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At least 649 records · Page 36

Stratigraphic Identification with Airborne Electromagnetic Methods at the Hanford Site, Washington

Stratigraphic units can influence the fate and transport of subsurface contaminants within groundwater. Units having coarse-grained sediments act as preferential flow pathways, and therefore can accelerate the transport of contaminants to reach human and ecological receptors. At legacy waste sites, detailed knowledge of subsurface stratigraphy can be used for effective monitoring and remediation planning to help minimize risk to human health and the environment. Airborne electromagnetic (AEM) methods can non-invasively provide information on kilometer-scale or larger subsurface stratigraphic features and fill informational gaps in directly sampled data from sparsely located boreholes. In this paper, we present inversion results of a 412 line-km frequency-domain AEM survey to delineate subsurface stratigraphic features at the Hanford Site, located in southeastern Washington State. The inversion was performed using a massively parallel 3D electromagnetic modeling and inversion code, where the modeling is based on solving frequency-domain Maxwell’s equations using an unstructured-mesh finite-element method and the inversion employs a Gauss-Newton optimization scheme. The results are compared to an underlying geologic framework model (GFM), built by interpolating contact depths of stratigraphic units interpreted from site borehole datasets. In areas with good borehole coverage, the inversion results show a good match with the GFM to a depth of about 60 m. Outside of these areas, the inversion results exhibit inconsistencies from the assumptions made to create the GFM, demonstrating that the AEM survey results can be used to improve the understanding of the geological conceptual model.

47 OTHER INSTRUMENTATION↗

Unlocking nighttime mobility: Land use and accessibility in public transit for night commuters

Night commuters are integral to urban transportation systems. Essential services such as healthcare and manufacturing rely on workers who travel at night, and reliable mobility options are crucial for them. A gap exists in understanding how land use and accessibility influence public transportation use among night commuters. This study addresses this gap by using public data to explore land use and accessibility factors that affect night commuters' public transportation use in New York State. We investigated (1) the demographic characteristics of night commuters; (2) the influence of land use and accessibility on nighttime public transportation use; and (3) potential improvements to increase public transportation use and their impact. We combined data from the National Household Travel Survey with the Smart Location Database to link home locations with land use characteristics. Using logistic regression, we found that although females are generally less likely to be night commuters, they are more likely to use public transportation. Longer commute distances are associated with higher use of public transportation. Increasing job density along fixed-guideway transit routes and improving overall job accessibility via public transportation significantly enhances public transportation use among night commuters. In conclusion, this research provides actionable insights for public transportation agencies and urban planners to support night commuters, improving access and encouraging nighttime employment.

Job accessibility↗

Multifunctional transition metal doped titanium dioxide reduced graphene oxide composites as highly efficient adsorbents and photocatalysts

A series of novel, mesoporous transition metal doped titanium dioxide-reduced graphene oxide composites are synthesized where the dopants were Mn, Co, Ni, Mo, and W. An in-situ synthesis method was used which involves a green, economic, hydrothermal process which can be scaled up easily. The composites show high surface areas (165–245 m 2 /g) and monomodal pore size distributions with average pore diameters in the range of 3–5 nm. The homogeneous distributions of the dopants are seen in SEM-EDX mapping data. The indirect band gaps of the composite materials are in the range of 2.20–2.48 eV. The composites show excellent dye adsorption activities where 100% adsorption of Rhodamine B occurs within 5 min when Mo–TiO 2 /rGO composite is used. Furthermore, the adsorbed dye can either be desorbed or photocatalytically degraded and the composite is reusable up to 10 cycles without losing significant activity. Mo–TiO 2 /rGO composite showed excellent adsorption of both cationic and anionic dyes at neutral pH.

36 MATERIALS SCIENCE↗

Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO 2 Flux and its Inter-Annual Variability

Drylands occupy ~40% of the land surface and are thought to dominate global carbon (C) cycle inter-annual variability (IAV). Therefore, it is imperative that global terrestrial biosphere models (TBMs), which form the land component of IPCC earth system models, are able to accurately simulate dryland vegetation and biogeochemical processes. However, compared to more mesic ecosystems, TBMs have not been widely tested or optimized using in situ dryland CO 2 fluxes. Here, for this work, we address this gap using a Bayesian data assimilation system and 89 site-years of daily net ecosystem exchange (NEE) data from 12 southwest US Ameriflux sites to optimize the C cycle parameters of the ORCHIDEE TBM. The sites span high elevation forest ecosystems, which are a mean sink of C, and low elevation shrub and grass ecosystems that are either a mean C sink or “pivot” between an annual C sink and source. We find that using the default (prior) model parameters drastically underestimates both the mean annual NEE at the forested mean C sink sites and the NEE IAV across all sites. Our analysis demonstrated that optimizing phenology parameters are particularly useful in improving the model's ability to capture both the magnitude and sign of the NEE IAV. At the forest sites, optimizing C allocation, respiration, and biomass and soil C turnover parameters reduces the underestimate in simulated mean annual NEE. Our study demonstrates that all TBMs need to be calibrated for dryland ecosystems before they are used to determine dryland contributions to global C cycle variability and long-term carbon-climate feedbacks.

59 BASIC BIOLOGICAL SCIENCES↗

Measurement and microscopic description of odd–even staggering of charge radii of exotic copper isotopes

Nuclear charge radii globally scale with atomic mass number A as A 1/3 , and isotopes with an odd number of neutrons are usually slightly smaller in size than their even-neutron neighbours. This odd–even staggering, ubiquitous throughout the nuclear landscape1, varies with the number of protons and neutrons, and poses a substantial challenge for nuclear theory. Here, we report measurements of the charge radii of short-lived copper isotopes up to the very exotic 78 Cu (with proton number Z = 29 and neutron number N = 49), produced at only 20 ions s –1 , using the collinear resonance ionization spectroscopy method at the Isotope Mass Separator On-Line Device facility (ISOLDE) at CERN. We observe an unexpected reduction in the odd–even staggering for isotopes approaching the N = 50 shell gap. To describe the data, we applied models based on nuclear density functional theory and A-body valence-space in-medium similarity renormalization group theory. Through these comparisons, we demonstrate a relation between the global behaviour of charge radii and the saturation density of nuclear matter, and show that the local charge radii variations, which reflect the many-body polarization effects, naturally emerge from A-body calculations fitted to properties of A ≤ 4 nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Electricity use in big area additive manufacturing of fiber-reinforced polymer composites

In recent years, additive manufacturing (AM), especially large-format additive manufacturing (LFAM), has gained momentum in the manufacturing industry. While LFAM offers benefits over conventional manufacturing processes, such as minimizing material waste and providing vast geometric freedom, assessing its sustainability remains challenging due to limited data, particularly on energy consumption. Most existing data pertain to small-scale or desktop AM and are not directly applicable to LFAM. In this study, we conducted real-time measurements of electricity usage for a type of LFAM known as big area additive manufacturing (BAAM), which typically uses fiber-reinforced polymer pellets as feedstock. We collected electricity usage data from fifteen printing jobs over two months in an industrial production setting. These data fill the existing gap and can be reused to enhance the community’s understanding of LFAM electricity usage, support further research, and promote sustainable development in advanced manufacturing technologies.

ecology↗

Spatial Impacts of Electric Vehicle Charging on Power Grid Stability: A Downtown Atlanta Case Study

The rapid increase in electric vehicle (EV) charging demand poses a potential risk to power grid stability, particularly as the spatial distribution of this demand remains underexplored. Existing research often focuses on technical optimization models while overlooking the geographic and human dynamics that affect energy consumption. This study addresses this gap by incorporating mobility data to estimate both building energy use and EV charging demand while also considering geographic factors for a better understanding of grid load. Using agent-based simulations and the Open-Source Distribution System Simulator, the study evaluates the effect of various EV penetration scenarios on grid voltage and unbalance. The results show that, although voltage remains within acceptable limits at lower EV penetration rates, significant voltage drop and unbalance occur as EV penetration exceeds 40%, particularly in residential areas with high charging demand. This study offers a framework for integrating spatial analysis and mobility data in power network simulations, providing insights for future EV infrastructure planning.

Pan, Melrose [ORNL] (ORCID:000000031627448X)↗

The very forward CASTOR calorimeter of the CMS experiment

The physics motivation, detector design, triggers, calibration, alignment, simulation, and overall performance of the very forward CASTOR calorimeter of the CMS experiment are reviewed. The CASTOR Cherenkov sampling calorimeter is located very close to the LHC beam line, at a radial distance of about 1 cm from the beam pipe, and at 14.4 m from the CMS interaction point, covering the pseudorapidity range of $-$6.6 $\lt\eta\lt$ $-$5.2. It was designed to withstand high ambient radiation and strong magnetic fields. The performance of the detector in measurements of forward energy density, jets, and processes characterized by rapidity gaps, is reviewed using data collected in proton and nuclear collisions at the LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Using a Large Language Model as a Building Block to Generate Usable Validation and Verification Suite for OpenMP

In the HPC area, both hardware and software move quickly. Often new hardware is developed and deployed, the corresponding software stack, including compilers and other tools, are under active development while leading edge software developers are working to port and tune their applications, all at the same time. While the software ecosystem is in flux, one of the key challenges for users is obtaining insight into the state of implementation of key features in the programming languages and models their applications are using – whether they have been implemented, and whether the implementation conforms to the specification, especially for newly implemented features (less tested by widespread use). OpenMP is one of the most prominent shared memory programming models used for on-node programming in HPC. With the shift towards accelerators (such as GPUs and FPGAs) and heterogeneous programming OpenMP features are getting more complex. It is natural to ask whether generative AI approaches, and large language models (LLMs) in particular, can help in producing validation and verification test suites to allow users better and faster insights into the availability and correctness of OpenMP features of interest. In this work, we explore the use of ChatGPT-4 to generate a suite of tests for OpenMP features. We have chosen a set of directives and clauses, a total of 78 combinations, which first appeared in OpenMP 3.0 (released in May 2008) but are also relevant for accelerators. We prompted ChatGPT to generate tests in the C and Fortran languages, for both host (CPU) and device (accelerator). On the Summit super-computer using the GNU implementation, we found that, of the 78 generated tests 67 C tests and 43 Fortran tests compiled successfully and fewer than those executed to completion. On further analysis we show that not all generated tests are valid. We document the process, results, and provide detailed analysis regarding the quality of tests generated. With the aim of providing input to a production quality validation and verification suite, we manually implement the corrections required to make the tests valid according to the current OpenMP specification. We quantify this effort as small, medium, or large, and record the lines of code changed to correct the invalid tests. With the corrected tests we validate recent implementations from HPE, AMD, and GNU on the Frontier supercomputer. Our experiment and subsequent analysis show that although LLMs are capable of producing HPC specific codes, they are limited by their understanding of the deeper semantics and restrictions of programming models such as OpenMP. Unsurprisingly more commonly used features have better support, while some OpenMP 3.0 directives such as sections and tasking are not universally supported on accelerators. We demonstrate that successful compilation and execution to completion are inadequate metrics for evaluating generated code and that, at this time, commodity LLMs require expert intervention for code verification. This points to gaps in the training data that is currently available for HPC. We demonstrate that with "small" effort 37% of generated invalid C tests and 63% of generated invalid Fortran tests could be corrected. This improves productivity of test generation as we circumvent writing from scratch and the common programming errors associated with it.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗

SFAI and Related Technologies

Researchers at Los Alamos have developed Swept-Frequency Acoustic Interferometry (SFAI) a technology that enables businesses to have greater control over their industrial processes, allowing for significantly improved efficiency by giving operators vital composition and flow rate information in real-time. This technology fills the information gap by providing this data non-invasively and at a fraction of the cost of traditional composition meters. SFAI uses engineered ultrasound and advanced signal processing to characterize multiphase flow (e.g., liquids, gasses, multi-phase mixtures) and other flows inside sealed containers and flow pipes. By being both low-cost and non-invasive, this technology is set to disrupt the current oil field monitoring state-of-the-art by providing individual well-level composition data, compared to the multi-well macroscopic information that is currently available. We are seeking a commercialization partner to license the technology or fund us through a Cooperative Research and Development Agreement (CRADA) to a further develop a usable product for commercial purposes.

03 NATURAL GAS↗

National Ignition Facility 192 beam 3w power sensor

NIF requires additional laser diagnostic capabilities to support existing missions and drive performance of the laser to higher powers and energies. There exists a current gap in laser power data on the facility due to the subset of beamlines that are measurement capable. Additionally, as NIF increases the radiation yield on target experiments, the performance of the current laser diagnostic 3w power sensor system has been steadily decreasing. The degradation of the current system is not well understood and needs to be characterized to facilitate any new system design.

42 ENGINEERING↗

Clean Energy Education and Training Resources and Opportunities in New York's Southern Tier Region

New York's Southern Tier Region is experiencing high growth and investment in the clean energy sector and is anticipating more jobs to come in energy efficiency, renewable energy, and manufacturing in the coming years. The Network for a Sustainable Tomorrow (NEST) is a nonprofit network of programs working to develop a regional backbone system for education and training programs as well as curricula to support the workforce needed for the region's growing industries to succeed. Through its participation in the US Department of Energy's Better Buildings Workforce Accelerator, NEST requested technical assistance in conducting a landscape and needs assessment of the region's existing clean energy education and workforce development assets. This report supports NEST's efforts by providing a baseline of clean energy employment data, an inventory and gap analysis of the education and workforce development assets currently available and serving the Southern Tier Region, and case studies of innovative and successful regional clean energy education and workforce coalitions from around the county.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Investigations into the Ternary NaF-KF-UF4 Salt System – Phase A

A knowledge gap exists in the data and understanding of fresh fuel salt and irradiated multicomponent fuel salt systems thermophysical properties. Quantifying these properties is necessary for the design and construction of test reactors, as well as the licensing of future commercial molten-salt reactors. To facilitate thermal property determination on a proposed fuel salt composition for Seaborg Technologies, several samples containing depleted uranium tetrafluoride (UF4), sodium fluoride (NaF), and potassium fluoride (KF) were blended, and a melt temperature analysis was performed. From the melting temperature analysis, it was determined that sample Seaborg-7, a ternary salt composition of 26.4UF4-24.7KF-48.9NaF (mol%), was very near a ternary eutectic point. Therefore, thermal properties such as melting temperature, salt stability, density, heat capacity, thermal diffusivity, and viscosity were experimentally determined on the Seaborg-7 salt. These measurements document the baseline properties of fresh fuel salt as a function of temperature, where future experiments on irradiated fuel salt will provide a holistic perspective on the change of thermophysical properties during reactor operations. Several precision instruments were used to collect property data, and instrument calibrations and data collection were performed and documented in a standardized and reproducible manner with meticulous detail. This process ensured that the measurement procedures and resulting data can readily be duplicated elsewhere. The Seaborg-7 salt was shown to be stable at temperatures up to 900°C, as no mass change was observed upon repeated heating and cooling. The peak melting temperature was determined to be 547°C (557°C endset). The enthalpy of fusion (??H?_fus^o) was determined to be 167.5 ± 2.7 J/g while the enthalpy of crystallization (??H?_c^o) was determined to be -147.8 ± 13.3 J/g. In addition to the eutectic melting peak, upon heating, several pre eutectic peaks were observed, occurring at 470°C (onset) and 499°C (peak). Specific heat capacity measurements showed a slightly increasing trend with respect to temperature in the solid phase, while the liquid-specific heat capacity showed a somewhat flat trend with an average value of 106.1 ± 1.24 J/mol·K between 600 to 800°C. Three independent trials using the Seaborg-7 salt determined the density to be ?(T) = 4.908 – 0.000363·T(°C), validated between 32 to 200°C, and ?(T) = 4.808 – 0.00113·T(°C), validated between ~575 to 850°C. Thermal diffusivity was determined for the liquid state and is represented by the linear equation y = 0.1581 + 0.000207·T(°C) between 550 to 850°C. The viscosity was determined from 600 to 800°C and is represented by the exponential fit equation, ? (mPa·s) = 736.58e^(-0.006·T(°C)). This report documents the conclusion of fuel salt thermophysical property measurements for the Seaborg SPP, Phase A project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NO x ), and sulfur dioxide (SO 2 ), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution. To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities. Version 1.0 of LOCAETA displays the estimated primary PM 2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH 3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics. LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles

Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption. This paper reviews the state-of-the-art of EV energy consumption models, aiming to provide guidance for future development of EV applications. Here, we summarize influential variables of EV energy consumption into four categories: vehicle component, vehicle dynamics, traffic and environment related factors. We classify and discuss EV energy consumption models in terms of modeling scale (microscopic vs. macroscopic) and methodology (data-driven vs. rule-based). Our review shows trends of increasing macroscopic models that can be used to estimate trip-level EV energy consumption and increasing data-driven models that utilized machine learning technologies to estimate EV energy consumption based on large volume real-world data. We identify research gaps for EV energy consumption models, including the development of energy estimation models for modes other than personal vehicles (e.g., electric buses, electric trucks, and electric non-road vehicles); the development of energy estimation models that are suitable for applications related to vehicle-to-grid integration; and the development of multi-scale energy estimation models as a holistic modeling approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Axially grooved heat pipe study

A technology evaluation study on axially grooved heat pipes is presented. The state-of-the-art is reviewed and present and future requirements are identified. Analytical models, the Groove Analysis Program (GAP) and a closed form solution, were developed to facilitate parametric performance evaluations. GAP provides a numerical solution of the differential equations which govern the hydrodynamic flow. The model accounts for liquid recession, liquid/vapor shear interaction, puddle flow as well as laminar and turbulent vapor flow conditions. The closed form solution was developed to reduce computation time and complexity in parametric evaluations. It is applicable to laminar and ideal charge conditions, liquid/vapor shear interaction, and an empirical liquid flow factor which accounts for groove geometry and liquid recession effects. The validity of the closed form solution is verified by comparison with GAP predictions and measured data.

Source record↗

Kasei Vallis of Mars: Dating the Interplay of Tectonics and Geomorphology

Crater density age dates on more than 250 small geomorphic surfaces in the Kasei Region of Mars show clusterings indicative of times of peak geomorphic and tectonic activity. Kasei Vallis is part of a 300 km wide channel system breaching a N-S trending ancient basement high (+50,000 crater age) separating the Chryse Basin from the Tharsis Volcanic Province of Mars. The basement high was covered by a least 3 groups of probable volcanic deposits. Major regional fracturing took place at age 4,000 to 5,000 and was immediately followed by deposition of regional volcanics of the Fesenkov Plains (age 3,000 to 4,200). Younger clusterings of dates in the 900 to 1,500 and 500 to 700 range represent only minor modification of the basic tectonic geomorphic landform. The data suggest that Kasei gap is a structurally controlled breach of a buried ridge by a rather brief episode of fluvial activity.

Wise, D. U.↗