Delay Maps Research Articles

Fuel Ignition Delay Maps for Molecularly Controlled Combustion

Fuel Ignition Delay Maps for Molecularly Controlled Combustion

Comprehending flame development and misfire at advanced engine conditions: Detailed experimental characterizations and machine learning-assisted kinetic analyses

Through comprehensive experimental and modeling efforts, this work unravels the underlying mechanisms governing flame development and misfire at advanced engine conditions that are representative of low-load and lean blow-out operations. Toward this, preliminary heat release, autoignition, and flame developing patterns are characterized, via a case study of n-heptane, at ultra-lean conditions in a well-controlled optical engine under various combustion modes including homogeneous charge compression ignition (HCCI), partially premixed combustion (PPC), and reactivity-controlled compression ignition (RCCI). Changes in preliminary heat release and flame developing patterns at three overall equivalence ratios (0.12, 0.18, and 0.24) are first characterized under the PPC mode. Flame development characteristics including flame areas and number of initial flame kernels at close-to-misfire conditions are further extracted and compared across the HCCI, RCCI, and three PPC modes, with two distinctive and one transition regimes identified. Further analyses indicate that sustainable flame development and misfire are largely controlled by the spatial distribution of local equivalence ratio (phi) and local temperature in the mixture, which dictate the initial flame kernel generation and the subsequent flame propagation through localized preliminary heat release and autoignition. Chemical kinetic modeling is also undertaken, using a recently updated gasoline chemistry model, in conjunction with a backpropagation neural network, where the predicted ignition delay map well captures the different regions of flame development. Further kinetic analysis and heat rate of production per reaction analysis corroborate the CH2O planar laser-induced fluorescence experiments and highlight the important chemical kinetics that govern the initial flame development patterns.

A novel method for tropospheric delay mapping function vertical modeling

A novel method for tropospheric delay mapping function vertical modeling

Single-voxel delay map from long-axial field-of-view PET scans.

We present an algorithm to estimate the delay between a tissue time-activity curve and a blood input curve at a single-voxel level tested on whole-body data from a long-axial field-of-view scanner with tracers of different noise characteristics. Whole-body scans of 15 patients divided equally among three tracers, namely [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, which were used in development and testing of the algorithm. Delay times were estimated by fitting the cumulatively summed input function and tissue time-activity curve with special considerations for noise. To evaluate the performance of the algorithm, it was compared against two other algorithms also commonly applied in delay estimation: name cross-correlation and a one-tissue compartment model with incorporated delay. All algorithms were tested on both synthetic time-activity curves produced with the one-tissue compartment model with increasing levels of noise and delays between the tissue activity curve and the blood input curve. Whole-body delay maps were also calculated for each of the three tracers with data acquired on a long-axial field-of-view scanner with high time resolution. Our proposed model performs better for low signal-to-noise ratio time-activity curves compared to both cross-correlation and the one-tissue compartment models for non-[15O]H2O tracers. Testing on synthetically produced time-activity curves showed only a small and even residual delay, while the one-tissue compartment model with included delay showed varying residual delays. The algorithm is robust to noise and proves applicable on a range of tracers as tested on [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, and hence is a viable option offering the ability for delay correction across various organs and tracers in use with kinetic modeling.

State Dependent Delay Maps: Numerical Algorithms and Dynamics of Projections

This work concerns the dynamics of a certain class of delay differential equations (DDEs) which we refer to as state dependent delay maps. These maps are generated by delay differential equations where the derivative of the current state depends only on delayed variables, and not on the un-delayed state. However, we allow that the delay is itself a function of the state variable. A delay map with constant delays can be rewritten explicitly as a discrete time dynamical system on an appropriate function space, and a delay map with small state dependent terms can be viewed as a “non-autonomous” perturbation. We develop a fixed point formulation for the Cauchy problem of such perturbations, and under appropriate assumptions obtain the existence of forward iterates of the map. The proof is constructive and leads to numerical procedures which we implement for illustrative examples, including the cubic Ikeda and Mackey-Glass systems with constant and state-dependent delays. After proving a local convergence result for the method, we study more qualitative/global convergence issues using data analytic tools for time series analysis (dimension and topological measures derived from persistent homology). Using these tools we quantify the convergence of the dynamics in the finite dimensional projections to the dynamics of the infinite dimensional system.

A Simple Atmospheric Delay Mapping Function for Near-Nadir Altimeters

A Simple Atmospheric Delay Mapping Function for Near-Nadir Altimeters

An efficient algorithm to measure arrival times of weak seismic phases

SUMMARY In seismic tomography, traveltime information of seismic body phases is commonly used to invert the seismic velocities of the subsurface structure. At long periods or for later seismic phases, the arrival time of seismic phases lack definitive onset and a direct picking of the absolute arrival time has large uncertainty and reproducibility. A common practice is to estimate the relative delay between the observed and synthetic signals that maximizes the correlation coefficient. For that aim, we must first select appropriate time windows around the candidate signals. To improve the ability to detect and extract weak signals, we develop a new morphological time window selection (MTWS) algorithm that adapts to the shape of signals and has robust performance in automated processing of massive data. The MTWS method consists of two successive steps. First, we detect the major peaks on the waveform envelope using a maximum filter. Secondly, we solve for the beginning and end of the time windows surrounding the peaks straightforwardly from simple geometrical equations. The efficiency and robustness of the MTWS algorithm make it very suitable for automated processing of huge data sets. We demonstrate the implementation of the method with both synthetic and observed long period (20–40 s) SH waves. From ∼100 000 traces of transverse-component seismograms recorded by global seismic networks over the course of a year, we obtain ∼15 000 Sdiff, ∼7500 ScS and also some ScS multiples. The global map of Sdiff correlation time delays shows consistent patterns with the shear wave velocity perturbations on the core–mantle boundary in the recent tomographic models.

Delay-Dependent Stability Analysis of Multi-Area LFC-EVs System

In this study, the delay-dependent stability of a multi-area Load Frequency Control (LFC) system with Electric Vehicle (EV) aggregators is investigated with the help of the Advanced Clustering with Frequency Sweeping (ACFS) method for incommensurate time delays. Both Integer-Order (IO) and Fractional-Order Proportional Integral (FOPI) controllers are utilized as a controller. The communication infrastructure used in LFC systems induces time delays resulting in deteriorations in the system stability. Even if the maximum allowable delay margin limits are not exceeded, these inevitable time delays could cause undesired frequency deviations and tie-line power fluctuations. The ACFS method is employed in this study to investigate impacts of time delays and to ensure better controller performance objectives taking into account the effects of time delays. Firstly, 2-dimensional (2D) stability delay maps are obtained for various LFC-EVs system parameters. The stability regions are then verified by the Quasi-Polynomial Mapping Root (QPmR) finder algorithm and MATLAB/Simulink-based time-domain simulations. The results clearly show that the participation of the EV aggregators in traditional LFC systems improves the frequency regulation and tie-line power-sharing in the system. Finally, it is concluded that the stability regions are enhanced as the fractional order of the FOPI decreases.

Scattering Attenuation Images of the Control of Thrusts and Fluid Overpressure on the 2016–2017 Central Italy Seismic Sequence

AbstractDeep fluid circulation likely triggered the large extensional events of the 2016–2017 Central Italy seismic sequence. Nevertheless, the connection between fault mechanisms, main crustal‐scale thrusts, and the circulation and interaction of fluids with tectonic structures controlling the sequence is still debated. Here, we show that the 3D temporal and spatial mapping of peak delays, proxy of scattering attenuation, detects thrusts and sedimentary structures and their control on fluid overpressure and release. After the mainshocks, scattering attenuation drastically increases across the hanging wall of the Monti Sibillini and Acquasanta thrusts, revealing fracturing and fluid migration. Before the sequence, low‐scattering volumes within Triassic formations highlight regions of fluid overpressure, which enhances rock compaction. Our results highlight the control of thrusts and paleogeography on the sequence and hint at the monitoring potential of the technique for the seismic hazard assessment of the Central Apennines and other tectonic regions.

Comparing end-tidal CO2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI

Cerebrovascular reactivity (CVR), defined as the cerebral blood flow response to a vasoactive stimulus, is an imaging biomarker with demonstrated utility in a range of diseases and in typical development and aging processes. A robust and widely implemented method to map CVR involves using a breath-hold task during a BOLD fMRI scan. Recording end-tidal CO2 (PETCO2) changes during the breath-hold task is recommended to be used as a reference signal for modeling CVR amplitude in standard units (%BOLD/mmHg) and CVR delay in seconds. However, obtaining reliable PETCO2 recordings requires equipment and task compliance that may not be achievable in all settings. To address this challenge, we investigated two alternative reference signals to map CVR amplitude and delay in a lagged general linear model (lagged-GLM) framework: respiration volume per time (RVT) and average gray matter BOLD response (GM-BOLD). In 8 healthy adults with multiple scan sessions, we compare spatial agreement of CVR maps from RVT and GM-BOLD to those generated with PETCO2. We define a threshold to determine whether a PETCO2 recording has “sufficient” quality for CVR mapping and perform these comparisons in 16 datasets with sufficient PETCO2 and 6 datasets with insufficient PETCO2. When PETCO2 quality is sufficient, both RVT and GM-BOLD produce CVR amplitude maps that are nearly identical to those from PETCO2 (after accounting for differences in scale), with the caveat they are not in standard units to facilitate between-group comparisons. CVR delays are comparable to PETCO2 with an RVT regressor but may be underestimated with the average GM-BOLD regressor. Importantly, when PETCO2 quality is insufficient, RVT and GM-BOLD CVR recover reasonable CVR amplitude and delay maps, provided the participant attempted the breath-hold task. Therefore, our framework offers a solution for achieving high quality CVR maps in both retrospective and prospective studies where sufficient PETCO2 recordings are not available and especially in populations where obtaining reliable measurements is a known challenge (e.g., children). Our results have the potential to improve the accessibility of CVR mapping and to increase the prevalence of this promising metric of vascular health.

Nonlinear dynamics of ascorbic acid‐KI interaction on carbon steel corrosion in acid medium

AbstractAscorbic acid (AA) has been reported as a corrosion inhibitor of carbon steel. The combined effect of AA and potassium iodide (KI) in the dynamics of the corrosion process of 1018 carbon steel is studied by electrochemical impedance spectroscopy (EIS) and electrochemical noise (EN) in an acid medium. EN data were used for nonlinear analysis by means of recurrence plots and their corresponding parameters, as well as by delay maps. Important information about the corrosion process of carbon steel corrosion in the presence of these two substances was obtained. AA does not behave as an inhibitor in this system, but the influence of KI is significant in inhibitor efficiency. The dynamics is established mainly by the adsorption of the I− ions on the steel surface and confirmed by the information entropy. The action of AA is to increase the degree of chaos when concentration increases. A relevant aspect determined is the relationship between the nonlinear dynamics of a corrosion process and its intensity.

A Simple Procedure for the Creation of Stability Charts in Delay Parameter Space for a Class of LTI Systems With Two Delays

The central task of the stability robustness with respect to delay uncertainties lies in creating the whole stability chart (delay map) in the delay parameter space. In this paper, we present a very simple frequency-sweeping procedure for creating stability chart in the delay parameter plane for a class of linear time-invariant (LTI) two-delay systems with a delay crossing talk. Actually, the procedure based on using Rekasius pseudo-delay substitution and discriminant of quadratic polynomial to characterize the crossing frequency set. The exact and exhaustive determination of crossing frequency intervals involves only finding all positive real roots of a real-coefficient polynomial. With the availability of the entire crossing frequency set, the famous cluster treatment of characteristic roots (CTCR) paradigm is applied to construct complete stability chart in the delay plane. A by-product of the proposed procedure is the revelation of the non-zero finite frequencies corresponding to infinite pseudo-delays. These frequencies divide the crossing frequency intervals into subintervals over each of which the frequency-sweeping technique provides continuous stability crossing curves in the domain of pseudo delays. For illustration and validation, two examples are provided.

Beyond linear correlation: Strong nonlinear structures in diurnal temperature range variability over southern China

The correlation structure and dynamical properties in diurnal temperature range (DTR) variability over southern China during 1979–2018 are studied in this study. Detailed results show that the linear correlation of DTR variability can be well captured by the first-order autoregressive (AR (1)) process over most of the southern stations. Since the standard detrended fluctuation analysis (DFA) based on power law assumption is designed to determine the long-range correlation strength but not the short-term correlation strength, a novel way of modified DFA is proposed to estimate the parameter of AR (1) process well over the range of short time scales. Moreover, beyond the linear correlation, the strong nonlinear structures are also detected in DTR variability with marked residual structures, i.e. significant time-reversal asymmetry and/or residual delay maps (RDM) with trough-ridge asymmetry. The mixed structures of linear correlation and strong nonlinear features improve the understandings on the prediction and predictability of DTR variability.

Systems analysis of neurosurgical first-case delays identifies opportunities to optimize operating room efficiency

BackgroundOperating room (OR) efficiency is a key target for optimizing healthcare delivery and value-based care. First-case delays are a common marker of OR efficiency. Our multidisciplinary team investigated the neurosurgical first-case delays at a large academic medical center. MethodsWe assessed all neurosurgical first-cases at the Massachusetts General Hospital between 7/1/18 and 7/1/19. We defined a delayed first-case as actual start (patient entering the OR) ≥ 15 minutes from the scheduled start time. We analyzed timestamp data in the electronic medical record (EMR) and used published methods to estimate costs associated with first-case delays. We also conducted direct process mapping and qualitative analyses of first-case delays. ResultsOf 1063 neurosurgical first-cases, 283 were delayed (27%). The median delay was 25 minutes (IQR: 18 – 35 minutes). The total delay was 9432 minutes (157.2 hours) over one year, and the estimated costs associated with these delays ranged from $25,843.68 to $238,252.32. There was a significant difference between the American Society of Anesthesia (ASA) Physical Classification scores of delayed first-cases vs. non-delayed first-cases (p = 0.03). Late arrival to the hospital contributed to delayed first-case starts (p < 0.01). Qualitative analysis identified patient preparation as the most common cause of delayed first-cases and venous and arterial lines as the most common causes of patient preparation-related delays. Direct process mapping identified system-level inefficiencies unaccounted by timestamp or qualitative analysis. ConclusionFirst-case delays are multifactorial and can impact healthcare delivery and costs. This study demonstrates the potential of a multimodal approach that includes objective EMR data, an OR cost estimation, direct observation, and qualitative analysis in pinpointing perioperative inefficiency.

Delay Domain-Based Signal Processing for Intelligent Manufacturing Systems

From a signal, x(i)∈ℜ, i = 0,1,…, a delay map consisting of the points {x(i),x(i+d)}, where d (a non-zero integer) is called the delay, can be constructed. These maps are highly informative when the signal is chaotic. In this study, a set of delay maps of cutting force signals of milling operations is constructed for different values of delay and cutting scenarios. It is found that for some specific values of delay, the delay maps exhibit distinguished patterns. The patterns can serve as the signature of cutting scenarios and, thus, can be used to construct intelligent monitoring systems for cyber-physical systems.

CYGNSS Soil Moisture Estimations Based on Quality Control

In this letter, we proposed a method based on Cyclone Global Navigation Satellite System (CYGNSS) for improving the accuracy of soil moisture (SM) estimation through the selection of auxiliary data and a four-step quality control. We investigate the impact of elevation and vegetation, as well as evaluating the quality of Doppler delay map (DDM) and different ground terrains. The program adopts the support vector machine (SVM) algorithm, input CYGNSS and auxiliary data. With the hourly SM data on Wuhan Baoxie site from January 2020 to August 2020 as an example, the effectiveness of quality control was verified. A substantial improvement in correlation coefficient of ~0.46 for average between CYGNSS reflectivity and in-situ SM was obtained compared with ~0.03 before quality control, resulting in better SM estimation accuracy compared with that of in-situ measurements (from R=0.67 to R= 0.87).

Measuring the photoelectron emission delay in the molecular frame

How long does it take to emit an electron from an atom? This question has intrigued scientists for decades. As such emission times are in the attosecond regime, the advent of attosecond metrology using ultrashort and intense lasers has re-triggered strong interest on the topic from an experimental standpoint. Here, we present an approach to measure such emission delays, which does not require attosecond light pulses, and works without the presence of superimposed infrared laser fields. We instead extract the emission delay from the interference pattern generated as the emitted photoelectron is diffracted by the parent ion’s potential. Targeting core electrons in CO, we measured a 2d map of photoelectron emission delays in the molecular frame over a wide range of electron energies. The emission times depend drastically on the photoelectrons’ emission directions in the molecular frame and exhibit characteristic changes along the shape resonance of the molecule.

Exploring different textures of a nematic liquid crystal for quantitative Fourier phase contrast microscopy

Quantitative phase microscopy (QPM) has emerged as a viable technique for investigating biological and biomedical samples in its natural environment. Contrary to well established phase microscopes, QPM provides phase map of the optical path length delays introduced by the specimen. Building on our prior technology of the Fourier phase contrast microscopy (FPCM) technique, we present a low-cost and robust quantitative Fourier phase contrast microscopy system that can easily be attached to most commercial brightfield microscopes. This is derived by merging the FPCM technique with phase shifting interferometry. By applying voltages across a nematic liquid crystal cell with various anchoring properties, Stokes’ parameters are obtained to unwrap the object information quantitatively. Further three different nematic textures were considered to improve the utility of the phase unwrapping: planar, twisted, and hybrid. Our results indicate that the hybrid nematic film presents the best phase contrast filter.

Preparing Datasets of Surface Roughness for Constructing Big Data from the Context of Smart Manufacturing and Cognitive Computing

In smart manufacturing, human-cyber-physical systems host digital twins and IoT-based networks. The networks weave manufacturing enablers such as CNC machine tools, robots, CAD/CAM systems, process planning systems, enterprise resource planning systems, and human resources. The twins work as the brains of the enablers; that is, the twins supply the required knowledge and help enablers solve problems autonomously in real-time. Since surface roughness is a major concern of all manufacturing processes, twins to solve surface roughness-relevant problems are needed. The twins must machine-learn the required knowledge from the relevant datasets available in big data. Therefore, preparing surface roughness-relevant datasets to be included in the human-cyber-physical system-friendly big data is a critical issue. However, preparing such datasets is a challenge due to the lack of a steadfast procedure. This study sheds some light on this issue. A state-of-the-art method is proposed to prepare the said datasets for surface roughness, wherein each dataset consists of four segments: semantic annotation, roughness model, simulation algorithm, and simulation system. These segments provide input information for digital twins’ input, modeling, simulation, and validation modules. The semantic annotation segment boils down to a concept map. A human- and machine-readable concept map is thus developed where the information of other segments (roughness model, simulation algorithm, and simulation system) is integrated. The delay map of surface roughness profile heights plays a pivotal role in the proposed dataset preparation method. The successful preparation of datasets of surface roughness underlying milling, turning, grinding, electric discharge machining, and polishing shows the efficacy of the proposed method. The method will be extended to the manufacturing processes in the next phase of this study.

Reverberation Mapping of Two Luminous Quasars: The Broad-line Region Structure and Black Hole Mass

Abstract We report the results of a multiyear spectroscopic and photometric monitoring campaign of two luminous quasars, PG 0923+201 and PG 1001+291, both located at the high-luminosity end of the broad-line region (BLR) size–luminosity relation with optical luminosities above 1045 erg s−1. PG 0923+201 is monitored for the first time, while PG 1001+291 was previously monitored but our campaign has a much longer temporal baseline. We detect time lags of variations of the broad Hβ, Hγ, and Fe ii lines with respect to those of the 5100 Å continuum. The velocity-resolved delay map of Hβ in PG 0923+201 indicates a complicated structure with a mix of Keplerian disk-like motion and outflow, and the map of Hβ in PG 1001+291 shows a signature of Keplerian disk-like motion. Assuming a virial factor of f BLR = 1 and FWHM line widths, we measure the black hole mass to be 118 − 16 + 11 × 10 7 M ⊙ for PG 0923+201 and 3.33 − 0.54 + 0.62 × 10 7 M ⊙ for PG 1001+291. Their respective accretion rates are estimated to be 0.21 − 0.07 + 0.06 × L Edd c − 2 and 679 − 227 + 259 × L Edd c − 2 , indicating that PG 0923+201 is a sub-Eddington accretor and PG 1001+291 is a super-Eddington accretor. While the Hβ time lag of PG 0923+201 agrees with the size–luminosity relation, the time lag of PG 1001+291 shows a significant deviation, confirming that in high-luminosity active galactic nuclei (AGNs), the BLR size depends on both luminosity and Eddington ratio. Black hole mass estimates from single-AGN spectra will be overestimated at high luminosities and redshifts if this effect is not taken into account.