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The Distribution of Snow Black Carbon observed in the Arctic and Compared to the GISS-PUCCINI Model

In this study, we evaluate the ability of the latest NASA GISS composition-climate model, GISS-E2- PUCCINI, to simulate the spatial distribution of snow BC (sBC) in the Arctic relative to present-day observations. Radiative forcing due to BC deposition onto Arctic snow and sea ice is also estimated. Two sets of model simulations are analyzed, where meteorology is linearly relaxed towards National Centers for Environmental Prediction (NCEP) and towards NASA Modern Era Reanalysis for Research and Applications (MERRA) reanalyses. Results indicate that the modeled concentrations of sBC are comparable with presentday observations in and around the Arctic Ocean, except for apparent underestimation at a few sites in the Russian Arctic. That said, the model has some biases in its simulated spatial distribution of BC deposition to the Arctic. The simulations from the two model runs are roughly equal, indicating that discrepancies between model and observations come from other sources. Underestimation of biomass burning emissions in Northern Eurasia may be the main cause of the low biases in the Russian Arctic. Comparisons of modeled aerosol BC (aBC) with long-term surface observations at Barrow, Alert, Zeppelin and Nord stations show significant underestimation in winter and spring concentrations in the Arctic (most significant in Alaska), although the simulated seasonality of aBC has been greatly improved relative to earlier model versions. This is consistent with simulated biases in vertical profiles of aBC, with underestimation in the lower and middle troposphere but overestimation in the upper troposphere and lower stratosphere, suggesting that the wet removal processes in the current model may be too weak or that vertical transport is too rapid, although the simulated BC lifetime seems reasonable. The combination of observations and modeling provides a comprehensive distribution of sBC over the Arctic. On the basis of this distribution, we estimate the decrease in snow and sea ice albedo and the resulting radiative forcing. We suggest that the albedo reduction due to BC deposition presents significant space-time variations, with highest mean reductions of 1.25% in the Russian Arctic, which are much larger than those in other Arctic regions (0.39% to 0.64 %). The averaged value over the Arctic north of 66degN is 0.4-0.6% during spring, leading to regional surface radiative forcings of 0.7, 1.1 and 1.0Wm(exp−2) in spring 2007, 2008 and 2009, respectively.

Dou, T.↗

Uncertainties in the Modelled CO2 Threshold for Antarctic Glaciation

frequently cited atmospheric CO2 threshold for the onset of Antarctic glaciation of approximately780 parts per million by volume is based on the study of DeConto and Pollard (2003) using an ice sheet model and the GENESIS climate model. Proxy records suggest that atmospheric CO2 concentrations passed through this threshold across the Eocene-Oligocene transition approximately 34 million years. However, atmospheric CO2 concentrations may have been close to this threshold earlier than this transition, which is used by some to suggest the possibility of Antarctic ice sheets during the Eocene. Here we investigate the climate model dependency of the threshold for Antarctic glaciation by performing offline ice sheet model simulations using the climate from 7 different climate models with Eocene boundary conditions (HadCM3L, CCSM3, CESM1.0, GENESIS, FAMOUS, ECHAM5 and GISS_ER). These climate simulations are sourced from a number of independent studies, and as such the boundary conditions, which are poorly constrained during the Eocene, are not identical between simulations. The results of this study suggest that the atmospheric CO2 threshold for Antarctic glaciation is highly dependent on the climate model used and the climate model configuration. A large discrepancy between the climate model and ice sheet model grids for some simulations leads to a strong sensitivity to the lapse rate parameter.

simulation↗

NASA ACC High Energy Dynamic Impact Methodology and Outcomes

High fidelity analysis methods known as Progressive Damage Analysis (PDA) methods, capable of reliably predicting the onset and progression of damage in composite materials, are being developed for HEDI event simulation. Four state-of-the-art PDA methods are being investigated: LS-DYNA MAT162, LS-DYNA MAT261, Smooth-Particle Galerkin (SPG), and EMU Peridynamics. Validation of these PDA models aims to follow a building block approach, starting with coupon- and component-level development. As part of the overall effort, material characterization testing was performed to bridge gaps between existing experimental data and the material property inputs required to predict ballistic impact behavior at the component-level. The material models were updated with the results of the coupon-level testing and were then used to predict panel behavior and damage in ballistic impact events. To assess the accuracy of the PDA methods, these pre-test predictions were compared to the results of ballistic impact testing.

Hunziker, Kenneth J.↗

Static Torsion Testing and Modeling of a Variable Thickness Hybrid Composite Bull Gear

Torsional strength of a variable thickness hybrid gear web was measured by performing static testing on the part in a large torsion test frame. The outer rim of the hybrid gear web was fixed to the bottom of the test frame and loading was applied to the web through a shaft. The test setup included the installation of digital image correlation (DIC) systems to obtain deformation and strain measurements from the surfaces of the hybrid gear web and the mechanical test equipment to ensure reliability of the test. The results indicated that the variable thickness hybrid gear web achieved approximately twice the torsional strength compared to that of previous hybrid gear designs. The DIC analysis showed significantly more straining of the loading shaft than the actual test article. Additionally, the results demonstrated the importance and affect that the metallic, lobed interlock features had on the principal strain and out-of-plane displacement fields. The analysis revealed that the fixed outer rim was in fact rotating and a rigid body motion compensation (RBMC) function was computed to determine the actual rotation of the hub and composite web relative to the outer rim. Modeling simulations were performed for the variable thickness hybrid gear web and correlated well with the RBMC rotational deformation seen in the DIC analysis. In addition to benchmarking the load capacity of the hybrid gear web, measuring its strength is useful information to define the parameters needed for dynamic, endurance, and other testing of the part.

Johnston, Joel P.↗

Multi-Angle Polarimetry: The Once and Future King of Aerosol Remote Sensing

Although aerosols (and their interactions with clouds) are widely known to be one of the most uncertain components of the climate, they remain largely unconstrained in climate simulations. This is because global observations of all the parameters relevant to such simulations - quantity, size, shape, optical properties and chemical composition - are very difficult to simultaneously retrieve from existing remote sensing instruments. The problem can be addressed by maximizing the scene information gathered by a remote sensing instrument, by the use of (passive) multi-spectral, multi-angle and polarimetrically sensitive sensors. These observations, coupled with a radiative transfer model, can be inverted to solve for aerosol parameters. However, the choices to be made when designing an such an observing system and retrieval algorithm are complex, and a variety of approaches have been undertaken by the scientific community. I will review the various multi-spectral, multi-angle, polarimetric observation systems employed for aerosol remote sensing and their corresponding retrieval algorithms. This includes the French Polarization and Directionality of Earth Reflectance (POLDER) instrument, which has been the only such instrument successfully deployed in orbit thus far (most recently from 2004-2013), the NASA Aerosol Polarimetry Sensor (APS) on the ill-fated NASA Glory Mission (launch failure in 2011), potential or planned polarimeters on the NASA Aerosol-Cloud-Ecosystem (ACE) and Pre-Aerosol, Clouds and ocean Ecosystems (PACE) missions, and airborne prototypes from around the world.

Knobelspiesse, Kirk↗

Strong Thermoset Regolith UV-Curable Composite Technology (STRUCT) Overview

Future lunar surface missions require construction materials that can be manufactured in situ using lo-cal resources while operating under extreme environmental conditions. Many Lunar material demands can be solved solely with regolith by compacting or sintering. And yet past Lunar missions rely on polymeric materials, and sustained Lunar missions must reduce Earth-supplied polymers dependence. Dual-cure (Ultraviolet (UV) and thermal) polymer-regolith composites offer a promising pathway by leveraging solar UV radiation, moderate thermal in-put, and regolith. Mission mass limits, power availability and energy constraints on the lunar surface further motivate low-energy processing and curing strategies for surface construction materials. The Strong Thermoset Regolith UV-Curable Composite Technology (STRUCT) project has successfully synthesized and demonstrated dual-cure photopolymer resins derivable from in-situ resources [3]. Morphological, thermal, and mechanical characterization show that the newly formulated UV curable resin systems integrates well with lunar regolith simulants. Processing and chemistry changes, and computational analysis advanced the composite design. X-ray CT scanned and computational analysis demonstrate that resin, regolith and additives are well incorporated. The large fraction of regolith, 95% by mass, large char yield (82% mass), low thermal conductivity (0.26 W/m/K), confirm this material as a promising high-performance thermal and structural material.

thermal conductivity↗

Micropolar deep material network

This study extends the Deep Material Network (DMN), a physics-informed machine learning framework, to predict the homogenized mechanical response of composite materials with micropolar (Cosserat-type) constitutive behavior. This extension incorporates microstructure-dependent size effects, enabling accurate, efficient, and size-aware predictions for composites with complex internal architectures. While traditional, direct numerical simulation micropolar models effectively capture size effects by introducing extra local degrees of freedom, they bring significant computational challenges, particularly for multiscale analyses relevant to engineering applications. The micropolar DMN developed in this paper achieves high accuracy while significantly reducing computation time compared to micropolar direct numerical simulations. This advancement enables multiscale analyses and parameter studies that were previously impractical, such as high-cycle fatigue simulations and comprehensive investigations of internal length scale effects notably in size-dependent plastic response and the optimization of lattice structures. By uniting microstructure-sensitive modeling, physics-driven learning, and scalable surrogate modeling, the micropolar DMN paves the way for accelerated material design, large-scale parametric studies, and the reliable incorporation of size-dependent effects across a wide range of engineering applications, including optimization and next-generation composite design.

36 MATERIALS SCIENCE↗

Building and Breaking Carbon Composites with REACTER

Carbon-based composites have become indispensable materials in aerospace and other high-performance applications, yet obtaining a detailed, nanoscale understanding of their morphology and failure mechanisms using only experimental methods remains a difficult challenge. REACTER is a versatile computational modeling tool for atomistic molecular dynamics simulations designed to model chemical reactions at the speed and length scales of classical force fields. In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites: carbon nanotube (CNT) composites and carbon fiber reinforced polymers (CFRP). A network of CNTs was grown dynamically using the new ‘create atoms’ feature of REACTER. The CNT filler was embedded into a polyarylacetylene (PAA) matrix by simulated in situ polymerization to obtain the final composite model. To generate the second class of carbon composite, fully carbonized (graphitic) carbon fiber morphologies were created by the method of Desai et al. [1], but using the advanced reaction constraints framework of REACTER. Two fiber models were created, representing a circular carbon fiber core and a flat surface, and similarly infiltrated with resin to obtain the final CFRP structure. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third order DFT-based tight-binding simulations, via a reaction constraint on the total potential energy of the involved atoms.

Polymer↗

Predictive Engineering Tools for Injection-Molded Long-Carbon-Thermoplastic Composites: Weight and Cost Analyses

This project proposed to integrate, optimize and validate the fiber orientation and length distribution models previously developed and implemented in the Autodesk Simulation Moldflow Insight (ASMI) package for injection-molded long-carbon-fiber thermoplastic composites into a cohesive prediction capability. The current effort focused on rendering the developed models more robust and efficient for automotive industry part design to enable weight savings and cost reduction. The project goal has been achieved by optimizing the developed models, improving and integrating their implementations in ASMI, and validating them for a complex 3D LCF thermoplastic automotive part (Figure 1). Both PP and PA66 were used as resin matrices. After validating ASMI predictions for fiber orientation and fiber length for this complex part against the corresponding measured data, in collaborations with Toyota and Magna PNNL developed a method using the predictive engineering tool to assess LCF/PA66 complex part design in terms of stiffness performance. Structural three-point bending analyses of the complex part and similar parts in steel were then performed for this purpose, and the team has then demonstrated the use of stiffness-based complex part design assessment to evaluate weight savings relative to the body system target (≥ 35%) set in Table 2 of DE-FOA-0000648 (AOI #1). In addition, starting from the part-to-part analysis, the PE tools enabled an estimated weight reduction for the vehicle body system using 50 wt% LCF/PA66 parts relative to the current steel system. Also, from this analysis an estimate of the manufacturing cost including the material cost for making the equivalent part in steel has been determined and compared to the costs for making the LCF/PA66 part to determine the cost per “saved” pound.

42 ENGINEERING↗

A Study of the Use of Contact Loading to Simulate Low Velocity Impact

Although numerous studies on the impact response of laminated composites have been conducted, there is as yet no agreement within the composites community on what parameter or parameters are adequate for quantifying the severity of an impact event. One of the more interesting approaches that has been proposed uses the maximum contact force during impact to "quantify" the severity of the impact event, provided that the impact velocity is sufficiently low. A significant advantage of this approach, should it prove to be reliable, is that quasi-static contact loading could be used to simulate low velocity impact. In principle, a single specimen, loaded quasi-statically to successively increasing contact loads could be used to map the entire spectrum of damage as a function of maximum contact force. The present study had as its objective assessing whether or not the maximum contact force during impact is a suitable parameter for characterizing an impact. The response of [+/-60/0(sub 4)/+/-60/0(sub 2)](sub s) laminates fabricated from Fiberite T300/934 graphite epoxy and subjected to quasi-static contact loading and to low velocity impact was studied. Three quasi-static contact load levels - 525 lb., 600 lb., and 675 lb. - were selected. Three impact energy levels - 1.14 ft.-lb., 2.0 ft.-lb., and 2.60 ft.-lb. - were chosen in an effort to produce impact events in which the maximum contact forces during the impact events were 525 lb., 600 lb., and 625 lb., respectively. Damage development was documented using dye-penetrant enhanced x-ray radiography. A digital image processing technique was used to obtain quantitative information about the damage zone. Although it was intended that the impact load levels produce maximum contact forces equal to those used in the quasi-static contact experiments, larger contact forces were developed during impact loading. In spite of this, the damage zones developed in impacted specimens were smaller than the damage zones developed in specimens subjected to the corresponding quasi-static contact loading. The impacted specimens may have a greater tendency to develop fiber fracture, but, at present, a quantitative assessment of fiber fracture is not available. In addressing whether or not contact force is an adequate metric for describing the severity of an impact event, the results of this study suggest that it is not. In cases where the quasi-static load level and the maximum contact force during impact were comparable, the quasi-statically loaded specimens consistently developed larger damage zones. It should be noted, however, that using quasi-static damage data to forecast the behavior of impacted material may give conservative estimates of the residual strength of impacted composites.

Highsmith, Alton L.↗

Grand Unification of Quantum Algorithms

Quantum algorithms offer significant speed-ups over their classical counterparts for a variety of problems. The strongest arguments for this advantage are borne by algorithms for quantum search, quantum phase estimation, and Hamiltonian simulation, which appear as subroutines for large families of composite quantum algorithms. A number of these quantum algorithms have recently been tied together by a novel technique known as the quantum singular value transformation (QSVT), which enables one to perform a polynomial transformation of the singular values of a linear operator embedded in a unitary matrix. In the seminal GSLW’19 paper on the QSVT [Gilyén et al., ACM STOC 2019], many algorithms are encompassed, including amplitude amplification, methods for the quantum linear systems problem, and quantum simulation. Here, we provide a pedagogical tutorial through these developments, first illustrating how quantum signal processing may be generalized to the quantum eigenvalue transform, from which the QSVT naturally emerges. Paralleling GSLW’19, we then employ the QSVT to construct intuitive quantum algorithms for search, phase estimation, and Hamiltonian simulation, and also showcase algorithms for the eigenvalue threshold problem and matrix inversion. This overview illustrates how the QSVT is a single framework comprising the three major quantum algorithms, suggesting a grand unification of quantum algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Connecting Organic Aerosol Climate-Relevant Properties to Chemical Mechanisms of Sources and Processing

The research conducted on this project aimed to improve our understanding of secondary organic aerosol (SOA) formation in the atmosphere, and how the properties of the SOA impact climate through its size, phase state, and optical properties. The goal of this project was to demonstrate that the use of molecular composition information to mechanistically connect source apportionment and climate properties can improve the physical basis for simulation of SOA formation and properties in climate models. The research involved developing and improving methods to provide online measurements of the molecular composition of SOA under atmospherically relevant conditions and to apply this technology to controlled simulation chamber experiments and field measurements. The science we have completed with the methodology will impact the simulation of aerosol particles in climate models.

54 ENVIRONMENTAL SCIENCES↗

Composition and Climate Impacts of Increasing Launches to Low Earth Orbit

We present simulations of an Earth system model in which launch vehicles inject gaseous and particulate combustion products into the stratosphere. We considered two plausible scenarios representative for the year 2050, one with 1000 launches per year and another with 10 times more, all of which assuming heavy lift (80 tons to low Earth orbit; LEO) launches using methane as a proxy for liquefied natural gas (LNG) fuel. An industry-standard plume flowfield model was used to predict emission of gaseous species including carbon monoxide, nitrogen oxides, and water vapor. Black carbon was introduced assuming vacuum emission equal 25% of equivalent kerosene engine. The gas emissions showed marginal or insignificant changes in atmospheric composition, while the black carbon emission was found to be the most influential component. Feedbacks involve tropopause and stratospheric warming, followed by a moistening of the stratosphere via tropospheric water vapor intrusions, together with a reduction in global albedo. The fact that LNG-fueled rockets could be a concern from aerosol emissions in our simulations, despite burning more efficiently than conventional fuels, underscores the need to better understand actual black carbon emissions from rocket engines in order to accurately predict the global impacts of launch vehicles on future climate.

Earth system model↗

SU-F-T-178: Optimized Design of a Diamond Detector Specifically Dedicated to the Dose Distribution Measurements in Clinical Proton Pencil Beams

Purpose: In proton-therapy, pencil beam scanning (PBS) dosimetry presents a real challenge due to the small size of the beam (about 3 to 8 mm in FWHM), the pulsed high dose rate (up to 100 Gy/s) and the proton energy variation (about 30 MeV to 250 MeV). In the framework of French INSERM DEDIPRO project, a specifically dedicated single crystal diamond dosimeter (SCDDo) was developed with the objective of obtaining accurate measurements of the dose distribution in PBS modality. Methods: Monte Carlo simulations with MCNPX were performed. A small proton beam of 5 mm in FWHM was simulated as well as diamond devices with various size, thickness and holder composition. The calculated doses-to-diamond were compared with the doses-to-water in order to reduce the perturbation effects. Monte-Carlo simulations lead to an optimized SCDDo design for small proton beams dosimetry. Following the optimized design, SCDDos were mounted in water-equivalent holders with electrical connection adapted to standard electrometer. First, SCDDos performances (stability, repeatability, signal-to-background ratio…) were evaluated with conventional photon beams. Then, characterizations (dose linearity, dose rate dependence…) with wide proton beams were performed at proton-therapy center (IC-CPO) from Curie Institute (France) with the passive proton delivery technique, in order to confirm dosimetric requirements. Finally, depth-dose distributions were measured in a water tank, for native and modulated Bragg Peaks with the collimator of 12 cm, and compared to a commercial PPC05 parallel-plate ionization chamber reference detector. Lateral-dose profiles were also measured with the collimator of 5 mm, and compared to a commercial SFD diode. Results: The results show that SCDDo design does not disturb the dose distributions. Conclusion: The experimental dose distributions with the SCDDo are in good agreement with the commercial detectors and no energy dependence was observed with this device configuration.

07 ISOTOPE AND RADIATION SOURCES↗

Organic synthesis in experimental impact shocks

Laboratory simulations of shocks created with a high-energy laser demonstrate that the efficacy of organic production depends on the molecular, not just the elemental composition of the shocked gas. In a methane-rich mixture that simulates a low-temperature equilibrium mixture of cometary material, hydrogen cyanide and acetylene were produced with yields of 5 x 10(17) molecules per joule. Repeated shocking of the methane-rich mixture produced amine groups, suggesting the possible synthesis of amino acids. No organic molecules were produced in a carbon dioxide-rich mixture, which is at odds with thermodynamic equilibrium approaches to shock chemistry and has implications for the modeling of shock-produced organic molecules on early Earth.

NASA Discipline Exobiology↗

Formation of helices with controllable chirality in gel-fiber composites

While microscale helices with specified chirality are pervasive in biological systems, driving purely synthetic materials to self-organize into such useful structures remains a significant challenge. Through theory and simulations, we model the behavior of initially flat ribbons of gel-fiber composites and show that these materials self-organize into three-dimensional helices with the application of heat. We specifically focus on thermo-responsive gels, which shrink when heated to a point near the lower critical solubility temperature (LCST). Within the composite, regions of the LCST gel that lie far from the fibers can readily shrink in response to the increased temperature; however, near the fibers the network is inhibited from undergoing the heat-induced collapse. This competition between the constrained and the unconstrained regions of the heated sample plays a vital role in the structural evolution of the material. Additionally, we find that this dynamic process can be controlled through the careful placement of the fibers on the outer surface of the gel. We specifically identify fiber arrangements that lead to the formation of helical structures with controlled chirality. Moreover, we isolate scenarios where constraining the movement of one or both the free ends of the sample promotes and stabilizes the formation of helical structures with specified handedness. Such structurally tailored composites are useful for creating mechanically robust actuators, and “appendages” for soft robots that can controllably curl and uncurl with variations in temperature.

36 MATERIALS SCIENCE↗

Composition Measurements of the HFG1 Glasses

This report provides results from the analyses of glass compositions for the High Fluoride Glasses-1, a series of simulated nuclear waste glasses fabricated at the Pacific Northwest National Laboratory. The series included the quenched version of the glasses. These data will be used to validate or identify areas of potential characterization improvements in the current glass property/composition models. Chemical analyses were performed on a representative sample of each of the quenched glasses to allow for comparisons with the targeted compositions. The relative differences between the targeted and measured concentrations of F, K 2 0, and Li 2 O for some of the glasses were greater than 10%. Overall, there were no indications of errors in batching of the simulated waste glasses. These results can be used in further characterization of this series of glasses, including the normalization of Product Consistency Test results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

High temperature metal matrix composites for future aerospace systems

Research was conducted on metal matrix composites and intermetallic matrix composites to understand their behavior under anticipated future operating conditions envisioned for aerospace power and propulsion systems of the 21st century. Extremes in environmental conditions, high temperature, long operating lives, and cyclic conditions dictate that the test evaluations not only include laboratory testing, but simulated flight conditions. The various processing techniques employed to fabricate composites are discussed along with the basic research underway to understand the behavior of high temperature composites, and the relationship of this research to future aerospace systems.

Stephens, Joseph R.↗

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