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

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

MicroResonators for Compacts Optical Sensors (μRCOS)

As the demand for continuous, in-situ surveillance of health of systems and environments rapidly increases, miniaturized sensors with fast responses are sought. Optical dielectric resonators supporting Whispering Gallery Modes (WGMs) have exceptional properties, like very high-power density, very narrow spectral linewidth, and extremely small mode volume. As the footprint of these sensors is drastically reduced, measurements of microvolumes samples with dramatic reduction in analysis time are possible, enabling large numbers of parallel analyses using microarrays. The high sensitivity and speed of WGM resonators combined with the ability to detect molecules in their native state have great future potential for basic and applied research such as reliable single molecule, trace-gas detection, environmental monitoring, chemical threat sensing, and biodefense Such appealing peculiarities motivated us developing WMG resonators (WGMRs) for Cavity Enhanced Absorption Spectroscopy (CEAS) for chem-bio detection. Specifically, we designed and batch-fabricated microspheres and fiber tapers for resonances excitation. We successfully detected gases (N 2 and CO 2 ) in customized environmental chambers, and bio-organisms (Inf. A and E. Coli) with integrated microfluidic systems. Background calibration and environmental isolation were always accounted for in proving the performances.

36 MATERIALS SCIENCE↗
DOE OSTI2021

MicroResonators for Compacts Optical Sensors (μRCOS)

As the demand for continuous, in-situ surveillance of health of systems and environments rapidly increases, miniaturized sensors with fast responses are sought. Optical dielectric resonators supporting Whispering Gallery Modes (WGMs) have exceptional properties, like very high-power density, very narrow spectral linewidth, and extremely small mode volume. As the footprint of these sensors is drastically reduced, measurements of microvolumes samples with dramatic reduction in analysis time are possible, enabling large numbers of parallel analyses using microarrays. The high sensitivity and speed of WGM resonators combined with the ability to detect molecules in their native state have great future potential for basic and applied research such as reliable single molecule, trace-gas detection, environmental monitoring, chemical threat sensing, and biodefense Such appealing peculiarities motivated us developing WMG resonators (WGMRs) for Cavity Enhanced Absorption Spectroscopy (CEAS) for chem-bio detection. Specifically, we designed and batch-fabricated microspheres and fiber tapers for resonances excitation. We successfully detected gases (N 2 and CO 2 ) in customized environmental chambers, and bio-organisms (Inf. A and E. Coli) with integrated microfluidic systems. Background calibration and environmental isolation were always accounted for in proving the performances.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Understanding How Organizations Handle Cybersecurity

If there is anything we can learn from the media, it is the frequency and severity of cyber-attacks is increasing and there are not enough qualified people to combat the risk organizations are facing. Current estimates say there are 3.5 million available cybersecurity related jobs globally and there has been a 350% growth in cybersecurity jobs since 2013 (Group, 2020). The Idaho Cyber Research Project (ICRP) is focused on finding an implementing solution to the problems in the workforce development pipeline. Our team consists of Cohort 2 of the ICRP, we are tasked with solving issues faced by organizations hiring new cyber personnel. To provide solutions to these issues we focused our research on four components of workforce availability and competency: resume and transcript analysis, apprenticeships, cyber incident response plan development, and adversarial mindset training. From this research we have produced the following focus areas and subsequent steps for each component of workforce capability: transcript and knowledge skills abilities (KSA) focused analysis, cybersecurity apprenticeships programs, the value of an adversarial mindset, and a guide to setting up cyber incident response plans for underprepared organizations. These solutions can be further developed and implemented to reduce the gap in workforce demand and talent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Scaling Ultrahigh-Resolution E3SM Land Model for Leadership-Class Supercomputers

This paper presents advancements in scaling the ultrahigh-resolution E3SM Land Model (uELM) for deployment on leadership-class supercomputers, addressing the increased demand for km-scale Earth system modeling. By focusing on km-scale ELM simulations, we enhance predictive capabilities for climate interactions, facilitating improved responses to climate change impacts on energy systems, agriculture, and water resources. Our approach leverages innovative software architecture optimizations, sophisticated data handling techniques, and advanced parallel processing, achieving strong scalability on two leadership supercomputers (2400 nodes (105,600 cores) on Summit, and 1200 nodes (76,800 cores) on Frontier). Results from extensive scalability assessments on the Summit and Frontier also demonstrate outstanding I/O performance (close to 400 GB/s write throughput) and the model's ability to efficiently handle increasing computational demands. This study not only establishes uELM's capability for high-resolution simulations over vast geographical domains, but also sets a foundation for future Earth system modeling breakthroughs.

Wang, Dali [ORNL] (ORCID:0000000168065108)↗
DOE OSTI2020

Energy-Storage Fed Smart Inverters for Mitigation of Voltage Fluctuations in Islanded Microgrids

The continuous integration of intermittent low-carbon energy resources makes islanded microgrids vulnerable to voltage fluctuations. Besides, different dynamic response of synchronous-based and inverter-based distributed generation (DG) units can result in an instantaneous power imbalance between supply and demand during transients. As a result, the ac-bus voltage of microgrid starts oscillating which might have severe consequences such as blackouts. This paper modifies the conventional control scheme of battery energy storage systems (BESSs) to participate in improving the dynamic behavior of islanded microgrids by mitigating the voltage fluctuations. A piecewise linear-elliptic (PLE) droop is proposed and employed in BESS to achieve an enhanced voltage profile by injecting/absorbing reactive power during transients. In this way, the conventional inverter implemented in BESS turns into a smart inverter to cope with fast transients. Using the proposed approach in this paper, any linear droop curve with a specified coefficient can be replaced by a PLE droop curve. Compared with linear droop, an enhanced dynamic response is achieved by utilizing the proposed PLE droop. Case study results are presented using PSCAD/EMTDC to demonstrate the superiority of the proposed approach in improving the dynamic behavior of islanded microgrids.

Pilehvar, Mohsen S.↗
DOE OSTI2022

Intentional and Responsible Energy Transitions: Integrating Design Choices in the Pursuit of Carbon-Neutral Futures

The transitions of energy systems to carbon neutrality are among is one of the most ambitious, complex, uncertain, significant, and transformative projects in human history. They will therefore demand extraordinarily thoughtful, informed, and careful leadership. In recent years, this project has reached an important turning point, with widespread agreement to decarbonize energy systems by 2050. We argue that the next step is to engage leaders in doing the work necessary to achieve that goal. Specifically, we argue that regional leaders, across sectors, should build collaborative initiatives to intentionally and responsibly design and advance regional energy transitions. These transitions will entail navigating uncertain and unknown terrain, requiring diverse organizations and communities to work together to chart and construct potential pathways, assess their implications, and collectively work to make progress. To address these challenges, we recommend adopting region-first, anticipatory, justice-oriented approaches. In such approachesthis process, regions can collaboratively identify, deliberate, design, and navigate toward endpoints along complex and shifting pathways that recognize that design will matter. Efuture energy systems will deeply shape and be shaped by the futures of both societies and economies. Transitions will therefore need to be inclusive, to provide broad public input into both how to proceed with transitions and the goals that guide their design.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Characterization of Temperature Heterogeneity in Utility-Scale Power Plant Boilers by Spatially Distributed Ultrasonic Measurements

In extreme environments, even hardened insertion sensors fail quickly. For such environments, we have developed an ultrasonic (US) method for measuring the spatial distribution of temperatures in solid materials and, specifically, across containments of extreme processes. By deploying US sensors in multiple locations, spatial heterogeneity in temperatures inside harsh environments may be characterized. In this note, we update our progress on testing the developed approach in an industrial setting and its performance in describing the temperature distribution inside a 500 MW (electrical) coalfired utility boiler of an electrical power generation plant. We use waveguides (WG) structured to contain echogenic features that produce a train of echoes in response to an excitation pulse. The time of flight between echoes encodes the information on the temperature distribution in the corresponding segment of the WG, which we reconstruct using its parametrization. Five waveguides were welded to the boiler’s heat exchange surface (waterwall) and different locations at the same boiler elevation and produced reliable US waveforms 18 months after the installation. For several weeks during the latest trial, we performed US measurements in five locations spanning half of the boiler’s 14-meter width. The measurements were acquired during regular operation, including load cycling to adjust for demand and intermittent contributions of renewable power sources, and during boiler shutdown for emergency maintenance and the subsequent restart. The interpretation of US waveforms by signal processing resulted in an accurate estimation of temperature distribution along the waveguides. We captured daily cyclical variations in demand-following load. Measurements performed in multiple locations revealed unexpected temperature variations across the boiler. We conclude that an array of developed sensors can provide responsive and spatial temperature measurements while maintaining functionality despite prolonged exposure to an extreme environment.

Walton, Kenneth↗
DOE OSTI2025

ClimGen: Learning the Forcing-Response Relationship in Climate System

Solar Radiation Management (SRM) is emerging as a potential geoengineering strategy to address the anthropogenic impact on climate, but its effective implementation requires an iterative and large ensemble of highly accurate and efficient climate projections. Traditional climate projections rely on executing computationally demanding and time-consuming numerical climate models. Recent advances in machine learning (ML) aim to enhance these approaches by emulating traditional methods. In this work, we propose a novel framework for directly learning the relationship between solar radiation flux at the top of the atmosphere and the corresponding surface temperature response. To evaluate the feasibility of this direct ML-based projection, we developed a dataset using an intermediate complexity model, incorporating a comprehensive suite of different forcing patterns and evaluation metrics to rigorously assess the ML model’s performance. We introduce a Conditional Denoising Diffusion Probabilistic Model (cDDPM) for this task, which demonstrates encouraging skill in representing climate statistics under previously unseen forcing patterns. This approach provides a promising pathway for direct climate projections by accurately learning the forcing-response relationship, with a wide range of applications in impact mitigation, emissions policy design, and SRM strategies.

Chen, Tse-Chun [BATTELLE (PACIFIC NW LAB)] (ORCID:↗
DOE OSTI2023

Multi-scale planning model for robust urban drought response

Increasingly severe droughts are straining municipal water resources and jeopardizing urban water security, but uncertainty in their duration, frequency, and intensity challenges drought planning and response. We develop the Drought Resilient Interscale Portfolio Planning model (DRIPP) to generate optimal planning responses to urban drought. DRIPP is a generalizable multi-scale framework for optimizing dynamic planning strategies of long-term infrastructure deployment and short-term drought response. It integrates climate and hydrological variability with high-fidelity representations of urban water distribution, available technology options, and demand reduction measures to yield robust and cost-effective water supply portfolios that are location-specific. We apply DRIPP in Santa Barbara, California to assess how least cost water supply portfolios vary under different drought scenarios and identify portfolios that are robust across drought scenarios. In Santa Barbara, we find that drought intensity, not duration or frequency, drives cost increases, reliability risk, and regret of overbuilding infrastructure. Under uncertain drought conditions, a diversified technology portfolio that includes both rapidly deployable, decentralized technologies alongside larger centralized technologies minimizes water supply cost while maintaining high robustness to climate uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Performance-based earthquake early warning for tall buildings

The ShakeAlert Earthquake Early Warning (EEW) system aims to issue an advance warning to residents on the West Coast of the United States seconds before the ground shaking arrives, if the expected ground shaking exceeds a certain threshold. However, residents in tall buildings may experience much greater motion due to the dynamic response of the buildings. Therefore, there is an ongoing effort to extend ShakeAlert to include the contribution of building response to provide a more accurate estimation of the expected shaking intensity for tall buildings. Currently, the supposedly ideal solution of analyzing detailed finite element models of buildings under predicted ground-motion time histories is not theoretically or practically feasible. The authors have recently investigated existing simple methods to estimate peak floor acceleration (PFA) and determined these simple formulas are not practically suitable. Instead, this article explores another approach by extending the Pacific Earthquake Engineering Research Center (PEER) performance-based earthquake engineering (PBEE) to EEW, considering that every component involved in building response prediction is uncertain in the EEW scenario. Additionally, while this idea is not new and has been proposed by other researchers, it has two shortcomings: (1) the simple beam model used for response prediction is prone to modeling uncertainty, which has not been quantified, and (2) the ground motions used for probabilistic demand models are not suitable for EEW applications. In this article, we address these two issues by incorporating modeling errors into the parameters of the beam model and using a new set of ground motions, respectively. We demonstrate how this approach could practically work using data from a 52-story building in downtown Los Angeles. Using the criteria and thresholds employed by previous researchers, we show that if peak ground acceleration (PGA) is accurately estimated, this approach can predict the expected level of human comfort in tall buildings.

58 GEOSCIENCES↗
DOE OSTI2021

Powering Post-COVID-19 Resilient Recovery with Green Stimulus

As the coronavirus disease (COVID-19) pandemic spread globally in early 2020, many governments enacted lockdown measures as an initial containment response. These lockdowns, while effective in slowing infection rates, have also had substantial economic consequences. A series of supply and demand shocks, workforce and supply chain disruptions, and other impacts of the pandemic and ensuing lockdowns have upended the livelihoods for much of the world's population. This quick read spotlights how green stimulus plans and other recovery measures can support near-term recovery and enable longer-term power system resilience against future threats. The term “green stimulus” encompasses fiscal measures (i.e., governmental tax and spending actions) that support short-term economic activity that enhances environmental and natural resource quality over a longer term. The deployment of energy efficiency (EE) and renewable energy (RE) technologies, as well as associated initiatives (e.g., grid modernization, electrification of transport, and so on) have been demonstrably effective in providing this kind of short-run economic boost while simultaneously strengthening the resilience of the power sector. Along with green stimulus packages, concurrent action on the regulatory side—for example, the development of green building codes, updating grid interconnection standards, creating programs and marketplaces for demand-side efficiency, and others—can be a force multiplier in ensuring that public spending achieves maximum impact in near-term recovery and long-term power sector transformation

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Security-by-Design: Light Water Small Modular Reactor

The growing demand for nuclear power is increasing pressure to find solutions to cost prohibitive requirements of both construction and security. Offsite response has been proposed as an option to reduce costs associated with training and maintaining an onsite response force. A previous report explored this option and revealed that security could be provided at the required level, but cost savings was not a result of this methodology. An offsite response strategy required costly active and passive delay barriers to provide sufficient time for responders to muster and deploy to a site in time to interrupt a determined and well-equipped adversary. Also, contrary to the hypothesis, the number of responders required for this strategy exceeded that needed for an onsite response force, as the adversaries could avail themselves of advantageous positions within the facility to repel arriving responders. This report builds upon the previous evaluation by using the same hypothetical light water small modular reactor (LWSMR) facility model, but this time an onsite response strategy was assessed. The goal of this analysis was to show that an onsite response strategy could be implemented effectively at a cost point that removes barriers within the industry at this critical time of growth and development. The assessment of the facility design and response strategy was completed through modeling using Scribe3D© and subsequent scenario analysis over the course of a two-day tabletop exercise. Subject matter experts in nuclear security, nuclear facility design, and response strategy and tactics contributed to the effort to ensure accurate representation of hypothetical scenarios. Several adaptations were made to the layout of the LWSMR based on lessons learned during the first day of scenario analysis. The subsequent design evaluated on the second day proved to provide a robust response posture against a large and well-trained adversary force. This report details the process of the analysis and compares the cost of the final facility design with that of the LWSMR model used for evaluation of offsite response. Ultimately, the results of this effort indicate that, when implemented correctly, an onsite response strategy is the best option from a security and cost perspective.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Best Practices for Resilience in Smart Grid-Interactive Efficient Buildings

The Federal Energy Management Program (FEMP) supports federal agencies' energy decisions with information and guidance on design, funding, and operations to ensure federal buildings are efficient and resilient. The modernization of building infrastructure and the evolution of buildings to support decarbonization involves complex implementation of multiple components across several systems. This includes energy-efficient equipment, on-site energy generation and storage systems, and control systems. These systems have operational modes that can operate more efficiently if they are able to behave responsively to the conditions of the electrical grid. These grid-interactive efficient buildings (GEB) allow facilities to manage power demand according to operational constraints and market signals issued by grid operators. With proper design and planning, these same capabilities have the potential to enable building and facility resilience - coordinating with microgrids, maintaining power on critical circuits to sustain essential operations, and monitoring building health and safety status during an outage. By managing the load of buildings, GEBs can also reduce the cost of backup generation and make better use of renewable power sources on site. This document outlines some of the processes and considerations to guide the design and operation of GEBs in ways that promote facility resilience.

building decarbonization↗
DOE OSTI2021

Spectral Fidelity of Earth's Terrestrial and Aquatic Ecosystems

The Surface Biology and Geology (SBG) investigation will create global maps of spectral surface reflectance and emissivity at a cadence of 16 days or better, with coverage to address global questions about Earth's geology, cryosphere and ecosystems. The revolutionary potential poses a commensurate challenge: creating contiguous maps free from regional biases induced by atmosphere, observation geometry, or inversion error. This will require an accurate calibration with precise knowledge of each channel's spectral response. In this work, we quantify the impact of spectral calibration on SBG's aquatic and terrestrial ecosystem objectives. We find that contemporary algorithms for ecosystem trait retrieval demand more accurate spectral calibration than historical missions. Errors due to drift or spatial nonuniformity in the wavelength calibration that have previously been considered acceptable can cause systematic errors larger than the instrument noise and of the same order as the variability SBG aims to measure. Moreover, their impact on atmospheric correction can induce climate-dependent systematic errors that thwart comparisons between ecosystems. These results underscore the importance of spectral response accuracy in SBG mission design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dynamics of organic matter molecular composition under aerobic decomposition and their response to the nitrogen addition in grassland soils

Grassland soils store a substantial proportion of the global soil carbon (C) stock. The transformation of C in grassland soils with respect to chemical composition and persistence strongly regulate the predicted terrestrial-atmosphere C flux in global C biogeochemical cycling models. In addition, increasing atmospheric nitrogen (N) deposition alters C chemistry in grassland soils. However, there remains controversy about the importance of mineralogical versus biochemical preservation of soil C, as well as uncertainty regarding how grassland soil C chemistry responds to elevated N. This study used grassland soils with diverse soil organic matter (SOM) chemistries in an 8-month aerobic incubation experiment to evaluate whether the chemical composition of SOM converged across sites over time, and how SOM persistence responded to the N addition. This study demonstrates that over the course of incubation, the richness of labile compounds decreased in soils with less ferrihydrite content, whereas labile compounds were more persistent in ferrihydrite rich soils. In contrast, we found that the richness of more complex compounds increased over the incubation in most sites, independent of soil mineralogy. Moreover, we demonstrate the extent to which the diverse chemical composition of SOM converged among sites in response to microbial decomposition. N fertilization decreased soil respiration and inhibited the convergence of molecular composition across ecosystems by altering N demand for microbial metabolism and chemical interactions between minerals and organic molecules. This study provides original evidence that the decomposition and metabolism of labile organic molecules were largely regulated by soil mineralogy (physicochemical preservation), while the metabolism of more complex organic molecules was controlled by substrate complexity (biochemical preservation) independent to mineral-organic interactions. This study advanced our understanding of the dynamic biogeochemical cycling of C by unveiling that N addition dampened C respiration and diminished the convergence of SOM chemistry across diverse grassland ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nano-spectroscopy of excitons in atomically thin transition metal dichalcogenides

Abstract Excitons play a dominant role in the optoelectronic properties of atomically thin van der Waals (vdW) semiconductors. These excitons are amenable to on-demand engineering with diverse control knobs, including dielectric screening, interlayer hybridization, and moiré potentials. However, external stimuli frequently yield heterogeneous excitonic responses at the nano- and meso-scales, making their spatial characterization with conventional diffraction-limited optics a formidable task. Here, we use a scattering-type scanning near-field optical microscope (s-SNOM) to acquire exciton spectra in atomically thin transition metal dichalcogenide microcrystals with previously unattainable 20 nm resolution. Our nano-optical data revealed material- and stacking-dependent exciton spectra of MoSe 2 , WSe 2 , and their heterostructures. Furthermore, we extracted the complex dielectric function of these prototypical vdW semiconductors. s-SNOM hyperspectral images uncovered how the dielectric screening modifies excitons at length scales as short as few nanometers. This work paves the way towards understanding and manipulation of excitons in atomically thin layers at the nanoscale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Data‐driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Summary Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well‐studied major crops. Using 727 maize ( Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre‐ and postanthesis maximum temperature, mid‐season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well‐studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Kusmec, Aaron↗