In the current CLSVOF method, the normal vector is calculated directly by discretising the LS gradient using a finite difference scheme. By appropriately choosing one of three finite difference schemes (central, forward, or backward differencing), it has been demonstrated that thin liquid ligaments can be well resolved see Xiao (2012). Although a high order discretisation scheme (e.g. 5th order WENO) has been found necessary for LS evolution in pure LS methods to reduce mass error, low order LS discretisation schemes (2nd order is used here) can produce accurate results when the LS equation is solved and constrained as indicated above in a CLSVOF method (see Xiao, 2012), since the VOF method maintains 2nd order accuracy. This is a further reason to adopt the CLSVOF method, which has been used for all the following simulations of liquid jet primary breakup.

O O O B I O O O O O O O O O B O O O B I I O O O O O O B I I O O O O O O O O O O O B O O O O O O O O O O B I I I O B I I O O O O O B O O O B O O B I I B I I I I O O O O O O O O O O O B O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O B I O O O O O O O O O O B O O O

5th order weno
clsvof method
finite difference scheme
finite difference schemes
high order discretisation scheme
liquid
low order ls discretisation schemes
ls
reduce mass error
vof method


Alternatively to H-atom photodetachment from the intermediate radicals, the latter may serve as reducing agents. Evidence has been reported in recent years that the pyridinyl radical (PyH) is an exceptionally strong reducing agent which can even reduce CO2 to formaldehyde, formic acid or methanol with suitable catalyzers [27–29], albeit the mechanisms of these reactions are currently poorly understood [30–32]. The theoretically predicted dissociation thresholds of the AcH, AOH and BAH radicals are about 2.7eV, 2.5eV and 3.0eV, respectively (see Fig. 4), while the predicted dissociation threshold of the pyridinyl radical is much lower, about 1.7eV [1]. Pyridinyl is thus a significantly stronger reductant than acridinyl and related radicals. It is therefore not expected that the latter will be able to reduce carbon dioxide in dark reactions.

O O O O O O B I O O O O O B I O O O O O O O O O B O B O O O O B I O O O O B O B B I O B O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O B O B O O B O O O O O O O O O O O O O B I O O O

ach, aoh and bah radicals
h-atom photodetachment
pyridinyl radical
reduce carbon dioxide in dark reactions

acridinyl
carbon dioxide
catalyzers
co2
formaldehyde
formic acid
intermediate radicals
methanol
pyh
pyridinyl
radicals
reducing agent
reducing agents
reductant


The pipes under pressure in the RCS or connected to RCS are usually made of austenitic or austenitic & ferritic stainless steel. Most connections are welded. The pipes may be exposed to various degradation phenomena (diverse hazards, mechanical fatigue, thermal fatigue, stress corrosion, etc.). Event screening in the databases showed a total of 116 events (33 related to cracks and 83 to leaks). Three main causes for failure were identified, namely, fatigue, corrosion and the presence of manufacturing defects. Human factor induced defects proved to have little impact – less than 10% of the cases could be attributed to operation errors. Fatigue was found being induced by several factors: excessive vibration, pressure shocks and the thermal regime of operating the pipe, as well as by combinations of these factors. Corrosion was induced, in most of the cases, by a non-appropriate choice of alloys while not taking into account the chemical parameters of the fluid inside pipes. Manufacturing defects mostly dealt with welding related problems and deviation from the design documentation during post-weld heat treatment.

O B O O O O B O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O

alloys
event screening
fluid
pipe
pipes
rcs


A fully-coupled numerical framework for two-phase flows with an implicit implementation of surface tension has been introduced in this article. This fully-coupled framework has then been used to compare the influence of the surface tension treatment on the time-step restrictions resulting from capillary waves. The conducted study demonstrates that restrictions on the numerical time-step resulting from capillary waves are valid and unchanged regardless of the numerical treatment of surface tension. Since surface tension is not a function of pressure or velocity, the change in implementation does not affect the matrix coefficients of the primitive variables and, thus, numerical stability is independent of the treatment of surface tension. Further analysis shows that the capillary time-step constraint is a requirement imposed by the spatiotemporal sampling of capillary waves, which is independent of the applied numerical methodology.

O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I I O O B I O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O B I I I I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O B I I

applied numerical methodology
capillary waves
compare the influence
numerical treatment of surface tension
surface tension


An essential part of nuclear reactor analysis is the prediction of the three-dimensional space-time kinetics of neutrons in a relatively large, finite, heterogeneous, three-dimensional reactor core. In a majority of safety analyses the prediction of reactor physics responses is performed using neutron diffusion theory applied to three-dimensional systems, with inputs usually derived from deterministic neutron transport solutions of two-dimensional lattice geometries. There has been increased activity related to uncertainty and sensitivity in reactor physics calculations, and the Organization for Economic Cooperation and Development – Nuclear Energy Agency (OECD-NEA) has sponsored an ongoing benchmark entitled “Uncertainty Analysis in Modelling” (UAM) related to these efforts. The goal of this work is to offer a strategy for computing lattice sensitivities using the DRAGON lattice code and WIMS-D4 multi-group library. Results are presented with comparison to those from TSUNAMI, developed by Oak Ridge National Laboratories.

O O O O B I O O O O O O O O O O B O O O O O O O B O O O O O B I O B I I I I O O O B O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B I I I I O O B I I O O O O O O O O O O O O B O O O O O O


A bond failure is thought of as a micro-crack nucleation, specifically as a separation between the adjacent cells in the cellular structure along their common face. Initially, the micro-cracks may be dispersed in the model reflecting the random distribution of pore sizes and the low level of interaction due to force redistribution. Interaction and coalescence may follow as the population of micro-cracks increases. These situations are illustrated in Fig. 3. The structure of the failed surface can be represented with a mathematical graph, where graph nodes represent failed faces and graph edges exist between failed faces with common triple line in the cellular structure, i.e. where two micro-cracks formed a continuous larger crack. With reference to Fig. 3, each failed face is a graph node and each pair of neighbouring failed faces is a graph edge.

O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O B I O O O O O B I O O O O O O B I O O O O O O O O B O O O O O O B I O O O O O O O O O B I O O O O

bond failure
cellular structure
crack
failed face
failed faces
failed surface
mathematical graph
pore


When dominated by surface shadowing mechanisms, the aggregation of vapor particles onto a surface is a complex, non-local phenomenon. In the literature, there have been many attempts to analyze the growth mechanism by means of pure geometrical considerations; i.e., by assuming that vapor particles arrive at the film surface along a single angular direction [38,41]. Continuum approaches, which are based on the fact that the geometrical features of the film (i.e., the nanocolumns) are much larger than the typical size of an atom [42,266,267], have been also explored. For instance, Poxson et al. [228] developed an analytic model that takes into account geometrical factors as well as surface diffusion. This model accurately predicted the porosity and deposition rate of thin films using a single input parameter related to the cross-sectional area of the nanocolumns, the volume of material and the thickness of the film. Moreover, in Ref. [39], an analytical semi-empirical model was presented to quantitatively describe the aggregation of columnar structures by means of a single parameter dubbed the fan angle. This material-dependent quantity can be experimentally obtained by performing deposition at normal incidence on an imprinted groove seeded substrate, and then measuring the increase in column diameter with film thickness. This model was tested under various conditions [40], which returned good results and an accurate prediction of the relation between the incident angle of the deposition flux and the tilt angle of the columns for several materials.

O O O B I I O B I I I I I I O O O O O O O O O O O O O O B I I I O O O O B I O O O O B I O O O B O O O B I I O B I O O O O O O O O B I O O B O O B O O O O O O O O O B O O O O O O O O O O O O O B I O O O O B I O O O B I O O O O O O O O O O B I O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O B I I I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O


The Magnox reactors represent the first generation of gas-cooled reactors in the UK that used carbon dioxide (CO2) as the primary coolant and a honeycomb network of graphite bricks to provide neutron moderation. During reactor operation significant amounts of carbon monoxide (CO) was produced from the CO2 coolant. This CO in turn can be radiolytically polymerised to form a carbonaceous deposit on free surfaces [12]. This non-graphitic carbon deposit is significantly more chemically reactive to air than the underlying graphite [12,13]. During the lifetime of some Magnox reactors, small quantities of methane gas were injected into the coolant gas to inhibit weight loss of the graphite core due to radiolytic oxidation [14]. Methane (CH4) is a precursor for carbonaceous deposits that form a sacrificial layer protecting the underlying graphite from excessive weight loss [15] and reduction in mechanical strength [16]. It is assumed nitrogen incorporation during deposit formation is the subsequent production route for the high 14C levels observed.

O B I O O O O O O O O O O O O B I B O O O B O O O O O B O O O B O O B O O O O B I B O O O O B B O B O O O O B I O B I I I I I I O O O O O O O O O O O B O O O B O O O O O O B I O O O B O O O O O B O O O O O O O B O O O B I O B B O O O O B I O O O O O O O O B O B I I O O B I I I O O O O B O O O O O O O O O O O O O O O


As already discussed, in dilute flows the choice between the hard sphere and soft sphere models largely depends on the computational time spent to solve the particle equation of motion. For very dilute flows, the hard sphere model is the most natural choice. However, when the collisions can no longer be assumed as binary and instantaneous, the soft sphere model is the only realistic option. It is interesting to know whether the choice of the collision model affects the statistics. Fig. 14 compares the mean velocity obtained from both models with the experimental data. The same comparison is performed for the smooth walls. The differences between the hard and soft sphere models for the smooth walls are almost negligible. However, the differences between the hard and soft sphere models for the rough walls are minor. This is because the rough wall treatment in the soft sphere implementation adds extra virtual walls during the collision of a particle with a wall, which is a more realistic representation of a rough wall compared to the hard sphere rough wall treatment where one random wall is considered. This is because, a soft sphere collision is not instantaneous and occurs over a finite amount of time. Similarly, the same effects are observed on the fluid statistics. However, Fig. 15, which compares the particle velocity fluctuations, shows that the differences are somewhat larger. Additionally, the differences in both particle mean and RMS velocity profiles are because the hard sphere collisions are unfortunately heavily dependent on the tangential coefficient of restitution (ψ); the effects by varying this quantity are shown in Figs. 16 and 17.

O O O O B I O O O O B I I I I I O O O O O O O O O O B O O O O O B I O B I I O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I I I I O O B I O O O O O O O O B I I I I O O B I O O O O O O B I O O O B I I O O B I O O O O O B O O B O O O O O O O O B I O O O B I I I I O O B I O O O O O O B I I O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O

rough wall treatment
solve the particle equation of motion

collision model
dilute flows
fluid
hard and soft sphere models
hard sphere and soft sphere models
hard sphere collisions
hard sphere model
hard sphere rough wall treatment
particle
random wall
rough wall
rough walls
smooth walls
soft sphere collision
soft sphere implementation
soft sphere model
virtual walls
wall


The sodium trimer has a long history of theoretical and experimental studies. A pioneering theoretical paper of Martin and Davidson published in 1978 showed that the obtuse isosceles geometry is lower in energy than the linear conformation [6]. Several extended PES scans of Na3 and other alkali trimers followed this initial study, employing DFT [7], complete active space SCF [8], or a configuration interaction approach based on valence bond wave functions [9]. Recently, the applicability of density functional theory (DFT) to JT-distorted systems has also been tested for Na3 [10], and the B-X transition has been revisited as well, applying state-averaged multi-reference configuration interaction with a large active space in order to derive more accurate non-adiabatic coupling terms for an improved interpretation of photoabsorption spectra [11–13].

O B I O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O B I O O O B I O B O O B I O O O O O B O B I I I O O O B I I O O B I I I O O O O O B I I B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O

alkali trimers
complete active space scf
configuration interaction approach
density functional theory
dft
linear conformation
na3
obtuse isosceles geometry
pes scans
photoabsorption spectra
sodium trimer
valence bond wave functions


The wind speed and cloud height Markov chains are produced accounting for seasonal variations. A Markov chain is used for each variable representing each of the four seasons, capturing the variability at different times of the year, totalling four chains each. The okta number Markov chains also consider the effect of season, with the inclusion of impacts from pressure and diurnal variation. Eight okta Markov chains are produced that are split by above and below average pressure for each season, and four additional morning okta Markov chains are produced to capture the diurnal variation for okta transitions between 00:00 and 05:00am for each season. The intent is to capture the variation in transition probability that occurs as a result of weather changes due to the presence of solar energy. 5am is considered the cut-off because it is a typical sunrise in the summer for the applied study locations. 5h represents 5 okta transitions and is considered an appropriate duration for the slight propensity to shift towards an increased okta to be represented, Fig. 8 demonstrates the diurnal transition differences. Fig. 2 visually demonstrates the mean okta Markov chain for the entire year, whilst the effect of season can be seen in Fig. 11.

O B I I I I I I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O B I I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O

wind speed and cloud height markov chains


It is critical to the success of the NPD technique that the MOF complex adsorbs a significant amount of D2 to boost the observed signal. This technique therefore has disadvantages when studying the binding interaction within MOFs with low uptakes. Furthermore, static crystallographic studies cannot provide insights into the dynamics of the adsorbed gas molecules. Thus, it is very challenging to probe experimentally the H2 binding interactions within a porous host system which has very low gas uptake due to the lack of suitable characterisation techniques. We report herein the application of the in situ inelastic neutron scattering (INS) technique to permit direct observation of the dynamics of the binding interactions between adsorbed H2 molecules and an aluminium-based porous MOF, NOTT-300, exhibiting moderate porosity, narrow pore window and very low uptake of H2. This neutron spectroscopy study reveals that adsorbed H2 molecules do not interact with the organic ligand within the pore channels, and form very weak interactions with [Al(OH)2O4] moieties via a type of through-spacing interaction (Al-O⋯H2). Interestingly, the very low H2 adsorption has been successfully characterised as weak binding interactions and, for the first time, we have found that the adsorbed H2 in the pore channel has a liquid type recoil motion at 5K (below its melting point) as a direct result of this weak interaction to the MOF host.

O O O O O O O O B I O O B O O O O O O B O O O O O O O O O O O O O B I O B O O O O B I I O O O O O O O O B I I O O O O O O O O O B O O O O O O O O O O O B O O O O O O O B I O O O O O O O B I I I I B O O B I I I I I I I I I O B I O O O O O B O O O O O O O O O O O O B O B I O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B I I O O O O O O O O O O B I O O O O O O B O O O O O O O O O O O O O O O B I O O B O

adsorbed h2 molecules
al-o⋯h2
[al(oh)2o4] moieties
aluminium-based porous mof
h2 adsorption
h2 binding interactions
mof complex
nott-300
through-spacing interaction


It has been known [9,14,18,22] that the fragmentation processes in polyatomic molecules induced by an intense ultrafast laser field can sometimes exhibit sensitive dependence on the instantaneous phase characteristics of the laser field. Depending on the change in sign the chirped laser pulses, fragmentation could be either enhanced or suppressed [14,18,22]. Controlling the outcome of such laser induced molecular fragmentation with chirped femtosecond laser pulses has brought forth a number of experimental and theoretical effects in the recent years. However, efforts are continuing for a specific fragment channel enhancement, which is difficult since it also is a function of the molecular system under study [20,22–24]. Here we report the observation of a coherently enhanced fragmentation pathway of n-propyl benzene, which seems to have such specific fragmentation channel available. We found that for n-propyl benzene, the relative yield of C3H3+ is extremely sensitive to the phase of the laser pulse as compared to any of the other possible channels. In fact, there is almost an order of magnitude enhancement in the yield of C3H3+ when negatively chirped pulses are used, while there is no effect with the positive chirp. Moreover, the relative yield of all the other heavier fragment ions resulting from interaction of the strong field with the molecule is not sensitive to the sign of the chirp, within the noise level.

O O O O O O O B O O B I O O O B I I I O O O O O O O O O O O O B I O O O O O O O B I I B O O O O O O O O O O O O O O O B O B I I I O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O B I O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B O O O O O O O O O O O O O O O O B I I O O O O O O O O O O B O O O O O O O O B I I O O O O O O O O O B O O O O O O O O B O O O O

channels
chirp
chirped femtosecond laser pulses
chirped laser pulses
fragmentation
fragment channel enhancement
heavier fragment ions
intense ultrafast laser field
laser field
laser pulse
molecular system
molecule
negatively chirped pulses
polyatomic molecules


The four bounding PCM wastes, given in Table 1, were simulated using the most appropriate materials and geometries. “Mock up” PCM drums were assembled using the following components: PCM drums were simulated using mild steel paint cans and lids (Fenton Packaging Ltd.); PVC bags were replicated using identical PVC sheeting (Romar Workwear Ltd.); the metallic waste was simulated using commercial grade 18/8 stainless steel, aluminium and copper (Avus Metals & Plastics Ltd.), and lead shot (Aldrich); the inorganic waste was simulated using waste Pyrex labware, crushed masonry, concrete and window glass; CeO2 (from Acros Organics, >99.9%; dried 15h at 600°C) was used as a PuO2 surrogate. Commercially available ground, granulated blast-furnace slag “Calumite” was used as an additive [27]. The analysed chemical composition is given in Table 3. Calumite is a powdered material, with a typical particle size distribution between limits of ca. 40 to ca. 400μm.

O O B I I O O O O O O O O O O O O O B I I I O O O O O O B I O O O B I I I I I O O O B I O O O B I I O O O O B I O O O O O O O O B O B O O O O O O B I O O B I O O O B I I O B B O B I B O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B O O B I O O O B O O O O O O O O O O

blast-furnace slag “calumite”
commercial grade 18/8 stainless steel

aluminium
bounding pcm wastes
calumite
ceo2
concrete
copper
identical pvc sheeting
inorganic waste
lead shot
masonry
metallic waste
mild steel paint cans and lids
“mock up” pcm drums
particle
pcm drums
powdered material
puo2 surrogate
pvc bags
waste pyrex labware
window glass


Generalized

polynomial

chaos

expansions.

One

approach

to

model

densities

with

stochastically

dependent

components

numerically,

is

to

reformulate

the

uncertainty

problem

as

a

set

of

independent

components

through

generalised

polynomial

chaos

expansion

As

described

in

detail

in

Section

a

Rosenblatt

transformation

allows

for

the

mapping

between

any

domain

and

the

unit

hypercube

With

a

double

transformation

we

can

reformulate

the

response

function

f

asf(x,t,Q)=f(x,t,TQ−1(TR(R)))≈fˆ(x,t,R)=∑n∈INcn(x,t)Φn(R),where

R

is

any

random

variable

drawn

from

pR,

which

for

simplicity

is

chosen

to

consists

of

independent

components.

Also,

{Φn}n∈IN

is

constructed

to

be

orthogonal

with

respect

to

LR,

not

LQ.

In

any

case,

R

is

either

selected

from

the

Askey-Wilson

scheme,

or

calculated

using

the

discretized

Stieltjes

procedure.

We

remark

that

the

accuracy

of

the

approximation

deteriorate

if

the

transformation

composition

is

not

smooth

Dakota,

Turns,

and

Chaospy

all

support

generalized

polynomial

chaos

expansions

for

independent

stochastic

variables

and

the

Normal/Nataf

copula

listed

in

Table

Since

Chaospy

has

the

Rosenblatt

transformation

underlying

the

computational

framework,

generalized

polynomial

chaos

expansions

are

in

fact

available

for

all

densities.

B I I I O O O B I O O O O O O O O O B I O O O O O O O B I I I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O B I O O B I B I I I O O O O O O O

computational framework
discretized stieltjes procedure
generalised polynomial chaos expansion
generalized polynomial chaos expansions
model densities
rosenblatt transformation
uncertainty problem


The data acquisition strategies must balance the relevant scales and volumes of the datasets to be used in the physical and statistical modeling. Approaches for extraction of the necessary information must be able to disregard spurious information, so as to develop a working network of models for each active mechanism related to each degradation pathway on the mesoscopic physical level and the data-driven statistical model level. To capture the temporal evolution of the energy material over long time frames, appropriate informatics methods are needed to balance data volume (e.g., simple univariate time-series data streams with high-dimensional volumetric imaging datasets) while considering their respective information contents [68,69]. The raw data and extracted information must be accessible for query and modeling. Similarly, the modeling approaches used to understand and parameterize active mechanisms and phenomena over lifetime fall into the broad categories of micro-, meso- and macroscopic approaches. Laboratory and real-world experimentation, informatics, analytics, and the development of network models for mesoscopic evolution of energy materials over lifetime together constitute the field of degradation science.

O B I I O O O O O O O O O O O O O O O O O O B O O B I I I I O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O B I O O B I I I O O B I O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O B I I I O O O O B I O O O O O O O B I

laboratory and real-world experimentation

analytics
appropriate informatics methods
capture the temporal evolution
data acquisition strategies
degradation science
development of network models
energy material
energy materials
extraction of the necessary information
informatics
modeling
network of models
query
statistical model


Hydrides, once precipitated in zirconium, degrade the mechanical properties of a component, leading to reductions in tensile strength, ductility and fracture toughness [35–40]. These changes can ultimately compromise the integrity of cladding during normal operating life , accident conditions and fuel storage [13]. As well as the degradation of mechanical properties, the presence of hydrides can also affect phenomena like pellet cladding mechanical interaction (PCMI); or introduce mechanisms for failure, such as delayed hydride cracking (DHC). The former mechanism is the product of thermal expansion in fuel pellets introducing stresses into the cladding, which may then lead to the formation of cracks in areas made brittle by large hydride concentrations [13]. The latter mechanism, DHC, is a sub-critical, time dependent cracking phenomenon that requires long range hydrogen diffusion for repeated local hydride growth and fracture at a hydrostatic tensile stress raiser [5,41,42]. The process occurs over an extended period of time under a continuously applied load that is below the yield stress of the material [5,41,42].

B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O B O O O O O O B O O B O O O O O O O B I I B O O O O O O O B I O B O O O O O B O O O O O O O O O O O O O O O B O O O O O B O O O O O B I O O O O B O O O O B O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O

fuel pellets
hydrogen diffusion
local hydride growth
pellet cladding mechanical interaction

cladding
cracking phenomenon
delayed hydride cracking
dhc
fuel
hydride
hydrides
hydrogen
hydrostatic tensile stress raiser
pcmi
thermal expansion
zirconium


A surfactant is a surface active agent. In this work a surfactant term will be used for compounds which improve the dispersability of the CI in the acid (as emulsifiers providing dispersed emulsion – not separated) while wetting the surface of the metallic material [14,20,24]. However, surfactants can offer corrosion protection themselves. Some examples when the same compound was used as a surfactant or active corrosion inhibitor ingredient are given below. Typical surfactants in the oilfield services industry are alkylphenol ethoxylates, e.g. nonylphenol ethoxylate (NPE) [14,15,30,106,107]. However, NPEs have been banned from use in the North Sea because of their toxicity. On the other hand, ethoxylated linear alcohols are more acceptable [20]. The quaternary ammonium salts and amines (when protonated) are the most used compounds of the cationic surfactants class, where the cation is the surface active specie. As the amines only function as a surfactant in the protonated state, they cannot be used at high pH. On the other hand, quaternary ammonium compounds, frequently abbreviated as “quats”, are not pH sensitive. Long-chain quaternary ammonium bromides were also reported to work as efficient CIs for steel materials [106]. A frequently employed surfactant was N-dodecylpyridinium bromide (DDPB) [9,60,61,108,109]. Anionic sulphates, anionic sulphonates, alkoxylated alkylphenol resins, and polyoxyethylene sorbitan oleates are also useful surfactants. Ali reported that a particularly useful surfactant is a blend of polyethylene glycol esters of fatty acids and ethoxylated alkylphenols [15]. Several examples of the surfactants used are given below in Section 5.6.

O B O O B I I O O O O B O O O O O B I I I I O O B O O B O B O B I O O O O O O O O O B I O O B O O B I O O O O O O O O O O O B O O O O O O O O O B O O O O O O B I O B I B O O B O O O O O O O O O O O O O O O O O B I I O O O O O B I I O B O O O O O O O O O B I I O O B O O B I I O O B O O O O B O O B I O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O B O B I O O O O B O O O B O B I B I B I I O B I I O O O B O O O O O O B O O B I I I I I I I I I I O O O O O B O O O O O O O


One of the most important outcomes of the comparative analysis is the fact that in all tested cases the use of FM is associated with a dramatic reduction in computational time when compared with FE, generally being in the order of seconds for FM and in the order of hours for FE. Table 1 reports the timings of the simulations for both methods. Free expansion is the fastest case, where FM reaches the load-free configuration in just 2 s, while simulations inside the vessels with the diameter of around 30 mm take approximately 30 s. Most of the execution time of the FM deployment algorithm is dedicated to the contact check and calculations of the implications the vessel wall has on the stent structure. Interestingly, in both methods, the highest computational time (i.e., curved vessels) is not associated with the most complex geometry (i.e., patient-specific case of aortic dissection). Another fact worth mentioning is the relation of the computational time to the diameter of the vessel in both methods. While the computational time of FM appeared to be directly related to the diameter of the vessel, no immediate relation was found for the FE simulations. Such outcome is probably related to the simplified contact model used by FM, which makes the stent-graft expansion terminate once the nodes come in contact with the vessel wall. On the contrary, it is well known that the contact algorithm used in the FE analyses increases the computational cost of the simulations.

O O O O O O O O B I O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O B O O O O O O O B O O O O O O O B O O O O O O O O O O B O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O B O O O O O O O B B O O O O O O O B I I O O B O O O O O O O O B O O O O O B O O O O O O O O O O B I O O O B O O O O O O O B

fe analyses
fe simulations
fm deployment algorithm
stent-graft expansion
vessel wall

comparative analysis
contact algorithm
curved vessels
fe
fm
nodes
simplified contact model
simulations
vessel
vessels


Since the receptors in human biology mostly consist of chiral molecules, drug action mostly involves a specified enantiomeric form. This has spurred the development, especially in the pharmaceutical industry, of a host of techniques to secure enantiopure products. Such methods, mostly multi-step and time-consuming, can typically be cast in one of two distinct categories: synthetic mechanisms designed to produce a single stereoisomer, or separation techniques to isolate distinct enantiomers from a racemic mixture. A significant drawback, for either approach, is a dependence on a supply of enantiopure reagents or substrates – synthesis routes generally utilise chiral building blocks or enantioselective catalysts [7,8], while enantiomer separation techniques typically incorporate chiral selector molecules to form chemically distinct and distinguishable diastereomeric complexes [8,9]. A key requirement in aiming to achieve enantiopure products, irrespective of the synthetic method, is therefore a means to measure, and duly quantitate the enantiomeric excess – signifying the degree of chirality within molecular products. Chiral discrimination through optical means is well-known to offer direct, non-contact ways to distinguish between molecules of different handedness, based on observations such as the subtle differences in absorption of left- and right-handed circularly polarised light, or indeed the twisting of polarisation in optical rotation. Other optical methods, under more recent development, also show some promise to achieve enantiomer separation, as will be introduced later.

O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O B O B I O O O B O O O O O O O O O O O O O O O O O B I I I O B I O O B I I O B I O O B I O O O B I I O O O O O O B I O O O O O O O O B I O O O B I O O O O O O O O O O B I O O O B I I O B I B I O B I O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O B I I I I I O B I O O O O O O O O O O B I O O O O O


For any quantum dynamical method, existing or emerging, reliable benchmarks are required to assess their accuracy. A model Hamiltonian exhibiting tunnelling dynamics through a multidimensional asymmetric double well potential has been used as a test by the MP/SOFT [18] and CCS methods [19] mentioned above, and also more recently by a configuration interaction (CI) expansion method [20] and two-layer version of CCS (2L-CCS). [21] The Hamiltonian consists of a 1-dimensional tunnelling mode coupled to an (M−1)-dimensional harmonic bath, hence it is a system-bath problem which bears some similarity to the Caldeira-Leggett model of tunnelling in a dissipative system [22,23]. This Hamiltonian is non-dissipative, however and the harmonic modes all have the same frequency. System-bath models play an important role in physics, being used to describe superconductivity at a Josephson junction in a superconducting quantum interface device (SQUID) [24], for which the Caldeira-Leggett model provides a theoretical basis, and magnetic and conductance phenomena in the spin-bath regime [25].

O O B I I O O O O B O O O O O O B I I O B I O O B I I I I O O O O O O O O O O O B I O O O O O O O O O B I B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B I O O O O O O O O O O O O B O O O O B I I I I O O B I I I B O O O O O O O O O O O B I I I O O O O O

configuration interaction (ci) expansion method

superconductivity at a josephson junction


As discussed above, proper inclusion of these interactions requires segment synchronization after every iteration. In order to minimize simulation errors due to incorrect values of the interactions potential, segments are synchronized after every iteration. Although relatively long communication times between remote processors may hinder this process in typical parallel computers, this is not the case for GPGPU architectures. Still, full recalculation of the interaction potential after each iteration is time consuming. Instead, the algorithm corrects the current potential by adding dipole contributions for every nearby charge that hopped during the previous iteration. Full updates of the interaction potential are only required for the grid points that are related to charges that hopped during the last iteration. Accumulative rounding errors that arise due to repetitive addition and subtraction are solve this by rounding all interaction potentials to a uniformly spaced range of floating point numbers.

O O O B I I I I O B I I I I O O O B I I O O O O O O O O B I I I I I O O O O O O O B O O O O O O B I O O O O O O B I O O O O O B I O O O O O O O O B B I I I O B I I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Gas sorption, storage and separation in carbon materials are mainly based on physisorption on the surfaces and particularly depend on the electrostatic and dispersion (i.e., vdW) interactions. The former can be tuned by introducing charge variations in the material, and the latter by chemical substitution. The strength of the interaction is determined by the surface characteristics of the adsorbent and the properties of targeted adsorbate molecule, including but not limited to the size and shape of the adsorbate molecule along with its polarizability, magnetic susceptibility, permanent dipole moment, and quadrupole moment. Li et al. summarise the adsorption-related physical parameters of many gas or vapour adsorbates, and herein Table 1 we show a few of those of interest, H2, N2, CO, CO2, CH4, NH3, SO2 and H2S [90]. For instance, an adsorbent with a high specific surface area is a good candidate for adsorption of a molecule with high polarizability but no polarity. Adsorbents with highly polarised surfaces are good for adsorbate molecules with a high dipole moment. The adsorbents with high electric field gradient surfaces are found to be ideal for the high quadrupole moment adsorbate molecules [91]. Normally, the binding or adsorption strength with a carbon nanostructure is relatively low for H2 and N2; intermediate for CO, CH4 and CO2; and relatively high for H2S, NH3 and H2O. Thus, surface modifications, such as doping, functionalization and improving the pore structure and specific surface area of nanocarbons, are important to enhance gas adsorption. For this purpose, graphene offers a great scope for tailor-made carbonaceous adsorbents.

O O O O O O B I O O O O B O O O O O O O O O O O O O O O O O O O O B I I I I I O O O O B I O O O O O O O O O O O O O B O O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O B B B B B B B O B O O O O B O O O O O O O O O O O O O O B O O O O O O B O O O O O O O B I O O O O O O B O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B O B O O B B O B O O O O B B O B O B I O O B B O B I I I I I I I I I O O O B I I O O O B O O O O O O O B

electrostatic and dispersion (i.e., vdw) interactions


The homologous series of n-alkanes are represented here as homonuclear chains of tangent Mie spherical CG segments. The development of CG models for long n-alkanes such as n-decane (n-C10H22) and n-eicosane (n-C20H42) has already been successfully demonstrated using the SAFT-γ Mie formalism [118]. The n-decane molecule was represented by chains of three and n-eicosane chains of six fully flexible tangentially bonded Mie segments. A certain degree of parameter degeneracy in terms of overall performance is expected as a consequence of the conformal nature of the EOS description [132]. In our current work, we use an alternative CG mapping for n-alkanes developed in reference [122], where each segment was taken to represent three alkyl carbon backbone atoms and their corresponding hydrogen atoms. By applying this mapping, n-alkanes chains containing multiples of three carbon units can be represented directly: n-C6H14, n-C9H20, n-C12H26, n-C15H32, n-C18H38, etc. A good description of the thermodynamic properties of these alkanes is found to be provided with CG alkyl beads characterised by the Mie (15–6) potential. For convenience, the exponent pair (15–6) is also used to represent the interactions between the CG beads of the intervening alkanes considered here; the number of segments m is taken to be the nearest integer of the division of the carbon number C by three. The size σ and energy ∊ parameters are then estimated from the experimental saturated-liquid density and vapour pressure of the individual alkanes following the usual SAFT-γ Mie procedure. The chosen mapping is by no means unique, as one can postulate parameter sets that fulfil other requisites, such as being “universal” across the entire homologous series [119] or correlated to the critical properties [125].

O O O O O O O O O B I I I I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O B I I I O O O B I O O O O O O O O O O B O O O O O O O O O O O O O B I I I I O O B O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O B I O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B I O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

development of cg models for long n-alkanes

homonuclear chains of tangent mie spherical cg segments


The need to represent scale interactions in weather and climate prediction models has, for many decades, motivated research into the use of adaptive meshes [3,34,38]. R-adaptivity – mesh redistribution – involves deforming a mesh in order to vary local resolution and was first considered for atmospheric modelling more than twenty years ago by Dietachmayer and Droegemeier [14]. It is an attractive form of adaptivity since it does not involve altering the mesh connectivity, does not create load balancing problems because points are never created or destroyed, does not require mapping of solutions between meshes [26], does not lead to sudden changes in resolution and can be retro-fitted into existing models. Variational methods exist which attempt to control resolution in different directions for r-adaptive meshes (e.g. [23,25]). Alternatively, the solution of the Monge–Ampère equation to generate an optimally transported (OT) mesh based on a scalar valued monitor function is a useful form of r-adaptive mesh generation because it generates a mesh equidistributed with respect to a monitor function and does not lead to mesh tangling [7]. We will see that the optimal transport problem on the sphere leads to a slightly different equation of Monge–Ampère type, which has not before been solved numerically on the surface of a sphere, which would be necessary for weather and climate prediction using r-adaptivity.

O O O B I I O B I I I O O O O O O O O O O O B I O O O B O O O B I I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B O O O O O B I I I O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B O O O O O O O B O O O O O O O B O O O O O B I O O O O O O B O O O O O B O O O O O B I O O O O O B O O O O O O O B I I I I I O O O O O O O B O O O O O O O O O O O O O B O O O O O B I I I O O

adaptive meshes
adaptivity
altering the mesh connectivity
atmospheric modelling
deforming a mesh
mapping of solutions between meshes
mesh
meshes
monge–ampère
monitor function
optimal transport problem on the sphere
represent scale interactions
sphere
variational methods
weather and climate prediction


There is still some debate about the crystal structure and composition of the fine oxides found in ODS steels and a number of different phases have been both proposed and identified. A complete characterisation of the oxide particles, including crystal structure and composition, is needed as different phases and chemical variants of a single structure have been shown to respond differently to high temperatures and irradiation. Ribis and de Carlan [6] have studied the coarsening characteristics of Y2O3 and Y2Ti2O7 oxides at high temperatures. They show that the increase in particle size is greater for the non-Ti containing phase. Similarly, Ratti et al. [9], although they do not allude to specific oxide phases, have shown that small Ti additions to an 18%Cr ODS alloy dramatically reduces the coarsening rates of dispersoids when compared to an equivalent alloy without titanium. For example, Ribis indicates that coarsening rates may be controlled by interfacial energy between the secondary phase particles and the matrix; he points out that the resistance to coarsening observed in the Y, Ti, O system is probably the result of a very low interface energy and this would differ from one phase to another. Whittle et al. [10] have shown that pyrochlore and structures closely related to the pyrochlore structure respond in different ways to irradiation. They revealed that oxide structure and variations in composition can affect their ability to withstand and recover from irradiation induced damage.

O O O O O O O B O O O O O B I O O B I O O O O O O O O O O O O O B I I I I I O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O B I O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O B O O O B I O B O O O O O B O B O O O O O B I O O O O O O O O O O B O O B O O O O O O O O O O O B B B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O B O O O B O O O O O O O O O O O O O O B O O


The vibrational spectra of l-cysteine have been recorded and assigned in both solution [8,9] and the solid state [10–14]. Spectral assignments have been made using empirical force fields [15], Hartree–Fock calculations [10,16,17] based on the isolated molecule approximation. For systems that exhibit strong intermolecular interactions, this approximation often leads to poor agreement between experiment and theory. A striking example is purine [18], where a study of the solid state vibrational spectra by isolated molecule and periodic calculations, gave almost quantitative agreement between theory and experiment for the latter, whereas the former gave only modest agreement and was unable to distinguish between the tautomers. In the present case, where the structure consists of ions linked by hydrogen bonds, periodic calculations based on the complete primitive cell are essential [19]. The only work [20] that includes some solid state effects used molecular dynamics but from which it is difficult to extract assignments. The aim of this paper is to provide a complete assignment of the vibrational spectra of l-cysteine in both the orthorhombic and monoclinic forms by the use of a combination of computational and experimental methods.

O O O O O O O O O O O O O O O O O O O B I O O O O B I I O B I O O O O B I I O O O O O O O O O O O O O O O O O O O O O O B O O O B I I I I I I O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O B O B I O O O B I I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I


The dynamics of various physical phenomena, such as the movement of pendulums, planets, or water waves can be described in a variational framework. The development of variational principles for classical mechanics traces back to Euler, Lagrange, and Hamilton; an overview of this history can be found in [1,19]. This approach allows to express all the dynamics of a system in a single functional – the Lagrangian – which is an action integral. Hamiltonian mechanics is a reformulation of Lagrangian mechanics which provides a convenient framework to study the symmetry properties of a system. This is expressed by Noether's theorem which establishes the direct connection between the symmetry properties of Hamiltonian systems and conservation laws. When one approximates the system numerically, it is advantageous to preserve the Hamiltonian structure also at the discrete level. Given that Hamiltonian systems are abundant in nature, their numerical approximation is therefore a topic of significant relevance.

O O O O B I O O O O O B B O B I O O O O O O B O O O B I O O O O O O O O O O O O O O O O O O O O O B O O O O O B I I I O O B I O O B O O O O B I B I O O O O B O O O O O B O B I I I I I I O O O O O O O O O O O O O O O O B I O O O O O O O B O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O O O

the dynamics of various physical phenomena


It is well-known that the optical properties of atoms and molecules can be influenced by their electronic environment. Local field effects on spontaneous emission rates within nanostructured photonic materials for example are familiar, and have been well summarized [1]. Optical processes, including resonance energy transfer are similarly dependent on the local environment of molecular chromophores [2–4]. Many biological systems are known to contain complex organizations of molecules with absorption bands shifted due to the electronic influence of other, nearby optical centres. For instance, in widely studied light-harvesting complexes, there are two identifiable forms of the photosynthetic antenna molecule bacteriochlorophyll, with absorption bands centred on 800 and 850nm; it has been shown that the most efficient forms of energy transfer between the two occurs when there is a neighbouring carotenoid species 5–7. Until now, research on the broader influence of a neighbouring, off-resonant, molecule on photon absorption has mostly centred on the phenomenon of induced circular dichroism, where both quantum electrodynamic (QED) calculations [8–10] and experimental procedures [11–13] predict and verify that a chiral mediator confers the capacity for an achiral acceptor to exhibit circular differential absorption.

O O O O O B I O B O B O O O O O B I B I I O O O O O B I I O O O O O O O O O O B I O O B I O O O O O B I I I I O O O O O O O O O O O B O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O B O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O B O B O O O O O O O O B I I O O B I B O O O B I O O O O O O B I O O O O O B I O O B I I


The main drawback of thermo-oxidation in most actual devices and ITER is its limitation to maintenance periods, when the vessel walls can be heated up around 300–400 °C by hot helium injection through the cooling system [19,20], and also because of the required reconditioning of the walls before plasma operation to remove the absorbed oxygen [10]. However, the temperature achieved is not homogeneous over the vessel, as it is limited to the distance to the cooling tubes, and thus to the device design. The analysis of this study is a continuation of previous works done for the treatment of ITER carbon co-deposits [1–3], so the temperatures studied are in the range of 350 °C for divertor and 200–275 °C for main wall and remote parts. At present, due to budget restrains as well as due to tritium trapped in co-deposited carbon layers, ITER will not use carbon materials at the divertor strike points in spite of their excellent resilience against large heat loads. Nevertheless, many present experimental nuclear fusion devices (DIII-D, TCV, etc.) and new ones (JT-60SA, KSTAR, Wenderstein-7X) use carbon elements, so the removal of carbon co-deposits is still necessary for a better device operation—plasma density control, dust events, etc. The temperatures used in this work are not very different from the ones achievable in present devices, such that the results can be extrapolated to them. Moreover, even for ITER this study could be useful if carbon materials have to be eventually installed in the case that operation with tungsten tiles at the strike points is precluded by unexpected reasons.

O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O B O O O B I O O O O O O O B O O O O B I O O O O B O O O O O O O O O O B O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O B O O O O B I O B I O O O O O O O O O O O B O O O B O B O O O B O O O B O O O O O O O O O O O O O O O O B I I O B O O O O O B O O B O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O B I O O O O O O O O O

carbon elements
carbon layers
carbon materials
diii-d
iter carbon
jt-60sa
plasma density control
removal of carbon co-deposits
thermo-oxidation
treatment of iter carbon co-deposits
wenderstein-7x

carbon
cooling system
cooling tubes
divertor
dust
helium
iter
kstar
main wall
nuclear fusion devices
oxygen
plasma operation
reconditioning
remote parts
tcv
tritium
tungsten tiles
vessel


This work shows how our approach based on the combination of Statistical Mechanics and nonlinear PDEs theory provides us with a novel and powerful tool to tackle phase transitions. This method leads to solution of perhaps the most known test-case that exhibits a first order phase transition (semi-heuristically described) such as the van der Waals model. In particular we have obtained the first global mean field partition function (Eq. (9)), for a system of finite number of particles. The partition function is a solution to the Klein–Gordon equation, reproduces the van der Waals isotherms away from the critical region and, in the thermodynamic limit N→∞ automatically encodes the Maxwell equal areas rule. The approach hereby presented is of remarkable simplicity, has been successfully applied to spin [17–19,14,16] and macroscopic thermodynamic systems [20,15] and can be further extended to include the larger class of models admitting partition functions of the form (4) to be used to extend to the critical region general equations of state of the form (7) including a class virial expansions.

O O O O O O O O O O O B I O B I I O O O O O O O O O O B I O O O O O O O O O O O O O O B I I I O O O O O B I I I O O O O O O O O O B I I O O O O O O O O O O O B I O O O O O B I O O B I I I O O O O O O O O B I I O O O B I I I O O O O O O O O O O O O O B O O B I I O O O O O O O O O O O O O O B I I I I O O O O O O O O O O B I I I I I I O O O B I I

class virial expansions
field partition function
first order phase transition
general equations of state of the form
klein–gordon equation
macroscopic thermodynamic systems
maxwell equal areas rule
nonlinear pdes theory
partition function
partition functions of the form
phase transitions
spin
statistical mechanics
thermodynamic limit n→∞
van der waals isotherms
van der waals model


Structural properties are well reproduced by all models (Table 2), but the significant improvement of our potential stands in the elastic constants which relate to how the system responds to stress. Indeed, structure and elasticity are important parameters for elucidating grain boundary stability. All potential models correctly predict the relative stability of the defect energies. The Morelon potential model performed best as it was specifically derived to replicate defect formation energies, but it largely underestimates the bulk modulus. The energies calculated with the Morl and the Arima potential models are overestimated; this is a known disadvantage of using rigid ion models as the ionic polarisability is not taken into account. For completeness, we report two shell models with the best results given by the Catlow potential model. The Morl, along with the Grimes shell potential model, accurately reproduce the activation energy of oxygen migration (the migration path was the lowest energy and most favourable diffusion mechanism observed in bulk UO2 [1]). The major deficiency of the Morl potential is that the cation defect energies are high, and hence the number of cation defects will be underestimated. However, this should not be an issue unless this model was applied to processes such as grain growth where cation mobility will contribute.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O B I I I I I I I O B I I O O O O O O O O B I I I O O O O O O O O O O O O B I I I I I O O O O O O O O O B I I O O O O O O O O O O O O O O B I O O O O O O O B I I O O O O O O O O O O O O O O O B O O B I O O O O O O O B I O O O B O O O O O O B I O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O B O O O

morl, along with the grimes shell potential model


The formulation in Table 1 was derived by an empirical approach and led to a non-classical glass matrix. Carter et al. [3] and Zhang et al. [4] took a more systematic approach to such glass-ceramic wasteforms. These wasteforms were targeted at Hanford K-basin sludges and the immobilisation of the primary waste stream from production of molybdenum-99 at the Australian Nuclear Science and Technology Organisation site in Sydney respectively. In the work of Carter et al. and Zhang et al. the intended crystalline phase was the closely related titanate pyrochlore, CaUTi2O7. The glass matrix was formulated such that the trivalent species in the glass network, boron and aluminium, were charge compensated on a molar basis by sodium. The stoichiometric composition of the glass in this wasteform was Na2AlBSi6O16. This glass provides a method by which the glass composition can be varied systematically. Given that the initial observations inferred an important role played by alumina, it was decided to prepare a suite of zirconolite glass-ceramics in which the glass matrix was defined by Na2Al1+xB1–xSi6O16 to investigate the role played by glass composition in controlling crystalline phase stability. The x=1 end member gives the mineral albite, NaAlSi3O8. The melting point of albite is 1120°C [5] and the composition cools to a glass at the cooling rates that occur during a HIP cycle. From the available phase diagrams, [6] no boron analogue for albite was shown, and the liquidus estimated from the relevant phase diagram is 1100–1200°C. No phase diagrams for the quaternary system Na2O–Al2O3–B2O3–SiO2 could be found.

O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B I B O B O O O O O O O O O O B O B O B O O O O O O O O B O O O O O B O O O O B O B O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O B O O O B O O O O O O O O O B B O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O B O O O

albite
alumina
aluminium
boron
cauti2o7
crystalline
glass
na2albsi6o16
na2o–al2o3–b2o3–sio2
naalsi3o8
sodium
titanate pyrochlore


In addition, the prediction of solar cell’s temperature is very important for the electrical characterisation of CPV modules. Rodrigo et al. (2014) reviewed various methods for the calculation of the cell temperature in High Concentrator PV (HCPV) modules. The methods were categorised based on: (1) heat sink temperature, (2) electrical parameters and (3) atmospheric parameters. The first two categories are based on direct measurements of CPV modules in indoor or outdoor experimental setups and presented the highest degree of accuracy (Root Mean Square Error (RMSE) 1.7–2.5K). Most of the methods reviewed by Rodrigo et al. (2014) calculate the cell temperature at open-circuit conditions. Methods that predict the cell temperature at maximum power point (MPP) operation offer a more realistic approach since they include the electrical energy generation of the solar cells (i.e. real operating conditions); Yandt et al. (2012) described a method predicting the cell temperature at MPP based on electrical parameters and Fernández et al. (2014b) based on heat sink temperature with absolute RMSE 0.55–1.44K. Fernández et al. (2014a) also proposed an artificial neural network model to estimate the cell temperature based on atmospheric parameters and an open-circuit voltage model based on electrical parameters (Fernandez et al., 2013a) offering good accuracy (RMSE 3.2K and 2.5K respectively (Rodrigo et al., 2014)). The main disadvantage of the aforementioned methods is that an experimental setup is required to obtain the parameters used for the cell temperature calculation.

O O O B I I I I O O O O O O O O B O O O O O O O O O O B I I I I O B I I B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O B O O B I I B O O O O O O O O O O B I I O O B I O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O

cell temperature calculation
estimate the cell temperature
open-circuit conditions
open-circuit voltage model
predicting the cell temperature at mpp
solar cell

artificial neural network model
calculate the cell temperature
calculation of the cell temperature
cell
cpv
electrical energy generation
hcpv
high concentrator pv
maximum power point
mpp
prediction of solar cell’s temperature
solar cells


The

control

of

the

RP

re-encounter

probability

finds

a

direct

application

to

improve

the

performance

of

chemical

devices.

Here,

we

show

how

a

simple-to-implement

control

scheme

highly

enhances

the

sensitivity

of

a

model

chemical

magnetometer

by

up

to

two

orders

of

magnitude.

The

basic

idea

behind

a

chemical

magnetometer

is

that,

since

a

change

in

the

magnetic

field

modifies

the

amount

of

singlet

products,

one

can

reverse

the

reasoning

and

measure

the

chemical

yield

to

estimate

B.

Intuitively,

the

magnetic

sensitivity

is

high

when

a

small

change

in

the

magnetic

field

intensity

produces

large

effects

on

the

singlet

yield.

Formally,

it

is

defined

as:(2)Λs(B)≡∂Φs(B)∂B=∫0∞pre(t)gs(B,t)dt,with

gs(B,t)≡∂fs(B,t)∂B

being

the

instantaneous

magnetic

sensitivity.

The

functional

form

of

fs(B,t)=Sρel(t)S

strongly

depends

on

the

specific

realization

of

the

radical

pair,

in

particular

on

the

number

of

the

surrounding

nuclear

spins.

Here,

we

consider

a

radical

pair

in

which

the

first

electron

spin

is

devoid

of

hyperfine

interactions,

while

the

second

electron

spin

interacts

isotropically

with

one

nucleus,

e.g.

nitrogen.

In

the

context

of

the

chemical

compass

(i.e.

when

the

task

is

determining

the

magnetic

field

direction

through

anisotropic

hyperfine

interactions),

an

analogous

configuration

(with

only

one

nucleus)

has

been

proposed

and

numerically

characterized

as

being

optimal:

Additional

nuclear

spins

would

perturb

the

intuitive

‘reference

and

probe’

picture.

The

Hamiltonian

then

simplifies

to

where

α

is

the

isotropic

hyperfine

coupling.

O O O O O O O O O O O O O O O O B I O O O O O O B I O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O B I O O O O B I O O O O O O O O B I O O B O O B I O O O O O O O O B I O O O O O O B I O O O O O O O O B I I O O O O O O O O O O B I I I I O O O O O O O O B I O O O O O O O O O O B I O O O B I O O O B I O O O O O O O B O O O O O B I O O O O O O O B I O O B I I O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B O O B I I

determining the magnetic field direction through anisotropic hyperfine interactions

improve the performance of chemical devices

analogous configuration
anisotropic hyperfine interactions
b
chemical compass
chemical devices
chemical magnetometer
chemical yield
control scheme
electron spin
hyperfine interactions
instantaneous magnetic sensitivity
isotropic hyperfine coupling
magnetic field
magnetic sensitivity
nitrogen
nuclear spins
realization of the radical pair
singlet products
singlet yield
α


We use open and close aperture Z-scan experiments, in analogy to the saturation absorption work discussed earlier in water [8], to respectively measure the β and n2 for a series of primary alcohols with the help of 1560nm femtosecond laser pulses, however, with the important inclusion of an optical-chopper. The vibrational combination states of the alcohols are coupled by the femtosecond laser pulses at 1560nm. These couplings result in the absorption of 1560nm and the excited molecules undergo relaxation through non-radiative processes, which gives rise to transient thermal effects. These transient thermal effects are related to the pure optical nonlinearity of the samples and can be measured as a change in their n2 values [14]. The transient thermal effects of individual pulses accumulate in case of high repetition-rate lasers to produce a cumulative thermal effect at longer timescales. We measure this cumulative thermal effect with the mode-mismatched two-color pump–probe experiment.

O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O B O O O O B I I I O O O O O O O O O B I I O O B O O O O B I I I I O O O O O B O O O O O B O O O O O O O O O B I I O B I I O O O O B I I O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O B I I O O O O O O B I I O O O O O O

1560nm femtosecond laser pulses
absorption
alcohols
cumulative thermal effect
femtosecond laser pulses at 1560nm
molecules
pure optical nonlinearity
transient thermal effects
vibrational combination states
water


Historically, the interest in accurate measurement of DNI started decades ago. Early studies (e.g., Linke, 1931; Linke and Ulmitz, 1940) identified the difficulty of separating the measurement of DNI from that of the diffuse irradiance in the immediate vicinity of the sun, hereafter referred to as circumsolar irradiance. Pastiels (1959) conducted a detailed study of the geometry of pyrheliometers, and how that geometry interacted with circumsolar radiance, using simplified representations of the latter. Various communications were then presented at a WMO Task Group meeting held in Belgium in 1966 (WMO, 1967) to improve the accuracy of pyrheliometric measurements, including estimates of the circumsolar enhancement. Ångström (1961) and Ångström and Rohde (1966) later contributed to the same topic, followed years later by Major (1973, 1980). The whole issue of instrument geometry vs. circumsolar irradiance was complex and confusing at the time because different makes and models of instruments had differing geometries. This was considerably simplified after WMO issued guidelines about the recommended geometry of pyrheliometers, which led to a relatively “standard” geometry used in all recent instruments. The experimental issues related to the measurement of DNI are discussed in Section 3.2.

O O O O O O O O O O O O O O O O O O O O O O O O B I I I I I I I I I I I I I I I I I O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O

separating the measurement of dni from that of the diffuse irradiance in the immediate vicinity of the sun


The aim of this paper is to investigate the influence of the particle shape on interacting particles flowing in a horizontal turbulent channel flow, for particles with a significant Stokes number. To achieve this, large eddy simulations (LES) of a horizontal turbulent channel flow laden with five different particle shapes, incorporating the drag, lift and toque model derived in Zastawny et al. (2012), are performed. The well-documented horizontal channel flow case described in Kussin and Sommerfeld (2002), who study spherical particles, is used as a reference case. The measurements in their work was done with phase Doppler anemometry (PDA), to measure the fluid and particle velocity simultaneously. The numerical framework applied in this paper has been previously validated for spherical particles in Mallouppas and van Wachem (2013). In that paper, it is shown that the comprehensive discrete element model (DEM) is more accurate in determining the behaviour of the particles in this horizontal gas–solid channel flow that the hard-sphere model. Moreover, this paper showed that the fluid mechanics are accurately modelled using the LES framework. In the current paper, this framework is extended to account for non-spherical particles.

O O O O O O O O O O O O B O O O B O O O B I I I O B O O O O O O O O B I I B O O B I I I O O O O B O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O B O O O O O O O O O O O O O O B I I B O O O B O B O O O B I O O O O O O O O O O B O O O O O O O O O O O O O O B I I I B O O O O B I I I I I I I I I I I O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O B


Complex Langevin (CL) dynamics [1,2] provides an approach to circumvent the sign problem in numerical simulations of lattice field theories with a complex Boltzmann weight, since it does not rely on importance sampling. In recent years a number of stimulating results has been obtained in the context of nonzero chemical potential, in both lower and four-dimensional field theories with a severe sign problem in the thermodynamic limit [3–8] (for two recent reviews, see e.g. Refs. [9,10]). However, as has been known since shortly after its inception, correct results are not guaranteed [11–16]. This calls for an improved understanding, relying on the combination of analytical and numerical insight. In the recent past, the important role played by the properties of the real and positive probability distribution in the complexified configuration space, which is effectively sampled during the Langevin process, has been clarified [17,18]. An important conclusion was that this distribution should be sufficiently localised in order for CL to yield valid results. Importantly, this insight has recently also led to promising results in nonabelian gauge theories, with the implementation of SL(N,C) gauge cooling [8,10].

B I B O O O O O O O O B I O B I I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B I I O O O O O O B I O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O B I I O O O O O O O O


Based on the theoretical analysis, the value of the measuring resistor, Rm, has no effect on the corrosion process and on the estimated value of noise resistance. In order to validate this conclusion, the experiment of Fig. 9 was performed. Specifically, a pair of nominally identical specimens was initially coupled by a 4.7kΩ resistor and their potential with respect to a saturated calomel electrode was recorded by using a NI-USB 6009 analog-to-digital converter. The electrochemical noise signal was recorded using in-house developed software, acquiring at 1023Hz segments of 1000 points at each iteration. Between iterations, the 1000 values acquired were averaged to obtain a single value of potential, subsequently saved to the file used for later processing. The final dataset comprised potential values spaced 1±0.05s in time. Under the assumption that the noise present above 1023Hz is negligible compared with the noise present below 0.5Hz, this procedure enables an accurate recording of the potential noise in the frequencies of interest, avoiding aliasing of frequencies between 0.5 and 1023Hz and minimizing the 50Hz interference from the mains supply.

O O O B I O B I I I I B O O O O O B I O O O O B I I I O O O B I I O O O O O O O O O B I I I I O O O O O O O O O O O O O O B I I O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I I O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I I I I I I I O O O O O O O O O O O O O O O O O

4.7kω resistor
in-house developed software
ni-usb 6009 analog-to-digital converter


Our procedure does not address the issue of how parameterizations can vary for different flow types. However, Edeling et al. [9] carried out separate calibrations for a set of 13 boundary-layer flows. They summarized this information across calibrations by computing Highest Posterior-Density (HPD) intervals, and subsequently represent the total solution uncertainty with a probability-box (p-box). This p-box represents both parameter variability across flows, and epistemic uncertainty within each calibration. A prediction of a new boundary-layer flow is made with uncertainty bars generated from this uncertainty information, and the resulting error estimate is shown to be consistent with measurement data. This approach is helpful, but it might be extended further by modelling proximity across flows through a distance that would relate to the flow characteristics in order to borrow strength across calibrations instead of splitting the calibrations and then merging the outcomes afterwards. This is a challenging but attractive venue for future research.

O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O B I I I I I I I O O O O O O O O O O O

boundary-layer flow
boundary-layer flows
highest posterior-density
modelling proximity across flows
p-box
probability-box


The related Volta potential (Ψ) is the potential difference between a position infinitely far away from the surface and a position just outside the surface, and is the measureable quantity characterising electrochemical behaviour of a metal [12,17]. The scanning Kelvin probe force microscopy (SKPFM) technique allows detection of local EWF (if the EWF of the tip is known), or Volta potential differences (ΔΨ) between an atomic force microscopy tip (usually Pt coated) and the metal surface [14,15,19]. The lateral resolution of SKPFM can be as high as 10’s of nm in ambient air, with a sensitivity up to 10–20meV [19]. Volta potential is a characteristic property of a metal surface and can be used to understand electrochemical processes [16] . It is sensitive to any kind of surface defects, chemical variations, and residual stress [13,17]. Volta potential differences in microstructure have been used to predict corrosion behaviour [10,15,18,20–22]. Regions with larger (ΔΨ) indicate increased surface reactivity [11,15,18], and even a correlation between Volta potential differences measured in nominally dry air and their free corrosion potential (Ecorr) pre-determined under immersed conditions has been reported [18].

O O B I B O O B I O O O O O O O O O O O O O O O O O O O B I O B I I I I O O B I I I I B O O B I I I O O O O O O O O O B I O B O O B I I I O B I O O B O O O O O O B O O O O O O O O O B I O O O O O O O B I O O O O O O B O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O B I I O O O O B O O O O O O O O O O B I O O O O B I O O B I I B O O O O O O O O

larger (δψ) indicate increased surface reactivity

volta potential differences in microstructure

ambient air
atomic force microscopy tip
detection of local ewf
dry air
ecorr
electrochemical behaviour of a metal
electrochemical processes
free corrosion potential
measureable quantity
metal
potential difference
predict corrosion behaviour
pt coated
scanning kelvin probe force microscopy
skpfm
volta potential
δψ
ψ


Although the free Kelvin wave problem is of considerable theoretical importance, problems with forcing and damping have greater practical importance. In nature, the forcing could be due to a wind stress at the free surface or an astronomical tidal potential, and the damping could be due to the turbulent stress of a bottom boundary layer. Regardless of the details, the forced response is composed of shallow-water waves, possibly including Kelvin waves, with the largest amplitudes in waves with a natural frequency ωf close to that of the forcing frequency ω; various examples of this sort are given in Chapters 9 and 10 of Gill [16]. When ω≈ωf, there is a large amplitude near-resonant response, the size of which is sensitive to the weak damping and |ω−ωf|. Thus, in numerical solutions of near-resonantly forced waves, we anticipate that errors in ωf (associated with the spatial discretisation) could lead to non-trivial errors in the forced response.

O O B I I I O O O O O O O B O B O O O O O O O B O O O O O B O O O O O O O B I I O O B O O O O O B I I I I I I O O O O O B I O O O O B O O B I O O O O O B O O B I B O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B I O O O B O O O O O B O O O B I O O O O O O O B I

forcing frequency
kelvin wave
near-resonantly forced waves
problems with forcing and damping
shallow-water waves
weak damping
wind stress at the free surface
|ω−ωf|


The remainder of our discussion proceeds as follows. In Section 2 we briefly describe the problem of cell tracking and introduce our approach to cell tracking, which may be regarded as fitting a mathematical model to experimental image data sets. We present the geometric evolution law model we seek to fit, which is a simplification of recently developed models in the literature that show good agreement with experiments [8,10–12,4,13,9]. We finish Section 2 by reformulating our model into the phase field framework, which appears more suitable for the problem in hand, and we formulate the cell tracking problem as a PDE constrained optimisation problem. In Section 3 we propose an algorithm for the resolution of the PDE constrained optimisation problem and we discuss some practical aspects related to the implementation. In particular we note that the theoretical and computational framework may be applied directly to multi-cell image data sets and raw image data sets (of sufficient quality) without segmentation. In Section 4 we present some numerical examples for the case of 2d single and multi-cell image data sets. Finally in Section 5 we present some conclusions of our study and discuss future extensions and applications of the work.

O O O O O O O O O O O O O O O B I I I O B I I I I I O O O O O O O B I O B I I I O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B I I O O O O O O O O O O O O O B I I O O B I I I O O O O O O B O O O O O B I I I O O O O O O O O O O O O O O O O B I I I O O O O O O B I I O O B I I O O O O B O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O

multi-cell image data sets
raw image data sets

algorithm
cell tracking problem
experimental image data sets
geometric evolution law model
image data sets
introduce our approach to cell tracking
mathematical model
our model
pde constrained optimisation problem
phase field framework
problem of cell tracking
segmentation
theoretical and computational framework


Half metallic ferromagnets (HMF) have attracted enormous interest due to their applications in spintronic devices [1]. Dilute magnetic semiconductors (DMSs) are considered to be the best materials to show half metallicity. These materials have two components, one being a semiconducting material with diamagnetic properties while the other is a magnetic dopant such as transition metal having un-paired d electrons [2]. The major advantage of these materials is utilization of electron's spin as information carrier since advanced functionalities in spintronic devices can be viable by the use of spin degree of freedom along with the charge of electrons [3]. The major issue regarding the applicability of these materials is to enhance the Curie temperature above room temperature. That's why the research interest shifted towards large band gap materials. A lot of work has been reported on DMSs with different II–VI and III–V semiconductors as host material such as, ZnS, CdS, GaN, ZnO, ZnSe, ZnTe, TiO2, SnO2 [4–12].

B I I B O O O O O O O O O B I O B I I B O O O O O O B I I I I O O O O O O O O B I O O O O O O O O B I O O B I O O O B O O O O O O O O O O B O O O O O O O O B I O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B I I I I I I O O O O O O O B I I I O O O O O O O O B O O B I I I O B I O O B B B B B B B B O

enhance the curie temperature above room temperature


There are some relevant studies on information dissemination in transportation systems using simulations. One category of studies look at how either local information (only about the neighbours) or global information (about the entire network) affects the global network performance. Our approach is different in the sense that we investigate the impact of information on the global network performance depending on the fraction of people that receive information. We analyse what is the effect of real time information dissemination and explain why this effect appears. Information is disseminated in real time and contains global details about how congested the roads are. This approach is important as it gives insights on the impact that massive use of real-time information can have on traffic. This can be useful for building more intelligent traffic control mechanisms where information is a steering tool.

O O O O O O B I I I I O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I I I I I I O O O O O O O O O O B I I I I I I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I I O O O O O O


Zirconium alloys are used as fuel cladding in pressurised and boiling water nuclear reactors. As such these materials are exposed to a large number of environmental factors that will promote degradation mechanisms such as oxidation. At high burn-ups, i.e. extended service life, oxidation and the associated hydrogen pick-up can be a limiting factor in terms of fuel efficiency and safety. The oxidation kinetics for many zirconium alloys are cyclical, demonstrating a series of approximately cubic kinetic curves separated by transitions [1–5]. These transitions are typified by a breakdown in the protective character of the oxide and are potentially linked to a number of mechanical issues. Understanding how these issues influence oxidation is a key to developing a full mechanistic understanding of the corrosion process.

B I O O O B O O O O O O B I O O O O O O O O O O O O O O O O B I O O B O O O O O O O B O O O O O O O O O O O O O B O O O O B O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O B I

understanding how these issues influence oxidation

corrosion process
degradation mechanisms
fuel
nuclear reactors
oxidation
oxide
zirconium alloys


Uranium carbide was traditionally used as fuel kernel for the US version of pebble bed reactors as opposed to the German version based on uranium dioxide. For the Generation IV nuclear systems, mixed uranium–plutonium carbides (U, Pu) C constitute the primary option for the gas fast reactors (GFR) and UCO is the first candidate for the very high temperature reactor (VHTR). In the former case the fuel high actinide density and thermal conductivity are exploited in view of high burnup performance. In the latter, UCO is a good compromise between oxides and carbides both in terms of thermal conductivity and fissile density. However, in the American VHTR design, the fuel is a 3:1 ratio of UO2:UC2 for one essential reason, well explained by Olander [2] in a recent publication. During burnup, pure UO2 fuel tends to oxidize to UO2+x. UO2+x reacts with the pyrocarbon coating layer according to the equilibrium:(1)UO2+x + xC → UO2 + xCO

B I O O O O B O O O O O O B I I O O O O O O O O B I O O B I I I O O B O O O O O O O O O B I I B O B O O O O O O B I I I B O O O O O B O B O O O O O O O O O O B O O O O B O O O O O B O B O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O B O B B O O O O O O O O O B I I O O O O O B O B O B

fuel kernel
mixed uranium–plutonium carbides
uc2
uo2 fuel
uo2+x
(u, pu) c

actinide
burnup
carbides
fuel
gas fast reactors
generation iv nuclear systems
gfr
oxides
pebble bed reactors
pyrocarbon coating layer
uco
uo2
uranium carbide
uranium dioxide
very high temperature reactor
vhtr
xc
xco


This study proposes a new framework of a numerical modelling of the gas exchange between air and water across their interface, and subsequent chemical reaction in water based on an extended two-compartment model. The major purpose of this study is to provide a fundamental concept for modelling physicochemical processes of the gas exchange, followed by the chemical reaction in water. Demonstrating fundamental data and knowledge on the important environmental transport phenomena, especially the effects of the Schmidt number and the chemical reaction rate on the gas exchange mechanisms across the interface have also been attempted. The gas exchange processes are separated into two physicochemical substeps, the first is the gas–liquid equilibrium between the two phases, and the second is the chemical reaction in the water phase. A first-order, irreversible chemical reaction of the gaseous material after its uptake into the water phase is assumed here to simplify interactions of the chemical reactions and turbulent transport phenomena in water. While a traditional two-compartment model assumes uniform concentration of a material in each compartment, the present two-compartment model uses a computational fluid dynamics (CFD) technique in the water compartment to evaluate temporal development of three-dimensional profiles of the velocity and concentration fields. A direct numerical simulation (DNS) approach is used to evaluate profiles of fluid velocities and concentrations in water, and several important turbulence statistics have been evaluated without using turbulent closures, and subgrid-scale models. We assume that a fluid flow in the water phase is a well-developed turbulent water layer of a low Reynolds number, and the Schmidt number is varied from 1 to 8 to observe the effects of the molecular diffusion of the gas in sub-interface water on the gas exchange rate at the interface. Six degrees of the nondimensional chemical reaction rate are used to find the effect of the chemical reaction rate on the gas exchange mechanisms. Extrapolations of the gas exchange rates and the related transport phenomena toward larger Schmidt number and the faster chemical reaction rate will also be examined to predict the gas exchange processes of the actual gases of Sc∼O(102) based on results from the present numerical experiments.

O O O O O B O O O O O O B O O B O B O O O O O B I O B O O O O O O O O O O O O O O O O B I O B I I O O B O O O O B I O B O O O O O O O O O B I O O B I I I I O O B I O O O B O O O O O O O O O O B O O O O O O O O O O O O B I O O O O O O O O O B I O O B I O O B I I O O B I O O O O O B I O O O O O O O O B I O O B I O B O O O O O O O O O O O O O O O O O O O O B I I B O O O B O O O O O O O O O O O O O O O B I I B O O O O B I I I I I I I I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B O O O O O O O O O O O O O O O O O O O O O O B I O O B O O B O O B O O O O O O O O O O B I O O O O O O O O O B I O O O B O O O O O B O O O O O B I O O O O O O O B I O O O O O O B I I I I O O O B O O O O O O O O B I


The Statistical Associating Fluid Theory (SAFT) is a well-developed perturbation theory used to describe quantitatively the volumetric properties of fluids. The reader is referred to several reviews on the topic which describe the various stages of its development and the multiple versions available [50–53]. The fundamental difference between the versions is in the underlying intermolecular potential employed to describe the unbounded constituent particles. Hard spheres, square well fluids, LJ fluids, argon, alkanes have all been employed as reference fluids in the different incarnations of SAFT. For the purpose of this work we will center on a particular version of the SAFT EoS, i.e. the SAFT-VR Mie recently proposed by Laffitte et al. [54] and expanded into a group contribution approach, SAFT-γ, by Papaioannou et al. [55]. This particular version of SAFT provides a closed form EoS that describes the macroscopical properties of the Mie potential [56], also known as the (m,n) potential; a generalized form of the LJ potential (albeit predating it by decades). The Mie potential has the form(1)ϕ(r)=Cεσrλr−σrλawhere C is an analytical function of the repulsive and attractive exponents, λa and λr, respectively, σ is a parameter that defines the length scale and is loosely related to the average diameter of a Mie bead; ɛ defines the energy scale and corresponds to the minimum potential energy between two isolated beads; expressed here as a ratio to the Boltzmann constant, kB. The Mie function, as written above, deceivingly suggests that four parameters are needed to characterize the behaviour of an isotropic molecule, however the exponents λa and λr are intimately related, and for fluid phase equilibria, one needs not consider them as independent parameters [57]. Accordingly, we choose herein to fix the attractive exponent to λa=6 which would be expected to be representative of the dispersion scaling of most simple fluids and refer from here on to the repulsive parameter as λ=λr. The potential simplifies to(2)ϕ(r)=λλ−6λ66/(λ−6)εσrλ−σr6

O B I I I B O O O B I O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I I B I O O B O B B B O O O O O O B O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B I I O O O O O O O O O O B O O B I I O O O O O O O B I O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O

(m,n) potential
lj fluids
square well fluids
saft eos
saft-γ
saft-vr mie
simple fluids
reference fluids

saft
alkanes
argon
bead
fluids
hard spheres
isotropic molecule
beads
unbounded constituent particles
statistical associating fluid theory
lj potential
closed form eos
fluid
group contribution approach
mie potential
intermolecular potential
perturbation theory