Backscatter Energy Research Articles

A practical guide to characterizing irradiated nuclear fuels using FIB tomography

Focused ion beam (FIB) tomography with combined electron backscatter diffraction (EBSD) and energy dispersive x-ray spectroscopy (EDS) is a technique capable of statistically characterizing the microstructure and spatial compositional variation of nuclear fuel in three-dimensions (3D). The 3D visualization from FIB tomography provides a comprehensive picture of the interconnected microstructural and compositional features that can impact fuel performance. While these features are often characterized with surface examination, the complexity and relationship of fission products and grain boundary networks may not fully be captured by these 2D methods. This work presents a practical guide to FIB tomography that is tailored to nuclear fuel characterization. The steps used to collect and process the data are provided along with the scripts used to process the data. Additionally, suggestions for future characterization efforts utilizing this approach are given.

Potential of the Coupled WRF/WRF-Hydro Modeling System for Flood Forecasting in the Ouémé River (West Africa)

Since the beginning of the 2000s, most of the West-African countries, particularly Benin, have experienced an increased frequency of extreme flood events. In this study, we focus on the case of the Ouémé river basin in Benin. To investigate flood events in this basin for early warning, the coupled atmosphere–hydrology model system WRF-Hydro is used, and analyzed for the period 2008–2010. Such a coupled model allows exploration of the contribution of atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro to correctly simulate streamflow in the Ouémé river basin is assessed by forcing the model with operational analysis datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF). Atmospheric and land surface processes are resolved at a spatial resolution of 5 km. The additional surface and subsurface water flow routing are computed at a resolution of 500 m. Key parameters of the hydrological module of WRF-Hydro are calibrated offline and tested online with the coupled WRF-Hydro. The uncertainty of atmospheric modeling on coupled results is assessed with the stochastic kinetic energy backscatter scheme (SKEBS). WRF-Hydro is able to simulate the discharge in the Ouémé river in offline and fully coupled modes with a Kling–Gupta efficiency (KGE) around 0.70 and 0.76, respectively. In the fully coupled mode, the model captures the flood event that occurred in 2010. A stochastic perturbation ensemble of ten members for three rain seasons shows that the coupled model performance in terms of KGE ranges from 0.14 to 0.79. Additionally, an assessment of the soil moisture has been developed. This ability to realistically reproduce observed discharge in the Ouémé river basin demonstrates the potential of the coupled WRF-Hydro modeling system for future flood forecasting applications.

Fabrication of enriched 170Yb2O3 thin targets for studying asymmetric fission in sub-lead mass region

Owing to the highly oxidizing and chemically active nature of rare-earth elements, preparation of isotopically enriched thin targets of rare-earth metals has been a challenging task. The successful fabrication of thin films of enriched 170Yb2O3 on carbon backing with areal density in the range 160–200 μg/cm2 and approximately 22μg/cm2, respectively is described here along with the various challenges encountered during the fabrication and new optimized operational parameters. On account of limited availability and high cost of the enriched 170Yb due to its extremely low natural abundance, many iterations were attempted with natural ytterbium to optimize the evaporation setup and its associated parameters. The electron beam physical vapour deposition technique in ultra-high vacuum facility was found suitable for the evaporation and a specially designed cylindrical tantalum crucible was used to further improve the collection efficiency. Optimization trials were carried out with the deposition parameters reported in the literature but a considerably high concentration of tantalum was noticed in the films. This impurity could drastically contaminate the experimental data and needed to be minimized. The present work reports a new set of deposition parameters optimized for the fabrication of thin ytterbium oxide films with the tantalum contamination reduced to indiscernible amounts. The final evaporation of enriched 170Yb2O3 was carried out with a 30 mg of the material that was found to be fully consumed. Various characterization techniques were carried out to ascertain thinness, purity and the elemental composition of the films viz. Rutherford Backscattering Spectroscopy (RBS) and Energy Dispersive X-ray Spectroscopy (EDS). These measurements corroborated the achieved optimization of deposition parameters with negligible contribution of impurities in the films. The purity and stability of the films were further established with a good quality of data obtained after irradiation with 28Si beam.

Surface adsorption structure determination using backscattering photoelectron diffraction

Following a brief historical introduction, the distinction between two modes of photoelectron diffraction, high-energy forward scattering and low energy backscattering, and two modes of data collection, angle-scan and energy-scan, is explained. This is followed by a review of energy-scan backscattering photoelectron diffraction (PhD). Examples are presented of atomic adsorption and molecular adsorption on metal surfaces and molecular adsorption on oxide surfaces. The paper ends with a brief survey of future prospects for the application of the PhD technique.

Subgrid-scale models of isotropic turbulence need not produce energy backscatter

This investigation questions the importance of inverse interscale energy fluxes, the so-called energy backscatter, for the modelling of the energy cascade in large-eddy simulations (LES) of turbulent flows. The invariance of the filtered Navier–Stokes equations to divergence-preserving transformations of the subgrid-scale (SGS) stress tensor is exploited here to explore alternative representations of the local SGS energy fluxes. Numerical optimisation procedures are applied to the SGS stress tensor – obtained by filtering isotropic turbulence flow fields – to find alternative stresses that satisfy the filtered Navier–Stokes equations, but that produce negligible backscatter. These alternative SGS stresses show that backscatter represents not a flux of energy from the subgrid to the resolved scales, but conservative spatial fluxes, and that it need not be modelled to reproduce the local energetic exchange between the resolved and the subgrid scales in LES. From the perspective of statistical mechanics, it is argued that this is a consequence of the strong statistical irreversibility of inertial-range dynamics, which precludes inverse energy cascades even in a local sense. These findings show that the energy cascade is strongly unidirectional locally, and that it can be modelled as an irreversible sink of energy, justifying the extended use of purely dissipative SGS models in LES.

Throughput Fairness for Wireless Powered Cognitive Hybrid Active-Passive Communications

In this paper, we consider a backscatter communication (BackCom)-based cognitive network that consists of one primary transmitter, one primary receiver, multiple secondary transmitters (STs), and one secondary receiver (SR). Each ST operates in the BackCom or energy harvesting model. Our goal is to jointly optimize the energy harvesting and backscatter time, the transmit power of the primary transmitter, and the power reflection coefficient of each ST to maximize the sum throughput of all the STs under a nonlinear energy harvesting model while satisfying multiple constraints, i.e., the energy causality of each ST, the quality of service of the primary transmitter, etc. The formulated problem is nonconvex due to the coupled variables and is hard to solve. In order to address this problem, we decouple partially coupled variables by using the properties of the objective function and constructing auxiliary variables, and the remaining coupled variables are decoupled via successive convex approximation (SCA). On this basis, a SCA-based iterative algorithm is developed to solve the formulated problem. Simulation results are provided to support our work.

Geophysical fluid models with simple energy backscatter: explicit flows and unbounded exponential growth

Motivated by numerical schemes for large-scale geophysical flow, we consider the rotating shallow water and Boussinesq equations on the whole space with horizontal kinetic energy backscatter source terms built from negative viscosity and stabilising hyperviscosity with constant parameters. We study the impact of this energy input through various explicit flows, which are simultaneously solving the nonlinear equations and the linear equations that arise upon dropping the transport nonlinearity, i.e. the linearisation in the zero state. These include barotropic, parallel and Kolmogorov flows as well as monochromatic inertia gravity waves. With focus on stable stratification, we find that the backscatter generates numerous solutions of this type that grow exponentially and unboundedly, also with vertical structure. This signifies the possibility of undesired energy concentration into specific modes due to the backscatter. Families of steady-state flows of this type arise as well and superposition principles in the nonlinear equations provide explicit sufficient conditions for instability of some of these. For certain steady barotropic flows of this type, we provide numerical evidence of eigenmodes whose growth rates are proportional to the amplitude factor of the flow. For all other arising steady solutions, we prove that this is not possible.

Sum-Throughput Maximization in Backscatter Communication-Based Cognitive Networks

In this paper, we consider a backscatter communication (BackCom) based cognitive network that consists of one primary transmitter, one primary receiver, multiple secondary transmitters (STs), and one secondary receiver (SR). Each ST operates in the BackCom or energy harvesting model. Our goal is to jointly optimize the energy harvesting and backscatter time, the transmit power of the primary transmitter, and the power reflection coefficient of each ST to maximize the sum throughput of all the STs under a nonlinear energy harvesting model while satisfying multiple constraints, i.e., the energy causality of each ST, the Quality of Service of the primary transmitter, etc. The formulated problem is nonconvex due to the coupled variables and hard to solve. In order to address this problem, we decouple partial coupled variables by using the properties of the objective function and constructing auxiliary variables, and the remaining coupled variables are decoupled via successive convex approximation (SCA). On this basis, a SCA based iterative algorithm is developed to solve the formulated problem. Simulation results are provided to support our work.

Turbulence kinetic energy transfers in direct numerical simulation of shock-wave–turbulence interaction in a compression/expansion ramp

A direct numerical simulation is performed for a supersonic turbulent boundary layer interacting with a compression/expansion ramp at an angle $\alpha =24^{\circ }$ , matching the same operating conditions of the direct numerical simulation by Priebe & Martín (J. Fluid Mech., vol. 699, 2012, pp. 1–49). The adopted numerical method relies on the high-order spectral difference scheme coupled with a bulk-based, low-dissipative, artificial viscosity for shock-capturing purposes (Tonicello et al., Comput. Fluids, vol. 197, 2020, 104357). Filtered and averaged fields are evaluated to study total kinetic energy transfers in the presence of non-negligible compressibility effects. The compression motions are shown to promote forward transfer of kinetic energy down the energy cascade, whereas expansion regions are more likely to experience backscatter of kinetic energy. A standard decomposition of the subgrid scale tensor in deviatoric and spherical parts is proposed to study the compressible and incompressible contributions in the total kinetic energy transfers across scales. On average, the correlation between subgrid scale dissipation and large-scale dilatation is shown to be caused entirely by the spherical part of the Reynolds stresses (i.e. the turbulent kinetic energy). On the other hand, subtracting the spherical contribution, a mild correlation is still noticeable in the filtered fields. For compressible flows, it seems reasonable to assume that the eddy-viscosity approximation can be a suitable model for the deviatoric part of the subgrid scale tensor, which is exclusively causing forward kinetic energy cascade on average. Instead, more complex models are likely to be needed for the spherical part, which, even in statistical average, provides an important mechanism for backscatter.

Wireless powered hybrid backscatter-active communications with hardware impairments

Wireless powered hybrid backscatter-active communication can full make use of the different tradeoff between power consumption and achievable rate of the active and backscatter communications, and thus achieving a better performance than wireless powered active or backscatter communications. In this paper, we design a throughput maximization-based resource allocation scheme for a wireless powered hybrid backscatter-active communication network, while considering the hardware impairments at all RF front ends of each transceiver. Towards this end, we formulate a problem by jointly optimizing the transmit power of the dedicated energy source, the time for pure energy harvesting, backscatter and active communications, the power reflection coefficient, and the transmit power of each IoT node during active communications. The formulated problem is non-convex and different to solve. Subsequently an iterative algorithm based on the block coordinated decent technology is proposed to address the above problem. Simulation results verify that our proposed iterative algorithm converges very fast and that the proposed scheme outperforms the baseline schemes in terms of the throughput.

A simple method to calculate incident dose for the proximity effect correction

A simple method for correcting the proximity effect (PEC) is demonstrated. By modifying the discretized point spread function (PSF), the incident dose is expressed as a function of the ideal deposition energy density, the backscattering energy and the center energy fraction of the PSF matrix. The optimum incident dose can thus be solved iteratively. Then, the constraint to the iterative equation is discussed and the allowed value range of the center energy fraction in the discretized PSF is calculated under the different pattern densities. The correcting result is finally experimental verified. Results showed the line width deviation from the mean is decreased from the maximum of 0.01 μ. to that of below 0.003 μ.m after the PEC applied. The improved critical dimension (CD) uniformity indicating a uniformity energy distribution is achieved by this method.

The Fusion of Physical, Textural, and Morphological Information in SAR Imagery for Hurricane Wind Speed Retrieval Based on Deep Learning

This study developed a deep-learning-based model to retrieve sea surface hurricane winds from synthetic aperture radar (SAR) imagery. We introduce the essential idea, residual learning, of the Residual Net into the artificial neural network and design a deep cross-layer concatenation network. The model inputs include SAR measured physical parameters in backscattering energy, the texture feature represented by the grey level co-occurrence matrix, and the morphological hurricane feature. We collected 45 satellite SAR images from Sentinel-1 over hurricane conditions. These images were divided into 39 and 6 for model development and independent testing. A total of 16,127 wind samples acquired from 39 SAR images and simultaneously measured by the Stepped Frequency Microwave Radiometer were collected as model tuning datasets, among which 80% and 20% were used for training and validation. Our validation results show that the deep-learning-based model achieved a correlation coefficient (CORR) and root-mean-square error (RMSE) of 0.98 and 1.72 m/s for wind speeds up to 75 m/s. We further applied the model to six independent SAR images. The model significantly outperformed two existing geophysical algorithms and one backpropagation neural network algorithm with the RMSE is 2.61 m/s and a CORR of 0.95. Moreover, statistical analysis in different wind speed regimes indicates that our model shows a stable performance improvement than comparable algorithms. The RMSE decreases 10%~ 70%, especially the reduction of RMSE is more than 45% at high wind speed (> 42 m/s). Furthermore, adding an independent rainfall estimate to the deep-learning model further enhanced the wind retrieval algorithm.

Comparing Backscatter Communication and Energy Harvesting in Massive IoT Networks

Backscatter communication (BC) and radio-frequency energy harvesting (RF-EH) are two promising technologies for extending the battery lifetime of wireless devices. Although there have been some qualitative comparisons between these two technologies, quantitative comparisons are still lacking, especially for massive IoT networks. In this paper, we address this gap in the research literature, and perform a quantitative comparison between BC and RF-EH in massive IoT networks with multiple primary users and multiple low-power devices acting as secondary users. An essential feature of our model is that it includes the interferences caused by the secondary users to the primary users, and we show that these interferences significantly impact the system performance of massive IoT networks. For the RF-EH model, the power requirements of digital-to-analog and signal amplification are taken into account. We pose and solve a power minimization problem for BC, and we show analytically when BC is better than RF-EH. The results of the numerical simulations illustrate the significant benefits of using BC in terms of saving power and supporting massive IoT, compared to using RF-EH. The results also show that the backscatter coefficients of the BC devices must be individually tunable, in order to guarantee good performance of BC.

A study on the creep behavior of alloy 709 using in-situ scanning electron microscopy

In this research, an experimental evaluation of creep properties of Alloy 709 in the temperature range of 750–850 °C was undertaken. Alloy 709 is a novel austenitic stainless steel with 20% Cr and 25% Ni by wt% that was developed for application in structural components of nuclear power plants. Creep rupture tests were conducted in an in-situ heating-loading and Scanning Electron Microscope (SEM) unit equipped with Electron Backscatter Diffraction (EBSD) detector and Energy Dispersive Spectroscopy (EDS). “Real-time” creep damage mechanisms of Alloy 709 at various stresses and temperatures using a flat, un-notched sample with continuously reducing cross-section is studied so that the failure and maximum creep damage occurred at the center of the sample where the in-situ SEM imaging could be focused. Accelerated creep tests at temperatures and stresses above service conditions were performed by employing multiple blocks of constant loads where the loads were increased once the sample attained constant creep rate, indicating a secondary creep regime. This technique ensures multiple data points can be obtained from the same test, saves the time required for an otherwise long-term creep test and usage of SEM. Coincident Site Lattice (CSL) boundary maps were collected as control maps before testing, and the grain boundaries were observed during the creep test to understand the effect of grain boundary character on the creep damage mechanism. Void growth, grain boundary separation, and sliding were found to be the main creep mechanisms whose rate is dependent on stress and temperature. Failure mechanisms studied on the fracture surface using SEM fractography were correlated to the sample surface observations to create complementary information to better understand the underline creep mechanism of Alloy 709.

Region-Based Polarimetric Covariance Difference Matrix for PolSAR Ship Detection

To more effectively detect small ships, in this article, a novel region-based polarimetric covariance difference matrix [RP] is put forward, which mainly consists of two stages. Briefly speaking, in the first stage, a new pixel representation way is proposed to depict the spatial characteristics of pixel, through which the difference information related to pixel’s local region is calculated as well. In the second stage, the global region difference information of pixel is computed. Finally, we construct [RP] via fusing these two different kinds of information together with a balance factor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$c$ </tex-math></inline-formula> . Meanwhile, considering that the backscattering energy of ships is useful for ship detection, a new intensity-driven polarimetric notch filter (ID-PNF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RP</sub> ) is also derived from [RP]. Three different datasets are adopted to evaluate the effectiveness of [RP] and ID-PNF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RP</sub> . Experimental results show that: 1) compared with the polarimetric covariance matrix [ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula> ] and the polarimetric covariance difference matrix [ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula> ], [RP] is more suitable for ship detection and 2) compared with the original geometrical perturbation-polarimetric notch filter (GP-PNF) and the total power detector SPAN, the proposed method ID-PNF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RP</sub> can better detect small ships with greater figure of merit (FoM) and target-to-clutter ratio (TCR) values.

Microstructure and electrochemical behavior of contemporary Ti6Al4V implant alloys.

Ti6Al4V is the most common titanium alloy within the biomaterial field. While material standards for different variations of this alloy exist, there are only minimal requirements with respect to its microstructure which is directly related to the alloy's properties. Thus, a better understanding of the Ti6Al4V microstructure of common contemporary implant components and its effect on the electrochemical behavior is needed; including additively manufactured (AM) devices. Therefore, this study aimed at characterizing the microstructures of conventional and AM total joint replacement components, and to identify the effect of microstructure on the electrochemical behavior. Thus, 22 components from conventional (surgically retrieved cast and wrought implants) and AM implants (not previously implanted) were analysed to characterize microstructure by means of electron backscatter diffraction (EBSD) and energy dispersive X-Ray spectroscopy (EDS), and tested to determine its electrochemical behavior (potentiodynamic polarization and EIS). The microstructure of the conventional implants varied broadly but could be categorized into four groups as to their grain size and shape: fine equiaxed, coarse equiaxed, bimodal, and lamellar. The AM components exhibited a fifth category: lath-type. The AM components had a network of β-phase along the α-phase grain boundaries, prior β-grains, and manufacturing voids. Finally, the electrochemical study showed that the equiaxed coarse grains and lath-type grains (AM components) had inferior electrochemical behavior, whereas cast alloys had superior electrochemical behaviour; fine-grained wrought alloys likely provide the best compromise between electrochemical and mechanical properties.

High Temperature Fatigue of Aged Heavy Section Austenitic Stainless Steels.

This work investigates two austenitic stainless steels, Sanicro 25 which is a candidate for high temperature heavy section components of future power plants and Esshete 1250 which is used as a reference material. The alloys were subjected to out-of-phase (OP) thermomechanical fatigue (TMF) testing under strain-control in the temperature range of 100 C to 650 C. Both unaged and aged (650 C, 3000 h) TMF specimens were tested to simulate service degradation resulting from long-term usage. The scanning electron microscopy methods electron backscatter diffraction (EBSD) and energy dispersive spectroscopy (EDS) were used to analyse and discuss active failure and deformation mechanisms. The Sanicro 25 results show that the aged specimens suffered increased plastic straining and shorter TMF-life compared to the unaged specimens. The difference in TMF-life of the two test conditions was attributed to an accelerated microstructural evolution that provided decreased the effectiveness for impeding dislocation motion. Ageing did not affect the OP-TMF life of the reference material, Esshete 1250. However, the structural stability and its resistance for cyclic deformation was greatly reduced due to coarsening and cracking of the strengthening niobium carbide precipitates. Sanicro 25 showed the higher structural stability during OP-TMF testing compare with the reference material.

A Novel Approach to Inhibit Intergranular Corrosion in Ferritic Stainless Steel Welds Using High-Speed Laser Cladding

Ferritic stainless steels are prone to localized corrosion phenomena such as pitting corrosion or intergranular corrosion, in particular when jointed by fusion welding processes. State-of-the-art techniques to avoid intergranular corrosion mainly consist of alternating alloy concepts or post-weld heat-treatments—all of which are associated with increased production costs. Hence, the present investigation seeks to introduce a novel approach for the inhibition of intergranular corrosion in ferritic stainless steel welds through the use of high-speed laser cladding. Here, vulnerable sites prone to intergranular corrosion along the weld seam area are coated with a chemically resistant alloy, whereby an overlap is achieved. Optical and electron microscopy as well as computer tomography and tensile tests reveal that the detrimental effects of intergranular corrosion in both stabilized and unstabilized ferritic stainless steel are substantially reduced. In addition to that, the effects of varying overlap widths on the identified corrosion phenomena are studied. Moreover, the resulting dilution and precipiation phenomena at the clad–sheet interface are thoroughly characterized by electron backscatter diffraction and energy dispersive X-ray spectroscopy, whereby interrelationships to corrosion resistance can be drawn. As a result of this investigation, the number of techniques for the inhibition of intergranular corrosion is enlarged, and substantial cost-saving potentials in the manufacturing industry are unlocked.

Quantitative Electron-Excited X-ray Microanalysis With Low-Energy L-shell X-ray Peaks Measured With Energy-Dispersive Spectrometry.

Quantification of electron-exited X-ray spectra following the standards-based “k-ratio” (unknown/standard intensity) protocol with corrections for “matrix effects” (electron energy loss and backscattering, X-ray absorption, and secondary X-ray fluorescence) is a well-established method with a record of rigorous testing and extensive experience. Two recent studies by Gopon et al. working in the Fe–Si system and Llovet et al. working in the Ni–Si system have renewed interest in studying the accuracy of measurements made using L-shell X-ray peaks. Both have reported unexpectedly large deviations in analytical accuracy when analyzing intermetallic compounds when using the low photon energy Fe or Ni L-shell X-ray peaks with pure element standards and wavelength-dispersive X-ray spectrometry. This study confirms those observations on the Ni-based intermetallic compounds using energy-dispersive X-ray spectrometry and extends the study of analysis with low photon energy L-shell peaks to a wide range of elements, Ti to Se. Within this range of elements, anomalies in analytical accuracy have been found for Fe, Co, and Ge in addition to Ni. For these elements, the use of compound standards instead of pure elements usually resulted in significantly improved analytical accuracy. However, compound standards do not always provide satisfactory accuracy as is demonstrated for L-shell peak analysis in the Fe–S system: FeS and FeS2 unexpectedly do not provide good accuracy when used as mutual standards.

Analisis Akustik Target Strength Penyu Hijau (Chelonia Mydas) Melalui Pengukuran Secara Terkontrol Pada Frekuensi 200 kHz

ABSTRACT&#x0D; Turtles are reptiles that live in the sea and are able to migrate over long distances along the Indian Ocean, Pacific Ocean and Southeast Asia. Currently the number of turtle populations in nature has greatly decreased. This population decline is caused by natural factors and human activities that endanger the population directly or indirectly. At this time the tagging set technique (ID tag code) is a method that is often used to detect the presence of turtles by attaching tags to female turtles who are landing to lay eggs on the beach or while in captivity or the discovery of the mother turtle by fishermen. One other method that can be used to detect the presence of turtles is to use the acoustic method. The purpose of this study was to analyze the characteristics of the acoustic backscattering energy of the green turtle (Chelonia mydes) and to analyze the relationship between target strength and total body length of the green turtle (Chelonia mydas). This research was conducted in the Tapak Paderi waters pond, Bengkulu City, in August-October 2020. The average target strength (TS) value for green turtles was -48.07 dB. Based on the regression equation, the value of determination (R2) obtained is 0.78. Where this value shows that the total length of the green turtle has an effect of 78% on the average target strength (TS) value, while for 22% it is caused by other factors such as body shape, environmental factors and other factors. Based on the ANOVA test, it can be concluded that there is a relationship between the total length and the value of the target strength (TS) on the green turtle or the value of the total length has an influence on the value of the target strength (TS) on the green turtle.&#x0D;