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Buzz Wincheski

Bio: Buzz Wincheski is an academic researcher from Langley Research Center. The author has contributed to research in topics: Eddy current & Eddy-current testing. The author has an hindex of 8, co-authored 47 publications receiving 349 citations.

Papers
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Journal ArticleDOI
TL;DR: This paper uses eddy current based techniques and reduced order modeling to explore the feasibility of detecting a subsurface damage in structures such as air foils and pipelines and suggests it can reduce the computational time on average by a factor of 3000.
Abstract: This paper uses eddy current based techniques and reduced order modeling to explore the feasibility of detecting a subsurface damage in structures such as air foils and pipelines. To identify the geometry of a damage, an optimization algorithm is employed which requires solving the forward problem numerous times. To implement these methods in a practical setting, the forward algorithm must be solved with extremely fast and accurate solution methods. Therefore, our computational methods are based on the reduced order Karhunen-Loeve or Proper Orthogonal Decomposition (POD) techniques. For proof-of-concept, we implement the methodology on a 2-D problem and find the methods to be efficient and robust even with data containing 10 Furthermore, the methods are fast; our findings suggest we can reduce the computational time on average by a factor of 3000.

69 citations

Journal ArticleDOI
TL;DR: In this paper, the authors explore the feasibility of detecting such damage by application of an eddy-current-based technique coupled with reduced order modelling, and propose two different algorithms for forming the POD approximations, a reduced order proper orthogonal decomposition (POD/Galerkin) and a POD/interpolation technique.
Abstract: In the field of nondestructive evaluation, new and improved techniques are constantly being sought to facilitate the detection of hidden corrosion and flaws in structures such as aeroplanes and pipelines. In this paper, we explore the feasibility of detecting such damage by application of an eddy-current-based technique coupled with reduced order modelling. We begin by developing a model for a specific eddy current method in which we make some simplifying assumptions reducing the three-dimensional problem to a two-dimensional problem (we do this for proof of concept). Theoretical results are then presented which establish the existence and uniqueness of solutions as well as continuous dependence of the solutions on the parameters which represent the damage. We further discuss theoretical issues concerning the least squares parameter estimation problem used in identifying the geometry of the damage. To solve the identification problem, an optimization algorithm is employed which requires solving the forward problem numerous times. To implement these methods in a practical setting, the forward algorithm must be solved with extremely fast and accurate solution methods. In constructing these computational methods, we employ reduced order proper orthogonal decomposition (POD) techniques. This approach permits one to create a set of basis elements spanning a data set consisting of either numerical simulations or experimental data. We discuss two different algorithms for forming the POD approximations, a POD/Galerkin technique and a POD/interpolation technique. Finally, results of the inverse problem associated with damage detection are given using both simulated data with relative noise added as well as experimental data obtained using a giant magnetoresistive sensor. The experimental results are based on successfully using experimental data to form the POD basis elements (instead of numerical simulations), thus illustrating the effectiveness of this method on a wide range of applications. In both instances the methods are found to be efficient and robust. Moreover, the methods were fast; our findings demonstrate a significant reduction in computational time.

52 citations

Journal ArticleDOI
TL;DR: In this paper, the authors show that exposure of as-produced HiPCo single-walled carbon nanotubes to a camera flash causes ignition, (oxidation) and subsequent coalescence of the Fe catalyst particles, while purified SWNTs do not respond to flashing.
Abstract: The exposure of as-produced HiPCo single-walled carbon nanotubes (SWNTs) to a camera flash causes ignition, (oxidation) and subsequent coalescence of the Fe catalyst particles, while purified SWNTs do not respond to flashing. TEM and electron energy loss spectroscopy (EELS) analysis attribute the phenomena to the pyrophoric oxidation of Fe nanoparticles.

49 citations

Patent
08 Dec 1992
TL;DR: In this paper, a non-contacting vibration apparatus produces resonant vibrations without introducing extraneous noise, which is correlated to known crack length in plates with similar resonant vibration shifts, and acoustic emissions of cracks at resonance frequencies are correlated to acoustic emissions from known crack geometries.
Abstract: A device and method are provided which non-destructively detect crack length and crack geometry in thin metallic plates. A non-contacting vibration apparatus produces resonant vibrations without introducing extraneous noise. Resulting resonant vibration shifts in cracked plates are correlated to known crack length in plates with similar resonant vibration shifts. In addition, acoustic emissions of cracks at resonance frequencies are correlated to acoustic emissions from known crack geometries.

27 citations

Proceedings ArticleDOI
16 Nov 2000
TL;DR: In this paper, a design modification to the very low frequency GMR based self-nulling probe has been presented to enable improved signal to noise ratio for deeply buried flaws, which is capable of clearly identifying flaws up to 1 cm deep in aluminum alloy structures.
Abstract: In this paper a design modification to the Very-Low Frequency GMR Based Self-Nulling Probe has been presented to enable improved signal to noise ratio for deeply buried flaws The design change consists of incorporating a feedback coil in the center of the flux focusing lens The use of the feedback coil enables cancellation of the leakage fields in the center of the probe and biasing of the GMR sensor to a location of high magnetic field sensitivity The effect of the feedback on the probe output was examined, and experimental results for deep flaw detection were presented The experimental results show that the modified probe is capable of clearly identifying flaws up to 1 cm deep in aluminum alloy structures

24 citations


Cited by
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Journal ArticleDOI
TL;DR: Error estimates for Galerkin proper orthogonal decomposition (POD) methods for nonlinear parabolic systems arising in fluid dynamics are proved and the backward Euler scheme is considered.
Abstract: Error estimates for Galerkin proper orthogonal decomposition (POD) methods for nonlinear parabolic systems arising in fluid dynamics are proved For the time integration the backward Euler scheme is considered The asymptotic estimates involve the singular values of the POD snapshot set and the grid-structure of the time discretization as well as the snapshot locations

752 citations

Book ChapterDOI
01 Jan 2005
TL;DR: In this article, the authors consider the problem of nonlinear evolution in real separable Hilbert spaces, where the inner product in V is given by a symmetric bounded, coercive, bilinear form.
Abstract: Nonlinear Dynamical System Let V and H be real separable Hilbert spaces and suppose that V is dense in H with compact embedding. By 〈· , ·〉H we denote the inner product in H. The inner product in V is given by a symmetric bounded, coercive, bilinear form a : V × V → IR: 〈φ,ψ〉V = a(φ,ψ) for all φ,ψ ∈ V (10.16) with associated norm given by ‖ · ‖V = √ a(· , ·). Since V is continuously injected into H, there exists a constant cV > 0 such that ‖φ‖H ≤ cV ‖φ‖V for all φ ∈ V. (10.17) We associate with a the linear operator A: 〈Aφ,ψ〉V ′,V = a(φ,ψ) for all φ,ψ ∈ V, where 〈· , ·〉V ′,V denotes the duality pairing between V and its dual. Then, by the Lax-Milgram lemma, A is an isomorphism from V onto V ′. Alternatively, A can be considered as a linear unbounded self-adjoint operator in H with domain D(A) = {φ ∈ V : Aφ ∈ H}. By identifying H and its dual H ′ it follows that 10 POD: Error Estimates and Suboptimal Control 269 D(A) ↪→ V ↪→ H = H ′ ↪→ V ′, each embedding being continuous and dense, when D(A) is endowed with the graph norm of A. Moreover, let F : V × V → V ′ be a bilinear continuous operator mapping D(A) × D(A) into H. To simplify the notation we set F (φ) = F (φ,φ) for φ ∈ V . For given f ∈ C([0, T ];H) and y0 ∈ V we consider the nonlinear evolution problem d dt 〈y(t), φ〉H + a(y(t), φ) + 〈F (y(t)), φ〉V ′,V = 〈f(t), φ〉H (10.18a) for all φ ∈ V and t ∈ (0, T ] a.e. and y(0) = y0 in H. (10.18b) Assumption (A1). For every f ∈ C([0, T ];H) and y0 ∈ V there exists a unique solution of (10.18) satisfying y ∈ C([0, T ];V ) ∩ L(0, T ;D(A)) ∩H(0, T ;H). (10.19) Computation of the POD Basis Throughout we assume that Assumption (A1) holds and we denote by y the unique solution to (10.18) satisfying (10.19). For given n ∈ IN let 0 = t0 < t1 < . . . < tn ≤ T (10.20) denote a grid in the interval [0, T ] and set δtj = tj − tj−1, j = 1, . . . , n. Define ∆t = max (δt1, . . . , δtn) and δt = min (δt1, . . . , δtn). (10.21) Suppose that the snapshots y(tj) of (10.18) at the given time instances tj , j = 0, . . . , n, are known. We set V = span {y0, . . . , y2n}, where yj = y(tj) for j = 0, . . . , n, yj = ∂ty(tj−n) for j = n + 1, . . . , 2n with ∂ty(tj) = (y(tj)−y(tj−1))/δtj , and refer to V as the ensemble consisting of the snapshots {yj} j=0, at least one of which is assumed to be nonzero. Furthermore, we call {tj}j=0 the snapshot grid. Notice that V ⊂ V by construction. Throughout the remainder of this section we let X denote either the space V or H. 270 Michael Hinze and Stefan Volkwein Remark 10.2.1 (compare [KV01, Remark 1]). It may come as a surprise at first that the finite difference quotients ∂ty(tj) are included into the set V of snapshots. To motivate this choice let us point out that while the finite difference quotients are contained in the span of {yj} j=0, the POD bases differ depending on whether {∂ty(tj)}j=1 are included or not. The linear dependence does not constitute a difficulty for the singular value decomposition which is required to compute the POD basis. In fact, the snapshots themselves can be linearly dependent. The resulting POD basis is, in any case, maximally linearly independent in the sense expressed in (P ) and Proposition 10.2.5. Secondly, in anticipation of the rate of convergence results that will be presented in Section 10.3.3 we note that the time derivative of y in (10.18) must be approximated by the Galerkin POD based scheme. In case the terms {∂ty(tj)}j=1 are included in the snapshot ensemble, we are able to utilize the estimate

294 citations