7,334 research outputs found
Characterisation of the structural properties of ECNF embedded pan nanomat reinforced glass fiber hybrid composites
A thesis submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering.
Johannesburg, May 2016In this study, hybrid multiscale epoxy composites were developed from woven glass fabrics and PAN nanofibers embedded with short ECNFs (diameters of ~200nm) produced via electrospinning. Unlike VGCNFs or CNTs which are prepared through bottom-up methods, ECNFs were produced through a top-down approach; hence, ECNFs are much more cost-effective than VGCNFs or CNTs. Impact absorption energy, tensile strength, and flexural strength of the hybrid multiscale reinforced GFRP composites were investigated. The control sample was the conventional GFRP composite prepared from the neat epoxy resin. With the increase of ECNFs fiber volume fraction up to 1.0%, the impact absorption energy, tensile strength, and flexural strength increased. The incorporation of ECNFs embedded in the PAN nanofibers resulted in improvements on impact absorption energy, tensile strength, and flexural properties (strength and modulus) of the GFPC. Compared to the PAN reinforced GRPC, the incorporation of 1.0% ECNFs resulted in the improvements of impact absorption energy by roughly 9%, tensile strength by 37% and flexural strength by 29%, respectively. Interfacial debonding of matrix from the fiber was shown to be the dominant mechanism for shear failure of composites without ECNFs. PAN/ECNFs networks acted as microcrack arresters enhancing the composites toughness through the bridging mechanism in matrix rich zones. More energy absorption of the laminate specimens subjected to shear failure was attributed to the fracture and fiber pull out of more ECNFs from the epoxy matrix. This study suggests that, the developed hybrid multiscale ECNF/PAN epoxy composite could replace conventional GRPC as low-cost and high-performance structural composites with improved out of plane as well as in plane mechanical properties. The strengthening/ toughening strategy formulated in this study indicates the feasibility of using the nano-scale reinforcements to further improve the mechanical properties of currently structured high-performance composites in the coming years. In addition, the present study will significantly stimulate the long-term development of high-strength high-toughness bulk structural nanocomposites for broad applications.MT201
General Perturbations of Homogeneous and Orthogonal Locally Rotationally Symmetric Class II Cosmologies with Applications to Dissipative Fluids
First order perturbations of homogeneous and hypersurface orthogonal LRS
(Locally Rotationally Symmetric) class II cosmologies with a cosmological
constant are considered in the framework of the 1+1+2 covariant decomposition
of spacetime. The perturbations, which are for a general energy-momentum
tensor, include scalar, vector and tensor modes and extend some previous works
where matter was assumed to be a perfect fluid. Through a harmonic
decomposition, the system of equations is then transformed to evolution
equations in time and algebraic constraints. This result is then applied to
dissipative one-component fluids, and on using the simplified acausal Eckart
theory the system is reduced to two closed subsystems governed by four and
eight harmonic coefficients for the odd and even sectors respectively. The
system is also seen to close in a simplified causal theory. It is then
demonstrated, within the Eckart theory, how vorticity can be generated from
viscosity.Comment: 27 pages, 1 figur
Determining the Measurement Quality of a Montessori High School Teacher Evaluation Survey
The purpose of this study was to conduct a psychometric validation of a course evaluation instrument, known as a student evaluation of teaching (SET), implemented in a Montessori high school. The authors demonstrate to the Montessori community how to rigorously examine the measurement and assessment quality of instruments used within Montessori schools. The Montessori high school community needs an SET that has been rigorously examined for measurement issues. The examined SET was developed by a Montessori high school, and the sample data were collected from Montessori high school students. Using a Rasch partial credit model, the results of the analysis identified several measurement issues, including multidimensionality, misfit items, and inappropriate item difficulty levels. A revised version of the SET underwent the same analysis procedure, and the results indicated that measurement issues persisted. The authors suggest several ways to improve the overall measurement quality of the instrument while keeping the Montessori foundation. Additional validation studies with a revised version of the SET will be needed before the instrument can be endorsed for full implementation in a Montessori setting
Hydrothermal modeling for optimum temperature control : an estimation-theoretic approach
Originally presented as part of the first author's thesis, (Environmental Engineer) in the M.I.T. Dept. of Civil EngineeringA short-term temperature forecasting (STF) system is proposed to
predict and control plant intake and discharge temperatures at Salem
Harbor Electric Generating Station. It is desired to minimize receiving-water (i.e., intake-water) temperatures during peak power
demand periods, in order to minimize the cost of complying with the
maximum discharge water temperature limit. This study addresses
the hydrothermal modeling requirements of an STF system.
An important element of an STF system is a predictive model of
plant intake water temperatures. For application to Salem Harbor
Station, strict model performance criteria exist, defining a model
development problem: Develop a simple model to predict plant intake
water temperatures 24 hours ahead, predicting daily peak intake temperatures within 10F on 90% of the days, and using only existing
measurements. An estimation-theoretic approach to model development is
used, which quantifies and minimizes the uncertainties in the model.
The approach employs optimal filtering and full-information maximum-
likelihood (FIML) estimation to obtain optimum parameter estimates.
A two-basin, two-layer hydrothermal model of Salem Harbor is developed.
The model computes hourly intake temperatures, incorporating tidal
flushing, stratification, surface heat exchange, and wind advection of
the plume. Twenty-eight model parameters and five noise statistics
are estimated from intake-temperature data.
Preliminary best-fit parameter values are obtained subjectively,
followed by FIML parameter estimation using a data base of 96 hourly
measurements (7/29 - 8/2/74). The model is tested for 106 days (5/17-
9/20/74) and various performance measures are computed, including sum-
of-squares of measurement residuals (S), whiteness (P), percent of daily
peak temperature predictions within 10F of actual (T), and others.
Visual inspection of 24-hour intake temperature predictions shows that
the two-basin, two-layer model performs qualitatively well. However,
the model fails statistical tests on S and P, indicating structural
weaknesses. FIML estimation yields physically unrealistic values for
certain parameters, probably compensating for inadequate model structure. Despite structural flaws in the two-basin, two-layer model, FIML
estimation yields parameters with consistently better performance than
the preliminary estimates (by a small amount). It is concluded that the two-basin, two-layer model is presently
unsuitable for STF use, largely due to structural weaknesses. Possible corrections are suggested; however, a statistical model of
hourly temperatures appears to offer greater potential accuracy than
physically-derived models. FIML parameter estimation is shown to be
useful for water quality model development on a real system, particularly
after subjective model development has been exhausted.New England Power Company under the MIT Energy Laboratory Electric Power Progra
Quantifying evolutionary constraints on B cell affinity maturation
The antibody repertoire of each individual is continuously updated by the
evolutionary process of B cell receptor mutation and selection. It has recently
become possible to gain detailed information concerning this process through
high-throughput sequencing. Here, we develop modern statistical molecular
evolution methods for the analysis of B cell sequence data, and then apply them
to a very deep short-read data set of B cell receptors. We find that the
substitution process is conserved across individuals but varies significantly
across gene segments. We investigate selection on B cell receptors using a
novel method that side-steps the difficulties encountered by previous work in
differentiating between selection and motif-driven mutation; this is done
through stochastic mapping and empirical Bayes estimators that compare the
evolution of in-frame and out-of-frame rearrangements. We use this new method
to derive a per-residue map of selection, which provides a more nuanced view of
the constraints on framework and variable regions.Comment: Previously entitled "Substitution and site-specific selection driving
B cell affinity maturation is consistent across individuals
A -adic RanSaC algorithm for stereo vision using Hensel lifting
A -adic variation of the Ran(dom) Sa(mple) C(onsensus) method for solving
the relative pose problem in stereo vision is developped. From two 2-adically
encoded images a random sample of five pairs of corresponding points is taken,
and the equations for the essential matrix are solved by lifting solutions
modulo 2 to the 2-adic integers. A recently devised -adic hierarchical
classification algorithm imitating the known LBG quantisation method classifies
the solutions for all the samples after having determined the number of
clusters using the known intra-inter validity of clusterings. In the successful
case, a cluster ranking will determine the cluster containing a 2-adic
approximation to the "true" solution of the problem.Comment: 15 pages; typos removed, abstract changed, computation error remove
Nudging investors big and small toward better decisions
Investors significantly reduce their future returns by selecting mutual funds with higher fees, allured by higher past returns that do not predict future performance. This suboptimal behavior, which can roughly halve an investor’s retirement savings, is driven by 2 psychological factors. One factor is difficulty comprehending rate information, which is critical given that mutual fund fees and returns are typically communicated in percentages. A second factor is devaluing small differences in returns or fees (i.e., a peanuts effect). These 2 factors interact such that large investors benefit when fees are stated in currency (as opposed to percentages), whereas small investors benefit from returns stated in currency. These striking results suggest behavioral interventions that are tailored specifically for small and large investors
Entrepreneurial learning in practice: The impact of knowledge transfer
The aim of this research is to provide perspectives on how entrepreneurial practitioners, specifically owners of high-tech
small firms (HTSFs), engage with knowledge transfer and learn. The authors draw on extant research and report on the
views and observations of the principals in two case study companies in the HTSF sector with regard to growing their
ventures and developing learning while part of a Knowledge Transfer Partnership (KTP) programme. Entrepreneurial
learning is an area of significant interest due to the growth of entrepreneurship and the varied ways in which learning can
take place. There are many different interventions that can be used to transfer knowledge and develop learning, but there
is limited, if any, consensus on their respective effectiveness. The researchers used an ethnographic approach in two
companies over an 18-month period. The study concludes that the KTP intervention facilitates an opportunity for learning
through disruption, with the key barrier to any new learning being established practice. Interestingly, the findings suggest
that entrepreneurial learning is greatly facilitated by ‘on-the-job’ learning
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