attenuation data from active-source seismic traces recorded along linear arrays. Then, these data can be inverted to obtain VS and DS profiles. This paper introduces two novel methodologies for extracting the phase velocity and attenuation data. These new approaches are based on an extension of the beamforming technique which can be combined with a modal filter to isolate different Rayleigh propagation modes. Thus, the techniques return reliable phase velocity and attenuation estimates even in the presence of a multimode wavefield, which is typical of complex stratigraphic conditions. The reliability and effectiveness of the proposed approaches are assessed on a suite of synthetic wavefields and on experimental data collected at the Garner Valley Downhole Array and Mirandola sites. The results reveal that, under proper modelling of wavefield conditions, accurate estimates of Rayleigh wave phase velocity and attenuation can be extracted from active-source MASW wavefields over a broad frequency range. Eventually, the estimation of soil mechanical parameters also requires a robust inversion procedure to map the experimental Rayleigh wave parameters into soil models describing VS and DS with depth. The simultaneous inversion of phase velocity and attenuation data is discussed in detail in the companion paper.

Subsurface chlorophyll maxima reduce the performance of non-photochemical quenching corrections in the Southern Ocean

Non-photochemical quenching (NPQ) within phytoplankton cells often causes the daytime suppression of chlorophyll fluorescence in the Southern Ocean. This is problematic and requires accurate correction when chlorophyll fluorescence is used as a proxy for chlorophyll-a concentration or phytoplankton abundance. In this study, we reveal that Southern Ocean subsurface chlorophyll maxima (SCMs) are the largest source of uncertainty when correcting for NPQ of chlorophyll fluorescence profiles. A detailed assessment of NPQ correction methods supports this claim by taking advantage of coincident chlorophyll fluorescence and chlorophyll concentration profiles. The best performing NPQ correction methods are conditional methods that consider the mixed layer depth (MLD), subsurface fluorescence maximum (SFM) and depth of 20% surface light. Compared to existing methods, the conditional methods proposed halve the bias in corrected chlorophyll fluorescence profiles and improve the success of replicating a SFM relative to chlorophyll concentration profiles. Of existing methods, the X12 and P18 methods, perform best overall, even when considering methods supplemented by beam attenuation or backscatter data. The widely-used S08 method, is more varied in its performance between profiles and its application introduced on average up to 2% more surface bias. Despite the significant improvement of the conditional method, it still underperformed in the presence of an SCM due to 1) changes in optical properties at the SCM and 2) large gradients of chlorophyll fluorescence across the pycnocline. Additionally, we highlight that conditional methods are best applied when uncertainty in chlorophyll fluorescence yields is within 50%. This highlights the need to better characterize the bio-optics of SCMs and chlorophyll fluorescence yields in the Southern Ocean, so that chlorophyll fluorescence data can be accurately converted to chlorophyll concentration in the absence of in situ water sampling.

A hybrid CNN–BiLSTM–AT model optimized with enhanced whale optimization algorithm for remaining useful life forecasting of fuel cell

To further improve the remaining useful life forecasting accuracy of fuel cells using classic deep learning models, a convolutional neural network combining bidirectional long and short-term memory networks (BiLSTM) and attention mechanism (AT) is optimized with the enhanced whale optimization algorithm (EWOA). Singular spectrum analysis preprocesses the attenuation data to eliminate noise and enhance its effective information; the CNN–BiLSTM model extracts spatiotemporal features and learns historical and future information; AT further explores the spatiotemporal correlation; and EWOA optimizes its hyperparameters to reduce human intervention error. Results demonstrate that, compared with long and short-term memory, CNN–LSTM, CNN–BiLSTM, CNN–BiLSTM–AT, and CNN–BiLSTM–AT optimized with other algorithms, the CNN–BiLSTM–AT model optimized with EWOA achieves lower root mean square error, mean absolute error, mean absolute percentage error, and relative errors of 0.1951%–0.2059%, 0.1267%–0.1538%, 0.0319%–0.0366%, and 0.026%–0.036%, respectively, with different training data. Importantly, the proposed model still maintains good prediction robustness with over 40% of the missing data.

Effect of Eu3+ ions concentration on visible red luminescence and radiative shielding properties of SrO–Al2O3– BaCl2–B2O3– TeO2 glasses

Trivalent europium (Eu3+) ions doped 10SrO-(10-x)Al2O3–10BaCl2–60B2O3–10TeO2 glasses were fabricated by the melt-and-quenching technique and characterized for excitation, absorption, emission, decay methods to analyze the suitability of the glasses for photonic device applications. In addition, gamma attenuation data of the prepared glasses were Obtained for energies 15 keV ≤ E ≤ 10 MeV using FLUKA and XCOM methods to check their suitability for radiative shielding purposes. Direct allowed, indirect allowed band gaps and Urbach energies were estimated from absorption spectra. Emission spectra obtained for an excitation wavelength of 362 nm have been used to estimate J-O intensity parameters Ωλ (where λ = 2, 4). The intensity parameters Ω2 and Ω4 were again used to evaluate various radiative properties for the emission transition 5D0→7F2 of Eu3+ ions doped OCBT glasses. Decay curves were well fitted by single exponential and in turn used to estimate experimental lifetime (τexp) of metastable state (5D0) of Eu3+ions. The analysis on radiative properties showed that 2.5 mol % of Eu3+ ions activated OCBT glasses for the emission transition 5D0→7F2 is well suitable for visible red lasers and display applications. Analysis of evaluated interaction parameters for gamma radiation fast and thermal neutrons showed clear cut dependence on the Eu2O3 content of the glasses. In addition, the radiation absorption ability of the glasses was compared with different classes of concrete, commercial glass shields, and nonconventional shielding materials. The present glasses showed great potential for deployment in radiation absorption roles in nuclear technologies.

Photon counting x-ray detectors as scatter probes.

Direct conversion x-ray Photon Counting Detectors (PCD) are posed to play a vital role in future medical imaging devices such as Computed Tomography (CT) scanners. PCD are expected to improve current CT technology on several fronts, such as resolution, dose utilization, and spectral performance. However, they are not readily expected to improve the handling of object scatter, one of the major sources of image artifacts in CT technology. We explore a potential method for obtaining in-situ object scatter estimation using the same PCD array used in the x-ray imaging system, such as in computed tomography. This unexpected benefit of using PCD has the potential to improve the image quality by providing better input into the scatter estimation and correction algorithms used in image reconstruction. In CT scanners the primary method for rejecting scatter signal originating from the scanned object relies on placing anti-scatter grids (ASG) close to the detector plane. This remains the case when transitioning to using PCD instead of energy integration detectors in CT. However, the combination of PCD and ASG opens a possibility to use some of the unique properties of PCD, namely, very low noise and coincidence counters to obtain, in addition to the attenuation data, a simultaneous and instantaneous estimate of the scatter signal reaching every detector element. When a small air gap is introduced between the ASG and the detector surface, the scatter radiation with large angular distribution has a greater probability of producing charge sharing events that can be detected by a coincidence counter. In this work we demonstrate the feasibility of such an approach in a tabletop experiment using PCD detector that lacks coincidence counting capability, instead we use the spectral signature of split charge events as proxy to coincidence counting. For this purpose, we first demonstrate the spectral impact of ASG misalignment using the same experimental setup. In addition, we perform a separate tabletop scattering experiment from a narrow column of water that demonstrates another potential use of the low noise capabilities of PCDs. We measured and quantified the high sensitivity of the spectral response to ASG alignment on the PCD detector pixel array, we found that the probability of energy misregistration of 60keV photons can increase by up to a factor of 3 when the ASG is poorly aligned. We then leveraged these results to obtain an estimate on the expected increase in coincidence counts for a wide range of scatter-to-primary (SPR) ratio and find a good match with expectations from a geometric modeling of the system, where the expected increase in coincidences was of the order of the SPR. Finally, the low noise detector also allowed us to measure the real space scatter signal associated with the coherent molecular form factor of water, revealing the ring-shaped scatter signal with an energy dependent distribution that was well captured by calculation. The advent of PCD detectors and their imminent use in commercial CT scanners opens new and exciting possibilities for utilizing PCD detectors in unexpected ways. In this proof-of-concept study, we showed how charge sharing, a spectral information degrading effect, can instead be used to obtain in-situ scatter estimation. We also demonstrated the PCD ability to perform extremely sensitive measurements using affordable benchtop setup for investigations normally reserved for synchrotron facilities.

SOH estimation method for lithium-ion batteries under low temperature conditions with nonlinear correction

The burgeoning growth of green energy in the transportation sector has resulted in increased expectations for battery longevity and safety. However, the capacity of lithium-ion batteries (LIBs) decreases with each successive charge and discharge cycle. And under harsh operating conditions, the capacity decay can exhibit strong nonlinearity. To enable effective battery management under such complex conditions, it is crucial to possess precise understanding of the state of health (SOH) of LIB. In this study, low-temperature aging experiments were designed to obtain capacity attenuation data of LIBs. Then the nonlinear component in capacity decay is identified and transformed into model nonlinear correction. Subsequently, we developed a long short-term memory (LSTM) neural network and extracted incremental capacity (IC) features based on experimentally collected data to train the model. The findings indicate that by training with only one cell aging dataset, the model can estimate the SOH for other samples. Furthermore, we introduced nonlinear correction features with an attention mechanism (AM) and analyzed the improvement of prediction accuracy through feature optimization and network adjustment to achieve SOH estimation with a maximum root mean square error (RMSE) of 0.92 %. This approach provides a potential solution for predicting SOH of LIBs at low temperature.

DETECTING MOISTURE IN BAUXITE USING MICROWAVES

AbstractMathematical modelling of microwaves travelling through bauxite ore provides a way to compute moisture content in the free space transmission method given data on signal attenuation, phase shift and variable bauxite depth. We extend a recently developed four-layer model that uses coupled ordinary differential wave equations for the electric field together with continuity boundary conditions at interfaces between ore, air and antenna to find a solution that incorporates multiple internal reflections in ore and air. The model provides good fits to data, depending on ore permittivity and conductivity.Our extensions are to use effective medium models to obtain electromagnetic properties of the ore mixture from moisture content and to incorporate the damping effects of scattering from the ore surface. Our model leads to a formula for the received signal showing how signal strengths SS and phase shifts depend on the moisture content of the bauxite ore, through the effects of moisture on permittivity and conductivity. We show that SS may be noninvertible, indicating that attenuation data alone cannot be used to infer moisture content. Combining with phase data typically corrects the noninvertibility. Reducing the operating frequency dramatically improves the usefulness of signal strength data for inferring moisture content.

Remaining useful life prediction of sodium-ion batteries based on ICEEMDAN-CNN-GRU

A hybrid battery remaining useful life (RUL) prediction model based on ICEEMDAN-CNN-GRU(M1) is proposed to address the nonlinearity and complexity of capacity degradation in sodium-ion batteries. Firstly, capacity attenuation data and some indirect parameters easily obtainable by sensors are experimentally measured. The original capacity sequence is reconstructed into a new one using the ICEEMDAN method to effectively suppress the influence of capacity regeneration and noise signals. Secondly, a hybrid CNN-GRU prediction model is constructed by leveraging the advantages of convolutional neural networks (CNN) in the field of data mining and gated recurrent unit (GRU) in time series prediction. Three sets of indirect parameters are used as inputs, and the reconstructed capacity is used as the output for RUL prediction model training with different starting points. Finally, the effectiveness of the algorithm is verified through data from three different rates, and the predicted indicators are better than those of traditional algorithms such as GRU, LSTM, and SVM.

Wind Direction Extraction from X-Band Marine Radar Images Based on the Attenuation Horizontal Component

This paper presents a novel algorithm based on the attenuation horizontal component for wind direction retrieval from X-band marine radar images. The range dependence of radar return on the ocean surface can be presented in radar images, and the radar return decreases with the increase in range. The traditional curve-fitting method averages the radar return of the whole range to retrieve the wind direction, but it is vulnerable to the interference of fixed objects and long-range low-intensity pixel points. For the pixels with the same range in the polar coordinates of the radar image, the ideal range attenuation model is derived by selecting the pixels with the highest intensity value. The ideal attenuation model is used to fit the attenuation data and calculate the attenuation horizontal component at each azimuth direction. To eliminate the effect of outliers, the iterative optimization method is used in the estimation of the attenuation horizontal component and the weights of the data are continuously updated. Finally, the wind direction is determined based on the azimuthal dependence of the attenuation horizontal component. This algorithm was tested using shipboard radar images and anemometer data collected in the East China Sea. The results show that, compared with the single curve-fitting method, the proposed algorithm can improve the wind direction retrieval accuracy in the case of more fixed targets. Under the condition of more fixed targets, the deviation and root mean square error are reduced by 16.3° and 16.2°, respectively.