New Developments in Virtual X-ray Imaging: Fast Simulation Using a Deterministic Approach

Current techniques for production data integration into reservoir models can be broadly grouped into two categories: deterministic and Bayesian. The deterministic approach relies on imposing parameter smoothness constraints using spatial derivatives to ensure large-scale changes consistent with the low resolution of the production data. The Bayesian approach is based on prior estimates of model statistics such as parameter covariance and data errors and attempts to generate posterior models consistent with the static and dynamic data. Both approaches have been successful for field-scale applications although the computational costs associated with the two methods can vary widely. This is particularly the case for the Bayesian approach that utilizes a prior covariance matrix that can be large and full. To date, no systematic study has been carried out to examine the scaling properties and relative merits of the methods. The purpose of this paper is twofold. First, we systematically investigate the scaling of the computational costs for the deterministic and the Bayesian approaches for realistic field-scale applications. Our results indicate that the deterministic approach exhibits a linear increase in the CPU time with model size compared to a quadratic increase for the Bayesian approach. Second, we propose a fast and robust adaptation of the Bayesian formulation that preserves the statistical foundation of the Bayesian method and at the same time has a scaling property similar to that of the deterministic approach. This can lead to orders of magnitude savings in computation time for model sizes greater than 100,000 grid blocks. We demonstrate the power and utility of our proposed method using synthetic examples and a field example from the Goldsmith field, a carbonate reservoir in west Texas.

With the recent rising application of mathematical models in the field of computational systems biology, the interest in sensitivity analysis methods had increased. The stochastic approach, based on chemical master equations, and the deterministic approach, based on ordinary differential equations (ODEs), are the two main approaches for analyzing mathematical models of biochemical systems. In this work, the performance of these approaches to compute sensitivity coefficients is explored in situations where stochastic and deterministic simulation can potentially provide different results (systems with unstable steady states, oscillators with population extinction and bistable systems). We consider two methods in the deterministic approach, namely the direct differential method and the finite difference method, and five methods in the stochastic approach, namely the Girsanov transformation, the independent random number method, the common random number method, the coupled finite difference method and the rejection-based finite difference method. The reviewed methods are compared in terms of sensitivity values and computational time to identify differences in outcome that can highlight conditions in which one approach performs better than the other.

Conditional generative adversarial network-assisted system for radiation-free evaluation of scoliosis using a single smartphone photograph: a model development and validation study

International Reference Ionosphere and ray tracing algorithm are discussed in the paper. Three-dimensional real-time ray tracing method is illustrated In accordance with International Reference Ionosphere, ray tracing equations are resolved by Runge-Kutta method. Based on International Reference Ionosphere and ray tracing algorithm, the three-dimensional ray tracing simulation software is presented. The three-dimensional ray trace and the group path are estimated by the simulation software. The effectiveness and accuracy of the simulation results are verified by comparing with the experimental results.

In today’s workplace, the personal computer and spreadsheet have become commonplace, while lens design software, often costing more than the computer, is not. Any one of the generic spreadsheet programs can be an effective ray tracing tool. Anyone who has developed ray tracing software has found that the input/output problem can often be more difficult than the algorithms for ray tracing. The advancement in today’s spreadsheets has eliminated the need for sophisticated programming skills to produce usable ray tracing functions. The worksheet developed combines third-order ray tracing with aproximate polarization equations. Useful graphic functions can be developed for displaying the third-order surface contributions and the polarization change for each surface. Examples of the macros developed are shown. A demonstration of a double Gauss ray trace is given. These macros can also be a useful tool for those with high powered lens design software. The macros are designed so that a lens can be set up in the spreadsheet and used as the input to commercially available lens design software.

The application scenarios and requirements are more diverse in the fifth-generation (5G) era than before. In order to successfully support the system design and deployment, accurate channel modeling is important. Ray-tracing (RT) based deterministic modeling approach is accurate with detailed angular information and is a suitable candidate for predicting time-varying channel and multiple-input multiple-output (MIMO) channel for various frequency bands. However, the computational complexity and the utility of RT are the main concerns of users. Aiming at 5G and beyond wireless communications, this paper presents a comprehensive tutorial on the design of RT and the applications. The role of RT and the state-of-the-art RT techniques are reviewed. The features of academic and commercial RT based simulators are summarized and compared. The requirements, challenges, and developing trends of RT to enable the visions are discussed. The practices of the design of high-performance RT simulation platform for 5G and beyond communications are introduced, with the publicly available high-performance cloud-based RT simulation platform as the main reference. The hardware structure, networking, workflow, data flow and fundamental functions of a flexible high-performance RT platform are discussed. The applications of high-performance RT are presented based on two 5G scenarios, i.e., a 3.5 GHz Beijing vehicle-to-infrastructure scenario and a 28 GHz Manhattan outdoor scenario. The questions on how to calibrate and validate RT based on measurements, how to apply RT for mobile communications in moving scenarios, and how to evaluate MIMO beamforming technologies are answered. This tutorial will be especially useful for researchers who work on RT algorithms development and channel modeling to meet the evaluation requirements of 5G and beyond technologies.

Ray tracing is a frequently used method for acoustic simulations, valued for its calculation speed and ease of use. Although it is fast, there are no fully ray tracing-based real-time simulation methods or engines. Under real-time restrictions, ray tracing simulations lose precision and the variance inherent in the random simulation method has too much impact on the outcome. In this paper, an algorithm called iterative ray tracing is presented that reduces the negative effects of real-time restrictions by iteratively improving the initial calculation and increasing the precision over time. In addition, new estimates of the expected value and variance of ray tracing simulations are presented and used to show the iteration steps in the new algorithm reduce variance, while maintaining the expected value. Simulations using iterative ray tracing are compared to measurements and simulations using the classical ray tracing method, and it is shown that iterative ray tracing can be used to improve precision over time. Although more testing is needed, iterative ray tracing can be used to extend most ray tracing algorithms, in order to decrease the adverse effects of real-time restrictions.

Deterministic simulation of thermal neutron radiography and tomography

In the ray tracing method, each pixel can be computed independently. Therefore, when the ray tracing algorithm is implemented on a parallel computer, a group of pixels is usually assigned to each element processor. The element processor must have all the environment data and object data for the rendering. When there are too many objects for local memory, a distorted image will be generated. In solving this problem, to date, the necessary data had to be transmitted. However, when the number of element processors is increased, efficient rendering cannot be expected because of communication overheads. This paper proposes a hybrid parallel ray tracing algorithm that combines pixel-parallel and object-parallel ray tracing. As this algorithm inherits the advantages of pixel-parallel ray tracing, high efficiency can be achieved even on a parallel computer using a large number of element processors.

Ray tracing has been considered as the next generation CG technology as its photorealistic rendering results. However, heavy computation load is a bottleneck which hindering its popularization. Hardware acceleration has been proved to be an effective method for the efficiency improvement of ray tracing and many related works have been published. In this work, we study three level parallelisms existing in ray tracing and analyze the feasible parallel patterns for each level. Times consumed by different steps of the tracing process are tested and the key factors affecting computation efficiency are pointed out based on experiment results. Latency caused by extern memory accessing is explored and data caching using high speed storage resource is applied to improve the data accessing performance. We also show the influence of context data coupling of instructions on calculation speed and make clear the main obstacle for achieving high tracing efficient. Results in this paper will contribute to hardware acceleration of ray tracing algorithm and design of acceleration devices.

A high speed 'image-based' ray tracing algorithm is presented that applies to both indoor and microcellular environments. The building database and image generation operates in two dimensions. However, for each 2D path, all the corresponding rays are calculated in 3D including multiple floor-ceiling reflections for the indoor case and the extra ground reflection for the outdoor scenario. The field calculation is implemented using dimensional vector analysis with each ray considered separately. To show the practicality of such models, the ray tracing engine has been used to investigate a microcellular environment in the centre of Bristol. The speed and complexity of the resulting model is investigated as a function of the number of reflection, transmission and diffraction generations.

A fast 3-D ray tracing propagation prediction model based on virtual source tree is presented in this paper, whose theoretical foundations are geometrical optics(GO) and the uniform theory of diffraction(UTD). In terms of typical single room indoor scene, taking the geometrical and electromagnetic information into account, some acceleration techniques are adopted to raise the efficiency of the ray tracing algorithm. The simulation results indicate that the runtime of the ray tracing algorithm will sharply increase when the number of the objects in the single room is large enough. Therefore, GPU acceleration technology is used to solve that problem. As is known to all, GPU is good at calculation operation rather than logical judgment, so that tens of thousands of threads in CUDA programs are able to calculate at the same time, in order to achieve massively parallel acceleration. Finally, a typical single room with several objects is simulated by using the serial ray tracing algorithm and the parallel one respectively. It can be found easily from the results that compared with the serial algorithm, the GPU-based one can achieve greater efficiency.

Purpose: The latest publications indicate that the Ray Tracing algorithm significantly overestimates the dose delivered as compared to the Monte Carlo (MC) algorithm. The purpose of this study is to quantify this overestimation and to identify significant correlations between the RT and MC calculated dose distributions. Methods: Preliminary results are based on 50 preexisting RT algorithm dose optimization and calculation treatment plans prepared on the Multiplan treatment planning system (Accuray Inc., Sunnyvale, CA). The analysis will be expanded to include 100 plans. These plans are recalculated using the MC algorithm, with high resolution and 1% uncertainty. The geometry and number of beams for a given plan, as well as the number of monitor units, is constant for the calculations for both algorithms and normalized differences are compared. Results: MC calculated doses were significantly smaller than RT doses. The D95 of the PTV was 27% lower for the MC calculation. The GTV and PTV mean coverage were 13 and 39% less for MC calculation. The first parameter of conformality, as defined as the ratio of the Prescription Isodose Volume to the PTV Volume was on average 1.18 for RT and 0.62 for MC. Maximum doses delivered to OARs was reduced in the MC plans. The doses for 1000 and 1500 cc of total lung minus PTV, respectively were reduced by 39% and 53% for the MC plans. The correlation of the ratio of air in PTV to the PTV with the difference in PTV coverage had a coefficient of −0.54. Conclusion: The preliminary results confirm that the RT algorithm significantly overestimates the dosages delivered confirming previous analyses. Finally, subdividing the data into different size regimes increased the correlation for the smaller size PTVs indicating the MC algorithm improvement verses the RT algorithm is dependent upon the size of the PTV.

An efficient method, which is called particle triangular patch scanning ray tracing algorithm on the basis of convex geometry (PTPSRTACG), is presented to specify an incident ray, its corresponding impinging points on the particle surface and propagating process inside the particle necessary to the ray tracing. It is applicable for a particle of arbitrary shape. This ray tracing method can contribute to scientific visualization and interactive techniques and virtual reality.

To achieve high-fidelity synthetic aperture radar (SAR) simulated images of typical target, we propose an echo-based SAR imaging simulation method assisted by ray tracing. The method incorporates multiple scattering mechanisms and establishes a backscattering model under the far-field plane wave assumption. A ray tracing algorithm is employed to capture the amplitude and phase of multiple backscattering components from numerous microfacets distributed across the target surface. The total backscattering field is then computed through vector superposition. Based on the principle of azimuthal synthetic aperture, we account for the real-time relative motion between the sensor and the target. A global phase correction is performed by leveraging the slant range history. This process transforms the local far-field scattering phase, which is referenced to the target modeling center, into a globally coherent scattering field. Then, the target’s global backscattering field is accurately reconstructed and serves as the raw echo signal. The range-Doppler (RD) imaging algorithm is subsequently applied to focus the simulated echo signal and generate the final SAR image. We select a typical aircraft carrier target for testing evaluation. The target is placed in the beam radiation scene and subjected to multi-angle rotation to produce corresponding multi-angle simulated SAR images. Qualitative and quantitative comparisons are conducted against both the RaySAR commercial software and real SAR image to verify the effectiveness of the proposed method.