Search NASA⌕ Search

SEARCH · Search NASA

Results for “COVID-19 modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Surface-Enhanced Raman Spectroscopy Combined with Multivariate Analysis for Fingerprinting Clinically Similar Fibromyalgia and Long COVID Syndromes

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10–20% of individuals following COVID-19 infection. FM and LC share similarities with regard to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCAs) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n = 48 FM and n = 46 LC) and volumetric absorptive micro-sampling tips (VAMS, n = 39 FM and n = 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra were acquired using SERS with gold nanoparticles (AuNPs). Soft independent modelling of class analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity, achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNP SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Earth's record-high greenness and its attributions in 2020

Terrestrial vegetation is a crucial component of Earth's biosphere, regulating global carbon and water cycles and contributing to human welfare. Despite an overall greening trend, terrestrial vegetation exhibits a significant inter-annual variability. The mechanisms driving this variability, particularly those related to climatic and anthropogenic factors, remain poorly understood, which hampers our ability to project the long-term sustainability of ecosystem services. Here, in this work, by leveraging diverse remote sensing measurements, we pinpointed 2020 as a historic landmark, registering as the greenest year in modern satellite records from 2001 to 2020. Using ensemble machine learning and Earth system models, we found this exceptional greening primarily stemmed from consistent growth in boreal and temperate vegetation, attributed to rising CO 2 levels, climate warming, and reforestation efforts, alongside a transient tropical green-up linked to the enhanced rainfall. Contrary to expectations, the COVID-19 pandemic lockdowns had a limited impact on this global greening anomaly. Our findings highlight the resilience and dynamic nature of global vegetation in response to diverse climatic and anthropogenic influences, offering valuable insights for optimizing ecosystem management and informing climate mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Sweden surpasses the UNAIDS 95-95-95 target: estimating HIV-1 incidence, 2003 to 2022

Background: Sweden reached the UNAIDS 90–90–90 target in 2015. It is important to reassess the HIV epi- demiological situation due to ever-changing migration patterns, the roll-out of PrEP and the impact of the COVID-19 pandemic. Aim: We aimed to assess the pro- gress towards the UNAIDS 95–95–95 targets in Sweden by estimating the proportion of undiagnosed people with HIV (PWHIV) and HIV incidence trends. Methods: We used routine laboratory data to inform a biomarker model of time since infection. When available, we used previous negative test dates, arrival dates for PWHIV from abroad and transmission modes to inform our incidence model. We also used data collected from the Swedish InfCareHIV register on antiretroviral therapy (ART). Results: The yearly incidence of HIV in Sweden decreased after 2014. In part, this was because the fraction of undiagnosed PWHIV had decreased almost twofold since 2006. After 2015, three of four PWHIV in Sweden were diagnosed within 1.9 and 3.2 years after infection among men who have sex with men and in heterosexual groups, respectively. While 80% of new PWHIV in Sweden acquired HIV before immigration, they make up 50% of the current PWHIV in Sweden. By 2022, 96% of all PWHIV in Sweden had been diag- nosed, and 99% of them were on ART, with 98% virally suppressed. Conclusions: By 2022, about half of all PWHIV in Sweden acquired HIV abroad. Using our new biomarker model, we assess that Sweden has reached the UNAIDS goal at 96–99–98.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

The Italian Summer Students Program at Fermilab and other US Laboratories: 40 years of education in particle physics and technology

Since 1983 the Italian groups collaborating with Fermilab (US) have been running a 2-month summer training program for Master students. While in the first year the program involved only 4 physics students, in the following years it was extended to engineering students. Many students have extended their collaboration with Fermilab with their Master Thesis and PhD. The program has involved more than 600 Italian students from more than 20 Italian universities. Each intern is supervised by a Fermilab Mentor responsible for the training program. Training programs spanned from Tevatron, CMS, Muon (g-2), Mu2e and SBN (MicroBooNE, Icarus, and SBND) and DUNE design and data analysis, development of particle detectors, design of electronic and accelerator components, development of infrastructures and software for tera-data handling, quantum computing and research on superconductive elements and accelerating cavities. In 2015 the University of Pisa included the program within its own educational programs. Summer Students are enrolled at the University of Pisa for the duration of the internship and at the end of the internship they write summary reports on their achievements. After positive evaluation by a University of Pisa Examining Board, interns are acknowledged 6 ECTS credits for their Diploma Supplement. The program was paused in 2020 and 2021 due to the COVID-19 pandemic, but it resumed in 2022. From 2022 to 2024, a total of 60 students participated in the nine-week training at Fermilab. We are currently organizing the 2025 program. This paper provides an overview of the program, which can serve as a model for other interested laboratories.

Barzi, Emanuela [Ohio State U.]↗
DOE OSTI2024

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don’t yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Evidence of Completion of Milestone 3: Experimental Testbed

Construction and deployment of the experimental testbed encountered scheduling delays, and completion was subsequently further delayed by curtailment of LANL operations due to the COVID-19 pandemic. Between March and October, LANL was in a state of “Limited Operations” such that only certain “mission-critical” work was performed with approximately 25% on-site staffing. In spite of this, much of the lab space preparation was executed and the five initial model house” units were constructed and installed during this period. Still, the pace of construction was impacted by difficulty in coordinating personnel and minimizing contact between workers. Currently, LANL is in the mode of “Normal Operations with Maximum Telework,” which continues to limit the availability of on-site personnel. Nevertheless, Milestone 3 is now complete. This document describes the experiment as it is deployed and provides status for each task for this milestone.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Bayesian Calibration of Stochastic Agent Based Model via Random Forest

Agent-based models (ABM) provide an excellent framework for modeling outbreaks and interventions in epidemiology by explicitly accounting for diverse individual interactions and environments. However, these models are usually stochastic and highly parametrized, requiring precise calibration for predictive performance. When considering realistic numbers of agents and properly accounting for stochasticity, this high-dimensional calibration can be computationally prohibitive. This paper presents a random forest-based surrogate modeling technique to accelerate the evaluation of ABMs and demonstrates its use to calibrate an epidemiological ABM named CityCOVID via Markov chain Monte Carlo (MCMC). The technique is first outlined in the context of CityCOVID's quantities of interest, namely hospitalizations and deaths, by exploring dimensionality reduction via temporal decomposition with principal component analysis (PCA) and via sensitivity analysis. The calibration problem is then presented, and samples are generated to best match COVID-19 hospitalization and death numbers in Chicago from March to June in 2020. Further, these results are compared with previous approximate Bayesian calibration (IMABC) results, and their predictive performance is analyzed, showing improved performance with a reduction in computation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Quantum-enhanced detection of viral cDNA via luminescence resonance energy transfer using upconversion and gold nanoparticles

Abstract The COVID-19 pandemic has profoundly impacted global economies and healthcare systems, revealing critical vulnerabilities in both. In response, our study introduces a sensitive and highly specific detection method for cDNA, leveraging Luminescence Resonance Energy Transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs), and achieves a detection limit of 242 fM for SARS-CoV-2 cDNA. This innovative sensing platform utilizes UCNPs conjugated with one primer and AuNPs with another, targeting the 5′ and 3′ ends of the SARS-CoV-2 cDNA, respectively, enabling precise differentiation of mismatched cDNA sequences and significantly improving detection specificity. Through rigorous experimental analysis, we established a quenching efficiency range from 10.4 % to 73.6 %, with an optimal midpoint of 42 %, thereby demonstrating the superior sensitivity of our method. Our work uses SARS-CoV-2 cDNA as a model system to demonstrate the potential of our LRET-based detection method. This proof-of-concept study highlights the adaptability of our platform for future diagnostic applications. Instrumental validation confirms the synthesis and formation of AuNPs, addressing the need for experimental verification of the preparation of nanomaterial. Our comparative analysis with existing SARS-CoV-2 detection methods revealed that our approach provides a low detection limit and high specificity for target cDNA sequences, underscoring its potential for targeted COVID-19 diagnostics. This study demonstrates the superior sensitivity and adaptability of using UCNPs and AuNPs for cDNA detection, offering significant advances in rapid, accessible diagnostic technologies. Our method, characterized by its low detection limit and high precision, represents a critical step forward in developing next-generation biosensors for managing current and future viral outbreaks. By adjusting primer sequences, this platform can be tailored to detect other pathogens, contributing to the enhancement of global healthcare responsiveness and infectious disease control.

Esmaeili, Shahriar [Institute for Quantum Science ↗
DOE OSTI2025

A Hands-On Curriculum for Training in HPC Cluster Deployment and Management

This paper presents the design, methodology, and outcomes of the High-Performance Computing Technologies (HPCT) course, a hands-on training program focused on the system-side of HPC cluster deployment and administration. Delivered as part of the Master in High Performance Computing (MHPC) program, the course introduces students to key concepts in cluster configuration, including networking, software stack provisioning, job scheduling, and monitoring. Initially taught in person, the course was transitioned to an online format during the COVID-19 pandemic. This shift led to the development of openly available instructional material and a flipped-classroom approach that continues to support both in-person and hybrid delivery. All course materials are publicly available at www.hpc.temple.edu/mhpc/hpc-technology/index.html. By documenting the structure, infrastructure, and evolution of HPCT, this paper offers a model for accessible HPC system training that supports workforce development in computational science.

Posada Correa, Fernando [ORNL] (ORCID:000000022565↗
DOE OSTI2026

New Norms or Old Habits: Evaluating Interlinked Trajectories of Online Shopping and Work Commute Post-Pandemic

The COVID-19 pandemic has significantly shifted travel behaviors, with major changes observed in online shopping and travel to work. Despite considerable research into pandemic-induced changes in travel behavior, it remains uncertain whether these new patterns have persisted or reverted to pre-pandemic norms. This study addresses this uncertainty by evaluating whether shifts in online shopping and work travel during the pandemic have become permanently ingrained in individuals' daily routine. Leveraging data from the 2022 National Household Travel Survey, a bivariate ordered probit model is employed to analyze changes in online shopping and work travel - whether they have increased, decreased, or remained stable compared to pre-pandemic levels across different population segments. The analysis finds that the pandemic did not significantly alter online shopping for home delivery and travel to work for the majority of society. However, a substantial portion of respondents reported increased online shopping for home delivery and reduced travel to work compared to pre-pandemic levels, with online shopping trends appearing more permanent. Segment-wise analysis and model results indicate heterogeneity in behavioral shifts with females engaging more in online shopping, while zero-vehicle households are traveling less to work, compared to pre-pandemic levels. Additionally, increase in online shopping frequency is significantly and negatively correlated with decrease in traveling to work. These findings highlight the need for improved digital infrastructure, flexible work policies, and integrated transportation solutions tailored to evolving demographic and socioeconomic needs in the post-pandemic era. Additionally, the study calls for integrating passenger and freight movement in a single framework rather than treating them in silos.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Microchannel-based Membrane-less Extraction of Li from Unconventional Lithium Sources & the Separation of REE

This final report provides an overview of the Project's entire duration, covering July 1, 2021 to December 31, 2023. It primarily focuses on the achievements, technological developments, and unique challenges the team faced while working on separating and extracting Lithium from produced waters. The project's primary aim was to create an integrated, high-throughput, membrane-less, and modular microfluidic platform that could extract Lithium from unconventional sources. We have successfully met all goals and milestones envisioned in the SOPO document. The most critical primary milestones, including the Go-No-Go milestone (refer to the Gantt chart in the Appendices), were successfully accomplished. We demonstrated phase separation (>90%) and extraction (>85%) performance in the MPSE using synthetic, and representative produced water composition feed at 50 ml/min total flow through MPSE 36. We have also performed a parametric study of the MPSE operations, beyond the scope of SOPO, exploring operating conditions of current and broader interest. The extended investigation of operational parameters is concurrent with our efforts to seek further development of the MPSE technology beyond the scope of the Project. Along these lines of development, we have made efforts to be responsive to DOE calls for technological developments of other types of resources (beyond PW) for the recovery of Critical Materials and higher TRL development (beyond TRL 4). During the work on this Project, we developed and implemented three innovative technical approaches that emerged from our efforts to successfully meet the Project milestones. The innovative & original technical approaches developed and implemented in this Project are now the contributions to process engineering that could be clearly credited to the Project. First, Convergent Design Approach is a comprehensive feedforward & feedback loop of four design phases: i) design for functionality, ii) design for manufacturing, iii) design for sustainability, and iv) design for market. Next was Process Intensification. A major aim of this Project was to create an innovative phase separation & extraction microscale-based technology for Li separation – thus the words microchannel-based in the Project title. A microscale-based technology is intrinsically in the center of the Process Intensification domain as defined by its unique principles. Therefore, Process Intensification was implicitly envisioned in the Project’s SOPO. Lastly, Time Scale Analysis is a novel tool for discovering the needs and directions of Process Intensification implementations in any process technology. This Project is fully credited for developing and implementing the three novel technical approaches mentioned above. These are general contributions to process engineering that emerged from this Project. Beyond the original SOPO scope, the OSU-U.Pitt research group utilized a Convergent Design methodology, integrating first-principles mathematical modeling with experimental validation on the Minimum Development Vehicle. By creating these Digital Twins, the team rapidly assessed manufacturing iterations to support TEA analysis. This framework further enabled the development of advanced Surface Modification Techniques, where hydrophobic and oleophobic coating strategies were optimized via Digital Twin tools and validated through rigorous 100-hour longevity testing. TEA Analysis: The closing efforts of this Project were focused on the TEA analysis. TEA analysis had two primary functions: i) enabling critical assessments of design variations withing 10 the Concurrent Design Approach, thus enabling evolution of the MPSE design to reach faster- better-cheaper alternatives; and ii) to create a bridge between the accomplishments of this Project and future projects of higher TRL, beyond TRL 6 level. It is important to note that the TEA model created in the Project stirred the technological solutions for the recovery of critical materials toward a vision of a very profitable modular plant that has unique zero-waste water discharge signature. More importantly, thanks to our experimental performance data and conservative assumptions, the TEA model predicts minimal technological and investment risks. Low cost of a modular unit of a nominal capacity of [1000 tons of Li 2 CO 3 /year] positions the MPSE based technology within the reach of community investors, thus offering a paradigm shift in the development of critical technologies. The project successfully navigated two primary challenges: solvent selection and manufacturing adaptation. Restricted by the SOPO to existing literature for lithium recovery, the team identified a critical need for a "material excellence program" to develop next-generation solvents, eventually concluding with a preliminary investigation into promising Ionic Liquids (ILs). Simultaneously, COVID-19 supply chain disruptions forced a pivot from traditional manufacturing to advanced additive methods at ATAMI-OSU. By transitioning from stainless steel to 3D-printed polymer substrates, the team achieved a transformative three-order-of- magnitude reduction in manufacturing costs and compressed prototyping timelines from several months to just two days. The MPSE technology offers significant energy, environmental, and economic advantages by overcoming the traditional bottlenecks of phase-separation hardware and contactor size. Unlike conventional mixer-settlers or membrane-based systems, MPSE operates without moving parts or fouling-prone membranes, achieving robust performance even with challenging, viscous, or particulate-heavy feeds. Key performance metrics include an energy intensity reduction of 5–50x (3–40 kJ/m 3 ) compared to incumbent technologies and a dramatic reduction of processing time to under 60 seconds, which drastically reduces the physical plant footprint. These technical efficiencies translate into superior economic outcomes; for a 100 t/year Li 2 CO 3 facility, implementing MPSE is projected to nearly halve contactor CAPEX (from $\$$6.08M to $\$$3.01M) and significantly increase the project's Net Present Value (NPV), derisking new investment and enabling distributed critical-mineral processing configurations. The commercialization of MPSE technology is being spearheaded by Vigsur Dynamics Inc., which has adopted a structured, parallel approach to technical and business development since its formation in January 2026. Following extensive customer discovery and engagement with the Oregon State University accelerator, Vigsur Dynamics is working to establish a business model that transitions from pilot demonstrations to modular hardware sales, ultimately aiming for a "build-own-operate" service strategy. Current technical milestones—including 100 hours of continuous operation, superior energy efficiency, and successful 6-unit modular scale-up— provide a foundation for this transition. Backed by ongoing IP licensing and a growing network of industrial and venture advisors, the company is actively de-risking the platform to replace conventional mixer-settler systems in the critical minerals market.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Using intrahost single nucleotide variant data to predict SARS-CoV-2 detection cycle threshold values

Over the last four years, each successive wave of the COVID-19 pandemic has been caused by variants with mutations that improve the transmissibility of the virus. Despite this, we still lack tools for predicting clinically important features of the virus. In this study, we show that it is possible to predict the PCR cycle threshold (Ct) values from clinical detection assays using sequence data. Ct values often correspond with patient viral load and the epidemiological trajectory of the pandemic. Using a collection of 36,335 high quality genomes, we built models from SARS-CoV-2 intrahost single nucleotide variant (iSNV) data, computing XGBoost models from the frequencies of A, T, G, C, insertions, and deletions at each position relative to the Wuhan-Hu-1 reference genome. Our best model had an R 2 of 0.604 [0.593–0.616, 95% confidence interval] and a Root Mean Square Error (RMSE) of 5.247 [5.156–5.337], demonstrating modest predictive power. Overall, we show that the results are stable relative to an external holdout set of genomes selected from SRA and are robust to patient status and the detection instruments that were used. This study highlights the importance of developing modeling strategies that can be applied to publicly available genome sequence data for use in disease prevention and control.

COVID19↗
DOE OSTI2025

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗
DOE OSTI2024

PRIME - A Software Toolkit for the Characterization of Partially Observed Epidemics in a Bayesian Framework

PRIME is a modeling framework designed for the “real-time’” characterization and forecasting of partially observed epidemics. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. The estimation problem is posed as one of Bayesian inference and solved using a Markov Chain Monte Carlo technique. The framework can accommodate multiple epidemic waves and can help identify different disease dynamics at the regional, state, and country levels. We include examples using publicly available COVID-19 data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

TDCOSMO - XVII. New time delays in 22 lensed quasars from optical monitoring with the ESO-VST 2.6m and MPG 2.2m telescopes

We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadence r-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The sample of targets consists of 19 quadruply and 3 doubly imaged quasars, which received a total of 1918 hours of on-sky time split into 21 581 wide-field frames, each 320 seconds long. In a given field, the 5-σ depth of the combined exposures typically reaches the 27th magnitude, while that of single visits is 24.5 mag – similar to the expected depth of the upcoming Vera-Rubin LSST. The fluxes of the different lensed images of the targets were reliably de-blended, providing not only light curves with photometric precision down to the photon noise limit, but also high-resolution models of the targets whose features and astrometry were systematically confirmed in Hubble Space Telescope imaging. This was made possible thanks to a new photometric pipeline, lightcurver, and the forward modelling method STARRED. Finally, the time delays between pairs of curves and their uncertainties were estimated, taking into account the degeneracy due to microlensing, and for the first time the full covariance matrices of the delay pairs are provided. Of note, this survey, with 13 square degrees, has applications beyond that of time delays, such as the study of the structure function of the multiple high-redshift quasars present in the footprint at a new high in terms of both depth and frequency. The reduced images will be available through the European Southern Observatory Science Portal.Key words: methods: data analysis / surveys / distance scale

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A Data-Driven Approach to Real-World Degradation of Backsheets

The objectives of this project are as follows: • The population behavior of fielded modules in various conditions of use • Predictions of materials in specific climatic zones • Understanding of a module’s local environment in the field on its degradation It aims to understand how and what backsheet materials of photovoltaic modules degrade in the real world field. • Field Survey Protocol This project is started from the protocol, because all the data, information, domain knowledge are from experience of the real world field surveys, which is based on the protocol. The Protocol is explored from the experience of the field survey observations. With the increasing of the field surveys, it is refined for three versions, which are Task 1.0 (Section 3.1), Task 6.0 (Section 3.6), Task 10.0 (Section 3.10) respectively. It includes a document and a training video, which is able to direct other teams to follow the same procedure with the sites surveyed during this project. The documents include the detailed information but is not limited to the terminology definition, instruments SOP, preparation items for the surveys, form for the data collections, the order of the information collection. The final version of the protocol can be found at Appendix A, see Section 5. Additional, It can also be found at Open Science Framework (OSF), see Section 3.18 for detail. • Written Waiver Request Before staring the field surveys, the request of the waiver for international surveys is completed, because the limitation of climate zone in the United States, see Appendix B in Section 6 for the request documents. Unfortunately, only 1 international site from Taiwan, China can be finished, due to the COVID-19. • Field Survey According to the protocol we built in Section 3.1, 3.6 and 3.10, 41 sites have been surveyed across seven different climate zones (Cfa, Csa, Csb, BSk, Dfa, Dfb, Am). A variety of materials, including Polyethylene Naphthalate (PEN), Polyethylene Terephthalate (PET), Polyvinyl Fluoride (PVF), Polyvinylidene Fluoride (PVDF), Acrylic PVDF, Fluoroethylene Vinyl Ether (FEVE), and Glass, were identified. These sites are located in various states including California, South Carolina, New Mexico, Maryland, Ohio, Tennessee, Florida, Massachusetts, Illinois, Minnesota, Oregon, Colorado, and Taiwan, Republic of China. The ages of the sites ranged from 2 - 38 years in service and the field size varied from 1 MW - 25 MW. All requirements for the modeling have been satisfied. Some observations like ’Edge Effect’ for the rows and Junction box heating will also be a useful knowledge to build the model. Section 3.7 provides detailed information on the sites visited during this reporting period.

14 SOLAR ENERGY↗
DOE OSTI2025

Akiachak Energy Efficiency Retrofit Project

The goal of the project is to reduce the overall energy use of the Akiachak Native Community (ANC) by implementing energy efficiency measures in five high-use Tribal buildings. This project will have the following outcomes: Projected annual energy savings of $17,369; projected annual reduction in fuel oil #1 of 1,200 gallons and electricity of 17,751 kWh; annual reduction in carbon dioxide emissions of approximately 60,340 pounds/year. ANC will install energy efficiency measures in the Laundry, Tribal Indian Reorganization Act (IRA) Office, Clinic, Daycare, and Police Station. ANC obtained energy audits on these buildings in 2018, and this project will implement high-payback recommendations such as replacing lighting with LEDs, installing setback thermostats and occupancy sensors, replacing furnaces with more efficient models, replacing the circulation pumps with variable speed ones, air tightening, and adding insulation. Buildings will see energy cost reductions from 15% to 40%. These retrofits will help build ANC’s long-term vision for sustainable energy usage and address the first goal of the Tribal IRA Council’s Energy Efficiency and Conservation Strategy, to “create and maintain functionally appropriate, sustainable, accessible, high quality tribal infrastructure and facilities.” ANC intends to replicate this project by using the resulting energy savings to address audit recommendations in other buildings as well as to demonstrate the value of energy efficiency to community members. Other outcomes will include an increase in community resiliency, reduced dependence on outside shipments of fuel oil, training for maintenance staff, and no-touch control of building appliances to reduce transmission of diseases such as COVID-19.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

The new ITER baseline, research plan and open R&D issues

A new baseline (NB) has been proposed by the ITER Project to ensure a robust achievement of the Projects’ goals, in view of past challenges including delays incurred due to the Covid-19 pandemic, technical challenges in completing first-of-a-kind components and in nuclear licensing. The NB includes modifications to the configuration of the ITER device and its ancillaries (e.g. change from beryllium to tungsten as first wall material, modification of the heating and current drive mix, etc.) as well as additional testing of components (e.g. toroidal field coils) or phased installation (start with inertially cooled first wall before later installation of the final actively water-cooled components) to minimise operational risks. In the NB, the ITER research plan (IRP) will be divided into three main phases: (a) start of research operation, with 40 MW of ECH and 10 MW of ICH, which will focus on the demonstration of 15 MA operation in L-mode, commissioning of all required systems, including disruption mitigation, and the demonstration of H-mode plasma operation in deuterium; (b) DT-1, with 60–67 MW of ECH, 33 MW of neutral beam injection (NBI) and 10–20 MW of ICH, which will demonstrate robust operation in high confinement H-mode plasmas in DT up to Q ⩾ 10 and for burn durations of 300–500 s within an accumulated neutron fluence of ∼1% of the ITER machine’s lifetime total, and; (c) DT-2, with up to 67 MW of ECH, up to 49.5 MW of NBI and up to 20 MW of ICH, with the ITER tokamak and ancillaries in their final configuration to demonstrate routine operation in DT plasmas at high Q and the Q ⩾ 5 long-pulse and steady-state scenarios to the final neutron fluence and to perform R&D on nuclear fusion reactor issues. The logic, physics basis, modelling and experimental evaluations carried out to support the NB and the associated IRP are described. These include the impact of the tungsten wall on plasma scenarios and associated risk mitigation measures, as well as the optimisation of the tokamak components and ancillaries to minimise Project risks. Open R&D issues related to these evaluations and mitigation measures are also described together with experimental, modelling and validation activities required to address them.

ITER↗