Development of the Breakthrough Vorcat Technologyfor Cloud-Based Complex Energy Simulations
- Vorcat, Inc., Woodland Hills, CA (United States)
The over-arching goal of this SBIR project is to offer Vorcat, Inc.'s ("Vorcat") breakthrough Computational Fluid Dynamics (CFD) technology in a High Performance Computing (HPC) cloud environment so as to extend its current reach and foster adoption. HPC most generally refers to the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation in order to solve large problems in science, engineering, or business. In particular, the cloud app(s) proposed here addresses the problem of advancing current capabilities for designing next generation wind turbines and automotive technologies through developing reliable and efficient means for simulating turbulent flows about complex settings. But ultimately the same platform can be extended to solve a myriad of turbulent flow design problems whose solutions are required to protect critical civil and military infrastructure. In Phase I, testing and validation of our source code were performed on two automotive geometries: (i) the MIRA benchmark configuration and, (ii) the Cronuz geometry, an electric concept SUV developed by APPLUS+IDIADA ("IDIADA"), Vorcat's software distributor in the EU. The flows over the two geometries were simulated and analyzed, while focusing on areas of the flow where current competitive software products fail to provide reliable and stable solutions. We demonstrated in Phase I that by selecting a small number of run parameters that dictate the resolution of the results, even a non-expert user will be able to employ the code for their applications as no guess work, intervention, or tweaking in real time is needed - all problems are treated in a consistent manner. Given the present shortage of experienced fluid mechanics engineers in a strong high technology driven economy, Vorcat’s solution offers big potential productivity gains for companies’ hiring newly graduated engineers. In Phase II, several improvements to and extensions of the code will be developed so as to construct and launch an App that is robust, fast, and reliable, unlike any product that is offered in this field. Specifically, the Phase I work laid the groundwork for, (i) extreme speedup of execution via General Purpose Graphic Processing Units (GPGPUs) computing, (ii) a few algorithmic upgrades that apply to the modeling of physical phenomena specific to real life automotive configurations such as the Cronuz and, (iii) a Phase II development plan devised by Vorcat, Inc. with the participation of Nimbis Services and HyperComp, Inc., following beta testing of Vorcat's pre/post visualization tool and HyperComp's gridding tool on Nimbis's cloud server. Our Phase II plan includes the development of a stripped down, customized gridding App by HyperComp, that will be offered on Vorcat's virtual store, to users who do not have access to gridding tools or such that do not wish to employ expensive tools for simple surface gridding required by the Vorcat App. The latter will allow us not only to offer users pre-processing, processing, and post-processing capabilities in one place, but also to simplify and streamline the entire process. Last but not least, in Phase I, we reached a joint effort agreement with IDIADA to customize and extend the core technology to meet the needs of the automotive CFD market. IDIADA is an off-shoot of the University of Barcelona, is a publicly traded, reputable automotive service company of 2500+ employees. Based on many years of experience in automotive CFD, IDIADA’s managers have elected to team up with Vorcat to meet said objective and become Vorcat’s exclusive distributor of the resulting software in the Automotive OEM market. IDIADA is, (i) funding a Ph.D. program for an employee, who has been utilizing Vorcat to research flow phenomena about the Cronuz, with an emphasis on drag reduction mechanisms and, (ii) employing Vorcat as a high-fidelity tool in the EU commission’s UPSCALE project that aims at improving CFD simulations through Machine Learning paradigms. The combination of Vorcat’s software technology and machine learning could usher in a revolution in accelerated CFD design, have a wide impact on the ground, air, and space transport sectors. IDIADA’s investment is estimated at a minimum of two highly skilled man-years per annum over three years. This in-kind contribution by IDIADA has strong synergy with our Phase II plan and, if it progresses as planned, it will allow us to aim at launching an additional, second App in the Phase II time frame. The candidate App will target wind/hydro turbine flows and it can be used in the planning of placing of turbines in wind farms, an application already tested and validated in past work. A successful completion of this project will provide the CFD community with reliable and efficient strategies for simulating the complex turbulent flows produced by next generation energy-related technologies, such as modern ground and air vehicles, flow control devices mounted on modern car and truck configurations that aim at substantial drag force reduction, wind and hydro turbines, among others. Understanding and accurately predicting such complex flow phenomena are essential aspects of modern efforts aimed at reducing energy consumption in existing technologies and in promoting new energy-lean technologies of the future.
- Research Organization:
- Vorcat, Inc., Woodland Hills, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- DOE Contract Number:
- SC0018547
- OSTI ID:
- 1496640
- Type / Phase:
- SBIR (Phase I)
- Report Number(s):
- DOE-VORCAT-TR-18-003; 8188546220
- Country of Publication:
- United States
- Language:
- English
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