100,504 research outputs found
UREJANJE KOLOIDNIH DELCEV NA MEHKIH POVRŠINAH
No full textA grafted polymer layer can be used to prevent the deposition of colloidal particles on a solid surface. This thesis presents Monte Carlo simulations of hard-sphere colloids pushed to a polymer brush under the influence of external fields (e.g. gravity). For weak fields colloids can not penetrate the brush and the effective potential acting on a single colloid is approximately quadratic. The phase diagram of three-dimensional hard-sphere colloids, that in one dimension are constrained to a plane by a harmonic potential, is presented. Under the influence of sufficiently strong external fields colloids penetrate the brush and form internally ordered, columnar structures that span the polymer layer. The morphology of the patterns that form depends sensitively on the strength of the applied field. We propose a simple phenomenological theory that accounts for the main characteristics of the observed behaviour. The present results suggest a simple experimental method to determine the surface polymer coverage.Polimerne krtačke varujejo površine pred adsorpcijo različnih delcev. V magistrski nalogi predstavimo Monte Carlo simulacije koloidov, ki so pod vplivom zunanjih polj (npr. gravitacijskega polja) potisnjeni ob polimerno krtačko. Pri šibkih poljih koloidi ne morejo predreti krtačke in efektivni potencial, ki ga čuti posamezen koloid, je približno harmonski. Predstavljen je fazni diagram tridimenzionalnih koloidov, ki so v eni dimenziji omejeni na površino s harmonskim potencialom. Pod vplivom dovolj močnih polj lahko koloidi prodrejo v krtačko, kjer tvorijo urejene, stebraste strukture. Morfologija vzorcev, ki nastanejo, je občutljivo odvisna od poljske jakosti. Predlagamo enostavno fenomenološko teorijo, ki pojasni glavne značilnosti opaženega obnašanja. S predstavljenimi rezultati predlagamo dokaj enostavno eksperimentalno metodo za določitev površinske gostote sidranih polimerov
Acoustic analysis and optimization of a performance automotive exhaust system.
No full textAvtomobili z notranjim izgorevanjem ustvarjajo različne hrupe, hrup izpušne cevi je med njimi najglasnejši. Potrebno je izvedeti, kakšne doprinose k dušenju zvoka imajo različni dušilni elementi celotnega izpušnega sistema in jih nato predelati in dodelati z uporabo simulacijskih orodij ter tako preveriti zvočno raven in padec le-te skozi celoten sistem. Pregledu celotne teoretične osnove izpušnih komponent in njihovega delovanja sledi preizkus v fizični obliki s pomočjo merilnih orodij nato pregled trenutno vgrajenih elementov sistema in predstavitev možnih nadgradenj ter udejanjanje teh v simulacijah. S pomočjo računalniških orodij primerjamo rezultate predelav s trenutnim izpušnim sistemom ter prikažemo primerjavo zvočne ravni simulacije in meritev in opredelimo verodostojnost tovrstne simulacije in morebitno nadaljnjo uporabo pri razvijanju izpušnih sistemov.Internal combustion automobiles produce a variety of noises, the loudest of which is the exhaust pipe noise. It is necessary to find out the contribution to sound attenuation of different silencing elements of the whole exhaust system and then to process and/or refine them using simulation tools to check the sound level and its drop through the whole system. An overview of the overall theoretical basis of exhaust components and their operation is followed by a physical test using measurement tools, then an overview of the currently installed system components and a presentation of possible upgrades and their implementation in simulations. Using computer aided tools, we compare results of the conversions with the current exhaust system and show the comparison betweeen simulated and physically measured noise levels to determine the validity of such simulations and possible further use in exhaust development
Letter, [Author unclear] to Paulina T. Merritt
No full textHandwritten letter to Paulina Merritt from an unknown author, October 1, 1876.
Machine Learning for functional genomics: some experiments with supervised learning on microarray data set
No full text
TA-clustering: Cluster analysis of gene expression profiles through Temporal Abstractions
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