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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Molecular detection of per- and polyfluoroalkyl substances in water using time-of-flight secondary ion mass spectrometry

Detection of per- and polyfluoroalkyl substances (PFASs) is crucial in environmental mitigation and remediation of these persistent pollutants. We demonstrate that time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a viable technique to analyze and identify these substances at parts per trillion (ppt) level in real field samples without complicated sample preparation due to its superior surface sensitivity. Several representative PFAS compounds, such as perfluorooctanesulfonic acid (PFOS), perfluorobutanoic acid (PFBA), perfluoropentanoic acid (PFPeA), perfluoheptanoic acid (PFHpA), and perfluorononanoic acid (PFNA), and real-world groundwater samples collected from monitoring wells installed around at a municipal wastewater treatment plant located in Southern California were analyzed in this work. ToF-SIMS spectral comparison depicts sensitive identification of pseudo-molecular ions, characteristic of reference PFASs. Additionally, principal component analysis (PCA) shows clear discrimination among real samples and reference compounds. Our results show that characteristic molecular ion and fragments peaks can be used to identify PFASs. Furthermore, SIMS two-dimensional (2D) images directly exhibit the distribution of perfluorocarboxylic acid (PFCA) and PFOS in simulated mixtures and real wastewater samples. Such findings indicate that ToF-SIMS is useable to determine PFAS compounds in complex environmental water samples. In conclusion, ToF-SIMS provides simple sample preparation and high sensitivity in mass spectral imaging, offering an alternative solution for environmental forensic analysis of PFASs in wastewater in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Soil Temperature and Moisture, Council Road Mile Marker 71, Seward Peninsula, Alaska, beginning 2016

Daily averages of soil temperature and moisture measured once every hour at different heights, as well as daily averages of hourly measured snow depths located at Intensive Monitoring Stations at Council Road Mile Marker 71 site. Deployed at each site is an Onset HOBO U30 data logger with five smart temperature sensors and three smart soil moisture sensors (10HS). Three sites (CN_IS_4, CN_IS_6A, CN_IS_7) are equipped with a snow depth sensor. Data are retrieved annually since 2016. Contains 53 *.CSV files including a file inventory list by year. Data files have header rows, NaN fields indicate invalid or missing data, and negative vertical offsets are above ground. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Investigating profile stiffness and critical gradients in shaped TCV discharges using local gyrokinetic simulations of turbulent transport

The experimental observation made on the TCV tokamak of a significant confinement improvement in plasmas with negative triangularity ( δ < 0) compared to those with standard positive triangularity has been interpreted in terms of different degrees of profile stiffness (Sauter et al. Phys. Plasmas 21 055906, 2014) and/or different critical gradients. Employing the Eulerian gyrokinetic code GENE (Jenko et al. Phys. Plasmas 7 1904, 2000), profile stiffness and critical gradients are studied under TCV relevant conditions. For the considered experimental discharges, trapped electron modes (TEMs) and electron temperature gradient (ETG) modes are the dominant microinstabilities, with the latter providing a significant contribution to the non-linear electron heat fluxes near the plasma edge. Two series of simulations with different levels of realism are performed, addressing the question of profile stiffness at various radial locations. Retaining finite collisionality, impurities and electromagnetic effects, as well as the physical electron-to-ion mass ratio are all necessary in order to approach the experimental flux measurements. However, flux-tube simulations are unable to fully reproduce the TCV results, pointing towards the need to carry out radially nonlocal (global) simulations, i.e. retaining finite machine size effects, in a future study. Some conclusions about the effect of triangularity can nevertheless be drawn based on the flux-tube results. In particular, the importance of considering the sensitivity to both temperature and density gradient is shown. The flux tube results show an increase of the critical gradients towards the edge, further enhanced when δ < 0, and they also appear to indicate a reduction of profile stiffness towards plasma edge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

SRS Strategy for Tank 3 Salt Dissolution - Performance and Lessons Learned - 20441

The Savannah River Site (SRS) Tank Farms have 51 underground waste tanks used to store and process liquid nuclear waste materials. There are 4 different tank types, ranging in capacity from 2,840,000 to 4,920,000 L (750,000 to 1,300,000 Gal). Twenty-four of the tanks are older style and do not meet full secondary containment standards. The older style tanks are the initial focus of waste removal efforts for tank closure at SRS. Eight of these twenty-four tanks have completed waste removal and are filled with grout. Prior to salt dissolution, Tank 3 was a dry salt tank that contained 5.06 m (199.3 in) of salt and sludge waste. Additional salt waste was present on cooling coils above the salt layer up to approximately 5.59 m (220 in). Three mixing eductors were installed in Tank 3 to aid in dissolving salt waste in three tank riser access ports. A transfer pump was installed, and the transfer pump suction was located 25.4 cm (10 in) from the tank bottom. Well water was added to the tank through a downcomer until the dry bulk salt was covered with liquid. During the initial fill of Tank 3, approximately 242,000 L (64,000 Gal) of rain water were added from periodic F-Tank Farm (FTF) Catch Tank additions and approximately 17,000 L (4,500 Gal) of well water were added. Following liquid additions to cover the dry bulk salt, well water was added through the three mixing eductors in batches during each stage. Additionally, during the salt dissolution campaigns, the FTF Catch Tank was utilized to add rain water through a downcomer in the center tank riser access port as needed for volume relief in the FTF Catch Tank. Following liquid additions, the water was recirculated (internal to the tank) using the transfer pump, and a sample was pulled to confirm the target specific gravity (SpG) of the dissolved salt solution was achieved. The dissolved salt solution was then transferred to the receipt tank (Tank 7), and the mixing eductors were lowered as close to the new bulk salt layer as possible, to support subsequent dissolution campaigns. While the mixing jets were able to dissolve salt successfully in Tank 3, they did not do so in a completely uniform manner. Throughout dissolution, mounds were discovered under Riser 1, Riser 2, and the Center Riser. The mixing jets dissolved the salt around the edges of the tank well but were not as effective toward the center of the tank. FTF Catch Tank additions through the center tank riser access port downcomer were required to impact the mound under the center tank riser. FTF Catch Tank additions were sporadic as they were dependent on rainfall in the area. Additionally, all mixing jets were rarely able to be lowered to the same elevation, indicating some mounding in the bulk salt layer. Indexing of the mixing jets was also utilized to impact the salt mounds. Overall, Tank 3 salt dissolution was successful as approximately 1,476,000 L (390,000 Gal) of dissolved salt solution was transferred to Tank 7 over six stages. Slightly less than 852,000 L (225,000 Gal) of water were added to Tank 3. The original material balance prediction estimated that the bulk salt level in Tank 3 would be 3.88 m (152.8 in) after six salt dissolution stages. After six stages the actual bulk salt level was 3.38 m (133 in). This paper will discuss the salt removal strategy, each salt dissolution stage, and lessons learned for future salt dissolution. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Monitoring of ground water table depth and soil moisture at the Point Reyes field site

Ground water table (GWT) depth and soil moisture (SM) have been monitored at several locations at the Point Reyes field site (Californian coastal grassland) from 2021 to 2024. Monitoring is still on-going and data may be added to this archive at later time. The SM data have been acquired using Teros 12 Meter soil moisture sensors placed at 10, 30, 60 and 90 cm depth at 5 locations along a small hillslope. These sensors also collect soil temperature and bulk conductance. In addition, some collocated sensors provide pore pressure and Photochemical Reflectance Index (PRI). The GWT depth has been inferred from various type of Onset pressure transducers. The pressure measurements have been corrected for atmospheric pressure variations and sensor position relative to the ground surface to infer GWT depth, as well as with RTK GPS data to infer GWT elevation. The GWT data have been acquired at 5 distinct locations from 2020 to 2024 with the sensors placed at about 4 m depth. In addition, GWT data has been acquired for the 2023-2024 period with sensors located in 1 m deep shallow wells installed near each deeper well. This data is intended to evaluate possibly different dynamic in shallow (perched) and deep aquifer. The datasets are all provided in csv format. Please note that the interpretation of the GWT data needs to be done with consideration of environmental and well characteristics at the site and uncertainty in various variables. For more information on GWT and SM data, please contact the author.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Techno-economic assessment of distributed wellhead RO water treatment for nitrate removal and salinity reduction: A field study in small disadvantaged communities

Techno-economic analysis of distributed wellhead water treatment and desalination (DWTD) systems was carried out based on a three-year field study in three small, disadvantaged communities (DACs) to evaluate the reliability and affordability of upgrading their impaired well water. The local water supplies of the three study DACs, located in Salinas Valley, California, were contaminated with nitrate at levels (~ 12–87 mg/L NO$^{-}_{3}$ - N) ) above the California maximum contaminant level (MCL) of 10 mg/L NO$^{-}_{3}$ - N , and had elevated water salinity (~600–1,600 mg/L total dissolved solids(TDS)) above its secondary MCL (SMCL) of 500 mg/L TDS. Well water nitrate removal and salinity reduction were accomplished via reverse osmosis (RO) based DWTD systems that operated autonomously, supported by remote monitoring and supervisory cyberinfrastructure. Reliable DWTD operation provided treated water quality, with respect to nitrate and salinity, in the range of 0.5–6.3 mg/L NO$^{-}_{3}$ - N and 57–161 mg/L TDS, respectively, which were well below the respective MCL and SMCL. The levelized cost of water treatment was in the range of ~$$2/m 3 - $$2.9/m 3 which aligns with typical residential water costs in California and in the study region, and monthly residential water costs (39 dollars-74 dollars/residential unit/month) were also within the range in California. The study showcased the DWTD approach as a viable and potentially scalable solution for upgrading impaired local potable water supply of communities lacking centralized water delivery infrastructure. However, streamlined permitting processes and standardized regulatory frameworks are critical to promoting wider adoption and maximizing the socio-economic benefits of the DWT approach. Moreover, DACs are likely to require government subsidies in order to cover the CapEx of DWTD systems in addition to upgrade of site infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Natural abundance nitrate isotopes from Rifle and the East River Watershed, Colorado

This data package provides data on the natural abundance isotopes of nitrate from various sources, including porewater, stream, and precipitation. The overall purpose of this data package is to complement additional data streams for nitrogen cycling metrics (e.g., riverine inorganic and organic nitrogen measurements) with specific data gleaned from the interpretation of terrestrial and riverine isotope measurements and collectively understand on how nitrogen is cycled around this system. The Rifle and East River are part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Collection locations include: Pumphouse (multiple sampling dates), River (upstream/ downstream meander C), Shallow soil lysimeters (hillslope, toeslope, floodplain), Hillslope-floodplain borehole wells (i.e., Pumphouse Lower Montane (PLM) wells), and Potassium chloride(KCL)-extracted soil samples. Copper Creek sampling includes 8x river sample points and two tributaries sampled on Sept. Oct. 2017, July 2018. East River below the Rocky Mountain Biological Laboratory sampling includes 1 access point sampled on July, Sept. Oct. 2017. Rifle floodplain sampling includes well TT03 across multiple collection times over 2014. Data is provided in 5 individual files by location in csv format, or all compiled in Excel format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Fermilab Booster loss modelling and rebalancing using Bayesian methods

To meet PIP-II upgrade requirements, Fermilab Booster losses need to be reduced by 50% compared to present levels. So far, simulations are not good enough to predict loss patterns. Thus, an extensive Booster tune up will be necessary to achieve required performance. In this paper we present an effort to build a data-driven loss model using Bayesian techniques, and subsequently to rebalance losses for higher trip margins. We first created several sets of spatially and temporally isolated orbit and optics knobs, and trained Gaussian process models for each beam loss monitor as well as beam current. Novel techniques of uncertainty constraints and approximate GP fitting were introduced to handle safety and timing requirements. We then performed single and multi-objective tuning using scalarized objectives comprised of critical beam loss locations. We achieved significant rebalancing of losses, increasing margins by 25%, as well as an overall improvement in transmission efficiency of 0.4%. Automated data collection is being developed so that more accurate surrogate models can be trained over time.

Kuklev, N. [Fermilab]↗
DOE OSTI2022

Automatic Calibration of a Geomechanical Model from Sparse Data for Estimating Stress in Deep Geological Formations

Summary In this study, we demonstrate geomechanical modeling with fully automatic parameter calibration to estimate the full geomechanical stress fields of a prospective US carbon dioxide (CO2) storage site, based on sparse measurement data. The goal is to compute full stress tensor field estimates (principal stresses and orientations) that are maximally compatible with observations within the constraints of the model assumptions, thereby extending pointwise, incomplete partial stress measurement to a simulated full formation stress field, as well as a rough assessment of the associated error. We use the Perch site, located in Otsego County, Michigan, USA, as our case study. The input data consist of partial stress tensor information inferred from in-situ borehole tests, geophysical well logs, and processing of seismic data. A static earth model (SEM) of the site was developed, and geomechanical simulation functionality of the open-source MATLAB Reservoir Simulation Toolbox (MRST) was used to model the stress field. Adjoint-based nonlinear optimization was used to adjust boundary conditions and material properties to calibrate simulated results of observations. Results were interpreted through a Bayesian framework. The focus of this paper is to demonstrate how the fully automatic calibration procedure works and discuss the results obtained; it does not attempt a detailed analysis of the stress field in the context of the proposed CO2 storage initiatives. Our work is part of a larger effort to noninvasively determine in-situ stresses in deep formations considered for CO2 storage. Guided by previously published research on geomechanical model calibration, our work presents a novel calibration approach supporting a potentially large number of linear or nonlinear calibration parameters to produce results optimally agreeing with available measurements and thus extend partial pointwise estimates to full tensor fields compatible with the physics of the site.

Engineering↗
DOE OSTI2020

Scale and Regionality of Nonelectric Markets for U.S. Nuclear Light Water Reactors

This study assesses existing and potential industries that could conceivably be directly coupled to existing nuclear reactors. The goal is to identify the scale, location, and accessibility of the candidate industrial-product markets, as well as process feedstocks that are available near the plants to establish new industries. For example, CO 2 as a feedstock can be combined with H 2 to produce formic acid (FA), transportation fuels, and lubricants. These new plants can be entirely supported with the heat and electricity provided by a nearby NPP. The potential demand for nonelectric industrial products was assessed by documenting current and possible growth of nonelectricity product markets considered. This assessment used DOE- and industry-supported tools, data, and projections to capture regional industrial market opportunities. Electricity-capacity markets that reward large and reliable generators, such as NPPs, were considered because the electricity market will likely continue to be an important revenue source to NPPs. The key is to balance the needs of energy customers so as to optimize revenue for the affiliated energy customers or partners. In most cases, flexible plant energy delivery and power generation for the grid will require either energy storage or a stock of intermediate products to sustain the industrial customers when the NPP dispatches electricity to the grid. A diverse mix of temperate regions with operating NPPs around the U.S.—representing a variety of operating markets, local generation mix, and seasonal climates—were chosen for this market study. Both current and future market opportunities for candidate industrial-product markets surrounding these NPPs were studied. Figure 2 illustrates the regions chosen for this study. The success of developing nonelectric industrial-product markets as alternative revenue-generating sources for LWRs depends, not only on demand from growing existing markets, such as petroleum refining and NH 3 production, but also on the development of new markets such as light-duty (LD) and heavy-duty (HD) hydrogen FCEVs, synfuels, chemical production, biofuels, metal refining, injection of hydrogen into NG pipelines for gas power-generating units, FA, polymers, and close-coupled industrial heat applications, all of which can significantly increase demand relative to current levels while decarbonizing energy sectors. This study also presents a sample analysis of the economics of hydrogen production in an area of Minnesota, considering the capital and operating costs of a hydrogen plant as well as the local market demand for hydrogen. It includes some assumptions on electricity-grid pricing, showing how hydrogen could be integrated with an NPP and be competitive with the incumbent hydrogen-production process, steam methane reforming (SMR). The objectives of this study include: Provide U.S. NPP operators a robust sampling of the market demand location, scale, and accessibility (including storage and transportation) of the wide variety of industrial-product choices that can be produced using nuclear thermal energy and electricity proximate to a subset of U.S. NPPs to inform the industry of the potential opportunity; show examples and trade-off analyses of how U.S. LWR operators can access these markets, including storage and transportation of industrial products to their intended markets; and present a general analysis example for one industrial product (hydrogen) in one region (Minnesota area), including production, storage, and transportation, to show how nuclear-hybrid integrated energy systems (IESs) could access local markets and improve the profitability of an NPP.

03 NATURAL GAS↗
DOE OSTI2020

Leakage detection using smart field technology

Various examples are provided for gas leakage detection from geologic storage sites. In one example, a system for detection of gas leakage from a geologic storage site includes permanent down-hole gauges (PDGs) disposed at different depths within a well and an evaluation system that can determine a three-dimensional (3D) location of the gas leakage from the geologic storage site and a leakage indicator. The 3D location and leakage indicator can be determined using pressure data provided by the PDGs. The geologic storage site can store, e.g., CO2, natural gas or other type of gas. In another example, a method for detecting gas leakage from a geologic storage site includes receiving pressure data provided by PDGs disposed within one or more wells associated with the geologic storage site, determining key performance indicators using the pressure data and determining a 3D location and a leakage indicator using the key performance indicators.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

From tides to seasons: How cyclic tidal drivers and plant physiology interact to affect carbon cycling at the terrestrial-estuarine boundary (Final technical report)

Coastal ecosystems are among the most biologically and biogeochemically active and diverse systems on Earth. Because they act as important linkages between terrestrial ecosystems and the open ocean, their incorporation in Earth system models (ESMs) is critical to predict coastal and global responses to environmental changes. However, they vary greatly in the magnitude of tides and the volume and timing of freshwater input from land, making it challenging to model the major biogeochemical reactions that control productivity and greenhouse gas emissions across coastal terrestrial aquatic interfaces (TAIs). Our overall objective was to improve mechanistic process understanding and modeling of tidal wetland hydro-biogeochemistry in coastal TAIs. We established a new flux tower site (Ameriflux US-PLo) in the oligohaline part of the Parker River to continuously monitor ecosystem-scale carbon fluxes under temporally varying salinity conditions. The site is co-located with long-term monitoring plots of the Plum Island Ecosystems LTER project. We installed wells and redox sensors in the marsh interior and creek bank, established biomass monitoring plots and deployed novel optode sensors in both locations. We used this data to parameterize plant-mediated transport in PFLOTRAN and tested the impact of soil heterogeneity on porewater constituents and gas fluxes. We collected observations of root oxygen release with a novel planar optode system in the field. Flux data collected during the measurement period encompasses a large variation in salinity ranging from drought to record precipitation years. We developed a method to extract functional relationships from the flux data using artificial neural networks, identifying salinity thresholds for CH 4 fluxes. Finally, we are using the coupled ELM-PFLOTRAN model to test the impact of antecedent hydrological conditions on the salinity-CH 4 flux relationship. This grant contributed to the professional development of one postdoc, three research assistants and one graduate student. The sensor data has been shared with external collaborators.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CFD modeling and simulation for corrosive wear of refractory in molten slag

The development of high-wear resistant refractories having minimal production costs is facilitated by characterizing the wear mechanisms associated with their corrosive wear. Static cup testing is a commonly used method for comparing the corrosion resistance performance of two or more refractory materials. Although the static cup test conditions are not as severe as dynamic tests, this study shows that the thermal gradient present within the system during heating and cooling stages serves to generate movement of the slag leading to mechanical wear. The thermal gradient within the refractory, and between the slag and the refractory, occurs during the ramp stage of the test and lasts until the soaking stage is reached bringing the system to a thermal equilibrium. Using computational fluid dynamics (CFD) capabilities embedded within ANSYS software, this study modelled and quantified the convection currents within the slag and associated shear stresses generated on the refractory walls due to the thermal gradient. A traditional ladle furnace was employed as a case study to verify the results of the studied CFD model. The corrosion rate of the refractory lining was found to depend on the mass transfer coefficient of the refractory dissolution into the slag, and a velocity term which governs the extent of corrosion at any given location. This velocity term is a function of slag viscosity, as well as the concentration gradient and/or temperature gradient at the triple points. In this study, wall shear stress was used as a reliable proxy for identifying high-velocity regions prone to excessive corrosive wear. Elevated wall shear stress near the slag/air and slag/molten steel interfaces align with observed corrosion grooves, which reflects the intensified corrosive wear at these locations.

Ramteke, Rajat Rajat Durgesh Ramteke [University o↗
DOE OSTI2023

Vehicle Localization in 3D World Coordinates Using Single Camera at Traffic Intersection

Optimizing traffic control systems at traffic intersections can reduce the network-wide fuel consumption, as well as emissions of conventional fuel-powered vehicles. While traffic signals have been controlled based on predetermined schedules, various adaptive signal control systems have recently been developed using advanced sensors such as cameras, radars, and LiDARs. Among these sensors, cameras can provide a cost-effective way to determine the number, location, type, and speed of the vehicles for better-informed decision-making at traffic intersections. In this research, a new approach for accurately determining vehicle locations near traffic intersections using a single camera is presented. For that purpose, a well-known object detection algorithm called YOLO is used to determine vehicle locations in video images captured by a traffic camera. YOLO draws a bounding box around each detected vehicle, and the vehicle location in the image coordinates is converted to the world coordinates using camera calibration data. During this process, a significant error between the center of a vehicle’s bounding box and the real center of the vehicle in the world coordinates is generated due to the angled view of the vehicles by a camera installed on a traffic light pole. As a means of mitigating this vehicle localization error, two different types of regression models are trained and applied to the centers of the bounding boxes of the camera-detected vehicles. The accuracy of the proposed approach is validated using both static camera images and live-streamed traffic video. Based on the improved vehicle localization, it is expected that more accurate traffic signal control can be made to improve the overall network-wide energy efficiency and traffic flow at traffic intersections.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A Simplified Method for Predicting Shaker Voltage in IMMATs

Impedance Matched Multi-Axis Tests (IMMATs) can replicate in-service vibration induced stress more accurately than single axis shaker table tests as they can better match a part’s operational boundary conditions and excite it in multiple degrees of freedom simultaneously. Here, the shakers used in IMMATs are less powerful than shaker tables, so shaker force limits can be exceeded during tests if they are not placed adequately for the desired environment. The ability to predict shaker voltage and force before performing a test is, therefore, helpful in selecting shaker locations so that their limits are not exceeded. In this study, electrodynamic shakers were modeled as discrete electromechanical systems, and the shaker parameters were chosen to match experimentally obtained acceleration/voltage frequency response functions (FRFs). These models were coupled to a finite element model of the device under test (DUT) via dynamic substructuring, and the substructured model was demonstrated to accurately predict shaker voltage as well as the error in reproducing the environment at multiple accelerometer locations. A simple method called the FRF Multiplication method, in which the FRF of the substructured system is approximated as the product of two separate FRFs of the shaker and DUT respectively, was proposed and applied to the same system, yielding similar voltage and error predictions to those obtained using substructuring. Simple case studies were presented to explore the applicability of the proposed method, and it was demonstrated to have similar accuracy to the substructuring method in a range of cases. Additionally, we showed that while it was not possible to derive a unique model of the shakers from acceleration/voltage FRFs alone, the models that could be obtained were sufficient to predict test error almost perfectly and shaker voltage with less than 40 percent error.

42 ENGINEERING↗
DOE OSTI2026

Nanopores with dynamic pore opening diameter

Solid state nanopores have emerged as model systems for understanding transport properties on the nanoscale. They serve as templates for both preparing mimics of biological channels and designing biological sensors. Unlike their biological inspirations, the majority of nanopores prepared thus far, however, have been structurally static devices such that the pore opening diameter is fixed. If we could prepare nanopores whose opening diameter fluctuated in time with controlled amplitude at known locations in the pore, we could create ionic memristors as well as achieve new transport modes. Here we present ∼10 nm diameter single nanopores drilled through a 10 nm thick gold layer positioned on top of a 30 nm thick silicon nitride film. Two types of devices were prepared; one containing single stranded DNA and the other containing hairpin DNA attached to the discrete layer of gold using thiol chemistry. When an external electric field was applied across a nanopore with single stranded DNA, the nanoconfined DNA molecules exhibited steric and electrical constraints that led to memristor-like behavior in the current–voltage curves. The degree of hysteresis was controlled by salt concentration, magnitude of voltage and pore diameter. In contrast, nanopores containing DNA hairpins conducted similar currents in forward and reverse bias in agreement with the rigidity of the hairpin molecule. The experiments are explained by Brownian dynamics simulations that reveal voltage and salt concentration induced changes in DNA extension. The degree of DNA extension was also found to be dependent on the location of the molecules along the pore axis. The nanopores presented here provide the first steps towards preparation of non-equilibrium nanopore systems.

Vlassiouk, Ivan [ORNL] (ORCID:0000000254940386)↗
DOE OSTI2021

Assessment of Contaminant Bioaccumulation in Aquatic Biota on and Adjacent to the Oak Ridge Reservation—2020

This report provides information on contaminant concentrations in multiple wildlife prey species inhabiting or associated with water bodies on and downstream from the Oak Ridge Reservation (ORR), including regional reference sites. This information can be used to understand the nature and extent of contaminant exposure and transfer through the food web and to provide a baseline for evaluating temporal trends in contaminant exposure and accumulation. This information was gathered as part of the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Five-Year Review (FYR) process, and it also addresses regulator comments on the annual Remediation Effectiveness Report (RER). This report summarizes the results of biological sampling completed in the spring and summer of 2020, prior to the 2021 FYR. Sampled locations included key sites upstream from the point sources of contaminants, along with watershed integration points on and off the ORR. Integration points are spatially the most important sampling sites because they capture biological responses to upstream contaminant inputs from both aqueous and groundwater sources, as well as responses to various remedial actions. These sites are most often located at a watershed administration unit boundary and may have regulatory significance for performance measures. In many cases, there are long-term biological and other monitoring data associated with these sites; these data generally fall within the areas of exposure and effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine Learning Approach for Spatiotemporal Multivariate Optimization of Environmental Monitoring Sensor Locations

Abstract Long-term environmental monitoring is critical for managing the soil and groundwater at contaminated sites. Recent improvements in state-of-the-art sensor technology, communication networks, and artificial intelligence have created opportunities to modernize this monitoring activity for automated, fast, robust, and predictive monitoring. In such modernization, it is required that sensor locations be optimized to capture the spatiotemporal dynamics of all monitoring variables as well as to make it cost-effective. The legacy monitoring datasets of the target area are important to perform this optimization. In this study, we have developed a machine-learning approach to optimize sensor locations for soil and groundwater monitoring based on ensemble supervised learning and majority voting. For spatial optimization, Gaussian process regression (GPR) is used for spatial interpolation, while the majority voting is applied to accommodate the multivariate temporal dimension. Results show that the algorithms significantly outperform the random selection of the sensor locations for predictive spatiotemporal interpolation. While the method has been applied to a four-dimensional dataset (with two-dimensional space, time, and multiple contaminants), we anticipate that it can be generalizable to higher-dimensional datasets for environmental monitoring sensor location optimization.

Siddiquee, Masudur R.↗