Log in

Relevant bibliographies by topics / Biological simulation / Journal articles

Journal articles on the topic 'Biological simulation'

To see the other types of publications on this topic, follow the link: Biological simulation.

Author: Grafiati

Published: 4 June 2021

Last updated: 31 January 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Biological simulation.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Adeeb, Samer, and Walter Herzog. "Simulation of biological growth." Computer Methods in Biomechanics and Biomedical Engineering 12, no. 6 (December 2009): 617–26. http://dx.doi.org/10.1080/10255840902802909.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Li, Yacong, Kuanquan Wang, Qince Li, and Henggui Zhang. "Biological pacemaker: from biological experiments to computational simulation." Journal of Zhejiang University-SCIENCE B 21, no. 7 (July 2020): 524–36. http://dx.doi.org/10.1631/jzus.b1900632.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Rhodes, Oliver, Luca Peres, Andrew G. D. Rowley, Andrew Gait, Luis A. Plana, Christian Brenninkmeijer, and Steve B. Furber. "Real-time cortical simulation on neuromorphic hardware." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2164 (December 23, 2019): 20190160. http://dx.doi.org/10.1098/rsta.2019.0160.

Full text

Abstract:

Real-time simulation of a large-scale biologically representative spiking neural network is presented, through the use of a heterogeneous parallelization scheme and SpiNNaker neuromorphic hardware. A published cortical microcircuit model is used as a benchmark test case, representing ≈1 mm 2 of early sensory cortex, containing 77 k neurons and 0.3 billion synapses. This is the first hard real-time simulation of this model, with 10 s of biological simulation time executed in 10 s wall-clock time. This surpasses best-published efforts on HPC neural simulators (3 × slowdown) and GPUs running optimized spiking neural network (SNN) libraries (2 × slowdown). Furthermore, the presented approach indicates that real-time processing can be maintained with increasing SNN size, breaking the communication barrier incurred by traditional computing machinery. Model results are compared to an established HPC simulator baseline to verify simulation correctness, comparing well across a range of statistical measures. Energy to solution and energy per synaptic event are also reported, demonstrating that the relatively low-tech SpiNNaker processors achieve a 10 × reduction in energy relative to modern HPC systems, and comparable energy consumption to modern GPUs. Finally, system robustness is demonstrated through multiple 12 h simulations of the cortical microcircuit, each simulating 12 h of biological time, and demonstrating the potential of neuromorphic hardware as a neuroscience research tool for studying complex spiking neural networks over extended time periods. This article is part of the theme issue ‘Harmonizing energy-autonomous computing and intelligence’.

APA, Harvard, Vancouver, ISO, and other styles

4

Read, Mark N., Kieran Alden, Louis M. Rose, and Jon Timmis. "Automated multi-objective calibration of biological agent-based simulations." Journal of The Royal Society Interface 13, no. 122 (September 2016): 20160543. http://dx.doi.org/10.1098/rsif.2016.0543.

Full text

Abstract:

Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based science; the baseline calibration forms a control for subsequent experimentation and hence is fundamental in the interpretation of results. Here, we develop and showcase a method, built around multi-objective optimization, for calibrating ABSs against complex target behaviours requiring several metrics (termed objectives ) to characterize. Multi-objective calibration (MOC) delivers those sets of parameter values representing optimal trade-offs in simulation performance against each metric, in the form of a Pareto front. We use MOC to calibrate a well-understood immunological simulation against both established a priori and previously unestablished target behaviours. Furthermore, we show that simulation-borne conclusions are broadly, but not entirely, robust to adopting baseline parameter values from different extremes of the Pareto front, highlighting the importance of MOC's identification of numerous calibration solutions. We devise a method for detecting overfitting in a multi-objective context, not previously possible, used to save computational effort by terminating MOC when no improved solutions will be found. MOC can significantly impact biological simulation, adding rigour to and speeding up an otherwise time-consuming calibration process and highlighting inappropriate biological capture by simulations that cannot be well calibrated. As such, it produces more accurate simulations that generate more informative biological predictions.

APA, Harvard, Vancouver, ISO, and other styles

5

Mehta, Shalin B., and Rudolf Oldenbourg. "Image simulation for biological microscopy: microlith." Biomedical Optics Express 5, no. 6 (May 13, 2014): 1822. http://dx.doi.org/10.1364/boe.5.001822.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Dasgupta, Subinay. "A computer simulation for biological ageing." Journal de Physique I 4, no. 10 (October 1994): 1563–70. http://dx.doi.org/10.1051/jp1:1994207.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Mattheck, C. "Computer simulation of adaptive biological growth." Journal of Biomechanics 25, no. 7 (July 1992): 780. http://dx.doi.org/10.1016/0021-9290(92)90513-z.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Albi, Giacomo, Marco Artina, Massimo Foransier, and Peter A. Markowich. "Biological transportation networks: Modeling and simulation." Analysis and Applications 14, no. 01 (January 2016): 185–206. http://dx.doi.org/10.1142/s0219530515400059.

Full text

Abstract:

We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.

APA, Harvard, Vancouver, ISO, and other styles

9

Fischle, Andreas, Axel Klawonn, Oliver Rheinbach, and Jörg Schröder. "Parallel Simulation of Biological Soft Tissue." PAMM 12, no. 1 (December 2012): 767–68. http://dx.doi.org/10.1002/pamm.201210372.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Woods, Christopher J., Muan Hong Ng, Steven Johnston, Stuart E. Murdock, Bing Wu, Kaihsu Tai, Hans Fangohr, et al. "Grid computing and biomolecular simulation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 363, no. 1833 (July 26, 2005): 2017–35. http://dx.doi.org/10.1098/rsta.2005.1626.

Full text

Abstract:

Biomolecular computer simulations are now widely used not only in an academic setting to understand the fundamental role of molecular dynamics on biological function, but also in the industrial context to assist in drug design. In this paper, two applications of Grid computing to this area will be outlined. The first, involving the coupling of distributed computing resources to dedicated Beowulf clusters, is targeted at simulating protein conformational change using the Replica Exchange methodology. In the second, the rationale and design of a database of biomolecular simulation trajectories is described. Both applications illustrate the increasingly important role modern computational methods are playing in the life sciences.

APA, Harvard, Vancouver, ISO, and other styles

11

Sun, Hao, and James D. Lee. "Simulation of cancer prognosis." Journal of Micromechanics and Molecular Physics 05, no. 01 (March 2020): 2050004. http://dx.doi.org/10.1142/s2424913020500046.

Full text

Abstract:

Most mechanobiology phenomena commonly involve biological growth and deformation. In this work, we propose an innovative model of cancerous growth which posits that an expandable tumor can be described as a poroelastic medium consisting of solid and fluid components. In our biologically informed mechanical description of tumor growth dynamics, we derive the governing equations of the tumor’s growth and incorporate them with large deformation and materially nonlinear constitutive equations to improve the accuracy and efficiency of our simulation. Meanwhile, the dynamic finite element equations (DFE) for coupled displacement field and pressure field are formulated and solved. The 3-dimensional porous model is introduced. Numerical results are presented and discussed.

APA, Harvard, Vancouver, ISO, and other styles

12

Besozzi, Daniela, Giulio Caravagna, Paolo Cazzaniga, Marco Nobile, Dario Pescini, and Alessandro Re. "GPU-powered Simulation Methodologies for Biological Systems." Electronic Proceedings in Theoretical Computer Science 130 (September 30, 2013): 87–91. http://dx.doi.org/10.4204/eptcs.130.14.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Salwinski, Lukasz, and David Eisenberg. "In silico simulation of biological network dynamics." Nature Biotechnology 22, no. 8 (July 4, 2004): 1017–19. http://dx.doi.org/10.1038/nbt991.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

PENNA, T. J. P., and D. STAUFFER. "EFFICIENT MONTE CARLO SIMULATION OF BIOLOGICAL AGING." International Journal of Modern Physics C 06, no. 02 (April 1995): 233–39. http://dx.doi.org/10.1142/s0129183195000186.

Full text

Abstract:

A bit-string model of biological life-histories is parallelized, with hundreds of millions of individuals. It gives the desired drastic decay of survival probabilities with increasing age for 32 age intervals.

APA, Harvard, Vancouver, ISO, and other styles

15

Pylnik, S. V., and I. G. Dueck. "Startup simulation for a rotating biological contactor." Theoretical Foundations of Chemical Engineering 46, no. 1 (February 2012): 72–79. http://dx.doi.org/10.1134/s0040579512010137.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Toghraee, Reza, Kyu-Il Lee, and Umberto Ravaioli. "Simulation of Ion Permeation in Biological Membranes." Computing in Science & Engineering 12, no. 2 (March 2010): 43–47. http://dx.doi.org/10.1109/mcse.2010.46.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Kaazempur-Mofrad, M. R., M. Bathe, H. Karcher, H. F. Younis, H. C. Seong, E. B. Shim, R. C. Chan, et al. "Role of simulation in understanding biological systems." Computers & Structures 81, no. 8-11 (May 2003): 715–26. http://dx.doi.org/10.1016/s0045-7949(02)00481-9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Saiz, Leonor, and Michael L. Klein. "Computer Simulation Studies of Model Biological Membranes." Accounts of Chemical Research 35, no. 6 (June 2002): 482–89. http://dx.doi.org/10.1021/ar010167c.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Tuckwell, Henry C., and Petr Lánsky. "On the simulation of biological diffusion processes." Computers in Biology and Medicine 27, no. 1 (January 1997): 1–7. http://dx.doi.org/10.1016/s0010-4825(96)00033-9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Mama, Saifuddin T. "1. Biological Simulation Model for Ovarian Cystectomy." Journal of Pediatric and Adolescent Gynecology 32, no. 2 (April 2019): 246. http://dx.doi.org/10.1016/s1083-3188(19)30125-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Felicetti, L., M. Femminella, and G. Reali. "A simulation tool for nanoscale biological networks." Nano Communication Networks 3, no. 1 (March 2012): 2–18. http://dx.doi.org/10.1016/j.nancom.2011.09.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Sarma, Gopal P., Travis W. Jacobs, Mark D. Watts, S. Vahid Ghayoomie, Stephen D. Larson, and Richard C. Gerkin. "Unit testing, model validation, and biological simulation." F1000Research 5 (August 10, 2016): 1946. http://dx.doi.org/10.12688/f1000research.9315.1.

Full text

Abstract:

The growth of the software industry has gone hand in hand with the development of tools and cultural practices for ensuring the reliability of complex pieces of software. These tools and practices are now acknowledged to be essential to the management of modern software. As computational models and methods have become increasingly common in the biological sciences, it is important to examine how these practices can accelerate biological software development and improve research quality. In this article, we give a focused case study of our experience with the practices of unit testing and test-driven development in OpenWorm, an open-science project aimed at modeling Caenorhabditis elegans. We identify and discuss the challenges of incorporating test-driven development into a heterogeneous, data-driven project, as well as the role of model validation tests, a category of tests unique to software which expresses scientific models.

APA, Harvard, Vancouver, ISO, and other styles

23

Wendoloski, J. J., Z. R. Wasserman, and F. R. Salemme. "Computer simulation of biological interactions and reactivity." Journal of Computer-Aided Molecular Design 1, no. 4 (January 1988): 313–22. http://dx.doi.org/10.1007/bf01677279.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Hunt, C. Anthony, Glen E. P. Ropella, Tai Ning Lam, Jonathan Tang, Sean H. J. Kim, Jesse A. Engelberg, and Shahab Sheikh-Bahaei. "At the Biological Modeling and Simulation Frontier." Pharmaceutical Research 26, no. 11 (September 9, 2009): 2369–400. http://dx.doi.org/10.1007/s11095-009-9958-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Yu, Seok Jong, Thai Quang Tung, Junho Park, Jongtae Lim, and Jaesoo Yoo. "A unified biological modeling and simulation system for analyzing biological reaction networks." Journal of the Korean Physical Society 63, no. 11 (December 2013): 2247–54. http://dx.doi.org/10.3938/jkps.63.2247.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Xue, Pengfei, David Schwab, Xing Zhou, Chenfu Huang, Ryan Kibler, and Xinyu Ye. "A Hybrid Lagrangian–Eulerian Particle Model for Ecosystem Simulation." Journal of Marine Science and Engineering 6, no. 4 (September 26, 2018): 109. http://dx.doi.org/10.3390/jmse6040109.

Full text

Abstract:

Current numerical methods for simulating biophysical processes in aquatic environments are typically constructed in a grid-based Eulerian framework or as an individual-based model in a particle-based Lagrangian framework. Often, the biogeochemical processes and physical (hydrodynamic) processes occur at different time and space scales, and changes in biological processes do not affect the hydrodynamic conditions. Therefore, it is possible to develop an alternative strategy to grid-based approaches for linking hydrodynamic and biogeochemical models that can significantly improve computational efficiency for this type of linked biophysical model. In this work, we utilize a new technique that links hydrodynamic effects and biological processes through a property-carrying particle model (PCPM) in a Lagrangian/Eulerian framework. The model is tested in idealized cases and its utility is demonstrated in a practical application to Sandusky Bay. Results show the integration of Lagrangian and Eulerian approaches allows for a natural coupling of mass transport (represented by particle movements and random walk) and biological processes in water columns which is described by a nutrient-phytoplankton-zooplankton-detritus (NPZD) biological model. This method is far more efficient than traditional tracer-based Eulerian biophysical models for 3-D simulation, particularly for a large domain and/or ensemble simulations.

APA, Harvard, Vancouver, ISO, and other styles

27

Byvaltsev, V. A., A. A. Kalinin, E. G. Belykh, and I. A. Stepanov. "Simulation technologies in spinal surgery." Annals of the Russian academy of medical sciences 71, no. 4 (August 2, 2016): 297–303. http://dx.doi.org/10.15690/vramn681.

Full text

Abstract:

This review reflects the current state of simulation technologies in neurosurgery and, in particular, in spinal surgery. Currently, there are different types of simulations used in spine surgery including the biological, artificial and virtual models. Simulations help to facilitate an optimal study of the anatomy, understand the spatial relationships between organs and tissues, plan properly the surgical intervention, and gain tactile surgical skills. The implementation of simulation technologies in the educational process provides objective assessment of the initial level of training, improvement of the competence in trained professionals, as well as prevention of surgical errors in various clinical situations.

APA, Harvard, Vancouver, ISO, and other styles

28

Saiz, Leonor, Sanjoy Bandyopadhyay, and Michael L. Klein. "Towards an Understanding of Complex Biological Membranes from Atomistic Molecular Dynamics Simulations." Bioscience Reports 22, no. 2 (April 1, 2002): 151–73. http://dx.doi.org/10.1023/a:1020130420869.

Full text

Abstract:

Computer simulation has emerged as a powerful tool for studying the structural and functional properties of complex biological membranes. In the last few years, the use of recently developed simulation methodologies and current generation force fields has permitted novel applications of molecular dynamics simulations, which have enhanced our understanding of the different physical processes governing biomembrane structure and dynamics. This review focuses on frontier areas of research with important biomedical applications. We have paid special attention to polyunsaturated lipids, membrane proteins and ion channels, surfactant additives in membranes, and lipid–DNA gene transfer complexes.

APA, Harvard, Vancouver, ISO, and other styles

29

Meizhen Huang, Meizhen Huang, and Yaxing Tong Yaxing Tong. "Numerical simulation and experiment of optothermal response of biological tissue irradiated by continuous xenon lamp." Chinese Optics Letters 10, no. 1 (2012): 011701–11704. http://dx.doi.org/10.3788/col201210.011701.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Gao, Lei, Guohua Nie, and Teng Zhang. "A Study of Hierarchical Biological Composite Structures Via a Coarse-Grained Molecular Dynamics Simulation Approach." International Journal of Applied Mechanics 08, no. 06 (September 2016): 1650084. http://dx.doi.org/10.1142/s1758825116500848.

Full text

Abstract:

A coarse-grained molecular dynamics (MD) simulation approach based on a widely used fuse model is developed to study the mechanical behaviors of hierarchical brick and mortar bio-composites made from hard minerals and soft polymers. Massively parallel MD simulations are performed to investigate the toughness enhancement and the effect of stochastic variations in brick strength in representative bio-composites. Our simulations indicate that the hierarchical structure of bio-composites not only plays a key role in toughness optimization, but also reduces the sensitivity of the structure to biomineral imperfections. This work demonstrates a simple and efficient simulation platform for designing novel biomimetic materials.

APA, Harvard, Vancouver, ISO, and other styles

31

Amirkulova, Dilnoza B., and Andrew D. White. "Combining enhanced sampling with experiment-directed simulation of the GYG peptide." Journal of Theoretical and Computational Chemistry 17, no. 03 (May 2018): 1840007. http://dx.doi.org/10.1142/s0219633618400072.

Full text

Abstract:

Experiment-directed simulation (EDS) is a technique to minimally bias molecular dynamics simulations to match experimentally observed results. The method improves accuracy but does not address the sampling problem of molecular dynamics simulations of large systems. This work combines EDS with both the parallel-tempering or parallel-tempering well-tempered ensemble replica-exchange methods to enhance sampling. These methods are demonstrated on the GYG tripeptide in explicit water. The collective variables biased by EDS are chemical shifts, where the set-points are determined by NMR experiments. The results show that it is possible to enhance sampling with either parallel-tempering and parallel-tempering well-tempered ensemble in the EDS method. This combination of methods provides a novel approach for both accurately and exhaustively simulating biological systems.

APA, Harvard, Vancouver, ISO, and other styles

32

Cremonesi, Francesco, Georg Hager, Gerhard Wellein, and Felix Schürmann. "Analytic performance modeling and analysis of detailed neuron simulations." International Journal of High Performance Computing Applications 34, no. 4 (April 3, 2020): 428–49. http://dx.doi.org/10.1177/1094342020912528.

Full text

Abstract:

Big science initiatives are trying to reconstruct and model the brain by attempting to simulate brain tissue at larger scales and with increasingly more biological detail than previously thought possible. The exponential growth of parallel computer performance has been supporting these developments, and at the same time maintainers of neuroscientific simulation code have strived to optimally and efficiently exploit new hardware features. Current state-of-the-art software for the simulation of biological networks has so far been developed using performance engineering practices, but a thorough analysis and modeling of the computational and performance characteristics, especially in the case of morphologically detailed neuron simulations, is lacking. Other computational sciences have successfully used analytic performance engineering, which is based on “white-box,” that is, first-principles performance models, to gain insight on the computational properties of simulation kernels, aid developers in performance optimizations and eventually drive codesign efforts, but to our knowledge a model-based performance analysis of neuron simulations has not yet been conducted. We present a detailed study of the shared-memory performance of morphologically detailed neuron simulations based on the Execution-Cache-Memory performance model. We demonstrate that this model can deliver accurate predictions of the runtime of almost all the kernels that constitute the neuron models under investigation. The gained insight is used to identify the main governing mechanisms underlying performance bottlenecks in the simulation. The implications of this analysis on the optimization of neural simulation software and eventually codesign of future hardware architectures are discussed. In this sense, our work represents a valuable conceptual and quantitative contribution to understanding the performance properties of biological networks simulations.

APA, Harvard, Vancouver, ISO, and other styles

33

Lopatiev, A. O., A. P. Vlasov, and A. P. Demichkovskyi. "Peculiarities of Simulation of Biomechanical and Biological Systems." Teorìâ ta Metodika Fìzičnogo Vihovannâ 17, no. 2 (June 25, 2017): 79–85. http://dx.doi.org/10.17309/tmfv.2017.2.1192.

Full text

Abstract:

The objective is to combine the methods and principles of biomechanics and continuum mechanics in order to pose and solve problems that have practical application in extreme conditions. Materials & methods: the movement of blood through large vessels was studied on the basis of the Euler and Navier-Stokes equations. Analysis of the cardiovascular system was used for the examination of the functional state of the athlete. The initial experimentally measured heart rate (HR) was determined by the Polar RC800 cardiac monitor. The resulting time series is analyzed using the software package Kubios HRV. Results: the article proposes to consider a model describing human body as a discrete-continuous system. Using the Euler equation, a mathematical model of the movement of blood through large vessels is considered. A mathematical model of the process of pulse wave propagation in blood vessels is given. We found and interpreted hidden periodicities relative to the numerical series occurring during analysis of biological and heart rhythms of athletes during training and competitive activities. Conclusions: the use of methods and principles of continuum mechanics makes it possible to pose and solve the problems of mathematical physics for practical purposes. These include the movement of blood through large vessels, the issue of heat protection, and so on. The heart rate changes during the day and has a fluctuating character with certain periods. Periods of heart rate depend on the activity of a person and the time of day. Moreover, the heart rate tends to increase the amplitude and depend significantly on person’s workload.

APA, Harvard, Vancouver, ISO, and other styles

34

KOMEIJI, Yuto, Masami UEBAYASI, and Umpei NAGASHIMA. "Molecular Dynamics Simulation of Biological Molecules. (1). Methods." Journal of Chemical Software 6, no. 1 (2000): 1–36. http://dx.doi.org/10.2477/jchemsoft.6.1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

KOMEIJI, Yuto, Sumie TAJIMA, Makoto HARAGUCHI, Nobuyuki TAKAHASHI, Masami UEBAYASI, and Umpei NAGASHIMA. "Molecular Dynamics Simulation of Biological Molecules. (2). Practice." Journal of Chemical Software 7, no. 1 (2001): 1–28. http://dx.doi.org/10.2477/jchemsoft.7.1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Le Tallec, X., A. Vidal, and D. Thornberg. "Upflow biological filter: modeling and simulation of filtration." Water Science and Technology 39, no. 4 (February 1, 1999): 79–84. http://dx.doi.org/10.2166/wst.1999.0192.

Full text

Abstract:

One of the most important operating parameters for the operation and the design of biofilters is the headloss due to clogging of the system leading to a semi-continuous operation with filtration cycles and backwashes. Some basic aspects of the filtration operation have been studied. The work consists in understanding and modelling the clogging phenomena due to the suspended solids retention, and validating the simulation results by calibration with experimental and full-scale results. Tracer experiments allowed us to simplify the hydrodynamics within the Biofilters into a plug-flow reactor with axial diffusion. Mass balances for the suspended solids have been therefore written accordingly, including solids retention represented as a mass transfer from the liquid to the solid phase. This affects the porosity of the system, leading on one hand to a modification of the filtration coefficient (responsible for the transfer of SS from liquid to “solid” phase) and on the other hand to an increased clogging measured by the headloss in the system. The Kozeny-Carman equation could successfully be used and a linear relationship between the filter coefficient and the water porosity could be validated. Experimental work has been conducted to calibrate the model and in this paper validations from pilot scale unit to full-scale plant are shown.

APA, Harvard, Vancouver, ISO, and other styles

37

Rossle, Shaila, C. "First-principles simulation of photoreactions in biological systems." Frontiers in Bioscience 14, no. 1 (2009): 4862. http://dx.doi.org/10.2741/3574.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

HANSMANN, ULRICH H. E. "COMPUTER SIMULATION OF BIOLOGICAL MACROMOLECULES IN GENERALIZED ENSEMBLES." International Journal of Modern Physics C 10, no. 08 (December 1999): 1521–30. http://dx.doi.org/10.1142/s0129183199001303.

Full text

Abstract:

For many years the emphasis in protein-folding simulations has been laid as to how to predict the three-dimensional structure of proteins. Only recently has there be a shift in interest towards the thermodynamics of folding. We show that generalized-ensemble techniques are well suited to study both questions for realistic protein models.

APA, Harvard, Vancouver, ISO, and other styles

39

Liu, H. "Simulation-Based Biological Fluid Dynamics in Animal Locomotion." Applied Mechanics Reviews 58, no. 4 (July 1, 2005): 269–82. http://dx.doi.org/10.1115/1.1946047.

Full text

Abstract:

This article presents a wide-ranging review of the simulation-based biological fluid dynamic models that have been developed and used in animal swimming and flying. The prominent feature of biological fluid dynamics is the relatively low Reynolds number, e.g. ranging from 100 to 104 for most insects; and, in general, the highly unsteady motion and the geometric variation of the object result in large-scale vortex flow structure. We start by reviewing literature in the areas of fish swimming and insect flight to address the usefulness and the difficulties of the conventional theoretical models, the experimental physical models, and the computational mechanical models. Then we give a detailed description of the methodology of the simulation-based biological fluid dynamics, with a specific focus on three kinds of modeling methods: (1) morphological modeling methods, (2) kinematic modeling methods, and (3) computational fluid dynamic methods. An extended discussion on the verification and validation problem is also presented. Next, we present an overall review on the most representative simulation-based studies in undulatory swimming and in flapping flight over the past decade. Then two case studies, of the tadpole swimming and the hawkmoth hovering analyses, are presented to demonstrate the context for and the feasibility of using simulation-based biological fluid dynamics to understanding swimming and flying mechanisms. Finally, we conclude with comments on the effectiveness of the simulation-based methods, and also on its constraints.

APA, Harvard, Vancouver, ISO, and other styles

40

Shirakashi, Ryo, and Ichiro Tanasawa. "Numerical Simulation of Freezing Process of Biological Tissues." Transactions of the Japan Society of Mechanical Engineers Series B 61, no. 587 (1995): 2642–47. http://dx.doi.org/10.1299/kikaib.61.2642.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Brettle, D., and E. Niebur. "Detailed parallel simulation of a biological neuronal network." IEEE Computational Science and Engineering 1, no. 4 (1994): 31–43. http://dx.doi.org/10.1109/99.338772.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Greenspan, D. "Particle simulation of biological sorting on a supercomputer." Computers & Mathematics with Applications 18, no. 9 (1989): 823–34. http://dx.doi.org/10.1016/0898-1221(89)90180-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Meester, Ronald. "Simulation of biological evolution and the NFL theorems." Biology & Philosophy 24, no. 4 (September 23, 2008): 461–72. http://dx.doi.org/10.1007/s10539-008-9134-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

López Cascales, J. J., J. García de la Torre, S. J. Marrink, and H. J. C. Berendsen. "Molecular dynamics simulation of a charged biological membrane." Journal of Chemical Physics 104, no. 7 (February 15, 1996): 2713–20. http://dx.doi.org/10.1063/1.470992.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Pedersen, Michael, Nicolas Oury, Colin Gravill, and Andrew Phillips. "Bio Simulators: a web UI for biological simulation." Bioinformatics 30, no. 10 (January 27, 2014): 1491–92. http://dx.doi.org/10.1093/bioinformatics/btu050.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Dematté, Lorenzo, Corrado Priami, and Alessandro Romanel. "Modelling and simulation of biological processes in BlenX." ACM SIGMETRICS Performance Evaluation Review 35, no. 4 (March 2008): 32–39. http://dx.doi.org/10.1145/1364644.1364653.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Pickwell, E., B. E. Cole, A. J. Fitzgerald, V. P. Wallace, and M. Pepper. "Simulation of terahertz pulse propagation in biological systems." Applied Physics Letters 84, no. 12 (March 22, 2004): 2190–92. http://dx.doi.org/10.1063/1.1688448.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Dasgupta, Subinay. "Computer Simulation of Biological AgeingA Birds-Eye View." Physica Scripta T106, no. 1 (2003): 19. http://dx.doi.org/10.1238/physica.topical.106a00019.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Pitts, Marvin J., and Denny C. Davis. "SpaceStation©-Computer Simulation Tool Demonstrating Biological Systems." Journal of Engineering Education 85, no. 3 (July 1996): 187–91. http://dx.doi.org/10.1002/j.2168-9830.1996.tb00232.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Zhu, Qiaoqiao, Xin Gao, H. Thomas Temple, Mark D. Brown, and Weiyong Gu. "Simulation of biological therapies for degenerated intervertebral discs." Journal of Orthopaedic Research 34, no. 4 (October 13, 2015): 699–708. http://dx.doi.org/10.1002/jor.23061.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!