The objective of this paper is to experimentally validate the graph-based approach that was advanced in our previous work for predicting the heat flux in metal additive manufactured parts. We realize this objective in the specific context of the directed energy deposition (DED) additive manufacturing process. Accordingly, titanium alloy (Ti6Al4V) test parts (cubes) measuring 12.7 mm × 12.7 mm × 12.7 mm were deposited using an Optomec hybrid DED system at the University of Nebraska-Lincoln (UNL). A total of six test parts were manufactured under varying process settings of laser power, material flow rate, layer thickness, scan velocity, and dwell time between layers. During the build, the temperature profiles for these test parts were acquired using a single thermocouple affixed to the substrate (also Ti6Al4V). The graph-based approach was tailored to mimic the experimental DED process conditions. The results indicate that the temperature trends predicted from the graph theoretic approach closely match the experimental data; the mean absolute percentage error between the experimental and predicted temperature trends were in the range of 6% ∼ 15%. This work thus lays the foundation for predicting distortion and the microstructure evolved in metal additive manufactured parts as a function of the heat flux. In our forthcoming research we will focus on validating the model in the context of the laser powder bed fusion process.
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An Adaptive Approach to Minimize System Level Tests Targeting Low Voltage DVFS Failures
Traditional low cost scan based structural tests no longer suffice for delivering acceptable defect levels in many processor SOCs, especially those targeting low power applications. Expensive functional system level tests (SLTs) have become an additional and necessary final test screen. Efforts to eliminate or minimize the use of SLTs have focused on new fault models and improved test generation methods to improve the effectiveness of scan tests. In this paper we argue that given the limitations of scan timing tests, such an approach may not be sufficient to detect all the low voltage failures caused by circuit timing variability that appear to dominate SLT fallout. Instead, we propose an alternate approach for meaningful cost savings that adaptively avoids SLT tests for a subset of the manufactured parts. This is achieved by using parametric and scan tests results from earlier in the test flow to identify low delay variability parts that can avoid SLT with minimal impact on DPPM. Extensive SPICE simulations support the viability of our proposed approach. We also show that such an adaptive test flow is also very well suited to real time optimization during the using machine-learning techniques.
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- Award ID(s):
- 1910964
- NSF-PAR ID:
- 10355107
- Date Published:
- Journal Name:
- 2019 IEEE International Test Conference (ITC)
- Page Range / eLocation ID:
- 1 to 10
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Purpose There is recent emphasis on designing new materials and alloys specifically for metal additive manufacturing (AM) processes, in contrast to AM of existing alloys that were developed for other traditional manufacturing methods involving considerably different physics. Process optimization to determine processing recipes for newly developed materials is expensive and time-consuming. The purpose of the current work is to use a systematic printability assessment framework developed by the co-authors to determine windows of processing parameters to print defect-free parts from a binary nickel-niobium alloy (NiNb5) using laser powder bed fusion (LPBF) metal AM. Design/methodology/approach The printability assessment framework integrates analytical thermal modeling, uncertainty quantification and experimental characterization to determine processing windows for NiNb5 in an accelerated fashion. Test coupons and mechanical test samples were fabricated on a ProX 200 commercial LPBF system. A series of density, microstructure and mechanical property characterization was conducted to validate the proposed framework. Findings Near fully-dense parts with more than 99% density were successfully printed using the proposed framework. Furthermore, the mechanical properties of as-printed parts showed low variability, good tensile strength of up to 662 MPa and tensile ductility 51% higher than what has been reported in the literature. Originality/value Although many literature studies investigate process optimization for metal AM, there is a lack of a systematic printability assessment framework to determine manufacturing process parameters for newly designed AM materials in an accelerated fashion. Moreover, the majority of existing process optimization approaches involve either time- and cost-intensive experimental campaigns or require the use of proprietary computational materials codes. Through the use of a readily accessible analytical thermal model coupled with statistical calibration and uncertainty quantification techniques, the proposed framework achieves both efficiency and accessibility to the user. Furthermore, this study demonstrates that following this framework results in printed parts with low degrees of variability in their mechanical properties.more » « less
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Introduction Multi-series CT (MSCT) scans, including non-contrast CT (NCCT), CT Perfusion (CTP), and CT Angiography (CTA), are widely used in acute stroke imaging. While each scan has its advantage in disease diagnosis, the varying image resolution of different series hinders the ability of the radiologist to discern subtle suspicious findings. Besides, higher image quality requires high radiation doses, leading to increases in health risks such as cataract formation and cancer induction. Thus, it is highly crucial to develop an approach to improve MSCT resolution and to lower radiation exposure. Hypothesis MSCT imaging of the same patient is highly correlated in structural features, the transferring and integration of the shared and complementary information from different series are beneficial for achieving high image quality. Methods We propose TL-GAN, a learning-based method by using Transfer Learning (TL) and Generative Adversarial Network (GAN) to reconstruct high-quality diagnostic images. Our TL-GAN method is evaluated on 4,382 images collected from nine patients’ MSCT scans, including 415 NCCT slices, 3,696 CTP slices, and 271 CTA slices. We randomly split the nine patients into a training set (4 patients), a validation set (2 patients), and a testing set (3 patients). In preprocessing, we remove the background and skull and visualize in brain window. The low-resolution images (1/4 of the original spatial size) are simulated by bicubic down-sampling. For training without TL, we train different series individually, and for with TL, we follow the scanning sequence (NCCT, CTP, and CTA) by finetuning. Results The performance of TL-GAN is evaluated by the peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM) index on 184 NCCT, 882 CTP, and 107 CTA test images. Figure 1 provides both visual (a-c) and quantity (d-f) comparisons. Through TL-GAN, there is a significant improvement with TL than without TL (training from scratch) for NCCT, CTP, and CTA images, respectively. These significances of performance improvement are evaluated by one-tailed paired t-tests (p < 0.05). We enlarge the regions of interest for detail visual comparisons. Further, we evaluate the CTP performance by calculating the perfusion maps, including cerebral blood flow (CBF) and cerebral blood volume (CBV). The visual comparison of the perfusion maps in Figure 2 demonstrate that TL-GAN is beneficial for achieving high diagnostic image quality, which are comparable to the ground truth images for both CBF and CBV maps. Conclusion Utilizing TL-GAN can effectively improve the image resolution for MSCT, provides radiologists more image details for suspicious findings, which is a practical solution for MSCT image quality enhancement.more » « less
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Abstract Aim To investigate the cryptic diversity and diversification timing in the putatively low‐dispersal Amazonian leaf‐litter lizard
Loxopholis osvaldoi , and to ask how geography (rivers, isolation by distance, IBD), ecological drivers (isolation by environment, IBE) and historical factors (climatic refugia) explain intraspecific genetic variation.Location Central Amazonia, Brazil.
Taxon Squamata; Gymnophthalmidae;
Loxopholis osvaldoi. Methods We sequenced two mitochondrial and two nuclear markers in 157 individuals. Phylogeographic structure and the occurrence of independent evolving lineages where explored through phylogenetic and coalescent analyses. A species tree and divergence dates of lineages were inferred with *BEAST, employing multiple DNA substitution rates. The potential genetic impacts of geographical distance among localities, the environment and the position of localities in relation to main rivers were tested by redundancy analysis (RDA).
Results We detected 11 independently evolving and largely divergent intraspecific lineages. Lineage distribution patterns are complex and do not match any conspicuous barrier to gene flow, except for the Amazon River. Most lineages appear to have originated in the lower Miocene and Pliocene, in disagreement with the Pleistocene refuge hypothesis. IBD, IBE and rivers appear to have acted in concert establishing and maintaining genetic structure. However, when controlling for other explanatory variables, IBD explains significantly more variation than rivers, IBE or historical factors.
Main Conclusions Our results strongly suggest that
L .osvaldoi is a species complex. Future taxonomic work should use an integrative approach to explore whether morphological variation is present and congruent with the genetic data. While the use of a sensitive dating analysis allowed us to better describe the diversification history ofL .osvaldoi , the lack of a spatial model of Neogene river dynamics prevents the test of specific, more informative river barrier hypotheses. The data suggest that nonlinear correlation analyses (e.g. RDA) should be preferred to detect factors that affect phylogeographic patterns in the Amazon, instead of linear multiple regressions (e.g. Mantel tests). Given the high level of cryptic diversity detected within this and other Amazonian species, we caution against hypothesis tests based solely on the distribution of nominal taxa, which can provide a rather incomplete view of the processes behind Amazonian diversity. -
Abstract—Recent advances in process technology have resulted in novel defect mechanisms making the test generation process very challenging. In addition to complete opens and shorts that can be represented via extreme defect resistance magnitudes, partial resistive opens and shorts are also of concern in deeply scaled CMOS technologies. For open defects with intermediate defect magnitude values, it has been shown that multi-pattern tests are necessary for defect exposure. We extend this approach to short defects with intermediate defect magnitude values to obtain a suite of multi-pattern tests for standard cell instances that cover complete as well as partial intra-cell open and short defects. A hierarchical scan-compatible SAT-based test generation approach for full scan sequential circuits is then proposed that allows such multi-pattern tests to be applied to the circuit via the scan infrastructure. A key innovation is the combined use of shift and capture operations along with launch-on-capture and launch-on- shift scan based test application for increased defect coverage. Resulting defect coverage improvements over conventional two-pattern tests are demonstrated on ISCAS89 benchmark circuits.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ITC44170.2019.9000173
