Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “warning”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Standardized perioperative management in acute abdominal surgery: Swedish SMASH controlled study

Abstract Background Acute high-risk abdominal surgery is common, as are the attendant risks of organ failure, need for intensive care, mortality, or long hospital stay. This study assessed the implementation of standardized management. Methods A prospective study of all adults undergoing emergency laparotomy over an interval of 42 months (2018–2021) was undertaken; outcomes were compared with those of a retrospective control group. A new standardized clinical protocol was activated for all patients including: prompt bedside physical assessment by the surgeon and anaesthetist, interprofessional communication regarding location of resuscitation, elimination of unnecessary factors that might delay surgery, improved operating theatre competence, regular epidural, enhanced recovery care, and frequent early warning scores. The primary endpoint was 30-day mortality. Secondary endpoints were duration of hospital stay, need for intensive care, and surgical complications. Results A total of 1344 patients were included, 663 in the control group and 681 in the intervention group. The use of antibiotics increased (81.4 versus 94.7 per cent), and the time from the decision to operate to the start of surgery was reduced (3.80 versus 3.22 h) with use of the new protocol. Fewer anastomoses were performed (22.5 versus 16.8 per cent). The 30-day mortality rate was 14.5 per cent in the historical control group and 10.7 per cent in the intervention group (P = 0.045). The mean duration of hospital (11.9 versus 10.2 days; P = 0.007) and ICU (5.40 versus 3.12 days; P = 0.007) stays was also reduced. The rate of serious surgical complications (grade IIIb–V) was lower (37.6 versus 27.3 per cent; P = <0.001). Conclusion Standardized management protocols improved outcomes after emergency laparotomy.

Timan, Terje J.↗
DOE OSTI2023

Population Aging and Heat Exposure in the 21st Century: Which U.S. Regions Are at Greatest Risk and Why?

Abstract Background and Objectives The co-occurring trends of population aging and climate change mean that rising numbers of U.S. older adults are at risk of intensifying heat exposure. We estimate county-level variations in older populations’ heat exposure in the early (1995–2014) and mid (2050) 21st century. We identify the extent to which rising exposures are attributable to climate change versus population aging. Research Design and Methods We estimate older adults’ heat exposure in 3,109 counties in the 48 contiguous U.S. states. Analyses use NASA NEX Global Daily Downscaled Product (NEX-GDDP-CMIP6) climate data and county-level projections for the size and distribution of the U.S. age 69+ population. Results Population aging and rising temperatures are documented throughout the United States, with particular “hotspots” in the Deep South, Florida, and parts of the rural Midwest. Increases in heat exposure by 2050 will be especially steep in historically colder regions with large older populations in New England, the upper Midwest, and rural Mountain regions. Rising temperatures are driving exposure in historically colder regions, whereas population aging is driving exposure in historically warm southern regions. Discussion and Implications Interventions to address the impacts of temperature extremes on older adult well-being should consider the geographic distribution and drivers of this exposure. In historically cooler areas where climate change is driving exposures, investments in warning systems may be productive, whereas investments in health care and social services infrastructures are essential in historically hot regions where exposures are driven by population aging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Red supergiant candidates for multimessenger monitoring of the next Galactic supernova

ABSTRACT We compile a catalogue of 578 highly probable and 62 likely red supergiants (RSGs) of the Milky Way, which represents the largest list of Galactic RSG candidates designed for continuous follow-up efforts to date. We match distances measured by Gaia DR3, 2MASS photometry, and a 3D Galactic dust map to obtain luminous bright late-type stars. Determining the stars’ bolometric luminosities and effective temperatures, we compare to Geneva stellar evolution tracks to determine likely RSG candidates, and quantify contamination using a catalogue of Galactic AGB in the same luminosity-temperature space. We add details for common or interesting characteristics of RSG, such as multistar system membership, variability, and classification as a runaway. As potential future core-collapse supernova progenitors, we study the ability of the catalogue to inform the Supernova Early Warning System (SNEWS) coincidence network made to automate pointing, and show that for 3D position estimates made possible by neutrinos, the number of progenitor candidates can be significantly reduced, improving our ability to observe the progenitor pre-explosion and the early phases of core-collapse supernovae.

Astronomy & Astrophysics↗
DOE OSTI2023

Global variations in critical drought thresholds that impact vegetation

ABSTRACT Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001–2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Real-Time Series Resistance Monitoring in PV Systems Without the Need for I-V Curves

We apply the physical principles of a familiar method, suns-V oc , to a new application: the real-time detection of series resistance changes in modules and systems operating outside. The real-time series resistance (RTSR) method that we describe avoids the need for collecting I-V curves or constructing full series resistance-free I-V curves. RTSR is most readily deployable at the module level on microinverters or module-integrated electronics, but it can also be extended to full strings. We found that automated detection of series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We also describe the method in detail and describe a sample application to data collected from modules operating in the field.

14 SOLAR ENERGY↗
DOE OSTI2019

Continuous Data Acquisition for Liquid Argon Time Projection Chamber Neutrino Detectors Using FPGA-Based Real-Time Compression Algorithms

Liquid argon time projection chambers (LArTPCs) have been proposed as neutrino detectors that combine both large sizes to maximize the number of neutrino interactions and detailed recording of the interaction. The readout of thousands of channels at MHz sampling rates produce images of the neutrino-nucleus interaction with millimeter-scale resolution, enabling the identification of the resulting particles and offering multiple handles to measure their energies at the expense of large data rates. Continuous acquisition of the LArTPC data is required to enable the use of high-latency triggers for capturing non-accelerator-beam events. We describe the case of the continuous readout of the MicroBooNE LArTPC, that grants the possibility of acquiring the neutrino burst from a supernova using the SNEWS (Supernova Early Warning System) alert as delayed trigger. The continuous data acquisition is accomplished by using real-time compression algorithms (zero suppression and Huffman compression) implemented in an FPGA in the readout electronics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

An Experimental Setup for Mechanical Vibration Analysis Using VLC

This study explores the potential applications across various domains, including earthquake detection and warning systems, where the system’s sensitivity to ground vibrations can contribute to early seismic event detection. Additionally, the study paves the way of developing applications of VLC/T in mechanical vibration and stability analysis of engines and platforms, offering insights into structural integrity and performance optimization. These multifaceted applications underscore the adaptability and potential of VLC/T systems in diverse fields, heralding advancements in sensing, communication, and security technologies. To achieve this, in this study, Peak to Average Power Ratio (PAPR) is proposed to represent the impact of mechanical shocks and vibrations generated by several weights dropped onto the platform with which the receiver is fixed. Even though non-contact measurement methodology is preferred for various reasons, the proposed measurement campaign obtains the data in contact form; however, the system and signal model proposed in this study could easily be extended into non-contact form. Considering the fact that the proposed measurement campaign employs off-the-shelf products, it is cost-effective and very scalable.

Yilmaz, Ahmet Mucahit↗
DOE OSTI2021

Remote Monitoring and Diagnostics of Pitch-Bearing Defects in an MW-Scale Wind Turbine Using Pitch Symmetrical-Component Analysis

Recently, multiple wind turbine failure databases have reviewed that the pitch system is one of the subassemblies with the highest failure rates and largest contributors to the overall downtime. Therefore, there has been an increasing interest to provide remote health monitoring for wind turbine pitch system. While most of the research articles are discussing pitch actuation system (hydraulic or electric actuator) faults only, there is very limited research on pitch-bearing-defect detection. This article provides a remote and hardware-free solution to monitor multiaxis pitch-bearing health condition called pitch symmetrical-component analysis. It leverages readily available low-resolution (100 Hz) electrical measurements, mechanical measurements, and control signals from the existing pitch control platform, and innovatively applies symmetrical-component analysis in multiphase ac system to multiaxis pitch control system and introduces multiaxis pitch-bearing degradation trending curves. This hardware-free solution can be directly applied to the existing wind turbines and successfully give the wind farm operator an early warning before multiaxis pitch bearing fails. It has been proved to be accurate, low cost, and has minimum impacts on turbine normal operation, and has been validated by field data from several North America MW-scale wind farms. This approach turns out to be the first hardware-free (no additional hardware needed) method to remotely monitor and diagnose multiaxis wind turbine pitch-bearing condition.

17 WIND ENERGY↗
DOE OSTI2015

Exploiting Redundancy and Application Scalability for Cost-Effective, Time-Constrained Execution of HPC Applications on Amazon EC2

The use of clouds to execute high-performance computing (HPC) applications has greatly increased recently. Clouds provide several potential advantages over traditional supercomputers and in-house clusters. The most popular cloud is currently Amazon EC2, which provides fixed-cost and variable-cost, auction-based options. The auction market trades lower cost for potential interruptions that necessitate checkpointing; if the market price exceeds the bid price, a node is taken away from the user without warning. We explore techniques to maximize performance per dollar given a time constraint within which an application must complete. Specifically, we design and implement multiple techniques to reduce expected cost by exploiting redundancy in the EC2 auction market. We then design an adaptive algorithm that selects a scheduling algorithm and determines the bid price. We show that our adaptive algorithm executes programs up to seven times cheaper than using the on-demand market and up to 44 percent cheaper than the best non-redundant, auction-market algorithm. We extend our adaptive algorithm to incorporate application scalability characteristics for further cost savings. In conclusion, we show that the adaptive algorithm informed with scalability characteristics of applications achieves up to 56 percent cost savings compared to the expected cost for the base adaptive algorithm run at a fixed, user-defined scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Exploring Properties and Correlations of Fatal Events in a Large-Scale HPC System

In this study, we explore potential correlations of fatal system events for one of the most powerful supercomputers-IBM Blue Gene/Q Mira, which is deployed at Argonne National Laboratory, based on its 5-year reliability, availability, and serviceability (RAS) log. Our contribution is two-fold. (1) We design an efficient log analysis tool, namely LogAider, with a novel filtering method to effectively extract fatal events from masses of system messages that are heavily duplicated in the log. LogAider exhibits a very precise detection of temporal-correlation with a high similarity (up to 95 percent) to the ground-truth (i.e., compared to the failure records reported by the administrators). The total number of fatal events can be reduced to about 1,255 compared with originally 2.6 million duplicated fatal messages. (2) We analyze the 5-year RAS log of the MIRA system using LogAider, and summarize six important "takeaways" which can help system vendors and administrators better understand an extreme-scale system's fatal events. Specifically, we find that the distribution or proportion of the fatal system events follow a Pareto-like principle in general. The temporal correlation among fatal events is much stronger than that of warn messages and info messages, and the correlated events tend to constitute a few clusters. The mean time between fatal events (MTBFE) of the Mira system is about 1.3 days from the perspective of the system, and the MTTI is 2-4 days from the perspective of users. The most error-prone item value with respect to any key attribute appears likely in the log every 2-10 days. Weibull, Gamma, and Pearson6 are the three best-fit distributions for the fatal event intervals. The overall correlation of fatal events on the 5D torus network is not prominent, whereas the small-region locality correlation (e.g., the fatal events inside racks) is relatively strong. We believe our work will be interesting to large-scale HPC system administrators and vendors and to fault tolerance researchers, enabling them to better understand fatal events and mitigate such events accordingly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Design of the Electromagnetic Particle Injector (EPI) for Tokamak Deployment

Both predicting and controlling disruptions are critical and urgent issues for ITER as some disruptions with a short warning time may be unavoidable. For these cases, a rapid response disruption mitigation system (DMS) referred to as the electromagnetic particle injector (EPI) is being developed. The primary advantages of the EPI are its fast response time and high velocity, which have been demonstrated in offline experiments (Raman et al., 2021). The EPI is capable of accelerating a metallic sabot electromagnetically using a rail gun to the required velocities ( > 2 km/s) within 2 ms. Two high-field racetrack magnets able to generate fields over 2 T are positioned above and below the rails to permit high velocity at low rail currents, a requirement to minimize electrode erosion. At the end of the acceleration phase, a sabot capture mechanism retains the spent sabot inside the vacuum chamber that houses the EPI. At this point, it releases well-defined microspheres, or a shell pellet, of a radiative payload into the disrupting plasma. A remotely operated sabot loading system positioned behind the injector contains several pre-equipped sabots that can be loaded by an operator from the tokamak control room. The injector is interfaced to the tokamak through a guide tube attached to the front of the EPI vacuum chamber. Finally, the advantages of the EPI system over other DMSs under consideration are described in conjunction with the details of an EPI system designed for near-term test on an existing large tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Agent-Based Simulation Framework for Multi-Variant Surveillance

Early detection of an emerging VOC (Variant-Of-Concern) is essential for effective preparedness for a disease like COVID-19. The spreading of an emerging VOC not only depends on the disease dynamics of itself but also depends on the state of the circulating variants and the susceptibility of the population. Resources for testing are typically quite limited, and a number of strategies have been considered for deploying them. However, it has been difficult to evaluate the performance of such strategies, especially higher order effects, and inequities, while incorporating constraints on these resources. Here, we develop an agent-based surveillance framework, Networkdetect, to understand the early warning system of an emerging VOC. Our framework allows us to incorporate various population heterogeneities and resource constraints.

Moon, Sifat [ORNL] (ORCID:0000000344968809)↗
DOE OSTI2023

Mixotrophic microbes create carbon tipping points under warming

Mixotrophs are ubiquitous and integral to microbial food webs, but their impacts on the dynamics and functioning of broader ecosystems are largely unresolved. Here, we show that mixotrophy produces a unique type of food web module that exhibits unusual ecological dynamics, with surprising consequences for carbon flux under warming. We develop a generalizable model of a mixotrophic food web module that incorporates dynamic switching between phototrophy and phagotrophy to assess ecological dynamics and total system CO 2 flux. We find that warming switches mixotrophic systems between alternative stable carbon states—including a phototrophy-dominant carbon sink state, a phagotrophy-dominant carbon source state and cycling between these two. Moreover, warming always shifts this mixotrophic system from a carbon sink state to a carbon source state, but a coordinated increase in nutrients can erase early warning signals of this transition and expand hysteresis. This suggests that mixotrophs can generate critical carbon tipping points under warming that will be more abrupt and less reversible when combined with increased nutrient levels, having widespread implications for ecosystem functioning in the face of rapid global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Enhancement of microbiome management by machine learning for biological wastewater treatment

Here we propose to develop microbiome-based machine learning models to predict the response of biological wastewater treatment systems to environmental or operational disturbances or to design specific microbiomes to achieve a desired system function. These machine learning models can be used to enhance the stability of microbiome-based biological systems and warn against the failure of these systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Review article: therapeutic bile acids and the risks for hepatotoxicity

Summary Background Bile acids play important roles in cholesterol metabolism and signal through farnesoid X receptor and G protein‐coupled receptors. Given their importance in liver biology, bile acid therapy enables therapeutic applications beyond the treatment of cholestatic liver disease. However, predicting hepatotoxicity of bile acids in humans is obscured due to inconsistent extrapolations of animal data to humans. Aim To review the evidence that could explain discordant bile acids hepatotoxicity observed in humans and animals. Method Literature search was conducted in PubMed using keywords “bile acid,” “transporter,” “hepatotoxicity,” “clinical study,” “animal study,” “species difference,” “mechanism,” “genetic disorder.” Relevant articles were selected for review. Results Clinically significant hepatotoxicity was reported in response to certain bile acids, namely chenodeoxycholic acid, which was given a boxed warning for potential hepatotoxicity. The chemical structure, specifically the number and orientation of hydroxyl groups, significantly affects their hydrophobicity, an important factor in bile acid toxicity. Experimental studies show that hydrophobic bile acids can lead to liver injury through various mechanisms, such as death receptor signalling, mitochondrial dysfunction and inflammation. Although animal studies play a central role in investigating bile acid safety, there are considerable differences in bile acid composition, metabolism and hepatobiliary disposition across species. This does not allow appropriate safety inference, especially for predicting hepatotoxicity in humans. Exploring evidences stemming from inborn errors, genetic models of disease and toxicology studies further improves an understanding of bile acid hepatotoxicity. Conclusion Species differences should be considered in the development of bile acid related therapeutics. Although the mechanism of bile acid hepatotoxicity is still not fully understood, continued mechanistic studies will deepen our understanding.

Ashby, K.↗
DOE OSTI2022

Temperature optimum for marsh resilience and carbon accumulation revealed in a whole ecosystem warming experiment

Coastal marshes are globally important, carbon dense ecosystems simultaneously maintained and threatened by sea-level rise. Warming temperatures may increase wetland plant productivity and organic matter accumulation, but temperature-modulated feedbacks between productivity and decomposition make it difficult to assess how wetlands and their thick, organic rich soils will respond to climate warming. Here, we actively increased aboveground plant-surface and below-ground soil temperatures in two marsh plant communities, and found that a moderate amount of warming (1.7°C above ambient temperatures) consistently maximized root growth, marsh elevation gain, and below-ground carbon accumulation. Marsh elevation loss observed at higher temperatures was associated with increased carbon mineralization and increased microtopographic heterogeneity, a potential early warning signal of marsh drowning. Here, maximized elevation and below-ground carbon accumulation for moderate warming scenarios uniquely suggest linkages between metabolic theory of individuals and landscape-scale ecosystem resilience and function, but our work indicates nonpermanent benefits as global temperatures continue to rise.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Transcriptomic analysis of skin pigmentation variation in the Virginia opossum ( Didelphis virginiana )

Abstract Skin pigmentation and coat pigmentation are two of the best‐studied examples of traits under natural selection given their quantifiable fitness interactions with the environment (e.g., camouflage) and signalling with other organisms (e.g., warning coloration). Previous morphological studies have found that skin pigmentation variation in the Virginia opossum ( Didelphis virginiana ) is associated with variation in precipitation and temperatures across its distribution range following Gloger's rule (lighter pigmentation in temperate environments). To investigate the molecular mechanism associated with skin pigmentation variation, we used RNA‐Seq and quantified gene expression of wild opossums from tropical and temperate populations. Using differential expression analysis and a co‐expression network approach, we found that expression variation in genes with melanocytic and immune functions is significantly associated with the degree of skin pigmentation variation and may be underlying this phenotypic difference. We also found evidence suggesting that the Wnt/β‐catenin signalling pathway might be regulating the depigmentation observed in temperate populations. Based on our study results, we present several alternative hypotheses that may explain Gloger's rule pattern of skin pigmentation variation in opossum, including changes in pathogen diversity supporting a pathogen‐resistant hypothesis, thermal stress associated with temperate environments, and pleiotropic and epistatic interactions between melanocytic and immune genes.

Nigenda‐Morales, Sergio F.↗
DOE OSTI2024

Enhancing risk and crisis communication with computational methods: A systematic literature review

Abstract Recent developments in risk and crisis communication (RCC) research combine social science theory and data science tools to construct effective risk messages efficiently. However, current systematic literature reviews (SLRs) on RCC primarily focus on computationally assessing message efficacy as opposed to message efficiency. We conduct an SLR to highlight any current computational methods that improve message construction efficacy and efficiency. We found that most RCC research focuses on using theoretical frameworks and computational methods to analyze or classify message elements that improve efficacy. For improving message efficiency, computational and manual methods are only used in message classification. Specifying the computational methods used in message construction is sparse. We recommend that future RCC research apply computational methods toward improving efficacy and efficiency in message construction. By improving message construction efficacy and efficiency, RCC messaging would quickly warn and better inform affected communities impacted by current hazards. Such messaging has the potential to save as many lives as possible.

Mathematical Methods In Social Sciences↗