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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Risk-Aware Framework Development for Disruption Prediction: Alcator C-Mod and DIII-D Survival Analysis

Abstract Survival regression models can achieve longer warning times at similar receiver operating characteristic performance than previously investigated models. Survival regression models are also shown to predict the time until a disruption will occur with lower error than other predictors. Time-to-event predictions from time-series data can be obtained with a survival analysis statistical framework, and there have been many tools developed for this task which we aim to apply to disruption prediction. Using the open-source Auton-Survival package we have implemented disruption predictors with the survival regression models Cox Proportional Hazards, Deep Cox Proportional Hazards, and Deep Survival Machines. To compare with previous work, we also include predictors using a Random Forest binary classifier, and a conditional Kaplan-Meier formalism. We benchmarked the performance of these five predictors using experimental data from the Alcator C-Mod and DIII-D tokamaks by simulating alarms on each individual shot. We find that developing machine-relevant metrics to evaluate models is an important area for future work. While this study finds cases where disruptive conditions are not predicted, there are instances where the desired outcome is produced. Giving the plasma control system the expected time-to-disruption will allow it to determine the optimal actuator response in real time to minimize risk of damage to the device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Resonances in a Chaotic Attractor Crisis of the Lorenz Flow

Local bifurcations of stationary points and limit cycles have successfully been characterized in terms of the critical exponents of these solutions. Lyapunov exponents and their associated covariant Lyapunov vectors have been proposed as tools for supporting the understanding of critical transitions in chaotic dynamical systems. However, it is in general not clear how the statistical properties of dynamical systems change across a boundary crisis during which a chaotic attractor collides with a saddle. This behavior is investigated here for a boundary crisis in the Lorenz flow, for which neither the Lyapunov exponents nor the covariant Lyapunov vectors provide a criterion for the crisis. Instead, the convergence of the time evolution of probability densities to the invariant measure, governed by the semigroup of transfer operators, is expected to slow down at the approach of the crisis. Such convergence is described by the eigenvalues of the generator of this semigroup, which can be divided into two families, referred to as the stable and unstable Ruelle–Pollicott resonances, respectively. The former describes the convergence of densities to the attractor (or escape from a repeller) and is estimated from many short time series sampling the state space. The latter is responsible for the decay of correlations, or mixing, and can be estimated from a long times series, invoking ergodicity. It is found numerically for the Lorenz flow that the stable resonances do approach the imaginary axis during the crisis, as is indicative of the loss of global stability of the attractor. On the other hand, the unstable resonances, and a fortiori the decay of correlations, do not flag the proximity of the crisis, thus questioning the usual design of early warning indicators of boundary crises of chaotic attractors and the applicability of response theory close to such crises.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Increasing risk of cascading hazards in the central Himalayas

Cascading hazards are becoming more prevalent in the central Himalayas. Primary hazards (e.g., earthquakes, avalanches, and landslides) often trigger secondary hazards (e.g., landslide dam, debris flow, and flooding), compounding the risks to human settlements, infrastructures, and ecosystems. Risk management strategies are commonly tailored to a single hazard, leaving human and natural systems vulnerable to cascading hazards. In this commentary, we characterize diverse natural hazards in the central Himalayas, including their cascading mechanisms and potential impacts. A scientifically sound understanding of the cascading hazards, underlying mechanisms, and appropriate tools to account for the compounding risks are crucial to informing the design of risk management strategies. Here, we also discuss the need for an integrated modeling framework, reliable prediction and early warning system, and sustainable disaster mitigation and adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Yesterday’s extremes, today’s new normal: flood risk in the Kathmandu Valley, Nepal

Unplanned urban growth has left many cities increasingly vulnerable to extreme rainfall events, particularly in regions with inadequate drainage infrastructures and development encroaching on natural floodplains. Here, in this perspective paper, we examine the September 2024 floods that struck Central Nepal, triggered by a persistent low-pressure system and enhanced by converging moisture flows from the Arabian Sea and the Bay of Bengal which led to widespread catastrophic damage. In the Kathmandu Valley, floodwaters expanded to more than 2.5 times the bankfull water extent, causing significant damage to housing, transportation network, and critical infrastructure, displacing thousands of residents, and severely disrupting urban services. This event highlights the urgent need for improved flood management strategies that integrate both structural and non-structural measures into the infrastructure development. While early warning systems provided critical lead time, challenges remain in reducing forecasting uncertainties and improving communication across government agencies and with local communities. A forward-looking approach is essential, including probabilistic flood forecasting systems, sustainable floodplain management, risk-sensitive land use planning, climate- and disaster- resilient infrastructure development, and the integration of nature-based solutions like urban green and blue spaces to mitigate flood impacts. By involving local communities in planning and preparedness efforts, particularly through citizen science initiatives, and engagement with underserved and disadvantaged communities, Nepal can better adapt to the growing risks posed by extreme rainfall and urban flooding and enhance long-term disaster resilience in rapidly urbanizing areas like Kathmandu Valley.

Kathmandu Valley↗
DOE OSTI2025

Impact of Cyber Threat Awareness on Driver Response to an Unexpected Vehicle Cyberattack

Here, the integration of advanced cyber-physical systems in heavy vehicles introduces new vulnerabilities by expanding the possibility of cyberattacks. The objective of this study is to evaluate (1) how threat awareness influences driver response to an unexpected cyberattack, (2) how the provision of a basic cyberattack response protocol influences driver performance, and (3) how professionally trained versus standard drivers compare in their responses to a cyberattack. An on-road driving study (N = 50) was conducted using a medium heavy-duty vehicle. Participants were divided into three groups: Control, which remained unaware of any potential cyberattack; Aware, which was informed about the potential cyberattack; and Aware + Protocol, which received the same warning as the Aware group with the addition of a basic cyberattack response protocol. An instrument cluster cyberattack was executed at the same location for all participants. The findings highlight the essential role of awareness and response protocol in enhancing driver response to an unexpected vehicle cyberattack. The Aware + Protocol group had the highest stop rate (100%) and the shortest stopping distances (224 m for standard drivers and 254 m for professionals), compared to the Control group (828 and 520 m, respectively). Aware + Protocol also had the fastest reaction time, averaging 7.53 s, versus 16.12 s (Aware) and 30.29 s (Control). These results emphasize that awareness alone is insufficient. Providing drivers with clear, actionable protocols significantly improves their ability to react quickly and safely to cyberattacks, enhancing overall road safety.

Cybersecurity↗
DOE OSTI2021

Investigating the relation between instantaneous driving decisions and safety critical events in naturalistic driving environment

The availability of large-scale naturalistic driving data provides enormous opportunities for studying relationships between instantaneous driving decisions prior to involvement in safety critical events (SCEs). This study investigates the role of driving instability prior to involvement in SCEs. While past research has studied crash types and their contributing factors, the role of pre-crash behavior in such events has not been explored as extensively. The research demonstrates how measures and analysis of driving volatility can be leading indicators of crashes and contribute to enhancing safety. Highly detailed microscopic data from naturalistic driving are used to provide the analytic framework to rigorously analyze the behavioral dimensions and driving instability that can lead to different types of SCEs such as roadway departures, rear end collisions, and sideswipes. Modeling results reveal a positive association between volatility and involvement in SCEs. Specifically, increases in both lateral and longitudinal volatilities represented by Bollinger bands and vehicular jerk lead to higher likelihoods of involvement in SCEs. Further, driver behavior related factors such as aggressive driving and lane changing also increases the likelihood of involvement in SCEs. Driver distraction, as represented by the duration of secondary tasks, also increases the risk of SCEs. Likewise, traffic flow parameters play a critical role in safety risk. The risk of involvement in SCEs decreases under free flow traffic conditions and increases under unstable traffic flow. Further, the model shows prediction accuracy of 88.1 % and 85.7 % for training and validation data. These results have implications for proactive safety and providing in-vehicle warnings and alerts to prevent the occurrence of such SCEs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Late-time small body disruptions for planetary defense

Here, diverting hazardous small bodies on impact trajectories with the Earth can in some circumstances be impossible without risking disrupting them. Disruption is a much more difficult planetary defense scenario to assess, being linked both to the response of the body to shock loading and the much more complicated gravitational dynamics of the fragments in the solar system relative to pure deflection scenarios. In this work we present a new simulation suite built on N-body gravitational methods that solves fragment orbits in the full gravitational system without recourse to more approximate methods. We assess the accuracy of our simulations and the simplifying assumptions we adopt to make the system tractable, and then discuss in more detail several specific, plausible planetary defense scenarios based on real close encounters. We find that disruption can be a very effective planetary defense strategy even for very late (sub-year) interventions, and should be considered an effective backup strategy should preferred methods, which require long warning times, fail.

42 ENGINEERING↗
DOE OSTI2018

Sirt1 S-nitrosylation induces acetylation of HMGB1 in LPS-activated RAW264.7 cells and endotoxemic mice

Highlights: • S-nitrosylation of SIRT1 (SNO-SIRT1) by NO resulted in HMGB1 release in LPS-activated RAW264.7 cells. • The iNOS inhibitor (1400 W) and si-iNOS significantly inhibited SNO-SIRT1, which decreased the HMGB1 release by LPS. • The levels of SNO-SIRT were significantly increased in LPS-injected mice lung, which was inhibited by 1400 W treatment. • The SNO-SIRT1 under endotoxic conditions may uninhibit the acetylation of HMGB1 and its extracellular release. Excessive inflammation plays a detrimental role in endotoxemia. A recent study indicated that alarmins such as high mobility group box 1 (HMGB1) have drawn attention as therapeutic targets of sepsis. Post-translational modification (i.e., acetylation of lysine residues) of HMGB1 leads to the release of HMGB1 into the cellular space, operating as a warning signal that induces inflammation. Sirtuin 1 (SIRT1) has been shown to negatively regulate HMGB1 hyperacetylation and its extracellular release in sepsis. Therefore, we hypothesized that the S-nitrosylation (SNO) of SIRT1 may disrupt the ability of SIRT1 to negatively regulate the hyperacetylation of HMGB1. As long as the S-nitrosylation of SIRT1 occurs during septic conditions, it may worsen the situation. We found that the activity of SIRT1 decreased as the SNO-SIRT1 levels increased, resulting in HMGB1 release by LPS in RAW264.7 cells. Both the iNOS inhibitor (1400 W) and silencing iNOS significantly inhibited SNO-SIRT1, allowing increases in SIRT1 activity that decreased the HMGB1 release by LPS. SNAP, a NO donor, significantly increased both SNO-SIRT1 levels and the HMGB1 release that was accompanied by decreased sirt1 activity. However, sirtinol, a Sirt1 inhibitor, by itself decreased Sirt1 activity compared to that of the control, so that it did not affect already increased SNO-SIRT levels by SNAP. Most importantly, in lung tissues of LPS-endotoxic mice, significantly increased levels of SNO-SIRT were found, which was inhibited by 1400 W treatment. Plasma nitrite and HMGB1 levels were significantly higher than those in the sham controls, and the elevated levels were significantly lowered in the presence of 1400 W. We concluded that the S-nitrosylation of Sirt1 under endotoxic conditions may uninhibit the acetylation of HMGB1 and its extracellular release.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Out-of-distribution detection with non-parametric density estimation for models predicting processing history of uranium ore concentrates

The rapid advancement in machine learning (ML) and computer vision (CV) coincides with the growth of interest in deploying these ML/CV models in numerous fields from medicine to social science. Similar to those areas, we have witnessed a great number of works in materials science employing ML/CV models – neural networks in particular – in their studies in recent years. These models have proven to obtain accurate performance in various tasks. However, these models struggle to attain a similar performance when encountering test samples coming from a distribution that is different from the training set. More importantly, they fail without providing any warning to the users. Therefore, we propose a framework for detecting out-of-distribution (OOD) samples to alert users when a human intervention might be necessary in this work. Specifically, we explore the use of a non-parametric density estimation method to detect OOD samples. Here, we assess OOD detection capability of the proposed framework on ML models developed for categorizing precipitation routes of U 3 O 8 when encountering OOD datasets that contain samples (1) undergone different imaging acquisition process, (2) undergone different material synthesis process, and (3) different materials than ID set. Through those experiments, we achieve an average area under the receiver operating characteristic (AUROC) of at least 91% on average in detecting OOD samples. With minimal overhead cost and superior performance, the proposed framework enables a reliable and safe system when deploying in real-world scenarios.

Convolutional neural networks↗
DOE OSTI2021

Transcriptional and translational landscape of Candida auris in response to caspofungin

Candida auris has emerged as a serious worldwide threat by causing opportunistic infections that are frequently resistant to one or more conventional antifungal medications resulting in high mortality rates. Against this backdrop, health warnings around the world have focused efforts on understanding C. auris fungal biology and effective prevention and treatment approaches to combat this fungus. To date, there is little information about the differentially expressed genes when this fungus is treated with conventional antifungals, and caspofungin is a standard echinocandin deployed in the therapy against C. auris. In this work, we treated two distinct strains of C. auris for 24h with caspofungin, and the cellular responses were evaluated at the morphological, translational and transcriptional levels. We first observed that the echinocandin caused morphological alterations, aggregation of yeast cells, and modifications in the cell wall composition of C. auris. Transcriptomic analysis revealed an upregulation of genes related to the synthesis of the cell wall, ribosome, and cell cycle after exposure to caspofungin. Supporting these findings, the integrated proteomic analysis showed that caspofungin-treated cells were enriched in ribosome-related proteins and cell wall, especially mannoproteins. Altogether, these results provide further insights into the biology of C. auris and expands our understanding regarding the antifungal activity of caspofungin and reveal cellular targets, as the mannose metabolism, that can be further explored for the development of novel antifungals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Record-breaking 2020 summer marine heatwaves in the western North Pacific

Record-breaking marine heatwaves (MHWs) occurred in the western North Pacific during the summer of 2020. These unprecedented MHWs were consistent with favorable large-scale conditions that are linked to an anomalous western North Pacific subtropical high (WNPSH), resulting mainly from sea surface temperature (SST) anomalies across the tropical oceans. In addition, a moderate La Niña-like pattern was also conducive to transporting warm seawater to the western North Pacific. Mixed-layer heat budgets suggest that surface heat flux contributed to the SST anomaly in the western subtropical Pacific. In contrast, oceanic heat advection dominanted in the South China Sea and the western equatorial Pacific. Numerical model experiments indicated that the tropical Indian Ocean SST anomalies were responsible for the enhanced WNPSH. The increased zonal SST gradient across the tropical Pacific also played an important role. Inter-ocean interactions can modulate climate variability through ocean-atmospheric coupling and deserve more attention when predicting MHWs within the context of global warming. Additionally, it is critical to consider MHWs as a powerful tool in detecting acute, intense thermal stress events in the coral bleaching pre-warning system.

Coral bleaching↗
DOE OSTI2026

A hybrid CNN-LSTM surrogate model for hyper-resolution spatiotemporal flood forecasting in Norfolk, Virginia

Study region: Norfolk, Virginia, United States Study focus: Accurate and timely flood forecasting is essential for enhancing resilience in coastal urban areas in the context of increasing frequency and intensity of rainfall, sea level rise and urbanization. This study presents a hybrid deep learning-based surrogate model that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to enable real-time spatiotemporal flood forecasting. The model leverages CNN to capture spatial features from inputs such as elevation and Topographic Wetness Index (TWI), while LSTM processes time-series inputs of rainfall and tide data to capture temporal features. New hydrologic insights for the region: The hybrid CNN-LSTM model was trained using the physics-based hydrodynamic model simulations obtained from the Two-dimensional Unsteady FLOW (TUFLOW) model for Norfolk, Virginia, and achieved high predictive accuracy across diverse flood-prone areas. The reduced computational time from four to six hours using TUFLOW to 3.2 min per event using CNN-LSTM enables rapid flood inundation mapping and early warning applications. The model effectively captured both spatial flood extents and their temporal evolution across different flooding scenarios, providing forecasts at a 2.5-m spatial resolution and 15-min temporal resolution and a one-hour-ahead prediction horizon. While challenges remain in terms of transferability to new regions and real-time data assimilation, this approach demonstrates strong potential for supporting operational flood risk management in coastal urban environments.

Coastal urban flooding↗
DOE OSTI2018

ARC algorithm: A novel approach to forecast and manage daily electrical maximum demand

This paper proposes an innovative algorithm for predicting short-term electrical maximum demand by using historical demand data. The ability to recognize in peak demand pattern for commercial or industrial customers would propose numerous direct and indirect benefits to the customers and utility providers in terms of demand reduction, cost control, and system stability. Prior works in electrical maximum demand forecasting have been mainly focused on seasonal effects, which is not a feasible approach for industrial manufacturing facilities in short-term load forecasting. The proposed algorithm, denoted as the Adaptive Rate of Change (ARC), determines the logarithmic rate-of-change in load profile prior to a peak by postulating the demand curve as a stochastic, mean-reverting process. The rationale behind this analysis, is that the energy efficient program requires not only demand estimation but also to warn the user of imminent maximum peak occurrence. This paper analyzes demand trend data and incorporates stochastic model and mean reverting half-life to develop an electrical maximum demand forecasting algorithm, which is statistically evaluated by cross-table and F-score for three different manufacturing facilities. Lastly, the aggregate results show an overall accuracy of 0.91 and a F-score of 0.43, which indicates that the algorithm is effective predicting peak demand in predicting peak demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

A game theory approach for assessing risk value and deploying search-and-rescue resources after devastating tsunamis

Highlights: • Two game theoretic models are designed for search-and-rescue resource allocation. • A simulation based upon 2011 Japan tsunami data. • Shapley value division is more efficient than the proportional division. The current early-warning system and tsunami protection measures tend to fall short because they always underestimate the level of destruction, and it is difficult to predict the level of damage by a devastating tsunami on uncertain targets. As we know, the key to minimizing the total number of fatalities after a disaster is the deployment of search and rescue efforts in the first few hours. However, the resources available to the affected districts for emergency response may be limited. This study proposes two game theoretic models that are designed for search-and-rescue resource allocation. First, the interactions between a compounded disaster and a response agent in the affected district are modelled as a non-cooperative game, after which the risk value is derived for each district from the Nash equilibrium. The risk value represents the threat, vulnerability, and consequence of a specific disaster for the affected district. Second, the risk values for fifteen districts are collected for calculation of each district's Shapley value. Then an acceptable plan for resource deployment among all districts is made based on their expected marginal contribution. The model is verified in a simulation based upon 2011 tsunami data. The experimental results show the proposed approach to be more efficient than the proportional division of rescue resources, for dealing with compounded disaster, and is feasible as a method for planning the mobilization of resources and to improve relief efforts against devastating tsunamis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

The human skin as a sub-THz receiver – Does 5G pose a danger to it or not?

Highlights: • The sweat duct is regarded as a helical antenna in the sub-THz band, reflectance depends on perspiration. • We outline the background for non-thermal effects based on the structure of sweat ducts. • We have introduced a realistic skin EM model and found the expected SAR for the 5G standard. In the interaction of microwave radiation and human beings, the skin is traditionally considered as just an absorbing sponge stratum filled with water. In previous works, we showed that this view is flawed when we demonstrated that the coiled portion of the sweat duct in upper skin layer is regarded as a helical antenna in the sub-THz band. Experimentally we showed that the reflectance of the human skin in the sub-THz region depends on the intensity of perspiration, i.e. sweat duct's conductivity, and correlates with levels of human stress (physical, mental and emotional). Later on, we detected circular dichroism in the reflectance from the skin, a signature of the axial mode of a helical antenna. The full ramifications of what these findings represent in the human condition are still unclear. We also revealed correlation of electrocardiography (ECG) parameters to the sub-THz reflection coefficient of human skin. In a recent work, we developed a unique simulation tool of human skin, taking into account the skin multi-layer structure together with the helical segment of the sweat duct embedded in it. The presence of the sweat duct led to a high specific absorption rate (SAR) of the skin in extremely high frequency band. In this paper, we summarize the physical evidence for this phenomenon and consider its implication for the future exploitation of the electromagnetic spectrum by wireless communication. Starting from July 2016 the US Federal Communications Commission (FCC) has adopted new rules for wireless broadband operations above 24 GHz (5 G). This trend of exploitation is predicted to expand to higher frequencies in the sub-THz region. One must consider the implications of human immersion in the electromagnetic noise, caused by devices working at the very same frequencies as those, to which the sweat duct (as a helical antenna) is most attuned. We are raising a warning flag against the unrestricted use of sub-THz technologies for communication, before the possible consequences for public health are explored.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2018

Spatio-temporal variation of trematode parasites community in Cerastoderma edule cockles from Ria de Aveiro (Portugal)

Highlights: • Trematode communities from the Ria de Aveiro are characterized by low abundance. • Trematode communities showed to be spatially homogenous and showed no seasonal pattern. • Interannual differences in trematode parasite community structure were detected. • Trematode communities can be used as early warning indicators of global changes. • Effective use of trematodes to assess ecosystem's deteriorating conditions. Cerastoderma edule (edible cockle) is among the most exploited bivalves in Europe playing an important socio-economic role. Cockles live in estuaries and lagoons where their population is controlled by several environmental factors including parasitism. Parasites represent an important part of the world known biodiversity but are often neglected. Trematodes are the most prevalent macroparasites of cockles being able to exert an impact both at the individual and population levels. Therefore, it is of prime relevance to recognize and understand the parasite-host system dynamics in order to better predict potential conservation threats to bivalve populations and to maximize the success of stock and disease episodes management. Cockle monitoring was conducted in 2012 and 2016, in six and eight stations, respectively, at the Ria de Aveiro coastal lagoon, Portugal. Cockles were sampled in one single occasion in 2012 and seasonally in 2016. The tested hypothesis is that the trematode community in cockles was spatially and seasonally heterogeneous but stable over time. The main result showed that despite a relative homogeneity of the parasite community structure in cockles, the among-years heterogeneity of trematode communities was higher than among-stations and among-seasons heterogeneity rejecting the postulated hypothesis. Results demonstrated that trematode communities from the Ria de Aveiro are characterized by low abundance, which resulted in a spatial and seasonal trematode homogeneity (despite an overall channel difference and a slight downstream-upstream gradient). The interannual analysis showed a worrisome loss of trematode diversity and prevalence which consequently indicates an important loss of overall diversity and/or environmental conditions reflecting the negative effects of global change (mean temperature rise and overharvesting, among others). The present study highlighted the importance of trematodes in characterising their associated environment and respective biodiversity which might be helpful to assess ecosystem ecological status and to identify threatened areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Toxics (Pb, Cd) and trace elements (Zn, Cu, Mn) in women during pregnancy and at delivery, South Benin, 2014–2015

Highlights: • Lack of data on maternal exposure to toxic and trace elements in Africa. • Longitudinal blood measurements of Pb, Cd, Zn, Cu and Mn during pregnancy in Benin. • Evidence of maternal exposure to Pb and Cd. • Identification of potential sources for Pb exposure during pregnancy. During pregnancy, fetal development can be hindered by maternal exposure to toxic elements and abnormal concentrations of trace elements. Few data are available in African countries. Our goal was to assess the body burden of lead (Pb), cadmium (Cd), manganese (Mn), zinc (Zn) and copper (Cu) in pregnant women in Benin. The study was carried out in Sô-Ava district, from November 2015 to April 2016. Sixty women were recruited from the RECIPAL pre-conceptional cohort study. In all women, blood samples were collected during the first trimester of pregnancy. Thirty-two women had additional maternal and cord blood samples collected at delivery. Blood samples were analyzed by inductively coupled plasma mass spectrometry. At delivery, Cd median (IQR) concentration in maternal blood was 0.34 µg/L (0.24–0.46) in this non-smoking population. Pb median (IQR) concentration in maternal blood at delivery was 37.4 µg/L (30.5–52.0), with 31.3% of blood Pb levels above the 50 μg/L threshold. These pregnant women lived in semi-rural lakeside villages. Potential sources of Pb exposure identified during pregnancy were having water supply by drill pump and activities such as smoking fish by the woman and fishing by the household head. At delivery, Zn, Cu, and Mn median (IQR) concentrations in maternal blood were, respectively, 5415 μg/L (4894–5822), 1609 μg/L (1295–1771) and 16.0 μg/L (12.5–20.8). Pb, Cd, Mn and Cu blood concentrations were significantly higher at delivery than during the first trimester of pregnancy. Pb, Cd, Zn and Cu concentrations were significantly lower in cord blood than in maternal blood, contrary to Mn concentration, which was significantly higher in cord blood than in maternal blood at delivery. This exploratory study is the first one performed in Benin, and warns us about exposition of women from Sô-Ava district to Pb and Cd during pregnancy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Certification and prediction of post-disturbance states in dynamic security assessment

Dynamic security assessment usually involves the simulation of system dynamics under large disturbances. The instant large disturbance occurs, the post-disturbance state of the system could deviate significantly from the pre-disturbance one. It is desirable and necessary to develop an efficient method to certify the existence of state and predict the approximate post-disturbance state because: (1) faster warning can be made in online assessment; and (2) the dynamic simulator can be given better initial values to calculate precise solutions, which prevents convergence failure brought on by poor initial values. We propose a novel approach for efficiently certifying and predicting the post-disturbance states in dynamic security assessment. Based on the fixed-point power flow mapping approach applied to salient pole generator models, the criterion for determining the existence and uniqueness of the post-disturbance solution is derived, and the bounds of post-disturbance solution can be rigorously characterized.

24 POWER TRANSMISSION AND DISTRIBUTION↗