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At least 325 records · Page 18

Hourly Electricity Demand Projections for Eight Combined Climate and Socioeconomic Scenarios

This dataset contains 40 years (1980-2019) of simulated historical hourly electricity demand (i.e., loads) and 80 years (2020-2099) of projected hourly loads for 54 Balancing Authorities (BAs) and 48 states plus the District of Columbia. Details about the scenarios and variables included in this dataset are in the readme.pdf file. The two primary models that created the dataset are a version of the Global Change Analysis Model with detailed sectoral resolution over the United States (GCAM-USA) and the Total ELectricity Loads (TELL) model. Links to the model source code and workflow for deriving the dataset are provided in an accompanying meta-repository: https://github.com/IMMM-SFA/burleyson-etal_2023_applied_energy. Projections are for four future climate scenarios that represent combinations of Representative Concentration Pathways (RCPs) 4.5 and 8.5 combined with two levels of climate model sensitivities: rcp45cooler, rcp45hotter, rcp85cooler, and rcp85hotter. The four climate scenarios are crossed with Shared Socioeconomic Pathways (SSPs) 3 and 5 to yield eight different future load projections: rcp45cooler_ssp3, rcp45cooler_ssp5, rcp45hotter_ssp3, rcp45hotter_ssp5, rcp85cooler_ssp3, rcp85cooler_ssp5, rcp85hotter_ssp3, and rcp85hotter_ssp5. The climate scenarios are from the IM3 Thermodynamic Global Warming (TGW) dataset which is linked below in the related metadata. The related metadata also contains links to a repository containing the raw GCAM-USA output files.

Climate Change↗

Hourly Electricity Demand Projections for Eight Combined Climate and Socioeconomic Scenarios

This dataset contains 40 years (1980-2019) of simulated historical hourly electricity demand (i.e., loads) and 80 years (2020-2099) of projected hourly loads for 54 Balancing Authorities (BAs) and 48 states plus the District of Columbia. Details about the scenarios and variables included in this dataset are in the readme.pdf file. The two primary models that created the dataset are a version of the Global Change Analysis Model with detailed sectoral resolution over the United States (GCAM-USA) and the Total ELectricity Loads (TELL) model. Links to the model source code and workflow for deriving the dataset are provided in an accompanying meta-repository: https://github.com/IMMM-SFA/burleyson-etal_2024_applied_energy. Projections are for four future climate scenarios that represent combinations of Representative Concentration Pathways (RCPs) 4.5 and 8.5 combined with two levels of climate model sensitivities: rcp45cooler, rcp45hotter, rcp85cooler, and rcp85hotter. The four climate scenarios are crossed with Shared Socioeconomic Pathways (SSPs) 3 and 5 to yield eight different future load projections: rcp45cooler_ssp3, rcp45cooler_ssp5, rcp45hotter_ssp3, rcp45hotter_ssp5, rcp85cooler_ssp3, rcp85cooler_ssp5, rcp85hotter_ssp3, and rcp85hotter_ssp5. The climate scenarios are from the IM3 Thermodynamic Global Warming (TGW) dataset which is linked below in the related metadata. The related metadata also contains links to a repository containing the raw GCAM-USA output files.

Climate Change↗

Global and Local Helioseismic Studies of Solar Convection Zone Dynamics Using SOI-MDI on SOHO

Our joint collaborative analyses of global mode data to characterize the solar differential rotation (e.g. Thompson et al. 1996, Schou et al. 1998), and most recently to detect and analyze temporal variations in angular velocity Omega profiles both within the convection zone and in the deeper radiative interior (e.g. Howe et al 2000a,b; Toomre et al. 2000), have led to a series of fascinating discoveries. These should be pursued further as the solar cycle continues. The physical deductions being made from these studies have been greatly strengthened by utilizing both SOI-MDI and GONG data in order to have two independent observational realizations of Doppler images spanning a five-year interval, using two separate procedures to determine global mode splittings, and then analyzing those splitting data sets using both RLS and SOLA inversion procedures. There are considerable subtleties in the effects of instrumental response functions and calibrations, sensitivity of peak finding algorithms and their mode leakage estimates, and stochastic variations in mode amplitudes that can all contribute to apparent changes in the Omega profiles being inferred from sequences of helioseismic data. We have come to understand the implications of many of these calibration and analysis steps, greatly aided by frequent multi-week collaborative working sessions in our Helioseismic Analysis Facility (HAF) at JILA involving many members of the SO1 dynamics and inversion team, including most of our Co-Is during the summer months when we hold intensive working sessions. Considerable further focused attention is required in a collaborative setting on such global mode issues as we continue studying the changing sun.

Toomre, Juri↗

Superstructure Optimization of Waste Plastic Pyrolysis, Integrating Thermal, Catalytic, and Plasma Technologies with Machine Learning

Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.

Life cycle assessment↗

GLOBAL REFERENCE ATMOSPHERIC MODELS FOR AEROASSIST APPLICATIONS

Aeroassist is a broad category of advanced transportation technology encompassing aerocapture, aerobraking, aeroentry, precision landing, hazard detection and avoidance, and aerogravity assist. The eight destinations in the Solar System with sufficient atmosphere to enable aeroassist technology are Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Saturn's moon Titan. Engineering-level atmospheric models for five of these targets - Earth, Mars, Titan, Neptune, and Venus - have been developed at NASA's Marshall Space Flight Center. These models are useful as tools in mission planning and systems analysis studies associated with aeroassist applications. The series of models is collectively named the Global Reference Atmospheric Model or GRAM series. An important capability of all the models in the GRAM series is their ability to simulate quasi-random perturbations for Monte Carlo analysis in developing guidance, navigation and control algorithms, for aerothermal design, and for other applications sensitive to atmospheric variability. Recent example applications are discussed.

Duvall, Aleta↗

Robust Algorithm for Estimating Total Suspended Solids (TSS) in Inland and Nearshore Coastal Waters

One of the challenging tasks in modern aquatic remote sensing is the retrieval of near-surface concentrations of Total Suspended Solids (TSS). This study aims to present a Statistical, inherent Optical property (IOP) -based, and muLti-conditional Inversion proceDure (SOLID) for enhanced retrievals of satellite-derived TSS under a wide range of in-water bio-optical conditions in rivers, lakes, estuaries, and coastal waters. In this study, using a large in situ database (N > 3500), the SOLID model is devised using a three-step procedure: (a) water-type classification of the input remote sensing reflectance (R(sub rs)), (b) retrieval of particulate backscattering (b(sub bp)) in the red or near-infrared (NIR) regions using semi-analytical, machine-learning, and empirical models, and (c) estimation of TSS from b(sub bp) via water-type-specific empirical models. Using an independent subset of our in situ data (N = 2729) with TSS ranging from 0.1 to 2626.8 [g/m (exp 3)], the SOLID model is thoroughly examined and compared against several state-of-the-art algorithms (Miller and McKee, 2004; Nechad et al., 2010; Novoa et al., 2017; Ondrusek et al., 2012; Petus et al., 2010). We show that SOLID outperforms all the other models to varying degrees, i.e., from 10 to > 100%, depending on the statistical attributes (e.g., global versus water-type-specific metrics). For demonstration purposes, the model is implemented for images acquired by the MultiSpectral Imager aboard Sentinel-2A/B over the Chesapeake Bay, San-Francisco-Bay-Delta Estuary, Lake Okeechobee, and Lake Taihu. To enable generating consistent, multimission TSS products, its performance is further extended to, and evaluated for, other missions, such as the Ocean and Land Color Instrument (OLCI), Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and Operational Land Imager (OLI). Sensitivity analyses on uncertainties induced by the atmospheric correction indicate that 10% uncertainty in Rrs leads to < 20% uncertainty in TSS retrievals from SOLID. While this study suggests that SOLID has a potential for producing TSS products in global coastal and inland waters, our statistical analysis certainly verifies that there is still a need for improving retrievals across a wide spectrum of particle loads.

Total suspended solids↗

The Relationship Between Constraint and Ductile Fracture Initiation as Defined by Micromechanical Analyses

The use of small laboratory specimens to predict the integrity of large, complex structures relies on the validity of single parameter fracture mechanics. Unfortunately, the constraint loss associated with large scale yielding, whether in a laboratory specimen because of its small size or in a structure because it contains shallow flaws loaded in tension, can cause the breakdown of classical fracture mechanics and the loss of transferability of critical, global fracture parameters. Although the issue of constraint loss can be eliminated by testing actual structural configurations, such an approach can be prohibitively costly. Hence, a methodology that can correct global fracture parameters for constraint effects is desirable. This research uses micromechanical analyses to define the relationship between global, ductile fracture initiation parameters and constraint in two specimen geometries (SECT and SECB with varying a/w ratios) and one structural geometry (circumferentially cracked pipe). Two local fracture criteria corresponding to ductile fracture micromechanisms are evaluated: a constraint-modified, critical strain criterion for void coalescence proposed by Hancock and Cowling and a critical void ratio criterion for void growth based on the Rice and Tracey model. Crack initiation is assumed to occur when the critical value in each case is reached over some critical length. The primary material of interest is A516-70, a high-hardening pressure vessel steel sensitive to constraint; however, a low-hardening structural steel that is less sensitive to constraint is also being studied. Critical values of local fracture parameters are obtained by numerical analysis and experimental testing of circumferentially notched tensile specimens of varying constraint (e.g., notch radius). These parameters are then used in conjunction with large strain, large deformation, two- and three-dimensional finite element analyses of the geometries listed above to predict crack initiation loads and to calculate the associated (critical) global fracture parameters. The loads are verified experimentally, and microscopy is used to measure pre-crack length, crack tip opening displacement (CTOD), and the amount of stable crack growth. Results for A516-70 steel indicate that the constraint-modified, critical strain criterion with a critical length approximately equal to the grain size (0.0025 inch) provides accurate predictions of crack initiation. The critical void growth criterion is shown to considerably underpredict crack initiation loads with the same critical length. The relationship between the critical value of the J-integral for ductile crack initiation and crack depth for SECT and SECB specimens has been determined using the constraint-modified, critical strain criterion, demonstrating that this micromechanical model can be used to correct in-plane constraint effects due to crack depth and bending vs. tension loading. Finally, the relationship developed for the SECT specimens is used to predict the behavior of circumferentially cracked pipe specimens.

Panontin, Tina L.↗

Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R 2 =0.70, P<0.001) and BBC (R 2 =0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon-to-nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to the global C cycle.

54 ENVIRONMENTAL SCIENCES↗

Characterization of Infrasonic Signatures of Earth-Grazing Fireballs as Analogues to Hypersonic Vehicles (Final Report)

Accurate detection, discrimination, and characterization of high-altitude hypersonic events using infrasonic monitoring are critical to planetary defense and global strategic surveillance. This report synthesizes recent advances achieved through rigorous analysis of infrasonic signatures from natural meteoroids, emphasizing shallow entry-angle meteoroids as essentially proxies for artificial hypersonic systems. Meteoroids naturally encompass diverse velocities, trajectories, altitudes, and fragmentation behaviors, enabling systematic validation of empirical period–yield relationships, waveform morphology classifiers, and trajectory-induced back-azimuth deviation models. Integration of adaptive array-processing enhancements within Cardinal software further extends infrasonic detection sensitivity and signal classification reliability. Collectively these advances, based solely on infrasonic signatures or limited optical data, offer robust methodologies for distinguishing natural from artificial hypersonic sources, significantly reducing event geolocation uncertainties and refining source-function determination. The outcomes detailed herein lay foundational groundwork for improved global hypersonic event-surveillance frameworks, supporting improved security preparedness and informing strategic monitoring and defense policies.

54 ENVIRONMENTAL SCIENCES↗

MGS Radio Science Electron Density Profiles: Interannual Variability and Implications for the Martian Neutral Atmosphere

Martian electron density profiles provided by the Mars Global Surveyor (MGS) Radio Science (RS) experiment over the 95-200 km altitude range indicate what the height of the electron peak and the longitudinal structure of the peak height are sensitive indicators of the physical state of the Mars lower and upper atmospheres. The present analysis is carried out on five sets of occultation profiles, all at high solar zenith angles (SZA). Variations spanning 2 Martian years are investigated near aphelion conditions at high northern latitudes (64.7 - 77.6 N) making use of four of these data sets. A mean ionospheric peak height of 133.5 - 135 km is obtained near SZA = 78 - 82 deg.; a corresponding mean peak density of 7.3 - 8.5 x l0(exp 4)/ qu cm is also measured during solar moderate conditions at Mars. Strong wave number 2 - 3 oscillations in peak heights are consistently observed as a function of longitude over the 2 Martian years. These observed ionospheric features are remarkably similar during aphelion conditions 1 Martian year apart. This year-to-year repeatability in the thermosphere-ionosphere structure is consistent with that observed in multiyear aphelion temperature data of the Mars lower atmosphere. Coupled Mars general circulation model (MGCM) and Mars thermospheric general circulation model (MTGCM) codes are run for Mars aphelion conditions, yielding mean and longitude variable ionospheric peak heights that reasonably match RS observations. A tidal decomposition of MTGCM thermospheric densities shows that observed ionospheric wave number 3 features are linked to a non-migrating tidal mode with semidiurnal period (sigma = 2) and zonal wave number 1 (s = -1) characteristics. The height of this photochemically determined ionospheric peak should be monitored regularly.

Bougher, S. W.↗

A NASA-Air Force Precipitation Analysis for Near-Real-Time Operations

This article describes a new precipitation analysis algorithm developed by NASA for time-sensitive operations at the United States Air Force. Implemented as part of the Land Information System—a land modeling and data assimilation software framework—this NASA–Air Force Precipitation Analysis (NAFPA) combines numerical weather prediction model outputs with rain gauge measurements and satellite estimates to produce global, gridded 3-h accumulated precipitation fields at approximately 10-km resolution. Input observations are subjected to quality control checks before being used by the Bratseth analysis algorithm that converges to optimal interpolation. NAFPA assimilates up to 3.5 million observations without artificial data thinning or selection. To evaluate this new approach, a multiyear reanalysis is generated and intercompared with eight alternative precipitation products across the contiguous United States, Africa, and the monsoon region of eastern Asia. NAFPA yields superior accuracy and correlation over low-latency (up to 14 h) alternatives (numerical weather prediction and satellite retrievals), and often outperforms high-latency (up to 3.5 months) products, although the details for the latter vary by region and product. The development of NAFPA offers a high-quality, near-real-time product for use in meteorological, land surface, and hydrological research and applications.

Africa↗

Detailing Cloud Property Feedbacks with a Regime-Based Decomposition

Diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.

climate sensitivity↗

Nonlinear Impact-Echo Test for Quantitative Evaluation of ASR Damage in Concrete

Nonlinear acoustic methods demonstrate high sensitivity for concrete damage evaluation. Among these methods, nonlinear resonance acoustic methods have been widely used in laboratory tests on small scale test samples. In this study, a nonlinear impact-echo (IE) method for concrete damage evaluation was introduced, in which the IE frequency shift was measured at different impact force levels. The nonlinear IE test and the nonlinear impact resonance acoustic spectroscopy (NIRAS) test share similarities in the experimental setup and analysis method. However, the nonlinear IE test excites a local thickness resonance mode of a member instead of the global resonance vibration. Therefore, the analyzed mode is unaffected by member boundary conditions and is applicable to large concrete structural members. To identify the fundamental IE frequencies, multiple impacts were applied along the members. Once the fundamental IE frequencies were determined, the effectiveness of the nonlinear IE method was evaluated by testing seven concrete beam specimens with varying levels of alkali-silica reaction (ASR) damage. In conclusion, the nonlinear IE test demonstrates high sensitivity to concrete damage and allows for quantitative assessment of the damage state of concrete without a baseline measurement.

36 MATERIALS SCIENCE↗

Detailing cloud property feedbacks with a regime-based decomposition

Here, we report diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.

58 GEOSCIENCES↗

On the global dynamics of adaptive systems - A study of an elementary example

The inherent nonlinear character of adaptive systems poses serious theoretical problems for the analysis of their dynamics. On the other hand, the importance of their dynamic behavior is directly related to the practical interest in predicting such undesirable phenomena as nonlinear oscillations, abrupt transients, intermittence or a high sensitivity with respect to initial conditions. A geometrical/qualitative description of the phase portrait of a discrete-time adaptive system with unmodeled disturbances is given. For this, the motions in the phase space are referred to normally hyperbolic (structurally stable) locally invariant sets. The study is complemented with a local stability analysis of the equilibrium point and periodic solutions. The critical character of adaptive systems under rather usual working conditions is discussed. Special emphasis is put on the causes leading to intermittence. A geometric interpretation of the effects of some commonly used palliatives to this problem is given. The 'dead-zone' approach is studied in more detail. The predicted dynamics are compared with simulation results.

Espana, Martin D.↗

Sustainable Recycling of Rare-Earth Elements from NdFeB Magnet Swarf: Techno-Economic and Environmental Perspectives

Rare-earth elements (REEs) are increasingly susceptible to supply risks due to their limited geographical availability and growing demand in clean energy applications such as neodymium-iron-boron (NdFeB) magnets used in electric vehicles and wind turbines. When NdFeB magnets are produced, 6–73% of swarf is generated during the manufacturing steps. This paper presents an innovative technology that utilizes copper nitrate to dissolve REEs in NdFeB magnet swarf and subsequently recovers ~97% of them as mixed rare-earth oxides (REOs) of purity higher than 99.5%. Techno-economic analysis (TEA) and life cycle assessment (LCA) quantified the economic and environmental impacts of adopting the proposed acid-free dissolution technology, projecting a net profit margin of 12–43% and a global warming impact reduction by up to 73% compared to the prevailing REO production routes in China. As copper nitrate is the single largest contributor to the cost and environmental footprint, recycling of copper nitrate was investigated as well as using alternative copper salts (e.g., copper acetate), revealing significant improvements in TEA and LCA results. Dysprosium was a major revenue source, highlighting the importance of targeting electric vehicle magnets that are rich in dysprosium. As the REO market is volatile, sensitivity analysis was employed to evaluate the profitability of the proposed technology under different REO prices over the last 11 years. Overall, our results confirmed the economic and environmental viability of the proposed technology for sustainable recycling of REEs from the NdFeB magnet swarf.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effective Materials Property Information Management for the 21st Century

This paper discusses key principles for the development of materials property information management software systems. There are growing needs for automated materials information management in various organizations. In part these are fueled by the demands for higher efficiency in material testing, product design and engineering analysis. But equally important, organizations are being driven by the need for consistency, quality and traceability of data, as well as control of access to sensitive information such as proprietary data. Further, the use of increasingly sophisticated nonlinear, anisotropic and multi-scale engineering analyses requires both processing of large volumes of test data for development of constitutive models and complex materials data input for Computer-Aided Engineering (CAE) software. And finally, the globalization of economy often generates great needs for sharing a single "gold source" of materials information between members of global engineering teams in extended supply chains. Fortunately, material property management systems have kept pace with the growing user demands and evolved to versatile data management systems that can be customized to specific user needs. The more sophisticated of these provide facilities for: (i) data management functions such as access, version, and quality controls; (ii) a wide range of data import, export and analysis capabilities; (iii) data "pedigree" traceability mechanisms; (iv) data searching, reporting and viewing tools; and (v) access to the information via a wide range of interfaces. In this paper the important requirements for advanced material data management systems, future challenges and opportunities such as automated error checking, data quality characterization, identification of gaps in datasets, as well as functionalities and business models to fuel database growth and maintenance are discussed.

Ren, Weiju↗

Exploring rapidity-even dipolar flow in isobaric collisions at RHIC

Abstract Employing the AMPT transport model, we investigate the response of the rapidity-even dipolar flow ( v 1 even ) and its associated Global Momentum Conservation (GMC) parameterKto structural disparities within 96 Ru and 96 Zr nuclei. We analyze Ru + Ru and Zr + Zr collisions at a center-of-mass energy of s NN = 200 GeV. Our analysis demonstrates that the eccentricityε 1 , v 1 even andKexhibit subtle yet discernible sensitivity to the input nuclear structure distinctions between 96 Ru and 96 Zr isobars. This observation suggests that measuring v 1 even and the GMC parameter in these isobaric collisions could serve as a means to fine-tune the comprehension of their nuclear structure disparities and offer insights to enhance the initial condition assumptions of theoretical models.

Physics↗