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DOE OSTI2022

Psb27, a photosystem II assembly protein, enables quenching of excess light energy during its participation in the PSII lifecycle

Photosystem II (PSII), the enzyme responsible for oxidizing water into molecular oxygen, undergoes a complex lifecycle during which multiple assembly proteins transiently bind to and depart from PSII assembly intermediate complexes. Psb27 is one such protein. It associates with the CP43 chlorophyll-binding subunit of PSII to form a Psb27-PSII sub-complex that constitutes 7–10% of the total PSII pool. Psb27 remains bound to PSII assembly intermediates and dissociates prior to the formation of fully functional PSII. In this study, we compared a series of Psb27 mutant strains in the cyanobacterium Synechocystis sp. PCC 6803 with varied expression levels of Psb27: wild type (WT); psb27 genetic deletion (Del27), genetically complemented psb27 (Com27); and over-expressed Psb27 (OE27). The Del27 strain demonstrated decreased non-photochemical fluorescence quenching, while the OE27 strain showed increased non-photochemical quenching and tolerance to fluctuating light conditions. Multiple flashes and fluorescence decay analysis indicated that OE27 has the least affected maximum PSII quantum yield of the mutants. OE27 also displayed a minimal impact on the half-life of the fast component of QA – reoxidation over multiple flashes, indicating robust PSII function. Further, we propose that the close association between Psb27 and CP43, and the absence of a fully functional manganese cluster in the Psb27-PSII complex create a PSII sub-population that dissipates excitation energy prior to its recruitment into the functional PSII pool. Efficient energy dissipation prevents damage to this pre-PSII pool and allows for efficient PSII repair and maturation. Participation of Psb27 in the PSII life cycle ensures high-quality PSII assembly.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Bayesian And Human Reliability Analysis (hra)-aided Method For The Reliability Analysis Of Software (bahamas)

The purpose of the BAHAMAS code is to provide a simplified process for performing quantitative evaluations of software reliability. The Bayesian and Human Reliability Analysis (HRA)-Aided method for the Reliability Analysis of software (BAHAMAS) was developed specifically to perform quantification under limited data conditions, i.e., when limited testing or operational data are available, such as during early development stages. BAHAMAS essentially examines the quality of a software development life cycle to determine the probability of specific types of software failure. BAHAMAS will have modules to support user input for detailed and simplified analyses. The user interface will also support software common cause failure analysis.

Wang, Congjian (0000000207789927)↗

DOE OSTI2023

Effect of Humidity-Triggered Controlled-Release 1-Methylcyclopropene (1-MCP) on Postharvest Quality of Papaya Fruit

Papaya (Carica papaya L.) is a valuable economic crop that is widely cultivated in tropical and subtropical regions but has a short storage and shelf life. Exploring effective strategies to improve the postharvest quality of papaya is important. This study explored the effect of humidity-triggered controlled-release 1-methylcyclopropene (1-MCP) sheets on the postharvest quality of papaya fruit. ‘Rainbow’ papayas underwent cold storage at 10 ± 0.5 °C, RH 85% ± 2% for 14 days, and then were transferred to 20 ± 0.5 °C, RH 85% ± 2% for 10 days to simulate shelf life. The 1-MCP sheets were cut into different sizes and placed in storage containers in advance to create corresponding concentrations at 0.5, 1.0, 2.0, and 4.0 ppm. Results showed that 1-MCP treatment inhibited fruit softening, and reduced weight loss and peel color deterioration without causing any physiological disorders. The 1.0–2.0 ppm 1-MCP-treated fruit received the highest score for papaya flavor and sweetness respectively and the lowest score for off-flavor. The humidity-triggered controlled-release 1-MCP sheets are effective and convenient, and they can serve as an important tool for regulating postharvest papaya ripening with economic benefits.

Agriculture↗

DOE OSTI2022

Impact of acute temperature and air pollution exposures on adult lung function: A panel study of asthmatics

Background Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM 2.5 ) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. Methods and findings Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV 1 )), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM 2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM 2.5 , DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM 2.5 , but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM 2.5 , had a significant association with FEV 1 . When DBGT and PM 2.5 exposures were placed in the same model, the strongest association between cumulative PM 2.5 exposures and the use of rescue bronchodilator was identified at the 0–24 hours (OR = 1.030; 95% CI = 1.012–1.049; p-value = 0.001) and 0–48 hours (OR = 1.030; 95% CI = 1.013–1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (β = 3.257; SE = 0.879; p-value>0.001) and 0–6 hours (β = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV 1 . No significant interactions between DBGT and PM 2.5 were observed for rescue bronchodilator use or FEV 1 . Conclusions Short-term increases in PM 2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV 1 ). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM 2.5 and DBGT on lung function in asthmatics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Toward the Advanced Manufacturing of Land-Based Wind Turbine Blades

The National Renewable Energy Laboratory and General Electric (GE) are partners within the Additive and Modular-Enabled Rotor Blades and Integrated Composites Assembly (AMERICA) project. AMERICA aims to develop advanced manufacturing solutions to reduce labor and cycle time while increasing recyclability of wind turbine blades. The project is funded by the U.S. Department of Energy's Advanced Manufacturing Office. This paper describes the techno-economic and life cycle analysis of the novel manufacturing process applied to the 15-meter long tip of the blade of a representative 3.4 MW land-based wind turbine. We establish a comparison to a standard manufacturing process, highlighting challenges and opportunities. Several uncertainties affect the analysis, but we highlight an opportunity space. With the current set of assumptions, the tip adopting advanced manufacturing is predicted to lower labor by 21%, cycle time by 39%, and total blade tip costs by 15% while simultaneously increasing production quality and adopting recyclable thermoplastic resin. A life cycle analysis returns comparable metrics for climate change impact and embodied energy between the two processes.

3D printing↗

DOE OSTI2024

Pathways to IEC Standards for Heliostat Design Qualification and Site Acceptance in Central Receiver CSP Applications

This paper surveys the existing landscape of standards relevant to heliostats, identifies their gaps, and proposes a path forward to a comprehensive set of heliostat guidelines, technical specifications, and standards under the framework of International Electrotechnical Commission (IEC) TC 117. Gaps in existing guidelines and standards are surveyed using a three-tiered taxonomy: component-level, heliostat-level, and field-level. At each level, the gap analysis is followed by a proposal for a coordinated path forward on the development of standards. At the component level, advances in the understanding of wind loading should inform a technical specification for drives and structures. Reflectors require consolidation of measurement guidelines into existing standards documents. Communications & controls require technical standards to inform their selection and secure implementation. At the heliostat level, IEC 62817 (solar trackers) adequately characterizes drive systems, structures, and electronics, but requires adaptation to heliostats' use patterns, operating modes, and expected life cycles. IEC 62817 does not address heliostat beam quality and pointing accuracy, but the process for determining both is elaborated in the SolarPACES Guideline for Heliostat Performance Testing. This SolarPACES document requires two main modifications: adaptation to IEC language and inclusion of testing after heliostats which have undergone accelerated weathering and mechanical cycling (to understand performance degradation). At the field level, IEC 62862-4-2 addresses the function and control of heliostat fields but does not cover the statistically rigorous testing of heliostat groups, or field performance factors like security and soiling. The addition of documents under IEC-62862-4 is proposed to address this gap.

beam↗

DOE OSTI2023

Increasing the Fissile Mass Loading of High-Level Waste Glass Canisters to Greater Than 2,500 g/m 3 at the Savannah River Site

To eliminate future fissile mass loading constraints for the Savannah River Site H-Canyon Facility and Liquid Waste system, the Savannah River National Laboratory recommends a repository evaluation of a uranium fissile mass loading in glass at 7,144 g/m 3 in addition to the existing International Atomic Energy Agency safeguards and security limit of 2,500 g/m 3 total plutonium. This recommended increase above the authorized 2,500 g/m 3 fissile mass loading limit is based on concentrations of uranium and plutonium shown to produce an acceptable glass waste form rather than projections of the maximum fissile mass loading in future sludge batches. An authorized fissile mass loading limit greater than 2,500 g/m 3 will increase facility flexibility, reduce the number of high-level waste canisters produced, and potentially avoid an increase in the Department of Energy Environmental Management mission life without compromising safety or glass product quality.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Observationally constrained analysis on the distribution of fine- and coarse-mode nitrate in global models

Nitrate plays an important role in the Earth system and air quality. A key challenge in simulating the life cycle of nitrate aerosol in global models is to accurately represent mass size distribution of nitrate aerosol. In this study, we evaluate the performance of the Energy Exascale Earth System Model version 2 (E3SMv2) and the Community Earth System Model version 2 (CESM2), along with Aerosol Comparisons between Observations and Models (AeroCom) phase III models, in simulating spatial distribution of fine-mode nitrate, the mass size distribution of fine- and coarse-mode nitrate, and the gas–aerosol partitioning between nitric acid gas and nitrate, using long-term ground-based observations and measurements from multiple aircraft campaigns. We find that most models underestimate the annual mean PM 2.5 (particulate matter with diameter less than 2.5 µm) nitrate surface concentration averaged over all sites. The observed nitrate PM 2.5 / PM 10 and PM 1 / PM 4 ratios are influenced by the relative contribution of fine sulfate or organic particles and coarse dust or sea salt particles. Overall, the ground-based observations give an annual mean surface nitrate PM 2.5 / PM 10 ratio of 0.7. Most models underestimate the annual mean PM 2.5 / PM 10 ratio in all regions. There are large spreads in the modeled nitrate PM 1 / PM 4 ratios, which span the full range from 0 to 1. Most models underestimate the surface molar ratio of nitrate to total inorganic nitrate averaged across all sites. Our study indicates the importance of gas–aerosol partition parameterization and the simulation of dust and sea salt in correctly simulating the mass size distribution of nitrate.

Nitrate↗

DOE OSTI2025

Meta‐Analysis and Regression Modeling of the Impacts of Four Indoor Environmental Quality Metrics on Office Performance

Awareness of how buildings interact with the occupant experience—especially human performance—is becoming more prevalent, as seen by increasing interest and investment in healthy built environments. However, there is a need to synthesize the wide array of existing indoor environmental assessment and performance research in a way that can translate directly to building design and operation. Existing research in this area typically focuses on a single isolated metric and has not focused on making the results utilizable by building practitioners. The aim of this research is to investigate existing office performance literature through meta‐analyses and produce regression models for four indoor environmental quality (IEQ) metrics to support critical decision‐making for building operation and renovation. To reach this aim, a literature review was conducted to identify studies that measure the impact of changing ventilation rate, temperature, horizontal illuminance, and noise level in offices on occupant task performance. This repository of field and laboratory studies was analyzed to visualize the trends between the selected IEQ metrics and task performance. The temperature, ventilation rate, and horizontal illuminance regression models showed clear improvement potential when modifying indoor conditions toward the defined high‐performance range, while the regression model for noise level was inconclusive. The discussion notes the importance of designing holistically for all components of these IEQ categories to utilize the results, for example, good filtration on outdoor air for quantifying ventilation impact and uniform overhead lighting with low contrast for quantifying horizontal illuminance impact. The novelty of this work is in considering multiple facets of the indoor environment under a single, unified analysis schema and producing IEQ‐based performance gains that can directly inform cost‐benefit analyses of building design and renovation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗

DOE OSTI2021

Practical algorithms for multivariate rational approximation

We present two approaches for computing rational approximations to multivariate functions, motivated by their effectiveness as surrogate models for high-energy physics (HEP) applications. Our first approach builds on the Stieltjes process to efficiently and robustly compute the coefficients of the rational approximation. Our second approach is based on an optimization formulation that allows us to include structural constraints on the rational approximation (in particular, constraints demanding the absence of singularities), resulting in a semi-infinite optimization problem that we solve using an outer approximation approach. We present results for synthetic and real-life HEP data, and we compare the approximation quality of our approaches with that of traditional polynomial approximations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Distributed Solar Quality and Safety in India: Key Challenges and Potential Solutions

The quality and safety of solar systems and their installation has become a concern for investors, regulators, consumers, and Discoms in India. The push for low prices and lack of quality standards are driving project developers to install low quality products, with poor system design and execution on-site. Existing literature and stakeholder interviews point to the rampant use of low quality, sub-standard solar products in India. These products deliver less energy than expected, or have high detrition rates, or have lower product life–all of which are serious issues for developers whose return on investment depend on the amount of power generation from these solar systems for the expected life of the project. Equipment which does not conform to the minimum quality standards also creates safety risks for the distribution network. Performance and safety concerns lower investor and consumer confidence in solar products with the potential to threaten market development. This report formulates a set of recommendations to concerned authorities in India to improve the quality and safety of rooftop solar systems. Primary and secondary sources are employed to understand the current solar quality and safety scenario in India to provide the basis for future recommendations. An overview of international experiences and lessons learned on solar quality and safety issues is also conducted to understand potential solutions for India.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Robot-based Additive Manufacturing of Lego-type Modular Molds for Wind Blades

The objective of this project is to reduce the cost and lead time of horizontal wind turbine blade mold tooling and blade transportation, while maintaining the highest standards of blade quality. The solution involves a smart-design family of modular molds that are easily transportable to fabrication sites near the place of service. Key innovations include the use of additive manufacturing (AM) to integrate conformal thermal management channels, offering enhanced control over the thermal profiles tailored to specific blade materials. This approach enables in-situ quality assurance during mold fabrication, significantly improves mold life, and allows for reuse across multiple production cycles. Ultimately, the solution aims to optimize both tooling and transportation costs, contributing to the scalability of wind turbine blade production. A significant barrier to scaling up the production of large wind turbine blades lies in the high costs associated with tooling and the transportation of blades. Traditional molds are expensive, bulky, and difficult to transport, adding considerable lead time and cost to the overall manufacturing process. Additionally, transporting blades to distant locations for final assembly further exacerbates these challenges. The project aims to address these inefficiencies by demonstrating a modularized, additive-manufactured mold that meets all necessary blade specification requirements, specifically for blade lengths between 120m and 150m.

17 WIND ENERGY↗

DOE OSTI2023

Interplay between Shelf Life and Printability of Silica-Filled Suspensions

Although fumed silica/siloxane suspensions are commonly employed in additive manufacturing technology, the interplay between shelf life, storage conditions, and printability has yet to be explored. In this work, direct ink writing (DIW) was used to print unique three-dimensional structures that required suspensions to retain shape and form while being printed onto a substrate. Suspensions containing varying concentrations of hydrophobic and hydrophilic silica were formulated and evaluated over a time span of thirty days. Storage conditions included low (8%) and high (50%) relative humidity and temperatures ranging from 4 °C to 25 °C. The shelf life of the suspensions was examined by comparing the print quality of pristine and aged samples via rheology, optical microscopy, and mechanical testing. Results showed a significant decrease in printability over time for suspensions containing hydrophilic fumed silica, whereas the printability of suspensions containing hydrophobic fumed silica remained largely unchanged after storage. The findings in this work established the following recommendations for extending the shelf life and printability of suspensions commonly used in DIW technology: (1) higher fumed silica concentrations, (2) low humidity and low temperature storage environments, and (3) the use of hydrophobic fumed silica instead of hydrophilic fumed silica.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Supplementing biofuel mandates with a carbon mitigation policy can lead to water quality co-benefits

Biofuel mandates can impact the environment in multiple ways that may be positive or negative, including affecting life-cycle greenhouse gas (GHG) emissions by displacing fossil fuels, affecting soil carbon stocks due to accompanying land use change, and water quality due to changes in fertilizer requirements and the mix of crops used as feedstocks. To achieve desired environmental outcomes in the presence of a biofuel mandate, additional policy instruments must be adopted to supplement the mandate. We develop an integrated and spatially explicit ecosystem-economic modeling framework to analyze the cost-effectiveness of alternative policies to achieve desired targets for GHG emissions reduction from the agricultural and fuel sectors in the USA and nitrate leaching reduction in the Gulf of Mexico below the levels that would be achieved by a corn ethanol and/or a cellulosic ethanol mandate in the USA. We find that while a corn ethanol mandate lowers GHG emissions, it increases nitrate leaching due to the expansion of corn production; a cellulosic ethanol mandate lowers both GHG emissions and nitrate leaching relative to a corn ethanol mandate, but the additional carbon and nitrate prices are needed to achieve anticipated GHG reduction and nitrate reduction targets. We also find that accompanying a biofuel mandate with a GHG reduction target alone leads to substantial nitrate reduction co-benefits, but a nitrate reduction target alone is less effective in reducing GHG emissions. Combining a GHG standard with a nitrate standard can achieve GHG and nitrate reduction targets at lower carbon and nitrate prices as compared to implementing each of these policies independently. Furthermore, our findings show that disregarding policy co-benefits can overestimate the GHG and nitrate prices needed to achieve policy targets and higher policy costs.

09 BIOMASS FUELS↗

DOE OSTI2022

A Novel Approach for Real-Time Quality Monitoring in Machining of Aerospace Alloy through Acoustic Emission Signal Transformation for DNN

Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which is retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with a propensity to rapid crack propagation, has limited the application of γ-TiAl. Any cracks introduced during manufacturing would dramatically lower the useful (fatigue) life of γ-TiAl components, making the workpiece surface’s quality from finish machining a critical component to product quality and performance. To address this issue and enable more widespread use of γ-TiAl, this research aims to develop a real-time non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN). Previous efforts have opted for traditional approaches to AE signal analysis, using statistical feature extraction and classification, which face challenges such as the extraction of good/relevant features and low classification accuracy. Hence, this work proposes a novel AI-enabled method that uses a convolutional neural network (CNN) to extract rich and relevant features from a two-dimensional image representation of 1D time-domain AE signals (known as scalograms), subsequently classifying the AE signature based on pedigreed experimental data and finally predicting the process-induced surface quality. The results of the present work show good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, establishing the significant potential for real-time quality monitoring in manufacturing processes.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate

Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NO x ), ammonia (NH 3 ), and nitrous oxide (N 2 O). Here, the propensity of NO x and NH 3 to generate ozone and fine particulate matter (PM) and associated impacts on health are highly variable, whereas the climate impacts of long-lived N 2 O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially-resolved, monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the agricultural emissions of Nr from across the United States. We then apply a reduced-form air pollution health effects model to assess air quality impacts from NO x and NH 3 and a social cost of N 2 O to assess the climate impacts. Assuming an $\$$8.2 million Value of a Statistical Life (VSL) and a $\$$13,100/ton social cost of N 2 O, the air quality impacts are a factor of ~7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Hydrogen Sustainable Infrastructure Guidelines (H2SIG)

Infrastructure interacts with major global challenges inclusive of climate change, resilience, equity and social justice, environmental protection and biodiversity, public health, and economic recovery. This effort directly addresses how to apply sustainability assessments to the unique aspects of hydrogen (H2) infrastructure projects using the Envision® sustainability framework developed by the Institute for Sustainable Infrastructure (ISI). Envision is a flexible system of criteria and performance objectives to aid decision makers and help project teams identify sustainable approaches during planning, design and construction of infrastructure projects that will continue throughout the project’s operations, maintenance, and end-of-life phases. The goal of this work is to support those interested in conducting sustainability assessments for hydrogen infrastructure projects. Through this work the team has developed hydrogen-specific guidelines and best practices to assist project developers, investors and regulators in straightforward application of the Envision framework to systematically enhance clarity and increase objectivity across hydrogen projects. Subject matter experts from 20 different organizations (industry, non-profits, municipalities, emissions regulators, national labs) were engaged through 7 focus groups to discuss the H2-prioritized Envision requirements and elements to be included in the guidelines. In addition to these guidelines, the team conducted case studies as a way of demonstrating and informing the guidelines and providing examples or ideas for implementing sustainability in future projects. Through this study, the authors found that hydrogen infrastructure projects can incorporate many sustainable practices including reducing GHG emissions affecting climate change, reducing air pollutant emissions affecting the health of communities, synergistically handling waste byproducts, integrating into existing infrastructure, incorporating renewable energy, and addressing equity and environmental justice. Additionally, hydrogen infrastructure projects could benefit from 2-way communication engagement and collaborative planning with stakeholders, educational awareness of hydrogen technology, tracking and reporting on water use and water quality, and including monetized environmental and social benefits in life-cycle cost estimates. This document is the final technical report for the Hydrogen Sustainability Assessment Methods for Project Development project. While the main focus of the report is to provide guidelines for applying sustainability to hydrogen infrastructure, there are sections within the appendix providing completed project tasks and methodology.

08 HYDROGEN↗