Impact Of Initial Conditions Research Articles

A quantum information theoretic analysis of reinforcement learning-assisted quantum architecture search

In the field of quantum computing, variational quantum algorithms (VQAs) represent a pivotal category of quantum solutions across a broad spectrum of applications. These algorithms demonstrate significant potential for realising quantum computational advantage. A fundamental aspect of VQAs involves formulating expressive and efficient quantum circuits (namely ansatz), and automating the search of such ansatz is known as quantum architecture search (QAS). Recently reinforcement learning (RL) techniques is utilized to automate the search for ansatzes, know as RL-QAS. This study investigates RL-QAS for crafting ansatz tailored to the variational quantum state diagonalisation problem. Our investigation includes a comprehensive analysis of various dimensions, such as the entanglement thresholds of the resultant states, the impact of initial conditions on the performance of RL-agent, the phase transition behaviour of correlation in concurrence bounds, and the discrete contributions of qubits in deducing eigenvalues through conditional entropy metrics. We leverage these insights to devise an entanglement-guided admissible ansatz in QAS to diagonalise random quantum states using optimal resources. Furthermore, the methodologies presented herein offer a generalised framework for constructing reward functions within RL-QAS applicable to variational quantum algorithms.

Impact of initial conditions on the effectiveness of rolling dynamic compaction of granular soils

A finite element model (FEM) of rolling dynamic compaction (RDC) technology of a BH 1300 4 sided 8 tonne impact roller, developed previously by the authors, has shown to have reasonable agreement with that observed in the field. The use of this FEM is likely to provide high fidelity insights into the capability of the BH 1300 4 sided 8 tonne impact roller, namely in predicting the settlement and densification of an underlying granular material. A parametric study utilising this FEM with respect to initial density and shear strength parameters is undertaken to explore the relationship these properties have to the settlement and densification of a soil subject to RDC with a BH 1300 4 sided 8 tonne impact roller. The empirical relationships constructed within this study are validated against field trials from the literature of the roller improving sandy gravel fill at typical operating speeds of 10 km/h.

Research progress and development trends of hydrogen explosion suppression materials and mechanisms

In order to effectively control and reduce the destructive effects caused by hydrogen leakage and explosion accidents, continuously improving the theoretical system of hydrogen suppression. Based on a survey of literature, this article reviews and discusses the current research status of hydrogen explosion characteristics, explosion suppression materials, and explosion suppression mechanisms. In terms of research on hydrogen explosion characteristics, the impact of initial conditions on macroscopic parameters such as explosion limit, explosion pressure and flame propagation speed were mainly studied. In terms of research on hydrogen suppression, summarizes the research progress of hydrogen explosion suppression materials in recent years from five aspects: inert gas, water mist, solid powder, halogenated hydrocarbons and composite suppression. The suppression effects and suppression mechanisms of different materials were comparatively analyzed. The analysis found that the explosion suppression mechanism of inert gas is mainly physical inerting, and a higher concentration of inert gas is required to completely suppress hydrogen explosion. The explosion suppression mechanism of fine water mist is mainly evaporation and heat absorption, but it cannot completely suppress lean fuel hydrogen explosion. Solid powder materials have almost no inhibitory effect on hydrogen explosion. The explosion suppression mechanism of halogenated hydrocarbons is mainly to eliminate H radicals, but halogenated hydrocarbons have an promoting effect on lean fuel hydrogen. The suppression effect of composite explosion suppressants is better than that of a single explosion suppressor. However, there are currently few studies on the suppression of hydrogen explosions by composite suppressants, and the mechanism of explosion needs to be improved. The article proposes that hydrogen absorption materials, eliminate H radical targeted suppression materials and composite explosion suppression materials are the focus of research on hydrogen suppression materials. Using advanced optical diagnostic technology to study the concentration of radicals and explosion flow field characteristics, and using kinetic simulation software to reveal the complex chain reaction process are important means to study the mechanism of hydrogen explosion suppression. Large-scale explosion suppression experiments are more instructive for engineering applications, but there is a lack of large-scale equipment and experimental research.

Study on the epoxidation of chain olefins using biquaternary ammonium phosphotungstic acid phase transfer catalysts under no-solvent condition.

In this study, we have developed a novel catalyst synthesized by phosphotungstic acid and a gemini quaternary ammonium cation salt. This quaternary ammonium salt not only reduces the interfacial tension between olefins and hydrogen peroxide but also forms a notably stable structure with phosphotungstic acid. Dodecene was successfully epoxidized to epoxy dodecane with a selectivity of 82.9 %. The impact of initial conditions was systematically investigated such as molar ratio, temperature, reaction time, and catalyst dosage on the catalytic performance. Characterization of the catalyst morphology was performed by SEM, TEM and SAXS. Raman spectra, FT-IR and XPS spectra were employed to perform the catalyst transformation during the epoxidation reaction. This catalytic mechanism study could provide the industrial application in the epoxidation of long-chain olefins.

On the impact of initial conditions in the forecast of Hurricane Leslie extratropical transition

Hurricane Leslie (2018) was a non-tropical system that lasted for a long time undergoing several transitions between tropical and extratropical states. Its trajectory was highly uncertain and difficult to predict. Here the extratropical transition of Leslie is simulated using the Model for Prediction Across Scales (MPAS) with two different sets of initial conditions (IC): the operational analysis of the Integrate Forecast System (IFS) and the Global Forecast System (GFS).Discrepancies in Leslie position are found in the IC patterns, and in the intensity and amplitude of the dorsal-trough system in which Leslie is found. Differences are identified both in the geopotential height at 300 hPa and the geopotential thickness. Potential temperature in the dynamic tropopause shows a broader, more intense trough displaced western when using the IC-IFS. The IC-IFS simulation shows lesser trajectory errors but wind speed overestimation than the IC-GFS one. The complex situation of the extratropical transition, where Leslie interacts with a trough, increases the uncertainty associated with the intensification process.The disparities observed in the simulations are attributed to inaccuracies in generating the ICs. Both ICs generate different atmospheric configurations when propagated in time. Results suggest that during an extratropical transition in a highly baroclinic atmosphere, the IFS model's data assimilation method produced a more precise analysis than GFS due to the greater number of observations assimilated by the IFS, the greater spatial resolution of the model and the continuous adjustment of the simulations with the field of observations.

Chaotic dynamics of an extended Duffing-van der Pol system with a non-smooth perturbation and parametric excitation

Abstract Chaotic dynamics of a fifth-order extended Duffing-van der Pol system with a non-smooth periodic perturbation and parametric excitation are investigated both analytically and numerically in this paper. With the Fourier series, the system is expanded to the equivalent smooth system. The Melnikov perturbation method is used to derive the horseshoe chaos condition in the cases of homoclinic and heteroclinic intersections. The chaotic features for different system parameters are investigated in detail. The monotonic variation of the coefficients of parametric excitation and non-smooth periodic disturbance is found. With numerical methods, we validate the analytical results obtained by Melnikov’s method. The impact of initial conditions is carefully analyzed by basins of attraction and the effect of non-smooth periodic disturbance on the basin of attraction is also investigated. Besides, the effect of different parameters on the bifurcation pathway into chaotic attractors is examined.

A robust score-driven filter for multivariate time series

A multivariate score-driven filter is developed to extract signals from noisy vector processes. By assuming that the conditional location vector from a multivariate Student’s t distribution changes over time, we construct a robust filter which is able to overcome several issues that naturally arise when modeling heavy-tailed phenomena and, more in general, vectors of dependent non-Gaussian time series. We derive conditions for stationarity and invertibility and estimate the unknown parameters by maximum likelihood. Strong consistency and asymptotic normality of the estimator are derived. Analytical formulae are derived which consent to develop estimation procedures based on a fast and reliable Fisher scoring method. An extensive Monte–Carlo study is designed to assess the finite samples properties of the estimator, the impact of initial conditions on the filtered sequence, the performance when some of the underlying assumptions are violated, such as symmetry of the underlying distribution and homogeneity of the degrees of freedom parameter across marginals. The theory is supported by a novel empirical illustration that shows how the model can be effectively applied to estimate consumer prices from home scanner data.

The Numerical Identification of Basins of Attraction for the Vibration Response of the Rigid Rotor with Squeeze Film Dampers

The article deals with the computational study of the rigid rotor coupled with squeeze film dampers. Various techniques such as the method of computation of the synchronous response with a circular centred orbit, the harmonic balance method, and the direct time integration method are used to analyse the nonlinear behaviour of the rotor system. The results indicate that the rotor system can exhibit both a synchronous circular response with a large orbit radius and a nonsynchronous response with a quasiperiodic character. However, both responses are undesirable in rotating machinery and should be avoided. The new results are presented to provide insight into the impact of initial conditions on the vibration response via basins of attraction. The simulations show that: (i) the basins of attraction are more sensitive to the choice of the initial velocities than displacements, (ii) the basins of attraction are noticeably dependent on the rotor speed in the region of a nonsynchronous response, and (iii) the border between the basins of attraction can be smooth or without a clear structure. The research brings clear conditions defined by parameters such as the dimensionless SFD constant, unbalance, and rotational speed for the suppression of undesirable nonlinear phenomena. The results suggest that the damper can effectively improve the vibration response of high-speed rotating machinery, but its design must be chosen appropriately.

Impact of initial conditions and gas dynamics on the evaporation of a sessile droplet in microgravity and on-ground explained by a numerical model

The wide interest in the evaporation dynamics of sessile droplets has led to many studies aiming at understanding specific phenomena and overall behaviour. The effect of controlling the initial conditions, or the lack thereof, has not been studied extensively. One of the main issues are the conditions under which the droplet is injected on the substrate. This problem does not only raise questions on an experimental basis but also for numerical predictions. In the context of preparatory work for future space experiments in a sounding rocket and on board the International Space Station, initial conditions are difficult to control and their complete understanding lacks, whereas simulations may shed light on the subject. This work develops a comprehensive axisymmetric transient model that describes the injection of a sessile droplet evaporating into a gas phase as well as the evaporation process of that droplet. The model is validated against experimental data in both Earth and microgravity conditions. The amount of injected volume has been shown to increase the evaporation rate, with a weaker influence at microgravity with respect to Earth conditions. Comparing our model to the case where no injection history is present reveals that neglecting the latter has no significant influence on the evaporation dynamics nor on the simulated velocity and temperature profiles. This suggests that in most cases it is not necessary to include the injection period, so that uncertainties involving the injection are not an obstacle to model the evaporation of sessile droplets. Moreover, it also appears that thermal supply by the injected fluid plays a large role during injection in suppressing Marangoni convection, whilst the latter becomes the main mechanism determining the flow patterns after the injection. Finally, it appears that for high-molar-mass vapours the gas dynamics play an important role in the evaporation process. In particular, for correct numerical simulations, it is necessary to consider concentration-dependent gas properties, and especially concentration-dependent gas density, these effects being most often neglected in other approaches, which results in underestimated evaporation rates.

Impact of initial conditions on modelling extreme precipitation: case of November 29–30, 2010 floods over Morocco

Impact of initial conditions on modelling extreme precipitation: case of November 29–30, 2010 floods over Morocco

Comparative Development of Indonesia and Nigeria in the First Two Decades of Democracy: Divergence or Convergence?

Indonesia and Nigeria are considered suitable candidates for comparative analysis because of their similarities in natural endowments and geographical attributes, demography, economic structure, sociocultural diversity, and political history. Indonesia began to achieve rapid growth in the 1980s while Nigeria did not. During that period, economic policies in the two countries diverged, and this led to sustained economic growth in Indonesia and prolonged economic decline in Nigeria. However, as the countries transitioned to democratic rule in 1999 following the collapse of authoritarian regimes, some aspects of their political and economic trajectories revealed a trend towards convergence. Using the descriptive comparison of secondary data, the researcher analyzed those converging paths and the areas where the divergence continues. The study concludes that despite exhibiting more signs of convergence and dealing with similar challenges, the impact of initial conditions is likely to influence the developmental efforts in Indonesia and Nigeria.

Impacts of initial conditions and model configuration on simulations of polar lows near Svalbard using Polar WRF with 3DVAR

AbstractThe impacts of initial conditions and model configuration on the simulations of polar lows (PLs) near Svalbard, the global “hotspot” for PL activity, were investigated using the Polar Weather Research and Forecasting (Polar WRF or PWRF) model and WRF three‐dimensional data assimilation (3DVAR). The well‐documented PL case presented by Sergeev et al., in 2017 from March 26, 2013 featuring in situ aircraft observations is revisited using PWRF and 3DVAR to identify the most suitable model configuration to simulate PLs. The simulation results using initial conditions from PWRF and 3DVAR cycling runs were compared with those of cold‐start experiments using reanalysis as the initial condition. For cycling runs, the impacts of initial conditions from synoptic observations together with satellite radiances were superior to the assimilation of synoptic data alone. Several additional experiments were undertaken to further refine the PWRF configuration by considering the horizontal resolution, analysis nudging, digital filter initialization, and two boundary‐layer and four microphysics schemes. Based on the chosen configuration of Polar WRF and 3DVAR from the case‐study, the monthly reanalysis mode with 3 hr time window cycling data assimilation and short‐term forecasts using PWRF alone were performed for March 2013 and the PLs that formed over the Nordic Seas were evaluated. Manual identification and verification of PLs were performed using thermal infrared satellite imagery and 10 m scatterometer winds. Overall, nine PLs were identified in addition to the case presented by Sergeev et al., in 2017. Both the case‐study and monthly simulation results show that the high‐resolution initial condition is the most important factor, but a reasonable forecast model configuration can help to improve the simulation performance. Satellite radiance data are very important for producing the high‐resolution initial conditions for Polar WRF to simulate PLs successfully; the best performance was obtained by assimilating both synoptic data and satellite radiances.

Impact of initial conditions and cloud parameterization on the heavy rainfall event of Kerala (2018)

In Aug 2018, the extreme precipitation event had created devastation over Kerala's state for 1 week and led to more than 483 deaths, and destructions of properties cost more than 50,000 Crore rupees. We simulated the event with the Advanced Research Weather Research and Forecasting model (WRF-ARW). Two most popular initial conditions (ICs), i.e., the National Centre for Environment Prediction (NCEP-FNL) and European Centre for Medium-range Weather Forecasting (ECMWF-ERA5), have been used to investigate the impacts of ICs on the forecast skills (up to day1) with particular reference to rainfall. Using these ICs, the study simulated the event with four cloud microphysics parameterization schemes (CMPS), namely, Milbrandt–Yau, Thompson, Aerosol aware Thompson, and WDM6. The study examined the role of ICs in modulating the cloud microphysical properties and associated mechanisms impacting the rainfall characteristics, hydrometeor formation, and related convective mechanism over the region. A total of 24 simulations (2 ICs × 4 CMPS × 3 initial days 13–15 Aug 2018) are conducted. Results show that the ERA5 IC with Milbrandt–Yau CMPS has performed best among all the simulations. Nevertheless, in general, there is an underestimation of rainfall in the model. It is found that though an ample amount of moisture available at the lower levels of the troposphere in the model, however, due to the lack of intense updraft, this moisture could not reach the middle levels, resulting in robust dryness at these levels and adversely impacting the convection and rainfall. This process shows a deficiency in the formation of frozen hydrometeors in the model's upper levels, leading to the lack of cloud heating and weakly developed vertical pressure gradient. These chain processes resulted in weak convection and reduced rainfall in the model experiments. These findings are highly relevant to understand the limitations of the model, influences of ICs, and cloud microphysical parameterizations to forecast extreme rainfall events accurately.

Prediction of lightning activity using WRF-ELEC model: Impact of initial and boundary conditions

The impact of initial conditions in predicting lightning activity using the Weather Research and Forecasting (WRF) with the electrification (ELEC) extra package, known as WRF-ELEC model, has been investigated. The severity, frequency, and some physical and dynamical properties of lightning occurred during 11 years (2004–2014) are considered. Four thundercloud events with distinctive characteristics over the Tehran area were chosen for detailed study. The selection process was made based on the observational data received from the Iranian Meteorological Organization (IRIMO), ground-based lightning data from the World Wide Lightning Location Network (WWLLN) and satellite-based lightning data from the Lightning Imaging Sensor (LIS). The WRF-ELEC simulations initialized with the European Centre for Medium-Range Weather Forecasts-ERA Interim (ECMWF-ERA Interim), National Centers for Environmental Prediction Final Analysis (NCEP-FNL) and the NCEP operational Global Forecast System (GFS) data have been conducted to obtain the Number Of Lightning flash density (NOL) associated with each case study. The numerical simulations are compared qualitatively and quantitatively with the observations. Several statistical metrics are used in order to determine the performance of the WRF-ELEC model initialized by various IBCs (initial and boundary conditions) for lightning prediction purposes. The results show that in the most of the studied cases, there is a good agreement between the simulated time-averaged horizontal patterns of the Lightning Potential Index (LPI) obtained from the ERA-Interim-based experiments and the locations of lightning occurrence of WWLLN data as well as LIS observations. Furthermore, GFS-based simulations have a better quantitative performance in the NOL prediction than FNL and ERA-Interim-based simulations regarding the values of Standard Deviation (SD), and centered Root Mean Square Error (RMSE). The results of further statistical analysis using different metrics reveal that ERA-Interim initialization has the best performance of lightning activity prediction.

The Impact of Initial Condition and Warm Conveyor Belt Forecast Uncertainty on Variability in the Downstream Waveguide in an ECWMF Case Study

AbstractPerturbations to the potential vorticity (PV) waveguide, which can result from latent heat release within the warm conveyor belt (WCB) of midlatitude cyclones, can lead to the downstream radiation of Rossby waves, and in turn high-impact weather events. Previous studies have hypothesized that forecast uncertainty associated with diabatic heating in WCBs can result in large downstream forecast variability; however, these studies have not established a direct connection between the two. This study evaluates the potential impact of latent heating variability in the WCB on subsequent downstream forecasts by applying the ensemble-based sensitivity method to European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasts of a cyclogenesis event over the North Atlantic. For this case, ensemble members with a more amplified ridge are associated with greater negative PV advection by the irrotational wind, which is associated with stronger lower-tropospheric southerly moisture transport east of the upstream cyclone in the WCB. This transport is sensitive to the pressure trough to the south of the cyclone along the cold front, which in turn is modulated by earlier differences in the motion of the air masses on either side of the front. The position of the cold air behind the front is modulated by upstream tropopause-based PV anomalies, such that a deeper pressure trough is associated with a more progressive flow pattern, originating from Rossby wave breaking over the North Pacific. Overall, these results suggest that more accurate forecasts of upstream PV anomalies and WCBs may reduce forecast uncertainty in the downstream waveguide.

Cavity-QED simulator of slow and fast scrambling

We study information scrambling, as diagnosed by the out-of-time order correlations (OTOCs), in a system of large spins collectively interacting via spatially inhomogeneous and incommensurate exchange couplings. The model is realisable in a cavity QED system in the dispersive regime. Fast scrambling, signalled by an exponential growth of the OTOCs, is observed when the couplings do not factorise into the product of a pair of local interaction terms, and at the same time the state of the spins points initially coplanar to the equator of the Bloch sphere. When one of these conditions is not realised, OTOCs grow algebraically with an exponent sensitive to the orientation of the spins in the initial state. The impact of initial conditions on the scrambling dynamics is attributed to the presence of a global conserved quantity, which critically slows down the evolution for initial states close to the poles of the Bloch sphere.

Review—Understanding the Thermal Runaway Behavior of Li-Ion Batteries through Experimental Techniques

Heavy duty Li-ion batteries in the electric vehicles suffer from serious safety issues due to their operation in abuse conditions. The worst consequence of these conditions is the thermal runaway, which causes a dramatic rise in temperature and pressure leading to a catastrophic failure of the battery. Therefore, precise determination of thermal runaway behavior of the battery under different abusive scenarios holds critical importance. This paper reviews the understanding of the thermal runaway behavior of Li-ion batteries through experimental routes. The impact of initial conditions (SoC, overcharge and ageing) and design (geometry, material and capacity) of the battery on the severity of thermal runaway is extensively discussed. It is observed that the thermal runaway becomes more severe in high SoC, overcharged and aged batteries, and the mechanism of thermal runaway primarily depends on the battery design. The quantification of the fire-induced hazards is presented in terms of the heat release rate. Further, we observe that the electrical and mechanical abuse conditions induce an internal short circuit in the battery due to a component collapse. We also briefly review the prevention techniques of thermal runaway which include detection modelling, heat dissipation strategies and the use of the non-flammable electrolytes.

Significance of Early and Late Stages of Coupled Aggregation and Sedimentation in the Fate of Nanoparticles: Measurement and Modeling.

Despite aggregation's crucial role in controlling the environmental fate of nanoparticles (NP), the extent to which current models can describe the progressive stages of NP aggregation/sedimentation is still unclear. In this paper, 24 model combinations of two population-balance models and various collision frequency and settling velocity models are used to analyze spatiotemporal variations in the size and concentration of hydroxyapatite (HAp) NP. The impact of initial conditions and variability in attachment efficiency, α, with aggregate size are investigated. Although permeability models perform well in calculating collision frequencies, they are not appropriate for describing settling velocity because of their negative correlation or insensitivity in respect to fractal dimension. Considering both early and late stages of aggregation, both experimental and model data indicate overall mass removal peaks at an intermediate ionic strength (5 mM CaCl2) even though the mean aggregate size continued to increase through higher ionic strengths (to 10 mM CaCl2). This trend was consistent when different approaches to the initial particle size distribution were used and when a variable or constant α was used. These results point to the importance of accurately considering different stages of aggregation in modeling NP fate within various environmental conditions.

Impact of initial conditions on the prediction of the spread of thermal pollution in rivers

The influence of initial conditions on the prediction of the increase of river temperature below the point of release of heated water for a designed power plant has been analysed in this study. The results for different assumed values of river flow and different temperatures of the discharged heated water have been presented. The results have been analysed taking into account existing legal frames. The two-dimensional inhouse RivMix model has been used to simulate the temperature distribution whereas the two-dimensional depth-averaged turbulent open channel flow model CCHE2D has been used to simulate the velocity fields and the water depths for the selected flows of the river.

The role of heat transfer time scale in the evolution of the subsea permafrost and associated methane hydrates stability zone during glacial cycles

Climate warming may lead to degradation of the subsea permafrost developed during Pleistocene glaciations and release methane from the hydrates, which are stored in this permafrost. It is important to quantify time scales at which this release is plausible. While, in principle, such time scale might be inferred from paleoarchives, this is hampered by considerable uncertainty associated with paleodata. In the present paper, to reduce such uncertainty, one-dimensional simulations with a model for thermal state of subsea sediments forced by the data obtained from the ice core reconstructions are performed. It is shown that heat propagates in the sediments with a time scale of ∼ 10–20kyr. This time scale is longer than the present interglacial and is determined by the time needed for heat penetration in the unfrozen part of thick sediments. We highlight also that timings of shelf exposure during oceanic regressions and flooding during transgressions are important for simulating thermal state of the sediments and methane hydrates stability zone (HSZ). These timings should be resolved with respect to the contemporary shelf depth (SD). During glacial cycles, the temperature at the top of the sediments is a major driver for moving the HSZ vertical boundaries irrespective of SD. In turn, pressure due to oceanic water is additionally important for SD ≥ 50m. Thus, oceanic transgressions and regressions do not instantly determine onsets of HSZ and/or its disappearance. Finally, impact of initial conditions in the subsea sediments is lost after ∼ 100kyr. Our results are moderately sensitive to intensity of geothermal heat flux.