determining the complex young™s modulus of polymer...

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Determining the Complex Young’s Modulus of Polymer Materials Fabricated with Microstereolithography C. Morris*, J. M. Cormack*, M. F. Hamilton*, M. R. Haberman*, C. C. Seepersad* *Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712 †Applied Research Laboratories, The University of Texas at Austin, Austin, TX 78758 Abstract Microstereolithography is capable of producing millimeter-scale polymer parts having micron-scale features. Material properties of the cured polymers can vary depending on build parameters such as exposure time and laser power. Current techniques for determining the material properties of these polymers are limited to static measurements via micro/nanoindentation, leaving the dynamic response undetermined. Frequency-dependent material parameters, such as the complex Young’s modulus, have been determined for other relaxing materials by measuring the wave speed and attenuation of an ultrasonic pulse traveling through the materials. This method is now applied to determine the frequency-dependent material parameters of polymers manufactured using microstereolithography. Because the ultrasonic wavelength is comparable to the part size, a model that accounts for both geometric and viscoelastic effects is used to determine the material properties using experimental data. Introduction Parts produced by additive manufacturing (AM) are increasingly utilized for applications such as energy absorbing honeycomb structures, prosthetic limbs, and shock isolation systems where the response of the material to dynamic loading must be considered [1, 2, 3]. Due to the geometric design freedom introduced by AM, parts can achieve mechanical performance levels previously unattainable by other manufacturing technologies [4]. Successful prediction of the mechanical performance of parts made from AM processes requires accurate mechanical modeling which, in turn, requires precise knowledge of rate-dependent material properties of the as-built parts. The frequency dependent modulus that relates the stress developed in the material due to a dynamically applied strain is one such property. The material property describing this relationship is known as the dynamic modulus, which is frequency dependent and expressed as a complex quantity that accounts for both storage and loss of mechanical energy. The modulus of low-loss elastic materials like metals is approximately rate independent for most applications, and can therefore be described with static elastic moduli. The static Young’s modulus for the uniaxial loading case is one such property that can be measured through quasi-static tensile or three point bending tests. If the material exhibits viscoelastic behavior, the mathematical description of the frequency dependent storage and loss moduli require a more generalized constitutive model [5], the parameters of which must be obtained experimentally. When a viscoelastic material is dynamically loaded, some of the imparted strain energy is stored elastically within the material while some of the energy is dissipated. The amount of 426 Solid Freeform Fabrication 2017: Proceedings of the 28th Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference

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  • Determining the Complex Young’s Modulus of Polymer Materials Fabricated

    with Microstereolithography

    C. Morris*, J. M. Cormack*†, M. F. Hamilton*†, M. R. Haberman*†, C. C. Seepersad*

    *Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712

    †Applied Research Laboratories, The University of Texas at Austin, Austin, TX 78758

    Abstract

    Microstereolithography is capable of producing millimeter-scale polymer parts having

    micron-scale features. Material properties of the cured polymers can vary depending on build

    parameters such as exposure time and laser power. Current techniques for determining the

    material properties of these polymers are limited to static measurements via

    micro/nanoindentation, leaving the dynamic response undetermined. Frequency-dependent

    material parameters, such as the complex Young’s modulus, have been determined for other

    relaxing materials by measuring the wave speed and attenuation of an ultrasonic pulse traveling

    through the materials. This method is now applied to determine the frequency-dependent

    material parameters of polymers manufactured using microstereolithography. Because the

    ultrasonic wavelength is comparable to the part size, a model that accounts for both geometric

    and viscoelastic effects is used to determine the material properties using experimental data.

    Introduction

    Parts produced by additive manufacturing (AM) are increasingly utilized for applications

    such as energy absorbing honeycomb structures, prosthetic limbs, and shock isolation systems

    where the response of the material to dynamic loading must be considered [1, 2, 3]. Due to the

    geometric design freedom introduced by AM, parts can achieve mechanical performance levels

    previously unattainable by other manufacturing technologies [4]. Successful prediction of the

    mechanical performance of parts made from AM processes requires accurate mechanical

    modeling which, in turn, requires precise knowledge of rate-dependent material properties of the

    as-built parts.

    The frequency dependent modulus that relates the stress developed in the material due to

    a dynamically applied strain is one such property. The material property describing this

    relationship is known as the dynamic modulus, which is frequency dependent and expressed as a

    complex quantity that accounts for both storage and loss of mechanical energy. The modulus of

    low-loss elastic materials like metals is approximately rate independent for most applications,

    and can therefore be described with static elastic moduli. The static Young’s modulus for the

    uniaxial loading case is one such property that can be measured through quasi-static tensile or

    three point bending tests. If the material exhibits viscoelastic behavior, the mathematical

    description of the frequency dependent storage and loss moduli require a more generalized

    constitutive model [5], the parameters of which must be obtained experimentally.

    When a viscoelastic material is dynamically loaded, some of the imparted strain energy is

    stored elastically within the material while some of the energy is dissipated. The amount of

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    Solid Freeform Fabrication 2017: Proceedings of the 28th Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference

  • energy that is stored and dissipated can vary with the frequency of the applied load. A general

    form of the complex modulus, 𝐸(𝜔), that captures this phenomenon is

    𝐸(𝜔) = 𝐸′(𝜔) + 𝑗𝐸′′(𝜔), (1)

    where the real part, 𝐸′(𝜔), is the storage modulus corresponding to the frequency-dependent,

    elastic storage of energy, and the imaginary part 𝐸′′(𝜔) is the loss modulus that accounts for the dissipation of dynamic energy. Both the storage and loss modulus must be determined to obtain

    the dynamic modulus. However, the standard quasi-static test previously mentioned only

    captures the zero frequency component of the storage modulus. In order to obtain the complete

    behavior of the dynamic modulus other testing methods must be explored.

    One such method, ultrasonic characterization, is of particular interest to the additive

    manufacturing community because it is a nondestructive way of measuring dynamic material

    properties over a large range of frequencies. It is well documented that the material properties of

    parts produced via AM can vary across machines, parts, and even different locations of the same

    part [6, 7]. Therefore, a methodology must be developed that can determine material properties

    for individual parts both quickly and effectively; furthermore, to be applicable to a range of

    processes, including microstereolithography, it must be applicable to parts with small

    characteristic dimensions, on the order of millimeters or even smaller. In this paper, an

    experimental approach and analysis procedure is applied to determine the dynamic modulus of

    an additively manufactured part using ultrasonic characterization. The procedure, in general, can

    capture the dynamic modulus for a large range of frequencies, geometries, and part sizes and was

    demonstrated on a rod produced by microstereolithography to determine the dynamic modulus in

    the ultrasonic range of 400 kHz to 1.3 MHz.

    Microstereolithography

    Microstereolithography is an additive manufacturing process based on

    photopolymerization in which a liquid polymer solidifies when exposed to a particular

    wavelength of light. Figure 1 provides a schematic of a typical microstereolithography system

    [8]. The microstereolithography system builds parts layer by layer by activating/deactivating

    each pixel of a Digital Micromirror Device (DMD) so that the correct image is formed when a

    UV light source reflects off the device. Then through a series of optics, the light image is greatly

    reduced in size and focused on the top of a build stage at the surface of a volume of liquid

    photopolymer. A thin layer of the photopolymer solidifies on the build plate that matches the

    light image. Once the layer has solidified the build stage moves downward, the liquid polymer

    flows over the part to form another layer, and the build process is repeated to form the final part.

    Figure 1: Schematic of microstereolithography system [8].

    427

  • The material properties of the final part produced by microstereolithography will vary

    based on several factors including the layer thickness, exposure time, and volume fraction of

    constituents [9, 10]. These parameters can vary from build to build based on desired

    performance. For example, some builds may require a smaller layer thickness for increased part

    resolution. Therefore, a metrology part should be produced for each set of build parameters to

    evaluate the dynamic modulus. When developing the metrology part, the build envelope must be

    considered because it plays a vital role in determining what testing methods can be used. The

    system of interest can produce parts with resolution on the order of tens of microns with overall

    parts sizes of about 2.5mm x 2.5mm x 15mm. The resolution and part size can vary from system

    to system and the system used in this paper at the University of Akron is capable of the

    dimensions previously described. With these geometric constraints, the testing methods to

    consider for determining the dynamic modulus are the Impulse Excitation Technique, Dynamic

    Mechanical Analysis, Nanoindentation, and ultrasonic material characterization.

    Dynamic Modulus Determination

    The Impulse Excitation Technique (IET) determines the dynamic modulus by providing

    an impulsive load to a sample, which excites the material to vibrate at its natural frequencies

    [11]. The quality factor and dynamic modulus can be determined for the material by measuring

    the ringdown response, but only at the natural frequencies of the specimen. To obtain the

    modulus at other frequencies, multiple specimens must be produced, each having different

    geometries that permit the measurement of the dynamic modulus over a wide range of

    frequencies. This is rarely an efficient strategy for characterization over wide frequency ranges.

    Further, measurement accuracy can be negatively impacted since the material properties of

    additively manufactured parts often vary from part to part.

    The Dynamic Mechanical Analyzer (DMA) is a commercially available device that can

    be used to determine the dynamic modulus of viscoelastic materials [12]. The DMA provides a

    time-dependent load to a specimen (usually sinusoidally varying) in a temperature-controlled

    environment and measures the response of the part to the load. The DMA then sweeps through

    various ambient temperatures to obtain the frequency-dependent response of the material at those

    discrete temperatures. The response for all temperature and frequency combinations can then be

    used to determine the dynamic modulus of the material for a wide range of frequencies and

    temperatures using the principle of time-temperature superposition [13]. This range of

    frequencies and temperatures can actually exceed the testable range if the material is

    thermorheologically simple, meaning regardless of the initial stress, the stress relaxation times

    share the same dependence on changes in temperature [14].

    Mixtures of photopolymers and photoinitiators have been shown to be

    thermorheologically complex because they exhibit multiple time-temperature shifts from

    multiple viscoelastic domains [15]. The principle of time-temperature superposition cannot be

    used for these thermorheologically complex materials so the maximum testable frequency of the

    DMA bounds the range of attainable information about the dynamic modulus. For commercially

    available DMAs this maximum testable frequency is around a few hundred hertz [16].

    Furthermore, the DMA requires the specimen to be of a certain geometry to interface with its

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  • fixtures. For certain additive manufacturing methods like microstereolithography, it may be

    prohibitively difficult to produce a part of adequate size to interface with the provided fixtures,

    therefore another testing method is needed to test these parts. It should be noted that Chartrain et

    al. used DMA to determine the effect of temperature on the dynamic modulus of a thin film

    manufactured by microstereolithography [17]. They were able to produce a viable part because

    the build volume of their system was 4mm x 6mm x 35mm which allowed them to produce a

    larger test specimen.

    Another method, closely related to the DMA is the use of a nanoindentor to deform the

    material of interest. Typically, nanoindentation is used to determine the static modulus of

    elasticity, but if the machine is carefully calibrated and a sinusoidal indenting force is applied,

    the response of the material can be used to determine the frequency-dependent dynamic

    modulus. The careful calibration required is an extensive process and, even if carried out to

    ASTM standards, the results can differ when compared to the DMA [18]. Similar to the DMA it

    also has a limited range of frequencies that can be used to determine the dynamic modulus

    limiting the efficacy of the testing.

    A method that allows for a large range of frequencies to be evaluated for parts of various

    sizes is ultrasonic material characterization. Ultrasonic material characterization measures the

    propagation of an input wave pulse in a specimen and relates the response to the material

    properties and geometry through a forward model [19]. The forward model is the cornerstone of

    the method because it predicts wave propagation through a specimen. Forward models, which

    allow the measured response to be inverted to determine material properties, can be constructed

    for simple and complex geometries. Therefore, ultrasonic material characterization was selected

    as the method to determine the dynamic modulus of the metrology part produced using

    microstereolithography.

    Before beginning ultrasonic material characterization, a geometry must be selected for

    the dynamic modulus metrology part. A natural choice for the design is a cylindrical rod due to

    its ability to be produced rapidly by all additive manufacturing technologies. A forward model

    for wave propagation in a cylindrical rod is well known and will be discussed in the next section.

    Ultrasonic Material Characterization

    The simplest definition of ultrasonic material characterization is an experimental method

    that uses measurements of the speed of sound in a specimen paired with a forward model to

    determine the material properties of the specimen. The forward model relates the frequency-

    dependent sound speed to the geometry and frequency-dependent material properties of the

    specimen. Accurate measurement of the sound speed paired with knowledge of specimen

    geometry can therefore be used to infer the material properties via a minimization of the

    difference between the experimental data and forward model predictions as the properties are

    varied [20].

    The simplest example of ultrasonic material characterization is the determination of a

    frequency-independent Young’s modulus of a material by measuring the time-of -flight, or the

    time it takes for a wave to travel from one point of a material to another point, in a lossless

    429

  • material. The sound speed, which is more accurately called the phase speed, 𝑐p, can be

    determined by 𝑐p = 𝑑/𝑡 , where 𝑡 is the time-of-flight and 𝑑 is the distance traveled by the wave.

    The forward model that relates the phase speed and the material properties for longitudinal pulse

    propagation in a thin rod is 𝑐p = √𝐸/𝜌, where E is the Young’s modulus and 𝜌 is the density.

    The previous equation can be inverted to obtain 𝐸 = 𝜌𝑐p2 which allows the Young’s modulus to

    be determined from measurable quantities.

    The use of the time-of-flight method described above determines a single value of the

    phase speed because in that example the Young’s modulus was assumed to be frequency-

    independent. For most geometries and materials this is not necessarily true. If the Young’s

    modulus is frequency-dependent, the phase speed and attenuation, 𝛼, will be dependent on the

    frequency, 𝜔, as well [21] which results in the complex wavenumber:

    𝜉(𝜔) =𝜔

    𝑐p(𝜔)− 𝑗𝛼(𝜔). (2)

    where exp(𝑗𝜔𝑡) time dependence is assumed.

    The complex wavenumber is related to the material properties, frequency, and specimen

    geometry by a dispersion relationship. The dispersion relationship can then be inverted to relate

    the material properties to the phase speed and attenuation. While the dispersion relationship may

    be complicated and contain both real and imaginary components, the methodology for

    determining the material properties is nearly identical to that of the simple time-of-flight

    example illustrated above. First, the frequency-dependent, complex wavenumber is measured

    and the dispersion relationship describing the specimen is obtained. Next, the dispersion

    relationship is inverted to solve for the material properties in terms of the measured wavenumber

    and geometry, allowing for the determination of the dynamic modulus.

    Dispersion in a Solid Rod of Circular Cross-Section

    For the case of axisymmetric longitudinal wave propagation in a viscoelastic rod with

    circular cross-section, the dispersion relationship is governed by two factors: (i) the viscoelastic

    constitutive relationship of the material, and (ii) the geometry of the rod. Pochhammer and Chree

    were the first to independently describe the dispersion relationship for an infinite, elastic

    cylindrical rod, which was later modified by Zhao and Gary to incorporate viscoelasticity [22,

    23, 24]. The dispersion relationship describing axisymmetric longitudinal wave propagation in

    an infinite, viscoelastic, cylindrical rod is

    2𝐴

    𝑟(𝐵2 + 𝜉2)𝐽1(𝐴𝑟)𝐽1(𝐵𝑟) − (𝐵

    2 − 𝜉2)2𝐽0(𝐴𝑟)𝐽1(𝐵𝑟) − 4𝜉2𝐴𝐵𝐽1(𝐴𝑟)𝐽0(𝐵𝑟) = 0, (3)

    where the coefficients 𝐴 and 𝐵 are defined by

    𝐴2 =𝜌𝜔2

    𝐾 +43 𝜇

    − 𝜉2, (4)

    and

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  • 𝐵2 =𝜌𝜔2

    𝜇− 𝜉2. (5)

    In Eq. (3) r is the radius of the rod, 𝐽𝑛(𝑧) is the 𝑛𝑡ℎ order Bessel function of the first kind, K is

    the bulk modulus, and 𝜇 is the shear modulus of the material. The bulk modulus and the shear

    modulus are related to the Young’s modulus by 𝐸 = 9𝐾𝜇/(3𝐾 + 𝜇) [25]. Note for |𝜉𝑟| ≪ 1 and

    as 𝜔 → 0, Eq. (3) reduces to the simple case of longitudinal pulse propagation in a thin rod with

    phase speed 𝑐p = √𝐸/𝜌, as discussed in the previous section.

    In the derivation of Eq. (3) it is assumed that the rod is infinitely long. In practice then,

    the length of the rod, l, must be much larger than the wavelength, λ, where

    λ =2𝜋𝑐p

    𝜔≪ 𝑙. (6)

    Therefore, lower frequency measurements may not be accurately described by Eq. (3), if the

    wavelength is on the order of the rod length. This condition must be considered when

    investigating rods produced by additive manufacturing systems because the build envelope

    determines the maximum rod length. It also should be noted that Eq. (3) cannot be easily

    inverted analytically as in the earlier example so that the material properties are given in terms of

    the frequency, wavenumber, and geometry. A numerical solver must be used to obtain the

    material properties once the other parameters are determined for each frequency. For a given

    frequency, there may be multiple solutions to Eq. (3), each corresponding to different modes of

    wave propagation along the axis of the rod. The existence of multiple modes requires careful

    treatment when measuring the relationship between wavenumber and frequency. Figure 2 shows

    equivalent representations of a dispersion plot for an elastic rod where in Figure 2(a) the

    horizontal axis is the frequency and the vertical axis is the phase speed and for Figure 2(b) the

    horizontal axis is the real component of the wavenumber and the vertical axis is the frequency.

    Figure 2: Plot of the (a) phase speed as a function of frequency and (b) the real component of

    inverse wavelength as a function of frequency when multiple modes are present for r = 1.25 mm,

    E = 4.5 GPa, and ν = 0.375.

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  • As shown in Figure 2, when a cylindrical rod is excited, multiple modes may propagate

    through the rod and appear in the complex wavenumber measurement. The following section

    discusses how this measurement of the complex wavenumber is performed

    Determining Complex Wavenumber

    Determining the complex wavenumber requires measuring both the frequency-dependent

    phase speed and wave attenuation. This is accomplished by measuring ultrasonic wave packets at

    a range of positions as they propagate along the axis of the rod to obtain spatial and temporal

    information about the propagating wave. Performing a two-dimensional (2D) fast Fourier

    transform (FFT), with one dimension being time and the other space, one obtains the complex

    amplitude of the propagating pulses for frequency, wavenumber pairs. The data is easily

    visualized with a surface plot where the horizontal axis is the real component of the

    wavenumber, the vertical axis is the frequency, and the magnitude is the amplitude of the

    transformed signal. This representation is commonly referred to as the dispersion diagram of the

    elastic waveguide. If only axisymmetric modes are present, the amplitude of the surface plot is

    dramatically higher along curves that satisfy the dispersion relationship Eq. (3). The degree of

    agreement between the values calculated with Eq. (3) (the forward model) and the experimental

    data depends primarily on the accuracy of the material properties provided as inputs to the

    forward model. As previously discussed, multiple modes may be present, so filtering of the data

    may be required if one wishes to isolate any specific propagating mode. Once a single mode is

    isolated from the dispersion diagram, the frequency-dependent phase speed for the mode of

    interest can be extracted by determining the real component of the wave number for each

    frequency where the amplitude of the signal is highest. This allows for numerical determination

    of the phase speed.

    With the isolated mode, it is then possible to use the filtered data to determine the

    imaginary component of the wavenumber. An inverse Fourier transform of the filtered data can

    be taken to yield the amplitude of the selected mode in time and space. For each measurement

    separated by a distance Δ𝑥, a FFT can be taken in the time domain. Then the transfer

    function 𝐻(𝜔) between adjacent measurements, �̃�2(𝜔, 𝑥) and �̃�1(𝜔, 𝑥), is defined to be

    𝐻(𝜔) =�̃�2

    �̃�1= 𝑒−𝛼Δ𝑥𝑒

    −𝑗𝜔𝑐𝑝

    Δ𝑥. (7)

    The magnitude of the transfer function and knowledge of distance between measurement

    locations can then be used to determine the attenuation coefficient using the expression

    𝛼 = −1

    Δxln|𝐻(𝜔)|. (8)

    The method described above provides a means to determine the real and imaginary components

    of the complex wavenumber from experimentally obtained data. That information is then used to

    determine the material properties through inversion of the dispersion relationship Eq. (3).

    The complex wavenumber can be constructed at each frequency where attenuation and

    phase speed information is available through Eq. (2). The complex wavenumber and frequency

    432

  • are substituted into the dispersion relationship of Eq. (3) which is then separated into its real and

    imaginary components forming a system of two simultaneous equations. The material properties

    are then determined by obtaining values of the bulk modulus and shear modulus that minimize

    the magnitude of both equations through the use of the fsolve function in MATLAB®. This

    methodology was applied to a rod produced via microstereolithography. The experimental setup

    and results are discussed in the next section.

    Experimental Setup and Results

    An ultrasonic transducer, laser Doppler vibrometer (LDV), and linear stage were used to

    obtain spatial and temporal measurements. Figure 3 presents a schematic of the experimental

    setup where a rod is placed between two ultrasonic transducers and the LDV is positioned so that

    the laser path is perpendicular to the axis of the rod. The rod and transducers are mounted on a

    linear stage that allows the sample to be moved in the axial direction. The transducer transmits a

    broadband ultrasonic pulse that travels axially through the rod. While the pulse propagates

    axially, the surface of the rod contracts and expands radially due to the Poisson effect. The radial

    surface velocity is measured by the LDV. Multiple measurements along the rod axis can be taken

    with the LDV by incrementally moving the rod and transducer setup with the linear stage. This

    generates both spatial and temporal information of ultrasonic wave propagation along the rod.

    Figure 3: Schematic of experimental setup for surface velocity measurement of rod.

    It should be emphasized that this experimental setup has major advantages compared to

    other arrangements that could obtain spatio-temporal data. Two setups will briefly be discussed

    that could be implemented if the LDV were not available, however both methods introduce

    significant errors. In the absence of the LDV, the second ultrasonic transducer serves as a

    receiver for the transmitted signal of the first transducer. In one alternative experimental setup,

    spatio-temporal data could be collected by shortening/cutting the rod incrementally and

    measuring the received pulse for each length. Due to variation in loading conditions, the signal

    transmitted to the receive transducer will vary from measurement to measurement reducing the

    credibility of the results. A second alternative experiment uses a single rod of one length. The

    second transducer measures the first arrival of the wave as well as the second arrival that comes

    after reflection from the exciting transducer. Material properties are obtained through

    comparison of the two signals. The second arrival is due to an impedance mismatch between the

    transducer, coupling gel, and rod at the interface, therefore additional unknowns are introduced

    433

  • to the measurement. Furthermore, if the material attenuates strongly, the signal from the reflected

    signal will be too small to detect. For viscoelastic rods, like the ones selected, the reflected signal

    is far too weak to be measured above the noise level.

    To validate the experimental and inversion approach, measurements were made with a

    material having known dynamic modulus in the ultrasonic range. Tests were therefore performed

    on a 12.7 mm diameter rod of acrylic (PMMA) with a length of 30 mm. The ultrasonic

    transducer was a 1 MHz Olympus V603-RB transducer with a nominal bandwidth of 0.69-1.29

    MHz. The LDV was a Polytec OFV-505, and data was captured using a 60 MHz LeCroy

    WaveAce 102 digital oscilloscope. The linear stage allowed for a spatial resolution of 0.0254

    mm. Spatial and temporal data were collected for the acrylic rod and the results were compared

    to the values previously determined in the literature. The real component of the dynamic

    modulus for acrylic has been shown to be nearly constant in the ultrasonic range with a value of

    4.9 GPa. The imaginary component of the dynamic modulus is approximately linear with

    frequency with a slope of 1.31 dB/cm/MHz [26, 27]. Using these values and a Poisson value of

    0.37, the multimodal, real-valued dispersion curves were generated and overlaid on the results of

    the spectral transform of the LDV data as shown in Fig. 4. There is excellent agreement between

    the experimental results and established values, especially for the first propagating mode.

    Figure 4: Experimental dispersion curves obtained from an acrylic rod (surface) with real

    components of dispersion curves determined from established values (white).

    Following the successful validation of the method with the acrylic rod, a rod was

    produced via microstereolithography with a diameter of 2.47 mm and a length of 15 mm. The

    polymer blend used to produce the rod was CD9021/HDDA (70w/30w), with 1 w% DMPA as

    the photo-initiator, and 0.15 w% Tinuvin 327® as the light absorber. After exciting the rod with

    the ultrasonic transducer, the radial surface velocity at various axial locations on the rod was

    measured with the LDV. A total of 250 measurements were taken at 0.0508 mm increments and

    every tenth result is shown in the waterfall plot of Fig. 5. The horizontal axis is time and the

    vertical axis indicates distance from the first measurement taken. The waterfall plot shows that

    434

  • pulse shape changes drastically as it progresses along the rod due to attenuation and dispersion

    effects in the waveguide.

    Figure 5: Waterfall plot demonstrating propagation of wave through rod.

    The dispersion diagram associated with the data is generated using the 2D FFT as discussed in

    the previous section and the results are shown in Fig. 6.

    Figure 6: Plot of frequency vs wavenumber obtained by 2D FFT of time-space data.

    To generate Fig. 6 a 250-point Hamming window was used in the spatial domain when

    taking the 2D FFT of the time-space data. Figure 6 shows that significant signal is being

    obtained for frequencies as low as 0.15 MHz and as high as 1.6 MHz. The wavelengths at the

    lower frequencies are on the order of the specimen length of 15 mm so the dispersion

    relationship at those frequencies likely does not fit the model of Eq. (3) due to the development

    of standing waves. From Fig. 6 it is also be evident that multiple modes are propagating through

    the rod. For initial analysis of the material properties, only information regarding the first mode

    of propagation is desired. To isolate the first mode, the piecewise, Gaussian filter with a standard

    deviation of 0.15 mm-1 shown in Fig. 7 was applied to the spectral data to obtain Fig. 8.

    435

  • Figure 7: Plot of filter applied to spectral data.

    Figure 8: Filtered plot of frequency vs wavenumber for the first mode.

    With the filtered plot of Fig. 8, the real component of the wave number was obtained by

    selecting the wavenumber at each frequency with the highest signal amplitude. The curve

    depicting these results of the real component of the wavenumber against frequency is shown in

    Fig. 9 as well as the 5th order polynomial fit to the real dispersion curve data with an R2 value of

    0.99. The phase speed is also plotted in Figure 11(a) which was determined from the real part of

    the wavenumber using the relation 𝑐p = 𝜔\Re(𝜉).

    Figure 9: Real component of the wavenumber extracted from the wavenumber-frequency plot

    with regression curve.

    436

  • The filtered spectral data was then inverted with a 2D IFFT to obtain a waterfall plot just

    like that of Fig 5 but with data containing information associated with the first mode contribution

    to the ultrasonic pulse, which is shown in Fig. 10.

    Figure 10: Waterfall plot of the first mode propagation.

    Each spatial measurement in Fig. 10 was then transformed to the temporal frequency domain and

    the transfer function between adjacent spatial measurements was obtained using Eq. (7). Eq. (8)

    was then used to obtain the frequency-dependent attenuation shown in Fig. 11(b). One standard

    deviation of variation is shown to demonstrate the low level of variance in the data.

    Figure 11: Plot of the (a) phase speed as a function of frequency and (b) attenuation as a

    function of frequency.

    437

  • The attenuation of the material is characteristic of a viscoelastic material where the

    attenuation, in general, increases with frequency. With the real and imaginary components of the

    wavenumber determined, the dynamic modulus was determined by inverting the dispersion

    relation Eq. (3) and assuming a Poisson ratio of 0.375. Results are presented in Fig. 12 where the

    variation in the dynamic modulus, plotted in green, is derived from the variation in the

    attenuation and the blue line is determined with the mean attenuation values.

    Figure 12: Plot of the (a) real component of dynamic modulus and (b) imaginary component of

    dynamic modulus.

    The dynamic modulus was obtained for the frequency range of 0.4 MHz to 1.3 MHz

    although there was information outside this range. This range was chosen to match the nominal

    bandwidth of the transducer as well as to ensure the assumptions regarding the dispersion

    relationship were not violated. The values of the moduli are well within reasonable limits as the

    static modulus for both HDDA and CD9021 have been both experimentally determined to be

    around 1 GPa [28, 29].

    To corroborate the value of the storage modulus of 0.59 MPa at 400 kHz that was

    determined through ultrasonic material characterization, a secondary experiment was designed to

    measure the storage modulus at lower frequencies. The experimental setup is shown in Figure 13

    438

  • where the microstereolithography rod was mounted as a cantilever beam and excited by a shaker

    table to measure the resonance frequency.

    Figure 13: Experimental setup showing microstereolithography rod mounted as a cantilever to

    measure the storage modulus at lower frequencies.

    The same LDV used previously measured the velocity at the base of the cantilever beam

    as well as the tip of the cantilever beam while a logarithmically increasing frequency sweep from

    1 Hz to 4500 Hz was performed over 120 s. By computing the transfer function between the top

    velocity and base velocity, shown in Figure 14, the natural frequency of the rod, 𝑓n, was found to be 1.63 kHz.

    Figure 14: Transfer function between the base velocity (measurement location 1 in Fig. 13) and

    tip velocity (measurement location 2 in Fig. 13).

    The storage modulus at the natural frequency was determined to be 0.56 MPa from

    𝐸′ = (2𝜋𝑓n

    3.52)

    2 𝐴𝜌𝑙4

    𝐼, (9)

    where the length of the rod, l, was 12 mm as opposed to the original 15 mm due to the size of the

    clamps, A is the cross-sectional area, and I is the area moment of inertia [30]. The experimentally

    obtained storage modulus at the resonance frequency of this rod (1.63 kHz) is well within the

    range of variance for the storage modulus at 400 kHz. The agreement in values indicates that the

    ultrasonic material characterization method is accurately predicting the storage modulus though

    caution should be used due to the difference in frequency of the corroborating results.

    439

  • Conclusion

    A methodology for determining the dynamic modulus of parts produced by additive

    manufacturing was applied to a rod produced by microstereolithography. By modeling the

    dispersion relationship for the part of interest and then measuring the frequency-dependent

    attenuation and sound speed experimentally, the dynamic modulus was determined. For the

    microstereolithography rod, the dynamic modulus was obtained in the ultrasonic range of 0.4

    MHz -1.3 MHz by utilizing the dispersion relationship for an infinite cylindrical rod. This range

    of frequencies is much larger than that of most methods to determine the dynamic modulus and

    quasi-static modulus like DMA, IET, and nanoindentation.

    Future work will focus on obtaining the dynamic modulus at higher and lower

    frequencies than those already determined. Determination of the modulus at lower frequencies

    while simultaneously obtaining a wide frequency range of dynamic moduli can be accomplished

    by using a longer rod length or different dispersion relationship. To increase the upper limit on

    the frequency range, information regarding higher mode wave propagation can be explored.

    Acknowledgements

    The authors would like to acknowledge support from the National Science Foundation

    under Grant No. CMMI -1435548. We would also like to acknowledge Sumanth Kashyap and

    Dr. Jae-Won Choi from the University of Akron and Dr. Eric MacDonald from Youngstown

    State for their input and production of the microstereolithography rods. Any opinions, findings

    and conclusions or recommendations expressed in this material are those of the authors and do

    not necessarily reflect the views of the sponsor.

    440

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    WelcomeTitle PagePrefaceOrganizing CommitteePapers to JournalsTable of ContentsMaterialsScanning Strategies in Electron Beam Melting to Influence Microstructure DevelopmentRelating Processing of Selective Laser Melted Structures to Their Material and Modal PropertiesThermal Property Measurement Methods and Analysis for Additive Manufacturing Solids and PowdersPrediction of Fatigue Lives in Additively Manufactured Alloys Based on the Crack-Growth ConceptFatigue Behavior of Additive Manufactured Parts in Different Process Chains – An Experimental StudyEffect of Process Parameter Variation on Microstructure and Mechanical Properties of Additively Manufactured Ti-6Al-4VOptimal Process Parameters for In Situ Alloyed Ti15Mo Structures by Laser Powder Bed FusionEfficient Fabrication of Ti6Al4V Alloy by Means of Multi-Laser Beam Selective Laser MeltingEffect of Heat Treatment and Hot Isostatic Pressing on the Morphology and Size of Pores in Additive Manufactured Ti-6Al-4V PartsEffect of Build Orientation on Fatigue Performance of Ti-6Al-4V Parts Fabricated via Laser-Based Powder Bed FusionEffect of Specimen Surface Area Size on Fatigue Strength of Additively Manufactured Ti-6Al-4V PartsSmall-Scale Mechanical Properties of Additively Manufactured Ti-6Al-4VDesign and Fabrication of Functionally Graded Material from Ti to Γ-Tial by Laser Metal DepositionTailoring Commercially Pure Titanium Using Mo₂C during Selective Laser MeltingCharacterization of MAR-M247 Deposits Fabricated through Scanning Laser Epitaxy (SLE)Mechanical Assessment of a LPBF Nickel Superalloy Using the Small Punch Test MethodEffects of Processing Parameters on the Mechanical Properties of CMSX-4® Additively Fabricated through Scanning Laser Epitaxy (SLE)Effect of Heat Treatment on the Microstructures of CMSX-4® Processed through Scanning Laser Epitaxy (SLE)On the Use of X-Ray Computed Tomography for Monitoring the Failure of an Inconel 718 Two-Bar Specimen Manufactured by Laser Powder Bed FusionLaser Powder Bed Fusion Fabrication and Characterization of Crack-Free Aluminum Alloy 6061 Using In-Process Powder Bed Induction HeatingPorosity Development and Cracking Behavior of Al-Zn-Mg-Cu Alloys Fabricated by Selective Laser MeltingEffect of Optimizing Particle Size in Laser Metal Deposition with Blown Pre-Mixed PowdersAluminum Matrix Syntactic Foam Fabricated with Additive ManufacturingBinderless Jetting: Additive Manufacturing of Metal Parts via Jetting NanoparticlesCharacterization of Heat-Affected Powder Generated during the Selective Laser Melting of 304L Stainless Steel PowderEffects of Area Fraction and Part Spacing on Degradation of 304L Stainless Steel Powder in Selective Laser MeltingInfluence of Gage Length on Miniature Tensile Characterization of Powder Bed Fabricated 304L Stainless SteelStudy of Selective Laser Melting for Bonding of 304L Stainless Steel to Grey Cast IronMechanical Performance of Selective Laser Melted 17-4 PH Stainless Steel under Compressive LoadingMicrostructure and Mechanical Properties Comparison of 316L Parts Produced by Different Additive Manufacturing ProcessesA Parametric Study on Grain Structure in Selective Laser Melting Process for Stainless Steel 316L316L Powder Reuse for Metal Additive ManufacturingCompeting Influence of Porosity and Microstructure on the Fatigue Property of Laser Powder Bed Fusion Stainless Steel 316LStudying Chromium and Nickel Equivalency to Identify Viable Additive Manufacturing Stainless Steel ChemistriesInvestigation of the Mechanical Properties on Hybrid Deposition and Micro-Rolling of Bainite SteelProcess – Property Relationships in Additive Manufacturing of Nylon-Fiberglass Composites Using Taguchi Design of ExperimentsDigital Light Processing (DLP): Anisotropic Tensile ConsiderationsDetermining the Complex Young’s Modulus of Polymer Materials Fabricated with MicrostereolithographyEffect of Process Parameters and Shot Peening on Mechanical Behavior of ABS Parts Manufactured by Fused Filament Fabrication (FFF)Expanding Material Property Space Maps with Functionally Graded Materials for Large Scale Additive ManufacturingConsidering Machine- and Process-Specific Influences to Create Custom-Built Specimens for the Fused Deposition Modeling ProcessRheological Evaluation of High Temperature Polymers to Identify Successful Extrusion ParametersA Viscoelastic Model for Evaluating Extrusion-Based Print ConditionsTowards a Robust Production of FFF End-User Parts with Improved Tensile PropertiesInvestigating Material Degradation through the Recycling of PLA in Additively Manufactured PartsEcoprinting: Investigating the Use of 100% Recycled Acrylonitrile Butadiene Styrene (ABS) for Additive ManufacturingMicrowave Measurements of Nylon-12 Powder Ageing for Additive ManufacturingImprovement of Recycle Rate in Laser Sintering by Low Temperature ProcessDevelopment of an Experimental Laser Sintering Machine to Process New Materials like Nylon 6Optimization of Adhesively Joined Laser-Sintered PartsInvestigating the Impact of Functionally Graded Materials on Fatigue Life of Material Jetted SpecimensFabrication and Characterization of Graphite/Nylon 12 Composite via Binder Jetting Additive Manufacturing ProcessFabricating Zirconia Parts with Organic Support Material by the Ceramic On-Demand Extrusion ProcessThe Application of Composite Through-Thickness Assessment to Additively Manufactured StructuresTensile Mechanical Properties of Polypropylene Composites Fabricated by Material ExtrusionPneumatic System Design for Direct Write 3D PrintingCeramic Additive Manufacturing: A Review of Current Status and ChallengesRecapitulation on Laser Melting of Ceramics and Glass-CeramicsA Trade-Off Analysis of Recoating Methods for Vat Photopolymerization of CeramicsAdditive Manufacturing of High-Entropy Alloys – A ReviewMicrostructure and Mechanical Behavior of AlCoCuFeNi High-Entropy Alloy Fabricated by Selective Laser MeltingSelective Laser Melting of AlCu5MnCdVA: Formability, Microstructure and Mechanical PropertiesMicrostructure and Crack Distribution of Fe-Based Amorphous Alloys Manufactured by Selective Laser MeltingConstruction of Metallic Glass Structures by Laser-Foil-Printing TechnologyBuilding Zr-Based Metallic Glass Part on Ti-6Al-4V Substrate by Laser-Foil-Printing Additive ManufacturingOptimising Thermoplastic Polyurethane for Desktop Laser Sintering

    ModelingReal-Time Process Measurement and Feedback Control for Exposure Controlled Projection LithographyOptimization of Build Orientation for Minimum Thermal Distortion in DMLS Metallic Additive ManufacturingUsing Skeletons for Void Filling in Large-Scale Additive ManufacturingImplicit Slicing Method for Additive Manufacturing ProcessesTime-Optimal Scan Path Planning Based on Analysis of Sliced GeometryA Slicer and Simulator for Cooperative 3D PrintingStudy on STL-Based Slicing Process for 3D PrintingORNL Slicer 2: A Novel Approach for Additive Manufacturing Tool Path PlanningComputer Integration for Geometry Generation for Product Optimization with Additive ManufacturingMulti-Level Uncertainty Quantification in Additive ManufacturingComputed Axial Lithography for Rapid Volumetric 3D Additive ManufacturingEfficient Sampling for Design Optimization of an SLS ProductReview of AM Simulation Validation TechniquesGeneration of Deposition Paths and Quadrilateral Meshes in Additive ManufacturingAnalytical and Experimental Characterization of Anisotropic Mechanical Behaviour of Infill Building Strategies for Fused Deposition Modelling ObjectsFlexural Behavior of FDM Parts: Experimental, Analytical and Numerical StudySimulation of Spot Melting Scan Strategy to Predict Columnar to Equiaxed Transition in Metal Additive ManufacturingModelling Nanoparticle Sintering in a Microscale Selective Laser Sintering Process3-Dimensional Cellular Automata Simulation of Grain Structure in Metal Additive Manufacturing ProcessesNumerical Simulation of Solidification in Additive Manufacturing of Ti Alloy by Multi-Phase Field MethodThe Effect of Process Parameters and Mechanical Properties Oof Direct Energy Deposited Stainless Steel 316Thermal Modeling of 304L Stainless Steel Selective Laser MeltingThe Effect of Polymer Melt Rheology on Predicted Die Swell and Fiber Orientation in Fused Filament Fabrication Nozzle FlowSimulation of Planar Deposition Polymer Melt Flow and Fiber Orientaiton in Fused Filament FabricationNumerical Investigation of Stiffness Properties of FDM Parts as a Function of Raster OrientationA Two-Dimensional Simulation of Grain Structure Growth within Substrate and Fusion Zone during Direct Metal DepositionNumerical Simulation of Temperature Fields in Powder Bed Fusion Process by Using Hybrid Heat Source ModelThermal Simulation and Experiment Validation of Cooldown Phase of Selective Laser Sintering (SLS)Numerical Modeling of High Resolution Electrohydrodynamic Jet Printing Using OpenFOAMMesoscopic Multilayer Simulation of Selective Laser Melting ProcessA Study into the Effects of Gas Flow Inlet Design of the Renishaw AM250 Laser Powder Bed Fusion Machine Using Computational ModellingDevelopment of Simulation Tools for Selective Laser Melting Additive ManufacturingMachine Learning Enabled Powder Spreading Process Map for Metal Additive Manufacturing (AM)

    Process DevelopmentMelt Pool Dimension Measurement in Selective Laser Melting Using Thermal ImagingIn-Process Condition Monitoring in Laser Powder Bed Fusion (LPBF)Performance Characterization of Process Monitoring Sensors on the NIST Additive Manufacturing Metrology TestbedMicroheater Array Powder Sintering: A Novel Additive Manufacturing ProcessFabrication and Control of a Microheater Array for Microheater Array Powder SinteringInitial Investigation of Selective Laser Sintering Laser Power vs. Part Porosity Using In-Situ Optical Coherence TomographyThe Effect of Powder on Cooling Rate and Melt Pool Length Measurements Using In Situ Thermographic TecniquesMonitoring of Single-Track Degradation in the Process of Selective Laser MeltingMachine Learning for Defect Detection for PBFAM Using High Resolution Layerwise Imaging Coupled with Post-Build CT ScansSelection and Installation of High Resolution Imaging to Monitor the PBFAM Process, and Synchronization to Post-Build 3D Computed TomographyMultisystem Modeling and Optimization of Solar Sintering SystemContinuous Laser Scan Strategy for Faster Build Speeds in Laser Powder Bed Fusion SystemInfluence of the Ratio between the Translation and Contra-Rotating Coating Mechanism on Different Laser Sintering Materials and Their Packing DensityThermal History Correlation with Mechanical Properties for Polymer Selective Laser Sintering (SLS)Post Processing Treatments on Laser Sintered Nylon 12Development of an Experimental Test Setup for In Situ Strain Evaluation during Selective Laser MeltingIn Situ Melt Pool Monitoring and the Correlation to Part Density of Inconel® 718 for Quality Assurance in Selective Laser MeltingInfluence of Process Time and Geometry on Part Quality of Low Temperature Laser SinteringIncreasing Process Speed in the Laser Melting Process of Ti6Al4V and the Reduction of Pores during Hot Isostatic PressingA Method for Metal AM Support Structure Design to Facilitate RemovalExpert Survey to Understand and Optimize Part Orientation in Direct Metal Laser SinteringFabrication of 3D Multi-Material Parts Using Laser-Based Powder Bed FusionMelt Pool Image Process Acceleration Using General Purpose Computing on Graphics Processing UnitsBlown Powder Laser Cladding with Novel Processing Parameters for Isotropic Material PropertiesThe Effect of Arc-Based Direct Metal Energy Deposition on PBF Maraging SteelFiber-Fed Laser-Heated Process for Printing Transparent GlassReducing Mechanical Anisotropy in Extrusion-Based Printed PartsExploring the Manufacturability and Resistivity of Conductive Filament Used in Material Extrusion Additive ManufacturingActive - Z Printing: A New Approach to Increasing 3D Printed Part StrengthA Mobile 3D Printer for Cooperative 3D PrintingA Floor Power Module for Cooperative 3D PrintingChanging Print Resolution on BAAM via Selectable NozzlesPredicting Sharkskin Instability in Extrusion Additive Manufacturing of Reinforced ThermoplasticsDesign of a Desktop Wire-Feed Prototyping MachineProcess Modeling and In-Situ Monitoring of Photopolymerization for Exposure Controlled Projection Lithography (ECPL)Effect of Constrained Surface Texturing on Separation Force in Projection StereolithographyModeling of Low One-Photon Polymerization for 3D Printing of UV-Curable SiliconesEffect of Process Parameters and Shot Peening on the Tensile Strength and Deflection of Polymer Parts Made Using Mask Image Projection Stereolithography (MIP-SLA)Additive Manufacturing Utilizing Stock Ultraviolet Curable SiliconeTemperature and Humidity Variation Effect on Process Behavior in Electrohydrodynamic Jet Printing of a Class of Optical AdhesivesReactive Inkjet Printing Approach towards 3D Silcione Elastomeric Structures FabricationMagnetohydrodynamic Drop-On-Demand Liquid Metal 3D PrintingSelective Separation Shaping of Polymeric PartsSelective Separation Shaping (SSS) – Large-Scale Fabrication PotentialsMechanical Properties of 304L Metal Parts Made by Laser-Foil-Printing ProcessInvestigation of Build Strategies for a Hybrid Manufacturing Process Progress on Ti-6Al-4VDirect Additive Subtractive Hybrid Manufacturing (DASH) – An Out of Envelope MethodMetallic Components Repair Strategies Using the Hybrid Manufacturing ProcessRapid Prototyping of EPS Pattern for Complicated Casting5-Axis Slicing Methods for Additive Manufacturing ProcessA Hybrid Method for Additive Manufacturing of Silicone StructuresAnalysis of Hybrid Manufacturing Systems Based on Additive Manufacturing TechnologyFabrication and Characterization of Ti6Al4V by Selective Electron Beam and Laser Hybrid MeltingDevelopment of a Hybrid Manufacturing Process for Precision Metal PartsDefects Classification of Laser Metal Deposition Using Acoustic Emission SensorAn Online Surface Defects Detection System for AWAM Based on Deep LearningDevelopment of Automatic Smoothing Station Based on Solvent Vapour Attack for Low Cost 3D PrintersCasting - Forging - Milling Composite Additive Manufacturing ThechnologyDesign and Development of a Multi-Tool Additive Manufacturing SystemChallenges in Making Complex Metal Large-Scale Parts for Additive Manufacturing: A Case Study Based on the Additive Manufacturing ExcavatorVisual Sensing and Image Processing for Error Detection in Laser Metal Wire Deposition

    ApplicationsEmbedding of Liquids into Water Soluble Materials via Additive Manufacturing for Timed ReleasePrediction of the Elastic Response of TPMS Cellular Lattice Structures Using Finite Element MethodMultiscale Analysis of Cellular Solids Fabricated by EBMAn Investigation of Anisotropy of 3D Periodic Cellular Structure DesignsModeling of Crack Propagation in 2D Brittle Finite Lattice Structures Assisted by Additive ManufacturingEstimating Strength of Lattice Structure Using Material Extrusion Based on Deposition Modeling and Fracture MechanicsControlling Thermal Expansion with Lattice Structures Using Laser Powder Bed FusionDetermination of a Shape and Size Independent Material Modulus for Honeycomb Structures in Additive ManufacturingAdditively Manufactured Conformal Negative Stiffness HoneycombsA Framework for the Design of Biomimetic Cellular Materials for Additive ManufacturingA Post-Processing Procedure for Level Set Based Topology OptimizationMulti-Material Structural Topology Optimization under Uncertainty via a Stochastic Reduced Order Model ApproachTopology Optimization for 3D Material Distribution and Orientation in Additive ManufacturingTopological Optimization and Methodology for Fabricating Additively Manufactured Lightweight Metallic MirrorsTopology Optimization of an Additively Manufactured BeamQuantifying Accuracy of Metal Additive Processes through a Standardized Test ArtifactIntegrating Interactive Design and Simulation for Mass Customized 3D-Printed Objects – A Cup Holder ExampleHigh-Resolution Electrohydrodynamic Jet Printing of Molten Polycaprolactone3D Bioprinting of Scaffold Structure Using Micro-Extrusion TechnologyFracture Mechanism Analysis of Schoen Gyroid Cellular Structures Manufactured by Selective Laser MeltingAn Investigation of Build Orientation on Shrinkage in Sintered Bioceramic Parts Fabricated by Vat PhotopolymerizationHypervelocity Impact of Additively Manufactured A356/316L Interpenetrating Phase CompositesUnderstanding and Engineering of Natural Surfaces with Additive ManufacturingAdditive Fabrication of Polymer-Ceramic Composite for Bone Tissue EngineeringBinder Jet Additive Manufacturing of Stainless Steel - Tricalcium Phosphate Biocomposite for Bone Scaffold and Implant ApplicationsSelective Laser Melting of Novel Titanium-Tantalum Alloy as Orthopedic BiomaterialDevelopment of Virtual Surgical Planning Models and a Patient Specific Surgical Resection Guide for Treatment of a Distal Radius Osteosarcoma Using Medical 3D Modelling and Additive Manufacturing ProcessesDesign Optimisation of a Thermoplastic SplintReverse Engineering a Transhumeral Prosthetic Design for Additive ManufacturingBig Area Additive Manufacturing Application in Wind Turbine MoldsDesign, Fabrication, and Qualification of a 3D Printed Metal Quadruped Body: Combination Hydraulic Manifold, Structure and Mechanical InterfaceSmart Parts Fabrication Using Powder Bed Fusion Additive Manufacturing TechnologiesDesign for Protection: Systematic Approach to Prevent Product Piracy during Product Development Using AMThe Use of Electropolishing Surface Treatment on IN718 Parts Fabricated by Laser Powder Bed Fusion ProcessTowards Defect Detection in Metal SLM Parts Using Modal Analysis “Fingerprinting”Electrochemical Enhancement of the Surface Morphology and the Fatigue Performance of Ti-6Al-4V Parts Manufactured by Laser Beam MeltingFabrication of Metallic Multi-Material Components Using Laser Metal DepositionA Modified Inherent Strain Method for Fast Prediction of Residual Deformation in Additive Manufacturing of Metal Parts 2539Effects of Scanning Strategy on Residual Stress Formation in Additively Manufactured Ti-6Al-4V PartsHow Significant Is the Cost Impact of Part Consolidation within AM Adoption?Method for the Evaluation of Economic Efficiency of Additive and Conventional ManufacturingIntegrating AM into Existing Companies - Selection of Existing Parts for Increase of AcceptanceRamp-Up-Management in Additive Manufacturing – Technology Integration in Existing Business ProcessesRational Decision-Making for the Beneficial Application of Additive ManufacturingApproaching Rectangular Extrudate in 3D Printing for Building and Construction by Experimental Iteration of Nozzle DesignAreal Surface Characterization of Laser Sintered Parts for Various Process ParametersDesign and Process Considerations for Effective Additive Manufacturing of Heat ExchangersDesign and Additive Manufacturing of a Composite Crossflow Heat ExchangerFabrication and Quality Assessment of Thin Fins Built Using Metal Powder Bed Fusion Additive ManufacturingA Mobile Robot Gripper for Cooperative 3D PrintingTechnological Challenges for Automotive Series Production in Laser Beam MeltingQualification Challenges with Additive Manufacturing in Space ApplicationsMaterial Selection on Laser Sintered Stab Resistance Body ArmorInvestigation of Optical Coherence Tomography Imaging in Nylon 12 PowderPowder Bed Fusion Metrology for Additive Manufacturing Design GuidanceGeometrical Accuracy of Holes and Cylinders Manufactured with Fused Deposition ModelingNew Filament Deposition Technique for High Strength, Ductile 3D Printed PartsApplied Solvent-Based Slurry Stereolithography Process to Fabricate High-Performance Ceramic Earrings with Exquisite DetailsDesign and Preliminary Evaluation of a Deployable Mobile Makerspace for Informal Additive Manufacturing EducationComparative Costs of Additive Manufacturing vs. Machining: The Case Study of the Production of Forming Dies for Tube Bending

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