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Research article Special Issues

Optimization of intelligent compaction based on finite element simulation and nonlinear multiple regression


  • In intelligent compaction, a critical issue is determining the combination of construction parameters (e.g., the rolling speed and the number of passes) for achieving optimal compaction results. In this paper, a finite element model was developed based on the Mohr-Coulomb elasto-plastic model to simulate the field compaction process of subgrade, which was validated by field compaction tests. Nonlinear multiple regression was used to match the impacts of construction factors on compaction quality based on the model simulation. Then, the linear search approach was used to find the ideal combination of construction parameters that optimizes the compaction quality. The findings indicated that the ideal combination of construction parameters for reaching the ideal compaction degree is a rolling speed of 1.3 m/s with 4 roller passes.

    Citation: Chengyong Chen, Fagang Chang, Li Li, Wenqiang Dou, Changjing Xu. Optimization of intelligent compaction based on finite element simulation and nonlinear multiple regression[J]. Electronic Research Archive, 2023, 31(5): 2775-2792. doi: 10.3934/era.2023140

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  • In intelligent compaction, a critical issue is determining the combination of construction parameters (e.g., the rolling speed and the number of passes) for achieving optimal compaction results. In this paper, a finite element model was developed based on the Mohr-Coulomb elasto-plastic model to simulate the field compaction process of subgrade, which was validated by field compaction tests. Nonlinear multiple regression was used to match the impacts of construction factors on compaction quality based on the model simulation. Then, the linear search approach was used to find the ideal combination of construction parameters that optimizes the compaction quality. The findings indicated that the ideal combination of construction parameters for reaching the ideal compaction degree is a rolling speed of 1.3 m/s with 4 roller passes.



    Quantum calculus or briefly q-calculus is a study of calculus without limits. Post-quantum or (p,q)-calculus is a generalization of q-calculus and it is the next step ahead of the q-calculus. Quantum Calculus is considered an incorporative subject between mathematics and physics, and many researchers have a particular interest in this subject. Quantum calculus has many applications in various mathematical fields such as orthogonal polynomials, combinatorics, hypergeometric functions, number theory and theory of differential equations etc. Many scholars researching in the field of inequalities have started to take interest in quantum calculus during the recent years and the active readers are referred to the articles [2,3,7,8,9,11,12,16,17,21,24,25,27,28,29] and the references cited in them for more information on this topic. The authors explore various integral inequalities in all of the papers mentioned above by using q-calculus and (p,q)-calculus for certain classes of convex functions.

    In this paper, the main motivation is to study trapezoid type (p,q)-integral inequalities for convex and quasi-convex functions. In fact, we prove that the assumption of the differentiability of the mapping in the (p,q) -Hermite-Hadamard type integral inequalities given in [12] can be eliminated. The relaxation of the differentiability of the mapping in the (p,q)-Hermite-Hadamard type integral inequalities proved in [12] also indicates the originality of results established in our research and these findings have some relationships with those results proved in earlier works.

    The basic concepts and findings which will be used in order to prove our results are addressed in this section.

    Let IR be an interval of the set of real numbers. A function f:IR is called as a convex on I, if the inequality

    f(tx+(1t)y)tf(x)+(1t)f(y)

    holds for every x,yI and t[0,1].

    A f:IR known to be a quasi-convex function, if the inequality

    f(tx+(1t)y)sup{f(x),f(y)}

    holds for every x,yI and t[0,1].

    The following properties of convex functions are very useful to obtain our results.

    Definition 2.1. [19] A function f defined on I has a support at x0I if there exists an affine function A(x)=f(x0)+m(xx0) such that A(x)f(x) for all xI. The graph of the support function A is called a line of support for f at x0.

    Theorem 2.1. [19] A function f:(a,b)R is a convex function if and only if there is at least one line of support for f at each x0(a,b).

    Theorem 2.2. [4] If f:[a,b]R is a convex function, then f is continuous on (a,b).

    Perhaps the most famous integral inequalities for convex functions are known as Hermite-Hadamard inequalities and are expressed as follows:

    f(a+b2)1babaf(t)dtf(a)+f(b)2, (2.1)

    where the function f:IR is convex and a,bI with a<b.

    By using the following identity, Pearce and Pečarić proved trapezoid type inequalities related to the convex functions in [18] and [6]. Some trapezoid type inequalities related to quasi-convex functions are proved in [1] and [9].

    Lemma 2.3. [6] Let f:IRR be a differentiable mapping on I (I is the interior of I), a,bI with a<b. If fL[a,b], then the following equality holds:

    f(a)+f(b)21babaf(t)dt=ba210(12t)f(ta+(1t)b)dt. (2.2)

    Some definitions and results for (p,q)-differentiation and (p,q)-integration of the function f:[a,b]R in the papers [12,22,23].

    Definition 2.2. Let f:[a,b]R be a continuous function and 0<q<p1, then (p,q)-derivative of f at t[a,b] is characterized by the expression

    aDp,qf(t)=f(pt+(1p)a)f(qt+(1q)a)(pq)(ta), ta. (2.3)

    The function f is said to be (p,q)-differentiable on [a,b], if aDp,qf(t) exists for all t[a,b]. It should be noted that

    aDp,qf(a)=limtaaDp,qf(t).

    It is clear that if p=1 in (2.3), then

    aDqf(t)=f(t)f(qt+(1q)a)(1q)(ta), ta.aDqf(a)=limtaaDqf(t) (2.4)

    the q-derivative of the function f defined on [a,b] (see [16,21,25,26]).

    Remark 2.1. If one takes a=0 in (2.3), then 0Dp,qf(t)=Dp,qf(t), where Dp,qf(t) is the (p,q)-derivative of f at t[0,b] (see [5,10,20]) defined by the expression

    Dp,qf(t)=f(pt)f(qt)(pq)t, t0. (2.5)

    Remark 2.2. If for a=0 and p=1 in (2.3), then 0Dqf(x)=Dqf(t), where Dqf(t) is the q-derivative of f at t[0,b] (see [15]) given by the expression

    Dqf(t)=f(t)f(qt)(1q)t, t0. (2.6)

    Definition 2.3. Let f:[a,b]R be a continuous function and 0<q<p1. The definite (p,q)-integral of the function f on [a,b] is defined as

    baf(t)adp,qt=(pq)(ba)n=0qnpn+1f(qnpn+1b+(1qnpn+1)a) (2.7)

    If c(a,b), then the definite (p,q)-integral of the function f on [c,b] is defined as

    bcf(t)adp,qt=baf(t)adp,qtcaf(t)adp,qt. (2.8)

    Remark 2.3. Let p=1 be in (2.7), then

    baf(t)adqt=(1q)(ba)n=0qnf(qnb+(1qn)a) (2.9)

    the definite q-integral of the function f defined on [a,b] (see [16,21,25,26]).

    Remark 2.4. Suppose that a=0 in (2.7), then

    b0f(t)0dp,qt=b0f(t)dp,qt=(pq)bn=0qnpn+1f(qnpn+1b) (2.10)

    the definite (p,q)-integral of f on [0,b] (see [20,22,23]). We notice that for a=0 and p=1 in (2.7), then

    b0f(t)0dqt=b0f(t)dqt=(1q)bn=0qnf(qnb) (2.11)

    is the definite q-integral of f over the interval [0,b] (see [15]).

    Remark 2.5. When we take a=0 and p=1, then the existing definitions in the literature are obtained, hence the Definition 2.2 and Definition 2.3 are well defined.

    Quantum trapezoid type inequalities are obtained by Noor et al.[16] and Sudsutad [21] by applying the definition convex and quasi-convex functions on the absolute values of the q-derivative over the finite interval of the set of real numbers.

    Lemma 2.4. Let f:[a,b]RR be a continuous function and 0<q<1. If aDqf is a q-integrable function on (a,b), then the equality holds:

    1babaf(t)adqtqf(a)+f(b)1+q=q(ba)1+q10(1(1+q)t)aDqf(tb+(1t)b)0dqt. (2.12)

    The (p,q)-Hermite-Hadamard type inequalities were proved in [12].

    Theorem 2.5. Let f:[a,b]R be a convex differentiable function on [a,b] and 0<q<p1. Then we have

    f(qa+pbp+q)1p(ba)pb+(1p)aaf(x)adp,qxqf(a)+pf(b)p+q. (2.13)

    In this paper, we remove the (p,q)-differentiability assumption of the function f in Theorem 2.5 and establish (p,q)-analog of the Lemma 2.4 and Lemma 2.3. We obtain (p,q)-analog of the trapezoid type integral inequalities by applying the established identity, which generalize the inequalities given in [1,6,9,16,18,21].

    Throughout this section let IR be an interval, a,bI (I is the interior of I) with a<b (in other words [a,b]I) and 0<q<p1 are constants. Let us start proving the inequalities (2.13), with the lighter conditions for the function f.

    Theorem 3.1. Let f:IR be a convex function on I and a,bI with a<b, then the following inequalities hold:

    f(qa+pbp+q)1p(ba)pb+(1p)aaf(x)adp,qxqf(a)+pf(b)p+q. (3.1)

    Proof. Since f is convex function on the interval I, by Theorem 2.2 f is continuous on I and [a,b]I, the function  f is continuous on [a,b]. By using Theorem 2.1, there is at least one line of support for f at each x0(a,b). Since x0=qa+pbp+q(a,b), using Definition 2.1

    A(x)=f(qa+pbp+q)+m(xqa+pbp+q)f(x) (3.2)

    For all x[a,b] and some m[f(qa+pbp+q),f+(qa+pbp+q)]. In the proof of the Theorem 2.5 the authors used the tangent line at the point of x0=qa+pbp+q. Similarly, using the inequality (3.2) and a similar method with the proof of the Theorem 2.5 we have (3.1) but we omit the details. Thus the proof is accomplished.

    We will use the following identity to prove trapezoid type (p,q)-integral inequalities for convex and quasi-convex functions.

    Lemma 3.2. Let f:IRR be a continuous function on I and a,bI with a<b. If aDp,qf is continuous on [a,b], then the equality:

    1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q=q(ba)p+q10(1(p+q)t)aDp,qf(tb+(1t)a)0dp,qt (3.3)

    holds.

    Proof. Since f is continuous on I and a,bI, the function f is continuous on [a,b]. Hence, clearly a<pb+(1p)ab for 0<p1 and [a,pb+(1p)a][a,b]. Hence f is continuous on [a,pb+(1p)a] and hence according to the condition of the Definition 2.3, the function f is (p,q)-integrable on [a,pb+(1p)a]. This means that the (p,q)-integral

    pb+(1p)aaf(x)adp,qx

    is well defined and exists.

    Since f is continuous on [a,b]. Hence from Definition 2.2, f is (p,q)-differentiable on [a,b]. Thus the (p,q)-derivative of f given by the expression

    aDp,qf(tb+(1t)a)=[f(p[tb+(1t)a]+(1p)a)f(q[tb+(1t)a]+(1q)a)](pq)[tb+(1t)aa]=f(ptb+(1pt)a)f(qtb+(1qt)a)t(pq)(ba)t0 (3.4)

    is well defined and exists.

    Since (1(p+q)t) is continuous on [0,1] and aDp,qf is continuous on [a,b], then

    (1(p+q)t)aDp,qf(tb+(1t)a)

    is continuous on [0,1] and from Definition 2.3. Thus (1(p+q)t)aDp,qf(tb+(1t)a) is (p,q)-integrable on [0,1] and the (p,q)-integral

    10(1(p+q)t)aDp,qf(tb+(1t)a)0dp,qt

    is well defined and exists.

    By using (2.7) and (3.4), we get

    q(ba)p+q10(1(p+q)t)aDp,qf(tb+(1t)a)0dp,qt
    =q(ba)p+q10(1(p+q)t)f(ptb+(1pt)a)f(qtb+(1qt)a)t(pq)(ba)0dp,qt
    =qp+q[1(pq)10f(ptb+(1pt)a)f(qtb+(1qt)a)t0dp,qt
    (p+q)(pq)10f(ptb+(1pt)a)f(qtb+(1qt)a)0dp,qt]
    =q(p+q)(pq)[10f(ptb+(1pt)a)t0dp,qt10f(qtb+(1qt)a)t0dp,qt(p+q)10f(ptb+(1pt)a)0dp,qt+(p+q)10f(qtb+(1qt)a)0dp,qt]
    =q(p+q)[n=0f(qnpnb+(1qnpn)a)n=0f(qn+1pn+1b+(1qn+1pn+1)a)(p+q)n=0qnpn+1f(qnpnb+(1qnpn)a)+(p+q)n=0qnpn+1f(qn+1pn+1b+(1qn+1pn+1)a)]
    =q(p+q)[f(b)f(a)(p+q)pn=0qnpnf(qnpnb+(1qnpn)a)+(p+q)qn=0qn+1pn+1f(qn+1pn+1b+(1qn+1pn+1)a)]
    =q(p+q)[f(b)f(a)(p+q)qf(b)(p+q)pn=0qnpnf(qnpnb+(1qnpn)a)
    +(p+q)qn=1qn+1pn+1f(qn+1pn+1b+(1qn+1pn+1)a)]
    =q(p+q)[f(a)pqf(b)(p+q)pn=0qnpnf(qnpnb+(1qnpn)a)+(p+q)qn=0qnpnf(qnpnb+(1qnpn)a)]
    =q(p+q)[f(a)pqf(b)((p+q)p(p+q)q)n=0qnpnf(qnpnb+(1qnpn)a)]
    =q(p+q)[f(a)pqf(b)((p+q)p(p+q)q)1(pq)(ba)pb+(1p)aaf(x)adp,qx]
    =1p(bq)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q.

    This completes the proof.

    Remark 3.1. The subsequent observations are important to note from the result of Lemma 3.2:

    1. If p=1, we recapture Lemma 2.4,

    2. If p=1 and q1, we recapture Lemma 2.3.

    We can now prove some quantum estimates of (p,q)-trapezoidal integral inequalities by using convexity and quasi-convexity of the absolute values of the (p,q)-derivatives.

    Theorem 3.3. Let f:IRR be a continuous function on I and a,bI with a<b such that aDp,qf is continuous on [a,b] and 0<q<p1. If |aDp,qf|r is a convex function on [a,b] for r1, then

    |1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q| (3.5)
    q(ba)p+q[2(p+q1)(p+q)2]11r[γ1(p,q)|aDp,qf(b)|r+γ2(p,q)|aDp,qf(a)|r]1r

    holds, where

    γ1(p,q)=q[(p32+2p)+(2p2+2)q+pq2]+2p22p(p+q)3(p2+pq+q2)

    and

    γ2(p,q)=q[(5p34p22p+2)+(6p24p2)q+(5p2)q2+2q3]+(2p42p32p2+2p)(p+q)3(p2+pq+q2).

    Proof. Taking absolute value on both sides of (3.3), applying the power-mean inequality and by using the convexity of |aDp,qf|r for r1, we obtain

    |1p(ba)pb+(1p)aaf(x) adp,qxpf(b)+qf(a)p+q| (3.6)
    q(ba)p+q10|1(p+q)t||aDp,qf(tb+(1t)a)|0dp,qt
    q(ba)p+q(10|1(p+q)t|0dp,qt)11r(10|1(p+q)t||aDp,qf(tb+(1t)a)|r0dp,qt)1r
    q(ba)p+q(10|1(p+q)t|0dp,qt)11r
    ×[|aDp,qf(b)|r10t|1(p+q)t|0dp,qt+|aDp,qf(a)|r10(1t)|1(p+q)t|0dp,qt]1r.

    We evaluate the definite (p,q)-integrals as follows

    10|1(p+q)t|0dp,qt=1p+q0(1(p+q)t)0dp,qt11p+q(1(p+q)t)0dp,qt (3.7)
    =21p+q0(1(p+q)t)0dp,qt10(1(p+q)t)0dp,qt=2(p+q1)(p+q)2,
    10t|1(p+q)t|0dp,qt=21p+q0t(1(p+q)t) 0dp,qt10t(1(p+q)t)0dp,qt (3.8)
    =2p2+2pq+2q22p2q(p+q)3(p2+pq+q2)pq(p+q)(p2+pq+q2)
    =p3q+2p2q2+pq3+2p2+2pq+2q22p2q(p+q)3(p2+pq+q2)
    =q[(p32+2p)+(2p2+2)q+pq2]+2p22p(p+q)3(p2+pq+q2)=γ1(p,q)

    and

    10(1t)|1(p+q)t|0dp,qt=10|1(p+q)t|0dp,qt10t|1(p+q)t|0dp,qt (3.9)
    =2(p+q1)(p+q)2[p3q+2p2q2+pq3+2p2+2pq+2q22p2q](p+q)3(p2+pq+q2)
    =q[(5p34p22p+2)+(6p24p2)q+(5p2)q2+2q3]+(2p42p32p2+2p)(p+q)3(p2+pq+q2)
    =γ2(p,q).

    Making use of (3.7), (3.8) and (3.9) in (3.6), gives us the desired result (3.5). The proof is thus accomplished.

    Corollary 3.1. We can get the following subsequent results from (3.5) proved in Theorem 3.3:

    (1). Suppose p=1 and r=1, then we acquire the inequality proved in [21,Theorem 4.1] (see also [13,inequality (5)]):

    |1(ba)baf(x)adqxqf(a)+f(b)1+q| (3.10)
    q2(ba)(1+q)4(1+q+q2)[[1+4q+q2]|aDqf(b)|+[1+3q2+2q3]|aDqf(a)|].

    (2). Letting p=1, provides the inequality established in [16,Theorem 3.2] (see also [14], [21,Theorem 4.2] and [13]):

    |1(ba)baf(x)adqxqf(a)+f(b)1+q|q(ba)1+q[2q(1+q)2]11r (3.11)
    ×[q[1+4q+q2](1+q)3(1+q+q2)|aDqf(b)|r+q[1+3q2+2q3](1+q)3(1+q+q2)|aDqf(a)|r]1r.

    (3). Taking p=1 and letting q1, gives the inequality proved in [18,Theorem 1]:

    |1(ba)baf(x)dxf(a)+f(b)2|(ba)4[|f(a)|r+|f(b)|r2]1r. (3.12)

    (4). Suppose r=1, p=1 and letting q1, we obtain the inequality proved in [6,Theorem 2.2]:

    |1(ba)baf(x)dxf(a)+f(b)2|(ba)[|f(a)|+|f(b)|]8. (3.13)

    Theorem 3.4. Let f:IRR be a continuous function on I and a,bI with a<b. If aDp,qf is continuous on [a,b], 0<q<p1 and|aDp,qf|r is a convex function on [a,b] for r>1, then

    |1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q| (3.14)
    q(ba)p+q[γ3(p,q;s)]1s(|aDp,qf(b)|r+(p+q1)|aDp,qf(a)|rp+q)1r,

    where

    γ3(p,q;s)=10|1(p+q)t|s0dp,qt

    and 1r+1s=1.

    Proof. Taking absolute value on both sides of (3.3), applying the Hölder inequality and using the convexity of |aDp,qf|r for r>1, we get

    |1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q| (3.15)
    q(ba)p+q(10|1(p+q)t|s0dp,qt)1s
    ×[|aDp,qf(b)|r10t0dp,qt+|aDp,qf(a)|r10(1t)0dp,qt]1r
    =q(ba)p+q(γ3(p,q;s))1s[|aDp,qf(b)|r10t0dp,qt+|aDp,qf(a)|r10(1t)0dp,qt]1r.

    We evaluate the definite (p,q)-integrals as follows

    10t 0dp,qt=1p+q

    and

    10(1t) 0dp,qt=p+q1p+q.

    By using the values of the above definite (p,q)-integrals in (3.15), we get what is required.

    Corollary 3.2. In Theorem 3.4;

    (1). If we take p=1, then

    |1(ba)baf(x)adqxqf(a)+f(b)1+q| (3.16)
    q(ba)1+q[γ3(1,q;s)]1s(|aDqf(b)|r+q|aDqf(a)|r1+q)1r.

    (2). If we take p=1 and letting q1, then

    |1(ba)baf(x)dxf(a)+f(b)2|(ba)2(s+1)1s[|f(a)|r+|f(b)|r2]1r. (3.17)

    Remark 3.5. The inequality (3.17) has been established in [6,Theorem 2.3].

    Theorem 3.5. Let f:IRR be a continuous function on I and a,bI with a<b. Suppose that aDp,qf is continuous on [a,b], 0<q<p1 and |aDp,qf|r is a convex function on [a,b] for r>1, then

    |1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q| (3.18)
    q(ba)p+q[2(p+q1)(p+q)2]1s[γ1(p,q)|aDp,qf(b)|r+γ2(p,q)|aDp,qf(a)|r]1r,

    where γ1(p,q), γ2(p,q) are defined as in Theorem 3.3 and 1r+1s=1.

    Proof. Taking absolute value on both sides of (3.3), applying the Hölder inequality and using the convexity of |aDp,qf|r for r>1, we have that

    |1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q| (3.19)
    =q(ba)p+q|10(1(p+q)t)aDp,qf(tb+(1t)a)0dp,qt|
    =q(ba)p+q|10(1(p+q)t)1s(1(p+q)t)1raDp,qf(tb+(1t)a)0dp,qt|
    q(ba)p+q[10|1(p+q)t|0dp,qt]1s[10|1(p+q)t||aDp,qf(tb+(1t)a)|r0dp,qt]1r
    q(ba)p+q[10|1(p+q)t|0dp,qt]1s
    ×[|aDp,qf(b)|r10t|1(p+q)t|0dp,qt+|aDp,qf(a)|r10(1t)|1(p+q)t|0dp,qt]1r.

    Making use of (3.7), (3.8) and (3.9) in (3.19), gives us the desired result (3.18). The proof is thus accomplished.

    Corollary 3.3. The following results are the consequences of Theorem 3.5:

    (1). Taking p=1, we obtain the inequality proved in [16,Theorem 3.3] (see also [14,inequality (8)]):

    |1(ba)baf(x)adqxqf(a)+f(b)1+q|q(ba)1+q[2q(1+q)2]1s (3.20)
    ×[q[1+4q+q2](1+q)3(1+q+q2)|aDqf(b)|r+q[1+3q2+2q3](1+q)3(1+q+q2)|aDqf(a)|r]1r,

    (2). Taking p=1 and letting q1, we obtain the inequality proved in [18,Theorem 1]:

    |1(ba)baf(x)dxf(a)+f(b)2|(ba)2s+1[|f(b)|r+|f(a)|r4]1r. (3.21)

    Some results related for quasi-convexity are presented in the following theorems.

    Theorem 3.6. Let f:IRR be a continuous function on I and a,bI with a<b. If aDp,qf is continuous on [a,b], where 0<q<p1 and |aDp,qf|r is a quasi-convex function on [a,b] r1, then

    |1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q| (3.22)
    q(ba)p+q[2(p+q1)(p+q)2]sup{|aDp,qf(a)|,|aDp,qf(b)|}.

    Proof. Taking absolute value on both sides of (3.3), applying the power mean inequality and using the quasi-convexity of |aDp,qf|r on [a,b] for r1, we have that

    |1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q|
    q(ba)p+q10|1(p+q)t||aDp,qf(tb+(1t)a)|0dp,qt
    q(ba)p+q(10|1(p+q)t|0dp,qt)11r
    ×(10|1(p+q)t| 0dp,qtsup{|aDp,qf(a)|r,|aDp,qf(b)|r})1r
    =q(ba)p+q(10|1(p+q)t|0dp,qt)sup{|aDp,qf(a)|,|aDp,qf(b)|}.

    From (3.7), we have

    10|1(p+q)t|0dp,qt=2(p+q1)(p+q)2.

    Hence the inequality (3.22) is established.

    Corollary 3.4. In Theorem 3.6

    (1). If we let p=1, then:

    |1(ba)baf(x)adqxqf(a)+f(b)1+q| (3.23)
    q(ba)1+q[2q(1+q)2]sup{|aDqf(a)|,|aDqf(b)|}.

    (2). If we take p=1 and letting q1, then:

    |1(ba)baf(x)dxf(a)+f(b)2|(ba)4sup{|f(a)|,|f(b)|}. (3.24)

    Remark 3.3. From the results of Corollary 4, we can observe the following consequences

    (1). The result of the inequality (3.23) has also been obtained in [16,Theorem 3.4] (see also [14,inequality (9)]),

    (2). The result of the inequality (3.24) was established in [1,Theorem 6] and [9,Theorem 1].

    Theorem 3.7. Let f:IRR be a continuous function on I and a,bI with a<b. If aDp,qf is continuous on [a,b], where 0<q<p1 and |aDp,qf|r is a quasi-convex function on [a,b] for r>1, then:

    |1p(ba)pb+(1p)aaf(x)adp,qxpf(b)+qf(a)p+q| (3.25)
    q(ba)p+q[γ3(p,q;s)]1s(sup{|aDp,qf(a)|,|aDp,qf(b)|}),

    where γ3(p,q;s) is as defined in Theorem 3.4 and 1r+1s=1.

    Proof. Taking absolute value on both sides of (3.3), applying the Hölder inequality and using the quasi-convexity of |aDp,qf|r on [a,b] for r>1, we have that

    |1p(ba)pb+(1p)aaf(x) adp,qxpf(b)+qf(a)p+q|
    q(ba)p+q10|1(p+q)t||aDp,qf(tb+(1t)a)|0dp,qt
    q(ba)p+q[10|1(p+q)t|s0dp,qt]1s
    ×[10|aDp,qf(tb+(1t)a)|r0dp,qt]1r
    q(ba)p+q[10|1(p+q)t|s0dp,qt]1ssup{|aDp,qf(b)|,|aDp,qf(a)|}.
    =q(ba)p+q[γ3(p,q;s)]1s(sup{|aDp,qf(a)|,|aDp,qf(b)|})

    The inequality (3.25) is proved.

    Corollary 3.5. In Theorem 3.7;

    (1). If p=1, then we obtain the inequality proved in [9,Theorem 2]:

    |1(ba)baf(x)adqxqf(a)+f(b)1+q|q(ba)1+q[γ3(1,q;s)]1s(sup{|aDqf(a)|,|aDqf(b)|}), (3.26)

    (2). If p=1 and letting q1, then:

    |1(ba)baf(x)dxf(a)+f(b)2|(ba)2(s+1)1ssup{|f(a)|,|f(b)|}. (3.27)

    The authors would like to thank the referee for his/her careful reading of the manuscript and for making valuable suggestions.

    The authors declare to have no conflict of interest.



    [1] P. Vennapusa, D. White, S. Schram, Roller-integrated compaction monitoring for hot-mix asphalt overlay construction, J. Transp. Eng., 139 (2013), 1164–1173. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000602 doi: 10.1061/(ASCE)TE.1943-5436.0000602
    [2] T. Chen, T. Ma, X. Huang, S. Ma, S. Wu, Microstructure of synthetic composite interfaces and verification of mixing order in cold-recycled asphalt emulsion mixture, J. Clean. Prod., 263 (2020), 121467. https://doi.org/10.1016/j.jclepro.2020.121467 doi: 10.1016/j.jclepro.2020.121467
    [3] J. Zhu, T. Ma, J. Fan, Z. Fang, T. Chen, Y. Zhou, Experimental study of high modulus asphalt mixture containing reclaimed asphalt pavement, J. Clean. Prod., 263 (2020), 121447. https://doi.org/10.1016/j.jclepro.2020.121447 doi: 10.1016/j.jclepro.2020.121447
    [4] Y. Ma, F. Chen, T. Ma, X. Huang, Y. Zhang, Intelligent compaction: An improved quality monitoring and control of asphalt pavement construction technology, IEEE T. Intell. Transp., 23 (2022), 14875–14822. https://doi.org/10.1109/TITS.2021.3134699 doi: 10.1109/TITS.2021.3134699
    [5] Q. Xu, G. Chang, Evaluation of intelligent compaction for asphalt materials, Autom. Constr., 30 (2013), 104–112. https://doi.org/10.1016/j.autcon.2012.11.015 doi: 10.1016/j.autcon.2012.11.015
    [6] Q. Xu, G. Chang, V. Gallivan, Development of a systematic method for intelligent compaction data analysis and management, Constr. Build. Mater., 37 (2012), 470–480. https://doi.org/10.1016/j.conbuildmat.2012.08.001 doi: 10.1016/j.conbuildmat.2012.08.001
    [7] X. Zhao, Study on Intelligent Compaction Control Technology of Subgrade, M.S. thesis, Chang'an University in Xi'an, 2016. https://doi.org/10710-2013521093
    [8] B. Chen, Research on Real-time Detection System of Subgrade Compaction Degree, M.S. thesis, Chang'an University in Xi'an, 2019. https://doi.org/10710-2016125023
    [9] R. Minchin, H. Thomas, Validation of vibration-based onboard asphalt density measuring system, J. Constr. Eng. M., 129 (2003), 1–7. https://doi.org/10.1061/(ASCE)0733-9364(2003)129:1(1) doi: 10.1061/(ASCE)0733-9364(2003)129:1(1)
    [10] H. Zhao, Study on the Evaluation Index of Roadbed Compaction Quality, M.S. thesis, Chang'an University in Xi'an, 2015. https://doi.org/10710-2013225045
    [11] Editorial Department of China Journal of Highway and Transport, Review on China's Pavement Engineering Research·2020, China J. Highw. Transp., 33 (2020), 1–66. https://doi.org/10.19721/j.cnki.1001-7372.2020.10.001
    [12] H. Cui, Based on Intelligent Compaction Technology of Filling Roadbed Compaction Degree Test Research, M.S. thesis, Hebei University in Shijiazhuang, 2017. https://doi.org/10075-20151780
    [13] F. Hao, Finite Element Analysis of "Vibration Wheel-Soil" Model, M.S. thesis, Chang'an University in Xi'an, 2007. https://doi.org/10710-20040455
    [14] Z. Wu, S. Zhang, L. Guo, Application of ABAQUS secondary development in rock breaking simulation of PDC cutter, J. Xi'an Shiyou Univ., 35 (2020), 104–109. https://doi.org/10.3969/j.issn.1673-064X.2020.01.015 doi: 10.3969/j.issn.1673-064X.2020.01.015
    [15] D. Liu, M. Lin, S. Li, Real-time quality monitoring and control of highway compaction, Autom. Constr., 62 (2016), 114–123. https://doi.org/10.3876 /j.issn.1000-1980.2018.04.005 doi: 10.3876/j.issn.1000-1980.2018.04.005
    [16] Q. Zhang, T. Liu, Z. Zhang, Z. Huangfu, Q. Li, Z. An, Unmanned rolling compaction system for rockfill materials, Autom. Constr., 100 (2019), 103–117. https://doi.org/10.1016/j.autcon.2019.01.004 doi: 10.1016/j.autcon.2019.01.004
    [17] Z. Wu, S. Zhang, L. Guo, W. Wang, Y. Pan, Application of ABAQUS secondary development in rock breaking simulation of PDC cutter, J. Xi'an Shiyou Univ., 35 (2020), 104–109. https://doi.org/10.3969/j.issn.1673-064X.2020.01.015 doi: 10.3969/j.issn.1673-064X.2020.01.015
    [18] F. Chen, C. Wang, W. Li, J. Yang, Application of Abaqus secondary development in shot peening strengthening of aerospace arc-shaped frame, Comp. Aided Eng., 29 (2020), 55–60. https://doi.org/10.13340/j.cae.2020.02.011 doi: 10.13340/j.cae.2020.02.011
    [19] W. Hu, X. Jia, X. Zhu, A. Su, B. Huang, Influence of moisture content on intelligent soil compaction, Autom. Constr., 113 (2020), 103141. https://doi.org/10.1016/j.autcon.2020.103141 doi: 10.1016/j.autcon.2020.103141
    [20] Y. Ma, Y. Luan, W. Zhang, Y. Zhang, Numerical simulation of intelligent compaction for subgrade construction, J. Cent. South Univ., 27 (2020), 2173–2184. https://doi.org/10.1007/s11771-020-4439-2 doi: 10.1007/s11771-020-4439-2
    [21] Y. Ma, Z. Fang, T. Han, S. Wang, B. Li, Dynamic simulation and evolution of key control parameters for intelligent compaction of subgrade, J. Cent. South Univ., 52 (2021), 2246–2257. https://doi.org/10.11817/j.issn.1672-7207.2021.07.012 doi: 10.11817/j.issn.1672-7207.2021.07.012
    [22] Y. Ma, Y. Zhang, W. Zhao, X. Ding, Z. Wang, T. Ma, Assessment of intelligent compaction quality evaluation index and uniformity, J. Transp. Eng. B-Pave., 2 (2022), 04022024. https://doi.org/10.1061/JPEODX.0000368 doi: 10.1061/JPEODX.0000368
    [23] X. Teng, Numerical Analysis and Quality Control of Dynamic Consolidation of Silty Soil Subgrade –in Yellow River Alluvial Plain, M.S. thesis, Shandong University in Jinan, 2017. https://doi.org/10422-201413217
    [24] X. Yan, Some Studies on Functional Linear Regression, Ph.D. thesis, East China Normal University in Shanghai, 2020. https://doi.org/10269-52164404001
    [25] Q. Xu, The Research on Non-Linear Regression Analysis Methods, M.S. thesis, Hefei University of Technology in Hefei, 2009. https://doi.org/10359-0631111370
    [26] D. Zhou, Research on Correlation Optimization of Differential Privacy Regression Analysis Based on Laplace Mechanism, M.S. thesis, Heilongjiang University in Heilongjiang, 2018. https://doi.org/10212-2151237
    [27] D. White, P. Vennapusa, H. Gieselman, Field assess uthorment and specification review for roller-integrated compaction monitoring technologies, Adv. Civ. Eng., 2011, (2011), 1–15. https://doi.org/10.1155/2011/783836 doi: 10.1155/2011/783836
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