scholarly journals Experiments and Agent Based Models of Zooplankton Movement within Complex Flow Environments

Biomimetics ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 2
Author(s):  
Mustafa Kemal Ozalp ◽  
Laura A. Miller ◽  
Thomas Dombrowski ◽  
Madeleine Braye ◽  
Thomas Dix ◽  
...  

The movement of plankton is often dictated by local flow patterns, particularly during storms and in environments with strong flows. Reefs, macrophyte beds, and other immersed structures can provide shelter against washout and drastically alter the distributions of plankton as these structures redirect and slow the flows through them. Advection–diffusion and agent-based models are often used to describe the movement of plankton within marine and fresh water environments and across multiple scales. Experimental validation of such models of plankton movement within complex flow environments is challenging because of the difference in both time and spatial scales. Organisms on the scale of 1 mm or less swim by beating their appendages on the order of 1 Hz and are advected meters to kilometers over days, weeks, and months. One approach to study this challenging multiscale problem is to insert actively moving agents within a background flow field. Open source tools to implement this sort of approach are, however, limited. In this paper, we combine experiments and computational fluid dynamics with a newly developed agent-based modeling platform to quantify plankton movement at the scale of tens of centimeters. We use Artemia spp., or brine shrimp, as a model organism given their availability and ease of culturing. The distribution of brine shrimp over time was recorded in a flow tank with simplified physical models of macrophytes. These simplified macrophyte models were 3D-printed arrays of cylinders of varying heights and densities. Artemia nauplii were injected within these arrays, and their distributions over time were recorded with video. The detailed three-dimensional flow fields were quantified using computational fluid dynamics and validated experimentally with particle image velocimetry. To better quantify plankton distributions, we developed an agent-based modeling framework, Planktos, to simulate the movement of plankton immersed within such flow fields. The spatially and temporally varying Artemia distributions were compared across models of varying heights and densities for both the experiments and the agent-based models. The results show that increasing the density of the macrophyte bed drastically increases the average time it takes the plankton to be swept downstream. The height of the macrophyte bed had less of an effect. These effects were easily observed in both experimental studies and in the agent-based simulations.

2017 ◽  
Vol 8 (4) ◽  
pp. 387-395 ◽  
Author(s):  
Joshua Conrad Jackson ◽  
David Rand ◽  
Kevin Lewis ◽  
Michael I. Norton ◽  
Kurt Gray

Agent-based modeling is a long-standing but underused method that allows researchers to simulate artificial worlds for hypothesis testing and theory building. Agent-based models (ABMs) offer unprecedented control and statistical power by allowing researchers to precisely specify the behavior of any number of agents and observe their interactions over time. ABMs are especially useful when investigating group behavior or evolutionary processes and can uniquely reveal nonlinear dynamics and emergence—the process whereby local interactions aggregate into often-surprising collective phenomena such as spatial segregation and relational homophily. We review several illustrative ABMs, describe the strengths and limitations of this method, and address two misconceptions about ABMs: reductionism and “you get out what you put in.” We also offer maxims for good and bad ABMs, give practical tips for beginner modelers, and include a list of resources and other models. We conclude with a seven-step guide to creating your own model.


2017 ◽  
Vol 27 (10) ◽  
pp. 1379-1391 ◽  
Author(s):  
Jihong Wang ◽  
Tengfei (Tim) Zhang ◽  
Hongbiao Zhou ◽  
Shugang Wang

To design a comfortable aircraft cabin environment, designers conventionally follow an iterative guess-and-correction procedure to determine the air-supply parameters. The conventional method has an extremely low efficiency but does not guarantee an optimal design. This investigation proposed an inverse design method based on a proper orthogonal decomposition of the thermo-flow data provided by full computational fluid dynamics simulations. The orthogonal spatial modes of the thermo-flow fields and corresponding coefficients were firstly extracted. Then, a thermo-flow field was expressed into a linear combination of the spatial modes with their coefficients. The coefficients for each spatial mode are functions of air-supply parameters, which can be interpolated. With a quick map of the cause–effect relationship between the air-supply parameters and the exhibited thermo-flow fields, the optimal air-supply parameters were determined from specific design targets. By setting the percentage of dissatisfied and the predicted mean vote as design targets, the proposed method was implemented for inverse determination of air-supply parameters in two aircraft cabins. The results show that the inverse design using computational fluid dynamics-based proper orthogonal decomposition method is viable. Most of computing time lies in the construction of data samples of thermo-flow fields, while the proper orthogonal decomposition analysis and data interpolation is efficient.


2021 ◽  
Vol 9 (2) ◽  
pp. 417
Author(s):  
Sherli Koshy-Chenthittayil ◽  
Linda Archambault ◽  
Dhananjai Senthilkumar ◽  
Reinhard Laubenbacher ◽  
Pedro Mendes ◽  
...  

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.


The ODD Protocol has become a standard for documenting and describing agent based models. The protocol is organized around three main elements, from which the ODD acronym originates: Overview, Design concepts, and Details. This chapter is organized around these primary elements and further broken down into seven sub-elements to provide a clear purpose and understanding of the model simulation. The sub-elements are: Purpose, State Variables and Scales, Process Overview and Scheduling, Design Concepts, Initialization, Input, and Sub-models. The model presented is a proto-agent behavioral model and is utilized in an agent based modeling simulation to help identify possible emergent behavioral outcomes of the populations in the area of interest. By varying the rules governing the interactions of the multinational and incumbent government proto-agents, different strategies can be identified for increasing the effectiveness of those proto-agents and the utilization of resources.


2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Yichen Jiang ◽  
Peidong Zhao ◽  
Li Zou ◽  
Zhi Zong ◽  
Kun Wang

Abstract The offshore wind industry is undergoing a rapid development due to its advantage over the onshore wind farm. The vertical axis wind turbine (VAWT) is deemed to be potential in offshore wind energy utilization. A design of the offshore vertical axis wind turbine with a deflector is proposed and studied in this paper. Two-dimensional computational fluid dynamics (CFD) simulation is employed to investigate the aerodynamic performance of wind turbine. An effective method of obtaining the blade’s angle of attack (AoA) is introduced in CFD simulation to help analyze the blade aerodynamic torque variation. The numerical simulations are validated against the measured torque and wake velocity, and the results show a good agreement with the experiment. It is found that the blade instantaneous torque is correlated with the local AoA. Among the three deflector configurations, the front deflector leads to favorable local flow for the blade, which is responsible for the improved performance.


2019 ◽  
Vol 141 (8) ◽  
Author(s):  
Rick Dehner ◽  
Ahmet Selamet

The present work combines experimental measurements and unsteady, three-dimensional computational fluid dynamics predictions to gain further insight into the complex flow-field within an automotive turbocharger centrifugal compressor. Flow separation from the suction surface of the main impeller blades first occurs in the mid-flow range, resulting in local flow reversal near the periphery, with the severity increasing with decreasing flow rate. This flow reversal improves leading-edge incidence over the remainder of the annulus, due to (a) reduction of cross-sectional area of forward flow, which increases the axial velocity, and (b) prewhirl in the direction of impeller rotation, as a portion of the tangential velocity of the reversed flow is maintained when it mixes with the core flow and transitions to the forward direction. As the compressor operating point enters the region where the slope of the constant speed compressor characteristic (pressure ratio versus mass flow rate) becomes positive, rotating stall cells appear near the shroud side diffuser wall. The angular propagation speed of the diffuser rotating stall cells is approximately 20% of the shaft speed, generating pressure fluctuations near 20% and 50% of the shaft frequency, which were also experimentally observed. For the present compressor and rotational speed, flow losses associated with diffuser rotating stall are likely the key contributor to increasing the slope of the constant speed compressor performance curve to a positive value, promoting the conditions required for surge instabilities. The present mild surge predictions agree well with the measurements, reproducing the amplitude and period of compressor outlet pressure fluctuations.


2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Francis H. Harlow

This paper describes extensions of computational fluid dynamics (CFD) to fields of analysis lying well beyond their current realms of application. In particular, three examples are presented. The first is to the collective behavior of mobs of people interacting with sources of danger and/or opportunity to which each individual responds by actions that depend strongly on the inducement of fear and/or excitement, depending on the intrinsic susceptibilities of the person. This behavior results in both individual activities (agent-based) and collective behaviors (crowd-based stochastic) with consequences of potentially great significance. Extensions are also described for which various other emotional developments are important to the behavior of a mob. The second example is to the processes of biological evolution, in particular to the driving forces that influence the directions of species alterations through a succession of characteristics that are tested for survivability in classical Darwinian fashion. The key to the analysis lies in the newly emerging field of epigenetics, in which numerous important experimental studies are producing astonishing results leading to major challenges to the creation of computational models of the collective fluid-like dynamics of interacting biological species. The third example explores an alternative to the Big Bang theory for describing the origin of our universe. The idea is that a parent universe exists, being composed of energy, matter, and antimatter in various forms. In some region a perturbation occurs, which locally has an excess of matter over antimatter. An enormous gravitational buildup of matter and energy in the region leads to a black hole, in which there is distortion in the fourth dimension. The result then leads to an offspring entity (universe) that becomes completely detached from the parent. To apply computational fluid dynamics to the analysis of this process requires formulations that include a major component of relevant physical representations. In all three of these examples, instabilities, fluctuations, and turbulence play major roles. These arise naturally in agent-based numerical formulations (the first and second of our examples), but are much more challenging to describe in a stochastic representation (e.g., the Navier–Stokes equations). Some promising spectral analysis extensions for stochastic formulations are included in this paper.


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