Second-order Interaction Research Articles

Wave- and drag-driven subharmonic responses of a floating wind turbine

The nonlinear hydrodynamic responses of a novel spar-type soft-moored floating offshore wind turbine are investigated via analysis of motion measurements from a wave-basin campaign. A prototype of the TetraSpar floater, supporting a$1:60$scale model of the DTU 10 MW reference wind turbine, was subjected to irregular wave forcing (with no wind) and shown to exhibit subharmonic resonant motions, which greatly exceeded the wave-frequency motions. These slow-drift responses are excited nonlinearly, since the rigid-body natural frequencies of the system lie below the incident-wave frequency range. Pitch motion is examined in detail, allowing for identification of different hydrodynamic forcing mechanisms. The resonant response is found to contain odd-harmonic components, in addition to the even harmonics expecteda prioriand excited by second-order difference-frequency hydrodynamic interactions. Data analysis utilising harmonic separation and signal conditioning suggests that Morison drag excitation or third-order subharmonic potential flow forcing could be at play. In the extreme survival-conditions sea state, the odd resonant responses are identified to be drag-driven. Their importance for the tested floater is appreciable, as their magnitude is comparable to the second-order potential flow effects. Under such severe conditions, the turbine would not be operating, and as such neglecting aerodynamic forcing and motion damping is likely to be reasonable. Additionally, other possible drivers of the resonant pitch response are explored. Both Mathieu-type parametric excitation and wavemaker-driven second-order error waves are found to have negligible influence. However, we note slight contamination of the measurements arising from wave-basin sloshing.

Equity Market Description under High and Low Volatility Regimes Using Maximum Entropy Pairwise Distribution.

The financial market is a complex system in which the assets influence each other, causing, among other factors, price interactions and co-movement of returns. Using the Maximum Entropy Principle approach, we analyze the interactions between a selected set of stock assets and equity indices under different high and low return volatility episodes at the 2008 Subprime Crisis and the 2020 COVID-19 outbreak. We carry out an inference process to identify the interactions, in which we implement the a pairwise Ising distribution model describing the first and second moments of the distribution of the discretized returns of each asset. Our results indicate that second-order interactions explain more than 80% of the entropy in the system during the Subprime Crisis and slightly higher than 50% during the COVID-19 outbreak independently of the period of high or low volatility analyzed. The evidence shows that during these periods, slight changes in the second-order interactions are enough to induce large changes in assets correlations but the proportion of positive and negative interactions remains virtually unchanged. Although some interactions change signs, the proportion of these changes are the same period to period, which keeps the system in a ferromagnetic state. These results are similar even when analyzing triadic structures in the signed network of couplings.

Toxicity inhibition strategy of microplastics to aquatic organisms through molecular docking, molecular dynamics simulation and molecular modification

In the present study, the combined toxic effect of microplastics and their additives (five) on aquatic organisms (zebrafish) was studied using full factorial design method, molecular docking, and molecular dynamics (MD) simulation technology. The aquatic toxicity control programmer was designed to improve the optimal combination of plasticizer and microplastics based on the design of environment-friendly phthalic acid ester (PAE) derivatives. First, a total of 64 groups of microplastic-additives were designed using the full factorial design method. Next, the microplastic-additives and aquatic receptor protein were docked together, and the binding energy of these complexes was calculated using the MD simulation method. The results revealed that the aquatic toxicity effects of different microplastic-additive combinations were variable; therefore, the optimal combination of microplastics exhibiting the lowest aquatic toxicity effect could be screened out. Base on the analyzing the bonding effect and surrounded amino acid residues between the microplastic additives and receptor protein, the main driving forces for the binding of the microplastic-additive and the protein were hydrophobic force, hydrogen bonding force and electrostatic force. The main effects and the second-order interaction of the microplastic-additives combination were analyzed using the fixed-effect model. The main additives that affect the aquatic toxicity of the microplastics can be known. In addition, based on the MD simulation of the molecular replacement of PAE derivatives, the optimal level of component combination of low aquatic toxicity effect of microplastics was constructed.

Rotational spectrum of chloroform, “grass-roots among the forest of trees”: The v2 = 1, v3 = 2, v5 = 1, and v6 = 3 vibrational states of CH35Cl3

We have recently analyzed the broadband millimeter-wave rotational spectrum of chloroform CH35Cl3 in the v3 = v6 = 1 (E symmetry) and v6 = 2 (A1 + E) excited vibrational states . In the present work, we have used the same spectrum (recorded in the 150 - 330 and 360–660 GHz spectral regions) for a rotational analysis of the v2 = 1 and v3 = 2 A1 states of the same molecule, together with a new analysis of the v5=1 (E) fundamental vibration.For the v2 = 1 state (A1, near 677 cm−1), the body of assigned data comprises 392 rotational transitions. The corresponding frequencies were fitted within an isolated-level model, with a standard deviation of 36.4 kHz, and the obtained parameters are in good agreement with the previous IR work.For the v3 = 2 vibrational state (A1, near 734 cm−1), a total of 351 rotational transitions were assigned. Their fit was improved by inclusion of a second-order Coriolis coupling term with the v5 = 1 fundamental level, providing standard deviation of 40.2 kHz.At the same time, the description of the v5 = 1 vibration (E symmetry, 776 cm−1), studied previously with high-resolution as an isolated level, was also improved. The quantitative interpretation of the newly assigned 612 MMW data and the significantly extended set of IR assignments necessitated the introduction of the second-order Coriolis interaction with v3 = 2, but more importantly of an anharmonic interaction with the v6 = 3 (A1 + A2 + E, near 782 cm−1) level. For this latter level more than 200 rotational transitions, together with several series of rovibrational transitions, could finally be assigned and included in the fit.

Utilization Efficiency of Growth Regulators in Wheat under Drought Stress and Sandy Soil Conditions

Drought stress and nutrient status are highly important for plant growth and productivity. Two field experiments were conducted during two consecutive seasons (2017–2018 and 2018–2019) at El-Molak, Abo-Hammad, Sharkia, Egypt. This work was conducted under sandy soil conditions to evaluate the effects of foliar application with growth regulators (PGRs) such as cycocel (CCC), applied at 0, 500, or 1000 mg L−1, and/or salicylic acid (SA), applied at 0, 0.05, or 0.1 mM on the productivity as well as improving drought tolerance of three wheat cultivars, i.e., Gemmeiza 11, Misr 1, and Giza 171 under three irrigation intervals, i.e., 10, 15, and 20 days. Foliar spray was given at 35 and 50 days after planting (DAP). The obtained results showed that mean squares as a result of the main effect and first- and second-order interactions were significant (p ≤ 0.01) for all studied traits. The application of SA increased total chlorophyll content and flag leaf area (cm2) while the number of days to 50% heading was decreased; however, the number of spikes m−2, protein and proline contents were increased with the application of CCC. The cultivar Misr 1 outperformed the other cultivars in the most studied traits. Estimates of heritability in the broad sense (h2b) were, on average, higher in five physiological traits than other agronomic traits, and the highest estimate of h2b (95.1%) was shown by the number of days to 50% heading followed by protein content (91.90%). Among the interactions between irrigation and growth regulators, the I(10) × SA(0.1) recorded the highest flag leaf area (cm2), SPAD value, number of grains spike−1, 1000-grain weight (g), and grain yield (t ha−1). Among the interactions between irrigation and cultivars, the I(10) × Misr 1 recorded the highest flag leaf area (cm2), SPAD value, number of grains spike−1, and grain yield (t ha−1). Among the interactions among irrigation, growth regulators and cultivars, the I(10) × SA(0.1) × Misr 1 recorded the highest flag leaf area (cm2), number of grains spike−1, 1000-grain weight (g), and grain yield (t ha−1). Correlation coefficient between grain yield (t ha−1) and each of the number of days to 50% heading, flag leaf area, total chlorophyll content, number of spikes m−2, number of grains spike−1, and 1000-grain weight was positive and significant. Three main factors for the studied variables were created from the application of the factor analysis technique. Grain yield ha−1 (Y) can be predicted by the method of forwarding stepwise through applying the automatic linear regression analysis. Besides, the best prediction equation of grain yield ha−1 (Y) was formulated as: Ỷ = −14.36 + 0.11 number of grains spike−1 (NGS) + 0.09 1000-grain weight (THW) + 0.04 number of spike m−2 (NSm) + 0.03 days to 50% heading (DF) + 0.02 total chlorophyll content (TC) with adjusted-R2 (87.33%).

Fundamental vibrational frequencies of isolated 2-phosphaethynolate and 2-phosphaethynthiolate anions: OCP– and SCP–

Both second-order vibrational perturbation theory (VPT2) and vibrational configuration interaction (VCI) theory have been employed to compute the fundamental vibrational frequencies of the isolated 2-phosphaethynolate and 2-phosphaethynthiolate anions (OCP and SCP) near the CCSD(T) complete basis set (CBS) limit. Our best estimates of the fundamental frequency associated with the doubly degenerate bending mode of these linear triatomic ions () are 492 cm for OCP and 362 cm for SCP. Due to strong coupling, the stretching motions of SCP are best described as pseudo-symmetric () and pseudo-antisymmetric () stretches that we estimate to be 588 cm and 1367 cm, respectively. For OCP, our best predictions are 792 cm for and 1795 cm for , with the latter having predominantly CO stretching character. In the absence of experimental gas-phase vibrational spectra for these species, these computed anharmonic frequencies provide important reference values to help quantify spectroscopic perturbations induced by environmental effects such as those from solvents or counter ions.

Implementation and Performance Evaluation of a Bivariate Cut-HDMR Metamodel for Semiconductor Packaging Design Problems with a Large Number of Input Variables

A metamodeling technique based on Bivariate Cut High Dimensional Model Representation (Bivariate Cut HDMR) is implemented for a semiconductor packaging design problem with 10 design variables. Bivariate Cut-HDMR constructs a metamodel by considering only up to second-order interactions. The implementation uses three uniformly distributed sample points (s = 3) with quadratic spline interpolation to construct the component functions of Bivariate Cut-HDMR, which can be used to make a direct comparison with a metamodel based on Central Composite Design (CCD). The performance of Bivariate Cut-HDMR is evaluated by two well-known error metrics: R-squared and Relative Average Absolute Error (RAAE). The results are compared with the performance of CCD. Bivariate Cut HDMR does not compromise the accuracy compared to CCD, although the former uses only one-fifth of sample points (201 sample points) required by the latter (1045 sample points). The sampling schemes and the predictions of cut-planes and boundary-planes are discussed to explain possible reasons for the outstanding performance of Bivariate Cut HDMR.

Isotope shifts for S01−P0,1o3 Yb lines from multiconfiguration Dirac-Hartree-Fock calculations

Relativistic multiconfiguration Dirac-Hartree-Fock calculations with configuration interaction are carried out for the $^{1}S_{0}$ and $^{3}P_{0,1}^{o}$ states in neutral ytterbium by use of the available grasp2018 package. From the resultant atomic state functions and the ris4 program, we evaluate the mass- and field-shift parameters for the $^{1}S_{0}\ensuremath{-}\phantom{\rule{0.16em}{0ex}}^{3}P_{0}^{o}$ (clock) and $^{1}S_{0}\ensuremath{-}\phantom{\rule{0.16em}{0ex}}^{3}P_{1}^{o}$ (intercombination) lines. We present improved estimates of the nuclear charge parameters ${\ensuremath{\lambda}}^{A,{A}^{\ensuremath{'}}}$ and differences in mean-square charge radii $\ensuremath{\delta}{\ensuremath{\langle}{r}^{2}\ensuremath{\rangle}}^{A,{A}^{\ensuremath{'}}}$ and examine the second-order hyperfine interaction for the $^{3}P_{0,1}^{o}$ states. Isotope shifts for the clock transition have been estimated by three largely independent means from which we predict the unknown clock-line frequencies in bosonic Yb isotopes. Knowledge of these line frequencies has implications for King-plot nonlinearity tests and the search for beyond-standard-model signatures.

A second-order three-wave interaction system and its rogue wave solutions

A second-order three-wave interaction system and its rogue wave solutions

Silicon-nitride microring resonators for nonlinear optical and biosensing applications.

We discuss the design, fabrication, and characterization of silicon-nitride microring resonators for nonlinear-photonic and biosensing device applications. The first part presents new theoretical and experimental results that overcome highly normal dispersion of silicon-nitride microresonators by adding a dispersive coupler. The latter parts review our work on highly efficient second-order nonlinear interaction in a hybrid silicon-nitride slot waveguide with nonlinear polymer cladding and silicon-nitride microring application as a biosensor for human stress indicator neuropeptide Y at the nanomolar level.

Experimental and theoretical electronic absorption spectra, optical, photoelectrical characterizations of 1, 2, 3-Thiazaphosphinine and 1, 2-Azaphospholes bearing a chromone ring: Solvatochromic effect and TD/DFT approach

Geometry, global energetic and dipole moment of the studied structures 1-4 in the ground state are calculated using the DFT/B3LYB/6-311++G (d,p) level of theory. It has been uncovered that compounds containing 1, 2, 3-thiazaphosphinine and 1, 2-azaphospholes bearing a Chromone ring structure displays noteworthy biological properties. The studied compounds 1-4 are non-planar, as indicated from the dihedral angles. Using frontier molecular orbital (FMO) analysis, various spectroscopic and quantum chemical parameters are evaluated. Besides, absorption energies, oscillator strength, and electronic transitions of 1, 2, 3-thiazaphosphinine and 1, 2-azaphospholes 1-4 molecules have been derived at TD-DFT/CAM-B3LYP/6-311++G (d, p) computations utilizing a PCM and measured in different solvents polar and non-polar experimentally in Uv-Vis spectra. The second-order perturbation interactions between donor and acceptor MOs of the ground state and the natural bond orbital (NBO) analysis show a localization and delocalization of electron density, intermolecular Charge Transfer CT character of n-π*, π-π* transitions. The calculated at the same level of theory which NLO, α, Δα and first order β were showed promising optical properties. For the understanding of reactivity points, the molecular electrostatic potential surfaces (MEPS) plots have been computed. All the calculations have been performed in the gas phase.

Origin of terahertz excitations in single-crystalline lead substituted M-type barium hexaferrite doped with Al

Single-crystalline lead substituted M-type barium hexaferrites doped with different concentrations of Al3+, synthesized by flux technique are investigated at terahertz and infrared frequencies (8-8000 cm−1). The spectra of reflection coefficient (R), transmission coefficient (T), complex dielectric permittivity (ε` and ε``) were obtained using terahertz time-domain, and infrared Fourier transform spectrometers over a broadband frequency range 0.24-240 THz and at temperatures 5 K-300 K. The observed absorption lines are assigned to the electronic transitions within the fine-structured ground state of Fe2+ ions at terahertz frequencies and to optical phonon mode at far-infrared frequencies. To analyze the origin of terahertz excitations in the compounds, we provided a model that accounts for the second-order spin-orbit interactions, the triagonal distortion of the crystal field, and the selection rules of the (C3v) point group symmetry of tetrahedral site-position of Fe2+.

DETERMINING NOMINAL VALUES OF INPUT PARAMETERS FOR PRODUCTION PROCESS USING DOE

Application of statistical methods in quality improvement of molded parts is presented in this paper. Implementation of two stages of DMAIC improvement cycle in a pre-production process is analysed in detail. DOE method is performed to define nominal values of process parameters of injection molding process. A fraction-factorial design with a single central point is used. A linear mathematical model with included elements of second-order interaction is defined. Finally, control stage is performed using prior defined nominal values. Process capability test is conducted in order to determine whether the process is capable of producing parts within specified tolerance field.

Optimization of the Electrospun Niobium-Tungsten Oxide Nanofibers Diameter Using Response Surface Methodology.

The present research aimed to investigate the effect of working parameters on the electrospinning of niobium–tungsten oxide nanofibers and optimize the process using central composite design (CCD) based on the response surface methodology (RSM). An experiment was designed to assess the effects of five variables including the applied voltage (V), spinning distance (D), polymer concentration (P), flow rate (F), and addition of NaCl (N) on the resulting diameter of the nanofibers. Meanwhile, a second-order prediction model of nanofibers diameter was fitted and verified using analysis of variance (ANOVA). The results show that the diameter of the nanofibers was significantly influenced by all the variables except the flow rate. Some second-order and cross factor interactions such as VD, DP, PF, PN, and P2 also have significant effects on the diameter of the nanofibers. The results of the ANOVA yielded R2 and adjusted R2 values of 0.96 and 0.93 respectively, this affirmed that the predictive model fitted well with the experimental data. Furthermore, the process parameters were optimized using the CCD method and a maximum desirability function of 226 nm was achieved for the diameter of the nanofibers. This is very close to the 233 nm diameter obtained from a confirmatory experiment using the optimum conditions. Therefore, the model is representative of the process, and it could be used for future studies for the reduction of the diameter of electrospun nanofibers.

Binder Jetting of Silicon Steel, Part I: Process Map of Green Density

Abstract This study focuses on developing and demonstrating a straightforward workflow for identifying pathways to increase green part density in binder jetting additive manufacturing (BJAM) using statistically driven process maps. The workflow was applied to investigate the effects of process parameters toward improving green part density, with a direct application in manufacturing of Fe-Si components. Specifically, a half-factorial experimental design was used to study the effects of four key parameters—layer thickness, powder spreading speed, roller rotational speed, and binder saturation—on Fe-Si spherical powder with D50 of 32.40 µm. Relative bulk density was estimated via three methods: geometrical and mass measurements, the Archimedes test, and CT imaging. The study discusses relative bulk density as well as localized density variation in the printed parts, which is attributed to both parameter selection and inherent process variability. A regression analysis was used to reveal the significance of main effects and second-order interactions. The regression model (R2 = 0.915) was used to derive an expression for green density as a function of the parameters and had a prediction error of 0.96%. Based on the regression model, an optimized set of parameters was obtained that would maximize green density up to 57.96% for the machine and material system.

New branding for Metso Outotec

Simulation of non-Darcian Casson flow subject to a second-order velocity slip and heat transfer due to nanofluid over a permeable stretching surface is exemplified numerically. The second-order velocity slip interaction is quite different from the first-order velocity slip as it results in two slip parameters that can effectively regulate the boundary layer development. To the best of the authors’ knowledge, this parameter was here incorporated for the first time in such a field of radiative Casson nanofluid flow. The model, which is governed by the system of PDEs, accomplishes the Chebyshev collocation Method (CCM). It is vital to remark that the account for the second-order slip velocity in the boundary conditions decreases the velocity component. In addition, the role of (Prandtl-number = 7 water) on the Skin friction coefficient becomes more significant when the Variable viscosity increases compared to the (Prandtl-number = 0.71 air). Also, non-Newtonian Casson fluid parameter show a solid characteristic when yield stress is more than the shear stress. Consequently, those parameters contribute to the cooling plate, while others have the opposite effect. Therefore, the cooling/heating mechanism can be developed with appropriate Casson fluid model and the control parameter. At last, this article includes some future recommendations.

Extended residual coherence with a financial application

Abstract Residual coherence is a graphical tool for selecting potential second-order interaction terms as functions of a single time series and its lags. This paper extends the notion of residual coherence to account for interaction terms of multiple time series. Moreover, an alternative criterion, integrated spectrum, is proposed to facilitate this graphical selection. A financial market application shows that new insights can be gained regarding implied market volatility.

Coherent phonon detection gated by transient spin-polarized electrons

Manipulating electron spins on ultrashort timescales shows promise in the field of data processing. Because of the direct electron-photon coupling, photons have been widely used for such studies, but not phonons. Here we tie coherent phonon detection to transient spin populations. We optically excite gigahertz picosecond phonon wave packets in a metal-coated GaAs slab containing $\mathrm{GaAs}\text{/}{\mathrm{Al}}_{0.4}{\mathrm{Ga}}_{0.6}\mathrm{As}$ multiple quantum wells on the opposite side. Before the phonon wave-packet arrival, circularly polarized light induces a transient spin polarization. Phonon-induced ultrafast polarization rotation and reflectivity changes contingent on the transient spin population are detected by a heterodyne modulation technique. With an analytical model, we posit the presence of significant second-order interactions, enabled by spins, in the coherent-phonon optical detection. Applications include transient spin population monitoring and novel spintronic nanodevices.

A Theory of Higher Order Interactions Between Sensitive Variables: Empirical Evidences and an Application to a Variety of Smoking

In carrying out surveys involving sensitive characteristics, randomized response models have been considered among the best techniques since they provide the maximum privacy protection to the respondents and procure honest responses. Over the years, researchers have carried out studies on the estimation of proportions of the population possessing sensitive characteristics. However, there is a paucity of research studies that have addressed higher order interactions between these sensitive characters. In this article, we develop a new theory based on three proposed randomized response models which we name as: simple model, semi-crossed model, and fully crossed model. Twenty-one new unbiased estimators of seven parameters are introduced, their variance expressions are derived, and unbiased estimators of variances are developed. The three models are compared under various values of the parameters by computing the percent relative efficiency of one model over another model. The most efficient model is then applied to study the population proportions of three varieties of smoking habits among students, and their first- and second-order interactions. The last four sections (Ninth to Twelfth) are verifications of theoretical results using the Cramer–Rao lower bounds of variances for the developed 21 new estimators in randomized response sampling.

Variance-based global sensitivity analysis and beyond in life cycle assessment: an application to geothermal heating networks

PurposeGlobal sensitivity analysis increasingly replaces manual sensitivity analysis in life cycle assessment (LCA). Variance-based global sensitivity analysis identifies influential uncertain model input parameters by estimating so-called Sobol indices that represent each parameter’s contribution to the variance in model output. However, this technique can potentially be unreliable when analyzing non-normal model outputs, and it does not inform analysts about specific values of the model input or output that may be decision-relevant. We demonstrate three emerging methods that build on variance-based global sensitivity analysis and that can provide new insights on uncertainty in typical LCA applications that present non-normal output distributions, trade-offs between environmental impacts, and interactions between model inputs.MethodsTo identify influential model inputs, trade-offs, and decision-relevant interactions, we implement techniques for distribution-based global sensitivity analysis (PAWN technique), spectral clustering, and scenario discovery (patient rule induction method: PRIM). We choose these techniques because they are applicable with generic Monte Carlo sampling and common LCA software. We compare these techniques with variance-based Sobol indices, using a previously published LCA case study of geothermal heating networks. We assess eight environmental impacts under uncertainty for three design alternatives, spanning different geothermal production temperatures and heating network configurations.ResultsIn the application case on geothermal heating networks, PAWN distribution-based sensitivity indices generally identify influential model parameters consistently with Sobol indices. However, some discrepancies highlight the potentially misleading interpretation of Sobol indices on the non-normal distributions obtained in our analysis, where variance may not meaningfully describe uncertainty. Spectral clustering highlights groups of model results that present different trade-offs between environmental impacts. Compared to second-order Sobol interaction indices, PRIM then provides more precise information regarding the combinations of input values associated with these different groups of calculated impacts. PAWN indices, spectral clustering, and PRIM have a computational advantage because they yield stable results at relatively small sample sizes (n = 12,000), unlike Sobol indices (n = 100,000 for second-order indices).ConclusionsWe recommend adding these new techniques to global sensitivity analysis in LCA as they give more precise as well as additional insights on uncertainty regardless of the distribution of the model outputs. PAWN distribution-based global sensitivity analysis provides a computationally efficient assessment of input sensitivities as compared to variance-based global sensitivity analysis. The combination of clustering and scenario discovery enables analysts to precisely identify combinations of input parameters or uncertainties associated with different outcomes of environmental impacts.