Multiple Surges Research Articles

Incipient instability real-time warning via adaptive wavelet synchrosqueezed transform: Onboard applications from compressors to gas turbine engines

To address the limitations of existing stall/surge warning methods—including variations in research subjects, sensor configurations, computational complexity, and the universality of thresholds—this study proposes a novel incipient instability warning approach utilizing adaptive wavelet synchrosqueezed transform. Each detection cycle begins with the acquisition of a low-pass filtered and downsampled total pressure signal from the compressor outlet, captured via a sliding window to represent the pressure sample. Then, the adaptive wavelet synchrosqueezed transform (AWSST), employing dynamic discretization with scales and synchrosqueezing technology, analyzes the real-time pressure sample to extract precise instantaneous frequency changes at low computational costs. Features of instability severity are derived from the amplitude, phase, and pressure drop within the time-frequency spectrum, leading to the formulation of a warning logic. The proposed method's effectiveness and universality are validated through hardware-in-loop (HIL) tests using multiple surge test data. Results show that the proposed method outperforms traditional real-time warning methods, which rely on the pressure change rate, by enhancing accuracy and advancing warning times by 15 ms–50 ms. Notably, the threshold is universal for compressors or engines of the same model. By increasing the acceptable performance decline criteria, compressors, turbofan engines, and turboshaft engines can employ a common set of thresholds.

Debris‐flow entrainment modelling under climate change: Considering antecedent moisture conditions along the flow path

AbstractDebris‐flow volumes can increase along their flow path by entraining sediment stored in the channel bed and banks, thus also increasing hazard potential. Theoretical considerations, laboratory experiments and field investigations all indicate that the saturation conditions of the sediment along the flow path can greatly influence the amount of sediment entrained. However, this process is usually not considered for practical applications. This study aims to close this gap by combining runout and hydrological models into a predictive framework that is calibrated and tested using unique observations of sediment erosion and debris‐flow properties available at a Swiss debris‐flow observation station (Illgraben). To this end, hourly water input to the erodible channel is predicted using a simple, process‐based hydrological model, and the resulting water saturation level in the upper sediment layer of the channel is modelled based on a Hortonian infiltration concept. Debris‐flow entrainment is then predicted using the RAMMS debris‐flow runout model. We find a strong correlation between the modelled saturation level of the sediment on the flow path and the channel‐bed erodibility for single‐surge debris‐flow events with distinct fronts, indicating that the modelled water content is a good predictor for erosion simulated in RAMMS. Debris‐flow properties with more complex flow behaviour (e.g., multiple surges or roll waves) are not as well predicted using this procedure, indicating that more physically complete models are necessary. Finally, we demonstrate how this modelling framework can be used for climate change impact assessment and show that earlier snowmelt may shift the peak of the debris‐flow season to earlier in the year. Our novel modelling framework provides a plausible approach to reproduce saturation‐dependent entrainment and thus better constrain event volumes for current and future hazard assessment.

Real-scale measurements of debris-flow run-ups

Rapid mass movements, such as debris flows, endanger alpine areas due to their destructive nature. In order to counteract these dangerous flows, it is necessary to design appropriate mitigation measures. A particular problem is the run-up of debris flows that impact on such structures. We provide in situ measurements of the run-up of three natural debrnis flows, each with multiple surges, in Gadria Creek, resulting from interaction with a mid-channel structure monitoring station. Four models were checked against data from other studies and the in situ measurements of the natural debris flows. The natural debris-flow measurements are all located in low Froude areas (Fr < 3) typical of Alpine granular debris flows. Sediment-laden pre-surges with Froude values greater than 2 produced the largest run-up factors in terms of run-up heights standardized to flow heights. Nevertheless, ensuing debris-flow surges exhibited a notable granular behavior and occurred at low Froude values. The findings indicate that the use of an energy conservation-based prediction model yields the most accurate estimates of the observed run-up factors. However, this smooth, gradual run-up can also be enhanced by preceding debris deposition and the formation of ramps. This can also prevent the formation of a reflection or shock wave, as assumed in models based on conservation of mass and momentum. These models have mainly overestimated the run-up factors of the observed debris flows.

Long-term impact of the COVID-19 pandemic on self-management of chronic conditions among high-risk adults in the USA: protocol for the C3 observational cohort study

IntroductionCOVID-19 is an unprecedented public health threat in modern times, especially for older adults or those with chronic illness. Beyond the threat of infection, the pandemic may also have longer-term...

A Surge/Stall-Capable Dynamic Performance Simulation Methodology for a Turbojet Engine

Abstract A lumped-parameter dynamic performance model for a single-spool turbojet engine is presented in this paper. This model can handle pre and poststall transients under forward and reverse-flow conditions. The inter-component volume technique is employed instead of the standard matching technique to be able to handle high-frequency transients and reverse-flow conditions. Inspired by Greitzer's lumped-parameter surge model, momentum (duct) and volume elements are placed within the flow path to handle surge dynamics. Compressor and turbine maps are extended to low-flow and reverse-flow regions using a combination of the guidelines presented by Kurzke, the cubic axisymmetric characteristics of Moore and Greitzer, and a quadratic function guess for in-stall characteristics. Combustor efficiency, stability limits, and delay are taken from the literature. Poststall behavior of the model is validated using the data available in the literature for a Rolls-Royce Viper engine. A good match is observed with a correct prediction of poststall behaviors, which transition from surge after locked stall to multiple surge cycles around 80% speed and multiple surge cycles to surge after flameout around 95% speed. The effects of different modeling choices and modeling parameters on the obtained results are discussed. The produced model can be calibrated for a specific engine with surge tests, and it can be used for hard-to-test scenarios like surge after shaft breakage. Different surge/stall-causing events, such as fuel spiking, in-bleeding, and shaft breakage, are simulated to see the capabilities of the model.

A Perspective of Surge Dynamics in Natural Debris Flows Through Pulse‐Doppler Radar Observations

AbstractAs a consequence of their natural occurrence and the frequent formation of multiple surges with high sediment loads, debris flows are considered one of the most hazardous gravity‐driven mass movements in mountain regions. Field measurements of surge dynamics are an essential link in the chain of understanding fundamental process dynamics and engineering protection against debris flows. However, continuous information on the velocities of multiple consecutive surges within a single debris‐flow event with high temporal resolution is rare. In this study, we present a new pulse‐Doppler radar (PD radar) for high‐resolution real‐time debris‐flow monitoring. We analyze PD radar data sets over a torrent length of 250 m for two debris flows that occurred at the Gadria creek (IT), on 26 July 2019 and 10 August 2020. The radar data were validated with independently derived data from particle image velocimetry and manually tracked velocities. We observe that between surges, the flow frequently comes to a complete halt and is re‐mobilized by subsequent surges, resembling erosion‐deposition waves in granular flows. In addition, our data confirm that surges can superimpose and merge. We anticipate that the outcomes of this work serve as a blueprint for future high‐resolution observations of debris‐flow surge dynamics with PD radar and that our findings provide new insights into the physical principles of natural debris flows.

Genomic Surveillance of SARS-CoV-2 in Malaysia during the Era of Endemic COVID-19.

On 5 May 2023, WHO declared the end of coronavirus disease 2019 (COVID-19) as a public health emergency of international concern. However, the risk of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants causing rapid and high surges in cases and deaths remained. In Malaysia, five COVID-19 waves during the pandemic phase were well characterized, but similar studies focusing on the endemic phase were lacking. Hence, we retrieved 14,965 SARS-CoV-2 genomic sequences from the GISAID EpiCoV database for clade, lineage, and phylogenetic analysis in order to provide an insight into the population dynamics of SARS-CoV-2 that circulated in Malaysia from June 2022 to April 2023. The dominance of the Omicron variants was observed, and two new waves of infections driven by BA.5.2 and XBB.1, respectively, were detected. Data as of April 2023 also pointed to a possible eighth wave driven by XBB.1.9. Although new variants associated with higher transmissibility were behind the multiple surges, these subsequent waves had lower intensities as compared to the fourth and fifth waves. The on-going circulation and evolution of SARS-CoV-2 mean that COVID-19 still poses a serious threat, necessitating active genomic surveillance for early warning of potential new variants of concern.

Characterization of Three Surges of the Kyagar Glacier, Karakoram

Glaciers experience periodic variations in flow velocity called surges, each of which influences the glacier’s characteristics and the occurrence of downstream disasters (e.g., ice-dammed lake outburst floods). The Karakoram region contains many surging glaciers, yet there are few comprehensive studies of multiple surge cycles. In this work, Landsat, topographic map, Shuttle Radar Topography Mission (SRTM), TerraSAR-X/TanDEM-X, ITS_LIVE, and Sentinel-1 glacier velocity data were used to systematically analyze the characteristics of Kyagar Glacier since the 1970s. Three surging events were identified, with active phases in 1975–1978, 1995–1997, and 2014–2016. The timing of these surges was similar, with a cycle of 19–20 years, an active phase of 3–4 years, and a quiescent phase of 16–17 years. During the quiescent phase, a large amount of ice accumulates in the lower part of the accumulation zone, and the terminal of the tongue thins significantly. According to the most recent surge event (2014–2016), glacier flow accelerated suddenly in the active phase and reached a maximum velocity of 2 ± 0.08 m d−1. Then, the glacier terminal thickened sharply, the reservoir zone thinned by 12 ± 0.2 m, and the terminal receiving zone thickened by 28 ± 0.2 m. The glacier may have entered a quiescent phase after July 2016. The glacier surge causes a large amount of material to transfer from upstream to downstream, forming an ice dam and creating conditions for a glacial lake outburst flood (GLOF). At the termination of the active phase, the subglacial drainage channel became effective, triggering the GLOF. For a period of the quiescent phase, the glacier ablation intensifies and the GLOF repeats constantly. One surge caused 7–8 GLOFs, and then a continuous reduction in the ice dam elevation. Eventually, the ice dam disappeared, and the GLOF no longer continued before the next glacier-surging event.

Systematic vertical organization of matrix-rich and associated matrix-poor sandstones in ancient deep-marine slope and basin-floor deposits

AbstractDeepmarine two-part strata consisting of a sand-rich basal part overlain sharply by a mud-rich upper part have been termed linked debrites, hybrid event beds, transitional flow deposits, and bipartite facies. In continental slope and proximal basin floor strata of the Neoproterozoic Windermere Supergroup (western North America) and distal basin-floor strata of the Ordovician Cloridorme Formation (eastern North America), bipartite facies form the middle of a depositional continuum hundreds of meters long consisting upflow of thick-bedded, matrix-poor sandstone (&amp;lt;20% detrital mud matrix) to thin-bedded, sandy mud-stone (50%–90% mud matrix). This consistent lithofacies change is interpreted to reflect particle settling in a rapidly but systematically evolving, negligibly sheared sand-mud suspension developed along the margins (Windermere) and downflow terminus (Cloridorme) of a high-energy, mud-enriched avulsion jet.In both study areas, beds of similar lithofacies type succeed one another vertically and transform to the next facies in the depositional continuum at about the same along-strike position, forming stratal units two to nine beds thick whose grain-size distribution gradually decreases upward. This spatial and temporal regularity is interpreted to be caused by multiple surges of a single, progressively waning turbidity current, with sufficient lag between successive surges for the deposition of a traction-structured sandstone overlain by mudstone cap. Furthermore, the systematic back-stepping or side-stepping recognized at the stratal unit scale is interpreted to have been driven by a combination of knickpoint migration and local topographic steering of the flows, which continued until the supply of mud from local seafloor erosion became exhausted, the main channel avulsed elsewhere, or a new stratal element developed.

Spatial distribution of natural debris-flow impact

The high destructive potential of debris flows poses a challenge for the design of structural mitigation measures to protect vulnerable areas. An essential part of designing such structures is to determine the magnitude and spatial distribution of the impact forces. The impact is expected to be related to the composition of the flow, which can vary from clay to large boulders along a flow event and between events. Experimental studies are prone to scaling bias and benchmark observations at the full scale are rare so far. Here we present measurements of the temporal and spatial variations of the impact of a natural debris flow in the Gadria creek, IT, onto an instrumented barrier structure. The flow event was preceded by a precursory surge, which was then followed by the debris flow with multiple surges. The flow height reached up to 2.3 m. We found that the impact of boulders occurs primarily in the upper half of the flow profile, the highest forces were measured in first part of the flow, and deposition has a strong influence on the lower part of the structure by damping and/or redirection.

Comparison of the epidemiological features of COVID-19 patients in the first and second waves: A study from South India.

The coronavirus disease 2019 (COVID-19) pandemic has seen multiple surges globally since its emergence in 2019. The second wave of the pandemic was generally more aggressive than the first, with more cases and deaths. This study compares the epidemiological features of the first and second COVID-19 waves in Kozhikode district of Kerala and identifies the factors associated with this change. A comparative cross-sectional study was conducted in Kozhikode district. A total of 132,089 cases from each wave were selected for the study using a consecutive sampling method. Data were collected from the District COVID-19 line list using a semistructured proforma and analyzed using Statistical Package for Social Sciences (SPSS) ver. 18. The second wave had a higher proportion of symptomatic cases (17.3%; 20.1%), cases with severe symptoms (0.3%; 0.6%), intensive care unit (ICU) admissions (11.2%; 17.9%), and case fatality rate (0.69%; 0.72%). Significant difference was noted in the age, gender, locality, source of infection, comorbidity profile, symptom, and the pattern of admission in various healthcare settings between the first and second wave. Among the deceased, gender, duration between onset of symptoms and death, comorbidity status, and cause of death were significantly different in both waves. The presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant, as well as changes in human behavior and threat perception as the pandemic progressed, resulted in significant differences in various epidemiological features of the pandemic in both waves, indicating the need for continued vigilance during each COVID-19 wave.

Pulse-Doppler radar measurements of debris flows: High-resolution monitoring of surge dynamics from two events in the Gadria Creek (Italy)

As a consequence of their spontaneous occurrence, and frequent formation of multiple surges with high sediment loads, debris flows are considered one of the most hazardous gravity-driven mass movements in montane regions. Field measurements of surface velocities are an essential link in the chain of understanding fundamental process dynamics and applied protection against debris flows. In order to measure the velocities of multiple consecutive surges within a single debris-flow event, a PD radar (pulse-Doppler high-frequency radar) sensor for high-resolution real-time debris-flow monitoring has been developed. In this contribution we present PD radar measurements of two debris flows, that occurred at the Gadria creek in Italy on July 26, 2019, and August 10, 2020, over a torrent length of 250 meters. We record over 55 high-amplitude surges that overlap and superimpose at the front of the debris flow, but also subsequently throughout the debris-flow body. Our results demonstrate applicability of a PD radar for debris-flow monitoring and serve as a data source for modelling surge dynamics in debris flows.

Research on Inventory Simulation of Pulse Supply Chain Based on Controllable Lead Time

In the e-commerce environment, how supply chain enterprises respond to surge demands has become an urgent issue to address. This article takes into consideration the overall interests of the supply chain system, aiming to maximize the supply chain profit. By applying system dynamics theory, an in-depth analysis is conducted on a two-tier supply chain consisting of a single manufacturer and a single retailer with controllable lead times. A system dynamics model is constructed using Vensim simulation software as the modeling platform, and simulation analyses are performed for both single and multiple surge demands. The findings reveal that in both single and multiple surge demand scenarios, implementing a controllable retailer lead time strategy leads to higher profits compared to normal lead time and random lead time strategies. Moreover, as the lead time is compressed, the profit exhibits an increasing-to-decreasing trend. Additionally, when both the manufacturer and retailer lead times are controllable, the profit of the entire supply chain surpasses that of the normal lead time and random lead time strategies.

SARS-CoV-2 reinfections with BA.1 (Omicron) variant among fully vaccinated individuals in northeastern Brazil.

BackgroundThe first case of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in Rio Grande do Norte, northeastern Brazil, was diagnosed on March 12, 2020; thereafter, multiple surges of infection occurred, similar to what was seen elsewhere. These surges were mostly due to SARS-CoV-2 mutations leading to emergence of variants of concern (VoC). The introduction of new VoCs in a population previously exposed to SARS-CoV-2 or after vaccination has been a challenge to understanding the kinetics of the protective immune response against this virus. The aim of this study was to investigate the outbreak of SARS-CoV-2 reinfections observed in mid-January 2022 in Rio Grande do Norte state, Brazil. It describes the clinical and genomic characteristics of nine cases of reinfection that occurred coincident with the introduction of the omicron variant.Methodology/Principal findingsOf a total of 172,965 individuals with upper respiratory symptoms tested for SARS-CoV-2, between March 2020 through mid-February 2022, 58,097 tested positive. Of those, 444 had documented a second SARS-CoV-2 infection and nine reinfection cases were selected for sequencing. Genomic analysis revealed that virus lineages diverged between primary infections and the reinfections, with the latter caused by the Omicron (BA.1) variant among individuals fully vaccinated against SARS-CoV-2.Conclusions/SignificanceOur findings suggest that the Omicron variant is able to evade both natural and vaccine-induced immunity, since all nine cases had prior natural infection and, in addition, were fully vaccinated, emphasizing the need to develop effective blocking vaccines.

Hydraulic Scale Modeling of Mass Oscillations in a Pumped Storage Plant with Multiple Surge Tanks

Hydraulic Scale Modeling of Mass Oscillations in a Pumped Storage Plant with Multiple Surge Tanks

Kinematic evolution of kilometre-scale fold trains in surge-type glaciers explored with a numerical model

Glacier surging provides a window into the processes responsible for some of the fastest ice flow on Earth. Surge-type glaciers are festooned with fold trains—many visible from space—which encode the history of polyphase deformation associated with this form of episodic fast flow. We conduct the first investigation of the kinematic evolution of these kilometre-scale folds using a full-Stokes numerical ice-flow model. We model the folds through multiple surge cycles within a set of synthetic glacier confluence configurations, and identify how differences in glacier flow regimes imprint themselves on three-dimensional fold geometry. Based on simulation results across parameter space, we present an archetype of kinematic evolution that describes the transition from cylindrical vertically plunging gentle folds emplaced during the surge phase, to complex depth-varying folds following multiple cycles of surging and quiescent flow. A detailed examination of the surface trace of these folds highlights the links between glacier flow regime and folding. The initial fold geometry is controlled by longitudinal and lateral shear stress regimes during surging, while fold evolution is governed primarily by lateral shearing after emplacement. This reflects the influence of valley geometry and glacier dynamics on the variability of flow regimes during both surging and quiescent flow. Finally, we illustrate the potential of our approach to reconstruct more complex fold geometries as observed in nature.

Erosion Process of Multiple Debris Flow Surges Caused by Check Dam Removal: An Experimental Study

AbstractDebris flows are one of the most serious natural disasters on Earth and cause great losses in human life and property each year. Check dams have been widely utilized in debris flow hazard mitigation, and over time, some control projects have exceeded their designed service lifetime. However, the processes of stored sediment erosion with multiple surges of debris flows after check dam removal are unknown. Here, the stored sediment erosion processes associated with different reductions in the dam height (i.e., the removed height) were revealed by physical experiments. The results showed that erosion was concentrated on the stored sediment scarp formed by dam removal and that the erosion process mainly included undercutting and widening. The erosion efficiency of the debris flow gradually decreased with the development of erosion and was positively correlated with removed height, negatively correlated with the accumulated debris flow volume, and proportional to the remaining potential volume of sediment to be eroded. The erosion volume development process was well described by an exponential function model, and the physical meanings of the parameters in the model and their empirical values were clarified. Moreover, the distribution of the erosion volume along the flume was shown to satisfy the Weibull distribution, and the distribution parameters were related to the removed height, erosion volume, and sediment volume fraction of the debris flow. We anticipate that our results will serve as a starting point for the demolition and reconstruction of debris flow hazard mitigation engineering in mountainous areas.

Outcomes of Monoclonal Antibody Infusion Treatment During Delta (B.1.617.2) and Omicron (B.1.1.529) COVID 19 Variant Surges among Vaccinated and Unvaccinated Patients.

Background:Coronavirus infection of 2019 (COVID-19) is associated with significant morbidity and mortality. Vaccines supplement public health and social measures in preventing severe illness and mortality from COVID-19; however, vaccination rates remain inadequate in many regions. It is important to continuously explore the effective treatment due to the insufficient vaccination rate and increasing number of patients infected with virus. The emergence of new variants has led to multiple surges throughout the world requiring changes to treatment protocols.Method:We conducted a single-center observational study on all adult patients who received monoclonal antibody (mAb) infusion as a treatment for COVID-19 infection. Based on the predominant variant, patients were either offered Casirivimab (600 mg)/imdevimab (600 mg) or Sotrovimab (500 mg). Forty-six patients were given mAbs; 24 were vaccinated, and the remaining unvaccinated.Result:The mean age was 56 years, and the majority (63.04%) of the patients were female. Clinical symptoms of COVID-19 improved within 3 days of infusion in the majority of the patients (70%). None of the patients who received mAb showed progression of disease or required hospitalization at 30 days follow-up. There were no deaths at 30 days follow-up. Monoclonal antibodies are highly effective in reducing hospitalizations and mortality when given within 7 days of symptoms onset in patients with high-risk factors for progression to severe COVID-19 infection. The mean number of days after the onset at which the mAbs were administered to the patient was 4.Conclusion:Monoclonal antibodies should be considered in both vaccinated and unvaccinated patients with COVID-19 infection if newer antiviral agents are contraindicated. Our study highlights the effectiveness of monoclonal antibody infusions when given early in the course of COVID-19 infection regardless of vaccination status

A Bayesian Mixture Model for Predicting the COVID-19 Related Mortality in the United States.

ABSTRACTAn outbreak of SARS-CoV-2 has led to a global pandemic affecting virtually every country. As of August 31, 2020, globally, there have been approximately 25,500,000 confirmed cases and 850,000 deaths; in the United States (50 states plus District of Columbia), there have been more than 6,000,000 confirmed cases and 183,000 deaths. We propose a Bayesian mixture model to predict and monitor COVID-19 mortality across the United States. The model captures skewed unimodal (prolonged recovery) or multimodal (multiple surges) curves. The results show that across all states, the first peak dates of mortality varied between April 4, 2020 for Alaska and June 18, 2020 for Arkansas. As of August 31, 2020, 31 states had a clear bimodal curve showing a strong second surge. The peak date for a second surge ranged from July 1, 2020 for Virginia to September 12, 2020 for Hawaii. The first peak for the United States occurred about April 16, 2020—dominated by New York and New Jersey—and a second peak on August 6, 2020—dominated by California, Texas, and Florida. Reliable models for predicting the COVID-19 pandemic are essential to informing resource allocation and intervention strategies. A Bayesian mixture model was able to more accurately predict the shape of the mortality curves across the United States than other models, including the timing of multiple peaks. However, given the dynamic nature of the pandemic, it is important that the results be updated regularly to identify and better monitor future waves, and characterize the epidemiology of the pandemic.

Reliability-based retrofit assessment of coastal bridges subjected to wave forces using 3D CFD simulation and metamodeling

ABSTRACT This paper proposes a comprehensive analysis framework, combining three-dimensional (3D) numerical modelling and metamodeling, to investigate the probabilistic performance of retrofit actions on coastal bridges subjected to extreme wave forces. Specifically, a 3D Computational Fluid Dynamics (CFD) model is developed to calculate extreme wave load on the bridge superstructure. The established 3D model is validated by laboratory experiments. The characteristics of wave forces are parametrically investigated, and an Artificial Neural Network (ANN) metamodel is utilised to quantify the loading effects with multiple surge and wave parameters. Such a numerical-based ANN metamodel could predict wave forces under variable scenarios accurately, and significantly reduce the high computational cost of the 3D numerical model. Based on the numerical and metamodeling results, the bridge fragility curve is derived by considering uncertainties associated with structural demand, capacity, and hurricane hazard. Long-term failure risk is assessed under different climate change scenarios. Furthermore, different retrofit methods to improve structural performance and reduce failure risk are examined according to the proposed framework, including inserting air venting holes, enhancing connection strengths, and elevating bridge structures. The proposed framework could facilitate the optimal and robust design and maintenance of coastal infrastructures under hurricane effects in a long-term time interval.