PREDICTIVE MATURITY OF INEXACT AND UNCERTAIN STRONGLY COUPLED NUMERICAL MODELS

The Computer simulations are commonly used to predict the response of complex systems in many branches of engineering and science. These computer simulations involve the theoretical foundation, numerical modeling and supporting experimental data, all of which contain their associated errors. Furthermore, real-world problems are generally complex in nature, in which each phenomenon is described by the respective constituent models representing different physics and/or scales. The interactions between such constituents are typically complex in nature, such that the outputs of a particular constituent may be the inputs for one or more constituents. Thus, the natural question then arises concerning the validity of these complex computer model predictions, especially in cases where these models are executed in support of high-consequence decision making. The overall accuracy and precision of the coupled system is then determined by the accuracy and precision of both the constituents and the coupling interface. Each constituent model has its own uncertainty and bias error. Furthermore, the coupling interface also brings in a similar spectrum of uncertainties and bias errors due to unavoidably inexact and incomplete data transfer between the constituents. This dissertation contributes to the established knowledge of partitioned analysis by investigating the numerical uncertainties, validation and uncertainty quantification of strongly coupled inexact and uncertain models. The importance of this study lies in the urgent need for gaining a better understanding of the simulations of coupled systems, such as those in multi-scale and multi-physics applications, and to identify the limitations due to uncertainty and bias errors in these models

A GROUND-MOTION PREDICTION MODEL FOR SMALL-TO-MODERATE INDUCED EARTHQUAKES FOR CENTRAL AND EASTERN UNITED STATES AND GROUND MOTION MODEL RANKING

A GROUND-MOTION PREDICTION MODEL FOR SMALL-TO-MODERATE INDUCED EARTHQUAKES FOR CENTRAL AND EASTERN UNITED STATES AND GROUND MOTION MODEL RANKIN

The Role of Lymph Node Density in Predicting Survival Post-Cystectomy in Patients with Bladder Cancer; A Single-Center Retrospective Analysis

Background:  Lymph Node involvement in patients with bladder cancer directly affects their prognosis after cystectomy. With the advent of various extensions for lymphadenectomy during radical cystectomy, Lymph Node Density (LND) has been introduced as a stable measure to quantify the extent of LN involvement. This study evaluates the prognostic value of LND on the survival of these patients in our center. Methods: Our historical cohort reviewed the clinical records of 165 patients who underwent cystectomy at Modarres Hospital in Tehran, Iran during 2012-2018. The presence of positive LNs, the total number of positive LN, and LN density were evaluated for their effect on Overall survival (OS) and recurrence-free survival (RFS) at 3- and 5-years post-surgery. In addition, we assessed the impact of age, gender, type of diversion, P stage, lymphovascular invasion (LVI), location of involved LNs, ureteral involvement, positive surgical margin, and the presence of carcinoma in situ on patients’ survival. Results: According to ROC curve analysis, an LND cut-off point of 10.82 was calculated to predict patients’ survival (AUC:0.70, 95%CI: 0.496-0.691). An LND >10.82 significantly increased the risk of cancer-related death. Among all study variables, LND had the most prominent effect on OS (HR:2.49, 95% CI:1.3-4.4, P=0.002). For 3- and 5-year RFS, LVI had the highest impact (HR: 2.63, 95% CI: 1.3-5.1, P=0.005 and HR: 1.96, 95% CI: 1.2-3.0, P=0.002, respectively) Conclusion: Our analysis indicates that an LND >10.82 has the highest predictive potential for OS among the pathological features of patients undergoing cystectomy

A Comprehensive Energy Management Framework for Electric Vehicle Driving Range Extension Considering Battery Aging

The longer charging time and scarcity of fast-charging stations contribute to range anxiety, a significant obstacle to the widespread adoption of electric vehicles (EVs). In addition, the battery pack of an electric vehicle is both expensive and has a limited lifespan. Reduced range and lower resale value are concerns for potential EV owners due to the degradation of capacity over time. The thesis puts forward a novel Energy Management Strategy (EMS) framework that is specifically developed to optimize the speed profile in real-time, thereby extending the driving range and battery lifespan of EVs. The contributions of this study include the integration of battery degradation considerations into the EMS of EVs, eliminating the reliance on precise mathematical modeling through the use of machine learning (ML) techniques, the introduction of driver-adjustable power-saving modes, and the execution of long-term performance analysis simulating up to one year of driving under varying temperatures and driving cycles. The proposed EMS framework is developed based on an autonomous EV platform, facilitating the optimization of the vehicle’s speed profile. However, it can also be adapted for human-driven vehicles by translating the throttle angle into torque demand. The subject of this research is a single-source-powered Battery EV (BEV). The proposed EMS utilizes Multi-Objective Genetic Algorithm (MOGA), Model Predictive Control (MPC), and Pontryagin’s Minimum Principle (PMP) as optimization techniques in three distinct models. The study develops a longitudinal vehicle model, maps motor-inverter characteristics based on experimental tests, and builds battery State of Charge (SOC) and State of Health (SOH) models using ML algorithms. The EMS framework is tested on identical EVs across various driving cycles and temperatures, and is compared against a reference model to assess its effectiveness. Results demonstrate that the proposed EMS, in its moderate mode, can increase driving range by 10.9%, reduce power consumption by 11%, and mitigate battery aging by 15.3%. In aggressive power-saving mode, the EMS extends the driving range by up to 17.7%, minimizes consumption by 16.7%, and improves battery SOH by 21.9%. These findings confirm that the proposed EMS framework can significantly enhance EV’s performance without major compromises to driving experience

Nonlocal nonlinear mechanics of imperfect carbon nanotubes

In this article, for the first time, a coupled nonlinear model incorporating scale influences is presented to simultaneously investigate the influences of viscoelasticity and geometrical imperfections on the nonlocal coupled mechanics of carbon nanotubes; large deformations, stress nonlocality and strain gradients are captured in the model. The Kelvin-Voigt model is also applied in order to ascertain the viscoelasticity effects on the mechanics of the initially imperfect nanoscale system. The modified coupled equations of motion are then derived via the Hamilton principle. A solution approach for the derived coupled equations is finally developed applying a decomposition-based procedure in conjunction with a continuation-based scheme. The significance of many parameters such as size parameters, initial imperfections, excitation parameters and linear and nonlinear damping effects in the nonlinear mechanical response of the initially imperfect viscoelastic carbon nanotube is assessed. The present results can be useful for nanoscale devices using carbon nanotubes since the viscoelasticity and geometrical imperfection are simultaneously included in the proposed model

Nonlinear scale-dependent deformation behaviour of beam and plate structures

Improving the knowledge of the mechanics of small-scale structures is important in many microelectromechanical and nanoelectromechanical systems. Classical continuum mechanics cannot be utilised to determine the mechanical response of small-scale structures, since size effects become significant at small-scale levels. Modified elasticity models have been introduced for the mechanics of ultra-small structures. It has recently been shown that higher-order models, such as nonlocal strain gradient and integral models, are more capable of incorporating scale influences on the mechanical characteristics of small-scale structures than the classical continuum models. In addition, some scaledependent models are restricted to a specific range of sizes. For instance, nonlocal effects on the mechanical behaviour vanish after a particular length. Scrutinising the available literature indicates that the large amplitude vibrations of small-scale beams and plates using two-parameter scaledependent models and nonlocal integral models have not been investigated yet. In addition, no twoparameter continuum model with geometrical nonlinearity has been introduced to analyse the influence of a geometrical imperfection on the vibration of small-scale beams. Analysing these systems would provide useful results for small-scale mass sensors, resonators, energy harvesters and actuators using small-scale beams and plates. In this thesis, scale-dependent nonlinear continuum models are developed for the time-dependent deformation behaviour of beam-shaped structures. The models contain two completely different size parameters, which make it able to describe both the reduction and increase in the total stiffness. The first size parameter accounts for the nonlocality of the stress, while the second one describes the strain gradient effect. Geometrical nonlinearity on the vibrations of small-scale beams is captured through the strain-displacement equations. The small-scale beam is assumed to possess geometrical imperfections. Hamilton’s approach is utilised for deriving the corresponding differential equations. The coupled nonlinear motion equations are solved numerically employing Galerkin’s method of discretisation and the continuation scheme of solution. It is concluded that geometrical imperfections would substantially alter the nonlinear vibrational response of small-scale beams. When there is a relatively small geometrical imperfection in the structure, the small-scale beam exhibits a hardeningtype nonlinearity while a combined hardening- and softening-type nonlinearity is found for beams with large geometrical imperfections. The strain gradient influence is associated with an enhancement in the beam stiffness, leading to higher nonlinear resonance frequencies. By contrast, the stress nonlocality is related to a remarkable reduction in the total stiffness, and consequently lower nonlinear resonance frequencies. In addition, a scale-dependent model of beams is proposed in this thesis to analyse the influence of viscoelasticity and geometrical nonlinearity on the vibration of small-scale beams. A nonlocal theory incorporating strain gradients is used for describing the problem in a mathematical form. Implementing the classical continuum model of beams causes a substantial overestimation in the beam vibrational amplitude. In addition, the nonlinear resonance frequency computed by the nonlocal model is less than that obtained via the classical model. When the forcing amplitude is comparatively low, the linear and nonlinear damping mechanisms predict almost the same results. However, when forcing amplitudes become larger, the role of nonlinear viscoelasticity in the vibrational response increases. The resonance frequency of the scale-dependent model with a nonlinear damping mechanism is lower than that of the linear one. To simulate scale effects on the mechanical behaviour of ultra-small plates, a novel scale-dependent model of plates is developed. The static deflection and oscillation of rectangular plates at small-scale levels are analysed via a two-dimensional stress-driven nonlocal integral model. A reasonable kernel function, which fulfil all necessary criteria, is introduced for rectangular small-scale plates for the first time. Hamilton and Leibniz integral rules are used for deriving the non-classical motion equations of the structure. Moreover, two types of edge conditions are obtained for the linear vibration. The first type is the well-known classical boundary condition while the second type is the nonclassical edge condition associated with the curvature nonlocality. The differential quadrature technique as a powerful numerical approach for implementing complex boundary conditions is used. It is found that while the Laplacian-based nonlocal model cannot predict size influences on the bending of small-scale plates subject to uniform lateral loading, the bending response is remarkably size-dependent based on the stress-driven plate model. When the size influence increases, the difference between the resonance frequency obtained via the stress-driven model and that of other theories substantially increases. Moreover, the resonance frequency is higher when the curvature nonlocality increases due to an enhancement in the plate stiffness. It is also concluded that more constraint on the small-scale plate causes the system to vibrate at a relatively high frequency. In addition to the linear vibration, the time-dependent large deformation of small-scale plates incorporating size influences is studied. The stress-driven theory is employed to formulate the problem at small-scale levels. Geometrical nonlinearity effects are taken into account via von Kármán’s theory. Three types of edge conditions including one conventional and two nonconventional conditions are presented for nonlinear vibrations. The first non-classical edge condition is associated with the curvature nonlocality while the second one is related to nonlocal in-plane strain components. A differential quadrature technique and an appropriate iteration method are used to compute the nonlinear natural frequencies and maximum in-plane displacements. Molecular dynamics simulations are also performed for verification purposes. Nonlinear frequency ratios are increased when vibration amplitudes increase. Furthermore, the curvature nonlocality would cause the small-scale pate to vibrate at a lower nonlinear frequency ratio. By contrast, the nonlocal in-plane strain has the opposite effect on the small-scale system. The outcomes from this thesis will be useful for engineers to design vibrating small-scale resonators and sensors using ultra-small plates.Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 202

Theoretical study of the effect of the element silicon, the adsorption enthalpy nitrite, on the surface of graphene nanostructure

The project is comparing four types of calculation derived graphene. To evaluate the effect of silicon element to Thermochemistry parameters of absorption of nitrite in these derivatives. Two of these derivatives of graphene carbon nitrite connection made, the difference is only in the state of Para and meta carbons connectivity state (named P & M). But in other Derivations first put silicon instead carbon in the meta and para position(named GER Si2 para & GER Si2 metha), then nitrite is added to the silicon(named P* & M*)

Relationship Between Level of Welfare Services and Quality of Life in Surrounding Villages of Zanjan City (Case study: Zanjanrud-e Bala Rural District)

The villages around the city are simultaneously the scene of formation, growth and continuation of opportunities and threats that affect the quality of life and the way to meet the needs of the residents. The purpose of this study was to investigate the relationship between the level of welfare services and quality of life in Surrounding Villages of Zanjan city. This study was conducted by cross-sectional survey on 333 villagers of Zanjanrud-e Bala rural district. The samples were randomly selected from the selected villages by stratified sampling method. Pearson correlation coefficient was used to test the hypotheses by SPSS software. The results showed a statistically significant positive relationship between having welfare facilities and economic, social and environmental quality of life; and a negative and significant relationship between welfare facilities and quality of life with the variable distance from the city. The villages close to the city have a lower level of social welfare, and in contrast, far from the city, the higher the facilities. In addition, people assess the level of welfare facilities and quality of life for the economic dimension as moderate to low and significantly moderate to high for the social and environmental dimensions and a significant difference was between facilities and quality of life. Multiple regression showed independent variables together predict 12.6% of the variance of the quality of life. In general, people have assessed the quality of life along with the welfare facilities of the village as moderate to low and are more deprived.

Effect of Temperature on thermodynamic parameters and chemical properties at adsorption process nitrite on the Graphene Nano surface, density functional theory method

The project is comparing four types of calculation derived graphene. That two of these derivatives of graphene carbon nitrite connection created the difference is only in the state of Para and meta carbons connectivity state. But other derivatives first silicon-carbon alternatives in the meta and para position, then nitrite is added to the silicon. To evaluate the effect of silicon element to absorb energy and other thermodynamic parameters in the derivatives compared with them