Mechanical and Energy Engineering Works

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    Time-Dependent System Reliability Analysis With Second-Order Reliability Method
    (American Society of Mechanical Engineers, 2020) Wu, Hao; Hu, Zhangli; Du, Xiaoping; Mechanical and Energy Engineering, School of Engineering and Technology
    System reliability is quantified by the probability that a system performs its intended function in a period of time without failures. System reliability can be predicted if all the limit-state functions of the components of the system are available, and such a prediction is usually time consuming. This work develops a time-dependent system reliability method that is extended from the component time-dependent reliability method using the envelope method and second-order reliability method. The proposed method is efficient and is intended for series systems with limit-state functions whose input variables include random variables and time. The component reliability is estimated by the second-order component reliability method with an improve envelope approach, which produces a component reliability index. The covariance between component responses is estimated with the first-order approximations, which are available from the second-order approximations of the component reliability analysis. Then, the joint distribution of all the component responses is approximated by a multivariate normal distribution with its mean vector being component reliability indexes and covariance being those between component responses. The proposed method is demonstrated and evaluated by three examples.
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    Direct and Extended Piezoresistive and Piezoelectric Strain Fusion for a Wide Band PVDF/MWCNT-Based 3D Force Sensor
    (IEEE, 2021) Alotaibi, Ahmed; Anwar, Sohel; Mechanical and Energy Engineering, School of Engineering and Technology
    This paper presents a novel 3D force sensor design based on in-situ nanocomposite strain sensors. The polymer matrix of the polyvinylidene fluoride (PVDF) and multi-walled carbon nanotubes (MWCNT) conductive filler nanocomposite film have been chosen as sensing elements for the 3D force sensor. A bioinspired tree branch design was used as the 3D force sensor’s elastic structure, that was built using thin Aluminum plates and a laser cutting fabrication process. The PVDF/MWCNT films contained piezoresistive and piezoelectric characteristics, allowing for static/low and dynamic strain measurements, respectively. Two compositions with 0.1 and 2 wt.% PVDF/MWCNT sensing elements were selected for piezoelectric and piezoresistive strain measurements, respectively. These characteristic measurements were investigated under different loading frequencies in a simply supported beam experiment. The 3D force sensor was tested under dynamic excitation in the Z-direction and the X-direction. A Direct Piezoresistive/Piezoelectric fusion (DPPF) method was developed by fusing the piezoresistive and piezoelectric measurements at a given frequency that overcomes the limited frequency ranges of each of the strain sensor characteristics. The DPPF method is based on a fuzzy inference system (FIS) which is constructed and tuned using the subtractive clustering technique. Different nonlinear Hammerstein-Wiener (nlhw) models were used to estimate the actual strain from piezoresistive and piezoelectric measurements at the 3D force sensor. In addition, an Extended direct Piezoresistive/Piezoelectric fusion (EPPF) algorithm is introduced to enhance the DPPF method via performing the fusion in a range of frequencies instead of a particular one. The DPPF and EPPF methods were implemented on the 3D force sensor data, and the developed fusion algorithms were tested on the new 3D force sensor via experimental data. The simulation results show that the proposed fusion methods have been effective in achieving lower Root Mean Square Error (RMSE) in the estimated strain than those obtained from the tuned nlhw models at different operating frequencies.
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    Modified Particle Swarm Optimization Based Powertrain Energy Management for Range Extended Electric Vehicle
    (MDPI, 2023-06-30) Parkar, Omkar; Snyder, Benjamin; Rahi, Adibuzzaman; Anwar, Sohel; Mechanical and Energy Engineering, School of Engineering and Technology
    The efficiency of hybrid electric powertrains is heavily dependent on energy and power management strategies, which are sensitive to the dynamics of the powertrain components that they use. In this study, a Modified Particle Swarm Optimization (Modified PSO) methodology, which incorporates novel concepts such as the Vector Particle concept and the Seeded Particle concept, has been developed to minimize the fuel consumption and NOx emissions for an extended-range electric vehicle (EREV). An optimization problem is formulated such that the battery state of charge (SOC) trajectory over the entire driving cycle, a vector of size 50, is to be optimized via a control lever consisting of 50 engine/generator speed points spread over the same 2 h cycle. Thus, the vector particle consisted of the battery SOC trajectory, having 50 elements, and 50 engine/generator speed points, resulting in a 100-D optimization problem. To improve the convergence of the vector particle PSO, the concept of seeding the vector particles was introduced. Additionally, further improvements were accomplished by adapting the Time-Varying Acceleration Coefficients (TVAC) PSO and Frankenstein’s PSO features to the vector particles. The MATLAB/SIMULINK platform was used to validate the developed commercial vehicle hybrid powertrain model against a similar ADVISOR powertrain model using a standard rule-based PMS algorithm. The validated model was then used for the simulation of the developed, modified PSO algorithms through a multi-objective optimization strategy using a weighted sum fitness function. Simulation results show that a fuel consumption reduction of 12% and a NOx emission reduction of 35% were achieved individually by deploying the developed algorithms. When the multi-objective optimization was applied, a simultaneous reduction of 9.4% fuel consumption and 7.9% NOx emission was achieved when compared to the baseline model with the rule-based PMS algorithm.
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    Predictive Energy Management of Mild-Hybrid Truck Platoon Using Agent-Based Multi-Objective Optimization
    (IEEE, 2023-07-11) Pramanik, Sourav; Anwar, Sohel; Mechanical and Energy Engineering, School of Engineering and Technology
    The objective of this paper is to formulate and analyze the benefits of a predictive non-linear multi objective optimization method for a platoon of mild-hybrid line haul trucks. In this study a group of three trucks with hybrid electric powertrain are considered in a platoon formation where each truck has a predictive optimal control to save fuel with out any loss of trip time. While the controller on each truck uses the look ahead knowledge of the entire route in terms of road grade, the overall platoon controller used a multi agent method (Metropolis algorithm) to define coordination between the trucks. While the individual trucks, showed significant improvement in fuel economy when running on predictive mode, the true savings came from the entire platoon and showed promising results in terms of absolute fuel economy without trading off on total trip time. The proposed algorithm also proved to be significantly emission efficient. A platoon of 3 trucks achieved an average of 10% fuel savings while cutting back 13% on engine out NOx emissions for engine off coasting and 9.3% fuel saving with 8% emissions reduction for engine idle coast configuration when compared to non-predictive non-platoon configuration.
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    Quantification of orthodontic loads on teeth in the correction of canine overeruption using different archwire designs
    (Elsevier, 2023-01) Wang, Dongcai; Turkkahraman, Hakan; Chen, Jie; Li, Boxiu; Liu, Yunfeng; Mechanical and Energy Engineering, School of Engineering and Technology
    Introduction This study quantifies the effects of material, size of the continuous archwires, and level of overeruption on the loads on teeth in the correction of overerupted canines. Methods An orthodontic force test (OFT) was used to measure the 3-dimensional loads delivered by the archwires to the brackets attached to the maxillary right incisors, canine, and premolars. Dentoforms simulating canine overeruptions at the 0.5 mm and 1 mm levels were made from computerized tomography scans. Archwires with 2 types of material (stainless steel [SS] and nickel-titanium [NiTi]) and 2 sizes (0.014-in and 0.016-in) were tested, respectively, on the 0.022 × 0.028-in brackets through elastomeric ligatures. Results The forces were dominantly intrusive on the canines and extrusive on the first premolars and lateral incisors. The magnitudes of the extrusive forces were about 74% and 52% that of intrusive force on the canines, which range from −0.48 ± 0.01 N to −5.70 ± 0.14 N depending on the wire material, size, and severity of overeruption (P <0.01). The canine intrusive forces created by SS wires were about 3 times higher than that of NiTi wires with the same sizes, 0.016-in archwires were about twice higher than that of 0.014-in with the same materials, and 1 mm overeruption level doubled with respect to 0.5 mm. Significant second-order moment as coupled with the intrusive or extrusive forces. Conclusions The intrusive and extrusive forces on teeth in the correction of canine overeruption can be quantified by the in vitro orthodontic force test, and the effects of the 3 factors significantly affect the loads on the teeth.
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    Envelope Method for Time- and Space-Dependent Reliability Prediction
    (ASCE-ASME, 2022-12) Wu, Hao; Du, Xiaoping; Mechanical and Energy Engineering, School of Engineering and Technology
    Reliability can be predicted by a limit-state function, which may vary with time and space. This work extends the envelope method for a time-dependent limit-state function to a time- and space-dependent limit-state function. The proposed method uses the envelope function of time- and space-dependent limit-state function. It at first searches for the most probable point (MPP) of the envelope function using the sequential efficient global optimization in the domain of the space and time under consideration. Then the envelope function is approximated by a quadratic function at the MPP for which analytic gradient and Hessian matrix of the envelope function are derived. Subsequently, the second-order saddlepoint approximation method is employed to estimate the probability of failure. Three examples demonstrate the effectiveness of the proposed method. The method can efficiently produce an accurate reliability prediction when the MPP is within the domain of the space and time under consideration.
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    Three-dimensional analytical models for predicting coating thickness on non-axial symmetrical workpieces in electron beam physical vapor deposition
    (Elsevier, 2022-08) Li, Yafeng; Ji, Zhengzhao; Dhulipalla, Anvesh; Zhang, Jian; Yang, Xuehui; Dube, Tejesh; Kim, Bong-Gu; Jung, Yeon-Gil; Koo, Dan Daehyun; Zhang, Jing; Mechanical and Energy Engineering, School of Engineering and Technology
    In this work, three-dimensional (3D) analytical models for non-axial symmetric workpieces, including ellipsoid and cylinder, are derived to predict the coating thickness distributions in the EB-PVD process. Additionally, 3D analytical models for axial symmetric workpieces, including disk and sphere are presented, which will be used for deriving the non-axial symmetric workpiece solutions. The models are based on extending the two-dimensional (2D) models of a disk workpiece by Schiller et al. (1982) and a circular arc on a cylinder by Fuke et al. (2005). The 3D models for disk and sphere workpieces are also presented which are used to derive the non-axial symmetric models. The results show that the 3D analytical models are consistent with the 2D models, and also in excellent agreement with our finite element (FE) model predictions and experimental data in the literature.
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    Smoothed Particle Hydrodynamics Modeling of Thermal Barrier Coating Removal Process Using Abrasive Water Jet Technique
    (ASME, 2022-09) Zhang, Jian; Yang, Xuehui; Sagar, Sugrim; Dube, Tejesh; Koo, Dan Daehyun; Kim, Bong-Gu; Jung, Yeon-Gil; Zhang, Jing; Mechanical and Energy Engineering, School of Engineering and Technology
    In this work, a new smoothed particle hydrodynamics (SPH)-based model is developed to simulate the removal process of thermal barrier coatings (TBCs) using the abrasive water jet (AWJ) technique. The effects of water jet abrasive particle concentration, incident angle, and impacting time on the fracture behavior of the TBCs are investigated. The Johnson–Holmquist plasticity damage model (JH-2 model) is used for the TBC material, and abrasive particles are included in the water jet model. The results show that the simulated impact hole profiles are in good agreement with the experimental observation in the literature. Both the width and depth of the impact pit holes increase with impacting time. The deepest points in the pit hole shift gradually to the right when a 30-deg water jet incident angle is used because the water jet comes from the right side, which is more effective in removing the coatings on the right side. A higher concentration of abrasive particles increases both the width and depth, which is consistent with the experimental data. The depths of the impact pit holes increase with the water jet incident angle, while the width of the impact holes decreases with the increase in the water jet incident angle. The water jet incident angle dependence can be attributed to the vertical velocity components. The erosion rate increases with the incidence angle, which shows a good agreement with the analytical model. As the water jet incident angle increases, more vertical velocity component contributes to the kinetic energy which is responsible for the erosion process.
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    Multi-Objective Bayesian Optimization of Lithium-Ion Battery Cells for Electric Vehicle Operational Scenarios
    (MDPI, 2022-05-31) Gaonkar, Ashwin; Valladares, Homero; Tovar, Andres; Zhu, Likun; El-Mounayri, Hazim; Mechanical and Energy Engineering, School of Engineering and Technology
    The development of lithium-ion batteries (LIBs) based on current practice allows an energy density increase estimated at 10% per year. However, the required power for portable electronic devices is predicted to increase at a much faster rate, namely 20% per year. Similarly, the global electric vehicle battery capacity is expected to increase from around 170 GWh per year today to 1.5 TWh per year in 2030—this is an increase of 125% per year. Without a breakthrough in battery design technology, it will be difficult to keep up with their increasing energy demand. The objective of this investigation is to develop a design methodology to accelerate the LIB development through the integration of electro-chemical numerical simulations and machine learning algorithms. In this work, the Gaussian process (GP) regression model is used as a fast approximation of numerical simulation (conducted using Simcenter Battery Design Studio®). The GP regression models are systematically updated through a multi-objective Bayesian optimization algorithm, which enables the exploration of innovative designs as well as the determination of optimal configurations. The results reported in this work include optimal thickness and porosities of LIB electrodes for several practical charge–discharge scenarios which maximize energy density and minimize capacity fade.
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    Integrating skeletal anchorage into fixed and aligner biomechanics
    (Elsevier, 2022-08) Roberts, W. Eugene; Chang, Chris H.; Chen, Jie; Brezniak, Naphtali; Yadav, Sumit; Mechanical and Energy Engineering, School of Engineering and Technology
    Routine alignment with fixed appliances and aligners is indeterminate mechanics because equilibrium equations are only applicable to two abutments: teeth, segments, or arches. Orthodontists must depend on compliance and resilience of materials (archwires and aligners) for initial alignment. However, stabilized segments and arches are "large multirooted teeth" that can be moved with determinate mechanics using temporary skeletal anchorage devices. Temporary skeletal anchorage devices have advanced from retromolar implants and inter-radicular miniscrews to extra-alveolar bone screws placed in the basilar bone buccal to the first molars: mandibular buccal shelf and infrazygomatic crest. Extra-alveolar anchorage is determinate mechanics to move teeth, segments, and arches. Retraction and rotation of the lower arch reverses the etiology of Class III open bite malocclusion to correct severe skeletal dysplasia with no extractions or orthognathic surgery.