Turbulent model validations with CFD/wind tunnel test and application to SEA for wind noise prediction

Wind noise is becoming to have a higher priority in automotive industry. Several past studies investigated whether SEA can be utilized to predict wind noise by applying a turbulent spectrum model as the input. However, there are many kinds of turbulent models developed and the appropriate model for input to SEA is still unclear. Due to this, this paper focuses on clarifying an appropriate turbulent model for SEA simulation. First, the input turbulent pressure spectrum from five models are validated with wind tunnel tests and CFD. Next, a conventional numerical approach is used to validate models from the aspect of response accuracy. Finally, turbulent models are applied to an SEA model developed for a wind tunnel, and the SEA response is validated with test data. From those input/response validations, an appropriate turbulent model is investigated.

Opensync: An Opensource Platform for Synchronizing Multiple Measures in Neuroscience Experiments

Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measures such as task accuracy and latency. To create a better understanding of human behavior and brain functionality, we should introduce other measures and analyze behavior from various aspects. However, it is technically complex and costly to design and implement the experiments that record multiple measures. To address this issue, a platform that allows synchronizing multiple measures from human behavior is needed. Method: This paper introduces an opensource platform named OpenSync, which can be used to synchronize multiple measures in neuroscience experiments. This platform helps to automatically integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from mouse, keyboard, joystick, etc.), and task-related information (stimulus markers). In this paper, we explain the structure and details of OpenSync, provide two case studies in PsychoPy and Unity. Comparison with existing tools: Unlike proprietary systems (e.g., iMotions), OpenSync is free and it can be used inside any opensource experiment design software (e.g., PsychoPy, OpenSesame, Unity, etc., https://pypi.org/project/OpenSync/ and https://github.com/moeinrazavi/OpenSync_Unity). Results: Our experimental results show that the OpenSync platform is able to synchronize multiple measures with microsecond resolution.

Optimization-Driven Controller Design for a High-Performance Electro-Hydrostatic Asymmetric Actuator Operating in All Quadrants

This paper presents an optimization-driven controller design for smooth and accurate position control of a newly developed single-rod electro-hydrostatic actuator (EHA). The design approach uses logically guided iterative runs of the EHA to determine the optimal gain and poles' locations of a simple, yet effective low-bandwidth controller. The optimization algorithm used in the paper is the globalized bounded Nelder-Mead algorithm with deterministic restarts for improved globalization and lower numerical cost. The design also incorporates a pre-filter to ensure minimum jerk in the system's step input response in the beginning and while approaching steady-state. The step response of the filter is a 7th-degree polynomial curve that ensures the minimum change in acceleration. Experimental results reveal that the addition of the proposed pre-filter reduces jerk in the system by up to 90%. Results also indicate that the controller performs very well in all quadrants with external load uncertainty of up to 367 kg and thus proves the effectiveness of the design approach.

COVID-Anosmia Checker: A rapid and low-cost alternative tool for mass screening of COVID-19

BackgroundCOVID-19 curve can be flattened by adopting mass screening protocols with aggressive testing and isolating infected populations. The current approach largely depends on RT-PCR/rapid antigen tests that require expert personnel resulting in higher costs and reduced testing frequency. Loss of smell is reported as a major symptom of COVID-19, however, a precise olfactory testing tool to identify COVID-19 patient is still lacking.MethodsTo quantitatively check for the loss of smell, we developed an odor strip, “COVID-Anosmia checker”, spotted with gradients of coffee and lemon grass oil. We validated its efficiency in healthy and COVID-19 positive subjects. A trial screening to identify SARS-CoV-2 infected persons was also carried out to check the sensitivity and specificity of our screening tool.FindingsIt was observed that COVID positive participants were hyposmic instead of being anosmic when they were subjected to smelling higher odor concentration. Our tool identified 97% of symptomatic and 94% of asymptomatic COVID-19 positive subjects after excluding most confounding factors like concurrent chronic sinusitis. Further, it was possible to reliably predict COVID-19 infection by calculating a loss of smell score with 100% specificity. We coupled this tool with a mobile application, which takes the input response from the user, and can readily categorize the user in the appropriate risk groups.ConclusionLoss of smell can be used as a reliable marker for screening for COVID-19. Our tool can be used for first-line screening to trace out COVID-19 infection effectively. It can be used in difficult to reach geographical locations.

Full-State Feedback Control Design for Shape Formation using Linear Quadratic Regulator

This study investigated the capability of a group of agents to form a desired shape formation by designing the feedback control using a linear quadratic regulator. In real application, the state condition of agents may change due to some particular problems such as a slow input response. In order to compensate for the problem that affects agent-to-agent coordination, a robust regulator was implemented into the formation algorithm. In this study, a linear quadratic regulator as the full-state feedback of robust regulator method for shape formation was considered. The result showed that a group of agents can form the desired shape (square) formation with a modification of the trajectory shape of each agent. The results were validated through numerical experiments.