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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Telomerase-Activated Magnetic Resonance Imaging Probe for Consecutively Monitoring Tumor Growth Kinetics and In Situ Screening Inhibitors

Telomerase has long been considered as a biomarker for cancer diagnosis and a therapeutic target for drug discovery. Detecting telomerase activity in vivo could provide more direct information of tumor progression and response to drug treatment, which, however, is hampered by the lack of an effective probe that can generate an output signal without a tissue penetration depth limit. Here in this study, using the principle of distance-dependent magnetic resonance tuning, we constructed a telomerase-activated magnetic resonance imaging probe (TAMP) by connecting superparamagnetic ferroferric oxide nanoparticles (SPFONs) and paramagnetic Gd-DOTA (Gd(III) 1,4,7,10- tetraazacyclododecane-1,4,7,10-tetraazacyclododecane-1,4,7,10-tet-raacetic acid) complexes via telomerase-responsive DNA motifs. Upon telomerase-catalyzed extension of the primer in TAMP, Gd-DOTA-conjugated oligonucleotides can be liberated from the surface of SPFONs through a DNA strand displacement reaction, restoring the T 1 signal of the Gd-DOTA for a direct readout of the telomerase activity. Here we show that, by tracking telomerase activity, this probe provides consistent monitoring of tumor growth kinetics during progression and in response to drug treatment and enables in situ screening of telomerase inhibitors in whole-animal models. This study provides an alternative toolkit for cancer diagnosis, treatment response assessment, and anticancer drug screening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics

Experimental soil heating experiments have found a consistent increase in soil-surface CO 2 emissions ( F s ), but inconsistent soil organic carbon (SOC) responses. Interpretation of heating effects is complicated by spatial heterogeneity and soil moisture, nitrogen availability, and microbial and plant responses. Here we applied a mechanistic ecosystem model to interpret heating impacts on a California forest subjected to 1 m deep, 4°C heating. The model accurately simulated control-plot CO 2 fluxes, SOC stocks, fine root biomass, soil moisture, and soil temperature, and the observed increases in F s and decreases in fine root biomass. We show that a complex suite of interactions can lead to a consistent increase in F s (~17%) over the 5-year study period, with very small changes in SOC stocks (<1%). Modeled increases in leaf water stress from soil drying reduced GPP and NPP. The resulting reduction in leaf and fine root allocation increased fine root litter inputs to the soil and reduced root exudation. Soil heating led to about a 50% larger increase in root autotrophic respiration than in heterotrophic respiration, with the heating effect on both these fluxes decreasing over the simulation period. Increased heterotrophic respiration led to increased soil N availability and plant N uptake. These heating responses are mechanistically linked, of magnitudes that can affect ecosystem dynamics, and long-term observations of them are rarely made. Therefore, we conclude that a coupled observational and mechanistic modeling framework is needed to interpret manipulation experiments, and to improve projections of climate change impacts on terrestrial ecosystem carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Advances in catalytic production processes of biomass-derived vinyl monomers

Plastic industries currently source the majority of monomers from crude oil substances. Although we have witnessed a significant interest of companies in the utilization of sustainable feedstock materials for bio-based compound synthesis in the past decade, the transition to photosynthetic or chemosynthetic plant-based production in a circular carbon economy is largely slow due to complex biomass processing, costs and related reaction factors. The upgrade of the separated platform chemicals with a deeper supporting understanding of processes, models and a root–cause analysis about the underlying distribution challenges of engineered transformation mechanisms, catalyzed conversion pathways and selectivity would be beneficial to advance applied scientific development, bio-refining and manufacturing output amount. This review provides a summary, assessment and perspective for three important polymer-forming vinyl molecules, i.e. acrylic acid, methacrylic acid and styrene. These provide a backbone to produce acrylates, polystyrene, resins, rubbers, protective surface coatings, adhesives, textiles and other obtained copolymers. A succinct analytical overview on the thermo-catalytic intermediate routes for property-wise drop-in alternatives is presented. Sugars, acrolein, allyl alcohol, ethylbenzene, glycerol, 3-hydroxypropionic acid, isobutene, itaconic acid and lactic acid are considered as the main starting reactants. Catalysts span mixed metal oxides, silicates, native or impregnated zeolite frameworks (HBEA, HZSM, and MFI) and hetero-poly acids as well as homogeneous base hydroxides or platinum group metals, supported on carbon, alumina and sulfates. Finally, the article concludes with a brief state sum-up of the results, topics and opportunities for systematic future research or scaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Assessing Critical Conditions for Scour Near Obstructions using Bed Shear, Particle Onset of Motion Balances, and CFD-DEM Modeling of Granular Beds

Computational Fluid Dynamics combined with a Discrete Element Method is one of the computational methods that can be used to model multiphase flows. In this method various phases, gas and liquid or solid, are present in the same computational domain. The local averaged Navier–Stokes equations determine the flow of the continuous phase fluid and are solved using the traditional CFD finite volume approach. DEM is based on a Lagrangian formulation, which solves the equations of motion, expressed in ordinary differential equations, for representative particles as they move in space and time. The interactions between the continuous fluid phase and discrete solid phase are modeled with the use of Newton’s laws of motion via drag force. The particles interact with each other and with the boundaries of the fluid continuum, and the resulting contact forces are included in the equations of motion. The properties of solid particles and boundaries are treated as elastic bodies, with specified density, elastic modulus, and Poisson’s ratio. Particle shapes may vary from single spherical particles to more complex-shaped composite particles. The particles may be introduced into the domain by random or structured injection at a point, surface, or volume, depending on the application. More details on the formulation can be found in the Simcenter STAR-CCM+ User’s Manual and OpenFOAM website.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

DUNE experiment physics

The Deep Underground Neutrino Experiment (DUNE) will feature a 40-kton liquid argon TPC detector situated a mile below the surface at the Sanford Underground Research Facility. A new broadband high-intensity neutrino source and Near Detector complex will be located at Fermilab, 1300 kilometers away. This arrangement will provide unprecedented sensitivity in the search for neutrino CP violation, determination of the neutrino mass ordering, and precision measurements of neutrino mixing parameters. The underground Far Detector also allows for low background, low threshold observations of supernova neutrinos, with a unique sensitivity to the electron neutrino flux. Further, DUNE will conduct a wide range of searches for physics beyond the Standard Model, including baryon number violation, rare scattering processes, and non-standard flavor transitions. In this poster, we review DUNE's extensive physics program and show updated sensitivities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Postmortem and Antemortem Forensic Assessment of Pediatric Fracture Healing from Radiographs and Machine Learning Classification

A timeline of pediatric bone healing using fracture healing characteristics that can be assessed solely using radiographs would be practical for forensic casework, where the fracture event may precede death by days, months, or years. However, the dating of fractures from radiographs is difficult, imprecise, and lacks consensus, as only a few aspects of the healing process are visible on radiographs. Multiple studies in both the clinical and forensic literature have attempted to develop a usable scale to assess pediatric bone healing on radiographs using various healing characteristics. In contrast to the orthopedic definition, a fracture in forensic casework is only considered to be healed when the area around the fracture has been remodeled to the point that the fracture is difficult to detect on a radiograph or on the surface of the bone itself, a process that can take several years. We subjectively assessed visible characteristics of healing in radiograms of fractures occurring in 942 living children and adolescents. By dividing these assessments into learning and test (validation) sets, the accuracy of a newly proposed fracture healing scale was compared to a previous study. Two machine learning models were used to test predictions of the new scale. All three models produced similar estimates with substantial imprecision. Results corroborate the Malone model with an independent dataset and support the efficacy of using less complex models to estimate fracture age in children.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Full‐dimensional coupled‐channel statistical approach to atom‐triatom systems and applications to H/D + O 3 reaction

Abstract The statistical quantum model (SQM), which assumes that the reactivity is controlled by entrance/exit channel quantum capture probabilities, is well suited for chemical reactions with a long‐lived intermediate complex. In this work, a time‐independent coupled‐channel implementation of the SQM approach is developed for atom‐triatom systems in full dimensionality. As SQM treats the capture dynamics quantum mechanically, it is capable of handling quantum effects such as tunneling. A detailed study of the H/D + O 3 capture dynamics was performed by applying the newly developed SQM method on an accurate global potential energy surface. Agreement with previous ring polymer molecular dynamics (RPMD) results on the same potential energy surface is excellent except for very low temperatures. The SQM results are also in reasonably good agreement with available experimental rate coefficients. The strong H/D kinetic isotope effect underscores the dominant role of quantum tunneling under an entrance channel barrier at low temperatures.

Yang, Dongzheng↗
DOE OSTI2024

Insight into the autoproteolysis mechanism of the RsgI9 anti‐σ factor from Clostridium thermocellum

Abstract Clostridium thermocellum is a potential microbial platform to convert abundant plant biomass to biofuels and other renewable chemicals. It efficiently degrades lignocellulosic biomass using a surface displayed cellulosome, a megadalton sized multienzyme containing complex. The enzymatic composition and architecture of the cellulosome is controlled by several transmembrane biomass‐sensing RsgI‐type anti‐σ factors. Recent studies suggest that these factors transduce signals from the cell surface via a conserved RsgI extracellular (CRE) domain (also called a periplasmic domain) that undergoes autoproteolysis through an incompletely understood mechanism. Here we report the structure of the autoproteolyzed CRE domain from the C. thermocellum RsgI9 anti‐σ factor, revealing that the cleaved fragments forming this domain associate to form a stable α/β/α sandwich fold. Based on AlphaFold2 modeling, molecular dynamics simulations, and tandem mass spectrometry, we propose that a conserved Asn‐Pro bond in RsgI9 autoproteolyzes via a succinimide intermediate whose formation is promoted by a conserved hydrogen bond network holding the scissile peptide bond in a strained conformation. As other RsgI anti‐σ factors share sequence homology to RsgI9, they likely autoproteolyze through a similar mechanism.

Takayesu, Allen↗
DOE OSTI2026

Measuring pH Changes Inside a Bipolar Membrane Junction

Here, the local pH environment within bipolar membrane (BPM) junctions is complex and not well understood, yet it is important to control for advancing the performance of BPM-based electrochemical systems. We report a voltammetric strategy using an ultrathin Ni mesh pH probe to spatially resolve pH changes in the BPM junction during model BPM electrolyzer operation. Under reverse bias, we observe depletion of OH – at the anion-exchange layer (AEL) interface, with a degree diminishing with increasing distance from the AEL. These gradients correlate with current-dependent water dissociation (WD) and are modulated by the electric field and the surface charge state of the catalyst. By correlating spatial pH profiles with the surface-charging behavior of WD catalysts, we explore a mechanism of catalyst-mediated H + and OH – transfer facilitated by hydrogen-bonding networks. These findings highlight the role of local chemistry and electrostatics in BPM performance and offer new methods to probe and engineer catalytic junctions in electrochemical energy devices.

Hou, Shujin [University of California, Berkeley, C↗
DOE OSTI2025

Stationary Oxygen Vacancy Construction toward a Superior-Performance Ultrahigh Nickel Single-Crystal Cathode

Oxygen vacancies exert a complex and profound influence on the layered cathodes, especially those with ultrahigh nickel content. They can facilitate lithium-ion transport and enhance electronic conductivity, while aggressive oxygen vacancy formation causes structural degradation and electrolyte decomposition. Herein, taking ultrahigh nickel single-crystal LiNi 0.92 Co 0.06 Mn 0.02 O 2 (SC-Ni92) as a model material, we propose a pinning strategy to harness the benefits of oxygen vacancies while mitigating their detrimental effects. Through a carefully controlled thermal process, both oxygen vacancies and pinning atoms are successfully introduced into the surface region. The resulting anchored oxygen vacancies, capitalizing on their inherent advantages, improve conductivity and lithium-ion diffusion. Simultaneously, the neighboring pinning atoms effectively increase the migration barrier and suppress the adverse effects of these vacancies, including electrolyte decomposition and structural degradation during long-term electrochemical cycling. Consequently, oxygen vacancy-anchored single-crystal LiNi 0.92 Co 0.06 Mn 0.02 O 2 (SC-Ni92-OV) demonstrates significantly improved high-voltage electrochemical performance, with 86.16% capacity retention after 200 cycles at 4.6 V and 1 C in a half-cell and 90.71% after 300 cycles at 4.5 V and 1 C in a full cell. Furthermore, this study not only provides valuable insights into the chemistry of oxygen vacancy but also introduces a viable strategy for leveraging oxygen vacancies to achieve stable high-voltage performance in ultrahigh nickel single-crystal cathodes.

defects in solids↗
DOE OSTI2022

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are used extensively in many industrial applications. These batteries consist of electrodes that are put together with heterogeneous material compositions. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Such reconstructions of material constituents help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. These images often suffer from low image contrast between multiple material constituents, hence making it difficult for humans to distinguish and characterize these constituents through visual inspection. A minor error in detecting distributions of the material constituents can lead to magnified errors in the calculated parameters of material properties (e.g., porosity). We present MatPhase, a novel hierarchical curriculum learning technique to address the complex task of estimating material constituent distribution in battery electrodes. MatPhase comprises three modules: (i) an uncertainty-aware global model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a local model to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator model to appropriately fuse the local and global effects towards obtaining the final distribution. On average, MatPhase improves prediction up to 8.5% relative to other sophisticated modeling pipelines and state-of-the-arts (SOTA) object detection models employed in the performance comparison.

Tabassum, Anika↗
DOE OSTI2021

Control of the Plasma-Material Interface for Long Pulse Optimization in the Experimental Advanced Superconducting Tokamak (EAST) (Final Report)

This project involved a collaborative effort, led by Dr. Rajesh Maingi of Princeton Plasma Physics Laboratory, to understand and control the plasma-material interface to improve long pulse discharge control and performance in the EAST devices. The focus is on long pulse recycling control and optimization, which can be challenging because of their broad range of materials used for plasma-facing components (PFC) and wall conditioning techniques. The purpose of the EAST device is to demonstrate long-pulse, stable, high performance plasma operation, providing a test-bed for key physics and technology issues for next step devices. As part of these tests, EAST has deployed carbon for the lower divertor PFC, tungsten for the upper divertor, and molybdenum for the main wall. In addition wall coatings are deployed for long pulse recycling control: lithium (Li) via several delivery tools, boronization, and recently also siliconization; for example, in 2013, a layer of SiC was deposited on all of the graphite tiles. Oxygen is also present at trace levels, making for a complex mix of materials and plasma-materials interactions (PMI). This mix of materials and the limited durability of wall coatings, coupled to partially optimized cryo-pumping, lead to evolution of the recycling off the PFCs, which restricts the duration of stationary, high performance, long pulse discharges. Comparing the wall conditioning techniques, Li enables the highest energy confinement and lowest recycling for the longest duration, while also suppressing ELMs in certain discharges. More specifically, research activities at the University of Tennessee focused on heat flux profile measurements in EAST, modeling the surface response, including the bonding energetics and chemical interactions between Li with carbon, tungsten, hydrogen and impurities, in addition to post situ experimental characterization and analysis of the divertor plasma facing components in EAST. This final report describes the overall progress within each of these tasks at the University of Tennessee within the project.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-physics Topology OPtimization and Additive Manufacturing for High-temperature Heat Exchangers

This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Controlled 3D nanoparticle deposition by drying of colloidal suspension in designed thin micro-porous architectures

Nanoparticle deposition by drying of colloidal suspension in thin micro-porous architectures has attracted a lot of attention in scientific research as well as industrial applications. However, the underlying mechanisms of such three-dimensional (3D) deposition are not yet fully revealed due to the complexity of the co-occurring processes of two-phase fluid flows, phase change and mass transport. Consequently, the control of 3D nanoparticle deposition remains a challenge. We use a combined experimental and numerical approach to achieve controlled 3D nanoparticle deposition by drying of colloidal suspension in two pillar-based thin micro-porous architectures. By the design of pillar layout, rectangular-spiral and circular-spiral deposition configurations are obtained globally. By varying the surface wettability, vertically symmetric and sloped nanoparticle depositions can be achieved locally. While the numerical modeling reveals the mechanisms of liquid internal flow, as well as the impact of local drying rate on nanoparticle transport, accumulation and final deposition, the experimental results of deposition configurations validate the controlling strategies. This combined experimental and numerical work provides a framework to achieve desired 3D nanoparticle deposition in thin micro-porous architectures, with a thorough understanding of the underlying mechanisms of two-phase fluid flows, phase change and mass transport.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tracking Local pH Dynamics during Water Electrolysis via In-Line Continuous Flow Raman Spectroscopy

The performance of electrochemical devices, which play a critical role in decarbonization efforts, is often governed by proton-coupled electron transfer reactions at the electrode–electrolyte interface. These reactions are highly sensitive to the complex and dynamic microenvironment present at the electrode surface. However, characterizing this environment─particularly monitoring interfacial pH and its evolution under reaction conditions─remains challenging, necessitating the development of advanced analytical tools. Here, in this study, we introduce in-line continuous flow Raman spectroscopy (CFRS) as a spectroelectrochemical platform for quantifying interfacial pH swings generated during water-splitting. By monitoring phosphate ion speciation and controlling the hydrodynamics with a flow cell, we measure pH swings as a function of current density, flow rate, and distance from the electrode. Comparison with theoretical models reveals the impact of bulk pH, boundary layer thickness, and bubble dynamics at high current densities. Collectively, these findings establish CFRS as a platform for quantitatively investigating pH dynamics, offering critical insights for advancing electrochemical energy conversion technologies.

Marquez, Raul A. [Univ. of Texas, Austin, TX (Unit↗
DOE OSTI2024

Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective

Stoichiometric genome-scale metabolic models (generally abbreviated GSM, GSMM, or GEM) have had many applications in exploring phenotypes and guiding metabolic engineering interventions. Nevertheless, these models and predictions thereof can become limited as they do not directly account for protein cost, enzyme kinetics, and cell surface or volume proteome limitations. Lack of such mechanistic detail could lead to overly optimistic predictions and engineered strains. Initial efforts to correct these deficiencies were by the application of precursor tools for GSMs, such as flux balance analysis with molecular crowding. In the past decade, several frameworks have been introduced to incorporate proteome-related limitations using a genome-scale stoichiometric model as the reconstruction basis, which herein are called resource allocation models (RAMs). This review provides a broad overview of representative or commonly used existing RAM frameworks. This review discusses increasingly complex models, beginning with stoichiometric models to precursor to RAM frameworks to existing RAM frameworks. RAM frameworks are broadly divided into two categories: coarse-grained and fine-grained, with different strengths and challenges. Discussion includes pinpointing their utility, data needs, highlighting framework strengths and limitations, and appropriateness to various research endeavors, largely through contrasting their mathematical frameworks. Finally, promising future applications of RAMs are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Li-ion Battery Material phase prediction through Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are widely adopted in many industrial applications. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Therefore, it can eventually help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. However, these images often suffer from low image contrast between multiple material constituents , making it difficult for humans to distinguish and characterize these constituents through visualization. A minor error in detecting distributions among the material constituents can lead to a high error in the calculated parameters of material properties.We present a novel hierarchical curriculum learning framework to address the complex task of estimating material constituent distribution in battery electrodes. To provide spatially smooth prediction, our framework comprises three modules: (i) an uncertainty-aware model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a technique to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator to appropriately fuse the local and global effects towards obtaining the final distribution.

Tabassum, Anika↗
DOE OSTI2020

Radiological Monitoring Plan for the Oak Ridge Y-12 National Security Complex: Surface Water

DOE Order 458.1 requires that dose estimates consider contributions from all facilities. In the Y-12 Radiological Monitoring Plan (RMP), surface water is monitored at points that reflect individual facilities, as well as at points that reflect the combined contributions of all facilities. This monitoring plan does not consider other potential routes (i.e., airborne releases and food chains). Thus, a complete determination of total effective dose (TED) cannot be made based on this plan alone. The other routes from Y-12, and all routes from other DOE facilities on the Oak Ridge Reservation (e.g., Oak Ridge National Laboratory (ORNL) and The Heritage Center), must be considered in order to satisfy DOE Order 458.1 requirements. Determination of TED from all sites and pathways is done through the use of dose-assessment models and is documented in the Annual Site Environmental Report. This monitoring plan provides adequate monitoring goals for Y-12 surface water releases to provide input of sufficient sensitivity and accuracy to reliably determine the Y-12 surface water component of the TED. The routine radiological monitoring program is designed to monitor effluents at four types of locations: (1) treatment facilities, (2) other point and area source discharges, (3) instream locations, and (4) production building roof run-off. With this sampling and analysis program, data will be obtained on primary point sources as well as on locations that represent the composite of other potential sources. This plan will be reviewed periodically to determine necessary modifications to the sampling frequencies, parameters, and locations. Modifications, if any, will be based on the analysis of the previous data and its effectiveness in satisfying the objectives of this plan. Appendix A contains graphs of the sum of the DCS fractions for locations and frequencies contained in a previous version of this plan. The data was collected from January 2009 through December 2019. Each sample was analyzed, and each result was divided by the appropriate DCS to compute a DCS fraction. These fractions were summed for all isotopes. According to DOE –STD-1196-2011, the annual average of these sums should be below 1.

54 ENVIRONMENTAL SCIENCES↗