Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “time service”

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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Embedding of Fiber Optic Sensors in Stainless Steel for Sensing in Harsh Environments

Structural health monitoring is critical for components working in harsh environments to assess their safety and integrity. This can be realized with advanced sensors, such as fiber optic sensors, embedded in these components. Recent studies have used ultrasonic consolidation (UC) and laser-based additive manufacturing (AM) techniques to embed fiber optic sensors in metals. However, sensor embedding using these techniques has been challenging, with gaps and voids around the embedded fiber. Successful embedding of fiber optic sensors requires good contact between the fiber and the matrix to eliminate potential gas/liquid leaks in critical systems such as in nuclear and aerospace services. Defect-free fiber/matrix bond is also essential for accurate measurement of parameters of interest, such as temperature and strain. This study developed a novel fiber embedding technique based on electric field-assisted sintering (EFAS). Sapphire optical fibers with diameters of 125 µm and 250 µm were embedded in stainless steel (SS) 316L using EFAS. The embedding was completed by sintering SS 316L powders at a pressure of 50MPa, hold time of 5 min, and temperatures of 1000°C, 1100°C, and 1200°C. Joule heating mechanism during EFAS enabled rapid sintering of the SS 316L powder with resulting sample densities over 99%. Microscopy analysis performed on the cross-sections revealed a defect-free bond between the embedded fiber and SS 316L. The good integrity of the embedded fiber was evidenced by optical transmittance measurement. Optical attenuation of the fiber before and after embedment was examined in the near-infrared region. Scanning electron microscopy was employed to investigate the grain morphology of SS 316L near the embedded fiber. Hardness distribution in the sintered part was also investigated to study the effect of the embedded fiber on the mechanical properties of the as-fabricated component. The results indicated that EFAS was able to embed fiber in SS with good fiber functionality and part quality.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments

The study presented here focuses on performance characteristics and trade-offs associated with running machine-learning tasks in multi-GPU environments on both on-site cloud computing resources and commercial cloud services (Azure). Specifically, this study examines these tradeoffs by examining the performance of training and fine-tuning of transformer-based deep-learning (DL) networks on clinical notes and data, a task of critical importance in the medical domain. To this end, we perform DL-related experiments on the widely deployed NVIDIA V100 GPUs and on the newer A100 GPUs connected via NVLink or PCIe. This study analyzes the execution time of major operations to train DL models and investigate popular options to optimize each of them. We examine and present the findings on the impacts that various operations (e.g. data loading into GPUs, training, fine-tuning), optimizations, and system configurations (single vs. multi-GPU, NVLink vs. PCIe) have on the overall training performance.

Begoli, Edmon↗
DOE OSTI2024

CORSAIR: A Framework for Human Mobility Prediction through Visit Characterization and Spatial Behavior Modeling

The rapid advancement of location acquisition technologies has led to the daily collection of vast amounts of mobile trajectory data, facilitating in-depth research on human mobility and enabling more accurate mobility prediction models. However, existing methodologies often fall short in capturing the intricate dynamics of human navigation and spatial behavior. This paper addresses this gap by exploring the multifaceted relationships between individuals and their environments, considering the diverse influences of personal preferences and experiences. Some places hold sentimental value and are visited frequently, while others serve as transient points of passage. To model these differences, we introduce CORSAIR, a novel visit characterization framework that leverages visitation patterns and dwell times to delineate an individual’s relationship with specific places. CORSAIR classifies visits into seven distinct types: casual, occasional, routine, special, anchor, important, and resettling. Also, we show that explicitly recognizing these distinct visit types and incorporating nuanced visit intents into mobility prediction models leads to a substantial improvement in prediction accuracy. This distinction allows for more precise modeling of the individual’s transitions, enhancing the personalization and relevance of location-based services. Our findings suggest that a deeper understanding of the complexities of individual-environment interactions is crucial for developing effective predictive tools in mobility research.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗
DOE OSTI2021

Application of Principal Component Analysis for the Monitoring of the Aging Process of Nuclear Electrical Cable Insulation

To ensure the safe operation of nuclear power plants (NPPs), it is critical to understand how NPP electrical cable insulation will degrade under different service environments. In this study, various nondestructive examination methods were selected to evaluate degradation of electrical cable insulation after aging. Elongation at break, indenter modulus, relaxation constant, mass change, total color difference, and carbonyl index were collected stepwise on cross-linked polyethylene (XLPE) cable insulations after predetermined exposure intervals. Three different insulation aging scenarios were investigated: 1) simultaneous irradiation and heating at 150°C, 2) heating at 150°C followed by corresponding times of irradiation at ambient temperature, and 3) irradiation at ambient temperature followed by heating at 150°C for the same duration. A constant dose rate of 300 Gy/hr was selected with a total gamma irradiation absorbed dose up to 320 kGy. To gain insight into the long-term performance of NPP electrical cable insulation, principal component analysis (PCA), a data-driven approach, was utilized to identify key indicators of cable insulation degradation. By reducing the dimensionality of the data while retaining degradation information, PCA was used to highlight the changes in the measured properties under gamma irradiation according to total absorbed dose and the different aging scenarios.

Li, Donghui↗
DOE OSTI2022

Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements

An emerging use-case of machine learning (ML) is to train a model on a high-performance system and deploy the trained model on energy-constrained embedded systems. Neuromorphic hardware platforms, which operate on principles of the biological brain, can significantly lower the energy overhead of a machine learning inference task, making these platforms an attractive solution for embedded ML systems. In this paper, we present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a Non-Volatile Memory (NVM)-based neuromorphic hardware. Through detailed circuit-level simulations at scaled process technology nodes, we show the negative impact of technology scaling on the information-processing latency, which impacts the quality-of-service (QoS) of an embedded ML system. At a finer granularity, the latency inside a PE depends on 1) the delay introduced by parasitic components on its current paths, and 2) the varying delay to sense different resistance states of its NVM cells. Based on these two observations, we make the following three contributions. First, on the technology front, we propose an optimization scheme where the NVM resistance state that takes the longest time to sense is set on current paths having the least delay, and vice versa, reducing the average PE latency, which improves the QoS. Second, on the architecture front, we introduce isolation transistors within each PE to partition it into regions that can be individually power-gated, reducing both latency and energy. Finally, on the system-software front, we propose a mechanism to leverage the proposed technological and architectural enhancements when implementing a machine-learning inference task on neuromorphic PEs of the hardware. Evaluations with a recent neuromorphic hardware architecture show that our proposed design-technology co-optimization approach improves both performance and energy efficiency of machine-learning inference tasks without incurring high cost-per-bit.

42 ENGINEERING↗
DOE OSTI2022

2022 GETEM Geothermal Drilling Cost Curve Update

The Geothermal Electricity Technology Evaluation Model (GETEM) is an essential tool for the U.S. Department of Energy's (DOE) Geothermal Technologies Office (GTO) to understand the performance and cost of technologies it is seeking to improve. This detailed model is used for supply curve analyses, assessing the current economic feasibility and levelized cost of energy (LCOE) of hydrothermal geothermal systems and enhanced geothermal systems (EGS), and evaluating the potential impact of advanced geothermal technologies. GETEM can be used to estimate the performance and costs of currently available U.S. geothermal power systems. It is also used to estimate the costs of technologies 5 to 20 years in the future, given the direction of potential research, development, and demonstration (RD&D) projects. The model is intended to help GTO determine which proposed RD&D programs and projects might offer the most efficient improvement when using taxpayer funding. The model requires annual updates as well as revisions to reflect the current state of the art. Drilling costs are a significant portion of total geothermal development costs. The current GETEM drilling cost inputs rely on drilling data from 2009 and require an updated analysis of more recent data to ensure they remain representative of current technologies. An updated, more accurate understanding of costs could help the geothermal industry secure project development financing and investment funding and better allow the oil and gas (O&G) industry (both operators and service companies) to weigh potential geothermal market participation and customization. This report details recent drilling improvements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) and the O&G sector, comparing drilling performance and costs with values in GETEM, particularly the baseline drilling cost curves. Although drilling performance at FORGE has improved significantly, we did not find associated cost decreases that would justify lowering the GETEM baseline cost curves at this time.

API↗
DOE OSTI2024

BESSIE: Battery & Energy Storage Supply Chain Analysis, Mitigation Deployment, and Tools

Battery energy storage systems (BESS) and their associated power electronic interfaces are key components to delivering clean and more resilient energy, providing much-needed fast-ramping, emergency discharge, generation, and operations support to the electric grid. These services have grown to be invaluable over the past ten years and will soon be an irreplaceable element of energy delivery. The Idaho National Laboratory (INL) strives to address these challenges through a strategic approach to supply chain risk assessment and mitigation for BESS and related digital energy equipment through the BESSIE project under the Center for Securing Digital Energy Technology. Recognizing that decreasing dependence on a foreign supply chain will take significant time and investment, BESSIE’s focus is strategically addressing battery supply chain risks by pairing short-term steps to operate securely through today’s risks with long-term steps to shape the supply chain over the coming years.

25 ENERGY STORAGE↗
DOE OSTI2021

Quantifying the anomalous water absorption behavior of cement mortar in view of its physical sensitivity to water

The one-dimensional water absorption into cement-based materials, possibly the simplest case of unsaturated water flow playing a fundamental role in predicting mass transport and durability, is still far from being completely understood due to several puzzling anomalies. Considering the water sensitivity of C-S-H gels (swell upon wetting and contract upon drying), a modified Richards equation (MRE) is proposed to quantify the anomalous water absorption into cement-based materials of changing porosity. Consistent experimental tests on a cement mortar and calculations indicate that the MRE with time-decaying water permeability can quantitatively capture the long-term absorption with two linear stages and a nonlinear transition stage between them. The water sensitivity is validated to be responsible for the anomalous deviation of water absorption from the classical square root of time law. It also partially contributes to the anomalous dependence of sorptivity on the temperature-dependent surface tension and viscosity of water and many organic liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Siting and sizing of public–private charging stations impacts on household and electric vehicle fleets

To facilitate the provision of electric vehicle charging stations (EVCS) in urban areas, this study investigates the benefits of co-locating fleet-owned chargers with public charging stations to enable construction incentives and cord-sharing cost savings. Shared EVCS can serve charging demand from both user types: private (household) EV owners and those managing fleet vehicles – like shared and fully automated EV (SAEV) fleets. Using POLARIS to simulate all person-travel across the 6-county Austin, Texas region, new EVCS were sited and sized with DC fast-charging (DCFC) plugs to lower operating and construction costs while providing public + private (PP) service across an 81-square-mile core geofence (where 200 SAEVs were active) over 24-hour days. When co-location is permitted, 115 DCFC cords were added to the 23 existing (publicly available) stations to enable SAEVs and household EVs (HHEVs) charging access, within the geofence. Each 250-mile-range SAEV was simulated to travel an average of 330 miles per day, serve over 92 person-trips, and recharge 2.7 times a day (for 2.4 h per session). The new DCFC plugs were primarily added to public EVCS at shopping centers and schools, and in residential settings along freeways. The average plug served 4.8 EVs per day. Most co-located PP EVCS permitted immediate (no-wait) charging, except for 2 stations along freeways that averaged 8 min of wait time to begin charging. In conclusion, the co-location strategy lowered fleet owners’ initial EVCS construction costs by 12 % (thanks to cord-sharing to avoid cord duplication), while reducing SAEV wait times to just 3.1 min (versus 10.7 min if SAEV managers had to build and operate their own EVCS).

EV charging modeling↗
DOE OSTI2024

The Importance of Accounting for Landscape Position When Investigating Grasslands: A Multidisciplinary Characterisation of a California Coastal Grassland

Abstract Grasslands are one of the most common land‐cover types, providing important ecosystem services globally, yet few studies have examined grassland critical‐zone functioning throughout hillslopes. This study characterised a coastal grassland over a small hillslope at Point Reyes National Seashore, California, using multidisciplinary techniques, combining remotely‐sensed, geophysical, plant, and soil measurements. Clustering techniques delineated the study area into four landscape zones, up‐, mid‐, and down‐slope, and a bordering riparian ecotone, which had distinct environmental properties that varied spatially across the site, with depth, and time. Soil moisture increased with depth and down slope towards a bordering riparian zone, and co‐varied with soil CO 2 flux rates both spatially and temporally. This highlighted three distinct controls of soil moisture on soil respiration: CO 2 fluxes were inhibited by high moisture content in the down‐slope during the wet winter months, and converged across landscape positions in the dry summer months, while also displaying post‐rain pulses. The normalised difference vegetation index (NDVI) ranged from 0.32 (September)–0.80 (April) and correlated positively with soil moisture and aboveground biomass, moving down slope. Yet, NDVI, aboveground biomass, and soil moisture were not correlated to soil organic carbon (SOC) content (0.4%–4.5%), which was highest in the mid‐slope. The SOC content may instead be linked to shifts in dominant grassland species and their rhizosphere properties with landscape position. This multidisciplinary characterisation highlighted significant heterogeneity in grassland properties with landscape position, and demonstrated an approach that could be used to characterise other critical‐zone environments on hillslopes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

AmeriFlux US-GL1 Stannard Rock

This is the AmeriFlux version of the carbon flux data for the site US-GL1 Stannard Rock. Site Description - Stannard Rock is located 39 km from the nearest shore (Keweenaw Peninsula) in Lake Superior, 44 miles NNE of Marquette, Michigan, and 24 miles ESE of Manitou Island. The site is located on the historic Stannard Rock Lighthouse, which was completed in 1882. Eddy covariance instrumentation was installed in 2008 by a network of scientists from both US and Canada, eventually to be called the Great Lakes Evaporation Network (GLEN). The intent of GLEN has been to provide observations of over-lake meteorology and evaporation, improve forecasting of Great Lakes water levels, and support a wide variety of stakeholders, including the National Weather Service (NWS), Environment and Climate Change Canada, National Oceanic and Atmospheric Administration, U.S. Coast Guard, recreational boaters and commercial shipping, emergency management officials, and the Great Lakes research community. The eddy covariance station along with other ancillary meteorological instrumentation is located at an approximate elevation of 39.2 meters above mean lake water level. Meteorological data from the lighthouse are sent to the National Data Buoy Center, where they can be viewed in real-time at http://www.ndbc.noaa.gov/station_page.php?station=stdm4 Uncorrected half-hour fluxes were computed directly on the logger using a 30-minute block averaging period as high-frequency data were not available. The half hour flux measurements downloaded from the datalogger were post-processed with the following filters and corrections. Latent and sensible heat and carbon dioxide fluxes were corrected with 2-D coordinate rotation. Although the primary objective of data collection at Stannard Rock was to quantify the evaporative flux, additional preliminary measurements of the carbon dioxide concentration and flux from the LI-7500 are also included in this dataset but it is advised to use the carbon data with caution. Carbon data reported in this dataset includes turbulent fluxes of CO2 with no storage correction (FC, µmol m-2 s-1) and CO2 density in mole fraction of wet air (CO2), which was originally output on the datalogger as average CO2 density (mg m-2 s-1) and converted into µmol mol-1 using air temperature and pressure in post-processing. Webb, Pearman, and Leuning terms were applied to account for density fluctuations for water vapor and CO2. Sonic path length, high-frequency attenuation and sensor separation were accounted for according to Horst and Massman, and the oxygen absorption correction for the KH2O hygrometer was also applied. Latent and sensible heat fluxes were assumed to be unrealistic above an absolute value of 1000 W m-2 and were removed. Both carbon flux (FC) and carbon dioxide mole fraction in wet air (CO2) and were assumed to be unrealistic above 1000 µmol m-2 s-1 and 1000 µmol mol-1 respectively. Spikes in latent and sensible heat and carbon fluxes and densities (often due to periods of precipitation) were identified by computing the mean and standard deviation over a moving, overlapping window of 336 half-hours (7 days), similar to Shao et al., and were removed when the flux was more than 1.5 standard deviations from the moving window’s mean. While Vickers and Mahrt use a threshold of 3.5 standard deviations from the mean, a conservative value of 1.5 was chosen due to the noisy nature of over-lake data at this particular site. This process was repeated twice for latent and sensible heat, and carbon dioxide fluxes and densities and therefore it is possible that some real, realistic data was filtered out in this process. No detrending was performed. As per AmeriFlux standards, no friction velocity (USTAR, m s-1) filtering was performed.

Spence, Chris↗
DOE OSTI2025

AmeriFlux FLUXNET-1F US-GL1 Stannard Rock

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-GL1 Stannard Rock. This is the FLUXNET version of the carbon flux data for the site US-GL1 Stannard Rock produced by applying the standard ONEFlux (1F) software. Site Description - Stannard Rock is located 39 km from the nearest shore (Keweenaw Peninsula) in Lake Superior, 44 miles NNE of Marquette, Michigan, and 24 miles ESE of Manitou Island. The site is located on the historic Stannard Rock Lighthouse, which was completed in 1882. Eddy covariance instrumentation was installed in 2008 by a network of scientists from both US and Canada, eventually to be called the Great Lakes Evaporation Network (GLEN). The intent of GLEN has been to provide observations of over-lake meteorology and evaporation, improve forecasting of Great Lakes water levels, and support a wide variety of stakeholders, including the National Weather Service (NWS), Environment and Climate Change Canada, National Oceanic and Atmospheric Administration, U.S. Coast Guard, recreational boaters and commercial shipping, emergency management officials, and the Great Lakes research community. The eddy covariance station along with other ancillary meteorological instrumentation is located at an approximate elevation of 39.2 meters above mean lake water level. Meteorological data from the lighthouse are sent to the National Data Buoy Center, where they can be viewed in real-time at http://www.ndbc.noaa.gov/station_page.php?station=stdm4 Uncorrected half-hour fluxes were computed directly on the logger using a 30-minute block averaging period as high-frequency data were not available. The half hour flux measurements downloaded from the datalogger were post-processed with the following filters and corrections. Latent and sensible heat and carbon dioxide fluxes were corrected with 2-D coordinate rotation. Although the primary objective of data collection at Stannard Rock was to quantify the evaporative flux, additional preliminary measurements of the carbon dioxide concentration and flux from the LI-7500 are also included in this dataset but it is advised to use the carbon data with caution. Carbon data reported in this dataset includes turbulent fluxes of CO2 with no storage correction (FC, µmol m-2 s-1) and CO2 density in mole fraction of wet air (CO2), which was originally output on the datalogger as average CO2 density (mg m-2 s-1) and converted into µmol mol-1 using air temperature and pressure in post-processing. Webb, Pearman, and Leuning terms were applied to account for density fluctuations for water vapor and CO2. Sonic path length, high-frequency attenuation and sensor separation were accounted for according to Horst and Massman, and the oxygen absorption correction for the KH2O hygrometer was also applied. Latent and sensible heat fluxes were assumed to be unrealistic above an absolute value of 1000 W m-2 and were removed. Both carbon flux (FC) and carbon dioxide mole fraction in wet air (CO2) and were assumed to be unrealistic above 1000 µmol m-2 s-1 and 1000 µmol mol-1 respectively. Spikes in latent and sensible heat and carbon fluxes and densities (often due to periods of precipitation) were identified by computing the mean and standard deviation over a moving, overlapping window of 336 half-hours (7 days), similar to Shao et al., and were removed when the flux was more than 1.5 standard deviations from the moving window’s mean. While Vickers and Mahrt use a threshold of 3.5 standard deviations from the mean, a conservative value of 1.5 was chosen due to the noisy nature of over-lake data at this particular site. This process was repeated twice for latent and sensible heat, and carbon dioxide fluxes and densities and therefore it is possible that some real, realistic data was filtered out in this process. No detrending was performed. As per AmeriFlux standards, no friction velocity (USTAR, m s-1) filtering was performed.

Spence, Chris [Environment and Climate Change Cana↗
DOE OSTI2020

Modular, Mobile Systems for the Treatment of Contaminated Water at Three Magnox Sites in the United Kingdom - 20421

Veolia Nuclear Solutions (VNS), and its mitigated entity, Veolia Nuclear Solutions Federal Services (VNSFS), are designing, overseeing the fabrication and installation, and supporting the commissioning of highly mobile and modular skid-based water treatment systems to assist in the decommissioning of three Magnox reactor sites based in the U.K. These Modular Active Effluent Treatment Plants (MAETP) will be deployed at the Chapelcross, Hinkley Point A, and Dungeness A sites to process contaminated water through the use of ion exchange systems and/or filtration units. At the time of writing, two systems have been installed and inactively commissioned, and the third system is expected to be delivered in 2020. Veolia has utilized a multi-national team of engineers, based in the UK and the US, to effectively leverage the best of Veolia expertise in the design and delivery of mobile, modular systems. The VNS team continues to refine the modular, mobile, and scalable approach to water processing system delivery, and has successfully patented the evolving technology for proprietary protection. The intent of this technology investment is to improve the functionality, mobility, and modularity, resulting in a system which can be adapted to a broad range of throughput and isotope removal requirements to achieve the most cost effective, flexible system possible for customers. Designing, fabricating, and factory-testing the modules off site followed by onsite installation, testing, start-up, and commissioning ensures expedited delivery and setup, as well as cost savings for nuclear applications. For the MAETP systems, VNS's previous nuclear site experience and ongoing Research and Development (R and D), combined with the resulting mobile/modular water processing systems developed and successfully deployed by VNS, have proven to be important inputs for the successful end-design of the systems, materials selection, system testing and commissioning. The lessons learned in the development and continued enhancement of the patented systems described in this paper will prove useful in advancing and deploying future systems for other nuclear sites, where rapid customizing and cost-effective implementation are critical factors. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Preventing Reverse Engineering of Critical Industrial Data with DIOD

Business analytics augmented by artificial intelligence and machine learning (AI/ML) have revolutionized the role of data in the modern world. In recent years, businesses have incorporated data into their decision-making process for better prediction, risk-assessment, content creation, etc. While such businesses often seek to leverage the full use of their data through third-party AI/ML services, they are often hampered by the risks of data leaks, reverse-engineering, stolen technology, etc. that often have disastrous consequences for businesses and their stakeholders alike. Thus, there arises a need for data masking prior to its transmission that obfuscates proprietary information while preserving the information relevant for AI/ML applications. In order to meet the needs of industrial data which are significantly different from those of data warehouses, previous work proposed an efficient time and space-scalable data masking paradigm known as the deceptive infusion of data (DIOD) methodology. The present work expands upon this work by leveraging existing reverse-engineering capabilities to facilitate the decomposition of industrial data into its proprietary and AI/ML-relevant parts, referred to as fundamental and inference metadata respectively. Both sets of metadata are further obfuscated in accordance with the DIOD methodology to create the DIOD rendition of the industrial data, which is rendered immune to reverse-engineering by discarding proprietary information and only preserving AI/ML-relevant information. Additionally, constraints of the original DIOD manuscript are relaxed using mutual information by configuring the methodology to the target AI/ML application to unlock the full potential of the DIOD methodology. As an example, data from a nuclear reactor is transformed into that from a nonlinear spring-mass system with different levels of data masking as required by the generic system and the target application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Cosimulating Integrated Energy Systems With Heterogeneous Digital Twins: Matching a Connected World

Energy system integration promises in-creased resiliency and the unlocking of synergies, while also contributing to our goal of decarbonization. It is enabled by both old and new technologies, glued together with data and digital services. Hydrolyzers, heat pumps, distributed renewable generation, smart buildings, and the digital grid edge are all currently the subject of integration with the power system and the energy sector at large. To plan and operate such a multidisciplinary and multisectoral system properly, insight, tools, and expertise are all needed. Further, this is exactly where the state of the art fails to deliver: tools for integrated energy systems (IESs) are still in their infancy, and many times, even academia treats these sectors separately, producing experts in each of them but not across.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Permafrost and Climate Change: Carbon Cycle Feedbacks From the Warming Arctic

Rapid Arctic environmental change affects the entire Earth system as thawing permafrost ecosystems release greenhouse gases to the atmosphere. Understanding how much permafrost carbon will be released, over what time frame, and what the relative emissions of carbon dioxide and methane will be is key for understanding the impact on global climate. In addition, the response of vegetation in a warming climate has the potential to offset at least some of the accelerating feedback to the climate from permafrost carbon. Temperature, organic carbon, and ground ice are key regulators for determining the impact of permafrost ecosystems on the global carbon cycle. Together, these encompass services of permafrost relevant to global society as well as to the people living in the region and help to determine the landscape-level response of this region to a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Preliminary description of a new creep-fatigue design method that reduces over conservatism and simplifies the high temperature design process

The report provides the initial description of a new creep-fatigue design method for structural components in high temperature nuclear service. The new method is based on an integrated elastic-perfectly plastic (EPP) analysis and Simplified Model Test (SMT) approach that reduces over conservatism, improves the treatment of elastic follow up, and simplifies the design procedure, when compared with the current creep-fatigue design methods in ASME Boiler and Pressure Vessel Code. Developing the design charts for the EPP-SMT design method requires extrapolating SMT test data as a function of hold time and follow up factor. The report develops the preliminary design charts for Alloy 617 at temperatures between 800°C and 950°C by combining two extrapolation approaches developed in a previous work. The report also presents a comparative analysis between the EPP-SMT design method and the current ASME creep-fatigue design methods by evaluating design life of two sample geometries under different loading conditions. Results from the comparative analysis verify the EPP-SMT design charts but suggest the requirement of additional test data in the low strain range regime for improving the extrapolation procedure that will further reduce the over conservatism in the creep-fatigue damage evaluation. The report also concludes that the EPP-SMT design procedure can account for effect of primary load on creep-fatigue life by using a fixed, bounding value of follow up in constructing the design charts. The conclusions to this report describe the future work required to complete this new design method so it can be codified through a nuclear Code Case.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Differences in urban plant community compositions across an urban-rural gradient in Knoxville, TN

Urban forests, or vegetation in areas under heavy human influence, provide many ecosystem services to urban residents such as localized cooling via evapotranspiration, shade, filtering of air pollution, and the associated health benefits of natural spaces. In order to quantify the magnitude of localized cooling by trees growing in varying levels of urbanization (based on % impervious surfaces, e.g., buildings, pavement), urban forest species composition, tree size, and tree density must be characterized. As a part of Oak Ridge National Laboratory’s (ORNL) urban forest temperature study, we conducted tree censuses in five Knoxville city parks where ORNL meteorological stations are deployed. Moreover, we measured every woody plant ≥ 5 cm diameter at breast height (DBH) within a 50 m radius of each site’s meteorological station for its DBH and species identification. When possible, individuals were identified down to species. Certain genera (Quercus spp., Carya spp., Pinus spp.) were identified down to genera in interest of time. Individual and total site basal area were calculated from measured DBH data. Results show notable differences in urban plant community compositions and total woody plant basal area across sites, with more urban sites closer to downtown (West View and SEEED) having lower tree basal area than the more suburban sites (West Hills, Cumberland Estates, and Victor Ashe). We identified 54 species across all sites, with West Hills and Victor Ashe having the highest species diversity. Our results show differences in forest compositions and sizes across Knoxville, which are currently informing ORNL’s evapotranspiration estimates for each site. Data Summary: Census data for West Hills (WH), Cumberland Estates (CE), Victor Ashe (VA), West View (WV), and Socially Equal Energy Efficient Development or SEEED (SD) urban forests in Knoxville, TN, USA, including tree size based on diameter at breast height (DBH; 1.3 m), species identification (Latin and common names), and basal area per stem (BA=π×[.5*DBH]^2). Field data are summarized in this file: “Community_Composition_Data.CSV”. Site-specific data detailing each site’s coordinates, number of stems measured at DBH, average tree DBH, α-diversity (number of species present), and total site basal area (sum of individual basal areas per site) are in this file: “Site_Comparisons.CSV”.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗