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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Estuarine nutrient pollution impact reduction assessment through euphotic zone avoidance/bypass considerations

The feasibility of reducing nutrient pollution impact by redirecting the effluent to depths below the euphotic zone was investigated for the deep estuarine Puget Sound region of the Salish Sea in the Pacific Northwest of America. The hypothesis tested was that the thickness of the outflow layer in deep estuaries may be greater than the euphotic zone depth, allowing a fraction of nutrients to be exported out passively through the layers immediately below. The euphotic zone depth in Puget Sound varies from 8 to 25 m while the depth of the outflow layer can reach up to ≈ 60 m. Outfall relocation strategies were tested on 99% of the anthropogenic nutrient loads currently delivered to Puget Sound. The impact was quantified using the previously established biophysical Salish Sea Model, using gross primary production and exposure to low dissolved oxygen (DO) levels as the metric (< 2 mg/L for hypoxia and < 5 mg/L for impairment). Eliminating nutrient pollution (above natural) from rivers and wastewater reduced hypoxia exposure by 8.1% and 11.2%, respectively. Relocating the outfalls to deeper waters resulted in improvements, but only in the sill-less sub-basins such as Whidbey, where hypoxia and DO impairment exposure decreased (7.9% and 6.8%, respectively). The presence of multiple sills and circulation cells in Puget Sound resulted in increased exposure and rendered nutrient bypass goals unfeasible as originally envisioned. However, an alternate nutrient export pathway was identified through bottom exchange flow out of Puget Sound via Whidbey Basin and Deception Pass. An unexpected reduction in the exchange outflow magnitude (≈ 4%) due additional (22%) freshwater discharged to the estuary bottom was also noted. The potential loss in circulation strength due to rerouting of natural surface freshwater through submerged deep-water outfalls is identified as a new unforeseen anthropogenic impact.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Re-Envisioning RCx: Achieving Max Potential HVAC Controls Retrofits through Modernized BAS Hardware and Software

Most existing buildings have sub-optimal heating, ventilation, and air conditioning (HVAC) controls, resulting in wasted energy and occupant discomfort. Retro-commissioning (RCx) addresses many of these issues, but it is a lengthy and highly customized process. Limited capabilities of existing building automation system hardware restricts the scope of most RCx projects. Incentive programs consider building automation system (BAS) hardware retrofits to be high-capital investments and do not allow them in typical RCx programs. This paper describes work that the authors are leading to facilitate technical and market innovation in the BAS industry to unlock large savings in existing commercial buildings through deep retrofits of BAS hardware and software. California and New York research projects are demonstrating BAS retrofits leveraging the American Society of Heating, Refrigeration, and Air Conditioning Engineers’ (ASHRAE) new Guideline 36 high performance sequences of operation to achieve greater than 20 percent whole building energy savings, while saving costs and reducing risk through streamlined processes and standardization across BAS manufacturer product lines and across implementation practices. This paper describes market barriers that impede achieving deep savings from BAS retrofits in custom incentive and traditional RCx programs and presents a new maximum potential BAS retrofit model that addresses these barriers. The new model leverages the authors’ efforts in market enablement through open standards, BAS industry partnerships, and tools for cost-effective scaling that includes tools for project screening, savings calculations, and measurement and verification (M&V). This approach is widely applicable and will be ready for at-scale implementation within two years.

Paliaga, Gwelen↗
DOE OSTI2020

Geothermal Deep Direct Use for Turbine Inlet Cooling in East Texas

The National Renewable Energy Laboratory (NREL), the Southern Methodist University Geothermal Laboratory (SMU), Eastman Chemical (Longview, TX), and TAS (Houston, TX) evaluated the feasibility of using geothermal heat to improve the performance of a natural-gas power plant in East Texas. The area of interest is the Eastman Chemical plant in Longview, Texas, which is on the northwestern margin of a geologic region known as the Sabine Uplift. The feasibility study focused on determining the potential for accessing a subsurface hot-water geothermal resource within a 10-km radius of the site to provide thermal energy for absorption chillers. Wells within a 20-km radius are included for broader geological comparison to determine the heat flow, temperature-at-depth, field porosity and permeability. The lithologies of most interest are the Lower Cretaceous Trinity Group and Upper Jurassic Cotton Valley Group. The deeper Cotton Valley formations are hotter (averaging 117 to 130°C), yet permeability and porosity are low. The shallower Trinity Group contains more variability in permeability and porosity and lower temperatures averaging about 98 to 117°C. The shallower formations are considered despite the lower temperature because of increased ability to produce larger volumes of water and extract enough heat before reinjection. The complete SMU analysis is available in the National Geothermal Data System (NGDS). Tapping such deep geothermal sources for direct heating (as opposed to power generation) is known as geothermal deep direct use (DDU). Geothermal DDU has potential across a wide swath of the United States but is underutilized due to challenging project economics associated with developing a deep geothermal resource for what are typically small-scale, variable-demand projects. This project examines the feasibility of geothermal energy integration in a natural-gas combined cycle power station in East Texas. The DDU resource is tapped to drive absorption chillers (24/7) for production of chilled water at 5-10°C (41-50°F). This chilled water is stored until needed, which allows for continuous operation with a relatively small-capacity geothermal/absorption chiller system. When conditions are favorable, the chilled water is dispatched to cool the air entering the compressor stage of a gas combustion turbine. This process, known as turbine inlet cooling (TIC), boosts power production during periods of high temperature and high-power demand. Such systems can enhance grid reliability and reduce the cost for peak-demand power. A simulation model of the power plant was developed in IPSEpro software and validated against operational data from the plant. This model allowed the team to estimate the additional power that could be produced by applying TIC under different operating and ambient conditions. Absorption chiller performance was estimated from vendor sources to determine the production rate of chilled water from the geothermal resource. Geothermal drilling and development costs were estimated using NREL's GEOPHIRES 2.0. The expected lower drilling costs in this region led to an estimated cost of geothermal heat of about $4/MMBtu (1.4 cents/kWh t ). The estimated cost for the absorption chillers and TIC hardware were obtained from literature sources and project partners. Hourly data were obtained for weather, natural gas and electricity prices, and plant operating state for 2017, which served as a representative year. NREL estimated the capital cost, operating cost, and additional electricity production and revenue for different combinations of geothermal capacity, chiller capacity, and water storage-tank size. The analysis drove toward smaller geothermal and chiller systems to reduce equipment cost. A relatively low-cost water storage tank accumulated the near-continuous chilled water output for later use when TIC was most valued.

15 GEOTHERMAL ENERGY↗
NASA NTRS2015

NASA Near Earth Network (NEN), Deep Space Network (DSN) and Space Network (SN) Support of CubeSat Communications

There has been a historical trend to increase capability and drive down the Size, Weight and Power (SWAP) of satellites and that trend continues today. Small satellites, including systems conforming to the CubeSat specification, because of their low launch and development costs, are enabling new concepts and capabilities for science investigations across multiple fields of interest to NASA. NASA scientists and engineers across many of NASAs Mission Directorates and Centers are developing exciting CubeSat concepts and welcome potential partnerships for CubeSat endeavors. From a communications and tracking point of view, small satellites including CubeSats are a challenge to coordinate because of existing small spacecraft constraints, such as limited SWAP and attitude control, low power, and the potential for high numbers of operational spacecraft. The NASA Space Communications and Navigation (SCaN) Programs Near Earth Network (NEN), Deep Space Network (DSN) and the Space Network (SN) are customer driven organizations that provide comprehensive communications services for space assets including data transport between a missions orbiting satellite and its Mission Operations Center (MOC). The NASA NEN consists of multiple ground antennas. The SN consists of a constellation of geosynchronous (Earth orbiting) relay satellites, named the Tracking and Data Relay Satellite System (TDRSS). The DSN currently makes available 13 antennas at its three tracking stations located around the world for interplanetary communication. The presentation will analyze how well these space communication networks are positioned to support the emerging small satellite and CubeSat market. Recognizing the potential support, the presentation will review the basic capabilities of the NEN, DSN and SN in the context of small satellites and will present information about NEN, DSN and SN-compatible flight radios and antenna development activities at the Goddard Space Flight Center (GSFC) and across industry. The presentation will review concepts on how the SN multiple access capability could help locate CubeSats and provide a low-latency early warning system. The presentation will also present how the DSN is evolving to maximize use of its assets for interplanetary CubeSats. The critical spectrum-related topics of available and appropriate frequency bands, licensing, and coordination will be reviewed. Other key considerations, such as standardization of radio frequency interfaces and flight and ground communications hardware systems, will be addressed as such standardization may reduce the amount of time and cost required to obtain frequency authorization and perform compatibility and end-to-end testing. Examples of standardization that exist today are the NASA NEN, DSN and SN systems which have published users guides and defined frequency bands for high data rate communication, as well as conformance to CCSDS standards. The workshop session will also seek input from the workshop participants to better understand the needs of small satellite systems and to identify key development activities and operational approaches necessary to enhance communication and navigation support using NASA's NEN, DSN and SN.

Telecommunication↗
DOE OSTI2013

An alma survey of submillimeter galaxies in the extended Chandra deep field-south: The agn fraction and X-ray properties of submillimeter galaxies

The large gas and dust reservoirs of submillimeter galaxies (SMGs) could potentially provide ample fuel to trigger an active galactic nucleus (AGN), but previous studies of the AGN fraction in SMGs have been controversial largely due to the inhomogeneity and limited angular resolution of the available submillimeter surveys. Here we set improved constraints on the AGN fraction and X-ray properties of the SMGs with Atacama Large Millimeter/submillimeter Array (ALMA) and Chandra observations in the Extended Chandra Deep Field-South (E-CDF-S). This study is the first among similar works to have unambiguously identified the X-ray counterparts of SMGs; this is accomplished using the fully submillimeter-identified, statistically reliable SMG catalog with 99 SMGs from the ALMA LABOCA E-CDF-S Submillimeter Survey. We found 10 X-ray sources associated with SMGs (median redshift z = 2.3), of which eight were identified as AGNs using several techniques that enable cross-checking. The other two X-ray detected SMGs have levels of X-ray emission that can be plausibly explained by their star formation activity. Six of the eight SMG-AGNs are moderately/highly absorbed, with N {sub H} > 10{sup 23} cm{sup –2}. An analysis of the AGN fraction, taking into account the spatial variation of X-ray sensitivity, yields an AGN fraction of 17{sub −6}{sup +16}% for AGNs with rest-frame 0.5-8 keV absorption-corrected luminosity ≥7.8 × 10{sup 42} erg s{sup –1}; we provide estimated AGN fractions as a function of X-ray flux and luminosity. ALMA's high angular resolution also enables direct X-ray stacking at the precise positions of SMGs for the first time, and we found four potential SMG-AGNs in our stacking sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

3DD - Three Dimensional Disposal of Spent Nuclear Fuel - 12449

Three dimensional disposal is being considered as a way in which to store long-term spent nuclear fuel in underground disposal facilities in the Czech Republic. This method involves a combination of the two most common internationally recognised disposal methods in order to practically apply the advantages of both whilst, at the same time, eliminating their weaknesses; the method also allows easy removal in case of potential re-use. The proposed method for the disposal of spent nuclear fuel will reduce the areal requirements of future deep geological repositories by more than 30%. It will also simplify the container handling process by using gravitational forces in order to meet requirements concerning the controllability of processes and ensuring operational and nuclear safety. With regard to the issue of the efficient potential removal of waste containers, this project offers an ingenious solution which does not disrupt the overall stability of the original disposal complex. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2008

Optical Communications from Planetary Distances

Future planetary campaigns, including human missions, will require data rates difficult to realize by microwave links. Optical channels not only provide an abundance of bandwidth, they also allow for significant size, weight, and power reduction. Moreover, optical-based tracking may enhance spacecraft navigation with respect to microwave-based tracking. With all its advantages, optical communications from deep space is not without its challenges. Due to the extreme distance between the two ends of the link, specialized technologies are needed to enable communications in the deep space environment. Although some of the relevant technologies have been developed in the last decade, they remain to be validated in an appropriate domain. The required assets include efficient pulsed laser sources, modulators, transmitters, receivers, detectors, channel encoders, precise beam pointing technologies for the flight transceiver and large apertures for the ground receiver. Clearly, space qualification is required for the systems that are installed on a deep space probe. Another challenge is atmospheric effects on the optical beam. Typical candidate locations on the ground have a cloud-free line of sight only on the order of 60-70% of the time. Furthermore, atmospheric losses and background light can be problematic even during cloud-free periods. Lastly, operational methodologies are needed for efficient and cost effective management of optical links. For more than a decade, the National Aeronautics and Space Administration (NASA) has invested in relevant technologies and procedures to enable deep space optical communications capable of providing robust links with rates in the order of 1 Gb/s from Mars distance. A recent publication indicates that potential exists for 30-dB improvement in performance through technology development with respect to the state-of-the-art in the early years of this decade. The goal is to fulfill the deep space community needs from about 2020 to the foreseeable future. It is envisioned that, at least initially, optical links will be complemented by microwave assets for added robustness, especially for human missions. However, it is expected that as optical techniques mature, laser communications may be operated without conventional radio frequency links. The purpose of this paper is to briefly review the state-of-the-art in deep space laser communications and its challenges and discuss NASA-supported technology development efforts and plans for deep space optical communications at JPL.

Laser Communications↗
NASA NTRS2018

Semi-Autonomous Rodent Habitat for Deep Space Exploration

NASA has flown animals to space as part of trailblazing missions and to understand the biological responses to spaceflight. Mice traveled in the Lunar Module with the Apollo 17 astronauts and now mice are frequent research subjects in LEO on the ISS. The ISS rodent missions have focused on unravelling biological mechanisms, better understanding risks to astronaut health, and testing candidate countermeasures. A critical barrier for longer-duration animal missions is the need for humans-in-the-loop to perform animal husbandry and perform routine tasks during a mission. Using autonomous or telerobotic systems to alleviate some of these tasks would enable longer-duration missions to be performed at the Deep Space Gateway. Rodent missions performed using the Gateway as a platform could address a number of critical risks identified by the Human Research Program (HRP), as well as Space Biology Program questions identified by NRC Decadal Survey on Biological and Physical Sciences in Space, (2011). HRP risk areas of potentially greatest relevance that the Gateway rodent missions can address include those related to visual impairment (VIIP) and radiation risks to central nervous system, cardiovascular disease, as well as countermeasure testing. Space Biology focus areas addressed by the Gateway rodent missions include mechanisms and combinatorial effects of microgravity and radiation. The objectives of the work proposed here are to 1) develop capability for semi-autonomous rodent research in cis-lunar orbit, 2) conduct key experiments for testing countermeasures against low gravity and space radiation. The hardware and operations system developed will enable experiments at least one month in duration, which potentially could be extended to one year in duration. To gain novel insights into the health risks to crew of deep space travel (i.e., exposure to space radiation), results obtained from Gateway flight rodents can be compared to ground control groups and separate groups of mice exposed to simulated Galactic Cosmic Radiation (at the NASA Space Radiation Lab). Results can then be compared to identical experiments conducted on the ISS. Together results from Gateway, ground-based, and ISS rodent experiments will provide novel insight into the effects of space radiation.

deep space gateway↗
DOE OSTI2026

Federated learning for 2D synchrotron x-ray diffractometry: a cross-institutional approach for phase quantification of Ti–6Al–4V alloy

High-energy Two dimensional (2D) synchrotron x-ray diffractometry provides important insights into the atomistic structure and phase evolution of materials, yet traditional analysis methods remain complex, knowledge-intensive, and computationally demanding. Deep-learning models offer a powerful alternative for automating their analysis. Institutions that hold these datasets may be unwilling to share their data due to privacy and security policies, as well as the challenges associated with large-scale data transfer. As a result, models trained on local datasets often perform well only on their own data but exhibit bias and poor generalization across different instruments or facilities. To overcome these limitations, we explore federated learning (FL) for 2D synchrotron diffractograms, enabling collaborative model training without exchanging raw data. In this study, 2D synchrotron diffractograms of Ti–6Al–4V alloy collected from two independent facilities are used to train convolutional neural networks for predicting the β-phase volume fraction. Experimental results show that federated global models significantly outperform locally trained models in terms of generalization and achieve accuracy comparable to centralized trained models. These findings demonstrate the potential of FL to enable secure, cross-institutional collaboration and enhance the scalability of deep-learning-based materials characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Warming Response of Deep Soil Carbon (LDRD Final Report)

The overarching objective of this LDRD project was to determine the vulnerability of deep soil organic carbon (SOC) to warming in the Sierra Nevada region. Deep soils (>30 cm) store more than 70% of global SOC, and increased SOC decomposition and CO 2 emissions caused by warming are potentially large climate change feedbacks. According to the Intergovernmental Panel on Climate Change, temperatures are expected to increase by 4°C by the year 2100, warming the land and underlying soil, and making understanding of how warming will influence deep SOC storage and persistence critical to projecting the land carbon sink. However, uncertainty remains in our process-level understanding and ability to quantify how projected warming will impact the stability of carbon in deep soils. We investigated warming effects on deep (up to 16 m) SOC stability across climate, vegetation, and soil mineralogy gradients in California. We sampled soils from the surface to bedrock (down to 16 meters) at four sites representing vastly different ecosystems across the Northern and Southern Sierra Nevada mountains. This study quantified the response of SOC concentration, distribution, and vulnerability to warming using a soil incubation experiment to warm the whole soil profile and radiocarbon and stable isotopes to assess which pools are vulnerable to loss under warming. Our results refine our understanding of the terrestrial carbon cycle by revealing the vulnerability of deep SOC to future changes in climate and how minerology may influence that vulnerability.

58 GEOSCIENCES↗
DOE OSTI2019

A deep learning approach to anomaly detection in geological carbon sequestration sites using pressure measurements

Carbon capture and storage (CCS) has been extensively investigated as a potential engineering measure to reduce anthropogenic carbon emission to the atmosphere. Real-time monitoring of the safety and integrity of carbon storage reservoirs is a critical aspect of any commercial-scale CCS deployment. Pressure-based sensing is cost effective, suitable for real-time monitoring, and scalable to large monitoring networks. However, questions remain on how to best harness intelligent information from the high-frequency pressure monitoring sensors to support real-time decisions. Here this work presents a deep-learning-based framework for analyzing and detecting anomalies in pressure data streams by using a convolutional long short-term memory (ConvLSTM) neural network model, which allows for the fusion of both static and dynamic reservoir data. In ConvLSTM, the convolutional neural network (CNN) is used for spatial pattern mining and the LSTM is used for temporal pattern recognition. The performance of the ConvLSTM model for real-time anomaly detection is demonstrated using a set of pressure monitoring data collected from Cranfield, Mississippi, an active enhanced-oil-recovery field. The anomaly detection model is trained using bottom-hole pressure data acquired from the base experiment (without leak event) and then tested on pressure data collected during a series of controlled CO 2 release experiments (with artificially created leak events). Results show that the ConvLSTM neural network model successfully detected anomalies in the pressure time series obtained from the controlled release experiments. Inclusion of static information into the model further improves the robustness of ConvLSTM.

13 HYDRO ENERGY↗
NASA NTRS2017

Screening of High Temperature Organic Materials for Future Stirling Convertors

Along with major advancement of Stirling-based convertors, high temperature organics are needed to develop future higher temperature convertors for much improved efficiencies as well as to improve the margin of reliability for the current SOA (State-of-the-Art) convertors. The higher temperature capabilities would improve robustness of the convertors and also allow them to be used in additional missions, particularly ones that require a Venus flyby for a gravity assist. Various organic materials have been employed as essential components in the convertor for their unique properties and functions such as bonding, potting, sealing, thread locking, insulation, and lubrication. The Stirling convertor radioisotope generators have been developed for potential future space applications including Lunar/Mars surface power or a variety of spacecraft and vehicles, especially with a long mission cycle, sometimes up to 17 years, such as deep space exploration. Thus, performance, durability, and reliability of the organics should be critically evaluated in terms of every possible material structure-process-service environment relations based on the potential mission specifications. The initial efforts in screening the high temperature candidates focused on the most susceptible organics, such as adhesive, potting compound, O-ring, shrink tubing, and thread locker materials in conjunction with commercially available materials. More systematic and practical test methodologies that were developed and optimized based on the extensive organic evaluations and validations performed for various Stirling convertor types were employed to determine thermal stability, outgassing, and material compatibility of the selected organic candidates against their functional requirements. Processing and fabrication conditions and procedures were also optimized. This report presents results of the three-step candidate evaluation processes, their application limitations, and the final selection recommendations.

Screening↗
NASA NTRS2012

Static Indentation Load Capacity of the Superelastic 60NiTi for Rolling Element Bearings

The nickel-rich, binary nickel-titanium alloys, such as 60NiTi (60Ni-40Ti by wt%), are emerging as viable materials for use in mechanical components like rolling element bearings and gears. 60NiTi is a superelastic material that simultaneously exhibits high hardness and a relatively low elastic modulus (approx.100 GPa). These properties result in the potential to endure extremely high indentation loads such as those encountered in bearings, gears and other mechanical components. In such applications, quantifying the load that results in permanent deformation that can affect component performance and life is important. In this paper, the static load capacity is measured by conducting indentation experiments in which 12.7 mm diameter balls made from the ceramic Si3N4 are pressed into highly polished, hardened 60NiTi flat plates. Hertz stress calculations are used to estimate contact stress. The results show that the 60NiTi surface can withstand an approximately 3400 kN load before significant denting (>0.6 microns deep) occurs. This load capacity is approximately twice that of high performance bearing steels suggesting that the potential exists to make highly resilient bearings and components from such materials.

DellaCorte, Christopher↗
DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS

Comprehensive, quantitative information on abundances of proteins and their post-translational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labelling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification and quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples, and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2014

Phase 1 Methyl Iodide Deep-Bed Adsorption Tests

Nuclear fission results in the production of fission products (FPs) and activation products including iodine-129, which could evolve into used fuel reprocessing facility off-gas systems, and could require off-gas control to limit air emissions to levels within acceptable emission limits. Research, demonstrations, and some reprocessing plant experience have indicated that diatomic iodine can be captured with efficiencies high enough to meet regulatory requirements. Research on the capture of organic iodides has also been performed, but to a lesser extent [Jubin 2012b]. Several questions remain open regarding the capture of iodine bound in organic compounds. Deep-bed methyl iodide adsorption testing has progressed according to a multi-laboratory methyl iodide adsorption test plan. This report summarizes the first phase of methyl iodide adsorption work performed according to this test plan using the deep-bed iodine adsorption test system at the Idaho National Laboratory (INL), performed during Fiscal Year (FY) 2013 and early FY-2014. Testing has been performed to address questions posed in the test plan, and followed the testing outline in the test plan. Tests established detection limits, developed procedures for sample analysis with minimal analytical interferences, and confirmed earlier results that show that the methyl iodide reacts when in contact with the AgZ sorbent, and not significantly in the gas flow upstream of the sorbent. The reaction(s) enable separation of the iodine from the organic moiety, so that the iodine can chemisorb onto the sorbent. The organic moiety can form other compounds, some of which are organic compounds that are detected and can be tentatively identified using GC-FID and GCMS. Test results also show that other gas constituents (NOx and/or H2O) can affect the methyl iodide reactions. With NOx and H2O present in the gas stream, the majority of uncaptured iodine exiting iodine-laden sorbent beds is in the form of I2 or HI, species that are soluble in NaOH scrubbing solution for iodine analysis. But when NOx and H2O are not present, then the majority of the uncaptured iodine exiting iodine-laden sorbent is in the form of methyl iodide. Methyl iodide adsorption efficiencies have been high enough so that initial DFs exceed 1,000 to 10,000. The methyl iodide mass transfer zone depths are estimated at 4-8 inches, possibly deeper than mass transfer zone depths estimated for I2 adsorption on AgZ. Additional deep-bed testing and analyses are recommended to (a) expand the data base for methyl iodide adsorption under various conditions specified in the methyl iodide test plan, and (b) provide more data for evaluating organic iodide reactions and reaction byproducts for different potential adsorption conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A Study of Intermittent Turbulence in Stable Arctic Boundary Layers

Abstract Polar boundary layers are difficult to model due to the existence of intermittent turbulence within stable layers. Here we present a case study evaluation of coherent structures in a stable boundary layer observed during a series of flights with an uncrewed aircraft system (DataHawk2) on 19 October 2016 at Oliktok Point, Alaska as part of the ERASMUS (Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems) field campaign. During a sequence of five flights over a nine-hour period, 57 profiles of atmospheric properties (0–400 m a.g.l) were collected. Turbulence was identified using derived Richardson Number, temperature structure function parameter, and turbulence kinetic energy dissipation. Throughout all flights on this strongly stable day, intermittent turbulence was observed. These turbulent layers showed well-mixed potential temperature profiles embedded within otherwise stable potential temperature profiles; often resulting in a characteristic staircase pattern. Turbulent layers ranged from 1 to 30 m deep, with most individual layers being 1–2 m deep. Vertical propagation velocities of layers in the lower atmosphere were on the order of a few cm s −1 , typical of non-convective environments. In different regions of the profile, turbulence was driven by a different balance of buoyancy and shear forces, with turbulence in the near surface environment driven by strong shear forces overcoming strong resistance to buoyancy, while turbulence in elevated layers characterized by weaker shear forces overcoming weaker resistance to buoyancy. We discuss the potential of such datasets for improving subgrid parameterizations of small-scale turbulence embedded within stable boundary layers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Physics-Informed Deep Learning-Based Proof-of-Concept Study of a Novel Elastohydrodynamic Seal for Supercritical CO 2 Turbomachinery

Supercritical carbon dioxide (sCO 2 ) power cycles show promising potential of higher plant efficiencies and power densities for a wide range of power generation applications such as fossil fuel power plants, nuclear power production, solar power, and geothermal power generation. sCO 2 leakage through the turbomachinery has been one of the main concerns in such applications. To offer a potential solution, we propose an elastohydrodynamic (EHD) seal that can work at elevated pressures and temperatures with low leakage and minimal wear. The EHD seal has a very simple, sleeve-like structure, wrapping on the rotor with minimal initial clearance at micron levels. Here, in this work, a proof-of-concept study for the proposed EHD seal was presented by using the simplified Reynolds equation and Lame’s formula for the fluid flow in the clearance and for seal deformation, respectively. The set of nonlinear equations was solved by using both the conventional Prediction–Correction (PC) method and modern Physics-Informed Neural Network (PINN). It was shown that the physics-informed deep learning method provided good computational efficiency in resolving the steep pressure gradient in the clearance with good accuracy. The results showed that the leakage rates increased quadratically with working pressures and reached a steady-state at high-pressure values of 15~20 MPa, where Q = 300 g/s at 20 MPa for an initial seal clearance of 255 μm. This indicates that the EHD seal could be tailored to become a potential solution to minimize the sCO 2 discharge in power plants.

30 DIRECT ENERGY CONVERSION↗