Development of a hardware-accelerated simulation kernel for ultra-high vacuum with Nvidia RTX GPUs

Molflow+ is a Monte Carlo (MC) simulation software for ultra-high vacuum, mainly used to simulate pressure in particle accelerators. In this article, we present and discuss the design choices arising in a new implementation of its ray-tracing–based simulation unit for Nvidia RTX Graphics Processing Units (GPUs). The GPU simulation kernel was designed with Nvidia’s OptiX 7 API to make use of modern hardware-accelerated ray-tracing units, found in recent RTX series GPUs based on the Turing and Ampere architectures. Even with the challenges posed by switching to 32 bit computations, our kernel runs much faster than on comparable CPUs at the expense of a marginal drop in calculation precision.

A Novel Inspection Technique for Electronic Components Using Thermography (NITECT)

Unverified or counterfeited electronic components pose a big threat globally because they could lead to malfunction of safety-critical systems and reduced reliability of high-hazard assets. The current inspection techniques are either expensive or slow, which becomes the bottleneck of large volume inspection. As a complement of the existing inspection capabilities, a pulsed thermography-based screening technique is proposed in this paper using a digital twin methodology. A FEM-based simulation unit is initially developed to simulate the internal structure of electronic components with deviations of multiple physical properties, informed by X-ray data, along with its thermal behaviour under exposure to instantaneous heat. A dedicated physical inspection unit is then integrated to verify the simulation unit and further improve the simulation by taking account of various uncertainties caused by equipment and samples. Principle component analysis is used for feature extraction, and then a set of machine learning-based classifiers are employed for quantitative classification. Evaluation results of 17 chips from different sources successfully demonstrate the effectiveness of the proposed technique.

Prediction Method and Verification of Fatigue Life for a Turbine Disk with Bolt Hole

In order to improve the fatigue life prediction accuracy of FGH96 material for turbine engine at higher stress gradient notch, such as bolt holes, the new mean stress formula is used in this paper, the effect of stress gradient and size effect are considered at the same time, Fatigue test of FGH96 material inter-stage disc simulation test piece is done, and the parameters in the life prediction equation of the model are fitted. Further study on fatigue test of FGH96 material turbine pin bolt hole simulation unit is done, and test results is compared with the forecast results. The result shows that, the improved fatigue life prediction method has higher accuracy, and the validity of the method is proved.

P039: Application of the Delphi method to refine key components in the iterative development of a mobile tele-simulation unit (MTU)

Introduction: Safe and efficient provision of quality healthcare requires maintenance of knowledge and skills relevant to daily practice. This is particularly relevant in rural and remote locations where high-acuity low-occurrence procedures and clinical scenarios present even less frequently. Simulation based training is widely used to supplement clinical exposure and practice but effective delivery of this approach to the rural/ remote practitioner must address barriers of time, cost and geographical separation. Mobile tele-simulation is an innovative approach that may help in bridging the gap through delivery of effective mentoring using telemedicine technologies and tailored educational content. Methods: To help direct the iterative design cycle for the mobile tele-simulation unit, input from potential future users was felt to be essential. The Delphi method was employed to reach consensus among study participants on four key questions: 1) What applications would the MTU be best suited for?, 2) What technical requirements and teaching tools would be needed to make the MTU successful?, 3) Which fields, besides EM/medical education, may benefit from partnerships with the final MTU?, 4) What research studies could be developed using the MTU? It was decided in advance that two rounds would be the maximum due to time constraints of the larger MTU projects. The first questionnaire focused on demographics and the four questions above. Independent reviewers analyzed, compiled and compared responses. Participants were sent the updated list, asked to confirm their responses and then to rank the responses highest to lowest priority. Results: Fifteen of 17 first round participants completed the questions, giving an 88.2% response rate. All shared a simulation background. 66% were physicians, 13.3% medical students, and 20% staff at Memorials Simulation Center. 66% had been involved with simulation-based education less than 5 years, and the others greater than 5 year. 13 of 15 (86.7%) responded in round 2. Consensus was not reached statistically using Kendalls W test for each of the four questions. However, there were several responses that showed higher median ranks than the others under each question. Application use: rural healthcare training, and medical professional training Technical factors: reliable learner-mentor connection, and competent technical support Non-technical factors: knowledgeable mentor and content relevant to locations practice, Research studies: training needs assessment from rural sites, and learners experience compared to stationary simulation center Conclusion: Input from a heterogeneous group of simulation users was sought to help prioritize key features in the development of the Mobile Tele-simulation Unit. Although statistically the study did not reach consensus, valuable feedback was compiled and pragmatically applied in the iterative development cycle.