Ray Tracing Algorithm Research Articles

Measurement method of hot forging dimension based on green laser depth information.

The application field of large forgings is extensive. Accurate dimensional measurement is an important factor to ensure the quality of the finished forging product when it is forged at high temperature. Therefore, this paper proposes a green laser scanning measurement method based on depth information. First, a geometric measurement model based on depth information is established by studying the relationship between green laser depth information and forging dimension. Then, based on the heat transfer theory, distribution of the temperature field around hot forgings is studied, and an error function caused by light refraction is established using a ray tracing algorithm. After that, the error function is used to modify the measurement model to obtain the accurate distance between the forging and background plane and then obtain the dimensional information of the forging. Finally, this measurement method was experimentally verified in the laboratory, and the experimental results show that the measurement error of this method meets the dimensional measurement requirements of large hot forgings.

Thermal and energy analysis of a novel solar updraft tower design with divergent chimney and convergent collector concept: CFD analysis with experimental validation

Abstract The fact that energy sources are heavily dependent on fossil fuels increases the need for alternative energy day by day. Solar energy is the most popular alternative energy source with massive potential. Solar chimney power plants (SCPP) are one of the systems of interest based on solar energy. SCPP systems are rare systems that can provide 24-hour power output. Their performance has been the subject of constant research since the first pilot plant in Manzanares. Design is crucial for performance figures of SCPPs, and the limitation of climatic parameters causes the system to be approached with different designs. This study makes a 3D CFD model by combining the divergent chimney and convergent collector structure based on the first pilot plant. The solar ray tracing algorithm and the RNG k-e turbulence model are applied and the model equations are solved under dynamic conditions with the reliable software ANSYS FLUENT. After the mesh-independent solution of the model is complete, it is validated with experimental data. The two cases are compared for solar radiation of 1000 W/m2 and environmental temperature of 293 K. A power output of 50.51 kW is achieved for standard pilot sizing. With the new model, the power output rises to 146.34 kW. It is seen that the divergent chimney and convergent collector affect the airflow in the system, increasing the maximum air velocity to 19.363 m/s. In parallel with the experimental data, it is seen that the temperature on the ground exceeds 360 K in the CFD results.

The expression of multimedia animation art design in the era of artificial intelligence

Abstract Aesthetic rules are the basis of animation art design, combined with the user-centered design method is a new form of multimedia animation art design. This paper combines the existing three-dimensional animation art forms of expression, the use of points, lines, and surfaces to generate three-dimensional animation three-dimensional space, and selected virtual reality technology to achieve three-dimensional animation conversion. Based on ray tracing algorithm and radiance global illumination technology, to optimize animation scene realism, analyze the difficulties of rendering image styles. Combined with the Canny edge extraction algorithm to extract the target area contour, homogenization processing of local area coloring, fusion of the extracted contour and coloring area, the formation of animation style rendering, constituting the design of this paper three-dimensional animation art design expression. Analyze the rendering data of trees in a typical natural scene and use design evaluation indexes to assess the performance impact of animation scene art design. The average score for the animation scene expressing information content, the average score for the animation matching with the information, and the average score for the animation effect art and beauty are 7.672, 7.027, and 7.474, respectively. The scores indicate that the animation art design expression proposed in this paper can provide a more accurate depiction of the aesthetics of animation art.

Towards Quantum Ray Tracing.

Rendering on conventional computers is capable of generating realistic imagery, but the computational complexity of these light transport algorithms is a limiting factor of image synthesis. Quantum computers have the potential to significantly improve rendering performance through reducing the underlying complexity of the algorithms behind light transport. This paper investigates hybrid quantum-classical algorithms for ray tracing, a core component of most rendering techniques. Through a practical implementation of quantum ray tracing in a 3D environment, we show quantum approaches provide a quadratic improvement in query complexity compared to the equivalent classical approach. Based on domain specific knowledge, we then propose algorithms to significantly reduce the computation required for quantum ray tracing through exploiting image space coherence and a principled termination criteria for quantum searching. We show results obtained using a simulator for both Whitted style ray tracing, and for accelerating ray tracing operations when performing classical Monte Carlo integration for area lights and indirect illumination.

The Implementation of Ray Tracing Algorithm with OpenMP Parallelization

The Implementation of Ray Tracing Algorithm with OpenMP Parallelization

Efficient Binocular Rendering of Volumetric Density Fields With Coupled Adaptive Cube-Map Ray Marching for Virtual Reality.

Creating visualizations of multiple volumetric density fields is demanding in virtual reality (VR) applications, which often include divergent volumetric density distributions mixed with geometric models and physics-based simulations. Real-time rendering of such complex environments poses significant challenges for rendering quality and performance. This article presents a novel scheme for efficient real-time rendering of varying translucent volumetric density fields with global illumination (GI) effects on high-resolution binocular VR displays. Our scheme proposes creative solutions to address three challenges involved in the target problem. First, to tackle the doubled heavy workloads of binocular ray marching, we explore the anti-aliasing principles and more advanced potentials of ray marching on interior cube-map faces, and propose a coupled ray-marching technique that converges to multi-resolution cube maps with interleaved adaptive sampling. Second, we devise a fully dynamic ambient GI approximation method that leverages spherical-harmonics (SH) transform information of the phase function to reduce the huge amount of ray sampling required for GI while ensuring fidelity. The method catalyzes spatial ray-marching reuse and adaptive temporal accumulation. Third, we deploy a two-phase ray-tracing algorithm with a tiled k-buffer to achieve fast processing of order-independent transparency (OIT) for multiple volume instances. Consequently, high-quality and high-performance real-time dynamic volume rendering can be achieved under constrained budgets controlled by developers. As our solution supports mixed mesh-volume rendering, the test results prove the practical usefulness of our approach for high-resolution binocular VR rendering on hybrid multi-volumetric and geometric environments.

Numerical investigation on the effect of different types of configuration on the optical performance of solar flat plat reflecting system

The solar flat plate reflecting system (SFPRS) and its configuration significantly influence the reflection pattern of the solar radiation to the receiving surface. Present study numerically investigates the impact of square type configuration (STC) and hexagonal type configuration (HTC), on the performance of SFPRS by analysing the behaviour of beam rays and their interaction with the reflectors. The derived equations for solar radiation and fundamental equations of three-dimensional geometry were employed to develop a customized ray tracing algorithm (RTA) within the MATLAB software. The code incorporates a methodology to explore the behaviour of rays, including direct rays (DR), single reflected rays (SR), twice reflected rays (TR), three times reflected rays (THR), and rays leaving the system (LR). The results for the STC were validated with previous successful experimental outcomes. The optical performance of HTC is 15% higher than STC. Additionally, HTC demonstrates geometrical advantages over STC with an 8% increase in SR and a 13% increase in TR types of rays. Besides, STC exhibits greater participation of THRs and LRs type’s rays, resulting in lower optical efficiency. Consequently, the study concludes that the use of HTC is preferable over STC, when dealing with low solar altitude angles on multiple days.

Three-dimensional dose prediction based on deep convolutional neural networks for brain cancer in CyberKnife: accurate beam modelling of homogeneous tissue.

Accurate beam modelling is essential for dose calculation in stereotactic radiation therapy (SRT), such as CyberKnife treatment. However, the present deep learning methods only involve patient anatomical images and delineated masks for training. These studies generally focus on traditional intensity-modulated radiation therapy (RT) plans. Nevertheless, this paper aims to develop a deep CNN-based method for CyberKnife plan dose prediction about brain cancer patients. It utilized modelled beam information, target delineation, and patient anatomical information. This study proposes a method that adds beam information to predict the dose distribution of CyberKnife in brain cases. A retrospective dataset of 88 brain and abdominal cancer patients treated with the Ray-tracing algorithm was performed. The datasets include patients' anatomical information (planning CT), binary masks for organs at risk (OARs) and targets, and clinical plans (containing beam information). The datasets were randomly split into 68, 6, and 14 brain cases for training, validation, and testing, respectively. Our proposed method performs well in SRT dose prediction. First, for the gamma passing rates in brain cancer cases, with the 2 mm/2% criteria, we got 96.7% ± 2.9% for the body, 98.3% ± 3.0% for the planning target volume, and 100.0% ± 0.0% for the OARs with small volumes referring to the clinical plan dose. Secondly, the model predictions matched the clinical plan's dose-volume histograms reasonably well for those cases. The differences in key metrics at the target area were generally below 1.0 Gy (approximately a 3% difference relative to the prescription dose). The preliminary results for selected 14 brain cancer cases suggest that accurate 3-dimensional dose prediction for brain cancer in CyberKnife can be accomplished based on accurate beam modelling for homogeneous tumour tissue. More patients and other cancer sites are needed in a further study to validate the proposed method fully. With accurate beam modelling, the deep learning model can quickly generate the dose distribution for CyberKnife cases. This method accelerates the RT planning process, significantly improves its operational efficiency, and optimizes it.

GPU-accelerated polyenergetic forward projection for 9 MeV industrial CT system

Polyenergetic forward projection has great significance in inspecting hazardous materials, establishing optimal radiographic variables and investigating beam hardening effects. However, it is computationally intensive to perform polyenergetic forward-projection calculations for high-resolution phantoms. To address this issue, a rapid polyenergetic forward-projection algorithm is proposed for a 9 MeV industrial computed tomography (CT) system. The FLUktuierende KAskade (FLUKA) software package is used to generate the 9 MeV X-ray spectrum data. Two voxelised phantoms are used to model scanned objects, one being a multi-material cylinder and the other a single-material turbine blade. An incremental version of Siddon's algorithm is adopted to calculate the intersection lengths between the X-rays and the auxiliary phantoms. Three strategies are utilised to accelerate the calculation, in which: the intersection lengths do not vary with the energy bins and can be used repeatedly until all the energy bins are counted; a graphics processing unit (GPU) is used to accelerate the ray tracing algorithm by utilising a parallel computing technique; and faster memory access is achieved by binding the auxiliary phantoms to texture objects. The simulation results in this paper show that the GPU-based approach not only maintains the image precision but also gains significant speed-ups over the conventional central processing unit (CPU)-based Siddon method. Furthermore, beam hardening artefacts can clearly be seen from the profile curves of the reconstructed slices, indicating that this method is effective.

Deep-Neural-Network-Based Receiver Design for Downlink Non-Orthogonal Multiple-Access Underwater Acoustic Communication

The excavation of the ocean has led to the submersion of numerous autonomous vehicles and sensors. Hence, there is a growing need for multi-user underwater acoustic communication. On the other hand, due to the limited bandwidth of the underwater acoustic channel, downlink non-orthogonal multiple access (NOMA) is one of the fundamental pieces of technology for solving the problem of limited bandwidth, and it is expected to be beneficial for many modern wireless underwater acoustic applications. NOMA downlink underwater acoustic communication (UWA) is accomplished by broadcasting data symbols from a source station to several users, which uses superimposed coding with variable power levels to enable detection through successive interference cancellation (SIC) receivers. Nevertheless, comprehensive information of the channel condition and channel state information (CSI) are both essential for SIC receivers, but they can be difficult to obtain, particularly in an underwater environment. To address this critical issue, this research proposes downlink underwater acoustic communication using a deep neural network utilizing a 1D convolution neural network (CNN). Two cases are considered for the proposed system in the first case: in the first case, two users with different power levels and distances from the transmitter employ BPSK and QPSK modulations to support multi-user communication, while, in the second case, three users employ BPSK modulation. Users far from the base station receive the most power. The base station uses superimposed coding. The BELLHOP ray-tracing algorithm is utilized to generate the training dataset with user depth and range modifications. For training the model, a composite signal passes through the samples of the UWA channel and is fed to the model along with labels. The DNN receiver learns the characteristic of the UWA channel and does not depend on CSI. The testing CIR is used to evaluate the trained model. The results are compared to the traditional SIC receiver. The DNN-based DL NOMA underwater acoustic receiver outperformed the SIC receiver in terms of BER in simulation results for all the modulation orders.

The intensity of diffuse galactic emission reflected by meteor trails

ABSTRACT We calculate the reflection of diffuse galactic emission by meteor trails and investigate its potential relationship to meteor radio afterglow (MRA). The formula to calculate the reflection of diffuse galactic emission is derived from a simplified case, assuming that the signals are mirrored by the cylindrical overdense ionization trail of meteors. The overall observed reflection is simulated through a ray tracing algorithm together with the diffuse galactic emission modelled by the Global Sky Model sky model. We demonstrate that the spectrum of the reflected signal is broad-band and follows a power law with a negative spectral index of around −1.3. The intensity of the reflected signal varies with local sidereal time and the brightness of the meteor and can reach 2000 Jy. These results agree with some previous observations of MRAs. Therefore, we think that the reflection of galactic emission by meteor trails can be a possible mechanism causing MRAs, which is worthy of further research.

Development of a composite model for predicting urban surface temperature distribution in the context of GIS

In this paper, we present a new model for simulating radiation heat transfer and surface temperatures in urban environments, which is a prerequisite for simulating outdoor mean radiant temperature for pedestrians. We propose a new model whose novelty lies in a new algorithm for simulating diffuse radiation by combining the Nusselt unit sphere method and Monte Carlo ray tracing algorithm. This combined use of different methods is automatically activated depending on the complexity of the scene and, in particular, the arrangement of the facets facing each other. The model is implemented in a Python-based tool, t4gpd, which combines the capabilities of geographic information science and related technologies (GIS &T) with efficient ray-casting solutions. The model is tested on a theoretical mock-up of nine virtual buildings in Nantes under summer and winter weather conditions and compared with SOLENE-Microclimat results. The view factor and solar radiation flux simulation results agree well with the reference solution, with a significant reduction in simulation computation time. However, the model has limitations due to the exclusion of vegetation evapotranspiration characteristics, wind profile model, and soil with complete stratigraphy. Overall, this new model provides an efficient tool for simulating outdoor pedestrian thermal comfort in urban environments and has potential for further development and validation.

Numerical Evaluation on the Thermal Performance of the Solar External Cylinder Receiver using Monte Carlo Ray-Tracing Algorithm

Numerical Evaluation on the Thermal Performance of the Solar External Cylinder Receiver using Monte Carlo Ray-Tracing Algorithm

Numerical Analysis of Temperature Deformation Characteristics for Super-High Arch Dams considering Solar Radiation Effects

Considering that the effect of solar radiation on the super-high arch dam temperature field remains poorly studied, the calculation accuracy of dam temperature deformation is unable to be guaranteed accordingly. To address the issue, the solar radiation effect is adequately taken into consideration by proposing a practical calculation method based on the ray-tracing algorithm, the precomputation algorithm, and the ASHRAE clear sky model in this paper. With the aid of the ASHRAE clear sky model, the solar radiation received by the super-high arch dam and reservoir water is calculated. The shading effects are calculated by means of the ray-tracing algorithm, and the precomputation technology is introduced to further enhance the computational efficiency. Finally, to guarantee the authenticity of the calculation results, the dam thermodynamic parameters are inversed by employing the hybrid genetic algorithm. Based on the application in a real-life case, we concluded that around one third of the entire dam radial temperature deformation was attributable to solar radiation during continuous sunny days. The analysis results signify a critical role for taking account of the solar radiation in dam deformation calculation. Furthermore, the practicability and utilization prospect of the proposed method was verified.

Predicting C/N0 as a Key Parameter for Network RTK Integrity Prediction in Urban Environments

Autonomuous transportation systems require navigation performance with a high level of integrity. As Global Navigation Satellite System (GNSS) real-time kinematic (RTK) solutions are needed to ensure lane level accuracy of the whole system, these solutions should be trustworthy, which is often not the case in urban environments. Thus, the prediction of integrity for specific routes or trajectories is of interest. The carrier-to-noise density ratio (C/N0) reported by the GNSS receiver offers important insights into the signal quality, the carrier phase availability and subsequently the RTK solution integrity. The ultimate goal of this research is to investigate the predictability of the GNSS signal strength. Using a ray-tracing algorithm together with known satellite positions and 3D building models, not only the satellite visibility but also the GNSS signal propagation conditions at waypoints along an intended route are computed. Including antenna gain, free-space propagation as well as reflection and diffraction at surfaces and vegetation, the predicted C/N0 is compared to that recorded by an Septentrio Altus receiver during an experiment in an urban environment in Hannover. Although the actual gain pattern of the receiving antenna was unknown, good agreements were found with small offsets between measured and predicted C/N0.

Direct Collapse to Precursors of Supermassive Black Hole Seeds: Radiation-feedback-generated Outflows

We use high-resolution zoom-in cosmological simulations to model outflow triggered by radiation and thermal drivers around the central mass accumulation during direct collapse within the dark matter (DM) halo. The maximal resolution is 1.3 × 10−5 pc, and no restrictions are put on the geometry of the inflow/outflow. The central mass is considered prior to the formation of the supermassive black hole seed at a redshift of z ∼ 15.9 and can constitute either a supermassive star (SMS) of ∼105 M ⊙ surrounded by a growing accretion disk or a self-gravitating disk. The radiation transfer is modeled using the ray-tracing algorithm. Due to the high accretion rate of ∼1 M ⊙ yr−1 determined by the DM halo, accretion is mildly supercritical, resulting in mildly supercritical luminosity that has only a limited effect on the accretion rate, with a duty cycle of ∼0.9. We observe a fast development of hot cavities, which quickly extend into polar funnels and expand dense shells. Within the funnels, fast winds, ∼103 km s−1, are mass-loaded by the accreting gas. We follow the expanding shells to ∼1 pc, when the shell velocity remains substantially (∼5 times) above the escape speed. The ionization cones formed by the central UV/X-ray completely ionize the cavities. Extrapolating the outflow properties shows that the halo material outside the shell will have difficulty stopping it. We therefore conclude that the expanding wind-driven shell will break out of the central parsec and will reach the halo virial radius. Finally, the anisotropic accretion flow on subparsec scales will attenuate the UV/soft X-rays on the H2. Hence, the formation of funnels and powerful outflows around, e.g., SMSs can have interesting observational corollaries.

LESS LiDAR: A Full-Waveform and Discrete-Return Multispectral LiDAR Simulator Based on Ray Tracing Algorithm

Light detection and ranging (LiDAR) is a widely used technology for the acquisition of three-dimensional (3D) information about a wide variety of physical objects and environments. However, before conducting a campaign, a test is typically conducted to assess the potential of the utilized algorithm for information retrieval. It might not be a real campaign but rather a simulation to save time and costs. Here, a multi-platform LiDAR simulation model considering the location, direction, and wavelength of each emitted laser pulse was developed based on the large-scale remote sensing (RS) data and image simulation framework (LESS) model, which is a 3D radiative transfer model for simulating passive optical remote sensing signals using the ray tracing algorithm. The LESS LiDAR simulator took footprint size, returned energy, multiple scattering, and multispectrum LiDAR into account. The waveform and point similarity were assessed with the LiDAR module of the discrete anisotropic radiative transfer (DART) model. Abstract and realistic scenes were designed to assess the simulated LiDAR waveforms and point clouds. A waveform comparison in the abstract scene with the DART LiDAR module showed that the relative error was lower than 1%. In the realistic scene, airborne and terrestrial laser scanning were simulated by LESS and DART LiDAR modules. Their coefficients of determination ranged from 0.9108 to 0.9984. Their mean was 0.9698. The number of discrete returns fitted well and the coefficient of determination was 0.9986. A terrestrial point cloud comparison in the realistic scene showed that the coefficient of determination between the two sets of data could reach 0.9849. The performance of the LESS LiDAR simulator was also compared with the DART LiDAR module and HELIOS++. The results showed that the LESS LiDAR simulator is over three times faster than the DART LiDAR module and HELIOS++ when simulating terrestrial point clouds in a realistic scene. The proposed LiDAR simulator offers two modes for simulating point clouds: single-ray and multi-ray modes. The findings demonstrate that utilizing a single-ray simulation approach can significantly reduce the simulation time, by over 28 times, without substantially affecting the overall point number or ground pointswhen compared to employing multiple rays for simulations. This new LESS model integrating a LiDAR simulator has great potential in terms of simultaneously simulating LiDAR data and optical images based on the same 3D scene and parameters. As a proof of concept, the normalized difference vegetation index (NDVI) results from multispectral images and the vertical profiles from multispectral LiDAR waveforms were simulated and analyzed. The results showed that the proposed LESS LiDAR simulator can fulfill its design goals.

Comparison of two optimization algorithms (VOLOTM , SEQU) for CyberKnife® treatment of acoustic neuromas, lung metastases, and liver metastases.

Two optimization algorithms VOLO™ and sequential optimization algorithm (SEQU) are compared in the Precision® treatment planning system from Accuray® for stereotactic radiosurgery and stereotactic body radiotherapy (SBRT) treatment plans. The aim is to compare the two algorithms to assess if VOLO™ is better of SEQU in certain treatment site. Sixty clinical treatment cases were compared. Entities include Acoustic neuroma (AN), lung metastases, and liver metastases. In each entity, 10 SEQU and 10 VOLO™ treatment plans were optimized. The Ray-Tracing calculation algorithm was used for all treatment plans and the treatments were planned exclusively with fixed cones (5-50mm). The number of nodes, beams, total MU, and treatment time were compared. Conformity index (CI), new conformity index (nCI), homogeneity index (HI), gradient index (GI), and target coverage were examined for agreement. Dmin , Dmean , Dmax , D100%, D98%, and D2% dose in the target volume as well as exposure to organs at risk was checked. To determine peripheral doses, the isodose volumes from V10% to V98% were evaluated. AN treatment plans showed significant differences for the number of nodes, beams, total MU, treatment time, D98%, D100% for the target volume, and the doses for all organs at risk. VOLO™ achieved better results on average. Total MU, treatment time, coverage, and D98% are significantly better for VOLO™ for lung metastases. For liver metastases, a significant reduction in number of nodes, total MU, and treatment time was observed for VOLO™ plans. The mean target coverage increased slightly with VOLO™, while the mean CI deteriorated slightly. The averages of Dmin , Dmean , D98%, D100%, and V80% resulted in a significant increase for VOLO™. The results of the present study indicate that VOLO™ should be used in place of SEQU as a standard for AN cases moving forward. Despite the lack of significance in the lung and liver cases, VOLO™ optimization is recommended because OAR sparing was similar, but coverage, Dmin , and Dmean were increased, and thus better tumor control can be expected.

An extended laser beam heating model for a numerical platform to simulate multi-material selective laser melting

A laser beam heating model (LBHM) is an important part of a platform for numerical modelling of a multi-material selective laser melting process. The LBHM is utilised as a ray-tracing algorithm that is widely applied for rendering in different applications, mainly for visualisation and very recently for laser heating models in selective laser melting. The model presented in this paper was further extended to transparent and translucent materials, including materials where transparency is dependent on the material temperature. In addition to reflection and surface absorption, commonly considered in such models, phenomena such as refraction, scattering and volume absorption were also implemented. Considering associated energy transfer, the model represents a laser beam as a stream of moving particles, i.e. photons of the same energy. When the photons meet a boundary between materials, they are reflected, absorbed or transmitted according to geometric and thermal interfacial characteristics. This paper describes the LBHM in detail, its verification and validation, and also presents several simulation examples of the entire selective laser melting process with implemented LBHM.

Effect of layer thickness on the melt pool behavior and pore defects evolution of selective laser melting CuCrZr alloy

Despite the great potential of selective laser melting technology, the low build rate has become a major reason limiting its large-scale use. Thick layer thickness can significantly increase the build rate, but an unlimited increase in layer thickness can easily lead to defects which can seriously affect the mechanical properties of the part. To date, the correlation between powder layer thickness and melt pool dynamics behavior and its influence on defect evolution in the production of copper-based alloys by selective laser melting remains unclear. Therefore, in this paper, a high-fidelity computational fluid dynamics (CFD) model combined with a ray-tracing algorithm is developed to investigate the effect of layer thickness on melt pool dynamics and the evolution of pore defects. The results show that as the powder layer thickness increases, the melt track width and depth rise, reaching a maximum of 169.8 µm and 177.2 µm at 60 µm layer thickness, which is probably attributed to the growth of global absorptivity. Besides, the increased instability of melt flow under thick layer thickness resulted in undulations in the solidification track surface and accompanying slag phenomena. It is worth noting that the generation of pores was observed at 45 µm and 60 µm layer thickness. Both the number and dimension of pores increase with thicker layer thickness, which are caused by the multiple reflection behavior of the laser rays in the keyhole. In addition, the elimination of pore defects under thick layer thickness was also explored, and it was found that remelting could effectively reduce the pores generated by previous layers.