Local Energy Decay in Even Dimensions for the Wave Equation with a Time-Periodic Non-Trapping Metric and Applications to Strichartz Estimates

2000 Mathematics Subject Classification: 35B40, 35L15.

Green's function for paraxial equation

The theory and experimental applications of optical Airy beams are in active development recently. The Airy beams are characterised by very special properties: they are non-diffractive and propagate along parabolic trajectories. Among the striking applications of the optical Airy beams are optical micro-manipulation implemented as the transport of small particles along the parabolic trajectory, Airy-Bessel linear light bullets, electron acceleration by the Airy beams, plasmonic energy routing. The detailed analysis of the mathematical aspects as well as physical interpretation of the electromagnetic Airy beams was done by considering the wave as a function of spatial coordinates only, related by the parabolic dependence between the transverse and the longitudinal coordinates. Their time dependence is assumed to be harmonic. Only a few papers consider a more general temporal dependence where such a relationship exists between the temporal and the spatial variables. This relationship is derived mostly by applying the Fourier transform to the expressions obtained for the harmonic time dependence or by a Fourier synthesis using the specific modulated spectrum near some central frequency. Spatial-temporal Airy pulses in the form of contour integrals is analysed near the caustic and the numerical solution of the nonlinear paraxial equation in time domain shows soliton shedding from the Airy pulse in Kerr medium. In this paper the explicitly time dependent solutions of the electromagnetic problem in the form of time-spatial pulses are derived in paraxial approximation through the Green's function for the paraxial equation. It is shown that a Gaussian and an Airy pulse can be obtained by applying the Green's function to a proper source current. We emphasize that the processes in time domain are directional, which leads to unexpected conclusions especially for the paraxial approximation.

Corporate cash-pool valuation in a multi-firm context: a closed formula

Following our earlier paper on the subject, we present a general closed formula to value the interest savings due to a multi-firm cash-pool system. Assuming normal distribution of the accounts the total savings can be expressed as the product of three independent factors representing the interest spread, the number and the correlation of the firms, and the time-dependent distribution of the cash accounts. We derive analytic results for two special processes one characterizing the initial build-up period and the other describing the mature period. The value gained in the stationary system can be thought of as the interest, paid at the net interest spread rate on the standard deviation of the account. We show that pooling has substantial value already in the transient period. In order to increase the practical relevance of our analysis we discuss possible extensions of our model and we show how real option pricing technics can be applied here.

Temporal analysis of land use and transportation investments with geographic information system

Land use and transportation interaction has been a research topic for several decades. There have been efforts to identify impacts of transportation on land use from several different perspectives. One focus has been the role of transportation improvements in encouraging new land developments or relocation of activities due to improved accessibility. The impacts studied have included property values and increased development. Another focus has been on the changes in travel behavior due to better mobility and accessibility. Most studies to date have been conducted in metropolitan level, thus unable to account for interactions spatially and temporally at smaller geographic scales. ^ In this study, a framework for studying the temporal interactions between transportation and land use was proposed and applied to three selected corridor areas in Miami-Dade County, Florida. The framework consists of two parts: one is developing of temporal data and the other is applying time series analysis to this temporal data to identify their dynamic interactions. Temporal GIS databases were constructed and used to compile building permit data and transportation improvement projects. Two types of time series analysis approaches were utilized: univariate models and multivariate models. Time series analysis is designed to describe the dynamic consequences of time series by developing models and forecasting the future of the system based on historical trends. Model estimation results from the selected corridors were then compared. ^ It was found that the time series models predicted residential development better than commercial development. It was also found that results from three study corridors varied in terms of the magnitude of impacts, length of lags, significance of the variables, and the model structure. Long-run effect or cumulated impact of transportation improvement on land developments was also measured with time series techniques. The study offered evidence that congestion negatively impacted development and transportation investments encouraged land development. ^

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

In vivo characterization of epileptic tissue with optical spectroscopy

For children with intractable seizures, surgical removal of epileptic foci, if identifiable and feasible, can be an effective way to reduce or eliminate seizures. The success of this type of surgery strongly hinges upon the ability to identify and demarcate those epileptic foci. The ultimate goal of this research project is to develop an effective technology for detection of unique in vivo pathophysiological characteristics of epileptic cortex and, subsequently, to use this technology to guide epilepsy surgery intraoperatively. In this PhD dissertation the feasibility of using optical spectroscopy to identify uniquein vivo pathophysiological characteristics of epileptic cortex was evaluated and proven using the data collected from children undergoing epilepsy surgery. ^ In this first in vivo human study, static diffuse reflectance and fluorescence spectra were measured from the epileptic cortex, defined by intraoperative ECoG, and its surrounding tissue from pediatric patients undergoing epilepsy surgery. When feasible, biopsy samples were taken from the investigated sites for the subsequent histological analysis. Using the histological data as the gold standard, spectral data was analyzed with statistical tools. The results of the analysis show that static diffuse reflectance spectroscopy and its combination with static fluorescence spectroscopy can be used to effectively differentiate between epileptic cortex with histopathological abnormalities and normal cortex in vivo with a high degree of accuracy. ^ To maximize the efficiency of optical spectroscopy in detecting and localizing epileptic cortex intraoperatively, the static system was upgraded to investigate histopathological abnormalities deep within the epileptic cortex, as well as to detect unique temporal pathophysiological characteristics of epileptic cortex. Detection of deep abnormalities within the epileptic cortex prompted a redesign of the fiberoptic probe. A mechanical probe holder was also designed and constructed to maintain the probe contact pressure and contact point during the time dependent measurements. The dynamic diffuse reflectance spectroscopy system was used to characterize in vivo pediatric epileptic cortex. The results of the study show that some unique wavelength dependent temporal characteristics (e.g., multiple horizontal bands in the correlation coefficient map γ(λref = 800 nm, λcomp ,t)) can be found in the time dependent recordings of diffuse reflectance spectra from epileptic cortex defined by ECoG.^

A retrospective-longitudinal examination of the relationship between apportionment of seat time in community-college algebra courses and student academic performance

During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

Determinants of Waterpipe and Cigarette Smoking Progression among a School Based Sample of Adolescents in Irbid, Jordan: A Three-Year Longitudinal Study (2008-2011)

The prevalence of waterpipe smoking exceeds that of cigarettes among adolescents in the Middle East where waterpipe is believed as less harmful, less addictive and can be a safer alternative to cigarettes. This dissertation tested the gateway hypothesis that waterpipe can provide a bridge to initiate cigarette smoking, identified the predictors of cigarette smoking progression, and identified predictors of waterpipe smoking progression among a school-based sample of Jordanian adolescents (mean age ± SD) (12.7 ±0.61) years at baseline. Data for this research have been drawn from Irbid Longitudinal Study of smoking behavior, Jordan (2008-2011). The grouped-time survival analysis showed that waterpipe smoking was associated with a higher risk of cigarette smoking initiation compared to never smokers (P < 0.001) and this association was dose dependent (P < 0.001). Predictors of cigarette smoking progression were peer smoking and attending public schools for boys, siblings’ smoking for girls, and the urge to smoke for both genders. Predictors of waterpipe smoking progression were enrollment in public schools, frequent physical activity, and low refusal self-efficacy for boys, ever smoking cigarettes, friends’ and siblings’ waterpipe smoking for girls. Awareness of harms of waterpipe among boys and seeing warning labels on the tobacco packs by girls were protective against waterpipe smoking progression. In Conclusion, waterpipe can serve as a gateway to cigarette smoking initiation among adolescents. Waterpipe and cigarette smoking progressions among initiators were solely family-related among girls, and mainly peer-related among boys. The unique gender differences for both cigarette and waterpipe smoking among Jordanian adolescents in Irbid call for cultural and gender-specific smoking prevention interventions to prevent the progression of smoking among initiators.

The effect of weathering processes on the vertical turbulent dispersion characteristics of crude oil spilled on the sea

Since the Exxon Valdez accident in 1987, renewed interest has come forth to better understand and predict the fate and transport of crude oil lost to marine environments. The short-term fate of an Arabian Crude oil was simulated in laboratory experiments using artificial seawater. The time-dependent changes in the rheological and chemical properties of the oil under the influence of natural weathering processes were characterized, including dispersion behavior of the oil under simulated ocean turbulence. Methodology included monitoring the changes in the chemical composition of the oil by Gas Chromatography/Mass Spectrometry (GCMS), toxicity evaluations for the oil dispersions by Microtox analysis, and quantification of dispersed soluble aromatics by fluorescence spectrometry. Results for this oil show a sharp initial increase in viscosity, due to evaporative losses of lower molecular weight hydrocarbons, with the formation of stable water-in-oil emulsions occurring within one week. Toxicity evaluations indicate a decreased EC-50 value (higher toxicity) occurring after the oil has weathered eight hours, with maximum toxicity being observed after weathering seven days. Particle charge distributions, determined by electrophoretic techniques using a Coulter DELSA 440, reveal that an unstable oil dispersion exists within the size range of 1.5 to 2.5 um, with recombination processes being observed between sequential laser runs of a single sample.

Pitting and porous layer formation on n-InP anodes

Surface pitting occurs when InP electrodes are anodized in KOH electrolytes at concentrations in the range 2 - 5 mol dm-3. The process has been investigated using atomic force microscopy (AFM) and the results correlated with cross-sectional transmission electron microscopy (TEM) and electroanalytical measurements. AFM measurements show that pitting of the surface occurs and the density of pits is observed to increase with time under both potentiodynamic and potentiostatic conditions. This indicates a progressive pit nucleation process and implies that the development of porous domains beneath the surface is also progressive in nature. Evidence for this is seen in plan view TEM images in which individual domains are seen to be at different stages of development. Analysis of the cyclic voltammograms of InP electrodes in 5 mol dm-3 KOH indicates that, above a critical potential for pit formation, the anodic current is predominantly time dependent and there is little differential dependence of the current on potential. Thus, pores continue to grow with time when the potential is high enough to maintain depletion layer breakdown conditions.

Mechanistic Models of Anti-HIV Microbicide Drug Delivery

A new modality for preventing HIV transmission is emerging in the form of topical microbicides. Some clinical trials have shown some promising results of these methods of protection while other trials have failed to show efficacy. Due to the relatively novel nature of microbicide drug transport, a rigorous, deterministic analysis of that transport can help improve the design of microbicide vehicles and understand results from clinical trials. This type of analysis can aid microbicide product design by helping understand and organize the determinants of drug transport and the potential efficacies of candidate microbicide products.

Microbicide drug transport is modeled as a diffusion process with convection and reaction effects in appropriate compartments. This is applied here to vaginal gels and rings and a rectal enema, all delivering the microbicide drug Tenofovir. Although the focus here is on Tenofovir, the methods established in this dissertation can readily be adapted to other drugs, given knowledge of their physical and chemical properties, such as the diffusion coefficient, partition coefficient, and reaction kinetics. Other dosage forms such as tablets and fiber meshes can also be modeled using the perspective and methods developed here.

The analyses here include convective details of intravaginal flows by both ambient fluid and spreading gels with different rheological properties and applied volumes. These are input to the overall conservation equations for drug mass transport in different compartments. The results are Tenofovir concentration distributions in time and space for a variety of microbicide products and conditions. The Tenofovir concentrations in the vaginal and rectal mucosal stroma are converted, via a coupled reaction equation, to concentrations of Tenofovir diphosphate, which is the active form of the drug that functions as a reverse transcriptase inhibitor against HIV. Key model outputs are related to concentrations measured in experimental pharmacokinetic (PK) studies, e.g. concentrations in biopsies and blood. A new measure of microbicide prophylactic functionality, the Percent Protected, is calculated. This is the time dependent volume of the entire stroma (and thus fraction of host cells therein) in which Tenofovir diphosphate concentrations equal or exceed a target prophylactic value, e.g. an EC50.

Results show the prophylactic potentials of the studied microbicide vehicles against HIV infections. Key design parameters for each are addressed in application of the models. For a vaginal gel, fast spreading at small volume is more effective than slower spreading at high volume. Vaginal rings are shown to be most effective if inserted and retained as close to the fornix as possible. Because of the long half-life of Tenofovir diphosphate, temporary removal of the vaginal ring (after achieving steady state) for up to 24h does not appreciably diminish Percent Protected. However, full steady state (for the entire stromal volume) is not achieved until several days after ring insertion. Delivery of Tenofovir to the rectal mucosa by an enema is dominated by surface area of coated mucosa and whether the interiors of rectal crypts are filled with the enema fluid. For the enema 100% Percent Protected is achieved much more rapidly than for vaginal products, primarily because of the much thinner epithelial layer of the mucosa. For example, 100% Percent Protected can be achieved with a one minute enema application, and 15 minute wait time.

Results of these models have good agreement with experimental pharmacokinetic data, in animals and clinical trials. They also improve upon traditional, empirical PK modeling, and this is illustrated here. Our deterministic approach can inform design of sampling in clinical trials by indicating time periods during which significant changes in drug concentrations occur in different compartments. More fundamentally, the work here helps delineate the determinants of microbicide drug delivery. This information can be the key to improved, rational design of microbicide products and their dosage regimens.

Experimental analysis of novel telecom source materials and devices

Incumbent telecommunication lasers emitting at 1.5 µm are fabricated on InP substrates and consist of multiple strained quantum well layers of the ternary alloy InGaAs, with barriers of InGaAsP or InGaAlAs. These lasers have been seen to exhibit very strong temperature dependence of the threshold current. This strong temperature dependence leads to a situation where external cooling equipment is required to stabilise the optical output power of these lasers. This results in a significant increase in the energy bill associated with telecommunications, as well as a large increase in equipment budgets. If the exponential growth trend of end user bandwidth demand associated with the internet continues, these inefficient lasers could see the telecommunications industry become the dominant consumer of world energy. For this reason there is strong interest in developing new, much more efficient telecommunication lasers. One avenue being investigated is the development of quantum dot lasers on InP. The confinement experienced in these low dimensional structures leads to a strong perturbation of the density of states at the band edge, and has been predicted to result in reduced temperature dependence of the threshold current in these devices. The growth of these structures is difficult due to the large lattice mismatch between InP and InAs; however, recently quantum dots elongated in one dimension, known as quantum dashes, have been demonstrated. Chapter 4 of this thesis provides an experimental analysis of one of these quantum dash lasers emitting at 1.5 µm along with a numerical investigation of threshold dynamics present in this device. Another avenue being explored to increase the efficiency of telecommunications lasers is bandstructure engineering of GaAs-based materials to emit at 1.5 µm. The cause of the strong temperature sensitivity in InP-based quantum well structures has been shown to be CHSH Auger recombination. Calculations have shown and experiments have verified that the addition of bismuth to GaAs strongly reduces the bandgap and increases the spin orbit splitting energy of the alloy GaAs1−xBix. This leads to a bandstructure condition at x = 10 % where not only is 1.5 µm emission achieved on GaAs-based material, but also the bandstructure of the material can naturally suppress the costly CHSH Auger recombination which plagues InP-based quantum-well-based material. It has been predicted that telecommunications lasers based on this material system should operate in the absence of external cooling equipment and offer electrical and optical benefits over the incumbent lasers. Chapters 5, 6, and 7 provide a first analysis of several aspects of this material system relevant to the development of high bismuth content telecommunication lasers.

Predicting Forest Responses to Changing Environmental Conditions

Forests change with changes in their environment based on the physiological responses of individual trees. These short-term reactions have cumulative impacts on long-term demographic performance. For a tree in a forest community, success depends on biomass growth to capture above- and belowground resources and reproductive output to establish future generations. Here we examine aspects of how forests respond to changes in moisture and light availability and how these responses are related to tree demography and physiology.

First we address the long-term pattern of tree decline before death and its connection with drought. Increasing drought stress and chronic morbidity could have pervasive impacts on forest composition in many regions. We use long-term, whole-stand inventory data from southeastern U.S. forests to show that trees exposed to drought experience multiyear declines in growth prior to mortality. Following a severe, multiyear drought, 72% of trees that did not recover their pre-drought growth rates died within 10 years. This pattern was mediated by local moisture availability. As an index of morbidity prior to death, we calculated the difference in cumulative growth after drought relative to surviving conspecifics. The strength of drought-induced morbidity varied among species and was correlated with species drought tolerance.

Next, we investigate differences among tree species in reproductive output relative to biomass growth with changes in light availability. Previous studies reach conflicting conclusions about the constraints on reproductive allocation relative to growth and how they vary through time, across species, and between environments. We test the hypothesis that canopy exposure to light, a critical resource, limits reproductive allocation by comparing long-term relationships between reproduction and growth for trees from 21 species in forests throughout the southeastern U.S. We found that species had divergent responses to light availability, with shade-intolerant species experiencing an alleviation of trade-offs between growth and reproduction at high light. Shade-tolerant species showed no changes in reproductive output across light environments.

Given that the above patterns depend on the maintenance of transpiration, we next developed an approach for predicting whole-tree water use from sap flux observations. Accurately scaling these observations to tree- or stand-levels requires accounting for variation in sap flux between wood types and with depth into the tree. We compared different models with sap flux data to test the hypotheses that radial sap flux profiles differ by wood type and tree size. We show that radial variation in sap flux is dependent on wood type but independent of tree size for a range of temperate trees. The best-fitting model predicted out-of-sample sap flux observations and independent estimates of sapwood area with small errors, suggesting robustness in new settings. We outline a method for predicting whole-tree water use with this model and include computer code for simple implementation in other studies.

Finally, we estimated tree water balances during drought with a statistical time-series analysis. Moisture limitation in forest stands comes predominantly from water use by the trees themselves, a drought-stand feedback. We show that drought impacts on tree fitness and forest composition can be predicted by tracking the moisture reservoir available to each tree in a mass balance. We apply this model to multiple seasonal droughts in a temperate forest with measurements of tree water use to demonstrate how species and size differences modulate moisture availability across landscapes. As trees deplete their soil moisture reservoir during droughts, a transpiration deficit develops, leading to reduced biomass growth and reproductive output.

This dissertation draws connections between the physiological condition of individual trees and their behavior in crowded, diverse, and continually-changing forest stands. The analyses take advantage of growing data sets on both the physiology and demography of trees as well as novel statistical techniques that allow us to link these observations to realistic quantitative models. The results can be used to scale up tree measurements to entire stands and address questions about the future composition of forests and the land’s balance of water and carbon.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Time-dependency of Rocks and Implications Associated with Tunnelling

The formulation of a geotechnical model and the associated prediction of the mechanical behaviour is a challenge engineers need to overcome in order to optimize tunnel design and meet project requirements. Special challenges arise in cases where rocks and rockmasses are susceptible to time-effects and time-dependent processes govern. Progressive rockmass deformation and instability, time-dependent overloading of support and delayed failures are commonly the result of time-dependent phenomena. The research work presented in this thesis serves as an attempt to provide more insight into the time-dependent behaviour of rocks. Emphasis is given on investigating and analyzing creep deformation and time-dependent stress relaxation phenomenon at the laboratory scale and in-depth analyses are presented. This thesis further develops the understanding of these phenomena and practical yet scientific tools for estimating and predicting the long-term strength and the maximum stress relaxation of rock materials are proposed. The identification of the existence of three distinct behavioural stages during stress relaxation is presented and discussed. The main observations associated with time-dependent behaviour are employed in numerical analyses and applied at the tunnel scale. A new approach for simulating and capturing the time-dependent behaviour coupled with the tunnel advancement effect is also developed and analyzed. Guidance is provided to increase the understanding of the support-rockmass interaction and the main implications and significance of time-dependent behaviour associated with rock tunnelling are discussed. The work presented in this thesis advances the scientific understanding of time-dependent rock and rockmass behaviour, increases the awareness of how such phenomena are captured numerically, and lays out a framework for dealing with such deformations when predicting tunnel deformations. Practical aspects of this thesis are also presented, which will increase their usage in the associated industries and close the gap between the scientific and industry communities.