A normal form-based power system out-of-step protection
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Ugwuanyi, Nnaemeka Sunday (ORCID:0000000285788962)↗
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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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Temperature-responsive smart tracers for field-measurement of inter-well thermal evolution: Heterogeneous kinetics and field demonstration
Temperature-responsive smart tracers enable advanced warning of a “premature thermal breakthrough” and may therefore improve reservoir management and reduce financial risk. A successful calculation of inter-well fluid temperatures requires that temperature-dependent kinetics are known, which typically result from homogeneous batch reactor experiments. However, recent meso-scale field experiments at the Altona Field Laboratory involving fluid flow in a discretely-fractured reservoir suggest that silica-fluid interfaces may accelerate hydrolysis kinetics. Here, the Arrhenius parameters of phenyl acetate hydrolysis are investigated under heterogeneous reaction conditions in packed-bed column experiments. The breakthrough curve of the reaction product is compared to an inert reference tracer (carbon-cored nanoparticles). Temperatures experienced during field testing ranging from 10 to 40 °C were studied using a phosphate buffer solution to maintain a near-neutral pH, as found in the reservoir. The empirically-determined pre-exponential factor and activation energy values are subsequently used in a first-order kinetic model to improve calculations of effective reservoir temperatures for these meso-scale field tests. Here, the results suggest that hydrolysis reactions can directly monitor inter-well reservoir temperatures, but only if the influence of solid-fluid interactions are carefully accounted for.
15 GEOTHERMAL ENERGY↗
A metric for evaluating conformance robustness during geologic CO 2 sequestration operations
A metric for quantifying the robustness of a designation of conformance of a geologic CO 2 sequestration (GCS) project during its operational phase is developed and demonstrated. Conformance in this context is a measure of the degree to which the sequestration system is understood and can be accurately modeled along with the degree to which the storage system is performing as designed. The robustness of conformance quantifies the degree to which parameter values can deviate from their current nominal estimates and still produce model forecasts that meet the performance criteria for the GCS operation. We develop and demonstrate the approach on a simplified scenario to illustrate the concept using a single uncertain parameter (homogeneous reservoir permeability) and a single performance criterion (critical pressure at a monitoring well in the reservoir; i.e., one that may displace brine from the reservoir to an overlying drinking water aquifer for example). Increased confidence in conformance assessment as more monitoring data are obtained is incorporated through the standard error of the coefficient (reservoir permeability in the case presented here), which we designate as the concordance metric. As more monitoring data become available during the course of the GCS operation, the standard error of the coefficient decreases (in general), thereby leading to increased conformance robustness as a larger deviation from nominal is required to fail to meet performance criteria. Increasing conformance robustness over time builds confidence that a GCS project will continue to meet performance criteria during the life-span of the project, thereby supporting designations of conformance. Furthermore a lack of conformance robustness provides a critical warning that the performance criteria of the GCS operation are not robust against probabilistic and non-probabilistic uncertainty in model conceptualization and/or model parameters.
58 GEOSCIENCES↗
Application of emerging monitoring techniques at the Illinois Basin – Decatur Project
The Illinois Basin – Decatur Project is a large-scale carbon capture and storage demonstration project located in Decatur, Illinois, USA. In this project, one million metric tons of carbon dioxide (CO 2 ) was captured from an ethanol production facility and successfully injected into a deep saline reservoir over a period of three years. The scale of this project presented an opportunity to explore emerging technologies for effective long-term monitoring of the carbon capture and storage site. This research documents the application of three emerging monitoring techniques: (1) a prototype “open-path” sensor, a method of continuously monitoring atmospheric CO 2 by applying tunable diode laser absorption spectroscopy to provide a warning system for personnel safety along pipelines and at wellheads; (2) the Greenhouse Gas Laser Imaging Tomography Experiment (GreenLITE), an automated system for measuring two-dimensional spatial distribution of atmospheric CO 2 concentrations; and (3) periodic aerial imagery, a method of documenting surface-vegetation dynamics to detect vegetative responses to CO 2 leaks. The objective of this work was to assess the advantages and limitations of these monitoring techniques and quantify their reliability over an extended deployment at an active industrial site. These results will aid in determining viability of long-term monitoring on a commercial scale.
42 ENGINEERING↗
Computerized System for Safety Verification of External Beam Radiation Therapy Planning
Purpose: To report an assessment of in-house software, Verifier, developed to improve efficacy and efficiency of the radiation therapy (RT) treatment planning process and quality control review (QCR). Methods and Materials: Radiation therapy plan parameters retrieved from our treatment planning database are used by automated tests to give 75 types of warnings, such as prescription and plan discrepancies. The software is continuously updated on the basis of new issues, ideas, and planning policies. Verifier was retrospectively assessed (2007-2015) by examining impact on treatment plan revisions, frequency of quality improvement incident reports of avoidable RT plan-related safety events, unaddressed issues, and staff efficiency. Results: Plan revisions for specific issues declined dramatically in response to implementation of corresponding Verifier tests. Between 2012 and 2015 our institution's total rate of plan revisions dropped from 18.0% to 11.2%. Between 2008 and 2015 specific tests were added to Verifier while the rate of corresponding avoidable safety events was reduced from 0.34% to 0.00% over the same period. Simulations suggest Verifier saves approximately 2 to 5 minutes per QCR. Conclusions: The decrease in quantifiable metrics of plan revisions and incident reports suggests automatic RT plan-checking software enhances patient safety and clinical efficiency. Although only modest time savings may be gained using Verifier for the QCR itself, the greater impact on efficiency is through avoiding late-stage plan modifications and improving documentation via automation. We encourage other institutions to consider working toward adding similar technologies to enhance their RT quality assurance programs.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Development and testing of a continuous maritime monitor for radionuclide aerosols
Monitoring airborne concentrations of radionuclide activity may provide a timely warning to sea-based assets to avoid contamination from a radioactive plume. The development and testing of an automated aerosol monitoring system that can capture and detect radioactive particulate from marine air is presented. A custom electrostatic precipitator (ESP) was designed to capture particulate onto a reusable collection media. The collection efficiency of the ESP system for radon progeny was determined to be ~23%. A conservative calculation of the minimum detectable concentration of 214 Bi was estimated as 0.3-8 Bq/m 3 . The system was demonstrated in continuous operation, without consumables and limited maintenance, in a marine environment at the PNNL campus in Sequim, Washington. In conclusion, a successful 2-month deployment indicates the feasibility of the approach for continuous maritime monitoring for radionuclide aerosols.
Moore, Michael E. [Pacific Northwest National Labo↗
Predicting river turbidity in Pine Island Bayou using machine learning techniques coupled with variational mode decomposition
Elevated turbidity levels pose significant public health risks by facilitating the transport of harmful pollutants, including metals, organic compounds, and pathogenic microorganisms into the surface water. These conditions create serious challenges for public recreational water use and drinking water treatment, leading to economic losses and health risks. This study utilizes water monitoring data in Pine Island Bayou, Texas, and develops a Sequence-to-Sequence (S2S) model to predict turbidity using Attention-based Gated Recurrent Units with Encoder-Decoder (AT-GRU-ED) and Long Short-Term Memory (LSTM), coupled with Variational Mode Decomposition (VMD). Compared to the model without VMD, the model demonstrates satisfactory 72-hour turbidity prediction performance, achieving MAEs of 2.60 and 3.29 NTU (reductions of 53% and 58%), RMSEs of 21.08 and 31.49 NTU (reductions of 82% and 80%), and R² values of 0.96 and 0.84 on the validation and test sets, respectively. Feature importance analysis reveals that water temperature is the dominant factor influencing seasonal turbidity patterns, while real-time hourly rainfall significantly contributes to short-term variability. Turbidity typically peaks within 48 hours after rainfall events due to lagged effects from surface runoff and upstream flow. Findings suggest suspending recreational water use and water supply pumping for three days after heavy rainfall can benefit public health and improve water treatment processes. Discharges above 100 m3/s are found to accelerate sediment dilution and transport, reducing turbidity levels more quickly after the peak. In conclusion, the proposed model demonstrates reliable 72-hour turbidity prediction, supporting decision-making for water treatment plant operations and providing early warning for public recreational water use.
Deep learning↗
Intercomparison of flood inundation models across land use types and hydrological flood stages
Flood Inundation Mapping (FIM) model selection is a key operational decision because accurate, rapid mapping underpins early warning and resource allocation. FIM performance is context-dependent and can vary with hydrograph phase, land-use/land-cover (LULC), and the evaluation benchmark. Intercomparison studies typically assess a single near-peak snapshot against one reference dataset. Here, we provide a context-stratified intercomparison across (i) multiple hydrograph phases, (ii) LULC classes, and (iii) benchmark types, for five FIM approaches spanning a wide range of physical complexity and operational cost (TRITON, LISFLOOD-FP, HEC-RAS 2D, ARC-Curve2Flood, and OWP HAND-FIM). We use the Hurricane Matthew flood (2016) in the Neuse River Basin, North Carolina, USA, as a case study. Using high-resolution remote sensing-derived flood inundation maps, hand-labeled points, and building footprints, we assess model skill across two rising and two falling hydrograph limbs and across major LULC types. Results show that model rankings shift systematically across contexts: LISFLOOD-FP ranks highest in three of four flood phases, while TRITON leads during one rising limb phase; LISFLOOD-FP performs best in vegetated areas, whereas HEC-RAS improves relative performance in agricultural and urban areas; and benchmark choice influences conclusions, with LISFLOOD-FP performing best for flooded-building detection in the late falling limb, while TRITON ranks highest against hand-labeled points. We also report representative wall-clock runtimes for each workflow to provide use-case context for operational feasibility. Together, these results offer transferable guidance for model selection and for designing large-scale, benchmark-aware FIM intercomparison studies.
Nikrou, Parvaneh [University of Alabama]↗
Seismic tomography of compressional wave velocity and attenuation structure for Makushin Volcano, Alaska
Located in the central portion of the Alaska-Aleutian subduction zone, Makushin Volcano is among the most active volcanoes in the United States and has been classified as a very high threat by the National Volcano Early Warning System based on its eruptive history and proximity to the City of Unalaska and international air routes. In 2015, five standalone seismic stations and three mini seismic arrays of 15 stations each were deployed on Unalaska Island to supplement the Alaska Volcano Observatory permanent seismic network. This temporary array was operational for one year. Taking advantage of the increased azimuthal coverage and the array's increased earthquake detection capability, we developed body-wave Vp and Vp/Vs seismic images of the velocity structure beneath the volcano. Our results show a complex structure with the upper 4 km of the crust. The shallow high-Vp features possibly delineate remnant magma pathways or conduits. Low-Vp regions are found east of the caldera at approximately 4–8 km depth. This is in agreement with previous seismic tomographic work and InSAR-based geodetic models, which had identified this region as a possible long-term source of magma. A three-dimensional compressional wave attenuation model complemented the velocity models. In general, we observe regions of corresponding low P-wave velocity and high attenuation east of the summit caldera between 5 and 7 km depth, supporting the presence of a melt-rich zone. The absolute Vp values (5.5–6.0 km/s) in this region are consistent with the presence of a magma body with a mafic signature. Here, we suggest that a triggering mechanism that involves mafic injections into a more evolved shallow magma chamber is representative of the current magmatic system below the volcano, similarly to what petrological studies have inferred for past eruptions.
58 GEOSCIENCES↗
Acoustic emission monitoring of crack propagation in additively manufactured and conventional titanium components
We report that additive manufacturing (AM) is a novel and innovative production technology that can produce complex and lightweight engineering products. In AM components, as in all engineering materials, fatigue is considered as one of the principle causes of unexpected failure. In order to detect, localise and characterise cracks in various material components and metals, acoustic emission (AE) is used as a non-destructive monitoring technique. One of the main advantages of AE is that it can be also used for dynamic damage characterisation and specifically for crack propagation monitoring. In this research, we use AE to monitor the fatigue crack growth behaviour of Ti6Al4V components under four-point bending. The samples were produced by means of AM as well as conventional material. Notched and unnotched specimens were investigated with respect to the crack severity and crack detection using AE. The main AE signal parameters –such as cumulative events, hits, duration, average frequency and rise time– were evaluated and indicate sensitivity to damage propagation in order to lead to a warning against the final fracture occurrence. Finally, this is the first time that AE is applied in AM components under fatigue.
36 MATERIALS SCIENCE↗
Synthesis and application of thermally responsive nanofiber coatings for overtemperature monitoring
This study presents a one-pot synthesis route to organometallic nanofibers based on copper thiolate, exhibiting distinctive chemical and physical characteristics. Electron microscopy analysis of morphology and composition revealed 2-10 μm-long, 50-90 nm-diameter hollow and non-hollow fibers composed of copper, sulfur, oxygen, hydrocarbon, and chlorine. Thermogravimetric analysis showed a pronounced mass loss within 120°C-135°C. To elucidate the thermal responsive pathways, the nanofibers were characterized before and after heating. X-ray photoelectron spectroscopy indicates that an initially mixed Cu(I)/Cu(II) oxidation states transition to predominantly Cu(I) upon heating. A layer of nanofiber was coated on battery pouch foil and evaluated as a candidate thermally sensitive coating. At elevated temperature (100-130°C), nanofiber coating released volatile organic compounds, sulfide and sulfur dioxide as detected using multiple gas sensors. This thermally responsive gas release/sensing approach provides a potential large-area temperature monitoring strategy, which is particularly relevant where direct temperature measurements of individual batteries is impractical. The results established proof of concept for nanofiber-coated battery pouch foil as overtemperature warning platform that can provide alerts when surface temperatures exceed a critical threshold. More broadly, the ability to form interconnected fiber networks positions copper thiolate nanofiber coatings as promising materials for advanced applications.
Ihala Gamaralalage, Chanaka [ORNL] (ORCID:00000002↗
Development of complex-shaped liver multicellular spheroids as a human-based model for nanoparticle toxicity assessment in vitro
The emergence of human-based models is incontestably required for the study of complex physiological pathways and validation of reliable in vitro methods as alternative for in vivo studies in experimental animals for toxicity assessment. With this objective, we have developed and tested three dimensional environments for cells using different types of hydrogels including transglutaminase-cross-linked gelatin, collagen type I, and growth-factor depleted Matrigel. Cells grown in Matrigel exhibited the greatest cell proliferation and spheroid diameter. Moreover, analysis of urea and albumin biosynthesis revealed that the created system allowed the immortalized liver cell line HepG2 to re-establish normal hepatocyte-like properties which were not observed under the conditions of conventional cell cultures. This study presents a scalable technology for production of complex-shaped liver multicellular spheroids as a system which improves the predictive value of cell-based assays for safety and risk assessment. The time- and dose-dependent toxicity of nanoparticles demonstrates a higher cytotoxic effect when HepG2 cells grown as monolayer than embedded in hydrogels. The experimental setup provided evidence that the cell environment has significant influence on cell sensitivity and that liver spheroid is a useful and novel tool to examine nanoparticle dosing effect even at the level of in vitro studies. Therefore, this system can be applied to a wide variety of potentially hostile compounds in basic screening to provide initial warning of adverse effects and trigger subsequent analysis and remedial actions. - Highlights: • Comparison of HepG2 cells growth in Matrigel, Collagen I gel and gelatin gel. • Examination of nanoparticles (NP) dosing effect at the level of in vitro studies. • Influence of the cell culture media composition on the cytotoxic effect of NP.
60 APPLIED LIFE SCIENCES↗
Mid-century climate change impacts on tornado-producing tropical cyclones
Tornadoes are a co-occurring extreme that can be produced by landfalling tropical cyclones (TCs). These tornadoes can exacerbate the loss of life and property damage caused by the TC from which they were spawned. It is uncertain how the severe weather environments of landfalling TCs may change in a future climate and how this could impact tornado activity from TCs. In this study, we investigated four TCs that made landfall in the U.S. and produced large tornado outbreaks. We performed four-member ensembles of convective-allowing (4-km resolution) regional climate model simulations representing each TC in the historical climate and a mid-twenty-first century future climate. To identify potentially tornadic storms, or TC-tornado (TCT) surrogates, we used thresholds for three-hourly maximum updraft helicity and radar reflectivity, as tornadoes are not resolved in the model. We found that the ensemble-mean number of TCT-surrogates increased substantially (56–299%) in the future, supported by increases in most-unstable convective available potential energy, surface-to-700-hPa bulk wind shear, and 0–1-km storm-relative helicity in the tornado-producing region of the TCs. On the other hand, future changes in most-unstable convective inhibition had minimal influence on future TCT-surrogates. This provides robust evidence that tornado activity from TCs may increase in the future. Furthermore, TCT-surrogate frequency between 00Z and 09Z increased for three of the four cases, suggesting enhanced tornado activity at night, when people are asleep and more likely to miss warnings. All of these factors indicate that TC-tornadoes may become more frequent and a greater hazard in the future, compounding impacts from future increases in TC winds and precipitation.
54 ENVIRONMENTAL SCIENCES↗
Hemoglobin pretreatment endows rat cortical astrocytes resistance to hemin-induced toxicity via Nrf2/HO-1 pathway
Highlights: • Hb-pretreatment endowed astrocytes the resistance to hemin-induced toxicity. • Hb-pretreatment induced HO-1 expression and prevented hemin-induced ROS production. • Hb-pretreatment induced Nrf2 expression and promoted its nuclear translocation. • Nrf2 knockdown suppressed Hb-induced upregulation of HO-1 expression. • Nrf2 knockdown increased the susceptibility of Hb-pretreated astrocytes to hemin. Oxidative stress mediated secondary injury contributes to neurological deterioration after intracerebral hemorrhage (ICH). Astrocytes, the most dominant cells in the central nervous system (CNS), play key roles in maintaining redox homeostasis by providing oxidative stress defense. Hemoglobin (Hb), the primary component released by hemolysis, is an effective activator of astrocytes. Hemin, the product of Hb degradation, is highly toxic due to the induction of reactive oxygen species (ROS). We speculate that Hb-activated astrocytes are resistant to hemin-induced toxicity. To verify our speculation, Hb-pretreated astrocytes were exposed to hemin, intracellular ROS accumulation and cell apoptosis were evaluated. Heme oxygenase 1 (HO-1) and nuclear transcription factor-erythroid 2 related factor (Nrf2) expression were observed to explore the potential mechanism. The results demonstrated that Hb induced upregulation and nuclear translocation of Nrf2 in astrocytes, resulted in HO-1 upregulation, which contributed to reduced ROS accumulation and apoptosis rate. Knocking down Nrf2 expression by siRNA suppressed Hb-induced upregulation of HO-1 expression and increased the susceptibility of Hb-pretreated astrocytes to hemin-induced toxicity. Taken together, Hb-activated astrocytes acquired resistance to hemin-induced toxicity via Nrf2/HO-1 pathway. This phenomenon can be considered as the adaptive self-defense in the pathological process of ICH. Hb pre-warned astrocytes and enhanced their capability of handling the coming hemin “flood”. Nrf2/HO-1 may be employed as a target for neuroprotection after ICH.
60 APPLIED LIFE SCIENCES↗
Do Households Adapt? Repeated Hurricane Exposure and the Purchasing of Bottled Water
Understanding how households adapt to hurricanes is increasingly important as these events become more frequent and severe. This paper examines how past hurricane exposure influences current household preparedness, focusing specifically on the stockpiling of bottled water. Leveraging scanner data on bottled water purchases for households in the Southeastern United States, we employ a difference-in-differences event study framework to analyze how repeated hurricane experiences affect consumer behavior. Our results indicate that households exposed to hurricane warnings do not increase their preparedness in the subsequent hurricane season, and those experiencing a landfall event underprepare. These results suggest limited learning from past events.
D12↗
Benchmarking Concentration and Extraction Methods for Wastewater-Based Surveillance of Eight Human Respiratory Viruses: Implications for Rapid Application to Novel Pathogens
To provide early warning and support a rapid response to a novel virus through wastewater surveillance, it would be ideal to understand in advance which concentration and extraction methods are likely to be effective for dPCR-based methods, depending on virus characteristics. In this study, we spiked raw wastewater samples with eight human respiratory viruses and processed them with four methods that concentrate and/or extract nucleic acids from both liquid and solid fractions (Promega, Nanotrap, and InnovaPrep) or only the solid fraction of wastewater (Solids). Our findings provide encouraging evidence that all four methods combined with dPCR could detect an emerging virus in wastewater, although they differed in sensitivity. The pattern of recovery efficiency for adenoviruses, coronaviruses, and influenza A viruses was consistent across methods, with Promega producing higher median recovery efficiencies, while distinct patterns were observed for coxsackieviruses. We also normalized the concentration data with two endogenous fecal indicators, PMMoV and Carjivirus (formerly crAssphage). We found that normalization could reduce method-associated differences if the indicator exhibited a recovery pattern similar to that of the target virus. These findings can guide the selection of concentration and extraction methods for wastewater monitoring based on the properties of target viruses, thus enhancing pandemic preparedness.
Biological and medical sciences↗
In Situ Monitoring of Groundwater Contamination Using the Kalman Filter
This study presents a Kalman filter-based framework to establish a real-time in situ monitoring system for groundwater contamination based on in situ measurable water quality variables, such as specific conductance (SC) and pH. First, this framework uses principal component analysis (PCA) to identify correlations between the contaminant concentrations of interest and in situ measurable variables. It then applies the Kalman filter to estimate contaminant concentrations continuously and in real-time by coupling data-driven concentration-decay models with the previously identified data correlations. We demonstrate our approach with historical groundwater data from the Savannah River Site F-Area: We use SC and pH data to estimate tritium and uranium concentrations over time. Results show that the developed method can estimate these contaminant concentrations based on in situ measurable variables. The estimates remain reliable with less frequent or no direct measurements of the contaminant concentrations, while capturing the dynamics of short- and long-term contaminant concentration changes. In addition, we show that data mining, such as PCA, is useful to understand correlations in groundwater data and to design long-term monitoring systems. As a result, the developed in situ monitoring methodology is expected to improve long-term groundwater monitoring by continuously confirming the contaminant plume's stability and by providing an early warning system for unexpected changes in the plume's migration.
54 ENVIRONMENTAL SCIENCES↗
Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks
Short-term Quantitative Precipitation Forecasting is important for flood forecasting, early flood warning, and natural hazard management. This study proposes a precipitation forecast model by extrapolating Cloud-Top Brightness Temperature (CTBT) using advanced Deep Neural Networks, and applying the forecasted CTBT into an effective rainfall retrieval algorithm to obtain the Short-term Quantitative Precipitation Forecasting (0–6 hr). To achieve such tasks, we propose a Long Short-Term Memory (LSTM) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), respectively. The precipitation forecasts obtained from our proposed framework, (i.e., LSTM combined with PERSIANN) are compared with a Recurrent Neural Network (RNN), Persistency method, and Farneback optical flow each combined with PERSIANN algorithm and the numerical model results from the first version of Rapid Refresh (RAPv1.0) over three regions in the United States, including the states of Oregon, Oklahoma, and Florida. We report our experiments indicate better statistics, such as correlation coefficient and root-mean-square error, for the CTBT forecasts from the proposed LSTM compared to the RNN, Persistency, and the Farneback method. The precipitation forecasts from the proposed LSTM and PERSIANN framework has demonstrated better statistics compared to the RAPv1.0 numerical forecasts and PERSIANN estimations from RNN, Persistency, and Farneback projections in terms of Probability of Detection, False Alarm Ratio, Critical Success Index, correlation coefficient, and root-mean-square error, especially in predicting the convective rainfalls. The proposed method shows superior capabilities in short-term forecasting over compared methods, and has the potential to be implemented globally as an alternative short-term forecast product.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗