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At least 685 records · Page 38

Vision-based localization for cooperative robot-CNC hybrid manufacturing

Wire and arc additive manufacturing (WAAM) has shown promise in recent years for producing large-scale parts with higher deposition rates than other additive processes. WAAM is often combined with subtractive machining to form a hybrid manufacturing process. This hybrid process can be realized by retrofitting computer numerical control (CNC) machines with deposition heads, adding spindles and deposition heads to robots, or developing part localization methods to transfer parts from an additive cell to a CNC machine. Here, a novel, robot-CNC hybrid configuration is introduced where a maneuverable robot is placed in front of a CNC machine to deposit material within the machine envelop. Furthermore, this method removes the need for part localization and the extensive machine modifications required for retrofitting; however, the problem of robot localization is also added. In this work, the effects of error in vision-based, contactless robot localization on machining parameters in a robot-machine hybrid process were studied. Performance was characterized on an implementation of this system using classical computer vision techniques. In addition, machining simulations were conducted to evaluate the effects of image-induced error on chip thickness, material removal rate, and machining allowance. Initial tests show that computer vision could adequately locate a robot for the hybrid WAAM process within .5 mm.

Hybrid manufacturing↗

Association of small vessel disease with tau pathology

Emerging evidence suggests that small vessel disease (SVD) is a risk factor for clinical dementia and may contribute to AD neuropathological changes. Watershed brain regions are located at the most distal areas between arterial territories, making them vulnerable to SVD-related changes. We examined the association of pathologic markers of SVD, specifically arteriolosclerosis in watershed brain regions, with AD pathologic changes. Participants (N= 982; mean age-at-death = 90; 69% women) were enrolled as part of one of two cohort studies of aging and dementia. At autopsy, neuropathological evaluation included semi-quantitative grading of arteriolosclerosis pathology from 2 cortical watershed regions: the anterior watershed (AWS) and posterior watershed (PWS), densities for cortical β-amyloid and tau-tangle pathology, and other common age-related pathologies. Linear regression models examined the association of watershed arteriolosclerosis pathology with β-amyloid and tau-tangle burden. In follow-up analyses, available ex-vivo MRI and proteomics data in a subset of decedents were leveraged to examine the association of whole brain measure of WMH, as a presumed MRI marker of SVD, with β-amyloid and tau-tangle burden, as well as to examine the association of watershed arteriolosclerosis with proteomic tau. Watershed arteriolosclerosis was common, with 45% of older persons having moderate-to-severe arteriolosclerosis pathology in the AWS region, and 35% in the PWS. In fully adjusted models that controlled for demographics and common age-related pathologies, an increase in severity of PWS arteriolosclerosis was associated with a higher burden of tau-tangle burden, specifically neocortical tau burden, but not with β-amyloid. AWS arteriolosclerosis was not associated with β-amyloid or tau pathology. Ex-vivo WMH was associated with greater tau-tangle pathology burden but not β-amyloid. Furthermore, PWS arteriolosclerosis was associated with higher abundance of tau phosphopeptides, that promote formation of tau aggregates. These data provide compelling evidence that SVD, specifically posterior watershed arteriolosclerosis pathology, is linked with tau pathological changes in the aging brain.

60 APPLIED LIFE SCIENCES↗

A space-time parallel algorithm with adaptive mesh refinement for computational fluid dynamics

This work describes a space-time parallel algorithm with space-time adaptive mesh refinement (AMR). AMR with subcycling is added to multigrid reduction-in-time (MGRIT) in order to provide solution efficient adaptive grids with a reduction in work performed on coarser grids. This algorithm is achieved by integrating two software libraries: XBraid (Parallel time integration with multigrid. https://computation.llnl.gov/projects/parallel-timeintegration-multigrid) and Chombo (Chombo software package for AMR applications—design document, 2014). The former is a parallel time integration library using multigrid and the latter is a massively parallel structured AMR library. Employing this adaptive space-time parallel algorithm is Chord (Comput Fluids 123:202–217, 2015), a computational fluid dynamics (CFD) application code for solving compressible fluid dynamics problems. For the same solution accuracy, speedups are demonstrated from the use of space-time parallelization over the time-sequential integration on Couette flow and Stokes’ second problem. On a transient Couette flow case, at least a 1.5× speedup is achieved, and with a time periodic problem, a speedup of up to 13.7× over the time-sequential case is obtained. In both cases, the speedup is achieved by adding processors and exploring additional parallelization in time. The numerical experiments show the algorithm is promising for CFD applications that can take advantage of the time parallelism. Future work will focus on improving the parallel performance and providing more tests with complex fluid dynamics to demonstrate the full potential of the algorithm.

97 MATHEMATICS AND COMPUTING↗

Rainfall events stimulate episodic associative nitrogen fixation in switchgrass

Abstract Associative N 2 fixation (ANF) is widespread but poorly characterized, limiting our ability to estimate global inputs from N 2 fixation. In some places, ANF rates are at or below detection most of the time but occasionally and unpredictably spiking to very high rates. Here we test the hypothesis that plant phenology and rainfall events stimulate ANF episodes. We measured ANF in intact soil cores in switchgrass ( Panicum virgatum L.) in Michigan, USA. We used rain exclusion shelters to impose three rainfall treatments with each receiving 60 mm of water over a 20-day period but at different frequencies. We concurrently established a treatment that received ambient rainfall, and all four treatments were replicated four times. To assess the effects of plant phenology, we measured ANF at key phenological stages in the ambient treatment. To assess the effects of rainfall, we measured ANF immediately before and immediately after each wetting event in each treatment involving rainfall manipulation. We found that the previous day’s rainfall could explain 29% of the variation in ANF rates within the ambient treatment alone, and that bulk soil C:N ratio was also positively correlated with ANF, explaining 18% of the variation alone. Wetting events increased ANF and the magnitude of response to wetting increased with the amount of water added and decreased with the amount of inorganic N added in water. ANF episodes thus appear to be driven primarily by wetting events. Wetting events likely increase C availability, promote microbial growth, and make rhizosphere conditions conducive to ANF.

Vizza, Carmella (ORCID:0000000292690357)↗

Coal polymer composites prepared by fused deposition modeling (FDM) 3D printing

Coal is a vital energy resource worldwide, but pollutants and greenhouse gases from its combustion cause environmental problems. To explore the non-combustion approach to use and valorize coal, anthracite and lignite were blended with polyamide 12 (PA 12) through FDM printing in this work and compared in the composites. By adding lignite, Young’s modulus improved with increasing loading to 50 wt% while tensile strength leveled off among the composites, compared to that of PA 12. By contrast, the addition of anthracite decreased the tensile performance at all loadings. Rheology tests and morphology analyses suggested that the interactions between fillers (anthracite and lignite) and PA 12 may cause differences in tensile properties. In addition, the printed lignite composites showed improved thermal conductivity (~ twofold), indicating lignite demonstrates the potential to build functional composites. This work provides a strategy to use lignite in composites by 3D printing for value-added products and reduces the demand for petroleum-based polymers. Overall, our approach diverts lignite from combustion processes and alleviates the negative impact of lignite use on the environment.

36 MATERIALS SCIENCE↗

Kinetic Inductance Traveling Wave Amplifier Designs for Practical Microwave Readout Applications

Abstract A Kinetic Inductance Traveling Wave Amplifier (KIT) utilizes the nonlinear kinetic inductance of superconducting films, particularly niobium titanium nitride (NbTiN), for parametric amplification. These amplifiers achieve remarkable performance in terms of gain, bandwidth, and compression power and frequently approach the quantum limit for noise. However, most KIT demonstrations have been isolated from practical device readout systems. Using a KIT as the first amplifier in the readout chain of an unoptimized microwave SQUID multiplexer coupled to a transition-edge sensor microcalorimeter, we see an initial improvement in the flux noise [1]. One challenge in KIT integration is the considerable microwave pump power required to drive the non-linearity. To address this, we have initiated efforts to reduce the pump power by using thinner NbTiN films and an inverted microstrip transmission line design. In this article, we present the new transmission line design, fabrication procedure, and initial device characterization—including gain and added noise. These devices exhibit over 10 dB of gain with a 3 dB bandwidth of approximately 5.5–7.25 GHz, a maximum practical gain of 12 dB, and typical gain ripple under 4 dB peak to peak. We observe an appreciable impedance mismatch in the NbTiN transmission line, which is likely the source of the majority of the gain ripple. Finally, we perform an initial noise characterization and demonstrate system-added noise of three quanta or less over nearly the entire 3 dB bandwidth.

Physics↗

Clustering and Cliques in Preferential Attachment Random Graphs with Edge Insertion

In this paper, we investigate the global clustering coefficient (a.k.a transitivity) and clique number of graphs generated by a preferential attachment random graph model with an additional feature of allowing edge connections between existing vertices. Specifically, at each time step t, either a new vertex is added with probability f(t), or an edge is added between two existing vertices with probability 1 – f(t). We establish concentration inequalities for the global clustering and clique number of the resulting graphs under the assumption that f(t) is a regularly varying function at infinity with index of regular variation –$\gamma$, where $\gamma$ $\in$ [0, 1). Finally, we also demonstrate an inverse relation between these two statistics: the clique number is essentially the reciprocal of the global clustering coefficient.

97 MATHEMATICS AND COMPUTING↗

Development, feasibility, and uncertainty of radioactive 22 Na tracer dilution and gamma spectroscopy for mass determination of molten salt for pyroprocessing spent nuclear fuels

Accurate knowledge of the total mass of molten salts both for pyroprocessing spent nuclear fuels and for molten salt reactors is necessary for safeguards purposes. However, it is challenging to know or measure the total mass of molten salt due to the complicated shapes as well as the compositional—and thus density—changes that occur over time during operation. Here, we investigated radioactive tracer dilution (RTD) as a potential safeguards technique for application to the total mass measurement of LiCl–KCl–UCl 3 salt used for uranium electrorefining, with a focus on the feasibility, uncertainty, and fission product effect of RTD for salt mass measurement. To this end, experimental-scale RTD tests (600–700 g of total mass) were initially carried out by adding 22 Na tracer salt into LiCl–KCl salt containing 0, 5, and 28wt% radioactive salts from an electrorefiner (ER) for refining uranium. Upon the completion of the experimental-scale RTD tests, we performed a scale-up RTD test by directly adding 22 Na tracer salts to the ER, which uses about 12 kg of LiCl–KCl–UCl 3 salt during normal operation. This paper reports the main features of RTD for total mass measurement of molten salt and summarizes the results of the experimental-scale and scale-up RTD tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

New soil carbon sequestration with nitrogen enrichment: a meta-analysis

Background and aims: Through agriculture and industry, humans are increasing the deposition and availability of nitrogen (N) in ecosystems worldwide. Carbon (C) isotope tracers provide useful insights into soil C dynamics, as they allow to study soil C pools of different ages. In this study we evaluated to what extent N enrichment affects soil C dynamics in experiments that applied C isotope tracers. Methods: Using meta-analysis, we synthesized data from 35 published papers. We made a distinction between “new C” and “old C” stocks, i.e., soil C derived from plant C input since the start of the isotopic enrichment, or unlabeled, pre-existing soil C. Results: Averaged across studies, N addition increased new soil C stocks (+30.3%), total soil C stocks (+6.1%) and soil C input proxies (+30.7%). Although N addition had no overall, average, effect on old soil C stocks and old soil C respiration, old soil C stocks increased with the amount of N added and respiration of old soil C declined. Nitrogen-induced effects on new soil C and soil C input both decreased with the amount of extraneous N added in control treatments. Conclusion: Although our findings require additional confirmation from long-term field experiments, our analysis provides isotopic evidence that N addition stimulates soil C storage both by increasing soil C input and (at high N rates) by decreasing decomposition of old soil C. Furthermore, we demonstrate that the widely reported saturating response of plant growth to N enrichment also applies to new soil C storage.

54 ENVIRONMENTAL SCIENCES↗

Optimizing first- and last-mile public transit services leveraging transportation network companies (TNC)

First-mile last-mile (FMLM) mobility services that connect riders to public transit can lead to improved transit accessibility and network efficiency if such services are convenient and reliable. However, many current FMLM services are inefficient and costly because they are inflexible (e.g., fixed supply of shuttles) and do not leverage collected data for optimized decision making. At the same time, new forms of shared mobility can provide added flexibility and real-time analytics to FMLM systems when carefully integrated. This study evaluates performance and cost implications of public/private coordination between transit shuttles and transportation network companies (TNC) in the FMLM context. A real-time operations model was developed to simulate daily operations for an existing FMLM system using real-world demand data. Three supply strategies were tested with varying levels of flexibility: (1) Status Quo (two 23-passenger on-demand shuttles), (2) Hybrid (one 23-passenger on-demand shuttle + TNC), and (3) TNC Only (exclusively use TNC services). Results indicated that the added flexibility of the Hybrid service design (using shuttles and TNCs) improved service performance (a 7.7% improvement), reduced daily operating costs (– 6.0%), and improved service reliability (95th percentile travel times decreased by up to 40% during peak periods). In addition, the Hybrid service design was more robust to variations in demand. Here, the Hybrid service was significantly cheaper to operate (– 31.6%) at reduced demand levels (50% of normal), and improved service performance (a 10.2% improvement) when demand levels were increased (150% of normal). These findings emphasize the importance of flexibility in FMLM service designs, especially when demand is sparse and variable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fitting Matérn smoothness parameters using automatic differentiation

The Mat$\acute{e}$rn covariance function is ubiquitous in the application of Gaussian processes to spatial statistics and beyond. Perhaps the most important reason for this is that the smoothness parameter $\nu$ gives complete control over the mean-square differentiability of the process, which has significant implications for the behavior of estimated quantities such as interpolants and forecasts. Unfortunately, derivatives of the Mat$\acute{e}$rn covariance function with respect to $\nu$ require derivatives of the modified second-kind Bessel function $K$ $\nu$ with respect to $\nu$. While closed form expressions of these derivatives do exist, they are prohibitively difficult and expensive to compute. For this reason, many software packages require fixing $\nu$ as opposed to estimating it, and all existing software packages that attempt to offer the functionality of estimating $\nu$ use finite difference estimates for $\partial$ $\nu$ $K$ $\nu$ . In this work, we introduce a new implementation of $K$$\nu$ that has been designed to provide derivatives via automatic differentiation (AD), and whose resulting derivatives are significantly faster and more accurate than those computed using finite differences. Here, we provide comprehensive testing for both speed and accuracy and show that our AD solution can be used to build accurate Hessian matrices for second-order maximum likelihood estimation in settings where Hessians built with finite difference approximations completely fail.

97 MATHEMATICS AND COMPUTING↗

Interlaboratory Reproducibility of Contour Method Data Analysis and Residual Stress Calculation

While the contour method for residual stress assessment has developed rapidly, no published study documents its interlaboratory reproducibility. Objective: Here we report an initial reproducibility experiment focused on contour method data analysis and residual stress calculation. The experiment uses surface topography data from a physical process simulation of elastic-plastic beam bending. The simulation provides surface topography, for input to the contour method data analysis, as well as a known residual stress field with 130 MPa peak magnitude. Additionally, to increase realism, noise and specific artifacts are added to the topography data. A group of participants received the topography data (without the known residual stress), independently analyzed the data, and submitted results as a two-dimensional residual stress field. Analysis of submissions provides a group average residual stress field and the spatial distribution of reproducibility standard deviation. The group average residual stress agrees with the known stress in magnitude and spatial trend. The reproducibility standard deviation ranges from 2 to 54 MPa over the measurement plane, with an average of 5.4 MPa. Reproducibility standard deviation is smaller in the cross-section interior (≤ 5 MPa), modest near local extrema in the stress field (5 to 10 MPa), and larger near the cross-section boundaries (10 to 30 MPa). Overall, the largest values of reproducibility standard deviation (up to 54 MPa) occur in limited areas where artifacts had been added to the topography data; while some participants identified and removed these artifacts, some did not, leading to systematic differences that elevated the standard deviation.

42 ENGINEERING↗

Phase equilibria and microstructure evolution in the Ni-rich region of binary Ni-Ce and ternary Ni-Ce-X (X=Al, Nb, Cr, Ti) systems at 900 °C

The equilibrium compositions of all phases in the Ni-rich region of binary Ni-Ce and ternary Ni-Ce-X (X=Al, Nb, Cr, Ti) systems at 900 °C were determined experimentally through isothermal annealing for up to 500 h and compared with currently available computational thermodynamic descriptions. Additionally, the study examined how adding a third element to the binary system affects the microstructure by analyzing changes in the volume fraction of the intermetallic phase in the eutectic region. It was observed that Nb and Ti addition lowered the intermetallic fraction in the eutectic region while Al and Cr addition did the opposite. The fraction of intermetallic phase in the eutectic region is very important because it contributes to extreme brittleness of these alloys. Also, Al, Nb and Ti addition promoted different precipitates upon annealing when added in sufficient amounts. The collected data on composition and phase equilibria provides crucial information for improving the thermodynamic assessments of the binary and ternary alloy systems.

energy dispersive spectrometry↗

Understanding the Effects of Ash Content on Various Pretreatment Technologies for the Bioconversion of Corn Stover

Here, the study aimed to examine the effects of adding biomass ash on the biochemical processes involved in fermentable sugar production. Corn stover was pretreated using several methods—hot water, dilute acid, alkaline, γ-valerolactone, and ionic liquid methods, each examined with ash loadings of 7.18% and 21.07%. The findings demonstrated that increased ash content adversely affected both pretreatment and enzymatic hydrolysis. Specifically, the total sugar yield was 3 to 16% lower at the higher ash content across all pretreatment methods, and up to 4.01% lower during enzymatic hydrolysis. For acidic pretreatment, the sugar yield decreased as ash content increased. In contrast, ash content had a lesser impact on alkaline pretreatment compared to acidic pretreatment. For example, using corn stover with an ash content as high as 22.65% resulted in only a 2.90% decrease in total sugar yield compared to corn stover without added ash. Further, the primary reasons for the reduced sugar yield in higher ash biomass during acidic pretreatments were likely the neutralizing effect of the ash and decreased acid access to the substrates. During enzymatic hydrolysis, ash reduced the sugar yield by limiting enzyme access to cellulose.

09 BIOMASS FUELS↗

Variation in Biomass Yield and Cell Wall Composition in Switchgrass Natural Variants Under Two Nitrogen Regimes

Switchgrass (Panicum virgatum) is a promising lignocellulosic biofuel crop for which biomass and processing quality are important. Inherent plant variability across genotypes and environments challenges uniformity and product quality. In this study, the impact of nitrogen (N) application on switchgrass yield and quality was examined under field conditions using a highly diverse switchgrass panel over a 4-year period at Knoxville, TN. Overall, biomass production was correlated between low (0 kg of added N/ha) and moderate (135 kg of added N/ha) nitrogen treatments, suggesting that the N impact is largely uniform across the genotypes. Nonetheless, high biomass genotypes were identified with high nitrogen-use efficiency ; biomass was congruent or even higher (up to 9-fold) in the low N treatment. Genotypes were also identified with up to 94% nitrogen-remobilization efficiency. Furthermore, nitrogen application appeared to impact lignin content in whole tillers but was neutral to lignin monomer syringyl-to-guaiacyl (S/G) ratio. The same panel grown under natural conditions in Watkinsville, GA, produced significantly more biomass than the Tennessee panel in the first 3 years, but biomass was similar across both sites and treatments in year 4. Top performing genotypes overlapped between sites by 20-37%. There were low correlations in lignin content in whole tillers across the two field sites, but moderate correlations were observed for S/G ratios. The high yielding genotypes from the low N plot identified in this study can be used in breeding programs and management strategies in switchgrass to evade adverse environmental and economic effects.

09 BIOMASS FUELS↗

Review of internal and external surface finishing technologies for additively manufactured metallic alloys components and new frontiers

Surface finishing in additive manufacturing (AM) is a technological bottleneck. The field of surface finishing of AM parts is vast because it not only focuses on roughness reduction in the hard-to-access internal surfaces but also includes the scope of adding coatings and sensors. Even though metal AM component is reaching the density and bulk microstructure at par or even better than conventionally produced components, adverse impact of surface roughness and imperfections is becoming the major obstruction. It is observed that external and internal surface roughness of AM components is a high probability cause of many unavoidable issues such as corrosion, incorrect tolerance estimations during the build stage, and the fatigue failure of parts before the expected life cycle. At present, AM field mainly focuses on improving and enhancing the internal and external surface roughness to pass the stringent qualification requirements for actual applications. To address these challenges, researchers worldwide are conducting many experiments and developing different surface finishing techniques. This paper reviews the state-of-the-art knowledge and processes of different surface finishing technology that can be applied to AM metal components. This article mainly highlights several liquid-based surfaces finishing approaches to develop promising surface microstructures on interior and exterior surfaces as a micromachining tool. The future of making strong and self-monitoring AM component requires broadening of surface finishing field and including advanced topics such as coatings and adding sensor technology. We also discuss new frontiers and the scope of future work in the surface finishing field to bring attention to related concerns and possibilities associated with making smart and strong AM components for twenty-first-century integrated engineering systems.

36 MATERIALS SCIENCE↗

Emulating the impact of additional proton-proton interactions in the ATLAS simulation by pre-sampling sets of inelastic Monte Carlo events

The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton-proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run (2015-2018) there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.

97 MATHEMATICS AND COMPUTING↗

Carbon nanotube (CNT) metal composites exhibit greatly reduced radiation damage

Radiation damage of structural materials leads to mechanical property degradation, eventually inducing failure. Secondary-phase dispersoids or other radiation defect sinks are often added to materials to boost their radiation resistance. We demonstrate that a metal composite made by adding 1D carbon nanotubes (CNTs) to aluminum (Al) exhibits superior radiation resistance. In situ ion irradiation with transmission electron microscopy (TEM) and atomistic simulations together reveal the mechanisms of rapid defect migration to CNTs, facilitating defect recombination and enhancing radiation tolerance. The origin of this effect is an evolving stress gradient in the Al matrix resulting from CNT transformation under irradiation, and the stability of resulting carbides. Extreme value statistics of large defect behavior in our simulations highlight the role of CNTs in reducing accumulated damage. Furthermore, this approach to controlling defect migration represents a promising opportunity to enhance the radiation resistance of nuclear materials without detrimental effects.

36 MATERIALS SCIENCE↗