Semi-empirical Technique Research Articles

The source characteristics and ground motion parameters measure with structural damages of Mw6.4, 2018 Hualien earthquake Taiwan from GPS data

On February 6, 2018, a moderate earthquake with a magnitude of ML6.2, known as the 0206 earthquake, struck Hualien in eastern Taiwan, resulting in significant destruction, 17 fatalities, and over 300 injuries. This research investigates the kinematic source model of the earthquake by inverting coseismic Global Positioning System (GPS) displacement recordings from the area surrounding the epicenter. The inverted source model indicates that most asperities above the hypocenter are minor, with large slips occurring at depths shallower than 10 km, which contributed to the severe damage in Hualien City. Additionally, we calculated the Coulomb stress changes at depths ranging from 6 km to 14 km, revealing that most aftershocks within a month occurred within a Coulomb stress range of >0.1 bar, extending from shallow to deep and from southwest to northeast of the epicenter. Notably, despite high Coulomb stress, few aftershocks were generated in the western part of the epicenter, suggesting a seismic gap that may lead to a more significant earthquake in the future. Two years later, two moderate earthquakes (ML=5) occurred at depths of 17.53 and 12.1 km in the region where Coulomb stress had increased, validating our predictions. Furthermore, by applying the derived seismic source model and a stochastic semi-empirical technique to assess five parameters related to building damage, we found that all damaged buildings were within the danger alert level, with some located along the Meilun Fault, indicating that the destruction was due to the combined effects of the 0206 earthquake and the fault's induced movement.

Review of Cell Level Battery (Calendar and Cycling) Aging Models: Electric Vehicles

Electrochemical battery cells have been a focus of attention due to their numerous advantages in distinct applications recently, such as electric vehicles. A limiting factor for adaptation by the industry is related to the aging of batteries over time. Characteristics of battery aging vary depending on many factors such as battery type, electrochemical reactions, and operation conditions. Aging could be considered in two sections according to its type: calendar and cycling. We examine the stress factors affecting these two types of aging in detail under subheadings and review the battery aging literature with a comprehensive approach. This article presents a review of empirical and semi-empirical modeling techniques and aging studies, focusing on the trends observed between different studies and highlighting the limitations and challenges of the various models.

Source Modeling of Deep Plate Boundary 2021 Miyagi Earthquake (Mw7.0) Employing Modified Semi-Empirical Technique with Site Effects: A Step Forward Towards Hazard Mitigation

ABSTRACT The source modeling of 2021 Miyagi earthquake (Mw7.0) offers a significant tool to understand the initial evaluation of M9 earthquake cycle in this region. This article seeks to simulate the 2021 Miyagi earthquake (Mw7.0) using the modified semi-empirical technique (MSET) after incorporating site effects determined using the Horizontal to Vertical spectral ratio technique. We propose the best-fitting source model of this earthquake from a spectrum of rupture model parameters using MSET. We believe that this effort is the first to use MSET to model this earthquake and will provide significant contribution for seismic hazard assessment of the Miyagi region.

Machine Learning Modelling for Soil Moisture Retrieval from Simulated NASA-ISRO SAR (NISAR) L-Band Data

Soil moisture is a critical factor that supports plant growth, improves crop yields, and reduces erosion. Therefore, obtaining accurate and timely information about soil moisture across large regions is crucial. Remote sensing techniques, such as microwave remote sensing, have emerged as powerful tools for monitoring and mapping soil moisture. Synthetic aperture radar (SAR) is beneficial for estimating soil moisture at both global and local levels. This study aimed to assess soil moisture and dielectric constant retrieval over agricultural land using machine learning (ML) algorithms and decomposition techniques. Three polarimetric decomposition models were used to extract features from simulated NASA-ISRO SAR (NISAR) L-Band radar images. Machine learning techniques such as random forest regression, decision tree regression, stochastic gradient descent (SGD), XGBoost, K-nearest neighbors (KNN) regression, neural network regression, and multilinear regression were used to retrieve soil moisture from three different crop fields: wheat, soybean, and corn. The study found that the random forest regression technique produced the most precise soil moisture estimations for soybean fields, with an R2 of 0.89 and RMSE of 0.050 without considering vegetation effects and an R2 of 0.92 and RMSE of 0.042 considering vegetation effects. The results for real dielectric constant retrieval for the soybean field were an R2 of 0.89 and RMSE of 6.79 without considering vegetation effects and an R2 of 0.89 and RMSE of 6.78 with considering vegetation effects. These findings suggest that machine learning algorithms and decomposition techniques, along with a semi-empirical technique like Water Cloud Model (WCM), can be effective tools for estimating soil moisture and dielectric constant values precisely. The methodology applied in the current research contributes essential insights that could benefit upcoming missions, such as the Radar Observing System for Europe in L-band (ROSE-L) and the collaborative NASA-ISRO SAR (NISAR) mission, for future data analysis in soil moisture applications.

On the applicability of the Redlich-Kister framework for viscosity estimation of molten halide salt mixtures

For molten halide salt mixtures already being utilized or under consideration for carbon-free energy production systems, it is crucial that their viscosity is well understood so that system thermal hydraulics can be reliably assessed. Because of the difficulty in accurately measuring molten halide viscosity and the sheer size of the matrix of possible higher order salt mixtures that may be of interest to the energy industry, there are several gaps in the quantified understanding of molten halide viscosity across this matrix. As such, both first-principles and semi-empirical modeling techniques may be crucial for rapidly assessing this broad, complex compositional domain. Herein, the Redlich-Kister framework is applied to assess the feasibility of broadly interpolating and estimating the viscosity of several pseudobinary and pseudoternary molten halide salt systems that may be of key interest to the energy industry. The framework is based on the assumption that an ideal component and a nonideal component collectively describe the viscosity as a function of composition and temperature for a given molten halide system. Three different ideal models were considered for the ideal component, including Grunburg-Nissan, Katti-Chaudhri, and Gambill methods. Regarding the pseudobinary interpolations, the Redlich-Kister models with either the Grunburg-Nissan or Katti-Chaudhri models as the ideal component resulted in either highly (average error less than 5%) or reasonably (average error less than 15%) accurate interpolations of pseudobinary halide viscosity; BeF2- or UF4-bearing salts tended to result in reasonably accurate interpolations, whereas other pseudobinary mixtures tended to show high accuracy. Regarding the pseudoternary extrapolations, the Redlich-Kister framework shows reasonable success at estimating the extent to which a pseudoternary system may indicate deviations from ideal Grunburg-Nissan mixing, where discrepancies with comparative experimental data generally stay within 30%. The primary reasons identified for such discrepancies are (1) inaccuracy in the underlying experimental data, (2) different complexation behavior in the higher order systems compared to the pseudobinary subsystems, and (3) extrapolation into temperatures too far out of the domain, which is valid for the underlying experimental data feeding the Redlich-Kister model.

The polymethine nature of Vis/NIR chromophores

AbstractThe polymethine concept is known to rationalize a plethora of spectroscopic issues, thus finding wide applications in modern color theory. This approach was questioned by the arguments in the relevant “dye” literature. Based on the critical analysis of these arguments, the errors are clarified and the superiority of the polymethine concept above other attempts to qualitatively explain color and constitution relationships is exemplified at relevant dye molecules absorbing in the visible and near‐infrared spectral region. The classical chromophore theory, topological approaches, different‐level semiempirical techniques, and DFT/ab initio methods are comparatively analyzed to interpret the optical effects of structural modifications in conjugated compounds regarded as polymethine derivatives.

Modelling of 1991 Uttarkashi and 2011 Indo-Nepal earthquakes using the modified semi-empirical technique by integrating site-specific quality factor

Modelling of 1991 Uttarkashi and 2011 Indo-Nepal earthquakes using the modified semi-empirical technique by integrating site-specific quality factor

Designing Nonconventional Luminescent Materials with Efficient Emission in Dilute Solutions via Modulation of Dynamic Hydrogen Bonds.

Nonconventional luminescent materials (NLMs) which do not contain traditional aromatic chromophores are of great interest due to their unique chemical structures, optical properties, and their potential applications in various areas, such as cellular imaging and chemical sensing. However, most reported NLMs show weak or no emission in dilute solutions, which severely limits their applications. In this work, dynamic hydrogen bonds were utilized to design NLMs with efficient emission in dilute solutions. To further validate the results, polymers P1 and P2 were successfully prepared and investigated. It was found that the luminescence quantum efficiency of P1 and P2 at a concentration of 0.1 mg/mL in water solution was 8.9 and 0.6%, respectively. The high efficiency can be attributed to the fact that polymer P1 has more intra- or intermolecular dynamic hydrogen bonds and other short interactions than P2 in dilute solutions, allowing P1 to achieve the through-space conjugation effect to increase the degree of system conjugation, restrict molecular motion, and decrease nonradiative transitions, which can effectively improve luminescence. In addition, polymer P2 exhibits the characteristics of clustering-triggered emission, excitation wavelength-dependent and concentration-dependent fluorescence properties, excellent photobleaching resistance, low cytotoxicity, and selective recognition of Fe3+. The present study investigates the manipulation of luminescence properties of NLMs in dilute solutions through the modulation of dynamic hydrogen bonds. This approach can serve as a semi-empirical technique for designing and building innovative NLMs in the times ahead.

An Application of Spherical Cavity Expansion Theory in Soft Rock Pile-Base Resistance

The failure mode should be taken into account in the analytical solution for pile base resistance. In order to determine the pile’s failure pattern in soft rock, the graphical model test method is used. That the compression zone below the pile base in soft rock is compatible with the spherical cavity expansion is shown. An improved calculation model for the ultimate base resistance may be developed by considering the force balance of the rigid cone under the pile-end in the ultimate stress state and the limit pressure required to expand a spherical cavity. To account for the influence of socket length, the limiting pressure for the spherical cavity expansion in infinite space is adjusted to that in semi-infinite space. The ultimate resistance of a base is computed by factoring in the length effect. The normalization of the base resistance-displacement relation is provided based on the findings of pressure chamber experiments on pile load-settlement, which are independent of socket length and overburden pressure. This semi-empirical technique is verified via the use of pressure chamber experiments and field testing of piles in soft rock.

Solvent-controlled formation of alkali and alkali-earth-secured cucurbituril/guest trimers.

Cucurbit[7]uril (CB[7]) encapsulates adamantyl and trimethylsilyl substituents of positively charged guests in dimethyl sulfoxide (DMSO). Unlike in water or deuterium oxide, addition of a selection of alkali and alkali-earth cations with van der Waals radii between 1.0 and 1.4 Å (Na+, K+, Ca2+, Sr2+, Ba2+ and Eu3+) to the CB[7]/guest complexes triggers their cation-mediated trimerization, a process that is very slow on the nuclear magnetic resonance (NMR) time scale. Smaller (Li+, Mg2+) or larger cations (Rb+, Cs+ or NH4+) are inert. The trimers display extensive CH-O interactions between the equatorial and pseudo-equatorial hydrogens of CB[7] and the carbonyl rim of the neighboring CB[7] unit in the trimer, and a deeply nested cation between the three interacting carbonylated CB[7] rims; a counteranion is likely perched in the shallow cavity formed by the three outer walls of CB[7] in the trimer. Remarkably, a guest must occupy the cavity of CB[7] for trimerization to take place. Using a combination of semi-empirical and density functional theory techniques in conjunction with continuum solvation models, we showed that trimerization is favored in DMSO, and not in water, because the penalty for the partial desolvation of three of the six CB[7] portals upon aggregation into a trimer is less unfavorable in DMSO compared to water.

Напівемпіричне оцінювання акустичних навантажень на головну частину ракети при нестандартній конфігурації стартових споруд

The paper deals with assessing the acoustic loads on the surface of a launching rocket obtained using the semiempirical technique NASA SP-8072 adapted for a launch pad located above the water area. The features of the launch facilities include the reduced length of the gas duct and the presence of a wedge-shaped gas-dynamic deflector divided into two symmetrical oppositely directed slopes. The calculations are made with the allowance for the limited length of the rocket jet's laminar core during take-off due to interaction with the gas-dynamic deflector. A corrected dependence is used for the overall acoustic energy distribution along the supersonic jet for the first time in domestic practice. The contributions of the sound sources associated with different jet sections and acoustic reflection from the water surface are assessed, depending on the current height of the rocket lift. A significant dependence of the resulting acoustic field around the rocket head on the length of the horizontal section of the gas duct is noted.

Application of The Computational Semi-Empirical Method in Calculating The Fission Yield with Reference to The JENDL Data

Fission Yield calculation techniques can be completed in various ways. In this work, other calculation techniques will be described. Namely, a semi-empirical technique that utilizes random numbers. This semi-empirical method can produce fitting parameters to obtain other physical quantities. Because it uses a random number initiator, computations can be completed in parallel. Therefore, the computation time is shorter. This paper will show in sequence the steps of this technique. The calculation begins by assigning a value to the incident energy and random position of the nucleons, and then ends after fission products occur. This paper only describes the process of calculating the Fission Yield for several U isotopes.

Landslide Hazard Assessments of A Potential Earthquake-triggered in Central Taiwan Using Newmark's Model with the Stochastic Semi-Empirical Technique

This research aims to evaluate the probability distribution of landslides triggered by a potential earthquake. Based on the evaluations, successive disaster prevention and mitigation can be well-prepared in advance. Deriving the critical acceleration value depends on the geometry and strength of the material on the slope. Thus, the Newmark's displacement of slope can be determined using the critical acceleration and strong motion recording of an earthquake. A threshold value of Newmark's displacement is assumed as 5cm, which means a landslide may occur if Newmark's displacement is greater than it. To identify the feasibility, we synthesize two waveforms of the 1999 Chi-Chi earthquake (M_w 7.6) and one for the 2013 Nantou earthquake (M_w 6.2) to compute the Newmark's displacements at Jiou-Jiou Peaks and Shinyi town in Nantou County, Taiwan by using the stochastic semi-empirical technique. The Newmark's displacements are 9.75 averaged and 6cm respectively, which are coincident with the earthquake-triggered landslides occurring actually. By counting accumulations of Coulomb's stress changes of Nantou earthquakes in 2013 in central Taiwan, we predict the epicenter of a potential earthquake. The regression relation between critical acceleration with Arias intensity of the seismic waveform is employed to calculate Newmark's displacements in the Nontou County. Accompanied by Newmark's displacement, the empirical probabilities of earthquake-induced landslides are derived. Accordingly, there are four populated densely areas with higher Newmark's displacements and probabilities, indicating that high landslide risk is existing potentially in these areas and the corresponding disaster prevention management and mitigation must be carefully regulated.

Physical Modeling, Simulation and Validation of Small Fixed-Wing UAV

The flight dynamics of small Unmanned Aerial Vehicles (UAVs) exhibits substantial nonlinear features which should not be ignored in simulation or analysis. In this work, a complete six degrees of freedom (6DOF) and high-fidelity simulation model of a case study of a small fixed-wing UAV is developed. To accurately estimate the nonlinear UAV’s mathematical model, the mass-inertia properties are investigated through experiments. Moreover, the aerodynamic model characteristics are estimated using a semi-empirical technique to estimate the aerodynamic coefficients and derivatives. The propulsion system’s physical characteristics are estimated and analyzed through experimental measurements. The International Standard Atmosphere (ISA) tables are used to develop the atmospheric model. Furthermore, the actuation model is estimated and validated experimentally through system identification techniques. These estimated sub-model data are integrated to complete the nonlinear flight dynamics model in MATLAB® (Simulink). The UAV trim calculations are graphically derived and then the developed model is tested and verified. The open loop simulation results have proved the superiority of the utilized model techniques to describe the UAV motion. Moreover, it gives very optimistic results to test the flight dynamics of the UAV and design a consistent flight control and guidance system.

A Technique for Metallic Waste Characterization and Segregation in Management Routes

Adequate radiological characterization is important for optimization of metallic waste management. For decommissioning planning, the objective is to obtain a radiological understanding of the involved installation. The characterization at this stage could be carried out by means of: 1) neutron activation calculations based on reactor design and neutron flux; 2) dose rate measurements; 3) in-situ gamma spectrometry; 4) sampling for determination of the scaling factors in activated and contaminated components. During dismantling, in-situ characterization is carried out to classify and package the generated waste. Then, the packages are monitored for assessment of activity and determination of the management route. The selection of cutting and decontamination techniques should be based on accurate determination of the radionuclides inside the material and/ or on the surface contamination. . It is important to decide in which cases the decontamination will be efficient as well as to select the appropriate decontamination techniques based on whether the waste is slightly activated or contaminated or both. Α Semi-empirical technique for optimization of determination of contamination and activation of components and metallic waste is under development based on combination of gamma spectrometry measurements and MCNPX Monte Carlo simulations. Firstly, the technique aims at reduction of the uncertainties related to the density and activity distribution. The specific activities inside and on the surface of the materials could be determined by using the measurement results of the proposed non-destructive technique in combination with the use of the scaling factors for activation and/ or contamination.

Estimation of the number density of active cavitation bubbles in a sono-irradiated aqueous solution using a thermodynamic approach

An alternative semi-empirical technique is developed to determine the number density of active cavitation bubbles (N) formed in sonicated solutions. This was achieved by relating the acoustic power supplied to the solution (i.e., determined experimentally) to the released heat by a single bubble. The energy dissipation via heat exchange is obtained by an advanced cavitation model accounting for the liquid compressibility and viscosity, the non-equilibrium condensation/evaporation of water vapor, and heat conduction across the bubble wall and heats of chemical reactions resulting within the bubble at the collapse. A good concordance was observed between our results and those found in the literature. It was found that the number of active bubbles increased proportionally with a rise in ultrasound frequency. Additionally, the increase of acoustic intensity increases the number of active bubbles, whatever the sonicated solution's volume. On the other hand, it was observed that the rise of the irradiated solution volume causes the number of active bubbles to be reduced even when the acoustic power is increased. A decrease in acoustic energy accelerates this negative impact.

Structural Significance of Conformational Preferences and Ribose-Ring-Puckering of Hyper Modified Nucleotide 5'-Monophosphate 2-Methylthio Cyclic N6-Threonylcarbamoyladenosine (p-ms2ct6A) Present at 37th Position in Anticodon Loop of tRNALys.

Structural significance of conformational preferences and ribose ring puckering of newly discovered hyper modified nucleotide, 5'-monophosphate 2-methylthio cyclic N6-threonylcarbamoyladenosine (p-ms2ct6A) have been investigated using quantum chemical semi-empirical RM1 and molecular dynamics simulation techniques. Automated geometry optimization of most stable structure of p-ms2ct6A has also been carried out with the help of abinitio (HF SCF, DFT) as well as semi empirical quantum chemical (RM1, AM1, PM3, and PM6) methods. Most stable structure of p-ms2ct6A is stabilized by intramolecular interactions between N(3)…HC(2'), N(1)…HC(16), O(13)…HC(15), and O(13)…HO(14). The torsion angles alpha (α) and beta (β) show the significant characteristic patterns with the involvement of intramolecular hydrogen bonding to provide stability to the p-ms2ct6A. Further, molecular dynamics simulations of p-ms2ct6A revealed the role of ribose sugar ring puckering i.e. C2'-endo and C3'-endo on the structural dynamics of ms2ct6A side chain. The modified nucleotide p-ms2ct6A periodically prefers both the C2'-endo and C3'-endo sugar with 'anti' and 'syn' conformations. This property of p-ms2ct6A could be useful to recognize the starting ANN codons. All atom explicit MD simulation of anticodon loop (ACL) of tRNALys of Bacillus subtilis containing ms2ct6A at 37th position showed the U-turn feature, base stacking ability with other adjacent bases and hydrogen bonding interactions similar to the isolated base p-ms2ct6A. The ribose sugar puckering contributes to the orientation of the side chain conformation of p-ms2ct6A. Thus, the present study could be helpful to understand the structure-function relationship of the hypermodified nucleoside, ms2ct6A in recognition of the proper codons AAA/AAG during protein biosynthesis.

A Comprehensive Review on the Characteristics and Modeling of Lithium-Ion Battery Aging

Battery aging is one of the critical problems to be tackled in battery research, as it limits the power and energy capacity during the battery’s life. Therefore, optimizing the design of battery systems requires a good understanding of aging behavior. Due to their simplicity, empirical and semiempirical models (EMs) are frequently used in smart charging studies, feasibility studies, and cost analyses studies, among other uses. Unfortunately, these models are prone to significant estimation errors without appropriate knowledge of their inherent limitations and the interdependence between stress factors. This article presents a review of empirical and semiempirical modeling techniques and aging studies, focusing on the trends observed between different studies and highlighting the limitations and challenges of the various models. First, we summarize the main aging mechanisms in lithium-ion batteries. Next, empirical modeling techniques are reviewed, followed by the current challenges and future trends, and a conclusion. Our results indicate that the effect of stress factors is easily oversimplified, and their correlations are often not taken into account. The provided knowledge in this article can be used to evaluate the limitations of aging models and improve their accuracy for various applications.

Revised semi-empirical aerodynamic estimation for modelling flight dynamics of an airship

Modelling of dynamics of an airship is essential in the prediction of the flight characteristics, stability analysis and the design of control laws for autonomous operation. In the dynamics model that was proposed by Ashraf and Choudhry [1], deviations were observed between the simulation results and the validation data since the lengths and areas associated with the calculation of aerodynamic coefficients were not normalised. This paper documents the revisions proposed to the incorporation of semi-empirical aerodynamic estimation technique in the dynamics modelling of an airship as well as the normalisation of aerodynamic coefficients. Simulations are performed on the revised airship dynamics model and are compared with the simulation results of preceding models. A satisfactory agreement is seen between the revised model and the validation data, both in terms of magnitude and trends.

Machine learning based approach for phase prediction in high entropy borides

The current investigation uses a novel data-driven machine learning (ML) technique to provide the appropriate phase structures of multicomponent high entropy diborides. In the absence of sufficient experimental data for higher order diborides, the semi-empirical technique was first used to create the dataset using structure plots and develop a k-Nearest Neighbour (kNN) algorithm based classification model based on many structural and thermodynamic characteristics. Correlation analysis shows that the input feature space is suitable to model HEC compositions for the current dataset. Furthermore, testing accuracy of ∼ 90% and excellent performance of other model evaluation metrics showed that the trained kNN model could further predict both quaternary and quinary high entropy diborides. A high F1 score (= 0.941) denotes low false positives and low false negatives for the trained model, which reciprocates how well the model predicts true values. The examination of the predicted compositions indicates that the ML framework developed can use the trend learned from the structure plot along with the available data from the literature to make reasonable predictions. ML with new data can be a reliable design method for the phase prediction in high entropy ceramics without requiring any prior experiments.