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At least 1,081 records · Page 60

Measuring Degradation of Fielded Systems on an Ongoing Basis with RdTools

The solar investment community needs up-to-date and data-derived system degradation rates to use in financial models that calculate the risk and expectation of energy revenue. To date, the majority of financial models choose degradation rates from past studies that are limited and may not be representative of future solar assets (systems) they are financing. As the solar industry expands in all sectors (residential, commercial, and utility), there is a growing amount of energy production available to analyze. With the help of the open source degradation analysis code (RdTools) it is now possible to derive degradation on an ongoing basis and continuously provide up-to-date durability statistics to the investment community. Ongoing and accurate statistics of fielded photovoltaic systems allows financial stakeholders to constrain energy revenue projections, lower financial risk, and increase the bankability of solar. This poster will present considerations and software engineering best practices to encourage data owners to measure degradation of their own photovoltaic assets on an ongoing basis. This poster will also preview an upcoming DOE-funded kWh Analytics degradation project which involves applying RdTools analysis on kWh Analytics’ industry database, aggregating results across variables such as weather, hardware, system configurations etc., and sharing the aggregated results with the broader community.

14 SOLAR ENERGY↗

Polarimetric radar and aircraft observations of saggy bright bands during MC3E

Polarimetric radar observations increasingly are used to understand cloud microphysical processes, which is critical for improving their representation in cloud and climate models. In particular, there has been recent focus on improving representations of ice collection processes (e.g., aggregation, riming), as these influence precipitation rate, heating profiles, and ultimately cloud life cycles. However, distinguishing these processes using conventional polarimetric radar observations is difficult, as they produce similar fingerprints. This necessitates improved analysis techniques and integration of complementary data sources. Furthermore, the Midlatitude Continental Convective Clouds Experiment (MC3E) provided such an opportunity.

54 ENVIRONMENTAL SCIENCES↗

Chemical crystallography by serial femtosecond X-ray diffraction

Abstract Inorganic–organic hybrid materials represent a large share of newly reported structures, owing to their simple synthetic routes and customizable properties 1 . This proliferation has led to a characterization bottleneck: many hybrid materials are obligate microcrystals with low symmetry and severe radiation sensitivity, interfering with the standard techniques of single-crystal X-ray diffraction 2,3 and electron microdiffraction 4–11 . Here we demonstrate small-molecule serial femtosecond X-ray crystallography (smSFX) for the determination of material crystal structures from microcrystals. We subjected microcrystalline suspensions to X-ray free-electron laser radiation 12,13 and obtained thousands of randomly oriented diffraction patterns. We determined unit cells by aggregating spot-finding results into high-resolution powder diffractograms. After indexing the sparse serial patterns by a graph theory approach 14 , the resulting datasets can be solved and refined using standard tools for single-crystal diffraction data 15–17 . We describe the ab initio structure solutions of mithrene (AgSePh) 18–20 , thiorene (AgSPh) and tethrene (AgTePh), of which the latter two were previously unknown structures. In thiorene, we identify a geometric change in the silver–silver bonding network that is linked to its divergent optoelectronic properties 20 . We demonstrate that smSFX can be applied as a general technique for structure determination of beam-sensitive microcrystalline materials at near-ambient temperature and pressure.

36 MATERIALS SCIENCE↗

Energy consumption and charging load profiles from long-haul truck electrification in the United States

Abstract The urgent need to decarbonize the transportation sector combined with falling battery prices has spurred industry and policy interest in long-haul truck electrification. The charging behavior and resulting loads from electrified long-haul freight trucks are crucial for the smooth operation of the electric grid and have far-reaching environmental impacts (e.g., greenhouse gas and other air pollutant emissions). However, the aggregate energy impact of a fleetwide shift to electrified long-haul freight trucking has not been explored. This study combines electric truck design scenarios, bottom-up truck weight modeling, vehicle energy modeling, large-scale truck traffic data, and simulation of likely operation and charging behaviors to estimate end-use energy consumption and location-specific hourly charging loads for a national fleet of long-haul electric trucks. Relative to a fleet of future diesel trucks, electrification would reduce direct end-use energy consumption by 0.9 × 10 18 J (0.9 quadrillion BTU), but electrification might increase life cycle energy consumption depending on the electricity source. The electricity required to charge long-haul electric trucks is equivalent to five percent of annual electricity consumption in the United States (US). The simulated truck charging loads peak during the day across the US grid regions, but the charging peaks’ exact timing is sensitive to when trucks are dispatched for operation. The load shapes suggest that electric trucks’ charging loads can coincide with peaks in solar power generation, and planning could enable on- or off-site integration between truck charging stations and renewable electricity generation.

Tong, Fan (ORCID:0000000346613956)↗

A High-Throughput Solver for Marginalized Graph Kernels on GPU

Here, we present the design and optimization of a solver for efficient and high-throughput computation of the marginalized graph kernel on General Purpose GPUs. The graph kernel is computed using the conjugate gradient method to solve a generalized Laplacian of the tensor product between a pair of graphs. To cope with the large gap between the instruction throughput and the memory bandwidth of the GPUs, our solver forms the graph tensor product on-the-fly without storing it in memory. This is achieved by using threads in a warp cooperatively to stream the adjacency and edge label matrices of individual graphs by small square matrix blocks called tiles, which are then staged in registers and the shared memory for later reuse. Warps across a thread block can further share tiles via the shared memory to increase data reuse. We exploit the sparsity of the graphs hierarchically by storing only non-empty tiles using a coordinate format and nonzero elements within each tile using bitmaps. We propose a new partition-based reordering algorithm for aggregating nonzero elements of the graphs into fewer but denser tiles to further exploit sparsity. We carry out extensive theoretical analyses on the graph tensor product primitives for tiles of various density and evaluate their performance on synthetic and real-world datasets. Our solver delivers three to four orders of magnitude speedup over existing CPU-based solvers such as GraKeL and GraphKernels. The capability of the solver enables kernel-based learning tasks at unprecedented scales.

97 MATHEMATICS AND COMPUTING↗

Fleet Utilization

A key goal of NextGen Profiles' fleet utilization study was to conduct a comprehensive, strategic, and standardized assessment of the operational behavior and utilization patterns across EV and EVSE production-ready fleets. These data-driven insights were intended to inform current fleet management strategies and support future infrastructure planning, ensuring the effective adoption and adaptation of the growing EV fleet market. The study applied a series of metrics defined in NextGen Profiles to evaluate diverse fleet operations across various use cases, emphasizing trends in charging, routing, and other critical behaviors. The fleet utilization dataset includes these three sets of metrics from 17 EV fleets, each consisting of a wide range of vehicle types and operational categories, as well as two EVSE fleets. Data were collected from a variety of sources and reformatted into a unified structure before metric computation, ensuring consistency and comparability across all fleets. To protect confidentiality, all fleet metadata are anonymized, and the publicly released metric datasets are aggregated to an hourly cadence.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Case for the Use of Active Social Media in Nonproliferation and Nuclear Security

A great amount of attention and consideration is being directed at possible applications of social media in many challenging areas. The use of social media has already shown its importance in the area of disaster response, where, each citizen is essentially acting as a sensor in reporting local conditions. In the aggregate, valuable information is obtained to enable a more effective response as well as provide timely information to those in the disaster area. No one needs to be trained to understand what constitutes a disaster, so a social media data stream from the public is literally always active and ready to engage. A similar but more focused approach is the use of crowdsourcing for science, where specific challenges in areas such as mathematics, astronomy, and biology are posted to social media and solved by the crowd.

Schanfein, Mark J.↗

Edible oil structures at low and intermediate concentrations. II. Ultra-small angle X-ray scattering of in situ tristearin solids in triolein

Ultra-small angle X-ray scattering has been used for the first time to elucidate, in situ, the aggregation structure of a model edible oil system. The three-dimensional nano- to micro-structure of tristearin solid particles in triolein solvent was investigated using 5, 10, 15, and 20% solids. Three different sample preparation procedures were investigated: two slow cooling rates of 0.5°/min, case 1 (22 days of storage at room temperature) and case 2 (no storage), and one fast cooling of 30°/min, case 3 (no storage). The length scale investigated, by using the Bonse-Hart camera at beamline ID-15D at the Advanced Photon Source, Argonne National Laboratory, covered the range from 300 Å to 10 μm. The unified fit and the Guinier-Porod models in the Irena software were used to fit the data. The former was used to fit 3 structural levels. Level 1 structures showed that the primary scatterers were essentially 2-dimensional objects for the three cases. The scatterers possessed lateral dimensions between 1000 and 4300 Å. This is consistent with the sizes of crystalline nanoplatelets present which were observed using cryo-TEM. Level 2 structures were aggregates possessing radii of gyration, R{sub g2} between 1800 Å and 12000 Å and fractal dimensions of either D{sub 2}=1 for case 3 or 1.8≤D{sub 2}≤2.1 for case 1 and case 2. D{sub 2} = 1 is consistent with unaggregated 1-dimensional objects. 1.8 ≤ D{sub 2} ≤ 2.1 is consistent with these 1-dimensional objects (below) forming structures characteristic of diffusion or reaction limited cluster-cluster aggregation. Level 3 structures showed that the spatial distribution of the level 2 structures was uniform, on the average, for case 1, with fractal dimension D{sub 3}≈3 while for case 2 and case 3 the fractal dimension was D{sub 3}≈2.2, which suggested that the large-scale distribution had not come to equilibrium. The Guinier-Porod model showed that the structures giving rise to the aggregates with a fractal dimension given by D{sub 2} in the unified fit level 2 model were cylinders described by the parameter s≈1 in the Guinier-Porod model. The size of the base of these cylinders was in agreement with the cryo-TEM observations as well as with the results of the level 1 unified fit model. By estimating the size of the nanoplatelets and understanding the structures formed via their aggregation, it will be possible to engineer novel lipids systems that embody desired functional characteristics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Molecular dynamics simulations of zinc oxide solubility: From bulk down to nanoparticles

The solubility of metal oxides is one of the key descriptors for the evaluation of their potential toxic effects, both in the bulk form and in nanoparticulated aggregates. Current work presents a new methodology for the in silico assessment of the solubility of metal oxides, which is demonstrated using a well-studied system, ZnO. The calculation of the solubility is based on statistical thermodynamics tools combined with Density Functional Tight Binding theory for the evaluation of the free energy exchange during the dissolution process. Models of small ZnO clusters are used for describing the final dissolved material, since the complete ionic dissolution of ZnO is hindered by the formation of O2- anions in solution, which are highly unstable. Results show very good agreement between the computed solubility values and experimental data for ZnO bulk, up to 0.5 mg·L-1 and equivalents of 50 g·L-1 for the free Zn2+ cation in solution. However, the reference model for solid nanoparticles formed by free space nanoparticles can only give a limited quantitative solubility evaluation for ZnO nanoparticles.

DFTB modelling↗

An empirical analysis of supply offers in the ERCOT operating reserves markets

Here, this paper seeks to improve theoretical and empirical understanding of supplier dynamics in wholesale markets for operating reserves, which have been understudied compared to energy markets. We begin by identifying several economic factors that unit owners may consider when submitting offers into operating reserves auctions in two-stage, co-optimized markets common across much of North America. Next, we analyze historical offer data from the Electric Reliability Council of Texas (ERCOT) market to assess whether actual reserve market behavior aligns with expectations based on economic theory, as well as with commonly used assumptions in electricity market modeling efforts. We find that the aggregate supply of operating reserves in ERCOT varies meaningfully over time, becoming more expensive during summer afternoons, which is consistent with theoretical expectations but contradicts the typical modeling assumption of temporally invariant reserve offers. Analysis of offers made by individual units uncovers additional insights, such as the existence of large offer pattern differences by unit owner and the tendency of battery storage units to submit very low offer prices. We conclude by discussing how our findings can be integrated into electricity market modeling assumptions to improve alignment with observed operating reserve offer inputs and pricing outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Identifying Disadvantaged Communities in the United States: An Energy-Oriented Mapping Tool that Aggregates Environmental and Socioeconomic Burdens

This paper defines a policy-relevant nationwide composite index to identify communities disproportionately impacted by environmental, energy, and climate injustices in the United States. We review existing vulnerability indicators and indices to assess the tradeoffs of different design parameters, including variable selection, geographic unit, dimensionality reduction, weighting, and aggregation methods. From this methodological review, we create the first nationwide, census tract-level index of cumulative burden that includes energy-relevant indicators alongside climate, social, environmental, and economic indicators, and is flexible to the inclusion of additional data sources. We provide a summary of the sources of inputs used to develop a definition for "disadvantaged communities" that can be used to prioritize energy investments. We discuss use-cases for this index including the implementation of the Justice40 Initiative, which calls for 40% of certain federal clean energy benefits to flow to disadvantaged communities in the United States. We use our results to examine historic allocations of federal energy investments and show that communities that we identify as disadvantaged received about 37% fewer funds per capita than non-disadvantaged communities.

cumulative burden↗

Stereotactic Body Radiation Therapy for Locally Advanced Pancreatic Cancer: A Systematic Review and Pooled Analysis of 19 Trials

Purpose: Although surgery is the standard of care for resectable pancreatic cancer (PC), standard-dose chemoradiation therapy and chemotherapy alone are suitable for patients with unresectable disease. Stereotactic body radiation therapy (SBRT) is an alternative, focused local therapy that delivers high radiation doses within a few fractions to the cancer, sparing the surrounding critical tissue. We performed a systematic review and pooled analysis of published trials to evaluate the efficacy and safety of this emerging treatment modality. Methods and Materials: We searched the Cochrane Central Register of Controlled Trials, PubMed, EMBASE, SCOPUS, the Web of Science, and CINAHL for publications regarding SBRT for locally advanced PC. The 1-year overall survival (OS) rate was the primary endpoint, and the median OS, 2-year OS rate, 1-year locoregional control (LRC) rate, and grade 3 to 4 toxicities were the secondary endpoints. A multivariate random-effects meta-analysis was performed to calculate the aggregated OS rates at 1 and 2 years and the 1-year LRC rate. Results: A total of 19 studies, encompassing 1009 patients, were included in the present analysis. The pooled 1-year OS was 51.6% in 13 trials with data available. The median OS ranged from 5.7 to 47 months (median 17). The LRC rate at 1 year was 72.3%. Overall, the occurrence of severe adverse events did not exceed 10%. LRC appeared to correlate with the total SBRT dose and the number of fractions. Conclusions: The advantages of SBRT in terms of treatment time, satisfactory OS, and LRC indicate that it is an effective option for inoperable PC. However, a definitive validation of this treatment modality in large randomized studies is required, owing to the nonrandomized nature of the included studies and the limitations of small single-center series that include mixed populations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗

MEP: Mobility Energy Productivity Metric

In response to the need to assess fundamental improvements in mobility as technology provides new modes, methods, and opportunities in urban areas to connect people with goods, services, and employment, a mobility-energy productivity score (MEPS) has been developed. The MEPS fundamentally measures the potential of a multi-modal system to connect a person to a variety of services and activities that define a high-quality of life. The MEPS is measured relative to the convenience and energy needed to provide connectivity. Fundamentally derived from accessibility theory, the MEPS advances practice by using readily available travel time data (either from web-based APIs or outputs from an urban transportation model) combined with established parameters that reflect the energy intensity of various travel modes, and relative frequency of activity engagement. The construction of the MEPS allows for aggregation and disaggregation to the appropriate spatial, modal, and trip purpose resolution, as analysis needs dictate. The MEPS could be used to compare alternative futures related to technology, infrastructure investment, or policy, providing a much needed tool for planners, researchers, and analysts. In other words, the metric measures how efficiently connected a place is.

Hou, Yi↗

Quantifying Diurnal Cloud Radiative Effects by Cloud Type in the Tropical Western Pacific

Cloud radiative effects are examined using long-term datasets collected at the three Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facilities in the tropical western Pacific. We quantify the surface radiation budget, cloud populations, and cloud radiative effects by partitioning the data by cloud type, time of day, and as a function of large scale modes of variability such as El Niño Southern Oscillation (ENSO) phase and wet/dry seasons at Darwin. The novel facet of our analysis is that we break aggregate cloud radiative effects down by cloud type across the diurnal cycle. The Nauru cloud populations and subsequently the surface radiation budget are strongly impacted by ENSO variability whereas the cloud populations over Manus only shift slightly in response to changes in ENSO phase. The Darwin site exhibits large seasonal monsoon related variations. We show that while deeper convective clouds have a strong conditional influence on the radiation reaching the surface, their limited frequency reduces their aggregate radiative impact. The largest source of shortwave cloud radiative effects at all three sites comes from low clouds. We use the observations to demonstrate that potential model biases in the amplitude of the diurnal cycle and mean cloud frequency would lead to larger errors in the surface energy budget compared to biases in the timing of the diurnal cycle of cloud frequency. Our results provide solid benchmarks to evaluate model simulations of cloud radiative effects in the tropics.

54 ENVIRONMENTAL SCIENCES↗

Utility Managed Distributed Energy Resources Intelligent Community - UDERMS iCommunity (Final Technical Report)

The Utility Managed Distributed Energy Resources Intelligent Community (UDERMS iCommunity) project, led by PacifiCorp and supported by the U.S. Department of Energy’s Building Technologies Office (Award No. DEEE0009782), aimed to demonstrate an integrated, utility-managed “behind-the-meter” distributed energy resource (DER) program connecting multifamily, commercial, institutional, and industrial buildings to deliver grid services and improve energy efficiency.

14 SOLAR ENERGY↗

Longitudinal data analysis in support of functional stability concepts for leachate management at closed municipal landfills

Highlights: • Longitudinal data analysis using a mixed-effects regression model. • Dataset consisted of a total of 1402 samples from 101 closed municipal landfills. • Target analytes and classes generally showed predictable degradation trends. • Validates historical studies focused on macro organic indicators such as BOD. • BOD can serve as “gateway” indicator for planning leachate management. - Abstract: Landfill functional stability provides a target that supports no environmental threat at the relevant point of exposure in the absence of active control systems. With respect to leachate management, this study investigates “gateway” indicators for functional stability in terms of the predictability of leachate characteristics, and thus potential threat to water quality posed by leachate emissions. Historical studies conducted on changes in municipal solid waste (MSW) leachate concentrations over time (longitudinal analysis) have concentrated on indicator compounds, primarily chemical oxygen demand (COD) and biochemical oxygen demand (BOD). However, validation of these studies using an expanded database and larger constituent sets has not been performed. This study evaluated leachate data using a mixed-effects regression model to determine the extent to which leachate constituent degradation can be predicted based on waste age or operational practices. The final dataset analyzed consisted of a total of 1402 samples from 101 MSW landfills. Results from the study indicated that all leachate constituents exhibit a decreasing trend with time in the post-closure period, with 16 of the 25 target analytes and aggregate classes exhibiting a statistically significant trend consistent with well-studied indicators such as BOD. Decreasing trends in BOD concentration after landfill closure can thus be considered representative of trends for many leachate constituents of concern.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗