SBIR Phase I: Composing Digital-Twins from Disparate Data Sources

SBIR 第一阶段：从不同的数据源构建数字孪生

• 批准号: 2106410
• 负责人: John Blackwell
• 金额: $ 25.6万
• 依托单位: DIAMOND AGE TECHNOLOGY LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106410&HistoricalAwards=false
• 关键词: SBIR; Phase; Composing; Digital; Twins

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project relates to the creation of a "digital twin," a real-world system projected into spatially-computed environment such as virtual and augmented reality. This technology creates the infrastructure necessary for the application of virtual and augmented reality in industrial workplaces, at scale. By making the full-scale roll out of these technologies possible, the technology seeks to impact human health and safety, operational efficiencies, and environmental risk reduction for process operations facilities, such as oil refineries and chemical plants. The long term impacts of the technology may also enable automation and optimization, improving their efficiency, security, and safety. Such facilities are critical infrastructure and play a significant role in the national economy. The availability of this product may also enhance market opportunities for other businesses in the scanning, spatial computing, and training markets. The impact may be further broadened by adapting the process for digital twin production to new domains unrelated to the industrial market.This Small Business Innovation Research (SBIR) Phase I project is advancing knowledge and understanding in both machine learning and spatial computing. This project focuses on a method for digitizing a complex, real-world system, in an efficient manner, sufficient to recreate the captured reality as an interactive digital twin. The primary technical hurdle is the combining of different data sources that describe aspects of a particular real-world system into a single complete description. The initial physical systems being modelled are industrial process operations, but the core methods could apply to other types of systems, including natural systems, such as a rainforest. For industrial process operations, the goal is to encode the entire process operations facilities at the component level, with sub-cm accuracy, at 10% of the current time and cost requirements. To achieve this, this project will combine physical scans with engineering documentation and relational probabilities. Once combined, the model will be used as the basis for a digital twin of the real-world system projected into spatial computed environments, such as virtual and augmented reality. These techniques replace a tedious and impractical static scan and human labor workflow with rapid scans, computer vision, and a combination of procedural and trained algorithms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小型企业创新研究(SBIR)第一阶段项目的更广泛的影响/商业潜力与创建“数字孪生兄弟”有关，这是一种投射到虚拟和增强现实等空间计算环境中的现实世界系统。这项技术为虚拟和增强现实在工业工作场所的大规模应用创造了必要的基础设施。通过使这些技术的全面推广成为可能，该技术寻求影响人类健康和安全、运营效率以及炼油厂和化工厂等流程运营设施的环境风险降低。该技术的长期影响还可能实现自动化和优化，提高它们的效率、安全性和安全性。这些设施是关键的基础设施，在国民经济中发挥着重要作用。该产品的推出还可能增加扫描、空间计算和培训市场中其他企业的市场机会。通过调整数字双胞胎生产过程以适应与工业市场无关的新领域，这种影响可能会进一步扩大。这个小型企业创新研究(SBIR)第一阶段项目正在促进机器学习和空间计算方面的知识和理解。这个项目的重点是一种方法，以一种有效的方式将复杂的真实世界系统数字化，足以将捕获的现实重建为交互式数字双胞胎。主要的技术障碍是将描述特定真实世界系统的各个方面的不同数据源组合成单个完整的描述。最初被建模的物理系统是工业过程操作，但核心方法可以应用于其他类型的系统，包括自然系统，如热带雨林。对于工业过程操作，目标是以当前时间和成本要求的10%的精度，在组件级别对整个过程操作设施进行编码。为了实现这一点，该项目将把物理扫描与工程文档和关系概率结合起来。一旦组合在一起，该模型将被用作现实世界系统的数字孪生兄弟，投射到空间计算环境中，如虚拟和增强现实。这些技术用快速扫描、计算机视觉以及程序性和训练有素的算法的组合取代了乏味而不切实际的静态扫描和人工工作流程。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。