Three-dimensional surface reconstruction within noncontact diffuse optical tomography using structured light

A main field in biomedical optics research is diffuse optical tomography, where intensity variations of the transmitted light traversing through tissue are detected. Mathematical models and reconstruction algorithms based on finite element methods and Monte Carlo simulations describe the light transport inside the tissue and determine differences in absorption and scattering coefficients. Precise knowledge of the sample's surface shape and orientation is required to provide boundary conditions for these techniques. We propose an integrated method based on structured light three-dimensional (3-D) scanning that provides detailed surface information of the object, which is usable for volume mesh creation and allows the normalization of the intensity dispersion between surface and camera. The experimental setup is complemented by polarization difference imaging to avoid overlaying byproducts caused by inter-reflections and multiple scattering in semitransparent tissue.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

Three dimensional finite element simulation of polymer melting and flow in a single-screw extruder : optimization of screw channel geometry

Single-screw extrusion is one of the widely used processing methods in plastics industry, which was the third largest manufacturing industry in the United States in 2007 [5]. In order to optimize the single-screw extrusion process, tremendous efforts have been devoted for development of accurate models in the last fifty years, especially for polymer melting in screw extruders. This has led to a good qualitative understanding of the melting process; however, quantitative predictions of melting from various models often have a large error in comparison to the experimental data. Thus, even nowadays, process parameters and the geometry of the extruder channel for the single-screw extrusion are determined by trial and error. Since new polymers are developed frequently, finding the optimum parameters to extrude these polymers by trial and error is costly and time consuming. In order to reduce the time and experimental work required for optimizing the process parameters and the geometry of the extruder channel for a given polymer, the main goal of this research was to perform a coordinated experimental and numerical investigation of melting in screw extrusion. In this work, a full three-dimensional finite element simulation of the two-phase flow in the melting and metering zones of a single-screw extruder was performed by solving the conservation equations for mass, momentum, and energy. The only attempt for such a three-dimensional simulation of melting in screw extruder was more than twenty years back. However, that work had only a limited success because of the capability of computers and mathematical algorithms available at that time. The dramatic improvement of computational power and mathematical knowledge now make it possible to run full 3-D simulations of two-phase flow in single-screw extruders on a desktop PC. In order to verify the numerical predictions from the full 3-D simulations of two-phase flow in single-screw extruders, a detailed experimental study was performed. This experimental study included Maddock screw-freezing experiments, Screw Simulator experiments and material characterization experiments. Maddock screw-freezing experiments were performed in order to visualize the melting profile along the single-screw extruder channel with different screw geometry configurations. These melting profiles were compared with the simulation results. Screw Simulator experiments were performed to collect the shear stress and melting flux data for various polymers. Cone and plate viscometer experiments were performed to obtain the shear viscosity data which is needed in the simulations. An optimization code was developed to optimize two screw geometry parameters, namely, screw lead (pitch) and depth in the metering section of a single-screw extruder, such that the output rate of the extruder was maximized without exceeding the maximum temperature value specified at the exit of the extruder. This optimization code used a mesh partitioning technique in order to obtain the flow domain. The simulations in this flow domain was performed using the code developed to simulate the two-phase flow in single-screw extruders.

Modeling spontaneous three-dimensional polymerization

For human beings, the origin of life has always been an interesting and mysterious matter, particularly how life arose from inorganic matter through natural processes. Polymerization is always involved in such processes. In this paper we built what we refer to as ideal and physical models to simulate spontaneous polymerization based on certain physical principles. As the modeling confirms, without taking external energy, small and simple inorganic molecules formed bigger and more complicated molecules, which are necessary ingredients of all living organisms. In our simulations, we utilized actual ranges of parameters according to their experimentally observed values. The results from the simulations led to a good agreement with the nature of polymerization. After sorting out through all the models that were built, we arrived at a final model that, it is hoped, can be used to simply and efficiently describe spontaneous polymerization using only three parameters: the dipole moment, the distance between molecules, and the temperature.

A comparison between two-dimensional and three-dimensional cephalometry on frontal radiographs and on cone beam computed tomography scans of human skulls

The aim of this study was to evaluate whether measurements performed on conventional frontal radiographs are comparable to measurements performed on three-dimensional (3D) models of human skulls derived from cone beam computed tomography (CBCT) scans and if the latter can be used in longitudinal studies. Cone beam computed tomography scans and conventional frontal cephalometric radiographs were made of 40 dry human skulls. From the CBCT scan a 3D model was constructed. Standard cephalometric software was used to identify landmarks and to calculate ratios and angles. The same operator identified 10 landmarks on both types of cephalometric radiographs, and on all images, five times with a time interval of 1 wk. Intra-observer reliability was acceptable for all measurements. There was a statistically significant and clinically relevant difference between measurements performed on conventional frontal radiographs and on 3D CBCT-derived models of the same skull. There was a clinically relevant difference between angular measurements performed on conventional frontal cephalometric radiographs, compared with measurements performed on 3D models constructed from CBCT scans. We therefore recommend that 3D models should not be used for longitudinal research in cases where there are only two-dimensional (2D) records from the past.

Three-dimensional electron beam dose calculations

The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^

Extension and Partitioning in an Oblique Subduction Zone, New Zealand: Constraints from Three-Dimensional Numerical Modeling

Contraction, strike slip, and extension displacements along the Hikurangi margin northeast of the North Island of New Zealand coincide with large lateral gradients in material properties. We use a finite- difference code utilizing elastic and elastic-plastic rheologies to build large- scale, three-dimensional numerical models which investigate the influence of material properties on velocity partitioning within oblique subduction zones. Rheological variation in the oblique models is constrained by seismic velocity and attenuation information available for the Hikurangi margin. We compare the effect of weakly versus strongly coupled subduction interfaces on the development of extension and the partitioning of velocity components for orthogonal and oblique convergence and include the effect of ponded sediments beneath the Raukumara Peninsula. Extension and velocity partitioning occur if the subduction interface is weak, but neither develops if the subduction interface is strong. The simple mechanical model incorporating rheological variation based on seismic observations produces kinematics that closely match those published from the Hikurangi margin. These include extension within the Taupo Volcanic Zone, uplift over ponded sediments, and dextral contraction to the south.

Three-Dimensional Mechanics of Yakutat Convergence in the Southern Alaskan Plate Corner

Three-dimensional numerical models are used to investigate the mechanical evolution of the southern Alaskan plate corner where the Yakutat and the Pacific plates converge on the North American plate. The evolving model plate boundary consists of Convergent, Lateral, and Subduction subboundaries with flow separation of incoming material into upward or downward trajectories forming dual, nonlinear advective thermal/mechanical anomalies that fix the position of major subaerial mountain belts. The model convergent subboundary evolves into two teleconnected orogens: Inlet and Outlet orogens form at locations that correspond with the St. Elias and the Central Alaska Range, respectively, linked to the East by the Lateral boundary. Basins form parallel to the orogens in response to the downward component of velocity associated with subduction. Strain along the Lateral subboundary varies as a function of orogen rheology and magnitude and distribution of erosion. Strain-dependent shear resistance of the plate boundary associated with the shallow subduction zone controls the position of the Inlet orogen. The linkages among these plate boundaries display maximum shear strain rates in the horizontal and vertical planes where the Lateral subboundary joins the Inlet and Outlet orogens. The location of the strain maxima shifts with time as the separation of the Inlet and Outlet orogens increases. The spatiotemporal predictions of the model are consistent with observed exhumation histories deduced from thermochronology, as well as stratigraphic studies of synorogenic deposits. In addition, the complex structural evolution of the St Elias region is broadly consistent with the predicted strain field evolution. Citation: Koons, P. O., B. P. Hooks, T. Pavlis, P. Upton, and A. D. Barker (2010), Three-dimensional mechanics of Yakutat convergence in the southern Alaskan plate corner, Tectonics, 29, TC4008, doi: 10.1029/2009TC002463.

Air-Sea Interactions During the Passage of a Winter Storm Over the Gulf Stream: A Three-Dimensional Coupled Atmosphere-Ocean Model Study

A three-dimensional, regional coupled atmosphere-ocean model with full physics is developed to study air-sea interactions during winter storms off the U. S. east coast. Because of the scarcity of open ocean observations, models such as this offer valuable opportunities to investigate how oceanic forcing drives atmospheric circulation and vice versa. The study presented here considers conditions of strong atmospheric forcing (high wind speeds) and strong oceanic forcing (significant sea surface temperature (SST) gradients). A simulated atmospheric cyclone evolves in a manner consistent with Eta reanalysis, and the simulated air-sea heat and momentum exchanges strongly affect the circulations in both the atmosphere and the ocean. For the simulated cyclone of 19-20 January 1998, maximum ocean-to-atmosphere heat fluxes first appear over the Gulf Stream in the South Atlantic Bight, and this results in rapid deepening of the cyclone off the Carolina coast. As the cyclone moves eastward, the heat flux maximum shifts into the region near Cape Hatteras and later northeast of Hatteras, where it enhances the wind locally. The oceanic response to the atmospheric forcing is closely related to the wind direction. Southerly and southwesterly winds tend to strengthen surface currents in the Gulf Stream, whereas northeasterly winds weaken the surface currents in the Gulf Stream and generate southwestward flows on the shelf. The oceanic feedback to the atmosphere moderates the cyclone strength. Compared with a simulation in which the oceanic model always passes the initial SST to the atmospheric model, the coupled simulation in which the oceanic model passes the evolving SST to the atmospheric model produces higher ocean-to-atmosphere heat flux near Gulf Stream meander troughs. This is due to wind-driven lateral shifts of the stream, which in turn enhance the local northeasterly winds. Away from the Gulf Stream the coupled simulation produces surface winds that are 5 similar to 10% weaker. Differences in the surface ocean currents between these two experiments are significant on the shelf and in the open ocean.

Systematic literature review of digital three-dimensional superimposition techniques to create virtual dental patients

PURPOSE Digital developments have led to the opportunity to compose simulated patient models based on three-dimensional (3D) skeletal, facial, and dental imaging. The aim of this systematic review is to provide an update on the current knowledge, to report on the technical progress in the field of 3D virtual patient science, and to identify further research needs to accomplish clinical translation. MATERIALS AND METHODS Searches were performed electronically (MEDLINE and OVID) and manually up to March 2014 for studies of 3D fusion imaging to create a virtual dental patient. Inclusion criteria were limited to human studies reporting on the technical protocol for superimposition of at least two different 3D data sets and medical field of interest. RESULTS Of the 403 titles originally retrieved, 51 abstracts and, subsequently, 21 full texts were selected for review. Of the 21 full texts, 18 studies were included in the systematic review. Most of the investigations were designed as feasibility studies. Three different types of 3D data were identified for simulation: facial skeleton, extraoral soft tissue, and dentition. A total of 112 patients were investigated in the development of 3D virtual models. CONCLUSION Superimposition of data on the facial skeleton, soft tissue, and/or dentition is a feasible technique to create a virtual patient under static conditions. Three-dimensional image fusion is of interest and importance in all fields of dental medicine. Future research should focus on the real-time replication of a human head, including dynamic movements, capturing data in a single step.

Reduced order modeling of three dimensional external aerodynamic flows

A method is presented to construct computationally efficient reduced-order models (ROMs) of three-dimensional aerodynamic flows around commercial aircraft components. The method is based on the proper orthogonal decomposition (POD) of a set of steady snapshots, which are calculated using an industrial solver based on some Reynolds averaged Navier-Stokes (RANS) equations. The POD-mode amplitudes are calculated by minimizing a residual defined from the Euler equations, even though the snapshots themselves are calculated from viscous equations. This makes the ROM independent of the peculiarities of the solver used to calculate the snapshots. Also, both the POD modes and the residual are calculated using points in the computational mesh that are concentrated in a close vicinity of the aircraft, which constitute a much smaller number than the total number of mesh points. Despite these simplifications, the method provides quite good approximations of the flow variables distributions in the whole computational domain, including the boundary layer attached to the aircraft surface and the wake. Thus, the method is both robust and computationally efficient, which is checked considering the aerodynamic flow around a horizontal tail plane, in the transonic range 0.4?Mach number?0.8, ?3°?angle of attack?3°.

Edge Detection by Adaptive Splitting II. The Three-Dimensional Case

In Llanas and Lantarón, J. Sci. Comput. 46, 485–518 (2011) we proposed an algorithm (EDAS-d) to approximate the jump discontinuity set of functions defined on subsets of ℝ d . This procedure is based on adaptive splitting of the domain of the function guided by the value of an average integral. The above study was limited to the 1D and 2D versions of the algorithm. In this paper we address the three-dimensional problem. We prove an integral inequality (in the case d=3) which constitutes the basis of EDAS-3. We have performed detailed computational experiments demonstrating effective edge detection in 3D function models with different interface topologies. EDAS-1 and EDAS-2 appealing properties are extensible to the 3D case

Comparison of dynamic effects of high-speed traffic load on ballasted track using a simplified two-dimensional and full three-dimensional model.

The vertical dynamic actions transmitted by railway vehicles to the ballasted track infrastructure is evaluated taking into account models with different degree of detail. In particular, we have studied this matter from a two-dimensional (2D) finite element model to a fully coupled three-dimensional (3D) multi-body finite element model. The vehicle and track are coupled via a non-linear Hertz contact mechanism. The method of Lagrange multipliers is used for the contact constraint enforcement between wheel and rail. Distributed elevation irregularities are generated based on power spectral density (PSD) distributions which are taken into account for the interaction. The numerical simulations are performed in the time domain, using a direct integration method for solving the transient problem due to the contact nonlinearities. The results obtained include contact forces, forces transmitted to the infrastructure (sleeper) by railpads and envelopes of relevant results for several track irregularities and speed ranges. The main contribution of this work is to identify and discuss coincidences and differences between discrete 2D models and continuum 3D models, as wheel as assessing the validity of evaluating the dynamic loading on the track with simplified 2D models

Three-dimensional inverse modelling of magnetic anomaly sources based on a genetic algorithm.

We present a modelling method to estimate the 3-D geometry and location of homogeneously magnetized sources from magnetic anomaly data. As input information, the procedure needs the parameters defining the magnetization vector (intensity, inclination and declination) and the Earth's magnetic field direction. When these two vectors are expected to be different in direction, we propose to estimate the magnetization direction from the magnetic map. Then, using this information, we apply an inversion approach based on a genetic algorithm which finds the geometry of the sources by seeking the optimum solution from an initial population of models in successive iterations through an evolutionary process. The evolution consists of three genetic operators (selection, crossover and mutation), which act on each generation, and a smoothing operator, which looks for the best fit to the observed data and a solution consisting of plausible compact sources. The method allows the use of non-gridded, non-planar and inaccurate anomaly data and non-regular subsurface partitions. In addition, neither constraints for the depth to the top of the sources nor an initial model are necessary, although previous models can be incorporated into the process. We show the results of a test using two complex synthetic anomalies to demonstrate the efficiency of our inversion method. The application to real data is illustrated with aeromagnetic data of the volcanic island of Gran Canaria (Canary Islands).

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.