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DOE OSTI2023

Effects of Saccharomyces cerevisiae quorum sensing signal molecules on ethanol production in bioethanol fermentation process

Here in this study, the concentrations of Saccharomyces cerevisiae quorum sensing signal molecules (QSMs) were determined, not to mention the exploration of the effects of exogenous S. cerevisiae QSMs on the sole fermentation of S. cerevisiae and co-fermentation of S. cerevisiae and Lactobacillus plantarum. The results showed that the concentrations of three signal molecules (2-phenylethanol (2-PE), tyrosol and tryptophan) produced by S. cerevisiae increased with a higher bacteria density, which tends to become stable up to 118.02, 32.05 and 1.93 mg/L respectively when cultivating for 144 h. Among the three signaling molecules, only 2-PE promoted the ethanol production capacity of S. cerevisiae. The ethanol concentration of the sole fermentation of S. cerevisiae loaded with 120 mg/L 2-PE reached 3.2 g/L in 9 h, which was 58.7% higher than that of the group without 2-PE addition. Moreover, 2-PE reduced the negative impact of L. plantarum on S. cerevisiae. Within 12 h of the co-fermentation of L. plantarum and S. cerevisiae, the ethanol concentration in the co-fermentation group loaded with 2-PE reached 5.6 g/L, similar to that in the group fermenting with sole S. cerevisiae, and the yeast budding rate was also restored to 28.51%. qRT-PCR results of S. cerevisiae which was in sole fermentation with 2-PE addition for 9 h showed that the relative expression levels of ethanol dehydrogenase gene ADH1 in S. cerevisiae decreased by 25% and the relative expression levels of MLS1, CIT2, IDH1,CIT1 decreased by 26%, 30%, 22%,18%, respectively, meant that the glyoxylic and tricarboxylic acid cycles were greatly inhibited, which promotes the accumulation of ethanol. The results of this study provide basic data for using QSMs more than antibiotics in the the prevention of contamination during the industrialized bioethanol production.

2-phenylethanol↗

DOE OSTI2022

Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System, Meet Future Demand for City Passenger and Delivery Load/Unload Spaces, and Reduce Energy Consumption

This three-year project supported by the U.S. Department of Energy Vehicle Technologies Office has the potential to radically improve the urban freight system in ways that help both the public and private sectors. Working from 2018-2021, project researchers at the University of Washington’s Urban Freight Lab and collaborators at the Pacific Northwest National Laboratory have produced key data, tested technologies in complex urban settings, developed a prototype parking availability app, and helped close major knowledge gaps. All the fruits of this project can be harnessed to help cities better understand, support and actively manage truck load/unload operations and their urban freight transport infrastructure. Project learnings and tools can be used to help make goods delivery firms more efficient by reducing miles traveled and the time it takes to complete deliveries, benefitting businesses and residents who rely on the urban freight system for supplies of goods. And, ultimately, these project learnings and tools can be used to make cities more livable by minimizing wasted travel, which, in turn, contributes to reductions in fuel consumption and emissions. Cities today are challenged to effectively and efficiently manage their infrastructure to absorb the impacts of ever-increasing e-commerce-fueled delivery demand. All delivery trucks need to park somewhere to unload and load. Yet today’s delivery drivers have no visibility on available parking until they arrive at a site, which may be full. That means they can wind up cruising for parking, which wastes time and fuel and contributes to congestion. Once drivers do find parking, the faster they can unload at the spot, the faster they free up space for other drivers, helping others avoid circling for parking. This makes the parking space—and thus the greater load/unload network—more productive. To this end, the research team successfully met the project’s three goals, developing and piloting strategies and technologies to: 1. Reduce parking-seeking behavior in the study area by 20%; 2. Reduce parcel truck dwell time (the time a truck spends in a spot to load/unload) in the study area by 30%; 3. Increase curb space, alley space and private loading bay occupancy rates in the study area. The research team met these goals by creating and piloting on Seattle streets OpenPark, a first-of-its-kind real-time and forecasting curb parking app customized for commercial delivery drivers—giving drivers the “missing link” in their commonly used routing tools that tell them how best to get to delivery locations, but not what parking is available to use when they get there. Installing in-ground sensors on commercial vehicle load zones (CVLZs) and passenger load zones (PLZs) in the 10-block study area in Seattle’s downtown neighbourhood of Belltown let researchers glean real-time curb parking data. The research team also met project goals by piloting three parcel lockers in public and private spaces open to any delivery carrier, creating a consolidated delivery hub that lets drivers complete deliveries faster and spend less time parked. Researchers collected and analysed data to produce the first empirical, robust, statistically significant results as to the impact of the lockers, and app, on on-the-ground operations. In addition to collecting and analyzing sensor and other real-time and historical data, researchers rode along with delivery drivers to confirm real-world routing and parking behavior. Researchers also surveyed building managers on their private loading bay operations to understand how to boost usage.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Combined Effects of Electric Vehicle Charging and Rooftop Solar Integration on Voltage Imbalance in Residential Distribution Networks

Residential electric vehicle (EV) chargers, as single phase loads, contribute to unbalanced voltage drops across phases, while rooftop solar systems, as single phase generators, can exacerbate voltage imbalance by causing unbalanced voltage increases. This paper investigates combined effects of residential EV charging and rooftop solar generation on voltage imbalance in residential distribution grids. The study examines these simultaneous impacts using the IEEE 8500-node test system, enhanced with a secondary network to realistically model the EV chargers and rooftop solar integration. To account for the variability and uncertainty in the EV charging loads and solar generation, a Monte Carlo approach is employed to capture and quantify the simultaneous impact of the EV charging and rooftop solar integration. In this approach, multiple influencing factors are considered, including state-of-charge (SOC), maximum charging power levels, and geographic distribution of chargers. The results provide practical insights for utilities and stakeholders, offering expectations for planning and operating strategies that effectively manage the increasing adoption of EVs and solar power while maintaining grid reliability.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗

DOE OSTI2023

Load Shedding for Voltage Regulation With Probabilistic Agent Compliance

With the increased observability and controllability of distribution systems, the share of behind-the-meter systems is trending upwards rapidly. As a consequence, the impact of human behaviors on system performance can no longer be ignored and should be reflected in the energy management system models. In this paper, we discuss the problem of distribution system voltage control by active power curtailment where the agent compliance of the load curtailment signal is probabilistic. We discuss the modeling of the optimal voltage control problem with probabilistic agent compliance as a chance-constrained optimization problem, its tractable safe approximation using convex restriction, and a scenario-based mixed-integer reformulation as well as the associated solution method based on augmented Lagrangian method. The numerical simulation on IEEE test system validates the effectiveness of the proposed approach in obtaining high-quality feasible load curtailment signal with low computational cost, which makes it a viable tool for real time decision making.

augmented Lagrangian method↗

DOE OSTI2023

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decom- pose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high- level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for one-year lead hourly load below 5% MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗

DOE OSTI2023

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM: Preprint

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below 5% MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗

DOE OSTI2023

In situ high-temperature 3D imaging of the damage evolution in a SiC nuclear fuel cladding material

Silicon carbide (SiC)-based nuclear fission fuel rod cladding has been considered as one of the possible designs for accident tolerant fuels. It is in the form of a SiC fibre reinforced SiC matrix composite tube (SiC f -SiC m ) with monolithic SiC outer and/or inner coating layers. This study focuses on the deformation and fracture processes in this material using in situ X-ray micro-computed tomography (XCT) at room temperature (RT) and 1200 °C in an inert gas environment in a C-ring compression loading configuration. Prior to testing, local properties and residual stresses were characterised using nanoindentation and Raman spectroscopy since they can impact the mechanical behaviour of the material. The 3D strain distribution, crack formation and propagation processes including the toughening mechanisms (e.g., crack deflection, micro-cracking, crack bridging and bifurcation) are investigated in the coating and underlying composites at RT and 1200 °C. There is no particular sequence which toughening mechanism occurs first – this is very different from the conventional toughening theory in ceramic-matrix composites under uniaxial tension loading. Indeed, no evidence of fibre pull-out or fibre fracture was observed in this SiC f -SiC m nuclear cladding material in the current C-ring compression configuration. The correlation between local measurements and bulk mechanical behaviour are discussed.

3D imaging↗

DOE OSTI2025

Advancing Grid Resilience through Smart Charge Management: Findings from Maryland’s Pilot

This report presents research findings from a four-year Smart Charge Management (SCM) pilot program conducted by Maryland’s largest electric utilities—Baltimore Gas and Electric (BGE), Potomac Electric Power Company (Pepco), and Delmarva Power & Light (DPL)—to evaluate strategies for optimizing electric vehicle (EV) charging loads and enhancing grid stability. Supported by the U.S. Department of Energy (DOE), Argonne National Laboratory collaborated with all project partners and examined the effectiveness of Time-of-Use (TOU) and Load Balancing (LB) strategies in managing peak demand, deferring costly infrastructure upgrades, and reducing grid constraints at the feeder level. Using charging data from over 4,600 EV drivers, the study analyzed SCM’s impact on the distribution systems of BGE and Pepco, which consists of over 2000 feeders. Unlike prior research that focused on system-wide trends or synthetic feeders, this analysis offers granular, feeder-level insights based on real-world operational data. It highlights how transformer density, load profiles, and infrastructure constraints influence smart charging performance. Results show feeder-level conditions play a crucial role in SCM effectiveness, with most feeders benefiting more from LB, while TOU-based SCM may be sufficient for others. By 2035, LB reduced peak charging loads by 27% on average, compared to 23% under TOU-based SCM, though some feeders saw reductions exceeding 35%, while others experienced minimal impact. Feeders with higher transformer utilization and limited capacity benefited more from LB, which more effectively distributed charging demand during off-peak hours. Beyond reducing grid constraints, SCM offers long-term operational and financial benefits. By shifting EV charging demand strategically, utilities can optimize asset utilization, delay infrastructure investments, and enhance grid performance. In terms of infrastructure upgrade deferrals, at the feeder level, LB consistently reduced peak charging loads and resulting infrastructure upgrade costs, particularly in high EV enrollment areas, decreasing the number of overloaded transformers by up to 35%, while TOU-based SCM achieved 20-30% reductions depending on feeder characteristics. At the system level, LB has the potential to defer total upgrade costs by $\$$186 million for BGE, compared to $\$$159 million under TOU-based SCM. For Pepco, TOU-based SCM performed slightly better, deferring upgrade costs by $\$$30 million, compared to $\$$29 million under LB. Section 4.5 reviews some of the system differences between BGE and Pepco. However, as EV adoption scales, TOU-based SCM will introduce secondary peak charging loads, reinforcing the need for more advanced, adaptive SCM approaches to prevent new grid challenges. As EV adoption continues to grow, feeder-level managed charging strategies will be essential for mitigating grid stress, improving infrastructure efficiency, and maintaining energy affordability for consumers. This report provides critical insights for utilities, Public Utility Commissions (PUCs), and state agencies on the role of feeder-specific smart charging in infrastructure planning, policy development, and grid modernization. The findings underscore the importance of tailored, data-driven SCM solutions that align with local grid conditions, ensuring a resilient, cost-effective transition to increasing EV adoption while safeguarding distribution system performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Carbon-Binder Weight Loading Optimization for Improved Lithium-Ion Battery Rate Capability

Battery performance is strongly correlated with electrode microstructure and weight loading of the electrode components. Among them are the carbon-black and binder additives that enhance effective conductivity and provide mechanical integrity. However, these both reduce effective ionic transport in the electrolyte phase and reduce energy density. Therefore, an optimal additive loading is required to maximize performance, especially for fast charging where ionic transport is essential. Such optimization analysis is however challenging due to the nanoscale imaging limitations that prevent characterizing this additive phase and thus quantifying its impact on performance. Herein, an additive-phase generation algorithm has been developed to remedy this limitation and identify percolation threshold used to define a minimal additive loading. Improved ionic transport coefficients from reducing additive loading has been then quantified through homogenization calculation, macroscale model fitting, and experimental symmetric cell measurement, with good agreement between the methods. Rate capability test demonstrates capacity improvement at fast charge at the beginning of life, from 37% to 55%, respectively for high and low additive loading during 6C CC charging, in agreement with macroscale model, and attributed to a combination of lower cathode impedance, reduced electrode tortuosity and cathode thickness.

25 ENERGY STORAGE↗

DOE OSTI2024

Carbon-Binder Optimization for Lithium-Ion Battery Extreme Fast Charge

carbon-binder additives↗

NASA NTRS1947

Some Tests and Calculations Pertaining to the Dive Path and to Wing and Tail Loads in the Accident to Eastern Airlines C54B Airplane, NC-88814, Near Bainbridge, Maryland, May 30, 1947

Several dive paths were calculated for a C54 airplane starting from level flight at an altitude of 4000 feet and from an initial indicated airspeed of 200 miles per hour. The results show that, within the limits of the possible paths permitted by the evidence of the crash at Bainbridge, the speed of impact would be about 370 miles per hour and the time to crash would be between 12 1/2 and 15 1/2 seconds. Tail load calculations indicate that, with moderate negative acceleration of the airplane, the tail would fail near the end of the dive in a manner consistent in several important respects with the evidence. A number of tests were made of the elevator tab control system to determine whether the tab would move by an amount sufficient to have caused the observed dive if the stored energy in the tab control cable were suddenly released. The results of these tests indicated that the probable tab movement is such as to be capable of causing a dive similar to the one observed at Bainbridge.

Rhode, Richard V.↗

NASA NTRS1985

The influence of lay-up and thickness on composite impact damage and compression strength

The effects of composite stacking sequence, thickness, and percentage of zero-degree plies on the size, shape, and distribution of delamination through the laminate thickness and on residual compression strength following impact were studied. Graphite/epoxy laminates were impacted with an 0.5 inch diameter aluminum sphere at a specific low or high velocity. Impact damage was measured nondestructively by ultrasonic C-scans and X-radiography and destructively by the deply technique, and compression strength tests were performed. It was found that differences in compression failure strain due to stacking sequence were small, while laminates with very low percentages of zero-degree plies had similar failure loads but higher failure strains than laminates with higher percentages of zero-degree plies. Failure strain did not correlate with planar impact damage area, and delaminations in impact regions were associated with matrix cracking.

Guynn, E. G.↗

DOE OSTI2022

Durable High-Power Membrane Electrode Assemblies with Low Pt Loading

Recent progress in developing and implementing Pt-alloy cathode catalysts and thin (10-15 micron) low resistance membranes has enabled high performance state of art (SOA) membrane electrode assembly (MEA) with low Pt loading. However, these high performing MEAs do not meet durability requirements, especially at peak power, because of complex degradation mechanisms that are sensitive to the materials, MEA design, and fuel cell operating strategy. Specifically, power degradation of the cathode occurs via Pt and Co dissolution as well as deterioration of O 2 transport properties. Additionally, thin membranes are subject to failure due to manufacturing defects in the adjacent gas diffusion media and electrodes and the formation of membrane-attacking radical species caused by high gas crossover. In this project led by General Motors LLC (GM), the objective was to enhance the durability of SOA MEA through optimization of operating conditions, instead of new materials development. Along with our project partners, we have mapped the impact of operating conditions on the durability of SOA MEA. Output of the project include a low Pt loading SOA MEA that exceeds Department of Energy (DOE) 2020 target of >1 W/cm 2 at rated power and pathway to achieve >5000 h of durability. Durability studies in the project provide a detailed understanding of failure modes and operating condition sensitivity on cathode and membrane failure, critical for defining operating conditions and hybridization strategies that can guide system controls to maximize low-Pt MEA life. The project also generated and validated degradation models that will provide future research direction, critical for guiding future cycles of automotive MEA development.

08 HYDROGEN↗

NASA NTRSDate not supplied

Study of Aircraft Structural Response and Occupant Loading During a Ditching Event Utilizing LS-DYNA Simulation

In this study, the capability of finite element model (FEM) analysis to assess aircraft structural response and occupant injury risk during aircraft water ditching conditions was evaluated. A FEM of the Fokker F28 aircraft, previously validated against full-scale crash test data, was simulated in a realistic water impact environment utilizing recorded conditions from the ditching of US Airways Flight 1549 into the Hudson River. The FEM of the F28 aircraft, was developed from a NASTRAN loads model provided by the vehicle manufacturer, calibrated using component fuselage drop-tests, and validated through test-analysis comparisons from a full-scale crash test of the F28 onto soil. Simulation results are presented in several categories: vehicle kinematics, structural accelerations, damage, occupant responses, and injury risk predictions. Results were consistent with the general outcomes of Flight 1549, indicating that the developed vehicle FEM, validated against land impact test data, may provide an effective tool for evaluating water ditching events.

Jacob Putnam↗

DOE OSTI2026

Examining the Impacts of Microphysical-Dynamical Feedbacks on Convective Clouds in Different Aerosol Environments Using Enhanced Observational and Modeling Strategies

This project investigated how microphysical–dynamical feedbacks influence deep convective clouds across a range of aerosol conditions, storm lifecycles, and meteorological regimes, and how these sensitivities depend on the modeling framework used to represent convection and microphysics. Using the Aerosol, Cloud, Precipitation, and Climate (ACPC) Working Group model intercomparison simulations of isolated deep convection in the Houston region, we found a robust warm-phase aerosol response in most cloud-resolving models. Increased aerosol loading tended to suppress warm-rain production, increase cloud water, and reduce surface rainfall and near-surface evaporation. These impacts were typically strongest early in the convective lifecycle, with the largest aerosol-driven differences occurring during the first half of storm evolution. The ice-phase response, on the other hand, varied widely across modeling frameworks, and differed in sign, timing, and vertical structure. Ice microphysical pathways and parameterizations are therefore leading sources of uncertainty in aerosol–deep convection interactions. Theoretical analyses further suggested that aerosol-driven invigoration through cold-phase processes was much weaker than previously hypothesized for cold-based storms, and in warm-based storms could even reduce updraft strength. These results imply that any invigoration signal is more likely linked to warm-phase processes and peaks early in storm development.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1980

Contact law and impact responses of laminated composites

Static identation tests were performed to determine the law of contact between a steel ball and glass/epoxy and graphite/epoxy laminated composites. For both composites the power law with an index of 1.5 was found to be adequate for the loading curve. Substantial permanent deformations were noted after the unloading. A high order beam finite element was used to compute the dynamic contact force and response of the laminated composite subjected to the impact of an elastic sphere. This program can be used with either the classical Hertzian contact law or the measured contact law. A simple method is introduced for estimating the contact force and contact duration in elastic impacts.

Sun, C. T.↗

DOE OSTI2025

Behind-the-Meter Energy Storage and Generation in Support of Electrified Rental Car Centers

Electrification of rental car centers at major airports is expected to generate tens of MW in additional power loads. The magnitude of these loads poses challenges including high utility costs, expensive and lengthy distribution capacity upgrades, and disruptions to traditional operation. Behind-the-meter stationary battery storage and onsite photovoltaic generation offer a viable solution to these challenges without impacting the operation and business model of rental car companies, defined by minimal fleet inventory and short vehicle dwell time. Using data-driven syn-thetic charging loads for the rental car center at the Dallas/Fort Worth airport in the United States, we show that optimally-designed and controlled behind - the- meter resources can reduce the lifecycle cost of electrified rental centers by an average 41 % and reduce peak grid demand by 64 %, deferring the need for distribution upgrades or potentially avoiding it altogether.

battery storage↗

NASA NTRS2004

Lunar and Planetary Science XXXV: Effects of Impacts: Shock and Awe

This document discusses the following topics: Zircon as a Shock Indicator in Impactites of Drill Core Yaxcopoil-1, Chicxulub Impact Structure, Mexico; Experimental Investigation of Shock Effects in a Metapelitic Granulite; Experimental Reproduction of Shock Veins in Single-Crystal Minerals; Post-Shock Crystal-Plastic Processes in Quartz from Crystalline Target Rocks of the Charlevoix Impact Structure; Shock Reequilibration of Fluid Inclusions; How Does Tektite Glass Lose Its Water?; Assessing the Role of Anhydrite in the KT Mass Extinction: Hints from Shock-loading Experiments; A Mineralogical and Geochemical Study of the Nonmarine Permian/Triassic Boundary in the Southern Karoo Basin, South Africa; Extraterrestrial Chromium in the Permian-Triassic Boundary at Graphite Peak, Antarctica; Magnetic Fe,Si,Al-rich Impact Spherules from the P-T Boundary Layer at Graphite Peak, Antarctica; A Newly Recognized Late Archean Impact Spherule Layer in the Reivilo Formation, Griqualand West Basin, South Africa; Initial Cr-Isotopic and Iridium Measurements of Concentrates from Late Eocene Cpx-Spherule Deposits; An Ordinary Chondrite Impactor Composition for the Bosumtwi Impact Structure, Ghana, West Africa: Discussion of Siderophile Element Contents and Os and Cr Isotope Data.

Kyte, F. T.↗