Design and Optimization

This work is on the aerodynamics design of the body and frame of a motor tricycle using SolidWorks 2011 modeling system. Its Computational Fluid Dynamics (CFD) feature was used to run simulation tests at a target speed of 150 km/h to evaluate the aerodynamic performance of the tricycle. Simulation results presented shows that lift and drag forces are diminished considerably and that 170 km/h is the maximum speed to be travelled by the tricycle for a smooth and stable ride. Also, the design reduced drastically the effects of lift and drag forces, increased the tricycle’s stability, traction and performance as well as minimized the weight of the tricycle as a result of the use of high performance to mass ratio materials such as carbon fiber for the body and alloy steel for the frame and rims.

This work is on the aerodynamics design of the body and frame of a motor tricycle using SolidWorks 2011 modeling system. Its Computational Fluid Dynamics (CFD) feature was used to run simulation tests at a target speed of 150 km/h to evaluate the aerodynamic performance of the tricycle. Simulation results presented shows that lift and drag forces are diminished considerably and that 170 km/h is the maximum speed to be traveled by the tricycle for a smooth and stable ride. Also, the design reduced drastically the effects of lift and drag forces, increased the tricycle’s stability, traction and performance as well as minimized the weight of the tricycle as a result of the use of high performance to mass ratio materials such as carbon fiber for the body and alloy steel for the frame and rims.

Electric Overhead Travelling (EOT) Crane is one of the essential industrial equipment for material handling job. In recent years little attention has been paid to the optimal design of Heavy Electric Overhead Travelling Crane Bridges. The motive might be, but not limited to the availability of prevailing FEM, DIN, ISO, CMAA, BS, Chinese and now CEN standards for the design of cranes. Most of the crane manufacturers have standardized the single dimensioned box section for multiple spans and duties of Crane Bridges for manufacturing simplicity. Owing to the recent upward trend in the price of structural materials not to mention the demanding dimensions of heavy duty crane box girders, utilization of modern design optimization tools is inevitable. This paper demonstrates design optimization of EOT crane thin walled welded box girder subjected to rolling loads. A simple and innovative procedure has been introduced to use Generalized Reduced Gradient (GRG2) nonlinear optimization code for optimization of various parameters of the welded box section bridge and then comparing the results with the FE simulation. Local buckling of web and compression flange has also been taken in account while performing GRG2 optimization. Later vigorous random and 1st order Design Optimization is performed to establish design space and convergent solutions utilizing commercially available FEA software. Maximum allowable bending stress, allowable shear stress and deflection are constrained to recommended limits of design norms, keeping the volume of the bridge as objective function. The size and thicknesses of plates, stiffeners and reinforcement are included as design parameters (DV's). Optimal girder so designed is efficient in respect of design technique and verified as cost-effective.

In performance-based architectural design optimization, the design of building massings and façades is commonly separated, which weakens the effectiveness in performance improvement. In response, this study proposes a hybrid massing-façade integrated design generation and optimization workflow to integrate the two elements in an evolutionary design process. Compared with the existing approaches, the proposed workflow emphasizes the diversity of building design generation, with which various combinations of building massing forms and façade patterns can be systematically explored. Two case studies and a corresponding comparison study are presented to demonstrate the efficacy of the proposed workflow. Results show that the optimization can produce designs coupling the potential of building massings and façades in performance improvement. In addition, the optimization can provide information that supports early-stage architectural design exploration. Such information also enables the architect to understand the performance implications associated with the synergy of building massing and façade design.

although hypoid gears provide smooth operation and high reduction ratios where compactness of design and maximum pinion strength are important, their efficiency is less than that of a similar set of spiral bevel gears. However, hypoid gears generally have greater tolerance to shock loading and can frequently be used at higher single stage ratios than spiral bevel gears. The objective of the present work is to develop a computer aided design (CAD) package for optimizing the design of hypoid gears. The CAD program calculates the gear set geometrical and strength performance variables such as the bending and contact safety factors. Strength calculations are based on ANSI/AGMA 2003-B97 standards. The CAD package allows the designer to select and change the design variables to satisfy any applied constraints. A genetic based optimization module manipulates the CAD package in a manner similar to the way that can be done by the designer but in an iterative and systematic way. The optimization module changes the design variables and compares the results to minimize the objective function subject to specified constraints. A minimum pinion volume objective function has been chosen in the present work. The main constraints are to equate the working bending and contact stresses to their respective allowable stresses. This would further make the best utilization of material and indirectly minimizes the volume. A numerical example is given to demonstrate the analysis procedure and the effectiveness of the optimization module. The results showed that the optimization procedure reduced the volume of a gear designed according to ANSI/AGMA 2003-B97 to 54% of its original volume. Further analysis was performed to study the effect of the design variables and the input parameters on the objective function.

As a result of the development in information technology, programming has become an inevitable attribute for its function and discipline. Its inclusion in the coding design process, which is the first step of programming and program development, has been achieved with the growth of computeraided design. Mass data-indexed progression of design has led the developments to bring new approaches to the process. These approaches help to shorten the analysis and processing time of the design and bring designers closer to data science-supported machine learning in the formation of architectural design. By working on Generative Adversarial Networks (GAN), which is an exemplary framework in machine learning, to learn and produce to feed alike. With GAN, similar and different new designs are created according to data inputs in architecture. The presence of an AI technology that can support this process is a big step forward for designers to have powerful techniques that can make better design decisions in space experience optimization. In this study, the potential of GAN technology and its better understanding and application in the field of architectural design is researched.

Traditional urban design methods, still relying on the static and sectoral approaches, reach their limits to adapt themselves to the growing complexities and dynamics of modern cities. With the flourishing of artificial intelligence, a new approach called “cognitive design computing” has been proposed to utilize both the human creativity and computing power for the development of next generation urban design supporting tools, where Evolutionary Multi-objective Optimization (EMO) is employed for urban synthesis. However, a unified data structure is missing for the genotype representation of different urban features, such as streets, blocks, plots and buildings, so that they can be optimized together. This paper aims to address this problem and is focused on i) the introduction and description of the genotype data structure, and ii) the application of the prototype of the proposed design tool in practice. (1) PhD student, Future Cities Laboratory, Singapore-ETH Centre; ETH Zürich. Ema...

The adsorption of simulated aqueous solution containing textile remazol reactive dye, namely Red 3BS by palm shell activated carbon (PSAC) as adsorbent was carried out using Response Surface Methodology (RSM). A Box-Behnken design in three most important operating variables; initial dye concentration, dosage of adsorbent and speed of impeller was employed for experimental design and optimization of results. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95% confidence limits. Model indicated that with the increasing of dosage and speed give the result of removal up to 90% with the capacity uptake more than 7 mg/g. High regression coefficient between the variables and the response (R-Sq = 93.9%) showed of good evaluation of experimental data by polynomial regression model.

www.waset.org/publications/2809

— This paper investigates the effect of various rotor structures on the torque production capability of DC excited flux-switching motors. In these machines two set of windings, excited with DC and three-phase AC currents, are placed within the stator and the rotor structure should ensure that the applicable magnetic circuit is present to achieve both a high and smooth torque. As such, the rotor structure is an important factor that affects the performance of DC excited flux-switching motors. Results show that it is possible to increase the mean torque by varying the rotor tooth width or decreasing the torque ripple value by shaping the rotor tooth tip.

The Roadway vehicles like cars, buses, trucks and land movers having many mechanical parts in common like Engine parts, Propeller shafts, Gearbox, Brakes, Clutches, Wheels, etc., To make the vehicle fuel efficient which in result make the transportation economical, the weight of that vehicle should be reduced. Since the composite materials are light weight with more strength & stiffness, inclusion of composite materials to conventional steel materials used in auto parts will reduce the weight and improve the mechanical properties of those components. This paper deals with propeller shaft of heavy vehicle to design the shaft for its minimum dimensions to satisfy current problem specification and then replace conventional steel material with composite material. The design of the propeller shaft is first theoretically designed for steel, Carbon/Epoxy and Glass/Epoxy composite material for its safe dimensions. Then they can be created as a part model for respective dimensions in CREO software. After modeling, Torsional buckling analysis can be carried out in the propeller shafts using ABAQUS software to check whether theoretical calculations and analytical results are similar. Then obtained results are compared among those three materials and Carbon/Epoxy composite material is selected as suitable replacement material for conventional steel material in terms of several mechanical properties.

Genetic algorithm (GA) is a Non-Traditional method is useful and applicable for optimization of mechanical component design. The GA is an efficient search method which is inspired from a natural genetic selection process to explore a given search space. In this work, GA is applied to minimize the volume of hypoid gear with respect to a specified set of constraints. Module, face width and number of teeth of hypoid are used as design variables and the bending stress, contact stress and a geometric limit on the face width are set as constraints. The results showed that the optimal procedure reduced the volume of a gear designed according to ANSI/AGMA 2003-B97 to 54% of its original volume. Further analysis was performed to study the effect of the design variables and the input parameters of the objective function.

Recent years have witnessed the use of wind as renewable energy source. This rapid growth has tremendously developed since the growing concern of the environmental pollution and also oil crisis. The size of the blades is a major factor in the power output of a wind turbine and as a result, blade length has tremendously increased in line with the growth of the wind turbine industry. However, the rapid expansion in use and size of wind turbines contribute its problems. Among the problem is maintaining the shape control at high load especially which substantially affect the aerodynamic efficiency of the airfoil of the wind blade. The structure of the wind blade is made of glass fibre reinforced plastic (GFRP) which is not only has high strength -to-weight ratio and also good rigidity. Nevertheless, it can't resist the shape upon operational air loading such as deflection from root to tip. The higher stress levels acting on the blade root will also contributes to the accumulation of fatigue damages and consequently catastrophic failures. This study intends to experimentally investigate the application of smart materials in composite wind turbine blades like structures. Nickel-Titanium (NiTi) wire which is classified as Shape Memory Alloy (SMA) has been embedded in the core of a graded beam to alleviate the load at the fixed. This corrective action relieves the high stress concentration at blade root and as a consequence minimizes fatigue damages to the blade. The study closely look at the heat load needs to be applied, the transformation temperatures, the recovery stress of NiTi. The recovery stress is very important in structural application for SMA as the recovered stress could be purposely for actuation and damping control in composite blades. A mathematical model has been developed on commercial finite element software ABAQUS for comparison.

Purpose -This paper aims to develop a simulating model of a journal porous metal bearing under elastohydrodynamic conditions and combined (radial, friction and thermal) load distribution and to carry out structural optimization. Design/methodology/approach -The structure analysis is carried out for each kind of load separately and for the combined load distribution of the bearing, where a dynamically loaded porous metal bearing is simulated. This simulating model is developed by finite elements method using the structure analysis module of the CATIA V5 software. Further, a parameter optimization of a porous metal bearing is presented considering the elastic deformations of the bearing shell. Findings -It is revealed that the bearing, even at points with maximum displacements, could not reach the mounting clearance value during its operational life. Relatively small bearing dimensions produce very high values of eigenfrequency response (over 150 kHz) and common dynamic loads met in all sorts of sliding bearing are not dangerous for bearing damage compared with static loads. In the stage of structural optimization based on the correlation between stress and geometric bearing parameters like wall thickness and outer diameter, the influence of finite element dimension on calculated results can be also analyzed and a proper choice of the latter is achieved.

An epistomologic framework, this paper draws from social sciences, media theory, philosophy, business, and the practice of design to develop a comprehensive knowledge construct deciphering the role of the designer in an age of Big Data. From this framework, areas of design research and practice are defined. Practice methods for the designer as an executive member of the business strategy team are framed in terms of efficiency and value. The possibilities for implementing crowd-sourced subjective and multi/media data, interpreted by the vast numbers of social media users at a scale even greater than big data, are explored - hivedesign for big data. It is argued that designers are best qualified to perceive, interpret and contextualize phenomena such as mass customization, the quantified-self and wearable interfaces in an effort to achieve an optimized and rich whole data synthesis. The paper asserts:
 Big Data is quantifiable but ultimately without much meaning.
 Soft Data, four times as big as Big Data, requires human minds to inter-pret.
 Data without Design is insufficient to make rich decisions
 Whole Data Research integrates structured and non/structured data and is the ideal information construct to generate the most valuable knowledge
 Social Media Ontology describes identity and existence as mediated through the agency of social media interfaces, presence and status
 Interfacing and the Data-fied Self is the phenomena of self-monitoring and engaging in biological/technical interfacing through wearable technol-ogy
 Mass Customization and Device Topology describes creating value and longevity for the platform and tools by empowering individuals to personalize the performance of his/her device.

An Optimized Kitchen
A specific recipe prepared in a specific kitchen creates a specific path through that kitchen. If one parameter is changed, e.g. the layout of the kitchen or the instructions in the recipe, the length of the path created by this recipe in this kitchen changes. If one wants to optimise the process of cooking, one way is to change the spatial arrangement of the kitchen. Another way is to change the sequence of a recipe. For now let us say, we would like to “optimize” the recipe, by finding the shortest path that visits every function needed. This problem can be understood through a graph. The different functions are represented through the nodes. The edges represent the distance between the functions. This problem is referred to as the “traveling salesman problem” in computer science.
When a recipe needs to visit three functions A, B, C in a kitchen, and each function is connected with each other function, there is one solution AB, BC, CA. Are there four functions A, B, C, D there are already three possible sequences [AB, BD, DC, CA], [AD, DB, BC, CA] and [AB, BC, CD, DA]. To know which of these sequences is the shortest, all have to be calculated. With n = 4 all possible sequences can be computed2 with ease but when n increases the amount of pos- sible solutions quickly becomes infinite.3 Different approaches to such problems have been developed. The search for the optimal solution is computed is discarded in favor of a good enough solution in a reasonable time. This is called “a heuristic” in computer sciences. Starting from such a heuristic the solution can be improved through applying different “optimization” algorithms. Some of these algorithms guarantee an improvement in quality of the solution, others don’t (e.g.: Genetic Algorithms).
Another way to “optimize” a kitchen is to minimize the space occupied by the kitchen and thus shorten the distances between the elements within the kitchen, as demonstrated by Margarete Schütte-Lihotzky with the Frankfurt Kitchen. If you “optimize” the spatial layout, the storage space available will also be minimized. The smaller the storage space, the more often you have to go shopping4 and the more time you need to buy your supplies. But the more often you go shopping the less you will have to carry at once. Two things are important in every optimization processes, the definition of an optimum and the setup of a prototypical model. Both influence the outcome. In case of the Frankfurt Kitchen the prototypical model included all the elements needed in a kitchen, but it did not take into ac- count the way to and from the store or the weight of the supplies.
What is the optimum of a kitchen? Is it a minimum of space occupied by the kitchen, is it a maximum of storage space provided within the kitchen or do the recipes have to be adapted in order to optimize the kitchen?

This paper provides an optimum design for regular thin-walled box section beams on their cross-sectional profiles. The thin-walled box beams with optimized cross-sectional dimensions perform ideally during the crashworthiness analysis. In this paper, the response surface method (RSM) is utilized to formulate the complex design problem. During the optimum design, the specific energy absorption (SEA) is set as the design objective, and it is constrained by the maximum crushing force (P m ) and the cross-sectional dimensions. Detailed finite element (FE) models are created for such thin-walled box beams which are used for the design optimization. Finally, simplified FE models for these beams are also created for the same design process. Optimal design obtained with the simplified models is compared to the design achieved from the detailed models to verify the accuracy and efficiency of the simplified models. ᭧

Tujuan penelitian ini adalah melakukan analisis kekuatan mekanis knuckle, dibuat dari material FCD 50, dengan menggunakan analisis statis pada pembebanan maksimal. Beban maksimal ini diperoleh dari perhitungan pembebanan pada poros depan kendaraan dalam kondisi operasi kendaraan yang direm pada saat berbelok di jalan menurun. Pada analisis pembebanan poros kendaraan sebelumnya diperoleh beberapa nilai pembebanan pada beberapa nilai kecepatan dan deselerasi. Akhirnya, diperoleh nilai deselerasi dan nilai kecepatan maksimum kendaraan dimana kendaraan aman dioperasikan pada saat direm di jalan menurun dan berbelok. Sebagai perbandingan juga dilakukan perhitungan pembebanan poros depan kendaraan pada kondisi operasi kendaraan yang direm pada saat berbelok di jalan mendatar, karena deselerasi yang berbeda untuk masing-masing kondisi operasi, yaitu 0,5g untuk kondisi operasi di jalan mendatar dan 0,2g untuk kondisi operasi di jalan menurun. Hasil perhitungan tetap menunjukkan pembebanan maksimum pada kondisi operasi di jalan menurun. Studi statika diarahkan pada deskripsi kuantitatif dari gaya-gaya yang bekerja pada struktur teknik dalam kesetimbangan.

For the purpose of integrating wavelength division multiplexer (WDM) into erbium doped waveguide amplifiers (EDWA), we present a 980/1550nm planar lightwave circuit (PLC) WDM directional coupler. This silica based coupler is designed according to the fiber to waveguide coupling restriction and fabrication limitation. The coupler is designed and modeled in BeamPROP environment, utilizing Finite Difference Beam Propagation Method (FD-BPM) to measure light propagation in the silica waveguide. To determine output of the coupler, the length of the coupling region, L and the edge to edge spacing between two adjacent waveguides, d are manipulated. The detailed procedures of design and optimization of the coupler is also described. The designed coupler is 11.5mm long with 160gm channel spacing. The simulation results show that 980nm and 1550nm are successfully coupled from two opposite inputs into the same output. The variation of L and d to the output intensity are plotted and analyzed. The important parameters of the coupler design are given and the advantage of the design is discussed.

Tribological behaviour of a hybrid composite with the aluminium alloy base A356 reinforced by 10 wt. % SiC and 5 wt. % of graphite is treated in this paper. The optimization of tribological behaviour was conducted through the application of Taguchi method. Hybrid composites were obtained in the compocasting procedure. Tribological examinations were executed on the block on disc tribometer with the variation of two different load values (20 and 30 N), three sliding speed values (0.25, 0.5 and 1 m/s) and three sliding distance values (30, 90 and 150 m). All the examinations were carried out in conditions with no lubrication existing. The analysis of the wear rate was conducted using the ANOVA method of analysis. The greatest impact on the wear rate has the load (62.11 %), then the sliding speed (32.88 %), and the least the sliding distance (2.57 %). The interaction of the factors does not have a significant impact on the wear rate.

Electric Overhead Travelling (EOT) Crane is one of the essential industrial equipment for material handling job. In recent years little attention has been paid to the optimal design of Heavy Electric Overhead Travelling Crane Bridges. The motive might be, but not limited to the availability of prevailing FEM, DIN, ISO, CMAA, BS, Chinese and now CEN standards for the design of cranes. Most of the crane manufacturers have standardized the single dimensioned box section for multiple spans and duties of Crane Bridges for manufacturing simplicity. Owing to the recent upward trend in the price of structural materials not to mention the demanding dimensions of heavy duty crane box girders, utilization of modern design optimization tools is inevitable. This paper demonstrates design optimization of EOT crane thin walled welded box girder subjected to rolling loads. A simple and innovative procedure has been introduced to use Generalized Reduced Gradient (GRG2) nonlinear optimization code for optimization of various parameters of the welded box section bridge and then comparing the results with the FE simulation. Local buckling of web and compression flange has also been taken in account while performing GRG2 optimization. Later vigorous random and 1st order Design Optimization is performed to establish design space and convergent solutions utilizing commercially available FEA software. Maximum allowable bending stress, allowable shear stress and deflection are constrained to recommended limits of design norms, keeping the volume of the bridge as objective function. The size and thicknesses of plates, stiffeners and reinforcement are included as design parameters (DV's). Optimal girder so designed is efficient in respect of design technique and verified as cost-effective.

Mechanical systems will almost inevitably fail at some point during operation. This can either be due to a preexisting design flaw or some unexpected damage during usage. No matter how much planning and fault analysis is performed it is impossible to create a perfectly reliable machine. Existing approaches to improving reliability normally involve advances in modeling and detection to include specific mechanisms to overcome a particular failure or mitigate its effect. Whilst this has gone a long way to increasing the operational life of a machine, the overall complexity of systems has improved sharply and it is becoming more and more difficult to predict and account for all possible failure modes. Rather than focusing on mitigating or reducing the probability of failure, a new design philosophy is proposed that allows systems to reconfigure themselves to overcome failure -thus yielding a self-healing design. This approach is demonstrated in the design of a selfrectifying 4-bar linkage mechanism.

This paper proposes the incorporation of engineering knowledge through both (a) advanced state-of-the-art preference handling decision-making tools integrated in multiobjective evolutionary algorithms and (b) engineering knowledge-based variancereduction simulation as enhancing tools for the robust optimum design of structural frames taking uncertainties into consideration in the design variables. The simultaneous minimization of the constrained weight (adding structural weight and average distribution of constraint violations) on the one hand and the standard deviation of the distribution of constraint violation on the other are handled with multiobjective optimization-based evolutionary computation in two different multiobjective algorithms. The optimum design values of the deterministic structural problem in question are proposed as a reference point (the aspiration level) in reference-point-based evolutionary multiobjective algorithms (here g-dominance is used). Results including -metric statistics in a structural frame test case with uncertain loads show considerable reductions in computational costs without harming the nondominated front quality, obtaining a design set that makes it possible to select minimum weight and maximum robustness optimum designs.

Generative Design coupled with associative parametric modelling is proving to be a successful tool for many designers particularly in the early phases of design. The wealth of design solutions which can be rapidly generated certainly help in expanding ideas and exploring possibilities. But simply having the capability to generate different solutions is only half of the process. The designer must make decisions as to which solutions are better. ParaGen, as described in this paper, offers a way to direct the generative process toward more desirable results, and to explore better solutions.

Generative Design coupled with associative parametric modelling is proving to be a successful tool for many designers particularly in the early phases of design. The wealth of design solutions which can be rapidly generated certainly help in expanding ideas and exploring possibilities. But simply having the capability to generate different solutions is only half of the process. The designer must make decisions as to which solutions are better. ParaGen, as described in this paper, offers a way to direct the generative process toward more desirable results, and to explore better solutions.

Traditional urban design methods, still relying on the static and sectoral approaches, reach their limits to adapt themselves to the growing complexities and dynamics of modern cities. With the flourishing of artificial intelligence, a new approach called " cognitive design computing " has been proposed to utilize both the human creativity and computing power for the development of next generation urban design supporting tools, where Evolutionary Multi-objective Optimization (EMO) is employed for urban synthesis. However, a unified data structure is missing for the genotype representation of different urban features, such as streets, blocks, plots and buildings, so that they can be optimized together. This paper aims to address this problem and is focused on i) the introduction and description of the genotype data structure, and ii) the application of the prototype of the proposed design tool in practice. (1) PhD student,

This paper presents an effective methodology for reliability-based robust design optimization (RBRDO). The eigenvector dimension reduction (EDR) method plays a pivotal role in making RBRDO effective because the EDR method turns out to be very efficient and accurate for probability analysis. The use of the EDR method provides three benefits to RBRDO. First, an approximate response surface facilitates sensitivity calculation of reliability and quality where the response surface is constructed using the eigenvector samples. Thus, sensitivity analysis becomes very efficient and simple. Second, one EDR execution evaluates a set of quality (objective) and reliability (constraint) functions. In general, the EDR requires 2N + 1 or 4N + 1 simulation runs where N is the total number of random variables. The EDR execution does not require an iterative process, so the proposed RBRDO methodology has a single-loop structure. Moreover, the EDR execution time can be much shorter by taking advantage of a parallel computing power, and RBRDO can be far more efficient. Third, the EDR method allows solving problems with statistically correlated and non-normally distributed random inputs. Three practical engineering problems are used to demonstrate the effectiveness of the proposed RBRDO method using the EDR method.

This paper describes an optimisation methodology that has been specifically developed for engineering design problems. The methodology is based on a Tabu search (TS) algorithm that has been shown to find high quality solutions with a relatively low number of objective function evaluations. Whilst the methodology was originally intended for a small range of design problems it has since been successfully applied to problems from different domains with no alteration to the underlying method. This paper describes the method and it's application to three different problems. The first is from the field of structural design, the second relates to the design of electromagnetic pole shapes and the third involves the design of turbomachinery blades.

This paper reports the arrangement, portrayal and exploratory examination of Nylon 6 (N6) built up with alumina oxide (Al 2 O 3) mixtures. The test samples were ready in an Injection molding machine, by fluctuating the weight extents of Al 2 O 3 elements mixed with N6. The tribological characteristics of the mixtures were seen by utilizing a nail to plate wear test rig under dry sliding conditions. The significant four boundaries were considered to appraise the wear of the mixture substances like load (P), speed (N), weight % (W), and sliding speed (V) and similar four-cycle boundaries are considered to foster the Numerical models. The mathematical models were created by the procedure of plan of the trial (DOE). ANOVA method was applied to take a look at the legitimacy of the model. Mathematical models were created and the reactions were successfully anticipated. Wear impacts of interaction boundaries on reaction were investigated by plotting outlines.

Recent years have witnessed the use of wind as renewable energy source. This rapid growth has tremendously developed since the growing concern of the environmental pollution and also oil crisis. The size of the blades is a major factor in the power output of a wind turbine and as a result, blade length has tremendously increased in line with the growth of the wind turbine industry. However, the rapid expansion in use and size of wind turbines contribute its problems. Among the problem is maintaining the shape control at high load especially which substantially affect the aerodynamic efficiency of the airfoil of the wind blade. The structure of the wind blade is made of glass fibre reinforced plastic (GFRP) which is not only has high strength-to-weight ratio and also good rigidity. Nevertheless, it can't resist the shape upon operational air loading such as deflection from root to tip. The higher stress levels acting on the blade root will also contributes to the accumulation of ...

... to the development of the engineering materials, little effort has been focused on the optimization ... optimum design is processed for the cross-sectional profiles of the thin-walled box beams ... some simple basic functions such as polynomials to approximate the crash behavior of a ...

The design of a propeller for a high-speed craft is addressed by using a multi-objective numerical optimization approach. By combining a fast and reliable Boundary Elements Method (BEM), a viscous flow solver based on the RANSE approximation, a parametric 3D description of the blade and a genetic algorithm , the new propeller shape is designed to improve the propulsive efficiency, reduce the cavitation extension, increase the cavitation inception speed and maximize, at the same time, the ship speed. Rather than by constraining the propeller delivered thrust, indeed, the proposed procedure works together with an engine-propeller matching algorithm that, each time a new propeller is defined, identifies the achievable maximum ship speed and the resulting engine functioning point that turn in additional goals for the multi-objective optimization. A set of optimal propellers, obtained through the design by optimization based on potential flow calculations (via the Boundary Elements Method), are selected for additional viscous analyses (RANSE calculations) in order to further validate the results of the BEM calculations and provide a deeper insight into the complex flow fields of high speed propellers. Among this subset of optimal configurations, a final geometry is selected to verify the reliability of the design procedure by means of dedicated cavitation tunnel tests and full-scale measurements on a high-speed craft provided by Azimut|Benetti.

Tujuan penelitian ini adalah melakukan analisis kekuatan mekanis knuckle, dibuat dari material FCD 50, dengan menggunakan analisis statis pada pembebanan maksimal. Beban maksimal ini diperoleh dari perhitungan pembebanan pada poros depan kendaraan dalam kondisi operasi kendaraan yang direm pada saat berbelok di jalan menurun. Pada analisis pembebanan poros kendaraan sebelumnya diperoleh beberapa nilai pembebanan pada beberapa nilai kecepatan dan deselerasi. Akhirnya, diperoleh nilai deselerasi dan nilai kecepatan maksimum kendaraan dimana kendaraan aman dioperasikan pada saat direm di jalan menurun dan berbelok. Sebagai perbandingan juga dilakukan perhitungan pembebanan poros depan kendaraan pada kondisi operasi kendaraan yang direm pada saat berbelok di jalan mendatar, karena deselerasi yang berbeda untuk masing-masing kondisi operasi, yaitu 0,5g untuk kondisi operasi di jalan mendatar dan 0,2g untuk kondisi operasi di jalan menurun. Hasil perhitungan tetap menunjukkan pembebanan maksimum pada kondisi operasi di jalan menurun. Studi statika diarahkan pada deskripsi kuantitatif dari gaya-gaya yang bekerja pada struktur teknik dalam kesetimbangan.

This paper presents a design optimization methodology under three sources of uncertainty: physical variability (aleatory); data uncertainty (epistemic) due to sparse or imprecise data; and model uncertainty (epistemic) due to modeling errors/approximations. A likelihood-based method is use to fuse multiple formats of information, and a non-parametric probability density function (PDF) is constructed. Two types of model errors are considered: model form error and numerical solution error, each of which is a function of the design variables that are changing at each iteration of the optimization. Gaussian process (GP) surrogate models are constructed for efficient computation of model errors in the optimization. The treatment in this paper yields a distribution of the output that accounts for various sources of uncertainty. The use of a probabilistic approach to include both aleatory and epistemic uncertainties allows for their efficient integration into the optimization framework. The proposed methods are illustrated using a three-dimensional wing design problem involving fluid-structure interaction analysis.

There is a paradox in design that significantly impacts the ability to improve building performance. The decisions that have the greatest impact on total facility cost and energy usage are made early in the design process without understanding how those decisions will impact building energy costs. This is because significant first-cost or life-cycle-cost analyses cannot be conducted until those decisions are made. To eliminate this paradox and to optimize building performance, therefore, it is essential to comprehensively explore the cost and performance of available design options during the conceptual phase—well
before critical decisions are made. Computational analysis
becomes an excellent tool with which to inform design, rather than simply validating it after the fact.