
The environmental impact of mining and smelting in the world-class Monte Amiata mercury (Hg) ore field has long been studied, before and after the final closure in 1982. A first summary was presented in 2015. With this contribution, we review the studies conducted in the last eight years. The most significant results include ⅰ) Hg-isotope characterization of primary ore (cinnabar), smelting waste (calcines), soil, fish and stream sediments; ⅱ) analysis of the interplay between geomorphological evolution, fluvial dynamics and Hg distribution in the Paglia River catchment, which drains the main mining areas; ⅲ) an improved quantification of the Hg loads discharged to the Mediterranean Sea; ⅳ) the use of biomonitors to reveal the dispersion of Hg; ⅴ) new detailed surveys, including innovative techniques, of Hg distribution in air; ⅵ) specific investigations to support the ongoing reclamation at Abbadia San Salvatore, the main mining and smelting center of the district, and ⅶ) the assessment of the variability of Hg distribution in air, water and soil from the reclaimed Siele mine. Despite these progresses, there are further steps to be conducted to achieve optimal management of the wide contamination evidenced in this district. It is now fully clear that the diffuse character of contamination results in unfeasible hypotheses for total remediation. Therefore, the goal is that of a sustainable coexistence between contamination and human activities. This goal may involve the following activities: a) implementation of GIS-based contamination maps as a direct operational instrument for local authorities to tune up specific limitations and regulations of human activities (e.g., fishing, instream quarrying and wildfire management); b) mitigation measures such as increasing the vegetal cover of river banks to limit erosion and runoff, and c) continuous monitoring of air, water and soil contamination, including transfer to the food chain.
Citation: Alessia Nannoni, Federica Meloni, Marco Benvenuti, Jacopo Cabassi, Francesco Ciani, Pilario Costagliola, Silvia Fornasaro, Pierfranco Lattanzi, Marta Lazzaroni, Barbara Nisi, Guia Morelli, Valentina Rimondi, Orlando Vaselli. Environmental impact of past Hg mining activities in the Monte Amiata district, Italy: A summary of recent studies[J]. AIMS Geosciences, 2022, 8(4): 525-551. doi: 10.3934/geosci.2022029
[1] | Muhammad Tariq, Hijaz Ahmad, Soubhagya Kumar Sahoo, Artion Kashuri, Taher A. Nofal, Ching-Hsien Hsu . Inequalities of Simpson-Mercer-type including Atangana-Baleanu fractional operators and their applications. AIMS Mathematics, 2022, 7(8): 15159-15181. doi: 10.3934/math.2022831 |
[2] | Saad Ihsan Butt, Artion Kashuri, Muhammad Umar, Adnan Aslam, Wei Gao . Hermite-Jensen-Mercer type inequalities via Ψ-Riemann-Liouville k-fractional integrals. AIMS Mathematics, 2020, 5(5): 5193-5220. doi: 10.3934/math.2020334 |
[3] | Saad Ihsan Butt, Erhan Set, Saba Yousaf, Thabet Abdeljawad, Wasfi Shatanawi . Generalized integral inequalities for ABK-fractional integral operators. AIMS Mathematics, 2021, 6(9): 10164-10191. doi: 10.3934/math.2021589 |
[4] | Jamshed Nasir, Saber Mansour, Shahid Qaisar, Hassen Aydi . Some variants on Mercer's Hermite-Hadamard like inclusions of interval-valued functions for strong Kernel. AIMS Mathematics, 2023, 8(5): 10001-10020. doi: 10.3934/math.2023506 |
[5] | Soubhagya Kumar Sahoo, Fahd Jarad, Bibhakar Kodamasingh, Artion Kashuri . Hermite-Hadamard type inclusions via generalized Atangana-Baleanu fractional operator with application. AIMS Mathematics, 2022, 7(7): 12303-12321. doi: 10.3934/math.2022683 |
[6] | Thabet Abdeljawad, Muhammad Aamir Ali, Pshtiwan Othman Mohammed, Artion Kashuri . On inequalities of Hermite-Hadamard-Mercer type involving Riemann-Liouville fractional integrals. AIMS Mathematics, 2021, 6(1): 712-725. doi: 10.3934/math.2021043 |
[7] | Yamin Sayyari, Mana Donganont, Mehdi Dehghanian, Morteza Afshar Jahanshahi . Strongly convex functions and extensions of related inequalities with applications to entropy. AIMS Mathematics, 2024, 9(5): 10997-11006. doi: 10.3934/math.2024538 |
[8] | Muhammad Zakria Javed, Muhammad Uzair Awan, Loredana Ciurdariu, Omar Mutab Alsalami . Pseudo-ordering and δ1-level mappings: A study in fuzzy interval convex analysis. AIMS Mathematics, 2025, 10(3): 7154-7190. doi: 10.3934/math.2025327 |
[9] | Miguel Vivas-Cortez, Muhammad Aamir Ali, Artion Kashuri, Hüseyin Budak . Generalizations of fractional Hermite-Hadamard-Mercer like inequalities for convex functions. AIMS Mathematics, 2021, 6(9): 9397-9421. doi: 10.3934/math.2021546 |
[10] | Thongchai Botmart, Soubhagya Kumar Sahoo, Bibhakar Kodamasingh, Muhammad Amer Latif, Fahd Jarad, Artion Kashuri . Certain midpoint-type Fejér and Hermite-Hadamard inclusions involving fractional integrals with an exponential function in kernel. AIMS Mathematics, 2023, 8(3): 5616-5638. doi: 10.3934/math.2023283 |
The environmental impact of mining and smelting in the world-class Monte Amiata mercury (Hg) ore field has long been studied, before and after the final closure in 1982. A first summary was presented in 2015. With this contribution, we review the studies conducted in the last eight years. The most significant results include ⅰ) Hg-isotope characterization of primary ore (cinnabar), smelting waste (calcines), soil, fish and stream sediments; ⅱ) analysis of the interplay between geomorphological evolution, fluvial dynamics and Hg distribution in the Paglia River catchment, which drains the main mining areas; ⅲ) an improved quantification of the Hg loads discharged to the Mediterranean Sea; ⅳ) the use of biomonitors to reveal the dispersion of Hg; ⅴ) new detailed surveys, including innovative techniques, of Hg distribution in air; ⅵ) specific investigations to support the ongoing reclamation at Abbadia San Salvatore, the main mining and smelting center of the district, and ⅶ) the assessment of the variability of Hg distribution in air, water and soil from the reclaimed Siele mine. Despite these progresses, there are further steps to be conducted to achieve optimal management of the wide contamination evidenced in this district. It is now fully clear that the diffuse character of contamination results in unfeasible hypotheses for total remediation. Therefore, the goal is that of a sustainable coexistence between contamination and human activities. This goal may involve the following activities: a) implementation of GIS-based contamination maps as a direct operational instrument for local authorities to tune up specific limitations and regulations of human activities (e.g., fishing, instream quarrying and wildfire management); b) mitigation measures such as increasing the vegetal cover of river banks to limit erosion and runoff, and c) continuous monitoring of air, water and soil contamination, including transfer to the food chain.
L: Length; E: Young's modulus; I: a moment of inertia of cross section; A: cross section area; x: longitudinal axis; ρ: density; s: Displacement; K1, K2: linear stiffness of the springs at right and left ends, respectively; S(x): normal function; ω: eigenfequencey; c: wave speed; η: eigenvalues; Ci(i=1,2,3,4): cnstant coefficient; Q(x): weighted functions; Ni(i=1,2,3,4): shape functions; sj: function of space and time component; ¯sj: amplitude of vibration varying with time; kϵ: stiffness matrix; mϵ: mass matrix; N: number of element
The beam, a fundamental structural element, is typically characterized by having one dimension significantly larger than its other dimensions. This elongated geometry allows beams to efficiently carry loads and distribute them along their length. Euler-Bernoulli beam (EBB) theory stands as one of the foundational frameworks used to describe the behavior of beams under certain conditions [1]. The development of beam equations has a rich historical context, with contributions from notable figures such as Vinci and Galilei. During the eighteenth century, significant advancements in beam theory were made by eminent mathematicians including Euler, Jacob, and Daniel, culminating in the establishment of comprehensive analytical tools for understanding beam behavior. The application of beam theory extends across a diverse range of engineering disciplines, reflecting its essential role in various practical applications. In transportation engineering, beams are integral components of bridges, roadways, and railway tracks, where they provide structural support and facilitate the safe passage of vehicles and pedestrians. Structural engineering heavily relies on beam theory to design and analyze buildings, bridges, and other infrastructure projects, ensuring their stability and resilience against external forces such as wind and seismic loads. In aerospace engineering, beams play a crucial role in the design and construction of aircraft, spacecraft, and aerospace structures, where they must withstand complex loading conditions and extreme environments. Scholarly research in the field of continuous structural beam systems has yielded valuable insights and methodologies that contribute to advancements in engineering practice. Works by [2,3] exemplify the breadth of studies focused on beam theory, covering topics ranging from structural analysis and design optimization to materials research and performance evaluation. These studies underscore the interdisciplinary nature of beam theory and its significance in addressing real-world engineering challenges across multiple sectors.
Numerous researchers have delved into the intricate dynamics of transverse vibrations exhibited by beam-spring systems, conducting both exact and approximate analyses to ascertain the natural frequencies governing their behavior. These investigations have explored the nuanced interplay between beam vibrations and various factors, including the characteristics of the elastic foundation supporting the beam. The effects of springs, rotary inertia, and mass distribution have been subjects of intensive scrutiny across a spectrum of studies, underscoring the multidimensional nature of beam-spring dynamics. The significance of springs in modulating beam vibrations has been a focal point of investigation, with studies such as [4,5] shedding light on their role in altering the structural response. Additionally, the influence of rotary inertia, mass distribution, and other dynamic parameters has been rigorously examined in works [6], among others. These investigations have contributed valuable insights into the intricate dynamics of beam-spring systems and their implications for diverse engineering applications. ¨Oz [7] and ¨Ozkaya [8] determined beam frequencies, incorporating mass and using both analytic and finite element methods. Grossi and Arenas [9] employed Rayleigh-Ritz and optimized Rayleigh-Schmidt methods to investigate frequency variations with changes in height and width. Smith et al. [10] introduced the fully Sinc-Galerkin method in space and time to solve beams with cantilever and fixed boundary conditions. Moaaz et al. [11] formulated mathematical expressions for transverse resonance in simply supported, axially compressed thermoelastic nanobeams, employing nonlocal elasticity theory and the dual-phase-lag heat transfer model to explore the impact of length scale and axial velocity on system responses. Baccouch [12] applied the Galerkin method to solve the Euler-Bernoulli beam equation, while Xie and Zhang [13] investigated difference methods for nonlinear equations with damping. Additionally, Shi et al. [14] explored the mixed finite element method for solving such equations.
The variational iteration technique was used by Liu and Gurran [15] to find the natural frequencies and mode shapes of the beam under different boundary conditions. Galerkin finite element method (FEM), Rayleigh-Ritz, and exact solutions were compared by Hamdan and Latif [16], and the exhibited FEM was preferable because of good accuracy. Jafari et al. [17] derived the equation of motion of beam by applying Hamilton's principle and obtained the eigenfrequencies and mode shapes for cantilever beam connected with linear spring at the tip by using the FEM.
Unlike boundary element method, finite difference method, and finite volume method, which are widely used in acoustic and fluid mechanics (see for example, [18,19]), the study of FEM is considered as the standard approach in presenting solutions to structural problems, see for instance, [20,21]. Many industries use FEM software such as ABAQUS (based on Abundant Beads Addition Calculation Utility System tool), NASA structure analysis, and analysis system for the commercial purpose. It has been widely discussed on static problems where numerous codes existed while having less validation and verification for standard problems with respect to dynamics of determining the eigenfrequencies. In the study of beam dynamics using FEM, consistent mass (CM) and lumped mass (LM) matrices are critical in accurately representing the system's behavior. The choice between these two matrices has an impact on the accuracy and computing efficiency of the analysis. The consistent mass matrix accurately preserves the system's mass distribution by taking into account the mass contributions of all finite constituents. This matrix is constructed directly from the discretized governing equations, yielding more accurate results, particularly for bigger models with variable element sizes. However, its bigger size necessitates more computing effort and storage. The lumped mass matrix, on the other hand, combines the mass contributions into nodal points, making the computing process easier. While this matrix decreases computational effort and storage needs, it may produce less accurate results, especially in systems with large mass variations or irregular geometries. Hence, the primary aim of this study is to present a comprehensive analysis of the vibration behavior of beam-spring systems using FEM with a focus on the comparative performance of CM and LM matrices. Our work bridges the gap between mathematical analysis and engineering applications by addressing two primary objectives:
(1) Determining the preferred matrix type (CM or LM) for such analyses from a mathematical perspective;
(2) Examining the deflection behavior while adjusting the stiffness of the supports at each end of the beam from an engineering perspective.
The novelty of our study lies in its detailed comparison of CM and LM matrices and providing insights into their respective accuracies in calculating eigenfrequencies and mode shapes, which has not been extensively covered in existing literature. By varying the stiffness of the beam supports, we analyze the dynamic behavior of the system, offering practical insights valuable for both theoretical and applied contexts. Additionally, we provide a numerical results section to include a deeper analysis of the outcomes prior to yielding a detailed introduction to the FEM procedure, including the assembly of global stiffness and mass matrices and the incorporation of boundary conditions. Therefore, the underlying study is crucial for both mathematical analysis and practical engineering applications, making our study a valuable contribution to the field of applied mathematics.
This article is categorized as follows: the governing problem is formulated in Section 2. The analytical and numerical results are presented in Section 3. Results and discussions are given in Section 4 and the validation has been performed in Section 5 while the study is summarized in Section 6.
Consider the beam configuration attached to linear springs at both ends having length, as can be viewed through Figure 1. The material of the beam is made of stainless steel. The Young's modulus is 210 GPa and material density is 7850 Kg/m3. The length, width, and thickness of the beam are taken as 1 m, 0.02 m, and 0.003 m, respectively.
The equation of motion for the transverse deflection function in case of free beam's vibration is given by [22]
EI∂4s(x,t)∂x4+ρA∂2s(x,t)∂t2=0. | (2.1) |
Equation (2.1) together with the standard linear spring conditions of beam defined in [23] will be considered for the correct determination of eigenfrequencies and mode shapes. The objective is to provide a more optimal and accurate solution approach by considering the lumped and consistent mass matrices while providing the finite element solution in proceeding sections. The flexural boundary conditions at x=0 and x=L, representing the stiffness of the springs in the positive direction from left to right, are provided below:
EI∂2s(0,t)∂x2=0, | (2.2a) |
EI∂3s(0,t)∂x3=−K1s(0,t), | (2.2b) |
EI∂2s(L,t)∂x2=0, | (2.2c) |
EI∂3s(L,t)∂x3=K2s(L,t). | (2.2d) |
Equation (2.1) along with boundary conditions (2.2a–d) is solved by separation of variables to acquire the characteristics and mode shape equations where the roots of the characteristic equation are extracted through Mathematica-based code. These roots are termed as eigenfrequencies and will be useful in determining the eigenmodes in the subsequent section.
As we seek to determine the natural frequency and mode shape of the vibrating beam as given by previously defined boundary conditions, we use an analytical and numerical approach to obtain the desired results. It is appropriate to note that a numerical approach is used to consider CM and LM matrices, which provides a justification for solving more complex problems with a similar scheme.
We apply separation of variables to the governing problem given in Section 2 by letting
s(x,t)=S(x)T(t). | (3.1) |
Therefore, Eq (2.1) can be written as [24]
c21S(x)∂4S(x)∂x4=−1T(t)∂2T(t)∂t2=ω2, | (3.2) |
where
c=√EIρA, |
and Eq (3.2) is further split as
d4S(x)dx4−η4S(x)=0 | (3.3) |
and
d2T(t)dt2+ω2T(t)=0, | (3.4) |
where η is given by
η=√ωc. | (3.5) |
Equation (3.3) yields the following equation
S(x)=C1sin(ηx)+C2cos(ηx)+C3sinh(ηx)+C4cosh(ηx). | (3.6) |
Using Eq (3.6) in Eq (2.2a–d), we obtain
−EIC2η2+EIC4η2=0, | (3.7) |
−EIη3C1+C2K1+EIη3C3+C4K1=0, | (3.8) |
−C1η2EIsin(ηL)−C2η2EIcos(ηL)+C3η2EIsinh(ηL)+C4η2EIcosh(ηL)=0 | (3.9) |
and
C1[−EIη3cos(ηL)−K2sin(ηL)]+C2[EIη3sin(ηL)−K2cos(ηL)] +C3[EIcosh(ηL)−K2sinh(ηL)]+C4[EIη3sinh(ηL)−K2cosh(ηL)]=0. | (3.10) |
By using Eq (3.7) in Eq (3.6), we obtain
S(x)=C1[C2C1(cosh(ηx)+cos(ηx))+sin(ηx)+C3C1sinh(ηx)]. | (3.11) |
The results obtained by using boundary conditions (2.2a–d) are given by Eqs (3.7)–(3.10) representing a system of four equations with four unknowns C1–C4. In order to have a nontrivial solution, the determinant of the coefficient matrix must be zero, which leads to a frequency equation given as
−2η2EI[−η3EIcosh(η)(EIη3cos(ηL)+sin(ηL)(K1+K2)) +(EIη3(K1+K2)cos(ηL)+2sin(ηL)K1K2)sinh(ηL)+E2I2η6]=0. | (3.12) |
After finding the values of C3C1 and C2C1 from Eqs (3.8) and (3.10), respectively, and putting into Eq (3.11), the nth mode shape equation is determined. This equation is used to plot the mode shapes/eigenmodes subject to corresponding eigenfrequencies. The eigenfrequencies are computed by using Eq (3.5), after determining the eigenvalues (η) from Eq (3.12).
The analytic solution for the beam attached to linear springs is achieved more conveniently. However, in case of more complex and challenging problems with added effects and flexural boundary conditions, and structural and material discontinuities [25], it becomes difficult to obtain analytical solutions. Therefore, we propose the finite element scheme with the consideration of LM and CM matrices to obtain numerical solutions for such problems in subsequent section. Albeit the scheme to be adopted herein will provide a reference model for the comparative analysis. In case of substantial problems related to beams, FEM provides a fast and easy method to address these problems.
This section aims to provide the workings of FEM by CM and LM matrices to calculate the eigenmodes and eigenfrequencies.
The first step in FEM is to discretize the beam into a finite number of elements. There are two end nodes, each with two degrees of freedom, for each beam element. As demonstrated in Figure 2, these degrees of freedom include both translational displacements (Vi, where i = 1, 2) and rotational displacements (θj, where j = 1, 2).
The node's movement across the axis of the beam is indicated by the translational degrees of freedom, and its rotation about the corresponding axes is indicated by the rotational degrees of freedom. As the beam under examination is uniform, it is assumed that all elements, utilized to mesh the total beam, are indistinguishable. The subsequent step is to acquire the weak form of the differential equation. For this purpose, the weight functions are multiplied with the residual value of an approximate solution and are then integrated over the domain yielding zero value. While using the process of discretization and weak formation in Eq (2.1), it is found that
∫L0Q(x)(EId4sdx4+ρAd2sdt2)dx=Q(x)EId3sdx3|L0−EId2sdx2dQdx|L0+∫L0EId2sdx2d2Qdx2dx+∫L0Q(x)(ρAd2sdt2)dx=0. | (3.13) |
It is noted that the highest order of derivative in Eq (3.13) is three; therefore, an approximate function of thrice differentiable is selected. A cubic interpolation polynomial fulfills this requirement [26] normally. Applying the Galerkin FEM, a weight function is equated with the approximate function
Qi=Ni, |
where these cubic interpolation functions are called cubic spline functions, given as
N1=1−3(xL)2+2(xL)3,N2=x(xL−1)2,N3=(xL)2(3−2xL),N4=x2L(xL−1). | (3.14) |
While putting these shape functions, given by Figure 3, into Eq (3.13) and assuming
s=4∑j=1sjNj, |
we get
∫L0Q(x)(EId4sdx4+ρAd2sdt2)dx=EIsjNiNj,xxx]L0−EIsjNj,xxNi,x]L0+∫L0EINi,xxNj,xxsjdx+ρA∫L0sj,ttNiNjdx=0. | (3.15) |
Equation (3.15) can be written as
[kϵ]sj+[mϵ]sj,tt=0, | (3.16) |
where sj can be written as
sj={¯sj}eiωt. | (3.17) |
Putting Eq (3.17) in Eq (3.16), we obtain
[kϵ]−ω2[mϵ]=0, | (3.18) |
where [kϵ] and [mϵ] are given as
[kϵ]=EIL3[126L−126L6L4L2−6L2L2−12−6L12−6L6L2L2−6L4L2], | (3.19) |
[mϵ]=ρAL420[15622L54−13L22L4L2L3L−3L25413L156−22L−13L−3L2−22L4L2], | (3.20) |
and the LM matrix [21] would be
ρAL2[1000000000100000]. | (3.21) |
Here, we clarify the computational procedures using MATLAB codes based on FEM with LM and CM matrices to calculate the eigenfrequencies and mode shapes of the beam subject to linear springs. Below is a detailed description of our approach:
(I) Development of global matrices
(1) The MATLAB code generates the global stiffness, and LM and CM matrices for the highest number of elements.
(2) Boundary conditions are incorporated after forming the global stiffness and mass matrices.
(II) Incorporating boundary conditions
(1) The stiffness of the linear spring attached to the left end is added to the first entry of the first row of the global stiffness matrix.
(2) Similarly, the stiffness of the spring at the right end is added to the second to last entry of the final row of the global stiffness matrix.
(III) Calculation of eigenvalues and eigenfrequencies
(1) Eigenvalues are calculated from the global stiffness and mass matrices according to Eq (3.18).
(2) Eigenfrequencies are then obtained by taking the square root of these eigenvalues.
This procedure follows the methods outlined in several studies, such as references [27,28,29,30,31].
This section aims to discuss the eigenmodes/mode shapes of the structural dynamics of the beam, which actually describes the deformation that the beam component would exhibit if it vibrates at the eigenfrequency. The deformation usually takes place through an excitation, which leads to the overall vibration of a component of the beam that includes the individual shapes of vibration. Therefore, eigenfrequencies and mode shapes indicate how the beam structure behaves under certain boundary conditions. It is noteworthy that the eigenmode characteristic is suitable for the qualitative evaluation of the dynamics of the beam component. The tabular and graphical analysis are presented to discuss beam dynamics at length.
Table 1 lists the comparison of eigenfrequencies determined by analytic method (AM), FEM by CM and LM matrices, receptively, with
K1,K2=10000 N/m. |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.90724849 | 6.90796199 | 6.91434953 | 0.01032973 | 0.10280563 |
2nd | 26.09674381 | 26.13470717 | 26.42771700 | 0.14547164 | 1.26825473 |
3rd | 52.84510702 | 53.16067633 | 54.27922231 | 0.59715900 | 2.71380904 |
4th | 81.45836541 | 82.55087709 | 74.63946703 | 1.34119028 | 8.37102285 |
N=10 | |||||
1st | 6.90724849 | 6.90729342 | 6.90918512 | 0.00065048 | 0.02803765 |
2nd | 26.09674381 | 26.09915748 | 26.18963094 | 0.00924893 | 0.35593375 |
3rd | 52.84510702 | 52.86511702 | 53.29345172 | 0.03786538 | 0.84841289 |
4th | 81.45836541 | 81.53039633 | 80.56105229 | 0.08842667 | 1.10156043 |
N=50 | |||||
1st | 6.90724849 | 6.90724856 | 6.90732785 | 0.000000101 | 0.00114894 |
2nd | 26.09674382 | 26.09674771 | 26.10054215 | 0.00001487 | 0.01455480 |
3rd | 52.84510702 | 52.84513933 | 52.86350476 | 0.00006114 | 0.03481446 |
4th | 81.45836541 | 81.45848351 | 81.43321124 | 0.00014498 | 0.03087979 |
N=100 | |||||
1st | 6.90724849 | 6.90724851 | 6.90726831 | 0.00000029 | 0.00028694 |
2nd | 26.09674382 | 26.09674412 | 26.09769399 | 0.00000115 | 0.00028694 |
3rd | 52.84510702 | 52.84510912 | 52.84970909 | 0.00000397 | 0.00870860 |
4th | 81.45836541 | 81.45837285 | 81.45215478 | 0.00000913 | 0.00762930 |
The accuracy of eigenfrequencies are increased by increasing the number of elements of the beam. The percentage errors (with N = 5) for the CM matrix are 0.01032973, 0.14547164, 0.59715900, and 1.34119028, respectively.
While 0.10280563, 1.26825474, 2.71380904, and 8.37102285 are percentage errors for the LM matrix, this indicates that the CM matrix gives better accuracy for nonclassical boundary conditions as compared to the LM matrix even for the lower number of elements. Table 1 clearly demonstrates that CM gives excellent agreement at
N=50, |
but does not get the same accuracy for LM even by using
N=100. |
It is noteworthy that
N=10 |
yields excellent accuracy; however,
N=50 |
and
N=100 |
are intended merely to demonstrate that increasing the number of elements improves accuracy.
Table 2 is a comparison of natural frequencies calculated by analytical and numerical methods, respectively, by decreasing the spring stiffness of the right end. The table shows that natural frequencies and stiffness of the right end spring are in a direct relationship, where natural frequencies decrease with decreasing spring stiffness. In addition, the numerical results are in close agreement with the analytical results when comparing the numerical solution for the CM matrices instead of the LM matrices. Rather, FEM by the consideration of CM matrices gives excellent accuracy not only for lower modes but also for higher modes.
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.35701924 | 6.35757819 | 6.38367463 | 0.00879264 | 0.41930642 |
2nd | 18.88435515 | 18.89870611 | 18.60125288 | 0.07599391 | 1.49913654 |
3rd | 37.23312923 | 37.33388399 | 34.14209661 | 0.27060513 | 8.30183410 |
4th | 66.98883703 | 67.54369195 | 61.04497484 | 0.82827967 | 8.87291440 |
N=10 | |||||
1st | 6.35701924 | 6.35705430 | 6.36418013 | 0.00055151 | 0.11264540 |
2nd | 18.88435515 | 18.88526930 | 18.82742317 | 0.00484077 | 0.30147696 |
3rd | 37.23312923 | 37.23999014 | 36.48814214 | 0.01842689 | 2.00087155 |
4th | 66.98883703 | 66.92997846 | 65.34527890 | 0.08786325 | 2.45348061 |
N=50 | |||||
1st | 6.35701924 | 6.35701929 | 6.35730648 | 0.00000078 | 0.00451846 |
2nd | 18.88435515 | 18.88435660 | 37.20428112 | 0.00000767 | 0.01115087 |
3rd | 37.23312923 | 37.23314046 | 37.20428112 | 0.00003016 | 0.07747968 |
4th | 66.98883703 | 66.98890259 | 66.92288123 | 0.00009786 | 0.09845789 |
N=100 | |||||
1st | 6.35701924 | 6.35701923 | 6.35709101 | 0.00000015 | 0.00112898 |
2nd | 18.88435515 | 18.88435528 | 18.88383000 | 0.00000068 | 0.00278087 |
3rd | 37.23312923 | 37.23312992 | 37.22592579 | 0.00000185 | 0.01934685 |
4th | 66.98883703 | 66.98884110 | 66.97235365 | 0.00000607 | 0.02460615 |
Table 3 indicates the comparison of eigenfrequencies by increasing the stiffness of the left end. From tables, it is observed easily by increasing the value of K1 that eigenfrequencies are also increased. A study has demonstrated that the CM matrices can give accurate eigenfrequencies for higher modes as well as lower ones, but LM cannot give the best accuracy for lower modes as well as for higher modes.
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.96985529 | 6.97058784 | 6.97318699 | 0.01051026 | 0.04780157 |
2nd | 27.03932973 | 27.08117845 | 27.20251475 | 0.15476981 | 0.60350986 |
3rd | 57.08313134 | 57.47001406 | 57.52811675 | 0.67775315 | 0.77953924 |
4th | 92.56612927 | 94.07004264 | 80.41180184 | 1.62469078 | 13.13042635 |
N=10 | |||||
1st | 6.96985529 | 6.96990142 | 6.97085023 | 0.00066185 | 0.01427757 |
2nd | 27.03932973 | 27.04200859 | 27.09268028 | 0.00990727 | 0.19730722 |
3rd | 57.08313134 | 57.10818680 | 57.34259598 | 0.04389293 | 0.45453827 |
4th | 92.56612927 | 92.67041635 | 90.82713601 | 0.11238909 | 1.87864964 |
N=50 | |||||
1st | 6.96985529 | 6.96985536 | 6.96989697 | 0.00000100 | 0.00059800 |
2nd | 27.03932973 | 27.03933403 | 27.04157469 | 0.00001590 | 0.00830257 |
3rd | 57.08313134 | 57.08317194 | 57.09446492 | 0.00007112 | 0.01985452 |
4th | 92.56612927 | 92.56630243 | 92.51496052 | 0.00018707 | 0.05527805 |
N=100 | |||||
1st | 6.96985529 | 6.96985538 | 6.96986568 | 0.00000129 | 0.00014907 |
2nd | 27.03932973 | 27.03932996 | 27.03989174 | 0.00000085 | 0.00207849 |
3rd | 57.08313134 | 57.08313385 | 57.08597067 | 0.00000440 | 0.00497403 |
4th | 92.56612927 | 92.56614015 | 92.55346771 | 0.00001175 | 0.01367839 |
Table 4 mentions the comparison of numerical and analytical results by increasing the spring stiffness of both ends and shows a similar behavior for natural frequencies and solution accuracy as in case of Tables 1–3.
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 7.00984547 | 7.01058818 | 7.01069925 | 0.01059524 | 0.01217972 |
2nd | 27.72533453 | 27.77009228 | 27.75837598 | 0.01614326 | 0.11917421 |
3rd | 61.16521834 | 61.63086692 | 61.09088070 | 0.76129635 | 0.12153580 |
4th | 105.4525306 | 107.82633768 | 101.05828707 | 2.25106688 | 4.16703475 |
N=10 | |||||
1st | 7.00984547 | 7.00989023 | 7.01218744 | 0.00063853 | 0.03340972 |
2nd | 27.72533453 | 27.72813738 | 27.74771968 | 0.01010934 | 0.08273897 |
3rd | 61.16521834 | 61.19584117 | 61.39079599 | 0.05006575 | 0.08073897 |
4th | 105.4525306 | 105.60832597 | 106.45143402 | 0.14773974 | 0.94725408 |
N=50 | |||||
1st | 7.00984547 | 7.00984337 | 7.00986020 | 0.00002995 | 0.00021013 |
2nd | 27.72533453 | 27.72529534 | 27.72631753 | 0.00014135 | 0.00354549 |
3rd | 61.16521834 | 61.16521665 | 61.17571474 | 0.00002763 | 0.01716073 |
4th | 105.4525306 | 105.45258028 | 105.49998929 | 0.00004703 | 0.04500470 |
N=100 | |||||
1st | 7.00984547 | 7.00984334 | 7.00984750 | 0.00003038 | 0.00002895 |
2nd | 27.72533453 | 27.72529099 | 27.72554833 | 0.00015704 | 0.00077113 |
3rd | 61.16521834 | 61.16516979 | 61.16781319 | 0.00007937 | 0.00424236 |
4th | 105.4525306 | 105.45234022 | 105.46427897 | 0.00018055 | 0.03111408 |
Figures 4–7 represent the first four natural modes for varying the spring stiffness of the underlying beam configuration. It is evident that the number of node points increases with each successive mode. The occurrence of node points indicates negligible deflection at certain locations of the beam. For higher natural modes, deflection becomes zero at multiple locations on the beam. Furthermore, the mode shapes clearly provide alternative symmetric and antisymmetric modes in case of even and odd modes, respectively. It is worth noting that the greatest amount of deflection occurs at the end of the beam because the spring beam system generally shows an initial deflection to obtain the equilibrium position. However, the spring no longer deflects after having static equilibrium.
The intent of this section is to demonstrate the validity of the results mentioned above. The underlying results for a few specific cases that have already been documented in the literature are rendered for this purpose. The simply supported EBB eigenfrequencies have been determined to be precisely comparable to those reported by Leissa [23] when
K1=K2=1012 |
has been taken into account, as shown in Table 5. Furthermore, letting the stiffness parameters be
K1=K2=0 |
Modes | [23] | FEM by CM | FEM by LM |
K1=K2=1012 | |||
1st | 9.8696 | 9.8696 | 9.8695 |
2nd | 39.478 | 39.4782 | 39.4737 |
3rd | 88.876 | 88.8769 | 88.7669 |
4th | 57.914 | 157.7529 | 157.5231 |
K1=K2=0 | |||
1st | 0.0000 | 0, 0000 | 0.0000 |
2nd | 0.000 | 0.0002 | 0.0041 |
3rd | 22.273 | 22.3740 | 21.7055 |
4th | 61.373 | 61.6881 | 58.6391 |
verifies the findings of the free free EBB [23].
In this article, the modal analysis of the Euler-Bernoulli beam subject to attached linear springs has been made. Eigenfrequencies and mode shapes were evaluated by comparing the analytic method and FEM using CM and LM matrices by varying the stiffness of the springs. It has been noted that more numbers of beam elements resulted in better accuracy of eigenfrequencies whereas consideration of the CM matrix showed excellent accuracy as compared to the LM matrix for N = 5 or N = 100. This has justified the preference of considering the CM matrix over the LM matrix even for a small number of beam elements for the greater advantage and better accuracy of the solution. Also, it has been observed that a large amount of deflection occurred at the end points of the beam which justified the dynamics of the spring beam system.
While dealing with more complex and practical problems of beam dynamics, obtaining analytical solutions often becomes challenging and sometimes impossible. It has been noticed that the use of FEM with the consideration of the LM matrix is rather convenient in addressing more challenging and practical problems related to beam dynamics. The underlying study concluded with the aim to provide an effective way to treat such problems numerically in a more efficient way. Furthermore, it is important to note that the suggested method can be easily extended to specific two-dimensional structures such as plates and shells with common boundary conditions, albeit with numerical concerns. However, it is critical to recognize that adding plates and shell-like structures may create complexities that are beyond the capability of typical numerical methods. In such circumstances, mode-matching algorithms have emerged as viable options for addressing complex structures; see, for reference, [32,33]. While mode-matching methods may neglect some effects, such as break-out, they provide useful insights into vibrating processes and serve as benchmark answers for fully numerical systems. Traditionally, numerical and analytical methods are used to describe finite-length plate or shell-like structures. Numerical methods, such as the finite element method or the boundary element method, allow for the analysis of structures of various shapes and sizes. However, as the excitation frequency and structure dimensions increase, so does the number of degrees of freedom, making these approaches unsuitable even for relatively small structures. As a result, in situations where typical numerical approaches are limited, mode-matching solutions provide a desirable and precisely computed option for handling the complexity inherent in modeling finite-length plate or shell-like structures.
M. Alkinidri: conceptualization, methodology, writing (review and editing), investigation, analysis, visualization, validation, resources; R. Nawaz: conceptualization, methodology, writing (original draft), investigation, analysis, visualization, validation, supervision; H. Alahmadi: methodology, writing (review and editing), investigation, analysis, visualization, validation, resources.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
The authors express their gratitude to Dr. Gulnaz Kanwal for her valuable suggestions, particularly regarding the computational aspects of the study, which significantly improved the quality of the article.
The authors declare no conflicts of interest.
[1] |
Beckers F, Rinklebe J (2017) Cycling of mercury in the environment: Sources, fate, and human health implications: A review. Crit Rev Environ Sci Tech 47: 693–794. https://doi.org/10.1080/10643389.2017.1326277 doi: 10.1080/10643389.2017.1326277
![]() |
[2] |
Bjørklund G, Dadar M, Mutter J, et al. (2017) The toxicology of mercury: Current research and emerging trends. Environ Res 159: 545–554. https://doi.org/10.1016/j.envres.2017.08.051 doi: 10.1016/j.envres.2017.08.051
![]() |
[3] |
Natasha SM, Khalid S, Bibi I, et al. (2020) A critical review of mercury speciation, bioavailability, toxicity and detoxification in soil-plant environment: ecotoxicology and health risk assessment. Sci Total Environ 711: 134749. https://doi.org/10.1016/j.scitotenv.2019.134749 doi: 10.1016/j.scitotenv.2019.134749
![]() |
[4] |
Kocman D, Wilson SJ, Amos HM, et al. (2017) Toward an assessment of the global inventory of present-day mercury releases to freshwater environments. Int J Environ Res Public Health 14: 138. https://doi.org/10.3390/ijerph14020138 doi: 10.3390/ijerph14020138
![]() |
[5] |
Kim KH, Kabir E, Jahan SA (2016) A review on the distribution of Hg in the environment and its human health impacts. J Hazard Mater 306: 376–385. https://doi.org/10.1016/j.jhazmat.2015.11.031 doi: 10.1016/j.jhazmat.2015.11.031
![]() |
[6] |
Pirrone N, Cinnirella S, Feng X, et al. (2010) Global mercury emissions to the atmosphere from anthropogenic and natural sources. Atmos Chem Phys 10: 5951–5964. https://doi.org/10.5194/acp-10-5951-2010 doi: 10.5194/acp-10-5951-2010
![]() |
[7] |
Ciani F, Rimondi V, Costagliola P (2021) Atmospheric mercury pollution: The current methodological framework outlined by environmental legislation. Air Qual Atmos Health 14: 1633–1645. https://doi.org/10.1007/s11869-021-01044-4 doi: 10.1007/s11869-021-01044-4
![]() |
[8] |
Driscoll CT, Mason RP, Chan HM, et al. (2013) Mercury as a global pollutant: sources, pathways, and effects. Environ Sci Technol 47: 4967–4983. https://doi.org/10.1021/es305071v doi: 10.1021/es305071v
![]() |
[9] |
Li WC, Tse HF (2015) Health risk and significance of mercury in the environment. Environ Sci Pollut Res 22: 192–201. https://doi.org/10.1007/s11356-014-3544-x doi: 10.1007/s11356-014-3544-x
![]() |
[10] |
Gibb H, O'Leary KG (2014) Mercury exposure and health impacts among individuals in the artisanal and small-scale gold mining community: a comprehensive review. Environ Health Perspect 122: 667–672. https://doi.org/10.1289/ehp.1307864 doi: 10.1289/ehp.1307864
![]() |
[11] | US EPA. Mercury study report to Congress. U.S. Environmental Protection Agency. 1997. Available from: https://www.epa.gov/mercury/mercury-study-report-congress. |
[12] | UNEP. Review of Minamata Convention initial assessment reports: key findings for health. Geneva: World Health Organization. 2021. Available from: https://apps.who.int/iris/handle/10665/351133. |
[13] |
Kocman D, Horvat M, Pirrone N, et al. (2013) Contribution of contaminated sites to the global mercury budget. Environ Res 125: 160–170. https://doi.org/10.1016/j.envres.2012.12.011 doi: 10.1016/j.envres.2012.12.011
![]() |
[14] |
Rytuba JJ (2003) Mercury from mineral deposits and potential environmental impact. Environ Geol 43: 326–338. https://doi.org/10.1007/s00254-002-0629-5 doi: 10.1007/s00254-002-0629-5
![]() |
[15] |
Hylander LD, Meili M (2003) 500 years of mercury production: global annual inventory by region until 2000 and associated emissions. Sci Total Environ 304: 13–27. https://doi.org/10.1016/S0048-9697(02)00553-3 doi: 10.1016/S0048-9697(02)00553-3
![]() |
[16] | Strappa O (1977) Storia delle miniere di mercurio del Monte Amiata—I Parte. L'industria mineraria (in Italian). |
[17] |
Bombace MA, Rossi LC, Clemente GF, et al. (1973) Ecological study of the mercury-bearing area of Monte Amiata. Comitato Nazionale per l'Energia Nucleare, Casaccia 29: 191–237. https://doi.org/10.2172/4948308 doi: 10.2172/4948308
![]() |
[18] | Benvenuti M, Costagliola P (2016) Il distretto mercurifero del comprensorio amiatino: nuovi dati sull'impatto ambientale nel sistema fuviale Paglia-Tevere. Geol Ambient 24: 2–5 (in Italian). |
[19] | Dall'Aglio M (1966) Distribuzione del mercurio nelle acque superfciali. Atti Soc Tosc Sci Nat 36: 577–595. |
[20] | Dall'Aglio M, Da Roit R, Orlandi C, et al. (1967) Prospezione geochimica del mercurio. Distribuzione Del Mercurio Nelle Alluvioni Della Toscana. Ind Miner 17: 391–398. |
[21] |
Rimondi V, Chiarantini L, Lattanzi P, et al. (2015) Metallogeny, exploitation and environmental impact of the Mt. Amiata mercury ore district (Southern Tuscany, Italy). Ital J Geosci 134: 323–336. https://doi.org/10.3301/IJG.2015.02 doi: 10.3301/IJG.2015.02
![]() |
[22] |
Marroni M, Moratti G, Costantini A, et al. (2015) Geology of the Monte Amiata region, Southern Tuscany, Central Italy. Ital J Geosci 134: 171–199. https://doi.org/10.3301/IJG.2015.13 doi: 10.3301/IJG.2015.13
![]() |
[23] |
Laurenzi MA, Braschi E, Casalini M, et al. (2015) New 40Ar-39Ar dating and revision of the geochronology of the Monte Amiata Volcano, Central Italy. Ital J Geosci 134: 255–265. https://doi.org/10.3301/IJG.2015.11 doi: 10.3301/IJG.2015.11
![]() |
[24] | Tanelli G, Lattanzi P (1983) Pyritic ores of southern Tuscany. Ita Geol Soc S Afr Spec Publ 7: 315–323. |
[25] | Lattanzi P, Benvenuti M, Costagliola P, et al. (1994) An overview on recent research on the metallogeny of Tuscany, with special reference to the Apuane Alps. Mem Soc Geol Ital 48: 613–625. |
[26] |
Pribil MJ, Rimondi V, Costagliola P, et al. (2020) Assessing mercury distribution using isotopic fractionation of mercury processes and sources adjacent and downstream of a legacy mine district in Tuscany, Italy. Appl Geochem 117: 104600. https://doi.org/10.1016/j.apgeochem.2020.104600 doi: 10.1016/j.apgeochem.2020.104600
![]() |
[27] |
Deng CZ, Sun GY, Rong YM, et al. (2021) Recycling of mercury from the atmosphere-ocean system into volcanic-arc—associated epithermal gold systems. Geology 49: 309–313. https://doi.org/10.1130/G48132.1 doi: 10.1130/G48132.1
![]() |
[28] |
Bellander T, Merler E, Ceccarelli F, et al. (1998) Historical exposure to inorganic mercury at the smelter works of Abbadia San Salvatore, Italy. Ann Occup Hyg 42: 81–90. https://doi.org/10.1016/S0003-4878(97)00052-5 doi: 10.1016/S0003-4878(97)00052-5
![]() |
[29] |
Ciccacci S, Galiano M, Roma MA, et al. (2009) Morphodynamics and morphological changes of the last 50 years in a badland sample area of Southern Tuscany (Italy). Z Geomorphol 53: 273–297. https://doi.org/10.1127/0372-8854/2009/0053-0273 doi: 10.1127/0372-8854/2009/0053-0273
![]() |
[30] |
Ciccacci S, D'Alessandro L, Fredi P, et al. (1988) Contributo dell'analisi geomorfica quantitativa allo studio dei processi di denudazione nel bacino idrografco del Torrente Paglia (Toscana meridionale—Lazio settentrionale). Geogr Fis Dinam Quat 1: 171–188 (In Italian). https://doi.org/10.13140/2.1.2991.6802 doi: 10.13140/2.1.2991.6802
![]() |
[31] | Moretti GP, Cianficconi F, Peroni E, et al. (1988) Considerazioni sulle comunità macrobentoniche del sistema fluviale Paglia Chiani. Boll Mus Sto Nat Lunigiana 67: 157161. |
[32] |
Protano G, Nannoni F (2018) Influence of ore processing activity on Hg, As and Sb contamination and fractionation in soils in a former mining site of Monte Amiata ore district (Italy). Chemosphere 199: 320–330. https://doi.org/10.1016/j.chemosphere.2018.02.051 doi: 10.1016/j.chemosphere.2018.02.051
![]() |
[33] | Montefinese S, Benvenuti M, Buccianti A, et al. (2021) Mercury in Quaternary sediments of the Paglia-Pagliola River system (Monte Amiata). Congresso della Società Geologica Italiana In press. |
[34] |
Fornasaro S, Morelli G, Rimondi V, et al. (2022) Mercury distribution around the Siele Hg mine (Mt. Amiata district, Italy) twenty years after reclamation: Spatial and temporal variability in soil, stream sediments, and air. J Geochem Explor 232: 106886. https://doi.org/10.1016/j.gexplo.2021.106886 doi: 10.1016/j.gexplo.2021.106886
![]() |
[35] | Italian Ministry of the Environment. D.Lgs 152/06—Legislative Decree. Norme in Materia Ambientale. Gazzetta Ufficiale N. 88. 2006. Available from: https://www.gazzettaufficiale.it/dettaglio/codici/materiaAmbientale |
[36] |
Pasquetti F, Vaselli O, Zanchetta G, et al. (2020) Sedimentological, Mineralogical and Geochemical Features of Late Quaternary Sediment Profiles from the Southern Tuscany Hg Mercury District (Italy): Evidence for the Presence of Pre-Industrial Mercury and Arsenic Concentrations. Water 12: 1998. https://doi.org/10.3390/w12071998 doi: 10.3390/w12071998
![]() |
[37] |
Ruggieri G, Morelli G, Benvenuti M, et al. (2021) Origin of the As anomaly in Quaternary sediments of Southern Tuscany (Italy): New insights from geological, geochemical and fluid inclusion data from the Pecora River and Bruna River Valleys. Sed Geol 416: 105876. https://doi.org/10.1016/j.sedgeo.2021.105876 doi: 10.1016/j.sedgeo.2021.105876
![]() |
[38] |
Gray JE, Pribil MJ, Higueras PL (2013) Mercury isotope fractionation during ore retorting in the Almadén mining district, Spain. Chem Geol 357: 150–157. https://doi.org/10.1016/j.chemgeo.2013.08.036 doi: 10.1016/j.chemgeo.2013.08.036
![]() |
[39] |
Meloni F, Montegrossi G, Lazzaroni M, et al. (2021) Total and leached arsenic, mercury and antimony in the mining waste dumping area of Abbadia San Salvatore (Mt. Amiata, Central Italy). Appl Sci 11: 7893. https://doi.org/10.3390/app11177893 doi: 10.3390/app11177893
![]() |
[40] |
Rimondi V, Gray JE, Costagliola P, et al. (2012) Concentration, distribution, and translocation of mercury and methylmercury in mine-waste, sediment, soil, water, and fish collected near the Abbadia San Salvatore mercury mine, Monte Amiata district, Italy. Sci Total Environ 414: 318–327. https://doi.org/10.1016/j.scitotenv.2011.10.065 doi: 10.1016/j.scitotenv.2011.10.065
![]() |
[41] |
Pattelli G, Rimondi V, Benvenuti M, et al. (2014) Effects of the November 2012 flood event on the mobilization of Hg from the mount Amiata Mining district to the sediments of the Paglia river basin. Minerals 4: 241–256. https://doi.org/10.3390/min4020241 doi: 10.3390/min4020241
![]() |
[42] |
Gray JE, Rimondi V, Costagliola P, et al. (2014) Long-distance transport of Hg, Sb, and As from a mined area, conversion of Hg to methyl-Hg, and uptake of Hg by fish on the Tiber River basin, west-central Italy. Environ Geochem Health 36: 145–157. https://doi.org/10.1007/s10653-013-9525-z doi: 10.1007/s10653-013-9525-z
![]() |
[43] |
Colica A, Benvenuti M, Chiarantini L, et al. (2019) From point source to diffuse source of contaminants: the example of mercury dispersion in the Paglia River (Central Italy). Catena 172: 488–500. https://doi.org/10.1016/j.catena.2018.08.043 doi: 10.1016/j.catena.2018.08.043
![]() |
[44] |
Rimondi V, Costagliola P, Lattanzi P, et al. (2019) A 200 km-long mercury contamination of the Paglia and Tiber floodplain: monitoring results and implications for environmental management. Environ Pollut 255: 11319. https://doi.org/10.1016/j.envpol.2019.113191 doi: 10.1016/j.envpol.2019.113191
![]() |
[45] |
Fornasaro S, Morelli G, Rimondi V, et al. (2022) The extensive mercury contamination in soil and legacy sediments of the Paglia River basin (Tuscany, Italy): interplay between Hg-mining waste discharge along rivers, 1960s economic boom, and ongoing climate change. J Soils Sediments 22: 656–671. https://doi.org/10.1007/s11368-021-03129-0 doi: 10.1007/s11368-021-03129-0
![]() |
[46] |
Brigante R, Cencetti C, De Rosa P, et al. (2017) Use of aerial multispectral images for spatial analysis of flooded riverbed-alluvial plain systems: the case study of the Paglia River (central Italy). Geomatic Nat Hazard Risk 8: 1126–1143. https://doi.org/10.1080/19475705.2017.1300607 doi: 10.1080/19475705.2017.1300607
![]() |
[47] |
Chiarantini L, Benvenuti M, Beutel M, et al. (2016) Mercury and arsenic in stream sediments and surface waters of the Orcia River basin, southern Tuscany, Italy. Water Air Soil Pollut 227: 1–15. https://doi.org/10.1007/s11270-016-3110-x doi: 10.1007/s11270-016-3110-x
![]() |
[48] |
Lattanzi P, Rimondi V, Chiarantini L, et al. (2017) Mercury dispersion through streams draining the Mt. Amiata district, southern Tuscany, Italy. Procedia Earth Planet Sci 17: 468–471. https://doi.org/10.1016/j.proeps.2016.12.118 doi: 10.1016/j.proeps.2016.12.118
![]() |
[49] |
Lattanzi P, Costagliola P, Paolieri M (2020) Potential risk from the use of mine-contaminated sediments for road and rail embankments: preliminary data from Central Italy. EGU General Assembly Conference Abstracts, 11394. https://doi.org/10.5194/egusphere-egu2020-11394 doi: 10.5194/egusphere-egu2020-11394
![]() |
[50] |
Chiarantini L, Rimondi V, Bardelli F, et al. (2017) Mercury speciation in Pinus nigra barks from Monte Amiata (Italy): An X-ray absorption spectroscopy study. Environ Pollut 227: 83–88. https://doi.org/10.1016/j.envpol.2017.04.038 doi: 10.1016/j.envpol.2017.04.038
![]() |
[51] |
Bardelli F, Rimondi V, Lattanzi P, et al. (2022) Pinus nigra barks from a mercury mining district studied with high resolution XANES spectroscopy. Environ Sci Processes Impacts. https://doi.org/10.1039/D2EM00239F doi: 10.1039/D2EM00239F
![]() |
[52] |
Rimondi V, Bardelli F, Benvenuti M, et al. (2014) Mercury speciation in the Mt. Amiata mining district (Italy): Interplay between urban activities and mercury contamination. Chem Geol 380: 110–118. https://doi.org/10.1016/j.chemgeo.2014.04.023 doi: 10.1016/j.chemgeo.2014.04.023
![]() |
[53] | Italian Ministry of the Environment. D.Lgs 31/01—Legislative Decree. Attuazione della direttiva 98/83/CE relativa alla qualità delle acque destinate al consumo umano. Gazzetta Ufficiale N. 52. 2001. Available from: https://www.gazzettaufficiale.it/eli/id/2001/03/03/001G0074/sg. |
[54] |
Minissale A, Magro G, Vaselli O, et al. (1997) Geochemistry of water and gas discharges from the Mt. Amiata silicic complex and surrounding areas (central Italy). J Volcanol Geotherm Res 79: 223–251. https://doi.org/10.1016/S0377-0273(97)00028-0 doi: 10.1016/S0377-0273(97)00028-0
![]() |
[55] |
Tamasi G, Cini R (2003) Study of binary and ternary metal complexes containing the sulfato ligand: molecular models for selected non-catalytic sites in sulfurylase. Dalton Trans 14: 2928–2936. https://doi.org/10.1039/b302779a doi: 10.1039/b302779a
![]() |
[56] |
Magi F, Doveri M, Menichini M, et al. (2019) Groundwater response to local climate variability: hydrogeological and isotopic evidences from the Mt. Amiata volcanic aquifer (Tuscany, central Italy). Rend Fis Nat Acc Lincei 30: 125–136. https://doi.org/10.1007/s12210-019-00779-8 doi: 10.1007/s12210-019-00779-8
![]() |
[57] |
Vaselli O, Lazzaroni M, Nisi B, et al. (2021) Discontinuous Geochemical Monitoring of the Galleria Italia Circumneutral Waters (Former Hg-Mining Area of Abbadia San Salvatore, Tuscany, Central Italy) Feeding the Fosso Della Chiusa Creek. Environments 8: 15. https://doi.org/10.3390/environments8020015 doi: 10.3390/environments8020015
![]() |
[58] |
Lazzaroni M, Vetuschi Zuccolini M, Nisi B, et al. (2022) Mercury and Arsenic Discharge from Circumneutral Waters Associated with the Former Mining Area of Abbadia San Salvatore (Tuscany, Central Italy). Int J Environ Res Public Health 19: 5131. https://doi.org/10.3390/ijerph19095131 doi: 10.3390/ijerph19095131
![]() |
[59] |
Vaselli O, Higueras P, Nisi B, et al. (2013) Distribution of gaseous Hg in the Mercury mining district of Mt. Amiata (Central Italy): A geochemical survey prior the reclamation project. Environ Res 125: 179–187. https://doi.org/10.1016/j.envres.2012.12.010 doi: 10.1016/j.envres.2012.12.010
![]() |
[60] |
Cabassi J, Tassi F, Venturi S, et al. (2017) A new approach for the measurement of gaseous elemental mercury (GEM) and H2S in air from anthropogenic and natural sources: examples from Mt. Amiata (Siena, Central Italy) and Solfatara Crater (Campi Flegrei, Southern Italy). J Geochem Explor 175: 48–58. https://doi.org/10.1016/j.gexplo.2016.12.017 doi: 10.1016/j.gexplo.2016.12.017
![]() |
[61] |
McLagan DS, Monaci F, Huang H, et al. (2019) Characterization and Quantification of Atmospheric Mercury Sources Using Passive Air Samplers. J Geophys Res Atmos 124: 2351–2362. https://doi.org/10.1029/2018JD029373 doi: 10.1029/2018JD029373
![]() |
[62] | Galoppini C, Lotti G, Pelosi P (1971) Contenuto di mercurio di piante cresciute al Monte Amiata. Agric Italliana 71. |
[63] |
Bargagli R, Barghigiani C, Maserti, BE (1986) Mercury in vegetation of the Mount Amiata area (Italy). Chemosphere 15: 1035–1042. https://doi.org/10.1016/0045-6535(86)90555-2 doi: 10.1016/0045-6535(86)90555-2
![]() |
[64] |
Bargagli R, Barghigiani C (1991) Lichen biomonitoring of mercury emission and deposition in mining, geothermal and volcanic areas of Italy. Environ Monit Assess 16: 265–275. https://doi.org/10.1007/BF00397614 doi: 10.1007/BF00397614
![]() |
[65] |
Ferrara R, Maserti BE, Breder R (1991) Mercury in abiotic and biotic compartments of an area affected by a geochemical anomaly (Mt. Amiata, Italy). Water Air Soil Pollut 56: 219–233. https://doi.org/10.1007/BF00342273 doi: 10.1007/BF00342273
![]() |
[66] |
Bacci E, Gaggi C, Duccini M, et al. (1994) Mapping mercury vapours in an abandoned cinnabar mining area by azalea (Azalea indica) leaf trapping. Chemosphere 29: 641–656. https://doi.org/10.1016/0045-6535(94)90036-1 doi: 10.1016/0045-6535(94)90036-1
![]() |
[67] |
Barghigiani C, Ristori, T (1994) Mercury levels in agricultural products of Mt. Amiata (Tuscany, Italy). Arch Environ Contam Toxicol 26: 329–334. https://doi.org/10.1007/BF00203559 doi: 10.1007/BF00203559
![]() |
[68] |
Rimondi V, Costagliola P, Benesperi R, et al. (2020) Black pine (Pinus nigra) barks: A critical evaluation of some sampling and analysis parameters for mercury biomonitoring purposes. Ecol Indic 112: 106110. https://doi.org/10.1016/j.ecolind.2020.106110 doi: 10.1016/j.ecolind.2020.106110
![]() |
[69] |
Rimondi V, Benesperi R, Beutel MW, et al. (2020) Monitoring of airborne mercury: Comparison of different techniques in the Monte Amiata District, Southern Tuscany, Italy. Int J Environ Res Public Health 17: 2353. https://doi.org/10.3390/ijerph17072353 doi: 10.3390/ijerph17072353
![]() |
[70] | Fornasaro S, Ciani F, Morelli G, et al. (2022) Mercury in chestnut tree-rings of the Monte Amiata area (Central Italy): impact of past mining activity and present-day geothermal power plants. SGI-SIMP Mtg, Torino. In press. |
[71] |
Monaci F, Ancora S, Paoli L, et al. (2022) Air quality in post-mining towns: tracking potentially toxic elements using tree leaves. Environ Geochem Health, 1–17. https://doi.org/10.1007/s10653-022-01252-6 doi: 10.1007/s10653-022-01252-6
![]() |
[72] | Mattioli A (2019) Inquinamento da mercurio dei fiumi Paglia e Tevere. Valutazione di impatto sulla salute. Azienda Unità Sanitaria Locale Umbria 2, Unita di Progetto Ambiente e salute Terni, 17. Available from: https://www.snpambiente.it/2019/04/29/contaminazione-da-mercurio-dellasta-fluviale-paglia-tevere/. |
[73] | Borum B, Manibusan MK, Schoeny R, et al. (2001) Water quality criterion for the protection of human health: methylmercury. USEPA. |
[74] | Fornasaro S, Delicato G, Ciani F, et al. (2021) The potential wildfire effects on mercury remobilization from soil and biomass in the Mt. Amiata mining district. Congresso della Società Geologica Italiana 1: 270. |
[75] | Lamborg CH, Bowman K, Hammerschmidt C, et al. (2014) Mercury in the anthropocene ocean. Oceanography 27: 76–87. Available from: https://www.jstor.org/stable/24862122. |
[76] |
Kotnik J, Horvat M, Tessier E, et al. (2007) Mercury speciation in surface and deep waters of the Mediterranean Sea. Mar Chem 107: 13–30. https://doi.org/10.1016/j.marchem.2007.02.012 doi: 10.1016/j.marchem.2007.02.012
![]() |
[77] |
Baldi F, Bargagli R, Renzoni A (1979) The distribution of mercury in the surficial sediments of the northern Tyrrhenian Sea. Mar Pollut Bull 10: 301–303. https://doi.org/10.1016/0025-326X(79)90201-7 doi: 10.1016/0025-326X(79)90201-7
![]() |
[78] |
Seritti A, Petrosino A, Morelli E, et al. (1982) The biogeochemical cycle of mercury in the mediterranean: Part Ⅰ: Participate and dissolved forms of mercury in the Northern Tyrrhenian Sea. Environ Technol Lett 3: 251–256. https://doi.org/10.1080/09593338209384124 doi: 10.1080/09593338209384124
![]() |
[79] |
Baldi F, D'Amato ML (1986) Mercury pollution in marine sediment cores near cinnabar deposits and a chlor-alkali plant. Sci Total Environ 57: 111–120. https://doi.org/10.1016/0048-9697(86)90016-1 doi: 10.1016/0048-9697(86)90016-1
![]() |
[80] | Barghigiani C, Ristori T (1995) Preliminary Results on the Role of Rivers in Total Hg Concentrations in Marine Sediments and Benthic Organisms of a Coastal Area of Italy, Mercury as a Global Pollutant, Springer, Dordrecht. https://doi.org/10.1007/978-94-011-0153-0_111 |
[81] |
Ferrara R, Maserti BE, Andersson M, et al. (1997) Mercury degassing rate from mineralized areas in the Mediterranean basin. Water Air Soil Pollut 93: 59–66. https://doi.org/10.1007/BF02404747 doi: 10.1007/BF02404747
![]() |
[82] |
Rajar R, Četina M, Horvat M, et al. (2007) Mass balance of mercury in the Mediterranean Sea. Mar Chem 107: 89–102. https://doi.org/10.1016/j.marchem.2006.10.001 doi: 10.1016/j.marchem.2006.10.001
![]() |
[83] |
Scanu S, Piazzolla D, Frattarelli FM, et al. (2016) Mercury enrichment in sediments of the coastal area of northern Latium, Italy. Bull Environ Contam Toxicol 96: 630–637. https://doi.org/10.1007/s00128-016-1776-9 doi: 10.1007/s00128-016-1776-9
![]() |
[84] |
Montuori P, Aurino S, Garzonio F, et al. (2016) Estimation of heavy metal loads from Tiber River to the Tyrrhenian Sea and environmental quality assessment. Environ Sci Poll Res 23: 23694–23713. https://doi.org/10.1007/s11356-016-7557-5 doi: 10.1007/s11356-016-7557-5
![]() |
[85] | Lattanzi P, Costagliola P, Rimondi V, et al. (2019) New data on the presence and distribution of Hg in the Paglia-Tiber fluvial system. Geophysical Res Abstract 21. |
[86] |
Fornasaro S, Morelli G, Costagliola P, et al. (2022) The contribute of the Paglia-Tiber River system (Central Italy) to the total mercury mass load in the Mediterranean Sea. Toxics 10: 395. https://doi.org/10.3390/toxics10070395 doi: 10.3390/toxics10070395
![]() |
[87] | Belardi G, Marabini AM, et al. (1996) Check on level of environmental contamination by mercury and cleanup of Abetina Mining area (Grosseto-Italia). Warrendale, PA (United States). |
[88] | Bacci E, Facciotto C, Giunti M, et al. (2003) Miniera del Siele: azioni di monitoraggio e verifiche statiche a bonifica terminata. Novembre 2001-dicembre 2002. Report to Comunità Montana Amiata Senese, Piancastagnaio (In Italian). |
[89] | Malferrari D, Brigatti MF, Elmi C, et al. (2011) Determination of Hg binding forms in contaminated soils and sediments: state of the art and a case study approaching abandoned mercury mines from Mt. Amiata (Siena, Italy). N Jb Miner Abh 188: 65–74. https://doi.org/10.1127/0077-7757/2011/0194 |
[90] | Mining Italiana (1996) Progetto esecutivo di bonifica ambientale dell'area mineraria del Siele. All. 1A. Roma (Italy), 32 (in Italian). |
[91] | Bianchi F, Rappuoli D, Vaselli O, et al. (2019) Distribution of mercury, antimony and arsenic in the terrains from the former mining area of Abbadia San Salvatore (Siena, central Italy). Abstr SGI-SIMP Congress. Available from: https://www.socgeol.it/N2119/congresso-simp-sgi-sogei-2019-il-tempo-del-pianeta-terra-e-il-tempo-dell-uomo-le-geoscienze-fra-passato-e-futuro.html |
[92] | Vaselli O, Rappuoli D, Bianchi F, et al. (2019) One hundred years of mercury exploitation at the mining area of Abbadia San Salvatore (Mt. Amiata, Central Italy): A methodological approach for a complex reclamation activity before the establishment of a new mining park. El patrimonio geológico y minero: Identidad y motor de desarrollo, Instituto Geológico y Minero de España, 1109–1126. |
[93] |
Vaselli O, Nisi B, Rappuoli D, et al. (2017) Gaseous elemental mercury and total and leached mercury in building materials from the former Hg-mining area of Abbadia San Salvatore (Central Italy). Int J Environ Res Public Health 14: 425. https://doi.org/10.3390/ijerph14040425 doi: 10.3390/ijerph14040425
![]() |
[94] |
Lazzaroni M, Nisi B, Rappuoli D, et al. (2020) A New Low-Cost and Reliable Method to Evaluate the Release of Hg0 from Synthetic Materials. Processes 8: 1282. https://doi.org/10.3390/pr8101282 doi: 10.3390/pr8101282
![]() |
[95] |
Cabassi J, Lazzaroni M, Giannini L, et al. (2022) Continuous and near real-time measurements of gaseous elemental mercury (GEM) from an Unmanned Aerial Vehicle: A new approach to investigate the 3D distribution of GEM in the lower atmosphere. Chemosphere 288: 132547. https://doi.org/10.1016/j.chemosphere.2021.132547 doi: 10.1016/j.chemosphere.2021.132547
![]() |
[96] | Meloni F, Vaselli O, Nisi B, et al. (2019) Geochemical feature of shallow aquifer in the former mining area of Abbadia San Salvatore (Tuscany, central Italy). Abstr SGI-SIMP Congress 645. Available from: https://www.socgeol.it/N2119/congresso-simp-sgi-sogei-2019-il-tempo-del-pianeta-terra-e-il-tempo-dell-uomo-le-geoscienze-fra-passato-e-futuro.html |
[97] | Parkhurst DL, Appelo CAJ (1999) User's guide to PHREEQC (Version 2): A computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations. Water-Resour Invest Rep 99: 312. |
[98] | Barsi C (1957) Lo stato attuale della silicosi nei minatori di mercurio del Monte Amiata. Rass Med Ind 26: 74–86. (In Italian). |
[99] | Barsi C (1956) Studio clinico-statistico sul mercurialismo nell'industria mineraria del mercurio del Monte Amiata. Rass Med Ind 25: 121–132. (In Italian). |
[100] | Caselli G, Rosati C, Simone M (2007) La popolazione dei comuni minerari dell'Amiata. Popolazione E Storia 8: 63–89. (In Italian). Available from: https://popolazioneestoria.it/article/view/276. |
[101] | RAIS. The Risk Assessment Information System, Toxicity Profiles, Condensed Toxicity Summary for Mercury, 2018. Available from: https://rais.ornl.gov/tox/profiles/mercury_c_V1.html. |
[102] | Società Italiana Valori di Riferimento (2017) Quarta lista dei valori di riferimento per elementi, composti organici e loro metaboliti. Available from: http://www.sivr.it/ |
[103] |
Rossi LC, Clemente GF, Santaroni G (1976) Mercury and selenium distribution in a defined area and in its population. Arch Environ Health Int J 31: 160–165. https://doi.org/10.1080/00039896.1976.10667211 doi: 10.1080/00039896.1976.10667211
![]() |
[104] | Cinquina AL, Vaccari S, Santis LD, et al. (2000) Mercury contamination in products of animal origin [honey-ewe milk-freshwater fish] and biologic matrices [sheep kidney-wool-blood] taken from Mount Amiata [Tuscany]. Obiettivi e Documenti Veterinari 21: 55–58. |
[105] | Montomoli L, Sisinni AG, Cioni F, et al. (2002) Valutazione delle fonti di assorbimento di mercurio tramite lo studio dei livelli di mercurio urinario della popolazione generale. Med Lav 93: 184–188. |
[106] | Minichilli F, Nuvolone D, Bustaffa E, et al. (2012) State of health of populations residing in geothermal areas of Tuscany. Epidemiol Prev 36: 1–104. |
[107] |
Bustaffa E, Minichilli F, Nuvolone D, et al. (2017) Mortality of populations residing in geothermal areas of Tuscany during the period 2003–2012. Ann Ist Super Sanità 53: 108–117. https://doi.org/10.4415/ANN_17_02_06 doi: 10.4415/ANN_17_02_06
![]() |
[108] |
Bustaffa E, Cori L, Manzella A, et al. (2020) The health of communities living in proximity of geothermal plants generating heat and electricity: A review. Sci Tot Environ 706: 135998. https://doi.org/10.1016/j.scitotenv.2019.135998 doi: 10.1016/j.scitotenv.2019.135998
![]() |
[109] | ARS, Agenzia Regionale Sanità della Toscana (2021) Geotermia e salute in Toscana—Rapporto 2021. Available from: https://www.ars.toscana.it/2-articoli/4688-geotermia-e-salute-in-toscana-rapporto-2021.html |
[110] |
Bates MN, Garrett N, Graham B, et al. (1997) Air pollution and mortality in the Rotorua geothermal area. Aust N Zealand J Public Health 21: 581–586. https://doi.org/10.1111/j.1467-842X.1997.tb01759.x doi: 10.1111/j.1467-842X.1997.tb01759.x
![]() |
[111] | Fornasaro S, Morelli G, Rimondi V, et al. (2021) Mercury and Methylmercury in the Monte Amiata Mining District. Mendeley Data. https://doi.org/10.17632/62jm9wr36b.1 |
1. | Maimoona Karim, Aliya Fahmi, Zafar Ullah, Muhammad Awais Tariq Bhatti, Ather Qayyum, On certain Ostrowski type integral inequalities for convex function via AB-fractional integral operator, 2023, 8, 2473-6988, 9166, 10.3934/math.2023459 | |
2. | Hasan Bayram, Sibel Yalçın, Jia-Bao Liu, Convolution and Coefficient Estimates for (p,q)-Convex Harmonic Functions Associated with Subordination, 2022, 2022, 2314-8888, 1, 10.1155/2022/5317797 | |
3. | Soubhagya Kumar Sahoo, Y.S. Hamed, Pshtiwan Othman Mohammed, Bibhakar Kodamasingh, Kamsing Nonlaopon, New midpoint type Hermite-Hadamard-Mercer inequalities pertaining to Caputo-Fabrizio fractional operators, 2023, 65, 11100168, 689, 10.1016/j.aej.2022.10.019 | |
4. | Soubhagya Kumar Sahoo, Ravi P. Agarwal, Pshtiwan Othman Mohammed, Bibhakar Kodamasingh, Kamsing Nonlaopon, Khadijah M. Abualnaja, Hadamard–Mercer, Dragomir–Agarwal–Mercer, and Pachpatte–Mercer Type Fractional Inclusions for Convex Functions with an Exponential Kernel and Their Applications, 2022, 14, 2073-8994, 836, 10.3390/sym14040836 | |
5. | Miguel Vivas-Cortez, Muhammad Uzair Awan, Sehrish Rafique, Muhammad Zakria Javed, Artion Kashuri, Some novel inequalities involving Atangana-Baleanu fractional integral operators and applications, 2022, 7, 2473-6988, 12203, 10.3934/math.2022678 | |
6. | Mirna Rodić, On the Converse Jensen-Type Inequality for Generalized f-Divergences and Zipf–Mandelbrot Law, 2022, 10, 2227-7390, 947, 10.3390/math10060947 | |
7. | Bandar Bin-Mohsin, Sehrish Rafique, Clemente Cesarano, Muhammad Zakria Javed, Muhammad Uzair Awan, Artion Kashuri, Muhammad Aslam Noor, Some General Fractional Integral Inequalities Involving LR–Bi-Convex Fuzzy Interval-Valued Functions, 2022, 6, 2504-3110, 565, 10.3390/fractalfract6100565 | |
8. | Saad Ihsan Butt, Iram Javed, Praveen Agarwal, Juan J. Nieto, Newton–Simpson-type inequalities via majorization, 2023, 2023, 1029-242X, 10.1186/s13660-023-02918-0 | |
9. | Fahd Jarad, Soubhagya Kumar Sahoo, Kottakkaran Sooppy Nisar, Savin Treanţă, Homan Emadifar, Thongchai Botmart, New stochastic fractional integral and related inequalities of Jensen–Mercer and Hermite–Hadamard–Mercer type for convex stochastic processes, 2023, 2023, 1029-242X, 10.1186/s13660-023-02944-y | |
10. | Jun Yang, Muhammad Kamran Siddiqui, Mazhar Hussain, Shazia Manzoor, Nazir Hussain, Zohaib Saddique, QSPR Analysis of Some Phenolic Compounds Present in Moringa Oleifera , 2024, 44, 1040-6638, 4197, 10.1080/10406638.2023.2247120 | |
11. | XIAOMAN YUAN, LEI XU, TINGSONG DU, SIMPSON-LIKE INEQUALITIES FOR TWICE DIFFERENTIABLE (s,P)-CONVEX MAPPINGS INVOLVING WITH AB-FRACTIONAL INTEGRALS AND THEIR APPLICATIONS, 2023, 31, 0218-348X, 10.1142/S0218348X2350024X | |
12. | Asfand Fahad, Saad Ihsaan Butt, Josip Pečarić, Marjan Praljak, Generalized Taylor’s Formula and Steffensen’s Inequality, 2023, 11, 2227-7390, 3570, 10.3390/math11163570 | |
13. | Mulugeta Dawud Ali, D. L. Suthar, On the fractional q-integral operators involving q-analogue of Mittag-Leffler function, 2024, 44, 0174-4747, 245, 10.1515/anly-2023-0107 | |
14. | Saad Ihsan Butt, Praveen Agarwal, Juan J. Nieto, New Hadamard–Mercer Inequalities Pertaining Atangana–Baleanu Operator in Katugampola Sense with Applications, 2024, 21, 1660-5446, 10.1007/s00009-023-02547-3 | |
15. | WENBING SUN, HAIYANG WAN, HERMITE–HADAMARD-TYPE INEQUALITIES INVOLVING SEVERAL KINDS OF FRACTIONAL CALCULUS FOR HARMONICALLY CONVEX FUNCTIONS, 2023, 31, 0218-348X, 10.1142/S0218348X23501098 | |
16. | Saad Ihsan Butt, Yamin Sayyari, Praveen Agarwal, Juan J. Nieto, Muhammad Umar, On some inequalities for uniformly convex mapping with estimations to normal distributions, 2023, 2023, 1029-242X, 10.1186/s13660-023-02997-z | |
17. | Muhammad Nadeem, Awais Yousaf, Seemab Sheik, A Novel Approach to Investigate Sadhana and PI Indices, 2024, 44, 1040-6638, 5060, 10.1080/10406638.2023.2259566 | |
18. | Muhammad Tariq, Sotiris K. Ntouyas, Bashir Ahmad, Ostrowski-Type Fractional Integral Inequalities: A Survey, 2023, 3, 2673-9321, 660, 10.3390/foundations3040040 | |
19. | Miguel Vivas–Cortez, Muhammad Zakria Javed, Muhammad Uzair Awan, Muhammad Aslam Noor, Silvestru Sever Dragomir, Bullen-Mercer type inequalities with applications in numerical analysis, 2024, 96, 11100168, 15, 10.1016/j.aej.2024.03.093 | |
20. | Ammara Nosheen, Sana Ijaz, Khuram Ali Khan, Khalid Mahmood Awan, Hüseyin Budak, Quantum symmetric integral inequalities for convex functions, 2024, 47, 0170-4214, 14878, 10.1002/mma.10310 | |
21. | Erhan Set, Ahmet Akdemir, Emin Özdemir, Ali Karaoğlan, Mustafa Dokuyucu, New integral inequalities for Atangana-Baleanu fractional integral operators and various comparisons via simulations, 2023, 37, 0354-5180, 2251, 10.2298/FIL2307251S | |
22. | Timur Gamilov, Ruslan Yanbarisov, Fractional-Order Windkessel Boundary Conditions in a One-Dimensional Blood Flow Model for Fractional Flow Reserve (FFR) Estimation, 2023, 7, 2504-3110, 373, 10.3390/fractalfract7050373 | |
23. | Muhammad Mudassar Hassan, Shamoona Jabeen, Haidar Ali, Parvez Ali, Connection-based modified Zagreb indices of Boron triangular sheet BTS(m,n), 2023, 0026-8976, 10.1080/00268976.2023.2226242 | |
24. | Asfand Fahad, Saad Ihsaan Butt, Bahtiyar Bayraktar, Mehran Anwar, Yuanheng Wang, Some New Bullen-Type Inequalities Obtained via Fractional Integral Operators, 2023, 12, 2075-1680, 691, 10.3390/axioms12070691 | |
25. | Tahir Rasheed, Saad Ihsan Butt, Ðilda Pečarić, Josip Pečarić, New bounds of Popoviciu's difference via weighted Hadamard type inequalities with applications in information theory, 2024, 47, 0170-4214, 5750, 10.1002/mma.9889 | |
26. | Shanhe Wu, Muhammad Adil Khan, Shah Faisal, Tareq Saeed, Eze R. Nwaeze, Derivation of Hermite-Hadamard-Jensen-Mercer conticrete inequalities for Atangana-Baleanu fractional integrals by means of majorization, 2024, 57, 2391-4661, 10.1515/dema-2024-0024 | |
27. | Zeynep Çiftci, Merve Coşkun, Çetin Yildiz, Luminiţa-Ioana Cotîrlă, Daniel Breaz, On New Generalized Hermite–Hadamard–Mercer-Type Inequalities for Raina Functions, 2024, 8, 2504-3110, 472, 10.3390/fractalfract8080472 | |
28. | Muhammad Amer Latif, New extensions related to Fejér-type inequalities for GA-convex functions, 2024, 57, 2391-4661, 10.1515/dema-2024-0006 | |
29. | PANUMART SAWANGTONG, K. LOGESWARI, C. RAVICHANDRAN, KOTTAKKARAN SOOPPY NISAR, V. VIJAYARAJ, FRACTIONAL ORDER GEMINIVIRUS IMPRESSION IN CAPSICUM ANNUUM MODEL WITH MITTAG-LEFFLER KERNAL, 2023, 31, 0218-348X, 10.1142/S0218348X23400492 | |
30. | Barış Çelik, Hüseyin Budak, Erhan Set, On generalized Milne type inequalities for new conformable fractional integrals, 2024, 38, 0354-5180, 1807, 10.2298/FIL2405807C | |
31. | Çetin Yıldız, Samet Erden, Seth Kermausuor, Daniel Breaz, Luminiţa-Ioana Cotîrlă, New estimates on generalized Hermite–Hadamard–Mercer-type inequalities, 2025, 2025, 1687-2770, 10.1186/s13661-025-02012-y |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.90724849 | 6.90796199 | 6.91434953 | 0.01032973 | 0.10280563 |
2nd | 26.09674381 | 26.13470717 | 26.42771700 | 0.14547164 | 1.26825473 |
3rd | 52.84510702 | 53.16067633 | 54.27922231 | 0.59715900 | 2.71380904 |
4th | 81.45836541 | 82.55087709 | 74.63946703 | 1.34119028 | 8.37102285 |
N=10 | |||||
1st | 6.90724849 | 6.90729342 | 6.90918512 | 0.00065048 | 0.02803765 |
2nd | 26.09674381 | 26.09915748 | 26.18963094 | 0.00924893 | 0.35593375 |
3rd | 52.84510702 | 52.86511702 | 53.29345172 | 0.03786538 | 0.84841289 |
4th | 81.45836541 | 81.53039633 | 80.56105229 | 0.08842667 | 1.10156043 |
N=50 | |||||
1st | 6.90724849 | 6.90724856 | 6.90732785 | 0.000000101 | 0.00114894 |
2nd | 26.09674382 | 26.09674771 | 26.10054215 | 0.00001487 | 0.01455480 |
3rd | 52.84510702 | 52.84513933 | 52.86350476 | 0.00006114 | 0.03481446 |
4th | 81.45836541 | 81.45848351 | 81.43321124 | 0.00014498 | 0.03087979 |
N=100 | |||||
1st | 6.90724849 | 6.90724851 | 6.90726831 | 0.00000029 | 0.00028694 |
2nd | 26.09674382 | 26.09674412 | 26.09769399 | 0.00000115 | 0.00028694 |
3rd | 52.84510702 | 52.84510912 | 52.84970909 | 0.00000397 | 0.00870860 |
4th | 81.45836541 | 81.45837285 | 81.45215478 | 0.00000913 | 0.00762930 |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.35701924 | 6.35757819 | 6.38367463 | 0.00879264 | 0.41930642 |
2nd | 18.88435515 | 18.89870611 | 18.60125288 | 0.07599391 | 1.49913654 |
3rd | 37.23312923 | 37.33388399 | 34.14209661 | 0.27060513 | 8.30183410 |
4th | 66.98883703 | 67.54369195 | 61.04497484 | 0.82827967 | 8.87291440 |
N=10 | |||||
1st | 6.35701924 | 6.35705430 | 6.36418013 | 0.00055151 | 0.11264540 |
2nd | 18.88435515 | 18.88526930 | 18.82742317 | 0.00484077 | 0.30147696 |
3rd | 37.23312923 | 37.23999014 | 36.48814214 | 0.01842689 | 2.00087155 |
4th | 66.98883703 | 66.92997846 | 65.34527890 | 0.08786325 | 2.45348061 |
N=50 | |||||
1st | 6.35701924 | 6.35701929 | 6.35730648 | 0.00000078 | 0.00451846 |
2nd | 18.88435515 | 18.88435660 | 37.20428112 | 0.00000767 | 0.01115087 |
3rd | 37.23312923 | 37.23314046 | 37.20428112 | 0.00003016 | 0.07747968 |
4th | 66.98883703 | 66.98890259 | 66.92288123 | 0.00009786 | 0.09845789 |
N=100 | |||||
1st | 6.35701924 | 6.35701923 | 6.35709101 | 0.00000015 | 0.00112898 |
2nd | 18.88435515 | 18.88435528 | 18.88383000 | 0.00000068 | 0.00278087 |
3rd | 37.23312923 | 37.23312992 | 37.22592579 | 0.00000185 | 0.01934685 |
4th | 66.98883703 | 66.98884110 | 66.97235365 | 0.00000607 | 0.02460615 |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.96985529 | 6.97058784 | 6.97318699 | 0.01051026 | 0.04780157 |
2nd | 27.03932973 | 27.08117845 | 27.20251475 | 0.15476981 | 0.60350986 |
3rd | 57.08313134 | 57.47001406 | 57.52811675 | 0.67775315 | 0.77953924 |
4th | 92.56612927 | 94.07004264 | 80.41180184 | 1.62469078 | 13.13042635 |
N=10 | |||||
1st | 6.96985529 | 6.96990142 | 6.97085023 | 0.00066185 | 0.01427757 |
2nd | 27.03932973 | 27.04200859 | 27.09268028 | 0.00990727 | 0.19730722 |
3rd | 57.08313134 | 57.10818680 | 57.34259598 | 0.04389293 | 0.45453827 |
4th | 92.56612927 | 92.67041635 | 90.82713601 | 0.11238909 | 1.87864964 |
N=50 | |||||
1st | 6.96985529 | 6.96985536 | 6.96989697 | 0.00000100 | 0.00059800 |
2nd | 27.03932973 | 27.03933403 | 27.04157469 | 0.00001590 | 0.00830257 |
3rd | 57.08313134 | 57.08317194 | 57.09446492 | 0.00007112 | 0.01985452 |
4th | 92.56612927 | 92.56630243 | 92.51496052 | 0.00018707 | 0.05527805 |
N=100 | |||||
1st | 6.96985529 | 6.96985538 | 6.96986568 | 0.00000129 | 0.00014907 |
2nd | 27.03932973 | 27.03932996 | 27.03989174 | 0.00000085 | 0.00207849 |
3rd | 57.08313134 | 57.08313385 | 57.08597067 | 0.00000440 | 0.00497403 |
4th | 92.56612927 | 92.56614015 | 92.55346771 | 0.00001175 | 0.01367839 |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 7.00984547 | 7.01058818 | 7.01069925 | 0.01059524 | 0.01217972 |
2nd | 27.72533453 | 27.77009228 | 27.75837598 | 0.01614326 | 0.11917421 |
3rd | 61.16521834 | 61.63086692 | 61.09088070 | 0.76129635 | 0.12153580 |
4th | 105.4525306 | 107.82633768 | 101.05828707 | 2.25106688 | 4.16703475 |
N=10 | |||||
1st | 7.00984547 | 7.00989023 | 7.01218744 | 0.00063853 | 0.03340972 |
2nd | 27.72533453 | 27.72813738 | 27.74771968 | 0.01010934 | 0.08273897 |
3rd | 61.16521834 | 61.19584117 | 61.39079599 | 0.05006575 | 0.08073897 |
4th | 105.4525306 | 105.60832597 | 106.45143402 | 0.14773974 | 0.94725408 |
N=50 | |||||
1st | 7.00984547 | 7.00984337 | 7.00986020 | 0.00002995 | 0.00021013 |
2nd | 27.72533453 | 27.72529534 | 27.72631753 | 0.00014135 | 0.00354549 |
3rd | 61.16521834 | 61.16521665 | 61.17571474 | 0.00002763 | 0.01716073 |
4th | 105.4525306 | 105.45258028 | 105.49998929 | 0.00004703 | 0.04500470 |
N=100 | |||||
1st | 7.00984547 | 7.00984334 | 7.00984750 | 0.00003038 | 0.00002895 |
2nd | 27.72533453 | 27.72529099 | 27.72554833 | 0.00015704 | 0.00077113 |
3rd | 61.16521834 | 61.16516979 | 61.16781319 | 0.00007937 | 0.00424236 |
4th | 105.4525306 | 105.45234022 | 105.46427897 | 0.00018055 | 0.03111408 |
Modes | [23] | FEM by CM | FEM by LM |
K1=K2=1012 | |||
1st | 9.8696 | 9.8696 | 9.8695 |
2nd | 39.478 | 39.4782 | 39.4737 |
3rd | 88.876 | 88.8769 | 88.7669 |
4th | 57.914 | 157.7529 | 157.5231 |
K1=K2=0 | |||
1st | 0.0000 | 0, 0000 | 0.0000 |
2nd | 0.000 | 0.0002 | 0.0041 |
3rd | 22.273 | 22.3740 | 21.7055 |
4th | 61.373 | 61.6881 | 58.6391 |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.90724849 | 6.90796199 | 6.91434953 | 0.01032973 | 0.10280563 |
2nd | 26.09674381 | 26.13470717 | 26.42771700 | 0.14547164 | 1.26825473 |
3rd | 52.84510702 | 53.16067633 | 54.27922231 | 0.59715900 | 2.71380904 |
4th | 81.45836541 | 82.55087709 | 74.63946703 | 1.34119028 | 8.37102285 |
N=10 | |||||
1st | 6.90724849 | 6.90729342 | 6.90918512 | 0.00065048 | 0.02803765 |
2nd | 26.09674381 | 26.09915748 | 26.18963094 | 0.00924893 | 0.35593375 |
3rd | 52.84510702 | 52.86511702 | 53.29345172 | 0.03786538 | 0.84841289 |
4th | 81.45836541 | 81.53039633 | 80.56105229 | 0.08842667 | 1.10156043 |
N=50 | |||||
1st | 6.90724849 | 6.90724856 | 6.90732785 | 0.000000101 | 0.00114894 |
2nd | 26.09674382 | 26.09674771 | 26.10054215 | 0.00001487 | 0.01455480 |
3rd | 52.84510702 | 52.84513933 | 52.86350476 | 0.00006114 | 0.03481446 |
4th | 81.45836541 | 81.45848351 | 81.43321124 | 0.00014498 | 0.03087979 |
N=100 | |||||
1st | 6.90724849 | 6.90724851 | 6.90726831 | 0.00000029 | 0.00028694 |
2nd | 26.09674382 | 26.09674412 | 26.09769399 | 0.00000115 | 0.00028694 |
3rd | 52.84510702 | 52.84510912 | 52.84970909 | 0.00000397 | 0.00870860 |
4th | 81.45836541 | 81.45837285 | 81.45215478 | 0.00000913 | 0.00762930 |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.35701924 | 6.35757819 | 6.38367463 | 0.00879264 | 0.41930642 |
2nd | 18.88435515 | 18.89870611 | 18.60125288 | 0.07599391 | 1.49913654 |
3rd | 37.23312923 | 37.33388399 | 34.14209661 | 0.27060513 | 8.30183410 |
4th | 66.98883703 | 67.54369195 | 61.04497484 | 0.82827967 | 8.87291440 |
N=10 | |||||
1st | 6.35701924 | 6.35705430 | 6.36418013 | 0.00055151 | 0.11264540 |
2nd | 18.88435515 | 18.88526930 | 18.82742317 | 0.00484077 | 0.30147696 |
3rd | 37.23312923 | 37.23999014 | 36.48814214 | 0.01842689 | 2.00087155 |
4th | 66.98883703 | 66.92997846 | 65.34527890 | 0.08786325 | 2.45348061 |
N=50 | |||||
1st | 6.35701924 | 6.35701929 | 6.35730648 | 0.00000078 | 0.00451846 |
2nd | 18.88435515 | 18.88435660 | 37.20428112 | 0.00000767 | 0.01115087 |
3rd | 37.23312923 | 37.23314046 | 37.20428112 | 0.00003016 | 0.07747968 |
4th | 66.98883703 | 66.98890259 | 66.92288123 | 0.00009786 | 0.09845789 |
N=100 | |||||
1st | 6.35701924 | 6.35701923 | 6.35709101 | 0.00000015 | 0.00112898 |
2nd | 18.88435515 | 18.88435528 | 18.88383000 | 0.00000068 | 0.00278087 |
3rd | 37.23312923 | 37.23312992 | 37.22592579 | 0.00000185 | 0.01934685 |
4th | 66.98883703 | 66.98884110 | 66.97235365 | 0.00000607 | 0.02460615 |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 6.96985529 | 6.97058784 | 6.97318699 | 0.01051026 | 0.04780157 |
2nd | 27.03932973 | 27.08117845 | 27.20251475 | 0.15476981 | 0.60350986 |
3rd | 57.08313134 | 57.47001406 | 57.52811675 | 0.67775315 | 0.77953924 |
4th | 92.56612927 | 94.07004264 | 80.41180184 | 1.62469078 | 13.13042635 |
N=10 | |||||
1st | 6.96985529 | 6.96990142 | 6.97085023 | 0.00066185 | 0.01427757 |
2nd | 27.03932973 | 27.04200859 | 27.09268028 | 0.00990727 | 0.19730722 |
3rd | 57.08313134 | 57.10818680 | 57.34259598 | 0.04389293 | 0.45453827 |
4th | 92.56612927 | 92.67041635 | 90.82713601 | 0.11238909 | 1.87864964 |
N=50 | |||||
1st | 6.96985529 | 6.96985536 | 6.96989697 | 0.00000100 | 0.00059800 |
2nd | 27.03932973 | 27.03933403 | 27.04157469 | 0.00001590 | 0.00830257 |
3rd | 57.08313134 | 57.08317194 | 57.09446492 | 0.00007112 | 0.01985452 |
4th | 92.56612927 | 92.56630243 | 92.51496052 | 0.00018707 | 0.05527805 |
N=100 | |||||
1st | 6.96985529 | 6.96985538 | 6.96986568 | 0.00000129 | 0.00014907 |
2nd | 27.03932973 | 27.03932996 | 27.03989174 | 0.00000085 | 0.00207849 |
3rd | 57.08313134 | 57.08313385 | 57.08597067 | 0.00000440 | 0.00497403 |
4th | 92.56612927 | 92.56614015 | 92.55346771 | 0.00001175 | 0.01367839 |
Modes | AM | FEM by CM | FEM by LM | Percentage error | |
For CM | For LM | ||||
N=5 | |||||
1st | 7.00984547 | 7.01058818 | 7.01069925 | 0.01059524 | 0.01217972 |
2nd | 27.72533453 | 27.77009228 | 27.75837598 | 0.01614326 | 0.11917421 |
3rd | 61.16521834 | 61.63086692 | 61.09088070 | 0.76129635 | 0.12153580 |
4th | 105.4525306 | 107.82633768 | 101.05828707 | 2.25106688 | 4.16703475 |
N=10 | |||||
1st | 7.00984547 | 7.00989023 | 7.01218744 | 0.00063853 | 0.03340972 |
2nd | 27.72533453 | 27.72813738 | 27.74771968 | 0.01010934 | 0.08273897 |
3rd | 61.16521834 | 61.19584117 | 61.39079599 | 0.05006575 | 0.08073897 |
4th | 105.4525306 | 105.60832597 | 106.45143402 | 0.14773974 | 0.94725408 |
N=50 | |||||
1st | 7.00984547 | 7.00984337 | 7.00986020 | 0.00002995 | 0.00021013 |
2nd | 27.72533453 | 27.72529534 | 27.72631753 | 0.00014135 | 0.00354549 |
3rd | 61.16521834 | 61.16521665 | 61.17571474 | 0.00002763 | 0.01716073 |
4th | 105.4525306 | 105.45258028 | 105.49998929 | 0.00004703 | 0.04500470 |
N=100 | |||||
1st | 7.00984547 | 7.00984334 | 7.00984750 | 0.00003038 | 0.00002895 |
2nd | 27.72533453 | 27.72529099 | 27.72554833 | 0.00015704 | 0.00077113 |
3rd | 61.16521834 | 61.16516979 | 61.16781319 | 0.00007937 | 0.00424236 |
4th | 105.4525306 | 105.45234022 | 105.46427897 | 0.00018055 | 0.03111408 |
Modes | [23] | FEM by CM | FEM by LM |
K1=K2=1012 | |||
1st | 9.8696 | 9.8696 | 9.8695 |
2nd | 39.478 | 39.4782 | 39.4737 |
3rd | 88.876 | 88.8769 | 88.7669 |
4th | 57.914 | 157.7529 | 157.5231 |
K1=K2=0 | |||
1st | 0.0000 | 0, 0000 | 0.0000 |
2nd | 0.000 | 0.0002 | 0.0041 |
3rd | 22.273 | 22.3740 | 21.7055 |
4th | 61.373 | 61.6881 | 58.6391 |