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At least 811 records · Page 45

Research in nonlinear structural and solid mechanics

Recent and projected advances in applied mechanics, numerical analysis, computer hardware and engineering software, and their impact on modeling and solution techniques in nonlinear structural and solid mechanics are discussed. The fields covered are rapidly changing and are strongly impacted by current and projected advances in computer hardware. To foster effective development of the technology perceptions on computing systems and nonlinear analysis software systems are presented.

Mccomb, H. G., Jr.↗

Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation

Studies on domain adaptation (DA) for remote sensing (RS) imagery analysis lack consistency in selection and description of evaluation scenarios. Without properly characterizing datasets, model assumptions, and evaluation scenarios, it is difficult to objectively compare DA methods and reach conclusions about their suitability across different applications. With this motivation, this work seeks to empirically assess to which extent the interaction between data characteristics and model assumptions influences the effectiveness of DA methods. Using the widely explored task of building footprint segmentation as a case study, we perform a large-scale study across over 200 DA scenarios that include variations across view angles, areas observed, and sensors used for data acquisition. Rather than adopting different model architectures or optimization criteria, we contrast the performances of two DA methods based on adversarial learning that differ only in their assumptions about source and target domains. Informed by metadata and data characteristics unveiled using traditional computer vision (CV) techniques as well as pretrained deep models, we provide a detailed meta-analysis of experiments highlighting the importance of accurately considering data assumptions for DA in RS segmentation tasks. As demonstrated by a “cherry-picking” exercise, different claims regarding which model is best could be made by selecting different subsets of evaluation scenarios. While well-calibrated assumptions can be beneficial, mismatching assumptions can lead to negative biases in DA applications. Furthermore, this study intends to motivate the community toward more consistent evaluation protocols while providing recommendations and insights toward creating novel benchmark datasets, documenting data characteristics, application-specific knowledge, and model assumptions.

42 ENGINEERING↗

Numerical modeling and experimental validation of low velocity impact of woven GFRP/CFRP composites

Low-velocity impact of 2D woven glass fiber reinforced polymer (GFRP) and carbon fiber reinforced polymer (CFRP) composite laminates was studied experimentally and numerically. Hybrid laminates containing blocked layers of GFRP/CFRP/GFRP with all plies oriented at 0° were investigated. Relatively high impact energies were used to obtain full perforation of the laminate in a low-velocity impact setup. Numerical simulations were carried out using the in-house transient dynamics finite element code, Sierra/SM, developed at Sandia National Laboratories. A three-dimensional continuum damage model was used to describe the response of a woven composite ply. Two methods for handling delamination were considered and compared: (1) cohesive zone modeling and (2) continuum damage mechanics. The reduced model size achieved by omission of the cohesive zone elements produced acceptable results at reduced computational cost. Further, the comparison between different modeling techniques can be used to inform modeling decisions relevant to low velocity impact scenarios. The modeling was validated by comparing with the experimental results and showed good agreement in terms of predicted damage mechanisms and impactor velocity and force histories.

36 MATERIALS SCIENCE↗

SPH modelling of energy partitioning during impacts on Venus

Impact cratering of the Venusian planetary surface by meteorites was investigated numerically using the Smoothed Particle Hydrodynamics (SPH) method. Venus presently has a dense atmosphere. Vigorous transfer of energy between impacting meteorites, the planetary surface, and the atmosphere is expected during impact events. The investigation concentrated on the effects of the atmosphere on energy partitioning and the flow of ejecta and gas. The SPH method is particularly suitable for studying complex motion, especially because of its ability to be extended to three dimensions. In our simulations, particles representing impactors and targets are initially set to a uniform density, and those of atmosphere are set to be in hydrostatic equilibrium. Target, impactor, and atmosphere are represented by 9800, 80, and 4200 particles, respectively. A Tillotson equation of state for granite is assumed for the target and impactor, and an ideal gas with constant specific heat ratio is used for the atmosphere. Two dimensional axisymmetric geometry was assumed and normal impacts of 10km diameter projectiles with velocities of 5, 10, 20, and 40 km/s, both with and without an atmosphere present were modeled.

Takata, T.↗

Challenges in predicting protein-protein interactions of understudied viruses: Arenavirus-human interactions

Understanding protein-protein interactions (PPIs) between viruses and host organisms is crucial for uncovering infection mechanisms and identifying potential therapeutic targets. The ability to generalize PPI predictive models across understudied viruses presents a significant challenge. In this work, we use arenavirus-human PPIs to illustrate the difficulties associated with model generalization, which are compounded by a lack of both positive and negative data. We employ a Transfer Learning approach to investigate arenavirus-human PPIs by utilizing models trained on better-studied virus-human and human-human PPIs. Additionally, we curate and assess four types of negative sampling datasets to evaluate their impact on model performance. Despite the overall high accuracies (93–99 %) and AUPRC scores (0.8–0.9) appearing promising, further analysis indicates that these performance metrics can be misleading due to data leakage, data bias, and overfitting, especially concerning under-represented viral proteins. We reveal these gaps and assess the impact of data imbalance using standard k-fold cross-validation and Independent Blind Testing with a Balanced Dataset, resulting in a drop in accuracy below 50 %. We propose a viral protein-specific evaluation framework that categorizes viral proteins into majority and minority classes based on their representation in the dataset, enabling comparison of model performance across these groups using balanced accuracies. This framework offers a more robust evaluation of model generalizability, addressing biases inherent in standard evaluation techniques and paving the way for more reliable PPI prediction models for understudied viruses.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling framework for evaluating the impacts of hydrodynamic pressure on hydrologic exchange fluxes and residence time for a large-scale river section over a long-term period

Quantifying hydrologic exchange fluxes (HEF) at the river and subsurface interface and their residence times (RT) in subsurface are important for managing the water quality and ecosystem health in dynamic river corridor systems. In this study, a modeling framework is developed for coupling the three-dimensional (3D) multi-phase surface, subsurface flow transport, and numerical tracer model for RT in a large-scale river section over a long period. The framework is utilized to evaluate the impacts of hydrodynamic pressure on HEFs and RT for a 30 km section of the Columbia River in Washington State over a three-year period. Based on comparisons between model simulations with and without considering hydrodynamic pressure, we found that hydrodynamic pressure increases the net HEFs by 7% with river gaining water from the subsurface domain, and leads to slight reduction of RT.

54 ENVIRONMENTAL SCIENCES↗

Planning for a Large Space Weather Event: Preparation for and Lessons Learned from the 2024 Space Weather Interagency Tabletop Exercise

On May 8-9 2024, the Space Radiation Analysis Group (SRAG) at NASA/Johnson Space Center participated in a joint exercise with DoD, FEMA, OSTP, DOE and other agencies to assess their ability to respond to a large hypothetical space weather event. SRAG is a uniquely skilled group of scientists and engineers tasked with mitigating impacts of radiation exposure to the astronaut crew aboard the International Space Station and upcoming missions beyond Low Earth Orbit (LEO). In meeting this objective, the team has developed expertise in both modeling the impacts of an enhanced space environment and in the real-time operational support of the Flight Control Team when assessing a response to the environment. Several members of SRAG worked with the Tabletop Exercise (TTX) planners to define a realistic large event and to model the resulting radiation exposure on an Artemis crew. SRAG members participating in the TTX were blinded to the results of this analysis. As the event unfolded during the TTX, SRAG provided their assessment of the likely impact on the crew and recommendations for crew actions. During the exercise, the team tracked lessons learned for their own planning, currently in work, for Artemis-II and subsequent missions.

Janet Barzilla↗

Core formation by giant impacts

The present model for the timing and mechanisms of planetary core formation argues that once a planet reaches a certain minimum mass, the large impacts that are typical of late accretion can trigger core formation. This model circumvents the difficulties posed by the large-scale segregation of molten iron into diapirs, and the displacement of the cold, elastic interior of the planet by the iron. The analytical melting model used is based on the Hugoniot equations, the empirical relationship for the decline of particle velocity with distance, and the linear shock-particle velocity relationship.

Tonks, W. B.↗

Impact Cratering: Bridging the Gap Between Modeling and Observations

This volume contains abstracts that have been accepted for presentation at the workshop on Impact Cratering: Bridging the Gap Between Modeling and Observations, February 7-9, 2003, in Houston, Texas. Logistics, onsite administration, and publications for this workshop were provided by the staff of the Publications and Program Services Department at the Lunar and Planetary Institute.

Source record↗

Climate Impacts on Global Agriculture Emerge Earlier in New Generation of Climate and Crop Models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to −6% (SSP126) and from +1% to −24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO 2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

crop model↗

Validating Ancient Age of the Buried Floor of the Northern Lowlands, Mars

Hesperian and Amazonian plains units cover the northern lowlands but little is known about what this surface covers. Models for the creation of the lowlands and the dichotomy boundary implement mechanisms which vary from internal processes, such as plate tectonics or first-order mantle convection, to external processes, such as a single large impact or multiple impacts. Different models require different time scales for low-land formation; determining the age of the buried low-land surface would help constrain the formation models. The Mars Orbiting Laser Altimeter (MOLA) has yielded a high-precision, topographic gridded data set that reveals the presence of Quasi-Circular Depressions (QCDs) in both the southern highlands and the northern lowlands. Most of these roughly circular depressions have no corresponding visible structural feature on the surface. It is proposed that these QCDs are the surface representation of buried impact craters. Based on this assumption, cumulative number vs. diameter curves were constructed, which placed the age of the buried surface of the northern lowlands in the Early or pre-Noachian. A Noachian basement is supported by the remnants of large craters and multi-ring basins discovered in earlier research, but the QCDs provide the first evidence of this for the entire lowland. Constraining the age of the basement floor to the earliest Noachian, however, would require that the process that formed the northern lowlands either occurred in the early Noachian or involves removal of material from the bottom of the crust without destroying the previously formed craters to achieve the modeled crustal thinning. But can we establish that the QCDs do in fact represent buried impact craters, and thus validate an Early Noachian age for the buried lowland floor?

Buczkowski, D. L.↗

In-Depth Modeling and Simulation Analysis of Artemis Missions Using the Impact Probabilistic Risk Assessment Tool

BACKGROUND The Artemis campaign is a Moon exploration program with a series of six planned missions, five of which will be crewed. These five crewed missions will contain a single mission segment (space flight), or multiple mission segments involving space flight (Orion), lunar landing (LTV) and/or space habitat (Gateway). Each crewed segment faces the risk of unique medical conditions, necessitating medical sets/kits tailored to those specificities. To support and enable a data-driven and evidence-based decision-making process through out a mission’s life cycle, a software tool called IMPACT was developed. Using probabilistic risk assessment (PRA) methodologies, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool built for analyzing the possibility of encountering complex medical risks during space flight, and for identifying the medical resources and capabilities needed to treat those potential at-risk medical conditions. IMPACT achieves this by performing hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. During an extended simulation modeling phase, IMPACT generated analytical results for medical risks, and the medical resources and capabilities to address those risks, for every segment of every crewed Artemis mission. This presentation will highlight the reliability, consistency and validity of IMPACT’s computational modeling techniques and will showcase the library of analytical outcomes generated for the Artemis missions. OVERVIEW During the early stages of IMPACT’s design, architecture and technical requirements collection, “scenarios” (use cases) - achievement goals required for acceptance testing, were identified by stakeholders. IMPACT successfully completed the scenario testing requirements and undertook an extensive operational run phase utilizing a wide range of input combinations with a goal of delivering a cohesive, trustworthy, reliable, vast, and diverse body of evidence. The intent of these modeling runs was to validate consistency in output, ensure solidity of executable operations and to streamline processes by identifying areas requiring efficiency improvements. Using the many missions of Artemis, IMPACT ran variations of operational runs to assess the output for acceptable, as well as unusual characteristics. This rigorous long-term “shakedown” analysis was implemented to help build a collective body of evidence to aid in securing a high level of confidence, reliability, and validity in the output, whether from the applicational components of IMPACT, or the entirety of the operational process. ANTICIPATED ANALYSIS AND CONCLUSION This presentation will discuss the various categories of input criteria; the comparisons in the application of these input criteria to various Artemis missions; the preparation and collection of the body of evidence, and reliability of the computational modeling techniques. This paper serves as an initial analytical overview of IMPACT’s probabilistic risk assessment (PRA) medical risk outputs covering Artemis missions and is not intended to be deemed the official medical response for the Artemis campaign.

Crew Composition↗

Characteristics of Impact Craters and Interior Deposits: Analysis of the Spatial and Temporal Distribution of Volatiles in the Highlands of Mars

The martian southern highlands contain impact craters that display pristine to degraded morphologies, and preserve a record of degradation that can be attributed to fluvial, eolian, mass wasting, volcanic and impact-related processes. However, the relative degree of modification by these processes and the amounts of material contributed to crater interiors are not well constrained. Impact craters (D>10 km) within Terra Cimmeria (0deg-60degS, 190deg-240degW), Terra Tyrrhena (0deg-30degS, 260deg-310degW) and Noachis Terra (20deg-50degS, 310deg-340degW) are being examined to better understand the degradational history and evolution of highland terrains. The following scientific objectives will be accomplished. 1) Determine the geologic processes that modified impact craters (and surrounding highland terrains). 2) Determine the sources (e.g. fluvial, lacustrine, eolian, mass wasting, volcanic, impact melt) and relative amounts of material composing crater interior deposits. 3) Document the relationships between impact crater degradation and highland fluvial systems. 4) Determine the spatial and temporal relationships between degradational processes on local and regional scales. And 5) develop models of impact crater (and highland) degradation that can be applied to these and other areas of the martian highlands. The results of this study will be used to constrain the geologic, hydrologic and climatic evolution of Mars and identify environments in which subsurface water might be present or evidence for biologic activity might be preserved.

Mest, S. C.↗

Multimodel Estimates of Atmospheric Lifetimes of Long-lived Ozone-Depleting Substances: Present and Future

We have diagnosed the lifetimes of long-lived source gases emitted at the surface and removed in the stratosphere using six three-dimensional chemistry-climate models and a two-dimensional model. The models all used the same standard photochemical data. We investigate the effect of different definitions of lifetimes, including running the models with both mixing ratio (MBC) and flux (FBC) boundary conditions. Within the same model, the lifetimes diagnosed by different methods agree very well. Using FBCs versus MBCs leads to a different tracer burden as the implied lifetime contained in the MBC value does not necessarily match a model's own calculated lifetime. In general, there are much larger differences in the lifetimes calculated by different models, the main causes of which are variations in the modeled rates of ascent and horizontal mixing in the tropical midlower stratosphere. The model runs have been used to compute instantaneous and steady state lifetimes. For chlorofluorocarbons (CFCs) their atmospheric distribution was far from steady state in their growth phase through to the 1980s, and the diagnosed instantaneous lifetime is accordingly much longer. Following the cessation of emissions, the resulting decay of CFCs is much closer to steady state. For 2100 conditions the model circulation speeds generally increase, but a thicker ozone layer due to recovery and climate change reduces photolysis rates. These effects compensate so the net impact on modeled lifetimes is small. For future assessments of stratospheric ozone, use of FBCs would allow a consistent balance between rate of CFC removal and model circulation rate

CFC↗

Multimodel Estimates of Atmospheric Lifetimes of Long-Lived Ozone-Depleting Substances: Present and Future

We have diagnosed the lifetimes of long-lived source gases emitted at the surface and removed in the stratosphere using six three-dimensional chemistry-climate models and a two-dimensional model. The models all used the same standard photochemical data. We investigate the effect of different definitions of lifetimes, including running the models with both mixing ratio (MBC) and flux (FBC) boundary conditions. Within the same model, the lifetimes diagnosed by different methods agree very well. Using FBCs versus MBCs leads to a different tracer burden as the implied lifetime contained in theMBC value does not necessarilymatch a model's own calculated lifetime. In general, there are much larger differences in the lifetimes calculated by different models, the main causes of which are variations in the modeled rates of ascent and horizontal mixing in the tropical midlower stratosphere. The model runs have been used to compute instantaneous and steady state lifetimes. For chlorofluorocarbons (CFCs) their atmospheric distribution was far from steady state in their growth phase through to the 1980s, and the diagnosed instantaneous lifetime is accordingly much longer. Following the cessation of emissions, the resulting decay of CFCs is much closer to steady state. For 2100 conditions the model circulation speeds generally increase, but a thicker ozone layer due to recovery and climate change reduces photolysis rates. These effects compensate so the net impact on modeled lifetimes is small. For future assessments of stratospheric ozone, use of FBCs would allow a consistent balance between rate of CFC removal and model circulation rate.

CH3CCl3↗

Assimilation of SMAP Brightness Temperature Observations in the GEOS Land–Atmosphere Data Assimilation System

Errors in soil moisture adversely impact the modeling of land–atmosphere water and energy fluxes and, consequently, near-surface atmospheric conditions in atmospheric data assimilation systems (ADAS). To mitigate such errors, a land surface analysis is included in many such systems, although not yet in the currently operational NASA Goddard Earth Observing System (GEOS) ADAS. This article investigates the assimilation of L-band brightness temperature (Tb) observations from the Soil Moisture Active Passive (SMAP) mission in the GEOS weakly coupled land–atmosphere data assimilation system (LADAS) during boreal summer 2017. The SMAP Tb analysis improves the correlation of LADAS surface and root-zone soil moisture versus in situ measurements by ∼0.1–0.26 over that of ADAS estimates; the unbiased root-mean-square error of LADAS soil moisture is reduced by 0.002–0.008 m^3 /m^3 from that of ADAS. Furthermore, the global land average RMSE versus in situ measurements of screen-level air specific humidity (q2m) and daily maximum temperature (T2m_max ) is reduced by 0.05 g/kg and 0.04 K, respectively, for LADAS compared to ADAS estimates. Regionally, the RMSE of LADAS q2m and T2m_max is improved by up to 0.4 g/kg and 0.3 K, respectively. Improvement in LADAS specific humidity extends into the lower troposphere (below ∼700 mb), with relative improvements in bias of 15–25%, although LADAS air temperature bias slightly increases relative to that of ADAS. Finally, the root mean square of the LADAS Tb observation-minus-forecast residuals is smaller by up to ∼0.1 K than in a land-only assimilation system, corroborating the positive impact of the Tb analysis on the modeled land–atmosphere coupling.

microwave remote sensing↗

The value of human data annotation for machine learning based anomaly detection in environmental systems

Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised models, which do not require labels. While academic research has produced a vast array of tools and machine learning models for automated anomaly detection, the research community focused on environmental systems still lacks a comparative analysis that is simultaneously comprehensive, objective, and systematic. This knowledge gap is addressed for the first time in this study, where 15 different supervised and unsupervised anomaly detection models are evaluated on 5 different environmental datasets from engineered and natural aquatic systems. To this end, anomaly detection performance, labelling efforts, as well as the impact of model and algorithm tuning are taken into account. As a result, our analysis reveals the relative strengths and weaknesses of the different approaches in an objective manner without bias for any particular paradigm in machine learning. Most importantly, our results show that expert-based data annotation is extremely valuable for anomaly detection based on machine learning.

54 ENVIRONMENTAL SCIENCES↗

Assessing Uncertainties and Approximations in Solar Heating of the Climate System

In calculating solar radiation, climate models make many simplifications, in part to reduce computational cost and enable climate modeling, and in part from lack of understanding of critical atmospheric information. Whether known errors or unknown errors, the community's concern is how these could impact the modeled climate. The simplifications are well known and most have published studies evaluating them, but with individual studies it is difficult to compare. Here, we collect a wide range of such simplifications in either radiative transfer modeling or atmospheric conditions and assess potential errors within a consistent framework on climate-relevant scales. We build benchmarking capability around a solar heating code (Solar-J) that doubles as a photolysis code for chemistry and can be readily adapted to consider other errors and uncertainties. The broad classes here include: use of broad wavelength bands to integrate over spectral features; scattering approximations that alter phase function and optical depths for clouds and gases; uncertainty in ice-cloud optics; treatment of fractional cloud cover including overlap; and variability of ocean surface albedo. We geographically map the errors in W m -2 using a full climate re-creation for January 2015 from a weather forecasting model. For many approximations assessed here, mean errors are ~2 W m -2 with greater latitudinal biases and are likely to affect a model’s ability to match the current climate state. Combining this work with previous studies, we make priority recommendations for fixing these simplifications based on both the magnitude of error and the ease or computational cost of the fix.

58 GEOSCIENCES↗