GPU-Based Local Tone Mapping in the Context of Virtual Night Driving

Virtual Prototyping of automotive headlights requires a realistic illumination model, capable of rendering scenes of high contrast in fine detail. Due to the high dynamic range nature of headlight beam pattern data, which is projected onto the virtual road, high dynamic range illumination models are required. These are used as the basis for illumination in simulations for automotive headlight Virtual Prototyping. Since high dynamic range illumination models operate on brightness ranges commensurate with the real world, a post-processing operation, known as tone mapping, is required to map each frame into the device-specific range of the display hardware. Algorithms for tone mapping, called tone mapping operators, can be classified as global or local. Global operators are efficient to compute at the expense of scene quality. Local operators preserve scene detail, but, due to their additional computational complexity, are rarely used with interactive applications. Local tone mapping methods produce more usable visualization results for engineering tasks. This paper proposes a local tone mapping method suitable for use with interactive applications. To develop a suitable tone mapping operator, a state of the art local tone mapping method was accelerated using modern, work-efficient GPU algorithms. Optimal performance, both in terms of memory and speed, was achieved by means of General-Purpose GPU programming with CUDA. A prototypic implementation has shown that the method works well with high dynamic range OpenGL applications. In the near future, the tone mapper will be integrated into the virtual night driving simulator at our institute.

Direct Simulation of Lateral Migration of Buoyant Particles in Channel Flow Using GPU Computing

The current work promotes the implementation of the Smoothed Particle Hydrodynamics (SPH) method for the Fluid-Solid Interaction (FSI) problems on three levels: 1- an algorithm is described to simulate FSI problems, 2- a parallel GPU implementation is described to efficiently alleviate the performance problem of the SPH method, and 3- validations against other numerical methods and experimental results are presented to demonstrate the accuracy of SPH and SPH-based FSI simulations. While the numerical solution of the fluid dynamics is performed via SPH method, the general Newton-Euler equations of motion are solved for the time evolution of the rigid bodies. Moreover, the frictional contacts in the solid phase are resolved by the Discrete Element Method (DEM), which draws on a viscoelastic model for the mutual interactions. SPH is a Lagrangian method and allows an efficient and straightforward coupling of the fluid and solid phases, where any interface, including boundaries, can be decomposed by SPH particles. Therefore, with a single SPH algorithm, fluid flow and interfacial interactions, namely force and motion, are considered. Furthermore, without any extra effort, the contact resolution of rigid bodies with complex geometries benefits from the spherical decomposition of solid surfaces. Although SPH provides 2nd order accuracy in the discretization of mass and momentum equations, the pressure field may still exhibit large oscillations. One of the most straightforward and computationally inexpensive solutions to this problem is the density re-initialization technique. Additionally, to prevent particle interpenetration and improve the incompressibility of the flow field, the XSPH correction is adopted herein. Despite being relatively straightforward to implement for the analysis of both internal and free surface flows, a naïve SPH simulation does not exhibit the efficiency required for the 3D simulation of real-life fluid flow problems. To address this issue, the software implementation of the proposed framework relies on parallel implementation of the spatial subdivision method on the Graphics Processing Unit (GPU), which allows for an efficient 3D simulation of the fluid flow. Similarly, the time evolution and contact resolution of rigid bodies are implemented using independent GPU-based kernels, which results in an embarrassingly parallel algorithm. Three problems are considered in the current work to show the accuracy of SPH and FSI algorithms. In the first problem, the simulation of the transient Poiseuille flow exhibits an exact match with the analytical solution in series form. The lateral migration of the neutrally buoyant circular cylinder, referred to as tubular pinch effect, is successfully captured in the second problem. In the third problem, the migration of spherical particles in pipe flow was simulated. Two tests were performed to demonstrate whether the Magnus effect or the curvature of the velocity profile cause the particle migration. At the end, the original experiment of the Segre and Silberberg (Segre and Silberberg, Nature 189 (1961) 209–210), which is composed of 3D fluid flow and several rigid particles, is simulated.

Human Carrying Simulation With Symmetric and Asymmetric Loads

Human carrying is simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). Predictive dynamics approach is used to predict the carrying motion with symmetric and asymmetric loads. In this process, the model predicts joints dynamics using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion and ground reaction forces data during symmetric and asymmetric load carrying task. With such prediction capability the model could be used for biomedical and ergonomic studies.

Foundation for Model Integration: Semantic Backplane

One of the primary goals of the Adaptive Vehicle Make (AVM) program of DARPA is the construction of a model-based design flow and tool chain, META, that will provide significant productivity increase in the development of complex cyber-physical systems. In model-based design, modeling languages and their underlying semantics play fundamental role in achieving compositionality. A significant challenge in the META design flow is the heterogeneity of the design space. This challenge is compounded by the need for rapidly evolving the design flow and the suite of modeling languages supporting it. Heterogeneity of models and modeling languages is addressed by the development of a model integration language – CyPhy – supporting constructs needed for modeling the interactions among different modeling domains. CyPhy targets simplicity: only those abstractions are imported from the individual modeling domains to CyPhy that are required for expressing relationships across sub-domains. This “semantic interface” between CyPhy and the modeling domains is formally defined, evolved as needed and verified for essential properties (such as well-formedness and invariance). Due to the need for rapid evolvability, defining semantics for CyPhy is not a “one-shot” activity; updates, revisions and extensions are ongoing and their correctness has significant implications on the overall consistency of the META tool chain. The focus of this paper is the methods and tools used for this purpose: the META Semantic Backplane. The Semantic Backplane is based on a mathematical framework provided by term algebra and logics, incorporates a tool suite for specifying, validating and using formal structural and behavioral semantics of modeling languages, and includes a library of metamodels and specifications of model transformations.

Mask Image Planning for Deformation Control in Projection-Based Stereolithography Process

In this research, we investigate the shrinkage related deformation control for a mask-image-projection-based Stereolithography process (MIP-SL). Based on a Digital Micromirror Device (DMD), MIP-SL uses an area-processing approach by dynamically projecting mask images onto a resin surface to selectively cure liquid resin into layers of an object. Consequently, the related additive manufacturing process can be much faster with a lower cost than the laser-based Stereolithography Apparatus (SLA) process. However, current commercially available MIP-SL systems are based on Acrylate resins, which have bigger shrinkages than epoxy resins that are widely used in the SLA process. Consequently controlling size accuracy and shape deformation in the MIP-SL process is challenging. To address the problem, we evaluate different image exposing strategies for projection mask images. A mask image planning method and related algorithms have been developed for the MIP-SL process. The planned mask images have been tested by using a commercial MIP-SL machine. The experimental results illustrate that our method can effectively reduce the deformation by as much as 32%. A discussion on the test results and future research directions are also presented.

Motion-Aware Adaptive Dead Reckoning Algorithm for Distributed Virtual Reality Systems

Dead reckoning algorithms are employed in distributed virtual reality systems (DVR systems) for predicting objects states at any given moment of time that makes it possible to minimize bandwidth requirements while maintaining required data consistency. However, existing implementations often do not take into account information on the object motion dynamics and, in general, apply static prediction models. In this paper a novel motion-aware adaptive dead reckoning algorithm is introduced based on dynamical prediction model selection depending on the object motion pattern. The results show that considerable reduction in update messages can be achieved without sacrificing prediction accuracy. In addition, it becomes possible to dynamically adjust the size of update messages according to the motion pattern and, thus, provide more flexible use of network bandwidth.

Aligning Operational Decisions to Enterprise Objectives Through a Dynamic Enterprise Architecture Approach

As the rate of change in both business models and business complexity increases, enterprise architecture can be positioned to supply decision support for executives. The authors propose a dynamic enterprise architecture framework that supports business executive needs for rapid response and contextualized numerical decision support. The classic approaches to business decision making are both over simplified and insufficient to account for the dynamic complexities of reality. Recent failures of historically sound businesses demonstrate that a more robust mathematical approach is required to establish and maintain the alignment between operational decisions and enterprise objectives. We begin with an enterprise architecture (EA) framework that is robust enough to capture the elements of the business within the structure of a meta model that describes how the elements will be stored and tested for completeness and coherence. We add to that the analytical tools needed to innovate and improve the business. Finally, dynamic causal and agent layers are added to account for the qualitative and evolutionary elements that are normally missing or over simplified in most decision systems. This results in a dynamic model of an enterprise that can be simulated and analyzed to answer key business questions and provide decision support. We present a case study and demonstrate how the models are used within the decision framework to support executive decision makers.

Instruction Generation for Assembly Operations Performed by Humans

This paper presents the design of an instruction generation system that can be used to automatically generate instructions for complex assembly operations performed by humans on factory shop floors. Multimodal information—text, graphical annotations, and 3D animations—is used to create easy-to-follow instructions. This thereby reduces learning time and eliminates the possibility of assembly errors. An automated motion planning subsystem computes a collision-free path for each part from its initial posture in a crowded scene onto its final posture in the current subassembly. Visualization of this computed motion results in generation of 3D animations. The system also consists of an automated part identification module that enables the human to identify, and pick, the correct part from a set of similar looking parts. The system’s ability to automatically translate assembly plans into instructions enables a significant reduction in the time taken to generate instructions and update them in response to design changes.

Towards Automated Evaluation of Vehicle Dynamics in System-Level Designs

We describe the use of the Cyber-Physical Modeling Language (CyPhyML) to support trade studies and integration activities in system-level vehicle designs. CyPhyML captures parameterized component behavior using acausal models (i.e. hybrid bond graphs and Modelica) to enable automatic composition and synthesis of simulation models for significant vehicle subsystems. Generated simulations allow us to compare performance between different design alternatives. System behavior and evaluation are specified independently from specifications for design-space alternatives. Test bench models in CyPhyML are given in terms of generic assemblies over the entire design space, so performance can be evaluated for any selected design instance once automated design space exploration is complete. Generated Simulink models are also integrated into a mobility model for interactive 3-D simulation.