Understanding dislocation plasticity of single crystalline Ta micropillars under dynamic loading
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36 MATERIALS SCIENCE↗
SEARCH · Engineering Papers
Results for “Impact testing”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Microstructure and crystallographic texture of high frequency electric resistance welded X65 pipeline steel
Here, microstructure and crystallographic texture and their correlation with impact toughness of high-frequency electric resistance welded (HF-ERW) X65 Grade pipeline steel have been investigated. X65 base metal after HF-ERW has formed a typical hourglass-shaped weld joint with four different regions, including the thermomechanical-affected zone (TMAZ), fine-grained heat affected zone (FGHAZ), coarse-grained heat affected zone (CGHAZ), and bondline (Weld Zone). X65 base metal shows prominent (113) [110] and (112) [110] texture components due to thermomechanical-controlled processing. TMAZ depicted random texture with a minor intensity of Cube component (001)[110] due to the partial recrystallization during welding. In the FGHAZ and CGHAZ, near the bondline, the base metal texture has been converted to rotated Goss (110) [110], Goss (110) [001], and rotated cube (001) [110] due to the recrystallization of the austenite and the shear deformation in the austenite temperature range. A high density of {100} and {110} cleavage planes is observed in the CGHAZ, which is often found to be the fracture location for the impact toughness testing.
36 MATERIALS SCIENCE↗
A full-scope, high-fidelity simulator-based hardware-in-the-loop testbed for comprehensive nuclear power plant cybersecurity research
Nuclear power plant (NPP) cybersecurity research often relies on hardware-in-the-loop (HIL) testbeds that integrate real hardware components into simulated environments. These testbeds allow researchers to identify vulnerabilities, evaluate attack impacts, and test security measures in a controlled setting. Furthermore, previous HIL testbeds lacked fidelity to accurately represent real nuclear systems, limiting the scope of cybersecurity analysis. This study presents the creation of a HIL testbed, devised upon a full-scope, high-fidelity NPP simulator, to facilitate realistic and comprehensive cybersecurity research. To demonstrate its capabilities, the control logic for the steam generator water level was migrated from the simulator to an external programmable logic controller. As a practical application of the developed testbed, supply chain attack scenarios were simulated by injecting malicious code into the controller logic, and the effects of manipulating sensor inputs and control commands were observed. While this HIL testbed provides more detailed simulations, enhanced realism, and wider applicability compared to other options utilizing a less complex simulator, it is also more intricate and costly. For this reason, we include a detailed comparison with some alternative architectures to aid fellow researchers and practitioners in the selection of a suitable HIL architecture based on specific research objectives.
47 OTHER INSTRUMENTATION↗
Eutectic melting of alloy microparticles upon low velocity impact
Although impact melting has been quantified in a number of pure metals, alloyed microparticles have access to low melting-point eutectics that can promote earlier melting. Through real-time monitoring of single particle impacts resolved at the nanosecond- and micron-scales, we explore the impact melting of AA7075 from high velocities, where it is abundant and clear, to velocities as low as ∼269 m/s. Here, by using a hard substrate to isolate the deformation largely to the particle, we show that the adiabatic heat produced by the plasticity of the impact can explain the onset of melting at low velocity.
Additive manufacturing↗
Elucidating Drought-Tolerance Mechanisms in Plant Roots through 1H NMR Metabolomics in Parallel with MALDI-MS, and NanoSIMS Imaging Techniques
As direct mediators between plants and soil, roots play an important role in metabolic responses to environmental stresses such as drought, yet these responses are vastly uncharacterized on a plant-specific level, especially for co-occurring species. Here, we aim to examine the effects of drought on root metabolic profiles and carbon allocation pathways of three tropical rainforest species by combining cutting-edge metabolomic and imaging technologies in an in situ position-specific 13C-pyruvate root-labeling experiment. Further, washed (rhizosphere-depleted) and unwashed roots were examined to test the impact of microbial presence on root metabolic pathways. Drought had a species-specific impact on the metabolic profiles and spatial distribution in Piper sp. and Hibiscus rosa sinensis roots, signifying different defense mechanisms; Piper sp. enhanced root structural defense via recalcitrant compounds including lignin, while H. rosa sinensis enhanced biochemical defense via secretion of antioxidants and fatty acids. In contrast, Clitoria fairchildiana, a legume tree, was not influenced as much by drought but rather by rhizosphere presence where carbohydrate storage was enhanced, indicating a close association with symbiotic microbes. This study demonstrates how multiple techniques can be combined to identify how plants cope with drought through different drought-tolerance strategies and the consequences of such changes on below-ground organic matter composition.
Drought, Carbon cycle, MALDI-MSI, Metabolomics, Na↗
Mixed Nd 4+/3+ and Cluster Magnetism in Hexagonal Perovskite 12R-Ba 4 NdMn 3 O 12−γ
Hexagonal perovskite oxides with 12R stacking host well-separated face-sharing octahedral metal trimers with short metal–metal distances, leading in some cases to large degrees of magnetic frustration and cluster magnetism. Introducing magnetic ions in proximity to these trimers can influence the degree of frustration and cluster magnetism, but the extent to which the magnetism can be tuned by varying neighboring metal cations remains an open question. In this work, we test the impacts of using Nd in proximity to Mn trimers in the hexagonal perovskite 12R-Ba 4 NdMn 3 O 12−γ . Given this stoichiometry, Nd should assume the 4+ oxidation state with a spin state of S = 1, which would be the first realization of Nd 4+ in an oxide environment. Through detailed bulk magnetic, X-ray absorption spectroscopic, and powder neutron diffraction (PND) measurements, we find that Nd 4+ is realized in this material, but there is also partial reduction to Nd 3+ , which is charge-balanced by O vacancies. Magnetometry measurements indicate an antiferromagnetic ordering temperature T N ≈ 16 K, and PND measurements reveal a surprising collinear antiferromagnetic structure with magnetic space group Pc2/m (no. 10.49 in BNS notation), which has not previously been seen in this class of materials. Our results represent a comprehensive analysis of the structural, electronic, and magnetic properties of 12R-Ba 4 NdMn 3 O 12−γ , showing the first observation of partial Nd 4+ in an oxide, and demonstrating that this structural class can host a broad range of magnetic structures which are not easily predicted based on compositional trends.
14 SOLAR ENERGY↗
Deep Learning Estimation of Daily Ground–Level NO 2 Concentrations from Remote Sensing Data
The limited number of nitrogen dioxide (NO 2 ) surface measurements calls for the development of highly accurate approaches to estimating surface NO 2 concentrations. In this study, we leverage a new satellite instrument, the TROPOspheric Monitoring Instrument (TROPOMI), along with other predictor variables, to estimate daily surface NO 2 concentrations over Texas in 2019. We use the deep convolutional neural network (Deep-CNN), an advanced deep learning algorithm, to obtain estimates and achieve a correlation coefficient (R) of 0.91, an index of agreement (IOA) of 0.95, and a mean absolute bias (MAB) of 1.75 ppb in surface NO 2 estimation. Additionally, we leverage a novel approach, SHapley Additive exPlanations (SHAP), to describe how Deep-CNN understands each predictor variable. The SHAP results show that the Deep-CNN model has an advanced understanding of the dataset, revealing that TROPOMI closely captures levels of NO 2 . In addition, we show the superiority of our Deep-CNN model at estimating surface NO 2 over other well-known machine learning and regression models in the field, including the support vector machines (SVM), random forest (RF), and multiple linear regression (MLR). Although SVM and RF show strong capabilities at estimating surface NO 2 concentrations, their accuracy is inferior to that of the Deep-CNN model, ranking second and third in model accuracy in this study. The MLR, however, shows a poor ability at NO 2 estimation and ranks last among all models. Furthermore, testing the impact of sample size on model performance, we also show that, compared to other models, Deep-CNN needs more samples to trigger its strength at surface NO 2 estimation.
54 ENVIRONMENTAL SCIENCES↗
Uptake of polystyrene nanospheres by wheat and Arabidopsis roots in agar, hydroponics, and soil
Plant uptake of micro- and nanoplastics can lead to contamination of food with plastic particles and subsequent human consumption of plastics. There is evidence that plant roots can take up micro and nanoplastics; however, most of this evidence stems from experiments conducted with plants grown in hydroponics or agar systems where uptake of nanoparticles by roots is more favorable than when plants were grown in soil. Here, we discern the root uptake and accumulation of polystyrene nanospheres in plants grown in different growth media: agar, hydroponics, and soil. In addition, we tested the impacts of nanospheres on plant biomass and plant stress. Wheat and Arabidopsis thaliana were grown in agar, hydroponics, and soil media and exposed to polystyrene nanospheres. Three different nanospheres were used (40 nm and 200 nm carboxylate-modified and 200 nm amino-modified polystyrene) and uniformly mixed into the growth media. Plants were grown for 7 to 10 days and the roots were then examined for the presence of nanospheres by confocal laser scanning microscopy and scanning electron microscopy. Plant stress was evaluated by measuring reactive oxygen species (ROS). We observed the 40 nm nanospheres inside the plant roots, but the 200 nm nanospheres only adhered to the root cap cells showing no uptake into the roots. Furthermore, confocal images indicated that root uptake of nanospheres was favored in hydroponic solutions as compared to agar and soil media. Plant biomass was generally not affected by the nanospheres, except for hydroponically grown Arabidopsis thaliana, where biomass was significantly reduced. Small sized (40 nm) and positively charged (200 nm amino-modified) nanospheres showed higher ROS accumulation in plants than negatively charged 200 nm carboxylate-modified nanospheres. In conclusion, this study provides evidence that polystyrene nanospheres can be taken up into the interior of plant roots and cause plant stress, but these impacts are less pronounced in media where the plastic particles are less mobile, like in agar and soil media as compared to hydroponic systems.
54 ENVIRONMENTAL SCIENCES↗
Multi-probe analysis of the galaxy cluster CL J1226.9+3332: Hydrostatic mass and hydrostatic-to-lensing bias
The precise estimation of the mass of galaxy clusters is a major issue for cosmology. Large galaxy cluster surveys rely on scaling laws that relate cluster observables to their masses. From the high-resolution observations of ~45 galaxy clusters with the NIKA2 and XMM-Newton instruments, the NIKA2 Sunyaev-Zel’dovich Large Program should provide an accurate scaling relation between the thermal Sunyaev-Zel’dovich effect and the hydrostatic mass. In this paper we present an exhaustive analysis of the hydrostatic mass of the well-known galaxy cluster CL J1226.9+3332, the highest-redshift cluster in the NIKA2 Sunyaev-Zel’dovich Large Program at z = 0.89. We combined the NIKA2 observations with thermal Sunyaev-Zel’dovich data from the NIKA, Bolocam, and MUSTANG instruments and XMM-Newton X-ray observations, and tested the impact of the systematic effects on the mass reconstruction. We conclude that slight differences in the shape of the mass profile can be crucial when defining the integrated mass at R 500 , which demonstrates the importance of the modelling in the mass determination. We prove the robustness of our hydrostatic mass estimates by showing the agreement with all the results found in the literature. Another key factor for cosmology is the bias of the masses estimated assuming the hydrostatic equilibrium hypothesis. Based on the lensing convergence maps from the Cluster Lensing And Supernova survey with Hubble (CLASH) data, we obtain the lensing mass estimate for CL J1226.9+3332. From this we are able to measure the hydrostatic-to-lensing mass bias for this cluster, which spans from 1–b HSE/lens ~0.7 to 1, presenting the impact of data sets and mass reconstruction models on the bias.
79 ASTRONOMY AND ASTROPHYSICS↗
Weak lensing mass-richness relation of redMaPPer clusters in LSST DESC DC2 simulations
Cluster scaling relations are key ingredients in cluster abundance-based cosmological studies. In optical cluster cosmology, where clusters are detected through their richness, cluster-weak gravitational lensing has proven to be a powerful tool to constrain the cluster mass-richness relation. This work is conducted as part of the Dark Energy Science Collaboration (DESC), which aims to analyze the Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory, starting in 2026. Cluster properties inferred from weak lensing, such as mass, suffer from several sources of bias. In this paper, we aim to test the impact of modeling choices and observational systematics in cluster lensing on the inference of the mass-richness relation. We constrained the mass-richness relation of 3600 clusters detected by the redMaPPer algorithm in the cosmoDC2 extragalactic mock catalog of the LSST DESC DC2 simulation, covering 440 deg 2 , using number count measurements and either stacked weak lensing profiles or mean cluster masses in several intervals of richness (20 ≤ λ ≤ 200) and redshift (0.2 ≤ z ≤ 1). We provide the first constraints on the redMaPPer cluster mass-richness relation detected in cosmoDC2. We find that for an LSST-like source galaxy density, our constraints are robust to changes in the concentration-mass relation, as well as the dark matter density profile modeling choices, when source redshifts and shapes are perfectly known. We find that photometric redshift uncertainties can introduce bias at the 1σ level, which could be mitigated by an overall correction factor fitted jointly with the scaling parameters. We find that including positive shear-richness covariance in the fit shifts the results by up to 0.5σ. Our constraints also offer a fair comparison to a fiducial mass-richness relation, obtained from matching cosmoDC2 halo masses to redMaPPer-detected cluster richness results.
galaxy clusters↗
Robustness of cosmic birefringence measurement against Galactic foreground emission and instrumental systematics
The polarization of the cosmic microwave background (CMB) can be used to search for parity-violating processes like that predicted by a Chern-Simons coupling to a light pseudoscalar field. Such an interaction rotates E modes into E modes in the observed CMB signal through an effect known as cosmic birefringence. Even though isotropic birefringence can be confused with the rotation produced by a miscalibration of the detectors' polarization angles, the degeneracy between both effects is broken when Galactic foreground emission is used as a calibrator. Here, in this work, we use realistic simulations of the High-Frequency Instrument of the Planck mission to test the impact that Galactic foreground emission and instrumental systematics have on the recent birefringence measurements obtained through this technique. Our results demonstrate the robustness of the methodology against the miscalibration of polarization angles and other systematic effects, like intensity-to-polarization leakage, beam leakage, or cross-polarization effects. However, our estimator is sensitive to the EB correlation of polarized foreground emission. Here we propose to correct the bias induced by dust EB by modeling the foreground signal with templates produced in Bayesian component-separation analyses that fit parametric models to CMB data. Acknowledging the limitations of currently available dust templates like that of the Commander sky model, high-precision CMB data and a characterization of dust beyond the modified blackbody paradigm are needed to obtain a definitive measurement of cosmic birefringence in the future.
79 ASTRONOMY AND ASTROPHYSICS↗
HOD-dependent systematics for luminous red galaxies in the DESI 2024 BAO analysis
In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD models for LRGs, including the base 5-parameter vanilla model and two extensions to it, that we refer to as baseline and extended models. The baseline model is described by the 5 vanilla HOD parameters, an incompleteness factor and a velocity bias parameter, whereas the extended one also includes a galaxy assembly bias and a satellite profile parameter. We utilize the 25 dark matter simulations available in the AbacusSummit simulation suite at z=0.8 and generate mock catalogs for our different HOD models. To test the impact of the HOD modeling in the position of the BAO peak, we run BAO fits for all these sets of simulations and compare the best-fit BAO-scaling parameters α iso and α AP between every pair of HOD models. Furthermore, we do this for both Fourier and configuration spaces independently, using post-reconstruction measurements. We find a 3.3σ detection of HOD systematic for α AP in configuration space with an amplitude of 0.19%. For the other cases, we did not find a 3σ detection, and we decided to compute a conservative estimation of the systematic using the ensemble of shifts between all pairs of HOD models. By doing this, we quote a systematic with an amplitude of 0.07% in α iso for both Fourier and configuration spaces; and of 0.09% in α AP for Fourier space.
79 ASTRONOMY AND ASTROPHYSICS↗
Neuromuscular Junction Model Optimized for Electrical Platforms
Neuromuscular junctions (NMJs), specialized synapses between motor neurons and muscle fibers, are essential for muscle activity. A simple and reproducible cell-based in vitro NMJ platform is needed to test the impact of chemicals on the neuron-muscle communication. Our platform utilizes genetically modified neurons and muscle cells, optimized culture conditions, and commercially available multielectrode array system for recording action potentials. Neuronal cells (NSC34) were optogenetically modified with channelrhodopsin chimera to allow for simultaneous, light-mediated, millisecond-precise activation of neuronal population. This signal is propagated through functional synapses to the muscle fibers. Muscle cells (C2C12) were modified by incorporating gap junction protein (Connexin-43) to improve intracellular communication without affecting muscle differentiation. This communication between muscle fibers resulted in better signal propagation and signal strength. Optimized culture medium facilitated the growth and differentiation of both cell types together. Our system was validated using vecuronium, a muscle relaxant, which abolished the muscle response. This in vitro model provides a unique tool for establishing a NMJ platform that is easy to record and analyze. Potential applications include nondestructive long-term screening of drugs affecting the NMJ.
59 BASIC BIOLOGICAL SCIENCES↗
Blending and obscuration in weak-lensing magnification
ABSTRACT We test the impact of some systematic errors in weak-lensing (WL) magnification measurements with the COSMOS 30-band photo-z Survey flux limited to Iauto < 25.0 using correlations of both source galaxy counts and magnitudes. Systematic obscuration effects are measured by comparing counts and magnification correlations. We use the Advanced Camera for Survey-Hubble Space Telescope catalogues to identify potential blending objects (close pairs) and perform the magnification analyses with and without blended objects. We find that blending effects start to be important (∼0.04-mag obscuration) at angular scales smaller than 0.1 arcmin. Extinction and other systematic obscuration effects can be as large as 0.10 mag (U band) but are typically smaller than 0.02 mag depending on the band. After applying these corrections, we measure a 3.9σ magnification signal that is consistent for both counts and magnitudes. The corresponding projected mass profiles of galaxies at redshift z ≃ 0.6 (MI ≃ −21) is Σ = 25 ± 6 M⊙ h3 pc–2 at 0.1 Mpc h–1, consistent with NFW type profile with M200 ≃ 2 × 1012 M⊙h pc–2. Tangential shear and flux-size magnification over the same lenses show similar mass profiles. We conclude that magnification from counts and fluxes using photometric redshifts has the potential to provide complementary WL information in future wide-field surveys once we carefully take into account systematic effects, such as obscuration and blending.
79 ASTRONOMY AND ASTROPHYSICS↗
Dark Energy Survey Year 6 results: cell-based coadds and METADETECTION weak lensing shape catalogue
We present the metadetection weak lensing galaxy shape catalogue from the 6-yr Dark Energy Survey (DES Y6) imaging data. This data set is the final release from DES, spanning 4422 deg 2 of the southern sky. We describe how the catalogue was constructed, including the two new major processing steps, cell-based image coaddition, and shear measurements with metadetection. The DES Y6 M etadetection weak lensing shape catalogue consists of 151 922 791 galaxies detected over riz bands, with an effective number density of n eff = 8.22 galaxies per arcmin 2 and shape noise of σ e = 0.29. We carry out a suite of validation tests on the catalogue, including testing for point spread function (PSF) leakage, testing for the impact of PSF modelling errors, and testing the correlation of the shear measurements with galaxy, PSF, and survey properties. In addition to demonstrating that our catalogue is robust for weak lensing science, we use the DES Y6 image simulation suite to estimate the overall multiplicative shear bias of our shear measurement pipeline. We find no detectable multiplicative bias at the roughly half-per cent level, with m = (3.4 ± 6.1) x 10 –3 , at 3σ uncertainty. This is the first time both cell-based coaddition and Metadetection algorithms are applied to observational data, paving the way to the Stage-IV weak lensing surveys.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Tidal Love numbers of novel and admixed celestial objects
A sub-fraction of dark matter or new particles trapped inside celestial objects can significantly alter their macroscopic properties. Here, we investigate the new physics imprint on celestial objects by using a generic framework to solve the Tolman-Oppenheimer-Volkoff (TOV) equations for up to two fluids. We test the impact of populations of new particles on celestial objects, including the sensitivity to self-interaction sizes, new particle mass, and net population mass. Applying our setup to neutron stars and boson stars, we find rich phenomenology for a range of these parameters, including the creation of extended atmospheres. These atmospheres are detectable by their impact on the tidal love number, which can be measured at upcoming gravitational wave experiments such as Advanced LIGO, the Einstein Telescope, and LISA. We release our calculation framework as a publicly available code at this URL, allowing the TOV equations to be generically solved for arbitrary new physics models in novel and admixed celestial objects.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Decision Making Under Uncertainty Human Subjects Data - Fire Evacuation Task
This dataset contains de-identified data from human subjects experiments, along with the images and code that were used to run the experiments (as a crowdsourced online study). In this study, participants were shown the probability of a house being in the burn zone of a wildfire. They were asked if they would stay in the house or evacuate in that scenario. The probability information was presented in different ways, including text and maps. The studies tested the impact of different visual cues on the participants' patterns of decisions.
Matzen, Laura E. [Sandia National Laboratories (SN↗
Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities
To tackle climate challenges, communities need to harvest renewable energy and resources on site locally to close the loops for enhancing the resilience of communities facing unpredictable and uncertain future changes. A decentralization planning of urban renewable energy systems is proposed by treating urban waste streams and producing biomass through applying algal biotechnology. When applying algal technology as a renewable and decentralized energy source in urban systems, the overall performance can vary by levels of urban nutrients, solar and CO 2 resources, and the transportation cost when considering its application to different urban densities, urban form, and the spatial scale of urban settings. This research explores three potential impacts on the algal system’s energy performance: (1) urban density, (2) urban form in different contexts, and (3) spatial scale. The research examines the impacts by testing urban settings given in actual contexts in Atlanta, Georgia, USA. Four neighborhoods representing the high-density urban, mid-density urban, mixed suburban, and typical suburban areas are investigated. The density-scale–performance relationships are explored through testing different urban forms of neighborhoods in both hypothetical and actual neighborhood settings. A GIS-based model is developed to estimate the overall energy performance of the decentralized renewable energy system in urban environments. Results show that the energy performance is positive mainly for high-density urban neighborhoods with small-to-medium scales, up to 0.36 MJ per ton of municipal solid wastes for actual settings and 0.37 MJ for hypothetical cases. Neighborhoods with higher density have higher energy performance while up scaling has negative effects on the energy performance with a low degree of significance. Optimal scales are found as a 1-km radius in real test beds and 1.3 km in hypothetical settings, in which the results show trade-offs between scaling effects in the system efficiency gain and the transportation cost increase.
Quan, Steven Jige↗