地质导向钻井关键技术及方法

On the basis of analyzing the principle and realization of geo-steering drilling system, the key technologies and methods in it are systematically studied in this paper. In order to recognize lithology, distinguish stratum and track reservoirs, the techniques of MWD and data process about natural gamma, resistivity, inductive density and porosity are researched. The methods for pre-processing and standardizing MWD data and for converting geological data in directional and horizontal drilling are discussed, consequently the methods of data conversion between MD and TVD and those of formation description and adjacent well contrast are proposed. Researching the method of identifying sub-layer yields the techniques of single well explanation, multi-well evaluation and oil reservoir description. Using the extremum and variance clustering analysis realizes logging phase analysis and stratum subdivision and explanation, which provides a theoretical method and lays a technical basis for tracing oil reservoirs and achieving geo-steering drilling. Researching the technique for exploring the reservoir top with a holdup section provides a planning method of wellpath control scheme to trace oil and gas reservoir dynamically, which solves the problem of how to control well trajectory on condition that the layer’s TVD is uncertain. The control scheme and planning method of well path for meeting the demands of target hitting, soft landing and continuous steering respectively provide the technological guarantee to land safely and drill successfully for horizontal, extended-reach and multi-target wells. The integrative design and control technologies are researched based on geology, reservoir and drilling considering reservoir disclosing ratio as a primary index, and the methods for planning and control optimum wellpath under multi-target restriction, thus which lets the target wellpath lie the favorite position in oil reservoir during the process of geo-steering drilling. The BHA (bottomhole assembly) mechanical model is discussed using the finite element method, and the BHA design methods are given on the basis of mechanical analyses according to the shape of well trajectory and the characteristics of BHA’s structure and deformation. The methods for predicting the deflection rate of bent housing motors and designing their assemblies are proposed based on the principle of minimum potential energy, which can clearly show the relation between the BHA’s structure parameters and deflection rate, especially the key factors’ effect to the deflection rate. Moreover, the interaction model between bit and formation is discussed through the process of equivalent formation and equivalent bit considering the formation anisotropy and bit anisotropy on the basis of analyzing the influence factors of well trajectory. Accordingly, the inherence relationship among well trajectory, formation, bit and drilling direction is revealed, which lays the theory basis and technique for predicting and controlling well trajectory.

Protein Docking by the Underestimation of Free Energy Funnels in the Space of Encounter Complexes

Similarly to protein folding, the association of two proteins is driven by a free energy funnel, determined by favorable interactions in some neighborhood of the native state. We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of the interface side chains. The method, called semi-definite programming-based underestimation (SDU), employs a general quadratic function to underestimate a set of local energy minima and uses the resulting underestimator to bias further sampling. While SDU effectively minimizes functions with funnel-shaped basins, its application to docking in the rotational and translational space SE(3) is not straightforward due to the geometry of that space. We introduce a strategy that uses separate independent variables for side-chain optimization, center-to-center distance of the two proteins, and five angular descriptors of the relative orientations of the molecules. The removal of the center-to-center distance turns out to vastly improve the efficiency of the search, because the five-dimensional space now exhibits a well-behaved energy surface suitable for underestimation. This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. Results for standard protein docking benchmarks establish that in this space the free energy landscape is a funnel in a reasonably broad neighborhood of the native state and that the SDU strategy can generate docking predictions with less than 5 � ligand interface Ca root-mean-square deviation while achieving an approximately 20-fold efficiency gain compared to Monte Carlo methods.

Specialized Mappings Architecture with Applications to Vision-based Estimation of Articulated Body Pose

A fundamental task of vision systems is to infer the state of the world given some form of visual observations. From a computational perspective, this often involves facing an ill-posed problem; e.g., information is lost via projection of the 3D world into a 2D image. Solution of an ill-posed problem requires additional information, usually provided as a model of the underlying process. It is important that the model be both computationally feasible as well as theoretically well-founded. In this thesis, a probabilistic, nonlinear supervised computational learning model is proposed: the Specialized Mappings Architecture (SMA). The SMA framework is demonstrated in a computer vision system that can estimate the articulated pose parameters of a human body or human hands, given images obtained via one or more uncalibrated cameras. The SMA consists of several specialized forward mapping functions that are estimated automatically from training data, and a possibly known feedback function. Each specialized function maps certain domains of the input space (e.g., image features) onto the output space (e.g., articulated body parameters). A probabilistic model for the architecture is first formalized. Solutions to key algorithmic problems are then derived: simultaneous learning of the specialized domains along with the mapping functions, as well as performing inference given inputs and a feedback function. The SMA employs a variant of the Expectation-Maximization algorithm and approximate inference. The approach allows the use of alternative conditional independence assumptions for learning and inference, which are derived from a forward model and a feedback model. Experimental validation of the proposed approach is conducted in the task of estimating articulated body pose from image silhouettes. Accuracy and stability of the SMA framework is tested using artificial data sets, as well as synthetic and real video sequences of human bodies and hands.

The use of a dynamic truck-trailer drive-by system to monitor bridge damping

Bridge structures are continuously subject to degradation due to the environment, ageing and excess loading. Periodic monitoring of bridges is therefore a key part of any maintenance strategy as it can give early warning if a bridge becomes unsafe. This article investigates an alternative method for the monitoring of bridge dynamic behaviour: a truck-trailer vehicle system, with accelerometers fitted to the axles of the trailer. The method aims to detect changes in the damping of a bridge, which may indicate the existence of damage. A simplified vehicle-bridge interaction model is used in theoretical simulations to assess the effectiveness of the method in detecting those changes. The influence of road profile roughness on the vehicle vibration is overcome by recording accelerations from both axles of a trailer and then analysing the spectra of the difference in the accelerations between the two axles. The effectiveness of the approach in detecting damage simulated as a loss in stiffness is also investigated. In addition, the sensitivity of the approach to the vehicle speed, road roughness class, bridge span length, changes in the equal axle properties and noise is investigated.

Experimental investigation of a wavelet based drive-by bridge inspection system incorporating pattern recognition

This paper presents the results of an experimental investigation, carried out in order to verify the feasibility of a ‘drive-by’ approach which uses a vehicle instrumented with accelerometers to detect and locate damage in a bridge. In theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach in detecting damage in a bridge from vehicle accelerations. For this purpose, the accelerations are processed using a continuous wavelet transform and damage indicators are evaluated and compared. Alternative statistical pattern recognition techniques are incorporated to allow for repeated vehicle passes. Parameters such as vehicle speed, damage level, location and road roughness are varied in simulations to investigate the effect. A scaled laboratory experiment is carried out to assess the effectiveness of the approach in a more realistic environment, considering a number of bridge damage scenarios.

An indirect bridge inspection method incorporating a wavelet-based damage indicator and pattern recognition

In recent years, there has been a move towards the development of indirect structural health monitoring (SHM)techniques for bridges; the low-cost vibration-based method presented in this paper is such an approach. It consists of the use of a moving vehicle fitted with accelerometers on its axles and incorporates wavelet analysis and statistical pattern recognition. The aim of the approach is to both detect and locate damage in bridges while reducing the need for direct instrumentation of the bridge. In theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach in detecting damage in a bridge from vehicle accelerations. For this purpose, the accelerations are processed using a continuous wavelet transform as when the axle passes over a damaged section, any discontinuity in the signal would affect the wavelet coefficients. Based on these coefficients, a damage indicator is formulated which can distinguish between different damage levels. However, it is found to be difficult to quantify damage of varying levels when the vehicle’s transverse position is varied between bridge crossings. In a real bridge field experiment, damage was applied artificially to a steel truss bridge to test the effectiveness of the indirect approach in practice; for this purpose a two-axle van was driven across the bridge at constant speed. Both bridge and vehicle acceleration measurements were recorded. The dynamic properties of the test vehicle were identified initially via free vibration tests. It was found that the resulting damage indicators for the bridge and vehicle showed similar patterns, however, it was difficult to distinguish between different artificial damage scenarios.

Experimental validation of a drive-by stiffness identification method for bridge monitoring

An experimental investigation is carried out to verify the feasibility of using an instrumented vehicle to detect and monitor bridge dynamic parameters. The low-cost method consists of the use of a moving vehicle fitted with accelerometers on its axles. In the laboratory experiment, the vehicle–bridge interaction model consists of a scaled two-axle vehicle model crossing a simply supported steel beam. The bridge model also includes a scaled road surface profile. The effects of varying the vehicle model configuration and speed are investigated. A finite element beam model is calibrated using the experimental results, and a novel algorithm for the identification of global bridge stiffness is validated. Using measured vehicle accelerations as input to the algorithm, the beam stiffness is identified with a reasonable degree of accuracy.

Parametric study to extract bridge frequencies from the dynamic response of passing vehicles

A conventional way to identify bridge frequencies is utilizing vibration data measured directly from the bridge. A drawback with this approach is that the deployment and maintenance of the vibration sensors are generally costly and time-consuming. One way to cope with the drawback is an indirect approach utilizing vehicle vibrations while the vehicle passes over the bridge. In the indirect approach, however, the vehicle vibration includes the effect of road surface roughness, which makes it difficult to extract the bridge modal properties. One solution may be subtracting signals of two trailers towed by a vehicle to reduce the effect of road surface roughness. A simplified vehicle-bridge interaction model is used in the numerical simulation; the vehicle - trailer and bridge system are modeled as a coupled model. In addition, a laboratory experiment is carried out to verify results of the simulation and examine feasibility of the damage detection by the indirect method.

Elastodynamic Modeling and Analysis for an Exechon Parallel Kinematic Machine

As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.

A wavelet based drive-by bridge inspection system

This paper investigates a low-cost wavelet-based approach for the preliminary monitoring of bridge structures, consisting of the use of a vehicle fitted with accelerometers on its axles. The approach aims to reduce the need for direct instrumentation of the bridge. A time-frequency analysis is carried out in order to identify the existence and location of damage from vehicle accelerations. Firstly, in theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach. A number of damage indicators are evaluated and compared. A range of parameters such as the bridge span, vehicle speed, damage level and location, signal noise and road roughness are varied in simulations. Secondly, a scaled laboratory experiment is carried out to validate the results of the theoretical analysis and assess the ability of the selected damage indicators to detect changes in the bridge response from vehicle accelerations. 

Big and beautiful: attractiveness and health ratings of the female body by male "fat admirers"

This study examined the body weight and waist-to-hip ratio (WHR) preferences of “fat admirers” (FAs), that is, individuals who are sexually attracted to heavier partners. Fifty-six heterosexual men involved in the FA community rated a series of line drawings that varied in three levels of body weight and six of WHR for physical attractiveness and health. The results showed significant main effects of body weight and WHR, as well as a significant body weight × WHR interaction for both health ratings. In general, there was a preference for heavyweight figures and high WHRs for ratings of attractiveness and normal-weight figures and mid-ranging WHRs for ratings of health. Limitations of the study and explanations for fat admiration are discussed.

Curso E-learning de sistemas multicorpo (multibody systems) para engenheiros mecânicos

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Asymmetries of Influence: Differential Effects of Body Postures on Perceptions of Emotional Facial Expressions

The accuracy and speed with which emotional facial expressions are identified is influenced by body postures. Two influential models predict that these congruency effects will be largest when the emotion displayed in the face is similar to that displayed in the body: the emotional seed model and the dimensional model. These models differ in whether similarity is based on physical characteristics or underlying dimensions of valence and arousal. Using a 3- alternative forced-choice task in which stimuli were presented briefly (Exp 1a) or for an unlimited time (Exp 1b) we provide evidence that congruency effects are more complex than either model predicts; the effects are asymmetrical and cannot be accounted for by similarity alone. Fearful postures are especially influential when paired with facial expressions, but not when presented in a flanker task (Exp 2). We suggest refinements to each model that may account for our results and suggest that additional studies be conducted prior to drawing strong theoretical conclusions.

Modelling the rheology of sea ice as a collection of diamond-shaped floes

In polar oceans, seawater freezes to form a layer of sea ice of several metres thickness that can cover up to 8% of the Earth’s surface. The modelled sea ice cover state is described by thickness and orientational distribution of interlocking, anisotropic diamond-shaped ice floes delineated by slip lines, as supported by observation. The purpose of this study is to develop a set of equations describing the mean-field sea ice stresses that result from interactions between the ice floes and the evolution of the ice floe orientation, which are simple enough to be incorporated into a climate model. The sea ice stress caused by a deformation of the ice cover is determined by employing an existing kinematic model of ice floe motion, which enables us to calculate the forces acting on the ice floes due to crushing into and sliding past each other, and then by averaging over all possible floe orientations. We describe the orientational floe distribution with a structure tensor and propose an evolution equation for this tensor that accounts for rigid body rotation of the floes, their apparent re-orientation due to new slip line formation, and change of shape of the floes due to freezing and melting. The form of the evolution equation proposed is motivated by laboratory observations of sea ice failure under controlled conditions. Finally, we present simulations of the evolution of sea ice stress and floe orientation for several imposed flow types. Although evidence to test the simulations against is lacking, the simulations seem physically reasonable.

Body-centric modelling, identification, and acceleration tracking control of a quadrotor UAV

This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.