Computational Materials Science and Engineering: Model Development and Case Study

This study presents three tailored models for popular problems in energy storage and biological materials which demonstrate the application of computational materials science in material system development in these fields. The modeling methods can be extended for solving similar practical problems and applications. In the first application, the thermo-mechanical stress concentrated region in planar sodium sulfur (NaS) cells with large diameter and different container materials has been estimated as well as the shear and normal stresses in these regions have been quantified using finite-element analysis (FEA) computation technique. It is demonstrated that the primary failure mechanism in the planar NaS system design considered in the current work would be the interfacial fracture between the insulating header (IH) and the upper insert metal (IM1) due to the normal stress in cell height direction, and the necessary treatments, including better material selection or improved bonding technology between IH and IM1, must be involved to avoid the fractures of constituent components in the joint area. In the second application, a full atomistic molecular dynamics (MD) computation approach has been employed to quantify the Flory-Huggins parameters between poly(lactic acid) (PLA), poly(glycolic acid) (PGA), and tetracycline-HCl (TC-HCl) drugs, which can elucidate the thermodynamic stability and the interaction between drugs and poly(lactic/glycolic acid) (PLGA) carriers polymers. Thermodynamic analysis regarding the miscibility and the stability of PLA, PGA, TC-HCl phases are then conducted in line with the experimental fabrication of polymer-drug films of two different copolymer ratio products, i.e., 50/50 (PLA/PGA ratio) and 75/25 PLGA samples. Meso-scale computations using phase-field method (PFM) are also conducted to predict the structural evolution of PLGA/TC-HCl systems using the calculated Flory-Huggins parameters. The results show that the surface morphology of PLGA/TC-HCl film can be highly dependent upon the thermodynamic interaction between the polymer and drug phases. In the third application, full atomistic MD simulations have been performed on tetra-sulfides and undoped conjugated polymers pernigraniline base polyaniline (PNB), leucoemeraldine base polyaniline (LEB), poly(3,4-ethylenedioxythiophene) (PEDOT) and polypyrrole (PPY) to investigate the binding effectiveness between polysulfides and polymer binders. The weight ratio between sulfur and binder in lithium{sulfur cells is considered in 1:1 v/v mixture of dioxolane/dimethoxyethane. The simulations reveal that the end group 2 of PNB can effectively bind a lithium tetra-sulfide (i.e. Li2S4) cluster or 2 out of 43 Li2S4 molecules with the effect of solvent. However, repeat units of PNB, LEB, PEDOT and PPY seem ineffective in binding solvated Li2S4 through non-bonded interaction, especially when the concentration of tetra-sulfide/binder in a local domain of the cathode is low. Therefore, polymers with this specific functional group (i.e. the end group 2 of PNB) are suggested to be further studied as potential effective binders to inhibit the shuttle effect of solvated lithium polysulfides. Also, since the solvent has considerable impact on the binding effectiveness between tetra-sulfides and binder, it is suggested to take advantage of the explicit solvation models, such as those built in this work, to predict how other influencing factors affect binding between polysulfides and polymers

Behavioral asset pricing in Chinese stock markets

This thesis addresses asset pricing in Chinese A-share stock markets using a dataset consisting of all shares listed in Shanghai and Shenzhen stock exchanges from January 1997 to December 2007. The empirical work is carried out based on two theoretical foundations: the efficient market hypothesis and behavioural finance. It examines and compares the validity of two traditional asset pricing models and two behavioural asset pricing models. The investigation is initially performed within a traditional asset pricing framework. The three-factor Fama-French model is estimated and then augmented by additional macroeconomic and bond market variables. The results suggest that these traditional asset pricing models fail to explain fully the time-variation of stock returns in Chinese stock markets, leaving non-normally distributed and heteroskedastic residuals, calling for further explanatory variables and suggesting the existence of a structure break. Indeed, the macroeconomic and bond market factors provide little help to the asset pricing model. Using the Fama-French model as the benchmark, further research is done by investigating investor sentiment as the third dimension beside returns and risks. Investor sentiment helps explain the mis-pricing component of returns in the Fama-French model and the time-variation in the factors themselves. Incorporating investor sentiment into the asset pricing model improves the model performance, lessening the importance of the Fama-French factors, and suggesting that in China, sentiment affects both the way in which investors judge risks as well as portfolio returns directly. The sentiment effect on asset pricing is also examined under a nonlinear Markov-switching framework. The stochastic regime-dependent model reveals that stock returns in China are driven by fundamental factors in bear and low volatility markets but are prone to sentiment and become uncoupled from fundamental risks in bull and high volatility markets

Tuning for robust and optimal dynamic positioning control in BlueROV2

A tuning approach for the robust and optimal dynamic positioning control of BlueROV2 subjected to currents with varying speeds and headings is presented. A 2D planar dynamic model of BlueROV2 is developed in Matlab/Simulink and used for the study. The surge, sway and yaw motions are controlled by individual PID controllers. An extensive sensitivity study is carried out on a total of nine cases with different current speeds, current headings, and measurement noise levels. The results show that tuning a model solely using step responses from a linearized model might not produce optimal results. Further it is important to verify the system responses in time domain after tuning. Finally, it is observed that re-tuning the controllers for each simulation case may lead to better performance. However, it is also shown that the base case controller gains are sufficiently robust and lead to good performances for the other simulation cases.publishedVersio

Using the Kriging Response Surface Method for the Estimation of Failure Values of Carbon-Fibre-Epoxy Subsea Composite Flowlines under the Influence of Stochastic Processes

This paper investigates the use of the Kriging response surface method to estimate failure values in carbon-fibre-epoxy composite flow-lines under the influence of stochastic processes. A case study of a 125 mm flow-line was investigated. The maximum stress, Tsai-Wu and Hashin failure criteria was used to assess the burst design under combined loading with axial forces, torsion and bending moments. An extensive set of measured values was generated using Monte Carlo simulation and used as the base case population to which the results from the response surfaces was compared. The response surfaces were evaluated in detail in their ability to reproduce the statistical moments, probability and cumulative distributions and failure values at low probabilities of failure. In addition, the optimisation of the response surface calculation was investigated in terms of reducing the number of input parameters and size of the response surface. Finally, a decision chart that can be used to build a response surface to calculate failures in a carbon fibre-epoxy-composite (CFEC) flow-line was proposed based on the findings obtained. The results show that the response surface method is suitable and can calculate failure values close to that calculated using a large set of measured values. The results from this paper provide an analytical framework for identifying the principal design parameters, response surface generation, and failure prediction for CFEC flow-lines.publishedVersio

Novel deconvolution method for extreme FPSO vessel hawser tensions during offloading operations

Robust prediction of extreme hawser tensions during Floating Production Storage and Offloading (FPSO) operations is an important safety and reliability concern. Excessive hawser tension may occur during certain environmental conditions, posing an operational risk. The novel deconvolution method is proposed in this paper to provide an accurate extreme value prediction. The predicted return level values produced by the new deconvolution approach are compared with those obtained by the Naess-Gaidai method. On the basis of the suggested approach's overall performance, it is concluded that the innovative deconvolution method may give a more robust and accurate forecast of excessive hawser stress. The stated method may be used effectively at the stage of vessel design while determining appropriate vessel characteristics to reduce possible FPSO hawser stress.publishedVersio

Is it Too Optimistic to Assume Light Touch Interventions can Improve Educational Workers’ Wellbeing? Insights from a Field Randomized Control Trial in Canada

Educator wellbeing has broad implications for students and schools. Current approaches to address this problem are generally resource-intensive. This trial used novel nudges to increase wellbeing and decrease burnout among educators and other school-based faculty. We designed a light touch intervention where T1 received evidence-based wellbeing weekly text messages and T2 received weekly messages plus leadership endorsement emails. We evaluated this intervention in a large-scale three-arm RCT with participants (n=1,155) from K-12 schools in Manitoba, Alberta, and British Columbia. When compared to the control group, we saw no significant difference between the control group and T1 and T2 groups on burnout or wellbeing. The failure of these evidence-based text messages in increasing educators’ wellbeing and reducing their burnout highlights both the difficulty of addressing this problem and the importance of learning lessons from trials with null results to contribute to our knowledge base of improving educators’ wellbeing

Gaidai-Xing reliability method validation for 10-MW floating wind turbines

In contrast to well-known bivariate statistical approach, which is known to properly forecast extreme response levels for two-dimensional systems, the research validates innovative structural reliability method, which is particularly appropriate for multi-dimensional structural responses. The disadvantage of dealing with large system dimensionality and cross-correlation across multiple dimensions is not a benefit of traditional dependability approaches that deal with time series. Since offshore constructions are built to handle extremely high wind and wave loads, understanding these severe stresses is essential, e.g. wind turbines should be built and operated with the least amount of inconvenience. In the first scenario, the blade root flapwise bending moment is examined, whereas in the second, the tower bottom fore-aft bending moment is examined. The FAST simulation program was utilized to generate the empirical bending moments for this investigation with the load instances activated at under-rated, rated, and above-rated speeds. The novel reliability approach, in contrast to conventional reliability methods, does not call for the study of a multi-dimensional reliability function in the case of numerical simulation. As demonstrated in this work, it is now possible to assess multi-degree-of-freedom nonlinear system failure probability, in the case when only limited system measurements are available.publishedVersio

Improving extreme offshore wind speed prediction by using deconvolution

This study proposes an innovative method for predicting extreme values in offshore engineering. This includes and is not limited to environmental loads due to offshore wind and waves and related structural reliability issues. Traditional extreme value predictions are frequently constructed using certain statistical distribution functional classes. The proposed method differs from this as it does not assume any extrapolation-specific functional class and is based on the data set's intrinsic qualities. To demonstrate the method's effectiveness, two wind speed data sets were analysed and the forecast accuracy of the suggested technique has been compared to the Naess-Gaidai extrapolation method. The original batch of data consisted of simulated wind speeds. The second data related to wind speed was recorded at an offshore Norwegian meteorological station.publishedVersio

Programmable base editing of zebrafish genome using a modified CRISPR-Cas9 system.

Precise genetic modifications in model animals are essential for biomedical research. Here, we report a programmable "base editing" system to induce precise base conversion with high efficiency in zebrafish. Using cytidine deaminase fused to Cas9 nickase, up to 28% of site-specific single-base mutations are achieved in multiple gene loci. In addition, an engineered Cas9-VQR variant with 5'-NGA PAM specificities is used to induce base conversion in zebrafish. This shows that Cas9 variants can be used to expand the utility of this technology. Collectively, the targeted base editing system represents a strategy for precise and effective genome editing in zebrafish.The use of base editing enables precise genetic modifications in model animals. Here the authors show high efficient single-base editing in zebrafish using modified Cas9 and its VQR variant with an altered PAM specificity

Offshore tethered platform springing response statistics

This paper demonstrates the validity of the Naess–Gadai method for extrapolating extreme value statistics of second-order Volterra series processes through application on a representative model of a deep water small size tension leg platform (TLP), with specific focus on wave sum frequency effects affecting restrained modes: heave, roll and pitch. The wave loading was estimated from a second order diffraction code WAMIT, and the stochastic TLP structural response in a random sea state was calculated exactly using Volterra series representation of the TLP corner vertical displacement, chosen as a response process. Although the wave loading was assumed to be a second order (non-linear) process, the dynamic system was modelled as a linear damped mass-spring system. Next, the mean up-crossing rate based extrapolation method (Naess–Gaidai method) was applied to calculate response levels at low probability levels. Since exact solution was available via Volterra series representation, both predictions were compared in this study, namely the exact Volterra and the approximate one. The latter gave a consistent way to estimate efficiency and accuracy of Naess–Gaidai extrapolation method. Therefore the main goal of this study was to validate Naess–Gaidai extrapolation method by available analytical-based exact solution. Moreover, this paper highlights limitations of mean up-crossing rate based extrapolation methods for the case of narrow band effects, such as clustering, typically included in the springing type of response.publishedVersio