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Research article

An investigative study on the parameters optimization of the electric discharge machining of Ti6Al4V

  • This investigative study explored the field of electrical discharge machining (EDM), with a particular focus on the machining of Ti6Al4V, a titanium alloy that finds widespread application in aerospace, airframes, engine components, and non-aerospace applications such as power generation and marine and offshore environments. Ti6Al4V presents difficulties for conventional metal cutting techniques because of high cutting forces, poor surface integrity, and tool wear. This has led to the adoption of unconventional techniques like EDM. However, problems like high electrode wear rates, low material removal rates, long machining times, and less-than-ideal surface finishes still exist, especially in large-scale applications. By addressing the particular difficulties associated with large-scale electrical discharge machining and by putting forth a multi-objective optimization strategy, this research makes a substantial contribution to the field. With an emphasis on the optimization of input parameters like pulse on time (Ton), pulse off time (Toff), voltage (HV), and current (LV), which are critical in large-scale industrial applications, the study attempts to evaluate the optimal parameter states that simultaneously accomplish multiple goals during the machining process. This work is the first to simultaneously optimize all relevant output responses, such as material removal rate (MRR), electrode wear rate (EWR), machining time (Tm), surface roughness (Ra), and base radius. Previous studies have concentrated on one or two output responses. To optimize MRR, EWR, Tm, Ra, and base radius, the experiments were carefully planned using design of experiment (DOE) and response Surface methodology (RSM). Regression analysis and ANOVA are two statistical techniques that were used with Minitab 15 to help interpret experimental data and build a solid regression model specifically for Ti6Al4V. Throughout the experiment, a variety of input factor settings were employed, and the responses to those were noted. The following parameters were used to obtain the experimental data: current (LV) at 30 and 50 A, voltage (HV) at 0.3 and 0.7 V, pulse on time (Ton) at 4 and 6.5 µs, and pulse off time (Toff) at 5.5 and 6.5 µs. Ton and current are the most significant variables that influence most of the output responses. By addressing the simultaneous optimization of multiple output responses, this investigative study not only sets a new standard in the field but also identifies current bottlenecks and offers solutions.

    Citation: Muhammad Mansoor Uz Zaman Siddiqui, Syed Amir Iqbal, Ali Zulqarnain, Adeel Tabassum. An investigative study on the parameters optimization of the electric discharge machining of Ti6Al4V[J]. Clean Technologies and Recycling, 2024, 4(1): 43-60. doi: 10.3934/ctr.2024003

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  • This investigative study explored the field of electrical discharge machining (EDM), with a particular focus on the machining of Ti6Al4V, a titanium alloy that finds widespread application in aerospace, airframes, engine components, and non-aerospace applications such as power generation and marine and offshore environments. Ti6Al4V presents difficulties for conventional metal cutting techniques because of high cutting forces, poor surface integrity, and tool wear. This has led to the adoption of unconventional techniques like EDM. However, problems like high electrode wear rates, low material removal rates, long machining times, and less-than-ideal surface finishes still exist, especially in large-scale applications. By addressing the particular difficulties associated with large-scale electrical discharge machining and by putting forth a multi-objective optimization strategy, this research makes a substantial contribution to the field. With an emphasis on the optimization of input parameters like pulse on time (Ton), pulse off time (Toff), voltage (HV), and current (LV), which are critical in large-scale industrial applications, the study attempts to evaluate the optimal parameter states that simultaneously accomplish multiple goals during the machining process. This work is the first to simultaneously optimize all relevant output responses, such as material removal rate (MRR), electrode wear rate (EWR), machining time (Tm), surface roughness (Ra), and base radius. Previous studies have concentrated on one or two output responses. To optimize MRR, EWR, Tm, Ra, and base radius, the experiments were carefully planned using design of experiment (DOE) and response Surface methodology (RSM). Regression analysis and ANOVA are two statistical techniques that were used with Minitab 15 to help interpret experimental data and build a solid regression model specifically for Ti6Al4V. Throughout the experiment, a variety of input factor settings were employed, and the responses to those were noted. The following parameters were used to obtain the experimental data: current (LV) at 30 and 50 A, voltage (HV) at 0.3 and 0.7 V, pulse on time (Ton) at 4 and 6.5 µs, and pulse off time (Toff) at 5.5 and 6.5 µs. Ton and current are the most significant variables that influence most of the output responses. By addressing the simultaneous optimization of multiple output responses, this investigative study not only sets a new standard in the field but also identifies current bottlenecks and offers solutions.



    Special polynomials, generating functions, and the trigonometric functions are used not only in mathematics but also in many branches of science such as statistics, mathematical physics, and engineering.

    Let N,Z,R and C indicate the set of positive integers, the set of integers, the set of real numbers, and the set of complex numbers, respectively. Let αN0=N{0} and λC (or R).

    The Apostol-Bernoulli polynomials B(α)n(x;λ) of order α are defined by means of the following exponential generating function (see [1,2,3]):

    n=0B(α)n(x;λ)tnn!=(tλet1)αext, (1.1)
    (λC; |t|<2π, when λ=1; and |t|<|logλ|, when λ1). (1.2)

    Note that B(α)n(x;1)=B(α)n(x) denote the Bernoulli polynomials of order α and B(α)n(0;λ)=B(α)n(λ) denote the Apostol-Bernoulli numbers of order α, respectively. Setting α=1 into (1.1), we get B(1)n(λ)=Bn(λ) which are the so-called Apostol-Bernoulli numbers.

    The Apostol-Euler polynomials E(α)n(x;λ) of order α are defined by means of the following exponential generating function (see [4,5]):

    n=0E(α)n(x;λ)tnn!=(2λet+1)αext, (1.3)
    (|t|<π when λ=1; |t|<|log(λ)| when λ1;1α:=1). (1.4)

    By virtue of (1.3), we have E(α)n(x;1)=E(α)n(x) denote the Euler polynomials of order α and E(α)n(0;λ)=E(α)n(λ) denote the Apostol-Euler numbers of order α, respectively. Setting α=1 into (1.3), we get E(1)n(λ)=En(λ) which are the so-called Apostol-Euler numbers.

    The Apostol-Genocchi polynomials G(α)n(x;λ) of order α are defined by means of the following exponential generating function (see [6]):

    n=0G(α)n(x;λ)tnn!=(2tλet+1)αext, (1.5)
    (|t|<π when λ=1; |t|<|log(λ)| when λ1;1α:=1). (1.6)

    By virtue of (1.5), we have G(α)n(x;1)=G(α)n(x) denote the Genocchi polynomials of order α and G(α)n(0;λ)=G(α)n(λ) denote the Apostol-Genocchi numbers of order α, respectively. Setting α=1 into (1.5), we get G(1)n(λ)=Gn(λ) which are the so-called Apostol-Genocchi numbers.

    In recent years, many generalizations of these polynomials have been studied by mathematicians. See for example [7,8,9,10,11,12,13,14,15,16,17,18,19,20]. With the aid of these polynomials two parametric kinds of Apostol-Bernoulli, Apostol-Euler and Apostol-Genocchi of order α defined by Srivastava et al. [15,19] whose generating functions are given by

    n=0B(c,α)n(x,y;λ)tnn!=(tλet1)αextcos(yt), (1.7)
    n=0B(s,α)n(x,y;λ)tnn!=(tλet1)αextsin(yt), (1.8)

    and

    n=0E(c,α)n(x,y;λ)tnn!=(2λet+1)αextcos(yt), (1.9)
    n=0E(s,α)n(x,y;λ)tnn!=(2λet+1)αextsin(yt), (1.10)

    and

    n=0G(c,α)n(x,y;λ)tnn!=(2tλet+1)αextcos(yt), (1.11)
    n=0G(s,α)n(x,y;λ)tnn!=(2tλet+1)αextsin(yt). (1.12)

    Remark 1.1. Note that the symbols c and s occurring in the superscripts on the left-hand sides of these last Eqs (1.7)–(1.12) indicate the presence of the trigonometric cosine and the trigonometric sine functions, respectively, in the generating functions on the corresponding right-hand sides.

    The motivation of this paper is to obtain F-analogues of the Eqs (1.7)–(1.12) with the help of the Golden calculus. Namely, we define the parametric Apostol Bernoulli-Fibonacci, the Apostol Euler-Fibonacci, and the Apostol Genocchi-Fibonacci polynomials by means of the Golden Calculus. Utilizing the Golden-Euler formula and these generating functions with their functional equations, numerous properties of these polynomials are given. The special cases of these polynomials and numbers are studied in detail. The rest of this paper is structured as follows. In Section 2, we present some key definitions and properties that are crucial to Golden calculus. Then, with the help of the Golden calculus, we mention some polynomials that have been previously defined in the literature. In Section 3, considering the properties of Golden calculus, we introduce six families of two-parameter polynomials with the help of Golden trigonometric functions and exponential functions. Then, in the three subsections of this section, we examine the various properties of these polynomials defined with the help of generating functions and their functional equations.

    In this part of the our paper, we mention some definitions and properties related to Golden calculus (or F-calculus).

    The Fibonacci sequence is defined by means of the following recurrence relation:

    Fn=Fn1+Fn2,  n2

    where F0=0, F1=1. Fibonacci numbers can be expressed explicitly as

    Fn=αnβnαβ,

    where α=1+52 and β=152. α1,6180339 is called Golden ratio. The golden ratio is frequently used in many branches of science as well as mathematics. Interestingly, this mysterious number also appears in architecture and art. Miscellaneous properties of Golden calculus have been defined and studied in detail by Pashaev and Nalci [21]. Therefore, [21] is the key reference for Golden calculus. In addition readers can also refer to Pashaev [22], Krot [23], and Ozvatan [24].

    The product of Fibonacci numbers, called F-factorial was defined as follows:

    F1F2F3Fn=Fn!, (2.1)

    where F0!=1. The binomial theorem for the F-analogues (or-Golden binomial theorem) are given by

    (x+y)nF=nk=0(1)(k2)(nk)Fxnkyk, (2.2)

    in terms of the Golden binomial coefficients, called as Fibonomials

    (nk)F=Fn!Fnk!Fk!

    with n and k being nonnegative integers, nk. Golden binomial coefficients (or-Fibonomial coefficients) satisfy the following identities as follows:

    (nk)F=βk(n1k)F+αnk(n1k1)F,

    and

    (nk)F=αk(n1k)F+βnk(n1k1)F.

    The Golden derivative defined as follows:

    FFx(f(x))=f(αx)f(xα)(α(1α))x=f(αx)f(βx)(αβ)x. (2.3)

    The Golden Leibnitz rule and the Golden derivative of the quotient of f(x) and g(x) can be given as

    FFx(f(x)g(x))=FFxf(x)g(αx)+f(xα)FFxg(x),
    FFx(f(x)g(x))=FFxf(x)g(αx)FFxg(x)f(αx)g(αx)g(xα),

    respectively. The first and second type of Golden exponential functions are defined as

    exF=n=0(x)nFFn!, (2.4)

    and

    ExF=n=0(1)(n2)(x)nFFn!. (2.5)

    Briefly, we use the following notations throughout the paper

    exF=n=0xnFn!, (2.6)

    and

    ExF=n=0(1)(n2)xnFn!. (2.7)

    Using the Eqs (2.2), (2.4), and (2.5), the following equation can be given

    exFEyF=e(x+y)FF. (2.8)

    The Fibonacci cosine and sine (Golden trigonometric functions) are defined by the power series as

    cosF(x)=n=0(1)nx2nF2n!, (2.9)

    and

    sinF(x)=n=0(1)nx2n+1F2n+1!. (2.10)

    For arbitrary number k, Golden derivatives of ekxF, EkxF, cosF(kx), and sinF(kx) functions are

    FFx(ekxF)=kekxF, (2.11)
    FFx(EkxF)=kEkxF, (2.12)
    FFx(cosF(kx))=ksinF(kx), (2.13)

    and

    FFx(sinF(x))=kcosF(kx). (2.14)

    Using (2.4), Pashaev and Ozvatan [25] defined the Bernoulli-Fibonacci polynomials and related numbers. After that Kus et al. [26] introduced the Euler-Fibonacci numbers and polynomials. Moreover they gave some identities and matrix representations for Bernoulli-Fibonacci polynomials and Euler-Fibonacci polynomials. Very recently, Tuglu and Ercan [27] (also, [28]) defined the generalized Bernoulli-Fibonacci polynomials and generalized Euler-Fibonacci polynomials, namely, they studied the Apostol Bernoulli-Fibonacci and Apostol Euler-Fibonacci of order α as follows:

    (tλetF1)αextF=n=0Bαn,F(x;λ)tnFn!,

    and

    (2λetF+1)αextF=n=0Eαn,F(x;λ)tnFn!.

    Krot [23] defined the fibonomial convolution of two sequences as follows. Let an and bn are two sequences with the following generating functions

    AF(t)=n=0antnFn! and BF(t)=n=0bntnFn!,

    then their fibonomial convolution is defined as

    cn=anbn=nl=0(nk)Falbnl.

    So, the generating function takes the form

    CF(t)=AF(t)BF(t)=n=0cntnFn!.

    Let p,qR. The Taylor series of the functions eptFcosF(qt) and eptFsinF(qt) can be express as follows:

    eptFcosF(qt)=n=0Cn,F(p,q)tnFn!, (3.1)

    and

    eptFsinF(qt)=n=0Sn,F(p,q)tnFn!, (3.2)

    where

    Cn,F(p,q)=n2k=0(1)k(n2k)F pn2kq2k, (3.3)
    Sn,F(p,q)=n12k=0(1)k(n2k+1)F pn2k1q2k+1. (3.4)

    By virtue of above definitions of Cn,F(p,q) and Sn,F(p,q) and the numbers B(α)n,F(λ), E(α)n,F(λ) and G(α)n,F(λ), we can define two parametric types of the Apostol Bernoulli-Fibonacci polynomials, the Apostol Euler-Fibonacci polynomials, and the Apostol Genocchi-Fibonacci polynomials of order α, as follows:

    B(c,α)n,F(p,q;λ)=B(α)n,F(λ)Cn,F(p,q),
    B(s,α)n,F(p,q;λ)=B(α)n,F(λ)Sn,F(p,q),
    E(c,α)n,F(p,q;λ)=E(α)n,F(λ)Cn,F(p,q),
    E(s,α)n,F(p,q;λ)=E(α)n,F(λ)Sn,F(p,q),
    G(c,α)n,F(p,q;λ)=G(α)n,F(λ)Cn,F(p,q),
    G(s,α)n,F(p,q;λ)=G(α)n,F(λ)Sn,F(p,q),

    whose exponential generating functions are given, respectively, by

    (tλetF1)αeptFcosF(qt)=n=0B(c,α)n,F(p,q;λ)tnFn!, (3.5)
    (tλetF1)αeptFsinF(qt)=n=0B(s,α)n,F(p,q;λ)tnFn!, (3.6)
    (2λetF+1)αeptFcosF(qt)=n=0E(c,α)n,F(p,q;λ)tnFn!, (3.7)
    (2λetF+1)αeptFsinF(qt)=n=0E(s,α)n,F(p,q;λ)tnFn!, (3.8)
    (2tλetF+1)αeptFcosF(qt)=n=0G(c,α)n,F(p,q;λ)tnFn!, (3.9)
    (2tλetF+1)αeptFsinF(qt)=n=0G(s,α)n,F(p,q;λ)tnFn!. (3.10)

    Remark 3.1. By virtue of (3.5) and (3.6), when λ1, B(c,α)0,F(p,q;λ)=0 and when λ=1, B(c,α)0,F(p,q;1)=1. Moreover for λC, B(s,α)0,F(p,q;λ)=0.

    Remark 3.2. By virtue of (3.7), when λ=1, E(c,α)0,F(p,q;1) is undefined and when λ1, E(c,α)0,F(p,q;λ)=(2λ+1)α. Also, from (3.8), when λ1, E(s,α)0,F(p,q;λ)=0. For λ=1, E(s,α)0,F(p,q;1) is determined according to the values of α.

    Remark 3.3. By virtue of (3.9) and (3.10), when λ1, G(c,α)0,F(p,q;λ)=0 and λ=1, G(c,α)0,F(p,q;1)=(2)α. Moreover for λC, G(s,α)0,F(p,q;λ)=0.

    Remark 3.4. If we take α=1 and q=0 in (3.5), (3.7), and (3.9), we get Apostol Bernoulli-Fibonacci polynomials, Apostol Euler-Fibonacci polynomials, and Apostol Genocchi-Fibonacci polynomials

    teptFλetF1=n=0Bn,F(p;λ)tnFn!, (3.11)
    2eptFλetF+1=n=0En,F(p;λ)tnFn!, (3.12)
    2teptFλetF+1=n=0Gn,F(p;λ)tnFn!, (3.13)

    respectively. If we take p=0 in (3.11)–(3.13), we obtain Apostol Bernoulli-Fibonacci numbers Bn,F(λ), Apostol Euler-Fibonacci numbers En,F(λ), and Apostol Genocchi-Fibonacci numbers Gn,F(λ).

    Theorem 3.1. The following identities hold true:

    B(c,α)n,F(p+r,q;λ)=nk=0(1)(nk2)(nk)FB(c,α)k,F(p,q;λ)rnk, (3.14)

    and

    B(s,α)n,F(p+r,q;λ)=nk=0(1)(nk2)(nk)FB(s,α)k,F(p,q;λ)rnk. (3.15)

    Proof. By applying (3.5), we first derive the following functional equation:

    n=0B(c,α)n,F(p+r,q;λ)tnFn!=(tλetF1)αe(p+r)FtFcosF(qt)=(tλetF1)αeptFcosF(qt)ErtF,

    which readily yields

    n=0B(c,α)n,F(p+r,q;λ)tnFn!=(n=0B(c,α)n,F(p,q;λ)tnFn!)(n=0(1)(n2)(rt)nFn!)=n=0(nk=0(1)(nk2)(nk)FB(c,α)k,F(p,q;λ)rnk)tnFn!.

    Comparing the coefficients of tn on both sides of this last equation, we have

    B(c,α)n,F(p+r,q;λ)=nk=0(1)(nk2)(nk)FB(c,α)k,F(p,q;λ)rnk,

    which proves the result (3.14). The assertion (3.15) can be proved similarly.

    Remark 3.5. We claim that

    B(c,α)n,F(p+1,q;λ)B(c,α)n,F(p,q;λ)=n1k=0(1)(nk2)(nk)FB(c,α)k,F(p,q;λ),

    and

    B(s,α)n,F(p+1,q;λ)B(s,α)n,F(p,q;λ)=n1k=0(1)(nk2)(nk)FB(s,α)k,F(p,q;λ).

    Theorem 3.2. For every nN, following identities hold true:

    FFp{B(c,α)n,F(p,q;λ)}=FnB(c,α)n1,F(p,q;λ), (3.16)
    FFp{B(s,α)n,F(p,q;λ)}=FnB(s,α)n1,F(p,q;λ), (3.17)
    FFq{B(c,α)n,F(p,q;λ)}=FnB(s,α)n1,F(p,q;λ), (3.18)

    and

    FFq{B(s,α)n,F(p,q;λ)}=FnB(c,α)n1,F(p,q;λ). (3.19)

    Proof. Using (3.5) and applying the Golden derivative operator FFp, we obtain

    n=0FFp{B(c,α)n,F(p,q;λ)}tnFn!=FFp{(tλetF1)αeptF}cosF(qt)=t(tλetF1)αeptFcosF(qt)=n=0B(c,α)n,F(p,q;λ)tn+1Fn!=n=1B(c,α)n1,F(p,q;λ)tnFn1!.

    By comparing the coefficients of tn on both sides of this last equation, we arrive at the desired result (3.16). To prove (3.18), using (3.5) and applying the Golden derivative operator FFq, we find that

    n=0FFq{B(c,α)n,F(p,q;λ)}tnFn!=FFq{(tλetF1)αeptFcosF(qt)}=FFq{cosF(qt)}(tλetF1)αeptF=tsinF(qt)(tλetF1)αeptF=n=1B(s,α)n1,F(p,q;λ)tnFn1!.

    Comparing the coefficients of tn on both sides of this last equation, we arrive at the desired result (3.18). Equations (3.17) and (3.19) can be similarly derived.

    Theorem 3.3. The following identities hold true:

    B(c,1)n,F(p,q;λ)=nk=0(nk)FBk,F(λ)Cnk(p,q), (3.20)

    and

    B(s,1)n,F(p,q;λ)=nk=0(nk)FBk,F(λ)Snk(p,q). (3.21)

    Proof. Setting α=1 in (3.5) and using (3.1), we find that

    n=0B(c,1)n,F(p,q;λ)tnFn!=tλetF1eptFcosF(qt)=(n=0Bn,F(p;λ)tnFn!)(n=0Cn,F(p,q)tnFn!)=n=0(nk=0(nk)FBk,F(λ)Cnk(p,q))tnFn!.

    Comparing the coefficients of tn on both sides of this last equation, we arrive at the desired result (3.20). Equation (3.21) can be similarly derived.

    Theorem 3.4. The following identities hold true:

    B(c,1)n,F(p,q;λ)=n2k=0(1)kq2k(n2k)FBn2k,F(p;λ), (3.22)

    and

    B(s,1)n,F(p,q;λ)=n12k=0(1)kq2k+1(n2k+1)FBn2k1,F(p;λ). (3.23)

    Proof. Setting α=1 in (3.5) and using (2.9), we find that

    n=0B(c,1)n,F(p,q;λ)tnFn!=tλetF1eptFcosF(qt)=(n=0Bn,F(p;λ)tnFn!)(n=0(1)nq2nt2nF2n!)=n=0(n2k=0(1)kq2k(n2k)FBn2k,F(p;λ))tnFn!.

    Comparing the coefficients of tn on both sides of this last equation, we arrive at the desired result (3.22). Equation (3.23) can be similarly derived.

    Theorem 3.5. The following identities hold true:

    Cn,F(p,q)=λnk=01Fk+1(nk)FB(c,1)nk,F(p,q;λ)+(λ1)Fn+1B(c,1)n+1,F(p,q;λ), (3.24)

    and

    Sn,F(p,q)=λnk=01Fk+1(nk)FB(s,1)nk,F(p,q;λ)+(λ1)Fn+1B(s,1)n+1,F(p,q;λ). (3.25)

    Proof. Using the following equation for the proof of (3.24), we have

    eptFcosF(qt)=λetF1ttλetF1eptFcosF(qt)n=0Cn,F(p,q)tnFn!=(λn=0tn1Fn!1t)(n=0B(c,1)n,F(p,q;λ)tnFn!)=(λn=1tn1Fn!+λ1t)(n=0B(c,1)n,F(p,q;λ)tnFn!).

    Considering B(c,1)0,F(p,q;λ)=0, and doing some calculations, we arrive at the desired result (3.24). Equation (3.25) can be similarly derived.

    Theorem 3.6. The following identities hold true:

    B(c,1)n,F(p,q;λ)=nk=0pk(nk)FB(c,1)nk,F(q;λ), (3.26)

    and

    B(s,1)n,F(p,q;λ)=nk=0pk(nk)FB(s,1)nk,F(q;λ). (3.27)

    Proof. By applying (3.5), we have

    n=0B(c,1)n,F(p,q;λ)tnFn!=tλetF1eptFcosF(qt)=(n=0B(c,1)n,F(q;λ)tnFn!)(n=0pntnFn!)=n=0(nk=0pk(nk)FB(c,1)nk,F(q;λ))tnFn!.

    Comparing the coefficients of tn on both sides of this last equation, we arrive at the desired result (3.26). Equation (3.27) can be similarly derived.

    Theorem 3.7. Determinantal forms of the cosine and sine Apostol Bernoulli-Fibonacci polynomials are given by

    B(c,1)n+1,F(p,q;λ)=1(λ1)n+2|Fn+1Cn,F(p,q)λFn+1λFn+1(n1)Fλ(nn)FFnCn1,F(p,q)λ1λFn(n10)Fλ(n1n1)FFn1Cn2,F(p,q)0λ1λ(n2n2)FF0C1,F(p,q)00λ1|,

    and

    B(s,1)n+1,F(p,q;λ)=1(λ1)n+2|Fn+1Sn,F(p,q)λFn+1λFn+1(n1)Fλ(nn)FFnSn1,F(p,q)λ1λFn(n10)Fλ(n1n1)FFn1Sn2,F(p,q)0λ1λ(n2n2)FF0S1,F(p,q)00λ1|.

    Proof. Equation (3.24) cause the system of unknown (n+2)-equations with B(c,1)n,F(p,q;λ), (n=0,1,2,). Then we apply the Cramer's rule to solve this equation. We obtain the desired result. In a similar way, we can obtain the determinantal form for sine Apostol Bernoulli-Fibonacci polynomials.

    In subsections 3.2 and 3.3, we give the some basic properties of the polynomials E(c,α)n,F(p,q;λ), E(s,α)n,F(p,q;λ), G(c,α)n,F(p,q;λ), and G(s,α)n,F(p,q;λ). Their proofs run parallel to those of the results presented in this subsection; so, the proofs are omitted.

    Theorem 3.8. The following identities hold:

    E(c,α)n,F(p+r,q;λ)=nk=0(1)(nk2)(nk)FE(c,α)k,F(p,q;λ)rnk

    and

    E(s,α)n,F(p+r,q;λ)=nk=0(1)(nk2)(nk)FE(s,α)k,F(p,q;λ)rnk.

    Remark 3.6. We claim that

    E(c,α)n,F(p+1,q;λ)E(c,α)n,F(p,q;λ)=n1k=0(1)(nk2)(nk)FE(c,α)k,F(p,q;λ),
    E(s,α)n,F(p+1,q;λ)E(s,α)n,F(p,q;λ)=n1k=0(1)(nk2)(nk)FE(s,α)k,F(p,q;λ).

    Theorem 3.9. For every nN, following identities hold true:

    FFp{E(c,α)n,F(p,q;λ)}=FnE(c,α)n1,F(p,q;λ),
    FFp{E(s,α)n,F(p,q;λ)}=FnE(s,α)n1,F(p,q;λ),
    FFq{E(c,α)n,F(p,q;λ)}=FnE(s,α)n1,F(p,q;λ),

    and

    FFq{E(s,α)n,F(p,q;λ)}=FnE(c,α)n1,F(p,q;λ).

    Theorem 3.10. The following identities hold true:

    E(c,1)n,F(p,q;λ)=nk=0(nk)FEk,F(λ)Cnk(p,q),

    and

    E(s,1)n,F(p,q;λ)=nk=0(nk)FEk,F(λ)Snk(p,q).

    Theorem 3.11. The following identities hold true:

    E(c,1)n,F(p,q;λ)=n2k=0(1)kq2k(n2k)FEn2k,F(p;λ),

    and

    E(s,1)n,F(p,q;λ)=n12k=0(1)kq2k+1(n2k+1)FEn2k1,F(p;λ).

    Theorem 3.12. The following identities hold true:

    Cn,F(p,q)=12E(c,1)n,F(p,q;λ)+λ2nk=0(nk)FE(c,1)nk,F(p,q;λ),

    and

    Sn,F(p,q)=12E(s,1)n,F(p,q;λ)+λ2nk=0(nk)FE(s,1)nk,F(p,q;λ).

    Theorem 3.13. The following identities hold true:

    E(c,1)n,F(p,q;λ)=nk=0pk(nk)FE(c,1)nk,F(q;λ),

    and

    E(s,1)n,F(p,q;λ)=nk=0pk(nk)FE(s,1)nk,F(q;λ).

    Theorem 3.14. Determinantal forms of the cosine and sine Apostol Euler-Fibonacci polynomials are given by

    E(c,1)n,F(p,q;λ)=(2λ+1)n+1|Cn,F(p,q)λ2(n1)Fλ2(n2)Fλ2(nn)FCn1,F(p,q)λ+12λ2(n11)Fλ2(n1n1)FCn2,F(p,q)0λ+12λ2(n2n2)FC0,F(p,q)00λ+12|,

    and

    E(s,1)n,F(p,q;λ)=(2λ+1)n+1|Sn,F(p,q)λ2(n1)Fλ2(n2)Fλ2(nn)FSn1,F(p,q)λ+12λ2(n11)Fλ2(n1n1)FSn2,F(p,q)0λ+12λ2(n2n2)FS0,F(p,q)00λ+12|.

    Theorem 3.15. The following identities hold true:

    G(c,α)n,F(p+r,q;λ)=nk=0(1)(nk2)(nk)FG(c,α)k,F(p,q;λ)rnk,

    and

    G(s,α)n,F(p+r,q;λ)=nk=0(1)(nk2)(nk)FG(s,α)k,F(p,q;λ)rnk.

    Remark 3.7. We claim that

    G(c,α)n,F(p+1,q;λ)G(c,α)n,F(p,q;λ)=n1k=0(1)(nk2)(nk)FG(c,α)k,F(p,q;λ),
    G(s,α)n,F(p+1,q;λ)G(s,α)n,F(p,q;λ)=n1k=0(1)(nk2)(nk)FG(s,α)k,F(p,q;λ).

    Theorem 3.16. For every nN, following identities hold true:

    FFp{G(c,α)n,F(p,q;λ)}=FnG(c,α)n1,F(p,q;λ),
    FFp{G(s,α)n,F(p,q;λ)}=FnG(s,α)n1,F(p,q;λ),
    FFq{G(c,α)n,F(p,q;λ)}=FnG(s,α)n1,F(p,q;λ),

    and

    FFq{G(s,α)n,F(p,q;λ)}=FnG(c,α)n1,F(p,q;λ).

    Theorem 3.17. The following identities hold true:

    G(c,1)n,F(p,q;λ)=nk=0(nk)FGk(λ)Cnk(p,q),

    and

    G(s,1)n,F(p,q;λ)=nk=0(nk)FGk,F(λ)Snk(p,q).

    Theorem 3.18. The following identities hold true:

    G(c,1)n,F(p,q;λ)=n2k=0(1)kq2k(n2k)FGn2k,F(p;λ),

    and

    G(s,1)n,F(p,q;λ)=n12k=0(1)kq2k+1(n2k+1)FGn2k1,F(p;λ).

    Theorem 3.19. The following identities hold true:

    Cn,F(p,q)=λ2nk=01Fk+1(nk)FG(c,1)nk,F(p,q;λ)+λ+12Fn+1G(c,1)n+1,F(p,q;λ),

    and

    Sn,F(p,q)=λ2nk=01Fk+1(nk)FG(s,1)nk,F(p,q;λ)+λ+12Fn+1G(s,1)n+1,F(p,q;λ).

    Theorem 3.20. The following identities hold true:

    G(c,1)n,F(p,q;λ)=nk=0pk(nk)FG(c,1)nk,F(q;λ),

    and

    G(s,1)n,F(p,q;λ)=nk=0pk(nk)FG(s,1)nk,F(q;λ).

    Theorem 3.21. Determinantal forms of the cosine and sine Apostol Genocchi-Fibonacci polynomials are given by

    G(c,1)n+1,F(p,q;λ)=(2λ+1)n+2|Fn+1Cn,F(p,q)λ2Fn+1(n0)Fλ2Fn+1(n1)Fλ2(nn)FFnCn1,F(p,q)λ+12λ2Fn(n10)Fλ2(n1n1)FFn1Cn2,F(p,q)0λ+12λ2(n2n2)F000λ+12|,

    and

    G(s,1)n+1,F(p,q;λ)=(2λ+1)n+2|Fn+1Sn,F(p,q)λ2Fn+1(n0)Fλ2Fn+1(n1)Fλ2(nn)FFnSn1,F(p,q)λ+12λ2Fn(n10)Fλ2(n1n1)FFn1Sn2,F(p,q)0λ+12λ2(n2n2)F000λ+12|.

    Our aim in this article is to define the F-analogues of the parametric types of the Apostol Bernoulli, the Apostol Euler, and the Apostol Genocchi polynomials studied by Srivastava et al. [15,19]. Namely, we have defined parametric types of the Apostol Bernoulli-Fibonacci, the Apostol Euler-Fibonacci, and the Apostol Genocchi-Fibonacci polynomials using the Golden calculus and investigated their properties. In our future work, we plan to define the parametric types of some special polynomials with the help of Golden calculus and to obtain many combinatorial identities with the help of their generating functions.

    All authors declare no conflicts of interest in this paper.



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