A study on the ephemeral nature of knowledge shared within multiagent systems

Achieving knowledge sharing within an artificial swarm system could lead to significant development in autonomous multiagent and robotic systems research and realize collective intelligence. However, this is difficult to achieve since there is no generic framework to transfer skills between agents other than a query-response-based approach. Moreover, natural living systems have a "forgetfulness" property for everything they learn. Analyzing such ephemeral nature (temporal memory properties of new knowledge gained) in artificial systems has never been studied in the literature. We propose a behavior tree-based framework to realize a query-response mechanism for transferring skills encoded as the condition-action control sub-flow of that portion of the knowledge between agents to fill this gap. We simulate a multiagent group with different initial knowledge on a foraging mission. While performing basic operations, each robot queries other robots to respond to an unknown condition. The responding robot shares the control actions by sharing a portion of the behavior tree that addresses the queries. Specifically, we investigate the ephemeral nature of the new knowledge gained through such a framework, where the knowledge gained by the agent is either limited due to memory or is forgotten over time. Our investigations show that knowledge grows proportionally with the duration of remembrance, which is trivial. However, we found minimal impact on knowledge growth due to memory. We compare these cases against a baseline that involved full knowledge pre-coded on all agents. We found that knowledge-sharing strived to match the baseline condition by sharing and achieving knowledge growth as a collective system.Comment: In Proceedings of the Fifth International Symposium on Swarm Behavior and Bio-Inspired Robotics 2022 (SWARM 5th 2022

A Computational Study on the Leakage of Supercritical Carbon Dioxide through Labyrinth Seals

To meet future energy needs the use of alternative fuel sources are gaining popularity. The supercritical carbon dioxide Brayton cycle has been proposed as a possible cycle for next generation nuclear and concentrated solar power generation. Large density fluctuations of carbon dioxide in the supercritical region can be exploited to maintain compressor inlet conditions close to the critical point and thereby, reducing the compressor work and the back work ratio. In order to improve the efficiency of turbomachinery equipment it is important to reduce internal leakage through seals. A computational study was performed to understand the leakage through seals subject to large pressure differential using Open source CFD software OpenFOAM. FIT (Fluid Property Interpolation Tables) program is implemented in OpenFOAM to accurately model the properties of CO_(2) required to solve the governing equations. To predict flow behavior in the two phase dome HEM (Homogeneous equilibrium model) is assumed to be valid. Effects of geometrical parameters and operating conditions are isolated from each other and a parametric study was performed in two parts to understand the effects of both geometrical parameters and operating conditions. Results of the geometrical parameter study indicated that the carryover coefficient of a seal is independent of pressure drop across the seal and is only a function of geometry. A model for carryover was developed as a function of c/s (clearance to pitch ratio) and w_(cavity)/c (cavity width to clearance). It has been identified that the major non-dimensional parameter influencing the discharge through an annular orifice is w_(tooth)/c (tooth width to clearance) and a model for Cd (discharge coefficient) can be developed based on the results we obtained. Flow through labyrinth seals can be considered as a series of annular orifices and cavities. Using this analogy, leakage rate equations can be written for each tooth and the mass flow rate can be modeled as a function of the discharge coefficient under each tooth and the carryover coefficient, which accounts for the turbulent dissipation of kinetic energy in a cavity. The discharge coefficient of first tooth in a labyrinth seal is similar to that of an annular orifice, whereas, the discharge coefficient of the rest of the tooth was found to be a function of the C_(d) of the previous tooth and the carryover coefficient. To understand the effects of operating conditions, a 1-D isentropic choking model is developed for annular orifices resulting in upper and lower limit curves on a T-s diagram which show the choking phenomenon of flow through a seal. This model was applied to simulations performed on both an annular orifice and a labyrinth seal. It has been observed that the theory is, in general, valid for any labyrinth seal, but the upper and lower limit curves on a T-s diagram depend on number of constrictions. As the number of constrictions increases these two curves move farther away from the critical point. Finally, some experimental results for a plain orifice (L/D ~ 5) were used to show the capabilities of the FIT model implemented in OpenFOAM. Error analysis indicated that OpenFOAM is capable of predicting experimental data within a 10 % error with the majority of data close to a 5 % error. This validates the FIT model and HEM assumption

Aging effects on airflow dynamics and lung function in human bronchioles

Background and objective The mortality rate for patients requiring mechanical ventilation is about 35% and this rate increases to about 53% for the elderly. In general, with increasing age, the dynamic lung function and respiratory mechanics are compromised, and several experiments are being conducted to estimate these changes and understand the underlying mechanisms to better treat elderly patients. Materials and methods Human tracheobronchial (G1 ~ G9), bronchioles (G10 ~ G22) and alveolar sacs (G23) geometric models were developed based on reported anatomical dimensions for a 50 and an 80-year-old subject. The aged model was developed by altering the geometry and material properties of the model developed for the 50-year-old. Computational simulations using coupled fluid-solid analysis were performed for geometric models of bronchioles and alveolar sacs under mechanical ventilation to estimate the airflow and lung function characteristics. Findings The airway mechanical characteristics decreased with aging, specifically a 38% pressure drop was observed for the 80-year-old as compared to the 50-year-old. The shear stress on airway walls increased with aging and the highest shear stress was observed in the 80-year-old during inhalation. A 50% increase in peak strain was observed for the 80-year-old as compared to the 50-year-old during exhalation. The simulation results indicate that there is a 41% increase in lung compliance and a 35%-50% change in airway mechanical characteristics for the 80-year-old in comparison to the 50-year-old. Overall, the airway mechanical characteristics as well as lung function are compromised due to aging. Conclusion Our study demonstrates and quantifies the effects of aging on the airflow dynamics and lung capacity. These changes in the aging lung are important considerations for mechanical ventilation parameters in elderly patients. Realistic geometry and material properties need to be included in the computational models in future studies

Breast Tumor Simulation and Parameters Estimation Using Evolutionary Algorithms

An estimation methodology is presented to determine the breast tumor parameters using the surface temperature profile that may be obtained by infrared thermography. The estimation methodology involves evolutionary algorithms using artificial neural network (ANN) and genetic algorithm (GA). The ANN is used to map the relationship of tumor parameters (depth, size, and heat generation) to the temperature profile over the idealized breast model. The relationship obtained from ANN is compared to that obtained by finite element software. Results from ANN training/testing were in good agreement with those obtained from finite element model. After ANN validation, GA is used to estimate tumor parameters by minimizing a fitness function involving comparing the temperature profiles from simulated or clinical data to those obtained by ANN. Results show that it is possible to determine the depth, diameter, and heat generation rate from the surface temperature data (with 5% random noise) with good accuracy for the 2D model. With 10% noise, the accuracy of estimation deteriorates for deep-seated tumors with low heat generation. In order to further develop this methodology for use in a clinical scenario, several aspects such as 3D breast geometry and the effects of nonuniform cooling should be considered in future investigations

Investigating the Role of Vitamin D and DNA Repair in Influencing Cancer Presentation and Outcomes

Recent studies have identified differences in cancer risk, severity, and response to treatments in different ethnic groups. When comparing Americans of African descent to those of Caucasian descent, symptoms in African American patients were consistently severe with increased mortality rates. Research has indicated that this difference in the cancer phenotype between these two ethnic groups may be a result of both biological and socioeconomic factors 1. Our current study will focus on the potential- biological factors. We hypothesize that vitamin D deficiency in the AA population and associated differences in DNA repair capacity are the biological basis of the cancer- phenotypic variance between these populations. Lymphoblastic (LCL) cell lines cataloged in (http://www.1000genomes.org/) with known genotypes of human repair genes will be quantified for DNA repair capacity using comet assay, cell cycle analysis, and gene expression of key DNA repair genes (for both ethnic groups) after exposure to DNA damaging chemotherapeutic agents. Chi-square based population association approach will be used to associate genotypes of DNA repair genes to DRC capacity, thus providing the basis of population difference in the cancer phenotype

VCU Stress Relief: Programs and Tools to Ease Student Stress

Examine how VCU can support students who are having trouble, especially in the freshman year, due to economic challenges their families are facing (parent\u27s loss of jobs, parent\u27s loss of home, students tuition debt, etc). Explore ways to address these issues in the classroom or in individual or group settings

Multiscale approach including microfibril scale to assess elastic constants of cortical bone based on neural network computation and homogenization method

The complexity and heterogeneity of bone tissue require a multiscale modelling to understand its mechanical behaviour and its remodelling mechanisms. In this paper, a novel multiscale hierarchical approach including microfibril scale based on hybrid neural network computation and homogenisation equations was developed to link nanoscopic and macroscopic scales to estimate the elastic properties of human cortical bone. The multiscale model is divided into three main phases: (i) in step 0, the elastic constants of collagen-water and mineral-water composites are calculated by averaging the upper and lower Hill bounds; (ii) in step 1, the elastic properties of the collagen microfibril are computed using a trained neural network simulation. Finite element (FE) calculation is performed at nanoscopic levels to provide a database to train an in-house neural network program; (iii) in steps 2 to 10 from fibril to continuum cortical bone tissue, homogenisation equations are used to perform the computation at the higher scales. The neural network outputs (elastic properties of the microfibril) are used as inputs for the homogenisation computation to determine the properties of mineralised collagen fibril. The mechanical and geometrical properties of bone constituents (mineral, collagen and cross-links) as well as the porosity were taken in consideration. This paper aims to predict analytically the effective elastic constants of cortical bone by modelling its elastic response at these different scales, ranging from the nanostructural to mesostructural levels. Our findings of the lowest scale's output were well integrated with the other higher levels and serve as inputs for the next higher scale modelling. Good agreement was obtained between our predicted results and literature data.Comment: 2

Aeroelastic assessment of cracked composite plate by means of fully coupled finite element and Doublet Lattice Method

© 2018 Elsevier Ltd. This paper presents an investigation on flutter speed of cracked composite plates. This work is divided into two sections: (a) variation of crack length at a fixed location on the plate, and (b) variation of crack location on the plate with a fixed crack length, modelled as a unidirectional composite for 00,900 and 1350 orientations. Mori-Tanaka homogenization model is applied to obtain the effective composite constitutive properties as the function of fiber and matrix volume fraction. Doublet Lattice Method (DLM) is used to calculate the unsteady aerodynamic forces, i.e., lift distributions. It is found that the existence of small crack ratio on the composite plate (less than 0.4) has triggered an increment of the flutter speed. To support this statement, flutter response modes for each crack ratio are plotted, where the structure appears to be more stiffened than the undamaged plate. However, the crack results in the reduction of flutter speed when the crack ratio reaches 0.5. For the crack location assessment, the flutter speed increases as the crack location moves from the root to the tip due to the reduction of flutter frequency. The results show a good agreement with the validation using Strip Theory considering unsteady aerodynamics