IU Indianapolis ScholarWorks :: Browsing by Author "Tovar, Andres"

Browsing by Author "Tovar, Andres"

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Accurate location of tumor in head and neck cancer radiotherapy treatment with respect to machine isocentre
(2017-05) Tangirala, Deepak Kumar; Razban, Ali; Chen, Jie; Tovar, Andres
Radiation Therapy has been one of the most common techniques to treat various types of cancers, in particular is Head and Neck Cancer (HNC) which accounts for three percent of all cancers in the United States. During the treatment procedure, the patient is immobilized using immobilization devices such as the full head face mask, bite blocks, stereotactic frame, etc. to get accurate location of tumor. The disadvantage of these devices is that they are very uncomfortable to the patient especially people suffering from Post-Traumatic Stress Disorder (PTSD) and claustrophobia who cannot wear any confined masked system such as the full head mask or bite block during the treatment procedure. To mitigate this problem, there has been a lot of research in modifying such immobilizing devices without neglecting the accurate location of tumor. To this end, the research presented in this thesis focuses on developing a mask less system with accurately locating the position of tumor using the technique of coordinate transformation at the same time fulfilling the three important characteristics: • Comfort • Accuracy • Low price Such a system is comfortable to the patient because no confining mask system is used and we choose minimal contact points on the patient for fixing the patient. Traditionally, such type of cancer treatment is carried out in two stages: Diagnosis stage, which identifies the location of the tumor and the external markers and the Treatment stage where the tumor is treated with immobilization device being common in both the stages. In the new system, the immobilization devices vary at the two stages. The head position is monitored by using pressure sensor assembly where spring and pressure sensor setup detects the amount and direction of head deviation. We also prepare a customized 3D printed nose bridge part for extra referencing in the treatment room. Also, it is important that we use material for our immobilization devices which does not contain any metal and MRI compatible. Once the patient lies down on the treatment couch and is immobilized using the immobilization devices, then tumor location is calculated using the theory of coordinate transformation and transformation matrix in the Diagnosis and Treatment Stage. To validate the system, simulation of immobilization devices used in the new design was carried out using ANSYS Workbench 15.0 and LS-Dyna software’s Explicit Dynamics method. The simulation for the head-fixing device showed a deflection of ±0.1974 mm with respect to machine isocenter with a load of 60 N, which is lower than the customer requirement of ±3 mm with respect to machine isocenter of head deviation. The material used for the external markers for patient positioning was selected to be polyetheretherketone (PEEK) which is a radiolucent and widely used MRI compatible material. The system also takes into consideration the effect of weight loss, which is one of the drawbacks of the current systems. Although still in the development stage, this mask less system holds to be the next new variety of immobilization devices that are comfortable to the patient and less expensive to be implemented in future cancer treatment practices.
Active Disturbance Rejection Control based on Generalized Proportional Integral Observer to Control a Bipedal Robot with Five Degrees of Freedom
(IEEE, 2016-07) Arcos-Legarda, Jaime; Cortes-Romero, John; Tovar, Andres; Department of Mechanical Engineering, School of Engineering and Technology
An Active Disturbance Rejection Control based on Generalized Proportional Integral observer (ADRC with GPI observer) was developed to control the gait of a bipedal robot with five degrees of freedom. The bipedal robot used is a passive point feet which produces an underactuated dynamic walking. A virtual holonomic constraint is imposed to generate online smooth trajectories which were used as references of the control system. The proposed control strategy is tested through numerical simulation on a task of forward walking with the robot exposed to external disturbances. The performance of ADRC with GPI observer strategy is compared with a feedback linearization with proportional-derivative control. A stability test consisting on analyzing the existence of limit cycles using the Poincaré's method revealed that asymptotically stable walking was achieved. The proposed control strategy effectively rejects the external disturbances and keeps the robot in a stable dynamic walking.
Advances in Vehicular Aerodynamics
(2024-05) Dave, Deepam; Dalir, Hamid; El-Mounayri, Hazim A.; Tovar, Andres; Anwar, Sohel
This article-based research traces the evolution and advancements of vehicular aerodynamic concepts and emphasizes on the significance of vehicle aerodynamics for high-performance vehicles. The thesis further explores the scope of integrating advanced vehicle aerodynamic concepts into consumer vehicles. The thesis aims to point out the significant improvements achieved with the integration of active aerodynamic concepts in terms of both vehicle performance as well as efficiency figures for consumer vehicles. Additionally, exploring the scope for the development of these advanced active aerodynamic systems as third-party modifications is the secondary objective of the presented research. The thesis also highlights the development and integration of unique active aerodynamic systems featured in performance vehicles and analyzes the performance gains achieved using MATLAB program-based simulations supported by a graphical representation of analyzed output data. The study of Active aerodynamic systems for both performance/track-oriented and consumer vehicles remains the primary emphasis for the presented thesis.
Agent-Based Numerical Methods for 3D Bioprinting in Tissue Engineering
(Elsevier, 2018) Sego, T. J.; Moldovan, Nicanor I.; Tovar, Andres; Mechanical Engineering, School of Engineering and Technology
Additive manufacturing has contributed significantly to the development of new surgical and diagnostic aids, personalized medical devices, implants, and prostheses. Now, it aspires to the direct digital manufacturing of living tissue, organs, and body parts. This can be achieved using three-dimensional (3D) bioprinting techniques in which the printing medium consists of biomaterials and living cells. Several 3D bioprinting methods are currently available, including inkjet, extrusion, and stereolithography. An emerging approach is the creation three-dimensional cellular patterns by the use of cell spheroids. The optimal application and further development of 3D bioprinting techniques could largely benefit from computational models capable of predicting the complex behavior of the printed cellular structures on multiple scales. This book chapter summarizes the state of the art of computational models in this field, with an emphasis on agent-based approaches and cell spheroid-based 3D bioprinting.
Bayesian Optimization of Active Materials for Lithium-Ion Batteries
(SAE, 2021-04) Valladares, Homero; Li, Tianyi; Zhu, Likun; El-Mounayri, Hazim; Tovar, Andres; Hashem, Ahmed; Abdel-Ghany, Ashraf E.; Mechanical Engineering, School of Engineering and Technology
The design of better active materials for lithium-ion batteries (LIBs) is crucial to satisfy the increasing demand of high performance batteries for portable electronics and electric vehicles. Currently, the development of new active materials is driven by physical experimentation and the designer’s intuition and expertise. During the development process, the designer interprets the experimental data to decide the next composition of the active material to be tested. After several trial-and-error iterations of data analysis and testing, promising active materials are discovered but after long development times (months or even years) and the evaluation of a large number of experiments. Bayesian global optimization (BGO) is an appealing alternative for the design of active materials for LIBs. BGO is a gradient-free optimization methodology to solve design problems that involve expensive black-box functions. An example of a black-box function is the prediction of the cycle life of LIBs. The cycle life cannot be predicted using a simple closed-form expression but only through the cycling performance test or a numerical simulation. BGO has two main components: a surrogate probabilistic model of the black-box function and an acquisition function that guides the optimization. This research employs BGO in the design of cathode active materials for LIB cells. The training data corresponds to the initial capacity and cycle life of five coin cells with different compositions of LiNixMn2 − xO4 in their cathode, where x is the content of Ni. BGO utilizes the experimental data to identify five new compositions that can produce cells with high initial capacity and\or large cycle life. The surrogate models of the initial capacity and cycle life are Gaussian Processes. The acquisition function is the constrained multi-objective expected improvement. The results show that BGO can identify high-performance active materials for LIBs. Designers can use the data generated during the optimization to decide the composition of the next batch of active materials to be tested, i.e., guide the physical experimentation.
Bio-Inspired Design of Lightweight and Protective Structures
(SAE, 2016-04) Mehta, Prasad S.; Solis Ocampo, Jennifer; Tovar, Andres; Chaudhari, Prathamesh; Mechanical and Energy Engineering, School of Engineering and Technology
Biologically inspired designs have become evident and proved to be innovative and efficacious throughout the history. This paper introduces a bio-inspired design of protective structures that is lightweight and provides outstanding crashworthiness indicators. In the proposed approach, the protective function of the vehicle structure is matched to the protective capabilities of natural structures such as the fruit peel (e.g., pomelo), abdominal armors (e.g., mantis shrimp), bones (e.g., ribcage and woodpecker skull), as well as other natural protective structures with analogous protective functions include skin and cartilage as well as hooves, antlers, and horns, which are tough, resilient, lightweight, and functionally adapted to withstand repetitive high-energy impact loads. This paper illustrates a methodology to integrate designs inspired by nature, Topology optimization, and conventional modeling tools. Two designs are explained to support this methodology: Helmet design inspired by human bone cellular structure (trabecular structure) and vehicle body inspired by a water droplet, ribcage, and human bone. In the helmet design, a finite part of is optimized using topology optimization to generate the porous structure. In the vehicle body design, a water droplet framework, the bio-inspired simulation-based design algorithm used in this work generates innovative layouts. At the vehicle scale, the generated spaceframe has a structure similar to the one of a long bone. In essence, the aerodynamic water droplet shape is protected by the specialized ribcage. At the component scale, each spaceframe tubular component is filled with a functionally graded cellular structure. This internal cellular structure reminds the one of a bone. The spaceframe is attainable with few parts of greater complexity. Such complex, lightweight, multiscale structural layout can be manufactured using 3D printing technologies.
Building a Tensegrity-Based Computational Model to Understand Endothelial Alignment Under Flow
(2021-12) Al-Muhtaseb, Tamara; Ji, Julie; Na, Sungsoo; Tovar, Andres
Endothelial cells form the lining of the walls of blood vessels and are continuously subjected to mechanical stimuli from the blood flow. Microtubule-organizing center (MTOC), also known as centrosome is a structure found in eukaryotic cells close to the nucleus. MTOC relocates relative to the nucleus when endothelial cells are exposed to shear stress which determines their polarization, thus it plays a critical role in cell migration and wound healing. The nuclear lamina, a mesh-like network that lies underneath the nuclear membrane, is composed of lamins, type V intermediate filament proteins. Mutations in LMNA gene that encodes A-type lamins cause the production of a mutant form of lamin A called progerin and leads to a rare premature aging disease known as Hutchinson-Gilford Progeria Syndrome (HGPS). The goal of this study is to investigate how fluid flow affects the cytoskeleton of endothelial cells. This thesis consists of two main sections; computational mechanical modeling and laboratory experimental work. The mechanical model was implemented using Ansys Workbench software as a tensegrity-based cellular model in order to simulate the state of an endothelial cell under the effects of induced shear stress from the blood fluid flow. This tensegrity-based cellular model - composed of a plasma membrane, cytoplasm, nucleus, microtubules, and actin filaments - aims to understand the effects of the fluid flow on the mechanics of the cytoskeleton. In addition, the laboratory experiments conducted in this study examined the MTOC-nuclear orientation of endothelial cells under shear stress with the presence of wound healing. Wild-type lamin A and progerin-expressing BAECs were studied under static and sheared conditions. Moreover, a custom MATLAB code was utilized to measure the MTOC-nuclear orientation angle and classification. Results demonstrate that shear stress leads to different responses of the MTOC orientation between the wild-type and progerin-expressing cells around the vertical wound edge. Future directions for this study involve additional experimental work together with the improved simulation results to confirm the MTOC orientation relative to the nucleus under shear stress.
Calibration and Validation of a High-Fidelity Discrete Element Method (DEM) Based Soil Model Using Physical Terramechanical Experiments
(2022-08) Ghike, Omkar Ravindra; El-Mounayri, Hazim; Tovar, Andres; Zhang, Jing
A procedure for calibrating a discrete element (DE) computational soil model for various moisture contents using a conventional Asperity-Spring friction modeling technique is presented in this thesis. The procedure is based on the outcomes of two physical soil experiments: (1) Compression and (2) unconfined shear strength at various levels of normal stress and normal pre-stress. The Compression test is used to calibrate the DE soil plastic strain and elastic strain as a function of Compressive stress. To calibrate the DE inter-particle friction coefficient and adhesion stress as a function of soil plastic strain, the unconfined shear test is used. This thesis describes the experimental test devices and test procedures used to perform the physical terramechanical experiments. The calibration procedure for the DE soil model is demonstrated in this thesis using two types of soil: sand-silt (2NS Sand) and silt-clay(Fine Grain Soil) over 5 different moisture contents: 0%, 4%, 8%, 12%, and 16%. The DE based models response are then validated by comparing them to experimental pressure-sinkage results for circular disks and cones for those two types of soil over 5 different moisture contents. The Mean Absolute Percentage Error (MAPE) during the compression calibration was 26.9% whereas during the unconfined shear calibration, the MAPE was calculated to be 11.38%. Hence, the overall MAPE was calculated to be 19.34% for the entire calibration phase.
Cellular Helmet Liner Design through Bio-inspired Structures and Topology Optimization of Compliant Mechanism Lattices
(SAE International, 2018-12-28) Najmon, Joel; DeHart, Jacob; Wood, Zebulun; Tovar, Andres; Department of Mechanical Engineering, School of Engineering and Technology
The continuous development of sport technologies constantly demands advancements in protective headgear to reduce the risk of head injuries. This article introduces new cellular helmet liner designs through two approaches. The first approach is the study of energy-absorbing biological materials. The second approach is the study of lattices comprised of force-diverting compliant mechanisms. On the one hand, bio-inspired liners are generated through the study of biological, hierarchical materials. An emphasis is given on structures in nature that serve similar concussion-reducing functions as a helmet liner. Inspiration is drawn from organic and skeletal structures. On the other hand, compliant mechanism lattice (CML)-based liners use topology optimization to synthesize rubber cellular unit cells with effective positive and negative Poisson's ratios. Three lattices are designed using different cellular unit cell arrangements, namely, all positive, all negative, and alternating effective Poisson's ratios. The proposed cellular (bio-inspired and CML-based) liners are embedded between two polycarbonate shells, thereby, replacing the traditional expanded polypropylene foam liner used in standard sport helmets. The cellular liners are analyzed through a series of 2D extruded ballistic impact simulations to determine the best performing liner topology and its corresponding rubber hardness. The cellular design with the best performance is compared against an expanded polypropylene foam liner in a 3D simulation to appraise its protection capabilities and verify that the 2D extruded design simulations scale to an effective 3D design.
Characterization and Simulated Analysis of Carbon Fiber with Nanomaterials and Additive Manufacturing
(2023-12) Omole, Oluwaseun; Dalir, Hamid; Agarwal, Magilal; Tovar, Andres
Due to the vast increase and versatility of Additive Manufacturing and 3D-printing, in this study, the mechanical behavior of implementing both continuous and short carbon fiber within Nylon and investigated for its effectiveness within additively manufactured prints. Here, 0.1wt% of pure nylon was combined with carbon nanotubes through both dry and heat mixing to determine the best method and used to create printable filaments. Compression, tensile and short beam shear (SBS) samples were created and tested to determine maximum deformation and were simulated using ANSYS and its ACP Pre tool. SEM imaging was used to analyze CNT integration within the nylon filament, as well as the fractography of tested samples. Experimental testing shows that compressive strength increased by 28%, and the average SBS samples increased by 8% with minimal impacts on the tensile strength. The simulated results for Nylon/CF tensile samples were compared to experimental results and showed that lower amounts of carbon fiber samples tend to have lower errors.

Browsing by Author "Tovar, Andres"

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