In this work, we use structural topology optimization to design the hip bone with multi-load conditions of walking gait cycle. Previous research works on optimal bone design primarily aimed to design the micro-structure of the femur bone using a multi-load approach with global geometry fixed. To the best of authors’ knowledge, no optimal design research literature is available on the hip bone. This work uses the concept of multiload conditions, since it considers the effect of entire gait cycle while applying loading conditions. We consider three cases for the weights. Those are (i) equi-weight case, (ii) non-equi weight case based on the fraction of the phase in the gait cycle and (iii) non-equi weight case based on the ratio of magnitude of the hip joint force in respective phases to the total hip joint force of the entire walking gait cycle. The optimal designs are compared with natural hip bone by measuring shape similarity using Procrustes Analysis. Results show that the compliance is less for the optimal designs compared with natural hip bone. The shape similarity values for the three cases are found to be 64%, 78% and 73% respectively. Optimal design obtained from the non-equi weight case based on the duration of phase has highest shape similarity value due to creation of a hole similar to obturator foramen in lower portion of the hip bone. The maximum stress and maximum displacement values are lower in optimal designs compared with natural hip bone. From the shape similarity results, the optimal design from the non-equi weight based on duration of the phase may be more suitable for prosthesis applications.

The Natural Energy Laboratory of Hawaii Authority’s (NELHA) campus on The Island of Hawai’i supplies resources for a number of renewable energy and aquaculture research projects. There is a growing interest at NELHA to convert the research campus to a 100% renewable, islanded microgrid to improve the resiliency of the campus for critical ocean water pumping loads and to limit the increase in the long-term cost of operations. Currently, the campus has solar array to cover some electricity needs but scaling up this system to fully meet the needs of the entire research campus will require significant changes and careful planning to minimize costs. This study will investigate least-cost solar and energy storage system sizes capable of meeting the needs of the campus. The campus is split into two major load centers that are electrically isolated and have different amounts of available land for solar installations. The value of adding an electrical transmission line if NELHA converts to a self-contained microgrid is explored by estimating the cost of resources for each load center individually and combined. Energy storage using lithium-ion and hydrogen-based technologies is investigated. For the hydrogen-based storage system, a variable efficiency and fixed efficiency representation of the electrolysis and fuel cell systems are used. Results using these two models show the importance of considering the changing performance of hydrogen systems for sizing algorithms.

The surface finish of industrial components has an important role in their performance and lifetime. Therefore, it is crucial to find the cutting parameters that provide the best surface finish. In this work, an experimental study of the effect of cutting parameters on ultra-high molecular weight polyethylene (UHMWPE) by a turning process was carried out. Today, the UHMWPE polymer continues to find applications mainly in the automotive industry and biomechanics because it is resistant to impact and corrosive materials to use. A face-centered Central Composite Design (CCD) and Response Surface Methodology (RSM) were applied to evaluate the influence of the cutting speed (V c ), feed rate (f) and depth of cut (a p ) of the turning operation on the Average Surface Roughness (R a ) and Material Removal Rate (MRR). Results allowed obtaining an adjusted multivariable regression model that describes the behavior of the Ra that depends on the cutting parameters in the turning process. The predictive model of Ra showed that it fits well with a correlation coefficient (R 2 ) around 0.9683 to the experimental data for R a . The ANOVA results for R a showed that the feed is the most significant factor with a contribution of 42.3 % for the term f 2 , while the speed and depth of cut do not affect R a with contributions of 0.19% and 0.18%, respectively. A reduction of feed from 0.30 to 0.18 mm·rev −1 produces a decrease in surface roughness from 6.68 to 3.81 μm. However, if the feed continued to reduce an increase in surface roughness, a feed of 0.05 mm·rev −1 induces a surface roughness of 14.93 μm. Feeds less than 0.18 mm·rev −1 cause a heat generation during turning that increases the temperature in the process zone, producing surface roughness damage of the UHMWPE polymer. Also, the results for MRR demonstrated that all of the cutting parameters are significant with contributions of 31.4%, 27.4% and 15.4% to feed, speed, and depth of cut, respectively. The desirability function allowed optimizing the cutting parameters (V c = 250 m·min −1 , a p = 1.5 mm y f = 0.27 mm·rev −1 ) to obtain a minimum surface roughness (R a = 4.3 μm) with a maximum material removal rate (MMR = 97.1 cm 3 ·min −1 ). Finally, the predictive model of Ra can be used in the industry to obtain predictions on the experimental range analyzed, reducing the surface roughness and the manufacturing time of UHMWPE cylindrical components.

Ceramic to metal brazing is a common bonding process used in many advanced systems such as automotive engines, aircraft engines, and electronics. In this study, we use optimization techniques and finite element analysis utilizing viscoplastic and thermo-elastic material models to find an optimum thermal profile for a Kovar ® washer bonded to an alumina button that is typical of a tension pull test. Several active braze filler materials are included in this work. Cooling rates, annealing times, aging, and thermal profile shapes are related to specific material behaviors. Viscoplastic material models are used to represent the creep and plasticity behavior in the Kovar ® and braze materials while a thermo-elastic material model is used on the alumina. The Kovar ® is particularly interesting because it has a Curie point at 435°C that creates a nonlinearity in its thermal strain and stiffness profiles. This complex behavior incentivizes the optimizer to maximize the stress above the Curie point with a fast cooling rate and then favors slow cooling rates below the Curie point to anneal the material. It is assumed that if failure occurs in these joints, it will occur in the ceramic material. Consequently, the maximum principle stress of the ceramic is minimized in the objective function. Specific details of the stress state are considered and discussed.

Geometric variation is one of the sources of quality issues in a product. Spot welding is an operation that impacts the final geometric variation of a sheet metal assembly considerably. Evaluating the outcome of the assembly, considering the existing geometrical variation between the components can be achieved using the Method of Influence Coefficients (MIC), based on the Finite Element Method (FEM). The sequence, with which the spot welding operation is performed, influences the final geometric deformations of the assembly. Finding the optimal sequence that results in the minimum geometric deformation is a combinatorial problem that is experimentally and computationally expensive. For an assembly with N number of welds, there are N! possible sequences to perform the spot welding operation. Traditionally, spot welding optimization strategies have been to simulate the geometric variation of the spot-welded assembly after the assembly has been positioned in an inspection fixture, using an appropriate measure of variation. In this approach, the calculation of deformation after springback is one of the most time-consuming steps. In this paper, the cause of variation in the deformations after the springback, between different sequences is identified. The relative displacements of the weld points in the assembly fixture, when welded in a sequence, is the source of such behavior. Capturing these displacements leads to large time savings during sequence optimization. Moreover, this approach is independent of the inspection fixture. The relative weld displacements have been evaluated on two sheet metal assemblies. The sequence optimization problem has been solved for the two assemblies using this approach. The optimal sequence, the corresponding final assembly deformations, and the time-consumption have been compared to the traditional approach. The results show a significant correlation between the weld relative displacements in the assembly fixture, and the assembly deformation in the inspection fixture. Considering the relative weld displacement makes each assembly evaluation less time-consuming, and thereby, sequence optimization time can be reduced up to 30%, compared to the traditional approach.

Three-dimensional (3D) porous tissue scaffolds combined with bioactive molecules and cells offer key advantages for bone repair mechanisms. A functional bone tissue scaffold should provide mechanical support with an adequate combination of porosity and permeability for nutrients, oxygen supply, waste removal, and growth factors release as well as controlled degradation. Although a vast amount of work exist to address these challenges, to the best of our knowledge, a design framework taking tissue differentiation, diffusion, and growth factor (GF) release into account in time-domain simultaneously does not exist. In this paper, we provide an initial effort to address such a need by laying down the foundations for a simulation framework incorporating these effects within a Finite Element Analysis (FEA) model in COMSOL Multiphysics ® software. The effectiveness of the numerical model is demonstrated via preliminary mechano-biology analyses on a simulated 3D poroelastic bone scaffold. Initial time-dependent results demonstrate the suitability of this model for an optimization framework. More specifically, it is demonstrated that coupled Multiphysics equations of diffusion, GF release, and differentiation could provide valuable inputs for ideal bone scaffold systems for effective bone repair tasks in the future.

The increase of heat generated in integrated circuit because of the miniaturization of electronic components requires more aggressive cooling solutions in order to minimize this high heat flux and address the temperature non-uniformity. In this paper, a manifold microchannel heat sinks has been investigated. In order to enhance the heat transfer performance of the microchannel, an improved version of the augmented epsilon constraint method is adopted for the optimization of the device. Four non-dimensional design variables have been used to describe the geometry of the manifold microchannel heat sinks. The thermal performance and the pumping power have been incorporated in the mathematical programming formulation as indicators of the thermal performance. A surrogate-based approximation based on the Response Surface Approximation has been utilized to evaluate these two objectives. This new mathematical approach has been implemented in the General Algebraic Modelling Systems (GAMS). Details about single and multi-objective optimization formulation of the problem will be disclosed. Optimal solutions describing the best geometrical configuration of the device will be computed. The implications of the geometrical configuration on the performance the manifold microchannel heat sinks will form part of the main contribution of this study.

In order to maximize the electrical energy harvested by photovoltaic panels in a setup with fixed angles, it is important to get the angle optimized. In the present work, sunlight availability or sky coverage conditions of year-long period based on ten years’ data are counted in the modeling to optimize the PV panel tilt angles targeting for the maximal energy in a year. The analysis uses precise sunray calculation models. The energy harvested in every 6 minutes by a PV panel is summated for the daily time period from sunrise to sunset when the sun elevation angles are above 5 degree, with the sky-coverage factor multiplied. The results show that the annual solar energy received by a PV solar panel tilted with a fixed angle equal to the local latitude (at Tucson AZ, USA) could reach 2297 kWh/m 2 under 10-year averaged sky coverage conditions. However, the gain in the yearly solar energy harvest is expected to be about 4.28%, 7.06%, and 8.42% higher if a PV panel is inclined optimally according to two-season, four-season, and monthly adjustments, respectively, compared to the optimized life-long fixed angle.

Multiple fastener reduced-order models and fitting strategies are used on a multiaxial dataset and these models are further evaluated using a high-fidelity analysis model to demonstrate how well these strategies predict load-displacement behavior and failure. Two common reduced-order modeling approaches, the plug and spot weld, are calibrated, assessed, and compared to a more intensive approach — a “two-block” plug calibrated to multiple datasets. An optimization analysis workflow leveraging a genetic algorithm was exercised on a set of quasistatic test data where fasteners were pulled at angles from 0° to 90° in 15° increments to obtain material parameters for a fastener model that best capture the load-displacement behavior of the chosen datasets. The one-block plug is calibrated just to the tension data, the spot weld is calibrated to the tension (0°) and shear (90°), and the two-block plug is calibrated to all data available (0°–90°). These calibrations are further assessed by incorporating these models and modeling approaches into a high-fidelity analysis model of the test setup and comparing the load-displacement predictions to the raw test data.

Bone drilling is an important step in orthopedic surgeries for the reconstruction and repair of fractured bones. The main concern in bone drilling is to create holes without causing minimum damage to the bone tissues. It is well reported that high temperature and high force in drilling cause bone thermal necrosis leading to the delayed bone healing and implant failure. In the past, a significant amount of research has been conducted to understand and mitigate the issues in bone drilling. However, the current practice in bone drilling is that medical surgeons still rely on their own experience and feeling, which often causes unwanted damage to the bone. The present paper aims to provide a comprehensive review of surgical bone drilling and impending factors affecting drilling and biological performance of the bone. Current protocols and practices in tackling issues around drilling are discussed and assessed in terms of results obtained in both experimental and computational domains. This pragmatic discussion will signify the importance and challenges ahead in empowering medical surgeons to enable improved surgical outcome. Furthermore, the findings of this extensive review are expected to drive further exploration of new opportunities for developing advanced bone drilling system integrated with intelligent sensors and control technology.

Structures having a non-homogenous axial distribution of geometrical and material parameters have shown marked improvements in their load carrying capacity, bucking and vibration characteristics. Viscoelastic polymeric materials inherently offer a combination of stiffness and damping which are dependent on frequency and temperature. Therefore, the vibration and dynamic behavior of such engineering structures can be manipulated by grading polymeric viscoelastic materials in a structure. In this research, the transverse vibration performance of an axially graded polymeric beam is considered through systematic modeling and optimization study. A piecewise continuous model has been developed for axially graded beams and their free vibration and frequency response characteristics were analyzed for different combination and grading schemes of polymeric materials. By spatially distributing the range of polymeric materials along the span, spectral characteristics (natural frequencies, modal damping) of graded beams are obtained. Numerical simulations are carried out with axially graded beams made of materials (PLA, ABS, Nylon and TPU) which are easily available for 3D printing. Their spectral characteristics were analyzed and it is demonstrated that frequency and damping characteristics can be manipulated with a prescribed axial distribution of viscoelastic materials. Hence they can be the basis for optimal structural design to achieve a desired dynamic performance.

With mobile autonomous robots on the rise, data structuring and algorithm design plays a significant role in how fast data can be parsed and processed. With robotic systems that are decreasing in size and increasing with complexity, the speed at which data can be processed from multiple sources is crucial to how the system as a whole works. This paper plans to show the difference between certain computational algorithm complexities, both time and space complexity, in order to demonstrate the key ideas in data parsing for systems where computational time of an algorithm can affect the outcome performance of a robot dramatically. The algorithmic types being analyzed in this paper are in relation to a 3D LIDAR scanner in order to produce a point cloud as the output from pre-recorded files. Trigonometric calculations will need to be done in order to produce this output and each file used will be verified using a program supplied from the manufacturer of the LIDAR, Velodyne, in order to ensure the data is being read correctly. The sample data consists of two specific recorded sets, a loading bay and a downtown urban city. Each of data set covers the two configurable outputs, a 20 Mhz Dual Return mode and a 10 Mhz Single Return mode, providing a reasonable range in terms of size in bytes. This paper will show various levels of optimization in areas of trigonometric functions, specifically sine and cosine, algorithmic design, memory safety and defragmenting, and pointer manipulation in order to produce a robust, complex yet ideal algorithm for loading large sets of data rapidly and quickly while holding the level of reliability high. All software written in this paper intends to be natively implemented, meaning no operating system specific external binaries will be used for the end product.

In this research, optimization of a wind turbine airfoil is done by Genetic Algorithm (GA) as optimization method, coupled with CFD (Computational Fluid Dynamics) and Artificial Neural Network (ANN). A pressure-based implicit procedure is used to solve the Navier-Stokes equations on a nonorthogonal mesh with collocated finite volume formulation to calculate the aerodynamic coefficients. The boundedness criteria for the numerical procedure are determined from Normalized Variable Diagram (NVD) scheme and the k–ε eddy-viscosity turbulence model is utilized. ANN has been used as surrogate model to reduce computational cost and time. Single objective and multi objective optimization of wind turbine airfoil have been performed and the results of optimization are presented. To reduce the number of design variables and producing a smooth shaped airfoil, modified Hicks-Henne functions are used. In this process, the Eppler E387 airfoil has been applied as the base airfoil. Angle of attack varies from 0 to 20 degrees and Reynolds number of the flow is 460000.

Synthetic jets, known as zero-net mass-flux (ZNMF) devices, have been widely used for cooling electronics. A synthetic jet is generally composed of a cavity with an orifice on one side and an oscillating diagram on the other side. The vibration of the diaphragm will generate a periodically impinging flow through the orifice which is found to be effective in enhancing heat transfer. The thermal performance of the synthetic jet is highly dependent on the peak velocity of the synthetic jet is able to generate. The orifice shape, orifice thickness, and the number of the orifices are the factors which affect the vibration condition of the diaphragm and thus to affect the performance of the synthetic jet. This study will use both experimental and computational methods to find out the optimal design of synthetic jet and how these factors affect synthetic jet performance. The synthetic jet arrays are driven by a piezoelectric stack actuator which is vibrating at around 720 Hz and the mean-to-peak amplitude is around 0.2 mm. The jet diaphragm (120 mm × 15 mm) is designed using a composite structure composed of a carbon fiber beam, a carbon fiber frame, and a jet frame fabricated by polymethyl methacrylate (PMMA). Four different orifice shapes (square, single slot, double slot, and triangle) with the same area have been designed and the square orifice has the highest velocity. The effect of the orifice thickness is also studied by testing four kinds of PMMA films with different thicknesses (1.5 mm, 2 mm, 3 mm, and 4.5 mm) and the case with 4.5 mm thick orifice has the best performance. The numerical simulation is conducted using the CFD software ANSYS Fluent to support the experimental results. The vibrating of the diaphragm is defined as a moving wall using a user defined function. The fluid power consumed by the diaphragm is used to determine the performances of different designs. The same trend with orifice thickness has been found and the reason has been demonstrated.

A number of studies have been performed to assess the potential of using supercritical carbon dioxide (S-CO 2 ) in closed-loop Brayton cycles for power generation. Different configurations have been examined among which recompression and partial cooling configurations have been found very promising, especially for concentrating solar power (CSP) applications. It has been demonstrated that the S-CO 2 Brayton cycle using these configurations is capable of achieving more than 50% efficiency at operating conditions that could be achieved in central receiver tower type CSP systems. Although this efficiency is high, it might be further improved by considering an appropriate bottoming cycle utilizing waste heat from the top S-CO 2 Brayton cycle. The organic Rankine cycle (ORC) is one alternative proposed for this purpose, however, its performance is substantially affected by the selection of the working fluid. In this paper, a simple S-CO 2 Brayton cycle, a recompression S-CO 2 Brayton cycle, and a partial cooling S-CO 2 Brayton cycle are first simulated and compared with the available data in the literature. Then, an ORC is added to each configuration for utilizing the waste heat. Different working fluids are examined for the bottoming cycles and the operating conditions are optimized. The combined cycle efficiencies and turbine expansion ratios are compared to find the appropriate working fluids for each configuration. It is also shown that combined recompression-ORC cycle achieves higher efficiency compared with other configurations.

An innovative solution for a rapidly deployable shelter for use in austere environments is presented in this paper. The design incorporates a self-erecting dome structure and a compressible, high R-value thermal barrier to enable rapid in-theatre deployment of personnel in harsh environmental conditions. The design concept presented in the paper was originally developed in response to the Army branch of the small business innovative research (SBIR) solicitation topic A11-099. The proposed 400 ft 2 shelter meets the design goals of deployment by two people in 20 minutes, capability of withstanding 100 mph winds, and an R value of at least 15. These objectives have been proven via test, analysis, and mechanical demonstration of the key design components and systems. The primary structure consists of eight composite tubes. The tubes are slip-fit into a central hub; each member is similar to a spoke extending outward radially from the hub. A tension cable is run around the outer perimeter of the radial spokes, passing through a fitting at the tip of each spoke, and a protective skin is draped over the structural members. The structure is then elastically deformed via buckling into a dome-shaped structure by tensioning the cable. This allows quick, easy shelter erection from a single location by one person using a winch. The protective skin is then tensioned to the shelter base with adjustable straps. Stakes are not required to support the structure. A scale model of the primary structure was built to demonstrate the controlled buckling of the members to form the main structural components, and the scale model successfully demonstrated deployment in minimal time. A cellular fabric blanket, which uses entrapped air to provide a thermal barrier, is hung from the inside of the structure and is mechanically expanded to maintain the desired cell size. It can then be packed to 1/20th of its deployed volume for transportation. Simulations and tests were used to optimize the cell size and aspect ratio for weight, manufacturability, and R value. Analytical predictions and component-level testing have demonstrated that a system-level R value of 15 is achievable.

The strain energy present in the structure due to manufacturing imperfections as initial strains are considered and the method for investigating the effects of strain energy due to manufacturing imperfections is developed. The strain energy restored in the structures produced by the initial strains is optimised to find the worst case set of imperfections. The methods proposed are validated by applying to one freedom truss structure. Then the case of a truss is considered with the worst set of imperfections for strain energy, peak force value and work input determined. The worst case set of imperfections contributes maximum strain energy in the truss with different configuration angles is found and driving force values and work input due to presence of changing strain energy through deployment are determined, the worst case set of imperfections are also found by optimisation of these quantities. The methods developed in this paper can be extended to all planar deployable truss structures.

In this paper, the Blade Element Momentum (BEM) theory is used to design the horizontal wind turbine blades. The design procedure concerns the main parameters of the axial/angular induction factors, chord length, twist/attack angles, and local power/thrust coefficients. These factors in turns affect the blade aerodynamics characteristics and efficiency at the corresponding nominal speed. NACA 4-digits airfoil geometry is obtained, using BEM theory, to achieve the maximum lift to drag ratios. The optimization of the power coefficient and its distribution versus different speeds is carried out by modifying the twist angle and chord length distribution along the blade span. The dynamic characteristics of both the original and optimized design are examined through forward dynamic simulation of the blade model. Since large-size wind turbine blade is considered, the dynamic model is established using the Absolute Nodal Coordinate Formulation (ANCF), which is suitable for large-rotation large-deformation problems. Finally, in order to verify the dynamic enhancements in the Aerodynamic/Structural properties, the fluid-solid interaction simulation for both the original and optimized model is performed using ANSYS code. The obtained results show a good rank of the proposed optimization procedure for a practical case of wind data upon Gulf of Suez-Egypt.

The advent of improved factory data collection offers a prime opportunity to continuously study and optimize factory operations. Although manufacturing optimization tools can be considered mainstream technology, most U.S. manufacturers do not take full advantage of such technology because of the time-intensive procedures required to manually develop models, deal with factory data acquisition problems, and resolve the incompatibility of factory and optimization data representations. Therefore, automated data acquisition, automated generation of production models, and the automated integration of data into the production models are required for any optimization analysis to be timely and cost effective. In this paper, we develop a system methodology and software framework for the optimization of production systems in a more efficient manner towards the goal of fully automated optimization. The case study of an automotive casting operation shows that a highly integrated approach enables the modeling and simulation of the complex casting operation in a responsive, cost-effective and exacting nature. Technology gaps and interim strategies will be discussed.

Minimization of pumping energy is a major concern for designing sustainable water supply in buildings. Modular designs of tree-shaped water supply piping system, such as 2 by N array include water cisterns of water closet in public toilets, washbasin taps in schools are commonly found in building complexes. Potable water demands in water systems serving built environment are unsteady, random and intermittent. However, the existing statistical Hunter-based probabilistic approaches to pipe sizing, however, do not consider the minimization of pumping energy for water distribution through proper selection of pipe radii. This paper demonstrates a pipe sizing method with probabilistic demands for optimizing pipe friction energy loss constrained by the fixed pipeline volume. A mathematical model for pumping energy optimization in infinite tree-shape water supply piping networks for probabilistic demands is proposed. Compared with the Hunter’s based probabilistic approach in sizing an 8-section tree-shape water supply network for demand of probabilities 0.1 and 0.2, the proposed method offers reduction potentials of pipe friction energy loss of 12% and 43% respectively. With piping systems of pipe radius ratios, the optimal tree-shape networks are also determined.