The aerodynamic analysis of vehicles using Computational Fluid Dynamics (CFD) is a powerful tool that is used to explore and investigate how air flow behaves around the vehicle, gives a qualitative idea of aerodynamic behavior and provides engineers with the information necessary to design the pieces that will be tested in the wind tunnel. This technique allows to find the values of forces and moments to get an idea of the drag resistance and lift forces on the vehicle. It is also possible to determine the position of the center of pressure that exerts a vital importance in the definition of the directional stability of the vehicle in its lateral dynamics. On the other hand, it offers the advantage of being able to see many variables of the problem that are very difficult to access in reality, for example to see current lines, vortex shedding, fields of pressures around the vehicle. Although the use of CFD has become a common practice in the automotive industry in recent decades, it is still not considered as a single technique, since one of the limitations is related to the dynamics of a turbulent flow is quite complex so which analytical and computational study depends on what is called Turbulence Models. This article aims to show the aerodynamic design process by CFD simulation of a Baja SAE vehicle chassis using Ansys software, widely used for simulation of static charges, thermodynamics, fluid mechanics, multiphysics systems and vibrations and to provide information that can be validated experimentally in the future.

Redundant manipulators are mechanical systems with more degrees of freedom than required for their task. The paper considers the problem of energy minimization, given a required task, for such systems. The problem is formulated as a constrained optimal control with additional inequality constraints. A dynamic projection enables transforming the problem into an equivalent unconstrained, reduced order one. The solution scheme presented here combines the problems of path planning and tracking control. It includes decomposition of the problem into a bi-level structure. The parametric, higher-level problem is solved using a genetic algorithm and the lower level one is solved using optimal control. Comparison with full optimal control solutions shows the superiority of the combined evolutionary algorithm in terms of computational feasibility and overall energy savings.

The chassis is one of the main components of the vehicle, which provides not only support and stiffness but also gives the vehicle its shape. Its design is a challenge for the mechanical engineer: to achieve an optimum resistance-weight ratio which can ensure the safety of the pilot. To optimize its design, engineers can rely on the Finite Element Analysis (FEA) an ideal method to predict the behavior of the chassis to the different loads (Mechanical Effort, fatigue, movement) and effects (Vibration, heat, fluid flow, transfer of heat) given in real environments. This analysis is able to describe if a product may break, wear out or, otherwise, it will work as expected. Additionally, it allows the variation of the geometry and materials used so that the most suitable one can be selected for the application in study. This article aims to show the preliminary design of the chassis (Simplified 3D model using CAD) taking into account the rules of the SAE competition and its optimization by using the FEA analysis and also taking into account its geometry. Static load analysis will start by selecting the appropriate mesh size and having as criteria that Von Mises stress should be less than the yield point of the selected material. Likewise, the deformation of the members that make up the chassis should not put at risk the safety of the pilot. Moreover, a Modal Analysis of the chassis to verify the natural frequencies and vibration modes is also made. The result of this research provides a design approach for the validation (theory vs simulation) and optimization of the chassis to ensure better performance as well as to facilitate the manufacture of its parts and assembly.

The simultaneous optimum design for structural and control systems is very important to realize better performance, short lead time and low cost in the development of product. Previous researches on the simultaneous optimum design of these systems are mainly based on mathematical optimization or coupled computation by CAE which are based on point-based iterative calculation. On the other hand, it is general and essential that the required performances and the influence factors for them have some kinds of uncertainty especially in the initial design stage of structural design and uncertainty arising from the difference of real structural (mechanical) and mathematical models in the control system. In this research, for the expression of uncertainty, we use set-based method rather than point-based for processing these uncertainties. Also, generally, the design of the system has often multi-performances, whether structural system or control system. Then, how effective the set-based design method is to solve the simultaneous design problem is investigated, using simple examples of classical control and modern control. As a result, it is found that the applicability of the set-based design method is shown.

Two major responsibilities are taken by a knee joint during level ground walking of a human being. At stance phase, knee joint is locked in order to provide stability against ground reaction force, and in swing phase, knee flexes for ground clearance of the foot. In this study, a four-bar controlled compliance actuator (FCCA) has been configured for assisting the knee joint during walking. The main focus of FCCA design is the reduction of required mechanical power through a compliance actuation strategy and amplification of motor power. The proposed design consists of two linear spring-damper systems, out of which, one controls the locking of knee during stance phase and another takes care of knee flexion at swing phase. Without a proper selection of stiffness and damping coefficient for both the springs, the knee may be subjected to jerk during flexion, which may give rise to discomfort to the user and consequently, he/she may fall during walking. This study aims to ensure smooth knee operation in both stance phase as well as swing phase by assigning the proper spring stiffness and damping coefficient for both the springs. The responsibility is given to a non-traditional optimization tool, namely particle swarm optimization (PSO). The optimization is carried out using a co-simulation approach between Matlab and ADAMS. The aim of PSO (run in Matlab) is to minimize both the frequency as well as amplitude of the jerk by finding a suitable set of design variables, that is, spring stiffness and damping coefficient of two spring-damper systems.

Motion planning and control to generate human like walking with bipedal robots has been an active area of research for several decades. Besides walking, humans are capable of performing several other complex maneuvers using their limbs. A handspring is one such maneuver. During this acrobatic move, a person performs a complete revolution of the body by first placing her hands as if in a handstand, then pushing off of the floor with her hands to return to a standing position. Often, acrobats leverage the momentum from one handspring to perform a series of continuous back-to-back handsprings. In this paper, we present handspring trajectory planning for a simple two link robot using numerical optimization. We are able to generate near-periodic perpetual handspring-like maneuvers using two different actuation strategies (i) a constant torque at the hip joint, and (ii) an impulsive actuation to the imminent free leg.

In this paper, an optimization procedure is derived to find the best controller for the trajectory-tracking of an autonomous underwater vehicle (AUV) subject to uncertainties (e.g., current disturbances, un-modeled dynamics and parameter variations). The proposed algorithm is based on the dynamic model of the system and a recently proposed controller called Hierarchical Robust Nonlinear Controller (HRNC). The first objective is to find the best values for the controller gains to achieve trajectory tracking of the leader AUV. Starting from a random configuration, the leader AUV and the five followers make and keep a given formation all along the trajectory. A multi-objective optimization, based on genetic algorithms, is used here. A star formation with 6 AUVs is used as a case study to test the proposed algorithm. Simulation results show that the optimized controller gains led to successful formation keeping along the selected path with relatively minimum controller output toques.

Current understanding of blast wave transmission and mechanism of primary traumatic brain injury (TBI) and the role of helmet is incomplete thus limiting the development of protection and therapeutic measures. Combat helmets are usually designed based on costly and time consuming laboratory tests, firing range, and forensic data. Until now advanced medical imaging and computational modeling tools have not been adequately utilized in the design and optimization of combat helmets. The goal of this work is to develop high fidelity computational tools, representative virtual human head and combat helmet models that could help in the design of next generation helmets with improved blast and ballistic protection. We explore different helmet configurations to investigate blast induced brain biomechanics and understand the protection role of helmet by utilizing an integrated experimental and computational method. By employing the coupled Eulerian-Lagrangian fluid structure interaction (FSI) approach we solved the dynamic problem of helmet and head under the blast exposure. Experimental shock tube tests of the head surrogate provide benchmark quality data and were used for the validation of computational models. The full-scale computational NRL head-neck model with a combat helmet provides physical quantities such as acceleration, pressure, strain, and energy to blast loads thus provides a more complete understanding of the conditions that may contribute to TBI. This paper discusses possible pathways of blast energy transmission to the brain and the effectiveness of helmet systems at blast loads. The existing high-fidelity image-based finite element (FE) head model was applied to investigate the influence of helmet configuration, suspension pads, and shell material stiffness. The two-phase flow model was developed to simulate the helium-air shock wave interaction with the helmeted head in the shock tube. The main contribution was the elucidation of blast wave brain injury pathways, including wave focusing in ocular cavities and the back of head under the helmet, the effect of neck, and the frequency spectrum entering the brain through the helmet and head. The suspension material was seen to significantly affect the ICP results and energy transmission. These findings can be used to design next generation helmets including helmet shape, suspension system, and eye protection.

The focus of this paper is on the development of an open loop controller for type 1 diabetic patients which is robust to meal and initial condition uncertainties in the presence of hypo- and hyperglycemic constraints. Bernstein polynomials are used to parametrize the evolving uncertain blood-glucose. The unique bounding properties of these polynomials are then used to enforce the desired glycemic constraints. A convex optimization problem is posed in the perturbation space of the model and is solved repeatedly to sequentially converge on a sub-optimal solution. The proposed approach is demonstrated on the classic Bergman model for Type 1 diabetic patients.

This paper puts forward a new kind of SOFC - GT distributed energy system with methanol as fuel, through the absorption refrigeration (AR) and heat exchanger (HE) to recover the waste heat of GT. Based on thermodynamic analysis model, the performances, especially the exergy losses of the unit as well as its subsystems mainly including eight parts were obtained. The chemical energy of the fuel will directly be changed into electricity. Energy conversion efficiency can be as high as 85% above. The theoretical value has been paid attention by the researchers from all over the world. Comparative study in this paper, the simulation calculation and thermal performance analysis of the performance of two kinds of SOFC - GT is conducted. The results show that the total power generation efficiency of pure SOFC system, Case A and Case B are 19.28%, 55.79% and 52.26% respectively. The total thermal efficiency of Case A and B are 83.44 % and 82.79 % respectively. Additionally, the changing laws of total exergy loss, energy and exergy efficiency of integrated system at different loads also were studied. The results provide not only theory basis and scientific support for the design of the SOFC - GT distributed energy system with absorption refrigeration and heat exchanger recovering waste heat, but also a new scheme of energy saving and optimization for the units.

Distributed electric generation systems are increasingly considered to offset energy costs and carbon emissions of large building complexes. College campuses, with their physical compactness, and diversity in building loads, present a common application for distributed generation systems. This paper presents the analysis approach and the main results of a feasibility study of a distributed generation system to supply electric and thermal energy for a large university campus, incorporating energy efficiency measures, to reduce carbon emissions at minimal life cycle cost. The presented study uses a load profile developed based on calibrated detailed simulation energy models for prototypical campus buildings. The calibration analysis is carried out using measured energy consumption data, at the individual building level, and the whole-campus level. Several combinations of distributed generation options are evaluated, using an hourly optimization analysis tool, to meet the entire campus hourly electrical and thermal loads. Proposed efficiency measures and distributed generation options are evaluated using different indicators, including life cycle cost and carbon emissions. The analysis results indicate that implementing energy efficiency measures to reduce electrical and thermal loads before implementing distributed generation options is the most cost-effective approach to reducing the campus’s energy-related carbon emissions. The results of the study are summarized to guide college campuses and managers of other urban districts as they adapt to a changing energy landscape.

The supercritical carbon dioxide (sCO 2 ) power generation system holds tremendous potential in nuclear, chemical and renewable energy utilization fields due to its compactness, security and high efficiency. However, the dramatic variation in the physical property of sCO 2 complicates the system analysis and optimization. Recent researches usually took simple stack of all governing equations of individual components as the physical model of system. Besides, based on the traditional heat transfer modeling method, some researches apply the segmentation method to take fluid property variation into consideration. These methods exacerbate the multivariate nonlinearity of the system and are not suitable to analyze complex sCO 2 thermal systems. Moreover, taking the consideration of the strong nonlinearity of sCO 2 system, most researches adopt single parameter analysis to obtain the optimum solution, which may not achieve global optimization. In this contribution, introduction of a new definition of thermal resistance of heat exchanger disassembles the original implicit nonlinear properties of heat transfer processes as the linear relation between inlet temperature difference of fluids and heat flow rate, and the explicit nonlinear expression of thermal resistance. For the nonlinearity caused by the variable properties of sCO 2 , segmentation is also used in heat exchanger modeling. However differently, the introduction of new defined thermal resistance enables the elimination of most intermediate variables produced by segmentation, which contributes to the connection of all segments in heat exchanger into a heat exchanger network. Furthermore, based on the system layout, the equivalent power flow diagram of the system is built to derive the corresponding governing equations revealing the overall transfer and conversion laws of heat. Combining the flow resistance balance equations of all components and the accompanying power flow processes constraints offers the inherent physical constraints among operating parameters. Benefit from the conciseness of system model, the genetic algorithm can be used for the model optimization. Taking thermal efficiency of the system as the optimization objective, the optimal matching of the operating parameters under variable working conditions is obtained.

Background: Pressure distribution for transtibial amputees (TTA) patients varies at the limb socket interface according to several factors. Although socket technology is getting more advanced, the majority of researchers are still facing problems with relief areas. Objectives: This study focused on the theoretical and experimental aspects of the design to figure out patients’ sensitivity to pain when wearing sockets. Relief areas were analyzed using data collected from patients’ centers and optimized under different static and dynamic conditions. Methods: Finite element trials and DOE optimization using Design Expert 8 software and analysis of variance (ANOVA) revealed that holes with relief areas are appropriates for lower extremities patients where scanning electron images (SEM) of the worn areas show direct relations between relieved sockets with holes at fibula head (FH) and patient lifestyle and activity. Clinical Relevance: A patient that moves rather slowly, as a result of old age or sedentary level of activity would greatly benefit from the FH socket hole implementation, and thus reduces the wear of socket materials after longer period of time and increases the level of comfort of patient skins. the interviews conducted were evident that patients endured pain at the PT and FH. Moreover, further studies were performed on the FH, and results revealed that lateral forces play a major role and is influenced by the lifestyle of the patient.

A 2-dimensional anatomical knee model was developed for aligning knee joint related bone structures with experimental kinematic data. The experimental data was collected using motion capture cameras, which recorded the position of reflective markers placed on the human subject. Velocities were calculated by numerically differentiating the marker position with respect to time. Joints, such as the hip, knee, and ankle, were represented by axes of rotation. These axes were determined by calculating the relative instantaneous center of rotation of a body segment with respect to the adjacent body segment. Body-fixed coordinate systems were set for both thigh and shin. Anatomical bone structures were obtained from an x-ray and represented mathematically as polynomials. The femoral bone surface was aligned with the experimental data by superimposing the center of rotation of the shin with respect to thigh with the geometric center of the femoral condyle. The tibial surface was aligned with the experimental data by aligning the bones at minimum flexion and then superimposing the tibia with a shared point between femur and tibia. Ligaments were modeled as non-linear elastic springs. Cruciate ligaments were divided into a posterior and anterior ligament fiber bundle. Cruciate ligament forces were calculated for the squatting exercise for five different femoral geometric centers. Geometric centers were determined using a nonlinear least squares optimization technique. Cruciate ligament forces are discussed in this paper.

This paper firstly educes an energy-based ecological function (EF) which is a compromise between energy pumping rate (EPR) and dissipation of EPR for an endoreversible chemical pump (CP) cycle. By solving the equations of Euler Lagrange, the fundamental optimization relationships of the EF and coefficient of performance (COP) for the CP cycles with linear mass transfer (MT) law and diffusive MT law are derived. The numerical calculations to analyze the influences of the cycle parameters on the relationship between the EF and COP are provided, and the influence of two different MT laws on the EF and COP characteristic is discussed in detail. The maximum EF of the cycle with the linear MT law is bigger than that with the diffusive MT law. The results obtained in this paper can be applied to design a class of devices, such as photochemical, electrochemical and solid-state apparatus as well as mass exchangers, etc.

Sustainable energy transition requires a critical prediction for the long-term evolvement of energy systems around the world. It is affected by several factors: the changes in the oil economy, the climate change, and the development of renewable energy supply technologies. The aim of this research is to compare and analyze Abu Dhabi’s generation sector in its transition from complete conventional gas to a mix of conventional and Photovoltaic (PV) energy systems. Employing a Mixed Integer Linear Program (MILP) and PLEXOS software, two capacity expansion scenarios of Abu Dhabi’s generation sector for five years are optimized, analyzed, and compared using a real data from the generation and demand sides. This research means to highlight, to the UAE government, the effect of introducing more renewable energy and to evaluate the performance of the generation side in meeting the forecasted demand. Furthermore, this work opens the doors wide for further development and optimization in the GCC area.

Magnetic gearing is a developing technology that utilizes magnetic forces to transmit torque through a system. Unlike traditional gears that rely on teeth engagement to transmit motion and torque, interacting magnetic fields in a magnetic gear transfer the torque with no contact area required. Early magnetic gearbox designs stemmed from an electromagnetic design, however, at larger scales the assembly process as well as electromagnetic design drives the overall mechanical design, due to high magnetic forces and stresses during the assembly. The development of magnetic gearboxes involves the optimization of the assembly process, the electromagnetic design and the mechanical performance to achieve a design that is robust, efficient, manufacturable, and economical. Each of these attributes is necessary to advance the technical readiness for applications as varied as wind turbines or robotics. These qualities were sought in the design of two new magnetic gearboxes which have been manufactured and tested. The mechanical design of the multistage gearbox established a repeatable assembly process that could be upscaled without compromising the structural integrity of the components. Design variants were simulated and tested to limit bending and shear stresses in the gearbox, whilst maintaining the electromagnetic performance of the system. The mechanical design of the modular magnetic gearbox established a new rotor design where manufacturability and configurability were improved to make the gearbox ideal for applications that require varying gear ratios.

The Measurement While Drilling (MWD) tool is used by oil and gas industry to provide the directional survey information while drilling. With rig rates exceeding $1 million per day and wells that are drilled at depths of over 30,000 ft (9144 m), operators needs to have an MWD tool that can self-power itself to provide high data rates and strong signal strength. Among different types of MWD tool, the Continuous Mud-Pulse Telemetry (C-MPT) can generate high data rates and signal strength. The C-MPT has a rotating valve that propagates signal upstream through the drilling fluid in the drill string. However, the ability to power a C-MPT for the MWD tool using the existing hydraulic forces of the drilling fluid has not been extensively researched. The focus of this study was to propose the 2-lobe and 3-lobe turbo siren designs that can provide power to an alternator while maintain high data rates and signal strength. All turbo siren designs are based on a vein, rotor, and stator. The turbo siren systems were manufactured with 3D printing. An experimental wind tunnel was designed and built to simulate the downhole drilling environment. The testing results of the turbo siren systems are presented and discussed, including no-load rotation speed (RPM), stall torque, power and data rate. The results provide the guidance for the optimization of the self-powered MWD turbo siren design.

Emissions compliance during engine start-up conditions is a major obstacle for current automotive manufacturers across global markets. The challenges to meeting emissions targets are both due to increasingly stringent regulations and the difficulty in developing control strategies for a high degree-of-freedom and highly non-linear system. Online extremum-seeking (ES) methods offer a promising alternative to traditional optimization based on design-of-experiment based automotive calibration. With extremum-seeking methods, results from all prior experiments are used to intelligently and efficiently generate the next iteration of the control parameter(s). In this work, the applicability of the online extremum-seeking method is explored to optimize five performance variables (injection timing for two injection events, the injection fuel mass divided between the first and second injection events, air-fuel equivalence ratio and exhaust cam timing) to minimize brake specific fuel consumption while imposing different constraints on NO x emissions. The experiments were conducted using a production turbocharged four-cylinder gasoline engine with an advanced fuel injection system. The results show the utility of the ES strategy to quickly identify optimal control parameter combinations and the emissions and engine performance improvements during the calibration process. The results also demonstrate the dramatic benefit of the ES calibration strategy in terms of test time required.

The newly developed airplanes are using composite laminates to replace the metal alloys for different components, such as the fuselage and the wings. The major advantage of the composite materials is to reduce structural weight which results in reducing the fuel consumption. The aim of this project is to investigate the structural integrity of an airplane fuselage, which uses various types of carbon composite laminates under the static loading of the cabin pressurization. The research is performed using the finite element method and the HYPERMESH commercial software with a composite tool to change the thickness and the orientation of carbon fiber laminates used in the facesheet of the sandwich structure. Three different orientations/stacking sequence of the HexPly 8552 AS4 carbon fibers with two honeycomb cores: Hexagonal Al and Nomex. The results show that the composite material using the HexPly 8552 carbon fiber oriented at angle 30 and angle 45 and the Nomex Honeycomb core of a total laminate thickness of 15.875mm outperform all other thicknesses and orientations in regards to the static loading failure.