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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Codesign Framework for Online Data Analysis and Reduction

In this paper we discuss our design of a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for performing parametric studies on coupled applications. Cheetah facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage vs. compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design choices of Cheetah by using a reaction-diffusion simulation (Gray-Scott) paired with an analysis application to demonstrate initial results of fine-grained process placement on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory.

Mehta, Kshitij↗
DOE OSTI2016

SU-D-201-07: A Survey of Radiation Oncology Residents’ Training and Preparedness to Lead Patient Safety Programs in Clinics

Purpose: Safety and quality has garnered increased attention in radiation oncology, and physicians and physicists are ideal leaders of clinical patient safety programs. However, it is not clear whether residency programs incorporate formal patient safety training and adequately equip residents to assume this leadership role. A national survey was conducted to evaluate medical and physics residents’ exposure to safety topics and their confidence with the skills required to lead clinical safety programs. Methods: Radiation oncology residents were identified in collaboration with ARRO and AAPM. The survey was released in February 2016 via email using REDCap. This included questions about exposure to safety topics, confidence leading safety programs, and interest in training opportunities (i.e. workshops). Residents rated their exposure, skills, and confidence on 4 or 5-point scales. Medical and physics residents responses were compared using chi-square tests. Results: Responses were collected from 56 of 248 (22%) physics and 139 of 690 (20%) medical residents. More than two thirds of all residents had no or only informal exposure to incident learning systems (ILS), root cause analysis (RCA), failure mode and effects analysis (FMEA), and the concept of human factors engineering (HFE). Likewise, 63% of residents had not heard of RO-ILS. Response distributions were similar, however more physics residents had formal exposure to FMEA (p<0.0001) and felt they were adequately trained to lead FMEAs in clinic (p<0.001) than medical residents. Only 36% of residents felt their patient safety training was adequate, and 58% felt more training would benefit their education. Conclusion: These results demonstrate that, despite increasing desire for patient safety training, medical and physics residents’ exposure to relevant concepts is low. Physics residents had more exposure to FMEA than medical residents, and were more confident in leading FMEA. This suggests that increasing resident exposure to specific topics may increase their confidence.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Leverage demand-side policies for energy security

Energy security is a top priority for governments, companies, and households because energy systems and the critical functions that they support are threatened by disruptions from wars, pandemics, climate change, and other shocks (1). More often than not, governments rely on policies focused on energy supply to enhance energy security while generally ignoring demand-side possibilities. Further, the indicators traditionally used to measure energy security are also tilted toward the supply side; this fails to capture the full spectrum of vulnerability to energy crises. Energy security assessments need to reflect the wider benefits of security related interventions more accurately. To that end, we develop a systematic approach to measuring the energy security impacts of policy interventions that explicitly considers energy demand (buildings, transport, and industry). Here, we determine that demand-side actions outperform conventional supply-side approaches at making countries more resilient. Energy demand links more directly than supply to the satisfaction of critical social functions and human well-being that are at the core of energy security. Yet, demand-side perspectives tend to be neglected or underrepresented in analysis and policy debates on energy security. Factors that contribute to this supply-side bias include the traditional sectoral organization of industries and policy institutions along fuels (coal, oil, and gas) and energy forms (electric utilities) as well as the decentralized and multivaried activities characteristic of energy demand (from vehicles to household appliances to manufacturing and more), which leads to a multitude of actors and institutional fragmentation. The basic fundamentals of energy systems and markets, where demand and supply are intricately linked, have also not yet risen from vague awareness to a central organizing principle among policy-makers for structuring the energy security discourse.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

The Genomes of Three Uneven Siblings: Footprints of the Lifestyles of Three Trichoderma Species

SUMMARY The genus Trichoderma contains fungi with high relevance for humans, with applications in enzyme production for plant cell wall degradation and use in biocontrol. Here, we provide a broad, comprehensive overview of the genomic content of these species for “hot topic” research aspects, including CAZymes, transport, transcription factors, and development, along with a detailed analysis and annotation of less-studied topics, such as signal transduction, genome integrity, chromatin, photobiology, or lipid, sulfur, and nitrogen metabolism in T. reesei , T. atroviride , and T. virens , and we open up new perspectives to those topics discussed previously. In total, we covered more than 2,000 of the predicted 9,000 to 11,000 genes of each Trichoderma species discussed, which is >20% of the respective gene content. Additionally, we considered available transcriptome data for the annotated genes. Highlights of our analyses include overall carbohydrate cleavage preferences due to the different genomic contents and regulation of the respective genes. We found light regulation of many sulfur metabolic genes. Additionally, a new Golgi 1,2-mannosidase likely involved in N -linked glycosylation was detected, as were indications for the ability of Trichoderma spp. to generate hybrid galactose-containing N -linked glycans. The genomic inventory of effector proteins revealed numerous compounds unique to Trichoderma , and these warrant further investigation. We found interesting expansions in the Trichoderma genus in several signaling pathways, such as G-protein-coupled receptors, RAS GTPases, and casein kinases. A particularly interesting feature absolutely unique to T. atroviride is the duplication of the alternative sulfur amino acid synthesis pathway.

Schmoll, Monika↗
DOE OSTI2018

Group III Acceptors with Shallow and Deep Levels in Silicon Carbide: ESR and ENDOR Studies

Results of investigations of Group III acceptors (B, Al, and Ga) in crystals of silicon carbide using the most informative electron spin resonance and electron nuclear double resonance methods are presented. Structural models of the acceptors with shallow and deep levels are considered. In addition to the data obtained earlier, studies using high-frequency magnetic resonance were obtained, which allowed revealing orthorhombic deviations from the axial symmetry for the deep acceptors; theoretical analysis explains experimentally found shifts of g factors for the deep acceptors arising due to the orthorhombic deviations, which appear probably due to the Jahn–Teller effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Optimizing Fast Charging and Wetting in Lithium-Ion Batteries with Optimal Microstructure Patterns Identified by Genetic Algorithm

To sustain the high-rate current required for fast charging electric vehicle batteries, electrodes must exhibit sufficiently high effective ionic diffusion. Additionally, to reduce battery manufacturing costs, wetting time must decrease. Both of these issues can be addressed by structuring the electrodes with mesoscale pore channels. However, their optimal spatial distribution, or patterns, is unknown. Herein, a genetic algorithm has been developed to identify these optimal patterns using a CPU-cheap proxy distance-based model to evaluate the impact of the added pore networks. Both coin-cell and pouch cell form factors have been considered for the wetting analysis, with their respective electrolyte infiltration mode. Regular hexagonal and mud-crack-like patterns, respectively, for fast charging and fast wetting were found to be optimal and have been compared with pre-determined, easier to manufacture, patterns. The model predicts that using cylindrical channels arranged in a regular hexagonal pattern is ∼6.25 times more efficient for fast charging as compared to grooved lines with both structuring strategies being restricted to a 5% electrode total volume loss. The model also shows that only a very limited electrode volume loss (1%–2%) is required to dramatically improve the wetting (5–20 times) compared to an unstructured electrode.

25 ENERGY STORAGE↗
DOE OSTI2018

An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

This paper presents a satellite-observation-based evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmosphere Model, version 5 (CAM5), simulations, one with the standard parameterization schemes (CAM5–Base) and the other with the Cloud Layers Unified by Binormals scheme (CAM5–CLUBB). When comparing the direct model outputs, the authors find that CAM5–CLUBB produces more MBL clouds, a smoother transition from stratocumulus to cumulus, and a tighter correlation between in-cloud water and cloud fraction than CAM5–Base. In the model-to-observation comparison using the COSP satellite simulators, the authors find that both simulations capture the main features and spatial patterns of the observed cloud fraction from MODIS and shortwave cloud radiative forcing (SWCF) from CERES. However, CAM5–CLUBB suffers more than CAM5–Base from a problem that can be best summarized as “undetectable” clouds (i.e., a significant fraction of simulated MBL clouds are thinner than the MODIS detection threshold). This issue leads to a smaller COSP–MODIS cloud fraction and a weaker SWCF in CAM5–CLUBB than the observations and also CAM5–Base in the tropical descending regions. Finally, the authors compare modeled radar reflectivity with CloudSat observations and find that both simulations, especially CAM5–CLUBB, suffer from an excessive drizzle problem. Further analysis reveals that the subgrid precipitation enhancement factors in CAM5–CLUBB are unrealistically large, which makes MBL clouds precipitate too excessively, and in turn results in too many undetectable thin clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Casing-integrity mapping using top-casing electrodes and surface based EM fields

Wellbore integrity is of paramount importance to subsurface resource extraction, energy storage and hazardous waste disposal. We introduce a simple non-invasive technology for casing integrity screening, based on the continuity of electrical current flow. Applying low frequency current to a wellhead, with a distant return electrode, produces a casing current dependent on the properties and depth extent of the well casing as well as the background formation. These currents in-turn generate surface electrical fields that can be captured in a radial profile and be used to analyze properties of the well casing. Numerical modeling results reveal a strong relation of the electric field to the casing properties and depth extent of the well. A small breakage in the casing produces a profile coincident to a cased well with a completion depth above the break. A corroded patch, where the casing conductivity is reduced, also alters the field profiles and its depth may be estimated by comparing to the profile expected from the well completion diagrams. The electric field profiles are also strongly dependent on background resistivity distributions and on whether the well was drilled using water or oil-based drilling fluids. We validate the proof of concept in a field experiment, where we applied currents at the wellheads of two wells with different casing lengths. The two profiles were similar in appearance but offset in amplitude by more than a factor of 5, consistent with the theoretical analysis as well as the 3D modeling results. These results demonstrate that our proposed approach has promise for mapping the general casing condition without well intervention. This approach can be a practical and effective tool for rapidly screening a number of wells before expensive logging-based technologies are employed for casing inspection in detail.

58 GEOSCIENCES↗
DOE OSTI2019

Femoral Fracture in Primary Soft-Tissue Sarcoma of the Thigh and Groin Treated with Intensity-Modulated Radiation Therapy: Observed versus Expected Risk

Purpose: This study was designed to compare the observed risk of femoral fracture in primary soft-tissue sarcoma (STS) of the thigh/groin treated with intensity-modulated radiation therapy (IMRT) to expected risk calculated using the Princess Margaret Hospital (PMH) nomogram. Methods: Expected femoral fracture risk was calculated by using the PMH nomogram. Cumulative risk of fracture was estimated by using Kaplan–Meier statistics. Prognostic factors were assessed with univariate and multivariate analysis using Cox’s stepwise regression. Results: Between February 2002 and December 2010, 92 consecutive eligible patients were assessed. Median follow-up was 73 months (106 months in surviving patients). IMRT was delivered preoperatively (50 Gy) in 13 (14%) patients and postoperatively in 79 (86%) patients (median dose, 63 Gy; range, 59.4–66.6 Gy). The observed crude risk of fractures was 6.5% compared with 25.6% expected risk from the nomogram; the cumulative risk of fracture using IMRT at 5 years was 6.7% (95% CI 2.8–16.0%). The median time to fracture was 23 months (range, 6.9–88.6). Significant predictors of fracture on univariate analysis were age ≥ 60 years (p = 0.03), tumor location in the anterior thigh (p = 0.008), and periosteal stripping to > 20 cm (p < 0.0001). On multivariate analysis, age ≥ 60 years and periosteal stripping > 20 cm retained significance (p = 0.04 and p = 0.009, respectively). Conclusions: In this study, the cumulative risk of femur fracture in patients treated with IMRT (6.7%) is less than the expected risk using the PMH nomogram (25.6%). Established predictors of femur fracture, such as gender, tumor size, and dose of RT, seem to have less impact on fracture risk when using IMRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Enhanced lightning strike protection using vertically oriented carbon fiber melded with conventional carbon fiber-reinforced composite and its validation through damage analysis

Lightning strike protection (LSP) is one of the prime factors in aerospace and wind industries concerning safety, enhanced service life, and reduced downtime. To ensure better LSP, high electrical conductivity is required to dissipate the current, which is always a challenge for polymer composites due to the inherent insulating nature of the polymer matrix. Conventional carbon fiber-reinforced composites (CFRP) offer electrical conductivity in the planar direction while the vertical i.e. through-thickness conductivity still remains a challenge. Having been motivated by this fact, we have fabricated CFRP interleaved with vertically oriented CF (Z-fiber) for the lightning strike test (100 kA). A paint was applied to mimic the actual service condition of the composite laminates. We have prepared two Z-fiber composites: (a) Z-1 containing one Z-fiber layer on the top along with conventional CF layers and (b) Z-5 containing five interleaved Z-fiber layers and compared the properties with conventional CFRP (Z-0). Interestingly, even a single Z-fiber layer (Z-1) showed lower damage (visual damage diameter 22 mm) than Z-0 (visual damage diameter 26 mm). Z-5 displayed the lowest damage (visual damage diameter 16.7 mm), which was further confirmed by cross-sectional optical microscopy. Improved LSP was attributed to the higher through-thickness electrical conductivity in the case of Z-5 (9 times with respect to Z-0) reflecting a lower electrical anisotropy for Z-fiber composites. The residual mechanical property after the lightning test was analyzed through the flexural test, and the retention of flexural strength and modulus was 66% and 86%, respectively for Z-5 showing a significant improvement in comparison to Z-0 (>40% for both).

Saha, Subhabrata↗
DOE OSTI2017

Summary of FY17 ParaChoice Accomplishments

As part of analysis support for FCTO, Sandia assesses the factors that influence the future of FCEVs and Hydrogen in the US vehicle fleet. Using ParaChoice, we model competition between FCEVs, conventional vehicles, and other alternative vehicle technologies in order to understand the drivers and sensitivities of adoption of FCEVs. ParaChoice leverages existing tools such as Autonomie (Moawad et al., 2016), AEO (U.S. Energy Information Administration, 2016), and the Macro System Model (Ruth et al., 2009) in order to synthesize a complete picture of the co-evolution of vehicle technology development, energy price evolution, and hydrogen production and pricing, with consumer demand for vehicles and fuel. We then assess impacts of FCEV market penetration and hydrogen use on green- house gas (GHG) emissions and petroleum consumption, providing context for the role of policy, technology development, infrastructure, and consumer behavior on the vehicle and fuel mix through parametric and sensitivity analyses.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Assessing the PACE of California residential solar deployment: Impacts of Property Assessed Clean Energy programs on residential solar photovoltaic deployment in California, 2010-2015

A new study by Berkeley Lab found that residential Property Assessed Clean Energy (R-PACE) programs increased deployment of residential solar photovoltaic (PV) systems in California, raising it by about 7-12% in cities that adopt these programs. R-PACE is a financing mechanism that uses a voluntary property tax assessment, paid off over time, to facilitate energy improvements and, in some jurisdictions, water and resilience measures. While previous studies demonstrated that early, regional R-PACE programs increased solar PV deployment, this new analysis is the first to demonstrate these impacts from the large, statewide R-PACE programs dominating the California market today, which use private capital to fund the upfront costs of the improvements. Berkeley Lab estimated the impacts using econometric techniques on two samples: -Large cities only, allowing annual demographic and economic data as control variables -All California cities, without these annual data Analysis of both samples controls for several factors other than R-PACE that would be expected to drive solar PV deployment. We infer that on average, cities with R-PACE programs were associated with greater solar PV deployment in our study period (2010-2015). In the large cities sample, solar PV deployment in jurisdictions with R-PACE programs was higher by 1.1 watts per owner-occupied household per month, or 12%. Across all cities, solar PV deployment in jurisdictions with R-PACE programs was higher by 0.6 watts per owner-occupied household per month, or 7%. The large cities results are statistically significant at conventional levels; the all-cities results are not. The estimates imply that the majority of solar PV deployment financed by R-PACE programs would likely not have occurred in their absence. Results suggest that R-PACE programs have increased PV deployment in California even in relatively recent years, as R-PACE programs have grown in market share and as alternate approaches for financing solar PV have developed. The U.S. Department of Energy’s Building Technologies Office supported this research.

14 SOLAR ENERGY↗
DOE OSTI2017

Interaction between Heat Pump Water Heaters or Other Internal Point Source Loads and a Central Heating System

Water heating represents approximately 18% of residential energy consumption, or 4.6 quadrillion Btus of source energy use annually (EIA 2009). Heat pump water heaters (HPWHs) offer an efficient option for residential water heating, with the ability to reduce water heating energy consumption by up to 63%. Previous research has demonstrated the laboratory performance of HPWHs and has shown savings of 43 to 62% on water heating energy consumption are possible, based on field tests (Ecotope 2015). In order to achieve such high efficiencies, HPWHs employ a refrigeration cycle to move heat from the ambient air into the water. Therefore, when HPWHs are installed in conditioned space, they will remove heat from that space which can help the HVAC system in the cooling season and require additional energy from the HVAC system in the heating season. This project provides an unbiased evaluation of the space conditioning interactions between a HPWH and the heating system in several locations throughout the home to further our understanding of the impact that HPWHs have on space conditioning loads. This report explores the HPWH interaction factor from several perspectives: (1) a theoretical analysis, (2) a review of previous literature, and (2) an experimental assessment. The experiments were conducted in PNNL’s side-by-side Lab Homes, which provide a platform for evaluating energy-saving and grid-responsive technologies in a controlled environment. The PNNL Lab Homes are two factory-built homes installed on PNNL’s campus in Richland, Washington. The homes represent existing homes, which account for approximately 99% of occupied homes in the U.S. These 1500 ft2 homes have three bedrooms, two bathrooms, and are equipped with 7.7 HSPF heat pump and an electric forced air furnace. Both homes have R-22 floors, R-11 walls and R-22 ceiling insulation levels, with double-pane clear glass windows. The results of this experiment verified that the energy use of the HVAC system increases as a point source cooling load, like a HPWH, is moved closer to the thermostat. The opposite is also true, as a point source heating load is moved closer to the thermostat, the heating load decreases. The results show between 30-40% difference between the interaction that this type of load has when it is placed in the master bathroom compared to the living room for the PNNL Lab Homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

ParaChoice Model

Sandia National Laboratories' (SNL's) Parametric Choice Model (ParaChoice) supports the U.S. Department of Energy Vehicle Technologies Office (VTO) mission. Using early-stage research as input, ParaChoice supports the informed development of technology that will improve affordability of transportation, while encouraging innovation and reducing dependence on petroleum. Analysis with ParaChoice enables exploration of key factors that influence consumer choice, as well as projecting the effects of technology, fuel, and infrastructure development for the vehicle fleet mix. Because of the distinct differences between requirements, needs, and use patterns for light duty vehicles (LDVs) relative to heavy duty vehicles (HDVs), this project separately models the dynamics of each of these segments to accurately characterize the factors that influence technology adoption.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

First Look Fund - An Early-Stage Aligned Intermediary to Enhance the Flow of Private Capital into Energy Companies (Final Technical Report)

The technologies required to advance society into a cleaner, better future will come from a broad range of scientific disciplines including materials science, chemistry, physics, and biology. The innovations will rely on scientific breakthroughs rather than software innovation and can be referred to as “hardtech.” These new technology developments will have vast implications across most industrial sectors: energy, materials, manufacturing, electronics, life sciences, etc. The majority of these scientific breakthroughs will be produced and developed by startup companies, which are best suited for high-risk, early-stage development work. However, a large funding gap exists between lab-scale scientific research of the startup world and industrial-scale commercialization. Activate Global, Inc (Activate), a 501(c)3 nonprofit, fills one part of this gap with the Activate Fellowship program1.To fully bridge the gap between lab and market, additional and aligned capital sources are needed. Through this project, Activate’s goals were: Research the recent history (2005-2015) of hardtech investing to discover the driving forces behind positive and negative outcomes from the viewpoint of investors.; Create a database of “technology pathways” categorized by specific technology areas and showing what technology milestones would be needed to be attractive to a partner or acquirer and what resources were available to achieve those goals.; Build a financial model supported by the data acquired that would show attractive returns were possible in early-stage hardtech investing.; Create an investment thesis around the financial model to show how attractive returns could be achieved in an early-stage hardtech-focused fund.; Publish a paper with a qualitative comparative analysis to help investors better understand driving factors of outcomes.; Share these findings with asset managers not currently investing in early-stage hardtech to attract partners to execute the investment strategy.; Implement the investment strategy and begin investing in early-stage hardtech companies through a new vehicle: First Look Fund. Through this research, Activate created a database of nearly 200 hardtech companies that exited via an M&A transaction between 2005 and 2015. Much of the data Activate obtained was nonpublic information and therefore, the database was anonymized. Activate also created the technology pathways database to help new early-stage hardtech companies define milestones, technology objectives and potential resources. Activate created a financial model with a legal structure showing that market-rate returns were possible, created an investment thesis around that model, and then shared these findings with potential partners. Finally, Activate’s research was used to publish a paper with Stanford on driving factors behind financial outcomes that will help investors better guide their portfolios. While Activate was not able to launch the First Look Fund during the project timeline, mostly due to the fallout from COVID-19 (global economic shocks decreasing interest in first time funds, inability to meet potential investors in person), the research has created enough interest for Activate to continue pursuing the goals of the project, showing the potential feasibility of the endeavor. Regardless of Activate’s ability to execute on the investment strategy, the resulting research has been downloaded, viewed, and referenced by investors and becomes another tool to encourage investment in the early-stage hardtech space.

14 SOLAR ENERGY↗
DOE OSTI2021

Absorptive corrections to the forward elastic proton-proton analyzing power A N

In the RHIC Polarized Atomic Hydrogen Gas Jet Target (HJET) measurements of the protonproton analyzing power A N (t), absorptive corrections to the electromagnetic form factor were not considered in the data analysis. Recently, these corrections were evaluated theoretically. However, the results were presented in form of integral expressions which were calculated numerically. In this note, the expressions are simplified to make them more suitable for the HJET data analysis. Possible effect of the absorptive corrections in the A N (t) measurement is discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States, 2022 Edition

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The latest edition of the report focuses on systems installed through year-end 2021, and is based on data from roughly 2.5 million systems. New to the report this year is an expanded coverage of paired PV-plus-storage systems, including details on system design and pricing trends. The report describes trends related to: -Project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership -Median installed-price trends, both nationally and by state, including preliminary data for first half of 2022 -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive and econometric analysis

14 SOLAR ENERGY↗