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Data-driven models utilizing powerful artificial intelligence (AI) algorithms have been implemented over the past two decades in different fields of simulation-based engineering science. Most numerical procedures involve processing data sets developed from physical or numerical experiments to create closed-form formulae to predict the corresponding systems' mechanical response. Efficient AI methodologies that will allow the development and use of accurate predictive models for solving computational intensive engineering problems remain an open issue. In this research work, high-performance machine learning (ML) algorithms are proposed for modeling structural mechanics-related problems, which are implemented in parallel and distributed computing environments to address extremely computationally demanding problems. Four machine learning algorithms are proposed in this work and their performance is investigated in three different structural engineering problems. According to the parametric investigation of the prediction accuracy, the extreme gradient boosting with extended hyper-parameter optimization (XGBoost-HYT-CV) was found to be more efficient regarding the generalization errors deriving a 4.54% residual error for all test cases considered. Furthermore, a comprehensive statistical analysis of the residual errors and a sensitivity analysis of the predictors concerning the target variable are reported. Overall, the proposed models were found to outperform the existing ML methods, where in one case the residual error was decreased by 3-fold. Furthermore, the proposed algorithms demonstrated the generic characteristic of the proposed ML framework for structural mechanics problems. [ABSTRACT FROM AUTHOR]

Function approximation is a fundamental process in a variety of problems in computational mechanics, structural engineering, as well as other domains that require the precise approximation of a phenomenon with an analytic function. This work demonstrates a unified approach to these techniques, utilizing partial sums of the Taylor series in a high arithmetic precision. In particular, the proposed approach is capable of interpolation, extrapolation, numerical differentiation, numerical integration, solution of ordinary and partial differential equations, and system identification. The method employs Taylor polynomials and hundreds of digits in the computations to obtain precise results. Interestingly, some well-known problems are found to arise in the calculation accuracy and not methodological inefficiencies, as would be expected. In particular, the approximation errors are precisely predictable, the Runge phenomenon is eliminated, and the extrapolation extent may a priory be anticipated. The attained polynomials offer a precise representation of the unknown system as well as its radius of convergence, which provides a rigorous estimation of the prediction ability. The approximation errors are comprehensively analyzed for a variety of calculation digits and test problems and can be reproduced by the provided computer code. [ABSTRACT FROM AUTHOR]

Heat transfer through the soil is important in shallow geothermal applications, in plant growth as well as in the surface energy balance. In this work, an analytical solution for a conduction–convection equation that models heat transfer is presented for non-homogeneous soil. The main assumption underlying the solution is that the thermal diffusivity of soil is piecewise-constant. A method to determine the depth-dependent thermal diffusivity and the water flux density through the porous medium based on temperature measurements is also developed and applied to field data from a site in Ioannina, Greece. The thermal diffusivity was found to increase in the layer below the surface and decrease for larger depths, while convection through the porous medium was found to be present in wet conditions and to account for about 10% of the heat flux in terms of the annual variability of temperature. Finally, the capability of the novel method in capturing the spatio-temporal variability of soil temperature is compared to three commonly used algorithms: the amplitude, the phase, and the conduction–convection algorithm. The novel method is able to reduce the root-mean-square error for the predicted variability of temperature at all depths by an order of magnitude compared to the other three algorithms. [ABSTRACT FROM AUTHOR]

Optimization algorithms appear in the core calculations of numerous Artificial Intelligence (AI) and Machine Learning methods and Engineering and Business applications. Following recent works on AI's theoretical deficiencies, a rigour context for the optimization problem of a black-box objective function is developed. The algorithm stems directly from the theory of probability, instead of presumed inspiration. Thus the convergence properties of the proposed methodology are inherently stable. In particular, the proposed optimizer utilizes an algorithmic implementation of the n-dimensional inverse transform sampling as a search strategy. No control parameters are required to be tuned, and the trade-off among exploration and exploitation is, by definition, satisfied. A theoretical proof is provided, concluding that when falling into the proposed framework, either directly or incidentally, any optimization algorithm converges. The numerical experiments verify the theoretical results on the efficacy of the algorithm apropos reaching the sought optimum. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed optimization method is a general tool which can have numerous applications in various mathematical, engineering and technological fields. Due to its simplicity and straight-forward implementation, it can easily be applied by non-experts to obtain optimized results. A new, fast, elegant, and simple stochastic optimization search method is proposed, which exhibits surprisingly good performance and robustness considering its simplicity. We name the algorithm pure random orthogonal search (PROS). The method does not use any assumptions, does not have any parameters to adjust, and uses basic calculations to evolve a single candidate solution. The idea is that a single decision variable is randomly changed at every iteration and the candidate solution is updated only when an improvement is observed; therefore, moving orthogonally towards the optimal solution. Due to its simplicity, PROS can be easily implemented with basic programming skills and any non-expert in optimization can use it to solve problems and start exploring the fascinating optimization world. In the present work, PROS is explained in detail and is used to optimize 12 multi-dimensional test functions with various levels of complexity. The performance is compared with the pure random search strategy and other three well-established algorithms: genetic algorithms (GA), particle swarm optimization (PSO), and differential evolution (DE). The results indicate that, despite its simplicity, the proposed PROS method exhibits very good performance with fast convergence rates and quick execution time. The method can serve as a simple alternative to established and more complex optimizers. Additionally, it could also be used as a benchmark for other metaheuristic optimization algorithms as one of the simplest, yet powerful, optimizers. The algorithm is provided with its full source code in MATLAB for anybody interested to use, test or explore. [ABSTRACT FROM AUTHOR]

Non-conservative distributed parameter systems connected to external damping sources and possessing non-normal modes are analyzed in this work. The mathematical model of such systems is presented and real valued modal analysis is used to obtain the coupled modal equations of motion. A decoupling technique is developed using Fourier expansion, fictitious damping ratios, modal coupling parameters and pseudo forces. The method is applicable to all types of excitation. A normal mode criterion in the form of non-proportionality indices is also provided. The theoretical predictions are verified through application to a non-conservative Euler–Bernoulli beam with non-proportional damping configuration and various types of boundary conditions. Numerical examples emphasize the response errors associated with the proportional damping assumption and reveal the advantages of the proposed approach over the exact method. [ABSTRACT FROM AUTHOR]

The literature review highlights that previous studies have been identifying risk management as an essential tool for project management and could increase the chance of successfully meeting project objectives. In addition, as found from the reviewed literature, risk management has been seen as a tool of allowing the project team to communicate risk information, so as to enhance the decision-making process towards balancing threats and opportunities. Thus, this research aims to examine participants' views on the alignment of risk management, project management and organizational project success. Machine learning algorithms are employed to explore collective data from posts on twitter in order to obtain valuable knowledge about discussions regarding risk management, and project management. Additionally, the corresponding scientific literature obtained from Scopus database was analyzed utilizing bibliometric tools, in order to investigate diverse perceptions in academia and industry. Findings of this study will have implications for practitioners' perception of project risk management. [ABSTRACT FROM AUTHOR]

Geophysical turbulence is observed to self-organize into large-scale flows such as zonal jets and coherent vortices. Previous studies of barotropic $\unicode[STIX]{x1D6FD}$ -plane turbulence have shown that coherent flows emerge from a background of homogeneous turbulence as a bifurcation when the turbulence intensity increases. The emergence of large-scale flows has been attributed to a new type of collective, symmetry-breaking instability of the statistical state dynamics of the turbulent flow. In this work, we extend the analysis to stratified flows and investigate turbulent self-organization in a two-layer fluid without any imposed mean north–south thermal gradient and with turbulence supported by an external random stirring. We use a second-order closure of the statistical state dynamics, that is termed S3T, with an appropriate averaging ansatz that allows the identification of statistical turbulent equilibria and their structural stability. The bifurcation of the statistically homogeneous equilibrium state to inhomogeneous equilibrium states comprising zonal jets and/or large-scale waves when the energy input rate of the excitation passes a critical threshold is analytically studied. Our theory predicts that there is a large bias towards the emergence of barotropic flows. If the scale of excitation is of the order of (or larger than) the deformation radius, the large-scale structures are barotropic. Mixed barotropic–baroclinic states with jets and/or waves arise when the excitation is at scales shorter than the deformation radius with the baroclinic component of the flow being subdominant for low energy input rates and insignificant for higher energy input rates. The predictions of the S3T theory are compared with nonlinear simulations. The theory is found to accurately predict both the critical transition parameters and the scales of the emergent structures but underestimates their amplitude. [ABSTRACT FROM AUTHOR]

Zonal jets in a barotropic setup emerge out of homogeneous turbulence through a flow-forming instability of the homogeneous turbulent state (zonostrophic instability), which occurs as the turbulence intensity increases. This has been demonstrated using the statistical state dynamics (SSD) framework with a closure at second order. Furthermore, it was shown that for small supercriticality the flow-forming instability follows Ginzburg–Landau (G–L) dynamics. Here, the SSD framework is used to study the equilibration of this flow-forming instability for small supercriticality. First, we compare the predictions of the weakly nonlinear G–L dynamics to the fully nonlinear SSD dynamics closed at second order for a wide range of parameters. A new branch of jet equilibria is revealed that is not contiguously connected with the G–L branch. This new branch at weak supercriticalities involves jets with larger amplitude compared to the ones of the G–L branch. Furthermore, this new branch continues even for subcritical values with respect to the linear flow-forming instability. Thus, a new nonlinear flow-forming instability out of homogeneous turbulence is revealed. Second, we investigate how both the linear flow-forming instability and the novel nonlinear flow-forming instability are equilibrated. We identify the physical processes underlying the jet equilibration as well as the types of eddies that contribute in each process. Third, we propose a modification of the diffusion coefficient of the G–L dynamics that is able to capture the evolution of weak jets at scales other than the marginal scale (side-band instabilities) for the linear flow-forming instability. [ABSTRACT FROM AUTHOR]

The purpose of this article is to examine the prediction accuracy of the Random Forests, a machine learning method, when it is applied for residential mass appraisals in the city of Nicosia, Cyprus. The analysis is performed using transaction sales data from the Cyprus Department of Lands and Surveys, the Consumer Price Index of Cyprus from the Cyprus Statistical Service and the Central Bank of Cyprus' Residential Index (Price index for apartments). The Consumer Price Index and the price index for apartments record quarterly price changes, while the dependent variables for the computational models were the Declared and the Accepted Prices that were conditional on observed values of a variety of independent variables. The Random Forests method exhibited enhanced prediction accuracy, especially for the models that comprised of a sufficient number of independent variables, indicating the method as prominent, although it has not yet been utilized adequately for mass appraisals. [ABSTRACT FROM AUTHOR]

Background: Systematic reviews may provide less biased evidence than narrative reviews because they observe a strict methodology, similarly to primary studies. Hence, for clinical research questions, systematic reviews should be the study design of choice. It would be important to evaluate the prevalence and characteristics of narrative and systematic reviews published in prominent medical journals. Researchers and clinicians give great value to articles published in such scientific journals. This study sought to evaluate the prevalence and characteristics of narrative and systematic reviews in the five highest-ranked general medical journals and investigate the associations among type of review, number of citations, and impact factor (IF).Methods: We surveyed the five highest-ranked medical journals (The New England Journal of Medicine, The Lancet, The Journal of the American Medical Association, The BMJ, and Annals of Internal Medicine) for narrative and systematic reviews published between June 2015 and June 2016. We independently selected and extracted the data from the reviews by strictly following the pre-determined eligibility criteria (Systematic and narrative reviews that focused on the management of diseases). We conducted regression analyses to investigate the associations among review type, number of citations, and IF. We also descriptively reported narrative reviews containing some methodology that might be reproducible.Results: Two hundred seventy-five reviews were included: 75 (27%) systematic; 126 (46%) narrative with some methodology reported, and 74 (27%) narrative reviews. In comparison to systematic reviews, narrative reviews were more frequently published in journals with higher IF (risk ratio [RR] = 1.114 (95% CI 1.080 to 1.149). Systematic reviews received more citations than narrative reviews (group formed by narrative and narrative with some methodology reported (RR = 0.985 95% CI 0.978 to 0.991).Conclusions: Non-systematic evidence is the most prevalent type of evidence in reviews published in the five highest-ranked general medical journals. Narrative reviews were more frequently published in journals with higher IF. We recommend that journals limit their space for narrative information, and to address clinical research questions, these journals consider publishing systematic evidence exclusively. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to establish a complete analytical solution concerning the linear pressure distribution under rigid rectangular spread footings. An eccentricity diagram is developed to map the unique footing deformations and compression zones in each one of five distinct regions. For each region, the linear soil pressure, neutral axis position, and pressure values at the four corners are expressed in closed forms. The accuracy and consistency of the explicit expressions are verified by presenting several special boundary cases, whereas the physical interpretation is brought out by analyzing the eccentricity diagram. A generic nomogram providing the maximum soil pressure is also formed to promote efficient structural footing design. The developed analytical formulas for responses and resultants enable algorithmic implications without iterations and offer high computational efficiency. Proper examples, generated via developed computer software, exhibit how the theoretical content of this article is applied in practice. The software enables three-dimensional (3D) viewing of the deformed and undeformed physical and mathematical model of the structure, allowing detailed visual inspection of the results. [ABSTRACT FROM AUTHOR]

In this review paper, we computationally analyze a vast volume of published articles in the field of Adaptive Learning, as obtained by the Scopus Database. Particularly, we use a query with search terms targeting the area of Adaptive Learning Systems by utilizing a combination of specific keywords. Accordingly, we apply a multidimensional scaling algorithm to construct bibliometric maps for keywords, authors, and references. Subsequently, we present the computational results for the studied dataset, reveal significant patterns appearing in the field of adaptive learning and the inter-item associations, and interpret the findings based on the current state-of-the-art literature in the area. Furthermore, we demonstrate the time-series of the evolution of the research terms, their trends over time, as well as their prevalent statistical associations. [ABSTRACT FROM AUTHOR]

Zonal jets and nonzonal large-scale flows are often present in forced-dissipative barotropic turbulence on a beta plane. The dynamics underlying the formation of both zonal and nonzonal coherent structures is investigated in this work within the statistical framework of stochastic structural stability theory (S3T). Previous S3T studies have shown that the homogeneous turbulent state undergoes a bifurcation at a critical parameter and becomes inhomogeneous with the emergence of zonal and/or large-scale nonzonal flows and that these statistical predictions of S3T are reflected in direct numerical simulations. In this paper, the dynamics underlying the S3T statistical instability of the homogeneous state as a function of parameters is studied. It is shown that, for weak planetary vorticity gradient β, both zonal jets and nonzonal large-scale structures form from upgradient momentum fluxes due to shearing of the eddies by the emerging infinitesimal flow. For large β, the dynamics of the S3T instability differs for zonal and nonzonal flows but in both the destabilizing vorticity fluxes decrease with increasing β. Shearing of the eddies by the mean flow continues to be the mechanism for the emergence of zonal jets while nonzonal large-scale flows emerge from resonant and near-resonant triad interactions between the large-scale flow and the stochastically forced eddies. The relation between the formation of large-scale structure through modulational instability and the S3T instability of the homogeneous state is also investigated and it is shown that the modulational instability results are subsumed by the S3T results. [ABSTRACT FROM AUTHOR]

Zonal jets are commonly observed to spontaneously emerge in a β-plane channel from a background of turbulence that is sustained in a statistical steady state by homogeneous stochastic excitation and dissipation of vorticity. The mechanism for jet formation is examined in this work within the statistical wave--mean flow interaction framework of stochastic structural stability theory (SSST) that makes predictions for the emergence of zonal jets in β-plane turbulence. Using the coupled dynamical SSST system that governs the joint evolution of the second-order statistics and the mean flow, the structural stability of the spatially homogeneous statistical equilibrium with no mean zonal jets is studied. It is shown that close to the structural stability boundary, the eddy--mean flow dynamics can be split into two competing processes. The first, which is shearing of the eddies by the local shear described by Orr dynamics in a β plane, is shown in the limit of infinitesimal shear to lead to the formation of jets. The second, which is momentum flux divergence resulting from lateral wave propagation on the nonuniform local mean vorticity gradient, is shown to oppose jet formation. The upgradient momentum fluxes due to shearing of the eddies are shown to act exactly as negative viscosity for an anisotropic forcing and as negative hyperviscosity for isotropic forcing. The downgradient fluxes due to wave flux divergence are shown to act hyperdiffusively. [ABSTRACT FROM AUTHOR]

Large-scale mean flows often emerge in turbulent fluids. In this work, we formulate a stability theory, the stochastic structural stability theory (SSST), for the emergence of jets under external random excitation. We analytically investigate the structural stability of a two-dimensional homogeneous fluid enclosed in a channel and subjected to homogeneous random forcing. We show that two generic competing mechanisms control the instability that gives rise to the emergence of an infinitesimal jet: advection of the eddy vorticity by the mean flow that is shown to be jet forming and advection of the vorticity gradient of the jet by the eddies that is shown to hinder the formation of the mean flow. We show that stochastic forcing with small streamwise coherence and an amplitude larger than a certain threshold leads to the emergence of jets in the channel through a bifurcation of the non-linear SSST system. [ABSTRACT FROM PUBLISHER]

The role of nonnormality in the overreflection of gravity waves is investigated. In the limit of weak stratification, wave packets having a critical level inside a shear layer of finite depth are reflected with amplified energy. This process, which exhibits the characteristics of stimulated emission, occurs in three stages: first, the incoming wave enters the shear layer and excites nonpropagating perturbations leaning with and against the shear. Subsequently, the energy of perturbations leaning against the shear grows in a manner similar to energy growth of perturbations in constant shear flows, indicating that the Orr mechanism that is slightly modified by stratification underlies the observed growth. Finally, the amplified perturbations excite propagating waves originating from the vicinity of the shear layer boundary. The role of nonnormality in this process is also investigated from the perspective of the associated nonorthogonality of the modes of the dynamical system. It is found that the incident wave packet projects on nonorthogonal analytic modes having the structure of a downward propagating wave in the far field below the shear layer and overreflection expressed by the interaction among these nonorthogonal modes. [ABSTRACT FROM AUTHOR]

Non-modal mechanisms underlying transient growth of propagating acoustic waves and non-propagating vorticity perturbations in an unbounded compressible shear flow are investigated, making use of closed form solutions. Propagating acoustic waves amplify mainly due to two mechanisms: growth due to advection of streamwise velocity that is typically termed as the lift-up mechanism leading for large Mach numbers to an almost linear increase in streamwise velocity with time and growth due to the downgradient irrotational component of the Reynolds stress leading to linear growth of acoustic wave energy for large times. Synergy between these mechanisms along with the downgradient solenoidal component of the Reynolds stress produces large and robust energy amplification. On the other hand, non-propagating vorticity perturbations amplify due to kinematic deformation of vorticity by the mean flow. For weakly compressible flows, an initial vorticity perturbation abruptly excites acoustic waves with exponentially small amplitude, and the energy gained by vorticity perturbations is transferred back to the mean flow. For moderate Mach numbers, a strong coupling between vorticity perturbations and acoustic waves is found with the energy gained by vorticity perturbations being transferred to acoustic waves that are abruptly excited by the vortex. Calculation of the optimal perturbations for a viscous flow shows that for low Mach numbers, acoustic wave excitation by vorticity perturbations and the subsequent growth of acoustic waves leads to robust energy growth of the order of Reynolds number, while for large Mach numbers, synergy between the lift-up mechanism and the downgradient solenoidal component of the Reynolds stress dominates the growth and leads to a comparable large amplification of streamwise velocity. [ABSTRACT FROM AUTHOR]

In this article, a number of design approaches for 3D reinforced concrete (RC) buildings are formulated in the framework of structural optimization problems and are assessed in terms of their performance under earthquake loading. In particular, three design approaches for RC buildings are considered in this study. In the first, the initial construction cost is considered as the objective function to be minimized. The second one is formulated as a minimization problem of the torsional response, while a combined formulation is also examined as the third design approach. The third approach is considered with two distinctive formulations. According to the first approach, the torsional behavior is minimized by minimizing the eccentricity between the mass and rigidity centers, while the second one is achieved by minimizing the eccentricity between the mass and strength centers. It is shown that the optimized designs obtained according to the minimum eccentricity of the rigidity center behave better in frequent (50/50 hazard level) and occasional (10/50 hazard level) earthquakes, while the designs obtained according to the minimum eccentricity of the strength center formulation was found better in rare (2/50 hazard level) events. Designs obtained through a combined formulation seem to behave equally well in the three hazard levels examined. [ABSTRACT FROM AUTHOR]

Interaction of internal gravity waves with a horizontal shear flow in the absence of potential vorticity perturbations is investigated making use of closed-form solutions. Localized wave packet trajectories are obtained, the energy growth mechanisms occurring are identified, and the potential role of perturbation growth in wave breaking is assessed. Regarding meridional propagation, the wave packet motion is limited by turning levels where the waves are reflected and trapping levels where the waves stagnate. Regarding perturbation energy amplification, two growth mechanisms can be distinguished: growth due to advection of zonal velocity and growth due to downgradient Reynolds stresses. The three-dimensional perturbations producing optimal energy growth reveal that these two mechanisms produce large and robust amplification of zonal velocity and/or density and vertical velocity, potentially leading to shear or convective instability. For large static stability, amplification of density perturbations in conjunction with vertical orientation of the constant phase lines close to the trapping level potentially leads to a convective collapse of the wave packet near the trapping level, in agreement with existing direct numerical simulation studies. For lower static stability and for waves with phase lines oriented horizontally, growth due to advection of zonal velocity dominates, leading to rapid growth of streamwise streaks within the localized wave packet and potentially to shear instability. [ABSTRACT FROM AUTHOR]

Interaction among potential vorticity perturbations and propagating internal gravity waves in a horizontally sheared zonal flow is investigated. In the strong stratification limit, an initial vorticity perturbation weakly excites two propagating gravity waves while the density component of the potential vorticity perturbation is significantly amplified, potentially leading to convective collapse. If stratification is sufficiently weak, a strong coupling between vorticity perturbations and gravity waves is found and spontaneous gravity wave generation occurs. This coupling can be traced to the nonnormal interaction between the potential vorticity and gravity wave manifolds in the weak stratification limit. Vorticity perturbations amplify in energy due to downgradient Reynolds stress when their phase lines tilt against the shear and the large growth attained is transferred to propagating gravity waves. When the flow geometry is such that the excited gravity waves are confined in the vicinity of the vorticity perturbation by their trapping levels, an overall convective collapse of this region can be anticipated. On the other hand, when the flow geometry permits wave propagation, significant gravity wave emission occurs. [ABSTRACT FROM AUTHOR]

Shear flows with a free surface possess diverse branches of modal instabilities. By approximating the mean flow with a piecewise linear profile, an understanding and classification of the instabilities can be achieved by studying the interaction of the edge waves that arise at the density discontinuity at the surface and the vorticity waves that are supported at the mean vorticity gradient discontinuities in the interior. The various branches of instability are identified and their physical origin is clarified. The edge waves giving rise to the modal instabilities can also lead to a modest transient growth that extends into the regions of neutrality of the flow. However, when the continuous spectrum is excited substantial transient growth can arise and the optimal perturbations attain greater energy when compared with the energy of the fastest modal growing perturbation. These optimal perturbations utilize the continuous spectrum to excite at large amplitude the neutral or amplifying modes of the system. [ABSTRACT FROM AUTHOR]

Layered flows that are commonly observed in stratified turbulence are susceptible to the Taylor–Caulfield Instability. While the modal stability properties of layered shear flows have been examined, the non-modal growth of perturbations has not been investigated. In this work, the tools of Generalized Stability Theory are utilized to study linear transient growth within a finite time interval of two-dimensional perturbations in an inviscid, three-layer constant shear flow under the Boussinesq approximation. It is found that, for low optimization times, small-scale perturbations utilize the Orr mechanism and achieve growth equal to that in the case of an unstratified flow. For larger optimization times, transient growth is much larger compared to growth for an unstratified flow as the Kelvin–Orr waves comprising the continuous spectrum of the dynamical operator and the gravity edge-waves comprising the discrete spectrum interact synergistically. Maximum growth is obtained for perturbations with scales within the region of instability, but significant growth is maintained for modally stable perturbations as well. For perturbations with scales within the unstable region, the unstable normal modes are excited at high amplitude by their bi-orthogonals. For perturbations with modally stable scales, the Orr mechanism is utilized to excite at high amplitude neutral propagating waves resembling the neutral Taylor–Caulfield modes. [ABSTRACT FROM AUTHOR]

Interaction between the midlatitude jet and gravity waves is examined, focusing on the nonnormality of the underlying linear dynamics, which plays an essential role in processing the wave activity and selecting structures that dominate wave momentum and energy transport. When the interior of a typical midlatitude jet is stochastically forced, waves with short horizontal wavelength are trapped inside the jet and deposit momentum and energy at jet interior critical levels. Longer waves transport momentum and energy away from the jet, and the resulting momentum flux divergence produces a significant deceleration of the tropospheric and lower-stratospheric jet. This induced drag is found to depend on the shape of the jet and on the horizontal wavelength of the excited waves, reaching a maximum at wavelength λx = 20 km and leading to a deceleration O(1) m s-1 day-1 for a stochastic forcing rate of 0.1 W m-2 distributed over the height of the jet. This deceleration is robust to changes in static stability but is reduced when the stochastic forcing is correlated over too long a time. Implications of gravity wave absorption for middle-atmosphere circulation are discussed, focusing on differences implied for acceleration of the winter and summer midlatitude upper-stratospheric jets. The tropospheric flow is found not only to passively filter transiting waves, but also to amplify portions of the wave spectrum in conjunction with the distributed forcing, leading to enhanced gravity wave momentum and energy fluxes in agreement with observations linking middle-atmosphere enhanced variance with regions of high jet velocities. [ABSTRACT FROM AUTHOR]

In this paper, the emission of internal gravity waves from a local westerly shear layer is studied. Thermal and/or vorticity forcing of the shear layer with a wide range of frequencies and scales can lead to strong emission of gravity waves in the region exterior to the shear layer. The shear flow not only passively filters and refracts the emitted wave spectrum, but also actively participates in the gravity wave emission in conjunction with the distributed forcing. This interaction leads to enhanced radiated momentum fluxes but more importantly to enhanced gravity wave energy fluxes. This enhanced emission power can be traced to the nonnormal growth of the perturbations in the shear region, that is, to the transfer of the kinetic energy of the mean shear flow to the emitted gravity waves. The emitted wave energy flux increases with shear and can become as large as 30 times greater than the corresponding flux emitted in the absence of a localized shear region. Waves that have horizontal wavelengths larger than the depth of the shear layer radiate easterly momentum away, whereas the shorter waves are trapped in the shear region and deposit their momentum at their critical levels. The observed spectrum, as well as the physical mechanisms influencing the spectrum such as wave interference and Doppler shifting effects, is discussed. While for large Richardson numbers there is equipartition of momentum among a wide range of frequencies, most of the energy is found to be carried by waves having vertical wavelengths in a narrow band around the value of twice the depth of the region. It is shown that the waves that are emitted from the shear region have vertical wavelengths of the size of the shear region. [ABSTRACT FROM AUTHOR]

The objective of this paper is to obtain the optimum design of 3D reinforced concrete buildings in terms of their performance under earthquake loading. This goal is achieved by considering the minimisation of the eccentricity between the mass centre and the rigidity centre of each storey layout as the optimisation objective in order to produce torsionally balanced structures. This problem is considered as a combined topology and sizing optimisation problem. The location and the size of the columns and the shear walls of the structure of each storey layout constitute the design variables. Apart from the constraints imposed by the seismic and reinforced concrete structure design codes, architectural restrictions are also taken into account. The test examples showed that a reduction in the structural cost of the building is achieved by minimising the eccentricity between the mass centre and the rigidity centre of each storey layout. Evolutionary optimisation algorithms and in particular a specially tailored algorithm based on Evolution Strategies is implemented for the solution of this type of structural optimisation problems. [ABSTRACT FROM AUTHOR]

Three-dimensional perturbations producing optimal energy growth in stratified, unbounded constant shear flow are determined. The optimal perturbations are intrinsically three-dimensional in structure. Streamwise rolls emerge as the optimally growing perturbations at long times, but their energy growth factor is limited by stratification to E = O (1/Ri), where Ri is the Richardson number. The perturbations that attain the greatest energy growth in the flow are combinations of Orr solutions and roll solutions that maximize their energy growth in typically O (10) advective time units. These optimal perturbations are localized in the high-shear regions of the boundary layer and are associated with strong updrafts and downdrafts that evolve into streamwise velocity streaky structures in the form of hairpin vortices in agreement with observations. [ABSTRACT FROM AUTHOR]

In this study, a climatology of two key boundary layer features, the Planetary Boundary Layer Height (PBLH) and the wind field over Greece is derived. The climatology is based on daily soundings collected in Athens, Thessaloniki and Heraklion and spanning a 32-year period. The PBLH is estimated using a method based on the gradient of potential temperature and a method based on the bulk Richardson number. The wind field is analyzed by calculating the wind shear and the turning angle of the wind vector between the surface and the top of the boundary layer. The PBLH of the daytime boundary layer over Athens and Thessaloniki is found to exhibit seasonal variability with summer maxima and winter minima and has annual median values in the range of 1.4–1.7 km estimated using the gradient method. The PBLH over Heraklion is found to exhibit weak seasonal variability with a lower median value of 1.2 km. The nighttime boundary layer over all three sites is found to be much shallower with PBLH values in the range of 150–200 m with no seasonal variations. In addition, the bulk Richardson number method is found to systematically underestimate the PBLH compared to the gradient method. The wind field in the daytime boundary layer at all three sites is found to have small shear of the order of 1 ms − 1 and wind turning angles that are lower than 15 degrees, while in the nocturnal boundary layer it has larger shear of the order of 5–10 ms − 1 with turning angles lower than 20 degrees. In addition, for both the daytime and the nighttime boundary layer there is no general preference for veering or backing. [ABSTRACT FROM AUTHOR]

A recent study of property valuation literature indicated that the vast majority of researchers and academics in the field of real estate are focusing on Mass Appraisals rather than on the further development of the existing valuation methods. Researchers are using a variety of mathematical models used within the field of Machine Learning, which are applied to real estate valuations with high accuracy. On the other hand, it appears that professional valuers do not use these sophisticated models during daily practice, rather they operate using the traditional five methods. The Department of Lands and Surveys in Cyprus recently published the property values (General Valuation) for taxation purposes which were calculated by applying a hybrid model based on the Cost approach with the use of regression analysis in order to quantify the specific parameters of each property. In this paper, the authors propose a number of algorithms based on Artificial Intelligence and Machine Learning approaches that improve the accuracy of these results significantly. The aim of this work is to investigate the capabilities of such models and how they can be used for the mass appraisal of properties, to highlight the importance of sensitivity analysis in such models and also to increase the transparency so that automated valuation models (AVM) can be used for the day-to-day work of the valuer. [ABSTRACT FROM AUTHOR]