Search

Mitigation of combustion instability of solid propellant rocket motors is ever being attempted by several researchers as the problem is very complicated in nature. The acoustic admittance of composite solid propellants (AP/HTPB/RDX/Al) is experimentally investigated using Impedance tube technique. It is one of the indirect experimental techniques to determine the combustion response of the solid propellants besides T-burner. The governing equations based on the conservation of mass, momentum and energy (reactive flow is simplified to have only the axial temperature gradient) are linearized and solved to determine the acoustic admittance of the burning propellant. Different methods of analysis were explored to validate/compare the results obtained and are matching well. Some of the unreported details of the analysis are brought out. A novel way of utilizing the outer tube besides the inner tube as against the literature (wherein the inner tube is kept inside the outer tube) to maintain the chamber pressure is explored. A test conducted at fundamental acoustic mode (110 Hz) at 2 MPa at room temperature (303 K) is considered for the analysis. A rotary valve capable of operating up to a mean chamber pressure of 12 MPa is developed in this work to act as an acoustic driver for the experiments. The advantage of the impedance tube technique over T-burner is that the former is capable of measuring both the real and imaginary part of combustion response whereas the latter can only measure the real part. The imaginary part of the combustion response besides the real part is useful to predict the stability characteristics of the solid propellant rocket motor. [ABSTRACT FROM AUTHOR]

We propose a modification of the algorithm aimed at the construction of analytic solutions of plane axisymmetric problems of elasticity and thermoelasticity in stresses for solid cylinders formed by radially inhomogeneous coaxial layers. Unlike the original approach based on the application of the method of direct integration and the procedure of generalized differentiation, the proposed modification makes it possible to formulate and solve the governing equations of problems of this kind in terms of the classical derivatives with respect to the radial coordinate. In this way, we simplify the procedure of construction of iterated integral kernels of the resolvent solution of the governing integral equation of continuity to which the solution of the analyzed problems is reduced by the method of direct integration. [ABSTRACT FROM AUTHOR]

We develop a stochastic optimization framework to identify governing equations in multi-physics systems. The proposed approach discovers partial differential equations (PDEs) by combining user’s prior knowledge of the underlying physics of a target system and its observed data. The technique relies on evolutionary processes to randomly generate PDEs and stochastically optimize their structure and coefficients to the data by exploring the infinite model space. Furthermore, the method captures the spatiotemporal dynamics of physical system by direct evaluation of the candidate PDEs under physical constraints. To achieve significant computational speedup, the proposed stochastic optimization method relies on a series of novel modifications. These consist of the incorporation of a multi-purpose loss function into the parallel fitness test and bloat control techniques into the evolutionary processes. As such, these innovations lead to a significant improvement of the effectiveness and computational efficiency in identifying PDEs from given data. We demonstrate the applicability of methodology in two illustrative examples: the nonlinear Burgers’ equation and the linear/nonlinear advection-dispersion equation. The exact PDEs are successfully identified, even with significant data noise, and captures the underlying physics of the target system. Through series of simulations, we assess the accuracy, robustness, and limitations of the proposed approach. In particular, we show the impact of key dimensionless groups (that accounts for the competition between various physical phenomena) in controlling the accuracy of the identification process. This work shows that developed identification method is a promising effective and robust gray box modeling tool for identifying PDEs.

The paper is concerned with the derivation of asymptotically consistent equations governing the long-wave flexural response of a two-layered rectangular plate with high-contrast elastic properties. In the general case, the plate is under dynamic and variable surface, volume, and edge forces. Performing the asymptotic integration of the three-dimensional (3D) elasticity equations in the transverse direction and satisfying boundary conditions on the faces and interface, we derived the sequence of two-dimensional (2D) differential equations with respect to required functions in the first two approximations. The eight independent restraints for the generalized displacements and stress resultants are considered to formulate the 16 independent variants of boundary conditions. One of the main results of the paper is the Timoshenko–Reissner type equation capturing the effect of the softer layer and taking into account the in-plane deformation induced by the edge forces. Comparative calculations of natural frequencies were carried out based on our and alternative models. [ABSTRACT FROM AUTHOR]

The performance of a gas turbine directly affects its energy conversion efficiency and operation stability rate, while the optimization of the internal flow field is the key to improving its performance. Computational Fluid Dynamics (CFD), as a powerful numerical simulation tool, plays an important role in optimizing the gas turbine flow field. In this paper, the turbine of the gas turbine is taken as an object, and CFD technology is used to analyze the distribution of the flow field inside the turbine and to realize the optimization design of the gas turbine in this way. The finite volume method (FCM) based discretization of the N-S governing equations is selected, and the RNG k-ε turbulence model is used for numerical simulation. The mounting angle, geometric angle, and mid-arc are used to optimize the aerodynamic joint of the turbine’s dynamic and static blades based on the results of the 3D flow field analysis. The error of the RNG k-ε model in the efficiency characteristic line is smaller than that of the SST model and the EARSM model, and its maximum relative errors with the experimental values of efficiency and flow rate are 3.4% and 4.6%, respectively, which are within the reasonable range, indicating that the reliability of the numerical calculation method in this paper meets the requirements. Compared with the initial design of the turbine, the mass flow rate and total efficiency of the optimized turbine in this paper have been improved by 0.88% and 4.93%, respectively, and the expansion ratio has been reduced by 6.15%, which is a better optimization effect, and lays a practical foundation for further optimization of the design of the gas turbine.

With the progress and development of the times, the traditional aircraft power system and difficult to meet the needs of the current aviation development, for the aircraft power and heat exchanger research has been more and more extensive attention. This study takes the heat exchanger of the aircraft loop control system as an example, constructs the thermal management system of the aircraft according to the mechanism of its heat transfer and flow characteristics, and optimizes it under the consideration of manufacturing constraints. Based on the theory of fluid mechanics, the aircraft heat exchanger is simulated, and control equations based on heat transfer and flow characteristics are established. In this paper, the temperature difference of the heat exchanger is increased by 6.5°C and 5.4°C, respectively, and the heat transfer coefficient is between 11 and 14 kW/m²k. Furthermore, the fluid temperature has risen from 0.05 to 0.5 to 0.30 to 0.87 with the increase in flow rate. The maximum deviation values were 8.3%, 6.7%, and 8.6%, respectively, and the confidence intervals were all above 90%. This study can effectively improve the efficiency of aircraft heat exchangers compared to traditional heat exchangers and has more advantages in heat transfer performance, which provides a reference value for the development of the aviation field.

Hybrid cable-stayed suspension bridges combine the advantages of cable-stayed and suspension bridges, mitigating their deficiencies. Due to its super spanning ability, this novel form of bridge enjoys a bright application prospect as a large-span structure. This study introduces an analytical algorithm to estimate the full-bridge response of a hybrid cable-stayed suspension bridge with a vertical uniformly distributed load applied to the main beam. This method is based on the assumption that all parameters, such as the geometric configuration, internal force distribution, and material properties, of the whole bridge under a dead load are known; then, it analyzes the full-bridge response under a live load. First, the minimum and independent basic unknown parameters of the full-bridge response are determined. Next, the governing equations are derived and solved based on the conservation of unstressed length of each section of cable, closure of span lengths and elevation difference in different spans, and conditions for stress balance of the main beam. Thus, the values of basic unknown parameters are obtained. Finally, they are substituted into the governing equations to estimate the full-bridge response, including each bridge component's internal forces and deflections. The proposed analytical method involves no iterative procedures when dealing with nonlinear problems but only focuses on the bridge's state with and without loading. The results are obtained directly by solving the equations, which have the advantages of high efficiency, simplicity, and clear physical meaning. Finally, the feasibility and effectiveness of the proposed method are verified by a finite-element-based calculation of an exemplary asymmetric cable-stayed suspension cooperation system bridge with a main span of 1400 m. [ABSTRACT FROM AUTHOR]

Submarines are one of the most advanced marine vehicles navigating from the surface of the water to the depths of the seas and able to perform various operations. Submarines have no benefit in terms of speed relative to surface floats, but also the advantage of a (moving underwater) dive deep into the deep seas. Diving and hovering of a submarine are carried out with the help of water ballast tanks (WBTs). Considering the importance of WBTs in the dynamic and static stability of the submarine, in examining the emergency maneuver operations using WBTs, complete modeling of the compressed air blowing process in the main WBTs of a submarine should be made. Blowing and unloading submarine ballasts can potentially use as a complementary control system to improve submarine maneuverability. Submarine ballast tanks can use as a tool for emergency hovering operation. This critical issue has simulated in this article using StarCCM + software, among which the governing equations and essential parameters have been investigated. Also, a sensitivity analysis was done on the results. [ABSTRACT FROM AUTHOR]

• Analysis of planar arbitrarily curved microbeams with modified couple stress theory and Euler-Bernoulli beam model. • Derivation of governing equations and boundary conditions. • Numerical formulations with isogeometric analysis approach. • In-depth theoretical and numerical studies on size-dependent behavior. • Size effects on validity of the Euler-Bernoulli beam model for microbeams. This study addresses the deficiency of means for analysis of planar arbitrarily curved microbeams. More precisely, a formulation is developed for static analysis employing the modified couple stress theory and the Euler-Bernoulli beam model. Geometric and kinematic descriptions of a slender three-dimensional continuum body are consistently reduced to those of its beam axis. A systematic framework is presented to enable elegant determination of essential strain and stress measures. Then, the virtual work principle is employed to derive governing equations and boundary conditions. Some remarks are given on the numerical implementation with the isogeometric approach. In addition, to facilitate the verification of the derivation, the isogeometric approach is also applied to two-dimensional problems of the modified couple stress theory, and the implementation is detailed. Two comprehensive examples are used to investigate the size-dependent behavior of planar arbitrarily curved microbeams. Several rigorous tests are designed to examine the accuracy of the derived beam formulation and the validity of kinematic assumptions of the Euler-Bernoulli beam model. Finally, the robustness and efficiency of the isogeometric implementation for the proposed beam formulation are verified. [ABSTRACT FROM AUTHOR]

Subsurface flow is a critical component in the hydrological cycle, since it controls the quantity and timing of surface runoff and groundwater flow. Field studies have shown the fundamental influence of the bedrock surface geometry on subsurface stormflow (SSSF) and that the SSSF process consists of at least two major components: the matrix flow component and the macropore flow component that are in dynamical interaction toward forming the SSSF. Furthermore, field studies have shown that the bedrock surface that underlies the SSSF has essentially a two‐dimensional (2D) geometry, where not only the longitudinal profile along the hillslope but also the profile in the transverse direction influence the subsurface stormflow over the bedrock. The macropore flow itself being a multidimensional flow process, requires a multidimensional matrix flow component in order to quantify realistic dynamical interactions between these components within the subsurface stormflow module of a watershed hydrology model. Within this framework, the critical research question is how to extend the existing 2D Boussinesq model for the matrix flow over an inclined flat 2D surface in the longitudinal hillslope direction by developing the governing equations of matrix flow at hillslope scale over various 2D bedrock surface geometries that are reported in the field studies of SSSF. Then, numerical experiments are performed by applying the developed governing equations to various bedrock surface geometries. The results of the numerical simulations show (a) the proposed governing equations can simulate various two‐dimensional bedrock surface geometries, and are capable of incorporating the upward or downward concavity of bedrock surface in longitudinal and transverse directions into SSSF by modulating the timing and magnitude of the flows and (b) the proposed governing equations for matrix flow provide an appropriate setting for the dynamical interaction of the matrix flows with the macropore flows, creating a promising modeling framework for SSSF. Plain Language Summary: Field studies have shown the fundamental influence of the bedrock surface geometry on subsurface stormflow (SSSF). This study extends the existing two‐dimensional (2D) Boussinesq model for the matrix component of SSSF that was developed for a 2D flat but declining bedrock surface to various bedrock surface geometries that were reported in field studies. The numerical results show that the matrix flow component of SSSF is clearly a 2D flow process that is highly impacted by the bedrock surface geometry. Key Points: The governing equations of the matrix flow component of subsurface stormflow as function of two‐dimensional bedrock surface geometry were developed in this studyNumerical simulations showed the impact of the 2D bedrock surface geometry on the characteristics of the matrix flow over a hillslopeThe developed models can facilitate dynamical interactions with other flows, such as macropore flows, at a hillslope [ABSTRACT FROM AUTHOR]

The paper is concerned with the asymptotically consistent theory of nanoscale plates capturing the spatial nonlocal effects. The three-dimensional (3D) elasticity equations for a thin plate are used as the governing equations. In the general case, the plate is acted upon by dynamic body forces varying in the thickness direction, and by variable surface forces. The thickness of the plate is assumed to be greater than the characteristic micro/nanoscale measure and much smaller than the in-plane characteristic dimension (e.g., the wave or deformation length). The 3D constitutive equations of gradient elasticity are used to link the fields of nonlocal stresses and strains. Using the asymptotic approach, a sequence of relations for stresses and displacements in the form of polynomials in the transverse coordinate with coefficients depending on time and in-plane coordinates was obtained. The asymptotically consistent 2D differential equation governing vibration (or static deformation) of a plate accounting for both transverse shears and the spatial nonlocal contribution of the stress and strain fields was derived. It was revealed that capturing nonlocal effects in all directions leads to an increase in the correction factor compared with the well-known 2D theories based on kinematic hypotheses and the Eringen-type gradient constitutive equations. The effect of the internal length scales parameters on free low-frequency vibrations and displacements of a plate is discoursed. [ABSTRACT FROM AUTHOR]

With the development of automatic measurement and data storage, vast quantities of data can be recorded and analyzed for heat transfer processes, which provides an opportunity to discover the transient heat transfer governing laws from the data. In this study, a machine learning-based sequential threshold ridge regression (STRidge) approach is applied to extract partial differential equations (PDEs) and tested on the heat conduction equation and conductive–convective heat transfer equation subjected to different boundary conditions, data volumes, and noise levels. Moreover, we studied the learning of governing equation of nonlinear transient heat transfer and used the improved STRidge with genetic algorithm to learn PDE with incomplete candidate library. The results showcase highly accurate identification of governing equations for heat transfer. And our results reveal the vast potential of the data-driven method in complex geothermal problems. [ABSTRACT FROM AUTHOR]

Governing equations in the form of differential equations are fundamental modeling elements for understanding, controlling, and optimizing chemical processes. While significant advances in machine learning allow for high‐performance surrogate modeling, the resulting models typically fail to extrapolate to regimes beyond the training data and provide little physical insight regarding the underlying phenomena. In this work, we propose a moving horizon dynamic nonlinear optimization strategy that recovers parsimonious governing equations from large‐scale, noisy data sets. Differently from prior works, our approach does not rely on significant structural assumptions (mainly concerning linearity with respect to estimated model coefficients), which provides greater modeling flexibility and permits distilling governing equations of systems involving chemical reactions occurring under nonisothermal conditions. The main advantages and contributions of our proposed approach are demonstrated through two numerical case studies consisting of a continuously stirred tank reactor operated under isothermal and nonisothermal conditions. [ABSTRACT FROM AUTHOR]

In this work, the finite element technique is employed to evaluate the effects of thermal relaxation durations on temperature, displacements, and stresses in a two-dimensional, polymeric, orthotropic, elastic medium. The problem is considered in a homogeneous, polymeric, orthotropic medium in the context of the Green and Lindsay model with two thermal relaxation times. The bounding surface of the half-space was subjected to a heat flux with an exponentially decaying pulse. Finite element techniques were used to solve the governing formulations, with eight-node isoparametric rectangular elements with three degrees of freedom (DOF) per node. The developed method was calculated using numerical results applied to the polymeric, orthotropic medium. The findings were implemented and visually shown. Finally, the results were displayed to demonstrate the differences between classical dynamic coupling (CT), the Lord–Shulman (LS) and the Green and Lindsay (GL) models. [ABSTRACT FROM AUTHOR]

Abstract Non‐Newtonian fluids are considered to those types of fluids that do not follow Newton's law of viscosity where viscosity would change in either more solid or liquid. The objective of this study, a parametric simulation, was performed to investigate the considerable influence of non‐Newtonian fluids on different parameters on spiral tubes. Firstly, governing equations have derived by computational fluid dynamics methods to compare the laminar and turbulent flows. Then, the turbulent flow, the non‐Newtonian flow, power law flow, and cross models are simulated according to the boundary conditions. Consequently, for the Reynolds range of 600‐2500, increasing the Reynolds number decreases the friction coefficient. It is observed that in slow flow, there is no significant difference between the results of cross and power law models. The distribution of velocity profile has slight variation at the pipe outlet for Reynolds 9000 and 20 000. In other words, the flow is constant in developed region inside the spiral pipe. Moreover, the investigation of pressure drop inside the pipe revealed that regarding the increase in Reynolds number, the friction coefficient decreases. In spiral tubes, due to the presence of secondary currents, the friction coefficient is higher than the direct tube.

Constructing the governing dynamical equations of complex systems from observational data is of great interest for both theory and applications. However, it is a difficult inverse problem to explicitly construct the dynamical equations for many real complex systems based on observational data. Here, we propose to implicitly represent the dynamical equations of a complex system using a radial basis function (RBF) network trained on the observed data of the system. We show that the RBF network trained on trajectory data of the classical Lorenz and Chen system can faithfully reproduce the orbits, fixed points, and local bifurcations of the original dynamical equations. We also apply this method to electrocardiogram (ECG) data and show that the fixed points of the RBF network trained using ECG can discriminate healthy people from patients with heart disease, indicating that the method can be applied to real complex systems.

This article presents a numerical scheme for two‐phase flows consisting of compressible gas and incompressible liquid. Assuming that the gas density is determined by pressure only and that the liquid density is constant, we develop a new set of governing equations for compressible–incompressible two‐phase flows, which can be seen as a simplification of the previous unified governing equations. The volume fraction of gas, velocity, and pressure are the primary variables. Given the liquid's usual leading role in the flow motion, a pressure‐based method is employed to solve the equations. A fifth‐order accurate weighted essentially nonoscillatory (WENO) scheme is applied to discretize the advection terms, and the tangent of hyperbola for interface capturing (THINC) scheme is utilized to capture the interface. The numerical scheme proposed is validated against the generalized Bagnold model and the free drop of a water patch in a closed tank. The results show that the scheme can tackle low Mach number compressible–incompressible two‐phase flows. For the one‐dimensional Bagnold model, the present numerical model achieves first‐order convergence and gives better results than that based on the previous unified governing equations with the same numerical methods. In the simulation of the free drop of a water patch in a closed tank, a similar pressure curve with other reported work is given. [ABSTRACT FROM AUTHOR]

Copyright of Natural Gas Geoscience is the property of Natural Gas Geoscience and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents an analysis on ways to improve the annual energy production (AEP) of a wind turbine utilizing a drivetrain that operates based on the hydrostatic transmission. The system configuration of such a drivetrain is explained in details and a comparison of operation and characteristics with existing drivetrains is provided. AEP was estimated for these configurations through appropriate dynamic modeling and operational efficiency optimization. Optimal selection of a number of design variables and system parameters contributed to the improvements in the AEP. Findings of this study demonstrate that the proposed hydrostatic drivetrain improves the AEP of a 750 kW turbine by up to +8% when compared with a geared wind turbine. The AEP improvements of the hydrostatic drive wind turbine were more than 10% for a 1.5 MW system over geared configuration. It is also demonstrated that the efficiency of power generation can be improved under various wind speeds. The suitable selection of synchronous speed of the generator directly improves the efficiency of operation by up to 35% at low wind speeds. An efficiency improvement was also observed under higher operating pressures and longer turbine blades.

The authors propose an algorithm to estimate the path followed by refracted signals from a source to a target, through a medium formed by uniform parallel layers with known different refractive indices, a common model used for ice radio‐echo sounding. The analytical solution is a polynomial with a degree that exponentially depends on the number of layers, being computationally inefficient. For low incidence angles, the small‐angle approximation can be used to avoid the polynomial. In their technique, they normalise the governing equations to obtain a framework where to find a narrow angular interval containing the solution, finally estimated interpolating the boundaries. The new approach improves the results regarding the small‐angle approximation for a wider angular range at a slightly higher computational time. This method has been applied to focus airborne synthetic aperture radar images for deep ice sounding, reducing the calculation time and improving the detected response in wide beam and squinted geometries, used for high along‐track resolution or the detection of sloping internal layers. [ABSTRACT FROM AUTHOR]

Non‐Newtonian fluids are considered to those types of fluids that do not follow Newton's law of viscosity where viscosity would change in either more solid or liquid. The objective of this study, a parametric simulation, was performed to investigate the considerable influence of non‐Newtonian fluids on different parameters on spiral tubes. Firstly, governing equations have derived by computational fluid dynamics methods to compare the laminar and turbulent flows. Then, the turbulent flow, the non‐Newtonian flow, power law flow, and cross models are simulated according to the boundary conditions. Consequently, for the Reynolds range of 600‐2500, increasing the Reynolds number decreases the friction coefficient. It is observed that in slow flow, there is no significant difference between the results of cross and power law models. The distribution of velocity profile has slight variation at the pipe outlet for Reynolds 9000 and 20 000. In other words, the flow is constant in developed region inside the spiral pipe. Moreover, the investigation of pressure drop inside the pipe revealed that regarding the increase in Reynolds number, the friction coefficient decreases. In spiral tubes, due to the presence of secondary currents, the friction coefficient is higher than the direct tube. [ABSTRACT FROM AUTHOR]

This paper introduces a novel method called Wide-Array of Nonlinear Dynamics Approximation (WyNDA) for extracting mathematical models of dynamical systems from data. A key advantage of this method over existing approaches lies in its suitability for online implementation. Moreover, WyNDA stands out by not relying on optimization or machine learning, ensuring computational efficiency. The fundamental concept revolves around approximating the unknown function of a dynamical system through a diverse set of basis functions that encapsulate the available data. An adaptive observer is then employed to iteratively refine this approximation and estimate the associated parameters. The efficacy of the proposed method is demonstrated through numerical simulations encompassing linear systems, nonlinear systems, and control systems. The results underscore the method's ability to successfully unveil the governing equations of dynamical systems, highlighting its potential for extracting intricate system dynamics from observational data.•WyNDA represents a novel approach for uncovering mathematical models of dynamical systems from data.•Utilizing a series of basis functions, WyNDA effectively approximates the unknown structure inherent in dynamical systems.•The validation of WyNDA involves benchmark equations of dynamical systems, confirming its efficacy in diverse scenarios., Competing Interests: The author states that he does not have any competing financial interests or personal relationships that could have influenced the work presented in this paper., (© 2024 The Author(s).)

Information on soil erosion and related sedimentation processes are very important for natural resource management and sustainable farming. Plenty of models are available for studying soil erosion but only a few are suitable for dynamic soil erosion assessments at the field-scale. To date, there are no field-scale dynamic models available considering complex agricultural systems for the simulation of soil erosion. We conducted a review of 51 different models evaluated based on their representation of the processes of soil erosion by water. Secondly, we consider their suitability for assessing soil erosion for more complex field designs, such as patch cropping, strip cropping and agroforestry (alley-cropping systems) and other land management practices. Several models allow daily soil erosion assessments at the sub-field scale, such as EPIC, PERFECT, GUEST, EPM, TCRP, SLEMSA, APSIM, RillGrow, WaNuLCAS, SCUAF, and CREAMS. However, further model development is needed with respect to the interaction of components, i.e., rainfall intensity, overland flow, crop cover, and their scaling limitations. A particular shortcoming of most of the existing field scale models is their one-dimensional nature. We further suggest that platforms with modular structure, such as SIMPLACE and APSIM, offer the possibility to integrate soil erosion as a separate module/component and link to GIS capabilities, and are more flexible to simulate fluxes of matter in the 2D/3D dimensions. Since models operating at daily scales often do not consider a horizontal transfer of matter, such modeling platforms can link erosion components with other environmental components to provide robust estimations of the three-dimensional fluxes and sedimentation processes occurring during soil erosion events.

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Governing equations of physical problems are traditionally derived from conservation laws or physical principles. However, some complex problems still exist for which these first-principle derivations cannot be implemented. As data acquisition and storage ability have increased, data-driven methods have attracted great attention. In recent years, several works have addressed how to learn dynamical systems and partial differential equations using data-driven methods. Along this line, in this work, we investigate how to discover subsurface flow equations from data via a machine learning technique, the least absolute shrinkage and selection operator (LASSO). The learning of single-phase groundwater flow equation and contaminant transport equation are demonstrated. Considering that the parameters of subsurface formation are usually heterogeneous, we propose a procedure for learning partial differential equations with heterogeneous model parameters for the first time. Derivative calculation from discrete data is required for implementing equation learning, and we discuss how to calculate derivatives from noisy data. For a series of cases, the proposed data-driven method demonstrates satisfactory results for learning subsurface flow equations. [ABSTRACT FROM AUTHOR]

Sandwich structures are widely used in aerospace and naval industries as they are light in weight and have high energy absorption capacities. Sandwich beams with soft core are the most commonly used structures in many applications. Analysis of sandwich beams is the key in its design and the development of new family of super convergent shear deformable finite elements are presented in this article. In this article, formulation of three different Super Convergent shear deformable finite elements with 4, 7, and 10 degrees of freedom respectively, for analysis of the sandwich beams with soft core are presented. The formulation considers the top, bottom face sheets and core as separate entities and are coupled by beam kinematics. The performance of these elements are validated by results available in the published literature. The article highlights the issues with the traditional elements for modeling sandwich beams and the advantages of the elements developed, in particular wave propagation analysis, are addressed in this article. [ABSTRACT FROM AUTHOR]

In the paradigm of data-intensive science, automated, unsupervised discovering of governing equations for a given physical phenomenon has attracted a lot of attention in several branches of applied sciences. In this work, we propose a method able to avoid the identification of the constitutive equations of complex systems and rather work in a purely numerical manner by employing experimental data. In sharp contrast to most existing techniques, this method does not rely on the assumption on any particular form for the model (other than some fundamental restrictions placed by classical physics such as the second law of thermodynamics, for instance) nor forces the algorithm to find among a predefined set of operators those whose predictions fit best to the available data. Instead, the method is able to identify both the Hamiltonian (conservative) and dissipative parts of the dynamics while satisfying fundamental laws such as energy conservation or positive production of entropy, for instance. The proposed method is tested against some examples of discrete as well as continuum mechanics, whose accurate results demonstrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, lumped mass model is used to study the effect due to pile driving on ground response in the vicinity. This is a popular problem in structural dynamics, however, one issue is how to reduce time elapsed for soil behavior computation with a good enough accuracy of prediction. The major objective of this study is to find out the peak particle displacement, velocity and acceleration in the far field ground during pile driving, using lumped mass method and linear elastic soil model. The numerical results including displacement, velocity and acceleration showed a good match as compared with that from finite element method by Plaxis.

This paper presents an analysis on ways to improve the annual energy production (AEP) of a wind turbine utilizing a drivetrain that operates based on the hydrostatic transmission. The system configuration of such a drivetrain is explained in details and a comparison of operation and characteristics with existing drivetrains is provided. AEP was estimated for these configurations through appropriate dynamic modeling and operational efficiency optimization. Optimal selection of a number of design variables and system parameters contributed to the improvements in the AEP. Findings of this study demonstrate that the proposed hydrostatic drivetrain improves the AEP of a 750 kW turbine by up to +8% when compared with a geared wind turbine. The AEP improvements of the hydrostatic drive wind turbine were more than 10% for a 1.5 MW system over geared configuration. It is also demonstrated that the efficiency of power generation can be improved under various wind speeds. The suitable selection of synchronous speed of the generator directly improves the efficiency of operation by up to 35% at low wind speeds. An efficiency improvement was also observed under higher operating pressures and longer turbine blades. [ABSTRACT FROM AUTHOR]

In this study, the exergy analysis of a weir‐type cascade solar still connected to photovoltaic thermal (PV/T) collectors is provided. By formulating the energy balance for different components of solar still system, the governing equations were obtained as a set of non‐linear ordinary differential equations. A perfect exergy analysis is used to obtain irreversibility rates, exergy fractions and exergy efficiency. To find various temperatures and freshwater productivity, the governing equations are solved numerically. Moreover, through experimental data of previous studies, the numerical results were validated. In this study, the effect of the mass flow rate of brackish water and the number of PV/T collectors on the hourly variation of exergy efficiency, irreversibility rates and exergy fractions were investigated. Results showed that by connecting two PV/T collectors to the cascade solar still, the exergy efficiency can be improved twice. Moreover, the connection of two PV/T collectors and use of their output electrical power for heating brackish water can increment the fresh water production rate by 56.8%. The absorber plate and PV/T collectors include maximum 55.8 and 36.8% of system total irreversibility, respectively. The maximum exergy fraction is obtained in evaporating with a value of 0.85. [ABSTRACT FROM AUTHOR]

Continuous Time Random Maxima (CTRM) are a generalization of classical extreme value theory: Instead of observing random events at regular intervals in time, the waiting times between the events are also random variables which have arbitrary distributions. In case that the waiting times between the events have infinite mean, the limit process that appears differs from the limit process that appears in the classical case. With a continuous mapping approach, we derive a limit theorem for the case that the waiting times and the subsequent events are dependent as well as for the case that the waiting times depend on the preceding events (in this case we speak of an Overshooting Continuous Time Random Maxima, abbr. OCTRM). We get the distribution functions of the limit processes and a formula for the Laplace transform in time of the CTRM and the OCTRM limit. With this formula we have another way to calculate the distribution functions of the limit processes, namely by inversion of the Laplace transform. Moreover, we present governing equations which in our case are time fractional differential equations whose solutions are the distribution functions of our limit processes. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a space fractional negative binomial process (SFNB) by time-changing the space fractional Poisson process by a gamma subordinator. Its one-dimensional distributions are derived in terms of generalized Wright functions and their governing equations are obtained. It is a Lévy process and the corresponding Lévy measure is given. Extensions to the case of distributed order SFNB, where the fractional index follows a two-point distribution, are investigated in detail. The relationship with space fractional Polya-type processes is also discussed. Moreover, we define and study multivariate versions, which we obtain by time-changing a d-dimensional space-fractional Poisson process by a common independent gamma subordinator. Some applications to population’s growth and epidemiology models are explored. Finally, we discuss algorithms for the simulation of the SFNB process. [ABSTRACT FROM AUTHOR]